1,635 research outputs found

    Adaptiver stochastischer Sprache/Pause-Detektor

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    Is a multiple excitation of a single atom equivalent to a single excitation of an ensemble of atoms?

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    Recent technological advances have enabled to isolate, control and measure the properties of a single atom, leading to the possibility to perform statistics on the behavior of single quantum systems. These experiments have enabled to check a question which was out of reach previously: Is the statistics of a repeatedly excitation of an atom N times equivalent to a single excitation of an ensemble of N atoms? We present a new method to analyze quantum measurements which leads to the postulation that the answer is most probably no. We discuss the merits of the analysis and its conclusion.Comment: 3 pages, 3 figure

    Summed Parallel Infinite Impulse Response (SPIIR) Filters For Low-Latency Gravitational Wave Detection

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    With the upgrade of current gravitational wave detectors, the first detection of gravitational wave signals is expected to occur in the next decade. Low-latency gravitational wave triggers will be necessary to make fast follow-up electromagnetic observations of events related to their source, e.g., prompt optical emission associated with short gamma-ray bursts. In this paper we present a new time-domain low-latency algorithm for identifying the presence of gravitational waves produced by compact binary coalescence events in noisy detector data. Our method calculates the signal to noise ratio from the summation of a bank of parallel infinite impulse response (IIR) filters. We show that our summed parallel infinite impulse response (SPIIR) method can retrieve the signal to noise ratio to greater than 99% of that produced from the optimal matched filter. We emphasise the benefits of the SPIIR method for advanced detectors, which will require larger template banks.Comment: 9 pages, 6 figures, for PR

    Towards low-latency real-time detection of gravitational waves from compact binary coalescences in the era of advanced detectors

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    Electromagnetic (EM) follow-up observations of gravitational wave (GW) events will help shed light on the nature of the sources, and more can be learned if the EM follow-ups can start as soon as the GW event becomes observable. In this paper, we propose a computationally efficient time-domain algorithm capable of detecting gravitational waves (GWs) from coalescing binaries of compact objects with nearly zero time delay. In case when the signal is strong enough, our algorithm also has the flexibility to trigger EM observation before the merger. The key to the efficiency of our algorithm arises from the use of chains of so-called Infinite Impulse Response (IIR) filters, which filter time-series data recursively. Computational cost is further reduced by a template interpolation technique that requires filtering to be done only for a much coarser template bank than otherwise required to sufficiently recover optimal signal-to-noise ratio. Towards future detectors with sensitivity extending to lower frequencies, our algorithm's computational cost is shown to increase rather insignificantly compared to the conventional time-domain correlation method. Moreover, at latencies of less than hundreds to thousands of seconds, this method is expected to be computationally more efficient than the straightforward frequency-domain method.Comment: 19 pages, 6 figures, for PR

    Kalirin12 interacts with dynamin

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    <p>Abstract</p> <p>Background</p> <p>Guanine nucleotide exchange factors (GEFs) and their target Rho GTPases regulate cytoskeletal changes and membrane trafficking. Dynamin, a large force-generating GTPase, plays an essential role in membrane tubulation and fission in cells. Kalirin12, a neuronal RhoGEF, is found in growth cones early in development and in dendritic spines later in development.</p> <p>Results</p> <p>The IgFn domain of Kalirin12, not present in other Kalirin isoforms, binds dynamin1 and dynamin2. An inactivating mutation in the GTPase domain of dynamin diminishes this interaction and the isolated GTPase domain of dynamin retains the ability to bind Kalirin12. Co-immunoprecipitation demonstrates an interaction of Kalirin12 and dynamin2 in embryonic brain. Purified recombinant Kalirin-IgFn domain inhibits the ability of purified rat brain dynamin to oligomerize in response to the presence of liposomes containing phosphatidylinositol-4,5-bisphosphate. Consistent with this, expression of exogenous Kalirin12 or its IgFn domain in PC12 cells disrupts clathrin-mediated transferrin endocytosis. Similarly, expression of exogenous Kalirin12 disrupts transferrin endocytosis in cortical neurons. Expression of Kalirin7, a shorter isoform which lacks the IgFn domain, was previously shown to inhibit clathrin-mediated endocytosis; the GTPase domain of dynamin does not interact with Kalirin7.</p> <p>Conclusion</p> <p>Kalirin12 may play a role in coordinating Rho GTPase-mediated changes in the actin cytoskeleton with dynamin-mediated changes in membrane trafficking.</p

    The Entropy of a Binary Hidden Markov Process

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    The entropy of a binary symmetric Hidden Markov Process is calculated as an expansion in the noise parameter epsilon. We map the problem onto a one-dimensional Ising model in a large field of random signs and calculate the expansion coefficients up to second order in epsilon. Using a conjecture we extend the calculation to 11th order and discuss the convergence of the resulting series

    Single-molecule studies of conformational states and dynamics in the ABC importer OpuA

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    The current model of active transport via ABC importers is mostly based on structural, biochemical and genetic data. We here establish single-molecule Förster resonance energy transfer (smFRET) assays to monitor the conformational states and heterogeneity of the osmoregulatory type I ABC importer OpuA from Lactococcus~lactis. We present data probing both intradomain distances that elucidate conformational changes within the substrate-binding domain (SBD) OpuAC, and interdomain distances between SBDs or transmembrane domains. Using this methodology, we studied ligand-binding mechanisms, as well as ATP and glycine betaine dependences of conformational changes. Our work expands the scope of smFRET investigations towards a class of so far unstudied ABC importers, and paves the way for a full understanding of their transport cycle in the future

    Mining users' significant driving routes with low-power sensors

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    While there is significant work on sensing and recognition of significant places for users, little attention has been given to users' significant routes. Recognizing these routine journeys, opens doors to the development of novel applications, like personalized travel alerts, and enhancement of user's travel experience. However, the high energy consumption of traditional location sensing technologies, such as GPS or WiFi based localization, is a barrier to passive and ubiquitous route sensing through smartphones. In this paper, we present a passive route sensing framework that continuously monitors a vehicle user solely through a phone's gyroscope and accelerometer. This approach can differentiate and recognize various routes taken by the user by time warping angular speeds experienced by the phone while in transit and is independent of phone orientation and location within the vehicle, small detours and traffic conditions. We compare the route learning and recognition capabilities of this approach with GPS trajectory analysis and show that it achieves similar performance. Moreover, with an embedded co-processor, common to most new generation phones, it achieves energy savings of an order of magnitude over the GPS sensor.This research has been funded by the EPSRC Innovation and Knowledge Centre for Smart Infrastructure and Construction project (EP/K000314).This is the author accepted manuscript. The final version is available from ACM via http://dx.doi.org/10.1145/2668332.266834

    The histamine system and cognitive function: an in vivo H3 receptor PET imaging study in healthy volunteers and patients with schizophrenia

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    BACKGROUND: The histamine-3 receptor (H3R) is an auto- and heteroreceptor that inhibits the release of histamine and other neurotransmitters. Post-mortem evidence has found altered H3R expression in patients with psychotic disorders, which may underlie cognitive impairment associated with schizophrenia (CIAS). AIMS: We used positron emission tomography (PET) imaging to compare brain uptake of an H3R selective tracer between patients with schizophrenia and matched controls (healthy individuals). Regions of interest included the dorsolateral prefrontal cortex (DLPFC) and striatum. We explored correlations between tracer uptake and symptoms, including cognitive domains. METHODS: A total of 12 patients and 12 matched controls were recruited to the study and were assessed with psychiatric and cognitive rating scales. They received a PET scan using the H3R-specific radioligand [11C]MK-8278 to determine H3R availability. RESULTS: There was no statistically significant difference in tracer uptake between patients and controls in the DLPFC (t19 = 0.79, p = 0.44) or striatum (t21 = 1.18, p = 0.25). An exploratory analysis found evidence for lower volume of distribution in the left cuneus (pFWE-corrected = 0.01). DLPFC tracer uptake was strongly correlated with cognition in controls (trail making test (TMT) A: r = 0.77, p = 0.006; TMT B: rho = 0.74, p = 0.01), but not in patients (TMT A: r = -0.18, p = 0.62; TMT B: rho = -0.06, p = 0.81). CONCLUSIONS: These findings indicate H3R in the DLPFC might play a role in executive function and this is disrupted in schizophrenia in the absence of major alterations in H3R availability as assessed using a selective radiotracer for H3R. This provides further evidence for the role of H3R in CIAS

    Hidden Quantum Markov Models and Open Quantum Systems with Instantaneous Feedback

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    Hidden Markov Models are widely used in classical computer science to model stochastic processes with a wide range of applications. This paper concerns the quantum analogues of these machines --- so-called Hidden Quantum Markov Models (HQMMs). Using the properties of Quantum Physics, HQMMs are able to generate more complex random output sequences than their classical counterparts, even when using the same number of internal states. They are therefore expected to find applications as quantum simulators of stochastic processes. Here, we emphasise that open quantum systems with instantaneous feedback are examples of HQMMs, thereby identifying a novel application of quantum feedback control.Comment: 10 Pages, proceedings for the Interdisciplinary Symposium on Complex Systems in Florence, September 2014, minor correction
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