5 resultados para building footprint

em Duke University


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We report the observation with the North Alabama Lightning Mapping Array (LMA) related to a terrestrial gamma-ray flash (TGF) detected by RHESSI on 26 July 2008. The LMA data explicitly show the TGF was produced during the initial development of a compact intracloud (IC) lightning flash between a negative charge region centered at about 8.5 km above sea level (-22C temperature level) a higher positive region centered at 13 km, both confined to the convective core of an isolated storm in close proximity to the RHESSI footprint. After the occurrence of an LMA source with a high peak power (26 kW), the initial lightning evolution caused an unusually large IC current moment that became detectable 2 ms after the first LMA source and increased for another 2 ms, during which the burst of gamma-rays was produced. This slowly building current moment was most likely associated with the upward leader progression, which produced an uncommonly large IC charge moment change (+90 Ckm) in 3 ms while being punctuated by a sequence of fast discharge. These observations suggest that the leader development may be involved in the TGF production. Copyright © 2010 by the American Geophysical Union.

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We estimate a carbon mitigation cost curve for the U.S. commercial sector based on econometric estimation of the responsiveness of fuel demand and equipment choices to energy price changes. The model econometrically estimates fuel demand conditional on fuel choice, which is characterized by a multinomial logit model. Separate estimation of end uses (e.g., heating, cooking) using the U.S. Commercial Buildings Energy Consumption Survey allows for exceptionally detailed estimation of price responsiveness disaggregated by end use and fuel type. We then construct aggregate long-run elasticities, by fuel type, through a series of simulations; own-price elasticities range from -0.9 for district heat services to -2.9 for fuel oil. The simulations form the basis of a marginal cost curve for carbon mitigation, which suggests that a price of $20 per ton of carbon would result in an 8% reduction in commercial carbon emissions, and a price of $100 per ton would result in a 28% reduction. © 2008 Elsevier B.V. All rights reserved.

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DNaseI footprinting is an established assay for identifying transcription factor (TF)-DNA interactions with single base pair resolution. High-throughput DNase-seq assays have recently been used to detect in vivo DNase footprints across the genome. Multiple computational approaches have been developed to identify DNase-seq footprints as predictors of TF binding. However, recent studies have pointed to a substantial cleavage bias of DNase and its negative impact on predictive performance of footprinting. To assess the potential for using DNase-seq to identify individual binding sites, we performed DNase-seq on deproteinized genomic DNA and determined sequence cleavage bias. This allowed us to build bias corrected and TF-specific footprint models. The predictive performance of these models demonstrated that predicted footprints corresponded to high-confidence TF-DNA interactions. DNase-seq footprints were absent under a fraction of ChIP-seq peaks, which we show to be indicative of weaker binding, indirect TF-DNA interactions or possible ChIP artifacts. The modeling approach was also able to detect variation in the consensus motifs that TFs bind to. Finally, cell type specific footprints were detected within DNase hypersensitive sites that are present in multiple cell types, further supporting that footprints can identify changes in TF binding that are not detectable using other strategies.