Many people take protein supplements in an effort to gain muscle. However, there is some controversy as to whether this is really effective. There is evidence suggesting that consuming high level s of protein may in fact have negative side effects for health. The current study included 29 young Iraqi building muscles in two different groups (taken and not protein supplements) (age range=17-31 years), the cases were selected from family, friends, college students, and Gyms), from November 2014 to March 2015. A careful history was obtained from each volunteer including age, duration of sports, type of supplements, and family history of diseases. Some biochemical parameters like (glucose, urea, uric acid, creatinine, bilirubin, serum protein, serum albumin, triglyceride and alanine aminotransferase (ALT), as well as thyroid hormones (TSH, T3, and T4)) were estimated in the sera of the groups under study. The results indicated non- significant differences in the studied parameters in both groups (taken and not protein supplements), and significant differences in the body mass of young men building muscles that taken protein supplements from different origins (USA, Malaysia, Swiss, UK) when compared with the group that not taken any supplements.
The current study deals with the performance of constructed wetland (CW) incorporating a microbial fuel cell (MFC) for wastewater treatment and electricity generation. The whole unit is referred to as CW-MFC. This technique involves two treatments; the first is an aerobic treatment which occurs in the upper layer of the system (cathode section) and the second is anaerobic biological treatment in the lower layer of the system (anode section). Two types of electrode material were tested; stainless steel and graphite. Three configurations for electrodes arrangement CW-MFC were used. In the first unit of CW-MFC, the anode was graphite plate (GPa) and cathode was also graphite plate (GPc), in the second CW-MFC unit, the anode was stainless st
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The aim of this paper is adopted to give an approximate solution for advection dispersion equation of time fractional order derivative by using the Chebyshev wavelets-Galerkin Method . The Chebyshev wavelet and Galerkin method properties are presented. This technique is used to convert the problem into the solution of linear algebraic equations. The fractional derivatives are described based on the Caputo sense. Illustrative examples are included to demonstrate the validity and applicability of the proposed technique.
Background: Cystinosis is a rare autosomal recessive lysosomal storage disease with high morbidity and mortality. It is caused by mutations in the CTNS gene that encodes the cystine transporter, cystinosin, which leads to lysosomal cystine accumulation. It is the major cause of inherited Fanconi syndrome, and should be suspected in young children with failure to thrive and signs of renal proximal tubular damage. The diagnosis can be missed in infants, because not all signs of renal Fanconi syndrome are present during the first months of life. Elevated white blood cell cystine content is the cornerstone of the diagnosis. Since chitotriosidase (CHIT1 or chitinase-1) is mainly produced by activated macrophages both in normal and inflammator
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The present study utilised date palm fibre (DPF) waste residues to adsorb Congo red (CR) dye from aqueous solutions. The features of the adsorbent, such as its surface shape, pore size, and chemical properties, were assessed with X-ray diffraction (XRD), BET, Fourier-transform infrared (FTIR), X-ray fluorescence (XRF), and field emission scanning electron microscope (FESEM). The current study employed the batch system to investigate the ideal pH to adsorb the CR dye and found that acidic pH decolourised the dye best. Extending the dye-DPF waste mixing period at 25°C reportedly removed more dye. Consequently, the influence of the starting dye and DPF waste quantity on dye removal was explored in this study. At 5 g/L dye concentration, 48% d
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de
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Conditional logistic regression is often used to study the relationship between event outcomes and specific prognostic factors in order to application of logistic regression and utilizing its predictive capabilities into environmental studies. This research seeks to demonstrate a novel approach of implementing conditional logistic regression in environmental research through inference methods predicated on longitudinal data. Thus, statistical analysis of longitudinal data requires methods that can properly take into account the interdependence within-subjects for the response measurements. If this correlation ignored then inferences such as statistical tests and confidence intervals can be invalid largely.
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Separation of Trigonelline, the major alkaloid in fenugreek seeds, is difficult because the extract of these seeds usually contains Trigonelline, choline, mucilage, and steroidal saponins, in addition to some other substances. This study amis to isolate the quaternary ammonium alkaloid (Trigonelline) and choline from fenugreek seeds (Trigonella-foenum graecum L.) which have similar physiochemical properties by modifying of the classical method. Seeds were defatted and then extracted with methanol. The presence of alkaloids was detected by using Mayer's and Dragendorff's reagents. In this work, trigonilline was isolated with traces of choline by subsequent processes of purification using analytical and preparative TLC techniques.
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The logistic regression model regarded as the important regression Models ,where of the most interesting subjects in recent studies due to taking character more advanced in the process of statistical analysis .
The ordinary estimating methods is failed in dealing with data that consist of the presence of outlier values and hence on the absence of such that have undesirable effect on the result. &nbs
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