Due to the significant role in understanding cellular processes, the decomposition of Protein-Protein Interaction (PPI) networks into essential building blocks, or complexes, has received much attention for functional bioinformatics research in recent years. One of the well-known bi-clustering descriptors for identifying communities and complexes in complex networks, such as PPI networks, is modularity function. The contribution of this paper is to introduce heuristic optimization models that can collaborate with the modularity function to improve its detection ability. The definitions of the formulated heuristics are based on nodes and different levels of their neighbor properties. The modularity function and the formulated heuristics are then injected into the mechanism of a single objective Evolutionary Algorithm (EA) tailored specifically to tackle the problem, and thus, to identify possible complexes from PPI networks. In the experiments, different overlapping scores are used to evaluate the detection accuracy in both complex and protein levels. According to the evaluation metrics, the results reveal that the introduced heuristics have the ability to harness the accuracy of the existing modularity while identifying protein complexes in the tested PPI networks.
Fluid-structure interaction method is performed to predict the dynamic characteristics of axial fan system. A fluid-structure interface physical environment method (monolithic method) is used to couple the fluid flow solver with the structural solver. The integration of the three-dimensional Navier-Stokes equations is performed in the time Doman, simultaneously to the integration of the three dimensional structural model. The aerodynamic loads are transfer from the flow to structure and the coupling step is repeated within each time step, until the flow solution and the structural solution have converged to yield a coupled solution of the aeroelastic set of equations. Finite element method is applied to solve numerically
... Show MoreCoronavirus is considered the first virus to sweep the world in the twenty-first century, it appeared by the end of 2019. It started in the Chinese city of Wuhan and began to spread in different regions around the world too quickly and uncontrollable due to the lack of medical examinations and their inefficiency. So, the process of detecting the disease needs an accurate and quickly detection techniques and tools. The X-Ray images are good and quick in diagnosing the disease, but an automatic and accurate diagnosis is needed. Therefore, this paper presents an automated methodology based on deep learning in diagnosing COVID-19. In this paper, the proposed system is using a convolutional neural network, which is considered one o
... Show MoreDBNRAHA Hameed, IJRSSH PUBLICATION, 2018
During the period from September 2013 till the end of July 2014 ,a total of 340 birds Passer domesticus were collected from Tikrit city . The study revealed the infection of birds with seven species of cestoda helminthes , belonging to the genus Raillietin . These species included R. tetragona , R. echinobothrida , R. cesticellus and R. ransomi with prevalence infection of 36.1% , 30.1% . 15.0 % and 1.8 % respectively . And the genus Choanotaenia . These species included C. infundibulum and C. passerine with pervatence infection of 15.0% and 0.6% respectively . And the genus Anonchotuenia . The species included A.globate with prevantence infection 1.2% .
... Show MoreBackgroun1d: Polycythemia is defined as a central Hematocrit of at least 65%. Its` incidence is increased in babies who have intrauterine growth restriction (IUGR), are small for gestational age (SGA), and are born post term. Many infants with polycythemia are asymptomatic. However, it may be associated with feeding problems and lethargy.
Objectives: This work aimed to study the polycythemic neonates admitted to neonatal care unit in children welfare teaching hospital, medical city complex, Baghdad, including demographic features, risk factors, management and early outcome.
Patients and Methods: A descriptive study was carried out over
... Show MoreIn this study different methodological approaches are used and described by many features (indicators) of complex socio-economic process. Outcome of analysis has the most reliable and acceptable representation of the studied process specific to chosen case. In order to solve problems in this area (depending on the situation, case under consideration), methods from two groups are most often used: multidimensional comparative analysis and multi-criteria decision analysis. The first of these cases concern problems at the macro level (socio-economic development, demographic situation, population's living standards, etc.), in which the decisionmaker's participation is relatively small (eg the selection of diagnostic variables or expert assess
... Show MoreA food chain model in which the top predator growing logistically has been proposed and studied. Two types of Holling’s functional responses type IV and type II have been used in the first trophic level and second trophic level respectively, in addition to Leslie-Gower in the third level. The properties of the solution are discussed. Since the boundary dynamics are affecting the dynamical behavior of the whole dynamical system, the linearization technique is used to study the stability of the subsystem of the proposed model. The persistence conditions of the obtained subsystem of the food chain are established. Finally, the model is simulated numerically to understand the global dynamics of the food chain un
... Show MoreThe diseases presence in various species of fruits are the crucial parameter of economic composition and degradation of the cultivation industry around the world. The proposed pear fruit disease identification neural network (PFDINN) frame-work to identify three types of pear diseases was presented in this work. The major phases of the presented frame-work were as the following: (1) the infected area in the pear fruit was detected by using the algorithm of K-means clustering. (2) hybrid statistical features were computed over the segmented pear image and combined to form one descriptor. (3) Feed forward neural network (FFNN), which depends on three learning algorithms of back propagation (BP) training, namely Sca
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