<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

The problem of Bi-level programming is to reduce or maximize the function of the target by having another target function within the constraints. This problem has received a great deal of attention in the programming community due to the proliferation of applications and the use of evolutionary algorithms in addressing this kind of problem. Two non-linear bi-level programming methods are used in this paper. The goal is to achieve the optimal solution through the simulation method using the Monte Carlo method using different small and large sample sizes. The research reached the Branch Bound algorithm was preferred in solving the problem of non-linear two-level programming this is because the results were better.

were prepared by condensation of 6-R-2amino bcnzothiazol with Salicyldehyde.These Schiff bases were found to reach with maleic anhydride and citraconic to give

The two parameters of Exponential-Rayleigh distribution were estimated using the maximum likelihood estimation method (MLE) for progressively censoring data. To find estimated values for these two scale parameters using real data for COVID-19 which was taken from the Iraqi Ministry of Health and Environment, AL-Karkh General Hospital. Then the Chi-square test was utilized to determine if the sample (data) corresponded with the Exponential-Rayleigh distribution (ER). Employing the nonlinear membership function (s-function) to find fuzzy numbers for these parameters estimators. Then utilizing the ranking function transforms the fuzzy numbers into crisp numbers. Finally, using mean square error (MSE) to compare the outcomes of the survival

Objective: The purpose of this study was to determine the association between caries related microorganisms in children’s saliva, such as Streptococcus mutans and lactobacilli, and their demographic factors. Methods: This study involved a sample of 135, both sexes with an age range between 3 and 10 years. Unstimulated saliva was obtained and diluted in normal saline. Saliva was then placed in selective media. Salivaris agar was used for mutans streptococci while Rogosa agar for lactobacilli. After incubation, Streptococcus mutans counting of CFU (colony forming units) with morphology characterization and numbers of CFU per milliliter of saliva for lactobacilli. Demographic factors information was collected using a questionnaire.

ZM Al-Bahrani, Medico Legal Update, 2021

Background: Toxoplasma gondiiis an obligate intracellular protozoan that may infect nearly all warm-blooded animals, including humans. T gondiiis thought to infect one-third of the human population.The symptoms depending on the adequacy of the immune antiparasitic response. In humans, the main source of infection is through contact with the feces of infected cats, the final host in which the T. gondii completes its life cycle. Other source of infection occurs when drinking raw milk, ingestion of contaminated meat. Aim: This descriptive study estimated the seroprevalence and risk variables for Toxoplasma gondii infection forundergraduate students of a college of Pharmacy who were studying at University of Baghdad. The frequency rate ofToxopl