The pillars of sustainable development are representing the interface between environmental, economic, and social sustainability. Sustainable development is a method of planning and managing construction projects to reduce the effect of the construction process on the environment so that there is a balance between environmental capabilities and the human needs of present and future generations. Usually, Environmental sustainability is most important and effective in construction projects. The environment suffers from significant negative impacts as a result of the implementation of construction projects; therefore, this study aims to identify the effecting factors on environmentally sustainable development. The methodology of this s

Previous experimental studies have suggested that hot mixed asphalt (HMA) concrete using hydrated lime (HL) to partially replace the conventional limestone dust filler at 2.5% by the total weight of all aggregates showed an optimum improvement on several key mechanical properties, fatigue life span and moisture susceptibility. However, so far, the knowledge of the thermal response of the modified asphalt concrete and thermal influence on the durability of the pavement constructed are still relatively limited but important to inform pavement design. This paper, at first, reports an experimental study of the tensile fatigue life of HMA concrete mixes designed for wearing layer application. Tests were conducted under three different temperatur

Spatial data observed on a group of areal units is common in scientific applications. The usual hierarchical approach for modeling this kind of dataset is to introduce a spatial random effect with an autoregressive prior. However, the usual Markov chain Monte Carlo scheme for this hierarchical framework requires the spatial effects to be sampled from their full conditional posteriors one-by-one resulting in poor mixing. More importantly, it makes the model computationally inefficient for datasets with large number of units. In this article, we propose a Bayesian approach that uses the spectral structure of the adjacency to construct a low-rank expansion for modeling spatial dependence. We propose a pair of computationally efficient estimati

Breast 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

The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra

The study aimed to analyze the relationship between the internal public debt and the public budget deficit in Iraq during the period 2010–2020 using descriptive and analytical approaches to the data of the financial phenomenon. Furthermore, to track the development of public debt and the percentage of its contribution to the public budget of Iraq during the study period. The study showed that the origin of the debt with its benefits consumes a large proportion of oil revenues through what is deducted from these revenues to pay the principal debt with interest, which hinders the development process in the country. It has been shownthat although there was a surplus in some years of study, it was not

BN Rashid, International Journal of Research in Social Sciences and Humanities, 2019 - Cited by 1

DBNRHM Sami, International Journal of Research in Social Sciences and Humanities, 2020

The aim of this study was ‎the‎ discrimination of Salmonella‎‎ isolated from chicken and their feed ‎and drinking water for the epidemiological control of salmonellosis. Totally, 289 samples, ‎including 217 chicken cloaca swabs, 46 water, and 26 feed samples were collected from five ‎different farms in Karbala governorate, Iraq. Conventional bacteriology tests, API 20E, Vitek 2, ‎and serology were used for bacterial identification. Random amplified polymorphic ‎DNA (RAPD)-polymerase chain reaction (PCR) was applied to analyze the genetic relationships ‎among Salmonella‎‎ isolates. The isolation rate of Salmonella‎‎ spp. was 21.1% (61/289). While the ‎water samples constituted the highest rate (30.4%), a rate of