Transmission dynamics of fractional order SVEIR model for African swine fever virus with optimal control analysis.

Understanding the dynamics of the African swine fever virus during periods of intense replication is critical for effective combatting of the rapid spread. In our research, we have developed a fractional-order SVEIR model using the Caputo derivatives to investigate this behaviour. We have established the existence and uniqueness of the solution through fixed point theory and determined the basic reproduction number using the next-generation matrix method.

Role of preoperative CT imaging in penetrating thoraco-abdominal injuries: A multicenter study of urban trauma centers.

Introduction: Management of penetrating thoracoabdominal (PTA) injuries with signs of hemorrhage have warranted operative intervention but improved imaging capabilities have redefined interventions required. We examined outcomes of hemodynamically stable patients undergoing preoperative CT imaging with the hypothesis that CT imaging would decrease OR time without delaying OR arrival.

Methods: A retrospective multicenter study was performed amongst four urban trauma centers examining hemodynamically stable patients with PTA injuries requiring operative intervention from January 2017-December 2021.

Outcomes of Traumatic Brain Injury Patients Managed in a Non-Intensive Care Unit Setting.

Introduction: The management of traumatic brain injury (TBI) requires significant health-care resources. The modified Brain Injury Guidelines (mBIG) stratifies TBI patients by severity to help guide disposition and management. We sought to analyze the outcomes of TBI patients managed in a non-intensive care unit (ICU) setting after stratifying them using the mBIG criteria.

Application of Newton's polynomial interpolation scheme for variable order fractional derivative with power-law kernel.

This paper, offers a new method for simulating variable-order fractional differential operators with numerous types of fractional derivatives, such as the Caputo derivative, the Caputo-Fabrizio derivative, the Atangana-Baleanu fractal and fractional derivative, and the Atangana-Baleanu Caputo derivative via power-law kernels. Modeling chaotical systems and nonlinear fractional differential equations can be accomplished with the utilization of variable-order differential operators. The computational structures are based on the fractional calculus and Newton's polynomial interpolation.

Forecasting of solar radiation for a cleaner environment using robust machine learning techniques.

Intensified research is going on worldwide to increase renewable energy sources like solar and wind to reduce emissions and achieve worldwide targets and also to address the depleting fossil fuels resources and meet the increasing energy demand of the population. Solar radiation (SR) is intermittent, so forecasting solar radiation is a must. The objective of this research is to use modern machine techniques for different climatic conditions to forecast SR with higher accuracy.

Simulation of ground water quality for noyyal river basin of Coimbatore city, Tamilnadu using MODFLOW.

In recent years groundwater modelling has become a major part of many projects dealing with groundwater exploitation, protection and remediation. Coimbatore city is located along the Noyyal River which is grown in size and population on either side of the river and the dumping of wastes very close to the river banks, leads to pollution of both surface and groundwater. Study on the quality of groundwater along the Noyyal River in Coimbatore city of Tamilnadu, is necessary to safeguard the interest of the people with respect to quality and quantity of water.

Fluorine-enriched mesoporous carbon as efficient oxygen reduction catalyst: understanding the defects in porous matrix and fuel cell applications.

Herein, fluorine enrichment in mesoporous carbon (F-MC) was explored to introduce maximum charge polarization in the porous matrix, which is beneficial for the preferential orientation of O molecules and their subsequent reduction. doping of F to porous carbon derived from phloroglucinol-formaldehyde resin using Pluronic F-127 as a structure-directing agent is standardized. The optimized F-MC catalyst exhibited excellent electrocatalytic activity towards the oxygen reduction reaction (ORR) in alkaline media (0.

Genetic diagnosis of developmental disorders in the DDD study: a scalable analysis of genome-wide research data.

Background: Human genome sequencing has transformed our understanding of genomic variation and its relevance to health and disease, and is now starting to enter clinical practice for the diagnosis of rare diseases. The question of whether and how some categories of genomic findings should be shared with individual research participants is currently a topic of international debate, and development of robust analytical workflows to identify and communicate clinically relevant variants is paramount.

Methods: The Deciphering Developmental Disorders (DDD) study has developed a UK-wide patient recruitment network involving over 180 clinicians across all 24 regional genetics services, and has performed genome-wide microarray and whole exome sequencing on children with undiagnosed developmental disorders and their parents.

Exome sequencing improves genetic diagnosis of structural fetal abnormalities revealed by ultrasound.

The genetic etiology of non-aneuploid fetal structural abnormalities is typically investigated by karyotyping and array-based detection of microscopically detectable rearrangements, and submicroscopic copy-number variants (CNVs), which collectively yield a pathogenic finding in up to 10% of cases. We propose that exome sequencing may substantially increase the identification of underlying etiologies. We performed exome sequencing on a cohort of 30 non-aneuploid fetuses and neonates (along with their parents) with diverse structural abnormalities first identified by prenatal ultrasound.

Computational modeling of protein mutant stability: analysis and optimization of statistical potentials and structural features reveal insights into prediction model development.

Background: Understanding and predicting protein stability upon point mutations has wide-spread importance in molecular biology. Several prediction models have been developed in the past with various algorithms. Statistical potentials are one of the widely used algorithms for the prediction of changes in stability upon point mutations.

Structural analysis and prediction of protein mutant stability using distance and torsion potentials: role of secondary structure and solvent accessibility.

Analyzing the factors behind protein stability is a key research topic in molecular biology, and has direct implications on protein structure prediction and protein-protein interactions. We have analyzed protein stability upon point mutations using a distance-dependant pair potential representing mainly through-space interactions, and torsion angle potential representing mainly neighboring effects as a basic statistical mechanical setup for the analysis. The synergetic effect of accessible surface area and secondary structure preferences was used as a classifier for the potentials.

CUPSAT: prediction of protein stability upon point mutations.

CUPSAT (Cologne University Protein Stability Analysis Tool) is a web tool to analyse and predict protein stability changes upon point mutations (single amino acid mutations). This program uses structural environment specific atom potentials and torsion angle potentials to predict DeltaDeltaG, the difference in free energy of unfolding between wild-type and mutant proteins. It requires the protein structure in Protein Data Bank format and the location of the residue to be mutated.

Dietary small molecules and large-scale gene expression studies: an experimental approach for understanding their beneficial effects on the development of malignant and non-malignant proliferative diseases.

Epidemiological studies have repeatedly demonstrated a correlation between nutrition, development and the severity of malignant and non-malignant proliferative diseases such as cancer and atherosclerosis. Therefore, the prevention of chronic proliferative diseases through dietary intervention is currently receiving considerable attention. Until now, much of the research is being focused on the cellular and molecular action mechanisms of dietary small molecules explaining their beneficial effects.