هدف البحث الى التعرف على درجة التفكير الإبداعي لدى التلامذة، والتعرف على الفروق في درجات التفكير الإبداعي تبعاً لمتغير النوع ( ذكور – إناث) ، ولتحقيق أهداف البحث قامت الباحثة باعداد مقياس التفكير الإبداعي بالاعتماد على نظریة (سكنر) وتكون مقياس البحث بالصورة النهائيه من (14) فقرة وطبق مقياس البحث على العينة البالغة (100) طالب وطالبه تم اختيارهم بطريقة عشوائية بسيطة من مجتمع البحث ، وبعد جمع بيانات البحث تمت مع

The purpose of this research was to evaluate rice husk functionalized with Mg-Fe-layered double hydroxide (RH-Mg/Fe-LDH) as an adsorbent for the removal of meropenem antibiotic (MA) from an aqueous solution. Several batch experiments were undertaken using various conditions. Based on the results, the optimal Mg/Fe-LDH adsorbent with a pH of 9 and an M2+/M3+ ratio of 0.5 was associated with the lowest particle size (specifically. 11.1 nm). The Langmuir and Freundlich models were consistent with the experimental isotherm data (R2 was 0.984 and 0.993, respectively), and MA’s highest equilibrium adsorption capacity was 43.3 mg/g. Additionally, the second-order model was consistent with the adsorption kinetic results.

Background: One of the most common and prevalent oral diseases among adolescents is periodontal disease particularly gingivitis, however enamel anomalies and dental trauma could occur. Aims of the study: This study was conducted among 14-15 years intermediate school male students in urban area of Al-Khalis city to assess the oral hygiene (dental plaque) and to estimate the prevalence and severity of gingivitis, enamel anomalies, as well as traumatic dental injuries, furthermore to show the significant difference between these two ages concerning these oral problems. Materials and methods: In this study the total sample consisted of 735 students (397 aged 15 years and 338 aged 14 years ). In present study dental plaque was recorded accord

Channel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T