A Review of Research on Urban Playability from a Social Justice Perspective

Playability is an attribute that refers to the ability to stimulate individual responses or collective action in an immersive activity in an exploratory way. Playability is an important component of the enjoyment and well-being of urban dwellers, has the potential to stimulate urban vitality and is an important expression of the inclusiveness and equity of urban space. The pursuit of economic development and efficiency-oriented urban construction has led to the domination of urban space by overcrowded traffic, economy-oriented commerce and densely populated housing. Moreover, the existence of playable space has become a scarce resource and is seen as a site for the materialisation of social rights. As the haze of the COVID-19 pandemic fades and cities are again exposed to wider and more participatory use, determining how to adapt urban spaces to the playability needs of users of different ages, cultural backgrounds and social classes, and provide them with appropriate site use and experience, is becoming a hot issue of concern for building equitable and high-quality urban spaces. The study of the playability of urban spaces is highly complex, and the related research on social justice is cryptic. In order to better investigate the social equity aspects of urban playability, this paper integrates scientometric and manual methods to review the relevant research. This paper takes 2664 related papers from the Web of Science (WOS) core dataset from 1998 to 2022 as the research object and employs CiteSpace to organise the existing research results of playful urban spaces. Quantitative analysis is used to clarify the theoretical foundations, developments and research hotspots of urban spatial playability, while the manual collation and generalisation of the studies uncover the hidden issues of social justice research. Based on the proposed research method, we summarize the key three research stages related to urban spatial playability and social equity. We also discuss the development of urban spatial playability in the perspective of social justice from three aspects: micro, meso and macro. The results can help readers better understand the current status and development process of research on playful urban space. In particular, we clarify the issues related to social justice under the theme of the playability of urban spaces and provide directions for future research on building playful cities and promoting the development of urban socio-spatial equity.

Simulation Study on Airflow Organization and Environment in Reconstructed Fangcang Shelter Hospital Based on CFD

With frequent outbreaks of COVID-19, the rapid and effective construction of large-space buildings into Fangcang shelter hospitals has gradually become one of the effective means to control the epidemic. Reasonable design of the ventilation system of the Fangcang shelter hospital can optimize the indoor airflow organization, so that the internal environment can meet the comfort of patients and at the same time can effectively discharge pollutants, which is particularly important for the establishment of the Fangcang shelter hospital. In this paper, through the reconstruction of a large-space gymnasium, CFD software is used to simulate the living environment and pollutant emission efficiency of the reconstructed Fangcang shelter hospital in summer under different air supply temperatures, air supply heights and exhaust air volume parameters. The results show that when the air supply parameters are set to an air supply height of 4.5 m, an air supply temperature of 18 °C, and an exhaust air volume of a single bed of 150 m3/h, the thermal comfort can reach level I, and the ventilation efficiency for pollutants can reach 69.6%. In addition, the ventilation efficiency is 70.1% and 70.3% when the exhaust air volume of a single bed is continuously increased to 200 and 250 m3/h, which can no longer effectively improve the pollutant emission and will cause an uncomfortable blowing feeling to patients. © 2023 by the authors.

How Governor Directives Changed Health Workforce Flexibility in Response to the COVID-19 Pandemic.

OBJECTIVES: In times of heightened population health needs, the health workforce must respond quickly and efficiently, especially at the state level. We examined state governors' executive orders related to 2 key health workforce flexibility issues, scope of practice (SOP) and licensing, in response to the COVID-19 pandemic. METHODS: We conducted an in-depth document review of state governors' executive orders introduced in 2020 in all 50 states and the District of Columbia. We conducted a thematic content analysis of the executive order language using an inductive process and then categorized executive orders by profession (advanced practice registered nurses, physician assistants, and pharmacists) and degree of flexibility granted; for licensing, we indicated yes or no for easing or waiving cross-state regulatory barriers. RESULTS: We identified executive orders in 36 states containing explicit directives addressing SOP or out-of-state licensing, with those in 20 states easing regulatory barriers pertaining to both workforce issues. Seventeen states issued executive orders expanding SOP for advanced practice nurses and physician assistants, most commonly by completely waiving physician practice agreements, while those in 9 states expanded pharmacist SOP. Executive orders in 31 states and the District of Columbia eased or waived out-of-state licensing regulatory barriers, usually for all health care professionals. CONCLUSION: Governor directives issued through executive orders played an important role in expanding health workforce flexibility in the first year of the pandemic, especially in states with restrictive practice regulations prior to COVID-19. Future research should examine what effects these temporary flexibilities may have had on patient and practice outcomes or on permanent efforts to relax practice restrictions for health care professionals.

