Faculty Development Scheme (FDS) - Project Abstract

Project Reference No.: UGC/FDS25/E05/22
Project Title: Feasibility study on innovative hybrid wastewater treatment design for achieving carbon and energy neutrality by using forward osmosis-anaerobic membrane bioreactor (FO-AnMBR) with microalgae post-treatment
Principal Investigator: Dr CHAN Cho-yin (THEi)


In the past couple of years, apart from preventing the Covid-19 pandemic disease, the mitigation of adverse climate change has been regarded as the most challenging task that requires immediate action, commitment, and global collaboration. The effectiveness of different climate actions proposed since 2015 in the Paris Agreement for keeping the increased temperature levels within 1.5-2°C compared to the pre-industrial period is critically evaluated, to enhance the existing measures and determine what stronger mitigation policies are required to achieve the peak carbon dioxide emissions before 2030 and the ultimate goal of carbon neutrality before 2050 (or 2060 for some countries like the Mainland China and Russia). In November 2021, a significant global agreement addressed in the COP26 Glasgow Climate Pact has sought for further energy transitions to net zero (greenhouse gases emission) by phasing down the unabated fossil fuel, like coal power, and also extensive efforts have been suggested to focus on adopting more clean and renewable energy assisted by innovative-green technologies and international & financial support. As a result, a low energy consumption approach and proactive retrofitting design in different manufacturing and industrial processes are needed to fulfill the target of carbon emission reduction. Recently, energy-saving approaches in waste treatment design and even more aggressive approaches for energy positive in different waste-to-energy processes have been proposed. Among different processes, conventional wastewater treatment using activated sludge process (ASP) may require a significant change because of high electricity consumption in its aeration stage (50% in total energy use), for example, the estimated annual global electricity consumption by such wastewater treatment process is 2-3%, resulting in significant amounts of carbon emission, although ASP is successfully used for treating municipal wastewater for more than a century. Moreover, a larger amount of wastewater will be generated in the coming future due to rapid human population growth, as well as more stringent effluent discharge standards will be required because of the water reuse purpose. In fact, the amount of extractable energy from wastewater can be significantly further improved (now only 20% recovery from 2.7kWh/m3). Thus, an innovative treatment design is necessary for municipal wastewater to achieve the targets of carbon and energy neutrality. In this feasibility study, local sewage, after the removal of suspended particulates by primary sedimentation, will be treated by an anaerobic membrane bioreactor (AnMBR) to avoid the aeration process used in the conventional secondary treatment. Also, AnMBR has advantages including biogas production (i.e., methane) for in-plant electricity generation, allowing longer solid retention time (SRT) for treatment, less amount of sludge generation, and no secondary sedimentation tank is required for the sludge collection so that the overall footprint can be reduced. However, the relatively low organic substrate level (in terms of COD) found in primary effluent, may not be sufficient to support the growth of anaerobes for effective treatment and optimal level of biogas production that a simple pre-concentration step for this liquid waste will be conducted by using forward osmosis (FO), which enables water molecules of the liquid waste stream to pass through the semi-permeable membrane to the draw solution stream (i.e.,1M NaCl or seawater) while this process can be operated under a low energy pumping system. On the other hand, the degradation process of AnMBR can be generally conducted at 13-25°C while higher performance can be achieved at 30-35°C and the energy used for heating can be compensated by the biogas production. A side-stream operation mode of the membrane unit using ultra-filtration (UF) would be designed, then the essential membrane washing can be conducted separately to allow minimal disturbance towards the main bioreactor used in the anaerobic degradation process. Although 90-95% of COD can be removed by the AnMBR, nitrification and denitrification reactions are not proceeded, thus the accumulated high levels of ammonium nitrogen (NH4+) and also the phosphate are unacceptable for discharge or water reuse. Therefore, a simple post-treatment process after AnMBR is proposed by using microalgae, for example, Chlorella vulgaris and Scenedesmus obliquus. As a result, wastewater can be effectively treated, and extra renewable bioenergy and potential nutrients feedstock from microalgal biomass can be obtained. Finally, an innovative FO-AnMBR-microalgae hybrid system is developed for achieving carbon and energy neutrality in wastewater treatment.


Project Reference No.: UGC/FDS14/H19/22
Project Title: Advertising Innovative Products Across Cultures: The Manifestation of Innovativeness Cues and Their Relative Impact
Principal Investigator: Dr CHAN Fong-yee (HSUHK)


Committed to cultivating and promoting innovation, Hong Kong aspires to be the center of innovation in Asia. Despite the cross-cultural nature of consumer behavior and receptiveness to innovation, little is known about how innovativeness should be communicated to consumers across cultures to enhance innovation adoption. The proposed project will examine how advertisers manifest cues in innovative product advertising and how they enhance innovativeness perceptions across cultures. It will be conducted in three phases. In Phase 1, a content analysis of digital display advertisements for innovative products will be conducted to examine the extent to which innovativeness cues are manifested in advertisements. In Phase 2, the research stimuli will be manipulated and validated by a judging panel consisting of a national panel of consumers from the six cultures. In Phase 3, a pretest, pilot study and experimental study of the general public across the six cultures will be conducted to investigate the roles of cultural orientations, innovativeness cues and advertising appeals on consumer perceptions and the adoption of advertised innovative products. Exploring this new and fertile area is expected to make significant theoretical contributions to the literature on product innovation and intercultural communications. The empirical results will also help inform marketers as to whether a standardized advertising appeal could be adopted, and how to design more effective advertising appeals when promoting innovative products across cultures.


Project Reference No.: UGC/FDS11/B02/22
Project Title: Could a Tax Credit Rating System engender a Spillover Effect to reduce the Tax Avoidance of Peer Firms?
Principal Investigator: Prof CHAN Koon-hung (Caritas)


Tax revenue is a critical financial resource for governments to carry out their governance functions. Tax avoidance threatens a government’s ability to collect proper amounts of tax revenue according to tax laws. Therefore, the question of how to better protect and collect tax revenue is an important challenge that needs to be addressed continuously by governments.

Governments can use both carrots and sticks in revenue collection. Attention from professional practice and academic literature has focused mostly on the use of tax audits and penalties to enforce tax compliance. Not much attention has been devoted to the use of incentives to entice compliance. The main objective of the proposed research is to shed light on the efficacy of an incentive-based scheme coordinated and implemented by the Chinese tax authorities intended to reduce tax avoidance.

The research results should have significant policy implications for tax authorities, corporate management, investors, auditors, and relevant public policy makers. As this incentive system represents an important new development in tax administration, if proven effective, it can also serve as a useful model for tax authorities internationally, particularly those in developing economies, to enhance corporate tax compliance.


Project Reference No.: UGC/FDS24/E16/22
Project Title: Investigating Land Development and Land Tenure in the Greater Bay Area through Selected Case Studies: A New Path to China’s Territorial Development and City-Regionalization?
Principal Investigator: Prof CHAN Roger Chun-Kwong (PolyU SPEED)


Land tenure and property rights are determined by various forms of institutional design and social norms in each city. The process of land development, which is characterized by changes in the land’s physical form, value, and property rights, has close linkages and interactions with politics, society, economy, and urban form. Land development process has been the driving force behind China’s economic and urban development, as illustrated by the experience in the Greater Bay Area (GBA). The process has brought about changes in the land tenure and management system, which are due to the fiscal policy (gaming) among the central, provincial, and municipal authorities.

In the past, land for development was supplied by expropriation of urban land or conversion of collectively owned rural land into state-owned land since only the latter can be used for urban construction. With rising demand for land for urban development, collectively owned rural and suburban land has been taken for development purposes, accompanied by a marketization of collectively owned construction land with formal or informal rights. Appreciation in rural land value presents challenges to government-led urban development initiatives.

Through the application of data analytics technique and in conjunction with field study, questionnaire survey and interviews to examine development projects in the GBA; followed by in-depth case studies of four development projects in Guangzhou and Shenzhen; this research argues that the existing mechanism for assessing land development proposals is inadequate to meet the current socio-economic environment. Findings from this research will offer insights to articulate the post-land finance development strategy in the GBA. How the land tenure and management system could be improved? It will further shed lights on policy formulation and implementation of the (local government) land-based fiscal policy and urban development strategy in China.


Project Reference No.: UGC/FDS16/M03/22
Project Title: Study on the bioremediation of chlorpyrifos by two Scenedesmus species under different phosphorus concentrations
Principal Investigator: Dr CHAN Sidney Man-ngai (HKMU)


Organophosphorous pesticides (OPP) are a group of insecticides extensively applied in food crop production and non-food settings. After application, residual OPP pollute the environment. Chlorpyrifos, the mostly used conventional OPP, arouses public concern recently because of its neurological and endocrine disrupting toxicity, not only to insects and wildlife but also human. Wastewater contaminated with chlorpyrifos must be treated before disposal. Bioremediation, referring to biosorption, bioaccumulation and biodegradation, of organic pollutants by microorganisms including microalgae is believed to be a sustainable option of wastewater treatment. During bioremediation process, microalgae utilize nutrients in the wastewater and carbon dioxide to grow. The produced microalgal biomass can be converted to valuable resources such as biofuel, bioplastic, biochar, and animal and fish feeds.

Microalgae may biodegrade OPP into phosphate and alcohol by phosphotriesterase. OPP also cause oxidative stress leading to the generation of reactive oxygen species (ROS) that induce lipid peroxidation in microalgae. These ROS can break down OPP. Unlike other OPP, there is little bioremediation studies on chlorpyrifos by microalgae, probably because chlorpyrifos is more difficult to biodegrade. The metabolism of chlorpyrifos has seldom been studied. Limited research suggests that the biodegradation of OPP, including chlorpyrifos, may be incomplete and metabolites formed may be more harmful than the parent pollutants. Some species accumulate toxic degraded products such as 3,5,6-trichloro-s-pyridinol. In our recent preliminary study, two green microalgal isolates, Scenedesmus dimorphus and Scenedesmus quadricauda, were found to bioremediate chlorpyrifos in artificial wastewater. Both species showed more than 90% chlorpyrifos removal in 7 days, but S. quadricauda only achieved 19% biodegradation while S. dimorphus showed higher biodegradation (73%). This suggests that chlorpyrifos bioremediation capability, and mechanism involved may be species-specific. Understanding biodegradation of chlorpyrifos and metabolic pathways by specific microalgal species, particularly the isolates, is essential before the species is applied for bioremediation.

Biodegradation of chlorpyrifos by microalgae may be affected by phosphorus availability. Under conditions with limited or even lack of phosphorus, microalgae may biodegrade chlorpyrifos to obtain the phosphorus atom in chlorpyrifos’s structure as their phosphorus source. However, phosphorus metabolism in the presence of chlorpyrifos has never been reported, and such a response may be algal species-specific. The phosphorus metabolism of microalgae is complex and involves different interrelated enzymatic pathways, which is difficult to be studied via the measurements of individual enzyme activity alone. Proteomics is a technique that allows studying the responses of these interrelated enzymatic pathways at different phosphorus concentrations with or without chlorpyrifos in a holistic approach.

This project aims to understand chlorpyrifos bioremediation by two Scenedesmus isolates under different phosphorus concentrations and explore the mechanisms behind. Specific objectives include i) compare the biosorption and biodegradation of chlorpyrifos between S. dimorphus and S. quadricauda, in medium and real wastewater; ii) investigate effects of phosphorus concentrations on bioremediation efficiency and mechanisms, and analyze cellular phosphorus concentrations of the two species with and without chlorpyrifos; iii) evaluate the toxicological responses of the two species under different chlorpyrifos and phosphorus concentrations; iv) identify and monitor the changes of the major chlorpyrifos metabolic products by the two species; and v) explore the responses of phosphorus metabolism by the two species in the presence of chlorpyrifos based on proteomic approach. Through this project, bioremediation by microalgae, a sustainable treatment method will be demonstrated. The project will also contribute knowledge on chlorpyrifos metabolism by microalgae and enhance bioremediation efficiency by varying phosphorus availability. Furthermore, a robust microalgal species for chlorpyrifos bioremediation will be provided.


Project Reference No.: UGC/FDS11/M03/22
Project Title: Elucidating the novel role of hypothalamic GLP-1 receptor system in mechanism of nausea and emesis in Suncus murinus
Principal Investigator: Dr CHAN Sze-wa (Caritas)


The introduction of glucagon-like peptide-1 (GLP-1) receptor agonists changed the treatment strategies of type 2 diabetes mellitus (T2DM) as GLP-1 receptor agonists not only provide glycaemic control but have additional body weight control and cardiovascular benefits. However, the use of GLP-1 based therapy can be associated with gastrointestinal side effects, including nausea and emesis, limiting the doses that can be used. The mechanisms controlling emesis and the sensation of nausea and those involved in appetite are subtly different and is less well understood. Research strategies elucidating emesis and anti-emetic drugs have focused on the brainstem vomiting centre. The potential involvement of the hypothalamus, which is integral to autonomic control, has been overlooked. This project is based on our own original findings that intracerebral paraventricular hypothalamic (iPVH) administration of exendin-4 inhibited significantly food and water intake and induced emesis in a dose-dependent manner in Suncus murinus. Exendin-4 appeared more potent in inducing emesis following iPVH compared to intracerebroventricular administrations. We also showed that subcutaneous administration of exendin-4 induced emesis but not the associated inhibition of feeding was antagonized by iPVH administration of the GLP-1 receptor antagonist, exendin (9-39). In addition, the emetic effect of exendin-4 was dissociated from its anorectic effect. These findings suggest that hypothalamic GLP-1 receptors may be at least partially involved in mechanism of nausea and emesis. The parabrachial nucleus receives reciprocal inputs from the hypothalamus, amygdala and limbic system and sends projections to the nucleus tractus solitaries. We hypothesize that GLP-1 receptor activation in the PVH may modulate local release of GABA and/or glutamate and other transmitters which act as key modulators in these brain areas and are involved in mechanism of emesis control as well as nausea which is a subjective feeling involving higher brain functions.

In the present project, we aim to determine the role of the hypothalamic GLP-1 receptor system in feeding and emesis and the possible underlying mechanism of the signalling pathway. Animal experiments will be performed using standard behavioural testing and established radiotelemetric techniques to evaluate physiological changes indicative of nausea (PCIN) coupled with c-Fos immunohistochemistry analysis of brain function. Changes in brain neurotransmitters will be monitored using brain microdialysis. Our studies will uncover a novel mechanism of nausea and emesis. Data obtained from studying the emetic mechanisms of GLP-1 receptor system may not only enable a more improved management of diabetes and obesity, but may also lead to the discovery of new target for anti-emetic development and improve the quality of life of cancer patient receiving chemotherapy.


Project Reference No.: UGC/FDS16/B18/22
Project Title: Governance Reform in Stakeholder-oriented Context: A Behavioral Perspective
Principal Investigator: Dr CHEN Kelly Xing (HKMU)


Corporate governance varies across contexts. A key debate in organization science, economics, law, and sociology is whether corporate governance will converge toward the Anglo-American model, which is shareholder-oriented and often viewed as the “best” governance model. Studies show that some, but not all, firms in stakeholder-oriented contexts engage in governance reform toward the Anglo-American model. Nonetheless, we have limited understanding of what leads to the variety of governance reform at firm level in stakeholder-oriented contexts. Past literature mainly adopts agency theory and institutional theory to explain governance reform assuming that key decision makers of a firm engage in governance reform rationally either to reduce agency costs or seek legitimacy, which neglects the fact that decision makers are bounded rational and subject to the influence of behavioral factors. Besides, the impact of governance reform outside Anglo-American countries is far from being conclusive.

To fill these gaps, this project builds on the behavioral theory of the firm to explain the antecedents and consequences of governance reform in a stakeholder-oriented context. Specifically, bounded rational decision makers would engage in problemistic search when firm performance is below aspiration level. Search stops when a satisfactory solution is identified. I contend that governance reform in some firms result from change-inducing problemistic search. When key decision makers in a stakeholder-oriented context face performance shortfalls and engage in problemistic search, shareholder-oriented corporate governance in Anglo-American countries provides an alternative, or even an “ideal” type of governance arrangement that can be a solution to mend the performance shortfalls. However, such effect may not apply to all firms depending on the coalitions that influence a firm’s decisions, social proof, and key decision makers’ beliefs and orientations. For example, whether key decision makers are more stakeholder-oriented or shareholder-oriented will influence what kinds of solutions are deemed as appropriate. As for the consequence of governance reform, I propose that a governance reform that is simply driven by problemistic search is less likely to be effective.

I choose the stakeholder-oriented context of Japan because the embedded Japanese culture suggests that a firm is a community for employees rather than assets owned by shareholders and meanwhile part of Japanese firms have engaged in governance reform toward Anglo-American model, such as reducing board size, increasing board independence, and adopting stock option plans. By using Japanese listed firms to test the theoretical model, this project can offer several contributions. First, this study contributes to the literature of corporate governance in stakeholder-oriented contexts by incorporating a new perspective to explain the variation of governance reforms at firm level. Second, this study contributes to governance reform literature by identifying new antecedents of governance reform and identifying contingency that explains why governance reform may or may not be effective. In addition, this project can contribute to the behavioral theory of the firm by identifying governance reform as a possible solution for problemistic search and highlighting stakeholder orientation as an important factor that can influence the search for solutions.


Project Reference No.: UGC/FDS16/H04/22
Project Title: Life course trajectories of drug treatment among middle-aged and older people who use heroin in Hong Kong
Principal Investigator: Dr CHENG Shing (HKMU)


Statistics show that heroin is the most prominent illicit drug in Hong Kong, and most people who use heroin (PWUH) are middle-aged or older (≥ 40 years). However, the majority of current studies on drug use and treatment focus on younger people who use psychotropic drugs. Given that heroin use brings enormous individual and social harm, identifying factors that encourage middle-aged or older PWUH to participate in drug treatment and discourage them from dropping out would be very useful. Nonetheless, this topic has not been comprehensively explored in the Hong Kong context. In addition, while existing studies mainly focused on the treatment experience of PWUH at a particular stage of their lives, there is a lack of studies that examine the treatment trajectories of PWUH over their life course. Treatment trajectory refers to personal history in receiving drug treatment (e.g., treatment initiation, dropping out from treatment, reentering drug treatment after dropping out). To fill these research gaps, following the life course approach and differential association theory, this project describes and explains patterns of drug treatment trajectories among Hong Kong PWUH over 40 years of age throughout their life span. Life course approach explain continuity and changes in people’s experiences and behaviors over their life span. Differential association theory proposes that individuals are deeply affected by their social surroundings, and criminal behaviors are learned through social interaction with peers. More specifically, we explore patterns in the treatment trajectories of PWUH related to why they seek or drop out from drug treatment in different life stages, and how macro historical contexts and micro social environments (within the family, among peers, and in treatment programs) affect their treatment trajectories.

To answer these research themes, a topical life history approach will be used to explore our informants’ experiences as PWUH, focusing particularly on their treatment trajectory experiences. Three research methods will be used for data collection: archival research, in-depth interviews, and focus groups interviews. Archival research will be conducted to collect three types of information: (a) published books and articles, (b) newspapers, and (c) government policy documents and NGO reports. In-depth interviews will be conducted with 60 PWUH aged over 40 years to collect information about their treatment trajectories, as well as the macro historical background and micro social context behind their treatment trajectories. In addition, we will recruit and interview 10 current and retired frontline practitioners, such as social workers, former staff in the correctional services department, and managers of NGOs, to understand how drug policy was implemented in different historical periods. Furthermore, we will also interview 10 older people in the triad gang (in particular those who have long been involved in the street-level drug trade) to understand more about historical events in the criminal underworld. Finally, 20 of the PWUH with whom we will conduct individual interviews will subsequently be selected to participate in five focus group interviews for further data collection.

Finally, to minimize the impact of memory decay and facilitate data collection, two participatory visual research methods will be used—life diagram and photo elicitation. The PWUH will be encouraged to draw life diagrams to record each transition in their treatment trajectory and major events in their lives. The principal investigator (PI) will also show the PWUH a set of historical pictures (e.g., old pictures of treatment facilities, newspaper clips, and drug scenes in different historical periods) and ask them to express feelings and memories related to their drug use trajectories, treatment trajectories, and macro and micro social environments in which they experienced their treatment trajectories.

Overall, this project is both timely and important. Academically, this project explores the relationship between drug treatment trajectories and the micro/macro social context in Hong Kong. On a practical level, the findings identify factors that encourage drug treatment and thereby benefit PWUH, their family members, and society as a whole.


Project Reference No.: UGC/FDS17/H03/22
Project Title: Effect of Music Breathing, a programme based on mindful breathing and music therapy for promoting sense of coherence in young people: A randomized controlled trial
Principal Investigator: Dr CHENG Winnie Lai-sheung (TWC)


The negative impacts of the covid-19 pandemic on public health have affected people socially, psychologically and physically. Individuals worldwide are experiencing unprecedented levels of stress. Long-term stress may lead to psychological and physiological illness. Young people particularly are having to adjust many aspects of their personal lives: including transitions to work, college and independent living. These individuals may find the present situation more stressful than those in other age groups. Personal resources are important in mitigating stress and improve mental well-being during pandemic. Sense of coherence—an orientation to life, could be considered as a personal resource. It reflects an enduring feeling that the internal and external stimuli are structured and predictable (comprehensibility), the resources are available to meet the requirements of the stimuli (manageability), and the problems faced in life are challenges that are worthy of engagement and dedication (meaningfulness).

The proposed study will evaluate the effect of the MB programme on young people’s sense of coherence in promoting coping with stress using randomised controlled trial. A sample of 290 young people (aged 18-30) will be recruited and allocated randomly into one of two groups: the experimental group, which will participate in the MB programme, and the control group. Participants in the experimental group will participate in a 6-week MB programme that will include music therapy and mindful breathing guided by a certified music therapist. Participants in the control group will receive 6 weeks mental health education course. The primary outcome of the study will be measured using Sense of Coherence Scale at week 6 and 4 weeks after completion of the interventions. The secondary outcomes will be measured using the Coping Self-Efficacy Scale, Difficulties in Emotion Regulation Scale, Mindful Attention Awareness Scale, Depression Anxiety Stress Scales, BBC Subjective Well-being scale, respectively, at week 6 and 4 weeks after completion of the interventions. Physiological outcome will be measured with salivary cortisol levels at week 6.

The results will inform practice in coping with stress through promoting sense of coherence. Individuals will benefit from the long-term effect of this intervention to enhance their sense of coherence to cope with stressful events and promote a better mental well-being.


Project Reference No.: UGC/FDS24/H11/22
Project Title: Teaching Undergraduate Social Sciences and Business Writing: Integrating the Reader’s Perspective and Data-driven Teaching and Learning Approach
Principal Investigator: Dr CHEUNG Eric Lok-ming (PolyU SPEED)


This 24-month project integrates content-language integrated learning (CLIL) and data-driven learning (DDL) approaches for teaching advanced academic writing to undergraduate social sciences and business students. This project aims to foster collaboration between language and subject lecturers for elucidating the literacy requirements of the target subjects, and designing language instructional materials for the students to learn the knowledge about both the language and the target disciplines. The DDL approach is motivated by corpus-based language teaching (CBLT). With free, web-based corpus resources and the self-compiled student writing corpora, the researchers aim to facilitate students’ engagement with authentic texts and in corpus-aided discovery activities. The project hypothesises that introducing DDL facilitates students’ understanding of the disciplinary subjects, enhancing their receptive and productive skills, and achieving better academic writing performance in turn. Additionally, the present project targets to raise participants' awareness about the language and grammatical features for interacting with the target readers. This type of corpus-aided discovery learning may also foster students’ language learning motivation, and ultimately learning autonomy.


Project Reference No.: UGC/FDS25/H03/22
Project Title: Design and development of comfortable 3D-printed midsole smart sole shoe to improve older people’s balancing ability
Principal Investigator: Ms CHEUNG Ling (THEi)


The aim of this research is to design and develop a comfortable 3D-printed smart sole shoe to improve older people’s balancing ability.

Fall and fracture in older people are the leading causes of fragility fracture. Research shows that people with sarcopenia are associated with a 4-time increased rate of fragility fracture. Sarcopenia presents poor balancing abilities and a substantial increase in fall risks, making it an important predictive factor of fragility fracture in older people.

Older people have a higher possibility to show signs of imbalance, and fall accidents are common among them. With the growing aging population in Hong Kong, it will become a public health issue in the years to come. Since the changes in foot morphology and the occurrence of foot deformities and foot pain happened in older people frequently, wearing problem-fitting footwear leads to discomfort and risks of unbalance in older people.

Previous literature has reported on the feasibility of smart insoles but the level of comfortability was not fully considered, thus affecting its usability. In 2020, the Principal Investigator conducted a Seed Grant research project, supported by THEi, where a functional 3D-printed midsole design was primarily approved and can provide comfort, aesthetics, and sustainability. As suggested by Scheffler (2004), one important factor for creating a sole is comfortability.

Recently, research is stepping up to produce devices with advanced technology to alleviate the problem, for instance, introducing a smart insole with a fall detection algorithm for daily use by seniors. However, the smart insoles attached with 3D printed midsole have never been developed in the research stage or market. The research showed that older people should be recommended to wear hard-and thin soled shoes to improve foot position. However, comfort aspects likely outweigh safety concerns when older people select their shoes. Thus, 3D-printed midsoles could provide comfort when people use smart insoles. When they wear smart shoes it could detect the fall possibility and also provide fit and comfort.


Project Reference No.: UGC/FDS14/E02/22
Project Title: Early Detection of Cyberbullying Incidents in Chinese-English Code-Mixed Language with Targeted Emotional Colloquial Slang Phrases: A Transfer Learning Approach
Principal Investigator: Dr CHU Carlin Chun-fai (HSUHK)


Cyberbullying has become a global problem with the increasing usage of online social networks in the Web 2.0 era. Its frequent incidence, high propagation, and association with mental health problems underline the importance of imposing prompt intervention so as to mitigate or even stop the harmful impacts on the victims. In Hong Kong, approximately 85% of the total population are active social media users and cyberbullying incidents have been growing in the past few years. Nonetheless, empirical research on cyberbullying intervention in Hong Kong is scarce.

Automatic cyberbullying detection is an expert system of growing importance in the fields of natural language processing and machine learning. Conventional monolingual (English) text-based can provide support for an early detection of potential cyberbullying incidents. However, in Hong Kong, both Chinese and English languages are the medium of communication used in social media platforms. Such bilingual language environment makes the recently developed monolingual early detection system inapplicable. This proposed project will attempt to develop a new expert system for early detection of cyberbullying incidents in bilingual, specifically Chinese-English code-mixed language. The new expert system will address the cyberbullying problems in Hong Kong and nearby regions (such as Mainland China, Taiwan, and Macau) using both Chinese and English languages as medium of communication in social media platforms.


Project Reference No.: UGC/FDS16/E06/22
Project Title: Developing Efficient Behaviour-based Semi-supervised Drivers Status Prediction Algorithm from Small-scale Labelled Dataset
Principal Investigator: Dr CHUI Kwok-tai (HKMU)


Everybody is a road user, pedestrian and/or driver. Road safety is crucial; unfortunately, there are 1.3 million deaths and 50 million injuries caused by road traffic accidents according to the World Health Organization (WHO). Consequently, the losses of lives, disabilities, and pain have accounted for 3% of the world’s gross domestic product. Unfortunately, the significant figures in traffic deaths and injuries are unacceptable and preventable. The WHO and the United Nations (UN) have established a strong collaboration and action plan to halve traffic deaths and injuries by 2030, and the details are documented in the Decade of Action for Road Safety 2021-2030. In the plan, there is a statement on the safe road infrastructure that advanced driver assistance technologies are desired. Typical road accident prevention measures such as education, legislation, planning, and infrastructure, are not effective in reducing the number of traffic deaths and injuries: the numbers have remained steady in recent years. The realization of autonomous vehicles experiences a lot of challenges in the aspects of safety failures, liability, security attacks, cybersecurity, privacy, and artificial intelligence laws. Therefore, it is believed that human-driven vehicles will continue to dominate for the next decades. Automatic monitoring and prediction of drivers’ status via a machine learning algorithm is a promising preventive approach. Attention is drawn to drowsy, distracted, and stressed driving as the most common undesired driving behaviours.

The rationale for the research proposal is related to the limitations of the existing works (i) omission to capture the unique features from individual training samples (behavioural and environmental data associated with each driver) and incorporation into the machine learning model; (ii) limiting the consideration of the requirement on the time for the in-advance prediction. The time of occurrence and the nature of undesired driving behaviours can be varied. The requirements for in-advance prediction models for stressed, drowsy, and distracted driving are non-identical; and (iii) inadequate consideration of the possibility of updating the trained model with newly collected unlabelled data after model deployment. The model can be updated for performance enhancement with newly collected unlabeled data after deploying the model.

Three project objectives are defined to address the abovementioned limitations: (i) extract common and individual features from an individual’s driving behavior and environment factors to facilitate a better prediction model; (ii) design and develop a prolonged in-advance prediction algorithm for driver status, particularly on the research for the distinct requirement of the time range for stressed, drowsy, and distracted driving prediction models; and (iii) enhance the performance of prediction model with the availability of new unlabelled data using an incremental semi-supervised learning algorithm.

Realization of the objectives addresses the current research limitations by offering a more accurate and flexible model to predict future driver status and thus prevent the occurrence of undesired driving behaviour and traffic accidents when the model is deployed in practice. Early warnings and precautionary actions can be executed. In addition, the research promotes the solution of advanced driver assistance technology using a machine learning model to automatically monitor and predict drivers’ status. It also contributes to the decade of action on reducing road traffic deaths and injuries.


Project Reference No.: UGC/FDS16/E02/22
Project Title: A Study of Distributed Service-aware Wireless Cellular Networks (DS-WCNs): From User Demand Modeling to Performance Optimization
Principal Investigator: Dr FU Yaru (HKMU)


Owing to the increasing popularity of online social media, smart cities, and new artificial intelligence-based applications, end users can access data-intensive services more conveniently than ever before. However, the accompanying huge amount of data traffic induces severe network congestion, despite that the sixth generation of wireless communication network (6G) is expected to be more reliable, fast, and can support plenty of intelligent applications with ultra-low latency requirements. To cope with this challenge, the deployment of computing and storage resources at network edges provides a promising enabler. Meanwhile, the new paradigm for composing services/applications as a suite of small and independent micro-services (MSs) is leading to cases where functional units can be distributed over edges. As a result, far edge computing and caching are pushed to the very edge of the network, accelerating the transition of telecom architecture towards distributed (micro)service-based architecture. Specifically, by placing various MSs at the edge servers (ESs), such as base stations, and access points, effective networks with reduced delay, high scalability and increased responsiveness can be realized.

In such distributed (micro)service-enabled wireless cellular networks (DS-WCNs), each large and bulky service is composed of a set of independent MSs with each MS fulfills a particular aspect or function. The successful execution per service is highly dependent on the successful execution of each associated MS. Moreover, the ESs therein are more likely to be heterogeneous. Namely, each ES has different storage capacity, computing power, execution cost, and setup cost with respect to different MSs. In this regard, sophisticated management towards the heterogeneous edge resources and the placement of different MS instances among the ESs are highly required to minimize the aggregated cost. Another major issue to be resolved in DS-WCNs is the user’s demand pattern, as it exhibits a critical impact on the actual MSs placement in the DS-WCNs, which in turn affects networks’ performance. On one hand, the number of users is large. On the other hand, the demand behavior is not easy to characterize, particularly when the users’ individual feature information is not known a prior.

In this project, we first characterize the user demand behavior to different services, taking into account the screen size constraint. Thereof, the system chooses an assortment of services, showing them on users’ devices, aiming at maximizing the achievable revenue based on users’ service selections. Then, we will design the MSs placement algorithms for DS-WCNs with the consideration of the heterogeneity among different ESs under the given assortment decision for users. Afterwards, we will design the joint assortment decision and placement algorithms to maximize networks’ effectiveness, such as achievable revenue or aggregated cost saving capability considering users’ screen size and latency constraints, successful service execution, as well as ES’s storage capacity budget and execution capacity budget.

In a nutshell, this project aims to provide high-effectiveness DS-WCNs, covering from the fundamental analysis of user demand modeling, to the joint assortment decision and placement optimization algorithms. Due to the distinct nature of foregoing problems, in the design of the corresponding solutions, different models include revised multinomial logit choice model, optimization model, reinforcement learning model, and neuro network model will be used. All the investigations are collectively used to reap the benefits of DS-WCNs. Besides, the designed schemes will be validated by extensive numerical simulations under both synthetic and real datasets. Moreover, the developed solutions in this project will be applicable in 6G era, which benefit not only cellular networks but also end users. From network operators’ perspective, the overall costs (e.g., transmission, setup, and execution cost) can be reduced. For users, they can enjoy high quality data-oriented services.


Project Reference No.: UGC/FDS24/H03/22
Project Title: Street Audiences Feel the Same as Street Performers? A Psychological Approach
Principal Investigator: Dr HO Robbie Ming-hon (PolyU SPEED)


Street performance is performing or entertaining in a public space with the intention of seeking voluntary donations from passersby. Street performers are people conducting street performances. Street audience are the audience or spectators of a given street performance. Street performance has attracted scholarship across different disciplines, but little attention has been paid to the street audience. The psychological mechanisms underlying the audience’s reactions in experiencing street performance have remained largely open to investigation.

Do street audiences feel the same as street performers? Put differently, what is the level of agreement or disagreement between the audience’s and the performer’s experiences regarding a given street performance? Besides, what might be the psychological consequences of their shared experiences? And what might be the anteceding factors influencing those shared experiences?

Street performance is supposed to benefit the perception of public space. But despite its proven social and cultural values, street performance remains challenged in its legitimacy in real world. From a psychological viewpoint, the street audience might simply not feel the same way the street performers had intended, regardless of the performers’ good intentions.

Drawing on the recent research paradigm in the psychology of aesthetics and arts, we propose a framework of performer–audience shared experience (SSAE) comprising six SSAE factors: shared emotion, intellect, novelty, place, interaction, and technique. We hypothesize two behavioral outcomes of SSAE – the audience’s overall liking and donation intention. We also hypothesize two causal factors affecting SSAE – essentialist place and cultural match. Essentialist places have historical and distinctive features (e.g., a heritage site), whereas anti-essentialist places have modern and generic features (e.g., a pedestrian street). Cultural match is the situation where the audience watches a street performance conducted by a performer from the same culture, whereas cultural mismatch is where the performer is from a different culture relative to the audience.

To empirically evaluate the proposed framework, we will conduct two studies. Study 1 is a field study in Hong Kong, where street performers and street audiences will be surveyed on-site. Study 2 is a cross-cultural laboratory experiment between Hong Kong and Lublin, Poland, where a 2 × 2 × 2 between-subjects design will test the effects of the audience’s cultural background (Hong Kong vs. Polish), (anti-)essentialist place, and cultural (mis)match on SSAE. Hong Kong and Polish participants will be randomly assigned to viewing and evaluating videos of either Hong Kong or Polish street performances, in either essentialist or anti-essentialist places.

Theoretically, the proposed research updates the existing frameworks concerning the audience’s experience of street performance while engaging with the psychology of aesthetics and arts, environmental psychology, and cultural psychology. Practically, findings of this research can inform practitioners of street art and policy makers about the regulations of street performance.


Project Reference No.: UGC/FDS13/E01/22
Project Title: Automatic multiple level gum disease detection based on deep neural network: algorithm and system
Principal Investigator: Dr HSUNG Tai-Chiu (Chu Hai)


Background: Gum disease is one of the most prevalent plaque initiated dental diseases. Although most patients brush their teeth every day, they cannot keep all their teeth clean. Areas in the mouth that are difficult to access, such as crowded areas, posterior teeth or interdental areas, are usually affected. After a thorough professional tooth cleaning, dental plaque will begin to accumulate on the tooth surface near the gum edge within a few days. Clinical studies indicating that regular disruption to the plaque is needed so can prevent and arrest gum disease. However, dental diseases may take years to develop, patients usually do not have any pain and symptoms unless the disease have progressed to the advanced stage. Significant resources have been used to motivate patients to keep their mouth clean but the results are not satisfactory. Automated technique is therefore desirable for monitoring oral health daily so the patients can seek for treatment when it is needed.

Key issues: Patients’ response to plaque accumulated at the gum margin is by inflammation which brings more blood cells to the site to fight against the bacterial invasion. Inflammation of gum is manifested as an increase in redness (color), an increase in volume (oedema), and loss of surface texture characteristics. These affected areas can be identified by visual inspection with the dentist during the consultation or using intraoral photography. This requires professional dental training but the results often show significant variability among dentists which means low repeatability.

Objectives: The objective of this research is to apply deep neural network technology to detect gum inflammation and its continuous monitoring accurately from intraoral photos.

Problem: From preliminary study with 447 standard intraoral photographs, of which 337 image samples were used for training and 110 images for validation, it is found that the decoder-encoder based deep neural network approaches can fairly identify the inflammation area. However, the predicted results were not consistent under small image transformations such as shifting, scaling and rotation. It is not of sufficient quality to enable inflammation status monitoring over time.

Plan: We plan to have an extensive study of deep neural architecture to deliver automatic inflammation detection with high sensitivity and specificity. and we will further collect 1200 cases of standardized intraoral photography for better neural network training.


Project Reference No.: UGC/FDS15/H19/22
Project Title: Understanding the new solidarities and public roles of transnational Chinese Buddhist organizations by movement organization theory
Principal Investigator: Dr HUANG Weishan (Shue Yan)


The aim of the proposed qualitative research is to study the theoretical debate about religious transnationalism through looking at transnational practices and groups (here referring to their sustained linkages functioning across nation-states). By studying transnational religious organizations, this project will focus on the following objectives. (1) First, this project aims to not only study Buddhism as an immigrant religion, but also study its transnational solidarity. The function of immigrant religion could include the role of religion in immigrants’ socio-economic integration trajectories and the religious aspects of transnational migrant networks. The proposed research will also study the features of global Buddhist evangelism in the context of the two proposed transnational Buddhist organizations. (2) Second, the research will update our understanding of the cultural identity and solidarity of overseas Chinese. The project will inform the necessary know-how involved in the organizational sustainability of transnational organizations and the changing identities of ethnic-Chinese in Hong Kong, China, and other overseas Chinese societies.


Project Reference No.: UGC/FDS16/H02/22
Project Title: Ekphrasis in Hong Kong Poetry in English: Late 1970s to Early 2020s
Principal Investigator: Dr HUEN Pak-hang (HKMU)


Ekphrasis, an ancient Greek term for ‘description’, is now commonly used to refer to poetic descriptions of works of visual art. According to the online Oxford English Dictionary, ekphrasis is now specifically ‘a literary device in which a painting, sculpture, or other work of visual art is described in detail’. Studying the oeuvres of a representative number of poets writing in English from or in Hong Kong, this project focuses on these poets’ ekphrastic work. It determines, analyses and contextualises their ekphrastic engagements with a range of works of visual art, in particular, those from/ or about Hong Kong and mainland China.

The project benefits from the global recognition of creative writing in English as an academic discipline, the digital age, and the local popular museum and visual culture, and is conceived in a group of literary, critical, and theoretical contexts. There has been a long-standing tradition of modern poets’ engagements with ekphrasis, which has continued and evolved in the 21st century. Poetic ekphrasis has been growing in amount and variety at an unprecedented rate. Meanwhile, critical accounts of poetic ekphrasis have shifted from understanding ekphrasis as staging competitions between words and images to highlighting a range of themes with regards to our reception of the visual arts. These themes, the project argues, can include the city of Hong Kong itself, in the light of the emergence of poets writing about Hong Kong through ekphrasis.

The term ‘Hong Kong ekphrasis’, in line with an increasing amount of theoretical notions regarding ekphrasis, such as ‘photographic ekphrasis’ and ‘biographical ekphrasis’, is proposed and used to understand a unique kind of ekphrasis as seen in the works of those writing from, in, and/or about Hong Kong. Oriented by the proposed term, the mixed-methods research project is driven by literary criticism, which involves in-depth analysis of the selected poems with the uses of critical, historical and theoretical accounts, as well as varied research methods, namely, interviews with the poets, observations of their social media activities, and the principal investigator’s reflections on his own ekphrastic poems.

The project aims to increase and challenge our understanding of (1) the close connections between Hong Kong poetry in English and the visual arts since the late 1970s, (2) the factors in the continuation and evolution of these connections, (3) the potential of ‘Hong Kong ekphrasis’ in the critical and theoretical studies of poetic ekphrasis, (4) the nature and scope of Hong Kong poetry, Hong Kong literature, and Chinese literature. The project, in achieving these overriding aims, will also cast light on the role of Hong Kong in the growing and widespread interest in Chinese art and culture.


Project Reference No.: UGC/FDS41/H01/22
Project Title: Examining the contributions of parental language input quality to young children’s executive function, oral language skills and listening comprehension development: A longitudinal study
Principal Investigator: Dr HUNG On-ying (YCCECE)


Listening comprehension (i.e. oral language comprehension at discourse level) is essential for learning, literacy acquisition and social interactions. Children with poorer listening comprehension in early years were found with poorer writing and reading performance later at school (e.g. Kent & Wanzek, 2016). However, prior studies have primarily focused on the contribution of listening comprehension to reading development. Rather, fewer studies have investigated the development of listening comprehension in the early years. The question on how variation in the socio-ecological environment and individual cognition explains the differences in listening comprehension development has remained unclear. The proposed study, therefore, has a major goal of addressing the literature gap by examining factors that contribute to the individual differences in the early development of listening comprehension. More specifically, the proposed study will examine the direct and indirect effects of individual factors (i.e. executive function, oral language skills) and socio-ecological factor (i.e. the quality of parental language input) on listening comprehension among young children by using a longitudinal design. If early development of listening comprehension could lead to a profound impact on later reading and writing development, understanding how listening comprehension in early years develop could have potentials for interventions not only to improve children’s listening but also literacy acquisition (Kim & Pilcher, 2016).

Furthermore, listening comprehension is an important precursor to successful reading comprehension (Kim, 2020), and related to school achievement as a vehicle of learning. Therefore, a better understanding of the development of listening comprehension can inform parents and teachers with effective strategies to promote this ability in the early years; for instances, strategies in shared book reading, and pedagogical approaches. The findings could also provide evidence for teacher education by demonstrating the developmental process of listening comprehension in early years.

One hundred and six pairs of parents and children aged 3 years will be recruited from 9 kindergartens in Hong Kong using stratified sampling method. The parent-child dyad will be assessed at two time points, 9 months apart. At each time point, the parent will be invited to have parent-child activities with their children. The quality of parental language input recorded will be measured and analyzed. At both time points, the children will also be assessed on a series of measures including measures of executive function, oral language skills and listening comprehension. The data will be used to fit with the hypothetical model. The goal is to find out the explanations for the individual differences in listening comprehension development.


Project Reference No.: UGC/FDS24/E11/22
Project Title: Numerical and Experimental Investigation of the Combustion and Emission Characteristics of Low to Medium Calorific Value Landfill Gas Blended with Hydrogen
Principal Investigator: Dr KAHANGAMAGE Udaya Priyadarshana (PolyU SPEED)


Landfill gas (LFG) is a natural by-product of the biodegradation of organic wastes in a landfill site, and it is legally considered to be a waste. It contains methane (CH4) which is a hydrocarbon fuel with a high calorific value of 55.5 MJ/kg, and other inert gases such as CO2 and N2. The composition of the LFG varies widely depending on the design, age and deposited content of the landfill sites. When the LFG contains a high fraction of CH4 (>40 vol%), it can directly be used for power generation and heating applications as an effective renewable fuel. It is also used to produce synthetic natural gas through purification processes. However, when the LFG contains a low concentration of methane (<40 vol%), it is generally not economical or suitable for such applications. Currently, there are two methods commonly employed to manage the low-quality LFG; (i) controlled venting to the atmosphere and (ii) pumped extraction and flaring. Venting to atmosphere poses a greater impact on the environment as methane is a potent greenhouse gas with 28-34 times more global warming potential of CO2. Flaring helps reduce the environmental impact. However, it is a waste of energy. It is important to find ways to utilise this renewable source of energy to enhance the supply of sustainable forms of energy for future energy needs.

There is a potential to utilise low to medium calorific value LFG with 20 – 40 vol% CH4 for the process heating needs of industries. However, the presence of a high percentage of inert gases in low to medium calorific value LFG presents a challenge for maintaining stable combustion as required for practical applications. In particular, the high percentage of CO2 could result in unstable flame, blow-off, and production of harmful emissions. In order to minimise those problems and to enhance combustion performance of LFG, flame stability must be improved, and flammability limits expanded. Fuel enrichment techniques with high quality fuel can be used to achieve those requirements. Currently, there are limited research studies on the combustion of low to medium calorific value LFG using fuel enrichment techniques. The proposed project aims to have a better understanding of combustion, thermal and emission characteristics of LFG with low to medium calorific value and explore the potential of hydrogen enrichment technique to produce stable combustion. The hydrogen is selected as the potential enrichment fuel because of its future potential as an environmentally friendly source of energy, clean combustion, and high heating value (120-142 MJ/kg). The combustion and emission characteristics will be investigated numerically using CHEMKIN by applying the GRI-Mech 3.0 reaction mechanism and experimentally using various standard methods such as constant volume combustion bomb with schlieren photography, heat flux method, and pollutant emission measurement techniques. The effect of different compositions of diluents in the LFG and hydrogen enrichment will be investigated fully. The outcome from the project may enhance the fundamental knowledge of combustion, thermal and emission characteristics of hydrogen-enriched low to medium calorific value LFG and pave the way to design combustion systems to better utilise low-quality LFG as a renewable source of energy while reducing harmful emissions to the atmosphere.


Project Reference No.: UGC/FDS24/E18/22
Project Title: Development of Artificial Intelligence based Predictive Tool for Knee Magnetic Resonance Imaging Assessment: A Domain Adaptation Perspective
Principal Investigator: Dr KHAN Sheheryar (PolyU SPEED)


Clinically Magnetic Resonance Imaging (MRI) is widely utilized to assess the internal disorders of the knee, especially in tissues such as cartilage, bone, menisci and ligaments. Since the joint shape and tissue degenerations have a strong influence on knee related injuries and diseases, therefore non-invasive characterization of these features by MRI is valuable for disease diagnosis as well as planning therapeutic procedures. These investigations from MRI using manual delineation of knee tissue is time consuming and can be impractical when processing large cohorts in routine clinical applications. There is a pressing need to develop automatic machine intelligence-based imaging tools offering predictive outcomes that provide morphological and compositional insights to facilitate the understanding of disease as well as interpret insights from images timely and effectively. To this end, we propose to develop artificial intelligence (AI) based tool that can process a large cohort of MRI scans and generate an assessment record of knee anatomy with various morphological features along with 3D visualization of knee bone and tissue’s structure. The assessment record can further be processed to facilitate the practitioners to make decisions along with initial indications of predictive elements.

Deep convolutional neural networks (CNNs) have gained much popularity in computer vision society for cracking complex problems, however, in knee MRI the availability of suitable labelled data is a key factor that limits its direct application. Another common issue with supervised methods is their adaptability to newly acquired data in different domains. Usually, the data set used to train CNNs algorithms to come from the public datasets that are acquired in specific control settings, when it comes to testing the model on unseen unique samples from other domains (with different vendors and different acquisition protocols), the CNNs methods fail to adopt those changes and results in incomplete segmentation. The major concern in developing AI-based system in knee MRI is to mitigate the generalization problem or domain adaptation that arises with qualitative diversity among examinations and vary in imaging protocols, subjects, and hardware.

We argue that the self-supervised method with domain adaptation can be useful to solve this issue and benefit the knee MRI segmentation with better generalization abilities. To this end, we present an adversarial learning-based self-supervised segmentation approach that addresses the above-mentioned challenges in an unsupervised manner and provides a reliable estimate of favorable knee segmentation without user intervention. In our preliminary study, we have implemented and tested our idea on knee MRI data that features the knee MRI scans from the separate domains with different imaging protocols as well as vendors. The initial segmentation results show that the proposed method addresses the problem of tissue segmentation quite well. However, further experimental study is required to implement full pipeline and test on benchmark datasets as well as independent datasets to validate the segmentation. The segmentation from knee tissues serves the initial purpose of tissue region segmentation with domain adaptation perceptive. For the assessment module, we aim to establish model assisted interpretation. The module will be capable of processing the segmentation and producing the relevant clinical information such as (thickness measurements in 2D and 3D, abnormalities in meniscus such as tears, degradation in cartilages such as cartilage loss, etc). The information collected will be used to establish the domain invariant assessment along with 3D rendering of the knee structures. The automated assessment will be further compared with the benchmark gold standards, and thorough validation procedures will be conducted. Improvements will be made by exploring further key clinically relevant features by extracting and manslaying the radiomics features. The outcomes will be presented in terms of a compact tool that possess both qualitative as well as quantitative assessments of the knee MRI independent of the acquired domain.


Project Reference No.: UGC/FDS14/B12/22
Project Title: What Really Matters in Achieving Team and Individual Innovative Performance in Different Cultures: Innovation Leadership, Creative Collective and Self-Efficacy, and Initiative Climate
Principal Investigator: Dr KONG Hao (HSUHK)


Recognizing that “creativity and innovation are the foundation of organizations’ competitive advantage” (Acar, Tarakci, & Van Knippenberg, 2019, p. 96), this proposal aims to develop an integrated and multi-level model to understand why and how team members engage in individual innovative behaviors as well as in group innovation. We further examine the influence of leadership behaviors, organizational initiative climates, and creative efficacy beliefs on the innovation process. Specifically, we examine whether innovation leadership – involving three blocks of behaviors (incubation, advocation, and execution) that match with the three stages of the innovation process – can promote individual and team innovation through cultivating team members’ creative thinking self-efficacy (CTSE), creative performance self-efficacy (CPSE), creative thinking collective-efficacy (CTCE), and creative performance collective-efficacy (CPCE). In addition, we argue that culture differences play a role in the development of creative efficacy as in collectivist cultures, creative collective-efficacy may determine the development of creative self-efficacy, whereas such influences may not be found in individualist cultures.


Project Reference No.: UGC/FDS17/M06/22
Project Title: Effects of transcranial direct current stimulation (tDCS) on cognition in older adults with mild cognitive impairment: A randomized controlled trial
Principal Investigator: Dr KUO Michael Chih-chien (TWC)


Mild cognitive impairment (MCI) is considered an intermediate stage between normal cognitive aging and dementia. As such, improving cognitive functions of people with MCI may delay dementia onset. In recent years, transcranial direct current stimulation (tDCS) has become a commonly used brain stimulation method. Accumulating evidence indicates the promising effects of cognitive enhancement after tDCS over the frontal scalp regions. However, previous studies had methodological limitations. In addition, knowledge of the precise physiological consequences of tDCS on the brain tissue and related neural mechanisms in people with MCI remains rudimentary. The objectives of the proposed study, which will target people with MCI, are to investigate the effects of tDCS at the left dorsolateral prefrontal cortex on the cognitive performance and to explore the modulation of neural mechanisms associated with the use of tDCS. Forty-eight MCI participants aged 50–80 years will be recruited. All participants will be assessed by Hong Kong version of Montreal Cognitive Test. Participants that meet selection criteria will be invited to the experiment. They will be assigned to experimental or control groups randomly. The experiment will consist of pre- and post-assessments and a 1-month follow-up assessment. Between pre- and post-assessments, participants will receive 8 sessions (2x/week for 4 weeks) of tDCS treatment (either real or sham, 20 min per session). Outcome measures include digit span, colour trail test, verbal fluency test, Chinese version of the Verbal Learning Test, and Hong Kong version of Montreal Cognitive Assessment. Participants will also complete a computer memory task at each assessment point (performance in this task is also used as an outcome measure) and will have their brain wave recorded while completing the task. The study is innovative in that it will investigate multiple domains of cognition (e.g., attention, memory, executive function), the sustainability of the effects and include electroencephalography as an outcome measure. The results of this proposed project are expected to have an impact on the long-term care and rehabilitation of older and clinical populations (e.g., MCI, dementia) and to increase general knowledge about tDCS and related cognitive enhancement in MCI.


Project Reference No.: UGC/FDS17/H04/22
Project Title: The effectiveness of an e-health brisk walking intervention in increasing moderate to vigorous physical activity in physically inactive older people with cognitive frailty: A randomised controlled trial
Principal Investigator: Prof KWAN Yiu-cho (TWC)



Cognitive frailty is common in community-dwelling older people and is an at-risk state for adverse health outcomes such as dementia, dependency, and mortality. Fortunately, cognitive frailty is reversible, with a higher probability of reversibility at earlier stages. Physical activity is known to play a significant role in reversing cognitive frailty; its effect is moderated by intensity and sustainability. However, physical inactivity is very common in older people and is one of the key phenotypical characteristics of cognitive frailty. Moderate to vigorous physical activity (MVPA) can reduce the risk of worsening cognitive frailty. Brisk walking is a simple form of exercise that can be practised by community-dwelling older people every day to boost their physical activity to or above a moderate intensity level. Conventional behavioural change interventions (CBCIs) have been shown to effectively engage sedentary older people in physical activity, but their effect size is small. The use of e-health methods that adopt existing and popular e-platforms (e.g., Samsung Health and WhatsApp) to promote specific behaviours (e.g., regular brisk walking) in specific groups (e.g., older people with cognitive frailty) is an innovative, practically feasible and theoretically sound method of increasing MVPA. However, the relative effectiveness of e-health interventions and CBCIs in vulnerable groups (i.e., older people with cognitive frailty) is unknown.


The proposed study will compare the effectiveness of an e-health intervention with that of a CBCI in (1) increasing MVPA, (2) reducing cognitive frailty, (3) promoting cognitive function and (4) improving physical performance in older people with cognitive frailty.


A single-blinded, two parallel group, randomised controlled trial will be conducted in a community setting. Subjects will be recruited from five elderly community centres in Hong Kong. The eligibility criteria will be as follows: (1) aged ≥ 60, (2) cognitively frail, (3) physically inactive and (4) possessing a smartphone. The participants in the intervention group will receive an e-health intervention. Those in the control group will receive a CBCI. Each intervention will last for 14 weeks. The outcomes will be MVPA min/week (primary), as measured by a wrist-worn ActiGraph; cognitive frailty, as measured by an ordinal scale; cognitive function, as measured by the Montreal Cognitive Assessment; and frailty, as measured by the Fried frailty phenotype (FFP). The outcomes will be assessed at T0 (baseline), T1 (immediately post-intervention) and T2 (6 months post-intervention). We plan to recruit 192 subjects. Permuted block randomisation with randomly selected block sizes in a ratio of 1:1 will be used. Only the outcome assessors will be blinded. Four generalised estimating equations will be used to test the effects of the interventions on the four outcomes, which will be the dependent variables. The independent variables will be group, time and [group] x [time]. The level of significance will be set at 0.05.


If the e-health intervention proves to be more effective and sustainable than the CBCI, we will have evidence suggesting that e-health interventions can replace CBCIs in promoting MVPA and treating cognitive frailty in older people in community settings. Further studies could then examine the potential role of e-health interventions in delaying the onset of dementia and dependency.


Project Reference No.: UGC/FDS24/B06/22
Project Title: Value Statements are More Than a Buzzword: Impact of Green Value Statement and Employee Green Values on Financial Performance and Employee Green Behaviors via Green Human Resource Management
Principal Investigator: Dr KWOK Man-lung (PolyU SPEED)


Recent headlines that appeared in many international news reports are about global warming, greenhouse gases, Antarctic ice sheets melting, etc., and all these were attributed to human industrial activities (BBC, 2021). Therefore, governments in different countries are becoming aware of environmental and sustainability issues. Previous studies have put a lot of effort into corporate social responsibility, sustainability, and ESG topics. One of the lines of research in human resource management is green human resource management (Green HRM). Green HRM research has been blooming, and at the same time, it leaves a lot of unanswered questions that await researchers to deal with.

First of all, much previous research on Green HRM only focused on identifying simple antecedents or outcomes (Ren, Tang, & Jackson, 2018). However, discussing the trickling down effect of how the organization green value statements affect their Green HRM practices is very little. Thus, the current study tries to incorporate the strategic component, that is, the green value statements of the organization to link up with Green HRM practices, suggesting that the strategic process of values should have impact on any company policies or strategies, as illustrated by Green HRM practices.

At the same time, according to ability-motivation-opportunity theory (Boselie, Dietz, & Boon, 2005; Katou & Budhwar, 2010), Green HRM practices should have impact on organization financial performance and employee green behaviors (as measured by organizational citizenship behaviors towards the environment). Previous studies on Green HRM suggested that there is a need to collect different sources of data. Thus, our current paper tries to collect organization financial performance based on the actual financial performance in the reporting period published in the annual report.

Finally, based on the supplies-values fit theory (Edwards, 1996, 2007), when organizations supply the green values which are congruent with the employee individual green values, the fit or congruent situation will be achieved, and the impact on the employee attitude and behaviors can be strengthened. Thus, this study will examine the importance of individual green values, arguing the congruent should not be ignored in achieving green outcomes of the organizations.

This study contributes to the Green HRM and sustainability literature by enriching the research methodology and conceptualization of Green HRM. Specifically, this study examines the impact of organization green value statements (or green values) on Green HRM practices implementation and further the impact on employee green behaviors and financial performance. So far there is very little research in the Green HRM literature or strategic management literature discussing the trickling down impact of the value statements. Moreover, the results of the current study can further provide practical suggestions to companies on formulating the Green HRM practices and conveying the importance of having shaped the individual employees values to include green component. Again, this can be done by the training programmes carried out in the organization.


Project Reference No.: UGC/FDS15/H06/22
Project Title: The effect of abnormal structural and functional resting-state connectivity in prefrontal cortex and increased exposure to traffic-related air pollutants on schizotypy
Principal Investigator: Dr LAM Yin-hung (Shue Yan)


Background: Schizotypal personality traits (schizotypy) increase the risk of schizophrenia, thereby increasing the burden on the healthcare system. Mounting evidence has found reduced prefrontal cortex (PFC) gray matter volumes (GMV) and abnormal resting-state functional connectivity (rsFC) in schizophrenia. Additionally, exposure to increasing levels of traffic-related harmful pollutants (TRAPs), particularly nitrogen dioxide (NO2), is found to have a detrimental impact on schizophrenia. Furthermore, reduced prefrontal GMV and rsFC in schizophrenia is associated with exposure to these TRAPs. However, the mediation effect of environmental factors on schizotypy via PFC correlates remains unanswered.

Pilot findings: In 104 youth, exposure to NO2 levels was significantly and positively related to schizotypy after controlling for covariates.

Aims: This study aims to examine the relationship between environmental factors (NO2) and neural correlates (PFC GMV and rsFC) of schizotypy, and the mediation effect of NO2 on schizotypy via reduced PFC GMV and rsFC with a two-year longitudinal research design. Method: 130 non-clinical participants and 30 clinical patients with psychosis will be recruited from the PI’s cohort study. Sociodemographic information, psychosocial variables (e.g., loneliness and physical activity), behavioral and environmental estimates, as well as structural brain scans using magnetic resonance imaging will be assessed at baseline and one-year and two-year follow-ups. The primary behavioral assessment includes the Schizotypal Personality Questionnaire, which measures schizotypy. Environmental assessments include neighborhood-based estimates (e.g., greenspace density) computed within a radius of 300 meters surrounding the participant’s home. Estimates of individual exposure to TRAPs will also be measured. These data will be measured at four time-points in two years in order to control for any potential temporal variations due to seasonal change.

Predicted results: Both exposure to NO2 levels and PFC GMV and rsFC are hypothesized to predict levels of schizotypy respectively after controlling for covariates. Moreover, exposure to increased NO2 levels is hypothesized to predict reduced PFC GMV and rsFC and higher levels of schizotypy at the one-year and two-year follow-ups respectively while there will be no significant changes in these two variables for those with a lower level of NO2 exposure. Furthermore, more exposure to NO2 at baseline is hypothesized to predict smaller PFC GMV and reduced rsFC, which in turn lead to higher levels of schizotypy at the one-year and two-year follow-ups. These effects are predicted to be more significant in the high schizotypy individuals.

Implications: Hypothesized findings, which could show the mediating effect of increased NO2 exposure on schizotypy via reduced PFC GMV and rsFC, will have both theoretical and clinical implications. For instance, policymakers may adopt environmental measures to reduce NO2 emissions in Hong Kong in order to enhance prefrontal functioning and reduce schizotypy in youth, thereby preventing them from developing schizophrenia spectrum disorders.


Project Reference No.: UGC/FDS24/B07/22
Project Title: Rebuilding Port and Resilient Maritime Supply Chain Networks in Asia
Principal Investigator: Dr LAU Yui-yip (PolyU SPEED)


With the cancellation of sales and shipping contracts and economic contraction, late delivery of goods, and emergencies in response to the COVID-19 pandemic, global importers, exporters, and the tourism sector have all been significantly affected. The Greater Bay Area (GBA) in China and Association of Southeast Asian Nations (ASEAN) ports as the strategic intermodal connectors for maritime supply chains are no exception. Ports and maritime supply chains have done a magnificent job in business continuity. Yet, they have been affected by and contributed to a broad range of issues, including: (1) port traffic reduction, (2) challenges in conducting operations such as manual paperwork and dock works, (3) hinterland accessibility such as truck driver shortages, (4) the buildup of empty shipping containers and storage of perishable goods, and (5) practicing/supporting risk control measures. The wide range of maritime supply chain stakeholders, highly complex port and maritime supply chain operations, and port authorities are important factors for risk managers to take into consideration. They must consider the interaction among these factors to avoid the silo approach when devising/implementing new measures, especially with unprecedented risks, to enhance resilience. This would result in an acceptable level of resilience of the ports and maritime supply chains as a whole, rather than imbalanced and localized efforts to support the related people, processes, and systems. It is challenging to predict the long-term economic effects of the pandemic considering the involved immense uncertainty. However, exploring the short-term effects, vulnerable actors, activities, and systems are imperative. Here, resilience is defined as planning and preparing for changes, and absorbing, recovering from, and adapting to them. Therefore, it is critical to evaluate implemented/potential resilience-building measures (risk prevention and reduction controls) and determine the resilience level of the port and maritime supply chain. The very definition of resilience has changed due to the ongoing COVID-19 pandemic. Therefore, a new project is needed to address this research gap.

This 24-month study investigates the state of port and maritime supply chain resilience in the face of a pandemic by developing a Decision Supporting System for Port Pandemic Resilience (DPPR) and a practical Port Pandemic Resilience Index (PPRI). The system and the index are based on general port and maritime supply chain operations. After that, they are calibrated and quantified for eleven major ports in the GBA and nine major ports among the ASEAN nations. Additionally, we will conduct a complex network analysis to understand the connectivity among the maritime supply chain networks and ports in the GBA and ASEAN countries, their properties and structure within the context of pandemics, including COVID-19 itself. This offers a better outlook on the resilience of ports and the maritime supply chains in the emerging markets and mobilizes knowledge between them. It should be noted that the ports of interest are among the world’s busiest ports with direct connections to major global and regional markets. As such, the Institute of Seatransport and Hong Kong Sea Transport and Logistics Association are willing to provide the required data and support for the twenty selected ports. As mentioned above, the specific outcomes are: (1) theory and research methods in the context of port and maritime supply chain resilience, and disseminate findings in scientific and professional publications, webinars, and conferences; (2) a visually accessible, extendable, and updatable DPPR that is holistic in approach; (3) a PPRI; (4) networks with Chinese and ASEAN port authorities to enhance future communication and goal-oriented research and development; and (5) the mobilization of knowledge with Chinese and ASEAN ports in response to the pandemic.


Project Reference No.: UGC/FDS16/E10/22
Project Title: Development of Smart Analytic System with IoT Technology for Renewable Energy Feed-in Tariff in Suburban Agricultural Area
Principal Investigator: Dr LEE Chi-chung (HKMU)


Global warming is an important issue in the world during the last several decades. The major cause of global warming is the excessive carbon emission after the Industrial Revolution. Among the various sources of carbon emission, the electricity generation in power plants is the most serious origin in many countries and regions like Hong Kong. Therefore, in order to avoid further global warming, environmental protection policies like Carbon Neutral 2050 are agreed among most of countries and regions in the world. To achieve these goals on environmental protection without affecting the human being’s quality of life, the renewable energy should be adopted in a large extent on electricity generation. Among various renewable energies, solar and wind power are the choices available in most areas. However, these two types of renewable energy required a lot of land resources. A power company itself cannot raise the fuel-mix to a significant level without the involvement of land owners. Therefore, numerous governments or official organization introduced the feed-in tariff scheme to encourage the general public to produce solar and wind power by using their own land resources. It is because the general public can sell the renewable power generated to the power company at a rate higher than the normal electricity tariff rate to help recover the costs of investment. Nevertheless, the rate of participation is still low as the cost recovery period is still low. Recently, low-cost IoT systems to enhance the efficiency of renewable energy generation in the rural residential area and high-rise building have been proposed and demonstrated. However, the prospect of increasing the fuel-mix is still not optimistic as only a small portion of land resources is used even rural residential area and high-rise building are involved. To increase the fuel-mix significantly, the agricultural area should be used. Nevertheless, the problem of food shortage in view of the increasing population is also a crucial issue. The use of agricultural area for generation of renewable energy forms a competition with the food production. As a result, the optimized combination of agricultural activities and solar photovoltaic power generation, called agrivoltaics, was proposed and analyzed recently. However, the current researches on agrivoltaics mainly focus on the large-scaled agricultural areas with open and wide environment. There are only a few analytical results on the closed agriculture. In view of the suburban agricultural areas, like the small-scaled farms located at New Territories in Hong Kong with microclimate nearby, there is still no such deep investigation on it. Moreover, there is no smart analytic system integrated with agrivoltaics and wind power which is the real feed-in tariff scheme used in the developed cities like Hong Kong.

To address above problems, this research will first establish and validate the two smart IoT systems with numerical models in the small-scaled agricultural areas with microclimate to measure and control (i) the status of the farm, its crops and livestock, and (ii) the feed-in tariff provided by the agrivoltaics and wind power generated by facilities installed on the farm, separately. The two systems with numerical models will then be integrated together to enhance the cost effectiveness on the sensors and controls. At this stage, not only the sensors and controls will be integrated together, but also the land resources. The coupled numerical model will be trained by advanced machine learning methods. In the final stage, as the land resources are shared, an analysis on the effect of sharing the land resources for generating renewable energy on the crops and livestock will be studied. The mechanism to achieve the optimized net profit of these proposed sharing on land resources will be delivered.


Project Reference No.: UGC/FDS16/M01/22
Project Title: Modulation of Ichthyotoxicity of Karenia mikimotoi by Two Associated Alteromonas oceani Isolates (R2 and Y8) and Algal-bacterial Molecular Interaction Under Effects of Different Biotic and Abiotic Factors
Principal Investigator: Prof LEE Wang-fat (HKMU)


Human health and aquaculture industry have been adversely affected by Harmful algal blooms (HABs). Karenia mikimotoi is one of the most toxic and deadly HAB species. Fish-killing ability of this species is notably dangerous, and blooms caused by this species greatly affect both Hong Kong and mainland China. For example, it killed more than 200 tons of fish in several local fish-farming zones in Hong Kong in 2016. Although K. mikimotoi has been extensively studied in the past decades, their ichthyotoxicity (i.e., fish-killing) mechanism is poorly understood. The production of reactive oxygen species (ROS) and haemolytic activity of K. mikimotoi have been suggested as one of the possible mechanisms. However, the exact mechanism remains controversial.

Previous studies have shown that toxicity of HAB species can be affected by different growing conditions, particularly, algal growth phase and cell concentrations, salinities, nitrogen, and phosphate concentrations. On the other hand, several studies have demonstrated that toxicity of HAB species can also be regulated by their closely associated bacteria. However, the underlying mechanism on the toxicity modulation and the algal-bacterial interactions are virtually unknown. In addition, associated bacteria specifically isolated from K. mikimotoi have yet to be reported. No molecular studies at gene or protein levels have aimed to identify the underlying molecular pathway in the algae and its associated bacteria during their interactions. Our team has successfully established axenic culture of a K. mikimotoi strain (KMHK) isolated from an algal bloom in Hong Kong. The ichthyotoxicity of K. mikimotoi culture would be significantly enhanced in the absence of its associated bacteria and the effects of the algal culture when co-culturing with different bacterial isolates are varied, which indicate that the toxicity of K. mikimotoi can be modulated by their interactions with the associated bacteria. Two novel associated bacterial isolates of a same species Alteromonas oceani, namely R2 and Y8, have been isolated from the K. mikimotoi culture. The two bacterial isolates showed prominent but opposite effects on the ichthyotoxicity of K. mikimotoi. When axenic K. mikimotoi co-cultured with R2, the corresponding effect on fish gill cell viability become much higher than that of the axenic algal culture alone, whereas opposite effect is observed when the K. mikimotoi cells are co-cultured with Y8 bacteria. Our preliminary data also showed that the ichthyotoxicity of K. mikimotoi could also be significantly affected by various biotic and abiotic factors, and the direct and indirect contact between the algal cells and bacterial cells.

In continuation of our preliminary study, in the present study, we aim to investigate how ichthyotoxicity of K. mikimotoi is regulated by its associated bacteria using the pair of A. oceani isolates (R2 and Y8) as the study model. The effects imposed by both isolates under various experimental conditions will be compared. Ichthyotoxicity of K. mikimotoi co-cultured with R2 or Y8 growing under various biotic (cell concentrations and growth phases) and abiotic (salinities, nitrogen (N) - and phosphate (P) – concentrations) conditions will be assessed. The effects of algal-bacterial cell contact will be investigated through the co-cultivation of both cells in a system in which the bacterial cells and algal cells will be physically separated by a semipermeable membrane. Furthermore, molecular interactions between K. mikimotoi and the two A. oceani isolates under various selected conditions will be evaluated using comparative proteomic approaches. In parallel, molecular responses of both bacteria cells and K. mikimotoi cells through their interaction will also be deduced. Understanding the algal-bacterial molecular interactions will help to unravel the cellular regulation and possible pathways in algal toxicity modulations. Successful completion of this project can contribute to the eventual development of a proactive strategy for preventing fish-killing incidents by HAB which will have significant implications for fish farms and shellfish industries.


Project Reference No.: UGC/FDS11/E01/22
Project Title: Chaotized Plasma for actively combating airborne COVID19
Principal Investigator: Prof LEUNG Andrew Yee-tak (Caritas)


We propose a safe technology of Chaotized Plasma to disinfect suspended viruses because plasma air ionization was proven to reduce Coronavirus Surrogate MS2 Bacteriophage by 99% in Independent Spanish Testing and many other places.

UK Health and Safety Executive said, “Do not rely on recirculation units which just move COVID virus around”. Omicron viruses were found in the air purifiers at Silka Seaview Hotel on 18/1/2022 and at Hakka Cuisine in the Lion Rock Shopping Centre on 31/1/2022 and people were infected just under the air purifiers. Just air exchanges as mandated by the Hong Kong Government in designated places are not scientific as viruses are still active and infecting the air purifiers. Existing disinfection technologies, e.g. nano-coating, silver ions, spirit, and UVC(Ultraviolet-C light) are for landed viruses only. However, over 90% of COVID infection is through the air. The European Commission has published its decision to classify nano-coating as a category 2 carcinogen.

Evidence from the HK Airport Toilets and Moon Palace Restaurant shows that Omicron is not a landed virus and is transmitted mainly through the air. On 2/1/2022, the Health Protection Centre inspected the Moon Palace Restaurant in Festival Walk and collected over 80 environmental samples with no landed viruses found. On 4/2/2022, 5 people were infected in Caritas Hospital but the ventilation was good. Therefore, good ventilation may not be able to avoid infection. The main cause of the disease is airborne. Air disinfection is necessary.

The PI used chaotized bleach water in 2003 to disable viruses from patients coughing at an airspeed of 22m/s (funded by the Research Grant Council) and then chaotized ozone water in 2020 for negative pressure isolation rooms (funded by ITF). The former devices were installed in the Prince of Wales Hospital and the latter in Pok Oi Hospital and Society for the Blind Care Homes successfully. Now, instead of vapor, we use chaotized plasma, the first time in the world. Plasma is produced by elevating the usual 220V voltage to 5000V and discharging between positive and negative poles. For example, O2 is split into O+ and O- ions, both will neutralize back to O2 releasing tiny energy to disable microbe’s reproduction. However, ions and viruses are extremely small (nanometres) that they have little chance to meet in a finite space. Chaotic mixing of ions and virus is created inside the invented use of Chaosors so that, in a trial run using Eilat coronavirus, 99% efficacy of disinfection within 0.1 seconds can be achieved. It was found also that the efficacy is reduced to less than 10% when plasma was not chaotized. Plasma can also decompose big air molecules like formaldehyde and H2S. Therefore, chaotized plasma can deodorize.

The project’s deliverables include (1) chaotic simulation of viruses and plasma ions by computational fluid dynamics; (2) hardware: air disinfection devices for use in institutions; (3) Indoor Air Quality monitoring devices in smart and healthy city applications; (4) student learning materials in engineering, biophysics, and microbe disinfection; (5) patents, seminar and conference presentations and paper publications. New knowledge for teaching and learning in hygiene practices and air disinfection will be created in the post-COVID19 healthy-smart city.

The device will be installed at the inlet of an Air Handling Unit to clean air almost costless. It will also be tested in a model elevator. The piston effect of the lift car movement provides the airflow and cleans the adjacent air at merely 0.04% additional energy cost by chaotized plasma. The PI will use four of his invention patents in this project. Extensive public engagement activities are arranged for wide application and commercialization.


Project Reference No.: UGC/FDS24/B19/22
Project Title: Prevention is Better than Cure? How the Gamification Elements of Gerontechnology Influence the Elderly Mental Well-being and Cognitive Health: A Longitudinal Study in Hong Kong
Principal Investigator: Dr LEUNG Wilson Ka-shing (PolyU SPEED)


The population with dementia is on the rise due to the rapid ageing population in Hong Kong. By 2041, one out of every three people in Hong Kong will be over 65 years old. More and more elderly people may suffer from cognitive decline, creating a heavy burden on the public healthcare system and increasing the need for continuing care from their caregivers in Hong Kong. One way to reduce the prevalence of cognitive decline is to develop preventive strategies as dementia is difficult to diagnose at the initial stage. Offering cognitive training for the elderly may help to enhance cognitive function. However, many existing training exercises are face-to-face and not technology-based. There is a lack of technological resources for the prevention and treatment of dementia for the elderly, particularly in Hong Kong.

One of the gerontechnology to cope with this challenge is digital game-based cognitive trainings. It is more cost-effective, disseminate faster, and more patient-oriented than traditional cognitive training exercises. It not only can benefit the elderly but also mitigate the pressure on public healthcare system and workload on caregivers. However, empirical studies on how gamification features of technology-based cognitive trainings effectively affect elderly people well-being as well as the technology usage behaviors remain limited. Applying our research experience in healthcare technology adoption, this research team, which compose of researchers in the area of information systems, healthcare, and marketing, collaborates with elderly service organizations and a gerontech company with a cognitive training mobile game, and a clinical psychologist, to investigate the effectiveness of cognitive training mobile games in improving the elderly cognitive and mental well-being through two studies.

Understanding how elderly users achieve desirable outcomes (e.g., well-being) by taking advantage of the gamification affordances of cognitive training mobile games is critical for improving the training effectiveness. To fill the research gaps, a three-stage theoretical model drawn from affordance theory, the perspective of six common cognitive therapies, and computational theory of mind is developed to explain the well-being actualization of gamification affordances. Mixed-methods design will be applied to collect data. Additionally, an experiment will be conducted to investigate the effectiveness of cognitive training mobile games in improving elderly users’ cognitive health. With the assistance of the above collaborators, our multistage model will be examined by recruiting elderly people from their elderly centres. Partial Least Squares Structural Equation Modelling and MANOVA will be used for our data analysis. We will conduct a qualitative study to augment the insights gained from the survey results. Overall, our findings not only contribute to the literature on digital game-based cognitive training adoption, but also provide managerial guidance for the government, the elderly service organizations, the gerontech companies, and tertiary education about how to enhance the cognitive health among the elderly effectively.


Project Reference No.: UGC/FDS24/H05/22
Project Title: A Projective Analysis of Rhythmic Organisation in Free-Rhythm Musical Performances in West Asian Art Music
Principal Investigator: Dr LIE Nga-sze (PolyU SPEED)


This project aims to study the rhythmic organisation in “free-rhythm” traditional art music of West Asia using the theory of rhythmic projection, to understand how performers of Turco-Arabic and Persian art music create the impression of “free-rhythm” through manipulating the listeners’ expectation of metric rhythm, both locally at the phrase level and globally on the level of a complete performance, to analyse if morphological differences across instruments (and voices) affect the rhythmic strategies employed, and, lastly, to devise a notational system, based on standard western staff notation, that can also capture the fine rhythmic manipulations.

The traditional art music of West Asia, specifically that of the Turco-Arab tradition and the Persian tradition has been selected as the object of study, because of the high esteem free-rhythm performances have in these traditions, and the surprising lack of theorisation of their rhythmic organisation, due to the lack of theoretical apparatus in both western and native musicology. This study aims to fill the lacuna by employing the theory of rhythmic projection proposed by Hasty (1997) and employed in free-rhythm music by Roeder (2021) for an extensive study of free-rhythm performances across different instruments and voices in these traditions. The theory of rhythmic projection posits that two successive sounds would create a definite duration, one which the listener would “project” into the future as a benchmark by which the next sound will be judged. If the third sound happens in the expected duration, the projection is considered as “realised”, and if it doesn’t, the continued measurement of durations of the next sounds can reveal whether there has been an acceleration, deceleration, a hiatus/pause, or a new tempo that is being reset.

We seek to answer the following questions through this research: How do performers of Turco- Arabic and Persian art music create the impression of “free-rhythm” through manipulating the listeners’ expectation of metric rhythm, both locally at the phrase level and globally on the level of a complete performance? How do these relate to the prosodic system of these musics? Do morphological differences across instruments affect the rhythmic strategies employed? And if so, how? How can such music be better represented with a system based on western staff notation that is both legible and accurate?

This study will be conducted primarily through transcription and analysis. Transcription will be made of recordings of improvised vocal genres and improvised instrumental genres performed on plucked strings, bowed strings and wind instruments of Arabic, Turkish, and Persian classical music.

The lack of analytical work on such music is due to a lack of theoretical apparatus, especially the lack of a suitable notational method that can help researchers to record on paper the perceived rhythms correctly. Therefore, as part of this study, a second objective is to devise a notational system, based on standard western staff notation, that could be easily understood by musicologists and musicians trained in the western tradition, yet can also capture the fine rhythmic manipulations that have so far evaded study. Such a system will be of significant contribution to the analysis of different genres of free-rhythm music around the world (not limited to the two studied traditions), and will also provide a useful tool for pedagogues and composers to create new works.


Project Reference No.: UGC/FDS11/E02/22
Project Title: Robust Graph-based Clustering: From Shallow to Deep
Principal Investigator: Dr LIU Hui (Caritas)


Clustering is a fundamental task in data analysis, which partitions a set of samples into homogeneous groups. Over the past few years, graph-based clustering algorithms are becoming very popular and widely used in various applications due to the high efficiency and simplicity in implementation, i.e., graph-based clustering only requires a typical pairwise similarity matrix of samples (a.k.a. a graph) as input and performs spectral decomposition on that matrix to generate the clustering result. Despite its popularity, some fundamental issues still exist, which greatly affect its performance.

First, the performance of graph-based clustering algorithms is highly dependent on the quality of the input similarity matrix. Therefore, how to construct a high-quality graph which can best capture the underlying structures of data is the core of this kind of method. Besides, graph learning is also a hot research topic in signal processing. However, it is a challenging task. The traditional methods usually use the Euclidean distance of samples to construct the pairwise similarity matrix, which is very sensitive to the noise and usually suffers from high computational complexity. Besides, in practice, there is some side information available that may provide valuable information to promote graph-based clustering, such as the available supervisory information, which may be overlooked or not fully exploited to some extent. We will propose a unified theoretical framework capable of fully exploring the available side information, including the raw features and some weak supervisory information, to learn a more robust and informative similarity matrix for graph-based clustering.

Second, most of the traditional graph-based clustering methods adopt linear models to cluster the data, but in practice, the data is not necessarily located in the linear subspaces, which may significantly affect the performance of graph-based clustering algorithms. It becomes insufficient and unreliable to only use the linear models in graph-based clustering. In addition, inspired by the powerful representation capability of the deep learning framework to model the nonlinear system, in this project, we will develop a novel deep neural network architecture to learn a nonlinear mapping of the data to well adapt to the subspace clustering.

With our solid backgrounds and the promising verifications achieved, it is highly expected that our investigations will provide more efficient and effective graph-based clustering algorithms for the large-scale dataset. Clustering is a fundamental and universal problem related to many topics, including low-rank matrix/tensor approximation, low-dimensional embedding, semi-supervised learning, noise estimation, deep learning, etc. In addition, the constructed high-quality graph can be widely used in various tasks in data analysis rather than just limited to clustering. We believe that beyond the three years envisioned for this work, the scientific findings of this project will continuously motivate the research on a wide range of research communities and benefit various real-world applications.


Project Reference No.: UGC/FDS11/E03/22
Project Title: Chinese Calligraphic Animation Generation via Deep Stroke Segmentation and Contour-based Trajectory Identification
Principal Investigator: Dr LIU Xueting (Caritas)


Calligraphy is a popular visual art form that intends to produce pleasant writing, especially in East Asia. However, it is not easy for amateurs to write calligraphy due to the delicate writing trajectory and brush pressure control. To help beginners in calligraphic writing, calligraphic animation videos are extremely helpful to show the writing trajectories and brush pressures at all writing positions. Besides, calligraphic animations are frequently used in different digital media as a better way to present and animate the text, such as in movies, dramas, cartoons, and advertisements. While there are tools available for manually producing calligraphic animation, the process is tedious and requiring professional skills. An automatic calligraphic animation generation system would help much in this tedious and time-consuming calligraphic animation making process. What’s more, the generated animations with writing trajectories and brush pressures can be directly used in robot writing as well.

An automatic calligraphic animation generation system includes three parts: segmenting the calligraphic image into individual strokes, identifying trajectory and brush pressure for each stroke, and generating animations to all strokes. There are several key challenges to be solved. Firstly, a calligrapher may write freely with stylized strokes and writing topology, so the writing topology of different calligraphic characters may not be the same (Figure 1). Even though the writing order of the strokes for formally written characters is well defined, the calligraphic character may not follow the defined writing order. So, it is not realist to hardcode the writing order for animation generation. Secondly, the writing habits are very different for modern and traditional Chinese. The modern Chinese is customed to write from first left to right and then top to down, while the traditional Chinese is customed to write from first top to down and then right to left (Figure 2). It is needed to identify the writing order before animating the characters. Finally, the generated writing trajectory and brush pressures should be precise and smooth to simulate the real writing.

Despite the usefulness of the system in education, entertainment, and automation, the existing methods generally only focus on one part of the system. Without taking consideration of the whole system, the existing stroke segmentation methods usually only generate low-resolution output, so the segmented individual strokes can hardly be directly used for animation generation. Besides, the state-of-the-art stroke generation methods are usually trained on a specific font style and are error-prone to even minor font changes (Figure 3). On the other hand, the existing text animation generation methods generally rely on hardcode writing topology of each character, the character writing order and calligraphic characters that do not obey the defined writing topology are still lack of discussions.

In this project, we propose a novel system which consists of a novel learning-based stroke segmentation module, a contour-based trajectory and brush pressure identification module, and a learning-based stroke animation generation module. The key idea of the stroke segmentation module is an iteratively refined stroke segmentation network to gradually adaptive the network to different calligraphic fonts. The key to the trajectory identification module is to obtain the precise trajectories with brush pressure based on the contour information. The key to the stroke animation generation module is to first identify the writing order of the corresponding calligraphic image and then generate the ordering and animations of the strokes based on the identified writing order.

With the proposed system, we believe the tangible outcomes, e.g., publications and algorithms, should directly benefit the industry and the research society. The research project would also provide invaluable chance in developing the 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/FDS25/E06/22
Project Title: Development of Polyhydroxyalkanoates-Based Composite Nanofiber Membrane via Electrospinning, and Application in Particulate Matter Filtration
Principal Investigator: Dr LIU Yaohui (THEi)


Polyhydroxyalkanoates (PHAs) have been reported to be one of the promising polymers due to their intrinsic biodegradability and biocompatibility. However, high production cost significantly limits their application. Raw material costs have been known to be the main part of PHA production costs. Therefore, the project will be carried out using inexpensive, activated sludge generated from wastewater treatment processes as a major source of PHA raw material to replace the expensive commercial carbon source, meaning a significant reduction in the overall production cost.

In modern society, air pollution caused by traffic, manufacturing, and construction industries has become an outstanding global environmental and health problem. Due to the continuous release of dust and particulate matters into the atmosphere, various types of air filtration technologies have been studied and developed. By using electrospun biodegradable polymeric fibers as the building block of membrane filter structures, it is a novel step and a promising solution for producing biodegradable air filters to intercept particulate matters, volatile organic compounds (VOCs), or hazardous microbes. Electrospun biodegradable polymeric nanofibers are also becoming a versatile platform for producing air filtering materials due to their well-defined porous structure, high specific surface areas, controllable fiber diameters, and interconnected nanoscale pore structures; as well as their capability to incorporate surface chemistry in a nanoscale. Electrospun nanofibrous membrane fabricated by biodegradable PHAs-based materials has drawn much attention because of the high demand for sustainable development, and the products highly conform to green chemistry. Electrospun nanofibers membranes for air filtration have attracted lots of attention, including the pretreatment for electrospinning and the operation parameters relevant to produce desired filter properties. Although some advanced electrospun air filtration nanofibrous membranes exist for treating various types of pollutants in the living environment, there are limited studies on using PHAs as membrane materials that are still in deficiency.

This project focuses on the development and testing of electrospun PHAs-based membrane filters for air filtration and decontamination. PHAs properties will be optimized to fit the electrospinning process control. The commercial PHAs materials will be used for determining the optimal fraction of HB:HV. Biodegradable modification method will be adopted to synthesis PHAs for desired purposes. In the preliminary study, electrospun membrane samples were successfully collected with an applied voltage of 12 kV, a solution flow rate of 1 mL hr-1, and a PHB concentration of 14 wt. %. In order to improve the structure and physical properties of the electrospun nanofibrous membrane as an efficient air filter, the main focus is the modification of PHB membrane properties with a biodegradable plasticizer for air filtration. The effect of electrospinning nanofibrous membrane structure on filtration performance will be investigated. Biodegradability will be also studied.


Project Reference No.: UGC/FDS24/H04/22
Project Title: The Science of Design Thinking: Theories and Applications
Principal Investigator: Dr LO On-ting (PolyU SPEED)


The world has been changing these days rapidly due to the explosion of technological advancement. We are amazed by how previously impossible things become ubiquitous and even transform our habits. The world is brand-new every day, and so as the problems, we will encounter. In such a technologically interconnected world, the problems have become notably much more complicated than ever. In Hong Kong, we face complex challenges as well. The ageing population has posed tremendous pressure on the healthcare system. The housing problem is highly constrained by limited land resources. This is only an example of the difficult problems that Hong Kong people are facing. To make the world as well as Hong Kong a better place, nurturing a generation of excellent problem solvers through education is necessary.

To solve complicated problems, a flexible thinking system which is unbounded by specialized disciplines is more favourable. Current tertiary education still largely emphasizes on knowledge specialization in which students will pick up one or two majors in their 4-year curriculum, and their thinking styles will be shaped in correspondence with the disciplines. Fortunately, cross-disciplinary training (e.g., Bachelor of Arts and Sciences degrees) has attracted much more attention recently. The common goal of such cross-disciplinary education is to nurture creative problem solvers without rigid cognitive boundaries (Cook & Bush, 2018).

A creative problem-solving mindset can be achieved by design thinking (DT hereafter). DT is one of the three 21st-century skills (the other two are systems thinking and teamwork thinking) that competent problem solvers should possess (Rotherham & Willingham, 2009). According to Stanford d.School (2010), DT is a cognitive mechanism to solve problems which consists of five main processes including Empathize (e.g., be able to think of users’ needs), Define (e.g., be able to identify the problems and users’ needs), Ideate (e.g., be able to put forward different solutions to address the problems and users’ needs through various ways such as brainstorming), Prototype (e.g., be able to show, visualize, and present the products and solutions for addressing the problems and users’ needs) and Test (e.g., be able to test the complete product). DT is crucial for younger generations to solve academic, career and life problems in this complicated world (Razzouk & Shute, 2012).

DT is usually regarded as a “practical skill set” to solve different problems in extant research and practice. For example, Yeager and colleagues (2016) utilized DT to improve a positive psychology intervention. Tushar and colleagues (2020) examined how to improve building energy efficiency by a DT approach. Most extant research studies examining DT are qualitative and conceptual (McLaughlin et al., 2019). Quantitative research on the scientific nature of DT is still at its very beginning stage (Tsai & Wang, 2021). We know DT is powerful and valuable, but we are still largely unclear about the science behind DT.

To understand the science behind DT and facilitate DT education, in this proposed project, the research team will have two missions. (1) to build a theoretical model to identify the psychological correlates of design thinkers; (2) to build a preliminary big data database regarding the DT processes in solving DT cases for future DT research and education purposes.

The research team will publish the findings in international peer-reviewed journal(s). We will also disseminate the research findings to colleagues working in tertiary education sectors through research seminars. Students who have learnt DT would also be able to share this idea with their peers and significant others, making this project much more influential in society but not limited to the academic community. As for the big data database, data regarding DT cases will be collected continuously; once the data amount is significant, big data analytics can be performed so that valuable information regarding DT will be mined and shared with stakeholders.


Project Reference No.: UGC/FDS24/H18/22
Project Title: Establishing Central Sinitic Languages as a Linguistic Sprachbund - Transitional and Area-specific Features
Principal Investigator: Dr LU Wen (PolyU SPEED)


The Chinese language family comprises ten phylogenetically affiliated ‘dialectal’ groups, namely Mandarin, Jin, Wu, Hui, Gan, Xiang, Min, Hakka, Yue, Ping groups, according to the second edition of Language Atlas of China (2012). Among them, some varieties share more grammatical features in common than the others, therefore scholars have proposed several linguistic areas within Chinese languages. Hashimoto (1976, 1986), for instance, proposed a north-south divide among Chinese languages by the geographic Qinling-huaihe Line. For example, Northern Chinese languages like Beijing Mandarin have fewer tones, higher ratio of polysyllabic words, and a passive marker from CAUSATIVE-meaning verbs, whereas Southern Chinese languages like Cantonese possess more tones, higher ratio of monosyllabic words, and a passive marker from GIVE-meaning verb. Norman (1988) refined Hashimoto (1976)’s division by adding a ‘transitional’ zone, which sometimes demonstrate features of Northern Chinese languages, and at other times features of Southern Chinese languages. In addition to the Northern and Southern features, Chappell (2015) revealed plausible area-specific features for the ‘transitional’ zone and proposed a five-zone distinction among Chinese languages. Later Szeto (2019) carried out a quantitative study on 213 Chinese languages based on the Northern and Southern features, and concluded with a four-zone analysis.

Despite the advancement of the study on linguistic areas in Chinese languages, no study is dedicated to the Central Transitional Area, let alone the ‘fluctuating’ features and area-specific features which can categorize such a linguistic area, probably due the scarcity of research on the Central Chinese dialects themselves, especially Hui dialects.

Leveraged on our pilot study of a comprehensive description of a little-studied ‘transitional’ Chinese language, namely Tunxi Hui, we’re able to select 18 ‘fluctuating’ features and four candidate area-specific features as the feature pool for further investigation. Therefore, this proposed study, first of its kind, will embark on a typological investigation of the grammatical features of the Central Transitional Sinitic languages, mainly Wu, Hui, Gan, Xiang, Jianghuai Mandarin and Southwestern Mandarin varieties. In specific, we will select around 15 representatives ‘dialects’ of Transitional Sinitic languages, analyzed against 18 ‘transitional’ features affiliated with either Northern or Southern Chinese languages, and four candidate area-specific features unique to this area. In doing so, we aim to:

(i)  Investigate distributions of transitional and area-specific typological features in Central Sinitic languages;

(ii)  Reveal the relationship between such distributions, in characterizing a Central Transitional linguistic area of Chinese languages; and

(iii)  To evaluate if the area in question can be evaluated as a (transitional) linguistic area.

In sum, it is hoped that this project will bridge the gap in the little-studied Central Chinese languages, by revealing more on their transitional and unique features as transitional ‘dialects’ between Northern type of Chinese, e.g. Mandarin, and Southern type of Chinese, e.g. Cantonese.


Project Reference No.: UGC/FDS13/E03/22
Project Title: Application of Artificial Intelligence (AI) techniques in forecasting the variation of sediments in water ecosystem
Principal Investigator: Dr LU Yi (Chu Hai)


According to the Civil Engineering and Development Department, a large proportion of land in Hong Kong is used for country parks and special areas outside country parks. However, urbanisation has caused population loss in rural areas, resulting in the decline of valuable ecological and cultural resources, with several remote rural communities being close to abandonment. The Hong Kong government and some non-governmental organisations are making joint efforts to revitalise rural areas. Cultural and economic heritage should be preserved alongside the surrounding natural systems. The climate in Hong Kong is characterised by frequent high-intensity rainfalls, which have a great impact on the conditions of all bodies of water in the region. Therefore, it is crucial to study the eco-environmental situation in Hong Kong to ensure the environmental sustainability of rural revitalisation.

In the proposed project, we will build a comprehensive system to monitor and evaluate the water ecosystem in the Lai Chi Wo catchment, Hong Kong. First, we will establish an integrated database platform containing meteorological data such as atmospheric pressure, temperature, wind direction, and wind load, and hydrological data such as rainfall intensity, rainfall depth, flow rate, and water level. The data base will also include high-resolution data on the sediment status of the river system collected in a previous project. Second, artificial intelligence (AI) technology will be used to model and forecast sediment concentrations, which are indicators of water quality in a river system. Finally, we will construct an intelligent water-safety-early-warning platform that will provide short-term predictions of variations in the local water ecosystem. The platform will measure the impact of human activities (e.g., land use planning, artificial construction of channels, etc.) on river quality. Poor water quality is an indication of unfavourable activities in local communities. The system will also improve the efficiency of responses to water-related ecological disasters (e.g., impact of storms on soil erosion). The Hong Kong government can implement preventative measures based on the warning information, thus reducing risk to human life and property damage.


Project Reference No.: UGC/FDS14/E04/22
Project Title: Minimizing Maintenance Delays by Integrating Aircraft Maintenance Routing and Maintenance Workforce Scheduling with the Consideration of Component Availability
Principal Investigator: Dr MA Hoi-lam (HSUHK)


Aircraft maintenance routing problems (AMRPs) aim to determine a set of routes to cover an airline’s flight network with the aim of maximizing aircraft utilization and flight schedule reliability. In particular, aircraft must strictly comply with aircraft regulations stipulated by the civil aviation department, among which the maximum flying hour is prioritized. Typically, aircraft must perform A-checks every 400–600 flying hours. However, because of the long duration required by the A-checks (2–4 weeks), the utilization of aircraft is low. As such, many airlines have re-packaged the conventional A-check into many shorter (small) checks and performed them between flights during the normal flight operations. Therefore, the on-time completion of checks performed at maintenance stations becomes critical, as the scheduled maintenance time allowed is much shorter as compared with that of the conventional approach. Therefore, a delay maintenance may easily disrupt the flight schedule. In our prior completed FDS project, we developed a machine learning algorithm to predict the maintenance time required for maintenance tasks and estimated the corresponding delay risk for AMRPs optimization. The results show that the flight schedule reliability increased. Moreover, while we were analyzing historical data pertaining to maintenance, we discovered frequent maintenance delays due to insufficient manpower in the maintenance station caused by mismatch between the aircraft maintenance demand and workforce schedule. Moreover, we discovered that the maintenance delays can be caused by the shortage of components required for replacement. However, in the existing studies, manpower availability, component availability, and workforce scheduling at maintenance stations are not considered in AMRPs. Therefore, we propose to investigate an integrated problem comprising AMRPs and workforce scheduling problems with the consideration of component replacement availability problems.


Project Reference No.: UGC/FDS17/P01/22
Project Title: An investigation into chloroxylenol, a popular antimicrobial ingredient in hygiene and disinfection products, in Hong Kong through wastewater analysis
Principal Investigator: Miss MAK Deejay Suen-yui (TWC)


Chloroxylenol, a halogenated phenolic compound, is an antimicrobial ingredient frequently used in antibacterial hand sanitizers and household disinfectants. Particularly in 2020 after chloroxylenol was first evaluated to be effective at inactivating SARS-CoV-2 virus that causes Coronavirus Disease-2019 (COVID-19), human habits and lifestyles have changed, causing a surge in worldwide demand for popular brands (e.g., Dettol, Walch and Ariel) of antibacterial hand sanitizers and household hygiene disinfectants in which the main antimicrobial ingredient is chloroxylenol. The more frequent use of disinfection products in household, commercial, hospital and industrial settings may have greatly increased the occurrence and level of chloroxylenol washing down the drains and its collective delivery to sewage treatment plants (STPs) via domestic sewage systems. The subsequent release of chloroxylenol into the aquatic ecosystem poses toxicological threat to humans and aquatic animals, such as altered gene expression and histological lesions in rainbow trout. STPs thus play a key role in controlling the fate and ecological risk of chloroxylenol in the environment as these plants can limit the spread of chloroxylenol into downstream bodies of water (e.g., rivers and reservoirs) that support aquatic life and supply drinking water. The occurrence of chloroxylenol in aquatic environments was reported at levels of ng/L to µg/L level in some countries, such as the United Kingdom and the United States, before the COVID-19 pandemic. However, no study has investigated the distribution and level of chloroxylenol since the pandemic began. As Hong Kong is a city with one of the highest population densities in the world, as well as a city with massive use of antibacterial hand sanitizers and household disinfectants from Dettol and Walch, it is expected that a much higher concentration of chloroxylenol could be detected in the influent and effluent wastewater samples in STPs during the COVID-19 pandemic than before. As the routine river water quality monitoring programme implemented by the Environmental Protection Department (EPD) does not screen for chloroxylenol, it is important and urgent to determine how effectively the STPs in Hong Kong are eliminating chloroxylenol before discharging effluent into water bodies, and to understand the local distribution of chloroxylenol in rivers and creeks. However, no such study of chloroxylenol has been done in Hong Kong.

In the proposed project, the presence of chloroxylenol in influent and effluent wastewater samples of two STPs that use different treatment techniques (Stonecutters Island Sewage Treatment Works and Sha Tin Sewage Treatment Works) will be investigated in the wet and dry seasons. Removal efficiency of chloroxylenol at each STP will be calculated, and the potential ecological risks of the effluent to the aquatic ecosystem will be assessed. The findings will fill the gap in knowledge about seasonal variations in the chloroxylenol concentrations in the influent and effluent samples. Surface water samples from two rivers will also be collected to determine the spatial distribution and ecological risk of chloroxylenol. The proposed study will be the first to investigate the occurrence of chloroxylenol both in Hong Kong and during the COVID-19 pandemic. The findings will enable the creation of an essential knowledge base that will assist health and environmental authorities to strategically plan policies, systematically evaluate the efficiencies of STPs in removing chloroxylenol and set requirements for community environmental programmes to prevent the introduction and accumulation of this hazardous substance into the environment, thus preserving public health and safety.


Project Reference No.: UGC/FDS25/M03/22
Project Title: Design and pharmacological elucidation of novel anti-PD hybrids: neuroprotective and disease-modifying effects via synergistically acting on GSK3β/MEF2D and MAO-B
Principal Investigator: Dr MAK Shing-hung (THEi)


Parkinson’s disease (PD) has been ranked as the second most common neurodegenerative disorder worldwide. PD might severely cause the dysfunction of motor functions of patients. Since PD is multifactorial neurodegenerative disorders, and currently available drugs act only provide symptoms-relieving benefits to the patients. Accumulating evidence has indicated that the degeneration of neuronal cell in substantia nigra might be caused by multiple genetic/environmental factors. Thus, the “one-compound-multi-target ligands” strategy might be focused for the development of novel candidates for treating PD. Recent studies have also demonstrated that glycogen synthase kinase-3β (GSK3β)/ myocyte enhancer factor 2D (MEF2D) and monoamine oxidase-B (MAO-B) play important roles for the pathological progress of AD. As the results, GSK3β, MEF2D and MAO-B might be the critical drug targets for the prevention and/or treatment of PD.

In the previous studies, we have demonstrated that 3-substituted-2-indolin-ones compounds, including sunitinib analogs,indirubin-3-oxime and rhynchophylline, could provide significant neuroprotection against variety of neurotoxins associated with PD. The possible molecular mechanisms might regulate the MEF2D dysfunctions through the inhibition of GSK3β and/or MAO-B. Based on the multi-functional strategy, we now hypothesized that multi-functional candidates targeting GSK3β/MEF2D and MAO-B migh offer disease-modifying potential for the treatment of PD. By using a sequential combination of ligand and structure-based virtual screening techniques, as well as molecular docking analysis, we designed several virtual hybrids seems could be developed as multifunctional molecules by inhibiting GSK3β and MAO-B. Encouragingly, some of these candidates have exhibited with reasonable pharmacokinetic properties and low toxicity. Particularly, two of these novel hybrids, hybriding indolin-2-one core (pharmacophore of 3-substituted-2-indolin-ones compounds, MEF2 enhancer) and the propargyl (moiety of the irreversible MAO-B inhibitor, rasagiline) have shown promising inhibitory effects on GSK3β and MAO-B, respectively.

The primary objective of this proposal is to synthesize and optimize the multifunctional hybrids, and systematically investigate the multiple neuroprotections and underlying mechanisms of GSK3β/MEF2D & MAO-B inhibitory hybrids associated with PD in vitro. If success, we will develop a new generation of anti-PD leads with disease-modifying potential via synergistically acting on multiple targets.


Project Reference No.: UGC/FDS16/M05/22
Project Title: Combined chronic effects of dietary relevant concentrations of metal/loids and elevated water temperature on two economically important fish
Principal Investigator: Dr MO Wing-yin (HKMU)


Fish is an important protein source for populations in coastal areas. To ensure safety, metal and metalloid (metal/loid) concentrations in fish products and fish feeds are regulated, and their levels should not exceed the maximum permitted concentrations. However, metal/loids are still frequently detected in fish products and fish feeds, and this problem may be exacerbated by climate change. As ectothermic organisms, most fishes change their body temperatures according to the environmental temperature. Fish are more sensitive to environmental pollutants at hotter environment, as a higher water temperature increases their basal metabolic rates. Consequently, more feed is needed to compensate for higher energy expenditure at elevated temperatures. The resulting increase in metal/loid intake from the diet can increase metal/loid exposure in fish and metal/loid accumulation in fish products. Thus, as the climate warms due to climate change, increased intake of metal/loid present in fish feeds poses a greater threat to fish.

The Intergovernmental Panel on Climate Change (IPCC) has predicted that by the end of the 21st century, the Earth’s surface temperature will be 3.79 °C higher than it was in 1980–1990 and, as of 2022, about 0.7°C increment has been observed. Although a warmer climate may initially benefit the aquaculture industry, as fishes grow faster at higher temperatures, the industry will also be negatively affected by the following events: (1) increased feed consumption at higher water temperatures may lead to a greater accumulation of metal/loids in fish, leading to rejection of fish products exceeding the permissible limits; (2) even if metal/loid levels in fish are safe according to the current standards, fish may suffer from increased stress due to their higher sensitivity to metal/loids at higher temperatures, leading to greater losses; and (3) higher metabolic rates due to the increased energy expenditure of fish at higher temperatures will also lead to increased feed consumption and feed costs. The exact long-term effects of a warmer climate combined with metal/loid contamination on farmed fish are largely unknown. Therefore, there is an urgent need to study fish responses to warmer temperatures, investigate whether such temperature increments will affect metal/loid toxicity and accumulation in fish and determine the potential health risks to consumers.

This proposed project aims to investigate the combined chronic effects of relevant dietary concentrations of metal/loids and elevated water temperatures on the growth performance, productivity and the immunological, physiological and proteomic responses, metal/loids accumulation and the potential health risks of consuming two economically important fish species, Nile tilapia and mud carp. Nile tilapia is more heat-tolerant than mud carp. Experimental fish tank setups with temperature control will be used, and two separate experiments will be performed using both fish species. Fish in the tanks will be exposed to a combination of two water temperature ranges (low-temperature range: gradually increasing from 24 °C to 30 °C; high-temperature range: gradually increasing from 28 °C to 34 °C) or fixed temperatures (30 °C or 34 °C), and three dietary metal/loid concentrations (maximum permitted levels, ten times lower than the permitted level and un-spiked [control diet]), for six months. These treatments will simulate the global warming condition and the possible metal/loid contents in fish feeds. The results generated from this proposed project will be useful to the aquaculture industry, governmental departments and fish feed producers, who are faced with challenges related to the changing environment. These findings will also be converted to teaching materials and public seminars.


Project Reference No.: UGC/FDS15/H09/22
Project Title: Quality transition strategies facilitating the transition from teenage to adulthood for persons with intellectual disabilities and their family carers
Principal Investigator: Dr MO Yuen-han (Shue Yan)


In Hong Kong, special school leavers with a mild to moderate level of intellectual disabilities are waiting to transition to post-school placements. Although the Hong Kong government has always subsidized special schools and social service agencies to provide transition support for people with intellectual disabilities (PIDs), there is still a lack of seamless transition between special school and post-school placements. International studies have found that problems commonly encountered by PIDs and their family carers include long waiting time for post-school placements, low levels of parental participation in transition planning, and lack of cooperation between school, family, and social service system. To adopt an ecological perspective, different types of transition strategies can be provided to enhance the quality of transition at the individual, family, school, and societal level. Transition strategies can be described as the ways to facilitate transition, and develop and enhance inter-professional collaboration, as well as inter-agency partnership or improvement of existing policies that may influence the transition. Research objectives include (a) to examine factors that promote quality transition between special school and post-school placements for PIDs and their family carers; (b) to investigate the components of overall transition plan and the type of quality transition strategies; (c) to examine the relationship between transition strategies, psychological well-being, and quality of life for PIDs and their family carers; (d) to recommend quality transition strategies which can be adopted by special schools and social service agencies that will help the transition. Method: A mixed-method research study will be adopted. Qualitative data will be collected to explore the problems experienced by PIDs and their family carers during the transition period. Moreover, the data will be used to generate questionnaire items measuring transition strategies. A quantitative survey will be followed to examine the relationship between variables such as transition strategies, parental stress, quality of life, and psychological well-being of PIDs and their family carers. The study will discover the components of quality transition strategies and factors that promote quality transition.


Project Reference No.: UGC/FDS16/H18/22
Project Title: Biophilic Sense and Sensibility: Exploring Human-Animal Coexistence in Contemporary Environmental Literature
Principal Investigator: Dr NG Chak-kwan (HKMU)


The proposed research project is designed to be an intellectual inquiry into the dimensions and significance of human-animal coexistence as represented in contemporary fictional and non-fictional writings related to animals that show an obvious environmental awareness. Engaging with recent developments in animal studies, ecocriticism, and environmental humanities, the project will draw from critical theories that not only address “the animal question” but go further to develop ontologies of human-animal interconnectedness in various ways. Underlying the existence of all forms of life is our embodied presence in the planetary system of Earth that depends on multispecies entanglement. The dichotomy of nature and culture is a long-standing myth that is sustained by anthropocentric assumptions and ideologies. Contesting anthropocentrism and exploring possibilities of biocentrism, this project seeks to discover and articulate how animal-related writings can illustrate the vitalness of human-animal coexistence that is rooted in our multispecies experience. These writings embody values and insights that can constitute what I would attempt to designate as an “aesthetics of biophilia”—a concept inspired by Edward O. Wilson’s biophilia hypothesis, which suggests our innate love of life and living things. Selected fictional and non-fictional writings created by both literary writers and naturalists will be read and interpreted along with interdisciplinary discourses of human-animal relationships and coexistence, of particular interest for this project are the eco-phenomenological tradition and recent posthuman developments, as well as ecopsychology for healing and rewilding as a conservation practice. Far from being isolated areas, they indicate the dimensions of human-animal coexistence that can inform the “aesthetics of biophilia” this project aims to develop based on the primary texts. Additionally, with its goals and methods, the study aspires to respond to Edward O. Wilson’s call for “consilience” across the humanities-science divide.

The project aims to accomplish four tasks that are interrelated to each other in a progressive manner: 1) Explore the significance of embodiment and entanglement in selected contemporary fictional and non-fictional writings and begin to develop an aesthetics of biophilia by examining how the writings enact human-animal coexistence performatively; 2) Study human-animal coexistence in relation to the concept of healing in ecopsychology in selected contemporary fictional and non-fictional writings to address the affective and emotional dimensions of the aesthetics of biophilia, including psychological rewilding and interdependence; 3) Investigate recent conservation approach of rewilding and how it is narrated in literature of rewilding. The ecological significance of such narratives will be analysed, seeing the restoration and recovery process in rewilding as performative acts that conjoin human to nature’s creative poiesis; 4) Promote the public interest in reading animal-related and environmental literature so as to stimulate greater awareness of biophilia and foster ecocultural identity through intellectual and literary discussions.


Project Reference No.: UGC/FDS14/P04/22
Project Title: Admixture Analysis of Multi-Site Multivariate Time Series
Principal Investigator: Dr NG Chi-tim (HSUHK)


In the Big Data Era, the data are collected from many locations at different time points. For example, the air pollution data may consist of 15 indices measured hourly at around 1000 cities over 5 years. Policy makers in economics, environmental protection, and agriculture are interested in identifying a few locations that serve as proxies for the driving forces that affect all locations. The changes in the contribution proportions of these driving forces over the time are useful indicators for both practitioners and academia.

The goal of this proposed research is to study the novel statistical models and methods that can extract the information from the multi-site multivariate time series data about the hidden driving forces that cannot be observed directly. This is solved in the proposed research by introducing the ideas of admixture analysis and latent Dirichlet distributions. These concepts have been employed by the researchers in the context of population genetics and text mining. This is the first research that extend these ideas to multi-site multivariate time series analysis. The admixture components in the novel model can then be used to describe the so-called hidden driving forces. With the extra time ingredient, we can further investigate the time of appearance and disappearance of a driving force. This cannot be done directly with existing time series clustering methods and factor analysis methods.

Computational methods and computer software are developed for the estimation of the proposed model and the results can be visualized through the choropleth map. Statistical theory is established explaining the changes in the properties of the estimations as the numbers of locations, time points, and variables increase.

The research results can find important applications in many areas in the future. Large scale of geographical data collected from the remote sensing technology helps to build an ecosystem conservation information system so that the specialist can monitor the changes in the hazardous factors in the ecosystem. The proposed methods can also be applied to design marketing strategy for a supermarket chain store where the sales time series data from different branches are analyzed.


Project Reference No.: UGC/FDS24/H08/22
Project Title: Gamification or VR or Both? Examining Antecedents in Encouraging Continuance Pro-environmental Behavior
Principal Investigator: Dr NG Mei-lan (PolyU SPEED)


Due to the COVID-19 pandemic, a higher volume of single-use plastic waste is generated from take-away food packaging globally, intensifying global warming. Previous research showed that human behavior is the major underlying cause of global warming and environmental degradation. To deliberately reduce the environmental harms, performing pro-environmental behavior (PEB) is vital. PEB is a voluntary behavior and has been gaining environmental and societal concern. PEB involves even small and everyday sustainability behavior and thus, cultivation of PEB is urgently crucial to achieving a more sustainable future world. Up to date, less work has been done on what constitutes people to engage in voluntary PEB, especially on teenagers. Previous research examined the importance of perceived value as a key driver of an individual’s continuous intention towards a particular behavior. Therefore, this research attempts to understand how teenagers’ perceived values affect the intention to perform PEB. In addition, this research makes an effort to address the “tools or means” that enhance the perceived value of teenagers in order to predict their intentions and continuance intentions towards PEB.

With the development of innovative technology, immersive technology and virtual reality (VR) have become very popular and accessible to the public. In addition, emerging gamification (i.e. gamified apps) encourages individuals, especially teenagers, to engage in a behavior, such as online shopping behavior, learning behavior, and prosocial behavior. Many current studies showed that the use of immersive technology and gamification would positively predict individuals’ intention towards a behavior.

Following this line of thought, the present study aims to examine the relationship between teenagers’ perceived values and pro-environmental behavioral intention using three experimental studies so as to fill in the research gap. Study 1 examines whether gamification affects the perceived importance of PEB and PEB intention towards pro-environmental behavior. Study 2 examines the relationship among teenagers’ perceived values, beliefs and norms towards performing PEB with the effect of immersive virtual reality (VR). Study 3 examines the effects of gamification and VR on (1) teenagers’ intention towards PEB, (2) habit and (3) continuation intention of PEB using longitudinal approach (T1 and T2).

The findings of the study will contribute to both theoretical and practical contributions. First, the findings will contribute to pro-environmentalism and sustainability literature by examining the use of gamification and immersive technology in engaging teenagers’ PEB. Second, the present study helps government-related bodies to identify significant antecedents of continuation intention towards pro-environmental behavior, in turn, policymakers can design a better marketing strategy to promote green, pro-environmental and sustainable behavior. Finally, the findings will help schools design appropriate games and activities to encourage continuance PEB intention and pro-environmental behavior of teenagers.


Project Reference No.: UGC/FDS14/P05/22
Project Title: Generalized Fiducial Inference and Model Selection on Multiple Change-point Detection in Autoregressive Time Series
Principal Investigator: Dr NG Wai-leong (HSUHK)


Change-point analysis in time series has received considerable attention in various scientific fields such as financial econometric, genetics, environmental studies, astronomy, and engineering in recent decades. It allows researchers to segmentate a nonstationary time series into several approximate stationary segments which can be analyzed using stationary models. In the existing change-point analysis literature, many of the research studies deal with the change-point detection in a frequentist approach where the asymptotic properties of the change-point estimators rely on the behaviors of a double-sided random walk. Another popular approach is the Bayesian approach where the locations of change-points follow a prior distribution. In this proposal, the main objective is to develop a new statistical inference approach for multiple change-point detection in structural break autoregressive time series in the framework of generalized fiducial inference, in which the unknown change-points are also treated as model parameters in the inference. Unlike the classical Bayesian statistical inference, generalized fiducial inference defines inferentially meaningful probability statements about the subsets of the parameter space without the need for subjective prior information. The resulting generalized fiducial-type confidence sets are often shown in simulations to have very desirable properties, for example, conservative coverages with shorter expected lengths than competing procedures.

When we transform a piecewise stationary autoregressive time series model in a specific linear form, the problem of detecting the locations of possible change-points can be transformed into identifying the nonzero entries of the regression coefficient vector, and thus multiple change-point detection can be viewed as a model selection problem. The models with different nonzero coefficient entries correspond to the models with different change-points, and the generalized fiducial probabilities of each model are evaluated to select the most probable change-points. Also, a generalized fiducial-type confidence set can be constructed for each change-point. A modified group LASSO will be developed and implemented for solving the computational complexity problem due to the vast parameter space. Asymptotic properties of the proposed approach will be investigated and established under some general conditions. 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 generalized fiducial model selection method for multiple change-point estimation) A generalized fiducial model selection approach for detecting multiple change-points in structural break autoregressive time series models will be developed. Generalized fiducial probabilities are evaluated for each possible change-point models to select the most probable change-points. Construction of a generalized fiducial-type confidence set for each change-point will also be developed.

2.  (Modified group LASSO approach for efficient computation) A modified group LASSO on the specific transformed linear form for the structural break autoregressive time series models will be developed. The aim of the modified group LASSO approach is to select a set of potential change-points before performing the generalized fiducial model selection which can largely reduce the computational burden due to the vast amount of possible change-point models.

3.  (Asymptotic theory for the change-point estimation and the generalized fiducial-type confidence sets) The asymptotic behavior of the multiple change-point estimation by the generalized fiducial model selection will be studied. The asymptotic exactness in the frequentist sense of the generalized fiducial-type confidence sets will also be studied under general conditions.


Project Reference No.: UGC/FDS14/H15/22
Project Title: Transnational Ageing and Family Processes among Elderly Hong Kong Parents
Principal Investigator: Dr NGAN Lucille Lok-sun (HSUHK)


Transnational ageing is particularly relevant to Hong Kong due to the combination of its ageing population, increasing population mobility and elongation of post-retirement life. Much of the scholarly work on transnational migration from Hong Kong since the 1990s has focused on the transnational mobility of emigrants who departed to the west before the 1997 handover of Hong Kong to China. While studies have provided insights into their continuous migration through the life course, we know very little about their migration trajectories and how they live within a transnational context in their old age. This neglect by scholars and policy-makers is partly due to the fact that this cohort of migrants have not reached old age until recently, but more so because of the perceived privilege of their social positions and the common assumption of reduced mobility in later life. However, as people who possess social ties abroad, privileged mobility and relative affluence, they are especially susceptible to being involved in transnational processes in their old age. Yet, until recently, scholars have treated ageing and migration as separate areas of study. Studies of transnational family migration detail how social relationships are sustained across distance, but they tend to focus on young and middle-aged adults, often during the departure phase. Studies of ageing and even policies relating to ageing have centred around ageing in one place, as the common assumption is that mobility is reduced in old age. The aim of this study is to understand the links between ageing and migration and their impact on the elderly and on society. This study will explore the transnational processes of ageing among elderly returnees in Hong Kong and Hong Kong–born elderly migrants residing abroad who are 60 years and over. Our overriding research question is: “How do elderly Hong Kong transnationals organise and cope with ageing in contexts that are no longer bound to the frame of a single nation state?” Employing qualitative research methods, we will examine their residential considerations, the role of non-proximate family networks in care circuits, transnational coping strategies and practices, and cross-border utilisation of elderly care services. The scholarly significance of this study lies in its contributions to new dimensions in the fields of Chinese transnational family migration and ageing through the collection of emerging data locally and abroad. Economically and socially, this study will contribute to identifying the weaknesses and strengths of Hong Kong’s family institution, labour market, ageing and healthcare policies, and elderly services.


Project Reference No.: UGC/FDS11/E05/22
Project Title: Deep Learning Based Face Super-Resolution: for Small and Incomplete Images
Principal Investigator: Prof SIU Wan-Ch (Caritas)


Nowadays, a low resolution image gives us the impression of low-tech, old fashion, awkward style and uncertainty. This is particularly true if the image is used for advertisement, surveillance, medical diagnosis or object recognition. The low quality face image might devalue a person’s beauty and faith. In order to relieve the problem we may turn the image into higher resolution, with super-resolution technology. Image super-resolution (SR) usually refers to an increase of the resolution of a single low-resolution (LR) image by up-sampling, deblurring and denoising, while the resultant high-resolution (HR) image should preserve the characteristics of the natural image, such as sharp edges and rich texture. This research work is on a study of large-scale face super-resolution of small images, or even incomplete images. In this work, an incomplete image refers to an image which is so small that it is faint and unclear, and part of the details might be missing. This is a very difficult and ill-posed problem, since a number of unknown pixels have to be inferred from very limited information, say in the case of 16x super-resolution, or even higher.

We propose to investigate large-scale face super-resolution not only because we have fruitful experiences in face recognition and regular face super-resolution, but enlarging a face with good quality is always demanding, and viewers can easily appreciate the effect of good quality. We must stress that results of our investigation should be useful for many applications, such as on-line teaching, video conferencing, remote medical diagnosis, remote operation monitoring, computational photography, video surveillance, multi-media amusement and metaverse. Actually, the resultant techniques can also be generalized (not limited to faces), applying to medical imaging, the development of low cost electronic microscope, etc.

We have a strong background in digital signal processing, imaging and video technology, pattern recognition, machine learning and deep learning, which are particularly suitable for this research. We start to propose a new and effective deep learning structure with back projection framework for the face super-resolution. Novel arrangement and new algorithms will be used with some new techniques in deep learning, including the generation of a latent edge component, back-project strategy, smart arrangement of StyleGAN for high-resolution face generation, attention mechanism for global structure acquiring, etc. The following are some more brief points.

(i) We start with the super-resolution of 64x64 face images to 1024x1024 images.

(ii) Edge quality is important to an image, hence we form latent vector structure which is generated with the assistance of the edge image generated from the original LR image.

(iii) Pre-trained StyleGAN which can generate sharp image is used to generate the high-resolution image, with the guidance of the edge image.

(iv) A new back-projection strategy is designed for the overall structure of deep learning network.

(v) Our initial test has verified that the above arrangement is good, and seems more attractive compared with conventional approaches.


Project Reference No.: UGC/FDS11/H09/22
Project Title: Health literacy (HL) in patients with chronic kidney disease (CKD): A sequential mixed method explanatory design study
Principal Investigator: Prof SMITH Graeme Drummond (Caritas)


Health literacy (HL) means much more than just the ability to read health-related information or make clinic or hospital appointments. For patients with chronic illness, like chronic kidney disease (CKD), HL is a personal attribute which relates to the achievement of a level of knowledge that can help to prevent the development of health-related problems and protect health. In 2022, the focus of World Kidney Day will be ‘Bridge the knowledge gap to better kidney care’, emphasizing the importance of information needs and HL in CKD.

Globally, CKD is becoming increasing common because of the growing prevalence of diabetes mellitus, hypertension, obesity, and ageing. Left untreated, CKD is likely to progress to end-stage kidney disease, with higher risk of mortality. Fundamentally, it is the patient who is tasked with understanding, implementing, and maintaining the medical recommendations for CKD self-management. As such, HL is of great relevance in vulnerable patient groups, like immunocompromised patients with CKD. Currently it is estimated that over a quarter of CKD patients have limited HL, however the full extent of the problem remains unknown in Hong Kong. Increasingly CKD management involves self-management activities, therefore, as well as HL it is crucial that patients have good levels of self-efficacy so that they can gain access to, understand, and utilize health-related information. Inadequate levels of HL constitute a risk factor for low health outcomes and poor treatment compliance. In addition, limited health literacy is associated with poor control of disease, greater risk of cardiovascular disease, more missed treatment appointments and higher rates of hospitalization. The current situation is made even more challenging for those with CKD due to COVID-19 related issues.

In face of these clinical challenges, HL-sensitive forms of communication and educational support packages may play an important role in successful disease management, slowing down the progression of this chronic disease.

It is proposed that greater understanding of information needs, and HL could increase local patients’ ability to self-manage their disease more successfully and slow down the progression of their chronic condition. Despite the proposed influence of HL, research into this important ability remains lacking in Hong Kong.

In this three-phase mixed method study, we aim to address this issue. From a quantitative perspective we plan to explore levels of general, COVID-19 related health literacy and levels of self-efficacy in individuals with CKD who attend one renal self-help group in Hong Kong with validated questionnaires, to address adequacy of levels of HL. Then from a qualitative viewpoint, focus groups will be used to identify information priorities and needs to ascertain barriers to understanding and acting on health-related information in this patient’s group. Based on the information gained in the second phase of our study, a tailormade online health literacy support package for CKD patients will be developed in the third phase.

In this study we hope to address an important current knowledge gap, reducing potential inequalities of care and having a positive impact upon the health of CKD patients in Hong Kong and beyond. Ultimately, improving levels of HL in CKD patients may help to slow down disease progression, promoting more effective levels of self-efficacy, self- management, and optimal health outcomes.


Project Reference No.: UGC/FDS14/H03/22
Project Title: Business News Treasures in the Vanishing Old Newspapers in Hong Kong: The History, Characteristics, and Social Impact
Principal Investigator: Dr SONG Zhaoxun (HSUHK)


Hong Kong boasts a more than 160-year history of business journalism, which began when The Hong Kong Ship Price Newspaper, the first Chinese language business newspaper, was published in 1857. However, research on the history, characteristics, and social impact of Hong Kong business journalism is scarce. What is more regrettable is that in the course of Hong Kong’s long history of business news communication, many newspapers have ceased publication. Pages and whole issues of some early newspapers are missing. There is an urgent need to rescue and preserve the vanishing historical legacy of business newspapers in Hong Kong.

The proposed project will carry out a historical source analysis of business journalism in the defunct Chinese language newspapers in Hong Kong, identifying the characteristics of business news writing and reporting at different times. It will document the main timelines and publication-related characteristics of the focal newspapers. It will also explore the impact of business journalism on Hong Kong society based on interviews with veteran media practitioners, historians and other scholars, taking both a journalistic perspective and a historical perspective.


Project Reference No.: UGC/FDS16/E05/22
Project Title: The Development of Recycled Oyster Shell Waste in Polymer-modified Green Concrete towards Enhanced Mechanical Properties and Environmental Benefits
Principal Investigator: Dr TANG Fanny Wai-fan (HKMU)


Due to the extensive usage in large-scale buildings, highways, bridges, dams, and marine engineering constructions, worldwide use of concrete has expanded dramatically. During the manufacture of cement, significant volumes of greenhouse gases are generated. Excessive dredging, extraction, and processing of natural aggregates has already disrupted local eco-systems and harmed the environment. The conventional concrete production has a substantial adverse effect on the environment. This has initiated a drive towards more sustainable concrete production, in order to decrease the greenhouse gas emission. Some researchers have made attempts to look for alternative materials to substitute conventional materials in concrete. The most economical and sustainable ways is to replace cement by using waste-based materials for the substitution.

Recycled oyster shell waste has been reported to have been employed in a variety of industries, including fishing, farming, and the construction of oyster reefs in several countries. Despite the fact that oyster shell waste can be recycled and used in a variety of ways, the bulk of oyster shell waste still ends up in landfills. As a result, the research project team will investigate how oyster shells might be reused to make value-added green concrete.

A few researchers have been conducted on the use of seashell waste replace the coarse aggregates in concrete. However, there is no research on the reuse of oyster shell waste replace the cement and to improve the concrete properties of infrastructures. It is also worth to note that two more challenges in this research project. First, there is no standardized composition and weight percentage of oyster shell waste, aggregates, cement and polymer resin to provide optimum strength enhancement in concrete. Second, there is no comprehensive supply chain, beginning from the collection of oyster shell waste and pre-treatment to adaption of concrete with reused oyster shell. In this regards, the research project team will investigate this new and innovative research to provide sustainable construction materials.

In this project, oyster shell waste (particle or powder form) will be used to mix with polymer-based binder to replace traditional cementitious materials to develop green concrete, a comprehensive supply chain, beginning from the collection of oyster shells and pre-treatment to manufacture waste-based concrete with reused oyster shells, will be explored to determine the optimum mixture design of oyster shell waste, aggregates, cements and resin to obtain a cost-effective alternative for sustainable construction materials. Oyster shell waste is abundant with no cost (some cost is incurred only for the collection of the shells). By best using this waste could help the world solve many key problems, like huge amount of carbon dioxide coming from the production process of cement.


Project Reference No.: UGC/FDS16/H06/22
Project Title: A study on competency levels of post-secondary students in detecting fake news on social media in Hong Kong
Principal Investigator: Dr TANG Ko-wai (HKMU)


Since the recent social and health problems in Hong Kong began in June 2019, there has been a sudden rise in fake news. Social media allows users to rapidly disseminate fake news to other users, which may increase the circulation of false or misleading information. Fake news on social media affect stock markets and decelerate responses during disasters and even terrorist attacks.

Fake news has become an important issue today, which we are nowhere close to solving. Primary, secondary and post-secondary students must be guided and helped to detect fake news. There is no instrument to measure the competency levels of fake news detection competency level, and we should urgently attempt to understand it. Therefore, this proposed study attempts to address this gap.

