Abstract

      This research aims to identify the role of Psychological Capital (PsyCap) in the Spirituality at the Workplace (SAW) for a sample of the teaching staff of the four Colleges of the University of Kufa reached (200) out of (470) teaching, and to achieve the objective of this research and through access to research and studies of foreign adopted researchers standards scales of research variables, since it relied on the model (Luthans, Youssef, et al., 2007) to represent the components of Psychological Capital (self-efficacy, and hope, and optimism, and resilience), and given the attention organizations in the human element because of it

In this paper, new brain tumour detection method is discovered whereby the normal slices are disassembled from the abnormal ones. Three main phases are deployed including the extraction of the cerebral tissue, the detection of abnormal block and the mechanism of fine-tuning and finally the detection of abnormal slice according to the detected abnormal blocks. Through experimental tests, progress made by the suggested means is assessed and verified. As a result, in terms of qualitative assessment, it is found that the performance of proposed method is satisfactory and may contribute to the development of reliable MRI brain tumour diagnosis and treatments.

The atomic properties have been studied for He-like ions (He atom, Li+, Be2+ and B3+ions). These properties included, the atomic form factor f(S), electron density at the nucleus , nuclear magnetic shielding constant and diamagnetic susceptibility ,which are very important in the study of physical properties of the atoms and ions. For these purpose two types of the wave functions applied are used, the Hartree-Fock (HF) waves function (uncorrelated) and the Configuration interaction (CI) wave function (correlated). All the results and the behaviors obtained in this work have been discussed, interpreted and compared with those previously obtained.

There is an increasing interest in the use of plant extracts as therapeutic agents, particularly their capacity to inhibit the growth of pathogenic microorganisms. In this study antibacterial effect of Malva sylvestris, Anastatica hierochuntica and Vitis vinifera leaves extracts were evaluated against Escherichia coli, Pseudomonas aeruginosa, Bacillus subtilis, Staphylococcus aureus and Proteus mirabilis. The in vitro antibacterial activity was performed using agar well diffusion method and the minimum inhibitory concentration (MIC) was determined by microtitration technique. The result indicated that the extract of V. vinifera leaves inhibited with the growth of gram-positive bacteria, as well as gram-negative bacteria while the extract

In this research, a factorial experiment (4*4) was studied, applied in a completely random block design, with a size of observations, where the design of experiments is used to study the effect of transactions on experimental units and thus obtain data representing experiment observations that The difference in the application of these transactions under different environmental and experimental conditions It causes noise that affects the observation value and thus an increase in the mean square error of the experiment, and to reduce this noise, multiple wavelet reduction was used as a filter for the observations by suggesting an improved threshold that takes into account the different transformation levels based on the logarithm of the b

optical properties of pure poly(vinyl Alcohol) films and poly(vinyl Alcohol) doped with methyl red were study, different percentage prepared with constant thickness using casting technique. Absorption, Transmission spectra have been recorded in order to study the optical parameters such as absorption coefficient, energy gap, refractive index, Extinction coefficient and dispersion parameters were measured in the wavelength range (200-800)nm. This study reveals that the optical properties of PVA affect by increasing the impurity concentration.

Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin

The performance of the pavement in terms of vehicle safety and tire wear is affected by the friction behavior of the pavement. To highlight the main characteristics that affect the production of better friction resistance of the pavement surface in this work. The micro-texture and macro-texture of the asphalt surface of Baghdad Airport highway were studied using two methods: (sand patch method and the British pendulum test). The sand patch was examined by drawing sand grains of a specific volume, while the micro-texture was analyzed using a BPT under dry and wet surface conditions. All data obtained from the two examinations were analyzed and modelled statistically using SPSS 25 software. Results show that skid resistance of pavemen