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,

In this paper, Bayes estimators of the parameter of Maxwell distribution have been derived along with maximum likelihood estimator. The non-informative priors; Jeffreys and the extension of Jeffreys prior information has been considered under two different loss functions, the squared error loss function and the modified squared error loss function for comparison purpose. A simulation study has been developed in order to gain an insight into the performance on small, moderate and large samples. The performance of these estimators has been explored numerically under different conditions. The efficiency for the estimators was compared according to the mean square error MSE. The results of comparison by MSE show that the efficiency of B

In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

This work has been done to prepare a series of new alkene compounds derived from 4-thiozolidinones by substituting different aldehydes, P-acetamido-phenol, and 2-mercapto-benzoimidazole, which were used as starting materials to form ester [I]a,b and then make hydrazides [II]a,b, which were used to prepare 1, 3, and 4-oxadiazoles [III]a,b, which were then used for prepared Schiff bases [IV]a-f, The next step was the synthesis of 4-thiazoldinone derivatives [V]a-f  from Schiff bases. The final step was the synthesis of alkenes [VII]a-f, the prepared derivatives were identified with spectral methods (FT-IR, 1H-NMR, mass, and CHNS). The antibacterial activity of the prepared derivatives was evaluated against four types of bacteria, pos

In order to implement the concept of sustainability in the field of construction, it is necessary to find an alternative to the materials that cause pollution by manufacturing, the most important of which is cement. Because factory wastes provide siliceous and aluminous materials and contain calcium such as fly ash and slag that are used in the production of high-strength geopolymer concrete with specifications similar to ordinary concrete, it was necessary for developing this type of concrete that is helping to reduce CO₂ (dioxide carbon) in the atmosphere. Therefore, the aim of this study was to study the influence of incorporating various percentages of slag as a replacement for fly ash and the effect of sl

This paper presents an enhancement technique for tracking and regulating the blood glucose level for diabetic patients using an intelligent auto-tuning Proportional-Integral-Derivative PID controller. The proposed controller aims to generate the best insulin control action responsible for regulating the blood glucose level precisely, accurately, and quickly. The tuning control algorithm used the Dolphin Echolocation Optimization (DEO) algorithm for obtaining the near-optimal PID controller parameters with a proposed time domain specification performance index. The MATLAB simulation results for three different patients showed that the effectiveness and the robustness of the proposed control algorithm in terms of fast gene

    Hartha Formation is an overburdened horizon in the X-oilfield which generates a lot of Non-Productive Time (NPT) associated with drilling mud losses. This study has been conducted to investigate the loss events in this formation as well as to provide geological interpretations based on datasets from nine wells in this field of interest. The interpretation was based on different analyses including wireline logs, cuttings descriptions, image logs, and analog data. Seismic and coherency data were also used to formulate the geological interpretations and calibrate that with the loss events of the Hartha Fm.

   The results revealed that the upper part of the Hartha Fm. was identified as an interval capable of creating potentia