DWT-EMD Feature Level Fusion Based Approach over Multi and Single Channel EEG Signals for Seizure Detection.

Brain Computer Interface technology enables a pathway for analyzing EEG signals for seizure detection. EEG signal decomposition, features extraction and machine learning techniques are more familiar in seizure detection. However, selecting decomposition technique and concatenation of their features for seizure detection is still in the state-of-the-art phase.

Bacterial biofilm infections, their resistance to antibiotics therapy and current treatment strategies.

Nearly 80% of human chronic infections are caused due to bacterial biofilm formation. This is the most leading cause for failure of medical implants resulting in high morbidity and mortality. In addition, biofilms are also known to cause serious problems in food industry.

FastSS: Fast and smooth segmentation of JPEG compressed printed text documents using DC and AC signal analysis.

With the surge of COVID-19 pandemic, the world is moving towards digitization and automation more than it was presumed. The Internet is becoming one of the popular mediums for communication, and multimedia (image, audio, and video) combined with data compression techniques play a pivotal role in handling a huge volume of data that is being generated on a daily basis. Developing novel algorithms for automatic analysis of compressed data without decompression is the need of the present hour.

Predicting optoacoustic spectral behaviour of human erythrocytes, stomatocytes and echinocytes using a modified Green's function method.

Optoacoustic (OA) spectral properties of various sources mimicking normal and pathological red blood cells (RBCs) have been studied. The shapes of normal RBC and cells suffering from stomatocytosis (denoted by ST) were generated using mathematical models. However, the shape corresponding to the cells affected by echinocytosis (referred to as ET) was constructed by uniformly distributing half prolate spheroids on a central spherical object.

Antimicrobial Peptides from Human Microbiome Against Multidrug Efflux Pump of Pseudomonas aeruginosa: a Computational Study.

The excess use of antibiotics has led to the evolution of multidrug-resistant pathogenic strains causing worldwide havoc. These multidrug-resistant strains require potent inhibitors. Pseudomonas aeruginosa is a lead cause of nosocomial infections and also feature in the critical priority list of the world health organization (WHO) for the development of new antibiotics against their antimicrobial resistance.

Naturally occurring anthraquinones as potential inhibitors of SARS-CoV-2 main protease: an integrated computational study.

Unlabelled: The novel coronavirus disease (COVID-19) has spread throughout the globe, affecting millions of people. The World Health Organization (WHO) has declared this infectious disease a pandemic. At present, several clinical trials are going on to identify possible drugs for treating this infection.

Pathways in small cell lung cancer and its therapeutic perspectives.

Small cell lung cancer (SCLC) is known for its rapid growth with high metastatic spread. Its treatment remains a major challenge for oncologists due to the high mutation rate and other clinical disadvantages. The survival rate of these patients is very poor but there is no significant progress over the last few decades in the treatment protocols.

Determination of tyrosinase-cyanidin-3-O-glucoside and (-/+)-catechin binding modes reveal mechanistic differences in tyrosinase inhibition.

Tyrosinase, exquisitely catalyzes the phenolic compounds into brown or black pigment, inhibition is used as a treatment for dermatological or neurodegenerative disorders. Natural products, such as cyanidin-3-O-glucoside and (-/+)-catechin, are considered safe and non-toxic food additives in tyrosinase inhibition but their ambiguous inhibitory mechanism against tyrosinase is still elusive. Thus, we presented the mechanistic insights into tyrosinase with cyanidin-3-O-glucoside and (-/+)-catechin using computational simulations and in vitro assessment.

Identification of common genes in obesity and cancer through network interaction and targeting those genes by virtual screening approach.

Obesity may have an effect on cancer outcomes, resulting in global inequalities in cancer survival and death. Microarray data analysis was done to identify differentially expressed genes (DEGs) in obese and cancer patients. Total 1977 differentially expressed genes among obesity and gastric cancer, breast cancer, pancreatic cancer, and colorectal cancer were used to build a gene interaction network, which was then analyzed by using Cytoscape software.

Exploring polynomial based interpolation schemes for photoacoustic tomographic image reconstruction.

Photoacoustic tomography (PAT) imaging employing polynomial-based interpolation methods is discussed. Nearest-neighbor, bilinear, bicubic and biquintic algorithms were implemented for the construction of the model matrix, and images were formed using the Tikhonov regularization and total variation (TV) minimization procedures. The performance of the interpolation methods was assessed by comparing the reconstructed images of three numerical and two experimental phantoms.

Docking and molecular dynamics simulation for therapeutic repurposing in small cell lung cancer (SCLC) patients infected with COVID-19.

Cancer care has become a challenge with the current COVID-19 pandemic scenario. Specially, cancers like small cell lung cancers (SCLC) are difficult to treat even in the normal situation due to their rapid growth and early metastasis. For such patients, treatment can't be compromised and care must be taken to ensure their minimum exposure to the ongoing spread of COVID-19 infection.

Secure Cognitive Radio-Enabled Vehicular Communications under Spectrum-Sharing Constraints.

Vehicular communication has been envisioned to support a myriad of essential fifth-generation and beyond use-cases. However, the increasing proliferation of smart and intelligent vehicles has generated a lot of design and infrastructure challenges. Of particular interest are the problems of spectrum scarcity and communication security.

Cross-covariance based affinity for graphs.

The accuracy of graph based learning techniques relies on the underlying topological structure and affinity between data points, which are assumed to lie on a smooth Riemannian manifold. However, the assumption of local linearity in a neighborhood does not always hold true. Hence, the Euclidean distance based affinity that determines the graph edges may fail to represent the true connectivity strength between data points.

Repurposing of gastric cancer drugs against COVID-19.

Corona Virus Disease 2019 (COVID-19) caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has become a global pandemic. Additionally, the SARS-CoV-2 infection in the patients of Gastric Cancer (GC; the third leading cause of death in the world) pose a great challenge for the health management of the patients. Since there have been uncertainties to develop a new drug against COVID-19, there is an urgent need for repurposing drugs that can target key proteins of both SARS-CoV-2 and GC.

Identification of hub genes in common cancers of women in India and targeting for the search of anticancer agent from phytoconstituent using interaction network analysis and virtual screening.

Cancer is one of the most dreadful diseases across the globe, with the advancement in this field a great advent has been achieved in treating cancer by various therapies like chemotherapy, radiation therapy, hormone therapy, gene therapy, and many more but also the most serious concern associated with the available treatments are the toxicities or the side effects linked to them, apart from this the treatment of many malignancies are still not available, because of these such issues, tremendous research is still going on in the whole world to find a better and more potent treatment option for cancer. Cancer develops due to the synergistic effects of both genetic and epigenetic factors. The mutations that change the normal functioning of the genes are responsible for cancer.

Reversible electroporation study of realistic normal and cancerous cervical cells model using avalanche transistor-based nano pulse generator.

In this paper, we study the reversible electroporation process on normal and cancerous cervical cells. The 2D contour of the cervical cells is extracted using image processing techniques from the Pap smear images. The conductivity change in the cancer cell model has been used to differentiate the effects of the high-frequency electric field on normal and cancerous cells.

Computational Identification of SARS-CoV-2 Inhibitor in , .

A novel coronavirus disease (COVID-19), caused by SARS-CoV-2, has spread over more than 100 countries all over the world. The World Health Organization has recognized Coronavirus as a pandemic and finding an effective drug for this infectious disease is of high importance. In this study, we have explored the potent inhibitors of COVID-19 main protease from Tinospora cordifolia an Ayurvedic herb locally called as Amrita meaning 'immortality' and two other Ayurveda plants namely Cinnamomum zeylanicum and Myristica fragrans.

Autonomous magnetic microbots for environmental remediation developed by organic waste derived carbon dots.

Biodegradable precursors for micro/nanobots development are key requirements for several sustainable applications. In this regard, we propose an innovative solution for water purification at minimum cost and efforts where organic waste is used for the treatment of organic pollutants. Herein, catalytic magnetic microbots were developed by functionalizing iron oxide nanoparticles with carbon dots (C-Dots), which were synthesized by using household waste such as potato peels as precursors.

Network pharmacological evaluation of bioactive phytochemicals for identifying novel potential inhibitors against neurodegenerative disorder.

Neurodegenerative disorders are illnesses that are responsible for neuronal cell death and resulting in lifelong cognitive problems. Due to their unclear mechanism, there are no effective drugs available for the treatment. For a long time, herbal drugs have been used as a role model in the field of the drug discovery process.

Seamless Health Monitoring Using 5G NR for Internet of Medical Things.

Nowadays, information and communication technology grows rapidly. The microelectronics and communication mediums also enhance their reachability of coverage and connectivity. 5G enhances the capacity of the network in terms of lowest communication latency, highest speed, enhanced throughput, minimum E2E delay, and minimizing the packet loss.

Solving time-independent inhomogeneous optoacoustic wave equation numerically with a modified Green's function approach.

The purpose of the paper is twofold. First, a modified Green's function (MGF) approach is described for solving the time-independent inhomogeneous optoacoustic (OA) wave equation. The performance of this technique has been assessed with respect to the exact, traditional Born series and convergent Born series methods for an acoustically inhomogeneous spherical source.

A detailed review of the outbreak of COVID-19.

The disease COVID-19 caused by SARS-CoV-2 is the third highly infectious human Coronavirus epidemic in the 21 century due to its high transmission rate and quick evolution of its pathogenicity. Genomic studies indicate that it is zoonotic from bats. The COVID-19 has led to significant loss of lives and a tremendous economic decline in the world.

A simple cost-effective microfluidic platform for rapid synthesis of diverse metal nanoparticles: A novel approach towards fighting SARS-CoV-2.

The latest addition to the family of Coronaviruses, SARS-CoV-2, unleashed its wrath across the globe. The outbreak has been so rapid and widespread that even the most developed countries are still struggling with ways to contain the spread of the virus. The virus began spreading from Wuhan in China in December 2019 and has currently affected more than200 countries worldwide.

Evaluation of antidiabetic activity of dietary phenolic compound chlorogenic acid in streptozotocin induced diabetic rats: Molecular docking, molecular dynamics, in silico toxicity, in vitro and in vivo studies.

Background: Chlorogenic acid is amongst the well-known polyphenolic compounds being used in human food and beverages. Its presence has been reported in tea leaves, roasted green beans, coffee, cocoa, berry fruits, apples, citrus fruits, and pears.

Objective: The present study aims to elucidate the effectiveness of chlorogenic acid on in silico and in vitro inhibition of glucose metabolising enzymes (α-amylase and α-glucosidase) and on blood-based markers associated with diabetic complications in vivo.