In this study, the photodegradation of Congo red dye (CR) in aqueous solution was investigated using Au-Pd/TiO2 as photocatalyst. The concentration of dye, dosage of photocatalyst, amount of H2O2, pH of the medium and temperature were examined to find the optimum values of these parameters. It has been found that 28 ppm was the best dye concentration. The optimum amount of photocatalyst was 0.09 g/75 mL of dye solution when the degradation percent was ~ 96 % after irradiation time of 12 hours, while the best amount of hydrogen peroxide was 7μl/75 mL of dye solution at degradation percent ~97 % after irradiation time of 10 hours, whereas pH 5 was the best value to carry out the reaction at the highest degradation percent. In additio

For this research, the utilisation of electrocoagulation (EC) toremove theciprofloxacin (CIP) and levofloxacin (LVX) from aqueous solutions was examined. The effective removal efficiencies are 93.47% for CIP and 88.00% for LVX, under optimum conditions. The adsorption isotherm models with suitable mechanisms were applied to determine the elimination of CIP and LVX utilizingtheEC method. Thefindingsshowed the adsorption of CIP and LVX on iron hydroxide flocs followed the Sips isotherm, with correlation coefficient values (R2) of 0.939 and 0.937. Threekinetic models were reviewed to determine the accurate CIP and LVX elimination methods using the EC method. The results showed that itfittedfor the second-order model, which indicated that the c

The estimation of the parameters of Two Parameters Gamma Distribution in case of missing data has been made by using two important methods: the Maximum Likelihood Method and the Shrinkage Method. The former one consists of three methods to solve the MLE non-linear equation by which the estimators of the maximum likelihood can be obtained: Newton-Raphson, Thom and Sinha methods. Thom and Sinha methods are developed by the researcher to be suitable in case of missing data. Furthermore, the Bowman, Shenton and Lam Method, which depends on the Three Parameters Gamma Distribution to get the maximum likelihood estimators, has been developed. A comparison has been made between the methods in the experimental aspect to find the best meth

The individual average income is considered one of the most used criteria for the distinguishing between the developed and the developing countries, for this reason the efforts of economic development has been construed on increasing the average national income, the investment expenditures is considered one of the basic foundations for economic development operation which lead to the expanding the prodection power of the economy, and increasing the level of national income in an averages greaten than the primary expenditures due to the work and interaction between the multiplier and the accelerator. But the ability of the economic sectors in the generation of national income as a result of the primary expenditures is different fr

The turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. T

The most significant water supply, which is the basis of agriculture, industry and human and wildlife needs, is the river. In order to determine its suitability for drinking purposes, this study aims to measure the Water Quality Index (WQI) of the Tigris River in the Salah Al-Din Province (center of Tikrit), north of Baghdad. For ten (9) physio-chemical parameters, namely turbidity, total suspended sediments, PH, electrical conductivity, total dissolved solids, alkalinity, chloride, nitrogen as nitrate, sulphate, and then transported for examination to the laboratory, water samples were collected from 13 locations along the Tigris river. Using the weighted arithmetic index method, the WQI was measured and found to be 105,87 in up-stream, wh

Submerged arc welding (SAW) process is an essential metal joining processes in industry. The quality of weld is a very important working aspect for the manufacturing and construction industries, the challenges are made optimal process environment. Design of experimental using Taguchi method (L9 orthogonal array (OA)) considering three SAW parameter are (welding current, arc voltage and welding speed) and three levels (300-350-400 Amp. , 32-36-40 V and 26-28-30 cm/min). The study was done on SAW process parameters on the mechanical properties of steel type comply with (ASTM A516 grade 70). Signal to Noise ratio (S/N) was computed to calculate the optimal process parameters. Percentage contributions of each parameter are validated by using an

Autorías: Hadeer Idan Ghanim, Ishraq Mahmood. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 3, 2021. Artículo de Revista en Dialnet.

Background. Endodontic infections caused by remaining biofilm following disinfection with chemical fluids encourage secondary bacterial infection; hence, employing laser pulses to activate the fluids is advised to improve microbial biofilm clearance. This study investigated the performance of Er,Cr:YSGG laser in photon-induced photoacoustic streaming (PIPS) agitation of 5.25% sodium hypochlorite (NaOCl) to enhance the removal of mature Enterococcus faecalis (E. faecalis) biofilms in complex root canal systems. Methods. The mesial roots of the lower first and second molars were separated and inoculated with E. faecalis bacteria for 30 days. The roots were irrigated with 5.25% NaOCl, some of them were agitated with passive ultrasonic

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se