Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

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.

    In this work, the spirurid nematode Hartertia gallinarum was reported in the intestine of the spotted sandgrouse, Pterocles senegallus, collected in three different locations: Ga'ara Depression, Iraqi Western Desert, Zurbatiyah and Al-Attariyah, Middle of Iraq. Description and measurements of the nematode were given. The role of termites in the infection of P. senegallus with H. gallinarum was discussed. Occurrence of H. gallinarum in P. senegallus represents a new host record.

Previous studies indicated that supplementation with antioxidants has a protective effects against oxidative stress–induced damage in type 2 diabetes. In this study we evaluated the antioxidant effects of melatonin on the oxidative stress parameters and microalbuminuria in type 2 DM patients. 30 patients with type 2 DM were treated with 3mg/day melatonin for 90 days. Erythrocytes and plasma MDA and glutathione, fasting plasma glucose, %Hb_AIC, microalbuminuria, total plasma protein and lipid profile were measured each 30 days and compared with those obtained from 20 healthy controls.

A decrease in MDA levels associated with the elevation in GSH levels were observed, compared with the pre–treatment levels.

The 17 α-ethinylestradiol (EE2) adsorption from aqueous solution was examined using a novel adsorbent made from rice husk powder coated with CuO nanoparticles (CRH). Advanced analyses of FTIR, XRD, SEM, and EDSwere used to identify the classification parameters of a CRH-like surface morphology, configuration, and functional groups. The rice husk was coated with CuO nanoparticles, allowing it to create large surface area materials with significantly improved textural qualities with regard to functional use and adsorption performance, according to a detailed characterization of the synthesized materials. The adsorption process was applied successfully with elimination effectiveness of 100% which can be kept up to 61.3%. The parameters of ads

 The microdrilling and nanodrilling holes are produced by a Q-switched Nd :YAG laser (1064 nm) interaction with 8009 Al alloy using nanoparticles. Two kinds of nanoparticles were used with this alloy. These nanoparticles are tungsten carbide (WC) and silica carbide (SiC). In this work, the microholes and nanoholes have been investigated with different laser pulse energies (600, 700 and 800)mJ, different repetition rates (5Hz and 10Hz) and different concentration of nanoparticles (90%, 50% and 5% ). The results indicate that  the microholes and nanoholes have been achieved when the laser pulse energy is 600 mJ, laser repetition rate is 5Hz, and the concentration of the  nanoparticles (for the two types of n

Nanoparticles are a special group of materials with unique features and extensive applications in diverse fields. The use of nanoparticles of some metals is a viable solution to stop infectious diseases due to the antimicrobial properties of these nanoparticles. The present work demonstrates the effect of silver nanoparticles (AgNPs) on the antibacterial activity of four different antibiotics (amoxicillin, ceftriaxone, chloramphenicol, and penicillin) against eleven Gram-positive and Gram-negative isolates. Disk diffusion method was used to determine the antibacterial activity of various classes of antibiotics in the absence and presence of sub-inhibitory silver nanoparticles of concentration (80 microgram/ml). A synergistic effect was o