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As a form of social movement aiming to effect social change, protests could bring about unintended impacts on all walks of life. In other words, the cost of protests can be incurred by those who might not be protesters. The protests triggered by an extradition bill in Hong Kong since 2019 are no exception. This paper focuses on the impacts on the ridership of the metro system on protest days. It synthesizes and hypothesizes factors influencing the distribution of the ridership changes and conducts an empirical study in the context of Hong Kong to study the possible influences and spatial dependence. It is found that, across metro stations, political orientation (percentage of votes to pro-democracy camp in the 2019 Election of District Councils), law enforcement (permission from the police to protest), land use type (especially for commercial and open space), population age and income, as well as transit/road network characteristics and intermodal connectivity, significantly influence the ridership of metro stations during protest days. In addition, the mixed regressive spatial autoregressive model has higher explanatory power than the ordinary least square model, suggesting the need for a spatial lag and error specification. The results could also have significant implications for policy and planning for operating metro services and managing metro stations before, during, and after social shocks.

Grammatical metaphor in M. A. K. Halliday’s sense has long been extensively investigated by researchers in terms of theoretical and empirical studies. Regarding the empirical studies, they have predominantly employed observed or normalized frequencies of grammatical metaphor to uncover its distribution in different text types. Few studies, however, were conducted to quantitatively examine the complexity of grammatical metaphor in that no indicator presently is proposed to measure the degree of complexity in grammatical metaphor. This paper targeted at investigating the feasibility of implementing entropy to measure this complexity. The findings demonstrate that the entropy value could be afforded as an indicator of complexity of grammatical metaphor to efficiently uncover the way that disciplines of different registers build knowledge by means of employing such linguistic features as grammatical metaphor. This research is significant in that it sheds light on the quantitative comparison of complexity of grammatical metaphor in text analysis.

Being different from previous researches which explore the possible multiple modal patterns in Mandarin Chinese basically with invented examples, this study examines the attested patterns of successive use of modals facilitated by two large Chinese corpora (Corpus of Center for Chinese Linguistics Peking University or CCL, and Beijing Language and Culture University Corpus Center or BCC) and the reasons underlying these patterns. The data reveal that combinations of Chinese modals of different types comply with the proximity to the predicate verb of the proposition. The exact sequential order is demonstrated as follows: dynamic modality precedes the predicate verb; deontic modality precedes dynamic modality; and epistemic modality precedes deontic and dynamic modalities. In addition, different modal auxiliaries of the same type also co-occur in a special sequence. From the perspective of subjectivity and objectivity, we argue that the underlying principle of this ordering is that the more subjective a modal auxiliary is, the more distant it will be from the predicate verb of the proposition and vice versa. For successive patterns of different modal auxiliaries within the same type, the concept of gradability is employed. Although modal auxiliaries of the same type might occur at the same distance to the predicate verb of the proposition, they could characterize different degrees of gradabilities. Modals with higher degree of gradability could precede those with lower degrees, whereas those with the same degree of gradability are capable of the successive co-occurrence in either way.

Interpersonal modality, bifurcating modalization and modulation, is an important construct of interpersonal meaning in the architecture of Systemic Functional Linguistics. By meticulously reviewing relevant studies from the perspectives of traditional modality and modality’s semantic map, three respects with respect to the system of interpersonal modality have been supplemented. Firstly, modalization, being subcategorized into possibility and usuality, is suggested to entertain evidentiality from the traditional sense. Secondly, considering the delicacy of the system of interpersonal modality, possibility in modalization should be further categorized into epistemic and root possibility; necessity as one subtype of modulation, superseding the original obligation in modulation, is subclassified into obligation and permission; inclination, being the other subtype of modulation, should be specified as the superordinate of volition and ability. Thirdly, the shifting of modal meanings from root possibility to epistemic possibility in modalization and from inclination to necessity in modulation should be clearly specified as far as language evolvement is concerned.

A complete tour of metro users consists of their journeys inside the carriage and various activities outside the carriage, in particular, those in or around metro station areas (MSAs). To fathom out the spatiality and magnitude of those activities, which involve substantial interactions among people or with urban spaces, we assume that (a) metro users who spent 30 min or more together in or around the same MSA would physically interact with at least another person there; (b) the more an MSA sees metro riders co-presenting there the higher social interaction potential (SIP) there is; (c) SIP of an MSA is positively correlated with the number of distinct riders co-presenting in that MSA. By exploiting two-day metro smartcard data of Wuhan, China, we use the number of distinct riders co-presenting in that MSA to measure and visualize the MSA-level SIP in that city. Our visuals show the SIP varies across MSA and time of the day. Some MSAs have higher SIP in the daytime whereas other MSAs have higher SIP at the nighttime. Few MSAs continuously have high SIP. These results inform us where and when SIP would be the highest and the lowest across MSAs, which can facilitate metro operators’ monitoring and management of MSAs on the one hand and help businessmen and officials decide where and when to provide services and/or sell products across MSAs.

The grammatical pattern of explicit objective modal expressions and its three subtypes (i.e., explicit objective expressions of probability, usuality and obligation) are investigated in this paper....

As a sustainable mode of travel, walking for transportation has multiple environmental, social, and health-related benefits. In existing studies, however, such walking has rarely been differentiated between commuting and non-commuting trips. Using multilevel zero-inflated negative binomial regression and multilevel Tobit regression models, this study empirically examines the frequency and duration of commuting and non-commuting walking and their correlates in Xiamen, China. It finds that (1) non-commuting walking, on average, has a higher frequency and longer duration than commuting walking; (2) most socio-demographic variables are significant predictors, and age, occupation, and family size have opposite-direction effects on commuting and non-commuting walking; and (3) different sets of built environment variables are correlated with commuting and non-commuting walking, and the built environment collectively influences the latter more significantly than the former. The findings provide useful references for customized interventions concerning promoting commuting and non-commuting walking.

In this article, we address the public transportation system’s resilience in social movements, which has been under-explored in transportation scholarship. On the one hand, public transportation enables mass mobilization of people and materials and large-scale public engagement in political/social events in transit-reliant cities like Hong Kong. On the other hand, public transportation can be an instrument for both the government and event participants—the former interferes with the public transportation service provision to manage and mitigate the adverse impacts of social movements it perceives on society, whereas the latter disrupt public transportation services or vandalize and damage related facilities to express their discontent and to put pressure on the former. The dynamic resilience of the public transportation system against the above backdrop warrants more in-depth exploration. We incorporate both supply and demand shocks to theorize resilience as a public transportation system’s capability to return to a new equilibrium between the supply and demand after a disturbance. The theoretical approach is illustrated using empirical data and publicly available materials concerning the 2019 Anti-Extradition Law Amendment Bill movement in Hong Kong.

In Systemic Functional Linguistics, meanings in semantic stratum could be realized by congruent/premetaphorical, metaphorical, or demetaphorical/post-metaphorical expressions in lexico-grammatical stratum. This paper, evidenced from the Corpus of Historical American English (COHA), explores the specific pathway from metaphorical expressions to post-metaphorical ones guided by principles of Context-first and AS IF and the principle of double functionality. The findings show that grammatical postmetaphorization is mainly realized by post-metaphor of ideation and that of modality. The former finds its expressions from common nouns to proper nouns (e.g. from security to Security), or from uncountable nouns to countable nouns (e.g. from security to securities), and the latter is evidenced by expressions shifting from explicit objective orientation to its explicit subjective counterpart (e.g. from it is possible that to it might be possible that), or by modal probability of I think type shifting from clausal initial position to clausal medial or final position (e.g. I think in the medial or final position of the clause).

