The designer must find the optimum match between the object's technical and economic needs and the performance and production requirements of the various material options when choosing material for an engineering application. This study proposes an integrated (hybrid) strategy for selecting the optimal material for an engineering design depending on design requirements. The primary objective is to determine the best candidate material for the drone wings based on Ashby's performance indices and then rank the result using a grey relational technique with the entropy weight method. Aluminum alloys, titanium alloys, composites, and wood have been suggested as suitable materials for manufacturing drone wings. The requirement

This paper presents a computer simulation model of a thermally activated roof (TAR) to cool a room using cool water from a wet cooling tower. Modeling was achieved using a simplified 1-D resistance-capacitance thermal network (RC model) for an infinite slab. Heat transfer from the cooling pipe network was treated as 2-D heat flow. Only a limited number of nodes were required to obtain reliable results. The use of 6^th order RC-thermal model produced a set of ordinary differential equations that were solved using MATLAB - R2012a. The computer program was written to cover all possible initial conditions, material properties, TAR system geometry and hourly solar radiation. The cool water supply was considered time

This paper aims to improve the voltage profile using the Static Synchronous Compensator (STATCOM) in the power system in the Kurdistan Region for all weak buses. Power System Simulation studied it for Engineers (PSS\E) software version 33.0 to apply the Newton-Raphson (NR) method. All bus voltages were recorded and compared with the Kurdistan region grid index (0.95≤V ≤1.05), simulating the power system and finding the optimal size and suitable location of Static Synchronous Compensator (STATCOM)for bus voltage improvement at the weakest buses. It shows that Soran and New Koya substations are the best placement for adding STATCOM with the sizes 20 MVAR and 40 MVAR. After adding STATCOM with the sizes [20MVAR and 40MV

Plantation of humic acid nanoparticles on the inert sand through simple impregnation to obtain the permeable reactive barrier (PRB) for treating of groundwater contaminated with copper and cadmium ions. The humic acid was extracted from sewage sludge which is byproduct of the wastewater treatment plant; so, this considers an application of sustainable development. Batch tests signified that the coated sand by humic acid (CSHA) had removal efficiencies exceeded 98 % at contact time, sorbent dosage, and initial pH of 1 h, 0.25 g/50 mL and 7, respectively for 10 mg/L initial concentration and 200 rpm agitation speed. Results proved that physicosorption was the predominant mechanism for metals-CSHA interaction because the sorption data followed

Polycystic ovary syndrome (PCOS) is the main cause of female infertility. The role of insulin resistance in the development of polycystic ovary is actively discussed here. The study included patients with PCOS without insulin resistance (n = 48) and with insulin resistance (n = 39). The comparison groups were patients with no history of PCOS: a control group without insulin resistance (n = 46) and a group of patients with insulin resistance (n = 45). The following parameters were determined in patients: FSH, LH, TSH, T3_f, T4_f, PRL, E2, 17-OHd, Pr, AMH, Test total, Test_f, DHEAS, DHEAS_s, SHBG, ACTH, cortisol, IRI, IGF-1, C-peptide, and glucose level. The HOMA-IR index and the LH / FSH ratio and t

A robust and sensitive analytical method is presented for the extraction and determination of six pharmaceuticals in freshwater sediments.

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