This study aimed at identifying the counseling needs for classroom teachers specialization in
Jerash university. The sample of the study consisted (112) students. To achieve this goal a
scale with (39) items was built by the researcher, this scale has four domains they are as
follows; family, social, psychological and academic domain. The results of this study showed
that counseling needs obtain the heighest average. As well as, the results of the study revealed
that there were statistical differences in favor of gender and teaching year variable. Finally the
study stated a list of recommendations.

Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay

Nanoparticles of humic acid and iron oxide were impregnated on the inert sand to produce sorbent for treating groundwater contained of cadmium and copper ions by technology of permeable reactive barrier (PRB). Sewage sludge was the source of the humic acid to prepare the coated sand by humic acid—iron oxide (CSHAIO) sorbent; so, this work is consistent with sustainable development. For 10 mg/L metal concentration, batch tests at speed of 200 rpm signified that the removal efficiencies are greater than 90% at sorbent dosage 0.25 g/ 50 mL, pH 6 and contact time 1 h. The kinetic data was well described by the Pseudo first-order model indicating that physicosorption is the predominant mechanism. The maximum adsorption capacities (qmax) were c

The research aims: to build a measure of the cognitive competence of coaches from the point of view of players of Iraqi Premier League volleyball clubs and extract scores and standard levels for it. In order to achieve the objectives of the research, the descriptive method was used using the survey method. As for the research sample, it was chosen intentionally, and was represented by volleyball players for the Premier League 2024-2025. The sample was divided into exploratory, constructive, and standardizing, and starting the construction procedures, which included finding the scientific foundations for the scale, in addition to extracting the modified standard score and levels for the sample of the main experiment for standardization. Amou

          This study was done to evaluate a new technique to determine the presence of methamphetamine in the hair using nano bentonite-based adsorbent as the filler of extraction column. The state of the art of this study was based on the presence of silica in the nano bentonite that was assumed can interact with methamphetamine. The hair used was treated using methanol to extract the presence of methamphetamine, then it was continued by sonicating the hair sample. Qualitative analysis using Marquish reagent was performed to confirm the presence of methamphetamine in the isolate.The hair sample that has been taken in a different period confirmed that this current developing method can be used to analyzed methamphetamine. This m

Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

Background: Although mammography is a powerful screening tool in detection of early breast cancer, it is imperfect, particularly for women with dense breast, which have a higher risk to develop cancer and decrease the sensitivity of mammogram, Automated breast ultrasound is a recently introduced ultrasonography technique, developed with the purpose to standardize breast ultrasonography and overcome some limitations of handheld ultrasound, this study aims to evaluate the diagnostic efficacy of Automated breast ultrasound and compare it with handheld ultrasound in the detection and characterization of breast lesions in women with dense breasts.

Objectives:<

Medulloblastomas and ependymomas are the most common malignant brain tumors in children. However genetic abnormalities associated with their development and prognosis remain unclear. Recently two gene fusions, KIAA1549–BRAF and SRGAP3–RAF1 have been detected in a number of brain tumours. We report here our development and validation of RT-RQPCR assays to detect various isoforms of these two fusion genes in formalin fixed paraffin embedded (FFPE) tissues of medulloblastoma and ependymoma. We examined these fusion genes in 44 paediatric brain tumours, 33 medulloblastomas and 11 ependymomas. We detected both fusion transcripts in 8/33, 5/33 SRGAP3 ex10/RAF1 ex10, and 3/33 KIAA1549 ex16/BRAF ex9, meduloblastomas but none in the 11 ep