The research aims at clarifying the role of green human resource management practices in achieving sustainable development. The research problem is that the health sector is less concerned with environmental aspects, specifically green human resource management practices, Which are reflected on sustainable development with their economic, environmental and social dimensions as well as reducing costs, waste minimization and recycling, And the research started from two main hypotheses to explore the correlation and influence between the variables of the research by analyzing the answers of the research sample, which included (136) employees of the Al-Imamein Al-kadhemein medical city, Data and information were collected using quest

Background: The use of minerals in treatment of different diseases is as old as man himself. zinc is the most famous trace mineral related to male sexual function. Oligoasthenozoospermic subfertile patients were treated with zinc sulphate for three months.

Objectives: Aim of the research is to investigate the role of Zinc and if it affects the abnormalities of some semen parameters and to study the possible role of pharmaceutical preperations of zinc in amelioration of male subfertility as well as to assess the ability of Zinc to induce changes in the serum and semen zinc levels in addition to the levels of reproductive hormones (FSH and Testosterone).

Type of the study:

The need for participants’ performance assessments in academia and industry has been a growing concern. It has attendance, among other metrics, is a key factor in engendering a holistic approach to decision-making. For institutions or organizations where managing people is an important yet challenging task, attendance tracking and management could be employed to improve this seemingly time-consuming process while keeping an accurate attendance record. The manual/quasi-analog approach of taking attendance in some institutions could be unreliable and inefficient, leading to inaccurate computation of attendance rates and data loss. This work, therefore, proposes a system that employs embedded technology and a biometric/ w

With the continuous downscaling of semiconductor processes, the growing power density and thermal issues in multicore processors become more and more challenging, thus reliable dynamic thermal management (DTM) is required to prevent severe challenges in system performance. The accuracy of the thermal profile, delivered to the DTM manager, plays a critical role in the efficiency and reliability of DTM, different sources of noise and variations in deep submicron (DSM) technologies severely affecting the thermal data that can lead to significant degradation of DTM performance. In this article, we propose a novel fault-tolerance scheme exploiting approximate computing to mitigate the DSM effects on DTM efficiency. Approximate computing in hardw

The research aims to identify the availability of some basic competencies that are required to be available to workers in digital agricultural Extension from the point of view of senior management, middle management, and, employees with Post-graduate education degrees, represented by the following: Transition to digital agricultural Extension for sustainable and smart family farms, benefiting from international expertise and experiences in applying for Digital agricultural Extension, preparing and implementing Extension messages through platforms, factors affecting the effectiveness of digital agricultural Extension and its platforms, following up and evaluating the activities and programs of the digital Extension platform. The research pop

The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals