Toxoplasma gondii is an opportunistic parasite in immune-compromised persons. The prevalence of toxoplasmosis in psoriasis patients is investigated. In addition, the treatment effect on psoriasis patients infected with toxoplasmosis through evaluating Tumor Necrosis Factor-α (TNF-α) cytokine levels is studied. Blood samples were collected from 130 individuals who involved 60 control samples and 70 samples with psoriasis. They attended Medical City Hospital in Baghdad province from October 2017 - February 2018. Then, the anti- T. gondii antibodies (IgM and IgG) and TNF- α in the sera were determined via the enzyme linked immune-sorbent assay. The highe

Background: The aims of this study were to evaluate the effect of implant site preparation in low-density bone using osseodensification method in terms of implant stability changes during the osseous healing period and peri-implant bone density using CBCT. Material and methods: This prospective observational clinical study included 24 patients who received 46 dental implants that were installed in low-density bone using the osseodensification method. CBCT was used to measure the bone density pre- and postoperatively and implant stability was measured using Periotest® immediately after implant insertion and then after 6 weeks and 12 weeks postoperatively. The data were analyzed using paired t-test and the probability value <0.05 was conside

In this study, the electro-hydraulic servo system for speed control of fixed displacement hydraulic motor using proportional valve and (PID) controller is investigated theoretically ,experimentally and simulation . The theoretical part includes the derivation of the nonlinear mathematical model equation of (valve – motor ) combination system and the derivation of the transfer function for the complete hydraulic system , the stability test of the system during the operation through the transfer function using MATLAB package
V7.1 have been done. An experimental part includes design and built hydraulic test rig and simple PID controller .The best PID gains have been calculated experimentally and simulation, speed control performance te

Wellbore instability is one of the major issues observed throughout the drilling operation. Various wellbore instability issues may occur during drilling operations, including tight holes, borehole collapse, stuck pipe, and shale caving. Rock failure criteria are important in geomechanical analysis since they predict shear and tensile failures. A suitable failure criterion must match the rock failure, which a caliper log can detect to estimate the optimal mud weight. Lack of data makes certain wells' caliper logs unavailable. This makes it difficult to validate the performance of each failure criterion. This paper proposes an approach for predicting the breakout zones in the Nasiriyah oil field using an artificial neural network. It

Diacerein (DCN) is a semi-synthetic anthraquinone derivative of Rhein that is indicated for the management of osteoarthritis. Diacerein exhibits poor dissolution in the GIT fluids and suffers from low bioavailability upon oral administration in addition to the laxative effect of Rhein metabolites. The aim of the present study was to develop novasomal vesicles with optimized entrapment efficiency and size to serve as a carrier for transdermal delivery of diacerein. Novasomal vesicles were prepared by thin film hydration method thin film hydration. The prepared vesicles were optimized utilizing different surfactant to cholesterol molar ration, sonication type, different sonication times and varying fatty acid level. The prepared vesicles were

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi