Two molecular imprinted polymer (MIP) membranes for Levofloxacin (LEV) were prepared based on PVC matrix. The imprinted polymers were prepared by polymerization of styrene (STY) as monomer, N,N methylene di acrylamide as a cross linker ,benzoyl peroxide (BPO) as an initiator and levofloxacin as a template. Di methyl adepate (DMA) and acetophenone (AOPH) were used as plasticizers , the molecular imprinted membranes and the non molecular imprinted membranes were prepared. The slopes and detection limits of the liquid electrodes ranged from -21.96 – -19.38 mV/decade and 2×10-4M- 4×10-4M, and Its response time was around 1 minute, respectively. The liquid electrodes were packed with 0.1 M standard drug solution and its response were stable at pH ranges from 1.0 to 11.0 and with good selectivity for more than several type. The electrodes produced have been successfully applied in preparation of the pharmaceutical sample for the determination of the analyte without any time consuming pretreatment steps.
Modern communication and media technology has pioneered new horizons and curried out deep changes in the various fields of social life, It effected enormously human communication as well.
Content one Who late the developments which have effected the social relations ،due to the new media ،especially Face book ,will certainly notice the far cry changes of the social relation net which has been effected ,in a way or another ،the accelerated development ،under the appearance of the so called the virtual society .
Face book has embodied the means – communication ,which has become an important turn point in the social communication .
It is the point the present paper tries to expose an discuss by a field study curried on a sam
The new complexes including Cu(II), Co(II), Ni(II), Pt(IV), and Pd(II) metals with 4,4'-(((1E,1'E)-1,4-phenylenebis(methaneylylidene))bis(azaneylylidene))bis(5-(4-chlorophenyl)-4H-1,2,4-triazole-3-thione) have been synthesized of utilizing us polystyrene (PS) photostability. The supplement (0,5 w / v%) was for the production of polystyrene ( PS) in the form of tetrahydrofuran (THF). Polystyrene films were exposing irradiation (250 – 380 nm) absorption light intensity of 6.02 x 10-9 ein dm-3 s-1 at room temperature, through the changes that occur to each of viscosity average molecular weight (Mv), main chain scission (S), degree of polymerization (DPn), weight loss %, hydroxyl index (lOH), carbonyl index (ICo) determined the photo stabiliz
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In this paper the research introduces a new definition of a fuzzy normed space then the related concepts such as fuzzy continuous, convergence of sequence of fuzzy points and Cauchy sequence of fuzzy points are discussed in details.
A number of ehemical ion materials were used as an absorber against solar energy. These materials were selected according to their absorption spectra in the wavelength range 300-800nm where the solar spectrum is coventrated. A solar olleetorw^esigd and The ability of each material inside the collector for absorbing the solar radiation was examined by a converter parameter “R”.According to the “R” parameter, the cohaltous and copperic ions material seems to be of higher capability for absorbing solar energy than the other materials.All the results were analyzed by means of a least-squared fitting program.
Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature
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This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength. This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.
Moreover, the proposed controller i
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Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 % 1.66 %. This
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