In today's world, the science of bioinformatics is developing rapidly, especially with regard to the analysis and study of biological networks. Scientists have used various nature-inspired algorithms to find protein complexes in protein-protein interaction (PPI) networks. These networks help scientists guess the molecular function of unknown proteins and show how cells work regularly. It is very common in PPI networks for a protein to participate in multiple functions and belong to many complexes, and as a result, complexes may overlap in the PPI networks. However, developing an efficient and reliable method to address the problem of detecting overlapping protein complexes remains a challenge since it is considered a complex and hard optimization problem. One of the main difficulties in identifying overlapping protein complexes is the accuracy of the partitioning results. In order to accurately identify the overlapping structure of protein complexes, this paper has proposed an overlapping complex detection algorithm termed OCDPSO-Net, which is based on PSO-Net (a well-known modified version of the particle swarm optimization algorithm). The framework of the OCDPSO-Net method consists of three main steps, including an initialization strategy, a movement strategy for each particle, and enhancing search ability in order to expand the solution space. The proposed algorithm has employed the partition density concept for measuring the partitioning quality in PPI network complexes and tried to optimize the value of this quantity by applying the line graph concept of the original graph representing the protein interaction network. The OCDPSO-Net algorithm is applied to a Collins PPI network and the obtained results are compared with different state-of-the-art algorithms in terms of precision ( ), recall ( ), and F-measure ( ). Experimental results confirm that the proposed algorithm has good clustering performance and has outperformed most of the existing recent overlapping algorithms. .
Wireless Multimedia Sensor Networks (WMSNs) are a type of sensor network that contains sensor nodes equipped with cameras, microphones; therefore the WMSNS are able to produce multimedia data such as video and audio streams, still images, and scalar data from the surrounding environment. Most multimedia applications typically produce huge volumes of data, this leads to congestion. To address this challenge, This paper proposes Modify Spike Neural Network control for Traffic Load Parameter with Exponential Weight of Priority Based Rate Control algorithm (MSNTLP with EWBPRC). The Modify Spike Neural Network controller (MSNC) can calculate the appropriate traffi
... Show MoreNow that most of the conventional reservoirs are being depleted at a rapid pace, the focus is on unconventional reservoirs like tight gas reservoirs. Due to the heterogeneous nature and low permeability of unconventional reservoirs, they require a huge number of wells to hit all the isolated hydrocarbon zones. Infill drilling is one of the most common and effective methods of increasing the recovery, by reducing the well spacing and increasing the sweep efficiency. However, the problem with drilling such a large number of wells is the determination of the optimum location for each well that ensures minimum interference between wells, and accelerates the recovery from the field. Detail
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This recearch is about studying the novel (doorstep’s women) by the Iraqi
narrator Hadia Hussian, and I choose Semiolog as a Curriculum for this
critical approach, because I think that this Semiotic curriculum has the ability
to read the Subjects and the narrative constructions. Which form the structure
of the novel starting from the little to the characters.
The focus is on many narrative constructions in the novel we have
studied the semiology of the tittle, the semiology of the cover, of the color, the
names of the characters and the semiology of the female characters.
First the focus of the novel is on the women’s characters because most
of it’s characters are women. Secondly because these
In this paper we proposed the method of X-ray fluorescence (XRF) determination of some essential trace elements in medicinal herbs and vitamin-mineral complexes at the level of 100-101 mg/ml. To increase sensitivity and selectivity of the determination we simple and effective approach based on the extraction of metal ions from aqueous solutions with chemically modified polyurethane foam sorbents followed by direct XRF analysis. The conditions of sorption preconcentration of Co(II), Ni(II) and Zn(II) ions with modified sorbents were optimized. The proposed approach is used for the determination of trace elements in several kinds of medicinal herbs (coltsfoot leaves, nettle leaves and yarrow herb) and vitamin-mineral
... Show MoreA common approach to the color image compression was started by transform
the red, green, and blue or (RGB) color model to a desire color model, then applying
compression techniques, and finally retransform the results into RGB model In this
paper, a new color image compression method based on multilevel block truncation
coding (MBTC) and vector quantization is presented. By exploiting human visual
system response for color, bit allocation process is implemented to distribute the bits
for encoding in more effective away.
To improve the performance efficiency of vector quantization (VQ),
modifications have been implemented. To combines the simple computational and
edge preservation properties of MBTC with high c
Objective: To measure the serum levels of Fetuin-A, ischemia-modified albumin (IMA), and ferritin in hospitalized patients with severe COVID-19in Baghdad, Iraq. Moreover, to determine these biomarkers' cut-off valuesthat differentiate between severely ill patients and control subjects. Methods: This case-control study was done from 15 September to the end of December 2021 and involved a review of the files and collectionof blood samples from patients (n=45, group1) hospitalized in COVID-19 treatment centersbecause of severe symptoms compared tohealthy subjects as controls (n=44, group2). Results: Fetuin-A serum levels were not statistically different between patients and controls. In contrast, IMA and ferritin levels were significan
... Show MoreThe nuclear structure included the matter, proton and neutron densities of the ground state, the nuclear root-mean-square (rms) radii and elastic form factors of one neutron 23O and 24F halo nuclei have been studied by the two body model of within the harmonic oscillator (HO) and Woods-Saxon (WS) radial wave functions. The calculated results show that the two body model within the HO and WS radial wave functions succeed in reproducing neutron halo in these exotic nuclei. Moreover, the Glauber model at high energy has been used to calculated the rms radii and reaction cross section of these nuclei.
The neutron, proton, and matter densities of the ground state of the proton-rich 23Al and 27P exotic nuclei were analyzed using the binary cluster model (BCM). Two density parameterizations were used in BCM calculations namely; Gaussian (GS) and harmonic oscillator (HO) parameterizations. According to the calculated results, it found that the BCM gives a good description of the nuclear structure for above proton-rich exotic nuclei. The elastic form factors of the unstable 23Al and 27P exotic nuclei and those of their stable isotopes 27Al and 31P are studied by the plane-wave Born approximation. The main difference between the elastic form factors of unstable nuclei and the
... Show MoreThe purpose of this research is to investigate the impact of corrosive environment (corrosive ferric chloride of 1, 2, 5, 6% wt. at room temperature), immersion period of (48, 72, 96, 120, 144 hours), and surface roughness on pitting corrosion characteristics and use the data to build an artificial neural network and test its ability to predict the depth and intensity of pitting corrosion in a variety of conditions. Pit density and depth were calculated using a pitting corrosion test on carbon steel (C-4130). Pitting corrosion experimental tests were used to develop artificial neural network (ANN) models for predicting pitting corrosion characteristics. It was found that artificial neural network models were shown to be
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