Extracorporeal shock wave lithotripsy (ESWL) is considered a standard treatment for nephrolith or kidney stones measuring less than 20 mm. Anatomical, machine-related, and stone factors play pivotal roles in treatment outcomes, the latter being the leading role. This paper examined the relationship between stone density on native CT scans and ESWL treatment to remove renal stones concerning several treatments. One hundred and twenty patients (64 males and 56 females) were enrolled and completed the study from April 2019 to September 2020. Inclusion criteria were a single renal pelvis stone of 5–20 mm to be treated for the first time in adult patients with no urinary or musculoskeletal anatomical abnormalities. We assessed patients

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

Using an electrochemical polymerization technique at room temperature, poly nicotine amide (PNA) was produced from the monomer nicotine amide (NA) in aqueous solution. The structure of polymer layer generated on the stainless steel surface (316 L) (working electrode) is investigated by Fourier Transmission Infrared Region (FT-IR). The anti-corrosion activity of polymer coating on the stainless steel (SS 316 L) is investigated by electrochemical polarization in 0.20M solution of HCl at 293-323K. The graphene -modified polymer film-coated SS had greater protection efficiency (PE percent) when compared to Nano ZnO -modified polymer film-coated SS. For the corrosion process of SS 316 L, kinetic and thermo-dynamic parameters of activatio

Phase change materials (PCMs) such as paraffin wax can be used to store or release large amount of energy at certain temperature at which their solid-liquid phase changes occurs. Paraffin wax that used in latent heat thermal energy storage (LHTES) has low thermal conductivity. In this study, the thermal conductivity of paraffin wax has been enhanced by adding different mass concentration (1wt.%, 3wt.%, 5wt.%) of (TiO₂) nano-particles with about (10nm) diameter. It is found that the phase change temperature varies with adding (TiO₂) nanoparticles in to the paraffin wax. The thermal conductivity of the composites is found to decrease with increasing temperature. The increase in thermal conductivity ha

Spin coating technique has been applied in this work to prepared Xerogel films doped with Rhodamine 6G laser dyes. The solid host of laser dye modifies its spectroscopic properties with respect to liquid host. During the spin coating process the dye molecules suffer from changing their environment. The effects of three parameters were studied here: the spinning speed, multilayer coating and formaldehyde addition

In this study, polymeric coating was developed by incorporating nano graphene in the polymer blend with applications to oil storage tanks. The oil storage tanks samples were brought from the oil Pipeline Company / Doura refinery in Baghdad. The coating polymer was formed with a blend (epoxy resin and repcoat ZR). The proportion of mixing the mixture was 3:1:1 epoxy resin 21.06 gm: repcoat ZR 10.53 gm: hardener 10.53 gm. The blend/graphene was prepared using in stui-polymerization method with different weight percentage 1, 3, 5, and 7 wt % added to blend. The resulting solution was put in a glass tube on a magnetic stirrer for one hour at a temperature of 40 °C. The result of contact angle and water absorption the best ratio of 3wt

Abstract Software-Defined Networking (commonly referred to as SDN) is a newer paradigm that develops the concept of a software-driven network by separating data and control planes. It can handle the traditional network problems. However, this excellent architecture is subjected to various security threats. One of these issues is the distributed denial of service (DDoS) attack, which is difficult to contain in this kind of software-based network. Several security solutions have been proposed recently to secure SDN against DDoS attacks. This paper aims to analyze and discuss machine learning-based systems for SDN security networks from DDoS attack. The results have indicated that the algorithms for machine learning can be used to detect DDoS