New Onset Diabetes Mellitus in Post Covid Patients - an Observational Study

Background and Aims: The novel coronavirus,binds to angiotensin- converting enzyme 2 (ACE2) receptors, which are expressed in key metabolic organs and tissues, including pancreatic beta cells, adipose tissue, small intestine and kidneys. COVID-19 is attributed to the cytokine storm, followed by pancreatic cell damage.Thus, it is plausible that SARS-CoV-2 may cause pleiotropic alterations of glucose metabolism that could complicate the pathophysiology of pre-existing diabetes or lead to new onset Diabetes Mellitus.Thus, the study aims to analyze the development of new onset diabetes in post covid patients Methods: Serum glucose level of 500 patients, between the age of 18 to 50 who were previously normoglycemic and recovered from COVID-19 was measured and incidence of new onset diabetes mellitus was obtained. Result(s): Out of 500previously normoglycemic COVID-19 patients selected for the study, 97 patients (19.4%) developed new onset diabetes mellitus after recovering from COVID-19 disease. Conclusion(s): The results of this study show that a significant amount of people developed new onset type 2 diabetes mellitus after having recovered from COVID-19. Blood glucose control is important not only for prediabetics affected with COVID but also for those affected with no previous status of diabetes mellitus. The results of this paper could be useful in screening and diagnosis of new onset diabetes mellitus at an early stage can be beneficial to avoid further worsening of the patient's health.

Covid Explorer- A Web Based Covid Analysis and Tracking

In this paper, Covid Explorer model's aim is to provide information on Covid 19 like-how you can prevent the Corona Virus, symptoms of Corona Virus or how to book slots for the Corona Virus. You can add the current data related to Covid 19 like a graph indicated the increase or decrease of death rate from this virus, a report is given to show the death rate, the number of vaccines doses given on a particular day, state wise cases are also shown through Application Programming Interface (API) in Covid Explorer model. The model is analyzing and tracking Corona Virus. As per the data analysis this pandemic creates mental health issues but if a model gave up-to date data of the current scenario then stress can be overcome and society can fight against this pandemic. © 2022 IEEE.

An Optimized Modelling and Simulation on Task Scheduling for Multi-Processor System using Hybridized ACO-CVOA

Task allocation on the multi-processor system distributes the task according to capacity of each processor that optimally selects the best. The optimal selection of processor leads to increase performance and this also impact the makespan. In task scheduling, most of the research work focused on the objective of managing the power consumption and time complexity due to improper selection of processors for the given task items. This paper mainly focusses on the modelling of the optimal task allocation using a novel hybridization method of Ant Colony Optimization (ACO) with Corona Virus Optimization Algorithm (CVOA). There are several other methods that estimate the weight value of processors and find the best match to the task by using the traditional distance estimation method or by using standard rule-based validation. The proposed algorithm searches the best selection of machines for the corresponding parameters and weight value iteratively and finally recognizes the capacity of it. The performance of proposed method is evaluated on the parameters of elapsed time, throughput and compared with the state-of-art methods. © 2022 Institute of Information Science. All rights reserved.

Real-Time Face Mask Detection Using CNN in Covid-19 Aspect

The COVID-19 pandemic has reshaped everyone’s life as we know it. Many measures and proposals have been suggested to prevent the virus’s rapid spread since scientists detected it. In the midst of many of these, one major piece of advice was to “wear a mask!”. The mask or face coverings can protect the wearer from contracting the virus or spreading it to others. Hence, to ensure that the public is not wearing a mask, one of the applications we have developed is face mask detection, which uses biometrics to map the features of a human face, analyse the data, and determine whether the detected face is a positive image or a non-face or negative image by placing a box around it. The main ideology of studying and researching face mask detection is to use computer technology to directly mimic the action and manner of human facial features and develop a system that reduces the amount of effort required to identify whether or not the person is wearing a mask and notifying them with the assistance of the proposed model. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

COVID-19 Data Forecasting Using Soft Computing Technique

Corona viruses are large family of viruses that may affect human and animals. Middle East respiratory syndrome (MERS) and severe acute respiratory syndrome (SARS) are the respiratory infections caused by several corona viruses in human. COVID-19 is an infectious disease due to most recently discovered Corona virus. This Corona Virus Disease (COVID-19)’s outbreak was started from Wuhan, China in December 2019. The disease can spread from one person who has the virus to another person who is not infected. This is how the outbreak began and became a pandemic. This pandemic has become the biggest problem in the world. Number of infected and deaths are gradually increasing throughout the world. This effort is to analysis the graph and determine that when the graph will go down. Basically, we will make the prediction using some a time series forecasting techniques based on neural network. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Pharmacogenomic landscape of COVID-19 therapies from Indian population genomes.

Aim: Numerous drugs are being widely prescribed for COVID-19 treatment without any direct evidence for the drug safety/efficacy in patients across diverse ethnic populations. Materials & methods: We analyzed whole genomes of 1029 Indian individuals (IndiGen) to understand the extent of drug-gene (pharmacogenetic), drug-drug and drug-drug-gene interactions associated with COVID-19 therapy in the Indian population. Results: We identified 30 clinically significant pharmacogenetic variants and 73 predicted deleterious pharmacogenetic variants. COVID-19-associated pharmacogenes were substantially overlapped with those of metabolic disorder therapeutics. CYP3A4, ABCB1 and ALB are the most shared pharmacogenes. Fifteen COVID-19 therapeutics were predicted as likely drug-drug interaction candidates when used with four CYP inhibitor drugs. Conclusion: Our findings provide actionable insights for future validation studies and improved clinical decisions for COVID-19 therapy in Indians.

Educational assistance bot

An Internet bot performs automated tasks over the Internet. This software application is also known as a web robot or robot or simply bot, Typically, bots runs simple and structurally repetitive tasks, at a much higher rate than would be possible for a human alone. This effort is to help the users by providing all the basic student’s academic details like subjects, faculty names, books, notes and routine according to their need using bot. Users can also get other information like fees structure, library inventory list, calendar etc. Additional information like top educational sites, most trending educational videos etc will be regularly updated by the admin. This is an all-in-one application which can also be used to fetch and update information which is purely related to COVID-19. © 2021 Institute of Physics Publishing. All rights reserved.