Silica-based mesoporous materials are a class of porous materials with unique characteristics such as ordered pore structure, large surface area, and large pore volume. This review covers the different types of porous material (zeolite and mesoporous) and the physical properties of mesoporous materials that make them valuable in industry. Mesoporous materials can be divided into two groups: silica-based mesoporous materials and non-silica-based mesoporous materials. The most well-known family of silica-based mesoporous materials is the Mesoporous Molecular Sieves family, which attracts attention because of its beneficial properties. The family includes three members that are differentiated based on their pore arrangement. In this review,

The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

The study aims to identify the degree of Tabuk University practices to raise the intellectual awareness of students through scientific research, as well as to identify the degree of Tabuk University practicing to raise the intellectual awareness through the educational process (faculty member – activities). The study also seeks to identify the degree of Tabuk University practicing to raise the intellectual awareness of students through community service and university media. The study is descriptive in nature that employed the questionnaire as a tool in collecting data. Total of (540) students were chosen randomly from different colleges at universities of Tabuk to form the study sample. The results showed that faculty member has pract

Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d

     The research aims to analyze the impact of exchange rate fluctuations (EXM and EXN) and inflation (INF) on the gross domestic product (GDP) in Iraq for the period 1988-2020. The research is important by analyzing the magnitude of the macroeconomic and especially GDP effects of these variables, as well as the economic effects of exchange rates on economic activity. The results of the standard analysis using the ARDL model showed a long-term equilibrium relationship, according to the Bound Test methodology, from explanatory (independent) variables to the internal (dependent) variable, while the value of the error correction vector factor was negative and moral at a level less than (1%). The relationship bet

ان دراسة الدين العام في اقتصاد ريعي شديد الارتباط بسوق خارجية شديدة التقلب يعد من الدراسات الحساسة كونها تضع امام الباحثين القيود المالية التي سيتكبل بها اقتصاد ضعيف قليل التنوع يعتمد على سوق الطاقة مما يفقد حالة الاستدامة المالية وتفقد الدولة القدرة على الوفاء بالتزاماتها المالية ، ان الحدود الامنة للدين العام يجب ان تكون بنسبة لا تتجاوز 60% من الناتج المحلي الاجمالي حسب اتفاقية ماسترخت الخاصة بمجلس الاتحا

Since cancer is becoming a leading cause of death worldwide, efforts should be concentrated on understanding its underlying biological alterations that would be utilized in disease management, especially prevention strategies. Within this context, multiple bodies of evidence have highlighted leptin’s practical and promising role, a peptide hormone extracted from adipose and fatty tissues with other adipokines, in promoting the proliferation, migration, and metastatic invasion of breast carcinoma cells. Excessive blood leptin levels and hyperleptinemia increase body fat content and stimulate appetite. Also, high leptin level is believed to be associated with several conditions, including overeating, emotional stress, inflammation, obesity,