Privacy-Preserving Fast Three-Factor Authentication and Key Agreement for IoT-Based E-Health Systems

Electronic healthcare (e-health) systems have received renewed interest, particularly in the current COVID-19 pandemic (e.g., lockdowns and changes in hospital policies due to the pandemic). However, ensuring security of both data-at-rest and data-in-transit remains challenging to achieve, particularly since data is collected and sent from less insecure devices (e.g., patients' wearable or home devices). While there have been a number of authentication schemes, such as those based on three-factor authentication, to provide authentication and privacy protection, a number of limitations associated with these schemes remain (e.g., (in)security or computationally expensive). In this study, we present a privacy-preserving three-factor authenticated key agreement scheme that is sufficiently lightweight for resource-constrained e-health systems. The proposed scheme enables both mutual authentication and session key negotiation in addition to privacy protection, with minimal computational cost. The security of the proposed scheme is demonstrated in the Real-or-Random model. Experiments using Raspberry Pi show that the proposed scheme achieves reduced computational cost (of up to 89.9% in comparison to three other related schemes).

Shifting Trust: Examining How Trust and Distrust Emerge, Transform, and Collapse in COVID-19 Information Seeking

During crises like COVID-19, individuals are inundated with conflicting and time-sensitive information that drives a need for rapid assessment of the trustworthiness and reliability of information sources and platforms. This parallels evolutions in information infrastructures, ranging from social media to government data platforms. Distinct from current literature, which presumes a static relationship between the presence or absence of trust and people's behaviors, our mixed-methods research focuses on situated trust, or trust that is shaped by people's information-seeking and assessment practices through emerging information platforms (e.g., social media, crowdsourced systems, COVID data platforms). Our findings characterize the shifts in trustee (what/who people trust) from information on social media to the social media platform(s), how distrust manifests skepticism in issues of data discrepancy, the insufficient presentation of uncertainty, and how this trust and distrust shift over time. We highlight the deep challenges in existing information infrastructures that influence trust and distrust formation.

Social Media Use and COVID-19 Vaccination Intent: An Exploratory Study on the Mediating Role of Information Exposure

We stumble upon new and repeating information daily. As information comes from many sources, social media continues to play a predominant role in disseminating information, ultimately impacting individuals' perceptions and behaviors. A prime example of this impact was observed during the COVID-19 pandemic, in which social media use was influencing willingness to receive the COVID-19 vaccine. While studies on this relationship between social media use and vaccination intent have been widely investigated, less is known about the mechanisms that link these two variables, specifically the types of information seen on social media platforms and the effects of these different types of information. In this exploratory study, we demonstrate the mediator role of information exposure (to include both types of information and frequency) between social media use and vaccination intent. Our results show that different types of information mediate this relationship differently and demonstrate how these relationships were further moderated by the income level of the participant. We conclude with the implications of these findings and how our findings can inform the direction of future research within the field of human-computer interaction.

Investigating Older Adults' Atitudes towards Crisis Informatics Tools: Opportunities for Enhancing Community Resilience during Disasters

The world population is projected to rapidly age over the next 30 years. Given the increasing digital technology adoption amongst older adults, researchers have investigated how technology can support aging populations. However, little work has examined how technology can support older adults during crises, despite increasingly common natural disasters, public health emergencies, and other crisis scenarios in which older adults are especially vulnerable. Addressing this gap, we conducted focus groups with older adults residing in coastal locations to examine to what extent they felt technology could support them during emergencies. Our fndings characterize participants' desire for tools that enhance community resilience-local knowledge, preparedness, community relationships, and communication, that help communities withstand disasters. Further, older adults' crisis technology preferences were linked to their sense of control, social relationships, and digital readiness. We discuss how a focus on community resilience can yield crisis technologies that more efectively support older adults.

Exploit Social Distancing in Construction Scheduling: Visualize and Optimize Space-Time-Workforce Tradeoff

The COVID pandemic has given rise to the necessity of social distancing regulations, which has brought the importance of workspace management on the construction site to an unprecedented level. Understanding and visualizing the interaction and tradeoff among space, time, and workforce is critical for construction managers to schedule and deliver projects on time. Therefore, the objectives of this research are to investigate how the critical path method (CPM) and Takt-time planning methods utilize space, time, and workforce differently, develop a tool to visualize the space-time-workforce interactions, and investigate the space-time-workforce tradeoff based on different managers' preferences. This research selected a high-rise office building project and collected 889 sets of productivity data of five specialty trades. The research built a simulation model to investigate productivity and project performance under 267 scenarios of different combinations of the three resources. A dynamic tool was then developed to visualize workspace, time, and workforce interactions. Finally, a Choquet integral-based evaluation and decision tool was developed. The simulation results show that the Takt-time planning method can reduce up to 80% of workspace overlap compared with the actual production plan with less than 20% of duration extension. The contributions to the body of knowledge are (1) creating a visual framework for managers to understand the interaction and tradeoff among space, time, and workforce quickly and accurately, and (2) developing an innovative Choquet integral approach for managers to evaluate planning strategies according to project preferences. The framework and analysis method can be adapted to other construction projects to assist managers to visualize and optimize the space-time-workforce tradeoff under uncertain project drivers.

COVID-GAN plus : Estimating Human Mobility Responses to COVID-19 through Spatio-temporal Generative Adversarial Networks with Enhanced Features

Estimating human mobility responses to the large-scale spreading of the COVID-19 pandemic is crucial, since its significance guides policymakers to give Non-pharmaceutical Interventions, such as closure or reopening of businesses. It is challenging to model due to complex social contexts and limited training data. Recently, we proposed a conditional generative adversarial network (COVID-GAN) to estimate human mobility response under a set of social and policy conditions integrated from multiple data sources. Although COVID-GAN achieves a good average estimation accuracy under real-world conditions, it produces higher errors in certain regions due to the presence of spatial heterogeneity and outliers. To address these issues, in this article, we extend our prior work by introducing a new spatio-temporal deep generative model, namely, COVID-GAN+. COVID-GAN+ deals with the spatial heterogeneity issue by introducing a new spatial feature layer that utilizes the local Moran statistic to model the spatial heterogeneity strength in the data. In addition, we redesign the training objective to learn the estimated mobility changes from historical average levels to mitigate the effects of spatial outliers. We perform comprehensive evaluations using urban mobility data derived from cell phone records and census data. Results show that COVID-GAN+ can better approximate real-world human mobility responses than prior methods, including COVID-GAN.

Mapping the Landscape of COVID-19 Crisis Visualizations

In response to COVID-19, a vast number of visualizations have been created to communicate information to the public. Information exposure in a public health crisis can impact people's attitudes towards and responses to the crisis and risks, and ultimately the trajectory of a pandemic. As such, there is a need for work that documents, organizes, and investigates what COVID-19 visualizations have been presented to the public. We address this gap through an analysis of 668 COVID-19 visualizations. We present our findings through a conceptual framework derived from our analysis, that examines who, (uses) what data, (to communicate) what messages, in what form, under what circumstances in the context of COVID-19 crisis visualizations. We provide a set of factors to be considered within each component of the framework. We conclude with directions for future crisis visualization research.

Repurposing face mask waste to construct floating photothermal evaporator for autonomous solar ocean farming

Plastic waste caused by the extensive usage of face masks during COVID-19 pandemic has become a severe threat to natural environment and ecosystem. Herein, an eco-friendly approach to repurpose face mask waste for clean water production via solar thermal evaporation is proposed. By taking advantage of its interwind structure, face mask holds the promise to be an ideal candidate material for constructing photothermal evaporator. In-situ surface modifications are performed successively with polyvinyl alcohol and polypyrrole to improve its wettability and solar absorption (97%). The obtained face mask-based evaporator achieves significantly enhanced solar efficiency (91.5%) and long-term salt-rejection stability. The harvested clean water befits plant growing to enable farming on sea surface. A floating photothermal evaporation prototype is then developed to demonstrate autonomous solar ocean farming, with plants successfully cultivated over time. As such, the proposed strategy provides a promising solution towards ecological sustainability by tapping multiple benefits.

Women Workforce in Construction during the COVID-19 Pandemic: Challenges and Strategies

Changes and challenges in employment are inevitable under the measures enacted to contain the COVID-19 pandemic. Early evidence suggests that the pandemic would disproportionately affect women compared to men. Focussing on women workforce in construction, this exploratory study examines the challenges associated with changes in their job situations, the adopted strategies in addressing the challenges and their opinions on employment situation of women workforce during the pandemic. Results of a content analysis show that the top ranked challenges are: (i) overworked;(ii) working space;(iii) social interactions;(iv) collaboration;and (v) parenting. The most cited strategies in addressing these challenges are: (i) increased visual communication;(ii) a dedicated workspace;(iii) self-scheduling;(iv) flexible working arrangements;and (v) breaking out work time and personal time. The evidence is suggestive that most challenges are interrelated, and the strategies adopted by the respondents are multi-level and interdependent. The results also show that the most mentioned opinion is the increased caring and domestic responsibilities among women workforce. Under the uncertainty about the duration of the pandemic and future contagion waves, these findings are critical in informing employing organizations' human resource management challenges to better support their female employees during pandemic time and beyond.

2-((1H-indol-3-yl)thio)-N-phenyl-acetamides: SARS-CoV-2 RNA-dependent RNA polymerase inhibitors

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is the causative agent of Coronavirus Disease 2019 (COVID-19) pandemic. Despite intensive and global efforts to discover and develop novel antiviral therapies, only Remdesivir has been approved as a treatment for COVID-19. Therefore, effective antiviral therapeutics are still urgently needed to combat and halt the pandemic. Viral RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 demonstrates high potential as a reliable target for the development of antivirals. We previously developed a cell-based assay to assess the efficiency of compounds that target SARS-CoV-2 RdRp, as well as their tolerance to viral exoribonuclease-mediated proof-reading. In our previous study, we discovered that 2-((1H-indol-3-yl)thio)-N-phenyl-acetamides specifically targets the RdRp of both respiratory syncytial virus (RSV) and influenza A virus. Thus, we hypothesize that 2-((1H-indol-3-yl)thio)-N-phenyl-acetamides may also have the ability to inhibit SARS-CoV-2 replication by targeting its RdRp activity. In this research, we test a compound library containing 103 of 2-((1H-indol-3-yl)thio)-N-phenyl-acetamides against SARS-CoV-2 RdRp, using our cell-based assay. Among these compounds, the top five candidates strongly inhibit SARS-CoV-2 RdRp activity while exhibiting low cytotoxicity and resistance to viral exoribonuclease. Compound 6-72-2a is the most promising candidate with the lowest EC50 value of 1.41 mu M and highest selectivity index (CC50/EC50) (above 70.92). Furthermore, our data suggests that 4-46b and 6-72-2a also inhibit the replication of HCoV-OC43 and HCoV-NL63 virus in a dose-dependent manner. Compounds 4-46b and 6-72-2a exhibit EC50 values of 1.13 mu M and 0.94 mu M, respectively, on HCoV-OC43 viral replication. However, higher concentrations of these compounds are needed to effectively block HCoV-NL63 replication. Together, our findings successfully identified 4-46b and 6-72-2a as promising inhibitors against SARS-CoV-2 RdRp.

Pandemic, risk-adaptation and household saving: evidence from China

Purpose - Scholars have not agreed with each other on how people would behave after experiencing a catastrophic event. They could save more as a precautionary action for future difficulties or save less with a carpe diem attitude. This study aims to attempt to shed light on this debate with empirical observations on how the Covid-19 pandemic has affected household saving decisions. Design/methodology/approach - The two waves of the survey data allowed us to investigate both instantaneous and ongoing effects of Covid-19 on household saving decisions. The instantaneous effect refers to the immediate impact of the crisis, while the ongoing effect refers to the lasting impact of the pandemic when economic recovery had started. The variation in the number of confirmed cases across cities during the two waves provides the source of power for identification. The authors extend their analyses of the impact of Covid-19 on the household saving decision by using ordinary least squares models. Due to the ordered nature of survey responses, the authors also rerun all baseline models using the ordered probit regression method. Findings - This paper studied the impact of the Covid-19 pandemic on household saving decisions in China. This study found that households in the most affected cities would save more during the Covid-19 but tend to save less when the disaster started fading away. Combining findings in Kun et al. (2013) and Filipski et al. (2015), people do become more pessimistic during and after the Covid-19, possibly driving their observed precautionary and cape diem behaviors during the two points of time. Heterogeneity analysis shows that specific households would dramatically change their saving behavior. These observations might be useful for policymakers who concern the economic recovery after this pandemic disaster. Originality/value - Understanding how the Covid-19 pandemic would affect household consumption vs saving decisions is important for the economic recovery after this disaster comes to an end. The analyses presented in this research could be useful for policymakers who concern appropriate policies aiming to boost consumption and economic activities after Covid.

Research progress in targets and drugs for novel coronavirus

The outbreak of coronavirus disease-19 (COVID-19) caused by novel coronavirus (severe acute respiratory syndrome coronavirus-2, SARS-CoV-2) has posed a serious threat to public health. Virus particles of SARS-CoV-2 are composed of outer envelopes and inner nucleocapsids. The nonstructural and structural proteins encoded by the genome play an important role in the whole life cycle of their adsorption, penetration, uncoating, synthesis of nucleic acids and proteins, assembly and liberation. Antiviral drugs can be developed to target the virus itself or key host molecules for virus infection. So far, antibody drugs targeting spike glycoprotein S and small molecule drugs targeting RNA polymerase have shown antiviral effects. They are currently more promising candidate drugs. However, their efficacy still needs to be proved by further clinical trials, and miracle antiviral drugs have not yet appeared. Considering the virus and host targets, the combination therapy of multi-targets and multidrugs, may achieve better therapeutic effect. In this paper, the structure and life cycle of SARS-CoV-2, the research progress in potential targets and drugs were reviewed to provide useful information for the development of anti-SARS-CoV-2 drugs.

Evidence-Based Recommender System for a COVID-19 Publication Analytics Service

The rapid growth of COVID-19 publications has driven clinical researchers and healthcare professionals in pursuit to reduce the knowledge gap on reliable information for effective pandemic solutions. The manual task of retrieving high-quality publications based on the evidence pyramid levels, however, presents a major bottleneck in researchers' workflows. In this paper, we propose an "evidence-based" recommender system namely, KnowCOVID-19 that utilizes an edge computing service to integrate recommender modules for data analytics using end-user thin-clients. The edge computing service features chatbot-based web interface that handles a given COVID-19 publication dataset using two recommender system modules: (i) evidence-based filtering that observes domain specific topics across the literature and classifies the filtered information according to a clinical category, and (ii) social filtering that allows diverse experts with similar objectives to collaborate via a "social plane" to jointly find answers to critical clinical questions to fight the pandemic. We compare the Domain-specific Topic Model (DSTM) used in our evidence-based filtering with state-of-the-art models considering the CORD-19 dataset (a COVID-19 publication archive) and show improved generalization effectiveness as well as knowledge pattern query effectiveness. In addition, we conduct a comparison study between a manual literature review process and the KnowCOVID-19 augmented process, and evaluate the benefits of our information retrieval techniques over important queries provided by COVID-19 clinical experts.