When Adolescents Disagree with Their Vaccine-Hesitant Parents about COVID-19 Vaccination.

AbstractAs we journey into the fourth year of the COVID-19 pandemic, a majority of Americans express relief at a "return to normal," experience pandemic fatigue, or embrace the idea of living with COVID-19 in much the same way we live with the seasonal flu. But transition to a new phase of life with SARS-CoV-2 does not diminish the importance of vaccination. The US Centers for Disease Control and the Food and Drug Administration recently recommended another round of booster dose for persons age 5 and up, or an initial series for those not previously vaccinated, with an updated bivalent formula that protects against both the original virus strain and Omicron subvariants that are now the dominant source of infection. By most accounts most of the population has been or will become infected with SARS-CoV-2. Suboptimal uptake of the COVID-19 vaccines among the approximately 25 million adolescents in the United States is a significant obstacle to population coverage, public health, and the health and well-being of adolescents. A major cause of low adolescent uptake is parental vaccine hesitancy. This article discusses parental vaccine hesitancy and argues that permitting independent adolescent consent to COVID-19 vaccination should be an ethical and policy priority as we continue to confront the threat of Omicron and other variants of the coronavirus. We discuss the central role of the pediatric healthcare team in caring for adolescent patients who disagree with their parents about vaccination.

Changes in public travel willingness in the post-COVID-19 era: Evidence from social network data

Amid the impact of COVID-19, the public's willingness to travel has changed, which has had a fundamental impact on the ridership of urban public transport. Usually, travel willingness is mainly analyzed by questionnaire survey, but it needs to reflect the accurate psychological perception of the public entirely. Based on Weibo text data, this paper used natural language processing technology to quantify the public's willingness to travel in the post-COVID-19 era. First, web crawler technology was used to collect microblog text data, which will discuss COVID-19 and travel at the same time. Then, based on the Naive Bayes classification algorithm, travel sentiment analysis was carried out on the data, and the relationship between public travel willingness and urban public transport ridership was analyzed by Spearman correlation analysis. Finally, the LDA topic model was used to conduct content topic research on microblog text data during and after COVID-19. The results showed that the mean values of compelling travel emotion were-0.8197 and-0.0640 during and after COVID-19, respectively. The willingness of the public to travel directly affects the ridership of urban public transport. Compared with the COVID-19 period, the public's fear of travel infection in the post-COVID-19 era has significantly improved, but it still exists. The public pays more attention to the level of COVID-19 prevention and control and the length of travel time on public transport.

Intelligent medicine and beyond

With the developments of medical artificial intelligence (AI), meta-data analysis, intelligence-aided drug design and discovery, surgical robots and image-navigated precision treatments, intelligent medicine (IM) as a new era evolved from ancient medicine and biomedical medicine, has become an emerging topic and important criteria for clinical applications. It is fully characterized by fundamental research-driven, new-generation technique-directed as well as state-of-the-art paradigms for advanced disease diagnosis and therapy leading to an even broader future of modern medicine. As a fundamental subject and also a practice-oriented field, intelligent medicine is highly trans-disciplinary and cross-developed, which has emerged the knowledge of modern medicine, basic sciences and engineering. Basically, intelligent medicine has three domains of intelligent biomaterials, intelligent devices and intelligent techniques. Intelligent biomaterials derive from traditional biomedical materials, and currently are endowed with multiple functionalities for medical uses. For example, micro-/nanorobots, smart responsive biomaterials and digital drugs are representative intelligent biomaterials which have been already commercialized and applied to clinical uses. Intelligent devices, such as surgical robots, rehabilitation robots and medical powered exoskeleton, are an important majority in the family of intelligent medicine. Intelligent biomaterials and intelligent devices are more and more closely integrated with each other especially on the occasions of intelligence acquisition, remote transmission, AI-aided analysis and management. In comparison, intelligent techniques are internalized in the former two domains and are playing a critical role in the development of intelligent medicine. Representative intelligent techniques of telemedicine, image-navigated surgery, virtual/augmented reality and AI-assisted image analysis for early-stage disease assessments have been employed in nowadays clinical operations which to a large extent relieved medical labors. In the past decades, China has been in the leading groups compared to international colleagues in the arena of intelligent medicine, and a series of eminent research has been clinically translated for practical uses in China. For instance, the first 5G-aided remote surgery has been realized in Fujian Province in January 2019, which for the first time validated their applicability for human uses. The surgical robots have found China as the most vigorous market, and more than 10 famous Chinese companies are developing versatile surgical robots for both Chinese people and people all over the world. China also applied AI techniques to new drug developments especially in early 2020 when COVID-19 epidemic roared, and several active molecules and drug motifs have been discovered for early-stage COVID-19 screening and treatments. Based on the significance of intelligent medicine and its rapid developments in both basic research and industrials, this review summarized the comprehensive viewpoints of the Y6 Xiangshan Science Conferences titled with Fundamental Principles and Key Technologies of Intelligent Medicine, and gave an in-depth discussion on main perspectives of future developments of the integration of biomaterial and devices, the integration of bioinformatics and medical hardware, and the synergy of biotechnology and intelligence information. It is expected that this featuring article will further promote intelligent medicine to an even broader community not only for scientists but also for industrials, and in the long run embrace a perspective future for its blooming and rich contributions in China in the coming 5 years.

Scientific debrief: cirrhosis

Globally, hepatitis C (26%), alcohol (24%), and hepatitis B (23%) contribute almost equally to the global burden of cirrhosis. The contribution from nonalcoholic fatty liver disease (8%) is small but increasing. Patients with acutely decompensated cirrhosis have a dismal prognosis and frequently progress to acuteon-chronic liver failure, which is characterised by hepatic and extrahepatic organ failure, Cardiovascular alterations including portal hypertension trigger the formation of portocaval shunts and varices. Systemic under filling and arterial hypotension is compensated by vasoconstriction but might decline into a state of aggravated portal hypertension and cirrhotic cardiomyopathy, leading to a hyperdynamic state, microvascular dysfunction and reduced organ perfusion culminating in decompensation. The immune system is dysfunctional showing a contrary co-existence of immune paralysis and immune overstimulation leading to secondary infections and inflammatory response syndrome aggravating cardiovascular alterations but also initiating tissue injury and metabolic alteration. This transition from compensated to decompensated cirrhosis is characterised by the occurrence of ascites, variceal bleeding and/or hepatic encephalopathy or organ failures (in the case of ACLF. Precipitating events for ACLF vary between Western countries (bacterial infection, alcohol intake) and Eastern countries (flare of HBV, superimposed HAV or HEV). In the majority of patients, systemic inflammation is a major driver of progression from compensated to decompensated cirrhosis. Once the first episode of AD develops, systemic inflammation follows a chronic course, with transient periods of aggravation due to proinflammatory precipitants or bursts of bacterial translocation resulting in repeated episodes of AD. The multistate model describing the clinical outcomes of decompensated cirrhosis has been well validated. State 3 is defined by the occurrence of variceal bleeding alone, state 4 by any single non-bleeding event, state 5 by any 2 or more events and the late decompensate state by any event with organ failures either with or without ACLF. 5-year mortality across states from 3 to 5 is in the order of, respectively: 20%, 30%, 88%. With late decompensation mortality ranges between 60 and 80% at 1 year. Cirrhosis is increasingly common and morbid. Optimal utilisation of therapeutic strategies to prevent and control the complications of cirrhosis are central to improving clinical and patient-reported outcomes. Aetiology-focused therapies that can prevent cirrhosis and its complications. These include anti-viral therapies, psychopharmacological therapy for alcohol-use disorder, management of hepatic encephalopathy (HE), ascites, hepatorenal syndrome, non-pain symptoms of cirrhosis including pruritis, muscle cramps, sexual dysfunction and fatigue, and reduce the risk of hepatocellular carcinoma. New disease-modifying agents are expected to be identified in the next few years by systematic drug repurposing and the development of novel molecules currently undergoing pre-clinical or early clinical testing. COVID-19 continues to pose a significant healthcare challenge throughout the world. Comorbidities including diabetes and hypertension are associated with a significantly higher mortality risk. Cirrhosis is associated with an increased risk of all-cause mortality in COVID-19 infection compared to non-cirrhotic patients. Patients with cirrhosis should be considered for targeted public health interventions to prevent COVID-19 infection, such as shielding and prioritisation of vaccination.

Current situation and perspective of COVID-19 mRNA vaccine

In December 2019, Wuhan, China, found SARS-CoV-2. It causes covid-19, a worldwide respiratory illness. Its global pandemic broke out unexpectedly, and the number of infections and deaths continued to rise dramatically, causing the collapse of medical systems and disease control organizations in many countries at the start of the outbreak. Vaccine research and development must be prioritized in order to control and reduce virus spread as soon as possible. The mRNA vaccine stands out among traditional vaccines due to its rapid research and development, ability to stimulate human dual immune responses and non-infectivity. Both humoral and cellular immunity can be stimulated by mRNA vaccines, which means that the produced T cells can help eliminate antigens in time, so their number does not increase in order to protect the original cells, and they can also create long-lived plasma cells and memory B cells to continue playing an immunological role for years. mRNA vaccines may not need repeated injections, unlike inactivated vaccinations, which may enhance efficiency. the first mRNA vaccinations that were made accessible to the general population when the US FDA approved its emergency use in December 2020. The generation of mRNA for the mRNA vaccination uses cell-free expression techniques and in vitro transcription-based systems. LNPs system, a nanoscale vesicle that can enclose mRNA in their cavity and imitates the lipid structure of the cell membrane, is the most often utilized delivery system in mRNA vaccines. The most common mRNA vaccine technique involves injecting a genetic component that tells the body to make a protein fragment of a specific pathogen, which the immune system recognizes and keeps mounting a robust response if it is subsequently exposed to that pathogen. © 2023 SPIE.

AIM in Alternative Medicine

Alternative medicine (AM) is one of the medical fields that use more natural and traditional therapies for disease diagnosis and treatment, in which traditional Chinese medicine (TCM) now has been recognized as one of the main approaches of AM. As a clinical and evidencedriven discipline with long histories, AM is also heavily relied on in the utilization of big healthcare and therapeutic data for improving the capability of diagnosis and treatment. In particular, artificial intelligence (AI) has been widely adopted in AM to deliver more practical and feasible intelligent solutions for clinical operations since 1970s. This chapter summarizes the main approaches, related typical applications, and future directions of AI in AM to give related researchers a brief useful reference. We find that although AM has not been widely used in clinical practice internationally, the AI studies showed abundant experiences and technique trials in expert system, machine learning, data mining, knowledge graph, and deep learning. In addition, various types of data, such as bibliographic literatures, electronic medical records, and images were used in the related AI tasks and studies. Furthermore, during this COVID-19 pandemic era, we have witnessed the clinical effectiveness of TCM for COVID-19 treatment, which mostly was detected by real-world data mining applications. This indicates the potential opportunity of the booming of AI research and applications in various aspects (e.g., effective clinical therapy discovery and network pharmacology of AM drugs) in AM fields. © Springer Nature Switzerland AG 2022.

COVID-19 pandemic and hotel property performance

Purpose: The purpose of this study is to test the local impact of COVID-19 pandemic on hotel performance at the individual property level, and further examine the roles of hotel attributes and business mix in potentially moderating or intensifying the impact of a crisis. Design/methodology/approach: Using a sample of 5,090 hotel properties in Texas, USA from January 2020 to December 2021, this study estimates a monthly hotel performance model to evaluate how the pandemic affected hotels' operational performance based on revenue per available room. Findings: Results show that a 10% increase in the monthly number of confirmed COVID-19 cases led to a 0.522% decrease in hotel performance. Also, a series of moderators were identified within the pandemic–performance relationship: the negative impact of the pandemic was more severe among higher-end hotels and newer hotels;urbanization and localization diseconomies prevailed during the pandemic;and there was a smaller negative effect of COVID-19 on high rated hotels in the category of economy hotels. Originality/value: The moderators highlighted in this paper shed light on the heterogeneity of COVID-19's effects on hotel operations. Findings enrich the hospitality literature by considering business resilience in relation to the pandemic. © 2023, Emerald Publishing Limited.

Clinical characteristics of 71 death cases of COVID‐19

Objective: To provide a basis for the early identification and treatment of severe and critical coronavirus disease 2019 (COVID - 19) by analyzing the clinical characteristics of the death cases. Methods: We retrospectively analyzed the clinical characteristics of 71 COVID - 19 cases which died during hospitalization. The clinical data included general data, underlying disease, clinical manifestation, biochemical laboratory examination, imaging examination, complications, and treatment, then the influencing factors of in - hospital survival were analyzed. Results: Most of the 71 patients were ≥60 years old (78. 9%) and had underlying diseases (74. 6%), in which hypertension ranked first, and fever was the most common first symptom. Biochemical laboratory tests showed that D-Dimer and C-reactive protein maintained at high levels during hospitalization, and lymphocyte count declined. Leukocyte/neutrophil counts, neutrophil to lymphocyte ratio, procalcitonin, creatine kinase, and lactate dehydrogenase increased. The main imaging features of the dead cases were the multifocal ground glass changes and consolidation of the lungs. The most common complications were acute respiratory distress syndrome (89. 9%), shock (34. 3%), and acute myocardial injury (30. 4%). 90% of the patients received auxiliary ventilation, and the decrease of blood oxygen saturation and the increase of procalcitonin may be the risk factors for shorter in-hospital survival. Conclusion: Severe and critical COVID-19 patients show different characteristics in clinical manifestations, biochemical laboratory examination, imaging examination, complications, and treatment reactions, which need early identification and treatment, and bewaring of acute respiratory distress syndrome and multiple organs failure. © 2022 Editorial Board of Medical Journal of Wuhan University. All rights reserved.

Intelligent medicine and beyond

With the developments of medical artificial intelligence (AI), meta-data analysis, intelligence-aided drug design and discovery, surgical robots and image-navigated precision treatments, intelligent medicine (IM) as a new era evolved from ancient medicine and biomedical medicine, has become an emerging topic and important criteria for clinical applications. It is fully characterized by fundamental research-driven, new-generation technique-directed as well as state-of-the-art paradigms for advanced disease diagnosis and therapy leading to an even broader future of modern medicine. As a fundamental subject and also a practice-oriented field, intelligent medicine is highly trans-disciplinary and cross-developed, which has emerged the knowledge of modern medicine, basic sciences and engineering. Basically, intelligent medicine has three domains of intelligent biomaterials, intelligent devices and intelligent techniques. Intelligent biomaterials derive from traditional biomedical materials, and currently are endowed with multiple functionalities for medical uses. For example, micro-/nanorobots, smart responsive biomaterials and digital drugs are representative intelligent biomaterials which have been already commercialized and applied to clinical uses. Intelligent devices, such as surgical robots, rehabilitation robots and medical powered exoskeleton, are an important majority in the family of intelligent medicine. Intelligent biomaterials and intelligent devices are more and more closely integrated with each other especially on the occasions of intelligence acquisition, remote transmission, AI-aided analysis and management. In comparison, intelligent techniques are internalized in the former two domains and are playing a critical role in the development of intelligent medicine. Representative intelligent techniques of telemedicine, image-navigated surgery, virtual/augmented reality and AI-assisted image analysis for early-stage disease assessments have been employed in nowadays clinical operations which to a large extent relieved medical labors. In the past decades, China has been in the leading groups compared to international colleagues in the arena of intelligent medicine, and a series of eminent research has been clinically translated for practical uses in China. For instance, the first 5G-aided remote surgery has been realized in Fujian Province in January 2019, which for the first time validated their applicability for human uses. The surgical robots have found China as the most vigorous market, and more than 10 famous Chinese companies are developing versatile surgical robots for both Chinese people and people all over the world. China also applied AI techniques to new drug developments especially in early 2020 when COVID-19 epidemic roared, and several active molecules and drug motifs have been discovered for early-stage COVID-19 screening and treatments. Based on the significance of intelligent medicine and its rapid developments in both basic research and industrials, this review summarized the comprehensive viewpoints of the Y6 Xiangshan Science Conferences titled with Fundamental Principles and Key Technologies of Intelligent Medicine, and gave an in-depth discussion on main perspectives of future developments of the integration of biomaterial and devices, the integration of bioinformatics and medical hardware, and the synergy of biotechnology and intelligence information. It is expected that this featuring article will further promote intelligent medicine to an even broader community not only for scientists but also for industrials, and in the long run embrace a perspective future for its blooming and rich contributions in China in the coming 5 years. © 2023 Chinese Academy of Sciences. All rights reserved.

