A new efficient Two Derivative Runge-Kutta method (TDRK) of order five is developed for the numerical solution of the special first order ordinary differential equations (ODEs). The new method is derived using the property of First Same As Last (FSAL). We analyzed the stability of our method. The numerical results are presented to illustrate the efficiency of the new method in comparison with some well-known RK methods.

This study measures the indicators of social and environmental performance of the contents of the administration's prepared reports on its social and environmental performance by comparing the actual performance with the indicators set within the standards of the Global Reports Initiative (GRI), In preparing this research, the researchers relied on studying the criteria of the Global Reporting Initiative, which aims to achieve a high level of performance disclosure under sustainability, In light of contemporary global trends towards achieving sustainable development and its disclosure and the orientations of economic institutions and units in different countries towards emphasizing the extent of commitment during practicing its a

Arsenic is a prevalent and pervasive environmental contaminant with varied amounts in drinking water. Arsenic exposure causes cancer, cardiovascular, liver, nerve, and ophthalmic diseases. The current study aimed to find the best conditions for eliminating arsenic from simulated wastewater and their effect on biomarkers of hepatic in mice. Adsorption tests including pH, contact duration, Al-kheriat dosage, and arsenic concentrations were evaluated. Seventy-two healthy albino mice (male) were accidentally allocated into nine groups (n = 8), the first group was considered as healthy control, the second group (AL-Kheriat), and other groups received AL-Kheriat and arsenic 25, 50, 75, 100, 125, 150 and 175 mg/kg, respectively. Next 10 days, the

This study aimed to identify the extent of teachers' application of professional standards from the point of view of supervisors and detecting differences in the means of their estimates that may be attributed to the variables of the study (sex, number of years of service, educational qualification).The study adopted a descriptive approach. In order to achieve the aims of the study, a questionnaire including four areas, namely: (professional features, academic knowledge and pedagogy, teaching and learning, and professional development) was constructed.

The questionnaire was applied to a population which consisted of 60 supervisors of all school subjects in the Directorates of Education in

Support Vector Machines (SVMs) are supervised learning models used to examine data sets in order to classify or predict dependent variables. SVM is typically used for classification by determining the best hyperplane between two classes. However, working with huge datasets can lead to a number of problems, including time-consuming and inefficient solutions. This research updates the SVM by employing a stochastic gradient descent method. The new approach, the extended stochastic gradient descent SVM (ESGD-SVM), was tested on two simulation datasets. The proposed method was compared with other classification approaches such as logistic regression, naive model, K Nearest Neighbors and Random Forest. The results show that the ESGD-SVM has a

Background. Bone healing is a complex and dynamic process that represents a well-orchestrated series of biological events of cellular recruitment, proliferation, and differentiation. The use of medicinal plants in bone healing has attracted increasing interest because of their lower side effects. Punica granatum seed oil (PSO) contains high levels of phenolic compounds, promotes osteoblast function, and plays an important role in bone remodeling. A gelatin sponge (Spongostan) is a hemostatic agent that is extensively applied as scaffolds in engineering and as drug carriers in the medical field. This study aimed to evaluate the effectiveness of PSO for bone healing enhancement. Twenty adult male New Zealand rabbits, weighing an avera