Novel Coronavirus in India and Outbreaks Around World: A Statistical Analysis of Odisha, India and the World

Background: The Public Health Emergency of International Concern by the World Health Organization (WHO) declared novel Coronavirus (nCoV-2019) outbreaks in 2019 as pandemic. Method(s): This research work made an analysis of the nCoV-2019 outbreak in India solely based on a mathematical model. Result(s): The historical epidemics in the world are plague, AIDS, Swine flu, ebola, zika virus, Black Death and SARS. Considering the model used for SARS 2003, the present research on COVID-2019 estimates characteristics of the rate of infections (I) and rate of recovery(R), which leads to the estima-tion of the I and R leading to predict the number of infections and recovery. Through ruling out the un-predictable and unreasonable data, the model predicts that the number of the cumulative 2019-nCoV cases may reach from 3398458 (mid of May) to 15165863, with a peak of the unrecovered infection (2461434-15165863) occurring in late April to late July. In this paper, we predicate how the confirmed infected cases would rapidly decrease until late March to July in India. We also focus on how the Gov-ernment of Odisha (a state of India) creates history in the protective measures of COVID-19. Conclusion(s): The growing infected cases may get reduced by 70-79% by strong anti-epidemic measures. The enforcement of shutdown, lockdown, awareness, and improvement of medical and health care could also lead to about one-half transmission decrease and constructively abridge the duration of the 2019 n-CoV.Copyright © 2021 Bentham Science Publishers.

Ensemble Deep Convolution Neural Network for Sars-Cov-V2 Detection

-The continuing Covid-19 pandemic, caused by the SARS-CoV2 virus, has attracted the eye of researchers and many studies have focussed on controlling it. Covid-19 has affected the daily life, employment, and health of human beings along with socio-economic disruption. Deep Learning (DL) has shown great potential in various medical applications in the past decade and continues to assist in effective medical image analysis. Therefore, it is effectively being utilized to explore its potential in controlling the pandemic. Chest X-Ray (CXR) images were used in studies pertaining to DL for medical image analysis. With the burgeoning of Covid-19 cases by day, it becomes imperative to effectively screen patients whose CXR images show a tendency of Covid-19 infection. Several innovative Convolutional Neural Network (CNN) models have been proposed so far for classifying medical CXR images. Moreover, some studies used a transfer learning (TL) approach on state-of-art CNN models for the classification task. In this paper, we do a comparative study of these CNN models and TL approaches on state-of-art CNN models and have proposed an ensemble Deep Convolution Neural Network model (DCNN). General Terms: Neural Network, Deep Learning (DL), Covid-19, Chest X-Ray (CXR), Medical Image Analysis. © 2022 by Subrat Sarangi, Uddeshya Khanna and Rohit Kumar.

Tailoring magnetism in spinel vanadate CoV2O4epitaxial thin films.

Near itinerant cubic bulk CoV2O4is at variance with other spinel vanadates by not showing orbital ordering down to low temperature, albeit it displays fragile anomalies related to spin, and lattice structure, signaling a spin/orbital glass transition around 95 K. We investigate tetragonal-like epitaxial CoV2O4films on SrTiO3and (La0.3Sr0.7)(Al0.65Ta0.35)O3substrates that exhibit pronounced signature of spin reorientation transition from toa/bplane around 90 K unlike its bulk counterpart. Using in-plane and out-of-plane magnetic measurements, we demonstrate the intricate link between Co2+and V3+sublattice magnetizations that give rise to anisotropic magnetic switching. In-plane magnetic measurements reveal a wasp-waist shapedM(H) loop below reorientation transition temperature, while the out-of-plane follows antiferromagnet-likeM(H) response. The wasp-waist shaped feature could be linked to in-plane spin-canted (anti)ferromagnetism induced by canting away of V-spins away from antiferromagnetically coupled Co-spin direction below reorientation transition temperature. Further, we uncover the evidence for slow relaxation over a period of ∼104 s at 20 K and memory effect that indicates the possible existence for magnetic glassy phase in the low temperature regime. Using epitaxial strain as a control knob, our results inspire future study to manipulate orbital states, spin texture and itinerant electron character in tailored CoV2O4films away from cubic lattice symmetry.

Attitude, anxiety, psychological effects and prevention during covid-19 in India

With previous health warnings, personal anxieties could feed behavioral changes with many people of India considering notable changes in their transportation use and anticipating in preparation the purchase of goods, particularly masks. Asian respondents were especially likely to have talked about the pandemic with friends, whereas one-fourth of respondents globally had talked about the pandemic with their family. Our data on the correlation indicates that these conversations may increase existing rates of anxiety. Practitioners need to be mindful that rumors spread rapidly during periods of pandemic danger, with significant risks of both emotional and physical ‘contagion’ amongst individuals. Any rise in anxiety may lead to sudden changes in behavior, which can quickly lead to shortages and can enhance the need for treatment at home.

Procedural rationality in the time of COVID-19

Homo economicus, the typical economic man, is a rational agent whose goal is to find the optimal solution to any problem. However, this may not be feasible in complex situations like the current global pandemic. We argue that in such environments where Knightian uncertainty plays a big role, the behaviour of countries, sectors of the economy, and individuals may be characterised by procedural rationality. Instead of focusing on the outcome, it is argued that the decision-maker draws upon similar experiences and follows a consistent procedure. © 2020 Economic and Political Weekly. All rights reserved.