Showing papers by "Indrajit Banerjee published in 2021"

A SPEA-Based Multimetric Routing Protocol for Intelligent Transportation Systems

Abstract: For efficient communication among vehicles or infrastructure, an effective routing protocol for Intelligent Transportation Systems is profoundly required. Because of high mobility and recurrent topology deviations of Vehicular Ad-hoc Networks (VANets), finding a linked route with adequate delay is an important challenge with many limits and hitches. To overcome this, an efficient multimetric routing protocol is proposed here for Intelligent Transportation Systems. The proposed protocol considers five metrics - Link Capacity, Connectivity, Euclidean Distance, Relative Velocity and End-to-End Delay. The aim of the proposed method is maximizing the Packet Delivery Ratio (PDR) while minimizing the delay of the network. It tries to identify the path that has minimum delay, distance and relative velocity with maximum bandwidth and V2V connectivity. For this, the protocol adopts Strength Pareto Evolutionary Algorithm (SPEA) to optimize the five metrics and calculate the fitness value. Then the fitness value is used to find out the optimal path using a novel path finding algorithm for efficient data delivery to the target destination. Extensive simulation outcomes disclose that the proposed strategy shows an improvement of 6% in PDR, 11% in end-to-end delay and 2% improvement in hop-count as compared to the recent similar method.

Development and implementation of a potential coronavirus disease 2019 (COVID-19) vaccine: A systematic review and meta-analysis of vaccine clinical trials

Abstract: Background: To date, there is no comprehensive systematic review and meta-analysis to assess the suitability of COVID-19 vaccines for mass immunization The current systematic review and meta-analysis was conducted to evaluate the safety and immunogenicity of novel COVID-19 vaccine candidates under clinical trial evaluation and present a contemporary update on the development and implementation of a potential vaccines Methods: For this study PubMed, MEDLINE, and Embase electronic databases were used to search for eligible studies on the interface between novel coronavirus and vaccine design until December 31, 2020 Results: We have included fourteen non-randomized and randomized controlled phase I-III trials Implementation of a universal vaccination program with proven safety and efficacy through robust clinical evaluation is the long-term goal for preventing COVID-19 The immunization program must be cost-effective for mass production and accessibility Despite pioneering techniques for the fast-track development of the vaccine in the current global emergency, mass production and availability of an effective COVID-19 vaccine could take some more time Conclusion: Our findings suggest a revisiting of the reported solicited and unsolicited systemic adverse events for COVID-19 candidate vaccines Hence, it is alarming to judiciously expose thousands of participants to COVID-19 candidate vaccines at Phase-3 trials that have adverse events and insufficient evidence on safety and effectiveness that necessitates further justification

Mucormycosis and COVID-19 an epidemic in a pandemic?

Abstract: Mucormycosis and aspergillosis are rare, invasive and life-threatening infections primarily caused by Rhizopus arrhizus and Aspergillus fumigatus with higher case fatality rates (>50%), respectively. Invasive Aspergillosis and Mucormycosis have been established and recognized as complications of the SARS-CoV-2 infection. Such cases have been intimately linked and related to prior corticosteroid therapy. With the new highly infectious Delta strain (B.1.617.2 and B.1.617.2.1 or AY.1) of the coronavirus which is running rampant throughout India causing unprecedented death tolls, a new crisis is evolving. Invasive "black fungus" (Mucormycosis) is creating an epidemic within a global pandemic. The unique socio-economic, genetic and health status of Indian population culminates into a melting pot which sustains the viable triad for the "black fungus" infection to gain a stronghold. Diabetes mellitus, immunosuppression and the current COVID-19 global pandemic with its massive surges in the country have produced the "perfect storm." Ophthalmologist across India have reported a surge in invasive Mucormycosis cases with a rise in orbital compartment syndrome often calling for radical procedures such as enucleation surgeries. The "black fungus" pandemic and invasive Mucormycosis resulted in the sinister secondary infections and complications are closely linked with the COVID-19 infection in India. It is therefore of the upmost importance that neighbouring countries particularly Nepal and other Asiatic nations take great cognizance of this indolent "black fungus killer" and ensure new screening and testing protocols for early identification to ensure effective management.

Internet-of-Things-Enabled SmartVillages: An Overview

Abstract: Internet of Things (IoT) plays a vital role in smart village applications where IoT devices and automation would find its applications in agriculture, healthcare, education, and livestock management. IoT technologies are transforming villages by better infrastructure, better transportation systems, providing precision farming facilities, increasing farmer income, and improving the quality of human life. In the smart village paradigm, several communication technologies and consumer electronics (CE) have used to develop several IoT-enabled applications. Hence, this article provides state-of-the-art communication technologies and the CE aspect for IoT-based smart village realization. Furthermore, a taxonomy is devised by classifying the literature based on modern communication technologies, network types, supporting technologies, offering services, mode of operation, and requirements. Finally, we discuss important issues and opportunities regarding the smart village realization.

COVID-19 and mutations a threat level assessment

Abstract: A mutation is defined as an alteration in the DNA or RNA sequences of a genome which may consequently confer a new phenotypic and or genotypic advantage both increasing the virulence as well as the survival of a virus or pathogen At this current point in time there are 4 known major variants of the original SARS-CoV-2 virus, namely the English variant (B117), the South African variant (B1351), Brazilian variants (VOC202101/02 (P1) and VUI202101/01) and a variant similar to that of the South African variant found in North America (B1526), all of which have varying levels of resistance and infectivity It is evident that the SARS-CoV-2 variants pose an international health risk, the mutations of E484K and N501Y are the two most implicated mutations E484K being the most concerning as it aids in immune evasion and drastically causes the efficacy of the current vaccines to be reduced by large margins The most worrisome variant is the South African or B1351 which harbors the above mutations It is of the upmost importance that targeted vaccines are synthesized to ensure that immunized individuals have effective protection against these variants Until these specific targeted vaccines are synthesized the current vaccines offer little long-term protection, however do confer a level of immunity to stop severe infections It is thus advised that current vaccination programs should continue in earnest as a degree of protection is conferred

IoT-based Freezing of Gait detection using Grey Relational Analysis

Abstract: With the massive progress of Internet of Things based technologies, the importance of remote monitoring has increased by many folds especially for the assistance of patients suffering from life threatening diseases. This work deals with the detection of Freezing of Gait in patients having Parkinson’s disease with the help of wearable acceleration sensors placed on their legs and hips which consequently results in their real-time remote monitoring. This work proposes a FoG detection method based on Grey Relational Analysis which uses the readings from the sensors to predict the presence or absence of freezing in a patient. Additionally, an ensemble learning approach that uses Grey Relational Analysis as the base classification model has also been illustrated for FoG detection. The proposed approaches have been applied on benchmark Daphnet Freezing of Gait data set to verify their feasibility. The simulation results show that the proposed approaches have better accuracy when compared to other existing machine learning techniques.

IoT Based Data Aggregation Method for E-Health Monitoring System

Abstract: Health monitoring system has become accessible to every corner of the world with the internet. Proper aggregation of necessary medical data is very relevant for treatment, inadequate security often exposes the data to an unknown threat. In this paper, an Internet of things based e-Health monitoring system is proposed where various types of sensors are used to collect data about health-related and environment-related parameters and transmit them to the cloud. Schedule data aggregation is provided in the proposed system to reduce energy consumption and bandwidth. Proper privacy and security have become the major concern to avoid unauthorized users. So, the data are stored securely, redundant data can be avoided easily. People can smoothly maintain a record of their health condition and can also take proper precautions with the help of the information provided by these systems. Thus, we have tried to build a system that is compact, cost-effective. and handy.

An Improved PSOGSA for Clustering and Routing in WSNs

Abstract: Wireless sensor network (WSN) is an integration of sensing, communicating, computing in a board range environment. Efficient energy consumption becomes the most challenging task for sensor nodes. The clustering and routing techniques are promising methods to resolve the issue and extend the network’s lifespan. The clustering technique is defined as grouping data into classes, every cluster sharing a high degree of similarity in between them, and each cluster being dissimilar with others. This technique is the best data processing model for WSN, and it controls the redundant data inside the network. The nomination of the appropriate cluster head is a major factor in the clustering technique. The object of this proposed paper is to equipoise the energy of the clustering nodes and route the data from cluster head to sink. We propose an improved particle swarm optimization gravitational search algorithm for clustering and routing in WSNs. Here clustering algorithm makes equal energy in the entire network by the uniform distribution of cluster head, routing algorithm decides the ideal routing path to convey data packet between cluster head and sink. The proposed paper integrates the exploration capacity of GSA and the exploitation capability of PSO. Detailed simulation performs using MATLAB based simulator in terms of residual energy, network lifespan, and convergence rate. In comparing our proposed algorithm to other existing algorithms, it outperforms significantly.

An insight of medical student’s preference and opinions to Pharmacology textbooks

Abstract: Background: Various medical subjects pose a daunting task to students. Chief amongst which the subject’s students grapple with is pharmacology. The study’s primary objective was to find out the second professional medical student’s preferences, feedback, and attitude towards pharmacology textbooks at SSR Medical College, Mauritius. Methods: This cross-sectional questionnaire-based observational survey was conducted from May 2018- June 2018 at Seewoosagur Ramgoolam Medical College, Mauritius. A Chi-square test was performed to find out correlations between variables. p < 0.05 was considered as statistically significant. Results: A total of 192 medical students participated in the study out of 210 students, giving an overall response rate of 91.42%. 103 (35.6%) students chosen Essentials of Medical Pharmacology- K.D. Tripathi as a first preference, followed by 59 (30.7%) students selected Pharmacology for Medical Students- Tara V Shanbhag and Smita Shenoy as a second preference, and 22 (11.5%) chosen Medical Pharmacology- Padmaja Udaykumar as a third preference. Conclusion: The textbook Essentials of Medical Pharmacology by K.D. Tripathi is the most popular and most preferred textbook, closely seconded by Pharmacology for Medical Students by Tara V Shanbhag and Smita Shenoy and followed by Medical Pharmacology by Padmaja Udaykumar, the third in the list of the most preferred textbook. The shortcomings of textbooks, such as the innate lack of the ability to cultivate interest in common diseases which are prevalent in the home country of the students, as well as the lack to inspire students to do further reading into research articles and studies, clearly showcases the disconnect that exists between publishers, authors and users.

Novel drug for COVID-19: Virafin a therapeutic breakthrough

Abstract: Background: Pegylated Interferon Alpha-2b is synthesized via the use of PEG (polyethylene glycol). It is formulated via attaching a 12kDa mono methoxy polyethylene glycol moiety to the recombinant human Interferon Alpha-2b protein. Pegylated Interferon Alpha-2b acts via binding to the (JAK/STAT) Janus kinase signal transducer and activator of the transcription interferon receptor. The Pegylated Interferon Alpha-2b /Virafin binds to the (IFNAR1/2) alpha interferon receptor 1 and 2. Pegylated Interferon Alpha-2b better known as Virafin has been approved by the Drugs Controller General of India. This therapeutic agent is currently under a multicentric phase 3 trial with very promising results being reported. A single subcutaneous dose of Virafin has been shown to decrease the need for oxygen therapy in patients. This reduction in the need for oxygen therapy is a vital factor needed to provide relief to the Indian medical system in light of the recent oxygen shortages faced due to India’s worst wave of COVID-19 cases since the onset of the global pandemic. Pegylated Interferon Alpha-2b/ Virafin confers enhanced viral clearance and bolsters the immune response to induce a quicker recovery in patients with mild to moderate symptoms. Conclusion: It is of paramount importance that further research on Virafin is undertaken as it can hinder the progression of COVID-19, reduce pressure on the inundated health systems, and save countless lives.

A Closeness Centrality Based P2P Botnet Detection Approach Using Deep Learning

Abstract: A botnet (or, a network of bots) is an army of compromised machines that are often under the control and coordination of one or multiple sources or work in a peer-to-peer mode through a remote secure channel. Botnet infection modeling enables design for secure systems. This work proposes an innovative approach using the concept of graph theory-based closeness centrality seeded with deep learning to detect peer-to-peer botnet infection across nodes. Compromised networks can be quite big as botnets and malware infections utilize the ubiquitous internet to spread rapidly. Using closeness centrality as one of the major inclination factors of interacting nodes, the deep neural model is applied. The performance of the proposed method is evaluated by identifying botnet traffic with a high true positive rate (bot-infected node detection rate) and a low false-positive rate.

Privacy preservation and secure data sharing scheme in fog based vehicular ad-hoc network

Abstract: Due to the increase in vehicle numbers and various services, such as exchanging messages between vehicles under different traffic conditions and in an emergency, the vehicular cloud computing (VCC) has drawn significant attention. The current centralized system has the computation and safety requirements such as secure storage, authentication, access control, availability over alternative network connections, and a real-time summary of the data flow. The traditional method includes the transfer of data for processing from the edge node to a centralized server that reduces the available bandwidth and increases the latency across the network. Transmission of the vast amount of data from the edge devices to a central system increases the chances of getting a security breach that leads to compromised information and data loss. In this paper, we propose a Privacy Preservation and Secure Data Sharing Scheme in Fog Based Vehicular Ad-hoc Network by analyzing critical information and employing data confidentiality with the help of Hierarchical Attribute-Based Encryption (HABE) with an efficient key exchange. The proposed scheme also uses symmetric encryption and a Hash-based Message Authentication Code (HMAC) computation with the shared secret key to secure the message transmission between vehicles. It also provides fine-grained access control before outsourcing data to the cloud server to ensure privacy depends on ownership to reduce the number of data forwarded to the cloud server with a short period and decreases bandwidth requirements due to fast analytics at the edge. Assessment of the proposed scheme is done by finding the key generation computation cost on attribute authority, message broadcasting computation cost for vehicles, and message decryption computation cost for vehicles.

Gastrointestinal manifestations as early symptoms to diagnose COVID-19 paediatric cases

Abstract: Background: The international situation surrounding the COVID-19 pandemic is seeing multiple countries battle various waves of the SARS-CoV-2 virus infections, with millions of individuals being infected globally. COVID-19 cases initially involved the immuno-compromised and elderly. As the virus has infected millions globally, the demographic profile of cases has shifted with more children being infected; this increase in younger individuals contracting the infection has resulted in new symptoms with altered manifestations and presentations of the disease in the young. In comparison to the severe symptoms of COVID-19 in adults children present with a more trivial group of symptoms. The majority of children develop mild symptoms or remain asymptomatic. This is in stark contrast to adults who have a higher admission rate with severe symptoms. A sign of great importance and now incidence in pediatric cases with COVID-19 is that of the gastrointestinal tract. The virus has a tropism for the GIT due to the presence of ACE2 receptors, which facilitate the entry of the virus into the cell. Conclusion: It is now established that the GIT symptoms form part of a newly recognized multisystem inflammatory syndrome (MIS-C) which occurs as a result and or manifestation of the COVID-19 infection. The innate difficulty in correctly and accurately diagnosing such a case is that the symptoms very close mimic gastroenteritis and acute abdominal pathologies. Therefore, physicians need to be aware of the various manners in which the COVID-19 infection manifests itself in children to diagnose better and isolate the cases.

Dynamic Structural Impact of the COVID-19 Outbreak on the Stock Market and the Exchange Rate: A Cross-country Analysis Among BRICS Nations

Abstract: COVID-19 has impacted the economy of almost every country in the world. Of particular interest are the responses of the economic indicators of developing nations (such as BRICS) to the COVID-19 shock. As an extension to our earlier work on the dynamic associations of pandemic growth, exchange rate, and stock market indices in the context of India, we look at the same question with respect to the BRICS nations. We use structural variable autoregression (SVAR) to identify the dynamic underlying associations across the normalized growth measurements of the COVID-19 cumulative case, recovery, and death counts, and those of the exchange rate, and stock market indices, using data over 203 days (March 12 - September 30, 2020). Using impulse response analyses, the COVID-19 shock to the growth of exchange rate was seen to persist for around 10+ days, and that for stock exchange was seen to be around 15 days. The models capture the contemporaneous nature of these shocks and the subsequent responses, potentially guiding to inform policy decisions at a national level. Further, causal inference-based analyses would allow us to infer relationships that are stronger than mere associations.

Pharmacotherapy of Cytokine Release Syndrome in Severe COVID-19 Patients: A Systematic Review

Abstract: The coronavirus pandemic which spread from Wuhan China toward the latter part of 2019 has resulted in 216,303,376 confirmed cases and 4,498,451deaths deaths to date. The novelty and lack of a definitive treatment protocol for the virus and the acute respiratory distress syndrome it produces has resulted in patients being placed on artificial ventilation and most often never recovering therefrom. Very little is known about the pathophysiology of the virus and the biological mechanisms in which it disrupts to bring about the now identified wide array of clinical features which are not solely isolated to the respiratory tract. It is now an established fact however, that one of the major pathways implicated and on which often results in the death and or severe complications in COVID-19 patients is the cytokine storm. The use of new drugs to combat such a cytokine storm is thus important considering the current global COVID-19 situation so as to stop the further progression of the disease in patients and decrease both morbidity and mortality by crippling a major mechanism which hastens death in the hosts. It is, therefore, vital that a systematic analysis and review of the various therapeutic agents are undertaken to select the best drug for the treatment of patients with cytokine storm. This research aims to relate the best therapeutic regimens currently available precisely and concisely to physicians so as to ensure the best possible treatment modality is selected for each patient. An extensive review of the literature was done on the following databases: Google scholar, Trip database, EMBASE, PubMed, and PubMed Central. The keywords and the Boolean operators used for searches were “COVID-19” OR “SARS-CoV-2” AND “Therapeutics” OR “drug therapy” AND “Cytokine Release Syndrome.” The discovery and the use of such drugs, namely, Tocilizumab and potent corticosteroids such as dexamethasone and methylprednisolone in the maximum daily doses of 6 mg and 250 mg, respectively, have shown positive outcome to combat cytokine storm in severe COVID-19 patients. The rationale behind the use of these drugs being to suppress the immune system and thus decrease the detrimental cytokine cascade induced in severely ill COVID-19 patients will be instrumental in the treatment and prevention of severe complication. It is vital for the various drugs under trial and implemented in emergency use to be compared and studied so as to best select the drug which can be incorporated into a treatment regimen which is both effective and has diminished adverse effects.