2,182 research outputs found

    Identifying reliable traits across laboratory mouse exploration arenas: A meta-analysis

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    This study is a meta-analysis of 367 mice from a collection of behaviour neuroscience and behaviour genetic studies run in the same lab in Zurich, Switzerland. We employed correlation-based statistics to confirm and quantify consistencies in behaviour across the testing environments. All 367 mice ran exactly the same behavioural arenas: the light/dark box, the null maze, the open field arena, an emergence task and finally an object exploration task. We analysed consistency of three movement types across those arenas (resting, scanning, progressing), and their relative preference for three zones of the arenas (home, transition, exploration). Results were that 5/6 measures showed strong individual-differences consistency across the tests. Mean inter-arena correlations for these five measures ranged from +.12 to +.53. Unrotated principal component factor analysis (UPCFA) and Cronbach’s alpha measures showed these traits to be reliable and substantial (32-63% of variance across the five arenas). UPCFA loadings then indicate which tasks give the best information about these cross-task traits. One measure (that of time spent in “intermediate” zones) was not reliable across arenas. Conclusions centre on the use of individual differences research and behavioural batteries to revise understandings of what measures in one task predict for behaviour in others. Developing better behaviour measures also makes sound scientific and ethical sense

    Limericks on the Century of Genius

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    Local and global spontaneous calcium events regulate neurite outgrowth and onset of GABAergic phenotype during neural precursor differentiation

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    Neural stem cells can generate in vitro progenitors of the three main cell lineages found in the CNS. The signaling pathways underlying the acquisition of differentiated phenotypes in these cells are poorly understood. Here we tested the hypothesis that Ca2+ signaling controls differentiation of neural precursors. We found low-frequency global and local Ca2+ transients occurring predominantly during early stages of differentiation. Spontaneous Ca2+ signals in individual precursors were not synchronized with Ca2+ transients in surrounding cells. Experimentally induced changes in the frequency of local Ca2+signals and global Ca2+ rises correlated positively with neurite outgrowth and the onset of GABAergic neurotransmitter phenotype, respectively. NMDA receptor activity was critical for alterations in neuronal morphology but not for the timing of the acquisition of the neurotransmitter phenotype. Thus, spontaneous Ca2+ signals are an intrinsic property of differentiating neurosphere-derived precursors. Their frequency may specify neuronal morphology and acquisition of neurotransmitter phenotype

    The spider does not always win the fight for attention: Disengagement from threat is modulated by goal set

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    Stimulus-driven preferential attention to threat can be modulated by goal-driven attention. However, it remains unclear how this goal-driven modulation affects specific attentional components implied in threat interference. We hypothesise that goal-driven modulation most strongly impacts delayed disengagement from threat. A spatial cueing task was used that disentangles delayed disengagement from attentional capture by tightly manipulating the locus of attention at the time of target onset. Different top-down goals were induced by instructing participants to identify bird/fish targets (Experiment 1) or spider/cat targets (Experiment 2) among animal non-targets. Delayed disengagement from a non-target spider was observed only when the spider was part of the target set, not when it was task-irrelevant. This corroborates evidence that threat stimuli do not necessarily override goal-driven attentional control and that extended processing of threatening distractors is not obligatory

    TrustShadow: Secure Execution of Unmodified Applications with ARM TrustZone

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    The rapid evolution of Internet-of-Things (IoT) technologies has led to an emerging need to make it smarter. A variety of applications now run simultaneously on an ARM-based processor. For example, devices on the edge of the Internet are provided with higher horsepower to be entrusted with storing, processing and analyzing data collected from IoT devices. This significantly improves efficiency and reduces the amount of data that needs to be transported to the cloud for data processing, analysis and storage. However, commodity OSes are prone to compromise. Once they are exploited, attackers can access the data on these devices. Since the data stored and processed on the devices can be sensitive, left untackled, this is particularly disconcerting. In this paper, we propose a new system, TrustShadow that shields legacy applications from untrusted OSes. TrustShadow takes advantage of ARM TrustZone technology and partitions resources into the secure and normal worlds. In the secure world, TrustShadow constructs a trusted execution environment for security-critical applications. This trusted environment is maintained by a lightweight runtime system that coordinates the communication between applications and the ordinary OS running in the normal world. The runtime system does not provide system services itself. Rather, it forwards requests for system services to the ordinary OS, and verifies the correctness of the responses. To demonstrate the efficiency of this design, we prototyped TrustShadow on a real chip board with ARM TrustZone support, and evaluated its performance using both microbenchmarks and real-world applications. We showed TrustShadow introduces only negligible overhead to real-world applications.Comment: MobiSys 201

    Comment on ``Reduction of static field equation of Faddeev model to first order PDE'', arXiv:0707.2207

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    The authors of the article Phys. Lett. B 652 (2007) 384, (arXiv:0707.2207), propose an interesting method to solve the Faddeev model by reducing it to a set of first order PDEs. They first construct a vectorial quantity α\bm \alpha , depending on the original field and its first derivatives, in terms of which the field equations reduce to a linear first order equation. Then they find vectors α1\bm \alpha_1 and α2\bm \alpha_2 which identically obey this linear first order equation. The last step consists in the identification of the αi\bm \alpha_i with the original α\bm \alpha as a function of the original field. Unfortunately, the derivation of this last step in the paper cited above contains an error which invalidates most of its results
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