ABSTRACT
The Covid-19 pandemic has caused a dramatic and parallel rise in dangerous misinformation, denoted an 'infodemic' by the CDC and WHO. Misinformation tied to the Covid-19 infodemic changes continuously;this can lead to performance degradation of fine-tuned models due to concept drift. Degredation can be mitigated if models generalize well-enough to capture some cyclical aspects of drifted data. In this paper, we explore generalizability of pre-trained and fine-tuned fake news detectors across 9 fake news datasets. We show that existing models often overfit on their training dataset and have poor performance on unseen data. However, on some subsets of unseen data that overlap with training data, models have higher accuracy. Based on this observation, we also present KMeans-Proxy, a fast and effective method based on K-Means clustering for quickly identifying these overlapping subsets of unseen data. KMeans-Proxy improves generalizability on unseen fake news datasets by 0.1-0.2 f1-points across datasets. We present both our generalizability experiments as well as KMeans-Proxy to further research in tackling the fake news problem. © 2022 IEEE.
ABSTRACT
Background: As COVID-19 is spreading rapidly, it is emotionally challenging for everyone. It has been observed that health-care workers come to play a major role and give their efforts to a greater extent in such situations. The studies have reported adverse psychological reactions to the 2003 severe acute respiratory syndrome outbreak among health-care workers. Hence, the study was planned to assess depression, anxiety, and stress among health-care professionals during the corona pandemic. Materials and Methods: A cross-sectional, observational study was carried out on health-care professionals working in the state of Maharashtra who were involved in the management of COVID-19 patients. Institutional ethical permission was taken before the study. The questionnaire was created to collect the data which having background information and the Depression, Anxiety, and Stress Scale-21. Data were entered into Microsoft Excel sheets and appropriate statistical analysis was done. Results: A total of 200 participants were included in the study. It was observed in our study that 51% of participants had depression, 38% had stress, and 49% had anxiety. Depression, anxiety, and stress were more among female health-care professionals than male professionals and it was statistically significant. It was found in our study that depression, anxiety, and stress were more in urban professionals than in rural health-care professionals, and the difference was statistically significant. Conclusion: As our study demonstrated a higher burden of depression, stress, and anxiety, early screening of health-care professionals and implementation of psychological interventions are essential for protecting and maintaining the functionality of the health-care system.
ABSTRACT
COVID-19 is a transmissible infection triggered by a coronavirus that has newly detected effect. Most patients infected by COVID-19 are undergoing minor to severe breathing disease and could able to recover without any therapy. Old persons, and others with underlying medical conditions such as cardiovascular, diabetes and so on are further prone to become disabled. The best measure to avert and slow down the transmission is to be informed about the COVID-19 virus, disease it causes and how it spreads. Protecting yourself and others from the infectious disease by washing hands or using an alcohol based sanitizer frequently and avoid touching face and most importantly, following social distancing in Public Places. The proposed detection tool was intended to warn users that a video feed will keep a shielded distance from each other. The camera’s video framework was used as an input and YOLOv3 algorithm for object detection is pre-trained. The distance between persons can be measured and a red frame shows any incompatible pair of persons. The result reveals that the method proposed can calculate metrics for social distance in videos among several persons. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
BACKGROUND: COVID-19 (corona virus) is a recently acknowledged disease. Corona is spreading quickly in the whole world At least 185 countries. Many cases from china. Covid-19 causes many death and abnormalities. mortality rate in covid-19 patient is low(1.4-2.3) but in diabetic patients have poor immune system and this a severe co-morbidity so mortality rate is high in Diabetic patients with covid-19. Diabetes mellitus refer as risk factor that arises with mortality and severity of covid-19 there's no absolute article and journals to direct the actual connection between diabetes mellitus and covid-19. So the aim of this study to sum up the confirmation About covid-19 and diabetes mellitus breakout all over a meta-analysis and systematic review. METHODS: A writing analysis was applied within detail of SCOPUS PUBMED, DIRECT SCIENCE, & SCIENCE related network. Monitoring analysis, studies of case- series and case reports on the diabetes mellitus in covid-19, were involved. RESULT: Some studies recommended such there are no notable differences in symptoms between diabetes mellitus with covid-19 and non-diabetic corona patients. In this patient acute Respiratory distress syndrome prognosis is poor. Death chances increase with age and seriousness of disease. Those people survive ARS. Some recover completely, while other Encounter lasting Damage of Lungs. Serious Manifestations and rate of death is higher between patients of diabetes mellitus and covid-19. In short this recommended the patient who suffering from diabetes or will be treated with H C Q antibiotics, anti- viral drugs. CONCLUSION: The analysis and the data of this study Convey such determinant condition of diabetes mellitus, which shows the high rate of mortality and severity among the patient who are suffering from covid-19 this article also provide us guidelines and criteria regarding diagnosis that can be convenient in the treatment and prevention of medical condition of the patient who is suffering from diabetes mellitus and covid-19. © The Electrochemical Society
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A highly efficient and scalable process for the synthesis of novoldiamine and hydroxynovaldiamine is accomplished from levulinic acid, which is easily accessible from the natural feedstock. These diamines are used as the key intermediates for the synthesis of chloroquine, hydroxychloroquine and mepacrine. The key steps involved in this process are the coupling of levulinic acid with secondary amine assisted by 1, 1'-carbonyldiimidazole and one-pot reduction of oxime-amide functional groups to get the corresponding diamine.
ABSTRACT
Introduction Nosodes, the homeopathic preparations sourced from biological materials including clinical samples, cultures of organisms, and diseased tissues have been in use against the sourcespecific infections as well as other diseases. The nosodes have demonstrated some efficacy in managing epidemics, such as influenza, dengue, and leptospirosis. This article presents the need and process of development of nosodes from the SARS-CoV-2 to explore its prophylactic and therapeutic potentials against certain related viral diseases. Materials and methods A clinical sample of SARSCov-2 positive patient, based on the cycle threshold (CT) value of the qRT-PCR, heat-inactivated SARS-CoV-2, and spike glycoprotein all were processed for making nosodes as per the method described in Homoeopathy Pharmacopoeia of India. Molecular tests, such as qRT- PCR and sterility tests were performed to establish the live organisms, RNA material, and the absence of contamination. Results Three variants of Coronavirus Nosode were developed using a clinical sample, heat-inactivated SARS-CoV-2, and spike glycoprotein. In potencies 3c and above, no detectable SARS-CoV-2 RNA material was found by PCR. The analytical results for nosodes were reported as compliant for sterility testing as per the IP. Conclusion Three variants of Coronavirus nosodes were prepared which need to be evaluated further through pre-clinical and clinical studies. © International Journal of High Dilution Research. Not for commercial purposes.
ABSTRACT
During the crisis situation caused due to COVID-19 disease, managing mental health and psychological well-being is as important as physical health of people. As web based life is broadly utilized by individuals to communicate their feeling and supposition, our framework utilizes Twitter information posted by individuals during this emergency circumstance to dissect the feelings of individuals. For processing the cleaned data NRC Word-Emotion Association Lexicon (have aka EmoLex) is used. NRC Word-Emotion Association Lexicon is a list of English with real-valued scores of intensity for eight basic emotion words ns (anger, anticipation, disgust, fear, joy, sadness, surprise, and trust). The text content of tweeter dataset created by fetching tweets across the world have classified into basic emotions like anger, anticipation, disgust, fear, joy, sadness, surprise and trust. This analysis can be used by authorities to understand the mental health of the people and can take necessary measures to decide on policies to fight against coronavirus which is affecting the social well-being as well as economy of the whole world. © 2020 IEEE.