Binary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solving NP-hard problems. The main aim of this study is to make a close examination of the performance of the EAs where modularity and modularity density are selected as two different objective functions. Topology-based modularity and topology-based modularity density are designed to examine the detection ability of the EAs and to compare their performance. To conduct the experiments, two yeast Saccharomyces cerevisiae PPINs are used and evaluated under nine evaluation metrics. The results reveal the potential impact of the topology-based modularity density to outperform the counterpart modularity functions in almost all evaluation metrics.
Overall enthalpy and entropy of complex formation were calculated from stability constant measurements at different tempreture also experimental results
The new Schiff base 1‐[(2‐{1‐[(dicyclohexylamino)‐methyl]‐1H‐indol‐3‐yl}‐ethylimino)‐methyl]naphthalen‐2‐ol (HL) was prepared from 1‐{[2‐(1H‐Indol‐3‐yl)‐ethylimino] methyl}‐naphthalen‐2‐ol and dicyclohexyl amine. From this Schiff base, monomeric complexes [M (L)n (H2O)2 Cl2] with M = Cr, Fe, Mn, Cd, and Hg were synthesized and characterized based on elemental analysis (EA), FT‐IR, mass(MS), UV‐visible, thermal analysis, magnetic moment, and molar conductance. The results showed that the geometrical structural were octahedral geometries for the Cr(III) and Fe(III) complex
The new Schiff base 1‐[(2‐{1‐[(dicyclohexylamino)‐methyl]‐1H‐indol‐3‐yl}‐ethylimino)‐methyl]naphthalen‐2‐ol (HL) was prepared from 1‐{[2‐(1H‐Indol‐3‐yl)‐ethylimino] methyl}‐naphthalen‐2‐ol and dicyclohexyl amine. From this Schiff base, monomeric complexes [M (L)n (H2O)2 Cl2] with M = Cr, Fe, Mn, Cd, and Hg were synthesized and characterized based on elemental analysis (EA), FT‐IR, mass(MS), UV‐visible, thermal analysis, magnetic moment, and molar conductance. The results showed that the geometrical structural were octahedral geometries for the Cr(III) and Fe(III) complex
Researchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l
... Show MoreRock mechanical properties are critical parameters for many development techniques related to tight reservoirs, such as hydraulic fracturing design and detecting failure criteria in wellbore instability assessment. When direct measurements of mechanical properties are not available, it is helpful to find sufficient correlations to estimate these parameters. This study summarized experimentally derived correlations for estimating the shear velocity, Young's modulus, Poisson's ratio, and compressive strength. Also, a useful correlation is introduced to convert dynamic elastic properties from log data to static elastic properties. Most of the derived equations in this paper show good fitting to measured data, while some equations show scatters
... Show MoreThe deployment of UAVs is one of the key challenges in UAV-based communications while using UAVs for IoT applications. In this article, a new scheme for energy efficient data collection with a deadline time for the Internet of things (IoT) using the Unmanned Aerial Vehicles (UAV) is presented. We provided a new data collection method, which was set to collect IoT node data by providing an efficient deployment and mobility of multiple UAV, used to collect data from ground internet of things devices in a given deadline time. In the proposed method, data collection was done with minimum energy consumption of IoTs as well as UAVs. In order to find an optimal solution to this problem, we will first provide a mixed integer linear programming m
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