The research aims to measure the impact of envy on job stress because the topic of envy represents a negative emotion that exists at all organizational levels, which may cause stress in the work environment.

The Research problem is represented by the lack of perception of most of the faculty staff on the negative effects of envy on their well-being in the Technical College of Management - Baghdad, and what is the impact level of envy on their job stress.

To achieve this, the scale of envy was based on two dimensions (being envied, Envying others), While the job stress scale was based on seven dimensions (workload, conflict role, Family factors, work environment, work relationships

Soil water use and water storage vary by vegetative management practices, and these practices affect land productivity and hydrologic processes. This study investigated the effects of agroforestry buffers (AB), grass buffers (GB), and biofuel crops (BC), relative to row crops (RC) on soil water use for a claypan soil in northern Missouri, USA. The experiment located at the Greenley Memorial Research Center included RC, AB, GB, and BC established in 1991, 1997, 1997, and 2012, respectively. Soil water reflectometer sensors installed at 5‐, 10‐, 20‐, and 40‐cm depths monitored soil water from April to November in 2017 and 2018. Results showed significant differences in weekly volumetric water content (VWC) among treatments for all fou

In this article, the types of renewable energies and the environmental effects of consuming these energies are studied. Energy is one of the things necessary for economic and social development and improving the quality of life, and the presence of continuous and sustainable economic energy is essential for any economic development and growth. Humankind has been aware of renewable energies such as biomass and geothermal energy for a long time and has used these energies as heat sources for shelter. With the beginning of the extraction of fossil fuels such as oil and coal and unlimited access to these products, the use of renewable energy sources, except in remote places and forest areas, has become limited and forgotten. Currently in Iraq,

Firstly, in this study, a brief updated description and applications of different solar collectors used in renewable energy systems for supplying electric and thermal energy was presented. Secondly, an attempt was made to utilize tilting orientation of solar collector for maximizing collector energy with time in respect to horizontal orientation. For energy calculation, global solar radiation was used since they are directly related.  For that purpose, field measurements of half-hourly radiation on two flat panels of tilting and horizontal orientations were carried out throughout 8-month period under local climate of Baghdad. Then, energy gain and radiation level averages were calculated based on the field radiation

The Pulse Coupled Oscillator (PCO) has attracted substantial attention and widely used in wireless sensor networks (WSNs), where it utilizes firefly synchronization to attract mating partners, similar to artificial occurrences that mimic natural phenomena. However, the PCO model might not be applicable for simultaneous transmission and data reception because of energy constraints. Thus, an energy-efficient pulse coupled oscillator (EEPCO) has been proposed, which employs the self-organizing method by combining biologically and non-biologically inspired network systems and has proven to reduce the transmission delay and energy consumption of sensor nodes. However, the EEPCO method has only been experimented in attack-free networks without

Abstract

         Uncertainty, the deeply-rooted fact that surrounding the investment environment, especially the stock market which just prices have taken a specific trend until they moved to another one for its up or down. This means that the volatility characteristic of financial market requires the rational investor an argument led towards the adoption of planned acts to gain greater benefit in the goal of wealth maximizing. There is no possibility to achieve this goal without the burden of uncertainty and the risk of systematic fluctuations of investment returns in the financial market after the facts of  efficient diversification have pro

The study involved the effectiveness of Iraqi attapulgite (IQATP) clay as an environmentally friendly material that easily adsorbs brilliant green (BG) dye from water systems and is identified by various complementary methods (e.g., FTIR, SEM‐EDS, XRD, ICP‐OES, pH_pzc, and BET), where the result reported that the IQATP specific surface area is 29.15 m²/g. A systematic analysis was selected to evaluate the impact of different effective adsorption performance variables on BG dye decontamination. These variables included IQATP dosage (0.02–0.8 g/L), solution pH (3.05–8.15), contact time (ranging from 2 to 25 min), and initial BG dye concentration from 20 to 80 mg/L. The parameter

Clean energy applications widely recognize Proton Exchange Membrane Fuel Cells (PEMFCs) for their high efficiency and environmental compatibility. Accurate parameter identification of PEMFC models is essential for enhancing system performance and reliability, particularly under dynamic operating conditions. This paper presents a novel optimization-based approach called Heterogeneous Comprehensive Learning-Bald Eagle Search (HCLBES) with enhanced exploration and exploitation capabilities for the effective modeling of PEMFC. The algorithm combines the exploration strength of the Bald Eagle Search with comprehensive learning and heterogeneity mechanisms to achieve a balanced global and local search space. In this algorithm, the number

The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed