High-volume traffic with ultra-heavy axle loads combined with extremely hot weather conditions increases the propagation of rutting in flexible pavement road networks. Several studies suggested using nanomaterials in asphalt modification to delay the deterioration of asphalt pavement. The current work aims to improve the resistance of hot mix asphalt (HMA) to rutting by incorporating Nano Silica (NS) in specific concentrations. NS was blended into asphalt mixtures in concentrations of 2, 4, and 6% by weight of the binder. The behavior of asphalt mixtures subjected to aging was investigated at different stages (short-term and long-term aging). The performance characteristics of the asphalt mixtures were evaluated using the Marshall stability, flow, and wheel tracking tests. Field Emission Scanning Electron Microscopy (FESEM) was utilized to understand the microstructure changes of modified asphalt and estimate the dispersion of NS within the asphalt. The results revealed that using NS–asphalt mixtures as a surface layer in paving construction improved pavement performance by increasing stability, volumetric characteristics, and rutting resistance before and after aging. The FESEM images showed adequate dispersion of NS particles in the mixture. Results indicated that adding 4% of NS to asphalt mixtures effectively enhanced the pavement’s performance and rutting resistance. Doi: 10.28991/CEJ-SP2023-09-01 Full Text: PDF
Limited importance of research in a stand on the most important difficulties faced by both faculty and parents to communicate with each process to follow up on their children, and the analysis and inventory of the obstacles that hinder the educational process, and work to develop a vision of how to address these constraints and the important role of technology in the treatment of problems of the society so as to develop frameworks future to minimize the errors and the problems they face, and the development outlook for future generations in order to promote the educational level, especially that Iraq is going through a change in conditions in all sectors. Through the questionnaire, which includes questions set that was made on a sample o
... Show MoreThe present study aims to explore determinants of entrepreneurial behavior from perspective of social theory. It is based on model notions of (Tyler & Blader, 2003) which have focused on studying role of positively personal and social identity in motivating employees to practicing desired behavior which serves the organization in which they work. Based on these notions and previous literature, study model were built. This model explains the relationship between status judgments (perceived internal respect and perceived external prestige) and entrepreneurial behavior. It includes three main hypotheses. The first and second hypothesis are concerning the relationship between status judgmen
... Show MoreThis paper was aimed to study the efficiency of forward osmosis (FO) process as a new application for the treatment of wastewater from textile effluent and the factors affecting the performance of forward osmosis process.
The draw solutions used were magnesium chloride (MgCl2), and aluminum sulphate (Al2 ( SO4)3 .18 H2O), and the feed solutions used were reactive red, and disperse blue dyes.
Experimental work were includes operating the forward osmosis process using thin film composite (TFC) membrane as flat sheet for different draw solutions and feed solutions. The operating parameters studied were : draw solutions concentration (10 – 90 g/l), feed solutions concentration (5 – 30 mg/l), draw solutions flow rate (10 – 50 l/hr
Understanding the effects of fear, quadratic fixed effort harvesting, and predator-dependent refuge are essential topics in ecology. Accordingly, a modified Leslie–Gower prey–predator model incorporating these biological factors is mathematically modeled using the Beddington–DeAngelis type of functional response to describe the predation processes. The model’s qualitative features are investigated, including local equilibria stability, permanence, and global stability. Bifurcation analysis is carried out on the temporal model to identify local bifurcations such as transcritical, saddle-node, and Hopf bifurcation. A comprehensive numerical inquiry is carried out using MATLAB to verify the obtained theoretical findings and und
... Show MoreElectrical Discharge Machining (EDM) is a non-traditional cutting technique for metals removing which is relied upon the basic fact that negligible tool force is produced during the machining process. Also, electrical discharge machining is used in manufacturing very hard materials that are electrically conductive. Regarding the electrical discharge machining procedure, the most significant factor of the cutting parameter is the surface roughness (Ra). Conventional try and error method is time consuming as well as high cost. The purpose of the present research is to develop a mathematical model using response graph modeling (RGM). The impact of various parameters such as (current, pulsation on time and pulsation off time) are studied on
... Show MoreThe evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed
... Show MoreBreast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep
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