The modification of hydrophobic rock surfaces to the water-wet state via nanofluid treatment has shown promise in enhancing their geological storage capabilities and the efficiency of carbon dioxide (CO2) and hydrogen (H2) containment. Despite this, the specific influence of silica (SiO2) nanoparticles on the interactions between H2, brine, and rock within basaltic formations remains underexplored. The present study focuses on the effect of SiO2 nanoparticles on the wettability of Saudi Arabian basalt (SAB) under downhole conditions (323 K and pressures ranging from 1 to 20 MPa) by using the tilted plate technique to measure the contact angles between H2/brine and the rock surfaces. The findings reveal that the SAB's hydrophobicity intensif

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

  The current research is interested in the objective study of revitalizing the religious sites and the extent to which they achieve the pragmatic and semantic ends, because they are derived from history and civilization and have a clear impact over the recipient. The research question is (what are the techniques of developing the spaces of the religious shrines in accordance with revitalizing the interior spaces within them?).
The research aims at determining the weak and strong points in the process of revitalizing the interior spaces in the religious shrines.
The theoretical framework consists of two parts: the first addressed the revitalization in the interior design, and the second addressed the religious shrines and th

The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

The process involved isolating E. faecium from the gut of honeybees, screening the bacterium for bacteriocin-like inhibitory substance (BLIS), evaluating its impact on the expression of the mexA gene in multidrug-resistant (MDR) P. aeruginosa, and determining the role of bacteriocin in treating infected wounds in mice through histopathological examination. After evaluating the best circumstances for producing BLIS, it was discovered that glucose was a superior carbon source and yeast extract was the best source of nitrogen. The pH was found to be 5, the ideal incubation time was 72 hours, and ammonium sulfate salt was used for partial purification at 80% saturation. The identification of MDR P. aeruginosa isolates from pus infection