ASSOCIATION RULE MINING FOR PREDICTION OF COVID-19

COVID-19 is a raging pandemic that has created havoc with its impact ranging from loss of millions of human lives to social and economic disruptions of the entire world. Therefore, error-free prediction, quick diagnosis, disease identification, isolation and treatment of a COVID patient have become extremely important. Nowadays, mining knowledge and providing scientific decision making for diagnosis of diseases from clinical datasets has found wide-ranging applications in healthcare sector. In this direction, among different data mining tools, association rule mining has already emerged out as a popular technique to extract invaluable information and develop important knowledge-base to help in intelligent diagnosis of distinct diseases quickly and automatically. In this paper, based on 5434 records of COVID cases collected from a popular data science community and using Rapid Miner Studio software, an attempt is put forward to develop a predictive model based on frequent pattern growth algorithm of association rule mining to determine the likelihood of COVID-19 in a patient. It identifies breathing problem, fever, dry cough, sore throat, abroad travel and attended large gathering as the main indicators of COVID-19. Employing the same clinical dataset, a linear regression model is also proposed having a moderately high coefficient of determination of 0.739 in accurately predicting the occurrence of COVID-19. A decision support system can also be developed using the association rules to ease out and automate early detection of other diseases. © 2023 by the authors.

Perception Regarding Online Teaching among Undergraduate Students of a Peripheral Medical College of West Bengal: A descriptive cross-sectional study

Background: COVID 19 pandemic has severely impacted medical education and residency training all over the world. Tele-teaching via online platforms became an apt solution as a result. This study was conducted on MBBS undergraduate students of Bankura Sammilani Medical College to describe their perception regarding e-learning. Materials and methods: All the students of 4th and 6th semester MBBS of Bankura Sammilani Medical College were given a pre-designed, pre-tested Google form questionnaire and their responses were collected. Results: 73.12% students were satisfied or very satisfied in live lecture class compared to only 28.46% in live practical class. However, for theory classes, majority felt traditional class as superior than online modes with respect to understanding of content (85.77%), less distraction during class (58.10%), interaction with faculty (88.54%), interaction with peers (86.96%), clearing of doubts (83.79%). Virtual mode gained superiority in recording of information (66.40%), flexibility of class timing (64.03%) and flexibility of continuation of class (51.78%). For practical classes, majority thought that traditional modality is better than virtual modes with respect to all the parameters. Conclusion: Majority of students considered traditional teaching as a better mode of teaching than virtual mode of class. © 2022, Medicolegal Association of Maharashtra. All rights reserved.

Spirituality bestowing self-transcendence amid COVID-19 through slow fashion

We proposed and tested a conceptual model exploring how (i) COVID-stress evokes spirituality;(ii) COVID-stress and spirituality engender positive attitude toward the different dimensions of slow fashion (i.e. equity, authenticity, functionality, localism, and exclusivity) as a symbol of self-transcendence and (iii) spirituality mediates the relationships between COVID-stress and the different dimensions of slow fashion. We conducted an online survey in Amazon Mechanical Turk (n = 317) and analyzed the data through structural equation modeling. (i) COVID-stress positively influences spirituality;(ii) both COVID-stress and spirituality positively influence attitude toward slow fashion in terms of equity, authenticity, localism, and exclusivity;(iii) spirituality mediates the relationships between COVID-stress and all the dimensions of slow fashion except for functionality. Due to the fast-changing situations amid the pandemic and the uneven severity of the pandemic globally, a cross-sectional study may have limited the scope for capturing nuances of retail consumer behavior. In summary, we suggest that the consumption of slow fashion apparel as a symbol of self-transcendence may help consumers cope with COVID-stress in the hope of building spiritual ties with a higher power through the process of ethical consumption amid the pandemic. © 2023 Korean Scholars of Marketing Science.

Second wave of COVID-19 - Not a matter of great concern for pediatric hematologist/oncologist

Coronavirus disease-19 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a global pandemic and is giving rise to a serious health threat globally. SARS-CoV-2 infection ranges from asymptomatic carrier state to severe illness requiring intensive care unit (ICU) management. It is postulated that with COVID-19 infection, children are less prone to develop severe symptoms as compared with adults. The data on immunocompromised children affected with COVID-19 infection is limited and not many publications are there on the effects of 2nd wave of COVID-19 infection in pediatric hematology/oncology patients till date. In our experience during second wave, 17 patients were found to be positive for SARS-CoV-2 with a male: female ratio of 2.4: 1 and median age of 8 years (range 1-18 years). Out of these 17 patients, 10 (58.8%) patients required hospital admission whereas the remaining were managed at home. Only 1 patient required ventilatory support and there was no mortality. Though the number of pediatric patients with COVID-19 infection were more during the second wave but majority had mild to moderate symptoms and were easily managed.Copyright © 2022 Pediatric Hematology Oncology Chapter of Indian Academy of Pediatrics

A Green Eco-friendly Analytical Method Development, Validation, and Stress Degradation Studies of Favipiravir in Bulk and Different Tablet Dosages Form by UV-spectro- photometric and RP-HPLC Methods with their Comparison by Using ANOVA and in-vitro Dissolution Studies

Favipiravir is an antiviral drug with significant and widespread antiviral action. Favipiravir was crucial in the contest against the COVID-19 pandemic because of how well it treated the SARS-CoV-2 virus. It is well known that contemporary pharmaceutical analysis establishes green, stability-indicating analytical procedures. The current study aimed to develop and assess UV-spectrophotometric (zero order, first order, area under the curve) and RP-HPLC methods for estimating favipiravir in its pharmaceutical dose form, comparing them using ANOVA and an in-vitro dissolution analysis. A green solvents composition of methanol, ethanol, and water (25:35:40 v/v/v) is used for analysis as a mobile phase and diluent. Method A is a simple zero-order spectrophotometric method for determining favipiravir at 236 nm, and the correlation coefficient in the linearity study was found to be 0.9962, LOD, and LOQ are 0.18 and 0.55 mg/mL. Method B is a first-order spectrophotometric method for determining favipiravir at 227 nm, and the correlation coefficient in the linearity study was found to be 0.9964, LOD, and LOQ are 0.64 and 1.96 mg/mL. Method C is an area under the curve spectrophotometric method for determining favipiravir at 230 to 243 nm, and the correlation coefficient in the linearity study was found to be 0.9986, LOD, and LOQ are 0.32 and 0.96 mg/mL. Method D is the RP-HPLC method for the determination of favipiravir at the retention time of 7.216 min, a flow rate of 0.80 mL/min, column temperature of 25 degrees C, at 236 nm, Isocratic mode, and the correlation coefficient in the linearity study was found to be 0.9996, LOD, and LOQ are 0.52 and 1.56 mg/mL. All developed methods demonstrated good repeatability and recovery with %RSD < 2. The proposed established methods were assessed using one-way ANOVA. It was revealed that the Fcalculated value was lower than the Ftabulated value, with no discernible variation in the assay results. Studies on stress degradation show that oxidation and acid degradation mostly impact favipiravir solutions. The Analytical Eco-scale verified that these methods are the greenest and most environmentally friendly, enabling the suggested approach to use an effective green analytical methodology to measure favipiravir extensively. Phosphate buffer (pH 6.4) was the best dissolution medium after analysis of the favipiravir dissolution study in several dissolution media.

Impact of the COVID-19 face mask disposal on environment and perception of people of the Sultanate of Oman

Background: Environmental concerns are increasing in and around us due to improper discharge of personal protective gear or equipment (PPEs) during the current pandemic with SARS-CoV-2. The residents of Salalah, under the Dhofar governorate of Oman, were hastening to take every possible measure to safeguard their health against the COVID-19 pandemic. In this scenario, improper discard of facemasks in the environment entails a significant problem for public health and aquatic environments. Objective: This study aims to assess how the SARS-CoV-2 virus disrupted the household waste management chain in the Sultanate of Oman. In addition, descriptive survey has also identified people's perception about the existing household waste management system. Methods: Total 200 respondents were personally selected under the purposive sampling category. Data were analyzed using SPSS version 26. The mean, standard deviation, and distribution shape were calculated based on the retrieved data. The variables and frequencies were tabulated for categorical variables. Results show negative impacts on the environment, wildlife, and public health. It was also observed that there was a significant difference when grouped according to residence location since the obtainedalso observed a significant difference when grouped according to residence location since the p-value of 0.007 was less than 0.05 alpha level. This means that the responses differ significantly. It shows from the test conducted that participants from the village experienced and observed a negative impact on the discarded face masks compared to those in the city. Conclusion and recommendation: This study illustrates the real impact of the COVID-19 face masks on the environment, wildlife, and public health. In addition, the new management of the user's face masks for eliminating or reducing the risks to human health and the environment has been suggested.

Knowledge Deprivation Index: Measurement for the UG Students in Purulia and Paschim Bardhaman Districts of West Bengal, India

COVID-19 protocols primarily shifted the mode of higher education basically from offline to online mode with unavoidable dependence on remote and distance learning, which has its own pros and cons. The question is – How far students have been able to adapt and accept the new regime and how far do they find themselves or are deprived of being in the pre-COVID era? This chapter tries to find out, by formulating an index, the amount by which the students were deprived owing to the challenges faced by them over and above the opportunities enjoyed on experiencing this new method of learning. Anticipating that this pandemic is temporary and believing that not all changes were detrimental, this chapter proposes that, to ensure easy access and to avoid inequality in knowledge, campus mode must be resumed as soon as plausibly feasible as it was found that the knowledge deprivation index of the total group of respondents is about 40%. The shift of learning mode from ‘campus' to ‘online' not only increased ‘deprivation of knowledge' but also widened the intra-group, viz. male–female, rural–urban, etc., inequality, making it a socially unsustainable solution. Hence, it can be said that Corona waves will pass on but let not the campus be washed away. © 2023 selection and editorial matter, Ramesh Chandra Das;individual chapters, the contributors.

An Indian Green Deal: Greening our way out of the pandemic

The Indian economy is facing a crisis at three different levels — health, economic and climate-change related. This ongoing crisis has given India an opportunity to change the course of development, a model where people, not profits, form the core. Based on the Indian economy's employment-generating capacity, we propose an Indian Green Deal (IGD) that generates jobs and fundamentally alters the carbon footprint of the economy. The programme is divided into three components – care economy, infrastructure, and green energy transition – to address the triple crises, respectively. We show that for the same amount spent, 3.5 jobs will be generated in green energy programme compared to one job in the fossil fuel sector. If the amount promised under the Covid package of the Indian government are spent on IGD, it would generate 22.7 million jobs every year. It also provides disaggregated evidence on the quality of jobs as well as gender and caste representation. As for financing, there are two ways in which it can be financed — an international carbon fund and/or domestic sources. An IGD, financed through these sources, addresses both the questions of the climate crisis and climate injustice in one go. © 2023 Elsevier B.V.

Comprehensive In silico Investigation Validates Two Flavonoid Compounds of Derris robusta (Roxb. ex DC.) Benth. to Supplant Remdesivir as Natural Therapeutic Remedy Against a Range of Coronaviruses

Diversified Coronaviruses like MERS-CoV, SARS-CoV-1, SARS-CoV-2, etc., have badly affected human life by causing various respiratory syndromes. Natural bioactive products like flavonoids are well-known for their anti-viral property. Derris robusta (Roxb. ex DC.) Benth. is a reservoir of flavonoids, which encouraged the in silico study of the signature flavonoid compounds in it towards investigating the possible inhibitory effect of those flavonoid compounds against the viral replication of MERS-CoV, SARS-CoV-1, and SARS-CoV-2. Therefore, investigating the treatment methodology for alleviating these types of diseases is the ultimate priority for public health. In our in silico study, Flavonoids like Isosinensetin and Retusin inhibited the replication of all three viruses with greater binding affinity compared to the control drug Remdesivir in multiple instances. Physicochemical characterization of the compounds by following Lipinski's rule of fi ve and the ADMET study have helped recognize these compounds as a probable natural therapeutic drug against Coronaviruses. The present study exhibits the potential of alternative drug molecules as anti-viral compounds against these three types of Coronaviruses. Further in vitro and in vivo evaluation followed by clinical trials for developing and successfully implementing these two compounds as an effective inhibitory agents against Coronaviruses can be initiated. © 2022 by the authors.

