Frequency-Comb Based Double-Quantum Two-Dimensional Spectrum Identifies Collective Hyperfine Resonances in Atomic Vapor Induced by Dipole-Dipole Interactions

NASA Astrophysics Data System (ADS)

Lomsadze, Bachana; Cundiff, Steven T.

2018-06-01

Frequency-comb based multidimensional coherent spectroscopy is a novel optical method that enables high-resolution measurement in a short acquisition time. The method's resolution makes multidimensional coherent spectroscopy relevant for atomic systems that have narrow resonances. We use double-quantum multidimensional coherent spectroscopy to reveal collective hyperfine resonances in rubidium vapor at 100 °C induced by dipole-dipole interactions. We observe tilted and elongated line shapes in the double-quantum 2D spectra, which have never been reported for Doppler-broadened systems. The elongated line shapes suggest that the signal is predominately from the interacting atoms that have a near zero relative velocity.

Multidimensional chromatography in food analysis.

PubMed

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.

Spectral Analysis: From Additive Perspective to Multiplicative Perspective

NASA Astrophysics Data System (ADS)

Wu, Z.

2017-12-01

The early usage of trigonometric functions can be traced back to at least 17th century BC. It was Bhaskara II of the 12th century CE who first proved the mathematical equivalence between the sum of two trigonometric functions of any given angles and the product of two trigonometric functions of related angles, which has been taught these days in middle school classroom. The additive perspective of trigonometric functions led to the development of the Fourier transform that is used to express any functions as the sum of a set of trigonometric functions and opened a new mathematical field called harmonic analysis. Unfortunately, Fourier's sum cannot directly express nonlinear interactions between trigonometric components of different periods, and thereby lacking the capability of quantifying nonlinear interactions in dynamical systems. In this talk, the speaker will introduce the Huang transform and Holo-spectrum which were pioneered by Norden Huang and emphasizes the multiplicative perspective of trigonometric functions in expressing any function. Holo-spectrum is a multi-dimensional spectral expression of a time series that explicitly identifies the interactions among different scales and quantifies nonlinear interactions hidden in a time series. Along with this introduction, the developing concepts of physical, rather than mathematical, analysis of data will be explained. Various enlightening applications of Holo-spectrum analysis in atmospheric and climate studies will also be presented.

Beyond Fourier.

PubMed

Hoch, Jeffrey C

2017-10-01

Non-Fourier methods of spectrum analysis are gaining traction in NMR spectroscopy, driven by their utility for processing nonuniformly sampled data. These methods afford new opportunities for optimizing experiment time, resolution, and sensitivity of multidimensional NMR experiments, but they also pose significant challenges not encountered with the discrete Fourier transform. A brief history of non-Fourier methods in NMR serves to place different approaches in context. Non-Fourier methods reflect broader trends in the growing importance of computation in NMR, and offer insights for future software development. Copyright © 2017 Elsevier Inc. All rights reserved.

Raman and Autofluorescence Spectrum Dynamics along the HRG-Induced Differentiation Pathway of MCF-7 Cells

PubMed Central

Morita, Shin-ichi; Takanezawa, Sota; Hiroshima, Michio; Mitsui, Toshiyuki; Ozaki, Yukihiro; Sako, Yasushi

2014-01-01

Cellular differentiation proceeds along complicated pathways, even when it is induced by extracellular signaling molecules. One of the major reasons for this complexity is the highly multidimensional internal dynamics of cells, which sometimes causes apparently stochastic responses in individual cells to extracellular stimuli. Therefore, to understand cell differentiation, it is necessary to monitor the internal dynamics of cells at single-cell resolution. Here, we used a Raman and autofluorescence spectrum analysis of single cells to detect dynamic changes in intracellular molecular components. MCF-7 cells are a human cancer-derived cell line that can be induced to differentiate into mammary-gland-like cells with the addition of heregulin (HRG) to the culture medium. We measured the spectra in the cytoplasm of MCF-7 cells during 12 days of HRG stimulation. The Raman scattering spectrum, which was the major component of the signal, changed with time. A multicomponent analysis of the Raman spectrum revealed that the dynamics of the major components of the intracellular molecules, including proteins and lipids, changed cyclically along the differentiation pathway. The background autofluorescence signals of Raman scattering also provided information about the differentiation process. Using the total information from the Raman and autofluorescence spectra, we were able to visualize the pathway of cell differentiation in the multicomponent phase space. PMID:25418290

GenomeCAT: a versatile tool for the analysis and integrative visualization of DNA copy number variants.

PubMed

Tebel, Katrin; Boldt, Vivien; Steininger, Anne; Port, Matthias; Ebert, Grit; Ullmann, Reinhard

2017-01-06

The analysis of DNA copy number variants (CNV) has increasing impact in the field of genetic diagnostics and research. However, the interpretation of CNV data derived from high resolution array CGH or NGS platforms is complicated by the considerable variability of the human genome. Therefore, tools for multidimensional data analysis and comparison of patient cohorts are needed to assist in the discrimination of clinically relevant CNVs from others. We developed GenomeCAT, a standalone Java application for the analysis and integrative visualization of CNVs. GenomeCAT is composed of three modules dedicated to the inspection of single cases, comparative analysis of multidimensional data and group comparisons aiming at the identification of recurrent aberrations in patients sharing the same phenotype, respectively. Its flexible import options ease the comparative analysis of own results derived from microarray or NGS platforms with data from literature or public depositories. Multidimensional data obtained from different experiment types can be merged into a common data matrix to enable common visualization and analysis. All results are stored in the integrated MySQL database, but can also be exported as tab delimited files for further statistical calculations in external programs. GenomeCAT offers a broad spectrum of visualization and analysis tools that assist in the evaluation of CNVs in the context of other experiment data and annotations. The use of GenomeCAT does not require any specialized computer skills. The various R packages implemented for data analysis are fully integrated into GenomeCATs graphical user interface and the installation process is supported by a wizard. The flexibility in terms of data import and export in combination with the ability to create a common data matrix makes the program also well suited as an interface between genomic data from heterogeneous sources and external software tools. Due to the modular architecture the functionality of GenomeCAT can be easily extended by further R packages or customized plug-ins to meet future requirements.

Escher in color space: individual-differences multidimensional scaling of color dissimilarities collected with a gestalt formation task.

PubMed

Bimler, David; Kirkland, John; Pichler, Shaun

2004-02-01

The structure of color perception can be examined by collecting judgments about color dissimilarities. In the procedure used here, stimuli are presented three at a time on a computer monitor and the spontaneous grouping of most-similar stimuli into gestalts provides the dissimilarity comparisons. Analysis with multidimensional scaling allows such judgments to be pooled from a number of observers without obscuring the variations among them. The anomalous perceptions of color-deficient observers produce comparisons that are represented well by a geometric model of compressed individual color spaces, with different forms of deficiency distinguished by different directions of compression. The geometrical model is also capable of accommodating the normal spectrum of variation, so that there is greater variation in compression parameters between tests on normal subjects than in those between repeated tests on individual subjects. The method is sufficiently sensitive and the variations sufficiently large that they are not obscured by the use of a range of monitors, even under somewhat loosely controlled conditions.

Fast multi-dimensional NMR by minimal sampling

NASA Astrophysics Data System (ADS)

Kupče, Ēriks; Freeman, Ray

2008-03-01

A new scheme is proposed for very fast acquisition of three-dimensional NMR spectra based on minimal sampling, instead of the customary step-wise exploration of all of evolution space. The method relies on prior experiments to determine accurate values for the evolving frequencies and intensities from the two-dimensional 'first planes' recorded by setting t1 = 0 or t2 = 0. With this prior knowledge, the entire three-dimensional spectrum can be reconstructed by an additional measurement of the response at a single location (t1∗,t2∗) where t1∗ and t2∗ are fixed values of the evolution times. A key feature is the ability to resolve problems of overlap in the acquisition dimension. Applied to a small protein, agitoxin, the three-dimensional HNCO spectrum is obtained 35 times faster than systematic Cartesian sampling of the evolution domain. The extension to multi-dimensional spectroscopy is outlined.

The Use of Interactive Raster Graphics in the Display and Manipulation of Multidimensional Data

NASA Technical Reports Server (NTRS)

Anderson, D. C.

1981-01-01

Techniques for the review, display, and manipulation of multidimensional data are developed and described. Multidimensional data is meant in this context to describe scalar data associated with a three dimensional geometry or otherwise too complex to be well represented by traditional graphs. Raster graphics techniques are used to display a shaded image of a three dimensional geometry. The use of color to represent scalar data associated with the geometries in shaded images is explored. Distinct hues are associated with discrete data ranges, thus emulating the traditional representation of data with isarithms, or lines of constant numerical value. Data ranges are alternatively associated with a continuous spectrum of hues to show subtler data trends. The application of raster graphics techniques to the display of bivariate functions is explored.

Bayesian reconstruction of projection reconstruction NMR (PR-NMR).

PubMed

Yoon, Ji Won

2014-11-01

Projection reconstruction nuclear magnetic resonance (PR-NMR) is a technique for generating multidimensional NMR spectra. A small number of projections from lower-dimensional NMR spectra are used to reconstruct the multidimensional NMR spectra. In our previous work, it was shown that multidimensional NMR spectra are efficiently reconstructed using peak-by-peak based reversible jump Markov chain Monte Carlo (RJMCMC) algorithm. We propose an extended and generalized RJMCMC algorithm replacing a simple linear model with a linear mixed model to reconstruct close NMR spectra into true spectra. This statistical method generates samples in a Bayesian scheme. Our proposed algorithm is tested on a set of six projections derived from the three-dimensional 700 MHz HNCO spectrum of a protein HasA. Copyright © 2014 Elsevier Ltd. All rights reserved.

The interrelationship between orthorexia nervosa, perfectionism, body image and attachment style.

PubMed

Barnes, Marta A; Caltabiano, Marie L

2017-03-01

We investigated whether perfectionism, body image, attachment style, and self-esteem are predictors of orthorexia nervosa. A cohort of 220 participants completed a self-administered, online questionnaire consisting of five measures: ORTO-15, the Multidimensional Perfectionism Scale (MPS), the Multidimensional Body-Self Relations Questionnaire-Appearance Scale (MBSRQ-AS), the Relationship Scales Questionnaire (RSQ), and Rosenberg's Self-Esteem Scale (RSES). Correlation analysis revealed that higher orthorexic tendencies significantly correlated with higher scores for perfectionism (self-oriented, others-oriented and socially prescribed), appearance orientation, overweight preoccupation, self-classified weight, and fearful and dismissing attachment styles. Higher orthorexic tendencies also correlated with lower scores for body areas satisfaction and a secure attachment style. There was no significant correlation between orthorexia nervosa and self-esteem. Multiple linear regression analysis revealed that overweight preoccupation, appearance orientation and the presence of an eating disorder history were significant predictors of orthorexia nervosa with a history of an eating disorder being the strongest predictor. Orthorexia nervosa shares similarities with anorexia nervosa and bulimia nervosa with regards to perfectionism, body image attitudes, and attachment style. In addition, a history of an eating disorder strongly predicts orthorexia nervosa. These findings suggest that these disorders might be on the same spectrum of disordered eating.

Accessing Multi-Dimensional Images and Data Cubes in the Virtual Observatory

NASA Astrophysics Data System (ADS)

Tody, Douglas; Plante, R. L.; Berriman, G. B.; Cresitello-Dittmar, M.; Good, J.; Graham, M.; Greene, G.; Hanisch, R. J.; Jenness, T.; Lazio, J.; Norris, P.; Pevunova, O.; Rots, A. H.

2014-01-01

Telescopes across the spectrum are routinely producing multi-dimensional images and datasets, such as Doppler velocity cubes, polarization datasets, and time-resolved “movies.” Examples of current telescopes producing such multi-dimensional images include the JVLA, ALMA, and the IFU instruments on large optical and near-infrared wavelength telescopes. In the near future, both the LSST and JWST will also produce such multi-dimensional images routinely. High-energy instruments such as Chandra produce event datasets that are also a form of multi-dimensional data, in effect being a very sparse multi-dimensional image. Ensuring that the data sets produced by these telescopes can be both discovered and accessed by the community is essential and is part of the mission of the Virtual Observatory (VO). The Virtual Astronomical Observatory (VAO, http://www.usvao.org/), in conjunction with its international partners in the International Virtual Observatory Alliance (IVOA), has developed a protocol and an initial demonstration service designed for the publication, discovery, and access of arbitrarily large multi-dimensional images. The protocol describing multi-dimensional images is the Simple Image Access Protocol, version 2, which provides the minimal set of metadata required to characterize a multi-dimensional image for its discovery and access. A companion Image Data Model formally defines the semantics and structure of multi-dimensional images independently of how they are serialized, while providing capabilities such as support for sparse data that are essential to deal effectively with large cubes. A prototype data access service has been deployed and tested, using a suite of multi-dimensional images from a variety of telescopes. The prototype has demonstrated the capability to discover and remotely access multi-dimensional data via standard VO protocols. The prototype informs the specification of a protocol that will be submitted to the IVOA for approval, with an operational data cube service to be delivered in mid-2014. An associated user-installable VO data service framework will provide the capabilities required to publish VO-compatible multi-dimensional images or data cubes.

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.

Robust and transferable quantification of NMR spectral quality using IROC analysis

NASA Astrophysics Data System (ADS)

Zambrello, Matthew A.; Maciejewski, Mark W.; Schuyler, Adam D.; Weatherby, Gerard; Hoch, Jeffrey C.

2017-12-01

Non-Fourier methods are increasingly utilized in NMR spectroscopy because of their ability to handle nonuniformly-sampled data. However, non-Fourier methods present unique challenges due to their nonlinearity, which can produce nonrandom noise and render conventional metrics for spectral quality such as signal-to-noise ratio unreliable. The lack of robust and transferable metrics (i.e. applicable to methods exhibiting different nonlinearities) has hampered comparison of non-Fourier methods and nonuniform sampling schemes, preventing the identification of best practices. We describe a novel method, in situ receiver operating characteristic analysis (IROC), for characterizing spectral quality based on the Receiver Operating Characteristic curve. IROC utilizes synthetic signals added to empirical data as "ground truth", and provides several robust scalar-valued metrics for spectral quality. This approach avoids problems posed by nonlinear spectral estimates, and provides a versatile quantitative means of characterizing many aspects of spectral quality. We demonstrate applications to parameter optimization in Fourier and non-Fourier spectral estimation, critical comparison of different methods for spectrum analysis, and optimization of nonuniform sampling schemes. The approach will accelerate the discovery of optimal approaches to nonuniform sampling experiment design and non-Fourier spectrum analysis for multidimensional NMR.

Nonuniform sampling and non-Fourier signal processing methods in multidimensional NMR

PubMed Central

Mobli, Mehdi; Hoch, Jeffrey C.

2017-01-01

Beginning with the introduction of Fourier Transform NMR by Ernst and Anderson in 1966, time domain measurement of the impulse response (the free induction decay, FID) consisted of sampling the signal at a series of discrete intervals. For compatibility with the discrete Fourier transform (DFT), the intervals are kept uniform, and the Nyquist theorem dictates the largest value of the interval sufficient to avoid aliasing. With the proposal by Jeener of parametric sampling along an indirect time dimension, extension to multidimensional experiments employed the same sampling techniques used in one dimension, similarly subject to the Nyquist condition and suitable for processing via the discrete Fourier transform. The challenges of obtaining high-resolution spectral estimates from short data records using the DFT were already well understood, however. Despite techniques such as linear prediction extrapolation, the achievable resolution in the indirect dimensions is limited by practical constraints on measuring time. The advent of non-Fourier methods of spectrum analysis capable of processing nonuniformly sampled data has led to an explosion in the development of novel sampling strategies that avoid the limits on resolution and measurement time imposed by uniform sampling. The first part of this review discusses the many approaches to data sampling in multidimensional NMR, the second part highlights commonly used methods for signal processing of such data, and the review concludes with a discussion of other approaches to speeding up data acquisition in NMR. PMID:25456315

"Ersatz" and "hybrid" NMR spectral estimates using the filter diagonalization method.

PubMed

Ridge, Clark D; Shaka, A J

2009-03-12

The filter diagonalization method (FDM) is an efficient and elegant way to make a spectral estimate purely in terms of Lorentzian peaks. As NMR spectral peaks of liquids conform quite well to this model, the FDM spectral estimate can be accurate with far fewer time domain points than conventional discrete Fourier transform (DFT) processing. However, noise is not efficiently characterized by a finite number of Lorentzian peaks, or by any other analytical form, for that matter. As a result, noise can affect the FDM spectrum in different ways than it does the DFT spectrum, and the effect depends on the dimensionality of the spectrum. Regularization to suppress (or control) the influence of noise to give an "ersatz", or EFDM, spectrum is shown to sometimes miss weak features, prompting a more conservative implementation of filter diagonalization. The spectra obtained, called "hybrid" or HFDM spectra, are acquired by using regularized FDM to obtain an "infinite time" spectral estimate and then adding to it the difference between the DFT of the data and the finite time FDM estimate, over the same time interval. HFDM has a number of advantages compared to the EFDM spectra, where all features must be Lorentzian. They also show better resolution than DFT spectra. The HFDM spectrum is a reliable and robust way to try to extract more information from noisy, truncated data records and is less sensitive to the choice of regularization parameter. In multidimensional NMR of liquids, HFDM is a conservative way to handle the problems of noise, truncation, and spectral peaks that depart significantly from the model of a multidimensional Lorentzian peak.

Increasing Accuracy of Tissue Shear Modulus Reconstruction Using Ultrasonic Strain Tensor Measurement

NASA Astrophysics Data System (ADS)

Sumi, C.

Previously, we developed three displacement vector measurement methods, i.e., the multidimensional cross-spectrum phase gradient method (MCSPGM), the multidimensional autocorrelation method (MAM), and the multidimensional Doppler method (MDM). To increase the accuracies and stabilities of lateral and elevational displacement measurements, we also developed spatially variant, displacement component-dependent regularization. In particular, the regularization of only the lateral/elevational displacements is advantageous for the lateral unmodulated case. The demonstrated measurements of the displacement vector distributions in experiments using an inhomogeneous shear modulus agar phantom confirm that displacement-component-dependent regularization enables more stable shear modulus reconstruction. In this report, we also review our developed lateral modulation methods that use Parabolic functions, Hanning windows, and Gaussian functions in the apodization function and the optimized apodization function that realizes the designed point spread function (PSF). The modulations significantly increase the accuracy of the strain tensor measurement and shear modulus reconstruction (demonstrated using an agar phantom).

A Multi-Dimensional Functional Principal Components Analysis of EEG Data

PubMed Central

Hasenstab, Kyle; Scheffler, Aaron; Telesca, Donatello; Sugar, Catherine A.; Jeste, Shafali; DiStefano, Charlotte; Şentürk, Damla

2017-01-01

Summary The electroencephalography (EEG) data created in event-related potential (ERP) experiments have a complex high-dimensional structure. Each stimulus presentation, or trial, generates an ERP waveform which is an instance of functional data. The experiments are made up of sequences of multiple trials, resulting in longitudinal functional data and moreover, responses are recorded at multiple electrodes on the scalp, adding an electrode dimension. Traditional EEG analyses involve multiple simplifications of this structure to increase the signal-to-noise ratio, effectively collapsing the functional and longitudinal components by identifying key features of the ERPs and averaging them across trials. Motivated by an implicit learning paradigm used in autism research in which the functional, longitudinal and electrode components all have critical interpretations, we propose a multidimensional functional principal components analysis (MD-FPCA) technique which does not collapse any of the dimensions of the ERP data. The proposed decomposition is based on separation of the total variation into subject and subunit level variation which are further decomposed in a two-stage functional principal components analysis. The proposed methodology is shown to be useful for modeling longitudinal trends in the ERP functions, leading to novel insights into the learning patterns of children with Autism Spectrum Disorder (ASD) and their typically developing peers as well as comparisons between the two groups. Finite sample properties of MD-FPCA are further studied via extensive simulations. PMID:28072468

A multi-dimensional functional principal components analysis of EEG data.

PubMed

Hasenstab, Kyle; Scheffler, Aaron; Telesca, Donatello; Sugar, Catherine A; Jeste, Shafali; DiStefano, Charlotte; Şentürk, Damla

2017-09-01

The electroencephalography (EEG) data created in event-related potential (ERP) experiments have a complex high-dimensional structure. Each stimulus presentation, or trial, generates an ERP waveform which is an instance of functional data. The experiments are made up of sequences of multiple trials, resulting in longitudinal functional data and moreover, responses are recorded at multiple electrodes on the scalp, adding an electrode dimension. Traditional EEG analyses involve multiple simplifications of this structure to increase the signal-to-noise ratio, effectively collapsing the functional and longitudinal components by identifying key features of the ERPs and averaging them across trials. Motivated by an implicit learning paradigm used in autism research in which the functional, longitudinal, and electrode components all have critical interpretations, we propose a multidimensional functional principal components analysis (MD-FPCA) technique which does not collapse any of the dimensions of the ERP data. The proposed decomposition is based on separation of the total variation into subject and subunit level variation which are further decomposed in a two-stage functional principal components analysis. The proposed methodology is shown to be useful for modeling longitudinal trends in the ERP functions, leading to novel insights into the learning patterns of children with Autism Spectrum Disorder (ASD) and their typically developing peers as well as comparisons between the two groups. Finite sample properties of MD-FPCA are further studied via extensive simulations. © 2017, The International Biometric Society.

Young Friendship in HFASD and Typical Development: Friend versus Non-Friend Comparisons

ERIC Educational Resources Information Center

Bauminger-Zviely, Nirit; Agam-Ben-Artzi, Galit

2014-01-01

This study conducted comparative assessment of friendship in preschoolers with high-functioning autism spectrum disorder (HFASD, n = 29) versus preschoolers with typical development (n = 30), focusing on interactions with friends versus acquaintances. Groups were matched on SES, verbal/nonverbal MA, IQ, and CA. Multidimensional assessments…

Nonuniform sampling and non-Fourier signal processing methods in multidimensional NMR.

PubMed

Mobli, Mehdi; Hoch, Jeffrey C

2014-11-01

Beginning with the introduction of Fourier Transform NMR by Ernst and Anderson in 1966, time domain measurement of the impulse response (the free induction decay, FID) consisted of sampling the signal at a series of discrete intervals. For compatibility with the discrete Fourier transform (DFT), the intervals are kept uniform, and the Nyquist theorem dictates the largest value of the interval sufficient to avoid aliasing. With the proposal by Jeener of parametric sampling along an indirect time dimension, extension to multidimensional experiments employed the same sampling techniques used in one dimension, similarly subject to the Nyquist condition and suitable for processing via the discrete Fourier transform. The challenges of obtaining high-resolution spectral estimates from short data records using the DFT were already well understood, however. Despite techniques such as linear prediction extrapolation, the achievable resolution in the indirect dimensions is limited by practical constraints on measuring time. The advent of non-Fourier methods of spectrum analysis capable of processing nonuniformly sampled data has led to an explosion in the development of novel sampling strategies that avoid the limits on resolution and measurement time imposed by uniform sampling. The first part of this review discusses the many approaches to data sampling in multidimensional NMR, the second part highlights commonly used methods for signal processing of such data, and the review concludes with a discussion of other approaches to speeding up data acquisition in NMR. Copyright © 2014 Elsevier B.V. All rights reserved.

Deriving Multidimensional Poverty Indicators: Methodological Issues and an Empirical Analysis for Italy

ERIC Educational Resources Information Center

Coromaldi, Manuela; Zoli, Mariangela

2012-01-01

Theoretical and empirical studies have recently adopted a multidimensional concept of poverty. There is considerable debate about the most appropriate degree of multidimensionality to retain in the analysis. In this work we add to the received literature in two ways. First, we derive indicators of multiple deprivation by applying a particular…

Results on the energy dependence of cosmic-ray charge composition

NASA Technical Reports Server (NTRS)

Balasubrahmanyan, V. K.; Ormes, J. F.

1973-01-01

Results of measurements by a balloon-borne ionization spectrometer of the energy dependence of high-energy cosmic-ray charge composition. The results presented are greatly improved over those obtained earlier by Ormes et al. (1971) by the use of a multidimensional charge analysis with more efficient background rejection, and a more accurate energy determination. Complex couplings between the charge, energy, and trajectory information were taken into account and are discussed. The spectra of individual elements up to oxygen and of groups of nuclei up through iron were measured up to almost 100 GeV per nucleon. The energy spectrum of the secondary nuclei, B + N, is found to be steeper than that of the primary nuclei, C + O, in agreement with Smith et al. (1973). The most dramatic finding is that the spectrum of the iron nuclei is flatter than that of the carbon and oxygen nuclei by 0.57 plus or minus 0.14 of a power.

Instanton and noninstanton tunneling in periodically perturbed barriers: semiclassical and quantum interpretations.

PubMed

Takahashi, Kin'ya; Ikeda, Kensuke S

2012-11-01

In multidimensional barrier tunneling, there exist two different types of tunneling mechanisms, instanton-type tunneling and noninstanton tunneling. In this paper we investigate transitions between the two tunneling mechanisms from the semiclassical and quantum viewpoints taking two simple models: a periodically perturbed Eckart barrier for the semiclassical analysis and a periodically perturbed rectangular barrier for the quantum analysis. As a result, similar transitions are observed with change of the perturbation frequency ω for both systems, and we obtain a comprehensive scenario from both semiclassical and quantum viewpoints for them. In the middle range of ω, in which the plateau spectrum is observed, noninstanton tunneling dominates the tunneling process, and the tunneling amplitude takes the maximum value. Noninstanton tunneling explained by stable-unstable manifold guided tunneling (SUMGT) from the semiclassical viewpoint is interpreted as multiphoton-assisted tunneling from the quantum viewpoint. However, in the limit ω→0, instanton-type tunneling takes the place of noninstanton tunneling, and the tunneling amplitude converges on a constant value depending on the perturbation strength. The spectrum localized around the input energy is observed, and there is a scaling law with respect to the width of the spectrum envelope, i.e., the width ∝ℏω. In the limit ω→∞, the tunneling amplitude converges on that of the unperturbed system, i.e., the instanton of the unperturbed system.

A dynamic nuclear polarization strategy for multi-dimensional Earth's field NMR spectroscopy.

PubMed

Halse, Meghan E; Callaghan, Paul T

2008-12-01

Dynamic nuclear polarization (DNP) is introduced as a powerful tool for polarization enhancement in multi-dimensional Earth's field NMR spectroscopy. Maximum polarization enhancements, relative to thermal equilibrium in the Earth's magnetic field, are calculated theoretically and compared to the more traditional prepolarization approach for NMR sensitivity enhancement at ultra-low fields. Signal enhancement factors on the order of 3000 are demonstrated experimentally using DNP with a nitroxide free radical, TEMPO, which contains an unpaired electron which is strongly coupled to a neighboring (14)N nucleus via the hyperfine interaction. A high-quality 2D (19)F-(1)H COSY spectrum acquired in the Earth's magnetic field with DNP enhancement is presented and compared to simulation.

Evaluating the Invariance of Cognitive Profile Patterns Derived from Profile Analysis via Multidimensional Scaling (PAMS): A Bootstrapping Approach

ERIC Educational Resources Information Center

Kim, Se-Kang

2010-01-01

The aim of the current study is to validate the invariance of major profile patterns derived from multidimensional scaling (MDS) by bootstrapping. Profile Analysis via Multidimensional Scaling (PAMS) was employed to obtain profiles and bootstrapping was used to construct the sampling distributions of the profile coordinates and the empirical…

Applications of wavelet-based compression to multidimensional Earth science data

NASA Technical Reports Server (NTRS)

Bradley, Jonathan N.; Brislawn, Christopher M.

1993-01-01

A data compression algorithm involving vector quantization (VQ) and the discrete wavelet transform (DWT) is applied to two different types of multidimensional digital earth-science data. The algorithms (WVQ) is optimized for each particular application through an optimization procedure that assigns VQ parameters to the wavelet transform subbands subject to constraints on compression ratio and encoding complexity. Preliminary results of compressing global ocean model data generated on a Thinking Machines CM-200 supercomputer are presented. The WVQ scheme is used in both a predictive and nonpredictive mode. Parameters generated by the optimization algorithm are reported, as are signal-to-noise (SNR) measurements of actual quantized data. The problem of extrapolating hydrodynamic variables across the continental landmasses in order to compute the DWT on a rectangular grid is discussed. Results are also presented for compressing Landsat TM 7-band data using the WVQ scheme. The formulation of the optimization problem is presented along with SNR measurements of actual quantized data. Postprocessing applications are considered in which the seven spectral bands are clustered into 256 clusters using a k-means algorithm and analyzed using the Los Alamos multispectral data analysis program, SPECTRUM, both before and after being compressed using the WVQ program.

Understanding International GNC Hardware Trends

NASA Technical Reports Server (NTRS)

Greenbaum, Adam; Brady, Tye; Dennehy, Cornelius; Airey, Stephen P.; Roelke, Evan; Judd, Samuel Brady

2015-01-01

An industry-wide survey of guidance, navigation and control (GNC) sensors, namely star trackers, gyros, and sun sensors was undertaken in 2014, in which size, mass, power, and various performance metrics were recorded for each category. A multidimensional analysis was performed, looking at the spectrum of available sensors, with the intent of identifying gaps in the available capability range. Mission types that are not currently well served by the available components were discussed, as well as some missions that would be enabled by filling gaps in the component space. This paper continues that study, with a focus on reaction wheels and magnetometers, as well as with updates to the listings of star trackers, gyros, and sun sensors. Also discussed are a framework for making the database available to the community at large, and the continued maintenance of this database and the analysis of its contents.

Multidimensional Recurrence Quantification Analysis (MdRQA) for the Analysis of Multidimensional Time-Series: A Software Implementation in MATLAB and Its Application to Group-Level Data in Joint Action

PubMed Central

Wallot, Sebastian; Roepstorff, Andreas; Mønster, Dan

2016-01-01

We introduce Multidimensional Recurrence Quantification Analysis (MdRQA) as a tool to analyze multidimensional time-series data. We show how MdRQA can be used to capture the dynamics of high-dimensional signals, and how MdRQA can be used to assess coupling between two or more variables. In particular, we describe applications of the method in research on joint and collective action, as it provides a coherent analysis framework to systematically investigate dynamics at different group levels—from individual dynamics, to dyadic dynamics, up to global group-level of arbitrary size. The Appendix in Supplementary Material contains a software implementation in MATLAB to calculate MdRQA measures. PMID:27920748

Multidimensional Recurrence Quantification Analysis (MdRQA) for the Analysis of Multidimensional Time-Series: A Software Implementation in MATLAB and Its Application to Group-Level Data in Joint Action.

PubMed

Wallot, Sebastian; Roepstorff, Andreas; Mønster, Dan

2016-01-01

We introduce Multidimensional Recurrence Quantification Analysis (MdRQA) as a tool to analyze multidimensional time-series data. We show how MdRQA can be used to capture the dynamics of high-dimensional signals, and how MdRQA can be used to assess coupling between two or more variables. In particular, we describe applications of the method in research on joint and collective action, as it provides a coherent analysis framework to systematically investigate dynamics at different group levels-from individual dynamics, to dyadic dynamics, up to global group-level of arbitrary size. The Appendix in Supplementary Material contains a software implementation in MATLAB to calculate MdRQA measures.

Visual modeling in an analysis of multidimensional data

NASA Astrophysics Data System (ADS)

Zakharova, A. A.; Vekhter, E. V.; Shklyar, A. V.; Pak, A. J.

2018-01-01

The article proposes an approach to solve visualization problems and the subsequent analysis of multidimensional data. Requirements to the properties of visual models, which were created to solve analysis problems, are described. As a perspective direction for the development of visual analysis tools for multidimensional and voluminous data, there was suggested an active use of factors of subjective perception and dynamic visualization. Practical results of solving the problem of multidimensional data analysis are shown using the example of a visual model of empirical data on the current state of studying processes of obtaining silicon carbide by an electric arc method. There are several results of solving this problem. At first, an idea of possibilities of determining the strategy for the development of the domain, secondly, the reliability of the published data on this subject, and changes in the areas of attention of researchers over time.

A novel multidimensional protein identification technology approach combining protein size exclusion prefractionation, peptide zwitterion-ion hydrophilic interaction chromatography, and nano-ultraperformance RP chromatography/nESI-MS2 for the in-depth analysis of the serum proteome and phosphoproteome: application to clinical sera derived from humans with benign prostate hyperplasia.

PubMed

Garbis, Spiros D; Roumeliotis, Theodoros I; Tyritzis, Stavros I; Zorpas, Kostas M; Pavlakis, Kitty; Constantinides, Constantinos A

2011-02-01

The current proof-of-principle study was aimed toward development of a novel multidimensional protein identification technology (MudPIT) approach for the in-depth proteome analysis of human serum derived from patients with benign prostate hyperplasia (BPH) using rational chromatographic design principles. This study constituted an extension of our published work relating to the identification and relative quantification of potential clinical biomarkers in BPH and prostate cancer (PCa) tissue specimens. The proposed MudPIT approach encompassed the use of three distinct yet complementary liquid chromatographic chemistries. High-pressure size-exclusion chromatography (SEC) was used for the prefractionation of serum proteins followed by their dialysis exchange and solution phase trypsin proteolysis. The tryptic peptides were then subjected to offline zwitterion-ion hydrophilic interaction chromatography (ZIC-HILIC) fractionation followed by their online analysis with reversed-phase nano-ultraperformance chromatography (RP-nUPLC) hyphenated to nanoelectrospray ionization-tandem mass spectrometry using an ion trap mass analyzer. For the spectral processing, the sequential use of the SpectrumMill, Scaffold, and InsPecT software tools was applied for the tryptic peptide product ion MS(2) spectral processing, false discovery rate (FDR) assessment, validation, and protein identification. This milestone serum analysis study allowed the confident identification of over 1955 proteins (p ≤ 0.05; FDR ≤ 5%) with a broad spectrum of biological and physicochemical properties including secreted, tissue-specific proteins spanning approximately 12 orders of magnitude as they occur in their native abundance levels in the serum matrix. Also encompassed in this proteome was the confident identification of 375 phosphoproteins (p ≤ 0.05; FDR ≤ 5%) with potential importance to cancer biology. To demonstrate the performance characteristics of this novel MudPIT approach, a comparison was made with the proteomes resulting from the immunodepletion of the high abundant albumin and IgG proteins with offline first dimensional tryptic peptide separation with both ZIC-HILIC and strong cation exchange (SCX) chromatography and their subsequent online RP-nUPLC-nESI-MS(2) analysis.

Phase-sensitive spectral estimation by the hybrid filter diagonalization method.

PubMed

Celik, Hasan; Ridge, Clark D; Shaka, A J

2012-01-01

A more robust way to obtain a high-resolution multidimensional NMR spectrum from limited data sets is described. The Filter Diagonalization Method (FDM) is used to analyze phase-modulated data and cast the spectrum in terms of phase-sensitive Lorentzian "phase-twist" peaks. These spectra are then used to obtain absorption-mode phase-sensitive spectra. In contrast to earlier implementations of multidimensional FDM, the absolute phase of the data need not be known beforehand, and linear phase corrections in each frequency dimension are possible, if they are required. Regularization is employed to improve the conditioning of the linear algebra problems that must be solved to obtain the spectral estimate. While regularization smoothes away noise and small peaks, a hybrid method allows the true noise floor to be correctly represented in the final result. Line shape transformation to a Gaussian-like shape improves the clarity of the spectra, and is achieved by a conventional Lorentzian-to-Gaussian transformation in the time-domain, after inverse Fourier transformation of the FDM spectra. The results obtained highlight the danger of not using proper phase-sensitive line shapes in the spectral estimate. The advantages of the new method for the spectral estimate are the following: (i) the spectrum can be phased by conventional means after it is obtained; (ii) there is a true and accurate noise floor; and (iii) there is some indication of the quality of fit in each local region of the spectrum. The method is illustrated with 2D NMR data for the first time, but is applicable to n-dimensional data without any restriction on the number of time/frequency dimensions. Copyright © 2011. Published by Elsevier Inc.

Family Quality of Life and Psychological Well-Being in Parents of Children with Autism Spectrum Disorders: A Double ABCX Model

ERIC Educational Resources Information Center

Pozo, P.; Sarriá, E.; Brioso, A.

2014-01-01

Background: This study examined family quality of life (FQOL) and psychological well-being from a multidimensional perspective. The proposed model was based on the double ABCX model, with severity of the disorder, behaviour problems, social support, sense of coherence (SOC) and coping strategies as components. Method: One hundred and eighteen…

Children with autism and their friends: a multidimensional study of friendship in high-functioning autism spectrum disorder.

PubMed

Bauminger, Nirit; Solomon, Marjorie; Aviezer, Anat; Heung, Kelly; Gazit, Lilach; Brown, John; Rogers, Sally J

2008-02-01

This study of Israeli and American preadolescent children examined characteristics of friendship in 44 children with high-functioning autism spectrum disorder (HFASD) compared to 38 typically developing children (TYP), as they interacted with a close friend Participants were 8-12 years of age (HFASD: Israel, n = 24; USA, n = 20; TYP: Israel, n = 23; USA, n = 15), and were matched on SES, receptive language vocabulary, child age, and gender (each study group included one girl). Multidimensional assessments included: individual behaviors of target children and observed child-friend interactions during construction and drawing scenarios; target child's and friend's self-perceived mutual friendship qualities; and mother-reported characteristics (friendship's duration/frequency; friend's age/gender/disability status). Overall, children with HFASD displayed a number of differences on individual and dyadic friendship measures. Both age and verbal abilities affected friendship behaviors. Children with HFASD and their friends perceived friendship qualities similarly, suggesting that preadolescents with HFASD have capacities for interpersonal awareness. Between-group similarities also emerged on several complex social behaviors, suggesting that friendship follows a developmental trajectory in autism and may enhance social interaction skills in autism.

Practical aspects of NMR signal assignment in larger and challenging proteins

PubMed Central

Frueh, Dominique P.

2014-01-01

NMR has matured into a technique routinely employed for studying proteins in near physiological conditions. However, applications to larger proteins are impeded by the complexity of the various correlation maps necessary to assign NMR signals. This article reviews the data analysis techniques traditionally employed for resonance assignment and describes alternative protocols necessary for overcoming challenges in large protein spectra. In particular, simultaneous analysis of multiple spectra may help overcome ambiguities or may reveal correlations in an indirect manner. Similarly, visualization of orthogonal planes in a multidimensional spectrum can provide alternative assignment procedures. We describe examples of such strategies for assignment of backbone, methyl, and nOe resonances. We describe experimental aspects of data acquisition for the related experiments and provide guidelines for preliminary studies. Focus is placed on large folded monomeric proteins and examples are provided for 37, 48, 53, and 81 kDa proteins. PMID:24534088

Controlling specific locomotor behaviors through multidimensional monoaminergic modulation of spinal circuitries

PubMed Central

Musienko, Pavel; van den Brand, Rubia; Märzendorfer, Olivia; Roy, Roland R.; Gerasimenko, Yury; Edgerton, V. Reggie; Courtine, Grégoire

2012-01-01

Descending monoaminergic inputs markedly influence spinal locomotor circuits, but the functional relationships between specific receptors and the control of walking behavior remain poorly understood. To identify these interactions, we manipulated serotonergic, dopaminergic, and noradrenergic neural pathways pharmacologically during locomotion enabled by electrical spinal cord stimulation in adult spinal rats in vivo. Using advanced neurobiomechanical recordings and multidimensional statistical procedures, we reveal that each monoaminergic receptor modulates a broad but distinct spectrum of kinematic, kinetic and EMG characteristics, which we expressed into receptor–specific functional maps. We then exploited this catalogue of monoaminergic tuning functions to devise optimal pharmacological combinations to encourage locomotion in paralyzed rats. We found that, in most cases, receptor-specific modulatory influences summed near algebraically when stimulating multiple pathways concurrently. Capitalizing on these predictive interactions, we elaborated a multidimensional monoaminergic intervention that restored coordinated hindlimb locomotion with normal levels of weight bearing and partial equilibrium maintenance in spinal rats. These findings provide new perspectives on the functions of and interactions between spinal monoaminergic receptor systems in producing stepping, and define a framework to tailor pharmacotherapies for improving neurological functions after CNS disorders. PMID:21697376

DEVELOPMENT AND PSYCHOMETRIC TESTING OF A MULTIDIMENSIONAL INSTRUMENT OF PERCEIVED DISCRIMINATION AMONG AFRICAN AMERICANS IN THE JACKSON HEART STUDY

PubMed Central

Sims, Mario; Wyatt, Sharon B.; Gutierrez, Mary Lou; Taylor, Herman A.; Williams, David R.

2009-01-01

Objective Assessing the discrimination-health disparities hypothesis requires psychometrically sound, multidimensional measures of discrimination. Among the available discrimination measures, few are multidimensional and none have adequate psychometric testing in a large, African American sample. We report the development and psychometric testing of the multidimensional Jackson Heart Study Discrimination (JHSDIS) Instrument. Methods A multidimensional measure assessing the occurrence, frequency, attribution, and coping responses to perceived everyday and lifetime discrimination; lifetime burden of discrimination; and effect of skin color was developed and tested in the 5302-member cohort of the Jackson Heart Study. Internal consistency was calculated by using Cronbach α. coefficient. Confirmatory factor analysis established the dimensions, and intercorrelation coefficients assessed the discriminant validity of the instrument. Setting Tri-county area of the Jackson, MS metropolitan statistical area. Results The JHSDIS was psychometrically sound (overall α=.78, .84 and .77, respectively, for the everyday and lifetime subscales). Confirmatory factor analysis yielded 11 factors, which confirmed the a priori dimensions represented. Conclusions The JHSDIS combined three scales into a single multidimensional instrument with good psychometric properties in a large sample of African Americans. This analysis lays the foundation for using this instrument in research that will examine the association between perceived discrimination and CVD among African Americans. PMID:19341164

Wavelet analysis methods for radiography of multidimensional growth of planar mixing layers

DOE PAGES

Merritt, Elizabeth Catherine; Doss, Forrest William

2016-07-06

The counter-propagating shear campaign is examining instability growth and its transition to turbulence in the high-energy-density physics regime using a laser-driven counter-propagating flow platform. In these experiments, we observe consistent complex break-up of and structure growth in a tracer layer placed at the shear flow interface during the instability growth phase. We present a wavelet-transform based analysis technique capable of characterizing the scale- and directionality-resolved average intensity perturbations in static radiographs of the experiment. This technique uses the complete spatial information available in each radiograph to describe the structure evolution. We designed this analysis technique to generate a two-dimensional powermore » spectrum for each radiograph from which we can recover information about structure widths, amplitudes, and orientations. Lastly, the evolution of the distribution of power in the spectra for an experimental series is a potential metric for quantifying the structure size evolution as well as a system’s evolution towards isotropy.« less

Wavelet analysis methods for radiography of multidimensional growth of planar mixing layers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Merritt, E. C., E-mail: emerritt@lanl.gov; Doss, F. W.

2016-07-15

The counter-propagating shear campaign is examining instability growth and its transition to turbulence in the high-energy-density physics regime using a laser-driven counter-propagating flow platform. In these experiments, we observe consistent complex break-up of and structure growth in a tracer layer placed at the shear flow interface during the instability growth phase. We present a wavelet-transform based analysis technique capable of characterizing the scale- and directionality-resolved average intensity perturbations in static radiographs of the experiment. This technique uses the complete spatial information available in each radiograph to describe the structure evolution. We designed this analysis technique to generate a two-dimensional powermore » spectrum for each radiograph from which we can recover information about structure widths, amplitudes, and orientations. The evolution of the distribution of power in the spectra for an experimental series is a potential metric for quantifying the structure size evolution as well as a system’s evolution towards isotropy.« less

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…

ANALYSIS OF TRACE-LEVEL ORGANIC COMBUSTION PROCESS EMISSIONS USING NOVEL MULTIDIMENSIONAL GAS CHROMATOGRAPHY-MASS SPECTROMETRY PROCEDURES

EPA Science Inventory

The paper discusses the analysis of trace-level organic combustion process emissions using novel multidimensional gas chromatography-mass spectrometry (MDGC-MS) procedures. It outlines the application of the technique through the analyses of various incinerator effluent and produ...

Attosecond twin-pulse control by generalized kinetic heterodyne mixing.

PubMed

Raith, Philipp; Ott, Christian; Pfeifer, Thomas

2011-01-15

Attosecond double-pulse (twin-pulse) production in high-order harmonic generation is manipulated by a combination of two-color and carrier-envelope phase-control methods. As we show in numerical simulations, both relative amplitude and phase of the double pulse can be independently set by making use of multidimensional parameter control. Two technical implementation routes are discussed: kinetic heterodyning using second-harmonic generation and split-spectrum phase-step control.

Peak picking multidimensional NMR spectra with the contour geometry based algorithm CYPICK.

PubMed

Würz, Julia M; Güntert, Peter

2017-01-01

The automated identification of signals in multidimensional NMR spectra is a challenging task, complicated by signal overlap, noise, and spectral artifacts, for which no universally accepted method is available. Here, we present a new peak picking algorithm, CYPICK, that follows, as far as possible, the manual approach taken by a spectroscopist who analyzes peak patterns in contour plots of the spectrum, but is fully automated. Human visual inspection is replaced by the evaluation of geometric criteria applied to contour lines, such as local extremality, approximate circularity (after appropriate scaling of the spectrum axes), and convexity. The performance of CYPICK was evaluated for a variety of spectra from different proteins by systematic comparison with peak lists obtained by other, manual or automated, peak picking methods, as well as by analyzing the results of automated chemical shift assignment and structure calculation based on input peak lists from CYPICK. The results show that CYPICK yielded peak lists that compare in most cases favorably to those obtained by other automated peak pickers with respect to the criteria of finding a maximal number of real signals, a minimal number of artifact peaks, and maximal correctness of the chemical shift assignments and the three-dimensional structure obtained by fully automated assignment and structure calculation.

Iteration and superposition encryption scheme for image sequences based on multi-dimensional keys

NASA Astrophysics Data System (ADS)

Han, Chao; Shen, Yuzhen; Ma, Wenlin

2017-12-01

An iteration and superposition encryption scheme for image sequences based on multi-dimensional keys is proposed for high security, big capacity and low noise information transmission. Multiple images to be encrypted are transformed into phase-only images with the iterative algorithm and then are encrypted by different random phase, respectively. The encrypted phase-only images are performed by inverse Fourier transform, respectively, thus new object functions are generated. The new functions are located in different blocks and padded zero for a sparse distribution, then they propagate to a specific region at different distances by angular spectrum diffraction, respectively and are superposed in order to form a single image. The single image is multiplied with a random phase in the frequency domain and then the phase part of the frequency spectrums is truncated and the amplitude information is reserved. The random phase, propagation distances, truncated phase information in frequency domain are employed as multiple dimensional keys. The iteration processing and sparse distribution greatly reduce the crosstalk among the multiple encryption images. The superposition of image sequences greatly improves the capacity of encrypted information. Several numerical experiments based on a designed optical system demonstrate that the proposed scheme can enhance encrypted information capacity and make image transmission at a highly desired security level.

Simultaneous Classification and Multidimensional Scaling with External Information

ERIC Educational Resources Information Center

Kiers, Henk A. L.; Vicari, Donatella; Vichi, Maurizio

2005-01-01

For the exploratory analysis of a matrix of proximities or (dis)similarities between objects, one often uses cluster analysis (CA) or multidimensional scaling (MDS). Solutions resulting from such analyses are sometimes interpreted using external information on the objects. Usually the procedures of CA, MDS and using external information are…

A Canonical Correlation Analysis of the Influence of Social Comparison, Gender, and Grade Level on the Multidimensional Self-Concepts of Gifted Adolescents

ERIC Educational Resources Information Center

Rinn, Anne N.; Jamieson, Kelly M.; Gross, Candace M.; McQueen, Kand S.

2009-01-01

This study examines the effects of social comparison, gender, and grade level on gifted adolescents' multidimensional self-concept. Participants include 248 gifted adolescents who had completed the sixth through tenth grade during the previous academic year. Multidimensional self-concept was measured using the Self Description Questionnaire II…

Multi-dimensional PIC-simulations of parametric instabilities for shock-ignition conditions

NASA Astrophysics Data System (ADS)

Riconda, C.; Weber, S.; Klimo, O.; Héron, A.; Tikhonchuk, V. T.

2013-11-01

Laser-plasma interaction is investigated for conditions relevant for the shock-ignition (SI) scheme of inertial confinement fusion using two-dimensional particle-in-cell (PIC) simulations of an intense laser beam propagating in a hot, large-scale, non-uniform plasma. The temporal evolution and interdependence of Raman- (SRS), and Brillouin- (SBS), side/backscattering as well as Two-Plasmon-Decay (TPD) are studied. TPD is developing in concomitance with SRS creating a broad spectrum of plasma waves near the quarter-critical density. They are rapidly saturated due to plasma cavitation within a few picoseconds. The hot electron spectrum created by SRS and TPD is relatively soft, limited to energies below one hundred keV.

Multidimensional infrared spectroscopy reveals the vibrational and solvation dynamics of isoniazid

NASA Astrophysics Data System (ADS)

Shaw, Daniel J.; Adamczyk, Katrin; Frederix, Pim W. J. M.; Simpson, Niall; Robb, Kirsty; Greetham, Gregory M.; Towrie, Michael; Parker, Anthony W.; Hoskisson, Paul A.; Hunt, Neil T.

2015-06-01

The results of infrared spectroscopic investigations into the band assignments, vibrational relaxation, and solvation dynamics of the common anti-tuberculosis treatment Isoniazid (INH) are reported. INH is known to inhibit InhA, a 2-trans-enoyl-acyl carrier protein reductase enzyme responsible for the maintenance of cell walls in Mycobacterium tuberculosis but as new drug-resistant strains of the bacterium appear, next-generation therapeutics will be essential to combat the rise of the disease. Small molecules such as INH offer the potential for use as a biomolecular marker through which ultrafast multidimensional spectroscopies can probe drug binding and so inform design strategies but a complete characterization of the spectroscopy and dynamics of INH in solution is required to inform such activity. Infrared absorption spectroscopy, in combination with density functional theory calculations, is used to assign the vibrational modes of INH in the 1400-1700 cm-1 region of the infrared spectrum while ultrafast multidimensional spectroscopy measurements determine the vibrational relaxation dynamics and the effects of solvation via spectral diffusion of the carbonyl stretching vibrational mode. These results are discussed in the context of previous linear spectroscopy studies on solid-phase INH and its usefulness as a biomolecular probe.

Multidimensional scaling analysis of financial time series based on modified cross-sample entropy methods

NASA Astrophysics Data System (ADS)

He, Jiayi; Shang, Pengjian; Xiong, Hui

2018-06-01

Stocks, as the concrete manifestation of financial time series with plenty of potential information, are often used in the study of financial time series. In this paper, we utilize the stock data to recognize their patterns through out the dissimilarity matrix based on modified cross-sample entropy, then three-dimensional perceptual maps of the results are provided through multidimensional scaling method. Two modified multidimensional scaling methods are proposed in this paper, that is, multidimensional scaling based on Kronecker-delta cross-sample entropy (MDS-KCSE) and multidimensional scaling based on permutation cross-sample entropy (MDS-PCSE). These two methods use Kronecker-delta based cross-sample entropy and permutation based cross-sample entropy to replace the distance or dissimilarity measurement in classical multidimensional scaling (MDS). Multidimensional scaling based on Chebyshev distance (MDSC) is employed to provide a reference for comparisons. Our analysis reveals a clear clustering both in synthetic data and 18 indices from diverse stock markets. It implies that time series generated by the same model are easier to have similar irregularity than others, and the difference in the stock index, which is caused by the country or region and the different financial policies, can reflect the irregularity in the data. In the synthetic data experiments, not only the time series generated by different models can be distinguished, the one generated under different parameters of the same model can also be detected. In the financial data experiment, the stock indices are clearly divided into five groups. Through analysis, we find that they correspond to five regions, respectively, that is, Europe, North America, South America, Asian-Pacific (with the exception of mainland China), mainland China and Russia. The results also demonstrate that MDS-KCSE and MDS-PCSE provide more effective divisions in experiments than MDSC.

Multidimensional Framework for the Analysis of Innovations at Universities in Catalonia

ERIC Educational Resources Information Center

Tomas, Marina; Castro, Diego

2011-01-01

The purpose of this paper is to contribute to a better understanding of the nature of change processes and dynamics at Catalan universities. A multidimensional approach was adopted to examine the change processes and to analyse organizational innovation in higher education. The paper draws involved in each particular innovation. Analysis of these…

Multidimensional Riemann problem with self-similar internal structure - part III - a multidimensional analogue of the HLLI Riemann solver for conservative hyperbolic systems

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.

Multi-dimensional super-resolution imaging enables surface hydrophobicity mapping

NASA Astrophysics Data System (ADS)

Bongiovanni, Marie N.; Godet, Julien; Horrocks, Mathew H.; Tosatto, Laura; Carr, Alexander R.; Wirthensohn, David C.; Ranasinghe, Rohan T.; Lee, Ji-Eun; Ponjavic, Aleks; Fritz, Joelle V.; Dobson, Christopher M.; Klenerman, David; Lee, Steven F.

2016-12-01

Super-resolution microscopy allows biological systems to be studied at the nanoscale, but has been restricted to providing only positional information. Here, we show that it is possible to perform multi-dimensional super-resolution imaging to determine both the position and the environmental properties of single-molecule fluorescent emitters. The method presented here exploits the solvatochromic and fluorogenic properties of nile red to extract both the emission spectrum and the position of each dye molecule simultaneously enabling mapping of the hydrophobicity of biological structures. We validated this by studying synthetic lipid vesicles of known composition. We then applied both to super-resolve the hydrophobicity of amyloid aggregates implicated in neurodegenerative diseases, and the hydrophobic changes in mammalian cell membranes. Our technique is easily implemented by inserting a transmission diffraction grating into the optical path of a localization-based super-resolution microscope, enabling all the information to be extracted simultaneously from a single image plane.

Multi-dimensional super-resolution imaging enables surface hydrophobicity mapping

PubMed Central

Bongiovanni, Marie N.; Godet, Julien; Horrocks, Mathew H.; Tosatto, Laura; Carr, Alexander R.; Wirthensohn, David C.; Ranasinghe, Rohan T.; Lee, Ji-Eun; Ponjavic, Aleks; Fritz, Joelle V.; Dobson, Christopher M.; Klenerman, David; Lee, Steven F.

2016-01-01

Super-resolution microscopy allows biological systems to be studied at the nanoscale, but has been restricted to providing only positional information. Here, we show that it is possible to perform multi-dimensional super-resolution imaging to determine both the position and the environmental properties of single-molecule fluorescent emitters. The method presented here exploits the solvatochromic and fluorogenic properties of nile red to extract both the emission spectrum and the position of each dye molecule simultaneously enabling mapping of the hydrophobicity of biological structures. We validated this by studying synthetic lipid vesicles of known composition. We then applied both to super-resolve the hydrophobicity of amyloid aggregates implicated in neurodegenerative diseases, and the hydrophobic changes in mammalian cell membranes. Our technique is easily implemented by inserting a transmission diffraction grating into the optical path of a localization-based super-resolution microscope, enabling all the information to be extracted simultaneously from a single image plane. PMID:27929085

Thermodynamic Analysis of Dual-Mode Scramjet Engine Operation and Performance

NASA Technical Reports Server (NTRS)

Riggins, David; Tacket, Regan; Taylor, Trent; Auslender, Aaron

2006-01-01

Recent analytical advances in understanding the performance continuum (the thermodynamic spectrum) for air-breathing engines based on fundamental second-law considerations have clarified scramjet and ramjet operation, performance, and characteristics. Second-law based analysis is extended specifically in this work to clarify and describe the performance characteristics for dual-mode scramjet operation in the mid-speed range of flight Mach 4 to 7. This is done by a fundamental investigation of the complex but predictable interplay between heat release and irreversibilities in such an engine; results demonstrate the flow and performance character of the dual mode regime and of dual mode transition behavior. Both analytical and computational (multi-dimensional CFD) studies of sample dual-mode flow-fields are performed in order to demonstrate the second-law capability and performance and operability issues. The impact of the dual-mode regime is found to be characterized by decreasing overall irreversibility with increasing heat release, within the operability limits of the system.

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)

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.

DICON: interactive visual analysis of multidimensional clusters.

PubMed

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. © 2011 IEEE

Multidimensional Rasch Analysis of a Psychological Test with Multiple Subtests: A Statistical Solution for the Bandwidth-Fidelity Dilemma

ERIC Educational Resources Information Center

Cheng, Ying-Yao; Wang, Wen-Chung; Ho, Yi-Hui

2009-01-01

Educational and psychological tests are often composed of multiple short subtests, each measuring a distinct latent trait. Unfortunately, short subtests suffer from low measurement precision, which makes the bandwidth-fidelity dilemma inevitable. In this study, the authors demonstrate how a multidimensional Rasch analysis can be employed to take…

Exploring the Use of Multidimensional Analysis of Learner Language to Promote Register Awareness

ERIC Educational Resources Information Center

Aguado-Jimenez, Pilar; Perez-Paredes, Pascual; Sanchez, Purificacion

2012-01-01

This paper discusses the use of multidimensional analysis (MA) of learner language to promote the awareness of linguistic concepts such as register and variation. Our research explores the introduction of learner register awareness by using MA of learner language in the field of university Foreign Language Teaching (FLT). In this context, a group…

Points of View Analysis Revisited: Fitting Multidimensional Structures to Optimal Distance Components with Cluster Restrictions on the Variables.

ERIC Educational Resources Information Center

Meulman, Jacqueline J.; Verboon, Peter

1993-01-01

Points of view analysis, as a way to deal with individual differences in multidimensional scaling, was largely supplanted by the weighted Euclidean model. It is argued that the approach deserves new attention, especially as a technique to analyze group differences. A streamlined and integrated process is proposed. (SLD)

Bayesian Analysis of Multidimensional Item Response Theory Models: A Discussion and Illustration of Three Response Style Models

ERIC Educational Resources Information Center

Leventhal, Brian C.; Stone, Clement A.

2018-01-01

Interest in Bayesian analysis of item response theory (IRT) models has grown tremendously due to the appeal of the paradigm among psychometricians, advantages of these methods when analyzing complex models, and availability of general-purpose software. Possible models include models which reflect multidimensionality due to designed test structure,…

Numeric invariants from multidimensional persistence

DOE PAGES

Skryzalin, Jacek; Carlsson, Gunnar

2017-05-19

Topological data analysis is the study of data using techniques from algebraic topology. Often, one begins with a finite set of points representing data and a “filter” function which assigns a real number to each datum. Using both the data and the filter function, one can construct a filtered complex for further analysis. For example, applying the homology functor to the filtered complex produces an algebraic object known as a “one-dimensional persistence module”, which can often be interpreted as a finite set of intervals representing various geometric features in the data. If one runs the above process incorporating multiple filtermore » functions simultaneously, one instead obtains a multidimensional persistence module. Unfortunately, these are much more difficult to interpret. In this article, we analyze the space of multidimensional persistence modules from the perspective of algebraic geometry. First we build a moduli space of a certain subclass of easily analyzed multidimensional persistence modules, which we construct specifically to capture much of the information which can be gained by using multidimensional persistence instead of one-dimensional persistence. Fruthermore, we argue that the global sections of this space provide interesting numeric invariants when evaluated against our subclass of multidimensional persistence modules. Finally, we extend these global sections to the space of all multidimensional persistence modules and discuss how the resulting numeric invariants might be used to study data. This paper extends the results of Adcock et al. (Homol Homotopy Appl 18(1), 381–402, 2016) by constructing numeric invariants from the computation of a multidimensional persistence module as given by Carlsson et al. (J Comput Geom 1(1), 72–100, 2010).« less

A Multidimensional Scaling Analysis of Schizophrenics' and Normals' Perceptions of Verbal Similarity

ERIC Educational Resources Information Center

Neufeld, Richard W. J.

1975-01-01

Twenty-eight schizophrenics (14 paranoid and 14 nonparanoid) were compared with 14 normals on their judgments of similarity among words. The judgments were analyzed using an individual-differences multidimensional scaling procedure. (Editor)

The Aeronautical Data Link: Taxonomy, Architectural Analysis, and Optimization

NASA Technical Reports Server (NTRS)

Morris, A. Terry; Goode, Plesent W.

2002-01-01

The future Communication, Navigation, and Surveillance/Air Traffic Management (CNS/ATM) System will rely on global satellite navigation, and ground-based and satellite based communications via Multi-Protocol Networks (e.g. combined Aeronautical Telecommunications Network (ATN)/Internet Protocol (IP)) to bring about needed improvements in efficiency and safety of operations to meet increasing levels of air traffic. This paper will discuss the development of an approach that completely describes optimal data link architecture configuration and behavior to meet the multiple conflicting objectives of concurrent and different operations functions. The practical application of the approach enables the design and assessment of configurations relative to airspace operations phases. The approach includes a formal taxonomic classification, an architectural analysis methodology, and optimization techniques. The formal taxonomic classification provides a multidimensional correlation of data link performance with data link service, information protocol, spectrum, and technology mode; and to flight operations phase and environment. The architectural analysis methodology assesses the impact of a specific architecture configuration and behavior on the local ATM system performance. Deterministic and stochastic optimization techniques maximize architectural design effectiveness while addressing operational, technology, and policy constraints.

Trajectories of Multidimensional Caregiver Burden in Chinese Informal Caregivers for Dementia: Evidence from Exploratory and Confirmatory Factor Analysis of the Zarit Burden Interview.

PubMed

Li, Dan; Hu, Nan; Yu, Yueyi; Zhou, Aihong; Li, Fangyu; Jia, Jianping

2017-01-01

Despite its popularity, the latent structure of 22-item Zarit Burden Interview (ZBI) remains unclear. There has been no study exploring how caregiver multidimensional burden changed. The aim of the work was to validate the latent structure of ZBI and to investigate how multidimensional burden evolves with increasing global burden. We studied 1,132 dyads of dementia patients and their informal caregivers. The caregivers completed the ZBI and a questionnaire regarding caregiving. The total sample was randomly split into two equal subsamples. Exploratory factor analysis (EFA) was performed in the first subsample. In the second subsample, confirmatory factor analysis (CFA) was conducted to validate models generated from EFA. The mean of weighted factor score was calculated to assess the change of dimension burden against the increasing ZBI total score. The result of EFA and CFA supported that a five-factor structure, including role strain, personal strain, incompetency, dependency, and guilt, had the best goodness-of-fit. The trajectories of multidimensional burden suggested that three different dimensions (guilt, role strain and personal strain) became the main subtype of burden in sequence as the ZBI total score increased from mild to moderate. Factor dependency contributed prominently to the total burden in severe stage. The five-factor ZBI is a psychometrically robust measure for assessing multidimensional burden in Chinese caregivers. The changes of multidimensional burden have deepened our understanding of the psychological characteristics of caregiving beyond a single total score and may be useful for developing interventions to reduce caregiver burden.

A Meta-Analysis of Prosocial Media on Prosocial Behavior, Aggression, and Empathic Concern: A Multidimensional Approach

ERIC Educational Resources Information Center

Coyne, Sarah M.; Padilla-Walker, Laura M.; Holmgren, Hailey G.; Davis, Emilie J.; Collier, Kevin M.; Memmott-Elison, Madison K.; Hawkins, Alan J.

2018-01-01

Studies examining the effects of exposure to prosocial media on positive outcomes are increasing in number and strength. However, existing meta-analyses use a broad definition of prosocial media that does not recognize the multidimensionality of prosocial behavior. The aim of the current study is to conduct a meta-analysis on the effects of…

Maximizing the Information and Validity of a Linear Composite in the Factor Analysis Model for Continuous Item Responses

ERIC Educational Resources Information Center

Ferrando, Pere J.

2008-01-01

This paper develops results and procedures for obtaining linear composites of factor scores that maximize: (a) test information, and (b) validity with respect to external variables in the multiple factor analysis (FA) model. I treat FA as a multidimensional item response theory model, and use Ackerman's multidimensional information approach based…

Chemometric Strategies for Peak Detection and Profiling from Multidimensional Chromatography.

PubMed

Navarro-Reig, Meritxell; Bedia, Carmen; Tauler, Romà; Jaumot, Joaquim

2018-04-03

The increasing complexity of omics research has encouraged the development of new instrumental technologies able to deal with these challenging samples. In this way, the rise of multidimensional separations should be highlighted due to the massive amounts of information that provide with an enhanced analyte determination. Both proteomics and metabolomics benefit from this higher separation capacity achieved when different chromatographic dimensions are combined, either in LC or GC. However, this vast quantity of experimental information requires the application of chemometric data analysis strategies to retrieve this hidden knowledge, especially in the case of nontargeted studies. In this work, the most common chemometric tools and approaches for the analysis of this multidimensional chromatographic data are reviewed. First, different options for data preprocessing and enhancement of the instrumental signal are introduced. Next, the most used chemometric methods for the detection of chromatographic peaks and the resolution of chromatographic and spectral contributions (profiling) are presented. The description of these data analysis approaches is complemented with enlightening examples from omics fields that demonstrate the exceptional potential of the combination of multidimensional separation techniques and chemometric tools of data analysis. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Prose Representation: A Multidimensional Scaling Approach.

ERIC Educational Resources Information Center

LaPorte, Ronald E.; Voss, James F.

1979-01-01

Multidimensional scaling was used to study the comprehension of prose. Undergraduates rated the similarity of twenty nouns before and after reading passages containing those nouns. Results indicated that the scaling analysis provided an effective valid indicator of prose representation. (Author/JKS)

Elimination of uncertainty in solving system of multidimensional differential equations in X for identification of silver nanoparticles on fibers

NASA Astrophysics Data System (ADS)

Emelyanov, V. M.; Dobrovolskaya, T. A.; Emelyanov, V. V.

2018-05-01

In the article, an increase of the sensitivity of identification of biologically active metal silver nanoparticles to cancer cells is considered to be based on the results of compiling a system of multidimensional differential equations with respect to X of the ellipses of probabilistic intersection of the spectra of a Raman polarization spectrometer. The nine main peaks of the spectrum of polyester fibers with silver nanoparticles and without them are analyzed with polarization along the X-transverse and Y-along fibers directions. The correlation matrices of the interconnection of peaks of the Raman spectrum are to be introduced into differential equations. During the solution of the system of equations, there is an intersection of the ellipses of the distribution of the statistical data of peak measurements. When checking the solution from the graphical estimation of the intersection of the ellipses of the data distribution of the Raman spectra, there was a 20% error detected in determining the radii of curvature R0 and R1. To eliminate the uncertainty, numerical additive Δ = + 0.34342 is introduced into the differential equation and when solving this system of differential equations with the additive, the accuracy is (-1.42 · 10-14 ÷ 1.94 · 10-15) with the radius of curvature R0 = R1 = 3.458112896121225 at a sufficiently high accuracy of 10-14

Changes in frontal plane dynamics and the loading response phase of the gait cycle are characteristic of severe knee osteoarthritis application of a multidimensional analysis technique.

PubMed

Astephen, J L; Deluzio, K J

2005-02-01

Osteoarthritis of the knee is related to many correlated mechanical factors that can be measured with gait analysis. Gait analysis results in large data sets. The analysis of these data is difficult due to the correlated, multidimensional nature of the measures. A multidimensional model that uses two multivariate statistical techniques, principal component analysis and discriminant analysis, was used to discriminate between the gait patterns of the normal subject group and the osteoarthritis subject group. Nine time varying gait measures and eight discrete measures were included in the analysis. All interrelationships between and within the measures were retained in the analysis. The multidimensional analysis technique successfully separated the gait patterns of normal and knee osteoarthritis subjects with a misclassification error rate of <6%. The most discriminatory feature described a static and dynamic alignment factor. The second most discriminatory feature described a gait pattern change during the loading response phase of the gait cycle. The interrelationships between gait measures and between the time instants of the gait cycle can provide insight into the mechanical mechanisms of pathologies such as knee osteoarthritis. These results suggest that changes in frontal plane loading and alignment and the loading response phase of the gait cycle are characteristic of severe knee osteoarthritis gait patterns. Subsequent investigations earlier in the disease process may suggest the importance of these factors to the progression of knee osteoarthritis.

Recent advances on multidimensional liquid chromatography-mass spectrometry for proteomics: from qualitative to quantitative analysis--a review.

PubMed

Wu, Qi; Yuan, Huiming; Zhang, Lihua; Zhang, Yukui

2012-06-20

With the acceleration of proteome research, increasing attention has been paid to multidimensional liquid chromatography-mass spectrometry (MDLC-MS) due to its high peak capacity and separation efficiency. Recently, many efforts have been put to improve MDLC-based strategies including "top-down" and "bottom-up" to enable highly sensitive qualitative and quantitative analysis of proteins, as well as accelerate the whole analytical procedure. Integrated platforms with combination of sample pretreatment, multidimensional separations and identification were also developed to achieve high throughput and sensitive detection of proteomes, facilitating highly accurate and reproducible quantification. This review summarized the recent advances of such techniques and their applications in qualitative and quantitative analysis of proteomes. Copyright © 2012 Elsevier B.V. All rights reserved.

Multidimensional Poverty and Health Status as a Predictor of Chronic Income Poverty.

PubMed

Callander, Emily J; Schofield, Deborah J

2015-12-01

Longitudinal analysis of Wave 5 to 10 of the nationally representative Household, Income and Labour Dynamics in Australia dataset was undertaken to assess whether multidimensional poverty status can predict chronic income poverty. Of those who were multidimensionally poor (low income plus poor health or poor health and insufficient education attainment) in 2007, and those who were in income poverty only (no other forms of disadvantage) in 2007, a greater proportion of those in multidimensional poverty continued to be in income poverty for the subsequent 5 years through to 2012. People who were multidimensionally poor in 2007 had 2.17 times the odds of being in income poverty each year through to 2012 than those who were in income poverty only in 2005 (95% CI: 1.23-3.83). Multidimensional poverty measures are a useful tool for policymakers to identify target populations for policies aiming to improve equity and reduce chronic disadvantage. Copyright © 2014 John Wiley & Sons, Ltd.

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.

Impact of multidimensional poverty on the self-efficacy of older people: Results from an Australian longitudinal study.

PubMed

Callander, Emily J; Schofield, Deborah J

2017-02-01

Self-efficacy has numerous benefits for active and healthy aging, including giving the people the ability to make positive changes to their living standards and lifestyles. The present study aims to determine whether falling into multidimensional poverty lowers self-efficacy. Longitudinal analysis of waves 7-11 (2007-2011) of the nationally representative Household, Income and Labor Dynamics in Australia survey using linear regression models. The analysis focused on the Australian population aged 65 years and older. The Freedom Poverty Measure was used to identify those in multidimensional poverty. Those who fell into multidimensional poverty for 3 or 4 years between 2007 and 2011 had their self-efficacy scores decline by an average of 27 points (SD 21.2). Those who fell into poverty had significantly lower self-efficacy scores in 2011 - up to 57% lower (-66.6%, -45.7% P < 0.0001) after being in multidimensional poverty for 3 or 4 years between 2007 and 2011 than those who were never in poverty. Falling into multidimensional poverty lowers the self-efficacy scores of older people. In order to improve the chances of older people making long-term changes to improve their living standards, feelings of self-efficacy should first be assessed and improved. Geriatr Gerontol Int 2017; 17: 308-314. © 2015 Japan Geriatrics Society.

Multidimensional profiles of health locus of control in Hispanic Americans

PubMed Central

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

Characteristics of place identity as part of professional identity development among pre-service teachers

NASA Astrophysics Data System (ADS)

Gross, Michal; Hochberg, Nurit

2016-12-01

How do pre-service teachers perceive place identity, and is there a connection between their formative place identity and the development of their professional teaching identity? These questions are probed among pre-service teachers who participated in a course titled "Integrating Nature into Preschool." The design of the course was based on a multidimensional teaching model that yields a matrix of students' perceptions and the practical aspects derived from them as the students undergo a range of experiences in the course of an academic year. The profile of perceptions uses a mixed-methods analysis that presents statements attesting to four indicators of place identity: familiarity, belonging, involvement, and meaningfulness. These indicators point to a broad spectrum of perceptions arrayed on a continual time axes as well as differences in perception and its complexity. A connection between the development of place identity and that of professional teaching identity is found.

Multidimensional Analysis of Nuclear Detonations

DTIC Science & Technology

2015-09-17

Features on the nuclear weapons testing films because of the expanding and emissive nature of the nuclear fireball. The use of these techniques to produce...Treaty (New Start Treaty) have reduced the acceptable margins of error. Multidimensional analysis provides the modern approach to nuclear weapon ...scientific community access to the information necessary to expand upon the knowledge of nuclear weapon effects. This data set has the potential to provide

Multidimensional bioseparation with modular microfluidics

DOEpatents

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.

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)

Some theorems and properties of multi-dimensional fractional Laplace transforms

NASA Astrophysics Data System (ADS)

Ahmood, Wasan Ajeel; Kiliçman, Adem

2016-06-01

The aim of this work is to study theorems and properties for the one-dimensional fractional Laplace transform, generalize some properties for the one-dimensional fractional Lapalce transform to be valid for the multi-dimensional fractional Lapalce transform and is to give the definition of the multi-dimensional fractional Lapalce transform. This study includes: dedicate the one-dimensional fractional Laplace transform for functions of only one independent variable with some of important theorems and properties and develop of some properties for the one-dimensional fractional Laplace transform to multi-dimensional fractional Laplace transform. Also, we obtain a fractional Laplace inversion theorem after a short survey on fractional analysis based on the modified Riemann-Liouville derivative.

Ultrafast Multi-Dimensional Infrared Vibrational Echo Spectroscopy of Molecular Dynamics on Surfaces and in Bulk Systems

DTIC Science & Technology

2012-02-28

dimethylsulfoxide ( DMSO ). When chloroform is dissolved in a mixed solvent consisting of acetone and DMSO , both types of hydrogen bonded complexes exist. The...transition (negative) in the 2D IR spectrum. Also, line shape distortions caused by solvent background absorption and finite pulse durations do not affect...conditions as  = 7  1 ps. This is the first direct measurement of hydrogen bond exchange. b. Solute- Solvent Complex Switching Dynamics3 Hydrogen

From Molecules to Cells to Organisms: Understanding Health and Disease with Multidimensional Single-Cell Methods

NASA Astrophysics Data System (ADS)

Candia, Julián

2013-03-01

The multidimensional nature of many single-cell measurements (e.g. multiple markers measured simultaneously using Fluorescence-Activated Cell Sorting (FACS) technologies) offers unprecedented opportunities to unravel emergent phenomena that are governed by the cooperative action of multiple elements across different scales, from molecules and proteins to cells and organisms. We will discuss an integrated analysis framework to investigate multicolor FACS data from different perspectives: Singular Value Decomposition to achieve an effective dimensional reduction in the data representation, machine learning techniques to separate different patient classes and improve diagnosis, as well as a novel cell-similarity network analysis method to identify cell subpopulations in an unbiased manner. Besides FACS data, this framework is versatile: in this vein, we will demonstrate an application to the multidimensional single-cell shape analysis of healthy and prematurely aged cells.

Application of the Allan Variance to Time Series Analysis in Astrometry and Geodesy: A Review.

PubMed

Malkin, Zinovy

2016-04-01

The Allan variance (AVAR) was introduced 50 years ago as a statistical tool for assessing the frequency standards deviations. For the past decades, AVAR has increasingly been used in geodesy and astrometry to assess the noise characteristics in geodetic and astrometric time series. A specific feature of astrometric and geodetic measurements, as compared with clock measurements, is that they are generally associated with uncertainties; thus, an appropriate weighting should be applied during data analysis. In addition, some physically connected scalar time series naturally form series of multidimensional vectors. For example, three station coordinates time series X, Y, and Z can be combined to analyze 3-D station position variations. The classical AVAR is not intended for processing unevenly weighted and/or multidimensional data. Therefore, AVAR modifications, namely weighted AVAR (WAVAR), multidimensional AVAR (MAVAR), and weighted multidimensional AVAR (WMAVAR), were introduced to overcome these deficiencies. In this paper, a brief review is given of the experience of using AVAR and its modifications in processing astrogeodetic time series.

Igloo-Plot: a tool for visualization of multidimensional datasets.

PubMed

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.

Simultaneous Multi-Scale Diffusion Estimation and Tractography Guided by Entropy Spectrum Pathways

PubMed Central

Galinsky, Vitaly L.; Frank, Lawrence R.

2015-01-01

We have developed a method for the simultaneous estimation of local diffusion and the global fiber tracts based upon the information entropy flow that computes the maximum entropy trajectories between locations and depends upon the global structure of the multi-dimensional and multi-modal diffusion field. Computation of the entropy spectrum pathways requires only solving a simple eigenvector problem for the probability distribution for which efficient numerical routines exist, and a straight forward integration of the probability conservation through ray tracing of the convective modes guided by a global structure of the entropy spectrum coupled with a small scale local diffusion. The intervoxel diffusion is sampled by multi b-shell multi q-angle DWI data expanded in spherical waves. This novel approach to fiber tracking incorporates global information about multiple fiber crossings in every individual voxel and ranks it in the most scientifically rigorous way. This method has potential significance for a wide range of applications, including studies of brain connectivity. PMID:25532167

Analysis of self-similar solutions of multidimensional conservation laws

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keyfitz, Barbara Lee

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.

Measuring Sexual Orientation: A Review and Critique of U.S. Data Collection Efforts and Implications for Health Policy.

PubMed

Wolff, Margaret; Wells, Brooke; Ventura-DiPersia, Christina; Renson, Audrey; Grov, Christian

The U.S. Department of Health and Human Services' (HHS) Healthy People 2020 goals sought to improve health outcomes among sexual minorities; HHS acknowledged that a dearth of sexual orientation items in federal and state health surveys obscured a broad understanding of sexual minority-related health disparities. The HHS 2011 data progression plan aimed to advance sexual orientation data collection efforts at the national level. Sexual orientation is a complex, multidimensional construct often composed of sexual identity, sexual attraction, and sexual behavior, thus posing challenges to its quantitative and practical measurement and analysis. In this review, we (a) present existing sexual orientation constructs; (b) evaluate current HHS sexual orientation data collection efforts; (c) review post-2011 data progression plan research on sexual minority health disparities, drawing on HHS survey data; (d) highlight the importance of and (e) identify obstacles to multidimensional sexual orientation measurement and analysis; and (f) discuss methods for multidimensional sexual orientation analysis and propose a matrix for addressing discordance/branchedness within these analyses. Multidimensional sexual orientation data collection and analysis would elucidate sexual minority-related health disparities, guide related health policies, and enhance population-based estimates of sexual minority individuals to steer health care practices.

Assessing Dimensionality of Noncompensatory Multidimensional Item Response Theory with Complex Structures

ERIC Educational Resources Information Center

Svetina, Dubravka

2013-01-01

The purpose of this study was to investigate the effect of complex structure on dimensionality assessment in noncompensatory multidimensional item response models using dimensionality assessment procedures based on DETECT (dimensionality evaluation to enumerate contributing traits) and NOHARM (normal ogive harmonic analysis robust method). Five…

A Multidimensional Analysis of the Mental Health of Graduate Counselors in Training.

ERIC Educational Resources Information Center

White, Paul E.; Franzoni, Janet B.

1990-01-01

Examined level of mental health of 180 graduate counselor trainees. Gathered multidimensional mental health information using seven clinical scales of Minnesota Multiphasic Personality Inventory (MMPI), Adult Nowicki-Strickland Internal-External Control Scale, Life Style Personality Inventory, and Coping Resources Inventory for Stress. Trainees…

The Multivariate Nature of Professional Job Satisfaction.

ERIC Educational Resources Information Center

Wood, Donald A.; LeBold, William K.

Discussed are two theories of professional job satisfaction--(1) unidimensional and (2) multidimensional with special reference to Herzberg's two factor theory. A national sample of over 3,000 engineering graduates responded to a questionnaire and satisfaction index. Analysis of results revealed that job satisfaction is multidimensional. Job…

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'…

Detecting Multidimensionality: Which Residual Data-Type Works Best?

ERIC Educational Resources Information Center

Linacre, John Michael

1998-01-01

Simulation studies indicate that, for responses to complete tests, construction of Rasch measures from observational data, followed by principal components factor analysis of Rasch residuals, provides an effective means of identifying multidimensionality. The most diagnostically useful residual form was found to be the standardized residual. (SLD)

Multidimensional profiles of health locus of control in Hispanic Americans.

PubMed

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.

The Extraction of One-Dimensional Flow Properties from Multi-Dimensional Data Sets

NASA Technical Reports Server (NTRS)

Baurle, Robert A.; Gaffney, Richard L., Jr.

2007-01-01

The engineering design and analysis of air-breathing propulsion systems relies heavily on zero- or one-dimensional properties (e.g. thrust, total pressure recovery, mixing and combustion efficiency, etc.) for figures of merit. The extraction of these parameters from experimental data sets and/or multi-dimensional computational data sets is therefore an important aspect of the design process. A variety of methods exist for extracting performance measures from multi-dimensional data sets. Some of the information contained in the multi-dimensional flow is inevitably lost when any one-dimensionalization technique is applied. Hence, the unique assumptions associated with a given approach may result in one-dimensional properties that are significantly different than those extracted using alternative approaches. The purpose of this effort is to examine some of the more popular methods used for the extraction of performance measures from multi-dimensional data sets, reveal the strengths and weaknesses of each approach, and highlight various numerical issues that result when mapping data from a multi-dimensional space to a space of one dimension.

The Art of Extracting One-Dimensional Flow Properties from Multi-Dimensional Data Sets

NASA Technical Reports Server (NTRS)

Baurle, R. A.; Gaffney, R. L.

2007-01-01

The engineering design and analysis of air-breathing propulsion systems relies heavily on zero- or one-dimensional properties (e:g: thrust, total pressure recovery, mixing and combustion efficiency, etc.) for figures of merit. The extraction of these parameters from experimental data sets and/or multi-dimensional computational data sets is therefore an important aspect of the design process. A variety of methods exist for extracting performance measures from multi-dimensional data sets. Some of the information contained in the multi-dimensional flow is inevitably lost when any one-dimensionalization technique is applied. Hence, the unique assumptions associated with a given approach may result in one-dimensional properties that are significantly different than those extracted using alternative approaches. The purpose of this effort is to examine some of the more popular methods used for the extraction of performance measures from multi-dimensional data sets, reveal the strengths and weaknesses of each approach, and highlight various numerical issues that result when mapping data from a multi-dimensional space to a space of one dimension.

The Cognitive Visualization System with the Dynamic Projection of Multidimensional Data

NASA Astrophysics Data System (ADS)

Gorohov, V.; Vitkovskiy, V.

2008-08-01

The phenomenon of cognitive machine drawing consists in the generation on the screen the special graphic representations, which create in the brain of human operator entertainment means. These means seem man by aesthetically attractive and, thus, they stimulate its descriptive imagination, closely related to the intuitive mechanisms of thinking. The essence of cognitive effect lies in the fact that man receives the moving projection as pseudo-three-dimensional object characterizing multidimensional means in the multidimensional space. After the thorough qualitative study of the visual aspects of multidimensional means with the aid of the enumerated algorithms appears the possibility, using algorithms of standard machine drawing to paint the interesting user separate objects or the groups of objects. Then it is possible to again return to the dynamic behavior of the rotation of means for the purpose of checking the intuitive ideas of user about the clusters and the connections in multidimensional data. Is possible the development of the methods of cognitive machine drawing in combination with other information technologies, first of all with the packets of digital processing of images and multidimensional statistical analysis.

Measuring Mindreading: A Review of Behavioral Approaches to Testing Cognitive and Affective Mental State Attribution in Neurologically Typical Adults.

PubMed

Turner, Rose; Felisberti, Fatima M

2017-01-01

Mindreading refers to the ability to attribute mental states, including thoughts, intentions and emotions, to oneself and others, and is essential for navigating the social world. Empirical mindreading research has predominantly featured children, groups with autism spectrum disorder and clinical samples, and many standard tasks suffer ceiling effects with neurologically typical (NT) adults. We first outline a case for studying mindreading in NT adults and proceed to review tests of emotion perception, cognitive and affective mentalizing, and multidimensional tasks combining these facets. We focus on selected examples of core experimental paradigms including emotion recognition tests, social vignettes, narrative fiction (prose and film) and participative interaction (in real and virtual worlds), highlighting challenges for studies with NT adult cohorts. We conclude that naturalistic, multidimensional approaches may be productively applied alongside traditional tasks to facilitate a more nuanced picture of mindreading in adulthood, and to ensure construct validity whilst remaining sensitive to variation at the upper echelons of the ability.

Measuring Mindreading: A Review of Behavioral Approaches to Testing Cognitive and Affective Mental State Attribution in Neurologically Typical Adults

PubMed Central

Turner, Rose; Felisberti, Fatima M.

2017-01-01

Mindreading refers to the ability to attribute mental states, including thoughts, intentions and emotions, to oneself and others, and is essential for navigating the social world. Empirical mindreading research has predominantly featured children, groups with autism spectrum disorder and clinical samples, and many standard tasks suffer ceiling effects with neurologically typical (NT) adults. We first outline a case for studying mindreading in NT adults and proceed to review tests of emotion perception, cognitive and affective mentalizing, and multidimensional tasks combining these facets. We focus on selected examples of core experimental paradigms including emotion recognition tests, social vignettes, narrative fiction (prose and film) and participative interaction (in real and virtual worlds), highlighting challenges for studies with NT adult cohorts. We conclude that naturalistic, multidimensional approaches may be productively applied alongside traditional tasks to facilitate a more nuanced picture of mindreading in adulthood, and to ensure construct validity whilst remaining sensitive to variation at the upper echelons of the ability. PMID:28174552

The Impact of Learner Characteristics on the Multi-Dimensional Construct of Social Presence

ERIC Educational Resources Information Center

Mykota, David

2017-01-01

This study explored the impact of learner characteristics on the multi-dimensional construct of social presence as measured by the computer-mediated communication questionnaire. Using Multiple Analysis of Variance findings reveal that the number of online courses taken and computer-mediated communication experience significantly affect the…

Evidence for a Multidimensional Self-Efficacy for Exercise Scale

ERIC Educational Resources Information Center

Rodgers, W. M.; Wilson, P. M.; Hall, C. R.; Fraser, S. N.; Murray, T. C.

2008-01-01

This series of three studies considers the multidimensionality of exercise self-efficacy by examining the psychometric characteristics of an instrument designed to assess three behavioral subdomains: task, scheduling, and coping. In Study 1, exploratory factor analysis revealed the expected factor structure in a sample of 395 students.…

Confirmatory Factor Analysis of the Hewitt-Multidimensional Perfectionism Scale

ERIC Educational Resources Information Center

Barut, Yasar

2015-01-01

Various studies on the conceptual framework of perfectionism construct use Hewitt Multi-dimensional Perfectionism Scale (HMPS), as a basic approach. The measure has a prominent role with respect to the theoretical considerations of perfectionism dimensions. This study aimed to evaluate the psychometric properties of the Turkish version of the…

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…

Connectivity and Resilience: A Multidimensional Analysis of Infrastructure Impacts in the Southwestern Amazon

ERIC Educational Resources Information Center

Perz, Stephen G.; Shenkin, Alexander; Barnes, Grenville; Cabrera, Liliana; Carvalho, Lucas A.; Castillo, Jorge

2012-01-01

Infrastructure is a worldwide policy priority for national development via regional integration into the global economy. However, economic, ecological and social research draws contrasting conclusions about the consequences of infrastructure. We present a synthetic approach to the study of infrastructure, focusing on a multidimensional treatment…

Multidimensional Assessment of Phonological Similarity within and between Children

ERIC Educational Resources Information Center

Ingram, David; Dubasik, Virginia L.

2011-01-01

Multidimensional analysis involves moving away from one-dimensional analyses such as most articulation tests to comprehensive analyses involving levels of phonological information from the word level down to segments. This article outlines one such approach that looks at four levels from words to segments, using nine phonological measures. It also…

The Effects of Verbal Pretraining on the Multidimensional Generalization Behavior of Children

ERIC Educational Resources Information Center

Spiker, Charles C.; And Others

1972-01-01

Predictions for multidimensional generalization were derived from Hull-Spence learning theory, and an experiment is reported that was designed to test this aspect of the theory. Alternative to this analysis is presented in PS 502 062; authors respond in PS 502 063. (Authors/MB)

An Overview of Software for Conducting Dimensionality Assessment in Multidimensional Models

ERIC Educational Resources Information Center

Svetina, Dubravka; Levy, Roy

2012-01-01

An overview of popular software packages for conducting dimensionality assessment in multidimensional models is presented. Specifically, five popular software packages are described in terms of their capabilities to conduct dimensionality assessment with respect to the nature of analysis (exploratory or confirmatory), types of data (dichotomous,…

Cross-Cultural Validity of the Frost Multidimensional Perfectionism Scale in Korea

ERIC Educational Resources Information Center

Lee, Dong-gwi; Park, Hyun-joo

2011-01-01

This study with 213 South Korean college students (113 men) examined the cross-cultural generalizability of (a) the factor structure of the Frost Multidimensional Perfectionism Scale (F-MPS) and (b) the existence of adaptive perfectionists, maladaptive perfectionists, and nonperfectionists. A confirmatory factor analysis did not support the…

An asymptotic preserving multidimensional ALE method for a system of two compressible flows coupled with friction

NASA Astrophysics Data System (ADS)

Del Pino, S.; Labourasse, E.; Morel, G.

2018-06-01

We present a multidimensional asymptotic preserving scheme for the approximation of a mixture of compressible flows. Fluids are modelled by two Euler systems of equations coupled with a friction term. The asymptotic preserving property is mandatory for this kind of model, to derive a scheme that behaves well in all regimes (i.e. whatever the friction parameter value is). The method we propose is defined in ALE coordinates, using a Lagrange plus remap approach. This imposes a multidimensional definition and analysis of the scheme.

Highly efficient peptide separations in proteomics Part 1. Unidimensional high performance liquid chromatography.

PubMed

Sandra, Koen; Moshir, Mahan; D'hondt, Filip; Verleysen, Katleen; Kas, Koen; Sandra, Pat

2008-04-15

Sample complexity and dynamic range constitute enormous challenges in proteome analysis. The back-end technology in typical proteomics platforms, namely mass spectrometry (MS), can only tolerate a certain complexity, has a limited dynamic range per spectrum and is very sensitive towards ion suppression. Therefore, component overlap has to be minimized for successful mass spectrometric analysis and subsequent protein identification and quantification. The present review describes the advances that have been made in liquid-based separation techniques with focus on the recent developments to boost the resolving power. The review is divided in two parts; the first part deals with unidimensional liquid chromatography and the second part with bi- and multidimensional liquid-based separation techniques. Part 1 mainly focuses on reversed-phase HPLC due to the fact that it is and will, in the near future, remain the technique of choice to be hyphenated with MS. The impact of increasing the column length, decreasing the particle diameter, replacing the traditional packed beds by monolithics, amongst others, is described. The review is complemented with data obtained in the laboratories of the authors.

A tool to automatically analyze electromagnetic tracking data from high dose rate brachytherapy of breast cancer patients.

PubMed

Götz, Th I; Lahmer, G; Strnad, V; Bert, Ch; Hensel, B; Tomé, A M; Lang, E W

2017-01-01

During High Dose Rate Brachytherapy (HDR-BT) the spatial position of the radiation source inside catheters implanted into a female breast is determined via electromagnetic tracking (EMT). Dwell positions and dwell times of the radiation source are established, relative to the patient's anatomy, from an initial X-ray-CT-image. During the irradiation treatment, catheter displacements can occur due to patient movements. The current study develops an automatic analysis tool of EMT data sets recorded with a solenoid sensor to assure concordance of the source movement with the treatment plan. The tool combines machine learning techniques such as multi-dimensional scaling (MDS), ensemble empirical mode decomposition (EEMD), singular spectrum analysis (SSA) and particle filter (PF) to precisely detect and quantify any mismatch between the treatment plan and actual EMT measurements. We demonstrate that movement artifacts as well as technical signal distortions can be removed automatically and reliably, resulting in artifact-free reconstructed signals. This is a prerequisite for a highly accurate determination of any deviations of dwell positions from the treatment plan.

A tool to automatically analyze electromagnetic tracking data from high dose rate brachytherapy of breast cancer patients

PubMed Central

Lahmer, G.; Strnad, V.; Bert, Ch.; Hensel, B.; Tomé, A. M.; Lang, E. W.

2017-01-01

During High Dose Rate Brachytherapy (HDR-BT) the spatial position of the radiation source inside catheters implanted into a female breast is determined via electromagnetic tracking (EMT). Dwell positions and dwell times of the radiation source are established, relative to the patient’s anatomy, from an initial X-ray-CT-image. During the irradiation treatment, catheter displacements can occur due to patient movements. The current study develops an automatic analysis tool of EMT data sets recorded with a solenoid sensor to assure concordance of the source movement with the treatment plan. The tool combines machine learning techniques such as multi-dimensional scaling (MDS), ensemble empirical mode decomposition (EEMD), singular spectrum analysis (SSA) and particle filter (PF) to precisely detect and quantify any mismatch between the treatment plan and actual EMT measurements. We demonstrate that movement artifacts as well as technical signal distortions can be removed automatically and reliably, resulting in artifact-free reconstructed signals. This is a prerequisite for a highly accurate determination of any deviations of dwell positions from the treatment plan. PMID:28934238

Analysis of ligand-protein exchange by Clustering of Ligand Diffusion Coefficient Pairs (CoLD-CoP)

NASA Astrophysics Data System (ADS)

Snyder, David A.; Chantova, Mihaela; Chaudhry, Saadia

2015-06-01

NMR spectroscopy is a powerful tool in describing protein structures and protein activity for pharmaceutical and biochemical development. This study describes a method to determine weak binding ligands in biological systems by using hierarchic diffusion coefficient clustering of multidimensional data obtained with a 400 MHz Bruker NMR. Comparison of DOSY spectrums of ligands of the chemical library in the presence and absence of target proteins show translational diffusion rates for small molecules upon interaction with macromolecules. For weak binders such as compounds found in fragment libraries, changes in diffusion rates upon macromolecular binding are on the order of the precision of DOSY diffusion measurements, and identifying such subtle shifts in diffusion requires careful statistical analysis. The "CoLD-CoP" (Clustering of Ligand Diffusion Coefficient Pairs) method presented here uses SAHN clustering to identify protein-binders in a chemical library or even a not fully characterized metabolite mixture. We will show how DOSY NMR and the "CoLD-CoP" method complement each other in identifying the most suitable candidates for lysozyme and wheat germ acid phosphatase.

Analysis of the time structure of synchronization in multidimensional chaotic systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Makarenko, A. V., E-mail: avm.science@mail.ru

2015-05-15

A new approach is proposed to the integrated analysis of the time structure of synchronization of multidimensional chaotic systems. The method allows one to diagnose and quantitatively evaluate the intermittency characteristics during synchronization of chaotic oscillations in the T-synchronization mode. A system of two identical logistic mappings with unidirectional coupling that operate in the developed chaos regime is analyzed. It is shown that the widely used approach, in which only synchronization patterns are subjected to analysis while desynchronization areas are considered as a background signal and removed from analysis, should be regarded as methodologically incomplete.

Simulation and Spectrum Extraction in the Spectroscopic Channel of the SNAP Experiment

NASA Astrophysics Data System (ADS)

Tilquin, Andre; Bonissent, A.; Gerdes, D.; Ealet, A.; Prieto, E.; Macaire, C.; Aumenier, M. H.

2007-05-01

A pixel-level simulation software is described. It is composed of two modules. The first module applies Fourier optics at each active element of the system to construct the PSF at a large variety of wavelengths and spatial locations of the point source. The input is provided by the engineer's design program (Zemax). It describes the optical path and the distortions. The PSF properties are compressed and interpolated using shapelets decomposition and neural network techniques. A second module is used for production jobs. It uses the output of the first module to reconstruct the relevant PSF and integrate it on the detector pixels. Extended and polychromatic sources are approximated by a combination of monochromatic point sources. For the spectrum extraction, we use a fast simulator based on a multidimensional linear interpolation of the pixel response tabulated on a grid of values of wavelength, position on sky and slice number. The prediction of the fast simulator is compared to the observed pixel content, and a chi-square minimization where the parameters are the bin contents is used to build the extracted spectrum. The visible and infrared arms are combined in the same chi-square, providing a single spectrum.

A Demonstration of Optimal Apodization Determination for Proper Lateral Modulation

NASA Astrophysics Data System (ADS)

Sumi, Chikayoshi; Komiya, Yuichi; Uga, Shinya

2009-07-01

We have realized effective ultrasound (US) beamformings by the steering of plural beams and apodizations for B-mode imaging with a high lateral resolution and accurate measurement of tissue or blood displacement vector and/or strain tensor using the multidimensional cross-spectrum phase gradient method (MCSPGM), or multidimensional autocorrelation or Doppler methods (MAM and MDM) using multidimensional analytic signals. For instance, the coherent superposition of the steered beams performed in the lateral cosine modulation method (LCM) has a higher potential for realizing a more accurate measurement of a displacement vector than the synthesis of the displacement vector using the accurately measured axial displacements obtained by the multidimensional synthetic aperture method (MDSAM), multidirectional transmission method (MTM) or the use of plural US transducers. Originally, the apodization function to be used for realizing a designed point spread function (PSF) was obtained by the Fraunhofer approximation (FA). However, to obtain the best approximated, designed PSF in the least-squares sense, we proposed a linear optimization (LO) method. Furthermore, on the basis of the knowledge about the losts of US energy during the propagation, we have recently developed a nonlinear optimization (NLO) method, in which the feet of the main lobes in apodization function are properly truncated. Thus, NLO also allows the decrease in the number of channels or the confinement of the effective aperture. In this study, to gain insight into the ideal shape of the PSF, the accuracies of the two-dimensional (2D) displacement vector measurements were compared for typical PSFs with distinct lateral envelope shapes, particularly, in terms of full width at half maximum (FWHM) and the length of the feet, i.e., the Gaussian function, Hanning window and parabolic function. It was confirmed that a PSF having a wide FWHM and short feet was ideal. Such a PSF yielded an echo with a high signal-to-noise ratio (SNR), a large bandwidth and a large maximum spectrum of the center frequency. Moreover, for the three PSFs used, by calculating the PSFs using a typical transducer model and the apodization functions obtained by the respective LO and NLO methods and FA, we compare the approximation accuracies of the realized PSFs. NLO was effective for realizing such an ideal PSF. In addition, NLO allowed the significant decrease in the number of channels or the confinement of the effective aperture. Thus, in the comparisons of the three distinct PSFs, we obtain an appropriate apodization function. This study will assist the realization of the best lateral modulation.

The Use of the Visualisation of Multidimensional Data Using PCA to Evaluate Possibilities of the Division of Coal Samples Space Due to their Suitability for Fluidised Gasification

NASA Astrophysics Data System (ADS)

Jamróz, Dariusz; Niedoba, Tomasz; Surowiak, Agnieszka; Tumidajski, Tadeusz

2016-09-01

Methods serving to visualise multidimensional data through the transformation of multidimensional space into two-dimensional space, enable to present the multidimensional data on the computer screen. Thanks to this, qualitative analysis of this data can be performed in the most natural way for humans, through the sense of sight. An example of such a method of multidimensional data visualisation is PCA (principal component analysis) method. This method was used in this work to present and analyse a set of seven-dimensional data (selected seven properties) describing coal samples obtained from Janina and Wieczorek coal mines. Coal from these mines was previously subjected to separation by means of a laboratory ring jig, consisting of ten rings. With 5 layers of both types of coal (with 2 rings each) were obtained in this way. It was decided to check if the method of multidimensional data visualisation enables to divide the space of such divided samples into areas with different suitability for the fluidised gasification process. To that end, the card of technological suitability of coal was used (Sobolewski et al., 2012; 2013), in which key, relevant and additional parameters, having effect on the gasification process, were described. As a result of analyses, it was stated that effective determination of coal samples suitability for the on-surface gasification process in a fluidised reactor is possible. The PCA method enables the visualisation of the optimal subspace containing the set requirements concerning the properties of coals intended for this process.

The Evaluation of Classroom Social Structure by Three-Way Multidimensional Scaling of Sociometric Data.

ERIC Educational Resources Information Center

Langeheine, Rolf

1978-01-01

A three-way multidimensional scaling model is presented as a method for identifying classroom cliques, by simultaneous analysis of three variables (for example, chooser/choosen/criteria). Two scaling models--Carroll and Chang's INDSCAL and Lingoes' PINDIS--are presented and applied to two sets of empirical data. (CP)

Extracting Undimensional Chains from Multidimensional Datasets: A Graph Theory Approach.

ERIC Educational Resources Information Center

Yamomoto, Yoneo; Wise, Steven L.

An order-analysis procedure, which uses graph theory to extract efficiently nonredundant, unidimensional chains of items from multidimensional data sets and chain consistency as a criterion for chain membership is outlined in this paper. The procedure is intended as an alternative to the Reynolds (1976) procedure which is described as being…

Lexical Sophistication as a Multidimensional Phenomenon: Relations to Second Language Lexical Proficiency, Development, and Writing Quality

ERIC Educational Resources Information Center

Kim, Minkyung; Crossley, Scott A.; Kyle, Kristopher

2018-01-01

This study conceptualizes lexical sophistication as a multidimensional phenomenon by reducing numerous lexical features of lexical sophistication into 12 aggregated components (i.e., dimensions) via a principal component analysis approach. These components were then used to predict second language (L2) writing proficiency levels, holistic lexical…

The Controversial Classroom: Institutional Resources and Pedagogical Strategies for a Race Relations Course.

ERIC Educational Resources Information Center

Wahl, Ana-Maria; Perez, Eduardo T.; Deegan, Mary Jo; Sanchez, Thomas W.; Applegate, Cheryl

2000-01-01

Offers a model for a collective strategy that can be used to deal more effectively with problems associated with race relations courses. Presents a multidimensional analysis of the constraints that create problems for race relations instructors and highlights a multidimensional approach to minimizing these problems. Includes references. (CMK)

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…

Multidimensional Item Response Theory Models in Vocational Interest Measurement: An Illustration Using the AIST-R

ERIC Educational Resources Information Center

Wetzel, Eunike; Hell, Benedikt

2014-01-01

Vocational interest inventories are commonly analyzed using a unidimensional approach, that is, each subscale is analyzed separately. However, the theories on which these inventories are based often postulate specific relationships between the interest traits. This article presents a multidimensional approach to the analysis of vocational interest…

A Hierarchical Bayesian Multidimensional Scaling Methodology for Accommodating Both Structural and Preference Heterogeneity

ERIC Educational Resources Information Center

Park, Joonwook; Desarbo, Wayne S.; Liechty, John

2008-01-01

Multidimensional scaling (MDS) models for the analysis of dominance data have been developed in the psychometric and classification literature to simultaneously capture subjects' "preference heterogeneity" and the underlying dimentional structure for a set of designated stimuli in a parsimonious manner. There are two major types of latent utility…

A Heterogeneous Network Based Method for Identifying GBM-Related Genes by Integrating Multi-Dimensional Data.

PubMed

Chen Peng; Ao Li

2017-01-01

The emergence of multi-dimensional data offers opportunities for more comprehensive analysis of the molecular characteristics of human diseases and therefore improving diagnosis, treatment, and prevention. In this study, we proposed a heterogeneous network based method by integrating multi-dimensional data (HNMD) to identify GBM-related genes. The novelty of the method lies in that the multi-dimensional data of GBM from TCGA dataset that provide comprehensive information of genes, are combined with protein-protein interactions to construct a weighted heterogeneous network, which reflects both the general and disease-specific relationships between genes. In addition, a propagation algorithm with resistance is introduced to precisely score and rank GBM-related genes. The results of comprehensive performance evaluation show that the proposed method significantly outperforms the network based methods with single-dimensional data and other existing approaches. Subsequent analysis of the top ranked genes suggests they may be functionally implicated in GBM, which further corroborates the superiority of the proposed method. The source code and the results of HNMD can be downloaded from the following URL: http://bioinformatics.ustc.edu.cn/hnmd/ .

The Necessity-Concerns-Framework: A Multidimensional Theory Benefits from Multidimensional Analysis

PubMed Central

Phillips, L. Alison; Diefenbach, Michael; Kronish, Ian M.; Negron, Rennie M.; Horowitz, Carol R.

2014-01-01

Background Patients’ medication-related concerns and necessity-beliefs predict adherence. Evaluation of the potentially complex interplay of these two dimensions has been limited because of methods that reduce them to a single dimension (difference scores). Purpose We use polynomial regression to assess the multidimensional effect of stroke-event survivors’ medication-related concerns and necessity-beliefs on their adherence to stroke-prevention medication. Methods Survivors (n=600) rated their concerns, necessity-beliefs, and adherence to medication. Confirmatory and exploratory polynomial regression determined the best-fitting multidimensional model. Results As posited by the Necessity-Concerns Framework (NCF), the greatest and lowest adherence was reported by those with strong necessity-beliefs/weak concerns and strong concerns/weak necessity-beliefs, respectively. However, as could not be assessed using a difference-score model, patients with ambivalent beliefs were less adherent than those exhibiting indifference. Conclusions Polynomial regression allows for assessment of the multidimensional nature of the NCF. Clinicians/Researchers should be aware that concerns and necessity dimensions are not polar opposites. PMID:24500078

The necessity-concerns framework: a multidimensional theory benefits from multidimensional analysis.

PubMed

Phillips, L Alison; Diefenbach, Michael A; Kronish, Ian M; Negron, Rennie M; Horowitz, Carol R

2014-08-01

Patients' medication-related concerns and necessity-beliefs predict adherence. Evaluation of the potentially complex interplay of these two dimensions has been limited because of methods that reduce them to a single dimension (difference scores). We use polynomial regression to assess the multidimensional effect of stroke-event survivors' medication-related concerns and necessity beliefs on their adherence to stroke-prevention medication. Survivors (n = 600) rated their concerns, necessity beliefs, and adherence to medication. Confirmatory and exploratory polynomial regression determined the best-fitting multidimensional model. As posited by the necessity-concerns framework (NCF), the greatest and lowest adherence was reported by those necessity weak concerns and strong concerns/weak Necessity-Beliefs, respectively. However, as could not be assessed using a difference-score model, patients with ambivalent beliefs were less adherent than those exhibiting indifference. Polynomial regression allows for assessment of the multidimensional nature of the NCF. Clinicians/Researchers should be aware that concerns and necessity dimensions are not polar opposites.

The moderating effects of gender on the associations between multidimensional hostility and psychosomatic symptoms: a Chinese case.

PubMed

Weng, Chia-Ying; Lin, I-Mei; Jiang, Ding-Yu

2010-08-01

The purpose of this study was to examine the effects of gender on the relationship between multidimensional hostility and psychosomatic symptoms in Chinese culture. The participants in this study were 398 Chinese college students (40% female) recruited from Taiwan. Four dimensions of multidimensional hostility-hostility cognition, hostility affect, expressive hostility behavior, and suppressive hostility behavior-were measured by the Chinese Hostility Inventory. After controlling for the effects of depression and anxiety, the results of path analysis revealed that the multidimensional hostility predicted psychosomatic symptoms directly, and predicted psychosomatic symptoms indirectly through negative health behavior. Furthermore, gender moderated the relationships between multidimensional hostility and health outcomes. Expressive hostility exacerbated psychosomatic symptom in females but buffered it in males, while affective hostility exacerbated psychosomatic symptoms in males. Additionally, suppressive hostility behavior was correlated to psychosomatic symptoms indirectly through negative health behavior in females. Moreover, expressive hostility was correlated to psychosomatic symptoms indirectly through negative health behavior more in males than in females.

Three subgroups of pain profiles identified in 227 women with arthritis: a latent class analysis.

PubMed

de Luca, Katie; Parkinson, Lynne; Downie, Aron; Blyth, Fiona; Byles, Julie

2017-03-01

The objectives were to identify subgroups of women with arthritis based upon the multi-dimensional nature of their pain experience and to compare health and socio-demographic variables between subgroups. A latent class analysis of 227 women with self-reported arthritis was used to identify clusters of women based upon the sensory, affective, and cognitive dimensions of the pain experience. Multivariate multinomial logistic regression analysis was used to determine the relationship between cluster membership and health and sociodemographic characteristics. A three-class cluster model was most parsimonious. 39.5 % of women had a unidimensional pain profile; 38.6 % of women had moderate multidimensional pain profile that included additional pain symptomatology such as sensory qualities and pain catastrophizing; and 21.9 % of women had severe multidimensional pain profile that included prominent pain symptomatology such as sensory and affective qualities of pain, pain catastrophizing, and neuropathic pain. Women with severe multidimensional pain profile have a 30.5 % higher risk of poorer quality of life and a 7.3 % higher risk of suffering depression, and women with moderate multidimensional pain profile have a 6.4 % higher risk of poorer quality of life when compared to women with unidimensional pain. This study identified three distinct subgroups of pain profiles in older women with arthritis. Women had very different experiences of pain, and cluster membership impacted significantly on health-related quality of life. These preliminary findings provide a stronger understanding of profiles of pain and may contribute to the development of tailored treatment options in arthritis.

Joint mapping of genes and conditions via multidimensional unfolding analysis

PubMed Central

Van Deun, Katrijn; Marchal, Kathleen; Heiser, Willem J; Engelen, Kristof; Van Mechelen, Iven

2007-01-01

Background Microarray compendia profile the expression of genes in a number of experimental conditions. Such data compendia are useful not only to group genes and conditions based on their similarity in overall expression over profiles but also to gain information on more subtle relations between genes and conditions. Getting a clear visual overview of all these patterns in a single easy-to-grasp representation is a useful preliminary analysis step: We propose to use for this purpose an advanced exploratory method, called multidimensional unfolding. Results We present a novel algorithm for multidimensional unfolding that overcomes both general problems and problems that are specific for the analysis of gene expression data sets. Applying the algorithm to two publicly available microarray compendia illustrates its power as a tool for exploratory data analysis: The unfolding analysis of a first data set resulted in a two-dimensional representation which clearly reveals temporal regulation patterns for the genes and a meaningful structure for the time points, while the analysis of a second data set showed the algorithm's ability to go beyond a mere identification of those genes that discriminate between different patient or tissue types. Conclusion Multidimensional unfolding offers a useful tool for preliminary explorations of microarray data: By relying on an easy-to-grasp low-dimensional geometric framework, relations among genes, among conditions and between genes and conditions are simultaneously represented in an accessible way which may reveal interesting patterns in the data. An additional advantage of the method is that it can be applied to the raw data without necessitating the choice of suitable genewise transformations of the data. PMID:17550582

Validation of radiative transfer computation with Monte Carlo method for ultra-relativistic background flow

NASA Astrophysics Data System (ADS)

Ishii, Ayako; Ohnishi, Naofumi; Nagakura, Hiroki; Ito, Hirotaka; Yamada, Shoichi

2017-11-01

We developed a three-dimensional radiative transfer code for an ultra-relativistic background flow-field by using the Monte Carlo (MC) method in the context of gamma-ray burst (GRB) emission. For obtaining reliable simulation results in the coupled computation of MC radiation transport with relativistic hydrodynamics which can reproduce GRB emission, we validated radiative transfer computation in the ultra-relativistic regime and assessed the appropriate simulation conditions. The radiative transfer code was validated through two test calculations: (1) computing in different inertial frames and (2) computing in flow-fields with discontinuous and smeared shock fronts. The simulation results of the angular distribution and spectrum were compared among three different inertial frames and in good agreement with each other. If the time duration for updating the flow-field was sufficiently small to resolve a mean free path of a photon into ten steps, the results were thoroughly converged. The spectrum computed in the flow-field with a discontinuous shock front obeyed a power-law in frequency whose index was positive in the range from 1 to 10 MeV. The number of photons in the high-energy side decreased with the smeared shock front because the photons were less scattered immediately behind the shock wave due to the small electron number density. The large optical depth near the shock front was needed for obtaining high-energy photons through bulk Compton scattering. Even one-dimensional structure of the shock wave could affect the results of radiation transport computation. Although we examined the effect of the shock structure on the emitted spectrum with a large number of cells, it is hard to employ so many computational cells per dimension in multi-dimensional simulations. Therefore, a further investigation with a smaller number of cells is required for obtaining realistic high-energy photons with multi-dimensional computations.

Multidimensional human dynamics in mobile phone communications.

PubMed

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.

Highly efficient peptide separations in proteomics. Part 2: bi- and multidimensional liquid-based separation techniques.

PubMed

Sandra, Koen; Moshir, Mahan; D'hondt, Filip; Tuytten, Robin; Verleysen, Katleen; Kas, Koen; François, Isabelle; Sandra, Pat

2009-04-15

Multidimensional liquid-based separation techniques are described for maximizing the resolution of the enormous number of peptides generated upon tryptic digestion of proteomes, and hence, reduce the spatial and temporal complexity of the sample to a level that allows successful mass spectrometric analysis. This review complements the previous contribution on unidimensional high performance liquid chromatography (HPLC). Both chromatography and electrophoresis will be discussed albeit with reversed-phase HPLC (RPLC) as the final separation dimension prior to MS analysis.

Pathways into chronic multidimensional poverty amongst older people: a longitudinal study.

PubMed

Callander, Emily J; Schofield, Deborah J

2016-03-07

The use of multidimensional poverty measures is becoming more common for measuring the living standards of older people. However, the pathways into poverty are relatively unknown, nor is it known how this affects the length of time people are in poverty for. Using Waves 1 to 12 of the nationally representative Household, Income and Labour Dynamics in Australia (HILDA) survey, longitudinal analysis was undertaken to identify the order that key forms of disadvantage develop - poor health, low income and insufficient education attainment - amongst Australians aged 65 years and over in multidimensional poverty, and the relationship this has with chronic poverty. Path analysis and linear regression models were used. For all older people with at least a Year 10 level of education attainment earlier mental health was significantly related to later household income (p = 0.001) and wealth (p = 0.017). For all older people with at less than a Year 10 level of education attainment earlier household income was significantly related to later mental health (p = 0.021). When limited to those in multidimensional poverty who were in income poverty and also had poor health, older people generally fell into income poverty first and then developed poor health. The order in which income poverty and poor health were developed had a significant influence on the length of time older people with less than a Year 10 level of education attainment were in multidimensional poverty for. Those who developed poor health first then fell into income poverty spend significantly less time in multidimensional poverty (-4.90, p < .0001) than those who fell into income poverty then developed poor health. Knowing the order that different forms of disadvantage develop, and the influence this has on poverty entrenchment, is of use to policy makers wishing to provide interventions to prevent older people being in long-term multidimensional poverty.

Saturn Ring Data Analysis and Thermal Modeling

NASA Technical Reports Server (NTRS)

Dobson, Coleman

2011-01-01

CIRS, VIMS, UVIS, and ISS (Cassini's Composite Infrared Specrtometer, Visual and Infrared Mapping Spectrometer, Ultra Violet Imaging Spectrometer and Imaging Science Subsystem, respectively), have each operated in a multidimensional observation space and have acquired scans of the lit and unlit rings at multiple phase angles. To better understand physical and dynamical ring particle parametric dependence, we co-registered profiles from these three instruments, taken at a wide range of wavelengths, from ultraviolet through the thermal infrared, to associate changes in ring particle temperature with changes in observed brightness, specifically with albedos inferred by ISS, UVIS and VIMS. We work in a parameter space where the solar elevation range is constrained to 12 deg - 14 deg and the chosen radial region is the B3 region of the B ring; this region is the most optically thick region in Saturn's rings. From this compilation of multiple wavelength data, we construct and fit phase curves and color ratios using independent dynamical thermal models for ring structure and overplot Saturn, Saturn ring, and Solar spectra. Analysis of phase curve construction and color ratios reveals thermal emission to fall within the extrema of the ISS bandwidth and a geometrical dependence of reddening on phase angle, respectively. Analysis of spectra reveals Cassini CIRS Saturn spectra dominate Cassini CIRS B3 Ring Spectra from 19 to 1000 microns, while Earth-based B Ring Spectrum dominates Earth-based Saturn Spectrum from 0.4 to 4 microns. From our fits we test out dynamical thermal models; from the phase curves we derive ring albedos and non-lambertian properties of the ring particle surfaces; and from the color ratios we examine multiple scattering within the regolith of ring particles.

Method of multi-dimensional moment analysis for the characterization of signal peaks

DOEpatents

Pfeifer, Kent B; Yelton, William G; Kerr, Dayle R; Bouchier, Francis A

2012-10-23

A method of multi-dimensional moment analysis for the characterization of signal peaks can be used to optimize the operation of an analytical system. With a two-dimensional Peclet analysis, the quality and signal fidelity of peaks in a two-dimensional experimental space can be analyzed and scored. This method is particularly useful in determining optimum operational parameters for an analytical system which requires the automated analysis of large numbers of analyte data peaks. For example, the method can be used to optimize analytical systems including an ion mobility spectrometer that uses a temperature stepped desorption technique for the detection of explosive mixtures.

Using Multidimensional Rasch Analysis to Validate the Chinese Version of the Motivated Strategies for Learning Questionnaire (MSLQ-CV)

ERIC Educational Resources Information Center

Lee, John Chi-Kin; Zhang, Zhonghua; Yin, Hongbiao

2010-01-01

This article used the multidimensional random coefficients multinomial logit model to examine the construct validity and detect the substantial differential item functioning (DIF) of the Chinese version of motivated strategies for learning questionnaire (MSLQ-CV). A total of 1,354 Hong Kong junior high school students were administered the…

Effects of Multidimensional Family Therapy (MDFT) on Nonopioid Drug Abuse: A Systematic Review and Meta-Analysis

ERIC Educational Resources Information Center

Filges, Trine; Andersen, Ditte; Jørgensen, Anne-Marie Klint

2018-01-01

Purpose: This review evaluates the evidence of the effects of multidimensional family therapy (MDFT) on drug use reduction in young people for the treatment of nonopioid drug use. Method: We followed Campbell Collaboration guidelines to conduct a systematic review of randomized and nonrandomized trials. Meta-analytic methods were used to…

A Bifactor Multidimensional Item Response Theory Model for Differential Item Functioning Analysis on Testlet-Based Items

ERIC Educational Resources Information Center

Fukuhara, Hirotaka; Kamata, Akihito

2011-01-01

A differential item functioning (DIF) detection method for testlet-based data was proposed and evaluated in this study. The proposed DIF model is an extension of a bifactor multidimensional item response theory (MIRT) model for testlets. Unlike traditional item response theory (IRT) DIF models, the proposed model takes testlet effects into…

A Multidimensional Item Response Model: Constrained Latent Class Analysis Using the Gibbs Sampler and Posterior Predictive Checks.

ERIC Educational Resources Information Center

Hoijtink, Herbert; Molenaar, Ivo W.

1997-01-01

This paper shows that a certain class of constrained latent class models may be interpreted as a special case of nonparametric multidimensional item response models. Parameters of this latent class model are estimated using an application of the Gibbs sampler, and model fit is investigated using posterior predictive checks. (SLD)

Effectiveness of Multidimensional Family Therapy with Higher Severity Substance-Abusing Adolescents: Report from Two Randomized Controlled Trials

ERIC Educational Resources Information Center

Henderson, Craig E.; Dakof, Gayle A.; Greenbaum, Paul E.; Liddle, Howard A.

2010-01-01

Objective: We used growth mixture modeling to examine heterogeneity in treatment response in a secondary analysis of 2 randomized controlled trials testing multidimensional family therapy (MDFT), an established evidence-based therapy for adolescent drug abuse and delinquency. Method: The first study compared 2 evidence-based adolescent substance…

Comparison of Unidimensional and Multidimensional Approaches to IRT Parameter Estimation. Research Report. ETS RR-04-44

ERIC Educational Resources Information Center

Zhang, Jinming

2004-01-01

It is common to assume during statistical analysis of a multiscale assessment that the assessment has simple structure or that it is composed of several unidimensional subtests. Under this assumption, both the unidimensional and multidimensional approaches can be used to estimate item parameters. This paper theoretically demonstrates that these…

Analysis of complex neural circuits with nonlinear multidimensional hidden state models

PubMed Central

Friedman, Alexander; Slocum, Joshua F.; Tyulmankov, Danil; Gibb, Leif G.; Altshuler, Alex; Ruangwises, Suthee; Shi, Qinru; Toro Arana, Sebastian E.; Beck, Dirk W.; Sholes, Jacquelyn E. C.; Graybiel, Ann M.

2016-01-01

A universal need in understanding complex networks is the identification of individual information channels and their mutual interactions under different conditions. In neuroscience, our premier example, networks made up of billions of nodes dynamically interact to bring about thought and action. Granger causality is a powerful tool for identifying linear interactions, but handling nonlinear interactions remains an unmet challenge. We present a nonlinear multidimensional hidden state (NMHS) approach that achieves interaction strength analysis and decoding of networks with nonlinear interactions by including latent state variables for each node in the network. We compare NMHS to Granger causality in analyzing neural circuit recordings and simulations, improvised music, and sociodemographic data. We conclude that NMHS significantly extends the scope of analyses of multidimensional, nonlinear networks, notably in coping with the complexity of the brain. PMID:27222584

Toward the improvement of trail classification in national parks using the recreation opportunity spectrum approach.

PubMed

Oishi, Yoshitaka

2013-06-01

Trail settings in national parks are essential management tools for improving both ecological conservation efforts and the quality of visitor experiences. This study proposes a plan for the appropriate maintenance of trails in Chubusangaku National Park, Japan, based on the recreation opportunity spectrum (ROS) approach. First, we distributed 452 questionnaires to determine park visitors' preferences for setting a trail (response rate = 68 %). Respondents' preferences were then evaluated according to the following seven parameters: access, remoteness, naturalness, facilities and site management, social encounters, visitor impact, and visitor management. Using nonmetric multidimensional scaling and cluster analysis, the visitors were classified into seven groups. Last, we classified the actual trails according to the visitor questionnaire criteria to examine the discrepancy between visitors' preferences and actual trail settings. The actual trail classification indicated that while most developed trails were located in accessible places, primitive trails were located in remote areas. However, interestingly, two visitor groups seemed to prefer a well-conserved natural environment and, simultaneously, easily accessible trails. This finding does not correspond to a premise of the ROS approach, which supposes that primitive trails should be located in remote areas without ready access. Based on this study's results, we propose that creating trails, which afford visitors the opportunity to experience a well-conserved natural environment in accessible areas is a useful means to provide visitors with diverse recreation opportunities. The process of data collection and analysis in this study can be one approach to produce ROS maps for providing visitors with recreational opportunities of greater diversity and higher quality.

Beyond factor analysis: Multidimensionality and the Parkinson's Disease Sleep Scale-Revised.

PubMed

Pushpanathan, Maria E; Loftus, Andrea M; Gasson, Natalie; Thomas, Meghan G; Timms, Caitlin F; Olaithe, Michelle; Bucks, Romola S

2018-01-01

Many studies have sought to describe the relationship between sleep disturbance and cognition in Parkinson's disease (PD). The Parkinson's Disease Sleep Scale (PDSS) and its variants (the Parkinson's disease Sleep Scale-Revised; PDSS-R, and the Parkinson's Disease Sleep Scale-2; PDSS-2) quantify a range of symptoms impacting sleep in only 15 items. However, data from these scales may be problematic as included items have considerable conceptual breadth, and there may be overlap in the constructs assessed. Multidimensional measurement models, accounting for the tendency for items to measure multiple constructs, may be useful more accurately to model variance than traditional confirmatory factor analysis. In the present study, we tested the hypothesis that a multidimensional model (a bifactor model) is more appropriate than traditional factor analysis for data generated by these types of scales, using data collected using the PDSS-R as an exemplar. 166 participants diagnosed with idiopathic PD participated in this study. Using PDSS-R data, we compared three models: a unidimensional model; a 3-factor model consisting of sub-factors measuring insomnia, motor symptoms and obstructive sleep apnoea (OSA) and REM sleep behaviour disorder (RBD) symptoms; and, a confirmatory bifactor model with both a general factor and the same three sub-factors. Only the confirmatory bifactor model achieved satisfactory model fit, suggesting that PDSS-R data are multidimensional. There were differential associations between factor scores and patient characteristics, suggesting that some PDSS-R items, but not others, are influenced by mood and personality in addition to sleep symptoms. Multidimensional measurement models may also be a helpful tool in the PDSS and the PDSS-2 scales and may improve the sensitivity of these instruments.

Data-adaptive harmonic spectra and multilayer Stuart-Landau models

NASA Astrophysics Data System (ADS)

Chekroun, Mickaël D.; Kondrashov, Dmitri

2017-09-01

Harmonic decompositions of multivariate time series are considered for which we adopt an integral operator approach with periodic semigroup kernels. Spectral decomposition theorems are derived that cover the important cases of two-time statistics drawn from a mixing invariant measure. The corresponding eigenvalues can be grouped per Fourier frequency and are actually given, at each frequency, as the singular values of a cross-spectral matrix depending on the data. These eigenvalues obey, furthermore, a variational principle that allows us to define naturally a multidimensional power spectrum. The eigenmodes, as far as they are concerned, exhibit a data-adaptive character manifested in their phase which allows us in turn to define a multidimensional phase spectrum. The resulting data-adaptive harmonic (DAH) modes allow for reducing the data-driven modeling effort to elemental models stacked per frequency, only coupled at different frequencies by the same noise realization. In particular, the DAH decomposition extracts time-dependent coefficients stacked by Fourier frequency which can be efficiently modeled—provided the decay of temporal correlations is sufficiently well-resolved—within a class of multilayer stochastic models (MSMs) tailored here on stochastic Stuart-Landau oscillators. Applications to the Lorenz 96 model and to a stochastic heat equation driven by a space-time white noise are considered. In both cases, the DAH decomposition allows for an extraction of spatio-temporal modes revealing key features of the dynamics in the embedded phase space. The multilayer Stuart-Landau models (MSLMs) are shown to successfully model the typical patterns of the corresponding time-evolving fields, as well as their statistics of occurrence.

A general algorithm for peak-tracking in multi-dimensional NMR experiments.

PubMed

Ravel, P; Kister, G; Malliavin, T E; Delsuc, M A

2007-04-01

We present an algorithmic method allowing automatic tracking of NMR peaks in a series of spectra. It consists in a two phase analysis. The first phase is a local modeling of the peak displacement between two consecutive experiments using distance matrices. Then, from the coefficients of these matrices, a value graph containing the a priori set of possible paths used by these peaks is generated. On this set, the minimization under constraint of the target function by a heuristic approach provides a solution to the peak-tracking problem. This approach has been named GAPT, standing for General Algorithm for NMR Peak Tracking. It has been validated in numerous simulations resembling those encountered in NMR spectroscopy. We show the robustness and limits of the method for situations with many peak-picking errors, and presenting a high local density of peaks. It is then applied to the case of a temperature study of the NMR spectrum of the Lipid Transfer Protein (LTP).

Charged-particle motion in multidimensional magnetic-field turbulence

NASA Technical Reports Server (NTRS)

Giacalone, J.; Jokipii, J. R.

1994-01-01

We present a new analysis of the fundamental physics of charged-particle motion in a turbulent magnetic field using a numerical simulation. The magnetic field fluctuations are taken to be static and to have a power spectrum which is Kolmogorov. The charged particles are treated as test particles. It is shown that when the field turbulence is independent of one coordinate (i.e., k lies in a plane), the motion of these particles across the magnetic field is essentially zero, as required by theory. Consequently, the only motion across the average magnetic field direction that is allowed is that due to field-line random walk. On the other hand, when a fully three-dimensional realization of the turbulence is considered, the particles readily cross the field. Transport coefficients both along and across the ambient magnetic field are computed. This scheme provides a direct computation of the Fokker-Planck coefficients based on the motions of individual particles, and allows for comparison with analytic theory.

The multidimensional perturbation value: a single metric to measure similarity and activity of treatments in high-throughput multidimensional screens.

PubMed

Hutz, Janna E; Nelson, Thomas; Wu, Hua; McAllister, Gregory; Moutsatsos, Ioannis; Jaeger, Savina A; Bandyopadhyay, Somnath; Nigsch, Florian; Cornett, Ben; Jenkins, Jeremy L; Selinger, Douglas W

2013-04-01

Screens using high-throughput, information-rich technologies such as microarrays, high-content screening (HCS), and next-generation sequencing (NGS) have become increasingly widespread. Compared with single-readout assays, these methods produce a more comprehensive picture of the effects of screened treatments. However, interpreting such multidimensional readouts is challenging. Univariate statistics such as t-tests and Z-factors cannot easily be applied to multidimensional profiles, leaving no obvious way to answer common screening questions such as "Is treatment X active in this assay?" and "Is treatment X different from (or equivalent to) treatment Y?" We have developed a simple, straightforward metric, the multidimensional perturbation value (mp-value), which can be used to answer these questions. Here, we demonstrate application of the mp-value to three data sets: a multiplexed gene expression screen of compounds and genomic reagents, a microarray-based gene expression screen of compounds, and an HCS compound screen. In all data sets, active treatments were successfully identified using the mp-value, and simulations and follow-up analyses supported the mp-value's statistical and biological validity. We believe the mp-value represents a promising way to simplify the analysis of multidimensional data while taking full advantage of its richness.

Further Validation of the Multidimensional Fatigue Symptom Inventory-Short Form

PubMed Central

Stein, Kevin D.; Jacobsen, Paul B.; Blanchard, Chris M.; Thors, Christina

2008-01-01

A growing body of evidence is documenting the multidimensional nature of cancer-related fatigue. Although several multidimensional measures of fatigue have been developed, further validation of these scales is needed. To this end, the current study sought to evaluate the factorial and construct validity of the 30-item Multidimensional Fatigue Symptom Inventory-Short Form (MFSI-SF). A heterogeneous sample of 304 cancer patients (mean age 55 years) completed the MFSI-SF, along with several other measures of psychosocial functioning including the MOS-SF-36 and Fatigue Symptom Inventory, following the fourth cycle of chemotherapy treatment. The results of a confirmatory factor analysis indicated the 5-factor model provided a good fit to the data as evidenced by commonly used goodness of fit indices (CFI 0.90 and IFI 0.90). Additional evidence for the validity of the MFSI-SF was provided via correlations with other relevant instruments (range −0.21 to 0.82). In sum, the current study provides support for the MFSI-SF as a valuable tool for the multidimensional assessment of cancer-related fatigue. PMID:14711465

Exploring Children's Face-Space: A Multidimensional Scaling Analysis of the Mental Representation of Facial Identity

ERIC Educational Resources Information Center

Nishimura, Mayu; Maurer, Daphne; Gao, Xiaoqing

2009-01-01

We explored differences in the mental representation of facial identity between 8-year-olds and adults. The 8-year-olds and adults made similarity judgments of a homogeneous set of faces (individual hair cues removed) using an "odd-man-out" paradigm. Multidimensional scaling (MDS) analyses were performed to represent perceived similarity of faces…

A Multi-Dimensional Approach to Gradient Change in Phonological Acquisition: A Case Study of Disordered Speech Development

ERIC Educational Resources Information Center

Glaspey, Amy M.; MacLeod, Andrea A. N.

2010-01-01

The purpose of the current study is to document phonological change from a multidimensional perspective for a 3-year-old boy with phonological disorder by comparing three measures: (1) accuracy of consonant productions, (2) dynamic assessment, and (3) acoustic analysis. The methods included collecting a sample of the targets /s, [image omitted],…

Modification and Validation of the Multidimensional Scale of Perceived Social Support for Chinese School Teachers

ERIC Educational Resources Information Center

Ho, Sammy K.; Chan, Edmund S.

2017-01-01

This study aims to investigate the psychometric properties of the revised multidimensional scale of perceived social support (R-MSPSS) for Chinese school teachers. A questionnaire comprising the R-MSPSS and other psychological measures was administered to a sample of 539 school teachers in Hong Kong. A series of confirmatory factor analysis was…

Criteria of Career Success among Chinese Employees: Developing a Multidimensional Scale with Qualitative and Quantitative Approaches

ERIC Educational Resources Information Center

Zhou, Wenxia; Sun, Jianmin; Guan, Yanjun; Li, Yuhui; Pan, Jingzhou

2013-01-01

The current research aimed to develop a multidimensional measure on the criteria of career success in a Chinese context. Items on the criteria of career success were obtained using a qualitative approach among 30 Chinese employees; exploratory factor analysis was conducted to select items and determine the factor structure among a new sample of…

Measuring Healthcare Providers' Performances Within Managed Competition Using Multidimensional Quality and Cost Indicators.

PubMed

Portrait, France R M; van der Galiën, Onno; Van den Berg, Bernard

2016-04-01

The Dutch healthcare system is in transition towards managed competition. In theory, a system of managed competition involves incentives for quality and efficiency of provided care. This is mainly because health insurers contract on behalf of their clients with healthcare providers on, potentially, quality and costs. The paper develops a strategy to comprehensively analyse available multidimensional data on quality and costs to assess and report on the relative performance of healthcare providers within managed competition. We had access to individual information on 2409 clients of 19 Dutch diabetes care groups on a broad range of (outcome and process related) quality and cost indicators. We carried out a cost-consequences analysis and corrected for differences in case mix to reduce incentives for risk selection by healthcare providers. There is substantial heterogeneity between diabetes care groups' performances as measured using multidimensional indicators on quality and costs. Better quality diabetes care can be achieved with lower or higher costs. Routine monitoring using multidimensional data on quality and costs merged at the individual level would allow a systematic and comprehensive analysis of healthcare providers' performances within managed competition. Copyright © 2015 John Wiley & Sons, Ltd.

Development of a new multidimensional individual and interpersonal resilience measure for older adults.

PubMed

Martin, A'verria Sirkin; Distelberg, Brian; Palmer, Barton W; Jeste, Dilip V

2015-01-01

Develop an empirically grounded measure that can be used to assess family and individual resilience in a population of older adults (aged 50-99). Cross-sectional, self-report data from 1006 older adults were analyzed in two steps. The total sample was split into two subsamples and the first step identified the underlying latent structure through principal component exploratory factor analysis (EFA). The second step utilized the second half of the sample to validate the derived latent structure through confirmatory factor analysis (CFA). EFA produced an eight-factor structure that appeared clinically relevant for measuring the multidimensional nature of resilience. Factors included self-efficacy, access to social support network, optimism, perceived economic and social resources, spirituality and religiosity, relational accord, emotional expression and communication, and emotional regulation. CFA confirmed the eight-factor structure previously achieved with covariance between each of the factors. Based on these analyses we developed the multidimensional individual and interpersonal resilience measure, a broad assessment of resilience for older adults. This study highlights the multidimensional nature of resilience and introduces an individual and interpersonal resilience measure developed for older adults which is grounded in the individual and family resilience literature.

Development of a New Multidimensional Individual and Interpersonal Resilience Measure for Older Adults

PubMed Central

Martin, A’verria Sirkin; Distelberg, Brian; Palmer, Barton W.; Jeste, Dilip V.

2015-01-01

Objectives Develop an empirically grounded measure that can be used to assess family and individual resilience in a population of older adults (aged 50-99). Methods Cross-sectional, self-report data from 1,006 older adults were analyzed in two steps. The total sample was split into two sub-samples and the first step identified the underlying latent structure through principal component Exploratory Factor Analysis (EFA). The second step utilized the second half of the sample to validate the derived latent structure through Confirmatory Factor Analysis (CFA). Results EFA produced an eight-factor structure that appeared clinically relevant for measuring the multidimensional nature of resilience. Factors included self-efficacy, access to social support network, optimism, perceived economic and social resources, spirituality and religiosity, relational accord, emotional expression and communication, and emotional regulation. CFA confirmed the eight-factor structure previously achieved with covariance between each of the factors. Based on these analyses we developed the Multidimensional Individual and Interpersonal Resilience Measure (MIIRM), a broad assessment of resilience for older adults. Conclusion This study highlights the multidimensional nature of resilience and introduces an individual and interpersonal resilience measure developed for older adults which is grounded in the individual and family resilience literature. PMID:24787701

High resolution 4-D spectroscopy with sparse concentric shell sampling and FFT-CLEAN.

PubMed

Coggins, Brian E; Zhou, Pei

2008-12-01

Recent efforts to reduce the measurement time for multidimensional NMR experiments have fostered the development of a variety of new procedures for sampling and data processing. We recently described concentric ring sampling for 3-D NMR experiments, which is superior to radial sampling as input for processing by a multidimensional discrete Fourier transform. Here, we report the extension of this approach to 4-D spectroscopy as Randomized Concentric Shell Sampling (RCSS), where sampling points for the indirect dimensions are positioned on concentric shells, and where random rotations in the angular space are used to avoid coherent artifacts. With simulations, we show that RCSS produces a very low level of artifacts, even with a very limited number of sampling points. The RCSS sampling patterns can be adapted to fine rectangular grids to permit use of the Fast Fourier Transform in data processing, without an apparent increase in the artifact level. These artifacts can be further reduced to the noise level using the iterative CLEAN algorithm developed in radioastronomy. We demonstrate these methods on the high resolution 4-D HCCH-TOCSY spectrum of protein G's B1 domain, using only 1.2% of the sampling that would be needed conventionally for this resolution. The use of a multidimensional FFT instead of the slow DFT for initial data processing and for subsequent CLEAN significantly reduces the calculation time, yielding an artifact level that is on par with the level of the true spectral noise.

High Resolution 4-D Spectroscopy with Sparse Concentric Shell Sampling and FFT-CLEAN

PubMed Central

Coggins, Brian E.; Zhou, Pei

2009-01-01

SUMMARY Recent efforts to reduce the measurement time for multidimensional NMR experiments have fostered the development of a variety of new procedures for sampling and data processing. We recently described concentric ring sampling for 3-D NMR experiments, which is superior to radial sampling as input for processing by a multidimensional discrete Fourier transform. Here, we report the extension of this approach to 4-D spectroscopy as Randomized Concentric Shell Sampling (RCSS), where sampling points for the indirect dimensions are positioned on concentric shells, and where random rotations in the angular space are used to avoid coherent artifacts. With simulations, we show that RCSS produces a very low level of artifacts, even with a very limited number of sampling points. The RCSS sampling patterns can be adapted to fine rectangular grids to permit use of the Fast Fourier Transform in data processing, without an apparent increase in the artifact level. These artifacts can be further reduced to the noise level using the iterative CLEAN algorithm developed in radioastronomy. We demonstrate these methods on the high resolution 4-D HCCH-TOCSY spectrum of protein G's B1 domain, using only 1.2% of the sampling that would be needed conventionally for this resolution. The use of a multidimensional FFT instead of the slow DFT for initial data processing and for subsequent CLEAN significantly reduces the calculation time, yielding an artifact level that is on par with the level of the true spectral noise. PMID:18853260

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry combined with multidimensional scaling, binary hierarchical cluster tree and selected diagnostic masses improves species identification of Neolithic keratin sequences from furs of the Tyrolean Iceman Oetzi.

PubMed

Hollemeyer, Klaus; Altmeyer, Wolfgang; Heinzle, Elmar; Pitra, Christian

2012-08-30

The identification of fur origins from the 5300-year-old Tyrolean Iceman's accoutrement is not yet complete, although definite identification is essential for the socio-cultural context of his epoch. Neither have all potential samples been identified so far, nor there has a consensus been reached on the species identified using the classical methods. Archaeological hair often lacks analyzable hair scale patterns in microscopic analyses and polymer chain reaction (PCR)-based techniques are often inapplicable due to the lack of amplifiable ancient DNA. To overcome these drawbacks, a matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) method was used exclusively based on hair keratins. Thirteen fur specimens from his accoutrement were analyzed after tryptic digest of native hair. Peptide mass fingerprints (pmfs) from ancient samples and from reference species mostly occurring in the Alpine surroundings at his lifetime were compared to each other using multidimensional scaling and binary hierarchical cluster tree analysis. Both statistical methods highly reflect spectral similarities among pmfs as close zoological relationships. While multidimensional scaling was useful to discriminate specimens on the zoological order level, binary hierarchical cluster tree reached the family or subfamily level. Additionally, the presence and/or absence of order, family and/or species-specific diagnostic masses in their pmfs allowed the identification of mammals mostly down to single species level. Red deer was found in his shoe vamp, goat in the leggings, cattle in his shoe sole and at his quiver's closing flap as well as sheep and chamois in his coat. Canid species, like grey wolf, domestic dog or European red fox, were discovered in his leggings for the first time, but could not be differentiated to species level. This is widening the spectrum of processed fur-bearing species to at least one member of the Canidae family. His fur cap was allocated to a carnivore species, but differentiation between brown bear and a canid species could not be made with certainty. Copyright © 2012 John Wiley & Sons, Ltd.

Discrete decoding based ultrafast multidimensional nuclear magnetic resonance spectroscopy

NASA Astrophysics Data System (ADS)

Wei, Zhiliang; Lin, Liangjie; Ye, Qimiao; Li, Jing; Cai, Shuhui; Chen, Zhong

2015-07-01

The three-dimensional (3D) nuclear magnetic resonance (NMR) spectroscopy constitutes an important and powerful tool in analyzing chemical and biological systems. However, the abundant 3D information arrives at the expense of long acquisition times lasting hours or even days. Therefore, there has been a continuous interest in developing techniques to accelerate recordings of 3D NMR spectra, among which the ultrafast spatiotemporal encoding technique supplies impressive acquisition speed by compressing a multidimensional spectrum in a single scan. However, it tends to suffer from tradeoffs among spectral widths in different dimensions, which deteriorates in cases of NMR spectroscopy with more dimensions. In this study, the discrete decoding is proposed to liberate the ultrafast technique from tradeoffs among spectral widths in different dimensions by focusing decoding on signal-bearing sites. For verifying its feasibility and effectiveness, we utilized the method to generate two different types of 3D spectra. The proposed method is also applicable to cases with more than three dimensions, which, based on the experimental results, may widen applications of the ultrafast technique.

Structure and Membrane Interactions of the Antibiotic Peptide Dermadistinctin K by Multidimensional Solution and Oriented 15N and 31P Solid-State NMR Spectroscopy

PubMed Central

Verly, Rodrigo M.; Moraes, Cléria Mendonça de; Resende, Jarbas M.; Aisenbrey, Christopher; Bemquerer, Marcelo Porto; Piló-Veloso, Dorila; Valente, Ana Paula; Almeida, Fábio C.L.; Bechinger, Burkhard

2009-01-01

DD K, a peptide first isolated from the skin secretion of the Phyllomedusa distincta frog, has been prepared by solid-phase chemical peptide synthesis and its conformation was studied in trifluoroethanol/water as well as in the presence of sodium dodecyl sulfate and dodecylphosphocholine micelles or small unilamellar vesicles. Multidimensional solution NMR spectroscopy indicates an α-helical conformation in membrane environments starting at residue 7 and extending to the C-terminal carboxyamide. Furthermore, DD K has been labeled with 15N at a single alanine position that is located within the helical core region of the sequence. When reconstituted into oriented phosphatidylcholine membranes the resulting 15N solid-state NMR spectrum shows a well-defined helix alignment parallel to the membrane surface in excellent agreement with the amphipathic character of DD K. Proton-decoupled 31P solid-state NMR spectroscopy indicates that the peptide creates a high level of disorder at the level of the phospholipid headgroup suggesting that DD K partitions into the bilayer where it severely disrupts membrane packing. PMID:19289046

Assessing the multidimensionality of coastal erosion risks: public participation and multicriteria analysis in a Mediterranean coastal system.

PubMed

Roca, Elisabet; Gamboa, Gonzalo; Tàbara, J David

2008-04-01

The complex and multidimensional nature of coastal erosion risks makes it necessary to move away from single-perspective assessment and management methods that have conventionally predominated in coastal management. This article explores the suitability of participatory multicriteria analysis (MCA) for improving the integration of diverse expertises and values and enhancing the social-ecological robustness of the processes that lead to the definition of relevant policy options to deal with those risks. We test this approach in the Mediterranean coastal locality of Lido de Sète in France. Results show that the more adaptive alternatives such as "retreating the shoreline" were preferred by our selected stakeholders to those corresponding to "protecting the shoreline" and the business as usual proposals traditionally put forward by experts and policymakers on these matters. Participative MCA contributed to represent coastal multidimensionality, elicit and integrate different views and preferences, facilitated knowledge exchange, and allowed highlighting existing uncertainties.

Positive Traits in the Bipolar Spectrum: The Space between Madness and Genius

PubMed Central

Greenwood, Tiffany A.

2017-01-01

Bipolar disorder is a severe, lifelong mood disorder for which little is currently understood of the genetic mechanisms underlying risk. By examining related dimensional phenotypes, we may further our understanding of the disorder. Creativity has a historical connection with the bipolar spectrum and is particularly enhanced among unaffected first-degree relatives and those with bipolar spectrum traits. This suggests that some aspects of the bipolar spectrum may confer advantages, while more severe expressions of symptoms negatively influence creative accomplishment. Creativity is a complex, multidimensional construct with both cognitive and affective components, many of which appear to reflect a shared genetic vulnerability with bipolar disorder. It is suggested that a subset of bipolar risk variants confer advantages as positive traits according to an inverted-U-shaped curve with clinically unaffected allele carriers benefitting from the positive traits and serving to maintain the risk alleles in the population. The association of risk genes with creativity in healthy individuals (e.g., NRG1), as well as an overall sharing of common genetic variation between bipolar patients and creative individuals, provides support for this model. Current findings are summarized from a multidisciplinary perspective to demonstrate the feasibility of research in this area to reveal the mechanisms underlying illness. PMID:28277566

Analysis of precipitation data in Bangladesh through hierarchical clustering and multidimensional scaling

NASA Astrophysics Data System (ADS)

Rahman, Md. Habibur; Matin, M. A.; Salma, Umma

2017-12-01

The precipitation patterns of seventeen locations in Bangladesh from 1961 to 2014 were studied using a cluster analysis and metric multidimensional scaling. In doing so, the current research applies four major hierarchical clustering methods to precipitation in conjunction with different dissimilarity measures and metric multidimensional scaling. A variety of clustering algorithms were used to provide multiple clustering dendrograms for a mixture of distance measures. The dendrogram of pre-monsoon rainfall for the seventeen locations formed five clusters. The pre-monsoon precipitation data for the areas of Srimangal and Sylhet were located in two clusters across the combination of five dissimilarity measures and four hierarchical clustering algorithms. The single linkage algorithm with Euclidian and Manhattan distances, the average linkage algorithm with the Minkowski distance, and Ward's linkage algorithm provided similar results with regard to monsoon precipitation. The results of the post-monsoon and winter precipitation data are shown in different types of dendrograms with disparate combinations of sub-clusters. The schematic geometrical representations of the precipitation data using metric multidimensional scaling showed that the post-monsoon rainfall of Cox's Bazar was located far from those of the other locations. The results of a box-and-whisker plot, different clustering techniques, and metric multidimensional scaling indicated that the precipitation behaviour of Srimangal and Sylhet during the pre-monsoon season, Cox's Bazar and Sylhet during the monsoon season, Maijdi Court and Cox's Bazar during the post-monsoon season, and Cox's Bazar and Khulna during the winter differed from those at other locations in Bangladesh.

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.

PedsQL™ Multidimensional Fatigue Scale in sickle cell disease: feasibility, reliability, and validity.

PubMed

Panepinto, Julie A; Torres, Sylvia; Bendo, Cristiane B; McCavit, Timothy L; Dinu, Bogdan; Sherman-Bien, Sandra; Bemrich-Stolz, Christy; Varni, James W

2014-01-01

Sickle cell disease (SCD) is an inherited blood disorder characterized by a chronic hemolytic anemia that can contribute to fatigue and global cognitive impairment in patients. The study objective was to report on the feasibility, reliability, and validity of the PedsQL™ Multidimensional Fatigue Scale in SCD for pediatric patient self-report ages 5-18 years and parent proxy-report for ages 2-18 years. This was a cross-sectional multi-site study whereby 240 pediatric patients with SCD and 303 parents completed the 18-item PedsQL™ Multidimensional Fatigue Scale. Participants also completed the PedsQL™ 4.0 Generic Core Scales. The PedsQL™ Multidimensional Fatigue Scale evidenced excellent feasibility, excellent reliability for the Total Scale Scores (patient self-report α = 0.90; parent proxy-report α = 0.95), and acceptable reliability for the three individual scales (patient self-report α = 0.77-0.84; parent proxy-report α = 0.90-0.97). Intercorrelations of the PedsQL™ Multidimensional Fatigue Scale with the PedsQL™ Generic Core Scales were predominantly in the large (≥0.50) range, supporting construct validity. PedsQL™ Multidimensional Fatigue Scale Scores were significantly worse with large effects sizes (≥0.80) for patients with SCD than for a comparison sample of healthy children, supporting known-groups discriminant validity. Confirmatory factor analysis demonstrated an acceptable to excellent model fit in SCD. The PedsQL™ Multidimensional Fatigue Scale demonstrated acceptable to excellent measurement properties in SCD. The results demonstrate the relative severity of fatigue symptoms in pediatric patients with SCD, indicating the potential clinical utility of multidimensional assessment of fatigue in patients with SCD in clinical research and practice. © 2013 Wiley Periodicals, Inc.

PedsQL™ Multidimensional Fatigue Scale in Sickle Cell Disease: Feasibility, Reliability and Validity

PubMed Central

Panepinto, Julie A.; Torres, Sylvia; Bendo, Cristiane B.; McCavit, Timothy L.; Dinu, Bogdan; Sherman-Bien, Sandra; Bemrich-Stolz, Christy; Varni, James W.

2013-01-01

Background Sickle cell disease (SCD) is an inherited blood disorder characterized by a chronic hemolytic anemia that can contribute to fatigue and global cognitive impairment in patients. The study objective was to report on the feasibility, reliability, and validity of the PedsQL™ Multidimensional Fatigue Scale in SCD for pediatric patient self-report ages 5–18 years and parent proxy-report for ages 2–18 years. Procedure This was a cross-sectional multi-site study whereby 240 pediatric patients with SCD and 303 parents completed the 18-item PedsQL™ Multidimensional Fatigue Scale. Participants also completed the PedsQL™ 4.0 Generic Core Scales. Results The PedsQL™ Multidimensional Fatigue Scale evidenced excellent feasibility, excellent reliability for the Total Scale Scores (patient self-report α = 0.90; parent proxy-report α = 0.95), and acceptable reliability for the three individual scales (patient self-report α = 0.77–0.84; parent proxy-report α = 0.90–0.97). Intercorrelations of the PedsQL™ Multidimensional Fatigue Scale with the PedsQL™ Generic Core Scales were predominantly in the large (≥ 0.50) range, supporting construct validity. PedsQL™ Multidimensional Fatigue Scale Scores were significantly worse with large effects sizes (≥0.80) for patients with SCD than for a comparison sample of healthy children, supporting known-groups discriminant validity. Confirmatory factor analysis demonstrated an acceptable to excellent model fit in SCD. Conclusions The PedsQL™ Multidimensional Fatigue Scale demonstrated acceptable to excellent measurement properties in SCD. The results demonstrate the relative severity of fatigue symptoms in pediatric patients with SCD, indicating the potential clinical utility of multidimensional assessment of fatigue in patients with SCD in clinical research and practice. PMID:24038960

Development of multi-dimensional body image scale for malaysian female adolescents

PubMed Central

Taib, Mohd Nasir Mohd; Shariff, Zalilah Mohd; Khor, Geok Lin

2008-01-01

The present study was conducted to develop a Multi-dimensional Body Image Scale for Malaysian female adolescents. Data were collected among 328 female adolescents from a secondary school in Kuantan district, state of Pahang, Malaysia by using a self-administered questionnaire and anthropometric measurements. The self-administered questionnaire comprised multiple measures of body image, Eating Attitude Test (EAT-26; Garner & Garfinkel, 1979) and Rosenberg Self-esteem Inventory (Rosenberg, 1965). The 152 items from selected multiple measures of body image were examined through factor analysis and for internal consistency. Correlations between Multi-dimensional Body Image Scale and body mass index (BMI), risk of eating disorders and self-esteem were assessed for construct validity. A seven factor model of a 62-item Multi-dimensional Body Image Scale for Malaysian female adolescents with construct validity and good internal consistency was developed. The scale encompasses 1) preoccupation with thinness and dieting behavior, 2) appearance and body satisfaction, 3) body importance, 4) muscle increasing behavior, 5) extreme dieting behavior, 6) appearance importance, and 7) perception of size and shape dimensions. Besides, a multidimensional body image composite score was proposed to screen negative body image risk in female adolescents. The result found body image was correlated with BMI, risk of eating disorders and self-esteem in female adolescents. In short, the present study supports a multi-dimensional concept for body image and provides a new insight into its multi-dimensionality in Malaysian female adolescents with preliminary validity and reliability of the scale. The Multi-dimensional Body Image Scale can be used to identify female adolescents who are potentially at risk of developing body image disturbance through future intervention programs. PMID:20126371

Development of multi-dimensional body image scale for malaysian female adolescents.

PubMed

Chin, Yit Siew; Taib, Mohd Nasir Mohd; Shariff, Zalilah Mohd; Khor, Geok Lin

2008-01-01

The present study was conducted to develop a Multi-dimensional Body Image Scale for Malaysian female adolescents. Data were collected among 328 female adolescents from a secondary school in Kuantan district, state of Pahang, Malaysia by using a self-administered questionnaire and anthropometric measurements. The self-administered questionnaire comprised multiple measures of body image, Eating Attitude Test (EAT-26; Garner & Garfinkel, 1979) and Rosenberg Self-esteem Inventory (Rosenberg, 1965). The 152 items from selected multiple measures of body image were examined through factor analysis and for internal consistency. Correlations between Multi-dimensional Body Image Scale and body mass index (BMI), risk of eating disorders and self-esteem were assessed for construct validity. A seven factor model of a 62-item Multi-dimensional Body Image Scale for Malaysian female adolescents with construct validity and good internal consistency was developed. The scale encompasses 1) preoccupation with thinness and dieting behavior, 2) appearance and body satisfaction, 3) body importance, 4) muscle increasing behavior, 5) extreme dieting behavior, 6) appearance importance, and 7) perception of size and shape dimensions. Besides, a multidimensional body image composite score was proposed to screen negative body image risk in female adolescents. The result found body image was correlated with BMI, risk of eating disorders and self-esteem in female adolescents. In short, the present study supports a multi-dimensional concept for body image and provides a new insight into its multi-dimensionality in Malaysian female adolescents with preliminary validity and reliability of the scale. The Multi-dimensional Body Image Scale can be used to identify female adolescents who are potentially at risk of developing body image disturbance through future intervention programs.

Multi-dimensional scores to predict mortality in patients with idiopathic pulmonary fibrosis undergoing lung transplantation assessment.

PubMed

Fisher, Jolene H; Al-Hejaili, Faris; Kandel, Sonja; Hirji, Alim; Shapera, Shane; Mura, Marco

2017-04-01

The heterogeneous progression of idiopathic pulmonary fibrosis (IPF) makes prognostication difficult and contributes to high mortality on the waitlist for lung transplantation (LTx). Multi-dimensional scores (Composite Physiologic index [CPI], [Gender-Age-Physiology [GAP]; RIsk Stratification scorE [RISE]) demonstrated enhanced predictive power towards outcome in IPF. The lung allocation score (LAS) is a multi-dimensional tool commonly used to stratify patients assessed for LTx. We sought to investigate whether IPF-specific multi-dimensional scores predict mortality in patients with IPF assessed for LTx. The study included 302 patients with IPF who underwent a LTx assessment (2003-2014). Multi-dimensional scores were calculated. The primary outcome was 12-month mortality after assessment. LTx was considered as competing event in all analyses. At the end of the observation period, there were 134 transplants, 63 deaths, and 105 patients were alive without LTx. Multi-dimensional scores predicted mortality with accuracy similar to LAS, and superior to that of individual variables: area under the curve (AUC) for LAS was 0.78 (sensitivity 71%, specificity 86%); CPI 0.75 (sensitivity 67%, specificity 82%); GAP 0.67 (sensitivity 59%, specificity 74%); RISE 0.78 (sensitivity 71%, specificity 84%). A separate analysis conducted only in patients actively listed for LTx (n = 247; 50 deaths) yielded similar results. In patients with IPF assessed for LTx as well as in those actually listed, multi-dimensional scores predict mortality better than individual variables, and with accuracy similar to the LAS. If validated, multi-dimensional scores may serve as inexpensive tools to guide decisions on the timing of referral and listing for LTx. Copyright © 2017 Elsevier Ltd. All rights reserved.

Inferring the Joint Demographic History of Multiple Populations from Multidimensional SNP Frequency Data

PubMed Central

Gutenkunst, Ryan N.; Hernandez, Ryan D.; Williamson, Scott H.; Bustamante, Carlos D.

2009-01-01

Demographic models built from genetic data play important roles in illuminating prehistorical events and serving as null models in genome scans for selection. We introduce an inference method based on the joint frequency spectrum of genetic variants within and between populations. For candidate models we numerically compute the expected spectrum using a diffusion approximation to the one-locus, two-allele Wright-Fisher process, involving up to three simultaneous populations. Our approach is a composite likelihood scheme, since linkage between neutral loci alters the variance but not the expectation of the frequency spectrum. We thus use bootstraps incorporating linkage to estimate uncertainties for parameters and significance values for hypothesis tests. Our method can also incorporate selection on single sites, predicting the joint distribution of selected alleles among populations experiencing a bevy of evolutionary forces, including expansions, contractions, migrations, and admixture. We model human expansion out of Africa and the settlement of the New World, using 5 Mb of noncoding DNA resequenced in 68 individuals from 4 populations (YRI, CHB, CEU, and MXL) by the Environmental Genome Project. We infer divergence between West African and Eurasian populations 140 thousand years ago (95% confidence interval: 40–270 kya). This is earlier than other genetic studies, in part because we incorporate migration. We estimate the European (CEU) and East Asian (CHB) divergence time to be 23 kya (95% c.i.: 17–43 kya), long after archeological evidence places modern humans in Europe. Finally, we estimate divergence between East Asians (CHB) and Mexican-Americans (MXL) of 22 kya (95% c.i.: 16.3–26.9 kya), and our analysis yields no evidence for subsequent migration. Furthermore, combining our demographic model with a previously estimated distribution of selective effects among newly arising amino acid mutations accurately predicts the frequency spectrum of nonsynonymous variants across three continental populations (YRI, CHB, CEU). PMID:19851460

NMR analysis of a kinetically trapped intermediate of a disulfide-deficient mutant of the starch-binding domain of glucoamylase.

PubMed

Sugimoto, Hayuki; Noda, Yasuo; Segawa, Shin-ichi

2011-09-16

A thermally unfolded disulfide-deficient mutant of the starch-binding domain of glucoamylase refolds into a kinetically trapped metastable intermediate when subjected to a rapid lowering of temperature. We attempted to characterise this intermediate using multidimensional NMR spectroscopy. The (1)H-(15)N heteronuclear single quantum coherence spectrum after a rapid temperature decrease (the spectrum of the intermediate) showed good chemical shift dispersion but was significantly different from that of the native state, suggesting that the intermediate adopts a nonnative but well-structured conformation. Large chemical shift changes for the backbone amide protons between the native and the intermediate states were observed for residues in the β-sheet consisting of strands 2, 3, 5, 6, and 7 as well as in the C-terminal region. These residues were found to be in close proximity to aromatic residues, suggesting that the chemical shift changes are mainly due to ring current shifts caused by the aromatic residues. The two-dimensional nuclear Overhauser enhancement (NOE) spectroscopy experiments showed that the intermediate contained substantial, native-like NOE connectivities, although there were fewer cross peaks in the spectrum of the intermediate compared with that of the native state. It was also shown that there were native-like interresidue NOEs for residues buried in the protein, whereas many of the NOE cross peaks were lost for the residues involved in a surface-exposed aromatic cluster. These results suggest that, in the intermediate, the aromatic cluster at the surface is structurally less organised, whereas the interior of the protein has relatively rigid, native-like side-chain packing. Copyright © 2011 Elsevier Ltd. All rights reserved.

Modular Spectral Inference Framework Applied to Young Stars and Brown Dwarfs

NASA Technical Reports Server (NTRS)

Gully-Santiago, Michael A.; Marley, Mark S.

2017-01-01

In practice, synthetic spectral models are imperfect, causing inaccurate estimates of stellar parameters. Using forward modeling and statistical inference, we derive accurate stellar parameters for a given observed spectrum by emulating a grid of precomputed spectra to track uncertainties. Spectral inference as applied to brown dwarfs re: Synthetic spectral models (Marley et al 1996 and 2014) via the newest grid spans a massive multi-dimensional grid applied to IGRINS spectra, improving atmospheric models for JWST. When applied to young stars(10Myr) with large starpots, they can be measured spectroscopically, especially in the near-IR with IGRINS.

CFD Techniques for Propulsion Applications

NASA Technical Reports Server (NTRS)

1992-01-01

The symposium was composed of the following sessions: turbomachinery computations and validations; flow in ducts, intakes, and nozzles; and reacting flows. Forty papers were presented, and they covered full 3-D code validation and numerical techniques; multidimensional reacting flow; and unsteady viscous flow for the entire spectrum of propulsion system components. The capabilities of the various numerical techniques were assessed and significant new developments were identified. The technical evaluation spells out where progress has been made and concludes that the present state of the art has almost reached the level necessary to tackle the comprehensive topic of computational fluid dynamics (CFD) validation for propulsion.

Cosmic mass spectrometer

NASA Astrophysics Data System (ADS)

Anchordoqui, Luis A.; Barger, Vernon; Weiler, Thomas J.

2018-03-01

We argue that if ultrahigh-energy (E ≳1010GeV) cosmic rays are heavy nuclei (as indicated by existing data), then the pointing of cosmic rays to their nearest extragalactic sources is expected for 1010.6 ≲ E /GeV ≲1011. This is because for a nucleus of charge Ze and baryon number A, the bending of the cosmic ray decreases as Z / E with rising energy, so that pointing to nearby sources becomes possible in this particular energy range. In addition, the maximum energy of acceleration capability of the sources grows linearly in Z, while the energy loss per distance traveled decreases with increasing A. Each of these two points tend to favor heavy nuclei at the highest energies. The traditional bi-dimensional analyses, which simultaneously reproduce Auger data on the spectrum and nuclear composition, may not be capable of incorporating the relative importance of all these phenomena. In this paper we propose a multi-dimensional reconstruction of the individual emission spectra (in E, direction, and cross-correlation with nearby putative sources) to study the hypothesis that primaries are heavy nuclei subject to GZK photo-disintegration, and to determine the nature of the extragalactic sources. More specifically, we propose to combine information on nuclear composition and arrival direction to associate a potential clustering of events with a 3-dimensional position in the sky. Actually, both the source distance and maximum emission energy can be obtained through a multi-parameter likelihood analysis to accommodate the observed nuclear composition of each individual event in the cluster. We show that one can track the level of GZK interactions on an statistical basis by comparing the maximum energy at the source of each cluster. We also show that nucleus-emitting-sources exhibit a cepa stratis structure on Earth which could be pealed off by future space-missions, such as POEMMA. Finally, we demonstrate that metal-rich starburst galaxies are highly-plausible candidate sources, and we use them as an explicit example of our proposed multi-dimensional analysis.

Acoustic structure of the five perceptual dimensions of timbre in orchestral instrument tones

PubMed Central

Elliott, Taffeta M.; Hamilton, Liberty S.; Theunissen, Frédéric E.

2013-01-01

Attempts to relate the perceptual dimensions of timbre to quantitative acoustical dimensions have been tenuous, leading to claims that timbre is an emergent property, if measurable at all. Here, a three-pronged analysis shows that the timbre space of sustained instrument tones occupies 5 dimensions and that a specific combination of acoustic properties uniquely determines gestalt perception of timbre. Firstly, multidimensional scaling (MDS) of dissimilarity judgments generated a perceptual timbre space in which 5 dimensions were cross-validated and selected by traditional model comparisons. Secondly, subjects rated tones on semantic scales. A discriminant function analysis (DFA) accounting for variance of these semantic ratings across instruments and between subjects also yielded 5 significant dimensions with similar stimulus ordination. The dimensions of timbre space were then interpreted semantically by rotational and reflectional projection of the MDS solution into two DFA dimensions. Thirdly, to relate this final space to acoustical structure, the perceptual MDS coordinates of each sound were regressed with its joint spectrotemporal modulation power spectrum. Sound structures correlated significantly with distances in perceptual timbre space. Contrary to previous studies, most perceptual timbre dimensions are not the result of purely temporal or spectral features but instead depend on signature spectrotemporal patterns. PMID:23297911

Analysis of ligand-protein exchange by Clustering of Ligand Diffusion Coefficient Pairs (CoLD-CoP).

PubMed

Snyder, David A; Chantova, Mihaela; Chaudhry, Saadia

2015-06-01

NMR spectroscopy is a powerful tool in describing protein structures and protein activity for pharmaceutical and biochemical development. This study describes a method to determine weak binding ligands in biological systems by using hierarchic diffusion coefficient clustering of multidimensional data obtained with a 400 MHz Bruker NMR. Comparison of DOSY spectrums of ligands of the chemical library in the presence and absence of target proteins show translational diffusion rates for small molecules upon interaction with macromolecules. For weak binders such as compounds found in fragment libraries, changes in diffusion rates upon macromolecular binding are on the order of the precision of DOSY diffusion measurements, and identifying such subtle shifts in diffusion requires careful statistical analysis. The "CoLD-CoP" (Clustering of Ligand Diffusion Coefficient Pairs) method presented here uses SAHN clustering to identify protein-binders in a chemical library or even a not fully characterized metabolite mixture. We will show how DOSY NMR and the "CoLD-CoP" method complement each other in identifying the most suitable candidates for lysozyme and wheat germ acid phosphatase. Copyright © 2015 Elsevier Inc. All rights reserved.

Influence of Multidimensionality on Convergence of Sampling in Protein Simulation

NASA Astrophysics Data System (ADS)

Metsugi, Shoichi

2005-06-01

We study the problem of convergence of sampling in protein simulation originating in the multidimensionality of protein’s conformational space. Since several important physical quantities are given by second moments of dynamical variables, we attempt to obtain the time of simulation necessary for their sufficient convergence. We perform a molecular dynamics simulation of a protein and the subsequent principal component (PC) analysis as a function of simulation time T. As T increases, PC vectors with smaller amplitude of variations are identified and their amplitudes are equilibrated before identifying and equilibrating vectors with larger amplitude of variations. This sequential identification and equilibration mechanism makes protein simulation a useful method although it has an intrinsic multidimensional nature.

Nmrglue: an open source Python package for the analysis of multidimensional NMR data.

PubMed

Helmus, Jonathan J; Jaroniec, Christopher P

2013-04-01

Nmrglue, an open source Python package for working with multidimensional NMR data, is described. When used in combination with other Python scientific libraries, nmrglue provides a highly flexible and robust environment for spectral processing, analysis and visualization and includes a number of common utilities such as linear prediction, peak picking and lineshape fitting. The package also enables existing NMR software programs to be readily tied together, currently facilitating the reading, writing and conversion of data stored in Bruker, Agilent/Varian, NMRPipe, Sparky, SIMPSON, and Rowland NMR Toolkit file formats. In addition to standard applications, the versatility offered by nmrglue makes the package particularly suitable for tasks that include manipulating raw spectrometer data files, automated quantitative analysis of multidimensional NMR spectra with irregular lineshapes such as those frequently encountered in the context of biomacromolecular solid-state NMR, and rapid implementation and development of unconventional data processing methods such as covariance NMR and other non-Fourier approaches. Detailed documentation, install files and source code for nmrglue are freely available at http://nmrglue.com. The source code can be redistributed and modified under the New BSD license.

Nmrglue: An Open Source Python Package for the Analysis of Multidimensional NMR Data

PubMed Central

Helmus, Jonathan J.; Jaroniec, Christopher P.

2013-01-01

Nmrglue, an open source Python package for working with multidimensional NMR data, is described. When used in combination with other Python scientific libraries, nmrglue provides a highly flexible and robust environment for spectral processing, analysis and visualization and includes a number of common utilities such as linear prediction, peak picking and lineshape fitting. The package also enables existing NMR software programs to be readily tied together, currently facilitating the reading, writing and conversion of data stored in Bruker, Agilent/Varian, NMRPipe, Sparky, SIMPSON, and Rowland NMR Toolkit file formats. In addition to standard applications, the versatility offered by nmrglue makes the package particularly suitable for tasks that include manipulating raw spectrometer data files, automated quantitative analysis of multidimensional NMR spectra with irregular lineshapes such as those frequently encountered in the context of biomacromolecular solid-state NMR, and rapid implementation and development of unconventional data processing methods such as covariance NMR and other non-Fourier approaches. Detailed documentation, install files and source code for nmrglue are freely available at http://nmrglue.com. The source code can be redistributed and modified under the New BSD license. PMID:23456039

Situation exploration in a persistent surveillance system with multidimensional data

NASA Astrophysics Data System (ADS)

Habibi, Mohammad S.

2013-03-01

There is an emerging need for fusing hard and soft sensor data in an efficient surveillance system to provide accurate estimation of situation awareness. These mostly abstract, multi-dimensional and multi-sensor data pose a great challenge to the user in performing analysis of multi-threaded events efficiently and cohesively. To address this concern an interactive Visual Analytics (VA) application is developed for rapid assessment and evaluation of different hypotheses based on context-sensitive ontology spawn from taxonomies describing human/human and human/vehicle/object interactions. A methodology is described here for generating relevant ontology in a Persistent Surveillance System (PSS) and demonstrates how they can be utilized in the context of PSS to track and identify group activities pertaining to potential threats. The proposed VA system allows for visual analysis of raw data as well as metadata that have spatiotemporal representation and content-based implications. Additionally in this paper, a technique for rapid search of tagged information contingent to ranking and confidence is explained for analysis of multi-dimensional data. Lastly the issue of uncertainty associated with processing and interpretation of heterogeneous data is also addressed.

Multidimensional Mixing Behavior of Steam-Water Flow in a Downcomer Annulus During LBLOCA Reflood Phase with a Direct Vessel Injection Mode

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kwon, Tae-Soon; Yun, Byong-Jo; Euh, Dong-Jin

Multidimensional thermal-hydraulic behavior in the downcomer annulus of a pressurized water reactor (PWR) vessel with a direct vessel injection mode is presented based on the experimental observation in the MIDAS (multidimensional investigation in downcomer annulus simulation) steam-water test facility. From the steady-state test results to simulate the late reflood phase of a large-break loss-of-coolant accident (LBLOCA), isothermal lines show the multidimensional phenomena of a phasic interaction between steam and water in the downcomer annulus very well. MIDAS is a steam-water separate effect test facility, which is 1/4.93 linearly scaled down to a 1400-MW(electric) PWR type of a nuclear reactor, focusedmore » on understanding multidimensional thermal-hydraulic phenomena in a downcomer annulus with various types of safety injection during the refill or reflood phase of an LBLOCA. The initial and the boundary conditions are scaled from the pretest analysis based on the preliminary calculation using the TRAC code. The superheated steam with a superheating degree of 80 K at a given downcomer pressure of 180 kPa is injected equally through three intact cold legs into the downcomer.« less

Multidimensional poverty measure and analysis: a case study from Hechi City, China.

PubMed

Wang, Yanhui; Wang, Baixue

2016-01-01

Aiming at the anti-poverty outline of China and the human-environment sustainable development, we propose a multidimensional poverty measure and analysis methodology for measuring the poverty-stricken counties and their contributing factors. We build a set of multidimensional poverty indicators with Chinese characteristics, integrating A-F double cutoffs, dimensional aggregation and decomposition approach, and GIS spatial analysis to evaluate the poor's multidimensional poverty characteristics under different geographic and socioeconomic conditions. The case study from 11 counties of Hechi City shows that, firstly, each county existed at least four respects of poverty, and overall the poverty level showed the spatial pattern of surrounding higher versus middle lower. Secondly, three main poverty contributing factors were unsafe housing, family health and adults' illiteracy, while the secondary factors include fuel type and children enrollment rate, etc., generally demonstrating strong autocorrelation; in terms of poverty degree, the western of the research area shows a significant aggregation effect, whereas the central and the eastern represent significant spatial heterogeneous distribution. Thirdly, under three kinds of socioeconomic classifications, the intra-classification diversities of H, A, and MPI are greater than their inter-classification ones, while each of the three indexes has a positive correlation with both the rocky desertification degree and topographic fragmentation degree, respectively. This study could help policymakers better understand the local poverty by identifying the poor, locating them and describing their characteristics, so as to take differentiated poverty alleviation measures according to specific conditions of each county.

Quantifying traditional Chinese medicine patterns using modern test theory: an example of functional constipation.

PubMed

Shen, Minxue; Cui, Yuanwu; Hu, Ming; Xu, Linyong

2017-01-13

The study aimed to validate a scale to assess the severity of "Yin deficiency, intestine heat" pattern of functional constipation based on the modern test theory. Pooled longitudinal data of 237 patients with "Yin deficiency, intestine heat" pattern of constipation from a prospective cohort study were used to validate the scale. Exploratory factor analysis was used to examine the common factors of items. A multidimensional item response model was used to assess the scale with the presence of multidimensionality. The Cronbach's alpha ranged from 0.79 to 0.89, and the split-half reliability ranged from 0.67 to 0.79 at different measurements. Exploratory factor analysis identified two common factors, and all items had cross factor loadings. Bidimensional model had better goodness of fit than the unidimensional model. Multidimensional item response model showed that the all items had moderate to high discrimination parameters. Parameters indicated that the first latent trait signified intestine heat, while the second trait characterized Yin deficiency. Information function showed that items demonstrated highest discrimination power among patients with moderate to high level of disease severity. Multidimensional item response theory provides a useful and rational approach in validating scales for assessing the severity of patterns in traditional Chinese medicine.

Single-indicator-based Multidimensional Sensing: Detection and Identification of Heavy Metal Ions and Understanding the Foundations from Experiment to Simulation

PubMed Central

Leng, Yumin; Qian, Sihua; Wang, Yuhui; Lu, Cheng; Ji, Xiaoxu; Lu, Zhiwen; Lin, Hengwei

2016-01-01

Multidimensional sensing offers advantages in accuracy, diversity and capability for the simultaneous detection and discrimination of multiple analytes, however, the previous reports usually require complicated synthesis/fabrication process and/or need a variety of techniques (or instruments) to acquire signals. Therefore, to take full advantages of this concept, simple designs are highly desirable. Herein, a novel concept is conceived to construct multidimensional sensing platforms based on a single indicator that has capability of showing diverse color/fluorescence responses with the addition of different analytes. Through extracting hidden information from these responses, such as red, green and blue (RGB) alterations, a triple-channel-based multidimensional sensing platform could consequently be fabricated, and the RGB alterations are further applicable to standard statistical methods. As a proof-of-concept study, a triple-channel sensing platform is fabricated solely using dithizone with assistance of cetyltrimethylammonium bromide (CTAB) for hyperchromicity and sensitization, which demonstrates superior capabilities in detection and identification of ten common heavy metal ions at their standard concentrations of wastewater-discharge of China. Moreover, this sensing platform exhibits promising applications in semi-quantitative and even quantitative analysis individuals of these heavy metal ions with high sensitivity as well. Finally, density functional theory calculations are performed to reveal the foundations for this analysis. PMID:27146105

Multidimensional proteomics for cell biology.

PubMed

Larance, Mark; Lamond, Angus I

2015-05-01

The proteome is a dynamic system in which each protein has interconnected properties - dimensions - that together contribute to the phenotype of a cell. Measuring these properties has proved challenging owing to their diversity and dynamic nature. Advances in mass spectrometry-based proteomics now enable the measurement of multiple properties for thousands of proteins, including their abundance, isoform expression, turnover rate, subcellular localization, post-translational modifications and interactions. Complementing these experimental developments are new data analysis, integration and visualization tools as well as data-sharing resources. Together, these advances in the multidimensional analysis of the proteome are transforming our understanding of various cellular and physiological processes.

Non-negative Tensor Factorization for Robust Exploratory Big-Data Analytics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alexandrov, Boian; Vesselinov, Velimir Valentinov; Djidjev, Hristo Nikolov

Currently, large multidimensional datasets are being accumulated in almost every field. Data are: (1) collected by distributed sensor networks in real-time all over the globe, (2) produced by large-scale experimental measurements or engineering activities, (3) generated by high-performance simulations, and (4) gathered by electronic communications and socialnetwork activities, etc. Simultaneous analysis of these ultra-large heterogeneous multidimensional datasets is often critical for scientific discoveries, decision-making, emergency response, and national and global security. The importance of such analyses mandates the development of the next-generation of robust machine learning (ML) methods and tools for bigdata exploratory analysis.

Annual Review of Research Under the Joint Service Electronics Program.

DTIC Science & Technology

1979-10-01

Contents: Quadratic Optimization Problems; Nonlinear Control; Nonlinear Fault Analysis; Qualitative Analysis of Large Scale Systems; Multidimensional System Theory ; Optical Noise; and Pattern Recognition.

Factorial invariance of pediatric patient self-reported fatigue across age and gender: a multigroup confirmatory factor analysis approach utilizing the PedsQL™ Multidimensional Fatigue Scale.

PubMed

Varni, James W; Beaujean, A Alexander; Limbers, Christine A

2013-11-01

In order to compare multidimensional fatigue research findings across age and gender subpopulations, it is important to demonstrate measurement invariance, that is, that the items from an instrument have equivalent meaning across the groups studied. This study examined the factorial invariance of the 18-item PedsQL™ Multidimensional Fatigue Scale items across age and gender and tested a bifactor model. Multigroup confirmatory factor analysis (MG-CFA) was performed specifying a three-factor model across three age groups (5-7, 8-12, and 13-18 years) and gender. MG-CFA models were proposed in order to compare the factor structure, metric, scalar, and error variance across age groups and gender. The analyses were based on 837 children and adolescents recruited from general pediatric clinics, subspecialty clinics, and hospitals in which children were being seen for well-child checks, mild acute illness, or chronic illness care. A bifactor model of the items with one general factor influencing all the items and three domain-specific factors representing the General, Sleep/Rest, and Cognitive Fatigue domains fit the data better than oblique factor models. Based on the multiple measures of model fit, configural, metric, and scalar invariance were found for almost all items across the age and gender groups, as was invariance in the factor covariances. The PedsQL™ Multidimensional Fatigue Scale demonstrated strict factorial invariance for child and adolescent self-report across gender and strong factorial invariance across age subpopulations. The findings support an equivalent three-factor structure across the age and gender groups studied. Based on these data, it can be concluded that pediatric patients across the groups interpreted the items in a similar manner regardless of their age or gender, supporting the multidimensional factor structure interpretation of the PedsQL™ Multidimensional Fatigue Scale.

Identification of key regulators of pancreatic cancer progression through multidimensional systems-level analysis.

PubMed

Rajamani, Deepa; Bhasin, Manoj K

2016-05-03

Pancreatic cancer is an aggressive cancer with dismal prognosis, urgently necessitating better biomarkers to improve therapeutic options and early diagnosis. Traditional approaches of biomarker detection that consider only one aspect of the biological continuum like gene expression alone are limited in their scope and lack robustness in identifying the key regulators of the disease. We have adopted a multidimensional approach involving the cross-talk between the omics spaces to identify key regulators of disease progression. Multidimensional domain-specific disease signatures were obtained using rank-based meta-analysis of individual omics profiles (mRNA, miRNA, DNA methylation) related to pancreatic ductal adenocarcinoma (PDAC). These domain-specific PDAC signatures were integrated to identify genes that were affected across multiple dimensions of omics space in PDAC (genes under multiple regulatory controls, GMCs). To further pin down the regulators of PDAC pathophysiology, a systems-level network was generated from knowledge-based interaction information applied to the above identified GMCs. Key regulators were identified from the GMC network based on network statistics and their functional importance was validated using gene set enrichment analysis and survival analysis. Rank-based meta-analysis identified 5391 genes, 109 miRNAs and 2081 methylation-sites significantly differentially expressed in PDAC (false discovery rate ≤ 0.05). Bimodal integration of meta-analysis signatures revealed 1150 and 715 genes regulated by miRNAs and methylation, respectively. Further analysis identified 189 altered genes that are commonly regulated by miRNA and methylation, hence considered GMCs. Systems-level analysis of the scale-free GMCs network identified eight potential key regulator hubs, namely E2F3, HMGA2, RASA1, IRS1, NUAK1, ACTN1, SKI and DLL1, associated with important pathways driving cancer progression. Survival analysis on individual key regulators revealed that higher expression of IRS1 and DLL1 and lower expression of HMGA2, ACTN1 and SKI were associated with better survival probabilities. It is evident from the results that our hierarchical systems-level multidimensional analysis approach has been successful in isolating the converging regulatory modules and associated key regulatory molecules that are potential biomarkers for pancreatic cancer progression.

National-Level Wetland Policy Specificity and Goals Vary According to Political and Economic Indicators.

PubMed

Peimer, Alex W; Krzywicka, Adrianna E; Cohen, Dora B; Van den Bosch, Kyle; Buxton, Valerie L; Stevenson, Natalie A; Matthews, Jeffrey W

2017-01-01

Growing recognition of the importance of wetlands to human and ecosystem well-being has led countries worldwide to implement wetland protection policies. Different countries have taken different approaches to wetland protection by implementing various policies, including territorial exclusion, market-based offsetting, and incentive programs for land users. Our objective was to describe the relationship between components of national-level wetland protection policies and national characteristics, including natural resource, economic, social, and political factors. We compiled data on the wetland policies of all 193 countries recognized by the U.N. and described the relationships among wetland policy goals and wetland protection mechanisms using non-metric multidimensional scaling. The first non-metric multidimensional scaling axis strongly correlated with whether a country had a wetland-specific environmental policy in place. Adoption of a comprehensive, wetland-specific policy was positively associated with degree of democracy and a commitment to establishing protected areas. The second non-metric multidimensional scaling axis defined a continuum of policy goals and mechanisms by which wetlands are protected, with goals to protect wetland ecosystem services on one end of the spectrum and goals to protect biodiversity on the other. Goals for protecting ecosystem services were frequently cited in policy documents of countries with agriculture-based economies, whereas goals associated with wetland biodiversity tended to be associated with tourism-based economies. We argue that the components of a country's wetland policies reflect national-level resource and economic characteristics. Understanding the relationship between the type of wetland policy countries adopt and national-level characteristics is critical for international efforts to protect wetlands.

National-Level Wetland Policy Specificity and Goals Vary According to Political and Economic Indicators

NASA Astrophysics Data System (ADS)

Peimer, Alex W.; Krzywicka, Adrianna E.; Cohen, Dora B.; Van den Bosch, Kyle; Buxton, Valerie L.; Stevenson, Natalie A.; Matthews, Jeffrey W.

2017-01-01

Growing recognition of the importance of wetlands to human and ecosystem well-being has led countries worldwide to implement wetland protection policies. Different countries have taken different approaches to wetland protection by implementing various policies, including territorial exclusion, market-based offsetting, and incentive programs for land users. Our objective was to describe the relationship between components of national-level wetland protection policies and national characteristics, including natural resource, economic, social, and political factors. We compiled data on the wetland policies of all 193 countries recognized by the U.N. and described the relationships among wetland policy goals and wetland protection mechanisms using non-metric multidimensional scaling. The first non-metric multidimensional scaling axis strongly correlated with whether a country had a wetland-specific environmental policy in place. Adoption of a comprehensive, wetland-specific policy was positively associated with degree of democracy and a commitment to establishing protected areas. The second non-metric multidimensional scaling axis defined a continuum of policy goals and mechanisms by which wetlands are protected, with goals to protect wetland ecosystem services on one end of the spectrum and goals to protect biodiversity on the other. Goals for protecting ecosystem services were frequently cited in policy documents of countries with agriculture-based economies, whereas goals associated with wetland biodiversity tended to be associated with tourism-based economies. We argue that the components of a country's wetland policies reflect national-level resource and economic characteristics. Understanding the relationship between the type of wetland policy countries adopt and national-level characteristics is critical for international efforts to protect wetlands.

Evidence That Environmental and Familial Risks for Psychosis Additively Impact a Multidimensional Subthreshold Psychosis Syndrome.

PubMed

Pries, Lotta-Katrin; Guloksuz, Sinan; Ten Have, Margreet; de Graaf, Ron; van Dorsselaer, Saskia; Gunther, Nicole; Rauschenberg, Christian; Reininghaus, Ulrich; Radhakrishnan, Rajiv; Bak, Maarten; Rutten, Bart P F; van Os, Jim

2018-06-06

The observed link between positive psychotic experiences (PE) and psychosis spectrum disorder (PSD) may be stronger depending on concomitant presence of PE with other dimensions of psychopathology. We examined whether the effect of common risk factors for PSD on PE is additive and whether the impact of risk factors on the occurrence of PE depends on the co-occurrence of other symptom dimensions (affective dysregulation, negative symptoms, and cognitive alteration). Data from the Netherlands Mental Health Survey and Incidence Study 2 were used. Risk factors included childhood adversity, cannabis use, urbanicity, foreign born, hearing impairment, and family history of affective disorders. Logistic regression models were applied to test (1) the additive effect of risk factors (4 levels) on PE and (2) the moderating effects of symptom dimensions on the association between risk factors (present/absent) and PE, using additive interaction, expressed as the interaction contrast ratio. Risk factors were additive: the greater the number of risk factors, the greater the odds of PE. Furthermore, concomitant presence of the other symptom dimensions all increased the impact of risk factors on PE. After controlling for age, sex, and education, only affective dysregulation and negative symptoms remained significant moderators; only affective dysregulation remained a significant moderator if all dimensions were adjusted for each other. Risk factors may not be directly associated with PE but additively give rise to a multidimensional subthreshold state anticipating the multidimensional clinical syndrome. Early motivational and cognitive impairments in the context of PE may be reducible to affective dysregulation.

Development and psychometric properties of the Suicidality of Adolescent Screening Scale (SASS) using Multidimensional Item Response Theory.

PubMed

Sukhawaha, Supattra; Arunpongpaisal, Suwanna; Hurst, Cameron

2016-09-30

Suicide prevention in adolescents by early detection using screening tools to identify high suicidal risk is a priority. Our objective was to build a multidimensional scale namely "Suicidality of Adolescent Screening Scale (SASS)" to identify adolescents at risk of suicide. An initial pool of items was developed by using in-depth interview, focus groups and a literature review. Initially, 77 items were administered to 307 adolescents and analyzed using the exploratory Multidimensional Item Response Theory (MIRT) to remove unnecessary items. A subsequent exploratory factor analysis revealed 35 items that collected into 4 factors: Stressors, Pessimism, Suicidality and Depression. To confirm this structure, a new sample of 450 adolescents were collected and confirmatory MIRT factor analysis was performed. The resulting scale was shown to be both construct valid and able to discriminate well between adolescents that had, and hadn't previous attempted suicide. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Rethinking language in autism.

PubMed

Sterponi, Laura; de Kirby, Kenton; Shankey, Jennifer

2015-07-01

In this article, we invite a rethinking of traditional perspectives of language in autism. We advocate a theoretical reappraisal that offers a corrective to the dominant and largely tacitly held view that language, in its essence, is a referential system and a reflection of the individual's cognition. Drawing on scholarship in Conversation Analysis and linguistic anthropology, we present a multidimensional view of language, showing how it also functions as interactional accomplishment, social action, and mode of experience. From such a multidimensional perspective, we revisit data presented by other researchers that include instances of prototypical features of autistic speech, giving them a somewhat different-at times complementary, at times alternative-interpretation. In doing so, we demonstrate that there is much at stake in the view of language that we as researchers bring to our analysis of autistic speech. Ultimately, we argue that adopting a multidimensional view of language has wide ranging implications, deepening our understanding of autism's core features and developmental trajectory. © The Author(s) 2014.

"Staying safe" - a narrative review of falls prevention in people with Parkinson's - "PDSAFE".

PubMed

Hulbert, Sophia; Rochester, Lynn; Nieuwboer, Alice; Goodwin, Vicki; Fitton, Carolyn; Chivers-Seymour, Kim; Ashburn, Ann

2018-05-18

Parkinson's disease demonstrates a spectrum of motor and non-motor symptoms. Falling is common and disabling. Current medical management shows minimal impact to reduce falls or fall-related risk factors, such as deficits in gait, strength, and postural instability. Despite evidence supporting rehabilitation in reducing fall risk factors, the most appropriate intervention to reduce overall fall rate remains inconclusive. This article aims to 1) synthesise current evidence and conceptual models of falls rehabilitation in Parkinson's in a narrative review; and based on this evidence, 2) introduce the treatment protocol used in the falls prevention and multi-centre clinical trial "PDSAFE". Search of four bibliographic databases using the terms "Parkinson*" and "Fall*" combined with each of the following; "Rehab*, Balanc*, Strength*, Strateg*and Exercis*" and a framework for narrative review was followed. A total of 3557 papers were identified, 416 were selected for review. The majority report the impact of rehabilitation on isolated fall risk factors. Twelve directly measure the impact on overall fall rate. Results were used to construct a narrative review with conceptual discussion based on the "International Classification of Functioning", leading to presentation of the "PDSAFE" intervention protocol. Evidence suggests training single, fall risk factors may not affect overall fall rate. Combining with behavioural and strategy training in a functional, personalised multi-dimensional model, addressing all components of the "International Classification of Functioning" is likely to provide a greater influence on falls reduction. "PDSAFE" is a multi-dimensional, physiotherapist delivered, individually tailored, progressive, home-based programme. It is designed with a strong evidence-based approach and illustrates a model for the clinical delivery of the conceptual theory discussed. Implications for Rehabilitation Parkinson's disease demonstrates a spectrum of motor and non-motor symptoms, where falling is common and disabling. Current medical and surgical management have minimal impact on falls, rehabilitation of falls risk factors has strong evidence but the most appropriate intervention to reduce overall fall rate remains inconclusive. Addressing all components of the International Classification of Function in a multifactorial model when designing falls rehabilitation interventions may be more effective at reducing fall rates in people with Parkinson's than treating isolated risk factors. The clinical model for falls rehabilitation in people with Parkinson's should be multi-dimensional.

6D Visualization of Multidimensional Data by Means of Cognitive Technology

NASA Astrophysics Data System (ADS)

Vitkovskiy, V.; Gorohov, V.; Komarinskiy, S.

2010-12-01

On the basis of the cognitive graphics concept, we worked out the SW-system for visualization and analysis. It allows to train and to aggravate intuition of researcher, to raise his interest and motivation to the creative, scientific cognition, to realize process of dialogue with the very problems simultaneously. The Space Hedgehog system is the next step in the cognitive means of the multidimensional data analyze. The technique and technology cognitive 6D visualization of the multidimensional data is developed on the basis of the cognitive visualization research and technology development. The Space Hedgehog system allows direct dynamic visualization of 6D objects. It is developed with use of experience of the program Space Walker creation and its applications.

Chapter 3. A multidimensional model for narrative analysis of substance use-related dependency.

PubMed

Larsson, Sam; von Braun, Therese; Lilja, John

2013-11-01

This chapter examines the possibilities and limitations of using a narrative method as a framework within a multidimensional model for exploring and analyzing the use and misuse of alcohol and drugs. It is posited that a multidimensional model, based on narrative reasoning, can give a more detailed and specific understanding of substance users, who represent a heterogeneous population of people, and of substance use-related dependency problems. Such a model describes and analyses the drug-use related problems in a manner that provides holistic and important information and knowledge about the person by contextual and situation interaction processes which are involved in the use/misuse of alcohol and drugs. Tentative conclusions and unresolved critical issues are considered.

Dealing with the multidimensionality of sustainability through the use of multiple perspectives - a theoretical framework

NASA Astrophysics Data System (ADS)

Lönngren, Johanna; Svanström, Magdalena; Ingerman, Åke; Holmberg, John

2016-05-01

The concept of perspectives is important in discussions about the multidimensionality of sustainability problems and the need to consider many different aspects when dealing with them. This paper aims to facilitate discussions among both educators and researchers about didactical approaches to developing students' abilities to deal with the multidimensionality of sustainability challenges through the use of multiple perspectives. For this purpose, a theoretical framework was developed that describes perspectives in terms of a set of general characteristics, as well as a number of ways in which students can develop and reflect on perspectives. Development of the framework was supported by a qualitative content analysis of transcripts from interviews with undergraduate engineering students in Sweden.

Discrete models for the numerical analysis of time-dependent multidimensional gas dynamics

NASA Technical Reports Server (NTRS)

Roe, P. L.

1984-01-01

A possible technique is explored for extending to multidimensional flows some of the upwind-differencing methods that are highly successful in the one-dimensional case. Emphasis is on the two-dimensional case, and the flow domain is assumed to be divided into polygonal computational elements. Inside each element, the flow is represented by a local superposition of elementary solutions consisting of plane waves not necessarily aligned with the element boundaries.

Modulation stability analysis of exact multidimensional solutions to the generalized nonlinear Schrödinger equation and the Gross-Pitaevskii equation using a variational approach.

PubMed

Petrović, Nikola Z; Aleksić, Najdan B; Belić, Milivoj

2015-04-20

We analyze the modulation stability of spatiotemporal solitary and traveling wave solutions to the multidimensional nonlinear Schrödinger equation and the Gross-Pitaevskii equation with variable coefficients that were obtained using Jacobi elliptic functions. For all the solutions we obtain either unconditional stability, or a conditional stability that can be furnished through the use of dispersion management.

An Augmented Two-Layer Model Captures Nonlinear Analog Spatial Integration Effects in Pyramidal Neuron Dendrites.

PubMed

Jadi, Monika P; Behabadi, Bardia F; Poleg-Polsky, Alon; Schiller, Jackie; Mel, Bartlett W

2014-05-01

In pursuit of the goal to understand and eventually reproduce the diverse functions of the brain, a key challenge lies in reverse engineering the peculiar biology-based "technology" that underlies the brain's remarkable ability to process and store information. The basic building block of the nervous system is the nerve cell, or "neuron," yet after more than 100 years of neurophysiological study and 60 years of modeling, the information processing functions of individual neurons, and the parameters that allow them to engage in so many different types of computation (sensory, motor, mnemonic, executive, etc.) remain poorly understood. In this paper, we review both historical and recent findings that have led to our current understanding of the analog spatial processing capabilities of dendrites, the major input structures of neurons, with a focus on the principal cell type of the neocortex and hippocampus, the pyramidal neuron (PN). We encapsulate our current understanding of PN dendritic integration in an abstract layered model whose spatially sensitive branch-subunits compute multidimensional sigmoidal functions. Unlike the 1-D sigmoids found in conventional neural network models, multidimensional sigmoids allow the cell to implement a rich spectrum of nonlinear modulation effects directly within their dendritic trees.

Assessing the Multidimensional Relationship Between Medication Beliefs and Adherence in Older Adults With Hypertension Using Polynomial Regression.

PubMed

Dillon, Paul; Phillips, L Alison; Gallagher, Paul; Smith, Susan M; Stewart, Derek; Cousins, Gráinne

2018-02-05

The Necessity-Concerns Framework (NCF) is a multidimensional theory describing the relationship between patients' positive and negative evaluations of their medication which interplay to influence adherence. Most studies evaluating the NCF have failed to account for the multidimensional nature of the theory, placing the separate dimensions of medication "necessity beliefs" and "concerns" onto a single dimension (e.g., the Beliefs about Medicines Questionnaire-difference score model). To assess the multidimensional effect of patient medication beliefs (concerns and necessity beliefs) on medication adherence using polynomial regression with response surface analysis. Community-dwelling older adults >65 years (n = 1,211) presenting their own prescription for antihypertensive medication to 106 community pharmacies in the Republic of Ireland rated their concerns and necessity beliefs to antihypertensive medications at baseline and their adherence to antihypertensive medication at 12 months via structured telephone interview. Confirmatory polynomial regression found the difference-score model to be inaccurate; subsequent exploratory analysis identified a quadratic model to be the best-fitting polynomial model. Adherence was lowest among those with strong medication concerns and weak necessity beliefs, and adherence was greatest for those with weak concerns and strong necessity beliefs (slope β = -0.77, p<.001; curvature β = -0.26, p = .004). However, novel nonreciprocal effects were also observed; patients with simultaneously high concerns and necessity beliefs had lower adherence than those with simultaneously low concerns and necessity beliefs (slope β = -0.36, p = .004; curvature β = -0.25, p = .003). The difference-score model fails to account for the potential nonreciprocal effects. Results extend evidence supporting the use of polynomial regression to assess the multidimensional effect of medication beliefs on adherence.

Modernizing quality of life assessment: development of a multidimensional computerized adaptive questionnaire for patients with schizophrenia.

PubMed

Michel, Pierre; Baumstarck, Karine; Lancon, Christophe; Ghattas, Badih; Loundou, Anderson; Auquier, Pascal; Boyer, Laurent

2018-04-01

Quality of life (QoL) is still assessed using paper-based and fixed-length questionnaires, which is one reason why QoL measurements have not been routinely implemented in clinical practice. Providing new QoL measures that combine computer technology with modern measurement theory may enhance their clinical use. The aim of this study was to develop a QoL multidimensional computerized adaptive test (MCAT), the SQoL-MCAT, from the fixed-length SQoL questionnaire for patients with schizophrenia. In this multicentre cross-sectional study, we collected sociodemographic information, clinical characteristics (i.e., duration of illness, the PANSS, and the Calgary Depression Scale), and quality of life (i.e., SQoL). The development of the SQoL-CAT was divided into three stages: (1) multidimensional item response theory (MIRT) analysis, (2) multidimensional computerized adaptive test (MCAT) simulations with analyses of accuracy and precision, and (3) external validity. Five hundred and seventeen patients participated in this study. The MIRT analysis found that all items displayed good fit with the multidimensional graded response model, with satisfactory reliability for each dimension. The SQoL-MCAT was 39% shorter than the fixed-length SQoL questionnaire and had satisfactory accuracy (levels of correlation >0.9) and precision (standard error of measurement <0.55 and root mean square error <0.3). External validity was confirmed via correlations between the SQoL-MCAT dimension scores and symptomatology scores. The SQoL-MCAT is the first computerized adaptive QoL questionnaire for patients with schizophrenia. Tailored for patient characteristics and significantly shorter than the paper-based version, the SQoL-MCAT may improve the feasibility of assessing QoL in clinical practice.

Validating the European Health Literacy Survey Questionnaire in people with type 2 diabetes: Latent trait analyses applying multidimensional Rasch modelling and confirmatory factor analysis.

PubMed

Finbråten, Hanne Søberg; Pettersen, Kjell Sverre; Wilde-Larsson, Bodil; Nordström, Gun; Trollvik, Anne; Guttersrud, Øystein

2017-11-01

To validate the European Health Literacy Survey Questionnaire (HLS-EU-Q47) in people with type 2 diabetes mellitus. The HLS-EU-Q47 latent variable is outlined in a framework with four cognitive domains integrated in three health domains, implying 12 theoretically defined subscales. Valid and reliable health literacy measurers are crucial to effectively adapt health communication and education to individuals and groups of patients. Cross-sectional study applying confirmatory latent trait analyses. Using a paper-and-pencil self-administered approach, 388 adults responded in March 2015. The data were analysed using the Rasch methodology and confirmatory factor analysis. Response violation (response dependency) and trait violation (multidimensionality) of local independence were identified. Fitting the "multidimensional random coefficients multinomial logit" model, 1-, 3- and 12-dimensional Rasch models were applied and compared. Poor model fit and differential item functioning were present in some items, and several subscales suffered from poor targeting and low reliability. Despite multidimensional data, we did not observe any unordered response categories. Interpreting the domains as distinct but related latent dimensions, the data fit a 12-dimensional Rasch model and a 12-factor confirmatory factor model best. Therefore, the analyses did not support the estimation of one overall "health literacy score." To support the plausibility of claims based on the HLS-EU score(s), we suggest: removing the health care aspect to reduce the magnitude of multidimensionality; rejecting redundant items to avoid response dependency; adding "harder" items and applying a six-point rating scale to improve subscale targeting and reliability; and revising items to improve model fit and avoid bias owing to person factors. © 2017 John Wiley & Sons Ltd.

The HEUN-SCHRÖDINGER Radial Equation for Dh-Atoms

NASA Astrophysics Data System (ADS)

Tarasov, V. F.

This article deals with the connection between Schrödinger's multidimensional equation for DH-atoms (D≥1) and the confluent Heun equation with two auxiliary parameters ν and τ, where |1-ν| = o(1) and τ∈ℚ+, which influence the spectrum of eigenvalues, the Coulomb potential and the radial function. The case τ = ν = 1 and D = 3 corresponds to the "standard" form of Schrödinger's equation for a 3H-atom. With the help of parameter ν, e.g., some "quantum corrections" may be considered. The cases 0<τ<1 and τ>1, but â = (n-l-1)τ≥0 is an integer, change the "geometry" of the electron cloud in the atom, i.e. the so-called "exotic" 3H-like atoms arise, where Kummer's function 1F1(-â c; z) has â zeros and the discrete spectrum depends only on Z/(νn) but not on l and τ. Diagrams of the radial functions hat Pnl(r;τ ,ν ) as n≤3 are given.

Behind the Wheel and on the Map: Genetic and Environmental Associations between Drunk Driving and Other Externalizing Behaviors

PubMed Central

Quinn, Patrick D.; Harden, K. Paige

2013-01-01

Drunk driving, a major contributor to alcohol-related mortality, has been linked to a variety of other alcohol-related (e.g., Alcohol Dependence, early age at first drink) and non-alcohol-related externalizing behaviors. In a sample of 517 same-sex twin pairs from the National Longitudinal Study of Adolescent Health, we examined three conceptualizations of the etiology of drunk driving in relation to other externalizing behaviors. A series of behavioral-genetic models found consistent evidence for drunk driving as a manifestation of genetic vulnerabilities toward a spectrum of alcohol-related and non-alcohol-related externalizing behaviors. Most notably, multidimensional scaling analyses produced a genetic “map” with drunk driving located near its center, supporting the strength of drunk driving’s genetic relations with a broad range of externalizing behaviors. In contrast, non-shared environmental associations with drunk driving were weaker and more diffuse. Drunk driving may be a manifestation of genetic vulnerabilities toward a broad externalizing spectrum. PMID:24128260

Multi-dimensional Fokker-Planck equation analysis using the modified finite element method

NASA Astrophysics Data System (ADS)

Náprstek, J.; Král, R.

2016-09-01

The Fokker-Planck equation (FPE) is a frequently used tool for the solution of cross probability density function (PDF) of a dynamic system response excited by a vector of random processes. FEM represents a very effective solution possibility, particularly when transition processes are investigated or a more detailed solution is needed. Actual papers deal with single degree of freedom (SDOF) systems only. So the respective FPE includes two independent space variables only. Stepping over this limit into MDOF systems a number of specific problems related to a true multi-dimensionality must be overcome. Unlike earlier studies, multi-dimensional simplex elements in any arbitrary dimension should be deployed and rectangular (multi-brick) elements abandoned. Simple closed formulae of integration in multi-dimension domain have been derived. Another specific problem represents the generation of multi-dimensional finite element mesh. Assembling of system global matrices should be subjected to newly composed algorithms due to multi-dimensionality. The system matrices are quite full and no advantages following from their sparse character can be profited from, as is commonly used in conventional FEM applications in 2D/3D problems. After verification of partial algorithms, an illustrative example dealing with a 2DOF non-linear aeroelastic system in combination with random and deterministic excitations is discussed.

Assessment of health surveys: fitting a multidimensional graded response model.

PubMed

Depaoli, Sarah; Tiemensma, Jitske; Felt, John M

The multidimensional graded response model, an item response theory (IRT) model, can be used to improve the assessment of surveys, even when sample sizes are restricted. Typically, health-based survey development utilizes classical statistical techniques (e.g. reliability and factor analysis). In a review of four prominent journals within the field of Health Psychology, we found that IRT-based models were used in less than 10% of the studies examining scale development or assessment. However, implementing IRT-based methods can provide more details about individual survey items, which is useful when determining the final item content of surveys. An example using a quality of life survey for Cushing's syndrome (CushingQoL) highlights the main components for implementing the multidimensional graded response model. Patients with Cushing's syndrome (n = 397) completed the CushingQoL. Results from the multidimensional graded response model supported a 2-subscale scoring process for the survey. All items were deemed as worthy contributors to the survey. The graded response model can accommodate unidimensional or multidimensional scales, be used with relatively lower sample sizes, and is implemented in free software (example code provided in online Appendix). Use of this model can help to improve the quality of health-based scales being developed within the Health Sciences.

Use patterns of health information exchange through a multidimensional lens: conceptual framework and empirical validation.

PubMed

Politi, Liran; Codish, Shlomi; Sagy, Iftach; Fink, Lior

2014-12-01

Insights about patterns of system use are often gained through the analysis of system log files, which record the actual behavior of users. In a clinical context, however, few attempts have been made to typify system use through log file analysis. The present study offers a framework for identifying, describing, and discerning among patterns of use of a clinical information retrieval system. We use the session attributes of volume, diversity, granularity, duration, and content to define a multidimensional space in which each specific session can be positioned. We also describe an analytical method for identifying the common archetypes of system use in this multidimensional space. We demonstrate the value of the proposed framework with a log file of the use of a health information exchange (HIE) system by physicians in an emergency department (ED) of a large Israeli hospital. The analysis reveals five distinct patterns of system use, which have yet to be described in the relevant literature. The results of this study have the potential to inform the design of HIE systems for efficient and effective use, thus increasing their contribution to the clinical decision-making process. Copyright © 2014 Elsevier Inc. All rights reserved.

A Multidimensional Analysis Tool for Visualizing Online Interactions

ERIC Educational Resources Information Center

Kim, Minjeong; Lee, Eunchul

2012-01-01

This study proposes and verifies the performance of an analysis tool for visualizing online interactions. A review of the most widely used methods for analyzing online interactions, including quantitative analysis, content analysis, and social network analysis methods, indicates these analysis methods have some limitations resulting from their…

Seismic noise attenuation using an online subspace tracking algorithm

NASA Astrophysics Data System (ADS)

Zhou, Yatong; Li, Shuhua; Zhang, Dong; Chen, Yangkang

2018-02-01

We propose a new low-rank based noise attenuation method using an efficient algorithm for tracking subspaces from highly corrupted seismic observations. The subspace tracking algorithm requires only basic linear algebraic manipulations. The algorithm is derived by analysing incremental gradient descent on the Grassmannian manifold of subspaces. When the multidimensional seismic data are mapped to a low-rank space, the subspace tracking algorithm can be directly applied to the input low-rank matrix to estimate the useful signals. Since the subspace tracking algorithm is an online algorithm, it is more robust to random noise than traditional truncated singular value decomposition (TSVD) based subspace tracking algorithm. Compared with the state-of-the-art algorithms, the proposed denoising method can obtain better performance. More specifically, the proposed method outperforms the TSVD-based singular spectrum analysis method in causing less residual noise and also in saving half of the computational cost. Several synthetic and field data examples with different levels of complexities demonstrate the effectiveness and robustness of the presented algorithm in rejecting different types of noise including random noise, spiky noise, blending noise, and coherent noise.

Implementation of Finite Volume based Navier Stokes Algorithm Within General Purpose Flow Network Code

NASA Technical Reports Server (NTRS)

Schallhorn, Paul; Majumdar, Alok

2012-01-01

This paper describes a finite volume based numerical algorithm that allows multi-dimensional computation of fluid flow within a system level network flow analysis. There are several thermo-fluid engineering problems where higher fidelity solutions are needed that are not within the capacity of system level codes. The proposed algorithm will allow NASA's Generalized Fluid System Simulation Program (GFSSP) to perform multi-dimensional flow calculation within the framework of GFSSP s typical system level flow network consisting of fluid nodes and branches. The paper presents several classical two-dimensional fluid dynamics problems that have been solved by GFSSP's multi-dimensional flow solver. The numerical solutions are compared with the analytical and benchmark solution of Poiseulle, Couette and flow in a driven cavity.

Analysis of the Rotation-Torsion Spectrum of CH_2DOH Within the e_0, e_1, and o_1 Torsional Levels

NASA Astrophysics Data System (ADS)

Coudert, L. H.; Pearson, John C.; Yu, Shanshan; Margules, L.; Motiyenko, R. A.; Klee, S.

2013-06-01

Since the first assignments of Quade and coworkers, a more satisfactory understanding of the spectrum of CH_2DOH has now been achieved. Thanks to a multidimensional potential energy surface and to a new theoretical approach accounting for the internal rotation of a partially deuterated methyl group, 76 torsional subbands could be identified in the microwave and FIR domains. 8356 rotation and rotation-torsion transitions were also assigned for the three lowest lying torsional levels, e_0, e_1, and o_1, in the microwave and terahertz domains and were analyzed with empirical models. In this paper, a new approach aimed at accounting for the rotation-torsion energy levels of CH_2DOH will be presented. It is based on the exact expression of the generalized 4× 4 inertia tensor of the molecule and accounts for the C_s symmetry of the partially deuterated methyl group, for the dependence of the rotational constants on the angle of internal rotation, and for the rotation-torsion Coriolis coupling. This approach will be used to analyze high-resolution data involving the three lowest lying torsional levels, up to k=11. In addition to the microwave data reported recently,^d new transitions recorded in the terahertz domain at JPL will be analyzed. The results of the analysis will be presented in the paper and the parameters determined in the analysis will be discussed. Quade and Suenram, J. Chem. Phys. {73} (1980) 1127; and Su and Quade, J. Mol. Spec. {134} (1989) 290. Lauvergnat, Coudert, Klee, and Smirnov, J. Mol. Spec. {256} (2009) 204. El Hilali, Coudert, Konov, and Klee, J. Chem. Phys. {135} (2011) 194309. Pearson, Yu, and Drouin, J. Mol. Spec. {280} (2012) 119. Quade and Lin, J. Chem. Phys. {38} (1963) 540.

Modeling stock prices in a portfolio using multidimensional geometric brownian motion

NASA Astrophysics Data System (ADS)

Maruddani, Di Asih I.; Trimono

2018-05-01

Modeling and forecasting stock prices of public corporates are important studies in financial analysis, due to their stock price characteristics. Stocks investments give a wide variety of risks. Taking a portfolio of several stocks is one way to minimize risk. Stochastic process of single stock price movements model can be formulated in Geometric Brownian Motion (GBM) model. But for a portfolio that consist more than one corporate stock, we need an expansion of GBM Model. In this paper, we use multidimensional Geometric Brownian Motion model. This paper aims to model and forecast two stock prices in a portfolio. These are PT. Matahari Department Store Tbk and PT. Telekomunikasi Indonesia Tbk on period January 4, 2016 until April 21, 2017. The goodness of stock price forecast value is based on Mean Absolute Percentage Error (MAPE). As the results, we conclude that forecast two stock prices in a portfolio using multidimensional GBM give less MAPE than using GBM for single stock price respectively. We conclude that multidimensional GBM is more appropriate for modeling stock prices, because the price of each stock affects each other.

Multidimensional Homophily in Friendship Networks1

PubMed Central

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

Subtypes and comorbidity in mathematical learning disabilities: Multidimensional study of verbal and visual memory processes is key to understanding.

PubMed

Szűcs, D

2016-01-01

A large body of research suggests that mathematical learning disability (MLD) is related to working memory impairment. Here, I organize part of this literature through a meta-analysis of 36 studies with 665 MLD and 1049 control participants. I demonstrate that one subtype of MLD is associated with reading problems and weak verbal short-term and working memory. Another subtype of MLD does not have associated reading problems and is linked to weak visuospatial short-term and working memory. In order to better understand MLD we need to precisely define potentially modality-specific memory subprocesses and supporting executive functions, relevant for mathematical learning. This can be achieved by taking a multidimensional parametric approach systematically probing an extended network of cognitive functions. Rather than creating arbitrary subgroups and/or focus on a single factor, highly powered studies need to position individuals in a multidimensional parametric space. This will allow us to understand the multidimensional structure of cognitive functions and their relationship to mathematical performance. © 2016 Elsevier B.V. All rights reserved.

Spectral factorization of wavefields and wave operators

NASA Astrophysics Data System (ADS)

Rickett, James Edward

Spectral factorization is the problem of finding a minimum-phase function with a given power spectrum. Minimum phase functions have the property that they are causal with a causal (stable) inverse. In this thesis, I factor multidimensional systems into their minimum-phase components. Helical boundary conditions resolve any ambiguities over causality, allowing me to factor multi-dimensional systems with conventional one-dimensional spectral factorization algorithms. In the first part, I factor passive seismic wavefields recorded in two-dimensional spatial arrays. The result provides an estimate of the acoustic impulse response of the medium that has higher bandwidth than autocorrelation-derived estimates. Also, the function's minimum-phase nature mimics the physics of the system better than the zero-phase autocorrelation model. I demonstrate this on helioseismic data recorded by the satellite-based Michelson Doppler Imager (MDI) instrument, and shallow seismic data recorded at Long Beach, California. In the second part of this thesis, I take advantage of the stable-inverse property of minimum-phase functions to solve wave-equation partial differential equations. By factoring multi-dimensional finite-difference stencils into minimum-phase components, I can invert them efficiently, facilitating rapid implicit extrapolation without the azimuthal anisotropy that is observed with splitting approximations. The final part of this thesis describes how to calculate diagonal weighting functions that approximate the combined operation of seismic modeling and migration. These weighting functions capture the effects of irregular subsurface illumination, which can be the result of either the surface-recording geometry, or focusing and defocusing of the seismic wavefield as it propagates through the earth. Since they are diagonal, they can be easily both factored and inverted to compensate for uneven subsurface illumination in migrated images. Experimental results show that applying these weighting functions after migration leads to significantly improved estimates of seismic reflectivity.

Disentangling Heterogeneity of Childhood Disruptive Behavior Problems Into Dimensions and Subgroups.

PubMed

Bolhuis, Koen; Lubke, Gitta H; van der Ende, Jan; Bartels, Meike; van Beijsterveldt, Catharina E M; Lichtenstein, Paul; Larsson, Henrik; Jaddoe, Vincent W V; Kushner, Steven A; Verhulst, Frank C; Boomsma, Dorret I; Tiemeier, Henning

2017-08-01

Irritable and oppositional behaviors are increasingly considered as distinct dimensions of oppositional defiant disorder. However, few studies have explored this multidimensionality across the broader spectrum of disruptive behavior problems (DBPs). This study examined the presence of dimensions and distinct subgroups of childhood DBPs, and the cross-sectional and longitudinal associations between these dimensions. Using factor mixture models (FMMs), the presence of dimensions and subgroups of DBPs was assessed in the Generation R Study at ages 6 (n = 6,209) and 10 (n = 4,724) years. Replications were performed in two population-based cohorts (Netherlands Twin Registry, n = 4,402, and Swedish Twin Study of Child and Adolescent Development, n = 1,089) and a clinical sample (n = 1,933). We used cross-lagged modeling in the Generation R Study to assess cross-sectional and longitudinal associations between dimensions. DBPs were assessed using mother-reported responses to the Child Behavior Checklist. Empirically obtained dimensions of DBPs were oppositional behavior (age 6 years), disobedient behavior, rule-breaking behavior (age 10 years), physical aggression, and irritability (both ages). FMMs suggested that one-class solutions had the best model fit for all dimensions in all three population-based cohorts. Similar results were obtained in the clinical sample. All three dimensions, including irritability, predicted subsequent physical aggression (range, 0.08-0.16). This study showed that childhood DBPs should be regarded as a multidimensional phenotype rather than comprising distinct subgroups. Incorporating multidimensionality will improve diagnostic accuracy and refine treatment. Future studies need to address the biological validity of the DBP dimensions observed in this study; herein lies an important opportunity for neuroimaging and genetic measures. Copyright © 2017 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Influence of fusion dynamics on fission observables: A multidimensional analysis

NASA Astrophysics Data System (ADS)

Schmitt, C.; Mazurek, K.; Nadtochy, P. N.

2018-01-01

An attempt to unfold the respective influence of the fusion and fission stages on typical fission observables, and namely the neutron prescission multiplicity, is proposed. A four-dimensional dynamical stochastic Langevin model is used to calculate the decay by fission of excited compound nuclei produced in a wide set of heavy-ion collisions. The comparison of the results from such a calculation and experimental data is discussed, guided by predictions of the dynamical deterministic HICOL code for the compound-nucleus formation time. While the dependence of the latter on the entrance-channel properties can straigthforwardly explain some observations, a complex interplay between the various parameters of the reaction is found to occur in other cases. A multidimensional analysis of the respective role of these parameters, including entrance-channel asymmetry, bombarding energy, compound-nucleus fissility, angular momentum, and excitation energy, is proposed. It is shown that, depending on the size of the system, apparent inconsistencies may be deduced when projecting onto specific ordering parameters. The work suggests the possibility of delicate compensation effects in governing the measured fission observables, thereby highlighting the necessity of a multidimensional discussion.

Statistical Projections for Multi-resolution, Multi-dimensional Visual Data Exploration and Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoa T. Nguyen; Stone, Daithi; E. Wes Bethel

2016-01-01

An ongoing challenge in visual exploration and analysis of large, multi-dimensional datasets is how to present useful, concise information to a user for some specific visualization tasks. Typical approaches to this problem have proposed either reduced-resolution versions of data, or projections of data, or both. These approaches still have some limitations such as consuming high computation or suffering from errors. In this work, we explore the use of a statistical metric as the basis for both projections and reduced-resolution versions of data, with a particular focus on preserving one key trait in data, namely variation. We use two different casemore » studies to explore this idea, one that uses a synthetic dataset, and another that uses a large ensemble collection produced by an atmospheric modeling code to study long-term changes in global precipitation. The primary findings of our work are that in terms of preserving the variation signal inherent in data, that using a statistical measure more faithfully preserves this key characteristic across both multi-dimensional projections and multi-resolution representations than a methodology based upon averaging.« less

Minimal disease detection of B-cell lymphoproliferative disorders by flow cytometry: multidimensional cluster analysis.

PubMed

Duque, Ricardo E

2012-04-01

Flow cytometric analysis of cell suspensions involves the sequential 'registration' of intrinsic and extrinsic parameters of thousands of cells in list mode files. Thus, it is almost irresistible to describe phenomena in numerical terms or by 'ratios' that have the appearance of 'accuracy' due to the presence of numbers obtained from thousands of cells. The concepts involved in the detection and characterization of B cell lymphoproliferative processes are revisited in this paper by identifying parameters that, when analyzed appropriately, are both necessary and sufficient. The neoplastic process (cluster) can be visualized easily because the parameters that distinguish it form a cluster in multidimensional space that is unique and distinguishable from neighboring clusters that are not of diagnostic interest but serve to provide a background. For B cell neoplasia it is operationally necessary to identify the multidimensional space occupied by a cluster whose kappa:lambda ratio is 100:0 or 0:100. Thus, the concept of kappa:lambda ratio is without meaning and would not detect B cell neoplasia in an unacceptably high number of cases.

Detecting Shielded Special Nuclear Materials Using Multi-Dimensional Neutron Source and Detector Geometries

NASA Astrophysics Data System (ADS)

Santarius, John; Navarro, Marcos; Michalak, Matthew; Fancher, Aaron; Kulcinski, Gerald; Bonomo, Richard

2016-10-01

A newly initiated research project will be described that investigates methods for detecting shielded special nuclear materials by combining multi-dimensional neutron sources, forward/adjoint calculations modeling neutron and gamma transport, and sparse data analysis of detector signals. The key tasks for this project are: (1) developing a radiation transport capability for use in optimizing adaptive-geometry, inertial-electrostatic confinement (IEC) neutron source/detector configurations for neutron pulses distributed in space and/or phased in time; (2) creating distributed-geometry, gas-target, IEC fusion neutron sources; (3) applying sparse data and noise reduction algorithms, such as principal component analysis (PCA) and wavelet transform analysis, to enhance detection fidelity; and (4) educating graduate and undergraduate students. Funded by DHS DNDO Project 2015-DN-077-ARI095.

Application of random coherence order selection in gradient-enhanced multidimensional NMR

NASA Astrophysics Data System (ADS)

Bostock, Mark J.; Nietlispach, Daniel

2016-03-01

Development of multidimensional NMR is essential to many applications, for example in high resolution structural studies of biomolecules. Multidimensional techniques enable separation of NMR signals over several dimensions, improving signal resolution, whilst also allowing identification of new connectivities. However, these advantages come at a significant cost. The Fourier transform theorem requires acquisition of a grid of regularly spaced points to satisfy the Nyquist criterion, while frequency discrimination and acquisition of a pure phase spectrum require acquisition of both quadrature components for each time point in every indirect (non-acquisition) dimension, adding a factor of 2 N -1 to the number of free- induction decays which must be acquired, where N is the number of dimensions. Compressed sensing (CS) ℓ 1-norm minimisation in combination with non-uniform sampling (NUS) has been shown to be extremely successful in overcoming the Nyquist criterion. Previously, maximum entropy reconstruction has also been used to overcome the limitation of frequency discrimination, processing data acquired with only one quadrature component at a given time interval, known as random phase detection (RPD), allowing a factor of two reduction in the number of points for each indirect dimension (Maciejewski et al. 2011 PNAS 108 16640). However, whilst this approach can be easily applied in situations where the quadrature components are acquired as amplitude modulated data, the same principle is not easily extended to phase modulated (P-/N-type) experiments where data is acquired in the form exp (iωt) or exp (-iωt), and which make up many of the multidimensional experiments used in modern NMR. Here we demonstrate a modification of the CS ℓ 1-norm approach to allow random coherence order selection (RCS) for phase modulated experiments; we generalise the nomenclature for RCS and RPD as random quadrature detection (RQD). With this method, the power of RQD can be extended to the full suite of experiments available to modern NMR spectroscopy, allowing resolution enhancements for all indirect dimensions; alone or in combination with NUS, RQD can be used to improve experimental resolution, or shorten experiment times, of considerable benefit to the challenging applications undertaken by modern NMR.

Multidimensional data analysis in immunophenotyping.

PubMed

Loken, M R

2001-05-01

The complexity of cell populations requires careful selection of reagents to detect cells of interest and distinguish them from other types. Additional reagents are frequently used to provide independent criteria for cell identification. Two or three monoclonal antibodies in combination with forward and right-angle light scatter generate a data set that is difficult to visualize because the data must be represented in four- or five-dimensional space. The separation between cell populations provided by the multiple characteristics is best visualized by multidimensional analysis using all parameters simultaneously to identify populations within the resulting hyperspace. Groups of cells are distinguished based on a combination of characteristics not apparent in any usual two-dimensional representation of the data.

Synthesis-identification integration: One-pot hydrothermal preparation of fluorescent nitrogen-doped carbon nanodots for differentiating nucleobases with the aid of multivariate chemometrics analysis.

PubMed

Zhuang, Qianfen; Cao, Wei; Ni, Yongnian; Wang, Yong

2018-08-01

Most of the conventional multidimensional differential sensors currently need at least two-step fabrication, namely synthesis of probe(s) and identification of multiple analytes by mixing of analytes with probe(s), and were conducted using multiple sensing elements or several devices. In the study, we chose five different nucleobases (adenine, cytosine, guanine, thymine, and uracil) as model analytes, and found that under hydrothermal conditions, sodium citrate could react directly with various nucleobases to yield different nitrogen-doped carbon nanodots (CDs). The CDs synthesized from different nucleobases exhibited different fluorescent properties, leading to their respective characteristic fluorescence spectra. Hence, we combined the fluorescence spectra of the CDs with advanced chemometrics like principle component analysis (PCA), hierarchical cluster analysis (HCA), K-nearest neighbor (KNN) and soft independent modeling of class analogy (SIMCA), to present a conceptually novel "synthesis-identification integration" strategy to construct a multidimensional differential sensor for nucleobase discrimination. Single-wavelength excitation fluorescence spectral data, single-wavelength emission fluorescence spectral data, and fluorescence Excitation-Emission Matrices (EEMs) of the CDs were respectively used as input data of the differential sensor. The results showed that the discrimination ability of the multidimensional differential sensor with EEM data set as input data was superior to those with single-wavelength excitation/emission fluorescence data set, suggesting that increasing the number of the data input could improve the discrimination power. Two supervised pattern recognition methods, namely KNN and SIMCA, correctly identified the five nucleobases with a classification accuracy of 100%. The proposed "synthesis-identification integration" strategy together with a multidimensional array of experimental data holds great promise in the construction of differential sensors. Copyright © 2018 Elsevier B.V. All rights reserved.

Column-coupling strategies for multidimensional electrophoretic separation techniques.

PubMed

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 different intermediate and final detection methods implemented for such separations.

A Method for Generating Reduced-Order Linear Models of Multidimensional Supersonic Inlets

NASA Technical Reports Server (NTRS)

Chicatelli, Amy; Hartley, Tom T.

1998-01-01

Simulation of high speed propulsion systems may be divided into two categories, nonlinear and linear. The nonlinear simulations are usually based on multidimensional computational fluid dynamics (CFD) methodologies and tend to provide high resolution results that show the fine detail of the flow. Consequently, these simulations are large, numerically intensive, and run much slower than real-time. ne linear simulations are usually based on large lumping techniques that are linearized about a steady-state operating condition. These simplistic models often run at or near real-time but do not always capture the detailed dynamics of the plant. Under a grant sponsored by the NASA Lewis Research Center, Cleveland, Ohio, a new method has been developed that can be used to generate improved linear models for control design from multidimensional steady-state CFD results. This CFD-based linear modeling technique provides a small perturbation model that can be used for control applications and real-time simulations. It is important to note the utility of the modeling procedure; all that is needed to obtain a linear model of the propulsion system is the geometry and steady-state operating conditions from a multidimensional CFD simulation or experiment. This research represents a beginning step in establishing a bridge between the controls discipline and the CFD discipline so that the control engineer is able to effectively use multidimensional CFD results in control system design and analysis.

The application of a multi-dimensional assessment approach to talent identification in Australian football.

PubMed

Woods, Carl T; Raynor, Annette J; Bruce, Lyndell; McDonald, Zane; Robertson, Sam

2016-07-01

This study investigated whether a multi-dimensional assessment could assist with talent identification in junior Australian football (AF). Participants were recruited from an elite under 18 (U18) AF competition and classified into two groups; talent identified (State U18 Academy representatives; n = 42; 17.6 ± 0.4 y) and non-talent identified (non-State U18 Academy representatives; n = 42; 17.4 ± 0.5 y). Both groups completed a multi-dimensional assessment, which consisted of physical (standing height, dynamic vertical jump height and 20 m multistage fitness test), technical (kicking and handballing tests) and perceptual-cognitive (video decision-making task) performance outcome tests. A multivariate analysis of variance tested the main effect of status on the test criterions, whilst a receiver operating characteristic curve assessed the discrimination provided from the full assessment. The talent identified players outperformed their non-talent identified peers in each test (P < 0.05). The receiver operating characteristic curve reflected near perfect discrimination (AUC = 95.4%), correctly classifying 95% and 86% of the talent identified and non-talent identified participants, respectively. When compared to single assessment approaches, this multi-dimensional assessment reflects a more comprehensive means of talent identification in AF. This study further highlights the importance of assessing multi-dimensional performance qualities when identifying talented team sports.

Is Going Beyond Rasch Analysis Necessary to Assess the Construct Validity of a Motor Function Scale?

PubMed

Guillot, Tiffanie; Roche, Sylvain; Rippert, Pascal; Hamroun, Dalil; Iwaz, Jean; Ecochard, René; Vuillerot, Carole

2018-04-03

To examine whether a Rasch analysis is sufficient to establish the construct validity of the Motor Function Measure (MFM) and discuss whether weighting the MFM item scores would improve the MFM construct validity. Observational cross-sectional multicenter study. Twenty-three physical medicine departments, neurology departments, or reference centers for neuromuscular diseases. Patients (N=911) aged 6 to 60 years with Charcot-Marie-Tooth disease (CMT), facioscapulohumeral dystrophy (FSHD), or myotonic dystrophy type 1 (DM1). None. Comparison of the goodness-of-fit of the confirmatory factor analysis (CFA) model vs that of a modified multidimensional Rasch model on MFM item scores in each considered disease. The CFA model showed good fit to the data and significantly better goodness of fit than the modified multidimensional Rasch model regardless of the disease (P<.001). Statistically significant differences in item standardized factor loadings were found between DM1, CMT, and FSHD in only 6 of 32 items (items 6, 27, 2, 7, 9 and 17). For multidimensional scales designed to measure patient abilities in various diseases, a Rasch analysis might not be the most convenient, whereas a CFA is able to establish the scale construct validity and provide weights to adapt the item scores to a specific disease. Copyright © 2018 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Dynamic analysis, transformation, dissemination and applications of scientific multidimensional data in ArcGIS Platform

NASA Astrophysics Data System (ADS)

Shrestha, S. R.; Collow, T. W.; Rose, B.

2016-12-01

Scientific datasets are generated from various sources and platforms but they are typically produced either by earth observation systems or by modelling systems. These are widely used for monitoring, simulating, or analyzing measurements that are associated with physical, chemical, and biological phenomena over the ocean, atmosphere, or land. A significant subset of scientific datasets stores values directly as rasters or in a form that can be rasterized. This is where a value exists at every cell in a regular grid spanning the spatial extent of the dataset. Government agencies like NOAA, NASA, EPA, USGS produces large volumes of near real-time, forecast, and historical data that drives climatological and meteorological studies, and underpins operations ranging from weather prediction to sea ice loss. Modern science is computationally intensive because of the availability of an enormous amount of scientific data, the adoption of data-driven analysis, and the need to share these dataset and research results with the public. ArcGIS as a platform is sophisticated and capable of handling such complex domain. We'll discuss constructs and capabilities applicable to multidimensional gridded data that can be conceptualized as a multivariate space-time cube. Building on the concept of a two-dimensional raster, a typical multidimensional raster dataset could contain several "slices" within the same spatial extent. We will share a case from the NOAA Climate Forecast Systems Reanalysis (CFSR) multidimensional data as an example of how large collections of rasters can be efficiently organized and managed through a data model within a geodatabase called "Mosaic dataset" and dynamically transformed and analyzed using raster functions. A raster function is a lightweight, raster-valued transformation defined over a mixed set of raster and scalar input. That means, just like any tool, you can provide a raster function with input parameters. It enables dynamic processing of only the data that's being displayed on the screen or requested by an application. We will present the dynamic processing and analysis of CFSR data using the chains of raster function and share it as dynamic multidimensional image service. This workflow and capabilities can be easily applied to any scientific data formats that are supported in mosaic dataset.

Evidence against the continuum structure underlying motivation measures derived from self-determination theory.

PubMed

Chemolli, Emanuela; Gagné, Marylène

2014-06-01

Self-determination theory (SDT) proposes a multidimensional conceptualization of motivation in which the different regulations are said to fall along a continuum of self-determination. The continuum has been used as a basis for using a relative autonomy index as a means to create motivational scores. Rasch analysis was used to verify the continuum structure of the Multidimensional Work Motivation Scale and of the Academic Motivation Scale. We discuss the concept of continuum against SDT's conceptualization of motivation and argue against the use of the relative autonomy index on the grounds that evidence for a continuum structure underlying the regulations is weak and because the index is statistically problematic. We suggest exploiting the full richness of SDT's multidimensional conceptualization of motivation through the use of alternative scoring methods when investigating motivational dynamics across life domains.

Factors associated with multidimensional aspect of post-stroke fatigue in acute stroke period.

PubMed

Mutai, Hitoshi; Furukawa, Tomomi; Houri, Ayumi; Suzuki, Akihito; Hanihara, Tokiji

2017-04-01

Post-stroke fatigue (PSF) is a frequent and distressing consequence of stroke, and can be both acute and long lasting. We aimed to investigate multidimensional aspects of acute PSF and to determine the clinical factors relevant to acute PSF. We collected data of 101 patients admitted to the hospital for acute stroke. PSF was assessed using the Multidimensional Fatigue Inventory within 2 weeks of stroke. Measures included Mini-Mental State Examination, Hospital Anxiety and Depression Scale, and Functional Independence Measure. Stroke character, lesion location, and clinical variables that potentially influence PSF were also collected. The prevalence of pathological fatigue is 56.4% within 2 weeks of stroke. Binary logistic regression analysis revealed that anxiety was the only predictor for presence of PSF (OR=1.32, 95% CI: 1.13-1.53, P<0.001). Multivariate stepwise regression analysis showed anxiety, right lesion side, thalamus, and/or brainstem were independently associated with general fatigue, right lesion side, depression, diabetes mellitus, and anxiety with physical fatigue, depression with reduced activity, depression, and BMI with reduced motivation, depression, and diabetes mellitus with mental fatigue. PSF was highly prevalent in the acute phase, and specific factors including lesion location (right side lesion, thalamic and brainstem lesion), anxiety, and depression were independently associated with multidimensional aspects of PSF. Further study is needed to elucidate how specific structural lesions and anxiety symptoms relate to the development of early fatigue following stroke. Copyright © 2016 Elsevier B.V. All rights reserved.

Review of nutritional screening and assessment tools and clinical outcomes in heart failure.

PubMed

Lin, Hong; Zhang, Haifeng; Lin, Zheng; Li, Xinli; Kong, Xiangqin; Sun, Gouzhen

2016-09-01

Recent studies have suggested that undernutrition as defined using multidimensional nutritional evaluation tools may affect clinical outcomes in heart failure (HF). The evidence supporting this correlation is unclear. Therefore, we conducted this systematic review to critically appraise the use of multidimensional evaluation tools in the prediction of clinical outcomes in HF. We performed descriptive analyses of all identified articles involving qualitative analyses. We used STATA to conduct meta-analyses when at least three studies that tested the same type of nutritional assessment or screening tools and used the same outcome were identified. Sensitivity analyses were conducted to validate our positive results. We identified 17 articles with qualitative analyses and 11 with quantitative analysis after comprehensive literature searching and screening. We determined that the prevalence of malnutrition is high in HF (range 16-90 %), particularly in advanced and acute decompensated HF (approximate range 75-90 %). Undernutrition as identified by multidimensional evaluation tools may be significantly associated with hospitalization, length of stay and complications and is particularly strongly associated with high mortality. The meta-analysis revealed that compared with other tools, Mini Nutritional Assessment (MNA) scores were the strongest predictors of mortality in HF [HR (4.32, 95 % CI 2.30-8.11)]. Our results remained reliable after conducting sensitivity analyses. The prevalence of malnutrition is high in HF, particularly in advanced and acute decompensated HF. Moreover, undernutrition as identified by multidimensional evaluation tools is significantly associated with unfavourable prognoses and high mortality in HF.

Comprehensive lipidomic analysis of human plasma using multidimensional liquid- and gas-phase separations: Two-dimensional liquid chromatography-mass spectrometry vs. liquid chromatography-trapped-ion-mobility-mass spectrometry.

PubMed

Baglai, Anna; Gargano, Andrea F G; Jordens, Jan; Mengerink, Ynze; Honing, Maarten; van der Wal, Sjoerd; Schoenmakers, Peter J

2017-12-29

Recent advancements in separation science have resulted in the commercialization of multidimensional separation systems that provide higher peak capacities and, hence, enable a more-detailed characterization of complex mixtures. In particular, two powerful analytical tools are increasingly used by analytical scientists, namely online comprehensive two-dimensional liquid chromatography (LC×LC, having a second-dimension separation in the liquid phase) and liquid chromatography-ion mobility-spectrometry (LC-IMS, second dimension separation in the gas phase). The goal of the current study was a general assessment of the liquid-chromatography-trapped-ion-mobility-mass spectrometry (LC-TIMS-MS) and comprehensive two-dimensional liquid chromatography-mass spectrometry (LC×LC-MS) platforms for untargeted lipid mapping in human plasma. For the first time trapped-ion-mobility spectrometry (TIMS) was employed for the separation of the major lipid classes and ion-mobility-derived collision-cross-section values were determined for a number of lipid standards. The general effects of a number of influencing parameters have been inspected and possible directions for improvements are discussed. We aimed to provide a general indication and practical guidelines for the analyst to choose an efficient multidimensional separation platform according to the particular requirements of the application. Analysis time, orthogonality, peak capacity, and an indicative measure for the resolving power are discussed as main characteristics for multidimensional separation systems. Copyright © 2017 Elsevier B.V. All rights reserved.

Two chemically distinct light-absorbing pools of urban organic aerosols: A comprehensive multidimensional analysis of trends.

PubMed

Paula, Andreia S; Matos, João T V; Duarte, Regina M B O; Duarte, Armando C

2016-02-01

The chemical and light-absorption dynamics of organic aerosols (OAs), a master variable in the atmosphere, have yet to be resolved. This study uses a comprehensive multidimensional analysis approach for exploiting simultaneously the compositional changes over a molecular size continuum and associated light-absorption (ultraviolet absorbance and fluorescence) properties of two chemically distinct pools of urban OAs chromophores. Up to 45% of aerosol organic carbon (OC) is soluble in water and consists of a complex mixture of fluorescent and UV-absorbing constituents, with diverse relative abundances, hydrophobic, and molecular weight (Mw) characteristics between warm and cold periods. In contrast, the refractory alkaline-soluble OC pool (up to 18%) is represented along a similar Mw and light-absorption continuum throughout the different seasons. Results suggest that these alkaline-soluble chromophores may actually originate from primary OAs sources in the urban site. This work shows that the comprehensive multidimensional analysis method is a powerful and complementary tool for the characterization of OAs fractions. The great diversity in the chemical composition and optical properties of OAs chromophores, including both water-soluble and alkaline-soluble OC, may be an important contribution to explain the contrasting photo-reactivity and atmospheric behavior of OAs. Copyright © 2015 Elsevier Ltd. All rights reserved.

Decoupling Principle Analysis and Development of a Parallel Three-Dimensional Force Sensor

PubMed Central

Zhao, Yanzhi; Jiao, Leihao; Weng, Dacheng; Zhang, Dan; Zheng, Rencheng

2016-01-01

In the development of the multi-dimensional force sensor, dimension coupling is the ubiquitous factor restricting the improvement of the measurement accuracy. To effectively reduce the influence of dimension coupling on the parallel multi-dimensional force sensor, a novel parallel three-dimensional force sensor is proposed using a mechanical decoupling principle, and the influence of the friction on dimension coupling is effectively reduced by making the friction rolling instead of sliding friction. In this paper, the mathematical model is established by combining with the structure model of the parallel three-dimensional force sensor, and the modeling and analysis of mechanical decoupling are carried out. The coupling degree (ε) of the designed sensor is defined and calculated, and the calculation results show that the mechanical decoupling parallel structure of the sensor possesses good decoupling performance. A prototype of the parallel three-dimensional force sensor was developed, and FEM analysis was carried out. The load calibration and data acquisition experiment system are built, and then calibration experiments were done. According to the calibration experiments, the measurement accuracy is less than 2.86% and the coupling accuracy is less than 3.02%. The experimental results show that the sensor system possesses high measuring accuracy, which provides a basis for the applied research of the parallel multi-dimensional force sensor. PMID:27649194

Design Requirements for Unmanned Rotorcraft Used in Low-Risk Concepts of Operation

NASA Technical Reports Server (NTRS)

Hayhurst, Kelly J.; Maddalon, Jeffrey M.; Neogi, Natasha A.; Verstynen, Harry A.

2016-01-01

This technical report presents the results of the second of two research studies on design and performance requirements supporting airworthiness certification of midrange unmanned aircraft systems (UAS) intended for commercial use. The two studies focused attention on UAS in the middle of the multidimensional spectrum of UAS; that is, UAS with attributes and capabilities exceeding the criteria to operate under Part 107 of the Federal Aviation Regulations (FARs), but without the design or operational capabilities to comply with the airworthiness standards for commercially-operated manned aircraft. The goal of the two studies was to help address the gap in airworthiness standards for some UAS that fall between the extremes.

Droplet states in quantum XXZ spin systems on general graphs

NASA Astrophysics Data System (ADS)

Fischbacher, C.; Stolz, G.

2018-05-01

We study XXZ spin systems on general graphs. In particular, we describe the formation of droplet states near the bottom of the spectrum in the Ising phase of the model, where the Z-term dominates the XX-term. As key tools, we use particle number conservation of XXZ systems and symmetric products of graphs with their associated adjacency matrices and Laplacians. Of particular interest to us are strips and multi-dimensional Euclidean lattices, for which we discuss the existence of spectral gaps above the droplet regime. We also prove a Combes-Thomas bound which shows that the eigenstates in the droplet regime are exponentially small perturbations of strict (classical) droplets.

Rapid 3D NMR using the filter diagonalization method: application to oligosaccharides derivatized with 13C-labeled acetyl groups

NASA Astrophysics Data System (ADS)

Armstrong, Geoffrey S.; Cano, Kristin E.; Mandelshtam, Vladimir A.; Shaka, A. J.; Bendiak, Brad

2004-09-01

Rapid 3D NMR spectroscopy of oligosaccharides having isotopically labeled acetyl "isotags" was made possible with high resolution in the indirect dimensions using the filter diagonalization method (FDM). A pulse sequence was designed for the optimal correlation of acetyl methyl protons, methyl carbons, and carbonyl carbons. The multi-dimensional nature of the FDM, coupled with the advantages of constant-time evolution periods, resulted in marked improvements over Fourier transform (FT) and mirror-image linear prediction (MI-LP) processing methods. The three methods were directly compared using identical data sets. A highly resolved 3D spectrum was achieved with the FDM using a very short experimental time (28 min).

Rapid 3D NMR using the filter diagonalization method: application to oligosaccharides derivatized with 13C-labeled acetyl groups.

PubMed

Armstrong, Geoffrey S; Cano, Kristin E; Mandelshtam, Vladimir A; Shaka, A J; Bendiak, Brad

2004-09-01

Rapid 3D NMR spectroscopy of oligosaccharides having isotopically labeled acetyl "isotags" was made possible with high resolution in the indirect dimensions using the filter diagonalization method (FDM). A pulse sequence was designed for the optimal correlation of acetyl methyl protons, methyl carbons, and carbonyl carbons. The multi-dimensional nature of the FDM, coupled with the advantages of constant-time evolution periods, resulted in marked improvements over Fourier transform (FT) and mirror-image linear prediction (MI-LP) processing methods. The three methods were directly compared using identical data sets. A highly resolved 3D spectrum was achieved with the FDM using a very short experimental time (28 min).

Two-dimensional fourier transform spectrometer

DOEpatents

DeFlores, Lauren; Tokmakoff, Andrei

2016-10-25

The present invention relates to a system and methods for acquiring two-dimensional Fourier transform (2D FT) spectra. Overlap of a collinear pulse pair and probe induce a molecular response which is collected by spectral dispersion of the signal modulated probe beam. Simultaneous collection of the molecular response, pulse timing and characteristics permit real time phasing and rapid acquisition of spectra. Full spectra are acquired as a function of pulse pair timings and numerically transformed to achieve the full frequency-frequency spectrum. This method demonstrates the ability to acquire information on molecular dynamics, couplings and structure in a simple apparatus. Multi-dimensional methods can be used for diagnostic and analytical measurements in the biological, biomedical, and chemical fields.

Two-dimensional fourier transform spectrometer

DOEpatents

DeFlores, Lauren; Tokmakoff, Andrei

2013-09-03

The present invention relates to a system and methods for acquiring two-dimensional Fourier transform (2D FT) spectra. Overlap of a collinear pulse pair and probe induce a molecular response which is collected by spectral dispersion of the signal modulated probe beam. Simultaneous collection of the molecular response, pulse timing and characteristics permit real time phasing and rapid acquisition of spectra. Full spectra are acquired as a function of pulse pair timings and numerically transformed to achieve the full frequency-frequency spectrum. This method demonstrates the ability to acquire information on molecular dynamics, couplings and structure in a simple apparatus. Multi-dimensional methods can be used for diagnostic and analytical measurements in the biological, biomedical, and chemical fields.

Psychological distress increases the risk of falling into poverty amongst older Australians: the overlooked costs-of-illness.

PubMed

Callander, Emily J; Schofield, Deborah J

2018-04-17

This paper aimed to identify whether high psychological distress is associated with an increased risk of income and multidimensional poverty amongst older adults in Australia. We undertook longitudinal analysis of the nationally representative Household Income and Labour Dynamics in Australian (HILDA) survey using modified Poisson regression models to estimate the relative risk of falling into income poverty and multidimensional poverty between 2010 and 2012 for males and females, adjusting for age, employment status, place of residence, marital status and housing tenure; and Population Attributable Risk methodology to estimate the proportion of poverty directly attributable to psychological distress, measured by the Kessler 10 scale. For males, having high psychological distress increased the risk of falling into income poverty by 1.68 (95% CI: 1.02 to 2.75) and the risk of falling into multidimensional poverty by 3.40 (95% CI: 1.91 to 6.04). For females, there was no significant difference in the risk of falling into income poverty between those with high and low psychological distress (p = 0.1008), however having high psychological distress increased the risk of falling into multidimensional poverty by 2.15 (95% CI: 1.30 to 3.55). Between 2009 and 2012, 8.0% of income poverty cases for people aged 65 and over (95% CI: 7.8% to 8.4%), and 19.5% of multidimensional poverty cases for people aged 65 and over (95% CI: 19.2% to 19.9%) can be attributed to high psychological distress. The elevated risk of falling into income and multidimensional poverty has been an overlooked cost of poor mental health.

Effect of asthma on falling into poverty: the overlooked costs of illness.

PubMed

Callander, Emily J; Schofield, Deborah J

2015-05-01

Studies on the indirect costs of asthma have taken a narrow view of how the condition affects the living standards of patients by examining only the association with employment and income. To build on the current cost-of-illness literature and identify whether having asthma is associated with an increased risk of poverty, thus giving a more complete picture of the costs of asthma to individuals and society. Longitudinal analysis of the nationally representative Household Income and Labour Dynamics in Australian survey to estimate the relative risk of income poverty, multidimensional poverty, and long-term multidimensional poverty between 2007 and 2012 and population attributable risk method to estimate the proportion of poverty between 2007 and 2012 directly attributable to asthma. No significant difference was found in the risk of falling into income poverty between those with and without asthma (P = .07). Having asthma increased the risk of falling into multidimensional poverty by 1.35 (95% confidence interval [CI], 1.01-1.83) and the risk of falling into chronic multidimensional poverty by 2.22 (95% CI, 1.20-4.10). Between 2007 and 2012, a total of 5.2% of income poverty cases (95% CI, 5.1%-5.4%), 7.8% of multidimensional poverty cases (95% CI, 7.7%-8.0%), and 19.6% of chronic multidimensional poverty cases (95% CI, 19.2%-20.0%) can be attributed to asthma. Asthma is associated with an increased risk of falling into poverty. This should be taken into consideration when considering the suitability of different treatment options for patients with asthma. Copyright © 2015 American College of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Linear Power Spectra in Cold+Hot Dark Matter Models: Analytical Approximations and Applications

NASA Astrophysics Data System (ADS)

Ma, Chung-Pei

1996-11-01

This paper presents simple analytic approximations to the linear power spectra, linear growth rates, and rms mass fluctuations for both components in a family of cold + hot dark matter (CDM + HDM) models that are of current cosmological interest. The formulas are valid for a wide range of wavenumbers, neutrino fractions, redshifts, and Hubble constants: k ≤ 1O h Mpc-1, 0.05 ≤ Ωv le; 0.3 0 ≤ z ≤ 15, and 0.5 ≤ h ≤ 0.8. A new, redshift-dependent shape parameter, Γv = a½Ωvh2, is introduced to simplify the multidimensional parameter space and to characterize the effect of massive neutrinos on the power spectrum. The physical origin of Γv lies in the neutrino free-streaming process, and the analytic approximations can be simplified to depend only on this variable and Ωv. Linear calculations with these power spectra as input are performed to compare the predictions of Ωv ≤ 0.3 models with observational constraints from the reconstructed linear power spectrum and cluster abundance. The usual assumption of an exact scale-invariant primordial power spectrum is relaxed to allow a spectral index of 0.8 ≤ n ≤ 1. It is found that a slight tilt of n = 0.9 (no tensor mode) or n = 0.95 (with tensor mode) in 0.t-0.2 CDM + HDM models gives a power spectrum similar to that of an open CDM model with a shape parameter Γ = 0.25, providing good agreement with the power spectrum reconstructed by Peacock & Dodds and the observed cluster abundance at low redshifts. Late galaxy formation at high redshifts, however, will be a more severe problem in tilted models.

Comprehensive analysis of a multidimensional liquid chromatography mass spectrometry dataset acquired on a quadrupole selecting, quadrupole collision cell, time-of-flight mass spectrometer: I. How much of the data is theoretically interpretable by search engines?

PubMed

Chalkley, Robert J; Baker, Peter R; Hansen, Kirk C; Medzihradszky, Katalin F; Allen, Nadia P; Rexach, Michael; Burlingame, Alma L

2005-08-01

An in-depth analysis of a multidimensional chromatography-mass spectrometry dataset acquired on a quadrupole selecting, quadrupole collision cell, time-of-flight (QqTOF) geometry instrument was carried out. A total of 3269 CID spectra were acquired. Through manual verification of database search results and de novo interpretation of spectra 2368 spectra could be confidently determined as predicted tryptic peptides. A detailed analysis of the non-matching spectra was also carried out, highlighting what the non-matching spectra in a database search typically are composed of. The results of this comprehensive dataset study demonstrate that QqTOF instruments produce information-rich data of which a high percentage of the data is readily interpretable.

The risk of falling into poverty after developing heart disease: a survival analysis.

PubMed

Callander, Emily J; Schofield, Deborah J

2016-07-15

Those with a low income are known to have a higher risk of developing heart disease. However, the inverse relationship - falling into income poverty after developing heart disease has not been explored with longitudinal data. This paper aims to determine if those with heart disease have an elevated risk of falling into poverty. Survival analysis was conducted using the longitudinal Household Income and Labour Dynamics in Australia survey, between the years 2007 and 2012. The study focused on the Australian population aged 21 years and over in 2007 who were not already in poverty and did not already have heart disease, who were followed from 2007 to 2012. Cox regression models adjusting for age, sex and time-varying co-variates (marital status, home ownership and remoteness of area of residence) were constructed to assess the risk of falling into poverty. For those aged 20 who developed heart disease, the hazard ratio for falling into income poverty was 9.24 (95 % CI: 8.97-9.51) and for falling into multidimensional poverty the hazard ratio was 14.21 (95 % CI: 13.76-14.68); for those aged 40 the hazard ratio for falling into income poverty was 3.45 (95 % CI: 3.39-3.51) and for multidimensional poverty, 5.20 (95 % CI: 5.11-5.29); and for those aged 60 the hazard ratio for falling into income poverty was 1.29 (95 % CI: 1.28-1.30) and for multidimensional poverty, 1.52 (95 % CI: 1.51-1.54), relative those who never developed heart disease. The risk for both income and multidimensional poverty decreases with age up to the age of 70, over which, those who developed heart disease had a reduced risk of poverty. For those under the age of 70, developing heart disease is associated with an increased risk of falling into both income poverty and multidimensional poverty.

Pathology and immune reactivity: understanding multidimensionality in pulmonary tuberculosis.

PubMed

Dorhoi, Anca; Kaufmann, Stefan H E

2016-03-01

Heightened morbidity and mortality in pulmonary tuberculosis (TB) are consequences of complex disease processes triggered by the causative agent, Mycobacterium tuberculosis (Mtb). Mtb modulates inflammation at distinct stages of its intracellular life. Recognition and phagocytosis, replication in phagosomes and cytosol escape induce tightly regulated release of cytokines [including interleukin (IL)-1, tumor necrosis factor (TNF), IL-10], chemokines, lipid mediators, and type I interferons (IFN-I). Mtb occupies various lung lesions at sites of pathology. Bacteria are barely detectable at foci of lipid pneumonia or in perivascular/bronchiolar cuffs. However, abundant organisms are evident in caseating granulomas and at the cavity wall. Such lesions follow polar trajectories towards fibrosis, encapsulation and mineralization or liquefaction, extensive matrix destruction, and tissue injury. The outcome is determined by immune factors acting in concert. Gradients of cytokines and chemokines (CCR2, CXCR2, CXCR3/CXCR5 agonists; TNF/IL-10, IL-1/IFN-I), expression of activation/death markers on immune cells (TNF receptor 1, PD-1, IL-27 receptor) or abundance of enzymes [arginase-1, matrix metalloprotease (MMP)-1, MMP-8, MMP-9] drive genesis and progression of lesions. Distinct lesions coexist such that inflammation in TB encompasses a spectrum of tissue changes. A better understanding of the multidimensionality of immunopathology in TB will inform novel therapies against this pulmonary disease.

An Augmented Two-Layer Model Captures Nonlinear Analog Spatial Integration Effects in Pyramidal Neuron Dendrites

PubMed Central

JADI, MONIKA P.; BEHABADI, BARDIA F.; POLEG-POLSKY, ALON; SCHILLER, JACKIE; MEL, BARTLETT W.

