Diabetes mellitus is a metabolic disorder categorized hyperglycemia resulting from defects in insulin secretion, insulin action or both. Protein tyrosine kinase (PTK) is an enzyme that catalyzes the transfer of phosphate groups from ATP to the tyrosine residues of many important proteins resulting in proteins phosphorylation. The aim of current study was to evaluate serum levels of protein tyrosine kinase enzyme and thyroid hormone (T3, T4and TSH) and to find the correlation between them in type 2 diabetes mellitus and diabetic nephropathy Iraqi patients. Methods: This study was conducted at The National Diabetes Center, Al-Mustansiriya University, Baghdad, Iraq and included 150 patients divided into three groups the first group included 50

         Long-term use of sulfonylureas including chlorpropamide, is known to potentiate the antidiuretic action of arginine vasopressin (AVP), predisposing to hyponatremia.The present study was designed to evaluate the effect of long term use of glibenclamide on serum and urinary levels of sodium and potassium in Type 2 DM patients in Iraqi DM centers. Ninety eight patients with Type 2 DM who were maintained on different doses of glibenclamide for at least 1 year, attending the centre for Diabetes and Endocrinology in Al-Rusafa, Baghdad, were enrolled in the study, in addition to 15 normal healthy subjects. Patients were allocated into three groups according to the dose of glibenc

The aim of this study was to identify the effectiveness of using generative learning model in learning kinetic series on rings and horizontal bar in artistic gymnastics for men ,Also, the two groups were better in learning the two series of movements on the rings and horizontal bar . The experimental method was used to design two parallel groups with pretested and posttest .The sample included third graders at the College of Physical Education and Sports Sciences - University of Baghdad ,The third class (d) was chosen to represent the control group that applied the curriculum in the college, with (12) students per group. After conducting the tribal tests, the main experiment was carried out for (8) weeks at the rate of two units per week di

A reduced-order extended state observer (RESO) based a continuous sliding mode control (SMC) is proposed in this paper for the tracking problem of high order Brunovsky systems with the existence of external perturbations and system uncertainties. For this purpose, a composite control is constituted by two consecutive steps. First, the reduced-order ESO (RESO) technique is designed to estimate unknown system states and total disturbance without estimating an available state. Second, the continuous SMC law is designed based on the estimations supplied by the RESO estimator in order to govern the nominal system part. More importantly, the robustness performance is well achieved by compensating not only the lumped disturbance, but also its esti

    The research aimed at identifying the values of ball launch and ring entrance angle and relations among them as well as identifying the contribution of ball launch and angle variables in 3 point jump in basketball. The researchers hypothesized statistical relation between ball launch and entrance angle. They used the descriptive method on (10) basketball players best known for their 3 point jump shot. Each player is given (10) attempts and only attempts with a larger entrance angle in recorded. The results showed that the height of ball launch players an integral role in decreasing entrance angle as well as ball launch angle did not correlate with the entrance angle. Finally, ball launch variables have no effect or contribution on ba

The research aimed at identifying the values of ball launch and ring entrance angle and relations among them as well as identifying the contribution of ball launch and angle variables in 3 point jump in basketball. The researchers hypothesized statistical relation between ball launch and entrance angle. They used the descriptive method on (10) basketball players best known for their 3 point jump shot. Each player is given (10) attempts and only attempts with a larger entrance angle in recorded. The results showed that the height of ball launch players an integral role in decreasing entrance angle as well as ball launch angle did not correlate with the entrance angle. Finally, ball launch variables have no effect or contribution on ball entr

The calibration of a low-speed wind tunnel (LSWT) test section had been made in the present work. The tunnel was designed and constructed at the Aerodynamics Lab. in the Mechanical Engineering Department/University of Baghdad. The test section design speed is 70 m/s. Frictional loses and uniformity of the flow inside the test section had been tested and calibrated based on the British standards for flow inside ducts and conduits. Pitot-static tube, boundary layer Pitot tube were the main instruments which were used in the present work to measure the flow characteristics with emphasize on the velocity uniformity and boundary layer growth along the walls of the test section. It is found that the maximum calibrated velocity for empty test s

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

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