Search

Collection, as the first stage of the recycling process, and pre-processing to increase waste stream purity constitute key operations for achieving high recycling rates and a closed loop in the circular economy. For wastepaper recycling in Hong Kong, it is the semi-formal-informal recycling (SFIR) sector that plays a central role in both stages. This study analyses the so far little explored SFIR stakeholder network in Hong Kong and sheds light on value chains, recovered waste paper quantities and the impact of policies on the sector. The findings show that SFIR stakeholders reclaim 55.6 t/recycling station/month of wastepaper and thereby achieve about a 5.7 times higher reclaim rate than the formal-private recycling system. Critical to this achievement is the SFIR transaction network, which enables its stakeholders to develop a value chain and thereby generate an added value of around 1900 HKD (243.9 USD/t) for wastepaper. Given limited circular structures in Hong Kong, financial subsidies are critical to sustain the SFIR's operations over the short-term. However, over the long-term legalization and integration of its stakeholders are necessary to ensure an economically and socially sustainable wastepaper recovery system in Hong Kong. [Display omitted] • Qualitative & quantitative analysis of the semi-formal-informal recycling (SFIR) sector. • The SFIR's wastepaper value chain achieves a cumulative added value of 1900 HKD/t. • The SFIR recovered 5.7 times higher capacities than the formal system in 2021. • Financial support can enhance the SFIR sector's recovery capacities. [ABSTRACT FROM AUTHOR]

• This paper examined the relations between three managerial factors and multi-family dwelling recycling • Significant association was found between housing type and MFD recycling • No significant association was found between recycling mode and MFD recycling. • There was a significant association between initiative of property manager and MFD recycling. Solid waste is an acute environmental problem in most big cities around the world. Like other highly compact cities, Hong Kong developed a recycling program that primarily targets multi-family dwellings (MFDs). This paper intends to examine the relations between three managerial factors—housing type, recycling mode, and initiative of the property manager—and MFD recycling using data collected from a territory-wide telephone survey (n = 1,016) conducted in 2017. The results indicated that housing type and initiative of the property manager had significant relations with the recycling behavior of residents. The findings may supplement previous recycling studies and provide a reference for the improved implementation of the MFD recycling program in Hong Kong. [ABSTRACT FROM AUTHOR]

The current paper replicates findings related to the analytical heuristic of 'metalinguistic density'. It provides updated theoretical motivations for an analytical focus on explicit metalanguage in online text-based settings, based on notions of symbolic interactionism. An analysis of online user comment data of the 2019 Hong Kong protests reconfirms that the relative occurrence of metalanguage focusing on certain terms indicates the extent to which these terms' denotational norms are shared amongst a community of language users. While most terms in the corpus do not regularly attract explicit metalanguage, several terms thematically related to the protests did. This disproportionate metalinguistic attention may be explained by political disputes on the movement's legitimacy, which led to normative debates on the discursive representation of the protest movement. Finally, certain phrases had become indexical of a certain political position to the extent that they were the frequent target of irony. In general, the results suggests that 'metalinguistic density' is a useful heuristic to employ in text-analytical investigations that seek to explain participants' interpretations of discursive interactions. • 'Metalinguistic density' measures the sharedness of terms' denotations. • Results of earlier research are replicated in a thematically distinct dataset. • Metalanguage reflects ideological clashes over discursive representation. [ABSTRACT FROM AUTHOR]

Abstract: How university students write from sources has been an issue of long-standing interest among researchers of advanced academic literacy. Previous research in this regard in the context of L2 writing has tended to focus on novices'' textual borrowing; less attention has been given to exploring the potential light that theories from other intellectual domains may shed upon students'' process of source-based academic writing. The study to be reported in this paper used activity theory as an analytic tool to examine three ESL students'' activities of fulfilling a policy paper assignment at a university in Hong Kong. In the paper I present a description of the activity system concerned and its internal contradictions, characterize the sequences of actions that constituted the individual students'' activities, and analyze the students'' source-use practices in terms of their efforts to address a set of source-bound systemic tensions. At the end of the paper I propose a few lines of future explorations using activity theory as a heuristic to study literacy activities in academic contexts. [Copyright &y& Elsevier]

• This paper portrays the waste generation flow (WGF) of 132 construction projects. • Different WGFs follow different S-curves, but are far from steady streams. • The peaks of waste generation rates differ across projects. • New building projects generate waste faster than demolition and foundation projects. Understanding waste generation flow is vital to any evidence-based effort by policy-makers and practitioners to successfully manage construction project waste. Previous research has found that accumulative waste generation in construction projects follows an S-curve, but improving our understanding of waste generation requires its investigation at a higher level of granularity. Such efforts, however, are often constrained by lack of quality "bigger" data, i.e. data that is bigger than normal small data. This research aims to provide an anatomy of waste generation flow in building projects by making use of a large set of data on waste generation in 19 demolition, 59 foundation, and 54 new building projects undertaken in Hong Kong between 2011 and 2019. We know that waste is generated in far from a steady stream as it is always impacted by contingent factors. However, we do find that peaks of waste generation in foundation projects appear when project duration is at 50–85%, and in new building projects at 40–70% of total project time. Our research provides useful information for waste managers in developing their waste management plans, arranging waste hauling logistics, and benchmarking waste management performance. [ABSTRACT FROM AUTHOR]

The integration of business flow status updates creates a framework for dynamically evaluating operation and maintenance activities, and that assessment is an essential component of achieving intelligent management and control. Highway managers have relied on the operation and maintenance system to integrate business initiatives that improve performance at the organizational and individual levels recently. There are a few studies considering the actual accident or road infrastructure to improve the quality of the highway, but they ignore the power of operation and maintenance (O&M) management involving multiple parties. Furthermore, there is no comprehensive scale to measure the effect of implementing management measures. Therefore, this paper aims to develop a comprehensive multidimensional evaluation framework that considers the integration of the actual business and the objective environment from four aspects: worker, equipment, environment, and management measures. The proposed framework evaluates the current O&M performance with the improved Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) model, which is used to interpret the comprehensive index results, and highlights the differences and variations of the factors that influence the evaluation results based on the deconstruction analysis. We utilize a mixed dataset of the Hong Kong-Zhuhai-Macao Bridge (HZMB) for two consecutive years to evaluate the performance of each month. The results show that the evaluation framework can effectively measure the O&M performance, and "Worker- Quality of daily inspection work" was identified as the most critical factor affecting the O&M performance. In particular, a comprehensive multiparty operational status assessment helps to review and revise current management strategies for targeted improvements that will enhance the safety and quality of management. [ABSTRACT FROM AUTHOR]

Photorealistic 3D models are important data sources for digital twin cities and smart city applications. These models are usually generated from data collected by aerial or ground-based platforms (e.g., mobile mapping systems (MMSs) and backpack systems) separately. Aerial and ground-based platforms capture data from overhead and ground surfaces, respectively, offering complementary information for better 3D mapping in urban areas. Particularly, backpack mapping systems have gained popularity for 3D mapping in urban areas in recent years, as they offer more flexibility to reach regions (e.g., narrow alleys and pedestrian routes) inaccessible by vehicle-based MMSs. However, integration of aerial and ground data for 3D mapping suffers from difficulties such as tie-point matching among images from different platforms with large differences in perspective, coverage, and scale. Optimal fusion of the results from different platforms is also challenging. Therefore, this paper presents a novel method for the fusion of aerial, MMS, and backpack images and point clouds for optimized 3D mapping in urban areas. A geometric-aware model for feature matching is developed based on the SuperGlue algorithm to obtain sufficient tie-points between aerial and ground images, which facilitates the integrated bundle adjustment of images to reduce their geometric inconsistencies and the subsequent dense image matching to generate 3D point clouds from different image sources. After that, a graph-based method considering both geometric and texture traits is developed for the optimal fusion of point clouds from different sources to generate 3D mesh models of better quality. Experiments conducted on a challenging dataset in Hong Kong demonstrated that the geometric-aware model could obtain sufficient accurately matched tie-points among the aerial, MMS, and backpack images, which enabled the integrated bundle adjustment of the three image datasets to generate properly aligned point clouds. Compared with the results obtained from state-of-the-art commercial software, the 3D mesh models generated from the proposed point cloud fusion method exhibited better quality in terms of completeness, consistency, and level of detail. [ABSTRACT FROM AUTHOR]

• This study compared drivers of the same ethnic group driving across within-country borders. • The existing theoretical framework of cross-border risky behavior patterns has been expanded. • Gender, age, illumination, and weather do not individually affect cross-border driving risk. • Conclusions are of representative reference value for cross-border risk management policies. Introduction: Due to globalization and the acceleration of cross-border exchanges, cross-border risk behaviors have received widespread attention. Previous research has concluded that foreign cross-border drivers engage in relatively more risk-taking behavior patterns and are likely to experience a higher crash rate or be more inclined to cause severe crashes. However, there is little evidence on the comparison of drivers who belong to the same ethnic group driving across within-country borders. Method : Based on the cross-border motor-vehicle crash reports in 2006–2010 from the Road Traffic Accident Database of the China Ministry of Public Security, this paper examines the risk factors of being at fault and getting killed or seriously injured in cross-border traffic crashes and casual paths toward crash liability and injury severity for Hong Kong and Macao drivers driving in the Chinese mainland. Results : There are extremely complex factors behind drivers from Hong Kong and Macao causing at-fault crashes or sustaining fatal and serious injuries in the Chinese mainland. Factors such as gender, age, illumination, and weather conditions do not individually affect the risk of driver at-fault crashes or severe casualties in the crashes among Hong Kong and Macao drivers driving in the Chinese mainland. Nonetheless, collectively, these factors influence them along with different vehicle types, roads, and environmental factors. Conclusion s: This paper provides more theoretical findings for understanding the compound effect of multiple risk factors involving cross-border at-fault crashes or serious casualties. The conclusions of this research are valuable as representative references for cross-border risk management policies. Practical applications : To reduce the effects of different factors on cross-border risky driving behaviors and/or injurious crashes, various measures should be focused on, including specialized driver training, enhancement of the roads/environment, development of effective road safety campaigns, and directives facilitating cross-border cooperation in the field of road safety. [ABSTRACT FROM AUTHOR]

Much recent work on transport and the economy has focused on 'Wider Economic Impacts' (WEIs) of infrastructure investment, the impacts other than time savings benefiting those actually using the transport network. Differential effects of transportation infrastructure by mode such as urban rail and road are relatively well known. However, impacts of other mode such as walking are scarce. This paper estimates wider economic impacts related to productivity from full rail, road and walking transport networks in Hong Kong in 2016. To the best of our knowledge, this is the first paper that makes use of complex network science indicators with spatial cognition-weighted accessibility combining full urban rail network, road network, and pedestrian network in capturing wider economic impacts. We use an instrumental variable approach to identify the causal effect of transport network centralities on productivity measured by gross value added. Our identification strategy largely relies on the exogenous variations from historical planned and existing transport networks. A first specification confirms the significance of urban rail and road. Specification with pedestrian network shows that pedestrian and rail networks can statistically significantly increase productivity in Hong Kong while roads play a less significant but still meaningful role. Our findings are robust to a variety of sensitivity tests such as using night-time light intensity and residential wage as alternative measures for productivity. The research suggests a key planning policy implication: place-based policies in a dense city require improvement in pedestrian and rail network structure that impacts local and global transport accessibility. [ABSTRACT FROM AUTHOR]

The ubiquity of Internet gaming as part of the younger generation's (11-35 year-olds) lifestyle to-day warrants a deeper understanding of its impact on their mental health. In particular, there has been scant research investigating the link between Internet Gaming Disorder (IGD) and suicidal behaviors in this demographic group, even though several mental health symptoms of the former are known risk factors for the latter. This paper aims to establish the presence or absence of association between IGD and each of suicidal ideation, self-harm, and suicide attempt among the younger generation. A large-scale online survey on Internet gamers in Hong Kong was conducted in February 2019. 3430 respondents were recruited through purposive sampling. Study samples were stratified into distinct age groups and multiple logistic regression was conducted for each measured suicidal behavior in each age group. After controlling for sociodemographics, Internet usage, self-reported bullying perpetration and bullying victimization, social withdrawal, and self-reported psychiatric diagnoses such as depression and psychosis, analyses revealed that adolescent (11-17 year-old) gamers with IGD were more likely than their peers who had no IGD to have had suicidal ideation, self-harm, and suicide attempt in their lifetime. These associations did not hold for 18-35 year-old gamers. Findings suggest that it may be prudent to recognize IGD as a growing public mental health priority for the young populace, particularly adolescents. Existing suicide prevention efforts can be complemented through screening adolescents for IGD, and could be expanded to online gaming platforms to reach more hidden at-risk individuals. • Adolescent gamers with IGD had higher odds of lifetime suicidal ideation compared to their peers with no IGD. • Adolescent gamers with IGD had higher odds of lifetime self-harm compared to their peers with no IGD. • Adolescent gamers with IGD had higher odds of lifetime suicide attempt compared to their peers with no IGD. • IGD was not associated with lifetime suicidal behaviors among gamers aged 18–35 years old. • Suicide prevention efforts may be enhanced by screening individuals for IGD and expanding efforts to online game platforms. [ABSTRACT FROM AUTHOR]

This commentary on "Just wanna give you guys a bit of an update": Insider perspectives on business presentations in Hong Kong (2013) explores the significance of the paper written by Stephen Evans, its influence on the study of business English, and its main contributions to business communication and presentations, including a number of highlights for future research projects. • This is a researcher's commentary on Evans (2013). • It tries to highlight research interest in business English oral interactions. • The research on business presentations has multiple aspects to be studied. [ABSTRACT FROM AUTHOR]

In recent years, urban rail funding has become an increasing concern in some western cities. The underlying issues over ridership and funding has largely been driven by trends such as increasing teleworking and new transport modes like ridesharing, which are likely to further exacerbate funding issues in the aftermath of the worldwide health crisis. This paper contributes to the discussion through the examination of funding within urban rail transport, specifically the strengths and weaknesses of mechanisms that can be used to achieve sustainable, stable long-term funding. A unique, very long-term historical dataset of five large metros around the world was collected for this research, with the analysis based on evidence of actual practices, from a relatively rare organisational perspective. Key results include: i) appropriate fare-setting has been critical for long-term financial health, but is vulnerable to inflation effects and political interference; indexing is important but use of consumer prices has led to revenue erosion in real terms, since wage growth is typically higher. ii) How subsidies are generated can have varying impacts on funding stability and sustainability — dedicated taxes and cross-subsidies from road charges are typically better than direct grants as they are secured by legislation; they also reduce political changes and avoid competing claims from other types of government spending (health, education), as compared with grants. iii) Commercial revenue can be a valuable source for future growth, in light of increased resistance to taxation. Real estate-related revenues in particular can be substantial, as in Hong Kong and Tokyo, with historically faster growth than wages, while also capturing any further value increases from rail system improvements. • Strengths and weaknesses analysis of funding sources, using data from 5 large metros • Fare-setting with appropriate index (wages) is crucial for long-term financial health • How subsidies are generated – intrinsic impacts on funds stability and sustainability • Ideally, subsidies secured multi-year with legislation – avoids competing claims • Real estate enables long-term value capture and revenue growth from rail improvements [ABSTRACT FROM AUTHOR]

Urban morphology and spatial forms shape a city's character and user behavior, often embracing a particular type of people and unwelcoming other kinds of gender. City design policies and legislation have favored men since its beginning, affecting overall urban planning and design. While the world is delving into new techniques and methods to empower women, constraints in public space activities remain prevalent. This paper explores the scope of urban design strategies to catalyze women's social and physical inclusion in these spaces. It presents a systematic approach to identifying women's social roles during the use of public spaces and introduces the 'GenUrban: Shaping Cities for All Genders' framework to guide researchers and designers alike promote inclusive urban design and planning. The investigation, in the central area of Hong Kong, focuses on the cultural landscape created by the women-centric 'Foreign Domestic Helpers' community. A desktop literature review, direct observation of public spaces, and in-depth interviews with a focus group of women in the city's heart established and mapped the marginalized users' collective viewpoint and their appropriation of space. The framework can be used by professionals to transform urban spaces through a gender lens to improve the overall quality of public spaces and make them more inclusive and accessible. The paper generates gender-sensitive urban design principles that can be translated for planners to use for various user groups and contexts. When women become key drivers in activating public space, they are given back their right to the city. • Women's traveling patterns are frequent due to their caregiving responsibilities. • The unique cultural landscape of a city creates gender-centered activities. • Integrating gender-specific features ensures urban spaces cater to women's needs. • Reliable public transport is vital for women's mobility and engagement in city life. • A city catering to women tends to accommodate those they care for. [ABSTRACT FROM AUTHOR]

