Clean energy applications widely recognize Proton Exchange Membrane Fuel Cells (PEMFCs) for their high efficiency and environmental compatibility. Accurate parameter identification of PEMFC models is essential for enhancing system performance and reliability, particularly under dynamic operating conditions. This paper presents a novel optimization-based approach called Heterogeneous Comprehensive Learning-Bald Eagle Search (HCLBES) with enhanced exploration and exploitation capabilities for the effective modeling of PEMFC. The algorithm combines the exploration strength of the Bald Eagle Search with comprehensive learning and heterogeneity mechanisms to achieve a balanced global and local search space. In this algorithm, the number

A biostimulant is any microorganism or substance used to enhance the efficiency of nutrition, tolerance to abiotic stress and/or quality traits of crops, depending on its contents from nutrients. Plant biostimulants like honey bee (HB) and silymarin (Sm) are a strategic trend for managing stressed crops by promoting nutritional and hormonal balance, regulating osmotic protectors, antioxidants, and genetic potential, reflecting plant growth and productivity. We applied diluted honey bee (HB) and silymarin-enriched honey bee (HB- Sm) as foliar nourishment to investigate their improving influences on growth, yield, nutritional and hormonal balance, various osmoprotectant levels, different components of antioxidant system, and genetic p

Diabetic kidney disease (DKD) is caused by a variety of processes. As a result, one biomarker is insufficient to represent the complete process. This study Evaluate the diagnostic value of serum kidney injury molecule-1(KIM-1) and cystatin C (CysC) as early biochemical markers of DKD and predictive their sensitivities and specificities as biomarkers of nephropathy in Iraqi type 2 diabetic (T2DM) patients. This cross-sectional study include 161 T2DM patients from Diabetes and Endocrinology Center at Merjan medical city in Babylon. Patients divided according to urinary albumin creatinine ratio(ACR) (Group1:ACR≤30mg/g,Group2:ACR>30mg/g). Random spot urine and fasting blood samples were taken from each patient and urinary ACR, bloo

Background/Objectives: optimization of the therapeutic efficacy of antidiabetic agents is still a great challenge in the management of type 2 diabetes mellitus (T2DM), and attention is becoming more and more focused on the use of adjunctive agents that help target the drug action beyond the classic glycemic target. This study examined the effect of co-administration of an Artemisia herba-alba Asso (Asteraceae) aqueous extract on the glucose-lowering effect of dapagliflozin, a sodium–glucose cotransporter-2 (SGLT2) inhibitor. Methods: qualitative phytochemical screening and total phenolic and total flavonoid content were used to characterize the aqueous preparation. Male Wistar albino rats were divided into eight groups (10 rats ea

         تعد البيئة في يومنا المعاصر من الجوانب التي توليها المجتمعات البشرية اهمية كبرى لما لها من انعكاسات مباشرة وغير مباشرة على حياة الانسان ،وصحته، ومتطلبات حياته ،وأمنه، ومستقره في اي مكان في العالم تبرز مشكلة البحث ، في ان ما من سبيل صحيح لآعداد الاجيال القادمة إعدادا بيئيا ألا من خلال زيادة الوعي البيئي باستعمال كافة الوسائل التربوية المتخصصة، فالمعلومات ضرورية ولكنها لاتمنح

The current study aims to identify the introspective awareness of the study sample, as well as to identify the introspective awareness of the study sample in terms of gender. The researcher adopted the viewpoint of Mehling (2002) as a theoretical framework for Introspective awareness. A sample of (239) male students and (331) female students were chosen randomly from two universities (Baghdad University and Al- Mustansiriyah University). To achieve the objectives of the research, the researcher adopted a vulgar scale (Mehling, 2012), which in its final form consisted of (32) items distributed into eight domains. As for the reliability coefficient of the scale, it reached (0.896) in the Cronbach alpha equation. The study revealed that the

Channel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T