Analysing the Paradigm Shift of Consumer Behaviour Towards E-retail During Pandemic Lockdown

The consumer behaviour plays a vital role in determining the market dynamics of the country, and COVID-19 pandemic accelerated the demand for online shopping of essential products. The research study attempts to answer the cause and nature of transition of online shopping behaviour. Purposive sampling technique is applied with sample size of 300 respondents from the state of Jharkhand and Orissa participated in an online survey. The analysis of the research study administers use of Excel to determine the proportion of responses for each category and SPSS software for frequency analysis of the given set of items. The findings of the study indicated strong inclination towards online shopping of electronic items, grocery, and food delivery among the participants due to lockdown restriction, convenience, and safety as the prime factors. It is observed that the advantages of purchasing goods through E-retail are not fully utilized by individuals of all age categories especially among old-age population segment. The study contributes to the existing body of knowledge towards consumers buying behaviour from E-retail forum from specifically Eastern regions of the country during exigencies. This study will assist the E-retail industries to design their business plan and logistic process according the need of the present situation for such kind of outbreaks in future. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Survival and outcomes of tocilizumab use in severe and critically ill COVID-19 patients not responding to steroids Background

Background: Mortality and morbidity are highest in severe and critically ill patients with COVID -19 pneumonia. Recently corticosteroids have shown a definite mortality benefit in these patients. In this study we used interleukin-6 inhibitor, tocilizumab in patients who failed to show any clinical improvement after initial treatment with steroids. Patients and Methods: This is a retrospective observational study in Severe and critical COVID 19 patients, who got admitted to intensive care unit and subsequently received tocilizumab were included. Patients who worsened clinically or had no change in oxygen requirement even after 24hrs of receiving Intravenous methylprednisolone at a dose of 1-2mg/kg/day had received tocilizumab (maximum total dose of 800mg) intravenously. All-cause mortality and progression to mechanical ventilation at day 28 were the primary outcome measures. Clinical improvement and oxygen requirements after tocilizumab administration along with trends in inflammatory markers were secondary outcome. Secondary infections rates and other drug related side effects were also noted. Results: A total of 51 patients who did not show clinical improvement even after 24 hours of intravenous steroids and received tocilizumab were included. In these patients, there was a significant decrease in oxygen requirement by day 3 and clinical improvement by day 7 of tocilizumab administration. Among the inflammatory markers, we observed elevated median baseline values of CRP (114.2 mg/L) , IL-6 (55.4 pg/ml) and Neutrophil to Lymphocyte Ratio (12.4). Out of these only CRP showed a significant decrease after the drug administration. 13 (26.5%) of the 49 patients who were on non-invasive or conventional oxygen support progressed to mechanical ventilation. The day 28 all-cause mortality rate was 10/51(19.6%). 10(19.6%) of the 51 patients had life threatening infections, 1 patient had colonic perforation and 1 patient had transaminitis following tocilizumab administration. Conclusion: Early and timely administration of tocilizumab is a viable option in selected severe and critical covid 19 patients who do not respond to initial steroids. When given along with steroids?, incidence of life threatening infections seems to increase, hence a high suspicion of secondary infection should be kept.

Covid-19 Vaccine Tweets Sentiment Analysis and Topic Modelling for Public Opinion Mining

The world is facing the major crisis in the form of coronavirus pandemic. Since it's been more than a year of Covid-19 pandemic, there has been a significant call in social media regarding the requirement and feasibility for COVID-19 Vaccine. This paper aims at analyzing tweets related to Covid-19 Vaccine, determining the sentiments about vaccination and extracting the significant topics. We performed multi-class sentiment analysis, steps comprising of pre-processing followed by training three different classification models: Gaussian Naïve Bayes, Support Vector Machine and LSTM. Results of the model obtained was one the three (Positive, Negative, Neutral) sentiment. Based on the outcomes, accuracy and F1- scores were computed to draw comparison between distinct models. Topic Modeling was performed using LDA on the combined tweets dataset to derive top seven important topics. In addition, Exploratory Data Analysis was also performed on dataset consisting of Vaccination Progress worldwide to bring out popularity of vaccines. © 2021 IEEE.

Entity-Based Knowledge Graph Information Retrieval for Biomedical Articles

In this paper, we present an information retrieval system on a corpus of scientific articles related to COVID-19 and biomedical. We build a heterogeneous entity-based knowledge graph network, where edges are shared between biomedical entities and paper names, where entities appear in abstract of the paper. The biomedical entities are derived from the abstract of the scientific articles using a fine-tuned Bio-BERT model. For a user query, entities are derived using a fine-tuned Bio-BERT model and then semantic similarity to query is employed for the return of the top-most relevant papers on the titles. We also provide a small set of results for the information retrieval system. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Envisioning the Veracity of Digital Ecosystem in Improvising Effective Pandemic Response

The obfuscation and the kind of cover-up or delay in COVID-19 crisis response put the veracity of global healthcare settings at stake and appended a biological dimension to geopolitical tensions. The ineffectual surveillance systems of public health and social measures cause the swift viral transmission pace amid mounting death toll and necessitate for an effective, cohesive, and strategic response. The digital ecosystem can serve the purposes intended in a transparent and immutable manner. This article highlights the problems encountered by the global healthcare settings in responding to pandemic and throws light on how the global digital ecosystem can handle crisis by managing the landscape radically through transparent information sharing via Internet of things (IoT) with the data being utilized by artificial intelligence (AI) and blockchain technologies on a cross-disciplinary collaborative basis. It will help to develop and provide borderless solutions of public health via monitoring, surveillance, detection, and prevention as well as digi-tool-assisted repurposed treatment by the use of authentic and decentralized distributed database that makes all contributors (participating countries, United Nations Organizations, the world medical associations, and global media and publications) accountable, inviolable, and efficient to tackle healthcare processes. It will extricate a blanket ban on information sharing thereby bringing democracy and freedom.

Lockdown to contain the covid-19 pandemic: An opportunity to create a less polluted environment in India

Keeping aside the economic consequences, the imposition of strict lockdown in order to break the chain of deadly infection of SARS-CoV-2, has potentially improved the global environmental quality by facilitating a significant reduction in atmospheric pollution. In the present study, the level of atmospheric pollutants in India viz., NO2, AOD, and PM2.5 before and during lockdown 2020 were assessed and compared using standard methods. The study revealed a significant reduction in NO2 i.e., > 10% change in 73.71% parts in India along with a high negative anomaly of AOD (< –1.0 in 32.92% parts in India) primarily in the Indo-Gangetic Plains, western, southern, and eastern parts during the lockdown. The five megacities observed a sharp decline in the daily mean concentration of PM2.5 (ca. 32% (Delhi) to 59.62% (Bengaluru) during the lockdown 2020 as compared to the analogous period of lockdown in 2019. The study exhibited the very less contribution of seasonal and meteorological variables in the abatement of pollution during the lockdown period. The findings may be useful in guiding future strategies to maintain environmental quality by adopting a well-planned lockdown strategy. © The Author(s).

Synthesis of Copper(II) Coordination Complex, Its Molecular Docking and Computational Exploration for Novel Functional Properties: A Dual Approach

The present investigation uses a dual approach to study the copper (II) complex [Cu(phen)3]. (ClO4)2.HL.CH3CN (1) and its cationic complex- [Cu(II)(phen)3]2+ (1 a), where, HL = 4-Bromo-2((Z) -(naphthalene-4-ylimino)methyl)phenol, phen=1,10-phenanthroline. The complex (1) crystallized in the triclinic system of the space group P-1 with two molecules in the unit cell and reveals a distorted octahedral geometry. Inspiring by recent developments to find a potential inhibitor for the COVID-19 virus, we have also performed molecular docking study of [Cu(phen)3]+2 to see if our novel complex shows an affinity for the main protease (Mpro) of COVID-19 spike protein. Interestingly, the results are found quite encouraging where the binding affinity and inhibition constant were found to be −8.400 kcal/mol and 0.661 μM, respectively, for the best-docked confirmation of [Cu(II)(Phen)3]+2 complex with Mpro protein. This binding affinity is reasonably well as compared to recently known antiviral drugs. For instance, the binding affinity of [Cu(II)(Phen)3]+2 complex is found to be better than recently docking results of chloroquine (−6.293 kcal/mol), hydroxychloroquine (−5.573 kcal/mol) and remdesivir (−6.352 kcal/mol) with Mpro protein. Thus, we believe the broad-spectrum functional properties of our complex will provoke not only the interest of material chemists in materials designing but also incite the drug designing community. © 2021 Wiley-VCH GmbH

Anaesthetic considerations for whole lung lavage for pulmonary alveolar proteinosis

Pulmonary alveolar proteinosis (PAP) is an uncommon lung disease characterized by excessive accumulation of pulmonary surfactant that usually requires treatment with whole-lung lavage. A 47-year-old female presented with history of dry cough and breathlessness for past 6months. Chest radiograph demonstrated bilateral alveolar shadows and high resolution computerized tomography thorax showed crazy paving pattern. Broncho-alveolar lavage (BAL) and transbronchial lung biopsy confirmed a diagnosis of PAP. Due to worsening hypoxemia and respiratory failure, wholelung lavage was planned and performed. Anaesthetic management involved integrated use of pre-oxygenation, complete lung isolation, one-lung ventilation with optimal positive end-expiratory pressure, vigilant use of positional manoeuvres, and use of recruitment manoeuvres for the lavaged lung. We have discussed valuable strategies for the anaesthetic management of patients undergoing this multifaceted procedure in a case of severe PAP. Funding: None declared.