iNCOVACC COVID-19 vaccine: A Twitter based Social Media Analysis Using Natural Language Processing, Sentiment Analysis, and Topic Modelling

Most, if not all, the vaccine candidates designed to counteract COVID-19 due to SARS-CoV-2 infection require parenteral administration. Mucosal immunity established by vaccination could significantly contribute to containing the SARS-CoV-2 pandemic, which is spread by infected respiratory secretions. The world has been impacted on many fronts by the COVID-19 pandemic since early 2020 and has yet to recover entirely from the impact of the crisis. In late 2022 and early 2023, China experienced a new surge of COVID-19 outbreaks, mainly in the country's northeastern region. With the threat of new variants like XBB 1.5 and BF.7, India might experience a similar COVID-19 surge as China and needs to be prepared to avoid destruction again. An intranasal vaccine can elicit multiple immunological responses, including IgG neutralization, mucosal IgA production, and T-cell responses. In order to prevent further infection and the spread of COVID-19, local immune responses in the nasal mucosa are required. iNCOVACC is a recombinant vaccine vectored by an adenovirus that contains a SARS-CoV-2 spike protein that has been pre-fusion stabilized. This vaccine candidate has shown promise in both early and late-stage clinical trials. iNCOVACC has been designed for intranasal administration via nasal drops. The nasal delivery system was created to reduce expenses for those living in poor and moderate-income. © 2023, Editorial board of Journal of Experimental Biology and Agricultural Sciences. All rights reserved.

Sales Management Just Got Brighter and More Resilient during Covid-19: An Abstract

Covid-19 has made an impact on almost all aspects of our daily lives and organizations are no different. As their revenues got reduced, there has been a strong imperative to look for additional sources of new businesses, while still catering to the existing customers. The approaches for both these are vastly different and the pandemic situation accentuated this complexity. Among all the functions within an organization, the sales department has had to bear the maximum brunt during the crisis event of Covid-19. They were affected at several levels- employees lost their jobs as the revenues of organizations declined;almost all of them had to significantly strengthen their digital skills and had to cope with the new working arrangements. Facing customers with new and not very pleasant information daily led to lot of stress on sales people. Staying constantly wired internally with other departments, in terms of product modifications or revised terms and conditions for the business, was another reality. Though sales has changed from an operationally focused practice toward a strategically focused part of business strategy (Ingram et al., 2002;Jones et al., 2005;Leigh & Marshall, 2001;Storbacka et al., 2009;Williams & Plouffe, 2007), the Covid situation demanded high levels of both. This qualitative study investigates the impact of the Covid-19 pandemic (waves 1 and 2) on sales management by conducting in-depth interviews of product and service personnel across three countries—namely, the United Kingdom, Malaysia, and India. We draw on the sales effectiveness framework (Zoltners et al., 2008) and other well-established sales literature to analyze our findings. During Covid-19, the sales function played a crucial role and served as the "eyes, ears, and hands” of businesses: sales personnel rallied 24/7 to ensure customer referrals, customer loyalty, and customer delight. The sales process was significantly digitized and all the selling steps underwent modification. Overall, organizations became more innovative, agile, productive, and profitable during the pandemic. We recommend the use of a theoretical conceptual framework modified for sales management during Covid-19;we also list a set of 22 sub propositions derived from five major propositions, for future validation. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Modelling asymmetric sovereign bond yield volatility with univariate GARCH models: Evidence from India

Does Indian sovereign yield volatility reflect economic fundamentals, or whether it is a self-generated force flowing through markets with little connection to such fundamentals? To answer the question, this research explores the volatility dynamics and measures the persistence of shocks to the sovereign bond yield volatility in India from 1 January 2016, to 18 May 2022, using a family of GARCH models. The empirical results indicate the high volatility persistence across the maturity spectrum in the sample period. However, upon decomposing the markets into bull and bear phases, our results support the existence of weak volatility persistence and rapid mean reversion in the bear market. This shows that the economic response policies implemented by the government during the pandemic, including fiscal measures, have a restraining effect on sovereign yield volatility. For a positive γ, the results suggest the possibility of a "leverage effect” that is markedly different from that frequently seen in stock markets. Results further indicate that the fluctuations in Indian sovereign yields cannot be dissociated from inflation and money market volatility. Our findings herein provide valuable information and implications for policymakers and financial investors worldwide. © 2023 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.

Primary factors that determine the severity of various infections and effective nutraceutical intervention strategies

Current agricultural practices, food processing, and extensive availability of unhealthy "fast foods” impose a broad spectrum of degenerative disorders including bacterial, viral, parasitic, fungal, and yeast infections, all of which became a leading cause of death. An infection is defined as "The invasion and growth of germs in the body.” Several of these germs are opportunistic anaerobic organisms, while their propagation and proliferation potentiate the anaerobic bio-environment alarmingly. An ideal therapeutic objective is to restore a healthier cellular "aerobic” metabolic environment. This chapter will extensively focus on three important infectious disorders (i) COVID-19 infection, (ii) Herpesvirus infection, and (iii) Candida albicans yeast infections. Disease etiology, mechanisms, and pathology will be extensively discussed. Prevention and the potential of therapeutic interventions by structurally diverse nutraceuticals, phytopharmaceuticals, probiotics, and micronutrients will be extensively reviewed. © 2023 Elsevier Inc. All rights reserved.

IoT Based Intelligent System for Covid - 19 hotspot detection by CNN Crowd Density Algorithm

The worldwide health crisis is caused by the widespread of the Covid-19 virus. The virus is transmitted through droplet infection and it causes the common cold, coughing, sneezing, and also respiratory distress in the infected person and sometimes becomes fatal causing death. As the world battles against covid-19, the proposed approach can help to contain the clustering of covid hotspot areas for the treatment of over a million affected patients. Drones/ Unmanned Aerial Vehicles (UAVs) offer a great deal of support in this pandemic. As suggested in this research, they can also be used to get to remote places more quickly and efficiently than with conventional means. In the hospital's control room, there would be a person in command of the ambulance drone. For hotspot area detection, the drone would be equipped with FLIR camera and for detection and recognition of face the video transmission is used by raspberry pi camera. The detection of face is done by Haar cascade Classifier and recognition of the face with LBPH algorithm. This is used for identify the each individual's medical history or can be verified by Aadhar Card. Face recognition between still and video photos was compared, and the average accuracy of still and video images was 99.8 percent and 99.57 percent, respectively. To find the hotspot area is to use the CNN Crowd counting algorithm. If the threshold value is less than equal to 0.5 than it is hotspot area , if it is greater than 0.5 and less than equal to 0.75 than it is semi-normal area , if it is greater than 0.75 and less than equal to 1 than it is normal area. © 2022 IEEE.

Impact of COVID-19 on death anxiety in patients with anxiety spectrum disorders: A case-control study

Background: COVID-19 pandemic has exacerbated symptoms in existing diagnosed cases of anxiety. Its impact on people with mental illness is expected to be significant, leading to an increase in relapse rates and expectedly inducing or exacerbating death anxiety. Aims & Objectives: This study aimed to assess the impact of Covid 19 fear on general anxiety and wellbeing and death anxiety and compare people with anxiety spectrum disorders on perceived fear, autonomic anxiety symptoms, and death anxiety with those without these disorders. Materials & Methods: We recruited 36 participants with anxiety spectrum disorder (generalized anxiety disorder (n=6), obsessive-compulsive disorder (n=17), panic disorder (n=5) and mixed anxiety and depression (n=8) and 36 individuals free from any psychiatric illness. Tools used include General Health Questionnaire, Fear of COVID-19 Scale, Perceived Stress Scale, Beck Anxiety Inventory and Multidimensional Fear of Death Scale. Results: A statistically significant correlation was noted between many variables in both the study groups. The regression analysis showed a significant difference in general well-being and anxiety & death anxiety in the clinical group. Study outcomes indicated that the current pandemic has triggered significant fear and anxiety in anxiety patients and among healthy controls and has triggered significant death anxiety in the clinical and healthy control group. Conclusion: The study showed that fear of covid-19 is a predictive factor for stress, death anxiety, and general well-being. These findings may be helpful to plan preventive measures, tailored intervention focusing on death anxiety and relapse plans effectively. © 2022 by the Author(s).

