Detecting protein complexes in protein-protein interaction (PPI) networks is a challenging problem in computational biology. To uncover a PPI network into a complex structure, different meta-heuristic algorithms have been proposed in the literature. Unfortunately, many of such methods, including evolutionary algorithms (EAs), are based solely on the topological information of the network rather than on biological information. Despite the effectiveness of EAs over heuristic methods, more inherent biological properties of proteins are rarely investigated and exploited in these approaches. In this paper, we proposed an EA with a new mutation operator for complex detection problems. The proposed mutation operator is formulated under four expressions depending on the type of gene sub-ontology. To demonstrate the performance of the proposed evolutionary based complex detection algorithm, the Saccharomyces Cerevisiae (yeast) PPI network is used in the evaluation. The results reveal that the proposed algorithm achieves more accurate complex structures than the counterpart heuristic algorithms and the canonical evolutionary algorithm based on the topological-aware mutation operator.
The hazardous metabolic effects of treating schizophrenia patients with olanzapine comprise serotonin 2C receptor (5-HT2C) antagonists. Metabolic side effects of antipsychotic drugs, including lipid abnormalities, disturbed glucose metabolism, and weight gain, can have a major impact on treating psychiatric patients. The intent of this study was to investigate whether there is an associated link between the genetic polymorphism at -759C>T in the promoter region of the 5-hydroxytryptamine 2C receptor (HTR2C) gene and the metabolic syndrome driven by olanzapine in schizophrenia patients. A cross-sectional study that involved fifty hospitalized patients with schizophrenia. The patients were split into two groups (metabolic and non-metab
... Show MoreAir pollution is one of the important problems facing Iraq. Air pollution is the result of uncontrolled emissions from factories, car exhaust electric generators, and oil refineries and often reaches unacceptable limits by international standards. These pollutants can greatly affect human health and regular population activities. For this reason, there is an urgent need for effective devices to monitor the molecular concentration of air pollutants in cities and urban areas. In this research, an optical system has been built consisting of aHelium-Neonlaser,5mWand at 632.8 nm, a glass cell with a defined size, and a power meter(Gentec-E-model: uno) where a scattering of the laser beam occurs due to air pollution. Two pollutants were examin
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreThe meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when
... Show MoreA nano-sensor for nitrotyrosine (NT) molecule was found by studying the interactions of NT molecule with new B24N24 nanocages. It was calculated using density functionals in this case. The predicted adsorption mechanisms included physical and chemical adsorption with the adsorption energy of −2.76 to −4.60 and −11.28 to −15.65 kcal mol−1, respectively. The findings show that an NT molecule greatly increases the electrical conductivity of a nanocage by creating electronic noise. Moreover, NT adsorption in the most stable complexes significantly affects the Fermi level and the work function. This means the B24N24 nanocage can detect NT as a Φ–type sensor. The recovery time was determined to be 0.3 s. The sensitivity of pure BN na
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreIn this work Laser wireless video communication system using intensity modualtion direct
detection IM/DD over a 1 km range between transmitter and receiver is experimentally investigated and
demonstrated. Beam expander and beam collimeter were implemented to collimete laser beam at the
transmitter and focus this beam at the receiver respectively. The results show that IM/DD communication
sysatem using laser diode is quite attractive for transmitting video signal. In this work signal to noise
ratio (S/N) higher than 20 dB is achieved in this work.
The research aimed to study the job satisfaction of the staff of the Federal board of supreme Audit and its relation to the effectiveness of their performance, The questionnaire was adopted as a main tool in the collection of data and information from a random sample of (54) employees of the Federal board of supreme Audit. In light of this, the data were collected and analyzed and the hypotheses were tested using the statistical program (SPSS).
The researchers reached a number of conclusions, the most important of which were: (1) the respondents' response to the variables of job satisfaction and the effectiveness of the performance were medium; (2) there was a significant relationship between job satisfaction and performance effe
... Show MoreA new optoelectronic flow injection method is proposed for the determination of ferrous ions (Fe 2+ ) based on thiocyanate complexation to form a deep-red FeSCN 2+ complex.
Tin oxide: titanium oxide: bismuth oxide (SnO2 )1–x(TiO 2 :Bi 2O3 ) x composites with different loading ratios (0, 0.1, 0.15, 0.2, 0.25 and 0.3) have numerous new application in microelectronics, sensors, and capacitors. This work concerned with the synthesis of (SnO 2 )1–x(TiO 2 :Bi 2O3 ) xcomposites as well as, thin films which were deposited on glass substrates as well as, silicon wafers by using pulsed laser deposition. The diffraction pattern confirms the anatase teteragonal phase of undoped tin oxide. It was observed some peaks related with titanium and bismuth oxides appeared at high loading ratios. Upon the transmission-spectra analysis, the undoped samples declared transmittance 60–67% in a visible spectrum, and the energy ga
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