Role of Multimedia in Education and its Impact on Academic Achievements

Multimedia is a diversified and powerful means to strengthen and aid the education methodology, by making learning interactive and interesting, this paper further justifies the same. The Internet acts as a gateway between multimedia producers and consumers. It is free from discipline boundaries. Several tools allow nontechnical educators to deal with diverse multimedia to create the learning material. These tools should stand fit some parameters, briefly discussed. Its employment is rapidly magnifying, enabling self-learning, which was boosted in the Covid era. This paper emphasizes on to prevent traditional teaching from being used as a supplement but should be primary. Various hiccups in its efficient use in education still prevail but are heading toward resolution. © 2023 Bharati Vidyapeeth, New Delhi.

Statistical Analysis of Online Voting System Through Blockchain and ML Techniques: A Sustainable Approach for 21st Century Life Style and Smart Cities

A digital voting system is a process that allows people to vote while sitting at their homes and is based on their face recognition identification. The votes will be counted and saved in a blockchain-based structure which is secure and immutable, thus giving availability with security in a system. The traditional voting system does not allow people to vote sitting at their home. Considering the situation of covid, everything is going digital. Questions on EVM from losing parties regarding some malfunctioning. Copyright © 2022, IGI Global.

Utility of lung ultrasound score for severity categorization and CLUE protocol for disposition of COVID-19 patients presenting to emergency department

Objective: Lung ultrasound is a point-of-care diagnostic work-up tool used extensively in emergency departments. The COVID-19 Lung Ultrasound in Emergency Department (CLUE) protocol has shown initial promise in aiding emergency clinicians to make rapid and appropriate bedside clinical decisions. Its primary objective is to assess the performance of the lung ultrasound scoring system (LUSS) in determining SARS-CoV-2 pneumonia severity so that the patients can be moved to their designated ICUs, wards, or facility quarantine center from the emergency department. Methods: A cross-sectional study was undertaken among adult patients with a confirmed diagnosis of SARS-CoV-2 infection who were admitted/referred to the All India Institute of Medical Sciences, Rishikesh, Uttarakhand. The data were descriptively analyzed using Graphpad Prism (vs. 9.2.0). Results: Out of 197 patients included in this study, 74.6% were men with a mean age of 45.3 ± 15.5 years. The men to women ratio was 2.9:1. The most frequent symptoms on presentation were fever (59.9% of cases), cough (54.3%), dyspnea (36%), and 16.2% of the patients were asymptomatic. The mean LUSS score of the patients with invasive support was 24.3 ± 4.5, as compared to 15.7 ± 5.9 in the non-invasive group. Overall, 64.4% patients did not require any respiratory support with a mean LUSS score of 2.3 ± 3.5. Out of 197 patients, 5 (2.5%) died during hospital stay. The mean LUSS score of survivors was 7.1 ± 8.2, as compared to 22.2 ± 4.3 of the deceased. Conclusion: The CLUE protocol can help in triaging the patients in the mild and moderate severity group and discharging them directly from the emergency department itself to either a facility quarantine center or to home isolation. It ultimately helps in avoiding unnecessary referrals, eliminating contamination, and optimum utilization of health resources.

Market Survey On Consumption Pattern Of Street Food Products In Prayagraj District

There is a dearth of knowledge regarding the consumption habits of street foods, despite the fact that individuals in low- and middle-income nations rely heavily on SF for their diet. An online survey employing a structured questionnaire was used to perform a cross-sectional study on 200 street food consumers in the Prayagraj/Allahabad District. Customers were approached and requested to participate who went to the randomly sampled Street Foods vendors and stores. The majority of consumers were male, between the ages of, and had at least a 10+2 and a Bachelor's degree. The primary findings showed that 91.5% of these consumers virtually always ate street food. In Prayagraj/Allahabad District, the most frequently consumed items were various types of street food products. chaat, bun, samosa, kachauri/khasta, fritters, south and north Indian chow mein, non-vegetarian, eggs, and dried goods. Consumers answered that they would prefer to buy healthier street foods (91.5%) if they were accessible. In the Prayagraj/Allahabad District, there is a sizable market for consumers of street food. Although street food is the majority of what is eaten, if healthier options are offered, people would be eager to buy them. Copyright © 2023 Wolters Kluwer Medknow Publications. All rights reserved.

Ensemble method for multiclassification of COVID-19 virus using spatial and frequency domain features over X-ray images

In early 2020, WHO declared COVID-19, a pandemic disease, which severely infected human inhabitant and health. Researchers, doctors, etc., are finding ways to combat the disease. RT-PCR testing is the initial type of testing that was used to detect whether a patient is COVID (+) or COVID (−).This test kit is costly and the result takes around 6hours. So testing a heavy chunk of the population with RT-PCR is a difficult task. To counter this, X-rays/CT scan-based testing can be used to detect COVID (+) cases to control its spread. X-rays are preferable to CT as they are cheaper and even produce low radiations. The second issue that was noticed during this pandemic period was the availability of doctors. To resolve this issue, a robust automated system for early prediction is essential. Automated systems using machine learning (ML), deep learning (DL) approaches are giving promising results in the detection of COVID (+) cases. In this chapter, we propose a framework for automatic recognition of COVID (+), normal, and pneumonia cases (i.e., multiclassification) over X-ray images. In the proposed method, a dataset of COVID (+), normal, and pneumonia images is used. Initially, the dataset is preprocessed, followed by feature extraction using gray level cooccurrence matrix (GLCM), gray level difference method (GLDM), wavelet transform (WT), and fast Fourier transform (FFT) methods. Features extracted are concatenated to construct a feature pool and these features are used for multiclassification using ML algorithms: support vector machines (SVM) and XG Boost. XG Boost performs better than SVM. © 2022 Elsevier Inc. All rights reserved.

IMPACT OF SOCIAL ACCOUNTABILITY AND RESPONSIBILITY THROUGH EDUCATIO N AND ENVIRONMENT

This research paper is based on a fieldwork project, undertaken by the group of volunteer students in collaboration with Indian Development for Human Care (IDHC society), India. Slums are a global phenomenon that may be witnessed in nearly any city on the planet. Children from low-income families who live in slums are deprived of numerous essential facilities that non-slum children enjoy in general, therefore they require special attention. We as a team started the research by understanding the work and establishing good relationships with the staff and students to comprehend the way of their working in a better way. We were introduced to the youngsters with whom we will be working for their better future. We started by teaching them basic English, mathematics, basic habits, personal hygiene;we decided to plant trees as a good environment is necessary for our well-being, in this research work we spread awareness in our neighborhood regarding planting trees and keeping the surroundings clean. Also, spread awareness regarding Covid-19 to underprivileged children. © The Electrochemical Society

Machine Learning-Based Security Solutions for Healthcare: An Overview

The eruption of chronic diseases such as COVID-19 has re-emphasized the need for people all over the world to have access to urgent healthcare. The latest pandemic has shown the flaws in the conventional healthcare system, namely that hospitals and clinics alone are incapable of dealing with such a crisis. Smart and integrated wearables are one of the main technologies that favor modern healthcare solutions (Godi, B., Viswanadham, S., Muttipati, A.S., Prakash Samantray, O., Gadiraju student, S.R.: E-Healthcare Monitoring System using IoT with Machine Learning Approaches. In: 2020 International Conference on Computer Science, Engineering and Applications (ICCSEA). pp. 1–5. IEEE, Gunupur, India (2020). https://doi.org/10.1109/ICCSEA49143.2020.9132937 ). These wearables can now gather data on an unparalleled scale thanks to advancements in the Internet of Things (IoT). Healthcare is among many fields that have been transformed by IoT, with the Internet of Medical Things (IoMT) systems being introduced as an IoT branch. Patients with chronic diseases can be monitored remotely using IoMT systems. As a result, it can offer prompt diagnostics to patients, potentially saving their lives in the event of an emergency. However, protection in these vital systems is a major issue that has arisen as a result of their widespread use. This paper presents an overview of the technologies that are being used on IoMT as well as some security problems found in the literature. This survey will give an insight to the readers regarding the importance of security in healthcare and the different machine learning methods used to address that issue. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Text mining using Twitter data

The microblogging social networking service Twitter has been abuzz around the globe in the last decade. A number of allegations as well as exculpation of different types are being held against it. The list of pros and cons of social networks is huge. India on one hand had an abundance of internet access in last half of the decade. The growth of social media and its influence on people have affected the society in both good as well as in bad way. The following research was done in the month of September and October. The research was carried out on 13 lakh tweets approximately, collected over the course of a month from September to October providing insights about the different attributes of general tweets available on Twitter API for analysis. Insights include the hashtags, account mentions, sentiment, polarity, subject, and object of a tweet. The topics like Rhea Chakraborty and Sushant Singh Rajput, PM Narendra Modi's Birthday, IPL 2020 overshadowed the topics like COVID-19 and women's security. © 2021, IGI Global.

Impact of COVID-19 lockdown on mental health of patients with multi-drug resistant tuberculosis (MDRTB) in tertiary care centre Mumbai

Background &Objective : Multi-Drug Resistant Tuberculosis (MDRTB) and depression act synergistically that magnify the burden of disease. The present study aims to understand the differences in depression scale using Patient Health Questionnaire-9 (PHQ-9) over the time during the COVID-19 pandemic which may cause mental and psychological changes in the patients with MDRTB. Method: A total of 155 treatment naive adults and adolescents MDRTB are enrolled in an ongoing cohort. Each participant completes PHQ-9 to assess depression at baseline, 2 weeks, 1, 2, 3, 4, 5, 6, 12, 18, 24 months of treatment and post treatment 6 and 12 months. Differences in the PHQ9 scores for visits before COVID-19, during 1st lockdown, in unlock phase and 2nd lockdown were assessed by Chi-squared test and t-test and p<0.05 were considered statistically significant. Results: Out of 155 participants with median age of 27 years' 102 (65.8%) were females A significant difference was seen in the overall PHQ-9 scores across each time period (p<0.001). Also, significant changes were seen in overall PHQ-9 scores before COVID-19 and 1st lockdown (p<0.001), during unlock phase, 2nd lockdown (p<0.001) and without lockdown and during 1st and 2nd lockdowns (p<0.001). During 1st lockdown and unlock phase (p=0.165), there were no significant differences seen in the PHQ-9 scores. Conclusion: In this ongoing study, changes in the overall depression scale were significantly associated with COVID-19 lockdown, during unlock phase and 2nd lockdown phase. PHQ-9 screening can be useful for patients who may benefit from additional support and counselling during the treatment during COVID-19 pandemic.

Prevalence of SARS CoV-2 spike antibody in post COVID or post vaccinated individuals

Background &Objective : SARS-CoV-2 pandemic is causing high morbidity and mortality burden worldwide with unprecedented strain on health care systems. Data on the prevalence of the SARS-CoV-2 antibody is expanding with growing research. The initial data on antibodies was available for nucleocapsid target proteins however with advancing research and development of vaccines against the Spike RBD domain of the virus, antibody assays are being focussed to the Spike RBD proteins. The current study aims to understand the prevalence of Anti-Spike SARS cov2 antibodies. Method: A commercially available assay targeting the SPIKE RBD domain of the virus using a chemiluminescent microparticle immunoassay was used for the qualitative and quantitative determination of IgG antibodies to SARS-CoV-2 in a total of 260 individuals. Results: A total of 260 individuals were screened which included 147 males and 113 females with a mean age of 51+16 years. A positive seroprevalence was observed in 85.3% (222/260) individuals. Vaccination details were available for 225 individuals wherein 194 were seropositive. Around 12% did not show presence of antibodies (26/211) even after 21 days of vaccination. A few non-vaccinated individuals were seropositive due to prior history of Covid infection. However, 7 individuals with past history of Covid infection and 2 post vaccination were negative for antibodies. Conclusion: Serological testing plays a vital role in understanding and ultimately combating viral outbreaks and can help identifying individuals with an adaptive immune response to SARSCoV-2, indicating recent or prior infection. A high prevalence of positive spike antibodies is observed in most individuals.

Implementation Pathways of Smart Home by Exploiting Internet of Things (IoT) and Tensorflow

Today’s world is getting influenced by cutting edge technologies. We have experienced how technology played a key role during COVID-19 pandemic period in all over the world including fields like health sector, information technology, education, finance etc. With the rapid and huge development in electronic hardware technologies in the last decade resulted into Artificial Intelligence (AI) is now driving numerous fields. The homes have been becoming smart since the last decade and now AI is putting intelligence into the smart home forming a smart intelligent home. The things or devices of the smart home are controlled and networked by the means of the Internet of Things (IoT) technology. The computer vision is an emerging field which is embedding a smart vision to IoT based systems including smart home as well. The paper work presented here is based on experimentation with smart home using IoT and Computer Vision technologies. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

School Psychology Unified Call for Deeper Understanding, Solidarity, and Action to Eradicate Anti-AAAPI Racism and Violence

Racist rhetoric blaming the Asian, Asian American, and Pacific Islander (AAAPI) community for the COVID-19 pandemic has precipitated a surge of violence against the AAAPI community in the United States, including the Atlanta mass shooting on March 16, 2021. These incidents resurfaced the ongoing racism against AAAPIs that has largely been unaddressed despite lasting almost 2 centuries. The erasure of AAAPIs’ historical oppression, unique cultures, languages, immigration experiences, and contributions to scientific and social justice advancement in the United States has hindered AAAPI voices from being heard. School psychologists are ethically bound to promote equity and dismantle racism;it is imperative to increase visibility of AAAPIs’ experiences across training levels (P–12 and graduate programs), settings, and systems. In this unified statement, school psychology organizations have come together to reaffirm the field’s commitment to anti-racism by offering proactive strategies to effectively promote visibility and equity for AAAPI students, families, and communities. Impact Statement Although there has been a complete absence of discussion of anti-AAAPI racism and anti-racism in school psychology, the field is actively committed to dismantling systemic racism and inequalities in P–12 schools, institutions of higher education, and communities across our nation. This statements seeks to address this absence by providing (a) a much-needed starting point for school psychologists to learn about the history of discrimination, racism, and violence targeting AAAPIs in the United States that has been virtually unaddressed;(b) a critical context for the recent rise in COVID-19-related anti-AAAPI violence while shedding critical light on the deep-seated racism that has oppressed AAAPIs for centuries in America;and (c) beginning strategies that school psychology faculty members, practitioners, and students can engage in to dismantle anti-AAAPI racism across individual and systems levels. © 2021 National Association of School Psychologists.

PMU5 IMPACT of Telehealth Utilization during the COVID-19 Pandemic on Health Care Resource Utilization

Objectives: To assess the healthcare utilization (HCRU) among the patients who received care via telehealth during the COVID-19 pandemic. Methods: A retrospective 6-month pre-post analyses was conducted utilizing HealthJump data. Adult patients with incident telehealth visit (index date) between Feb 1st–April 30th, 2020 were identified, using the CMS CPT codes in conjunction with the description of encounters. Patients were required to be continuously enrolled in the baseline and follow-up period and should have zero telehealth visit in the baseline period. Age, gender and diagnosis on the index date were summarized for the sample. During the baseline and follow-up period, proportion of patients having >=1 visits for the following HCRU visits were evaluated and compared using McNemar’s test: (a) Office visits, (b) Inpatient visits, (c) Consultations, (d) Emergency Department visits, (e) Critical Care, (f) Nursing Facility, (g) Home Services, (f) Preventive care, (g) Mental Health (h) Non-face to Face (F2F) services. A subset analyses was conducted among patients with COVID-19 diagnosis. Results: 27,169 patients with a mean(SD) age of 50.15(17.11) and predominantly female (62.4%) were included in study. Hypertension, hyperlipidemia, anxiety disorder, type 2 diabetes mellitus and chronic obstructive pulmonary disorder were the top diagnoses associated with the index telehealth visit. Compared to baseline period, patients had a significant increase in outpatient (18 percentage points, p<0.0001) and non-F2F (13 percentage points, p<0.0001) visits and significant decrease in inpatient, consultation, emergency room, nursing facility and preventive visits during the follow-up period. Of the sample, 534 patients had COVID-19 diagnosis with a mean(SD) age of 49.9(16.04) and were predominantly female (61.6%). Similar decrease and increase in HCRU were observed in the subset of COVID-19 patients in our study. Conclusions: During COVID-19 pandemic, patients utilizing telehealth experienced similar shift in the HCRU, especially in outpatient & non-F2F visits, irrespective of the COVID diagnosis.

Breathing nitric oxide at high dose in severe-critical COVID-19 during pregnancy: A case series

Introduction: Pregnant patients with a severe form of COVID-19 are at increased risk of maternal and fetal complications. Nitric Oxide (NO) gas is a selective pulmonary vasodilator currently approved to treat newborns with pulmonary hypertension. Inhaled NO has been safely used in patients with severe pneumonia and for cases of pregnant patients with pulmonary hypertension. The antimicrobial effect of NO has been confirmed against bacteria and viruses. In vitro study demonstrated a dose-dependent effect of NO against SARS-CoV-1 and 2. We hypothesize that breathing NO at 160-200 ppm twice daily for 30 minutes in spontaneously breathing pregnant patients might provide a safe and effective treatment for COVID-19. Methods: We retrospectively reviewed the data of 6 pregnant patients hospitalized for COVID-19 treated with inhaled NO. Nitric Oxide was delivered at 160- 200 ppm for 30 minutes twice daily until resolution of respiratory symptoms or negative RT-PCR for SARS-CoV- 2. Demographic and clinical data were collected to assess cardiopulmonary function and safety during the treatment. For safety, we focused on the values of blood methemoglobin (MetHb) and inhaled Nitrogen Dioxide (NO2). Data regarding newborn delivery and health, and 28 days outcomes of mothers and babies were collected. Results: Six pregnant patients were admitted with a severe (2 patients) or critical (4 patients) form of COVID-19 and received inhaled NO therapy between April and June 2020. Two pregnant patients were in the second trimester, while 4 were in the third trimester. A total of 39 treatments were administered. No adverse events were reported relating to NO administration. MetHb peaked at 2.5% (1.95%-3%, safety limit =5%) and inhaled NO2 remained below the safety limit of 2ppm. The patients remained hemodynamically stable;cardiac ultrasound performed in three patients did not detect any rebound pulmonary hypertension after NO interruption. Oxygen saturation improved in hypoxemic patients after the initiation of NO (Figure-1). All patients experienced a reduction in respiratory rate (by a median 4.5breaths/min after NO initiation). Three patients delivered a total of 4 babies (negative for SARS-CoV-2) while the other 3 remained pregnant after hospitalization (gestational age 22-26-33weeks) with normal follow-ups. Five mothers out of 6 tested negative for COVID-19 28 days after hospitalization. Conclusion: Nitric oxide gas at 160-200 ppm was safely administered to pregnant patients with severe-critical COVID-19, improved oxygenation and reduced respiratory rate in all 6 patients. The clinical effectiveness shown suggests inhaled high dose NO as a therapeutic novel therapy for COVID-19 in pregnancy.

Repurposing mefenamic acid in the management of covid-19

With the growing understanding of coronavirus disease-2019 (COVID-19) pathogenesis, different therapeutic targets are being considered for the management of COVID-19. The development of new drugs is a time-consuming process;hence, many drugs acting on similar therapeutic targets/sites in the COVID-19 treatment are repurposed in COVID-19. In this article, an expert panel deliberated on the existing evidence on the immunopathogenesis, therapeutic targets under consideration for treatment of COVID-19, and the place of mefenamic acid in the therapy landscape of COVID-19. The expert panel has also provided recommendations regarding the dose and regimen of mefenamic acid in different phases of the COVID-19 disease.

Assessment of health infrastructure in tackling COVID-19: A case study of European and American scenario.

The COVID-19 coronavirus pandemic is an unparalleled threat intoday's quickly developing climate, and we face it as a global community. Like climate change, it is challenging our resilience from environmental health, social security, and government, to knowledge exchange and economic policy in all sectors of the economy and all fields of growth. So much as climate change, everybody's coming together would require the initiative. Throughout Europe and America, several organizations have mobilized to ensure that the neediest are not left behind, encouraging emergencies and disruptions avoidance and preparedness. The coronavirus outbreak has highlighted the growing community's strengths and vulnerabilities that it has influenced, and has provided us with the ability to benefit from each other's accomplishments and shortcomings. The comparison graph has also been shown in this paper displaying European and American scenarios. The globe might feel smaller amid disaster states and global travel bans, but it is a period when teamwork and looking outward were never more relevant.