The present study conducted on 120 males obese and 50 healthy males, their age
ranged from 20-50 years. The patients were divided into 3 groups based on Body
Mass Index (BMI) and Central Obesity (CO.); it has noticed that there is a
significant relation between both indexes. Effect of the obesity on the lipid profile
was investigated, the results showed that there is an elevated in TG, TC, LDL-C,
VLDL-C and lowered in HDL-C for all three obesity groups compare with control
group. Also, Significant differences (P≤0.05) revealed in TG, TC, LDL-C and
VLDL-C among three obesity groups and the greatest differences recorded in group
III obesity (279.52±1.10, 261.02±1.13, 169.32±1.81, and 55.08±1.33 mg/dl
respectively) followed by group II obesity (216.58±1.79, 228.20±1.28, 135.41±1.21
and 40.34±1.17 mg/dl respectively) and then group I obesity (152.00±1.81,
168.47±1.11, 104.33±1.99 and 27.90±1.46 mg/dl respectively). No significant
differences observed in HDL-C among groups I, II and III obesity (34.23±1.59,
36.65±1.78, 35.08±1.12 mg/dl respectively). The study included investigate for
serum GLP-1 enzyme levels, a lowered in GLP-1 levels was observed in groups I, II
and III obesity (39.33±1.31, 35.58±1.87, 35.56±1.66 pM respectively) compare with
control (62.50±1.50 pM). Besides having a highly significant correlation (P≤0.01)
between GLP-1 level and both indexes (BMI and CO.) in which an elevated in BMI
and CO. were correlated to an lowered in GLP-1 level.
This research aims to predict new COVID-19 cases in Bandung, Indonesia. The system implemented two types of deep learning methods to predict this. They were the recurrent neural networks (RNN) and long-short-term memory (LSTM) algorithms. The data used in this study were the numbers of confirmed COVID-19 cases in Bandung from March 2020 to December 2020. Pre-processing of the data was carried out, namely data splitting and scaling, to get optimal results. During model training, the hyperparameter tuning stage was carried out on the sequence length and the number of layers. The results showed that RNN gave a better performance. The test used the RMSE, MAE, and R2 evaluation methods, with the best numbers being 0.66975075, 0.470
... Show MoreIn this paper, we investigate two stress-strength models (Bounded and Series) in systems reliability based on Generalized Inverse Rayleigh distribution. To obtain some estimates of shrinkage estimators, Bayesian methods under informative and non-informative assumptions are used. For comparison of the presented methods, Monte Carlo simulations based on the Mean squared Error criteria are applied.
Nigella sativa has various pharmacological properties and has been used throughout history for a variety of reasons. However, there is limited data about the effects of N. sativa (NS) on human cancer cells. This study aimed at observing the roles of methanolic extract of N. sativa on apoptosis and autophagy pathway in the Human PC3 (prostate cancer) cell line. The cell viability was checked by MTT assay. Clonogenic assay was performed to demonstrate clonogenicity and Western blot was used to check caspase-3, TIGAR, p53, and LC3 protein expression. The results demonstrated that PC3 cell proliferation was inhibited, caspase-3 and p53 protein expression was induced, and LC3 protein expression was modulated. The clonogenic assay showed that PC3
... Show MoreThe current study investigated the stability and the extraction efficiency of emulsion liquid membrane (ELM) for Abamectin pesticide removal from aqueous solution. The stability was investigated in terms of droplet emulsion size distribution and emulsion breakage percent. The proposed ELM included a mixture of corn oil and kerosene (1:1) as a diluent, Span 80 (sorbitan monooleate) as a surfactant and hydrochloric acid (HCl) as a stripping agent without utilizing a carrier agent. Parameters such as homogenizer speed, surfactant concentration, emulsification time and internal to organic volume ratio (I/O) were evaluated. Results show that the lower droplet size of 0.9 µm and higher stable emulsion in terms of breakage percent of 1.12 % were
... Show MoreIn the presence of deep submicron noise, providing reliable and energy‐efficient network on‐chip operation is becoming a challenging objective. In this study, the authors propose a hybrid automatic repeat request (HARQ)‐based coding scheme that simultaneously reduces the crosstalk induced bus delay and provides multi‐bit error protection while achieving high‐energy savings. This is achieved by calculating two‐dimensional parities and duplicating all the bits, which provide single error correction and six errors detection. The error correction reduces the performance degradation caused by retransmissions, which when combined with voltage swing reduction, due to its high error detection, high‐energy savings are achieved. The res
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