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

A series of batch demulsification runs were carried out to evaluate the final emulsified water content of emulsion samples after the exposure to microwave. An experimental study was conducted to evaluate the effects of a set of operating variables on the demulsification performance. Several microwave irradiation demulsification runs were carried out at different irradiation powers (700, 800, and 900 watt), using water-in-oil emulsion samples containing different water contents (20-80%, 30-70%, and 50-50%) and salt contents (10000, 20000, and 30000 ppm). It was found that the best separation efficiency was obtained at 900watt, 50% water content and 160 s of irradiation time. Experimental results showed that microwave radiation method can

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

Receipt date:12/7/2020 accepted date:24/1/2021 Publication date:31/12/2021

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The constant characteristic of international relations is the constant change due to political, economic and military developments in addition to technology, and this in turn has led to many transformations in the concept of power, its uses, and the elements that form power and its distribution, and according to those variables, the concept of power has shifted from hard to soft, up to smart powe

The aim of this study is to highlight on the concept of joint arrangements and projects in accordance with IFRS 11, in addition, the study also focuses on accounting standards and IFRSs which are relevant to this standard.  With a description of the legislative and accounting challenges in the Iraqi environment facing the application of IFRS 11, as well as studying the reality of accounting in such economic activity of companies operating in this sector.

In order to achieve the study objectives, the researcher conducted a comparative analysis between IFRS 11 (Joint Arrangements) and the Iraqi Unified Accounting System, In the second step, IFRS 11 is applied to the Basrah Gas Company's (research sampl

In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func