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

Background. Dental implantation has become a standard procedure with high success rates, relying on achieving osseointegration between the implant surface and surrounding bone tissue. Polyether ether ketone (PEEK) is a promising alternative to traditional dental implant materials like titanium, but its osseointegration capabilities are limited due to its hydrophobic nature and reduced surface roughness. Objective. The aim of the study is to increase the surface roughness and hydrophilicity of PEEK by treating the surface with piranha solution and then coating the surface with epigallocatechin-3-gallate (EGCG) by electrospraying technique. Materials and Methods. The study includes four groups intended to investigate the effect of pir

Unmanned aerial vehicles (UAVs) can provide valuable spatial information products for many projects across a wide range of applications. One of the major challenges in this discipline is the quality of positioning accuracy of the resulting mapping products in professional photogrammetric projects. This is especially true when using low-cost UAV systems equipped with GNSS receivers for navigation. In this study, the influence of UAV flight direction and camera orientation on positioning accuracy in an urban area on the west bank of the Euphrates river in Iraq was investigated. Positioning accuracy was tested in this study with different flight directions and camera orientation settings using a UAV autopilot app (Pix4Dcapture software

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

In this study, a new adsorbent derived from sunflower husk powder and coated in CuO nanoparticles (CSFH) was investigated to evaluate the simultaneous adsorption of Levofloxacin (LEV), Meropenem (MER), and Tetracycline (TEC) from an aqueous solution. Significant improvements in the adsorption capacity of the sunflower husk were identified after the powder particles had been coated in CuO nanoparticles. Kinetic data were correlated using a pseudo-second-order model, and was successful for the three antibiotics. Moreover, high compatibility was identified between the LEV, MER, and TEC, isotherm data, and the Langmuir model, which produced a better fit to suit the isotherm curves. In addition, the spontaneous and exothermic nature of the adsor

The electrical and thermal performance of a typical single pass hybrid photovoltaic/thermal (PV/T) air collector is modeled, simulated and analyzed for two selected case studies in Iraq. An improved mathematical thermo-electrical model is derived in terms of design, operating and climatic parameters of the hybrid solar collector to evaluate its important characteristics: collector flow and heat removal factors, PV maximum power point and its temperature coefficient, and overall power and efficiency. Unlike previous PV/T thermal models, the present model is obtained with some additions and corrections in radiation and convection heat coefficients for the top loss and for the air duct with more applicable sky temperature correlation. The well

Abstract: The power and the size of the final spot of the laser beam reaching the target are very important requirements in most of the laser applications and fields such as medical, military, and scientific, so studying laser propagation in the atmosphere is a very important topic. The propagation of the laser beam through the atmosphere is subject to several attenuation processes that deplete the power and expand the beam. Through the simulation results of the free electron laser within the visible region of the electromagnetic spectrum (400-700nm), it was found that the attenuation increases with decreasing wavelength. Laser propagation in the presence of rain and snow leads to a very large loss of power compared to propagation i