Background Due to the intermittent, nonlinear, and uncertain behavior of renewable energy sources (res) such as solar and wind, grid stability and reliability require very high forecasting and optimization skills as widely reported in the literature. Traditional optimization methods work very well in small or static systems but are suffer difficulty on large-scale, dynamic and stochastic renewable environment due to their NP-hard nature. Methods The framework introduces the concept of a Machine Learning-Assisted Hybrid Cuckoo Search (ML-HCS) that combines CS with a hybrid metaheuristic and integrates Long Short-Term Memory (LSTM) networks for forecasting based on both regression models of LSTMs and hybrid optimization algorithm

A total of (25) stool samples were collected from children and adults (2- 4) years old suffering from diarrhea to isolate E. coli strains that produce heat-stable enterotoxin a (STa), and after performing microscopic examination, cultural characterization and biochemical identification only (11) isolates showed positive E. coli. STa activity was estimated by using suckling mouse assay (SMA) and from these (11) isolates only (5) showed STa activity and the one with the highest STa activity was selected for large scale production of STa, which was followed by partial purification using ion-exchange chromatography (normal phase) using DEAE sephadex A-50 column. After purification and determination of protein concentration by using the standard

The study objectives were to (1) describe the characteristics of the pharmacy professionals and (2) explore the association between job satisfaction and factors, such as work control, work stress, workload and organization and professional commitments.

This study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K

The physical behavior for the energy distribution function (EDF) of the reactant particles depending upon the gases (fuel) temperature are completely described by a physical model covering the global formulas controlling the EDF profile. Results about the energy distribution for the reactant system indicate a standard EDF, in which it’s arrive a steady state form shape and intern lead to fix the optimum selected temperature.

Experiments were carried out to investigate natural convection heat transfer in an inclined uniformly heated circular cylinder . The effects of surface heat flux and angle of inclination on the temperature and local Nusselt number variations along the cylinder surface are discussed . The investigation covers heat flux range from 92 W/m² to 487 W/m², and angles of inclination 0° ( horizontal) , 30° , 60° and 90° (vertical) . Results show an increase in the natural convection as heat flux increases and as angle of inclination moves from vertical to horizontal position. An empirical equation of average Nusselt number as a function of Rayliegh number was deduced for each angle of inclination .