The study was conducted to estimate the economic losses caused by insect mole cricket Gryllotalpa gryllotalpa on some agricultural crops and Potato tubers in collage of Agriculture- Abu Ghraib season 2012-2013. Study showed Mole cricket caused percentage of infestation in spring potato tubers variety Luciana reached to 11.61% and the percentage of loss in weight of tubers reached 18.88%. The study showed that addition of animal manure (organic fertilizer) to the soil when planting potatoes in the autumn increased the incidence of infestation and the number of tunnels caused by mole cricket which led to from increased economic losses. When matured potato tubers were left for a longer period in the soil percentage of infestation by mole cr

M(II) Ions using amino acid L- proline as a primary ligand and either Nicotinamide or 8- hydroxyqinoline as secondary ligand, respectively: a. The mixed ligand complexes of composition,[M(pro)2(na)2]. b. The mixed ligand complexes of composition , Na[M(pro)2(Q)]. Where proline (C5H9NO2) symbolized as pro H , Nicotinamide (C6H6N2O) symbolized as (NA) , 8- hydroxyqinoline, (C9H7NO2) symbolized as (8-HQ). The ligands and the metal chlorides were brought into reaction at room temperature (37ºc) in ethanol as solvent .The reaction required the following molar ratios [(1:2:2) metal:2NA:2pro-] and [(1:1:2) metal:Q:2pro-] with M+2 ions, where M = [Mn (II), Co(II), Ni(II), Cu(II), Zn(II), Cd(II) and pd(II)]. Products were found to be solid crystall

the visual and aesthetic characteristics of the city depending on understanding several levels of visual and aesthetic characteristics to the city, starting with the study of the physical characteristics and morphology of the city in general, and urban style to it, and then study of visual composition of the city from the optical components that affect the composition of the image (visual composition) of the city represent by pathways, borders, regions and the specific features as classified by (Kevin Lynch), and then studying the details and the attention of all elements that would confer the beautiful appearance as necessary for the needs of society and the environment in general, for example, interest in the distribution and c

Background Microorganisms and fungal growth especially Candida albicans, on soft denture lining material are the most common problem which can lead to chronic mucosal inflammation. The aim of this study was to evaluate the effect of zirconium nanoparticles into acrylic-based heat cured soft denture lining material against Candida albicans, and the amount of zirconium ion release of soft liner/ZrNPs composite. Furthermore, evaluate shear bond strength after ZrNPs addition to soft liner. Materials and methods: Zirconium nanoparticles were added into acrylic-based soft denture liner in various percentages (1%, and 1.5% by weight). Two hundred and fifty specimens were arranged and isolated into four groups as per the test to be done The antifu

The impacts of numerous important factors on the Energy Absorption (EA) of torsional Reinforced Concrete (RC) beams strengthened with external FRP is the main purpose and innovation of the current research. A total of 81 datasets were collected from previous studies, focused on the investigation of EA behaviour. The impact of nine different parameters on the Torsional EA of RC-beams was examined and evaluated, namely the concrete compressive strength (f’c), steel yield strength (fy), FRP thickness (tFRP), width-to-depth of the beam section (b/h), horizontal (ρh) and vertical (ρv) steel ratio, angle of twist (θu), ultimate torque (Tu), and FRP ultimate strength (fy-FRP). For the evaluation of the energy absorption capacity at di

This study aims to model the flank wear prediction equation in metal cutting, depending on the workpiece material properties and almost cutting conditions. A new method of energy transferred solution between the cutting tool and workpiece was introduced through the flow stress of chip formation by using the Johnson-Cook model. To investigate this model, an orthogonal cutting test coupled with finite element analysis was carried out to solve this model and finding a wear coefficient of cutting 6061-T6 aluminum and the given carbide tool.

The current study focuses on utilizing machine learning (ML) models in optimizing and predicting laser-induced surface cold hardening in aluminum alloy 6061-O using a pulsed fiber laser. Three input features were utilized: power density (Pd), frequency (f), and pulse overlap (OV), with surface hardness as the matching aim. A set of ML models, including XGBoost and Adaptive Ensemble, was employed. The dataset was preprocessed for normalization and outlier handling, hyperparameter tuning, and assessment through the grid search and cross-validation, and model performance was evaluated using the coefficient of determination (R²) and mean square error (MSE) metrics. The Linear regression and Random Forest regression models were excluded