276 research outputs found

    Emission estimates of HCFCs and HFCs in California from the 2010 CalNex study

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    The CalNex 2010 (California Research at the Nexus of Air Quality and Climate Change) study was designed to evaluate the chemical composition of air masses over key source regions in California. During May to June 2010, air samples were collected on board a National Oceanic and Atmospheric Administration (NOAA) WP-3D aircraft over the South Coast Air Basin of California (SoCAB) and the Central Valley (CV). This paper analyzes six effective greenhouse gases - chlorodifluoromethane (HCFC-22), 1,1-dichloro-1-fluoroethane (HCFC-141b), 1-chloro-1,1-difluoroethane (HCFC-142b), 2-chloro-1,1,1,2-tetrafluoroethane (HCFC-124), 1,1,1,2- tetrafluoroethane (HFC-134a), and 1,1-difluoroethane (HFC-152a) - providing the most comprehensive characterization of chlorofluorocarbon (CFC) replacement compound emissions in California. Concentrations of measured HCFCs and HFCs are enhanced greatly throughout the SoCAB and CV, with highest levels observed in the SoCAB: 310 ± 92 pptv for HCFC-22, 30.7 ± 18.6 pptv for HCFC-141b, 22.9 ± 2.0 pptv for HCFC-142b, 4.86 ± 2.56 pptv for HCFC-124, 109 ± 46.4 pptv for HFC-134a, and 91.2 ± 63.9 pptv for HFC-152a. Annual emission rates are estimated for all six compounds in the SoCAB using the measured halocarbon to carbon monoxide (CO) mixing ratios and CO emissions inventories. Emission rates of 3.05 ± 0.70 Gg for HCFC-22, 0.27 ± 0.07 Gg for HCFC-141b, 0.06 ± 0.01 Gg for HCFC-142b, 0.11 ± 0.03 Gg for HCFC-124, 1.89 ± 0.43 Gg for HFC-134a, and 1.94 ± 0.45 Gg for HFC-152b for the year 2010 are calculated for the SoCAB. These emissions are extrapolated from the SoCAB region to the state of California using population data. Results from this study provide a baseline emission rate that will help future studies determine if HCFC and HFC mitigation strategies are successful. Key PointsHCFC and HFC emissions are calculated for the year 2010 for the SoCABEmissions are extrapolated to the state of CaliforniaEmissions are calculated using CalNex field measurements © 2013. American Geophysical Union. All Rights Reserved

    Uniqueness of the compactly supported weak solutions of the relativistic Vlasov-Darwin system

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    We use optimal transportation techniques to show uniqueness of the compactly supported weak solutions of the relativistic Vlasov-Darwin system. Our proof extends the method used by Loeper in J. Math. Pures Appl. 86, 68-79 (2006) to obtain uniqueness results for the Vlasov-Poisson system.Comment: AMS-LaTeX, 21 page

    Autoencoder extreme learning machine for fingerprint-based positioning: A good weight initialization is decisive

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    Indoor positioning based on machine-learning (ML) models has attracted widespread interest in the last few years, given its high performance and usability. Supervised, semisupervised, and unsupervised models have thus been widely used in this field, not only to estimate the user position, but also to compress, clean, and denoise fingerprinting datasets. Some scholars have focused on developing, improving, and optimizing ML models to provide accurate solutions to the end user. This article introduces a novel method to initialize the input weights in autoencoder extreme learning machine (AE-ELM), namely factorized input data (FID), which is based on the normalized form of the orthogonal component of the input data. AE-ELM with FID weight initialization is used to efficiently reduce the radio map. Once the dimensionality of the dataset is reduced, we use k -nearest neighbors to perform the position estimation. This research work includes a comparative analysis with several traditional ways to initialize the input weights in AE-ELM, showing that FID provide a significantly better reconstruction error. Finally, we perform an assessment with 13 indoor positioning datasets collected from different buildings and in different countries. We show that the dimensionality of the datasets can be reduced more than 11 times on average, while the positioning error suffers only a small increment of 15% (on average) in comparison to the baseline

    ATLAS silicon module assembly and qualification tests at IFIC Valencia

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    ATLAS experiment, designed to probe the interactions of particles emerging out of proton proton collisions at energies of up to 14 TeV, will assume operation at the Large Hadron Collider (LHC) at CERN in 2007. This paper discusses the assembly and the quality control tests of forward detector modules for the ATLAS silicon microstrip detector assembled at the Instituto de Fisica Corpuscular (IFIC) in Valencia. The construction and testing procedures are outlined and the laboratory equipment is briefly described. Emphasis is given on the module quality achieved in terms of mechanical and electrical stability.Comment: 23 pages, 38 EPS figures, uses JINST LaTeX clas

    Forward SCT Module Assembly and Quality Control at IFIC Valencia

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    This note discusses the assembly and the quality control tests of 282 forward detector modules for the ATLAS Semiconductor Tracker assembled at the Instituto de Fisica Corpuscular (IFIC) in Valencia. The construction and testing procedures are outlined and the laboratory equipment is briefly described. Emphasis is given on the module quality achieved in terms of mechanical and electrical stability

    Expected Performance of the ATLAS Experiment - Detector, Trigger and Physics

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    A detailed study is presented of the expected performance of the ATLAS detector. The reconstruction of tracks, leptons, photons, missing energy and jets is investigated, together with the performance of b-tagging and the trigger. The physics potential for a variety of interesting physics processes, within the Standard Model and beyond, is examined. The study comprises a series of notes based on simulations of the detector and physics processes, with particular emphasis given to the data expected from the first years of operation of the LHC at CERN

    Neuroinflammation, Mast Cells, and Glia: Dangerous Liaisons

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    The perspective of neuroinflammation as an epiphenomenon following neuron damage is being replaced by the awareness of glia and their importance in neural functions and disorders. Systemic inflammation generates signals that communicate with the brain and leads to changes in metabolism and behavior, with microglia assuming a pro-inflammatory phenotype. Identification of potential peripheral-to-central cellular links is thus a critical step in designing effective therapeutics. Mast cells may fulfill such a role. These resident immune cells are found close to and within peripheral nerves and in brain parenchyma/meninges, where they exercise a key role in orchestrating the inflammatory process from initiation through chronic activation. Mast cells and glia engage in crosstalk that contributes to accelerate disease progression; such interactions become exaggerated with aging and increased cell sensitivity to stress. Emerging evidence for oligodendrocytes, independent of myelin and support of axonal integrity, points to their having strong immune functions, innate immune receptor expression, and production/response to chemokines and cytokines that modulate immune responses in the central nervous system while engaging in crosstalk with microglia and astrocytes. In this review, we summarize the findings related to our understanding of the biology and cellular signaling mechanisms of neuroinflammation, with emphasis on mast cell-glia interactions

    Identification of a Novel Risk Locus for Multiple Sclerosis at 13q31.3 by a Pooled Genome-Wide Scan of 500,000 Single Nucleotide Polymorphisms

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    Multiple sclerosis is a chronic inflammatory demyelinating disease of the central nervous system with an important genetic component and strongest association driven by the HLA genes. We performed a pooling-based genome-wide association study of 500,000 SNPs in order to find new loci associated with the disease. After applying several criteria, 320 SNPs were selected from the microarrays and individually genotyped in a first and independent Spanish Caucasian replication cohort. The 8 most significant SNPs validated in this cohort were also genotyped in a second US Caucasian replication cohort for confirmation. The most significant association was obtained for SNP rs3129934, which neighbors the HLA-DRB/DQA loci and validates our pooling-based strategy. The second strongest association signal was found for SNP rs1327328, which resides in an unannotated region of chromosome 13 but is in linkage disequilibrium with nearby functional elements that may play important roles in disease susceptibility. This region of chromosome 13 has not been previously identified in MS linkage genome screens and represents a novel risk locus for the disease
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