Large-Scale Analysis of New Employee Network Dynamics

The COVID-19 pandemic has accelerated digital transformations across industries, but also introduced new challenges into workplaces, including the difficulties of effectively socializing with colleagues when working remotely. This challenge is exacerbated for new employees who need to develop workplace networks from the outset. In this paper, by analyzing a large-scale telemetry dataset of more than 10,000 Microsoft employees who joined the company in the first three months of 2022, we describe how new employees interact and telecommute with their colleagues during their "onboarding"period. Our results reveal that although new hires are gradually expanding networks over time, there still exists significant gaps between their network statistics and those of tenured employees even after the six-month onboarding phase. We also observe that heterogeneity exists among new employees in how their networks change over time, where employees whose job tasks do not necessarily require extensive and diverse connections could be at a disadvantaged position in this onboarding process. By investigating how web-based people recommendations in organizational knowledge base facilitate new employees naturally expand their networks, we also demonstrate the potential of web-based applications for addressing the aforementioned socialization challenges. Altogether, our findings provide insights on new employee network dynamics in remote and hybrid work environments, which may help guide organizational leaders and web application developers on quantifying and improving the socialization experiences of new employees in digital workplaces. © 2023 ACM.

Under the Risk of COVID-19 Epidemic: A Study on the Influence of Life Attitudes, Leisure Sports Values, and Workplace Risk Perceptions on Urban Development and Public Well-Being

This study examined the impact of attitudes toward life, recreational sports values, and workplace risk perceptions on urban development and public well-being under the risk of the COVID-19 epidemic in China. A mixed-method research study was conducted, and 2400 valid questionnaires were collected via purposeful sampling. The questionnaires were analyzed using the SPSS 26.0 statistical software and validated with basic statistical methods and Pearson's correlation analysis. Semi-structured interviews were then conducted to collect the opinions of 12 respondents on the questionnaire results, including academics, foreign entrepreneurs and employees, local entrepreneurs and employees, and official institutions. Finally, all the data collected were discussed via triangulation analysis. The survey found that different cities' social and industrial development and job market needs lead to different attitudes toward life, leisure values, and perceptions of job-seeking and employment risks. The smoother a person's growing-up background, the better their learning history, the better their learning and working experience, and the richer their life experience;consequently, positive attitudes toward life, correct leisure values, and positive attitudes toward job hunting and employment can be cultivated. In addition, people with positive attitudes toward life, leisure values, and job hunting and employment can improve their city's economy and environment for sustainable development, thereby improving their quality of life and increasing their well-being.

Psychological intervention for three COVID patients who suffered online violence.

Three patients diagnosed with COVID-19 were all young women in their thirties who have suffered from Internet violence in their personal life after hospitalization. They showed significant emotional distress such as, depression state, acute stress disorder, and dissociative disorder. The current study adopts short-term, individualized and comprehensive psychological interventions, including psychological support, encouragement, listening, safety confirmation, catharsis, psychological suggestion, and stimulation of internal potential to treat patients. The third case was provided with psychological interventions combined with antipsychotic treatment. After timely psychological interventions all three patients achieved sound results.Copyright © 2021 Chinese Medical Journals Publishing House Co.Ltd.

Cost-Effectiveness Analysis of Nonpharmaceutical Interventions Combined with Inactivated Vaccination and Oral Medicine in China

Objectives: Various interventions were used to control the COVID-19 pandemic and protect population health, including vaccination, medication and nonpharmaceutical interventions (NPIs). This study aims to examine the cost-effectiveness of different combinations of NPIs (including social distancing, mask wearing, tracing-testing-isolation, mass testing, and lockdown), oral medicine (Paxlovid), and vaccination (including two-dose and three-dose vaccination) under the Delta and Omicron pandemic in China. Method(s): We constructed a Markov model using a SIRI structure with a one-week cycle length over one-year time horizon to estimate the cost-effectiveness of different combinations in China from societal perspective. Effectiveness of interventions, disease transition probabilities and costs were from published data, quality-adjusted life years (QALYs) gained and incremental cost-effectiveness ratios (ICER) and net monetary benefits were calculated for one-year time horizon. One-way and probabilistic sensitivity analyses were performed to test the robustness of the model. Scenario analysis was developed to examine different situations under the Omicron pandemic. Result(s): Under the Delta pandemic, implementing the combination of social distancing, mask wearing, mass testing and three-dose vaccination was the optimal strategy, with cost at $11165635.33 and utility of 94309.94 QALYs, and had 60% probability of being cost-effective compared with other strategies. Three-dose vaccination combinations were better than two-dose combinations. Under the Omicron pandemic, antigen testing was better than nucleic testing by avoiding cross infections;second, adding Paxlovid or lockdown to the combined intervention strategies could increase limited health outcomes at huge cost and thus were not cost-effective;last, encouraging patients to stay at home can save societal costs compared with concentrated quarantine at hospitals. Conclusion(s): Three-dose vaccination and self-quarantine of asymptomatic and mild cases can save total costs. Under the Omicron pandemic outbreak, antigen testing is a better way to control the pandemic, and adding Paxlovid or lockdown to intervention combinations is not cost-effective.Copyright © 2023

Exploring Health Outcomes By Occupation: Using the National Health and Wellness Survey to Describe Differences in Self-Reported Occupation Profiles

Objectives: Health is distributed unequally by occupation (Ravesteijn,2013). This research aims to explore patient-reported outcomes by occupation profiles using the National Health and Wellness Survey (NHWS). Method(s): Data from the 2022 US NHWS included employed respondents at least 18 years of age with information on occupation profile, defined as 22 categories from the Bureau of Labor Statistics. Descriptive statistics were used to analyze respondent characteristics and outcomes such as COVID-19 diagnoses, healthcare resource use over the past six months, and work impairment as measured by the Work Productivity and Activity Impairment Questionnaire (WPAI). Result(s): A total of 35,789 respondents were employed and had occupation information. Respondents were predominantly white (62.0%) and male (53.9%). Sales and Related occupations had the greatest proportion of respondents reporting a COVID-19 diagnosis (16.1%) while Building and Grounds Cleaning and Maintenance had the lowest proportion (3.8%). Educational Instruction and Library had the most respondents reporting that they had received at least one dose of the COVID-19 vaccine (79.2%) while Farming, Fishing, and Forestry had the least respondents (52.9%). Life, Physical, and Social Science had the greatest COVID-19 vaccination rate over the past year (66.5%) while Farming, Fishing, and Forestry had the lowest (45.0%). Office and Administrative Support had the greatest proportion of respondents with a traditional healthcare provider visit (79.8%), but the lowest proportion with an emergency room (ER) visit (12.7%) or a hospitalization (8.1%). Farming, Fishing, and Forestry had the greatest proportion of respondents with an ER visit (41.6%) or hospitalization (41.6%). The greatest proportion of respondents with any overall work impairment or activity impairment was in Farming, Fishing, and Forestry (work: 91.1%, activity: 87.4%) while the lowest proportion was in Office and Administrative Support (work: 50.0%, activity: 53.3%). Conclusion(s): Certain occupation profiles consistently show higher impairment while others consistently show lower impairment.Copyright © 2023

Promoting College Student's Systems Thinking

This study examined how college students in a medical school in China engaged in learning in asynchronous online learning environments during the COVID-19 health crisis. A quasi-experimental design approach was employed to compare if a class of students had better learning outcomes and developed systems thinking when asynchronous discussion forums incorporated an inquiry-based pedagogical approach in one unit, whereas the other unit followed a traditional instructor-led approach. In sum, 25 junior students participated in this study. Quantitative results show that the students had statistically significant higher assessment scores and improved systems thinking when the unit incorporated the inquiry-based pedagogical approach. Qualitative findings also demonstrated how students engaged in learning and how the instructor scaffolded students' inquiries and learning. Practical implications for instructors' teaching online courses are also discussed. © The author(s) 2023.

[Research progress on the relationship between COVID-19 and autoimmune diseases].

Different autoantibodies can be detected in patients with coronavirus disease 2019 (COVID-19). It is reported that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection could induce autoimmune diseases (AID), including children's multisystem inflammatory syndrome (MIS-C), Guillain Barre syndrome (GBS), Autoimmune hemolytic anemia (AIHA), immune thrombocytopenia (ITP) and thyroid autoimmune diseases. This article mainly reviews the similarities between COVID-19 and AID, the possibility of COVID-19 inducing AID, the risk of AID patients infected or vaccinated against COVID-19. The purpose is to provide strategies for the prevention, management and treatment of AID during the epidemic.

A meta-analysis of dynamic change of the SARS-CoV-2 specific antibody IgG positive rate in convalescent patients with COVID-19 in China

Objective To investigate the dynamic changes of severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) specific antibody IgG positive rate in coronavirus disease 2019 (COVID-19) survivors in China. Methods the relevant literatures about the positive rate of SARS-COV-2 specific antibody IgG in COVID-19 survivors in China were retrieved from PubMed, Embase, CNKI, Wanfang database and VIP database from December 2019 to February 24, 2022. The quality of the documents were assessed according the revised AHRQ (Agency for Healthcare Research and Quality) statement. Freeman-tukey double arsinusoidal conversion method was used to calculate the positive rate, and StataSE15.0 software was used for statistical analysis. Subgroup analysis was performed according to detection method and fragment, and publication bias was examined by Egger method. Results A total of 12 articles were included, IgG was detected from the first month to the twelfth month after SARS-COV-2 infection, and the total sample size ranged from 74 to 2 907 cases per month. The positive rate was the highest in the second month and the third month, 96.35% (95% CI: 93.98%-98.14%) and 97.23% (95% CI: 94.47%-99.05%) respectively. The positive rate decreased gradually with time, and reached 73.63% (95% CI: 50.31%-91.45%) in the twelfth month. The results of subgroup analysis showed that the heterogeneity between studies with the different detection method and the different detection fragment were significant differences (X2=5.02-39.57, all P < 0.05). Egger method test published bias, and the difference was not statistically significant (t=1.85, P=0.101). Conclusion Most people, one year after infection with SARSCOV- 2, could still detect SARS-COV-2 specific antibody IgG.

Accurate Assessment and Tracking the Process of Liver-Specific Injury by the Residual Tissue Activity of Carboxylesterase 1 and Dipeptidyl Peptidase 4

Accurately assessing and tracking the progression of liver-specific injury remains a major challenge in the field of biomarker research. Here, we took a retrospective validation approach built on the mutuality between serum and tissue biomarkers to characterize the liver-specific damage of bile duct cells caused by a-naphthyl isothiocyanate (ANIT). We found that carboxylesterase 1 (CES1), as an intrahepatic marker, and dipeptidyl peptidase 4 (DPP-IV), as an extrahepatic marker, can reflect the different pathophysiolo-gies of liver injury. Levels of CES1 and DPP-IV can be used to identify liver damage itself and the inflam-matory state, respectively. While the levels of the conventional serological biomarkers alkaline phosphatase (ALP), alanine aminotransferase (ALT), and aspartate aminotransferase (AST) were all con-comitantly elevated in serum and tissues after ANIT-induced injury, the levels of bile acids decreased in bile, increased in serum, and ascended in intrahepatic tissue. Although the level of c-glutamyl transpeptidase (c-GT) changed in an opposite direction, the duration was much shorter than that of CES1 and was quickly restored to normal levels. Therefore, among the abovementioned biomarkers, only CES1 made it possible to specifically determine whether the liver cells were destroyed or damaged with-out interference from inflammation. CES1 also enabled accurate assessment of the anti-cholestasis effects of ursodeoxycholic acid (UDCA;single component) and Qing Fei Pai Du Decoction (QFPDD;multi-component). We found that both QFPDD and UDCA attenuated ANIT-induced liver damage. UDCA was more potent in promoting bile excretion but showed relatively weaker anti-injury and anti-inflammatory effects than QFPDD, whereas QFPDD was more effective in blocking liver inflammation and repairing liver damage. Our data highlights the potential of the combined use of CES1 (as an intra-hepatic marker of liver damage) and DPP-IV (as an extrahepatic marker of inflammation) for the accurate evaluation and tracking of liver-specific injury-an application that allows for the differentiation of liver damage and inflammatory liver injury.(c) 2021 THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Federated Learning for Medical Imaging Segmentation via Dynamic Aggregation on Non-IID Data Silos

A large number of mobile devices, smart wearable devices, and medical and health sensors continue to generate massive amounts of data, making edge devices' data explode and making it possible to implement data-driven artificial intelligence. However, the "data silos” and other issues still exist and need to be solved. Fortunately, federated learning (FL) can deal with "data silos” in the medical field, facilitating collaborative learning across multiple institutions without sharing local data and avoiding user concerns about data privacy. However, it encounters two main challenges in the medical field. One is statistical heterogeneity, also known as non-IID (non-independent and identically distributed) data, i.e., data being non-IID between clients, which leads to model drift. The second is limited labeling because labels are hard to obtain due to the high cost and expertise requirement. Most existing federated learning algorithms only allow for supervised training settings. In this work, we proposed a novel federated learning framework, MixFedGAN, to tackle the above issues in federated networks with dynamic aggregation and knowledge distillation. A dynamic aggregation scheme was designed to reduce the impact of current low-performing clients and improve stability. Knowledge distillation was introduced into the local generator model with a new distillation regularization loss function to prevent essential parameters of the global generator model from significantly changing. In addition, we considered two scenarios under this framework: complete annotated data and limited labeled data. An experimental analysis on four heterogeneous COVID-19 infection segmentation datasets and three heterogeneous prostate MRI segmentation datasets verified the effectiveness of the proposed federated learning method. © 2023 by the authors.

Student financial support and sustainable recovery based on fuzzy-analytic hierarchy process comprehensive method

In the post-COVID-19 era, many university students face financial distress due to macroeconomic downturns. Helping college students overcome financial difficulties is an important aspect of sustainable recovery. Based on the theory of student satisfaction and the perspective of new financial support systems, this study constructs a performance evaluation system for financial support for financially distressed students in colleges and universities. To comprehensively evaluate financially distressed students for financial support from the perspective of satisfaction, an empirical study is conducted by taking the authors' college as an example according to the fuzzy Analytic Hierarchy Process analysis and evaluation model. The results show that, according to the characteristics of students, the students' families' characteristics should be considered and carefully sorted, and on this basis, the appropriate selection criteria for financially distressed students are selected. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Coronavirus disease 2019 vaccination in solid organ transplant recipients.

Solid organ transplant (SOT) recipients are a high-risk population for coronavirus disease 2019 (COVID-19), and the safety and efficacy of COVID-19 vaccines in this population is of great concern. At present, the published studies on COVID-19 vaccines for SOT recipients are mainly about mRNA vaccines and there are a few cases reports on recombinant adenovirus vector-based vaccines. These results show that the COVID-19 vaccines are safe for the SOT recipients, but the immune response rates are lower and the incidence of vaccine breakthrough infections is higher than that in the general population. Based on the results of the current studies, SOT recipients can start to be vaccinated with COVID-19 vaccines 1 to 3 months after organ transplantation. Prevention of COVID-19 after vaccination is still necessary to avoid vaccine breakthrough infections.Copyright © 2021 by the Chinese Medical Association.

Efficacy and safety of arbidol in the treatment of novel coronavirus pneumonia: a systematic review based on current and previous antiviral therapy.

Objective: To systematically evaluate the efficacy and safety of arbidol in the treatment of novel coronavirus pneumonia (COVID-19). Method(s): Randomized controlled trials (RCTs), cohort studies, and case-control studies on the efficacy and safety of arbidol for COVID-19, influenza, andother respiratory virus infections were collected by searching related database at home and abroad and network platform for preprint of Health Science Papers (medRxiv) (up to April 25, 2020). Quality of the enrolled studies was evaluated by bias risk assessment tool of Cochrane collaboration network and Newcastle-Ottawa Scale (NOS). Meta-analysis and descriptive analysis of relevant outcome indicators were performed using RevMan 5.3 software. Result(s): A total of 15 studies were enrolled in the study, including 7 cohort studies with high-quality and 8 RCTs, 6 of which were with low bias risk and the other 2 of which were with medium bias risk. Among these studies, 8 were on arbidol treatment for COVID-19, including 5 retrospective cohort studies, 2 prospective cohort studies, and 1 RCT, and involving 809 patients (479 patients in the arbidol group and 330 in the control group);7 were RCTs on arbidol treatment for influenza or other respiratory virus infections, involving 1 471 patients (745 patients in the arbidol group and 726 in the control group).In these studies, patients were treated with arbidol (0.15-1.2 g daily for 5-21 d) in the arbidol group while with the other antiviral agents or without any antiviral drug in the control group. Meta analysis on the efficacy and safety of arbidol in treatment for COVID-19 showed that the novel coronavirus (2019-nCoV) nucleic acid negative conversion rate in the arbidol group was significantly higher than that in the control group [71.7% (109/152) vs. 58.8% (94/160), relative risk (RR)=1.30, 95% confidence interval (CI): 1.01-1.67, P=0.04];the difference of time taken for 2019-nCoV nucleic acid negative conversion between the 2 groups was not statistically significant (standardized mean difference=-0.17, 95%CI: -0.72-0.38, P=0.55);the difference of disease improvement rate shown by chest CT on day 7 after treatment between the 2 groups was not statistically significant [46.2% (30/65) vs. 50.7% (36/71), RR=0.88, 95%CI: 0.39-1.98, P=0.76];and the difference of incidence of adverse reactions between the 2 groups was not statistically significant [16.9% (39/231) vs. 19.2% (47/245), risk difference (RD)=-0.03, 95%CI: -0.10-0.04, P=0.44]. Meta analysis on the safety of arbidol in treatment for influenza and other respiratory virus infections showed that the incidence of adverse reactions in the arbidol group was significantly lower than that in the control group [5.9% (44/745) vs. 11.3% (82/726), RR=0.52, 95%CI: 0.37-0.74, P<0.01]. Conclusion(s): Arbidol could effectively increase the 2019-nCoV nucleic acid negative conversion rate and it might be safe to treat COVID-19 using arbidol.Copyright © 2020 by the Chinese Medical Association.

Distinct profiles and kinetics of soluble infammatory markers in patients with acute and chronic HCV-infections and SARS-CoV-2-infections: Implications for the long-term consequences of viral infections?

Background and Aims Viral infections occur acutely but can also progress chronically, with the immune system having a central role in immunopathoge-nesis. The question arises whether all alterations in immune responses are reversible after viral elimination (spontaneously or by therapy). Therefore, the aim of this study is to compare soluble infammatory markers (SIM) during and after infection with SARS-CoV-2 and acute and chronic HCV-infections. Patients and Method Patients with acute HCV (n = 29), chronic HCV (n = 54), SARS-CoV-2 (n = 39) and 31 healthy-controls were included. Blood samples were tested at baseline, end of treatment/infection, and follow-up ( >= 9 months after baseline). IL-12p70, IL-1b, IL-4, IL-5, IL-6, IL-8, TNF, IFN-g, IL-10, IL-22, CXCL-10, MCP-1, MIP-1b, ITAC were quantified using the HD-SP-X Imaging and Analysis SystemTM. Results SIM profiles in patients with acute HCV were substantially elevated at baseline and the decrease during follow-up was considerably less compared to the SARS-CoV-2 cohort. In chronic HCV-patients, viral elimination by therapy resulted in a decrease in SIM, although not always to those of controls. Cirrhotic HCV patients had higher SIM levels after HCV elimination than non-cirrhotic chronic HCV-patients. In the SARS-CoV-2 cohort, most SIM returned to levels of controls 3 months after baseline. Conclusions SIM profiles and kinetics after viral elimination difer between blood-borne acute and chronic HCV- and respiratory SARS-CoV-2-infections. The immunologic imprint 9 months after cured HCV-infection (both acute and chronic) appears to be more pronounced than after SARS-CoV-2-infection. Further analysis is needed to correlate the SIM profle with the clinical pheno-type (long-HepC vs. long-COVID-19).

Capturing Secchi disk depth by using Sentinel-2 MSI imagery in Jiaozhou Bay, China from 2017 to 2021

Water clarity is a key parameter for assessing changes of aquatic environment. Coastal waters are complex and variable, remote sensing of water clarity for it is often limited by low spatial resolution. The Sentinel-2 Multi-Spectral Instrument (MSI) imagery with a resolution of up to 10 m are employed to solve the problem from 2017 to 2021. Distribution and characteristics of Secchi disk depth (SDD) in Jiaozhou Bay (JZB) are analyzed. Subtle changes in localized small areas are discovered, and main factors affecting the changes are explored. Among natural factors, precipitation and wind play dominant roles in variation in SDD. Human activities have a significant influence on transparency, among which fishery farming has the greatest impact. This is clearly evidenced by the significant improvement of SDD in JZB due to the sharp decrease in human activities caused by coronavirus disease 2019 (COVID-19).Copyright © 2022 The Authors

Epidemic Spread Modeling for COVID-19 Using Cross-fertilization of Mobility Data

We present an individual-centric model for COVID-19 spread in an urban setting. We first analyze patient and route data of infected patients from January 20, 2020, to May 31, 2020, collected by the Korean Center for Disease Control & Prevention (KCDC) and discover how infection clusters develop as a function of time. This analysis offers a statistical characterization of mobility habits and patterns of individuals at the beginning of the pandemic. While the KCDC data offer a wealth of information, they are also by their nature limited. To compensate for their limitations, we use detailed mobility data from Berlin, Germany after observing that mobility of individuals is surprisingly similar in both Berlin and Seoul. Using information from the Berlin mobility data, we cross-fertilize the KCDC Seoul data set and use it to parameterize an agent-based simulation that models the spread of the disease in an urban environment. After validating the simulation predictions with ground truth infection spread in Seoul, we study the importance of each input parameter on the prediction accuracy, compare the performance of our model to state-of-the-art approaches, and show how to use the proposed model to evaluate different what-if counter-measure scenarios. IEEE

Knowledge ecosystem of financial markets: a new perspective on alleviating the supply-demand contradiction of the rural finance in the post-COVID-19 era

Purpose: This paper aims to establish a systematic cognition to alleviate the supply–demand contradiction in rural financial markets from an integrated perspective of knowledge management and proposes the concept of rural financial knowledge ecosystem (RFKE) to encourage multifaceted solutions. Design/methodology/approach: The authors qualitatively describe the process that the knowledge management dilemmas cause the supply–demand contradiction in the rural finance and further summarize a systematic methodology from three dimensions: the knowledge subject, the knowledge environment and the knowledge ecology. Findings: The authors list four types of knowledge management dilemmas leading to the supply–demand contradiction in the rural finance, i.e. the weak knowledge sharing, the poor knowledge flow, the slow knowledge updating and the imperfect knowledge environment. Meanwhile, the RFKE model consisting of the ecological subject, the ecological environment and the ecological regulation is also presented. Research limitations/implications: The role of knowledge management in improving the allocation of financial resources to various rural financial market participants (government, rural financial institutions, farmers, agricultural enterprises, etc.). Originality/value: The authors creatively give the RFKE model, which complements and enriches the theory of knowledge management. Meanwhile, relevant management practices are urgently needed under the macro circumstance of the COVID-19 pandemic and the rural revitalization in China. © 2022, Emerald Publishing Limited.