3,484 research outputs found
Studies of high latitude current systems using MAGSAT vector data
The magnetic disturbance fields caused by global external current systems are considered with particular emphasis on improving the understanding of the physical processes which control high latitude current systems. Following processing the MAGSAT data were routinely plotted in the Universal Time (UT) format as well as in a polar plot format. The H'D'U' coordinate system, was adopted as the standard for representing the MAGSAT residual magnetic field vectors. A data file was generated and the TPOLAR computer code was developed to determine from the orbital elements, the time, latitude, and MLT of the extremum latitude of each transpolar segment of orbit. The precision of the vector data set from MAGSAT prompted an extended exploratory phase for data analysis procedures, modeling techniques and phenomenology
Studies of high latitude current systems using Magsat vector data
Disturbance fields caused by global external current systems are analyzed in order to gain an improved understanding of the phydical processes which control high latitude current systems and to increase the confidence level in the identification of internal field levels. The basic approach is to: (1) categorize the vector data by those physical parameters important for investigation of external current systems; (2) map the disturbances for appropriate conditions; (3) model the currents which might cause the mapped disturbances; and (4) correlate results with data from other sources. It is concluded that the Magsat data set appears to have remarkably high precision and quality and should permit major advances to be made in modeling current distribution at high latitudes in the ionosphere and magnetosphere
Specific protein-protein binding in many-component mixtures of proteins
Proteins must bind to specific other proteins in vivo in order to function.
The proteins must bind only to one or a few other proteins of the of order a
thousand proteins typically present in vivo. Using a simple model of a protein,
specific binding in many component mixtures is studied. It is found to be a
demanding function in the sense that it demands that the binding sites of the
proteins be encoded by long sequences of bits, and the requirement for specific
binding then strongly constrains these sequences. This is quantified by the
capacity of proteins of a given size (sequence length), which is the maximum
number of specific-binding interactions possible in a mixture. This calculation
of the maximum number possible is in the same spirit as the work of Shannon and
others on the maximum rate of communication through noisy channels.Comment: 13 pages, 3 figures (changes for v2 mainly notational - to be more in
line with notation in information theory literature
All Teleportation and Dense Coding Schemes
We establish a one-to-one correspondence between (1) quantum teleportation
schemes, (2) dense coding schemes, (3) orthonormal bases of maximally entangled
vectors, (4) orthonormal bases of unitary operators with respect to the
Hilbert-Schmidt scalar product, and (5) depolarizing operations, whose Kraus
operators can be chosen to be unitary. The teleportation and dense coding
schemes are assumed to be ``tight'' in the sense that all Hilbert spaces
involved have the same finite dimension d, and the classical channel involved
distinguishes d^2 signals. A general construction procedure for orthonormal
bases of unitaries, involving Latin Squares and complex Hadamard Matrices is
also presented.Comment: 21 pages, LaTe
Developing Intensity-Duration-Frequency (IDF) Curves From Satellite-Based Precipitation: Methodology and Evaluation
Given the continuous advancement in the retrieval of precipitation from satellites, it is important to develop methods that incorporate satellite-based precipitation data sets in the design and planning of infrastructure. This is because in many regions around the world, in situ rainfall observations are sparse and have insufficient record length. A handful of studies examined the use of satellite-based precipitation to develop intensity-duration-frequency (IDF) curves; however, they have mostly focused on small spatial domains and relied on combining satellite-based with ground-based precipitation data sets. In this study, we explore this issue by providing a methodological framework with the potential to be applied in ungauged regions. This framework is based on accounting for the characteristics of satellite-based precipitation products, namely, adjustment of bias and transformation of areal to point rainfall. The latter method is based on previous studies on the reverse transformation (point to areal) commonly used to obtain catchment-scale IDF curves. The paper proceeds by applying this framework to develop IDF curves over the contiguous United States (CONUS); the data set used is Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks – Climate Data Record (PERSIANN-CDR). IDFs are then evaluated against National Oceanic and Atmospheric Administration (NOAA) Atlas 14 to provide a quantitative estimate of their accuracy. Results show that median errors are in the range of (17–22%), (6–12%), and (3–8%) for one-day, two-day and three-day IDFs, respectively, and return periods in the range (2–100) years. Furthermore, a considerable percentage of satellite-based IDFs lie within the confidence interval of NOAA Atlas 14
Hydrologic Terrain Processing Using Parallel Computing
Abstract: Topography in the form of Digital Elevation Models (DEMs), is widely used to derive information for the modeling of hydrologic processes. Hydrologic terrain analysis augments the information content of digital elevation data by removing spurious pits, deriving a structured flow field, and calculating surfaces of hydrologic information derived from the flow field. The increasing availability of large terrain datasets with very small ground sample distance (GSD) poses a challenge for existing algorithms that process terrain data to extract this hydrologic information. This paper will describe a parallel algorithm that has been developed to enhance hydrologic terrain pre-processing so that larger datasets can be more efficiently computed. This paper describes a Message Passing Interface (MPI) parallel implementation for Pit Removal. This key functionality is used within the Terrain Analysis Using Digital Elevation Models (TauDEM) package to remove spurious elevation depressions that are an artifact of the raster representation of the terrain. The parallel algorithm works by decomposing the domain into stripes or tiles where each tile is processed by a separate processor. This method also reduces the memory requirements of each processor so that larger size grids can be processed. The parallel pit removal algorithm is adapted from the method of Planchon and Darboux that starts from a large elevation then iteratively scans the grid, lowering each grid cell to the maximum of the original elevation or the lowest neighbor. The MPI implementation reconcile
Spatial coherence and density correlations of trapped Bose gases
We study first and second order coherence of trapped dilute Bose gases using
appropriate correlation functions. Special attention is given to the discussion
of second order or density correlations. Except for a small region around the
surface of a Bose-Einstein condensate the correlations can be accurately
described as those of a locally homogeneous gas with a spatially varying
chemical potential. The degrees of first and second order coherence are
therefore functions of temperature, chemical potential, and position. The
second order correlation function is governed both by the tendency of bosonic
atoms to cluster and by a strong repulsion at small distances due to atomic
interactions. In present experiments both effects are of comparable magnitude.
Below the critical temperature the range of the bosonic correlation is affected
by the presence of collective quasi-particle excitations. The results of some
recent experiments on second and third order coherence are discussed. It is
shown that the relation between the measured quantities and the correlation
functions is much weaker than previously assumed.Comment: RevTeX, 25 pages with 7 Postscript figure
Doppler cooling and trapping on forbidden transitions
Ultracold atoms at temperatures close to the recoil limit have been achieved
by extending Doppler cooling to forbidden transitions. A cloud of ^40Ca atoms
has been cooled and trapped to a temperature as low as 6 \mu K by operating a
magneto-optical trap on the spin-forbidden intercombination transition.
Quenching the long-lived excited state with an additional laser enhanced the
scattering rate by a factor of 15, while a high selectivity in velocity was
preserved. With this method more than 10% of pre-cooled atoms from a standard
magneto-optical trap have been transferred to the ultracold trap. Monte-Carlo
simulations of the cooling process are in good agreement with the experiments
Application of a stochastic modeling to evaluate tuberculosis onset in patients treated with tumor necrosis factor inhibitors
In this manuscript we apply stochastic modeling to investigate the risk of
reactivation of latent mycobacterial infections in patients undergoing
treatment with tumor necrosis factor inhibitors. First, we review the
perspective proposed by one of the authors in a previous work and which
consists in predicting the occurrence of reactivation of latent tuberculosis
infection or newly acquired tuberculosis during treatment; this is based on
variational procedures on a simple set of parameters (e.g. rate of reactivation
of a latent infection). Then, we develop a full analytical study of this
approach through a Markov chain analysis and we find an exact solution for the
temporal evolution of the number of cases of tuberculosis infection
(re)activation. The analytical solution is compared with Monte Carlo
simulations and with experimental data, showing overall excellent agreement.
The generality of this theoretical framework allows to investigate also the
case of non-tuberculous mycobacteria infections; in particular, we show that
reactivation in that context plays a minor role. This may suggest that, while
the screening for tuberculous is necessary prior to initiating biologics, when
considering non-tuberculous mycobacteria only a watchful monitoring during the
treatment is recommended. The framework outlined in this paper is quite general
and could be extremely promising in further researches on drug-related adverse
events.Comment: 26 pages, 7 figure
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Real-world diagnostic potential of bacterial biomarkers of canine periodontitis.
INTRODUCTION: The objective of this study was to investigate the diagnostic potential of bacterial biomarkers by comparing the performance of molecular detection assays with clinical assessments of dogs oral health performed by veterinarians. METHODS: Supragingival and subgingival plaque samples were collected from 127 client-owned dogs, pre-booked for procedures under general anesthesia, visiting veterinary practices in the United States. DNA was extracted and bacterial biomarkers quantified using quantitative polymerase chain reaction. Gingivitis and periodontitis were recorded by a trained clinician using the Weighted Gingivitis Periodontitis Score which involved assessing the buccal surfaces of 18 teeth while under general anesthesia. Intraoral dental radiographs of the left and right mandibular first molar teeth were also obtained. These data were then used to establish the diagnostic performance of the molecular assay to detect periodontitis. RESULTS: An initial conscious, visual oral examination performed by the veterinarian identified 67.7% of dogs as having periodontitis, but examination under general anesthesia indicated a higher proportion (86.6%). Analysis of supragingival plaque samples collected by veterinarians from conscious and unconscious dogs demonstrated the assay had an accuracy of 77.7 to 80.9%, a sensitivity of 77.6 to 81.0%, and a specificity of 80.0%. DISCUSSION: Use of this molecular screening tool in conscious dogs has the potential to improve early periodontal disease detection and support veterinary decision making, ultimately improving the oral health of dogs and consequently their quality of life
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