Value of Biofire Filmarray pneumonia panel in evaluating secondary infection in critically ill patients with Coronavirus disease 2019.

Objective To explore the application value of Biofire Filmarry pneumonia panel (PN) in detection of secondary and concomitant pathogen among critically ill patients with coronavirus disease 2019(COVID-19). Methods We consecutively included and analyzed the clinical data of critically ill patients with COVID-19 transferred to the ICU from February to April 2020 in the Sino-French Campus of Wuhan Tongji Hospital. Samples of Bronchoalveolar lavage fluid obtained by bedside bronchoscopy were sent for Biofire Filmarray PN and standard culture concomitantly. We compared the results of two methods and evaluated their concordance. Results In total, 21 critically ill patients with COVID-19 were included and 54 samples were tested, including 33 (61.1%) Biofire Filmarray PN tests (21 patients) and 21 (38.9%) standard cultures (14 patients), in which 19 pairs (38 samples) underwent both tests simultaneously. In Biofire Filmarray PN group, the turnaround time was about 1 hour. There were 74 positive results in 32 samples (97.0%) from 20 patients, including 29 cases(39.2%) of Acinetobacter baumannii complex, 21 cases (28.4%) of Pseudomonas aeruginosa, 16 cases (21.6%)of Klebsiella pneumoniae, 5 cases (6.8%) of Escherichia coli, 1 case (1.4%)each of Enterobacter cloacae, Haemophilus influenzae, and respiratory syncytial virus. In the standard culture group, the turnaround time was about 3 days. 19 positive results returned in 16 (76.2%) samples from 11 patients, including 8 cases (42.1%) of Pseudomonas aeruginosa, 6 cases (31.6%) of Acinetobacter baumannii, 4 cases (21.1%) of Stenotrophomonas malt and 1 case (5.3%) of Myxobacterium. Among the 19 pairs of "back-to-back" specimens, 15 pairs were concordant, and the agreement ratio was 78.9%. Conclusions Acinetobacter baumannii and Pseudomonas aeruginosa may be the common pathogens of secondary or concomitant infection in critically ill patients with COVID-19. Biofire Filmarray PN is a rapid diagnostic test and has application value in such patients;its sensitivity and accuracy require further investigation with larger sample sizes.Copyright © 2021, Peking Union Medical College Hospital. All rights reserved.

Nanomaterials and Biosensing Technology for the SARS-CoV-2 Detection

The outbreak of corona virus disease 2019 (COVID-19) has aroused great attention around the world. SARS-CoV-2 possesses characteristics of faster transmission, immune escape, and occult transmission by many mutation, which caused still grim situation of prevention and control. Early detection and isolation of patients are still the most effective measures at present. So, there is an urgent need for new rapid and highly sensitive testing tools to quickly identify infected patients as soon as possible. This review briefly introduces general characteristics of SARS-CoV-2, and provides recentl overview and analysis based on different detection methods for nucleic acids, antibodies, antigens as detection target. Novel nano-biosensors for SARS-CoV-2 detection are analyzed based on optics, electricity, magnetism, and visualization. In view of the advantages of nanotechnology in improving detection sensitivity, specificity and accuracy, the research progress of new nano-biosensors is introduced in detail, including SERS-based biosensors, electrochemical biosensors, magnetic nano-biosensors and colorimetric biosensors. Functions and challenges of nano-materials in construction of new nano-biosensors are discussed, which provides ideas for the development of various coronavirus biosensing technologies for nanomaterial researchers.

China-Europe freight transportation under the first wave of COVID-19 pandemic and government restriction measures

International freight transportation experienced significant disruptions during the COVID-19 pandemic. The impact of the pandemic and related government restriction measures on international freight transportation is worth analysing for the development of transportation policies and practices in the post-pandemic period, but has received limited attention. To fill the gap, this study applies structural equation models to analyze the impact of the COVID-19 pandemic on the international transportation market and the relationships among the pandemic, government restriction measures, and international transportation market. The impact is also differentiated for different modes of transportation. Results confirm that both demand and supply of interna-tional transportation services have been negatively affected by the first wave of the pandemic, with sea trans-portation being more affected by the reduction of demand and air transportation more by the supply volatility. The government restriction measures are found to play a mediation role, in the way that the impact of the pandemic on the supply of transportation service is suppressed through the government restriction measures. Our findings provide important guidance for transportation industry players and governments in their decision-making process facing with global market shocks such as a pandemic.

