Hormones, their receptors, and the associated signaling pathways make compelling drug targets because of their wide-ranging biological significance to study the role of asprosin in obese male patients with diabetic mellitus type II. ELISA method was used to assay asprosin and insulin. Blood was taken with drawn sample from 30 obese normal patients with age range (40-60) years, 30 diabetic patients with age range (40-60) years at duration of disease (1-5) years and 30 normal healthy patients. The mean difference between T2DM according to insulin % (23.8±0.6) was increased than the mean of IFG (17.7±1.0) (P 0.000). The mean difference between T2DM according to asprosin (122.1±21.8) was increased than the mean of IFG (51.4±2.7) (P 0.000).the mean differences between DM2 and IFG cases in different weight groups (Ob., Ow. and Nw) according to insulin was studied, the results showed that, there were significant differences in DM and IFG obese groups (G1 and G2) according to insulin (24.18±1.13, 15.56±0.66) P (0.00), however, there were significant differences between DM and IFG in Normal weight groups (G5 and G6) according to insulin (19.98±0.93, 11.12) P (0.00), while no significant differences between DM and IFG in Over weight groups (G3 and G4) according to insulin (27.22±0.34,28.56±1.59) P (0.42).The mean differences between diabetic mellitus type 2 and impaired fasting glucose cases in different weight groups (obese, over weight and normal weight) according to Asprosin were shown in Table (3), Figure (). The results showed that, there were significant differences between DM and IFG in obese groups (G1 and G2) according to Asprosin (307.42±8.4, 66.3±2.2) P (0.00), However, there were significant differences between DM and IFG in overweight groups (G3 and G4) according to Asprosin (28.3±0.5, 51.7±3.2) P (0.00) In addition to that, there were significant differences between DM and IFG in normal weight groups (G5 and G6) according to Asprosin (30.5±1.7, 21.2±1.6)
A thin film of AgInSe2 and Ag1-xCuxInSe2 as well as n-Ag1-xCuxInSe2 /p-Si heterojunction with different Cu ratios (0, 0.1, 0.2) has been successfully fabricated by thermal evaporation method as absorbent layer with thickness about 700 nm and ZnTe as window layer with thickness about 100 nm. We made a multi-layer of p-ZnTe/n-AgCuInSe2/p-Si structures, In the present work, the conversion efficiency (η) increased when added the Cu and when used p-ZnTe as a window layer (WL) the bandgap energy of the direct transition decreases from 1.75 eV (Cu=0.0) to 1.48 eV (Cu=0.2 nm) and the bandgap energy for ZnTe=2.35 eV. The measurements of the electrical properties for prepared films showed that the D.C electrical conductivity (σd.c) increase
... Show MoreBuilding numerical reservoir simulation model with a view to model actual case requires enormous amount of data and information. Such modeling and simulation processes normally require lengthy time and different sets of field data and experimental tests that are usually very expensive. In addition, the availability, quality and accessibility of all necessary data are very limited, especially for the green field. The degree of complexities of such modelling increases significantly especially in the case of heterogeneous nature typically inherited in unconventional reservoirs. In this perspective, this study focuses on exploring the possibility of simplifying the numerical simulation pr
The aim of this study is to develop a novel framework for managing risks in smart supply chains by enhancing business continuity and resilience against potential disruptions. This research addresses the growing uncertainty in supply chain environments, driven by both natural phenomena-such as pandemics and earthquakes—and human-induced events, including wars, political upheavals, and societal transformations. Recognizing that traditional risk management approaches are insufficient in such dynamic contexts, the study proposes an adaptive framework that integrates proactive and remedial measures for effective risk mitigation. A fuzzy risk matrix is employed to assess and analyze uncertainties, facilitating the identification of disr
... Show MoreThe introduction of Industry 4.0, to improve Internet of Things (IoT) standards, has sparked the creation of 5G, or highly sophisticated wireless networks. There are several barriers standing in the way of 5G green communication systems satisfying the expectations for faster networks, more user capacity, lower resource consumption, and cost‐effectiveness. 5G standards implementation would speed up data transmission and increase the reliability of connected devices for Industry 4.0 applications. The demand for intelligent healthcare systems has increased globally as a result of the introduction of the novel COVID‐19. Designing 5G communication systems presents research problems such as optimizing