Research on machine learning-based epidemic impact on Social Electricity Consumption model

This paper uses social electricity consumption data from 2015-2021 in a city in Hubei province, and uses some methods of artificial intelligence, for example, python function fitting and machine learning to construct an impact analysis and prediction model of the COVID-19 epidemic on Electricity Consumption. Through comparison with the effects of general linear regression and polynomial regression, a better model is developed which comprises four independent variables and uses polynomial regression. The model developed in this paper helps to quantify and measure the impact of the epidemic on society's electricity consumption, and ultimately enables users in the electricity industry to make convenient and rapid forecasts, helping them to make reasonable power supply plans, trading plans and dispatch plans, and to ensure safe and economic operation of the Electricity System. © 2022 ACM.

Let the Big Data Speak: Collaborative Model of Topic Extract and Sentiment Analysis COVID-19 Based on Weibo Data

Micro-blog is an important medium of emergency communication. The topic and emotion analysis of micro-blog is of great significance in identifying and predicting potential problems and risks. In this paper, a collaborative analysis model of emotion and topic mining is constructed to analyze the users’ sentiment and the topics they care about, Firstly, we use SO-PMI to construct domain sentiment lexicon and extract topics with LDA. Then we use the collaborative model to analyze sentiment and topic. The results showed that the model we proposed can present the features of sentiment and topic of user concerns. And through text clustering and sentiment analysis, it is found that the attitude of users towards the COVID-19 has gone through three stages, namely, a period of fluctuating tension and anxiety, a period of slowly rising solidarity and a period of stable self-confidence with little fluctuation, on the whole, positive is greater than negative, positive than negative state. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

The Restorative Effects of Virtual Reality Forests on Elderly Individuals During the COVID-19 Lockdown

This study focuses on the restorative effects of immersive virtual reality (VR) forest experiences on elderly people during the COVID-19 lockdown. A field experiment with 63 elderly participants was conducted in an elderly care institution in China. The results showed that a five-minute VR forest experience with three minutes of subsequent reliving can bring immediate psychological improvements (i.e., increased positive affect, decreased negative affect, and enhanced stress recovery) to elderly individuals. The negative affect decrease and stress recovery enhancement were more obvious among introverted individuals. Furthermore, participating in three VR forest experiences over three consecutive days can bring continuous psychological improvements. Moreover, short VR forest experiences were unable to significantly decrease the blood pressure of participants. The effects of three VR experiences over three days on blood pressure improvement were also nonsignificant. Additionally, VR forest experiences can increase elderly participants' intentions to undertake real forest therapy.

[Research on the influence of coronavirus infection on maternal and infant health].

COVID-19 spreads with strong infectivity and triggered a public health crisis, home and abroad. SARS-CoV-2 has high pathogenic homology with SARS-CoV and MERS-CoV, and the three coronaviruses all belong to the Betacoronavirus family. Due to pregnant women's physical and psychological vulnerability, they are the susceptible and high-risk groups during the epidemic. This article will review the reports on adverse effects of maternal and fetal health during the SARS and MERS and COVID-19 epidemics to provide evidence for the clinical management and prevention and control of pregnant cases in SARS-CoV-2 infection.

The legitimacy of the Contactless teaching influence on student's learning efficiency in colleges and universities: From COVID- 19 epidemic perspective

The COVID-19 epidemic has impacted the normal opening of Chinese universities in the spring of 2020. 'Contactless' teaching can solve the contradiction between the epidemic's high infectivity and the high aggregation of students' study and life in colleges and universities, and become the guarantee for the normal operation of schools at all levels during the epidemic. However, the 'contactless' teaching model has a crisis of legitimacy. It is necessary to construct the legitimacy of 'contactless' teaching, that is, to realize the legalization process, so as to make students have the intrinsic motivation of full participation and improve their learning efficiency. © 2020 IEEE.

[A special on epidemic prevention and control: precautions in ophthalmic practice in the prevention and control of the novel coronavirus pneumonia epidemic].

This article was published ahead of print on the official website of Chinese Journal of Ophthalmology on March 2, 2020. Prevention and control of novel coronavirus pneumonia is now the top priority, and the protection of the eyes in the fight against the epidemic has also been an issue of great concern. Based on the latest progress made in basic and clinical research and practical experience in epidemic prevention and control, this article delivers objective guidance on whether the eye is a route of transmission of novel coronavirus infection, the precautions that should be taken by ophthalmologists in clinical practice during the epidemic, the novel coronavirus infection in the eyes and its clinical manifestation, and the public health education on eye protection, so as to provide valuable evidence for the scientific prevention and control of the epidemic and developing targeted countermeasures. (Chin J Ophthalmol, 2020, 56: 330-332).

[Epidemiological analysis on 1 052 cases of COVID-19 in epidemic clusters].

Objective: To understand the epidemiological characteristics of the cases of COVID-19 epidemic clusters, and explore the influence of family factors and social factors such as group activities on the spread of the disease. Methods: The data of cases of COVID-19 epidemic clusters from 19 January, 2020 to 25 February, 2020 were collected from the official platforms of 36 cities in 6 provinces in China. Descriptive statistical methods, χ(2) test and curve fitting were used to analyze the epidemiological characteristics of the clustered cases. Results: By 25 February, 2020, the data of 1 052 cases in 366 epidemic clusters were collected. In these clustered cases, 86.9%(914/1 050) occurred in families. Among the 1 046 cases with gender information, 513 were males (49.0%) and 533 were females (51.0%). The cases were mainly young adults between 18 and 59 years old, accounting for 68.5% (711/1 038). In the 366 epidemic clusters , the clusters in which the first confirmed cases with the history of sojourn in Wuhan or Hubei accounted for 47.0%(172/366). From 19 January to 3 February, 2020, the first confirmed cases with Wuhan or Hubei sojourn history accounted for 66.5%. From 4 to 25 February, the first confirmed cases who had Wuhan or Hubei sojourn history accounted for only 18.2%. The median of interval between the first generation case onset and the second generation case onset was 5 (2-8) days. The median of onset- diagnosis interval of the initial cases was 6 (3-9) days, and the median of onset-diagnosis interval of the secondary cases was 5 (3-8) days. Conclusions: Epidemic clusters of COVID-19 were common in many cities outside Wuhan and Hubei. Close contact in family was one of the main causes for the spread of household transmission of the virus. After 4 February, the epidemic clusters were mainly caused by the first generation or second generation cases in local areas, and the time for diagnosis became shorter.

[Healing the schism between public health and medicine, promoting the integration of prevention and treatment].

It has been nearly 30 years since the publication of "Healing the Schism: Epidemiology, Medicine, and the Public's Health" by Professor Kerr L. White. Although scholars have been calling for strengthening the integration of public health and clinical medicine in Chinese medical education and eliminating barriers between public health professionals and clinicians, these effects are not obvious. The epidemic situation of COVID-19 has become an open course for Chinese citizens on the treatment, prevention and control of infectious diseases. Consequently, the public has higher expectations on the modernization of public health governance, and the social atmosphere of bridging the gap between public health and clinical medical education has been establishing. In the future, when combating with novel infectious diseases and public health emergencies, the response capacity of public health system and treatment capacity of clinical system in China will be significantly improved, and the situation of insufficient integration of medical treatment and prevention is bound to be reversed.