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This study aims to investigate the interrelationships between COVID-19 pandemic impact and architectural, engineering and construction (AEC) organizations. To achieve that aim, the objectives are to: identify the critical pandemic impact (CPI) of COVID-19 on AEC organizations; compare the CPI between the different organization characteristics; and analyze the interrelationships between the CPI.

A systematic literature review of 519 articles and in-depth interviews with 40 AEC practitioners were carried out, yielding 12 COVID-19 impacts. Then, data on the 12 impact’s criticality were collected through a survey among AEC practitioners. In total, 127 valid responses were received and analyzed using mean ranking analysis, analysis of variance and Spearman’s correlation. The findings were also compared with pandemic impacts from prior works.

Five CPI exist among the 12 impacts, namely, “reduced construction productivity,” “reduced foreign investment in the construction industry,” “reduced demand on construction-related works,” “disruption in the supply chain” and “reduced number of public projects.” “Reduced foreign investment in the construction industry” and “reduced demand on construction-related works” significantly impact small-medium enterprises than large enterprises. Also, “disruption in the supply chain” and “reduced construction productivity” are recurring impacts in all countries compared. Finally, moderate relationships exist between “reduced foreign investment in the construction industry” and “reduced demand on construction-related works” and “disruption in the supply chain” and “reduced construction productivity.”

The findings can be used to prioritize available resources in developing short-term responses for COVID-19. Also, action plans can be developed to mitigate the CPI from recurring.

At a time when the US federal government failed to act on climate change, California's success as a subnational climate policy leader has been widely celebrated. However, California's landmark climate law drove a wedge between two segments of the state's environmental community. On one side was a coalition of “market-oriented” environmental social movement organizations (SMOs), who allied with private corporations to advance market-friendly climate policy. On the other side was a coalition of “justice-oriented” environmental SMOs, who viewed capitalist markets as the problem and sought climate policy that would mitigate the uneven distribution of environmental harms within the state. The social movement literature is not well equipped to understand this case, in which coalitional politics helped one environmental social movement succeed in its policy objectives at the expense of another. In this chapter, we draw on legislative and regulatory texts, archival material, and interviews with relevant political actors to compare the policymaking influence of each of these coalitions, and we argue that the composition of the two coalitions is the key to understanding why one was more successful than the other. At the same time, we point out the justice-oriented coalition's growing power, as market-oriented SMOs seek to preserve their legitimacy.

This research intends to investigate the determinants that affect consumers’ purchase intention of electric vehicles (EVs) in Malaysia using an extended theory of planned behaviour (TPB).

Survey data were collected with a sample size of 306. The research used SmartPLS 4.0 structural equation modelling tool to analyse the data. Reliability and validity tests (discriminant and convergent validity) were used and subsequently assessed the measurement and structural models. Mediation analysis was conducted to identify the role of the latent constructs.

The findings indicated that a green purchase attitude plays a complete mediation role in the effect of environmental knowledge on the purchase intention of EVs. In the same notion, the effect of price perception and availability of charging facilities on the purchase intention of EVs passes completely through perceived behavioural control. However, the subjective norm was an insignificant mediator of the impact between government support and EV purchase intention.

This paper helps to examine the latent constructs that impact purchase intention using environmental knowledge, government support, price perception and the availability of charging facilities. Successful green marketing and a sustainable consumerism framework are seen as a booster to promote the usage of EVs in Malaysia.

An extended TPB model has been employed in this research to study the effects of the above-mentioned constructs. The results show that most of the extended constructs are significant in explaining the purchase intention. The empirical results address the gap in the consumer green attitude and provide insight into this area of study.

The Equal Pay Act 1970 (which came into operation on 29 December 1975) provides for an “equality clause” to be written into all contracts of employment. S.1(2) (a) of the 1970 Act (which has been amended by the Sex Discrimination Act 1975) provides:

THE conclusion of another volume affords us an opportunity of surveying the past year as regards library progress and prospects. Briefly, it may be summed up as a year of building and Carnegie gifts. A considerable amount of activity has been displayed all over the country in the erection and opening of new buildings provided by the munificence of Mr. Carnegie, and the time seems to have arrived for gathering up all this planning and organization work and recording it in a special handbook of English and American Carnegie libraries. Such a record would prove of immense value to library committees and architects, and would form no unworthy memento of one of the most extraordinary developments of educational work the world has ever witnessed.

This research investigates the effects of consumers' online information searching on their dining satisfaction in upscale restaurants during the pandemic. Customers frequently rely on online sources to gather information about upscale restaurants prior to their visits.

Data from 307 diners across the top ten popular upscale restaurants in Hong Kong were analysed by using SEM to explore the links between customers' needs, information search, restaurant attributes and customer satisfaction.

This study uncovers customers' online search behaviours and identifies restaurant attributes that are associated with customer satisfaction, which were not typically emphasised before the COVID-19 pandemic. Driven by their social and psychological needs, customers devoted more time to reading written comments by other consumers compared to visual images or self-descriptions from restaurants. Only service attribute significantly influenced customer satisfaction, while food and price attributes were not significant.

The findings of this study provide valuable insights for researchers and practitioners, shedding light on the altered needs and preferences of consumers following the unprecedented health crisis.

This study contributes to the development of expectancy disconfirmation theory and needs theory through the investigation of consumers' online information searching behaviours and dining satisfaction in upscale restaurants during the pandemic. By identifying the most important attributes influencing customer satisfaction, this research can aid upscale restaurants in developing effective marketing strategies and enhancing customer experiences.

The purpose of this paper is to make the case for bringing compassion to students in educational settings, preschool through graduate school (PK-20).

First, the author defines what is meant by “compassion” and differentiates it from the related constructs. Next, the author discusses the importance of bringing compassion into education, thinking specifically about preschool, K-12 (elementary and middle school/junior high/high school), college students, and graduate students (e.g. law, medical, nurses, counselors and therapists-in-training). The author then reviews the scant empirical literature on compassion in education and makes recommendations for future research. In the final section, the author makes specific and practical recommendations for the classroom (e.g. how to teach and evaluate compassion in PK-20).

While there is a fair amount of research on compassion with college students, and specifically regarding compassion for oneself, as the author reviews in this paper, the field is wide open in terms of empirical research with other students and examining other forms of compassion.

This is not a formal review or meta-analysis.

This paper will be a useful resource for teachers and those interested in PK-20 education.

This paper highlights the problems and opportunities for bringing compassion into education settings.

To date, no review of compassion in PK-20 exists.

The purpose of this paper is to characterize distracted driving by quantifying the response time and response intensity to an emergency stop using the driver’s physiological states.

Field tests with 17 participants were conducted in the connected and automated vehicle test field. All participants were required to prioritize their primary driving tasks while a secondary nondriving task was asked to be executed. Demographic data, vehicle trajectory data and various physiological data were recorded through a biosignalsplux signal data acquisition toolkit, such as electrocardiograph for heart rate, electromyography for muscle strength, electrodermal activity for skin conductance and force-sensing resistor for braking pressure.

This study quantified the psychophysiological responses of the driver who returns to the primary driving task from the secondary nondriving task when an emergency occurs. The results provided a prototype analysis of the time required for making a decision in the context of advanced driver assistance systems or for rebuilding the situational awareness in future automated vehicles when a driver’s take-over maneuver is needed.

The hypothesis is that the secondary task will result in a higher mental workload and a prolonged reaction time. Therefore, the driver states in distracted driving are significantly different than in regular driving, the physiological signal improves measuring the brake response time and distraction levels and brake intensity can be expressed as functions of driver demographics. To the best of the authors’ knowledge, this is the first study using psychophysiological measures to quantify a driver’s response to an emergency stop during distracted driving.

This paper aims to review in-memory computing (IMC) for machine learning (ML) applications from history, architectures and options aspects. In this review, the authors investigate different architectural aspects and collect and provide our comparative evaluations.

Collecting over 40 IMC papers related to hardware design and optimization techniques of recent years, then classify them into three optimization option categories: optimization through graphic processing unit (GPU), optimization through reduced precision and optimization through hardware accelerator. Then, the authors brief those techniques in aspects such as what kind of data set it applied, how it is designed and what is the contribution of this design.

ML algorithms are potent tools accommodated on IMC architecture. Although general-purpose hardware (central processing units and GPUs) can supply explicit solutions, their energy efficiencies have limitations because of their excessive flexibility support. On the other hand, hardware accelerators (field programmable gate arrays and application-specific integrated circuits) win on the energy efficiency aspect, but individual accelerator often adapts exclusively to ax single ML approach (family). From a long hardware evolution perspective, hardware/software collaboration heterogeneity design from hybrid platforms is an option for the researcher.

IMC’s optimization enables high-speed processing, increases performance and analyzes massive volumes of data in real-time. This work reviews IMC and its evolution. Then, the authors categorize three optimization paths for the IMC architecture to improve performance metrics.