Riders Who Avoided Public Transit During COVID-19 Personal Burdens and Implications for Social Equity

Problem, research strategy, and findings Millions of North Americans stopped riding public transit in response to COVID-19. We treat this crisis as a natural experiment to illustrate the importance of public transit in riders' abilities to access essential destinations. We measured the impacts of riders forgoing transit through a survey of transportation barriers completed by more than 4,000 transit riders in Toronto and Vancouver (Canada). We used Heckman selection models to predict six dimensions of transport disadvantage and transport-related social exclusions captured in our survey. We then complemented model results with an analysis of survey comments describing barriers that individuals faced. Lack of access to alternative modes is the strongest predictor of a former rider experiencing transport disadvantage, particularly neighborhood walkability and vehicle ownership. Groups at risk of transport disadvantage before COVID-19, particularly women and people in poorer health, were also more likely to report difficulties while avoiding public transit. Barriers described by respondents included former supports no longer offering rides, gendered household car use dynamics, and lack of culturally specific or specialized amenities within walking distance. Takeaway for practice Policymakers should plan for a level of redundancy in transportation systems that enables residents to access essential destinations when unexpected service losses occur. Designing communities that enable residents to walk to those essential destinations will help reduce the burdens faced by transit riders during crises that render transit unfeasible. At the same time, planners championing active travel as an alternative to transit during such crises also need to devise solutions for former transit riders for whom active travel is ill suited, for example, due to physical challenges with carrying groceries or needing to chaperone children.

[A comparison of clinical characteristics between patients with and without"recurrence"RNA positive with COVID-19].

Objective: To analysis the clinical characteristics of"recurrence"RNA positive patients with Coronavirus disease 2019 （COVID-19） and compared with those without"recurrence". Methods: 98 patients with COVID-19 in Wuhan Jinyintan Hospital and designated treatment hospitals in Quanzhou were included in this study from February 2020 to April 2020. There were 55 males and 43 females， aged from15 to 83 years， with a median age of 57.5 years， in which 20 cases were complicated with basic diseases. 15 of these patients had been diagnosed and hospitalized had been found as"recurrence"2019-nCoV RNA positive after discharge while the other 83 cases were all negative. The clinical classification of all patients was common type. Clinical data of the COVID-19 RNA"recurrence"patients were collected， and general situations， symptoms， laboratory examinations and CT images were also observed and analyzed. The patients were divided into 2019-nCoV"recurrent"group and 2019-nCoV"non-recurrent"group. There are 10 males and 5 females in 2019-nCoV"recurrent"group while 45 males and 38 females in"non-recurrent"group （χ²=0.800，P=0.371）. The age of 2019-nCoV"recurrent"group （57±21） was higher than that of"non-recurrent"group（53±17）. 8 of 15 the COVID-19"recurrent"group patients and 12 of 83"non-recurrent"patients have basic diseases. IgG and IgM of 2019-nCoV， IL-6， procalcitonin， ESR， CRP， BNP and other serum biochemical index levels were measured and compared between groups. Results: （1） The proportion of patients with common type of COVID-19 was 15.3% during 2-week medical observation after discharge. （2） All of the 2019-nCoV"recurrent"patients were hospitalized due to COVID-19 RNA positive， when they were quarantined after discharged from hospital. All the patients with mild symptoms which were clarified as common type， including 5 cases of fever， 6 cases of cough， 5 cases of expectoration， and 2 cases of slight shortness of breath. The time of symptoms appeared on （5.73±2.82） days after discharge. （3） The serum procalcitonin of all 2019-nCoV"recurrent"group patients were normal（all<0.05 ng/ml）. The BNP of"recurrent"group （151±171） ng/L， was higher than that of"non-recurrent"group （63±78） ng/L （t = 3.207， P = 0.000）. There was no significant difference in laboratory tests like leukocyte ［（6.17±2.4） and （6.04±2.41）×109/L］， lymphocyte［（1.59±0.52） and （1.32±0.64）×109/L］， CRP ［（12.54±28.20） and （21.74±25.63）mg/L］， ESR ［（31.07±28.72） and （34.10±22.16）mm/1 h］， AST ［（24.73±9.15） and （30.24±23.20）U/L］， ALT ［（22.60±12.82） and （36.47±34.12）U/L）， LDH ［（268±208） and （270±164）U/L］， D-dimer ［（0.60±0.50） and （0.84±0.98）µg/L］， ferritin ［（294±195） and （395±319）µg/L］， IL-6 ［（9.17±6.42） and （14.28±17.74）ng/Lï¼½ and BUN （5.77±2.66） and （4.74±2.81）U/Lï¼½ between"recurrent"and"non-recurrent"groups （all P>0.05）. （4） In"recurrent"group， ground glass， exudative or solid lesions could be found in most of the chest CT performed on re-admission. Meanwhile， fibrosis lesion was relatively rare. （5） There were no secondary transmissions were found to be caused by the 2019-nCoV"recurrent"group patients. Conclusions: Most of the 2019-nCoV patients had underlying diseases and active lesions were still found in CT images， so the possibility of virus replication may still exist. All"recurrent"patients had mild illness which may suggest that they were in recovery stage, and no evidence of transmission is found.

Does Liuzijue Qigong affect anxiety in patients with chronic obstructive pulmonary disease, even during the COVID-19 outbreak? a randomized, controlled trial

Background: Anxiety is a common comorbidity associated with chronic obstructive pulmonary disease (COPD), but no well-recognized method can provide effective relief. Liuzijue Qigong (LQG) is a traditional Chinese fitness method, based on breath pronunciation. This study aimed to examine the efficacy of LQG to relieve anxiety in COPD patients and to explore the factors that influence anxiety, including whether LQG is effective during the coronavirus disease 2019 (COVID-19) outbreak. Methods: We conducted an open-label, randomized, controlled, clinical trial. A total of 60 patients with stable COPD were randomly assigned to two groups. Both groups were given routine medical treatment, and the patients in the pulmonary rehabilitation (PR) group were given an extra intervention in the form of LQG, performed for 30 minutes each day for 12 weeks. Data collection was performed at baseline and 12 weeks (during the COVID-19 epidemic). The primary outcomes were the self-rating anxiety scale (SAS) scores, and the secondary outcomes were relevant information during the epidemic and analyses of the related factors that influenced SAS scores during the COVID-19 outbreak. Results: Compared with baseline, patients in both groups demonstrated varying degrees of improvements in their SAS scores (all P < 0.01). An analysis of covariance, adjusted for baseline scores, indicated that the SAS scores improved more dramatically in the PR group than in the control group (F = 9.539, P = 0.004). During the outbreak, the SAS scores for sleep disorder were higher than all other factors, reaching 1.38 +/- 0.67, and the scores for "I can breathe in and out easily" for the PR group were lower than the scores for the control group (Z = -2.108, P = 0.035). Significant differences were identified between the two groups for the categories "How much has the outbreak affected your life", "Do you practice LQG during the epidemic" and "Do you practice other exercises during the epidemic" (all P < 0.05). Compared with current reports, LQG had a relatively high adherence rate (80.95%). A multiple linear regression analysis revealed multiple predictors for SAS scores during the outbreak: group (b = -3.907, t = -3.824, P < 0.001), COPD assessment test score (b = 0.309, t = 2.876, P = 0.006), SAS score at baseline (b = 0.189, t = 3.074, P = 0.004), and living in a village (b = 4.886, t = 2.085, P = 0.043). Conclusion: LQG could effectively reduce the risks of anxiety among COPD patients, even during the COVID-19 outbreak. For those COPD patients with high COPD assessment test and high baseline SAS scores or who live in villages, we should reinforce the management and intervention of psychological factors during the epidemic.