Background: Normal thyroid function is essential for neonatal growth and brain development. In a newborn infant with severe disease, endocrine regulation of hormones can be affected by abnormal metabolism. The assessment of thyroid parameters results in the recognition of a dysfunction and its association with disease severity. Objective: This study aimed to assess thyroid function profiles in critically ill neonates in the neonatal intensive care unit (NICU) compared with healthy controls. Additionally, we aimed to detect the presence of TD and its possible association with critical illness. Methods: A case-control study was performed in 100 neonates, comprising 50 sick neonates and 50 healthy controls. We measured thyroid functio

A new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification

This study was conducted with the Iraqi Pin-tailed Sandgrouse (Pterocles alchata). For this purpose, five adult birds weighing between 195–250 g were dissected and the spleen was removed. The organs were placed in 0.9% normal saline and fixed in 10% formalin and then preserved in 70% alcohol. Histological sections were prepared using the paraffin wax method, which involves several steps: Dehydration, clarification and embedding. The present results show that the spleen is surrounded by a capsule of connective tissue containing collagen fibres and smooth muscle. A series of connective tissue trabeculae extend from this capsule and penetrate the parenchyma of the spleen. The parenchyma consists of two main regions: the white pulp an

Chromium (Cr), a first-series transition metal with a standard atomic mass of approximately 52 g/mol, plays a sophisticated role as an essential trace element in human and animal physiology. Characterized by its diverse oxidation states most notably the highly stable Cr3+ this micronutrient functions primarily as a biochemical potentiator of insulin action. Through the activation of the low-molecular-weight chromium-binding substance, chromodulin, chromium amplifies insulin receptor tyrosine kinase activity, thereby facilitating efficient glucose uptake and the metabolism of carbohydrates, proteins, and lipids. Beyond glycemic control, chromium serves as a critical modulator of lipid profiles, stimulating lipase activity to reduce very low-

Moisture-induced damage is one of the primary causes of premature distress in asphalt pavements, leading to reduced service life and increased maintenance costs. Although nanomaterials have shown potential in enhancing asphalt performance, the underlying composite interaction mechanisms among nanomaterials, asphalt binder, and aggregate phases under moisture exposure are still not fully understood. In addition, comparative evaluations under consistent experimental conditions remain limited. This study investigates the influence of five nanomaterials: nano-silica (NS), nano-alumina (NA), nano-titanium dioxide (NT), nano-zinc oxide (NZ), and carbon nanotubes (CNT) on the physical and mechanical properties of asphalt binders and mixtur

Psoriasis is a chronic autoimmune inflammatory skin condition characterized by uncontrolled keratinocyte proliferation and potential systemic manifestations. Its pathogenesis involves activation of both innate and adaptive immune responses, leading to an imbalance in inflammatory cytokines. Interleukin (IL)-12 and IL-23 are key cytokines in the pathophysiology of psoriasis and sustain chronic skin inflammation. Biologic therapies, such as ustekinumab (UST), have been developed to induce long-term remission in moderate-to-severe psoriasis. The objective of this study was to identify differences in serum levels of inflammatory biomarkers [erythrocyte sedimentation rate, high-sensitivity C-reactive protein (hs-CRP), IL-12, IL-17, IL-22, and IL

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

The main theme of this thesis could be divided into three objectives : The first is to define and classify integral equations with one and multiple delay, including Fredholm, Volterra and integro-differential equations (Retarded, Neutral and Mixed types). While the second and popular objective of this work is to study the inverse problems related to delay integral equations by using non-classical variational formulation method. Some examples are given for each of the discussed type of delay integral equations. Also, a study to the direct and inverse problems related to integral equations with multiple delay, also considered as a third objective. Several examples are given for each type of these equations. Finally, the suggested approach

Breast cancer is highlighted in recent research as one of the most prevalent types of cancer. Timely identification is essential for enhancing patient results and decreasing fatality rates. Utilizing computer-assisted detection and diagnosis early on may greatly improve the chances of recovery by accurately predicting outcomes and developing suitable treatment plans. Grading breast cancer properly, especially evaluating nuclear atypia, is difficult owing to faults and inconsistencies in slide preparation and the intricate nature of tissue patterns. This work explores the capability of deep learning to extract characteristics from histopathology photos of breast cancer. The research introduces a new method called SMOTE-based Convolut

Peripheral artery disease (PAD) is associated with increased oxidative stress and impaired endothelial function. Ticagrelor treatment improves antioxidant properties in addition to its antiplatelet effects. This study investigated the impact of Ticagrelor treatment on serum superoxide dismutase (SOD) levels and other biochemical parameters in PAD patients. It also evaluated the potential diagnostic accuracy and clinical utility of specific biomarkers based on receiver operating characteristic (ROC) analysis. Seventy individuals were categorized into healthy control (n=40), baseline PAD patients not on Ticagrelor (B-PAD, n=30), and same PAD patients after treated with Ticagrelor (A-PAD, n=30). Parameters measured included SOD concent