1,954 research outputs found

    An empirically observed pitch-angle diffusion eigenmode in the Earth\u27s electron belt near L* = 5.0

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    Abstract Using data from NASA\u27s Van Allen Probes, we have identified a synchronized exponential decay of electron flux in the outer zone, near L* = 5.0. Exponential decays strongly indicate the presence of a pure eigenmode of a diffusion operator acting in the synchronized dimension(s). The decay has a time scale of about 4 days with no dependence on pitch angle. While flux at nearby energies and L* is also decaying exponentially, the decay time varies in those dimensions. This suggests the primary decay mechanism is elastic pitch angle scattering, which itself depends on energy and L *. We invert the shape of the observed eigenmode to obtain an approximate shape of the pitch angle diffusion coefficient and show excellent agreement with diffusion by plasmaspheric hiss. Our results suggest that empirically derived eigenmodes provide a powerful diagnostic of the dynamic processes behind exponential decays

    A Probabilistic, Facility-Centric Approach to Lightning Strike Location

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    A new probabilistic facility-centric approach to lightning strike location has been developed. This process uses the bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to determine the probability that the stroke is inside any specified radius of any location, even if that location is not centered on or even with the location error ellipse. This technique is adapted from a method of calculating the probability of debris collision~ith spacecraft. Such a technique is important in spaceport processing activities because it allows engineers to quantify the risk of induced current damage to critical electronics due to nearby lightning strokes. This technique was tested extensively and is now in use by space launch organizations at Kennedy Space Center and Cape Canaveral Air Force Station. Future applications could include forensic meteorology

    An Analysis of Peak Wind Speed Data from Collocated Mechanical and Ultrasonic Anemometers

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    This study compared peak wind speeds reported by mechanical and ultrasonic anemometers at Cape Canaveral Air Force Station and Kennedy Space Center (CCAFS/KSC) on the east central coast of Florida and Vandenberg Air Force Base (VAFB) on the central coast of California. Launch Weather Officers, forecasters, and Range Safety analysts need to understand the performance of wind sensors at CCAFS/KSC and VAFB for weather warnings, watches, advisories, special ground processing operations, launch pad exposure forecasts, user Launch Commit Criteria (LCC) forecasts and evaluations, and toxic dispersion support. The legacy CCAFS/KSC and VAFB weather tower wind instruments are being changed from propeller-and-vane (CCAFS/KSC) and cup-and-vane (VAFB) sensors to ultrasonic sensors under the Range Standardization and Automation (RSA) program. Mechanical and ultrasonic wind measuring techniques are known to cause differences in the statistics of peak wind speed as shown in previous studies. The 45th Weather Squadron (45 WS) and the 30th Weather Squadron (30 WS) requested the Applied Meteorology Unit (AMU) to compare data between the RSA ultrasonic and legacy mechanical sensors to determine if there are significant differences. Note that the instruments were sited outdoors under naturally varying conditions and that this comparison was not designed to verify either technology. Approximately 3 weeks of mechanical and ultrasonic wind data from each range from May and June 2005 were used in this study. The CCAFS/KSC data spanned the full diurnal cycle, while the VAFB data were confined to 1000-1600 local time. The sample of 1-minute data from numerous levels on five different towers on each range totaled more than 500,000 minutes of data (482,979 minutes of data after quality control). The ten towers were instrumented at several levels, ranging from 12 ft to 492 ft above ground level. The ultrasonic sensors were collocated at the same vertical levels as the mechanical sensors and typically within 15 ft horizontally of each another. Data from a total of 53 RSA ultrasonic sensors, collocated with mechanical sensors were compared. The 1- minute average wind speed/direction and the 1-second peak wind speed/direction were compared

    Extracting the depolarization coefficient D_NN from data measured with a full acceptance detector

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    The spin transfer from vertically polarized beam protons to Lambda or Sigma hyperons of the associated strangeness production pp -> pK Lambda (Sigma) is described with the depolarization coefficient D_NN. As the polarization of the hyperons is determined by their weak decays, detectors, which have a large acceptance for the decay particles, are needed. In this paper a formula is derived, which describes the depolarization coefficient D_NN by count rates of a 4 pi detector. It is shown, that formulas, which are given in publications for detectors with restricted acceptance, are specific cases of this formula for a 4 pi detector.Comment: Accepted for publication by Nuclear Instruments and Methods in Physics Research Section

    An Analysis of Peak Wind Speed Data from Collocated Mechanical and Ultrasonic Anemometers

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    This study focuses on a comparison of peak wind speeds reported by mechanical and ultrasonic anemometers at Cape Canaveral Air Force Station and Kennedy Space Center (CCAFS/KSC) on the east central coast of Florida and Vandenberg Air Force Base (VAFB) on the central coast of California. The legacy mechanical wind instruments on CCAFS/KSC and VAFB weather towers are being changed from propeller-and-vane (CCAFS/KSC) and cup-and-vane (VAFB) sensors to ultrasonic sensors under the Range Standardization and Automation (RSA) program. The wind tower networks on KSC/CCAFS and VAFB have 41 and 27 towers, respectively. Launch Weather Officers, forecasters, and Range Safety analysts at both locations need to understand the performance of the new wind sensors for a myriad of reasons that include weather warnings, watches, advisories, special ground processing operations, launch pad exposure forecasts, user Launch Commit Criteria (LCC) forecasts and evaluations, and toxic dispersion support. The Legacy sensors measure wind speed and direction mechanically. The ultrasonic RSA sensors have no moving parts. Ultrasonic sensors were originally developed to measure very light winds (Lewis and Dover 2004). The technology has evolved and now ultrasonic sensors provide reliable wind data over a broad range of wind speeds. However, because ultrasonic sensors respond more quickly than mechanical sensors to rapid fluctuations in speed, characteristic of gusty wind conditions, comparisons of data from the two sensor types have shown differences in the statistics of peak wind speeds (Lewis and Dover 2004). The 45th Weather Squadron (45 WS) and the 30 WS requested the Applied Meteorology Unit (AMU) to compare data from RSA and Legacy sensors to determine if there are significant differences in peak wind speed information from the two systems

    Quality control for more reliable integration of deep learning-based image segmentation into medical workflows

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    Machine learning algorithms underpin modern diagnostic-aiding software, whichhas proved valuable in clinical practice, particularly in radiology. However,inaccuracies, mainly due to the limited availability of clinical samples fortraining these algorithms, hamper their wider applicability, acceptance, andrecognition amongst clinicians. We present an analysis of state-of-the-artautomatic quality control (QC) approaches that can be implemented within thesealgorithms to estimate the certainty of their outputs. We validated the mostpromising approaches on a brain image segmentation task identifying whitematter hyperintensities (WMH) in magnetic resonance imaging data. WMH are acorrelate of small vessel disease common in mid-to-late adulthood and areparticularly challenging to segment due to their varied size, anddistributional patterns. Our results show that the aggregation of uncertaintyand Dice prediction were most effective in failure detection for this task.Both methods independently improved mean Dice from 0.82 to 0.84. Our workreveals how QC methods can help to detect failed segmentation cases andtherefore make automatic segmentation more reliable and suitable for clinicalpractice.<br

    Evaluation of bio-integration of rat knee cartilage repair using in vivo MRI at 7T

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    National audienceHigh-field magnetic resonance systems allowing high-resolution magnetic resosnance imaging -HR-MRI) is a powerful research tool to visualize and examine hyaline cartilage of small joints non-invasively. Different studies have shown that qualitative assessment of degenerative joint disease, derived from MR images, was reliable. The capability to show pathologic changes throughout the time course of the disease from three-dimensional (3D) datasets has also been demonstrated. However, in vivo quantitative imaging for an accurate determination of cartilage thickness and volume is challenging due to small size of rodent joints and dedicated coils are mandatory. Surgical articular cartilage repair therapies for cartilage defects such as osteochondral autograft transfer, autologous chondrocyte implantation or matrix associated autologous cell transplantation require non invasive technique to evaluate longitudinally the biointegration of the graft. The aim of this study was to follow using 7T MRI the biointegration of biomaterials colonized by mesenchymal stem cells or not after implantation in a calibrated full thickness focal lesion in the rat knee

    Applied Meteorology Unit - Operational Contributions to Spaceport Canaveral

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    The Applied Meteorology Unit (AMU) provides technology development, evaluation and transition services to improve operational weather support to the Space Shuttle and the National Space Program. It is established under a Memorandum of Understanding among NASA, the Air Force and the National .Weather Service (NWS). The AMU is funded and managed by NASA and operated by ENSCO, Inc. through a competitively awarded NASA contract. The primary customers are the 45th Weather Squadron (45WS) at Cape Canaveral Air Force Station (CCAFS), FL; the Spaceflight Meteorology Group (SMG) at Johnson Space Center (JSC) in Houston, TX; and the NWS office in Melbourne, FL (NWS MLB). This paper will briefly review the AMU's history and describe the three processes through which its work is assigned. Since its inception in 1991 the AMU has completed 72 projects, all of which are listed at the end of this paper. At least one project that highlights each of the three tasking processes will be briefly reviewed. Some of the projects that have been especially beneficial to the space program will also be discussed in more detail, as will projects that developed significant new techniques or science in applied meteorology
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