Background: Diabetic neuropathy can affect any peripheral nerve, including sensory neurons, motor neurons, and the autonomic nervous system. Therefore, diabetic neuropathy has the potential to affect essentially any organ and can affect parts of the nervous system like the optic nerve, spinal cord, and brain. In addition, chronic hyperglycemia affects Schwann cells, and more severe patterns of diabetic neuropathy in humans involve demyelization. Schwann cell destruction might cause a number of changes in the axon. study aims to evaluate serum myelin protein level as a predicting marker in the diagnosis of diabetic neuropathy and to prevent early neuropathy complications of type 2 diabetes.

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Background Osteoarthritis is a chronic degenerative disorder with rising prevalence. Early detection of structural damage is difficult. Consequently, there is a pressing demand for reliable biomarkers that enable an earlier diagnosis of osteoarthritis. The aim is to investigate the level of serum fibulin-3 in patients with primary knee osteoarthritis and its correlation with disease severity. Subjects and methods A case–control study was conducted at the Baqubah Teaching Hospital from November 2023 to January 2024. One hundred twenty persons participated in this study (eighty females with the diagnosis of knee osteoarthritis in its early and late stages, and forty age-matched, apparently healthy control. Serum fibulin-3, ESR, CRP, and cal

The research deals with the important and modern two subjects, strategic leadership which have six demotions and knowledge management
(four demotions') . the gools & the research is to know the relation & the effect them in the oil ministry (project department) , the sample was (50) persons who works in the department the questionnaire was the tool of data gathering .

The research divided to four parties, the first  to the theotical review of the research variables, the second to the research methrology, the third to analysis and discoed the empirical results the last to the conclusions and recommendations .

This paper is concerned with pre-test single and double stage shrunken estimators for the mean (?) of normal distribution when a prior estimate (?0) of the actule value (?) is available, using specifying shrinkage weight factors ?(?) as well as pre-test region (R). Expressions for the Bias [B(?)], mean squared error [MSE(?)], Efficiency [EFF(?)] and Expected sample size [E(n/?)] of proposed estimators are derived. Numerical results and conclusions are drawn about selection different constants included in these expressions. Comparisons between suggested estimators, with respect to classical estimators in the sense of Bias and Relative Efficiency, are given. Furthermore, comparisons with the earlier existing works are drawn.

Allah, in his Holy Quran introduced great prophet stories so as to learn from. The greatness of these stories lies in Allah himself being the author. He portrays his characters, lays the plot, defines the tests and Al- Ibtilla, provides ways of being patient, using Duaa to end all hard tests and generously describing the greatness of his rewards to all those who are patient. The purpose of this research is to study selected English prophet stories for children on three levels, the stories ability to convey lessons and Islamic teachings to children who do not speak Arabic, the stories portray the Islamic concept of patience, the teaching and learning styles andstrategies that Allah uses with each prophet. The concept of patience is defined a

Optical fiber chemical sensor based surface Plasmon resonance for sensing and measuring the refractive index and concentration for Acetic acid is designed and implemented during this work. Optical grade plastic optical fibers with a diameter of 1000μm were used with a diameter core of 980μm and a cladding of 20μm, where the sensor is fabricated by a small part (10mm) of optical fiber in the middle is embedded in a resin block and then the polishing process is done, after that it is deposited with about (40nm) thickness of gold metal and the Acetic acid is placed on the sensing probe.

This paper introduces a novel nonparametric hybrid cyber-intelligence-based statistical process control and anomaly detection framework in time series data. It is developed to overcome the shortcomings of the classical control schemes in dealing with complex, abnormal, and noisy input data, especially when it is autocorrelated. The proposed methodology combines three technical pillars: First, it utilizes a bidirectional long-short-term memory architecture (Bi-LSTM) to capture long-term time dependency and learn nonlinear patterns, leaving only true deviations as residuals that remove trends and noises from the market. Second, it adopts the Golden Eagle Optimizer (GEO) algorithm for optimal parameter selection. This intelligent algor