Beta-lactam medications are among the commonly used antibiotics. These drugs kill germs by disrupting cell wall formation. This drug treats bacterial infections in numerous body sections. A new, quick, high-performance liquid chromatography approach has been developed and verified by the FDA and EMA for the simultaneous estimation of drugs in their medicinal and pure forms. This study deals with the determination of beta-lactam drugs (Amoxicillin, Ampicillin, Cephalexin, Cefotaxime, Cefoxitin, Cefamandole, Cephalothin, Piperacillin, Penicillin, Oxacillin, Cloxacillin, Nafcillin, Carbenicillin, Mezlocillin, Dicloxacillin) by a Reversed-Phase High-Performance Liquid Chromatography (RP-HPLC) technique based on an UV detector using a

In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably

Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp

Electrical Discharge Machining (EDM) is a non-traditional cutting technique for metals removing which is relied upon the basic fact that negligible tool force is produced during the machining process. Also, electrical discharge machining is used in manufacturing very hard materials that are electrically conductive. Regarding the electrical discharge machining procedure, the most significant factor of the cutting parameter is the surface roughness (Ra). Conventional try and error method is time consuming as well as high cost. The purpose of the present research is to develop a mathematical model using response graph modeling (RGM). The impact of various parameters such as (current, pulsation on time and pulsation off time) are studied on

The aim of the research is to measure the change in the impact of the factors of the Corona pandemic on psychological sensitivity and COVID-19 phobia in a sample of Bisha University students and to detect the differences in the phobia (phobia) Covid-19 among the sample members in the measurement before the ban and after the ban was opened, in addition to the differences in psychological sensitivity of  The sample has between sizes before and after the spread of the Corona pandemic, as well as the differences in them according to the gender variable (male, female). The researcher relied on the comparative approach. The scale of psychological sensitivity and COVID-19 phobia was applied to a sample of (62) male and female respondents.

The beginning of COVID-19 in Wuhan, China in late December 2019 and its worldwide transmission has led the World Health Organization to formally address the pandemic. The pandemic has imposed influential impacts on different environmental, economic, social, health, and living aspects. Publishing in scholastic journals was not immune from these impacts.

This study aims to analyze the messages of a number of global news outlets on Twitter. In order to clarify the news outlets tactics of reporting, the subjects and focus during the crisis related to the spread of the Covid-19 virus. The study sample was chosen in a deliberate manner to provide descriptive results. Three news sites were selected: two of the most followed, professional and famous international news sites: New York Times and the Guardian, and one Arab news site: Al-Arabiya channel.

A total of 18,085 tweets were analyzed for the three accounts during the period from (1/3/2020) to (8/4/2020). A content analysis form was used to analyze the content of the news coverage.   The results indicate an increase in th

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