Diabetes mellitus caused by insulin resistance is prompted by obesity. Neuropeptide Nesfatin-1 was identified in several organs, including the central nervous system and pancreatic islet cells. Nesfatin-1 peptide appears to be involved in hypothalamic circuits that energy homeostasis and control food intake. Adiponectin is a plasma collagen-like protein produced by adipocytes that have been linked to the development of insulin resistance (IR), diabetes mellitus type 2 (DMT2), and cardiovascular disease (CVD). Resistin was first identified as an adipose tissue–specific hormone that was linked to obesity and diabetes. The aim of this study was to estimate the relationship between human serum nesfatin-1, adiponectin, resistin concentration, and obesity with T2DM. The results show a significant increase in serum neisfatin-1 and resistin levels in the obese diabetic group compared to the non-obese diabetic group. Adiponectin levels had a highly significant decrease in the obese diabetic group compared to the non-obese group and obese control group. Serum Nesfatin-1 and some variables, there was a significant positive correlation with (BMI, insulin, HOMA-IR), and serum resistin had a significant positive correlation with (BMI, WC, TG, insulin, HOMA-IR).On the other hand, there was a negative correlation between serum adiponectin and (BMI, TG, and HOMA-IR). The present results suggest that nesftin-1 may have a role in controlling food intake as well as the development of IR in obese patients.
A low-cost, RGB LED-based visible-light spectrophotometer was designed to measure dyes concentration. Dyes are widely used as indicators or coloring agents in different applications and knowing their concentration is an essential part for many studies. The proposed spectrophotometer provides many functionalities that clones the traditional expensive spectrophotometers for a budged price under $50. It was aimed to provide a versatile tool for instructors and educators to teach their students the fundamental concepts behind spectrophotometry. Malachite green, methyl red, and methyl orange dyes were chosen to be good samples to show the integrity of the proposed spectrophotometer in terms of accuracy, repeatability, and sensitivity as
... Show MoreMeasurements of Hall effect properties at different of annealing temperature have been made on polycrystalline Pb0.55S0.45 films were prepared at room temperature by thermal evaporation technique under high vacuum 4*10-5 torr . The thickness of the film was 2?m .The carrier concentration (n) was observed to decrease with increasing the annealing temperature. The Hall measurements showed that the charge carriers are electrons (i.e n-type conduction). From the observed dependence on the temperature, it is found that the Hall mobility (µH), drift velocity ( d) carrier life time ( ), mean free path (?) were increased with increasing annealing temperature
Abstract:
If we neglect the value of historical fashions as a source of inspiration for
contemporary fashion designers we will neglect a treasure of original designs.
In neglecting such a treasure how could we then know what is original. Today
the most famous fashion designers are often inspired, in the outwardly from
and internal lines of their fashions, by fashion designed during the ages of the
past.
Designers can find such fashions in books of history and museums. But
the historical ages are not equal in the fertility of the originality and novelty of
their fashions. Thus the contemporary designer may not find the old designs
inspiring so he invents them.
The researcher was keen in this paper to inclu
Mixed-effects conditional logistic regression is evidently more effective in the study of qualitative differences in longitudinal pollution data as well as their implications on heterogeneous subgroups. This study seeks that conditional logistic regression is a robust evaluation method for environmental studies, thru the analysis of environment pollution as a function of oil production and environmental factors. Consequently, it has been established theoretically that the primary objective of model selection in this research is to identify the candidate model that is optimal for the conditional design. The candidate model should achieve generalizability, goodness-of-fit, parsimony and establish equilibrium between bias and variab
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The apricot plant was washed, dried, and powdered after harvesting to produce a fine powder that was used in water treatment. created an alcoholic extract from the apricot plant using ethanol, which was then analysed using GC-MS, Fourier transform infrared spectroscopy, and ultraviolet-visible spectroscopy to identify the active components. Zinc nanoparticles were created using an alcoholic extract. FTIR, UV-Vis, SEM, EDX, and TEM are used to characterize zinc nanoparticles. Using a continuous processing procedure, zinc nanoparticles with apricot extract and powder were employed to clean polluted water. Firstly, 2 g of zinc nanoparticles were used with 20 ml of polluted water, and the results were Tetra 44% and Levo 32%; after
... Show MoreIn this study, investigations of structural properties of n-type porous silicon prepared by laser assisted-electrochemical etching were demonstrated. The Photo- electrochemical Etching technique, (PEC) was used to produce porous silicon for n-type with orientation of (111). X-ray diffraction studies showed distinct variations between the fresh silicon surface and the synthesized porous silicon surfaces. Atomic force microscopy (AFM) analysis was used to study the morphology of porous silicon layer. AFM results showed that root mean square (RMS) of roughness and the grain size of porous silicon decreased as etching current density increased. The chemical bonding and structure were investigated by using fourier transformation infrared spec
... Show MoreChannel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T
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