Aggravation of CoVID-19 infections due to air pollutant concentrations in Indian cities

The CoVID-19 infections began rising worldwide during the initial weeks of March 2020, reacting to which the Government of India called for nationwide lockdown for ~ 3 weeks. The concentration of pollutants during the lockdown were compared with pollution levels recorded during the preceding year for the same time frame. A direct relationship was established between the high level of air pollutants (PM2.5, PM10, NO2 and SO2) and CoVID-19 infections being reported in the Indian cities. The correlation indicates that the air pollutants like PM2.5, PM10, NO2 and SO2 are aggravating the number of casualties due to the CoVID-19 infections. The transmission of the virus in the air is in the form of aerosols;and hence places which are highly polluted may see a proportionate rise in CoVID-19 cases The high-level exposure of PM2.5 over a long period is found to be significantly correlated with the mortality per unit confirmed CoVID-19 cases as compared to other air pollutant parameters like PM10, NO2 and SO2. © 2023, The Author(s), under exclusive licence to Korea Spatial Information Society.

Mask Recognition through Deep Learning

A major part of computer vision is formed by Object detection. Most of the such tasks are done with efficient object detection. This paper aims to incorporate techniques for facial mask detection to achieve an accurate and efficient mask detection algorithm. The goal is to examine various deep learning algorithms to perform mask detection in this era of Covid. This paper aims on building an application based on facial mask recognition using different deep learning algorithms and compare the results to find out the most accurate algorithm. © 2022 IEEE.

Impact Analysis of Aspirin over the Cardiac Activity

Cardiovascular disease (CVD) is the leading cause of death in most developed countries, including the United States, with a significant economic impact. Lifestyle changes and the administration of antiplatelet medication, like aspirin, may significantly contribute to the secondary prevention of CVD in adults. For years, aspirin has been utilized for both secondary and primary cardiovascular disease prevention. Aspirin has been extensively used because of the belief that it may have a positive impact on primary prevention, despite the debate surrounding its usage. This study briefly examines usage patterns and discusses the potential variables and factors that can decrease the ability of aspirin to prevent cardiovascular disease. The present study also explore the key studies of aspirin use in the context of recent recommendations. The risk of bleeding has been observed to significantly rise, although large randomized clinical studies have demonstrated a reduction or absence of CVD events. Prevention strategies for cardiovascular disease with low-dose aspirin are no longer advised for persons at intermediate risk. To determine whether taking aspirin is worth the potential dangers, the benefits must be evaluated.Copyright © 2022 Novyi Russkii Universitet. All rights reserved.

Natural prebiotics and probiotics in use as an alternative to antiviral drugs against the pandemic COVID-19

The loss to humanity that incurred due to Covid-19 pandemic is immense in terms of the number of people who lost their lives and even people, who contacted the SARS-Cov2 virus and have survived, who now display lowered immunity, mental stress, unemployment, and economic burden. As realized, vaccine development and clinical trials consume a lot of time and resources from the point of view of their therapeutic design, administration, and cost. Under such circumstances, natural therapeutics like probiotics and prebiotics—which could boost immunity—can be used as potential immunity boosters and antiviral drugs. Covid-19 leads to gut dysbiosis and interferes with the gut microbiota, and here comes probiotics and prebiotics to our rescue as they can help in the restoration of the microbiota along the gut-lung axis. With the growing realization of the importance of functional foods, a balanced diet, and healthy lifestyle habits for the promotion of good health, the research on prebiotics and probiotics is growing exponentially. The beneficial effects exerted by probiotics are due to microbial colonization in a particular organ, while the prebiotics are nondigestible fibers from food that can boost the production and endurance/ viability of probiotics. © 2023 Elsevier Inc. All rights reserved.

Analysis of COVID-19 outbreak using GIS and SEIR model

COVID-19 originated from Wuhan (China) in December 2019 and has spread rapidly throughout the world. As of August 2020, COVID 19 has affected more than 200 countries and has caused approximately 8 million casualties to date. Government agencies are announcing several mitigation measures based on the guidelines issued by the WHO and the UN. Presently, the top five countries badly affected by this virus are the USA, Brazil, India, Russia, and South Africa. Geographic Information System (GIS) is the technology used to detect, store, manipulate, and analyze spatial (latitude and longitude) information and may be used effectively for understanding and responding to the disease outbreak by real- or near real-time mapping of the diseases. In this study, we make an attempt to generate the Heatmaps (a graphical representation) in a GIS environment using QGIS (an open-source GIS software). Further, we extend the analysis of the study to the prediction of possible COVID-19 outbreak in India using SEIR (Susceptible—Exposed-Infectious-Recovered) model. SEIR model may be used for the prediction of any epidemic disease. This study may help researchers to analyze and predict the COVID-19. © 2023 Elsevier Inc. All rights reserved.

CFD Analysis of Ventilation of Indian Railway 2 Tier AC Sleeper Coach

In light of the ongoing COVID-19 pandemic, it is important to analyse the ventilation system of an AC coach for safer as well as comfortable ride. In this study we have simulated the airflow, temperature distribution and velocity distribution inside the cabin, to find out the best layout for comfortable temperature as well as reduced chances of airborne infection. We have simulated various ventilation layouts of the 2 tier AC train coach of Indian Railways, to study the effect of the position of the inlet and outlet ports on the temperature and velocity distribution inside the cabin. CFD analysis was done using the Ansys Fluent solver employing the realizable k-ε model to solve the turbulence problem. Herein, a total of 12 layouts were simulated with 6 heated manikins sitting inside the cabin. The results of the study suggested that the temperature distribution inside the cabin changes significantly with a change in the inlet port position. Further, the layout with the above window and/or roof outlet has a relatively lower cabin temperature. This study forms the basis for further investigations to analyse the transmission of infection via cough droplets inside the cabin (unreported here). The results of this research are important for finding the optimum position of the inlet and outlet ports in AC coaches to enhance the overall thermal comfort and reduce infection transmission inside the cabin. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

COVID-19 infection in kidney transplant recipients during the first versus the second wave-Retrospective Observational study from a single center

Background: Kidney transplant recipients (KTRs) are deemed to be at a high risk of severe coronavirus disease (COVID-19). Herein, we describe the clinical, laboratory profiles, management, and outcomes of 26 KTRs who developed COVID-19 during the first and second waves of the pandemic from a tertiary care center in northern India. Methods: This retrospective observational study included KTRs detected with COVID-19 infection during the first wave (March-November 2020) and the second wave (March-July 2021). Their clinical and laboratory investigations, management aspects, and outcomes were compared, using data retrieved from clinical and telenephrology records, and the hospital information system. Results: Of the 23 KTRs, 20 were male (86%), 20 patients had fever (86%), and cough and breathlessness were seen in 19 (82%) and 12 (52%), respectively. Acute graft dysfunction was seen in 6 (26%) patients, and the need for renal replacement was seen in 4 (17%) patients. Supplemental oxygen by reservoir mask was utilized in 10 (43%) patients, high-flow nasal cannula in 3 (13%), noninvasive mechanical ventilation in 4 (17%), and invasive mechanical ventilation in 6 (26%) patients. All the KTRs with moderate and severe COVID illness and 6/7 nonsurvivors were infected during the second wave. Overall mortality in this group of patients was very high at 27%, and the mortality in the group on mechanical ventilation was 100%. Conclusions: The second wave of the COVID-19 pandemic was associated with greater severity of illness and high mortality in KTRs.

Comparative Analysis of COVID 19 Detection from Cough Speech Using Machine Learning Classifiers

Corona Virus Disease-2019, or COVID-19, has been on the rise since its emergence, so its early detection is necessary to stop it from spreading rapidly. Speech detection is one of the best ways to detect it at an early stage as it exhibits variations in the nasopharyngeal cavity and can be performed ubiquitously. In this research, three standard databases are used for detection of COVID-19 from speech signal. The feature set includes the baseline perceptual features such as spectral centroid, spectral crest, spectral decrease, spectral entropy, spectral flatness, spectral flux, spectral kurtosis, spectral roll off point, spectral skewness, spectral slope, spectral spread, harmonic to noise ratio, and pitch. 05 ML based classification techniques have been employed using these features. It has been observed that Generalized Additive Model (GAM) classifier offers an average of 95% and a maximum of 97.55% accuracy for COVID-19 detection from cough signals. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Analyzing The Factors Affecting Media Consumer Trends During The COVID-19 Period - The Rise Of Web Series By Different Otts V/S Traditional TV Serials In India

In the recent decade OTT platforms, also known as "Over the top," have seen a tremendous rise in the number of consumers and also gained a huge market share in the entertainment industry. The OTT service most users probably interact with regularly is video OTT. Services like Netflix and Disney+ Hotstar are video OTT services that provide users with a number of programming options, both in terms of a licensed library of TV shows and films and original programming. The study's objective is to carry out a detailed study of OTT (over-the-top) platforms, and how and why OTT platforms are rising in India. This study also investigates OTT platforms at the time of the COVID-19 pandemic. We found that recent years have witnessed several films emerging as pan-India hits, and the rise of alternative platforms has only widened the opportunities for actors and filmmakers. This study concludes that there is no competition between theatres and digital platforms filmmakers must up their game. OTT has resulted in more opportunities and redefined viewership patterns. Films and other mediums will thrive together because the same actors and makers are exploring different platforms. Copyright © 2023 Ubiquity Press. All rights reserved.

E-Payment System reforms and its impact on Currency in Circulation in India: Evaluation using Vector Autoregressive Model (VAR)

The present study contributes to the literature by investigating the impact of E-Payment System on Currency in circulation after facing three major reforms i.e., Demonetization of 500 and 1000 rupee note, implementation of GST and Current pandemic (Covid-19) situation. Results imply that with the increase in the volume of all the respective electronic payment systems the currency in circulation (in physical form) got minimized in the economy. Moreover, NEFT shows much higher influence on currency in circulation as compare to RTGS and IMPS but PPI’s shows the highest influence on currency in circulation from the selected E-Payment systems. Furthermore, Vector Autoregressive model suggests, RTGS, IMPS, NEFT, CARDS (POS), PPI’s, M-Banking are expected to increase whereas NACH is expected to observe a downfall in the near future. © 2022, School of Management Sciences. All rights reserved.

UPMRC: rewriting the success story of Lucknow Metro during Covid-19 crisis

Learning outcomes: After working through the case and assignment questions, students will be able to understand the following aspects:▪ how good strategic planning can convert a crisis into an opportunity;▪ importance of service excellence and customer satisfaction through customer delight and customer feedback;and▪ utilisation of resources and excellent time management strategies. Case overview/synopsis: This case discusses how vital teamwork and motivated leadership can convert a crisis such as Covid-19 into an opportunity. This case study talks about Uttar Pradesh Metro Rail Corporation (UPMRC), a metro rail corporation working to develop metro trains in the Indian state of Uttar Pradesh. The case discusses how challenging it was for the metro rail corporation to transform its processes in a short period and deal with the crisis on major fronts such as facilities maintenance, human resource management, ensuring safety and security of its staff and riders, motivation of staff, service quality and maintaining all operational aspects. The case discusses how UPMRC is a leader on all fronts and has excelled in its operational work. It talks about what challenges the lockdown and unlocking phase posed in front of the leadership and how teamwork, dedication to exemplary service quality and customer satisfaction gave the team the strength to make changes that improved their processes and helped them overcome the crisis.The case starts with a discussion of metro rail inception and incorporation of UPMRC and then how this newly formed metro has to face the challenges of pre-lockdown period where the team worked very hard for sanitisation and safety. The lockdown created a completely different set of challenges related to the facilities and the entire metro train systems, which was a difficult situation to deal because of restrictions and other challenges. However, the team dealt with situations with strength and strategic planning, leading to better managed processes and staff. The unlocking phase also gave many challenges that the team handled with a lot of care and efficiency. Complexity academic level: This case is suitable for post-graduate-level courses on services marketing, service operations management, general management, crisis management and strategic management. Participants can use the case to develop an understanding of strategic planning and management.This case can also be used in the executive education program for managers to encourage them to think through challenges faced by metro rail corporations. Supplementary materials: Teaching notes are available for educators only. Subject Code: CSS 10: Public Sector Management. © 2022, Emerald Publishing Limited.

CFD Analysis of Ventilation of Indian Railway 2 Tier AC Sleeper Coach

In light of the ongoing COVID-19 pandemic, it is important to analyse the ventilation system of an AC coach for safer as well as comfortable ride. In this study we have simulated the airflow, temperature distribution and velocity distribution inside the cabin, to find out the best layout for comfortable temperature as well as reduced chances of airborne infection. We have simulated various ventilation layouts of the 2 tier AC train coach of Indian Railways, to study the effect of the position of the inlet and outlet ports on the temperature and velocity distribution inside the cabin. CFD analysis was done using the Ansys Fluent solver employing the realizable k-ε model to solve the turbulence problem. Herein, a total of 12 layouts were simulated with 6 heated manikins sitting inside the cabin. The results of the study suggested that the temperature distribution inside the cabin changes significantly with a change in the inlet port position. Further, the layout with the above window and/or roof outlet has a relatively lower cabin temperature. This study forms the basis for further investigations to analyse the transmission of infection via cough droplets inside the cabin (unreported here). The results of this research are important for finding the optimum position of the inlet and outlet ports in AC coaches to enhance the overall thermal comfort and reduce infection transmission inside the cabin. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

COVID-19 Disease Detection using Pre-Trained Deep Convolutional Neural Network (GoogleNet) on Cloud Platform

Background and Purpose: The COVID-19 epidemics are causing the main rash in more than 151 countries around the whole world.Covid-19 has a bad effect on human life worldwide. One of the critical steps in fighting COVID-19 is finding the contaminated patients early enough and putting these infected people under special care. Our main aim is to separate COVID-19 patients from other patients. Materials and Methods: In this research article, we used GoogleNet as a learning network. GoogleNet is a deep convolutional neural network of 22 layers deep. We have used a pre-trained version of the GoogleNet trained on ImageNet. The pre-trained GoogleNet image input size is 224 x 224.GoogleNet;the deep convolutional neural network model can analyze X-ray images to classify the patient’s condition of the affected disease. Result: Experiments and evaluation of the GoogleNet have been effectively done based on 80% of X-ray pictures for training and 20% of X-ray pictures for testing phases respectively. GoogleNet shows a good result for disease classification with 91.40% of accuracy in 2.49 minutes. Conclusion: In this research paper, we have used the deep CNN model to classify COVID-19 disease using X-ray images based on the projected GoogleNet. Scientific studies will be the next goal of this research article.

Mass Gathering and Population Movement in India: Possible Risk of Vector-Borne Diseases

Surveillance tools measure and help to predict the possibility of the onset of any disease including vector-borne diseases during some specific situations likemass gatherings (MGs) that are closely related tothe disease epidemiology (why, what, who, where, when, and how)concerningthe transmission of infectious diseases including vector-borne diseases. Some situations ofmass gatherings may bring closely large and diverse population groups coming from different endemic zones/areas leading tothe transmission of communicable diseases including vector-borne diseases. Mass gatherings (MGs) may have the potential to enhance the transmission dynamics of vector-borne diseasesowing to different geographical, social, and climatic factors. Usually, MGs have been thought to have enhanced risks of disease transmission.Theyalso have the potential to increase the opportunities for other types of mechanical injuriesfrom accidents, stampedes, alcohol use, internal group fights etc. that may result in morbidity or mortality.Besides, they are potential breeding places for the proliferation of vector species, capable of transmitting malaria, dengue, chikungunya, and JE including ticks and mites-borne diseases. It is a well-known fact there area large number of asymptomatic cases which act as sub-clinical cases, hence, chances of local transmission through vectors during such mass gatherings can not be ruled out.There is always a need for well-structured, intensified real-time disease and vector surveillance and reporting systems in place which is essential for efficient MG planning, to ensure disease prevention and control. In the present context of the ongoing COVIDpandemic, such surveillance systems havebecome a vital component of such events of mass gatherings and large-scale movement of people. © 2022: Author(s).

Urban Flood Relief Management in COVID-19 Pandemic

Introduction: Urban floods were addressed as a separate disaster after the historical 2005 Mumbai floods. Urban flood peaks are 2-8 times and volume 6 times when compared with rural floods. We are now handling multiple disasters simultaneously due to the Covid-19 Pandemic. The river plains of north India are prone to floods in the monsoon season and geographical location of Prayagraj doubles the damage because it faces wrath from two sides. Very few researches have been conducted on urban floods and evidence needs to be generated from the field. Methodology: This qualitative research was planned with an objective to identify the difficulties faced in operating an urban flood relief camp during superimposed burden of COVID-19 Pandemic and to suggest remedial measures from the public health aspect. We conducted in-depth interviews of nodal officers, health staff and beneficiaries of the identified camps. Informed consent was taken from participant after explaining them about the research. Results: The findings from the interviews were categorized into 3phases of flood relief i.e. before the floods, during floods and lastly post flood. The most crucial work before floods is to spread awareness about do’s and don’ts in detail. Next was identification of the local people actually affected by flood. The space and facilities at few centers was low for the population load. Urban flood management needs a major overhauling of public health infrastructure to handle such disasters in future. Conclusion: The officials were working hard to make the homeless feel as if they are on a picnic. The database of beneficiaries should be strengthened and should also include students and labourers, anyone who is a flood victim and not only local flood victims. © 2022, Indian Association of Preventive and Social Medicine. All rights reserved.

COVID-19 VARIANTS OF CONCERNS TRACKING: HOW WE EASED OUT THE WHOLE PROCESS THROUGH OPEN-SOURCE SOFTWARE IN MADHYA PRADESH, INDIA

Objective: To comprehend the evolution and spread of the severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) virus and also to prevent the future spread of the same, sequencing and analyzing the genomic data of SARS CoV-2 are essential. The objective of the present study is to describe the scope of improvement identified by the state of Madhya Pradesh in the data flow chain and the methodology designed to address the identified shortcomings. Methods: The number of sources of sample data collection was altered as well as a series of Google Sheets were formulated as an open-source tool, to implement an efficient sample data-sharing platform. The application of the proposed tool (Google Sheets as a source of data collection and information sharing) was within the state of Madhya Pradesh, India. Result: After utilizing this mechanism, the state was able to trace more than 80% VOCs and 3341 primary contacts and was also able to communicate this result to all stakeholders without much delay. Conclusion: Based on successful implementation and results, the authors suggest widening the domain of the proposed tool to other states.

Healthcare Data Security Using Lightweight Protocol for Cyber Physical System

Healthcare systems are equipped with the latest technological advancement and remotely diagnose the patients. In critical conditions, the patients need continuous monitoring by health experts, which is almost impossible in many cases—for example- in the recent COVID-19 crisis when the hospitals are full of infected people. The advanced cyber-physical system (CPS) based medical devices supplement this monitoring system. Health specialists can connect with patients remotely and receive updated health reports simultaneously using Internet-enabled CPS devices. Due to the openness of security protocols, transferring information in the CPS module is a challenging task. Securing health data, on the other hand, is critical. Existing data security techniques, such as RSA and DSA, have drawbacks;one of the most prominent drawbacks of all existing data security strategies is a lack of resources. This study proposed a lightweight data security technique for sharing information in real-time to address this problem. The proposed approach is generalized, as it will work with all categories of data and provide security to the critical information of healthcare data. Additionally, the model is tested with the cross-platform dataset of different categories like.txt, .pdf, .doc, .png, etc., and found promising outcomes. IEEE

Potential of the triad of fatty acids, polyphenols, and prebiotics from cucurbita against COVID-19 in diabetic patients: A review

Though the scientific community of the entire world has been struggling to create preventive and therapeutic drugs for coronavirus disease 2019 (COVID-19), the role of nutraceuticals has been hitherto neglected. Established role of fatty acids and polyphenols in combating lifestyle disease can be harnessed to play a significant role in the prevention of this disease. The synergistic effect of these phytonutrients and prebiotics is anticipated to prove beneficial for prevention as well as attenuation of COVID-19 infection. Presence of fatty acids, polyphenols and prebiotics in vegetables from the Cucurbitaceae family makes them an attractive choice for being used as a nutritional supplement during COVID-19. These are known to attenuate the excessive immune response which may prove to be beneficial in preventing and mitigating COVID-19. Use of prebiotics to promote the growth of probiotics has also been recommended for the prevention and cure of COVID-19. However, no such report exists in literature that throws light on such role of cucurbita plants. The present review focuses on the role of the triad of fatty acids, prebiotics and polyphenols present in cucurbita plants in controlling systemic inflammation and endothelial damage, the two main etiopathological factors involved in COVID-19. Cucurbita plants are rich in all these components and their inclusion in diet would be an effective strategy to combat COVID-19. The main focus of the review is to discuss the role of various components of the plants of Cucurbita family, taken as dietary component, in prevention and control of the ongoing pandemic COVID19.

An Artificial Intelligence Technique for Covid-19 Detection with eXplainability using Lungs X-Ray Images

According to the World Health Organization, the coronavirus outbreak poses a daily threat to the global health system. Almost all countries' health resources are insufficient or unequally distributed. There are several issues, such as a lack of health care workers, beds, and intensive care units, to name a few. The key to the country's health systems overcoming this epidemic is to use limited resources at optimal levels. Disease detection is critical to averting an epidemic. The greater the success, the more tightly the covid viral spread may be managed. PCR (Polymerase chain reaction) testing is commonly used to determine whether or not a person has a virus. Deep learning approaches can be used to classify chest X-RAY images in addition to the PCR method. By analyzing multi-layered pictures in one go and establishing manually entered parameters in machine learning, deep learning approaches have become prominent in academic research. This popularity has a favorable impact on the available health datasets. The goal of this study was to detect disease in persons who had x-rays done for suspected COVID-19 (Coronavirus Disease-2019). A bi-nary categorization has been used in most COVID-19 investigations. Chest x-rays of COVID-19 patients, viral pneumonia patients, and healthy patients were obtained from IEEE [17] (Institute of Electrical and Electronics Engineers) and Kaggle [18]. Before the classification procedure, the data set was subjected to a data augmentation approach. These three groups have been classified through multiclassclassification deep learning models. We are also debating a taxonomy of recent contributions on the eXplainability of Artificial Intelligence (XAI). © 2022 IEEE.