The development of an instrument to measure fake news competency for post-secondary students is proposed. In consideration of the nature of fake news and the theoretical concept of information literacy, three characteristics of fake news—content, appearance, and motivation—and two of the latest information literacy frameworks—the Association of College and Research Libraries (ACRL) Information Literacy Competency Standard for Higher Education Students and the Hong Kong Information Literacy learning Framework—will be referred to by the proposed study.

This study will adopt a mixed approach to address the research questions. First, a qualitative study will be conducted to gather insights regarding post-secondary students’ aptitude and understanding of fact-checking fake news by using fake news identification tasks and semi-structured interviews. Based on the results of qualitative study and the theoretical background of information literacy, an attempt will be made to develop an instrument that includes surveys and quizzes. This will be followed by a quantitative study of the perception and competency of fake news detection among post-secondary students.

This study will contribute not only to the local community by introducing an instrument to measure the competency levels of fake news detection but also to the research community by providing theoretical advancements in the field of fake news and information literacy.


Project Reference No.: UGC/FDS25/E04/22
Project Title: Development of synergistic dual-atom catalysts with high activity and superior durability for catalytic hydrogen release reactions
Principal Investigator: Dr TSANG Chi-wing (THEi)


Climate disruption due to fossil fuels depletions is among the most challenging environmental issues confronting the society today. Hydrogen, as a clean energy carrier, can provide solutions for these problems since it can be derived from renewable resources such as water and can achieve the target for carbon neutrality. To realize hydrogen economy in a society, several technical bottleneck areas need to be urgently addressed, namely, the production, transportation and the storage, in which the last one remains as the hurdle to the widespread use of hydrogen for automotive applications. Current commercial hydrogen fuel cell powered vehicles use either compressed hydrogen tank, cryogenic hydrogen tank, liquified hydrogen tank, or metal hydride tank, and there are problems such as extra energy requirement for compression, liquefaction and adsorption/desorption process. On-board hydrogen production using water electrolysis and photocatalytic water splitting are another on-demand hydrogen options. However, the processes are generally energy intensive and sluggish, which are not practical for commercial uses. Obviously, a much safer and less-energy intensive option would encourage the use of hydrogen in Hong Kong. The use of safe and hydrogen storage materials with high mass energy density such as ammonia borane (AB) and formic acid (FA) could be a solution for this. These materials are generally very stable and only release hydrogen under special catalytic conditions. Currently, developing efficient, durable and low-cost metal catalysts for catalytic hydrogen generation from hydrogen storage materials is crucial to solving the bottleneck for the delivery of safe hydrogen power in automotive devices. Up to now, the best record to release all stored hydrogen from hydrogen storage materials such as ammonia borane is the Rh nanoparticle catalyst supported on g-C3N4 carbon material, with a turnover frequency of 969 molH2 molRh-1 min-1 at 25°C. However, they are still far from commercialization, due to technical challenges such as high cost, sluggish activity and low stability. Non-precious metal catalyst such as Co, Fe, Ni and Cu are much less costly but they generally exhibit low durability (reactivity dropped to 60% after five runs) and sluggish reaction rate. Metal nanoparticles tend to agglomerate to form larger particles due to the relatively large surface free energies, thus further decrease the durability. Also, nanoparticles generally have much lower atom utilization, thus leading to slow reaction rates. Interestingly, our recent preliminary studies showed that non-precious metal catalysts such as Co when they were downsized to the atomic scales to single atom could reach to 18.5 molH2 molCo-1 min-1 at 40°C, while the CoCu dual-atom catalyst could reach to 34.7 molH2 molCoCu-1 min-1 at a much lower temperature (25°C) with better durability, in which the rate was comparable to some precious metal catalysts. The improved rates could be ascribed to better atom utilization of these catalysts having atomically dispersed active sites. However, method to precisely synthesize dual-atom catalyst and the relevant mechanism of the synergistic effect remains elusive. In this project, 1) a novel pyrolytic method for synthesizing dual-atom anchored single atom catalyst (DASACs) with atomically dispersed active sites will be developed; 2) stable and durable dual-atom catalysts will be designed with unique coordination environment, which can effectively prevent metal atoms agglomeration; 3) the structural-activity relationship will be established between the catalytic performance and the physicochemical properties; 4) the nature and environment of the dual-atom active sites will be unequivocally determined by using advanced characterization techniques, such as the high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) and the synchrotron radiation (SR) techniques. Importantly, the mechanisms of the synergistic effects of the neighboring atom pairs in confined space will be elucidated, using the density functional theory modelling (DFT). This project will enable better understanding of the hydrogen release mechanism, synergistic effects and subsequently provide guidance to rationally design effective and high-performance catalysts for hydrogen release from high-capacity hydrogen storage materials, thus moving a step forward towards hydrogen economy and carbon neutrality in Hong Kong.


Project Reference No.: UGC/FDS21/H01/22
Project Title: A randomized controlled study of Collective Motivational Interviewing (CMI) for adolescents with internet gaming disorder
Principal Investigator: Dr TSE Ka-wo (CTIHE)


Internet gaming disorder (IGD) is a widespread public health problem. Excessive online gaming by adolescents could lead to getting too little sleep, eating improperly, failing to maintain proper personal hygiene, and withdrawing from social interactions, which also detriment interpersonal development.

Collective Motivational Interviewing (CMI) is a locally innovated change technology to mobilise a client’s motivation to change with the support of concerned significant others (CSOs). CMI roots in the forty decades of Motivational Interviewing (MI) evidence in addictive treatment, groundbreaking to engaging CSOs into the motivational process to cultivating positive and productive dialogues among the involved parties.

Our international research team will conduct a randomized controlled trial to test the efficacy of CMI in improving IGD among adolescents with IGD in Hong Kong. The primary outcome of the efficacy of the intervention will be indicated by the severity of IGD symptoms, together with secondary outcomes of motivation to change maladaptive gaming behaviour, craving for gaming, and social support from CSOs. The present study will also contribute to the local Chinese community with a practical intervention approach for counsellors, social workers, and service providers to improve the quality of life among adolescents with IGD and their CSOs.


Project Reference No.: UGC/FDS14/B10/22
Project Title: How do Team Insiders Respond to Newcomer Voice? A Mutual Influence Perspective of Newcomer Entry on Team Innovation
Principal Investigator: Dr WANG Amy Yamei (HSUHK)


To innovate successfully, organizations are increasingly striving to recruit new employees who can contribute their knowledge, fresh perspectives, and creative ideas. However, the arrival of a newcomer may not automatically translate into positive team-level outcomes as the adjustment of existing team members to the newcomer may be a stressful and resource draining experience. As virtually any established group must engage in some redevelopment or adaptation to accommodate the entrance of a newcomer as well as work together to achieve collective goals, much remains unexplored about the effects of new employees on existing team members, team dynamics, and the processes through which team outcomes unfold. Therefore, critical questions remain about whether, how, and when old team members respond to newcomers to influence team level outcomes. To address this important conjecture, this project aims to 1) examine the effects of newcomer entry within an expanded social context that highlights the presence, roles, and reactions of team insiders; and 2) identify and explore the mechanisms through which existing team members may respond differently to newcomers.


Project Reference No.: UGC/FDS16/E09/22
Project Title: Representation and Extraction of Quantitative Information for Large-scale Unstructured Healthcare Text Analysis
Principal Investigator: Prof WANG Fu-lee (HKMU)


Severe Acute Respiratory Syndrome (SARS) is the first disease to hit the global community in the 21st century. Twenty years after, the world is fighting against COVID-19 desperately. The community is now very vulnerable to major diseases. Fast processing of medical data can help to win the battle. It is of great need to develop novel techniques to process massive healthcare data utilizing advanced artificial intelligence methods. A large amount of valuable healthcare data exists in unstructured texts such as diagnosis records, ward round records, discharge summaries, online health discussions, medical literatures, and eligibility criteria of clinical trials. Among the various unstructured texts, quantitative information frequently occurs across languages and domains. For example, more than 40% of unstructured clinical trial texts contain explicit quantitative statements. Quantitative information describes fundamental properties associating with the magnitude aspect of quantity, which are necessary for defining and comparing clinical phenotypes such as medical attributes, demographic entities, and lab test values. The automated representation, extraction, and application of quantitative information are thus essential for patient eligibility determination, patient status assessment, patient condition monitoring, evidence-based medicine, disease risk prediction, infection prevention and control, clinical decision supports, etc.

Therefore, it is of great demand in developing effective methods for the representation and extraction of quantitative information to facilitate the analysis of healthcare texts such as clinical trials. There are four fundamental components in quantitative information, including entity, numeric value (or range), measurement unit, and comparison relator, while each component may have complex expressions. However, the current research of quantitative information representation and extraction faces several challenges. Firstly, there are abundant of medical terms and abbreviations causing low performance of common nature language processing tools. Secondly, multiple quantitative statements may co-exist in the same sentence and thus co-reference resolution is difficult for associating identified constructs correctly. Thirdly, a mass of healthcare texts contains incomplete or implicit statements such as missing measurement units, causing difficulties for component identification. Fourthly, various representations of comparison relators frequently occur in healthcare texts such as negation usage, special symbols, and implicit contexts. Finally, the relation contradiction problem exists in certain informal healthcare texts. These challenges cause huge difficulties for the relevant research on quantitative information in medical domain. At present, there are no effective methods available for representing and extracting quantitative information yet.

This project aims to design novel automatic methods for reliable quantitative information representation and extraction to enhance large-scale healthcare text analysis and their applications. To that end, this project will design a new model for representing quantitative information in a formalized manner with a newly designed markup language. In addition, a new neural network-based model will be developed for extracting medical entities, numeric values, units, and relators, as components of quantitative statements. After that, a new model will be developed to acquire complete quantitative information by associating the extracted components. The models will be applied to process at least three large-scale healthcare text datasets in English and Chinese, including 451,571 clinical trial studies covering 220 countries/regions for analyzing their commonalties and differences to contribute to healthcare advance. On the other hand, the proposed techniques can be extended to testing and certification industry that is a pillar industry in Hong Kong.


Project Reference No.: UGC/FDS14/E05/22
Project Title: MetaConfigurator: A Resource-Effective Method to Develop Needs-Based Configurators for Product Customisation
Principal Investigator: Dr WANG Yue (HSUHK)


Product configurators are considered to be critical toolkits for customised product design and have been successfully implanted in various companies, such as Dell, BMW and Nike. Among the various versions of product configurators, needs-based systems are particularly useful to map customer needs in natural language directly to the targeted product configurations. Although needs-based configurators are more user-friendly and applicable in B2C environment, they are resource intensive to be implemented. A large amount of product relevant data such as customer needs are required to be collected, annotated, and processed to train the configuration model. Such approach is, moreover, limited to one product family and cannot be generalised to other products or even the updated product family. This restricts its wide application in practice.

This proposal will develop a MetaConfigurator framework to overcome these challenges. We will leverage natural language processing, deep learning and transfer learning techniques to interpret ambiguous and probably ill-defined customer needs sentences and map them to well-defined product configurations. Using the massive amount of product review data from e-commerce website, we firstly extract product related knowledge or features in a product category. Then, the generic knowledge is adapted to a specific product using a relatively small amount of customer needs data to build the product-specific needs-based configurator. Through this pretraining-then-finetuning process, a more user-friendly product configurator can be derived in a more efficient way.


Project Reference No.: UGC/FDS15/H01/22 (Withdrawn)
Project Title: Hong Kong as the Pioneer Disseminating the Information on the West to the East: Retrace and Reinterpret the Intellectual Source for China’s and Japan’s Modernization in the Second Half of the 19th Century
Principal Investigator: Prof WEI Chuxiong (Shue Yan)


Project Reference No.: UGC/FDS16/M04/22
Project Title: Antihypertensive effects of traditional, aqueous and solvent extracts of Danshen, Danshensu and Tanshinone IIA and their combination on Bevacizumab-induced hypertension
Principal Investigator: Dr WONG Emily Sze-wan (HKMU)


Bevacizumab (Bev) is a monoclonal antibody acting on the vascular endothelial growth factor (VEGF). The drug has anticancer effect by inhibiting the angiogenesis. Though the drug has been recognised as the first line treatment of colorectal and non-small cell lung cancer, induction of hypertension is a common adverse effect of Bev. The key mechanisms may be due to the disturbance of relaxing factors [nitric oxide (NO) and prostacyclin] in blood vessels, increased intraglomerular pressure in kidneys, and increased blood lipid level.

Nowadays, there are still no evidence-based guidelines on the treatment of Bev-induced hypertension. Angiotensin converting enzyme (ACE) inhibitors are usually prescribed as they show efficacy in controlling Bev-induced hypertension. However, some recent studies reported that ACE inhibitors, such as perindopril and enalapril, may inhibit the anti-angiogenic effect of Bev and hence, decreasing its therapeutic effect. In addition to ACE inhibitors, other common types of antihypertensive drugs, such as angiotensin-receptor blockers (ARB), diuretics, calcium-channel blockers and beta antagonists, are not the proper choices for treating Bev-induced hypertension.

It is essential to identify a potential drug for treating Bev-induced hypertension. This drug should be effective in treating this hypertension by targeting on the key mechanisms described above and at the same time, the drug should not counteract the anticancer effect of Bev. It will be an advantage if the potential drug has additive or synergistic anticancer effect with Bev. Clinically, Chinese herbal medicines have been used in combination of antihypertensive or anticancer Western drugs. The therapeutic effects of combined therapies have been proved. Hence, Chinese herbal medicine may provide a potential candidate for treating Bev-induced hypertension. However, not much have been done on the antihypertensive effect of Chinese medicine on Bev-induced hypertension except our recent study in which the active component of Danshen, Danshensu, could reverse the disturbance of vasodilatation caused by Bev in rat mesenteric artery (data has not been published).

Danshen (root of Salvia miltiorrhiza) is a traditional Chinese herbal medicine. Clinically, the herb has been commonly prescribed in the oral-intake form of traditional decoction to treat cardiovascular diseases such as myocardial infarction, stroke, coronary heart disease, hypertension, renal injury and hyperlipidemia. Recently, aqueous extract of Danshen was reported to have anti-VEGF property which is similar to that of Bev. Danshensu [3-(3,4-dihydroxyphenyl)-2-hydroxy-propanoic acid], the chief biological active and water soluble component in Danshen, can reduce both systolic and diastolic blood pressure in spontaneously hypertensive rats via the NO and prostaglandin pathways. Tanshinone IIA (Tan IIA), being the most abundant lipophilic active component of Danshen, also shares similar effects on regulating blood pressure, renal protection and lowering blood lipid level.

A single crude herb of Danshen contains over 200 chemical components. Components to be extracted e.g. aqueous and lipophilic compounds, depends greatly on the extraction methods. Clinically, Danshen is used to be prescribed in oral-intake form of traditional decoction. Regarding the clinical applications and recent studies, we hypothesise that Danshen’s traditional decoction extract, aqueous extract, solvent extract and Danshen-derived active components (Danshensu, Tan IIA and their combination) may have different effects on Bev-induced hypertension. Our present study is to find out the best derivative of Danshen for the concurrent treatment with Bev and their underlying mechanisms. The results will provide strong support for clinical application of Bev, and hence, Chinese-Western medicine combined therapy.


Project Reference No.: UGC/FDS11/H04/22
Project Title: To retire or to work: Factors determining the decision of middle income earners in their old age
Principal Investigator: Prof WONG Yu-cheung (Caritas)


Inadequate retirement protection has long been a pressing problem for the elderly in Hong Kong. The major retirement pillars for the general public are the Mandatory Provident Fund (MPF) introduced in December, 2000, and the social security system for the low-income group. After the recent reform of the retirement system in 2017, half of the elderly persons are now supported by the means-tested social security system, which provides about 20% of the median employment income. The rest of the population have seen no substantial improvement for them. Those who earn higher than the median income will not be eligible for social security upon retirement and probably many years afterwards. Many will find it hard to maintain their standard of living if they retire at the normal retirement age of 65, and so must work afterwards. In the 3rd quarter of 2021, around 26% of those aged between 65 and 69 were still in the labour force, with a higher labour force participation rate among the male population (36.3%).

This study will focus on those aged between 65 and 69 who were employed at 60-64 with an employment income fell into the third income quartile regardless whether they are in the labour force or not at the time of interview. In the third quarter of 2021, this income quartile was between $20,000 and $33,000. The income range varies depending on their age during the interview. This proposed study will investigate their retirement and employment arrangements, namely, whether they are not-retired, i.e. having either a full-time or part-time employment, temporarily retired but having an intention to seek job, or completely retired. For those who are temporarily or completely retired, they will be further classifed as voluntary or involuntary in such arrangements based on whether they are dismissed or displaced from their job, and whether they retire completely because they believe that they cannot find suitable job in the labour market even if they want to work.

It will also study the factors associated with such arrangements, as well as the challenges they faced as elderly job-seekers and employees. Specifically, these factors will include financial readiness, caring responsibilities, and perceived age discrimination practices. A number of personal factors, such as gender, property ownership, health conditions, occupation, and family composition will be collected and controlled to identify the contribution and relative importance of these factors in their employment and retirement arrange.

A representative sample of the elderly persons aged 65-69 meeting the income criteria when they were 60-64 will be identified through randomized telephone contacts, followed by a survey with a structured questionnaire. The effective sample size will be 500. Follow-up in-depth interviews will be conducted with 18 respondents based on the result of the survey to gain more insights into the trajectory of their retirement and employment arrangement, and the process and mechanisms they made their decisions.

The study will generate useful information to make policy suggestions to improve the employment environment to allow them to have more and better choices after normal retirement age.


Project Reference No.: UGC/FDS15/H03/22
Project Title: Settlement towns built on the north-eastern steppe of Inner Mongolia during Khitan-Liao and their impact on Chinese history: A new inquiry on Touxia
Principal Investigator: Prof YANG Ruowei (Shue Yan)


This proposed study aims to investigate and examine settlement towns built on the north-eastern steppe of Inner Mongolia in Khitan-Liao (907–1125) with a focus on those recorded as ‘Touxia’ (投下). The impact of these settlement towns was felt not only by their contemporary social, political, and economic structures, but by later Chinese dynasties, as well. They had subsequent impact on the governance of diverse ethnicities and the development of agriculture and animal husbandry societies, and on the connections and interactions between China and Eurasia.

However, what were these towns known as Touxia and what does the term actually mean? This remains a mystery today. The term Touxia first appeared in historical records for the Khitan-Liao, followed by historical literature of the Mongolian-Yuan, and then disappeared suddenly from all later historical Chinese documents. Wang Guowei (王國維) first traced the etymology of Touxia in 1923, attracting sustained scholarly interest ever since in China and overseas. After almost a century of study, researchers generally have concluded that residents in Touxia were Han and other agricultural peoples captured in wars by the Khitan royal family and aristocracy, and these settlement towns are believed to be a unique system independent from the local prefecture and county systems of the empire. However, there are many doubts about this conception of Touxia, including its origin, governance, operation, and development, which has made it one of the major outstanding unsettled mysteries of the Khitan-Liao history.

As the main source of data for the study of Khitan-Liao – Liao Shi (遼史), one of the official twenty-four histories of China – is known for its crudeness, simplicity, and errors, the study of Touxia faces a serious lack of information. In particular, due to the multi-ethnic and multi-lingual coexistence across the vast territory of Khitan-Liao, the study of Touxia faces a distinct ethnolinguistic issue, which makes using only the interpretation of Liao Shi especially unreliable. To solve these problems, this proposed research will collect and analyze multi-source data from the perspectives of history, ethnology, linguistics, and archaeology.

To study Touxia, this project will consist of three stages. The first stage is mainly a visit of historical sites and local museums in the area where Touxia were located – eastern Inner Mongolia and western Liaoning today – to collect and inspect data including stele inscriptions, unearthed archaeological material, gazetteers and other historical records. The second stage is the analysis, starting with the comparison and cross-verification of all available data both newly collected and previously concerned or underestimated by other studies. The study will then examine Touxia from its linguistical origin, etymology, and semantics to its physical emergence, population composition, governance structure, and financial and military relations to the central government at different times of the dynasty. On this basis, the third and final stage of the project will organize and present the new material and associated insights into the Khitan-Liao history. Expected outputs include new arguments on the interpretation of Touxia and a conceptual framework of the local political and administrative institutions of Khitan-Liao through the case of Touxia. Based on collected evidence, the study will contribute to discussion of the centralized and decentralized paradigms of the political systems of that time, to systematic study of the political structure and power order of the empire, and to a juxtaposition between Khitan-Liao and its successors – Jurchen-Jin and Mongolian-Yuan. As the emergence of settlement towns in the steppe region was an innovative practice of the nomadic regime, this proposed study will offer new insights not only for the Khistan-Liao, but also for its influence on subsequent dynasties in pre-modern China and Inner Asia. The study will also have theoretical and practical implications for modern times, particularly in providing historical references for the coexistence and governance of diverse ethnic groups, as well as the process of urbanization in societies.


Project Reference No.: UGC/FDS14/B08/22
Project Title: Feedback Strategy for Motivating Loyalty Program Members in the Digital Era: The Role of Progress Framing
Principal Investigator: Dr YANG Xin (HSUHK)


Loyalty programs (LPs) are used widely in the hospitality services industry to stimulate consumption and strengthen consumer engagement. Digital technology has accelerated the use of LPs, with many firms relying on mobile LP applications (apps) to provide instant feedback to members regarding dining points, hotel stay points, frequent flyer miles, and the like that can be redeemed for program rewards or membership renewal/upgrade. Recently, the growing popularity of digital ordering during the COVID-19 pandemic has accelerated the use of digital LPs by firms to entice mobile app consumers. However, most LPs have failed to deliver the expected results, with surprisingly high levels of membership inactivity—as approximately 54% of app-based loyalty memberships become inactive within 1 year (Payments Journal, 2021).

The LP literature does not offer much guidance on how to solve the above problems, as most LP studies focus on understanding how to attract potential members (e.g., Gorlier and Michel, 2020; Steinhoff and Palmatier, 2016). But if the main purpose of LPs is to build loyalty through repeat patronage (Yang et al., 2021), arguably it is more important to examine how to motivate LP members to pursue LP rewards (Knowledge Gap 1) and to engage in their LPs (Knowledge Gap 2).

The proposed research aims to address these knowledge gaps by investigating how LP managers can develop effective feedback strategies that motivate existing members to pursue rewards and to engage in LPs. This research identifies two common but distinct feedback strategies that are used by many firms to update their members of their progress toward LP goals. Specifically, a looking-back feedback strategy highlights the progress already made, and a looking-forward feedback strategy highlights the progress yet to be made. This research proposes a conceptual framework that yields a series of novel hypotheses concerning the relative effectiveness of looking-back feedback versus looking-forward feedback strategies as a function of (1) program reward features and (2) program tier features. Both controlled experiments and field experiments will be employed to explore the interactions between different feedback strategies and loyalty program features. This research will enrich the limited LP literature on sustaining member interest and engagement and will guide LP managers to design effective feedback strategies to motivate their members.


Project Reference No.: UGC/FDS15/H15/22
Project Title: The interactions of L1 and L2 tonal systems in Mandarin-Cantonese late bilinguals
Principal Investigator: Dr YANG Yike (Shue Yan)


Nowadays an increasing number of people learn a second language (L2); however, accents are commonly found among late L2 learners, even after years of extensive exposure to the L2. Although there may be different accent sources in an L2, non-nativelikeness in L2 pronunciation is generally regarded as having been influenced from the learner’s first language (L1). At the same time, during the process of L2 acquisition, the learner’s L1 may also exhibit alteration due to influence from the L2, which is defined as L1 attrition. Research into L1 attrition and L2 attainment, however, has gone in two separate directions in terms of bilingual language development. Consequently, L1 and L2 interactions remain poorly understood.

Current speech learning models (e.g., Flege & Bohn, 2021) generally suggest a common phonetic/phonological space for L1 and L2 in the bilingual speaker’s mental representation, and they thus assume influences from the L1 to the L2. While some research points to the possibility of bidirectional influences between the L1 and L2 segments, it remains to be explored whether the tonal systems also show interactions of the L1 and L2. This proposed study attempts to associate both L1 attrition and L2 attainment and aims to closely investigate the possible interactions of the L1 and L2 tonal systems in Mandarin-Cantonese bilinguals. As two closely related Chinese dialects, Mandarin and Cantonese are tonal languages, and the differences in their tonal systems provide a natural environment for testing the hypotheses of speech learning models.

To fill the gaps in previous research, this proposed study has four aims: 1) to systematically examine the bidirectional influences between an L1 and an L2 in terms of the tonal system; 2) to test whether Mandarin-Cantonese bilinguals show attrition of the L1 in tone production and perception and whether they can have comparable performance with native speakers in L2 tone production and perception; 3) to combine both acoustic and perceptual measurements for the analysis of read speech and spontaneous speech, which is our methodological contribution; and 4) to probe potential non-linguistic factors that may foster phonetic attrition of a native language and phonetic acquisition of a target language. This study will recruit immigrants who spoke Mandarin as the only Chinese dialect before arriving in Hong Kong and speak fluent Cantonese. Another two groups of participants will include native Mandarin speakers with limited exposure to other Chinese dialects and native Cantonese speakers, both of whom will serve as this study’s control groups. The participants will perform various tasks in two experiments. The first experiment is the production of read and spontaneous speech, the data of which will be assessed acoustically and perceptually. For the perception experiment of lexical tones, the participants will be required to complete an identification task and a same-different discrimination task.

As the first attempt to systematically investigate the interactions of the L1 and L2 tonal systems in bilinguals, this study will provide evidence for or against the postulates of current speech learning models and advance our theoretical knowledge of L1 and L2 interactions. The results from this proposed research will also inform language teachers of the particularly challenging Cantonese tones for Mandarin-speaking learners, allowing the teachers to revise their syllabi and pedagogies when they are teaching Mandarin-speaking learners of Cantonese. Furthermore, this research will provide immediate research opportunities to undergraduate students, better preparing them for their future academic and career development.


Project Reference No.: UGC/FDS24/E08/22
Project Title: Time Series Artificial Intelligence for Energy Management of Chiller System
Principal Investigator: Dr YU Fu-wing (PolyU SPEED)


Chiller systems are commonly used to provide cooling energy with at least one-quarter of the total electricity consumption in commercial and institutional buildings. The energy performance of chiller systems depends on weather conditions and how operating variables are controlled within their settings which have time-dependent features. To improve and optimize the operation of chiller systems, it is worth exploring AI-based time series models to analyze the short- and long-term variations of the system cooling load and electricity consumption. Such a model would facilitate energy management and optimal operation of chiller systems.

This project aims to develop AI-based time-series models to carry out the energy management and optimization of chiller systems. A literature review will be conducted to identify suitable algorithms to model the operation and energy performance of chiller systems in commercial and/or institutional buildings. Field investigation will be carried out on one or two chiller systems with sophisticated data acquisition in order to collect comprehensive operating data and control requirements. The chiller system in PolyU Hung Hom Bay Campus serves as a case study because it is equipped with a trend logging facility to archive operating statuses and energy-related data of system components at 15-minute intervals. The operating data and control settings will be compiled to derive system input and output variables for developing the models. Proper algorithms will be selected to construct time-series models to simulate the cooling capacity output and electric power input of the chiller systems studied. Time series characteristics of operating variables will be analyzed to explore if deficiency exists in the current control and operation and hence to identify opportunities for system optimization.

The significance of this project is to demonstrate essential AI techniques to facilitate the energy management and optimization of chiller systems and minimize their electricity consumption while providing adequate cooling capacity. The chiller system improvement would eventually enhance the sustainable operation of commercial and institutional buildings to meet the carbon neutral plan in Hong Kong.


Project Reference No.: UGC/FDS14/P07/22
Project Title: Joint Sparse Optimization: Nonconvex Penalty Theory and Applications
Principal Investigator: Dr YU Kwok-wai (HSUHK)


Big data plays an important role in various disciplines. Joint sparse optimization is a practical technique for solving many big data problems, which adopts a synchronous effect of the multiple responses to enhance big data analysis. It has been successfully applied in various fields, such as multi-response regression, multi-task machine learning, multi-channel signal processing, distributed compressed sensing and systems biology. Extensive empirical studies in sparse optimization have showed that nonconvex penalty methods usually admit a significantly stronger sparsity promoting capability and a notably more robust sparse recovering stability than the (convex) 1 regularization method. However, the development of mathematical theory of joint sparse optimization is still in its infancy, especially for nonconvex penalty methods.

In this project, we will consider the nonconvex penalty method for joint sparse optimization (NPJSO), including smoothly clipped absolute deviation, minimax concave penalty, p regularization (p<1) and capped nonconvex penalty, and investigate its consistency theory of nonconvex optimization models and convergence theory of first-order optimization algorithms, as well as the phase transition theory of NPJSO problem and algorithms, and further discuss applications to systems biology. In the theoretical aspect, we will adopt a notion of joint restricted eigenvalue condition relative to the penalty (p-JREC) to establish the recovery bounds (including model error, absolute deviation and 2 recovery bound) for the global minima to quantitatively estimate the stability of the NPJSO. We will further calculate the lower bound of sample ratio for a random matrix such that it satisfies the p-JREC, and thus establish the phase transition theory of the NPJSO to exposit its theoretical sparse recovery boundary. In the algorithmic aspect, we will impose the continuation technique to the proximal gradient algorithm (PGMC) and the alternative direction method of multiplier (ADMMC), and will then employ the p-JREC to establish their convergence to an approximate ground true joint sparse solution (within a tolerance proportional to the noise level and the recovery bound) at a geometric rate. Moreover, the phase transition theory for nonconvex PGMC and ADMMC will be established for random matrices. This convergence theory will provide positive theoretical evidence to the sparse recovery availability of certain nonconvex sparse algorithms, and it will fill the gap of certain nonconvex penalty methods. In the application aspect, we will apply our theoretical results and numerical algorithms to solve the master gene regulator inference problem of cell fate conversion that is a powerful tool in developmental biology and regenerative medicine. The successful application to master gene regulator inference for cell fate conversion will help biologists to facilitate fast identification of key regulators, give raise to the possibility of higher successful conversion rate and in the hope of reducing experimental cost.


Project Reference No.: UGC/FDS17/M07/22
Project Title: Cure of Epstein-Barr virus in nasopharyngeal carcinoma cells through combinational CRISPR/Cas9 and CRISPR/Cas13 targeting
Principal Investigator: Dr YUEN Kit-san (TWC)


Nasopharyngeal carcinoma (NPC) is a common health problem in southern China, including in Hong Kong. The majority of patients diagnosed with advanced stage NPC may not respond well to conventional treatment, i.e., radiotherapy or chemotherapy. There is thus a critical need for novel effective treatments to improve the clinical management of this deadly malignancy. In this regard, given that NPC is an Epstein–Barr virus (EBV)-driven carcinoma, eliminating the EBV genome and/or viral transcripts from NPC cells warrants exploration as a novel treatment. In this project, we aim to develop such a treatment in the form of a novel CRISPR/CRISPR-associated protein (Cas) method for targeting EBV in NPC cells. First, we will obtain a proof of concept that CRISPR/Cas13-targeting of essential RNA components of EBV is an effective anti-EBV approach that may be applied as an NPC therapy. Second, to characterize the adjuvant role of the CRISPR/Cas system to the currently available chemotherapy agents to serve as a dual therapeutic approach to treat NPC. Third, to develop and optimize a protocol for the delivery of CRISPR agents to NPC cells.

This project will establish the feasibility of using a combined CRISPR/Cas9– CRISPR/Cas13 system to eliminate EBV from NPC cells. Crucially, this system may be able to be extended to develop a universal EBV inhibitor that can be used to treat patients suffering from any EBV-associated disease, including EBV+ lymphoma and gastric carcinoma.


Project Reference No.: UGC/FDS24/E03/22
Project Title: A Novel Real-Time HVAC Strategy based on Lightweight CFD Integrated with Reinforcement Learning for Public Transportation in Hong Kong
Principal Investigator: Dr ZHANG Hao (PolyU SPEED)


Hong Kong Government has proposed a carbon neutrality target which is expected to achieve by 2050. Since transportation represents almost two-tenths of Hong Kong’s carbon emissions, the city has set out long-term plans to push the adoption of electric public transportation, particularly electric buses (i.e., e-buses). However, due to the constraints of energy storage in batteries, the concern of driving range is one of the main reasons that e-buses have not yet been utilized in Hong Kong. The Heating, Ventilation, and Air Conditioning (HVAC) accounts for the most considerable burden of e-buses driving range among all auxiliary systems. Notably, the outbreak of COVID-19 has intensified the requirement of HVAC in public transportation. Currently, the HVAC strategy on public buses is deemed neither effective nor energy efficient. On the one hand, it is failed to achieve a comfortable and healthy micro-environment for passengers on board, especially during this COVID-19 period. On the other hand, the out-of-date HVAC strategy still wastes energy without achieving the expected ventilation. This not only exacerbates the fuel consumption, carbon emission, and road-level pollution of the current fossil fuel buses, but also dramatically diminishes the driving range and thus hinders the deployment of next-generation e-buses. Such a situation faced by Hong Kong serves as a strong motivation to develop better in-bus HVAC coordination. In this proposed project, an artificial intelligence-based real-time HVAC strategy will be developed for the present and next-generation public buses by striking the beneficial balance among the healthy level of cabin micro-environment, energy consumption, and passengers' satisfaction. Nevertheless, the state-of-art reveals the unsettled barriers in technology promotion. Among them, the notable challenge is the extremely complex and ever-changing cabin micro-environments. It is found that present research on in-bus microenvironments can be generalized as static and case-by-case, as they only took steady-state operating circumstances of bus cabins into account. Besides, current preliminary explorations of in-bus HVAC controls expose absence of real-word verification and guidance with appropriate physical models. This induces minimal control variables and rough indicators, as well as more serious sim-to-real problems as insurmountable gaps with practical realization. To achieve the goals and fulfil the existing research gaps, this project proposes an integrated approach by combining computational fluid dynamics (CFD), reinforcement learning (RL), and visual-based detection to tackle those difficult and complicated technical problems. With the support of in-bus experiments CFD is capable of verifying optimal bus micro-environments and identifying stagnation points. However, CFD has its inherent non-real-time deficiencies due to the intensive computational loads, which is not applicable to actual in-bus environments. RL is therefore recommended to bridge the gap between CFD and practical implementation in real-time. By inheriting advantages of CFD and complementing weaknesses of CFD, RL will make CFD lightweight to implement in real-world scenarios feasibly. In order to sense accurate cabin environments, a visual-based detection module will be deployed as real-time inputs for the HVAC coordination. By incorporating advantageous use of CFD, RL, and visual detection, a novel HVAC coordination strategy will be eventually integrated and systematized. To mitigate the sim-to-real problems, before-and-after filed experiments on real-life buses will be conducted to validate the effectiveness of the developed strategy; a synergistic procedure with hybrid learning and practical serving will also be established to provide extra real-world feedbacks to improve its practical performance. This HVAC strategy can be deployed in both fossil fuel buses and e-buses of Hong Kong, contributing to a healthy and energy-efficient bus cabin environment for not only the COIVD-19 era but also post-COVID further. The research outcomes are of both academic and practical importance and in line with the recent remarkable efforts of Hong Kong in the construction initiatives of green and smart city.


Project Reference No.: UGC/FDS14/B17/22
Project Title: Does Sharing the Same Auditor with Listed Affiliated Firms Affect IPO Audit Quality? An Analysis at the Audit Firm and Partner Levels
Principal Investigator: Dr ZHANG Weiyin (HSUHK)


Regulators, practitioners, investors, and academics often stress the importance of audit quality (Chan et al. 2006; Chen et al. 2016; Chen et al. 2010). DeFond and Zhang (2014) provide an insightful discussion on audit quality and identify client demand, supply of auditors, and regulatory intervention as important factors affecting audit quality. Specifically, auditors’ economic dependence on important clients is likely to compromise their independence and is associated with impaired audit quality (Chen et al. 2010). Sharing a common auditor in the business group may adversely affect audit quality due to the impairment of auditor independence resulting from client importance. However, knowledge spillover from sharing the same auditor in the business group may enhance audit quality. The main objective of this proposed study is to investigate the effect of sharing a common auditor on IPO audit quality and the post-IPO financial performance at the firm and individual partner levels.

China provides an interesting and unique setting to test the effect of a common auditor in the IPO context because of the special managerial incentives for gaining listing status. The merit-based IPO review system and explicit profitability requirements motivate Chinese IPO applicants to boost pre-IPO financial performance. Moreover, considering the high degree of competition in the Chinese IPO audit market, IPO auditors in China may compromise their audit independence and quality in exchange for economic benefits from the business group.

DeFond and Zhang (2014) call for more research on the reporting behavior of individual auditors. Hanlon et al. (2021) extend the call to include the effect of individual auditors not only on audit outcomes, but also on client outcomes. By echoing DeFond and Zhang (2014) and Hanlon et al. (2021), our proposed study plan to provide evidence on the effect of sharing a common auditor on audit outcomes at the individual auditor level in the context of IPO audit in a business group. We will also investigate the effect of common auditors on firms’ post-IPO performance.

The proposed research is significant because it will complement the literature on the effects of individual auditors on audit outcomes, which has recently attracted the attention of regulators. To our knowledge, our proposed study is the first to investigate whether a common auditor, both at the firm level and individual auditor level, affects IPO audit quality. By demonstrating the role of sharing a common auditor in an IPO audit setting, our results will help different stakeholders in the capital market make better-informed decisions and formulate policies and regulations related to IPOs. Given that the Shanghai and Shenzhen-Hong Kong Stock Connect facilitate Hong Kong investors to invest in the Chinese capital market, our findings will have significant implications for investors and regulators in Hong Kong.


Project Reference No.: UGC/FDS24/B02/22
Project Title: Developing A Real-time Tourism Demand Forecasting System for Hong Kong
Principal Investigator: Dr ZHANG Xinyan (PolyU SPEED)


Tourism demand forecasts can be produced for long- or short horizons. Given the uncertainty of tourism demand during major crises, such as the COVID-19 pandemic, high-frequency or real-time forecasts would be more valuable for fast decision-making in tourism destinations. Traditional econometric models generate forecasts on a low frequency – annual or quarterly, as the data on the explanatory variables in the models are generally released annually or quarterly. Because of this, a lot of potentially useful high-frequency information may have been overlooked. New methodological advances such as the mixed data sampling (MIDAS) model in econometrics over the past decade have made it possible for tourism demand forecasting to be carried out in a much higher frequency or even real-time.

Modern macroeconomic theories, such as the rational expectations theory and the forward-looking theory of consumption, suggest that economic confidence plays a crucial role in future economic activities. Survey-based data on business confidence or consumer confidence are commonly used to forecast macroeconomic variables due to their timeliness and ability to signal future development. However, survey-based data have largely been ignored in tourism forecasting research. This project is the first attempt to combine survey-based data with search query data to nowcast tourist demand in the context of the recent COVID-19 crisis.

This project aims to develop a real-time tourism demand forecasting system for Hong Kong with multiple data sources in order to capture the recovery trajectory of the tourism demand. The Markov-switching (MS) model in the MIDAS (or MS-MIDAS) framework will be applied to capture the demand volatility caused by the COVID-19 outbreak. As an advanced forecasting method that can account for mixed frequency indicators, MIDAS modelling is a rapidly growing area of research in real-time forecasting related to macroeconomics. However, limited research in tourism has utilized this method. To the best of our knowledge, MS-MIDAS models have not yet been considered in the tourism forecasting literature. Considering possible future uncertainties in tourism recovery, model-generated forecasts will be adjusted using judgmental methods to incorporate important extra information into the final forecasts.

According to UNWTO, domestic tourism is expected to drive the recovery of the industry. Considering Hong Kong, travellers may initially come from the neighbouring cities within the Greater Bay Area (GBA) after COVID-19. Therefore, this research will focus on forecasting tourist arrivals from mainland China, especially GBA, to Hong Kong.


Project Reference No.: UGC/FDS24/E02/22
Project Title: From Theories to Utilization: Development of a Learning-Based Aerial Swarm for Hong Kong Public Fire Services Applications
Principal Investigator: Dr ZHOU Weifeng (PolyU SPEED)


In the summer of 2019, large-scale bushfires have brought severe damage to the forest of France, Greece, and the USA. In the December of the same year, Australia has experienced a black summer caused by a series of bushfires, which were ten times larger than the normal scale. In Hong Kong, raging hill fires destroy ecological environments, and, in some cases, threaten human property and life. To resolve such issue, Hong Kong’s current solution highly depends on human labor, where firefighting crews of the Agriculture, Fisheries, and Conservation Department (AFCD) are on 24/7 duty around the clock during fire-frequent seasons to detect and combat hill fires within country parks. Nevertheless, this methodology is deemed rather time-consuming, labour-intensive, and hazardous. A team of aerial robots, on the other hand, could act as a promising alternative. A UAV swarm system consisted of two crews is now proposed to detect and also combat hill fires in the suburban district of Hong Kong in this research. Particularly, one crew is to regularly patrol the suburban district and detect for any emitting smoke of an early-stage fire. When a fire is detected, the Fire Services Department (FSD) will be alarmed. The second crew, equipped with a small-scale fire extinguisher, will be activated and fly to the fire spots to control the spread of fire buy time for the firefighters. The system will be primarily acting as a supporting module for such operation to enhance the overall efficacy. This UAV swarm system consists of two main units: the swarm coordination control system and the fire detection and fire prevention facilities. This research mainly focuses on developing a UAV swarm coordination control system, which operates in the suburban district of Hong Kong. To achieve so, a task decomposition and allocation module of a multi-UAV system based upon Linear Temporal Logic (LTL) methods will be developed first. This module is considered essential, as it is used to break down a mission into specific and detailed sub-tasks for each UAV in the swarm. Secondly, a sensor fusion module will be studied and designed to conduct perception, so that robots could be able to localize themselves within different land or forest conditions. By doing so, each of the UAVs in the swarm can generate an accurate estimation of itself and the surroundings and further act as the feedback signal of the swarm control system. For multi-UAV systems with fuzzy, non-linear, uncertain, and self-organizing characteristics, the deep reinforcement learning (RL) based control module is one of the sound solutions. The key function of this module is to optimize the final actions performed by the agents corresponding to a specific environment and the optimal results are usually represented as a cumulative reward. In short, the core idea of reinforcement learning is to allow the agent to learn in the interaction with the environment by setting a reward function. Meanwhile, this deep RL-based coordination control will function closely with the sensor fusion-based state estimator module. From place to place, when the state estimator module senses a change in the surrounding environment of a UAV, the control policy from the RL will change accordingly to better fit the real-time situation. This project will start from the development of the aforementioned three modules, followed by software-in-loop experiments. Then the gap between simulation to real flight will be addressed the sim-to-real problem. Upon completion, the finalized system is expected to have around ten UAVs patrolling a suburban district. The outcomes of this research work are of both academic and practical importance and in compliance with the future development of Hong Kong to achieve a smart city.