The present study was conducted on sixty five pregnant women that infected with acute toxoplasmosis, serum samples were tested for detection specific anti-Toxoplasma gondii IgM using the rapid Toxo IgG/IgM Chromatographic immune assay test cassette and ELISA, and fifty healthy married women (not pregnant) as was considered as control group. The level of serum IL-6, IL-8, IL-12, TNF-α, TGF-β1, IP-10, MIP-1, MIG and ICAM were significantly increased (P <0.005) in pregnant patients infected with acute toxoplasmosis, while serum level of MCP-1(14.46 ± 1.38pg/ml) was not significantly increased when compared to controls(11.25 ± 0.24pg/ml) , these levels can be used as indicator to acute toxoplasmosis. Trace elements concentrations in serum were measured during infection also, the results of this study revealed that serum Zn was markedly elevated (p<0.05) and serum Cu was significantly decreased (P<0.001) in Toxoplasmosis-seropositive women as compared with control.
An effort is made to study the effect of composite nanocoating using aluminum-9%wt silicon alloys reinforced with different percentage (0.5,1,2,4)wt.% of carbon nanotubes (CNTs) using plasma spraying. The effect of this composite on corrosion behavior for AA6061-T6 by extrapolation Tafel test in sea water 3.5wt% NaCl was invested. Many specimens where prepared from AA6061-T6 by the dimension (15x15x3)mm as this first set up and other steps include coating process, X-ray diffraction and SEM examination .The results show the CNTs increase the corrosion rate of the nanocomposite coatings with increasing the weight percentage of CNTs within the Al-Si matrix. Al-9wt%Si coating layer itself has less corrosion rate if compared with both n
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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To accommodate utilities in buildings, different sizes of openings are provided in the web of reinforced concrete deep beams, which cause reductions in the beam strength and stiffness. This paper aims to investigate experimentally and numerically the effectiveness of using carbon fiber reinforced polymer (CFRP) strips, as a strengthening technique, to externally strengthen reinforced concrete continuous deep beams (RCCDBs) with large openings. The experimental work included testing three RCCDBs under five-point bending. A reference specimen was prepared without openings to explore the reductions in strength and stiffness after providing large openings. Openings were created symmetrically at the center of spans of the other specimens
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A simple, rapid, accurate and sensitive spectrophotometric method is proposed for the detennination of chlorprQm<tZine -HCl in pwe form and in pharmaceutical formulation. This method is based on the formation. of ion assodation complexes of dmg with either thymol
blue or bromophenol blue in an acidic buffer at pH values 4.17 and
3.68, respectively.
The ion-pair complexes formed exhibit absorption maxima at 41 Onm for both thymol blue and bromophenol blue. These complexes· are quantitatively extracted &n
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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In this study, nano TiO2 was prepared with titanium isopropoxide (TTIP) as a resource to titanium oxide. The catalyst was synthesized using phosphotungstic acid (PTA) and, stearyl trimethyl ammonium bromide (STAB) was used as the structure-directing material. Characterization of the product was done by the X-ray diffraction (XRD), X-ray fluorescent spectroscopy (XRF), nitrogen adsorption/desorption measurements, Atomic Force Microscope (AFM) and Fourier transform infrared (FTIR) spectra, were used to characterize the calcined TiO2 nanoparticles by STAB and PWA. The TiO2 nanomaterials were prepared in three crystalline forms (amorphous, anatase, anatase-rutile). The results showed that the
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Human health was and still the most important problem and objective of all most researches. Finding out what causes in the decadence of healthiness of Iraqi population is our tendency in the present work, Uranium causing cancer that is affected by a correlation between age and gender of bladder cancer patients is studied in the present work. Mean of Uranium concentration (Uc) decreased with increasing age for all age group without dependency on gender. While, there is a wide dispersion in Mean Uc excretion between males and females, due to the effect of correlated gender with age, where female Mean Uc is maximum at age 50-69 year (2.355 µg/L), and it's higher than male Mean Uc (2.022 µg/L) in this age stage because of menopause, a
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The main objective of this paper is to study the behavior of Non-Prismatic Reinforced Concrete (NPRC) beams with and without rectangular openings either when exposed to fire or not. The experimental program involves casting and testing 9 NPRC beams divided into 3 main groups. These groups were categorized according to heating temperature (ambient temperature, 400°C, and 700°C), with each group containing 3 NPRC beams (solid beams and beams with 6 and 8 trapezoidal openings). For beams with similar geometry, increasing the burning temperature results in their deterioration as reflected in their increasing mid-span deflection throughout the fire exposure period and their residual deflection after cooling. Meanwhile, the existing ope
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The main objective of this paper is to study the behavior of Non-Prismatic Reinforced Concrete (NPRC) beams with and without rectangular openings either when exposed to fire or not. The experimental program involves casting and testing 9 NPRC beams divided into 3 main groups. These groups were categorized according to heating temperature (ambient temperature, 400°C, and 700°C), with each group containing 3 NPRC beams (solid beams and beams with 6 and 8 trapezoidal openings). For beams with similar geometry, increasing the burning temperature results in their deterioration as reflected in their increasing mid-span deflection throughout the fire exposure period and their residual deflection after cooling. Meanwhile, the existing ope
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