In this paper, the Reliability Analysis with utilizing a Monte Carlo simulation (MCS) process was conducted on the equation of the collapse potential predicted by ANN to study its reliability when utilized in a situation of soil that has uncertainty in its properties. The prediction equation utilized in this study was developed previously by the authors. The probabilities of failure were then plotted against a range of uncertainties expressed in terms of coefficient of variation. As a result of reliability analysis, it was found that the collapse potential equation showed a high degree of reliability in case of uncertainty in gypseous sandy soil properties within the specified coefficient of variation (COV) for each property. When t

Abstract

     In this research, the morphology and mechanical properties of (Epoxy/PVC) blend were investigated.  (EP/PVC) blend was prepared by manual mixing of epoxy resin with different weight ratios of (Poly vinyl chloride (PVC) after dissolving it in cyclohexanon). Five sheets of polymer blends in wt% included (0%, 5%, 10%, 15% and 20%) of PVC were prepared at room temperature. Tests were carried out to study some mechanical properties for these blends and compared with the properties of pure epoxy. The morphology of the prepared materials was examined to study the compatibility nature between the two polymers under work. It was found that the best ratio of addition is (20%) of PVC.

Sludge from stone-cutting (SSC) factories and stone mines cannot be used as decorative stones, stone powder, etc. These substances are left in the environment and cause environmental problems. This study aim is to produce artificial stone composite (ASC) using sludge from stone cutting factories, cement, unsaturated resin, water, silicon carbide nanoparticles (SiC-NPs), and nano-graphene oxide (NGO) as fillers. Nano graphene oxide has a hydrophobic plate structure that water is not absorbed due to the lack of surface tension on these plates. NGO has a significant effect on the properties of artificial stone due to its high specific surface area and low density in the composite. Its uniform distribution in ASC is very low due to its hydropho

The present study included the effect of chronic exposure for two concentrations of NaC? salt on the biology of fresh water zooplankton species Brachionus calyciflorus (from ^otifera). The concentrations 0.5 , 0.75%o were used for chronic exposure to investigate its effects on the life tables, range of the rate of expectation for further life and reproduction. The rotifer B. calyciflorus was sensitive to salinity and may tried to protect the species by increasing the size (2.22 ind./clutch lor control group and 2.9? for 0.5%o concentration) and number of clutches produced ?.1? clutch/female for control group and 2.9 ' ' ' for 0.75 %0 concentration) beside stimulation the animal to produce the first clutch of eggs earlier? ? small reduction

This review examines how artificial intelligence (AI) including machine learning (ML), deep learning (DL), and the Internet of Things (IoT) is transforming operations across exploration, production, and refining in the Middle Eastern oil and gas sector. Using a systematic literature review approach, the study analyzes AI adoption in upstream, midstream, and downstream activities, with a focus on predictive maintenance, emission monitoring, and digital transformation. It identifies both opportunities and challenges in applying AI to achieve environmental and economic goals. Although adoption levels vary across the region, countries such as Saudi Arabia, the UAE, and Qatar are leading initiatives that align with global sustainability targets.