7,507 research outputs found

    The Anaphase-Promoting Complex (APC) ubiquitin ligase affects chemosensory behavior in \u3cem\u3eC. elegans\u3c/em\u3e

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    The regulation of fundamental aspects of neurobiological function has been linked to the ubiquitin signaling system (USS), which regulates the degradation and activity of proteins and is catalyzed by E1, E2, and E3 enzymes. The Anaphase-Promoting Complex (APC) is a multi-subunit E3 ubiquitin ligase that controls diverse developmental and signaling processes in post-mitotic neurons; however, potential roles for the APC in sensory function have yet to be explored. In this study, we examined the effect of the APC ubiquitin ligase on chemosensation in Caenorhabditis elegans by testing chemotaxis to the volatile odorants, diacetyl, pyrazine, and isoamyl alcohol, to which wild-type worms are attracted. Animals with loss of function mutations in either of two alleles (g48 and ye143) of the gene encoding the APC subunit EMB-27 APC6 showed increased chemotaxis towards diacetyl and pyrazine, odorants sensed by AWA neurons, but exhibited normal chemotaxis to isoamyl alcohol, which is sensed by AWC neurons. The statistically significant increase in chemotaxis in the emb-27 APC6 mutants suggests that the APC inhibits AWA-mediated chemosensation in C. elegans. Increased chemotaxis to pyrazine was also seen with mutants lacking another essential APC subunit, MAT-2 APC1; however, mat-2 APC1 mutants exhibited wild type responses to diacetyl. The difference in responsiveness of these two APC subunit mutants may be due to differential strength of these hypomorphic alleles or may indicate the presence of functional sub-complexes of the APC at work in this process. These findings are the first evidence for APC-mediated regulation of chemosensation and lay the groundwork for further studies aimed at identifying the expression levels, function, and targets of the APC in specific sensory neurons. Because of the similarity between human and C. elegans nervous systems, the role of the APC in sensory neurons may also advance our understanding of human sensory function and disease

    Convex Optimization In Identification Of Stable Non-Linear State Space Models

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    A new framework for nonlinear system identification is presented in terms of optimal fitting of stable nonlinear state space equations to input/output/state data, with a performance objective defined as a measure of robustness of the simulation error with respect to equation errors. Basic definitions and analytical results are presented. The utility of the method is illustrated on a simple simulation example as well as experimental recordings from a live neuron.Comment: 9 pages, 2 figure, elaboration of same-title paper in 49th IEEE Conference on Decision and Contro

    An improved PaSR-based soot model for turbulent fires

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    The extension of the laminar smoke point based approach to turbulent combustion using the partially stirred reactor (PaSR) concept proposed by Chen et al. ; has been further improved to overcome the limitation in the formulations of Chen et al. ; which assumed infinitely fast soot oxidation chemistry and constant soot formation characteristic time. In the PaSR approach, each computational cell is split into two zones: the reacting zone and the non-reacting zone. Soot formation and oxidation are assumed to take place at finite rates in the reacting zone and computed from the corresponding laminar rates and the mass fractions for soot formation and oxidation, which are evaluated in each computational cell from the characteristic time scales for turbulent mixing, soot formation and oxidation. Since soot would be produced in not only the fine structures but also surrounding fluids in the Eddy-Dissipation-Concept (EDC) model, the average field parameters between the fine structure and surrounding fluid are employed instead of those Favre-averaged values in Chen et al.’s soot formation model. The newly extended model has been implemented in FireFOAM, a large eddy simulation (LES) based solver for fire simulation based on the open source CFD code OpenFOAM®. Numerical simulations of a 30 cm diameter heptane and toluene pool fires tested by Klassen and Gore [29] were performed for validation. The predicted soot volume fraction and temperature have achieved improved agreement with the experimental measurements in comparison with that of Chen et al. ; , demonstrating the potential of the improved PaSR-based soot model for fire applications

    Generating Accurate and Consistent Top-Of-Atmosphere Reflectance Products from the New Generation Geostationary Satellite Sensors

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    GeoNEX is a collaborative project by scientists from NASA, NOAA, JAXA, and other organizations around the world with the purpose of generating a suite of Earth-monitoring products using data streams from the latest geostationary (GEO) sensors including the GOES-16/17 ABI and the Himawari-8/9 AHI. An accurate and consistent top-of-atmosphere (TOA) reflectance product, in particular the bidirectional reflectance factor (BRF), is the starting point in the scientific processing chain. We describe the main considerations and corresponding algorithms in generating the GeoNEX TOA BRF product. First, a special advantage of geostationary data streams is their high temporal resolution (~10 minutes per full-disk scan), providing a key source of information for many downstream products. To fully utilize this high temporal frequency demands a high georegistration accuracy for every acquired image. Our analysis shows that there can be substantial georegistration uncertainties in both GOES and Himawari L1b data which we addressed by implementing a phase-based correction algorithm to remove residual errors. Second, geostationary sensors have distinct illumination-view geometry features in that the solar angle changes for every pixel. Therefore, to accurately derive a BRF requires a solar position algorithm and the estimation of the pixel-wise acquisition time within an uncertainty of 10 seconds. Third, we discuss the measures we adopted to check and correct residual radiometric calibration issues of individual sensors to enable time-series analysis as well as the cross calibration between different satellite sensors (including those from low-Earth orbit). Finally, we also explain the rationale for the choice of the global grid/tile system of the GeoNEX TOA BRF product

    GeoNEX: A Cloud Gateway for Near Real-time Processing of Geostationary Satellite Products

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    The emergence of a new generation of geostationary satellite sensors provides land andatmosphere monitoring capabilities similar to MODIS and VIIRS with far greater temporal resolution (5-15 minutes). However, processing such large volume, highly dynamic datasets requires computing capabilities that (1) better support data access and knowledge discovery for scientists; (2) provide resources to enable real-time processing for emergency response (wildfire, smoke, dust, etc.); and (3) provide reliable and scalable services for the broader user community. This paper presents an implementation of GeoNEX (Geostationary NASA-NOAA Earth Exchange) services that integrate scientific algorithms with Amazon Web Services (AWS) to provide near realtime monitoring (~5 minute latency) capability in a hybrid cloud-computing environment. It offers a user-friendly, manageable and extendable interface and benefits from the scalability provided by Amazon Web Services. Four use cases are presented to illustrate how to (1) search and access geostationary data; (2) configure computing infrastructure to enable near real-time processing; (3) disseminate and utilize research results, visualizations, and animations to concurrent users; and (4) use a Jupyter Notebook-like interface for data exploration and rapid prototyping. As an example of (3), the Wildfire Automated Biomass Burning Algorithm (WF_ABBA) was implemented on GOES-16 and -17 data to produce an active fire map every 5 minutes over the conterminous US. Details of the implementation strategies, architectures, and challenges of the use cases are discussed

    Functional anatomy of the masking level difference, an fMRI study

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    Introduction: Masking level differences (MLDs) are differences in the hearing threshold for the detection of a signal presented in a noise background, where either the phase of the signal or noise is reversed between ears. We use N0/Nπ to denote noise presented in-phase/out-of-phase between ears and S0/Sπ to denote a 500 Hz sine wave signal as in/out-of-phase. Signal detection level for the noise/signal combinations N0Sπ and NπS0 is typically 10-20 dB better than for N0S0. All combinations have the same spectrum, level, and duration of both the signal and the noise. Methods: Ten participants (5 female), age: 22-43, with N0Sπ-N0S0 MLDs greater than 10 dB, were imaged using a sparse BOLD fMRI sequence, with a 9 second gap (1 second quiet preceding stimuli). Band-pass (400-600 Hz) noise and an enveloped signal (.25 second tone burst, 50% duty-cycle) were used to create the stimuli. Brain maps of statistically significant regions were formed from a second-level analysis using SPM5. Results: The contrast NπS0- N0Sπ had significant regions of activation in the right pulvinar, corpus callosum, and insula bilaterally. The left inferior frontal gyrus had significant activation for contrasts N0Sπ-N0S0 and NπS0-N0S0. The contrast N0S0-N0Sπ revealed a region in the right insula, and the contrast N0S0-NπS0 had a region of significance in the left insula. Conclusion: Our results extend the view that the thalamus acts as a gating mechanism to enable dichotic listening, and suggest that MLD processing is accomplished through thalamic communication with the insula, which communicate across the corpus callosum to either enhance or diminish the binaural signal (depending on the MLD condition). The audibility improvement of the signal with both MLD conditions is likely reflected by activation in the left inferior frontal gyrus, a late stage in the what/where model of auditory processing. © 2012 Wack et al

    Differential binding patterns of anti-sulfatide antibodies to glial membranes

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    Sulfatide is a major glycosphingolipid in myelin and a target for autoantibodies in autoimmune neuropathies. However neuropathy disease models have not been widely established, in part because currently available monoclonal antibodies to sulfatide may not represent the diversity of anti-sulfatide antibody binding patterns found in neuropathy patients. We sought to address this issue by generating and characterising a panel of new anti-sulfatide monoclonal antibodies. These antibodies have sulfatide reactivity distinct from existing antibodies in assays and in binding to peripheral nerve tissues and can be used to provide insights into the pathophysiological roles of anti-sulfatide antibodies in demyelinating neuropathies
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