2014-01-01

In pursuit of the goal to understand and eventually reproduce the diverse functions of the brain, a key challenge lies in reverse engineering the peculiar biology-based “technology” that underlies the brain’s remarkable ability to process and store information. The basic building block of the nervous system is the nerve cell, or “neuron,” yet after more than 100 years of neurophysiological study and 60 years of modeling, the information processing functions of individual neurons, and the parameters that allow them to engage in so many different types of computation (sensory, motor, mnemonic, executive, etc.) remain poorly understood. In this paper, we review both historical and recent findings that have led to our current understanding of the analog spatial processing capabilities of dendrites, the major input structures of neurons, with a focus on the principal cell type of the neocortex and hippocampus, the pyramidal neuron (PN). We encapsulate our current understanding of PN dendritic integration in an abstract layered model whose spatially sensitive branch-subunits compute multidimensional sigmoidal functions. Unlike the 1-D sigmoids found in conventional neural network models, multidimensional sigmoids allow the cell to implement a rich spectrum of nonlinear modulation effects directly within their dendritic trees. PMID:25554708

Recent developments in multidimensional transport methods for the APOLLO 2 lattice code

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zmijarevic, I.; Sanchez, R.

1995-12-31

A usual method of preparation of homogenized cross sections for reactor coarse-mesh calculations is based on two-dimensional multigroup transport treatment of an assembly together with an appropriate leakage model and reaction-rate-preserving homogenization technique. The actual generation of assembly spectrum codes based on collision probability methods is capable of treating complex geometries (i.e., irregular meshes of arbitrary shape), thus avoiding the modeling error that was introduced in codes with traditional tracking routines. The power and architecture of current computers allow the treatment of spatial domains comprising several mutually interacting assemblies using fine multigroup structure and retaining all geometric details of interest.more » Increasing safety requirements demand detailed two- and three-dimensional calculations for very heterogeneous problems such as control rod positioning, broken Pyrex rods, irregular compacting of mixed- oxide (MOX) pellets at an MOX-UO{sub 2} interface, and many others. An effort has been made to include accurate multi- dimensional transport methods in the APOLLO 2 lattice code. These include extension to three-dimensional axially symmetric geometries of the general-geometry collision probability module TDT and the development of new two- and three-dimensional characteristics methods for regular Cartesian meshes. In this paper we discuss the main features of recently developed multidimensional methods that are currently being tested.« less

Factor structure and gender stability in the multidimensional condom attitudes scale.

PubMed

Starosta, Amy J; Berghoff, Christopher R; Earleywine, Mitch

2015-06-01

Sexually transmitted infections continue to trouble the United States and can be attenuated through increased condom use. Attitudes about condoms are an important multidimensional factor that can affect sexual health choices and have been successfully measured using the Multidimensional Condom Attitudes Scale (MCAS). Such attitudes have the potential to vary between men and women, yet little work has been undertaken to identify if the MCAS accurately captures attitudes without being influenced by underlying gender biases. We examined the factor structure and gender invariance on the MCAS using confirmatory factor analysis and item response theory, within-subscale differential item functioning analyses. More than 770 participants provided data via the Internet. Results of differential item functioning analyses identified three items as differentially functioning between the genders, and removal of these items is recommended. Findings confirmed the previously hypothesized multidimensional nature of condom attitudes and the five-factor structure of the MCAS even after the removal of the three problematic items. In general, comparisons across genders using the MCAS seem reasonable from a methodological standpoint. Results are discussed in terms of improving sexual health research and interventions. © The Author(s) 2014.

Data analytics and parallel-coordinate materials property charts

NASA Astrophysics Data System (ADS)

Rickman, Jeffrey M.

2018-01-01

It is often advantageous to display material properties relationships in the form of charts that highlight important correlations and thereby enhance our understanding of materials behavior and facilitate materials selection. Unfortunately, in many cases, these correlations are highly multidimensional in nature, and one typically employs low-dimensional cross-sections of the property space to convey some aspects of these relationships. To overcome some of these difficulties, in this work we employ methods of data analytics in conjunction with a visualization strategy, known as parallel coordinates, to represent better multidimensional materials data and to extract useful relationships among properties. We illustrate the utility of this approach by the construction and systematic analysis of multidimensional materials properties charts for metallic and ceramic systems. These charts simplify the description of high-dimensional geometry, enable dimensional reduction and the identification of significant property correlations and underline distinctions among different materials classes.

The Multidimensional Loss Scale: validating a cross-cultural instrument for measuring loss.

PubMed

Vromans, Lyn; Schweitzer, Robert D; Brough, Mark

2012-04-01

The Multidimensional Loss Scale (MLS) represents the first instrument designed specifically to index Experience of Loss Events and Loss Distress across multiple domains (cultural, social, material, and intrapersonal) relevant to refugee settlement. Recently settled Burmese adult refugees (N = 70) completed a questionnaire battery, including MLS items. Analyses explored MLS internal consistency, convergent and divergent validity, and factor structure. Cronbach alphas indicated satisfactory internal consistency for Experience of Loss Events (0.85) and Loss Distress (0.92), reflecting a unitary construct of multidimensional loss. Loss Distress did not correlate with depression or anxiety symptoms and correlated moderately with interpersonal grief and trauma symptoms, supporting divergent and convergent validity. Factor analysis provided preliminary support for a five-factor model: Loss of Symbolic Self, Loss of Interdependence, Loss of Home, Interpersonal Loss, and Loss of Intrapersonal Integrity. Received well by participants, the new scale shows promise for application in future research and practice.

Exploring children's face-space: a multidimensional scaling analysis of the mental representation of facial identity.

PubMed

Nishimura, Mayu; Maurer, Daphne; Gao, Xiaoqing

2009-07-01

We explored differences in the mental representation of facial identity between 8-year-olds and adults. The 8-year-olds and adults made similarity judgments of a homogeneous set of faces (individual hair cues removed) using an "odd-man-out" paradigm. Multidimensional scaling (MDS) analyses were performed to represent perceived similarity of faces in a multidimensional space. Five dimensions accounted optimally for the judgments of both children and adults, with similar local clustering of faces. However, the fit of the MDS solutions was better for adults, in part because children's responses were more variable. More children relied predominantly on a single dimension, namely eye color, whereas adults appeared to use multiple dimensions for each judgment. The pattern of findings suggests that children's mental representation of faces has a structure similar to that of adults but that children's judgments are influenced less consistently by that overall structure.

Computers as an Instrument for Data Analysis. Technical Report No. 11.

ERIC Educational Resources Information Center

Muller, Mervin E.

A review of statistical data analysis involving computers as a multi-dimensional problem provides the perspective for consideration of the use of computers in statistical analysis and the problems associated with large data files. An overall description of STATJOB, a particular system for doing statistical data analysis on a digital computer,…

Preliminary Development of a Multidimensional Semantic Patient Experience Measurement Questionnaire.

PubMed

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.

Violence and the Media: A Psychological Analysis.

ERIC Educational Resources Information Center

Javier, Rafael Art; Herron, William G.; Primavera, Louis

1998-01-01

Discussion of the influence of violence in the media, especially on children, presents a multidimensional analysis of factors contributing to violent behavior which makes it possible for violence in media to have its effect. A psychological analysis is offered through a discussion of the film "The Bad Lieutenant". Contains 51 references.…

Multitrait-Multimethod Analyses of Two Self-Concept Instruments.

ERIC Educational Resources Information Center

Marsh, Herbert W.; Smith, Ian D.

1982-01-01

The multidimensionality of self-concept and the use of factor analysis in the development of self-concept instruments are supported in multitrait-multimethod analyses of the Sears and Coopersmith instruments. Convergent validity and discriminate validity of subscales in factor analysis and multitrait-multimethod analysis of longitudinal data are…

PCA feature extraction for change detection in multidimensional unlabeled data.

PubMed

Kuncheva, Ludmila I; Faithfull, William J

2014-01-01

When classifiers are deployed in real-world applications, it is assumed that the distribution of the incoming data matches the distribution of the data used to train the classifier. This assumption is often incorrect, which necessitates some form of change detection or adaptive classification. While there has been a lot of work on change detection based on the classification error monitored over the course of the operation of the classifier, finding changes in multidimensional unlabeled data is still a challenge. Here, we propose to apply principal component analysis (PCA) for feature extraction prior to the change detection. Supported by a theoretical example, we argue that the components with the lowest variance should be retained as the extracted features because they are more likely to be affected by a change. We chose a recently proposed semiparametric log-likelihood change detection criterion that is sensitive to changes in both mean and variance of the multidimensional distribution. An experiment with 35 datasets and an illustration with a simple video segmentation demonstrate the advantage of using extracted features compared to raw data. Further analysis shows that feature extraction through PCA is beneficial, specifically for data with multiple balanced classes.

Multidimensional daily diary of fatigue-fibromyalgia-17 items (MDF-fibro-17). part 1: development and content validity.

PubMed

Morris, S; Li, Y; Smith, J A M; Dube', S; Burbridge, C; Symonds, T

2017-05-16

Fibromyalgia (FM), a disorder characterized by chronic widespread pain and tenderness, affects greater than five million individuals in the United States alone. Patients experience multiple symptoms in addition to pain, and among them, fatigue is one of the most bothersome and disabling. There is a growing body of literature suggesting that fatigue is a multidimensional concept. Currently, to our knowledge, no multidimensional Patient Reported Outcome (PRO) measure of FM-related fatigue meets Food and Drug Administration (FDA) requirements to support a product label claim. Therefore, the objective of this research was to evaluate qualitative and quantitative data previously gathered to inform the development of a comprehensive, multidimensional, PRO measure to assess FM-related fatigue in FM clinical trials. Existing qualitative and quantitative data from three previously conducted studies in patients with FM were reviewed to inform the initial development of a multidimensional PRO measure of FM-related fatigue: 1) a concept elicitation study involving in-depth, open-ended interviews with patients with FM in the United States (US) (N = 20), Germany (N = 10), and France (N = 10); 2) a cognitive debriefing and pilot study of a preliminary pool of 23 items (N = 20 US patients with FM); and 3) a methodology study that explored initial psychometrics of the item pool (N = 145 US patients with FM). Five domains were identified that intend to capture the broad experience of FM-related fatigue reported in the qualitative research: the Global Fatigue Experience, Cognitive Fatigue, Physical Fatigue, Motivation, and Impact on Function. Seventeen of the original pool of 23 items were selected to best capture these five dimensions. These 17 items formed the basis of a newly developed multidimensional PRO measure to assess FM-related fatigue in clinical trials: the Multidimensional Daily Diary of Fatigue-Fibromyalgia-17 (MDF-Fibro-17). Qualitative analysis, and preliminary quantitative item level data, confirmed that FM-related fatigue is multidimensional and provided strong support for the content validity of the MDF-Fibro-17. The next stage was to quantitatively evaluate the measure to confirm the factor structure, psychometric properties, sensitivity to change, and meaningful change. This has been conducted and is being reported separately.

Psychometric properties of the Polish version of the Multidimensional Fatigue Inventory-20 in cancer patients.

PubMed

Buss, Tomasz; Kruk, Agnieszka; Wiśniewski, Piotr; Modlinska, Aleksandra; Janiszewska, Justyna; Lichodziejewska-Niemierko, Monika

2014-10-01

Multidimensional questionnaires estimating cancer-related fatigue (CRF) as a symptom cluster or a clinical syndrome primarily have been used and validated in English-speaking populations. However, cultural issues and language peculiarities can affect CRF assessment The main aims of this study were to evaluate the psychometric properties of the Polish version of the Multidimensional Fatigue Inventory-20 (MFI-20) and to deliver to clinicians a multidimensional tool for CRF assessment in Polish-speaking patients with cancer. After forward-backward translation procedures, the Polish version of MFI-20 was administered to 340 cancer patients. The Polish MFI-20 was appraised in terms of acceptability, reliability, and validity. Internal consistency was assessed by calculating Cronbach's alpha coefficients. Structural validity was evaluated with confirmatory factor analysis. The translated MFI-20 was well accepted; 90% of subjects fully completed the questionnaire. The overall Cronbach's alpha coefficient was 0.9, ranging from 0.57 to 0.81. All correlation coefficients among Numeric Rating Scale-fatigue, fatigue-related items from the European Organization for Research and Treatment of Cancer Quality of Life Core-30 questionnaire, and the MFI--20 were statistically significant (P < 0.001). Confirmatory factor analysis demonstrated good structural validity and revealed only three dimensions in the Polish version of the MFI-20-physical and mental fatigue as well as reduced motivation. The Polish version of the MFI-20 is well accepted by patients, reliable, and a valid instrument to assess CRF in Polish cancer patients. Copyright © 2014 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

Multidimensional poverty, household environment and short-term morbidity in India.

PubMed

Dehury, Bidyadhar; Mohanty, Sanjay K

2017-01-01

Using the unit data from the second round of the Indian Human Development Survey (IHDS-II), 2011-2012, which covered 42,152 households, this paper examines the association between multidimensional poverty, household environmental deprivation and short-term morbidities (fever, cough and diarrhoea) in India. Poverty is measured in a multidimensional framework that includes the dimensions of education, health and income, while household environmental deprivation is defined as lack of access to improved sanitation, drinking water and cooking fuel. A composite index combining multidimensional poverty and household environmental deprivation has been computed, and households are classified as follows: multidimensional poor and living in a poor household environment, multidimensional non-poor and living in a poor household environment, multidimensional poor and living in a good household environment and multidimensional non-poor and living in a good household environment. Results suggest that about 23% of the population belonging to multidimensional poor households and living in a poor household environment had experienced short-term morbidities in a reference period of 30 days compared to 20% of the population belonging to multidimensional non-poor households and living in a poor household environment, 19% of the population belonging to multidimensional poor households and living in a good household environment and 15% of the population belonging to multidimensional non-poor households and living in a good household environment. Controlling for socioeconomic covariates, the odds of short-term morbidity was 1.47 [CI 1.40-1.53] among the multidimensional poor and living in a poor household environment, 1.28 [CI 1.21-1.37] among the multidimensional non-poor and living in a poor household environment and 1.21 [CI 1.64-1.28] among the multidimensional poor and living in a good household environment compared to the multidimensional non-poor and living in a good household environment. Results are robust across states and hold good for each of the three morbidities: fever, cough and diarrhoea. This establishes that along with poverty, household environmental conditions have a significant bearing on short-term morbidities in India. Public investment in sanitation, drinking water and cooking fuel can reduce the morbidity and improve the health of the population.

Mission Analysis and Design for Space Based Inter-Satellite Laser Power Beaming

DTIC Science & Technology

2010-03-01

56 4.3.1 Darwin Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 4.4 Obscuration Analysis...81 Appendix B. Additional Multi-Dimensional Darwin Plots from ModelCenter . 86 Appendix C. STK Access Report for... Darwin Data Explorer Window Showing Optimized Results in Tabular Form

Analysis of a municipal wastewater treatment plant using a neural network-based pattern analysis

USGS Publications Warehouse

Hong, Y.-S.T.; Rosen, Michael R.; Bhamidimarri, R.

2003-01-01

This paper addresses the problem of how to capture the complex relationships that exist between process variables and to diagnose the dynamic behaviour of a municipal wastewater treatment plant (WTP). Due to the complex biological reaction mechanisms, the highly time-varying, and multivariable aspects of the real WTP, the diagnosis of the WTP are still difficult in practice. The application of intelligent techniques, which can analyse the multi-dimensional process data using a sophisticated visualisation technique, can be useful for analysing and diagnosing the activated-sludge WTP. In this paper, the Kohonen Self-Organising Feature Maps (KSOFM) neural network is applied to analyse the multi-dimensional process data, and to diagnose the inter-relationship of the process variables in a real activated-sludge WTP. By using component planes, some detailed local relationships between the process variables, e.g., responses of the process variables under different operating conditions, as well as the global information is discovered. The operating condition and the inter-relationship among the process variables in the WTP have been diagnosed and extracted by the information obtained from the clustering analysis of the maps. It is concluded that the KSOFM technique provides an effective analysing and diagnosing tool to understand the system behaviour and to extract knowledge contained in multi-dimensional data of a large-scale WTP. ?? 2003 Elsevier Science Ltd. All rights reserved.

Extracting body image symptom dimensions among eating disorder patients: the Profile Analysis via Multidimensional Scaling (PAMS) approach.

PubMed

Olatunji, Bunmi O; Kim, Se-Kang; Wall, David

2015-09-01

The present study employs Profile Analysis via Multidimensional Scaling (PAMS), a procedure for extracting dimensions, in order to identify core eating disorder symptoms in a clinical sample. A large sample of patients with eating disorders (N=5193) presenting for treatment completed the Eating Disorders Inventory-2 (EDI-2; Garner, 1991), and PAMS was then employed to estimate individual profile weights that reflect the degree to which an individual's observed symptom profile approximates the pattern of the dimensions. The findings revealed three symptom dimensions: Body Thinness, Body Perfectionism, and Body Awareness. Subsequent analysis using individual level data illustrate that the PAMS profiles properly operate as prototypical profiles that encapsulate all individuals' response patterns. The implications of these dimensional findings for the assessment and diagnosis of eating disorders are discussed. Copyright © 2015 Elsevier Ltd. All rights reserved.

Schizophrenia spectrum and attention-deficit/hyperactivity disorder symptoms in autism spectrum disorder and controls.

PubMed

Gadow, Kenneth D

2012-10-01

This study compared the differential severity of specific symptoms of schizophrenia spectrum disorder (SSD) in children with autism spectrum disorder (ASD) and child psychiatry outpatient referrals (controls). Each group was further subdivided into subgroups with and without co-occurring attention-deficit/hyperactivity disorder (ADHD). Children with ASD (n = 147) and controls (n = 335) were evaluated with parent and teacher versions of a psychometrically established DSM-IV-referenced rating scale. The two ASD groups (with and without ADHD) had a larger number of more severe SSD symptoms than their respective control groups (with and without ADHD), extending the observation of an association between ASD and SSD to subgroups with and without co-occurring ADHD. The ASD groups exhibited more severe schizoid personality symptoms than controls, but findings for schizophrenia symptoms were mixed. The ASD + ADHD group generally had more severe disorganized thought, disorganized behavior, and negative schizophrenia symptoms than controls (with and without ADHD); nevertheless, findings varied according to ADHD status (present versus absent), individual symptom (symptom specificity), and informant (informant specificity). Ratings of hallucinations and delusions indicated mild severity and few group differences. Negative symptoms such as inappropriate emotional reactions evidenced considerable group divergence. Findings provide additional support for an interrelation between ASD and SSD symptoms and the differential influence of neurobehavioral syndromes on co-occurring symptom severity, underscore the multidimensionality of SSD in children with ASD, and suggest how symptom phenotypes may contribute to a better understanding of the etiology, nosology, and possibly clinical management. Copyright © 2012 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Delay differential analysis of time series.

PubMed

Lainscsek, Claudia; Sejnowski, Terrence J

2015-03-01

Nonlinear dynamical system analysis based on embedding theory has been used for modeling and prediction, but it also has applications to signal detection and classification of time series. An embedding creates a multidimensional geometrical object from a single time series. Traditionally either delay or derivative embeddings have been used. The delay embedding is composed of delayed versions of the signal, and the derivative embedding is composed of successive derivatives of the signal. The delay embedding has been extended to nonuniform embeddings to take multiple timescales into account. Both embeddings provide information on the underlying dynamical system without having direct access to all the system variables. Delay differential analysis is based on functional embeddings, a combination of the derivative embedding with nonuniform delay embeddings. Small delay differential equation (DDE) models that best represent relevant dynamic features of time series data are selected from a pool of candidate models for detection or classification. We show that the properties of DDEs support spectral analysis in the time domain where nonlinear correlation functions are used to detect frequencies, frequency and phase couplings, and bispectra. These can be efficiently computed with short time windows and are robust to noise. For frequency analysis, this framework is a multivariate extension of discrete Fourier transform (DFT), and for higher-order spectra, it is a linear and multivariate alternative to multidimensional fast Fourier transform of multidimensional correlations. This method can be applied to short or sparse time series and can be extended to cross-trial and cross-channel spectra if multiple short data segments of the same experiment are available. Together, this time-domain toolbox provides higher temporal resolution, increased frequency and phase coupling information, and it allows an easy and straightforward implementation of higher-order spectra across time compared with frequency-based methods such as the DFT and cross-spectral analysis.

Comparative exploration of multidimensional flow cytometry software: a model approach evaluating T cell polyfunctional behavior.

PubMed

Spear, Timothy T; Nishimura, Michael I; Simms, Patricia E

2017-08-01

Advancement in flow cytometry reagents and instrumentation has allowed for simultaneous analysis of large numbers of lineage/functional immune cell markers. Highly complex datasets generated by polychromatic flow cytometry require proper analytical software to answer investigators' questions. A problem among many investigators and flow cytometry Shared Resource Laboratories (SRLs), including our own, is a lack of access to a flow cytometry-knowledgeable bioinformatics team, making it difficult to learn and choose appropriate analysis tool(s). Here, we comparatively assess various multidimensional flow cytometry software packages for their ability to answer a specific biologic question and provide graphical representation output suitable for publication, as well as their ease of use and cost. We assessed polyfunctional potential of TCR-transduced T cells, serving as a model evaluation, using multidimensional flow cytometry to analyze 6 intracellular cytokines and degranulation on a per-cell basis. Analysis of 7 parameters resulted in 128 possible combinations of positivity/negativity, far too complex for basic flow cytometry software to analyze fully. Various software packages were used, analysis methods used in each described, and representative output displayed. Of the tools investigated, automated classification of cellular expression by nonlinear stochastic embedding (ACCENSE) and coupled analysis in Pestle/simplified presentation of incredibly complex evaluations (SPICE) provided the most user-friendly manipulations and readable output, evaluating effects of altered antigen-specific stimulation on T cell polyfunctionality. This detailed approach may serve as a model for other investigators/SRLs in selecting the most appropriate software to analyze complex flow cytometry datasets. Further development and awareness of available tools will help guide proper data analysis to answer difficult biologic questions arising from incredibly complex datasets. © Society for Leukocyte Biology.

Transforming community services through the use of a multidimensional model of clinical leadership.

PubMed

Leigh, Jacqueline Anne; Wild, Jill; Hynes, Celia; Wells, Stuart; Kurien, Anish; Rutherford, June; Rosen, Lyn; Ashcroft, Tim; Hartley, Victoria

2015-03-01

To evaluate the application of a Multidimensional Model of Clinical Leadership on the community healthcare leader and on transforming community services. Healthcare policy advocates clinical leadership as the vehicle to transform community and healthcare services. Few studies have identified the key components of an effective clinical leadership development model. The first two stages of Kirkpatrick's (Personnel Administrator 28, 1983, 62) Four/Five Levels of Evaluation were used to evaluate the application of the multidimensional model of clinical leadership. Eighty community healthcare leaders were exposed to this multidimensional clinical leadership development model through attendance of a community clinical leadership development programme. Twenty five leaders participated in focus group interviews. Data from the interviews were analysed utilising thematic content analysis. Three key themes emerged that influenced the development of best practice principles for clinical leadership development: 1. Personal leadership development 2. Organisational leadership 3. The importance of multiprofessional action learning/reflective groups Emergent best practice principles for clinical leadership development include adopting a multidimensional development approach. This approach encompasses: preparing the individual leader in the role and seeking organisational leadership development that promotes the vision and corporate values of the organisation and delivers on service improvement and innovation. Moreover, application of the Multidimensional Model of Clinical Leadership could offer the best platform for embedding the Six C's of Nursing (Compassion in Practice - Our Culture of Compassionate Care, Department of Health, Crown Copyright, 2012) within the culture of the healthcare organisation: care, compassion, courage, commitment, communication, and competency. This is achieved in part through the application of emotional intelligence to understand self and to develop the personal integrity of the healthcare leader and through supporting a culture of lifelong leadership learning. Embedding the best practice principles of clinical leadership development within a multidimensional model of clinical leadership provides a promising approach to: equipping the healthcare leader with those transferable leadership skills required to help them embark on a journey of lifelong leadership learning; and producing the healthcare leader who is caring, compassionate and can confidently and effectively transform community services. © 2014 John Wiley & Sons Ltd.

Laboratory tools and e-learning elements in training of acousto-optics

NASA Astrophysics Data System (ADS)

Barócsi, Attila; Lenk, Sándor; Ujhelyi, Ferenc; Majoros, Tamás.; Maák, Paál.

2015-10-01

Due to the acousto-optic (AO) effect, the refractive index of an optical interaction medium is perturbed by an acoustic wave induced in the medium that builds up a phase grating that will diffract the incident light beam if the condition of constructive interference is satisfied. All parameters, such as magnitude, period or phase of the grating can be controlled that allows the construction of useful devices (modulators, switches, one or multi-dimensional deflectors, spectrum analyzers, tunable filters, frequency shifters, etc.) The research and training of acousto-optics have a long-term tradition at our department. In this presentation, we introduce the related laboratory exercises fitted into an e-learning frame. The BSc level exercise utilizes a laser source and an AO cell to demonstrate the effect and principal AO functions explaining signal processing terms such as amplitude or frequency modulation, modulation depth and Fourier transformation ending up in building a free space sound transmitting and demodulation system. The setup for MSc level utilizes an AO filter with mono- and polychromatic light sources to learn about spectral analysis and synthesis. Smart phones can be used to generate signal inputs or outputs for both setups as well as to help students' preparation and reporting.

Preliminary investigation of human exhaled breath for tuberculosis diagnosis by multidimensional gas chromatography - Time of flight mass spectrometry and machine learning.

PubMed

Beccaria, Marco; Mellors, Theodore R; Petion, Jacky S; Rees, Christiaan A; Nasir, Mavra; Systrom, Hannah K; Sairistil, Jean W; Jean-Juste, Marc-Antoine; Rivera, Vanessa; Lavoile, Kerline; Severe, Patrice; Pape, Jean W; Wright, Peter F; Hill, Jane E

2018-02-01

Tuberculosis (TB) remains a global public health malady that claims almost 1.8 million lives annually. Diagnosis of TB represents perhaps one of the most challenging aspects of tuberculosis control. Gold standards for diagnosis of active TB (culture and nucleic acid amplification) are sputum-dependent, however, in up to a third of TB cases, an adequate biological sputum sample is not readily available. The analysis of exhaled breath, as an alternative to sputum-dependent tests, has the potential to provide a simple, fast, and non-invasive, and ready-available diagnostic service that could positively change TB detection. Human breath has been evaluated in the setting of active tuberculosis using thermal desorption-comprehensive two-dimensional gas chromatography-time of flight mass spectrometry methodology. From the entire spectrum of volatile metabolites in breath, three random forest machine learning models were applied leading to the generation of a panel of 46 breath features. The twenty-two common features within each random forest model used were selected as a set that could distinguish subjects with confirmed pulmonary M. tuberculosis infection and people with other pathologies than TB. Copyright © 2018 Elsevier B.V. All rights reserved.

Automated Tracking and Quantification of Autistic Behavioral Symptoms Using Microsoft Kinect.

PubMed

Kang, Joon Young; Kim, Ryunhyung; Kim, Hyunsun; Kang, Yeonjune; Hahn, Susan; Fu, Zhengrui; Khalid, Mamoon I; Schenck, Enja; Thesen, Thomas

2016-01-01

The prevalence of autism spectrum disorder (ASD) has risen significantly in the last ten years, and today, roughly 1 in 68 children has been diagnosed. One hallmark set of symptoms in this disorder are stereotypical motor movements. These repetitive movements may include spinning, body-rocking, or hand-flapping, amongst others. Despite the growing number of individuals affected by autism, an effective, accurate method of automatically quantifying such movements remains unavailable. This has negative implications for assessing the outcome of ASD intervention and drug studies. Here we present a novel approach to detecting autistic symptoms using the Microsoft Kinect v.2 to objectively and automatically quantify autistic body movements. The Kinect camera was used to film 12 actors performing three separate stereotypical motor movements each. Visual Gesture Builder (VGB) was implemented to analyze the skeletal structures in these recordings using a machine learning approach. In addition, movement detection was hard-coded in Matlab. Manual grading was used to confirm the validity and reliability of VGB and Matlab analysis. We found that both methods were able to detect autistic body movements with high probability. The machine learning approach yielded highest detection rates, supporting its use in automatically quantifying complex autistic behaviors with multi-dimensional input.

Monitoring dynamic reactions of red blood cells to UHF electromagnetic waves radiation using a novel micro-imaging technology.

PubMed

Ruan, Ping; Yong, Junguang; Shen, Hongtao; Zheng, Xianrong

2012-12-01

Multiple state-of-the-art techniques, such as multi-dimensional micro-imaging, fast multi-channel micro-spetrophotometry, and dynamic micro-imaging analysis, were used to dynamically investigate various effects of cell under the 900 MHz electromagnetic radiation. Cell changes in shape, size, and parameters of Hb absorption spectrum under different power density electromagnetic waves radiation were presented in this article. Experimental results indicated that the isolated human red blood cells (RBCs) do not have obviously real-time responses to the ultra-low density (15 μW/cm(2), 31 μW/cm(2)) electromagnetic wave radiation when the radiation time is not more than 30 min; however, the cells do have significant reactions in shape, size, and the like, to the electromagnetic waves radiation with power densities of 1 mW/cm(2) and 5 mW/cm(2). The data also reveal the possible influences and statistical relationships among living human cell functions, radiation amount, and exposure time with high-frequency electromagnetic waves. The results of this study may be significant on protection of human being and other living organisms against possible radiation affections of the high-frequency electromagnetic waves.

[Structural Equation Modeling of Self-Management in Patients with Hemodialysis].

PubMed

Cha, Jieun

2017-02-01

The purpose of this study was to construct and test a hypothetical model of self-management in patients with hemodialysis based on the Self-Regulation Model and resource-coping perspective. Data were collected from 215 adults receiving hemodialysis in 17 local clinics and one tertiary hospital in 2016. The Hemodialysis Self-management Instrument, the Revised Illness Perception Questionnaire, Herth Hope Index and Multidimensional Scale of Perceived Social Support were used. The exogenous variable was social context; the endogenous variables were cognitive illness representation, hope, self-management behavior, and illness outcome. For data analysis, descriptive statistics, Pearson correlation analysis, factor analysis, and structural equation modeling were performed. The hypothetical model with six paths showed a good fitness to the empirical data: GFI=.96, AGFI=.90, CFI=.95, RMSEA=.08, SRMR=.04. The factors that had an influence on self-management behavior were social context (β=.84), hope and cognitive illness representation (β=.37 and β=.27) explaining 92.4% of the variance. Self-management behavior mediated the relationship between psychosocial coping resources and illness outcome. This research specifies a more complete spectrum of the self-management process. It is important to recognize the array of clinical resources available to support patients' self-management. Healthcare providers can facilitate self-management through collaborative care and understanding the ideas and emotions that each patient has about the illness, and ultimately improve the health outcomes. This framework can be used to guide self-management intervention development and assure effective clinical assessment. © 2017 Korean Society of Nursing Science

Monitoring equity in vaccination coverage: A systematic analysis of demographic and health surveys from 45 Gavi-supported countries.

PubMed

Arsenault, Catherine; Harper, Sam; Nandi, Arijit; Mendoza Rodríguez, José M; Hansen, Peter M; Johri, Mira

2017-02-07

(1) To conduct a systematic analysis of inequalities in childhood vaccination coverage in Gavi-supported countries; (2) to comparatively assess alternative measurement approaches and how they may affect cross-country comparisons of the level of inequalities. Using the most recent Demographic and Health Surveys (2005-2014) in 45 Gavi-supported countries, we measured inequalities in vaccination coverage across seven dimensions of social stratification and of vulnerability to poor health outcomes. We quantified inequalities using pairwise comparisons (risk differences and ratios) and whole spectrum measures (slope and relative indices of inequality). To contrast measurement approaches, we pooled the estimates using random-effects meta-analyses, ranked countries by the magnitude of inequality and compared agreement in country ranks. At the aggregate level, maternal education, multidimensional poverty, and wealth index poverty were the dimensions associated with the largest inequalities. In 36 out of 45 countries, inequalities were substantial, with a difference in coverage of 10 percentage points or more between the top and bottom of at least one of these social dimensions. Important inequalities by child sex, child malnutrition and urban/rural residence were also found in a smaller set of countries. The magnitude of inequality and ranking of countries differed across dimension and depending on the measure used. Pairwise comparisons could not be estimated in certain countries. The slope and relative indices of inequality were estimated in all countries and produced more stable country rankings, and should thus facilitate more reliable international comparisons. Inequalities in vaccination coverage persist in a large majority of Gavi-supported countries. Inequalities should be monitored across multiple dimensions of vulnerability. Using whole spectrum measures to quantify inequality across multiple ordered social groups has important advantages. We illustrate these findings using an equity dashboard designed to support decision-making in the Sustainable Development Goals period. Copyright © 2017 Elsevier Ltd. All rights reserved.

Annual Review of Research Under the Joint Services Electronics Program.

DTIC Science & Technology

1978-10-01

Electronic Science at Texas Tech University. Specific topics covered include fault analysis, Stochastic control and estimation, nonlinear control, multidimensional system theory , Optical noise, and pattern recognition.

A cluster analysis of perfectionism among competitive athletes.

PubMed

Martinent, Guillaume; Ferrand, Claude

2006-12-01

In the present study, the ways in which athletes may experience perfectionism in a sport context were examined. The question of interest was whether self-confidence, intensity, and direction of cognitive and somatic precompetitive anxiety would differ across identifiable profiles of perfectionism. Competitive athletes (N= 166) completed the Sport-Multidimensional Perfectionism Scale, the French-Canadian Hewitt Multidimensional Perfectionism Scale, and the Competitive State Anxiety Inventory-2 Revised, including a Direction scale. Results of the cluster analysis indicated that athletes could be classified into three groups labelled Nonperfectionists, Adaptive perfectionists, and Maladaptive perfectionists. Perfectionism profiles differed significantly on Cognitive and Somatic Anxiety Intensity and on Cognitive Anxiety Direction. The importance of considering all dimensions of perfectionism simultaneously when examining the functional nature of this construct in sport is discussed.

Psychometric analysis of the Multidimensional Fatigue Inventory in a sample of persons treated for myocardial infarction.

PubMed

Fredriksson-Larsson, Ulla; Brink, Eva; Alsén, Pia; Falk, Kristin; Lundgren-Nilsson, Åsa

2015-01-01

Fatigue after myocardial infarction is a frequent and distressing symptom in the early recovery phase. The purpose of this study is to psychometrically evaluate the Multidimensional Fatigue Inventory (MFI-20). The MFI-20 was evaluated using Rasch analysis. The result showed that the MFI-20 can be used to obtain a global score reflecting an underlying unidimensional trait of fatigue; a transformation of the summarized raw scale scores into interval scale scores could be made. Also, 4 of the 5 original dimensions separately fitted the Rasch model. Calculation of a global score increases the possibility of identifying persons experiencing fatigue after myocardial infarction, and using the MFI-20 dimension scores increases the possibility of determining each person's specific fatigue profile.

Xarray: multi-dimensional data analysis in Python

NASA Astrophysics Data System (ADS)

Hoyer, Stephan; Hamman, Joe; Maussion, Fabien

2017-04-01

xarray (http://xarray.pydata.org) is an open source project and Python package that provides a toolkit and data structures for N-dimensional labeled arrays, which are the bread and butter of modern geoscientific data analysis. Key features of the package include label-based indexing and arithmetic, interoperability with the core scientific Python packages (e.g., pandas, NumPy, Matplotlib, Cartopy), out-of-core computation on datasets that don't fit into memory, a wide range of input/output options, and advanced multi-dimensional data manipulation tools such as group-by and resampling. In this contribution we will present the key features of the library and demonstrate its great potential for a wide range of applications, from (big-)data processing on super computers to data exploration in front of a classroom.

Between pink and blue: a multi-dimensional family approach to gender nonconforming children and their families.

PubMed

Malpas, Jean

2011-12-01

Families of gender nonconforming children need to negotiate the interactions between two gender systems: a rigid gender binary imported from familial, social, and cultural experiences and a fluid gender spectrum articulated by their child. This article reviews parental reactions to nonconforming gender developments and poses that the parental mandates of protection and acceptance are problematized by the difference of gender norms between the child and the family, as well as the child and the environment. Through multiple therapeutic modalities-parental coaching and education, parent support group, and child and family therapy-the author illustrates interventions supporting both parents and prepubescent children in their negotiation of safety, connection, and fluidity. Case vignettes illustrate the method in action.

Multidimensional phase space methods for mass measurements and decay topology determination

NASA Astrophysics Data System (ADS)

Altunkaynak, Baris; Kilic, Can; Klimek, Matthew D.

2017-02-01

Collider events with multi-stage cascade decays fill out the kinematically allowed region in phase space with a density that is enhanced at the boundary. The boundary encodes all available information as regards the spectrum and is well populated even with moderate signal statistics due to this enhancement. In previous work, the improvement in the precision of mass measurements for cascade decays with three visible and one invisible particles was demonstrated when the full boundary information is used instead of endpoints of one-dimensional projections. We extend these results to cascade decays with four visible and one invisible particles. We also comment on how the topology of the cascade decay can be determined from the differential distribution of events in these scenarios.

Brief report: The level and nature of autistic intelligence revisited.

PubMed

Bölte, Sven; Dziobek, Isabel; Poustka, Fritz

2009-04-01

Owing to higher performance on the Raven's Progressive Matrices (RPM) than on the Wechsler Intelligence Scales (WIS), it has recently been argued that intelligence is underestimated in autism. This study examined RPM and WIS IQs in 48 individuals with autism, a mixed clinical (n = 28) and a neurotypical (n = 25) control group. Average RPM IQ was higher than WIS IQ only in the autism group, albeit to a much lesser degree than previously reported and only for individuals with WIS IQs <85. Consequently, and given the importance of reliable multidimensional IQ estimates in autism, the WIS are recommended as first choice IQ measure in high functioning individuals. Additional testing with the RPM might be required in the lower end of the spectrum.

Affective Outcomes of Schooling: Full-Information Item Factor Analysis of a Student Questionnaire.

ERIC Educational Resources Information Center

Muraki, Eiji; Engelhard, George, Jr.

Recent developments in dichotomous factor analysis based on multidimensional item response models (Bock and Aitkin, 1981; Muthen, 1978) provide an effective method for exploring the dimensionality of questionnaire items. Implemented in the TESTFACT program, this "full information" item factor analysis accounts not only for the pairwise joint…

Multidimensional Functional Behaviour Assessment within a Problem Analysis Framework.

ERIC Educational Resources Information Center

Ryba, Ken; Annan, Jean

This paper presents a new approach to contextualized problem analysis developed for use with multimodal Functional Behaviour Assessment (FBA) at Massey University in Auckland, New Zealand. The aim of problem analysis is to simplify complex problems that are difficult to understand. It accomplishes this by providing a high order framework that can…

An Economic Wellbeing Index for the Spanish Provinces: A Data Envelopment Analysis Approach

ERIC Educational Resources Information Center

Murias, Pilar; Martinez, Fidel; De Miguel, Carlos

2006-01-01

This article presents the estimation of a synthetic economic wellbeing index using Data Envelopment Analysis (DEA). The DEA is a multidimensional technique that has its origins in efficiency analysis, but its usage within the social indicators context is particularly appropriate. It allows the researcher to take advantage of the inherent…

Changes to the Student Loan Experience: Psychological Predictors and Outcomes

ERIC Educational Resources Information Center

Mueller, Thomas

2014-01-01

This study builds on the work of scholars who have explored psychological perceptions of the student loan experience. Survey analysis ("N" = 175) revealed a multidimensional model was developed through factor analysis and testing, which revealed four latent variables: "Duress," "Mandatory," "Financial," and…

Towards Careful Practices for Automated Linguistic Analysis of Group Learning

ERIC Educational Resources Information Center

Howley, Iris; Rosé, Carolyn Penstein

2016-01-01

The multifaceted nature of collaborative learning environments necessitates theory to investigate the cognitive, motivational, and relational dimensions of collaboration. Several existing frameworks include aspects related to each of these three. This article explores the capability of multi-dimensional frameworks for analysis of collaborative…

A Visual Analytics Approach for Station-Based Air Quality Data

PubMed Central

Du, Yi; Ma, Cuixia; Wu, Chao; Xu, Xiaowei; Guo, Yike; Zhou, Yuanchun; Li, Jianhui

2016-01-01

With the deployment of multi-modality and large-scale sensor networks for monitoring air quality, we are now able to collect large and multi-dimensional spatio-temporal datasets. For these sensed data, we present a comprehensive visual analysis approach for air quality analysis. This approach integrates several visual methods, such as map-based views, calendar views, and trends views, to assist the analysis. Among those visual methods, map-based visual methods are used to display the locations of interest, and the calendar and the trends views are used to discover the linear and periodical patterns. The system also provides various interaction tools to combine the map-based visualization, trends view, calendar view and multi-dimensional view. In addition, we propose a self-adaptive calendar-based controller that can flexibly adapt the changes of data size and granularity in trends view. Such a visual analytics system would facilitate big-data analysis in real applications, especially for decision making support. PMID:28029117

A Visual Analytics Approach for Station-Based Air Quality Data.

PubMed

Du, Yi; Ma, Cuixia; Wu, Chao; Xu, Xiaowei; Guo, Yike; Zhou, Yuanchun; Li, Jianhui

2016-12-24

With the deployment of multi-modality and large-scale sensor networks for monitoring air quality, we are now able to collect large and multi-dimensional spatio-temporal datasets. For these sensed data, we present a comprehensive visual analysis approach for air quality analysis. This approach integrates several visual methods, such as map-based views, calendar views, and trends views, to assist the analysis. Among those visual methods, map-based visual methods are used to display the locations of interest, and the calendar and the trends views are used to discover the linear and periodical patterns. The system also provides various interaction tools to combine the map-based visualization, trends view, calendar view and multi-dimensional view. In addition, we propose a self-adaptive calendar-based controller that can flexibly adapt the changes of data size and granularity in trends view. Such a visual analytics system would facilitate big-data analysis in real applications, especially for decision making support.

Targeted quantitative analysis of Streptococcus pyogenes virulence factors by multiple reaction monitoring.

