Rutting is a crucial element of the mechanical performance characteristics of asphalt mixtures, which was the primary target of this study. The task involved substituting various portions of virgin coarse aggregate with recycled concrete aggregate materials that had been treated or left untreated at rates ranging from 25 to 100%, with a constant increase of 25%. The treatment process of recycled concrete aggregate involved soaking in acetic acid, followed by a mechanical process for a short time inside a Los Angeles machine without the balls. This research utilized two primary tests: the standard Marshall test to identify the optimal asphalt contents and the volumetric characteristics of asphalt mixtures. The other one w

Two novel demountable shear connectors for precast steel-concrete composite bridges are presented. The connectors use high-strength steel bolts, which are fastened to the steel beam with the aid of a special locking configuration that prevents slip of bolts within their holes. Moreover, the connectors promote accelerated construction and overcome typical construction tolerances issues of precast structures. Most importantly, the connectors allow bridge disassembly, and therefore, can address different bridge deterioration scenarios with minimum disturbance to traffic flow, i.e. (1) precast deck panels can be rapidly uplifted and replaced; (2) connectors can be rapidly removed and replaced; and (3) steel beams can be replaced, while precast

Objectives: Successful endodontic treatment outcome requires effective shaping and cleaning of root canals. This study aims to evaluate the smear layer removal after continuous chelation (CC) ) NaOCL\HEDP( and sequential chelation (SC) )NaOCL\EDTA( and their influence on the push-out bond strength (POBS) of Bio-C sealer. Materials and Methods: Palatal roots of the maxillary first molar (n=72) were divided into four groups (n=18) as follows: 3% NaOCL, SC: 3% NaOCL followed by 17% EDTA, CC: 3% NaOCL \9% HEDP and Distilled water. Thirty-two roots (n=8/group) were split longitudinally for smear layer evaluation using SEM. Forty roots were obturated with Guttapercha and Bio-C sealer using a single cone technique. Thre

Tests were performed on asphalt concrete specimens with (101.6 mm in diameter and 101.6 mm in height), and the results were implemented for calculating permanent deformation and resilient modulus under repeated compressive stress with different levels of stresses (0.068, 0.138 and 0.206) MPa at 40 ºC. Two types of additives namely (carbon black-asphalt) and (SBR-asphalt) were tried as rejuvenators with three percentages of (0.5, 1 and 1.5) % by weight of asphalt cement along with two ratios of AC (1 and 2) % have been implemented as rejuvenator and blended with the reclaimed asphalt concrete. Aged materials were obtained from the site. 100% Reclaimed Asphalt Pavement material from the reclaimed mixture is implemented. A

In recent decades, tremendous success has been achieved in the advancement of chemical admixtures for Portland cement concrete. Most efforts have concentrated on improving the properties of concrete and studying the factors that influence on these properties. Since the compressive strength is considered a valuable property and is invariably a vital element of the structural design, especially high early strength development which can be provide more benefits in concrete production, such as reducing construction time and labor and saving the formwork and energy. As a matter of fact, it is influenced as a most properties of concrete by several factors including water-cement ratio, cement type and curing methods employed.
Because of acce

The main objective of this study is to develop predictive models using SPSS software (version 18) for Marshall Test results of asphalt mixtures compacted by Hammer, Gyratory, and Roller compaction. Bulk density of (2.351) gm/cc, at OAC of (4.7) % was obtained as a benchmark after using Marshall Compactor as laboratory compactive effort with 75-blows. Same density was achieved by Roller and Gyratory Compactors using its mix designed methods.

A total of (75) specimens, for Marshall, Gyratory, and Roller Compactors have been prepared, based on OAC of (4.7) % with an additional asphalt contents of more and less than (0.5) % from the optimum value. All specimens have been subjected to Marshall Test. Mathematical model

The current research aims to identify the level of compulsive buying behavior and Histrionic Personality among a sample of primary school teachers for the academic year (2021-2022) and in the light of some variables

(sex, marital status). To measure the Histrionic Personality, the researcher applied two scales to a random stratified sample of (200) male and female teachers. The results showed statistically significant differences in the level of compulsive buying behavior according to the gender variable and in favor of female teachers. There are no statistically significant differences in terms of marital status. There are statistically significant differences in the Histrionic Personality based on gender variables in favor of f

The current research aims to diagnose the type and level of influence of social media, whose dimensions are represented by (attitudes towards social media marketing, knowledge and use of social media, influence on the Internet and social media, following up on social media) on customer behavior in its dimensions (attracting attention, raising Interest, desire creation, customer response), and the research sought to answer questions related to the research problem by testing the main hypotheses to explore correlations and influence between the two variables, and to achieve research hypothesis tests, the field study was used, as the research sample reached (135) individuals from the director and the assistant director And marketing personnel

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod