It is expected that in the near future wireless sensor network (WSNs) will be more widely used in the mobile environment, in applications such as Autonomous Underwater Vehicles (AUVs) for marine monitoring and mobile robots for environmental investigation. The sensor nodes' mobility can easily cause changes to the structure of a network topology, and lead to the decline in the amount of transmitted data, excessive energy consumption, and lack of security. To solve these problems, a kind of efficient Topology Control algorithm for node Mobility (TCM) is proposed. In the topology construction stage, an efficient clustering algorithm is adopted, which supports sensor node movement. It can ensure the balance of clustering, and reduce the energy consumption. In the topology maintenance stage, the digital signature authentication based on Error Correction Code (ECC) and the communication mechanism of soft handover are adopted. After verifying the legal identity of the mobile nodes, secure communications can be established, and this can increase the amount of data transmitted. Compared to some existing schemes, the proposed scheme has significant advantages regarding network topology stability, amounts of data transferred, lifetime and safety performance of the network.
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http://dx.doi.org/10.3390/s151229782 | DOI Listing |
BioData Min
December 2024
School of Computing, Queen's University, 557 Goodwin Hall, 21-25 Union St, Kingston, K7L 2N8, Ontario, Canada.
Background: Epistasis, the phenomenon where the effect of one gene (or variant) is masked or modified by one or more other genes, significantly contributes to the phenotypic variance of complex traits. Traditionally, epistasis has been modeled using the Cartesian epistatic model, a multiplicative approach based on standard statistical regression. However, a recent study investigating epistasis in obesity-related traits has identified potential limitations of the Cartesian epistatic model, revealing that it likely only detects a fraction of the genetic interactions occurring in natural systems.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Radiology, First Affiliated Hospital of Dalian Medical University, No. 222 Zhongshan Road, Xigang District, 116011, Dalian, China.
Our study aimed to investigate the relationship between δ-catenin expression and whole-brain small-world network in breast cancer patients before chemotherapy using rs-fMRI. The study was based on the hypothesis that different δ-catenin expression levels correspond to distinct brain imaging characteristics. A total of 105 pathologically confirmed breast cancer patients were collected and categorized into high δ-catenin expression (DH, 52 cases) and low expression (DL, 53 cases) groups.
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December 2024
Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi", Università di Bologna, 40126, Bologna, Italy.
Spiking Neural Networks (SNNs) stand as the third generation of Artificial Neural Networks (ANNs), mirroring the functionality of the mammalian brain more closely than their predecessors. Their computational units, spiking neurons, characterized by Ordinary Differential Equations (ODEs), allow for dynamic system representation, with spikes serving as the medium for asynchronous communication among neurons. Due to their inherent ability to capture input dynamics, SNNs hold great promise for deep networks in Reinforcement Learning (RL) tasks.
View Article and Find Full Text PDFSports Med
December 2024
Research Centre in Physical Activity, Health and Leisure, and Laboratory for Integrative and Translational Research in Population Health, University of Porto, Porto, Portugal.
Motor competence is related to a large number of correlates of different natures, forming together a system with flexible parts that are synergically and cooperatively connected to produce a wide range of motor outcomes that cannot be explained from a predetermined linear view or a unique mechanism. The diversity of interacting correlates, the various connections between them, and the fast changes between assessments at different time points are clear barriers to the study of motor competence. In this manuscript, we present a multilayer framework that accounts for the theoretical background and the potential mathematical procedures necessary to represent the non-linear, complex, and dynamic relationships between several underlying correlates that emerge as a motor competence network.
View Article and Find Full Text PDFBrain Struct Funct
December 2024
The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, China.
Acute cerebral ischemia alters brain network connectivity, leading to notable increases in both anatomical and functional connectivity while observing a reduction in metabolic connectivity. However, alterations of the cerebral blood flow (CBF) based functional connectivity remain unclear. We collected continuous CBF images using laser speckle contrast imaging (LSCI) technology to monitor ischemic occlusion-reperfusion progression through occlusion of the left carotid artery.
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