175 research outputs found

    Using unsupervised learning to partition 3D city scenes for distributed building energy microsimulation

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    Microsimulation is a class of Urban Building Energy Modeling techniques in which energetic interactions between buildings are explicitly resolved. Examples include SUNtool and CitySim+, both of which employ a sophisticated radiosity-based algorithm to solve for radiation exchange. The computational cost of this algorithm increases in proportion to the square of the number of surfaces of which an urban scene is comprised. To simulate large scenes, of the order of 10,000 to 1,000,000 surfaces, it is desirable to divide the scene to distribute the simulation task. However, this partitioning is not trivial as the energy-related interactions create uneven inter-dependencies between computing nodes. To this end, we describe in this paper two approaches (K-means and Greedy Community Detection algorithms) for partitioning urban scenes, and subsequently performing building energy microsimulation using CitySim+ on a distributed memory High-Performance Computing Cluster. To compare the performance of these partitioning techniques, we propose two measures evaluating the extent to which the obtained clusters exploit data locality. We show that our approach using Greedy Community Detection performs well in terms of exploiting data locality and reducing inter-dependencies among sub-scenes, but at the expense of a higher data preparation cost and algorithm run-time

    Modelling the emergence of cities and urban patterning using coupled integro-differential equations

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    Human residential population distributions show patterns of higher density clustering around local services such as shops and places of employment, displaying characteristic length scales; Fourier transforms and spatial autocorrelation show the length scale between UK cities is around 45 km. We use integro-differential equations to model the spatio-temporal dynamics of population and service density under the assumption that they benefit from spatial proximity, captured via spatial weight kernels. The system tends towards a well-mixed homogeneous state or a spatial pattern. Linear stability analysis around the homogeneous steady state predicts a modelled length-scale consistent with that observed in the data. Moreover, we show that spatial instability occurs only for perturbations with a sufficiently long wavelength and only where there is a sufficiently strong dependence of service potential on population density. Within urban centres, competition for space may cause services and population to be out of phase with one another, occupying separate parcels of land. By introducing competition, along with a preference for population to be located near, but not too near, to high service density areas, secondary out-of-phase patterns occur within the model, at a higher density and with a shorter length scale than in phase patterning. Thus, we show that a small set of core behavioural ingredients can generate aggregations of populations and services, and pattern formation within cities, with length scales consistent with real-world data. The analysis and results are valid across a wide range of parameter values and functional forms in the model

    Towards the development of a simulator for investigating the impact of people management practices on retail performance

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                   \ud           \ud 

    Towards an improved understanding of biogeochemical processes across surface-groundwater interactions in intermittent rivers and ephemeral streams

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    Surface-groundwater interactions in intermittent rivers and ephemeral streams (IRES), waterways which do not flow year-round, are spatially and temporally dynamic because of alternations between flowing, non-flowing and dry hydrological states. Interactions between surface and groundwater often create mixing zones with distinct redox gradients, potentially driving high rates of carbon and nutrient cycling. Yet a complete understanding of how underlying biogeochemical processes across surface-groundwater flowpaths in IRES differ among various hydrological states remains elusive. Here, we present a conceptual framework relating spatial and temporal hydrological variability in surface water-groundwater interactions to biogeochemical processing hotspots in IRES. We combine a review of theIRES biogeochemistry literature with concepts of IRES hydrogeomorphology to: (i) outline common distinctions among hydrological states in IRES; (ii) use these distinctions, together with considerations of carbon, nitrogen, and phosphorus cycles within IRES, to predict the relative potential for biogeochemical processing across different reach-scale processing zones (flowing water, fragmented pools, hyporheic zones, groundwater, and emerged sediments); and (iii) explore the potential spatial and temporal variability of carbon and nutrient biogeochemical processing across entire IRES networks. Our approach estimates the greatest reach-scale potential for biogeochemical processing when IRES reaches are fragmented into isolated surface water pools, and highlights the potential of relatively understudied processing zones, such as emerged sediments. Furthermore, biogeochemical processing in fluvial networks dominated by IRES is likely more temporally than spatially variable. We conclude that biogeochemical research in IRES would benefit from focusing on interactions between different nutrient cycles, surface-groundwater interactions in non-flowing states, and consideration of fluvial network architecture. Our conceptual framework outlines opportunities to advance studies and expand understanding of biogeochemistry in IRES

    Trauma management incorporating focused assessment with computed tomography in trauma (FACTT) - potential effect on survival

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    Background Immediate recognition of life-threatening conditions and injuries is the key to trauma management. To date, the impact of focused assessment with computed tomography in trauma (FACTT) has not been formally assessed. We aimed to find out whether the concept of using FACTT during primary trauma survey has a negative or positive effect on survival. Methods In a retrospective, multicentre study, we compared our time management and probability of survival (Ps) in major trauma patients who received FACTT during trauma resuscitation with the trauma registry of the German Trauma Society (DGU). FACTT is defined as whole-body computed tomography (WBCT) during primary trauma survey. We determined the probability of survival according to the Trauma and Injury Severity Score (TRISS), the Revised Injury Severity Classification score (RISC) and the standardized mortality ratio (SMR). Results We analysed 4.817 patients from the DGU database from 2002 until 2004, 160 (3.3%) were from our trauma centre at the Ludwig-Maximilians-University (LMU) and 4.657 (96.7%) from the DGU group. 73.2% were male with a mean age of 42.5 years, a mean ISS of 29.8. 96.2% had suffered from blunt trauma. Time from admission to FAST (focused assessment with sonography for trauma)(4.3 vs. 8.7 min), chest x-ray (8.1 vs. 16.0 min) and whole-body CT (20.7 vs. 36.6 min) was shorter at the LMU compared to the other trauma centres (p < 0.001). SMR calculated by TRISS was 0.74 (CI95% 0.40-1.08) for the LMU (p = 0.24) and 0.92 (CI95% 0.84-1.01) for the DGU group (p = 0.10). RISC methodology revealed a SMR of 0.69 (95%CI 0.47-0.92) for the LMU (p = 0.043) and 1.00 (95%CI 0.94-1.06) for the DGU group (p = 0.88). Conclusion Trauma management incorporating FACTT enhances a rapid response to life-threatening problems and enables a comprehensive assessment of the severity of each relevant injury. Due to its speed and accuracy, FACTT during primary trauma survey supports rapid decision-making and may increase survival

    The Complete Genome Sequence of Thermoproteus tenax: A Physiologically Versatile Member of the Crenarchaeota

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    Here, we report on the complete genome sequence of the hyperthermophilic Crenarchaeum Thermoproteus tenax (strain Kra 1, DSM 2078(T)) a type strain of the crenarchaeotal order Thermoproteales. Its circular 1.84-megabase genome harbors no extrachromosomal elements and 2,051 open reading frames are identified, covering 90.6% of the complete sequence, which represents a high coding density. Derived from the gene content, T. tenax is a representative member of the Crenarchaeota. The organism is strictly anaerobic and sulfur-dependent with optimal growth at 86 degrees C and pH 5.6. One particular feature is the great metabolic versatility, which is not accompanied by a distinct increase of genome size or information density as compared to other Crenarchaeota. T. tenax is able to grow chemolithoautotrophically (CO2/H-2) as well as chemoorganoheterotrophically in presence of various organic substrates. All pathways for synthesizing the 20 proteinogenic amino acids are present. In addition, two presumably complete gene sets for NADH:quinone oxidoreductase (complex I) were identified in the genome and there is evidence that either NADH or reduced ferredoxin might serve as electron donor. Beside the typical archaeal A(0)A(1)-ATP synthase, a membrane-bound pyrophosphatase is found, which might contribute to energy conservation. Surprisingly, all genes required for dissimilatory sulfate reduction are present, which is confirmed by growth experiments. Mentionable is furthermore, the presence of two proteins (ParA family ATPase, actin-like protein) that might be involved in cell division in Thermoproteales, where the ESCRT system is absent, and of genes involved in genetic competence (DprA, ComF) that is so far unique within Archaea
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