This research aims to study the important of the effect of analysis of covariance manner for one of important of design for multifactor experiments, which called split-blocks experiments design (SBED) to deal the problem of extended measurements for a covariate variable or independent variable (X) with data of response variable or dependent variable Y in agricultural experiments that contribute to mislead the result when analyze data of Y only. Although analysis of covariance with discussed in experiments with common deign, but it is not found information that it is discussed with split-Blocks experiments design (SBED) to get rid of the impact a covariance variable. As part application actual field experiment conducted, begun at

According to the importance of the conveyor systems in various industrial and service lines, it is very desirable to make these systems as efficient as possible in their work. In this paper, the speed of a conveyor belt (which is in our study a part of an integrated training robotic system) is controlled using one of the artificial intelligence methods, which is the Artificial Neural Network (ANN). A visions sensor will be responsible for gathering information about the status of the conveyor belt and parts over it, where, according to this information, an intelligent decision about the belt speed will be taken by the ANN controller. ANN will control the alteration in speed in a way that gives the optimized energy efficiency through

Expanded use of antibiotics may increase the ability of pathogenic bacteria to develop antimicrobial resistance. Greater attention must be paid to applying more sustainable techniques for treating wastewater contaminated with antibiotics. Semiconductor photocatalytic processes have proven to be the most effective methods for the degradation of antibiotics. Thus, constructing durable and highly active photocatalytic hybrid materials for the photodegradation of antibiotic pollutants is challenging. Herein, FeTiO3/Fe-doped g-C3N4 (FTO/FCN) heterojunctions were designed with different FTO to FCN ratios by matching the energy level of semiconductors, thereby developing effective direct Z-type heterojunctions. The photodegradation behaviors of th

A group of amino derivatives [4-aminobenzenesulfonamide,4-amino-N¹ methylbenzenesulfonamide, or N¹-(4-aminophenylsulfonyl)acetamide] bound to carboxyl group of mefenamic acid a well known nonsteroidal anti-inflammatory drugs (NSAIDs) were designed and synthesized for evaluation as a potential anti-inflammatory agent.  In vivo acute anti-inflammatory activity of the final compounds (9, 10 and 11) was evaluated in rat using egg-white induced edema model of inflammation in a dose equivalent to (7.5mg/Kg) of mefenamic acid. All tested compounds produced a significant reduction in paw edema with respect to the effect of propylene glycol 50% v/v (control group). Moreover, the 4-amino-N-methylbenzenesulfonamide derivative (c

 A new series of Sulfamethoxazole derivatives was prepared and examined for antifibrinolytic and antimicrobial activities. Sulfamethoxazole derivatives bear heterocyclic moieties such as 1,3,4-thiadiazine {3},  pyrazolidine-3,5-diol {4} 6-hydroxy-1,3,4-thiadiazinane-2-thione {5} and [(3-methyl-5-oxo-4,5-dihydro-1H-pyrazol-4-yl)diazenyl] {8}. Their structures were elucidated by spectral methods (FT-IR, H¹-NMR). Physical properties are also determined for all compound derivatives.  Recently prepared compounds were tested for their antimicrobial activity in the laboratory. Each screened compound showed good tendency to moderate antimicrobial activity.

<span lang="EN-US">The need for robotics systems has become an urgent necessity in various fields, especially in video surveillance and live broadcasting systems. The main goal of this work is to design and implement a rover robotic monitoring system based on raspberry pi 4 model B to control this overall system and display a live video by using a webcam (USB camera) as well as using you only look once algorithm-version five (YOLOv5) to detect, recognize and display objects in real-time. This deep learning algorithm is highly accurate and fast and is implemented by Python, OpenCV, PyTorch codes and the Context Object Detection Task (COCO) 2020 dataset. This robot can move in all directions and in different places especially in