BACKGROUND: Diabetes Mellitus is a complex chronic illness that has increased significantly around the world and is expected to affect 628 million in 2045. Undiagnosed type 2 diabetes may affect 24% - 62% of the people with diabetes; while the prevalence of prediabetes is estimated to be 470 million cases by 2030. AIM OF STUDY: To find the percentage of undiagnosed diabetes and prediabetes in a slice of people aged ≥ 45years, and relate it with age, gender, central obesity, hypertension, and family history of diabetes. METHODS: A cross sectional study that included 712 healthy individuals living in Baghdad who accepted to take part in this study and fulfilling the inclusion and exclusion criteria.

This paper concerns is the preparation and characterization of a bidentate ligand [4-(5,5- dimethyl-3-oxocyclohex-1-enylamino)-N-(5-methylisoxazol-3-yl) benzene sulfonamide]. The ligand was prepared from fusing of sulfamethoxazole and dimedone at (140) ºC for half hour. The complex was prepared by refluxing the ligand with a bivalent cobalt ion using ethanol as a solvent. The prepared ligand and complex were identified using Spectroscopic methods. The proposed tetrahedral geometry around the metal ions studied were concluded from these measurements. Both molar ratio and continuous variation method were studied to determine metal to ligand ratio (M:L). The M to L ratio was found to be (1:1). The adsorption of cobalt complex was carried out

In this work magnetite/geopolymer composite (MGP) were synthesized using a chemical co-precipitation technique. The synthesized materials were characterized using several techniques such as: “X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), vibrating sample-magnetometer (VSM), field-emission scanning electron microscopy (FE-SEM), energy dispersive X-ray spectroscopy (EDS), Brunauer–Emmett–Teller (BET) and Barrentt-Joyner-Halenda (BJH)” to determine the structure and morphology of the obtained material. The analysis indicated that metal oxide predominantly appeared at the shape of the spinel structure of magnetite, and that the presence of nano-magnetite had a substantial impact on the surface area and pore st

The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

Type 2 diabetes mellitus is a progressive and chronic disease manifested by β-cell dysfunction and improved insulin resistance. Higher levels of urokinase-type plasminogen activator receptors have been found to predict morbidity and mortality among diabetic patients with cardiac disease.

Drones play a vital role in the fundamental aspects of Industry 4.0 by converting conventional warehouses into intelligent ones, particularly in the realm of barcode scanning. Various potential issues frequently arise during barcode scanning by drones, specifically when the drone camera has difficulty obtaining distinct images due to certain factors, such as distance, capturing the image whilst flying, noise in the environment and different barcode dimensions. In addressing these challenges, this study proposes an approach that combines a proportional–integral–derivative (PID) controller with image processing techniques. The PID controller is responsible for continuously monitoring the camera’s input, detecting the difference

Background Parkinson’s disease (PD) is currently the fastest-growing neurological disorder in the world. Patients with PD face numerous challenges in managing their chronic condition, particularly in countries with scarce healthcare infrastructure. Objective This qualitative study aimed to delve into neurologists’ perspectives on challenges and gaps in the Iraqi healthcare system that influence the management of PD, as well as strategies to mitigate these obstacles. Method Semi-structured interviews were conducted with neurologists from five different Iraqi provinces, working in both hospitals and private neurology clinics, between November 2024 and January 2025. A thematic analysis approach was employed to identify the main challenge

Massive multiple-input multiple-output (massive-MIMO) is a promising technology for next generation wireless communications systems due to its capability to increase the data rate and meet the enormous ongoing data traffic explosion. However, in non-reciprocal channels, such as those encountered in frequency division duplex (FDD) systems, channel state information (CSI) estimation using downlink (DL) training sequence is to date very challenging issue, especially when the channel exhibits a shorter coherence time. In particular, the availability of sufficiently accurate CSI at the base transceiver station (BTS) allows an efficient precoding design in the DL transmission to be achieved, and thus, reliable communication systems can be obtaine