39,813 research outputs found

    A functional role for small-conductance calcium-activated potassium channels in sensory pathways including nociceptive processes

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    We investigated the role of small-conductance calcium-activated potassium (SK) and intermediate-conductance calcium-activated potassium channels in modulating sensory transmission from peripheral afferents into the rat spinal cord. Subunit-specific antibodies reveal high levels of SK3 immunoreactivity in laminas I, II, and III of the spinal cord. Among dorsal root ganglion neurons, both peripherin-positive (C-type) and peripherin-negative (A-type) cells show intense SK3 immunoreactivity. Furthermore, dorsal root-stimulated sensory responses recorded in vitro are inhibited when SK channel activity is increased with 1-ethyl-2-benzimidazolinone (1-EBIO). In vivo electrophysiological recordings show that neuronal responses to naturally evoked nociceptive and nonnociceptive stimuli increase after application of the selective SK channel blocker 8,14-diaza-1,7( 1,4)-diquinolinacyclotetradecaphanedium ditrifluoroacetate (UCL 1848), indicating that SK channels are normally active in moderating afferent input. Conversely, neuronal responses evoked by mechanical stimuli are inhibited when SK channel activity is increased with 1-EBIO. These effects are reversed by the subsequent application of UCL 1848. Our data demonstrate that SK channels have an important role in controlling sensory input into the spinal cord

    A Novel Document Generation Process for Topic Detection based on Hierarchical Latent Tree Models

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    We propose a novel document generation process based on hierarchical latent tree models (HLTMs) learned from data. An HLTM has a layer of observed word variables at the bottom and multiple layers of latent variables on top. For each document, we first sample values for the latent variables layer by layer via logic sampling, then draw relative frequencies for the words conditioned on the values of the latent variables, and finally generate words for the document using the relative word frequencies. The motivation for the work is to take word counts into consideration with HLTMs. In comparison with LDA-based hierarchical document generation processes, the new process achieves drastically better model fit with much fewer parameters. It also yields more meaningful topics and topic hierarchies. It is the new state-of-the-art for the hierarchical topic detection

    A Novel Online Scheduling Algorithm for Hierarchical Vehicle-to-Grid System

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    SAC-SGC.1: Smart Grid Energy Managementpostprin

    Simulating reinforced concrete members. Part 2: displacement-based analyses

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    A companion paper described the partial-interaction localised properties that require the development of pseudo properties. If the quantification through experimental testing of these pseudo properties could be removed by the use of mechanics-based models, which is the subject of this paper, then this would: (a) substantially reduce the cost of developing new reinforced concrete products by reducing the amount of testing; (b) increase the accuracy of designing existing and novel reinforced concrete members and structures, bearing in mind that experimentally derived pseudo properties are only applicable within the range of the testing from which they were derived; and (c) reduce the cost and increase the accuracy of developing reinforced concrete design rules. This paper deals with the development of pseudo properties and behaviours directly through mechanics, as opposed to experimental testing, and their incorporation into member global simulations. It also addresses the need for a fundamental shift to displacement-based analyses as opposed to strain-based analyses.Deric J. Oehlers, Phillip Visintin, Jian-Fei Chen and Tim J. Ibel

    Acceleration of Levenberg-Marquardt Training of Neural Networks with Variable Decay Rate

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    In the application of the standard Levenherg-Marquardt training process of neural networks, error oscillations are frequently observed and they usually aggravate on approaching the required accuracy. In this paper, a modified Levenberg-Marquardt method based on variable decay rate in each iteration is proposed in order to reduce such error oscillations. Through a certain variation of the decay rate, the time required for training of neural networks is cut down to less than half of that required in the standard Levenberg-Marquardt method. Several numerical examples are given to show the effectiveness of the proposed method.published_or_final_versio

    Tracking advanced persistent threats in critical infrastructures through opinion dynamics

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    Advanced persistent threats pose a serious issue for modern industrial environments, due to their targeted and complex attack vectors that are difficult to detect. This is especially severe in critical infrastructures that are accelerating the integration of IT technologies. It is then essential to further develop effective monitoring and response systems that ensure the continuity of business to face the arising set of cyber-security threats. In this paper, we study the practical applicability of a novel technique based on opinion dynamics, that permits to trace the attack throughout all its stages along the network by correlating different anomalies measured over time, thereby taking the persistence of threats and the criticality of resources into consideration. The resulting information is of essential importance to monitor the overall health of the control system and cor- respondingly deploy accurate response procedures. Advanced Persistent Threat Detection Traceability Opinion Dynamics.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

    Deletion within the Src homology domain 3 of Bruton's tyrosine kinase resulting in X-linked agammaglobulinemia (XLA).

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    The gene responsible for X-linked agammaglobulinemia (XLA) has been recently identified to code for a cytoplasmic tyrosine kinase (Bruton's agammaglobulinemia tyrosine kinase, BTK), required for normal B cell development. BTK, like many other cytoplasmic tyrosine kinases, contains Src homology domains (SH2 and SH3), and catalytic kinase domain. SH3 domains are important for the targeting of signaling molecules to specific subcellular locations. We have identified a family with XLA whose affected members have a point mutation (g-->a) at the 5' splice site of intron 8, resulting in the skipping of coding exon 8 and loss of 21 amino acids forming the COOH-terminal portion of the BTK SH3 domain. The study of three generations within this kinship, using restriction fragment length polymorphism and DNA analysis, allowed identification of the mutant X chromosome responsible for XLA and the carrier status in this family. BTK mRNA was present in normal amounts in Epstein-Barr virus-induced B lymphoblastoid cell lines established from affected family members. Although the SH3 deletion did not alter BTK protein stability and kinase activity of the truncated BTK protein was normal, the affected patients nevertheless have a severe B cell defect characteristic for XLA. The mutant protein was modeled using the normal BTK SH3 domain. The deletion results in loss of two COOH-terminal beta strands containing several residues critical for the formation of the putative SH3 ligand-binding pocket. We predict that, as a result, one or more crucial SH3 binding proteins fail to interact with BTK, interrupting the cytoplasmic signal transduction process required for B cell differentiation

    Stress distribution during cold compression of a quartz aggregate using synchrotron X-ray diffraction: Observed yielding, damage, and grain crushing

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    We report new experimental results that quantify the stress distribution within a quartz aggregate during pore collapse and grain crushing. The samples were probed with synchrotron X-ray diffraction as they were compressed in a multianvil deformation apparatus at room temperature from low pressure (tens of megapascal) to pressures of a few gigapascal. In such a material, stress is likely to concentrate at grain-to-grain contacts and vanish where grains are bounded by open porosity. Therefore, internal stress is likely to vary significantly from point to point in such an aggregate, and hence, it is important to understand both the heterogeneity and anisotropy of such variation with respect to the externally applied stress. In our quartz aggregate (grain size of ~4 μm), the measured diffraction peaks broaden asymmetrically at low pressure (tens of megapascal), suggesting that open pores are still a dominant characteristic of grain boundaries. In contrast, a reference sample of novaculite (a highly dense quartz polycrystal, grain size of ~6–9 μm) showed virtually no peak broadening with increasing pressure. In the quartz aggregate, we observed significant deviation in the pressure-volume curves in the range of P = 400–600 MPa. We suggest that this marks the onset of grain crushing (generally denoted as P* in the rock mechanic literature), which is commonly reported to occur in sandstones at pressures of this order, in general agreement with a Hertzian analysis of fracturing at grain contacts

    Building a profile of subjective well-being for social media users

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    Subjective well-being includes ‘affect’ and ‘satisfaction with life’ (SWL). This study proposes a unified approach to construct a profile of subjective well-being based on social media language in Facebook status updates. We apply sentiment analysis to generate users’ affect scores, and train a random forest model to predict SWL using affect scores and other language features of the status updates. Results show that: the computer-selected features resemble the key predictors of SWL as identified in early studies; the machine-predicted SWL is moderately correlated with the self-reported SWL (r = 0.36, p < 0.01), indicating that language-based assessment can constitute valid SWL measures; the machine-assessed affect scores resemble those reported in a previous experimental study; and the machine-predicted subjective well-being profile can also reflect other psychological traits like depression (r = 0.24, p < 0.01). This study provides important insights for psychological prediction using multiple, machine-assessed components and longitudinal or dense psychological assessment using social media language.Gong acknowledges support by the US National Institutes of Health Grant (HD-071988). The study is also supported in part by the MOE Project of the Center for Linguistics and Applied Linguistics, Guangdong University of Foreign Studies. However, the funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
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