Potential data interpretation is significant for subsurface structure characterization. The current study is an attempt to explore the magnetic low lying between Najaf and Diwaniyah Cities, In central Iraq. It aims to understand the subsurface structures that may result from this anomaly and submit a better subsurface structural image of the region. The study area is situated in the transition zone, known as the Abu Jir Fault Zone. This tectonic boundary is an inherited basement weak zone extending towards the NW-SE direction. Gravity and magnetic data processing and enhancement techniques; Total Horizontal Gradient, Tilt Angle, Fast Sigmoid Edge Detection, Improved Logistic, and Theta Map filters highlight source boundaries and the

After this systematic presentation of the phenomenon of rotation of formulas, ie the construction of the verb and the verb, and the narrated narratives therein differed among the readers, it became clear to us how the difference was clear between reading and the other, and how readers have varied in their readings of the verb, As we have noted through our modest research that the phenomenon of building the verb for the actor and the effect have included the act of both past and present tense, and not limited to a specific time, and this difference in reading was not limited to a particular environment, but beyond To more than one environment This is evidenced by the readings of various readers from the environment of Kufa, Basra, Mecca,

The research study focuses on the efficient and accurate detection and determination of cobalt ions. The detection method involves the formation of brilliant green aggregates with calcium hexacyanoferrate in the presence of nitric acid. (Nagham-four sources of white snow light-emitting diodes arranged in three rows corresponding to three detectors) (The NAG-4SX3-3D Analyzer is an optical, chemical, electronic, and detection tool that receives a cumulative signal (no amplification is required). The total distance travelled is 760 mm with regard to YZ(mV) - tsec (dmm). It was selected for its precise calculation of the energy transducer profile. The linear range for measuring cobalt (II) ions is 0.05 to 20 mM. For concentrations of 5

Platinum nanoparticles (PtNPs) exhibit promising biomedical properties, but concerns about biocompatibility and synthesis-related toxicity remain. This study aimed to develop eco-friendly PtNPs using aqueous broccoli extract as a natural reducing and stabilizing agent, and to assess their multifunctional biomedical potential. PtNPs were synthesized through sonochemical reduction of K₂PtCl₆ in broccoli extract, followed by purification and comprehensive physicochemical characterization. UV–Vis confirmed nanoparticle formation at 253 nm, while XRD and FTIR analyses verified the crystalline FCC structure and phytochemical capping. TEM revealed mainly spherical PtNPs with an average core size of 14.83 ± 7.67 nm. Conversely, DLS showe

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob