Fast dictionary learning for noise attenuation of multidimensional seismic data
NASA Astrophysics Data System (ADS)
Chen, Yangkang
2017-04-01
The K-SVD algorithm has been successfully utilized for adaptively learning the sparse dictionary in 2-D seismic denoising. Because of the high computational cost of many singular value decompositions (SVDs) in the K-SVD algorithm, it is not applicable in practical situations, especially in 3-D or 5-D problems. In this paper, I extend the dictionary learning based denoising approach from 2-D to 3-D. To address the computational efficiency problem in K-SVD, I propose a fast dictionary learning approach based on the sequential generalized K-means (SGK) algorithm for denoising multidimensional seismic data. The SGK algorithm updates each dictionary atom by taking an arithmetic average of several training signals instead of calculating an SVD as used in K-SVD algorithm. I summarize the sparse dictionary learning algorithm using K-SVD, and introduce SGK algorithm together with its detailed mathematical implications. 3-D synthetic, 2-D and 3-D field data examples are used to demonstrate the performance of both K-SVD and SGK algorithms. It has been shown that SGK algorithm can significantly increase the computational efficiency while only slightly degrading the denoising performance.
Fast dictionary learning for noise attenuation of multidimensional seismic data
NASA Astrophysics Data System (ADS)
Chen, Yangkang
2017-01-01
The K-SVD algorithm has been successfully utilized for adaptively learning the sparse dictionary in 2D seismic denoising. Because of the high computational cost of many SVDs in the K-SVD algorithm, it is not applicable in practical situations, especially in 3D or 5D problems. In this paper, I extend the dictionary learning based denoising approach from 2D to 3D. To address the computational efficiency problem in K-SVD, I propose a fast dictionary learning approach based on the sequential generalized K-means (SGK) algorithm for denoising multidimensional seismic data. The SGK algorithm updates each dictionary atom by taking an arithmetic average of several training signals instead of calculating a SVD as used in K-SVD algorithm. I summarize the sparse dictionary learning algorithm using K-SVD, and introduce SGK algorithm together with its detailed mathematical implications. 3D synthetic, 2D and 3D field data examples are used to demonstrate the performance of both K-SVD and SGK algorithms. It has been shown that SGK algorithm can significantly increase the computational efficiency while only slightly degrading the denoising performance.
Fast Packet Classification Using Multi-Dimensional Encoding
NASA Astrophysics Data System (ADS)
Huang, Chi Jia; Chen, Chien
Internet routers need to classify incoming packets quickly into flows in order to support features such as Internet security, virtual private networks and Quality of Service (QoS). Packet classification uses information contained in the packet header, and a predefined rule table in the routers. Packet classification of multiple fields is generally a difficult problem. Hence, researchers have proposed various algorithms. This study proposes a multi-dimensional encoding method in which parameters such as the source IP address, destination IP address, source port, destination port and protocol type are placed in a multi-dimensional space. Similar to the previously best known algorithm, i.e., bitmap intersection, multi-dimensional encoding is based on the multi-dimensional range lookup approach, in which rules are divided into several multi-dimensional collision-free rule sets. These sets are then used to form the new coding vector to replace the bit vector of the bitmap intersection algorithm. The average memory storage of this encoding is Θ (L · N · log N) for each dimension, where L denotes the number of collision-free rule sets, and N represents the number of rules. The multi-dimensional encoding practically requires much less memory than bitmap intersection algorithm. Additionally, the computation needed for this encoding is as simple as bitmap intersection algorithm. The low memory requirement of the proposed scheme means that it not only decreases the cost of packet classification engine, but also increases the classification performance, since memory represents the performance bottleneck in the packet classification engine implementation using a network processor.
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.
Fast Multidimensional Nearest Neighbor Search Algorithm Using Priority Queue
NASA Astrophysics Data System (ADS)
Ajioka, Shiro; Tsuge, Satoru; Shishibori, Masami; Kita, Kenji
Nearest neighbor search in high dimensional spaces is an interesting and important problem which is relevant for a wide variety of applications, including multimedia information retrieval, data mining, and pattern recognition. For such applications, the curse of high dimensionality tends to be a major obstacle in the development of efficient search methods. This paper addresses the problem of designing an efficient algorithm for high dimensional nearest neighbor search using a priority queue. The proposed algorithm is based on a simple linear search algorithm and eliminates unnecessary arithmetic operations from distance computations between multidimensional vectors. Moreover, we propose two techniques, a dimensional sorting method and a PCA-based method, to accelerate multidimensional search. Experimental results indicate that our scheme scales well even for a very large number of dimensions.
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
Gaussian ARTMAP: A Neural Network for Fast Incremental Learning of Noisy Multidimensional Maps.
Williamson, James R.
1996-07-01
A new neural network architecture for incremental supervised learning of analog multidimensional maps is introduced. The architecture, called Gaussian ARTMAP, is a synthesis of a Gaussian classifier and an adaptive resonance theory (ART) neural network, achieved by defining the ART choice function as the discriminant function of a Gaussian classifier with separable distributions, and the ART match function as the same, but with the distributions normalized to a unit height. While Gaussian ARTMAP retains the attractive parallel computing and fast learning properties of fuzzy ARTMAP, it learns a more efficient internal representation of a mapping while being more resistant to noise than fuzzy ARTMAP on a number of benchmark databases. SSeveral simulations are presented which demonstrate that Gaussian ARTMAP consistently obtains a better trade-off of classification rate to number of categories than fuzzy ARTMAP. Results on a vowel classification problem are also presented which demonstrate that Gaussian ARTMAP outperforms many other classifiers. Copyright 1996 Elsevier Science Ltd
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
NASA Technical Reports Server (NTRS)
Klann, P. G.; Lantz, E.; Mayo, W. T.
1973-01-01
A series of central core and core-reflector interface sample replacement experiments for 16 materials performed in the NASA heavy-metal-reflected, fast spectrum critical assembly (NCA) were analyzed in four and 13 groups using the GAM 2 cross-section set. The individual worths obtained by TDSN and DOT multidimensional transport theory calculations showed significant differences from the experimental results. These were attributed to cross-section uncertainties in the GAM 2 cross sections. Simultaneous analysis of the measured and calculated sample worths permitted separation of the worths into capture and scattering components which systematically provided fast spectrum averaged correction factors to the magnitudes of the GAM 2 absorption and scattering cross sections. Several Los Alamos clean critical assemblies containing Oy, Ta, and Mo as well as one of the NCA compositions were reanalyzed using the corrected cross sections. In all cases the eigenvalues were significantly improved and were recomputed to within 1 percent of the experimental eigenvalue. A comparable procedure may be used for ENDF cross sections when these are available.
CFMDS: CUDA-based fast multidimensional scaling for genome-scale data.
Park, Sungin; Shin, Soo-Yong; Hwang, Kyu-Baek
2012-01-01
Multidimensional scaling (MDS) is a widely used approach to dimensionality reduction. It has been applied to feature selection and visualization in various areas. Among diverse MDS methods, the classical MDS is a simple and theoretically sound solution for projecting data objects onto a low dimensional space while preserving the original distances among them as much as possible. However, it is not trivial to apply it to genome-scale data (e.g., microarray gene expression profiles) on regular desktop computers, because of its high computational complexity. We implemented a highly-efficient software application, called CFMDS (CUDA-based Fast MultiDimensional Scaling), which produces an approximate solution of the classical MDS based on CUDA (compute unified device architecture) and the divide-and-conquer principle. CUDA is a parallel computing architecture exploiting the power of the GPU (graphics processing unit). The principle of divide-and-conquer was adopted for circumventing the small memory problem of usual graphics cards. Our application software has been tested on various benchmark datasets including microarrays and compared with the classical MDS algorithms implemented using C# and MATLAB. In our experiments, CFMDS was more than a hundred times faster for large data than such general solutions. Regarding the quality of dimensionality reduction, our approximate solutions were as good as those from the general solutions, as the Pearson's correlation coefficients between them were larger than 0.9. CFMDS is an expeditious solution for the data dimensionality reduction problem. It is especially useful for efficient processing of genome-scale data consisting of several thousands of objects in several minutes.
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 [Princeton, NJ; Chen, Dong [Croton-On-Hudson, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Steinmacher-Burow, Burkhard D [Mount Kisco, NY; Vranas, Pavlos M [Bedford Hills, NY
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. Copyright © 2015 John Wiley & Sons, Ltd.
Xu, Dan; King, Kevin F.; Zhu, Yudong; McKinnon, Graeme C.; Liang, Zhi-Pei
2009-01-01
The vast majority of parallel transmission RF pulse designs so far are based on small-tip-angle (STA) approximation of the Bloch equation. These methods can design only excitation pulses with small flip angles (e.g., 30°). The linear class large-tip-angle (LCLTA) method is able to design large-tip-angle parallel transmission pulses through concatenating a sequence of small-excitation pulses when certain k-space trajectories are used. However, both STA and LCLTA are linear approximations of the nonlinear Bloch equation. Therefore, distortions from the ideal magnetization profiles due to the higher order terms can appear in the final magnetization profiles. This issue is addressed in this work by formulating the multidimensional multichannel RF pulse design as an optimal control problem with multiple controls based directly on the Bloch equation. Necessary conditions for the optimal solution are derived and a first-order gradient optimization algorithm is used to iteratively solve the optimal control problem, where an existing pulse is used as an initial “guess.” A systematic design procedure is also presented. Bloch simulation and phantom experimental results using various parallel transmission pulses (excitation, inversion, and refocusing) are shown to illustrate the effectiveness of the optimal control method in improving the spatial localization or homogeneity of the magnetization profiles. PMID:18306407
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.
Wong, Yong Foo; West, Rachel N; Chin, Sung-Tong; Marriott, Philip J
2015-08-07
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
Hout, Michael C; Goldinger, Stephen D; Ferguson, Ryan W
2013-02-01
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 review existing methods of collecting similarity data, and critically examine the spatial arrangement method (SpAM) proposed by Goldstone (1994a), in which similarity ratings are obtained by presenting many stimuli at once. The participant moves stimuli around the computer screen, placing them at distances from one another that are proportional to subjective similarity. This provides a fast, efficient, and user-friendly method for obtaining MDS spaces. Participants gave similarity ratings to artificially constructed visual stimuli (comprising 2-3 perceptual dimensions) and nonvisual stimuli (animal names) with less-defined underlying dimensions. Ratings were obtained with 4 methods: pairwise comparisons, spatial arrangement, and 2 novel hybrid methods. We compared solutions from alternative methods to the pairwise method, finding that the SpAM produces high-quality MDS solutions. Monte Carlo simulations on degraded data suggest that the method is also robust to reductions in sample sizes and granularity. Moreover, coordinates derived from SpAM solutions accurately predicted discrimination among objects in same-different classification. We address the benefits of using a spatial medium to collect similarity measures.
Hout, Michael C.; Goldinger, Stephen D.; Ferguson, Ryan W.
2012-01-01
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 review existing methods of collecting similarity data, and critically examine a spatial arrangement method (SpAM) proposed by Goldstone (1994a), in which similarity ratings are obtained by presenting many stimuli at once. The participant moves stimuli around the computer screen, placing them at distances from one another that are proportional to subjective similarity. This provides a fast, efficient, and user-friendly method for obtaining MDS spaces. Participants gave similarity ratings to artificially constructed visual stimuli (comprising 2–3 perceptual dimensions), and non-visual stimuli (animal names) with less-defined underlying dimensions. Ratings were obtained using four methods: pairwise comparisons, spatial arrangement, and two novel hybrid methods. We compared solutions from alternative methods to the pairwise method, finding that the SpAM produces high-quality MDS solutions. Monte Carlo simulations on degraded data suggest that the method is also robust to reductions in sample sizes and granularity. Moreover, coordinates derived from SpAM solutions accurately predicted discrimination among objects in “same/different” classification. In the General Discussion, we address the benefits of using a spatial medium to collect similarity measures. PMID:22746700
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…
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.
NASA Astrophysics Data System (ADS)
Rinas, Aimee; Jones, Lisa M.
2015-04-01
Peptides containing the oxidation products of hydroxyl radical-mediated protein footprinting experiments are typically much less abundant than their unoxidized counterparts. This is inherent to the design of the experiment as excessive oxidation may lead to undesired conformational changes or unfolding of the protein, skewing the results. Thus, as the complexity of the systems studied using this method expands, the detection and identification of these oxidized species can be increasingly difficult with the limitations of data-dependent acquisition (DDA) and one-dimensional chromatography. Here we report the application of multidimensional protein identification technology (MudPIT) in combination with hydroxyl radical footprinting as a method to increase the identification of quantifiable peptides in these experiments. Using this method led to a 37% increase in unique peptide identifications as well as a 70% increase in protein group identifications over one-dimensional data-dependent acquisition on the same samples. Furthermore, we demonstrate the combination of these methods as a means to investigate megadalton complexes.
Cunha, S C; Fernandes, J O; Oliveira, M B P P
2009-12-18
A method for the rapid trace analysis of 24 residual pesticides in apple juice by multidimensional gas chromatography-mass spectrometry (MD-GC/MS) using dispersive liquid-liquid microextraction (DLLME) was developed and optimized. Several parameters of the extraction procedure such as type and volume of extraction solvent, type and volume of dispersive solvent and salt addition were evaluated to achieve the highest yield and to attain the lowest detection limits. The DLLME procedure optimized consists in the formation of a cloudy solution promoted by the fast addition to the sample (5 ml) of a mixture of carbon tetrachloride (extraction solvent, 100 microl) and acetone (dispersive solvent, 400 microl). The tiny droplets formed and dispersed among the aqueous sample solution are further joined and sedimented (85 microl) in the bottom of the conical test tube by centrifugation. Once extracted, all the 24 pesticides were directly injected and separated by a dual GC column system, comprising a short wide-bore DB-5 capillary column with low film thickness connected by a Deans switch system to a second chromatographic narrower column, with identical stationary phase. The instrumental setting used, in combination with carefully optimized operational fast GC and MS parameters, markedly decreased the retention times of the targeted analytes. The total chromatographic run was 8 min. Mean recoveries for apple juice spiked at three concentrations ranged from 60% to 105% and the intra-repeatability ranged from 1% to 21%. The limits of detection of the 24 pesticides ranged from 0.06 to 2.20 microg/L. In 2 of a total of 28 analysed samples were found residues of captan, although at levels below the maximum limit legal established.
Papesh, Megan H.; Goldinger, Stephen D.
2012-01-01
The concept of similarity, or a sense of "sameness" among things, is pivotal to theories in the cognitive sciences and beyond. Similarity, however, is a difficult thing to measure. Multidimensional scaling (MDS) is a tool by which researchers can obtain quantitative estimates of similarity among groups of items. More formally, MDS refers to a set of statistical techniques that are used to reduce the complexity of a data set, permitting visual appreciation of the underlying relational structures contained therein. The current paper provides an overview of MDS. We discuss key aspects of performing this technique, such as methods that can be used to collect similarity estimates, analytic techniques for treating proximity data, and various concerns regarding interpretation of the MDS output. MDS analyses of two novel data sets are also included, highlighting in step-by-step fashion how MDS is performed, and key issues that may arise during analysis. PMID:23359318
Lovelace, J L; Kusmierz, J J; Desiderio, D M
1991-01-02
Methionine enkephalin (ME = YGGFM) was measured in five individual human post-mortem pituitaries using four different analytical methods, with the objective of comparing the molecular specificities of the methods. Radioreceptor assay (RRA) used a receptor-rich preparation from brain and [3H]etorphine as radioligand to determine ME-like receptoractivity (ME-LR). Radioimmunoassay (RIA) measured ME-like immunoreactivity (ME-LI). Pituitary samples analyzed by RRA and RIA were purified first with a high-performance liquid chromatography (HPLC) gradient on a polymer analytical column. Fast atom bombardment mass spectrometry (FAB-MS) in two different detection modes quantified ME using the protonated molecular ion MH+ of ME at 574 a.m.u. and B/E linked-field selected reaction monitoring (SRM) to monitor the specific unimolecular metastable transition that produced the unique amino acid sequence-determining tetrapeptide fragment ion YGGFA+ from the MH+ precursor ion. Both FAB-MS methods used the deuterated internal standard YGG[2H5-F]M. Samples analyzed with FAB-MS were purified first with multi-dimensional reversed-phase HPLC. The first dimension was an ODS gradient, and the second dimension was a polymer isocratic elution. The following ME amounts were measured (mean +/- standard error of the mean): ME-LR, 7.0 +/- 1.9 micrograms g-1 tissue; ME-LI, 1.8 +/- 0.7 micrograms g-1 tissue; MH+, 2.7 +/- 0.6 micrograms g-1 tissue; SRM, 3.0 +/- 0.8 micrograms g-1 tissue. The FAB SRM method provided the highest level of molecular specificity amount these four analytical methods used to measure picomole amounts of endogenous ME in a human pituitary.
Multidimensional chromatography in food analysis.
Herrero, Miguel; Ibáñez, Elena; Cifuentes, Alejandro; Bernal, Jose
2009-10-23
In this work, the main developments and applications of multidimensional chromatographic techniques in food analysis are reviewed. Different aspects related to the existing couplings involving chromatographic techniques are examined. These couplings include multidimensional GC, multidimensional LC, multidimensional SFC as well as all their possible combinations. Main advantages and drawbacks of each coupling are critically discussed and their key applications in food analysis described.
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 X-Space Magnetic Particle Imaging
Conolly, Steven M.
2012-01-01
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-in-variant 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. PMID:21402508
Multidimensional capillary electrophoresis.
Grochocki, Wojciech; Markuszewski, Michał J; Quirino, Joselito P
2015-01-01
Multidimensional separation where two or more orthogonal displacement mechanisms are combined is a promising approach to increase peak capacity in CE. The combinations allow dramatic improvement of analytical performance since the total peak capacity is given by a product of the peak capacities of all methods. The initial reports were concentrated on the construction of effective connections between capillaries for 2D analysis. Today, 2D and 3D CE systems are now able to separate real complex biological or environmental mixtures with good repeatability, improved resolution with minimal loss of sample. This review will present the developments in the field of multidimensional CE during the last 15 years. The endeavors in this specific field were on the development of interfaces, interface-free techniques including integrated separations, microdevices, and on-line sample concentration techniques to improve detection sensitivity.
Multidimensional diffusion MRI
NASA Astrophysics Data System (ADS)
Topgaard, Daniel
2017-02-01
Principles from multidimensional NMR spectroscopy, and in particular solid-state NMR, have recently been transferred to the field of diffusion MRI, offering non-invasive characterization of heterogeneous anisotropic materials, such as the human brain, at an unprecedented level of detail. Here we revisit the basic physics of solid-state NMR and diffusion MRI to pinpoint the origin of the somewhat unexpected analogy between the two fields, and provide an overview of current diffusion MRI acquisition protocols and data analysis methods to quantify the composition of heterogeneous materials in terms of diffusion tensor distributions with size, shape, and orientation dimensions. While the most advanced methods allow estimation of the complete multidimensional distributions, simpler methods focus on various projections onto lower-dimensional spaces as well as determination of means and variances rather than actual distributions. Even the less advanced methods provide simple and intuitive scalar parameters that are directly related to microstructural features that can be observed in optical microscopy images, e.g. average cell eccentricity, variance of cell density, and orientational order - properties that are inextricably entangled in conventional diffusion MRI. Key to disentangling all these microstructural features is MRI signal acquisition combining isotropic and directional dimensions, just as in the field of multidimensional solid-state NMR from which most of the ideas for the new methods are derived.
Multidimensional Potential Burgers Turbulence
NASA Astrophysics Data System (ADS)
Boritchev, Alexandre
2016-03-01
We consider the multidimensional generalised stochastic Burgers equation in the space-periodic setting: partial {u}/partial t+(nabla f({u}) \\cdot nabla) {u}-ν Δ {u}= nabla η, quad t ≥ 0, {x} in{T}^d=({R}/ {Z})^d, under the assumption that u is a gradient. Here f is strongly convex and satisfies a growth condition, ν is small and positive, while η is a random forcing term, smooth in space and white in time. For solutions u of this equation, we study Sobolev norms of u averaged in time and in ensemble: each of these norms behaves as a given negative power of ν. These results yield sharp upper and lower bounds for natural analogues of quantities characterising the hydrodynamical turbulence, namely the averages of the increments and of the energy spectrum. These quantities behave as a power of the norm of the relevant parameter, which is respectively the separation ℓ in the physical space and the wavenumber k in the Fourier space. Our bounds do not depend on the initial condition and hold uniformly in {ν}. We generalise the results obtained for the one-dimensional case in [10], confirming the physical predictions in [4, 30]. Note that the form of the estimates does not depend on the dimension: the powers of {ν, |{{k}}|, ℓ} are the same in the one- and the multi-dimensional setting.
Multidimensional visual statistical learning.
Turk-Browne, Nicholas B; Isola, Phillip J; Scholl, Brian J; Treat, Teresa A
2008-03-01
Recent studies of visual statistical learning (VSL) have demonstrated that statistical regularities in sequences of visual stimuli can be automatically extracted, even without intent or awareness. Despite much work on this topic, however, several fundamental questions remain about the nature of VSL. In particular, previous experiments have not explored the underlying units over which VSL operates. In a sequence of colored shapes, for example, does VSL operate over each feature dimension independently, or over multidimensional objects in which color and shape are bound together? The studies reported here demonstrate that VSL can be both object-based and feature-based, in systematic ways based on how different feature dimensions covary. For example, when each shape covaried perfectly with a particular color, VSL was object-based: Observers expressed robust VSL for colored-shape sub-sequences at test but failed when the test items consisted of monochromatic shapes or color patches. When shape and color pairs were partially decoupled during learning, however, VSL operated over features: Observers expressed robust VSL when the feature dimensions were tested separately. These results suggest that VSL is object-based, but that sensitivity to feature correlations in multidimensional sequences (possibly another form of VSL) may in turn help define what counts as an object.
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.
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.
Profile Analysis: Multidimensional Scaling Approach.
ERIC Educational Resources Information Center
Ding, Cody S.
2001-01-01
Outlines an exploratory multidimensional scaling-based approach to profile analysis called Profile Analysis via Multidimensional Scaling (PAMS) (M. Davison, 1994). The PAMS model has the advantages of being applied to samples of any size easily, classifying persons on a continuum, and using person profile index for further hypothesis studies, but…
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 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…
Suicide: a multidimensional malaise.
Leenaars, A A
1996-01-01
No one really knows why human beings commit suicide. The goal of this paper is to provide a psychological point of view on the topic, among the many other perspectives that are needed. It addresses the question by providing a theory of suicide, arguing that it is theory that allows us to sort out the booming buzzing mess of experience (Wm. James). Suicide is a multi-dimensional malaise. Metaphorically speaking, it is an intrapsychic drama on an interpersonal stage. As sound theory must be empirically observable, the theory is next applied to research of suicide notes, studying such factors as age, sex, and method of suicide, cross-culture and cross-time. Next, because all theory must have clinical applicability, a clinical case study of Goethe's Werther is provided. Overall, it is concluded that we need to continue to develop models to understand the suicidal mind.
Spectral multidimensional scaling
Aflalo, Yonathan; Kimmel, Ron
2013-01-01
An important tool in information analysis is dimensionality reduction. There are various approaches for large data simplification by scaling its dimensions down that play a significant role in recognition and classification tasks. The efficiency of dimension reduction tools is measured in terms of memory and computational complexity, which are usually a function of the number of the given data points. Sparse local operators that involve substantially less than quadratic complexity at one end, and faithful multiscale models with quadratic cost at the other end, make the design of dimension reduction procedure a delicate balance between modeling accuracy and efficiency. Here, we combine the benefits of both and propose a low-dimensional multiscale modeling of the data, at a modest computational cost. The idea is to project the classical multidimensional scaling problem into the data spectral domain extracted from its Laplace–Beltrami operator. There, embedding into a small dimensional Euclidean space is accomplished while optimizing for a small number of coefficients. We provide a theoretical support and demonstrate that working in the natural eigenspace of the data, one could reduce the process complexity while maintaining the model fidelity. As examples, we efficiently canonize nonrigid shapes by embedding their intrinsic metric into , a method often used for matching and classifying almost isometric articulated objects. Finally, we demonstrate the method by exposing the style in which handwritten digits appear in a large collection of images. We also visualize clustering of digits by treating images as feature points that we map to a plane. PMID:24108352
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 numerical modeling of heat exchangers
NASA Astrophysics Data System (ADS)
Sha, W. T.; Yang, C. I.; Kao, T. T.; Cho, S. M.
A comprehensive, multidimensional, thermal-hydraulic model is developed for the analysis of shell-and-tube heat exchangers for liquid-metal services. For the shellside fluid, the conservation equations of mass, momentum, and energy for continuum fluids are modified using the concept of porosity, surface permeability and distributed resistance to account for the blockage effects due to the presence of heat-transfer tubes, flow baffles/shrouds, the support plates, etc. On the tubeside, the heat-transfer tubes are connected in parallel between the inlet and outlet plenums, and tubeside flow distribution is calculated based on the plenum-to-plenum pressure difference being equal for all tubes. It is assumed that the fluid remains single-phase on the shell side and may undergo phase-change on the tube side, thereby simulating the conditions of Liquid Metal Fast Breeder Reactor (LMFBR) intermediate heat exchangers (IHX) and steam generators (SG).
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. © 2015 Wiley Periodicals, Inc.
Multidimensional peptide separations in proteomics.
Link, Andrew J
2002-12-01
Multidimensional peptide separation will play an increasingly important role in the drive to identify and quantitate the proteome. By increasing the peak and load capacity, multidimensional approaches increase the number and dynamic range of peptides that can be analyzed in a complex biological organism. Separation methods using different physical properties of peptides have been combined with varying degrees of success. The ultimate goal is a rapid separation strategy that can be coupled with analytical methods, such as mass spectrometry, to provide comprehensive monitoring of the changing concentration, interactions, and structures of proteins in the proteome.
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.
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…
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…
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…
Multidimensional Perfectionism and Ego Defenses
ERIC Educational Resources Information Center
Dickinson, Wendy L.; Ashby, Jeffrey S.
2005-01-01
This study examined the relationship between multidimensional perfectionism and ego defense style among 130 college students. Cluster analysis results facilitated the identification of groups of adaptive perfectionists, maladaptive perfectionists, and non-perfectionists. The researchers found that identified maladaptive perfectionists used…
Multidimensional Scaling of Video Surrogates.
ERIC Educational Resources Information Center
Goodrum, Abby A.
2001-01-01
Four types of video surrogates were compared under two tasks. Multidimensional scaling was used to map dimensional dispersions of users' judgments of similarity between videos and surrogates. Congruence between these maps was used to evaluate representativeness of each surrogate type. Congruence was greater for image-based than for text-based…
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 Perfectionism and Ego Defenses
ERIC Educational Resources Information Center
Dickinson, Wendy L.; Ashby, Jeffrey S.
2005-01-01
This study examined the relationship between multidimensional perfectionism and ego defense style among 130 college students. Cluster analysis results facilitated the identification of groups of adaptive perfectionists, maladaptive perfectionists, and non-perfectionists. The researchers found that identified maladaptive perfectionists used…
Multidimensional indexing tools for the virtual observatory
NASA Astrophysics Data System (ADS)
Csabai, I.; Dobos, L.; Trencséni, M.; Herczegh, G.; Józsa, P.; Purger, N.; Budavári, T.; Szalay, A. S.
2007-10-01
The last decade has seen a dramatic change in the way astronomy is carried out. The dawn of the the new microelectronic devices, like CCDs has dramatically extended the amount of observed data. Large, in some cases all sky surveys emerged in almost all the wavelength ranges of the observable spectrum of electromagnetic waves. This large amount of data has to be organized, published electronically and a new style of data retrieval is essential to exploit all the hidden information in the multiwavelength data. Many statistical algorithms required for these tasks run reasonably fast when using small sets of in-memory data, but take noticeable performance hits when operating on large databases that do not fit into memory. We utilize new software technologies to develop and evaluate fast multidimensional indexing schemes that inherently follow the underlying, highly non-uniform distribution of the data: they are layered uniform indices, hierarchical binary space partitioning, and sampled flat Voronoi tessellation of the data. These techniques can dramatically speed up operations such as finding similar objects by example, classifying objects or comparing extensive simulation sets with observations.
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. Copyright © 2015 Elsevier Inc. All rights reserved.
Multidimensional signatures in antimicrobial peptides
Yount, Nannette Y.; Yeaman, Michael R.
2004-01-01
Conventional analyses distinguish between antimicrobial peptides by differences in amino acid sequence. Yet structural paradigms common to broader classes of these molecules have not been established. The current analyses examined the potential conservation of structural themes in antimicrobial peptides from evolutionarily diverse organisms. Using proteomics, an antimicrobial peptide signature was discovered to integrate stereospecific sequence patterns and a hallmark three-dimensional motif. This striking multidimensional signature is conserved among disulfide-containing antimicrobial peptides spanning biological kingdoms, and it transcends motifs previously limited to defined peptide subclasses. Experimental data validating this model enabled the identification of previously unrecognized antimicrobial activity in peptides of known identity. The multidimensional signature model provides a unifying structural theme in broad classes of antimicrobial peptides, will facilitate discovery of antimicrobial peptides as yet unknown, and offers insights into the evolution of molecular determinants in these and related host defense effector molecules. PMID:15118082
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 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.
ERIC Educational Resources Information Center
Korn, Abe
1994-01-01
Presents an activity that enables students to answer for themselves the question of how fast a body must travel before the nonrelativistic expression must be replaced with the correct relativistic expression by deciding on the accuracy required in describing the kinetic energy of a body. (ZWH)
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.
Mechanics of multidimensional isolated horizons
NASA Astrophysics Data System (ADS)
Korzynski, Mikolaj; Lewandowski, Jerzy; Pawlowski, Tomasz
2005-06-01
Recently, a multidimensional generalization of the isolated horizon framework has been proposed (Lewandowski and Pawlowski 2005 Class. Quantum Grav. 22 1573 98). Therein the geometric description was easily generalized to higher dimensions and the structure of the constraints induced by the Einstein equations was analysed. In particular, the geometric version of the zeroth law of black-hole thermodynamics was proved. In this work, we show how the IH mechanics can be formulated in a dimension-independent fashion and derive the first law of BH thermodynamics for arbitrarily dimensional IH. We also propose a definition of energy for non-rotating horizons.
Robustness of Adaptive Testing to Multidimensionality.
ERIC Educational Resources Information Center
Weiss, David J.; Suhadolnik, Debra
The present monte carlo simulation study was designed to examine the effects of multidimensionality during the administration of computerized adaptive testing (CAT). It was assumed that multidimensionality existed in the individuals to whom test items were being administered, i.e., that the correct or incorrect responses given by an individual…
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…
Spatial Indexing and Visualization of Large Multi-Dimensional Databases
NASA Astrophysics Data System (ADS)
Dobos, L.; Csabai, I.; Trencséni, M.; Herczegh, G.; Józsa, P.; Purger, N.
2007-10-01
Scientific endeavors such as large astronomical surveys generate databases on the terabyte scale. These usually multi-dimensional databases must be visualized and mined in order to find interesting objects or to extract meaningful and qualitatively new relationships. Many statistical algorithms required for these tasks run reasonably fast when operating on small sets of in-memory data, but take noticeable performance hits when operating on large databases that do not fit into memory. We utilize new software technologies to develop and evaluate fast multi-dimensional, spatial indexing schemes that inherently follow the underlying highly non-uniform distribution of the data: one of them is hierarchical binary space partitioning; the other is sampled flat Voronoi partitioning of the data. Our working database is the 5-dimensional magnitude space of the Sloan Digital Sky Survey with more than 250 million data points. We show that these techniques can dramatically speed up data mining operations such as finding similar objects by example, classifying objects or comparing extensive simulation sets with observations. We are also developing tools to interact with the spatial database and visualize the data real-time at multiple resolutions at different zoom levels in an adaptive manner.
An Introduction to Coherent Multidimensional Spectroscopy.
Chen, Peter C
2016-12-01
Coherent multidimensional spectroscopy is a field that has drawn much attention as an optical analogue to multidimensional nuclear magnetic resonance imaging. Coherent multidimensional spectroscopic techniques produce spectra that show the magnitude of an optical signal as a function of two or more pulsed laser frequencies. Spectra can be collected in either the frequency or the time domain. In addition to improving resolution and overcoming spectral congestion, coherent multidimensional spectroscopy provides the ability to investigate and conduct studies based upon the relationship between different peaks. The purpose of this paper is to provide a general introduction to the area of coherent multidimensional spectroscopy, to provide a brief overview of current experimental approaches, and to discuss some emerging developments in this relatively young field.
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.
Convergence and the multidimensional niche.
Harmon, Luke J; Kolbe, Jason J; Cheverud, James M; Losos, Jonathan B
2005-02-01
Convergent evolution has played an important role in the development of the ecological niche concept. We investigated patterns of convergent and divergent evolution of Caribbean Anolis lizards. These lizards diversified independently on each of the islands of the Greater Antilles, producing the same set of habitat specialists on each island. Using a phylogenetic comparative framework, we examined patterns of morphological convergence in five functionally distinct sets of morphological characters: body size, body shape, head shape, lamella number, and sexual size dimorphism. We find evidence for convergence among members of the habitat specialist types for each of these five datasets. Furthermore, the patterns of convergence differ among at least four of the five datasets; habitat specialists that are similar for one set of characters are often greatly different for another. This suggests that the habitat specialist niches into which these anoles have evolved are multidimensional, involving several distinct and independent aspects of morphology.
Minimal Models of Multidimensional Computations
Fitzgerald, Jeffrey D.; Sincich, Lawrence C.; Sharpee, Tatyana O.
2011-01-01
The multidimensional computations performed by many biological systems are often characterized with limited information about the correlations between inputs and outputs. Given this limitation, our approach is to construct the maximum noise entropy response function of the system, leading to a closed-form and minimally biased model consistent with a given set of constraints on the input/output moments; the result is equivalent to conditional random field models from machine learning. For systems with binary outputs, such as neurons encoding sensory stimuli, the maximum noise entropy models are logistic functions whose arguments depend on the constraints. A constraint on the average output turns the binary maximum noise entropy models into minimum mutual information models, allowing for the calculation of the information content of the constraints and an information theoretic characterization of the system's computations. We use this approach to analyze the nonlinear input/output functions in macaque retina and thalamus; although these systems have been previously shown to be responsive to two input dimensions, the functional form of the response function in this reduced space had not been unambiguously identified. A second order model based on the logistic function is found to be both necessary and sufficient to accurately describe the neural responses to naturalistic stimuli, accounting for an average of 93% of the mutual information with a small number of parameters. Thus, despite the fact that the stimulus is highly non-Gaussian, the vast majority of the information in the neural responses is related to first and second order correlations. Our results suggest a principled and unbiased way to model multidimensional computations and determine the statistics of the inputs that are being encoded in the outputs. PMID:21455284
Global Langevin model of multidimensional biomolecular dynamics
NASA Astrophysics Data System (ADS)
Schaudinnus, Norbert; Lickert, Benjamin; Biswas, Mithun; Stock, Gerhard
2016-11-01
Molecular dynamics simulations of biomolecular processes are often discussed in terms of diffusive motion on a low-dimensional free energy landscape F ( 𝒙 ) . To provide a theoretical basis for this interpretation, one may invoke the system-bath ansatz á la Zwanzig. That is, by assuming a time scale separation between the slow motion along the system coordinate x and the fast fluctuations of the bath, a memory-free Langevin equation can be derived that describes the system's motion on the free energy landscape F ( 𝒙 ) , which is damped by a friction field and driven by a stochastic force that is related to the friction via the fluctuation-dissipation theorem. While the theoretical formulation of Zwanzig typically assumes a highly idealized form of the bath Hamiltonian and the system-bath coupling, one would like to extend the approach to realistic data-based biomolecular systems. Here a practical method is proposed to construct an analytically defined global model of structural dynamics. Given a molecular dynamics simulation and adequate collective coordinates, the approach employs an "empirical valence bond"-type model which is suitable to represent multidimensional free energy landscapes as well as an approximate description of the friction field. Adopting alanine dipeptide and a three-dimensional model of heptaalanine as simple examples, the resulting Langevin model is shown to reproduce the results of the underlying all-atom simulations. Because the Langevin equation can also be shown to satisfy the underlying assumptions of the theory (such as a delta-correlated Gaussian-distributed noise), the global model provides a correct, albeit empirical, realization of Zwanzig's formulation. As an application, the model can be used to investigate the dependence of the system on parameter changes and to predict the effect of site-selective mutations on the dynamics.
Multidimensional text classification for drug information.
Lertnattee, Verayuth; Theeramunkong, Thanaruk
2004-09-01
This paper proposes a multidimensional model for classifying drug information text documents. The concept of multidimensional category model is introduced for representing classes. In contrast with traditional flat and hierarchical category models, the multidimensional category model classifies each document using multiple predefined sets of categories, where each set corresponds to a dimension. Since a multidimensional model can be converted to flat and hierarchical models, three classification approaches are possible, i.e., classifying directly based on the multidimensional model and classifying with the equivalent flat or hierarchical models. The efficiency of these three approaches is investigated using drug information collection with two different dimensions: 1) drug topics and 2) primary therapeutic classes. In the experiments, k-nearest neighbor, naive Bayes, and two centroid-based methods are selected as classifiers. The comparisons among three approaches of classification are done using two-way analysis of variance, followed by the Scheffé's test for post hoc comparison. The experimental results show that multidimensional-based classification performs better than the others, especially in the presence of a relatively small training set. As one application, a category-based search engine using the multidimensional category concept was developed to help users retrieve drug information.
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.
Using Multidimensional Scaling for Curricular Goal Analysis.
ERIC Educational Resources Information Center
Leitzman, David F.; And Others
1980-01-01
Reports research that utilized multidimensional scaling and related analytic procedures to validate the curricular goals of a graduate therapeutic recreation program. Data analysis includes the use of the two-dimensional KYST and PREFMAP spaces. (Author/JD)
The Multidimensional Assessment of Interoceptive Awareness (MAIA)
Mehling, Wolf E.; Price, Cynthia; Daubenmier, Jennifer J.; Acree, Mike; Bartmess, Elizabeth; Stewart, Anita
2012-01-01
This paper describes the development of a multidimensional self-report measure of interoceptive body awareness. The systematic mixed-methods process involved reviewing the current literature, specifying a multidimensional conceptual framework, evaluating prior instruments, developing items, and analyzing focus group responses to scale items by instructors and patients of body awareness-enhancing therapies. Following refinement by cognitive testing, items were field-tested in students and instructors of mind-body approaches. Final item selection was achieved by submitting the field test data to an iterative process using multiple validation methods, including exploratory cluster and confirmatory factor analyses, comparison between known groups, and correlations with established measures of related constructs. The resulting 32-item multidimensional instrument assesses eight concepts. The psychometric properties of these final scales suggest that the Multidimensional Assessment of Interoceptive Awareness (MAIA) may serve as a starting point for research and further collaborative refinement. PMID:23133619
Subjective Geographic Distance: A Multidimensional Comparison
ERIC Educational Resources Information Center
Lundberg, Ulf; Ekman, Gosta
1973-01-01
The interdistances between thirteen places situated in different parts of the world were estimated by 60 subjects. The estimates were analysed by Kruskal's multidimensional technique and, after a cosine transformation, by factor analysis. (Author)
Tourette Syndrome: A Multidimensional Approach to Treatment.
ERIC Educational Resources Information Center
Anderson, Donna J.
1987-01-01
Describes Tourette syndrome, a chronic, neurological disorder characterized by involuntary muscular movements, uncontrollable sounds, and inappropriate words. Notes that Tourette syndrome is frequently misunderstood and mistreated, presents symptoms, and suggests a multidimensional approach to treatment. (Author/NB)
Multi-dimensional edge detection operators
NASA Astrophysics Data System (ADS)
Youn, Sungwook; Lee, Chulhee
2014-05-01
In remote sensing, modern sensors produce multi-dimensional images. For example, hyperspectral images contain hundreds of spectral images. In many image processing applications, segmentation is an important step. Traditionally, most image segmentation and edge detection methods have been developed for one-dimensional images. For multidimensional images, the output images of spectral band images are typically combined under certain rules or using decision fusions. In this paper, we proposed a new edge detection algorithm for multi-dimensional images using secondorder statistics. First, we reduce the dimension of input images using the principal component analysis. Then we applied multi-dimensional edge detection operators that utilize second-order statistics. Experimental results show promising results compared to conventional one-dimensional edge detectors such as Sobel filter.
Mormons and Social Distance: A Multidimensional Analysis
ERIC Educational Resources Information Center
Bunker, Gary L.; And Others
1977-01-01
Issues such as Mormon variation from general cultural ethnic attitudes and generalization from ecclesiastical norms to secular tolerance/intolerance are examined in light of multi-dimensional research. (Author/AM)
Multidimensional imaging using compressive Fresnel holography.
Horisaki, Ryoichi; Tanida, Jun; Stern, Adrian; Javidi, Bahram
2012-06-01
We propose a generalized framework for single-shot acquisition of multidimensional objects using compressive Fresnel holography. A multidimensional object with spatial, spectral, and polarimetric information is propagated with the Fresnel diffraction, and the propagated signal of each channel is observed by an image sensor with randomly arranged optical elements for filtering. The object data are reconstructed using a compressive sensing algorithm. This scheme is verified with numerical experiments. The proposed framework can be applied to imageries for spectrum, polarization, and so on.
Multidimensional Data Modeling for Business Process Analysis
NASA Astrophysics Data System (ADS)
Mansmann, Svetlana; Neumuth, Thomas; Scholl, Marc H.
The emerging area of business process intelligence attempts to enhance the analytical capabilities of business process management systems by employing data warehousing and mining technologies. This paper presents an approach to re-engineering the business process modeling in conformity with the multidimensional data model. Since the business process and the multidimensional model are driven by rather different objectives and assumptions, there is no straightforward solution to converging these models.
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
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 gene search with Genehopper
Munz, Matthias; Tönnies, Sascha; Balke, Wolf-Tilo; Simon, Eric
2015-01-01
The high abundance of genetic information enables researchers to gain new insights from the comparison of human genes according to their similarities. However, existing tools that allow the exploration of such gene-to-gene relationships, apply each similarity independently. To make use of multidimensional scoring, we developed a new search engine named Genehopper. It can handle two query types: (i) the typical use case starts with a term-to-gene search, i.e. an optimized full-text search for an anchor gene of interest. The web-interface can handle one or more terms including gene symbols and identifiers of Ensembl, UniProt, EntrezGene and RefSeq. (ii) When the anchor gene is defined, the user can explore its neighborhood by a gene-to-gene search as the weighted sum of nine normalized gene similarities based on sequence homology, protein domains, mRNA expression profiles, Gene Ontology Annotation, gene symbols and other features. Each weight can be adjusted by the user, allowing flexible customization of the gene search. All implemented similarities have a low pairwise correlation (max r2 = 0.4) implying a low linear dependency, i.e. any change in a single weight has an effect on the ranking. Thus, we treated them as separate dimensions in the search space. Genehopper is freely available at http://genehopper.ifis.cs.tu-bs.de. PMID:25990726
Multidimensional encoding of brain connectomes.
Caiafa, Cesar F; Pestilli, Franco
2017-09-13
The ability to map brain networks in living individuals is fundamental in efforts to chart the relation between human behavior, health and disease. Advances in network neuroscience may benefit from developing new frameworks for mapping brain connectomes. We present a framework to encode structural brain connectomes and diffusion-weighted magnetic resonance (dMRI) data using multidimensional arrays. The framework integrates the relation between connectome nodes, edges, white matter fascicles and diffusion data. We demonstrate the utility of the framework for in vivo white matter mapping and anatomical computing by evaluating 1,490 connectomes, thirteen tractography methods, and three data sets. The framework dramatically reduces storage requirements for connectome evaluation methods, with up to 40x compression factors. Evaluation of multiple, diverse datasets demonstrates the importance of spatial resolution in dMRI. We measured large increases in connectome resolution as function of data spatial resolution (up to 52%). Moreover, we demonstrate that the framework allows performing anatomical manipulations on white matter tracts for statistical inference and to study the white matter geometrical organization. Finally, we provide open-source software implementing the method and data to reproduce the results.
Multidimensional gene search with Genehopper.
Munz, Matthias; Tönnies, Sascha; Balke, Wolf-Tilo; Simon, Eric
2015-07-01
The high abundance of genetic information enables researchers to gain new insights from the comparison of human genes according to their similarities. However, existing tools that allow the exploration of such gene-to-gene relationships, apply each similarity independently. To make use of multidimensional scoring, we developed a new search engine named Genehopper. It can handle two query types: (i) the typical use case starts with a term-to-gene search, i.e. an optimized full-text search for an anchor gene of interest. The web-interface can handle one or more terms including gene symbols and identifiers of Ensembl, UniProt, EntrezGene and RefSeq. (ii) When the anchor gene is defined, the user can explore its neighborhood by a gene-to-gene search as the weighted sum of nine normalized gene similarities based on sequence homology, protein domains, mRNA expression profiles, Gene Ontology Annotation, gene symbols and other features. Each weight can be adjusted by the user, allowing flexible customization of the gene search. All implemented similarities have a low pairwise correlation (max r(2) = 0.4) implying a low linear dependency, i.e. any change in a single weight has an effect on the ranking. Thus, we treated them as separate dimensions in the search space. Genehopper is freely available at http://genehopper.ifis.cs.tu-bs.de. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.
Multichannel and Multidimensional Bargmann Potentials
NASA Astrophysics Data System (ADS)
Plekhanvov, E. B.; Suzko, A. S.; Zakhariev, B. N.
The class of potential matrices for which coupled channel Schrödinger equations have exact solutions is presented. This is achieved due to degeneration of the kernel of the inverse-problem integral equation with respect to the channel indices, in addition to separability of its coordinate dependence. No attention has been paid before to this fact. Maybe therefore there was no satisfactory multichannel generalization of Bargmann potentials.Partially nonlocal Bargmann potentials for multidimensional and many-particle systems are constructed. Examples of new transparent potentials are given.Translated AbstractMehrkanal und multidimensionale Bargmann-PotentialePotentialmatrizen, für die die Mehrkanal-Schrödingergleichung exakt lösbar ist, werden angegeben. Die entsprechenden Schrödingergleichungen sind exakt lösbar dank der Entartung des Kerns der Integralgleichung des inversen Streuproblems hinsichtlich sowohl der Koordinatenabhängigkeit als auch der Kanalindizes. Dieser Sachverhalt war bisher nicht bemerkt worden. Es werden teilweise nichtlokale Potentiale für mehrdimensionale und Vielteilchen-Systeme konstruiert. Neue Beispiele von nichtreflektierden Potentialen werden angegeben.
Vector fields in multidimensional cosmology
NASA Astrophysics Data System (ADS)
Meierovich, Boris E.
2011-09-01
Vector fields in the expanding Universe are considered within the multidimensional theory of general relativity. Vector fields in general relativity form a three-parametric variety. Our consideration includes the fields with a nonzero covariant divergence. Depending on the relations between the particular parameters and the symmetry of a problem, the vector fields can be longitudinal and/or transverse, ultrarelativistic (i.e. massless) or nonrelativistic (massive), and so on. The longitudinal and transverse vector fields are considered separately in detail in the background of the de Sitter cosmological metric. In most cases the field equations reduce to Bessel equations, and their temporal evolution is analyzed analytically. The energy-momentum tensor of the most simple zero-mass longitudinal vector fields enters the Einstein equations as an additive to the cosmological constant. In this case the de Sitter metric is the exact solution of the Einstein equations. Hence, the most simple zero-mass longitudinal vector field pretends to be an adequate tool for macroscopic description of dark energy as a source of the expansion of the Universe at a constant rate. The zero-mass vector field does not vanish in the process of expansion. On the contrary, massive fields vanish with time. Though their amplitude is falling down, the massive fields make the expansion accelerated.
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. Copyright © 2012 Wiley Periodicals, Inc.
Multidimensional evaluation of managed relocation
Richardson, David M.; Hellmann, Jessica J.; McLachlan, Jason S.; Sax, Dov F.; Schwartz, Mark W.; Gonzalez, Patrick; Brennan, E. Jean; Camacho, Alejandro; Root, Terry L.; Sala, Osvaldo E.; Schneider, Stephen H.; Ashe, Daniel M.; Clark, Jamie Rappaport; Early, Regan; Etterson, Julie R.; Fielder, E. Dwight; Gill, Jacquelyn L.; Minteer, Ben A.; Polasky, Stephen; Safford, Hugh D.; Thompson, Andrew R.; Vellend, Mark
2009-01-01
Managed relocation (MR) has rapidly emerged as a potential intervention strategy in the toolbox of biodiversity management under climate change. Previous authors have suggested that MR (also referred to as assisted colonization, assisted migration, or assisted translocation) could be a last-alternative option after interrogating a linear decision tree. We argue that numerous interacting and value-laden considerations demand a more inclusive strategy for evaluating MR. The pace of modern climate change demands decision making with imperfect information, and tools that elucidate this uncertainty and integrate scientific information and social values are urgently needed. We present a heuristic tool that incorporates both ecological and social criteria in a multidimensional decision-making framework. For visualization purposes, we collapse these criteria into 4 classes that can be depicted in graphical 2-D space. This framework offers a pragmatic approach for summarizing key dimensions of MR: capturing uncertainty in the evaluation criteria, creating transparency in the evaluation process, and recognizing the inherent tradeoffs that different stakeholders bring to evaluation of MR and its alternatives. PMID:19509337
Progress in multi-dimensional upwind differencing
NASA Technical Reports Server (NTRS)
Vanleer, Bram
1992-01-01
Multi-dimensional upwind-differencing schemes for the Euler equations are reviewed. On the basis of the first-order upwind scheme for a one-dimensional convection equation, the two approaches to upwind differencing are discussed: the fluctuation approach and the finite-volume approach. The usual extension of the finite-volume method to the multi-dimensional Euler equations is not entirely satisfactory, because the direction of wave propagation is always assumed to be normal to the cell faces. This leads to smearing of shock and shear waves when these are not grid-aligned. Multi-directional methods, in which upwind-biased fluxes are computed in a frame aligned with a dominant wave, overcome this problem, but at the expense of robustness. The same is true for the schemes incorporating a multi-dimensional wave model not based on multi-dimensional data but on an 'educated guess' of what they could be. The fluctuation approach offers the best possibilities for the development of genuinely multi-dimensional upwind schemes. Three building blocks are needed for such schemes: a wave model, a way to achieve conservation, and a compact convection scheme. Recent advances in each of these components are discussed; putting them all together is the present focus of a worldwide research effort. Some numerical results are presented, illustrating the potential of the new multi-dimensional schemes.
Multidimensional Poverty and Child Survival in India
Mohanty, Sanjay K.
2011-01-01
Background Though the concept of multidimensional poverty has been acknowledged cutting across the disciplines (among economists, public health professionals, development thinkers, social scientists, policy makers and international organizations) and included in the development agenda, its measurement and application are still limited. Objectives and Methodology Using unit data from the National Family and Health Survey 3, India, this paper measures poverty in multidimensional space and examine the linkages of multidimensional poverty with child survival. The multidimensional poverty is measured in the dimension of knowledge, health and wealth and the child survival is measured with respect to infant mortality and under-five mortality. Descriptive statistics, principal component analyses and the life table methods are used in the analyses. Results The estimates of multidimensional poverty are robust and the inter-state differentials are large. While infant mortality rate and under-five mortality rate are disproportionately higher among the abject poor compared to the non-poor, there are no significant differences in child survival among educationally, economically and health poor at the national level. State pattern in child survival among the education, economical and health poor are mixed. Conclusion Use of multidimensional poverty measures help to identify abject poor who are unlikely to come out of poverty trap. The child survival is significantly lower among abject poor compared to moderate poor and non-poor. We urge to popularize the concept of multiple deprivations in research and program so as to reduce poverty and inequality in the population. PMID:22046384
Sparse Sampling Methods In Multidimensional NMR
Mobli, Mehdi; Maciejewski, Mark W.; Schuyler, Adam D.; Stern, Alan S.; Hoch, Jeffrey C.
2014-01-01
Although the discrete Fourier transform played an enabling role in the development of modern NMR spectroscopy, it suffers from a well-known difficulty providing high-resolution spectra from short data records. In multidimensional NMR experiments, so-called indirect time dimensions are sampled parametrically, with each instance of evolution times along the indirect dimensions sampled via separate one-dimensional experiments. The time required to conduct multidimensional experiments is directly proportional to the number of indirect evolution times sampled. Despite remarkable advances in resolution with increasing magnetic field strength, multiple dimensions remain essential for resolving individual resonances in NMR spectra of biological macromolecues. Conventional Fourier-based methods of spectrum analysis limit the resolution that can be practically achieved in the indirect dimensions. Nonuniform or sparse data collection strategies, together with suitable non-Fourier methods of spectrum analysis, enable high-resolution multidimensional spectra to be obtained. Although some of these approaches were first employed in NMR more than two decades ago, it is only relatively recently that they have been widely adopted. Here we describe the current practice of sparse sampling methods and prospects for further development of the approach to improve resolution and sensitivity and shorten experiment time in multidimensional NMR. While sparse sampling is particularly promising for multidimensional NMR, the basic principles could apply to other forms of multidimensional spectroscopy. PMID:22481242
Multidimensional poverty and child survival in India.
Mohanty, Sanjay K
2011-01-01
Though the concept of multidimensional poverty has been acknowledged cutting across the disciplines (among economists, public health professionals, development thinkers, social scientists, policy makers and international organizations) and included in the development agenda, its measurement and application are still limited. OBJECTIVES AND METHODOLOGY: Using unit data from the National Family and Health Survey 3, India, this paper measures poverty in multidimensional space and examine the linkages of multidimensional poverty with child survival. The multidimensional poverty is measured in the dimension of knowledge, health and wealth and the child survival is measured with respect to infant mortality and under-five mortality. Descriptive statistics, principal component analyses and the life table methods are used in the analyses. The estimates of multidimensional poverty are robust and the inter-state differentials are large. While infant mortality rate and under-five mortality rate are disproportionately higher among the abject poor compared to the non-poor, there are no significant differences in child survival among educationally, economically and health poor at the national level. State pattern in child survival among the education, economical and health poor are mixed. Use of multidimensional poverty measures help to identify abject poor who are unlikely to come out of poverty trap. The child survival is significantly lower among abject poor compared to moderate poor and non-poor. We urge to popularize the concept of multiple deprivations in research and program so as to reduce poverty and inequality in the population.
Multidimensional Deterministic Electron Transport Calculations
1992-05-01
inlllnlnilinlmmm nMI MII n~lA - Is - -The SMART scattering matrix is not tied to a particular angular flux distribution . -There is considerable numerical...Both expressions are derived by performing an uncollided electron balance over the i’th path length cell. The uncollided flux is then distributed to the...OIS1UTInOIAVALAIT Y STAIEMENT LDIOSTRIUTION CODE Approved for public release; distribution unlimited. 13. A8STRACTO"d noww Fast and accurate techniques for
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.
NASA Astrophysics Data System (ADS)
Esposito, S.; Pisanti, O.
The following sections are included: * Elementary Considerations * The Integral Equation to the Neutron Distribution * The Critical Size for a Fast Reactor * Supercritical Reactors * Problems and Exercises
Multidimensional energy operator for image processing
NASA Astrophysics Data System (ADS)
Maragos, Petros; Bovik, Alan C.; Quatieri, Thomas F.
1992-11-01
The 1-D nonlinear differential operator (Psi) (f) equals (f')2 - ff' has been recently introduced to signal processing and has been found very useful for estimating the parameters of sinusoids and the modulating signals of AM-FM signals. It is called an energy operator because it can track the energy of an oscillator source generating a sinusoidal signal. In this paper we introduce the multidimensional extension (Phi) (f) equals (parallel)DELf(parallel)2 - fDEL2f of the 1-D energy operator and briefly outline some of its applications to image processing. We discuss some interesting properties of the multidimensional operator and develop demodulation algorithms to estimate the amplitude envelope and instantaneous frequencies of 2-D spatially-varying AM-FM signals, which can model image texture. The attractive features of the multidimensional operator and the related amplitude/frequency demodulation algorithms are their simplicity, efficiency, and ability to track instantaneously- varying spatial modulation patterns.
Resonance beyond frequency-matching: multidimensional resonance
NASA Astrophysics Data System (ADS)
Wang, Zhenyu; Li, Mingzhe; Wang, Ruifang
2017-03-01
Resonance, conventionally defined as the oscillation of a system when the temporal frequency of an external stimulus matches a natural frequency of the system, is important in both fundamental physics and applied disciplines. However, the spatial character of oscillation is not considered in this definition. We reveal the creation of spatial resonance when the stimulus matches the space pattern of a normal mode in an oscillating system. The complete resonance, which we call multidimensional resonance, should be a combination of both the temporal and the spatial resonance. We further elucidate that the spin wave produced by multidimensional resonance drives considerably faster reversal of the vortex core in a magnetic nanodisc. Multidimensional resonance provides insight into the nature of wave dynamics and opens the door to novel applications.
Multidimensional heritability analysis of neuroanatomical shape
Ge, Tian; Reuter, Martin; Winkler, Anderson M.; Holmes, Avram J.; Lee, Phil H.; Tirrell, Lee S.; Roffman, Joshua L.; Buckner, Randy L.; Smoller, Jordan W.; Sabuncu, Mert R.
2016-01-01
In the dawning era of large-scale biomedical data, multidimensional phenotype vectors will play an increasing role in examining the genetic underpinnings of brain features, behaviour and disease. For example, shape measurements derived from brain MRI scans are multidimensional geometric descriptions of brain structure and provide an alternate class of phenotypes that remains largely unexplored in genetic studies. Here we extend the concept of heritability to multidimensional traits, and present the first comprehensive analysis of the heritability of neuroanatomical shape measurements across an ensemble of brain structures based on genome-wide SNP and MRI data from 1,320 unrelated, young and healthy individuals. We replicate our findings in an extended twin sample from the Human Connectome Project (HCP). Our results demonstrate that neuroanatomical shape can be significantly heritable, above and beyond volume, and can serve as a complementary phenotype to study the genetic determinants and clinical relevance of brain structure. PMID:27845344
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.
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.
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.
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.
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…
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…
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…
Multidimensional Scaling Applied to Linguistic Relationships.
ERIC Educational Resources Information Center
Black, Paul
1973-01-01
As the several specific applications in this paper demonstrate, multidimensional scaling provides a long-needed means for investigating and describing spatial relationships among speech varieties. It is especially applicable to the relationships among varieties of a single language (or more properly, linguistic "cline"), which, as is…
Career Success: Constructing a Multidimensional Model
ERIC Educational Resources Information Center
Dries, Nicky; Pepermans, Roland; Carlier, Olivier
2008-01-01
A multidimensional model of career success was developed aiming to be more inclusive than existing models. In a first study, 22 managers were asked to tell the story of their careers. At the end of each interview, idiosyncratic career success "construct ladders" were constructed for each interviewee through an interactive process with the…
DICON: interactive visual analysis of multidimensional clusters.
Cao, Nan; Gotz, David; Sun, Jimeng; Qu, Huamin
2011-12-01
Clustering as a fundamental data analysis technique has been widely used in many analytic applications. However, it is often difficult for users to understand and evaluate multidimensional clustering results, especially the quality of clusters and their semantics. For large and complex data, high-level statistical information about the clusters is often needed for users to evaluate cluster quality while a detailed display of multidimensional attributes of the data is necessary to understand the meaning of clusters. In this paper, we introduce DICON, an icon-based cluster visualization that embeds statistical information into a multi-attribute display to facilitate cluster interpretation, evaluation, and comparison. We design a treemap-like icon to represent a multidimensional cluster, and the quality of the cluster can be conveniently evaluated with the embedded statistical information. We further develop a novel layout algorithm which can generate similar icons for similar clusters, making comparisons of clusters easier. User interaction and clutter reduction are integrated into the system to help users more effectively analyze and refine clustering results for large datasets. We demonstrate the power of DICON through a user study and a case study in the healthcare domain. Our evaluation shows the benefits of the technique, especially in support of complex multidimensional cluster analysis.
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…
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)
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…
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)
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 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…
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'…
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)
Multidimensional Screening as a Pharmacology Laboratory Experience.
ERIC Educational Resources Information Center
Malone, Marvin H.; And Others
1979-01-01
A multidimensional pharmacodynamic screening experiment that addresses drug interaction is included in the pharmacology-toxicology laboratory experience of pharmacy students at the University of the Pacific. The student handout with directions for the procedure is reproduced, drug compounds tested are listed, and laboratory evaluation results are…
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…
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…
An Examination of Alternative Multidimensional Scaling Techniques
ERIC Educational Resources Information Center
Papazoglou, Sofia; Mylonas, Kostas
2017-01-01
The purpose of this study is to compare alternative multidimensional scaling (MDS) methods for constraining the stimuli on the circumference of a circle and on the surface of a sphere. Specifically, the existing MDS-T method for plotting the stimuli on the circumference of a circle is applied, and its extension is proposed for constraining the…
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)
Multidimensional Tauberian theorems for generalized functions
NASA Astrophysics Data System (ADS)
Drozhzhinov, Yu N.
2016-12-01
This is a brief survey of multidimensional Tauberian theorems for generalized functions. Included are theorems of Hardy-Littlewood type, Tauberian and Abelian comparison theorems of Keldysh type, theorems of Wiener type, and Tauberian theorems for generalized functions with values in Banach spaces. Bibliography: 58 titles.
CAMS: OLAPing Multidimensional Data Streams Efficiently
NASA Astrophysics Data System (ADS)
Cuzzocrea, Alfredo
In the context of data stream research, taming the multidimensionality of real-life data streams in order to efficiently support OLAP analysis/mining tasks is a critical challenge. Inspired by this fundamental motivation, in this paper we introduce
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 stochastic approximation using locally contractive functions
NASA Technical Reports Server (NTRS)
Lawton, W. M.
1975-01-01
A Robbins-Monro type multidimensional stochastic approximation algorithm which converges in mean square and with probability one to the fixed point of a locally contractive regression function is developed. The algorithm is applied to obtain maximum likelihood estimates of the parameters for a mixture of multivariate normal distributions.
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'…
NASA Astrophysics Data System (ADS)
Craig, Paul; Roa-Seïler, Néna
2013-01-01
This paper describes a novel information visualization technique that combines multidimensional scaling and hierarchical clustering to support the exploratory analysis of multidimensional data. The technique displays the results of multidimensional scaling using a scatter plot where the proximity of any two items' representations is approximate to their similarity according to a Euclidean distance metric. The results of hierarchical clustering are overlaid onto this view by drawing smoothed outlines around each nested cluster. The difference in similarity between successive cluster combinations is used to colour code clusters and make stronger natural clusters more prominent in the display. When a cluster or group of items is selected, multidimensional scaling and hierarchical clustering are re-applied to a filtered subset of the data, and animation is used to smooth the transition between successive filtered views. As a case study we demonstrate the technique being used to analyse survey data relating to the appropriateness of different phrases to different emotionally charged situations.
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.
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.
Visualization of Multidimensional Data in Nursing Science.
Docherty, Sharron L; Vorderstrasse, Allison; Brandon, Debra; Johnson, Constance
2016-10-18
Nursing scientists have long been interested in complex, context-dependent questions addressing individual- and population-level challenges in health and illness. These critical questions require multilevel data (e.g., genetic, physiologic, biologic, behavioral, affective, and social). Advances in data-gathering methods have resulted in the collection of large sets of complex, multifaceted, and often non-comparable data. Scientific visualization is a powerful methodological tool for facilitating understanding of these multidimensional data sets. Our purpose is to demonstrate the utility of scientific visualization as a method for identifying associations, patterns, and trends in multidimensional data as exemplified in two studies. We describe a brief history of visual analysis, processes involved in scientific visualization, and opportunities and challenges in the use of visualization methods. Scientific visualization can play a crucial role in helping nurse scientists make sense of the structure and underlying patterns in their data to answer vital questions in the field.
Effective Friedmann model from multidimensional cosmologies
NASA Astrophysics Data System (ADS)
Zhuk, A.
2006-10-01
We investigate the possibility of the construction of the conventional Friedmann cosmology for our observable Universe if the underlying theory is the multidimensional Kaluza-Klein model. We show that the effective Friedmann model obtained by dynamic compactification of the multidimensional model is faced with too strong variations in the fundamental constants. On the other hand, models with stable compactification of the internal space are free from this problem and also result in conventional four-dimensonal cosmological behaviour for our Universe. We prove a no-go theorem, which shows that stable compactification of the internal spaces is possible only if the equations of state in the external and internal spaces are properly adjusted to each other. With a proper choice of parameters (fine tuning), the effective cosmological constant in this model provides the late-time acceleration of the Universe.
Multidimensional entropy landscape of quantum criticality
NASA Astrophysics Data System (ADS)
Grube, K.; Zaum, S.; Stockert, O.; Si, Q.; Löhneysen, H. V.
2017-08-01
The third law of thermodynamics states that the entropy of any system in equilibrium has to vanish at absolute zero temperature. At nonzero temperatures, on the other hand, matter is expected to accumulate entropy near a quantum critical point, where it undergoes a continuous transition from one ground state to another. Here, we determine, based on general thermodynamic principles, the spatial-dimensional profile of the entropy S near a quantum critical point and its steepest descent in the corresponding multidimensional stress space. We demonstrate this approach for the canonical quantum critical compound CeCu 6-xAux near its onset of antiferromagnetic order. We are able to link the directional stress dependence of S to the previously determined geometry of quantum critical fluctuations. Our demonstration of the multidimensional entropy landscape provides the foundation to understand how quantum criticality nucleates novel phases such as high-temperature superconductivity.
Elements Of Theory Of Multidimensional Complex Variables
NASA Technical Reports Server (NTRS)
Martin, E. Dale
1993-01-01
Two reports describe elements of theory of multidimensional complex variables, with emphasis on three dimensions. First report introduces general theory. Second, presents further developments in theory of analytic functions of single three-dimensional variable and applies theory to representation of ideal flows. Results of preliminary studies suggest analytic functions of new three-dimensional complex variables useful in numerous applications, including representing of three-dimensional flows and potentials.
Multidimensional incremental parsing for universal source coding.
Bae, Soo Hyun; Juang, Biing-Hwang
2008-10-01
A multidimensional incremental parsing algorithm (MDIP) for multidimensional discrete sources, as a generalization of the Lempel-Ziv coding algorithm, is investigated. It consists of three essential component schemes, maximum decimation matching, hierarchical structure of multidimensional source coding, and dictionary augmentation. As a counterpart of the longest match search in the Lempel-Ziv algorithm, two classes of maximum decimation matching are studied. Also, an underlying behavior of the dictionary augmentation scheme for estimating the source statistics is examined. For an m-dimensional source, m augmentative patches are appended into the dictionary at each coding epoch, thus requiring the transmission of a substantial amount of information to the decoder. The property of the hierarchical structure of the source coding algorithm resolves this issue by successively incorporating lower dimensional coding procedures in the scheme. In regard to universal lossy source coders, we propose two distortion functions, the local average distortion and the local minimax distortion with a set of threshold levels for each source symbol. For performance evaluation, we implemented three image compression algorithms based upon the MDIP; one is lossless and the others are lossy. The lossless image compression algorithm does not perform better than the Lempel-Ziv-Welch coding, but experimentally shows efficiency in capturing the source structure. The two lossy image compression algorithms are implemented using the two distortion functions, respectively. The algorithm based on the local average distortion is efficient at minimizing the signal distortion, but the images by the one with the local minimax distortion have a good perceptual fidelity among other compression algorithms. Our insights inspire future research on feature extraction of multidimensional discrete sources.
Progress in Multi-Dimensional Upwind Differencing
1992-09-01
advances in each of these components are discussed; putting them all together is the present focus of a worldwide research effort. Some numerical results ...as 1983 by Phil Roe [1]. A study of discrete multi-dimensional wave models by Roe followed in 1985 (ICASE Report 85-18, also [21), but it took until...consider the numerical results shown in Figure :3 and 4, taken from [:34] and [35], respectively. In Figure 3a the exact and discrete Mach-number
Applications of Multidimensional Wavelet Filtering in Geosciences
NASA Astrophysics Data System (ADS)
Yuen, D. A.; Vincent, A. P.; Kido, M.
2001-12-01
Today we are facing a severe crisis of being flooded with huge amounts of data being generated by higher-resolution numerical simulations , laboratory instrumentions and satellite observations. Since there is no way one can visualize the full data set, we must extract essential features from the data-set. One way of addressing this problem is to use mathematical filters , such as multidimensional wavelets. We present imaging results in the geosciences based on using multidimensional Gaussian wavelets as a filter. This approach has been applied to a wide-range of problems, which span from the nanoscale in mineral surfaces imaged by atomic force microscopy to hundreds of kilometers in geoidal undulations determined from satellite orbits or small-scale plumes in high Rayleigh number convection. Besides decomposing the field under consideration into various scales , called a scalogram, we have also constructed two-dimensional maps, delineating the spatial distributions of the maximum of the wavelet transformed quantity E-max and the associated local wave-number. We have generalized the application of multidimensional wavelets to quantify in terms of a two-dimensional map the correlation C for two multidimensional fields A and B. We will show a simple 2D isotropic wavelet-like transform for a spherical surface. We have analyzed the transformed geoid data with a band-pass filter in the spherical harmonic domain and have shown the equivalency of the two representations. This spherical wavelet-like filter can be applied also to problems in planetary science, such as the surface topography and geoid of other planetary bodies, like Mars.
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.
ERIC Educational Resources Information Center
Essexville-Hampton Public Schools, MI.
Described are components of Project FAST (Functional Analysis Systems Training) a nationally validated project to provide more effective educational and support services to learning disordered children and their regular elementary classroom teachers. The program is seen to be based on a series of modules of delivery systems ranging from mainstream…
2009-10-01
or any other computing topic, please visit our Digital Library at www.computer.org/publications/ dlib . NGUYEN: FAST CRCS 1331 Authorized licensed use... Library at http://doi.ieeecomputersociety.org/10.1109/ TC.2009.83. The notation ðk; l; dÞ denotes a systematic code with k ¼ the total bit length of
Trellis coding with multidimensional QAM signal sets
NASA Technical Reports Server (NTRS)
Pietrobon, Steven S.; Costello, Daniel J.
1993-01-01
Trellis coding using multidimensional QAM signal sets is investigated. Finite-size 2D signal sets are presented that have minimum average energy, are 90-deg rotationally symmetric, and have from 16 to 1024 points. The best trellis codes using the finite 16-QAM signal set with two, four, six, and eight dimensions are found by computer search (the multidimensional signal set is constructed from the 2D signal set). The best moderate complexity trellis codes for infinite lattices with two, four, six, and eight dimensions are also found. The minimum free squared Euclidean distance and number of nearest neighbors for these codes were used as the selection criteria. Many of the multidimensional codes are fully rotationally invariant and give asymptotic coding gains up to 6.0 dB. From the infinite lattice codes, the best codes for transmitting J, J + 1/4, J + 1/3, J + 1/2, J + 2/3, and J + 3/4 bit/sym (J an integer) are presented.
Incremental multidimensional scaling method for database visualization
NASA Astrophysics Data System (ADS)
Basalaj, Wojciech
1999-03-01
A collection of entity descriptions may be conveniently represented by a set of tuples or a set of objects with appropriate attributes. The utility of relational and object databases is based on this premise. Methods of multivariate analysis can naturally be applied to such a representation. Multidimensional Scaling deserves particular attention because of its suitability for visualization. The advantage of using Multidimensional Scaling is its generality. Provided that one can judge or calculate the dissimilarity between any pair of data objects, this method can be applied. This makes it invariant to the number and types of object attributes. To take advantage of this method for visualizing large collections of data, however, its inherent computational complexity needs to be alleviated. This is particularly the case for least squares scaling, which involves numerical minimization of a loss function; on the other hand the technique gives better configurations than analytical classical scaling. Numerical optimization requires selection of a convergence criterion, i.e. deciding when to stop. A common solution is to stop after a predetermined number of iterations has been performed. Such an approach, while guaranteed to terminate, may prematurely abort the optimization. The incremental Multidimensional Scaling method presented here solves these problems. It uses cluster analysis techniques to assess the structural significance of groups of data objects. This creates an opportunity to ignore dissimilarities between closely associated objects, thus greatly reducing input size. To detect convergence it maintains a compact representation of all intermediate optimization results. This method has been applied to the analysis of database tables.
Trellis coding with multidimensional QAM signal sets
NASA Technical Reports Server (NTRS)
Pietrobon, Steven S.; Costello, Daniel J.
1993-01-01
Trellis coding using multidimensional QAM signal sets is investigated. Finite-size 2D signal sets are presented that have minimum average energy, are 90-deg rotationally symmetric, and have from 16 to 1024 points. The best trellis codes using the finite 16-QAM signal set with two, four, six, and eight dimensions are found by computer search (the multidimensional signal set is constructed from the 2D signal set). The best moderate complexity trellis codes for infinite lattices with two, four, six, and eight dimensions are also found. The minimum free squared Euclidean distance and number of nearest neighbors for these codes were used as the selection criteria. Many of the multidimensional codes are fully rotationally invariant and give asymptotic coding gains up to 6.0 dB. From the infinite lattice codes, the best codes for transmitting J, J + 1/4, J + 1/3, J + 1/2, J + 2/3, and J + 3/4 bit/sym (J an integer) are presented.
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
Zand, Martin S; Wang, Jiong; Hilchey, Shannon
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.
Utilization of the Discrete Differential Evolution for Optimization in Multidimensional Point Clouds
Radecký, Michal; Snášel, Václav
2016-01-01
The Differential Evolution (DE) is a widely used bioinspired optimization algorithm developed by Storn and Price. It is popular for its simplicity and robustness. This algorithm was primarily designed for real-valued problems and continuous functions, but several modified versions optimizing both integer and discrete-valued problems have been developed. The discrete-coded DE has been mostly used for combinatorial problems in a set of enumerative variants. However, the DE has a great potential in the spatial data analysis and pattern recognition. This paper formulates the problem as a search of a combination of distinct vertices which meet the specified conditions. It proposes a novel approach called the Multidimensional Discrete Differential Evolution (MDDE) applying the principle of the discrete-coded DE in discrete point clouds (PCs). The paper examines the local searching abilities of the MDDE and its convergence to the global optimum in the PCs. The multidimensional discrete vertices cannot be simply ordered to get a convenient course of the discrete data, which is crucial for good convergence of a population. A novel mutation operator utilizing linear ordering of spatial data based on the space filling curves is introduced. The algorithm is tested on several spatial datasets and optimization problems. The experiments show that the MDDE is an efficient and fast method for discrete optimizations in the multidimensional point clouds. PMID:27974884
Uher, Vojtěch; Gajdoš, Petr; Radecký, Michal; Snášel, Václav
2016-01-01
The Differential Evolution (DE) is a widely used bioinspired optimization algorithm developed by Storn and Price. It is popular for its simplicity and robustness. This algorithm was primarily designed for real-valued problems and continuous functions, but several modified versions optimizing both integer and discrete-valued problems have been developed. The discrete-coded DE has been mostly used for combinatorial problems in a set of enumerative variants. However, the DE has a great potential in the spatial data analysis and pattern recognition. This paper formulates the problem as a search of a combination of distinct vertices which meet the specified conditions. It proposes a novel approach called the Multidimensional Discrete Differential Evolution (MDDE) applying the principle of the discrete-coded DE in discrete point clouds (PCs). The paper examines the local searching abilities of the MDDE and its convergence to the global optimum in the PCs. The multidimensional discrete vertices cannot be simply ordered to get a convenient course of the discrete data, which is crucial for good convergence of a population. A novel mutation operator utilizing linear ordering of spatial data based on the space filling curves is introduced. The algorithm is tested on several spatial datasets and optimization problems. The experiments show that the MDDE is an efficient and fast method for discrete optimizations in the multidimensional point clouds.
Multidimensional Image Analysis for High Precision Radiation Therapy.
Arimura, Hidetaka; Soufi, Mazen; Haekal, Mohammad
2017-01-01
High precision radiation therapy (HPRT) has been improved by utilizing conventional image engineering technologies. However, different frameworks are necessary for further improvement of HPRT. This review paper attempted to define the multidimensional image and what multidimensional image analysis is, which may be feasible for increasing the accuracy of HPRT. A number of researches in radiation therapy field have been introduced to understand the multidimensional image analysis. Multidimensional image analysis could greatly assist clinical staffs in radiation therapy planning, treatment, and prediction of treatment outcomes.
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
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
Multidimensional voice analysis of reflux laryngitis patients.
Pribuisienë, Rûta; Uloza, Virgilijus; Saferis, Viktoras
2005-01-01
The aim of the study was to analyze and quantify the voice characteristics of reflux laryngitis (RL) patients and to determine the most important voice tests and voice-quality parameters in the functional diagnostics of RL. The voices of 83 RL patients and 31 persons in the control group were evaluated. Vocal function was assessed using a multidimensional set of video laryngostroboscopic, perceptual, acoustic, aerodynamic and subjective measurements according to the protocol elaborated by the Committee on Phoniatrics of the European Laryngological Society. The mean values of the hoarseness visual analogue scale assessment and voice handicap index were significantly higher (P<0.05) in the group of RL patients as compared to the controls. Objective voice assessment revealed a significant increase in mean values of jitter, shimmer and normalized noise energy (NNE), along with a significant decrease in pitch range, maximum frequency, phonetogram area (S) and maximum phonation time (MPT) in RL patients, both in the male and female subgroups. According to the results of discriminant analysis, the NNE, MPT, S and intensity range were determined as an optimum set for functional diagnostics of RL. The derived function (equation) makes it possible to assign the person to the group of RL patients with an accuracy of 86.7%. The sensitivity and specificity of eight voice parameters were found to be higher than 50%. The results of the present study demonstrate a reduction of phonation capabilities and voice quality in RL patients. Multidimensional voice evaluation makes it possible to detect significant differences in mean values of perceptual, subjective and objective voice quality parameters between RL patients and controls groups. Therefore, multidimensional voice analysis is an important tool in the functional diagnostics of RL.
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.
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.
Hypernetworks: Multidimensional relationships in multilevel systems
NASA Astrophysics Data System (ADS)
Johnson, J. H.
2016-09-01
Networks provide a powerful way of modelling the dynamics of complex systems. Going beyond binary relations, embracing n-ary relations in network science can generalise many structures. This starts with hypergraphs and their Galois structures. Simplicial complexes generalise hypergraphs by adding orientation. Their multidimensional q-connectivity structure generalises connectivity in networks. Hypersimplices generalise simplices by making the relational structure explicit in the notation. This gives a new way of representing multilevel systems and their dynamics, leading to a new fragment-recombine operator to model the complex dynamics of interacting multilevel systems.
