هدف البحث إلى بناء مقياسين تخصصين للنزاعات اللاشعورية وحرية الإرادة لمدربي بعض ألعاب القوى والتعرف على مستوى كل منهما لديهم، وإعداد برنامج إرشادي نفسي مستند لرفع مستوى الحالات اللاشعورية وحرية الإرادة للمدربين الذين يعانون من انخفاض مستوى النزاعات اللاشعورية وحرية الإرادة، والتعرف على تأثير البرنامج الإرشادي نفسي في النزاعات اللاشعورية وحرية الإرادة لدى مدربي بعض ألعاب القوى، لتفترض بذلك الباحثة بإ

The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

This study focuses on improving the safety of embankment dams by considering the effects of vibration due to powerhouse operation on the dam body. The study contains two main parts. In the first part, ANSYS-CFX is used to create the three-dimensional (3D) Finite Volume (FV) model of one vertical Francis turbine unit. The 3D model is run by considering various reservoir conditions and the dimensions of units. The Re-Normalization Group (RNG) k-ε turbulence model is employed, and the physical properties of water and the flow characteristics are defined in the turbine model. In the second phases, a 3D finite element (FE) numerical model for a rock-fill dam is created by using ANSYS®, considering the dam connection with its powerhouse

Objective(s): The world of dentistry is constantly evolving, and with the advent of 3D printing technology, the possibilities are endless. However, little is known about the effects of adding ZrO2 NPs to the denture base resin of 3D additive manufacturing technique.Aim of this study is to evaluate the behavior of resin which is used to 3D printing of denture base with the addition of ZrO2 NPs on denture adaptation property and diametral compression strength.Methods: 60 samples were printed, 30 disks for diametral compressive test and 30 denture base for denture adaptation test. Three groups per test (n=10). The control group for each test included unreinforced 3Dprinted denture base resin, and the other groups were  reinforced with (2&

The present study aimed to investigate the effects of alcohol and hot aqueous extracts for leaves of Adhatoda vasica on, first larval instars Musca domestica. They were exposed to the suggested concentrations of alcoholic extract which were (500, 1000, 1500, 2000) PPM while the suggested concentrations of the hot aqueous extracts (500, 1000, 1500, 2000, 2500)PPM. The alcoholic (Methanol) extract of leaves was much effective on to killing the first larval instars of the M. domestica than hot aqueous extract.

In this study, doped thin cadmium peroxide films were prepared by pulsed laser deposition with different doping concentrations of aluminium of 0.0, 0.1, 0.3, and 0.5 wt.% for CdO2(1-X)Al(X) and thicknesses in the range of 200 nm. XRD patterns suggest the presence of cubic CdO2 and the texture factor confirms that the (111) plane was the preferential growth plane, where the texture factor and the grain size decreased from 2.02 to 9.75 nm, respectively, in the pure sample to 1.88 and 5.65 nm, respectively, at a concentration of 0.5 wt%. For the predominant growth plane, the deviation of the diffraction angle Δθ and interplanar distance Δd from the standard magnitudes was 2.774° and 0.318 Å, respectively, for the pure sample decreased to

Pseudomonas aeruginosa readily binds to different kind of abiotic surfaces and form biofilm. The ability of the bacterial species to form biofilm onto polyvinyl chloride (PVC) is associated with several economic, health and environmental problems. The effect of kind of water on ability of this bacterium to form biofilm is scanty in literature. In present study, the ability of different environmental isolates of P. aeruginosa to form biofilm onto polystyrene microtiter plate was evaluated. Furthermore, the effect of waters that collected from different sources on biofilm formation of this bacterium onto PVC was studied. Spectrophotometric method was used to check the ability of bacteria to form biofilm and evaluated the role of waters onto a

Background: Polymethyl methacrylate (PMMA) is used in denture fabrication and considered as the most reliable material for the construction of removable prosthodontic appliances. The material is far from ideal in fulfilling the mechanical requirements and the effect of autoclave processing has not been fully determined. The purpose of this study was to evaluate the effect of addition of salinized (ZrO2) Nano fillers in percentages 3%, 5% and 7% by weight on some properties of heat cured acrylic processed the by autoclave and compare it with 0% (control) group . Materials and methods: The silanized(ZrO2) Nano-particles was added to PMMA powder by weight in three different percentages 3%, 5% and 7%, mixed by probe ultra-sonication machine.

Focusing on the negative role of default risk on banks, as it is one of the most important risks facing banks, which are difficult to determine accurately, and its reflection on the indicators of profitability of cash flows. The increasing competition between banks led to an increase in the credit facilities granted by banks, and was accompanied by an increase in exposure to the risks of default, which led to an impact on the level of performance of banks in terms of achieving the required return according to the levels of high competition. Therefore, the problem of this study focused on the extent to which the risk indicators of default affect the profitability indicators of the cash flows of the banks research sample in the profit

Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt