Evaluation of Investor's Financial Attitude towards Trading Activity during Pandemic

Investors' trading activities are influenced by their financial attitudes. Even though existing research has recognized and investigated their relationship, behavioral assessments and financial attitude still poses questions. Furthermore, there is a lack of evidence about the trading activity of retail investors in the instance of a health crisis, like COVID-19 pandemic. The aim of study is to fill in the gaps in the existing literature by studying the relative impact of five dimensions of financial attitude on trading activity of retail investors' during the pandemic. We have used five dimensions to measure financial attitude such as financial anxiety, optimism of investors, financial security, self-control, and the need for precautionary savings. We collected 512 responses from retail investors with the help of a structured questionnaire. We analyzed financial attitude and trading activity using SEM to establish the structural relationship. The observed findings disclosed that self-control is the dominant variable followed by financial security, need for precautionary savings, financial anxiety, and optimism. © 2022, School of Management Sciences. All rights reserved.

Diagnosis for COVID-19

"COVID-2019,” a recently emerged novel coronavirus disease, is causing serious health issues to the public and becoming more and more fatal every next day. On December 31, 2019, low respiratory infection cases were detected in Wuhan, China, which is in China's Hubei province. The cases were reported to the WHO Office of China and they could not identify the agents for the cause. The first cases were classified to be "pneumonia of unknown etiology.” The investigation program was initiated by the Chinese Center for Disease Control and Prevention (CDC). The etiology of the disease was attributed to a novel virus of the coronavirus (CoV) family. Dr. Tedros Adhanom Ghebreyesus, WHO Director-General, called the disease caused by this CoV the "COVID-19,” which is an acronym for "coronavirus disease 2019.” It is found that "COVID-19” is caused by bête-coronavirus named "severe acute coronavirus-2” (SARS-CoV-2). It belongs to those virus families that appear as pneumonia in the human body. It affects the lower respiratory tract badly. This virus has been identified as another version of the family of severe acute respiratory syndrome coronavirus (SARS-CoV) and the Middle East respiratory syndrome coronavirus (MERS-CoV) [1, 2]. SARS-CoV-2, SARS-CoV, and MERS-CoV possess similarity with them. They have differences in genotypic and phenotypic structure that guide their pathogenesis. So far, as per the findings, this virus originated in bats. It reached humans through contact with unknown animals. The transmission of this virus among humans is via direct contacts, inhalation of infected droplets, and contaminated hands and surfaces. Some of the symptoms of this disease are cough, sore cough, fever, fatigue, and dyspnea/breathlessness. The remedy of this disease is to diagnose the infection at the initial stage, supportive treatment to survive, self-quarantines, mass-quarantines, etc. This paper presents a systematic review of the origin of coronavirus, its types, transmissions, symptoms, and the current developments in diagnosing testing and vaccine trials. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Utility of the Brixia CXR score, C-Reactive Protein and Absolute Neutrophil Count in Predicting the Need for Invasive Mechanical Ventilation, Length of Hospital Stay, and Mortality in Moderate to Severe COVID-19 Patients

Background: The Brixia Chest X-ray (CXR) score, C-reactive protein (CRP), and the absolute neutrophil count (ANC) have been useful to predict outcomes in Coronavirus disease 2019 (COVID-19 patients). We studied the utility of the Brixia CXR score, CRP, and ANC in predicting the outcomes in terms of the need for invasive mechanical ventilation, length of stay, and mortality in moderate-severe COVID-19 patients. Material(s) and Method(s): This was a single-centre, retrospective, study on 122 COVID-19 patients. Brixia CXR score, CRP, and ANC on admission to the hospital and the fifth day of hospital stay were noted along with the need for invasive mechanical ventilation (IMV), prolonged length of stay (LOS) >= 14 days, and mortality. Result(s): 122 patients were included for analysis. The median and interquartile range (IQR) for baseline CRP was 81.50 (39-151) mg/L and 11.0 (4-30) mg/L (p < 0.001) on the fifth day. The median and IQR for baseline Brixia score was 10.0 (7-13), and on the fifth day was 7 (4-11) (p <0.001). The receiver operating characteristic curve (ROC) showed that the baseline CRP >= 52.5mg/L predicted both the need for IMV, with an area under the curve (AUC) of 0.628, and prolonged LOS with an AUC of 0.608. The ROC curve depicted that the baseline ANC >8500/muL predicted IMV requirement with an AUC of 0.657. The fifth day CRP >= 32 mg/L, ANC >= 11,000/ muL and Brixia CXR score >= 7 predicted a higher mortality in hospitalized patients. Conclusion(s): Baseline CRP (> 52.5mg/L) predicts the need for IMV and a prolonged LOS, but not mortality. Baseline ANC (> 8500/muL) predicted the need for IMV. CRP, Brixia CXR score, and ANC on the fifth day were not useful to predict LOS or mortality, though there was a significant reduction in CRP and Brixia CXR score on the fifth day compared to baseline after treatment. The fifth day CRP >= 32 mg/L, ANC >= 11,000/ muL and Brixia CXR score >= 7 predicted a higher mortality.Copyright © 2023, College of Anaesthesiologists of Sri Lanka. All rights reserved.

Metaverse: An Innovative Model for Healthcare Domain

Present situation after the Coronavirus has made every one of us understand the deficiencies and the impediments of India's medical services area. There was an intense shortage of clinical staff, beds, and other such essential things, which made us believe this is the future to be lived with, and provided that this is true, then, at that point, it is a significant eye-opener for specialists, designers, government and each capable individual to think of an answer for this. This occasion touched off the inclination for the tracking down the arrangement or possibly a stage towards settling or, in any event, restricting this destruction. Metaverse, and its ground-breaking capacities are the same old thing to the world. It's been anticipated that it will revolutionize gaming, association with companions, shopping, and whatnot. But this paper is kept to spotlight the most deserving space, the healthcare sector. Metaverse can change the fortunes of the medical care area. This paper will examine all the potential ways this innovation can be valuable. It can work on obsolete facilities for treatment and educational purposes, and numerous such up-sides have been highlighted beneath. © 2023 IEEE.

UNet Deep Learning Architecture for Segmentation of Vascular and Non-Vascular Images: A Microscopic Look at UNet Components Buffered With Pruning, Explainable Artificial Intelligence, and Bias

Biomedical image segmentation (BIS) task is challenging due to the variations in organ types, position, shape, size, scale, orientation, and image contrast. Conventional methods lack accurate and automated designs. Artificial intelligence (AI)-based UNet has recently dominated BIS. This is the first review of its kind that microscopically addressed UNet types by complexity, stratification of UNet by its components, addressing UNet in vascular vs. non-vascular framework, the key to segmentation challenge vs. UNet-based architecture, and finally interfacing the three facets of AI, the pruning, the explainable AI (XAI), and the AI-bias. PRISMA was used to select 267 UNet-based studies. Five classes were identified and labeled as conventional UNet, superior UNet, attention-channel UNet, hybrid UNet, and ensemble UNet. We discovered 81 variations of UNet by considering six kinds of components, namely encoder, decoder, skip connection, bridge network, loss function, and their combination. Vascular vs. non-vascular UNet architecture was compared. AP(ai)Bias 2.0-UNet was identified in these UNet classes based on (i) attributes of UNet architecture and its performance, (ii) explainable AI (XAI), and, (iii) pruning (compression). Five bias methods such as (i) ranking, (ii) radial, (iii) regional area, (iv) PROBAST, and (v) ROBINS-I were applied and compared using a Venn diagram. Vascular and non-vascular UNet systems dominated with sUNet classes with attention. Most of the studies suffered from a low interest in XAI and pruning strategies. None of the UNet models qualified to be bias-free. There is a need to move from paper-to-practice paradigms for clinical evaluation and settings.

An Assessment of Gender Inequality Experienced by Female Youth in Indian Household During COVID-19 Online Classes

Due to the patriarchal society, the females in the houses suffer the most. Women's schooling attainment in India continues to lag considerably behind that of men. Gender discrimination in household expenditure on education has led to unsatisfactory educational attainment for women in many countries across the world. It has been observed that households across different states in rural and urban India prefer to incur more education expenditure for male members than females. This research examines the discrimination in Indian households between male and female children during lockdown due to COVID-19. The research was conducted by placing factors that determine discrimination, like availability of resources, nutrition, domestic violence, etc. Telephonic interviews were conducted for fifty-one university students from different states of India. The female students were asked about their difficulties in their education and daily chores due to gender discrimination at their respective homes. One of the critical factors that the research participants expressed was that even educated parents discriminated because they thought it is accepted and regular due to society's patriarchal mind-set. Female students were not appreciated for the daily chores or sacrifices as it was considered a part of their responsibilities. Changing this attitude and belief about women should begin from the house level for reducing gender stereotypes in society.

A Deep Net Model for Covid-19 Detection Based on ROC Analysis Using Radiographs

The European Centre of Disease Prevention & Control's analytical statistics show that the new corona virus (Covid-19) is rapidly spreading amongst millions of people & causing the deaths of thousands of them. Despite the daily increase in cases, there are still a finite quantity of Covid-19 test kits available. The use of an automatic recognition system is crucial for the diagnosis and control of Covid-19. Three important Inception-ResNetV2, InceptionV3, & ResNet50 models of convolutional neural networks are utilized to detect the Corona Virus in lung X-ray radiography. The ResNet50 version has the best result & accuracy rate of the present system. As compared to the current models, a novel procedures and ensuring on the CNN model delivers better specific, sensitivities, and precision. By using confusion matrix and ROC assessment, fivefold validation data is utilized to analyze the current models and compare them to the proposed system. © 2023 IEEE.

At the Crossroads of One Health: Lessons Learned from Foot and Mouth Disease in COVID-19 Pandemic

Foot-and-mouth disease (FMD) and Coronavirus Disease 2019 (COVID-19) are transboundary diseases caused by single-stranded positive-sense RNA viruses with similarities in genome replication and viral protein synthesis. In FMD, asymptomatic infection leads to carrier status and persistently infected animals that threaten the animals vaccinated with a trivalent inactivated whole virus vaccine. Similar information on COVID-19 is not yet available. As COVID-19 vaccination is introduced in January 2021 (since 16 January 2021 in India), its outcome can be assessed by the year-end;and while doing so, the experiences gained in the control of FMD in livestock worldwide can be applied, including monitoring of vaccination response, duration of immunity, level of herd immunity developed, and antigenic matching of the vaccine virus. Antigenic divergence of the virus is a major issue in FMD, and different geographical regions in the world use different virus strains in vaccine preparations to antigenically match circulating virus strains in respective regions for control of the disease. Non-synonymous mutations in the critical antigenic determinants of SARS-CoV-2 have been observed, and there is likely the existence/development of antigenic variants. Therefore, during the post-COVID-19 vaccination regime, it will be essential to monitor the suitability of the in-use vaccine strain region-wise from time to time, as there could be an eruption of isolated outbreaks in a country arising due to antigenic variation and variants. In the context of the present scenario of COVID-19 around the Globe and multiple ongoing efforts to develop suitable vaccine(s) to control the disease, it is a must to develop NSP-antibody (that differentiate infected from vaccinated) assays to differentiate infected from vaccinated individuals(DIVI;DIVA in veterinary epidemiology). The techniques used and experiences gained in ongoing FMD control programs in the endemic countries can be applied to COVID-19 control in a country;and finally, the Globe. After achieving the control of COVID-19, the aim would be to eradicate the virus, which will be tough even with vaccination, as the disease/infection may become endemic during the time to come. To achieve this, applying the principles of Progressive Control Pathway for Foot-and-Mouth Disease (PCP-FMD;FAO/OIE) to COVID-19 control will be beneficial in its control. The present review discusses the issue of control of COVID-19. © 2021 by the authors.

Comparative study of early versus delayed presentation of lens induced glaucoma: A retrospective study conducted among population in remote hilly areas of Uttarakhand

Aim: To compare the causes and visual outcome of lens induced glaucoma amongst those presenting early (within 7 days) with those presenting late (after 7 days). Materials and Methods: This was a retrospective study which included a total of 50 cases diagnosed as lens induced glaucoma. Patients were divided into two groups-group A presenting within 7 days and group B presenting after 7 days. All the patients underwent manual small incision cataract surgery with PMMA lens implantation. Visual outcome and intraocular pressure in both the groups preoperatively and on postoperative day 30 were compared. Results: Majority of patients were females and in the age group of 61-70 years. Phacomorphic glaucoma was the main cause of lens induced glaucoma accounting for 64% of the cases. Good vision in the other eye was the most common reason of delay in seeking medical aid (45.45%). Postoperative day 30 assessment of visual outcome showed that majority of group A patients had a visual acuity of 6/6 to 6/12. Group B patients showed majority with visual acuity of 6/18 to 6/60. Postoperative IOP of 74% patients was well controlled below 21 mm Hg at 1 month. Conclusion: The final BCVA in our study was found to be better in those who presented early, highlighting the importance of early diagnosis and efficient management. © 2023 Innovative Publication, All rights reserved.

Deep Learning based Face Mask Detection system with Automatic Indigation

The COVID-19 pandemic has quickly had an impact on our day-to-day lives, as well as on the movement of goods and people around the world. It has recently been common practice to shield one's face by using a mask. In the not too distant future, many businesses that provide public services will need their clients to correctly wear masks in order for them to receive those services. As a result, the detection of face masks has evolved into an important mission in the service of worldwide society. In this post, a relatively straightforward approach to achieving this goal is presented using basic machine learning tools like TensorFlow, Keras, OpenCV, and Scikit-Learn. The suggested method accurately locates the face inside the image before determining whether or not it is covered by a mask. While doing a surveillance task, it is capable of detecting a mask as well as a moving face. To properly detect the presence of masks without over-fitting, we look into numerous options for optimizing the values of the parameters in the Sequential Convolutional Neural Network model. © 2022 IEEE.

Diffusion and Adoption of Technology amongst Small and Medium Enterprises during COVID-19- with a focus on Internet of Things

The paper is a conceptual study of small and medium sized enterprises (SMEs) technology adoption and diffusion with a focus on impact on IoT adoption during COVID-19. The paper proposes that the pandemic has acted as a legitimizing force for technology adoption and diffusion amongst SMEs. SME's have adopted response strategies to cope with the pandemic that have an impact on their propensity to adopt new technology. This has resulted in increased uncertainty, which can be reduced through the strategies identified in this paper. Through literature review on SME IoT adoption during the pandemic, a gap is identified in current studies. This gap is addressed through the inclusion of case-studies and use-cases. The paper can be used as a reference by SMEs for strategy making to reduce information uncertainty, policy makers to support SMEs as well as academicians for further research. © 2022 IEEE Computer Society. All rights reserved.

A Hybrid technolgy using Machine learning and blockchain technology to prevent Covid

Since the year 2020, there has been an outbreak of the respiratory infection that caused a high peak mortality rate, which has led to an increase in the prevalence of Covid. The unanticipated development of the COVID-19 sickness as well as its unchecked global spread show the limitations of the currently available healthcare systems in their ability to respond to emergencies that harm the general population's health. As a result of cutting-edge technology like AI and biological computing (BC) these issues treated promisingly for the covid pandemic. In particular, BC assist in early detection to aid in the fight against pandemics. With the protocols that have been put in place to avoid infections, including the use of masks, social isolation within a radius of 6 meters, routine testing, and two doses of vaccinations. This system comprises the detection of masks, people, and temperatures, as well as the monitoring of information, tracking of in-person contact, and the present state of a person's medical record. Diseases are now able to be traced, and their transmission can be stopped, thanks to advances in technology and the growing prevalence of smartphone use. Because of the reopening of more economic sectors and the continuous widespread distribution of Covid, it is even more important to ensure that you adhere to the provided instructions in order to avoid contracting an infection. © 2023 IEEE.

Green Manufacturing in Apparel Industry: Future Trends and Scope

Humans have been exploiting the environmental resources as much as the environment today stands in crisis. There has become an urgent need of aligning profits with peace and prosperity of people and planet. In the race of economic growth and development, the disparity between social, economic and environment has aroused. The impact of Covid-19 pandemic further has highlighted the sustainable growth to be considered for a better future. Also, viewing the United Nations Sustainable Development Goals, there needs to be responsible consumption and production. Sustainability is the greatest challenge faced by the apparel industry. The industry, running on the adrenaline of glamor, pricing and pace, has recently realized that the old systems and processes cannot sustain, but there are not enough new systems and processes to replace. We are facing redundancies in an empty-handed way. Green manufacturing is an inevitable future. The paper explores key aspects of green manufacturing from apparel industries perspective, noting down the innovation and entrepreneurial solutions to the problems, identifying gaps and future scope. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Virtual Lab Development to Enhance Student Learning: A Quality Circle Approach

The COVID-19 pandemic has affected the student fraternity to physically access the laboratory and conduct experiments offline. Across the world, new platforms have been designed with ICT tools for the smooth conduction of academics specifically for laboratory courses. This article aims to provide quality circle-based guidance to the community to develop a Virtual Laboratory. The virtual lab is developed through an emphasis on Quality Circle methodology. The Quality Circle team has developed an instructional methodology known as the virtual laboratory (VL). It incorporates pedagogical techniques that help students to better understand the theoretical concepts in an effective and joyful way. © 2022, Rajarambapu Institute Of Technology. All rights reserved.

Comparative Study of Molecular Docking, Structural, Electronic, and Fukui Function Studies on Favipiravir and its Newly Designed Derivatives (Potential Inhibitors) for COVID-19 Protease

Favipiravir is an antiviral medication currently being trialed as a COVID-19 treatment. These results motivate us to develop new species (possibly drugs) from favipiravir, perform comparative molecular docking, and reexamine their biological and pharmacological activities. Detailed quantum chemical research on favipiravir and its newly designed derivatives has been carried out with the help of DFT/B3LYP/6–311 + + G (d, p). In the present work, the structure of favipiravir has been modified and 12 new species have been modeled (all species are inherently stable because no virtual frequency is found during the vibration analysis). Reactivity of all species using various descriptors (local) such as Fukui function, local softness, electrophilicity, and global, i.e., electronegativity, hardness, HOMO–LUMO gap, etc. of the same are calculated and discussed. In silico studies such as molecular docking of all species and complete quantum chemistry studies suggest that four of them may mitigate the effects of the COVID-19 protease. © 2023 Wiley-VCH GmbH.

Modified Synthesis and Isolation of an Advanced Intermediate of Remdesivir

Synthesis and isolation of an advanced intermediate (S)-2-Ethylbutyl 2-(((S)-(4-nitrophenoxy) (phenoxy) phosphoryl) amino) propanoate (1b), which is being used for the manufacture of the prodrug diastereoisomer 1d called Remdesivir have been carried out in high yield with efficient stereoselectivity. The isolated advanced intermediate 1b was a dia-stereoselective nucleoside phosphoramidate prodrug used as an antiviral agent having a mix-ture of two (SS) and (SR) diastereomers with stereocenter at phosphorus, which was purified by converting into a more stable diastereoselective isomer (SS) by simple physical fractional crystallization process, resulting in an improved yield of ~45%. The recrystallization has been afforded diastereomerically in 99% pure (SS)-isomer 1b. The 1H NMR characterization data confirm the (SS)-isomer (1b). The developed process holds significant potential for large-scale reactions relatively with commercially available low-cost solvents and co-solvents, resulting in an alternative cheaper process. © 2022 Bentham Science Publishers.

EXAMINING THE PREDICTORS OF ENVIRONMENTALLY RESPONSIBLE TOURISM BEHAVIOR DURING COVID-19

This study examines the predictors of environmentally responsible tourism behaviour during the COVID-19 pandemic. As the tourism industry keeps expanding and the effects of tourism on the environment become increasingly obvious, the idea of responsible tourism has received a lot of attention recently. Also, the COVID-19 outbreak, lead to a decrease in travel and a shift in consumer behaviour. This paper studies the impact of destination image, environmental concern and experience quality on environmentally responsible tourism behaviour. The study was performed using a cross-sectional survey with a 321 sample size and analysed using multiple regression. The study identified the advantageous and positive effect of destination image, environmental concern and experience quality on environmentally responsible tourism behaviour. This study can benefit destination managers and other tourism stakeholders to maintain the responsible behaviour of tourism among visitors. © 2022,Journal of Content, Community and Communication.All Rights Reserved.