Toxoplasma gondii is an obligate intracellular protozoan parasite; it spreads via the circulatory system during infection and causes chronic infection in various organs. Toxoplasmosis affects nearly one third of people worldwide, especially immunocompromised people. This study aimed to determine the effect of toxoplasmosis on renal function in hemodialysis patients. Overall 300 patients referred to the Medical City, Al-Karama General Hospital, Baghdad, Iraq were enrolled from 2021 to 2022. All serum samples were tested for T. gondii immunoglobulins (IgG and IgM) antibodies, urea and creatinine levels. In patients undergoing hemodialysis, the results revealed a high positivity percentage for anti-Toxoplasma IgG. In hemodialysis patients infe

Cadmium sulfide photodetector was fabricated. The CdS nano
powder has been prepared by a chemical method and deposited as a
thin film on both silicon and porous p- type silicon substrates by spin
coating technique. Structural, morphological, optical and electrical
properties of the prepared CdS nano powder are studied. The X-ray
analysis shows that the obtained powder is CdS with predominantly
hexagonal phase. The Hall measurements show that the nano powder
is n-type with carrier concentration of about (-5.4×1010) cm-3. The
response time of fabricated detector was measured by illuminating
the sample with visible radiation and its value was 5.25 msec. The
specific detectivity of the fabricated det

Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in

The piled raft is a geotechnical composite construction consisting of three elements: piles, raft and soil.
In the design of piled rafts, the load shared between the piles and the raft, and the piles are used up to a
load level that can be of the same order of magnitude as the bearing capacity of a comparable single
pile or even greater. Therefore, the piled raft foundation allows reduction of settlements in a very
economic way as compared to traditional foundation concepts.
This paper presents experimental study to investigate the behavior of piled raft system in sandy
soil. A small scale “prototype” model was tested in a sand box with load applied to the system through
a compression machine. The settlement was

Face recognition is required in various applications, and major progress has been witnessed in this area. Many face recognition algorithms have been proposed thus far; however, achieving high recognition accuracy and low execution time remains a challenge. In this work, a new scheme for face recognition is presented using hybrid orthogonal polynomials to extract features. The embedded image kernel technique is used to decrease the complexity of feature extraction, then a support vector machine is adopted to classify these features. Moreover, a fast-overlapping block processing algorithm for feature extraction is used to reduce the computation time. Extensive evaluation of the proposed method was carried out on two different face ima

Hydrocarbon displacement at the pore scale is mainly controlled by the wetness properties of the porous media. Consequently, several techniques including nanofluid flooding were implemented to manipulate the wetting behavior of the pore space in oil reservoirs. This study thus focuses on monitoring the displacement of oil from artificial glass porous media, as a representative for sandstone reservoirs, before and after nanofluid flooding. Experiments were conducted at various temperatures (25 – 50° C), nanoparticles concentrations (0.001 – 0.05 wt% SiO2 NPs), salinity (0.1 – 2 wt% NaCl), and flooding time. Images were taken via a high-resolution microscopic camera and analyzed to investigate the displacement of the oil at dif

This paper focuses on the optimization of drilling parameters by utilizing “Taguchi method” to obtain the minimum surface roughness. Nine drilling experiments were performed on Al 5050 alloy using high speed steel twist drills. Three drilling parameters (feed rates, cutting speeds, and cutting tools) were used as control factors, and L9 (3³) “orthogonal array” was specified for the experimental trials. Signal to Noise (S/N) Ratio and “Analysis of Variance” (ANOVA) were utilized to set the optimum control factors which minimized the surface roughness. The results were tested with the aid of statistical software package MINITAB-17. After the experimental trails, the tool diameter was found as the most important facto

In this paper, the solar attraction effect on the Moon orbital elements had been studied. The solar attraction considered a third body perturbation. The initial values of the Moon orbital elements at 2015-1-21.5 which are used (semi major axis=380963.78 km, eccentricity =0.056o, Eular angles (Ω=30°, ω=40°, , i=18.4°). The Moon in a perigee of its orbit at the initial time. A program which designed, was used to calculate the Moon position ,velocity and orbital elements through the years (2015-2035). The position and velocity components of the Moon were calculated by solving the equation of Kepler for elliptical orbit using Newton Raphson's method for (1000) periods and hundred steps of time for each period. The results show a secular

The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm