In this study, titanium dioxide (TiO₂) nanoparticles incorporated with cement were synthesis by a simple casting method as a function concentration of TiO₂ (0.2, 0.4, 0.8, 1, and 2 wt%). The prepared samples were characterized using the technique of Field Emission Scanning Electron Microscope (FESEM) and UV-Visible spectrophotometer, which was used to measure the adsorption spectra. The observed photocatalytic efficiency of TiO₂ nanoparticles (NP) incorporated with cement was investigated by decomposing the dye methyl blue (MB) solution under sunlight irradiation. According to the slope, the value of the k constant at the best sample is 0.8wt%, k=0.8265 min^-1. FESEM image of the TiO₂

Oxidative stress markers are of important diagnostic parameters for many disorders including cholelithiasis. This present study has aimed to assess the state of oxidative stress in symptomatic radiographically confirmed (Cholelithiasis) patients by measuring two parameters used as oxidative stress parameters which are serum myeloperoxidase (MPO) and superoxide dismutase (SOD). This study was carried out on 100 patient diagnosed as (Cholelithiasis) patients with 30 age and sex matched healthy controls by measuring serum (MPO) and (SOD) by ELIZA technique .Results showed significantly decrease in antioxidant enzyme(SOD) and increase in serum level of (MPO) comparing with controls.

Keywords: Cholelithiasis , Oxidative stress

It is commonly known that Euler-Bernoulli’s thin beam theorem is not applicable whenever a nonlinear distribution of strain/stress occurs, such as in deep beams, or the stress distribution is discontinuous. In order to design the members experiencing such distorted stress regions, the Strut-and-Tie Model (STM) could be utilized. In this paper, experimental investigation of STM technique for three identical small-scale deep beams was conducted. The beams were simply supported and loaded statically with a concentrated load at the mid span of the beams. These deep beams had two symmetrical openings near the application point of loading. Both the deep beam, where the stress distribution cannot be assumed linear, and the ex

After harvesting, Alfalfa plant was washed, dried and ground to get fine powder used in treatment water. We used alfalfa plant with ethanol to made alcoholic extract and characterized it applying (GC-Mass, FTIR, UV) spectroscopy to determine active compounds. Alcoholic extract was used to prepare zinc nanoparticle. We characterized Zinc nanoparticles by using FTIR, UV, SEM, EDX Zeta potential and AFM. Zinc nanoparticle with Alfalfa extract and alfalfa powder was used to treat pollutant water with pesticides and negative ions by two methods, namely Batch and continuous processing. Batch process was used two times firstly, with Alfalfa plant to treat water affected by pesticides and negative ions, after 1h pesticides (glyphosate 44.76%, sulfo

Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

   A new nano-sized NiMo/TiO₂-γ-Al₂O₃ was prepared as a Hydrodesulphurization catalyst for Iraqi gas oil with sulfur content of 8980 ppm, supplied from Al-Dura Refinery. Sol-gel method was used to prepare TiO₂- γ-Al₂O₃ nano catalyst support with 64% TiO_2, 32% Al₂O₃, Ni-Mo/TiO-γ-Al₂O₃ catalyst was prepared under vacuum impregnation conditions to loading metals with percentage 3.8 wt.% and 14 wt.% for nickel and molybdenum respectively while the percentage for alumina, and titanium became 21.7, and 58.61 respectively. The synthesized TiO₂- γ-Al₂O₃ nanocomposites and Ni-Mo /TiO₂

It is becoming a public health issue to predict which expectant women will develop gestational diabetes mellitus (GDM). The goal of this case control research is to investigate the role of maternal oxidative stress levels in the first, second, and third trimesters, as well as other factors, in the development of gestational diabetes mellitus (GDM). Methods Between October and December 2021, 142 women participated in this research. The 101 GDM patients were split into three groups based on their gestation (T1, T2, and T3), and 41 healthy pregnant women were chosen as the comparison group. TAS and TOS levels of oxidative stress and XO were calculated using a Spectrophotometer for colorimetric techniques; fasting and random sugar levels, as