A Study on the Impact of Mobility on the Performance of Routing Protocols in MANET-Based Online Learning Platforms

A rapid development in online learning systems to maintain the continuity of student education during the COVID-19 pandemic has been observed. The telecommunication technologies based on Mobile Ad hoc Network (MANET) are very useful and widely used to connect online learners staying remotely in jungles, forests and hilly areas where it is difficult to establish permanent infrastructure for communication. Routing protocols play a vital role in the background, which provide an uninterrupted learning session. In this context, by considering the mobile gadgets and other electronic devices as the nodes of the MANET system, it becomes quite imperative on the part of the researcher to further analyze and understand the impact of node mobility on the performance on MANET-based online learning systems in rural Indian terrain. A change in mobility can be achieved by changing the online learner's node speed during its movement or by changing the pause-time at its halt points during its random movement. Change in mobility causes link breaks between neighbor learners nodes;hence, a large number of packets drop in the network, which in other terms reduces the network performance and, simultaneously, the reliability of the online learning system. The performance of the MANET-based online platform is analyzed by taking parameters like packet delivery fraction, normalized routing load and average link break. This paper thoroughly discusses the performance variation due to change in mobility. © 2023 selection and editorial matter, Zdzislaw Polkowski, Samarjeet Borah, Sambit Kumar Mishra, and Darshana Desai;individual chapters, the contributors.

A Transfer Learning Approach for Diagnosis of COVID-19 Cases from Chest Radiography Images

The new coronavirus disease 2019 (COVID-19) pandemic completely changed individuals' daily lives and created economic disruption across the world. Many countries are using movement restrictions and physical distancing as their measures to slow down this transmission. Effective screening of COVID-19 cases is needed to stop the spreading of these diseases. In the first phases of clinical assessment, it was seen that patients with deformities in chest X-ray images show the signs of COVID-19 infection. Inspired from this, in this study, a novel framework is designed to detect the COVID-19 cases from chest radiography images. Here, a pre-trained deep convolutional neural network VGG-16 is used to extract discriminating features from the radiography images. These extracted features are given as an input to the Logistic regression classifier for automatic detection of COVID-19 cases. The suggested framework obtained a remarkable accuracy of 99.1% with a 100% sensitivity rate in comparison with other state-of-the-art classifier. © 2022 IEEE.

Synthesis, structural investigations, XRD, DFT, anticancer and molecular docking study of a series of thiazole based Schiff base metal complexes

A novel Schiff base (SB) ligand, abbreviated as HDMPM, resulted from the condensation of 2-amino-4 -phenyl-5-methyl thiazole and 4-(diethylamino)salicyaldehyde, and its metal complexes with [Co(II), Cu(II), Ni(II), and Zn(II)] ions in high yield were formed. The physico-chemical techniques such as elemental analysis, molar conductance, IR, 1 H and 13 C NMR, mass spectroscopy, and electronic absorption studies were utilized to characterize the synthesized compounds. The studied compounds were examined for their possible anticancer activity against a number of human cancerous cell lines, including A549 lung carcinoma, HepG2 liver cancer, HCT116 colorectal cancer, and MCF-7 breast cancer cell lines, with dox-orubicin serving as the standard. The study revealed that Zn(II) complex showed significant activity to inhibit growth of HepG2, MCF7, A549, and HCT116 cell lines by a factor of 88, 70, 75, and 70, respec-tively, when compared to untreated. In addition, the reported compounds were optimized by employing Gaussian16 program package with B3LYP functional incorporating dispersion with two different basis sets (LanL2DZ and 6-31G(d,p)). Moreover, Autodock Vina software was used to assess the biological effective-ness of the studied compounds against SARS-CoV-2 Omicron variant (PDB ID: 7T9K).(c) 2022 Elsevier B.V. All rights reserved.

