Coronavirus disease 2019 vaccination in patients with autoimmune diseases.

Benifits outweigh the risks for patients with autoimmune disease (AID) in remission period to be vaccinated with coronavirus disease 2019 (COVID-19) vaccines. The mRNA vaccines, inactivated vaccines, and recombinant protein subunit vaccines are safe for AID patients, whereas the safety of recombinant adenovirus vector-based vaccines is still uncertain. Some drugs for the treatment of AID may reduce the immune response of the body to the COVID-19 vaccines and affect the immune efficacy of the vaccine, which may be related to the timing of vaccination. Based on several published relevant guidelines and recommendations for the COVID-19 vaccines in AID patients, this article elaborates on vaccination problems to be paid attention to in patients with AID treated with different drugs.Copyright © 2021 by the Chinese Medical Association.

An End-to-End Knowledge Graph Based Question Answering Approach for COVID-19

Question Answering based on Knowledge Graph (KG) has emerged as a popular research area in general domain. However, few works focus on the COVID-19 kg-based question answering, which is very valuable for biomedical domain. In addition, existing question answering methods rely on knowledge embedding models to represent knowledge (i.e., entities and questions), but the relations between entities are neglected. In this paper, we construct a COVID-19 knowledge graph and propose an end-to-end knowledge graph question answering approach that can utilize relation information to improve the performance. Experimental result shows that the effectiveness of our approach on the COVID-19 knowledge graph question answering. Our code and data are available at https://github.com/CHNcreater/COVID-19-KGQA. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Research progress on the analysis of active ingredients and elements in Fritillaria ussuriensis Bulbus

Fritillaria ussuriensis Bulbus, a genuine medicinal material of Northeast China, is the dry bulb of Fritillaria ussuriensis Maxim. It contains various active ingredients, such as alkaloids, alkaloids glycosides, adenosines, polysaccharides, and trace elements . It has antitussive, eliminating phlegm, antiasthmatic, antiulcer, antiplatelet aggregation, and anti-inflammatory. The qualitative and quantitative analysis of alkaloids, polysaccharides, nucleosides, and trace elements in Fritillaria ussuriensis Bulbus were reviewed, which is helpful for its cultivation and accurate application, and would provide a new choice for the treatment of coronavirus disease 2019 (COVID-19). © 2022

FANG-COVID: A New Large-Scale Benchmark Dataset for Fake News Detection in German

As the world continues to fight the COVID-19 pandemic, it is simultaneously fighting an ‘infodemic’ – a flood of disinformation and spread of conspiracy theories leading to health threats and the division of society. To combat this infodemic, there is an urgent need for benchmark datasets that can help researchers develop and evaluate models geared towards automatic detection of disinformation. While there are increasing efforts to create adequate, open-source benchmark datasets for English, comparable resources are virtually unavailable for German, leaving research for the German language lagging significantly behind. In this paper, we introduce the new benchmark dataset FANG-COVID consisting of 28,056 real and 13,186 fake German news articles related to the COVID-19 pandemic as well as data on their propagation on Twitter. Furthermore, we propose an explainable textual- and social context-based model for fake news detection, compare its performance to "black-box" models and perform feature ablation to assess the relative importance of human-interpretable features in distinguishing fake news from authentic news. © 2021 Association for Computational Linguistics.

How a Successful Implementation and Sustainable Growth of e-Commerce can be Achieved in Developing Countries;a Pathway Towards Green Economy

Apart from the goal of the digital world and other benefits of e-commerce, it becomes the need of time during this COVID-19 pandemic. Successful implementation and sustainable growth of e-commerce in developing countries is a challenge. The goal of the digital world without the implementation and sustainable growth of e-commerce in developing countries is incomplete. Based on UTAUT theory, we have developed an integrated model to study the developing countries' consumers' adoption intentions towards e-commerce. We collected a valid useable sample of 796 respondents from a developing country, applied the SEM-ANN two-step hybrid approach to testing the proposed hypothesis, and ranked the antecedents according to their importance. Results revealed that Trust in e-commerce, Perceived risk of using e-commerce, Ease of use in e-commerce, Curiosity about e-commerce, Facilitating Conditions, and Awareness of e-commerce benefits influence the adoption intentions of developing countries' consumers. Sensitivity analysis results revealed that Ease of use in e-commerce platforms and awareness of e-commerce benefits are the two most crucial factors behind the adoption intentions in developing countries. The study's findings help authorities adopt sustainable e-commerce, multinational companies effectively market their goods online, and academics better understand how inhabitants of developing nations perceive e-commerce.

Joint Crypto-Blockchain Scheme for Trust-Enabled CCTV Videos Sharing

The declaration of COVID-19 as pandemic affected almost all public and private functionaries by enforcing them to operate remotely, and the judiciary is no exception. The trend seems to continue for the foreseeable future. The judicial proceedings where a piece of evidence, particularly the digital one, holds undisputed importance. Its preservation and intact transmission to the jury have gained an enhanced significance in this era which is highly susceptible to manipulation. This research proposes joint encryption and blockchain-based solution for immutable decentralised evidence management for CCTV footage. The permissioned chain of evidence system is implemented using Hyperledger Fabric to ensure the validity of the video metadata. The hash values are calculated on videos (recorded per session) and stored in the blockchain, while Region of Interest (ROI) based selective encryption of videos adds optimized security to individuals' privacy and protects from illegal access of stored videos. The experimental results provide a proof of concept that the proposed scheme facilitates the remote court services by maintaining a legal chain of evidence for CCTV videos. © 2021 IEEE.

TAX-B2BREC: Multi-Stage Cascade Downstream Company Recommender System Based on Taxation Data

The public crisis triggered by the COVID-19 pandemic has disastrous effects for B2B markets. With the supply chain and trade disrupted, the benefits of the company have been affected to varying degrees. In order to help companies find potential customers and recover the supply chain, we propose a multi-stage cascade downstream company recommender system based on taxation data. The proposed system can recommend potential buyers for upstream companies, which can help upstream companies find new sales channels. This system includes data processing, matching module, ranking module and system deployment. In the match module, we propose a hybrid recall algorithm to generate the candidate enterprises. In the ranking module, we use DCNV2 model to rank the candidate companies. Moreover, the multistage cascade recommendation algorithm achieves better results compared with the traditional algorithm in B2B recommender system. © 2021 IEEE.

Privacy-Preserved Credit Data Sharing Integrating Blockchain And Federated Learning For Industrial 4.0

The rapidly increasing volume of user credit-related data generated by connected devices in the Industrial Internet of Things (IIoT) paradigm opens up new possibilities for improving the quality of service for emerging applications through credit data sharing. However, security and privacy issues (such as credit data leakage) are significant barriers to credit data providers and applications sharing their data in wireless networks. Leakage of private credit data can lead to serious problems, not only in terms of financial loss for the data provider, but also in terms of illegal use of personal credit data. In particular, the economic recovery after the global COVID-19 pandemic has further boosted the demand for efficient, secure credit models for Industry 4.0, which could alleviate the potential credit crisis under financial pressure. IEEE

Coronavirus disease 2019 vaccination in patients with autoimmune diseases

Benifits outweigh the risks for patients with autoimmune disease (AID) in remission period to be vaccinated with coronavirus disease 2019 (COVID-19) vaccines. The mRNA vaccines, inactivated vaccines, and recombinant protein subunit vaccines are safe for AID patients, whereas the safety of recombinant adenovirus vector-based vaccines is still uncertain. Some drugs for the treatment of AID may reduce the immune response of the body to the COVID-19 vaccines and affect the immune efficacy of the vaccine, which may be related to the timing of vaccination. Based on several published relevant guidelines and recommendations for the COVID-19 vaccines in AID patients, this article elaborates on vaccination problems to be paid attention to in patients with AID treated with different drugs. Copyright © 2021 by the Chinese Medical Association.

Industry 4.0 smart reconfigurable manufacturing machines

This paper provides a fundamental research review of Reconfigurable Manufacturing Systems (RMS), which uniquely explores the state-of-the-art in distributed and decentralized machine control and machine intelligence. The aim of this review is to draw objective answers to two proposed research questions, relating to: (1) reconfigurable design and industry adoption;and (2) enabling present and future state technology. Key areas reviewed include: (a) RMS - fundamentals, design rational, economic benefits, needs and challenges;(b) Machine Control - modern operational technology, vertical and horizontal system integration, advanced distributed and decentralized control;(c) Machine Intelligence - distributed and decentralized paradigms, technology landscape, smart machine modelling, simulation, and smart reconfigurable synergy. Uniquely, this paper establishes a vision for next-generation Industry 4.0 manufacturing machines, which will exhibit extraordinary Smart and Reconfigurable (SR*) capabilities.

Are You Speaking with a Mask? An Investigation on Attention Based Deep Temporal Convolutional Neural Networks for Mask Detection Task

When writing this article, COVID-19 as a global epidemic, has affected more than 200 countries and territories globally and lead to more than 694,000 deaths. Wearing a mask is one of most convenient, cheap, and efficient precautions. Moreover, guaranteeing a quality of the speech under the condition of wearing a mask is crucial in real-world telecommunication technologies. To this line, the goal of the ComParE 2020 Mask condition recognition of speakers subchallenge is to recognize the states of speakers with or without facial masks worn. In this work, we present three modeling methods under the deep neural network framework, namely Convolutional Recurrent Neural Network(CRNN), Convolutional Temporal Convolutional Network(CTCNs) and CTCNs combined with utterance level features, respectively. Furthermore, we use cycle mode to fill the samples to further enhance the system performance. In the CTCNs model, we tried different network depths. Finally, the experimental results demonstrate the effectiveness of the CTCNs network structure, which can reach an unweighted average recall (UAR) at 66.4% on the development set. This is higher than the result of baseline, which is 64.4% in S2SAE+SVM nerwork(a significance level at p<0.001 by one-tailed z-test). It demonstrates the good performance of our proposed network. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Screening of anti-SARS-CoV-2 small molecular compounds from traditional Chinese medicine based on molecular docking

Objective: Based on the targets of SARS-CoV-S/ACE2 complex and SARS-CoV-2 Mpro hydrolase, we screened the binding blockers of SARS-CoV-2-ACE2 and inhibitors of SARS-CoV-2 Mpro hydrolase from TCMSP database as precursors to guide the discovery of new drugs from small molecules of traditional Chinese medicine (TCM) against SARS-CoV-2. Methods: According to the literature reports, the active sites of the crystal structure model of SARS-CoV-S/ACE2 complex protein and SARS-CoV-2 Mpro hydrolase were determined, and the small molecular compounds from TCMSP database were virtually screened using LibDock molecular docking technology. The screening results were optimized by combining the LibDock Score with the interaction mode between the compounds and the targeting receptor protein, and then the small molecular compounds of TCM which have the potential activity of anti-SARS-CoV-2 were obtained. Results: ASP38, GLN42, GLN325, GLU329, TYR436, TYR491 on the binding surface of SARS-CoV-S/ACE2 complex protein and THR24, THR25, THR26, LEU27, ASN28, ASN119 in the structure of Mpro hydrolase were identified as the key amino acids for molecular docking. Twenty candidate SARS-CoV-2-ACE2 binding blockers which can form hydrogen bond with key amino acids were screened by molecular docking, and the docking effect of four components mainly from Gardeniae Fructus, Glycyrrhizae Radix Et Rhizoma, Sophorae Tonkinensis Radix Et Rhizoma and Daturae Flos with the targeting protein was better than others. Thirty-four candidate SARS-CoV-2 Mpro hydrolase inhibitors which can form hydrogen bond with key amino acids were also screened, and the docking effect of four components mainly from Zingiberis Rhizoma, Rhizoma Dioscoreae Bulbiferae, Cimicifugae Rhizoma and Capsella Bursa-pastoris with the targeting protein was better than others. Kanzonol E from Glycyrrhizae Radix Et Rhizoma and kryptogenin from Rhizoma Dioscoreae Bulbiferae could interact with the largest number of key amino acids or form the most hydrogen bonds with the targeting protein respectively, and had the best molecular docking effect. Conclusion: Four candidate SARS-CoV-2-ACE2 binding blockers and four candidate SARS-CoV-2 Mpro hydrolase inhibitors from TCM have the potential activity of anti-SARS-CoV-2, among which priority can be given to kanzonol E, a component of Glycyrrhizae Radix Et Rhizoma, and kryptogenin, a component of Rhizoma Dioscoreae Bulbiferae, for further discovery of anti-SARS-CoV-2 new drugs.