Community Diversity Climate Impact on the Well-Being of Asian Americans Amid Anti-Asian Sentiment During the COVID-19 Pandemic: The Role of Two-Way Symmetrical Communication by Local Governments

Integrating the literature from public relations, community psychology, and minority stress theory, this study proposes and tests a model that describes the mechanism by which local governments' two-way symmetrical communication practices may affect local Asian Americans' experiences amid anti-Asian sentiment during the COVID-19 pandemic. The results of an online survey of 400 Asian Americans living in the United States indicated that local governments' two-way symmetrical communication practices with respect to diversity acceptance helped establish a community diversity climate. Such a perception lowered the target group's perceived stigma consciousness and fear of discrimination, which are the two main proximal stressors affecting minority members' emotions and wellbeing. Theoretical and practical implications on public relations and governmental communication are discussed.

Analyzing the Stock Volatility Spillovers in Chinese Financial and Economic Sectors

By regarding the Chinese financial and economic sectors as a system, this article studies the stock volatility spillover in the system and explores its effects on the overall performance of the macroeconomy in China. The recent outbreak of COVID-19, U.S.-China trade friction, and three historical financial turbulences are involved to distinguish the changes in the spillover in these distinct crises, which has seldom been unveiled in the literature. By considering that the stock volatility spillover may vary over distinct timescales, the spillovers are disclosed through innovatively constructing the multi-scale spillover networks, followed by connectedness computation, based on variational mode decomposition (VMD) and generalized vector autoregression (GVAR) process. Our empirical analysis first demonstrates the different levels of increases in the total sectoral volatility spillover and changes in the roles of the sectors in the system under the aforementioned crises. Besides, the increases in the sectoral spillover in the long-term are verified to negatively impact the macroeconomy and can thereby act as warning signals.

An Examination of the Spatial Spillover Effects of Tourism Transportation on Sustainable Development from a Multiple-Indicator Cross-Perspective

Tourism is linked to multiple dimensions, such as the economy, society, and environment, and the relationships among its influencing factors are complex, diverse, and overlapping. This study constructed an evaluation index system to measure the degree of coordinated development of tourism, transportation, and the regional economy, then built a tourism-transportation-based Spatial Durbin Model (SDM) regarding the process of the coordinated development of tourism in the Beijing-Tianjin-Hebei region (BTHR) from 2010 to 2020. This paper explains the current status of sustainable tourism development in the BTHR and the impact and spillover effects of transportation on tourism development. The results show that the normalized tourism coordinated development index (NTCDI) of the BTHR increased from 13.61 in 2010 to 18.75 in 2019, then decreased to 14.45 in 2020. The results of SDM show that different transportation modes have different spillover effects on tourism. Specifically, civil aviation transportation has a positive impact and significant spillover on a city's tourism revenue (TR), while high-speed railway transportation has a negative spillover effect. The model results also show that the degree of openness of the city and city economic development level have significant positive effects and spillover effects on tourism development. Finally, the implications of related variables are discussed, and some suggestions are put forward on tourism development in the BTHR. However, there are some limitations in this study. In the future, international cooperation and data sharing will be strengthened, and multivariate methods such as social network analysis, artificial intelligence, and machine learning will be further integrated to achieve accurate simulation and prediction of the spatial spillover effects of tourism transportation.

How Dialogic Vaccine Communication in the Workplace Facilitates Employee Advocacy for COVID-19 Vaccine Uptake

Encouraging employees' vaccine uptake and motivating their vaccine advocacy are crucial steps to secure workplace health and safety during the current pandemic. Yet, how to achieve those steps remains challenging. To address this challenge, this study examines whether and how companies' vaccine communication efforts with employees, particularly dialogic communication, can motivate employees' advocacy behaviors for COVID-19 vaccine uptake. Specifically, by drawing insights from public relations, management, psychology, and health communication research, we predict that organizations' dialogic communication will enhance employees' perceptions of organizational support for vaccination, which will further increase employees' positive emotions while decreasing their negative emotions toward the vaccines. These emotional states will ultimately contribute to employees' vaccine advocacy. An online survey among 505 full-time U.S. employees supported our predictions. Our study advances public relations, organizational communication, and workplace health scholarships and practice by revealing the under-explored role of workplace communication in promoting public health. © 2022 Taylor & Francis Group, LLC.

Pathogens inactivation in nutrient recovery from urine: A review

Urine source separation, a kind of new sewage management concept, has made great progress in technology development and application in the past 30 years. However, understanding of the potential microbial risks in reuse of urine derived fertilizer products (UDFPs) in agriculture is still lacking. Outbreak of pandemic of Coronavirus Disease 2019 and more deadly disease caused by Monkeypox strongly sounds the alarm bell to the attention on pathogens in urine and their fate in UDFPs. Therefore, this study presented a comprehensive review on pathogens inactivation in nutrient recovery technologies. The review suggests that technologies using alkaline or heating treatment can effectively reduce pathogens in UDFPs. However, technologies with characteristics such as membrane rejection of nutrients or nutrient adsorption may even concentrate pathogens in their fertilizer products. Based on an overall assessment, connections of technologies and the pathogens inactivation in their UDFPs have been established. This would help to provide a perspective on development of urine treatment technology and management of microbial risks in reusing urine nutrients in agriculture.

Forecasting pharmacy purchases orders

Inventory represents the largest asset in pharmacy products distribution. Forecasting pharmacy purchases is essential to keep an effective stock balancing supply and demand besides minimizing costs. In this work, we investigate how to forecast product purchases for a pharmaceutical distributor. The data contains inventory sale histories for more than 10 thousand active products during the past 15 years. We discuss challenges on data preprocessing of the pharmacy data including cleaning, feature constructions and selections, as well as processing data during the COVID period. We experimented on different machine learning and deep learning neural network models to predict future purchases for each product, including classical Seasonal Autoregressive Integrated Moving Average (SARIMA), Prophet from Facebook, linear regression, Random Forest, XGBoost and Long Short-Term Memory (LSTM). We demonstrate that a carefully designed SARIMA model outperformed the others on the task, and weekly prediction models perform better than daily predictions.

Passive WiFi CSI Sensing Based Machine Learning Framework for COVID-Safe Occupancy Monitoring

The COVID-19 pandemic requires social distancing to prevent transmission of the virus. Monitoring social distancing is difficult and expensive, especially in "travel corridors" such as elevators and commercial spaces. This paper describes a low-cost and non-intrusive method to monitor social distancing within a given space, using Channel State Information (CSI) from passive WiFi sensing. By exploiting the frequency selective behaviour of CSI with a cubic SVM classifier, we count the number of people in an elevator with an accuracy of 92%, and count the occupancy of an office to 97%. As opposed to using a multi-class counting approach, this paper aggregates CSI for the occupancies below and above a COVID-Safe limit. We show that this binary classification approach to the COVID safe decision problem has similar or better accuracy outcomes with much lower computational complexity, allowing for real-world implementation on IoT embedded devices. Robustness and scalability is demonstrated through experimental validation in practical scenarios with varying occupants, different environment settings and interference from other WiFi devices.

Development of an Indoor Exergame Based on Moving-Target Hitting Task for COVID-19 Epidemic: A Comparison Between AR and VR Mode

The COVID-19 has led to home quarantine in global scale, which increased people's need for indoor fitness activities in order to relieve stress/anxiety and learn knowledge well during the prevention. In this article, an augmented reality (AR) indoor exergame is developed, mainly a kind of moving target hitting task with Lomachenkos headwear speedball as the prototype. Then, a comparative experiment is performed to test the effect of the exergame in relieving anxiety, as well as the differences between AR and virtual reality modes (using HTC Vive Pro) on user experience (flow experience and motion sickness) and interaction efficiency. Results from 28 participants show that the anxiety level of participants significantly reduced after using the exergame. Although the difference on flow experience is not significant, there is a marginally significant difference on nausea level, a dimension of motion sickness. Moreover, interaction efficiency between the two modes is significantly different. In the task of moving target hitting, AR mode performed better in avoiding motion sickness and improving interaction performance.

Traditional Chinese medicines against COVID-19: A global overview

Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2, continues to be a global concern. Traditional Chinese medicines (TCMs) are an important element of the fight against COVID-19 in China. The combined application of TCMs and conventional medicines in the treatment of COVID-19 has achieved beneficial results, including the resolution of symptoms, prevention of disease progression, and reduced mortality. In this review, we summarize and discuss the current applications of TCMs with respect to COVID-19, as well as update the preclinical and clinical research, including chemical analysis, molecular mechanisms, quality control, drug development, and studies of clinical efficacy. The expectation is that a better understanding of the roles of TCMs against COVID-19 will improve the response to COVID-19, both in China and globally. © 2022 World Journal of Traditonal Chinese Medicine Published by Wolters Kluwer - Medknow.

Evaluation of Long-Term Modeling Fine Particulate Matter and Ozone in China During 2013-2019

Air quality in China has been undergoing significant changes due to the implementation of extensive emission control measures since 2013. Many observational and modeling studies investigated the formation mechanisms of fine particulate matter (PM2.5) and ozone (O-3) pollution in the major regions of China. To improve understanding of the driving forces for the changes in PM2.5 and O-3 in China, a nationwide air quality modeling study was conducted from 2013 to 2019 using the Weather Research and Forecasting/Community Multiscale Air Quality (WRF/CMAQ) modeling system. In this study, the model predictions were evaluated using the observation data for the key pollutants including O-3, sulfur dioxide (SO2), nitrogen dioxide (NO2), and PM2.5 and its major components. The evaluation mainly focused on five major regions, that is , the North China Plain (NCP), the Yangtze River Delta (YRD), the Pearl River Delta (PRD), the Chengyu Basin (CY), and the Fenwei Plain (FW). The CMAQ model successfully reproduced the air pollutants in all the regions with model performance indices meeting the suggested benchmarks. However, over-prediction of PM2.5 was noted in CY. NO2, O-3,O- and PM2.5 were well simulated in the north compared to the south. Nitrate (NO3-) and ammonium (NH4+) were the most important PM2.5 components in heavily polluted regions. For the performance on different pollution levels, the model generally over-predicted the clean days but underpredicted the polluted days. O-3 was found increasing each year, while other pollutants gradually reduced during 2013-2019 across the five regions. In all of the regions except PRD (all seasons) and YRD (spring and summer), the correlations between PM2.5 and O-3 were negative during all four seasons. Low-to-medium correlations were noted between the simulated PM2.5 and NO2, while strong and positive correlations were established between PM2.5 and SO2 during all four seasons across the five regions. This study validates the ability of the CMAQ model in simulating air pollution in China over a long period and provides insights for designing effective emission control strategies across China.

Managing supply chains during the Covid-19 crisis: synthesis of academic and practitioner visions and recommendations for the future

Purpose The Covid-19 pandemic has created an environment of high uncertainty and caused major disruptions in supply chains. The new normal that has emerged during the pandemic is leading to a need to identify new solutions to improve supply chain crisis management in the future. Practitioners require adapted recommendations for solutions to implement. These recommendations are laid out in this paper. Design/methodology/approach A combination of a systematic literature review (SLR), qualitative semi-structured interviews and a questionnaire survey of supply chain practitioners is applied. The interviews provide insights into supply chain practitioners' views of their approaches and, together with the solutions proposed in the literature, provide future recommendations for action for supply chain managers. Findings During the pandemic, companies experienced disruptions in supply, production and demand, as well as interruptions in transportation and distribution. The majority of the solutions proposed in the literature, coincide with the opinions of practitioners. These include collaborative risk management, real-time monitoring and information sharing, supply network management, scenario planning and "what-if" simulations. Research limitations/implications Although the number of interviews conducted and questionnaires completed is limited, they still serve to supplement the SLR with important practical insights and recommendations. Originality/value This paper presents a review of recent academic literature focusing on the impact of Covid-19 on supply chains and the existing solutions to mitigate that impact and manage future crises. It has been expanded to include industry perspectives and experiences. The findings of this study present recommended practices and strategies for better managing supply chains during a crisis.

