A sensitivity-turbidimetric method at (0-180o) was used for detn. of mebeverine in drugs by two solar cell and six source with C.F.I.A.. The method was based on the formation of ion pair for the pinkish banana color precipitate by the reaction of Mebeverine hydrochloride with Phosphotungstic acid. Turbidity was measured via the reflection of incident light that collides on the surface particles of precipitated at 0-180o. All variables were optimized. The linearity ranged of Mebeverine hydrochloride was 0.05-12.5mmol.L-1, the L.D. (S/N= 3)(3SB) was 521.92 ng/sample depending on dilution for the minimum concentration , with correlation coefficient r = 0.9966while was R.S.D% < 1% of 2,6 mmol.L-1 conc. of Mebeverine hydrochloride. The method is used successfully for three different of target drugs in three different pharmaceutical formulations. A comparison using t-test was studied. It was shown that there is no significant difference between two values.
In this research, Haar wavelets method has been utilized to approximate a numerical solution for Linear state space systems. The solution technique is used Haar wavelet functions and Haar wavelet operational matrix with the operation to transform the state space system into a system of linear algebraic equations which can be resolved by MATLAB over an interval from 0 to . The exactness of the state variables can be enhanced by increasing the Haar wavelet resolution. The method has been applied for different examples and the simulation results have been illustrated in graphics and compared with the exact solution.
ان تصنيع رمال مطلية بأوكسيد الحديد من خلال ترسيب الجزيئات النانوية لذلك الاوكسيد على سطوح الرمال واستخدامها في الحاجز التفاعلي النفاذ لإزالة ايونات الكادميوم والنحاس من المياه الجوفية الملوثة الهدف الرئيسي للدراسة الحالية. تم توصيف بيانات الامتزاز نتيجة تفاعل المادة المازة مع المادة الممتزة قيد الدراسة بشكل جيد من خلال نموذج لانكمير والذي كان أفضل من نموذج فراندلش. لقد وجد ان اعلى قيم لقابلية الامتزاز با
... Show MoreThe logistic regression model is an important statistical model showing the relationship between the binary variable and the explanatory variables. The large number of explanations that are usually used to illustrate the response led to the emergence of the problem of linear multiplicity between the explanatory variables that make estimating the parameters of the model not accurate.
... Show MoreIn this study, silver nanoparticles (AgNPs) were synthesized using a cold plasma technique and a plasma jet. They were then used to explore how photothermal treatment may be used to treat lung cancer (A549) and normal cells (REF) <i>in vitro</i>. The anti-proliferative activity of these nanoparticles was studied after A549 cells were treated with (AgNPs) at various concentrations (100%, 50%, or 25%) and exposure times (6 or 8 min) of laser after 1 h or 24 h from exposed AgNPs. The highest growth inhibition for cancer cells is (75%) at (AgNPs) concentration (100%) and the period of exposure to the laser is (8 min). Particle size for the prepared samples varied according to the diameter o
... Show MoreA new Schiff base, 2-N( 4- N,N – dimethyl benzyliden )5 – (p- methoxy phenyl) – 1,3,4- thiodiazol ,and their metal complexes Cu (Π) ,Ni (Π), Fe (III) , Pd (Π) , Pt (IV) , Zn(Π) ,V(IV) and Co (Π) , were synthesized. The prepared complexes were identified and their structural geometries were suggested by using flam atomic absorption technique , FT-IR and Uv-Vis spectroscopy, in addition to magnetic susceptibility and conductivity measurements. The study of the nature of the complexes formed in ethanol solution , following the mole ratio method , gave results which were compared successfully with those obtained from the isolated solid state studied. Structur
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreThe present work deals with five species of parasitic Hymenoptera belonging to Pteromalidae, Eupelmidae and Eurytornidae which have been reared from brachid beetles. A new species, Eurytoma irakensis is described and the species, Bruchocida orientalis Crawford is recorded for the first time from Iraq.
The use of Bayesian approach has the promise of features indicative of regression analysis model classification tree to take advantage of the above information by, and ensemble trees for explanatory variables are all together and at every stage on the other. In addition to obtaining the subsequent information at each node in the construction of these classification tree. Although bayesian estimates is generally accurate, but it seems that the logistic model is still a good competitor in the field of binary responses through its flexibility and mathematical representation. So is the use of three research methods data processing is carried out, namely: logistic model, and model classification regression tree, and bayesian regression tree mode
... Show MoreThe proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.
In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete
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