Project Reference No.: UGC/FDS24/E12/24
Project Title: Maximizing the Sustainable Energy Generation Potential from Ultra-Low Grade Waste Heat: Thermo-4E Optimization and Decision Making Analysis for Novel Integrated Vapor Compression Cycle and the Organic Rankine Cycle with Zeotropic Working Fluids
Principal Investigator: Dr ASIM Muhammad (PolyU SPEED)

Abstract

In hot and humid regions, refrigeration and air-conditioning systems consume a significant amount of total energy. Consequently, a substantial portion of low-temperature waste heat is discharged into the atmosphere, leading to an overall increase in carbon footprints. This research examines a methodology for recovering low-grade waste heat by introducing a novel integrated vapor compression cycle and organic Rankine cycle. The proposed system captures waste heat from air-conditioning units and utilizes it in the organic Rankine cycle for electricity generation. The study aims to enhance the thermodynamic performance of the integrated system through the use of zeotropic mixtures and optimization of the composition of the proposed working fluids. To achieve this objective, a concise methodology is adopted, employing a heat exchange network (HEN) with a linear programming model. This approach allows for the customization of the organic Rankine cycle configuration, enabling evaluation based on performance indicators. The primary focus of the research is the selection of appropriate working fluid pairs for both the integrated vapor compression cycle and the organic Rankine cycle. The waste heat temperature range for the vapor compression cycle is between 50°C and 89°C.

The ORC cycle includes a single stage (SS-ORC) and dual stage (DS-ORC) configuration. Both configurations employ a desuperheating approach to recover and utilize high-quality waste heat, thereby achieving favorable thermodynamic response. To reduce irreversibilities associated with non-isothermal heat addition, zeotropic mixtures are utilized. These mixtures possess a unique characteristic known as temperature glide at constant pressure, which facilitates better thermal matching and minimizes exergy losses during heat transfer. Consequently, higher conversion efficiency (ORC thermal efficiency) is achieved compared to using pure refrigerants. Moreover, by adjusting the composition of the mixture, desired properties can be achieved.

The organic Rankine cycle in the integrated system does not rely on an external heat source. Instead, a shared heat exchanger is employed, functioning as both the condenser for the vapor compression cycle and the evaporator for the organic Rankine cycle simultaneously. To optimize system performance, a multi-objective optimization approach utilizing the non-dominated sorting genetic algorithm-II (NSGA-II) is applied. This optimization aims to maximize the thermal performance of the system while minimizing system losses. The integrated system has also been analyzed not only thermodynamically, but also thermo-economically and thermo-environmentally using 4E (energy, exergy, economic and environmental) analysis to study the comprehensive performance of the system. Subsequently, the optimal solution is selected for the chosen zeotropic mixtures and compared using decision-making methods such as Shannon entropy, LINMAP, and TOPSIS. Ultimately, the Pareto-front solution is utilized to identify the most optimized composition of the zeotropic mixture for the organic Rankine cycle.

Project Reference No.: UGC/FDS16/M05/24
Project Title: Does habitat complexity regulate biodiversity and invasion success in artificial intertidal systems?
Principal Investigator: Dr ASTUDILLO P. Juan Carlos (HKMU)

Abstract

Homogenization of habitats due to human-dominated landscapes has become a global threat to the conservation of ecosystems and biodiversity. Irreversible coastal habitat loss has drastically increased due to land reclamation and construction of seawalls to accommodate growing coastal cities. The homogenous and simple surface of these seawalls lacks the complexity and microhabitats of natural shorelines that support species diversity under challenging environmental intertidal conditions. In addition, these degraded habitats facilitate the establishment of alien species, posing a compounding impact on biodiversity. It is accepted that habitat complexity governs biodiversity, however, the key factors that affect this relationship and its implication on alien species are still not well understood. Therefore, developing the understanding of the relationship between habitat complexity and biodiversity is imperative to promote ecosystem and biodiversity conservation, management, and restoration in natural and artificial shorelines.

This project aims to elucidate the mechanisms by which habitat complexity affects intertidal biodiversity and the presence of alien species on artificial seawalls. Habitat complexity can benefit the recruitment and survival of intertidal species by providing shelter against unfavourable environmental conditions such as surface temperature and desiccation during low tide events, and/or providing refuge against predators. The understanding of the effect and interaction of these key ecological factors is essential to assist and optimize restoration of homogenized shorelines. In recent decades, ecological engineering techniques have been developed to enhance habitat complexity and biodiversity on seawalls. Although this approach has been successful, the understanding of the key factors that drive the complexity-biodiversity relationship and its impact on alien species is still unclear. Understanding this relationship becomes essential to transfer ecological knowledge to engineering and architecture disciplines for the design and implementation of eco-engineered seawalls. To elucidate this relationship, this study will conduct field and laboratory experiments by quantitatively manipulating surface complexity of concrete tiles and the access of predators. Five levels of complexity, from flat (no complexity) to very high complexity, will be tested at different tidal heights in a seawall with high environmental stress caused by sun exposure. This experiment will assess the effect of habitat complexity in lowering environmental stress on the intertidal zone, and its effect on invertebrate biodiversity and alien species. The effect on biodiversity will be based on various metrics such as species richness, abundance, diversity index, biomass, functional traits and trophic level diversity. Another manipulative field experiment will be conducted to determine the effect of habitat complexity in reducing predation on intertidal communities. These field experiments will be complemented with controlled laboratory experiments to understand the effect of habitat complexity, environmental conditions and predation on the settlement and survival of native and alien mussel species. Mussels will be used as a model species because of their relevance in structuring intertidal communities and due to the presence of a fast-spreading alien species in Hong Kong (Xenostrobus securis ). Revealing how complexity can affect settlement and survival at vulnerable early life stages is critical to comprehend the recruitment success on seawalls and its contribution to intertidal community assemblages. Overall, the combination of field manipulative experiments and laboratory experiments will provide essential information to understand how habitat complexity regulates biodiversity and establishment of alien species on artificial shorelines. Therefore, the findings of this project can shed light on methods to eco-engineer artificial coastal habitats to achieve desirables goals of biodiversity and also to control the impact of invasive species.

Project Reference No.: UGC/FDS17/H02/24
Project Title: Does Specific App Features and Evidence Base Matter to Uptake? A Discrete Choice Experiment (DCE) to investigate Preferences and Willingness to Pay for a Mental Health Mobile App among People with Elevated Depressive Symptoms
Principal Investigator: Dr AUYEUNG Larry (TWC)

Abstract

Background: Mental Health Apps (MH apps) have a widespread reach, with many being self-help apps that allow users to learn skills and complete exercises without therapist guidance. Previous studies have demonstrated the effectiveness of MH apps in reducing symptoms of depression, suggesting their potential to alleviate the public health burden associated with depression. However, the value of MH apps as alternative care relies on users' adoption and continued use of clinically relevant apps.

Objective: This study aims to investigate and quantify users' preferences for specific features of MH apps, including but not limited to the app's evidence base.

Methods: A discrete choice experiment (DCE) will be conducted online with a sample of 300 Hong Kong adults experiencing depressive symptoms above the clinical threshold (PHQ-9 score greater than or equal to 10). The DCE will present the participants with pairs of alternative apps in a series of distinct choice sets. Each alternative will include seven preidentified app features: (1) evidence base, (2) price, (3) subscription method, (4) suggested therapeutic dosage, (5) privacy control, (6) offer of a seven-day free trial, and (7) evaluation and certification by reputable organisations, universities, or authorities.

Analytic plan: We will use a mixed logit model, a choice modelling method, to quantify the relative importance of each app feature and marginal willingness to pay for each feature in a scientifically rigorous manner. We will also explore preference heterogeneity across different subgroups.

Significance: Meeting the potential of mobile health technology to address mental health disparities requires understanding user preferences in real-world contexts. This study aims to be a pioneering investigation into the specific app features favored by users. While previous studies have highlighted the limited empirical trials conducted on publicly available mental health apps, none have focused on users' perception of the scientific evidence supporting app claims. This understanding is crucial for effectively disseminating safe and effective mHealth services.

Project Reference No.: UGC/FDS11/P01/24
Project Title: Preparation of electrospun tri-fluid Janus-core shell nanofibers and their potential wound dressings applications
Principal Investigator: Prof BLIGH Annie Sim-wan (SFU)

Abstract

Skin wounds have a significant impact on health especially when it is complicated by infection such as MRSA causing secondary infections. The wound healing process involves a series of biochemical events including cell growth and skin regeneration. It is crucial that treatments and care after a wound occurs are done properly to make sure the skin can rebuild itself, stay free from infections, and keep the new skin hydrated.

To help with wound healing, we can create special dressings that prevent infections and help the skin grow back. However, designing the perfect dressing is tough because it has to do more than just deliver medicine; it also has to adapt to changes in the wound, like dealing with different biological by-products and clearing out debris from infections.

In our project, we are exploring a new way to make a dressing that does multiple things at once: fight infections, aid the healing process, and encourage skin growth. When choosing how to deliver medicine through the dressing, we look for methods that keep the medicine effective and release it slowly at just the right rate. The medicines we are using include anti-microbial agents to prevent infections and growth factors to help skin grow. These drugs are quite different from each other, so we need a system that allows them to work well together. We are also adding a layer in the dressing that soaks up fluids to help manage the wound.

Here, we aim to develop a novel tri-fluid electrospinning process, by which a new type of nanostructures (i.e. Janus with a core-sheath side, J//CH) will be prepared using a novel designed tri-nozzle electrospinning tip. With natural and synthetic polymers as the filament-forming matrices, different functional ingredients will be loaded into different chambers of the complex nanostructures through different manners. The processing-structure-property relationship of electrospun chamber J//CH nanofibers will be ascertained for its feasibility as future wound dressings alternative.

Project Reference No.: UGC/FDS16/E16/24
Project Title: Behaviour of wire arc additively manufactured steel and stainless steel tubular stub columns at ambient and post-fire conditions
Principal Investigator: Dr CAI Yancheng (HKMU)

Abstract

Additive Manufacturing (AM) has been increasingly applied in many engineering disciplines, including aerospace, bioengineering, and automotive. This digital fabrication technology has also been explored in the construction industry in recent years. It offers new opportunities to address challenges faced in the construction industry, such as the shortage and ageing of skilled workers in Hong Kong and elsewhere, and safety issues on construction sites. It brings benefits such as reduced material consumption, optimised structural geometries, less wastage, ease of production in remote locations, strengthening and repair, which is consistent with the public policy of the Government of the Hong Kong Special Administrative Region in terms of construction waste reduction, energy efficiency, and sustainable development. Wire Arc Additive Manufacturing (WAAM) is widely recognised to be the most suitable AM technique for construction applications due to its relatively high deposition rate, large build volume, and low cost. This technique is currently available in China and elsewhere. However, the structures fabricated by the WAAM technique are relatively new to engineers and researchers. There are no codified design rules for WAAM components or structures due to the limited investigations. This situation restricts the use of such technique in the construction sector.

Steel (carbon steel) and stainless steel are among the most commonly used construction materials in buildings and infrastructures. They are widely used to manufacture tubular structural members. The understanding of the fundamental structural behaviour, including material properties, imperfections, residual stresses, section classifications, local buckling and section resistances, is a prerequisite for the stability and safety design of metallic tubular structures under different conditions, including ambient and post-fire conditions. It is proposed in this research project to investigate the fundamental structural behaviour through WAAM steel and stainless steel tubular stub columns at ambient and post-fire conditions. The feedstock wires of high-strength steel ER120S and austenitic stainless steel ER316L will be used to fabricate the WAAM stub columns in circular, square, and rectangular hollow sections. The specimens will be heated to different fire exposure temperatures up to 1000 °C.

Experimental and numerical investigations on the structural behaviour of the WAAM tubular stub columns will be carried out. This project will enhance the understanding of the structural performance of WAAM steel and stainless steel tubular members. The newly generated dataset will be used to develop new design guidelines and section classification criteria for WAAM tubular members, which will allow the use of such WAAM tubular members in structural applications. This will lead to a more innovative, efficient and reliable design on steel and stainless steel structures by WAAM technique.

Project Reference No.: UGC/FDS16/M16/24
Project Title: Move with Errorless Learning (Move WELL): an examination of the cognitive and affective processes in errorless motor learning
Principal Investigator: Dr CAPIO Catherine Mamaid (HKMU)

Abstract

Acquiring movement skills is crucial across the lifespan. When movement is impaired or ineffective, the impact on an individual’s development and wellbeing is life changing. For instance, a child who can move effectively in the playground can interact with other children and make friends. An older person who can walk around their home independently can continue to look after their own daily living activities.

One effective approach to acquiring or re-acquiring (e.g., following injury/disease) movement skills is referred to as errorless motor learning. This approach promotes success during practice (i.e., reduces errors) and culminates in a greater ability to engage in multi-tasking while performing skilled movements. The processes that underlie errorless motor learning have yet to be examined, which limits our ability to optimise this approach for diverse learners. For instance, the declining cognitive resources of older adults would likely affect the process in which they (re)acquire independent movement skills. If we understood this process clearly, we could amplify the factors that can make learning not only effective but also efficient. Such factors might vary as movement skill acquisition evolves from childhood to late adulthood. This research, therefore, explores the associated processes of errorless motor learning in children and older adults.

We will investigate two distinct processes associated with motor learning: (1) cognitive processing measured by movement variability and brain activity, and (2) affective processing measured by self-reports of motivation and brain activity. We will recruit two participant groups – children, and older adults – who will participate in separate experiments with comparable study designs, allowing for inter-cohort comparisons. Within each age group, participants will practice a functional movement task in either a condition where errors are minimised or a condition where errors freely occur. We will measure indicators of movement performance, cognitive process, and affective process before, during, and after practice. We will control for individual cognitive abilities (processing speed and executive function) and use sophisticated statistical analyses to compare the variables between the learning conditions and to verify whether the cognitive and affective processes moderate the outcomes following practice.

We will synthesise the findings from our experiments and develop a framework that contributes to the knowledge of the psychology that underpins movement acquisition and human development. Moreover, the framework could guide practitioners (e.g., therapists, teachers, coaches) when designing training programs that will enable children and older adults to move well.

Project Reference No.: UGC/FDS25/E01/24
Project Title: Development of a novel energy saving-low CO2 emission wastewater treatment approach by using microalgae-bacteria consortia immobilized with magnetic biochar nanocomposites
Principal Investigator: Dr CHAN Cho-yin (THEi)

Abstract

According to the Emission Gap Report 2023, greenhouse gas (GHG) emissions reached a record in 2022 and the global average temperature was measured ~1.8 °C above the pre-industrial levels resulting in the warmest year record had been reported. Urgent actions such as low-carbon economy, transformation of fossil fuels into renewable energy sources, and energy-saving in wastes treatment & waste-to-energy approaches have been implemented to meet the carbon neutrality goal. Conventional activated sludge process (ASP) was successfully adopted for more than a century, however, it has been critically reviewed for modifications in recent years because of its high electricity consumption, e.g. 50% total energy use for the aeration process resulted in ~2-3% annual global electricity consumption and significant amount of carbon emission. It is projected that the energy consumption in wastewater treatment would be significantly increased due to rapid population growth. Thus, higher level of treatment process is designed to increase the effluent quality for water reuse. Recently, after conventional ASP-sedimentation processes, large-scale microalgae cultivation has been investigated to serve as a post-treatment unit to remove residual nutrients content (N and P), results showed that high removal efficiency can be obtained by using simple raceway tanks or photobioreactors (PBR). Using microalgae is advantageous in wastewater treatment because microalgae are widespread, abundant, fast growing and easily to be cultivated. Its high CO2 capture ability can mitigate significant amount of CO2. Besides, its high lipids content can be converted into biofuel for renewable energy generation. However, due to diluted cell density and small cell size of microalgae, low efficiency of biomass separation was observed and significant amount of energy (20-30%) would be required for harvesting microalgae cells before the effluent discharge.

In this study, an alternative wastewater treatment approach using immobilized microalgae-bacteria consortia will be proposed. The O2 generated from microalgae photosynthesis can be used by heterotrophic bacteria for chemical oxygen demand (COD) removal and then the aeration process can be avoided, while the generated CO2 from microbial degradation can be captured by the microalgae thus the carbon dioxide emission in wastewater treatment can be reduced. Furthermore, rapid formation of microalgae-bacteria aggregates with high stability can be achieved by effective immobilization with magnetic biochar nanocomposites after simple gel entrapment process. The reasons of using magnetic biochar nanocomposites for immobilization are because of its high mechanical strength, high surface area, and porosity properties. On the other hand, biochar can be synthesized from different biomass materials like natural wastes (e.g. peanut shell), microalgae or dewatered sludge using pyrolysis process, it can achieve the merits of wastes reduction and resources recovery. Besides, magnetic biochar nanocomposites can facilitate the microalgae-bacteria consortia growth and mass transfer of soluble constituents resulting in higher treatment efficiency. Rapid collection of this newly synthesized magnetic biochar nanocomposites can be achieved by using external magnetic field. Thus, post-treatment processes like sedimentation or membrane separation before effluent discharge can be avoided.

Furthermore, hydraulic retention time (HRT) and solid retention time (SRT) can be decoupled in this new treatment design so that the stability of immobilized consortia and treatment capacity can be further enhanced. The optimal size of immobilized consortia beads should be determined to reduce the light scattering, while the thickness of biolayer can be controlled by optimal design of PBR dimensions and orientation (i.e. horizontal and tubular) to increase light penetration for microalgae photosynthesis during the daytime treatment. The ratio between selected microalgae, heterotrophic bacteria from sewage, and magnetic biochar nanocomposites will be critically determined to achieve higher beads stability and treatment performance. Finally, pilot study (100-200 L) in PBR using real wastewater sample will be conducted for techno-economic analysis and results will be compared to the ASP design. In summary, this study provides an innovative approach for reducing energy consumption and carbon dioxide emission in wastewater treatment in order to achieve the carbon neutrality goal.

Project Reference No.: UGC/FDS15/H07/24
Project Title: Longitudinal Associations Between Adverse Childhood Experiences, Anxiety and Depression, Resilience, and Emotional Eating: A Moderated Mediation Model
Principal Investigator: Dr CHAN Chui-yi (Shue Yan)

Abstract

There is a saying in Cantonese that goes, “turn grief and resentment into appetite,” which expresses the popular notion of using food to make oneself feel better—to fill emotional needs rather than one’s stomach. Emotional eating has been regarded as a potential precursor to eating disorders such as bulimia and binge eating disorders. Adverse childhood experiences, resilience, anxiety and depression symptoms were found to be associated with emotional eating in previous studies including research projects by the principal investigator (PI). However, the past work did not holistically examine proximal and distal risk factors within a single integrated model and thus the mechanism underlying emotional eating is still unclear. Additionally, the transition from the final year of undergraduate study to the first-year post-graduation presents a challenging period involving significant life changes, which may exacerbate the effects of adverse childhood experience on current psychological well-being. Besides, previous studies employed retrospective scales which may have limitations in accurately capturing food intake and the dynamics of emotions and eating behaviors. To address the limitations, the research team will employ mobile device-assisted ecological momentary assessment (mEMA), which allows for real-time data collection of participants’ thoughts, feelings, and behaviors in their natural environment.

To fill in the research gap, the proposed research is (1) To examine short-term longitudinal relationships between adverse childhood experiences, anxiety, depression, resilience, and emotional eating among final year undergraduates during transition from university to one-year after graduation. (2) To examine whether anxiety and depression serve as mediators in the relationship between adverse childhood experiences and emotional eating. (3) To examine if resilience moderates the mediated relationships between adverse childhood experiences, anxiety/depression and emotional eating. (4) To employ an intensive longitudinal study using mEMA to capture momentary experiences of anxiety, depression, resilience, emotional eating, and unhealthy snacking in the context of adverse childhood experiences. (5) To examine how momentary fluctuations in anxiety, depression, and resilience influence emotional eating and unhealthy snacking behavior in the context of adverse childhood experiences.

The proposed study contains a multimethod longitudinal study including a short-term longitudinal study with a quantitative design in study 1 and mEMA in study 2. In study 1, a sample of 500 final year undergraduates will be recruited to participate in a one-year longitudinal questionnaire study. The validated Traditional Chinese version of standardized psychological instruments will be used to assess the general tendency of eating behaviors, negative emotions, and resilience. To capture these variables in the context of daily life, a subset of 70 participants who have at least one ACE will be randomly selected to participate in study 2. The mEMA will be conducted between two time points of Study 1, collecting responses on negative emotional states, emotional eating, snacking, and resilience six times per day over 10 days.

The findings from this proposed project will contribute to understanding the impact of early adverse experiences on well-being and eating behaviors in the later stage of life and will contribute to the development of mental health promotion and intervention efforts to advance the psychological well-being of emerging adults, especially those with early life adversity.

Project Reference No.: UGC/FDS16/M01/24
Project Title: Impact of Heavy Metal Pollution on Urban Mangrove Ecosystem Functioning: Nutrient Cycles and Greenhouse Gas Balance – A Meta-transcriptomic Field Monitoring and Microcosm Study
Principal Investigator: Dr CHAN Ping-lung (HKMU)

Abstract

Climate change is one of humanity's most pressing challenges, primarily driven by excessive greenhouse gas (GHG) emissions. Mangroves, essential crucial carbon sinks, face threats from heavy metal pollution, especially in urban environments. Heavy metals in the environment, which modify the composition and function of microbial communities, might affect GHG emissions from mangrove sediments by disrupting the balance between the carbon cycle, methanogenesis and methanotrophy, and the nitrogen cycle. Recently discovered mechanisms, such as nitrate/nitrite-dependent anaerobic methane oxidation (n-DAMO, which links the carbon and nitrogen cycles), are reshaping our understanding of these nutrient cycles and highlighting the importance of studying nutrient and GHG cycles together. Studying the interaction between these cycles requires the elucidation of the gene expression profiles of the microbiome, which can only be achieved by the meta-transcriptomic approach since conventional metagenomic and qPCR approaches are limited by only assessing the metabolic potential and requiring presupposed knowledge of related genes, respectively. However, the meta-transcriptomic impacts of heavy metals on these crucial microbial processes remain underexplored. On the other hand, the direct causal relationship between the presence of heavy metals and corresponding GHG emissions and microbial gene expression, as suggested by field studies, has rarely been validated through controlled experiments. Validation of the causal effect of specific heavy metals on the emission of specific GHGs and the meta-transcriptomic profiles will help to pinpoint the genes and pathways responsible for the effect of heavy metals and to understand the role and functions of these genes and pathways in GHG emissions. The information obtained is also crucial for developing preventive and mitigation measures.

We, therefore, aim to delineate the effect of heavy metals on the interaction between nutrient and GHG cycles by characterising the microbial meta-transcriptomic changes associated with GHG emissions in mangrove sediments exposed to heavy metals and to discover the novel associations between GHG emissions, microbial gene expressions, and biogeochemical pathways. We hypothesise that different heavy metals in mangrove top sediments will differentially affect the emission of different GHGs by differentially affecting the expression level of genes related to nutrient cycles and GHG cycles. The objectives of this study are: (i) to quantify heavy metal concentrations, GHG emission, and profile microbial meta-transcriptome of the top sediment of the Mai Po Nature Reserve’s mangrove during both wet and dry seasons; (ii) to establish causal networks among the variables in the field monitoring above; (iii) to experimentally validate the effect of heavy metals on GHG emissions and the microbial gene expression levels through controlled microcosm experiments; and (iv) to identify specific microbial genes and metabolic pathways that may contribute to the observed effects.

This study is innovative in both the scientific question inquired and the methods used. The effect of heavy metals on the interaction between nutrient and GHG cycles and the microbial meta-transcriptomic profile remains underexplored. The meta-transcriptomic approach also presents the potential to uncover novel associations between microbial genes and nutrient and GHG cycles. Validation of the effects of heavy metals on GHG emissions and microbial gene expression by controlled microcosm experiments will markedly enhance the precision and reliability of our understanding of how heavy metals affect GHG emissions. This study will not only enhance scientific knowledge of biogeochemical cycles and microbial ecology but also establish the concept that pollution of mangrove sediments will impact GHG emissions and, potentially, climate change. The study will also provide compelling evidence for policy development to control heavy metal pollution. By identifying the microbial genes involved, the project may present novel targets for bioremediation and inform measures to mitigate the adverse effects of heavy metals on GHG emissions in urban mangroves.

Project Reference No.: UGC/FDS14/H04/24
Project Title: Coffee Houses, the Third Place and Hong Kong Modern Chinese Writers in the 1930s and 1940s
Principal Investigator: Dr CHAU Emily Tsz-yan (HSUHK)

Abstract

“Coffee house” is a significant urban landscape in modern life. Over time, researchers on modern Chinese literature have focused on the reception and transformation of coffee house culture of Europe and Japan within the context of Shanghai and Taipei. There has been limited discussion regarding the influence of coffee house culture on Hong Kong modern Chinese writers. The reasons behind Hong Kong modern Chinese writers' writings and visits to coffee houses, as well as the differences in their interpretation of coffee house culture and modern lives compared with writers in Shanghai and Taipei, will shed new light on the exploration of modernity in Chinese literature. This project aims to comprehensively illustrate the literary landscapes and the bodily experiences of coffee houses written by Hong Kong modern Chinese writers in the 1930s and 1940s. It will examine how the writers considered coffee houses as the “third place” to develop their attachments to the city, as well as explore their understanding and pursuit of “modernity”.

Project Reference No.: UGC/FDS16/P01/24
Project Title: Exploiting Reactive Oxygen Species as Molecular Triggers for Tetrazine Bioorthogonal Chemistry: Enabling Click-to-Release Strategies for Intracellular Applications
Principal Investigator: Dr CHEN Jianlin (HKMU)

Abstract

Bioorthogonal chemistry, a powerful tool in chemical biology, has revolutionized the selective labeling, imaging, and manipulation of biomolecules in complex biological systems. Among the various bioorthogonal reactions, tetrazine bioorthogonal chemistry has gained considerable attention due to its rapid reaction kinetics with dienophiles and high biocompatibility in the biological systems. Its applications in cellular labeling, live-cell imaging, diagnosis, drug release, and oncotherapy have shown great promise. However, there are challenges associated with the reactivity and stability trade-off of tetrazine derivatives and precise control over tetrazine ligation, limiting their optimal performance for in vivo applications. To address this limitation, although dihydrotetrazine (tetrazine’s procurer) has been used as alternative for direct tetrazine bioorthogonal chemistry, current methods for dihydrotetrazine oxidation rely on photoactivation with photocatalysts, which may introduce phototoxicity and inconvenience in live cell environments. Therefore, there is a need for alternative, biocompatible, and convenient oxidation methods to regulate tetrazine bioorthogonal reactions.

Reactive Oxygen Species (ROS) are highly reactive molecules generated during normal cellular metabolism and play crucial roles in physiological and pathological processes. Our preliminary studies have revealed that dihydrotetrazine derivatives are unreactive to dienophiles, but they can be selectively and rapidly oxidized by specific ROS to produce active tetrazines. This oxidation leads to the activation of tetrazine bioorthogonal chemistry, opening up exciting possibilities for further intracellular applications. Based on our promising findings, we propose that it is indeed feasible to achieve controlled and efficient tetrazine bioorthogonal reactions in intracellular environments by harnessing ROS as molecular triggers for dihydrotetrazine oxidation to produce tetrazine and click bioorthogonal reaction. By utilizing the inherent reactivity of ROS, we can precisely control the activation of tetrazine chemistry within living cells, providing a powerful tool for various intracellular applications. Therefore, the aim of this proposed project is to explore a novel approach that capitalizes on the use of ROS as molecular triggers for tetrazine bioorthogonal chemistry to expand applications in cellular and in vivo systems. We will investigate the reactivity of dihydrotetrazine with various intracellular ROS, such as t-BuOOH, t-BuOO•, ¹O₂, •OH, O₂⁻•, H₂O₂ , and HClO. By studying the reaction kinetics and optimizing the conditions of ROS triggered click-to-release of tetrazine, we seek to achieve precise control over the tetrazine bioorthogonal reaction within intracellular environments of various cells. This research is particularly relevant to tumor treatment using thermotherapy, as we plan to integrate this bioorthogonal reaction with the aggregation of gold nanoparticles. Our objective is to contribute to the development of efficient and targeted thermotherapy strategies for tumor treatment.

The outcomes of this research will have significant implications for the field of chemical biology and bioorthogonal chemistry as well as paving the way for innovative applications in intracellular environment, enabling precise labeling, imaging, and cancer treatment within living cells, advancing our understanding of intracellular processes, and opening up new possibilities for studying cellular processes and developing targeted therapies.

Project Reference No.: UGC/FDS16/E01/24
Project Title: Development of Interpretable Deep Biomarker for Monitoring Carotid Atherosclerosis Based on 3D Ultrasound Imaging
Principal Investigator: Dr CHEN Xueli (HKMU)

Abstract

Stroke is globally recognized as the second most common cause of death. Carotid atherosclerosis is a significant contributor to ischemic strokes, as it produces atherosclerotic emboli (platelet aggregates and plaque debris) that obstruct cerebral arteries. However, it is encouraging to note that lifestyle and dietary modifications, along with medical interventions, can prevent 75–80% of strokes in high-risk patients. Therefore, serial monitoring of carotid atherosclerosis is important for stroke risk stratification and treatment of atherosclerosis.

Our group pioneered 3D carotid ultrasound techniques and demonstrated their uses in monitoring carotid atherosclerosis and evaluating therapies. As carotid atherosclerosis is a focal disease predominantly occurring at the bifurcation, our group developed 3DUS-based volumetric measurements such as spatiotemporal changes of vessel-wall-plus-plaque thickness distribution (ΔVWT) and voxel-based vessel-wall-and-plaque volume change (ΔVVol), and texture-based biomarkers. With the advent of deep learning methods in medical image analysis, our group, for the first time, developed a deep biomarker to quantify the serial change of carotid atherosclerosis by integrating changes in the vessel wall and plaque volume, as well as changes in textural features extracted by a CNN. However, our initial deep learning-based biomarker has certain limitations that hinder its integration into clinical practice. First, the manual segmentation of the vessel wall contour required is subject to observer variability and is time-consuming. Secondly, the 2D CNN did not consider the correlation between slices. The correlation between slices would be important because one patient may have several plaques in the left or right vessels, each progressing at different rates. By collectively considering these plaques together, their synergy effects may provide additional clues about disease progression in patients. Finally, activation maps developed was a post-hoc method that did not participate in the network computation, leading to a lack of model transparency.

The primary objective of this project is to develop deep learning-based algorithms that not only address the limitations of our initial deep biomarkers but also enhance our understanding of carotid atherosclerosis, including: 1) This framework will include a local vessel-wall-and-plaque-focus similarity learning module utilizing a 2D Convolutional Neural Network (CNN), with an automatic segmentation network of vessel wall contours and a novel attention mechanism to guide the network toward the vessel-wall-and-plaque-relevant region; 2) This framework will include a hybrid CNN-transformer-based network to explore the complex interactions between different plaques in different slices of the left or right vessels for one patient, providing more clinical insights into carotid atherosclerosis. This network uses the high-level features from the CNN as input for the transformer and reduces the number of blocks of the transformer encoders to avoid computational complexity, which takes advantage of transformers to capture long-range dependencies, and of CNN to extract local information; and 3) This framework will guarantee a level of transparency, including visualizing attention maps in the CNN-based structure for clinicians to check its output for plausibility and analyzing the self-attention mechanism in transformer to show the correlation between different slices. This interpretability will help to win the trust of clinicians and pave the way for deep learning methods to be put into clinical practice.

Our proposed 3DUS measurement tools have the potential to be integrated into routine clinical practice, allowing clinicians to monitor the progression or regression of carotid atherosclerosis, which will have a great impact on the management of high-risk patients, evaluating new therapies and decreasing the risk of stroke.

Project Reference No.: UGC/FDS16/M04/24
Project Title: Molecular mechanisms of combination effects of Azoles, Echinocandins and Nikkomycin Z against Candida albicans and Candida auris
Principal Investigator: Dr CHEUNG Yuk-yam (HKMU)

Abstract

Candidaemia is the isolation of the Candida organism from blood cultures. These infections occur in patients who are already very vulnerable and therefore the mortality of candidaemia is high. High mortality rate of up to 96% was reported in intensive care units. Previous studies of Candida bloodstream infections have shown that C. albicans is responsible for approximately half of all candidaemic cases. Another Candida species, C. auris is an emerging, multidrug-resistant fungal pathogen that poses a significant threat to global public health. First identified in 2009, C. auris has rapidly spread worldwide, causing outbreaks in healthcare facilities, including hospitals and nursing homes in Hong Kong. Antifungal resistance in Candida has been increasingly reported as a consequence of the increased use of antifungal agents. The increasing number of antifungal treatment failures, such as those caused by antifungal resistance, demanding new alternative treatment strategies.

Azoles are a class of antifungal drugs that inhibit the synthesis of ergosterol in the fungal cell membrane. Three azole resistance mechanisms have been reported, including 1) mutation of the target gene, ERG11, leading to reduced affinity to azole; 2) upregulation of the target gene leading to reduced drug efficacy; and 3) efflux pump to reduce intracellular drug concentration. Echinocandins inhibit β-1,3-glucan synthase, they disrupt the synthesis of glucan in the fungal cell wall, leading to subsequent fungal cell lysis. In Candida, only target gene mutations in fks1 and fks2 have been described as the underlying mechanism of echinocandin resistance. Nikkomycin Z is an antifungal agent under investigation. It acts as a competitive analogue of the chitin synthase substrate and inhibits chitin biosynthesis. Nikkomycin Z was well tolerated in healthy human subjects with no treatment- or dose-related adverse events.

Antifungal combination therapy is considered a promising strategy to tackle drug-resistant Candida for several reasons: 1) drug-resistant Candida strains have developed mechanisms to evade the effects of single antifungal agents, it is possible to increase the chances of successful treatment by using a combination of antifungal drugs with different mechanisms of action, 2) the use of combination of antifungal drugs can help reduce the likelihood of resistance development; the Candida is less likely to develop resistance to all of antifungals in the combination simultaneously, as it would require multiple genetic changes; and 3) combining different antifungals can help overcome limitations of antifungals such as toxicity and poor penetration.

Combinations of nikkomycin Z and other antifungals have been proposed as a new therapeutic direction for fungal infections. In vitro synergistic effects have been reported when echinocandin is combined with nikkomycin Z in the treatment of various Candida species. Promising in vitro synergistic effects of echinocandin in combination with nikkomycin Z against C. albicans and its fks mutants have been reported. The in vivo effect of echinocandin in combination with nikkomycin Z against C. albicans and its fks mutants was also tested in an immunosuppressed mouse model of systemic candidiasis. The echinocandin-nikkomycin Z combination prolonged the survival of fks mutant infected mice better than either drug alone. Recently, other investigators also reported similar synergistic effects against multi-drug resistant C. auris. In spite of the promising in vitro and in vivo synergistic effects reported, the molecular mechanisms of synergistic effects of the antifungal combinations are not fully understood.

This project aims to investigate the molecular mechanisms of combination effects of azoles, echinocandins and nikkomycin Z against C. albicans, C. auris and their azole-resistant ERG11 and/or echinocandin-resistant FKS mutants. By elucidating the molecular mechanisms of the synergistic effects, the findings of the project could promote the potential application of the antifungal combinations in treating infections caused by antifungal-resistant Candida and address the problem of treatment failures caused by antifungal resistance.

Project Reference No.: UGC/FDS11/E05/24
Project Title: Generative AI Driven Text-based Chatbot for Mental Health Screening
Principal Investigator: Prof CHIU Dah-ming (SFU)

Abstract

When someone suffers depression or anxiety, and develops more severe mental disorders, there are some symptoms. If such symptoms can be observed, they can be used to suggest suitable relief measures and treatments, in order to prevent more serious consequences. The most effective way to discover and ascertain an individual having these symptoms is of course through a trained professional or doctor. Since there can be a large number of people potentially suffering from distress and anxiety in different degrees, a more cost-effective way is to identify the more likely cases by various screening questionnaires and tests. For example, the Patient Health Questionnaire-9 (PHQ-9), and the Generalized Anxiety Disorder 7-item Questionnaire (GAD-7) are commonly used. These questionnaires require the subject to answer a series of questions (9 and 7 respectively) with multiple-choice answers, either in paper or electronic format.

In this age of data science and AI, it is potentially feasible to link segments of conversation to the symptoms we want to identify, referred to as corpus-based analysis and prediction. Many studies have tried this approach to predict the risk of depression. While this method can help detect risks sometimes, it does not gather information from many different relevant angles. Instead of trying to screen people based on non-systematic collection of conversational data, a text-based chatbot screening tool, referred to as CST, is designed based on a given screening questionnaire/test and tries to collect answers to all questions in the given questionnaire.

To make it more user-friendly, the CST does not necessarily ask the questions exactly the same way as in the questionnaire, and exactly in the same order. By asking for the same information in a conversational manner, it helps subjects answer these questionnaires more comfortably. Additionally, if the user trusts the chatbot, more valuable information may be revealed during the conversation, such as the origin or details of the user's symptoms. This information cannot be obtained solely through assessment questionnaires. Thus, the CST can potentially be a better way to spot signs of depression, and anxiety. This project plans to build a prototype of Chinese language CST, based on PHQ-9 and GAD-7 respectively. We plan to get real users to try it out; and evaluate the practicality and usefulness of such an approach.

The CST we plan to build will be based on two popular screening questionnaires, PHQ-9 and GAD-7, and will achieve the following: ▪ An online, interactive, context-aware chatbot for screening on different assessments including PHQ-9 and GAD-7. It will be more accurate, and the extraction method is more natural. ▪ A reporting engine can itemize issues related to detected symptoms to obtain more useful information for reference.

Project Reference No.: UGC/FDS25/M03/24
Project Title: Sustainable utilization of food by-products and Chinese medicine residues: exploring their prebiotic potential
Principal Investigator: Dr CHOI Siu-mei (THEi)

Abstract

In this proposal, the spent coffee grounds (food by-products) and Smilax glabra Roxb. (Tufuling) residue (Chinese medicine residues) will be examined for exploring their potential as prebiotics to stimulate the growth of probiotics in the gastrointestinal tract for health promoting effect. The gut microbiota can degrade prebiotics for metabolism to support the probiotic bacterial growth. The current study aims to reduce the wastes through upcycling of food by-products and Chinese medicinal herbal residues as well as sustainable exploitation of natural resources of prebiotics.

Coffee beverage industry is one of the popular ready-to-eat food products and produce a significant amount of food by-products after processing. Spent coffee grounds are rich in non-indigestible carbohydrate and could be explored as a potential source of prebiotics to support probiotic growth. Based on our previous study, selected probiotic bacteria (Lactiplantibacillus plantarum subsp. plantarum ATCC14917 , Lactobacillus delbrueckii subsp. bulgaricus ATCC11842 and Bifidobacterium longum subsp. longum ATCC15707) which demonstrated ability to reduce acrylamide will be used to evaluate the potential prebiotic effect of extracted polysaccharides from spent coffee grounds.

Tufuling is the dried rhizome of Smilax glabra Roxb. under Liliaceae family. It is a traditional Chinese medicine grown in Southern China. It could unblock and promote the joints, remove dampness, and eliminate toxicity. Tufuling demonstrated cardiovascular protective, hepatoprotective effect, anti- bacterial, anti-hyperglycemic and anti-inflammatory effects. It has been used as a traditional Chinese medicinal material for herbal beverages industry. Tufuling was found to have blood glucose lowing effect. It could reduce blood glucose level in both non-insulin-dependent diabetic mice and normal mice. Tufuling was also found to have protective effect on ulcer by preventing free radical damage, up-regulating the pH of gastric juice, inducing gastric juice secretion, and suppressing lipid peroxidation in the stomach mucosa.

The spent coffee grounds and tufuling residues are considered to have potential health benefits due to the presence of dietary fibre which may function as prebiotics to stimulate the growth of probiotics. This study mainly focuses on (1) the extraction and purification of polysaccharides from the spent coffee grounds and tufuling residues; (2) the analysis of chemical and functional characteristics of the extracted polysaccharides; and (3) the evaluation of the prebiotic effects of extracted polysaccharides on Lactiplantibacillus plantarum subsp. plantarum ATCC14917, Lactobacillus delbrueckii subsp. bulgaricus ATCC11842 and Bifidobacterium longum subsp. longum ATCC15707. The total numbers of viable cells (CFU/mL) with or without extracted polysaccharides after incubation will be compared. These extracted polysaccharides could be applied as novel sources of prebiotics if an increase in the population of tested probiotics will be resulted.

This research project proposed that the spent coffee grounds and tufuling residues could be further utilized as functional food ingredients with prebiotic effects in promoting the growth of probiotics and the relevant health benefits in human. The production of various prebiotics from these waste materials can provide a value-added novel conversion of waste to prebiotics for human health.

Project Reference No.: UGC/FDS15/H13/24
Project Title: How Stroke-Survivor-Adult-Children-Caregiver Dyads Have Coped Interdependently in Achieving Well-being: A Mixed-Methods Study Informing Policy Decisions
Principal Investigator: Prof CHOW Esther Oi-wah (Shue Yan)

Abstract

This research explores the challenges faced by stroke survivors in Hong Kong and their adult-child caregivers due to the changes brought about by COVID-19 lockdowns and resource reallocations. It focuses on the implications of Hong Kong's “Aging in Place” (AIP) policies, which promote informal family care for older adults, typically provided by spouses. However, as life expectancy increases, adult children increasingly take on caregiving roles, often encountering family responsibilities, finances, health, and employment difficulties. The study uses a mixed-method approach to achieve several goals:

1. Investigate the effects of perceived stress, dyadic coping, and self-esteem on the quality of life and mental well-being of both caregivers and stroke survivors; 2. Assess how caring for stroke-survivor parents affects the quality of life of adult children; 3. Identify factors influencing the caregiving experience, both positive and negative; 4. Understand the unmet needs of adult-child caregivers; and 5. Explore policy development for AIP in the post-COVID context.

The research comprises four phases: forming an advisory group, conducting a quantitative survey of 160 dyads, performing semi-structured interviews with 28 dyads, and holding a feedback workshop to refine AIP policies. The study aims to enhance theoretical understanding and provide practical insights for community-based stroke care as Hong Kong's population ages.

Project Reference No.: UGC/FDS16/H21/24
Project Title: Implementing a Design Based Research Approach to Develop a Robust Generative AI Literacy Program for Older Adults
Principal Investigator: Prof CHU Samuel Kai-wah (HKMU)

Abstract

In the current era of technological advancement, digital literacy has become an essential knowledge and skill for social participation (Vuorikari et al., 2022). It is of paramount importance to ensure that all age groups, including older adults (i.e., people aged 60 and above) to have digital competence. Evidence shows that older adults (United Nations, 2019) are particularly vulnerable to digital exclusion given their inability to keep track of technological advancements (Malpass et al., 2022). The rapid developments in generative artificial intelligence (GenAI), coupled with the World Health Organization’s projection of an exponential growth in the global elderly population from 12% in 2015 to 22% in 2050 (WHO, 2022b). It highlights society’s responsibility to ensure the digital inclusion of older adults through promoting GenAI literacy (GAIL) and the urgent need for researchers to introduce relevant initiatives for promoting GAIL in this population.

The proposed project will aim to develop a GAIL Inclusion Programme (GAILIP) to enhance GAIL among older adults. This training programme will be designed, implemented, reviewed, and refined to enhance GAIL based on authentic experience in graphic design, music composition, and chatbot development tailored to users’ needs. Through the enhancement of GAIL, the programme may also improve cognitive functioning of older adults and reduce their feelings of loneliness by broadening their social circle. Through GAILIP, we will also investigate the major barriers to learning the latest technology experienced by older adults. The project will follow a design-based research approach in which 12 workshops will be conducted for three cohorts. The findings will enable not only the continual refinement of the pedagogical design of GAILIP but also the development of a research instrument for the evaluation of knowledge and proficiency of older adults in the area of GAIL. The developed research instrument will also be applicable for other researchers investigating GAIL worldwide.

Our research insights can guide other organisations in developing GAIL programmes for older adults. Moreover, through GAILIP, we will collaborate with various stakeholders, such as healthcare professionals, elderly community centres, large associations/corporations, and governments to expand the trajectory of GAILIP and make our programme accessible to older adults across communities. This is also expected to create opportunities for partnerships within different communities and regions.

Project Reference No.: UGC/FDS15/H21/24
Project Title: Navigating the Visual Tapestry: Unveiling Stress Coping in the Resilience Journey of Caregivers of Children with Special Educational Needs through Photovoice in Hong Kong
Principal Investigator: Dr CHUNG Man-chi (Shue Yan)

Abstract

The number of children with special educational needs (SEN) has significantly increased in the past decade, leading to a higher burden and increased stress levels among their caregivers. Previous research has shown that caregiver burden and mental health status are influenced by coping strategies and social emotional support. Building on these findings, this proposed study aims to explore and investigate stress-related variables in Hong Kong parents of children with SEN. The study sample will include main caregivers of children in early childhood, mid-childhood, and teenage years, as the sources and levels of stress may vary based on the developmental stage of the children.

The research design involves a 1.5-year qualitative study with a participatory action research (PAR) orientation and Photovoice design. The objectives of the study are to increase our understanding of parental stress levels, sources of stress, and the perception of quality of life among parents of children with SEN in Hong Kong. Additionally, the study aims to explore stress coping strategies and orientations in these parents, examine the process and effectiveness of utilizing Photovoice as a stress-reducing intervention, and develop a Photovoice Work Manual and Practical Guide for local use in the family education and social work field.

The study holds significant clinical and theoretical implications for various stakeholders in the community, including educators and professional clinicians, in preventing family tragedies and enhancing the mental well-being of caregivers. The research proposal will integrate the Coping Circumplex Model (CCM) and the Common Factor Model to construct a comprehensive theoretical framework. By adopting a participatory action research (PAR) orientation, the study aims to address the social issue of parental stress among parents of children with SEN.

Photovoice will be employed as both a research method and an intervention in the study. Each Photovoice group will consist of 7 to 10 participants, and a total of 30 participants will be recruited based on power analysis and the Photovoice manual. Data collection will include sociodemographic information, parental stress levels, stress coping strategies, parental competence, and quality of life measures. The study will involve 12 bi-weekly meetings with photographers, facilitators, and project investigators. Qualitative data analysis will be conducted using the SHOWeD protocol to analyze the data collected from the Photovoice intervention. The study aims to provide valuable insights into parental stress among caregivers of children with SEN, contributing to the prevention of family tragedies and the promotion of mental well-being.

The proposed research project on parental stress among caregivers of children with SEN will have significant long-term, medium-term, and short-term impacts. In the long run, it aims to provide a comprehensive framework that considers contextual factors, leading to robust findings for policy and intervention development. It also aims to decentralize mental health services, empowering individuals and promoting community-based support networks. In the medium term, the Photovoice Work Manual and Practical Guide will benefit practitioners and tertiary institutes. In the short term, parents of children with SEN, along with family members, schoolteachers, and the general public, will directly benefit, fostering understanding and support for caregivers. This project’s multifaceted approach will have wide-ranging effects on various stakeholders, enhancing the well-being of caregivers and improving the overall support system for children with SEN. The project will yield two peer-reviewed journal manuscripts and two conference presentations to share research findings. A Photovoice Work Manual and Practical Guide will be developed, accompanied by a Photovoice exhibition. A dedicated website will be created for publicizing the project and providing information on its outcomes.

Project Reference No.: UGC/FDS24/H20/24
Project Title: Quality and Utilisation of Primary Care among Older Adults: Driving for Holistic Healthy Ageing in Hong Kong
Principal Investigator: Dr FONG Ben Yuk-fai (PolyU SPEED)

Abstract

The rapid growth of the population of individuals aged 60 and above (older adults) in both size and proportion has not only threatened the sustainability of the healthcare system in meeting the diverse healthcare needs but also exacerbated pressure on the already overburdened public hospitals in Hong Kong. Recognising primary care as a cost-effective means for disease prevention and a gatekeeping to the expensive hospital and specialised care, this research will highlight the importance of enhancing the overall experience and perception of primary care, in terms of perceived service quality and satisfaction, leading to trust and revisit intention. Such a positive shift can decrease unnecessary access to public hospital services for mild illnesses, and reduce the long-term demand for expensive healthcare services, resulting in substantial healthcare cost savings.

In Hong Kong, the rather unique dual-track healthcare system provides public and private services addressing different individual needs of the population. However, older adults rely more on acute-centric care rather than primary care. To strengthen the health service capacity, one key strategy is to improve the overall quality, access, and utilisation of primary care service provision. The Hong Kong Government has been taking various steps over the years to reduce the burden of secondary and tertiary care by strengthening primary care, including the Elderly Health Care Voucher Scheme and Vaccination Subsidy Scheme as well as establishing Elderly Health Centres and District Health Centres in all the 18 administrative districts. Nevertheless, the efforts have not been effective in addressing the existing problems or realising substantial benefits. Evidence indicates that while adequate investment in primary care is essential, there are issues related to imbalanced and inefficient access and consumption of primary care services amongst the older population in Hong Kong. A more comprehensive and accessible primary healthcare system needs to be developed in Hong Kong in order to provide a better access and quality of primary care to the citizens, especially older adults.

This study aims to evaluate the current state of quality and utilisation among older adults in Hong Kong, employing the seven domains of Primary Care Assessment Tool (PCAT) that assess older adults’ experience and perception of primary care, and to determine the influences of the domains (or constructs) on perceived service quality, individual older adult’s satisfaction, trust, and revisit intention. The interaction effects among the constructs will be analysed using partial least squares-structural equation modelling (PLS-SEM). There will be two phases of the study: Phase 1: a quantitative study using a questionnaire for older adults aged 60 and above; Phase 2: a qualitative study using focus group discussions with older adults (participants from Phase 1) and their family members or carers.

The outcomes of this study are expected to guide improvements in the service quality and efficiency of primary care provision, aligning with the Primary Healthcare Blueprint released in December 2022. The ultimate objective is to contribute findings to the direction of developing a comprehensive primary healthcare system and driving holistic healthy ageing in Hong Kong. Dissemination of research findings will be exchanged to the relevant stakeholders, including healthcare professionals, elderly care providers and policy makers. The study can also enhance and foster research, education, collaboration and knowledge exchange among different stakeholders involved in primary care and healthy ageing.

Project Reference No.: UGC/FDS14/H15/24
Project Title: Standing on Threshold: Evil and the Will in Fyodor Dostoevsky's Fictions
Principal Investigator: Dr FUNG Kai-yeung (HSUHK)

Abstract

In 2014, Italian philosopher Simona Forti argues that the Russian writer Fyodor Dostoevsky paved a new dimension in understanding evil. Traditionally, a person commits evil only when his or her rational mind is corrupted by egoistic wishes. A person cannot will evil for the sake of evil. Evil only resides in those who fail to obey the moral law.

German philosopher Friedrich Schelling breaks the tradition, arguing that human freedom is measured precisely by a person’s ability to commit either good or evil. He argues that God consists of good and evil only when it appears in the human world. Originally, God is a single whole and is indissoluble. Only when he appears in the human world does he become a combination of good and evil. Man as the creation of God is now placed on a threshold where he is free to choose the principle of light (love, order, universal) or the principle of darkness (self-love, disorder and particular).

Evil is the excessive elevation of self-will. Those who choose evil are also those who refuses to open to others. Evil is the rejection of love; it is the unreserved indulgence in the rule of narcissistic wishes. The origin of evil, however, lies in its universal dimension. Mere selfishness may be bad, but it is not evil. Only when a person exalts such a will to an infinite extent, thinking that his will is the universal will, that he is a rival to God, he or she is truly possessed by evil.

Dostoevsky is the first writer who fully engages with Schelling’s radical idea of evil. The Dostoevsky’s hero can choose evil for the sake of evil, which is unprecedented in the modern history of European literature. Forti’s argument is based on Dostoevsky’s Demons. This project demonstrates that evil resides not only in Demons, but also other major novels. My contention is that evil cannot be eliminated by institutional punishment. Evil is a temptation with which the hero must grapple. This project traces the details of this struggle.

Project Reference No.: UGC/FDS16/P06/24
Project Title: Identification of structural defects in glass using isoconfiguration method
Principal Investigator: Dr FUNG Man-kin (HKMU)

Abstract

The role of glasses, including silicate glasses and its derivatives, polymer glasses and metallic glasses, is undoubtedly important in smart cities, as they are omnipresent in both everyday life and advanced technological applications. Glasses serve as a window that not only gives physical protection but also controls the light transmission to the indoor. Glasses with high transmission and low dispersion are used in premium optical instruments that deliver color free images. High-strength glasses are employed in high-end display panels, while polymer glasses find application in the packaging of micro-electronic chips. Metallic glasses are amorphous alloys, its high strength, low elastic elongation and high corrosion resistance made them suitable for the use in consumer electronics, biomedical devices, aerospace, and automotive industries, among others.

When a fluid undergoes rapid cooling, the atoms or molecules are unable to rearrange quickly enough to form a well-organized crystal structure. Instead, they form a disordered amorphous structure known as glass. Glass exhibits a significant increase in viscosity, often by orders of magnitude. Although glass is often referred to as a supercooled liquid, it exhibits all the mechanical properties characteristic of a solid material. However, the exact nature of the transition from the liquid to the glassy phase remains an unresolved question in physics.

In crystal structure, it is well known that the particle movement is initiated by the presence of vacancies. However, the origin of particle movement, specifically in the form of string-like motion, within amorphous structures remains a topic of debate. In a recent study conducted by our research group, direct evidence of a transition between vacancies in crystal structures and fragmented free volumes later named as quasivoids in amorphous structures has been observed. This discovery opens a new direction, enabling the possibility of drawing an analogy between crystals and amorphous materials. Since vacancies and their dynamics play a crucial role in understanding the behavior, properties, and transformations of crystalline materials, it is anticipated that the presence and dynamics of quasivoids in amorphous materials will provide a similar understanding in this context.

Unlike crystal structure which can be studied using mathematical model such as lattice model, the structural disorder found in glass systems, makes it difficult to apply traditional mathematical models. Due to the high viscosity of glasses, it is almost impossible to observe the dynamics of glasses in a reasonable time experimentally. As a result, computational simulations have been widely used as a feasible method to study the behavior of glassy materials.

In this proposal, our objectives will be studying the dynamics of glassy systems using Molecular Dynamics (MD) simulation. We will employ isoconfiguration method, a technique to produce a set of simulations called isoconfiguration ensemble that generated from the same initial spatial arrangement but with different velocities assigned to particles, to investigate the influence of the initial configuration on the presence of quasivoids. In addition to accurate identification of the vacancy alike quasivoids, we plan to study how they trigger particle movement. This results in better understanding of the glass heterogeneity. The statistical behavior of the ensemble will be analyzed to obtain information about particle trajectories and the probability of quasivoid formation.

Project Reference No.: UGC/FDS14/H01/24
Project Title: Healthcare in a Dual-Track System: Hong Kong Citizens' Demands and Preferences for the Voluntary Health Insurance Scheme
Principal Investigator: Dr FUNG Wing-hong (HSUHK)

Abstract

The Hong Kong SAR government implemented a healthcare reform in 2019. As part of this reform, the Voluntary Health Insurance Scheme (VHIS), a government-regulated voluntary health insurance program, was introduced. The objective of VHIS is to alleviate the financial burden on the public healthcare system by encouraging the middle and upper classes to obtain coverage from insurance companies and utilize private healthcare services. However, three years after the implementation of VHIS, only 14% of Hong Kong citizens are covered by this insurance scheme. This falls short of the estimated demand projected by the government and academic studies. Given the increasing public health expenditure in Hong Kong, it is crucial to increase the subscription rate of VHIS to ensure the financial sustainability of the public healthcare system.

In light of this situation, our proposed study aims to identify the factors influencing the demand for VHIS and examine consumer preferences for different VHIS product features. In the first part of the study, we will conduct an observational survey through household interviews to investigate the determinants of demand for VHIS. Drawing on the self-interest hypothesis, welfare ideology hypothesis, and trust hypothesis, we will identify potential factors influencing the demand for VHIS. Subsequently, we will empirically test the relevance of these factors by interviewing around 1,700 adults aged 18 or above who have either purchased or opted out of VHIS. In the second part, we will employ a discrete choice experiment, utilizing random utility theory, to analyze consumer preferences for four VHIS product features that received strong public support during the government's 2014 consultation but were ultimately excluded from the final version of VHIS. Respondents will be asked to choose among alternative product features in 10 choice sets, and their responses will be analyzed using the mixed logit model to determine the most desirable VHIS product features.

The results of this proposed study will provide valuable insights to policymakers and insurance companies. Firstly, understanding the characteristics of VHIS purchasers will enable policymakers to develop more effective promotional strategies to reach the target consumers, thereby increasing the subscription rate of VHIS. Secondly, comprehending consumer preferences for various product features will assist policymakers in redesigning VHIS to better align with the needs of the citizens of Hong Kong. Finally, the study findings will inform insurance companies in designing their health insurance products and provide additional options for the people of Hong Kong.

Project Reference No.: UGC/FDS15/H17/24
Project Title: Rethinking Time-honoured Business in Hong Kong Through the Lens of the Community Economy
Principal Investigator: Dr GAO Chong (Shue Yan)

Abstract

The proposed project aims to understand Hong Kong’s time-honoured businesses, commonly known as laozihao (老字號, literally ‘old signboard’), through a newly developed theoretical framework of the community economy. Due to the long-lasting business-friendly environment, a considerable number of laozihao companies/shops whose life of business is 50 years old or above are still in business in Hong Kong today. In recent years, laozihao in Hong Kong have been studied from different perspectives. In general, publications in this area tend to understand this type of long-established business as either a reminder of old-time economic patterns or a survivor of intense competition in a capitalist market economy. In many cases, this “reminder + survivor” viewpoint highlights the business success of the laozihao but does not go into further detail. In contrast, the community economy theory reminds us to pay more attention to economic forms centred on the interdependence, livelihood, and wellbeing of people. As such, this new perspective suggests us to explore how and why some laozihao choose to stay and “live” together with local people, and how they have long been operated in a relatively just, ethical, and people-friendly way. We believe that the new theoretical framework and new data to be collected from laozihao in Hong Kong will enable us to discover the inherent relationship between laozihao business and the new search for people-friendly economies. In this regard, the proposed project will investigate and explore the decision-making and daily operations of laozihao , the interactions between laozihao and their stakeholders, and analyse the potential of laozihao to foster a new form of community economy for local people in Hong Kong.

First, this project will use the community economy theory to reframe and reconceptualise laozihao business in Hong Kong. Conventional perspectives place focus on the business success of laozihao but do not provide a better understanding of the social, ethical, and humane values of laozihao. The new concept of seeking for more just and people-friendly economies enables us to place more attention to the particular way laozihao organise activities for the wellbeing of their stakeholders.

Second, this project aims to document the details of organising and operating laozihao in Hong Kong as a type of business doing good for the local people and taking care of its stakeholders. Based on the collected data, we will further analyse the potential of viewing laozihao as a resource for developing a distinctive form of the community economy. Since the community economy emphasises the interdependence, livelihood, and wellbeing of ordinary people, detailed information about the interactions amongst employees, regular customers and others will be collected. We will then summarise the features of Hong Kong’s laozihao and explore how to align them with the key ideas of the community economy.

Third, this study aims to use the case study of laozihao business in Hong Kong to broaden the scope of the community economy theory. Many leading researchers in this area have called on activists to create a better society by building community economies through a variety of new enterprise development projects and experiments. The problem here is that the potential of some long-standing businesses for building a community economy has been neglected. Therefore, this proposed study will provide a new platform to explore how to broaden the scope of a community economy by taking some laozihao into account.

Project Reference No.: UGC/FDS16/H37/24
Project Title: Bilingualism effects on cognitive skills in preschool children with Autism Spectrum Disorder
Principal Investigator: Dr GE Haoyan (HKMU)

Abstract

As a neurodevelopmental disorder, Autism Spectrum Disorder (ASD) is characterised by deficits in social interaction and communication as well as repetitive and restricted behaviours (American Psychiatric Association, 2013). ASD affects a child’s communication and cognitive abilities. There is a common belief that autistic children would suffer from an extra burden when they are exposed to two languages. However, there is no empirical support or rejection for this belief. The prevalence of ASD and the increasing number of bilingual children make it important to understand the relationship between bilingualism and ASD.

There have been few studies on how bilingualism affects cognitive skills in children with autism. Despite prior studies showing no additional cognitive deficits in bilingual autistic children, they only focus on one or two cognitive areas. The cognitive ability of bilingual autistic children needs to be measured holistically and systematically. Moreover, previous studies mostly focused on school-age children. These findings may not apply to preschool autistic children in early childhood. In addition, previous studies simply divided participants into distinct monolingual/bilingual categories and high-functioning/low-functioning ASD for group comparisons, despite the variability and complexity of the bilingual experience and autism severity. The population’s individual variation in bilingualism and autism needs to be captured on continua in order to see how these variables interact.

To fill in these gaps, we are looking at bilingualism and cognitive skills in preschool bilingual autistic children in Hong Kong. Besides the fact that this group is understudied, we are also interested in learning more about their cognitive skills so that we can improve early intervention accordingly. We will first measure their bilingual exposure and proficiency, then use parent reports and standardised cognitive tasks to systematically examine their cognitive skills. Our first goal is to identify whether autistic children have cognitive difficulties relative to typical developing (TD) children. Then, we will study how bilingual experience affects cognitive skills in autistic children before they start primary school.

The findings will help us understand how bilingualism interacts with ASD in early childhood. Additionally, they will contribute to the ongoing debate about bilingual cognitive advantage from an atypical perspective. Practically, the findings have the potential to help develop effective interventions and rehabilitation programs for ASD in bilingual settings. This project will also inform evidence-based practice and provide essential guidance to parents, clinicians, educators, and other professionals making decisions about autistic children in Hong Kong.

Project Reference No.: UGC/FDS16/B12/24
Project Title: The Creator Illusion: How the Use of Generative AIs Shapes Consumer Behavior
Principal Investigator: Dr GE Lin (HKMU)

Abstract

Enabled by large-scale language models, sophisticated algorithms, and supercomputing power, Generative AIs produce intellectual works and achieve superior performances across various task domains, ranging from coding, test-taking, and writing to disease diagnosis. Whereas extant business studies have focused on the productivity, performance, and applications of Generative AIs and consumers’ responses to Generative AIs, the PI goes beyond this focus and aims to examine how the use of Generative AIs affects consumers’ self-perception as well as its carry-over effects on consumers’ shopping decisions in general.

Specifically, the PI proposes that the use of Generative AIs results in a “creator illusion,” such that ordinary consumers feel like they are creators. The “creator illusion” will increase consumers’ self-perception of deservingness and, consequently, their spending on more rewarding product options. The PI argues that such a “creator illusion” results from a fundamental self-serving bias, in which consumers attribute the creative outputs of Generative AIs to their own inputs. Accordingly, the PI further proposes two boundary conditions of the “creator illusion”, and its downstream consequences: the effect of Generative AIs on consumers’ spending on rewarding products will be strengthened (a) when the task’s input-output gap is small and (b) consumers’ domain-specific expertise is high. The PI plans for a series of experiments with real behavioral measures and consequences to test the core proposition and theoretically derived boundary conditions across various task domains and operationalization of spending on rewarding product options.

Theoretically, the proposed research contributes to the burgeoning academic discussions of Generative AIs, which have been considered one of the most important advances in information technologies in 2023. The PI aims to shift the research focus from the consumers’ use and evaluation of Generative AIs to the carry-over impacts of Generative AIs on consumers’ daily shopping behaviors in a broader context outside the focal task domain. In this way, the proposed research will contribute to a more complete picture of how the emergence of Generative AIs impacts consumers and society.

Practically, understanding how consumers’ self-perception might change after the use of Generative AIs has important implications. For policymakers, a fuller picture of the potential societal impacts of the emergence and prevalence of Generative AIs beyond the productivity domain can be better revealed. For marketers, effective cross-selling strategies can be conceived if marketers could capture any subtle psychological changes created by the use of Generative AIs.

Project Reference No.: UGC/FDS13/B07/24
Project Title: The Depleted Working Expectant Father: The Impact of Partner's Pregnancy Fluctuation on Expectant Father's Physical and Career Outcomes
Principal Investigator: Dr GU Jingyang (Chu Hai)

Abstract

Enhancing the work experience of employees during pregnancy is a crucial step in addressing Hong Kong's declining fertility rate. However, the role of expectant fathers has often been overlooked in discussions about pregnancy-related challenges and solutions, with most focus on expectant mothers. It is important to recognize that expectant fathers play a vital role in supporting their families and partners throughout pregnancy and are inevitably affected by their partners' pregnancy journey. While conversations around pregnancy experiences typically emphasize achieving a work-family balance, the self-care needs of expectant fathers are frequently neglected. These fathers strive to be supportive partners, responsible parents, and dedicated employees, yet they also require attention to their own physical and mental well-being. Maintaining optimal levels of energy is crucial for them to effectively fulfill their various responsibilities. Thus, achieving a balance between self-care and supporting their partners’ self-care is an important but often underestimated issue. Our pilot study findings further highlight the prevalence of this challenge.

Against this background, our study aims to explore the experiences of expectant fathers during their partners' pregnancies from a self-care perspective. Expectant mothers experience various ups and downs during pregnancy, prompting expectant fathers to adjust their behavior to better support them. Therefore, this study examines the fluctuations in prenatal check-ups as a factor influencing expectant fathers' energy allocation. Expectant fathers are constantly torn between self-care and support for their partner's self-care. The allocation of energy directly impacts their physical conditions, which in turn affects their workplace experience during this transformative process.

Project Reference No.: UGC/FDS16/B04/24
Project Title: Investigating the role of information processing strategies relevant to greenhouse gas labels in the context of intra-destination tourist mobility
Principal Investigator: Dr HRANKAI Richard (HKMU)

Abstract

Urban transportation is vital to economic activities and the overall quality of life and well-being of citizens in cities. However, the transportation sector is a significant contributor to the emission of greenhouse gases at local levels. In this context, travel decisions relating to the mode of transportation play a crucial role in the global warming crisis. Vehicle emissions are a major contributor to individual-level carbon footprints, which may be mitigated by switching to environmentally friendly modes. To achieve low-carbon development goals such as clean air, road safety, and liveable cities, managing vehicle motorization and promoting the use of carbon-efficient modes of transportation are critical. Whilst the popularisation of electric vehicles in Hong Kong is currently in progress, the next step in decarbonizing urban mobility involves encouraging the use of green, alternative-fuelled transport modes other than private electric vehicles. It is evident that reducing carbon emissions necessitates changes both at the industry and individual levels to effectively address the challenges associated with climate change. The proposed research aims to investigate the motivating and hindering factors associated with environmentally friendly urban mobility. Specifically, this study develops and tests carbon emissions information labels (e.g., CO2) relevant to facilitate urban mobility decisions in Hong Kong. A stated choice experiment is designed to collect data on tourists’ route choice preferences with eco-labelling that is analysed through the discrete choice modelling framework. The estimated models allow quantifying the impact of carbon emission information on sustainable mobility decisions by conducting what-if-analysis and calculating measures of willingness-to-pay and value of travel time savings. To test the proposed idea empirically, Hong Kong serves as the empirical setting for this study. Results are expected to shed light on the role of carbon emission information and climate change attitudes in tourists’ decision-making process, allowing the elaboration of theoretical and managerial implications in a broader context.

Project Reference No.: UGC/FDS24/E02/24
Project Title: Investigating Green Conversion of Biomass to Biodegradable Flexible Electronics Based on Laser-induced Graphene Technology
Principal Investigator: Dr HUANG Libei (PolyU SPEED)

Abstract

The generation of global municipal solid waste (MSW) is projected to be 3.4 billion tonnes in 2050, half of which is disposed to the landfill without recycling. Landfill management causes an increase in labour force and environmental pollution, which pose a negative impact on the circular economy and long-term decarbonization. Biomass waste (e.g., wood, paper, grass, cardboard, food waste) and plastic waste account for 66% and 12% of the total MSW, respectively. Biomass recycling includes converting biochar to construction materials, sorting and refitting for plant mulch and fertilizer, and transforming into chemicals and fuels. Nonetheless, these recycling methods are either energy-intensive or low-efficiency/low-value. Alternative recycling methods are necessary to explore. Plastic waste has been becoming one of the most severe environmental issues in the 21st century, among which electronic waste (E-waste) is growing vastly, resulting from the advancement of electronic techniques and the huge demand for personal electronic equipment. However, only 20% of the E-waste in the landfill is recycled; the other discarded plastic waste threatens the lives of organisms and even human beings. Sustainable, innovative, and effective strategies to upcycle biomass waste and circumvent the plastics generation in E-waste are highly demanded. Here we propose an environmentally and economically advantageous roadmap, including two green technologies to upcycle biomass waste to biodegradable graphene for wearable electronics applications. Specifically, biomass (wood waste as demo) is first converted to biodegradable plastics (bioplastics) with high flexibility, excellent mechanical properties and improved thermal stability through an in-situ lignin regeneration (ISLR) technology. The chemicals involved are simple, harmless, and recyclable. The resulting bioplastics (sp3-carbon atoms) are then directly transformed into patternable graphene (sp2-carbon atoms) with high electric conductivity via laser-induced graphene (LIG) technology. Upon laser irradiation, the chemical bonds in the insulative bioplastic would be broken and recombined to form conductive graphene structure due to the photothermal and photochemical effects, without extra chemicals consumption and toxic gas release. LIG technology allows instantaneous engraving, simple manufacturing, and free patterning, providing potential to fabricate printable and miniaturized electronics. The electrical conductivity, adjustable microstructure, and oxygen-containing functional group (easily functionalized with other chemicals) of LIG make it highly potential to be applied in wearable sensors. By manipulating the bioplastics properties and adjusting the laser parameters, wearable electronics such as airflow sensors and temperature sensors based on LIG are fabricated and demonstrated to measure the breath conditions and the body temperature at a system level, which are extremely important in health monitoring. This proposed project aims to upcycle biomass waste to bioplastics with excellent mechanical properties, replace the metals with graphene materials as conductive circuits in wearable electronics, and omit the plastics generation in E-waste. The biodegradable nature of electronic devices makes it possible to integrate with implanted chips, which could facilitate mass production for single-use wearable electronics applications and contribute to modern medical treatment and research. Besides the two sensor demos that will be explored in this project, the printed graphene circuits from bioplastics show great promise in other sensors, including glucose sensor, humidity sensor, ion sensor, gas sensors, etc. And the byproduct bioplastics can also be employed in other various areas such as packaging and constructions. Moreover, the completion of this project will provide guiding significance and new insight for turning trash into treasure from other municipal solid waste.

Project Reference No.: UGC/FDS16/H18/24
Project Title: Echoes of the Past: Reconstructing Vanished Soundscapes in Hong Kong through Archaeoacoustics
Principal Investigator: Dr HUI Tak-cheung (HKMU)

Abstract

This research project explores the emerging field of archaeoacoustics, focusing on the auditory reconstruction of ancient sites in Hong Kong. Our long-term objective is to transform silent archaeological relics into dynamic soundscapes, thereby offering a novel auditory perspective on historical lifestyles and cultural narratives. In the short term, we aim to apply advanced technologies such as 3D spatial sound models, physical sound synthesis, and immersive audio to recreate the lost sounds of significant sites like the Northern Metropolis and Lantau Island.

Our investigation seeks to understand how the reconstructed soundscapes can enrich our knowledge of historical periods and how they can be effectively integrated into current artistic and technological frameworks. The project employs a multidisciplinary approach, combining archaeology, acoustics, and music technology in its research design.

The significance of this project lies in its unique blend of historical soundscapes with contemporary technology, creating a bridge between past and present. It aims to enrich our understanding of history and culture, inspiring new forms of artistic expression and sound design innovations.

The project incorporates a series of interactive workshops, exhibitions, and seminars aimed at involving local communities, students, and professionals to maximize engagement and impact. These activities are designed to foster a deeper appreciation of the region's archaeological heritage and to influence cultural heritage policies, emphasizing the importance of sound in historical preservation.

This project exemplifies the power of interdisciplinary collaboration, opening new avenues for exploring our shared cultural heritage through the lens of sound. It is easily accessible to a non-specialist audience, highlighting the project's innovative approach and potential impact on various fields.

Project Reference No.: UGC/FDS16/B25/24
Project Title: Beyond Numbers: The Differential Effects of Followership Level and Velocity on Influencer Conversion Performance in Sponsored Posts
Principal Investigator: Dr JI Jenny Li (HKMU)

Abstract

Brands increasingly use social media influencers to advertise their products through sponsored posts. These posts, often including brand-specific hashtags, are designed to direct social media users to the brand's page. However, there is an inconsistency in the methods used for pricing sponsored posts and evaluating their performance. In particular, the pricing of sponsored posts is negotiated beforehand, based on the static number of followers at the time of negotiation, while the conversion performance can only be evaluated ex post after the ad is released, using the click-through rates from the hashtags in their posts. Such a discrepancy between pricing and evaluation leads to potential marketing ineffectiveness because the firms may overspend on influencers with declining follower sizes.

Considering that users can easily follow and unfollow influencers at no cost, the follower size of influencers can fluctuate rapidly. This makes the static pricing scheme based on the follower size before releasing posts far from efficient. To address this issue, this proposed research integratively use followership level (i.e., the number of followers) and followership velocity, which is the first-order derivative of the trace of followership level, to examine their differential effect individually and jointly on influencers’ conversion performance.

Additionally, influencers can strategically showcase their explorative orientations by posting more innovative content thereby strengthening their bonds with followers, rather than simply capitalizing the influencer-follower relationship for monetary return. Therefore, this project also examines how influencers’ explorative orientation moderates the baseline relationship between followership level (versus velocity) and conversion performance.

The expected results from field data on social media platforms will facilitate brands in devising a novel pricing mechanism that takes into account the dynamic relationship between influencers and their followers. Additionally, it will encourage influencers to delve deeper into their long-term strategic orientation, and prompt platforms and regulators to develop enhanced solutions for fostering an authentic social media environment.

Project Reference No.: UGC/FDS16/P05/24
Project Title: 3D Additive Manufacturing of Thermoelectric Generators for Multiscale Waste Heat Recovery
Principal Investigator: Dr KARTHIKEYAN Vaithinathan (HKMU)

Abstract

Net-zero carbon emission technologies are the only solution to reduce the impact of climate change intensifying due to global energy demands. Statistically, an energy system operating with the principles of Carnot engine releases about one-third of the total energy consumed as heat. In the global scenario, this waste heat contributes to a loss over 370 TWh/year from industries, therefore harnessing just 1% of this waste heat can reduce CO2 emissions by approximately 3.7 Tg/year, contributing to the path of zero carbon emission by 2050. Though there exist methods for direct conversion of waste heat into electricity, such as Rankine cycle heat engines, they face practical limitations in terms of maintenance and scalability. In this regard, Thermoelectric Generators (TEGs) are one of the potential alternative solid-state devices capable of direct conversion of waste heat into electricity which offers a simple and compact operation. But their material design and device architecture need intense improvements to match the equivalent power conversion efficiency (PCE) of other emission-free renewable energy technologies. While significant breakthroughs have been made in thermoelectric (TE) material’s performance, through defect engineering, hierarchical structuring, the extensive application of TEGs is hindered by two main limitations: (1) thermal stagnation in the bulk monolithic legs and (2) inherent brittleness of its constituent materials. Firstly, the dense nature of monolithic bulk legs in TEGs causes heat to stagnate within them, posing difficulty in maintaining a uniform thermal gradient (ΔT) for the applied heat. This heat stagnation in turn reduces the PCE and module lifetime by weakening their mechanical strength irrespective of the TE material’s performance. Hence, a novel TE device design is required to overcome the geometric and thermal limitations for practical operations. Recently, the additive manufacturing (AM) techniques proves their competence in designing complex mechanical structure from microscale to meters with tuneable electronic and thermal properties. In this aspect, integrating TE materials science with the AM techniques can route to next generation TE devices with added advantages of size and shape conformable structures. Moreover, through this 3D structural design optimization process it will be possible to establish structures with high surface to volume ratios and high densities, thereby leading to a high specific power density. Our preliminary results on core-shell based thin film 3D TEGs demonstrated a large ΔT >150 ^oC in a Bi₂Te₃ device which stands as a base for this proposed work (Nature Communications 14, 2023, 2069). In this regard, we aim to fabricate 3D microlattice architecture TE structures using AM technique of stereolithography for effective waste heat recovery process. To achieve this goal, the development of TE nanocrystal based photocurable resin for stereolithographic fabrication is crucial owning to challenges in the material compatibility and stability. Hence, we opt the following strategies to develop a 3D microlattice TE structure: (1) microwave synthesis of TE Tin Selenide (SnSe) nanocrystals with uniform size distribution (50 nm); (2) electrostatic stabilization of SnSe nanocrystals in polyethylene glycol based photocurable resin; (3) design of 3D microlattice structure (1 cm³) with large surface to volume ratio and mechanical strength; and (4) stereolithographic fabrication of 3D TE microlattice structures. The uniqueness of 3D microlattice structure lies in their exceptionally large ΔT and their capability to endure a large compression strength which are required for real-time applications. With these advantages, here we propose to deliver (1) universal recipe for developing photocurable TE SnSe resin for stereolithographic AM process; (2) 3D TEG structural design with specific mechanical energy absorption >100 J g^-1; and (3) 3D microlattice TEG module with power conversion efficiency >10%. This breakthrough promises to realize macro- to micro-scale TEGs processability for multi-scale waste heat recovery in eco-friendly manner and at a reduced carbon cost. Successful execution of this work will contribute to advancements in waste heat recovery technology to attain carbon neutrality. We strongly believe that our proposed deliverables will pave the way to achieve zero carbon emission goals using TE technology for Hong Kong and Greater Bay Region which is a major energy consuming hub with high population density.

Project Reference No.: UGC/FDS16/B19/24
Project Title: Can we trust repeated transactions for long-term performance advantages amid technological uncertainty?
Principal Investigator: Dr KHURSHID Faisal (HKMU)

Abstract

Recent geopolitical events have led to heightened governmental pressure on companies, particularly those in high-tech industries, to reevaluate and adjust their strategic relationships. A notable example of this is Foxconn, a major supplier for Apple, which has decided to relocate some of its production operations from China to India in response to external factors that have introduced uncertainty. However, this transition poses significant challenges, particularly for companies that depend on mutual capabilities and maintain long-term buyer-supplier relationships. Previous research examining the influence of such long-term relationships on performance has yielded mixed results. Some studies emphasize the positive effects, while others emphasize negative or inverted U-shaped relationships between repeated transactions and performance. To reconcile these divergent findings, recent studies have underscored the significance of contextual factors underlying these repeated transactions.

However, the existing literature largely overlooks a critical contextual factor – the evolving nature of outsourced component’s technology. Technological evolution brings to the fore uncertainties. For instance, an examination of the flat panel display industry from 1963 to 2003 reveals that this sector encountered significant technological uncertainty in its early years due to the presence of multiple competing technologies, notably liquid crystal (LCD) and gas plasma displays. Around 1983, LCD technology emerged as the dominant technology, reducing technological uncertainty. In essence, before 1983, firms competed based on superior display panel technology, whereas competition shifted to offering higher-quality LCD technology following the emergence of the dominant technology (Eggers, 2016). This demonstrates the significant implications of the emergence of a dominant technology. Research investigating a diverse range of industries reveals that the performance effects of firms' strategic choices differ before and after the emergence of a dominant technology (Park & Tangpong, 2021). As noted earlier, the effects of repeated transactions can be both positive and negative, and the nature of competition changes with the emergence of a dominant technology. Thus, it is plausible that the performance consequences of repeated transactions may differ before and after the emergence of the outsourced component's dominant technology. However, existing studies have not explored the performance implications of repeated transactions between a buyer and supplier during the evolution of outsourced component technology. This research gap motivates us to address the following research question: Does the performance impact of a buying firm’s repeated transactions with its outsourced component supplier vary during the period in which the outsourced component’s technology is rapidly evolving?

We draw on the concepts of relational lock-in and relational asset and the evolving nature of the underlying product technology to discern how these forces determine product performance outcomes at different stages of technological evolution. We argue that before the emergence of the outsourced component’s dominant technology, repeated transactions are likely to play a negative role in product performance (relational lock-in). However, with the emergence of the dominant technology, these repeated transactions are expected to exert a positive effect on product performance (relational assets). Considering the potential existence of relational lock-in before the emergence of the dominant technology in the outsourced component, we propose that the accumulated knowledge of the firm plays a moderating role. To empirically investigate this phenomenon, we will examine Chinese high-tech companies from 2000 to 2023 as our empirical context. We anticipate that our data will be nested in at least two levels (firm level and product level) we thus plan to employ the multilevel modelling approach for data analysis. By examining the performance variability of repeated transactions amidst technological evolution, this study will contribute to the growing literature in this field and offer insights into the boundary conditions of performance variations resulting from repeated transactions.

Project Reference No.: UGC/FDS23/H02/24
Project Title: Effectiveness of a Peer-led Taekwondo Programme on Functional Fitness, Psychological Well-being and Exercise Motivation among Elderly in Hong Kong
Principal Investigator: Dr KWOK Heather Hei-man (HKBU SCE)

Abstract

As a super-aged society, the ageing population has several impacts on Hong Kong, including increased expenditure on medical and healthcare services, and decreased workforce in the market which leads to a decline in productivity. Policy makers, caregivers of elderly people and researchers also concerns about the physical health and psychological well-being of elderly people as it relates not only to economic expenses, but the quality of life of elderly people.

Regular engagement in sport and physical activity is a determinant of healthy ageing in the elderly populations and being promoted by the World Health Organization (WHO). Participating in sport and physical activity regularly enables the elderly people to maintain their functional ability which allows them to meet the basic needs of daily living and enables well-being. However, most elderly people failed to achieve the recommended physical activity level as suggested by the WHO. To provide solutions to the problem, researchers studied the barriers and facilitators of sport participation in the elderly populations. The results obtained in some studies suggested that an effective sport training programme with high adherence is characterised by strong perceived benefits from the programme, quality and consistency of the programme, availability of individualized instruction, and social interaction with peers. To make the best use of the impact of peers, a peer-led approach has been used in some health promotion programmes, such as nutrition promotion in the elderly population. Positive results were obtained in these peer-led health promotion programmes but the implementation of peer-led approach in sport programme in the elderly populations is lacking.

In view of this, this study takes a pioneering work in exploring the effectiveness of peer-led sport programme in the elderly people. Since the perceived benefits from the training programme is one of the facilitators of sport engagement in the elderly people, therefore, taekwondo has been chosen as the sport training programme in this study. Taekwondo provides multi-dimensional health benefits to the elderly people, such as improvements in functional fitness, psychological well-being, cognitive abilities, a reduced risk of falling, and an improved gait stability. Besides, researchers suggested that the elderly people have a higher adherence to taekwondo training than other exercises with similar benefits. In this study, a total of 177 participants will participate in this study. 32 participants will be classified into the taekwondo leader group, and the remaining participants will be classified into the peer-led taekwondo group, traditional taekwondo group and waiting-list control group (n = 47 per group). Taekwondo leaders will take part in a 16-session training programme which comprise of skill training and theory. After the completion of the 16-session training, taekwondo leaders will engage in practicum for 5 weeks in assisting peers for taekwondo training. Participants from the peer-led and traditional taekwondo intervention groups will participate in a 16-week taekwondo training programme; one group each will be coached using the traditional or peer-led approach. Pre- and post- test of the participants in all three groups will be performed at baseline, and after completing the 16-session intervention respectively, to evaluate the effectiveness of the interventions on the physical health, psychological well-being and exercise motivation of the participants. An additional measurement will be arranged for the taekwondo leader group after the completion of the practicum to reveal the outcomes after the completion of the skill and theory training.

As a pioneering work studying the effectiveness of peer-led sport programmes in the elderly populations, the results obtained in this proposed study will provide valuable insights into the development of sport programmes with peer-led approach.

Project Reference No.: UGC/FDS24/B13/24
Project Title: Career Up or Down? A Moderated Mediation Model of Gig Workers in Hong Kong
Principal Investigator: Dr KWOK Jonathan Man-lung (PolyU SPEED)

Abstract

The onset of COVID-19 pandemic has affected the global economy seriously, not only the productivity, but also the work style of the employees. Even now during the recovery stage, many countries experience labour shortage problems (Causa et al., 2022), and the labour shortage problem is forecasted to reach more than 85 million by 2030.

Hong Kong companies are not exceptional. It was reported that there would be 140,000 talents loss until the second quarter of 2022, almost double from the second quarter of 2020, and among them, 71,000 were regarded as “associate professionals” (The Standard, 2022).

At the same time, gig economy has been thriving in the labour markets of different countries. In Hong Kong, it was estimated that 700,000 people are involved in the gig economy (Lee & Chow, 2021). The projected gross volume of gig economy in the world has been witnessed an increase to US$401.4 billion in 2022 from US$204 billion in 2018 and expected to have US$455.2 billion in 2023 (Statista, 2022). The surge in this sector has motivated many scholars to study this special labour sector. Thus, this study aims to focus on the context of gig workers, especially professional gig workers and suggest an integrative model to suggest how they manage and develop their gig careers.

Despite the thrive of gig workers in different countries and Hong Kong, existing research has only mainly focused on exploring potential factors, mechanisms, and boundary conditions to answer questions like their motivations to become gig workers, or how they manage their well-being, among others. Minimal effort has been put into the career development and management aspect of gig workers. Previous research has suggested that job crafting can be a way for the employees who have a stable employment relationship with the organizations, to make the work more meaningful and engaging, but this knowledge is still absent among the gig workers (Cropanzano et al., 2022). Thus, this research aims to answer two main research questions: (1) How do gig workers sustain their career development? and (2) What underlying mechanisms and contextual factors shape the career sustainability of gig workers?

The current study makes three important contributions to the existing literature. First, we extend the literature by studying how gig workers can thrive and sustain their careers instead of only focusing on their motives and outcomes. Second, this study employs intervention to analyze the impact of job crafting among gig workers, given the understanding that many previous job crafting research only adopted job crafting for the standard employees. And finally, from the career development perspective, the study adopts the lens of career construction theory (CCT; Savickas, 2005, 2013) to propose proactive personality as a key individual difference factor that explain why some gig workers can sustain their career effectively but some cannot.

Project Reference No.: UGC/FDS16/M19/24
Project Title: What is the repurposing potential of anticoagulants for dementia?
Principal Investigator: Dr KWOK Maggie Man-ki (HKMU)

Abstract

Dementia poses challenges to global promotion of healthy aging given its escalating societal burden. Repurposing existing drugs is pivotal to find novel interventions for currently incurable dementia. The heart-brain connections highlight the potential of cardiovascular medications. Anticoagulants as the mainstay prophylaxis for patients with atrial fibrillation worldwide may be promising. Unraveling whether anticoagulants reduce dementia is essential for achieving the global therapeutic goals for dementia by 2025.

Genetic validation using Mendelian randomization informs potential benefits of anticoagulants in dementia prevention. Observationally, anticoagulants users appear to have fewer dementia than non-users. Several randomized trials on cognitive functions are underway, however a long-term clinical endpoint i.e., incident dementia is understudied. This Mendelian randomization study will clarify the role of inhibition of coagulation cascade targeted by anticoagulants in dementia so as to assist clinical decisions and inform dementia prevention.

Objectives: To assess the role of anticoagulants in dementia by evaluating genetically predicted individual coagulation factors targeted by anticoagulants in dementia in Westerners, and as a comparator, in East Asians.

Design: Two-sample Mendelian randomization studies

Participants: Genome-wide association studies (GWAS) of proteomics (n=3,301) and GWAS of dementia in the West (n=440,683); and BioBank Japan (n=58,110) and GWAS of dementia in East Asia (Japanese) (n=8,036).

Exposure: Coagulation factors targeted by anticoagulants based on genetic variants mimicking their effects as instruments.

Outcomes: Dementia (mainly late-onset Alzheimer’s disease).

Data analysis: Inverse variance weighting with multiplicative random effects, with sensitivity analyses including weighted median, MR-Egger, MR-ConMix, MR-PRESSO, and Multivariable MR.

Expected results: Coagulation factors targeted by anticoagulants will play a role in reducing the risk of dementia. Certain drug class (direct thrombin and factor Xa inhibitors versus vitamin K antagonists) might be better for dementia risk reduction, with greater relevance in East Asians than Westerners.

Significance: These findings will provide benefit assessment of various anticoagulants for dementia, thereby generating timely evidence to tackle dementia and promoting global healthy aging.

Project Reference No.: UGC/FDS14/H09/24
Project Title: Local E-government Performance, Data Openness, and City Competitiveness: Application of Local Online Service Index in the Greater China Region
Principal Investigator: Dr KWONG Ying-ho (HSUHK)

Abstract

E-governance plays a crucial role in promoting government accountability, public participation, and responsiveness, ultimately leading to good governance. While existing studies have focused on national-level e-government performance, this approach is limited to capture the diverse nature of local public services within a country. As highlighted by the United Nations E-Government Survey 2022, “people interact closely with local governments than with national authorities since the former deliver the vast majority of public services, making the provision of online services at the local level essential”. Recognizing the significance of local governments in delivering public services, there is a growing interest in studying e-government at the city level.

The Local Online Service Index (LOSI), developed by the United Nations (UN), has become a valuable tool for assessing and evaluating e-government performance at the local level. The results facilitate comparisons of the data openness that local governments are willing to provide. The latest version of the LOSI includes 86 indicators across five criteria: institutional framework, content provision, service provision, participation and engagement, and technology. However, the current LOSI study only includes 193 populous cities from UN member states, with Shanghai being the sole city selected from China.

This research project aims to pioneer the application of the LOSI methodology in assessing e-government performance in cities and districts of the Greater China Region. The project focuses on 102 economically competitive cities selected from the top 400 cities worldwide according to the Global Urban Competitiveness Report 2021. Additionally, this research project aims to assess e-government performance at the district level, which is the lower level of city government. 163 district government websites are further selected among the top 15 cities for further analysis.

This project seeks to examine the relationship between local e-government performance and city competitiveness. It aims to answer four key research questions: (1) To what extent does local e-government performance determine city competitiveness? (2) What factors contribute to better e-government performance among cities? (3) What factors contribute to better e-government performance among districts? (4) To what extent do district governments exhibit greater data openness compared to city governments?

The research methodology involves applying the LOSI methodology and conducting a Local Government Questionnaire. LOSI will be applied to all selected city and district governments, generating a performance score. Additionally, the Local Government Questionnaire, comprising eight sections, will be administered to assess responsiveness and collect quantitative and qualitative data.

By comparing local governments in the Greater China Region, this research project aims to contribute to the theoretical discussion in the fields of e-government literature, data openness and policy decentralization in China.

Project Reference No.: UGC/FDS16/M25/24
Project Title: A Proactive Patient-centered Interactive Smartphone-based Self-Management Support Program to Enhance Quality of Life in Patients with Chronic Obstructive Pulmonary Disease – A Pragmatic Randomized Controlled Trial with Mixed-method Evaluation
Principal Investigator: Dr LAI Agnes Yuen-kwan (HKMU)

Abstract

Quality of life impairment is a serious problem in COPD patients. A collaborative self-management intervention may improve health-related cognition, behavior and outcomes. We performed patients’ needs assessment and health professionals’ perception of patients’ self-management and designed a smartphone-based self-management support program (3S-C) to improve quality of life (QOL), with input from and pilot-tested on COPD patients. Our pilot findings showed good acceptability.

3S-C aims to improve COPD patients’ QOL (primary outcome), health-related cognition (patient activation and self-efficacy for self-management, and acceptance of illness), behavior [medication and treatment adherence, inhalation regimen and technique, physical activity, dietary habit and smoking behaviours (reduction and cessation)], clinical outcomes (dyspnea, exacerbation, lung function(FEV1), exercise capacity, sleep quality, emotions) and healthcare resource utilization.

3S-C is grounded on components of social cognitive theory to enhance self-efficacy, acceptance-based strategies to increase psychological flexibility, and a brief motivational interviewing approach to resolve the ambivalence of behavior change. We use the stepped care model and smartphone social media (WhatsApp/WeChat) to deliver holistic, multidimensional, structured, personalized informational and psychological support and provide chat-based coaching to enhance self-management cognition and action.

3S-C includes Part A, two individual motivational enhancement sessions; Part B, a set of 2-stage push instant theory- and theme-based WhatsApp/WeChat messages and telephone-delivered health coaching with a tapering schedule; Part C, continuous personalized chat-based messaging, phone call support, and hotline service; Part D, An e-platform for goal setting and self-monitoring; and Part E, A mutual support group session for peer support. Both groups will receive the same schedule and contact hours.

This randomized controlled trial will randomly recruit at least 180 COPD patients to the 3S-C group or General Hygiene Information (GH, control) group. We will examine the effectiveness of 3S-C with subjective and objective measurements by intention-to-treat and sensitivity analyses, with the outcome and process evaluations at 4 and 12 months. We will assess the intervention acceptability and credibility, satisfaction with care, health care resource utilization, and cost-utility and explore the possible mechanisms of the impact of 3S-C on QOL and related outcomes and the facilitators and barriers of self-management.

3S-C is a proactive, patient-centred, interactive program to enhance self-efficacy of self-management and health behaviour, and probably the simplest, lowest-cost and theory-based program to improve QOL and related outcomes in COPD patients. Findings from outcome and process evaluations and mechanistic, healthcare resource utilization and cost-utility analyses will add new knowledge for clinical practices. It will help build simple behavioral change models for further research on smartphone-based self-management interventions for other patients.

Project Reference No.: UGC/FDS16/B26/24
Project Title: The impact of oil price shocks on the performance of low-carbon intensity stocks: Evidence from the largest 300 Connect China A-Share enterprise
Principal Investigator: Dr LAM Yat-ming (HKMU)

Abstract

Does a firm’s carbon intensity - the amount of carbon dioxide emissions per dollar of revenue - affect the sensitivity of its stock price to oil price shocks? Moreover, if so, does it matter which industry the firm is in, or whether the oil price shocks are driven by demand or supply factors? This study attempts to answer those questions, and examines whether low-carbon stocks outperform high-carbon stocks adjusted for risk during periods of extreme oil price shocks and market turbulence.

The heightened global concern about the impact of carbon emissions contributing to climate change has led governments to encourage low-carbon emission production through direct subsidies and/or reduction in tax levies, whilst penalizing high-emission firms through more stringent regulations and taxes. Further, low-carbon companies attract environmentally-conscious individual investors and norm-constrained institutional investors. This study hypothesizes that expectations of government support and the composition of shareholders of low-carbon intensity stocks can dampen volatility-induced speculative trading volume of these stocks. The hypothesis is founded on the belief that low-carbon firms are less reliant on crude oil and other fossil fuels and, as a result, their earnings are less sensitive to oil price changes than their high-carbon emission counterparts.

The study focuses on the 300 largest A-share Chinese enterprises listed on the Shanghai and Shenzhen stock exchanges that are accessible to global investors through the Mainland-Hong Kong Stock Connect program. The potential findings from the research have significant local, national, and global socio-economic implications because China has been among the highest CO2 emission countries. The inquiry is facilitated by the newly introduced Connect China A Low-carbon Select Index (HSCALCS) and its parent Connect China A 300 Index (HSCA300) by the Hang Seng Indexes Company Limited. The low-carbon index currently contains 274 stocks but has a Weighted Average Carbon Intensity (WACI) of 47.66% less than the parent index which implies that the complementary set composed of the 26 excluded stocks has a substantially higher carbon intensity than the low-carbon index. We construct value-weighted, and market-capitalization-weighted portfolios (“high-carbon indexes”) from the high-carbon stocks, to gauge the performance of the low-carbon index.

Using the high-carbon index as a surrogate of a high-carbon footprint stock portfolio, our preliminary evidence inferred from one year of daily data (February 13, 2023, the launch date of the low-carbon intensity index to January 26, 2024) is encouraging as it shows that oil price volatility has less impact on the low-carbon index (HSCALCS) than the high-carbon intensity stock portfolio. Specifically, we use Diebold and Yilmaz’s (2012, 2014) connectedness measure to gauge the differential impact of oil price volatility on the two portfolios (see Table 3 in the proposal). The proposed study will examine individual stocks and portfolios using firm-level carbon intensity data from the Wind ESG database and the companies’ annual financial and sustainability reports. The research will examine the differential impacts of supply and demand driven oil shocks on the cross-sections of individual stocks and portfolios according to their carbon intensity and industrial sector classification. Further, the paper uses single and double-sorting analyses to examine the performance of individual stocks and portfolios particularly between the bottom and top percentile categories to test whether the impact of oil shocks and market turbulence on stock returns and volatility varies according to a stock’s carbon intensity.

The potential contribution of this study is to bridge the gap in the literature on the differential impacts of oil shocks on low and high-carbon stocks among the 300 largest Connect China A-shares enterprises accessible to overseas investors through the Stock Connect Program. The findings will provide significant information to worldwide individual and institutional investors for making strategic carbon investment decisions regarding the 300 largest Chinese companies. The global preference and support of low-carbon stocks can help China to achieve the goal of carbon neutrality.

Project Reference No.: UGC/FDS16/H32/24
Project Title: The Tone in Mashan Hmong Language in China: An Acoustic and Electroglottographic Study
Principal Investigator: Dr LAM Man-fong (HKMU)

Abstract

Hmong is an ethnic minority language well-known for its complex tonal system that incorporates pitch, phonation, and duration differences. Mashan Hmong is a prominent but phonetically understudied language spoken mainly in Guizhou Province, China. It is essential to investigate the phonological and phonetic aspects of the language, because of its extensive and complex tonal inventory, which is typologically rare among the wide variety of Hmong and tonal languages worldwide. Similar to other Hmong languages, Mashan Hmong exhibits the co-occurrence of non-modal phonation with tones.

However, the complexity of the language extends further, as it involves a combination of voicing, aspiration, and tonal contrasts. Investigating such complex and typologically rare tonal systems will enable us to address sound changes, particularly tonal ones.

Researchers have proposed that the laryngeal features present in syllable onsets and final consonants introduce F0 perturbations (variations in fundamental frequency) and pitch contours. These features then develop into complex lexical tones in languages spoken in China and Southeast Asia, including Hmong. This study adopted Thurgood’s tonogenesis model (2002, 2007) to examine the distinct features of tone in Mashan Hmong. Methodologically, this study combines an instrumental approach with field-based language documentation. It aims to investigate the acoustic-phonetic properties of the tonal systems of Mashan Hmong, using both acoustic and articulatory measures of first-hand acoustic and articulatory data obtained during fieldwork using acoustic and electroglottographic (EGG) recordings (Aim 1). It also examines the phonetic mechanism accounting for extremely rich tonal inventories, based on the results of the phonetic analysis of speech production (Aim 2). Lastly, the data on this endangered dialect of the Hmong language are archived by constructing spoken corpora, to thereby achieve educational and cultural objectives (Aim 3).

This contribution of this research holds great significance, as it yields essential data for investigating ongoing sound change processes, thus offering insights into the underlying mechanisms of tonal shifts, including tone development. Moreover, the proposed research is of utmost importance because it aims to examine the intricate phonetic properties of one of the most complex tonal systems currently in existence. Additionally, given the alarming decline in the number of speakers of minority languages, this study endeavours to contribute to the preservation and documentation of endangered dialects.

Project Reference No.: UGC/FDS41/H01/24
Project Title: Linguistic variations between Mandarin and Cantonese: the acquisition of syntax of Chinese
Principal Investigator: Dr LAU Elaine (YCCECE)

Abstract

This research examines the acquisition of Chinese syntax by young Mandarin-speaking and Cantonese-speaking children. It investigates how variations in syntax between these two closely related languages might lead to differences in acquisition of the respective language. The study targets six key differences in syntax between Mandarin and Cantonese (ditransitive construction, ba-construction, passive voice, reflexive, wh-question and relative clause), and would look in depth how different linguistic and cognitive factors modulate the acquisition of each syntactic property in study.

With this first-ever cross-linguistic comparison of the micro-variations in syntax between Cantonese and Mandarin, this research provides a stereoscopic view of the developmental trajectory and pattern of acquisition of Chinese. The findings from the two varieties of the Chinese language can also provide a better understanding of the universal mechanisms of child language acquisition, and reveal the effects of language-specific properties on how children acquire language.

This project can further inform issues of education (addressing the knowledge-state of Mandarin- and Cantonese-acquiring children at the onset of schooling), speech pathology (understanding the different normative trajectories for development) and language acquisition in different contexts, such as second language and bilingualism.

Project Reference No.: UGC/FDS15/H02/24
Project Title: Positive side to juggling between work and care? A mixed-method investigation on work-family enrichment among Hong Kong working caregivers for adults with long-term care needs
Principal Investigator: Dr LAU Hi-po (Shue Yan)

Abstract

Family and work are two important sources of satisfaction and meaning in adult life. Succeeding in both roles is often stressful but could also be significantly gratifying. With the aging population and the rise in the prevalence of decapacitating chronic illnesses, the global population of working caregivers is increasing. For instance, in the United Kingdom, the ratio of workers who need to juggle between work and informal care for an adult rose from one in nine in 2011 to one in seven in 2019. In Hong Kong, the population of informal caregivers for older adults and adults with disabilities reached 1.12 million in 2021, with about one-sixth to one-third of them working in a full-time job. Role theorists have long postulated that people engage in multiple roles for benefits such as self-esteem, knowledge, perspectives, and tangible resources. These resources may be transferred from one role to benefit the quality of life in another role, as captured by the concept known as work–family enrichment (WFE). While the literature has garnered sufficient understanding on how conflicts arise from juggling between work and care, researchers do not have an equivalent level of understanding on how engaging in one role may benefit the performance of another. Moreover, providing care to a needy adult is qualitatively different from childcare due to the greater complexity of duties arising from disabilities and multi-morbidities, higher vigilance required for acute incidences (e.g., hospitalization and falls), and an often-downward trajectory that ends with the death of the care recipient. Unfortunately, unlike working parents, empirical studies for working caregivers for a needy adult remain scarce. Considering these two gaps in the literature, this study will explore WFE, in contrast to work–family conflict (WFC), among Hong Kong working caregivers for adults with long-term care needs. This project will adopt an explanatory sequential mixed-method design to investigate four research objectives. Study 1 will be a two-wave longitudinal quantitative survey with 575 local Chinese working caregivers of an older adult or an adult with disability and/or chronic illness. Considering the heterogeneity of the population, latent profile analysis will be used to derive a typology for local Chinese working caregivers (Research Objective 1). Then, the levels of WFE and WFC will be compared across different caregiver profiles (Research Objective 2). Structural equations modelling will be used to model the associations among WFE and WFC with work, family, and well-being outcomes (Research Objective 3) and quality of care (Research Objective 4). In Study 2, a sub-sample of the caregivers with different latent profiles will be invited for an in-depth interview with their care recipients to derive a nuanced, contextualized understanding of WFE and WFC. While the findings of Study 1 will be used for enriching the interview guide of Study 2, the findings of Study 2 will also enrich the quantitative knowledge regarding the levels and strengths of associations among the key constructs from Study 1. The findings of the two studies will be connected to provide a comprehensive overview of the understudied phenomenon of WFE. Sustaining workforce participation despite the growing demand for informal care amid the aging population has become a policy priority for metropolises such as Hong Kong. By elaborating on the positive sides of the work–family dynamics, employers, care professionals, and policymakers will be equipped with the knowledge for developing and enforcing suitable family-friendly organizational policies as well as work-friendly long-term care services.

Project Reference No.: UGC/FDS15/H16/24
Project Title: Understanding the Elderly-computer Interaction (ECI) in Social-Virtual Reality Applications: An Exploratory Study of the Semiotic-driven Approach and Post-experiment User Enquiry
Principal Investigator: Dr LAU Kung-wong (Shue Yan)

Abstract

This research project addresses the growing elderly population and the need to improve their well-being and quality of life. With the global and Hong Kong elderly populations projected to increase, there is concern regarding healthcare capacity and retirement policies. Living in cramped environments can lead to negative effects on the elderly, such as loneliness and social isolation. Technology, particularly social virtual reality (social-VR) applications, has shown promise in improving the social well-being of the elderly. However, there is a lack of research specifically focused on the interactions of the elderly with social-VR platforms. This project aims to develop theories and principles for designing elderly–computer interaction (ECI) in social-VR applications. It focuses on exploring the development of ECI practices and addressing local ageing issues. The research design involves a semiotic-driven approach and analysis of existing human–computer interaction (HCI) in social-VR applications, followed by a post-experiment user inquiry. The findings from these phases will be used to develop principles for designing ECI.

The research questions include examining the effectiveness of elderly-specific interaction design in social-VR applications, identifying key principles for designing interfaces tailored to the elderly, and evaluating the applicability of traditional HCI theories and approaches to elderly users and interactions in the social-VR environment. Overall, this research project seeks to improve the well-being of the elderly through the development of ECI in social-VR applications, addressing the unique needs and challenges faced by this population.

Project Reference No.: UGC/FDS16/H10/24
Project Title: Resting-state functional connectivity of stress mindset and their association with psychological resilience: An fMRI study
Principal Investigator: Dr LAU Kwok-wai (HKMU)

Abstract

The Stress Mindset Theory states that our perception of stress is a meta-cognitive process that shapes our behaviors and coping styles independent of any specific stressful events. Under this theory, our stress response is monitored by the interpretation/mindset of stress that is either enhancing (stress-is-enhancing, SIE) or debilitating (stress-is-debilitating, SID). Cultivation of SIE has recently been demonstrated as an evidence-based training resulting in modification of biological and behavioral outcomes such as improved cardiovascular success, and reduced anxiety symptoms during COVID-19, in more than 5000 participants across 6 double-blind, randomized, controlled studies. Cultivation of SIE can be done by viewing short videos that illustrate the positive effect of stress. Although alteration of mindset has demonstrated promising changes in different populations, individual factors could exist and diminish the treatment outcomes. Particularly, it is unclear about the individual differences in terms of the relationship between the trait-like and state-like stress mindset. Understanding the neuroscience of stress mindset can help identify objective neural moderators or variables that determine the effectiveness of training in cultivating SIE. In another word, neuroscience can reveal the underlying mechanisms of Stress Mindset Theory, hence, isolate the effective components of SIE and optimize it. However, we found no reports on the neural features of stress mindset.

The current proposed study, therefore, aims to fill the research gap by investigating neural features of the trait-like and state-like stress mindset and determine their role in resilience. The first part aims to determine the resting-state functional connectivity of the trait-like stress mindset. One hundred and fifty university students will be assessed for their stress mindset and resilience levels using self-reported questionnaires. They will be divided into the positive mindset group (N=75) and the negative mindset group (N=75) based on their Stress Mindset Measure scores. Both groups will go through functional magnetic resonance imaging (fMRI) brain scans at rest and their resting-state fMRI will be compared. The second part aims to determine the influence of the trait-like nature of stress mindset (either positive or negative) on the state-like stress mindset stimulated by the SIE training materials. In this part, the same groups of participants will go through another round of fMRI scans in response to three short videos (the SIE videos) that demonstrate the positive influences of stress inside the scanner. Functional connectivity in response to the SIE videos will be compared between the positive and negative mindset groups. Their stress mindset and state resilience level will be evaluated immediately after the scan to assess the difference in stress mindset and state resilience before and after watching the SIE videos. Our preliminary findings of resting-state fMRI from 18 university students demonstrated significant higher levels of regional homogeneity (ReHo) in the left inferior frontal gyrus extending to insula and right fusiform gyrus, and lower ReHo in the right orbitofrontal cortex (OFC) and left superior parietal gyrus in subjects with dispositional SIE mindset (SIE group) than that in the SID group. These regions have been reported to be associated with psychological resilience.

Findings from this study would provide new knowledge on the neural mechanism of trait-like and state-like stress mindset, and their association with trait and state resilience. This information is important for tailored interventions for cultivating resilience and enhancing well-being.

Project Reference No.: UGC/FDS16/M06/24
Project Title: Development of Deep Learning Aided Raman Spectroscopy for Monitoring Harmful Algal Boom Causative Species
Principal Investigator: Dr LAU Po-ying (HKMU)

Abstract

Harmful algal blooms (HABs) are commonly found in Hong Kong waters, along the south coast in Mainland China and around the world. HABs give rise to many unfavorable impacts on aquatic environment such as wrapping of beaches with biomass or foam and a large quantity of fish death caused by oxygen depletion through excessive respiration or decomposition. HABs also cause great economic loss and damaging effects on aquaculture industry locally and worldwide. Early identification and monitoring of HABs are very important for protecting humans from the health risks and economic loss arising. A traditional method to identify and enumerate HAB causative species is light microscopy of organisms. It is tedious and time-consuming and requires a high-level of expertise in phytoplankton identification. Apart from light microscopy, current technologies applied for HAB detection and monitoring include remote sensing, in situ sensing, image-based appliances, molecular methods, and chemical assays. Different drawbacks and limitations of these technologies have been found such as high machine purchase cost and operational cost, and requirement for high technical usability.

Raman spectroscopy is a non-destructive chemical analytic technique, which renders information about chemical structure and molecular interactions. Raman scattering is an inelastic scattering of light that happens when matter is illuminated by light. Raman spectroscopy gives a fingerprint to identify molecules by detecting vibrational frequencies of their specific chemical bonds and symmetry. Several advantages of using Raman spectroscopy for taxonomic identification of microalgae include: identification by a taxonomist and sample preparation are not required; acquisition of Raman spectra is fast (real-time assessment); and it is non-invasive for the samples. On the other hand, recurrent neural networks (RNNs), which have internal memory, are a powerful and robust type of deep learning architecture. They are capable of remembering the input they receive, which enables them to predict subsequent data precisely. Especially, Long Short-Term Memory (LSTM) networks, an improved version of RNNs, are able to recognize patterns in sequential data and remember inputs over a long period of time. The storage of both long and short term memories greatly enhances its classification accuracy. Raman spectroscopy accompanied with LSTM networks provide a sophisticated technology for detecting and discriminating the imperceptible Raman spectral differences between microalgae species.

Limited studies have applied Raman spectroscopy to identify microalgae species, whether it is applied alone or in conjunction with machine learning algorithms, and the classifications were only at class or genus level. To date, no study has exploited Raman spectroscopy accompanied with LSTM networks for classifying microalgae species. In our pilot study, Raman spectroscopy were employed alongside a LSTM network to discriminate five HAB related microalgae species including Akashiwo sanguinea (AS), Dunaliella tertiolecta (DT), Fibrocapsa japonica (FJ), Peridinium sociale (PS), and Zooxanthella microadriatica (ZM). The overall accuracy of the LSTM algorithm was 0.932 ± 0.074, which showed an excellent performance of discriminating the five microalgae species. We have also developed a Raman spectroscopic protocol for analyzing field samples, with which spectra acquisitions were proceeded by the Raman machine automatically. The whole process from sample processing (filtering, resuspension, and centrifugation) to Raman spectral acquisition was less than 1 hour. This method greatly reduces the time and expertise for taxonomic identification by taxonomists using light microscope. Building on these pilot findings, this proposed study aims to develop a rapid, accurate and cost-effective technology to detect HAB causative species at species level for routine taxonomic identification in the laboratory and provide fundamental data for future study.

Project Reference No.: UGC/FDS25/E04/24
Project Title: Accurate urban forest carbon storage estimation by comprehensive remote sensing
Principal Investigator: Dr LEE Shing-him (THEi)

Abstract

Urban trees can sequester carbon and combat climate change. There are different methods to assess the carbon sequestration benefits brought by urban trees. Remote sensing techniques have been widely applied in the estimation of carbon storage by trees.

Urban forest managers can measure the key dimension of urban trees, e.g. diameter at breast height, tree height, etc., and substitute the measured quantities into previously derived equations to estimate the carbon storage in each tree. This method, called allometry, may be inefficient for large urban green space. Remote sensing technologies, e.g. LiDAR scanning, can quickly collect point-cloud data and reconstruct trees as virtual objects in a 3D-software space. However, the accuracy of the measurements can be improved because estimation input parameters, e.g. biomass, moisture percentage, and carbon content percentage, may be wrongly assumed. This project will demonstrate remote sensing techniques, coupled with previously obtained empirical data set for accurate measurement of carbon storage in trees in urban green space.

This project aims to: (1) quantify the carbon stock in trees in different types of urban green space during different seasons in study areas of Hong Kong; and (2) assess the improvement in accuracy by consolidating dendrometric data collected via terrestrial laser scanning in urban green space.

This project is divided into 6 six-months-long stages. After the initial preparation stage, pilot-testing will be initiated. Live data collection will cover three types of urban green space (urban parks, pocket parks, and slopes) in the wet and dry seasons (summer and winter). Comprehensive findings can be generated. After the promotion of the research findings in academic conferences, peer-reviewed publication will assist the knowledge transfer by this project.

Project Reference No.: UGC/FDS24/B11/24
Project Title: Effect of Online Community Engagement and Community Goals on Waste Reduction Spillover Behaviours: A Pygmalion Perspective
Principal Investigator: Dr LEE Suet-mui (PolyU SPEED)

Abstract

Solid waste continues to pose substantial environmental challenges to the world. Despite governments implementing various waste reduction policies, global solid waste is projected to double its 2020 volume by 2050 (The World Bank, 2022). In the case of Hong Kong, where two-thirds of municipal solid waste is domestic waste, it is imperative to address the pressing issue of limited advancements in waste reduction programs and policies, especially considering the imminent exhaustion of landfills (EPDHK, 2023). Programs mitigating citizens’ waste production and disposal have gained little progress as encouraging individuals to engage in voluntary pro-environmental behaviours necessitates extensive endeavours to modify their attitudes, motivations, beliefs, and self-efficacy. However, online community studies found that community engagement effectively stimulates individual behaviours through daily social media routines. Two decades of online brand community studies showed that engaging consumers in effortless actions in social media communities (e.g., viewing, liking, or sharing posts) significantly affects desired behaviours. Recently, scholars have expanded the knowledge of online community studies into the pro-environmental context and found that online community engagement is associated with community-advocated behaviours. These initial investigations have not fully exploited the vast knowledge of online community research, limiting the potential of using online communities to affect pro-environmental behaviours.

This project aims to examine how theories developed and conceptualised in prior online brand community studies can be applied in the online community to stimulate waste reduction and potential spillover behaviours. By understanding the effects of community identity (social identity theory) and community members’ expectations (the Pygmalion effect) on waste reduction behaviours advocated using the online community in social media, this study extends the theoretical application of online community research. This study will adopt a mixed-method design that integrates co-design sessions, controlled experiments, and post-experiment interviews to investigate the interaction effects of community identity and members’ expectations in online communities with different goals (social goal vs functional goal) and hosts (organisation vs user) on desired behaviours. The findings will also provide insights to pro-environmental and governmental organisations to use online social media communities to promote waste reduction and potential spillover behaviours.

Project Reference No.: UGC/FDS16/M13/24
Project Title: Dynamic Crosstalk Between Algicidal Bacterial Isolate Sagittula marina (F5) and Algal-associated Bacteria, and Regulation of F5 Efficacy Against Karenia mikimotoi Based on Metabolomic and Proteomic Analyses
Principal Investigator: Prof LEE Wang-fat (HKMU)

Abstract

Harmful algal blooms (HABs), particularly those caused by highly toxic Karenia mikimotoi, pose a significant global environmental issue, damaging the fishing industry and threatening human health. K. mikimotoi has notably affected Hong Kong and mainland China, causing substantial losses due to fish and shellfish deaths. For instance, outbreaks of K. mikimotoi blooms in 2012 caused a massive die-off of abalones in Fujian, China, resulting in losses exceeding US$330 million, and in 2016, over 200 tons of fish were killed in various Hong Kong fish farms. Therefore, controlling HABs is crucial, and studies suggest that algicidal bacteria could be an effective solution.

Research indicates that the efficacy of algicidal bacteria in killing algae can be influenced by algal-associated bacteria (bacteria that naturally coexist with the algae). Our research has focused on a K. mikimotoi strain (KMHK) and an algicidal bacterial strain (Sagittula marina, F5) isolated from a late stage of KMHK bloom in Hong Kong. We found that F5 has a strong indirect algicidal effect on KMHK, involving the release of algal-lytic algicides. Interestingly, the algicidal efficacy of the F5 bacterial culture in xenic KMHK was 60% higher than that in axenic KMHK, but a less potent algicidal effect of the bacterial supernatant on xenic KMHK was observed. This implies that there are interactions between KMHK-associated bacteria and F5, which boosts the ability of F5 to kill the algal cells. We then performed a similar experiment to co-culture axenic and xenic KMHK separately with natural seawater, with and without removal of the bacteria. Surprisingly, the cell density of xenic KMHK dropped dramatically when cultivated with natural seawater containing bacteria, when compared to other treatment groups and the controls. These findings strengthen the idea that algicidal bacteria interact not only with the algal cells but also with the bacteria associated with the algae. However, the underlying mechanism on their cell-to-cell interactions and modulation on the algicidal effect is virtually unknown. Furthermore, we discovered that the ichthyotoxicity of KMHK can be modulated by its associated bacteria, with varying effects from different individual bacterial isolates within the consortium. These KMHK-associated bacteria have been successfully isolated and will be adopted in this proposed study.

In continuation of our preliminary study, the present proposed research aims to investigate the molecular pathways and interactions between F5, KMHK, and their associated bacterial strains on the modulation of algicidal efficacy through comparative metabolomic and proteomic analyses. The project comprises three main parts. (1) We will investigate the impact of selected KMHK-associated bacterial strains on the algicidal efficacy of F5 and the combined effects of the strains exhibiting the highest and the lowest effects. (2) We will assess the influence of the cell-to-cell interaction between F5 and the KMHK-associated bacterial strains in modulating the algicidal effect. Following this, we will evaluate the biochemical, cellular and physiological responses of the microbial cells in various co-culturing experiments between F5, KMHK and /or associated bacterial strains. (3) We will study their molecular interactions under various selected conditions using comparative metabolomic and proteomic analyses. Concurrently, we will infer the molecular responses of both bacteria cells and KMHK cells through their exo- and endo-metabolites and protein profiles. It is crucial to understand the roles of the bacteria associated with the algae and the mechanism of their influence on the efficacy of algae killing, as this closely reflects the natural environmental conditions. This proposed study is the first to apply proteomic and metabolic approach to unravel the molecular interplay between the two types of bacteria and KMHK, and their modulation of algicidal efficacy. Results of this study can also contribute to the development of an effective strategy to prevent fish deaths caused by HAB, which will have significant implications for fish farms and shellfish industries.

Project Reference No.: UGC/FDS16/H01/24
Project Title: The Construction of Literary Thought and Cultural Ideology: An Analysis of Stephen Soong's Cultural Activities and Networks in Hong Kong (1951–1996) in the Cold War Context
Principal Investigator: Dr LEUNG Rebecca Mo-ling (HKMU)

Abstract

Stephen Soong (宋淇) (1919-1996) relocated with his family from Shanghai to Hong Kong in 1949 and passed away in 1996. During his more than 40 years in Hong Kong, the Cold War went through multiple critical stages before its conclusion. Throughout this period, Stephen Soong's cultural activities in Hong Kong vividly reflected his conceptualization of literary thought, as he delved into realms such as literary criticism, classical literature research, new literary creation, and other forms of literary discourse construction, which were driven by a strong motivation to actively participate in the literary and political discourse struggles during the Cold War period, as a literary critic. Additionally, Soong aimed to integrate into the political discourse of the Hong Kong literary field, while he faced challenges as a westernized intellectual and as a migrant from the south within the backdrop of the Cold War, adding a nuanced dimension to his experiences. Soong's pursuits in the cultural field encompassed a wide range of disciplines, including literary creation, translation, movie production, editing, publication, academic administration, and research. With an extensive social network, he maintained close connections with renowned scholars and writers such as Eileen Chang (張愛玲), Hsia Chih Ching (夏志清), and Hsia Tsi An (夏濟安), as well as cultural organizations and institutions like Motion Picture & General Investment Company Limited (國際電影懋業有限公司), the Chinese University of Hong Kong, Sing Tao Daily, and various scholarly magazines such as Renditions (《譯叢》) and Grove Magazine (《文林》). Additionally, Soong was actively engaged in the Cold War context through his association with organizations like the United States Information Agency, the Asia Foundation, Committee of Free Asia, and Hong Kong Union Press, among others. This research seeks to analyze how Soong, through his critical viewpoints, utilization of knowledge resources, and cultivation of interpersonal relationships, established his unique literary interests. Furthermore, it examines how he expanded his social networks to enhance his cultural capital and developed his own cultural ideology. The focal point of this study lies in exploring these aspects of Stephen Soong's work. Furthermore, the study will analyze the impact of Soong and his networks on the cultural sphere by examining how they positioned themselves amidst the dichotomy of nationalism and cosmopolitanism.

This study aims to investigate the period between Stephen Soong's initial involvement in Hong Kong's cultural field in 1951 and his passing in 1996. This research will employ Pierre Bourdieu's (1930-2002) literary field theory as the primary methodological framework. Through a comprehensive case study of Stephen Soong's cultural activities and networks, and by using digital tools and research data management skills, this study seeks to analyze how he constructed his own cultural ideology by integrating traditional literary thought with Western theoretical engagement, while also incorporating textual criticism within the context of the Cold War. Additionally, the research will explore the transformations experienced by different entities within the cultural field during this period. The study focuses on two primary areas. Firstly, through an in-depth examination of Stephen Soong and his connections, this project explores how their literary and academic networks contributed to the establishment of a cultural ideology that diverged from both contemporary Chinese Communist literature and Western perspectives during the Cold War. Secondly, this study aims to uncover the objective relationships between Soong, acting as an agent, and the positions established by his affiliated organizations and networks. By employing the field theory, social network analysis and digital tools, the research will digitize, visualize and analyze the impact of these relationships on the development of Soong's distinct brand of literary thought. Through these endeavors, this study will provide a deeper understanding of the socio-political and socio-cultural context of Hong Kong during the Cold War.

Project Reference No.: UGC/FDS24/B16/24
Project Title: Customizing Design Strategies for Virtual Reality to Reduce Cybersickness and Enhance Mood in Older Adults: Insights from Randomized Experiments in Hong Kong
Principal Investigator: Dr LEUNG Wilson Ka-shing (PolyU SPEED)

Abstract

The world is currently experiencing a phenomenon of population aging, and Hong Kong is no exception, with the aging population projected to reach 36.6% by 2066 (Wong & Yeung, 2019). Elderlies are particularly vulnerable to mood problems due to dwindling social relationships and declining health (CityUpdate, 2021), which poses a challenge for the public healthcare system (Borson et al., 2001). Addressing the emotional well-being of older adults has become a pressing social issue, as a positive mood state is crucial for their overall well-being. However, there is currently a lack of resources in Hong Kong specifically tailored to addressing emotional problems in older adults (The University of Hong Kong, 2022). A recent report in Hong Kong indicated that more technological resources should be allocated for mood management to complement the traditional methods such as counseling services (Our Hong Kong Foundation, 2022).

Recent reviews have suggested that virtual reality (VR) technology, by providing a strong sense of presence in the virtual scenes, has the potential to enhance one’s mood (Dermody et al., 2020; Riches et al., 2021a, 2023). However, its adoption among elderly remains limited due to concerns about cybersickness, which includes symptoms such as headaches, dizziness, and discomfort (Chang et al., 2020; Sevinc & Berkman, 2020). Cybersickness is a significant concern when introducing VR technology to the public, as it can hinder mood enhancement while experiencing virtual environments. Understanding this barrier is important for designing more effective virtual scenes that can be widely used for mood management. Potential cause of cybersickness are the degree of presence experienced in virtual environments and individual characteristics (Weech et al., 2019). However, previous studies have yielded inconsistent findings regarding the effects of manipulating presence on cybersickness, even when based on the same theoretical framework (Weech et al., 2019). Additionally, the potential influence of age on the experience of presence in VR and susceptibility to cybersickness has attracted limited academic attention (Dilanchian et al., 2021). There is no consensus in the existing literature on how to customize VR scenes to improve mood and reduce cybersickness, let alone exploring whether manipulating the presence levels of different age groups will lead to varying degrees of cybersickness. Our interdisciplinary research team, comprising researchers in the area of media and communication, information systems, and healthcare, collaborates with elderly service organizations (i.e., Sik Sik Yuen) will conduct two experiments to address the mentioned inconsistent research findings.

Given that there are two main ways to manipulate a sense of presence within virtual environments, namely physical and psychological (Weech et al., 2019), this study will undertake two randomized experiments by integrating presence theory with a number of other theories, such as cognitive load theory, sensory conflict theory, social presence theory, generation cohort theory, and mere exposure effect, to explore the relative effectiveness of each manipulation. A set of psychological state measures (e.g., State-Trait Anxiety Inventory and multidimensional mood questionnaire) and an objective stress level measurement – heart rate variability will be applied to measure the mood changes between pre-VR usage and post-VR usage. Additionally, mixed-methods design will be applied to refine our virtual environment development. Our findings could shed new light on whether there are interactions between presence and other variables that affect cybersickness and mood, thereby contributing to the development of the presence theory and the understanding of the occurrence of cybersickness. Overall, we contribute not only to the literature, but also provide managerial guidance for the government, elderly service organizations, VR content designers, and tertiary education.

Project Reference No.: UGC/FDS14/H10/24
Project Title: In Search of Property-Owning Democracy: The Idea of Predistribution in Adam Smith's and J.S. Mill's works
Principal Investigator: Dr LI Man-kong (HSUHK)

Abstract

This research project explores whether Adam Smith’s and J.S. Mill’s works could be reconstructed to provide better understandings and insights for the contemporary idea of predistribution, most prominently suggested by John Rawls in his idea of a property-owning democracy as an ideally just economic regime. In his work, Rawls defended his principles of justice, namely, the principles of equal basic liberties, the principle of fair equality of opportunity, and the difference principle which guarantees the greatest advantages to the worst off, as the guiding principles of regulating the basic structure of a society (2001, 42–43). While Rawls’s principles of justice are widely considered as providing philosophical justification of the welfare-state capitalism, Rawls himself argued that the large inequalities allowed by it make it violate all his principles of justice: that is, rendering the least advantages politically and economically subordinated to the capitalists. Instead, he proposed that we should endorse a ‘property-owning democracy’, which would guarantee ‘widespread ownership of productive assets and human capital (that is, education and trained skills) at the beginning of each period’ (2001, 139-140).

Yet, Rawls himself provided notoriously little details of what he meant by a property-owning democracy, or, as commonly understood in the literature, a predistribution regime (Thomas 2017), only citing the British Nobel-prize winner economist James Meade’s proposal (1964). But widespread ownership of capitals is only one part of Meade’s proposal, which arguably also has a strong redistributive welfare regime. Mainly due to a focus on whether Rawls was interpreting Meade correctly, the literature on Rawls’s idea of property-owning democracy tends to, curiously, gloss over Rawls’s own formulations. On the other hand, there is a contemporary discussion on the idea of predistribution as a radical proposal to reform capitalism, first suggested by the Yale political scientist Jacob Hacker; it was later even adopted by the British Labour party in their 2015 election platform, which argued that welfare-state policies are focusing too much on redistribution of people’s market income, rather than reforming the structure of market and capitals (Hacker 2011, BBC 2012).

This project suggests that looking to Adam Smith’s and J.S. Mill’s writings, rather than focusing on Meade, could provide a better understanding of a Rawlsian property-owning democracy, or predistribution regime. This is an unexplored area. While Rawls cited extensively Smith’s and Mill’s writings in his work, no systematic comparison of what they take as an ideally just economic regime has ever been done in Rawls scholarship. In Smith and Mill scholarship, a systematic comparison of their work with Rawls’s idea is also lacking. This is surprising, because recent literature on Smith and Mill tend to debunk the usual image of them being apologists of free-market capitalism. Instead, the literature suggests that Smith and Mill, as the founder and the most mature writer for the classical political economy tradition (Landreth & Colander 2002; O’Brien 2018), indeed shown traces of being egalitarians, who aiming at putting market in use for ensuring people’s distributive equality; Mill even self-identified himself as a ‘socialist’ (See e.g., Boucoyannis 2013; Herzog 2016; Persky 2016; McCable 2021). This research project, by nature an exercise of normative political and economic theory (Gaus 2018), thus aims to examine Smith’s and Mill’s ideas systematically, to see if they could provide fruitful insights for institutional and policy reform of capitalism to bring in a Rawlsian predistribution regime.

Project Reference No.: UGC/FDS16/E11/24
Project Title: Life-Cycle Resilience Enhancement to Tall Buildings against Typhoon-Induced Windborne Debris Risk
Principal Investigator: Dr LI Yaohan (HKMU)

Abstract

In past decades, climate change has escalated the frequency and intensity of climate-related hazards, with typhoons becoming a prominent threat, especially for coastal urban regions. Tall structures, integral to the modern cityscape, are now facing heightened risks from windborne debris during typhoon events. Historical observations have consistently identified such debris as a primary source of damage to the exterior of tall buildings during typhoons. This study is motivated by the pressing need to mitigate such risks posed to high-rise structures and enhance building resilience over its lifetime under the uncertain impact of climate change. To address these challenges, this research aims to develop a probabilistic framework to enhance the life-cycle resilience of tall buildings against typhoon-induced windborne debris. The focus is quantifying the vulnerability of building envelopes, assessing economic losses and lifetime resilience, and formulating strategic adaptations to mitigate the adverse impacts and enhance building resilience under climate change.

The proposed research will tackle two critical issues. The first objective is to develop a probabilistic fragility model that estimates the failure probability of building envelopes. This model will be informed by a detailed understanding of the failure mechanisms, which are due to the uncertain trajectories and impacts of flying debris during typhoon events. The second issue is to quantify the resilience and economic loss of the building, especially the downtime and recovery performance of tall buildings due to windborne debris damage under typhoons subjected to climate-related uncertainties within a life-cycle context, which is rarely described in existing literature. To address the first issue, a multivariate copula-based typhoon hazard analysis model will be developed to effectively address the complicated uncertainty modeling associated with typhoon parameters. Furthermore, a computational dynamics fluid model will be established to simulate the local wind parameters and the impact of flying debris hitting the investigated building. Subsequently, this project aims to tackle the second issue by quantifying both direct and indirect economic losses stemming from such non-structural damage. In particular, a life-cycle resilience assessment approach is proposed to quantify the downtime due to service interruption of the building and model the functional recovery following typhoon events. Additionally, an adaptive decision analysis tool is developed to yield an optimal adaptation strategy for tall buildings aligned with the life-cycle resilience enhancement goal. The optimal strategy will balance short-term practicality with long-term resilience objectives, thus empowering stakeholders to make well-informed decisions subjected to uncertainties in the changing climate. This research is expected to significantly contribute to hazard mitigation and structural engineering by offering a life-cycle resilience enhancement framework for tall buildings against typhoon-induced windborne debris under climate change, thereby ensuring their sustained functionality and mitigating potential losses. The proposed framework will be applied to tall buildings in Hong Kong and extending its implementation to typhoon-prone regions of the Greater Bay Area to facilitate the life-cycle resilience enhancement of urban buildings.

Project Reference No.: UGC/FDS14/B05/24
Project Title: Not Knowing is a Blessing? An Information Asymmetry Perspective of Pay Secrecy
Principal Investigator: Dr LIAO Yi (HSUHK)

Abstract

Employees refer to pay information to understand their value to the employer, while such information also plays a critical role for organizations to attract and retain talents. Nowadays, organizations are facing a dilemma in deciding their pay information disclosure practices—what elements and how much pay information to disclose, which channel to use, and what approach to adopt in dealing with employee reactions. While pressured by workforce and societal request for more transparency, many organizations still practice some level of pay secrecy, such as restricting disclosure of individual pay information or inhibiting employees from exchanging such information. To both organizations and their employees, there are important benefits and costs of practicing pay secrecy. Pay secrecy allows for greater discretion when determining compensation, thus avoiding invidious peer comparisons and protecting individual privacy. However, employees tend to assume the worst when they know that something is withheld from them. Restricting disclosure pay information as a shield for discriminatory salary practices may also hurt employees’ fairness perceptions, demotivate employees for potential inequity perceptions, limit the potential for labor mobility, and ultimately harm labor market efficiency, as employees are less likely to move to jobs for their highest value.

Given such controversy in organizational practice, pay secrecy also attracts scholarly attention. While some research identified its beneficial role in privacy protection, most recent research findings pointed out its undesired impact on employees’ fairness perceptions. However, extant research on pay secrecy has several gaps. Much investigation and scholarly discussion focused on macro-level topics, such as organizational policy making and human resource management strategies. Although researchers have started to investigate how such practices influence employees (and have thus adopted a micro-level focus), such studies are largely based on the organizational justice framework and experimental or simulation data. While pay secrecy practice has a complex nature—that it involves quantity and quality of information to be disclosed, channel and timing of disclosure, its impact on employees and organizations is also multifaceted and needs further theoretical extension and empirical evidence. Thus, it is important to adopt other theoretical perspectives as well as use actual organization data to further understand the mechanisms through which pay secrecy influences employees’ and organizational outcomes.

In this proposal, we integrate the information asymmetry perspective with the signaling theory to investigate employees’ reactions to pay secrecy practices, their subsequent perceptions of their own and organizations’ value, and the attitudinal and behavioral outcomes. In addition, we propose that credible and costly signals that can be sent by organizations will influence employees’ perceptions and responses. We posit that providing employees with specific signals from which they can infer their value and status can mitigate the unfavorable outcomes of pay secrecy. Our ultimate aim is to: (1) gain further understanding of the information asymmetry dynamics between organizations and employees; (2) develop theoretically important and practically meaningful frameworks to contribute to the pertinent literature; and (3) offer practical recommendations to organizations for appropriate and effective pay information disclosure strategies.

Project Reference No.: UGC/FDS14/H20/24
Project Title: A Study on the Anthologies related to Yushan Yaji in Mongol-Yuan Era
Principal Investigator: Dr LING Chung-wing (HSUHK)

Abstract

Gu Ying (顧瑛, also known as Gu Aying 顧阿瑛 or Gu Dehui 顧德輝, 1310-1369) was born into a wealthy merchant family in Kunshan 崑山 of the Wuzhong region 吳中地區. He was known for his grand garden named “Yushan Jiachu” 玉山佳處 (Wonderful Place amid Jade Mountain) to the west of his estate and organizing poetry salons that gathered literati from all over the empire. In view of the large number of participants and their diverse backgrounds, Gu established the most expansive social network of poets at that time, known as the “Yushan Yaji” 玉山雅集 (the Poets Gatherings at Jade Mountain), which is widely regarded as one of the most important cultural phenomena in late Yuan and even in the history of Chinese poetry. Beyond its significance in literary studies, the “Yushan Yaji” is also intricately tied to the issues of politics, cultural dissemination, and intellectual history during the Yuan era, standing out as a crucial pathway for studying the late Yuan period.

The primary research materials concerning the group stem from a series of anthologies compiled by Gu himself. According to various bibliographies, there are at least nine distinct titles, with six of them extant. Notably, Gu employed varied structures for each work within classic anthology format. Delving into these works could potentially offer a comprehensive understanding of the “Yushan Yaji” from diverse perspectives. However, the current research on this topic is not without its limitations. On the one hand, scholars frequently deny the significance of the group’s works in the realm of poetic studies, categorizing the anthologies as mere historical artifacts that reflect the gatherings. On the other hand, some researchers view the group as a subsidiary aspect of Yuan poetry research, hence the lack of in-depth discussions. These disparities highlight the necessity for further examination of this topic.

This project plans to commence by organizing and analyzing the fundamental information of relevant anthologies, and then turn to the poetic aspects for a meticulous examination of the writing techniques, poetic characteristics, artistic pursuits, and the literary historical value of the “Yushan Yaji”. The scope subsequently broadens to encompass diverse humanities topics, such as the salon culture and the psychological analysis of the late Yuan literati. The study will conclude with clarifying the values of the research topics, methods, and propositions to the academic community.

The significance of this project lies in its potential to address a crucial gap that has been overlooked in the current academic landscape, especially in the context of Yuan literature and Chinese poetics. It seeks to raise public awareness of Yuan poetry and its historical context and thus contributes to a deeper understanding of Chinese traditional literature. In the long run, this undertaking aspires to establish innovative and reliable paradigms in the studies of Yuan poetics and Chinese classic anthologies.

Project Reference No.: UGC/FDS11/E03/24
Project Title: Towards Building Trustworthy and Practical Deep Clustering Net
Principal Investigator: Dr LIU Hui (SFU)

Abstract

Deep clustering is a powerful machine learning technique that combines deep learning and clustering algorithms to perform unsupervised learning. Unlike the traditional clustering methods that rely on manual feature engineering or shallow representations, deep clustering utilizes deep neural networks to automatically learn intricate feature representations from raw data. By leveraging the hierarchical and non-linear capabilities of deep neural networks, deep clustering can effectively capture complex patterns and structures in high-dimensional and unstructured data, such as images, text, and audio. Deep clustering has been applied in diverse domains, including computer vision, natural language processing, and bioinformatics. Deep clustering enables the discovery of meaningful and coherent groups within the data without relying on labeled information, making it particularly valuable in scenarios where labeled data is limited or unavailable. However, the existing deep clustering methods usually suffer from two significant limitations. First, pseudo labeling, which is commonly used to fine-tune deep clustering networks, introduces the risk of overconfidence where the network's predicted confidence exceeds its actual accuracy. This overconfidence hinders the application of deep neural networks in decision-making systems, such as medical diagnosis. Second, previous methods assume balanced clusters, which is not realistic in real-world scenarios.

In this project, we aim to address these limitations and investigate trustworthy and practical deep clustering frameworks. First, to solve the over-confidence problem and build a well-calibrated unsupervised deep clustering net, we will explore methods to measure network calibration and develop techniques to align the constructed features with the network's output, reducing overconfidence. By establishing a well-calibrated deep clustering net, we can enhance the quality of pseudo labels and improve overall clustering performance. Second, to construct a practical deep clustering net capable of handling cluster imbalance scenarios, we will employ techniques to assess the imbalance level in clustered samples and propose effective approaches to tackle imbalanced clustering. Additionally, we will leverage the representation ability of the foundation model to alleviate challenges associated with cluster imbalance.

The development of a well-calibrated and reliable clustering model will have significant implications for various downstream tasks. In this project, we will focus on two specific tasks. First, we aim to reduce labeling costs by utilizing the well-calibrated unsupervised clustering net to guide the selection of important samples for labeling, thus optimizing overall labeling cost. Second, we will address the challenge of label noise. By utilizing the deep clustering net as a preprocessing step, we can learn a discriminative representation that is robust to label noise.

This project will contribute to fundamental research in unsupervised learning, deep learning, and clustering. It will also have practical applications in various domains such as general data compression and activities related to uncertainty estimation, including financial investment and disease diagnosis.

Project Reference No.: UGC/FDS14/B08/24
Project Title: Two Birds, One Stone? A Look on China's Targeted Reserve Reduction in the Context of Going Green and Opening up
Principal Investigator: Dr LIU Shuaiyi (HSUHK)

Abstract

The Chinese monetary policy regime is unique comparing to some others as the central bank has been frequently manipulating reserve requirements rather than the policy interest rate as a way to stabilize domestic economy. The reserve requirement ratio is found to be cut more aggressively for smaller and underprivileged banks when the central government revives the economy from COVID-19, which implies that heterogeneity in banks is interacting with targeted reserve adjustments to collectively impact bank lending and economic activities.

Apart from maintaining a medium-high speed growth, the country has been shifting its attention to environmental issues as domestic carbon dioxide emission is observed to rise concurrently with the swift economic expansion. While the Fourteenth Five-Year Plan aims to "facilitate environmentally-friendly progress and a balanced coexistence between humans and nature", the report of the 20th CPC National Congress reiterated the need of "advancing comprehensive environmental pollution management, and upholding precise, scientific, and lawful pollution control".

In light of this, would directional reserve reduction on banks’ green lending activities promote the country’s sustainable development? Particularly, considering China’s continuous efforts in opening up and the “pollution haven hypothesis”, will such directional reserve reduction for green loans be able to deter dirty inbound investment from polluted foreign firms?

To answer these questions, I propose to build a coherent Dynamic Stochastic General Equilibrium (DSGE) macro model of the Chinese monetary policy regime that explicitly incorporates the below two features. Firstly, China is modeled as a semi-open economy where the public but not the private sector would have access to international financial markets. Secondly, there is a dual-track banking system, in which greener firms have access to formal banks that enjoy lower reserve ratio; whereas more polluted firms borrow from the informal banking system that will be subject to higher reserve requirements. Using this framework, I study the welfare implication and environmental contribution of targeted reserve adjustments during the business cycle. A directional reserve reduction on green lending is anticipated to play a positive role in the country’s green transition. Furthermore, considering China’s long-standing commitment to financial reforms, I explore to what extent the effectiveness of targeted reserve requirements as a monetary policy tool might be affected by capital account liberalization, and if it could effectively discourage the pollution-haven-seeking behavior of some foreign firms when the country is further opening up.

Project Reference No.: UGC/FDS11/E02/24
Project Title: A transformer-based method for refining and abstracting sketches at different levels of details
Principal Investigator: Dr LIU Xue-ting (SFU)

Abstract

A sketch is a rough line drawing that is done quickly by an artist to represent the chief features of an object or a scene and is frequently used as a preliminary form of the final drawing in the field of design, such as urban design, architectural design, product design, and character design. After the preliminary sketching for conveying the idea, the artists commonly still need to abstract the sketchy lines or flesh out the details for different design and presentation purposes. For example, different levels of details are encouraged when the sketch is displayed on displays of different resolutions. Moreover, different scenes or objects may be designed at different levels of details by different artists, obtaining a visually consistent level of detail is important when a new sketch image is composed with different sketch components.

Unfortunately, despite the highly desired use of multi-level-of-detail sketch drawings, either refining or abstracting sketches due to the lack of precise definition in defining the level of details for a specific sketch drawing. That is, it is subjective to define whether two sketch drawings are of the same level of details. Without a specific metric for defining the level of details, the existing multi-level sketch generation methods mainly fall into two categories, raster solutions and vector solutions. The raster solutions take the raster sketch (a grid of pixels) as input and usually define the level of details as the style of the sketch drawing. Therefore, the raster solutions are usually lacking the capability of generating sketch drawings at infinite number of levels of details. Besides, the raster solutions may lead to blurred results with inconsecutive strokes. On the other hand, the vector solutions take the vector sketch (a list of strokes) as input and generally build a hierarchical tree or graph structure where the end nodes are the strokes or the graphical components. By progressively removing a node, the level of details of the sketches can be adjusted. However, these methods generally cannot be applied for refining the input sketch but can only be applied for sketch abstraction where the hierarchy of the original sketch is built on the input sketch. What’s more, the abstraction of the sketch is usually not semantic-based and is lack of the flexibility in abstract different types of components differently based on semantics. For example, a long wavy line could be abstracted into either a long straight line or a short wavy line.

We propose that semantic information should be adopted to guide the refinement or abstraction of the main structures, i.e., structural components, of the sketch so that the semantics of the sketch can remain unchanged. At the same time, the decorative components should be summarized or repeated directly based on its shape, without the need of semantic awareness for changing the structures. Motivated by this observation, it is expected to first classify structural strokes and decorative strokes in a sketch, and then apply different schemes for refining or abstracting the sketch. Specifically, we propose to encode a sketch into a vector form via a transformer-based representation. Then we decompose the sketch into structural components and decorative components by refining the network based on adversarial latent space stroke manipulation. The performance of the network could be improved by introducing contrastive learning and adversarial discriminator. Finally, we develop the abstraction operator and refinement operator to be used in the embedding space for manipulating the sketch.

The tangible research outputs of the proposed project would directly benefit the industry and the research society. The research project would also provide invaluable chance in developing the knowledge and skills of the teachers and the students in artificial intelligence and digital entertainment technology, which is also part of the curriculums and programmes offered by the school and the institute.

Project Reference No.: UGC/FDS16/E15/24
Project Title: Space-Air-Ground Integrated Networks: System Modeling and Performance Optimization
Principal Investigator: Dr LIU Yalin (HKMU)

Abstract

With the increasing deployment of aerial vehicles and satellites, their enabled non-terrestrial network will provide seamless coverage for global-range applications in future wireless networks. 3GPP has planned numerous standardization study items to integrate non-terrestrial networks into the upcoming 6G network. Several leading satellite providers, such as SpaceX and Lynk, are also establishing partnerships with mobile operators. Therefore, by integrating ground devices, aerial vehicles, and satellites, the space-air-ground integrated network (SAGIN) is a crucial technology for enabling the future network.

SAGIN can be considered a network comprising three spatial layers: i) the ground layer, consisting of ground devices; ii) the air layer, consisting of aerial vehicles; and iii) the space layer, consisting of satellites. Such a three-layer network has some unique characteristics. First, the integration of three network layers requires the merging of various network standards in terms of hardware and protocol, resulting in a heterogeneous network structure cross three layers. Meanwhile, due to the globally distributed satellites, SAGIN covers a wide range of ground devices and aerial vehicles all over the world, thus forming large-scale node distributions. Furthermore, the mobility of nodes in all three layers and the diverse transmission environments contribute to a highly dynamic network topology.

Overall, SAGIN is a large-scale, heterogeneous, and dynamic network. Implementing such a SAGIN is a complex process that necessitates meticulous planning, testing, and collaboration among multiple countries, mobile operators, and space/airborne vehicle providers. Theoretical research on system modeling and performance enhancement in SAGIN is crucial to facilitate this process and establish a solid foundation. However, to achieve this goal, we must tackle some challenges: 1) how to accurately model the heterogeneous network structure of SAGIN in large-scale three-layer node distributions; 2) how many performance metrics are required and how to investigate these metrics in SAGIN; and 3) how to design efficient network strategies in consideration of huge network dynamics in SAGIN.

This project aims to tackle the above challenges and develop theoretical research methods for accurate network modeling and efficient network optimization strategies for SAGIN. First, we plan to construct an accurate network model for SAGIN. The model can adapt to the heterogeneous structure of SAGIN, which includes diverse cross-layer transmissions with different propagation channels and transceiver configurations. Meanwhile, a spherical-based stochastic geometry method will be used to accurately represent the spatial locations and large-scale distributions of three-layer nodes in SAGIN. Second, we will investigate diverse performance metrics to meet the various application requirements in SAGIN. The investigated metrics include various common metrics such as path connectivity, outage probability, and network capacity. The analytical model for these metrics will also be developed in consideration of the accurate network model. Finally, we will exploit an efficient network optimization strategy to address the huge network dynamics in SAGIN. To effectively collect dynamic network status and implement the optimization strategy, we will utilize federated reinforcement learning to generate network decisions based on both local agents and global agents. Extensive simulation experiments will be conducted to validate the effectiveness of our network strategy.

Overall, this project will utilize theories from wireless communication, stochastic geometry, optimization theory, and federated reinforcement learning to establish a theoretical foundation for the practical implementation of SAGIN. The solution proposed in this project will also offer technical solutions for future SAGIN applications. For instance, the success of this project will help to construct an efficient SAGIN, consequently facilitating the development of the global range 6G network ecosystem, including smart cities and the metaverse.

Project Reference No.: UGC/FDS25/E05/24
Project Title: Fused Filament Manufacturing of 3D printed poly(3hydroxybutyrate 3 hydroxyvalerate) polylactic acid composite structure for footwear application: a new approach to efficient production of insole material
Principal Investigator: Dr LIU Yaohui (THEi)

Abstract

Interest in eco-friendly practices in the textile industry is increasing, especially around biodegradable materials that help reduce waste treatment pressure. While 3D printing is often used for making custom designs, there's not enough research on using biodegradable materials for this purpose. Our initial findings suggested that poly(3-hydroxybutyrate-3-hydroxyvalerates)(PHAs) demonstrate suitable flexibility and strength under optimal printing conditions and thermal treatment. Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) is one of widely focused biodegradable polymers of PHAs family. This project looks at how 3D printed fabrics made from two biodegradable plastics, PHBV and Polylactic Acid (PLA), can be used in producing tailor-made shoe insoles.

The project will firstly improve the processability and 3D printability of PHBV-PLA composite in Fused Filament Manufacturing by investigating various fractions of PHBV and PLA. Through a 3D modeling technique, insole structures will be designed and optimized using 3D printing software, and subsequently printed using a high-resolution 3D printer. Tensile tests will be conducted on the specimens to assess the behavior of the interconnected structures under tensile loads. The physical properties of insoles fabricated by PHBV-PLA composite under optimized conditions will be investigated for the potential for application. This study is poised to contribute to the advancement of research on the mechanical durability of biodegradable textile structures produced through 3D printing, particularly in the realm of wearables, with a focus on applications in footwear and textiles that hold promising prospects for the future.

Project Reference No.: UGC/FDS13(16)/E03/24
Project Title: Application of AI-enabled prediction of riverine ecosystem health for sustainable development
Principal Investigator: Dr LU Yi (HKMU)

Abstract

The world is witnessing a profound transformation driven by climate change. This phenomenon manifests through rising temperatures, altered precipitation patterns, and extreme weather events. According to United States Environmental Protection Agency, from 1901 to 2020, global precipitation has increased at an average rate of 0.04 inches (≈ 1.0 mm) per decade and global average surface temperature has risen at an average rate of 0.17°F (≈ 0.09 °C) per decade. These changes could disrupt riverine ecosystems, affecting species distribution, habitat availability, and overall ecological functioning, which are particularly vulnerable changes of temperature and water availability. Intense precipitations events significantly affect river flow, sediment transport, nutrient dynamics and water quality. Hong Kong, a densely populated metropolis, is home to over 200 rivers and streams. These rivers play a pivotal role in flood control, water source conservation, and biodiversity maintenance. A healthy mountainous river should sustain the stability and sustainability of its natural ecosystem while catering to the needs of human societal life and economic development. However, the sub-tropical climate in Hong Kong experiences extreme weather events almost every year, impacting river ecosystems. Intense rainfall, coupled with rising temperatures, affects water quality, flow dynamics, and aquatic life. Therefore, most likely, climate change poses a formidable challenge to riverine ecosystems worldwide, and Hong Kong must prioritize their conservation.

To safeguard riverine ecosystems, we propose collecting on-site data and employing advanced artificial intelligent (AI) techniques. It is vital to assess river health based on dominant functions, which is a multi-objective approach and not solely based on natural river functions. In this project, we aim to develop an Eco Sustainable Development Early Warning platform for enhancing our existing database into a comprehensive system capable of monitoring and evaluating the entire riverine ecosystem in the Lai Chi Wo (LCW) catchment, Hong Kong. This platform will encompass information on hydrological, ecological and environmental aspects. Our investigation will focus on assessing the impacts on local riverine health using AI-based deep learning models. Our previous study has already demonstrated the effectiveness of the AI models in predicting water quality for rivers. This success gives us the confidence to further apply deep learning models in our proposed project. In addition, the platform will also enhance the efficiency of responses to water-related ecological disasters, such as the impact of storms on soil erosion. This assessment method aligns with the socio-economic development and management of river basins. The Hong Kong government can implement preventative measures based on the warning information provided by our system, thus offering better pre-emptive protection for the local environment.

Project Reference No.: UGC/FDS14/E06/24
Project Title: Enhancing Production Efficiency and Responsiveness of Seru Production Systems: Uncovering the Synergy of Seru Formation and Seru Scheduling
Principal Investigator: Dr MA Hoi-lam (HSUHK)

Abstract

Seru production systems (SPSs), known as “Japanese Cell Manufacturing”, are recognized as one of the most successful manufacturing system designs in enhancing the responsiveness and resilience of the systems. Since the 1990s, because of the short product life cycle nature in electronic products, many giant electronics manufacturers (e.g., Sony, Canon) have adapted SPSs to enhance their responsiveness in adjusting their manufacturing capacity to response to the uncertain customer demands arising from different kind of products. SPSs innovatively focus on human-centric production mode, emphasizing the utilization of the flexibility empowered by the multiple skills of workers and the mobility of equipment to construct different seru to produce different product types. Thus, SPSs possess the capability to scale-up and scale-down very quickly and effectively. Nowadays, there are three main types of seru, namely divisional seru, rotating seru, and yatai.

However, in the existing SPSs literature, seru formations are usually assumed to be pre-formed before seru scheduling. Seru formation problems aim to determine the number of workers and the set of worker skills required to form different seru to produce different product types. Without seru formations, seru scheduling problems can only optimize the assignment of orders-to- seru, and the sequencing of the assigned orders in each seru. Thus, the performance of the SPSs is limited because no new seru can be formed during the seru scheduling to support the needs. Moreover, the pre-formed seru are usually assumed fixed during the whole production horizon (incapable of dynamically changing in response to the orders). Thus, this further limits the responsiveness.

To overcome the existing shortcomings/research gaps, this proposed project aims to integrate seru formation problems with seru scheduling problems to further maximize the efficiency and responsiveness of the SPSs. We name this new integrated approach Seru -FS. However, this new integrated problem is under-explored in the literature. As it is expected that because of the huge problem complexity in this new integrated problem, the computational time for the proposed exact algorithms may still not be efficient enough to tackle practical problems, thus, we also propose a new Genetic Algorithms based algorithm, named “Portfolio Dual-core Genetic Algorithm” (PD-GA) with novel boundary strategies to restrict randomness in evolution. This new breakthrough not only theoretically contributes to seru literature (especially to seru formation and seru scheduling), but also generates new insights into the SPSs operations and worker skill training management. Our findings will be essential to support electronics manufacturers to respond to the rapid market changes and retain high production efficiency. Besides, our work may extend to benefit other manufacturing industries, and materialized to become teaching materials for teaching in undergraduate courses in our university.

Project Reference No.: UGC/FDS15/H05/24
Project Title: Pakistani Entrepreneurship and its Socio-cultural Correlates: A Mixed-Method Study in Hong Kong
Principal Investigator: Dr MAN Pui-kwan (Shue Yan)

Abstract

Ethnic minority entrepreneurship has garnered significant attention from both academics and practitioners as a means to improve the economic status and upward socio-economic mobility of underprivileged groups. However, existing scholarship on South Asian entrepreneurship often treats this group as homogeneous, overlooking the specific experiences of Pakistanis. Compared to Indians and Nepalese, Pakistanis are recognized as an underprivileged group in terms of socio-economic status and employment opportunities. Moreover, most studies on South Asian entrepreneurship in Hong Kong have been qualitative in nature, providing fragmented evidence on the challenges faced by entrepreneurs. A comprehensive theoretical framework that explains the factors influencing business initiation, discrimination experiences, social capital, and living conditions of Pakistanis is lacking. This study aims to address these research gaps by investigating Pakistani entrepreneurship and its socio-cultural correlates in Hong Kong through a mixed-methods research design.

Since the 1980s, researchers have developed theories to explore factors influencing the development of ethnic businesses, including discrimination, social capital, and ethnic enclave economies. In this proposed study, these theories will be incorporated for analytical purposes. The research design will adopt a mixed-methods approach, combining qualitative focus group interviews and quantitative survey questionnaires. Qualitative data from the focus group interviews will provide rich contextual information on entrepreneurs’ difficulties and coping strategies, while the quantitative data will facilitate a deeper understanding of socio-cultural factors related to the establishment of Pakistani enterprises. Six focus groups, comprising a total of 30 Pakistani entrepreneurs, will be conducted to generate insights into business initiation and the mobilization of social and cultural resources available to Pakistanis. Subsequently, quantitative data will be collected from a structured survey involving 150 ethnic entrepreneurs. The survey questions will cover areas such as social capital, life experiences, perceived discrimination, and demographic characteristics. This mixed-methods approach will ensure a balance between the breadth and depth of the collected information.

In addition to making academic contributions by testing relevant theories and utilizing a mixed-methods approach that reflects the real situation, this study will have practical implications for NGOs serving ethnic minorities. The findings can help create social bonds and facilitate collaboration among Pakistani entrepreneurs, thereby assisting them in sustaining their businesses and improving their quality of life. Additionally, the research findings will highlight the obstacles that Pakistanis may encounter along their path to success. This study can serve as a valuable baseline for future comparisons between the Pakistani community and other successful ethnic communities, allowing for a deeper understanding of the factors that contribute to their achievements.

Project Reference No.: UGC/FDS16/M08/24
Project Title: The abuses of antibiotics in ornamental fishkeeping and its role in the transmission of antibiotic resistance in indoor environment
Principal Investigator: Dr MO Wing-yin (HKMU)

Abstract

The emergence of antibiotic resistance is one of the most significant environmental and public health issues. Currently, the primary focus of monitoring efforts and legislation by authorities worldwide is on the food production sector, as it is believed that the transmission of antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs) via food is a major route by which antibiotic resistance affects public health. However, the abuse of antibiotics in the ornamental fish industry has been largely ignored, even though antibiotics are often used during farming, transportation and in retail stores, to reduce fish mortality and subsequent economic loss. While the presence of ARB and ARGs in ornamental fish has been widely reported globally, the exact risks of antibiotic resistance in ornamental fish and its transmission to humans have seldom been explored. It is because people generally believe that the health risk to the general public is minimal as long as the ornamental fish are not consumed and there is no direct contact with the tank water. Previous research suggests that antibiotics intended for human use are also found in ornamental fish. As fishkeeping is a widespread hobby and fish are the third most common type of pet globally, ornamental fish cultivation and keeping may be an important, but overlooked, transmission route of antibiotic resistance. An air pump is an essential equipment in a fish tank to supply oxygen to the fish, but it may cause zoonotic bacteria present in tank water to become airborne during aeration and then persist in indoor aerosols. Aerosols containing pathogens are known as bioaerosols, and they can pose risks to occupants of indoor spaces and workers in ornamental fish industry, facilitate horizontal gene transfer between bacteria, and make other bacteria more resistant to antibiotics. Recent advances in aerosol research have suggested that humans are susceptible to the impact of bioaerosols, as we spend more time indoors. Fish feed pellets are frequently fed to ornamental fish. However, piscivorous (fish-eating) ornamental fish are also popular pets, and they are often fed other smaller ornamental fish that may have already been tainted with antibiotic residues or ARB. Piscivorous ornamental fish may accumulate more antibiotics and expose to more ARB and ARGs through their diets than other non-piscivorous ornamental fish.

The aims of this project are to (i) study the degree of antibiotic contamination of ornamental fish, in terms of antibiotic residues in piscivorous and non-piscivorous ornamental fish, (ii) determine the antibiotic resistance profile of associated bacteria, (iii) elucidate the risks of bioaerosols generated from ornamental fish keeping to occupants in indoor environment and workers in ornamental fish industry, and (iv) explore appropriate risk reduction methods. To achieve these aims, this project will comprise two parts. Part 1 will include a survey of the antibiotics application history used in four popular pet fish, including goldfish, koi carp, redtail catfish and iridescent shark, which are available from the retail shops in Hong Kong and direct exporters. These are common pets worldwide with different dietary preferences, and goldfish is also a common food for iridescent sharks and redtail catfish. Zoonotic bacteria isolated from these fish species will also be determined, and their resistance to selected antibiotics and the presence of ARGs will be investigated. In Part 2, a series of controlled fish tank experiments with the four target fish species will be set up to study changes in indoor bioaerosols due to aeration of fishkeeping and the changes of microbial composition and ARG quantity in fish, tank water and indoor air over time. Human health risk for inhalation and dermal contact with bioaerosols will be assessed, and mitigation measures will also be explored to reduce the risks. The results generated from this project will raise concerns among the aquarist communities, general public, ornamental fish industry as well as authorities worldwide, about the risks associated with use of antibiotics in ornamental fish to human health. Further, the findings will provide the scientific basis for policy updates to regulate the use of antibiotics in different stages of the supply chain of ornamental fish. The findings of this study will also be conveyed in teaching materials and public seminars.

Project Reference No.: UGC/FDS15/H24/24
Project Title: Lingnan Writing and the Reminiscence of Song Dynasty Culture: A Study of the Late Qing Poet Jiang Fengchen's Literary Works
Principal Investigator: Dr NG Chi-lim (Shue Yan)

Abstract

The late Qing dynasty is marked by a series of crises that necessitated national salvation and reforms. While most scholarly focus on this period revolves around the responses of intellectuals known throughout the state, there is relatively less attention paid to classical literary works written during this time, particularly poetry and prose from local regions. This project aims to address this gap by conducting a case study on Jiang Fengchen 江逢辰 (1859–1900), a renowned poet, lyricist, and painter born in Huizhou, Guangdong. In 1892, Jiang passed the imperial examination and briefly held an official position in the Ministry of Revenue in Shanxi. Despite his brief tenure as an official, he spent most of his life in his hometown, often considered part of the Lingnan region. Through the study of Jiang’s poems, this project seeks to examine how a local literati shapes and contributes to the cultural landscape of a specific area.

This project aims to contribute in the following three aspects. Firstly, it seeks to demonstrate how Jiang’s work contributes to the creation of a sense of place. By looking at a series of poems about local landmarks, the project aims to examine how Jiang’s discursive expressions contribute to the establishment of a local identity by creating sites imbued with cultural memory. Jiang used multiple imageries to conceptualize each of these sites. Under Jiang’s formulation, the landmarks were no longer scenic spots but sites laden with symbolic meaning that needed to be decoded with respect to social context. Another rhetorical device Jiang employed is writing about the sites visited by the renowned 11th-century literary figure Su Shi 蘇軾 (1037–1101). By drawing attention to this region’s unique cultural heritage, Jiang’s writings on these landmarks create a concrete sense of local identity.

Jiang not only pays homage to Su Shi by visiting the sites Su Shi frequented but also endeavors to emulate Su’s poetic style, composing verses in harmony with Su Shi’s works. This intertextuality warrants closer scrutiny as it sheds light on how Su Shi’s influence resonated among late Qing poets. Traditionally, literary histories have often focused on the Tong-Guang School poets, a group of writers dedicated to blending the beauty of traditional poetic imagination with scholarly learning. Jiang’s poems provide an alternative perspective for understanding late Qing poetry, particularly the prominence of Song poetry in Lingnan. Through the case study of Jiang’s poems, this project aims to recognize the intricate cultural factors contributing to regional poetic trends.

Lastly, Jiang’s poems frequently express admiration for the lifestyle of the Song literati, encompassing an appreciation for paintings, calligraphy, and art. This specific reminiscence of the culture in the Song dynasty is not only a sentiment expressed by him but also a common trend among a group of poets and scholars who interacted with Jiang. Through an investigation of Jiang’s extensive social network, this project aims to examine how the artistic community of poets was reminiscent of the Song dynasty. This project will demonstrate that their collective nostalgia for the Song is a response to the sociopolitical changes of the time.

A case study of Jiang Fengchen is long overdue, with his poetry collection, Jiang Xiaotong yiji, remaining unpublished since its initial release in the 19the century, resulting in a lack of related research to date. To address this gap, the PI is currently engaged in editing and publishing the collection, utilizing the original copy held by the Institute of Oriental Culture at the University of Tokyo. Jiang Xiaotong yiji embodies Lingnan culture, regional characteristics, and historical significance in late Qing China. The project’s findings, to be published in peer-reviewed journals, promise substantial contributions to the study of late Qing Lingnan literature, Chinese literary history, and the emergence of regional culture and identity. These contributions will prove beneficial for institutions teaching courses on literary history and Lingnan culture.

Project Reference No.: UGC/FDS14/P01/24
Project Title: Multiple Change-point Detection in Spatio-temporal Gaussian Random Fields under Spatial Fixed-domain and Mixed-domain Asymptotic Frameworks
Principal Investigator: Dr NG Wai-leong (HSUHK)

Abstract

With the rapid advancement of technologies for data collection, large spatial data over a region observed sequentially over long periods of time are becoming increasingly available. To analyze such spatio-temporal data, stationary models are often inadequate to describe the non-stationary behavior along the time dimension that occurred in such data. Instead of developing more complex models, it is more effective to incorporate change-point models which segment a nonstationary spatio-temporal data into several approximate stationary segments which can be analyzed using stationary models. Due to its effectiveness in modeling non-stationary data, change-point analysis in spatio-temporal data has received considerable attention in various fields such as climate science, financial econometric, genetics, environmetrics, astronomy and engineering in recent decades.

Although detection of structural breaks along the time dimension occurred in the spatio-temporal data is important for modeling the general structure of the data, change-point analysis in spatio-temporal data remains largely unexplored with only a handful of existing methods in the literature. The major difficulty of change-point analysis for spatio-temporal data stems from both theoretical and computational challenges of spatio-temporal modeling under the increase in dimensions of both space and time with the presence of unknown change-points. In spatial statistics, there are mainly three asymptotic frameworks, namely the increasing-domain asymptotics, the fixed-domain asymptotics and the mixed-domain asymptotics. The choice of asymptotic frameworks plays a crucial role in establishing theoretical properties of the statistical methodology. However, change-point analysis in spatio-temporal data in existing literature mainly focused on the increasing-domain asymptotics. In this proposal, we will investigate and establish theoretical properties of the proposed methodology under the fixed-domain asymptotics and the mixed-domain asymptotics. For overcoming the computational challenges due to the large amounts of correlated data, covariance tapering technique and truncated likelihood functions can be adopted to alleviate the computational difficulty of full likelihood for spatio-temporal data, and hence an approximate likelihood ratio scan statistics can be developed to quickly detect a set of potential change-points. A modified minimum description length information criterion will be developed for efficient change-point model selection. Extensive simulation results and real data examples will also be conducted to illustrate its finite sample performance. In this proposal, we plan to proceed as follows.

1. (Applying Covariance Tapering Technique and Truncated Likelihood Functions for Developing Likelihood Ratio Scan Statistics) An approximate likelihood ratio scan statistics for quick scanning for potential change-points along the time dimension will be developed. Covariance tapering technique and truncated likelihood functions can be applied to approximate the full likelihood for reducing the computational burden. 2. (Modified Minimum Description Length Information Criterion for Change-point Model Selection) A modified minimum description length information criterion for change-point model selection will be developed for estimation of the number and locations of the change-points in the spatio-temporal processes under the fixed-domain asymptotic and mixed-domain asymptotic frameworks. 3. (Fixed-domain Asymptotic and Mixed-domain Asymptotic Inference for the Change-point Estimation) The asymptotic properties of the proposed method are investigated and established under both fixed-domain asymptotic and mixed-domain asymptotic frameworks. Extensive simulation results and real data examples will also be conducted to illustrate its finite sample performance.

Project Reference No.: UGC/FDS16/H11/24
Project Title: Reporting on environmental protests in Vietnam: Critical Journalism in an Authoritarian One-Party Regime
Principal Investigator: Dr ORTMANN Stephan (HKMU)

Abstract

The research project seeks to understand how and why journalists report environmental protests in Vietnam, an authoritarian one-party state. The country has experienced a growing number of incidents in which residents have used disruptive methods to draw attention to environmental pollution in their neighborhood. Many of these incidents have been reported in the state-owned media and are described in a relatively objective manner. The government has treated the protests relatively leniently even if there was occasional repression. As they report on incidents of “rightful resistance”, such protests appear to not only be tolerated but even encouraged. Media reports are likely to encourage others to seek a similar recourse elsewhere. Meanwhile, at the same time there are, however, also protests that are censored from the press and those receive a much harsher repression. The reason is generally that those protests have grown into larger movements and thus pose a possible challenge to the regime. For journalists, it may be a difficult choice to report on some forms of resistance against pollution incidents while not on others. Similarly, the potential of reports in the media to encourage further activism may not be without risks for an authoritarian regime. To understand why protests are reported in the media and when they are censored is the goal of this project. It employs a qualitative methodology to seek a deep understanding of the motivations, opportunities, and limitations of journalism in a country which ranks at the bottom of global media freedom. The study will build and expand a database of reports on environmental protests – from 2020 until the present. After capturing the breadth of different protests, which can be categorized in different ways including in regard to the tactics of protesters, the target of the protests, and the location of the protest, to name a few. The database currently contains 417 articles from 2014 to 2019. The project will also involve conducting 20-30 interviews with journalists, editors, and specialists to gain insight into how Vietnamese media handles contentious political issues. The data will be analyzed using interpretive content analysis, with a focus on understanding the media's role in environmental contention and how perceptions of protests shift over time. The research will also seek to understand the underlying assumptions and biases in protest reporting.

Project Reference No.: UGC/FDS14/E04/24
Project Title: Dynamic Models of Salesforce Compensations
Principal Investigator: Dr SIU Chi-chung (HSUHK)

Abstract

Salesforce compensation plays a crucial role in motivating salespeople and driving sales. It comprises a combination of fixed regular remuneration, such as salary, and incentive payments that are tied to sales performance. Companies invest a significant amount of money in compensating their sales teams, and it is essential to understand how to design compensation plans that effectively incentivize high sales performance.

Existing empirical studies have identified several key elements that are effective in incentivizing salespeople, while the agency approach proves to be promising in designing optimal salesforce compensation schemes that incorporate various incentivizing features. However, the existing principal-agent approach typically focuses on either a static period or multi-period with binary efforts, which limits the scope of the analysis of the sales agent’s incentive adjustments towards changes in market conditions over time.

To address this limitation and advance the agency theory of salesforce compensation, this proposal aims to develop a framework for optimizing salesforce compensation in continuous time. By adopting a continuous-time approach, we can capture the dynamic nature of the market and account for the ever-changing conditions that influence salesperson behavior and sales performance.

In this research, we will investigate factors such as contract duration, risk aversion, carryover effect, moral hazard, and the inclusion of intermediate compensation in salesforce compensation plans. By studying these factors, we can uncover insights into how they shape salesperson behavior and performance over time, allowing for more effective design of compensation plans that align with market dynamics.

Moreover, this research proposal aims to provide practical recommendations for managers in designing effective salesforce compensation plans. By advancing the agency theory of salesforce compensation in continuous time, we can provide managers with valuable insights and strategies to optimize their compensation plans, align them with market dynamics, and drive sales team performance and business growth.

Project Reference No.: UGC/FDS11/E06/24
Project Title: Image Generative Model breaking away from Denoising in Diffusion-Like Environment
Principal Investigator: Prof SIU Wan-chi (SFU)

Abstract

Generative AI with deep learning has many useful applications, such as image super-resolution, image inpainting, image/video compression, data augmentation, virtual reality. etc. Recently, diffusion models have been considered as the most effective way to make image generation, for which noise is a means to bring and form the required statistical distributions to generate photo-realistic images. This research proposes a new domain transfer approach to break away from the requirement of using explicit noise operations for image super-resolution; hence no noise operation is required which can speed up the realization speed for over 100 times. It is also expected that this new Domain Transfer in Latent Space (DTLS) approach not only can perform high-quality image super-resolution, but can also be used to create an efficient image generative model, for various hi-tech applications.

Let us summarize the objectives of this Research work as follows.

1. To investigate the structure(s) of using domain transfer under diffusion‐like model without denoising for image super‐resolution: this involves finding the number of optimal steps for super‐resolution, the structure of the U‐Net or to have a new DNN design etc.

2. To improve the above structure to produce photo‐realistic image by conditioning the domain transfer with reference to the input LR image: this can have many possible designs, and much investigation is expected.

3. To convert the above super‐resolution approach into a generative model: this can be done by adding a GAN network in front of the LR image set, and GAN is used to produce LR image data set with consistent statistical distribution and subsequently be used to train the transfer domain super‐resolution module.

4. To make further quality improvement: this is to make further analysis of the GAN or StyleGAN for item 3 and to see the possibility of designing even a more efficient circuit to do the statistical matching, and try to use large image sizes for quality demonstrations.

5. To provide application examples for this new approach for image generation: this part is to give initial investigation to show that this genuine approach can be used for various applications, such as inpainting, image manipulations (aging, smiling, pose) and picture painting. However, this is not the major investigation of this proposal.

Project Reference No.: UGC/FDS24/H25/24
Project Title: Discovering Optimal Prompting Methodologies for Large Language Models via An AI Prompting Expert System with An Application on Computing Education
Principal Investigator: Dr SO Chi-chiu (PolyU SPEED)

Abstract

In the national 14th Five-year plan announced in 2021, Hong Kong has been supported to develop an “International Innovation and Technology (I&T) Hub”, based on which, Hong Kong government put forward a “Hong Kong Innovation and Technology Development Blueprint” in 2022 to outline several new directions.

The first direction is to enhance the I&T ecosystem and promote “new industrialization” in Hong Kong. One key strategy is to enhance the transformation of traditional manufacturing sector to smart production with the utilization of I&T. The second direction is to strengthen the I&T talent pool to create strong momentum for growth. The blueprint targets more than 35% of UGC-funded students to study in STEM-related programs in the coming 5 years. The third direction is to promote the development of a digital economy and develop Hong Kong into a smart city. According to the “Hong Kong Smart City Blueprint 2.0” launched by government in 2020, smart city is composed of “Smart Mobility”, “Smart Living”, “Smart Environment”, “Smart People”, “Smart Government” and “Smart Economy”.

About one year ago, a large language model (LLM), ChatGPT, was invented. It possesses a very strong ability to understand human languages. LLMs receive a text input which we call a prompt, transform it to an array of tokens, compute the tokens for response, and transform those computed tokens back to a text output. LLMs are found to have satisfying performance in a lot of applications and can be a strong catalyst to technological and economic development, but their capability to understand complex textual information remains questionable. This observation draws us to ask that by analyzing prompts and their interactions with ChatGPT, can we derive methodologies for better prompts to understand complex texts? Can we propose an objective framework to guide how prompts should be set to achieve optimal performance and applicable to other LLMs? Discovering the optimal prompting methodologies help all industries to leverage LLMs to realize “new industrialization” and make Hong Kong smart.

“Smart People” not only includes people who use smart technology, but also people who know how to implement smart technology to facilitate “Smart Economy” and “Smart Government” etc. In a smart city, knowing how to make use of LLMs becomes a basic skill in education computing. In computing education, students should first learn programming, but grading programming exercises is very time-consuming, especially when teachers need to give explanations on incorrect codes. Automation of such a grading process is of urgent need.

With these motivations, we will develop a framework of AI Prompting Expert System for prompt engineering for ChatGPT, with computing education as an application. The project is separated into five tasks: 1) Data collection of programming exercises and answers from real programming classes; 2) Metamorphic Transformation of collected data via common programming mistakes to strengthen the dataset; 3) Analysis and Optimization of prompt patterns with the principle of Differential Prompting; 4) Construction of an AI Prompting Expert System to consolidate our optimization findings; 5) Evaluation and control experiments for feedback analysis and refinement. Our framework of an AI Prompting Expert System is objective and explainable, which is an important property for reliability. Our AI Prompting Expert System can greatly relieve the burden of LLM users, making LLMs more easily and conveniently used by all stakeholders in the society, to facilitate Hong Kong as an international I&T hub. Although we use computing education as an application, our methodology is applicable to other LLMs and fields as well.

Project Reference No.: UGC/FDS16/M17/24
Project Title: Effectiveness of group-based nonviolent communication interventions for improving mental well-being in parents: a randomised controlled trial
Principal Investigator: Dr SUN Yuying (HKMU)

Abstract

Background: Nonviolent communication (NVC) is a way of life that helps cultivate compassion and empathy and improve the quality of relationships. We have conducted a pilot randomised controlled trial (RCT) of NVC interventions first registered in May 2022 on 44 parents in Hong Kong, which showed feasibility and a medium effect size on improving mental well-being and NVC skills, and a small effect size on reducing parental stress.

Objectives: To conduct a definitive RCT on the effectiveness of blended mode NVC interventions for improving mental well-being in parents who have children in primary schools and with mild to moderate depression or anxiety symptoms.

Hypothesis: Our intervention group will show more improvements in parents’ mental well-being and NVC skills, decreases in stress, depression and anxiety symptoms, child emotional and behavioural problems than the control group.

Design and subjects: An RCT (1:1 allocation ratio) on 172 parents. Eligibility will be assessed by Patient Health Questionnaire (PHQ)-9 and Generalized Anxiety Disorder (GAD)-7.

Instruments: Short Warwick-Edinburgh Mental Well-being Scale; self-developed scale of NVC skills; Parental Stress Scale; PHQ-9; GAD-7; Strengths and Difficulties Questionnaire.

Interventions: NVC professionals will train 5-10 social workers through two half-day train-the-trainer workshops. Six 1.5-hour weekly group sessions (blended mode: the first and last session face-to-face and the remaining sessions online) will be delivered by the trained social workers to the intervention group, including (1) an introduction to four principles of NVC; communication that blocks compassion; and distinguishing observations from evaluations; (2) identifying and expressing feelings; words that can be used to express feelings; (3) taking responsibility for feelings and needs; distinguishing between external events and the needs underlying feelings; (4) using positive action language when making requests; (5) sharing experiences and practices, and (6) review and summary. Group discussions and games will be used to increase and sustain participant engagement. After completing all assessments, the waitlist control group will have similar training sessions.

Outcome measures: Outcome variables will be measured at baseline (T1), immediately after the intervention (T2) and three months after the intervention (T3). The primary outcomes are mental well-being and NVC skills at T2. Secondary outcomes include mental well-being and NVC skills at T3, parental stress, depression and anxiety symptoms, child emotional and behavioural problems at T2 and T3. Process evaluation will be conducted for the interventions. In-depth interviews will be conducted within three weeks after T3 on 20 parents in the intervention group to explore participants’ perspectives.

Data analysis: Intention-to-treat approach. After adjusting for baseline outcome variables and demographics, a multilevel mixed model will be used to compare between-group mean differences in the outcomes of the two groups. Per-protocol analysis will include the adherent participants who complete at least four sessions. A cost analysis will be conducted. The content analysis method will be used to analyse the qualitative data. This proposal follows CONSORT-EHEALTH and will be registered to update the pilot trial.

Project Reference No.: UGC/FDS11/H07/24
Project Title: Motives for constructing a pro-environmental identity: a mixed methods sequential exploratory investigation
Principal Investigator: Dr SZETO Stephanie So-suet (SFU)

Abstract

Pro-environmental identity plays a pivotal role in influencing pro-environmental behaviour (PEB). Understanding motives for constructing a pro-environmental identity could help understand PEB. Previous research has identified motives, including self-esteem, efficacy, continuity, distinctiveness, meaning, belonging, morality and frugality, influencing cognitive evaluation of centrality within identity and enactment of identity.

However, the underlying motives driving the pro-environmental aspect of identity construction remain under-explored.

This research proposal aims to investigate the eight identity motives driving pro-environmental identity construction and its impact on PEB. A mixed methods sequential exploratory design will be employed, integrating qualitative and quantitative approaches to answer four research questions (RQs) in two major phases. In Study 1, in-depth interviews with 20 environmentalists from environmental organizations will be conducted, with Interpretative Phenomenological Analysis (IPA) to explore how identity motives might influence the construction of pro-environmental identity (RQ1) and whether additional identity motives contribute to this process (RQ2).

The findings from Study 1 will inform the subsequent cross-sectional studies, Studies 2a, 2b, and 2c, in which will recruit 200 participants each from environmental organisations, university students, and community samples, respectively. Online surveys will be employed to measure the extent that identity motives influence individuals’ perceptions of the centrality of pro-environmental aspect with identity and intention to enact this aspect. Correlation and regression analysis will be used to examine the relationships between these identity motives and to perceived centrality of their pro-environmental identity and PEB among environmentalists (RQ3) and across different samples (RQ4).

This research project will contribute to the literature on environmental psychology by elucidating the linkage between identity motives PEB, thereby promoting the understanding of the motivational forces underlying pro-environmental identity across worldwide researchers. Moreover, the insights gained from this research project hold implications for educational initiatives for fostering sustainable behaviours and informing environmental policies and interventions.

Project Reference No.: UGC/FDS24/H07/24
Project Title: Fostering Student Feedback Literacy Through A Technology-Mediated Multimodal Platform: A Teacher-Student Collaborative Approach
Principal Investigator: Dr TAM Choi-fung (PolyU SPEED)

Abstract

A significant number of undergraduate students consistently demonstrate below-average performance in disciplinary L2 writing. Student feedback literacy, which encompasses the abilities to appreciate feedback, make judgments, manage affect, and take action (Carless & Boud, 2018), has emerged as a significant factor influencing academic writing in higher education (Zhou, Yu, Liu & Jiang, 2022). Due to the growing prevalence of online learning and time constraints in classes, technology-mediated multimodal platforms can facilitate teacher-student conferences at any time and location. However, platforms like Zoom, Blackboard and Google Meet often adopt a standardized approach that may not adequately address the diverse needs of students in fostering feedback literacy.

This pioneer project aims to develop a technology-mediated multimodal platform, addressing contextual constraints, and bridging gaps in feedback modes. The ultimate goal is to foster student feedback literacy through the utilization of this platform. The project will modify an existing subscribed Microsoft Teams platform and develop a mobile application. The enhancements will include features that support text, audio, and video uploads, appointment and rating functions, as well as a progress-tracking portfolio. Undergraduate students specializing in Information Systems and Web Technologies will develop the student-centered multimodal platform under the research team’s guidance.

The team’s investigation will focus on assessing the impact of the platform on student feedback literacy, as well as evaluating its effectiveness and the factors that influence its usage. The anticipated findings of this study hold the potential for significant contributions in both theory advancement and practical applications for various stakeholders.

The study’s findings will significantly advance our understanding of student feedback literacy in the context of technology. By investigating the relationship between student feedback literacy and the platform under study, valuable insights will be gained on how technology can impact and enhance feedback literacy. These findings contribute to theory advancement, shedding light on the dynamics and implications of technology-mediated feedback. Moreover, the study expands our theoretical understanding of how technology influences feedback practices, student engagement, and learning outcomes. Overall, the research outcomes have implications for education research, impacting areas such as student writing, teaching, curriculum design, educational policy planning, and technological advancements.

Practically, the research outcomes will inform future educational practices and policies, fostering sustainable improvements across diverse domains and levels of education. Educators can enhance their teaching methodologies and strategies by leveraging the platform to improve student feedback literacy. Curriculum designers can integrate effective feedback practices into educational programs, promoting student engagement and learning outcomes. Policymakers can support the implementation of technology-mediated platforms for feedback literacy, facilitating educational advancements at a systemic level.

Additionally, the study’s practical implications extend to technological advancements in education. It will identify the strengths and limitations of the investigated platform, driving further improvements in its design and functionality. This will enhance the user experience and ensure the practical utilization of the platform in various educational contexts, locally and globally.

Project Reference No.: UGC/FDS14/H07/24
Project Title: Diversity and Innovation: A Close Reading of Yuan Zhen's Ancient Music Bureau Poetry
Principal Investigator: Dr TAN Mei-ah (HSUHK)

Abstract

This project analyzes Yuan Zhen’s (779–831) Ancient Music Bureau poems and identifies their innovations. The scholarly world generally treats these poems as New Music Bureau poems, but the two groups of poems differ significantly in content and style. This research demonstrates the important distinguishing characteristics of Yuan’s Ancient Music Bureau poems, explores their similarities with and differences from those of his precursors and contemporaries, and compares the relative strengths and weaknesses of close reading and contextual analysis for purposes of literary appreciation of poetry. In so doing, it provides a lens through which to examine the nature and development of the genre during the mid-Tang period.

Project Reference No.: UGC/FDS16/M11/24
Project Title: Effects of altered N:P ratios and elevated temperatures on the abundance, community composition, trophic mode, and trophic transfer of elements of marine mixoplankton
Principal Investigator: Dr TANG Chi-hung (HKMU)

Abstract

Environmental changes associated with human activities have impacted many aspects of the aquatic ecosystems, particularly the coastal regions where human activities are concentrated. These changes include increases in nutrient loadings into the water that perturbate the molar ratio between nitrogen (N) and phosphorus (P) and elevation in seawater temperature due to global warming. These two challenges are likely to affect most marine organisms. Mixoplankton, microscopic organisms that are capable of autotrophic and heterotrophic nutrition modes simultaneously, are ubiquitous in the oceans. They are believed to be the dominant functional group of harmful algal species in eutrophic waters. Despite their importance, mixoplankton’s response to the altered N:P ratios and elevated seawater temperatures has not been fully understood. The overall aim of this proposed project is to examine the abundance, taxonomic composition, trophic mode, and trophic transfer with mixoplankton in the basic food chain in response to altered N:P ratios and increased water temperatures. Detecting mixoplankton in action in the natural environment may pose a challenge. Therefore, a combination of flow cytometry and acidotropic probes targeting food vacuoles will be used to detect mixoplankton in the planktonic community. This proposal is the first of its kind to verify and optimize the detection method on laboratory cultures and field-collected samples in local waters. To investigate the effects of altered N:P ratios and elevated temperatures on mixoplankton, microcosm experiments will be conducted to simulate scenarios of various N:P ratios and water temperatures with natural whole seawater. Using molecular tools (meta-barcoding and meta-transcriptomics) and microscopic observation, this proposed study pioneers the investigation of the abundance, community composition, and gene functioning related to the trophic modes of mixoplankton in the microcosms. These experiments are designed to test the prediction that mixoplankton will become more heterotrophic at increased temperature and altered nutrient balance. Furthermore, incubation experiments will be conducted to study the effects of the presence of mixotrophic prey on the trophic transfer of elements to copepods. The incubation experiments test the hypothesis that mixotrophy improves the trophic transfer of energy at the lower planktonic food chain. Overall, results from this proposed project will help establish a method to study mixoplankton in the natural environment. It will also contribute to filling in the knowledge gap regarding mixoplankton’s response to altered N:P ratios and increased water temperatures. It will provide insights into modelling the biogeochemical cycling of elements and energy flow with mixotrophy in the planktonic food web. It could bring about positive impacts to academia and society in both the short and long terms.

Project Reference No.: UGC/FDS16/H13/24
Project Title: China's Role and Social Power in the Middle East and North Africa (MENA)
Principal Investigator: Dr TRAN Emilie (HKMU)

Abstract

In recent years, China’s rapidly growing relationship with the Middle East and North Africa (MENA) has had significant geopolitical implications, particularly in the context of the rivalry between major powers such as the United States, China, the European Union, and Russia.

This FDS project, led by Hong Kong Metropolitan University’s Principal Investigator Dr Emilie Tran and France- and Qatar-based Co-Investigator Prof Yahia Zoubir, aims to extend their five-year transnational research collaboration. Since 2019, they have co-authored five publications on China’s relations with the MENA. Their previous work has shown how China has increased its engagement with MENA countries during the COVID-19 pandemic through health diplomacy. This project will further explore how the post-COVID rapprochement between China and the MENA presents both opportunities and challenges in diplomacy, security, business, and world outlook values.

The project will assess China’s policy in the MENA and answer the central research question: What do China-MENA relations in the 2020s involve? Focusing on China on one hand, and on the MENA on the other hand, the central research question is broken down into four lines of inquiry and corresponding research methods:

(1) What roles does China play or aim to play to the selected Arab countries? (2) How do Chinese businesspeople and professionals contribute to China-MENA relations? (3) How do MENA governments perceive and respond to China’s policies? (4) What impacts do the growing relations between China and MENA countries have on MENA businesspeople and professionals?

The project will use a qualitative approach, collecting data through desk-research of policy-related materials and building a repository of China’s collaborative projects in Saudi Arabia, the UAE, Qatar, Iran, Egypt, and Algeria.

Project Reference No.: UGC/FDS16/H34/24
Project Title: Study on the Relationship between Tonal Prosody and Lyricism of Ci Poetry: Focusing on Liǔ Yǒng, Zhōu Bāngyàn, Jiāng Kuí, Zhāng Yán
Principal Investigator: Dr TSANG Chi-chung (HKMU)

Abstract

Ci poetry is most closely related to music among different genres of classical Chinese literature. Ci poetry can be sung, and its musicality can help poets to convey their emotions. It was a pity that most of the music scores were lost since Southern Song Dynasty. Many Ci poets later on can only write Ci poetry with reference to the sentence patterns, four tonal categories, rhymes, etc. of the well-known ones from the Northern Song Dynasty to retain the music and emotions involved in the Ci poetry. Nevertheless, the linkage between music and lyricism becomes less strong even the poets can express emotions through rhetorical devices. The music score of which, however, has been lost. With no standard as reference, scholars thereafter tend to analyses Ci poetry from a literary perspective. It is believed that although the music scores were lost and the tune of Ci poetry can no longer be played, part of the emotion weaved in the tune of Ci poetry could retain through the tonal prosody, i.e. word count, sentence pattern, tonal categories, rhymes, etc. The prosodic characteristics can be used as the starting point to examine the interconnection of music, tonal prosody and lyricism. This project focuses on four Ci poets, namely Liǔ Yǒng, Zhōu Bāngyàn, Jiāng Kuí, Zhāng Yán. They were not only well-versed in music but also good at crafting their emotion with an elaborative writing style. Liǔ Yǒng and Zhōu Bāngyàn represents the style of ‘mellow’, and Jiāng Kuí and Zhāng Yán, represents the style of ‘elegance’ in the study of Ci poetry. This project will examine how they utilized the tonal prosody to inscribe different emotions in their works, and explore the connection between the emotion weaved in the tune of Ci poetry and the construction of literary style. As a result, the status and contributions of the four Ci poets in the studies of Ci poetry will be re-examined. This project will also conduct comparative studies between the works of the four Ci poets and others, so as to explore the features and structures of various tune of Ci poetry and Ci poetry as a genre. This is an interdisciplinary research project with literature study as main body, involving other subject areas such as musicology, linguistics, phonology, etc., The study of the relationship between tonal prosody and lyricism of Ci Poetry supplemented by quantitative statistics and big data in digital humanities also demonstrated its originality.

Project Reference No.: UGC/FDS25/P01/24
Project Title: Development of Intrinsically Safe Rechargeable Nickel-Zinc Batteries with Tunable Hydrogel Electrolyte-integrated Covalent Organic Frameworks
Principal Investigator: Dr TSANG Chi-wing (THEi)

Abstract

The Hong Kong Government is committed to achieving carbon neutrality by 2050 to address climate change urgently. Transitioning to renewable energy sources like wind and solar power is crucial for reducing Hong Kong's carbon footprint and reducing reliance on fossil fuels. However, reliable and resilient energy systems require large-scale electrochemical energy storage solutions to manage the intermittent nature of renewable energy generation. Currently, rechargeable lithium-ion batteries (LIBs) are preferred choice, owing to their high energy density, long cycle life and low maintenance. However, public concerns about the safety issue of LIBs, such as thermal runaway and fires caused by flammable non-aqueous electrolytes have arisen. Moreover, the use of strategic raw materials in LIBs such as lithium and cobalt leads to supply chain security issues. Although aqueous-based rechargeable lead-acid batteries (LABs) are considered safer, they may not meet the required capacity for high energy density, long cycle life and environmental standards. Thus, striking a balance between safety and performance remains a challenge for large-scale electrochemical energy storage solutions.

Recently, rechargeable nickel-zinc batteries (RNZBs) are gaining attention as a promising option for large-scale electrochemical energy storage systems, owing to their relatively high energy density (≥120 Wh‧kg^-1 ), high power density (≥1000 W‧kg^-1 ) and environmental friendliness. However, their development encounters significant technical challenges. Zinc dendrite growth and hydrogen evolution reaction (HER) during the charging and discharging process pose serious technical issues, resulting in shorter battery cycle life and electrolyte leakage. Specifically, zinc dendrites can be formed when zincate anions unevenly deposit on the anode surface due to non-uniform ion flux, with a preference for lateral facets over horizontal planes. The continuous growth of zinc dendrites can puncture the separator, leading to short circuit and cell failure. Moreover, aqueous RNZBs, which typically work in the charge-discharge window of 1.2-1.9V, can lead to serious hydrogen evolution reactions during operation. This poses risks such as battery casing rupture, electrolyte leakage, and even electrolyte dry-out.

To enable the commercialization of RNZBs for large-scale electrochemical energy storage, it is highly desirable to address technical challenges such as zinc dendrite growth and hydrogen gas evolution reaction. In this project, the PI proposes the use of tunable hydrogel electrolyte-integrated covalent organic frameworks (THEi-COF) as potential anode interface materials (AIMs) for addressing the technical challenges of zinc dendrite growth and HER in tandem. The hydrogel is designed with multiple functions: promoting even zincate flux, enhancing ionic conductivity and serving as an effective hydroxide anion transporter. The COF, on the other hand, acts as a selective channel for capturing zincate anions, preventing random diffusion, and reducing the wettability of the anode to minimize HER reactions. By introducing appropriate substituent groups on the COF, it can function as a zincate sequester, a guide for crystal facet engineering and promoter for internal gas recombination. These advancements are expected to greatly improve the stability and overall performance of RNZBs, particularly increase cycle life and prevent electrolyte leakage. To gain a deeper understanding of the mechanisms involved in mitigating zinc dendrite growth and HER, advanced in-situ/ex-situ characterization techniques will also be employed for fundamental studies, particularly charge-discharge mechanism, failure analysis and fading modes analysis and synergistic effects of THEi-COF. For instance, operando optical microscopy imaging will be utilized to effectively visualize zinc dendrite growth, while in-situ differential electrochemical-mass spectrometry (DEMS) will be used to quantify hydrogen gas evolution reaction. The primary objective of this project is to minimize the shape changes and side reaction of ZnO anode by establishing a stable interface between ZnO anode and the alkaline electrolyte. Ultimately, the goal is to develop a rechargeable Ni-Zn battery system that is both leakage- and maintenance-free, thereby advancing the path towards the RNZBs for large-scale electrochemical energy storage system.

Project Reference No.: UGC/FDS16/E19/24
Project Title: Topological Insulator Based Tunable Frequency Selective Surface
Principal Investigator: Prof VELLAISAMY Arul Lenus Roy (HKMU)

Abstract

Tunable Frequency Selective Surface (FSS) with a conformable structured surface can transform the development of terahertz electronic devices to unleash the immense potential of terahertz technology in environmental monitoring, security screening, sensing, healthcare and future 6G mobile communications domains. The conventional predefined periodic metallic or dielectric frequency selective surface structures suffer from limited operation bandwidth, fixed frequency response, poor sensitivity, incompatibility in integration with other devices or surfaces and most of all complex fabrication processes. This leads to the search for new FSS fabrication with simplicity and highly deployable nature to enable the current technology on structural and on-demand electronic compatibility for interfacing with devices or surfaces, which cannot be guaranteed by the conventional FSS technology. In this regard, we aim to design and develop a tunable and conformable FSS via the integrated effect of topological insulator nanocrystals [Bismuth Selenide Telluride (Bi2Se3-xTex, BST)] and carbon composite patterned surfaces. Topological insulator materials possess unique electronic band structures that is three-dimensional with narrow band-gap levels and responsive in the regions of microwave and terahertz which is reported in our recent publication. In this proposal, we use the photoelectronic properties of topological insulator Bismuth Selenide Telluride (Bi2Se3-xTex) nanocrystals to design FSS with variable selectivity by tuning Se/Te ratio. The proposed approach of tuning Se/Te ratio in Bi2Se3-xTex would influence the energy levels as well as the spin-orbital coupling (interlocking of spin state and charge state) which eventually maximises the interaction with incident electromagnetic waves. Therefore, tuning of Se/Te ratio is essential for the selective response effectiveness for the proposed FSS. Experimentally, following two steps will be explored for the construction of shape conformable and tunable terahertz FSS: (1) Fabrication of a conformable microstructured pyramidal surface with dielectric carbon as the base substrate by drop casting and pyrolysis process; (2) Distribution of topological insulator Bi2Se3-xTex (bismuth selenide telluride) nanocrystals with crystal size <10 nm on the patterned carbon substrate which would result in terahertz bandwidth shifting between 0.1 to 1.1 THz via optimisation. Our recent publication on FSS and preliminary simulation results have proven the feasibility with estimated selectivity ranging between 0.1 to 1.1 THz corresponding to Se/Te ratio in Bi2Se3-xTex on the FSS structural design. In this project, we challenge a tunable frequency range from 0.1 to 1.1 THz to facilitate the advancement of next generation terahertz electronic devices. We will take a systematic approach to investigate the material composition and structural characterization procedures for the proposed FSS. The key deliverables from our proposed work include: (1) Synthesis of Bi2Se3-xTex (BST) nanocrystals via microwave reactors and optimisation of BST nanocrystalline structure; (2) Fabrication of wafer scale (4 inch) pyramidal microstructured dielectric carbon FSS; and (3) Incorporation of Bi2Se3-xTex nanocrystals on the dielectric carbon substrate to create the novel heterostructured FSS with tunable response in the region of 0.1 to 1.1 THz. The novelty of this proposal is producing a conformable, tunable FSS film prepared under simple fabrication procedure that could provide high quality interfacing with devices and surfaces for practical applications at lower cost. Successful execution of this work will contribute to advancements in terahertz radiation beam manipulation. We strongly believe that the proposed deliverables would accelerate the terahertz technology on screening, sensing, healthcare, and communication products for Hong Kong and Greater Bay Region (GBR) which is a major technology hub with high population density.

Project Reference No.: UGC/FDS16/E23/24
Project Title: Sentiment Analysis of ChatGPT Generated Text and Human Generated Text for Detection of ChatGPT Generated Text
Principal Investigator: Prof WANG Fu-lee (HKMU)

Abstract

With the rapid development of large-scale generative language models, such as ChatGPT, their ability to generate text has also been greatly improved. Many people, even non-experts, can easily generate massive quantities of indistinguishable text using ChatGPT due to its powerful functionality and user-friendly interactions. However, the evolution of ChatGPT generated text technology has brought gains but also many pitfalls. The abuse of ChatGPT is prone to disinformation dissemination, fraudulent behavior, overdependence, and so forth. Malicious users can adopt ChatGPT to generate fake product reviews, fraudulent news, and other misinformation to manipulate public opinions or gain profits. Even false, the ChatGPT text generated unintentionally by normal users can cause information pollution due to the rapid speed of Internet. At the meantime, schoolchildren can use ChatGPT to complete their assignments, resulting in a lack of development of their individual abilities. It is difficult for human to distinguish directly whether a text is machine generated text or human generated one, since these generative language models are trained on vast amounts of corpus data. The generative language models are highly effective in simulating human text-generating habits, yielding fluid and even cohesive chunks of text.

Therefore, it is essential to detect and discriminate whether the generated text originates from ChatGPT-like generative language models. However, how to tackle this challenge is a complex issue. Generally, due to massive data pre-training and large-scale parameter learning, generative language models are able to produce coherent text while taking into account the structure and logic of the generated text. Traditional text-based binary categorization methods have difficulty in accurately distinguishing the source of such generated text owing to the superior performance of such generative language models as ChatGPT. Fortunately, the recent probability-based text detection methods achieve exceedingly strong performance, since they identify the source of generated text straight from the underlying logic of generating text by machine, which is that the generative models will follow certain paradigms to generate text, such as selecting the text with the highest probability value as the output. Nevertheless, this probability-based approach necessitates knowledge of the generative model’s probability function or other internal information. The fact that ChatGPT, as a black-box model, has no access to its internal information creates a technical barrier that prevents us from applying probability-based text detect methods in ChatGPT. Furthermore, in real-world circumstances, the probability-based method performs less stable and idealized.

In light of these considerations, this project aims to design a novel emotion-enhanced probability-based text detection model to improve stability and robustness through taking both semantic and emotional coherence into account. To this end, firstly, this project will design a simulator model to provide the internal information of black models by simulating their behaviour, which can unify the text detection methods for white and black box models. Secondly, this project will develop an emotional perturbation text generation model to provide technical support for the emotion-enhanced text detection model.

Finally, this project will combine the proposed methodology with practical applications to develop a fine-grained text detection method for human-ChatGPT collaboration systems. This project will have an impact on the detection of various generated text. Furthermore, it can efficiently assist in diminishing the misuse of generative models like ChatGPT and mitigating machine generated text floods, which leads to a long-lasting influence on education and industry.

Project Reference No.: UGC/FDS16/E03/24
Project Title: A Unified Multi-modal Framework for Open-vocabulary 3D Object Detection and Multi-object Tracking
Principal Investigator: Dr WANG Weiming (HKMU)

Abstract

3D object detection and tracking aim to accurately localize and classify objects in unfamiliar environments, which facilitates 3D perception and understanding. For example, in autonomous driving systems, precise navigation and decision making heavily rely on the ability of the vehicle to correctly detect and recognize surrounding objects. In addition, with the growing demands of various real-world applications, such as unmanned aerial vehicles, robotics and augmented/virtual reality, there is an increasing need to develop robust 3D object detection and tracking methods to enable the smooth and safe operation of these applications.

Although a lot of promising algorithms have been proposed for detecting and tracking 3D objects in outdoor environments, there are still many challenging issues that degrade the performance of these algorithms in practical applications. For example, most 3D object detectors rely on mass labeled data to boost the model accuracy. However, it is time-consuming and labor-intensive to collect and annotate enough data for model training, particularly in 3D scenarios. In addition, one notable issue in existing cross-modal datasets for 3D object detection and tracking is the lack of labeled data for infrequent objects (long-tail setting), resulting in low detection accuracy when attempting to detect unusual objects. Moreover, these methods usually experience performance degradation when confronted with unseen objects because they are typically trained with a pre-defined set of categories and cannot adapt effectively to novel objects that are not present in the training data (open-vocabulary setting). Furthermore, the accuracy of numerous 3D object detectors is notably impacted when deployed in adverse weather, despite their satisfactory performance in normal weather, due to the substantial domain shift between the data captured in diverse weather conditions. Last but not least, 3D multi-object tracking (MOT) is also a challenging task because of false and missing trajectories that often arise in one or more modalities. Besides, complementary information from different modalities has not been fully exploited to promote multi-modal 3D MOT.

In this project, we shall conduct comprehensive research work to tackle the above challenges. First, to mitigate the shortage of labeled data in existing cross-modal datasets for network training, we shall develop a multi-modal data generator based on neural radiance fields (NeRF) and diffusion models, which can synthesize realistic scene-level data to alleviate the domain gap between synthetic and real data. Second, to enhance the ability of multi-modal representation learning, we shall combine autoencoders and contrastive learning into a unified framework to effectively extract both local and global features from point clouds for 3D understanding. Moreover, visual prompt tuning is exploited to fine-tune pre-trained models by introducing a small set of task-specific learnable parameters. Third, to increase the accuracy of open-vocabulary 3D object detection, we shall propose a deep cross-modal fusion network by comprehensively integrating multi-modal information at both feature and detection levels. Particularly, textual information is utilized to detect and identify unknown objects. Fourth, to improve the performance of 3D object detection in adverse weather, we shall propose a multi-modal semi-supervised learning network to improve the model generalizability based on the teacher-student model. Fifth, to improve the robustness of multi-modal 3D MOT, we shall propose a coarse-to-fine framework to generate and refine object trajectories progressively by fully exploiting complementary information from 2D images and 3D point clouds.

The deliverables of this project are a series of advanced deep learning algorithms to facilitate open-vocabulary 3D object detection and multi-object tracking, as well as novel networks for multi-modal data generation and representation learning. Moreover, we shall conduct extensive experiments to evaluate the performance of the proposed networks.

Project Reference No.: UGC/FDS15/H14/24
Project Title: Virtual Reality Based Cognitive Behavioral Therapy for Social Anxiety-Driven Depression among Youths: A Randomized Controlled Trial
Principal Investigator: Dr WANG Yi-zhou (Shue Yan)

Abstract

Background: Youth depression is becoming a serious issue in Hong Kong, with many secondary school and college students showing signs of depression. One of the main causes is social anxiety, which makes it even harder to treat. Traditional therapies like cognitive behavioral therapy (CBT) are helpful but may not fully address the deep-rooted fears that prevent young people from participating in important therapeutic activities.

Method: This study will test the effectiveness of a new approach using virtual reality (VR) to deliver CBT for social anxiety-driven depression in Hong Kong youths. 90 participants aged 15–24, who struggle with depression and find social situations challenging, will take part in the study. They will go through four VR sessions, each lasting 60 minutes, which simulate different social scenarios based on a well-known model of social anxiety. Progress will be measured before treatment, after the sessions, and three months later using specific questionnaires.

Research Questions: The study aims to find out if using VR can significantly reduce depression and social anxiety symptoms after the treatment and during follow-ups. It will also look at whether this VR approach is a cost-effective way to manage this type of depression.

Expected Outcomes and Implications: It is expected that the VR treatment will effectively reduce symptoms of depression and social anxiety in participants, with lasting benefits three months after the sessions. If successful, this approach could provide a more engaging, affordable, and scalable option compared to traditional therapies. The results could have a big impact on how we approach youth mental health care, encouraging the use of innovative technology in treatment and influencing future research, clinical practice, and policy-making in Hong Kong and beyond.

Project Reference No.: UGC/FDS13/H03/24
Project Title: Between state and market: War and Tea-Horse trade in the second half of the 16th century
Principal Investigator: Dr WANG Yongxi (Chu Hai)

Abstract

The northwestern border of the Ming Empire was a highly contested area, with competition between Mongols, Tibetan tribes, and Ming troops. The Ming court utilized the tea-horse trade to forge alliances with the Tibetan tribes against the Mongols, following a ”separate the barbarians and the Mongols” policy. The arrival of Mongolian forces in the Qinghai Lake region during the mid-Ming era added complexity to the situation along the northwestern border. During the early years of the Wanli Emperor's reign, the Ming court transitioned from passive defense to active offense to regain control of this borderland. These military operations significantly impacted the tea-horse trade system. While existing research has mainly focused on the trade before the mid-Ming period, this study seeks to address the gap in understanding the system after this period and challenge the existing research conclusions. It aims to gather historical materials related to the tea-horse trade from various rich Ming documents such as official records, literary anthologies, stone inscriptions, and local gazetteers, placing the trade within the broader context of the northwest and its military activities. This study promises to provide new insights into the distinctive role of the Chinese state in late imperial period trade.

Project Reference No.: UGC/FDS24/H24/24
Project Title: A Framework for Understanding the Acceptance of Student Created Screencasts by Teachers and Students to Implement Active Learning
Principal Investigator: Dr WONG Adam Ka-lok (PolyU SPEED)

Abstract

The rise of generative artificial intelligence (AI) applications, exemplified by tools like ChatGPT, presents opportunities and challenges for authentic assessment in education (Dehouche, 2021; Hosseini et al., 2023; Williamson et al., 2023). On the one hand, these AI tools offer the potential to enhance students' learning experience. From this perspective, educators should guide students to use these tools responsibly and ethically to achieve the intended learning outcomes. For example, students should not rely on these tools to produce their assignments but instead use them as a source of inspiration, feedback, or reference. On the other hand, there are severe concerns that current plagiarism detection software may struggle to identify content generated by these applications. It is because a student can provide the keywords from some assignment instructions, and the AI application can provide a well-structured essay. This type of generated text cannot be detected easily by existing plagiarism detection software. ChatGPT can also generate lines of program code according to the requirements entered by a student. In many cases, the students may copy-and-paste without much understanding of the information they have found. This is not only academic misconduct but also a reduction in learning effectiveness. Therefore, many universities also use plagiarism detection software to prevent academic dishonesty. Although specialized software such as Turnitin can detect and highlight the parts of an article that are plagiarized, students can defeat this using the "back-translation" method (Jones, 2009; Michael & Lynnaire, 2015; Yankova, 2020). There are also softwares that can detect computer code plagiarism or AI generated contents. However, these software often just return a probability that the text was plagiarised. It can lead to conflicts between students and teachers when there are disputes regarding the accusation. Afterall, the purpose of education is not to detect plagiarism, but to enable students to become critical thinkers.

Given the increasing proliferation of these AI applications in the workplace, higher education institutions should view them as allies rather than adversaries. Instead, university educators are encouraged to teach students to interact with these tools effectively, critically evaluate the materials created by these tools, and understand the limitations and biases that may exist in them. By doing so, students can develop their skills and knowledge and benefit from the advantages of AI tools.

The above purpose can be achieved by requiring students to explain their work in their own words or how the program code works to meet the requirements. This can be achieved by requiring students to submit videos of their explanations of their work and highlighting the relevant part of the essay or program code as they do so. The students are also expected to explain the diagrams they have used. The videos for this purpose are called student-created screencasts (SCSs). A SCS is a screen-capture video that shows the contents and actions on a student's screen. The actions include mouse clicks, drags and keyboard entries. The student's voice can also be part of the video. However, teachers need to make efforts to review SCSs. The effort may be reduced with the use of artificial intelligence (AI).

This proposed research study aims to understand the factors affecting the acceptance of SCSs, with AI-assisted marking, by teachers and students. This framework will be essential to help teachers implement active learning. The results of this research will guide teachers in designing SCSs as student assignments. For example, the SCS should include the student’s demonstration of the search, evaluation of the application of information from resources allowed by the teacher, including generative AI.

Project Reference No.: UGC/FDS14/E07/24
Project Title: Development of a Carbon Neutrality Model for Optimising Indirect Shipping Emissions from Components in a Multilevel Bill of Materials across the Value Chain in Product Life Cycle
Principal Investigator: Dr WONG Eugene Yin-cheung (HSUHK)

Abstract

The importance of reducing the carbon footprints of products has been emphasised in various World Economic Forums, and various countries have set carbon emission reduction targets. Over 110 countries have committed to a net-zero emission target by 2050. China has set a target of a 60%–65% reduction in carbon intensity by 2030 compared with the 2005 level. Thus, many companies have prioritised the mapping and mitigation of organisational and product-related carbon footprints. With the increasing complexity of the life cycle of products, controlling the direct and indirect carbon emissions (classified as Scope 1, 2, and 3 emissions according to global standards) throughout a product’s life cycle is becoming more challenging, particularly regarding Scope 3 indirect emissions. In addition to emissions directly generated by a company (Scope 1) and its electricity consumption (Scope 2), Scope 3 emissions encompass the remaining indirect emissions along the entire value chain of a product. These emissions range from upstream emissions associated with purchased goods and their transportation to downstream emissions, including the use of products sold and last-mile delivery. This category includes the indirect emissions associated with shipping all components of the products along the supply chain, as well as emissions from the product use phase. Current industry practices and previous research have focused on the methodology surrounding the overall concept of a carbon footprint, as well as the measurement and reduction of direct carbon emissions. However, there is a lack of frameworks, methodologies, and research dedicated to analysing, validating, and reducing these indirect emissions and to optimising decision variables related to shipping all product components along the value chain. This gap is particularly crucial for products with a large number of assembly components and complex operational processes, such as automotive, electronic, and beverage products. Advanced tools for mapping and minimising indirect emissions are needed. These tools guide decision-making by providing optimal sustainability requirements to third-party logistics suppliers, aiding in emission reduction through optimised shipping routing, fuel mix, and cargo consolidation. Additionally, these tools ensure accurate and reliable mapping of carbon footprints. Thus, a novel Scope 3 carbon neutrality emission model based on a recurrent neural network-based algorithm is proposed for minimising indirect emissions from the transportation of product components along the supply chain of a manufacturing product. The product components along the supply chain involve sequential decision factors such as shipment order volume, slot size, fuel mix, routing network, transportation mode, and reliability. These factors influence the volume of indirect emissions. The model will aid in the simulation of optimal sustainability requirements for shipping and logistics suppliers, providing reliable carbon footprint advice, and minimising parameters affecting carbon emissions. The novel model can serve as an optimal tool for minimising the indirect Scope 3 emissions for manufacturing products along the supply chain. Through advanced simulations, the significant volume of indirect emissions from products generated can be identified and significantly mitigated. The project deliverables from the carbon neutrality indirect emission model focusing on Scope 3 indirect emissions will be integrated into teaching modules to enrich students’ understanding of sustainable supply chains and advanced simulation tools.

Project Reference No.: UGC/FDS17/M03/24
Project Title: Effects of a nurse-led stress management and resilience training programme: A randomised wait-list controlled trial
Principal Investigator: Dr WONG Julia Sze-wing (TWC)

Abstract

Resilience is the ability to adapt well to adversity, trauma, tragedy, threats, or significant sources of stress. In Hong Kong, 15-year-old students have achieved a commendable third position globally in academic resilience but have some of the lowest levels of social and emotional resilience. The psychological, social, and mental health of Hong Kong youths has been significantly adversely affected by the protests that arose in Hong Kong in 2019–2020 and the social and economic impacts of the COVID-19 pandemic in 2020–2022.

The proposed project aims to introduce a nurse-led stress management and resilience training (SMART) programme for a group of nursing undergraduates and examine its effectiveness in improving their resilience and mental health outcomes. A randomised wait-list controlled trial will involve four hundred final-year nursing undergraduates randomly assigned to a wait-list control group or an intervention group. They will attend three 2.5-hour face-to-face training sessions every two weeks, with each session limited to a maximum capacity of 25 students. The levels of resilience and stress, anxiety, and depressive symptoms of both groups will be measured using two instruments, namely the Connor–Davidson Resilience Scale 10 and the Depression Anxiety and Stress Scale 21, at four time points (i.e., baseline, 2 weeks, 3 months, and 6 months after the completion of the SMART programme).

The results of the proposed project will contribute to the development of an evidence-based framework for cultivating resilience among college students and offer valuable insights to international researchers and educators at higher education institutions. If the SMART programme is effective in boosting the resilience of nursing undergraduates, it will help them persevere in their academic and nursing careers and reduce the attrition rate of nurses in Hong Kong.

Project Reference No.: UGC/FDS14/H13/24
Project Title: The Role of Pride and Shame in the Susceptibility to Misinformation in Social Movements
Principal Investigator: Dr WONG Muk-yan (HSUHK)

Abstract

Misinformation, defined as "well-formed and meaningful data (i.e. semantic content) that is false", (Floridi 2011, p. 260) is a very common phenomenon in social movements. The long-term prosperity of its dissemination is founded not only on the always advancing technical capabilities of media in creating and spreading information but also on human psychological vulnerability to misinformation which is deeply seeded in our evolutionary origins. The received explanations for susceptibility to misinformation, which draw on classic reasoning theories (Pennycook & Rand, 2019a), motivated cognition theories (Taber & Lodge, 2006), and anger theories (Martel et al., 2020), all make the dubious assumption that accepting the truth of information is a prerequisite for spreading it. The proposed project will argue that under the influence of the pride and shame feedback loops, members of social movements can remain ignorant of the truth of information and yet be eager to continuously disseminate it or reluctant to subject it to fact-checking.

Pride and shame are adaptive mechanisms that help to enhance or avoid diminishing a person’s social status in a group by motivating conduct that other group members value and discouraging alternative conduct. Strong evolutionary evidence for distinct, cross-culturally recognized forms of nonverbal expression that are reliably and spontaneously displayed in status-enhancing or status-diminishing situations, confirms the universality of such functions. I will argue that the basic function of pride and shame at an individual level is extended to a collective level when important values, goals, or lifestyles are acknowledged, shared, and respected by participants of a social movement and regarded as constitutive of their social self or collective identity. In particular, a participant feels pride or shame (1) when the social self is enhanced or diminished by oneself, (2) when the social self is enhanced or diminished by other participants with whom he or she “group identifies,” and (3) when other participants recognize one’s contribution to or condemn their damage to the social self.

Understanding pride and shame at a collective level can explain the wide spread of misinformation in social movements as a complement to the three received approaches. Specifically, pride serves as a motivation for individuals to spread information (whether real or fake) that substantiates a shared value, contributes to the achievement of a shared goal, or enhances the solidarity of a group to which they belong, especially when such substantiation, contribution, or enhancement is implicitly or explicitly recognized and acknowledged by other members of the group. Meanwhile, shame serves as a disincentive to fact-check group-favorable information because subjecting favorable news to such scrutiny is regarded as harmful to the legitimacy and solidarity of the group and as a form of distrust or even betrayal of other members. Thus, even when group members are uncertain of the truth of a piece of information that is affiliated with the shared values of the group, they will be eager to spread it or reluctant to subject it to fact-checking due to the influence of reciprocal pride and shame. Once group-favorable misinformation has been disseminated and the collective identity is reinforced, participants may experience amplified feelings of pride and shame within the group. This, in turn, may form a positive pride-oriented feedback loop that further motivates them to disseminate additional misinformation and a negative shame-oriented feedback loop that further discourages fact-checking activities.

Project Reference No.: UGC/FDS16/E08/24 (Withdrawn)
Project Title: A Principal Component Analysis based Distributed Local Representation for Spatial-Temporal Monitoring and Analytics
Principal Investigator: Dr WU Andrew Ho-chun (HKMU)

Project Reference No.: UGC/FDS24/E05/24
Project Title: Mapping and Designing of an Intelligent Charging Network for Increasing Electric Vehicles in Cross-Border Traffic Across Hong Kong and the Greater Bay Area – A Pilot Study
Principal Investigator: Dr WU Andrew Yang (PolyU SPEED)

Abstract

Electric vehicles (EV) have rapidly penetrated green and intelligent traffic in the past few years, especially in some leading countries and regions. One significant reason is EV have been considered an effective way to combat climate change and carbon emissions. It also contributed to roadside air quality for urban areas with a high density of population. Hong Kong, as a leading global metropolis, has actively provided incentives for EV penetration in the past years. In October 2022, a new Chief Executive Policy Address of HKSAR was published, indicating that around 700 electric buses will be deployed in service by the year 2027. Furthermore, a new northern metropolis area in the New Territories has been planned to integrate and interact further with the Greater Bay Area (GBA). This commitment will benefit Hong Kong people in many ways, including improved roadside air quality and natural environment, as well as more in-depth cross-border communication. In fact, the electric bus has widely penetrated the GBA as an essential part of green transportation. In the past few years, other neighbour cities in the GBA have aggressively deployed almost all taxi and bus services into EV, as a result of strong policy support and financial incentives, like Shenzhen and Macau. Hong Kong, as one leading role in the GBA, shall have no exception. Promoting EV has become an important part of upgrading both public and private transportation sectors in the next decade, which is in line with the future direction of Hong Kong.

The investigators team in this research proposal aims to develop a three-layer charging and communication network for electric buses in cross-border routes and the planned northern metropolis area. Firstly, in Task I, the feasibility of deploying electric buses for cross-border bus routes has been investigated using the hierarchical clustering method with consideration of optimal topological and traffic network problems. Main street network will be trimmed down for potential locations of building new charging stations or renovating existing parking spaces. The optimal algorithm will be coded via Python with data collected and supported by Google API and local transportation association. The target is to minimize charging time and detouring time. The constraints include local street network topology, traffic congestion, number of total charging stations, capacity of each charging station, and limited land spaces. Secondly, in Task II, the potential charging stations will bring a dynamic impact on the local electric power grid, including the increasing demand for power supply and the impact on the power distribution system at local community and micro-grid levels. Electric power flow will be analysed before and after the construction of potential charging stations, using Power-world software and Mat-lab Simulink with self-coding small programs. The target is to provide a sufficient power supply with optimal power flow dispatch and to minimize the associated economic costs. The constraints include the limit of local distribution cables and substations, as well as potential power transmission congestions. Furthermore, coupled objectives and constraints from both Task I and Task II will interact and impact each other, the synergies between which have to be carefully considered. Finally, in Task III, a small prototype of an intelligence communication program will be developed to illustrate the informatic communication between the transport control centre and users, to reflect update information like cruise location, expected detouring time, charging status, and charging vacancies. Upon completion of the project, suggestions with justifications on optimal locations of electric bus charging stations for cross-border routes and northern metropolis areas will be provided.

Last but not least, the investigators team started a pilot study last year, funded by internal financial support, which provided an inspiring experience and good background for implementing this proposal. Furthermore, we have sought support from some industries and associations in Hong Kong and the GBA.

Project Reference No.: UGC/FDS15/H23/24
Project Title: The Chinese Making of the Maritime Silk Road Heritage
Principal Investigator: Dr XIE Jieyi (Shue Yan)

Abstract

When we think about World Heritage Sites, we often picture a straightforward relationship between UNESCO, national governments, and local communities. However, this view misses crucial players in between – regional governments, museums, and cultural institutions that do much of the actual work in heritage management and promotion. These organizations, which operate between national and local levels, play vital roles in World Heritage nominations. They invest significant resources, manage heritage sites, and shape how cultural heritage is presented to the public. Yet, current research tends to overlook their importance, focusing instead on national-local relationships. This study examines China’s Maritime Silk Road (MSR) World Heritage project to understand how these regional cultural institutions contribute to national heritage initiatives. The research traces the development of the MSR concept from its emergence in UNESCO during the 1960s to 2024, looking at two main aspects:

• How new museums, exhibitions, and research centres present the Maritime Silk Road

• How existing historical sites adapt their stories to connect with this cultural route

This research bridges heritage studies and sociology by examining heritage as a form of capital that shapes institutional power dynamics. Traditional sociological theories of cultural capital focus on individuals, but this study shows how institutions strategically use heritage resources, revealing new dimensions of how cultural power operates at organizational levels. The study also challenges conventional understanding of heritage governance. By examining how regional cultural institutions create their own spaces of influence within seemingly top-down heritage systems, it provides new insights into how cultural governance actually works in practice, offering fresh perspectives on the relationship between global heritage frameworks and local institutional practices.

Project Reference No.: UGC/FDS16/M12/24
Project Title: Unveiling abiotic and biotic factors influencing allelopathic interactions between harmful algal species Karenia mikimotoi and Karenia papilionacea and the molecular mechanism
Principal Investigator: Dr XU Jingliang (HKMU)

Abstract

Harmful algal blooms (HABs) pose a significant threat to aquatic life and have caused massive economic losses due to fish die-offs in many countries. Although K. mikimotoi does not produce toxins harmful to humans, it is lethal to marine life. It has been linked to massive fish die-offs, causing significant economic damage. K. papilionacea, on the other hand, produces a tiny amount of brevetoxin, which shows toxicity to fish cell culture in laboratory experiments and can affect human health if ingested. Both species often bloom together, but the reasons for this are not fully understood. The study will explore the concept of allelopathy, a process where organisms produce secondary metabolites that affect neighboring organisms. K. mikimotoi, despite having a low reproductive rate and poor nutritional capacity, often develops HABs, and its allelopathic effect on other phytoplankton and zooplankton is considered one of the main reasons. Previous research has shown that K. mikimotoi has inhibitory allelopathic effects on the growth of other microalgae, and these effects can be influenced by various abiotic and biotic factors. These factors include temperature, nitrogen- or phosphorous-deficiency, algal cell density, and direct or indirect cell contact. However, the allelopathic mechanism of K. mikimotoi on other HAB species is not well understood, particularly on other species of the same genus, Karenia. Our team has previously tracked and recorded the co-bloom outbreaks of K. mikimotoi and K. papilionacea in Hong Kong coastal waters and conducted a thorough study on the mono-culture of K. mikimotoi. We found that the growth and ichthyotoxicity (toxicity to fish) of K. mikimotoi were sensitive to salinity, cell density, and growth phase. We also found that the community of algal-associated bacteria had a significant impact on the ichthyotoxicity of K. mikimotoi. This study aims to examine the allelopathic effects of K. papilionacea on the growth and toxicity of K. mikimotoi in direct and indirect contact modes and with different cell density ratios, and to explore the effects of abiotic factors (salinity, temperature, nitrogen- or phosphorous-deficiency) and algal-associated bacteria on these allelopathic effects. We will also attempt to elucidate the molecular mechanism of the allelopathic effect of K. papilionacea on K. mikimotoi through proteomic analysis. By exploring these interactions, we will gain a better understanding of why these two species often bloom together, and how their interactions affect their toxicity. This could potentially lead to better strategies for managing and mitigating the impacts of HABs.

Project Reference No.: UGC/FDS14/H19/24
Project Title: Shaping the Future of Film Education: Exploring the Possibilities of AI in Enhancing Creativity and Learning Outcomes
Principal Investigator: Dr YANG Rochelle Yi-hsuan (HSUHK)

Abstract

Integrating Artificial Intelligence (AI) into film and art education represents a ground-breaking paradigm shift in creative learning processes. AI as a tool has the potential to revolutionize the way stories are told, pushing the boundaries of visual storytelling and cinematic innovation (Landon, 2023) now and in the future. This proposal seeks to explore the transformative potential of AI in enhancing idea generation, concept development, creative methodologies, narrativity, and production within art and film education. By examining the impact of AI on students enrolled in art-related programs in Hong Kong-based universities, this study aims to clarify the applications, usages, methods, new forms of creativity, evaluation, and challenges associated with AI-generated artworks.

Through empirical study and comprehensive analysis, this research endeavors to provide valuable insights for educators, artists, filmmakers, researchers, policymakers, and beyond on the implications of AI in shaping the future of art and film education. The outcomes of this research are pivotal in enhancing our comprehension of the transformative role AI can assume in art and film education, offering valuable perspectives that can empower educators to leverage innovation and foster a vibrant learning milieu conducive to nurturing creativity and bolstering learning incentives for digital generations in Hong Kong.

Project Reference No.: UGC/FDS15/H09/24
Project Title: Effects of Diverse Training Paradigms on Enhancing Comprehensibility of Cantonese Speech in Immigrants
Principal Investigator: Dr YANG Yike (Shue Yan)

Abstract

Although there is an increasing number of people learning a second language (L2), it is widely accepted that attainment of native pronunciation is unlikely for post-puberty L2 learners. From a more practical point of view, L2 learners and teachers should focus more on the comprehensibility of L2 speech, rather than the accent. One feature of L2 learning is the lack of sufficient exposure to the L2, even in the immigration setting. Thus, the proposed study will examine the effects of various short-term training paradigms on the enhancement of comprehensibility in immigrants’ L2 Cantonese, in the hope of providing effective training methods for immigrants to compensate for a lack of sufficient exposure.

This proposed study has three aims: (1) test the effects of different training methods on L2 comprehensibility enhancement; (2) systematically examine the effects of different training methods on lexical tone production and perception; and (3) combine both acoustic and perceptual measurements for analysis of L2 Cantonese speech. This study will recruit immigrants with no prior knowledge of Cantonese before arriving in Hong Kong and will prepare different training methods to enhance the comprehensibility of their L2 Cantonese. To investigate the training effects, the participants’ performance of various tasks will be tested before and after training sessions.

As the first attempt to systematically investigate the effects of different training methods on Cantonese tone production and perception, this study will provide insight into training effectiveness and advance our theoretical knowledge of L2 speech learning. Furthermore, the results of this research will also inform language teachers of the optimal training method for Cantonese tones, allowing teachers to revise their syllabi and pedagogies when teaching L2 learners of Cantonese.

Project Reference No.: UGC/FDS13/H12/24
Project Title: Exploration of the rewriting of the new revised edition of Jin Yong's Novels by studying his Manuscripts
Principal Investigator: Dr YAU Kin-yan (Chu Hai)

Abstract

After two major revisions of Jin Yong’s novels, in which a lot of characters and plotlines were deleted and, in some cases, even the endings of the stories were rewritten, with the latest revision taking place from 1999 to 2006, the re-edited novels are collectively known as the "Newly Revised Edition of Jin Yong’s Novel Set."

The editing work for each novel with multiple alterations was done by a Taiwanese publisher, Yuan-Liou Publishing Company Limited. At the initial stage, Jin Yong himself made basic additions, deletions, and revisions on photocopies of the revised edition. New plotlines, in handwriting, were extensively added by Jin Yong, up to twenty-four pages at most, by marking the insertions into the original texts. The manuscripts were sent to Taiwan, where the editor would send the formatted drafts back to Hong Kong for Jin Yong's review. The editor would even communicate with Jin Yong through letters regarding any issues arising from the modifications, and Jin Yong would decide how to further modify them. Jin Yong would then make additional modifications or add annexed pages to the printed drafts before sending them back to Taiwan. Each novel was modified five to six times. All manuscripts, including unused additional plotlines, were retained by the publishing house, totaling over forty boxes of A4 photocopy paper.

The publishing house allows the Principal Investigator to page through materials in the office. The main purpose of the practice is to explore the editing process during Jin Yong's later years by organizing manuscripts and correspondence from various stages, reconstructing the trajectory of Jin Yong's thoughts during the revision of his works. The research work is divided into two stages: "Reconstruction" and "Description." The goal of "Reconstruction" is to identify the stages at which additions were made in the published novels which were previously revised based on the manuscripts and to recover the deleted portions. The next stage is "Description", which involves analyzing Jin Yong's thought process from the beginning to the end of rewriting the novels based on the details of the reconstruction and the correspondence. For example, there are extensive annotations in the newly revised novels. When were these annotations added? Why were they added? What do they reflect about his thoughts and intentions in the rewriting process? Similarly, for some added plot points that Jin Yong ultimately decided not to include, when did this decision occur, and why?

Jin Yong's novels are significant works in the world of Chinese literature, and the completely preserved manuscripts of the newly revised editions are precious and rare historical materials. Therefore, the research outcomes of this project hold great significance for the contemporary literary history of Hong Kong. The project serves two major purposes: "reconstructing historical materials" and "making significant discoveries." It allows for the exploration of Jin Yong's creative trajectory in rewriting novels by examining the modified manuscripts from various stages, providing a more comprehensive understanding of the creative process of this influential writer in both the Hong Kong and broader Chinese literary communities.

Project Reference No.: UGC/FDS11/H06/24
Project Title: Determinants and consequences of nonprofit voluntary disclosure in Hong Kong
Principal Investigator: Dr YI Cheong-heon (SFU)

Abstract

Nonprofit organizations enrich our lives by providing a multitude of goods and services in areas such as health care service, education, religion, poverty alleviation, etc. The nonprofit sector is a significant and growing part of the Hong Kong economy. For example, private charitable donations as a percentage of gross domestic product increased from 10 percent in 1980 to 45 percent in 2018. As our society evolves and changes over time, nonprofit organizations face critical challenges associated with accountability and transparency. Although nonprofits in Hong Kong are not legally required to publish annual reports, many nonprofits use them as a key information channel to communicate with donors and grantors about a nonprofit organization’s efficiency, effectiveness, and performance. However, relatively little is understood about what motivates nonprofit organizations to share more information through annual reports with stakeholders and whether the public and stakeholders use nonprofit disclosure in deciding where to donate.

To fill these gaps, this project adopts an explanatory sequential mixed methods approach to understand nonprofit voluntary disclosure behavior in Hong Kong. Firstly, it quantitatively examines the determinants and consequences of nonprofit voluntary disclosure in Hong Kong. Specifically, it investigates characteristics of nonprofit organizations providing more information, whether nonprofit disclosure affects the level of charitable contributions nonprofits attract, and whether the relationship between information disclosure and contributions changes during the COVID-19 pandemic period. In so doing, the project develops disclosure indices that capture the extent of information disclosures of financial, performance, and governance information in annual reports of nonprofits in Hong Kong. Secondly, it qualitatively explores the perceptions of nonprofit managers about the costs and benefits of voluntary disclosure through interviews.

While a large body of theoretical and empirical research over the years has investigated disclosure practices of for-profit organizations, there has been limited evidence in the nonprofit setting and even the existing evidence has been mostly documented for U.S. nonprofits. Given that institutional environments for US nonprofits are different from those for Hong Kong counterparts in terms of reporting requirements and the size of nonprofits, it is worthwhile to examine nonprofit voluntary disclosure in a Hong Kong setting. First, the proposed project will develop and test a determinants model of nonprofit disclosure by drawing on previous research on voluntary disclosure in for-profit and nonprofit settings. Specifically, we hypothesize that nonprofit voluntary disclosure is associated with the following three main factors: (1) the strength of governance, (2) the organizational performance of a nonprofit, and (3) the funding source. Second, the project will examine the consequences of nonprofit disclosure for the level of charitable contributions. We will document systematic variation in responses of stakeholders to voluntary disclosure across information type, donor type, and time. Third, the project will present the views of nonprofit managers on voluntary disclosure. The findings from this project will be of interest to regulators and stakeholders. Given that the global Pandemic together with the associated economic downturn has made competition among nonprofit organizations for limited resources more intense, the proposed project is timely and has the potential to provide new insights into the development of public policy on nonprofit disclosure and transparency. In sum, the findings will expand our understanding of how information disclosure in nonprofit annual reports may play a role in enhancing the relationship between the nonprofit sector and its stakeholders and how nonprofit organizations can be operated more efficiently and effectively.

Project Reference No.: UGC/FDS16/H35/24
Project Title: Chinese Anthropocene Science Fiction as a Contact Zone
Principal Investigator: Dr YU Xuying (HKMU)

Abstract

The fever for science fiction (sci-fi) has surged in China since the 2010s, establishing it as one of the most vibrant cultural phenomena in the nation. Liu Cixin’s Hugo Award-winning “The Three-Body Problem” in 2015 and the record-breaking Chinese sci-fi movie "The Wandering Earth" in 2019 are among the most prominent examples. Chinese sci-fi writers have not only captured immense international attention, but they have also enjoyed widespread popularity domestically, appealing to a broad audience beyond the core sci-fi community. In October 2023, Chengdu’s hosting of the World Science Fiction Convention elevated Chinese sci-fi fever to a new height, which subsequently sparked controversy. This fever underscores the strong appeal of Chinese sci-fi not only to fans, scholars, and the general public but also, significantly, to the Chinese government and cultural industry.

The rise of Chinese Anthropocene fiction, emerging from the landscape of the nation’s science fiction boom, epitomizes the complex interplay between locality and universality, attracting international scholarly attention. This subgenre showcases a dual narrative: a pronounced eagerness among creators, scholars, audiences, businesses, and the state to forge science fiction with distinctly Chinese contents and characteristics, while actively engaging with themes of universal significance, thereby placing Chinese works on par with global science fiction narratives. The active participation of Chinese science fiction in worldwide ecological discussions further underscores this balance. By exploring Chinese Anthropocene fiction in the context of Chinese science fiction fever, this project identifies the subgenre as a "contact zone" – a space where ecological particularism and universalism intersect, where state-led narratives encounter expansive planetary thought, and where Chinese science fiction intersects with and enriches World Literature.

This project consists of three parts, exploring Chinese Anthropocene fiction’s role of as a “contact zone” from three aspects: cultural particularism and human crisis, state discourse and planetary thinking, as well as the journey to the World. Part I firstly identifies two notable universal tendencies in recent Chinese sci-fi: “critiquing the Anthropocene”, which exposes the crises of the Anthropocene s including climate change, environmental pollution, and species vanishing, and criticizes the Anthropocentric mindset; and, then, “imagining the post-Anthropocene,” which imagines non-coercive and non-binary connectivity among multispecies. This part explores local values, ideologies, and aesthetics in terms of their ways of imagining solutions for humankind and the Earth as well as their visions of a universal post-Anthropocene. Part II scrutinizes the role of Chinese Anthropocene fiction as an active agent in its response to the state discourse on Ecological Civilization alongside developing planetary thinking. Focusing on the “Chinese sci-fi Translation Project,” and the translation of The Wandering Earth, Part III looks into the reconnection of China and the world via the distribution and dissemination of Chinese Anthropocene fiction, strategies of “coming out of China”, the international receptions, and questions of translation and translatability.

Positioning Chinese Anthropocene fiction as a “contact zone”, this project highlights connectivity as the most significant contribution of the recent Chinese sci-fi fever both within and beyond literature and further emphasizes the eco-political agency of Chinese sci-fi in constructing a discursive site for planetary consciousness to negotiate with state ideology.

Project Reference No.: UGC/FDS14/E03/24
Project Title: Robust Federated Learning Empowered Microservice Migration in Mobile Edge Computing
Principal Investigator: Dr ZHANG Chen (HSUHK)

Abstract

With the rapid development of 5G network technology, mobile edge computing (MEC) has emerged as a promising paradigm to support latency-sensitive applications. Service migration is critical in MEC to ensure the seamless provision of services as users move. In many applications such as autonomous driving, user location often changes during service provision, which may cause service interruption if the user is far away from the server running the requested service. Ensuring that such services can follow users’ movements is crucial for maintaining low response latency and providing a seamless user experience. While service migration has the potential to bring significant benefits, it also introduces additional overheads. An inappropriate service migration scheme may even increase service latency.

Reinforcement learning is a promising method for making service migration decisions owing to its high adaptability to dynamic environments. Most reinforcement learning-based designs focus on the migration of independent services. However, in real-world scenarios, the task requested by a user usually contains multiple subtasks with dependencies, and these subtasks follow a clear directed acyclic graph (DAG) structure. Therefore, dependencies between microservices need to be considered in migration decisions. Existing DAG-based service migration designs assume that all microservices corresponding to a DAG task will be migrated to a single edge server, which may lead to high service latency when the target edge server lacks sufficient resources to accommodate these microservices. It is important to allow microservices to be migrated to different edge servers to distribute workloads.

Additionally, the data used to train the service migration model contains sensitive user information (e.g., user trajectory data). Adopting a centralized training architecture will result in high transmission overheads and risks of privacy leakage. Federated learning enables edge servers to collaboratively train the service migration model without sharing local data. However, the distributed learning architecture of federated learning poses challenges to its robustness. If some edge servers are controlled by attackers and upload poisoned model updates during training, the performance of the service migration model will be significantly degraded. Although some defense schemes have been proposed to sift through model updates to identify outliers, they fail to consider the weight importance factor, resulting in significant degradation in defense performance under model poisoning attacks enhanced by weight importance.

The principal goal of this project is to fill the above-mentioned research gaps and design a robust federated learning based microservice migration in MEC. There are three main tasks in this project: 1) Design a federated reinforcement learning-based microservice migration framework for MEC to minimize the service latency of user-offloaded DAG tasks. The framework shall support the migration of microservices of a DAG task to different edge servers. 2) Design defense schemes to protect the federated learning-based microservice migration against model poisoning attacks. The proposed schemes should have strong defense under model poisoning attacks enhanced by weight importance. 3) Develop a prototype system of robust federated learning-based microservice migration for performance evaluation and fine tuning of the proposed designs under different datasets and network environments.

Project Reference No.: UGC/FDS24/M02/24
Project Title: A Photoacoustic-guided Iontophoresis Controllable Microneedles System for Advanced Close-loop Drug Delivery
Principal Investigator: Dr ZHOU Yingying (PolyU SPEED)

Abstract

It is widely recognized that the availability of medical resources in Hong Kong is notably constrained, resulting in challenges accessing medical treatment and prolonged waiting periods for appointments. Introducing self-homecare initiatives could substantially alleviate these issues. Among the various approaches to disease treatment, medication therapy is the most commonly employed. The duration of medical treatment is partly determined by the method used for drug administration. With the ongoing advancements in medical technology, various modes of drug delivery have emerged, including oral administration, intravenous injection, and transdermal administration. Transdermal administration offers advantages over oral administration and intravenous injection as it is less painful, bypasses the first-pass effect of the liver, provides sustained release, and is suitable for self-homecare due to its ease of operation.

One emerging technique for enhancing transdermal drug delivery is the use of microneedle (MNs) arrays. These arrays have garnered significant attention due to their minimally invasive nature, high drug permeability, and user-friendly application that does not require professional medical personnel. In the treatment process, timely monitoring, evaluating, and adjusting the administration effects of MNs can be beneficial for assessing drug performance in specific diseases and helping patients achieve better treatment outcomes. Precisely controlling the dosage and administration rate of drug delivery is crucial for patients. Therefore, monitoring the effect of microneedle administration can provide valuable guidance and facilitate real-time adjustments to the drug dosage, ultimately enabling the creation of personalized dosing regimens through feedback regulation.

Among the various imaging technologies, photoacoustic (PA) imaging stands out for its effectiveness in monitoring the drug delivery process by calculating the photoacoustic signals generated by specific drug dosages. Furthermore, the development of wearable photoacoustic patches can be applied in daily homecare, overcoming the inconvenience associated with bulky imaging devices. Iontophoresis is a non-invasive and well-established physical method that can effectively address the issues of low transdermal, corneal, and mucosal transport rates, as well as low absorption. Based on these considerations, we propose the design of a PA-guided iontophoresis controllable microneedle drug delivery system.

By combining the benefits of PA imaging and iontophoresis, this microneedle drug delivery system can enable advanced monitoring, guidance, and real-time adjustments for drug administration. It has the potential to offer a more convenient, comfortable, and personalized treatment experience, significantly promoting the development of self-homecare. Moreover, it presents an innovative solution to the challenges posed by limited medical resources in Hong Kong.