Azo derivative ligand[H3L] have been synthesized by the reaction of diazonium salt of p-amino benzoic acid with orcinol in(1:1)mole ratio. The bidente ligand was reacted with the metal ions MnII,FeIIandCrIIIin(2:1)mole ratio via reflux in ethanol using Et3N as a base to give complexes of the general formula: [ M(H2L)2(H2O)x]Cly The synthesized compounds were characterized by spectroscopic methods[ I.R , UV-Vis, A.A and H1 NMR]along with melting point, chloride content and conductivity measurements. The complexes were screend for their in vitro antibacterial activity against one strain of staphylococcus as Gram(+) positive and one strain of pseudomonas as Gram(-) Negative, using the agar diffusion technique.

Hydroxide upon the chemical composition and dry matter(DM) and organic matter(OM) digestibility . Rice straw was treated with 4% sodium hydroxide using 30% of DM basis moisture, and incubated at 40 ºC for 40 days., DM digestibility (DMD) was significantly affected (P<0.01) by the treatment , where DMD increased The objective of this experiment was to study the effect of physical form (long ,chopped and ground ) and washing rice straw treated with sodium from 42.32 to 45.41% , OM digestibility (OMD) and total digestible nutrient (TDN) increased(P<0.05) from 47.38 and 49.33 to 49.67 and 52.83% ,respectively. While hemicellulose content increased (P<0.05 ) from 261.71 to 268.17 gm/kg DM ,and metabolizable energy (ME) from 7.11 to 7.48 MJ/

The present work presents design and implementation of an automated two-axis solar tracking system using local materials with minimum cost, light weight and reliable structure. The tracking system consists of two parts, mechanical units (fixed and moving parts) and control units (four LDR sensors and Arduino UNO microcontroller to control two DC servomotors). The tracking system was fitted and assembled together with a parabolic trough solar concentrator (PTSC) system to move it according to information come from the sensors so as to keep the PTSC always perpendicular to sun rays. The experimental tests have been done on the PTSC system to investigate its thermal performance in two cases, with tracking system (case 1) and without trackin

           In this research, the preparation of a chemically activated carbon from date stones by using electric and microwave assisted K₂CO₃ activation was studied. The effect of radiation power, radiation time, and impregnation ratio on the yield and Iodine number on the activated carbons was investigated. The activated carbon characterizations were examined by its surface area, pore structure analysis, bulk density, moisture content, ash content, iodine number, FTIR, and scanning electron microscopy (SEM). The adsorption capacity was also studied by adsorption of fluoroquinolones antibiotics, CIP, NOR, and LEVO, by the prepared activated carbon.

Background: Abdominoplasty is one of the commonest surgical procedures that performed for those patients who had skin laxity, strive and muscle rectur diastasis. Combined using of liposuction and abdominoplasty it can give better result than traditional abdominoplasty with fear complications. Patient and Method: A total number of 25 female patients with age ranging between 27-55 years were underwent lipoabdominoplasty. With extensive liposuction of abdominal wall and selective undermining together with muscle plication. All of our patients had body mass index more than 30. Patients satisfaction and complication were documented postoperatively. Result: All of our patients had no Major complications and the postoperative period passed unevent

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

Pseudomonas aeruginosa is emerging opportunistic clinical pathogens. Clinical isolates of P. aeruginosaresist wide spectrum of antibiotics and form biofilm. The comparison study between clinical and environmental of P. aeruginosa in terms of biofilm formation and antibiotic resistance is very scanty. Thus, in current study microtiter plate technique was used to measure the biofilm formation by several clinical and environmental isolates. Moreover, the antibiotic susceptibility of these bacteria was evaluated by VITIK 2 techniques. The relationship between the antibiotic susceptibility and biofilm formation was evaluated for clinical and environmental isolates. Clinical and environm

Ball and Plate (B&P) system is a benchmark system in the control engineering field that has been used to verify many control methods. In this paper the design of a sliding mode . controller has been investigated and verified in real-time via implementation on a real ball and plate system hardware. The mathematical model has been derived and the necessary parameters have been measured. The sliding mode controller has been designed based on the obtained mathematical model. The resulting controller has been implemented using the Arduino Mega 2560 and a ball and plate system built completely from scratch. The Arduino has been programmed by the Arduino support target for Simulink. Three test signals has been used for verification purposes

Abstract

Characterized by the Ordinary Least Squares (OLS) on Maximum Likelihood for the greatest possible way that the exact moments are known , which means that it can be found, while the other method they are unknown, but approximations to their biases correct to 0(n^-1) can be obtained by standard methods. In our research expressions for approximations to the biases of the ML estimators (the regression coefficients and scale parameter) for linear (type 1) Extreme Value Regression Model for Largest Values are presented by using the advanced approach depends on finding the first derivative, second and third.