16,613 research outputs found

    Detection of bimanual gestures everywhere: why it matters, what we need and what is missing

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    Bimanual gestures are of the utmost importance for the study of motor coordination in humans and in everyday activities. A reliable detection of bimanual gestures in unconstrained environments is fundamental for their clinical study and to assess common activities of daily living. This paper investigates techniques for a reliable, unconstrained detection and classification of bimanual gestures. It assumes the availability of inertial data originating from the two hands/arms, builds upon a previously developed technique for gesture modelling based on Gaussian Mixture Modelling (GMM) and Gaussian Mixture Regression (GMR), and compares different modelling and classification techniques, which are based on a number of assumptions inspired by literature about how bimanual gestures are represented and modelled in the brain. Experiments show results related to 5 everyday bimanual activities, which have been selected on the basis of three main parameters: (not) constraining the two hands by a physical tool, (not) requiring a specific sequence of single-hand gestures, being recursive (or not). In the best performing combination of modeling approach and classification technique, five out of five activities are recognized up to an accuracy of 97%, a precision of 82% and a level of recall of 100%.Comment: Submitted to Robotics and Autonomous Systems (Elsevier

    Rare and common epilepsies converge on a shared gene regulatory network providing opportunities for novel antiepileptic drug discovery

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    Background The relationship between monogenic and polygenic forms of epilepsy is poorly understood, and the extent to which the genetic and acquired epilepsies share common pathways is unclear. Here, we use an integrated systems-level analysis of brain gene expression data to identify molecular networks disrupted in epilepsy. Results We identify a co-expression network of 320 genes (M30), which is significantly enriched for non-synonymous de novo mutations ascertained from patients with monogenic epilepsy, and for common variants associated with polygenic epilepsy. The genes in M30 network are expressed widely in the human brain under tight developmental control, and encode physically interacting proteins involved in synaptic processes. The most highly connected proteins within M30 network are preferentially disrupted by deleterious de novo mutations for monogenic epilepsy, in line with the centrality-lethality hypothesis. Analysis of M30 expression revealed consistent down-regulation in the epileptic brain in heterogeneous forms of epilepsy including human temporal lobe epilepsy, a mouse model of acquired temporal lobe epilepsy, and a mouse model of monogenic Dravet (SCN1A) disease. These results suggest functional disruption of M30 via gene mutation or altered expression as a convergent mechanism regulating susceptibility to epilepsy broadly. Using the large collection of drug-induced gene expression data from Connectivity Map, several drugs were predicted to preferentially restore the down-regulation of M30 in epilepsy toward health, most notably valproic acid, whose effect on M30 expression was replicated in neurons. Conclusions Taken together, our results suggest targeting the expression of M30 as a potential new therapeutic strategy in epilepsy

    Prehension and perception of size in left visual neglect

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    Right hemisphere damaged patients with and without left visual neglect, and age-matched controls had objects of various sizes presented within left or right body hemispace. Subjects were asked to estimate the objects’ sizes or to reach out and grasp them, in order to assess visual size processing in perceptual-experiential and action-based contexts respectively. No impairments of size processing were detected in the prehension performance of the neglect patients but a generalised slowing of movement was observed, associated with an extended deceleration phase. Additionally both patient groups reached maximum grip aperture relatively later in the movement than did controls. For the estimation task it was predicted that the left visual neglect group would systematically underestimate the sizes of objects presented within left hemispace but no such abnormalities were observed. Possible reasons for this unexpected null finding are discussed

    Adaptive heterogeneous parallelism for semi-empirical lattice dynamics in computational materials science.

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    With the variability in performance of the multitude of parallel environments available today, the conceptual overhead created by the need to anticipate runtime information to make design-time decisions has become overwhelming. Performance-critical applications and libraries carry implicit assumptions based on incidental metrics that are not portable to emerging computational platforms or even alternative contemporary architectures. Furthermore, the significance of runtime concerns such as makespan, energy efficiency and fault tolerance depends on the situational context. This thesis presents a case study in the application of both Mattsons prescriptive pattern-oriented approach and the more principled structured parallelism formalism to the computational simulation of inelastic neutron scattering spectra on hybrid CPU/GPU platforms. The original ad hoc implementation as well as new patternbased and structured implementations are evaluated for relative performance and scalability. Two new structural abstractions are introduced to facilitate adaptation by lazy optimisation and runtime feedback. A deferred-choice abstraction represents a unified space of alternative structural program variants, allowing static adaptation through model-specific exhaustive calibration with regards to the extrafunctional concerns of runtime, average instantaneous power and total energy usage. Instrumented queues serve as mechanism for structural composition and provide a representation of extrafunctional state that allows realisation of a market-based decentralised coordination heuristic for competitive resource allocation and the Lyapunov drift algorithm for cooperative scheduling

    Online Automated Synthesis of Compact Normative Systems

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    Visualization of the modeled degradation of building flooring systems in building maintenance

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    The development of a maintenance programme for construction projects is a highly complex and data intensive undertaking. This exercise is characterised by the lack of relevant data on the one hand and the overwhelming amount of extraneous data on the other. The uncertainties and complexities have resulted in increased conservatism in the development of lifecycle evaluation of building maintenance programing, subsequently, these programmes tend to display the symptoms of either the maintenance actions being uneconomical or fall short of providing the appropriate service to the users of the building. The current research project is based on the premise that the visual approach will facilitate a just-in-time solution to maintenance scheduling, hence, the use of virtual simulation of the building is proposed. The broader aim of this research is to develop a complete building maintenance programme through visualisation of buildings as they degrade over time. Here, the focus is on the flooring system and the manner they degrade over time. This requires a better understanding of their pattern and rate of usage. To this end, Anthroposophy and Anthropocentric descriptions of human movement pattern have been used to describe the behaviour of 'subjects' and subsequently represent the pattern and density of the degradation of flooring systems. The mathematics representing this behaviour has been developed which enables it to be embedded into the proposed overall visual building maintenance model

    An architectural framework for self-configuration and self-improvement at runtime

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    A large-scale study of a poultry trading network in Bangladesh: implications for control and surveillance of avian influenza viruses

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    Since its first report in 2007, avian influenza (AI) has been endemic in Bangladesh. While live poultry marketing is widespread throughout the country and known to influence AI dissemination and persistence, trading patterns have not been described. The aim of this study is to assess poultry trading practices and features of the poultry trading networks which could promote AI spread, and their potential implications for disease control and surveillance. Data on poultry trading practices was collected from 849 poultry traders during a cross-sectional survey in 138 live bird markets (LBMs) across 17 different districts of Bangladesh. The quantity and origins of traded poultry were assessed for each poultry type in surveyed LBMs. The network of contacts between farms and LBMs resulting from commercial movements of live poultry was constructed to assess its connectivity and to identify the key premises influencing it
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