Shock capturing schemes for multidimensional flow
NASA Technical Reports Server (NTRS)
Parpia, Ijaz H.
1991-01-01
Progress made in the development of a genuinely multidimensional finite volume algorithm for problems in inviscid gas dynamics is presented. The approach entails: (1) the reconstruction of flowfield data using a planar wave pattern in which the strengths and orientations of the component waves are derived independently of the mesh geometry; and (2) the development of a flux formula which provides a numerical approximation to the flux at a finite volume cell face during the passage of waves which are in general oblique to the face. Several algorithms are outlined, and the most recent developments are included. The results of several numerical cases are also included.
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 world, inflation, and modern acceleration
NASA Astrophysics Data System (ADS)
Bronnikov, K. A.; Rubin, S. G.; Svadkovsky, I. V.
2010-04-01
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.
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…
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…
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.
Temporal masking of multidimensional tactual stimuli
NASA Astrophysics Data System (ADS)
Tan, Hong Z.; Reed, Charlotte M.; Delhorne, Lorraine A.; Durlach, Nathaniel I.; Wan, Natasha
2003-12-01
Experiments were performed to examine the temporal masking properties of multidimensional tactual stimulation patterns delivered to the left index finger. The stimuli consisted of fixed-frequency sinusoidal motions in the kinesthetic (2 or 4 Hz), midfrequency (30 Hz), and cutaneous (300 Hz) frequency ranges. Seven stimuli composed of one, two, or three spectral components were constructed at each of two signal durations (125 or 250 ms). Subjects identified target signals under three different masking paradigms: forward masking, backward masking, and sandwiched masking (in which the target is presented between two maskers). Target identification was studied as a function of interstimulus interval (ISI) in the range 0 to 640 ms. For both signal durations, percent-correct scores increased with ISI for each of the three masking paradigms. Scores with forward and backward masking were similar and significantly higher than scores obtained with sandwiched masking. Analyses of error trials revealed that subjects showed a tendency to respond, more often than chance, with the masker, the composite of the masker and target, or the combination of the target and a component of the masker. The current results are compared to those obtained in previous studies of tactual recognition masking with brief cutaneous spatial patterns. The results are also discussed in terms of estimates of information transfer (IT) and IT rate, are compared to previous studies with multidimensional tactual signals, and are related to research on the development of tactual aids for the deaf.
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.
Testlet-Based Multidimensional Adaptive Testing.
Frey, Andreas; Seitz, Nicki-Nils; Brandt, Steffen
2016-01-01
Multidimensional adaptive testing (MAT) is a highly efficient method for the simultaneous measurement of several latent traits. Currently, no psychometrically sound approach is available for the use of MAT in testlet-based tests. Testlets are sets of items sharing a common stimulus such as a graph or a text. They are frequently used in large operational testing programs like TOEFL, PISA, PIRLS, or NAEP. To make MAT accessible for such testing programs, we present a novel combination of MAT with a multidimensional generalization of the random effects testlet model (MAT-MTIRT). MAT-MTIRT compared to non-adaptive testing is examined for several combinations of testlet effect variances (0.0, 0.5, 1.0, and 1.5) and testlet sizes (3, 6, and 9 items) with a simulation study considering three ability dimensions with simple loading structure. MAT-MTIRT outperformed non-adaptive testing regarding the measurement precision of the ability estimates. Further, the measurement precision decreased when testlet effect variances and testlet sizes increased. The suggested combination of the MTIRT model therefore provides a solution to the substantial problems of testlet-based tests while keeping the length of the test within an acceptable range.
Testlet-Based Multidimensional Adaptive Testing
Frey, Andreas; Seitz, Nicki-Nils; Brandt, Steffen
2016-01-01
Multidimensional adaptive testing (MAT) is a highly efficient method for the simultaneous measurement of several latent traits. Currently, no psychometrically sound approach is available for the use of MAT in testlet-based tests. Testlets are sets of items sharing a common stimulus such as a graph or a text. They are frequently used in large operational testing programs like TOEFL, PISA, PIRLS, or NAEP. To make MAT accessible for such testing programs, we present a novel combination of MAT with a multidimensional generalization of the random effects testlet model (MAT-MTIRT). MAT-MTIRT compared to non-adaptive testing is examined for several combinations of testlet effect variances (0.0, 0.5, 1.0, and 1.5) and testlet sizes (3, 6, and 9 items) with a simulation study considering three ability dimensions with simple loading structure. MAT-MTIRT outperformed non-adaptive testing regarding the measurement precision of the ability estimates. Further, the measurement precision decreased when testlet effect variances and testlet sizes increased. The suggested combination of the MTIRT model therefore provides a solution to the substantial problems of testlet-based tests while keeping the length of the test within an acceptable range. PMID:27917132
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.
Benchmarking the Multidimensional Stellar Implicit Code MUSIC
NASA Astrophysics Data System (ADS)
Goffrey, T.; Pratt, J.; Viallet, M.; Baraffe, I.; Popov, M. V.; Walder, R.; Folini, D.; Geroux, C.; Constantino, T.
2017-04-01
We present the results of a numerical benchmark study for the MUltidimensional Stellar Implicit Code (MUSIC) based on widely applicable two- and three-dimensional compressible hydrodynamics problems relevant to stellar interiors. MUSIC is an implicit large eddy simulation code that uses implicit time integration, implemented as a Jacobian-free Newton Krylov method. A physics based preconditioning technique which can be adjusted to target varying physics is used to improve the performance of the solver. The problems used for this benchmark study include the Rayleigh-Taylor and Kelvin-Helmholtz instabilities, and the decay of the Taylor-Green vortex. Additionally we show a test of hydrostatic equilibrium, in a stellar environment which is dominated by radiative effects. In this setting the flexibility of the preconditioning technique is demonstrated. This work aims to bridge the gap between the hydrodynamic test problems typically used during development of numerical methods and the complex flows of stellar interiors. A series of multidimensional tests were performed and analysed. Each of these test cases was analysed with a simple, scalar diagnostic, with the aim of enabling direct code comparisons. As the tests performed do not have analytic solutions, we verify MUSIC by comparing it to established codes including ATHENA and the PENCIL code. MUSIC is able to both reproduce behaviour from established and widely-used codes as well as results expected from theoretical predictions. This benchmarking study concludes a series of papers describing the development of the MUSIC code and provides confidence in future applications.
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.
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.
Multidimensional gravity in the nonrelativistic limit
NASA Astrophysics Data System (ADS)
Eingorn, Maxim; Zhuk, Alexander
2009-12-01
Exact solutions of the Poisson equation are found for multidimensional spaces with topology M3+d=R3×Td. These solutions describe smooth transitions from Newtonian behavior 1/r3 for distances bigger than the periods of the tori (the sizes of the extra dimensions) to multidimensional behavior 1/r3+d1+d in the small-distance limit. In the case of one extra dimension d=1, a compact and elegant formula for the gravitational potential is found. It is shown that corrections to the gravitational constant in Cavendish-type experiments can be within the measurement accuracy of Newton’s gravitational constant GN. Models with test masses smeared over some (or all) extra dimensions are proposed. It is shown that in a 10-dimensional spacetime with three smeared extra dimensions the size of the remaining three extra dimensions can be enlarged up to submillimeter scales in case of a fundamental Planck scale MPl(10)≈1TeV. In models with all extra dimensions smeared, the gravitational potential coincides exactly with the Newtonian one. Nevertheless, the hierarchy problem can be solved in these models.
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.
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.
Multi-dimensional MHD simple waves
Webb, G. M.; Ratkiewicz, R.; Brio, M.; Zank, G. P.
1996-07-20
In this paper we consider a formalism for multi-dimensional simple MHD waves using ideas developed by Boillat. For simple wave solutions one assumes that all the physical variables (the density {rho}, gas pressure p, fluid velocity u, gas entropy S, and magnetic induction B in the MHD case) depend on a single phase function {phi}(r,t). The simple wave solution ansatz and the MHD equations then require that the phase function {phi} satisfies an implicit equation of the form f({phi})=r{center_dot}n({phi})-{lambda}({phi})t, where n({phi})={nabla}{phi}/|{nabla}{phi}| is the wave normal, {lambda}({phi})={omega}/k=-{phi}{sub t}/|{nabla}{phi}| is the normal speed of the wave front, and f({phi}) is an arbitrary differentiable function of {phi}. The formalism allows for more general simple waves than that usually dealt with in which n({phi}) is a constant unit vector that does not vary along the wave front. The formalism has implications for shock formation and wave breaking for multi-dimensional waves.
Multi-dimensional MHD simple waves
NASA Technical Reports Server (NTRS)
Webb, G. M.; Ratkiewicz, R.; Brio, M.; Zank, G. P.
1995-01-01
In this paper we consider a formalism for multi-dimensional simple MHD waves using ideas developed by Boillat. For simple wave solutions one assumes that all the physical variables (the density rho, gas pressure p, fluid velocity V, gas entropy S, and magnetic induction B in the MHD case) depend on a single phase function phi(r,t). The simple wave solution ansatz and the MHD equations then require that the phase function has the form phi = r x n(phi) - lambda(phi)t, where = n(phi) = Delta phi / (absolute value of Delta phi) is the wave normal and lambda(phi) = omega/k = -phi t / (absolute value of Delta phi) is the normal speed of the wave front. The formalism allows for more general simple waves than that usually dealt with in which n(phi) is a constant unit vector that does not vary along the wave front. The formalism has implications for shock formation for multi-dimensional waves.
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 family therapy: which influences, which specificities?].
Bonnaire, C; Bastard, N; Couteron, J-P; Har, A; Phan, O
2014-10-01
Among illegal psycho-active drugs, cannabis is the most consumed by French adolescents. Multidimensional family therapy (MDFT) is a family-based outpatient therapy which has been developed for adolescents with drug and behavioral problems. MDFT has shown its effectiveness in adolescents with substance abuse disorders (notably cannabis abuse) not only in the United States but also in Europe (International Cannabis Need of Treatment project). MDFT is a multidisciplinary approach and an evidence-based treatment, at the crossroads of developmental psychology, ecological theories and family therapy. Its psychotherapeutic techniques find its roots in a variety of approaches which include systemic family therapy and cognitive therapy. The aims of this paper are: to describe all the backgrounds of MDFT by highlighting its characteristics; to explain how structural and strategy therapies have influenced this approach; to explore the links between MDFT, brief strategic family therapy and multi systemic family therapy; and to underline the specificities of this family therapy method. The multidimensional family therapy was created on the bases of 1) the integration of multiple therapeutic techniques stemming from various family therapy theories; and 2) studies which have shown family therapy efficiency. Several trials have shown a better efficiency of MDFT compared to group treatment, cognitive-behavioral therapy and home-based treatment. Studies have also highlighted that MDFT led to superior treatment outcomes, especially among young people with severe drug use and psychiatric co-morbidities. In the field of systemic family therapies, MDFT was influenced by: 1) the structural family therapy (S. Minuchin), 2) the strategic family theory (J. Haley), and 3) the intergenerational family therapy (Bowen and Boszormenyi-Nagy). MDFT has specific aspects: MDFT therapists think in a multidimensional perspective (because an adolescent's drug abuse is a multidimensional disorder), they
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 Chebyshev interpolation for warm and hot dense matter.
Faussurier, Gérald; Blancard, Christophe
2017-05-01
We propose a scheme based on a multidimensional Chebyshev interpolation to approximate smooth functions that depend on more than one variable. The present method generalizes the one dimensional Chebyshev approximation. The multidimensional approach can be used for generating databases like equation of state in the warm and hot dense matter. It is well suited to the present advance of massively parallel supercomputers.
Multidimensional Chebyshev interpolation for warm and hot dense matter
NASA Astrophysics Data System (ADS)
Faussurier, Gérald; Blancard, Christophe
2017-05-01
We propose a scheme based on a multidimensional Chebyshev interpolation to approximate smooth functions that depend on more than one variable. The present method generalizes the one dimensional Chebyshev approximation. The multidimensional approach can be used for generating databases like equation of state in the warm and hot dense matter. It is well suited to the present advance of massively parallel supercomputers.
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 =…
Nonlinear Multidimensional Assignment Problems Efficient Conic Optimization Methods and Applications
2015-06-24
AFRL-AFOSR-VA-TR-2015-0281 Nonlinear Multidimensional Assignment Problems Efficient Conic Optimization Methods and Applications Hans Mittelmann...2012 - March 2015 4. TITLE AND SUBTITLE Nonlinear Multidimensional Assignment Problems Efficient Conic Optimization Methods and Applications 5a...problems. The size 16 three-dimensional quadratic assignment problem Q3AP from wireless communications was solved using a sophisticated approach
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.
The Tunneling Method for Global Optimization in Multidimensional Scaling.
ERIC Educational Resources Information Center
Groenen, Patrick J. F.; Heiser, Willem J.
1996-01-01
A tunneling method for global minimization in multidimensional scaling is introduced and adjusted for multidimensional scaling with general Minkowski distances. The method alternates a local search step with a tunneling step in which a different configuration is sought with the same STRESS implementation. (SLD)
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 =…
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 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 Approximation Operators Generated by Lebesgue-Stieltjes Measures
NASA Astrophysics Data System (ADS)
Volkov, Yu I.
1984-06-01
A general class of sequences of multidimensional positive linear operators is defined and studied; it includes, in particular, sequences of multidimensional Berstein polynomials. The main asymptotic term is obtained in the remainder when derivatives of functions in certain classes are approximated by derivatives of the values of the operators on these functions. Bibliography: 10 titles.
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,…
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…
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…
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…
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…
Physical properties of multidimensional and multiferroic composites
NASA Astrophysics Data System (ADS)
Mori, Kiyotaka
The properties of multidimensional and multiferroic composite systems consisting of smart materials are investigated for the intended use in microelectromechanical systems (MEMS) sensor and actuator applications. A multidimensional composite system combines within it different dimensionalities such as 1-D, 2-D, and 3-D constituents. A multiferroic composite system, meanwhile, consists of different ferroics such as ferroelastic, ferromagnetic and ferroelectric materials. We demonstrate effects of dimensionality on thermoelastic properties of NiTi/Si cantilevers for MEMS actuators. The stress state of the bimorph cantilevers is controlled by the dimensionality of the Si cantilever surface (2-D or 1-D corrugated) or the NiTi thin film (2-D or 1-D patterned). Compared to single dimensional NiTi/Si cantilevers the multidimensional device features an improved actuation performance, that is, it combines a small thermoelastic with a large martensitic transformational deflection. We also demonstrate magnetoelectric effects as examples of multiferroic composite systems for novel sensor applications. An example is the magnetic field induced magnetoelectric effect, MEH, in a ferroelectric/ferromagnetic composite PVDF/Terfenol-D. Here, an applied magnetic field induces a piezomagnetic strain in Terfenol-D, which couples to PVDF and induces a piezoelectric charge or voltage. We obtained a MEH coefficient of 1.43 V/cm Oe in agreement with an analytical calculation. The magnetoelastic coupling coefficient of the PVDF/Terfenol-D composite is estimated as 11%. Further, we demonstrate an electrical field induced magnetoelectric effect, MEE, in the ferromagnetic/ferroelectric composites CoB/PZT and PZT/Metglas/PZT. In this case the application of an electric field induces a piezoelectric strain in the PZT ceramic. The strain couples to piezomagnetic CoB or Metglas. Hence, the magnetization of the ferromagnetic materials changes with the electrical field applied to the ferroelectric
Multidimensional optics and dynamics of liquid crystals
NASA Astrophysics Data System (ADS)
Tang, Shouping
2007-12-01
In this dissertation, we present an alternative description of multidimensional optics in liquid crystals and uniaxial media, and a systematical investigation on the dynamic properties of twist nematic devices and ECB devices including flow. We also present our investigation on the backflow and dynamic properties of nematic liquid crystals in modulated electric fields. Based on the understanding to backflow and dynamics of liquid crystals, the dynamics of colloidal particles dispersed in nematic liquid crystals and the flow-induced dynamic optical crosstalk between pixels in nematic liquid crystal devices are also studied. The alternative description of multidimensional optics combines the geometrical optics approximation (GOA) with the beam propagation method (BPM). The general treatment of this approach is developed both theoretically and numerically. The investigation on the dynamic properties of twist nematic devices and ECB devices with consideration of backflow is done experimentally, theoretically and numerically. The calculation results are compared with the experimental results, and the optical responses due to backflow are discussed in detail. The investigation on the backflow and dynamic properties of a nematic liquid crystal in modulated electric fields includes director, flow and the shift of liquid crystal fluid. Especially, an important phenomenon, reverseswitching, is shown in this investigation. The dynamics of colloidal particles dispersed in a nematic cela is studied experimentally and by computer simulation. The polarity of director distortions determines the direction of lift force, and the backflow is responsible for the horizontal translational motion. The optical crosstalk between pixels demonstrates the significance of switching-induce flow in pixilated devices. The electrical switching of a pixel in a twisted nematic device can induce an optical response in neighboring pixels. These phenomena are studied in detail, both experimentally and
Multidimensional Simulations of Type Ia Supernovae
NASA Astrophysics Data System (ADS)
Calder, A. C.; Ricker, P. M.; Dursi, L. J.; Truran, J. W.; Fryxell, B.; Rosner, R.; Timmes, F. X.; Tufo, H. M.; Zingale, M.; Olson, K.; MacNeice, P.
2001-12-01
We present results from two- and three-dimensional simulations of Type Ia supernovae carried out from first principles using the adaptive-mesh code FLASH. Considering off-center prompt detonations in Chandrasekhar-mass carbon-oxygen white dwarfs, we observe temperature and abundance inhomogeneities with a cell-like structure behind the detonation front. We discuss these results in light of the commonly accepted view that prompt detonation models cannot reproduce the abundances of intermediate-mass elements observed in Type Ia supernovae, considering in general the observability of multidimensional structure in carbon detonations under conditions present in a white dwarf. This research has been supported by the U.S. Department of Energy under grant no. B341495 to the ASCI Flash Center at the University of Chicago.
Masking failures of multidimensional sensors (extended abstract)
NASA Technical Reports Server (NTRS)
Chew, Paul; Marzullo, Keith
1990-01-01
When a computer monitors a physical process, the computer uses sensors to determine the values of the physical variables that represent the state of the process. A sensor can sometimes fail, however, and in the worst case report a value completely unrelated to the true physical value. The work described is motivated by a methodology for transforming a process control program that can not tolerate sensor failure into one that can. In this methodology, a reliable abstract sensor is created by combining information from several real sensors that measure the same physical value. To be useful, an abstract sensor must deliver reasonably accurate information at reasonable computational cost. Sensors are considered that deliver multidimensional values (e.g., location or velocity in three dimensions, or both temperature and pressure). Geometric techniques are used to derive upper bounds on abstract sensor accuracy and to develop efficient algorithms for implementing abstract sensors.
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.
Biological evolution in a multidimensional fitness landscape
NASA Astrophysics Data System (ADS)
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.
Testing for uniformity in multidimensional data.
Smith, S P; Jain, A K
1984-01-01
Testing for uniformity in multidimensional data is important in exploratory pattern analysis, statistical pattern recognition, and image processing. The goal of this paper is to determine whether the data follow the uniform distribution over some compact convex set in K-dimensional space, called the sampling window. We first provide a simple, computationally efficient method for generating a uniformly distributed sample over a set which approximates the convex hul of the data. We then test for uniformity by comparing this generated sample to the data by using Friedman-Rafsky's minimal spanning tree (MST) based test. Experiments with both simulated and real data indicate that this MST-based test is useful in deciding if data are uniform.
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.
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 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.
Multidimensional integrable models of gravitation and cosmology
NASA Astrophysics Data System (ADS)
Ivashchuk, V. D.; Melnikov, V. N.
Review of the motivation and main results in multidimentional gravitation and cosmology is presented. Special attention is devoted to results within the model with scalar fields and fields of forms in the billiard approach for obtaining cosmological solutions with branes and integrable configurations with fluxand black branes. In case of the quantum billiard with branes it is shown that the basis solutions for wave functions vanish in the limit of the formation of billiard walls (i.e., at the singularity) for the D = 11 model which mimics the D = 11 supergravitational cosmology. Another fruitful approach - to multidimensional gravity with higher derivatives is mentioned, which leads to a unified description of inflation and the present accelerated expansion of the Universe. Some of these models explain possible spatial and temporal variations of the fine structure and the gravitational constants.
Quantum effects in homogeneous multidimensional cosmologies
Szydlowski, M.; Szczesny, J.
1988-12-15
In the present paper we determine quantum distribution functions for a wide class of multidimensional cosmological models. The exact formulas for quantum distribution functions are given and their universal character at high and low temperatures shown. The obtained formulas provide us with the possibility to investigate the metric back reaction and to discuss the dimensional reduction problem. The assumption of the low-temperature approximation gives us the possibility to discuss the dynamics by using the methods of dynamical systems. Stable solutions, within the class FRW x S/sup 3/ x S/sup 3/ models, where FRW denotes Friedmann, Robertson and Walker, are discussed, and it is shown that only a zero-measure set of trajectories in the phase space leads to a solution with a static microspace. This analysis shows that, insofar as quantum effects lead to solutions with a static microspace, these solutions are unstable.
Multidimensional gas chromatography beyond simple volatiles separation.
Chin, Sung-Tong; Marriott, Philip J
2014-08-18
Multidimensional separation in gas chromatography (MDGC) plays an important role in chemical analysis. This review presents selected literature on MDGC development and examples of the range of functionality reported for MDGC methods over the past 2 decades. With the most obvious advantage of providing much greater capacity for resolving constituents of a sample, MDGC extends analytical efficiency to a more substantial molecular coverage, combined with operational flexibility. But by judicious choice of implementation method, important chemical information relating to the sample, its components, potentially physico-chemical properties, and improved capacity for absolute identification may be realised. Sample-to-sample comparison is improved, and sample characterisation is facilitated especially when MDGC is combined with the informing power of modern mass spectrometry. Innovative MDGC arrangements allow high resolution coupled with spectroscopy and alternative bioassays, and delivers molecular elucidation in ways that are beyond just simple analysis of volatiles.
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.
Compressed Sensing for Multidimensional Spectroscopy Experiments.
Sanders, Jacob N; Saikin, Semion K; Mostame, Sarah; Andrade, Xavier; Widom, Julia R; Marcus, Andrew H; Aspuru-Guzik, Alán
2012-09-20
Compressed sensing is a processing method that significantly reduces the number of measurements needed to accurately resolve signals in many fields of science and engineering. We develop a two-dimensional variant of compressed sensing for multidimensional spectroscopy and apply it to experimental data. For the model system of atomic rubidium vapor, we find that compressed sensing provides an order-of-magnitude (about 10-fold) improvement in spectral resolution along each dimension, as compared to a conventional discrete Fourier transform, using the same data set. More attractive is that compressed sensing allows for random undersampling of the experimental data, down to less than 5% of the experimental data set, with essentially no loss in spectral resolution. We believe that by combining powerful resolution with ease of use, compressed sensing can be a powerful tool for the analysis and interpretation of ultrafast spectroscopy data.
DRACO---A New Multidimensional Hydrocode
NASA Astrophysics Data System (ADS)
Keller, D.; Collins, T. J. B.; Delettrez, J. A.; McKenty, P. W.; Radha, P. B.; Town, R. P. J.; Whitney, B.; Moses, G. A.
1999-11-01
A program to develop a new multidimensional hydrocode is underway at LLE. DRACO is an arbitrary Lagrange-Eulerian (ALE) code designed to run in 1, 2, and 3 dimensions in planar (cartesian), cylindrical, and spherical geometries. The basic hydroportion of DRACO employs second-order rezoning and interface tracking. A mixed-material equation of state (EOS) using SESAME or Wisconsin table lookups has recently been incorporated. One of the main objectives of the program is to fully exploit the parallel capabilities of the 32-processor SGI Origin-2000. This paper will describe the basic code, present results of our parallel work, and show results of recent burnthrough calculations. This work was supported by the U.S. Department of Energy Office of Inertial Confinement Fusion under Cooperative Agreement No. DE-FC03-92SF19460, the University of Rochester, and the New York State Energy Research and Development Authority.
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.
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.
Transonic Shocks in Multidimensional Divergent Nozzles
NASA Astrophysics Data System (ADS)
Bae, Myoungjean; Feldman, Mikhail
2011-07-01
We establish existence, uniqueness and stability of transonic shocks for a steady compressible non-isentropic potential flow system in a multidimensional divergent nozzle with an arbitrary smooth cross-section, for a prescribed exit pressure. The proof is based on solving a free boundary problem for a system of partial differential equations consisting of an elliptic equation and a transport equation. In the process, we obtain unique solvability for a class of transport equations with velocity fields of weak regularity (non-Lipschitz), an infinite dimensional weak implicit mapping theorem which does not require continuous Fréchet differentiability, and regularity theory for a class of elliptic partial differential equations with discontinuous oblique boundary conditions.
Nonlinear, inelastic fast reactor subassembly interaction analyses
Sutherland, W.H.; Bard, F.E.
1983-01-01
Liquid Metal Fast Breeder Reactor (LMFBR) core structural design is complicated by the trade-offs associated with keeping the subassemblies closely packed for the neutronic considerations and accommodating the volumetric changes associated with irradiation swelling. The environmental variation across the reactor core results in temperature and neutron flux gradients across the subassemblies which in turn cause the subassemblies to bow as well as dilate and grow volumetrically. These deformations in a tightly packed reactor core cause the subassemblies to interact and can potentially result in excessive withdrawal loads during the refueling operations. ABADAN, a general purpose, nonlinear, inelastic, multi-dimensional finite element structural analysis computer code, was developed for the express purpose of solving large nonlinear problems as typified by the above interaction problems. For the subassembly interaction problem ABADAN has been applied to the solution of an interacting radial row of Fast Flux Test Facility (FFTF) fuel assemblies.
Modelling spatiotemporal change using multidimensional arrays Meng
NASA Astrophysics Data System (ADS)
Lu, Meng; Appel, Marius; Pebesma, Edzer
2017-04-01
The large variety of remote sensors, model simulations, and in-situ records provide great opportunities to model environmental change. The massive amount of high-dimensional data calls for methods to integrate data from various sources and to analyse spatiotemporal and thematic information jointly. An array is a collection of elements ordered and indexed in arbitrary dimensions, which naturally represent spatiotemporal phenomena that are identified by their geographic locations and recording time. In addition, array regridding (e.g., resampling, down-/up-scaling), dimension reduction, and spatiotemporal statistical algorithms are readily applicable to arrays. However, the role of arrays in big geoscientific data analysis has not been systematically studied: How can arrays discretise continuous spatiotemporal phenomena? How can arrays facilitate the extraction of multidimensional information? How can arrays provide a clean, scalable and reproducible change modelling process that is communicable between mathematicians, computer scientist, Earth system scientist and stakeholders? This study emphasises on detecting spatiotemporal change using satellite image time series. Current change detection methods using satellite image time series commonly analyse data in separate steps: 1) forming a vegetation index, 2) conducting time series analysis on each pixel, and 3) post-processing and mapping time series analysis results, which does not consider spatiotemporal correlations and ignores much of the spectral information. Multidimensional information can be better extracted by jointly considering spatial, spectral, and temporal information. To approach this goal, we use principal component analysis to extract multispectral information and spatial autoregressive models to account for spatial correlation in residual based time series structural change modelling. We also discuss the potential of multivariate non-parametric time series structural change methods, hierarchical
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.
Coherent multidimensional vibrational spectroscopy of representative N-alkanes.
Mathew, Nathan A; Rickard, Mark A; Kornau, Kathryn M; Pakoulev, Andrei V; Block, Stephen B; Yurs, Lena A; Wright, John C
2009-09-10
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.
Relations of goal orientations and expectations on multidimensional state anxiety.
Newton, M; Duda, J
1995-12-01
This study examined the relationships among task and ego orientation, expectations for success, and multidimensional state anxiety in a competitive sport situation. Subjects (N = 107) enrolled in a tennis skills class were gender- and ability-matched and asked to play an eight game pro-set. One week prior to the match goal orientations were assessed. Immediately prior to competition multidimensional state anxiety and performance expectations were measured. Multiple regression analyses predicting multidimensional state anxiety revealed that somatic and cognitive state anxiety were only predicted by performance expectations. Also, lower ego orientation and positive match expectations were predictive of state self-confidence. Results are interpreted in light of goal perspective theory.
A Conceptual Model for Multidimensional Analysis of Documents
NASA Astrophysics Data System (ADS)
Ravat, Franck; Teste, Olivier; Tournier, Ronan; Zurlfluh, Gilles
Data warehousing and OLAP are mainly used for the analysis of transactional data. Nowadays, with the evolution of Internet, and the development of semi-structured data exchange format (such as XML), it is possible to consider entire fragments of data such as documents as analysis sources. As a consequence, an adapted multidimensional analysis framework needs to be provided. In this paper, we introduce an OLAP multidimensional conceptual model without facts. This model is based on the unique concept of dimensions and is adapted for multidimensional document analysis. We also provide a set of manipulation operations.
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.
Zero Range Process and Multi-Dimensional Random Walks
NASA Astrophysics Data System (ADS)
Bogoliubov, Nicolay M.; Malyshev, Cyril
2017-07-01
The special limit of the totally asymmetric zero range process of the low-dimensional non-equilibrium statistical mechanics described by the non-Hermitian Hamiltonian is considered. The calculation of the conditional probabilities of the model are based on the algebraic Bethe ansatz approach. We demonstrate that the conditional probabilities may be considered as the generating functions of the random multi-dimensional lattice walks bounded by a hyperplane. This type of walks we call the walks over the multi-dimensional simplicial lattices. The answers for the conditional probability and for the number of random walks in the multi-dimensional simplicial lattice are expressed through the symmetric functions.
Development of out-of-core fast Fourier transform software for the connection machine. Final report
Sweet, R.; Wilson, J.
1995-10-01
This report describes the algorithm and implementation of an out-of-core Fast Fourier Transform routine for the Thinking Machines Corp. CM-5 parallel computer. The software has the capability of transforming multi-dimensional arrays that are both real and complex.
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.
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 Scalar Product Model for the Multidimensional Scaling of Choice
ERIC Educational Resources Information Center
Bechtel, Gordon G.; And Others
1971-01-01
Contains a solution for the multidimensional scaling of pairwise choice when individuals are represented as dimensional weights. The analysis supplies an exact least squares solution and estimates of group unscalability parameters. (DG)
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 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)
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.
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
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.
Towards a genuinely multi-dimensional upwind scheme
NASA Technical Reports Server (NTRS)
Powell, Kenneth G.; Vanleer, Bram; Roe, Philip L.
1990-01-01
Methods of incorporating multi-dimensional ideas into algorithms for the solution of Euler equations are presented. Three schemes are developed and tested: a scheme based on a downwind distribution, a scheme based on a rotated Riemann solver and a scheme based on a generalized Riemann solver. The schemes show an improvement over first-order, grid-aligned upwind schemes, but the higher-order performance is less impressive. An outlook for the future of multi-dimensional upwind schemes is given.
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.
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.
Lustenberger, Caroline; Wehrle, Flavia; Tüshaus, Laura; Achermann, Peter; Huber, Reto
2015-01-01
Study Objectives: Several studies proposed a link between sleep spindles and sleep dependent memory consolidation in declarative learning tasks. In addition to these state-like aspects of sleep spindles, they have also trait-like characteristics, i.e., were related to general cognitive performance, an important distinction that has often been neglected in correlative studies. Furthermore, from the multitude of different sleep spindle measures, often just one specific aspect was analyzed. Thus, we aimed at taking multidimensional aspects of sleep spindles into account when exploring their relationship to word-pair memory consolidation. Design: Each subject underwent 2 study nights with all-night high-density electroencephalographic (EEG) recordings. Sleep spindles were automatically detected in all EEG channels. Subjects were trained and tested on a word-pair learning task in the evening, and retested in the morning to assess sleep related memory consolidation (overnight retention). Trait-like aspects refer to the mean of both nights and state-like aspects were calculated as the difference between night 1 and night 2. Setting: Sleep laboratory. Participants: Twenty healthy male subjects (age: 23.3 ± 2.1 y) Measurements and Results: Overnight retention was negatively correlated with trait-like aspects of fast sleep spindle density and positively with slow spindle density on a global level. In contrast, state-like aspects were observed for integrated slow spindle activity, which was positively related to the differences in overnight retention in specific regions. Conclusion: Our results demonstrate the importance of a multidimensional approach when investigating the relationship between sleep spindles and memory consolidation and thereby provide a more complete picture explaining divergent findings in the literature. Citation: Lustenberger C, Wehrle F, Tüshaus L, Achermann P, Huber R. The multidimensional aspects of sleep spindles and their relationship to word
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
A Computational Model of Multidimensional Shape
Liu, Xiuwen; Shi, Yonggang; Dinov, Ivo
2010-01-01
We develop a computational model of shape that extends existing Riemannian models of curves to multidimensional objects of general topological type. We construct shape spaces equipped with geodesic metrics that measure how costly it is to interpolate two shapes through elastic deformations. The model employs a representation of shape based on the discrete exterior derivative of parametrizations over a finite simplicial complex. We develop algorithms to calculate geodesics and geodesic distances, as well as tools to quantify local shape similarities and contrasts, thus obtaining a formulation that accounts for regional differences and integrates them into a global measure of dissimilarity. The Riemannian shape spaces provide a common framework to treat numerous problems such as the statistical modeling of shapes, the comparison of shapes associated with different individuals or groups, and modeling and simulation of shape dynamics. We give multiple examples of geodesic interpolations and illustrations of the use of the models in brain mapping, particularly, the analysis of anatomical variation based on neuroimaging data. PMID:21057668
A Computational Model of Multidimensional Shape.
Liu, Xiuwen; Shi, Yonggang; Dinov, Ivo; Mio, Washington
2010-08-01
We develop a computational model of shape that extends existing Riemannian models of curves to multidimensional objects of general topological type. We construct shape spaces equipped with geodesic metrics that measure how costly it is to interpolate two shapes through elastic deformations. The model employs a representation of shape based on the discrete exterior derivative of parametrizations over a finite simplicial complex. We develop algorithms to calculate geodesics and geodesic distances, as well as tools to quantify local shape similarities and contrasts, thus obtaining a formulation that accounts for regional differences and integrates them into a global measure of dissimilarity. The Riemannian shape spaces provide a common framework to treat numerous problems such as the statistical modeling of shapes, the comparison of shapes associated with different individuals or groups, and modeling and simulation of shape dynamics. We give multiple examples of geodesic interpolations and illustrations of the use of the models in brain mapping, particularly, the analysis of anatomical variation based on neuroimaging data.
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 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 Hybridization of Dark Surface Plasmons.
Yankovich, Andrew B; Verre, Ruggero; Olsén, Erik; Persson, Anton E O; Trinh, Viet; Dovner, Gudrun; Käll, Mikael; Olsson, Eva
2017-04-07
Synthetic three-dimensional (3D) nanoarchitectures are providing more control over light-matter interactions and rapidly progressing photonic-based technology. These applications often utilize the strong synergy between electromagnetic fields and surface plasmons (SPs) in metallic nanostructures. However, many of the SP interactions hosted by complex 3D nanostructures are poorly understood because they involve dark hybridized states that are typically undetectable with far-field optical spectroscopy. Here, we use experimental and theoretical electron energy loss spectroscopy to elucidate dark SPs and their interactions in layered metal-insulator-metal disc nanostructures. We go beyond the established dipole SP hybridization analysis by measuring breathing and multipolar SP hybridization. In addition, we reveal multidimensional SP hybridization that simultaneously utilizes in-plane and out-of-plane SP coupling. Near-field classic electrodynamics calculations provide excellent agreement with all experiments. These results advance the fundamental understanding of SP hybridization in 3D nanostructures and provide avenues to further tune the interaction between electromagnetic fields and matter.
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.
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.
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.
Multidimensional imaging of the thorax: practical applications.
Ravenel, J G; McAdams, H P; Remy-Jardin, M; Remy, J
2001-10-01
Over the past decade, faster CT scan times, thinner collimation, and the development of multirow detectors, coupled with the increasing capability of computers to process large amounts of data in short periods of time, have lead to an expansion in the ability to create diagnostically useful two-dimensional (2D) and three-dimensional (3D) images within the thorax. Applications within the thorax include, but are not limited to, evaluation of pulmonary and systemic vasculature, evaluation of the tracheobronchial tree, and delineation of diffuse lung disease. Pulmonary nodule volume and growth can be more accurately predicted, and represents an improvement in the evaluation of the solitary pulmonary nodule. Multiplanar images increase our understanding of thoracic anatomy and can help to guide bronchoscopic procedures. Because there are strengths and weaknesses to all the reconstruction algorithms, the utility of any given technique is dependent on the clinical question to be answered. For instance, although maximum intensity projection imaging (MIP) is helpful in the evaluation of micronodular lung disease, it is of little value in the diagnosis of aortic dissection. As the ability to generate faster and more precise multidimensional images grow, the demand for such imaging is likely to increase. In this review, the authors discuss the various reconstruction techniques available, followed by a discussion of the clinical applications.
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 scaling visualization of earthquake phenomena
NASA Astrophysics Data System (ADS)
Lopes, António M.; Machado, J. A. Tenreiro; Pinto, C. M. A.; Galhano, A. M. S. F.
2014-01-01
Earthquakes are associated with negative events, such as large number of casualties, destruction of buildings and infrastructures, or emergence of tsunamis. In this paper, we apply the Multidimensional Scaling (MDS) analysis to earthquake data. MDS is a set of techniques that produce spatial or geometric representations of complex objects, such that, objects perceived to be similar/distinct in some sense are placed nearby/distant on the MDS maps. The interpretation of the charts is based on the resulting clusters since MDS produces a different locus for each similarity measure. In this study, over three million seismic occurrences, covering the period from January 1, 1904 up to March 14, 2012 are analyzed. The events, characterized by their magnitude and spatiotemporal distributions, are divided into groups, either according to the Flinn-Engdahl seismic regions of Earth or using a rectangular grid based in latitude and longitude coordinates. Space-time and Space-frequency correlation indices are proposed to quantify the similarities among events. MDS has the advantage of avoiding sensitivity to the non-uniform spatial distribution of seismic data, resulting from poorly instrumented areas, and is well suited for accessing dynamics of complex systems. MDS maps are proven as an intuitive and useful visual representation of the complex relationships that are present among seismic events, which may not be perceived on traditional geographic maps. Therefore, MDS constitutes a valid alternative to classic visualization tools, for understanding the global behavior of earthquakes.
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.
NASA Astrophysics Data System (ADS)
Schulz, Wolfgang; Hermanns, Torsten; Al Khawli, Toufik
2017-07-01
Decision making for competitive production in high-wage countries is a daily challenge where rational and irrational methods are used. The design of decision making processes is an intriguing, discipline spanning science. However, there are gaps in understanding the impact of the known mathematical and procedural methods on the usage of rational choice theory. Following Benjamin Franklin's rule for decision making formulated in London 1772, he called "Prudential Algebra" with the meaning of prudential reasons, one of the major ingredients of Meta-Modelling can be identified finally leading to one algebraic value labelling the results (criteria settings) of alternative decisions (parameter settings). This work describes the advances in Meta-Modelling techniques applied to multi-dimensional and multi-criterial optimization by identifying the persistence level of the corresponding Morse-Smale Complex. Implementations for laser cutting and laser drilling are presented, including the generation of fast and frugal Meta-Models with controlled error based on mathematical model reduction Reduced Models are derived to avoid any unnecessary complexity. Both, model reduction and analysis of multi-dimensional parameter space are used to enable interactive communication between Discovery Finders and Invention Makers. Emulators and visualizations of a metamodel are introduced as components of Virtual Production Intelligence making applicable the methods of Scientific Design Thinking and getting the developer as well as the operator more skilled.
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
Loslever, Pierre; Bouilland, Stéphane
2003-09-01
Most empirical studies concerning rehabilitation yield numerous multidimensional signals (dozens of time variables are obtained for dozens of empirical situations). The purpose of this paper is to suggest a statistical analysis procedure based on: 1) space-time fuzzy windowing; 2) signal behavior characterization within the windows using membership value averages (MVA); and 3) MVA analysis using the multiple correspondence analysis (MCA). A load lifting study provided an example of 78 multidimensional signals including 89 time variables (forces, energy indicators, linear and angular positions, speeds, and accelerations). The main goal of MCA was to compare and contrast biomechanical signals from two lifting modes: "free" and "isokinetic." In the first mode, three loads were tested--light, medium, and heavy. In the second, three speeds were tested--slow, medium, and fast. Thirteen male individuals without disabilities participated in this study. The MCA showed that most of the free load-lifting strategies cannot be used in isokinetic lifting because the constraints of the subject and the environment are different. In addition, as the level of difficulty increases, free lifting became more economical while isokinetic lifting became less economical. These results would appear to indicate that movement strategies used for free lifting cannot be learned using an isokinetic machine during rehabilitation sessions for chronic low back pain. MCA was also suggested as a tool for comparing patients with control individuals. To achieve this aim, the notion of "supplementary data" was introduced.
Ng, Elaine; Chen, Kaina; Hang, Annie; Syed, Abeer; Zhang, John X J
2016-04-01
Rapid screening of biomarkers, with high specificity and accuracy, is critical for many point-of-care diagnostics. Microfluidics, the use of microscale channels to manipulate small liquid samples and carry reactions in parallel, offers tremendous opportunities to address fundamental questions in biology and provide a fast growing set of clinical tools for medicine. Emerging multi-dimensional nanostructures, when coupled with microfluidics, enable effective and efficient screening with high specificity and sensitivity, both of which are important aspects of biological detection systems. In this review, we provide an overview of current research and technologies that utilize nanostructures to facilitate biological separation in microfluidic channels. Various important physical parameters and theoretical equations that characterize and govern flow in nanostructure-integrated microfluidic channels will be introduced and discussed. The application of multi-dimensional nanostructures, including nanoparticles, nanopillars, and nanoporous layers, integrated with microfluidic channels in molecular and cellular separation will also be reviewed. Finally, we will close with insights on the future of nanostructure-integrated microfluidic platforms and their role in biological and biomedical applications.
Ng, Elaine; Chen, Kaina; Hang, Annie; Syed, Abeer; Zhang, John X.J.
2016-01-01
Rapid screening of biomarkers, with high specificity and accuracy, is critical for many point-of-care diagnostics. Microfluidics, the use of microscale channels to manipulate small liquid samples and carry reactions in parallel, offers tremendous opportunities to address fundamental questions in biology and provide a fast growing set of clinical tools for medicine. Emerging multi-dimensional nanostructures, when coupled with microfluidics, enable effective and efficient screening with high specificity and sensitivity, both of which are important aspects of biological detection systems. In this review, we provide an overview of current research and technologies that utilize nanostructures to facilitate biological separation in microfluidic channels. Various important physical parameters and theoretical equations that characterize and govern flow in nanostructure-integrated microfluidic channels will be introduced and discussed. The application of multi-dimensional nanostructures, including nanoparticles, nanopillars, and nanoporous layers, integrated with microfluidic channels in molecular and cellular separation will also be reviewed. Finally, we will close with insights on the future of nanostructure-integrated microfluidic platforms and their role in biological and biomedical applications. PMID:26692080
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.
On delocalization effects in multidimensional lattices
NASA Astrophysics Data System (ADS)
Bystrik, Anna
A cubic lattice with random parameters is: reduced to a linear chain by the means of the projection technique. The continued fraction expansion (c.f.e.) approach is herein applied to the density of states. Coefficients of the c.f.e. are obtained numerically by the recursion procedure. Properties of the non-stationary second moments (correlations and dispersions) of their distribution are studied in a connection with the other evidences of transport in a one-dimensional Mori chain. The second moments and the spectral density are computed for the various degrees of disorder in the prototype lattice. The possible directions of the further development are outlined. The physical problem that is addressed in the dissertation is the possibility of the existence of a non-Anderson disorder of a specific type. More precisely, this type of a disorder in the one-dimensional case would result in a positive localization threshold. A specific type of such non-Anderson disorder was obtained by adopting a transformation procedure which assigns to the matrix expressing the physics of the multidimensional crystal a tridiagonal Hamiltonian. This Hamiltonian is then assigned to an equivalent one-dimensional tight-binding model. One of the benefits of this approach is that we are guaranteed to obtain a linear crystal with a positive localization threshold. The reason for this is the existence of a threshold in a prototype sample. The resulting linear model is found to be characterized by a correlated and a nonstationary disorder. The existence of such special disorder is associated with the absence of Anderson localization in specially constructed one-dimensional lattices, when the noise intensity is below the non-zero critical value. This work is an important step towards isolating the general properties of a non-Anderson noise. This gives a basis for understanding of the insulator to metal transition in a linear crystal with a subcritical noise.
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 seismic data reconstruction using tensor analysis
NASA Astrophysics Data System (ADS)
Kreimer, Nadia
Exploration seismology utilizes the seismic wavefield for prospecting oil and gas. The seismic reflection experiment consists on deploying sources and receivers in the surface of an area of interest. When the sources are activated, the receivers measure the wavefield that is reflected from different subsurface interfaces and store the information as time-series called traces or seismograms. The seismic data depend on two source coordinates, two receiver coordinates and time (a 5D volume). Obstacles in the field, logistical and economical factors constrain seismic data acquisition. Therefore, the wavefield sampling is incomplete in the four spatial dimensions. Seismic data undergoes different processes. In particular, the reconstruction process is responsible for correcting sampling irregularities of the seismic wavefield. This thesis focuses on the development of new methodologies for the reconstruction of multidimensional seismic data. This thesis examines techniques based on tensor algebra and proposes three methods that exploit the tensor nature of the seismic data. The fully sampled volume is low-rank in the frequency-space domain. The rank increases when we have missing traces and/or noise. The methods proposed perform rank reduction on frequency slices of the 4D spatial volume. The first method employs the Higher-Order Singular Value Decomposition (HOSVD) immersed in an iterative algorithm that reinserts weighted observations. The second method uses a sequential truncated SVD on the unfoldings of the tensor slices (SEQ-SVD). The third method formulates the rank reduction problem as a convex optimization problem. The measure of the rank is replaced by the nuclear norm of the tensor and the alternating direction method of multipliers (ADMM) minimizes the cost function. All three methods have the interesting property that they are robust to curvature of the reflections, unlike many reconstruction methods. Finally, we present a comparison between the methods
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 Convergence in Future 5G Networks
NASA Astrophysics Data System (ADS)
Ruffini, Marco
2017-02-01
Future 5G services are characterised by unprecedented need for high rate, ubiquitous availability, ultra-low latency and high reliability. The fragmented network view that is widespread in current networks will not stand the challenge posed by next generations of users. A new vision is required, and this paper provides an insight on how network convergence and application-centric approaches will play a leading role towards enabling the 5G vision. The paper, after expressing the view on the need for an end-to-end approach to network design, brings the reader into a journey on the expected 5G network requirements and outlines some of the work currently carried out by main standardisation bodies. It then proposes the use of the concept of network convergence for providing the overall architectural framework to bring together all the different technologies within a unifying and coherent network ecosystem. The novel interpretation of multi-dimensional convergence we introduce leads us to the exploration of aspects of node consolidation and converged network architectures, delving into details of optical-wireless integration and future convergence of optical data centre and access-metro networks. We then discuss how ownership models enabling network sharing will be instrumental in realising the 5G vision. The paper concludes with final remarks on the role SDN will play in 5G and on the need for new business models that reflect the application-centric view of the network. Finally, we provide some insight on growing research areas in 5G networking.
Fast exploration of an optimal path on the multidimensional free energy surface.
Chen, Changjun
2017-01-01
In a reaction, determination of an optimal path with a high reaction rate (or a low free energy barrier) is important for the study of the reaction mechanism. This is a complicated problem that involves lots of degrees of freedom. For simple models, one can build an initial path in the collective variable space by the interpolation method first and then update the whole path constantly in the optimization. However, such interpolation method could be risky in the high dimensional space for large molecules. On the path, steric clashes between neighboring atoms could cause extremely high energy barriers and thus fail the optimization. Moreover, performing simulations for all the snapshots on the path is also time-consuming. In this paper, we build and optimize the path by a growing method on the free energy surface. The method grows a path from the reactant and extends its length in the collective variable space step by step. The growing direction is determined by both the free energy gradient at the end of the path and the direction vector pointing at the product. With fewer snapshots on the path, this strategy can let the path avoid the high energy states in the growing process and save the precious simulation time at each iteration step. Applications show that the presented method is efficient enough to produce optimal paths on either the two-dimensional or the twelve-dimensional free energy surfaces of different small molecules.
Fast exploration of an optimal path on the multidimensional free energy surface
Chen, Changjun
2017-01-01
In a reaction, determination of an optimal path with a high reaction rate (or a low free energy barrier) is important for the study of the reaction mechanism. This is a complicated problem that involves lots of degrees of freedom. For simple models, one can build an initial path in the collective variable space by the interpolation method first and then update the whole path constantly in the optimization. However, such interpolation method could be risky in the high dimensional space for large molecules. On the path, steric clashes between neighboring atoms could cause extremely high energy barriers and thus fail the optimization. Moreover, performing simulations for all the snapshots on the path is also time-consuming. In this paper, we build and optimize the path by a growing method on the free energy surface. The method grows a path from the reactant and extends its length in the collective variable space step by step. The growing direction is determined by both the free energy gradient at the end of the path and the direction vector pointing at the product. With fewer snapshots on the path, this strategy can let the path avoid the high energy states in the growing process and save the precious simulation time at each iteration step. Applications show that the presented method is efficient enough to produce optimal paths on either the two-dimensional or the twelve-dimensional free energy surfaces of different small molecules. PMID:28542475
Fast multidimensional model for the simulation of Raman amplification in plasma.
Farmer, J P; Pukhov, A
2013-12-01
We present Leap, a simulation model for Raman amplification in plasma, combining an envelope treatment of the laser fields with an electrostatic particle-in-cell solver. The code is fully two dimensional, with the model readily extendible to three dimensions, and includes dispersive and refractive effects. Simulations carried out for Raman amplification in a plasma channel show that guiding of both the pump and the probe contribute to the evolution of the probe, resulting in a shorter, more intense pulse.
Fast, Multi-Dimensional and Simultaneous Kymograph-Like Particle Dynamics (SkyPad) Analysis
Cadot, Bruno; Gache, Vincent; Gomes, Edgar R.
2014-01-01
Background Kymograph analysis is a method widely used by researchers to analyze particle dynamics in one dimensional (1D) trajectories. Results Here we provide a Visual Basic-coded algorithm to use as a Microsoft Excel add-in that automatically analyzes particles in 2D trajectories with all the advantages of kymograph analysis. Conclusions This add-in, which we named SkyPad, leads to significant time saving and higher accuracy of particle analysis. Finally, SkyPad can also be used for 3D trajectories analysis. PMID:24586511
SAGE - MULTIDIMENSIONAL SELF-ADAPTIVE GRID CODE
NASA Technical Reports Server (NTRS)
Davies, C. B.
1994-01-01
SAGE, Self Adaptive Grid codE, is a flexible tool for adapting and restructuring both 2D and 3D grids. Solution-adaptive grid methods are useful tools for efficient and accurate flow predictions. In supersonic and hypersonic flows, strong gradient regions such as shocks, contact discontinuities, shear layers, etc., require careful distribution of grid points to minimize grid error and produce accurate flow-field predictions. SAGE helps the user obtain more accurate solutions by intelligently redistributing (i.e. adapting) the original grid points based on an initial or interim flow-field solution. The user then computes a new solution using the adapted grid as input to the flow solver. The adaptive-grid methodology poses the problem in an algebraic, unidirectional manner for multi-dimensional adaptations. The procedure is analogous to applying tension and torsion spring forces proportional to the local flow gradient at every grid point and finding the equilibrium position of the resulting system of grid points. The multi-dimensional problem of grid adaption is split into a series of one-dimensional problems along the computational coordinate lines. The reduced one dimensional problem then requires a tridiagonal solver to find the location of grid points along a coordinate line. Multi-directional adaption is achieved by the sequential application of the method in each coordinate direction. The tension forces direct the redistribution of points to the strong gradient region. To maintain smoothness and a measure of orthogonality of grid lines, torsional forces are introduced that relate information between the family of lines adjacent to one another. The smoothness and orthogonality constraints are direction-dependent, since they relate only the coordinate lines that are being adapted to the neighboring lines that have already been adapted. Therefore the solutions are non-unique and depend on the order and direction of adaption. Non-uniqueness of the adapted grid is
SAGE - MULTIDIMENSIONAL SELF-ADAPTIVE GRID CODE
NASA Technical Reports Server (NTRS)
Davies, C. B.
1994-01-01
SAGE, Self Adaptive Grid codE, is a flexible tool for adapting and restructuring both 2D and 3D grids. Solution-adaptive grid methods are useful tools for efficient and accurate flow predictions. In supersonic and hypersonic flows, strong gradient regions such as shocks, contact discontinuities, shear layers, etc., require careful distribution of grid points to minimize grid error and produce accurate flow-field predictions. SAGE helps the user obtain more accurate solutions by intelligently redistributing (i.e. adapting) the original grid points based on an initial or interim flow-field solution. The user then computes a new solution using the adapted grid as input to the flow solver. The adaptive-grid methodology poses the problem in an algebraic, unidirectional manner for multi-dimensional adaptations. The procedure is analogous to applying tension and torsion spring forces proportional to the local flow gradient at every grid point and finding the equilibrium position of the resulting system of grid points. The multi-dimensional problem of grid adaption is split into a series of one-dimensional problems along the computational coordinate lines. The reduced one dimensional problem then requires a tridiagonal solver to find the location of grid points along a coordinate line. Multi-directional adaption is achieved by the sequential application of the method in each coordinate direction. The tension forces direct the redistribution of points to the strong gradient region. To maintain smoothness and a measure of orthogonality of grid lines, torsional forces are introduced that relate information between the family of lines adjacent to one another. The smoothness and orthogonality constraints are direction-dependent, since they relate only the coordinate lines that are being adapted to the neighboring lines that have already been adapted. Therefore the solutions are non-unique and depend on the order and direction of adaption. Non-uniqueness of the adapted grid is
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.
NASA Astrophysics Data System (ADS)
Lee, Chang-Yong
2015-05-01
We propose a multi-dimensional fast simulated annealing method based on a multivariate Cauchy probability distribution and an initial temperature estimated from the configuration's variation. While conventional multi-dimensional fast simulated annealing adopts the product of onedimensional random variables generated by a univariate Cauchy distribution, the proposed method generates a random vector from a multivariate Cauchy distribution. In this way, fast simulated annealing for a multi-dimensional problem maintains the same annealing schedule as that for the one-dimensional case. The proposed method also utilizes the initial temperature estimated from the configuration's variation to generate a candidate state in addition to the conventional initial temperature derived from the variation of the objective function for the acceptance probability. The proposed method is shown not only to guarantee a fast annealing schedule but also to enhance the search capability. The proposed method was tested against the optimization of real-valued functions. We empirically found that the configuration's initial temperature, together with multivariate Cauchy distribution, is more suitable than the conventional scheme for a fast annealing schedule. Moreover, the proposed method outperforms the conventional one in optimization problems having many variables.
Visual Analysis and Processing of Clusters Structures in Multidimensional Datasets
NASA Astrophysics Data System (ADS)
Bondarev, A. E.
2017-05-01
The article is devoted to problems of visual analysis of clusters structures for a multidimensional datasets. For visual analyzing an approach of elastic maps design [1,2] is applied. This approach is quite suitable for processing and visualizing of multidimensional datasets. To analyze clusters in original data volume the elastic maps are used as the methods of original data points mapping to enclosed manifolds having less dimensionality. Diminishing the elasticity parameters one can design map surface which approximates the multidimensional dataset in question much better. Then the points of dataset in question are projected to the map. The extension of designed map to a flat plane allows one to get an insight about the cluster structure of multidimensional dataset. The approach of elastic maps does not require any a priori information about data in question and does not depend on data nature, data origin, etc. Elastic maps are usually combined with PCA approach. Being presented in the space based on three first principal components the elastic maps provide quite good results. The article describes the results of elastic maps approach application to visual analysis of clusters for different multidimensional datasets including medical data.
[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.
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
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.
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.
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.
Laser–plasma interactions for fast ignition
Kemp, A. J.; Fiuza, F.; Debayle, A.; ...
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
Multidimensional Integrative Genomics Approaches to Dissecting Cardiovascular Disease
Arneson, Douglas; Shu, Le; Tsai, Brandon; Barrere-Cain, Rio; Sun, Christine; Yang, Xia
2017-01-01
Elucidating the mechanisms of complex diseases such as cardiovascular disease (CVD) remains a significant challenge due to multidimensional alterations at molecular, cellular, tissue, and organ levels. To better understand CVD and offer insights into the underlying mechanisms and potential therapeutic strategies, data from multiple omics types (genomics, epigenomics, transcriptomics, metabolomics, proteomics, microbiomics) from both humans and model organisms have become available. However, individual omics data types capture only a fraction of the molecular mechanisms. To address this challenge, there have been numerous efforts to develop integrative genomics methods that can leverage multidimensional information from diverse data types to derive comprehensive molecular insights. In this review, we summarize recent methodological advances in multidimensional omics integration, exemplify their applications in cardiovascular research, and pinpoint challenges and future directions in this incipient field. PMID:28289683
Multidimensional poverty: an alternative measurement approach for the United States?
Waglé, Udaya R
2008-06-01
International poverty research has increasingly underscored the need to use multidimensional approaches to measure poverty. Largely embraced in Europe and elsewhere, this has not had much impact on the way poverty is measured in the United States. In this paper, I use a comprehensive multidimensional framework including economic well-being, capability, and social inclusion to examine poverty in the US. Data from the 2004 General Social Survey support the interconnectedness among these poverty dimensions, indicating that the multidimensional framework utilizing a comprehensive set of information provides a compelling value added to poverty measurement. The suggested demographic characteristics of the various categories of the poor are somewhat similar between this approach and other traditional approaches. But the more comprehensive and accurate measurement outcomes from this approach help policymakers target resources at the specific groups.
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.
... this page: //medlineplus.gov/ency/article/003766.htm Acid-fast stain To use the sharing features on this page, please enable JavaScript. The acid-fast stain is a laboratory test that determines ...
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 ...
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.
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…
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…
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…
Identification of Visual Dimensions in Photographs Using Multidimensional Scaling Techniques.
ERIC Educational Resources Information Center
McIsaac, Marina Stock; And Others
1984-01-01
Graduate students individually examined 34 photographs for an investigation of commonly perceived underlying visual dimensions. Similarity judgements between photographs were used for multidimensional scaling; subject interview data were used to describe meaningful visual concepts. Results indicate that pictures were grouped in clusters along…
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…
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…
Multidimensional Treatment of Attention Deficit Disorder: A Family Oriented Approach.
ERIC Educational Resources Information Center
Erk, Robert R.
1997-01-01
Counseling that involves the entire family has the potential to motivate children with Attention Deficit Disorder (ADD), improve the children's self-concept, and help them improve social skills or functioning. Probable causes, family patterns, effects of ADD on family interactions, counseling issues, and a multidimensional treatment approach are…
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…
Implementation and Measurement Efficiency of Multidimensional Computerized Adaptive Testing
ERIC Educational Resources Information Center
Wang, Wen-Chung; Chen, Po-Hsi
2004-01-01
Multidimensional adaptive testing (MAT) procedures are proposed for the measurement of several latent traits by a single examination. Bayesian latent trait estimation and adaptive item selection are derived. Simulations were conducted to compare the measurement efficiency of MAT with those of unidimensional adaptive testing and random…
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…
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.
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…
Mental Models of Text and Film: A Multidimensional Scaling Analysis.
ERIC Educational Resources Information Center
Rowell, Jack A.; Moss, Peter D.
1986-01-01
Reports results of experiment to determine whether mental models are constructed of interrelationships and cross-relationships of character attributions drawn in themes of novels and films. The study used "Animal Farm" in print and cartoon forms. Results demonstrated validity of multidimensional scaling for representing both media.…
Multidimensional Scaling of High School Students' Perceptions of Academic Dishonesty
ERIC Educational Resources Information Center
Schmelkin, Liora Pedhazur; Gilbert, Kimberly A.; Silva, Rebecca
2010-01-01
Although cheating on tests and other forms of academic dishonesty are considered rampant, no standard definition of academic dishonesty exists. The current study was conducted to investigate the perceptions of academic dishonesty in high school students, utilizing an innovative methodology, multidimensional scaling (MDS). Two methods were used to…
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…
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…
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)
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…
A Multidimensional Test of Self-Concept: Further Findings.
ERIC Educational Resources Information Center
Lathrop, Richard G.
The Multidimensional Test of Self-Concept (MTS) is based on the assumption that an individual's perception of his/her well-being is related to the difference between the current state of that individual and the desired state. This difference between the two states may be directly measured, and a single self-concept score generated. The MTS…
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…
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 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…
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.…
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…
Posterior Predictive Model Checking for Multidimensionality in Item Response Theory
ERIC Educational Resources Information Center
Levy, Roy; Mislevy, Robert J.; Sinharay, Sandip
2009-01-01
If data exhibit multidimensionality, key conditional independence assumptions of unidimensional models do not hold. The current work pursues posterior predictive model checking, a flexible family of model-checking procedures, as a tool for criticizing models due to unaccounted for dimensions in the context of item response theory. Factors…
Scoring and modeling psychological measures in the presence of multidimensionality.
Reise, Steven P; Bonifay, Wes E; Haviland, Mark G
2013-01-01
Confirmatory factor analytic studies of psychological measures showing item responses to be multidimensional do not provide sufficient guidance for applied work. Demonstrating that item response data are multifactorial in this way does not necessarily (a) mean that a total scale score is an inadequate indicator of the intended construct, (b) demand creating and scoring subscales, or (c) require specifying a multidimensional measurement model in research using structural equation modeling (SEM). To better inform these important decisions, more fine-grained psychometric analyses are necessary. We describe 3 established, but seldom used, psychometric approaches that address 4 distinct questions: (a) To what degree do total scale scores reflect reliable variation on a single construct? (b) Is the scoring and reporting of subscale scores justified? (c) If justified, how much reliable variance do subscale scores provide after controlling for a general factor? and (d) Can multidimensional item response data be represented by a unidimensional measurement model in SEM, or are multidimensional measurement models (e.g., second-order, bifactor) necessary to achieve unbiased structural coefficients? In the discussion, we provide guidance for applied researchers on how best to interpret the results from applying these methods and review their limitations.
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…
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…
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…
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 linearizable system of n-wave-type equations
NASA Astrophysics Data System (ADS)
Zenchuk, A. I.
2017-01-01
We propose a linearizable version of a multidimensional system of n-wave-type nonlinear partial differential equations ( PDEs). We derive this system using the spectral representation of its solution via a procedure similar to the dressing method for nonlinear PDEs integrable by the inverse scattering transform method. We show that the proposed system is completely integrable and construct a particular solution.
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…
Science Concepts in Semantic Space--A Multidimensional Scaling Study
ERIC Educational Resources Information Center
Preece, P. F. W.
1976-01-01
Data on the semantic proximity of classical mechanics concepts, obtained by means of a cross-sectional investigation (100 subjects) using a continued word association test, were analyzed by individual difference multidimensional scaling to permit the mapping of semantic space for individual subjects. (JC)
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:…
Multidimensional Treatment of Attention Deficit Disorder: A Family Oriented Approach.
ERIC Educational Resources Information Center
Erk, Robert R.
1997-01-01
Counseling that involves the entire family has the potential to motivate children with Attention Deficit Disorder (ADD), improve the children's self-concept, and help them improve social skills or functioning. Probable causes, family patterns, effects of ADD on family interactions, counseling issues, and a multidimensional treatment approach are…
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 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…
Best Practices Inquiry: A Multidimensional, Value-Critical Framework
ERIC Educational Resources Information Center
Petr, Christopher G.; Walter, Uta M.
2005-01-01
This article offers a multidimensional framework that broadens current approaches to "best practices" inquiry to include (1) the perspectives of both the consumers of services and professional practitioners and (2) a value-based critique. The predominant empirical approach to best practices inquiry is a necessary, but not sufficient, component of…
Interactive Multidimensional Scaling of Cognitive Structure Underlying Person Perception
ERIC Educational Resources Information Center
Kehoe, Jerard; Reynolds, Thomas J.
1977-01-01
A computer-interactive multidimensional scaling program was used together with free response methods to represent and label dimensions of individual cognitive structure underlying persons' perceptions. The dimensional structures derived were predictive of semantic differential, paired comparison, and Repertory Grid Test triad judgments.…
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…
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…
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…
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. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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…
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 &…
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…
Application of Unidimensional Item Response Theory Models to Multidimensional Data.
ERIC Educational Resources Information Center
Drasgow, Fritz; Parsons, Charles K.
The effects of a multidimensional latent trait space on estimation of item and person parameters by the computer program LOGIST are examined. Several item pools were simulated that ranged from truly unidimensional to an inconsequential general latent trait. Item pools with intermediate levels of prepotency of the general latent trait were also…
A multidimensional evaluation of a nursing information-literacy program.
Fox, L M; Richter, J M; White, N E
1996-01-01
The goal of an information-literacy program is to develop student skills in locating, evaluating, and applying information for use in critical thinking and problem solving. This paper describes a multidimensional evaluation process for determining nursing students' growth in cognitive and affective domains. Results indicate improvement in student skills as a result of a nursing information-literacy program. Multidimensional evaluation produces a well-rounded picture of student progress based on formal measurement as well as informal feedback. Developing new educational programs can be a time-consuming challenge. It is important, when expending so much effort, to ensure that the goals of the new program are achieved and benefits to students demonstrated. A multidimensional approach to evaluation can help to accomplish those ends. In 1988, The University of Northern Colorado School of Nursing began working with a librarian to integrate an information-literacy component, entitled Pathways to Information Literacy, into the curriculum. This article describes the program and discusses how a multidimensional evaluation process was used to assess program effectiveness. The evaluation process not only helped to measure the effectiveness of the program but also allowed the instructors to use several different approaches to evaluation. PMID:8826621
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…
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…
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…
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.
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…
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…
Bayesian Multidimensional IRT Models with a Hierarchical Structure
ERIC Educational Resources Information Center
Sheng, Yanyan; Wikle, Christopher K.
2008-01-01
As item response models gain increased popularity in large-scale educational and measurement testing situations, many studies have been conducted on the development and applications of unidimensional and multidimensional models. Recently, attention has been paid to IRT-based models with an overall ability dimension underlying several ability…
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,…
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…
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…
Stabilization of Internal Space in Noncommutative Multidimensional Cosmology
NASA Astrophysics Data System (ADS)
Khosravi, N.; Jalalzadeh, S.; Sepangi, H. R.
We study the cosmological aspects of a noncommutative, multidimensional universe where the matter source is assumed to be a scalar field which does not commute with the internal scale factor. We show that such noncommutativity results in the internal dimensions being stabilized.
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…
Identity Status and Empathic Response Patterns: A Multidimensional Investigation.
ERIC Educational Resources Information Center
Erlanger, David M.
1998-01-01
The multidimensional empathic response patterns of late adolescent undergraduate students (N=153) was examined according to their identity status. Subjects completed self-report measures of empathic response style and identity development. Findings for empathic concern, cognitive empathy, and empathic distress are related to identity status…
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.…
Stylistic Patterns in Language Teaching Research Articles: A Multidimensional Analysis
ERIC Educational Resources Information Center
Kitjaroenpaiboon, Woravit; Getkham, Kanyarat
2016-01-01
This paper presents the results of a multidimensional analysis to investigate stylistic patterns and their communicative functions in language teaching research articles. The findings were that language teaching research articles contained six stylistic patterns and communicative functions. Pattern I consisted of seven salient positive features…
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…
Best Practices Inquiry: A Multidimensional, Value-Critical Framework
ERIC Educational Resources Information Center
Petr, Christopher G.; Walter, Uta M.
2005-01-01
This article offers a multidimensional framework that broadens current approaches to "best practices" inquiry to include (1) the perspectives of both the consumers of services and professional practitioners and (2) a value-based critique. The predominant empirical approach to best practices inquiry is a necessary, but not sufficient, component of…
Preliminary Development of a Multidimensional Semantic Patient Experience Measurement Questionnaire.
Kleiss, James A
2016-10-01
The purpose of this research was to assess the utility and reliability of a multidimensional patient experience measurement questionnaire in a clinical setting. Patient experience has emerged as an important metric for quality of healthcare. A number of separate concepts have been used to measure patient experience, but psychological research suggests that subjective experience is actually a composite of several independent concepts including: (a) evaluation/valence, (b) potency/control, (c) activity/arousal, and (d) novelty. The present research evaluates the reliability of a multidimensional patient experience measurement questionnaire in a clinical setting. A multidimensional semantic differential questionnaire was developed to measure the four underlying semantic dimensions of patient experience mentioned above. A group of 60 patients used the questionnaire to assess prescan expectations and postscan experience of a magnetic resonance scan. Data for one patient were deleted because their scan was interrupted. Results revealed more positive evaluation/valence, higher potency/control, and lower activity/arousal for postscan ratings compared to prescan expectations. Ratings of novelty were neutral in both the prescan and the postscan conditions. Subsequent analysis suggested that internal consistency for some concepts could be improved by replacing several specific rating scales. Present results provide evidence of the utility and reliability of a multidimensional semantic questionnaire for measuring patient experience in an actual clinical setting. Recommendations to improve internal consistency for the concepts potency/control, activity/arousal, and novelty were also provided. © The Author(s) 2016.
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…
Deriving Stopping Rules for Multidimensional Computerized Adaptive Testing
ERIC Educational Resources Information Center
Wang, Chun; Chang, Hua-Hua; Boughton, Keith A.
2013-01-01
Multidimensional computerized adaptive testing (MCAT) is able to provide a vector of ability estimates for each examinee, which could be used to provide a more informative profile of an examinee's performance. The current literature on MCAT focuses on the fixed-length tests, which can generate less accurate results for those examinees whose…
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…
Mental Models of Text and Film: A Multidimensional Scaling Analysis.
ERIC Educational Resources Information Center
Rowell, Jack A.; Moss, Peter D.
1986-01-01
Reports results of experiment to determine whether mental models are constructed of interrelationships and cross-relationships of character attributions drawn in themes of novels and films. The study used "Animal Farm" in print and cartoon forms. Results demonstrated validity of multidimensional scaling for representing both media.…
Deriving Stopping Rules for Multidimensional Computerized Adaptive Testing
ERIC Educational Resources Information Center
Wang, Chun; Chang, Hua-Hua; Boughton, Keith A.
2013-01-01
Multidimensional computerized adaptive testing (MCAT) is able to provide a vector of ability estimates for each examinee, which could be used to provide a more informative profile of an examinee's performance. The current literature on MCAT focuses on the fixed-length tests, which can generate less accurate results for those examinees whose…
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,…
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…
Parentification of Adult Children of Divorce: A Multidimensional Analysis.
ERIC Educational Resources Information Center
Jurkovic, Gregory J.; Thirkield, Alison; Morrell, Richard
2001-01-01
Compared the responses of 381 late adolescent and young adult children of divorce and nondivorce on a new multidimensional measure of parentification assessing the extent and fairness of past and present family caregiving. Evidence that problematic forms of parentification in children of divorce continue into late adolescence and young adulthood…
Multidimensional Scaling of High School Students' Perceptions of Academic Dishonesty
ERIC Educational Resources Information Center
Schmelkin, Liora Pedhazur; Gilbert, Kimberly A.; Silva, Rebecca
2010-01-01
Although cheating on tests and other forms of academic dishonesty are considered rampant, no standard definition of academic dishonesty exists. The current study was conducted to investigate the perceptions of academic dishonesty in high school students, utilizing an innovative methodology, multidimensional scaling (MDS). Two methods were used to…
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 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:…
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…
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…
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…
Using Multidimensional Scaling to Explore Value Issues in Counseling.
ERIC Educational Resources Information Center
Richards, P. Scott; Davison, Mark L.
It is widely agreed that counselors' and clients' values influence every phase of psychotherapy. A preliminary appraisal of the usefulness of multidimensional scaling (MDS) for investigating the effects of values on counseling process and outcome was done. MDS was used to investigate how theistic or atheistic values of a counselor, when revealed,…
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…
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…
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 &…
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…
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…
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…
Teacher Self-Regulation: Examining a Multidimensional Construct
ERIC Educational Resources Information Center
Capa-Aydin, Yesim; Sungur, Semra; Uzuntiryaki, Esen
2009-01-01
This study aimed to develop and validate an instrument to assess the multidimensional nature of teacher self-regulation. A nine-factor structure was proposed: goal setting, intrinsic interest, performance goal orientation, mastery goal orientation, self-instruction, emotional control, self-evaluation, self-reaction, and help-seeking. Through a…
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…
Conditional Covariance-based Representation of Multidimensional Test Structure.
ERIC Educational Resources Information Center
Bolt, Daniel M.
2001-01-01
Presents a new nonparametric method for constructing a spatial representation of multidimensional test structure, the Conditional Covariance-based SCALing (CCSCAL) method. Describes an index to measure the accuracy of the representation. Uses simulation and real-life data analyses to show that the method provides a suitable approximation to…
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…
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…
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…
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.
ERIC Educational Resources Information Center
Kaya-Carton, Esin; Carton, Aaron S.
1986-01-01
Reports on the first phases of an American Council on the Teaching of Foreign Languages project to develop a computerized adaptive test of reading proficiency. The theoretical multidimensionality of the construct is clarified, and its implications for test development, item calibration, and validation procedures are discussed. (Author/SED)
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…
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
D'Ambroise, J.; Salerno, M.; Kevrekidis, P. G.; ...
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.
Nonuniform sampling and maximum entropy reconstruction in multidimensional NMR.
Hoch, Jeffrey C; Maciejewski, Mark W; Mobli, Mehdi; Schuyler, Adam D; Stern, Alan S
2014-02-18
NMR spectroscopy is one of the most powerful and versatile analytic tools available to chemists. The discrete Fourier transform (DFT) played a seminal role in the development of modern NMR, including the multidimensional methods that are essential for characterizing complex biomolecules. However, it suffers from well-known limitations: chiefly the difficulty in obtaining high-resolution spectral estimates from short data records. Because the time required to perform an experiment is proportional to the number of data samples, this problem imposes a sampling burden for multidimensional NMR experiments. At high magnetic field, where spectral dispersion is greatest, the problem becomes particularly acute. Consequently multidimensional NMR experiments that rely on the DFT must either sacrifice resolution in order to be completed in reasonable time or use inordinate amounts of time to achieve the potential resolution afforded by high-field magnets. Maximum entropy (MaxEnt) reconstruction is a non-Fourier method of spectrum analysis that can provide high-resolution spectral estimates from short data records. It can also be used with nonuniformly sampled data sets. Since resolution is substantially determined by the largest evolution time sampled, nonuniform sampling enables high resolution while avoiding the need to uniformly sample at large numbers of evolution times. The Nyquist sampling theorem does not apply to nonuniformly sampled data, and artifacts that occur with the use of nonuniform sampling can be viewed as frequency-aliased signals. Strategies for suppressing nonuniform sampling artifacts include the careful design of the sampling scheme and special methods for computing the spectrum. Researchers now routinely report that they can complete an N-dimensional NMR experiment 3(N-1) times faster (a 3D experiment in one ninth of the time). As a result, high-resolution three- and four-dimensional experiments that were prohibitively time consuming are now practical
Maximum Entropy Reconstruction and Nonuniform Sampling in Multidimensional NMR
HOCH, JEFFREY C.; MACIEJEWSKI, MARK W.; MOBLI, MEHDI; SCHUYLER, ADAM D.; STERN, ALAN S.
2014-01-01
CONSPECTUS NMR spectroscopy is one of the most powerful and versatile analytic tools available to chemists. The discrete Fourier transform (DFT) played a seminal role in the development of modern NMR, including the multidimensional methods that are essential for complex biomolecules, but it suffers from well-known limitations. Chief among these is the difficulty of obtaining high-resolution spectral estimates from short data records. For multidimensional NMR experiments, this imposes a sampling burden, because the time required to perform an experiment is proportional to the number of data samples. At high magnetic field, where spectral dispersion is greatest, the problem becomes particularly acute. Consequently multidimensional NMR experiments that rely on the DFT either must sacrifice resolution in order to be completed in reasonable time, or they must use inordinate amounts of time to achieve the potential resolution afforded by high-field magnets. Maximum entropy (MaxEnt) reconstruction is a non-Fourier method of spectrum analysis capable of providing high-resolution spectral estimates from short data records. It can also be used with nonuniformly sampled data sets. Since resolution is substantially determined by the largest evolution time sampled, nonuniform sampling enables high resolution while avoiding the need to uniformly sample at large numbers of evolution times. The Nyquist sampling theorem does not apply to nonuniformly sampled data, and artifacts that attend the use of nonuniform sampling can be viewed as frequency-aliased signals. Strategies for suppressing nonuniform sampling artifacts include careful design of the sampling scheme and special methods for computing the spectrum. Time savings of a factor of three for each of the N-1 indirect dimensions of an N-dimensional NMR experiment are now routinely reported, making practical high-resolution 3- and 4-dimensional experiments that were previously prohibitively time consuming. Conversely, tailored
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
Exploring and linking biomedical resources through multidimensional semantic spaces.
Berlanga, Rafael; Jiménez-Ruiz, Ernesto; Nebot, Victoria
2012-01-25
The semantic integration of biomedical resources is still a challenging issue which is required for effective information processing and data analysis. The availability of comprehensive knowledge resources such as biomedical ontologies and integrated thesauri greatly facilitates this integration effort by means of semantic annotation, which allows disparate data formats and contents to be expressed under a common semantic space. In this paper, we propose a multidimensional representation for such a semantic space, where dimensions regard the different perspectives in biomedical research (e.g., population, disease, anatomy and protein/genes). This paper presents a novel method for building multidimensional semantic spaces from semantically annotated biomedical data collections. This method consists of two main processes: knowledge and data normalization. The former one arranges the concepts provided by a reference knowledge resource (e.g., biomedical ontologies and thesauri) into a set of hierarchical dimensions for analysis purposes. The latter one reduces the annotation set associated to each collection item into a set of points of the multidimensional space. Additionally, we have developed a visual tool, called 3D-Browser, which implements OLAP-like operators over the generated multidimensional space. The method and the tool have been tested and evaluated in the context of the Health-e-Child (HeC) project. Automatic semantic annotation was applied to tag three collections of abstracts taken from PubMed, one for each target disease of the project, the Uniprot database, and the HeC patient record database. We adopted the UMLS Meta-thesaurus 2010AA as the reference knowledge resource. Current knowledge resources and semantic-aware technology make possible the integration of biomedical resources. Such an integration is performed through semantic annotation of the intended biomedical data resources. This paper shows how these annotations can be exploited for
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.…
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.
Oceans 2.0: Interactive tools for the Visualization of Multi-dimensional Ocean Sensor Data
NASA Astrophysics Data System (ADS)
Biffard, B.; Valenzuela, M.; Conley, P.; MacArthur, M.; Tredger, S.; Guillemot, E.; Pirenne, B.
2016-12-01
Ocean Networks Canada (ONC) operates ocean observatories on all three of Canada's coasts. The instruments produce 280 gigabytes of data per day with 1/2 petabyte archived so far. In 2015, 13 terabytes were downloaded by over 500 users from across the world. ONC's data management system is referred to as "Oceans 2.0" owing to its interactive, participative features. A key element of Oceans 2.0 is real time data acquisition and processing: custom device drivers implement the input-output protocol of each instrument. Automatic parsing and calibration takes place on the fly, followed by event detection and quality control. All raw data are stored in a file archive, while the processed data are copied to fast databases. Interactive access to processed data is provided through data download and visualization/quick look features that are adapted to diverse data types (scalar, acoustic, video, multi-dimensional, etc). Data may be post or re-processed to add features, analysis or correct errors, update calibrations, etc. A robust storage structure has been developed consisting of an extensive file system and a no-SQL database (Cassandra). Cassandra is a node-based open source distributed database management system. It is scalable and offers improved performance for big data. A key feature is data summarization. The system has also been integrated with web services and an ERDDAP OPeNDAP server, capable of serving scalar and multidimensional data from Cassandra for fixed or mobile devices.A complex data viewer has been developed making use of the big data capability to interactively display live or historic echo sounder and acoustic Doppler current profiler data, where users can scroll, apply processing filters and zoom through gigabytes of data with simple interactions. This new technology brings scientists one step closer to a comprehensive, web-based data analysis environment in which visual assessment, filtering, event detection and annotation can be integrated.
Lustenberger, Caroline; Wehrle, Flavia; Tüshaus, Laura; Achermann, Peter; Huber, Reto
2015-07-01
Several studies proposed a link between sleep spindles and sleep dependent memory consolidation in declarative learning tasks. In addition to these state-like aspects of sleep spindles, they have also trait-like characteristics, i.e., were related to general cognitive performance, an important distinction that has often been neglected in correlative studies. Furthermore, from the multitude of different sleep spindle measures, often just one specific aspect was analyzed. Thus, we aimed at taking multidimensional aspects of sleep spindles into account when exploring their relationship to word-pair memory consolidation. Each subject underwent 2 study nights with all-night high-density electroencephalographic (EEG) recordings. Sleep spindles were automatically detected in all EEG channels. Subjects were trained and tested on a word-pair learning task in the evening, and retested in the morning to assess sleep related memory consolidation (overnight retention). Trait-like aspects refer to the mean of both nights and state-like aspects were calculated as the difference between night 1 and night 2. Sleep laboratory. Twenty healthy male subjects (age: 23.3 ± 2.1 y). Overnight retention was negatively correlated with trait-like aspects of fast sleep spindle density and positively with slow spindle density on a global level. In contrast, state-like aspects were observed for integrated slow spindle activity, which was positively related to the differences in overnight retention in specific regions. Our results demonstrate the importance of a multidimensional approach when investigating the relationship between sleep spindles and memory consolidation and thereby provide a more complete picture explaining divergent findings in the literature. © 2015 Associated Professional Sleep Societies, LLC.
Lab-X-ray multidimensional imaging of processes inside porous media
NASA Astrophysics Data System (ADS)
Godinho, Jose
2017-04-01
Time-lapse and other multidimensional X-ray imaging techniques have mostly been applied using synchrotron radiation, which limits accessibility and complicates data analysis. Here, we present new time-lapse imaging approaches using laboratory X-ray computed microtomography (CT) to study transformations inside porous media. Specifically, three methods will be presented: 1) Quantitative time-lapse radiography to study sub-second processes. For example to study the penetration of particles into fractures and pores, which is essential to understand how proppants keep fractures opened during hydraulic fracturing and how filter cakes form during borehole drilling. 2) Combination of time-lapse CT with diffraction tomography to study the transformation between bio-inspired polymorphs in 6D, e.g. mineral phase transformation between ACC, Vaterite and Calcite - CaCO3, and between ACS, Anhydrite and Gypsum - CaSO4. Crystals can be resolved in nanopores down to 7 nm (over 100 times smaller than the resolution of CT), which allows studying the effect of confinement on phase stability and growth rates. 3) Fast iterative helical micro-CT scanning to study samples of high ratio height to width (e.g. long cores) with optimal resolution. Here we show how this can be useful to study the distribution of the products from fluid-mediated mineral reactions throughout longer reaction paths and more representative volumes. Using state of the art reconstruction algorithms allows reducing the scanning times from over ten hours to below two hours enabling time-lapse studies. It is expected that these new techniques will open new possibilities for time-lapse imaging of a wider range of geological processes using laboratory X-ray CT, thereby increasing the accessibility of multidimensional imaging to a larger number of users and applications in geology.
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.
Goree, J.; Ono, M.; Colestock, P.; Horton, R.; McNeill, D.; Park, H.
1985-07-01
Fast wave current drive is demonstrated in the Princeton ACT-I toroidal device. The fast Alfven wave, in the range of high ion-cyclotron harmonics, produced 40 A of current from 1 kW of rf power coupled into the plasma by fast wave loop antenna. This wave excites a steady current by damping on the energetic tail of the electron distribution function in the same way as lower-hybrid current drive, except that fast wave current drive is appropriate for higher plasma densities.
NASA Astrophysics Data System (ADS)
Balsara, Dinshaw S.; Nkonga, Boniface
2017-10-01
Just as the quality of a one-dimensional approximate Riemann solver is improved by the inclusion of internal sub-structure, the quality of a multidimensional Riemann solver is also similarly improved. Such multidimensional Riemann problems arise when multiple states come together at the vertex of a mesh. The interaction of the resulting one-dimensional Riemann problems gives rise to a strongly-interacting state. We wish to endow this strongly-interacting state with physically-motivated sub-structure. The fastest way of endowing such sub-structure consists of making a multidimensional extension of the HLLI Riemann solver for hyperbolic conservation laws. Presenting such a multidimensional analogue of the HLLI Riemann solver with linear sub-structure for use on structured meshes is the goal of this work. The multidimensional MuSIC Riemann solver documented here is universal in the sense that it can be applied to any hyperbolic conservation law. The multidimensional Riemann solver is made to be consistent with constraints that emerge naturally from the Galerkin projection of the self-similar states within the wave model. When the full eigenstructure in both directions is used in the present Riemann solver, it becomes a complete Riemann solver in a multidimensional sense. I.e., all the intermediate waves are represented in the multidimensional wave model. The work also presents, for the very first time, an important analysis of the dissipation characteristics of multidimensional Riemann solvers. The present Riemann solver results in the most efficient implementation of a multidimensional Riemann solver with sub-structure. Because it preserves stationary linearly degenerate waves, it might also help with well-balancing. Implementation-related details are presented in pointwise fashion for the one-dimensional HLLI Riemann solver as well as the multidimensional MuSIC Riemann solver.
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.
Integrative Physiology of Fasting.
Secor, Stephen M; Carey, Hannah V
2016-03-15
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. Copyright © 2016 John Wiley & Sons, Inc.
Estimating Cognitive Profiles Using Profile Analysis via Multidimensional Scaling (PAMS).
Kim, Se-Kang; Frisby, Craig L; Davison, Mark L
2004-10-01
Two of the most popular methods of profile analysis, cluster analysis and modal profile analysis, have limitations. First, neither technique is adequate when the sample size is large. Second, neither method will necessarily provide profile information in terms of both level and pattern. A new method of profile analysis, called Profile Analysis via Multidimensional Scaling (PAMS; Davison, 1996), is introduced to meet the challenge. PAMS extends the use of simple multidimensional scaling methods to identify latent profiles in a multi-test battery. Application of PAMS to profile analysis is described. The PAMS model is then used to identify latent profiles from a subgroup (N = 357) within the sample of the Woodcock-Johnson Psychoeducational Battery-Revised (WJ-R; McGrew, Werder, & Woodcock, 1991; Woodcock & Johnson, 1989), followed by a discussion of procedures for interpreting participants' observed score profiles from the latent PAMS profiles. Finally, advantages and limitations of the PAMS technique are discussed.
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.
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.
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.
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
2016-01-01
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. PMID:25855212
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. © The Author(s) 2015.
Optimized linear prediction for radial sampled multidimensional NMR experiments
NASA Astrophysics Data System (ADS)
Gledhill, John M.; Kasinath, Vignesh; Wand, A. Joshua
2011-09-01
Radial sampling in multidimensional NMR experiments offers greatly decreased acquisition times while also providing an avenue for increased sensitivity. Digital resolution remains a 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.
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.
Multidimensional self-perception: linkages to parental nurturance.
Hopkins, H R; Klein, H A
1993-12-01
Childhood experiences are important for developing self-perception. The present study examined the relationship between parental nurturance and Harter's (1988) multidimensional domains of self-perception as well as gender differences in patterns of perceived nurturance. We had 207 college students complete the Neemann & Harter's Self-Perception Profile for College Students (1986) and Buri's Parental Nurturance Scale (1989). Both men and women saw their mothers as more nurturant than they saw their fathers. We found, consistent with previous findings, a positive relationship between parental nurturance and global self-worth. Nurturance also showed a positive relationship with several dimensions of self-perception. This research underscores the importance of nurturance in the development of self-esteem and the usefulness of a multidimensional construct of self-perception.
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
Multidimensional Simulations of Thermonuclear Supernovae from The First Stars
NASA Astrophysics Data System (ADS)
Chen, Ke-Jung; Heger, Alexander; Almgren, Ann
2011-04-01
Current models of the formation of the first stars in the universe suggest that these stars were very massive, having a typical mass scale of hundreds of solar masses. Such stars would explode as pair instability supernovae (PSNe). These supernovae hold the key to understanding the formation of the first heavy elements and the first galaxy formation in the universe. The current theoretical models for PSNe are all based on one-dimensional calculations; until now, multidimensional simulations have been scarce. We present the results from multidimensional numerical studies of PSNe with a new radiation-hydrodynamics code, CASTRO and with realistic nuclear reaction networks. We simulate the fluid instabilities that occur in multiple spatial dimensions and discuss how the resulting mixing affects the explosion, mixing, and nucleosynthesis of these supernovae.
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.
[Multidimensional separations used in pharmaceutical and biological fields].
Tian, Jing; Lu, Xin; Yang, Jun; Kong, Hongwei; Wang, Yuan; Zhao, Xinjie; Tang, Ping; Yuan, Guangzhi; Xu, Guowang
2005-01-01
A review of multidimensional separations such as comprehensive two-dimensional gas chromatography (GC x GC), comprehensive two-dimensional high performance liquid chromatography (HPLC x HPLC) and their applications in pharmaceutical and biological fields is presented with 71 references. A single CO2 cryo-jet loop modulator was developed for GC x GC and it can be used to modulate compounds higher than C6 effectively. Comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC x GC/TOF-MS) analyses of traditional Chinese medicine volatile oils such as Pogostemon cablin Benth (Cablin Patchouli), Forsythia suspensa (Thunb.) Vahl and Zedoary were reported also. As an emerging technology, multidimensional separations hold the promise and play an important role in the future pharmaceutical and biological fields.
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 (OLAP) Analysis for Designing Dynamic Learning Strategy
NASA Astrophysics Data System (ADS)
Rozeva, A.; Deliyska, B.
2010-10-01
Learning strategy in an intelligent learning system is generally elaborated on the basis of assessment of the following factors: learner's time for reaction, content of the learning object, amount of learning material in a learning object, learning object specification, e-learning medium and performance control. Current work proposes architecture for dynamic learning strategy design by implementing multidimensional analysis model of learning factors. The analysis model concerns on-line analytical processing (OLAP) of learner's data structured as multidimensional cube. Main components of the architecture are analysis agent for performing the OLAP operations on learner data cube, adaptation generator and knowledge selection agent for performing adaptive navigation in the learning object repository. The output of the analysis agent is involved in dynamic elaboration of learning strategy that fits best to learners profile and behavior. As a result an adaptive learning path for individual learner and for learner groups is generated.
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.
Analysis of protein composition using multidimensional chromatography and mass spectrometry.
Link, Andrew J; Washburn, Michael P
2014-11-03
Multidimensional liquid chromatography of peptides produced by protease digestion of complex protein mixtures followed by tandem mass spectrometry can be coupled with automated database searching to identify large numbers of proteins in complex samples. These methods avoid the limitations of gel electrophoresis and in-gel digestions by directly identifying protein mixtures in solution. One method used extensively is named Multidimensional Protein Identification Technology (MudPIT), where reversed-phase chromatography and strong cation-exchange chromatography are coupled directly in a microcapillary column. This column is then placed in line between an HPLC and a mass spectrometer for complex mixture analysis. MudPIT remains a powerful approach for analyzing complex mixtures like whole proteomes and protein complexes. MudPIT is used for quantitative proteomic analysis of complex mixtures to generate novel biological insights.
Optimized fast mixing device for real-time NMR applications
NASA Astrophysics Data System (ADS)
Franco, Rémi; Favier, Adrien; Schanda, Paul; Brutscher, Bernhard
2017-08-01
We present an improved fast mixing device based on the rapid mixing of two solutions inside the NMR probe, as originally proposed by Hore and coworkers (J. Am. Chem. Soc. 125 (2003) 12484-12492). Such a device is important for off-equilibrium studies of molecular kinetics by multidimensional real-time NMR spectrsocopy. The novelty of this device is that it allows removing the injector from the NMR detection volume after mixing, and thus provides good magnetic field homogeneity independently of the initial sample volume placed in the NMR probe. The apparatus is simple to build, inexpensive, and can be used without any hardware modification on any type of liquid-state NMR spectrometer. We demonstrate the performance of our fast mixing device in terms of improved magnetic field homogeneity, and show an application to the study of protein folding and the structural characterization of transiently populated folding intermediates.
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.
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
Models for Multidimensional Tests and Hierarchically Structured Training Materials.
1985-05-01
Development and Evaluation of MIRT Models ........................ 2 Analysis of the General Rasch Model ......................... 6 Interpretation...multidimensional data. The first of the classes of models considered were extensions of the general model proposed by Rasch (1961). This model , in its most...r -- r r _ . . . .- . 5 , - ’ ,, " o 6 Analysis of the General Rasch Model The model presented in Equation I defines a very rich class of special
Multidimensional Dataflow Graph Modeling and Mapping for Efficient GPU Implementation
2012-10-01
design space exploration. Index Terms— Dataflow graph, multidimensional syn- chronous dataflow, graphics processing unit, integral his- togram. 1 ...with audio and video data stream pro- cessing, digital communications, and image processing (e.g., see [ 1 ]). Dataflow provides a formal mechanism for de...well as support for efficient scheduling and buffer size optimization [ 1 ]. However, the SDF model is well suited only for one-dimensional DSP
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.
Vacuum polarization in the field of a multidimensional global monopole
Grats, Yu. V. Spirin, P. A.
2016-11-15
An approximate expression for the Euclidean Green function of a massless scalar field in the spacetime of a multidimensional global monopole has been derived. Expressions for the vacuum expectation values 〈ϕ{sup 2}〉{sub ren} and 〈T{sub 00}〉{sub ren} have been derived by the dimensional regularization method. Comparison with the results obtained by alternative regularization methods is made.
Multidimensional scaling analysis of simulated air combat maneuvering performance data.
Polzella, D J; Reid, G B
1989-02-01
This paper describes the decomposition of air combat maneuvering by means of multidimensional scaling (MDS). MDS analyses were applied to performance data obtained from expert and novice pilots during simulated air-to-air combat. The results of these analyses revealed that the performance of expert pilots is characterized by advantageous maneuverability and intelligent energy management. It is argued that MDS, unlike simpler metrics, permits the investigator to achieve greater insights into the underlying structure associated with performance of a complex task.
Multi-dimensional Modeling of Nova with Realistic Nuclear Physics
Krueger, B.; Zingale, M.; Hoffman, R.
2011-10-10
Over the past year, we continued our exploration of novae explosions through multidimensional simulations with the MAESTRO code. The basic physics needed for these simulations was already in place, but a lot of optimization and refining was needed to produce plausible models. Work focused both on the initial model and the reaction network, and simulations were performed using an NSF TeraGrid allocation on the Kraken machine.
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.
Multidimensional counter-current chromatographic system and its application.
Yang, F; Quan, J; Zhang, T Y; Ito, Y
1998-04-17
A multidimensional counter-current chromatographic system was set up for the first time with two sets of high-speed counter-current chromatography instruments. This system was successfully applied to the preparative separation of isorhamnetin, kaempferol and quercetin from crude flavone aglycones of Ginkgo biloba L. and Hippophae rhamnoides L. with a two-phase solvent system composed of chloroform-methanol-water (4:3:2, v/v/v).
Accelerated expansion of the Universe and multidimensional theory of gravitation
NASA Astrophysics Data System (ADS)
Pakhomov, A. G.
2007-09-01
A condition for accelerated expansion of the Universe is derived from multidimensional formulas of gravitation, which is a generalization of the general theory of relativity for n dimensions. The model of a one-component ideal isotropic substance with a power-law diagonal metric is used as initial one. Restrictions on the state equations of our 3D space and accompanying additional dimensions are obtained.
In-in formalism on tunneling background: Multidimensional quantum mechanics
NASA Astrophysics Data System (ADS)
Sugimura, Kazuyuki
2013-07-01
We reformulate quantum tunneling in a multidimensional system where the tunneling sector is nonlinearly coupled to oscillators. The WKB wave function is explicitly constructed under the assumption that the system was in the ground state before tunneling. We find that the quantum state after tunneling can be expressed in the language of the conventional in-in formalism. Some implications of the result to cosmology are discussed.
Multidimensional signal modulation and/or demodulation for data communications
Smith, Stephen F [London, TN; Dress, William B [Camas, WA
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.
Multidimensional physical activity: An opportunity not a problem
Thompson, Dylan; Peacock, Oliver; Western, Max; Batterham, Alan M.
2015-01-01
Our research shows that no single metric will adequately reflect an individual’s physical activity because multiple biologically-important dimensions are independent and unrelated. We propose that there is an opportunity to exploit this multidimensional characteristic of physical activity in order to improve personalised feedback and offer physical activity options and choices that are tailored to an individual’s needs and preferences. PMID:25607280
Application of multidimensional spectrum analysis for analytical chemistry
Hatsukawa, Yuichi; Hayakawa, Takehito; Toh, Yosuke; Shinohara, Nobuo; Oshima, Masumi
1999-11-16
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.
NASA Technical Reports Server (NTRS)
Cezairliyan, Ared
1988-01-01
Design and operation of accurate millisecond and microsecond resolution optical pyrometers developed at the National Bureau of Standards during the last two decades are described. Results of tests are presented and estimates of uncertainties in temperature measurements are given. Calibration methods are discussed and examples of applications of fast pyrometry are given. Ongoing research in developing fast multiwavelength and spatial scanning pyrometers are summarized.
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.
Fast protein folding kinetics.
Gelman, Hannah; Gruebele, Martin
2014-05-01
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 <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.
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
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/. Copyright © 2014 Elsevier Inc. All rights reserved.
Confirmatory Factor Analysis and Profile Analysis via Multidimensional Scaling.
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 profiles in a multi-subtest test battery. Major profile patterns are represented as dimensions extracted from a MDS analysis. PAMS represents an individual observed score as a linear combination of dimensions where the dimensions are the most typical profile patterns present in a population. While the PAMS approach was initially developed for exploratory purposes, its results can later be confirmed in a different sample by CFA. Since CFA is often used to verify results from an exploratory factor analysis, the present paper makes the connection between a factor model and the PAMS model, and then illustrates CFA with a simulated example (that was generated by the PAMS model) and at the same time with a real example. The real example demonstrates confirmation of PAMS exploratory results by using a different sample. Fit indexes can be used to indicate whether the CFA reparameterization as a confirmatory approach works for the PAMS exploratory results.
Multidimensional physical self-concept of athletes with physical disabilities.
Shapiro, Deborah R; Martin, Jeffrey J
2010-10-01
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 = 36, M age = 16.11, SD age = 2.8) completed the Physical Self-Description Questionnaire. Participants reported mostly positive perceptions of self-esteem, global physical self-concept, endurance, body fat, sport competence, strength, flexibility, and physical activity (Ms ranging from 3.9 to 5.6 out of 6). Correlations indicated a number of significant relationships among self-esteem and reported PA and various dimensions of physical self-concept. Using physical self-concept, strength, endurance, and flexibility in the first regression equation and sport competence and endurance simultaneously in the second equation, 47 and 31% of the variance was accounted for in self-esteem and reported PA, respectively. The findings support the value of examining multidimensional physical self-concept as different aspects of the physical self appear to have different influences on reported PA engagement versus self-esteem.
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.
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.
Design of integrated and networked multidimensional grating digital readout
NASA Astrophysics Data System (ADS)
Chang, Li; Xu, Hui; Xiu, Guoyi
2008-10-01
The grating digital readout is the key measurement feedback device of the numerical control system and base of the equipment manufacturing industry. With the development of the complex machining, the multi-axis linkage is a new direction of the numerical control system, which needs the multidimensional measurement. Based on all digital grating moiré fringe subdivision theory, the paper introduces the design of integrated and networked multidimensional grating digital readout with an embedded system-on-chip ZA7V that is a complete field configurable system-on-chip with a 32- bit ARM7TDMI processor core, a programmable logic matrix, a robust memory subsystem and a high-performance dedicated internal bus. Networked functions include Ethernet interface, CAN bus interface, USB bus interface and GPRS interface so that the grating digital readout can access the device network, workshop network, intranet network and Internet. The simulation results and experimental data prove that the realization of the integrated and networked multidimensional grating digital readout. It will be widely used in the numerical control system and machining center.
Efficient Subtorus Processor Allocation in a Multi-Dimensional Torus
Weizhen Mao; Jie Chen; William Watson
2005-11-30
Processor allocation in a mesh or torus connected multicomputer system with up to three dimensions is a hard problem that has received some research attention in the past decade. With the recent deployment of multicomputer systems with a torus topology of dimensions higher than three, which are used to solve complex problems arising in scientific computing, it becomes imminent to study the problem of allocating processors of the configuration of a torus in a multi-dimensional torus connected system. In this paper, we first define the concept of a semitorus. We present two partition schemes, the Equal Partition (EP) and the Non-Equal Partition (NEP), that partition a multi-dimensional semitorus into a set of sub-semitori. We then propose two processor allocation algorithms based on these partition schemes. We evaluate our algorithms by incorporating them in commonly used FCFS and backfilling scheduling policies and conducting simulation using workload traces from the Parallel Workloads Archive. Specifically, our simulation experiments compare four algorithm combinations, FCFS/EP, FCFS/NEP, backfilling/EP, and backfilling/NEP, for two existing multi-dimensional torus connected systems. The simulation results show that our algorithms (especially the backfilling/NEP combination) are capable of producing schedules with system utilization and mean job bounded slowdowns comparable to those in a fully connected multicomputer.
The Compactification Problems of Additional Dimensions in Multidimensional Cosmological Theories
NASA Astrophysics Data System (ADS)
Saidov, Tamerlan
2011-11-01
Multidimensionality of our Universe is one of the most intriguing assumption in modern physics. It follows naturally from theories unifying different fundamental interactions with gravity, e.g. M/string theory. The idea has received a great deal of renewed attention over the last few years. However, it also brings a row of additional questions. According to observations the internal space should be static or nearly static at least from the time of primordial nucleosynthesis, otherwise the fundamental physical constants would vary. This means that at the present evolutionary stage of the Universe there are two possibilities: slow variation or compactification of internal space scale parameters. In many recent studies the problem of extra dimensions stabilization was studied for so-called ADD. Under these approaches a massive scalar fields (gravitons or radions) of external space-time can be presented as conformal excitations. In above mentioned works it was assumed that multidimensional action to be linear with respect to curvature. Although as follows from string theory, the gravity action needs to be extended to nonlinear one. In order to investigate effects of nonlinearity, in this Thesis a multidimensional Lagrangian will be studied, having the form L = f(R), where f(R) is an arbitrary smooth function of the scalar curvature.
Testing a multidimensional nonveridical aircraft collision avoidance system.
Knecht, William R
2008-08-01
This study explores operators' ability to use a multidimensional, nonveridical control display. Veridical displays represent realistic scenes. State space displays represent nonveridical n-dimensional information based on informative coordinate axes plus variable features such as color and shading. Empirical investigation of state space displays is relatively new to human factors research. Twelve licensed general aviation pilots flew flight scenarios, trying to deviate as little as possible from a preassigned course while still maintaining standard en route separation from traffic. Flight performance using only a veridical cockpit display of traffic information (CDTI) was compared with performance using the CDTI augmented by a 4-D nonveridical state space collision avoidance system (CDTI+4CAS). Using moderate traffic density and complex traffic geometry, the CDTI+4CAS condition showed performance superiority over the baseline CDTI-only condition for five of five dependent measures of maneuver efficiency, four of four measures of maneuver safety, and six of nine measures of user workload. Results suggest that nonveridical information display may enhance operator performance on a control task involving simultaneous processing of multidimensional information. Nonveridical information displays have potential application wherever human control of multidimensional processes is involved.
Multidimensional Dyspnea Profile: an instrument for clinical and laboratory research
O'Donnell, Carl R.; Guilfoyle, Tegan E.; Parshall, Mark B.; Schwartzstein, Richard M.; Meek, Paula M.; Gracely, Richard H.; Lansing, Robert W.
2015-01-01
There is growing awareness that dyspnoea, like pain, is a multidimensional experience, but measurement instruments have not kept pace. The Multidimensional Dyspnea Profile (MDP) assesses overall breathing discomfort, sensory qualities, and emotional responses in laboratory and clinical settings. Here we provide the MDP, review published evidence regarding its measurement properties and discuss its use and interpretation. The MDP assesses dyspnoea during a specific time or a particular activity (focus period) and is designed to examine individual items that are theoretically aligned with separate mechanisms. In contrast, other multidimensional dyspnoea scales assess recalled recent dyspnoea over a period of days using aggregate scores. Previous psychophysical and psychometric studies using the MDP show that: 1) subjects exposed to different laboratory stimuli could discriminate between air hunger and work/effort sensation, and found air hunger more unpleasant; 2) the MDP immediate unpleasantness scale (A1) was convergent with common dyspnoea scales; 3) in emergency department patients, two domains were distinguished (immediate perception, emotional response); 4) test–retest reliability over hours was high; 5) the instrument responded to opioid treatment of experimental dyspnoea and to clinical improvement; 6) convergent validity with common instruments was good; and 7) items responded differently from one another as predicted for multiple dimensions. PMID:25792641
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.
Enhancing Privacy in Participatory Sensing Applications with Multidimensional Data
Groat, Michael; Forrest, Stephanie; Horey, James L; Edwards, Benjamin; He, Wenbo
2012-01-01
Participatory sensing applications rely on individuals to share local and personal data with others to produce aggregated models and knowledge. In this setting, privacy is an important consideration, and lack of privacy could discourage widespread adoption of many exciting applications. We present a privacy-preserving participatory sensing scheme for multidimensional data which uses negative surveys. Multidimensional data, such as vectors of attributes that include location and environment fields, pose a particular challenge for privacy protection and are common in participatory sensing applications. When reporting data in a negative survey, an individual participant randomly selects a value from the set complement of the sensed data value, once for each dimension, and returns the negative values to a central collection server. Using algorithms described in this paper, the server can reconstruct the probability density functions of the original distributions of sensed values, without knowing the participants actual data. As a consequence, complicated encryption and key management schemes are avoided, conserving energy. We study trade-offs between accuracy and privacy, and their relationships to the number of dimensions, categories, and participants. We introduce dimensional adjustment, a method that reduces the magnification of error associated with earlier work. Two simulation scenarios illustrate how the approach can protect the privacy of a participant's multidimensional data while allowing useful population information to be aggregated.
Exploring and linking biomedical resources through multidimensional semantic spaces
2012-01-01
Background The semantic integration of biomedical resources is still a challenging issue which is required for effective information processing and data analysis. The availability of comprehensive knowledge resources such as biomedical ontologies and integrated thesauri greatly facilitates this integration effort by means of semantic annotation, which allows disparate data formats and contents to be expressed under a common semantic space. In this paper, we propose a multidimensional representation for such a semantic space, where dimensions regard the different perspectives in biomedical research (e.g., population, disease, anatomy and protein/genes). Results This paper presents a novel method for building multidimensional semantic spaces from semantically annotated biomedical data collections. This method consists of two main processes: knowledge and data normalization. The former one arranges the concepts provided by a reference knowledge resource (e.g., biomedical ontologies and thesauri) into a set of hierarchical dimensions for analysis purposes. The latter one reduces the annotation set associated to each collection item into a set of points of the multidimensional space. Additionally, we have developed a visual tool, called 3D-Browser, which implements OLAP-like operators over the generated multidimensional space. The method and the tool have been tested and evaluated in the context of the Health-e-Child (HeC) project. Automatic semantic annotation was applied to tag three collections of abstracts taken from PubMed, one for each target disease of the project, the Uniprot database, and the HeC patient record database. We adopted the UMLS Meta-thesaurus 2010AA as the reference knowledge resource. Conclusions Current knowledge resources and semantic-aware technology make possible the integration of biomedical resources. Such an integration is performed through semantic annotation of the intended biomedical data resources. This paper shows how these annotations
Rosset, Antoine; Spadola, Luca; Pysher, Lance; Ratib, Osman
2006-01-01
The display and interpretation of images obtained by combining three-dimensional data acquired with two different modalities (eg, positron emission tomography and computed tomography) in the same subject require complex software tools that allow the user to adjust the image parameters. With the current fast imaging systems, it is possible to acquire dynamic images of the beating heart, which add a fourth dimension of visual information-the temporal dimension. Moreover, images acquired at different points during the transit of a contrast agent or during different functional phases add a fifth dimension-functional data. To facilitate real-time image navigation in the resultant large multidimensional image data sets, the authors developed a Digital Imaging and Communications in Medicine-compliant software program. The open-source software, called OsiriX, allows the user to navigate through multidimensional image series while adjusting the blending of images from different modalities, image contrast and intensity, and the rate of cine display of dynamic images. The software is available for free download at http://homepage.mac.com/rossetantoine/osirix.
NASA Astrophysics Data System (ADS)
Nan, R. D.; Zhang, H. Y.; Zhang, Y.; Yang, L.; Cai, W. J.; Liu, N.; Xie, J. T.; Zhang, S. X.
2016-11-01
The Five-hundred-meter Aperture Spherical radio Telescope (FAST) is a Chinese mega-science project to build the largest single dish radio telescope in the world. A unique karst depression in Guizhou province has been selected as the site to build an active reflector radio telescope with a diameter of 500 m and three outstanding aspects, which enables FAST to have a large sky coverage and the ability of observing astronomical targets with a high precision. Chinese Academy of Sciences and Guizhou province are in charge of FAST construction. The first light of the telescope was expected on September 25, 2016.
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.
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.
Fasting and cognitive function.
Pollitt, E; Lewis, N L; Garza, C; Shulman, R J
The effects of short-term fasting (skipping breakfast) on the problem-solving performance of 9 to 11 yr old children were studied under the controlled conditions of a metabolic ward. The behavioral test battery included an assessment of IQ, the Matching Familiar Figure Test and Hagen Central Incidental Test. Glucose and insulin levels were measured in blood. All assessments were made under fasting and non-fasting conditions. Skipping breakfast was found to have adverse effects on the children's late morning problem-solving performance. These findings support observations that the timing and nutrient composition of meals have acute and demonstrable effects on behavior.
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.
Multi-Dimensional Structure of Crystalline Chiral Condensates in Quark Matter
NASA Astrophysics Data System (ADS)
Lee, Tong-Gyu; Nishiyama, Kazuya; Yasutake, Nobutoshi; Maruyama, Toshiki; Tatsumi, Toshitaka
We explore the multi-dimensional structure of inhomogeneous chiral condensates in quark matter. For a one-dimensional structure, the system becomes unstable at finite temperature due to the Nambu-Goldstone excitations. However, inhomogeneous chiral condensates with multi-dimensional modulations may be realized as a true long-range order at any temperature, as inferred from the Landau-Peierls theorem. We here present some possible strategies for searching the multi-dimensional structure of chiral crystals.
Pneumococcal Disease Fast Facts
... Home About Pneumococcal Types of Infection Risk Factors & Transmission Symptoms & Complications Diagnosis & Treatment Prevention Photos Fast Facts Pneumococcal Vaccination For Clinicians Streptococcus pneumoniae Transmission Clinical Features Risk Factors Diagnosis & Management Prevention For ...
FAST joins Breakthrough programme
NASA Astrophysics Data System (ADS)
Banks, Michael
2016-11-01
The 180m Five-hundred-meter Aperture Spherical radio Telescope (FAST) - the world's largest single-aperture radio receiver - has become part of the Breakthrough Listen programme, which launched in July 2015 to look for intelligent life beyond Earth.
Multi-dimensional Core-Collapse Supernova Simulations with Neutrino Transport
NASA Astrophysics Data System (ADS)
Pan, Kuo-Chuan; Liebendörfer, Matthias; Hempel, Matthias; Thielemann, Friedrich-Karl
We present multi-dimensional core-collapse supernova simulations using the Isotropic Diffusion Source Approximation (IDSA) for the neutrino transport and a modified potential for general relativity in two different supernova codes: FLASH and ELEPHANT. Due to the complexity of the core-collapse supernova explosion mechanism, simulations require not only high-performance computers and the exploitation of GPUs, but also sophisticated approximations to capture the essential microphysics. We demonstrate that the IDSA is an elegant and efficient neutrino radiation transfer scheme, which is portable to multiple hydrodynamics codes and fast enough to investigate long-term evolutions in two and three dimensions. Simulations with a 40 solar mass progenitor are presented in both FLASH (1D and 2D) and ELEPHANT (3D) as an extreme test condition. It is found that the black hole formation time is delayed in multiple dimensions and we argue that the strong standing accretion shock instability before black hole formation will lead to strong gravitational waves.
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.
Scholz, Gerhard H; Hanefeld, Markolf
2016-10-01
Since 1981, we have used the term metabolic syndrome to describe an association of a dysregulation in lipid metabolism (high triglycerides, low high-density lipoprotein cholesterol, disturbed glucose homeostasis (enhanced fasting and/or prandial glucose), gout, and hypertension), with android obesity being based on a common soil (overnutrition, reduced physical activity, sociocultural factors, and genetic predisposition). We hypothesized that main traits of the syndrome occur early and are tightly connected with hyperinsulinemia/insulin resistance, procoagulation, and cardiovascular diseases. To establish a close link between the traits of the metabolic vascular syndrome, we focused our literature search on recent original work and comprehensive reviews dealing with the topics metabolic syndrome, visceral obesity, fatty liver, fat tissue inflammation, insulin resistance, atherogenic dyslipidemia, arterial hypertension, and type 2 diabetes mellitus. Recent research supports the concept that the metabolic vascular syndrome is a multidimensional and interactive network of risk factors and diseases based on individual genetic susceptibility and epigenetic changes where metabolic dysregulation/metabolic inflexibility in different organs and vascular dysfunction are early interconnected. The metabolic vascular syndrome is not only a risk factor constellation but rather a life-long abnormality of a closely connected interactive cluster of developing diseases which escalate each other and should continuously attract the attention of every clinician.
FastBit: an efficient indexing technology for accelerating data-intensive science
NASA Astrophysics Data System (ADS)
Wu, Kesheng
2005-01-01
FastBit is a software tool for searching large read-only datasets. 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 onedimensional 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 can not. 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.
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.
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.
NASA Astrophysics Data System (ADS)
Zhang, J. S.
2014-09-01
FAST, the Five-hundred meter Aperture Spherical radio Telescope, will become the largest operating single-dish telescope in the coming years. It has many advantages: much better sensitivity for its largest collecting area; large sky coverage due to its innovative design of the active primary surface; extremely radio quiet from its unique location, etc. In this work, I will highlight the future capabilities of FAST to discover and observe both galactic and extragalactic masers.
Scaling Laws for the Multidimensional Burgers Equation with Quadratic External Potential
NASA Astrophysics Data System (ADS)
Leonenko, N. N.; Ruiz-Medina, M. D.
2006-07-01
The reordering of the multidimensional exponential quadratic operator in coordinate-momentum space (see X. Wang, C.H. Oh and L.C. Kwek (1998). J. Phys. A.: Math. Gen. 31:4329-4336) is applied to derive an explicit formulation of the solution to the multidimensional heat equation with quadratic external potential and random initial conditions. The solution to the multidimensional Burgers equation with quadratic external potential under Gaussian strongly dependent scenarios is also obtained via the Hopf-Cole transformation. The limiting distributions of scaling solutions to the multidimensional heat and Burgers equations with quadratic external potential are then obtained under such scenarios.
Advancing a multidimensional, developmental spectrum approach to preschool disruptive behavior.
Wakschlag, Lauren S; Briggs-Gowan, Margaret J; Choi, Seung W; Nichols, Sara R; Kestler, Jacqueline; Burns, James L; Carter, Alice S; Henry, David
2014-01-01
Dimensional approaches are gaining scientific traction. However, their potential for elucidating developmental aspects of psychopathology has not been fully realized. The goal of this article is to apply a multidimensional, developmental framework to model the normal-abnormal spectrum of preschool disruptive behavior. The Multidimensional Assessment of Preschool Disruptive Behavior (MAP-DB), a novel measure, was used to model dimensional severity across developmental parameters theorized to distinguish the normative misbehavior of early childhood from clinically salient disruptive behavior. The 4 MAP-DB dimensions are Temper Loss, Noncompliance, Aggression, and Low Concern for Others. Parents of a diverse sample of 1,488 preschoolers completed the MAP-DB. Multidimensional item response theory (IRT) was used for dimensional modeling. The 4-dimensional, developmentally informed model demonstrated excellent fit. Its factor loadings did not differ across demographic subgroups. All dimensions provided good coverage of the abnormal end of the severity continuum, but only Temper Loss and Noncompliance provided good coverage of milder, normatively occurring behaviors. The developmental expectability and quality of behaviors distinguished normative from atypical behaviors. The point at which frequency of behaviors was atypical varied based on dimensional location for Temper Loss, Noncompliance, and Aggression. The MAP-DB provides an innovative method for operationalizing developmentally specified, dimensional phenotypes in early childhood. Establishing the validity of these dimensional phenotypes in relation to clinical outcomes, neurocognitive substrates, and etiologic pathways will be a crucial test of their clinical utility. Copyright © 2014 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.
Multidimensional Sexual Perfectionism and Female Sexual Function: A Longitudinal Investigation.
Stoeber, Joachim; Harvey, Laura N
2016-11-01
Research on multidimensional sexual perfectionism differentiates four forms: self-oriented, partner-oriented, partner-prescribed, and socially prescribed. Self-oriented sexual perfectionism reflects perfectionistic standards people apply to themselves as sexual partners; partner-oriented sexual perfectionism reflects perfectionistic standards people apply to their sexual partner; partner-prescribed sexual perfectionism reflects people's beliefs that their sexual partner imposes perfectionistic standards on them; and socially prescribed sexual perfectionism reflects people's beliefs that society imposes such standards on them. Previous studies found partner-prescribed and socially prescribed sexual perfectionism to be maladaptive forms of sexual perfectionism associated with a negative sexual self-concept and problematic sexual behaviors, but only examined cross-sectional relationships. The present article presents the first longitudinal study examining whether multidimensional sexual perfectionism predicts changes in sexual self-concept and sexual function over time. A total of 366 women aged 17-69 years completed measures of multidimensional sexual perfectionism, sexual esteem, sexual anxiety, sexual problem self-blame, and sexual function (cross-sectional data). Three to six months later, 164 of the women completed the same measures again (longitudinal data). Across analyses, partner-prescribed sexual perfectionism emerged as the most maladaptive form of sexual perfectionism. In the cross-sectional data, partner-prescribed sexual perfectionism showed positive relationships with sexual anxiety, sexual problem self-blame, and intercourse pain, and negative relationships with sexual esteem, desire, arousal, lubrication, and orgasmic function. In the longitudinal data, partner-prescribed sexual perfectionism predicted increases in sexual anxiety and decreases in sexual esteem, arousal, and lubrication over time. The findings suggest that partner-prescribed sexual
Swedish translation and linguistic validation of the multidimensional dyspnoea profile
Ekström, Magnus; Sundh, Josefin
2016-01-01
Background Dyspnoea, the feeling of breathing discomfort, consists of multiple dimensions that can vary in intensity, including the level of unpleasantness, qualities or descriptors of the sensation, emotional responses, and impact on function. No validated instrument for multidimensional measurement of dyspnoea is available in Swedish. The Multidimensional Dyspnea Profile (MDP) was recently developed to measure the unpleasantness, sensory qualities, and emotional responses of dyspnoea across diseases and settings. We aimed to take forward a Swedish version of the MDP. Methods Translation and linguistic validation of the MDP was conducted in collaboration with a specialised company in the field (Mapi, Lyon, France). The structured process involved forward and backward translations by two independent certified translators, input from an in-country linguistic consultant, the developers, and three respiratory physicians. Understandability and acceptability were evaluated through in-depth interviews with five patients with dyspnoea in accordance with international guidelines. Results and Conclusion A Swedish version of the MDP was obtained and linguistically validated. The MDP includes 11 rated items: the immediate unpleasantness of the sensation, the presence and intensity of five sensory qualities, and the intensity of five emotional responses to dyspnoea. The time period of measurement is specified by the user. The MDP is copyrighted by the developers but can be used free of charge in the context of non-funded academic research. Conclusion The MDP is the first instrument for measuring multiple dimensions of dyspnoea available in Swedish and should be validated across diseases and settings. Multidimensional measurement is essential for improved assessment and management of dyspnoea in research and clinical care. PMID:27834177
Column-coupling strategies for multidimensional electrophoretic separation techniques.
Kler, Pablo A; Sydes, Daniel; Huhn, Carolin
2015-01-01
Multidimensional electrophoretic separations represent one of the most common strategies for dealing with the analysis of complex samples. In recent years we have been witnessing the explosive growth of separation techniques for the analysis of complex samples in applications ranging from life sciences to industry. In this sense, electrophoretic separations offer several strategic advantages such as excellent separation efficiency, different methods with a broad range of separation mechanisms, and low liquid consumption generating less waste effluents and lower costs per analysis, among others. Despite their impressive separation efficiency, multidimensional electrophoretic separations present some drawbacks that have delayed their extensive use: the volumes of the columns, and consequently of the injected sample, are significantly smaller compared to other analytical techniques, thus the coupling interfaces between two separations components must be very efficient in terms of providing geometrical precision with low dead volume. Likewise, very sensitive detection systems are required. Additionally, in electrophoretic separation techniques, the surface properties of the columns play a fundamental role for electroosmosis as well as the unwanted adsorption of proteins or other complex biomolecules. In this sense the requirements for an efficient coupling for electrophoretic separation techniques involve several aspects related to microfluidics and physicochemical interactions of the electrolyte solutions and the solid capillary walls. It is interesting to see how these multidimensional electrophoretic separation techniques have been used jointly with different detection techniques, for intermediate detection as well as for final identification and quantification, particularly important in the case of mass spectrometry. In this work we present a critical review about the different strategies for coupling two or more electrophoretic separation techniques and the
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. Copyright © 2016 Elsevier B.V. All rights reserved.
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.
Examining Similarity Structure: Multidimensional Scaling and Related Approaches in Neuroimaging
Shinkareva, Svetlana V.; Wedell, Douglas H.
2013-01-01
This paper covers similarity analyses, a subset of multivariate pattern analysis techniques that are based on similarity spaces defined by multivariate patterns. These techniques offer several advantages and complement other methods for brain data analyses, as they allow for comparison of representational structure across individuals, brain regions, and data acquisition methods. Particular attention is paid to multidimensional scaling and related approaches that yield spatial representations or provide methods for characterizing individual differences. We highlight unique contributions of these methods by reviewing recent applications to functional magnetic resonance imaging data and emphasize areas of caution in applying and interpreting similarity analysis methods. PMID:23662162
Parallel receivers and sparse sampling in multidimensional NMR.
Kupče, Ēriks; Freeman, Ray
2011-12-01
The recent introduction of NMR spectrometers with multiple receivers permits spectra from several different nuclear species to be recorded in parallel, and several standard pulse sequences to be combined into a single entity. It is shown how these improvements in the flow and quality of spectral information can be significantly augmented by compressive sensing techniques--controlled aliasing, Hadamard spectroscopy, single-point evaluation of evolution space (SPEED), random sampling, projection-reconstruction, and hyperdimensional NMR. Future developments of these techniques are confidently expected to mitigate one of the most serious limitations in multidimensional NMR--the excessive duration of the measurements. Copyright Â© 2011 Elsevier Inc. All rights reserved.
A multi-dimensional sampling method for locating small scatterers
NASA Astrophysics Data System (ADS)
Song, Rencheng; Zhong, Yu; Chen, Xudong
2012-11-01
A multiple signal classification (MUSIC)-like multi-dimensional sampling method (MDSM) is introduced to locate small three-dimensional scatterers using electromagnetic waves. The indicator is built with the most stable part of signal subspace of the multi-static response matrix on a set of combinatorial sampling nodes inside the domain of interest. It has two main advantages compared to the conventional MUSIC methods. First, the MDSM is more robust against noise. Second, it can work with a single incidence even for multi-scatterers. Numerical simulations are presented to show the good performance of the proposed method.
Indexing of multidimensional lookup tables in embedded systems.
Vrhel, Michael J
2004-10-01
The proliferation of color devices and the desire to have them accurately communicate color information has led to a need for embedded systems that perform color conversions. A common method for performing color space conversions is to characterize the device with a multidimensional lookup table (MLUT). To reduce cost, many of the embedded systems have limited computational abilities. This leads to a need for the design of efficient methods for performing MLUT indexing and interpolation. This paper examines and compares two methods of MLUT indexing within embedded systems. The comparison is made in terms of colorimetric accuracy and computational cost.
Recent progress in multidimensional optical sensing and imaging systems (MOSIS)
NASA Astrophysics Data System (ADS)
Shen, Xin; Javidi, Bahram
2017-05-01
We present recent progress of the previously reported Multidimensional Optical Sensing and Imaging Systems (MOSIS) 2.0 for target recognition, material inspection and integrated visualization. The degrees of freedom of MOSIS 2.0 include three-dimensional (3D) imaging, polarimetric imaging and multispectral imaging. Each of these features provides unique information about a scene. 3D computationally reconstructed images mitigate the occlusion in front of the object, which can be used for 3D object recognition. The degree of polarization (DoP) of the light reflected from object surface is measured by 3D polarimetric imaging. Multispectral imaging is able to segment targets with specific spectral properties.
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.
Adaptive multidimensional modulation and multiplexing for next generation optical networks
NASA Astrophysics Data System (ADS)
Cvijetic, Milorad
2015-01-01
The overall spectral efficiency in optical transmission systems needs to be enhanced by employment of advanced modulation, multiplexing, and coding schemes, as well as the advanced detection techniques. In parallel, novel networking concepts with the griddles and elastic bandwidth allocation are needed to increase the network dynamics and flexibility. In this paper we discuss multidimensional modulation, multiplexing, and coding schemes, which are enablers not only of the information capacity increase, but also for the next generation elastic high-speed optical networking and outline possible future directions and application scenario in different networking segments.
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
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.
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.
Unobtrusive interferometer tracking by path length oscillation for multidimensional spectroscopy.
Lee, Kevin F; Bonvalet, Adeline; Nuernberger, Patrick; Joffre, Manuel
2009-07-20
We track the path difference between interferometer arms with few-nanometer accuracy without adding optics to the beam path. We measure the interference of a helium-neon beam that copropagates through the interferometer with midinfrared pulses used for multidimensional spectroscopy. This can indicate motion, but not direction. By oscillating the path length of one arm with a mirror on a piezoelectric stack and monitoring the oscillations of the recombined helium-neon beam, the direction can be calculated, and the path delay can be continuously tracked.
Multidimensional master equation and its Monte-Carlo simulation.
Pang, Juan; Bai, Zhan-Wu; Bao, Jing-Dong
2013-02-28
We derive an integral form of multidimensional master equation for a markovian process, in which the transition function is obtained in terms of a set of discrete Langevin equations. The solution of master equation, namely, the probability density function is calculated by using the Monte-Carlo composite sampling method. In comparison with the usual Langevin-trajectory simulation, the present approach decreases effectively coarse-grained error. We apply the master equation to investigate time-dependent barrier escape rate of a particle from a two-dimensional metastable potential and show the advantage of this approach in the calculations of quantities that depend on the probability density function.
Strong relaxation limit of multi-dimensional isentropic Euler equations
NASA Astrophysics Data System (ADS)
Xu, Jiang
2010-06-01
This paper is devoted to study the strong relaxation limit of multi-dimensional isentropic Euler equations with relaxation. Motivated by the Maxwell iteration, we generalize the analysis of Yong (SIAM J Appl Math 64:1737-1748, 2004) and show that, as the relaxation time tends to zero, the density of a certain scaled isentropic Euler equations with relaxation strongly converges towards the smooth solution to the porous medium equation in the framework of Besov spaces with relatively lower regularity. The main analysis tool used is the Littlewood-Paley decomposition.
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.
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.
NASA Astrophysics Data System (ADS)
Goree, J.; Ono, M.; Colestock, P.; Horton, R.; McNeill, D.; Park, H.
1985-07-01
Experiments on the fast wave in the range of high ion cyclotron harmonics in the ACT-1 device show that current drive is possible with the fast wave just as it is for the lower hybrid wave, except that it is suitable for higher plasma densities. A 140° loop antenna launched the high ion cyclotron harmonic fast wave [ω/Ω=O(10)] into a He+ plasma with ne≂4×1012 cm-3 and B=4.5 kG. Probe and magnetic loop diagnostics and FIR laser scattering confirmed the presence of the fast wave, and the Rogowski loop indicated that the circulating plasma current increased by up to 40A with 1 kW of coupled power, which is comparable to lower hybrid current drive in the same device with the same unidirectional fast electron beam used as the target for the rf. A phased antenna array would be used for FWCD in a tokamak without the E-beam.
Robustness of multidimensional Brownian ratchets as directed transport mechanisms
NASA Astrophysics Data System (ADS)
González-Candela, Ernesto; Romero-Rochín, Víctor; Del Río, Fernando
2011-08-01
Brownian ratchets have recently been considered as models to describe the ability of certain systems to locate very specific states in multidimensional configuration spaces. This directional process has particularly been proposed as an alternative explanation for the protein folding problem, in which the polypeptide is driven toward the native state by a multidimensional Brownian ratchet. Recognizing the relevance of robustness in biological systems, in this work we analyze such a property of Brownian ratchets by pushing to the limits all the properties considered essential to produce directed transport. Based on the results presented here, we can state that Brownian ratchets are able to deliver current and locate funnel structures under a wide range of conditions. As a result, they represent a simple model that solves the Levinthal's paradox with great robustness and flexibility and without requiring any ad hoc biased transition probability. The behavior of Brownian ratchets shown in this article considerably enhances the plausibility of the model for at least part of the structural mechanism behind protein folding process.
Multidimensional excitation pulses based on spatiotemporal encoding concepts
NASA Astrophysics Data System (ADS)
Dumez, Jean-Nicolas; Frydman, Lucio
2013-01-01
The understanding and control of spin dynamics play a fundamental role in modern NMR imaging, for devising new ways to monitor an object's density as well as for enabling the tailored excitation of spins in space. It has recently been shown that by relying on spatiotemporal encoding (SPEN), new forms of single-scan multidimensional NMR spectroscopy and imaging become feasible. The present study extends those imaging developments, by introducing a new class of multidimensional excitation pulses that relies on SPEN concepts. We focus in particular on a family of "hybrid" 2D radiofrequency (RF) pulses that operate in both direct and reciprocal excitation space, and which can spatially sculpt the spin magnetization in manners that are beyond the reach of sequential 1D pulse shaping. These SPEN-based 2D pulses are compatible with a majority of single- and multi-scan imaging techniques. Like the corresponding SPEN-based hybrid 2D acquisitions, these pulses can benefit from a high robustness against field inhomogeneities and/or offset effects that affect their k-space-based counterparts. These properties are analyzed, and illustrated with numerical simulations and model experiments.
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.
Manycore Performance-Portability: Kokkos Multidimensional Array Library
Edwards, H. Carter; Sunderland, Daniel; Porter, Vicki; ...
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