362 research outputs found
Retrospective-Cost-Based Adaptive Input and State Estimation for the Ionosphere–Thermosphere
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140666/1/1.I010286.pd
Retrospective Cost Optimization for Adaptive State Estimation, Input Estimation, and Model Refinement
AbstractRetrospective cost optimization was originally developed for adaptive control. In this paper, we show how this technique is applicable to three distinct but related problems, namely, state estimation, input estimation, and model refinement. To illustrate these techniques, we give two examples. In the first example, retrospective cost model refinement is used with synthetic data to estimate the cooling dynamics that are missing from a model of the ionosphere-thermosphere. In the second example, retrospective cost adaptive state estimation is used with data from a satellite to estimate a solar driver in the ionosphere- thermosphere, with performance gauged by using data from a second satellite
Adaptive State Estimation for Nonminimum-Phase Systems with Uncertain Harmonic Inputs
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90727/1/AIAA-2011-6315-484.pd
Gold Standard for macromolecular crystallography diffraction data
Macromolecular crystallography (MX) is the dominant means of determining the three-dimensional structures of biological macromolecules. Over the last few decades, most MX data have been collected at synchrotron beamlines using a large number of different detectors produced by various manufacturers and taking advantage of various protocols and goniometries. These data came in their own formats: sometimes proprietary, sometimes open. The associated metadata rarely reached the degree of completeness required for data management according to Findability, Accessibility, Interoperability and Reusability (FAIR) principles. Efforts to reuse old data by other investigators or even by the original investigators some time later were often frustrated. In the culmination of an effort dating back more than two decades, a large portion of the research community concerned with high data-rate macromolecular crystallography (HDRMX) has now agreed to an updated specification of data and metadata for diffraction images produced at synchrotron light sources and X-ray free-electron lasers (XFELs). This 'Gold Standard' will facilitate the processing of data sets independent of the facility at which they were collected and enable data archiving according to FAIR principles, with a particular focus on interoperability and reusability. This agreed standard builds on the NeXus/HDF5 NXmx application definition and the International Union of Crystallography (IUCr) imgCIF/CBF dictionary, and it is compatible with major data-processing programs and pipelines. Just as with the IUCr CBF/imgCIF standard from which it arose and to which it is tied, the NeXus/HDF5 NXmx Gold Standard application definition is intended to be applicable to all detectors used for crystallography, and all hardware and software developers in the field are encouraged to adopt and contribute to the standard
Structural and molecular interrogation of intact biological systems
Obtaining high-resolution information from a complex system, while maintaining the global perspective needed to understand system function, represents a key challenge in biology. Here we address this challenge with a method (termed CLARITY) for the transformation of intact tissue into a nanoporous hydrogel-hybridized form (crosslinked to a three-dimensional network of hydrophilic polymers) that is fully assembled but optically transparent and macromolecule-permeable. Using mouse brains, we show intact-tissue imaging of long-range projections, local circuit wiring, cellular relationships, subcellular structures, protein complexes, nucleic acids and neurotransmitters. CLARITY also enables intact-tissue in situ hybridization, immunohistochemistry with multiple rounds of staining and de-staining in non-sectioned tissue, and antibody labelling throughout the intact adult mouse brain. Finally, we show that CLARITY enables fine structural analysis of clinical samples, including non-sectioned human tissue from a neuropsychiatric-disease setting, establishing a path for the transmutation of human tissue into a stable, intact and accessible form suitable for probing structural and molecular underpinnings of physiological function and disease
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Population allocation at the housing unit level: estimates around underground natural gas storage wells in PA, OH, NY, WV, MI, and CA
Background
Spatially accurate population data are critical for determining health impacts from many known risk factors. However, the utility of the increasing spatial resolution of disease mapping and environmental exposures is limited by the lack of receptor population data at similar sub-census block spatial scales.
Methods
Here we apply an innovative method (Population Allocation by Occupied Domicile Estimation – ABODE) to disaggregate U.S. Census populations by allocating an average person per household to geospatially-identified residential housing units (RHU). We considered two possible sources of RHU location data: address point locations and building footprint centroids. We compared the performance of ABODE with the common proportional population allocation (PPA) method for estimating the nighttime residential populations within 200 m radii and setback areas (100 – 300 ft) around active underground natural gas storage (UGS) wells (n = 9834) in six U.S. states.
Results
Address location data generally outperformed building footprint data in predicting total counts of census residential housing units, with correlations ranging from 0.67 to 0.81 at the census block level. Using residentially-sited addresses only, ABODE estimated upwards of 20,000 physical households with between 48,126 and 53,250 people living within 200 m of active UGS wells – likely encompassing the size of a proposed UGS Wellhead Safety Zone. Across the 9834 active wells assessed, ABODE estimated between 5074 and 10,198 more people living in these areas compare to PPA, and the difference was significant at the individual well level (p = < 0.0001). By either population estimation method, OH exhibits a substantial degree of hyperlocal land use conflict between populations and UGS wells – more so than other states assessed. In some rare cases, population estimates differed by more than 100 people for the small 200 m2 well-areas. ABODE’s explicit accounting of physical households confirmed over 50% of PPA predictions as false positives indicated by non-zero predictions in areas absent physical RHUs.
Conclusions
Compared to PPA – in allocating identical population data at sub-census block spatial scales –ABODE provides a more precise population at risk (PAR) estimate with higher confidence estimates of populations at greatest risk. 65% of UGS wells occupy residential urban and suburban areas indicating the unique land use conflicts presented by UGS systems that likely continue to experience population encroachment. Overall, ABODE confirms tens of thousands of homes and residents are likely located within the proposed UGS Wellhead Safety Zone – and in some cases within state’s oil and gas well surface setback distances – of active UGS wells
Global model comparison with Millstone Hill during September 2005
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95551/1/jgra18878.pd
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