The efficient behavior of a low-concentrating photovoltaic-thermal system with a micro-jet channel (LCPV/T-JET) and booster mirror reflector is experimentally evaluated here. Micro-jets promote the thermal management of PV solar cells by implementing jet water as active cooling, which is still in the early stages of development. The booster mirror reflector concentrates solar irradiance into solar cells and improves the thermal, electrical, and combined efficiencies of the LCPV/T-JET system. The LCPV/T-JET system was tested under ambient weather conditions in the city of Bangi, Selangor, Malaysia, and all data was recorded between 10:00 a.m. and 4:00 p.m. Parametric studies were conducted to compare the performance of the LCPV/T-JET system

A new ligand (H4L) and its complexes with ( ZnII, CdII and HgII) were prepared. This ligand was prepared in two steps. In the first step a solution of terephthaldehyde in methanol was reacted under reflux with 1,2-phenylenediamine to give an precursor compound which reacted in the second step with 2,4-dihydroxybenzaldehyde to give the ligand. The complexes were then synthesized by direct reaction of the corresponding metal chloride with the ligand. The ligand and complexes were characterized by spectroscopic methods FT-IR, UV-Vis, 1 HNMR, and atomic absorption, chloride content, HPLC, mole-ratio determination. in addition to conductivity measurement. The data of these measurements suggest a distorted tetrahedral geometry for ZnII, C

<p><strong>Objective: </strong>The aim of our study was to compare between flavonoids and phenolic acids contents of leaves and fruits of <em>Melia azedarach</em> since no phytochemical investigation had done previously in Iraq.</p><p><strong>Methods: </strong>The leaves and fruits of <em>Melia azedarach </em>were extracted by soxhlet using 80% ethanol then the dried extract was suspended in water and fractionated using petroleum ether, chloroform, ethyl acetate, and n-butanol. The n-butanol fraction was hydrolyzed by acid and partitioned with ethyl acetate. The different fractions containing flavonoids and phenolic acids were analyzed by HPLC and HPTLC.</p><

This research discussed, the process of comparison between the regression model of partial least squares and tree regression, where these models included two types of statistical methods represented by the first type "parameter statistics" of the partial least squares, which is adopted when the number of variables is greater than the number of observations and also when the number of observations larger than the number of variables, the second type is the "nonparametric statistic" represented by tree regression, which is the division of data in a hierarchical way. The regression models for the two models were estimated, and then the comparison between them, where the comparison between these methods was according to a Mean Square

Rutting has a significant impact on the pavements' performance. Rutting depth is often used as a parameter to assess the quality of pavements. The Asphalt Institute (AI) design method prescribes a maximum allowable rutting depth of 13mm, whereas the AASHTO design method stipulates a critical serviceability index of 2.5 which is equivalent to an average rutting depth of 15mm. In this research, static and repeated compression tests were performed to evaluate the permanent strain based on (1) the relationship between mix properties (asphalt content and type), and (2) testing temperature. The results indicated that the accumulated plastic strain was higher during the repeated load test than that during the static load tests. Notably, temperatur

Analysis the economic and financial phenomena and other requires to build the appropriate model, which represents the causal relations between factors. The operation building of the model depends on Imaging conditions and factors surrounding an in mathematical formula and the Researchers target to build that formula appropriately. Classical linear regression models are an important statistical tool, but used in a limited way, where is assumed that the relationship between the variables illustrations and response variables identifiable. To expand the representation of relationships between variables that represent the phenomenon under discussion we used Varying Coefficient Models

The aim of the research is to study the comparison between (ARIMA) Auto Regressive Integrated Moving Average and(ANNs) Artificial Neural Networks models and to select the best one for prediction the monthly relative humidity values depending upon the standard errors between estimated and observe values . It has been noted that both can be used for estimation and the best on among is (ANNs) as the values (MAE,RMSE, R2) is )0.036816,0.0466,0.91) respectively for the best formula for model (ARIMA) (6,0,2)(6,0,1) whereas the values of estimates relative to model (ANNs) for the best formula (5,5,1) is (0.0109, 0.0139 ,0.991) respectively. so that model (ANNs) is superior than (ARIMA) in a such evaluation.