With the development of digital technology and the popularity of human-centered concepts in museum exhibition design, the user experience of VR (virtual reality)-based museum exhibition (VRME) is gradually being emphasized. There are still many problems that need to be solved in the integration of technology and interaction in today’s VRME design. However, the existing museum exhibition design framework does not combine the characteristics of virtual reality technology to solve the problems unique to VRME in a targeted manner. Based on the traditional user experience framework, this paper summarizes the three levels of user experience (LoUX) in a museum exhibition and proposes the unique “creation level” experience of VRME, which constitutes the closed-loop of the VRME experience. Then, this paper analyzes the relevant researches in recent years through a literature review and summarizes the trends of technology application and the different interaction problems arising from each LoUX. Based on the results of literature analysis, this paper proposes a “rose model” of VRME. This model summarizes the relationship between exhibition technology, sensory types, LoUX, and human-exhibition interaction factors, which has certain guiding significance for VRME design. Finally, this paper discusses the results of the literature review and the interaction design insights brought by the model.

Background In the fight against the COVID-19 epidemic, internet-based diagnosis and treatment services are a promising technology that can be used effectively in health care. Objective The goal of this study was to examine the research state and show the hotspots and frontiers of Internet-based diagnosis and therapy using CiteSpace V. Methods From 2001 to 2020, we searched the Web of Science Core Collection (WoSCC) for papers on Internet-based diagnosis and therapy. CiteSpace V was used to produce network maps of author, country, and institution collaborations, revealing hotspots and frontiers of Internet-based diagnosis and treatment. Results The Web of Science Core Collection (WoSCC) yielded a total of 1067 studies linked to Internet-based diagnosis and therapy. The most prolific author was Gerhard Andersson (16 articles). The United States and Karolinska Institutet were the leading nations and institutions in this discipline, with 590 and 57 publications, respectively. There was active collaboration among the writers, nations, and institutions. Hot subjects included artificial intelligence, health-related quality, and breast cancer. Conclusions Based on the findings of CiteSpace V, the present study encourages active collaboration among authors, nations, and institutions. Major continuing research themes include cancer diagnosis and treatment based on artificial intelligence or Internet emphasis, as well as the interplay between Internet-based diagnostic and treatment services and health-related quality.

The impacts of coronavirus disease 2019 (COVID-19) on society and economy are wide-ranging, long-lasting, and global. The experience of multiple countries or regions in fighting the pandemic indicates that there could be multiple COVID-19 surges, where a growing number of cases can be observed in the more recent surge(s). Were COVID-19 cases and clusters of cases (across surges) randomly distributed in spaces? Did population density and activity centres influence clusters of cases and associated venues? Based on information on the associated venues of the four surges of COVID-19 cases between January 2020 and February 2021 as well as population density, visuals were made to distinguish the relationships between population density, activity centres, and clusters of cases in Hong Kong. Different spatial patterns were observed across the four surges: fewer cases were observed in the first surge with a more evenly distributed pattern of clusters; the second surge as compared to the first surge saw a wider distribution and an increase in the number/layer of clusters; compared to the second surge, the third surge suffered from many more cases but saw a decrease in the general number of clusters; and compared to the previous three surges, the fourth surge had the largest number of cases, yet even fewer clusters were observed, where several clusters are again concentrated in specific areas similar to the previous surge. Across the four surges, a few locales could see recurrent clusters of cases and a few communities were without cases.

English elemental ordering in a non-canonical word order incorporates preposing, postposing and elemental reversal. This paper intends to explore how these types of elemental ordering are distribut...

Vibrancy is one of the most desirable outcomes of transit-oriented development (TOD). The vibrancy of a metro station area (MSA) depends partially on the MSA’s built-environment features. Predicting an MSA’s vibrancy with its built-environment features is of great interest to decision makers as these features are often modifiable by public interventions. However, little has been done on MSAs’ vibrancy in existing studies. On the one hand, seldom has the vibrancy of MSAs been explicitly explored, and measuring the vibrancy is essential. On the other hand, because MSAs are interconnected, one MSA’s vibrancy depends on the MSA’s features and those of relevant MSAs. Hence, selecting a suitable metric that quantifies spatial relationships between MSAs can better predict MSAs’ vibrancy. In this study, we identify four single-dimensional vibrancy proxies and fuse them into an integrated index. Moreover, we design a two-layer graph convolutional neural network model that accounts for both the built-environment features of MSAs and spatial relationships between MSAs. We employ the model in an empirical study in Shenzhen, China, and illustrate (1) how different metrics of spatial relationships influence the prediction of MSAs’ vibrancy; (2) how the predictability varies across single-dimensional and integrated proxies of MSAs’ vibrancy; and (3) how the findings of this study can be used to enlighten decision makers. This study enriches our understandings of spatial relationships between MSAs. Moreover, it can help decision makers with targeted policies for developing MSAs towards TOD.

Dental caries is a widespread chronic infectious disease which may induce a series of oral and general problems if untreated. As a result, early diagnosis and follow-up following radiation-free dental caries therapy are critical. Terahertz (THz) waves with highly penetrating and non-ionizing properties are ideally suited for dental caries diagnosis, however related research in this area is still in its infancy. Here, we successfully observe the existence of THz birefringence phenomenon in enamel and demonstrate the feasibility of utilizing THz spectroscopy and birefringence to realize caries diagnosis. By comparing THz responses between healthy teeth and caries, the transmitted THz signals in caries are evidently reduced. Concomitantly, the THz birefringence is also unambiguously inhibited when caries occurs due to the destruction of the internal hydroxyapatite crystal structure. This THz anisotropic activity is position-dependent, which can be qualitatively understood by optical microscopic imaging of dental structures. To increase the accuracy of THz technology in detecting dental caries and stimulate the development of THz caries instruments, the presence of significant THz birefringence effect induced anisotropy in enamel, in combination with the strong THz attenuation at the caries, may be used as a new tool for caries diagnosis.

In recent decades, transit equity has become a recurrent topic within the domain of sustainable transportation, where accessibility is a crucial indicator. However, the measurement of acce...

Problem, research strategy, and findings: In this study, we investigate how to exploit big and open data (BOD) to quantitatively examine the relationships between transit-oriented development (TOD)...

This paper profiles the pathway from Bernstein’s code theory and knowledge structure to Halliday’s grammatical metaphor. It firstly delineates the theorizing of code theory and knowledge structure, and subsequently describes the process of associating itself with Karl Maton’s legitimate code theory. Finally, drawing upon the semantic dimension of legitimate code theory, that is, semantic density and semantic gravity, Halliday’s grammatical metaphor is expounded sociologically.

The application of Systemic Functional Linguistic theories into text analysis is not new, and so is the transitivity system. This paper combines the qualitative and quantitative research methodologies to elucidate how Mandela, chapter 115 of A Long Walk to Freedom, deploys the elements of transitivity system to expound his ideas to his compatriots and align them together with him to fight for their freedom. The findings show that he mainly incorporates material processes and relational processes and deliberately uses the passive voice to invoke his fellow countrymen to fulfill the role of “actors”.

Terahertz birefringence phenomenon in enamel is, for the first time, observed via terahertz time-domain spectroscopy, which is weakened or even disappeared when caries is formed, expecting to be applied in early diagnosis of dental caries.

The outbreak of COVID-19 and subsequent pandemic containment measures have significantly affected our daily life, which has been extensively examined in the existing scholarship. However, the existing scholarship has done little on the jobs/housing relationship impacts of COVID-19. We attempted to fill this gap by using an excess-commuting approach. The approach allows us to analyse a series of jobs-housing matrices based on the location-based service big data of around fifty million individuals in the Pearl River Delta (PRD), China before and amid COVID-19. In the PRD, a zero-COVID policy was implemented, which presents a distinct and interesting context for our study. We found that after the COVID-19 outbreak: (1) residences and employment became more centrally located in downtowns, which is opposite to the suburbanization trend elsewhere; (2) in the whole PRD, the minimum and maximum commutes became smaller while the actual commute became larger, indicating the simultaneous presences of some paradoxical phenomena: a better spatial juxtaposition of jobs and housing, more compressed distribution of jobs and housing, and longer average actual commutes; (3) inter-city commutes between large cities were significantly refrained and decreased, while new inter-city commuters between smaller cities emerged; (4) it was more likely for the less-educated and female workers to see smaller minimum commutes amid COVID-19. This paper illustrates the potential of big data in the longitudinal study on jobs-housing relationships and excess commuting. It also produces new insights into such relationships in a unique context where stringent anti-COVID-19 policies have been continuously in place.

Transit fares affect not only whether people are not overburdened with their expenditure on transit services but also whether people can get reasonable benefits from transit services for w...

MoS 2 /Silicon heterostructure is experimentally demonstrated to have terahertz (THz) transmission enhancement capability. THz spectrum measurements unveil 5% expansion compared with the Si substrate under heat excitations while photon injection induced enhancement originates from THz absorption reduction. The images of THz spots can extend those spectroscopic evolution processes. These findings not only lay a fundamental understanding of properties within transition metal dichalcogenides (TMDs) at THz frequency range, but also envision a novel class of compact, tunable THz modulation and gain devices.

Three-dimensional (3D) Nickel (Ni) Skeleton is a kind of flexible, process easily, low-cost, broadband, and efficient terahertz absorbing material, which can achieve more than 98% absorption in the frequency range of 0.5-2.0 THz. Based on this discovery, the feasibility of making 3D skeletal metal to achieve THz absorption is proposed and experimentally verified. It is believed that this discovery can accelerate the practical application of THz absorbing materials.

The beginning of 2020 has seen coronavirus spreading to many countries and regions. To contain the virus, China adopted, arguably, the most stringent quarantine countermeasures in the country’s history concerning restricting people flows, limiting outdoor activities, and extending the Spring Festival break. On the one hand, thousands of doctors and nurses directly fought and are still fighting coronavirus in various medical facilities; on the other hand, millions and even billions of residents and tourists self-quarantined and are still self-quarantining themselves in their homes (or temporary homes), fighting the virus in another manner. Across cities and regions, which have the highest percentage of “fighters” at home? To answer this, we downloaded and processed the publicly available Baidu Qianxi (migration) data for 11 consecutive days in 2019 and 2020. Then we geovisualized the answer. The visual indicates that several cities in Hubei, as expected, had the highest percentage, followed by several cities in Zhejiang Province and several cities in Guangxi Zhuang Autonomous Region and Hainan Province. In terms of percentage ranking across regions, East China is no.1.

TODness, i.e., the extent to which the existing conditions of TOD sites meet agreed-upon TOD standards often requires substantial investment and efforts. Given this, it is legitimate and understandable that decision-makers expect as many positive outcomes from TODness (or TODs) as possible. Non-traditional data (NTD) has provided more opportunities for us to develop (new) indicators for TODness and expected outcomes that we have for TODness. NTD, could, for instance, be used to formulate indicators across more spatiotemporal resolutions and samples and measure new expected outcomes, e.g., smartphone users per hour on weekdays by metro station across a city. Based on case study of Shenzhen, China, this paper introduces indicators for TODness and expected outcomes (partially) based on NTD. Through (spatial) regressions, it identifies the specific TODness (both at the site and regional levels) or station (area) characteristics that have the most impacts on different expected outcomes on weekdays and weekends. The findings and results can on the one hand revalidate the known relationships between expected outcomes in the existing literature and TODness and on the other hand reveal new relationships between the two, which can serve as extra references for TOD-related plan formulation, evaluation and decision-making.

The aim of this study was to develop a scale to measure students’ STEM continuing motivation (CM). In accordance with the conceptualisation of CM by Maehr (1976. Continuing motivation: An a...

This manuscript summarizes/reviews the current trends of ride-sharing services, which can be a supplement to or replacement of conventional transit services. It argues that smartcard data can be utilized to identify low-demand transit routes, where emerging ride-sharing services such as Uber and Lyft can play a role as a supplement to, or replacement of transit services along those routes. It outlines transferrable procedures and methods that can be used to process smartcard data and to define, identify and visualize low-demand transit routes. In an empirical study, it shows that some low-demand transit routes can probably be replaced by Uber at a lower level of overall costs. But the empirical study also indicates that the replacement can be challenging in reality given issues such as unwillingness or difficulties of local transit agencies and ride-sharing service providers in sharing financial information regarding their services, latent demand for private ride-sharing services, social equity and political/legal concerns over the introduction of private ride-sharing services into the transit-service market and usage of public funding for residents/riders to use private ride-sharing services.

Excess commuting, which concerns the differences between the actual commute and the optimal (minimum) commute afforded by a given distribution of jobs and housing, i.e., urban form, has been extensively studied across disciplines. In the existing excess commuting framework, the optimal commute considers commuting efficiency but overlooks commuting equity, which is defined as the variation in commuting cost across workers before and after the optimisation. The framework also overlooks the variation in commuting frequency across workers for a period of interest, which also affects the overall commuting cost for the period. In this paper, we propose a novel excess commuting framework using a Greedy-Initialisation-based Genetic Algorithm, where the optimal commute accounts for commuting efficiency and equity and commuting-frequency variation simultaneously. We illustrate and calibrate the framework using one-month metro smart card data in Shanghai. Comparing with two other existing models, the Greedy-Initialisation-based Genetic Algorithm can generate a commuting pattern that balances commuting efficiency and commuting equity, which the existing commuting framework and corresponding algorithms cannot.

China is generally considered a safe place: among the safest for foreigners to visit. For local (long-term) residents and for Chinese criminology scholars, China as a country and its individual cit...

A city can be divided into areas that are served by transit and those that are not. In this study, the former is referred to as “transit-served areas (TSAs)”. To quantify, monitor and visualise the TSAs of the Southeast Queensland (SEQ), this study analyses half-year smartcard data between 2012 and 2013 from TransLink, the transit agency for SEQ. Four scenarios are prescribed and four corresponding metrics (the minimum, actual, random and maximum travels) are calculated, which reflect transit riders' different levels of elasticity of distance travelled (EDT) relative to the cost of travel within or between TSAs and how transit riders could possibly travel as EDT varies. The total trips generated by or attracted to TSA and the temporal and spatial variations of these metrics across days are used to monitor TSAs, especially transit trips within or between them. The results indicate that transit trips attracted to, and generated by TSA and transit trips between TSAs vary significantly over time and across space. Across the scenarios, the temporal variance tends to be larger as EDT becomes more inelastic. The above results provide useful references for decision-makers to understand better the ranges of transit demand (by TSA) across the space and time when EDT is a variable.

Availability of new open/big data (NOBD) such as smartcard and General Transit Feed Specification data has provided unprecedented opportunities for transit planners and policy-analysts to conduct analyses that are highly challenging and even infeasible where only traditional data (e.g., censuses/surveys) are in presence. In this study, we first review and summarize discrete and scattering existing studies on (a) society and justice, (b) transportation/space and justice, and (c) transit fare and justice. We consider (c) as a subset of (b) and (b) as a subset of (a). We then illustrate how NOBD can supplement traditional data in the studies of the equity and spatial implications of transit fares via an exploratory study of Brisbane, Australia. Specifically, we propose and implement methods or procedures such as “trajectory rebuilding”, “fare matching”, “segment tagging”, “desired line/stop visualisation”, “commuter identification” and “scenario analysis” to show why and how transit fares could have important equity and spatial implications. In addition to empirical findings and policy recommendations, we offer some transferable methods and procedures for visualising and concretizing the aforementioned implications.

Commuting patterns where most if not all 'trips are optimised relative to a given distribution of jobs and housing can result in personal and socio-economic benefits. Excess commuting indicators provide useful information for academics and policy analysts to evaluate how the actual commuting pattern deviates from an optimal pattern where commuting costs are minimised. While actual commuting patterns vary from day-to-day, academic researchers have yet to quantify the temporal variation in these indicators over short time periods. This may be due to the lack of available longitudinal data as input for excess commuting indicators. This study shows that new, open and/or big data (NOBD) (e.g. smartcard data) can be exploited to serve as the input for such analysis. In this regard, our study uses half a year's worth of smartcard data from Brisbane, Australia to first derive/aggregate origins and destinations by small areas of the probable commuting trips by transit on all 122 weekdays over the study period. The study quantifies the day-to-day variation in excess commuting indicators for these trips and finds that excess commuting indicators vary considerably from one day to the next. Nevertheless, daily variations occur within a relatively consistent range which can be planned for. Our research suggests that more conscious and systematic utilisation of NOBD could change how commuting flows in cities are quantified, monitored and planned. In addition, with NOBD, we can more efficiently detect daily outliers in commuting patterns.

Existing studies have yet reached consistent conclusions on accessibility benefits of buses. Most existing studies have been conducted in the context of the West, where bus patronage is generally low. In this study, we used a database of 22,586 secondhand residential properties in 358 residential estates in Xiamen, China to develop four non-spatial hedonic pricing models (one standard and three Box-Cox transformed) and two spatial econometric models to quantify the effects of bus accessibility on property prices and analyze how the introduction of spatial econometric models would influence estimates of such benefits. Our findings are as follows. (1) Access to bus stops is positively correlated with property prices. This outcome is in contrast with findings of mainstream research (or conventional wisdom). For every bus stop within 500 m, the price of a property is 0.5% higher, all else being equal. (2) Bus travel times to essential destinations significantly influence housing prices. (3) Spatial econometric models that account for spatial autocorrelation outperform traditional hedonic pricing models. A few robustness check analyses further guarantee the plausibility of this study. However, the price premiums offered by bus accessibility may be gradually decreased, even eventually discarded, because of declining attractiveness for bus travel and continuous transit service enhancement in the forthcoming years.

Abrupt socioeconomic changes have become increasingly commonplace. In face of these, both institutions and individuals must adapt. Against the backdrop of the COVID-19 pandemic, suddenness, scale, and impacts of which are unprecedented as compared to its counterparts in history, we first propose transferable measures and methods that can be used to quantify and geovisualize COVID-19 and subsequent events' impacts on metro riders' travel behaviors. Then we operationalize and implement those measures and methods with empirical data from Hong Kong, a metropolis heavily reliant on transit/metro services. We map out where those impacts were the largest and explores its correlates. We exploit the best publicly available data to assemble probable explanatory variables and to examine quantitatively whether those variables are correlated to the impacts and if so, to what degree. We find that both macro- and meso-level external/internal events following the COVID-19 outbreak significantly influenced of metro riders' behaviors. The numbers of public rental housing residents, public and medical facilities, students' school locations, residents’ occupation, and household income significantly predict the impacts. Also, the impacts differ across social groups and locales with different built-environment attributes. This means that to effectively manage those impacts, locale- and group-sensitive interventions are warranted.

Terahertz (THz) spectroscopy provides multifaceted capabilities for observing low-energy responses of macromolecules, cells and tissues, understanding THz biophysical effects, and expecting to realize the application of THz technology in biomedicine. However, its high-frequency characteristics of limited penetration depth and strong absorption of water in the body comparable to microwaves are impeding the proliferation of THz spectroscopy. Here we show that THz spectroscopy makes possible the observation of THz anisotropy phenomena for the first time in fascia and lean tissue. Through optical microscopy, we infer that the microscopic mechanism of THz anisotropy comes from the periodic stripe structure of the biological tissue. The above related experimental findings may be expected to promote the application of THz technology in biomedicine.

Crime situation forecasting has always been a challenging task for smart city security decision support system construction. Accurate crime dynamic capture can optimize the allocation efficiency of police resources to respond to various crime situations. Existing crime forecasting approaches mainly utilize some stochastic process modeling methods, some statistical learning models or some pixel-level deep learning models to capture spatio-temporal dynamic. Compared with traditional models, Graph Neural Network (GNN) obviously can better capture the spatial structural features other than Euclidean distance. In this paper, we address the crime situation forecast task with Temporal Graph Convolutional Neural Network (T-GCN) approach, a graph deep learning approach for spatio-temporal dynamics capturing. Graph Convolutional Neural Network (GCN) and Recurrent Neural Network (RNN) are combined in T-GCN model to capture the spatial and temporal dynamics respectively. In experimental studies, we evaluate T-GCN model on crime statistics dataset of San Francisco City and demonstrate effectiveness of T-GCN compared with some traditional state-of-art baseline models.