ABSTRACT
The novel coronavirus disease (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The immune response to SARS-CoV-2 can play an important role in disease pathogenesis and clinical manifestations. Considering the antiviral, immuno-modulatory, anxiolytic, antiinflammatory and antioxidant properties, this open labelled, controlled, interventional, prophylactic study was conducted on individuals at risk in containment zones of different cities of India, viz., Lucknow, Aligarh, New Delhi, Srinagar, Mumbai and Bengaluru. The study focuses on number of patients turning COVID-19 positive, change in ISQ and WHOQOL-BREF scales in both the groups. Apparently, healthy individuals at risk in containment zones were divided into intervention and control groups. The intervention group was further divided into two subgroups. The first subgroup received Unani regimen- I including Unani Joshanda with Khamira Marwareed (KM), the second subgroup received Unani regimen- II including Unani Joshanda with Tiryaq Arba (TA). The control group did not receive any intervention. The duration of intervention was 20 days;follow ups were planned on day 10, day 20 and day 35. A total number of 33021 participants were enrolled in the study, of which 30,931 participants completed the study. It was observed that individuals receiving Unani regimen-I demonstrated lower risk of developing COVID-19 by 74% and those receiving Unani regimen-II by 62% in comparison to the control group. Interventional groups showed highly significant (p<0.001) effect on the quality of life.
ABSTRACT
The coronavirus, formerly known as COVID-19, has caused massive global disasters. As a precaution, most governments imposed quarantine periods ranging from months to years and postponed significant financial obligations. Furthermore, governments around the world have used cutting-edge technologies to track citizens’ activity. Thousands of sensors were connected to IoT (Internet of Things) devices to monitor the catastrophic eruption with billions of connected devices that use these novel tools and apps, privacy and security issues regarding data transmission and memory space abound. In this study, we suggest a block-chain-based methodology for safeguarding data in the billions of devices and sensors connected over the internet. Various trial secrecy and safety qualities are based on cutting-edge cryptography. To evaluate the proposed model, we recom-mend using an application of the system, a Raspberry Pi single-board computer in an IoT system, a laptop, a computer, cell phones and the Ethereum smart contract platform. The models ability to ensure safety, effectiveness and a suitable budget is proved by the Gowalla dataset results. © 2023, Tech Science Press. All rights reserved.
ABSTRACT
The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread globally. COVID-19 presents varied clinical features. The present study focuses on number of patients turning COVID-19 positive, change in Immune Status Questionnaire (ISQ) and WHO quality of life-Bref (WHO Qol – BREF) scales after taking intervention. This open labelled, double arm, controlled, interventional, clinical trial was conducted on high-risk individuals i.e., those residing with a COVID-19 positive member in the identified quarantine area. This twin armed study was conducted on asymptomatic individuals exposed to COVID-19. The test group were prescribed Unani poly-herbal decoction together with Unani formulations Khamira Marwareed and Tiryaq e Arba whereas the control group was not on any intervention. The duration of intervention was 20 days;follow ups were planned on day 10 and day 20. Of the 81 participants enrolled, none of the patients turned COVID-19 positive. However, 13.58% (n=11) developed COVID like symptoms and 70 patients completed the study. The mean age of the participants was 41.42±16.9 years;however, majority of the participants were 18-28 years male with Damvi (Sanguine) temperament. The quality of life of the intervention group improved significantly however, the immune status in both the groups increased with P <0.001. The Unani prophylactic regimen provides a 62% (relative risk reduction) protection against COVID-19. This pilot study paves for a study on a larger population. No adverse effects were observed during the study. Absence of biochemical investigations were limitations to the study. © 2022, National Institute of Science Communication and Information Resources. All rights reserved.
ABSTRACT
The outburst of novel corona viruses aggregated worldwide and has undergone severe trials to manage medical sector all over the world. A radiologist uses x-rays and Computed Tomography (CT) scans to analyze images through which the existence of corona virus is found. Therefore, imaging and visualization systems contribute a dominant part in diagnosing process and thereby assist the medical experts to take necessary precautions and to overcome these rigorous conditions. In this research, a Multi-Objective Black Widow Optimization based Convolutional Neural Network (MBWO-CNN) method is proposed to diagnose and classify covid-19 data. The proposed method comprises of four stages, preprocess the covid-19 data, attribute selection, tune parameters, and classify cov-id-19 data. Initially, images are fed to preprocess and features are selected using Convolutional Neural Network (CNN). Next, Multi-objective Black Widow Optimization (MBWO) method is imparted to finely tune the hyper parameters of CNN. Lastly, Extreme Learning Machine Auto Encoder (ELM-AE) is used to check the existence of corona virus and further classification is done to classify the covid-19 data into respective classes. The suggested MBWO-CNN model was evaluated for effectiveness by undergoing experiments and the outcomes attained were matched with the outcome stationed by prevailing methods. The outcomes confirmed the astonishing results of the ELM-AE model to classify cov-id-19 data by achieving maximum accuracy of 97.53%. The efficacy of the proposed method is validated and observed that it has yielded outstanding outcomes and is best suitable to diagnose and classify covid-19 data. © 2022, Tech Science Press. All rights reserved.