In this work, the possibility to use new suggested carriers (D= Aspirin, Ibuprofen, Paracetamol, Tramal) is discussed for diclofenac drug (voltarine) by using quantum mechanics calculations. The calculation methods (PM3) and (DFT) have been used for determination the reaction path of (O-D) bond rupture energies. Different groups of drugs as a carrier for diclofenac prodrugs (in a vacuum) have been used; at their optimized geometries. The calculations included the geometrical structure and some of the physical properties, in addition to the toxicity, biological activity, and NLO properties of the prodrugs, investigated using HF method. The calculations were done by Gaussian 09 program. The comparison was made for total energies of reactan

This study designed to prepare ultrafine apixaban (APX) o/w nanoemulsion (NE) based gel with droplet size below 50 nm as a good method for transdermal APX delivery without using permeation enhancer, alternatively, the formulation components itself act as permeation enhancer. APX, a potent oral anticoagulant drug that selectively and directly inhibit coagulation factor Xa, was selected as a good candidate for transdermal delivery as it displays poor water solubility (0.028 mg/mL) and low bioavailability (50%). APX-NE gel was prepared using triacetin, triton-x-100 and carbitol as oil phase, surfactant and cosurfactant respectively, while Carbopol 940 used as a gelling agent. Ex vivo permeation of APX-NE gel through human stratum c

Credit risk assessment has become an important topic in financial risk administration. Fuzzy clustering analysis has been applied in credit scoring. Gustafson-Kessel (GK) algorithm has been utilised to cluster creditworthy customers as against non-creditworthy ones. A good clustering analysis implemented by good Initial Centres of clusters should be selected. To overcome this problem of Gustafson-Kessel (GK) algorithm, we proposed a modified version of Kohonen Network (KN) algorithm to select the initial centres. Utilising similar degree between points to get similarity density, and then by means of maximum density points selecting; the modified Kohonen Network method generate clustering initial centres to get more reasonable clustering res

نظرة عامة: تُعرَّف المادة أو العامل الذي يمكن أن يؤثر على الحمض النووي أو الكروموسومات على أنه سم جيني. قد يؤدي تلف الحمض النووي في الخلية الجسدية إلى حدوث طفرة جسدية ، والتي قد تحفز التحول الخبيث ، في حين أن الضرر الذي يلحق بالخلية الجرثومية قد يؤدي إلى تغيير خاصية وراثية (طفرة في السلالة الجرثومية) (سرطان). أحد الأحماض الدهنية الأحادية غير المشبعة الأحادية غير الأساسية هو حمض البالميتوليك. بعد حمض الأوليك

A steel-concrete composite structure (1) is described. The steel-concrete composite structure comprises a steel member (2) having an upper surface (5) and a plurality of shear connector elements (6) upstanding from the upper surface and a concrete slab (4) having upper and lower surfaces (7, 8). The slab is supported on its lower surface by the upper surface of the steel member. The slab comprises a plurality of through holes (9) between the upper and lower surfaces, each through hole tapering towards the lower surface so as to form an inverted frustally-shaped seating surface (10). The concrete slab is configured and positioned with respect to the steel member such that at least one shear connector element projects into each through hole.

Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

The Mauddud reservoir, Khabaz oil field which is considered one of the main carbonate reservoirs in the north of Iraq. Recognizing carbonate reservoirs represents challenges to engineers because reservoirs almost tend to be tight and overall heterogeneous. The current study concerns with geological modeling of the reservoir is an oil-bearing with the original gas cap. The geological model is establishing for the reservoir by identifying the facies and evaluating the petrophysical properties of this complex reservoir, and calculate the amount of hydrocarbon. When completed the processing of data by IP interactive petrophysics software, and the permeability of a reservoir was calculated using the concept of hydraulic units then, there

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

In present work the effort has been put in finding the most suitable color model for the application of information hiding in color images. We test the most commonly used color models; RGB, YIQ, YUV, YCbCr1 and YCbCr2. The same procedures of embedding, detection and evaluation were applied to find which color model is most appropriate for information hiding. The new in this work, we take into consideration the value of errors that generated during transformations among color models. The results show YUV and YIQ color models are the best for information hiding in color images.