An Enhanced Binary Multi-Objective Hybrid Filter-Wrapper Chimp Optimization based Feature Selection Method for COVID-19 Patient Health Prediction

This work aims to discover the relevant factors to predict the health condition of COVID-19 patients by employing a fresh and enhanced binary multi-objective hybrid filter-wrapper chimp optimization (EBMOChOA-FW) based feature selection (FS) approach. FS is a preprocessing approach that has been highly fruitful in medical applications, as it not only reduces dimensionality but also allows us to understand the origins of an illness. Wrappers are computationally expensive but have excellent classification performance, whereas filters are recognized as quick techniques, although they are less accurate. This study presents an advanced binary multi-objective chimp optimization method based on the hybridization of filter and wrapper for the FS task using two archives. In exceptional instances, the initial ChOA version becomes stuck at the local optima. As a result, a novel ChOA termed EBMOChOA is developed here by integrating the Harris Hawk Optimization (HHO) into the original ChOA to improve the optimizer’s search capabilities and broaden the usage sectors. The location change step in the ChOA optimizer is separated into three parts: modifying the population using HHO to produce an HHO-based population;creating hybrid entities according to HHO-based and ChOA-based individuals;and altering the search agent in the light of greedy technique and ChOA’s tools. The effectiveness of the EBMOChOA-FW is proven by comparing it to five other well-known algorithms on nine different benchmark datasets. Then its strengths are applied to three real-world COVID-19 datasets to predict the health condition of COVID-19 patients. Author

Effect of Natural Compounds to Inhibit Human Respiratory Syncytial Virus

Current COVID-19 effects are forcing us to think about other deadly viral diseases. Respiratory syncytial virus (RSV) is one of them. Every year thousands of children lost their lives due to respiratory diseases which are occurred by this RSV. Nowadays, bioactive compounds show an enormous effect on many deadly diseases and show excellent therapeutic effects. In this study, we have identified five bioactive compounds from the plant which will be used in the treatment of RSV. Molecular docking on the protein was done by Autodock. Hydrogen was added and routable bonds were fixed in the preparation time of protein for docking. All those compounds show their non-toxic nature which is evaluated by Lipinski's Rule of Five. Molecular docking on RSV matrix protein and surface glycoprotein with those bioactive compounds shows very promising results. Between all those compounds Baicalein appears as a lead compound. It shows -8.1 Kcal/mol in the case of matrix protein and -7.9 kcal/mol in the case of the surface glycoprotein of RSV. Due to its availability and non-toxic nature, it can be used in the treatment of RSV. AS it is derived from plants, it also has very fewer side effects than chemical drugs.

In silico comparative structural and compositional analysis of glycoproteins of RSV to study the nature of stability and transmissibility of RSV A

The current scenario of COVID-19 makes us to think about the devastating diseases that kill so many people every year. Analysis of viral proteins contributes many things that are utterly useful in the evolution of therapeutic drugs and vaccines. In this study, sequence and structure of fusion glycoproteins and major surface glycoproteins of respiratory syncytial virus (RSV) were analysed to reveal the stability and transmission rate. RSV A has the highest abundance of aromatic residues. The Kyte–Doolittle scale indicates the hydrophilic nature of RSV A protein which leads to the higher transmission rate of this virus. Intra-protein interactions such as carbonyl interactions, cation–pi, and salt bridges were shown to be greater in RSV A compared to RSV B, which might lead to improved stability. This study discovered the presence of a network aromatic–sulphur interaction in viral proteins. Analysis of ligand binding pocket of RSV proteins indicated that drugs are performing better on RSV B than RSV A. It was also shown that increasing the number of tunnels in RSV A proteins boosts catalytic activity. This study will be helpful in drug discovery and vaccine development. © 2022, Jiangnan University.

Computational Intelligence in Identification of Some FDA Approved Drug Compounds for Treatment of COVID-19

Due to unavailability of FDA approved drug for COVID-19, pursuing of available drugs are highlighted to stop COVID-19. Insilico investigation by molecular docking and molecular dynamics simulation help to identify some FDA pre-approved drugs which have a therapeutic effect on SARS-CoV-2. In this study, four drug compounds have been identified by descriptor properties, molecular docking, and molecular dynamics simulation. Between them, Darunavir appeared as the best drug molecule to inhibit the 3C like main protease of SARS-CoV-2. It showed −9.1 kcal/mol binding energy in molecular docking with 3C like main protease of SARS-CoV-2. This study also enlightens on the theory “one molecule, multiple targets”. Multiple target protein was docked by every single drug compound, to check their high therapeutic effect. Molecular dynamics simulations indicate the stable binding of drugs with the target protein. Until the approval of any drug for COVID-19, Darunavir might use as an anti-covid drug. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Blockchain Meets COVID-19: A Framework for Contact Information Sharing and Risk Notification System

COVID-19 is a severe global epidemic in human history. Even though there are particular medications and vaccines to curb the epidemic, tracing and isolating the infection source is the best option to slow the virus spread and reduce infection and death rates. There are three disadvantages to the existing contact tracing system: 1. User data is stored in a centralized database that could be stolen and tampered with, 2. User's confidential personal identity may be revealed to a third party or organization, 3. Existing contact tracing systems [1] [2] only focus on information sharing from one dimension, such as location-based tracing, which significantly limits the effectiveness of such systems. We propose a global COVID-19 information sharing and risk notification system that utilizes the Blockchain, Smart Contract, and Bluetooth. To protect user privacy, we design a novel Blockchain-based platform that can share consistent and non-tampered contact tracing information from multiple dimensions, such as location-based for indirect contact and Bluetooth-based for direct contact. Hierarchical smart contract architecture is also designed to achieve global agreements from users about how to process and utilize user data, thereby enhancing the data usage transparency. Furthermore, we propose a mechanism to protect user identity privacy from multiple aspects. More importantly, our system can notify the users about the exposure risk via smart contracts. We implement a prototype system to conduct extensive measurements to demonstrate the feasibility and effectiveness of our system.

Spectrum of Bacterial Pathogens in Critical COVID-19 Patients Admitted in Intensive Care Units of a Tertiary Care Hospital during the First and Second Wave of the Pandemic

Objective: This study intends to compare the clinical characteristics and the prevalence and spectrum of bacterial pathogens in COVID-19 patients admitted to ICU during the first and second waves at a tertiary care, teaching and referral hospital of eastern India. Method: This is a hospital-based retrospective study which analysed demographic details, clinical profile and bacterial culture results of severe and critically ill COVID-19 patients admitted in intensive care units (ICU) during April -Oct 2020 (1stwave) and April -July 2021 (2ndwave). Result: The patients admitted during the 2ndwave were comparatively older and had multiple comorbidities compared to the 1stwave. (23.8%) (45/189) and 50% (173/346) of the COVID-19 patients admitted to ICU developed bacterial infection during the 1stand 2ndwave respectively. Overall, there was predominance of multidrug resistant Gram negative bacilli in both the waves. There was increased isolation of intrinsic colistin resistant microorganisms. Conclusion: Multidrug resistant Gram negative bacterial infections, remain a dreaded complication in severe and critically ill hospitalised COVID-19 patients requiring ICU care and high usage of colistin spirals the emergence and spread of pathogens intrinsically resistant to colistin. © 2022 Journal of Association of Physicians of India. All rights reserved.

Negative and positive environmental perspective of COVID-19: air, water, wastewater, forest, and noise quality

The ongoing coronavirus disease 2019 (COVID-19) pandemic driven by severe acute respiratory syndrome coronavirus–2 (SARS-CoV-2) has become the most critical universal health disaster of this century. Millions of people are staying at home obeying lockdown to halt the spread of this novel virus. The spread of the virus has forced people to use the mask, gloves, hand sanitizer, etc. daily, and healthcare workers to use personal protection equipment following the WHO guidelines, resulting in huge amounts of medical waste. This pandemic has led to a slowdown of economic activities significantly, and consequently, stock markets have nosedived beyond speculation. Although the deadly coronavirus has taken away millions of precious lives and the livelihood of many sections of people worldwide, it has brought several positive changes in the world. Furthermore, it has led to a massive restoration of the environment and improved air and water quality. Pandemic showed the resilient nature of the environment, including air and water, when human activities are paused. In addition, we also discussed how this pandemic affects human lifestyle behavior. © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Covid-19 Face Mask Prediction Using Machine Learning Techniques

Entire world including India is going through a pandemic that has arisen due to the outbreak of COVID-19. Medicines and Vaccine for Covid-19 are still under developmental stage. Wearing a Face Mask is the best viable option for humans to prevent the spread of infection due to Corona virus. As a result, controlling government agencies may want to know the percentage of people wearing masks during a period as well as which group of people are most likely to wear masks when they go outside. To help answer these questions, this paper introduces a model that can classify faces among masked faces and unmasked faces using Python 3.0 Language. In the present face detecting model, Vietnam based mask classifier dataset, CelebA dataset, WiderFace dataset and MAFA datasets are used for achieving better results. Single Stage Headless Face Detector (SSH) is successfully implemented to segregate human faces with or without mask. Experimental results with the Mask Classifier model show that it can achieve about 96.5% accuracy during testing stage. Selected on road going people video is tested successfully where the present model clearly segregated human faces with and without mask. The present model is useful to safeguard people from spread of Covid-19 virus in public places. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

South Asian Declaration-Consensus Guidelines for COVID-19 Vaccination in Cancer Patients.

