is survey article is a comprehensive discussion on Intelligent Optimization of Wireless Sensor Networks through Bio-Inspired Computing. e marvelous perfection of biological systems and its different aspects for optimized solutions for non-biological problems is presented here in detail. In the current research inclination, hiring of biological solutions to solve and optimize different aspects of arti�cial systems' problems has been shaped into an important �eld with the name of bio-inspired computing. We have tabulated the exploitation of key constituents of biological system for developing bio-inspired systems to represent its importance and emergence in problem solving trends. We have presented how the metaphoric relationship is developed between the two biological and non-biological systems by quoting an example of relationship between prevailing wireless system and the natural system. Interdisciplinary research is playing a splendid contribution for various problems' solving. e process of combining the individuals' output to form a single problem solving solution is depicted in three-stage ensemble design. Also the hybrid solutions from computational intelligence-based optimization are elongated to demonstrate the emergent involvement of these inspired systems with rich references for the interested readers. It is concluded that these perfect creations have remedies for most of the problems in non-biological system.
BackgroundMultimeric naphthoquinones are redox-active compounds that exhibit antineoplastic, antiprotozoal, and antiviral activities. Due to their multimodal effect on perturbation of cellular oxidative state, these compounds hold great potential as therapeutic agents against highly proliferative neoplastic cells. In our previous work, we developed a series of novel dimeric naphthoquinones and showed that they were selectively cytotoxic to human acute myeloid leukemia (AML), breast and prostate cancer cell lines. We subsequently identified the oxidoreductase NAD(P)H dehydrogenase, quinone 1 (NQO1) as the major target of dimeric naphthoquinones and proposed a mechanism of action that entailed induction of a futile redox cycling.ResultsHere, for the first time, we describe a direct physical interaction between the bromohydroxy dimeric naphthoquinone E6a and NQO1. Moreover, our studies reveal an extensive binding interface between E6a and the isoalloxazine ring of the flavin adenine dinucleotide (FAD) cofactor of NQO1 in addition to interactions with protein side chains in the active site. We also present biochemical evidence that dimeric naphthoquinones affect the redox state of the FAD cofactor of NQO1. Comparison of the mode of binding of E6a with those of other chemotherapeutics reveals unique characteristics of the interaction that can be leveraged in future drug optimization efforts.ConclusionThe first structure of a dimeric naphthoquinone-NQO1 complex was reported, which can be used for design and synthesis of more potent next generation dimeric naphthoquinones to target NQO1 with higher affinity and specificity.Electronic supplementary materialThe online version of this article (doi:10.1186/s12900-016-0052-x) contains supplementary material, which is available to authorized users.
In mobile wireless sensor network (MWSN), the lifetime of the network largely depends on energy efficient routing protocol. In the literature, cluster leader (CL) is selected based on remaining energy of mobile sensor nodes to enhance sensor network lifetime. In this study, a novel connectivity-based Low-Energy Adaptive Clustering Hierarchy-Mobile Energy Efficient and Connected (LEACH-MEEC) routing protocol was proposed, where CL is selected based on connectivity among neighboring nodes and the remaining energy of mobile sensor nodes. Consequently, it improves data delivery, network lifetime and balances the energy consumption. We studied various performance metrics including the number of alive nodes (NAN), remaining energy (RE) and packet delivery ratio (PDR). Our proposed LEACH-MEEC outperforms all other algorithms due to the connectivity metric. Moreover, the performance of mobility models was investigated through graphical and statistically tabulated results. The results show that Reference Point Group Mobility model (RPGM) is better than other mobility models.
In the ongoing era of flourishing e-commerce, people prefer online purchasing products and services to save time. These online purchase decisions are mostly influenced by the reviews/opinions of others who already have experienced them. Malicious review spam. This study aims to evaluate the performance of ensemble learning on review spam detection with selected features extracted from real and semi-real-life datasets. We study various performance metrics including Precision, Recall, F-Measure, and Receiver Operating Characteristic (RoC). Our proposed ensemble learning module (ELM) with ChiSquared feature selection technique outperformed all others with 0.851 Precision.
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