404 research outputs found

    Fragmentation with a Cut on Thrust: Predictions for B-factories

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    When high-energy single-hadron production takes place inside an identified jet, there are important correlations between the fragmentation and phase-space cuts. For example, when one-hadron yields are measured in on-resonance B-factory data, a cut on the thrust event shape T is required to remove the large b-quark contribution. This leads to a dijet final state restriction for the light-quark fragmentation process. Here we complete our analysis of unpolarized fragmentation of (light) quarks and gluons to a light hadron h with energy fraction z in e+ e- -> dijet + h at the center-of-mass energy Q=10.58 GeV. In addition to the next-to-next-to-leading order resummation of logarithms of 1-T, we include the next-to-leading order (NLO) nonsingular O(1-T) contribution to the cross section, the resummation of threshold logarithms of 1-z, and the leading nonperturbative contribution to the soft function. Our results for the correlations between fragmentation and the thrust cut are presented in a way that can be directly tested against B-factory data. These correlations are also observed in Pythia, but are surprisingly smaller at NLO.Comment: 10 pages + appendices, 13 figures, v2:updated discussion, journal versio

    A family of repulsive neutral conductor geometries via abstract vector spaces

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    Recently it was shown that it is possible for a neutral, isolated conductor to repel a point charge (or, a point dipole). Here we prove this fact using general properties of vectors and operators in an inner-product space. We find that a family of neutral, isolated conducting surface geometries, whose shape lies somewhere between a hemispherical bowl and an ovoid, will repel a point charge. In addition, we find another family of surfaces (with a different shape) that will repel a point dipole. The latter geometry can lead to Casimir repulsion.Comment: 6 pages, 4 figure

    AOIPS water resources data management system

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    A geocoded data management system applicable for hydrological applications was designed to demonstrate the utility of the Atmospheric and Oceanographic Information Processing System (AOIPS) for hydrological applications. Within that context, the geocoded hydrology data management system was designed to take advantage of the interactive capability of the AOIPS hardware. Portions of the Water Resource Data Management System which best demonstrate the interactive nature of the hydrology data management system were implemented on the AOIPS. A hydrological case study was prepared using all data supplied for the Bear River watershed located in northwest Utah, southeast Idaho, and western Wyoming

    JOURNAL OF FIRST TRIP OF UNIVERSITY OF CALIFORNIA TO JOHN DAY BEDS OF EASTERN OREGON

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    32 pagesThe journal is Dr. Miller's account of the University of California field expedition into the John Day Basin of Central Oregon in 1899. This expedition, as well as many that followed from that institution, was led by Dr. John C. Merriam. It began a long association of the University of California with that area of Oregon, an association which still continues. Although the events of this journal occurred over seventy years ago, they by no means represent the first investigation of the area, for these beds were already famous when Miller first saw them. Condon had first seen them forty years previously, and such well known paleontologists as Marsh and Cope among many others had collected there. It was not until the work of Merriam and his students from the University of California began that any real understanding of the geology of the area or the sequence of the faunas present was developed

    Evaluation of Noninvasive Respiratory Volume Monitoring in the PACU of a Low Resource Kenyan Hospital

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    This research aims to evaluate the use of the noninvasive respiratory volume monitor (RVM) compared to the standard of care (SOC) in the Post-Anesthesia Care Unit (PACU) of Kijabe Hospital, Kenya. The RVM provides real-time measurements for quantitative monitoring of non-intubated patients. Our evaluation was focused on the incidence of postoperative opioid-induced respiratory depression (OIRD). The RVM cohort (N = 50) received quantitative OIRD assessment via the RVM, which included respiratory rate, minute ventilation, and tidal volume. The SOC cohort (N = 46) received qualitative OIRD assessment via patient monitoring with oxygenation measurements (SpO2) and physical examination. All diagnosed cases of OIRD were in the RVM cohort (9/50). In the RVM cohort, participants stayed longer in the PACU and required more frequent airway maneuvers and supplemental oxygen, compared to SOC (all p \u3c 0.05). The SOC cohort may have had fewer diagnoses of OIRD due to the challenging task of distinguishing hypoventilation versus OIRD in the absence of quantitative data. To account for the higher OIRD risk with general anesthesia (GA), a subgroup analysis was performed for only participants who underwent GA, which showed similar results. The use of RVM for respiratory monitoring of OIRD may allow for more proactive care

    Revealing a signaling role of phytosphingosine-1-phosphate in yeast

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    Perturbing metabolic systems of bioactive sphingolipids with genetic approachMultiple types of “omics” data collected from the systemSystems approach for integrating multiple “omics” informationPredicting signal transduction information flow: lipid; TF activation; gene expressio

    Integrated Clustering and Anomaly Detection (INCAD) for Streaming Data (Revised)

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    Most current clustering based anomaly detection methods use scoring schema and thresholds to classify anomalies. These methods are often tailored to target specific data sets with "known" number of clusters. The paper provides a streaming clustering and anomaly detection algorithm that does not require strict arbitrary thresholds on the anomaly scores or knowledge of the number of clusters while performing probabilistic anomaly detection and clustering simultaneously. This ensures that the cluster formation is not impacted by the presence of anomalous data, thereby leading to more reliable definition of "normal vs abnormal" behavior. The motivations behind developing the INCAD model and the path that leads to the streaming model is discussed.Comment: 13 pages; fixes typos in equations 5,6,9,10 on inference using Gibbs samplin
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