Monitoring Engagement in Online Classes Through WiFi CSI

Due to the Covid-19 pandemic, people have been forced to move to online spaces to attend classes or meetings and so on. The effectiveness of online classes depends on the engagement level of students. A straightforward way to monitor the engagement is to observe students' facial expressions, eye gazes, head gesticulations, hand movements, and body movements through their video feed. However, video-based engagement detection has limitations, such as being influenced by video backgrounds, lighting conditions, camera angles, unwillingness to open the camera, etc. In this work, we propose a non-intrusive mechanism of estimating engagement level by monitoring the head gesticulations through channel state information (CSI) of WiFi signals. First, we conduct an anonymous survey to investigate whether the head gesticulation pattern is correlated with engagement. We then develop models to recognize head gesticulations through CSI. Later, we plan to correlate the head gesticulation pattern with the instructor's intent to estimate the students' engagement. © 2023 IEEE.

Observing Human Mobility Internationally During COVID-19

This article analyzes visual data captured from five countries and three U.S. states to evaluate the effectiveness of lockdown policies for reducing the spread of COVID-19. The main challenge is the scale: nearly six million images are analyzed to observe how people respond to the policy changes. © 1970-2012 IEEE.

A COVID-19 Infection Rate Detection Technique Using Bayes Probability

The main objective of this paper is to detect the infection rate of the SARS-Cov-2 virus among patients who are suffering from COVID with different symptoms. In this work, some data inputs from the intended patients (like contact with any COVID infected person and any COVID patient within 1 km.) are collected in the form of a questionnaire and then applied Naïve Bayes probabilistic technique to evaluate the probability of how much that patient is affected in this deadly virus. Following this process, we collect sample data of 80 patients and apply the proposed analysis process using the C programming language. This approach also shows the comparison for different test cases with respect to the feedbacks of actual patient data analysis. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Thermo-Chemical conversion of polyolefin-based facemask using bench-scale pyrolysis system

The generation of personal protective equipment (PPE) waste due to the impact of COVID has increased multi-fold globally. In this study, pyrolysis of polyolefin-based PPEs was carried out using a bench-scale reactor of 2 kg per batch capacity. Thermogravimetric (TGA) analysis of face masks was carried out to identify the optimal parameters for the pyrolysis process. Different combinations of catalysts (ZSM-5 and montmorillonite), catalyst to feed ratio (2.5% and 5%), experiment duration (2 h and 3 h), and process temperature (450 degrees C and 510 degrees C) were tested to determine the maximum yield of the pyrolysis oil. The oil and char obtained from the pyrolysis of PPEs were analyzed for its gross calorific value (GCV), elemental analysis (CHNS), and chemical composition. Based on the experiments conducted, the optimum pyrolysis temperature, catalyst, catalyst to feed ratio, and batch time for maximum oil yield (55.9% w/w) were determined to be 510 degrees C, ZSM-5, 5%, and 2 hours, respectively. Oil was free of sulfur and had a calorific value of 43.7 MJ/kg, which is comparable to commercial diesel fuel and makes it a suitable alternative fuel for ships, boilers, and furnaces.

COVID-19 Outbreak Estimation Approach Using Hybrid Time Series Modelling

In the beginning of March 2020, coronavirus was claimed to be a worldwide pandemic by the World Health Organization (WHO). In Wuhan, a region in China, around December 2019, the Corona virus, also known as the novel COVID-19 was first to arise and spread throughout the world within weeks. Depending upon publicly available data-sets, for the COVID-19 outbreak, we have developed a forecasting model with the use of hybridization of sequential and time series modelling. In our work, we assessed the main elements to forecasting the potential of COVID-19 outbreak throughout the globe. Inside the work, we have analyzed several relevant algorithms like Long short-term memory (LSTM) model (which is a sequential deep learning model), used to predict the tendency of the pandemic, Auto-Regressive Integrated Moving Average (ARIMA) method, used for analyzing and forecasting time series data, Prophet model an algorithm to construct forecasting/predictive models for time series data. Based on our analysis outcome proposed hybrid LSTM and ARIMA model outperformed other models in forecasting the trend of the Corona Virus Outbreak. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.