[Challenges of maintaining malaria elimination in China: Cross-border malaria].

China was certificated malaria-free by WHO in 2021 and has continued to maintain malaria elimination. However, there are still huge challenges in malaria control in the border regions between Yunnan Province, China and Myanmar due to lack of geographic barriers and frequent cross-border travel. Hereby, we review the direction contributions of the Global Fund Malaria Program implemented by Health Poverty Action (HPA), an international non-governmental organization (NGO), to malaria elimination in China, and analyze the challenges of malaria control caused by external environmental factors, such as COVID-19, in regions where the Global Fund Malaria Program is implemented. In addition, some suggestions are proposed for cross-border collaboration on malaria control.

COVID-Safe Spatial Occupancy Monitoring Using OFDM-Based Features and Passive WiFi Samples

During the COVID-19 pandemic, authorities have been asking for social distancing to prevent transmission of the virus. However, enforcing such distancing has been challenging in tight spaces such as elevators and unmonitored commercial settings such as offices. This article addresses this gap by proposing a low-cost and non-intrusive method for monitoring social distancing within a given space, using Channel State Information (CSI) from passive WiFi sensing. By exploiting the frequency selective behavior of CSI with a Support Vector Machine (SVM) classifier, we achieve an improvement in accuracy over existing crowd counting works. Our system counts the number of occupants with a 93% accuracy rate in an elevator setting and predicts whether the COVID-Safe limit is breached with a 97% accuracy rate. We also demonstrate the occupant counting capability of the system in a commercial office setting, achieving 97% accuracy. Our proposed occupancy monitoring outperforms existing methods by at least 7%. Overall, the proposed framework is inexpensive, requiring only one device that passively collects data and a lightweight supervised learning algorithm for prediction. Our lightweight model and accuracy improvements are necessary contributions for WiFi-based counting to be suitable for COVID-specific applications.(1)

Exploration of bioactive constituents and immunoregulatory mechanisms of a hanshi-yufei formulation for treating COVID-19

Objective: The objective of this study was to characterize the chemical compounds of a Hanshi-Yufei formulation (HSYF;a modified formulation of a traditional Chinese medicine used for treating COVID-19) to elucidate the mechanism of action and to evaluate potential anti-inflammatory effects of HSYF. Materials and Methods: The chemical constituents of HSYF extract were characterized using UPLC-Q-TOF/MS. Subsequently, a set of TCM network pharmacology methods was applied to identify disease-associated genes and to predict target profiles and pharmacological actions associated with the constituents of HSYF. Then, the antiviral effects of HSYF on H1N1 were assessed in RAW264.7 cells using MTT assays. Expression levels of pro-inflammatory cytokines interleukin (IL)-6 and tumor necrosis factor (TNF)-α following infection of RAW264.7 cells with H1N1 were measured using an enzyme-linked immune sorbent assay (ELISA), and expression levels of inflammatory-related factors were detected using western blotting. Results: In total, 165 chemical constituents (including glycosides, tannins, volatile oils, amino acids, triterpenoids, polyphenols, phenylpropanoids, sesquiterpenes, alkaloids, and flavonoids, among others) were tentatively identified in HSYF. Network pharmacology demonstrated that HSYF can regulate immunomodulatory- and anti-inflammatory-related targets of multiple pathways through its active ingredients, suggesting potential anti-COVID-19 effects. Furthermore, cell viability assays and ELISA showed that HSYF significantly inhibited H1N1 replication in RAW64.7 cells and markedly reduced expression of pro-inflammatory cytokines TNF-α and IL-6 at the proteins level. Conclusions: The results of the present study help improve our understanding of the therapeutic effects of HSYF in COVID-19 treatment from multi-level perspectives.

Safety and efficacy of convalescent plasma therapy in severely and critically ill patients with COVID-19: a systematic review with meta-analysis

Background: The rapidly evolving coronavirus disease 2019 (COVID-19) has resulted in more than 24 million infections and 821 thousand deaths. However, a vaccine or specific drug is absent up to this date and more attention has been focused on the use of convalescent plasma (CP). Several articles have described the CP treatment for patients with SARS-CoV-2 infection. But a comprehensive systematic review with meta-analysis about the safety and efficacy of CP transfusion in SARS-CoV-2-infected patients has not been published. We conducted this study for a better understanding of the therapeutic significance of CP for patients with COVID-19. Results: A fixed-effect model (I-2=0.0%) was used on the 9 articles for quantitative analysis showing that the mortality of patients with COVID-19 treated with or without CP was statistically significant (RR=0.57 [0.44-0.74]). Subgroup analysis showed that the severely ill patients benefited more from CP than the critically ill patients. Our study concluded that clinical improvement in severe COVID-19 cases were obvious. Adverse events were few and the effect of convalescent plasma on reducing viral load was apparent. Conclusions: Convalescent plasma therapy appears safe for COVID-19, and plasma treated patients have marked reductions in their serum viral loads and most are virus negative after transfusion. Patients with severe COVID-19 benefit more from the convalescent plasma transfusion than critical patients, and patients treated in early stage are more likely to survive. Methods: We reviewed the scientific literature from four databases published from December 8, 2019 to August 20, 2020. Statistical analyses were performed with STATA (version 15.1;Stata Corporation, College Station, TX, USA). The frequency with 95% confidence intervals (CI) was assessed using fixed effect model in analyzing the overall mortality and p <0.05 was considered statistically significant.

Impacts of Modifiable Factors on Ambient Air Pollution: A Case Study of COVID-19 Shutdowns

COVID-19-related closures offered a novel opportunity to observe and quantify the impact of activity levels of modifiable factors on ambient air pollution in real time. We use data from a network of low-cost Real-time Affordable Multi-Pollutant (RAMP) sensor packages deployed throughout Pittsburgh, Pennsylvania, along with data from Environmental Protection Agency regulatory monitors. The RAMP locations were divided into four site groups based on land use. Concentrations of PM2.5, CO, and NO2 following the COVID-related closures at each site group were compared to measurements from "business-as-usual" periods. Overall, PM,, concentrations decreased across the domain by similar to 3 mu g/m(3). The morning rush-hour-induced CO and NO2 concentrations at the high-traffic sites were both reduced by similar to 50%, which is consistent with observed reductions in commuter traffic (similar to 50%). The morning rush-hour PM2.5 enhancement from traffic emissions was reduced nearly 100%, from 1.4 to similar to 0 mu g/m(3) across all site groups. There was no significant change in the industry-related intraday variability of CO and PM2.5 at the industrial sites following the COVID-related closures. If PM2.5 National Ambient Air Quality Standards (NAAQS) are tightened, this natural experiment sheds light on the extent to which reductions in traffic-related emissions can aid in meeting more stringent regulations.

Driving Forces of Changes in Air Quality during the COVID-19 Lockdown Period in the Yangtze River Delta Region, China

During the COVID-19 lockdown period (from January 23 to February 29, 2020), ambient PM2.5 concentrations in the Yangtze River Delta (YRD) region were observed to be much lower, while the maximum daily 8 h average (MDA8) O-3 concentrations became much higher compared to those before the lockdown (from January 1 to 22, 2020). Here, we show that emission reduction is the major driving force for the PM2.5 change, contributing to a PM2.5 decrease by 37% to 55% in the four YRD major cities (i.e., Shanghai, Hangzhou, Nanjing, and Hefei), but the MDA8 O-3 increase is driven by both emission reduction (29%-52%) and variation in meteorological conditions (17%-49%). Among all pollutants, reduction in emissions mainly of primary PM contributes to a PM2.5 decrease by 28% to 46%, and NOx emission reduction contributes 7% to 10%. Although NOx emission reduction dominates the MDA8 O-3 increase (38%-59%), volatile organic compounds (VOCs) emission reduction lead to a 5% to 9% MDA8 O-3 decrease. Increased O-3 promotes secondary aerosol formation and partially offsets the decrease of PM2.5 caused by the primary PM emission reductions. The results demonstrate that more coordinated air pollution control strategies are needed in YRD.