Chemical pesticides have an impact on other living organisms in addition to their intended target organisms. Any chemical pesticide is therefore made safe for use by examining its biological characteristics and side effects. The present study was aimed at determining the resistance efficiency of six bacterial isolates obtained from malathion-contaminated soils. Bacteria were isolated from soil samples collected in Adhamiya, Baghdad, Iraq. Biochemical tests and VITEK 2 compact equipment were used to identify the bacterial isolates. Primary and secondary screening tests were conducted on the bacterial isolates for resistance against malathion pesticides. The optimal bacterial growth conditions were determined in malathion-contaminated media.

This study investigates the influence of silver oxide (Ag2O) concentration on the optical characteristics of phosphate bioactive glasses (PBGs). PBGs have emerged as promising alternatives to conventional silicate glasses in the medical field due to their excellent bioactivity and chemical resistance. Samples with varying Ag2O concentrations (0, 0.25, 0.5, and 0.75g) were sintered at 780°C for 2 hrs in an electric furnace. The samples were subjected to Fourier transfer infrared spectroscopy (FTIR), ultraviolet-visible (UV-Vis) spectroscopy, and photoluminescence (PL) tests to assess their functional groups and optical properties. By analyzing the FTIR spectrum of phosphate bioactive glass containing different amounts of Ag2O, it is

Background: elastomeric impression materials are indicated when a high degree of accuracy is required, due to their excellent properties like details reproduction, dimensional stability and tear strength but with main two disadvantages those are their hydrophilicity as well as the absence of antibacterial activity. This study aimed to evaluate the effect of incorporation of 0.5% wt Ag-Zn zeolite into condensation silicone through the following tests; setting time, dimensional stability, reproduction of details, wettability, and hardness . Materials and methods: one hundred specimens were constructed of condensation silicone, divided into two groups for the first 50 specimens one0.5% by wt Ag -Zn zeolite was added, keeping the other fifty sp

The aim of present work is to improve mechanical and fatigue properties for Aluminum alloy7049 by using Nano composites technique. The ZrO₂ with an average grain diameter of 30-40 nm, was selected as Nano particles, to reinforce Aluminum alloy7049 with different percentage as, 2, 4, 6 and 7 %. The Stir casting method was used to fabricate the Nano composites materials due to economical route for improvement and processing of metal matrix composites. The experimental results were shown that the adding of zirconium oxide (ZrO₂) as reinforced material leads to improve mechanical properties. The best percentage of improvement of mechanical properties of 7049 AA was with 4% wt. of ZrO₂ about (7.76% ) for ultim

Two simple methods spectrophotometric were suggested for the determination of Cefixime (CFX) in pure form and pharmaceutical preparation. The first method is based without cloud point (CPE) on diazotization of the Cefixime drug by sodium nitrite at 5Cº followed by coupling with ortho nitro phenol in basic medium to form orange colour. The product was stabilized and measured 400 nm. Beer’s law was obeyed in the concentration range of (10-160) μg∙mL^-1 Sandell’s sensitivity was 0.0888μg∙cm^-1, the detection limit was 0.07896μg∙mL^-1, and the limit of Quantitation was 0.085389μg∙mL^-1.The second method was cloud point extraction (CPE) with using  Trtion X-114 as surfactant. Beer

In this research, the problem of multi- objective modal transport was formulated with mixed constraints to find the optimal solution. The foggy approach of the Multi-objective Transfer Model (MOTP) was applied. There are three objectives to reduce costs to the minimum cost of transportation, administrative cost and cost of the goods. The linear membership function, the Exponential membership function, and the Hyperbolic membership function. Where the proposed model was used in the General Company for the manufacture of grain to reduce the cost of transport to the minimum and to find the best plan to transfer the product according to the restrictions imposed on the model.

Abstract  

Magnetic abrasive finishing (MAF) process is one of non-traditional or advanced finishing methods which is suitable for different materials and produces high quality level of surface finish where it uses magnetic force as a machining pressure. A set of experimental tests was planned according to Taguchi orthogonal array (OA) L27 (3⁶) with three levels and six input parameters. Experimental estimation and optimization of input parameters for MAF process for stainless steel type 316 plate work piece, six input parameters including amplitude of tooth pole, and number of cycle between teeth, current, cutting speed, working gap, and finishing time, were performed by design of experiment

This study is conducted to evaluate the therapeutic and antioxidant effect of lemon juice on some hematological and biochemical parameters. Thirty female mice used in this study were exposed to oxidative stress through giving them hydrogen peroxide in drinking water for 30 days. Animals randomly distributed over 3 groups, each group contained 10 animals and treated as follows: T1 control group (drinking distilled water only), T2 (0.75% hydrogen peroxide in drinking water) and T3 (0.75% hydrogen peroxide in drinking water with daily drenching with 1 mL lemon juice). At the end of the experiment, blood samples were collected from animals for evaluating the following hematological and biochemical parameters: Haemoglobin concentration (Hb),

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet