Fast adaptive estimation of multidimensional psychometric functions.
DiMattina, Christopher
2015-01-01
Recently in vision science there has been great interest in understanding the perceptual representations of complex multidimensional stimuli. Therefore, it is becoming very important to develop methods for performing psychophysical experiments with multidimensional stimuli and efficiently estimating psychometric models that have multiple free parameters. In this methodological study, I analyze three efficient implementations of the popular Ψ method for adaptive data collection, two of which are novel approaches to psychophysical experiments. Although the standard implementation of the Ψ procedure is intractable in higher dimensions, I demonstrate that my implementations generalize well to complex psychometric models defined in multidimensional stimulus spaces and can be implemented very efficiently on standard laboratory computers. I show that my implementations may be of particular use for experiments studying how subjects combine multiple cues to estimate sensory quantities. I discuss strategies for speeding up experiments and suggest directions for future research in this rapidly growing area at the intersection of cognitive science, neuroscience, and machine learning.
Fast adaptive estimation of multidimensional psychometric functions.
DiMattina, Christopher
2015-01-01
Recently in vision science there has been great interest in understanding the perceptual representations of complex multidimensional stimuli. Therefore, it is becoming very important to develop methods for performing psychophysical experiments with multidimensional stimuli and efficiently estimating psychometric models that have multiple free parameters. In this methodological study, I analyze three efficient implementations of the popular Ψ method for adaptive data collection, two of which are novel approaches to psychophysical experiments. Although the standard implementation of the Ψ procedure is intractable in higher dimensions, I demonstrate that my implementations generalize well to complex psychometric models defined in multidimensional stimulus spaces and can be implemented very efficiently on standard laboratory computers. I show that my implementations may be of particular use for experiments studying how subjects combine multiple cues to estimate sensory quantities. I discuss strategies for speeding up experiments and suggest directions for future research in this rapidly growing area at the intersection of cognitive science, neuroscience, and machine learning. PMID:26200886
Image matrix processor for fast multi-dimensional computations
Roberson, G.P.; Skeate, M.F.
1996-10-15
An apparatus for multi-dimensional computation is disclosed which comprises a computation engine, including a plurality of processing modules. The processing modules are configured in parallel and compute respective contributions to a computed multi-dimensional image of respective two dimensional data sets. A high-speed, parallel access storage system is provided which stores the multi-dimensional data sets, and a switching circuit routes the data among the processing modules in the computation engine and the storage system. A data acquisition port receives the two dimensional data sets representing projections through an image, for reconstruction algorithms such as encountered in computerized tomography. The processing modules include a programmable local host, by which they may be configured to execute a plurality of different types of multi-dimensional algorithms. The processing modules thus include an image manipulation processor, which includes a source cache, a target cache, a coefficient table, and control software for executing image transformation routines using data in the source cache and the coefficient table and loading resulting data in the target cache. The local host processor operates to load the source cache with a two dimensional data set, loads the coefficient table, and transfers resulting data out of the target cache to the storage system, or to another destination. 10 figs.
Image matrix processor for fast multi-dimensional computations
Roberson, George P.; Skeate, Michael F.
1996-01-01
An apparatus for multi-dimensional computation which comprises a computation engine, including a plurality of processing modules. The processing modules are configured in parallel and compute respective contributions to a computed multi-dimensional image of respective two dimensional data sets. A high-speed, parallel access storage system is provided which stores the multi-dimensional data sets, and a switching circuit routes the data among the processing modules in the computation engine and the storage system. A data acquisition port receives the two dimensional data sets representing projections through an image, for reconstruction algorithms such as encountered in computerized tomography. The processing modules include a programmable local host, by which they may be configured to execute a plurality of different types of multi-dimensional algorithms. The processing modules thus include an image manipulation processor, which includes a source cache, a target cache, a coefficient table, and control software for executing image transformation routines using data in the source cache and the coefficient table and loading resulting data in the target cache. The local host processor operates to load the source cache with a two dimensional data set, loads the coefficient table, and transfers resulting data out of the target cache to the storage system, or to another destination.
Gridding and fast Fourier transformation on non-uniformly sparse sampled multidimensional NMR data.
Jiang, Bin; Jiang, Xianwang; Xiao, Nan; Zhang, Xu; Jiang, Ling; Mao, Xi-an; Liu, Maili
2010-05-01
For multidimensional NMR method, indirect dimensional non-uniform sparse sampling can dramatically shorten acquisition time of the experiments. However, the non-uniformly sampled NMR data cannot be processed directly using fast Fourier transform (FFT). We show that the non-uniformly sampled NMR data can be reconstructed to Cartesian grid with the gridding method that has been wide applied in MRI, and sequentially be processed using FFT. The proposed gridding-FFT (GFFT) method increases the processing speed sharply compared with the previously proposed non-uniform Fourier Transform, and may speed up application of the non-uniform sparse sampling approaches. PMID:20236843
Gridding and fast Fourier transformation on non-uniformly sparse sampled multidimensional NMR data
NASA Astrophysics Data System (ADS)
Jiang, Bin; Jiang, Xianwang; Xiao, Nan; Zhang, Xu; Jiang, Ling; Mao, Xi-an; Liu, Maili
2010-05-01
For multidimensional NMR method, indirect dimensional non-uniform sparse sampling can dramatically shorten acquisition time of the experiments. However, the non-uniformly sampled NMR data cannot be processed directly using fast Fourier transform (FFT). We show that the non-uniformly sampled NMR data can be reconstructed to Cartesian grid with the gridding method that has been wide applied in MRI, and sequentially be processed using FFT. The proposed gridding-FFT (GFFT) method increases the processing speed sharply compared with the previously proposed non-uniform Fourier Transform, and may speed up application of the non-uniform sparse sampling approaches.
Design of Multidimensional Shinnar-Le Roux RF Pulses
Ma, Chao; Liang, Zhi-Pei
2014-01-01
Purpose To generalize the conventional Shinnar-Le Roux (SLR) method for the design of multidimensional RF pulses. Methods Using echo-planar gradients, the multidimensional RF pulse design problem was converted into a series of 1D polynomial design problems. Each of the 1D polynomial design problems was solved efficiently. B0 inhomogeneity compensation and design of spatial-spectral pulses were also considered. Results The proposed method was used to design 2D excitation and refocusing pulses. The results were validated through Bloch equation simulation and experiments on a 3.0 T scanner. Large-tip-angle, equiripple-error, multidimensional excitation was achieved with ripple levels closely matching the design specifications. Conclusion The conventional SLR method can be extended to design multidimensional RF pulses. The proposed method achieves almost equiripple excitation errors, allows easy control of the tradeoff among design parameters, and is computationally efficient. PMID:24578212
Wu, Zhaohua; Feng, Jiaxin; Qiao, Fangli; Tan, Zhe-Min
2016-04-13
In this big data era, it is more urgent than ever to solve two major issues: (i) fast data transmission methods that can facilitate access to data from non-local sources and (ii) fast and efficient data analysis methods that can reveal the key information from the available data for particular purposes. Although approaches in different fields to address these two questions may differ significantly, the common part must involve data compression techniques and a fast algorithm. This paper introduces the recently developed adaptive and spatio-temporally local analysis method, namely the fast multidimensional ensemble empirical mode decomposition (MEEMD), for the analysis of a large spatio-temporal dataset. The original MEEMD uses ensemble empirical mode decomposition to decompose time series at each spatial grid and then pieces together the temporal-spatial evolution of climate variability and change on naturally separated timescales, which is computationally expensive. By taking advantage of the high efficiency of the expression using principal component analysis/empirical orthogonal function analysis for spatio-temporally coherent data, we design a lossy compression method for climate data to facilitate its non-local transmission. We also explain the basic principles behind the fast MEEMD through decomposing principal components instead of original grid-wise time series to speed up computation of MEEMD. Using a typical climate dataset as an example, we demonstrate that our newly designed methods can (i) compress data with a compression rate of one to two orders; and (ii) speed-up the MEEMD algorithm by one to two orders. PMID:26953173
NASA Astrophysics Data System (ADS)
Wu, Z.
2015-12-01
In this big data era, it is more urgent than ever to solve two major issues: (1) fast data transmission method that can facilitate access to data from non-local sources, and (2) fast and efficient data analysis methods that can reveal the key information from the available data for particular purposes. Although approaches in different fields to address these two questions may differ significantly, the common part must involve data compression techniques and fast algorithm. In this paper, we introduce the recently developed adaptive and spatiotemporally local analysis method, namely the fast multi-dimensional ensemble empirical mode decomposition (MEEMD), for the analysis of large spatiotemporal dataset. The original MEEMD uses ensemble empirical mode decomposition (EEMD) to decompose time series at each spatial grid and then pieces together the temporal-spatial evolution of climate variability and change on naturally separated timescales, which is computationally expensive. By taking the advantage of the high efficiency of the principle component analysis/empirical orthogonal function (PCA/EOF) expression for spatiotemporally coherent data, we design a lossy compression method for climate data to facilitate its non-local transmission. In addition to that, we also explain the basic principles behind the fast MEEMD through decomposing PCs instead of original grid-wise time series to speedup computation of MEEMD. Using a typical climate dataset as an example, we demonstrate that our newly designed methods can (1) compress data with a compression rate of one to two orders; (2) speed up the MEEMD algorithm by one to two orders.
Wu, Zhaohua; Feng, Jiaxin; Qiao, Fangli; Tan, Zhe-Min
2016-01-01
In this big data era, it is more urgent than ever to solve two major issues: (i) fast data transmission methods that can facilitate access to data from non-local sources and (ii) fast and efficient data analysis methods that can reveal the key information from the available data for particular purposes. Although approaches in different fields to address these two questions may differ significantly, the common part must involve data compression techniques and a fast algorithm. This paper introduces the recently developed adaptive and spatio-temporally local analysis method, namely the fast multidimensional ensemble empirical mode decomposition (MEEMD), for the analysis of a large spatio-temporal dataset. The original MEEMD uses ensemble empirical mode decomposition to decompose time series at each spatial grid and then pieces together the temporal–spatial evolution of climate variability and change on naturally separated timescales, which is computationally expensive. By taking advantage of the high efficiency of the expression using principal component analysis/empirical orthogonal function analysis for spatio-temporally coherent data, we design a lossy compression method for climate data to facilitate its non-local transmission. We also explain the basic principles behind the fast MEEMD through decomposing principal components instead of original grid-wise time series to speed up computation of MEEMD. Using a typical climate dataset as an example, we demonstrate that our newly designed methods can (i) compress data with a compression rate of one to two orders; and (ii) speed-up the MEEMD algorithm by one to two orders. PMID:26953173
Bhanot, Gyan V.; Chen, Dong; Gara, Alan G.; Giampapa, Mark E.; Heidelberger, Philip; Steinmacher-Burow, Burkhard D.; Vranas, Pavlos M.
2008-01-01
The present in invention is directed to a method, system and program storage device for efficiently implementing a multidimensional Fast Fourier Transform (FFT) of a multidimensional array comprising a plurality of elements initially distributed in a multi-node computer system comprising a plurality of nodes in communication over a network, comprising: distributing the plurality of elements of the array in a first dimension across the plurality of nodes of the computer system over the network to facilitate a first one-dimensional FFT; performing the first one-dimensional FFT on the elements of the array distributed at each node in the first dimension; re-distributing the one-dimensional FFT-transformed elements at each node in a second dimension via "all-to-all" distribution in random order across other nodes of the computer system over the network; and performing a second one-dimensional FFT on elements of the array re-distributed at each node in the second dimension, wherein the random order facilitates efficient utilization of the network thereby efficiently implementing the multidimensional FFT. The "all-to-all" re-distribution of array elements is further efficiently implemented in applications other than the multidimensional FFT on the distributed-memory parallel supercomputer.
Bhanot, Gyan V.; Chen, Dong; Gara, Alan G.; Giampapa, Mark E.; Heidelberger, Philip; Steinmacher-Burow, Burkhard D.; Vranas, Pavlos M.
2012-01-10
The present in invention is directed to a method, system and program storage device for efficiently implementing a multidimensional Fast Fourier Transform (FFT) of a multidimensional array comprising a plurality of elements initially distributed in a multi-node computer system comprising a plurality of nodes in communication over a network, comprising: distributing the plurality of elements of the array in a first dimension across the plurality of nodes of the computer system over the network to facilitate a first one-dimensional FFT; performing the first one-dimensional FFT on the elements of the array distributed at each node in the first dimension; re-distributing the one-dimensional FFT-transformed elements at each node in a second dimension via "all-to-all" distribution in random order across other nodes of the computer system over the network; and performing a second one-dimensional FFT on elements of the array re-distributed at each node in the second dimension, wherein the random order facilitates efficient utilization of the network thereby efficiently implementing the multidimensional FFT. The "all-to-all" re-distribution of array elements is further efficiently implemented in applications other than the multidimensional FFT on the distributed-memory parallel supercomputer.
Rapid measurement of multidimensional 1H solid-state NMR spectra at ultra-fast MAS frequencies
NASA Astrophysics Data System (ADS)
Ye, Yue Qi; Malon, Michal; Martineau, Charlotte; Taulelle, Francis; Nishiyama, Yusuke
2014-02-01
A novel method to realize rapid repetition of 1H NMR experiments at ultra-fast MAS frequencies is demonstrated. The ultra-fast MAS at 110 kHz slows the 1H-1H spin diffusion, leading to variations of 1H T1 relaxation times from atom to atom within a molecule. The different relaxation behavior is averaged by applying 1H-1H recoupling during relaxation delay even at ultra-fast MAS, reducing the optimal relaxation delay to maximize the signal to noise ratio. The way to determine optimal relaxation delay for arbitrary relaxation curve is shown. The reduction of optimal relaxation delay by radio-frequency driven recoupling (RFDR) was demonstrated on powder samples of glycine and ethenzamide with one and multi-dimensional NMR measurements.
Lesot, Philippe; Kazimierczuk, Krzysztof; Trébosc, Julien; Amoureux, Jean-Paul; Lafon, Olivier
2015-11-01
Unique information about the atom-level structure and dynamics of solids and mesophases can be obtained by the use of multidimensional nuclear magnetic resonance (NMR) experiments. Nevertheless, the acquisition of these experiments often requires long acquisition times. We review here alternative sampling methods, which have been proposed to circumvent this issue in the case of solids and mesophases. Compared to the spectra of solutions, those of solids and mesophases present some specificities because they usually display lower signal-to-noise ratios, non-Lorentzian line shapes, lower spectral resolutions and wider spectral widths. We highlight herein the advantages and limitations of these alternative sampling methods. A first route to accelerate the acquisition time of multidimensional NMR spectra consists in the use of sparse sampling schemes, such as truncated, radial or random sampling ones. These sparsely sampled datasets are generally processed by reconstruction methods differing from the Discrete Fourier Transform (DFT). A host of non-DFT methods have been applied for solids and mesophases, including the G-matrix Fourier transform, the linear least-square procedures, the covariance transform, the maximum entropy and the compressed sensing. A second class of alternative sampling consists in departing from the Jeener paradigm for multidimensional NMR experiments. These non-Jeener methods include Hadamard spectroscopy as well as spatial or orientational encoding of the evolution frequencies. The increasing number of high field NMR magnets and the development of techniques to enhance NMR sensitivity will contribute to widen the use of these alternative sampling methods for the study of solids and mesophases in the coming years.
Fast multi-dimensional NMR acquisition and processing using the sparse FFT.
Hassanieh, Haitham; Mayzel, Maxim; Shi, Lixin; Katabi, Dina; Orekhov, Vladislav Yu
2015-09-01
Increasing the dimensionality of NMR experiments strongly enhances the spectral resolution and provides invaluable direct information about atomic interactions. However, the price tag is high: long measurement times and heavy requirements on the computation power and data storage. We introduce sparse fast Fourier transform as a new method of NMR signal collection and processing, which is capable of reconstructing high quality spectra of large size and dimensionality with short measurement times, faster computations than the fast Fourier transform, and minimal storage for processing and handling of sparse spectra. The new algorithm is described and demonstrated for a 4D BEST-HNCOCA spectrum. PMID:26123316
Wong, Yong Foo; West, Rachel N; Chin, Sung-Tong; Marriott, Philip J
2015-08-01
This work demonstrates the potential of fast multiple heart-cut enantioselective multidimensional gas chromatography (GC-eGC) and enantioselective comprehensive two-dimensional gas chromatography (eGC×GC), to perform the stereoisomeric analysis of three key chiral monoterpenes (limonene, terpinen-4-ol and α-terpineol) present in tea tree oil (TTO). In GC-eGC, separation was conducted using a combination of mid-polar first dimension ((1)D) column and a chiral second dimension ((2)D) column, providing interference-free enantioresolution of the individual antipodes of each optically active component. A combination of (1)D chiral column and (2)D polar columns (ionic liquid and wax phases) were tested for the eGC×GC study. Quantification was proposed based on summation of two major modulated peaks for each antipode, displaying comparable results with those derived from GC-eGC. Fast chiral separations were achieved within 25min for GC-eGC and<20min for eGC×GC, while ensuring adequate interference-free enantiomer separation. The suitability of using these two enantioselective multidimensional approaches for the routine assessment of chiral monoterpenes in TTO was evaluated and discussed. Exact enantiomeric composition of chiral markers for authentic TTOs was proposed by analysing a representative number of pure TTOs sourced directly from plantations of known provenance in Australia. Consistent enantiomeric fractions of 61.6±1.5% (+):38.4±1.5% (-) for limonene, 61.7±1.6% (+):38.3±1.6% (-) for terpinen-4-ol and 79.6±1.4% (+):20.4±1.4% (-) for α-terpineol were obtained for the 57 authentic Australian TTOs. The results were compared (using principle component analysis) with commercial TTOs (declared as derived from Melaleuca alternifolia) obtained from different continents. Assessing these data to determine adulteration, or additives that affect the enantiomeric ratios, in commercially sourced TTOs is discussed. The proposed method offers distinct advantages over e
Wong, Yong Foo; West, Rachel N; Chin, Sung-Tong; Marriott, Philip J
2015-08-01
This work demonstrates the potential of fast multiple heart-cut enantioselective multidimensional gas chromatography (GC-eGC) and enantioselective comprehensive two-dimensional gas chromatography (eGC×GC), to perform the stereoisomeric analysis of three key chiral monoterpenes (limonene, terpinen-4-ol and α-terpineol) present in tea tree oil (TTO). In GC-eGC, separation was conducted using a combination of mid-polar first dimension ((1)D) column and a chiral second dimension ((2)D) column, providing interference-free enantioresolution of the individual antipodes of each optically active component. A combination of (1)D chiral column and (2)D polar columns (ionic liquid and wax phases) were tested for the eGC×GC study. Quantification was proposed based on summation of two major modulated peaks for each antipode, displaying comparable results with those derived from GC-eGC. Fast chiral separations were achieved within 25min for GC-eGC and<20min for eGC×GC, while ensuring adequate interference-free enantiomer separation. The suitability of using these two enantioselective multidimensional approaches for the routine assessment of chiral monoterpenes in TTO was evaluated and discussed. Exact enantiomeric composition of chiral markers for authentic TTOs was proposed by analysing a representative number of pure TTOs sourced directly from plantations of known provenance in Australia. Consistent enantiomeric fractions of 61.6±1.5% (+):38.4±1.5% (-) for limonene, 61.7±1.6% (+):38.3±1.6% (-) for terpinen-4-ol and 79.6±1.4% (+):20.4±1.4% (-) for α-terpineol were obtained for the 57 authentic Australian TTOs. The results were compared (using principle component analysis) with commercial TTOs (declared as derived from Melaleuca alternifolia) obtained from different continents. Assessing these data to determine adulteration, or additives that affect the enantiomeric ratios, in commercially sourced TTOs is discussed. The proposed method offers distinct advantages over e
Marcotte, Isabelle; Separovic, Frances; Auger, Michèle; Gagné, Stéphane M.
2004-01-01
Enkephalins are pentapeptides found in the central nervous system. It is believed that these neuropeptides interact with the nerve cell membrane to adopt a conformation suitable for their binding to an opiate receptor. In this work, we have determined the three-dimensional structure of methionine-enkephalin (Menk) in fast-tumbling bicelles using multidimensional 1H NMR. Bicelles were selected as model membranes because both their bilayer organization and composition resemble those of natural biomembranes. The effect of the membrane composition on the peptide conformation was explored using both zwitterionic (PC bicelles) and negatively charged bicelles (Bic/PG). Pulsed field gradient experiments allowed the determination of the proportion of Menk bound to the model membranes. Approximately 60% of the water-soluble enkephalin was found to associate to the bicellar systems. Structure calculations from torsion angle and NOE-based distance constraints suggest the presence of both μ- and δ-selective conformers of Menk in each system and slightly different conformers in PC bicelles and Bic/PG. As opposed to previous studies of enkephalins in membrane mimetic systems, our results show that these opiate peptides could adopt several conformations in a membrane environment, which is consistent with the flexibility and poor selectivity of enkephalins. PMID:14990485
ERIC Educational Resources Information Center
Hout, Michael C.; Goldinger, Stephen D.; Ferguson, Ryan W.
2013-01-01
Although traditional methods to collect similarity data (for multidimensional scaling [MDS]) are robust, they share a key shortcoming. Specifically, the possible pairwise comparisons in any set of objects grow rapidly as a function of set size. This leads to lengthy experimental protocols, or procedures that involve scaling stimulus subsets. We…
Zanni, Martin Thomas; Damrauer, Niels H.
2010-07-20
A multidimensional spectrometer for the infrared, visible, and ultraviolet regions of the electromagnetic spectrum, and a method for making multidimensional spectroscopic measurements in the infrared, visible, and ultraviolet regions of the electromagnetic spectrum. The multidimensional spectrometer facilitates measurements of inter- and intra-molecular interactions.
Multidimensional Risk Analysis: MRISK
NASA Technical Reports Server (NTRS)
McCollum, Raymond; Brown, Douglas; O'Shea, Sarah Beth; Reith, William; Rabulan, Jennifer; Melrose, Graeme
2015-01-01
Multidimensional Risk (MRISK) calculates the combined multidimensional score using Mahalanobis distance. MRISK accounts for covariance between consequence dimensions, which de-conflicts the interdependencies of consequence dimensions, providing a clearer depiction of risks. Additionally, in the event the dimensions are not correlated, Mahalanobis distance reduces to Euclidean distance normalized by the variance and, therefore, represents the most flexible and optimal method to combine dimensions. MRISK is currently being used in NASA's Environmentally Responsible Aviation (ERA) project o assess risk and prioritize scarce resources.
On the Need for Multidimensional Stirling Analysis
NASA Technical Reports Server (NTRS)
Dyson, Rodger; Wilson, Scott; Tew, Roy; Demko, Rikako
2006-01-01
Contents include the following: Dual opposed convertors. High efficiency. Low mass space power. One-dimensional analysis. Fast computation. Design optimizations are easily done. Need for multidimensional modeling. Axisymmetric simulation. Flow characteristics. Low mach number. Laminar, transitional, and turbulent flow. Conjugate heat transfer. Third order analysis. Recent whole engine modeling. Regenerator geometry. Turbulence modeling. Flat head heater not 1-D. Empirical coefficients needed. Experiment design. Flow distribution. Sensor placement. Calibration. Validation.
Multidimensional spectral load balancing
Hendrickson, B.; Leland, R.
1993-01-01
We describe an algorithm for the static load balancing of scientific computations that generalizes and improves upon spectral bisection. Through a novel use of multiple eigenvectors, our new spectral algorithm can divide a computation into 4 or 8 pieces at once. These multidimensional spectral partitioning algorithms generate balanced partitions that have lower communication overhead and are less expensive to compute than those produced by spectral bisection. In addition, they automatically work to minimize message contention on a hypercube or mesh architecture. These spectral partitions are further improved by a multidimensional generalization of the Kernighan-Lin graph partitioning algorithm. Results on several computational grids are given and compared with other popular methods.
Multidimensional x-space magnetic particle imaging.
Goodwill, Patrick W; Conolly, Steven M
2011-09-01
Magnetic particle imaging (MPI) is a promising new medical imaging tracer modality with potential applications in human angiography, cancer imaging, in vivo cell tracking, and inflammation imaging. Here we demonstrate both theoretically and experimentally that multidimensional MPI is a linear shift-invariant imaging system with an analytic point spread function. We also introduce a fast image reconstruction method that obtains the intrinsic MPI image with high signal-to-noise ratio via a simple gridding operation in x-space. We also demonstrate a method to reconstruct large field-of-view (FOV) images using partial FOV scanning, despite the loss of first harmonic image information due to direct feedthrough contamination. We conclude with the first experimental test of multidimensional x-space MPI.
Multidimensional spectroscopy of photoreactivity
Ruetzel, Stefan; Diekmann, Meike; Nuernberger, Patrick; Walter, Christof; Engels, Bernd; Brixner, Tobias
2014-01-01
Coherent multidimensional electronic spectroscopy is commonly used to investigate photophysical phenomena such as light harvesting in photosynthesis in which the system returns back to its ground state after energy transfer. By contrast, we introduce multidimensional spectroscopy to study ultrafast photochemical processes in which the investigated molecule changes permanently. Exemplarily, the emergence in 2D and 3D spectra of a cross-peak between reactant and product reveals the cis–trans photoisomerization of merocyanine isomers. These compounds have applications in organic photovoltaics and optical data storage. Cross-peak oscillations originate from a vibrational wave packet in the electronically excited state of the photoproduct. This concept isolates the isomerization dynamics along different vibrational coordinates assigned by quantum-chemical calculations, and is applicable to determine chemical dynamics in complex photoreactive networks. PMID:24639540
Multidimensional radar picture
NASA Astrophysics Data System (ADS)
Waz, Mariusz
2010-05-01
In marine navigation systems, the three-dimensional (3D) visualization is often and often used. Echosonders and sonars working in hydroacustic systems can present pictures in three dimensions. Currently, vector maps also offer 3D presentation. This presentation is used in aviation and underwater navigation. In the nearest future three-dimensional presentation may be obligatory presentation in displays of navigation systems. A part of these systems work with radar and communicates with it transmitting data in a digital form. 3D presentation of radar picture require a new technology to develop. In the first step it is necessary to compile digital form of radar signal. The modern navigation radar do not present data in three-dimensional form. Progress in technology of digital signal processing make it possible to create multidimensional radar pictures. For instance, the RSC (Radar Scan Converter) - digital radar picture recording and transforming tool can be used to create new picture online. Using RSC and techniques of modern computer graphics multidimensional radar pictures can be generated. The radar pictures mentioned should be readable for ECDIS. The paper presents a method for generating multidimensional radar picture from original signal coming from radar receiver.
Multidimensional sexual perfectionism.
Stoeber, Joachim; Harvey, Laura N; Almeida, Isabel; Lyons, Emma
2013-11-01
Perfectionism is a multidimensional personality characteristic that can affect all areas of life. This article presents the first systematic investigation of multidimensional perfectionism in the domain of sexuality exploring the unique relationships that different forms of sexual perfectionism show with positive and negative aspects of sexuality. A sample of 272 university students (52 male, 220 female) completed measures of four forms of sexual perfectionism: self-oriented, partner-oriented, partner-prescribed, and socially prescribed. In addition, they completed measures of sexual esteem, sexual self-efficacy, sexual optimism, sex life satisfaction (capturing positive aspects of sexuality) and sexual problem self-blame, sexual anxiety, sexual depression, and negative sexual perfectionism cognitions during sex (capturing negative aspects). Results showed unique patterns of relationships for the four forms of sexual perfectionism, suggesting that partner-prescribed and socially prescribed sexual perfectionism are maladaptive forms of sexual perfectionism associated with negative aspects of sexuality whereas self-oriented and partner-oriented sexual perfectionism emerged as ambivalent forms associated with positive and negative aspects. PMID:23842783
Theta vocabulary II. Multidimensional case
NASA Astrophysics Data System (ADS)
Kharchev, S.; Zabrodin, A.
2016-06-01
It is shown that the Jacobi and Riemann identities of degree four for the multidimensional theta functions as well as the Weierstrass identities emerge as algebraic consequences of the fundamental multidimensional binary identities connecting the theta functions with Riemann matrices τ and 2 τ.
Multidimensional Perfectionism and the Self
ERIC Educational Resources Information Center
Ward, Andrew M.; Ashby, Jeffrey S.
2008-01-01
This study examined multidimensional perfectionism and self-development. Two hundred seventy-one undergraduates completed a measure of multidimensional perfectionism and two Kohutian measures designed to measure aspects of self-development including social connectedness, social assurance, goal instability (idealization), and grandiosity. The…
Multidimensional persistence in biomolecular data
Xia, Kelin; Wei, Guo-Wei
2015-01-01
Persistent homology has emerged as a popular technique for the topological simplification of big data, including biomolecular data. Multidimensional persistence bears considerable promise to bridge the gap between geometry and topology. However, its practical and robust construction has been a challenge. We introduce two families of multidimensional persistence, namely pseudo-multidimensional persistence and multiscale multidimensional persistence. The former is generated via the repeated applications of persistent homology filtration to high dimensional data, such as results from molecular dynamics or partial differential equations. The latter is constructed via isotropic and anisotropic scales that create new simiplicial complexes and associated topological spaces. The utility, robustness and efficiency of the proposed topological methods are demonstrated via protein folding, protein flexibility analysis, the topological denoising of cryo-electron microscopy data, and the scale dependence of nano particles. Topological transition between partial folded and unfolded proteins has been observed in multidimensional persistence. The separation between noise topological signatures and molecular topological fingerprints is achieved by the Laplace-Beltrami flow. The multiscale multidimensional persistent homology reveals relative local features in Betti-0 invariants and the relatively global characteristics of Betti-1 and Betti-2 invariants. PMID:26032339
Multidimensional persistence in biomolecular data.
Xia, Kelin; Wei, Guo-Wei
2015-07-30
Persistent homology has emerged as a popular technique for the topological simplification of big data, including biomolecular data. Multidimensional persistence bears considerable promise to bridge the gap between geometry and topology. However, its practical and robust construction has been a challenge. We introduce two families of multidimensional persistence, namely pseudomultidimensional persistence and multiscale multidimensional persistence. The former is generated via the repeated applications of persistent homology filtration to high-dimensional data, such as results from molecular dynamics or partial differential equations. The latter is constructed via isotropic and anisotropic scales that create new simiplicial complexes and associated topological spaces. The utility, robustness, and efficiency of the proposed topological methods are demonstrated via protein folding, protein flexibility analysis, the topological denoising of cryoelectron microscopy data, and the scale dependence of nanoparticles. Topological transition between partial folded and unfolded proteins has been observed in multidimensional persistence. The separation between noise topological signatures and molecular topological fingerprints is achieved by the Laplace-Beltrami flow. The multiscale multidimensional persistent homology reveals relative local features in Betti-0 invariants and the relatively global characteristics of Betti-1 and Betti-2 invariants.
Kawai, Shinnosuke; Fujimura, Yo; Kajimoto, Okitsugu; Yamashita, Takefumi; Li, Chun-Biu; Komatsuzaki, Tamiki; Toda, Mikito
2007-02-15
One of the most fundamental problems in studying general Hamiltonian systems with many degrees of freedom is to extract a low-dimensional subsystem including the essential dynamics. In this paper, a new partial normal form (PNF) method is developed to reduce the number of coupling terms in the Hamiltonian and to simplify the dynamics analyses. The PNF method allows one to decouple many unimportant bath modes as well as the reactive mode from the system by assessing the significance of the coupling terms. The method is applied to the chemical reaction O({sup 1}D)+N{sub 2}O{yields}NO+NO, which was found to exhibit efficient energy exchange between the two NO stretching modes despite the short lifetime of the reaction intermediate [S. Kawai et al., J. Chem. Phys. 124, 184315 (2006)]. Through the analysis of the two-dimensional PNF Hamiltonian subsystem, it is found that the motion of the subsystem preserves the 'normal mode picture' of the symmetric and antisymmetric NO stretching modes despite its high energy. Then the vibrational energy, initially localized in the newly formed NO bond, is transferred to the reactants' NO bond through the beating between the symmetric and antisymmetric stretching modes. The preservation of the normal mode picture and the short period of the beating explain the fast energy exchange between the two NO bonds. This successful application proves that the PNF method can extract the essential small subspace from many-degrees-of-freedom Hamiltonian systems.
Generalized multidimensional dynamic allocation method.
Lebowitsch, Jonathan; Ge, Yan; Young, Benjamin; Hu, Feifang
2012-12-10
Dynamic allocation has received considerable attention since it was first proposed in the 1970s as an alternative means of allocating treatments in clinical trials which helps to secure the balance of prognostic factors across treatment groups. The purpose of this paper is to present a generalized multidimensional dynamic allocation method that simultaneously balances treatment assignments at three key levels: within the overall study, within each level of each prognostic factor, and within each stratum, that is, combination of levels of different factors Further it offers capabilities for unbalanced and adaptive designs for trials. The treatment balancing performance of the proposed method is investigated through simulations which compare multidimensional dynamic allocation with traditional stratified block randomization and the Pocock-Simon method. On the basis of these results, we conclude that this generalized multidimensional dynamic allocation method is an improvement over conventional dynamic allocation methods and is flexible enough to be applied for most trial settings including Phases I, II and III trials.
On the Need for Multidimensional Stirling Simulations
NASA Technical Reports Server (NTRS)
Dyson, Rodger W.; Wilson, Scott D.; Tew, Roy C.; Demko, Rikako
2005-01-01
Given the cost and complication of simulating Stirling convertors, do we really need multidimensional modeling when one-dimensional capabilities exist? This paper provides a comprehensive description of when and why multidimensional simulation is needed.
Recycling Behavior: A Multidimensional Approach
ERIC Educational Resources Information Center
Meneses, Gonzalo Diaz; Palacio, Asuncion Beerli
2005-01-01
This work centers on the study of consumer recycling roles to examine the sociodemographic and psychographic profile of the distribution of recycling tasks and roles within the household. With this aim in mind, an empirical work was carried out, the results of which suggest that recycling behavior is multidimensional and comprises the undertaking…
A Multidimensional Software Engineering Course
ERIC Educational Resources Information Center
Barzilay, O.; Hazzan, O.; Yehudai, A.
2009-01-01
Software engineering (SE) is a multidimensional field that involves activities in various areas and disciplines, such as computer science, project management, and system engineering. Though modern SE curricula include designated courses that address these various subjects, an advanced summary course that synthesizes them is still missing. Such a…
Multidimensional digital signal processing
NASA Astrophysics Data System (ADS)
Lanfear, T. A.; Constantinides, A. G.
1984-06-01
The computer program SIMUL is intended to simulate the ALPS system architecture at a high level so as to answer such questions as: is a signal processing application feasible with a particular hardware configuration?; how fast can the processing be performed?; will the system degrade gracefully if some of the resources fail?; what is the effect upon system performance of changes to details such as the number of resources available, the execution time of a resource etc. This document should be read in conjunction with previous documentation for ALPS. The program takes as input data the following information: the number of nodes in the signal flow graph, the number of types of resources, the number of data busses, the time to transfer a block of data from one resource to another, the signal flow graph connectivity and edge prioritization in the form of an adjacency matrix, the number of each type of resource, the execution time of each resource and the type of resource associated with each graph node.
Deterministic multidimensional nonuniform gap sampling.
Worley, Bradley; Powers, Robert
2015-12-01
Born from empirical observations in nonuniformly sampled multidimensional NMR data relating to gaps between sampled points, the Poisson-gap sampling method has enjoyed widespread use in biomolecular NMR. While the majority of nonuniform sampling schemes are fully randomly drawn from probability densities that vary over a Nyquist grid, the Poisson-gap scheme employs constrained random deviates to minimize the gaps between sampled grid points. We describe a deterministic gap sampling method, based on the average behavior of Poisson-gap sampling, which performs comparably to its random counterpart with the additional benefit of completely deterministic behavior. We also introduce a general algorithm for multidimensional nonuniform sampling based on a gap equation, and apply it to yield a deterministic sampling scheme that combines burst-mode sampling features with those of Poisson-gap schemes. Finally, we derive a relationship between stochastic gap equations and the expectation value of their sampling probability densities.
Deterministic multidimensional nonuniform gap sampling
NASA Astrophysics Data System (ADS)
Worley, Bradley; Powers, Robert
2015-12-01
Born from empirical observations in nonuniformly sampled multidimensional NMR data relating to gaps between sampled points, the Poisson-gap sampling method has enjoyed widespread use in biomolecular NMR. While the majority of nonuniform sampling schemes are fully randomly drawn from probability densities that vary over a Nyquist grid, the Poisson-gap scheme employs constrained random deviates to minimize the gaps between sampled grid points. We describe a deterministic gap sampling method, based on the average behavior of Poisson-gap sampling, which performs comparably to its random counterpart with the additional benefit of completely deterministic behavior. We also introduce a general algorithm for multidimensional nonuniform sampling based on a gap equation, and apply it to yield a deterministic sampling scheme that combines burst-mode sampling features with those of Poisson-gap schemes. Finally, we derive a relationship between stochastic gap equations and the expectation value of their sampling probability densities.
Multidimensional theory of protein folding
NASA Astrophysics Data System (ADS)
Itoh, Kazuhito; Sasai, Masaki
2009-04-01
Theory of multidimensional representation of free energy surface of protein folding is developed by adopting structural order parameters of multiple regions in protein as multiple coordinates. Various scenarios of folding are classified in terms of cooperativity within individual regions and interactions among multiple regions and thus obtained classification is used to analyze the folding process of several example proteins. Ribosomal protein S6, src-SH3 domain, CheY, barnase, and BBL domain are analyzed with the two-dimensional representation by using a structure-based Hamiltonian model. The extension to the higher dimensional representation leads to the finer description of the folding process. Barnase, NtrC, and an ankyrin repeat protein are examined with the three-dimensional representation. The multidimensional representation allows us to directly address questions on folding pathways, intermediates, and transition states.
Multidimensional bioseparation with modular microfluidics
Chirica, Gabriela S.; Renzi, Ronald F.
2013-08-27
A multidimensional chemical separation and analysis system is described including a prototyping platform and modular microfluidic components capable of rapid and convenient assembly, alteration and disassembly of numerous candidate separation systems. Partial or total computer control of the separation system is possible. Single or multiple alternative processing trains can be tested, optimized and/or run in parallel. Examples related to the separation and analysis of human bodily fluids are given.
Cuba: Multidimensional numerical integration library
NASA Astrophysics Data System (ADS)
Hahn, Thomas
2016-08-01
The Cuba library offers four independent routines for multidimensional numerical integration: Vegas, Suave, Divonne, and Cuhre. The four algorithms work by very different methods, and can integrate vector integrands and have very similar Fortran, C/C++, and Mathematica interfaces. Their invocation is very similar, making it easy to cross-check by substituting one method by another. For further safeguarding, the output is supplemented by a chi-square probability which quantifies the reliability of the error estimate.
Multidimensional time-correlated single photon counting
NASA Astrophysics Data System (ADS)
Becker, Wolfgang; Bergmann, Axel
2006-10-01
Time-correlated single photon counting (TCSPC) is based on the detection of single photons of a periodic light signal, measurement of the detection time of the photons, and the build-up of the photon distribution versus the time in the signal period. TCSPC achieves a near ideal counting efficiency and transit-time-spread-limited time resolution for a given detector. The drawback of traditional TCSPC is the low count rate, long acquisition time, and the fact that the technique is one-dimensional, i.e. limited to the recording of the pulse shape of light signals. We present an advanced TCSPC technique featuring multi-dimensional photon acquisition and a count rate close to the capability of currently available detectors. The technique is able to acquire photon distributions versus wavelength, spatial coordinates, and the time on the ps scale, and to record fast changes in the fluorescence lifetime and fluorescence intensity of a sample. Biomedical applications of advanced TCSPC techniques are time-domain optical tomography, recording of transient phenomena in biological systems, spectrally resolved fluorescence lifetime imaging, FRET experiments in living cells, and the investigation of dye-protein complexes by fluorescence correlation spectroscopy. We demonstrate the potential of the technique for selected applications.
Measures for a multidimensional multiverse
NASA Astrophysics Data System (ADS)
Chung, Hyeyoun
2015-04-01
We explore the phenomenological implications of generalizing the causal patch and fat geodesic measures to a multidimensional multiverse, where the vacua can have differing numbers of large dimensions. We consider a simple model in which the vacua are nucleated from a D -dimensional parent spacetime through dynamical compactification of the extra dimensions, and compute the geometric contribution to the probability distribution of observations within the multiverse for each measure. We then study how the shape of this probability distribution depends on the time scales for the existence of observers, for vacuum domination, and for curvature domination (tobs,tΛ , and tc, respectively.) In this work we restrict ourselves to bubbles with positive cosmological constant, Λ . We find that in the case of the causal patch cutoff, when the bubble universes have p +1 large spatial dimensions with p ≥2 , the shape of the probability distribution is such that we obtain the coincidence of time scales tobs˜tΛ˜tc . Moreover, the size of the cosmological constant is related to the size of the landscape. However, the exact shape of the probability distribution is different in the case p =2 , compared to p ≥3 . In the case of the fat geodesic measure, the result is even more robust: the shape of the probability distribution is the same for all p ≥2 , and we once again obtain the coincidence tobs˜tΛ˜tc . These results require only very mild conditions on the prior probability of the distribution of vacua in the landscape. Our work shows that the observed double coincidence of time scales is a robust prediction even when the multiverse is generalized to be multidimensional; that this coincidence is not a consequence of our particular Universe being (3 +1 )-dimensional; and that this observable cannot be used to preferentially select one measure over another in a multidimensional multiverse.
On Compensation in Multidimensional Response Modeling
ERIC Educational Resources Information Center
van der Linden, Wim J.
2012-01-01
The issue of compensation in multidimensional response modeling is addressed. We show that multidimensional response models are compensatory in their ability parameters if and only if they are monotone. In addition, a minimal set of assumptions is presented under which the MLEs of the ability parameters are also compensatory. In a recent series of…
Multidimensional Scaling of Classroom Interaction Data.
ERIC Educational Resources Information Center
Rumery, Robert E.; Hartnett, Barbara M.
The use of Kruskal's nonmetric multidimensional scaling model for analysis of classroom interaction data is discussed. Four distance models are proposed which lead to multidimensional representation of single sequences, sets of sequences, and behavior categories using symmetric and conditional proximity options of the model. Results of application…
Multidimensional Adaptation in MAS Organizations.
Alberola, Juan M; Julian, Vicente; Garcia-Fornes, Ana
2013-04-01
Organization adaptation requires determining the consequences of applying changes not only in terms of the benefits provided but also measuring the adaptation costs as well as the impact that these changes have on all of the components of the organization. In this paper, we provide an approach for adaptation in multiagent systems based on a multidimensional transition deliberation mechanism (MTDM). This approach considers transitions in multiple dimensions and is aimed at obtaining the adaptation with the highest potential for improvement in utility based on the costs of adaptation. The approach provides an accurate measurement of the impact of the adaptation since it determines the organization that is to be transitioned to as well as the changes required to carry out this transition. We show an example of adaptation in a service provider network environment in order to demonstrate that the measurement of the adaptation consequences taken by the MTDM improves the organization performance more than the other approaches.
NASA Astrophysics Data System (ADS)
Wright, John C.
2016-10-01
Spectroscopy is a dominant measurement methodology because it resolves molecular level details over a wide concentration range. Its limitations, however, become challenged when applied to complex materials. Coherent multidimensional spectroscopy (CMDS) is the optical analogue of multidimensional NMR and like NMR, its multidimensionality promises to increase the spectral selectivity of vibrational and electronic spectroscopy. This article explores whether this promise can make CMDS a dominant spectroscopic method throughout the sciences. In order for CMDS to become a dominant methodology, it must create multidimensional spectral fingerprints that provide the selectivity required for probing complex samples. Pump-CMDS probe methods separate the pump's measurement of dynamics from a multidimensional and selective probe. Fully coherent CMDS methods are ideal multidimensional probes because they avoid relaxation effects, spectrally isolate the output signals, and provide unique and invariant spectral signatures using any combination of vibrational and electronic quantum states.
Random Effects Diagonal Metric Multidimensional Scaling Models.
ERIC Educational Resources Information Center
Clarkson, Douglas B.; Gonzalez, Richard
2001-01-01
Defines a random effects diagonal metric multidimensional scaling model, gives its computational algorithms, describes researchers' experiences with these algorithms, and provides an illustration of the use of the model and algorithms. (Author/SLD)
Systems of Values and Their Multidimensional Representations
ERIC Educational Resources Information Center
Jones, Russell A.; And Others
1978-01-01
Values were elicited spontaneously from a sample of undergraduates and adults attending college, and were compared to Rokeach's terminal and instrumental values. Multidimensional scaling revealed a simpler structure among spontaneously mentioned values than Rokeach's values. (JKS)
VH-1: Multidimensional ideal compressible hydrodynamics code
NASA Astrophysics Data System (ADS)
Hawley, John; Blondin, John; Lindahl, Greg; Lufkin, Eric
2012-04-01
VH-1 is a multidimensional ideal compressible hydrodynamics code written in FORTRAN for use on any computing platform, from desktop workstations to supercomputers. It uses a Lagrangian remap version of the Piecewise Parabolic Method developed by Paul Woodward and Phil Colella in their 1984 paper. VH-1 comes in a variety of versions, from a simple one-dimensional serial variant to a multi-dimensional version scalable to thousands of processors.
Multidimensional stochastic approximation Monte Carlo.
Zablotskiy, Sergey V; Ivanov, Victor A; Paul, Wolfgang
2016-06-01
Stochastic Approximation Monte Carlo (SAMC) has been established as a mathematically founded powerful flat-histogram Monte Carlo method, used to determine the density of states, g(E), of a model system. We show here how it can be generalized for the determination of multidimensional probability distributions (or equivalently densities of states) of macroscopic or mesoscopic variables defined on the space of microstates of a statistical mechanical system. This establishes this method as a systematic way for coarse graining a model system, or, in other words, for performing a renormalization group step on a model. We discuss the formulation of the Kadanoff block spin transformation and the coarse-graining procedure for polymer models in this language. We also apply it to a standard case in the literature of two-dimensional densities of states, where two competing energetic effects are present g(E_{1},E_{2}). We show when and why care has to be exercised when obtaining the microcanonical density of states g(E_{1}+E_{2}) from g(E_{1},E_{2}). PMID:27415383
Multidimensionally encoded magnetic resonance imaging.
Lin, Fa-Hsuan
2013-07-01
Magnetic resonance imaging (MRI) typically achieves spatial encoding by measuring the projection of a q-dimensional object over q-dimensional spatial bases created by linear spatial encoding magnetic fields (SEMs). Recently, imaging strategies using nonlinear SEMs have demonstrated potential advantages for reconstructing images with higher spatiotemporal resolution and reducing peripheral nerve stimulation. In practice, nonlinear SEMs and linear SEMs can be used jointly to further improve the image reconstruction performance. Here, we propose the multidimensionally encoded (MDE) MRI to map a q-dimensional object onto a p-dimensional encoding space where p > q. MDE MRI is a theoretical framework linking imaging strategies using linear and nonlinear SEMs. Using a system of eight surface SEM coils with an eight-channel radiofrequency coil array, we demonstrate the five-dimensional MDE MRI for a two-dimensional object as a further generalization of PatLoc imaging and O-space imaging. We also present a method of optimizing spatial bases in MDE MRI. Results show that MDE MRI with a higher dimensional encoding space can reconstruct images more efficiently and with a smaller reconstruction error when the k-space sampling distribution and the number of samples are controlled.
Multidimensional stochastic approximation Monte Carlo
NASA Astrophysics Data System (ADS)
Zablotskiy, Sergey V.; Ivanov, Victor A.; Paul, Wolfgang
2016-06-01
Stochastic Approximation Monte Carlo (SAMC) has been established as a mathematically founded powerful flat-histogram Monte Carlo method, used to determine the density of states, g (E ) , of a model system. We show here how it can be generalized for the determination of multidimensional probability distributions (or equivalently densities of states) of macroscopic or mesoscopic variables defined on the space of microstates of a statistical mechanical system. This establishes this method as a systematic way for coarse graining a model system, or, in other words, for performing a renormalization group step on a model. We discuss the formulation of the Kadanoff block spin transformation and the coarse-graining procedure for polymer models in this language. We also apply it to a standard case in the literature of two-dimensional densities of states, where two competing energetic effects are present g (E1,E2) . We show when and why care has to be exercised when obtaining the microcanonical density of states g (E1+E2) from g (E1,E2) .
Multidimensional Modeling of Nova Outbursts
NASA Astrophysics Data System (ADS)
José, J.
2014-12-01
Classical novae repeatedly eject ˜10-4-10-5 M⊙ enriched in nuclear-processed material relative to solar abundances, recurring on intervals of decades to tens of millennia. They are probably the main sources of Galactic 15N, 17O and 13C. The origin of the large enhancements and inhomogeneous distribution of these species observed in high-resolution spectra of ejected nova shells has, however, remained unexplained for almost 50 years. Several mechanisms, including mixing by diffusion, shear or resonant gravity waves, have been proposed in the framework of one-dimensional or two-dimensional simulations, but none has proven successful because convective mixing can only be modeled accurately in three-dimensions. This review focuses on multidimensional modeling of nova explosions, with emphasis on mixing at the core-envelope interface. Examples of buoyant fingering driving vortices from the Kelvin-Helmholtz instability, leading to enrichment of the accreted envelope with material from the outer white dwarf core, will be described. This mixing mechanism naturally accounts for large-scale chemical inhomogeneities. Preliminary simulations of the interaction between the nova ejecta and the secondary star will also be outlined.
ERIC Educational Resources Information Center
Van Deun, Katrijn; Heiser, Willem J.; Delbeke, Luc
2007-01-01
A multidimensional unfolding technique that is not prone to degenerate solutions and is based on multidimensional scaling of a complete data matrix is proposed: distance information about the unfolding data and about the distances both among judges and among objects is included in the complete matrix. The latter information is derived from the…
Improved multidimensional semiclassical tunneling theory.
Wagner, Albert F
2013-12-12
We show that the analytic multidimensional semiclassical tunneling formula of Miller et al. [Miller, W. H.; Hernandez, R.; Handy, N. C.; Jayatilaka, D.; Willets, A. Chem. Phys. Lett. 1990, 172, 62] is qualitatively incorrect for deep tunneling at energies well below the top of the barrier. The origin of this deficiency is that the formula uses an effective barrier weakly related to the true energetics but correctly adjusted to reproduce the harmonic description and anharmonic corrections of the reaction path at the saddle point as determined by second order vibrational perturbation theory. We present an analytic improved semiclassical formula that correctly includes energetic information and allows a qualitatively correct representation of deep tunneling. This is done by constructing a three segment composite Eckart potential that is continuous everywhere in both value and derivative. This composite potential has an analytic barrier penetration integral from which the semiclassical action can be derived and then used to define the semiclassical tunneling probability. The middle segment of the composite potential by itself is superior to the original formula of Miller et al. because it incorporates the asymmetry of the reaction barrier produced by the known reaction exoergicity. Comparison of the semiclassical and exact quantum tunneling probability for the pure Eckart potential suggests a simple threshold multiplicative factor to the improved formula to account for quantum effects very near threshold not represented by semiclassical theory. The deep tunneling limitations of the original formula are echoed in semiclassical high-energy descriptions of bound vibrational states perpendicular to the reaction path at the saddle point. However, typically ab initio energetic information is not available to correct it. The Supporting Information contains a Fortran code, test input, and test output that implements the improved semiclassical tunneling formula. PMID:24224758
Image demodulation using multidimensional energy separation
NASA Astrophysics Data System (ADS)
Maragos, Petros; Bovik, Alan C.
1995-09-01
Locally narrow-band images can be modeled as two-dimensional (2D) spatial AM-FM signals with several applications in image texture analysis and computer vision. We formulate an image-demodulation problem and present a solution based on the multidimensional energy operator Phi (f)= \\double-vertical-bar \\inverted-Delta-triangle f \\double-vertical-bar 2-f \\inverted-Delta-triangle 2 f . This nonlinear operator is a multidimensional extension of the one-dimensional (1D) energy-tracking operator Psi (f)=( f\\prime)2 -ff\\prime\\prime , which has been found useful for demodulating 1D AM-FM and speech signals. We discuss some interesting properties of the multidimensional operator and develop a multidimensional energy-separation algorithm to estimate the amplitude envelope and instantaneous frequencies of 2D spatially varying AM-FM signals. Experiments are also presented on applying this 2D energy-demodulation algorithm to estimate the instantaneous amplitude contrast and spatial frequencies of image textures bandpass filtered by means of Gabor filters. The attractive features of the multidimensional energy operator and the 2D energy-separation algorithm are their simplicity, efficiency, and ability to track instantaneously varying
On simplified application of multidimensional Savitzky-Golay filters and differentiators
NASA Astrophysics Data System (ADS)
Shekhar, Chandra
2016-02-01
I propose a simplified approach for multidimensional Savitzky-Golay filtering, to enable its fast and easy implementation in scientific and engineering applications. The proposed method, which is derived from a generalized framework laid out by Thornley (D. J. Thornley, "Novel anisotropic multidimensional convolution filters for derivative estimation and reconstruction" in Proceedings of International Conference on Signal Processing and Communications, November 2007), first transforms any given multidimensional problem into a unique one, by transforming coordinates of the sampled data nodes to unity-spaced, uniform data nodes, and then performs filtering and calculates partial derivatives on the unity-spaced nodes. It is followed by transporting the calculated derivatives back onto the original data nodes by using the chain rule of differentiation. The burden to performing the most cumbersome task, which is to carry out the filtering and to obtain derivatives on the unity-spaced nodes, is almost eliminated by providing convolution coefficients for a number of convolution kernel sizes and polynomial orders, up to four spatial dimensions. With the availability of the convolution coefficients, the task of filtering at a data node reduces merely to multiplication of two known matrices. Simplified strategies to adequately address near-boundary data nodes and to calculate partial derivatives there are also proposed. Finally, the proposed methodologies are applied to a three-dimensional experimentally obtained data set, which shows that multidimensional Savitzky-Golay filters and differentiators perform well in both the internal and the near-boundary regions of the domain.
Preface: Special Topic on Multidimensional Spectroscopy
NASA Astrophysics Data System (ADS)
Mukamel, Shaul; Bakker, Huib J.
2015-06-01
Multidimensional signals are generated by subjecting molecules to sequences of short optical pulses and recording correlation plots related to the various controlled delay periods. These techniques which span all the way from the THz to the x-ray regimes provide qualitatively new structural and dynamical molecular information not available from conventional one-dimensional techniques. This issue surveys the recent experimental and theoretical progresses in this rapidly developing 20 year old field which illustrates the novel insights provided by multidimensional techniques into electronic and nuclear motions. It should serve as a valuable source for experts in the field and help introduce newcomers to this exciting and challenging branch of nonlinear spectroscopy.
Preface: Special Topic on Multidimensional Spectroscopy
Mukamel, Shaul; Bakker, Huib J.
2015-06-07
Multidimensional signals are generated by subjecting molecules to sequences of short optical pulses and recording correlation plots related to the various controlled delay periods. These techniques which span all the way from the THz to the x-ray regimes provide qualitatively new structural and dynamical molecular information not available from conventional one-dimensional techniques. This issue surveys the recent experimental and theoretical progresses in this rapidly developing 20 year old field which illustrates the novel insights provided by multidimensional techniques into electronic and nuclear motions. It should serve as a valuable source for experts in the field and help introduce newcomers to this exciting and challenging branch of nonlinear spectroscopy.
Preface: Special Topic on Multidimensional Spectroscopy.
Mukamel, Shaul; Bakker, Huib J
2015-06-01
Multidimensional signals are generated by subjecting molecules to sequences of short optical pulses and recording correlation plots related to the various controlled delay periods. These techniques which span all the way from the THz to the x-ray regimes provide qualitatively new structural and dynamical molecular information not available from conventional one-dimensional techniques. This issue surveys the recent experimental and theoretical progresses in this rapidly developing 20 year old field which illustrates the novel insights provided by multidimensional techniques into electronic and nuclear motions. It should serve as a valuable source for experts in the field and help introduce newcomers to this exciting and challenging branch of nonlinear spectroscopy.
Confirmatory Factor Analysis and Profile Analysis via Multidimensional Scaling
ERIC Educational Resources Information Center
Kim, Se-Kang; Davison, Mark L.; Frisby, Craig L.
2007-01-01
This paper describes the Confirmatory Factor Analysis (CFA) parameterization of the Profile Analysis via Multidimensional Scaling (PAMS) model to demonstrate validation of profile pattern hypotheses derived from multidimensional scaling (MDS). Profile Analysis via Multidimensional Scaling (PAMS) is an exploratory method for identifying major…
The Efficacy of Multidimensional Constraint Keys in Database Query Performance
ERIC Educational Resources Information Center
Cardwell, Leslie K.
2012-01-01
This work is intended to introduce a database design method to resolve the two-dimensional complexities inherent in the relational data model and its resulting performance challenges through abstract multidimensional constructs. A multidimensional constraint is derived and utilized to implement an indexed Multidimensional Key (MK) to abstract a…
Fast Fourier Transform algorithm design and tradeoffs
NASA Technical Reports Server (NTRS)
Kamin, Ray A., III; Adams, George B., III
1988-01-01
The Fast Fourier Transform (FFT) is a mainstay of certain numerical techniques for solving fluid dynamics problems. The Connection Machine CM-2 is the target for an investigation into the design of multidimensional Single Instruction Stream/Multiple Data (SIMD) parallel FFT algorithms for high performance. Critical algorithm design issues are discussed, necessary machine performance measurements are identified and made, and the performance of the developed FFT programs are measured. Fast Fourier Transform programs are compared to the currently best Cray-2 FFT program.
Multidimensional Human Dynamics in Mobile Phone Communications
Quadri, Christian; Zignani, Matteo; Capra, Lorenzo; Gaito, Sabrina; Rossi, Gian Paolo
2014-01-01
In today's technology-assisted society, social interactions may be expressed through a variety of techno-communication channels, including online social networks, email and mobile phones (calls, text messages). Consequently, a clear grasp of human behavior through the diverse communication media is considered a key factor in understanding the formation of the today's information society. So far, all previous research on user communication behavior has focused on a sole communication activity. In this paper we move forward another step on this research path by performing a multidimensional study of human sociality as an expression of the use of mobile phones. The paper focuses on user temporal communication behavior in the interplay between the two complementary communication media, text messages and phone calls, that represent the bi-dimensional scenario of analysis. Our study provides a theoretical framework for analyzing multidimensional bursts as the most general burst category, that includes one-dimensional bursts as the simplest case, and offers empirical evidence of their nature by following the combined phone call/text message communication patterns of approximately one million people over three-month period. This quantitative approach enables the design of a generative model rooted in the three most significant features of the multidimensional burst - the number of dimensions, prevalence and interleaving degree - able to reproduce the main media usage attitude. The other findings of the paper include a novel multidimensional burst detection algorithm and an insight analysis of the human media selection process. PMID:25068479
Longitudinal Network Analysis Using Multidimensional Scaling.
ERIC Educational Resources Information Center
Barnett, George A.; Palmer, Mark T.
The Galileo System, a variant of metric multidimensional scaling, is used in this paper to analyze over-time changes in social networks. The paper first discusses the theoretical necessity for the use of this procedure and the methodological problems associated with its use. It then examines the air traffic network among 31 major cities in the…
Multidimensional Perspectives on Principal Leadership Effectiveness
ERIC Educational Resources Information Center
Beycioglu, Kadir, Ed.; Pashiardis, Petros, Ed.
2015-01-01
Exceptional management skills are crucial to success in educational environments. As school leaders, principals are expected to effectively supervise the school system while facing a multitude of issues and demands. "Multidimensional Perspectives on Principal Leadership Effectiveness" combines best practices and the latest approaches in…
Uncertainty of Comparative Judgments and Multidimensional Structure
ERIC Educational Resources Information Center
Sjoberg, Lennart
1975-01-01
An analysis of preferences with respect to silhouette drawings of nude females is presented. Systematic intransitivities were discovered. The dispersions of differences (comparatal dispersons) were shown to reflect the multidimensional structure of the stimuli, a finding expected on the basis of prior work. (Author)
Bilingual Creativity, Multidimensional Analysis, and World Englishes.
ERIC Educational Resources Information Center
Baker, Wendy; Eggington, William G.
1999-01-01
Using Biber's multidimensional analysis (1998) to examine a large corpus of world English literatures written in Indian, West African, British, Anglo-American, and Mexican-American varieties of English, examines whether quantitative analyses can also be insightful and useful in the examination of world Englishes literatures in expanding…
Multidimensional human dynamics in mobile phone communications.
Quadri, Christian; Zignani, Matteo; Capra, Lorenzo; Gaito, Sabrina; Rossi, Gian Paolo
2014-01-01
In today's technology-assisted society, social interactions may be expressed through a variety of techno-communication channels, including online social networks, email and mobile phones (calls, text messages). Consequently, a clear grasp of human behavior through the diverse communication media is considered a key factor in understanding the formation of the today's information society. So far, all previous research on user communication behavior has focused on a sole communication activity. In this paper we move forward another step on this research path by performing a multidimensional study of human sociality as an expression of the use of mobile phones. The paper focuses on user temporal communication behavior in the interplay between the two complementary communication media, text messages and phone calls, that represent the bi-dimensional scenario of analysis. Our study provides a theoretical framework for analyzing multidimensional bursts as the most general burst category, that includes one-dimensional bursts as the simplest case, and offers empirical evidence of their nature by following the combined phone call/text message communication patterns of approximately one million people over three-month period. This quantitative approach enables the design of a generative model rooted in the three most significant features of the multidimensional burst - the number of dimensions, prevalence and interleaving degree - able to reproduce the main media usage attitude. The other findings of the paper include a novel multidimensional burst detection algorithm and an insight analysis of the human media selection process. PMID:25068479
Multidimensional human dynamics in mobile phone communications.
Quadri, Christian; Zignani, Matteo; Capra, Lorenzo; Gaito, Sabrina; Rossi, Gian Paolo
2014-01-01
In today's technology-assisted society, social interactions may be expressed through a variety of techno-communication channels, including online social networks, email and mobile phones (calls, text messages). Consequently, a clear grasp of human behavior through the diverse communication media is considered a key factor in understanding the formation of the today's information society. So far, all previous research on user communication behavior has focused on a sole communication activity. In this paper we move forward another step on this research path by performing a multidimensional study of human sociality as an expression of the use of mobile phones. The paper focuses on user temporal communication behavior in the interplay between the two complementary communication media, text messages and phone calls, that represent the bi-dimensional scenario of analysis. Our study provides a theoretical framework for analyzing multidimensional bursts as the most general burst category, that includes one-dimensional bursts as the simplest case, and offers empirical evidence of their nature by following the combined phone call/text message communication patterns of approximately one million people over three-month period. This quantitative approach enables the design of a generative model rooted in the three most significant features of the multidimensional burst - the number of dimensions, prevalence and interleaving degree - able to reproduce the main media usage attitude. The other findings of the paper include a novel multidimensional burst detection algorithm and an insight analysis of the human media selection process.
Multidimensional IRT Models for Composite Scores
ERIC Educational Resources Information Center
Yen, Shu Jing; Walker, Leah
2007-01-01
Tests of English Language Proficiency are often designed such that each section of the test measures a single latent ability. For instance an English Proficiency Assessment might consist of sections measuring Speaking, Listening, and Reading ability. However, Overall English Proficiency and composite abilities are naturally multidimensional. This…
Determining Factor Structure in a Multidimensional Inventory.
ERIC Educational Resources Information Center
Deeter, Thomas E.; Gill, Diane L.
A two-step procedure is described and used to revise a multidimensional inventory in its developmental stages. First, the latent factors influencing the observed variables on the inventory are determined and justified using the following five methods: Kaiser's criterion, root staring, examination of difference values, examination of root mean…
Stability of Adolescents' Multidimensional Life Satisfaction Reports
ERIC Educational Resources Information Center
Antaramian, Susan P.; Huebner, E. Scott
2009-01-01
Eighty-four students were administered the Multidimensional Students' Life Satisfaction Scale (MSLSS) on three occasions, 1 year apart (Grades 8, 9, and 10). The 1-year stability coefficients ranged from 0.29 to 0.59, whereas the 2-year stability coefficients ranged from 0.41 to 0.59. MSLSS mean scores were consistent across administrations, with…
A New Heterogeneous Multidimensional Unfolding Procedure
ERIC Educational Resources Information Center
Park, Joonwook; Rajagopal, Priyali; DeSarbo, Wayne S.
2012-01-01
A variety of joint space multidimensional scaling (MDS) methods have been utilized for the spatial analysis of two- or three-way dominance data involving subjects' preferences, choices, considerations, intentions, etc. so as to provide a parsimonious spatial depiction of the underlying relevant dimensions, attributes, stimuli, and/or subjects'…
Multidimensional NMR spectroscopy in a single scan.
Gal, Maayan; Frydman, Lucio
2015-11-01
Multidimensional NMR has become one of the most widespread spectroscopic tools available to study diverse structural and functional aspects of organic and biomolecules. A main feature of multidimensional NMR is the relatively long acquisition times that these experiments demand. For decades, scientists have been working on a variety of alternatives that would enable NMR to overcome this limitation, and deliver its data in shorter acquisition times. Counting among these methodologies is the so-called ultrafast (UF) NMR approach, which in principle allows one to collect arbitrary multidimensional correlations in a single sub-second transient. By contrast to conventional acquisitions, a main feature of UF NMR is a spatiotemporal manipulation of the spins that imprints the chemical shift and/or J-coupling evolutions being sought, into a spatial pattern. Subsequent gradient-based manipulations enable the reading out of this information and its multidimensional correlation into patterns that are identical to those afforded by conventional techniques. The current review focuses on the fundamental principles of this spatiotemporal UF NMR manipulation, and on a few of the methodological extensions that this form of spectroscopy has undergone during the years. PMID:26249041
A Multidimensional Construct of Self-Esteem
ERIC Educational Resources Information Center
Norem-Hebeisen, Ardyth A.
1976-01-01
Evidence for construct validity of this multi-dimensional concept of self esteem includes the relative congruence of the factor structure with the theoretical construct, the stability of the structure when subjected to a series of empirical tests, increasingly positive self-referent responses with increasing age, willingness to become more…
The Multidimensional Curriculum Model (MdCM)
ERIC Educational Resources Information Center
Vidergor, Hava E.
2010-01-01
The multidimensional Curriculum Model (MdCM) helps teachers to better prepare gifted and able students for our changing world, acquiring much needed skills. It is influenced by general learning theory of constructivism, notions of preparing students for 21st century, Teaching the Future Model, and current comprehensive curriculum models for…
Scaling Multidimensional Inference for Structured Gaussian Processes.
Gilboa, Elad; Saatçi, Yunus; Cunningham, John P
2013-09-30
Exact Gaussian process (GP) regression has O(N^3) runtime for data size N, making it intractable for large N. Many algorithms for improving GP scaling approximate the covariance with lower rank matrices. Other work has exploited structure inherent in particular covariance functions, including GPs with implied Markov structure, and inputs on a lattice (both enable O(N) or O(N log N) runtime). However, these GP advances have not been well extended to the multidimensional input setting, despite the preponderance of multidimensional applications. This paper introduces and tests three novel extensions of structured GPs to multidimensional inputs, for models with additive and multiplicative kernels. First we present a new method for inference in additive GPs, showing a novel connection between the classic backfitting method and the Bayesian framework. We extend this model using two advances: a variant of projection pursuit regression, and a Laplace approximation for non-Gaussian observations. Lastly, for multiplicative kernel structure, we present a novel method for GPs with inputs on a multidimensional grid. We illustrate the power of these three advances on several datasets, achieving performance equal to or very close to the naive GP at orders of magnitude less cost.
Scaling Multidimensional Inference for Structured Gaussian Processes.
Gilboa, Elad; Saatçi, Yunus; Cunningham, John P
2015-02-01
Exact Gaussian process (GP) regression has O(N(3)) runtime for data size N, making it intractable for large N . Many algorithms for improving GP scaling approximate the covariance with lower rank matrices. Other work has exploited structure inherent in particular covariance functions, including GPs with implied Markov structure, and inputs on a lattice (both enable O(N) or O(N log N) runtime). However, these GP advances have not been well extended to the multidimensional input setting, despite the preponderance of multidimensional applications. This paper introduces and tests three novel extensions of structured GPs to multidimensional inputs, for models with additive and multiplicative kernels. First we present a new method for inference in additive GPs, showing a novel connection between the classic backfitting method and the Bayesian framework. We extend this model using two advances: a variant of projection pursuit regression, and a Laplace approximation for non-Gaussian observations. Lastly, for multiplicative kernel structure, we present a novel method for GPs with inputs on a multidimensional grid. We illustrate the power of these three advances on several data sets, achieving performance equal to or very close to the naive GP at orders of magnitude less cost.
Multidimensional neural growing networks and computer intelligence
Yashchenko, V.A.
1995-03-01
This paper examines information-computation processes in time and in space and some aspects of computer intelligence using multidimensional matrix neural growing networks. In particular, issues of object-oriented {open_quotes}thinking{close_quotes} of computers are considered.
Multidimensional Treatment of Fear of Death.
ERIC Educational Resources Information Center
Hoelter, Jon W.
1979-01-01
Presents a multidimensional conception of fear of death and provides subscales for measuring suggested dimensions (fear of the dying process, of the dead, of being destroyed, for significant others, of the unknown, of conscious death, for body after death, and of premature death). Evidence for construct validity is provided. (Author/BEF)
Paradoxical Results in Multidimensional Item Response Theory
ERIC Educational Resources Information Center
Hooker, Giles; Finkelman, Matthew; Schwartzman, Armin
2009-01-01
In multidimensional item response theory (MIRT), it is possible for the estimate of a subject's ability in some dimension to decrease after they have answered a question correctly. This paper investigates how and when this type of paradoxical result can occur. We demonstrate that many response models and statistical estimates can produce…
Unidimensional Interpretations for Multidimensional Test Items
ERIC Educational Resources Information Center
Kahraman, Nilufer
2013-01-01
This article considers potential problems that can arise in estimating a unidimensional item response theory (IRT) model when some test items are multidimensional (i.e., show a complex factorial structure). More specifically, this study examines (1) the consequences of model misfit on IRT item parameter estimates due to unintended minor item-level…
MATLAB tensor classes for fast algorithm prototyping : source code.
Bader, Brett William; Kolda, Tamara Gibson
2004-10-01
We present the source code for three MATLAB classes for manipulating tensors in order to allow fast algorithm prototyping. A tensor is a multidimensional or Nway array. This is a supplementary report; details on using this code are provided separately in SAND-XXXX.
On the monotonicity of multidimensional finite difference schemes
NASA Astrophysics Data System (ADS)
Kovyrkina, O.; Ostapenko, V.
2016-10-01
The classical concept of monotonicity, introduced by Godunov for linear one-dimensional difference schemes, is extended to multidimensional case. Necessary and sufficient conditions of monotonicity are obtained for linear multidimensional difference schemes of first order. The constraints on the numerical viscosity are given that ensure the monotonicity of a difference scheme in the multidimensional case. It is proposed a modification of the second order multidimensional CABARET scheme that preserves the monotonicity of one-dimensional discrete solutions and, as a result, ensures higher smoothness in the computation of multidimensional discontinuous solutions. The results of two-dimensional test computations illustrating the advantages of the modified CABARET scheme are presented.
Preface: Special Topic on Multidimensional Spectroscopy.
Mukamel, Shaul; Bakker, Huib J
2015-06-01
Multidimensional signals are generated by subjecting molecules to sequences of short optical pulses and recording correlation plots related to the various controlled delay periods. These techniques which span all the way from the THz to the x-ray regimes provide qualitatively new structural and dynamical molecular information not available from conventional one-dimensional techniques. This issue surveys the recent experimental and theoretical progresses in this rapidly developing 20 year old field which illustrates the novel insights provided by multidimensional techniques into electronic and nuclear motions. It should serve as a valuable source for experts in the field and help introduce newcomers to this exciting and challenging branch of nonlinear spectroscopy. PMID:26049418
Multidimensional integration in a heterogeneous network environment
NASA Astrophysics Data System (ADS)
Veseli, Siniša
1998-01-01
We consider several issues related to the multidimensional integration using a network of heterogeneous computers. Based on these considerations, we develop a new general purpose scheme which can significantly reduce the time needed for evaluation of integrals with CPU intensive integrands. This scheme is a parallel version of the well-known adaptive Monte Carlo method (the VEGAS algorithm), and is incorporated into a new integration package which uses the standard set of message-passing routines in the PVM software system.
Multidimensional reaction rate theory with anisotropic diffusion.
Berezhkovskii, Alexander M; Szabo, Attila; Greives, Nicholas; Zhou, Huan-Xiang
2014-11-28
An analytical expression is derived for the rate constant that describes diffusive transitions between two deep wells of a multidimensional potential. The expression, in contrast to the Kramers-Langer formula for the rate constant, is valid even when the diffusion is highly anisotropic. Our approach is based on a variational principle for the reactive flux and uses a trial function for the splitting probability or commitor. The theoretical result is validated by Brownian dynamics simulations.
Multidimensional Homophily in Friendship Networks1
Block, Per; Grund, Thomas
2014-01-01
Homophily – the tendency for individuals to associate with similar others – is one of the most persistent findings in social network analysis. Its importance is established along the lines of a multitude of sociologically relevant dimensions, e.g. sex, ethnicity and social class. Existing research, however, mostly focuses on one dimension at a time. But people are inherently multidimensional, have many attributes and are members of multiple groups. In this article, we explore such multidimensionality further in the context of network dynamics. Are friendship ties increasingly likely to emerge and persist when individuals have an increasing number of attributes in common? We analyze eleven friendship networks of adolescents, draw on stochastic actor-oriented network models and focus on the interaction of established homophily effects. Our results indicate that main effects for homophily on various dimensions are positive. At the same time, the interaction of these homophily effects is negative. There seems to be a diminishing effect for having more than one attribute in common. We conclude that studies of homophily and friendship formation need to address such multidimensionality further. PMID:25525503
Van Dyke, William J.
1992-01-01
A fast valve is disclosed that can close on the order of 7 milliseconds. It is closed by the force of a compressed air spring with the moving parts of the valve designed to be of very light weight and the valve gate being of wedge shaped with O-ring sealed faces to provide sealing contact without metal to metal contact. The combination of the O-ring seal and an air cushion create a soft final movement of the valve closure to prevent the fast air acting valve from having a harsh closing.
Van Dyke, W.J.
1992-04-07
A fast valve is disclosed that can close on the order of 7 milliseconds. It is closed by the force of a compressed air spring with the moving parts of the valve designed to be of very light weight and the valve gate being of wedge shaped with O-ring sealed faces to provide sealing contact without metal to metal contact. The combination of the O-ring seal and an air cushion create a soft final movement of the valve closure to prevent the fast air acting valve from having a harsh closing. 4 figs.
A multidimensional study of preference judgements for excerpts of music.
Tekman, H G
1998-06-01
Subjects evaluated how well they liked each one of 38 short excerpts of Western music and also judged how well each excerpt was described by 23 adjectives. How well an excerpt was liked was negatively correlated with the use of the adjectives 'unpleasant', 'complex', 'tense', and 'dissonant'. The use of the adjectives 'melodic', 'pleasant', 'sentimental', and 'familiar', was positively related to how well an excerpt was liked. The correlations between the preference judgments of different excerpts were taken as a measure of similarity between the excerpts. This measure of similarity was used in a multidimensional scaling analysis with the purpose of identifying dimension that may determine preferences for music. In the six-dimensional space generated (stress value was .255) coordinates on three of the dimensions could be predicted, in part, by the use of the adjectives 'sentimental', 'fast', and a combination of 'high pitched', 'calm', and 'sad', respectively. Thus, some clues to the factors underlying musical preferences were obtained. Although a large number of dimensions were necessary and all of them could not be interpreted meaningfully here, this method may be developed as a way of conceptualizing musical preferences with a more careful selection of excerpts and more detailed assessment of their qualities. PMID:9676495
Li, Yifei; Huang, Mitchell; Byrd, R. Andrew
2015-01-01
The advantages of non-uniform sampling (NUS) in offering time savings and resolution enhancement in NMR experiments have been increasingly recognized. The possibility of sensitivity gain by NUS has also been demonstrated. Application of NUS to multidimensional NMR experiments requires the selection of a sampling scheme and a reconstruction scheme to generate uniformly sampled time domain data. In this report, an efficient reconstruction scheme is presented and used to evaluate a range of regularization algorithms that collectively yield a generalized solution to processing NUS data in multidimensional NMR experiments. We compare l1-norm (L1), iterative re-weighted l1-norm (IRL1), and Gaussian smoothed l0-norm (Gaussian-SL0) regularization for processing multidimensional NUS NMR data. Based on the reconstruction of different multidimensional NUS NMR data sets, L1 is demonstrated to be a fast and accurate reconstruction method for both quantitative, high dynamic range applications (e.g. NOESY) and for all J-coupled correlation experiments. Compared to L1, both IRL1 and Gaussian-SL0 are shown to produce slightly higher quality reconstructions with improved linearity in peak intensities, albeit with a computational cost. Finally, a generalized processing system, NESTA-NMR, is described that utilizes a fast and accurate first-order gradient descent algorithm (NESTA) recently developed in the compressed sensing field. NESTA-NMR incorporates L1, IRL1, and Gaussian-SL0 regularization. NESTA-NMR is demonstrated to provide an efficient, streamlined approach to handling all types of multidimensional NMR data using proteins ranging in size from 8 to 32 kDa. PMID:25808220
Nuclear Forensic Inferences Using Iterative Multidimensional Statistics
Robel, M; Kristo, M J; Heller, M A
2009-06-09
Nuclear forensics involves the analysis of interdicted nuclear material for specific material characteristics (referred to as 'signatures') that imply specific geographical locations, production processes, culprit intentions, etc. Predictive signatures rely on expert knowledge of physics, chemistry, and engineering to develop inferences from these material characteristics. Comparative signatures, on the other hand, rely on comparison of the material characteristics of the interdicted sample (the 'questioned sample' in FBI parlance) with those of a set of known samples. In the ideal case, the set of known samples would be a comprehensive nuclear forensics database, a database which does not currently exist. In fact, our ability to analyze interdicted samples and produce an extensive list of precise materials characteristics far exceeds our ability to interpret the results. Therefore, as we seek to develop the extensive databases necessary for nuclear forensics, we must also develop the methods necessary to produce the necessary inferences from comparison of our analytical results with these large, multidimensional sets of data. In the work reported here, we used a large, multidimensional dataset of results from quality control analyses of uranium ore concentrate (UOC, sometimes called 'yellowcake'). We have found that traditional multidimensional techniques, such as principal components analysis (PCA), are especially useful for understanding such datasets and drawing relevant conclusions. In particular, we have developed an iterative partial least squares-discriminant analysis (PLS-DA) procedure that has proven especially adept at identifying the production location of unknown UOC samples. By removing classes which fell far outside the initial decision boundary, and then rebuilding the PLS-DA model, we have consistently produced better and more definitive attributions than with a single pass classification approach. Performance of the iterative PLS-DA method
Construct continuity in the presence of multidimensionality
NASA Astrophysics Data System (ADS)
Staniewska, Dorota
Unidimensionality -- a condition, under which only one dominant construct is being measured by the test, is a fundamental assumption of most modern day psychometric models. However, some tests are multidimensional by design. A test, for instance, might measure physics, biology and chemistry subscales combined to measure a "general science" composite. The relative magnitudes of those subscales sometimes shift from administration to administration, which results in an altered composite. This study examined the conditions under which two different forms of a multidimensional test measure the same composite construct to a degree that allows them to be equated, i.e. used interchangeably. IRT true-score equating was used in a simulation study to assess the closeness of the scores on the forms. Conditions examined included the correlations between subscales, varying number of items per subscale form to form, and different subpopulation ability estimates on the subscales. Differences in the equating errors due to generating model (1PL or 3PL) were also examined. A way of calculating a unidimensional composite from a two-dimensional ability was devised and compared to the unidimensional composite obtained from Parscale. It was found that in general, the errors increase with decreasing correlation between traits and increased divergence of the two forms to be equated, with the later being the main predictor of the equating errors. However, the magnitude of those errors was small for the population as a whole especially when all examinee abilities are drawn from the same distribution. It was concluded that IRT true score equating is relatively robust to multidimensionality for the conditions examined, especially if the overall population score is desired. However, when accurate estimate of the equated score for individuals at the extremes of the population is needed, or whenever population abilities are drawn from more than one distribution, the unidimensional true score
ERIC Educational Resources Information Center
Toro, Maritsa
2011-01-01
The statistical assessment of dimensionality provides evidence of the underlying constructs measured by a survey or test instrument. This study focuses on educational measurement, specifically tests comprised of items described as multidimensional. That is, items that require examinee proficiency in multiple content areas and/or multiple cognitive…
Palmprint based multidimensional fuzzy vault scheme.
Liu, Hailun; Sun, Dongmei; Xiong, Ke; Qiu, Zhengding
2014-01-01
Fuzzy vault scheme (FVS) is one of the most popular biometric cryptosystems for biometric template protection. However, error correcting code (ECC) proposed in FVS is not appropriate to deal with real-valued biometric intraclass variances. In this paper, we propose a multidimensional fuzzy vault scheme (MDFVS) in which a general subspace error-tolerant mechanism is designed and embedded into FVS to handle intraclass variances. Palmprint is one of the most important biometrics; to protect palmprint templates; a palmprint based MDFVS implementation is also presented. Experimental results show that the proposed scheme not only can deal with intraclass variances effectively but also could maintain the accuracy and meanwhile enhance security. PMID:24892094
A multidimensional representation model of geographic features
Usery, E. Lynn; Timson, George; Coletti, Mark
2016-01-28
A multidimensional model of geographic features has been developed and implemented with data from The National Map of the U.S. Geological Survey. The model, programmed in C++ and implemented as a feature library, was tested with data from the National Hydrography Dataset demonstrating the capability to handle changes in feature attributes, such as increases in chlorine concentration in a stream, and feature geometry, such as the changing shoreline of barrier islands over time. Data can be entered directly, from a comma separated file, or features with attributes and relationships can be automatically populated in the model from data in the Spatial Data Transfer Standard format.
A multidimensional representation model of geographic features
Usery, E. Lynn; Timson, George; Coletti, Mark
2016-01-01
A multidimensional model of geographic features has been developed and implemented with data from The National Map of the U.S. Geological Survey. The model, programmed in C++ and implemented as a feature library, was tested with data from the National Hydrography Dataset demonstrating the capability to handle changes in feature attributes, such as increases in chlorine concentration in a stream, and feature geometry, such as the changing shoreline of barrier islands over time. Data can be entered directly, from a comma separated file, or features with attributes and relationships can be automatically populated in the model from data in the Spatial Data Transfer Standard format.
Multidimensional world, inflation, and modern acceleration
Bronnikov, K. A.; Rubin, S. G.; Svadkovsky, I. V.
2010-04-15
Starting from pure multidimensional gravity with curvature-nonlinear terms but no matter fields in the initial action, we obtain a cosmological model with two effective scalar fields related to the size of two extra factor spaces. The model includes both an early inflationary stage and that of modern accelerated expansion and satisfies the observational data. There are no small parameters; the effective inflaton mass depends on the initial conditions which explain its small value as compared to the Planck mass. At the modern stage, the size of extra dimensions slowly increases, therefore this model predicts drastic changes in the physical laws of our Universe in the remote future.
Multidimensional visualization and browsing for intelligence analysis
Crow, V.; Pottier, M.; Thomas, J.
1994-09-01
Visualization tools have been invaluable in the process of scientific discovery by providing researchers with insights gained through graphical tools and techniques. At PNL, the Multidimensional Visualization and Advanced Browsing (MVAB) project is extending visualization technology to the problems of intelligence analysis of textual documents by creating spatial representations of textual information. By representing an entire corpus of documents as points in a coordinate space of two or more dimensions, the tools developed by the MVAB team give the analyst the ability to quickly browse the entire document base and determine relationships among documents and publication patterns not readily discernible through traditional lexical means.
Evolution of multidimensional flat anisotropic cosmological models
Beloborodov, A. ); Demianski, M. Nicolaus Copernicus Astronomical Center, Bartycka 18, 00-716 Warsaw International Center for Relativistic Astrophysics , Universita di Roma I, La Sapienza, Rome ); Ivanov, P.; Polnarev, A.G. )
1993-07-15
We study the dynamics of a flat multidimensional anisotropic cosmological model filled with an anisotropic fluidlike medium. By an appropriate choice of variables, the dynamical equations reduce to a two-dimensional dynamical system. We present a detailed analysis of the time evolution of this system and the conditions of the existence of spacetime singularities. We investigate the conditions under which violent, exponential, and power-law inflation is possible. We show that dimensional reduction cannot proceed by anti-inflation (rapid contraction of internal space). Our model indicates that it is very difficult to achieve dimensional reduction by classical means.
Modeling, calculating, and analyzing multidimensional vibrational spectroscopies.
Tanimura, Yoshitaka; Ishizaki, Akihito
2009-09-15
Spectral line shapes in a condensed phase contain information from various dynamic processes that modulate the transition energy, such as microscopic dynamics, inter- and intramolecular couplings, and solvent dynamics. Because nonlinear response functions are sensitive to the complex dynamics of chemical processes, multidimensional vibrational spectroscopies can separate these processes. In multidimensional vibrational spectroscopy, the nonlinear response functions of a molecular dipole or polarizability are measured using ultrashort pulses to monitor inter- and intramolecular vibrational motions. Because a complex profile of such signals depends on the many dynamic and structural aspects of a molecular system, researchers would like to have a theoretical understanding of these phenomena. In this Account, we explore and describe the roles of different physical phenomena that arise from the peculiarities of the system-bath coupling in multidimensional spectra. We also present simple analytical expressions for a weakly coupled multimode Brownian system, which we use to analyze the results obtained by the experiments and simulations. To calculate the nonlinear optical response, researchers commonly use a particular form of a system Hamiltonian fit to the experimental results. The optical responses of molecular vibrational motions have been studied in either an oscillator model or a vibration energy state model. In principle, both models should give the same results as long as the energy states are chosen to be the eigenstates of the oscillator model. The energy state model can provide a simple description of nonlinear optical processes because the diagrammatic Liouville space theory that developed in the electronically resonant spectroscopies can easily handle three or four energy states involved in high-frequency vibrations. However, the energy state model breaks down if we include the thermal excitation and relaxation processes in the dynamics to put the system in a
Noncommutative accelerated multidimensional universe dominated by quintessence
NASA Astrophysics Data System (ADS)
El-Nabulsi, Ahmad Rami
2010-04-01
Noncommutative Geometry recently attracted growing interest of cosmologists, mainly after the greatest success of unifying the forces of nature into a single gravitational spectral action in a purely algebraic way, rather than as being an entirely new formalism. In the present work, we discuss a multidimensional Friedmann-Robertson-Walker flat universe in which the perfect fluid has a Gaussian profile in time and depends on a fundamental minimal length sqrt{θ} like ρ= ρ(0)exp (- t 2/4 θ) for some positive constant ρ(0). This special form is motivated by a more recent noncommutative inflationary cosmological model, which was found to be able to drive the universe through a bounce without the need of any scalar field. Furthermore, we conjecture that the generalized equation of state has the special form p= ω a m ρ- ρ,( ω, m)∈ℝ where a( t) is the scale factor. It was found that the expansion of the multidimensional universe accelerates in time and is dominated for very large time by quintessence. Many additional consequences are revealed and discussed in some detail.
Multidimensional Learner Model In Intelligent Learning System
NASA Astrophysics Data System (ADS)
Deliyska, B.; Rozeva, A.
2009-11-01
The learner model in an intelligent learning system (ILS) has to ensure the personalization (individualization) and the adaptability of e-learning in an online learner-centered environment. ILS is a distributed e-learning system whose modules can be independent and located in different nodes (servers) on the Web. This kind of e-learning is achieved through the resources of the Semantic Web and is designed and developed around a course, group of courses or specialty. An essential part of ILS is learner model database which contains structured data about learner profile and temporal status in the learning process of one or more courses. In the paper a learner model position in ILS is considered and a relational database is designed from learner's domain ontology. Multidimensional modeling agent for the source database is designed and resultant learner data cube is presented. Agent's modules are proposed with corresponding algorithms and procedures. Multidimensional (OLAP) analysis guidelines on the resultant learner module for designing dynamic learning strategy have been highlighted.
Multidimensional Modeling of Coronal Rain Dynamics
NASA Astrophysics Data System (ADS)
Fang, X.; Xia, C.; Keppens, R.
2013-07-01
We present the first multidimensional, magnetohydrodynamic simulations that capture the initial formation and long-term sustainment of the enigmatic coronal rain phenomenon. We demonstrate how thermal instability can induce a spectacular display of in situ forming blob-like condensations which then start their intimate ballet on top of initially linear force-free arcades. Our magnetic arcades host a chromospheric, transition region, and coronal plasma. Following coronal rain dynamics for over 80 minutes of physical time, we collect enough statistics to quantify blob widths, lengths, velocity distributions, and other characteristics which directly match modern observational knowledge. Our virtual coronal rain displays the deformation of blobs into V-shaped features, interactions of blobs due to mostly pressure-mediated levitations, and gives the first views of blobs that evaporate in situ or are siphoned over the apex of the background arcade. Our simulations pave the way for systematic surveys of coronal rain showers in true multidimensional settings to connect parameterized heating prescriptions with rain statistics, ultimately allowing us to quantify the coronal heating input.
Heterogeneous multidimensional scaling for complex networks
NASA Astrophysics Data System (ADS)
Xuan, Qi; Ma, Xiaodi; Fu, Chenbo; Dong, Hui; Zhang, Guijun; Yu, Li
2015-07-01
Many real-world networks are essentially heterogeneous, where the nodes have different abilities to gain connections. Such networks are difficult to be embedded into low-dimensional Euclidean space if we ignore the heterogeneity and treat all the nodes equally. In this paper, based on a newly defined heterogeneous distance and a generalized network distance under the constraints of network and triangle inequalities, respectively, we propose a new heterogeneous multidimensional scaling method (HMDS) to embed different networks into proper Euclidean spaces. We find that HMDS behaves much better than the traditional multidimensional scaling method (MDS) in embedding different artificial and real-world networks into Euclidean spaces. Besides, we also propose a method to estimate the appropriate dimensions of Euclidean spaces for different networks, and find that the estimated dimensions are quite close to the real dimensions for those geometrical networks under study. These methods thus can help to better understand the evolution of real-world networks, and have practical importance in network visualization, community detection, link prediction and localization of wireless sensors.
Visualizing multidimensional query results using animation
NASA Astrophysics Data System (ADS)
Sawant, Amit P.; Healey, Christopher G.
2008-01-01
Effective representation of large, complex collections of information (datasets) presents a difficult challenge. Visualization is a solution that uses a visual interface to support efficient analysis and discovery within the data. Our primary goal in this paper is a technique that allows viewers to compare multiple query results representing user-selected subsets of a multidimensional dataset. We present an algorithm that visualizes multidimensional information along a space-filling spiral. Graphical glyphs that vary their position, color, and texture appearance are used to represent attribute values for the data elements in each query result. Guidelines from human perception allow us to construct glyphs that are specifically designed to support exploration, facilitate the discovery of trends and relationships both within and between data elements, and highlight exceptions. A clustering algorithm applied to a user-chosen ranking attribute bundles together similar data elements. This encapsulation is used to show relationships across different queries via animations that morph between query results. We apply our techniques to the MovieLens recommender system, to demonstrate their applicability in a real-world environment, and then conclude with a simple validation experiment to identify the strengths and limitations of our design, compared to a traditional side-by-side visualization.
MULTIDIMENSIONAL MODELING OF CORONAL RAIN DYNAMICS
Fang, X.; Xia, C.; Keppens, R.
2013-07-10
We present the first multidimensional, magnetohydrodynamic simulations that capture the initial formation and long-term sustainment of the enigmatic coronal rain phenomenon. We demonstrate how thermal instability can induce a spectacular display of in situ forming blob-like condensations which then start their intimate ballet on top of initially linear force-free arcades. Our magnetic arcades host a chromospheric, transition region, and coronal plasma. Following coronal rain dynamics for over 80 minutes of physical time, we collect enough statistics to quantify blob widths, lengths, velocity distributions, and other characteristics which directly match modern observational knowledge. Our virtual coronal rain displays the deformation of blobs into V-shaped features, interactions of blobs due to mostly pressure-mediated levitations, and gives the first views of blobs that evaporate in situ or are siphoned over the apex of the background arcade. Our simulations pave the way for systematic surveys of coronal rain showers in true multidimensional settings to connect parameterized heating prescriptions with rain statistics, ultimately allowing us to quantify the coronal heating input.
Multidimensional Conservation Laws and Low Regularity Solutions
Barbara Lee Keyfitz
2007-06-16
This is the concluding report for the project, a continuation of research by Keyfitz and co-workers on multidimensional conservation laws, and applications of nonhyperbolic conservation laws in the two-fluid model for multiphase flow. The multidimensional research project was started with Suncica Canic, at the University of Houston and with Eun Heui Kim, now at California State University Long Beach. Two postdoctoral researchers, Katarina Jegdic and Allen Tesdall, also worked on this research. Jegdic's research was supported (for a total of one year) by this grant. Work on nonhyperbolic models for two-phase flows is being pursued jointly with Michael Sever, Hebrew University. Background for the project is contained in earlier reports. Note that in 2006, the project received a one-year no-cost extension that will end in September, 2007. A new proposal, for continuation of the research and for new projects, will be submitted in the Fall of 2007, with funding requested to begin in the summer of 2008. The reason for the 'funding gap' is Keyfitz's four-year stint as Director of the Fields Institute in Toronto, Canada. The research has continued, but has been supported by Canadian grant funds, as seems appropriate during this period.
Computations of entropy bounds: Multidimensional geometric methods
Makaruk, H.E.
1998-02-01
The entropy bounds for constructive upper bound on the needed number-of-bits for solving a dichotomy is represented by the quotient of two multidimensional solid volumes. For minimization of this upper bound exact calculation of the volume of this quotient is needed. Three methods for exact computing of the volume of a given nD volume are presented: (1) general method for calculation any nD volume by slicing it into volumes of decreasing dimension is presented; (2) a method applying appropriate curvilinear coordinate system is described for volume bounded by symmetrical curvilinear hypersurfaces (spheres, cones, hyperboloids, ellipsoids, cylinders, etc.); and (3) an algorithm for dividing any nD complex into simplices and computing of the volume of the simplices is presented, supplemented by a general formula for calculation of volume of an nD simplex. These mathematical methods enable exact calculation of volume of any complicated multidimensional solids. The methods allow for the calculation of the minimal volume and lead to tighter bounds on the needed number-of-bits.
Heteronuclear Multidimensional Protein NMR in a Teaching Laboratory
ERIC Educational Resources Information Center
Wright, Nathan T.
2016-01-01
Heteronuclear multidimensional NMR techniques are commonly used to study protein structure, function, and dynamics, yet they are rarely taught at the undergraduate level. Here, we describe a senior undergraduate laboratory where students collect, process, and analyze heteronuclear multidimensional NMR experiments using an unstudied Ig domain (Ig2…
Multidimensional Computerized Adaptive Testing for Indonesia Junior High School Biology
ERIC Educational Resources Information Center
Kuo, Bor-Chen; Daud, Muslem; Yang, Chih-Wei
2015-01-01
This paper describes a curriculum-based multidimensional computerized adaptive test that was developed for Indonesia junior high school Biology. In adherence to the Indonesian curriculum of different Biology dimensions, 300 items was constructed, and then tested to 2238 students. A multidimensional random coefficients multinomial logit model was…
Multidimensional Linking for Tests with Mixed Item Types
ERIC Educational Resources Information Center
Yao, Lihua; Boughton, Keith
2009-01-01
Numerous assessments contain a mixture of multiple choice (MC) and constructed response (CR) item types and many have been found to measure more than one trait. Thus, there is a need for multidimensional dichotomous and polytomous item response theory (IRT) modeling solutions, including multidimensional linking software. For example,…
Evaluating Item Fit for Multidimensional Item Response Models
ERIC Educational Resources Information Center
Zhang, Bo; Stone, Clement A.
2008-01-01
This research examines the utility of the s-x[superscript 2] statistic proposed by Orlando and Thissen (2000) in evaluating item fit for multidimensional item response models. Monte Carlo simulation was conducted to investigate both the Type I error and statistical power of this fit statistic in analyzing two kinds of multidimensional test…
Multidimensional Physical Self-Concept of Athletes with Physical Disabilities
ERIC Educational Resources Information Center
Shapiro, Deborah R.; Martin, Jeffrey J.
2010-01-01
The purposes of this investigation were first to predict reported PA (physical activity) behavior and self-esteem using a multidimensional physical self-concept model and second to describe perceptions of multidimensional physical self-concept (e.g., strength, endurance, sport competence) among athletes with physical disabilities. Athletes (N =…
The Concept of Aptitude and Multidimensional Validity Revisited.
ERIC Educational Resources Information Center
Roeser, Robert W.; Shavelson, Richard J.; Kupermintz, Haggai; Lau, Shun; Ayala, Carlos; Haydel, Angela; Schultz, Susan; Gallagher, Larry; Quihuis, Gisell
2002-01-01
Provides an overview of the approach of Richard E. Snow to the concept of aptitude and multidimensional validity and summarizes the studies in this special issue. Overall, studies confirmed the multidimensional structure of science achievement scores, the validity of some key motivational constructs for predicting achievement, and other ideas…
Entropic uncertainty relations in multidimensional position and momentum spaces
Huang Yichen
2011-05-15
Commutator-based entropic uncertainty relations in multidimensional position and momentum spaces are derived, twofold generalizing previous entropic uncertainty relations for one-mode states. They provide optimal lower bounds and imply the multidimensional variance-based uncertainty principle. The article concludes with an open conjecture.
HDF5-FastQuery: Accelerating Complex Queries on HDF Datasets usingFast Bitmap Indices
Gosink, Luke; Shalf, John; Stockinger, Kurt; Wu, Kesheng; Bethel,Wes
2006-03-30
Large scale scientific data is often stored in scientific data formats such as FITS, netCDF and HDF. These storage formats are of particular interest to the scientific user community since they provide multi-dimensional storage and retrieval. However, one of the drawbacks of these storage formats is that they do not support semantic indexing which is important for interactive data analysis where scientists look for features of interests such as ''Find all supernova explosions where energy > 10{sup 5} and temperature > 10{sup 6}''. In this paper we present a novel approach called HDF5-FastQuery to accelerate the data access of large HDF5 files by introducing multi-dimensional semantic indexing. Our implementation leverages an efficient indexing technology called bitmap indexing that has been widely used in the database community. Bitmap indices are especially well suited for interactive exploration of large-scale read only data. Storing the bitmap indices into the HDF5 file has the following advantages: (a) Significant performance speedup of accessing subsets of multi-dimensional data and (b) portability of the indices across multiple computer platforms. We will present an API that simplifies the execution of queries on HDF5 files for general scientific applications and data analysis. The design is flexible enough to accommodate the use of arbitrary indexing technology for semantic range queries. We will also provide a detailed performance analysis of HDF5-FastQuery for both synthetic and scientific data. The results demonstrate that our proposed approach for multi-dimensional queries is up to a factor of 2 faster than HDF5.
HDF5-FastQuery: Accelerating Complex Queries on HDF Datasets UsingFast Bitmap Indices
Gosink, Luke; Shalf, John; Stockinger, Kurt; Wu, Kesheng; Bethel,Wes
2005-12-07
Large scale scientific data is often stored in scientific data formats such as FITS, netCDF and HDF. These storage formats are of particular interest to the scientific user community since they provide multi-dimensional storage and retrieval. However, one of the drawbacks of these storage formats is that they do not support semantic indexing which is important for interactive data analysis where scientists look for features of interests such as ''Find all supernova explosions where energy >105 and temperature >106''. In this paper we present a novel approach called HDF5-FastQuery to accelerate the data access of large HDF5 files by introducing multi-dimensional semantic indexing. Our implementation leverages an efficient indexing technology called ''bitmapindexing'' that has been widely used in the database community. Bitmapindices are especially well suited for interactive exploration of large-scale read-only data. Storing the bitmap indices into the HDF5 file has the following advantages: (a) Significant performance speedup of accessing subsets of multi-dimensional data and (b) portability of the indices across multiple computer platforms. We will present an API that simplifies the execution of queries on HDF5 files for general scientific applications and data analysis. The design is flexible enough to accommodate the use of arbitrary indexing technology for semantic range queries. We will also provide a detailed performance analysis of HDF5-FastQuery for both synthetic and scientific data. The results demonstrate that our proposed approach for multi-dimensional queries is up to a factor of 2 faster than HDF5.
Multidimensional scaling of musical time estimations.
Cocenas-Silva, Raquel; Bueno, José Lino Oliveira; Molin, Paul; Bigand, Emmanuel
2011-06-01
The aim of this study was to identify the psycho-musical factors that govern time evaluation in Western music from baroque, classic, romantic, and modern repertoires. The excerpts were previously found to represent variability in musical properties and to induce four main categories of emotions. 48 participants (musicians and nonmusicians) freely listened to 16 musical excerpts (lasting 20 sec. each) and grouped those that seemed to have the same duration. Then, participants associated each group of excerpts to one of a set of sine wave tones varying in duration from 16 to 24 sec. Multidimensional scaling analysis generated a two-dimensional solution for these time judgments. Musical excerpts with high arousal produced an overestimation of time, and affective valence had little influence on time perception. The duration was also overestimated when tempo and loudness were higher, and to a lesser extent, timbre density. In contrast, musical tension had little influence. PMID:21853763
AMADA-Analysis of multidimensional astronomical datasets
NASA Astrophysics Data System (ADS)
de Souza, R. S.; Ciardi, B.
2015-09-01
We present AMADA, an interactive web application to analyze multidimensional datasets. The user uploads a simple ASCII file and AMADA performs a number of exploratory analysis together with contemporary visualizations diagnostics. The package performs a hierarchical clustering in the parameter space, and the user can choose among linear, monotonic or non-linear correlation analysis. AMADA provides a number of clustering visualization diagnostics such as heatmaps, dendrograms, chord diagrams, and graphs. In addition, AMADA has the option to run a standard or robust principal components analysis, displaying the results as polar bar plots. The code is written in R and the web interface was created using the SHINY framework. AMADA source-code is freely available at https://goo.gl/KeSPue, and the shiny-app at http://goo.gl/UTnU7I.
Multidimensional Electronic Spectroscopy of Photochemical Reactions.
Nuernberger, Patrick; Ruetzel, Stefan; Brixner, Tobias
2015-09-21
Coherent multidimensional electronic spectroscopy can be employed to unravel various channels in molecular chemical reactions. This approach is thus not limited to analysis of energy transfer or charge transfer (i.e. processes from photophysics), but can also be employed in situations where the investigated system undergoes permanent structural changes (i.e. in photochemistry). Photochemical model reactions are discussed by using the example of merocyanine/spiropyran-based molecular switches, which show a rich variety of reaction channels, in particular ring opening and ring closing, cis-trans isomerization, coherent vibrational wave-packet motion, radical ion formation, and population relaxation. Using pump-probe, pump-repump-probe, coherent two-dimensional and three-dimensional, triggered-exchange 2D, and quantum-control spectroscopy, we gain intuitive pictures on which product emerges from which reactant and which reactive molecular modes are associated. PMID:26382095
Multidimensional student skills with collaborative filtering
NASA Astrophysics Data System (ADS)
Bergner, Yoav; Rayyan, Saif; Seaton, Daniel; Pritchard, David E.
2013-01-01
Despite the fact that a physics course typically culminates in one final grade for the student, many instructors and researchers believe that there are multiple skills that students acquire to achieve mastery. Assessment validation and data analysis in general may thus benefit from extension to multidimensional ability. This paper introduces an approach for model determination and dimensionality analysis using collaborative filtering (CF), which is related to factor analysis and item response theory (IRT). Model selection is guided by machine learning perspectives, seeking to maximize the accuracy in predicting which students will answer which items correctly. We apply the CF to response data for the Mechanics Baseline Test and combine the results with prior analysis using unidimensional IRT.
Multidimensional multiphysics simulation of TRISO particle fuel
NASA Astrophysics Data System (ADS)
Hales, J. D.; Williamson, R. L.; Novascone, S. R.; Perez, D. M.; Spencer, B. W.; Pastore, G.
2013-11-01
Multidimensional multiphysics analysis of TRISO-coated particle fuel using the BISON finite element nuclear fuels code is described. The governing equations and material models applicable to particle fuel and implemented in BISON are outlined. Code verification based on a recent IAEA benchmarking exercise is described, and excellent comparisons are reported. Multiple TRISO-coated particles of increasing geometric complexity are considered. The code's ability to use the same algorithms and models to solve problems of varying dimensionality from 1D through 3D is demonstrated. The code provides rapid solutions of 1D spherically symmetric and 2D axially symmetric models, and its scalable parallel processing capability allows for solutions of large, complex 3D models. Additionally, the flexibility to easily include new physical and material models and straightforward ability to couple to lower length scale simulations makes BISON a powerful tool for simulation of coated-particle fuel. Future code development activities and potential applications are identified.
Multidimensional Multiphysics Simulation of TRISO Particle Fuel
J. D. Hales; R. L. Williamson; S. R. Novascone; D. M. Perez; B. W. Spencer; G. Pastore
2013-11-01
Multidimensional multiphysics analysis of TRISO-coated particle fuel using the BISON finite-element based nuclear fuels code is described. The governing equations and material models applicable to particle fuel and implemented in BISON are outlined. Code verification based on a recent IAEA benchmarking exercise is described, and excellant comparisons are reported. Multiple TRISO-coated particles of increasing geometric complexity are considered. It is shown that the code's ability to perform large-scale parallel computations permits application to complex 3D phenomena while very efficient solutions for either 1D spherically symmetric or 2D axisymmetric geometries are straightforward. Additionally, the flexibility to easily include new physical and material models and uncomplicated ability to couple to lower length scale simulations makes BISON a powerful tool for simulation of coated-particle fuel. Future code development activities and potential applications are identified.
Path integral learning of multidimensional movement trajectories
NASA Astrophysics Data System (ADS)
André, João; Santos, Cristina; Costa, Lino
2013-10-01
This paper explores the use of Path Integral Methods, particularly several variants of the recent Path Integral Policy Improvement (PI2) algorithm in multidimensional movement parametrized policy learning. We rely on Dynamic Movement Primitives (DMPs) to codify discrete and rhythmic trajectories, and apply the PI2-CMA and PIBB methods in the learning of optimal policy parameters, according to different cost functions that inherently encode movement objectives. Additionally we merge both of these variants and propose the PIBB-CMA algorithm, comparing all of them with the vanilla version of PI2. From the obtained results we conclude that PIBB-CMA surpasses all other methods in terms of convergence speed and iterative final cost, which leads to an increased interest in its application to more complex robotic problems.
Biological evolution in a multidimensional fitness landscape.
Saakian, David B; Kirakosyan, Zara; Hu, Chin-Kun
2012-09-01
We considered a multiblock molecular model of biological evolution, in which fitness is a function of the mean types of alleles located at different parts (blocks) of the genome. We formulated an infinite population model with selection and mutation, and calculated the mean fitness. For the case of recombination, we formulated a model with a multidimensional fitness landscape (the dimension of the space is equal to the number of blocks) and derived a theorem about the dynamics of initially narrow distribution. We also considered the case of lethal mutations. We also formulated the finite population version of the model in the case of lethal mutations. Our models, derived for the virus evolution, are interesting also for the statistical mechanics and the Hamilton-Jacobi equation as well.
Multi-dimensional Liquid Chromatography in Proteomics
Zhang, Xiang; Fang, Aiqin; Riley, Catherine P.; Wang, Mu; Regnier, Fred E.; Buck, Charles
2010-01-01
Proteomics is the large-scale study of proteins, particularly their expression, structures and functions. This still-emerging combination of technologies aims to describe and characterize all expressed proteins in a biological system. Because of upper limits on mass detection of mass spectrometers, proteins are usually digested into peptides and the peptides are then separated, identified and quantified from this complex enzymatic digest. The problem in digesting proteins first and then analyzing the peptide cleavage fragments by mass spectrometry is that huge numbers of peptides are generated that overwhelm direct mass spectral analyses. The objective in the liquid chromatography approach to proteomics is to fractionate peptide mixtures to enable and maximize identification and quantification of the component peptides by mass spectrometry. This review will focus on existing multidimensional liquid chromatographic (MDLC) platforms developed for proteomics and their application in combination with other techniques such as stable isotope labeling. We also provide some perspectives on likely future developments. PMID:20363391
Multidimensional Scaling Visualization Using Parametric Entropy
NASA Astrophysics Data System (ADS)
Lopes, António M.; Tenreiro Machado, J. A.; Galhano, Alexandra M.
2015-12-01
This paper studies complex systems using a generalized multidimensional scaling (MDS) technique. Complex systems are characterized by time-series responses, interpreted as a manifestation of their dynamics. Two types of time-series are analyzed, namely 18 stock markets and the gross domestic product per capita of 18 countries. For constructing the MDS charts, indices based on parametric entropies are adopted. Multiparameter entropies allow the variation of the parameters leading to alternative sets of charts. The final MDS maps are then assembled by means of Procrustes’ method that maximizes the fit between the individual charts. Therefore, the proposed method can be interpreted as a generalization to higher dimensions of the standard technique that represents (and discretizes) items by means of single “points” (i.e. zero-dimensional “objects”). The MDS plots, involving one-, two- and three-dimensional “objects”, reveal a good performance in capturing the correlations between data.
The path decomposition expansion and multidimensional tunneling
NASA Astrophysics Data System (ADS)
Auerbach, Assa; Kivelson, S.
This paper consists of two main topics. (i) The path decomposition expansion: a new path integral technique which allows us to break configuration space into disjoint regions and express the dynamics of the full system in terms of its parts. (ii) The application of the PDX and semiclassical methods for solving quantum-mechanical tunneling problems in multidimensions. The result is a conceptually simple, computationally straightforward method for calculating tunneling effects in complicated multidimensional potentials, even in cases where the nature of the states in the classically allowed regions is nontrivial. Algorithms for computing tunneling effects in general classes of problems are obtained.In addition, we present the detailed solutions to three model problems of a tunneling coordinate coupled to a phonon. This enables us to define various well-controlled approximation schemes, which help to reduce the dimensions of complicated tunneling calculations in real physical systems.
Biological evolution in a multidimensional fitness landscape.
Saakian, David B; Kirakosyan, Zara; Hu, Chin-Kun
2012-09-01
We considered a multiblock molecular model of biological evolution, in which fitness is a function of the mean types of alleles located at different parts (blocks) of the genome. We formulated an infinite population model with selection and mutation, and calculated the mean fitness. For the case of recombination, we formulated a model with a multidimensional fitness landscape (the dimension of the space is equal to the number of blocks) and derived a theorem about the dynamics of initially narrow distribution. We also considered the case of lethal mutations. We also formulated the finite population version of the model in the case of lethal mutations. Our models, derived for the virus evolution, are interesting also for the statistical mechanics and the Hamilton-Jacobi equation as well. PMID:23030957
Multidimensional Langevin Modeling of Nonoverdamped Dynamics
NASA Astrophysics Data System (ADS)
Schaudinnus, Norbert; Bastian, Björn; Hegger, Rainer; Stock, Gerhard
2015-07-01
Based on a given time series, data-driven Langevin modeling aims to construct a low-dimensional dynamical model of the underlying system. When dealing with physical data as provided by, e.g., all-atom molecular dynamics simulations, effects due to small damping may be important to correctly describe the statistics (e.g., the energy landscape) and the dynamics (e.g., transition times). To include these effects in a dynamical model, an algorithm that propagates a second-order Langevin scheme is derived, which facilitates the treatment of multidimensional data. Adopting extensive molecular dynamics simulations of a peptide helix, a five-dimensional model is constructed that successfully forecasts the complex structural dynamics of the system. Neglect of small damping effects, on the other hand, is shown to lead to significant errors and inconsistencies.
Coherent Multidimensional Vibrational Spectroscopy of Representative N-Alkanes
NASA Astrophysics Data System (ADS)
Mathew, Nathan A.; Rickard, Mark A.; Kornau, Kathryn M.; Pakoulev, Andrei V.; Block, Stephen B.; Yurs, Lena A.; Wright, John C.
2009-08-01
Mixed frequency/time domain, two color triply vibrationally enhanced (TRIVE) four wave mixing (FWM) spectroscopy is used to study the methyl and methylene modes in octane and dotriacontane. The experiments involve scanning different combinations of the two excitation frequencies, the monochromator frequency, and the two time delays between the three excitation pulses while the remaining variables are fixed. Two dimensional spectra of the methyl and methylene stretching region have weak, asymmetrical diagonal- and cross-peaks when the excitation pulses are temporally overlapped. As the time delays change, the spectra change as new peaks appear and their peak intensity and position change. Combined two-dimensional scans of the excitation frequency and time delay show the changes are caused by relaxation of the initially excited populations to other states that are coupled to the methyl and methylene stretching modes. Two dimensional time delay scans show that the coherence dephasing rates are very fast so fully coherent TRIVE FWM pathways involving multiple quantum coherences are not possible without shorter excitation pulses. Similar experiments involving the methyl and methylene bend and stretching modes identify cross-peaks between these modes and population transfer processes that create cross-peaks. The asymmetric methylene stretch/Fermi resonance band is observed to contain unresolved states that couple differently with the symmetric methylene stretching and scissor modes as well as with lower lying quantum states that are fed by population transfer. The TRIVE FWM data show that the multidimensional spectra are dominated by rapid population transfer within the methyl and methylene stretching modes and to lower quantum states that are coupled to the stretching modes.
A study of multidimensional modeling approaches for data warehouse
NASA Astrophysics Data System (ADS)
Yusof, Sharmila Mat; Sidi, Fatimah; Ibrahim, Hamidah; Affendey, Lilly Suriani
2016-08-01
Data warehouse system is used to support the process of organizational decision making. Hence, the system must extract and integrate information from heterogeneous data sources in order to uncover relevant knowledge suitable for decision making process. However, the development of data warehouse is a difficult and complex process especially in its conceptual design (multidimensional modeling). Thus, there have been various approaches proposed to overcome the difficulty. This study surveys and compares the approaches of multidimensional modeling and highlights the issues, trend and solution proposed to date. The contribution is on the state of the art of the multidimensional modeling design.
Multidimensional displacement vector measurement methods utilizing instantaneous phase.
Sumi, Chikayoshi
2005-01-01
In this report, we propose two new methods for measuring multidimensional displacement vector using instantaneous ultrasound signal phase, i.e., the multidimensional autocorrelation method and the multidimensional Doppler's method. In order to realize high measurement accuracy, respective displacement vector measurement methods are combined with our proposed useful lateral modulation method, i.e., the lateral Gaussian envelop cosine modulation method. We further report measurement accuracy evaluated through simulations. These methods can be applied to tissue strain measurement, blood flow measurement, sonar measurement, etc.
NASA Multidimensional Stirling Convertor Code Developed
NASA Technical Reports Server (NTRS)
Tew, Roy C.; Thieme, Lanny G.
2004-01-01
A high-efficiency Stirling Radioisotope Generator (SRG) for use on potential NASA Space Science missions is being developed by the Department of Energy, Lockheed Martin, Stirling Technology Company, and the NASA Glenn Research Center. These missions may include providing spacecraft onboard electric power for deep space missions or power for unmanned Mars rovers. Glenn is also developing advanced technology for Stirling convertors, aimed at substantially improving the specific power and efficiency of the convertor and the overall power system. Performance and mass improvement goals have been established for second- and third-generation Stirling radioisotope power systems. Multiple efforts are underway to achieve these goals, both in house at Glenn and under various grants and contracts. These efforts include the development of a multidimensional Stirling computational fluid dynamics code, high-temperature materials, advanced controllers, an end-to-end system dynamics model, low-vibration techniques, advanced regenerators, and a lightweight convertor. Under a NASA grant, Cleveland State University (CSU) and its subcontractors, the University of Minnesota (UMN) and Gedeon Associates, have developed a twodimensional computer simulation of a CSUmod Stirling convertor. The CFD-ACE commercial software developed by CFD Research Corp. of Huntsville, Alabama, is being used. The CSUmod is a scaled version of the Stirling Technology Demonstrator Convertor (TDC), which was designed and fabricated by the Stirling Technology Company and is being tested by NASA. The schematic illustrates the structure of this model. Modeled are the fluid-flow and heat-transfer phenomena that occur in the expansion space, the heater, the regenerator, the cooler, the compression space, the surrounding walls, and the moving piston and displacer. In addition, the overall heat transfer, the indicated power, and the efficiency can be calculated. The CSUmod model is being converted to a two
Exploring multidimensional free energy surfaces of peptides
NASA Astrophysics Data System (ADS)
Wang, Yan; Kuczera, Krzysztof
1997-03-01
A new statistical mechanics thermodynamic integration method is presented, enabling exploration of multidimensional conformational free energy surfaces of large flexible molecules. In this approach a single molecular dynamics simulation in which a set of coordinates has been constrained to fixed values yields the free energy gradient with respect to all coordinates in the set. The availability of the multidimensional gradient opens new possibilities for exploration of molecular conformational free energy surfaces, including free energy optimization to locate free energy minima, calculation of higher free energy derivatives, and finding optimal free energy paths between states. Additionally, choosing of all "soft" degrees of freedom as the constrained set leads to accelerated convergence of averages, effectively overcoming the sampling problem of free energy simulations. Two applications of the method are presented: Helical states of model peptides. For model peptides (Ala)n and (Aib)n where n=6,8,10 and Aib is α-methylalanine in vacuum, free energy maps and free energy optimization in φ-ψ space are used to locate free energy minima corresponding to α-, π- and 3_10-helical structures. The stability of the minima is characterized by calculating numerical second derivatives of the free energy. Free energy decomposition is employed to reveal the molecular mechanism for the improved stability of the 3_10h relative to the ah in Aib-containing peptides. DPDPE peptide pre-organization. For the linear form of the opioid peptide DPDPE in aqueous solution, the effective local sampling made possible by fixing all soft degrees of freedom is used to calculate the free energy difference between the open and cyclic-like structures, providing an estimate of the free energy of pre-organizing the peptide for disulfide bond formation. The open structure was found to be more stable by 4.0 ± 0.8 kcal/mol. The cyclic-like conformation was much better solvated than the open
The Measurement of Self-Rated Depression: A Multidimensional Approach.
ERIC Educational Resources Information Center
Bolon, Kevin; Barling, Julian
1980-01-01
Investigates the capacity of the Zung Self-Rating Depression Scale for providing specific multidimensional descriptors of depressive behavior. Ideational, physiological and behavioral depression factors were evident in data from 96 normal, white university student volunteers. (Author/RH)
A multidimensional subdiffusion model: An arbitrage-free market
NASA Astrophysics Data System (ADS)
Li, Guo-Hua; Zhang, Hong; Luo, Mao-Kang
2012-12-01
To capture the subdiffusive characteristics of financial markets, the subordinated process, directed by the inverse α-stale subordinator Sα(t) for 0 < α < 1, has been employed as the model of asset prices. In this article, we introduce a multidimensional subdiffusion model that has a bond and K correlated stocks. The stock price process is a multidimensional subdiffusion process directed by the inverse α-stable subordinator. This model describes the period of stagnation for each stock and the behavior of the dependency between multiple stocks. Moreover, we derive the multidimensional fractional backward Kolmogorov equation for the subordinated process using the Laplace transform technique. Finally, using a martingale approach, we prove that the multidimensional subdiffusion model is arbitrage-free, and also gives an arbitrage-free pricing rule for contingent claims associated with the martingale measure.
The space transformation in the simulation of multidimensional random fields
Christakos, G.
1987-01-01
Space transformations are proposed as a mathematically meaningful and practically comprehensive approach to simulate multidimensional random fields. Within this context the turning bands method of simulation is reconsidered and improved in both the space and frequency domains. ?? 1987.
Preliminary versions of the MATLAB tensor classes for fast algorithm prototyping.
Bader, Brett William; Kolda, Tamara Gibson
2004-07-01
We present the source code for three MATLAB classes for manipulating tensors in order to allow fast algorithm prototyping. A tensor is a multidimensional or Nway array. This is a supplementary report; details on using this code are provided separately in SAND-XXXX.
Central Schemes for Multi-Dimensional Hamilton-Jacobi Equations
NASA Technical Reports Server (NTRS)
Bryson, Steve; Levy, Doron; Biegel, Bryan (Technical Monitor)
2002-01-01
We present new, efficient central schemes for multi-dimensional Hamilton-Jacobi equations. These non-oscillatory, non-staggered schemes are first- and second-order accurate and are designed to scale well with an increasing dimension. Efficiency is obtained by carefully choosing the location of the evolution points and by using a one-dimensional projection step. First-and second-order accuracy is verified for a variety of multi-dimensional, convex and non-convex problems.
Multidimensional Programming Methods for Energy Facility Siting: Alternative Approaches
NASA Technical Reports Server (NTRS)
Solomon, B. D.; Haynes, K. E.
1982-01-01
The use of multidimensional optimization methods in solving power plant siting problems, which are characterized by several conflicting, noncommensurable objectives is addressed. After a discussion of data requirements and exclusionary site screening methods for bounding the decision space, classes of multiobjective and goal programming models are discussed in the context of finite site selection. Advantages and limitations of these approaches are highlighted and the linkage of multidimensional methods with the subjective, behavioral components of the power plant siting process is emphasized.
A multidimensional approach for striping noise compensation in hyperspectral imaging devices
NASA Astrophysics Data System (ADS)
Meza, Pablo; Parra, Francisca; Torres, Sergio N.; Pezoa, Jorge E.; Coelho, Pablo
2011-10-01
Algorithms for striping noise compensation (SNC) for push-broom hyperspectral cameras (PBHCs) are primarily based on image processing techniques. These algorithms rely on the spatial and temporal information available at the readout data; however, they disregard the large amount of spectral information also available at the data. In this paper such flaw has been tackled and a multidimensional approach for SNC is proposed. The main assumption of the proposed approach is the short-term stationary behavior of the spatial, spectral, and temporal input information. This assumption is justified after analyzing the optoelectronic sampling mechanism carried out by PBHCs. Namely, when the wavelength-resolution of hyperspectral cameras is high enough with respect to the target application, the spectral information at neighboring photodetectors in adjacent spectral bands can be regarded as a stationary input. Moreover, when the temporal scanning of hyperspectral information is fast enough, consecutive temporal and spectral data samples can also be regarded as a stationary input at a single photodetector. The strength and applicability of the multidimensional approach presented here is illustrated by compensating for stripping noise real hyperspectral images. To this end, a laboratory prototype, based on a Photonfocus Hurricane hyperspectral camera, has been implemented to acquire data in the range of 400-1000 [nm], at a wavelength resolution of 1.04 [nm]. A mobile platform has been also constructed to simulate and synchronize the scanning procedure of the camera. Finally, an image-processing-based SNC algorithm has been extended yielding an approach that employs all the multidimensional information collected by the camera.
Numerical approaches for multidimensional simulations of stellar explosions
NASA Astrophysics Data System (ADS)
Chen, Ke-Jung; Heger, Alexander; Almgren, Ann S.
2013-11-01
We introduce numerical algorithms for initializing multidimensional simulations of stellar explosions with 1D stellar evolution models. The initial mapping from 1D profiles onto multidimensional grids can generate severe numerical artifacts, one of the most severe of which is the violation of conservation laws for physical quantities. We introduce a numerical scheme for mapping 1D spherically-symmetric data onto multidimensional meshes so that these physical quantities are conserved. We verify our scheme by porting a realistic 1D Lagrangian stellar profile to the new multidimensional Eulerian hydro code CASTRO. Our results show that all important features in the profiles are reproduced on the new grid and that conservation laws are enforced at all resolutions after mapping. We also introduce a numerical scheme for initializing multidimensional supernova simulations with realistic perturbations predicted by 1D stellar evolution models. Instead of seeding 3D stellar profiles with random perturbations, we imprint them with velocity perturbations that reproduce the Kolmogorov energy spectrum expected for highly turbulent convective regions in stars. Our models return Kolmogorov energy spectra and vortex structures like those in turbulent flows before the modes become nonlinear. Finally, we describe approaches to determining the resolution for simulations required to capture fluid instabilities and nuclear burning. Our algorithms are applicable to multidimensional simulations besides stellar explosions that range from astrophysics to cosmology.
Correlative visualization techniques for multidimensional data
NASA Technical Reports Server (NTRS)
Treinish, Lloyd A.; Goettsche, Craig
1989-01-01
Critical to the understanding of data is the ability to provide pictorial or visual representation of those data, particularly in support of correlative data analysis. Despite the advancement of visualization techniques for scientific data over the last several years, there are still significant problems in bringing today's hardware and software technology into the hands of the typical scientist. For example, there are other computer science domains outside of computer graphics that are required to make visualization effective such as data management. Well-defined, flexible mechanisms for data access and management must be combined with rendering algorithms, data transformation, etc. to form a generic visualization pipeline. A generalized approach to data visualization is critical for the correlative analysis of distinct, complex, multidimensional data sets in the space and Earth sciences. Different classes of data representation techniques must be used within such a framework, which can range from simple, static two- and three-dimensional line plots to animation, surface rendering, and volumetric imaging. Static examples of actual data analyses will illustrate the importance of an effective pipeline in data visualization system.
Multidimensional quantum tunneling in the Schwinger effect
NASA Astrophysics Data System (ADS)
Dumlu, Cesim K.
2016-03-01
We study the Schwinger effect, in which the external field having a spatiotemporal profile creates electron-positron pairs via multidimensional quantum tunneling. Our treatment is based on the trace formula for the QED effective action, whose imaginary part is represented by a sum over complex worldline solutions. The worldlines are multiperiodic, and the periods of motion collectively depend on the strength of spatial and temporal inhomogeneity. We argue that the classical action that leads to the correct tunneling amplitude must take into account both the full period, T ˜ and the first fundamental period, T1. In view of this argument we investigate pair production in an exponentially damped sinusoidal field and find that the initial momenta for multiperiodic trajectories lie on parabolic curves, such that on each curve the ratio T ˜/T1 stays uniform. Evaluation of the tunneling amplitude using these trajectories shows that vacuum decay rate is reduced by an order of magnitude, with respect to the purely time-dependent case, due to the presence of magnetic field.
Multi-dimensionally encoded magnetic resonance imaging
Lin, Fa-Hsuan
2013-01-01
Magnetic resonance imaging typically achieves spatial encoding by measuring the projection of a q-dimensional object over q-dimensional spatial bases created by linear spatial encoding magnetic fields (SEMs). Recently, imaging strategies using nonlinear SEMs have demonstrated potential advantages for reconstructing images with higher spatiotemporal resolution and reducing peripheral nerve stimulation. In practice, nonlinear SEMs and linear SEMs can be used jointly to further improve the image reconstruction performance. Here we propose the multi-dimensionally encoded (MDE) MRI to map a q-dimensional object onto a p-dimensional encoding space where p > q. MDE MRI is a theoretical framework linking imaging strategies using linear and nonlinear SEMs. Using a system of eight surface SEM coils with an eight-channel RF coil array, we demonstrate the five-dimensional MDE MRI for a two-dimensional object as a further generalization of PatLoc imaging and O-space imaging. We also present a method of optimizing spatial bases in MDE MRI. Results show that MDE MRI with a higher dimensional encoding space can reconstruct images more efficiently and with a smaller reconstruction error when the k-space sampling distribution and the number of samples are controlled. PMID:22926830
Multi-dimensional cosmology and GUP
Zeynali, K.; Motavalli, H.; Darabi, F. E-mail: f.darabi@azaruniv.edu
2012-12-01
We consider a multidimensional cosmological model with FRW type metric having 4-dimensional space-time and d-dimensional Ricci-flat internal space sectors with a higher dimensional cosmological constant. We study the classical cosmology in commutative and GUP cases and obtain the corresponding exact solutions for negative and positive cosmological constants. It is shown that for negative cosmological constant, the commutative and GUP cases result in finite size universes with smaller size and longer ages, and larger size and shorter age, respectively. For positive cosmological constant, the commutative and GUP cases result in infinite size universes having late time accelerating behavior in good agreement with current observations. The accelerating phase starts in the GUP case sooner than the commutative case. In both commutative and GUP cases, and for both negative and positive cosmological constants, the internal space is stabilized to the sub-Planck size, at least within the present age of the universe. Then, we study the quantum cosmology by deriving the Wheeler-DeWitt equation, and obtain the exact solutions in the commutative case and the perturbative solutions in GUP case, to first order in the GUP small parameter, for both negative and positive cosmological constants. It is shown that good correspondence exists between the classical and quantum solutions.
Proposed empirical gas geothermometer using multidimensional approach
Supranto; Sudjatmiko; Toha, Budianto; Wintolo, Djoko; Alhamid, Idrus
1996-01-24
Several formulas of surface gas geothermometer have been developed to utilize in geothermal exploration, i.e. by D'Amore and Panichi (1980) and by Darling and Talbot (1992). This paper presents an empirical gas geothermometer formula using multidimensional approach. The formula was derived from 37 selected chemical data of the 5 production wells from the Awibengkok Geothermal Volcanic Field in West Java. Seven components, i.e., gas volume percentage, CO_{2}, H_{2}S, CH_{4}, H_{2}, N_{2}, and NH_{3}, from these data are utilize to developed three model equations which represent relationship between temperature and gas compositions. These formulas are then tested by several fumarolic chemical data from Sibual-buali Area (North Sumatera) and from Ringgit Area (South Sumatera). Preliminary result indicated that gas volume percentage, H_{2}S and CO_{2} concentrations have a significant role in term of gas geothermometer. Further verification is currently in progress.
Multidimensional mass spectrometry-based shotgun lipidomics.
Wang, Miao; Han, Xianlin
2014-01-01
Multidimensional mass spectrometry-based shotgun lipidomics (MDMS-SL) has become a foundational analytical technology platform among current lipidomics practices due to its high efficiency, sensitivity, and reproducibility, as well as its broad coverage. This platform has been broadly used to determine the altered content and/or composition of lipid classes, subclasses, and individual molecular species induced by diseases, genetic manipulations, drug treatments, and aging, among others. Herein, we briefly discuss the principles underlying this technology and present a protocol for routine analysis of many of the lipid classes and subclasses covered by MDMS-SL directly from lipid extracts of biological samples. In particular, lipid sample preparation from a variety of biological materials, which is one of the key components of MDMS-SL, is described in detail. The protocol for mass spectrometric analysis can readily be expanded for analysis of other lipid classes not mentioned as long as appropriate sample preparation is conducted, and should aid researchers in the field to better understand and manage the technology for analysis of cellular lipidomes. PMID:25270931
COMMUNITY READINESS AS A MULTIDIMENSIONAL CONSTRUCT
Chilenski, Sarah M.; Greenberg, Mark T.; Feinberg, Mark E.
2008-01-01
Both the organizational studies literature and the community psychology literature discuss the importance of readiness when implementing change. Although each area emphasizes different characteristics, several common themes are present within the literature. The current study integrates and applies organizational and community psychology literature in evaluating community readiness in the context of a school–community–university collaborative prevention model. Results demonstrate (a) that there is substantial agreement between members of community prevention teams on the level of readiness of a community; (b) that readiness is a cohesive, but multidimensional, construct related to hypothesized community and individual characteristics; and (c) that there is small to moderate agreement between members of prevention teams and their “agency directors.” These results support the notion that clear “theories of change” need to be formulated before deciding how to assess community readiness, as assessments will vary due to several factors: the type of respondent, the level in which analyses are conducted, and the specific community domain (i.e., school, workplace collaboration, collaboration experience) investigated. PMID:18714368
The Path Decomposition Expansion and Multidimensional Tunneling
NASA Astrophysics Data System (ADS)
Auerbach, Assa
The dissertation consists of two main topics. (a) The Path Decomposition Expansion (PDX): A new path integral technique which allows us to break configuration space into disjoint regions, and express the dynamics of the full system in terms of its parts. (b) The application of the PDX and semiclassical methods for solving quantum -mechanical problems in multidimensions. The result is a conceptually simple, computationally straightforward method for calculating tunneling effects in complicated multidimensional potentials, even in cases where the nature of the states in the classically allowed regions in nontrivial. Algorithms for computing tunneling effects in general classes of problems are obtained. The detailed solutions to several model problems are presented. These enable us to define various well -controlled approximation schemes, which help to reduce the dimensions of complicated tunneling calculations in real physical systems. The dramatic effects of transverse fluctuations on the asymptotic behavior of the groundstate tunnel-splitting are studied also in potentials with non -quadratic minima where standard instanton techniques fail. The power of the PDX is demonstrated by a calculation of the optical absorption coefficient of trans-polyacetylene where large amplitude (non-perturbative) quantum fluctuations of the lattice play an important role in determining the sub-gap absorption tail. Good agreement with experimental data is found, and suggestions for further measurements in this regime are made.
Multidimensional In Vivo Hazard Assessment Using Zebrafish
Tanguay, Robert L.
2014-01-01
There are tens of thousands of man-made chemicals in the environment; the inherent safety of most of these chemicals is not known. Relevant biological platforms and new computational tools are needed to prioritize testing of chemicals with limited human health hazard information. We describe an experimental design for high-throughput characterization of multidimensional in vivo effects with the power to evaluate trends relating to commonly cited chemical predictors. We evaluated all 1060 unique U.S. EPA ToxCast phase 1 and 2 compounds using the embryonic zebrafish and found that 487 induced significant adverse biological responses. The utilization of 18 simultaneously measured endpoints means that the entire system serves as a robust biological sensor for chemical hazard. The experimental design enabled us to describe global patterns of variation across tested compounds, evaluate the concordance of the available in vitro and in vivo phase 1 data with this study, highlight specific mechanisms/value-added/novel biology related to notochord development, and demonstrate that the developmental zebrafish detects adverse responses that would be missed by less comprehensive testing strategies. PMID:24136191
Multidimensional thermal-chemical cookoff modeling
Baer, M.R.; Gross, R.J.; Gartling, D.K.; Hobbs, M.L.
1994-08-01
Multidimensional thermal/chemical modeling is an essential step in the development of a predictive capability for cookoff of energetic materials in systems subjected to abnormal thermal environments. COYOTE II is a state-of-the-art two- and three-dimensional finite element code for the solution of heat conduction problems including surface-to-surface thermal radiation heat transfer and decomposition chemistry. Multistep finite rate chemistry is incorporated into COYOTE II using an operator-splitting methodology; rate equations are solved element-by-element with a modified matrix-free stiff solver, CHEMEQ. COYOTE II is purposely designed with a user-oriented input structure compatible with the database, the pre-processing mesh generation, and the post-processing tools for data visualization shared with other engineering analysis codes available at Sandia National Laboratories. As demonstrated in a companion paper, decomposition during cookoff in a confined or semi-confined system leads to significant mechanical behavior. Although mechanical effect are not presently considered in COYOTE II, the formalism for including mechanics in multidimensions is under development.
Multidimensional View of the Bacterial Cytoskeleton
Celler, Katherine; Koning, Roman I.; Koster, Abraham J.
2013-01-01
The perspective of the cytoskeleton as a feature unique to eukaryotic organisms was overturned when homologs of the eukaryotic cytoskeletal elements were identified in prokaryotes and implicated in major cell functions, including growth, morphogenesis, cell division, DNA partitioning, and cell motility. FtsZ and MreB were the first identified homologs of tubulin and actin, respectively, followed by the discovery of crescentin as an intermediate filament-like protein. In addition, new elements were identified which have no apparent eukaryotic counterparts, such as the deviant Walker A-type ATPases, bactofilins, and several novel elements recently identified in streptomycetes, highlighting the unsuspected complexity of cytostructural components in bacteria. In vivo multidimensional fluorescence microscopy has demonstrated the dynamics of the bacterial intracellular world, and yet we are only starting to understand the role of cytoskeletal elements. Elucidating structure-function relationships remains challenging, because core cytoskeletal protein motifs show remarkable plasticity, with one element often performing various functions and one function being performed by several types of elements. Structural imaging techniques, such as cryo-electron tomography in combination with advanced light microscopy, are providing the missing links and enabling scientists to answer many outstanding questions regarding prokaryotic cellular architecture. Here we review the recent advances made toward understanding the different roles of cytoskeletal proteins in bacteria, with particular emphasis on modern imaging approaches. PMID:23417493
Multidimensional multiphysics simulation of nuclear fuel behavior
NASA Astrophysics Data System (ADS)
Williamson, R. L.; Hales, J. D.; Novascone, S. R.; Tonks, M. R.; Gaston, D. R.; Permann, C. J.; Andrs, D.; Martineau, R. C.
2012-04-01
Nuclear fuel operates in an environment that induces complex multiphysics phenomena, occurring over distances ranging from inter-atomic spacing to meters, and times scales ranging from microseconds to years. This multiphysics behavior is often tightly coupled and many important aspects are inherently multidimensional. Most current fuel modeling codes employ loose multiphysics coupling and are restricted to 2D axisymmetric or 1.5D approximations. This paper describes a new modeling tool able to simulate coupled multiphysics and multiscale fuel behavior, for either 2D axisymmetric or 3D geometries. Specific fuel analysis capabilities currently implemented in this tool are described, followed by a set of demonstration problems which include a 10-pellet light water reactor fuel rodlet, three-dimensional analysis of pellet clad mechanical interaction in the vicinity of a defective fuel pellet, coupled heat transfer and fission product diffusion in a TRISO-coated fuel particle, a demonstration of the ability to couple to lower-length scale models to account for material property variation with microstructural evolution, and a demonstration of the tool's ability to efficiently solve very large and complex problems using massively-parallel computing. A final section describes an early validation exercise, comparing simulation results to a light water reactor fuel rod experiment.
A lock-free priority queue design based on multi-dimensional linked lists
Dechev, Damian; Zhang, Deli
2015-04-03
The throughput of concurrent priority queues is pivotal to multiprocessor applications such as discrete event simulation, best-first search and task scheduling. Existing lock-free priority queues are mostly based on skiplists, which probabilistically create shortcuts in an ordered list for fast insertion of elements. The use of skiplists eliminates the need of global rebalancing in balanced search trees and ensures logarithmic sequential search time on average, but the worst-case performance is linear with respect to the input size. In this paper, we propose a quiescently consistent lock-free priority queue based on a multi-dimensional list that guarantees worst-case search time of O(logN) for key universe of size N. The novel multi-dimensional list (MDList) is composed of nodes that contain multiple links to child nodes arranged by their dimensionality. The insertion operation works by first injectively mapping the scalar key to a high-dimensional vector, then uniquely locating the target position by using the vector as coordinates. Nodes in MDList are ordered by their coordinate prefixes and the ordering property of the data structure is readily maintained during insertion without rebalancing nor randomization. Furthermore, in our experimental evaluation using a micro-benchmark, our priority queue achieves an average of 50% speedup over the state of the art approaches under high concurrency.
A lock-free priority queue design based on multi-dimensional linked lists
Dechev, Damian; Zhang, Deli
2015-04-03
The throughput of concurrent priority queues is pivotal to multiprocessor applications such as discrete event simulation, best-first search and task scheduling. Existing lock-free priority queues are mostly based on skiplists, which probabilistically create shortcuts in an ordered list for fast insertion of elements. The use of skiplists eliminates the need of global rebalancing in balanced search trees and ensures logarithmic sequential search time on average, but the worst-case performance is linear with respect to the input size. In this paper, we propose a quiescently consistent lock-free priority queue based on a multi-dimensional list that guarantees worst-case search time of O(logN)more » for key universe of size N. The novel multi-dimensional list (MDList) is composed of nodes that contain multiple links to child nodes arranged by their dimensionality. The insertion operation works by first injectively mapping the scalar key to a high-dimensional vector, then uniquely locating the target position by using the vector as coordinates. Nodes in MDList are ordered by their coordinate prefixes and the ordering property of the data structure is readily maintained during insertion without rebalancing nor randomization. Furthermore, in our experimental evaluation using a micro-benchmark, our priority queue achieves an average of 50% speedup over the state of the art approaches under high concurrency.« less
FAST: FAST Analysis of Sequences Toolbox
Lawrence, Travis J.; Kauffman, Kyle T.; Amrine, Katherine C. H.; Carper, Dana L.; Lee, Raymond S.; Becich, Peter J.; Canales, Claudia J.; Ardell, David H.
2015-01-01
FAST (FAST Analysis of Sequences Toolbox) provides simple, powerful open source command-line tools to filter, transform, annotate and analyze biological sequence data. Modeled after the GNU (GNU's Not Unix) Textutils such as grep, cut, and tr, FAST tools such as fasgrep, fascut, and fastr make it easy to rapidly prototype expressive bioinformatic workflows in a compact and generic command vocabulary. Compact combinatorial encoding of data workflows with FAST commands can simplify the documentation and reproducibility of bioinformatic protocols, supporting better transparency in biological data science. Interface self-consistency and conformity with conventions of GNU, Matlab, Perl, BioPerl, R, and GenBank help make FAST easy and rewarding to learn. FAST automates numerical, taxonomic, and text-based sorting, selection and transformation of sequence records and alignment sites based on content, index ranges, descriptive tags, annotated features, and in-line calculated analytics, including composition and codon usage. Automated content- and feature-based extraction of sites and support for molecular population genetic statistics make FAST useful for molecular evolutionary analysis. FAST is portable, easy to install and secure thanks to the relative maturity of its Perl and BioPerl foundations, with stable releases posted to CPAN. Development as well as a publicly accessible Cookbook and Wiki are available on the FAST GitHub repository at https://github.com/tlawrence3/FAST. The default data exchange format in FAST is Multi-FastA (specifically, a restriction of BioPerl FastA format). Sanger and Illumina 1.8+ FastQ formatted files are also supported. FAST makes it easier for non-programmer biologists to interactively investigate and control biological data at the speed of thought. PMID:26042145
FAST: FAST Analysis of Sequences Toolbox.
Lawrence, Travis J; Kauffman, Kyle T; Amrine, Katherine C H; Carper, Dana L; Lee, Raymond S; Becich, Peter J; Canales, Claudia J; Ardell, David H
2015-01-01
FAST (FAST Analysis of Sequences Toolbox) provides simple, powerful open source command-line tools to filter, transform, annotate and analyze biological sequence data. Modeled after the GNU (GNU's Not Unix) Textutils such as grep, cut, and tr, FAST tools such as fasgrep, fascut, and fastr make it easy to rapidly prototype expressive bioinformatic workflows in a compact and generic command vocabulary. Compact combinatorial encoding of data workflows with FAST commands can simplify the documentation and reproducibility of bioinformatic protocols, supporting better transparency in biological data science. Interface self-consistency and conformity with conventions of GNU, Matlab, Perl, BioPerl, R, and GenBank help make FAST easy and rewarding to learn. FAST automates numerical, taxonomic, and text-based sorting, selection and transformation of sequence records and alignment sites based on content, index ranges, descriptive tags, annotated features, and in-line calculated analytics, including composition and codon usage. Automated content- and feature-based extraction of sites and support for molecular population genetic statistics make FAST useful for molecular evolutionary analysis. FAST is portable, easy to install and secure thanks to the relative maturity of its Perl and BioPerl foundations, with stable releases posted to CPAN. Development as well as a publicly accessible Cookbook and Wiki are available on the FAST GitHub repository at https://github.com/tlawrence3/FAST. The default data exchange format in FAST is Multi-FastA (specifically, a restriction of BioPerl FastA format). Sanger and Illumina 1.8+ FastQ formatted files are also supported. FAST makes it easier for non-programmer biologists to interactively investigate and control biological data at the speed of thought.
Information theoretic approaches to multidimensional neural computations
NASA Astrophysics Data System (ADS)
Fitzgerald, Jeffrey D.
Many systems in nature process information by transforming inputs from their environments into observable output states. These systems are often difficult to study because they are performing computations on multidimensional inputs with many degrees of freedom using highly nonlinear functions. The work presented in this dissertation deals with some of the issues involved with characterizing real-world input/output systems and understanding the properties of idealized systems using information theoretic methods. Using the principle of maximum entropy, a family of models are created that are consistent with certain measurable correlations from an input/output dataset but are maximally unbiased in all other respects, thereby eliminating all unjustified assumptions about the computation. In certain cases, including spiking neurons, we show that these models also minimize the mutual information. This property gives one the advantage of being able to identify the relevant input/output statistics by calculating their information content. We argue that these maximum entropy models provide a much needed quantitative framework for characterizing and understanding sensory processing neurons that are selective for multiple stimulus features. To demonstrate their usefulness, these ideas are applied to neural recordings from macaque retina and thalamus. These neurons, which primarily respond to two stimulus features, are shown to be well described using only first and second order statistics, indicating that their firing rates encode information about stimulus correlations. In addition to modeling multi-feature computations in the relevant feature space, we also show that maximum entropy models are capable of discovering the relevant feature space themselves. This technique overcomes the disadvantages of two commonly used dimensionality reduction methods and is explored using several simulated neurons, as well as retinal and thalamic recordings. Finally, we ask how neurons in a
Multidimensional coherent spectroscopy of a semiconductor microcavity
NASA Astrophysics Data System (ADS)
Wilmer, Brian L.; Passmann, Felix; Gehl, Michael; Khitrova, Galina; Bristow, Alan D.
2016-03-01
Multidimensional coherent spectroscopy maps the detuning dependence of the upper (UP) and lower (LP) excitonpolariton branches1 in a wedged microcavity with a single InGaAs quantum well at 5 K. Features on the diagonal correspond to intra-action coherences of the UP and LP branches. Off-diagonal peaks are interaction coherences between the UP and LP branches. With increasing detuning (Δ), all peaks move to higher energy, the exciton-like (EEX) and cavity-like (Eγ) modes swap position and have maximum intensity near the anti-crossing at Δ=0. An isolated biexciton (B) is only seen at Δ<0, separated by a binding energy of approximately 2 meV. For Δ>0, the spectral weight of the off-diagonal features swap, as the LP and B come into resonance. This indicates that the off-diagonal features are sensitive to the interactions including two-quantum contributions and that a situation similar to a Feshbach resonance exists.2 Polarization of two-quantum contributions show spin sensitive two-polariton and new biexciton correlations. The latter likely influence the Feshbach resonance between biexcitons and two-polariton states. The two-quantum signatures also demonstate that biexcitons perturb the light-matter coupling in the microcavity to reduce the mixed two-polariton contributions. Detuning dependence of zero-quantum contributions show Raman-like coherences that are enhanced near zero detuning. Asymmetry of the Raman coherences are indicative of many-body interactions, which also grow stronger as the light-matter interactions are enhanced near zero deuning.
Multidimensional radiative effects in supercritical shocks
NASA Astrophysics Data System (ADS)
Leygnac, S.; Lanz, T.; Stehlé, C.; Michaut, C.; Korĉáková, D.
Recent radiative shocks experiments performed on the LULI laser at Ecole Polytechnique in France (Fleury et al., Lasers and Particle Beams 20, 263, 2002) put in evidence a supercritical shock wave in a xenon gas cell. The structure of these shocks is quite similar to those of accretion shock wave in the case of stellar formation, as indicated in Stehlé and Chieze (SF2A - Paris proceedings, 2002). Some points require further studies like the contribution of the gas excitation/ionization energy to the compression ratio and the understanding of the discrepancy, which was noted between the velocity of the radiative precursor in the experiment and in the 1D simulation. Thus, to understand the physics of the radiative shock waves, the academic case of the stationary shock is particularly interesting. We have thus studied the structure of a radiative shock wave which propagates in an ionized gas. We study the extended Rankine Hugoniot equations in various media with inclusion of radiation pressure and energy and study also the extension of the radiative precursor in the diffusion approximation. We also study the equations of multidimensional radiative transfer for a snapshot of the experimental shock in xenon in order to quantify the radiative losses in the finite experimental cell. This academic approach will help to improve the knowledge of the physical processes which take place in radiative shocks of astrophysical interest, like in the birth and death of stars, and prepare ourselves to define appropriate experiments on future high power lasers like LIL and LMJ in Bordeaux.
Multidimensional spectroscopy with entangled light: loop vs ladder delay scanning protocols
Dorfman, Konstantin E.; Mukamel, Shaul
2015-01-01
Multidimensional optical signals are commonly recorded by varying the delays between time ordered pulses. These control the evolution of the density matrix and are described by ladder diagrams. We propose a new non-time-ordered protocol based on following the time evolution of the wavefunction and described by loop diagrams. The time variables in this protocol allow to observe different types of resonances and reveal information about intraband dephasing not readily available by time ordered techniques. The time variables involved in this protocol become coupled when using entangled light, which provides high selectivity and background free measurement of the various resonances. Entangled light can resolve certain states even when strong background due to fast dephasing suppresses the resonant features when probed by classical light. PMID:26709344
Reducing acquisition times in multidimensional NMR with a time-optimized Fourier encoding algorithm
Zhang, Zhiyong; Smith, Pieter E. S.; Frydman, Lucio
2014-11-21
Speeding up the acquisition of multidimensional nuclear magnetic resonance (NMR) spectra is an important topic in contemporary NMR, with central roles in high-throughput investigations and analyses of marginally stable samples. A variety of fast NMR techniques have been developed, including methods based on non-uniform sampling and Hadamard encoding, that overcome the long sampling times inherent to schemes based on fast-Fourier-transform (FFT) methods. Here, we explore the potential of an alternative fast acquisition method that leverages a priori knowledge, to tailor polychromatic pulses and customized time delays for an efficient Fourier encoding of the indirect domain of an NMR experiment. By porting the encoding of the indirect-domain to the excitation process, this strategy avoids potential artifacts associated with non-uniform sampling schemes and uses a minimum number of scans equal to the number of resonances present in the indirect dimension. An added convenience is afforded by the fact that a usual 2D FFT can be used to process the generated data. Acquisitions of 2D heteronuclear correlation NMR spectra on quinine and on the anti-inflammatory drug isobutyl propionic phenolic acid illustrate the new method's performance. This method can be readily automated to deal with complex samples such as those occurring in metabolomics, in in-cell as well as in in vivo NMR applications, where speed and temporal stability are often primary concerns.
Reducing acquisition times in multidimensional NMR with a time-optimized Fourier encoding algorithm.
Zhang, Zhiyong; Smith, Pieter E S; Frydman, Lucio
2014-11-21
Speeding up the acquisition of multidimensional nuclear magnetic resonance (NMR) spectra is an important topic in contemporary NMR, with central roles in high-throughput investigations and analyses of marginally stable samples. A variety of fast NMR techniques have been developed, including methods based on non-uniform sampling and Hadamard encoding, that overcome the long sampling times inherent to schemes based on fast-Fourier-transform (FFT) methods. Here, we explore the potential of an alternative fast acquisition method that leverages a priori knowledge, to tailor polychromatic pulses and customized time delays for an efficient Fourier encoding of the indirect domain of an NMR experiment. By porting the encoding of the indirect-domain to the excitation process, this strategy avoids potential artifacts associated with non-uniform sampling schemes and uses a minimum number of scans equal to the number of resonances present in the indirect dimension. An added convenience is afforded by the fact that a usual 2D FFT can be used to process the generated data. Acquisitions of 2D heteronuclear correlation NMR spectra on quinine and on the anti-inflammatory drug isobutyl propionic phenolic acid illustrate the new method's performance. This method can be readily automated to deal with complex samples such as those occurring in metabolomics, in in-cell as well as in in vivo NMR applications, where speed and temporal stability are often primary concerns. PMID:25416883
Reducing acquisition times in multidimensional NMR with a time-optimized Fourier encoding algorithm
Zhang, Zhiyong; Frydman, Lucio
2014-01-01
Speeding up the acquisition of multidimensional nuclear magnetic resonance (NMR) spectra is an important topic in contemporary NMR, with central roles in high-throughput investigations and analyses of marginally stable samples. A variety of fast NMR techniques have been developed, including methods based on non-uniform sampling and Hadamard encoding, that overcome the long sampling times inherent to schemes based on fast-Fourier-transform (FFT) methods. Here, we explore the potential of an alternative fast acquisition method that leverages a priori knowledge, to tailor polychromatic pulses and customized time delays for an efficient Fourier encoding of the indirect domain of an NMR experiment. By porting the encoding of the indirect-domain to the excitation process, this strategy avoids potential artifacts associated with non-uniform sampling schemes and uses a minimum number of scans equal to the number of resonances present in the indirect dimension. An added convenience is afforded by the fact that a usual 2D FFT can be used to process the generated data. Acquisitions of 2D heteronuclear correlation NMR spectra on quinine and on the anti-inflammatory drug isobutyl propionic phenolic acid illustrate the new method's performance. This method can be readily automated to deal with complex samples such as those occurring in metabolomics, in in-cell as well as in in vivo NMR applications, where speed and temporal stability are often primary concerns. PMID:25416883
Wu, Kesheng
2007-08-02
An index in a database system is a data structure that utilizes redundant information about the base data to speed up common searching and retrieval operations. Most commonly used indexes are variants of B-trees, such as B+-tree and B*-tree. FastBit implements a set of alternative indexes call compressed bitmap indexes. Compared with B-tree variants, these indexes provide very efficient searching and retrieval operations by sacrificing the efficiency of updating the indexes after the modification of an individual record. In addition to the well-known strengths of bitmap indexes, FastBit has a special strength stemming from the bitmap compression scheme used. The compression method is called the Word-Aligned Hybrid (WAH) code. It reduces the bitmap indexes to reasonable sizes and at the same time allows very efficient bitwise logical operations directly on the compressed bitmaps. Compared with the well-known compression methods such as LZ77 and Byte-aligned Bitmap code (BBC), WAH sacrifices some space efficiency for a significant improvement in operational efficiency. Since the bitwise logical operations are the most important operations needed to answer queries, using WAH compression has been shown to answer queries significantly faster than using other compression schemes. Theoretical analyses showed that WAH compressed bitmap indexes are optimal for one-dimensional range queries. Only the most efficient indexing schemes such as B+-tree and B*-tree have this optimality property. However, bitmap indexes are superior because they can efficiently answer multi-dimensional range queries by combining the answers to one-dimensional queries.
[Cutaneous lupus erythematosus, a multidimensional entity].
Méndez-Flores, Silvia; Tinoco-Fragoso, Fátima; Hernández-Molina, Gabriela
2015-01-01
Skin lesions caused by systemic lupus erythematosus are among the most frequent manifestations of this disease. These lesions show great variability in both their clinical and histological expression, making their understanding and study difficult. Patients presenting with cutaneous lupus do not necessarily have serious systemic complications, but they do have significant morbidity from impact on quality of life given the extent of the lesions, chronic tendency, and the risk of scarring; hence the importance of establishing a fast and effective treatment. This paper addresses the different varieties of specific injuries attributed to lupus erythematosus, correlation with systemic activity, quality of life, and the treatments available.
Graphical Representation of Proximity Measures for Multidimensional Data
Zand, Martin S.; Wang, Jiong; Hilchey, Shannon
2015-01-01
We describe the use of classical and metric multidimensional scaling methods for graphical representation of the proximity between collections of data consisting of cases characterized by multidimensional attributes. These methods can preserve metric differences between cases, while allowing for dimensional reduction and projection to two or three dimensions ideal for data exploration. We demonstrate these methods with three datasets for: (i) the immunological similarity of influenza proteins measured by a multidimensional assay; (ii) influenza protein sequence similarity; and (iii) reconstruction of airport-relative locations from paired proximity measurements. These examples highlight the use of proximity matrices, eigenvalues, eigenvectors, and linear and nonlinear mappings using numerical minimization methods. Some considerations and caveats for each method are also discussed, and compact Mathematica programs are provided. PMID:26692757
The acquisition of multidimensional NMR spectra within a single scan
Frydman, Lucio; Scherf, Tali; Lupulescu, Adonis
2002-01-01
A scheme enabling the complete sampling of multidimensional NMR domains within a single continuous acquisition is introduced and exemplified. Provided that an analyte's signal is sufficiently strong, the acquisition time of multidimensional NMR experiments can thus be shortened by orders of magnitude. This could enable the characterization of transient events such as proteins folding, 2D NMR experiments on samples being chromatographed, bring the duration of higher dimensional experiments (e.g., 4D NMR) into the lifetime of most proteins under physiological conditions, and facilitate the incorporation of spectroscopic 2D sequences into in vivo imaging investigations. The protocol is compatible with existing multidimensional pulse sequences and can be implemented by using conventional hardware; its performance is exemplified here with a variety of homonuclear 2D NMR acquisitions. PMID:12461169
Formalism for Hypercomplex Multidimensional NMR Employing Partial-Component Subsampling
Schuyler, Adam D; Maciejewski, Mark W; Stern, Alan S; Hoch, Jeffrey C
2012-01-01
Multidimensional NMR spectroscopy typically employs phase-sensitive detection, which results in hypercomplex data (and spectra) when utilized in more than one dimension. Nonuniform sampling approaches have become commonplace in multidimensional NMR, enabling dramatic reductions in experiment time, increases in sensitivity and/or increases in resolution. In order to utilize nonuniform sampling optimally, it is necessary to characterize the relationship between the spectrum of a uniformly sampled data set and the spectrum of a subsampled data set. In this work we construct an algebra of hypercomplex numbers suitable for representing multidimensional NMR data along with partial-component nonuniform sampling (i.e. the hypercomplex components of data points are subsampled). This formalism leads to a modified DFT–convolution relationship involving a partial-component, hypercomplex point-spread function set. The framework presented here is essential for the continued development and appropriate characterization of partial-component nonuniform sampling. PMID:23246651
Quantum and Multidimensional Explanations in a Neurobiological Context of Mind.
Korf, Jakob
2015-08-01
This article examines the possible relevance of physical-mathematical multidimensional or quantum concepts aiming at understanding the (human) mind in a neurobiological context. Some typical features of the quantum and multidimensional concepts are briefly introduced, including entanglement, superposition, holonomic, and quantum field theories. Next, we consider neurobiological principles, such as the brain and its emerging (physical) mind, evolutionary and ontological origins, entropy, syntropy/neg-entropy, causation, and brain energy metabolism. In many biological processes, including biochemical conversions, protein folding, and sensory perception, the ubiquitous involvement of quantum mechanisms is well recognized. Quantum and multidimensional approaches might be expected to help describe and model both brain and mental processes, but an understanding of their direct involvement in mental activity, that is, without mediation by molecular processes, remains elusive. More work has to be done to bridge the gap between current neurobiological and physical-mathematical concepts with their associated quantum-mind theories.
Ultrafast Multidimensional Laplace NMR Using a Single-Sided Magnet.
King, Jared N; Lee, Vanessa J; Ahola, Susanna; Telkki, Ville-Veikko; Meldrum, Tyler
2016-04-11
Laplace NMR (LNMR) consists of relaxation and diffusion measurements providing detailed information about molecular motion and interaction. Here we demonstrate that ultrafast single- and multidimensional LNMR experiments, based on spatial encoding, are viable with low-field, single-sided magnets with an inhomogeneous magnetic field. This approach shortens the experiment time by one to two orders of magnitude relative to traditional experiments, and increases the sensitivity per unit time by a factor of three. The reduction of time required to collect multidimensional data opens significant prospects for mobile chemical analysis using NMR. Particularly tantalizing is future use of hyperpolarization to increase sensitivity by orders of magnitude, allowed by single-scan approach.
Measurement Error, Multidimensionality, and Scale Shrinkage: A Reply to Yen and Burket.
ERIC Educational Resources Information Center
Camilli, Gregory
1999-01-01
Yen and Burket suggested that shrinkage in vertical equating cannot be understood apart from multidimensionality. Reviews research on reliability, multidimensionality, and scale shrinkage, and explores issues of practical importance to educators. (SLD)
MATLAB tensor classes for fast algorithm prototyping.
Bader, Brett William; Kolda, Tamara Gibson
2004-10-01
Tensors (also known as mutidimensional arrays or N-way arrays) are used in a variety of applications ranging from chemometrics to psychometrics. We describe four MATLAB classes for tensor manipulations that can be used for fast algorithm prototyping. The tensor class extends the functionality of MATLAB's multidimensional arrays by supporting additional operations such as tensor multiplication. The tensor as matrix class supports the 'matricization' of a tensor, i.e., the conversion of a tensor to a matrix (and vice versa), a commonly used operation in many algorithms. Two additional classes represent tensors stored in decomposed formats: cp tensor and tucker tensor. We descibe all of these classes and then demonstrate their use by showing how to implement several tensor algorithms that have appeared in the literature.
Fast Whole-Engine Stirling Analysis
NASA Technical Reports Server (NTRS)
Dyson, Rodger W.; Wilson, Scott D.; Tew, Roy C.; Demko, Rikako
2007-01-01
An experimentally validated approach is described for fast axisymmetric Stirling engine simulations. These simulations include the entire displacer interior and demonstrate it is possible to model a complete engine cycle in less than an hour. The focus of this effort was to demonstrate it is possible to produce useful Stirling engine performance results in a time-frame short enough to impact design decisions. The combination of utilizing the latest 64-bit Opteron computer processors, fiber-optical Myrinet communications, dynamic meshing, and across zone partitioning has enabled solution times at least 240 times faster than previous attempts at simulating the axisymmetric Stirling engine. A comparison of the multidimensional results, calibrated one-dimensional results, and known experimental results is shown. This preliminary comparison demonstrates that axisymmetric simulations can be very accurate, but more work remains to improve the simulations through such means as modifying the thermal equilibrium regenerator models, adding fluid-structure interactions, including radiation effects, and incorporating mechanodynamics.
Fast Whole-Engine Stirling Analysis
NASA Technical Reports Server (NTRS)
Dyson, Rodger W.; Wilson, Scott D.; Tew, Roy C.; Demko, Rikako
2005-01-01
An experimentally validated approach is described for fast axisymmetric Stirling engine simulations. These simulations include the entire displacer interior and demonstrate it is possible to model a complete engine cycle in less than an hour. The focus of this effort was to demonstrate it is possible to produce useful Stirling engine performance results in a time-frame short enough to impact design decisions. The combination of utilizing the latest 64-bit Opteron computer processors, fiber-optical Myrinet communications, dynamic meshing, and across zone partitioning has enabled solution times at least 240 times faster than previous attempts at simulating the axisymmetric Stirling engine. A comparison of the multidimensional results, calibrated one-dimensional results, and known experimental results is shown. This preliminary comparison demonstrates that axisymmetric simulations can be very accurate, but more work remains to improve the simulations through such means as modifying the thermal equilibrium regenerator models, adding fluid-structure interactions, including radiation effects, and incorporating mechanodynamics.
On the clustering of multidimensional pictorial data
NASA Technical Reports Server (NTRS)
Bryant, J. D. (Principal Investigator)
1979-01-01
Obvious approaches to reducing the cost (in computer resources) of applying current clustering techniques to the problem of remote sensing are discussed. The use of spatial information in finding fields and in classifying mixture pixels is examined, and the AMOEBA clustering program is described. Internally, a pattern recognition program, from without, AMOEBA appears to be an unsupervised clustering program. It is fast and automatic. No choices (such as arbitrary thresholds to set split/combine sequences) need be made. The problem of finding the number of clusters is solved automatically. At the conclusion of the program, all points in the scene are classified; however, a provision is included for a reject classification of some points which, within the theoretical framework, cannot rationally be assigned to any cluster.
Laser–plasma interactions for fast ignition
Kemp, A. J.; Fiuza, F.; Debayle, A.; Johzaki, T.; Mori, W. B.; Patel, P. K.; Sentoku, Y.; Silva, L. O.
2014-04-17
In the electron-driven fast-ignition approach to inertial confinement fusion, petawatt laser pulses are required to generate MeV electrons that deposit several tens of kilojoules in the compressed core of an imploded DT shell. We review recent progress in the understanding of intense laser- plasma interactions (LPI) relevant to fast ignition. Increases in computational and modeling capabilities, as well as algorithmic developments have led to enhancement in our ability to perform multidimensional particle-in-cell (PIC) simulations of LPI at relevant scales. We discuss the physics of the interaction in terms of laser absorption fraction, the laser-generated electron spectra, divergence, and their temporalmore » evolution. Scaling with irradiation conditions such as laser intensity, f-number and wavelength are considered, as well as the dependence on plasma parameters. Different numerical modeling approaches and configurations are addressed, providing an overview of the modeling capabilities and limitations. In addition, we discuss the comparison of simulation results with experimental observables. In particular, we address the question of surrogacy of today's experiments for the full-scale fast ignition problem.« less
Laser–plasma interactions for fast ignition
Kemp, A. J.; Fiuza, F.; Debayle, A.; Johzaki, T.; Mori, W. B.; Patel, P. K.; Sentoku, Y.; Silva, L. O.
2014-04-17
In the electron-driven fast-ignition approach to inertial confinement fusion, petawatt laser pulses are required to generate MeV electrons that deposit several tens of kilojoules in the compressed core of an imploded DT shell. We review recent progress in the understanding of intense laser- plasma interactions (LPI) relevant to fast ignition. Increases in computational and modeling capabilities, as well as algorithmic developments have led to enhancement in our ability to perform multidimensional particle-in-cell (PIC) simulations of LPI at relevant scales. We discuss the physics of the interaction in terms of laser absorption fraction, the laser-generated electron spectra, divergence, and their temporal evolution. Scaling with irradiation conditions such as laser intensity, f-number and wavelength are considered, as well as the dependence on plasma parameters. Different numerical modeling approaches and configurations are addressed, providing an overview of the modeling capabilities and limitations. In addition, we discuss the comparison of simulation results with experimental observables. In particular, we address the question of surrogacy of today's experiments for the full-scale fast ignition problem.
Best Design for Multidimensional Computerized Adaptive Testing with the Bifactor Model
ERIC Educational Resources Information Center
Seo, Dong Gi; Weiss, David J.
2015-01-01
Most computerized adaptive tests (CATs) have been studied using the framework of unidimensional item response theory. However, many psychological variables are multidimensional and might benefit from using a multidimensional approach to CATs. This study investigated the accuracy, fidelity, and efficiency of a fully multidimensional CAT algorithm…
Multidimensional Measurement of Poverty among Women in Sub-Saharan Africa
ERIC Educational Resources Information Center
Batana, Yele Maweki
2013-01-01
Since the seminal work of Sen, poverty has been recognized as a multidimensional phenomenon. The recent availability of relevant databases renewed the interest in this approach. This paper estimates multidimensional poverty among women in fourteen Sub-Saharan African countries using the Alkire and Foster multidimensional poverty measures, whose…
A Multidimensional Scaling Analysis of Students' Attitudes about Science Careers
ERIC Educational Resources Information Center
Masnick, Amy M.; Valenti, S. Stavros; Cox, Brian D.; Osman, Christopher J.
2010-01-01
To encourage students to seek careers in Science, Technology, Engineering and Mathematics (STEM) fields, it is important to gauge students' implicit and explicit attitudes towards scientific professions. We asked high school and college students to rate the similarity of pairs of occupations, and then used multidimensional scaling (MDS) to create…
Turkish Validity Examination of the Multidimensional Students' Life Satisfaction Scale
ERIC Educational Resources Information Center
Irmak, Sezgin; Kuruuzum, Ayse
2009-01-01
The validation studies of the Multidimensional Students' Life Satisfaction Scale (MSLSS) have been conducted with samples from different nations but mostly from western individualistic cultures. Life satisfaction and its constructs could differ depending on cultural characteristics and life satisfaction scales should be validated in different…
An overview of multidimensional liquid phase separations in food analysis.
Franco, Maraíssa Silva; Padovan, Rodrigo Nogueira; Fumes, Bruno Henrique; Lanças, Fernando Mauro
2016-07-01
Food safety is a priority public health concern that demands analytical methods capable to detect low concentration level of contaminants (e.g. pesticides and antibiotics) in different food matrices. Due to the high complexity of these matrices, a sample preparation step is in most cases mandatory to achieve satisfactory results being usually tedious, lengthy, and prone to the introduction of errors. For this reason, many research groups have focused efforts on the development of online systems capable to do the cleanup, concentration, and separation steps at once through multidimensional separation techniques (MDS). Among several possible setups, the most popular are the multidimensional chromatographic techniques (MDC) that consist in combining more than one mobile and/or stationary phase to provide a satisfactory separation. In the present review, we selected a variety of multidimensional separation systems used for food contaminant analysis in order to discuss the instrumentation aspects, the concept of orthogonality, column approaches used in these systems, and new materials that can be used in these columns. Selected classes of contaminants present in food matrices are introduced and discussed as example of the potential applications of multidimensional liquid phase separation techniques in food safety. PMID:27030380
Multidimensional Scaling: Review and Geographical Applications, Technical Paper No. 10.
ERIC Educational Resources Information Center
Golledge, R. G.; Rushton, Gerard
The purpose of this monograph is to show that sufficient achievements in scaling applications have been made to justify serious study of scaling methodologies, particularly multidimensional scaling (MDS) as a tool for geographers. To be useful research, it was felt that the common methodological and technical problems that specialized researchers…
Multidimensional Scoring of Abilities: The Ordered Polytomous Response Case
ERIC Educational Resources Information Center
de la Torre, Jimmy
2008-01-01
Recent work has shown that multidimensionally scoring responses from different tests can provide better ability estimates. For educational assessment data, applications of this approach have been limited to binary scores. Of the different variants, the de la Torre and Patz model is considered more general because implementing the scoring procedure…
An overview of multidimensional liquid phase separations in food analysis.
Franco, Maraíssa Silva; Padovan, Rodrigo Nogueira; Fumes, Bruno Henrique; Lanças, Fernando Mauro
2016-07-01
Food safety is a priority public health concern that demands analytical methods capable to detect low concentration level of contaminants (e.g. pesticides and antibiotics) in different food matrices. Due to the high complexity of these matrices, a sample preparation step is in most cases mandatory to achieve satisfactory results being usually tedious, lengthy, and prone to the introduction of errors. For this reason, many research groups have focused efforts on the development of online systems capable to do the cleanup, concentration, and separation steps at once through multidimensional separation techniques (MDS). Among several possible setups, the most popular are the multidimensional chromatographic techniques (MDC) that consist in combining more than one mobile and/or stationary phase to provide a satisfactory separation. In the present review, we selected a variety of multidimensional separation systems used for food contaminant analysis in order to discuss the instrumentation aspects, the concept of orthogonality, column approaches used in these systems, and new materials that can be used in these columns. Selected classes of contaminants present in food matrices are introduced and discussed as example of the potential applications of multidimensional liquid phase separation techniques in food safety.
BMDS: A Collection of R Functions for Bayesian Multidimensional Scaling
ERIC Educational Resources Information Center
Okada, Kensuke; Shigemasu, Kazuo
2009-01-01
Bayesian multidimensional scaling (MDS) has attracted a great deal of attention because: (1) it provides a better fit than do classical MDS and ALSCAL; (2) it provides estimation errors of the distances; and (3) the Bayesian dimension selection criterion, MDSIC, provides a direct indication of optimal dimensionality. However, Bayesian MDS is not…
A MULTIDIMENSIONAL AND MULTIPHYSICS APPROACH TO NUCLEAR FUEL BEHAVIOR SIMULATION
R. L. Williamson; J. D. Hales; S. R. Novascone; M. R. Tonks; D. R. Gaston; C. J. Permann; D. Andrs; R. C. Martineau
2012-04-01
Important aspects of fuel rod behavior, for example pellet-clad mechanical interaction (PCMI), fuel fracture, oxide formation, non-axisymmetric cooling, and response to fuel manufacturing defects, are inherently multidimensional in addition to being complicated multiphysics problems. Many current modeling tools are strictly 2D axisymmetric or even 1.5D. This paper outlines the capabilities of a new fuel modeling tool able to analyze either 2D axisymmetric or fully 3D models. These capabilities include temperature-dependent thermal conductivity of fuel; swelling and densification; fuel creep; pellet fracture; fission gas release; cladding creep; irradiation growth; and gap mechanics (contact and gap heat transfer). The need for multiphysics, multidimensional modeling is then demonstrated through a discussion of results for a set of example problems. The first, a 10-pellet rodlet, demonstrates the viability of the solution method employed. This example highlights the effect of our smeared cracking model and also shows the multidimensional nature of discrete fuel pellet modeling. The second example relies on our the multidimensional, multiphysics approach to analyze a missing pellet surface problem. As a final example, we show a lower-length-scale simulation coupled to a continuum-scale simulation.
Multidimensional profiling of cell surface proteins and nuclear markers
Han, Ju; Chang, Hang; Andarawewa, Kumari; Yaswen, Paul; Helen Barcellos-Hoff, Mary; Parvin, Bahram
2009-01-30
Cell membrane proteins play an important role in tissue architecture and cell-cell communication. We hypothesize that segmentation and multidimensional characterization of the distribution of cell membrane proteins, on a cell-by-cell basis, enable improved classification of treatment groups and identify important characteristics that can otherwise be hidden. We have developed a series of computational steps to (i) delineate cell membrane protein signals and associate them with a specific nucleus; (ii) compute a coupled representation of the multiplexed DNA content with membrane proteins; (iii) rank computed features associated with such a multidimensional representation; (iv) visualize selected features for comparative evaluation through heatmaps; and (v) discriminate between treatment groups in an optimal fashion. The novelty of our method is in the segmentation of the membrane signal and the multidimensional representation of phenotypic signature on a cell-by-cell basis. To test the utility of this method, the proposed computational steps were applied to images of cells that have been irradiated with different radiation qualities in the presence and absence of other small molecules. These samples are labeled for their DNA content and E-cadherin membrane proteins. We demonstrate that multidimensional representations of cell-by-cell phenotypes improve predictive and visualization capabilities among different treatment groups, and identify hidden variables.
A Multidimensional Latent Trait Model for Measuring Learning and Change.
ERIC Educational Resources Information Center
Embretson, Susan E.
1991-01-01
A multidimensional model is presented for measuring learning and change based on item response theory. The model specifies a Wiener simplex pattern for involvement of initial ability and one or more modifiabilities in response potential for successive measurement occasions. Properties of the model are explored for several classical issues. (SLD)
Psychometric Properties of the Multidimensional-Multiattributional Causality Scale.
ERIC Educational Resources Information Center
Hamilton, Richard J.; Akhter, Selina
2002-01-01
Studied the construct validity of the dimensions of the Multidimensional-Multiattributional Causality Scale based on B. Wiener's attribution model (1979) in achievement and affiliation goal domains. Results for 172 New Zealand college students provide evidence that the measure is better used as a goal specific measure than a general measure. (SLD)
Multidimensional Vector Model of Stimulus-Response Compatibility
ERIC Educational Resources Information Center
Yamaguchi, Motonori; Proctor, Robert W.
2012-01-01
The present study proposes and examines the multidimensional vector (MDV) model framework as a modeling schema for choice response times. MDV extends the Thurstonian model, as well as signal detection theory, to classification tasks by taking into account the influence of response properties on stimulus discrimination. It is capable of accounting…
Assessing Multidimensional Energy Literacy of Secondary Students Using Contextualized Assessment
ERIC Educational Resources Information Center
Chen, Kuan-Li; Liu, Shiang-Yao; Chen, Po-Hsi
2015-01-01
Energy literacy is multidimensional, comprising broad content knowledge as well as affect and behavior. Our previous study has defined four core dimensions for the assessment framework, including energy concepts, reasoning on energy issues, low-carbon lifestyle, and civic responsibility for a sustainable society. The present study compiled a…
Three-Mode Multidimensional Scaling with Points of View Solutions
ERIC Educational Resources Information Center
Tzeng, Oliver C. S.; Landis, Dan
1978-01-01
Two popular models for performing multidimensional scaling, Tucker and Messick's points-of-view model, and Tucker's three mode model, are combined into a single analytic procedure, the 3M-POV model. The procedure is described and its strengths are discussed. Carroll and Chang's INDSCAL model is also mentioned. (JKS)
Reporting of Subscores Using Multidimensional Item Response Theory
ERIC Educational Resources Information Center
Haberman, Shelby J.; Sinharay, Sandip
2010-01-01
Recently, there has been increasing interest in reporting subscores. This paper examines reporting of subscores using multidimensional item response theory (MIRT) models (e.g., Reckase in "Appl. Psychol. Meas." 21:25-36, 1997; C.R. Rao and S. Sinharay (Eds), "Handbook of Statistics, vol. 26," pp. 607-642, North-Holland, Amsterdam, 2007; Beguin &…
A Review of the Brief Multidimensional Students' Life Satisfaction Scale
ERIC Educational Resources Information Center
Huebner, E. Scott; Seligson, Julie L.; Valois, Robert F.; Suldo, Shannon M.
2006-01-01
There are few psychometrically sound measures of life satisfaction suitable for children and adolescents. The purpose of this paper is to describe the rationale, development, and psychometric properties of a brief multidimensional life satisfaction scale appropriate for use with children of ages 8-18. The paper summarizes extant studies of its…
Generalizations of Paradoxical Results in Multidimensional Item Response Theory
ERIC Educational Resources Information Center
Jordan, Pascal; Spiess, Martin
2012-01-01
Maximum likelihood and Bayesian ability estimation in multidimensional item response models can lead to paradoxical results as proven by Hooker, Finkelman, and Schwartzman ("Psychometrika" 74(3): 419-442, 2009): Changing a correct response on one item into an incorrect response may produce a higher ability estimate in one dimension. Furthermore,…
Income Tax Preparation Assistance Service Learning Program: A Multidimensional Assessment
ERIC Educational Resources Information Center
Aldridge, Richard; Callahan, Richard A.; Chen, Yining; Wade, Stacy R.
2015-01-01
The authors present a multidimensional assessment of the outcomes and benefits of an income tax preparation assistance (ITPA) service learning program. They measure the perceived proximate benefits at the delivery of the service program, the actual learning outcome benefits prior to graduation, and the perceived long-term benefits from a…
Individual and Institutional Determinants of Multidimensional Poverty: A European Comparison
ERIC Educational Resources Information Center
Dewilde, Caroline
2008-01-01
In this article we evaluate to what extent between-country differences in the probability of being "multidimensional" poor can be explained by a range of "domain-specific" indicators of welfare regime arrangements. To this end, a so-called micro-macro model is estimated, testing the "independent" effect of institutions, as opposed to alternative…
Development and Validation of the Multidimensional State Boredom Scale
ERIC Educational Resources Information Center
Fahlman, Shelley A.; Mercer-Lynn, Kimberley B.; Flora, David B.; Eastwood, John D.
2013-01-01
This article describes the development and validation of the Multidimensional State Boredom Scale (MSBS)--the first and only full-scale measure of state boredom. It was developed based on a theoretically and empirically grounded definition of boredom. A five-factor structure of the scale (Disengagement, High Arousal, Low Arousal, Inattention, and…
Income and beyond: Multidimensional Poverty in Six Latin American Countries
ERIC Educational Resources Information Center
Battiston, Diego; Cruces, Guillermo; Lopez-Calva, Luis Felipe; Lugo, Maria Ana; Santos, Maria Emma
2013-01-01
This paper studies multidimensional poverty for Argentina, Brazil, Chile, El Salvador, Mexico and Uruguay for the period 1992-2006. The approach overcomes the limitations of the two traditional methods of poverty analysis in Latin America (income-based and unmet basic needs) by combining income with five other dimensions: school attendance for…
The Multi-Dimensional Demands of Reading in the Disciplines
ERIC Educational Resources Information Center
Lee, Carol D.
2014-01-01
This commentary addresses the complexities of reading comprehension with an explicit focus on reading in the disciplines. The author proposes reading as entailing multi-dimensional demands of the reader and posing complex challenges for teachers. These challenges are intensified by restrictive conceptions of relevant prior knowledge and experience…
Multidimensional Poverty in China: Findings Based on the CHNS
ERIC Educational Resources Information Center
Yu, Jiantuo
2013-01-01
This paper estimates multidimensional poverty in China by applying the Alkire-Foster methodology to the China Health and Nutrition Survey 2000-2009 data. Five dimensions are included: income, living standard, education, health and social security. Results suggest that rapid economic growth has resulted not only in a reduction in income poverty but…
Multidimensional Item Response Theory Parameter Estimation with Nonsimple Structure Items
ERIC Educational Resources Information Center
Finch, Holmes
2011-01-01
Estimation of multidimensional item response theory (MIRT) model parameters can be carried out using the normal ogive with unweighted least squares estimation with the normal-ogive harmonic analysis robust method (NOHARM) software. Previous simulation research has demonstrated that this approach does yield accurate and efficient estimates of item…
Five Evils: Multidimensional Poverty and Race in America
ERIC Educational Resources Information Center
Reeves, Richard; Rodrigue, Edward; Kneebone, Elizabeth
2016-01-01
Poverty is about a lack of money, but it's not only about that. As a lived experience, poverty is also characterized by ill health, insecurity, discomfort, isolation, and more. To put it another way: Poverty is multidimensional, and its dimensions often cluster together to intensify the negative effects of being poor. In this first of a two-part…
The Structure and Validity of the Multidimensional Social Support Questionnaire
ERIC Educational Resources Information Center
Hardesty, Patrick H.; Richardson, George B.
2012-01-01
The factor structure and concurrent validity of the Multidimensional Social Support Questionnaire, a brief measure of perceived social support for use with adolescents, was examined. Findings suggest that four dimensions of perceived social support may yield more information than assessments of the unitary construct of support. (Contains 8 tables…
The structure of multidimensional strained flames under transcritical conditions
NASA Astrophysics Data System (ADS)
Pons, L.; Darabiha, N.; Candel, S.; Schmitt, T.; Cuenot, B.
2009-06-01
Strained flames are commonly used to study the structure of reactive layers and describe the local properties of turbulent combustion. This model is attractive because constant strain rate flames only depend on a transverse coordinate and can be treated as a one-dimensional problem. This configuration is considered in a multidimensional context in which the strained flow is obtained by two counterflowing streams of reactants. It is used to examine the structure of transcritical strained flames in which one or two reactants are injected at a high pressure exceeding the critical value while their temperature is below the critical value. Calculations are carried out in a two-dimensional domain to test numerical models developed for multidimensional simulations and test thermodynamic and transport models devised to deal with high pressure real gas effects. Multidimensional strained flame calculations carried out in this study serve to check the validity of a new version of a Navier-Stokes flow solver (AVBP) conceived to deal with transcritical combustion of interest to liquid propellant rocket applications. This article describes the basic elements of such simulations and discusses results of calculations. It is shown that the calculated multidimensional strained flames have the expected features in terms of structure and response to the imposed strain rate. To cite this article: L. Pons et al., C. R. Mecanique 337 (2009).
Multidimensional Model of Trauma and Correlated Antisocial Personality Disorder
ERIC Educational Resources Information Center
Martens, Willem H. J.
2005-01-01
Many studies have revealed an important relationship between psychosocial trauma and antisocial personality disorder. A multidimensional model is presented which describes the psychopathological route from trauma to antisocial development. A case report is also included that can illustrate the etiological process from trauma to severe antisocial…
Multi-Dimensional Models for Teaching Deaf-Blind Children.
ERIC Educational Resources Information Center
Baud, Hank, Ed.; Garrett, Jeff, Ed.
Presented are five papers on multidimensional teaching models presented at a workshop for professionals serving deaf-blind children. In "Interpretation of Visual Reports", M. Efron discusses procedures for improving visual diagnosis and provides a questionnaire format for an educationally oriented vision report. M. Marshall, in her paper entitled…
Educational Mismatch of Graduates: A Multidimensional and Fuzzy Indicator
ERIC Educational Resources Information Center
Betti, Gianni; D'Agostino, Antonella; Neri, Laura
2011-01-01
In this paper we attempt to measure the educational mismatch, seen as a problem of overeducation, using a multidimensional and fuzzy methodology. Educational mismatch can be difficult to measure because many factors can converge to its definition and the traditional unidimensional indicators presented in literature can offer a restricted view of…
Linear and Nonlinear Thinking: A Multidimensional Model and Measure
ERIC Educational Resources Information Center
Groves, Kevin S.; Vance, Charles M.
2015-01-01
Building upon previously developed and more general dual-process models, this paper provides empirical support for a multidimensional thinking style construct comprised of linear thinking and multiple dimensions of nonlinear thinking. A self-report assessment instrument (Linear/Nonlinear Thinking Style Profile; LNTSP) is presented and…
The Multidimensionality of Calling: Conceptualization, Measurement and a Bicultural Perspective
ERIC Educational Resources Information Center
Hagmaier, Tamara; Abele, Andrea E.
2012-01-01
The experience of a calling may be seen as the ultimate form of subjective career success that has many positive consequences for individuals and organizations. We are here concerned with the conceptualization of a new multidimensional measure of calling, the MCM. In the first two studies we employed a qualitative approach and came up with five…
Analysis of stock market indices through multidimensional scaling
NASA Astrophysics Data System (ADS)
Machado, J. Tenreiro; Duarte, Fernando B.; Duarte, Gonçalo Monteiro
2011-12-01
We propose a graphical method to visualize possible time-varying correlations between fifteen stock market values. The method is useful for observing stable or emerging clusters of stock markets with similar behaviour. The graphs, originated from applying multidimensional scaling techniques (MDS), may also guide the construction of multivariate econometric models.
ERIC Educational Resources Information Center
Ding, Cody
2012-01-01
There has been considerable debate over the ways in which children's early literacy skills develop over time. Using confirmatory multidimensional scaling (MDS) growth analysis, this paper directly tested the hypothesis of a cumulative trajectory versus a compensatory trajectory of development in early literacy skills among a group of 1233…
Examining the Reliability of Student Growth Percentiles Using Multidimensional IRT
ERIC Educational Resources Information Center
Monroe, Scott; Cai, Li
2015-01-01
Student growth percentiles (SGPs, Betebenner, 2009) are used to locate a student's current score in a conditional distribution based on the student's past scores. Currently, following Betebenner (2009), quantile regression (QR) is most often used operationally to estimate the SGPs. Alternatively, multidimensional item response theory (MIRT) may…
The Relationship between Anxiety and Stuttering: A Multidimensional Approach
ERIC Educational Resources Information Center
Ezrati-Vinacour, Ruth; Levin, Iris
2004-01-01
The relationship between anxiety and stuttering is equivocal from both clinical and empirical perspectives. This study examined the relationship within the framework of the multidimensional interaction model of anxiety that includes an approach to general anxiety in specific situations [J. Pers. Soc. Psychol. 60 (1991) 919]. Ninety-four males aged…
The Structure of Masculinity-Femininity: Multidimensionality and Gender Differences.
ERIC Educational Resources Information Center
Ratliff, Elyse Sutherland; Conley, James
1981-01-01
Investigated the structure of sex role self-descriptors. Factor analyzed responses of female and male undergraduates to the Bem Sex Role Inventory. Seven factors emerged: personal warmth, social dominance, autonomy, affect, masculinity-feminity, vulnerability, and responsibility. Results support a multidimensional conception of…
Evaluation of Linking Methods for Multidimensional IRT Calibrations
ERIC Educational Resources Information Center
Min, Kyung-Seok
2007-01-01
Most researchers agree that psychological/educational tests are sensitive to multiple traits, implying the need for a multidimensional item response theory (MIRT). One limitation of applying a MIRT in practice is the difficulty in establishing equivalent scales of multiple traits. In this study, a new MIRT linking method was proposed and evaluated…
Gender and Attitudes toward People Using Wheelchairs: A Multidimensional Perspective
ERIC Educational Resources Information Center
Vilchinsky, Noa; Werner, Shirli; Findler, Liora
2010-01-01
This study aims to investigate the effect of observer's gender and target's gender on attitudes toward people who use wheelchairs due to a physical disability. Four hundred four Jewish Israeli students without disabilities completed the "Multidimensional Attitudes Scale Toward Persons With Disabilities" (MAS). Initially, confirmatory factor…
The Multidimensional Structure of Verbal Comprehension Test Items.
ERIC Educational Resources Information Center
Peled, Zimra
1984-01-01
The multidimensional structure of verbal comprehension test items was investigated. Empirical evidence was provided to support the theory that item tasks are multivariate-multiordered composites of faceted components: language, contextual knowledge, and cognitive operation. Linear and circular properties of cylindrical manifestation were…
A Multidimensional Approach to E-Learning Sustainability
ERIC Educational Resources Information Center
Trentin, Guglielmo, Ed.
2007-01-01
The aim of the article is to outline the possible key elements related to the sustainability of e-learning. After analyzing trends in e-learning diffusion, a multidimensional model for sustainability of e-learning innovations is presented. The proposed model is characterized by eight dimensions that are closely and mutually interrelated:…
On the Solution of NBVP for Multidimensional Hyperbolic Equations
Ashyralyev, Allaberen
2014-01-01
We are interested in studying multidimensional hyperbolic equations with nonlocal integral and Neumann or nonclassical conditions. For the approximate solution of this problem first and second order of accuracy difference schemes are presented. Stability estimates for the solution of these difference schemes are established. Some numerical examples illustrating applicability of these methods to hyperbolic problems are given. PMID:24983006
The Multidimensional Behavior Rating Scale: An Assessment Device for Depression.
ERIC Educational Resources Information Center
Rothblum, Esther D.; Green, Leon
The Multidimensional Behavior Rating Scale (MBRS) was constructed to assess symptoms of depression across seven modalities: behavior, affect, sensation, imagery, cognition, interpersonal relationship, and drugs. Subjects (N=33) were matched by level of depression on the Minnesota Multiphasic Personality Inventory Depression Scale to either a…
Extending Validity Evidence for Multidimensional Measures of Coaching Competency
ERIC Educational Resources Information Center
Myers, Nicholas D.; Wolfe, Edward W.; Maier, Kimberly S.; Feltz, Deborah L.; Reckase, Mark D.
2006-01-01
This study extended validity evidence for multidimensional measures of coaching competency derived from the Coaching Competency Scale (CCS; Myers, Feltz, Maier, Wolfe, & Reckase, 2006) by examining use of the original rating scale structure and testing how measures related to satisfaction with the head coach within teams and between teams.…
A Framework for Dimensionality Assessment for Multidimensional Item Response Models
ERIC Educational Resources Information Center
Svetina, Dubravka; Levy, Roy
2014-01-01
A framework is introduced for considering dimensionality assessment procedures for multidimensional item response models. The framework characterizes procedures in terms of their confirmatory or exploratory approach, parametric or nonparametric assumptions, and applicability to dichotomous, polytomous, and missing data. Popular and emerging…
The Multidimensionality of Child Poverty: Evidence from Afghanistan
ERIC Educational Resources Information Center
Trani, Jean-Francois; Biggeri, Mario; Mauro, Vincenzo
2013-01-01
This paper examines multidimensional poverty among children in Afghanistan using the Alkire-Foster method. Several previous studies have underlined the need to separate children from their adult nexus when studying poverty and treat them according to their own specificities. From the capability approach, child poverty is understood to be the lack…
The Multidimensional Fear of Death Scale: An Independent Analysis.
ERIC Educational Resources Information Center
Walkey, Frank H.
1982-01-01
Examined the factor structure and subscale reliabilities of an eight-dimensional measure of fear of death (the Multidimensional Fear of Death Scale) using a New Zealand sample. Comparison with the results of a United States study showed that both the subscale reliabilities and the factor structure were almost perfectly reproduced. (Author)
A General Multidimensional Model for the Measurement of Cultural Differences.
ERIC Educational Resources Information Center
Olmedo, Esteban L.; Martinez, Sergio R.
A multidimensional model for measuring cultural differences (MCD) based on factor analytic theory and techniques is proposed. The model assumes that a cultural space may be defined by means of a relatively small number of orthogonal dimensions which are linear combinations of a much larger number of cultural variables. Once a suitable,…
Multidimensional Adaptive Testing with Optimal Design Criteria for Item Selection
ERIC Educational Resources Information Center
Mulder, Joris; van der Linden, Wim J.
2009-01-01
Several criteria from the optimal design literature are examined for use with item selection in multidimensional adaptive testing. In particular, it is examined what criteria are appropriate for adaptive testing in which all abilities are intentional, some should be considered as a nuisance, or the interest is in the testing of a composite of the…
Positivity-preserving numerical schemes for multidimensional advection
NASA Technical Reports Server (NTRS)
Leonard, B. P.; Macvean, M. K.; Lock, A. P.
1993-01-01
This report describes the construction of an explicit, single time-step, conservative, finite-volume method for multidimensional advective flow, based on a uniformly third-order polynomial interpolation algorithm (UTOPIA). Particular attention is paid to the problem of flow-to-grid angle-dependent, anisotropic distortion typical of one-dimensional schemes used component-wise. The third-order multidimensional scheme automatically includes certain cross-difference terms that guarantee good isotropy (and stability). However, above first-order, polynomial-based advection schemes do not preserve positivity (the multidimensional analogue of monotonicity). For this reason, a multidimensional generalization of the first author's universal flux-limiter is sought. This is a very challenging problem. A simple flux-limiter can be found; but this introduces strong anisotropic distortion. A more sophisticated technique, limiting part of the flux and then restoring the isotropy-maintaining cross-terms afterwards, gives more satisfactory results. Test cases are confined to two dimensions; three-dimensional extensions are briefly discussed.
Multidimensional representation of objects--The influence of task demands.
Goldfarb, L; Sabah, K
2016-04-01
In our daily life, we often encounter situations in which different features of several multidimensional objects must be perceived simultaneously. There are two types of environments of this kind: environments with multidimensional objects that have unique feature associations, and environments with multidimensional objects that have mixed feature associations. Recently, we (Goldfarb & Treisman, 2013) described the association effect, suggesting that the latter type causes behavioral perception difficulties. In the present study, we investigated this effect further by examining whether the effect is determined via a feedforward visual path or via a high-order task demand component. In order to test this question, in Experiment 1 a set of multidimensional objects were presented while we manipulated the letter case of a target feature, thus creating a visually different but semantically equivalent object, in terms of its identity. Similarly, in Experiment 2 artificial groups with different physical properties were created according to the task demands. The results indicated that the association effect is determined by the task demands, which create the group of reference. The importance of high-order task demand components in the association effect is further discussed, as well as the possible role of the neural synchrony of object files in explaining this effect. PMID:26163190
A Multidimensional Analysis of a Written L2 Spanish Corpus
ERIC Educational Resources Information Center
Asencion-Delaney, Yuly; Collentine, Joseph
2011-01-01
The present study adds to our understanding of how learners employ lexical and grammatical phenomena to communicate in writing in different types of interlanguage discourse. A multidimensional (factor) analysis of a corpus of L2 Spanish writing (202,241 words) generated by second- and third-year, university-level learners was performed. The…
Multidimensional Collaboration: Reflections on Action Research in a Clinical Context
ERIC Educational Resources Information Center
Gregory, Sheila; Poland, Fiona; Spalding, Nicola J.; Sargen, Kevin; McCulloch, Jane; Vicary, Penny
2011-01-01
This paper reflects on the challenges and benefits of multidimensional collaboration in an action research study to evaluate and improve preoperative education for patients awaiting colorectal surgery. Three cycles of planning, acting, observing and reflecting were designed to evaluate practice and implement change in this interactive setting,…
Integrable multidimensional gravitational and cosmological models and applications
NASA Astrophysics Data System (ADS)
Ivashchuk, V. D.; Melnikov, V. N.
2016-01-01
Two families of exact solutions in multidimensional gravity with scalar fields and fields of forms are considered: fluxbrane and black brane ones. A brief overview of main results on billiard approach for cosmological-type models with branes is also presented.
D'Ambroise, J.; Salerno, M.; Kevrekidis, P. G.; Abdullaev, F. Kh.
2015-11-19
The existence of multidimensional lattice compactons in the discrete nonlinear Schrödinger equation in the presence of fast periodic time modulations of the nonlinearity is demonstrated. By averaging over the period of the fast modulations, an effective averaged dynamical equation arises with coupling constants involving Bessel functions of the first and zeroth kinds. We show that these terms allow one to solve, at this averaged level, for exact discrete compacton solution configurations in the corresponding stationary equation. We focus on seven types of compacton solutions. Single-site and vortex solutions are found to be always stable in the parametric regimes we examined.more » We also found that other solutions such as double-site in- and out-of-phase, four-site symmetric and antisymmetric, and a five-site compacton solution are found to have regions of stability and instability in two-dimensional parametric planes, involving variations of the strength of the coupling and of the nonlinearity. We also explore the time evolution of the solutions and compare the dynamics according to the averaged equations with those of the original dynamical system. Finally, the possible observation of compactons in Bose-Einstein condensates loaded in a deep two-dimensional optical lattice with interactions modulated periodically in time is also discussed.« less
D'Ambroise, J.; Salerno, M.; Kevrekidis, P. G.; Abdullaev, F. Kh.
2015-11-19
The existence of multidimensional lattice compactons in the discrete nonlinear Schrödinger equation in the presence of fast periodic time modulations of the nonlinearity is demonstrated. By averaging over the period of the fast modulations, an effective averaged dynamical equation arises with coupling constants involving Bessel functions of the first and zeroth kinds. We show that these terms allow one to solve, at this averaged level, for exact discrete compacton solution configurations in the corresponding stationary equation. We focus on seven types of compacton solutions. Single-site and vortex solutions are found to be always stable in the parametric regimes we examined. We also found that other solutions such as double-site in- and out-of-phase, four-site symmetric and antisymmetric, and a five-site compacton solution are found to have regions of stability and instability in two-dimensional parametric planes, involving variations of the strength of the coupling and of the nonlinearity. We also explore the time evolution of the solutions and compare the dynamics according to the averaged equations with those of the original dynamical system. Finally, the possible observation of compactons in Bose-Einstein condensates loaded in a deep two-dimensional optical lattice with interactions modulated periodically in time is also discussed.
NASA Astrophysics Data System (ADS)
D'Ambroise, J.; Salerno, M.; Kevrekidis, P. G.; Abdullaev, F. Kh.
2015-11-01
The existence of multidimensional lattice compactons in the discrete nonlinear Schrödinger equation in the presence of fast periodic time modulations of the nonlinearity is demonstrated. By averaging over the period of the fast modulations, an effective averaged dynamical equation arises with coupling constants involving Bessel functions of the first and zeroth kinds. We show that these terms allow one to solve, at this averaged level, for exact discrete compacton solution configurations in the corresponding stationary equation. We focus on seven types of compacton solutions. Single-site and vortex solutions are found to be always stable in the parametric regimes we examined. Other solutions such as double-site in- and out-of-phase, four-site symmetric and antisymmetric, and a five-site compacton solution are found to have regions of stability and instability in two-dimensional parametric planes, involving variations of the strength of the coupling and of the nonlinearity. We also explore the time evolution of the solutions and compare the dynamics according to the averaged equations with those of the original dynamical system. The possible observation of compactons in Bose-Einstein condensates loaded in a deep two-dimensional optical lattice with interactions modulated periodically in time is also discussed.
Second order multidimensional sign-preserving remapping for ALE methods
Hill, Ryan N; Szmelter, J.
2010-12-15
A second-order conservative sign-preserving remapping scheme for Arbitrary Lagrangian-Eulerian (ALE) methods is developed utilising concepts of the Multidimensional Positive Definite Advection Transport Algorithm (MPDATA). The algorithm is inherently multidimensional, and so does not introduce splitting errors. The remapping is implemented in a two-dimensional, finite element ALE solver employing staggered quadrilateral meshes. The MPDATA remapping uses a finite volume discretization developed for volume coordinates. It is applied for the remapping of density and internal energy arranged as cell centered, and velocity as nodal, dependent variables. In the paper, the advection of scalar fields is examined first for test cases with prescribed mesh movement. A direct comparison of MPDATA with the performance of the van Leer MUSCL scheme indicates advantages of a multidimensional approach. Furthermore, distinctly different performance between basic MPDATA and the infinite gauge option is illustrated using benchmarks involving transport of a sign changing velocity field. Further development extends the application of MPDATA remapping to the full ALE solver with a staggered mesh arrangement for density, internal energy and momentum using volume coordinates. At present, two options of the algorithm - basic and infinite gauge - are implemented. To ensure a meaningful assessment, an identical Lagrangian solver and computational mesh update routines are used with either MPDATA or van Leer MUSCL remapping. The evaluation places particular focus on the abilities of both schemes to accurately model multidimensional problems. Theoretical considerations are supported with numerical examples. In addition to the prescribed mesh movement cases for advection of scalars, the demonstrations include two-dimensional Eulerian and ALE flow simulations on quadrilateral meshes with both fixed and variable timestep control. The key comparisons include the standard test cases of Sod and Noh
... challenge to eat healthy when going to a fast food place. In general, avoiding items that are deep ... challenge to eat healthy when going to a fast food place. In general, avoiding items that are deep ...
Fast foods are quick, reasonably priced, and readily available alternatives to home cooking. While convenient and economical for a busy lifestyle, fast foods are typically high in calories, fat, saturated fat, ...
ERIC Educational Resources Information Center
Hawkins, Colleen C.; Watt, Helen M. G.; Sinclair, Kenneth E.
2006-01-01
The psychometric properties of the Frost, Marten, Lahart, and Rosenblate Multidimensional Perfectionism Scale (1990) are investigated to determine its usefulness as a measurement of perfectionism with Australian secondary school girls and to find empirical support for the existence of both healthy and unhealthy types of perfectionist students.…
Garber, Andrea K; Lustig, Robert H
2011-09-01
Studies of food addiction have focused on highly palatable foods. While fast food falls squarely into that category, it has several other attributes that may increase its salience. This review examines whether the nutrients present in fast food, the characteristics of fast food consumers or the presentation and packaging of fast food may encourage substance dependence, as defined by the American Psychiatric Association. The majority of fast food meals are accompanied by a soda, which increases the sugar content 10-fold. Sugar addiction, including tolerance and withdrawal, has been demonstrated in rodents but not humans. Caffeine is a "model" substance of dependence; coffee drinks are driving the recent increase in fast food sales. Limited evidence suggests that the high fat and salt content of fast food may increase addictive potential. Fast food restaurants cluster in poorer neighborhoods and obese adults eat more fast food than those who are normal weight. Obesity is characterized by resistance to insulin, leptin and other hormonal signals that would normally control appetite and limit reward. Neuroimaging studies in obese subjects provide evidence of altered reward and tolerance. Once obese, many individuals meet criteria for psychological dependence. Stress and dieting may sensitize an individual to reward. Finally, fast food advertisements, restaurants and menus all provide environmental cues that may trigger addictive overeating. While the concept of fast food addiction remains to be proven, these findings support the role of fast food as a potentially addictive substance that is most likely to create dependence in vulnerable populations.
Garber, Andrea K; Lustig, Robert H
2011-09-01
Studies of food addiction have focused on highly palatable foods. While fast food falls squarely into that category, it has several other attributes that may increase its salience. This review examines whether the nutrients present in fast food, the characteristics of fast food consumers or the presentation and packaging of fast food may encourage substance dependence, as defined by the American Psychiatric Association. The majority of fast food meals are accompanied by a soda, which increases the sugar content 10-fold. Sugar addiction, including tolerance and withdrawal, has been demonstrated in rodents but not humans. Caffeine is a "model" substance of dependence; coffee drinks are driving the recent increase in fast food sales. Limited evidence suggests that the high fat and salt content of fast food may increase addictive potential. Fast food restaurants cluster in poorer neighborhoods and obese adults eat more fast food than those who are normal weight. Obesity is characterized by resistance to insulin, leptin and other hormonal signals that would normally control appetite and limit reward. Neuroimaging studies in obese subjects provide evidence of altered reward and tolerance. Once obese, many individuals meet criteria for psychological dependence. Stress and dieting may sensitize an individual to reward. Finally, fast food advertisements, restaurants and menus all provide environmental cues that may trigger addictive overeating. While the concept of fast food addiction remains to be proven, these findings support the role of fast food as a potentially addictive substance that is most likely to create dependence in vulnerable populations. PMID:21999689
OsiriX: an open-source software for navigating in multidimensional DICOM images.
Rosset, Antoine; Spadola, Luca; Ratib, Osman
2004-09-01
A multidimensional image navigation and display software was designed for display and interpretation of large sets of multidimensional and multimodality images such as combined PET-CT studies. The software is developed in Objective-C on a Macintosh platform under the MacOS X operating system using the GNUstep development environment. It also benefits from the extremely fast and optimized 3D graphic capabilities of the OpenGL graphic standard widely used for computer games optimized for taking advantage of any hardware graphic accelerator boards available. In the design of the software special attention was given to adapt the user interface to the specific and complex tasks of navigating through large sets of image data. An interactive jog-wheel device widely used in the video and movie industry was implemented to allow users to navigate in the different dimensions of an image set much faster than with a traditional mouse or on-screen cursors and sliders. The program can easily be adapted for very specific tasks that require a limited number of functions, by adding and removing tools from the program's toolbar and avoiding an overwhelming number of unnecessary tools and functions. The processing and image rendering tools of the software are based on the open-source libraries ITK and VTK. This ensures that all new developments in image processing that could emerge from other academic institutions using these libraries can be directly ported to the OsiriX program. OsiriX is provided free of charge under the GNU open-source licensing agreement at http://homepage.mac.com/rossetantoine/osirix.
NASA Astrophysics Data System (ADS)
Duy, Truong Vinh Truong; Ozaki, Taisuke
2014-01-01
The fast Fourier transform (FFT) is undoubtedly an essential primitive that has been applied in various fields of science and engineering. In this paper, we present a decomposition method for the parallelization of multi-dimensional FFTs with the smallest communication amounts for all ranges of the number of processes compared to previously proposed methods. This is achieved by two distinguishing features: adaptive decomposition and transpose order awareness. In the proposed method, the FFT data is decomposed based on a row-wise basis that maps the multi-dimensional data into one-dimensional data, and translates the corresponding coordinates from multi-dimensions into one dimension so that the one-dimensional data can be divided and allocated equally to the processes using a block distribution. As a result and different from previous works that have the dimensions of decomposition pre-defined, our method can adaptively decompose the FFT data on the lowest possible dimensions depending on the number of processes. In addition, this row-wise decomposition provides plenty of alternatives in data transpose, and different transpose order results in different amounts of communication. We identify the best transpose orders with the smallest communication amounts for the 3-D, 4-D, and 5-D FFTs by analyzing all possible cases. We also develop a general parallel software package for the most popular 3-D FFT based on our method using the 2-D domain decomposition. Numerical results show good performance and scaling properties of our implementation in comparison with other parallel packages. Given both communication efficiency and scalability, our method is promising in the development of highly efficient parallel packages for the FFT.
Rice, S; McAllister, E J; Dhurandhar, N V
2007-06-01
Fast food is routinely blamed for the obesity epidemic and consequentially excluded from professional dietary recommendations. However, several sections of society including senior citizens, low-income adult and children, minority and homeless children, or those pressed for time appear to rely on fast food as an important source of meals. Considering the dependence of these nutritionally vulnerable population groups on fast food, we examined the possibility of imaginative selection of fast food, which would attenuate the potentially unfavorable nutrient composition. We present a sample menu to demonstrate that it is possible to design a fast food menu that provides reasonable level of essential nutrients without exceeding the caloric recommendations. We would like to alert health-care professionals that fast food need not be forbidden under all circumstances, and that a fresh look at the role of fast food may enable its inclusion in meal planning for those who depend on it out of necessity, while adding flexibility.
NASA Technical Reports Server (NTRS)
Walatka, Pamela P.; Clucas, Jean; McCabe, R. Kevin; Plessel, Todd; Potter, R.; Cooper, D. M. (Technical Monitor)
1994-01-01
The Flow Analysis Software Toolkit, FAST, is a software environment for visualizing data. FAST is a collection of separate programs (modules) that run simultaneously and allow the user to examine the results of numerical and experimental simulations. The user can load data files, perform calculations on the data, visualize the results of these calculations, construct scenes of 3D graphical objects, and plot, animate and record the scenes. Computational Fluid Dynamics (CFD) visualization is the primary intended use of FAST, but FAST can also assist in the analysis of other types of data. FAST combines the capabilities of such programs as PLOT3D, RIP, SURF, and GAS into one environment with modules that share data. Sharing data between modules eliminates the drudgery of transferring data between programs. All the modules in the FAST environment have a consistent, highly interactive graphical user interface. Most commands are entered by pointing and'clicking. The modular construction of FAST makes it flexible and extensible. The environment can be custom configured and new modules can be developed and added as needed. The following modules have been developed for FAST: VIEWER, FILE IO, CALCULATOR, SURFER, TOPOLOGY, PLOTTER, TITLER, TRACER, ARCGRAPH, GQ, SURFERU, SHOTET, and ISOLEVU. A utility is also included to make the inclusion of user defined modules in the FAST environment easy. The VIEWER module is the central control for the FAST environment. From VIEWER, the user can-change object attributes, interactively position objects in three-dimensional space, define and save scenes, create animations, spawn new FAST modules, add additional view windows, and save and execute command scripts. The FAST User Guide uses text and FAST MAPS (graphical representations of the entire user interface) to guide the user through the use of FAST. Chapters include: Maps, Overview, Tips, Getting Started Tutorial, a separate chapter for each module, file formats, and system
Incompressible limit of solutions of multidimensional steady compressible Euler equations
NASA Astrophysics Data System (ADS)
Chen, Gui-Qiang G.; Huang, Feimin; Wang, Tian-Yi; Xiang, Wei
2016-06-01
A compactness framework is formulated for the incompressible limit of approximate solutions with weak uniform bounds with respect to the adiabatic exponent for the steady Euler equations for compressible fluids in any dimension. One of our main observations is that the compactness can be achieved by using only natural weak estimates for the mass conservation and the vorticity. Another observation is that the incompressibility of the limit for the homentropic Euler flow is directly from the continuity equation, while the incompressibility of the limit for the full Euler flow is from a combination of all the Euler equations. As direct applications of the compactness framework, we establish two incompressible limit theorems for multidimensional steady Euler flows through infinitely long nozzles, which lead to two new existence theorems for the corresponding problems for multidimensional steady incompressible Euler equations.
A Multidimensional Data Warehouse for Community Health Centers.
Kunjan, Kislaya; Toscos, Tammy; Turkcan, Ayten; Doebbeling, Brad N
2015-01-01
Community health centers (CHCs) play a pivotal role in healthcare delivery to vulnerable populations, but have not yet benefited from a data warehouse that can support improvements in clinical and financial outcomes across the practice. We have developed a multidimensional clinic data warehouse (CDW) by working with 7 CHCs across the state of Indiana and integrating their operational, financial and electronic patient records to support ongoing delivery of care. We describe in detail the rationale for the project, the data architecture employed, the content of the data warehouse, along with a description of the challenges experienced and strategies used in the development of this repository that may help other researchers, managers and leaders in health informatics. The resulting multidimensional data warehouse is highly practical and is designed to provide a foundation for wide-ranging healthcare data analytics over time and across the community health research enterprise.
Ultrafast Multidimensional Laplace NMR Using a Single-Sided Magnet.
King, Jared N; Lee, Vanessa J; Ahola, Susanna; Telkki, Ville-Veikko; Meldrum, Tyler
2016-04-11
Laplace NMR (LNMR) consists of relaxation and diffusion measurements providing detailed information about molecular motion and interaction. Here we demonstrate that ultrafast single- and multidimensional LNMR experiments, based on spatial encoding, are viable with low-field, single-sided magnets with an inhomogeneous magnetic field. This approach shortens the experiment time by one to two orders of magnitude relative to traditional experiments, and increases the sensitivity per unit time by a factor of three. The reduction of time required to collect multidimensional data opens significant prospects for mobile chemical analysis using NMR. Particularly tantalizing is future use of hyperpolarization to increase sensitivity by orders of magnitude, allowed by single-scan approach. PMID:26960011
Advanced numerics for multi-dimensional fluid flow calculations
Vanka, S.P.
1984-04-01
In recent years, there has been a growing interest in the development and use of mathematical models for the simulation of fluid flow, heat transfer and combustion processes in engineering equipment. The equations representing the multi-dimensional transport of mass, momenta and species are numerically solved by finite-difference or finite-element techniques. However despite the multiude of differencing schemes and solution algorithms, and the advancement of computing power, the calculation of multi-dimensional flows, especially three-dimensional flows, remains a mammoth task. The following discussion is concerned with the author's recent work on the construction of accurate discretization schemes for the partial derivatives, and the efficient solution of the set of nonlinear algebraic equations resulting after discretization. The present work has been jointly supported by the Ramjet Engine Division of the Wright Patterson Air Force Base, Ohio, and the NASA Lewis Research Center.
The West Haven-Yale Multidimensional Pain Inventory (WHYMPI).
Kerns, R D; Turk, D C; Rudy, T E
1985-12-01
The complexity of chronic pain has represented a major dilemma for clinical researchers interested in the reliable and valid assessment of the problem and the evaluation of treatment approaches. The West Haven-Yale Multidimensional Pain Inventory (WHYMPI) was developed in order to fill a widely recognized void in the assessment of clinical pain. Assets of the inventory are its brevity and clarity, its foundation in contemporary psychological theory, its multidimensional focus, and its strong psychometric properties. Three parts of the inventory, comprised of 12 scales, examine the impact of pain on the patients' lives, the responses of others to the patients' communications of pain, and the extent to which patients participate in common daily activities. The instrument is recommended for use in conjunction with behavioral and psychophysiological assessment strategies in the evaluation of chronic pain patients in clinical settings. The utility of the WHYMPI in empirical investigations of chronic pain is also discussed.
Multidimensional nanomaterials for the control of stem cell fate
NASA Astrophysics Data System (ADS)
Chueng, Sy-Tsong Dean; Yang, Letao; Zhang, Yixiao; Lee, Ki-Bum
2016-09-01
Current stem cell therapy suffers low efficiency in giving rise to differentiated cell lineages, which can replace the original damaged cells. Nanomaterials, on the other hand, provide unique physical size, surface chemistry, conductivity, and topographical microenvironment to regulate stem cell differentiation through multidimensional approaches to facilitate gene delivery, cell-cell, and cell-ECM interactions. In this review, nanomaterials are demonstrated to work both alone and synergistically to guide selective stem cell differentiation. From three different nanotechnology families, three approaches are shown: (1) soluble microenvironmental factors; (2) insoluble physical microenvironment; and (3) nano-topographical features. As regenerative medicine is heavily invested in effective stem cell therapy, this review is inspired to generate discussions in the potential clinical applications of multi-dimensional nanomaterials.
Optimized Linear Prediction for Radial Sampled Multidimensional NMR Experiments
Gledhill, John M.; Kasinath, Vignesh; Wand, A. Joshua
2011-01-01
Radial sampling in multidimensional NMR experiments offers greatly decreased acquisition times while also providing an avenue for increased sensitivity. Digital resolution remains concern and depends strongly upon the extent of sampling of individual radial angles. Truncated time domain data leads to spurious peaks (artifacts) upon FT and 2D FT. Linear prediction is commonly employed to improve resolution in Cartesian sampled NMR experiments. Here, we adapt the linear prediction method to radial sampling. Significantly more accurate estimates of linear prediction coefficients are obtained by combining quadrature frequency components from the multiple angle spectra. This approach results in significant improvement in both resolution and removal of spurious peaks as compared to traditional linear prediction methods applied to radial sampled data. The ‘averaging linear prediction’ (ALP) method is demonstrated as a general tool for resolution improvement in multidimensional radial sampled experiments. PMID:21767968
Advanced numerics for multi-dimensional fluid flow calculations
NASA Technical Reports Server (NTRS)
Vanka, S. P.
1984-01-01
In recent years, there has been a growing interest in the development and use of mathematical models for the simulation of fluid flow, heat transfer and combustion processes in engineering equipment. The equations representing the multi-dimensional transport of mass, momenta and species are numerically solved by finite-difference or finite-element techniques. However despite the multiude of differencing schemes and solution algorithms, and the advancement of computing power, the calculation of multi-dimensional flows, especially three-dimensional flows, remains a mammoth task. The following discussion is concerned with the author's recent work on the construction of accurate discretization schemes for the partial derivatives, and the efficient solution of the set of nonlinear algebraic equations resulting after discretization. The present work has been jointly supported by the Ramjet Engine Division of the Wright Patterson Air Force Base, Ohio, and the NASA Lewis Research Center.
Fitness of multidimensional phenotypes in dynamic adaptive landscapes.
Laughlin, Daniel C; Messier, Julie
2015-08-01
Phenotypic traits influence species distributions, but ecology lacks established links between multidimensional phenotypes and fitness for predicting species responses to environmental change. The common focus on single traits rather than multiple trait combinations limits our understanding of their adaptive value, and intraspecific trait covariation has been neglected in ecology despite its importance in evolutionary theory and its likely impact on species distributions. Here, we extend the adaptive landscape framework to ecological sorting of multidimensional phenotypes across environments and discuss how two analytical approaches can be used to quantify fitness as a function of the interaction between the phenotype and the environment. We encourage ecologists to consider how phenotypic integration will constrain species responses to environmental change.
Analyzing stochastic dependence of cognitive processes in multidimensional source recognition.
Meiser, Thorsten
2014-01-01
Stochastic dependence among cognitive processes can be modeled in different ways, and the family of multinomial processing tree models provides a flexible framework for analyzing stochastic dependence among discrete cognitive states. This article presents a multinomial model of multidimensional source recognition that specifies stochastic dependence by a parameter for the joint retrieval of multiple source attributes together with parameters for stochastically independent retrieval. The new model is equivalent to a previous multinomial model of multidimensional source memory for a subset of the parameter space. An empirical application illustrates the advantages of the new multinomial model of joint source recognition. The new model allows for a direct comparison of joint source retrieval across conditions, it avoids statistical problems due to inflated confidence intervals and does not imply a conceptual imbalance between source dimensions. Model selection criteria that take model complexity into account corroborate the new model of joint source recognition.
Multidimensional profiles of health locus of control in Hispanic Americans.
Champagne, Brian R; Fox, Rina S; Mills, Sarah D; Sadler, Georgia Robins; Malcarne, Vanessa L
2016-10-01
Latent profile analysis identified health locus of control profiles among 436 Hispanic Americans who completed the Multidimensional Health Locus of Control scales. Results revealed four profiles: Internally Oriented-Weak, -Moderate, -Strong, and Externally Oriented. The profile groups were compared on sociocultural and demographic characteristics, health beliefs and behaviors, and physical and mental health outcomes. The Internally Oriented-Strong group had less cancer fatalism, religiosity, and equity health attributions, and more alcohol consumption than the other three groups; the Externally Oriented group had stronger equity health attributions and less alcohol consumption. Deriving multidimensional health locus of control profiles through latent profile analysis allows examination of the relationships of health locus of control subtypes to health variables.
Coherent multidimensional optical spectra measured using incoherent light
NASA Astrophysics Data System (ADS)
Turner, Daniel B.; Arpin, Paul C.; McClure, Scott D.; Ulness, Darin J.; Scholes, Gregory D.
2013-08-01
Four-wave mixing measurements can reveal spectral and dynamics information that is hidden in linear spectra by the interactions among light-absorbing molecules and with their environment. Coherent multidimensional optical spectroscopy is an important variant of four-wave mixing because it resolves a map of interactions and correlations between absorption bands. Previous coherent multidimensional optical spectroscopy measurements have used femtosecond pulses with great success, and it may seem that femtosecond pulses are necessary for such measurements. Here we present coherent two-dimensional electronic spectra measured using incoherent light. The spectra of model molecular systems using broadband spectrally incoherent light are similar but not identical to those expected from measurements using femtosecond pulses. Specifically, the spectra show particular sensitivity to long-lived intermediates such as photoisomers. The results will motivate the design of similar experiments in spectral ranges where femtosecond pulses are difficult to produce.
Multidimensional Analysis of Quenching: Comparison of Inverse Techniques
Dowding, K.J.
1998-11-18
Understanding the surface heat transfer during quenching can be beneficial. Analysis to estimate the surface heat transfer from internal temperature measurements is referred to as the inverse heat conduction problem (IHCP). Function specification and gradient adjoint methods, which use a gradient search method coupled with an adjoint operator, are widely u led methods to solve the IHCP. In this paper the two methods are presented for the multidimensional case. The focus is not a rigorous comparison of numerical results. Instead after formulating the multidimensional solutions, issues associated with the numerical implementation and practical application of the methods are discussed. In addition, an experiment that measured the surface heat flux and temperatures for a transient experimental case is analyzed. Transient temperatures are used to estimate the surface heat flux, which is compared to the measured values. The estimated surface fluxes are comparable for the two methods.
An object-oriented multidimensional model for data warehouse
NASA Astrophysics Data System (ADS)
Gosain, Anjana; Mann, Suman
2011-12-01
Organizations, to have a competitive edge upon each other, resort to business intelligence which refers to information available for enterprise to make strategic decisions. Data warehouse being the repository of data provides the backend for achieving business intelligence. The design of data warehouse, thereby, forms the key, to extract and obtain the relevant information facilitating to make strategic decisions. The initial focus for the design had been upon the conceptual models but now object oriented multidimensional modelling has emerged as the foundation for the designing of data warehouse. Several proposals have been put forth for object oriented multidimensional modelling, each incorporating some or other features, but not all. This paper consolidates all the features previously introduced and the new introduced, thus, proposing a new model having features to be incorporated while designing the data warehouse.
Multidimensional and Multimodal Separations by HPTLC in Phytochemistry
NASA Astrophysics Data System (ADS)
Ciesla, Lukasz; Waksmundzka-Hajnos, Monika
HPTLC is one of the most widely applied methods in phytochemical analysis. It is due to its numerous advantages, e.g., it is the only chromatographic method offering the option of presenting the results as an image. Other advantages include simplicity, low costs, parallel analysis of samples, high sample capacity, rapidly obtained results, and possibility of multiple detection. HPTLC provides identification as well as quantitative results. It also enables the identification of adulterants. In case of complex samples, the resolving power of traditional one-dimensional chromatography is usually inadequate, hence special modes of development are required. Multidimensional and multimodal HPTLC techniques include those realized in one direction (UMD, IMD, GMD, BMD, AMD) as well as typical two-dimensional methods realized on mono- or bi-layers. In this manuscript, an overview on variable multidimensional and multimodal methods, applied in the analysis of phytochemical samples, is presented.
Counting multidimensional objects: implications for the neural-synchrony theory.
Goldfarb, Liat; Treisman, Anne
2013-03-01
It has been suggested that a neural instantiation of the temporary multidimensional representations of objects might be synchrony of firing between the neurons representing the features that co-occur in a given location. In this article, we direct attention to a logical problem that arises when certain synchrony assumptions are applied to real situations in which multiple multidimensional objects are presented. We demonstrate a new behavioral effect that shows that this logical problem coincides with a genuine behavioral problem. Even when a display contains only a small number of objects characterized by features on two dimensions, the representation of the display becomes difficult when, according to our described assumptions, the object representations cannot be simultaneously synchronized on both features. This article outlines a new principle that governs object representation, and the experimental results might be unique behavioral evidence for a neural-based theory of feature binding. PMID:23334446
A Multidimensional Data Warehouse for Community Health Centers
Kunjan, Kislaya; Toscos, Tammy; Turkcan, Ayten; Doebbeling, Brad N.
2015-01-01
Community health centers (CHCs) play a pivotal role in healthcare delivery to vulnerable populations, but have not yet benefited from a data warehouse that can support improvements in clinical and financial outcomes across the practice. We have developed a multidimensional clinic data warehouse (CDW) by working with 7 CHCs across the state of Indiana and integrating their operational, financial and electronic patient records to support ongoing delivery of care. We describe in detail the rationale for the project, the data architecture employed, the content of the data warehouse, along with a description of the challenges experienced and strategies used in the development of this repository that may help other researchers, managers and leaders in health informatics. The resulting multidimensional data warehouse is highly practical and is designed to provide a foundation for wide-ranging healthcare data analytics over time and across the community health research enterprise. PMID:26958297
Analysis of self-similar solutions of multidimensional conservation laws
Keyfitz, Barbara
2014-02-15
This project focused on analysis of multidimensional conservation laws, specifically on extensions to the study of self-siminar solutions, a project initiated by the PI. In addition, progress was made on an approach to studying conservation laws of very low regularity; in this research, the context was a novel problem in chromatography. Two graduate students in mathematics were supported during the grant period, and have almost completed their thesis research.
Probes for multidimensional nanospectroscopic imaging and methods of fabrication thereof
Weber-Bargioni, Alexander; Cabrini, Stefano; Bao, Wei; Melli, Mauro; Yablonovitch, Eli; Schuck, Peter J
2015-03-17
This disclosure provides systems, methods, and apparatus related to probes for multidimensional nanospectroscopic imaging. In one aspect, a method includes providing a transparent tip comprising a dielectric material. A four-sided pyramidal-shaped structure is formed at an apex of the transparent tip using a focused ion beam. Metal layers are deposited over two opposing sides of the four-sided pyramidal-shaped structure.
Unveiling Bacterial Interactions through Multidimensional Scaling and Dynamics Modeling
Dorado-Morales, Pedro; Vilanova, Cristina; P. Garay, Carlos; Martí, Jose Manuel; Porcar, Manuel
2015-01-01
We propose a new strategy to identify and visualize bacterial consortia by conducting replicated culturing of environmental samples coupled with high-throughput sequencing and multidimensional scaling analysis, followed by identification of bacteria-bacteria correlations and interactions. We conducted a proof of concept assay with pine-tree resin-based media in ten replicates, which allowed detecting and visualizing dynamical bacterial associations in the form of statistically significant and yet biologically relevant bacterial consortia. PMID:26671778
Multidimensional signal modulation and/or demodulation for data communications
Smith, Stephen F.; Dress, William B.
2008-03-04
Systems and methods are described for multidimensional signal modulation and/or demodulation for data communications. A method includes modulating a carrier signal in a first domain selected from the group consisting of phase, frequency, amplitude, polarization and spread; modulating the carrier signal in a second domain selected from the group consisting of phase, frequency, amplitude, polarization and spread; and modulating the carrier signal in a third domain selected from the group consisting of phase, frequency, amplitude, polarization and spread.
Application of Multidimensional Spectrum Analysis for Analytical Chemistry
Hatsukawa, Yuichi; Hayakawa, Takehito; Toh, Yosuke; Shinohara, Nobuo; Oshima, Masumi
1999-12-31
Feasibility of application of the multidimensional {gamma} ray spectroscopy for analytical chemistry was examined. Two reference igneous rock (JP-1, JB-1a) samples issued by the Geological Survey of Japan (GSJ) were irradiated at a research reactor with thermal neutrons, and {gamma} rays from the radioisotopes produced by neutron capture reactions were measured using a {gamma}-ray detector array. Simultaneously 27 elements were observed with no chemical separation.
Multidimensional, multiphysics simulations of core-collapse supernovae
Messer, Bronson; Mezzacappa, Anthony; Blondin, J. M.; Bruenn, S. W.; Hix, William Raphael
2008-01-01
CHIMERA is a multi-dimensional radiation hydrodynamics code designed to study core-collapse supernovae. The code is made up of three essentially independent parts: a hydrodynamics module, a nuclear burning module, and a neutrino transport solver combined within an operator-split approach. We review the code s architecture and some recently improved implementations used in the code. We also briefly discuss preliminary results obtained with the code in three spatial dimensions.
Multidimensional, multiphysics simulations of core-collapse supernovae
Messer, Bronson; Mezzacappa, Anthony; Blondin, J. M.; Bruenn, S. W.; Hix, William Raphael
2008-01-01
CHIMERA is a multi-dimensional radiation hydrodynamics code designed to study core-collapse supernovae. The code is made up of three essentially independent parts: a hydrodynamics module, a nuclear burning module, and a neutrino transport solver combined within an operator-split approach. We review the code's architecture and some recently improved implementations used in the code. We also briefly discuss preliminary results obtained with the code in three spatial dimensions.
A preliminary report on the development of MATLAB tensor classes for fast algorithm prototyping.
Bader, Brett William; Kolda, Tamara Gibson
2004-07-01
We describe three MATLAB classes for manipulating tensors in order to allow fast algorithm prototyping. A tensor is a multidimensional or N-way array. We present a tensor class for manipulating tensors which allows for tensor multiplication and 'matricization.' We have further added two classes for representing tensors in decomposed format: cp{_}tensor and tucker{_}tensor. We demonstrate the use of these classes by implementing several algorithms that have appeared in the literature.
Multidimensionality in host manipulation mimicked by serotonin injection.
Perrot-Minnot, Marie-Jeanne; Sanchez-Thirion, Kevin; Cézilly, Frank
2014-12-01
Manipulative parasites often alter the phenotype of their hosts along multiple dimensions. 'Multidimensionality' in host manipulation could consist in the simultaneous alteration of several physiological pathways independently of one another, or proceed from the disruption of some key physiological parameter, followed by a cascade of effects. We compared multidimensionality in 'host manipulation' between two closely related amphipods, Gammarus fossarum and Gammarus pulex, naturally and experimentally infected with Pomphorhynchus laevis (Acanthocephala), respectively. To that end, we calculated in each host-parasite association the effect size of the difference between infected and uninfected individuals for six different traits (activity, phototaxis, geotaxis, attraction to conspecifics, refuge use and metabolic rate). The effects sizes were highly correlated between host-parasite associations, providing evidence for a relatively constant 'infection syndrome'. Using the same methodology, we compared the extent of phenotypic alterations induced by an experimental injection of serotonin (5-HT) in uninfected G. pulex to that induced by experimental or natural infection with P. laevis. We observed a significant correlation between effect sizes across the six traits, indicating that injection with 5-HT can faithfully mimic the 'infection syndrome'. This is, to our knowledge, the first experimental evidence that multidimensionality in host manipulation can proceed, at least partly, from the disruption of some major physiological mechanism.
Multidimensional colorimetric sensor array for discrimination of proteins.
Mao, Jinpeng; Lu, Yuexiang; Chang, Ning; Yang, Jiaoe; Zhang, Sichun; Liu, Yueying
2016-12-15
An extensible multidimensional colorimetric sensor array for the detection of protein is developed based on DNA functionalized gold nanoparticles (DNA-AuNPs) as receptors. In the presence of different proteins, the aggregation behavior of DNA-AuNPs was regulated by the high concentrations of salt and caused different color change; while DNA-AuNPs grew induced by the reduction of HAuCl4 and NH2OH as a reductant on the surface of nanoparticles exhibited different morphologies and color appearance for different proteins. The transducers based on AuNPs modified by specific and nonspecific DNA enables naked-eye discrimination of the target analytes. This extensible sensing platform with only two receptors could simultaneously discriminate ten native proteins and their thermally denatured conformations using hierarchical cluster analysis (HCA) at the concentration of 50nM with 100% accuracy. This opens up the possibility of the sensor array to investigate the different conformational changes of biomacromolecules, and it gives a new direction of developing multidimensional transduction principles based on plasmonic nanoparticle conjugates. Furthermore, the sensing system could discriminate proteins at the concentration of 500nM in the presence of 50% human urine, which indicated this sensor array has great potential ability in analyzing real biological fluids. In addition, the multidimensional colorimetric sensor array is suitable for analysis of target analytes in the resource-restricted regions because of rapid, simple, low cost, and in-field detection with the naked eye. PMID:27322936
Multidimensionality in host manipulation mimicked by serotonin injection.
Perrot-Minnot, Marie-Jeanne; Sanchez-Thirion, Kevin; Cézilly, Frank
2014-12-01
Manipulative parasites often alter the phenotype of their hosts along multiple dimensions. 'Multidimensionality' in host manipulation could consist in the simultaneous alteration of several physiological pathways independently of one another, or proceed from the disruption of some key physiological parameter, followed by a cascade of effects. We compared multidimensionality in 'host manipulation' between two closely related amphipods, Gammarus fossarum and Gammarus pulex, naturally and experimentally infected with Pomphorhynchus laevis (Acanthocephala), respectively. To that end, we calculated in each host-parasite association the effect size of the difference between infected and uninfected individuals for six different traits (activity, phototaxis, geotaxis, attraction to conspecifics, refuge use and metabolic rate). The effects sizes were highly correlated between host-parasite associations, providing evidence for a relatively constant 'infection syndrome'. Using the same methodology, we compared the extent of phenotypic alterations induced by an experimental injection of serotonin (5-HT) in uninfected G. pulex to that induced by experimental or natural infection with P. laevis. We observed a significant correlation between effect sizes across the six traits, indicating that injection with 5-HT can faithfully mimic the 'infection syndrome'. This is, to our knowledge, the first experimental evidence that multidimensionality in host manipulation can proceed, at least partly, from the disruption of some major physiological mechanism. PMID:25339729
Interdisciplinary hospice team processes and multidimensional pain: a qualitative study.
Dugan Day, Michele
2012-01-01
Hospice teams may address multidimensional pain through the synergistic interaction of team members from various professional disciplines during regularly scheduled team meetings. However, the occurrence of that critical exchange has not been adequately described or documented. The purpose of this qualitative study was to explore two processes in team pain palliation: communication and collaboration. Data were gathered through individual interviews and a 1-year observation of team members from two hospices (physicians, nurses, aides, chaplains, social workers). Utilizing constant comparison, 14 final thematic categories were discovered. Use of biopsychosocial/spiritual terms by all team members meant that the team had the common language needed to communicate about multidimensional pain. Interviews and observation revealed a gap in translating multidisciplinary communication in team meetings into collaborative acts for pain treatment. In addition, structural influences inhibited creativity in pain palliation. There was no mutual understanding of the purpose for team meetings, no recognition of the need to reflect on team process, or common definition of leadership. Social work roles in hospice should include leadership that moves teams toward interdisciplinary care for multidimensional pain.
Multidimensional EEMD filter bank for geophysical data processing
NASA Astrophysics Data System (ADS)
Jeng, Yih; Chen, Chih-Sung; Lee, Chao-Shing
2014-05-01
The ensemble empirical mode decomposition (EEMD) algorithm is a noise-assisted data-driven nonlinear analysis method evolved from its original version, the empirical mode decomposition (EMD) method. The advantage of using EEMD is mainly to alleviate mode mixing problem of the EMD filter bank. The EMD and EEMD techniques have been widely applied to many fields of scientific and engineering studies in the last decade but just a few to the geophysical exploration data analysis probably due to the multidimensional feature of exploration data. Several 2D EMD based data analysis algorithms have been developed lately; however, the difficulty of sifting 2D data and the mode mixing problem inherited from EMD algorithm hindered their further developments. To deal with the stated issues, we modify a newer technique, the multidimensional ensemble empirical mode decomposition (MDEEMD) algorithm, to achieve a 2D EEMD filter bank for exploration data signal enhancement. With the data reconstructed by using significant components of the filter bank, the signal embedded in the original data can be retrieved successfully. Furthermore, we compare the performance of MDEEMD with that of logarithmic transformed multidimensional empirical mode decomposition (NLT MDEMD) to find a solution for compromising computation cost. A controlled model study along with a set of real exploration data example are provided to demonstrate the robustness of the proposed method.
An Improved Multidimensional MPA Procedure for Bidirectional Earthquake Excitations
Wang, Feng; Sun, Jian-Gang; Zhang, Ning
2014-01-01
Presently, the modal pushover analysis procedure is extended to multidimensional analysis of structures subjected to multidimensional earthquake excitations. an improved multidimensional modal pushover analysis (IMMPA) method is presented in the paper in order to estimate the response demands of structures subjected to bidirectional earthquake excitations, in which the unidirectional earthquake excitation applied on equivalent SDOF system is replaced by the direct superposition of two components earthquake excitations, and independent analysis in each direction is not required and the application of simplified superposition formulas is avoided. The strength reduction factor spectra based on superposition of earthquake excitations are discussed and compared with the traditional strength reduction factor spectra. The step-by-step procedure is proposed to estimate seismic demands of structures. Two examples are implemented to verify the accuracy of the method, and the results of the examples show that (1) the IMMPA method can be used to estimate the responses of structure subjected to bidirectional earthquake excitations. (2) Along with increase of peak of earthquake acceleration, structural response deviation estimated with the IMMPA method may also increase. (3) Along with increase of the number of total floors of structures, structural response deviation estimated with the IMMPA method may also increase. PMID:25140333
An improved multidimensional MPA procedure for bidirectional earthquake excitations.
Wang, Feng; Sun, Jian-Gang; Zhang, Ning
2014-01-01
Presently, the modal pushover analysis procedure is extended to multidimensional analysis of structures subjected to multidimensional earthquake excitations. an improved multidimensional modal pushover analysis (IMMPA) method is presented in the paper in order to estimate the response demands of structures subjected to bidirectional earthquake excitations, in which the unidirectional earthquake excitation applied on equivalent SDOF system is replaced by the direct superposition of two components earthquake excitations, and independent analysis in each direction is not required and the application of simplified superposition formulas is avoided. The strength reduction factor spectra based on superposition of earthquake excitations are discussed and compared with the traditional strength reduction factor spectra. The step-by-step procedure is proposed to estimate seismic demands of structures. Two examples are implemented to verify the accuracy of the method, and the results of the examples show that (1) the IMMPA method can be used to estimate the responses of structure subjected to bidirectional earthquake excitations. (2) Along with increase of peak of earthquake acceleration, structural response deviation estimated with the IMMPA method may also increase. (3) Along with increase of the number of total floors of structures, structural response deviation estimated with the IMMPA method may also increase. PMID:25140333
Igloo-Plot: a tool for visualization of multidimensional datasets.
Kuntal, Bhusan K; Ghosh, Tarini Shankar; Mande, Sharmila S
2014-01-01
Advances in science and technology have resulted in an exponential growth of multivariate (or multi-dimensional) datasets which are being generated from various research areas especially in the domain of biological sciences. Visualization and analysis of such data (with the objective of uncovering the hidden patterns therein) is an important and challenging task. We present a tool, called Igloo-Plot, for efficient visualization of multidimensional datasets. The tool addresses some of the key limitations of contemporary multivariate visualization and analysis tools. The visualization layout, not only facilitates an easy identification of clusters of data-points having similar feature compositions, but also the 'marker features' specific to each of these clusters. The applicability of the various functionalities implemented herein is demonstrated using several well studied multi-dimensional datasets. Igloo-Plot is expected to be a valuable resource for researchers working in multivariate data mining studies. Igloo-Plot is available for download from: http://metagenomics.atc.tcs.com/IglooPlot/.
Theme section: Multi-dimensional modelling, analysis and visualization
NASA Astrophysics Data System (ADS)
Guilbert, Éric; Çöltekin, Arzu; Castro, Francesc Antón; Pettit, Chris
2016-07-01
Spatial data are now collected and processed in larger amounts, and used by larger populations than ever before. While most geospatial data have traditionally been recorded as two-dimensional data, the evolution of data collection methods and user demands have led to data beyond the two dimensions describing complex multidimensional phenomena. An example of the relevance of multidimensional modelling is seen with the development of urban modelling where several dimensions have been added to the traditional 2D map representation (Sester et al., 2011). These include obviously the third spatial dimension (Biljecki et al., 2015) as well as the temporal, but also the scale dimension (Van Oosterom and Stoter, 2010) or, as mentioned by (Lu et al., 2016), multi-spectral and multi-sensor data. Such a view provides an organisation of multidimensional data around these different axes and it is time to explore each axis as the availability of unprecedented amounts of new data demands new solutions. The availability of such large amounts of data induces an acute need for developing new approaches to assist with their dissemination, visualisation, and analysis by end users. Several issues need to be considered in order to provide a meaningful representation and assist in data visualisation and mining, modelling and analysis; such as data structures allowing representation at different scales or in different contexts of thematic information.
Grey Ballard, Austin Benson
2014-11-26
This software provides implementations of fast matrix multiplication algorithms. These algorithms perform fewer floating point operations than the classical cubic algorithm. The software uses code generation to automatically implement the fast algorithms based on high-level descriptions. The code serves two general purposes. The first is to demonstrate that these fast algorithms can out-perform vendor matrix multiplication algorithms for modest problem sizes on a single machine. The second is to rapidly prototype many variations of fast matrix multiplication algorithms to encourage future research in this area. The implementations target sequential and shared memory parallel execution.
Fitch, Alistair J; Kadyrov, Alexander; Christmas, William J; Kittler, Josef
2005-08-01
A new, fast, statistically robust, exhaustive, translational image-matching technique is presented: fast robust correlation. Existing methods are either slow or non-robust, or rely on optimization. Fast robust correlation works by expressing a robust matching surface as a series of correlations. Speed is obtained by computing correlations in the frequency domain. Computational cost is analyzed and the method is shown to be fast. Speed is comparable to conventional correlation and, for large images, thousands of times faster than direct robust matching. Three experiments demonstrate the advantage of the technique over standard correlation.
Gavrankapetanović, F
1997-01-01
Fasting (arabic-savm) was proclaimed through islam, and thus it is an obligation for Holly Prophet Muhammad s.a.v.s.-Peace be to Him-in the second year after Hijra (in 624 after Milad-born of Isa a.s.). There is a month of fasting-Ramadan-each lunar (hijra) year. So, it was 1415th fasting this year. Former Prophets have brought obligative messages on fasting to their people; so there are also certain forms of fasting with other religions i.e. with Catholics, Jews, Orthodox. These kinds of fasting above differ from muslim fasting, but they also appear obligative. All revelations have brought fasting as obligative. From medical point of view, fasting has two basical components: psychical and physical. Psychical sphere correlate closely with its fundamental ideological message. Allah dz.s. says in Quran: "... Fasting is obligative for you, as it was obligative to your precedents, as to avoid sins; during very few days (II, II, 183 & 184)." Will strength, control of passions, effort and self-discipline makes a pure faithfull person, who purify its mind and body through fasting. Thinking about The Creator is more intensive, character is more solid; and spirit and will get stronger. We will mention the hadith saying: "Essaihune humus saimun!" That means: "Travellers at the Earth are fasters (of my ummet)." The commentary of this hadith, in the Collection of 1001 hadiths (Bin bir hadis), number 485, says: "There are no travelling dervishs or monks in islam; thus there is no such a kind of relligousity in islam. In stead, it is changed by fasting and constant attending of mosque. That was proclaimed as obligation, although there were few cases of travelling in the name of relligousity, like travelling dervishs and sheichs." In this paper, the author discusses medical aspects of fasting and its positive characteristics in the respect of healthy life style and prevention of many sicks. The author mentions positive influence of fasting to certain system and organs of human
Integrative Physiology of Fasting.
Secor, Stephen M; Carey, Hannah V
2016-04-01
Extended bouts of fasting are ingrained in the ecology of many organisms, characterizing aspects of reproduction, development, hibernation, estivation, migration, and infrequent feeding habits. The challenge of long fasting episodes is the need to maintain physiological homeostasis while relying solely on endogenous resources. To meet that challenge, animals utilize an integrated repertoire of behavioral, physiological, and biochemical responses that reduce metabolic rates, maintain tissue structure and function, and thus enhance survival. We have synthesized in this review the integrative physiological, morphological, and biochemical responses, and their stages, that characterize natural fasting bouts. Underlying the capacity to survive extended fasts are behaviors and mechanisms that reduce metabolic expenditure and shift the dependency to lipid utilization. Hormonal regulation and immune capacity are altered by fasting; hormones that trigger digestion, elevate metabolism, and support immune performance become depressed, whereas hormones that enhance the utilization of endogenous substrates are elevated. The negative energy budget that accompanies fasting leads to the loss of body mass as fat stores are depleted and tissues undergo atrophy (i.e., loss of mass). Absolute rates of body mass loss scale allometrically among vertebrates. Tissues and organs vary in the degree of atrophy and downregulation of function, depending on the degree to which they are used during the fast. Fasting affects the population dynamics and activities of the gut microbiota, an interplay that impacts the host's fasting biology. Fasting-induced gene expression programs underlie the broad spectrum of integrated physiological mechanisms responsible for an animal's ability to survive long episodes of natural fasting. PMID:27065168
Gelman, Hannah; Gruebele, Martin
2014-01-01
Fast folding proteins have been a major focus of computational and experimental study because they are accessible to both techniques: they are small and fast enough to be reasonably simulated with current computational power, but have dynamics slow enough to be observed with specially developed experimental techniques. This coupled study of fast folding proteins has provided insight into the mechanisms which allow some proteins to find their native conformation well less than 1 ms and has uncovered examples of theoretically predicted phenomena such as downhill folding. The study of fast folders also informs our understanding of even “slow” folding processes: fast folders are small, relatively simple protein domains and the principles that govern their folding also govern the folding of more complex systems. This review summarizes the major theoretical and experimental techniques used to study fast folding proteins and provides an overview of the major findings of fast folding research. Finally, we examine the themes that have emerged from studying fast folders and briefly summarize their application to protein folding in general as well as some work that is left to do. PMID:24641816
O'Brien, Travis A.; Kashinath, Karthik
2015-05-22
This software implements the fast, self-consistent probability density estimation described by O'Brien et al. (2014, doi: ). It uses a non-uniform fast Fourier transform technique to reduce the computational cost of an objective and self-consistent kernel density estimation method.
Trueland, Jennifer
2013-12-18
The 5.2 diet involves two days of fasting each week. It is being promoted as the key to sustained weight loss, as well as wider health benefits, despite the lack of evidence on the long-term effects. Nurses need to support patients who wish to try intermittent fasting. PMID:24345130
NASA Astrophysics Data System (ADS)
Zhao, Yongli; Ji, Yuefeng; Zhang, Jie; Li, Hui; Xiong, Qianjin; Qiu, Shaofeng
2014-08-01
Ultrahigh throughout capacity requirement is challenging the current optical switching nodes with the fast development of data center networks. Pbit/s level all optical switching networks need to be deployed soon, which will cause the high complexity of node architecture. How to control the future network and node equipment together will become a new problem. An enhanced Software Defined Networking (eSDN) control architecture is proposed in the paper, which consists of Provider NOX (P-NOX) and Node NOX (N-NOX). With the cooperation of P-NOX and N-NOX, the flexible control of the entire network can be achieved. All optical switching network testbed has been experimentally demonstrated with efficient control of enhanced Software Defined Networking (eSDN). Pbit/s level all optical switching nodes in the testbed are implemented based on multi-dimensional switching architecture, i.e. multi-level and multi-planar. Due to the space and cost limitation, each optical switching node is only equipped with four input line boxes and four output line boxes respectively. Experimental results are given to verify the performance of our proposed control and switching architecture.
Pardo, Zulay D.; Olsen, Greg; Fernández-Valle, María Encarnación; Frydman, Lucio; Martínez-Álvarez, Roberto; Herrera, Antonio
2016-01-01
Recent years have witnessed unprecedented advances in the development of fast multidimensional NMR acquisition techniques. This progress could open valuable new opportunities for the elucidation of chemical and biochemical processes. This study demonstrates one such capability, with the first real-time 2D dynamic analysis of a complex organic reaction relying on unlabeled substrates. Implementing such measurements required the development of new ultrafast 2D methods, capable of monitoring multiple spectral regions of interest as the reaction progressed. The alternate application of these acquisitions in an interleaved, excitation-optimized fashion, allowed us to extract new structural and dynamic insight concerning the reaction between aliphatic ketones and triflic anhydride in the presence of nitriles to yield alkylpyrimidines. Up to 2500 2D NMR data sets were thus collected over the course of this nearly 100 min long reaction, in an approach resembling that used in functional magnetic resonance imaging. With the aid of these new frequency-selective low-gradient-strength experiments, supplemented by chemical shift calculations of the spectral coordinates observed in the 2D heteronuclear correlations, previously postulated intermediates involved in the alkylpyrimidine formation process could be confirmed, and hitherto undetected ones were revealed. The potential and limitations of the resulting methods are discussed. PMID:22283498
Seismic interferometry by multidimensional deconvolution without wavefield separation
NASA Astrophysics Data System (ADS)
Ravasi, Matteo; Meles, Giovanni; Curtis, Andrew; Rawlinson, Zara; Yikuo, Liu
2015-07-01
Seismic interferometry comprises a suite of methods to redatum recorded wavefields to those that would have been recorded if different sources (so-called virtual sources) had been activated. Seismic interferometry by cross-correlation has been formulated using either two-way (for full wavefields) or one-way (for directionally decomposed wavefields) representation theorems. To obtain improved Green's function estimates, the cross-correlation result can be deconvolved by a quantity that identifies the smearing of the virtual source in space and time, the so-called point-spread function. This type of interferometry, known as interferometry by multidimensional deconvolution (MDD), has so far been applied only to one-way directionally decomposed fields, requiring accurate wavefield decomposition from dual (e.g. pressure and velocity) recordings. Here we propose a form of interferometry by multidimensional deconvolution that uses full wavefields with two-way representations, and simultaneously invert for pressure and (normal) velocity Green's functions, rather than only velocity responses as for its one-way counterpart. Tests on synthetic data show that two-way MDD improves on results of interferometry by cross-correlation, and generally produces estimates of similar quality to those obtained by one-way MDD, suggesting that the preliminary decomposition into up- and downgoing components of the pressure field is not required if pressure and velocity data are jointly used in the deconvolution. We also show that constraints on the directionality of the Green's functions sought can be added directly into the MDD inversion process to further improve two-way multidimensional deconvolution. Finally, as a by-product of having pressure and particle velocity measurements, we adapt one- and two-way representation theorems to convert any particle velocity receiver into its corresponding virtual dipole/gradient source by means of MDD. Thus data recorded from standard monopolar (e
Sakurai, Atsunori; Tanimura, Yoshitaka
2011-04-28
To investigate the role of quantum effects in vibrational spectroscopies, we have carried out numerically exact calculations of linear and nonlinear response functions for an anharmonic potential system nonlinearly coupled to a harmonic oscillator bath. Although one cannot carry out the quantum calculations of the response functions with full molecular dynamics (MD) simulations for a realistic system which consists of many molecules, it is possible to grasp the essence of the quantum effects on the vibrational spectra by employing a model Hamiltonian that describes an intra- or intermolecular vibrational motion in a condensed phase. The present model fully includes vibrational relaxation, while the stochastic model often used to simulate infrared spectra does not. We have employed the reduced quantum hierarchy equations of motion approach in the Wigner space representation to deal with nonperturbative, non-Markovian, and nonsecular system-bath interactions. Taking the classical limit of the hierarchy equations of motion, we have obtained the classical equations of motion that describe the classical dynamics under the same physical conditions as in the quantum case. By comparing the classical and quantum mechanically calculated linear and multidimensional spectra, we found that the profiles of spectra for a fast modulation case were similar, but different for a slow modulation case. In both the classical and quantum cases, we identified the resonant oscillation peak in the spectra, but the quantum peak shifted to the red compared with the classical one if the potential is anharmonic. The prominent quantum effect is the 1-2 transition peak, which appears only in the quantum mechanically calculated spectra as a result of anharmonicity in the potential or nonlinearity of the system-bath coupling. While the contribution of the 1-2 transition is negligible in the fast modulation case, it becomes important in the slow modulation case as long as the amplitude of the
Enhancing Privacy in Participatory Sensing Applications with Multidimensional Data
Forrest, Stephanie; He, Wenbo; Groat, Michael; Edwards, Benjamin; Horey, James L
2013-01-01
Participatory sensing applications rely on individuals to share personal data to produce aggregated models and knowledge. In this setting, privacy concerns can discourage widespread adoption of new applications. We present a privacy-preserving participatory sensing scheme based on negative surveys for both continuous and multivariate categorical data. Without relying on encryption, our algorithms enhance the privacy of sensed data in an energy and computation efficient manner. Simulations and implementation on Android smart phones illustrate how multidimensional data can be aggregated in a useful and privacy-enhancing manner.
Intrinsic irreversibility limits the efficiency of multidimensional molecular motors.
Jack, M W; Tumlin, C
2016-05-01
We consider the efficiency limits of Brownian motors able to extract work from the temperature difference between reservoirs or from external thermodynamic forces. These systems can operate in a variety of modes, including as isothermal engines, heat engines, refrigerators, and heat pumps. We derive analytical results showing that certain classes of multidimensional Brownian motor, including the Smoluchowski-Feynman ratchet, are unable to attain perfect efficiency (Carnot efficiency for heat engines). This demonstrates the presence of intrinsic irreversibilities in their operating mechanism. We present numerical simulations showing that in some cases the loss process that limits efficiency is associated with vortices in the probability current.
Multi-dimensional ENO schemes for general geometries
NASA Technical Reports Server (NTRS)
Harten, Ami; Chakravarthy, Sukumar R.
1991-01-01
A class of ENO schemes is presented for the numerical solution of multidimensional hyperbolic systems of conservation laws in structured and unstructured grids. This is a class of shock-capturing schemes which are designed to compute cell-averages to high order accuracy. The ENO scheme is composed of a piecewise-polynomial reconstruction of the solution form its given cell-averages, approximate evolution of the resulting initial value problem, and averaging of this approximate solution over each cell. The reconstruction algorithm is based on an adaptive selection of stencil for each cell so as to avoid spurious oscillations near discontinuities while achieving high order of accuracy away from them.
Multi-Scale Multi-Dimensional Ion Battery Performance Model
2007-05-07
The Multi-Scale Multi-Dimensional (MSMD) Lithium Ion Battery Model allows for computer prediction and engineering optimization of thermal, electrical, and electrochemical performance of lithium ion cells with realistic geometries. The model introduces separate simulation domains for different scale physics, achieving much higher computational efficiency compared to the single domain approach. It solves a one dimensional electrochemistry model in a micro sub-grid system, and captures the impacts of macro-scale battery design factors on cell performance and materialmore » usage by solving cell-level electron and heat transports in a macro grid system.« less
Multidimensional electron-photon transport with standard discrete ordinates codes
Drumm, C.R.
1995-12-31
A method is described for generating electron cross sections that are compatible with standard discrete ordinates codes without modification. There are many advantages of using an established discrete ordinates solver, e.g. immediately available adjoint capability. Coupled electron-photon transport capability is needed for many applications, including the modeling of the response of electronics components to space and man-made radiation environments. The cross sections have been successfully used in the DORT, TWODANT and TORT discrete ordinates codes. The cross sections are shown to provide accurate and efficient solutions to certain multidimensional electronphoton transport problems.
Overview of the BISON Multidimensional Fuel Performance Code
R. L. Williamson; J. D. Hales; S. R. Novascone; B. W. Spencer; D. M. Perez; G. Pastore; R. C. Martineau
2013-10-01
BISON is a modern multidimensional multiphysics finite-element based nuclear fuel performance code that has been under development at the Idaho National Laboratory (USA) since 2009. A brief background is provided on the code’s computational framework (MOOSE), governing equations, and material and behavioral models. Ongoing code verification and validation work is outlined, and comparative results are provided for select validation cases. Recent applications are discussed, including specific description of two applications where 3D treatment is important. A summary of future code development and validation activities is given. Numerous references to published work are provided where interested readers can find more complete information.
Analysis of world economic variables using multidimensional scaling.
Machado, J A Tenreiro; Mata, Maria Eugénia
2015-01-01
Waves of globalization reflect the historical technical progress and modern economic growth. The dynamics of this process are here approached using the multidimensional scaling (MDS) methodology to analyze the evolution of GDP per capita, international trade openness, life expectancy, and education tertiary enrollment in 14 countries. MDS provides the appropriate theoretical concepts and the exact mathematical tools to describe the joint evolution of these indicators of economic growth, globalization, welfare and human development of the world economy from 1977 up to 2012. The polarization dance of countries enlightens the convergence paths, potential warfare and present-day rivalries in the global geopolitical scene.
Intrinsic irreversibility limits the efficiency of multidimensional molecular motors
NASA Astrophysics Data System (ADS)
Jack, M. W.; Tumlin, C.
2016-05-01
We consider the efficiency limits of Brownian motors able to extract work from the temperature difference between reservoirs or from external thermodynamic forces. These systems can operate in a variety of modes, including as isothermal engines, heat engines, refrigerators, and heat pumps. We derive analytical results showing that certain classes of multidimensional Brownian motor, including the Smoluchowski-Feynman ratchet, are unable to attain perfect efficiency (Carnot efficiency for heat engines). This demonstrates the presence of intrinsic irreversibilities in their operating mechanism. We present numerical simulations showing that in some cases the loss process that limits efficiency is associated with vortices in the probability current.
Analysis of world economic variables using multidimensional scaling.
Machado, J A Tenreiro; Mata, Maria Eugénia
2015-01-01
Waves of globalization reflect the historical technical progress and modern economic growth. The dynamics of this process are here approached using the multidimensional scaling (MDS) methodology to analyze the evolution of GDP per capita, international trade openness, life expectancy, and education tertiary enrollment in 14 countries. MDS provides the appropriate theoretical concepts and the exact mathematical tools to describe the joint evolution of these indicators of economic growth, globalization, welfare and human development of the world economy from 1977 up to 2012. The polarization dance of countries enlightens the convergence paths, potential warfare and present-day rivalries in the global geopolitical scene. PMID:25811177
Revealing and Characterizing Dark Excitons through Coherent Multidimensional Spectroscopy.
Tollerud, Jonathan O; Cundiff, Steven T; Davis, Jeffrey A
2016-08-26
Dark excitons are of fundamental importance in a broad range of contexts but are difficult to study using conventional optical spectroscopy due to their weak interaction with light. We show how coherent multidimensional spectroscopy can reveal and characterize dark states. Using this approach, we identify parity-forbidden and spatially indirect excitons in InGaAs/GaAs quantum wells and determine details regarding lifetimes, homogeneous and inhomogeneous linewidths, broadening mechanisms, and coupling strengths. The observations of coherent coupling between these states and bright excitons hint at a role for a multistep process by which excitons in the barrier can relax into the quantum wells. PMID:27610881
A multidimensional approach for selecting child care workers.
Jones, J W; Joy, D S; Martin, S L
1990-10-01
A multidimensional selection battery was designed to predict a variety of criteria important in the selection of child care workers. The battery assesses constructs related to honesty, violence, substance abuse, emotional stability and safety. A series of studies were used to test the validity of the selection battery. Scores on the test battery were compared with those from three alternative selection procedures to define the measured constructs. Three additional studies show the relation of scores on the selection battery and the behavior of child care workers. The test battery was correlated with the job performance of child care workers and identified adults convicted for sexual offenses against minors. PMID:2263707
Multi-dimensional Hermite polynomials in quantum optics
NASA Astrophysics Data System (ADS)
Kok, Pieter; Braunstein, Samuel L.
2001-08-01
We study a class of optical circuits with vacuum input states consisting of Gaussian sources without coherent displacements such as down-converters and squeezers, together with photo-detectors and passive interferometry (beamsplitters, polarization rotations, phase-shifters, etc). We show that the outgoing state leaving the optical circuit can be expressed in terms of so-called multi-dimensional Hermite polynomials and give their recursion and orthogonality relations. We show how quantum teleportation of single-photon polarization states can be modelled using this description.
Intrinsic irreversibility limits the efficiency of multidimensional molecular motors.
Jack, M W; Tumlin, C
2016-05-01
We consider the efficiency limits of Brownian motors able to extract work from the temperature difference between reservoirs or from external thermodynamic forces. These systems can operate in a variety of modes, including as isothermal engines, heat engines, refrigerators, and heat pumps. We derive analytical results showing that certain classes of multidimensional Brownian motor, including the Smoluchowski-Feynman ratchet, are unable to attain perfect efficiency (Carnot efficiency for heat engines). This demonstrates the presence of intrinsic irreversibilities in their operating mechanism. We present numerical simulations showing that in some cases the loss process that limits efficiency is associated with vortices in the probability current. PMID:27300832
Revealing and Characterizing Dark Excitons through Coherent Multidimensional Spectroscopy
NASA Astrophysics Data System (ADS)
Tollerud, Jonathan O.; Cundiff, Steven T.; Davis, Jeffrey A.
2016-08-01
Dark excitons are of fundamental importance in a broad range of contexts but are difficult to study using conventional optical spectroscopy due to their weak interaction with light. We show how coherent multidimensional spectroscopy can reveal and characterize dark states. Using this approach, we identify parity-forbidden and spatially indirect excitons in InGaAs/GaAs quantum wells and determine details regarding lifetimes, homogeneous and inhomogeneous linewidths, broadening mechanisms, and coupling strengths. The observations of coherent coupling between these states and bright excitons hint at a role for a multistep process by which excitons in the barrier can relax into the quantum wells.
Nursing care systematization as a multidimensional and interactive phenomenon.
Backes, Dirce Stein; Koerich, Magda Santos; Nascimento, Keyla Cristiane do; Erdmann, Alacoque Lorenzini
2008-01-01
This study aimed to understand the meaning of Nursing Care Systematization (NCS) for multiprofessional health team professionals based on the relationships, interactions and associations of Complex thought. This qualitative study uses Grounded Theory as a methodological reference framework. Data were obtained through interviews with three sample groups, totaling 15 professionals from different institutions. Simultaneous data codification and analysis identified the central theme: 'Glimpsing nursing care systematization as an interactive and multidimensional phenomenon' and the respective reference model. NCS appoints, in addition to interactivity and professional complementarity, the importance of dialog and connection between the academy, health practices and regulatory offices, based on new reference frameworks for the organization of health practices.
Multidimensional electronic spectroscopy of phycobiliproteins from cryptophyte algae
NASA Astrophysics Data System (ADS)
Turner, Daniel
2011-03-01
We describe new spectroscopic measurements which reveal additional information regarding the observed quantum coherences in proteins extracted from photosynthetic algae. The proteins we investigate are the phycobiliproteins phycoerythrin 545 and phycocyanin 645. Two new avenues have been explored. We describe how changes to the chemical and biological environment impact the quantum coherence present in the 2D electronic correlation spectrum. We also use new multidimensional spectroscopic techniques to reveal insights into the nature of the quantum coherence and the nature of the participating states.
Analysis of World Economic Variables Using Multidimensional Scaling
Machado, J.A. Tenreiro; Mata, Maria Eugénia
2015-01-01
Waves of globalization reflect the historical technical progress and modern economic growth. The dynamics of this process are here approached using the multidimensional scaling (MDS) methodology to analyze the evolution of GDP per capita, international trade openness, life expectancy, and education tertiary enrollment in 14 countries. MDS provides the appropriate theoretical concepts and the exact mathematical tools to describe the joint evolution of these indicators of economic growth, globalization, welfare and human development of the world economy from 1977 up to 2012. The polarization dance of countries enlightens the convergence paths, potential warfare and present-day rivalries in the global geopolitical scene. PMID:25811177
FastBit: An Efficient Indexing Technology For AcceleratingData-Intensive Science
Wu, Kesheng
2005-06-27
FastBit is a software tool for searching large read-only data sets. It organizes user data in a column-oriented structure which is efficient for on-line analytical processing (OLAP), and utilizes compressed bitmap indices to further speed up query processing. Analyses have proven the compressed bitmap index used in FastBit to be theoretically optimal for one-dimensional queries. Compared with other optimal indexing methods, bitmap indices are superior because they can be efficiently combined to answer multi-dimensional queries whereas other optimal methods cannot. In this paper, we first describe the searching capability of FastBit, then briefly highlight two applications that make extensive use of FastBit, namely Grid Collector and DEX.
Van Devender, John P.; Emin, David
1986-01-01
A reusable fast opening switch for transferring energy, in the form of a high power pulse, from an electromagnetic storage device such as an inductor into a load. The switch is efficient, compact, fast and reusable. The switch comprises a ferromagnetic semiconductor which undergoes a fast transition between conductive and insulating states at a critical temperature and which undergoes the transition without a phase change in its crystal structure. A semiconductor such as europium rich europhous oxide, which undergoes a conductor to insulator transition when it is joule heated from its conductor state, can be used to form the switch.
Van Devender, J.P.; Emin, D.
1983-12-21
A reusable fast opening switch for transferring energy, in the form of a high power pulse, from an electromagnetic storage device such as an inductor into a load. The switch is efficient, compact, fast and reusable. The switch comprises a ferromagnetic semiconductor which undergoes a fast transition between conductive and metallic states at a critical temperature and which undergoes the transition without a phase change in its crystal structure. A semiconductor such as europium rich europhous oxide, which undergoes a conductor to insulator transition when it is joule heated from its conductor state, can be used to form the switch.
2014-11-26
This software provides implementations of fast matrix multiplication algorithms. These algorithms perform fewer floating point operations than the classical cubic algorithm. The software uses code generation to automatically implement the fast algorithms based on high-level descriptions. The code serves two general purposes. The first is to demonstrate that these fast algorithms can out-perform vendor matrix multiplication algorithms for modest problem sizes on a single machine. The second is to rapidly prototype many variations of fastmore » matrix multiplication algorithms to encourage future research in this area. The implementations target sequential and shared memory parallel execution.« less
Till, C.E.; Chang, Y.I.; Kittel, J.H.; Fauske, H.K.; Lineberry, M.J.; Stevenson, M.G.; Amundson, P.I.; Dance, K.D.
1980-07-01
This report is a compilation of Fast Breeder Reactor (FBR) resource documents prepared to provide the technical basis for the US contribution to the International Nuclear Fuel Cycle Evaluation. The eight separate parts deal with the alternative fast breeder reactor fuel cycles in terms of energy demand, resource base, technical potential and current status, safety, proliferation resistance, deployment, and nuclear safeguards. An Annex compares the cost of decommissioning light-water and fast breeder reactors. Separate abstracts are included for each of the parts.
NASA Astrophysics Data System (ADS)
Wilkinson, P.
2016-02-01
FAST offers "transformational" performance well-suited to finding new phenomena - one of which might be polarised spectral transients. But discoveries will only be made if "the system" provides its users with the necessary opportunities. In addition to designing in as much observational flexibility as possible, FAST should be operated with a philosophy which maximises its "human bandwidth". This band includes the astronomers of tomorrow - many of whom not have yet started school or even been born.
Subsonic Flow for the Multidimensional Euler-Poisson System
NASA Astrophysics Data System (ADS)
Bae, Myoungjean; Duan, Ben; Xie, Chunjing
2016-04-01
We establish the existence and stability of subsonic potential flow for the steady Euler-Poisson system in a multidimensional nozzle of a finite length when prescribing the electric potential difference on a non-insulated boundary from a fixed point at the exit, and prescribing the pressure at the exit of the nozzle. The Euler-Poisson system for subsonic potential flow can be reduced to a nonlinear elliptic system of second order. In this paper, we develop a technique to achieve a priori {C^{1,α}} estimates of solutions to a quasi-linear second order elliptic system with mixed boundary conditions in a multidimensional domain enclosed by a Lipschitz continuous boundary. In particular, we discovered a special structure of the Euler-Poisson system which enables us to obtain {C^{1,α}} estimates of the velocity potential and the electric potential functions, and this leads us to establish structural stability of subsonic flows for the Euler-Poisson system under perturbations of various data.
Towards a multidimensional root trait framework: a tree root review.
Weemstra, Monique; Mommer, Liesje; Visser, Eric J W; van Ruijven, Jasper; Kuyper, Thomas W; Mohren, Godefridus M J; Sterck, Frank J
2016-09-01
Contents 1159 I. 1159 II. 1161 III. 1164 IV. 1166 1167 References 1167 SUMMARY: The search for a root economics spectrum (RES) has been sparked by recent interest in trait-based plant ecology. By analogy with the one-dimensional leaf economics spectrum (LES), fine-root traits are hypothesised to match leaf traits which are coordinated along one axis from resource acquisitive to conservative traits. However, our literature review and meta-level analysis reveal no consistent evidence of an RES mirroring an LES. Instead the RES appears to be multidimensional. We discuss three fundamental differences contributing to the discrepancy between these spectra. First, root traits are simultaneously constrained by various environmental drivers not necessarily related to resource uptake. Second, above- and belowground traits cannot be considered analogues, because they function differently and might not be related to resource uptake in a similar manner. Third, mycorrhizal interactions may offset selection for an RES. Understanding and explaining the belowground mechanisms and trade-offs that drive variation in root traits, resource acquisition and plant performance across species, thus requires a fundamentally different approach than applied aboveground. We therefore call for studies that can functionally incorporate the root traits involved in resource uptake, the complex soil environment and the various soil resource uptake mechanisms - particularly the mycorrhizal pathway - in a multidimensional root trait framework.
Aggression in borderline personality disorder: A multidimensional model.
Mancke, Falk; Herpertz, Sabine C; Bertsch, Katja
2015-07-01
This article proposes a multidimensional model of aggression in borderline personality disorder (BPD) from the perspective of the biobehavioral dimensions of affective dysregulation, impulsivity, threat hypersensitivity, and empathic functioning. It summarizes data from studies that investigated these biobehavioral dimensions using self-reports, behavioral tasks, neuroimaging, neurochemistry as well as psychophysiology, and identifies the following alterations: (a) affective dysregulation associated with prefrontal-limbic imbalance, enhanced heart rate reactivity, skin conductance, and startle response; (b) impulsivity also associated with prefrontal-limbic imbalance, central serotonergic dysfunction, more electroencephalographic slow wave activity, and reduced P300 amplitude in a 2-tone discrimination task; (c) threat hypersensitivity associated with enhanced perception of anger in ambiguous facial expressions, greater speed and number of reflexive eye movements to angry eyes (shown to be compensated by exogenous oxytocin), enhanced P100 amplitude in response to blends of happy versus angry facial expressions, and prefrontal-limbic imbalance; (d) reduced cognitive empathy associated with reduced activity in the superior temporal sulcus/gyrus and preliminary findings of lower oxytocinergic and higher vasopressinergic activity; and (e) reduced self-other differentiation associated with greater emotional simulation and hyperactivation of the somatosensory cortex. These biobehavioral dimensions can be nicely linked to conceptual terms of the alternative Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5) model of BPD, and thus to a multidimensional rather than a traditional categorical approach. PMID:26191822
PCA feature extraction for change detection in multidimensional unlabeled data.
Kuncheva, Ludmila I; Faithfull, William J
2014-01-01
When classifiers are deployed in real-world applications, it is assumed that the distribution of the incoming data matches the distribution of the data used to train the classifier. This assumption is often incorrect, which necessitates some form of change detection or adaptive classification. While there has been a lot of work on change detection based on the classification error monitored over the course of the operation of the classifier, finding changes in multidimensional unlabeled data is still a challenge. Here, we propose to apply principal component analysis (PCA) for feature extraction prior to the change detection. Supported by a theoretical example, we argue that the components with the lowest variance should be retained as the extracted features because they are more likely to be affected by a change. We chose a recently proposed semiparametric log-likelihood change detection criterion that is sensitive to changes in both mean and variance of the multidimensional distribution. An experiment with 35 datasets and an illustration with a simple video segmentation demonstrate the advantage of using extracted features compared to raw data. Further analysis shows that feature extraction through PCA is beneficial, specifically for data with multiple balanced classes.
Extended Darknet: Multi-Dimensional Internet Threat Monitoring System
NASA Astrophysics Data System (ADS)
Shimoda, Akihiro; Mori, Tatsuya; Goto, Shigeki
Internet threats caused by botnets/worms are one of the most important security issues to be addressed. Darknet, also called a dark IP address space, is one of the best solutions for monitoring anomalous packets sent by malicious software. However, since darknet is deployed only on an inactive IP address space, it is an inefficient way for monitoring a working network that has a considerable number of active IP addresses. The present paper addresses this problem. We propose a scalable, light-weight malicious packet monitoring system based on a multi-dimensional IP/port analysis. Our system significantly extends the monitoring scope of darknet. In order to extend the capacity of darknet, our approach leverages the active IP address space without affecting legitimate traffic. Multi-dimensional monitoring enables the monitoring of TCP ports with firewalls enabled on each of the IP addresses. We focus on delays of TCP syn/ack responses in the traffic. We locate syn/ack delayed packets and forward them to sensors or honeypots for further analysis. We also propose a policy-based flow classification and forwarding mechanism and develop a prototype of a monitoring system that implements our proposed architecture. We deploy our system on a campus network and perform several experiments for the evaluation of our system. We verify that our system can cover 89% of the IP addresses while darknet-based monitoring only covers 46%. On our campus network, our system monitors twice as many IP addresses as darknet.
Multidimensional epistasis and fitness landscapes in enzyme evolution.
Zhang, Wei; Dourado, Daniel F A R; Fernandes, Pedro Alexandrino; Ramos, Maria João; Mannervik, Bengt
2012-07-01
The conventional analysis of enzyme evolution is to regard one single salient feature as a measure of fitness, expressed in a milieu exposing the possible selective advantage at a given time and location. Given that a single protein may serve more than one function, fitness should be assessed in several dimensions. In the present study we have explored individual mutational steps leading to a triple-point-mutated human GST (glutathione transferase) A2-2 displaying enhanced activity with azathioprine. A total of eight alternative substrates were used to monitor the diverse evolutionary trajectories. The epistatic effects of the mutations on catalytic activity were variable in sign and magnitude and depended on the substrate used, showing that epistasis is a multidimensional quality. Evidently, the multidimensional fitness landscape can lead to alternative trajectories resulting in enzymes optimized for features other than the selectable markers relevant at the origin of the evolutionary process. In this manner the evolutionary response is robust and can adapt to changing environmental conditions. PMID:22533640
NMRPipe: a multidimensional spectral processing system based on UNIX pipes.
Delaglio, F; Grzesiek, S; Vuister, G W; Zhu, G; Pfeifer, J; Bax, A
1995-11-01
The NMRPipe system is a UNIX software environment of processing, graphics, and analysis tools designed to meet current routine and research-oriented multidimensional processing requirements, and to anticipate and accommodate future demands and developments. The system is based on UNIX pipes, which allow programs running simultaneously to exchange streams of data under user control. In an NMRPipe processing scheme, a stream of spectral data flows through a pipeline of processing programs, each of which performs one component of the overall scheme, such as Fourier transformation or linear prediction. Complete multidimensional processing schemes are constructed as simple UNIX shell scripts. The processing modules themselves maintain and exploit accurate records of data sizes, detection modes, and calibration information in all dimensions, so that schemes can be constructed without the need to explicitly define or anticipate data sizes or storage details of real and imaginary channels during processing. The asynchronous pipeline scheme provides other substantial advantages, including high flexibility, favorable processing speeds, choice of both all-in-memory and disk-bound processing, easy adaptation to different data formats, simpler software development and maintenance, and the ability to distribute processing tasks on multi-CPU computers and computer networks.
Automated multidimensional single molecule fluorescence microscopy feature detection and tracking.
Rolfe, Daniel J; McLachlan, Charles I; Hirsch, Michael; Needham, Sarah R; Tynan, Christopher J; Webb, Stephen E D; Martin-Fernandez, Marisa L; Hobson, Michael P
2011-10-01
Characterisation of multi-protein interactions in cellular networks can be achieved by optical microscopy using multidimensional single molecule fluorescence imaging. Proteins of different species, individually labelled with a single fluorophore, can be imaged as isolated spots (features) of different colour light in different channels, and their diffusive behaviour in cells directly measured through time. Challenges in data analysis have, however, thus far hindered its application in biology. A set of methods for the automated analysis of multidimensional single molecule microscopy data from cells is presented, incorporating Bayesian segmentation-based feature detection, image registration and particle tracking. Single molecules of different colours can be simultaneously detected in noisy, high background data with an arbitrary number of channels, acquired simultaneously or time-multiplexed, and then tracked through time. The resulting traces can be further analysed, for example to detect intensity steps, count discrete intensity levels, measure fluorescence resonance energy transfer (FRET) or changes in polarisation. Examples are shown illustrating the use of the algorithms in investigations of the epidermal growth factor receptor (EGFR) signalling network, a key target for cancer therapeutics, and with simulated data.
The multidimensional self-adaptive grid code, SAGE
NASA Technical Reports Server (NTRS)
Davies, Carol B.; Venkatapathy, Ethiraj
1992-01-01
This report describes the multidimensional self-adaptive grid code SAGE. A two-dimensional version of this code was described in an earlier report by the authors. The formulation of the multidimensional version is described in the first section of this document. The second section is presented in the form of a user guide that explains the input and execution of the code and provides many examples. Successful application of the SAGE code in both two and three dimensions for the solution of various flow problems has proven the code to be robust, portable, and simple to use. Although the basic formulation follows the method of Nakahashi and Deiwert, many modifications have been made to facilitate the use of the self-adaptive grid method for complex grid structures. Modifications to the method and the simplified input options make this a flexible and user-friendly code. The new SAGE code can accommodate both two-dimensional and three-dimensional flow problems.
Dirac-bracket structure in multidimensional mode conversion
NASA Astrophysics Data System (ADS)
Brizard, A. J.; Tracy, E. R.; Kaufman, A. N.; Johnston, D.; Zobin, N.
2012-05-01
The intersection of two (2 n - 1)-dimensional dispersion manifolds Da and Db in the 2 n-dimensional ray phase space P yields a (2 n - 2)-dimensional conversion manifold M≡Da∩Db that naturally possesses a Dirac-bracket structure that is inherited from the canonical Poisson bracket on ray phase space. The canonical symplectic two-form Ω ≡ Ω∥ + Ω⊥, defined on the 2 n-dimensional tangent plane TP≡TM⊕(TM)⊥, can thus be decomposed into the Dirac two-form Ω∥ on the (2 n - 2)-dimensional tangent plane TM at a conversion point z0∈M, and the symplectic two-form Ω⊥ on its orthogonal 2-dimensional complement (TM)⊥. These two symplectic two-forms are introduced in our analysis of multidimensional mode conversion, where their respective geometrical roles are defined. We note that since the Dirac-bracket structure Ω∥ vanishes identically when n = 1, it represents a new structure in multidimensional ( n > 1) mode conversion theory.
A multidimensional approach to apathy after traumatic brain injury.
Arnould, Annabelle; Rochat, Lucien; Azouvi, Philippe; Van der Linden, Martial
2013-09-01
Apathy is commonly described following traumatic brain injury (TBI) and is associated with serious consequences, notably for patients' participation in rehabilitation, family life and later social reintegration. There is strong evidence in the literature of the multidimensional nature of apathy (behavioural, cognitive and emotional), but the processes underlying each dimension are still unclear. The purpose of this article is first, to provide a critical review of the current definitions and instruments used to measure apathy in neurological and psychiatric disorders, and second, to review the prevalence, characteristics, neuroanatomical correlates, relationships with other neurobehavioural disorders and mechanisms of apathy in the TBI population. In this context, we propose a new multidimensional framework that takes into account the various mechanisms at play in the facets of apathy, including not only cognitive factors, especially executive, but also affective factors (e.g., negative mood), motivational variables (e.g., anticipatory pleasure) and aspects related to personal identity (e.g., self-esteem). Future investigations that consider these various factors will help improve the understanding of apathy. This theoretical framework opens up relevant prospects for better clinical assessment and rehabilitation of these frequently described motivational disorders in patients with brain injury. PMID:23921453
Multidimensional NMR inversion without Kronecker products: Multilinear inversion.
Medellín, David; Ravi, Vivek R; Torres-Verdín, Carlos
2016-08-01
Multidimensional NMR inversion using Kronecker products poses several challenges. First, kernel compression is only possible when the kernel matrices are separable, and in recent years, there has been an increasing interest in NMR sequences with non-separable kernels. Second, in three or more dimensions, the singular value decomposition is not unique; therefore kernel compression is not well-defined for higher dimensions. Without kernel compression, the Kronecker product yields matrices that require large amounts of memory, making the inversion intractable for personal computers. Finally, incorporating arbitrary regularization terms is not possible using the Lawson-Hanson (LH) or the Butler-Reeds-Dawson (BRD) algorithms. We develop a minimization-based inversion method that circumvents the above problems by using multilinear forms to perform multidimensional NMR inversion without using kernel compression or Kronecker products. The new method is memory efficient, requiring less than 0.1% of the memory required by the LH or BRD methods. It can also be extended to arbitrary dimensions and adapted to include non-separable kernels, linear constraints, and arbitrary regularization terms. Additionally, it is easy to implement because only a cost function and its first derivative are required to perform the inversion. PMID:27209370
Multidimensional NMR inversion without Kronecker products: Multilinear inversion
NASA Astrophysics Data System (ADS)
Medellín, David; Ravi, Vivek R.; Torres-Verdín, Carlos
2016-08-01
Multidimensional NMR inversion using Kronecker products poses several challenges. First, kernel compression is only possible when the kernel matrices are separable, and in recent years, there has been an increasing interest in NMR sequences with non-separable kernels. Second, in three or more dimensions, the singular value decomposition is not unique; therefore kernel compression is not well-defined for higher dimensions. Without kernel compression, the Kronecker product yields matrices that require large amounts of memory, making the inversion intractable for personal computers. Finally, incorporating arbitrary regularization terms is not possible using the Lawson-Hanson (LH) or the Butler-Reeds-Dawson (BRD) algorithms. We develop a minimization-based inversion method that circumvents the above problems by using multilinear forms to perform multidimensional NMR inversion without using kernel compression or Kronecker products. The new method is memory efficient, requiring less than 0.1% of the memory required by the LH or BRD methods. It can also be extended to arbitrary dimensions and adapted to include non-separable kernels, linear constraints, and arbitrary regularization terms. Additionally, it is easy to implement because only a cost function and its first derivative are required to perform the inversion.
Multidimensionality in host manipulation mimicked by serotonin injection
Perrot-Minnot, Marie-Jeanne; Sanchez-Thirion, Kevin; Cézilly, Frank
2014-01-01
Manipulative parasites often alter the phenotype of their hosts along multiple dimensions. ‘Multidimensionality’ in host manipulation could consist in the simultaneous alteration of several physiological pathways independently of one another, or proceed from the disruption of some key physiological parameter, followed by a cascade of effects. We compared multidimensionality in ‘host manipulation’ between two closely related amphipods, Gammarus fossarum and Gammarus pulex, naturally and experimentally infected with Pomphorhynchus laevis (Acanthocephala), respectively. To that end, we calculated in each host–parasite association the effect size of the difference between infected and uninfected individuals for six different traits (activity, phototaxis, geotaxis, attraction to conspecifics, refuge use and metabolic rate). The effects sizes were highly correlated between host–parasite associations, providing evidence for a relatively constant ‘infection syndrome’. Using the same methodology, we compared the extent of phenotypic alterations induced by an experimental injection of serotonin (5-HT) in uninfected G. pulex to that induced by experimental or natural infection with P. laevis. We observed a significant correlation between effect sizes across the six traits, indicating that injection with 5-HT can faithfully mimic the ‘infection syndrome’. This is, to our knowledge, the first experimental evidence that multidimensionality in host manipulation can proceed, at least partly, from the disruption of some major physiological mechanism. PMID:25339729
Manycore Performance-Portability: Kokkos Multidimensional Array Library
Edwards, H. Carter; Sunderland, Daniel; Porter, Vicki; Amsler, Chris; Mish, Sam
2012-01-01
Large, complex scientific and engineering application code have a significant investment in computational kernels to implement their mathematical models. Porting these computational kernels to the collection of modern manycore accelerator devices is a major challenge in that these devices have diverse programming models, application programming interfaces (APIs), and performance requirements. The Kokkos Array programming model provides library-based approach to implement computational kernels that are performance-portable to CPU-multicore and GPGPU accelerator devices. This programming model is based upon three fundamental concepts: (1) manycore compute devices each with its own memory space, (2) data parallel kernels and (3) multidimensional arrays. Kernel executionmore » performance is, especially for NVIDIA® devices, extremely dependent on data access patterns. Optimal data access pattern can be different for different manycore devices – potentially leading to different implementations of computational kernels specialized for different devices. The Kokkos Array programming model supports performance-portable kernels by (1) separating data access patterns from computational kernels through a multidimensional array API and (2) introduce device-specific data access mappings when a kernel is compiled. An implementation of Kokkos Array is available through Trilinos [Trilinos website, http://trilinos.sandia.gov/, August 2011].« less
Situation exploration in a persistent surveillance system with multidimensional data
NASA Astrophysics Data System (ADS)
Habibi, Mohammad S.
2013-03-01
There is an emerging need for fusing hard and soft sensor data in an efficient surveillance system to provide accurate estimation of situation awareness. These mostly abstract, multi-dimensional and multi-sensor data pose a great challenge to the user in performing analysis of multi-threaded events efficiently and cohesively. To address this concern an interactive Visual Analytics (VA) application is developed for rapid assessment and evaluation of different hypotheses based on context-sensitive ontology spawn from taxonomies describing human/human and human/vehicle/object interactions. A methodology is described here for generating relevant ontology in a Persistent Surveillance System (PSS) and demonstrates how they can be utilized in the context of PSS to track and identify group activities pertaining to potential threats. The proposed VA system allows for visual analysis of raw data as well as metadata that have spatiotemporal representation and content-based implications. Additionally in this paper, a technique for rapid search of tagged information contingent to ranking and confidence is explained for analysis of multi-dimensional data. Lastly the issue of uncertainty associated with processing and interpretation of heterogeneous data is also addressed.
Neural Prediction of Multidimensional Decisions in Monkey Superior Colliculus
NASA Astrophysics Data System (ADS)
Hasegawa, Ryohei P.; Hasegawa, Yukako T.; Segraves, Mark A.
To examine the function of the superior colliculus (SC) in decision-making processes and the application of its single trial activity for “neural mind reading,” we recorded from SC deep layers while two monkeys performed oculomotor go/no-go tasks. We have recently focused on monitoring single trial activities in single SC neurons, and designed a virtual decision function (VDF) to provide a good estimation of single-dimensional decisions (go/no-go decisions for a cue presented at a specific visual field, a response field of each neuron). In this study, we used two VDFs for multidimensional decisions (go/no-go decisions at two cue locations) with the ensemble activity which was simultaneously recorded from a small group (4 to 6) of neurons at both sides of the SC. VDFs predicted cue locations as well as go/no-go decisions. These results suggest that monitoring of ensemble SC activity had sufficient capacity to predict multidimensional decisions on a trial-by-trial basis, which is an ideal candidate to serve for cognitive brain-machine interfaces (BMI) such as two-dimensional word spellers.
Monte Carlo methods for multidimensional integration for European option pricing
NASA Astrophysics Data System (ADS)
Todorov, V.; Dimov, I. T.
2016-10-01
In this paper, we illustrate examples of highly accurate Monte Carlo and quasi-Monte Carlo methods for multiple integrals related to the evaluation of European style options. The idea is that the value of the option is formulated in terms of the expectation of some random variable; then the average of independent samples of this random variable is used to estimate the value of the option. First we obtain an integral representation for the value of the option using the risk neutral valuation formula. Then with an appropriations change of the constants we obtain a multidimensional integral over the unit hypercube of the corresponding dimensionality. Then we compare a specific type of lattice rules over one of the best low discrepancy sequence of Sobol for numerical integration. Quasi-Monte Carlo methods are compared with Adaptive and Crude Monte Carlo techniques for solving the problem. The four approaches are completely different thus it is a question of interest to know which one of them outperforms the other for evaluation multidimensional integrals in finance. Some of the advantages and disadvantages of the developed algorithms are discussed.
A New Online Calibration Method for Multidimensional Computerized Adaptive Testing.
Chen, Ping; Wang, Chun
2016-09-01
Multidimensional-Method A (M-Method A) has been proposed as an efficient and effective online calibration method for multidimensional computerized adaptive testing (MCAT) (Chen & Xin, Paper presented at the 78th Meeting of the Psychometric Society, Arnhem, The Netherlands, 2013). However, a key assumption of M-Method A is that it treats person parameter estimates as their true values, thus this method might yield erroneous item calibration when person parameter estimates contain non-ignorable measurement errors. To improve the performance of M-Method A, this paper proposes a new MCAT online calibration method, namely, the full functional MLE-M-Method A (FFMLE-M-Method A). This new method combines the full functional MLE (Jones & Jin in Psychometrika 59:59-75, 1994; Stefanski & Carroll in Annals of Statistics 13:1335-1351, 1985) with the original M-Method A in an effort to correct for the estimation error of ability vector that might otherwise adversely affect the precision of item calibration. Two correction schemes are also proposed when implementing the new method. A simulation study was conducted to show that the new method generated more accurate item parameter estimation than the original M-Method A in almost all conditions. PMID:26608960
Flexible multi-dimensional modulation method for elastic optical networks
NASA Astrophysics Data System (ADS)
He, Zilong; Liu, Wentao; Shi, Sheping; Shen, Bailin; Chen, Xue; Gao, Xiqing; Zhang, Qi; Shang, Dongdong; Ji, Yongning; Liu, Yingfeng
2016-01-01
We demonstrate a flexible multi-dimensional modulation method for elastic optical networks. We compare the flexible multi-dimensional modulation formats PM-kSC-mQAM with traditional modulation formats PM-mQAM using numerical simulations in back-to-back and wavelength division multiplexed (WDM) transmission (50 GHz-spaced) scenarios at the same symbol rate of 32 Gbaud. The simulation results show that PM-kSC-QPSK and PM-kSC-16QAM can achieve obvious back-to-back sensitivity gain with respect to PM-QPSK and PM-16QAM at the expense of spectral efficiency reduction. And the WDM transmission simulation results show that PM-2SC-QPSK can achieve 57.5% increase in transmission reach compared to PM-QPSK, and 48.5% increase for PM-2SC-16QAM over PM-16QAM. Furthermore, we also experimentally investigate the back to back performance of PM-2SC-QPSK, PM-4SC-QPSK, PM-2SC-16QAM and PM-3SC-16QAM, and the experimental results agree well with the numerical simulations.
ERIC Educational Resources Information Center
Min, Shangchao; He, Lianzhen
2014-01-01
This study examined the relative effectiveness of the multidimensional bi-factor model and multidimensional testlet response theory (TRT) model in accommodating local dependence in testlet-based reading assessment with both dichotomously and polytomously scored items. The data used were 14,089 test-takers' item-level responses to the…
Bifactor Approach to Modeling Multidimensionality of Physical Self-Perception Profile
ERIC Educational Resources Information Center
Chung, ChihMing; Liao, Xiaolan; Song, Hairong; Lee, Taehun
2016-01-01
The multi-dimensionality of Physical Self-Perception Profile (PSPP) has been acknowledged by the use of correlated-factor model and second-order model. In this study, the authors critically endorse the bifactor model, as a substitute to address the multi-dimensionality of PSPP. To cross-validate the models, analyses are conducted first in…
On Multi-Dimensional Vocabulary Teaching Mode for College English Teaching
ERIC Educational Resources Information Center
Zhou, Li-na
2010-01-01
This paper analyses the major approaches in EFL (English as a Foreign Language) vocabulary teaching from historical perspective and puts forward multi-dimensional vocabulary teaching mode for college English. The author stresses that multi-dimensional approaches of communicative vocabulary teaching, lexical phrase teaching method, the grammar…
ERIC Educational Resources Information Center
Lee, Eunjung
2013-01-01
The purpose of this research was to compare the equating performance of various equating procedures for the multidimensional tests. To examine the various equating procedures, simulated data sets were used that were generated based on a multidimensional item response theory (MIRT) framework. Various equating procedures were examined, including…
Posterior Predictive Model Checking for Conjunctive Multidimensionality in Item Response Theory
ERIC Educational Resources Information Center
Levy, Roy
2011-01-01
If data exhibit multidimensionality, key conditional independence assumptions of unidimensional models do not hold. The current work pursues posterior predictive model checking (PPMC) as a tool for criticizing models due to unaccounted for dimensions in data structures that follow conjunctive multidimensional models. These pursuits are couched in…
ERIC Educational Resources Information Center
Clark, W. Crawford; Ferrer-Brechner, Theresa
Multidimensional scaling (MDS) offers a rigorous approach to many problems in perception, emotion, personality, and cognition, where the stimuli are too complex to be quantified by other means. In these procedures similarity ratings of the stimulus objects are modeled as points in multidimensional space, such that perceived similarity is…
ERIC Educational Resources Information Center
Karatas, Zeynep; Tagay, Ozlem
2012-01-01
The purpose of this study is to determine whether there is a relationship between self-esteem, locus of control and multidimensional perfectionism, and the extent to which the variables of self-esteem, locus of control and multidimensional perfectionism contribute to the prediction of subjective well-being. The study was carried out with 318 final…
ERIC Educational Resources Information Center
Findler, Liora; Vilchinsky, Noa; Werner, Shirli
2007-01-01
This study presents the development of a new instrument, the "Multidimensional Attitudes Scale Toward Persons With Disabilities" (MAS). Based on the multidimensional approach, it posits that attitudes are composed of three dimensions: affect, cognition, and behavior. The scale was distributed to a sample of 132 people along with a self-esteem…
Health, Wealth and Wisdom: Exploring Multidimensional Inequality in a Developing Country
ERIC Educational Resources Information Center
Nilsson, Therese
2010-01-01
Despite a broad theoretical literature on multidimensional inequality and a widespread belief that welfare is not synonymous to income--not the least in a developing context--empirical inequality examinations rarely includes several welfare attributes. We explore three techniques on how to evaluate multidimensional inequality using Zambian…
ERIC Educational Resources Information Center
Odekar, Anshula; Hallowell, Brooke
2005-01-01
Purpose: Multidimensional scoring methods yield valuable information about communication abilities. However, issues of training demands for valid and reliable scoring, especially in current service delivery contexts, may preclude common usage. Alternatives to multidimensional scoring were investigated in a sample of adults with aphasia. Method:…
ERIC Educational Resources Information Center
Coromaldi, Manuela; Zoli, Mariangela
2012-01-01
Theoretical and empirical studies have recently adopted a multidimensional concept of poverty. There is considerable debate about the most appropriate degree of multidimensionality to retain in the analysis. In this work we add to the received literature in two ways. First, we derive indicators of multiple deprivation by applying a particular…
Effects of Multidimensional Concept Maps on Fourth Graders' Learning in Web-Based Computer Course
ERIC Educational Resources Information Center
Huang, Hwa-Shan; Chiou, Chei-Chang; Chiang, Heien-Kun; Lai, Sung-Hsi; Huang, Chiun-Yen; Chou, Yin-Yu
2012-01-01
This study explores the effect of multidimensional concept mapping instruction on students' learning performance in a web-based computer course. The subjects consisted of 103 fourth graders from an elementary school in central Taiwan. They were divided into three groups: multidimensional concept map (MCM) instruction group, Novak concept map (NCM)…
Item Vector Plots for the Multidimensional Three-Parameter Logistic Model
ERIC Educational Resources Information Center
Bryant, Damon; Davis, Larry
2011-01-01
This brief technical note describes how to construct item vector plots for dichotomously scored items fitting the multidimensional three-parameter logistic model (M3PLM). As multidimensional item response theory (MIRT) shows promise of being a very useful framework in the test development life cycle, graphical tools that facilitate understanding…
Can a Multidimensional Test Be Evaluated with Unidimensional Item Response Theory?
ERIC Educational Resources Information Center
Wiberg, Marie
2012-01-01
The aim of this study was to evaluate possible consequences of using unidimensional item response theory (UIRT) on a multidimensional college admission test. The test consists of 5 subscales and can be divided into two sections, that is, it can be considered both as a unidimensional and a multidimensional test. The test was examined with both UIRT…
ERIC Educational Resources Information Center
Baghaei, Purya
2013-01-01
This study aims to develop and validate a multidimensional scale of willingness to communicate in a foreign language. Multidimensional random coefficient multinomial logit model was employed to analyze the scale. Likelihood deviance test and information criteria showed that a three-dimensional model fits significantly better than a two-dimensional…
Multidimensional Poverty and Health Status as a Predictor of Chronic Income Poverty.
Callander, Emily J; Schofield, Deborah J
2015-12-01
Longitudinal analysis of Wave 5 to 10 of the nationally representative Household, Income and Labour Dynamics in Australia dataset was undertaken to assess whether multidimensional poverty status can predict chronic income poverty. Of those who were multidimensionally poor (low income plus poor health or poor health and insufficient education attainment) in 2007, and those who were in income poverty only (no other forms of disadvantage) in 2007, a greater proportion of those in multidimensional poverty continued to be in income poverty for the subsequent 5 years through to 2012. People who were multidimensionally poor in 2007 had 2.17 times the odds of being in income poverty each year through to 2012 than those who were in income poverty only in 2005 (95% CI: 1.23-3.83). Multidimensional poverty measures are a useful tool for policymakers to identify target populations for policies aiming to improve equity and reduce chronic disadvantage.
Laser-plasma interactions for fast ignition
NASA Astrophysics Data System (ADS)
Kemp, A. J.; Fiuza, F.; Debayle, A.; Johzaki, T.; Mori, W. B.; Patel, P. K.; Sentoku, Y.; Silva, L. O.
2014-05-01
In the electron-driven fast-ignition (FI) approach to inertial confinement fusion, petawatt laser pulses are required to generate MeV electrons that deposit several tens of kilojoules in the compressed core of an imploded DT shell. We review recent progress in the understanding of intense laser-plasma interactions (LPI) relevant to FI. Increases in computational and modelling capabilities, as well as algorithmic developments have led to enhancement in our ability to perform multi-dimensional particle-in-cell simulations of LPI at relevant scales. We discuss the physics of the interaction in terms of laser absorption fraction, the laser-generated electron spectra, divergence, and their temporal evolution. Scaling with irradiation conditions such as laser intensity are considered, as well as the dependence on plasma parameters. Different numerical modelling approaches and configurations are addressed, providing an overview of the modelling capabilities and limitations. In addition, we discuss the comparison of simulation results with experimental observables. In particular, we address the question of surrogacy of today's experiments for the full-scale FI problem.
Multi-dimensional structure of accreting young stars
NASA Astrophysics Data System (ADS)
Geroux, C.; Baraffe, I.; Viallet, M.; Goffrey, T.; Pratt, J.; Constantino, T.; Folini, D.; Popov, M. V.; Walder, R.
2016-04-01
This work is the first attempt to describe the multi-dimensional structure of accreting young stars based on fully compressible time implicit multi-dimensional hydrodynamics simulations. One major motivation is to analyse the validity of accretion treatment used in previous 1D stellar evolution studies. We analyse the effect of accretion on the structure of a realistic stellar model of the young Sun. Our work is inspired by the numerical work of Kley & Lin (1996, ApJ, 461, 933) devoted to the structure of the boundary layer in accretion disks, which provides the outer boundary conditions for our simulations. We analyse the redistribution of accreted material with a range of values of specific entropy relative to the bulk specific entropy of the material in the accreting object's convective envelope. Low specific entropy accreted material characterises the so-called cold accretion process, whereas high specific entropy is relevant to hot accretion. A primary goal is to understand whether and how accreted energy deposited onto a stellar surface is redistributed in the interior. This study focusses on the high accretion rates characteristic of FU Ori systems. We find that the highest entropy cases produce a distinctive behaviour in the mass redistribution, rms velocities, and enthalpy flux in the convective envelope. This change in behaviour is characterised by the formation of a hot layer on the surface of the accreting object, which tends to suppress convection in the envelope. We analyse the long-term effect of such a hot buffer zone on the structure and evolution of the accreting object with 1D stellar evolution calculations. We study the relevance of the assumption of redistribution of accreted energy into the stellar interior used in the literature. We compare results obtained with the latter treatment and those obtained with a more physical accretion boundary condition based on the formation of a hot surface layer suggested by present multi-dimensional
Regularized Multitask Learning for Multidimensional Log-Density Gradient Estimation.
Yamane, Ikko; Sasaki, Hiroaki; Sugiyama, Masashi
2016-07-01
Log-density gradient estimation is a fundamental statistical problem and possesses various practical applications such as clustering and measuring nongaussianity. A naive two-step approach of first estimating the density and then taking its log gradient is unreliable because an accurate density estimate does not necessarily lead to an accurate log-density gradient estimate. To cope with this problem, a method to directly estimate the log-density gradient without density estimation has been explored and demonstrated to work much better than the two-step method. The objective of this letter is to improve the performance of this direct method in multidimensional cases. Our idea is to regard the problem of log-density gradient estimation in each dimension as a task and apply regularized multitask learning to the direct log-density gradient estimator. We experimentally demonstrate the usefulness of the proposed multitask method in log-density gradient estimation and mode-seeking clustering.
New approach of color image quantization based on multidimensional directory
NASA Astrophysics Data System (ADS)
Chang, Chin-Chen; Su, Yuan-Yuan
2003-04-01
Color image quantization is a strategy in which a smaller number of colors are used to represent the image. The objective is to make the quality approximate as closely to the original true-color image. The technology is widely used in non-true-color displays and in color printers that cannot reproduce a large number of different colors. However, the main problem the quantization of color image has to face is how to use less colors to show the color image. Therefore, it is very important to choose one suitable palette for an index color image. In this paper, we shall propose a new approach which employs the concept of Multi-Dimensional Directory (MDD) together with the one cycle LBG algorithm to create a high-quality index color image. Compared with the approaches such as VQ, ISQ, and Photoshop v.5, our approach can not only acquire high quality image but also shorten the operation time.
Multidimensional coherent optical spectroscopy of semiconductor nanostructures: a review
NASA Astrophysics Data System (ADS)
Nardin, Gaël
2016-02-01
Multidimensional coherent optical spectroscopy (MDCS) is an elegant and versatile tool to measure the ultrafast nonlinear optical response of materials. Of particular interest for semiconductor nanostructures, MDCS enables the separation of homogeneous and inhomogeneous linewidths, reveals the nature of coupling between resonances, and is able to identify the signatures of many-body interactions. As an extension of transient four-wave mixing (FWM) experiments, MDCS can be implemented in various geometries, in which different strategies can be used to isolate the FWM signal and measure its phase. I review and compare different practical implementations of MDCS experiments adapted to the study of semiconductor materials. The power of MDCS is illustrated by discussing experimental results obtained on semiconductor nanostructures such as quantum dots, quantum wells, microcavities, and layered semiconductors.
Conservation laws for multidimensional systems and related linear algebra problems
NASA Astrophysics Data System (ADS)
Igonin, Sergei
2002-12-01
We consider multidimensional systems of PDEs of generalized evolution form with t-derivatives of arbitrary order on the left-hand side and with the right-hand side dependent on lower order t-derivatives and arbitrary space derivatives. For such systems we find an explicit necessary condition for the existence of higher conservation laws in terms of the system's symbol. For systems that violate this condition we give an effective upper bound on the order of conservation laws. Using this result, we completely describe conservation laws for viscous transonic equations, for the Brusselator model and the Belousov-Zhabotinskii system. To achieve this, we solve over an arbitrary field the matrix equations SA = AtS and SA = -AtS for a quadratic matrix A and its transpose At, which may be of independent interest.
Multidimensional Time-Resolved Spectroscopy of Vibrational Coherence in Biopolyenes
NASA Astrophysics Data System (ADS)
Buckup, Tiago; Motzkus, Marcus
2014-04-01
Multidimensional femtosecond time-resolved vibrational coherence spectroscopy allows one to investigate the evolution of vibrational coherence in electronic excited states. Methods such as pump-degenerate four-wave mixing and pump-impulsive vibrational spectroscopy combine an initial ultrashort laser pulse with a nonlinear probing sequence to reinduce vibrational coherence exclusively in the excited states. By carefully exploiting specific electronic resonances, one can detect vibrational coherence from 0 cm-1 to over 2,000 cm-1 and map its evolution. This review focuses on the observation and mapping of high-frequency vibrational coherence for all-trans biological polyenes such as Î²-carotene, lycopene, retinal, and retinal Schiff base. We discuss the role of molecular symmetry in vibrational coherence activity in the S1 electronic state and the interplay of coupling between electronic states and vibrational coherence.
Human tissue profiling with multidimensional protein identification technology.
Cagney, Gerard; Park, Stephen; Chung, Clement; Tong, Bianca; O'Dushlaine, Colm; Shields, Denis C; Emili, Andrew
2005-01-01
Profiling of tissues and cell types through systematic characterization of expressed genes or proteins shows promise as a basic research tool, and has potential applications in disease diagnosis and classification. We used multidimensional protein identification protein identification technology (MudPIT) to analyze proteomes for enriched nuclear extracts of eight human tissues: brain, heart, liver, lung, muscle, pancreas, spleen, and testis. We show that the method is approximately 80% reproducible. We address issues of relative abundance, tissue-specificity, and selectivity, and the significance of proteins whose expression does not correlate with that of the corresponding mRNA. Surprisingly, most proteins are detected in a single tissue. These proteins tend to fulfill specialist (and potentially tissue-specific) functions compared to proteins expressed in two or more tissues.
Multidimensional scaling analysis of the dynamics of a country economy.
Tenreiro Machado, J A; Mata, Maria Eugénia
2013-01-01
This paper analyzes the Portuguese short-run business cycles over the last 150 years and presents the multidimensional scaling (MDS) for visualizing the results. The analytical and numerical assessment of this long-run perspective reveals periods with close connections between the macroeconomic variables related to government accounts equilibrium, balance of payments equilibrium, and economic growth. The MDS method is adopted for a quantitative statistical analysis. In this way, similarity clusters of several historical periods emerge in the MDS maps, namely, in identifying similarities and dissimilarities that identify periods of prosperity and crises, growth, and stagnation. Such features are major aspects of collective national achievement, to which can be associated the impact of international problems such as the World Wars, the Great Depression, or the current global financial crisis, as well as national events in the context of broad political blueprints for the Portuguese society in the rising globalization process. PMID:24294132
A Multi-Dimensional Classification Model for Scientific Workflow Characteristics
Ramakrishnan, Lavanya; Plale, Beth
2010-04-05
Workflows have been used to model repeatable tasks or operations in manufacturing, business process, and software. In recent years, workflows are increasingly used for orchestration of science discovery tasks that use distributed resources and web services environments through resource models such as grid and cloud computing. Workflows have disparate re uirements and constraints that affects how they might be managed in distributed environments. In this paper, we present a multi-dimensional classification model illustrated by workflow examples obtained through a survey of scientists from different domains including bioinformatics and biomedical, weather and ocean modeling, astronomy detailing their data and computational requirements. The survey results and classification model contribute to the high level understandingof scientific workflows.
Multidimensional vector model of stimulus-response compatibility.
Yamaguchi, Motonori; Proctor, Robert W
2012-04-01
The present study proposes and examines the multidimensional vector (MDV) model framework as a modeling schema for choice response times. MDV extends the Thurstonian model, as well as signal detection theory, to classification tasks by taking into account the influence of response properties on stimulus discrimination. It is capable of accounting for stimulus-response compatibility, which is known to be an influential task variable determining choice-reaction performance but has not been considered in previous mathematical modeling efforts. Specific MDV models were developed for 5 experiments using the Simon task, for which stimulus location is task irrelevant, to examine the validity of model assumptions and illustrate characteristic behaviors of model parameters. The MDV models accounted for the experimental data to a remarkable degree, demonstrating the adequacy of the framework as a general schema for modeling the latency of choice performance. Some modeling issues involved in the MDV model framework are discussed.
Anonymous voting for multi-dimensional CV quantum system
NASA Astrophysics Data System (ADS)
Rong-Hua, Shi; Yi, Xiao; Jin-Jing, Shi; Ying, Guo; Moon-Ho, Lee
2016-06-01
We investigate the design of anonymous voting protocols, CV-based binary-valued ballot and CV-based multi-valued ballot with continuous variables (CV) in a multi-dimensional quantum cryptosystem to ensure the security of voting procedure and data privacy. The quantum entangled states are employed in the continuous variable quantum system to carry the voting information and assist information transmission, which takes the advantage of the GHZ-like states in terms of improving the utilization of quantum states by decreasing the number of required quantum states. It provides a potential approach to achieve the efficient quantum anonymous voting with high transmission security, especially in large-scale votes. Project supported by the National Natural Science Foundation of China (Grant Nos. 61272495, 61379153, and 61401519), the Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20130162110012), and the MEST-NRF of Korea (Grant No. 2012-002521).
Multidimensional scaling of ferrous sulfate and basic tastes.
Stevens, David A; Smith, Rebecca F; Lawless, Harry T
2006-02-28
The status of metallic sensations as a primary or basic taste category is controversial. Ferrous sulfate (FeSO4) has been suggested as a prototypical metallic chemosensory stimulus. At least part of the metallic sensation from FeSO4 arises from a metallic retronasal smell. The quality of this sensation was studied via multidimensional scaling (MDS) of taste similarities, with and without nasal closure to eliminate retronasal olfactory sensations. The metallic stimulus was embedded in a series containing classical "basic taste" stimuli, alum and monosodium glutamate. With olfaction available, the metallic stimulus plotted away from basic tastes and taste mixtures. Scaled ratings of sensory properties related to metallic taste (iron-nail, copper-penny-like, aftertaste) of FeSO4 decreased with nasal closure. Results are consistent with the idea that ferrous sulfate produces a distinctly different sensation from the traditional basic tastes, which includes both olfactory and oral sensations.
Development and validation of the multidimensional state boredom scale.
Fahlman, Shelley A; Mercer-Lynn, Kimberley B; Flora, David B; Eastwood, John D
2013-02-01
This article describes the development and validation of the Multidimensional State Boredom Scale (MSBS)-the first and only full-scale measure of state boredom. It was developed based on a theoretically and empirically grounded definition of boredom. A five-factor structure of the scale (Disengagement, High Arousal, Low Arousal, Inattention, and Time Perception) was supported by exploratory factor analyses and confirmatory factor analyses of two independent samples. Furthermore, all subscales were significantly related to a single, second-order factor. The MSBS factor structure was shown to be invariant across gender. MSBS scores were significantly correlated with measures of trait boredom, depression, anxiety, anger, inattention, impulsivity, neuroticism, life satisfaction, and purpose in life. Finally, MSBS scores distinguished between participants who were experimentally manipulated into a state of boredom and those who were not, above and beyond measures of trait boredom, negative affect, and depression.
Development and validation of the multidimensional motivational climate observation system.
Smith, Nathan; Tessier, Damien; Tzioumakis, Yannis; Quested, Eleanor; Appleton, Paul; Sarrazin, Philippe; Papaioannou, Athanasios; Duda, Joan L
2015-02-01
This article outlines the development and validation of the Multidimensional Motivational Climate Observation System (MMCOS). Drawing from an integration of the dimensions of the social environment emphasized within achievement goal theory and self-determination theory (as assumed within Duda's [2013] conceptualization of "empowering" and "disempowering" climates), the MMCOS was developed to enable an objective assessment of the coach-created motivational environment in sport. Study 1 supported the initial validity and reliability of the newly developed observation system. Study 2 further examined the interobserver reliability and factorial structure of the MMCOS. Study 3 explored the predictive validity of the observational system in relation to athletes' reported basic psychological need satisfaction. Overall, the results of these studies provide preliminary support for the inter- and intraobserver reliability, as well as factorial and predictive validity of the MMCOS. Suggestions for the use of this observational system in future research in sport are provided.
Multidimensional stock network analysis: An Escoufier's RV coefficient approach
NASA Astrophysics Data System (ADS)
Lee, Gan Siew; Djauhari, Maman A.
2013-09-01
The current practice of stocks network analysis is based on the assumption that the time series of closed stock price could represent the behaviour of the each stock. This assumption leads to consider minimal spanning tree (MST) and sub-dominant ultrametric (SDU) as an indispensible tool to filter the economic information contained in the network. Recently, there is an attempt where researchers represent stock not only as a univariate time series of closed price but as a bivariate time series of closed price and volume. In this case, they developed the so-called multidimensional MST to filter the important economic information. However, in this paper, we show that their approach is only applicable for that bivariate time series only. This leads us to introduce a new methodology to construct MST where each stock is represented by a multivariate time series. An example of Malaysian stock exchange will be presented and discussed to illustrate the advantages of the method.
A Multidimensional Scaling Analysis of Students' Attitudes about Science Careers
NASA Astrophysics Data System (ADS)
Masnick, Amy M.; Stavros Valenti, S.; Cox, Brian D.; Osman, Christopher J.
2010-03-01
To encourage students to seek careers in Science, Technology, Engineering and Mathematics (STEM) fields, it is important to gauge students' implicit and explicit attitudes towards scientific professions. We asked high school and college students to rate the similarity of pairs of occupations, and then used multidimensional scaling (MDS) to create a spatial representation of occupational similarity. Other students confirmed the emergent MDS map by rating each of the occupations along several dimensions. We found that participants across age and sex considered scientific professions to be less creative and less people-oriented than other popular career choices. We conclude that students may be led away from STEM careers by common misperceptions that science is a difficult, uncreative, and socially isolating pursuit.
Lagrangian simulation of multidimensional anomalous transport at the MADE site
NASA Astrophysics Data System (ADS)
Zhang, Yong; Benson, David A.
2008-04-01
Contaminant transport through regional-scale natural geological formations typically exhibits several ``anomalous'' features, including direction-dependent spreading rates, channeling along preferential flow paths, trapping of solute in relatively immobile domains, and/or the local variation of transport speed. Simulating these plume characteristics can be computationally intensive using a traditional advection-dispersion equation (ADE) because anomalous features of transport generally depend on local-scale subsurface properties. Here we develop an alternative simulation approach that solves the full nonlocal, multidimensional, spatiotemporal fractional-order ADE with variable coefficients in a Lagrangian framework using a novel non-Markovian random walk method. This model allows us to simulate anomalous plumes without the need to explicitly define local-scale heterogeneity. The simple model accurately simulates the tritium plume measured at the extensively characterized MADE test site.
[Multidimensional counseling and intervention in anxiety problems in school].
Jeck, Stephan
2003-01-01
Multidimensional counselling and intervention in case of anxiety problems in school can be understood as a challenge for educational psychologists who has to solve individual anxiety disorders on the one hand and participate in processes of school development in order to prevent anxiety on the other hand. There are a lot of techniques and strategies to construct classroom settings which reduce anxiety. Improving self-efficacy and training stress management for teachers and students are possible programs presented in order to change the culture of educational organizations like schools. To realize such programs all members of the school community have to cooperate and teachers have to modify their instructional actions. Therefore they have to develop better diagnostic skills in order to detect anxious and inconspicuous students who need special fostering for better learning in school. For extreme anxiety disorders with school refusal there are many therapeutic treatments out of school, one of the best for children and adolescents are cognitive-behavioral settings.
Reinforcement learning in multidimensional environments relies on attention mechanisms.
Niv, Yael; Daniel, Reka; Geana, Andra; Gershman, Samuel J; Leong, Yuan Chang; Radulescu, Angela; Wilson, Robert C
2015-05-27
In recent years, ideas from the computational field of reinforcement learning have revolutionized the study of learning in the brain, famously providing new, precise theories of how dopamine affects learning in the basal ganglia. However, reinforcement learning algorithms are notorious for not scaling well to multidimensional environments, as is required for real-world learning. We hypothesized that the brain naturally reduces the dimensionality of real-world problems to only those dimensions that are relevant to predicting reward, and conducted an experiment to assess by what algorithms and with what neural mechanisms this "representation learning" process is realized in humans. Our results suggest that a bilateral attentional control network comprising the intraparietal sulcus, precuneus, and dorsolateral prefrontal cortex is involved in selecting what dimensions are relevant to the task at hand, effectively updating the task representation through trial and error. In this way, cortical attention mechanisms interact with learning in the basal ganglia to solve the "curse of dimensionality" in reinforcement learning.
Multidimensional scaling analysis of the dynamics of a country economy.
Tenreiro Machado, J A; Mata, Maria Eugénia
2013-01-01
This paper analyzes the Portuguese short-run business cycles over the last 150 years and presents the multidimensional scaling (MDS) for visualizing the results. The analytical and numerical assessment of this long-run perspective reveals periods with close connections between the macroeconomic variables related to government accounts equilibrium, balance of payments equilibrium, and economic growth. The MDS method is adopted for a quantitative statistical analysis. In this way, similarity clusters of several historical periods emerge in the MDS maps, namely, in identifying similarities and dissimilarities that identify periods of prosperity and crises, growth, and stagnation. Such features are major aspects of collective national achievement, to which can be associated the impact of international problems such as the World Wars, the Great Depression, or the current global financial crisis, as well as national events in the context of broad political blueprints for the Portuguese society in the rising globalization process.
Implementation fidelity of Multidimensional Family Therapy in an international trial.
Rowe, Cynthia; Rigter, Henk; Henderson, Craig; Gantner, Andreas; Mos, Kees; Nielsen, Philip; Phan, Olivier
2013-04-01
Implementation fidelity, a critical aspect of clinical trials research that establishes adequate delivery of the treatment as prescribed in treatment manuals and protocols, is also essential to the successful implementation of effective programs into new practice settings. Although infrequently studied in the drug abuse field, stronger implementation fidelity has been linked to better outcomes in practice but appears to be more difficult to achieve with greater distance from model developers. In the INternational CAnnabis Need for Treatment (INCANT) multi-national randomized clinical trial, investigators tested the effectiveness of Multidimensional Family Therapy (MDFT) in comparison to individual psychotherapy (IP) in Brussels, Berlin, Paris, The Hague, and Geneva with 450 adolescents with a cannabis use disorder and their parents. This study reports on the implementation fidelity of MDFT across these five Western European sites in terms of treatment adherence, dose and program differentiation, and discusses possible implications for international implementation efforts.
Anonymous voting for multi-dimensional CV quantum system
NASA Astrophysics Data System (ADS)
Rong-Hua, Shi; Yi, Xiao; Jin-Jing, Shi; Ying, Guo; Moon-Ho, Lee
2016-06-01
We investigate the design of anonymous voting protocols, CV-based binary-valued ballot and CV-based multi-valued ballot with continuous variables (CV) in a multi-dimensional quantum cryptosystem to ensure the security of voting procedure and data privacy. The quantum entangled states are employed in the continuous variable quantum system to carry the voting information and assist information transmission, which takes the advantage of the GHZ-like states in terms of improving the utilization of quantum states by decreasing the number of required quantum states. It provides a potential approach to achieve the efficient quantum anonymous voting with high transmission security, especially in large-scale votes. Project supported by the National Natural Science Foundation of China (Grant Nos. 61272495, 61379153, and 61401519), the Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20130162110012), and the MEST-NRF of Korea (Grant No. 2012-002521).
Multidimensional Scaling Analysis of the Dynamics of a Country Economy
Mata, Maria Eugénia
2013-01-01
This paper analyzes the Portuguese short-run business cycles over the last 150 years and presents the multidimensional scaling (MDS) for visualizing the results. The analytical and numerical assessment of this long-run perspective reveals periods with close connections between the macroeconomic variables related to government accounts equilibrium, balance of payments equilibrium, and economic growth. The MDS method is adopted for a quantitative statistical analysis. In this way, similarity clusters of several historical periods emerge in the MDS maps, namely, in identifying similarities and dissimilarities that identify periods of prosperity and crises, growth, and stagnation. Such features are major aspects of collective national achievement, to which can be associated the impact of international problems such as the World Wars, the Great Depression, or the current global financial crisis, as well as national events in the context of broad political blueprints for the Portuguese society in the rising globalization process. PMID:24294132
Regularized Multitask Learning for Multidimensional Log-Density Gradient Estimation.
Yamane, Ikko; Sasaki, Hiroaki; Sugiyama, Masashi
2016-07-01
Log-density gradient estimation is a fundamental statistical problem and possesses various practical applications such as clustering and measuring nongaussianity. A naive two-step approach of first estimating the density and then taking its log gradient is unreliable because an accurate density estimate does not necessarily lead to an accurate log-density gradient estimate. To cope with this problem, a method to directly estimate the log-density gradient without density estimation has been explored and demonstrated to work much better than the two-step method. The objective of this letter is to improve the performance of this direct method in multidimensional cases. Our idea is to regard the problem of log-density gradient estimation in each dimension as a task and apply regularized multitask learning to the direct log-density gradient estimator. We experimentally demonstrate the usefulness of the proposed multitask method in log-density gradient estimation and mode-seeking clustering. PMID:27171983
Multidimensional time-resolved spectroscopy of vibrational coherence in biopolyenes.
Buckup, Tiago; Motzkus, Marcus
2014-01-01
Multidimensional femtosecond time-resolved vibrational coherence spectroscopy allows one to investigate the evolution of vibrational coherence in electronic excited states. Methods such as pump-degenerate four-wave mixing and pump-impulsive vibrational spectroscopy combine an initial ultrashort laser pulse with a nonlinear probing sequence to reinduce vibrational coherence exclusively in the excited states. By carefully exploiting specific electronic resonances, one can detect vibrational coherence from 0 cm(-1) to over 2,000 cm(-1) and map its evolution. This review focuses on the observation and mapping of high-frequency vibrational coherence for all-trans biological polyenes such as β-carotene, lycopene, retinal, and retinal Schiff base. We discuss the role of molecular symmetry in vibrational coherence activity in the S1 electronic state and the interplay of coupling between electronic states and vibrational coherence.
The Multi-Dimensional Character of Core-Collapse Supernovae
Hix, William Raphael; Lentz, E. J.; Bruenn, S. W.; Mezzacappa, Anthony; Messer, Bronson; Endeve, Eirik; Blondin, J. M.; Harris, James Austin; Marronetti, Pedro; Yakunin, Konstantin N
2016-01-01
Core-collapse supernovae, the culmination of massive stellar evolution, are spectacular astronomical events and the principle actors in the story of our elemental origins. Our understanding of these events, while still incomplete, centers around a neutrino-driven central engine that is highly hydrodynamically unstable. Increasingly sophisticated simulations reveal a shock that stalls for hundreds of milliseconds before reviving. Though brought back to life by neutrino heating, the development of the supernova explosion is inextricably linked to multi-dimensional fluid flows. In this paper, the outcomes of three-dimensional simulations that include sophisticated nuclear physics and spectral neutrino transport are juxtaposed to learn about the nature of the three dimensional fluid flow that shapes the explosion. Comparison is also made between the results of simulations in spherical symmetry from several groups, to give ourselves confidence in the understanding derived from this juxtaposition.
Estimating a treatment effect from multidimensional longitudinal data.
Gray, S M; Brookmeyer, R
1998-09-01
Multidimensional longitudinal data result when researchers measure an outcome through time that is quantified by many different response variables. These response variables are often defined on different numerical scales. The objective of this paper is to present a method to summarize and estimate an overall treatment effect from this type of longitudinal data. A regression model is proposed that assumes the treatment effect can be parameterized as an acceleration or deceleration of the time scale of each response variable's trajectory. Generalized estimating equations are used to estimate the model parameters. Cognitive and functional ability data from Alzheimer's disease patients and quality of life data from an AIDS clinical trial are used to illustrate the model.
Multidimensional modeling of pyrolysis gas transport inside orthotropic charring ablators
NASA Astrophysics Data System (ADS)
Weng, Haoyue
During hypersonic atmospheric entry, spacecraft are exposed to enormous aerodynamic heat. To prevent the payload from overheating, charring ablative materials are favored to be applied as the heat shield at the exposing surface of the vehicle. Accurate modeling not only prevents mission failures, but also helps reduce cost. Existing models were mostly limited to one-dimensional and discrepancies were shown against measured experiments and flight-data. To help improve the models and analyze the charring ablation problems, a multidimensional material response module is developed, based on a finite volume method framework. The developed computer program is verified through a series of test-cases, and through code-to-code comparisons with a validated code. Several novel models are proposed, including a three-dimensional pyrolysis gas transport model and an orthotropic material model. The effects of these models are numerically studied and demonstrated to be significant.
Towards a multi-dimensional approach to COPD.
Zanforlin, Alessandro; Sorino, Claudio; Sferrazza Papa, Giuseppe F
2016-06-01
Chronic obstructive pulmonary disease (COPD) is the third leading cause of mortality worldwide. Clinical features of the disease include exertional dyspnea and chronic cough, while persistent airflow obstruction detected at spirometry is the defining element of the disease. Notably, subjects with smoke exposure and symptoms, but normal FEV1/FVC ratio (previously classified as "stage 0" by the GOLD classification), are not considered affected and do not require treatment according to guidelines. The recent GeneCOPD study suggested that a proportion of this population might present significant radiological features of respiratory disease. This commentary article focuses on the possible future role of chest imaging, including ultrasound of the respiratory muscles, integrated with additional functional tests, such as body plethysmography and diffusing capacity for carbon monoxide of the lungs (DLCO), in a multidimensional assessment of COPD. PMID:27424499
Reconciling semiclassical and Bohmian mechanics. VI. Multidimensional dynamics
Poirier, Bill
2008-08-28
In previous articles [J. Chem. Phys. 121, 4501 (2004); J. Chem. Phys. 124, 034115 (2006); J. Chem. Phys. 124, 034116 (2006); J. Phys. Chem. A 111, 10400 (2007); J. Chem. Phys. 128, 164115 (2008)] an exact quantum, bipolar wave decomposition, {psi}={psi}{sub +}+{psi}{sub -}, was presented for one-dimensional stationary state and time-dependent wavepacket dynamics calculations, such that the components {psi}{sub {+-}} approach their semiclassical WKB analogs in the large action limit. The corresponding bipolar quantum trajectories are classical-like and well behaved, even when {psi} has many nodes or is wildly oscillatory. In this paper, both the stationary state and wavepacket dynamics theories are generalized for multidimensional systems and applied to several benchmark problems, including collinear H+H{sub 2}.
Acceleration of multi-dimensional propagator measurements with compressed sensing.
Paulsen, Jeffrey L; Cho, HyungJoon; Cho, Gyunggoo; Song, Yi-Qiao
2011-12-01
NMR can probe the microstructures of anisotropic materials such as liquid crystals, stretched polymers and biological tissues through measurement of the diffusion propagator, where internal structures are indicated by restricted diffusion. Multi-dimensional measurements can probe the microscopic anisotropy, but full sampling can then quickly become prohibitively time consuming. However, for incompletely sampled data, compressed sensing is an effective reconstruction technique to enable accelerated acquisition. We demonstrate that with a compressed sensing scheme, one can greatly reduce the sampling and the experimental time with minimal effect on the reconstruction of the diffusion propagator with an example of anisotropic diffusion. We compare full sampling down to 64× sub-sampling for the 2D propagator measurement and reduce the acquisition time for the 3D experiment by a factor of 32 from ∼80 days to ∼2.5 days. PMID:21924932
Multidimensional Extension of the Generalized Chowla-Selberg Formula
NASA Astrophysics Data System (ADS)
Elizalde, E.
After recalling the precise existence conditions of the zeta function of a pseudodifferential operator, and the concept of reflection formula, an exponentially convergent expression for the analytic continuation of a multidimensional inhomogeneous Epstein-type zeta function of the general form
Tissue proteomics using capillary isoelectric focusing-based multidimensional separations.
Wang, Yueju; Balgley, Brian M; Lee, Cheng S
2005-10-01
The capabilities of capillary isoelectric focusing-based multidimensional separations for performing proteome analysis from minute samples create new opportunities in the pursuit of biomarker discovery using enriched and selected cell populations procured from tissue specimens. In this article, recent advances in online integration of capillary isoelectric focusing with nano-reversed phase liquid chromatography for achieving high-resolution peptide and protein separations prior to mass spectrometry analysis are reviewed, along with its potential application to tissue proteomics. These proteome technological advances combined with recently developed tissue microdissection techniques, provide powerful tools for those seeking to gain a greater understanding at the global level of the cellular machinery associated with human diseases such as cancer.
Multidimensional stationary probability distribution for interacting active particles
Maggi, Claudio; Marconi, Umberto Marini Bettolo; Gnan, Nicoletta; Di Leonardo, Roberto
2015-01-01
We derive the stationary probability distribution for a non-equilibrium system composed by an arbitrary number of degrees of freedom that are subject to Gaussian colored noise and a conservative potential. This is based on a multidimensional version of the Unified Colored Noise Approximation. By comparing theory with numerical simulations we demonstrate that the theoretical probability density quantitatively describes the accumulation of active particles around repulsive obstacles. In particular, for two particles with repulsive interactions, the probability of close contact decreases when one of the two particle is pinned. Moreover, in the case of isotropic confining potentials, the radial density profile shows a non trivial scaling with radius. Finally we show that the theory well approximates the “pressure” generated by the active particles allowing to derive an equation of state for a system of non-interacting colored noise-driven particles. PMID:26021260
Leibon, Gregory; Rockmore, Daniel N.; Park, Wooram; Taintor, Robert; Chirikjian, Gregory S.
2008-01-01
We present algorithms for fast and stable approximation of the Hermite transform of a compactly supported function on the real line, attainable via an application of a fast algebraic algorithm for computing sums associated with a three-term relation. Trade-offs between approximation in bandlimit (in the Hermite sense) and size of the support region are addressed. Numerical experiments are presented that show the feasibility and utility of our approach. Generalizations to any family of orthogonal polynomials are outlined. Applications to various problems in tomographic reconstruction, including the determination of protein structure, are discussed. PMID:20027202
Fast Overcurrent Tripping Circuit
NASA Technical Reports Server (NTRS)
Sullender, Craig C.; Davies, Bryan L.; Osborn, Stephen H.
1993-01-01
Fast overcurrent tripping circuit designed for incorporation into power metal oxide/semiconductor field-effect transistor (MOSFET) switching circuit. Serves as fast electronic circuit breaker by sensing voltage across MOSFET's during conduction and switching MOSFET's off within 1 microsecond after voltage exceeds reference value corresponding to tripping current. Acts more quickly than Hall-effect current sensor and, in comparison with shunt current-measuring circuits, smaller and consumes less power. Also ignores initial transient overcurrents during first 5 microseconds of switching cycle.
Delusions in Patients with Alzheimer's Disease: A Multidimensional Approach.
D'Onofrio, Grazia; Panza, Francesco; Sancarlo, Daniele; Paris, Francesco F; Cascavilla, Leandro; Mangiacotti, Antonio; Lauriola, Michele; Paroni, Giulia H; Seripa, Davide; Greco, Antonio
2016-01-01
In Alzheimer's disease (AD) patients with delusions, clinical outcomes and mortality result from a combination of psychological, biological, functional, and environmental factors. We determined the effect of delusions on mortality risk, clinical outcomes linked to comprehensive geriatric assessment (CGA), cognitive, depressive, and neuropsychiatric symptoms (NPS) in 380 consecutive AD patients with Mini-Mental State Examination, Clinical Dementia Rating scale, 15-item Geriatric Depression Scale, and Neuropsychiatric Inventory (NPI), assessing one-year mortality risk using the Multidimensional Prognostic Index (MPI). We included 121 AD patients with delusions (AD-D) and 259 AD patients without delusions (AD-noD). AD-D patients were significantly older, with higher age at onset and cognitive impairment, a more severe stage of dementia, and more depressive symptoms than AD-noD patients. Disease duration was slightly higher in AD-D patients than in those without delusions, although this difference was not statistically significant. At CGA, AD-D patients showed a higher grade of disability in basic and instrumental activities of daily living, and an increased risk of malnutrition and bedsores. The two groups of patients significantly differed in MPI score (AD-D: 0.65 versus AD-noD: 0.51, p < 0.0001) and MPI grade. AD-D patients showed also a significant higher score in NPI of the following NPS than AD-noD patients: hallucinations, agitation/aggression, depression mood, apathy, irritability/lability, aberrant motor activity, sleep disturbances, and eating disorders. Therefore, AD-D patients showed higher dementia severity, and higher impairment in cognitive and depressive symptoms, and several neuropsychiatric domains than AD-noD patients, and this appeared to be associated with higher multidimensional impairment and increased risk of mortality. PMID:26890768
Multidimensional optimal droop control for wind resources in DC microgrids
NASA Astrophysics Data System (ADS)
Bunker, Kaitlyn J.
Two important and upcoming technologies, microgrids and electricity generation from wind resources, are increasingly being combined. Various control strategies can be implemented, and droop control provides a simple option without requiring communication between microgrid components. Eliminating the single source of potential failure around the communication system is especially important in remote, islanded microgrids, which are considered in this work. However, traditional droop control does not allow the microgrid to utilize much of the power available from the wind. This dissertation presents a novel droop control strategy, which implements a droop surface in higher dimension than the traditional strategy. The droop control relationship then depends on two variables: the dc microgrid bus voltage, and the wind speed at the current time. An approach for optimizing this droop control surface in order to meet a given objective, for example utilizing all of the power available from a wind resource, is proposed and demonstrated. Various cases are used to test the proposed optimal high dimension droop control method, and demonstrate its function. First, the use of linear multidimensional droop control without optimization is demonstrated through simulation. Next, an optimal high dimension droop control surface is implemented with a simple dc microgrid containing two sources and one load. Various cases for changing load and wind speed are investigated using simulation and hardware-in-the-loop techniques. Optimal multidimensional droop control is demonstrated with a wind resource in a full dc microgrid example, containing an energy storage device as well as multiple sources and loads. Finally, the optimal high dimension droop control method is applied with a solar resource, and using a load model developed for a military patrol base application. The operation of the proposed control is again investigated using simulation and hardware-in-the-loop techniques.
Relevance in the science classroom: A multidimensional analysis
NASA Astrophysics Data System (ADS)
Hartwell, Matthew F.
While perceived relevance is considered a fundamental component of adaptive learning, the experience of relevance and its conceptual definition have not been well described. The mixed-methods research presented in this dissertation aimed to clarify the conceptual meaning of relevance by focusing on its phenomenological experience from the students' perspective. Following a critical literature review, I propose an identity-based model of perceived relevance that includes three components: a contextual target, an identity target, and a connection type, or lens. An empirical investigation of this model that consisted of two general phases was implemented in four 9th grade-biology classrooms. Participants in Phase 1 (N = 118) completed a series of four open-ended writing activities focused on eliciting perceived personal connections to academic content. Exploratory qualitative content analysis of a 25% random sample of the student responses was used to identify the main meaning-units of the proposed model as well as different dimensions of student relevance perceptions. These meaning-units and dimensions provided the basis for the construction of a conceptual mapping sentence capturing students' perceived relevance, which was then applied in a confirmatory analysis to all other student responses. Participants in Phase 2 (N = 139) completed a closed survey designed based on the mapping sentence to assess their perceived relevance of a biology unit. The survey also included scales assessing other domain-level motivational processes. Exploratory factor analysis and non-metric multidimensional scaling indicated a coherent conceptual structure, which included a primary interpretive relevance dimension. Comparison of the conceptual structure across various groups (randomly-split sample, gender, academic level, domain-general motivational profiles) provided support for its ubiquity and insight into variation in the experience of perceived relevance among students of different
Statistical Downscaling in Multi-dimensional Wave Climate Forecast
NASA Astrophysics Data System (ADS)
Camus, P.; Méndez, F. J.; Medina, R.; Losada, I. J.; Cofiño, A. S.; Gutiérrez, J. M.
2009-04-01
Wave climate at a particular site is defined by the statistical distribution of sea state parameters, such as significant wave height, mean wave period, mean wave direction, wind velocity, wind direction and storm surge. Nowadays, long-term time series of these parameters are available from reanalysis databases obtained by numerical models. The Self-Organizing Map (SOM) technique is applied to characterize multi-dimensional wave climate, obtaining the relevant "wave types" spanning the historical variability. This technique summarizes multi-dimension of wave climate in terms of a set of clusters projected in low-dimensional lattice with a spatial organization, providing Probability Density Functions (PDFs) on the lattice. On the other hand, wind and storm surge depend on instantaneous local large-scale sea level pressure (SLP) fields while waves depend on the recent history of these fields (say, 1 to 5 days). Thus, these variables are associated with large-scale atmospheric circulation patterns. In this work, a nearest-neighbors analog method is used to predict monthly multi-dimensional wave climate. This method establishes relationships between the large-scale atmospheric circulation patterns from numerical models (SLP fields as predictors) with local wave databases of observations (monthly wave climate SOM PDFs as predictand) to set up statistical models. A wave reanalysis database, developed by Puertos del Estado (Ministerio de Fomento), is considered as historical time series of local variables. The simultaneous SLP fields calculated by NCEP atmospheric reanalysis are used as predictors. Several applications with different size of sea level pressure grid and with different temporal domain resolution are compared to obtain the optimal statistical model that better represents the monthly wave climate at a particular site. In this work we examine the potential skill of this downscaling approach considering perfect-model conditions, but we will also analyze the
Describing temperament in an ungulate: a multidimensional approach.
Graunke, Katharina L; Nürnberg, Gerd; Repsilber, Dirk; Puppe, Birger; Langbein, Jan
2013-01-01
Studies on animal temperament have often described temperament using a one-dimensional scale, whereas theoretical framework has recently suggested two or more dimensions using terms like "valence" or "arousal" to describe these dimensions. Yet, the valence or assessment of a situation is highly individual. The aim of this study was to provide support for the multidimensional framework with experimental data originating from an economically important species (Bos taurus). We tested 361 calves at 90 days post natum (dpn) in a novel-object test. Using a principal component analysis (PCA), we condensed numerous behaviours into fewer variables to describe temperament and correlated these variables with simultaneously measured heart rate variability (HRV) data. The PCA resulted in two behavioural dimensions (principal components, PC): novel-object-related (PC 1) and exploration-activity-related (PC 2). These PCs explained 58% of the variability in our data. The animals were distributed evenly within the two behavioural dimensions independent of their sex. Calves with different scores in these PCs differed significantly in HRV, and thus in the autonomous nervous system's activity. Based on these combined behavioural and physiological data we described four distinct temperament types resulting from two behavioural dimensions: "neophobic/fearful--alert", "interested--stressed", "subdued/uninterested--calm", and "neoophilic/outgoing--alert". Additionally, 38 calves were tested at 90 and 197 dpn. Using the same PCA-model, they correlated significantly in PC 1 and tended to correlate in PC 2 between the two test ages. Of these calves, 42% expressed a similar behaviour pattern in both dimensions and 47% in one. No differences in temperament scores were found between sexes or breeds. In conclusion, we described distinct temperament types in calves based on behavioural and physiological measures emphasising the benefits of a multidimensional approach.
Continuously tunable optical multidimensional Fourier-transform spectrometer.
Dey, P; Paul, J; Bylsma, J; Deminico, S; Karaiskaj, D
2013-02-01
A multidimensional optical nonlinear spectrometer (MONSTR) is a robust, ultrastable platform consisting of nested and folded Michelson interferometers that can be actively phase stabilized. The MONSTR provides output pulses for nonlinear excitation of materials and phase-stabilized reference pulses for heterodyne detection of the induced signal. This platform generates a square of identical laser pulses that can be adjusted to have arbitrary time delays between them while maintaining phase stability. This arrangement is ideal for performing coherent optical experiments, such as multidimensional Fourier-transform spectroscopy. The present work reports on overcoming some important limitations on the original design of the MONSTR apparatus. One important advantage of the MONSTR is the fact that it is a closed platform, which provides the high stability. Once the optical alignment is performed, it is desirable to maintain the alignment over long periods of time. The previous design of the MONSTR was limited to a narrow spectral range defined by the optical coating of the beam splitters. In order to achieve tunability over a broad spectral range the internal optics needed to be changed. By using broadband coated and wedged beam splitters and compensator plates, combined with modifications of the beam paths, continuous tunability can be achieved from 520 nm to 1100 nm without changing any optics or performing alignment of the internal components of the MONSTR. Furthermore, in order to achieve continuous tunability in the spectral region between 520 nm and 720 nm, crucially important for studies on numerous biological molecules, a single longitudinal mode laser at 488.5 nm was identified and used as a metrology laser. The shorter wavelength of the metrology laser as compared to the usual HeNe laser has also increased the phase stability of the system. Finally, in order to perform experiments in the reflection geometry, a simple method to achieve active phase stabilization
Response inhibition and its relation to multidimensional impulsivity.
Wilbertz, Tilmann; Deserno, Lorenz; Horstmann, Annette; Neumann, Jane; Villringer, Arno; Heinze, Hans-Jochen; Boehler, Carsten N; Schlagenhauf, Florian
2014-12-01
Impulsivity is a multidimensional construct that has been suggested as a vulnerability factor for several psychiatric disorders, especially addiction disorders. Poor response inhibition may constitute one facet of impulsivity. Trait impulsivity can be assessed by self-report questionnaires such as the widely used Barratt Impulsiveness Scale (BIS-11). However, regarding the multidimensionality of impulsivity different concepts have been proposed, in particular the UPPS self-report questionnaire ('Urgency', 'Lack of Premeditation', 'Lack of Perseverance', 'Sensation Seeking') that is based on a factor analytic approach. The question as to which aspects of trait impulsivity map on individual differences of the behavioral and neural correlates of response inhibition so far remains unclear. In the present study, we investigated 52 healthy individuals that scored either very high or low on the BIS-11 and underwent a reward-modulated Stop-signal task during fMRI. Neither behavioral nor neural differences were observed with respect to high- and low-BIS groups. In contrast, UPPS subdomain Urgency best explained inter-individual variability in SSRT scores and was further negatively correlated to right IFG/aI activation in 'Stop>Go' trials - a key region for response inhibition. Successful response inhibition in rewarded compared to nonrewarded stop trials yielded ventral striatal (VS) activation which might represent a feedback signal. Interestingly, only participants with low Urgency scores were able to use this VS feedback signal for better response inhibition. Our findings indicate that the relationship of impulsivity and response inhibition has to be treated carefully. We propose Urgency as an important subdomain that might be linked to response inhibition as well as to the use of reward-based neural signals. Based on the present results, further studies examining the influence of impulsivity on psychiatric disorders should take into account Urgency as an important
GPR image signal enhancement and feature extraction using contemporary multidimensional EMD methods
NASA Astrophysics Data System (ADS)
Jeng, Yih; Chen, Chih-Sung
2016-04-01
Although the empirical mode decomposition (EMD) method has been introduced to the geophysical community for more than one decade, most applications are limited to one dimensional (1D) time series analysis or the likes. However, the EMD has long been prone to multidimensional, and the algorithm has been renovated from pseudo type to real multidimensional. There are two parallel novel multidimensional algorithms have been proposed in recent years, i.e. the multidimensional ensemble empirical mode decomposition (MEEMD or MDEEMD) and the multivariate empirical mode decomposition (MEMD). Probably due to the complexity of algorithms and high computation cost, these two multidimensional EMD methods are very little employed to process geophysical data. In this study, we mainly apply the MEMD to the ground penetrating radar (GPR) data processing which, to the best of authors' knowledge, hasn't been done before. The MEMD determines the multidimensional envelopes by projecting data on hyperspheres which extends the 1D algorithm to multidimensional, and the extrema of the data are determined by considering the data in all directions consequently. This renovation technique improves the alignment of intrinsic mode functions (IMFs) and reduces the mode mixing and aliasing problems of the EMD. We demonstrate this method using GPR field data acquired from an area of poor reflection quality. Some modifications of the computation procedures are made to facilitate the application of this approach in the geophysical data processing. To evaluate the success of this approach, MDEEMD results are also presented for comparison.
Czech, Kyle J; Thompson, Blaise J; Kain, Schuyler; Ding, Qi; Shearer, Melinda J; Hamers, Robert J; Jin, Song; Wright, John C
2015-12-22
We report the first coherent multidimensional spectroscopy study of a MoS2 film. A four-layer sample of MoS2 was synthesized on a silica substrate by a simplified sulfidation reaction and characterized by absorption and Raman spectroscopy, atomic force microscopy, and transmission electron microscopy. State-selective coherent multidimensional spectroscopy (CMDS) on the as-prepared MoS2 film resolved the dynamics of a series of diagonal and cross-peak features involving the spin-orbit split A and B excitonic states and continuum states. The spectra are characterized by striped features that are similar to those observed in CMDS studies of quantum wells where the continuum states contribute strongly to the initial excitation of both the diagonal and cross-peak features, while the A and B excitonic states contributed strongly to the final output signal. The strong contribution from the continuum states to the initial excitation shows that the continuum states are coupled to the A and B excitonic states and that fast intraband relaxation is occurring on a sub-70 fs time scale. A comparison of the CMDS excitation signal and the absorption spectrum shows that the relative importance of the continuum states is determined primarily by their absorption strength. Diagonal and cross-peak features decay with a 680 fs time constant characteristic of exciton recombination and/or trapping. The short time dynamics are complicated by coherent and partially coherent pathways that become important when the excitation pulses are temporally overlapped. In this region, the coherent dynamics create diagonal features involving both the excitonic states and continuum states, while the partially coherent pathways contribute to cross-peak features. PMID:26525496
Anusha, L. S.; Nagendra, K. N.
2011-09-01
In two previous papers, we solved the polarized radiative transfer (RT) equation in multi-dimensional (multi-D) geometries with partial frequency redistribution as the scattering mechanism. We assumed Rayleigh scattering as the only source of linear polarization (Q/I, U/I) in both these papers. In this paper, we extend these previous works to include the effect of weak oriented magnetic fields (Hanle effect) on line scattering. We generalize the technique of Stokes vector decomposition in terms of the irreducible spherical tensors T{sup K}{sub Q}, developed by Anusha and Nagendra, to the case of RT with Hanle effect. A fast iterative method of solution (based on the Stabilized Preconditioned Bi-Conjugate-Gradient technique), developed by Anusha et al., is now generalized to the case of RT in magnetized three-dimensional media. We use the efficient short-characteristics formal solution method for multi-D media, generalized appropriately to the present context. The main results of this paper are the following: (1) a comparison of emergent (I, Q/I, U/I) profiles formed in one-dimensional (1D) media, with the corresponding emergent, spatially averaged profiles formed in multi-D media, shows that in the spatially resolved structures, the assumption of 1D may lead to large errors in linear polarization, especially in the line wings. (2) The multi-D RT in semi-infinite non-magnetic media causes a strong spatial variation of the emergent (Q/I, U/I) profiles, which is more pronounced in the line wings. (3) The presence of a weak magnetic field modifies the spatial variation of the emergent (Q/I, U/I) profiles in the line core, by producing significant changes in their magnitudes.
Magnetic quantum tunneling: key insights from multi-dimensional high-field EPR.
Lawrence, J; Yang, E-C; Hendrickson, D N; Hill, S
2009-08-21
Multi-dimensional high-field/frequency electron paramagnetic resonance (HFEPR) spectroscopy is performed on single-crystals of the high-symmetry spin S = 4 tetranuclear single-molecule magnet (SMM) [Ni(hmp)(dmb)Cl](4), where hmp(-) is the anion of 2-hydroxymethylpyridine and dmb is 3,3-dimethyl-1-butanol. Measurements performed as a function of the applied magnetic field strength and its orientation within the hard-plane reveal the four-fold behavior associated with the fourth order transverse zero-field splitting (ZFS) interaction, (1/2)B(S + S), within the framework of a rigid spin approximation (with S = 4). This ZFS interaction mixes the m(s) = +/-4 ground states in second order of perturbation, generating a sizeable (12 MHz) tunnel splitting, which explains the fast magnetic quantum tunneling in this SMM. Meanwhile, multi-frequency measurements performed with the field parallel to the easy-axis reveal HFEPR transitions associated with excited spin multiplets (S < 4). Analysis of the temperature dependence of the intensities of these transitions enables determination of the isotropic Heisenberg exchange constant, J = -6.0 cm(-1), which couples the four spin s = 1 Ni(II) ions within the cluster, as well as a characterization of the ZFS within excited states. The combined experimental studies support recent work indicating that the fourth order anisotropy associated with the S = 4 state originates from second order ZFS interactions associated with the individual Ni(II) centers, but only as a result of higher-order processes that occur via S-mixing between the ground state and higher-lying (S < 4) spin multiplets. We argue that this S-mixing plays an important role in the low-temperature quantum dynamics associated with many other well known SMMs.
NASA Astrophysics Data System (ADS)
Leutenegger, Marcel; Geissbuehler, Matthias; Märki, Iwan; Leitgeb, Rainer A.; Lasser, Theo
2008-02-01
We present a method for fast calculation of the electromagnetic field near the focus of an objective with a high numerical aperture (NA). Instead of direct integration, the vectorial Debye diffraction integral is evaluated with the fast Fourier transform for calculating the electromagnetic field in the entire focal region. We generalize this concept with the chirp z transform for obtaining a flexible sampling grid and an additional gain in computation speed. Under the conditions for the validity of the Debye integral representation, our method yields the amplitude, phase and polarization of the focus field for an arbitrary paraxial input field in the aperture of the objective. Our fast calculation method is particularly useful for engineering the point-spread function or for fast image deconvolution. We present several case studies by calculating the focus fields of high NA oil immersion objectives for various amplitude, polarization and phase distributions of the input field. In addition, the calculation of an extended polychromatic focus field generated by a Bessel beam is presented. This extended focus field is of particular interest for Fourier domain optical coherence tomography because it preserves a lateral resolution of a few micrometers over an axial distance in the millimeter range.
ERIC Educational Resources Information Center
Education Commission of the States, Denver, CO.
This paper provides an overview of Fast ForWord, a CD-ROM and Internet-based training program for children (pre-K to grade 8) with language and reading problems that helps children rapidly build oral language comprehension and other critical skills necessary for learning to read or becoming a better reader. With the help of computers, speech…
Till, C.E.; Chang, Y.I. ); Lineberry, M.J. )
1990-01-01
Argonne National Laboratory, since 1984, has been developing the Integral Fast Reactor (IFR). This paper will describe the way in which this new reactor concept came about; the technical, public acceptance, and environmental issues that are addressed by the IFR; the technical progress that has been made; and our expectations for this program in the near term. 5 refs., 3 figs.
A log-linear multidimensional Rasch model for capture-recapture.
Pelle, E; Hessen, D J; van der Heijden, P G M
2016-02-20
In this paper, a log-linear multidimensional Rasch model is proposed for capture-recapture analysis of registration data. In the model, heterogeneity of capture probabilities is taken into account, and registrations are viewed as dichotomously scored indicators of one or more latent variables that can account for correlations among registrations. It is shown how the probability of a generic capture profile is expressed under the log-linear multidimensional Rasch model and how the parameters of the traditional log-linear model are derived from those of the log-linear multidimensional Rasch model. Finally, an application of the model to neural tube defects data is presented.
Accessing Multi-Dimensional Images and Data Cubes in the Virtual Observatory
NASA Astrophysics Data System (ADS)
Tody, Douglas; Plante, R. L.; Berriman, G. B.; Cresitello-Dittmar, M.; Good, J.; Graham, M.; Greene, G.; Hanisch, R. J.; Jenness, T.; Lazio, J.; Norris, P.; Pevunova, O.; Rots, A. H.
2014-01-01
Telescopes across the spectrum are routinely producing multi-dimensional images and datasets, such as Doppler velocity cubes, polarization datasets, and time-resolved “movies.” Examples of current telescopes producing such multi-dimensional images include the JVLA, ALMA, and the IFU instruments on large optical and near-infrared wavelength telescopes. In the near future, both the LSST and JWST will also produce such multi-dimensional images routinely. High-energy instruments such as Chandra produce event datasets that are also a form of multi-dimensional data, in effect being a very sparse multi-dimensional image. Ensuring that the data sets produced by these telescopes can be both discovered and accessed by the community is essential and is part of the mission of the Virtual Observatory (VO). The Virtual Astronomical Observatory (VAO, http://www.usvao.org/), in conjunction with its international partners in the International Virtual Observatory Alliance (IVOA), has developed a protocol and an initial demonstration service designed for the publication, discovery, and access of arbitrarily large multi-dimensional images. The protocol describing multi-dimensional images is the Simple Image Access Protocol, version 2, which provides the minimal set of metadata required to characterize a multi-dimensional image for its discovery and access. A companion Image Data Model formally defines the semantics and structure of multi-dimensional images independently of how they are serialized, while providing capabilities such as support for sparse data that are essential to deal effectively with large cubes. A prototype data access service has been deployed and tested, using a suite of multi-dimensional images from a variety of telescopes. The prototype has demonstrated the capability to discover and remotely access multi-dimensional data via standard VO protocols. The prototype informs the specification of a protocol that will be submitted to the IVOA for approval, with an
Magnetically assisted fast ignition.
Wang, W-M; Gibbon, P; Sheng, Z-M; Li, Y-T
2015-01-01
Fast ignition (FI) is investigated via integrated particle-in-cell simulation including both generation and transport of fast electrons, where petawatt ignition lasers of 2 ps and compressed targets of a peak density of 300 g cm(-3) and areal density of 0.49 g cm(-2) at the core are taken. When a 20 MG static magnetic field is imposed across a conventional cone-free target, the energy coupling from the laser to the core is enhanced by sevenfold and reaches 14%. This value even exceeds that obtained using a cone-inserted target, suggesting that the magnetically assisted scheme may be a viable alternative for FI. With this scheme, it is demonstrated that two counterpropagating, 6 ps, 6 kJ lasers along the magnetic field transfer 12% of their energy to the core, which is then heated to 3 keV. PMID:25615473
NASA Astrophysics Data System (ADS)
Uvarov, I. V.; Postnikov, A. V.; Svetovoy, V. B.
2016-03-01
Lack of fast and strong microactuators is a well-recognized problem in MEMS community. Electrochemical actuators can develop high pressure but they are notoriously slow. Water electrolysis produced by short voltage pulses of alternating polarity can overcome the problem of slow gas termination. Here we demonstrate an actuation regime, for which the gas pressure is relaxed just for 10 μs or so. The actuator consists of a microchamber filled with the electrolyte and covered with a flexible membrane. The membrane bends outward when the pressure in the chamber increases. Fast termination of gas and high pressure developed in the chamber are related to a high density of nanobubbles in the chamber. The physical processes happening in the chamber are discussed so as problems that have to be resolved for practical applications of this actuation regime. The actuator can be used as a driving engine for microfluidics.
Testing the multidimensionality of the inventory of school motivation in a Dutch student sample.
Korpershoek, Hanke; Xu, Kun; Mok, Magdalena Mo Ching; McInerney, Dennis M; van der Werf, Greetje
2015-01-01
A factor analytic and a Rasch measurement approach were applied to evaluate the multidimensional nature of the school motivation construct among more than 7,000 Dutch secondary school students. The Inventory of School Motivation (McInerney and Ali, 2006) was used, which intends to measure four motivation dimensions (mastery, performance, social, and extrinsic motivation), each comprising of two first-order factors. One unidimensional model and three multidimensional models (4-factor, 8-factor, higher order) were fit to the data. Results of both approaches showed that the multidimensional models validly represented the school motivation among Dutch secondary school pupils, whereas model fit of the unidimensional model was poor. The differences in model fit between the three multidimensional models were small, although a different model was favoured by the two approaches. The need for improvement of some of the items and the need to increase measurement precision of several first-order factors are discussed. PMID:25562335
ERIC Educational Resources Information Center
Dori, Yehudit J.; Hameiri, Mira
1998-01-01
Details the development of a multidimensional problem analysis, classification, and authoring method used to improve student understanding of the mole concept. Includes the results of assessment of the studyware. Contains 46 references. (DDR)
ERIC Educational Resources Information Center
Whitehead, James R.; Corbin, Charles B.
1988-01-01
Trial administrations of the FITLOC, multidimensional scales for the measurement of locus of control of reinforcement for physical fitness behavior, provided preliminary evidence for the scales' reliability and validity. (Author/CB)
ERIC Educational Resources Information Center
Redfield, Joel
1978-01-01
TMFA, a FORTRAN program for three-mode factor analysis and individual-differences multidimensional scaling, is described. Program features include a variety of input options, extensive preprocessing of input data, and several alternative methods of analysis. (Author)
ERIC Educational Resources Information Center
Kim, Chulwan; Rangaswamy, Arvind; DeSarbo, Wayne S.
1999-01-01
Presents an approach to multidimensional unfolding that reduces the occurrence of degenerate solutions and conducts a Monte Carlo study to demonstrate the superiority of the new method to the ALSCAL and KYST nonmetric procedures for student preference data. (SLD)
NASA Astrophysics Data System (ADS)
Chadwick, Alan V.
Fast ion conductors, sometimes referred to as superionic conductors or solid electrolytes, are solids with ionic conductivities that are comparable to those found in molten salts and aqueous solutions of strong electrolytes, i.e., 10-2-10 S cm-1. Such materials have been known of for a very long time and some typical examples of the conductivity are shown in Fig. 1, along with sodium chloride as the archetypal normal ionic solid. Faraday [1] first noted the high conductivity of solid lead fluoride (PbF2) and silver sulphide (Ag2S) in the 1830s and silver iodide was known to be unusually high ionic conductor to the German physicists early in the 1900s. However, the materials were regarded as anomalous until the mid 1960s when they became the focus of intense interest to academics and technologists and they have remained at the forefront of materials research [2-4]. The academic aim is to understand the fundamental origin of fast ion behaviour and the technological goal is to utilize the properties in applications, particularly in energy applications such as the electrolyte membranes in solid-state batteries and fuel cells, and in electrochemical sensors. The last four decades has seen an expansion of the types of material that exhibit fast ion behaviour that now extends beyond simple binary ionic crystals to complex solids and even polymeric materials. Over this same period computer simulations of solids has also developed (in fact these methods and the interest in fast ion conductors were almost coincidental in their time of origin) and the techniques have played a key role in this area of research.
Soha, Aria; Chiu, Mickey; Mannel, Eric; Stoll, Sean; Lynch, Don; Boose, Steve; Northacker, Dave; Alfred, Marcus; Lindesay, James; Chujo, Tatsuya; Inaba, Motoi; Nonaka, Toshihiro; Sato, Wataru; Sakatani, Ikumi; Hirano, Masahiro; Choi, Ihnjea
2014-01-15
This is a technical scope of work (TSW) between the Fermi National Accelerator Laboratory (Fermilab) and the experimenters of PHENIX Fast TOF group who have committed to participate in beam tests to be carried out during the FY2014 Fermilab Test Beam Facility program. The goals for this test beam experiment are to verify the timing performance of the two types of time-of-flight detector prototypes.
Fast track evaluation methodology.
Duke, J R
1991-06-01
Evaluating hospital information systems has taken a variety of forms since the initial development and use of automation. The process itself has moved from a hardware-based orientation controlled by data processing professionals to systems solutions and a user-driven process overseen by management. At Harbor Hospital Center in Baltimore, a fast track methodology has been introduced to shorten system evaluation time to meet the rapid changes that constantly affect the healthcare industry.
NASA Technical Reports Server (NTRS)
1996-01-01
The NASA Fast Track Study supports the efforts of a Special Study Group (SSG) made up of members of the Advanced Project Management Class number 23 (APM-23) that met at the Wallops Island Management Education Center from April 28 - May 8, 1996. Members of the Class expressed interest to Mr. Vem Weyers in having an input to the NASA Policy Document (NPD) 7120.4, that will replace NASA Management Institute (NMI) 7120.4, and the NASA Program/Project Management Guide. The APM-23 SSG was tasked with assisting in development of NASA policy on managing Fast Track Projects, defined as small projects under $150 million and completed within three years. 'Me approach of the APM-23 SSG was to gather data on successful projects working in a 'Better, Faster, Cheaper' environment, within and outside of NASA and develop the Fast Track Project section of the NASA Program/Project Management Guide. Fourteen interviews and four other data gathering efforts were conducted by the SSG, and 16 were conducted by Strategic Resources, Inc. (SRI), including five interviews at the Jet Propulsion Laboratory (JPL) and one at the Applied Physics Laboratory (APL). The interviews were compiled and analyzed for techniques and approaches commonly used to meet severe cost and schedule constraints.
NASA Astrophysics Data System (ADS)
Mar, Mark H.
1990-11-01
The purpose of this paper is to report the results of testing the fast Hartley transform (FHT) and comparing it with the fast Fourier transform (FFT). All the definitions and equations in this paper are quoted and cited from the series of references. The author of this report developed a FORTRAN program which computes the Hartley transform. He tested the program with a generalized electromagnetic pulse waveform and verified the results with the known value. Fourier analysis is an essential tool to obtain frequency domain information from transient time domain signals. The FFT is a popular tool to process many of today's audio and electromagnetic signals. System frequency response, digital filtering of signals, and signal power spectrum are the most practical applications of the FFT. However, the Fourier integral transform of the FFT requires computer resources appropriate for the complex arithmetic operations. On the other hand, the FHT can accomplish the same results faster and requires fewer computer resources. The FHT is twice as fast as the FFT, uses only half the computer resources, and so could be more useful than the FFT in typical applications such as spectral analysis, signal processing, and convolution. This paper presents a FORTRAN computer program for the FHT algorithm along with a brief description and compares the results and performance of the FHT and the FFT algorithms.
Johnstone, A M
2007-05-01
Adult humans often undertake acute fasts for cosmetic, religious or medical reasons. For example, an estimated 14% of US adults have reported using fasting as a means to control body weight and this approach has long been advocated as an intermittent treatment for gross refractory obesity. There are unique historical data sets on extreme forms of food restriction that give insight into the consequences of starvation or semi-starvation in previously healthy, but usually non-obese subjects. These include documented medical reports on victims of hunger strike, famine and prisoners of war. Such data provide a detailed account on how the body adapts to prolonged starvation. It has previously been shown that fasting for the biblical period of 40 days and 40 nights is well within the overall physiological capabilities of a healthy adult. However, the specific effects on the human body and mind are less clearly documented, either in the short term (hours) or in the longer term (days). This review asks the following three questions, pertinent to any weight-loss therapy, (i) how effective is the regime in achieving weight loss, (ii) what impact does it have on psychology? and finally, (iii) does it work long-term? PMID:17444963
Abramavicius, Darius; Mukamel, Shaul
2004-05-01
Sequences of carefully timed and shaped optical pulses provide femtosecond snapshots of molecular structure as well as electronic and vibrational dynamical processes, in analogy with multidimensional NMR. We apply a genetic learning algorithm towards the design of pulse sequences which simplify the multidimensional signals by controlling the relative intensities of various peaks. Numerical simulations demonstrate how poorly resolved weak features may be amplified and observed by using optimized optical pulses, specifically shaped to achieve a desired spectroscopic target.
Neighborhood fast food availability and fast food consumption
Oexle, Nathalie; Barnes, Timothy L; Blake, Christine E; Bell, Bethany A; Liese, Angela D
2015-01-01
Recent nutritional and public health research has focused on how the availability of various types of food in a person’s immediate area or neighborhood influences his or her food choices and eating habits. It has been theorized that people living in areas with a wealth of unhealthy fast-food options may show higher levels of fast-food consumption, a factor that often coincides with being overweight or obese. However, measuring food availability in a particular area is difficult to achieve consistently: there may be differences in the strict physical locations of food options as compared to how individuals perceive their personal food availability, and various studies may use either one or both of these measures. The aim of this study was to evaluate the association between weekly fast-food consumption and both a person’s perceived availability of fast-food and an objective measure of fast-food presence—Geographic Information Systems (GIS)—within that person’s neighborhood. A randomly selected population-based sample of eight counties in South Carolina was used to conduct a cross-sectional telephone survey assessing self-report fast-food consumption and perceived availability of fast food. GIS was used to determine the actual number of fast-food outlets within each participant’s neighborhood. Using multinomial logistic regression analyses, we found that neither perceived availability nor GIS-based presence of fast-food was significantly associated with weekly fast-food consumption. Our findings indicate that availability might not be the dominant factor influencing fast-food consumption. We recommend using subjective availability measures and considering individual characteristics that could influence both perceived availability of fast food and its impact on fast-food consumption. If replicated, our findings suggest that interventions aimed at reducing fast-food consumption by limiting neighborhood fast-food availability might not be completely
Neighborhood fast food availability and fast food consumption.
Oexle, Nathalie; Barnes, Timothy L; Blake, Christine E; Bell, Bethany A; Liese, Angela D
2015-09-01
Recent nutritional and public health research has focused on how the availability of various types of food in a person's immediate area or neighborhood influences his or her food choices and eating habits. It has been theorized that people living in areas with a wealth of unhealthy fast-food options may show higher levels of fast-food consumption, a factor that often coincides with being overweight or obese. However, measuring food availability in a particular area is difficult to achieve consistently: there may be differences in the strict physical locations of food options as compared to how individuals perceive their personal food availability, and various studies may use either one or both of these measures. The aim of this study was to evaluate the association between weekly fast-food consumption and both a person's perceived availability of fast-food and an objective measure of fast-food presence - Geographic Information Systems (GIS) - within that person's neighborhood. A randomly selected population-based sample of eight counties in South Carolina was used to conduct a cross-sectional telephone survey assessing self-report fast-food consumption and perceived availability of fast food. GIS was used to determine the actual number of fast-food outlets within each participant's neighborhood. Using multinomial logistic regression analyses, we found that neither perceived availability nor GIS-based presence of fast-food was significantly associated with weekly fast-food consumption. Our findings indicate that availability might not be the dominant factor influencing fast-food consumption. We recommend using subjective availability measures and considering individual characteristics that could influence both perceived availability of fast food and its impact on fast-food consumption. If replicated, our findings suggest that interventions aimed at reducing fast-food consumption by limiting neighborhood fast-food availability might not be completely effective.
Neighborhood fast food availability and fast food consumption.
Oexle, Nathalie; Barnes, Timothy L; Blake, Christine E; Bell, Bethany A; Liese, Angela D
2015-09-01
Recent nutritional and public health research has focused on how the availability of various types of food in a person's immediate area or neighborhood influences his or her food choices and eating habits. It has been theorized that people living in areas with a wealth of unhealthy fast-food options may show higher levels of fast-food consumption, a factor that often coincides with being overweight or obese. However, measuring food availability in a particular area is difficult to achieve consistently: there may be differences in the strict physical locations of food options as compared to how individuals perceive their personal food availability, and various studies may use either one or both of these measures. The aim of this study was to evaluate the association between weekly fast-food consumption and both a person's perceived availability of fast-food and an objective measure of fast-food presence - Geographic Information Systems (GIS) - within that person's neighborhood. A randomly selected population-based sample of eight counties in South Carolina was used to conduct a cross-sectional telephone survey assessing self-report fast-food consumption and perceived availability of fast food. GIS was used to determine the actual number of fast-food outlets within each participant's neighborhood. Using multinomial logistic regression analyses, we found that neither perceived availability nor GIS-based presence of fast-food was significantly associated with weekly fast-food consumption. Our findings indicate that availability might not be the dominant factor influencing fast-food consumption. We recommend using subjective availability measures and considering individual characteristics that could influence both perceived availability of fast food and its impact on fast-food consumption. If replicated, our findings suggest that interventions aimed at reducing fast-food consumption by limiting neighborhood fast-food availability might not be completely effective. PMID
Multidimensional modelling to investigate interspecies hydrogen transfer in anaerobic biofilms.
Batstone, D J; Picioreanu, C; van Loosdrecht, M C M
2006-09-01
Anaerobic digestion is a multistep process, mediated by a functionally and phylogenetically diverse microbial population. One of the crucial steps is oxidation of organic acids, with electron transfer via hydrogen or formate from acetogenic bacteria to methanogens. This syntrophic microbiological process is strongly restricted by a thermodynamic limitation on the allowable hydrogen or formate concentration. In order to study this process in more detail, we developed an individual-based biofilm model which enables to describe the processes at a microbial resolution. The biochemical model is the ADM1, implemented in a multidimensional domain. With this model, we evaluated three important issues for the syntrophic relationship: (i) Is there a fundamental difference in using hydrogen or formate as electron carrier? (ii) Does a thermodynamic-based inhibition function produced substantially different results from an empirical function? and; (iii) Does the physical co-location of acetogens and methanogens follow directly from a general model. Hydrogen or formate as electron carrier had no substantial impact on model results. Standard inhibition functions or thermodynamic inhibition function gave similar results at larger substrate field grid sizes (> 10 microm), but at smaller grid sizes, the thermodynamic-based function reduced the number of cells with long interspecies distances (> 2.5 microm). Therefore, a very fine grid resolution is needed to reflect differences between the thermodynamic function, and a more generic inhibition form. The co-location of syntrophic bacteria was well predicted without a need to assume a microbiological based mechanism (e.g., through chemotaxis) of biofilm formation.
CASTRO: Multi-dimensional Eulerian AMR Radiation-hydrodynamics Code
NASA Astrophysics Data System (ADS)
CenterComputational Sciences; Engineering (Berkeley); Howell, Louis; Singer, Mike
2011-05-01
CASTRO is a multi-dimensional Eulerian AMR radiation-hydrodynamics code that includes stellar equations of state, nuclear reaction networks, and self-gravity. Initial target applications for CASTRO include Type Ia and Type II supernovae. CASTRO supports calculations in 1-d, 2-d and 3-d Cartesian coordinates, as well as 1-d spherical and 2-d cylindrical (r-z) coordinate systems. Time integration of the hydrodynamics equations is based on an unsplit version of the the piecewise parabolic method (PPM) with new limiters that avoid reducing the accuracy of the scheme at smooth extrema. CASTRO can follow an arbitrary number of isotopes or elements. The atomic weights and amounts of these elements are used to calculate the mean molecular weight of the gas required by the equation of state. CASTRO supports several different approaches to solving for self-gravity. The most general is a full Poisson solve for the gravitational potential. CASTRO also supports a monopole approximation for gravity, and a constant gravity option is also available. The CASTRO software is written in C++ and Fortran, and is based on the BoxLib software framework developed by CCSE.
Classification of multipartite entangled states by multidimensional determinants
Miyake, Akimasa
2003-01-01
We find that multidimensional determinants 'hyperdeterminants', related to entanglement measures (the so-called concurrence, or 3-tangle for two or three qubits, respectively), are derived from a duality between entangled states and separable states. By means of the hyperdeterminant and its singularities, the single copy of multipartite pure entangled states is classified into an onion structure of every closed subset, similar to that by the local rank in the bipartite case. This reveals how inequivalent multipartite entangled classes are partially ordered under local actions. In particular, the generic entangled class of the maximal dimension, distinguished as the nonzero hyperdeterminant, does not include the maximally entangled states in Bell's inequalities in general (e.g., in the n{>=}4 qubits), contrary to the widely known bipartite or three-qubit cases. It suggests that not only are they never locally interconvertible with the majority of multipartite entangled states, but they would have no grounds for the canonical n-partite entangled states. Our classification is also useful for the mixed states.
Zhuang, Wei; Hayashi, Tomoyuki; Mukamel, Shaul
2009-01-01
The response of complex molecules to sequences of femtosecond infrared pulses provides a unique window into their structure, dynamics and fluctuating environments, as projected into the vibrational degrees of freedom. In this review we survey the basic principles of these novel two dimensional infrared (2DIR) analogues of multidimensional NMR. The perturbative approach for computing the nonlinear optical response of coupled localized chromophores is introduced and applied to the amide backbone transitions of protein, liquid water, membrane lipids, and amyloid fibrils. The signals are analyzed using classical MD simulations combined with an effective fluctuating Hamiltonian for coupled localized anharmonic vibrations whose dependence on the local electrostatic environment is parameterized by an ab initio map. Several simulation protocols. Including the Cumulant expansion of Gaussian Fluctuation (CGF), a quasiparticle scattering approach (NEE), the Stochastic Liouville Equations (SLE), and Direct Numerical Propagation are surveyed. These are implemented in a code SPECTRON that interfaces with standard electronic structure and molecular mechanisms MD codes. Chirality-induced techniques which dramatically enhance the resolution are demonstrated. Signatures of conformational and hydrogen bonding fluctuations, protein folding, and chemical exchange processes are discussed. PMID:19415637
Discrete decoding based ultrafast multidimensional nuclear magnetic resonance spectroscopy
Wei, Zhiliang; Lin, Liangjie; Ye, Qimiao; Li, Jing; Cai, Shuhui; Chen, Zhong
2015-07-14
The three-dimensional (3D) nuclear magnetic resonance (NMR) spectroscopy constitutes an important and powerful tool in analyzing chemical and biological systems. However, the abundant 3D information arrives at the expense of long acquisition times lasting hours or even days. Therefore, there has been a continuous interest in developing techniques to accelerate recordings of 3D NMR spectra, among which the ultrafast spatiotemporal encoding technique supplies impressive acquisition speed by compressing a multidimensional spectrum in a single scan. However, it tends to suffer from tradeoffs among spectral widths in different dimensions, which deteriorates in cases of NMR spectroscopy with more dimensions. In this study, the discrete decoding is proposed to liberate the ultrafast technique from tradeoffs among spectral widths in different dimensions by focusing decoding on signal-bearing sites. For verifying its feasibility and effectiveness, we utilized the method to generate two different types of 3D spectra. The proposed method is also applicable to cases with more than three dimensions, which, based on the experimental results, may widen applications of the ultrafast technique.
Multi-Dimensional Calibration of Impact Dynamic Models
NASA Technical Reports Server (NTRS)
Horta, Lucas G.; Reaves, Mercedes C.; Annett, Martin S.; Jackson, Karen E.
2011-01-01
NASA Langley, under the Subsonic Rotary Wing Program, recently completed two helicopter tests in support of an in-house effort to study crashworthiness. As part of this effort, work is on-going to investigate model calibration approaches and calibration metrics for impact dynamics models. Model calibration of impact dynamics problems has traditionally assessed model adequacy by comparing time histories from analytical predictions to test at only a few critical locations. Although this approach provides for a direct measure of the model predictive capability, overall system behavior is only qualitatively assessed using full vehicle animations. In order to understand the spatial and temporal relationships of impact loads as they migrate throughout the structure, a more quantitative approach is needed. In this work impact shapes derived from simulated time history data are used to recommend sensor placement and to assess model adequacy using time based metrics and orthogonality multi-dimensional metrics. An approach for model calibration is presented that includes metric definitions, uncertainty bounds, parameter sensitivity, and numerical optimization to estimate parameters to reconcile test with analysis. The process is illustrated using simulated experiment data.
Implicitly causality enforced solution of multidimensional transient photon transport equation.
Handapangoda, Chintha C; Premaratne, Malin
2009-12-21
A novel method for solving the multidimensional transient photon transport equation for laser pulse propagation in biological tissue is presented. A Laguerre expansion is used to represent the time dependency of the incident short pulse. Owing to the intrinsic causal nature of Laguerre functions, our technique automatically always preserve the causality constrains of the transient signal. This expansion of the radiance using a Laguerre basis transforms the transient photon transport equation to the steady state version. The resulting equations are solved using the discrete ordinates method, using a finite volume approach. Therefore, our method enables one to handle general anisotropic, inhomogeneous media using a single formulation but with an added degree of flexibility owing to the ability to invoke higher-order approximations of discrete ordinate quadrature sets. Therefore, compared with existing strategies, this method offers the advantage of representing the intensity with a high accuracy thus minimizing numerical dispersion and false propagation errors. The application of the method to one, two and three dimensional geometries is provided. PMID:20052050
Entropy of Leukemia on Multidimensional Morphological and Molecular Landscapes
NASA Astrophysics Data System (ADS)
Vilar, Jose M. G.
2014-04-01
Leukemia epitomizes the class of highly complex diseases that new technologies aim to tackle by using large sets of single-cell-level information. Achieving such a goal depends critically not only on experimental techniques but also on approaches to interpret the data. A most pressing issue is to identify the salient quantitative features of the disease from the resulting massive amounts of information. Here, I show that the entropies of cell-population distributions on specific multidimensional molecular and morphological landscapes provide a set of measures for the precise characterization of normal and pathological states, such as those corresponding to healthy individuals and acute myeloid leukemia (AML) patients. I provide a systematic procedure to identify the specific landscapes and illustrate how, applied to cell samples from peripheral blood and bone marrow aspirates, this characterization accurately diagnoses AML from just flow cytometry data. The methodology can generally be applied to other types of cell populations and establishes a straightforward link between the traditional statistical thermodynamics methodology and biomedical applications.
Heterogeneous Data Fusion via Space Alignment Using Nonmetric Multidimensional Scaling
Choo, Jaegul; Bohn, Shawn J.; Nakamura, Grant C.; White, Amanda M.; Park, Haesun
2012-04-26
Heterogeneous data sets are typically represented in different feature spaces, making it difficult to analyze relationships spanning different data sets even when they are semantically related. Data fusion via space alignment can remedy this task by integrating multiple data sets lying in different spaces into one common space. Given a set of reference correspondence data that share the same semantic meaning across different spaces, space alignment attempts to place the corresponding reference data as close together as possible, and accordingly, the entire data are aligned in a common space. Space alignment involves optimizing two potentially conflicting criteria: minimum deformation of the original relationships and maximum alignment between the different spaces. To solve this problem, we provide a novel graph embedding framework for space alignment, which converts each data set into a graph and assigns zero distance between reference correspondence pairs resulting in a single graph. We propose a graph embedding method for fusion based on nonmetric multidimensional scaling (MDS). Its criteria using the rank order rather than the distance allows nonmetric MDS to effectively handle both deformation and alignment. Experiments using parallel data sets demonstrate that our approach works well in comparison to existing methods such as constrained Laplacian eigenmaps, Procrustes analysis, and tensor decomposition. We also present standard cross-domain information retrieval tests as well as interesting visualization examples using space alignment.
Efficient VLSI architecture for multi-dimensional discrete wavelet transform
NASA Astrophysics Data System (ADS)
Xiong, Cheng-Yi; Tian, Jin-Wen; Liu, Jian
2005-10-01
Efficient VLSI architectures for multi-dimensional (m-D) discrete wavelet transform (DWT), e.g. m=2, 3, are presented, in which the lifting scheme of DWT is used to reduce efficiently hardware complexity. The parallelism of 2m subbands transforms in lifting-based m-D DWT is explored, which increases efficiently the throughput rate of separable m-D DWT. The proposed architecture is composed of m2m-1 1-D DWT modules working in parallel and pipelined, which is designed to process 2m input samples per clock cycle, and generate 2m subbands coefficients synchronously. The total time of computing one level of decomposition for a 2-D image (3-D image sequence) of size N2 (MN2) is approximately N2/4 (MN2/8) intra- clock cycles (ccs). An efficient line-based architecture framework for both 2D+t and t+2D 3-D DWT is first proposed. Compared with the similar works reported in previous literature, the proposed architecture has good performance in terms of production of computation time and hardware cost. The proposed architecture is simple, regular, scalable and well suited for VLSI implementation.
GPLOM: the generalized plot matrix for visualizing multidimensional multivariate data.
Im, Jean-François; McGuffin, Michael J; Leung, Rock
2013-12-01
Scatterplot matrices (SPLOMs), parallel coordinates, and glyphs can all be used to visualize the multiple continuous variables (i.e., dependent variables or measures) in multidimensional multivariate data. However, these techniques are not well suited to visualizing many categorical variables (i.e., independent variables or dimensions). To visualize multiple categorical variables, 'hierarchical axes' that 'stack dimensions' have been used in systems like Polaris and Tableau. However, this approach does not scale well beyond a small number of categorical variables. Emerson et al. [8] extend the matrix paradigm of the SPLOM to simultaneously visualize several categorical and continuous variables, displaying many kinds of charts in the matrix depending on the kinds of variables involved. We propose a variant of their technique, called the Generalized Plot Matrix (GPLOM). The GPLOM restricts Emerson et al.'s technique to only three kinds of charts (scatterplots for pairs of continuous variables, heatmaps for pairs of categorical variables, and barcharts for pairings of categorical and continuous variable), in an effort to make it easier to understand. At the same time, the GPLOM extends Emerson et al.'s work by demonstrating interactive techniques suited to the matrix of charts. We discuss the visual design and interactive features of our GPLOM prototype, including a textual search feature allowing users to quickly locate values or variables by name. We also present a user study that compared performance with Tableau and our GPLOM prototype, that found that GPLOM is significantly faster in certain cases, and not significantly slower in other cases.
Multidimensional scaling of multiplex data: human milk cytokines.
Groer, Maureen W; Beckstead, Jason W
2011-07-01
The purpose of this study was to use multidimensional scaling (MDS) and cluster-analytic techniques to examine how cytokine levels from a large multiplex assay of human milk samples covary. Milk samples were collected at 4-6 weeks postpartum from 57 women and were assayed by Luminex multiplex technology for 20 cytokines, chemokines, and growth factors. The MDS was applied to a proximity-score matrix based on these values. A three-dimensional (3D) space was sufficient to accommodate the configuration of relationships. Cytokines that covaried in their concentrations were assigned similar coordinates and plotted close together in 3D space. Several clusters of cytokines were identified. Since very little is known about the origins and functions of cytokines in milk, this approach may provide new clues that will guide future explorations of origins and functional relationships of the separate clusters. This analytical tool may provide a new approach to understanding the physiology of milk cytokines and may be generalizable to multiplex data in general.
Multi-Dimensional Dynamics of Human Electromagnetic Brain Activity
Kida, Tetsuo; Tanaka, Emi; Kakigi, Ryusuke
2016-01-01
Magnetoencephalography (MEG) and electroencephalography (EEG) are invaluable neuroscientific tools for unveiling human neural dynamics in three dimensions (space, time, and frequency), which are associated with a wide variety of perceptions, cognition, and actions. MEG/EEG also provides different categories of neuronal indices including activity magnitude, connectivity, and network properties along the three dimensions. In the last 20 years, interest has increased in inter-regional connectivity and complex network properties assessed by various sophisticated scientific analyses. We herein review the definition, computation, short history, and pros and cons of connectivity and complex network (graph-theory) analyses applied to MEG/EEG signals. We briefly describe recent developments in source reconstruction algorithms essential for source-space connectivity and network analyses. Furthermore, we discuss a relatively novel approach used in MEG/EEG studies to examine the complex dynamics represented by human brain activity. The correct and effective use of these neuronal metrics provides a new insight into the multi-dimensional dynamics of the neural representations of various functions in the complex human brain. PMID:26834608
The Role of CT Scanning in Multidimensional Phenotyping of COPD
2011-01-01
Background: COPD is a heterogeneous disease characterized by airflow obstruction and diagnosed by lung function. CT imaging is emerging as an important, noninvasive tool in phenotyping COPD. However, the use of CT imaging in defining the disease heterogeneity above lung function is not fully known. Methods: Seventy-five patients with COPD (58 men, 17 women) were studied with CT imaging and with measures of airway inflammation. Airway physiology and health status were also determined. Results: The presence of emphysema (EM), bronchiectasis (BE), and bronchial wall thickening (BWT) was found in 67%, 27%, and 27% of subjects, respectively. The presence of EM was associated with lower lung function (mean difference % FEV1, −20%; 95% CI, −28 to −11; P < .001). There was no difference in airway inflammation, exacerbation frequency, or bacterial load in patients with EM alone or with BE and/or BWT ± EM. The diffusing capacity of the lung for carbon monoxide/alveolar volume ratio was the most sensitive and specific parameter in identifying EM (area under the receiver operator characteristic curve, 0.87; 95% CI, 0.79-0.96). Physiologic cluster analysis identified three clusters, two of which were EM predominant and the third characterized by a heterogeneous combination of EM and BE. Conclusions: The application of CT imaging can be useful as a tool in the multidimensional approach to phenotyping patients with COPD. PMID:21454400
Exploring perceptually similar cases with multi-dimensional scaling
NASA Astrophysics Data System (ADS)
Wang, Juan; Yang, Yongyi; Wernick, Miles N.; Nishikawa, Robert M.
2014-03-01
Retrieving a set of known lesions similar to the one being evaluated might be of value for assisting radiologists to distinguish between benign and malignant clustered microcalcifications (MCs) in mammograms. In this work, we investigate how perceptually similar cases with clustered MCs may relate to one another in terms of their underlying characteristics (from disease condition to image features). We first conduct an observer study to collect similarity scores from a group of readers (five radiologists and five non-radiologists) on a set of 2,000 image pairs, which were selected from 222 cases based on their images features. We then explore the potential relationship among the different cases as revealed by their similarity ratings. We apply the multi-dimensional scaling (MDS) technique to embed all the cases in a 2-D plot, in which perceptually similar cases are placed in close vicinity of one another based on their level of similarity. Our results show that cases having different characteristics in their clustered MCs are accordingly placed in different regions in the plot. Moreover, cases of same pathology tend to be clustered together locally, and neighboring cases (which are more similar) tend to be also similar in their clustered MCs (e.g., cluster size and shape). These results indicate that subjective similarity ratings from the readers are well correlated with the image features of the underlying MCs of the cases, and that perceptually similar cases could be of diagnostic value for discriminating between malignant and benign cases.
Multidimensional electron-photon transport with standard discrete ordinates codes
Drumm, C.R.
1997-04-01
A method is described for generating electron cross sections that are comparable with standard discrete ordinates codes without modification. There are many advantages of using an established discrete ordinates solver, e.g. immediately available adjoint capability. Coupled electron-photon transport capability is needed for many applications, including the modeling of the response of electronics components to space and man-made radiation environments. The cross sections have been successfully used in the DORT, TWODANT and TORT discrete ordinates codes. The cross sections are shown to provide accurate and efficient solutions to certain multidimensional electron-photon transport problems. The key to the method is a simultaneous solution of the continuous-slowing-down (CSD) portion and elastic-scattering portion of the scattering source by the Goudsmit-Saunderson theory. The resulting multigroup-Legendre cross sections are much smaller than the true scattering cross sections that they represent. Under certain conditions, the cross sections are guaranteed positive and converge with a low-order Legendre expansion.
Multidimensional electron-photon transport with standard discrete ordinates codes
Drumm, C.R.
1997-09-01
A method is described for generating electron cross sections that are compatible with standard discrete ordinates codes without modification. There are many advantages to using an established discrete ordinates solver, e.g., immediately available adjoint capability. Coupled electron-photon transport capability is needed for many applications, including the modeling of the response of electronics components to space and synthetic radiation environments. The cross sections have been successfully used in the DORT, TWODANT, and TORT discrete ordinates codes. The cross sections are shown to provide accurate and efficient solutions to certain multidimensional electron-photon transport problems. The key to the method is a simultaneous solution of the continuous-slowing-down and elastic-scattering portions of the scattering source by the Goudsmit-Saunderson theory. The resulting multigroup-Legendre cross sections are much smaller than the true scattering cross sections that they represent. Under certain conditions, the cross sections are guaranteed positive and converge with a low-order Legendre expansion.
Signature neural networks: definition and application to multidimensional sorting problems.
Latorre, Roberto; de Borja Rodriguez, Francisco; Varona, Pablo
2011-01-01
In this paper we present a self-organizing neural network paradigm that is able to discriminate information locally using a strategy for information coding and processing inspired in recent findings in living neural systems. The proposed neural network uses: 1) neural signatures to identify each unit in the network; 2) local discrimination of input information during the processing; and 3) a multicoding mechanism for information propagation regarding the who and the what of the information. The local discrimination implies a distinct processing as a function of the neural signature recognition and a local transient memory. In the context of artificial neural networks none of these mechanisms has been analyzed in detail, and our goal is to demonstrate that they can be used to efficiently solve some specific problems. To illustrate the proposed paradigm, we apply it to the problem of multidimensional sorting, which can take advantage of the local information discrimination. In particular, we compare the results of this new approach with traditional methods to solve jigsaw puzzles and we analyze the situations where the new paradigm improves the performance.
Modified multidimensional scaling approach to analyze financial markets
NASA Astrophysics Data System (ADS)
Yin, Yi; Shang, Pengjian
2014-06-01
Detrended cross-correlation coefficient (σDCCA) and dynamic time warping (DTW) are introduced as the dissimilarity measures, respectively, while multidimensional scaling (MDS) is employed to translate the dissimilarities between daily price returns of 24 stock markets. We first propose MDS based on σDCCA dissimilarity and MDS based on DTW dissimilarity creatively, while MDS based on Euclidean dissimilarity is also employed to provide a reference for comparisons. We apply these methods in order to further visualize the clustering between stock markets. Moreover, we decide to confront MDS with an alternative visualization method, "Unweighed Average" clustering method, for comparison. The MDS analysis and "Unweighed Average" clustering method are employed based on the same dissimilarity. Through the results, we find that MDS gives us a more intuitive mapping for observing stable or emerging clusters of stock markets with similar behavior, while the MDS analysis based on σDCCA dissimilarity can provide more clear, detailed, and accurate information on the classification of the stock markets than the MDS analysis based on Euclidean dissimilarity. The MDS analysis based on DTW dissimilarity indicates more knowledge about the correlations between stock markets particularly and interestingly. Meanwhile, it reflects more abundant results on the clustering of stock markets and is much more intensive than the MDS analysis based on Euclidean dissimilarity. In addition, the graphs, originated from applying MDS methods based on σDCCA dissimilarity and DTW dissimilarity, may also guide the construction of multivariate econometric models.
Medina-Cleghorn, Daniel; Heslin, Ann; Morris, Patrick J.; Mulvihill, Melinda M.; Nomura, Daniel K.
2014-01-01
We are environmentally exposed to countless synthetic chemicals on a daily basis with an increasing number of these chemical exposures linked to adverse health effects. However, our understanding of the (patho)physiological effects of these chemicals remains poorly understood, due in-part to a general lack of effort to systematically and comprehensively identify the direct interactions of environmental chemicals with biological macromolecules in mammalian systems in vivo. Here, we have used functional chemoproteomic and metabolomic platforms to broadly identify direct enzyme targets that are inhibited by widely used organophosphorus (OP) pesticides in vivo in mice and to determine metabolic alterations that are caused by these chemicals. We find that these pesticides directly inhibit over 20 serine hydrolases in vivo leading to widespread disruptions in lipid metabolism. Through identifying direct biological targets of OP pesticides, we show heretofore unrecognized modes of toxicity that may be associated with these agents and underscore the utility of utilizing multidimensional profiling approaches to obtain a more complete understanding of toxicities associated with environmental chemicals. PMID:24205821
Multi-Dimensional Dynamics of Human Electromagnetic Brain Activity.
Kida, Tetsuo; Tanaka, Emi; Kakigi, Ryusuke
2015-01-01
Magnetoencephalography (MEG) and electroencephalography (EEG) are invaluable neuroscientific tools for unveiling human neural dynamics in three dimensions (space, time, and frequency), which are associated with a wide variety of perceptions, cognition, and actions. MEG/EEG also provides different categories of neuronal indices including activity magnitude, connectivity, and network properties along the three dimensions. In the last 20 years, interest has increased in inter-regional connectivity and complex network properties assessed by various sophisticated scientific analyses. We herein review the definition, computation, short history, and pros and cons of connectivity and complex network (graph-theory) analyses applied to MEG/EEG signals. We briefly describe recent developments in source reconstruction algorithms essential for source-space connectivity and network analyses. Furthermore, we discuss a relatively novel approach used in MEG/EEG studies to examine the complex dynamics represented by human brain activity. The correct and effective use of these neuronal metrics provides a new insight into the multi-dimensional dynamics of the neural representations of various functions in the complex human brain. PMID:26834608
Novel Multidimensional Tracers for Geothermal Inter-Well Diagnostics
Tang, Yongchun; Goddard, William A.; Shuler, Patrick; Ma, John; Henderson, Fred; Chan, Ngo Yeung; Wu, Sheng; Banerjee, Sandeep; Vaddadi, Sridhar; Sun, Megan
2013-03-31
This is the Final Report of the three-year project “Novel Multidimensional Tracers for Geothermal Inter-Well Diagnostics” (DE-EE00003032, April 1, 2010 – March 30, 2013), in which we present our major accomplishments with detailed descriptions of our experimental and theoretical efforts. Upon the successful conduction of this project, we have followed our proposed breakdown work structure completing most of the technical tasks. Finally, we have developed and demonstrated the matrix of smart geothermal tracers and the corresponding interpretation tools together with the novel pre-concentration technique – the Hollow Fiber Liquid-Liquid Micro-Extraction (HFLLME), which present superior performance in terms of the ultralow detection limits (up to 10-12g/mL with signal-to-noise ratio of 2); high workable temperature up to 300°C; and the significant enhancement in the characterization of subsurface environment. We have developed in- depth mechanistic understandings on the complicated chemistry involved in the tracer- matrix interaction as well as developed the unique yet effective experimental protocols (screening methodologies, analytical tools, pre-concentration and derivatization techniques) for achieving a highly efficient yet economically feasible and environmentally friendly geothermal tracer system. The most important findings have been reported to DOE in this Final Report and our 12 Quarterly Reports.
The Flux-integral Method for Multidimensional Convection and Diffusion
NASA Technical Reports Server (NTRS)
Leonard, B. P.; Macvean, M. K.; Lock, A. P.
1994-01-01
The flux-integral method is a procedure for constructing an explicit, single-step, forward-in-time, conservative, control volume update of the unsteady, multidimensional convection-diffusion equation. The convective plus diffusive flux at each face of a control-volume cell is estimated by integrating the transported variable and its face-normal derivative over the volume swept out by the convecting velocity field. This yields a unique description of the fluxes, whereas other conservative methods rely on nonunique, arbitrary pseudoflux-difference splitting procedures. The accuracy of the resulting scheme depends on the form of the subcell interpolation assumed, given cell-average data. Cellwise constant behavior results in a (very artificially diffusive) first-order convection scheme. Second-order convection-diffusion schemes correspond to cellwise linear (or bilinear) subcell interpolation. Cellwise quadratic subcell interpolants generate a highly accurate convection-diffusion scheme with excellent phase accuracy. Under constant-coefficient conditions, this is a uniformly third-order polynomial interpolation algorithm (UTOPIA).
Transverse Spin Azimuthal Asymmetries in SIDIS at COMPASS: Multidimensional Analysis
NASA Astrophysics Data System (ADS)
Parsamyan, Bakur
2016-02-01
COMPASS is a high-energy physics experiment operating at the SPS at CERN. Wide physics program of the experiment comprises study of hadron structure and spectroscopy with high energy muon and hadrons beams. As for the muon-program, one of the important objectives of the COMPASS experiment is the exploration of the transverse spin structure of the nucleon via spin (in)dependent azimuthal asymmetries in single-hadron production in deep inelastic scattering of polarized leptons off transversely polarized target. For this purpose a series of measurements were made in COMPASS, using 160 GeV/c longitudinally polarized muon beam and transversely polarized 6LiD (in 2002, 2003 and 2004) and NH3 (in 2007 and 2010) targets. The experimental results obtained by COMPASS for unpolarized target azimuthal asymmetries, Sivers and Collins effects and other azimuthal observables play an important role in the general understanding of the three-dimensional nature of the nucleon. Giving access to the entire twsit-2 set of transverse momentum dependent parton distribution functions and fragmentation functions COMPASS data triggers constant theoretical interest and is being widely used in phenomenological analyses and global data fits. In this review main focus is given to the very recent results obtained by the COMPASS collaboration from first ever multi-dimensional extraction of transverse spin asymmetries.
Multidimensional indexing structure for use with linear optimization queries
NASA Technical Reports Server (NTRS)
Bergman, Lawrence David (Inventor); Castelli, Vittorio (Inventor); Chang, Yuan-Chi (Inventor); Li, Chung-Sheng (Inventor); Smith, John Richard (Inventor)
2002-01-01
Linear optimization queries, which usually arise in various decision support and resource planning applications, are queries that retrieve top N data records (where N is an integer greater than zero) which satisfy a specific optimization criterion. The optimization criterion is to either maximize or minimize a linear equation. The coefficients of the linear equation are given at query time. Methods and apparatus are disclosed for constructing, maintaining and utilizing a multidimensional indexing structure of database records to improve the execution speed of linear optimization queries. Database records with numerical attributes are organized into a number of layers and each layer represents a geometric structure called convex hull. Such linear optimization queries are processed by searching from the outer-most layer of this multi-layer indexing structure inwards. At least one record per layer will satisfy the query criterion and the number of layers needed to be searched depends on the spatial distribution of records, the query-issued linear coefficients, and N, the number of records to be returned. When N is small compared to the total size of the database, answering the query typically requires searching only a small fraction of all relevant records, resulting in a tremendous speedup as compared to linearly scanning the entire dataset.
Developing a Multi-Dimensional Hydrodynamics Code with Astrochemical Reactions
NASA Astrophysics Data System (ADS)
Kwak, Kyujin; Yang, Seungwon
2015-08-01
The Atacama Large Millimeter/submillimeter Array (ALMA) revealed high resolution molecular lines some of which are still unidentified yet. Because formation of these astrochemical molecules has been seldom studied in traditional chemistry, observations of new molecular lines drew a lot of attention from not only astronomers but also chemists both experimental and theoretical. Theoretical calculations for the formation of these astrochemical molecules have been carried out providing reaction rates for some important molecules, and some of theoretical predictions have been measured in laboratories. The reaction rates for the astronomically important molecules are now collected to form databases some of which are publically available. By utilizing these databases, we develop a multi-dimensional hydrodynamics code that includes the reaction rates of astrochemical molecules. Because this type of hydrodynamics code is able to trace the molecular formation in a non-equilibrium fashion, it is useful to study the formation history of these molecules that affects the spatial distribution of some specific molecules. We present the development procedure of this code and some test problems in order to verify and validate the developed code.
Multidimensional representation of odors in the human olfactory cortex.
Fournel, A; Ferdenzi, C; Sezille, C; Rouby, C; Bensafi, M
2016-06-01
What is known as an odor object is an integrated representation constructed from physical features, and perceptual attributes mainly mediated by the olfactory and trigeminal systems. The aim of the present study was to comprehend how this multidimensional representation is organized, by deciphering how similarities in the physical, olfactory and trigeminal perceptual spaces of odors are represented in the human brain. To achieve this aim, we combined psychophysics, functional MRI and multivariate representational similarity analysis. Participants were asked to smell odors diffused by an fMRI-compatible olfactometer and to rate each smell along olfactory dimensions (pleasantness, intensity, familiarity and edibility) and trigeminal dimensions (irritation, coolness, warmth and pain). An event-related design was implemented, presenting different odorants. Results revealed that (i) pairwise odorant similarities in anterior piriform cortex (PC) activity correlated with pairwise odorant similarities in chemical properties (P < 0.005), (ii) similarities in posterior PC activity correlated with similarities in olfactory perceptual properties (P <0.01), and (iii) similarities in amygdala activity correlated with similarities in trigeminal perceptual properties (P < 0.01). These findings provide new evidence that extraction of physical, olfactory and trigeminal features is based on specific fine processing of similarities between odorous stimuli in a distributed manner in the olfactory system. Hum Brain Mapp 37:2161-2172, 2016. © 2016 Wiley Periodicals, Inc. PMID:26991044
Discrete decoding based ultrafast multidimensional nuclear magnetic resonance spectroscopy
NASA Astrophysics Data System (ADS)
Wei, Zhiliang; Lin, Liangjie; Ye, Qimiao; Li, Jing; Cai, Shuhui; Chen, Zhong
2015-07-01
The three-dimensional (3D) nuclear magnetic resonance (NMR) spectroscopy constitutes an important and powerful tool in analyzing chemical and biological systems. However, the abundant 3D information arrives at the expense of long acquisition times lasting hours or even days. Therefore, there has been a continuous interest in developing techniques to accelerate recordings of 3D NMR spectra, among which the ultrafast spatiotemporal encoding technique supplies impressive acquisition speed by compressing a multidimensional spectrum in a single scan. However, it tends to suffer from tradeoffs among spectral widths in different dimensions, which deteriorates in cases of NMR spectroscopy with more dimensions. In this study, the discrete decoding is proposed to liberate the ultrafast technique from tradeoffs among spectral widths in different dimensions by focusing decoding on signal-bearing sites. For verifying its feasibility and effectiveness, we utilized the method to generate two different types of 3D spectra. The proposed method is also applicable to cases with more than three dimensions, which, based on the experimental results, may widen applications of the ultrafast technique.
Individual differences in anxiety and executive functioning: a multidimensional view.
Visu-Petra, Laura; Miclea, Mircea; Visu-Petra, George
2013-01-01
The relationship between individual differences in anxiety and executive functioning was investigated in a sample of young adults. Verbal and spatial working memory, resistance to interference, negative priming, and task-switching measures were used to assess three executive functioning dimensions: updating, inhibition, and shifting. An additional index of basic psychomotor speed was added to this cognitive battery. According to the multidimensional interaction model of anxiety proposed by Endler (1997), state (cognitive-worry and autonomic-emotional) and trait (related to social evaluation, physical danger, ambiguous situations, and daily routines) anxiety were assessed in this evaluation context. Results indicated that shifting and inhibition (negative priming) efficiency were negatively related to state (cognitive-worry) and trait (related to social evaluation) anxiety. However, there was a relative advantage of subjects higher in social evaluation apprehensions in their memory updating performance. The results are consistent with several predictions of the attentional control theory (Eysenck, Derakshan, Santos, & Calvo, 2007), and are relevant for research regarding the interaction of situational, personality, and cognitive functioning dimensions.
On non-singular solutions in multidimensional cosmology
Melnikov, V. N.
2009-05-18
Exact solutions with an exponential behaviour of the scale factors are considered in a multidimensional cosmological model describing the dynamics of n+1 Ricci-flat factor spaces M{sub i} in the presence of a one-component perfect fluid. The pressures in all spaces are proportional to the density: p{sub i} = w{sub i}{rho}, i = 0,...,n. Solutions with accelerated expansion of our 3-space M{sub 0} and a small enough variation of the gravitational constant G are found.A family of generalized non-singular S-brane solutions with orthogonal intersection rules and n Ricci-flat factor spaces in the theory with several scalar fields, antisymmetric forms and multiple scalar potential is considered. The solution possess exponential behaviour of scale factors. These solutions contain a sub-family of solutions with accelerated expansion of certain factor spaces. Some examples of solutions with exponential dependence of one scale factor and constant scale factors of ''internal'' spaces (e.g. Freund-Rubin type solutions) are also considered.
Multidimensional representation of odors in the human olfactory cortex.
Fournel, A; Ferdenzi, C; Sezille, C; Rouby, C; Bensafi, M
2016-06-01
What is known as an odor object is an integrated representation constructed from physical features, and perceptual attributes mainly mediated by the olfactory and trigeminal systems. The aim of the present study was to comprehend how this multidimensional representation is organized, by deciphering how similarities in the physical, olfactory and trigeminal perceptual spaces of odors are represented in the human brain. To achieve this aim, we combined psychophysics, functional MRI and multivariate representational similarity analysis. Participants were asked to smell odors diffused by an fMRI-compatible olfactometer and to rate each smell along olfactory dimensions (pleasantness, intensity, familiarity and edibility) and trigeminal dimensions (irritation, coolness, warmth and pain). An event-related design was implemented, presenting different odorants. Results revealed that (i) pairwise odorant similarities in anterior piriform cortex (PC) activity correlated with pairwise odorant similarities in chemical properties (P < 0.005), (ii) similarities in posterior PC activity correlated with similarities in olfactory perceptual properties (P <0.01), and (iii) similarities in amygdala activity correlated with similarities in trigeminal perceptual properties (P < 0.01). These findings provide new evidence that extraction of physical, olfactory and trigeminal features is based on specific fine processing of similarities between odorous stimuli in a distributed manner in the olfactory system. Hum Brain Mapp 37:2161-2172, 2016. © 2016 Wiley Periodicals, Inc.
Structural dynamics in complex liquids studied with multidimensional vibrational spectroscopy
Tokmakoff, Andrei
2013-08-31
The development of new sustainable energy sources is linked to our understanding of the molecular properties of water and aqueous solutions. Energy conversion, storage, and transduction processes, particularly those that occur in biology, fuel cells, and batteries, make use of water for the purpose of moving energy in the form of charges and mediating the redox chemistry that allows this energy to be stored as and released from chemical bonds. To build our fundamental knowledge in this area, this project supports work in the Tokmakoff group to investigate the molecular dynamics of water’s hydrogen bond network, and how these dynamics influence its solutes and the mechanism of proton transport in water. To reach the goals of this grant, we developed experiments to observe molecular dynamics in water as directly as possible, using ultrafast multidimensional vibrational spectroscopy. We excite and probe broad vibrational resonances of water, molecular solutes, and protons in water. By correlating how molecules evolve from an initial excitation frequency to a final frequency, we can describe the underlying molecular dynamics. Theoretical modeling of the data with the help of computational spectroscopy coupled with molecular dynamics simulations provided the atomistic insight in these studies.
Perceptual Dominant Color Extraction by Multidimensional Particle Swarm Optimization
NASA Astrophysics Data System (ADS)
Kiranyaz, Serkan; Uhlmann (Eurasip Member), Stefan; Ince, Turker; Gabbouj, Moncef
2010-12-01
Color is the major source of information widely used in image analysis and content-based retrieval. Extracting dominant colors that are prominent in a visual scenery is of utmost importance since the human visual system primarily uses them for perception and similarity judgment. In this paper, we address dominant color extraction as a dynamic clustering problem and use techniques based on Particle Swarm Optimization (PSO) for finding optimal (number of) dominant colors in a given color space, distance metric and a proper validity index function. The first technique, so-called Multidimensional (MD) PSO can seek both positional and dimensional optima. Nevertheless, MD PSO is still susceptible to premature convergence due to lack of divergence. To address this problem we then apply Fractional Global Best Formation (FGBF) technique. In order to extract perceptually important colors and to further improve the discrimination factor for a better clustering performance, an efficient color distance metric, which uses a fuzzy model for computing color (dis-) similarities over HSV (or HSL) color space is proposed. The comparative evaluations against MPEG-7 dominant color descriptor show the superiority of the proposed technique.
Online Nanoflow Multidimensional Fractionation for High Efficiency Phosphopeptide Analysis*
Ficarro, Scott B.; Zhang, Yi; Carrasco-Alfonso, Marlene J.; Garg, Brijesh; Adelmant, Guillaume; Webber, James T.; Luckey, C. John; Marto, Jarrod A.
2011-01-01
Despite intense, continued interest in global analyses of signaling cascades through mass spectrometry-based studies, the large-scale, systematic production of phosphoproteomics data has been hampered in-part by inefficient fractionation strategies subsequent to phosphopeptide enrichment. Here we explore two novel multidimensional fractionation strategies for analysis of phosphopeptides. In the first technique we utilize aliphatic ion pairing agents to improve retention of phosphopeptides at high pH in the first dimension of a two-dimensional RP-RP. The second approach is based on the addition of strong anion exchange as the second dimension in a three-dimensional reversed phase (RP)-strong anion exchange (SAX)-RP configuration. Both techniques provide for automated, online data acquisition, with the 3-D platform providing the highest performance both in terms of separation peak capacity and the number of unique phosphopeptide sequences identified per μg of cell lysate consumed. Our integrated RP-SAX-RP platform provides several analytical figures of merit, including: (1) orthogonal separation mechanisms in each dimension; (2) high separation peak capacity (3) efficient retention of singly- and multiply-phosphorylated peptides; (4) compatibility with automated, online LC-MS analysis. We demonstrate the reproducibility of RP-SAX-RP and apply it to the analysis of phosphopeptides derived from multiple biological contexts, including an in vitro model of acute myeloid leukemia in addition to primary polyclonal CD8+ T-cells activated in vivo through bacterial infection and then purified from a single mouse. PMID:21788404
Spectral viscosity approximations to multidimensional scalar conservation laws
Chen, Gui-Qiang ); Du, Qiang ); Tadmor, E. )
1993-10-01
The authors study the spectral viscosity (SV) method in the context of multidimensional scalar conservation laws with periodic boundary conditions. They show that the spectral viscosity, which is sufficiently small to retain the formal spectral accuracy of the underlying Fourier approximation, is large enough to enforce the correct amount of entropy dissipation (which is otherwise missing in the standard Fourier method). Moreover, they prove that because of the presence of the spectral viscosity, the truncation error in this case becomes spectrally small, independent of whether the underlying solution is smooth or not. Consequently, the SV approximation remains uniformly bounded and converges to a measure-valued solution satisfying the entropy condition, that is, the unique entropy solution. They also show that the SV solution has a bounded total variation, provided that the total variation of the initial data is bounded, thus confirming its strong convergence to the entropy solution. They obtain an L[sup 1] convergence rate of the usual optimal order one-half. 22 refs.
Best practices in wraparound: a multidimensional view of the evidence.
Walter, Uta M; Petr, Christopher G
2011-01-01
This article presents a systematic review of the effectiveness of wraparound, a value-guided, widely used service planning process and philosophy of care originally developed for children with serious emotional disturbance and their families. In contrast to conventional systematic reviews, which concentrate on the empirical literature, this article uses the multidimensional evidence-based practice approach, which adds professional knowledge and consumer perspectives to a value-critical analysis. The findings contextualize the limited empirical support for wraparound within a social work value frame, suggesting areas of improvement for the implementation of the wraparound model. A broader ecological frame for wraparound highlights the need to include more natural supports on teams, to ensure backing from higher level administrators, and to emphasize client self-determination. Youths and families should be afforded leadership roles on teams and be supported by parent advocates. To extend the empowerment idea of wraparound beyond the individual case level, a clear commitment to social justice by working toward systems changes must be added.
ERIC Educational Resources Information Center
Charner, Ivan; Fraser, Bryna Shore
A study examined the employment of Hispanics in the fast-food industry. Data were obtained from a national survey of employees at 279 fast-food restaurants from seven companies in which 194 (4.2 percent) of the 4,660 respondents reported being Hispanic. Compared with the total sample, Hispanic fast-food employees were slightly less likely to be…
Simplified fast neutron dosimeter
Sohrabi, Mehdi
1979-01-01
Direct fast-neutron-induced recoil and alpha particle tracks in polycarbonate films may be enlarged for direct visual observation and automated counting procedures employing electrochemical etching techniques. Electrochemical etching is, for example, carried out in a 28% KOH solution at room temperature by applying a 2000 V peak-to-peak voltage at 1 kHz frequency. Such recoil particle amplification can be used for the detection of wide neutron dose ranges from 1 mrad. to 1000 rads. or higher, if desired.
NASA Technical Reports Server (NTRS)
Bishop, Matt
1988-01-01
The organization of some tools to help improve passwork security at a UNIX-based site is described along with how to install and use them. These tools and their associated library enable a site to force users to pick reasonably safe passwords (safe being site configurable) and to enable site management to try to crack existing passworks. The library contains various versions of a very fast implementation of the Data Encryption Standard and of the one-way encryption functions used to encryp the password.
DeLuca, P.M. Jr.; Pearson, D.W.
1992-01-01
This progress report concentrates on two major areas of dosimetry research: measurement of fast neutron kerma factors for several elements for monochromatic and white spectrum neutron fields and determination of the response of thermoluminescent phosphors to various ultra-soft X-ray energies and beta-rays. Dr. Zhixin Zhou from the Shanghai Institute of Radiation Medicine, People's Republic of China brought with him special expertise in the fabrication and use of ultra-thin TLD materials. Such materials are not available in the USA. The rather unique properties of these materials were investigated during this grant period.
Detering, Brent A.; Donaldson, Alan D.; Fincke, James R.; Kong, Peter C.; Berry, Ray A.
1999-01-01
A fast quench reaction includes a reactor chamber having a high temperature heating means such as a plasma torch at its inlet and a means of rapidly expanding a reactant stream, such as a restrictive convergent-divergent nozzle at its outlet end. Metal halide reactants are injected into the reactor chamber. Reducing gas is added at different stages in the process to form a desired end product and prevent back reactions. The resulting heated gaseous stream is then rapidly cooled by expansion of the gaseous stream.
Detering, B.A.; Donaldson, A.D.; Fincke, J.R.; Kong, P.C.; Berry, R.A.
1999-08-10
A fast quench reaction includes a reactor chamber having a high temperature heating means such as a plasma torch at its inlet and a means of rapidly expanding a reactant stream, such as a restrictive convergent-divergent nozzle at its outlet end. Metal halide reactants are injected into the reactor chamber. Reducing gas is added at different stages in the process to form a desired end product and prevent back reactions. The resulting heated gaseous stream is then rapidly cooled by expansion of the gaseous stream. 8 figs.
Snell, A.H.
1957-12-01
This patent relates to a reactor and process for carrying out a controlled fast neutron chain reaction. A cubical reactive mass, weighing at least 920 metric tons, of uranium metal containing predominantly U/sup 238/ and having a U/sup 235/ content of at least 7.63% is assembled and the maximum neutron reproduction ratio is limited to not substantially over 1.01 by insertion and removal of a varying amount of boron, the reactive mass being substantially freed of moderator.
NASA Astrophysics Data System (ADS)
Ghosh, Sanjay; Chaudhury, Kunal N.
2016-03-01
We propose a simple and fast algorithm called PatchLift for computing distances between patches (contiguous block of samples) extracted from a given one-dimensional signal. PatchLift is based on the observation that the patch distances can be efficiently computed from a matrix that is derived from the one-dimensional signal using lifting; importantly, the number of operations required to compute the patch distances using this approach does not scale with the patch length. We next demonstrate how PatchLift can be used for patch-based denoising of images corrupted with Gaussian noise. In particular, we propose a separable formulation of the classical nonlocal means (NLM) algorithm that can be implemented using PatchLift. We demonstrate that the PatchLift-based implementation of separable NLM is a few orders faster than standard NLM and is competitive with existing fast implementations of NLM. Moreover, its denoising performance is shown to be consistently superior to that of NLM and some of its variants, both in terms of peak signal-to-noise ratio/structural similarity index and visual quality.
Nguyen, M.N.; /SLAC
2007-06-18
As part of an improvement project on the linear accelerator at SLAC, it was necessary to replace the original thyratron trigger generator, which consisted of two chassis, two vacuum tubes, and a small thyratron. All solid-state, fast rise, and high voltage thyratron drivers, therefore, have been developed and built for the 244 klystron modulators. The rack mounted, single chassis driver employs a unique way to control and generate pulses through the use of an asymmetric SCR, a PFN, a fast pulse transformer, and a saturable reactor. The resulting output pulse is 2 kV peak into 50 {Omega} load with pulse duration of 1.5 {mu}s FWHM at 180 Hz. The pulse risetime is less than 40 ns with less than 1 ns jitter. Various techniques are used to protect the SCR from being damaged by high voltage and current transients due to thyratron breakdowns. The end-of-line clipper (EOLC) detection circuit is also integrated into this chassis to interrupt the modulator triggering in the event a high percentage of line reflections occurred.
Fast Fourier transform telescope
Tegmark, Max; Zaldarriaga, Matias
2009-04-15
We propose an all-digital telescope for 21 cm tomography, which combines key advantages of both single dishes and interferometers. The electric field is digitized by antennas on a rectangular grid, after which a series of fast Fourier transforms recovers simultaneous multifrequency images of up to half the sky. Thanks to Moore's law, the bandwidth up to which this is feasible has now reached about 1 GHz, and will likely continue doubling every couple of years. The main advantages over a single dish telescope are cost and orders of magnitude larger field-of-view, translating into dramatically better sensitivity for large-area surveys. The key advantages over traditional interferometers are cost (the correlator computational cost for an N-element array scales as Nlog{sub 2}N rather than N{sup 2}) and a compact synthesized beam. We argue that 21 cm tomography could be an ideal first application of a very large fast Fourier transform telescope, which would provide both massive sensitivity improvements per dollar and mitigate the off-beam point source foreground problem with its clean beam. Another potentially interesting application is cosmic microwave background polarization.
Multiple-Flat-Panel System Displays Multidimensional Data
NASA Technical Reports Server (NTRS)
Gundo, Daniel; Levit, Creon; Henze, Christopher; Sandstrom, Timothy; Ellsworth, David; Green, Bryan; Joly, Arthur
2006-01-01
The NASA Ames hyperwall is a display system designed to facilitate the visualization of sets of multivariate and multidimensional data like those generated in complex engineering and scientific computations. The hyperwall includes a 77 matrix of computer-driven flat-panel video display units, each presenting an image of 1,280 1,024 pixels. The term hyperwall reflects the fact that this system is a more capable successor to prior computer-driven multiple-flat-panel display systems known by names that include the generic term powerwall and the trade names PowerWall and Powerwall. Each of the 49 flat-panel displays is driven by a rack-mounted, dual-central-processing- unit, workstation-class personal computer equipped with a hig-hperformance graphical-display circuit card and with a hard-disk drive having a storage capacity of 100 GB. Each such computer is a slave node in a master/ slave computing/data-communication system (see Figure 1). The computer that acts as the master node is similar to the slave-node computers, except that it runs the master portion of the system software and is equipped with a keyboard and mouse for control by a human operator. The system utilizes commercially available master/slave software along with custom software that enables the human controller to interact simultaneously with any number of selected slave nodes. In a powerwall, a single rendering task is spread across multiple processors and then the multiple outputs are tiled into one seamless super-display. It must be noted that the hyperwall concept subsumes the powerwall concept in that a single scene could be rendered as a mosaic image on the hyperwall. However, the hyperwall offers a wider set of capabilities to serve a different purpose: The hyperwall concept is one of (1) simultaneously displaying multiple different but related images, and (2) providing means for composing and controlling such sets of images. In place of elaborate software or hardware crossbar switches, the
Multidimensional Clinical Phenotyping of an Adult Cystic Fibrosis Patient Population
Conrad, Douglas J.; Bailey, Barbara A.
2015-01-01
Background Cystic Fibrosis (CF) is a multi-systemic disease resulting from mutations in the Cystic Fibrosis Transmembrane Regulator (CFTR) gene and has major manifestations in the sino-pulmonary, and gastro-intestinal tracts. Clinical phenotypes were generated using 26 common clinical variables to generate classes that overlapped quantiles of lung function and were based on multiple aspects of CF systemic disease. Methods The variables included age, gender, CFTR mutations, FEV1% predicted, FVC% predicted, height, weight, Brasfield chest xray score, pancreatic sufficiency status and clinical microbiology results. Complete datasets were compiled on 211 subjects. Phenotypes were identified using a proximity matrix generated by the unsupervised Random Forests algorithm and subsequent clustering by the Partitioning around Medoids (PAM) algorithm. The final phenotypic classes were then characterized and compared to a similar dataset obtained three years earlier. Findings Clinical phenotypes were identified using a clustering strategy that generated four and five phenotypes. Each strategy identified 1) a low lung health scores phenotype, 2) a younger, well-nourished, male-dominated class, 3) various high lung health score phenotypes that varied in terms of age, gender and nutritional status. This multidimensional clinical phenotyping strategy identified classes with expected microbiology results and low risk clinical phenotypes with pancreatic sufficiency. Interpretation This study demonstrated regional adult CF clinical phenotypes using non-parametric, continuous, ordinal and categorical data with a minimal amount of subjective data to identify clinically relevant phenotypes. These studies identified the relative stability of the phenotypes, demonstrated specific phenotypes consistent with published findings and identified others needing further study. PMID:25822311
Chemistry and Transport in a Multi-Dimensional Model
NASA Technical Reports Server (NTRS)
Yung, Yuk L.
2004-01-01
Our work has two primary scientific goals, the interannual variability (IAV) of stratospheric ozone and the hydrological cycle of the upper troposphere and lower stratosphere. Our efforts are aimed at integrating new information obtained by spacecraft and aircraft measurements to achieve a better understanding of the chemical and dynamical processes that are needed for realistic evaluations of human impact on the global environment. A primary motivation for studying the ozone layer is to separate the anthropogenic perturbations of the ozone layer from natural variability. Using the recently available merged ozone data (MOD), we have carried out an empirical orthogonal function EOF) study of the temporal and spatial patterns of the IAV of total column ozone in the tropics. The outstanding problem about water in the stratosphere is its secular increase in the last few decades. The Caltech/PL multi-dimensional chemical transport model (CTM) photochemical model is used to simulate the processes that control the water vapor and its isotopic composition in the stratosphere. Datasets we will use for comparison with model results include those obtained by the Total Ozone Mapping Spectrometer (TOMS), the Solar Backscatter Ultraviolet (SBUV and SBUV/2), Stratosphere Aerosol and Gas Experiment (SAGE I and II), the Halogen Occultation Experiment (HALOE), the Atmospheric Trace Molecular Spectroscopy (ATMOS) and those soon to be obtained by the Cirrus Regional Study of Tropical Anvils and Cirrus Layers Florida Area Cirrus Experiment (CRYSTAL-FACE) mission. The focus of the investigations is the exchange between the stratosphere and the troposphere, and between the troposphere and the biosphere.
Multidimensional discretization of conservation laws for unstructured polyhedral grids
Burton, D.E.
1994-08-22
To the extent possible, a discretized system should satisfy the same conservation laws as the physical system. The author considers the conservation properties of a staggered-grid Lagrange formulation of the hydrodynamics equations (SGH) which is an extension of a ID scheme due to von Neumann and Richtmyer (VNR). The term staggered refers to spatial centering in which position, velocity, and kinetic energy are centered at nodes, while density, pressure, and internal energy are at cell centers. Traditional SGH formulations consider mass, volume, and momentum conservation, but tend to ignore conservation of total energy, conservation of angular momentum, and requirements for thermodynamic reversibility. The author shows that, once the mass and momentum discretizations have been specified, discretization for other quantities are dictated by the conservation laws and cannot be independently defined. The spatial discretization method employs a finite volume procedure that replaces differential operators with surface integrals. The method is appropriate for multidimensional formulations (1D, 2D, 3D) on unstructured grids formed from polygonal (2D) or polyhedral (3D) cells. Conservation equations can then be expressed in conservation form in which conserved currents are exchanged between control volumes. In addition to the surface integrals, the conservation equations include source terms derived from physical sources or geometrical considerations. In Cartesian geometry, mass and momentum are conserved identically. Discussion of volume conservation will be temporarily deferred. The author shows that the momentum equation leads to a form-preserving definition for kinetic energy and to an exactly conservative evolution equation for internal energy. Similarly, the author derives a form-preserving definition and corresponding conservation equation for a zone-centered angular momentum.
Multidimensional analysis and probabilistic model of volcanic and seismic activities
NASA Astrophysics Data System (ADS)
Fedorov, V.
2009-04-01
body, as well as to forecast of changes in its relief. As the volcanic and seismic processes are of cosmic nature and occurrence, it seems logical to investigate their chronological structure in terms of astronomical time reference system or in parameters of the Earth orbital movement. Gravitational interaction of the Earth with the moon, the Sun and planets of the Solar system forms the physical basis of this multidimensional system; it manifests itself in tidal deformations of the Earth's lithosphere and in periodical changes in the planet rotation and orbital speed. A search for chronological correlation between the Earth's volcanism and seismicity on one hand and the orbital parameters dynamic on the other shows a certain promise in relation to prognostic decisions. It should be kept in mind that the calculation of astronomical characteristics (Ephemerides), which is one of the main lines in theoretical astronomy, spans many years both in the past and in future. It seems appropriate therefore to apply the astronomical time reference system to investigations of chronological structure of volcanic and seismic processes from the methodical viewpoint, as well as for retrospective and prognostic analyses. To investigate temporal pattern of the volcanic and seismic processes and to find a degree of their dependence on tidal forces, we used the astronomical time reference system as related to the Earth's orbital movement. The system is based on substitution of calendar dates of eruption and earthquakes for corresponding values of known astronomical characteristics, such as the Earth to Sun and Earth to Moon distances, ecliptic latitude of the Moon, etc. In coordinates of astronomical parameters (JPL Planetary and Lunar Efemerides, 1997, as compiled by the Jet Propulsion Laboratory, California Institute of Technology, on the basis of DE 406 block developed by NASA), we analyzed massifs of information, both volcanological (Catalogue of the World volcanic eruptions by I
Huang, Tzu-Hsueh; Ning, Xinghai; Wang, Xiaojian; Murthy, Niren; Tzeng, Yih-Ling; Dickson, Robert M
2015-02-01
Flow cytometry holds promise to accelerate antibiotic susceptibility determinations; however, without robust multidimensional statistical analysis, general discrimination criteria have remained elusive. In this study, a new statistical method, probability binning signature quadratic form (PB-sQF), was developed and applied to analyze flow cytometric data of bacterial responses to antibiotic exposure. Both sensitive lab strains (Escherichia coli and Pseudomonas aeruginosa) and a multidrug resistant, clinically isolated strain (E. coli) were incubated with the bacteria-targeted dye, maltohexaose-conjugated IR786, and each of many bactericidal or bacteriostatic antibiotics to identify changes induced around corresponding minimum inhibition concentrations (MIC). The antibiotic-induced damages were monitored by flow cytometry after 1-h incubation through forward scatter, side scatter, and fluorescence channels. The 3-dimensional differences between the flow cytometric data of the no-antibiotic treated bacteria and the antibiotic-treated bacteria were characterized by PB-sQF into a 1-dimensional linear distance. A 99% confidence level was established by statistical bootstrapping for each antibiotic-bacteria pair. For the susceptible E. coli strain, statistically significant increments from this 99% confidence level were observed from 1/16x MIC to 1x MIC for all the antibiotics. The same increments were recorded for P. aeruginosa, which has been reported to cause difficulty in flow-based viability tests. For the multidrug resistant E. coli, significant distances from control samples were observed only when an effective antibiotic treatment was utilized. Our results suggest that a rapid and robust antimicrobial susceptibility test (AST) can be constructed by statistically characterizing the differences between sample and control flow cytometric populations, even in a label-free scheme with scattered light alone. These distances vs paired controls coupled with rigorous
A GROUP FINDING ALGORITHM FOR MULTIDIMENSIONAL DATA SETS
Sharma, Sanjib; Johnston, Kathryn V. E-mail: kvj@astro.columbia.ed
2009-09-20
We describe a density-based hierarchical group finding algorithm capable of identifying structures and substructures of any shape and density in multidimensional data sets where each dimension can be a numeric attribute with arbitrary measurement scale. This has applications in a wide variety of fields from finding structures in galaxy redshift surveys, to identifying halos and subhalos in N-body simulations and group finding in Local Group chemodynamical data sets. In general, clustering schemes require an a priori definition of a metric (a non-negative function that gives the distance between two points in a space) and the quality of clustering depends upon this choice. The general practice is to use a constant global metric which is optimal only if the clusters in the data are self-similar. For complex data configurations even the most finely tuned constant global metric turns out to be suboptimal. Moreover, the correct choice of metric also becomes increasingly important as the number of dimensions increase. To address these problems, we present an entropy-based binary space partitioning algorithm which uses a locally adaptive metric for each data point. The metric is employed to calculate the density at each point and a list of its nearest neighbors, and this information is then used to form a hierarchy of groups. Finally, the ratio of maximum to minimum density of points in a group is used to estimate the significance of the groups. Setting a threshold on this significance can effectively screen out groups arising due to Poisson noise and helps organize the groups into meaningful clusters. For a data set of N points, the algorithm requires only O(N) space and O(N(log N){sup 3}) time which makes it ideally suitable for analyzing large data sets. As an example, we apply the algorithm to identify structures in a simulated stellar halo using the full six-dimensional phase space coordinates.
Multidimensional assessment of empathic abilities: neural correlates and gender differences.
Derntl, Birgit; Finkelmeyer, Andreas; Eickhoff, Simon; Kellermann, Thilo; Falkenberg, Dania I; Schneider, Frank; Habel, Ute
2010-01-01
Empathy is a multidimensional construct and comprises the ability to perceive, understand and feel the emotional states of others. Gender differences have been reported for various aspects of emotional and cognitive behaviors including theory of mind. However, although empathy is not a single ability but a complex behavioral competency including different components, most studies relied on single aspects of empathy, such as perspective taking or emotion perception. To extend those findings we developed three paradigms to assess all three core components of empathy (emotion recognition, perspective taking and affective responsiveness) and clarify to which extent gender affects the neural correlates of empathic abilities. A functional MRI study was performed with 12 females (6 during their follicular phase, 6 during their luteal phase) and 12 males, measuring these tasks as well as self-report empathy questionnaires. Data analyses revealed no significant gender differences in behavioral performance, but females rated themselves as more empathic than males in the self-report questionnaires. Analyses of functional data revealed distinct neural networks in females and males, and females showed stronger neural activation across all three empathy tasks in emotion-related areas, including the amygdala. Exploratory analysis of possible hormonal effects indicated stronger amygdala activation in females during their follicular phase supporting previous data suggesting higher social sensitivity and thus facilitated socio-emotional behavior. Hence, our data support the assumption that females and males rely on divergent processing strategies when solving emotional tasks: while females seem to recruit more emotion and self-related regions, males activate more cortical, rather cognitive-related areas. PMID:19914001
MUSIC for Multidimensional Spectral Estimation: Stability and Super-Resolution
NASA Astrophysics Data System (ADS)
Liao, Wenjing
2015-12-01
This paper presents a performance analysis of the MUltiple SIgnal Classification (MUSIC) algorithm applied on $D$ dimensional single-snapshot spectral estimation while $s$ true frequencies are located on the continuum of a bounded domain. Inspired by the matrix pencil form, we construct a D-fold Hankel matrix from the measurements and exploit its Vandermonde decomposition in the noiseless case. MUSIC amounts to identifying a noise subspace, evaluating a noise-space correlation function, and localizing frequencies by searching the $s$ smallest local minima of the noise-space correlation function. In the noiseless case, $(2s)^D$ measurements guarantee an exact reconstruction by MUSIC as the noise-space correlation function vanishes exactly at true frequencies. When noise exists, we provide an explicit estimate on the perturbation of the noise-space correlation function in terms of noise level, dimension $D$, the minimum separation among frequencies, the maximum and minimum amplitudes while frequencies are separated by two Rayleigh Length (RL) at each direction. As a by-product the maximum and minimum non-zero singular values of the multidimensional Vandermonde matrix whose nodes are on the unit sphere are estimated under a gap condition of the nodes. Under the 2-RL separation condition, if noise is i.i.d. gaussian, we show that perturbation of the noise-space correlation function decays like $\\sqrt{\\log(\\#(\\mathbf{N}))/\\#(\\mathbf{N})}$ as the sample size $\\#(\\mathbf{N})$ increases. When the separation among frequencies drops below 2 RL, our numerical experiments show that the noise tolerance of MUSIC obeys a power law with the minimum separation of frequencies.
Measuring and modeling multidimensional dispersion in a meandering river
NASA Astrophysics Data System (ADS)
Logan, B. L.; Nelson, J. M.; Runkel, R. L.; McDonald, R. R.
2009-04-01
As part of a study to separate and characterize the active and passive components of sturgeon larval dispersal in a large river, we made detailed measurements of the dispersion of a large pulse of Rhodamine dye injected at a single upstream point. The study occurred on the Kootenai River, USA, a 200m-wide meandering river with an unusually low gradient, 2x10-5, and an average depth of 5 m at the moderate study flow of 271 m3/s. For the first 14 river kilometers downstream from the injection site, a detailed concentration data set describing the spatial and temporal evolution of the dye pulse was obtained using GPS receivers and high-accuracy fluorometers mounted on several boats. Beyond this initial reach, the dye was predominantly well-mixed in the cross-stream direction except near the leading and trailing edges of the pulse, and only longitudinal dispersion was measured. These measurements were made at a series of 11 fixed locations for an additional 45 river kilometers downstream, at which point peak dye concentrations were near the detection limit. Even for a relatively simple channel, the data indicate that local topography and bank irregularity exert a strong influence on the distribution of dye. While most of the dye pulse was apparently well mixed in the cross-stream and vertical directions, deep pools and lateral separation zones produced complex 3-dimensional structure in the concentration field, especially at the leading edge of the dye pulse. The dispersion data show that travel times in different reaches were more variable than predicted by a simple 1-dimensional model. Comparisons of the field data with results from multidimensional computational models indicate that uncommon channel features play a disproportionately important role in determining the storage and subsequent release of constituents that are passively advected and diffused.
Voloschenko, A. M.
2006-07-01
In the paper a way to prevent the P1 synthetic acceleration (P1SA) scheme degradation in solving small absorption highly heterogeneous (SAHH) multidimensional problems that ensures fast pointwise convergence of the P1SA scheme is discussed. Numerical experiment has shown that the lack of the difference scheme mono-tonicity is the reason of the consistent P1SA scheme degradation in solving SAHH problems. So, improvement of the difference scheme mono-tonicity also improves convergence of the consistent P1SA scheme in solving SAHH problems. In the paper we discuss remedies those improve the difference scheme mono-tonicity without essential degradation in accuracy. We also present results which demonstrate that a suitable choice of the fix-up function in the adaptive weighted diamond difference (AWDD) scheme essentially extends the class of SAHH problems, which can be efficiently accelerated by the consistent P1SA scheme. (authors)
Development of multi-dimensional body image scale for malaysian female adolescents.
Chin, Yit Siew; Taib, Mohd Nasir Mohd; Shariff, Zalilah Mohd; Khor, Geok Lin
2008-01-01
The present study was conducted to develop a Multi-dimensional Body Image Scale for Malaysian female adolescents. Data were collected among 328 female adolescents from a secondary school in Kuantan district, state of Pahang, Malaysia by using a self-administered questionnaire and anthropometric measurements. The self-administered questionnaire comprised multiple measures of body image, Eating Attitude Test (EAT-26; Garner & Garfinkel, 1979) and Rosenberg Self-esteem Inventory (Rosenberg, 1965). The 152 items from selected multiple measures of body image were examined through factor analysis and for internal consistency. Correlations between Multi-dimensional Body Image Scale and body mass index (BMI), risk of eating disorders and self-esteem were assessed for construct validity. A seven factor model of a 62-item Multi-dimensional Body Image Scale for Malaysian female adolescents with construct validity and good internal consistency was developed. The scale encompasses 1) preoccupation with thinness and dieting behavior, 2) appearance and body satisfaction, 3) body importance, 4) muscle increasing behavior, 5) extreme dieting behavior, 6) appearance importance, and 7) perception of size and shape dimensions. Besides, a multidimensional body image composite score was proposed to screen negative body image risk in female adolescents. The result found body image was correlated with BMI, risk of eating disorders and self-esteem in female adolescents. In short, the present study supports a multi-dimensional concept for body image and provides a new insight into its multi-dimensionality in Malaysian female adolescents with preliminary validity and reliability of the scale. The Multi-dimensional Body Image Scale can be used to identify female adolescents who are potentially at risk of developing body image disturbance through future intervention programs. PMID:20126371
Anusha, L. S.; Nagendra, K. N.
2012-02-10
The solution of polarized radiative transfer equation with angle-dependent (AD) partial frequency redistribution (PRD) is a challenging problem. Modeling the observed, linearly polarized strong resonance lines in the solar spectrum often requires the solution of the AD line transfer problems in one-dimensional or multi-dimensional (multi-D) geometries. The purpose of this paper is to develop an understanding of the relative importance of the AD PRD effects and the multi-D transfer effects and particularly their combined influence on the line polarization. This would help in a quantitative analysis of the second solar spectrum (the linearly polarized spectrum of the Sun). We consider both non-magnetic and magnetic media. In this paper we reduce the Stokes vector transfer equation to a simpler form using a Fourier decomposition technique for multi-D media. A fast numerical method is also devised to solve the concerned multi-D transfer problem. The numerical results are presented for a two-dimensional medium with a moderate optical thickness (effectively thin) and are computed for a collisionless frequency redistribution. We show that the AD PRD effects are significant and cannot be ignored in a quantitative fine analysis of the line polarization. These effects are accentuated by the finite dimensionality of the medium (multi-D transfer). The presence of magnetic fields (Hanle effect) modifies the impact of these two effects to a considerable extent.
Fast Food Jobs. National Study of Fast Food Employment.
ERIC Educational Resources Information Center
Charner, Ivan; Fraser, Bryna Shore
A study examined employment in the fast-food industry. The national survey collected data from employees at 279 fast-food restaurants from seven companies. Female employees outnumbered males by two to one. The ages of those fast-food employees in the survey sample ranged from 14 to 71, with fully 70 percent being in the 16- to 20-year-old age…
Multi-dimensional forward modeling of frequency-domain helicopter-borne electromagnetic data
NASA Astrophysics Data System (ADS)
Miensopust, M.; Siemon, B.; Börner, R.; Ansari, S.
2013-12-01
Helicopter-borne frequency-domain electromagnetic (HEM) surveys are used for fast high-resolution, three-dimensional (3-D) resistivity mapping. Nevertheless, 3-D modeling and inversion of an entire HEM data set is in many cases impractical and, therefore, interpretation is commonly based on one-dimensional (1-D) modeling and inversion tools. Such an approach is valid for environments with horizontally layered targets and for groundwater applications but there are areas of higher dimension that are not recovered correctly applying 1-D methods. The focus of this work is the multi-dimensional forward modeling. As there is no analytic solution to verify (or falsify) the obtained numerical solutions, comparison with 1-D values as well as amongst various two-dimensional (2-D) and 3-D codes is essential. At the center of a large structure (a few hundred meters edge length) and above the background structure in some distance to the anomaly 2-D and 3-D values should match the 1-D solution. Higher dimensional conditions are present at the edges of the anomaly and, therefore, only a comparison of different 2-D and 3-D codes gives an indication of the reliability of the solution. The more codes - especially if based on different methods and/or written by different programmers - agree the more reliable is the obtained synthetic data set. Very simple structures such as a conductive or resistive block embedded in a homogeneous or layered half-space without any topography and using a constant sensor height were chosen to calculate synthetic data. For the comparison one finite element 2-D code and numerous 3-D codes, which are based on finite difference, finite element and integral equation approaches, were applied. Preliminary results of the comparison will be shown and discussed. Additionally, challenges that arose from this comparative study will be addressed and further steps to approach more realistic field data settings for forward modeling will be discussed. As the driving
Dunn, Michael S; Vulic, Natalie; Shellie, Robert A; Whitehead, Simon; Morrison, Paul; Marriott, Philip J
2006-10-13
Two approaches are described and compared for the analysis of suspected allergens (SAs) in fragrance products, which are defined by the Scientific Committee of Cosmetics and Non-Food Products (SCCNFP). The first consists of a comprehensive two-dimensional gas chromatography (GC x GC) experiment using both a "conventional" non-polar/polar column combination and an "inverse" polar/non-polar column set. The second approach uses a targeted multidimensional gas chromatography (MDGC) system employing a Deans type pneumatic switch and a longitudinally modulated cryogenic system (LMCS). It was found that the conventional and inverse column sets complement each other well, providing identification of SAs present. Compounds well retained on the second dimension of one column set were the first to be eluted from the other. In some instances SAs co-eluting with matrix components on the second dimension for a given column set were clearly resolved on the other, although this has the disadvantage of requiring two analytical runs. Targeted MDGC with a non-polar/polar column set, successfully separated all SAs identified within a fragrance product. The instrument is set up in a similar fashion to a GC x GC system though with longer second dimension ((2)D) column, a cryogenic trap at the beginning of the second column, and a pneumatic switch coupling both columns. The data are easier to process than for a GC x GC experiment. The targeted MDGC method has the capacity to deliver far greater efficiency to targeted regions of a primary separation than a GC x GC experiment, whilst still maintaining overall run times similar to those of a conventional one-dimensional (1D) GC experiment. Cryogenic focussing at the beginning of the (2)D column delivers enhanced sensitivity, accurate (2)D retention times and narrow peak widths; these are responsible for an increased resolution obtained from the fast, relatively short (approximately 5 m) (2)D column. The two column set GC x GC analysis
Bender, M.; Bennett, F.K.; Kuckes, A.F.
1963-09-17
A fast-acting electric switch is described for rapidly opening a circuit carrying large amounts of electrical power. A thin, conducting foil bridges a gap in this circuit and means are provided for producing a magnetic field and eddy currents in the foil, whereby the foil is rapidly broken to open the circuit across the gap. Advantageously the foil has a hole forming two narrow portions in the foil and the means producing the magnetic field and eddy currents comprises an annular coil having its annulus coaxial with the hole in the foil and turns adjacent the narrow portions of the foil. An electrical current flows through the coil to produce the magnetic field and eddy currents in the foil. (AEC)
Davis, F.J.; Hurst, G.S.; Reinhardt, P.W.
1959-08-18
An improved proton recoil spectrometer for determining the energy spectrum of a fast neutron beam is described. Instead of discriminating against and thereby"throwing away" the many recoil protons other than those traveling parallel to the neutron beam axis as do conventional spectrometers, this device utilizes protons scattered over a very wide solid angle. An ovoidal gas-filled recoil chamber is coated on the inside with a scintillator. The ovoidal shape of the sensitive portion of the wall defining the chamber conforms to the envelope of the range of the proton recoils from the radiator disposed within the chamber. A photomultiplier monitors the output of the scintillator, and a counter counts the pulses caused by protons of energy just sufficient to reach the scintillator.
Batzer, T.H.; Cummings, D.B.; Ryan, J.F.
1962-05-22
A high-current, fast-acting switch is designed for utilization as a crowbar switch in a high-current circuit such as used to generate the magnetic confinement field of a plasma-confining and heat device, e.g., Pyrotron. The device particularly comprises a cylindrical housing containing two stationary, cylindrical contacts between which a movable contact is bridged to close the switch. The movable contact is actuated by a differential-pressure, airdriven piston assembly also within the housing. To absorb the acceleration (and the shock imparted to the device by the rapidly driven, movable contact), an adjustable air buffer assembly is provided, integrally connected to the movable contact and piston assembly. Various safety locks and circuit-synchronizing means are also provided to permit proper cooperation of the invention and the high-current circuit in which it is installed. (AEC)
Maximoff, Sergey N.; Head-Gordon, Martin P.
2009-01-01
A chemicurrent is a flux of fast (kinetic energy ≳ 0.5−1.3 eV) metal electrons caused by moderately exothermic (1−3 eV) chemical reactions over high work function (4−6 eV) metal surfaces. In this report, the relation between chemicurrent and surface chemistry is elucidated with a combination of top-down phenomenology and bottom-up atomic-scale modeling. Examination of catalytic CO oxidation, an example which exhibits a chemicurrent, reveals 3 constituents of this relation: The localization of some conduction electrons to the surface via a reduction reaction, 0.5 O2 + δe− → Oδ− (Red); the delocalization of some surface electrons into a conduction band in an oxidation reaction, Oδ− + CO → CO2δ− → CO2 + δe− (Ox); and relaxation without charge transfer (Rel). Juxtaposition of Red, Ox, and Rel produces a daunting variety of metal electronic excitations, but only those that originate from CO2 reactive desorption are long-range and fast enough to dominate the chemicurrent. The chemicurrent yield depends on the universality class of the desorption process and the distribution of the desorption thresholds. This analysis implies a power-law relation with exponent 2.66 between the chemicurrent and the heat of adsorption, which is consistent with experimental findings for a range of systems. This picture also applies to other oxidation-reduction reactions over high work function metal surfaces. PMID:19561296
An Efficient Feature Subset Selection Algorithm for Classification of Multidimensional Dataset
Devaraj, Senthilkumar; Paulraj, S.
2015-01-01
Multidimensional medical data classification has recently received increased attention by researchers working on machine learning and data mining. In multidimensional dataset (MDD) each instance is associated with multiple class values. Due to its complex nature, feature selection and classifier built from the MDD are typically more expensive or time-consuming. Therefore, we need a robust feature selection technique for selecting the optimum single subset of the features of the MDD for further analysis or to design a classifier. In this paper, an efficient feature selection algorithm is proposed for the classification of MDD. The proposed multidimensional feature subset selection (MFSS) algorithm yields a unique feature subset for further analysis or to build a classifier and there is a computational advantage on MDD compared with the existing feature selection algorithms. The proposed work is applied to benchmark multidimensional datasets. The number of features was reduced to 3% minimum and 30% maximum by using the proposed MFSS. In conclusion, the study results show that MFSS is an efficient feature selection algorithm without affecting the classification accuracy even for the reduced number of features. Also the proposed MFSS algorithm is suitable for both problem transformation and algorithm adaptation and it has great potentials in those applications generating multidimensional datasets. PMID:26491718
The Art of Extracting One-Dimensional Flow Properties from Multi-Dimensional Data Sets
NASA Technical Reports Server (NTRS)
Baurle, R. A.; Gaffney, R. L.
2007-01-01
The engineering design and analysis of air-breathing propulsion systems relies heavily on zero- or one-dimensional properties (e:g: thrust, total pressure recovery, mixing and combustion efficiency, etc.) for figures of merit. The extraction of these parameters from experimental data sets and/or multi-dimensional computational data sets is therefore an important aspect of the design process. A variety of methods exist for extracting performance measures from multi-dimensional data sets. Some of the information contained in the multi-dimensional flow is inevitably lost when any one-dimensionalization technique is applied. Hence, the unique assumptions associated with a given approach may result in one-dimensional properties that are significantly different than those extracted using alternative approaches. The purpose of this effort is to examine some of the more popular methods used for the extraction of performance measures from multi-dimensional data sets, reveal the strengths and weaknesses of each approach, and highlight various numerical issues that result when mapping data from a multi-dimensional space to a space of one dimension.
An Efficient Feature Subset Selection Algorithm for Classification of Multidimensional Dataset.
Devaraj, Senthilkumar; Paulraj, S
2015-01-01
Multidimensional medical data classification has recently received increased attention by researchers working on machine learning and data mining. In multidimensional dataset (MDD) each instance is associated with multiple class values. Due to its complex nature, feature selection and classifier built from the MDD are typically more expensive or time-consuming. Therefore, we need a robust feature selection technique for selecting the optimum single subset of the features of the MDD for further analysis or to design a classifier. In this paper, an efficient feature selection algorithm is proposed for the classification of MDD. The proposed multidimensional feature subset selection (MFSS) algorithm yields a unique feature subset for further analysis or to build a classifier and there is a computational advantage on MDD compared with the existing feature selection algorithms. The proposed work is applied to benchmark multidimensional datasets. The number of features was reduced to 3% minimum and 30% maximum by using the proposed MFSS. In conclusion, the study results show that MFSS is an efficient feature selection algorithm without affecting the classification accuracy even for the reduced number of features. Also the proposed MFSS algorithm is suitable for both problem transformation and algorithm adaptation and it has great potentials in those applications generating multidimensional datasets. PMID:26491718
The Extraction of One-Dimensional Flow Properties from Multi-Dimensional Data Sets
NASA Technical Reports Server (NTRS)
Baurle, Robert A.; Gaffney, Richard L., Jr.
2007-01-01
The engineering design and analysis of air-breathing propulsion systems relies heavily on zero- or one-dimensional properties (e.g. thrust, total pressure recovery, mixing and combustion efficiency, etc.) for figures of merit. The extraction of these parameters from experimental data sets and/or multi-dimensional computational data sets is therefore an important aspect of the design process. A variety of methods exist for extracting performance measures from multi-dimensional data sets. Some of the information contained in the multi-dimensional flow is inevitably lost when any one-dimensionalization technique is applied. Hence, the unique assumptions associated with a given approach may result in one-dimensional properties that are significantly different than those extracted using alternative approaches. The purpose of this effort is to examine some of the more popular methods used for the extraction of performance measures from multi-dimensional data sets, reveal the strengths and weaknesses of each approach, and highlight various numerical issues that result when mapping data from a multi-dimensional space to a space of one dimension.
Misty Mountain clustering: application to fast unsupervised flow cytometry gating
2010-01-01
Background There are many important clustering questions in computational biology for which no satisfactory method exists. Automated clustering algorithms, when applied to large, multidimensional datasets, such as flow cytometry data, prove unsatisfactory in terms of speed, problems with local minima or cluster shape bias. Model-based approaches are restricted by the assumptions of the fitting functions. Furthermore, model based clustering requires serial clustering for all cluster numbers within a user defined interval. The final cluster number is then selected by various criteria. These supervised serial clustering methods are time consuming and frequently different criteria result in different optimal cluster numbers. Various unsupervised heuristic approaches that have been developed such as affinity propagation are too expensive to be applied to datasets on the order of 106 points that are often generated by high throughput experiments. Results To circumvent these limitations, we developed a new, unsupervised density contour clustering algorithm, called Misty Mountain, that is based on percolation theory and that efficiently analyzes large data sets. The approach can be envisioned as a progressive top-down removal of clouds covering a data histogram relief map to identify clusters by the appearance of statistically distinct peaks and ridges. This is a parallel clustering method that finds every cluster after analyzing only once the cross sections of the histogram. The overall run time for the composite steps of the algorithm increases linearly by the number of data points. The clustering of 106 data points in 2D data space takes place within about 15 seconds on a standard laptop PC. Comparison of the performance of this algorithm with other state of the art automated flow cytometry gating methods indicate that Misty Mountain provides substantial improvements in both run time and in the accuracy of cluster assignment. Conclusions Misty Mountain is fast, unbiased
Bhatia, Mona; Rosset, Antoine; Platon, Alexandra; Didier, Dominique; Becker, Christoph D; Poletti, Pierre-Alexandre
2010-01-01
Computed tomographic angiography (CTA) is a frequent noninvasive alternative to digital subtraction angiography. We previously reported the development of a new subtraction software to overcome limitations of adjacent bone and calcification in CT angiographic subtraction. Our aim was to further develop and improve this fast and automated computerized software, universally available for free use and compatible with most CT scanners, thus enabling better delineation of vascular structures, artifact reduction, and shorter reading times with potential clinical benefits. This computer-based free software will be available as an open source in the next release of OsiriX at the Web site http://www.osirix-viewer.com.