Gestational diabetes mellitus (GDM) is a complication of gestation that is characterized by impaired glucose tolerance with first recognition during gestation. It develops when ?- cell of pancreas fail to compensate the diminished insulin sensitivity during gestation. This study aims to investigate the relationship between mother adiponectin level and ?- cell dysfunction with development gestational diabetes mellitus (GDM) and other parameters in the last trimester of pregnancy. This study includes (80) subjects ( pregnant women) in the third trimester of pregnancy, (40) healthy pregnant individuals as control group aged between (17 - 42) years and (40) gestational diabetes mellitus patients with aged between (20 - 42) years. The following biochemical investigation is studied: oral glucose tolerance test (OGTT), adiponectin , insulin, C-reactive protein (CRP),body mass index (BMI), and homeostasis model assessment- insulin resistance (HOMA – IR). The adiponectin levels are significantly lesser in females who develop GDM than the control group (P?0.01), while the insulin and OGTT concentrations were significantly higher in females with GDM than control group (P?0.01).The concentrations of CRP are non significantly different between the females who develop GDM and the control group.Conclusions: Lower adiponectin concentrations are associated with an increased risk of the development of gestational diabetes mellitus and females, who develop gestational diabetes mellitus, have higher levels of insulin resistance from normal females, Obesity is a shape of persistent low grade inflammation which causes elevated concentrations of C- reactive protein.
Nanomaterials enhance the performance of both asphalt binders and asphalt mixtures. They also improve asphalt durability, which reduces resource consumption and environmental impact in the long term associated with the production and transportation of asphalt materials. Thus, this paper studies the effectiveness of Nano Calcium Carbonate (Nano CaCO3) and Nano Hydrated Lime (NHL) as modifiers and examines their impact on ranges from 0% to 10% through comprehensive laboratory tests. Softening point, penetration, storage stability, viscosity, and mass loss due to short-term aging using the Rolling Thin Film Oven Test (RTFO) were performed on asphalt binders. Results indicated a significant improvement in binder stiffness, particularly
... Show MoreEmploying phase-change materials (PCM) is considered a very efficient and cost-effective option for addressing the mismatch between the energy supply and the demand. The high storage density, little temperature degradation, and ease of material processing register the PCM as a key candidate for the thermal energy storage system. However, the sluggish response rates during their melting and solidification processes limit their applications and consequently require the inclusion of heat transfer enhancers. This research aims to investigate the potential enhancement of circular fins on intensifying the PCM thermal response in a vertical triple-tube casing. Fin arrays of non-uniform dimensions and distinct distribution patterns were des
... Show MoreFilms of pure Poly (methyl methacrylate) (PMMA) doped by potassium iodide (KI) salt with percentages (1%) at different thickness prepared by casting method at room temperature. In order to study the effect of increasing thickness on optical properties, transmission and absorption spectra have been record for five different thicknesses(80,140,210,250,320)µm. The study has been extended to include the changes in the band gap energies, refractive index, extinction coefficient and absorption coefficient with thickness.
In order to understand the effect of (length of pile / diameter of pile) ratio on the load carrying capacity and settlement reduction behavior of piled raft resting on loose sand, laboratory model tests were conducted on small-scale models. The parameters studied were the effect of pile length and the number of piles. The load settlement behavior obtained from the tests has been validated by using 3-D finite element in ABAQUS program, was adopted to understand the load carrying response of piled raft and settlement reduction. The results of experimental work show that the increase in (Lp/dp) ratio led to increase in load carrying capacity by piled raft from (19.75 to 29.35%), (14.18 to 28.87%) and (0 to 16.49%) , the maximum load carr
... Show MorePetroleum is one of the most important substances consumed by man at present times, a major energy source in this century, petroleum oils can cause environmental pollution during various stages of production, transportation, refining and use, petroleum hydrocarbons pollutions ranging from soil, ground water to marine environment, become an inevitable problem in the modern life, current study focused on bioremediation process of hydrocarbons contaminants that remaining in the bottom of gas cylinders and discharged to the soil. Twenty-four bacterial isolates were isolated from contaminated soils all of them gram negative bacteria, bacterial isolates screening to investigate the ability of biodegradation of hydrocarbons, these isolates inocula
... Show Moreالوصف The synthesis of 2 (N-phenyl dithio carboxamid) benzothiazol Ligand (L) from reaction of 2-Mercaptobenzothiozol with phenylisothiocyanate using ratio 1: 1. The ligand was characterized by elemental analysis (CHN),'H-NMR, IR and UV-Vis. The complexes with bivalent ions (Ni, Cu, Zn, Cd and Hg) have been prepared and characterized. The structural diagnosis was established using IR, UV–Visible spectro photometer, molar conductivity, atomic absorption and molar ratio with selected metal ions (Ni2+, Cu2+). The complexes of (Ni, Cu) gave octahedral structural while the complexes of (Zn, Cd, Hg) gave tetrahedral structural. The study of biological activity of the ligand (L) and its complexes (Ni, Cu, Hg) in two deferent concentration (
... Show MoreData scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for