Research Trends in the Management of Scaphoid Non-unions: A Bibliometric Review.

Background: The scaphoid is the most commonly fractured carpal bone, often going into non-union and secondary complications. Despite this, no explicit guidelines exist for the management of its non-union till date. This study quantitatively analyses the existent research on scaphoid nonunions from 2013 to 2024 using bibliometric methodology.

Effect of matrix material property on the composite tibia fracture plate: a biomechanical study.

For the purpose of fixing tibia fractures, composite bone plates are suggested. Metal plates cause stress shielding, lessen the compression force at the fracture site, and have an impact on the healing process because they are significantly more rigid than bone. To prevent excessive shear strain and consequent instability at the fracture site, it is imperative to reduce stiffness in the axial direction without lowering stiffness in the transverse direction.

Deep-Fuzz: A synergistic integration of deep learning and fuzzy water flows for fine-grained nuclei segmentation in digital pathology.

Robust semantic segmentation of tumour micro-environment is one of the major open challenges in machine learning enabled computational pathology. Though deep learning based systems have made significant progress, their task agnostic data driven approach often lacks the contextual grounding necessary in biomedical applications. We present a novel fuzzy water flow scheme that takes the coarse segmentation output of a base deep learning framework to then provide a more fine-grained and instance level robust segmentation output.

Novel Statistical Investigation for COVID-19 Community Response.

A novel coronavirus (COVID-19) that highly affected the mortality rate on the global health crisis emerged to be a pandemic from November 19. COVID-19 is known as a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The virus was initially originated from bats and was transmitted to humans through unknown intermediary animals.

Development of a Rice Plant Disease Classification Model in Big Data Environment.

More than the half of the global population consume rice as their primary energy source. Therefore, this work focused on the development of a prediction model to minimize agricultural loss in the paddy field. Initially, rice plant diseases, along with their images, were captured.

Online Predictor Using Machine Learning to Predict Novel Coronavirus and Other Pathogenic Viruses.

The problem of virus classification is always a subject of concern for virology or epidemiology over the decades. In this regard, a machine learning technique can be used to predict the novel coronavirus by considering its sequence. Thus, we are proposing a machine learning-based novel coronavirus prediction technique, called COVID-Predictor, where 1000 sequences of SARS-CoV-1, MERS-CoV, SARS-CoV-2, and other viruses are used to train a Naive Bayes classifier so that it can predict any unknown sequences of these viruses.

Modeling and simulation of high energy density lithium-ion battery for multiple fault detection.

Lithium-ion battery, a high energy density storage device has extensive applications in electrical and electronic gadgets, computers, hybrid electric vehicles, and electric vehicles. This paper presents multiple fault detection of lithium-ion battery using two non-linear Kalman filters. A discrete non-linear mathematical model of lithium ion battery has been developed and Unscented Kalman filter (UKF) is employed to estimate the model parameter.

Thermodynamic effect of RNA virus infection on the human cardiovascular system.

In this work, analysis of cardiovascular system under the influence of RNA virus infection has been performed from a thermodynamic perspective. An exergetic efficiency of the system has been defined for this purpose. Results show that except for asymptomatic case, the exergetic efficiency reduces as the viral load goes up.

Whole genome analysis of more than 10 000 SARS-CoV-2 virus unveils global genetic diversity and target region of NSP6.

Whole genome analysis of SARS-CoV-2 is important to identify its genetic diversity. Moreover, accurate detection of SARS-CoV-2 is required for its correct diagnosis. To address these, first we have analysed publicly available 10 664 complete or near-complete SARS-CoV-2 genomes of 73 countries globally to find mutation points in the coding regions as substitution, deletion, insertion and single nucleotide polymorphism (SNP) globally and country wise.

A Brief on Biological Thermodynamics for Human Physiology.

Thermodynamics, the science of energy interactions, governs the direction of processes found in nature. While the subject finds wide applications in science and technology, its connection to biological sciences and in particular to bio-engineering is becoming increasingly important. In this work, after a brief introduction to the fundamental concepts in thermodynamics, we focus on its application in human physiology.

COVID-DeepPredictor: Recurrent Neural Network to Predict SARS-CoV-2 and Other Pathogenic Viruses.

The COVID-19 disease for Novel coronavirus (SARS-CoV-2) has turned out to be a global pandemic. The high transmission rate of this pathogenic virus demands an early prediction and proper identification for the subsequent treatment. However, polymorphic nature of this virus allows it to adapt and sustain in different kinds of environment which makes it difficult to predict.

Performance analysis of human respiratory system based on the second law of thermodynamics.

The purpose of this study is to develop a comprehensive thermodynamic model of the human respiratory system and quantify the effects of inspiratory air temperature, relative humidity (RH), lung capacity and O fluctuation in metabolic reaction on the human respiratory system under three different physiological conditions, i.e. rest, moderate level of physical activity and extreme level of physical activity.

An improved analytical model for heat flow in cancerous tumours to avoid thermal injuries during hyperthermia.

The present study highlights an analytical hybrid scheme consisted of a shift of variables and finite integral transform for analysing a local thermal non-equilibrium (LTNE) bioheat model. This model can have utilised to be a betterment of prediction of the temperature field in the localised hyperthermia therapy (LHT) for the treatment of cancer patients. As the hyperthermia treatment is only the application in living tissues, an appropriate initial condition for the therapeutic thermal response is proposed instead of a constant temperature taken in the previous studies based on the 1-D heat flow.

Topological Analysis for Sequence Variability: Case Study on more than 2K SARS-CoV-2 sequences of COVID-19 infected 54 countries in comparison with SARS-CoV-1 and MERS-CoV.

The pandemic due to novel coronavirus, SARS-CoV-2 is a serious global concern now. More than thousand new COVID-19 infections are getting reported daily for this virus across the globe. Thus, the medical research communities are trying to find the remedy to restrict the spreading of this virus, while the vaccine development work is still under research in parallel.

A novel CFD analysis to minimize the spread of COVID-19 virus in hospital isolation room.

The COVID-19 is a severe respiratory disease caused by a devastating coronavirus family (2019-nCoV) has become a pandemic across the globe. It is an infectious virus and transmits by inhalation or contact with droplet nuclei produced during sneezing, coughing, and speaking by infected people. Airborne transmission of COVID-19 is also possible in a confined place in the immediate environment of the infected person.

Mapping sequence to feature vector using numerical representation of codons targeted to amino acids for alignment-free sequence analysis.

The phylogenetic analysis based on sequence similarity targeted to real biological taxa is one of the major challenging tasks. In this paper, we propose a novel alignment-free method, CoFASA (Codon Feature based Amino acid Sequence Analyser), for similarity analysis of nucleotide sequences. At first, we assign numerical weights to the four nucleotides.

Inferring the genetic variability in Indian SARS-CoV-2 genomes using consensus of multiple sequence alignment techniques.

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is a threat to the human population and has created a worldwide pandemic. Daily thousands of people are getting affected by the SARS-CoV-2 virus; India being no exception. In this situation, there is no doubt that vaccine is the primary prevention strategy to contain the wave of COVID-19 pandemic.

Genome-wide analysis of Indian SARS-CoV-2 genomes for the identification of genetic mutation and SNP.

The wave of COVID-19 is a big threat to the human population. Presently, the world is going through different phases of lock down in order to stop this wave of pandemic; India being no exception. We have also started the lock down on 23rd March 2020.

Devulcanization of Waste Rubber and Generation of Active Sites for Silica Reinforcement.

Each year, hundreds of millions of tires are produced and ultimately disposed into nature. To address this serious environmental issue, devulcanization could be one of the sustainable solutions that still remains as one of the biggest challenges across the globe. In this work, sulfur-vulcanized natural rubber (NR) is mechanochemically devulcanized utilizing a silane-based tetrasulfide as a devulcanizing agent, and subsequently, silica (SiO)-based rubber composites are prepared.

Entropy generation in the human lung due to effect of psychrometric condition and friction in the respiratory tract.

Background And Objective: Entropy generation is associated with the irreversibility of any thermodynamic system. It provides an indication of lost energy and hence the efficiency of a system. In this paper, an attempt has been made to study the effects of specific humidity, relative humidity, ambient temperature change, breathing air friction with the respiratory tract on the entropy generation during the respiration process at different physiological conditions.

2dSpAn: semiautomated 2-d segmentation, classification and analysis of hippocampal dendritic spine plasticity.

Motivation: Accurate and effective dendritic spine segmentation from the dendrites remains as a challenge for current neuroimaging research community. In this article, we present a new method (2dSpAn) for 2-d segmentation, classification and analysis of structural/plastic changes of hippocampal dendritic spines. A user interactive segmentation method with convolution kernels is designed to segment the spines from the dendrites.

Cancer classification from gene expression data by NPPC ensemble.

The most important application of microarray in gene expression analysis is to classify the unknown tissue samples according to their gene expression levels with the help of known sample expression levels. In this paper, we present a nonparallel plane proximal classifier (NPPC) ensemble that ensures high classification accuracy of test samples in a computer-aided diagnosis (CAD) framework than that of a single NPPC model. For each data set only, a few genes are selected by using a mutual information criterion.