Corporate ESG and resilience of stock prices in the context of the COVID-19 pandemic in China

The COVID-19 pandemic has had a significant impact on both the financial market and the real economy, leading to widespread concern about the relationship between environmental, social, and governance (ESG) responsibilities and shareholders' wealth. This paper examines the relationship between ESG responsibility and stock returns in the context of the COVID-19 pandemic and investigates the impact of ESG responsibility on stock price resilience. The results indicate that corporate ESG scores have positive impacts on stock returns during and after the COVID-19 crisis, with the positive impacts of ESG being more significant in the post-crisis period. Among the different ESG dimensions, environmental responsibility (ESG_E) has a more significant impact on stock returns, while social responsibility (ESG_S) and governance responsibility (ESG_G) have mixed impacts during the crisis. Furthermore, during and after the outbreak of COVID-19, the positive impacts of ESG are more pronounced among firms located in low-trust regions and firms with lower analyst coverage. Additionally, the study finds that corporate ESG responsibility help restore the resilience of stock prices during the crisis, with better ESG performance leading to stronger stock price resilience. Overall, the results strongly support the conclusion that ESG has acted as an "equity vaccine” during the COVID-19 pandemic. © 2023 Elsevier B.V.

Do financial asset holdings affect investor expectations under negative events? The shock of COVID-19 pandemic

Holding excessive financial assets will lead to corporate financialization, making investors underestimate its risks in front of extreme benefits and the "reservoir effect” in boom periods, especially in rapid-growing emerging economies. Few studies have explored the investors' real perceptions and attitudes towards such risks when dealing with unexpected shocks. The 2019 novel coronavirus disease (COVID-19) provides new insights into these questions. Using event study method, this study examines how investors react to corporate financialization in the risk-release condition. First, we find that firms with more financial asset holdings experience significant lower market return during the COVID-19 pandemic. Second, we find that the pandemic-induced drop in stock returns is milder when firms hold more low-liquidity or safe financial assets, have higher solvency, are less exposed to COVID-19 pandemic and have better information environment. These findings show that the investors' attitude is widely negative towards corporate financialization when the negative shock comes and strong financial flexibility and good corporate governance can alleviate the risk. It implicates that the hidden risks of corporate financialization can be perceived by investors and responded by "voting with their feet” and the managers should be alert to it rather than just seeking financial benefits. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Assessment of residual chlorine in soil microbial community using metagenomics

Chlorine-containing disinfectants have been widely used around the world for the prevention and control of the COVID-19 pandemic. However, at present, little is known about the impact of residual chlorine on the soil micro-ecological environment. Herein, we treated an experimental soil-plant-microbiome microcosm system by continuous irrigation with a low concentration of chlorine-containing water, and then analyzed the influence on the soil microbial community using metagenomics. After 14-d continuous chlorine treatment, there were no significant lasting effect on soil microbial community diversity and composition either in the rhizosphere or in bulk soil. Although metabolic functions of the rhizosphere microbial community were affected slightly by continuous chlorine treatment, it recovered to the original status. The abundance of several resistance genes changed by 7 d and recovered by 14 d. According to our results, the chlorine residue resulting from daily disinfection may present a slight long-term effect on plant growth (shoot length and fresh weight) and soil micro-ecology. In general, our study assisted with environmental risk assessments relating to the application ofchlorine-containing disinfectants and minimization of risks to the environment during disease control, such as COVID-19. © 2022, Higher Education Press.

Bridging the Social Distance: Offline to Online Social Support during the COVID-19 Pandemic

The severe impact of COVID-19 in the United States has forced many students to replace in-person socialization with online digital contact. In this study, we investigate the mental health impacts associated with this shift by examining properties of online interactions that may affect loneliness and perceived social support. Students were surveyed (N=827) across 97 universities across the US during their first full semester impacted by the COVID-19 pandemic (Fall 2020). Private online interactions (messaging, phone call, video call) were found to have a comparable correlation to social support as face-To-face interactions, but public online interactions (social media) were associated with more negative outcomes. Among private platforms, messaging had the strongest correlation with social support;and daily self-disclosure over messaging yielded social support levels that were 1.21x higher than rarely or never disclosing over this platform. We speculate that factors such as the level of privacy and peoples' feelings of control contributed to disclosure and perceived social support in online platforms. © 2022 ACM.

An Epistemic Trend or a Digital Pitfall? De-Westernizing Media and Communication Studies in Digital China

Governments hiding facts and truth from the public seems to have become a common phenomenon, especially during the social crisis in China. The practice of the public using various media to express dissent and opinions, to overcome government censorship, appears to contribute to freedom of speech. Inspired by widespread online articles during the COVID-19 pandemic in 2020, this paper argues that the flaws in this logic are the dualism, which digital media created (pro-democracy vs authoritarian;freedom vs control), in understanding media in China. By borrowing the discussion of the de-westernization of media and communication studies, the paper argues that the introduc-tion of digital media makes de-westernized studies in China harder because it prompts us to think "digitally."

Unlocking private investment as a new determinant of green finance for renewable development in China

The COVID-19 pandemic has pushed up the green finance for renewable energy development. Private investment has been recognized as a dominant driver of the renewable energy industry, an essential and critical step in averting greenhouse gas emissions. Nonetheless, despite the increasing pace, private investment in green finance for renewable development is still restricted to several developed nations, where it is crucial. Prior studies have offered some understanding of the complexities and challenges that investment confronts in this industry, which remains underexplored in the case of China. This study employs the ARDL-PMG model used to examine the public listed companies in Shanghai and Shenzhen during China's 2010–2020 period. This research adds to the body of knowledge by rigorously examining the variables on FDI in renewable energy production in China and how these effects differ depending on the source of investment. Some of these factors include the adoption of national renewable energy legislation, the supply of foreign public money, and the broader economic environment. The findings indicate that worldwide financial assistance, legislative support policies, feed-in tariffs, and economic stability are potent drivers of green finance for developing renewable energy investment in China. Further, this research explains that the impacts of private sector investment and entrepreneurial contextual factors on expenditure vary depending on the source of finance, emphasizing the importance of dissecting investment spreads to fully comprehend private investment decisions in green finance for renewable development. © 2022

Study on specific antibodies in patients infected with SARS-CoV-2 and recipients of inactivated vaccine

Objective To detect the serum levels of SARS-CoV-2-specific IgM and IgG antibodies in patients infected with SARS-CoV-2 and recipients of inactivated vaccine in different periods for understanding their variation patterns in vivo. Methods Chemiluminescence immunoassay was used to detect the levels of SARS-CoV-2-specific IgM and IgG antibodies in 144 serum samples of 44 COVID-19 patients, 381 serum samples of 118 asymptomatic infected cases and 398 serum samples of 273 inactivated vaccine recipients collected at different periods. The results were statistically analyzed together with basic characteristics and vaccination status. Results The positive rates of IgM antibody in COVID-19 patients, asymptomatic infected cases and inactivated vaccine recipients were 52. 27% (23 / 44), 23. 73% (28 / 118) and 14. 29% (39 / 273). The positive rate of IgM antibody was higher in COVID-19 patients than in asymptomatic infected cases and vaccine recipients (χ2 = 12. 106, P = 0. 001;χ2 = 34. 755, P<0. 001). The positive rates of IgG antibody in the three populations were 100. 00% (44 / 44), 97. 46% (115 / 118) and 98. 81% (166 / 168), and the differences were not statistically significant (χ2 = 2. 944, P = 0. 229). In COVID-19 patients, the concentration of IgM antibody in <40 years old group was lower than that in ≥40 years old group (Waldχ2 = 6. 609, P = 0. 010), and the concentration of IgG antibody in patients with vaccination was higher than that in patients without vaccination (Waldχ2 = 12. 402,P<0. 001). In asymptomatic infected cases, the concentration of IgG antibody was higher in people with vaccination than in those without vaccination (Waldχ2 = 4. 530, P = 0. 033). In SARS-CoV-2 vaccine recipients, the concentration of IgG antibody in <40 years old group was higher than that in ≥40 years old group (Waldχ2 = 9. 565, P = 0. 002). Dynamic analysis of antibody levels showed that from week 1 to week 9, the concentrations of IgM and IgG antibodies in COVID-19 patients were higher than those in asymptomatic infected cases and vaccine recipients. Conclusions The concentrations of IgM and IgG antibodies in COVID-19 patients were higher than those in asymptomatic infected cases and inactivated vaccine recipients. COVID-19 patients aged ≥40 years had higher level of IgM antibody. COVID-19 patients and asymptomatic infected cases who had received vaccination had higher concentration of IgG antibody. Inactivated vaccine showed good immunogenicity after whole course of immunization, and the IgG antibody level in <40 years old group was higher.

An APT Malware Classification Method Based on Adaboost Feature Selection and LightGBM

Advanced Persistent Threat (APT) attack activities with the theme of COVID-19 and vaccine are also growing rapidly. The target of APT attack has gradually expanded from government agencies to vaccine manufacturers, medical industry and so on. What's more, APT groups have a strict organizational structure and professional division of labor and malware delivered by the same APT groups are similar. Classifying malware samples into known APT groups in time can minimize losses as soon as possible and keep relevant industries vigilant. In our paper, we proposed a multi-classification method of APT malware based on Adaboost and LightGBM. We collect real APT malware samples that have been delivered by 12 known APT groups. The API call sequence of each APT malware is obtained through the sandbox. For the relationship between adjacent APIs, we use TF-IDF algorithm combined with bi-gram. Then, Adaboost algorithm is used to select out the important API features, which form the target feature subset. Finally, we use the above subset combined with LightGBM ensemble algorithm to train multiple classifiers, named Ada-LightGBM. The experimental results show that our method is superior to the single Adaboost and LightGBM method. The classifier has good recognition performance for the test samples. © 2021 IEEE.

Sars-Cov-2 Antibody Decay Monitoring in mRNA Vaccinated Multiple Myeloma Patients

Introduction: Amid the current COVID-19 pandemic, the highest mortality rates are among the elderly and immunocompromised. Multiple myeloma (MM) patients are immunocompromised and often are elderly. Not only do MM patients develop more frequent infections, but it is one of the leading causes of death for these patients. This population develops more severe COVID-19 due to various mechanisms that impair their ability to fight infection. This also reduces their ability to generate immunity from vaccination, as has been demonstrated by their diminished responses to vaccines for various respiratory illnesses. It follows that while phase III trial results for mRNA1273 and BNT162b2 COVID-19 vaccines showed an efficacy of 94-95% against even mild infection with this virus, the efficacy has been shown to be lower among MM patients. We recently evaluated patients' antibody responses to vaccination for COVID-19 by measuring anti-spike IgG levels in patient serum from before vaccination (baseline) and two weeks after dose 2 (D2W2) of vaccination with mRNA-1273 or BNT162b2, and found that most MM patients have impaired responses (Stampfer et al., Leukemia 2021). Patients who received mRNA-1273 vaccine had higher antibody levels than those who were vaccinated with BNT162b2, and specific clinical and myeloma-related characteristics predicted vaccine responsiveness. In the current study, we are monitoring anti-spike IgG antibody levels at Dose 2 Week 8 (D2W8) and Dose 2 Week 16 (D2W16) post-mRNA vaccination among these patients and in age-matched healthy controls to investigate antibody decay. Methods: Participants in the trial included MM patients (n=91) at the Berenson Cancer Center, and age-matched healthy controls (n=27). Healthy subjects were not known to be immunocompromised or currently receiving immunosuppressive therapy. Vaccination was done outside of the clinic and subjects provided copies of their CDC-issued COVID-19 vaccination cards to confirm dosing dates. Sera from vaccinated individuals were drawn at baseline (0-60 days prior to first vaccine dose) and at intervals following their second dose (14-21, 56-70, and 112-126 days post-vaccination). Background levels were determined from the clinic's serum bank of healthy subjects drawn pre-April 2019. Using an ELISA-based assay that detects IgG antibodies to SARS-CoV-2 spike protein, we determined Anti-SARS-CoV-2 spike ectodomain serum antibody levels and quantified them in IU/mL based on the WHO International Standard 20/136. Results: We analyzed the patient and control populations, and specifically for those classified as responders from our original published study (D2W2 >50 IU/mL). All controls but only 70% of patients (64/91) were classified as responders, so this responder-specific analysis was only relevant for patients. There was a significant decline in anti-SARS-CoV-2 spike antibodies from D2W2 to D2W8 for both patients and controls;D2W16 results are pending. Median values dropped from 283.1 IU/mL to 90.9 IU/mL among patients, and 893.6 IU/mL to 354.4 IU/mL among controls. Median antibody levels among patients classified as responders dropped from 482.9 IU/mL to 145.5 IU/mL (p <0.0001). We also found that the D2W8 value for patients was significantly lower than that of controls (90.9 IU/mL vs 354.4 IU/mL, p<0.0001), as well as among the responder group (145.5 IU/mL vs 354.4 IU/mL, p=0.0005). A cutoff of <147 IU/mL has previously been associated with an increased risk for breakthrough infections. Spike antibody levels of 50% of patients who responded and 64.8% of all patients were <147 IU/mL at D2W8, whereas only 7.4% of controls were <147 IU/mL (p<0.0001). Conclusions: The markedly lower anti-spike antibody levels among MM patients compared to healthy controls at week 8 post-vaccination indicate that they remain at high risk for breakthrough infections. Combined with their rapid decline in anti-spike antibody levels over only a 6-week period, this indicates that even MM patients who responded initially to vaccination are likely to require boosters sooner tha healthy individuals. This immunocompromised population remains at high risk even following vaccination and should continue to maintain social distancing precautions during periods of high local SARS-CoV-2 transmission. Disclosures: No relevant conflicts of interest to declare.

The Time Variation in Risk Appetite and Uncertainty

We formulate a dynamic no-arbitrage asset pricing model for equities and corporate bonds, featuring time variation in both risk aversion and economic uncertainty. The joint dynamics among cash flows, macroeconomic fundamentals, and risk aversion accommodate both heteroskedasticity and non-Gaussianity. The model delivers measures of risk aversion and uncertainty at the daily frequency. We verify that equity variance risk premiums are very informative about risk aversion, whereas credit spreads and corporate bond volatility are highly correlated with economic uncertainty. Our model-implied risk premiums outperform standard instruments for predicting asset excess returns. Risk aversion is substantially correlated with consumer confidence measures and in early 2020 reacted more strongly to new COVID cases than did an uncertainty proxy.

Reaserch and implementation of social distancing monitoring technology based on SSD

In the fight against the Covid-19, social distancing has proven to be a very effective measure to mitigate the spread of the disease. As resumption of work, production and classes accelerates, it is necessary to limit people's social distance to reduce the rate of the virus spread. To solve this problem, a method for monitoring social distancing based on SSD object detection technology is proposed in this study. This method utilizes SSD300 model to detect people in a video or picture, and labels a Red Line as warning on the people whose distances are less than the default one, implementing real-time social distancing monitoring, and the mAP reaches 88.44%. © 2021 The Authors. Published by Elsevier B.V.

A data capture model and its associate study on the public web published COVID-19 data

Background and Objective: The Coronavirus Disease 2019 pandemic situation is remaining severe worldwide. A single outbreak data source is not adequate for comprehensive analyses of the response to the pandemic. Such analyses need to seek proper integration of epidemic data for subsequent statistical analyses. Methods: 1) Considering reputations of publishers, activities, public users' accessibility, and retrievable historical data among several platforms, the World Health Organization (WHO), the US Centers for Disease Control (CDC), and Baidu's Real-time Epidemics (BRE) websites were selected as our data sources. 2) Data for 32 weeks until August 15th, 2020, were followed, including the US cumulative confirmed cases (CCCs), cumulative death cases (CDCs), cumulative discharged or cured cases (CD\vert CCs), daily new infective confirmed cases (DNCCs), and daily new death cases (DNDCs). 3) Estimators for the weekly current active infected confirm cases (CACs) and the weekly COVID19 fatal rate in the US hospitals (WFRUSH) were derived. Graphic display modules demonstrated the risks associated with demographic data. Results: 1) CCCs reached 5,285,546 cases in the US on August 15th, 2020, which initially climbed from the 9th-11th week;the CDCs were 167,546. The fatality rate initially climbed from the 12th-13th week, but fast turned over to decrease from the 18th week, then gradually flattened out near 3.17% till the mid of August 2020. 2) The WFRUSH first rose sharply at the 10th-11th week and started to decline in the 12th week, although there was a repeated smaller fluctuation in the 13th-14th week, during the generally downward process. 3) The US demographic characteristics and CDCs showed that the proportion of fatal cases in the senior Americans (age group over 65) accounted was 78.8%, about 4 (3.83) times the proportions of the other age groups. Supposed the death cases of seniors, directly caused by the COVID-19 rather than caused by the fundamental diseases, the \gamma value of the seniors, a ratio between the senior CDCs proportion over the senior population proportion was 4.81. Such a \gamma value for seniors, indicated a much higher fatality risk than other age groups. Conclusion: Integrative capture data from the publicly web-published COVID-19 statistics helps extend analyzable data and estimate or derive new-useful indicators CACs, WFRUSH, and \gamma value for the demographic group. As of the including the working population age of over 45, would have a much higher fatality rate than younger ages. It seemed necessary to study further if these death were caused directly by the COVID-19. Additionally, the African Americans, and male Americans, had relatively higher fatality rates. These high risks require more attention to strengthening health prevention;including the working-age population, even although the WFRUSH as a more appropriate and vital indication becomes stable to a low level after July 2020, meaning the clinical interventions and treatments were improved, or the virus fatality power was declined. © 2020 IEEE.

[Predictive value of combination of MRI tumor regression grade and apparent diffusion coefficient for pathological complete remission after neoadjuvant treatment of locally advanced rectal cancer].

Objective: Pelvic high-resolution magnetic resonance imaging (MRI) has now become a standard method for evaluating the efficacy of neoadjuvant treatment for locally advanced rectal cancer (LARC). However, this traditional morphological qualitative assessment method based on T2-weighted imaging (T2WI) is not effective in predicting pathological complete remission (pCR). The purpose of this study is to investigate whether combining the magnetic resonance tumor regression grade (mrTRG) with apparent diffusion coefficient (ADC) can improve diagnostic value for pCR after preoperative neoadjuvant chemoradiotherapy (nCRT) of LARC. Methods: This was a diagnostic study. Clinicopathological data of 134 LARC patients who received nCRT and radical surgery in the First Affiliated Hospital of Kunming Medical University from January 2017 to December 2019 were retrospectively analyzed. All the patients underwent MRI which included T2WI and DWI sequences before and 8 weeks after nCRT. Two radiologists independently drew ROIs on T2WI and DWI to estimate mrTRG stage and calculate the mean ADC value. Receiver operating characteristics (ROC) method was applied to evaluate the predict value of mrTRG combined with mean ADC value for pCR. Results: Of 134 LARC patients, 85 were male and 49 were female with median age of 58 (28-82) years. After nCRT, MRI suggested 21 patients (15.7%) had clinical complete remission (cCR), e.g. mrTRG stage 1-2. Postoperative pathology revealed 31 (23.1%) patients had pCR. The evaluations of mrTRG and ADC value by the two readers were highly consistent, and the intra-group correlation coefficients were 0.83 (95% CI: 0.703-0.881) and 0.96 (95% CI: 0.989-0.996), respectively. There was a negative correlation between mrTRG and pCR (r(s)=-0.505, P<0.01), and a positive correlation between mean ADC value and pCR (r(s)=0.693, P<0.01). The ROC curve showed that mrTRG alone had a medium predictive value for pCR, with an area under the curve (AUC) of 0.832 (95% CI: 0.743-0.921); the mean ADC value had a higher predictive value for pCR, with AUC of 0.906 (95% CI: 0.869-0.962). The predictive value of the combined model of mrTRG and ADC value for pCR was significantly better than that of mrTRG alone (P=0.015), and the AUC was 0.908 (95% CI: 0.849-0.968). Conclusion: Both mrTRG and mean ADC value can be non-invasive methods to predict the efficacy of nCRT for LARC. Combining the mean ADC value with mrTRG can result in better pCR prediction.