The study aimed to examine the sensitivity to stress and its relation to positive mood among educational supervisors. The researcher used the descriptive approach as more an appropriate method for the current study. The sample is composed of (200) educational supervisor. To collect study data, two scales have been used: one scale to measure the sensitivity to stress and the other to measure the positive mood. The results indicated that a high level of sensitivity to stress with low level of positive mood among educational supervisors, sensitivity to stress showed significant differences among the sample regarding to major. There is no correlation between sensitivity to stress and positive mood, and finally, there are no significant diffe

Cryptocurrency became an important participant on the financial market as it attracts large investments and interests. With this vibrant setting, the proposed cryptocurrency price prediction tool stands as a pivotal element providing direction to both enthusiasts and investors in a market that presents itself grounded on numerous complexities of digital currency. Employing feature selection enchantment and dynamic trio of ARIMA, LSTM, Linear Regression techniques the tool creates a mosaic for users to analyze data using artificial intelligence towards forecasts in real-time crypto universe. While users navigate the algorithmic labyrinth, they are offered a vast and glittering selection of high-quality cryptocurrencies to select. The

The lipid profile and adipokines of an adolescent may be affected by some parasite infections. Recently, it has been discovered that these parasites are connected to body mass index (BMI), lipids and adipokines. The current study, therefore, aimed to specify how Toxoplasma gondii (T. gondii) affect BMI, lipid profile and adipokines. This study was conducted in Al Madain hospital, Baghdad from October to December 2022. An ELISA test was performed to examine the anti-T. gondii IgG and IgM for a group of adolescents attending the hospital. Based on this examination ninety adolescents were chosen to be involved in the study. They were separated in to two groups: individuals who tested positive for the parasite (n=45) and those who teste

     One technique used to prepare nanoparticles material is Pulsed Laser Ablation in Liquid (PLAL), Silver Oxide nanoparticles (AgO) were prepared by using  this technique, where silver target was submerged in ultra-pure water (UPW)  at room temperature after that Nd:Yag laser which characteristics by 1064 nm wavelength, Q-switched, and 6ns pulse duration was used to irradiated silver target. This preparation method was used to study the effects of laser irradiation on Nanoparticles synthesized by used varying laser pulse energy 1000 mJ, 500 mJ, and 100 mJ, with 500 pulses each time on the particle size. Nanoparticles are characterized using XRD, SEM, AFM, and UV-Visible spectroscopy. All the structural peaks determined by the XRD

The objective of this study was to progress another method for coagulation/flocculation of the microalga Chlorella vulgaris via pellet-forming of the fungal species Aspergillus niger which was isolated from municipal wastewater mud and the facultative heterotrophic microalga "C.vulgaris was used. The main factors studies were spore inoculums, organic carbon concentration in medium as well as pH variation which had considerably positive effects on microalgae/fungi co-pelletization formation. The process parameters are an inoculum1×104 spores/ML, 15 g/l sucrose as carbon source and pH ranged from 5 - 7.0 were found optimal for efficient microalgae/fungi co-pelletization formation. For autotrophic growth, when pH of culture broth was adjusted

There is a great deal of systems dealing with image processing that are being used and developed on a daily basis. Those systems need the deployment of some basic operations such as detecting the Regions of Interest and matching those regions, in addition to the description of their properties. Those operations play a significant role in decision making which is necessary for the next operations depending on the assigned task. In order to accomplish those tasks, various algorithms have been introduced throughout years. One of the most popular algorithms is the Scale Invariant Feature Transform (SIFT). The efficiency of this algorithm is its performance in the process of detection and property description, and that is due to the fact that

Georeferencing process is one of the most important prerequisites for various geomatics applications; for example, photogrammetry, laser scan analysis, remotely sensing, spatial and descriptive data collection, and others. Georeferencing mostly involves the transformation of coordinates obtained from images that are inhomogeneous due to accuracy differences. The georeferencing depends on image resolution and accuracy level of measurements of reference points ground coordinates.  Accordingly, this study discusses the subject of coordinate’s transformation from the image to the global coordinates system (WGS84) to find a suitable method that provides more accurate results. In this study, the Artificial Neural Network (ANN) method wa

In this article, we propose a Bayesian Adaptive bridge regression for ordinal model. We developed a new hierarchical model for ordinal regression in the Bayesian adaptive bridge. We consider a fully Bayesian approach that yields a new algorithm with tractable full conditional posteriors. All of the results in real data and simulation application indicate that our method is effective and performs very good compared to other methods. We can also observe that the estimator parameters in our proposed method, compared with other methods, are very close to the true parameter values.