Abstract      Organic compounds with pyrazole cores have a variety of uses, notably in the pharmaceutical and agrochemical sectors. The interest in creating pyrazole compounds, examining their many features, and looking for potential uses is growing. Our work has concert with synthesis of  chalcones and pyrazolines, then finally pyrazoline-aniline derivatives and evaluation their anti-inflammatory, antibacterial and antifungal activities

This study outlines the synthesis of substituted 1,2,4-triazole derivatives through the cyclization reaction of thiourea derivatives. The process begins with the reaction of different halides with KSCN to produce isothiocyanate derivatives. then followed by a reaction with isonicotinic acid hydrazide to yield thioureas (1-6), with a yield rate of (72-88%). Then, compounds (1-6) were treated with alkaline medium 4 N (NaOH) to produced 1,2,4-triazole derivatives (7-12) with a yield (51-69%).The structure of the prepared compounds was characterized using FTIR,1HNMR and 13CNMR spectroscopy. Some of the synthesized compounds were tested for antimicrobial activity when, compound 9 showed strong activity against gram positive bacteria (Sta

The disposal of textile effluents to the surface water bodies represents the critical issue especially these effluents can have negative impacts on such bodies due to the presence of dyes in their composition. Biological remediation methods like constructed wetlands are more cost-effective and environmental friendly technique in comparison with traditional methods. The ability of vertical subsurface flow constructed wetlands units for treating of simulated wastewater polluted with Congo red dye has been studied in this work. The units were packed with waterworks sludge bed that either be unplanted or planted with Phragmites australis and Typha domingensis. The efficacy of present units was evaluated by monitoring of DO, Temperature, COD

This article aims to establish and evaluate standards for critical equipment and materials in highway projects in Iraq. Delphi technique has been used to analyze, explore, and discover the main criteria and sub-criteria that affect equipment and materials in highway construction projects in Iraq. To determine the correct response to the criteria presented in this study, a program (IBM, SPSS/V25) was used to assess the main criteria and sub-criteria using the mean score (MS) and standard deviation (SD) technique, as well as to check reliability using Cronbach's alpha factor (α). The experts' qualifications and the extent to which the person is ready to commit are both important factors in panel selection. The design of a

 A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.

Grass trimming operation is widely done in Malaysia for the purpose of maintaining highways. Large number of operators engaged in this work encounters high level of noise generated by back pack type grass trimmer used for this purpose. High level of noise exposure gives different kinds of ill effect on human operators. Exact nature of deteriorated work performance is not known. For predicting the work efficiency deterioration, fuzzy tool has been used in present research. It has been established that a fuzzy computing system will help in identification and analysis of fuzzy models fuzzy system offers a convenient way of representing the relationships between the inputs and outputs of a system in the form of IF-THEN rules. The paper presents

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

One of the recent significant but challenging research studies in computational biology and bioinformatics is to unveil protein complexes from protein-protein interaction networks (PPINs). However, the development of a reliable algorithm to detect more complexes with high quality is still ongoing in many studies. The main contribution of this paper is to improve the effectiveness of the well-known modularity density ( ) model when used as a single objective optimization function in the framework of the canonical evolutionary algorithm (EA). To this end, the design of the EA is modified with a gene ontology-based mutation operator, where the aim is to make a positive collaboration between the modularity density model and the proposed