The expression of MUC5AC has been associated with the loss of the differentiation, TNM system, and nodal metastasis, in many cancers including gastric carcinoma (GC).Objective: To evaluate whether the MUC5AC could be used as a predictor in patients with GC and to assess the correlation between the expression of MUC5AC& the clinicpathological parameters as age, sex, histopathological subtypes, grade and stage of the tumor. This is a retrospective study conducted on 60 randomly selected patients (30 normal vs 30 GC), at the Pathology Department of the Gastroenterology and Hepatology Teaching Hospital&some private laboratories. They were collected and diagnosed during the period 2014-2018. Histological sections were stained with H&E and IHC st

During the last few years, the greener additives prepared from bio-raw materials with low-cost and multifunctional applications have attracted considerable attention in the field of lubricant industry. In the present work, copolymers derived from sunflower and linseed oils with decyl methacrylate were synthesized by a thermal method using benzoyl peroxide (BPO) as a radical initiator. Direct polymerization of fatty acid double bonds in the presence of a free radical initiator results in the development of environmentally friendly copolymeric additives (Co-1 and Co-2). Fourier Transform Infrared (FTIR) and Proton Nuclear Magnetic Resonance (1H-NMR) were used to characterize the resulting copolymers. Thermal decomposition of copolymers was de

Objective Thalassemic patients present with multiple immune abnormalities that may predispose them to oral Candida, however this has not been investigated. The aim of this study was to assess oral candidal colonization in a group of patients with β-thalassemia major both qualitatively and quantitatively. Study design The oral mycologic flora of 50 β-thalassemia major patients and 50 age- and sex-matched control subjects was assessed using the concentrated oral rinse technique. Candida species were identified using the germ tube test and the Vitek yeast identification system. Results Oral Candida was isolated from 37 patients (74%) and 28 healthy subjects (56%; P = .04). The mean candidal count was significantly higher in thalassemic patie

In this work, an inventive photovoltaic evaporative cooling (PV/EC) hybrid system was constructed and experimentally investigated. The PV/EC hybrid system has the prosperous advantage of producing electrical energy and cooling the PV panel besides providing cooled-humid air. Two cooling techniques were utilized: backside evaporative cooling (case #1) and combined backside evaporative cooling with a front-side water spray technique (case #2). The water spraying on the front side of the PV panel is intermittent to minimize water and power consumption depending on the PV panel temperature. In addition, two pad thicknesses of 5 cm and 10 cm were investigated at three different water flow rates of 1, 2, and 3 lpm. In Case #1,

The solution casting method was used to prepare a polyvinylpyrrolidone (PVP)/Multi-walled carbon nanotubes (MWCNTs) nanocomposite with Graphene (Gr). Field Effect Scanning Electron Microscope (FESEM) and Fourier Transformer Infrared (FTIR) were used to characterize the surface morphology and optical properties of samples. FESEM images revealed a uniform distribution of graphene within the PVP-MWCNT nanocomposite. The FTIR spectra confirmed the nanocomposite information is successful with apperaring the presence of primary distinct peaks belonging to vibration groups that describe the prepared samples.. Furthermore, found that the DC electrical conductivity of the prepared nanocomposites increases with increasing MWCNT concentratio

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class