Study of body composition analysis in the view of obesity prognosis

Chronic overweight is characterized by significant elevations in abdominal fat as well as changes in the composition of fat free mass, particularly total body fluids and its interstitial compartment. The applied in the real restrictions placed by morbid obesity, as well as changes in body content from those of healthy weight, provide enormous hurdles to fat percentage assessment. This research concentrates on some of the research and practice challenges connected with using popular fat percentage measures, and it finds available evidence on suitable approaches for use in extremely obese people. There is already little scientific literature on which body composition measures may be utilised confidently in very obese people. A typical 3 model that combines readings of body mass by air - assisted plethysmography and total body liquid by bio-electrical impedance could provide metrics of percentage body fat in the extremely obese that are significant compared to a conventional, technically skilled 3 storage area prototype that requires infrastructure including such isotopic ratios mass spectrometry as well as important technological knowledge. This study focuses on a few fundamental issues that investigators and physicians confront when doing anthropometric studies on highly obese individuals. A 3 basic framework that is efficient and simple to implement shows potential for usage in this community. Nonetheless, more study on this and other suitable techniques of fat percentage measurement in a broad sample of extremely overweight adults is required. © 2023 Author(s).

Development of hybrid technology using Machine Learning and Block chain Technology to prevent from COVID 19 through the proper information gathering

Blockchain and artificial intelligence (AI) have shown promise in combating the Covid epidemic. Blockchain in particular may aid in early detection to fight pandemics. The methods established for infection prevention include the use of face masks, public isolation within a 6 metre radius, regular check-ups, and two doses of vaccinations.This system has features for detecting masks, people, temperature, information tracking, in-person interactions, and a person's medical history. Diseases might be monitored and their spread contained with the advancement of technology and the rise in smartphone use. Because additional economic sectors are opening up and because Covid is still spreading widely, adhering to the guidelines is more important than ever for avoiding infection. © 2023 IEEE.

Molecular Modelling and Docking Simulation for Unravelling Medicinal Properties of Soor and Pakhoi, the Lesser-Known Traditional Drinks of Himalayas

With the spread of COVID-19, it has become a high need of finding out the drugs that can combat and prevent this deadly disease. Most of the researchers are finding suitable drugs by using coronavirus spike protein as a target. In this study, we have used alternate drug targets of the coronavirus and have used the phytochemicals of the alcoholic beverage of Tons Valley, Garhwal Himalayas called Soor and Pakhoi, to check whether the drink could act as an antiviral agent. For this purpose, modern computational techniques like molecular modelling and docking simulation with the help of iGEMDOCK software have been used in finding out the permissible results in the form of high docking interaction energy. Therefore, the specific binding of the phytochemicals with the viral protein could disrupt the natural targets of the virus with the viral proteins. Hence, Soor and Pakhoi can be a deterrent source for the coronavirus infection. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

PVR Limited at a crossroads

Learning outcomes: The case study "PVR Limited at a Crossroads” has been designed with the requirements of strategic management. The learning objectives are as follows: • Situational analysis – understand the global and Indian media and entertainment industry PESTEL. • Strategic planning – internal and external environmental analysis – strength, weakness, opportunities and threats (SWOT) analysis helps in achieving the strategic plan. • Strategy development – to accomplish the turnaround plan, various alternatives are developed;choosing from the possible alternatives is a part of strategic planning. Case overview/synopsis: PVR Limited (PVR) is the largest premium film exhibition company in India. In their annual report for 2019–2020, Chief Executive Officer Gautam Dutta acknowledged, "It was the first time in our more than two-decade history that we witnessed over 100 million patrons entering our premises in a year”. However, with the onset of Covid-19 pandemic in January 2020, things changed for the entertainment industry in India. There were fears of an eminent third wave and the detection of a new Covid-19 variant, Omicron, added to these fears. Being a major player in the game, PVR felt the impact. And even when the business started to reopen, social distancing remained a concern and ticket sales were impacted. Over-the-top viewership rose dramatically at the cost of the multiplex. The lockdown halted film productions worldwide, leading to a shortage of content. Other revenue streams, such as food and beverage, convenience fees and advertising, also came to a halt. Given the circumstances, Dutta was facing the twin dilemma of how to bring customers back to cinema in a post-pandemic world without in any way compromising the security of its patrons and keeping costs under control while investing in social distancing, safety measures and entertainment infrastructure to enhance the cinematic experience. Complexity academic level: This case was written for use in Strategic Management classes at the undergraduate and MBA levels. It can be used in both management studies and executive development programs. It is suitable for courses on strategic management and strategic planning focusing on a turnaround strategy. Additionally, the case could be used in consumer behaviour courses in management as the focus of the case is well aligned with discussions related to change in consumer behaviour. Supplementary materials: Teaching notes are available for educators only. Subject code: CSS 11: Strategy. © 2022, Emerald Publishing Limited.

Develop a Model for Assessing the Most Efficient Diseases Diagnosis using Machine Learning

so, machine learning techniques are being developed to improve performance and maintenance prediction. Increasing our knowledge of the relationship between humans and algorithms, Because data is so valuable, improving strategies for intelligently having to manage the now-ubiquitous content infrastructures is a necessary part of the process toward completely autonomous agents. Numerous researchers recently developed numerous computer-aided diagnostic algorithms employing various supervised learning approaches. Early identification of sickness may help to reduce the number of people who die as a result of these illnesses. Using machine learning techniques, this research creates an efficient automated illness diagnostic algorithm. We chose three key disorders in this paper: coronavirus, cardiovascular diseases, and diabetes. The data are inputted into a mobile application in the suggested model, the investigation is then done in a real-time dataset that used a pre-trained model machine learning technique trained within the same dataset then implemented in firebase, and lastly, the illness identification result can be seen in the mobile application. Logistic regression is a method of prediction calculation © 2022 IEEE.

Lichen as potential armamentarium against the SARS CoV-2 (COVID-19)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a strain of coronavirus that causes COVID-19 (coronavirus disease 2019), has been responsible for a respiratory tract disease which has taken the proportion of the pandemic (COVID-19) ravaging the planet for last 2 and half year. The COVID-19 pandemic has been responsible for about sixty-one million deaths and about 500 million infections worldwide. The medication of infected individuals has been mainly cantered around repurposing of available known antiviral drugs, immunosuppressor/ immunomodulator drugs, monoclonal antibody concoctions and various vaccines as prophylaxis measures. Use phytometabolites in studies have been found to very effective in counter the SARS-CoV-2 spike protein binding sites, the main step to virus attack on the respiratory epithelial cells. Lichen secondary metabolites are well known for their antimicrobial, immunomodulator and antiviral activities. Current study was done to assess the spike protein binding capabilities of some lichen secondary metabolites of SARS-CoV-2 (Wuhan strain) spike protein binding sites using in-silico docking modelling. The study found that some of the lichen metabolites such as Cryptostictic acid and Quaesitic acid were effective in blocking the target cell recognising regions of the SARS-CoV-2 spike protein and can be effectively developed as therapeutic medicine.

An observational cross-sectional study on the neuropsychiatric manifestations of covid-19 pandemic in suspected and positive patients in northern India

Psychotherapy and grief reduction have been the mainstays of mental health care. Mental health on the other hand, is distinct from the lack of ‘Mental Illness in that it encompasses psychological, social, and psychological wellbeing. The purpose of this study is to assess the Hamilton Depression Rating in COVID-19 patients in a tertiary care facility in Northern India. An observational study of Covid-19 positive individuals hospitalized to a tertiary healthcare centre in northern India was conducted. Over the course of six months, 1040 Covid-19 positive/ suspected individuals were enrolled in this study. The HDRS (Hamilton Rating Scale for Depression) was designed with hospital patients in mind, stressing the physical signs and symptoms of depression. The HAM-D scale is used to assess the severity of depression in patients with Covid-19. Despite the fact that there are 21 sections, the patient's score is based on the first 17 responses. During the six-month research period, a total of 1040 covid-19 suspected and positive patients were admitted. There were 240 covid-19 positive patients and 800 covid-19 suspicious patients out of a total of 1040. In positive patients, anxiety was present in 95.83 percent, mood change in 55 percent, and fear of death 23.33 percent;in suspected covid-19 patients, anxiety was present in 57 percent, mood alteration in 19 percent, and fear of death 13.5 percent. According to current research, severe COVID-19 may produce delirium in the acute stage of disease, followed by depression, anxiety, lethargy, insomnia, and post-traumatic stress disorder (PTSD) in the long term. © 2021 MEDIC SCIENTIFIC. All Rights Reserved.

In-silico analysis of interaction of human tetherin protein with sars-cov-2orf7a proteins and its mutants

Objective: One of the best ways to counter any pathogen including SARS-CoV-2 is through enhancement of self-immune response. Tetherin or BST2 is one such interferon-induced antiviral protein or immune regulatory protein of the human host that can restrict the release of virions of SARS-CoV-2. The ORF7a encoded protein of SARS-CoV-2 in-turn has been found to act as an antagonist to the human tetherin protein by interacting with key amino acid residues, thereby weakening the immune response. Methods: In this research after consensus analysis of results from various servers mutations have been induced in selected residues of ORF7a coronavirus protein. Most conserved residues have been obtained through Consurf server, ligand binding pockets, and active sites have been identified after combining results from multiple servers like CastP and 3DLigand Site. Results: The most deleterious mutation has been identified through DUET and DynaMut servers and mutations induced thereafter have been tested for a decrease in binding affinity through the HawkDock server. The protein-protein interaction studies have been performed before and after the induction of mutation through the HawkDock server. Conclusions: The decrease in binding affinity between human tetherin and ORF7a protein is supportive of the need to study the induction of mutation and its detrimental effect on viruses, so that effective combat study can be designed with the interplay of our native immune system and drugs from external sources. Moreover, other deterrents like anti-viral peptides can be designed against selected amino acids. © IJCRR.