The objective of the current research is to identify the degree of awareness of the teachers of Arabic language with the requirements of sustainable development. The research sample consisted of (100) male and female teachers of the Arabic language. A 3-likert scale of (71) items grouped into practical and cognitive aspects, five trends for each aspect was designed by the researcher to explore the required data. The results showed that the level of awareness of teachers of the Arabic language was moderate of both the cognitive and practical aspects of sustainable education with means (1.69) and (1.48) respectively. The researcher presented a set of recommendations and suggestions.

بهذا البحث نقارن معاييرالمعلومات التقليدية (AIC , SIC, HQ , FPE ) مع معيارمعلومات الانحراف المحور (MDIC) المستعملة لتحديد رتبة انموذج الانحدارالذاتي (AR) للعملية التي تولد البيانات,باستعمال المحاكاة وذلك بتوليد بيانات من عدة نماذج للأنحدارالذاتي,عندما خضوع حد الخطأ للتوزيع الطبيعي بقيم مختلفة لمعلماته

This research is carried out to investigate the behavior of self-compacting concrete (SCC) two-way slabs with central square opening under uniformly distributed loads. The experimental part of this research is based on casting and testing six SCC simply supported square slabs having the same dimentions and reinforcement. One of these slabs was cast without opening as a control slab. While, the other five slabs having opening ratios (O_R) of 2.78%, 6.25%, 11.11%, 17.36% and 25.00%. From the experimental results it is found that the maximum percentage decrease in cracking and ultimate uniform loads were 31.82% and 12.17% compared to control slab for opening ratios (O_R

Photovoltaic devices (PVs) were fabricated by spray-coating an ink of copper indium diselenide CuInSeR 2 R(CIS) nanocrystals as the light-absorbing layer. Without high-temperature post-deposition annealing, PVs were made on glass substrates with power conversion efficiencies of up to 1.5% and 0.9%, for Au and Mo coated respectively, under AM 1.5 illumination. UV–Vis spectrophotometer in the wavelength range 350–1500 nm. X-ray diffraction (XRD) and energy dispersive spectroscopy (EDS) analysis it is evident that CuInSeR 2 R have the chalcopyrite structure as the major phase and no secondary phase with a preferred orientation along (112) direction and The atomic ratio of Cu : In : Se in the nanocrystals is nearly 1 : 1 : 2.

An investigation was conducted for the determination of the effects of the forming conditions in the production of Gamma Alumina catalyst support on the crushing strength property. Eight variables were studied , they are ;binder content which is the sodium silicate , Solvent content which is the water, speed of mixing , time of mixing, drying temperature , drying time , calcinations temperature and the calcinations time
Design of the experiments was made by using the response Surface method in Minitab 15 software which supply us 90 experiments .
The results of this investigation show that the crushing strength for the dried Gamma alumina extrudate was affected by the drying temperature and the drying time only and there is no inter

The research aims to know the question asking skills in terms of levels, conditions, classification, and types. The research limited to the literature that dealt with the importance of questioning for students and teachers. The most important term used in the research is the skill (Ryan defined it as "the ability to perform with great efficiency, accuracy, and ease). The results of the research are as follows: 1. the questions asked by the schoolteacher within the assessment of students' learning. 2. Teachers should focus on the lower levels of learning (remembering, understanding and comprehension) and then evaluating students at the higher levels (synthesis and evaluation). 3. Teacher with good knowledge can skillfully use the question

   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be