Background: Oral Lichen planus (OLP) is a T-cell mediated chronic inflammatory oral mucosal disease of unknown etiology. Recent studies have reported an increased oxidative stress and lipid peroxidation in such patients. This suggests that reactive oxygen species may have a role in the pathogenesis of lichen planus. Oxidative stress in OLP release molecules consisting of granzymes resulting in local tissue damage in the effectors. Antioxidants that can defend against oxidative stress in the body cells include enzymes, as well as non- enzymatic antioxidants, such as melatonin, uric acid, vitamin A and E. Purpose: To study the level of salivary vitamin E and uric acid as antioxidant agents in patients with OLP and compared with healthy con

The reaction of methyldopa with o-vanillin in refluxing ethanol afforded Schiff base and characterized through physical analysis with a number of spectra also the study of biological activity. The geometry of the Schiff base was identified through using (C.H.N) analysis, Mass, 1H-NMR, FT-IR, UV-Vis spectroscopy. Metal complexes of Cr3+, Mn2+, Co2+, Ni2+, Cu2+, Zn2+, Cd2+ and Hg2+ with Schiff base have been prepared in the molar ratio 2:1 (Metal:L), (L = Schiff base ligand) except Hg2+ at molar ratio 1:1 (Hg:L). The prepared complexes were characterized by using Mass, FT-IR and UV-Vis spectral studies, on other than magnetic properties and flame atomic absorption, conductivity measurements. According to the results a dinuclear octahedral geo

In the image processing’s field and computer vision it’s important to represent the image by its information. Image information comes from the image’s features that extracted from it using feature detection/extraction techniques and features description. Features in computer vision define informative data. For human eye its perfect to extract information from raw image, but computer cannot recognize image information. This is why various feature extraction techniques have been presented and progressed rapidly. This paper presents a general overview of the feature extraction categories for image.

This work reports the development of an analytical method for the simultaneous analysis of three fluoroquinolones; ciprofloxacin (CIP), norfloxacin (NOR) and ofloxacin (OFL) in soil matrix. The proposed method was performed by using microwave-assisted extraction (MAE), solid-phase extraction (SPE) for samples purification, and finally the pre-concentrated samples were analyzed by HPLC detector. In this study, various organic solvents were tested to extract the test compounds, and the extraction performance was evaluated by testing various parameters including extraction solvent, solvent volume, extraction time, temperature and number of the extraction cycles. The current method showed a good linearity over the concentration ranging from

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