In this paper, we investigate the basic characteristics of "magnetron sputtering plasma" using the target V₂O₅. The "magnetron sputtering plasma" is produced using "radio frequency (RF)" power supply and Argon gas. The intensity of the light emission from atoms and radicals in the plasma measured by using "optical emission spectrophotometer", and the appeared peaks in all patterns match the standard lines from NIST database and employed are to estimate the plasma parameters, of computes electron temperature and the electrons density. The characteristics of V₂O₅ sputtering plasma at multiple discharge provisos are studied at the "radio frequency" (RF) power ranging from 75 - 150 Wat

Background: This in vitro study compares a novel calcium-phosphate etchant paste to conventional 37% phosphoric acid gel for bonding metal and ceramic brackets by evaluating the shear bond strength, remnant adhesive and enamel damage following water storage, acid challenge and fatigue loading. Material and Methods: Metal and ceramic brackets were bonded to 240 extracted human premolars using two enamel conditioning protocols: conventional 37% phosphoric acid (PA) gel (control), and an acidic calcium-phosphate (CaP) paste. The CaP paste was prepared from β-tricalcium phosphate and monocalcium phosphate monohydrate powders mixed with 37% phosphoric acid solution, and the resulting phase was confirmed using FTIR. The bonded premolars were exp

This research deals with the study of top soil electrical conductive regions located within Baghdad City. The research included measuring the dissolved soil material extraction Electrical Conductivity (EC) with an aqueous solution for the top (0-30 cm) soil layer of the study area. As the electrical conductivity values increase by increasing the amount of dissolved salts in principle, we can consider that the aim of this research is to predict the amount and distribution of (soil contamination with salts) which is represented by the (Salt Index), this factor calculated for each soil representative sample taken from the region with a depth of (30 cm). Laboratory (EC) test values measured by the use of solutions (EC) digital meter for the ex

Maximum power point tracking (MPPT) is used in photovoltaic (PV) systems to enhance efficiency and maximize the output power of PV module, regardless the variation of temperature, irradiation, and the electrical characteristics of the load. A new MPPT system has been presented in this research, consisting of a synchronous DC-DC step-down Buck converter controlled by an Arduino microcontroller based unit. The MPPT process with Perturb and Observe method is performed with a DC-DC converter circuit to overcome the problem of voltage mismatch between the PV modules and the loads. The proposing system has high efficiency, lower cost and can be easily modified to handle more energy sources. The test results indicate that the u

This paper presents ABAQUS simulations of fully encased composite columns, aiming to examine the behavior of a composite column system under different load conditions, namely concentric, eccentric with 25 mm eccentricity, and flexural loading. The numerical results are validated with the experimental results obtained for columns subjected to static loads. A new loading condition with a 50 mm eccentricity is simulated to obtain additional data points for constructing the interaction diagram of load-moment curves, in an attempt to investigate the load-moment behavior for a reference column with a steel I-section and a column with a GFRP I-section. The result comparison shows that the experimental data align closely with the simulation

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an