8,264 research outputs found

    The Interface Region Imaging Spectrograph (IRIS)

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    The Interface Region Imaging Spectrograph (IRIS) small explorer spacecraft provides simultaneous spectra and images of the photosphere, chromosphere, transition region, and corona with 0.33-0.4 arcsec spatial resolution, 2 s temporal resolution and 1 km/s velocity resolution over a field-of-view of up to 175 arcsec x 175 arcsec. IRIS was launched into a Sun-synchronous orbit on 27 June 2013 using a Pegasus-XL rocket and consists of a 19-cm UV telescope that feeds a slit-based dual-bandpass imaging spectrograph. IRIS obtains spectra in passbands from 1332-1358, 1389-1407 and 2783-2834 Angstrom including bright spectral lines formed in the chromosphere (Mg II h 2803 Angstrom and Mg II k 2796 Angstrom) and transition region (C II 1334/1335 Angstrom and Si IV 1394/1403 Angstrom). Slit-jaw images in four different passbands (C II 1330, Si IV 1400, Mg II k 2796 and Mg II wing 2830 Angstrom) can be taken simultaneously with spectral rasters that sample regions up to 130 arcsec x 175 arcsec at a variety of spatial samplings (from 0.33 arcsec and up). IRIS is sensitive to emission from plasma at temperatures between 5000 K and 10 MK and will advance our understanding of the flow of mass and energy through an interface region, formed by the chromosphere and transition region, between the photosphere and corona. This highly structured and dynamic region not only acts as the conduit of all mass and energy feeding into the corona and solar wind, it also requires an order of magnitude more energy to heat than the corona and solar wind combined. The IRIS investigation includes a strong numerical modeling component based on advanced radiative-MHD codes to facilitate interpretation of observations of this complex region. Approximately eight Gbytes of data (after compression) are acquired by IRIS each day and made available for unrestricted use within a few days of the observation.Comment: 53 pages, 15 figure

    Arkansas Bulletin of Water Research - Issue 2018

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    The Arkansas Bulletin of Water Research is a publication of the Arkansas Water Resources Center (AWRC). This bulletin is produced in an effort to share water research relevant to Arkansas water stakeholders in an easily searchable and aesthetically engaging way. This is the second publication of the bulletin and will be published annually. The submission of a paper to this bulletin is appropriate for topics at all related to water resources, by anyone conducting water research or investigations. This includes but is not limited to university researchers, consulting firms, watershed groups, and other agencies. Prospective authors should read the “Introduction to the Arkanasas Bulletin of Water Research” contained within this publication and should refer to the AWRC website for additional infromation. https://arkansas-water-center.uark.edu

    Rapid methods of landslide hazard mapping : Fiji case study

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    A landslide hazard probability map can help planners (1) prepare for, and/or mitigate against, the effects of landsliding on communities and infrastructure, and (2) avoid or minimise the risks associated with new developments. The aims of the project were to establish, by means of studies in a few test areas, a generic method by which remote sensing and data analysis using a geographic information system (GIS) could provide a provisional landslide hazard zonation map. The provision of basic hazard information is an underpinning theme of the UN’s International Decade for Natural Disaster Reduction (IDNDR). It is an essential requirement for disaster preparedness and mitigation planning. This report forms part of BGS project 92/7 (R5554) ‘Rapid assessment of landslip hazards’ Carried out under the ODA/BGS Technology Development and Research Programme as part of the British Government’s provision of aid to developing countries. It provides a detailed technical account of work undertaken in a test area in Viti Levu in collaboration with Fiji Mineral Resources Department. The study represents a demonstration of a methodology that is applicable to many developing countries. The underlying principle is that relationships between past landsliding events, interpreted from remote sensing, and factors such as the geology, relief, soils etc provide the basis for modelling where future landslides are most likely to occur. This is achieved using a GIS by ‘weighting’ each class of each variable (e.g. each lithology ‘class’ of the variable ‘geology’) according to the proportion of landslides occurring within it compared to the regional average. Combinations of variables, produced by summing the weights in individual classes, provide ‘models’ of landslide probability. The approach is empirical but has the advantage of potentially being able to provide regional scale hazard maps over large areas quickly and cheaply; this is unlikely to be achieved using conventional ground-based geotechnical methods. In Fiji, landslides are usually triggered by intense rain storms commonly associated with tropical cyclones. However, the regional distribution of landslides has not been mapped nor is it known how far geology and landscape influence the location and severity of landsliding events. The report discusses the remote sensing and GIS methodology, and describes the results of the pilot study over an area of 713 km2 in south east Viti Levu. The landslide model uses geology, elevation, slope angle, slope aspect, soil type, and forest cover as inputs. The resulting provisional landslide hazard zonation map, divided into high, medium and low zones of landslide hazard probability, suggests that whilst rainfall is the immediate cause, others controls do exert a significant influence. It is recommended that consideration be given in Fiji to implementing the techniques as part of a national strategic plan for landslide hazard zonation mapping

    Infrastructure for Detector Research and Development towards the International Linear Collider

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    The EUDET-project was launched to create an infrastructure for developing and testing new and advanced detector technologies to be used at a future linear collider. The aim was to make possible experimentation and analysis of data for institutes, which otherwise could not be realized due to lack of resources. The infrastructure comprised an analysis and software network, and instrumentation infrastructures for tracking detectors as well as for calorimetry.Comment: 54 pages, 48 picture

    Detection and prediction of urban archetypes at the pedestrian scale: computational toolsets, morphological metrics, and machine learning methods

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    Granular, dense, and mixed-use urban morphologies are hallmarks of walkable and vibrant streets. However, urban systems are notoriously complex and planned urban development, which grapples with varied interdependent and oft conflicting criteria, may — despite best intentions — yield aberrant morphologies fundamentally at odds with the needs of pedestrians and the resiliency of neighbourhoods. This work addresses the measurement, detection, and prediction of pedestrian-friendly urban archetypes by developing techniques for high-resolution urban analytics at the pedestrian scale. A spatial-analytic computational toolset, the cityseer-api Python package, is created to assess localised centrality, land-use, and statistical metrics using contextually sensitive workflows applied directly over the street network. cityseer-api subsequently facilitates a review of mixed-use and street network centrality methods to improve their utility concerning granular urban analysis. Unsupervised machine learning methods are applied to recover ‘signatures’ — urban archetypes — using Principal Component Analysis, Variational Autoencoders, and clustering methods from a high-resolution multi-variable and multi-scalar dataset consisting of centralities, land-uses, and population densities for Greater London. Supervised deep-learning methods applied to a similar dataset developed for 931 towns and cities in Great Britain demonstrate how, with the aid of domain knowledge, machine-learning classifiers can learn to discriminate between ‘artificial’ and ‘historical’ urban archetypes. These methods use complex systems thinking as a departure point and illustrate how high-resolution spatial-analytic quantitative methods can be combined with machine learning to extrapolate benchmarks in keeping with more qualitatively framed urban morphological conceptions. Such tools may aid urban design professionals in better anticipating the outcomes of varied design scenarios as part of iterative and scalable workflows. These techniques may likewise provide robust and demonstrable feedback as part of planning review and approvals processes

    Construction and demolition waste recycling through conventional jig, air jig, and sensor-based sorting a comparison

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    The paper presents a comparison of the concentration methods conventional jig, air jig, and sensor-based sorting to treat construction and demolition waste. All tests were made with concrete, brick, and gypsum particles and the tests aim to separate these materials into different size ranges, depending on the method. The equipment tested, conventional jig, air jig, and sensor-based sorting present good results to concentrate construction and demolition waste particles, with different concentrations and mass recoveries. The results show particularly good mass recoveries and particle concentration for conventional jig, especially for concrete and gypsum particles. Sensor-based sorting should preferably use concentration circuits for best results

    GEANT4 : a simulation toolkit

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    Abstract Geant4 is a toolkit for simulating the passage of particles through matter. It includes a complete range of functionality including tracking, geometry, physics models and hits. The physics processes offered cover a comprehensive range, including electromagnetic, hadronic and optical processes, a large set of long-lived particles, materials and elements, over a wide energy range starting, in some cases, from 250 eV and extending in others to the TeV energy range. It has been designed and constructed to expose the physics models utilised, to handle complex geometries, and to enable its easy adaptation for optimal use in different sets of applications. The toolkit is the result of a worldwide collaboration of physicists and software engineers. It has been created exploiting software engineering and object-oriented technology and implemented in the C++ programming language. It has been used in applications in particle physics, nuclear physics, accelerator design, space engineering and medical physics. PACS: 07.05.Tp; 13; 2

    Mine haul road rolling resistance: influences and impacts

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    Energy efficiency of haulage, in the production of mineral ores, was investigated through measurement of the rolling resistance experienced by haul trucks while traversing unsealed, unbound granular pavements. It appears pavement surface condition influences rolling resistance more significantly than pavement structural capacity. Validation of various modelling methods with in-situ pavement deflection measurements showed that simple methods are able to estimate pavement surface deflection with similar accuracy to more complex techniques, such as Finite Element Analysis

    A gradual depth-dependent change of connectivity features of supragranular pyramidal cells in rat barrel cortex

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    Recent experimental evidence suggests a finer genetic, structural and functional subdivision of the layers which form a cortical column. The classical layer II/III (LII/III) of rodent neocortex integrates ascending sensory information with contextual cortical information for behavioral read-out. We systematically investigated to which extent regular-spiking supragranular pyramidal neurons, located at different depths within the cortex, show different input-output connectivity patterns. Combining glutamate-uncaging with whole-cell recordings and biocytin filling, we revealed a novel cellular organization of LII/III: (i) “Lower LII/III” pyramidal cells receive a very strong excitatory input from lemniscal LIV and much fewer inputs from paralemniscal LVa. They project to all layers of the home column, including a feedback projection to LIV whereas transcolumnar projections are relatively sparse. (ii) “Upper LII/III” pyramidal cells also receive their strongest input from LIV, but in addition, a very strong and dense excitatory input from LVa. They project extensively to LII/III as well as LVa and Vb of their home and neighboring columns, (iii) “Middle LII/III” pyramidal cell show an intermediate connectivity phenotype that stands in many ways in-between the features described for lower versus upper LII/III. “Lower LII/III” intracolumnarly segregates and transcolumnarly integrates lemniscal information whereas “upper LII/III” seems to integrate lemniscal with paralemniscal information. This suggests a finegrained functional subdivision of the supragranular compartment containing multiple circuits without any obvious cytoarchitectonic, other structural or functional correlate of a laminar border in rodent barrel cortex
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