FedUSC: Collaborative Unsupervised Representation Learning from Decentralized Data for Internet of Things

Federated Learning (FL) lately has shown much promise in improving the shared model and preserving data privacy. However, these existing methods are only of limited utility in the Internet of Things (IoT) scenarios, as they either heavily depend on high-quality labeled data or only perform well under idealized conditions, which typically cannot be found in practical applications. In this paper, we propose a novel federated unsupervised learning method for image classification without the use of any ground truth annotations. In IoT scenarios, a big challenge is that decentralized data among multiple clients is normally non-IID, leading to performance degradation. To address this issue, we further propose a dynamic update mechanism that can decide how to update the local model based on weights divergence. Extensive experiments show that our method outperforms all baseline methods by large margins, including +6.67% on CIFAR-10, +5.15% on STL-10, and +8.44% on SVHN in terms of classification accuracy. In particular, we obtain promising results on Mini-ImageNet and COVID-19 datasets and outperform several federated unsupervised learning methods under non-IID settings. IEEE

Online Education Innovation Using the CEPHEI E-learning Platform in the New Pandemic Situation

The Covid-19 pandemic has posed major challenges to the education of innovation for students at university, and to the links between industry and university. This chapter describes an innovation-based blended course, the education practices of students staying in different countries, and links the model of academia–industry in the new pandemic situation in China. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Do guests care more about hotel cleanliness during COVID-19? Understanding factors associated with cleanliness importance of hotel guests

Purpose: Growing health concerns amid the COVID-19 pandemic have led guests to focus on various aspects of hotel cleanliness. This study aims to investigate whether customers' perceived importance of hotel cleanliness during their stay depends on local pandemic severity and moderators of the pandemic–cleanliness relationship. Design/methodology/approach: Based on TripAdvisor data from 26,519 reviews in 2020 for 2,024 hotels across the USA, this study evaluated the importance of hotel cleanliness using the estimated coefficient of the cleanliness score in a regression of overall hotel rating scores. Findings: Results of a multilevel ordered logit model confirmed that a more difficult local pandemic situation rendered cleanliness more important during hotel stays. Additionally, the effect of the pandemic was more pronounced among specific groups: men and travelers with more expertise, and guests staying in hotels without COVID-19 protocols for linen cleaning, with a lower average rating, with a larger size and in a more urbanized location. Originality/value: This study represents a pioneering effort to assess how pandemics shape people's (perceived) importance of cleanliness during hotel stays based on revealed data. Despite potential managerial relevance, a number of the moderating variables included in this study, such as traveler expertise and hotel location, have never been studied within the context of cleanliness perceptions during a pandemic. © 2023, Emerald Publishing Limited.

Emergency response scheme selection with T-spherical hesitant probabilistic fuzzy TODIM-TPZSG approach

This paper aims to investigate an innovative framework to handle emergency response scheme selection (ERSS) issues by integrating TODIM and TPZSG (two-person zero-sum game) methods under novel T-spherical hesitant probabilistic fuzzy set (T-SHPFS) environments. First, T-SHPFS is defined as an extension of the existing tools, which can depict the complex assessment information including several possible values of the various membership functions' degrees and the associated statistical uncertainty information. Concomitantly, T-SHPFS's normalization method, comparison laws, operation rules, cross-entropy measure and Hausdorff distance are explored. Then, an objective attribute weight determining model is constructed, considering the credibility of T-SHPF evaluations and the divergence degrees between attribute assessments simultaneously. Next, an integrated TODIM-TPZSG decision-making approach is developed to select the most desirable emergency response scheme. Finally, an illustrative example concerning the selection of the best medical waste disposal method during the COVID-19 epidemic is conducted to verify the effectiveness of the proposed TODIM-TPZSG method. Sensitivity analysis and comparisons between the TODIM-TPZSG and other representative methods are also provided to demonstrate the superiorities of the proposed method. The results reveal that the developed T-SHPFSs give DMs more assessment freedom;the proposed TODIM-TPZSG approach considers the decision makers' psychological behaviors;the ranking results of the proposed method can reflect the specific divergence degrees among the alternatives;and the needed computation burden and computational complexity are low and less affected by the number of alternatives and criteria than most current ERSS methods. © 2023