Exploring the Effect of Social Media and Spatial Characteristics During the COVID-19 Pandemic in China

The declaration of COVID-19 as a pandemic has largely amplified the spread of related information on social platforms, such as Twitter, Facebook and WeChat. In this work, we investigate how the disease and information co-evolve in the population. We focus on COVID-19 and its information during the period when the disease was widely spread in China, i.e., from January 25th to March 24th, 2020. The co-evolution between disease and information is explored via the spatial analysis of the two spreading processes. We visualize the geo-location of both disease and information at the province level and find that disease is more geo-localized compared to information. High correlation between disease and information data is observed, and also people care about the spread of disease only when it comes to their neighborhood. Regard to the content of the information, we obtain that positive messages are more negatively correlated with the disease compared to negative and neutral messages. Additionally, two machine learning algorithms, i.e., linear regression and random forest, are introduced to further predict the number of infected using characteristics, such as disease spatial related and information-related features. We obtain that both the disease spatial related characteristics of nearby cities and information-related characteristics can help to improve the prediction accuracy. The methodology proposed in this paper may shed light on new clues of emerging infections prediction. © 2013 IEEE.

Investor sentiment and the Chinese new energy stock market: A risk–return perspective

The new energy industry is crucial for solving the problem of pollution, and its development requires support from the stock market. This paper proposes a Chinese investor sentiment index based on the Long Short-Term Memory (LSTM) deep learning method, and investigates the effect of investor sentiment on new energy stock returns as well as value at risks (VaR) behavior before and during COVID-19. It also compares these effects on traditional energy companies to identify differences between the new energy and traditional companies. The empirical results show that investor sentiment has significant effects on stock returns and VaR of both new and traditional energy companies but the effects are stronger in the new energy industry. The effects of investor sentiment have increased during COVID-19, and investors pay more attention on risks than returns during COVID-19. These results provide guidance for small and medium-sized investors in China to optimize their investment strategies and alleviate losses associated with extreme risks. © 2022 Elsevier Inc.

Keep concentrated and carry on: redesigning supply chain concentration in the face of COVID-19

The global COVID-19 outbreak has led to significant challenges for supply chain management, while insights on how to configure the supply chain network to respond to this crisis are limited. Therefore, the present research extends the understanding of supply chain resilience by investigating whether supply chain concentration has influenced the shock of COVID-19 on firm performance. This study assesses four sub-dimensions of supply chain concentration: supplier, customer, product, and region. Based on a large-scale sample of Chinese listed manufacturing firms, we employed a difference-in-difference approach to investigate whether supply chain concentration ameliorated or exacerbated the shock of COVID-19. The results indicate that treatment groups (firms with lower supplier, customer, product, and region concentration) have experienced a considerably more significant performance deterioration than control firms. Overall, this study paves the way for future research and offers vital insights into the redesign of supply chains in response to COVID-19 and similar crises. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

Are commodity futures a hedge against inflation? A Markov-switching approach

This study examines the inflation hedging ability of various commodity futures using Markov-switching vector error correction models (MS-VECM). We find that total commodity futures fail to provide a hedge against inflation over the sample period between January 1983 and December 2021. However, industrial metals and precious metals are able to hedge against inflation. Other sub-indexes, including energy, agriculture, and livestock, do not have a significant inflation hedging ability. The inflation hedging capacity of industrial metals exhibits substantial variation over time, with most of the inflation hedging power occurring during the relatively longer and more common regimes covering the Great Moderation, the post-subprime crisis, and the periods after the outbreak of the COVID-19 pandemic. We further evaluate the inflation hedge ability of commodity futures by including stocks and bonds in the model. Our results suggest that industrial metals are more reliable inflation hedges. © 2023 Elsevier Inc.

Using the big data analysis and basic information from lecture Halls to predict air change rate

School lecture halls are often designed as confined spaces. During the period of COVID-19, indoor ventilation has played an even more important role. Considering the economic reasons and the immediacy of the effect, the natural ventilation mechanism becomes the primary issue to be evaluated. However, the commonly used CO2 tracer gas concentration decay method consumes a lot of time and cost. To evaluate the ventilation rate fast and effectively, we use the common methods of big data analysis - Principal Component Analysis (PCA), K-means and linear regression to analyze the basic information of the lecture hall to explore the relation between variables and air change rate. The analysis results show that the target 37 lecture halls are divided into two clusters, and the measured 11 lecture halls contributed 64.65%. When analyzing the two clusters separately, there is a linear relation between the opening area and air change rate (ACH), and the model error is between 6% and 12%, which proves the feasibility of the basic information of the lecture hall by calculating the air change rate. © 2023 Elsevier Ltd

A systems view of responding to the COVID-19 pandemic: A causal loop model for Taiwan's approach

Since the worldwide outbreak of the COVID-19 pandemic in December 2019, Taiwan has successfully stopped the spread of COVID-19. The policies and works of the epidemic control are a complex and dynamic process. This study applied the methodology of system dynamics to explore the structure of the COVID-19 epidemic control system in Taiwan and analysed its system behaviours. The results show that the system is composed of key subsystems, such as national health insurance and quarantine, combined with government policies. Joint efforts among the central and local governments and the general public have been made to strengthen the quarantine of border entrants, encourage the public to wear masks and employ technology for contact tracing and tracking down those being tested positive with COVID-19. Together with the efficient increase in the capacity of testing and medical treatments, these measures can effectively reach a balance between epidemic control and economic activities. © 2022 John Wiley & Sons, Ltd.

Evolution Characteristics and Influencing Factors of Global Dairy Trade

There are imbalances and uncertainties in the global supply and demand of dairy products, owing to the adverse influence of overall economic changes, dairy prices, agricultural politics, the COVID-19 pandemic, and severe climate. This paper aims to explore the evolving characteristics and influencing factors of the global dairy trade pattern and make recommendations for the sustainable development of the global dairy trade. This paper studies the evolutionary characteristics of the global dairy trade pattern from the perspective of the overall structure, individual characteristics, and core–periphery structure through complex network analysis (CNA), using the countries involved in dairy trade from 2000 to 2020. Furthermore, this study explores the influencing factors of the dairy trade network using a quadratic allocation procedure (QAP). The results indicate that the global dairy trade network has been expanding, with prominent scale-free features and small-world characteristics. Individual countries display obvious heterogeneity, whereas the core import regions of the dairy shift from Europe, East Asia, and America to North America, the Middle East, and East Asia. Contrary to this, there is no significant change in the core export regions. Consequently, the entire dairy trade network represents a clear core–periphery structure. Moreover, the income per capita gaps, geographic distance gaps, and common language always affect the trade value and dairy trade relations across the countries. Meanwhile, economic level gaps and regional trade agreements have become increasingly significant. Thus, the dairy trade may not follow the "border effect”. Lastly, this paper also extends recommendations for the sustainable development of the dairy trade. © 2023 by the authors.

Infrared Spectroscopy Study on Temperature Characteristics of Several Common Antibiotics and Therapeutic COVID-19 Drugs

The far infrared (1 similar to 10 THz) and mid-infrared (400 similar to 4 000 cm(-1)) spectra of six common antibiotics (Ofloxacin capsules, Ofloxacin tablets, Norfloxacin capsules, Azithromycin tablets, Roxithromycin tablets and Levofloxacin hydrochloride tablets), three antiviral drugs for COVID-19 (Ribavirin tablets, Abidol hydrochloride tablets and Chloroquine phosphate tablets) and an expectorant drug (Ambroxol hydrochloride tablets) within shelf-life were studied. The effects of vehicles and another high temperature environment (65 degrees C) on the structure and crystal form of drugs were simulated and fed back to the changes in infrared spectra. After two months of continuous experiments, it was found that the structure and crystal form of other drugs had hardly changed except in ambroxol hydrochloride tablets. When capsule drugs were placed in high-temperature environment for a long time, the epidermis would become brittle and easy to rupture, but the efficacy of internal drugs had hardly changed. Taking fluoroquinolone antibiotics (Ofloxacin and Norfloxacin) as examples, combined with density functional theory (DFT) and the potential energy distribution (PED) method, the theoretical infrared spectra of the two antibiotics monomers, polymers and crystals were calculated by Crystal 14 and Gaussian 16 software with B3LYP/6-311++G(d,p) basis set. The vibrational modes and their contribution rates corresponding to all characteristic peaks were obtained, and the experimental spectrum was accurately identified. It was also found that from monomer to polymer and then to crystal, the stacking force (pi-pi interaction) between lattices accounted for the largest proportion of inter-molecular interaction, more than 90%. Therefore, the theoretical calculation was more consistent with the experimental results only when the crystal with periodic boundary conditions was taken as the initial configuration. The vibrational modes in the far infrared band mainly came from the collective vibration of molecules (vibration accounts for more than 99%, rotation and translation account for less than 1%), and the out-of-plane bending caused by inter-molecular hydrogen bond and Van der Waals force contributes the most, more than 90%. In the mid-infrared band, there were also a certain proportion of inter-molecular interactions. For example, the peaks of norfloxacin at 1 440 cm(-1) and ofloxacin at 1 524 cm(-1) can only be reproduced in the theoretical spectrum with the crystal as the configuration, respectively, from the collective vibration and the stretching of O-H center dot center dot center dot O bonds.

Differential expression and immune correlation analysis of COVID-19 receptor ACE2 and TMPRSS2 genes in all normal and tumor tissues.

The outbreak of COVID-19 seriously affected people's life and safety, and it has not been effectively controlled all over the world at present. The binding of S protein of SARS-COV-2 virus to ACE2 receptor requires the assistance of Transmembrane Serine Protease 2 (TMPRSS2), which can activate the S protein on the surface of virus and promote its binding to the ACE2 receptor. With the continuous accumulation of experience in the treatment of COVID-19 patients and the experimental studies of a large number of scientific researchers, it was found that COVID-19 patients had a higher mortality rate in patients with underlying diseases. Therefore, for COVID-19 patients with tumors, the mortality rate may be significantly higher than other people. Clinical studies had found that some patients were complicated with cytokine storm in clinical treatment, which was also the direct cause of death for some patients. The infiltration of immune cells and the release of a variety of cytokines were important factors causing cytokine storm. Therefore, for COVID-19 patients with tumors, it was of great clinical significance to explore the relationship between COVID-19 virus receptor ACE2, TMPRSS2 and immune cell infiltration, which can help clinicians to make some more appropriate treatment plans.

Evidence for elevated psychiatric distress, poor sleep, and quality of life concerns during the COVID-19 pandemic among U.S. young adults with suspected and reported psychiatric diagnoses.

We report distress levels and functional outcomes based on self-reported pre-existing mental health conditions among U.S. young adults (N=898) during the COVID-19 pandemic (April 13-May 19, 2020). Depression, anxiety, and PTSD symptoms, as well as COVID-19-related concerns, sleep problems, and quality of life were compared across the following pre-existing mental health groups: 1) no diagnosis, 2) suspected diagnosis, 3) diagnosed and untreated, and 4) diagnosed and treated. Compared to those without a diagnosis, the likelihood of scoring above the clinical threshold for those with a diagnosis - whether treated or not - was more than six-fold for depression, and four-to six-fold for anxiety and PTSD. Individuals with a suspected diagnosis were 3 times more likely to score above the clinical threshold for depression and anxiety and 2 times more as likely to score above this threshold for PTSD compared to those with no diagnosis. We also present higher levels of COVID-19-related worry and grief, poorer sleep, and poorer reported health-related quality of life among those with either a suspected or reported mental health diagnosis. Findings provide evidence of vulnerability among individuals with a mental health diagnosis or suspected mental health concerns during the initial weeks of the COVID-19 pandemic.

Attach importance to research and development of Chinese materia medica based on prevention and control needs of SARS-CoV-2 infection

In the first 20 years of the new century, two times of coronavirus “visiting” China has become a public health emergency, which has attracted great attention at home and abroad. At the critical time of epidemic prevention and control in SARS-CoV-2 infection, the excellent achievements of traditional Chinese medicine (TCM) show the advantages and contributions of TCM. In view of the complexity of the symptoms of patients with coronavirus infection, the diversity of organ and tissue damage and functional damage or failure, how to adapt to the needs of clinical prevention and treatment is not only a problem of modern medicine, but also a problem of TCM. In this review article, the authors combed the research of TCM prescription and single medicine after understanding the cause of coronavirus infection and pathogenicity and multiple organ dysfunction and failure caused by coronavirus. Based on the emphasis on the TCM scientific research and application, the TCM therapeutic effect on SARS-CoV-2 infection is discussed. The framework of new drug research and development based on possible “target” is proposed, and we put forward the ideas for researching new TCM products through the expanding molecular mechanism of infection.