Background : The kidneys may be injured in abdominal trauma, both blunt & penetrating. Renal trauma may manifest in a dramatic fashion for both the patient and the clinician. Objectives: To evaluate the incidence, management, morbidity &mortality of renal injury in blunt & penetrating abdominal trauma.
Results:The majority o f patients were males (35= 77.8%), the rest were females (10= 22.2%). The average age was 37 years (range= 18-56 years). The most common grades were grade1, grade2 and grade3 (40=88.9%), while 5 patients (11.1%) were grades 4 and 5.The most common associated injuries were liver, spleen, small & large bowels and diaphragm. The mortality was 20% (9 patients). The most common cause of death was multip

in this paper, the current work was devoted to the manufacture of TiO2 nanoparticles doped with manganese,  synthesis by the sol-gel technique using a dip-conting device, for their hydrophilic properties and photocatalytic activity, and the products were characterized by X-ray diffraction, scanning electron microscopy, and Uv-Visible absorption, and the results  XRD showed an  phase Anatase  ,  and the results of the SEM Explained the shape of the morphology of the samples after the doping process compared with pure TiO2, and the results of a shift in light absorption from ultraviolet rays to visible light were evident. The results showed that the thin films have a high wettability   under visible rays

       This work demonstrates the synthesis and storage of molecular-imprinted polymers (MIP) at room temperature using bulk polymerisation of Metformin (Met) characterized by high sensitivity, low cost, and high stability. To ensure an acceptable adsorption capacity, the research employed 0.8:4:20 mmol ratios of template, monomer, and cross-linking agents for the polymerization. A functional monomer, 2-acrylamido-2-methyl-1-propane sulphonic acid C₇H₁₃NO₄S, was cross-linked with N,N-methylene bisacrylamide C₇H₁₀N₂O₂ to form Met-MIP, which could be characterized using a UV-VIS spectrophotometer at 236 nm, FT-IR spectroscopy, and scanning electron

Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

     The present study investigates the implementation of machine learning models on crop data to predict crop yield in Rajasthan state, India. The key objective of the study is to identify which machine learning model performs are better to provide the most accurate predictions. For this purpose, two machine learning models (decision tree and random forest regression) were implemented, and gradient boosting regression was used as an optimization algorithm. The result clarifies that using gradient boosting regression can reduce the yield prediction mean square error to 6%. Additionally, for the present data set, random forest regression performed better than other models. We reported the machine learning model's performance using Mea

Due to the importance of egg parasitoids inthe natural and biological control of economically important insects, including egg parasitoid Pseudoligositaba bylonica Viggiani on dubas bug, the spread of the parasitoid and population distribution of parasitoid, In order to estimate the role of parasitoid as one of the biological factors in decreasing population density of dubas bug on date palm. Some aspects of the life of parasitoids were also studied, including the role of insect parasitoids in organizing the population of their families, geographical distribution and hosts range of genus Pseudoligosita, seasonal presence of parasitoid Pseudoligositaba bylonica Viggiani (Hymenoptera: Trichogrammatidae) , life studies and percentages