Obesity is a risk factor associated with age-related disorders that accelerate aging, and it increases the risk of metabolic diseases. Therefore, this study was conducted to investigate the association of leukocyte telomere length (LTL) with the presence of higher body weight in middle-aged females and males. The study subjects comprised 160 (80 control and 80 higher body mass index BMI groups) with ranging ages of 30-50 years included and stratified for BMI. The physio-biochemical analysis was measured using enzymatic determination. Mean telomere length was determined by using the southern blotting technique. The association analysis revealed a significant variance (P < 0.01) in biochemical parameters between higher BMI grou

Obesity-related deaths continue to rise, and thus losing weight in overweight and obese patients is critical to prevent complications. Anredera cordifolia (Ten,) Steenis, species of succulent plant of the genus Basellaceae, is widely used in herbal medicine to decrease body weight. This study evaluated the potential benefits of Anredera cordifolia ethanol extract to reduce body weight in high-fat diet-induced obesity rat model. This was an experimental with post-test only control group design study involving 36 obese rats. They were divided into two groups: three control groups (K1, K2, K3) and three treatment groups (P1, P2, P3). All the groups were induced with high-fat diet, except K1 control group that received a standard di

Abstract  Liver cancer with hepatocellular carcinoma a serious clinical illness that progresses quickly and has a bad prognosis because to increased malignancy. Fibrosis is the precursor of liver cancer, which progresses to cirrhosis and carcinoma Diethylnitrosamine (DEN) is a chemical molecule that has been used as a carcinogenic agent to promote cancer in test animals because of its strong carcinogenic potential. Herbal plants have long been used as inexpensive, effective alternatives to pharmaceuticals in various liver-associated complications, since they contain many bioactive compounds useful in liver disorders. Hibiscus tiliaceus L. (Malvaceae) contain various phytochemicals in the plant extracts such as Flavonoids, phe

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

A novel technique Sumudu transform Adomian decomposition method (STADM), is employed to handle some kinds of nonlinear time-fractional equations. We demonstrate that this method finds the solution without discretization or restrictive assumptions. This method is efficient, simple to implement, and produces good results. The fractional derivative is described in the Caputo sense. The solutions are obtained using STADM, and the results show that the suggested technique is valid and applicable and provides a more refined convergent series solution. The MATLAB software carried out all the computations and graphics. Moreover, a graphical representation was made for the solution of some examples. For integer and fractional order problems, solutio

The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. As the standard DE algorithm is a fixed length optimizer, it is not suitable for solving signal de-noising problems that call for variability. A modified crossover scheme called rand-length crossover was designed to fit the proposed variable-length DE, and the new DE algorithm is referred to as the random variable-length crossover differential evolution (rvlx-DE) algorithm. The measurement results demonstrate a highly efficient capability for target detection in terms of frequency response and peak forming that was isola

A new Azo‐Schiff base ligand L was prepared by reaction of m‐hydroxy benzoic acid with (Schiff base B) of 3‐[2‐(1H–indol‐3‐yl)‐ethylimino]‐1.5‐dimethyl‐2‐phenyl‐2,3‐dihydro‐1H‐pyrazol‐4‐ylamine. This synthesized ligand was used for complexation with different metal ions like Ni(II), Co(II), Pd(II) and Pt(IV) by using a molar ratio of ligand: metal as 1:1. Resulted compounds were characterized by NMR (¹H and ¹³C), UV–vis spectroscopy, TGA, FT‐IR, MS, elemental analysis, magnetic moment and molar conductivity studies. The activation thermodynamic parameters, such as ΔE*, ΔH^*, ΔS^*, ΔG^*and

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

The synthesis of new benzodiazepine, imidazole, isatin, maleimide, pyrimidine and 1,2,4-triazole derived from 2-amino-4-hydroxy-1,3,5-triazine, via its cyclocondensation reaction with different organic reagents, is described. FT-IR, 1H-NMR and as well as 13C-NMR spectra disclosed the structures of the precursors and heterocyclic derivatives formed.

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve