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

based search on two variables two main (Administrative empowerment ) and (technical innovation) target detection relationship and influence between the five dimensions (the delegation of authority , personnel training , effective communication, work teams , motivating employees) and
(technical innovation) conducted research in General Company for electrical Industries , and through the sample included the views of managers in the various administrative levels poll .

And adopted a researcher at a major tool for data collection is questionnaire designed to find, as was the contents of the questionnaire analysis according to the Statistical Information System ( Spss), The (55) to identi

In this work, a vertical pulsating heat pipe heat exchanger (PHPHE)  was designed for waste heat recovery, exchanging thermal energy between two air streams in a counterflow configuration. The heat exchanger consists of six rows, each row consists of one pulsating heat pipe (PHP), and each PHP has six turns. The working fluid used in the heat pipe was acetone with fill ratios of 50%, 60%, and 70%. The effect of evaporator inlet temperature at 40, 45, and 50°C and air velocity at 0.5, 0.7, and 0.9 m/s on the pulsating heat pipes consisting of three sections- evaporator, condenser, and adiabatic, whose dimensions were 25 x 25 x 10 cm, was studied. At the same time, the condenser temperature was maintained at 26°C. The system’s th

Electrochemical Grinding (ECG) process is a mechanically assisted electrochemical process for material processing. The process is able to successfully machine electrically conducting harder materials at faster rate with improved surface finish and dimensional control. This research studies the effect of applied current, electrolyte concentration, spindle speed and the gap between workpiece and tool on hardness and material removal rate during electrochemical grinding for stainless steel 316. The characteristic features of the electrochemical grinding process are explored through Taguchi-design-based experimental studies. The better hardness can be obtained at 10 A of the current, 150 g/l of the electrolyte concentration, 0.3 mm of gap an

Guanine has a variety of roles in chemistry, from its basic function in the storing and transferring genetic information to its usages in synthetic chemistry and other fields. Because of its distinct structure and biological importance, it is a fundamental component of contemporary study in organic chemistry and molecular biology. In this review, we focused on covering the synthetic pathways of various derivatives of guanine from the year 2000 until the present. As a result of the guanine molecule containing multiple functional groups, this gives us the ability to prepare several guanines such as O6-alkylating guanines, O6-benzylguanines, 8-aza-O6-benzylguanines, 9-substituted guanines, guanine-azo derivatives, guanine Schiff bases, guanin

 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.

Document source identification in printer forensics involves determining the origin of a printed document based on characteristics such as the printer model, serial number, defects, or unique printing artifacts. This process is crucial in forensic investigations, particularly in cases involving counterfeit documents or unauthorized printing. However, consistent pattern identification across various printer types remains challenging, especially when efforts are made to alter printer-generated artifacts. Machine learning models are often used in these tasks, but selecting discriminative features while minimizing noise is essential. Traditional KNN classifiers require a careful selection of distance metrics to capture relevant printing