Beta-lactam medications are among the commonly used antibiotics that share the presence of a beta-lactam ring in their chemical formation. A modern, rapid, highperformance liquid chromatography technique was advanced and validated according to FDA and EMA rules for the concurrent determination of medications in their pharmaceutical and pure forms This study deals with the determination of beta-lactam drugs )Amoxicillin, Ampicillin Cephalexin, Cefotaxime, Cefoxitin, Cefamandole, Cephalothin, Piperacillin, Penicillin, Oxacillin, Cloxacillin Nafcillin, Carbenicillin, Mezlocillin and Dicloxacillin) which is a RP-HPLC technique with an UV detector using a column NEUCLEODUR C-18 (4.0 mm × 100 mm, 5µm particle size), The heat of the chromatographic column was 30o C, and the mobile phase of acetonitrile and KH2 PO4 using a progression elution with a total separation time of 19.54 min, a flow rate of 1.3, and the wavelength was 220 nm. The concentration range was among (0.2–20 µg/ml) with coefficients of determination of 0.9994. Recoveries were 100.4 – 90.86%, the limit of detection (LOD) was 0.0069–0.0659 µg/ml and limit of quantitation (LOQ) was 0.0211–0.1997 µg/ml. The chromatography approach advanced in this study was applied to simultaneously identify drugs in medical dosage forms obtained from pharmacies.
Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu
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چکیدهی بحث
به نظر میآید که عالم هستی ، بر مسألهی « حرکت» استوار دارد ، و روح ، همیشه دنبال دگرگونی و تکامل و برتری میگردد. حرکت ، همهی چیزها در عالم إمکان را در بر میگیرد. حرکت در بنیادهای فکر مولانا جای مهمی دارد .اشعار مولانا مقدار زیادی از پویایی و حرکت برخوردارست، و از آنجایی که فعل ، عنصر تکانبخش جمله ، و کانون دلالت است ، ترجیح دادیم - علاوه بر دیگر عنا
... Show MoreThe reaction oisolated and characterized by elemental analysis (C,H,N) , 1H-NMR, mass spectra and Fourier transform (Ft-IR). The reaction of the (L-AZD) with: [VO(II), Cr(III), Mn(II), Co(II), Ni(II), Cu(II), Zn(II), Cd(II) and Hg(II)], has been investigated and was isolated as tri nuclear cluster and characterized by: Ft-IR, U. v- Visible, electrical conductivity, magnetic susceptibilities at 25 Co, atomic absorption and molar ratio. Spectroscopic evidence showed that the binding of metal ions were through azide and carbonyl moieties resulting in a six- coordinating metal ions in [Cr (III), Mn (II), Co (II) and Ni (II)]. The Vo (II), Cu (II), Zn (II), Cd (II) and Hg (II) were coordinated through azide group only forming square pyramidal
... Show MoreIn this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho
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