ABSTRACT
In the context of COVID-19, numerous people present their opinions through social networks. It is thus highly desired to conduct sentiment analysis towards COVID-19 tweets to learn the public's attitudes, and facilitate the government to make proper guidelines for avoiding the social unrest. Although many efforts have studied the text-based sentiment classification from various domains (e.g., delivery and shopping reviews), it is hard to directly use these classifiers for the sentiment analysis towards COVID-19 tweets due to the domain gap. In fact, developing the sentiment classifier for COVID-19 tweets is mainly challenged by the limited annotated training dataset, as well as the diverse and informal expressions of user-generated posts. To address these challenges, we construct a large-scale COVID-19 dataset from Weibo and propose a dual COnsistency-enhanced semi-superVIseD network for Sentiment Anlaysis (COVID-SA). In particular, we first introduce a knowledge-based augmentation method to augment data and enhance the model's robustness. We then employ BERT as the text encoder backbone for both labeled data, unlabeled data, and augmented data. Moreover, we propose a dual consistency (i.e., label-oriented consistency and instance-oriented consistency) regularization to promote the model performance. Extensive experiments on our self-constructed dataset and three public datasets show the superiority of COVID-SA over state-of-the-art baselines on various applications. IEEE
ABSTRACT
In this paper, we propose an analytical model that can analyze the impact of emergencies on open source software (OSS) development. As the core of this model, a metric system is used to comprehensively describe the OSS development process, which includes three dimensions: team activity, development activity, and development risk, with a total of 30 metrics. To demonstrate the effectiveness of the model, we construct an empirical study analyzing the impact of COVID-19 on OSS development. This study is based on the development process events between January 2019 and April 2022 belonging to 50 selected open source projects on GitHub. The results show that more than 72.4% of projects were negatively impacted following the COVID-19 outbreak. Interestingly, we observe that variants of covide-19 did not exacerbate its impact on software development. On the contrary, some project development activities have obviously resumed, indicating that the development team has adapted and gradually got rid of the impact of the epidemic. © 2022 IEEE.
ABSTRACT
Vehicular Ad-Hoc Networks (VANETs), as the crucial support of Intelligent Transportation Systems (ITS), have received great attention in recent years. With the rapid development of VANETs, various services have generated a great deal of data that can be used for transportation planning and safe driving. Especially, with the advent of Coronavirus Disease 2019 (COVID-19), the transportation system has been impacted, thus novel modes of transportation planning and intelligent applications are necessary. Digital twins can provide powerful support for artificial intelligence applications in Transportation Big Data (TBD). The features of VANETs are varying, which arises the main challenge of digital twins applying in TBD. Network traffic prediction, as part of digital twins, is useful for network management and security in VANETs, such as network planning and anomaly detection. This paper proposes a network traffic prediction algorithm aiming at time-varying traffic flows with a large number of fluctuations. This algorithm combines Deep Q-Learning (DQN) and Generative Adversarial Networks (GAN) for network traffic feature extraction. DQN is leveraged to carry out network traffic prediction, in which GAN is involved to represent Q-network. Meanwhile, the generative network can increase the number of samples to improve the prediction error. We evaluate the performance of our method by implementing it on three real network traffic data sets. Finally, we compare the two state-of-the-art competing methods with our method. IEEE
ABSTRACT
Background: COVID-19, caused by SARS-CoV-2, has spread worldwide and become a global pandemic. Objective(s): Studies of the earliest events of the COVID-19 pandemic are critical in understanding how the pandemic started and providing insight into the spread of SARS-CoV-2 and its infection in humans. Method(s): In this report, we studied the epidemiological characteristics of all 34 confirmed COVID-19 cases in Wuhu, China, from January 3 to March 19, 2020. Result(s): Our study indicated that cases in male patients (61.76%, 21/34) outnumbered those in female patients (38.24%, 13/34). Studies of the age distribution among the confirmed cases revealed that most COVID-19 patients were 15 to 59 years of age (26/34, 76%), while more than 14% (5/34) were >= 60 years old, and less than 9% (3/34) were <= 14 years old. Notably, 32 of the 34 confirmed cases were (a) people who had recently resided in or traveled to Wuhan or had close contact with Wuhan residents or visitors (22 cases);and (b) people who had close contact with these 22 confirmed COVID-19 patients (10 cases). Conclusion(s): This study revealed the epidemiological characteristics of COVID-19 outbreaks in Wuhu between January and March 2020 and provided insight into the earliest events of the COVID-19 pandemic in China. Our analyses suggested that the COVID-19 cases confirmed in Wuhu in 2020 were directly related to or originated from the outbreaks in Wuhan. Copyright © 2022, Author(s).
ABSTRACT
Personal protective clothing (PPC) protects healthcare workers from infectious diseases such as COVID-19;however, there are limited technologies regarding the production of breathable and adaptive thermo-responsive personal protective clothing, which can improve the wearers' comfort. In this chapter, the development of such breathable and adaptive thermo-responsive personal protective clothing is described, and recent trends in material development for preparing such clothing are also presented. This review chapter also considers related technology for the fabrication of such breathable and adaptive thermo-responsive personal protective clothing. Finally, the future outlook regarding personal protective clothing is discussed. © 2022 Elsevier Ltd. All rights reserved.
ABSTRACT
OBJECTIVE: Isatidis Radix is the dried root of Isatis indigotica Fortune of Cruciferae. As a representative traditional Chinese medicine for heat-clearing and detoxification, Isatidis Radix and its preparations are widely used in the prevention and treatment of all kinds of colds and have played an active role in the prevention and treatment of SARS, H1N1 and COVID-19. Although the chemical ingredient of Isatidis Radix has been studied deeply, there is no information bank, website or literature that can comprehensively query the information of all compounds at home and abroad, which is not conducive to the development of related research. So establishment of the chemical composition information bank is in need. METHODS: According to the category of chemical ingredients, the Chinese and English names, molecular formulas, exact molecular weights, structural formulas and references of nearly 400 chemical components in Isatidis Radix were comprehensively sorted out, and the chemical composition information bank of Isatidis Radix was constructed. RESULTS: By September 2020, a total of 392 compounds in 17 categories had been extracted, isolated and identified from Isatidis Radix. CONCLUSIONT: The established chemical composition information bank can provide the basis for the separation and identification of chemical components, quality control, material basis mining, network pharmacology research and so on. Copyright 2022 by the Chinese Pharmaceutical Association.
ABSTRACT
In December 2019, a novel coronavirus called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak was reported for the first time in Wuhan, Hubei province, China. This coronavirus has been referred as Coronavirus Disease 2019 or COVID-19 by World Health Organization (WHO). The spread of COVID-19 has become unstoppable, infecting around 93.5 million people worldwide, with the infections and deaths still increasing. Today, the entire planet has changed due to the greatest threat on the planet since the introduction of this lethal disease. This pandemic has left the world in turmoil and various measures have been taken by many countries including movement control order or lockdown, to slow down or mitigate the infection. Since the lockdown has been implemented almost in all affected countries, there has been a significant reduction in anthropogenic activity, including a reduction in industrial operations, vehicle numbers, and marine-related activities. All of these changes have also led to some unexpected environmental consequences. As a result of this lockdown, it had a positive and negative impact on the environment including the aquatic environment. Hence this review will therefore focus on the good and bad perspectives of the lockdown toward the aquatic environment. © 2021 Penerbit Universiti Kebangsaan Malaysia. All rights reserved.
ABSTRACT
Recently, COVID-19 has spread throughout China with new cases increasing abroad. Family physicians, a major provider of community medical services as well as the gatekeeper of residents' health, also play a vital role in the control and prevention of COVID-19.As their duties and working mechanism in combating COVID-19 are not completely clear yet, we tried to develop a sound working mechanism by comprehensively discussing and summarizing the deployment and role of family physicians in combating the epidemic, hoping to give full play of their role in doing the work based on maintaining sound physical and mental health with scientific self-protection, such as collaboratively identifying the suspected cases by screening the priority groups, standardizedly managing the isolated observational cases while managing contracted residents, and delivering individualized health education of COVID-19, by strengthening administrative management, clearing their duties, formulating a working procedure, strengthening the training before combating the epidemic, and caring for their physical and mental health. Copyright © 2020 by the Chinese General Practice.