We provide the South Asian Declaration, containing the consensus guidelines for coronavirus disease 2019 (COVID-19) vaccination in cancer patients.

Post-COVID-19 respiratory management: expert panel report

This report is the first expert panel report on the management of post-COVID-19 patients from India. The report contains high risk groups, post-COVID-19 patient management at primary care level, general principles of medical management of post-COVID-19 in primary care settings, management of post-COVID-19 symptoms in primary care settings, recommendations for inclusion and exclusion into the Pulmonary Rehabilitation Programme, post-COVID-19 patient management at tertiary care level, post-COVID-19 complete assessment and management, and respiratory disease-specific conditions requiring expert opinion and further research.

P09.48 Experience and Outcome of COVID-19-Positive Lung Cancer Patients from a Eastern Indian Hospital

Introduction: The COVID-19 pandemic has caused unprecedented crisis in the care of non-Covid patients all across the globe and care for lung cancer patients is no exception. Lung Cancer patients are at increased risks of COVID due to increased mortality from dual aggressive pathology in the lungs. Our aim was to examine the impact of COVID-19 on lung cancer therapy and factors responsible delay in optimal care during the pandemic. Methods: This study included all patients with a diagnosis of lung cancer being treated at our Institute, a tertiary level referral hospital in eastern part of India during on going pandemic. Seven developed COVID-19, confirmed by RT-PCR method (Table 1). Results: The mean age of the patients was 49 years. All the patients had metastatic lung cancer. All males had history of smoking. Hypertension was present in only one patient. Four patients (57%) died from concomitant COVID-19 at our institution.Three patients who recovered from COVID were stable. One of them (positive for ROS1) was switched over to Crizotinib and other patient resumed chemotherapy only after he had recovered from COVID-19. Most of the patients acquired COVID-19 infection during the process of evaluatio/chemotherapy and that further delayed the treatment. [Formula presented] Conclusion: The results were disappointing because more than half of lung cancer patients died due to COVID-19. The disease course of COVID-19 has been more severe in patients with lung cancers with Chemotherapy. There have been delay in resuming treatment among survivors by few weeks. Fear of aggressiveness of disease was the key factor for interruption or delay in chemotherapy. Other variable factors like stage of cancer, palliative intent of chemotherapy, ECOG status were key determinants for interruption of treatment. The decision to temporarily suspend chemotherapy while waiting for recovery from SARS-CoV-2 and then restart, was not easy due to the risk of cancer progression. The findings amplify the importance of optimizing of lung cancer care in the context of the COVID-19 prevalence. The decisions need to be taken on the basis of individual cases rather than rely on a generalized approach. In resource limited country like India diverting the existing resources to an emergency leads to compromise of routine outpatient care, especially patients with chronic illness. We need to be flexible in restarting of services guided by local COVID prevalence, while awaiting a definite management plan for COVID-19. Keywords: lung cancer, India, COVID-19, SARS-CoV-2

P88.03 Asymptomatic COVID-19 in a ROS1 positive Non Small Cell Lung Cancer

Introduction: COVID-19 pandemic has led to reconsider the traditional management approach in lung cancer. Oral tyrosine kinase inhibitors (TKIs) are being preferred in oncogene addicted advanced non-Small Cell Lung Cancer. Methods: A young never-smoker woman presented with left hilar mass with left pleural effusion in February 2020. There was an incidental detection of thrombus in right main and descending pulmonary artery. She was diagnosed to have ROS1 rearranged advanced NSCLC with pulmonary embolism. She was initiated on conventional chemotherapy with carboplatin and pemetrexed along with anticoagulation. After fourth cycle of chemotherapy, although there was clinical improvement attributed to reduction of amount of effusion and disappearance thrombus, RECIST 1.1 criteria suggested the progression of disease in view of appearance of adrenal metastasis. Meanwhile, she had a history of high risk exposure with a patient of COVID- 19 in July 2020. Although she was asymptomatic, RT- PCR for SARS-COV2 came out to be positive. Results: She remained asymptomatic for next 10 days during hospitalization. Then she was started on Crizotinib and was discharged with advice on further follow up. Conclusion: Although patients on cancer chemotherapy are at high risk of severe COVID-19 diseases, asymptomatic cases can happen. The patients preferably should be shifted to or started on oral TKIs as per available expert recommendations. Keywords: ROS1, COVID-19, TKI