In this study, the flexural performance of a new composite beam–slab system filled with concrete material was investigated, where this system was mainly prepared from lightweight cold-formed steel sections of a beam and a deck slab for carrying heavy floor loads as another concept of a conventional composite system with a lower cost impact. For this purpose, seven samples of a profile steel sheet–dry board deck slab (PSSDB/PDS) carried by a steel cold-formed C-purlins beam (CB) were prepared and named “composite CBPDS specimen”, which were tested under a static bending load. Specifically, the effects of the profile steel sheet (PSS) direction (parallel or perpendicular to the span of the specimen) using different C-purlins c

Copper (1) oxide nanoparticles together with matrix polymers of polyvinyl alcohol (PVA) and polyaniline (PANI) composite films were synthesized, as these materials are of importance in optoelectronic applications. ‎Nanoparticles of Cu₂O were produced by chemical precipitation. Polymerization of aniline was carried out through polymerization in an acidic medium. Structural, thermal, and optical properties of PVA+PANI/Cu₂O nanocomposite were inspected by x-ray diffraction (XRD), scanning electron microscopy (SEM), fourier-transform infrared (FTIR), differential scanning calorimeter (DSC) and ultraviolet-visible spectroscopy (UV-Vis spectroscopy). X-ray diffraction peaks at 29.53°, 36.34°, and 42.22° indicated the

Background: despite the rise in the incidence of renal cell carcinoma attributed to availability of medical imaging, a considerable decline in mortality is an association. Morbidity-wise, the shift from radical nephrectomy to partial nephrectomy is the trend for now. Multiple scoring systems have been introduced over the past decades to help surgeons choose between radical and partial nephrectomy. One commonly used system is the RENAL nephrometry score that was first introduced by Kutikov and Uzzo in 2009.

Objective: to evaluate the role of RENAL nephrometry scoring system in predicting the surgical technique to use to resect renal masses and associated perioperative outcomes.

Vast percentage of the Hor Al-Dalmaj area is covered with sand dunes fields due to desertification. Therefore, it is vital to research these dunes to limit their bad action on the natural environment by defining the mineralogical composition of these sand dunes deposited around Hor Al-Dalmaj lake between Wast and Al-Qasisiyah Governorates to determine the provenance or the source of these dunes. Barchan and Nabkha dunes represent the main types that are recognized. The dimensions of barchan dunes are recognizing by a height range of about 0.5 to 3m, with lateral extension ranging from 2 to 15m and longitudinal extinction ranging from 3 to 15m. While the dimensions of nabkha dunes range from 10 cm to 2m in length and 15cm to 2m high. Acco

Water quality planning relies on Biochemical Oxygen Demand BOD. BOD testing takes five days. The Particle Swarm Optimization (PSO) is increasingly used for water resource forecasting. This work designed a PSO technique for estimating everyday BOD at Al-Rustumiya wastewater treatment facility inlet. Al-Rustumiya wastewater treatment plant provided 702 plant-scale data sets during 2012-2022. The PSO model uses the daily data of the water quality parameters, including chemical oxygen demand (COD), chloride (Cl-), suspended solid (SS), total dissolved solids (TDS), and pH, to determine how each variable affects the daily incoming BOD. PSO and multiple linear regression (MLR) findings are compared, and their performance is evaluated usin

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a pandemic of coronavirus disease 2019 (COVID-19) which represents a global public health crisis. Based on recent published studies, this review discusses current evidence related to the transmission, clinical characteristics, diagnosis, management and prevention of COVID-19. It is hoped that this review article will provide a benefit for the public to well understand and deal with this new virus, and give a reference for future researches.

Thin films ZrO₂: MgO nanostructure have been synthesized by a radio frequency magnetron plasma sputtering technique at different ratios of MgO (0,6, 8 and  10)% percentage to be used as the gas sensor for nitrogen dioxide NO₂. The samples were investigated by X-ray diffraction (XRD), atomic force microscopy (AFM), scanning electron microscopy (SEM), energy-dispersive X-ray (EDX) and sensing properties were also investigated. The average particle size of all prepared samples was found lower than 33.22nm and the structure was a monoclinic phase. The distribution of grain size was found lower than36.3 nm and uninformed particles on the surface. Finally, the data of sensing properties have been discussed, where the

The Multiplicative Cyclic Group has been used to construct a New Digital Algebraic Generator System (NDAGS). This cryptosystem can be classified as a stream cipher cryptosystem. In this paper we will estimate the efficiency and security of the (NDAGS) by using the Basic Efficiency Criteria (BEC). A comparison has made between the some known generators and (NDAGS). The results of applying the BEC and the comparison results proof the high efficiency of the (NDAGS).

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