One of the most interested problems that recently attracts many research investigations in Protein-protein interactions (PPI) networks is complex detection problem. Detecting natural divisions in such complex networks is proved to be extremely NP-hard problem wherein, recently, the field of Evolutionary Algorithms (EAs) reveals positive results. The contribution of this work is to introduce a heuristic operator, called protein-complex attraction and repulsion, which is especially tailored for the complex detection problem and to enable the EA to improve its detection ability. The proposed heuristic operator is designed to fine-grain the structure of a complex by dividing it into two more complexes, each being distinguished with a core protein. Then, it is possible for each of the remaining proteins associated with the original coarse-grained complex to repulse from one of the new generated complexes while attracted by the core protein of the second complex. The topology-based complex detection models presented in the literature are adopted to inter-play with the proposed heuristic operator inside the EA general framework. To assess the performance of the EA when coupled with the proposed heuristic operator, the well known Saccaromycaes Cerevisiae yeast PPI network and one reference set of benchmark complexes created from MIPS are used in the experiments. The results prove the positive impact of the heuristic operator to harness the strength of almost all adopted EA models.
Tested effective Alttafaria some materials used for different purposes, system a bacterial mutagenesis component of three bacterial isolates belonging to different races and materials tested included drug Briaktin
Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural
... Show More
(10)
(4)
The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med
... Show More
(1)
(1)
Geotechnical engineering like any other engineering field has to develop and cope with new technologies. This article intends to investigate the spatial relationships between soil’s liquid limit (LL), plasticity index (PI) and Liquidity index (LI) for particular zones of Sulaymaniyah City. The main objective is to study the ability to produce digital soil maps for the study area and determine regions of high expansive soil. Inverse Distance Weighting (IDW) interpolation tool within the GIS (Geographic Information System) program was used to produce the maps. Data from 592 boreholes for LL and PI and 245 boreholes for LI were used for this study. Layers were allocated into three depth ranges (1 to 2, 2 to 4 and 4 to 6)
... Show More
(6)
The novel coronavirus 2019 (COVID-19) is a respiratory syndrome with similar traits to common pneumonia. This major pandemic has affected nations both socially and economically, disturbing everyday life and urging the scientific community to develop solutions for the diagnosis and prevention of COVID-19. Reverse transcriptase-polymerase chain reaction (RT–PCR) is the conventional approach used for detecting COVID-19. Nevertheless, the initial stage of the infection is less predictable in PCR tests, making early prediction challenging. A robust and alternative diagnostic method based on digital computerised technologies to support conventional methods would greatly help society. Therefore, this paper reviews recent research bas
... Show More
(2)
The Polarographic study of the interaction between ascorbic acid and Ni+2 was carried out at dropping mercury electrode [DME] . This study included the determination of the kinetic parameters (kfh ,n) and thermodynamic parameters such as enthalpy change (H), free energy change (G) and entropy change (S) of Ni+2 complexes with ascorbic acid in 0.1 M KCl solution over the temperature rang of (294-309)K. The electrode processes were irreversible and diffusion controlled.
In this paper, a numerical model for fluid-structure interaction (FSI) analysis is developed for investigating the aeroelastic response of a single wind turbine blade. The Blade Element Momentum (BEM) theory was adopted to calculate the aerodynamic forces considering the effects of wind shear and tower shadow. The wind turbine blade was modeled as a rotating cantilever beam discretized using Finite Element Method (FEM) to analyze the deformation and vibration of the blade. The aeroelastic response of the blade was obtained by coupling these aerodynamic and structural models using a coupled BEM-FEM program written in MATLAB. The governing FSI equations of motion are iteratively calculated at each time step, through exchanging data between
... Show MoreSimulation of the Linguistic Fuzzy Trust Model (LFTM) over oscillating Wireless Sensor Networks (WSNs) where the goodness of the servers belonging to them could change along the time is presented in this paper, and the comparison between the outcomes achieved with LFTM model over oscillating WSNs with the outcomes obtained by applying the model over static WSNs where the servers maintaining always the same goodness, in terms of the selection percentage of trustworthy servers (the accuracy of the model) and the average path length are also presented here. Also in this paper the comparison between the LFTM and the Bio-inspired Trust and Reputation Model for Wireless Sensor Network
... Show More
In this study a new composite nano material was prepared and characterized through the polymerization of inter attuplgie layered m-phenylendiamine with p-kresol. The results indicated that the propagated polymer separated the clay aluminosilicate layers as a two dimensional nano-sheets soaked in the prepared polymer matrix with losing the original fibrous structure of Attuplgite clay.