248 research outputs found

    S2: Summary

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    The perception of acting conspecifics engages a number of brain regions. Typically pSTS counts as the protagonist, but also the premotor cortex and areas co-activated by static bodies (EBA) and faces (OFA/FFA) light up. Thompson will talk about a parsimonious conceptual dichotomy (form vs. motion) using fMRI in humans, supplemented with fMRI data from both humans and macaque monkeys by Orban. The other talks all employ TMS over pSTS and a stimulation focus on premotor (Sayin), EBA (Vangeneugden), or OFA (Atkinson), all aiming at a better understanding of the neural underpinnings of the action perception network

    double dissociation between the extrastriate body area and the posterior superior temporal sulcus during biological motion perception converging evidence from tms and fmri

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    Our brains engage numerous regions when exposed to biological motion, with the posterior superior temporal sulcus (pSTS) being the primary locus. The exact roles of hMT+ and the extrastriate body area (EBA) remain unclear. Here, we set out to determine the specific roles of pSTS and EBA during biological motion perception, focusing on walker orientation and walking direction. To obtain converging evidence, we conducted separate TMS and fMRI experiments within the same subjects (N = 12). Two separate tasks were used in the TMS study: walker orientation probing form processing and walking direction probing motion/sequence processing. Task performance was compared before and after applying repetitive offline TMS (1 Hz) over EBA and pSTS (based on fMRI-guided stereotaxy). In the fMRI study, EBA and pSTS were mapped in separate scans using standard localizers. Subsequently, runs with point-light walkers were subjected to MVPA, determining the amount of static (orientation) and dynamic (direction) information p..

    Optimization of Precursor Injection in an Atmospheric Pressure Plasma Jet System

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    Atmospheric Pressure Plasma Enhanced Chemical Vapor Deposition (AP PECVD) of thin films is a recently emerged technology, showing important advantages in comparison with the traditional and well established low pressure plasma enhanced deposition methods. The main benefit of AP-PECVD is the potential of cost efficient in-line production without expensive and bulky vacuum equipment. In this work, an innovative AP plasma jet system is investigated which serves as a pilot system for industrial scale equipment, the VITO PlasmaLine®. Applications include moisture/oxygen diffusion barriers as well as grease barriers, UV curing of coatings or chemical activation of a surface. For industrial application a high throughput (~ 100-1000 m/min) is critical in order to compete with conventional techniques, such as wet chemical coating. Barrier coating deposition by AP-PECVD on polymer substrates has been demonstrated to be superior to wet chemical coating, with less consumption of precursor material [1], though many technical challenges remain to obtain the desired (dynamic) growth rates. The pilot equipment utilizes a 0.5 mm double slit configuration with 1000-2000 W power input at a frequency of 40-50 kHz with N2 as the primary carrier gas. By utilizing the plasma afterglow remote from the source, uniform surface treatment can be achieved despite the filamentary discharge in the slits. Deposition on the electrodes is prevented by injection of precursor into the jet and because of the remote nature of the plasma source the thermal load on the substrate is minimized, making it ideally suited for treatment of polymers and paper. A key area for improvement and upscaling of the pilot system for industrial application is optimization of gaseous and liquid (aerosol) precursor injection. To this end, extensive characterization of the plasma jet is undertaken, including current-voltage, fast imaging and optical emission and absorption measurements, with focus on the dynamics of gaseous and aerosol precursor particles in the jet. For optimum control over the gas distribution and precursor injection, Computational Fluid Dynamic models are presented in conjunction with the experimental work

    Signatures of knee osteoarthritis in women in the temporal and fractal dynamics of human gait

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    Background: Osteoarthritis of the knee is characterized by progressive cartilage deterioration causing pain and function loss. Symptoms develop late with limited disease-modifying opportunities. Osteoarthritis is a major cause of immobility, with a higher prevalence above 60 years. This age-related increase in prevalence is further amplified by the female gender. Imaging and biochemical analyses for detection of osteoarthritis of the knee are expensive and labor-intensive. Continuous movement tracking could aid in detecting onset and/or worsening of symptoms.Methods: We used portable technology to investigate kinematic differences in female patients with knee osteoarthritis, weight-matched healthy female volunteers and obese female patients with osteoarthritis of the knee. Knee osteoarthritis was established radiographically and corroborated using magnetic resonance imaging.Findings: The total amount, type and level of activity did not differ significantly between groups. The temporal activity pattern during the day was however significantly different with a bimodal signature in healthy volunteers only. Sequence analyses revealed more time to recuperate after dynamic activity in both patient groups. Analysis of walking bouts revealed significant differences in stride interval dynamics, indicative of gait naturalness, only in healthy volunteers. Temporal activity, sequence and walking patterns were independent of body weight.Interpretation: We thus provide for the first-time evidence of temporal specific kinematic signatures in amount and quality of movement also in stride interval dynamics between people with and without osteoarthritis of the knee independent of body weight. These findings could allow early and non-intrusive diagnosis of osteoarthritis enabling concordant treatment.</p

    Real-time dynamic modelling for the design of a cluster-randomized phase 3 Ebola vaccine trial in Sierra Leone.

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    BACKGROUND: Declining incidence and spatial heterogeneity complicated the design of phase 3 Ebola vaccine trials during the tail of the 2013-16 Ebola virus disease (EVD) epidemic in West Africa. Mathematical models can provide forecasts of expected incidence through time and can account for both vaccine efficacy in participants and effectiveness in populations. Determining expected disease incidence was critical to calculating power and determining trial sample size. METHODS: In real-time, we fitted, forecasted, and simulated a proposed phase 3 cluster-randomized vaccine trial for a prime-boost EVD vaccine in three candidate regions in Sierra Leone. The aim was to forecast trial feasibility in these areas through time and guide study design planning. RESULTS: EVD incidence was highly variable during the epidemic, especially in the declining phase. Delays in trial start date were expected to greatly reduce the ability to discern an effect, particularly as a trial with an effective vaccine would cause the epidemic to go extinct more quickly in the vaccine arm. Real-time updates of the model allowed decision-makers to determine how trial feasibility changed with time. CONCLUSIONS: This analysis was useful for vaccine trial planning because we simulated effectiveness as well as efficacy, which is possible with a dynamic transmission model. It contributed to decisions on choice of trial location and feasibility of the trial. Transmission models should be utilised as early as possible in the design process to provide mechanistic estimates of expected incidence, with which decisions about sample size, location, timing, and feasibility can be determined

    The representation of subordinate shape similarity in human occipitotemporal cortex

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    We investigated the coding of subordinate shape similarity in human object-selective cortex in two event-related functional magnetic resonance adaptation (fMR-A) experiments. Previous studies using faces have concluded that there is a narrow tuning of neuronal populations selective to each face, and that tuning is relative to the expected &quot;average&quot; face (norm-based encoding). Here we investigated these issues using outlines of animals and tools occupying a particular position on different morphing sequences per category. In a first experiment, we inferred the width of neural tuning to exemplars by examining whether the release from adaptation with increasing shape changes between two stimuli asymptotes. In a second experiment, we compared the response to central and extreme positions in shape space while controlling for the number of presentations of each unique stimulus to study whether the expected &quot;average&quot; category exemplar plays a role. The current fMR-A results show that a small change in exemplar shape produces a large release of adaptation, but only for outline shape changes of animals and not for man-made tools. Furthermore, our results suggested that central and extreme positions were not treated differently. Together, these results suggest a narrow tuning in object-selective cortex for individual exemplars from natural object categories, consistent with an exemplar-based encoding principle

    A novel network architecture for train-to-wayside communication with quality of service over heterogeneous wireless networks

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    In the railway industry, there are nowadays different actors who would like to send or receive data from the wayside to an onboard device or vice versa. These actors are e.g., the Train Operation Company, the Train Constructing Company, a Content Provider, etc. This requires a communication module on each train and at the wayside. These modules interact with each other over heterogeneous wireless links. This system is referred to as the Train-to-Wayside Communication System (TWCS). While there are already a lot of deployments using a TWCS, the implementation of quality of service, performance enhancing proxies (PEP) and the network mobility functions have not yet been fully integrated in TWCS systems. Therefore, we propose a novel and modular IPv6-enabled TWCS architecture in this article. It jointly tackles these functions and considers their mutual dependencies and relationships. DiffServ is used to differentiate between service classes and priorities. Virtual local area networks are used to differentiate between different service level agreements. In the PEP, we propose to use a distributed TCP accelerator to optimize bandwidth usage. Concerning network mobility, we propose to use the SCTP protocol (with Dynamic Address Reconfiguration and PR-SCTP extensions) to create a tunnel per wireless link, in order to support the reliable transmission of data between the accelerators. We have analyzed different design choices, pinpointed the main implementation challenges and identified candidate solutions for the different modules in the TWCS system. As such, we present an elaborated framework that can be used for prototyping a fully featured TWCS

    Robust Henderson III estimators of variance components in the nested error model

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    Common methods for estimating variance components in Linear Mixed Models include Maximum Likelihood (ML) and Restricted Maximum Likelihood (REML). These methods are based on the strong assumption of multivariate normal distribution and it is well know that they are very sensitive to outlying observations with respect to any of the random components. Several robust altematives of these methods have been proposed (e.g. Fellner 1986, Richardson and Welsh 1995). In this work we present several robust alternatives based on the Henderson method III which do not rely on the normality assumption and provide explicit solutions for the variance components estimators. These estimators can later be used to derive robust estimators of regression coefficients. Finally, we describe an application of this procedure to small area estimation, in which the main target is the estimation of the means of areas or domains when the within-area sample sizes are small
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