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This study analyzed the impact of COVID-19 outbreak and targeted required reserve ratio cut policy on stock returns of Chinese listed companies. This paper uses the data of 3,449 A-share listed companies from February 3, 2020 to December 31, 2020 for research, the empirical results showed that stock prices of private enterprises with stronger debt-paying ability and looser financing constraints, and state-owned enterprises with less supply chain credit risks performed better, in the central and western regions, enterprises with stronger solvency and looser financing constraints have better stock price performance during the early stages of pandemic. After the implementation of the targeted RRR cut policy, the stock prices of enterprises with poor solvency, private enterprises, and enterprises in central and western regions with strong financing constraints, state-owned enterprises, and enterprises in eastern region with high credit risks all showed significant reversals, and the stock prices reflected the effect of the targeted RRR cut policy in the short and medium term. Over time, the pandemic has been controlled, and the resumption of work and production has freed most enterprises from financial difficulties. However, due to sporadic outbreaks, large private enterprises and eastern enterprises with strong risk resistance and loose financing constraints enjoy better stock price performance. This study is helpful for enterprises to understand the value of financial flexibility and solvency and provides a reference for enterprises to make financial decisions: how to balance the benefits and costs of solvency. © Tian Wang, Fang Fang and Linhao Zheng, 2023.
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The aim of this study is to explore the preference of corporations for sponsorship motives and the impact of sponsorship motives on sponsoring intention in the post-epidemic era of COVID-19. Taking a Taiwanese company as a case study, a total of 60 expert groups comprising 300 respondents (the management of the sampled companies) were surveyed in the post-epidemic period, with data being collected from 60 sampled companies in February-May 2022. Data were analyzed by using two different functional approaches, including fuzzy preference relations (FPR) for the first survey (study 1) and structural equation model (SEM) for the second survey (study 2). Results reveal that corporate image is the most preferential motive of sponsorship and also demonstrates the most significant and positive influence on sponsoring intention. Meanwhile, the measured factor of performing corporate social responsibility (CSR) appears the most correlated with the construct of corporate image. Based on the results, the study can fully fill the gap between sponsorship motives and sponsoring intention in sponsorship knowledge. Additionally, the conjunction of FPR and SEM can also create methodological synergies, namely, enhancing complementary effects and achieving better holistic analysis. Findings also suggest that special attention should be paid to CSR, which plays a pivotal role in affecting the decision of corporations for sponsorship motives and sponsoring intention and, in a post-epidemic era, continuing to develop CSR actions to enhance corporate image can be the best strategy while facing internal and external challenges of implementing sustainable development (SD).
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The COVID-19 pandemic has caused a severe global problem of ventilator shortage. Placing multiple patients on a single ventilator (ventilator sharing) or dual patient ventilation has been proposed and conducted to increase the cure efficiency for ventilated patients. However, the ventilator-sharing method needs to use the same ventilator settings for all the patients, which cannot meet the ventilation needs of different patients. Therefore, a novel multivent system for non-invasive ventilation has been proposed in this study. The close loop system consists of the proportional valve and the flow-pressure sensor can regulate the airway pressure and flow for each patient. Multiple ventilation circuits can be combined in parallel to meet patients’ventilation demands simultaneously. Meanwhile, the mathematical model of the multivent system is established and validated through experiments. The experiments for different inspired positive airway pressure (IPAP), expired positive airway pressure (EPAP), inspiratory expiratory ratio (I:E), and breath per minute (BPM) have been conducted and analyzed to test the performance of the multivent system. The results show that the multivent system can realize the biphasic positive airway pressure (BIPAP) ventilation mode in non-invasive ventilation without interfering among the three ventilation circuits, no matter the change of IPAP, EPAP, I:E, and BPM. However, pressure fluctuation exists during the ventilation process because of the exhaust valve effect, especially in EPAP control. The control accuracy and stability need to be improved. Nevertheless, the novel designed multivent system can theoretically solve the problem of ventilator shortage during the COVID-19 pandemic and may bring innovation to the current mechanical ventilation system. Author
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This work utilizes Sentinel-2A L1C remote sensing photographs from the years 2018, 2020, and 2022 to identify the different land use categories in the study area using the support vector machine (SVM) technique. The accuracy of categorization is greater than 90%. This research explores four factors of the dynamic change in land use in Hongta District from 2018 to 2022: the proportion of various types of land;the extent of something like the changing land usage;land use transfer;and the dynamic degree of the change in land use. According to the study's results, the proportion of cultivated and grassland land grew, while the quantity of barren and construction land fell by 1.90 percent, 0.03 percent, and 0.69 percent, respectively. The water system land portion of total area increased by 2.58 percent and 0.13 percent, respectively. After comparing the two research periods, the entire dynamic degree of the second stage is determined to be 3.5 percent lower than that of the first stage, and the pace of land use change is quite sluggish, which may be associated with the worldwide COVID-19 outbreak in 2020. The outcomes of the research may give the natural resources department the knowledge it needs to manage land resources properly. © 2023 SPIE.
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This case analyzes how Zalora has applied various strategies to gain a sustainable advantage in the e-commerce industry and provide solutions that continuously add value for its customers, even during the COVID-19 pandemic. It describes the company's efforts to capitalize on customer demand and external and internal forces to be more agile and nimble in an increasingly competitive environment. Zalora has introduced several technologies that reflect its digitization, digitalization, and digital transformation efforts. The use of digital technologies has helped Zalora to capture and analyze relevant data from its business processes and customer interactions. The information and automation generated by the technologies have enabled Zalora to continuously improve and reinvent itself to stay ahead of the competition. The challenges and opportunities of digital transformation are also discussed. © 2023, American Accounting Association. All rights reserved.
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Project objective: Despite the recent revolution in immune checkpoint inhibitors (ICIs), only modest improvement in overall survival and likely caused by not enough potent cellular immunity among BC patients. Our lab has been focus on inducing cellular immunity against HER2+ BC through vaccination against the tumor-associated antigen HER2. Approximately 20 years ago, we performed an experimental pilot study by administrating HER2 peptide and recombinant protein pulsed dendritic cells (DC vaccine) to six patients with refractory HER2+ advanced or metastatic (stage II (>= 6 +LN), III, or stage IV) BC. We followed the patients on 2019 found that all of the six patients were still alive, 18 years after vaccination. Their blood sample were analyzed with cytometry by time-offlight (CyTOF) and found there is a significantly increased presence of CD27 expressing memory T cells in response to HER2 peptide stimulation. Recent report on the SARS-CoV2 mRNA vaccine also suggested that CD27 expressing memory T cells plays a critical role in long-lasting cellular immunity against SARS-CoV2 infection. Therefore, we hypothesized that CD27 plays a critical role in cellular immunity against BC, and the stimulation of CD27 expressing T cells with mAb targeting CD27 significantly increase the cellular immunity triggered by vaccination against tumor-associated antigen. Result(s): We recapitulate the rise of CD27+ antigen specific T cells among the vaccinated patients using a transgenic mouse model expressing human CD27. When combined the adenoviral-vector based HER2 (Ad-HER2) vaccination with a single dose of human aCD27 antibody (Varlilumab), we found there is a robust increase in the HER2 specific T cells compared to vaccination alone, especially CD27+CD44+ memory CD4 T cells, even after 120 days post vaccination. Using an ICIinsensitive syngeneic HER2+ BC models, we found 50% of mice in the combination group of aCD27 antibody plus Ad-HER2 showed total tumor regression by the end of study. When combined with anti-PD1 antibody, the combination of AdHER2 and Varlilumab leads to total tumor regression in 90% of tumor bearing mice with syngeneic HER2+ BC, indicating that the vaccination against tumor associated antigen HER2 plus anti-CD27 antibody sensitized ICI-insensitive HER2+ BC toward ICI. Conclusion(s): Our data demonstrates that the administration of anti-CD27 antibody significantly increase the long term presence of CD27+ antigen specific memory T cells after vaccination against tumor associated antigen HER2. As consequence, combination of anti-CD27 with HER2 sensitized the immune unresponsive breast cancer toward anti-PD1 antibody. Our study suggests that the vaccination against tumor-associated antigen with mAb targeting CD27 leads to the robust cellular immunity, which is required for successful ICIs against breast cancer.
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During the global efforts to prevent and control the COVID-19 pandemic, extensive research and development of SARS-CoV-2 vaccines using various technical approaches have taken place. Among these, vaccines based on adenovirus vector have gained substantial knowledge and experience in effectively combating potential emerging infectious diseases, while also providing novel ideas and methodologies for vaccine research and development (R&D). This comprehensive review focuses on the adenovirus vector technology platform in vaccine R&D, emphasizing the importance of mucosal immunity induced by adenoviral vector-based vaccine for COVID-19 prevention. Furthermore, it analyzes the key technical challenges and obstacles encountered in the development of vaccines based on the adenovirus vector technology platform, with the aim of providing valuable insights and references for researchers and professionals in related fields.
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Background: Infancy is an important developmental period when the human microbiome is shaped. Given links between young age at antiretroviral treatment (ART) initiation and smaller persisting viral reservoirs, we hypothesized that earlier ART initiation may leave distinct microbial signatures in the oral cavity detectable in children living with HIV (CLWH). Method(s): Oral swab samples were collected from 477 CLWH and 123 children without HIV at two sites in Johannesburg, South Africa. CLWH had started ART < 2 years of age with 60% starting < 6 months of age. Most were wellcontrolled on ART at a median of 10 years of age when the swab was collected. Controls were age-matched and recruited from the same communities. Sequencing of the V4 amplicon of the 16S rRNA gene was done using established protocols. DADA2, decontam, and phyloseq were used for sequence inference, contaminant removal, and subsequent analyses. All p-values were adjusted for multiple testing using Benjamini-Hochberg false discovery rate method. Statistical analyses were performed with R. Result(s): CLWH had lower alpha diversity than uninfected children (Shannon index p< 0.0001). Genus-level abundances of Granulicatella, Streptococcus and Gemella were greater and Neisseria and Haemophilus were less abundant among CLWH compared to uninfected children. Associations were strongest among boys. There was no evidence of attenuation of associations with earlier ART initiation. In fact, decreased bacterial diversity and differences in taxa abundances in CLWH versus controls were consistent regardless of whether ART was started before or after 6 months of age. Shifts in genus-level taxa abundances relative to uninfected controls were most marked in children on regimens containing lopinavir/ritonavir;with few shifts seen if on regimens containing efavirenz. Conclusion(s): A distinct profile of less diverse oral bacterial taxa was observed in school-age CLWH on ART versus uninfected age-matched children suggesting persisting interference of HIV and its treatments on microbiota in the mouth. Any effects of earlier ART initiation were not detectable at this age. Studies of treated adults with HIV have observed similar shifts in taxa abundances. Oral microbiota have been linked to salivary cytokine levels with associations between Granulicatella and IL-8 and Neisseria and IL-6. Declines in Neisseria abundances in oral samples have been associated with more severe outcomes in influenza and COVID-19.
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The sudden outbreak of COVID-19 has dealt a huge blow to traditional education and training companies. Institutions use the WeChat platform to attract users, but how to identify high-quality users has always been a difficult point for enterprises. In this paper, researchers proposed a classification algorithm based on SMOTE and the improved AdaBoost, which fuses feature information weights and sample weights to effectively solve the problems of overfitting and sample imbalance. To justify the study, it was compared with other traditional machine-learning algorithms. The accuracy and recall of the model increased by 19% and 36%, respectively, and the AUC value reached 0.98, indicating that the model could effectively identify the user's purchase intention. The proposed algorithm also ensures that it works well in spam identification and fraud detection. This research is of great significance for educational institutions to identify high-quality users of the WeChat platform and increase purchase conversion rate.
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Surface longwave downward radiation (LWDR) is a key factor affecting the surface energy balance. The daily LWDR and the diurnal variations of LWDR are of great significance for studies of climate change and surface processes. How to obtain LWDR at an averaged temporal scale from instantaneous LWDR is one of the longstanding problems in the field of radiation budget from remote sensing. In this paper, two temporal upscaling methods are introduced, namely, a method based on the diurnal variations of LWDR (diurnal variation based, DVB) and a method based on random forest regression (RFR). The results reveal that: (1) The DVB method has a global hourly and daily LWDR root-mean-square error (RMSE) of less than 21 W/m2 and 15 W/m2, respectively, and the RMSE of the daily LWDR based on RFR is less than 7 W/m2;(2) When compared with four existing statistical interpolation methods, the DVB method can not only ensure the accuracy, but also can overcome the problem of missing samples and/or an abnormal samples during upscaling;(3) Except for directly predict daily LWDR, the DVB methods can also obtain more accurate LWDR diurnal variations such as hourly, half-hourly etc. The RFR method enables high-efficiency and accurate estimation of daily averaged LWDR from instantaneous measurements. Compared with existing methods and products, the proposed methods are not only efficient, but also have a superior applicability and reliable accuracy. The proposed strategies provide new ideas for the community in estimating LWDR at continuous temporal scales from remotely sensed measurements.
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The demand for same-day delivery (SDD) has increased rapidly in the last few years and has particu-larly boomed during the COVID-19 pandemic. The fast growth is not without its challenge. In 2016, due to low concentrations of memberships and far distance from the depot, certain minority neighborhoods were excluded from receiving Amazon's SDD service, raising concerns about fairness. In this paper, we study the problem of offering fair SDD service to customers. The service area is partitioned into differ-ent regions. Over the course of a day, customers request for SDD service, and the timing of requests and delivery locations are not known in advance. The dispatcher dynamically assigns vehicles to make de-liveries to accepted customers before their delivery deadline. In addition to overall service rate ( utility ), we maximize the minimal regional service rate across all regions ( fairness ). We model the problem as a multi-objective Markov decision process and develop a deep Q-learning solution approach. We introduce a novel transformation of learning from rates to actual services, which creates a stable and efficient learn-ing process. Computational results demonstrate the effectiveness of our approach in alleviating unfairness both spatially and temporally in different customer geographies. We show this effectiveness is valid with different depot locations, providing businesses with an opportunity to achieve better fairness from any location. We also show that the proposed approach performs efficiently when serving heterogeneously wealthy districts in the city.(c) 2022 Elsevier B.V. All rights reserved.
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This study investigates the effect of social media (SM) use purposes and user characteristics on individual psychological wellbeing (PWB) during the coronavirus pandemic (COVID-19). Informed by the uses and gratifications theory and PWB research, this study analyzed survey data collected from 282 SM users aged 18 through 59 from a minority-serving university in the United States in March-April 2020. Our quantitative data analysis showed that social media can be used to improve the quality of personal experiences during the COVID-19 crisis through three mechanisms-connectedness (i.e., social), engagement (i.e., collaborative), and entertainment (i.e., hedonic). However, the effect varied by gender, SM usage level, and individual concern about COVID-19 risk. The findings contribute to the literature and offer implications in technology use for enhancing public mental health during crises. © 2023 IEEE Computer Society. All rights reserved.
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Introduction: The COVID-19 pandemic has created a chronically stressful work environment for healthcare workers, increasing the negative psychological effects experienced. Aim(s): The authors of this systematic review and meta-analysis aimed to assess the impact of COVID-19 on frontline healthcare workers' mental health, using various psychological outcomes. Method(s): A systematic literature search was conducted up until June 30th, 2022 on MEDLINE, EMBASE, CINAHL, Cochrane Library, Web of Science, ClinicalTrials.gov, and Dissertations and Theses. Result(s): This meta-analysis includes 22 cross-sectional studies with a total of 32,690 participants. Anxiety (ES = 0.23, CI: [0.18, 0.28]), depression (ES = 0.17, CI: [0.10, 0.24]), PTSD (ES = 0.28, CI: [0.08, 0.48]), and stress (ES = 0.35, CI: [0.17, 0.53]) was significantly prevalent among frontline healthcare workers. Conclusion(s): Our results suggested that European healthcare workers were experiencing high psychological symptoms associated with the COVID-19 pandemic. The monitoring of their psychological symptoms, preventative interventions, and treatments should be implemented to prevent, reduce, and treat the worsening of their mental health.Copyright © 2023 The Authors. Published by Semmelweis University, Institute of Mental Health, Budapest.
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Since inflation of commodities is becoming more and more severe recently caused by many macro events, such as COVID-19 and Russian-Ukrainian conflict, systemic risk of commodity futures market is getting more attention from academic and industrial areas. Instead of using external factors to explain this risk as previous researches, we explain it by internal topology and structures of commodity futures market. This method helps us understand its key driving factors and their different impact to Chinese and international commodity futures markets. © 2023 Elsevier Inc.
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To evaluate the predictive value of early warning scores for intensive care unit (ICU) admission in patients with coronavirus disease 2019 (COVID-19). For COVID-19 patients who were admitted to Shijiazhuang People's Hospital from January 2021 to February 2021, national early warning score (NEWS), national early warning score 2 (NEWS2), rapid emergency medicine score (REMS), quick sepsis-related organ failure (qSOFA), altered consciousness, blood urea nitrogen, respiratory rate, blood pressure, and age-65 (CURB-65) were used to evaluate the inpatient condition and the predictive value for ICU admission. A total of 368 patients were included, and 32 patients (8.7%) were transferred to the ICU. The median age was 49.0 (34.0,61.0) years. The scores of NEWS, NEWS2, REMS, and CURB-65 were 1 (0, 2), 1 (0, 2), 4 (2, 6) and 0 (0, 1), respectively. The receiver operating characteristic (ROC) cure (AUC) was used to evaluate the predictive value in detecting patients who are at risk of being transferred to the ICU. Area under the ROC AUC of NEWS was 0.756, sensitivity 65.6%, and specificity 71.3%. ROC AUC of NEWS2 was 0.732, sensitivity 62.5%, and specificity 61.3%. ROC AUC of REMS was 0.787, sensitivity 84.4%, and specificity 64.6%. ROC AUC of CURB-65 was 0.814, sensitivity 81.3%, and specificity 76.8%. The predictive value of NEWS and NEWS2 combined with age were significantly improved. The ROC AUC of NEWS combined with age was 0.885, sensitivity 85.1%, and specificity 75.0%. The ROC AUC of NEWS2 combined with age was 0.883, sensitivity 84.2%, and specificity 75.0%. NEWS and NEWS2 combined with age can be used as a predictive tool for whether COVID-19 patients will be admitted to the ICU.
Subject(s)
COVID-19 , Humans , Middle Aged , Aged , Retrospective Studies , Hospitalization , Intensive Care Units , ROC Curve , Prognosis , Hospital MortalityABSTRACT
In order to improve the cure rate of critically ill patients in Wuhan epidemic area and reduce the fatality rate, the state have dispatched medical staffs from the whole country to support Wuhan and treat critically ill patients in dedicated facilities. A medical team from the First Affiliated Hospital of Xi'an Jiaotong University, consisting of 133 medical staffs major in critical care medicine, respiralogy, infection, cardiology, and general surgery, entirely took over the critical care unit of the East Hospital of the Renmin Hospital of Wuhan University, and formed a multidisciplinary collaboration team with local medical staffs to treat patients together. Up to March 13th in 2020, the author's medical team has admitted a total of 109 patients, of which 48 had been discharged up on recovery. Critically ill patients with Corona Virus Disease 2019 mainly have elder age, comorbidities, complicated conditions, and difficult diagnosis and treatment. The author and the author's team combined with clinical practice, share experience and strategies of general surgery related issues in the treatment of critically ill patients, providing reference for collegues in general surgery.Copyright © 2020 by the Chinese Medical Association.
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COVID-19 has resulted in the increased use of distance learning around the world. With the advancement of information technology, traditional classroom teaching has gradually integrated the Internet and distance learning methods. Students need to be able to learn on their own in a distance learning environment, so their ability to self-regulate their learning in a distance learning environment cannot be ignored. However, in previous studies on self-regulated learning, most learners learn alone. When they have academic doubts, they cannot obtain help and support from their studies, resulting in reduced learning outcomes. This study uses the peer self-disciplined learning mechanism to establish a distance teaching system that assists students and to improve their own learning status by meeting with peers at a distance. It can also help learners orient themselves by observing their peers' learning status and goal considerations. The participants in this study were 112 college students in the department of information management. The control group used a general self-regulated teaching system for learning, and the experimental group used a distance learning system, incorporating peer self-regulated learning. The results of the study found that learners who used the distance peer learning mechanism were more effective than those who used the general distance self-regulated learning system;learners who used the distance peer-regulated learning mechanism had better motivation, self-efficacy, and reflection after the learning activity than those who used the general distance self-regulated learning system. In addition, with the aid of such mechanisms, learners' cognitive load can be reduced, and learning effectiveness can be improved. © 2023 by the authors.
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The COVID-19 pandemic period brings huge uncertainty, especially for the real estate sector. On the one hand, restrictions on the mobility of a population, decline in travel demands, popularization of remote work and education models caused doubts among investors questioning the future of the sector and the functions of real estate. On the other hand, the large supply of cash after the first waves of the pandemic and the upcoming increase in inflation resulted in many investors boldly investing cash in real estate, considering them as assets of stable value. This research aims to analyze the processes of value migration among real estate companies listed on the Warsaw Stock Exchange during this turbulent process. We analyzed the changes in the main drivers of value and the migration rates of the real estate sector based on data for 2018, 2019, 2020 and Q3 2021. The first period of the pandemic is the time of the collapse of the main profitability factors, sales and profitability of sales decline in the entire sector. However, the financial pillars of the analyzed companies are stable and we are not seeing signs of liquidity problems or a significant increase in debt. The second year of the pandemic is a significant reflection of most of the drivers of value, often to levels higher than those observed before the pandemic. Investors seem to remain insensitive to turbulent changes in accounting measures of effectiveness. We observe the relative stability of market measures. The processes of the migration of values from and to the sector do not show significant changes when comparing the periods before and during the pandemic. We observe various intensities of the studied phenomena in various groups of the real estate segment. © 2023 Michał J. Kowalski1 et al., published by Sciendo.