Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt

ABSTRACT Background: Diabetes and periodontitis are complicated prolonged disorders through a recognized two-way association. There is elongated-conventional mark that hyperglycaemia in diabetes is affected on immune-inflammatory response and disturb the action of osteoclast and in balance bone turnover, which might rise the person vulnerability to the progress of prolonged periodontitis. Osteocalcin is one of the greatest plentiful matrix proteins originate in bones and produced absolutely there. Small osteocalcin crumbles are noticed in regions of bone remodeling and are in fact degradation products of the bone matrix, that is released outside cells into the Gingival Crevicular Fluid (GCF) and saliva after destruction of periodontal tissu

This study focuses on producing wood-plastic composites using unsaturated polyester resin reinforced with Pistacia vera shell particles and wood industry waste powder. Composites with reinforcement ratios of 0%, 20%, 30%, and 40% were prepared and tested for thermal conductivity, impact strength, hardness, and compressive strength. The results revealed that thermal conductivity increases with reinforcement, while maintaining good thermal insulation, reaching a peak value of 0.633453 W/m·K. Hardness decreased with increased reinforcement, reaching a minimum nominal hardness value of 0.9479. Meanwhile, impact strength and compressive strength improved, with peak values of 14.103 k/m² and 57.3864568 MPa, respectively. The main aim is to manu

In this research work a composite material was prepared contains a matrix which is unsaturated polyester resin (UPE) reinforced with carbon nanotube the percentage weight (0.1, 0.2, 0.4.0.5) %, and Zn particle the percentage weight (0.1, 0.2,0.4,0.5)%.
All sample were prepared by hand lay-up, process the mechanical tests contains hardness test, wear rate test, and the coefficient of thermal conductivity. The results showed a significant improvement in the properties of overlapping, Article containing carbon nano-tubes and maicroparticles of zinc because of its articles of this characteristics of high quality properties led to an, an increase in the coefficient of the rmalconductivity, and increase the hardness values with increased pe

The present work involved four steps: First step include reaction of acrylamide ,N-?-Methylen-bis(acryl amide) and N-tert Butyl acryl amide with poly acryloyl chloride in the presence of triethyl amine (Et3N) as catalyst, the second step include homopolymerization of all products of the first step by using benzoyl peroxide(BPO) as initiator in (80-90)Co in the presence of Nitrogen gas(N2). In the third step the poly acrylimide which prepare in second step was convert into potassium salt by using alcoholic potassium hydroxide solution. Fourth step include Alkylation of the prepared polymeric salts in third step by react it with different alkyl halides(benzyl chloride, allylbromide , methyl iodide) by using DMF as solvent for(10-12) hours.

This research explores the concept of cruel optimism in the context of challenging patriarchal, cultural, and social traditions in Ayad Akhtar’s The Who and the What. Cruel optimism, a term coined by Lauren Berlant, refers to the paradoxical attachment to positive aspirations that may ultimately obstruct personal fulfillment and well-being. This study examines how individuals who resist patriarchal norms and entrenched cultural traditions often face significant emotional, psychological, and social challenges. Through a multidisciplinary approach, including literary analysis, sociological perspectives, and psychological insights, the research delves into the lived experiences of those who strive for autonomy, equality, and self-realization

Background: Oncogenesis in the oral cavity is widely believed to result from cumulative genetic alterations that cause a transformation of the mucosa from normal to dysplastic to invasive carcinoma. The p16 gene produces p16 protein, which in turn inhibits phosphorylation of retinoblastoma (Rb), p16 play a significant role in early carcinogenesis. A number of epidermal growth factor receptor (EGFR) family, HER2/neu, has received much attention because of its therapeutic implications. The aims of the study were to evaluate and compare the immunohistochemical expression of the cell cycle protein P16 INK4a and c-erbB2 (HER2/neu) in NOM, OED, and OSCC. Correlate both marker expression with each other as well as with various clinicopathological

The experiment was conducted to study the effect of leaves extract of Salvia sclarea , Rosmarinus officinalis and Thymus vulgaris with 10% and 30% concentration on germination of seeds and growth of seedlings . The effect of these extracts on infection percentage of seeds decay and surface growth of Rhizoctonia solani . The results showed that the three extracts effected significantly to reduced percentage of seeds germination, acceleration of germination , promoter indicator , infection percentage of seeds decay and surface growth of R. solani especially in 30% concentration .

Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne