Minimal sourced and lightweight federated transfer learning models for skin cancer detection.

One of the most fatal diseases that affect people is skin cancer. Because nevus and melanoma lesions are so similar and there is a high likelihood of false negative diagnoses challenges in hospitals. The aim of this paper is to propose and develop a technique to classify type of skin cancer with high accuracy using minimal resources and lightweight federated transfer learning models.

AI-based hybrid power quality control system for electrical railway using single phase PV-UPQC with Lyapunov optimization.

This research paper presents an advanced AI-driven hybrid power quality management system for electrical railways that addresses critical challenges in 25 kV AC traction networks through a novel integration of single-phase PV-UPQC with ANN-Lyapunov control architecture. The system effectively manages voltage unbalance exceeding 2%, high THD, voltage variations of ± 10%, and poor power factor through a dual-approach methodology combining ANN-based reference signal generation with Lyapunov optimization, enabling dynamic parameter tuning and real-time load adaptation. MATLAB/Simulink simulations validate the system's superior performance, demonstrating significant improvements, including voltage unbalance reduction from 1.

Silymarin: a promising modulator of apoptosis and survival signaling in cancer.

Cancer, one of the deadliest diseases, has remained the epicenter of biological research for more than seven decades. Yet all the efforts for a perfect therapeutic cure come with certain limitations. The use of medicinal plants and their phytochemicals as therapeutics has received much attention in recent years.

Association Between SHBG Levels and Hypertensive Disorders of Pregnancy: A Systematic Review and Meta-Analysis.

Sex hormone-binding globulin (SHBG) regulates sex hormone availability and is influenced by metabolic factors. Variations in SHBG levels during pregnancy may affect the development of hypertensive disorders such as gestational hypertension (GH) and preeclampsia (PE). This systematic review and meta-analysis explores the potential of SHBG as a biomarker for predicting GH and PE.

Production and characterization of sophorolipid under yeast-mediated submerged fermentation utilizing Agro-industrial waste.

The challenges of pollution and agro-industrial waste management have led to the development of bioconversion techniques to transform these wastes into valuable products. This has increased the focus on the sustainable and cost-efficient production of biosurfactants from agro-industrial waste. Hence, the present study investigates the production of sophorolipid biosurfactants using the yeast strain IIPL32 under submerged fermentation, employing sugarcane bagasse hydrolysate-a renewable, low-cost agro-industrial waste as the feedstock.

The interplay of senescence and MMPs in myocardial infarction: implications for cardiac aging and therapeutics.

Aging is associated with a marked increase in cardiovascular diseases, such as myocardial infarction (MI). Cellular senescence is also a crucial factor in the development of age-related MI. Matrix metalloproteinases (MMPs) interaction with cellular senescence is a critical determinant of MI development and outcomes, most notably in the aged heart.

Targeting senescence and GATA4 in age-related cardiovascular disease: a comprehensive approach.

The growing prevalence of age-related cardiovascular diseases (CVDs) poses significant health challenges, necessitating the formulation of novel treatment approaches. GATA4, a vital transcription factor identified for modulating cardiovascular biology and cellular senescence, is recognized for its critical involvement in CVD pathogenesis. This review collected relevant studies from PubMed, Google Scholar, and Science Direct using search terms like 'GATA4,' 'cellular senescence,' 'coronary artery diseases,' 'hypertension,' 'heart failure,' 'arrhythmias,' 'congenital heart diseases,' 'cardiomyopathy,' and 'cardiovascular disease.

A comprehensive review of sustainable hydrogels from lignin for advanced wastewater solutions.

Throughout the recent years, water bodies have been significantly contaminated via various industrial and pollution wastes posing threats to the living. To tackle the situation, Lignin-Based Hydrogels have appeared as a material with great potential for wastewater treatment. Biomass-derived polymers for wastewater treatment present a sustainable replacement to plastics based on petroleum owing to its biocompatibility, affordability, eco-friendliness and biodegradability.

Advanced microgrid optimization using price-elastic demand response and greedy rat swarm optimization for economic and environmental efficiency.

In this paper, a comprehensive energy management framework for microgrids that incorporates price-based demand response programs (DRPs) and leverages an advanced optimization method-Greedy Rat Swarm Optimizer (GRSO) is proposed. The primary objective is to minimize the generation cost and environmental impact of microgrid systems by effectively scheduling distributed energy resources (DERs), including renewable energy sources (RES) such as solar and wind, alongside fossil-fuel-based generators. Four distinct demand response models-exponential, hyperbolic, logarithmic, and critical peak pricing (CPP)-are developed, each reflecting a different price elasticity of demand.

Energy feature extraction and visualization of voltage sags using wavelet packet analysis for enhanced power quality monitoring.

Power quality (PQ) disturbances, such as voltage sags, are significant issues that can lead to damage in electrical equipment and system downtime. Detecting and classifying these disturbances accurately is essential for maintaining reliable power systems. This paper introduces a novel approach to voltage sag analysis by employing wavelet packet analysis combined with energy-based feature extraction to enhance PQ monitoring.

Optimal parameter identification of photovoltaic systems based on enhanced differential evolution optimization technique.

Identifying the parameters of a solar photovoltaic (PV) model optimally, is necessary for simulation, performance assessment, and design verification. However, precise PV cell modelling is critical for design due to many critical factors, such as inherent nonlinearity, existing complexity, and a wide range of model parameters. Although different researchers have recently proposed several effective techniques for solar PV system parameter identification, it is still an interesting challenge for researchers to enhance the accuracy of the PV system modelling.

Patterns and trends in burden of asthma and its attributable risk factors from 1990 to 2021 among south Asian countries: a systematic analysis for the Global Burden of Disease Study 2021.

Objective: Asthma poses a significant health burden in South Asia, with increasing incidence and mortality despite a global decline in age-standardized prevalence rates. This study aims to analyze asthma trends from 1990 to 2021, focusing on prevalence, incidence, mortality, and disability-adjusted life years (DALYs) across South Asia. The study also assesses the impact of risk factors like high body mass index (BMI), smoking, and occupational exposures on asthma outcomes.

Burden of rheumatic diseases among people with diabetes: A systematic review and meta-analysis.

Diabetes mellitus type 2 (DM2) is a prevalent metabolic condition affecting over 500 million people globally and associated with serious comorbidities, including various rheumatologic conditions. Some studies have reported a significant association between rheumatological conditions and DM2. However, the global burden of rheumatological conditions among people with DM2 remains unknown.

Efficient pressure regulation in nonlinear shell-and-tube steam condensers via a Novel TDn(1 + PIDn) controller and DCSA algorithm.

Steam condensers are vital components of thermal power plants, responsible for converting turbine exhaust steam back into water for reuse in the power generation cycle. Effective pressure regulation is crucial to ensure operational efficiency and equipment safety. However, conventional control strategies, such as PI, PI-PDn and FOPID controllers, often struggle to manage the nonlinearities and disturbances inherent in steam condenser systems.

Optimizing Linezolid: Transforming It into a Selective MAO-B Inhibitor via a Toxicity-to-Activity Optimization Approach.

Linezolid, a widely used oxazolidinone antibiotic, exhibits potent activity against resistant bacterial infections but is associated with serotonergic toxicity, primarily due to its inhibition of monoamine oxidase (MAO). MAOs, consisting of MAO-A and MAO-B isoforms, play crucial roles in neurotransmitter metabolism, with implications for neurodegenerative disorders like Parkinson's and Alzheimer's diseases. This study aims to optimize Linezolid's structure to transform it into a selective MAO-B inhibitor.

Burden of diabetes in correctional facilities: A global systematic review and meta-analysis.

Background: Diabetes mellitus presents significant public health challenges worldwide. While its prevalence and management in the general population have been extensively studied, comprehensive research on diabetes among incarcerated individuals is lacking. This study aims to conduct a systematic review and -analysis to determine the prevalence of diabetes within the prison population.

Antidiabetic phytochemicals: an overview of medicinal plants and their bioactive compounds in diabetes mellitus treatment.

Diabetes mellitus (DM) is a group of metabolic disorders characterized by hyperglycemia due to insufficient insulin secretion or action. Contributing factors include genetic predisposition, obesity, family history, inactivity, and environmental risks. Type 2 diabetes mellitus (T2DM), the most common form, involves impaired insulin secretion by pancreatic β-cells, leading to insulin resistance.

Exploring the link between sex hormone-binding globulin levels and prostate cancer risk: a comprehensive systematic review and meta-analysis.

Background: Sex hormone-binding globulin (SHBG) plays a critical role in regulating androgen bioavailability and has been hypothesized to influence prostate cancer risk, though existing evidence is inconsistent. This systematic review and meta-analysis aimed to evaluate the association between SHBG levels and prostate cancer risk.

Methods: A comprehensive search was conducted across PubMed, Embase, and Web of Science for studies published up to December 1, 2024.

Wind energy assessment and hybrid micro-grid optimization for selected regions of Saudi Arabia.

This study investigates the optimization of wind energy integration in hybrid micro grids (MGs) to address the rising demand for renewable energy, particularly in regions with limited wind potential. A comprehensive assessment of wind energy potential was conducted, and optimal sizing of standalone MGs incorporating photovoltaic (PV) systems, wind turbines (WT), and battery storage (BS) systems was performed for six regions in the Kingdom Saudi Arabia. Wind resource analysis utilizing the Weibull distribution function shows that all regions exhibited Class 1 wind energy characteristics, with average annual wind power densities ranging from 36.

An approach for load frequency control enhancement in two-area hydro-wind power systems using LSTM + GA-PID controller with augmented lagrangian methods.

This paper proposes an advanced Load Frequency Control (LFC) strategy for two-area hydro-wind power systems, using a hybrid Long Short-Term Memory (LSTM) neural network combined with a Genetic Algorithm-optimized PID (GA-PID) controller. Traditional PID controllers, while extensively used, often face limitations in handling the nonlinearities and uncertainties inherent in interconnected power systems, leading to slower settling time and higher overshoot during load disturbances. The LSTM + GA-PID controller mitigates these issues by utilizing LSTM's capacity to learn from historical data by using gradient descent to forecast the future disturbances, while the GA optimizes the PID parameters in real time, ensuring dynamic adaptability and improved control precision.

Insights into the biogenic production of nanocomposites of NiO-chitosan for wastewater remediation.

In our study, we have tried to enhance the biological qualities of nickel oxide nanoparticles and nanocomposites which were prepared using the extract of Aegle marmelos tree leaves and chitosan biopolymer. For in-depth study of the fabricated samples, numerous physiochemical approaches were utilized. The analysis used consists of field emission scanning electron microscopy with energy dispersive X-ray analysis and photoluminescence, X-ray diffraction, UV-visible spectroscopy, and Fourier transform infrared spectroscopy.

Multi-scale feature fusion of deep convolutional neural networks on cancerous tumor detection and classification using biomedical images.

In the present scenario, cancerous tumours are common in humans due to major changes in nearby environments. Skin cancer is a considerable disease detected among people. This cancer is the uncontrolled evolution of atypical skin cells.

Speciation and historical invasions of the Asian black-spined toad (Duttaphrynus melanostictus).

Animal translocations provide striking examples of the human footprint on biodiversity. Combining continental-wide genomic and DNA-barcoding analyses, we reconstructed the historical biogeography of the Asian black-spined toad (Duttaphrynus melanostictus), a toxic commensal amphibian that currently threatens two biodiversity hotspots through biological invasions (Wallacea and Madagascar). The results emphasize a complex diversification shaped by speciation and mitochondrial introgression that comprises two distinct species.