Cooperative relay selection for load balancing with mobility in hierarchical WSNs: A multi-armed bandit approach

© 2013 IEEE. Energy efficiency is the major concern in hierarchical wireless sensor networks(WSNs), where the major energy consumption originates from radios for communication. Due to notable energy expenditure of long-range transmission for cluster members and data aggregation for Cluster Head (CH), saving and balancing energy consumption is a tricky challenge in WSNs. In this paper, we design a CH selection mechanism with a mobile sink (MS) while proposing relay selection algorithms with multi-user multi-armed bandit (UM-MAB) to solve the problem of energy efficiency. According to the definition of node density and residual energy, we propose a conception referred to as a Virtual Head (VH) for MS to collect data in terms of energy efficiency. Moreover, we naturally change the relay selection problem into permutation problem through employing the two-hop transmission in cooperative power line communication, which deals with long-distance transmission. As far as the relay selection problem is concerned, we propose the machine learning algorithm, namely MU-MAB, to solve it through the reward associated with an increment for energy consumption. Furthermore, we employ the stable matching theory based on marginal utility for the allocation of the final one-to-one optimal combinations to achieve energy efficiency. In order to evaluate MU-MAB, the regret is taken advantage to demonstrate the performance by using upper confidence bound (UCB) index. In the end, simulation results illustrate the efficacy and effectiveness of our proposed solutions for saving and balancing energy consumption

Human motion retrieval based on freehand sketch

In this paper, we present an integrated framework of human motion retrieval based on freehand sketch. With some simple rules, the user can acquire a desired motion by sketching several key postures. To retrieve efficiently and accurately by sketch, the 3D postures are projected onto several 2D planes. The limb direction feature is proposed to represent the input sketch and the projected-postures. Furthermore, a novel index structure based on k-d tree is constructed to index the motions in the database, which speeds up the retrieval process. With our posture-by-posture retrieval algorithm, a continuous motion can be got directly or generated by using a pre-computed graph structure. What's more, our system provides an intuitive user interface. The experimental results demonstrate the effectiveness of our method. © 2014 John Wiley & Sons, Ltd

Load-balancing rendezvous approach for mobility-enabled adaptive energy-efficient data collection in WSNs

Copyright © 2020 KSII The tradeoff between energy conservation and traffic balancing is a dilemma problem in Wireless Sensor Networks (WSNs). By analyzing the intrinsic relationship between cluster properties and long distance transmission energy consumption, we characterize three node sets of the cluster as a theoretical foundation to enhance high performance of WSNs, and propose optimal solutions by introducing rendezvous and Mobile Elements (MEs) to optimize energy consumption for prolonging the lifetime of WSNs. First, we exploit an approximate method based on the transmission distance from the different node to an ME to select suboptimal Rendezvous Point (RP) on the trajectory for ME to collect data. Then, we define data transmission routing sequence and model rendezvous planning for the cluster. In order to achieve optimization of energy consumption, we specifically apply the economic theory called Diminishing Marginal Utility Rule (DMUR) and create the utility function with regard to energy to develop an adaptive energy consumption optimization framework to achieve energy efficiency for data collection. At last, Rendezvous Transmission Algorithm (RTA) is proposed to better tradeoff between energy conservation and traffic balancing. Furthermore, via collaborations among multiple MEs, we design Two-Orbit Back-Propagation Algorithm (TOBPA) which concurrently handles load imbalance phenomenon to improve the efficiency of data collection. The simulation results show that our solutions can improve energy efficiency of the whole network and reduce the energy consumption of sensor nodes, which in turn prolong the lifetime of WSNs

Metabolic Pathways Enhancement Confers Poor Prognosis in p53 Exon Mutant Hepatocellular Carcinoma.

RNA-Sequencing (RNA-Seq), the most commonly used sequencing application tool, is not only a method for measuring gene expression but also an excellent media to detect important structural variants such as single nucleotide variants (SNVs), insertion/deletion (Indels), or fusion transcripts. The Cancer Genome Atlas (TCGA) contains genomic data from a variety of cancer types and also provides the raw data generated by TCGA consortium. p53 is among the top 10 somatic mutations associated with hepatocellular carcinoma (HCC). The aim of the present study was to analyze concordant different gene profiles and the priori defined set of genes based on p53 mutation status in HCC using RNA-Seq data. In the study, expression profile of 11 799 genes on 42 paired tumor and adjacent normal tissues was collected, processed, and further stratified by the mutated versus normal p53 expression. Furthermore, we used a knowledge-based approach Gene Set Enrichment Analysis (GSEA) to compare between normal and p53 mutation gene expression profiles. The statistical significance (nominal P value) of the enrichment score (ES) genes was calculated. The ranked gene list that reflects differential expression between p53 wild-type and mutant genotypes was then mapped to metabolic process by KEGG, an encyclopedia of genes and genomes to assign functional meanings. These approaches enable us to identify pathways and potential target gene/pathways that are highly expressed in p53 mutated HCC. Our analysis revealed 2 genes, the hexokinase 2 (HK2) and Enolase 1 (ENO1), were conspicuous of red pixel in the heatmap. To further explore the role of these genes in HCC, the overall survival plots by Kaplan-Meier method were performed for HK2 and ENO1 that revealed high HK2 and ENO1 expression in patients with HCC have poor prognosis. These results suggested that these glycolysis genes are associated with mutated-p53 in HCC that may contribute to poor prognosis. In this proof-of-concept study, we proposed an approach for identifying novel potential therapeutic targets in human HCC with mutated p53. These approaches can take advantage of the massive next-generation sequencing (NGS) data generated worldwide and make more out of it by exploring new potential therapeutic targets

Status epilepticus alters hippocampal PKAβ and PKAγ expression in mice

AbstractObjectivesTo investigate the localization and progressive changes of cyclic-AMP dependent protein kinase (cPKA) in the mouse hippocampus at acute stages during and after pilocarpine induced status epilepticus.MethodsPilocarpine induced status epilepticus mice were sacrificed 30min, 2h or 1 day after the start of a ∼7h lasting status as assessed by video-electroencephalography. Brains were processed for quantitative immunohistochemistry of hippocampal cPKAβ and cPKAγ, and immunohistochemical co-localization of cPKAβ and cPKAγ with calbindin (CB), calretinin (CR), and parvalbumin (PV).ResultsBased on anatomical and morphological assessment, cPKAβ was primarily expressed by principal cells and cPKAγ by interneurons. In CA1, cPKAβ co-localized with 76% of CB, 41% of CR, and 95% of PV-immunopositive cells, while cPKAγ co-localized with 50% of CB, 29% of CR, and 80% of PV-immunopositive cells. Upon induction of status epilepticus, cPKAβ expression was transiently reduced in CA1, whereas cPKAγ expression was sustainably reduced.ConclusioncPKA may play an important role in neuronal hyperexcitability, death and epileptogenesis during and after pilocarpine induced status epilepticus