A simple analytical method was used in the present work for the simultaneous quantification of Ciprofloxacin and Isoniazid in pharmaceutical preparations. UV-Visible spectrophotometry has been applied to quantify these compounds in pure and mixture solutions using the first-order derivative method. The method depends on the first derivative spectrophotometry using zero-cross, peak to baseline, peak to peak and peak area measurements. Good linearity was shown in the concentration range of 2 to 24 µg∙mL-1 for Ciprofloxacin and 2 to 22 µg∙mL-1 for Isoniazid in the mixture, and the correlation coefficients were 0.9990 and 0.9989 respectively using peak area mode. The limits of detection (LOD) and limits of quantification (LOQ) were measured with first derivative method. The LOD and LOQ were found as 0.45 µg∙mL-1 and 1.50 µg∙mL-1 for Ciprofloxacin and 0.68 µg∙mL-1 and 2.28 µg∙mL-1 for Isoniazid, respectively. Accuracy and precision were determined by measuring the relative standard deviation and recoveries. The results also showed that the proposed method was successfully applied for direct analysis of ciprofloxacin and isoniazid in the tablet samples.
The levels of shooting in basketball not very good appears un healthy phenomenon for age stages especially youth players on Iraq and therefore there is lower level in skills especially shooting that seems the players represent their players not good levels which cause difficult in choosing players for youth national team. The research sample were youth teams in Baghdad for season 2012-2013 their birth 1996 and the number teams (7) and after getting results and treat it statically the important ones were : there is a large number of failure attempts on success ones in basic shooting in basketball for youth teams in Baghdad teams (2012-2013) season and basic shooting have effective participation (positive relation) in youth teams ranking in B
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The research aims to develop physical exercises with auxiliary training tools that work to develop the explosive power of the arms and legs, and then find out their effect on the accuracy of shooting from free throw and correction from jumping of advanced basketball players, as the researchers found a problem that these players have weakness in the skill of throwing Free throwing and shooting by jumping calculated with two points as a result of adopting unhealthy physical and technical positions, which led to a lack of focus and accuracy, and thus negatively affected the performance technique of free throw and jump shot, as most teams use traditional exercises without the use of auxiliary training tools, and this topic gave researchers the
... Show Moreيؤدي عرض معلومات مضللة او محرفة ضمن القوائم المالية والتي تعد أهم مصادر المعلومات الموثوقة التي يُعول عليها لاتخاذ القرارات السليمة الى عدم قدرتها على عكس نتيجة النشاط والمركز المالي لها او اعمال الوحدة الاقتصادية لتلك الفترات الزمنية بصورة صادقة وعادلة نتيجة لنوعية المعلومات المفصح عنها في القوائم المالية لذلك زاد الاهتمام بتطوير الممارسات المحاسبية لتتضمن افصاحات كافية بغرض اعطائهم صورة صادقة وعادلة
... Show MoreBackground: Toxoplasmosis is a very common infection caused by the obligate intracellular protozoan parasite. This parasite is called Toxoplasma gondii widely distributed around the world . Toxoplasma gondii can be vertically transmitted to the fetus during pregnancy and may cause wide range of clinical manifestations in the offspring.
Objective: To determine seroprevalence Immunoglobulin G (IgG) and Immunoglobulin M (IgM ) to toxoplasma gondii among pregnant women and to identify the risk factors.
Type of the study: A cross-sectional study.
Methods: A total of 110 blood samples of pregnant women were collected from
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Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod
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Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F
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Age, hypertension, and diabetes can cause significant alterations in arterial structure and function, including changes in lumen diameter (LD), intimal-medial thickness (IMT), flow velocities, and arterial compliance. These are also considered risk markers of atherosclerosis and cerebrovascular disease. A difference between right and left carotid artery blood flow and IMT has been reported by some researchers, and a difference in the incidence of nonlacunar stroke has been reported between the right and left brain hemispheres. The aim of this study was to determine whether there are differences between the right and left common carotid arteries and internal carotid arteries in patient
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