Mapping of highly dynamic changes in land use and land cover (LULC) can be hindered by various cloudy conditions with optical satellite images. These conditions result in discontinuities in high-temporal-density LULC mapping. In this paper, we developed an integrated time series mapping method to enhance the LULC mapping accuracy and frequency in cloud-prone areas by incorporating spectral-indices-fused deep models and time series reconstruction techniques. The proposed method first reconstructed cloud-contaminated pixels through time series filtering, during which the cloud masks initialized by a deep model were refined and updated during the reconstruction process. Then, the reconstructed time series images were fed into a spectral-indices-fused deep model trained on samples collected worldwide for classification. Finally, post-classification processing, including spatio-temporal majority filtering and time series refinement considering land–water interactions, was conducted to enhance the LULC mapping accuracy and consistency. We applied the proposed method to the cloud- and rain-prone Pearl River Delta (i.e., Guangdong–Hong Kong–Macao Greater Bay Area, GBA) and used time series Sentinel-2 images as the experimental data. The proposed method enabled seamless LULC mapping at a temporal frequency of 2–5 days, and the production of 10 m resolution annual LULC products in the GBA. The assessment yielded a mean overall accuracy of 87.01% for annual mapping in the four consecutive years of 2019–2022 and outperformed existing mainstream LULC products, including ESA WorldCover (83.98%), Esri Land Cover (85.26%), and Google Dynamic World (85.06%). Our assessment also reveals significant variations in LULC mapping accuracies with different cloud masks, thus underscoring their critical role in time series LULC mapping. The proposed method has the potential to generate seamless and near real-time maps for other regions in the world by using deep models trained on datasets collected globally. This method can provide high-quality LULC data sets at different time intervals for various land and water dynamics in cloud- and rain-prone regions. Notwithstanding the difficulties of obtaining high-quality LULC maps in cloud-prone areas, this paper provides a novel approach for the mapping of LULC dynamics and the provision of reliable annual LULC products. • Novel LULC mapping via indices-fused deep models and time series reconstruction. • High-temporal-density 10 m seamless LULC mapping in cloudy and rainy areas (PRD). • Overall mapping accuracy yielded up to 87.01%, outperforming existing LULC products. • Potential to generate seamless near real-time maps and high-quality LULC data sets. [ABSTRACT FROM AUTHOR]

• This paper focused on the reliability of settlement prediction of immersed tunnel. • This paper focused on impact of time-dependent effects on settlement prediction. • A time-dependent expression for foundation modulus is proposed. • Several extreme conditions are considered in the future settlement prediction. The focus of immersed tunnel research has primarily revolved around settlement monitoring or prediction. However, there has been a lack of discussion regarding the time-dependent effects on settlement prediction, which could lead to obvious misjudgments in subsequent maintenance work. This paper addresses this issue by applying the physics-informed machine learning (PIML) algorithm to conduct an inverse analysis of the foundation modulus of the Hong Kong-Zhuhai-Macau Bridge (HZMB) tunnel, thereby identifying its variation tendency with time. The proposed time-dependent expression of foundation modulus demonstrates that the time-dependent effect is related to both post-construction settlement and the accumulation of back silting, which is significant and could persist throughout the entire service life of the HZMB tunnel. In further studies on settlement prediction for the HZMB tunnel, the results show that errors in prediction can exceed 30 mm at certain monitoring points. This error can be mitigated by considering the time-dependent effect, thereby significantly enhancing the reliability of predictions. [ABSTRACT FROM AUTHOR]

In recent years, promoting regional synergistic development has become the shared objective in city-regions during the new stages of development. This paper aims to uncover the dynamics of synergistic development in urban agglomerations by constructing an index measurement system based on four dimensions: industrial synergy, innovation synergy, infrastructure synergy, and institutional synergy. By comprehensively employing theories and methods such as "space of flow" big data analysis, network analysis, and interlocking network models, this study examines patterns and capacities of synergistic development in the Guangdong-Hong Kong-Macao Greater Bay Area. The main instances of industrial cooperation between cities are observed in Hong Kong-Shenzhen and Guangzhou-Shenzhen; capital flows primarily concentrate in Guangzhou-Shenzhen and Hong Kong-Shenzhen. Research paper and patent collaborations between cities are predominantly concentrated in Hong Kong-Shenzhen; joint laboratories are mainly established in Hong Kong-Macao and Hong Kong-Guangzhou; inter-city co-construction of higher education institutions is mainly focused on Guangzhou-Foshan and Shenzhen-Hong Kong. Infrastructure synergistic development performs best in Guangzhou-Shenzhen, Guangzhou-Foshan, and Shenzhen-Dongguan. Cross-border collaboration benefits from institutional advantages held by Hong Kong and Macao. Urban interactions with outstanding performance include Guangzhou-Shenzhen, Hong Kong-Shenzhen, Guangzhou-Foshan, Shenzhen-Dongguan. Additionally, increasing interaction trends can be observed between Guangzhou-Dongguan as well as Shenzhen-Zhuhai/Shenzen-Foshan partnerships. Understanding the typical characteristics and potential trends of synergetic development within the GBA holds significant practical value for establishing a first-class bay area along with a world-class urban agglomeration. • Concept and connotation of synergistic development in urban agglomeration area was examined. • Indicators and methods for evaluation of synergistic development in the GBA were conducted. • Patterns and capacities of synergistic development at urban scale in the GBA were explained. • Urban interaction with highest synergistic development level is Guangzhou-Shenzhen. [ABSTRACT FROM AUTHOR]

In this paper, we aim to examine people's EV purchase intention in Hong Kong, an Asian compact city, and how the influential factors are different from the Western context, for which a low-density Nordic context, Denmark, was chosen. To achieve this, we conducted a survey in Hong Kong to understand the effects of several key factors, including subjective norms, personal norms, and perceptions and knowledge about EVs. Structural equation modelling was employed and multi-group analysis was conducted. Our findings show that EV purchase intentions in Hong Kong are highly value-driven with the assimilation to social expectations directly and strongly encouraging individuals' EV acceptance, which is different from the European case where the adoption desire is built upon the assessment of usage difficulty. In addition, range anxiety poses a direct deterrence to EV adoption even in the compact city. Availability of charging opportunities, be it the public ones or home-based ones, plays a critical role in an individual's decision of EV adoption in the high-density city. Our study reveals a strong disparity in the pathways towards EV adoption between the Asian and the Nordic contexts, thereby illustrating the necessity to differentiate e-mobility promotion policies in compact cities from low-density cities. • We analyse the influential factors of EV purchase intention in Hong Kong & Denmark. • Attitude, moral obligation and perceived ease of use affect EV adoption. • EV purchase intentions are highly value-driven in Hong Kong. • Range anxiety poses a deterrence to EV adoption even in the compact city (HK). • Availability of charging facilities is key to EV adoption. [ABSTRACT FROM AUTHOR]

Mobile learning (m-learning) is gaining its importance in recent years. For libraries, it is inevitable to adapt to this trend and provide various information services and support for m-learning. This paper studies the m-learning usage of Library and Information Science (LIS) students, who will be the new blood for the library in future. In this paper, we invited 267 subjects from Hong Kong, Japan, and Taiwan to participate in our online survey. We found that LIS students from these regions do adopt communication tools and social media for m-learning. However, they less frequently use their smartphones for academic reading. Plus, they rely more on search engines for fulfilling their information needs instead of library resources. We also found that the lack of a mobile version of the library website constitutes a significant barrier in m-learning, but the lack of mobile apps is relatively acceptable by the respondents. The result of this study shows that there are no big differences in m-learning usage among the three regions, except that LIS students from Hong Kong are accessing the learning management platforms via their smartphones more frequently compared to students from Japan and Taiwan. [ABSTRACT FROM AUTHOR]

• A mixed bus fleet location-routing-scheduling framework under driving range uncertainty is proposed. • A range reliability (RR)-based two-stage stochastic program is formulated. • An adaptive time-space-energy network is proposed to address diverse forms of the refueling problem. • The vehicle routing, scheduling, and refueling station location problem are solved simultaneously. • Regular services ensure to cover the scheduled trips up to a certain reliability level with minimal total cost. This paper develops a framework to address the multi-depot vehicle location-routing-scheduling problem with multi-vehicle types, including electric buses, under range uncertainty. Three major issues in bus routing and scheduling are addressed in this framework, i.e., uncertain driving range, refueling or charging need, and locating refueling or charging facilities. Mathematically, the problem is formulated as a two-stage stochastic program. Two types of services, regular services running on fixed schedules and ad hoc services to cover incomplete scheduled trips arising from energy shortage of certain buses, are considered in this paper. An adaptive time-space-energy network is developed to model the refueling issues and location problem. We introduce the notion of range reliability to decompose and solve the two-stage stochastic formulation under range uncertainty. The regular services schedule is determined in stage-one to cover the demand under a certain range reliability level. Upon realization of the random driving range, the deployment of ad hoc services is made in stage-two to address the occurrence of energy shortage of certain buses. A range reliability-based gradient algorithm is developed to minimize the expected total cost of the system. We then apply the proposed method to bus services in Hong Kong. The range reliability-based approach shows promising results, leading to substantial cost savings as compared with the traditional methods that ignore the effects of driving range uncertainty. [ABSTRACT FROM AUTHOR]

• This paper integrates bifacial photovoltaics as sunshades into buildings. • The impact of installation and building factors on power generation is studied. • The impact of installation factors of bPV on the energy savings is studied. • The south orientation, small tilt angle and wide bPV are recommended to install. • The buildings with high wall reflectivity and low WWR achieve more energy savings. Solar photovoltaic (PV) shading systems are of great significance for achieving low-carbon buildings. Bifacial photovoltaics (bPV) is a promising technology that can generate electricity from both the front and rear sides of bPV modules. By integrating bPV shading systems into buildings, more power generation and less building energy consumption can be achieved compared to traditional shading systems. This study aims to integrate and optimize bPV shading systems into the building vertical façades in hot and humid regions, considering varying installation and building parameters. The evaluations of electricity generation and energy saving were conducted based on a typical three-story office building in Hong Kong. The evaluation of electricity generation reveals that the optimal installation condition for bPV sunshades in Hong Kong is south orientation with a tilt angle of 35°. Regarding the width of bPV sunshades, as the width increases, the annual electricity generation per unit area (AEGPA) decreases, but the total annual electricity generation (TAEG) increases. Besides, the bifacial gain of optimized bPV sunshades increases from 3.3% to 6.1% as the wall reflectivity increases from 0.15 to 0.7, while being insensitive to window reflectivity. Similarly, when the window-to-wall ratio (WWR) increases, the bifacial gain decreases. Furthermore, the energy-saving evaluation indicates that the south orientation with small tilt angles and wide sunshades tends to achieve much more energy savings benefits. The findings of this study provide practical guidance for maximizing the power generation and optimizing the design of building-integrated bPV sunshades to achieve maximum energy savings. [ABSTRACT FROM AUTHOR]

Equity and inclusion continue to pose significant challenges for many cities. Disparities in access to resources and facilities among the residents of these areas are often influenced by factors such as geographical location and income level, among others. Therefore, creating a quantitative basis to detect spatial and socio-economic inequities in residents' access to vital infrastructures is crucial for advancing smart cities. This paper introduces a novel measure of Spatial Inequity that is based on 1) computing building-level scores for each building in terms of access to facilities, and 2) comparing the distribution of the scores of these facilities using the Gini coefficient. The proposed building-level scores will enable the identification of GIS hotspots at a high resolution. Then, the Gini-based measure will facilitate a comparison of the distribution of the scores, and determine if they are evenly distributed and equitably accessible. The Gini coefficient was highest (0.89) for waste management and elderly care, and lowest (0.56) for hospitals, reflecting varying levels of inequality. This study applies this Spatial Ineqity methodological framework to Hong Kong, a representative of Highly Dense Cities. The framework benchmarks urban infrastructure, identifies hotspots, and selects interventions for equitable urban development. • Novel approach identifies spatial inequities via building-level scores & Gini coefficient. • Precise hotspot identification enhances targeted interventions in dense urban areas. • Applied methodology in Hong Kong offers insights into urban development complexities. • Gini coefficient unveils varying degrees of inequality across essential services. • Geospatial analysis & quantitative measures support equitable urban resource allocation. [ABSTRACT FROM AUTHOR]

• Examine the use of metaverse for transportation and logistics operations. • Establish an AI supported digital technological framework. • Propose and discuss future research areas. In the digital age, supported by disruptive technologies such as artificial intelligence (AI), blockchain (BC), digital twins (DT), and extended reality (ER), the use of metaverse for real-world operations has emerged. In this paper, we examine the use of metaverse for transportation and logistics operations. To be specific, we first examine the related literature by a selective critical review. Then, we discuss how the use of metaverse can facilitate transportation operations with some relevant cases such as the metaverse project of MTR (from Hong Kong). We establish an AI supported digital technological framework, called the ABCDE framework, for transportation and logistics companies to adopt with their use of metaverse. Finally, we propose and discuss several important future research areas. To the best of our knowledge, this is the first study which comprehensively examines the use of metaverse for transportation and logistics operations. The theoretical framework also lays the foundation for future studies. The findings and insights provide constructive and helpful guidance to both practitioners and academics on the future development of the topic. [ABSTRACT FROM AUTHOR]

The construction of an ecological security pattern (ESP) is an important undertaking in ensuring the stability of the ecosystem and the long-term growth of humanity. Existing research, However, existing research often overlooks the quantification of policy implications in ESP development. The objective of this paper was to bridge this gap by integrating policy quantification analysis (PQA) with nature, society and into ESP construction and providing targeted ecological management recommendations. The policy texts were quantified into reusable research data, which served as a foundation for the selection of indicators and the optimization of ecological security patterns, by using machine learning techniques. The methodology "Patch-matrix-corridor" was used to create a spatially correlated ecological security pattern. Through factor analysis and Random Forest (RF), the impact of each indicator on ecological security was thoroughly examined, offering substantial support for policy development and ESP construction planning. The Guangdong-Hong Kong-Macao Greater Bay Area(GBA) was selected as the study area, the study found that: (1) The proposed framework PQA based-ESP could provide a useful eco-management tools. (2) Policy adaptability had a substantial impact on environmental security in the GBA, but the ecosystem service index has the highest impact. (3) Applying the framework, we identified a total of 1,993 km2 of ecological sources, 23 key ecological corridors, 58 general ecological corridors, and 31 ecological nodes. An improved ESP, characterized as "one circle, two bays, three rivers, multiple areas, corridors, and nodes," was constructed in the GBA. (4) Given the multi-scale analysis, tailored ecological management policy recommendations were proposed for each city in the GBA. The study's findings offer actionable solutions for the international community facing growing ecological challenges. [ABSTRACT FROM AUTHOR]

Electric buses (EBs) are considered a more environmentally friendly mode of public transit. In addition to other practical challenges, including high infrastructure costs and short driving ranges, the operations of EBs are more demanding due to the necessary battery charging activities. Consequently, more sophisticated optimisation models and algorithms are required for effective operations. This paper presents an EB scheduling problem with multiple termini and service routes. Various realistic but complicated factors, such as shared facilities at multiple termini, the flexibility of plugging and unplugging chargers before an EB is fully charged, stochastic travel times, and EB breakdowns, are considered. We propose an integrated learning and mixed-integer linear programming (MILP) framework to overcome the computational difficulties when solving the problem. This framework leverages the strengths of reinforcement learning and MILP for fast computations due to its capability of learning from outcomes of state–action pairs and computational effectiveness guaranteed by the constraints governing the solution feasibility. Q-Learning and Twin Delayed Deep Deterministic Policy Gradient are adopted as our training methods. We conduct numerical experiments on artificial instances and realistic instances of a bus network in Hong Kong to assess the performance of our proposed approach. The results show that our proposed framework outperforms the benchmark optimisation approach, in terms of penalty on missed service trips, average headway, and variance of headway. The benefits of our proposed framework are more significant under a highly stochastic environment. • Electric bus scheduling with multiple termini and service routes. • Shared facilities at multiple termini and the flexibility of plugging and unplugging chargers considered. • Integration of Q-learning and mixed-integer linear programming for solving the problem. • Experiments on artificial instances and a real-world case to demonstrate the high computational performance. • Managerial insights derived from the experiments. [ABSTRACT FROM AUTHOR]

Covid-19 has wreaked havoc worldwide. To mitigate the spread of the virus, societies around the world implemented various social control measures and restrictions on mobility. Traditional work practices were upended, leading to a widespread adoption of telecommuting in many cities, effectively turning urban spaces into expansive work-from-home laboratories. The exchange of digitized documents, virtual conversations, and online transactions replaced physical movements and face-to-face communication, allowing for the continuation of productive activities. This shift to telecommuting raises important questions about the impact on traditional business practices and power dynamics in the workplace. It also prompts us to examine how new communication and surveillance tools facilitate collaboration and enhance worker productivity. Furthermore, it is essential to understand how employees navigate and adapt to the opportunities and limitations presented in a teleworking environment. To gain insights into these issues, this paper focuses on the experiences of work-from-home employees in the community of Tin Shui Wai in Hong Kong, using the concept of governmobility as an analytical framework. The findings reveal that telecommuting is enabled by innovative social interaction mechanisms, changes in power dynamics, and the implementation of new discourse and surveillance methods, all of which are contingent on specific work and life conditions. The various experiences of telecommuting, such as working in a home office, in virtual workspaces, and using on-body devices, demonstrate adaptable responses to the emerging opportunities and constraints of telecommuting. These experiences illuminate the intricate ways in which work and life intertwine in both physical and temporal dimensions. • Exploring the mechanisms of governmobility in telecommuting during the Covid-19 pandemic. • Theorizing diverse telecommuting practices and experiences. • Discussing the prospects of telecommuting in the post-Covid world. [ABSTRACT FROM AUTHOR]

Radiative cooling coating technology is gaining increasing attention in the context of mitigating urban heat island and tackling global climate change. This paper is concerned with the development of an inorganic geopolymer-based radiative cooling coating using red mud, incorporating varying sizes of TiO 2 and hollow glass beads. The developed colored coating demonstrates its radiative cooling capability in reducing the surface temperature by harnessing the potential of red mud. The physico-chemical properties, surface morphology, and element distribution of the coating were characterized by XRD, FTIR, TG-DAT, SEM and EDS. The coating exhibited lower UV (0.0844) and visible reflectance (0.5275) but high NIR reflectance (0.7536), as well as high infrared emissivity of 0.9455, enabling a red color with a CIE value of L* = 74.56, a* = 9.55, and b* = 11.98, and a maximum temperature reduction of 7.3 °C under the climate of Hong Kong. Additionally, the skid resistance, abrasive resistance and adhesion strength of the proposed coating could meet the requirements of standards, indicating a great potential for footway applications. [ABSTRACT FROM AUTHOR]

Digital storytelling, an innovative way of writing, has been introduced to young learners who are taught to construct stories with digital tools to convey their knowledge and ideas. In 2018 and 2019, 31 digital stories created by Hong Kong primary school students were published on a digital story writing platform and linked from an online gamified reading platform. Each book on average gained 4,000+ views from across the globe and received 3,000+ favorable comments in total. While the digital stories are popular in these platforms, their quality and education value are uncertain. A review of the literature shows there is a lack of robust tools for assessing digital stories by young authors. The research team for this paper thus constructed their own framework in evaluating digital stories. An assessment of the stories has been done by two capable assessors, who found that the stories overall were of good quality and suggested room for improvement. This paper made three contributions: (1) "invention" of a digital story assessment framework; (2) it shows that stories created by students (with support from educators) can be an enjoyable and useful educational resource for their peers; and (3) digital storytelling can help foster the development of young authors. [ABSTRACT FROM AUTHOR]

• Around 1.4 million sales transaction data of 25 years were used in this study. • In 1991–2015, sale-related renovation waste could reach up to 4.46 MT. • A self-reporting levy is proposed to refine the waste and policing cost estimate. • More informed market forces may help address latent renovation-inducing factors. Using data of 1.4 million non-aggregate, publicly available, private residential property resale transactions for Hong Kong from 1991 to 2015, this paper addresses a public policy question raised by Demsetz from a Coasian angle. It estimates the impact of a less explored but ecologically problematic realm of renovation waste upon change of ownership of property units in a highly commodified property market. The estimate shows the extent and possibly high cost of the government in addressing negative externalities. Informed by the findings, this paper puts forward the recommendation of a prepaid lump sum waste monitoring levy, which is reimbursable upon self-reporting of waste generation. The collected information, when made open to the public, may help market forces to address poor building quality which causes legitimate major renovations and encourage better workmanship for future edifices. [ABSTRACT FROM AUTHOR]

• This paper proposes a reliable method to evaluate GNSS multipath effects on a smartphone with the known positions in urban canyons. • This paper for the first time to evaluate GNSS errors comprehensively using large-scale data on the smartphone. • This paper is the first to determine the primary error source for smartphone GNSS in urban areas -NLOS or multipath errors. • For the first time, this paper established connections between fault-free measurements and the sides of the street in urban areas. • Results show that pedestrian network can be used to identify the sides of the street for pedestrian, eliminating the need of complex 3D building models. In urban environments, the code measurements of Global Navigation Satellite System (GNSS) on smartphones can be significantly degraded by presence of multipath and non-Line-Of-Sight (NLOS) effects. Extensive studies have been carried out on characterizing the quality of GNSS code measurements under different conditions, which can be used to refine the weighting model and fault detection method. However, our knowledge regarding the impacts of multipath effects on smartphones remains limited. This includes determining the dominant error source for urban GNSS on smartphones between multipath and NLOS errors, and characterizing the fault-free code measurements for pedestrians in urban canyons. To address these issues, we conducted extensive tests in a typical urban area in Hong Kong and analyzed characteristics of multipath effects. Analysis revealed that 92.5 % of code outliers stem from NLOS signals, which result in longer ranging measurements, making NLOS the dominant error source impacting GNSS performance. Further, we established that over 92 % of fault-free signals are from the opposite sky of a pedestrian, and we found that the sidewalk can be reliably determined by examining signal-to-noise ratio (SNR) measurements, eliminating the need of complex 3D building models. The identified sidewalk can be used to enhance GNSS performance in urban areas. An experiment in the urban canyon was performed in urban canyons. Results show that the accuracy can be improved from 15 m to 4.6 m when the correct sidewalk can be identified. [ABSTRACT FROM AUTHOR]

Zero-energy buildings usually achieve annual net-zero energy balance by generating electricity using on-site renewable energies and interconnecting with the power grid. However, the impact of energy mismatch problem in zero-energy buildings design on the grid is often overlooked, which potentially compromises grid's stability. To address this issue, this paper presents an optimization design method based on "grid-friendly interaction" which optimizes the energy system of zero-energy buildings to ensure better alignment between the building's electricity purchase/sale and grid demand. In this study, an indicator of "grid-friendly interaction", which represents the ratio of the net building friendly interaction power to the total annual interaction power, is firstly established to guide buildings in improving their interaction with the grid. Next, the energy supply, demand, and storage schemes of renewable energy systems in the zero-energy building are iteratively adjusted to achieve the best match with grid's expectations. This optimization design method was applied to a practical case in Hong Kong. Results show that, compared to the benchmark building, the optimal system design scheme increases grid friendliness by 83 %, reduces carbon dioxide emissions by 77 %, but also incurs a total cost increase of 180 %. The optimization design method proposed in this paper can effectively mitigate the impact of zero-energy buildings on the power grid, fostering enhanced interplay between the building structures and the grid. The study significantly contributes to the advancement of exploring the potential for energy flexibility in zero-energy buildings, which is of great significance for the safe and stable operation of future grids. The purpose of this study is to explore the energy flexibility potential of zero-energy buildings, which is of great significance for the safe and stable operation of future grids. • A novel indicator that reflects the degree of friendly interaction is proposed. • An optimization design method based on "grid-friendly interaction" is presented. • Single-objective and multi-objective optimization are applied respectively to ZCB. • It is of great significance for the safe and stable operation of future grids. [ABSTRACT FROM AUTHOR]

• Automatic MiC envelopes and layout generation by a novel SSG-MOO method. • Multi-objective optimization formulation for passive MiC design. • A pilot MiC study in Hong Kong produced 5 selected Pareto optima out of 625. • Up to 0.42% energy savings and 9.71% spatial daylight autonomy improvement against the baseline. • A multi-level analysis of results and design strategies for practitioners. Modular-integrated Construction (MiC) is an emerging construction technique promoted in the building sector for high productivity and low waste emission in the construction phase; yet, the standardized modules also bring new challenges, such as balancing passive energy efficiency and spatial daylight autonomy, to the operational phase. This paper proposes a Symmetric Skeleton Grammar-based Multi-Objective Optimization (SSG-MOO) method to formulate parametric MiC envelopes and detailed layout, with the two objective functions being energy efficiency and interior daylight performance in the operational phase. Pareto optima of the SSG-MOO, computed by the Non-dominated Sorting Genetic Algorithm II, are generally verified and analyzed in three levels, i.e., MOO's solution space, SSG layout, and MiC design parameters. A case study of MiC residential building in Hong Kong demonstrated the SSG-MOO method through five new passive MiC designs (i.e., spatial reorganization of three architectural modules, and parameter tuning of the envelops and corridors), achieving up to 0.42% energy savings and 9.71% spatial daylight autonomy improvement compared to the baseline design. The contribution of this paper is two-fold, including a novel and sound SSG-MOO formulation for parametric MiC designs, and offering time-efficient and evidence-based design tactics for MiC designers and industrial practitioners to push boundaries of MiC. [ABSTRACT FROM AUTHOR]

Urban rail development can increase land value, reduce commute time, and increase accessibility, as reported in the literature. However, little is known about the impact of opening urban rail transit stations on people's sentiment, particularly in the context of large metropolises where population density is significantly high. This paper investigates such impact by studying six new transit stations opened in Hong Kong. People's sentiment and activity in station nearby areas are estimated by tweet sentiment and tweet activity. We use the difference-in-difference model to study the impact of opening new transit stations. Tweet sentiment, tweet activity, tweet content, and footprints of people who visit the station-influenced area 'before and after' the opening of transit stations are analyzed. The results suggest that, in general, the introduction of transit stations causes a positive change in tweet activity, and the change is statistically significant after six months. Regarding tweet sentiment, new transit stations tend to pose a mixed effect in a short-term, a positive influence on areas with high-density residential places, yet a negative influence on areas with a large proportion of nature reserve areas. These short-term effects, positive or negative, become not significant in the long term (after twelve months). Our analysis also confirmed that the introduction of new transit stations increased accessibility from (to) other parts of the city to(from) the station's nearby area, which was shown by the expanded locations sustaining users visited. These findings indicate that the urban rail transit system in Hong Kong promotes more active neighborhoods yet does not always promotes positive influence on people's sentiment. Further studies are needed to make future urban rail transit systems promoting active and happy neighborhoods. The study is relevant to the Belt and Road Initiative (BRI) in methodologies, data, and findings. The social media analysis method used in this study, including text mining and sentiment analysis, can be easily extended to multiple language analysis for Singapore, Malaysia, as well as other regions in the belt and road plan. The developed tools could contribute to analyzing the influence of cross-country projects on local neighborhoods in the belt and road plan. • This study assessed the effect of new transit station on people's activity and sentiment via social media data. • Methods on analyzing Twitter data in Hong Kong are developed. • The introduction of new transit stations increases tweet activity in nearby areas. • New transit stations yet not always promote positive changes on tweet sentiment in nearby areas. • The methodologies, data, and findings are applicable to other regions in the Belt and Road Initiative. [ABSTRACT FROM AUTHOR]

• This study analyzed demolition practices and discussed existing challenges. • BIM is integrated with advanced technologies for building demolition. • Three key services are proposed to facilitate the building demolition. • A case study is provided to demonstrate the proposed framework. • A benefit-cost analysis is used to assess the proposed framework performance. Hong Kong's construction industry, known for its massive building infrastructure, produces an enormous amount of waste every year, the vast majority of which is disposed for landfills. Therefore, some effective operational measures and waste management policies have been implemented. However, enormous waste remains a concern for stakeholders and exert pressure on the limited capacity of Hong Kong's landfills. Though previous research discusses Building Information Modelling (BIM) application for construction waste management enhancement, the BIM model has not been widely implemented for building demolition with waste management. Hence, as a response to the aforementioned shortcomings, this paper develops a conceptual framework that allows collecting, maintaining, and analyzing comprehensive information through Smart BIM that uses advanced technologies such as Internet of Things (IoT) and capable of reacting to user activities such as waste quantitative assessment, demolition process planning, optimal disposal route selection, and waste management strategy are executed. The advantages of the proposed framework are shown in a case study benefit-cost analysis based on three planned reuse and recycling-rate scenarios that explain on- and off-site recycling methods. The results show that the proposed framework will pave the way for generating sustainable waste disposal practices by providing technical and decision-making support functionalities to engineers and planners in the construction industry. [ABSTRACT FROM AUTHOR]

• An optimal width allocation policy for traffic lanes and footpaths is developed. • Optimal lane width is 5.4 m when user and agency costs are equally important. • Hong Kong road agency places a higher weight on each dollar of user cost. • Allocation to footpaths can reflect the importance placed on pedestrian safety. Introduction: Walkability continues to attract great attention from urban planners, designers, and engineers as they recognize not only the merits of pedestrian facilities in terms of the health benefits but also their demerits in terms of accident risk to pedestrians. Wide footpaths improve the pedestrian environment and experience, and thereby motivate travelers to walk as much as possible. However, if footpaths are too wide, they may leave a smaller space for the roadway. On the other hand, wide road lanes may lead to higher road vehicle safety but are costly to construct and maintain and also may leave little space for the footpath. Evidently, for a fixed urban space, what is needed is an optimal balance between the vehicle lane and pedestrian path. This problem is encountered routinely in dense cities including Hong Kong where land availability is severely limited. Method: To address the issue, this paper first establishes safety performance functions (SPFs) for the pedestrian space and the road space, using the random-parameter negative binomial regression. The results indicate the extent to which road lane and footpath width changes are associated with changes in in-vehicle occupant and pedestrian casualties. Then the paper uses the SPFs to develop a methodology for optimizing the width allocations to the road lanes and footpaths, duly considering the user (safety) costs and agency (construction) costs associated with each candidate allocation of the widths. Finally, the paper analyzes the sensitivity of the optimal solution to the relative weights of user cost and agency cost. Results: When user and agency costs are considered equally important, the optimal lane width is 5.4 m. Conclusion: It is observed that the road space allocation ratio used by the Hong Kong road agency suggests that the agency places a higher weight to user cost compared to agency cost. Practical Application: The findings can help incorporate design-safety relationships, and the stakeholders (agency and users) perspectives in urban road and footpath design. [ABSTRACT FROM AUTHOR]

• The study tested effects of demographic, psychological, and situational variables on Leave No Litter intention. • Attitude, perceived behavioral control, and preparedness had significant direct effects. • Attitude, subjective norm, and perceived behavioral control had significant indirect effects. • Theoretical and practical implications of the findings were discussed. Along the line that "Leave No Litter" (LNL) in protected areas is promoted globally, Hong Kong launched its LNL campaign in 2016. The success of the campaign is critically dependent on the compliance of the park visitors. Because behavioral intention is influenced by determinants of different domains, this study adopted a multilevel perspective to examine how demographic, psychological, and situational variables affected LNL intention using a voluntary response sample of 374 hikers in Hong Kong. The results indicated that attitude, perceived behavioral control, and preparedness were significant predictors of LNL intention, indicating the direct associations between them. Furthermore, preparedness mediated the effects of attitude, subjective norm, and perceived behavioral control on LNL intention. The findings of this paper may contribute to the body of knowledge on pro-environmental behavior of recreationists by providing a novel understanding of LNL intention of Hong Kong hikers. Furthermore, this study may cast light on the sustainable management of protected areas in Hong Kong as well as cities around the world. [ABSTRACT FROM AUTHOR]

Transit-induced gentrification is a popular topic of research and a pressing concern worldwide. However, little attention is paid to the connection between rail transit development and the movement of low-income residents. To investigate this important issue, this paper studies the development of the Mass Transit Railway (MTR) in Hong Kong between 2001 and 2006, which added three new rail transit lines covering a total length of 65 km. By using census statistics at the district council constituency area (DCCA) level in a difference-in-differences approach, we find that MTR development in Hong Kong between 2002 and 2004 increased the number of advanced degree holders (Bachelor's degree and above) by 10% in the New Territories and 7.81% in the new towns and reduced the number of low-income households by 5.85% in the New Territories and 7.53% in the new towns. To confirm that these socioeconomic changes were driven by internal migration, we further use household-level data from the 5% population censuses in 2001 and 2006 in a multinomial logistic regression. The results indicate that MTR development between 2002 and 2004 was likely to induce high-educated people to move into and low-income households to move out of MTR-served areas. The results show that the New Territories and the new towns in Hong Kong underwent gentrification between 2001 and 2006. We therefore suggest that the Hong Kong government negotiate with MTR Corporation to allocate resources to develop properties for low-income families. [ABSTRACT FROM AUTHOR]

• The proposed tropical cyclone model is completely driven by a set of environmental variables. • This model reproduces the spatial and temporal characteristics of observed tropical cyclones. • The model achieves remarkable balance between computational complexity and efficiency. • This model will provide decision-makers with valuable information regarding potential wind-induced hazards. • When future climate data are fed into this model, the impact of climate change on tropical cyclones can be evaluated. This paper presents an environment-driven tropical cyclone (TC) model for the Western North Pacific basin, which comprises a revised Poisson regression genesis model, a tailored beta-advection track model, and a fast intensity model. The TC model reproduces the temporal and spatial distributions of genesis events, the motion pattern of tracks, as well as the intensity evolutions along tracks. Risk analyses for Hong Kong and along the southeast coastline of mainland China demonstrate that this model can simulate extreme TC events with high fidelity. And the Gaussian mixture model outperforms the Frank Copula in approximating the joint distributions of the annual maximum wind speeds and the corresponding wind directions. This model is driven by a set of environmental variables including relative vorticity, relative humidity, sea surface temperature, vertical wind shear, potential intensity, sub mixed layer depth stratification, mixture layer depth and so on. This enables the model to not only reproduce historical records, but also make predictions for future TC behaviors under climate change with combination of global climate models. Besides, the computational efficiency of the TC model is comparable to traditional purely statistical models. The proposed model can also be coupled with other natural hazard models to conduct multi-hazard analysis. [ABSTRACT FROM AUTHOR]

• A comprehensive analysis of root causes for the accelerated internal corrosion in steel saltwater pipes coated with fusion bonded epoxy. • Cathodic delamination of the epoxy lining is identified as the primary cause of early internal corrosion failure. • Dynamic cyclic load has a greater chance for crack propagation in the epoxy lining compared to static load. • Development of recommendations and precautions based on the results of failure analysis. Effective functioning of saltwater supply system is essential to Hong Kong government agencies. However, it has been frequently observed that steel saltwater pipes suffered from severe internal corrosion and consequently early burst accidents, which may cause high economic loss and safety concerns to the public. Therefore, by taking a sample saltwater pipe made of DN450 mild steel with internal and external walls coated with fusion bonded epoxy in Hong Kong, this paper investigates the root causes and failure mechanism for the internal corrosion of this failed steel saltwater pipe through laboratory experiments and numerical simulation analysis. Two hypotheses are proposed and validated: (1) cathodic delamination of the epoxy lining, and (2) delamination of the epoxy lining due to external mechanical loads. The results verify that the sample saltwater pipe failed due to the cathodic delamination of the epoxy lining, and the electrochemical corrosion of the inner pipe wall. Moreover, it can be concluded that external mechanical load has few significant impacts on the damage of the epoxy lining for this sample pipe. This study exemplifies the importance of an in-depth analysis on the internal corrosion of steel water pipes, especially in a highly-corrosive internal environment. [ABSTRACT FROM AUTHOR]

• A quantified approach to evaluate users' attitudes towards Crowd Management System. • Estimating the Willingness-to-Pay with the Contingent Valuation method. • Perceived usefulness and online payment habit greatly influence users' attitudes. • Good indications for future research on the use of ICT for safety enhancement. Smart city projects are being launched globally to enhance the well-being of citizens. Meanwhile, the value-added of the projects is not easy to evaluate due to the non-market nature of the public services provided. This study intends to investigate the attitudes of potential users of a Crowd Management System (CMS) to help with the decision-making on smart city projects. The CMS studied in this paper is applied in large-scale events to enable safe and efficient dissipation of event participants as one of the pilot Smart City projects in Hong Kong. It does so by providing real-time information on public transport for their return journeys when a large number of participants all finish their activities within a short time span. Reducing injuries of pedestrians can be achieved in major gatherings to improve safety. This paper presents an experimental analysis of users' attitudes towards the CMS with the Contingent Valuation (CV) method. A marathon event in Hong Kong was chosen for an on-the-spot survey of actual users as part of an experimental study. Subsequently a similar survey was carried out off-site among marathon runners not participating in that event (as a control group) for data reliability comparison. The Willingness-to-Pay value is also derived from the pooled samples to evaluate users' attitudes. Besides, the results indicate that runners' perceived usefulness and online payment habit significantly influence the stated Willingness-to-Pay (WTP) for the CMS in question. [ABSTRACT FROM AUTHOR]

In this paper, we estimate the energy efficiency of educational buildings with the case study of buildings in City University of Hong Kong by constructing an energy demand stochastic frontier model. The model is estimated by using the university statistical data from 2011 to 2015. For the consistent frequency of data among the variables, we have adopted the quadratic-match sum method to convert annual university report data into a monthly dataset. Our result shows the average energy efficiency is 0.87, implying that 13% of total energy consumption can be saved. We then calculate how much of the energy saving potential has been achieved by constructing the performance score, which increases from 0.08 to 0.17. It implies that the campus performs more efficiently in saving energy over time. We further develop econometric decomposition analysis based on the energy demand frontier model to identify the factors affecting energy consumption. It suggests that research activities account for a large share of overall energy consumption. Analysis on energy end-use shows university should improve efficiency in lab instrument as it is least efficient among the four usages. We expect this paper can provide the fundamental and methodological guideline for university-scale energy efficiency estimation. • Estimating energy efficiency of educational buildings needs to consider the composition of research related factors. • Energy efficiency of campus building presents increasing tendency with seasonal cycle over time. • Research related variables affect significantly on energy efficiency of educational buildings. • Energy use in lab instrument needs to be effectively managed to save energy. [ABSTRACT FROM AUTHOR]

• This paper focuses on daily natural gas consumption forecasting. • A novel hybrid model is developed for daily natural gas consumption forecasting. • The most recent datasets of four cities in three climate zones are collected. • An improved singular spectrum analysis is first proposed. In daily natural gas consumption forecasting, the accuracy of forecasting models is vulnerably affected by the noise data in historical time series. Singular spectrum analysis (SSA) is often introduced into hybrid models for denoising. However, as a deterministic-based algorithm, SSA does not give good results when a time series is contaminated with a high noise level. Considering this fact, this paper proposes an improved SSA (ISSA) that modifies the determination method of subseries selection in the reconstruction stage of SSA. Combining ISSA with long short-term memory (LSTM), a novel hybrid model, ISSA-LSTM, is thus developed. Additionally, for validating the robustness and superiority of ISSA-LSTM, the historical datasets of four representative cities located in three climate zones are collected as the training and testing datasets, and a comparison of ISSA-LSTM with five advanced models is performed. The results reveal that SSA would generate negative values when time series close to zero and the contribution of SSA in improving the forecasting accuracy of LSTM is insignificant. In contrast, ISSA avoids generating negative values and reduces the mean absolute range normalized error (MARNE) of LSTM by a range of 0.86–11.86%. Among the models, ISSA-LSTM achieves the best performance and its MARNEs for London (temperate zone), Melbourne (subtropical zone), Karditsa (subtropical zone), and Hong Kong (tropical zone) are 4.68%, 5.72%, 5.76%, and 14.10%, respectively. The MARNE of the tropical city is higher than that of others, which is caused by the complex natural gas consumption pattern of itself. [ABSTRACT FROM AUTHOR]

The ageing population has become a global problem in which enhanced understanding on their activity-travel patterns is needed. In this paper, an analysis of retired and dual-earner couples is conducted to investigate how retirement would change their activity time use and patterns. In particular, intra-household interactions are considered, to explore the interdependencies among household members' choices, social-demographics and travel behaviours. Household survey data from Hong Kong are employed. Results show that retirement would substantially increase joint participations and durations in various out-of-home activities. In addition, the importance of walkability is emphasised for retired couples in a mixed-land-use and transit-dependent city, and a potential social exclusion issue is identified for the low-income retired population. Scenarios analyses including changes of built environment and lifestyles (e.g., telecommuting, online shopping and food delivery) are conducted, to investigate how couples would reallocate the saved travel time. In summary, this paper highlights the importance of considering the group decision mechanism in a household for activity generation and travel demand forecasting. It sheds light on policies to improve quality-of-life for couples before and after the retirement. [ABSTRACT FROM AUTHOR]

In practice, most of the intelligent transportation systems provide average travel times of all vehicles on selected paths in real time on a regular basis. However, path travel times of different vehicles could vary widely under different traffic conditions. There is a need to consider the differences in vehicle classes for path travel time estimation. This paper proposes a novel modeling framework that considers variance–covariance relationships between vehicle classes for real-time estimation of multi-class path travel times with use of multi-source traffic data collected from various types of sensors. The proposed methodology is examined with a case study of a selected urban expressway in Hong Kong with data obtained from multiple sources. The path travel time estimates by vehicle class are validated and the results demonstrate the merits and performance of the proposed framework. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicle (UAV)-based commercial services, exemplified by drone delivery, have captured wide interest in tech companies, entrepreneurs, and policymakers. Structured route-based UAV operations have been implemented for traffic management of UAVs in support of commercial delivery services in cities. Yet, its essence, multi-path planning with constraints is not well solved in the existing literature. Centralized planning might result in inefficiencies and unfairness in the allocation of precious urban airspace to individual routes. This paper describes a novel distributed route planning method to support UAV operations in a high-density urban environment. The method allows each origin–destination (OD) pair to compete against other OD pairs for an optimized route (e.g. shortest distance), coordinated by a system-level evaluation, leading to a network design that maximizes the performance of not only the individual routes but also the entire system. The core concept is the introduction of congestion pricing, a soft constraint to coordinate the allocation of airspace. The method is tested in standard 2D scenarios and compared with other state-of-the-art methods. The results show that (1) the method is able to generate routes with short individual distances as well as occupying the least airspace by the route network; (2) in some complex scenarios, the method is able to find a solution in a short period of time while other state-of-the-art method fails. The method has also been applied to a real urban environment (Mong Kok in Hong Kong) to demonstrate its capability. • Presented a multi-path method to design air route networks for urban drone delivery. • Introduced congestion cost as a flexible constraint for airspace allocation. • Employed a distributed approach for resolving conflicts between origin-destination pairs. • Outperformed other leading methods in balancing efficiency and computation speed. • Validated the proposed system through tests in real-world settings. [ABSTRACT FROM AUTHOR]

This paper investigates the time-varying and land use-induced spillover effects of urban redevelopment, providing a lens through which to understand the welfare implications of both the temporal dynamics and the land use changes that occur through urban transformation. By analysing redevelopment project and housing transaction data from Hong Kong between 2005 and 2020, we find significant, positive spillover effects of urban redevelopment on local housing prices following the redevelopment announcement, with diminishing magnitudes as the redevelopment project proceeds. We also find heterogeneous spillover effects associated with different functional land use changes in redevelopment projects. The direction and extent of these externalities depend on the trade-off between the changes in local amenities and the changes in the level of competitiveness in the local housing market. • Redevelopment has time-varying and land use-induced spillover effects. • In general, spillover effects show a diminishing magnitude as the project proceeds. • The time-varying spillover patterns depend on the specific changes in land uses. • Redevelopments pose negative spillovers through the competitiveness channel. • Redevelopments pose positive spillovers through the amenity channel. [ABSTRACT FROM AUTHOR]

Time-series interferometric synthetic aperture radar (InSAR) provides a unique tool for measuring large-scale and long-term land surface deformation. Under the assumption of a single linear deformation model in conventional InSAR, it is difficult to quantify and interpret the impacts of multiple environmental factors that presumably induce nonlinear deformations. In this paper, we propose a SAR-Transformer method to decompose InSAR time-series signals into various physics-related components and apply the method to evaluate the deformation of the world's longest cross-sea bridge, the Hong Kong-Zhuhai-Macao Bridge (HZMB). We first developed an improved bridge geometry-based InSAR network to monitor the deformation of the HZMB using Sentinel-1 and COSMO-SkyMed images from 2019 to 2022, which were validated using the leveling and GPS data. The SAR-Transformer model was trained using synthetic InSAR time-series samples and applied to decompose the monitored InSAR measurements. Compared with that of conventional curve-fitting and seasonal-trend decomposition using LOESS, SAR-Transformer reduced the mean absolute error at least by 58.32% and mean absolute percentage error at least by 8.84% for time-series signal reconstruction. We evaluated the decomposed patterns according to the geotechnical, meteorological, and marine processes, and found that: 1) Seasonal thermal expansion owing to temperature changes was significant in all parts of the bridge, and deflection due to concrete shrinkage and creep was observed on cable-stayed bridges. 2) The artificial islands experienced evident ground subsidence with a decelerating trend. In particular, the newly adopted non-dredged reclamation method resulted in a lower decelerated settlement than that of fully-dredged reclamation areas. 3) The seawall showed linear horizontal movement from the outward stretching of the reclaimed soil consolidation and periodic displacement related to sea tidal loading. Furthermore, typhoons and coastal earthquakes had limited effects on the permanent movement of the bridge. These results improve the understanding of the interactions between artificial super-infrastructures and environmental factors, and provide valuable guidelines for the maintenance and management of the HZMB. • An improved BGN was developed to monitor bridge deformations in TSInSAR. • The SAR-Transformer model was proposed to decompose the InSAR time series. • Three indexes were generated for time-series deformation characterization. • The decomposed patterns were evaluated using various environmental factors. [ABSTRACT FROM AUTHOR]

Hong Kong, among the world's most densely populated cities, has witnessed rapid growth in traffic volume, resulting in increased traffic density and vehicle loads. Regular bridge inspections are imperative to ensure human safety and safeguard property. However, conventional visual inspection methods are highly criticized for their critical limitations such as inaccuracy, subjectivity, labor-intensiveness, tediousness, and hazardousness. Cracks are regarded as the most prevalent type of defects encountered during inspection of reinforced concrete bridges. Automated detection of bridge surface cracks is a quite challenging and hectic task due to their random characteristics and usual in complex and non-uniform background textures. Presence. In light of foregoing, this paper proposes a novel computer vision model for concrete bridge crack detection in an attempt to circumvent the critical deficiencies of manual visual inspection. The developed model is envisioned on the use of you only look once version 8 (YOLOv8) architecture, which is cited as one of the most advanced convolutional neural networks structures for multi-scale object detection. Comprising three fundamental components - the backbone, neck, and head, this model introduces the concept of a decoupled head, segregating it into a detection head and a classification head. This design empowers the model with greater flexibility in handling diverse tasks. Moreover, the incorporation of the global attention module (GAM) and the wise intersection over union (IoU) loss function serves to further boost detection correctness of the developed model and amplify its generalization ability. The developed YOLOv8-GAM-Wise-IoU is compared against some of the widely acknowledged one-stage and two-stage deep learning models using the evaluation metrics of precision, recall, F1-score, mean average precision (mAP) and IoU. It outperformed them accomplishing testing precision, recall, F1-score, mAP50, mAP50–95 and mAP75 of 97.4%, 94.9%, 0.96, 98.1%, 76.2%, and 97.8%, respectively. It is also observed that developed model maintains a modest size of 93.20 M resulting in diminishing the computational cost of training and inference processes. This makes it highly deployable in various crack detection pertaining applications. It can be argued that the developed model can contribute notably to the preservation of safety and integrity of reinforced concrete bridges in Hong Kong environment. • Previously developed bridge crack detection models are reviewed. • A Novel YOLOv8-GAM-Wise-IoU Model is proposed for bridge crack detection. • GAM and Wise-IOU are introduced to enhance detection correctness. • One-stage and two-stage deep learning models are used for validation. • Efficiency of the developed model is extensively scrutinized and exemplified. [ABSTRACT FROM AUTHOR]

This paper reports a new knowledge-driven engineered feature learning approach in response to the Global AI Challenge for Building E&M Facilities held by the Electrical and Mechanical Service Department (EMSD) of the Hong Kong SAR. The results were awarded with a Grand Prize by the competition organizer. A dynamically engineered multi-modal feature learning (DEMMFL) method is proposed for predicting the cooling load of two office buildings. The DEMMFL model is estimated with the Lasso-ridge regression and compared with other well-known methods such as the Lasso. The novel approach applies control system knowledge to engineer useful features and explore load patterns for multi-mode modeling. Deep learning methods including LSTM, GRU, and AutoGluon are implemented for automated machine learning and tested in parallel to compare the performance of the proposed model with existing methods. The proposed model is demonstrated to predict long-term cooling load most accurately using engineered features from weather information only. • A new dynamic feature engineering method for office building cooling load prediction. • Slow and fast dynamic features engineered from available weather data only. • Control-knowledge based feature to learn on-hours dynamic responses. • Multi-modal approach with eight day-type features to learn occupancy loads. • Deep recurrent learning and AutoML methods compared to the proposed method. [ABSTRACT FROM AUTHOR]

Conductive hydrogels have wide use in multifunctional sensors. Nevertheless, the intrinsic features of conductive hydrogels, including the absence of sensation mechanisms with varied properties, impede their application in wearable devices. To this end, this paper fabricated a novel 3D network material, namely C/PVA/CaCl 2 /HK (CPCH) hydrogel, that comprises incorporation of graphite (C), calcium chloride (CaCl 2), hydrolyzed keratin (HK), and the polyvinyl alcohol-based (PVA-based) hydrogel. The CPCH hydrogel and the CPCH secondary hydrogel both exhibit impressive mechanical properties. The former features a maximum stress of 2.98 MPa and a maximum strain of 588 %, while the corresponding values of the latter are 1.590 MPa and 573 %, respectively. Additionally, the result showed a maximum reflected light barrier of the CPCH hydrogel at a wavelength of 248 nm. The study found that the CPCH hydrogel holds the fingers attached to the upper surface during heating for up to 10 s, demonstrating superior heat insulation performance. The gel fraction analysis revealed that the gel makes up 57.1 % of our prepared CPCH hydrogel with a porosity of 62.5 %. Besides, we conducted a conductivity test on the proposed hydrogel, obtaining a measured conductivity value of 0.04 mS/cm. Furthermore, its practicality and feasibility have been confirmed via experiments. The results show that the CPCH conductive hydrogel can potentially be a temperature-strain sensor for wearable devices. [Display omitted] • Discovering a new type of material that can be reused. • Doping graphite can significantly enhance the mechanical properties of the material. • Doping graphite enhances the hydrogel's conductivity and flexibility, thereby improving the sensor's performance. • The temperature-strain sensor made of flexible conductive hydrogel exhibits good reliability and stability. [ABSTRACT FROM AUTHOR]

This paper reports on an exploration into difficulties in junior secondary science lessons taught through English in the largely Cantonese-speaking context of Hong Kong. The study was carried out by an educational linguist and a science education specialist working in collaboration, and identified difficulties through student questionnaires, interviews with teachers, and classroom observation. Understandings of genre based in systemic functional linguistics were used in conjunction with knowledge of the science curriculum to investigate these difficulties. Extracts from lessons and teaching materials on energy conversion are discussed, with additional reference to interviews and questionnaires. Analysis revealed the influence of teaching materials on coherence between curricular objectives and teacher discourse. In particular, complex description detracted from explanations, affecting student understanding of the lesson. [ABSTRACT FROM AUTHOR]