PubMed

Lange, Vinzenz; Malmström, Johan A; Didion, John; King, Nichole L; Johansson, Björn P; Schäfer, Juliane; Rameseder, Jonathan; Wong, Chee-Hong; Deutsch, Eric W; Brusniak, Mi-Youn; Bühlmann, Peter; Björck, Lars; Domon, Bruno; Aebersold, Ruedi

2008-08-01

In many studies, particularly in the field of systems biology, it is essential that identical protein sets are precisely quantified in multiple samples such as those representing differentially perturbed cell states. The high degree of reproducibility required for such experiments has not been achieved by classical mass spectrometry-based proteomics methods. In this study we describe the implementation of a targeted quantitative approach by which predetermined protein sets are first identified and subsequently quantified at high sensitivity reliably in multiple samples. This approach consists of three steps. First, the proteome is extensively mapped out by multidimensional fractionation and tandem mass spectrometry, and the data generated are assembled in the PeptideAtlas database. Second, based on this proteome map, peptides uniquely identifying the proteins of interest, proteotypic peptides, are selected, and multiple reaction monitoring (MRM) transitions are established and validated by MS2 spectrum acquisition. This process of peptide selection, transition selection, and validation is supported by a suite of software tools, TIQAM (Targeted Identification for Quantitative Analysis by MRM), described in this study. Third, the selected target protein set is quantified in multiple samples by MRM. Applying this approach we were able to reliably quantify low abundance virulence factors from cultures of the human pathogen Streptococcus pyogenes exposed to increasing amounts of plasma. The resulting quantitative protein patterns enabled us to clearly define the subset of virulence proteins that is regulated upon plasma exposure.

Nuclear Forensic Inferences Using Iterative Multidimensional Statistics

DOE Office of Scientific and Technical Information (OSTI.GOV)

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. Inmore » 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 compared favorably to that of classification and regression tree (CART) and k nearest neighbor (KNN) algorithms, with the best combination of accuracy and robustness, as tested by classifying samples measured independently in our laboratories against the vendor QC based reference set.« less

Reliability and validity of the PedsQL™ Multidimensional Fatigue Scale in Japan.

PubMed

Kobayashi, Kyoko; Okano, Yoshiyuki; Hohashi, Naohiro

2011-09-01

To examine the reliability and validity of the Japanese-language version of the PedsQL™ Multidimensional Fatigue Scale and to investigate the agreement between child self-reported fatigue and parent proxy-reported fatigue. The Japanese-language version of the PedsQL™ Multidimensional Fatigue Scale was administered to 652 preschoolers and schoolchildren aged 5-12 and their parents, and to 91 parents of preschool children aged 1-4. Internal consistency reliability was 0.62-0.87 for children and 0.81-0.93 for parents. Known-group validity was examined between a group of healthy samples (n = 530) and chronic condition sample (n = 102); the chronically ill group reported a significantly higher perceived fatigue problem. Correlations between child self- and parent proxy reports ranged from poor to fair. In subgroups identified by cluster analysis based on child self-reported scores, the greatest agreement between child and parent reports was seen in the good HRQOL group, while the least occurred in the poor HRQOL group. The parents overestimated their child's fatigue more when the child's HRQOL was low. The Japanese-language version of the PedsQL™ Multidimensional Fatigue Scale demonstrated good reliability and validity and could be useful in evaluating Japanese children in school and health care settings.

Reliability and Validity of the Korean Version of the Multidimensional Fatigue Inventory (MFI-20): A Multicenter, Cross-Sectional Study.

PubMed

Song, Sang-Wook; Kang, Sung-Goo; Kim, Kyung-Soo; Kim, Moon-Jong; Kim, Kwang-Min; Cho, Doo-Yeoun; Kim, Young-Sang; Joo, Nam-Seok; Kim, Kyu-Nam

2018-01-01

A nonspecific symptom, fatigue accompanies a variety of diseases, including cancer, and can have a grave impact on patients' quality of life. As for multidimensional instruments, one of the most widely used is the Multidimensional Fatigue Inventory (MFI). This study aims to verify the reliability and validity of the MFI Korean (MFI-K) version. This study was performed at four university hospitals in the Republic of Korea. Among outpatients visiting the Department of Family Medicine, those complaining of fatigue or visiting a chronic care clinic were enrolled in this study. A total of 595 participants were included, and the mean age was 42.2 years. The Cronbach's alpha coefficient of the MFI-K was 0.88. The MFI-K had good convergent validity. Most subscales of the MFI-K were significantly correlated with the Visual Analogue Scale (VAS) and Fatigue Severity Scale (FSS). In particular, general and physical fatigue had the greatest correlation with the VAS and FSS. Although the English version of MFI had five subscales, the factor analysis led to four subscales in the Korean version. This study demonstrated the clinical usefulness of MFI-K instrument, particularly in assessing the degree of fatigue and performing a multidimensional assessment of fatigue.

Does ℏ play a role in multidimensional spectroscopy? Reduced hierarchy equations of motion approach to molecular vibrations.

PubMed

Sakurai, Atsunori; Tanimura, Yoshitaka

2011-04-28

To investigate the role of quantum effects in vibrational spectroscopies, we have carried out numerically exact calculations of linear and nonlinear response functions for an anharmonic potential system nonlinearly coupled to a harmonic oscillator bath. Although one cannot carry out the quantum calculations of the response functions with full molecular dynamics (MD) simulations for a realistic system which consists of many molecules, it is possible to grasp the essence of the quantum effects on the vibrational spectra by employing a model Hamiltonian that describes an intra- or intermolecular vibrational motion in a condensed phase. The present model fully includes vibrational relaxation, while the stochastic model often used to simulate infrared spectra does not. We have employed the reduced quantum hierarchy equations of motion approach in the Wigner space representation to deal with nonperturbative, non-Markovian, and nonsecular system-bath interactions. Taking the classical limit of the hierarchy equations of motion, we have obtained the classical equations of motion that describe the classical dynamics under the same physical conditions as in the quantum case. By comparing the classical and quantum mechanically calculated linear and multidimensional spectra, we found that the profiles of spectra for a fast modulation case were similar, but different for a slow modulation case. In both the classical and quantum cases, we identified the resonant oscillation peak in the spectra, but the quantum peak shifted to the red compared with the classical one if the potential is anharmonic. The prominent quantum effect is the 1-2 transition peak, which appears only in the quantum mechanically calculated spectra as a result of anharmonicity in the potential or nonlinearity of the system-bath coupling. While the contribution of the 1-2 transition is negligible in the fast modulation case, it becomes important in the slow modulation case as long as the amplitude of the frequency fluctuation is small. Thus, we observed a distinct difference between the classical and quantum mechanically calculated multidimensional spectra in the slow modulation case where spectral diffusion plays a role. This fact indicates that one may not reproduce the experimentally obtained multidimensional spectrum for high-frequency vibrational modes based on classical molecular dynamics simulations if the modulation that arises from surrounding molecules is weak and slow. A practical way to overcome the difference between the classical and quantum simulations was discussed.

Scientific Visualization Tools for Enhancement of Undergraduate Research

NASA Astrophysics Data System (ADS)

Rodriguez, W. J.; Chaudhury, S. R.

2001-05-01

Undergraduate research projects that utilize remote sensing satellite instrument data to investigate atmospheric phenomena pose many challenges. A significant challenge is processing large amounts of multi-dimensional data. Remote sensing data initially requires mining; filtering of undesirable spectral, instrumental, or environmental features; and subsequently sorting and reformatting to files for easy and quick access. The data must then be transformed according to the needs of the investigation(s) and displayed for interpretation. These multidimensional datasets require views that can range from two-dimensional plots to multivariable-multidimensional scientific visualizations with animations. Science undergraduate students generally find these data processing tasks daunting. Generally, researchers are required to fully understand the intricacies of the dataset and write computer programs or rely on commercially available software, which may not be trivial to use. In the time that undergraduate researchers have available for their research projects, learning the data formats, programming languages, and/or visualization packages is impractical. When dealing with large multi-dimensional data sets appropriate Scientific Visualization tools are imperative in allowing students to have a meaningful and pleasant research experience, while producing valuable scientific research results. The BEST Lab at Norfolk State University has been creating tools for multivariable-multidimensional analysis of Earth Science data. EzSAGE and SAGE4D have been developed to sort, analyze and visualize SAGE II (Stratospheric Aerosol and Gas Experiment) data with ease. Three- and four-dimensional visualizations in interactive environments can be produced. EzSAGE provides atmospheric slices in three-dimensions where the researcher can change the scales in the three-dimensions, color tables and degree of smoothing interactively to focus on particular phenomena. SAGE4D provides a navigable four-dimensional interactive environment. These tools allow students to make higher order decisions based on large multidimensional sets of data while diminishing the level of frustration that results from dealing with the details of processing large data sets.

A Quantitative Analysis of Countries' Research Strengths

ERIC Educational Resources Information Center

Saxena, Anurag; Brazer, S. David; Gupta, B. M.

2009-01-01

This study employed a multidimensional analysis to evaluate transnational patterns of scientific research to determine relative research strengths among widely varying nations. Findings from this study may inform national policy with regard to the most efficient use of scarce national research resources, including government and private funding.…

Proceedings of the Third Annual Symposium on Mathematical Pattern Recognition and Image Analysis

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr.

1985-01-01

Topics addressed include: multivariate spline method; normal mixture analysis applied to remote sensing; image data analysis; classifications in spatially correlated environments; probability density functions; graphical nonparametric methods; subpixel registration analysis; hypothesis integration in image understanding systems; rectification of satellite scanner imagery; spatial variation in remotely sensed images; smooth multidimensional interpolation; and optimal frequency domain textural edge detection filters.

Mergeomics: a web server for identifying pathological pathways, networks, and key regulators via multidimensional data integration.

PubMed

Arneson, Douglas; Bhattacharya, Anindya; Shu, Le; Mäkinen, Ville-Petteri; Yang, Xia

2016-09-09

Human diseases are commonly the result of multidimensional changes at molecular, cellular, and systemic levels. Recent advances in genomic technologies have enabled an outpour of omics datasets that capture these changes. However, separate analyses of these various data only provide fragmented understanding and do not capture the holistic view of disease mechanisms. To meet the urgent needs for tools that effectively integrate multiple types of omics data to derive biological insights, we have developed Mergeomics, a computational pipeline that integrates multidimensional disease association data with functional genomics and molecular networks to retrieve biological pathways, gene networks, and central regulators critical for disease development. To make the Mergeomics pipeline available to a wider research community, we have implemented an online, user-friendly web server ( http://mergeomics. idre.ucla.edu/ ). The web server features a modular implementation of the Mergeomics pipeline with detailed tutorials. Additionally, it provides curated genomic resources including tissue-specific expression quantitative trait loci, ENCODE functional annotations, biological pathways, and molecular networks, and offers interactive visualization of analytical results. Multiple computational tools including Marker Dependency Filtering (MDF), Marker Set Enrichment Analysis (MSEA), Meta-MSEA, and Weighted Key Driver Analysis (wKDA) can be used separately or in flexible combinations. User-defined summary-level genomic association datasets (e.g., genetic, transcriptomic, epigenomic) related to a particular disease or phenotype can be uploaded and computed real-time to yield biologically interpretable results, which can be viewed online and downloaded for later use. Our Mergeomics web server offers researchers flexible and user-friendly tools to facilitate integration of multidimensional data into holistic views of disease mechanisms in the form of tissue-specific key regulators, biological pathways, and gene networks.

Mega-analysis of Odds Ratio: A Convergent Method for a Deep Understanding of the Genetic Evidence in Schizophrenia.

PubMed

Jia, Peilin; Chen, Xiangning; Xie, Wei; Kendler, Kenneth S; Zhao, Zhongming

2018-06-20

Numerous high-throughput omics studies have been conducted in schizophrenia, providing an accumulated catalog of susceptible variants and genes. The results from these studies, however, are highly heterogeneous. The variants and genes nominated by different omics studies often have limited overlap with each other. There is thus a pressing need for integrative analysis to unify the different types of data and provide a convergent view of schizophrenia candidate genes (SZgenes). In this study, we collected a comprehensive, multidimensional dataset, including 7819 brain-expressed genes. The data hosted genome-wide association evidence in genetics (eg, genotyping data, copy number variations, de novo mutations), epigenetics, transcriptomics, and literature mining. We developed a method named mega-analysis of odds ratio (MegaOR) to prioritize SZgenes. Application of MegaOR in the multidimensional data resulted in consensus sets of SZgenes (up to 530), each enriched with dense, multidimensional evidence. We proved that these SZgenes had highly tissue-specific expression in brain and nerve and had intensive interactions that were significantly stronger than chance expectation. Furthermore, we found these SZgenes were involved in human brain development by showing strong spatiotemporal expression patterns; these characteristics were replicated in independent brain expression datasets. Finally, we found the SZgenes were enriched in critical functional gene sets involved in neuronal activities, ligand gated ion signaling, and fragile X mental retardation protein targets. In summary, MegaOR analysis reported consensus sets of SZgenes with enriched association evidence to schizophrenia, providing insights into the pathophysiology underlying schizophrenia.

Implementation and evaluation of a hypercube-based method for spatiotemporal exploration and analysis

NASA Astrophysics Data System (ADS)

Marchand, Pierre; Brisebois, Alexandre; Bédard, Yvan; Edwards, Geoffrey

This paper presents the results obtained with a new type of spatiotemporal topological dimension implemented within a hypercube, i.e., within a multidimensional database (MDDB) structure formed by the conjunction of several thematic, spatial and temporal dimensions. Our goal is to support efficient SpatioTemporal Exploration and Analysis (STEA) in the context of Automatic Position Reporting System (APRS), the worldwide amateur radio system for position report transmission. Mobile APRS stations are equipped with GPS navigation systems to provide real-time positioning reports. Previous research about the multidimensional approach has proved good potential for spatiotemporal exploration and analysis despite a lack of explicit topological operators (spatial, temporal and spatiotemporal). Our project implemented such operators through a hierarchy of operators that are applied to pairs of instances of objects. At the top of the hierarchy, users can use simple operators such as "same place", "same time" or "same time, same place". As they drill down into the hierarchy, more detailed topological operators are made available such as "adjacent immediately after", "touch during" or more detailed operators. This hierarchy is structured according to four levels of granularity based on cognitive models, generalized relationships and formal models of topological relationships. In this paper, we also describe the generic approach which allows efficient STEA within the multidimensional approach. Finally, we demonstrate that such an implementation offers query run times which permit to maintain a "train-of-thought" during exploration and analysis operations as they are compatible with Newell's cognitive band (query runtime<10 s) (Newell, A., 1990. Unified theories of cognition. Harvard University Press, Cambridge MA, 549 p.).

Highly Reproducible Label Free Quantitative Proteomic Analysis of RNA Polymerase Complexes*

PubMed Central

Mosley, Amber L.; Sardiu, Mihaela E.; Pattenden, Samantha G.; Workman, Jerry L.; Florens, Laurence; Washburn, Michael P.

2011-01-01

The use of quantitative proteomics methods to study protein complexes has the potential to provide in-depth information on the abundance of different protein components as well as their modification state in various cellular conditions. To interrogate protein complex quantitation using shotgun proteomic methods, we have focused on the analysis of protein complexes using label-free multidimensional protein identification technology and studied the reproducibility of biological replicates. For these studies, we focused on three highly related and essential multi-protein enzymes, RNA polymerase I, II, and III from Saccharomyces cerevisiae. We found that label-free quantitation using spectral counting is highly reproducible at the protein and peptide level when analyzing RNA polymerase I, II, and III. In addition, we show that peptide sampling does not follow a random sampling model, and we show the need for advanced computational models to predict peptide detection probabilities. In order to address these issues, we used the APEX protocol to model the expected peptide detectability based on whole cell lysate acquired using the same multidimensional protein identification technology analysis used for the protein complexes. Neither method was able to predict the peptide sampling levels that we observed using replicate multidimensional protein identification technology analyses. In addition to the analysis of the RNA polymerase complexes, our analysis provides quantitative information about several RNAP associated proteins including the RNAPII elongation factor complexes DSIF and TFIIF. Our data shows that DSIF and TFIIF are the most highly enriched RNAP accessory factors in Rpb3-TAP purifications and demonstrate our ability to measure low level associated protein abundance across biological replicates. In addition, our quantitative data supports a model in which DSIF and TFIIF interact with RNAPII in a dynamic fashion in agreement with previously published reports. PMID:21048197

GLO-Roots: an imaging platform enabling multidimensional characterization of soil-grown root systems

PubMed Central

Rellán-Álvarez, Rubén; Lobet, Guillaume; Lindner, Heike; Pradier, Pierre-Luc; Sebastian, Jose; Yee, Muh-Ching; Geng, Yu; Trontin, Charlotte; LaRue, Therese; Schrager-Lavelle, Amanda; Haney, Cara H; Nieu, Rita; Maloof, Julin; Vogel, John P; Dinneny, José R

2015-01-01

Root systems develop different root types that individually sense cues from their local environment and integrate this information with systemic signals. This complex multi-dimensional amalgam of inputs enables continuous adjustment of root growth rates, direction, and metabolic activity that define a dynamic physical network. Current methods for analyzing root biology balance physiological relevance with imaging capability. To bridge this divide, we developed an integrated-imaging system called Growth and Luminescence Observatory for Roots (GLO-Roots) that uses luminescence-based reporters to enable studies of root architecture and gene expression patterns in soil-grown, light-shielded roots. We have developed image analysis algorithms that allow the spatial integration of soil properties, gene expression, and root system architecture traits. We propose GLO-Roots as a system that has great utility in presenting environmental stimuli to roots in ways that evoke natural adaptive responses and in providing tools for studying the multi-dimensional nature of such processes. DOI: http://dx.doi.org/10.7554/eLife.07597.001 PMID:26287479

Towards a European Framework to Monitor Infectious Diseases among Migrant Populations: Design and Applicability

PubMed Central

Riccardo, Flavia; Dente, Maria Grazia; Kärki, Tommi; Fabiani, Massimo; Napoli, Christian; Chiarenza, Antonio; Giorgi Rossi, Paolo; Velasco Munoz, Cesar; Noori, Teymur; Declich, Silvia

2015-01-01

There are limitations in our capacity to interpret point estimates and trends of infectious diseases occurring among diverse migrant populations living in the European Union/European Economic Area (EU/EEA). The aim of this study was to design a data collection framework that could capture information on factors associated with increased risk to infectious diseases in migrant populations in the EU/EEA. The authors defined factors associated with increased risk according to a multi-dimensional framework and performed a systematic literature review in order to identify whether those factors well reflected the reported risk factors for infectious disease in these populations. Following this, the feasibility of applying this framework to relevant available EU/EEA data sources was assessed. The proposed multidimensional framework is well suited to capture the complexity and concurrence of these risk factors and in principle applicable in the EU/EEA. The authors conclude that adopting a multi-dimensional framework to monitor infectious diseases could favor the disaggregated collection and analysis of migrant health data. PMID:26393623

A Multidimensional Theory of Suicide.

PubMed

Leenaars, Antoon A; Dieserud, Gudrun; Wenckstern, Susanne; Dyregrov, Kari; Lester, David; Lyke, Jennifer

2018-04-05

Theory is the foundation of science; this is true in suicidology. Over decades of studies of suicide notes, Leenaars developed a multidimensional model of suicide, with international (crosscultural) studies and independent verification. To corroborate Leenaars's theory with a psychological autopsy (PA) study, examining age and sex of the decedent, and survivor's relationship to deceased. A PA study in Norway, with 120 survivors/informants was undertaken. Leenaars' theoretical-conceptual (protocol) analysis was undertaken of the survivors' narratives and in-depth interviews combined. Substantial interjudge reliability was noted (κ = .632). Overall, there was considerable confirmatory evidence of Leenaars's intrapsychic and interpersonal factors in suicide survivors' narratives. Differences were found in the age of the decedent, but not in sex, nor in the survivor's closeness of the relationship. Older deceased people were perceived to exhibit more heightened unbearable intrapsychic pain, associated with the suicide. Leenaars's theory has corroborative verification, through the decedents' suicide notes and the survivors' narratives. However, the multidimensional model needs further testing to develop a better evidence-based way of understanding suicide.

Hierarchical and Multidimensional Academic Self-Concept of Commercial Students.

PubMed

Yeung; Chui; Lau

1999-10-01

Adapting the Marsh (1990) Academic Self-Description Questionnaire (ASDQ), this study examined the academic self-concept of students in a school of commerce in Hong Kong (N = 212). Confirmatory factor analysis found that students clearly distinguished among self-concept constructs in English, Chinese, Math and Statistics, Economics, and Principles of Accounting, and each of these constructs was highly associated with a global Academic self-concept construct, reflecting the validity of each construct in measuring an academic component of self-concept. Domain-specific self-concepts were more highly related with students' intention of course selection in corresponding areas than in nonmatching areas, further supporting the multidimensionality of the students' academic self-concept. Students' self-concepts in the five curriculum domains can be represented by the global Academic self-concept, supporting the hierarchical structure of students' academic self-concept in an educational institution with a specific focus, such as commercial studies. The academic self-concepts of the commercial students are both multidimensional and hierarchical. Copyright 1999 Academic Press.

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.

GLO-Roots: An imaging platform enabling multidimensional characterization of soil-grown root systems

DOE PAGES

Rellan-Alvarez, Ruben; Lobet, Guillaume; Lindner, Heike; ...

2015-08-19

Root systems develop different root types that individually sense cues from their local environment and integrate this information with systemic signals. This complex multi-dimensional amalgam of inputs enables continuous adjustment of root growth rates, direction, and metabolic activity that define a dynamic physical network. Current methods for analyzing root biology balance physiological relevance with imaging capability. To bridge this divide, we developed an integrated-imaging system called Growth and Luminescence Observatory for Roots (GLO-Roots) that uses luminescence-based reporters to enable studies of root architecture and gene expression patterns in soil-grown, light-shielded roots. We have developed image analysis algorithms that allow themore » spatial integration of soil properties, gene expression, and root system architecture traits. We propose GLO-Roots as a system that has great utility in presenting environmental stimuli to roots in ways that evoke natural adaptive responses and in providing tools for studying the multi-dimensional nature of such processes.« less

Towards a European Framework to Monitor Infectious Diseases among Migrant Populations: Design and Applicability.

PubMed

Riccardo, Flavia; Dente, Maria Grazia; Kärki, Tommi; Fabiani, Massimo; Napoli, Christian; Chiarenza, Antonio; Giorgi Rossi, Paolo; Munoz, Cesar Velasco; Noori, Teymur; Declich, Silvia

2015-09-17

There are limitations in our capacity to interpret point estimates and trends of infectious diseases occurring among diverse migrant populations living in the European Union/European Economic Area (EU/EEA). The aim of this study was to design a data collection framework that could capture information on factors associated with increased risk to infectious diseases in migrant populations in the EU/EEA. The authors defined factors associated with increased risk according to a multi-dimensional framework and performed a systematic literature review in order to identify whether those factors well reflected the reported risk factors for infectious disease in these populations. Following this, the feasibility of applying this framework to relevant available EU/EEA data sources was assessed. The proposed multidimensional framework is well suited to capture the complexity and concurrence of these risk factors and in principle applicable in the EU/EEA. The authors conclude that adopting a multi-dimensional framework to monitor infectious diseases could favor the disaggregated collection and analysis of migrant health data.

Conceptualizing the multidimensional nature of self-efficacy: assessment of situational context and level of behavioral challenge to maintain safer sex. National Institute of Mental Health Multisite HIV Prevention Trial Group.

PubMed

Murphy, D A; Stein, J A; Schlenger, W; Maibach, E

2001-07-01

A. Bandura (1991) argued that self-efficacy measurement should be specific both to the situation in which the behavior occurs and level of challenge in that situation. Measures consistent with the 2 dimensions were developed with graded challenge levels and differing gender-appropriate situations. Participants were 1,496 controls in the National Institute of Mental Health Multisite HIV Prevention Trial recruited from STD clinics and health service centers (925 women and 571 men). The authors tested 4 separate-sex confirmatory factor analysis models as follows: (a) Condom negotiation efficacy as a unitary construct across situations and gradation of difficulty; (b) situation as preeminent, which transfers across skills whatever the gradation of difficulty; (c) skill as predominant, irrespective of situation; and (d) a multidimensional design that simultaneously accounts for both situation and graded difficulty. Consistent with Bandura's theory, the multidimensional model provided the best fit for both samples.

Application of Multi-Parameter Data Visualization by Means of Multidimensional Scaling to Evaluate Possibility of Coal Gasification

NASA Astrophysics Data System (ADS)

Jamróz, Dariusz; Niedoba, Tomasz; Surowiak, Agnieszka; Tumidajski, Tadeusz; Szostek, Roman; Gajer, Mirosław

2017-09-01

The application of methods drawing upon multi-parameter visualization of data by transformation of multidimensional space into two-dimensional one allow to show multi-parameter data on computer screen. Thanks to that, it is possible to conduct a qualitative analysis of this data in the most natural way for human being, i.e. by the sense of sight. An example of such method of multi-parameter visualization is multidimensional scaling. This method was used in this paper to present and analyze a set of seven-dimensional data obtained from Janina Mining Plant and Wieczorek Coal Mine. It was decided to examine whether the method of multi-parameter data visualization allows to divide the samples space into areas of various applicability to fluidal gasification process. The "Technological applicability card for coals" was used for this purpose [Sobolewski et al., 2012; 2017], in which the key parameters, important and additional ones affecting the gasification process were described.

Numeric invariants from multidimensional persistence

DOE Office of Scientific and Technical Information (OSTI.GOV)

Skryzalin, Jacek; Carlsson, Gunnar

2017-05-19

In this paper, we analyze the space of multidimensional persistence modules from the perspectives of algebraic geometry. We first build a moduli space of a certain subclass of easily analyzed multidimensional persistence modules, which we construct specifically to capture much of the information which can be gained by using multidimensional persistence over one-dimensional persistence. We argue that the global sections of this space provide interesting numeric invariants when evaluated against our subclass of multidimensional persistence modules. Lastly, we extend these global sections to the space of all multidimensional persistence modules and discuss how the resulting numeric invariants might be usedmore » to study data.« less

A meta-analysis of prosocial media on prosocial behavior, aggression, and empathic concern: A multidimensional approach.

PubMed

Coyne, Sarah M; Padilla-Walker, Laura M; Holmgren, Hailey G; Davis, Emilie J; Collier, Kevin M; Memmott-Elison, Madison K; Hawkins, Alan J

2018-02-01

Studies examining the effects of exposure to prosocial media on positive outcomes are increasing in number and strength. However, existing meta-analyses use a broad definition of prosocial media that does not recognize the multidimensionality of prosocial behavior. The aim of the current study is to conduct a meta-analysis on the effects of exposure to prosocial media on prosocial behavior, aggression, and empathic concern while examining multiple moderators that the prosocial behavior literature suggests are important to our understanding of why individuals voluntarily help others (e.g., target, type, cost). Results from 72 studies involving 243 effect sizes revealed that exposure to prosocial media was related to higher levels of prosocial behavior and empathic concern and lower levels of aggressive behavior. Moderation analyses suggest that several moderators accounted for heterogeneity in the model, including age of participant, region, media type (active vs. passive), and study design. In terms of multidimensional moderators, prosocial media had stronger effects on prosocial behavior toward strangers than did any other target and on helping and prosocial thinking but not donating or volunteering. Comparisons with other meta-analyses on media effects are made and implications for parents, media producers, and researchers are discussed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

An integrated approach for the knowledge discovery in computer simulation models with a multi-dimensional parameter space

DOE Office of Scientific and Technical Information (OSTI.GOV)

Khawli, Toufik Al; Eppelt, Urs; Hermanns, Torsten

2016-06-08

In production industries, parameter identification, sensitivity analysis and multi-dimensional visualization are vital steps in the planning process for achieving optimal designs and gaining valuable information. Sensitivity analysis and visualization can help in identifying the most-influential parameters and quantify their contribution to the model output, reduce the model complexity, and enhance the understanding of the model behavior. Typically, this requires a large number of simulations, which can be both very expensive and time consuming when the simulation models are numerically complex and the number of parameter inputs increases. There are three main constituent parts in this work. The first part ismore » to substitute the numerical, physical model by an accurate surrogate model, the so-called metamodel. The second part includes a multi-dimensional visualization approach for the visual exploration of metamodels. In the third part, the metamodel is used to provide the two global sensitivity measures: i) the Elementary Effect for screening the parameters, and ii) the variance decomposition method for calculating the Sobol indices that quantify both the main and interaction effects. The application of the proposed approach is illustrated with an industrial application with the goal of optimizing a drilling process using a Gaussian laser beam.« less

An integrated approach for the knowledge discovery in computer simulation models with a multi-dimensional parameter space

NASA Astrophysics Data System (ADS)

Khawli, Toufik Al; Gebhardt, Sascha; Eppelt, Urs; Hermanns, Torsten; Kuhlen, Torsten; Schulz, Wolfgang

2016-06-01

In production industries, parameter identification, sensitivity analysis and multi-dimensional visualization are vital steps in the planning process for achieving optimal designs and gaining valuable information. Sensitivity analysis and visualization can help in identifying the most-influential parameters and quantify their contribution to the model output, reduce the model complexity, and enhance the understanding of the model behavior. Typically, this requires a large number of simulations, which can be both very expensive and time consuming when the simulation models are numerically complex and the number of parameter inputs increases. There are three main constituent parts in this work. The first part is to substitute the numerical, physical model by an accurate surrogate model, the so-called metamodel. The second part includes a multi-dimensional visualization approach for the visual exploration of metamodels. In the third part, the metamodel is used to provide the two global sensitivity measures: i) the Elementary Effect for screening the parameters, and ii) the variance decomposition method for calculating the Sobol indices that quantify both the main and interaction effects. The application of the proposed approach is illustrated with an industrial application with the goal of optimizing a drilling process using a Gaussian laser beam.

A New Multi-dimensional General Relativistic Neutrino Hydrodynamics Code of Core-collapse Supernovae. III. Gravitational Wave Signals from Supernova Explosion Models

NASA Astrophysics Data System (ADS)

Müller, Bernhard; Janka, Hans-Thomas; Marek, Andreas

2013-03-01

We present a detailed theoretical analysis of the gravitational wave (GW) signal of the post-bounce evolution of core-collapse supernovae (SNe), employing for the first time relativistic, two-dimensional explosion models with multi-group, three-flavor neutrino transport based on the ray-by-ray-plus approximation. The waveforms reflect the accelerated mass motions associated with the characteristic evolutionary stages that were also identified in previous works: a quasi-periodic modulation by prompt post-shock convection is followed by a phase of relative quiescence before growing amplitudes signal violent hydrodynamical activity due to convection and the standing accretion shock instability during the accretion period of the stalled shock. Finally, a high-frequency, low-amplitude variation from proto-neutron star (PNS) convection below the neutrinosphere appears superimposed on the low-frequency trend associated with the aspherical expansion of the SN shock after the onset of the explosion. Relativistic effects in combination with detailed neutrino transport are shown to be essential for quantitative predictions of the GW frequency evolution and energy spectrum, because they determine the structure of the PNS surface layer and its characteristic g-mode frequency. Burst-like high-frequency activity phases, correlated with sudden luminosity increase and spectral hardening of electron (anti-)neutrino emission for some 10 ms, are discovered as new features after the onset of the explosion. They correspond to intermittent episodes of anisotropic accretion by the PNS in the case of fallback SNe. We find stronger signals for more massive progenitors with large accretion rates. The typical frequencies are higher for massive PNSs, though the time-integrated spectrum also strongly depends on the model dynamics.

An alternative to Rasch analysis using triadic comparisons and multi-dimensional scaling

NASA Astrophysics Data System (ADS)

Bradley, C.; Massof, R. W.

2016-11-01

Rasch analysis is a principled approach for estimating the magnitude of some shared property of a set of items when a group of people assign ordinal ratings to them. In the general case, Rasch analysis not only estimates person and item measures on the same invariant scale, but also estimates the average thresholds used by the population to define rating categories. However, Rasch analysis fails when there is insufficient variance in the observed responses because it assumes a probabilistic relationship between person measures, item measures and the rating assigned by a person to an item. When only a single person is rating all items, there may be cases where the person assigns the same rating to many items no matter how many times he rates them. We introduce an alternative to Rasch analysis for precisely these situations. Our approach leverages multi-dimensional scaling (MDS) and requires only rank orderings of items and rank orderings of pairs of distances between items to work. Simulations show one variant of this approach - triadic comparisons with non-metric MDS - provides highly accurate estimates of item measures in realistic situations.

Estuarial fingerprinting through multidimensional fluorescence and multivariate analysis.

PubMed

Hall, Gregory J; Clow, Kerin E; Kenny, Jonathan E

2005-10-01

As part of a strategy for preventing the introduction of aquatic nuisance species (ANS) to U.S. estuaries, ballast water exchange (BWE) regulations have been imposed. Enforcing these regulations requires a reliable method for determining the port of origin of water in the ballast tanks of ships entering U.S. waters. This study shows that a three-dimensional fluorescence fingerprinting technique, excitation emission matrix (EEM) spectroscopy, holds great promise as a ballast water analysis tool. In our technique, EEMs are analyzed by multivariate classification and curve resolution methods, such as N-way partial least squares Regression-discriminant analysis (NPLS-DA) and parallel factor analysis (PARAFAC). We demonstrate that classification techniques can be used to discriminate among sampling sites less than 10 miles apart, encompassing Boston Harbor and two tributaries in the Mystic River Watershed. To our knowledge, this work is the first to use multivariate analysis to classify water as to location of origin. Furthermore, it is shown that curve resolution can show seasonal features within the multidimensional fluorescence data sets, which correlate with difficulty in classification.

Using multidimensional topological data analysis to identify traits of hip osteoarthritis.

PubMed

Rossi-deVries, Jasmine; Pedoia, Valentina; Samaan, Michael A; Ferguson, Adam R; Souza, Richard B; Majumdar, Sharmila

2018-05-07

Osteoarthritis (OA) is a multifaceted disease with many variables affecting diagnosis and progression. Topological data analysis (TDA) is a state-of-the-art big data analytics tool that can combine all variables into multidimensional space. TDA is used to simultaneously analyze imaging and gait analysis techniques. To identify biochemical and biomechanical biomarkers able to classify different disease progression phenotypes in subjects with and without radiographic signs of hip OA. Longitudinal study for comparison of progressive and nonprogressive subjects. In all, 102 subjects with and without radiographic signs of hip osteoarthritis. 3T, SPGR 3D MAPSS T 1ρ /T 2 , intermediate-weighted fat-suppressed fast spin-echo (FSE). Multidimensional data analysis including cartilage composition, bone shape, Kellgren-Lawrence (KL) classification of osteoarthritis, scoring hip osteoarthritis with MRI (SHOMRI), hip disability and osteoarthritis outcome score (HOOS). Analysis done using TDA, Kolmogorov-Smirnov (KS) testing, and Benjamini-Hochberg to rank P-value results to correct for multiple comparisons. Subjects in the later stages of the disease had an increased SHOMRI score (P < 0.0001), increased KL (P = 0.0012), and older age (P < 0.0001). Subjects in the healthier group showed intact cartilage and less pain. Subjects found between these two groups had a range of symptoms. Analysis of this subgroup identified knee biomechanics (P < 0.0001) as an initial marker of the disease that is noticeable before the morphological progression and degeneration. Further analysis of an OA subgroup with femoroacetabular impingement (FAI) showed anterior labral tears to be the most significant marker (P = 0.0017) between those FAI subjects with and without OA symptoms. The data-driven analysis obtained with TDA proposes new phenotypes of these subjects that partially overlap with the radiographic-based classical disease status classification and also shows the potential for further examination of an early onset biomechanical intervention. 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018. © 2018 International Society for Magnetic Resonance in Medicine.

The Social Profile of Students in Basic General Education in Ecuador: A Data Analysis

ERIC Educational Resources Information Center

Buri, Olga Elizabeth Minchala; Stefos, Efstathios

2017-01-01

The objective of this study is to examine the social profile of students who are enrolled in Basic General Education in Ecuador. Both a descriptive and multidimensional statistical analysis was carried out based on the data provided by the National Survey of Employment, Unemployment and Underemployment in 2015. The descriptive analysis shows the…

Developing Multidimensional Likert Scales Using Item Factor Analysis: The Case of Four-Point Items

ERIC Educational Resources Information Center

Asún, Rodrigo A.; Rdz-Navarro, Karina; Alvarado, Jesús M.

2016-01-01

This study compares the performance of two approaches in analysing four-point Likert rating scales with a factorial model: the classical factor analysis (FA) and the item factor analysis (IFA). For FA, maximum likelihood and weighted least squares estimations using Pearson correlation matrices among items are compared. For IFA, diagonally weighted…

Social and economic ideologies differentially predict prejudice across the political spectrum, but social issues are most divisive.

PubMed

Crawford, Jarret T; Brandt, Mark J; Inbar, Yoel; Chambers, John R; Motyl, Matt

2017-03-01

Liberals and conservatives both express prejudice toward ideologically dissimilar others (Brandt et al., 2014). Previous work on ideological prejudice did not take advantage of evidence showing that ideology is multidimensional, with social and economic ideologies representing related but separable belief systems. In 5 studies (total N = 4912), we test 3 competing hypotheses of a multidimensional account of ideological prejudice. The dimension-specific symmetry hypothesis predicts that social and economic ideologies differentially predict prejudice against targets who are perceived to vary on the social and economic political dimensions, respectively. The social primacy hypothesis predicts that such ideological worldview conflict is experienced more strongly along the social than economic dimension. The social-specific asymmetry hypothesis predicts that social conservatives will be more prejudiced than social liberals, with no specific hypotheses for the economic dimension. Using multiple target groups, multiple prejudice measures (e.g., global evaluations, behavior), and multiple social and economic ideology measures (self-placement, issue positions), we found relatively consistent support for the dimension-specific symmetry and social primacy hypotheses, and no support for the social-specific asymmetry hypothesis. These results suggest that worldview conflict and negative intergroup attitudes and behaviors are dimension-specific, but that the social dimension appears to inspire more political conflict than the economic dimension. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Multiple acquisitions via sequential transfer of orphan spin polarization (MAeSTOSO): How far can we push residual spin polarization in solid-state NMR?

NASA Astrophysics Data System (ADS)

Gopinath, T.; Veglia, Gianluigi

2016-06-01

Conventional multidimensional magic angle spinning (MAS) solid-state NMR (ssNMR) experiments detect the signal arising from the decay of a single coherence transfer pathway (FID), resulting in one spectrum per acquisition time. Recently, we introduced two new strategies, namely DUMAS (DUal acquisition Magic Angle Spinning) and MEIOSIS (Multiple ExperIments via Orphan SpIn operatorS), that enable the simultaneous acquisitions of multidimensional ssNMR experiments using multiple coherence transfer pathways. Here, we combined the main elements of DUMAS and MEIOSIS to harness both orphan spin operators and residual polarization and increase the number of simultaneous acquisitions. We show that it is possible to acquire up to eight two-dimensional experiments using four acquisition periods per each scan. This new suite of pulse sequences, called MAeSTOSO for Multiple Acquisitions via Sequential Transfer of Orphan Spin pOlarization, relies on residual polarization of both 13C and 15N pathways and combines low- and high-sensitivity experiments into a single pulse sequence using one receiver and commercial ssNMR probes. The acquisition of multiple experiments does not affect the sensitivity of the main experiment; rather it recovers the lost coherences that are discarded, resulting in a significant gain in experimental time. Both merits and limitations of this approach are discussed.

Designing Trend-Monitoring Sounds for Helicopters: Methodological Issues and an Application

ERIC Educational Resources Information Center

Edworthy, Judy; Hellier, Elizabeth; Aldrich, Kirsteen; Loxley, Sarah

2004-01-01

This article explores methodological issues in sonification and sound design arising from the design of helicopter monitoring sounds. Six monitoring sounds (each with 5 levels) were tested for similarity and meaning with 3 different techniques: hierarchical cluster analysis, linkage analysis, and multidimensional scaling. In Experiment 1,…

Error control techniques for satellite and space communications

NASA Technical Reports Server (NTRS)

Costello, Daniel J., Jr.

1988-01-01

During the period December 1, 1987 through May 31, 1988, progress was made in the following areas: construction of Multi-Dimensional Bandwidth Efficient Trellis Codes with MPSK modulation; performance analysis of Bandwidth Efficient Trellis Coded Modulation schemes; and performance analysis of Bandwidth Efficient Trellis Codes on Fading Channels.

Visualizing the Structure of Medical Informatics Using Term Co-Occurrence Analysis.

ERIC Educational Resources Information Center

Morris, Theodore Allan

2000-01-01

Examines the structure of medical informatics and the relationship between biomedicine and information science and information technology. Uses co-occurrence analysis of subject headings assigned to items indexed for MEDLINE as well as multidimensional scaling to show seven to eight broad multidisciplinary subject clusters. (Contains 28…

Communication Network Analysis Methods.

ERIC Educational Resources Information Center

Farace, Richard V.; Mabee, Timothy

This paper reviews a variety of analytic procedures that can be applied to network data, discussing the assumptions and usefulness of each procedure when applied to the complexity of human communication. Special attention is paid to the network properties measured or implied by each procedure. Factor analysis and multidimensional scaling are among…

The Circumplex Pattern of the Life Styles Inventory: A Reanalysis.

ERIC Educational Resources Information Center

Levin, Joseph

1991-01-01

A reanalysis of the intercorrelation matrix from a principal components analysis of the Life Styles Inventory was conducted using a Canadian sample. Using nonmetric multidimensional scaling, analyses show an almost perfect circumplex pattern. Results illustrate the inadequacy of factor analytic procedures for the analysis and representation of a…

Mining a Web Citation Database for Author Co-Citation Analysis.

ERIC Educational Resources Information Center

He, Yulan; Hui, Siu Cheung

2002-01-01

Proposes a mining process to automate author co-citation analysis based on the Web Citation Database, a data warehouse for storing citation indices of Web publications. Describes the use of agglomerative hierarchical clustering for author clustering and multidimensional scaling for displaying author cluster maps, and explains PubSearch, a…

A Comparative Study of Online Item Calibration Methods in Multidimensional Computerized Adaptive Testing

ERIC Educational Resources Information Center

Chen, Ping

2017-01-01

Calibration of new items online has been an important topic in item replenishment for multidimensional computerized adaptive testing (MCAT). Several online calibration methods have been proposed for MCAT, such as multidimensional "one expectation-maximization (EM) cycle" (M-OEM) and multidimensional "multiple EM cycles"…

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…

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…

Time-space and cognition-space transformations for transportation network analysis based on multidimensional scaling and self-organizing map

NASA Astrophysics Data System (ADS)

Hong, Zixuan; Bian, Fuling

2008-10-01

Geographic space, time space and cognition space are three fundamental and interrelated spaces in geographic information systems for transportation. However, the cognition space and its relationships to the time space and geographic space are often neglected. This paper studies the relationships of these three spaces in urban transportation system from a new perspective and proposes a novel MDS-SOM transformation method which takes the advantages of the techniques of multidimensional scaling (MDS) and self-organizing map (SOM). The MDS-SOM transformation framework includes three kinds of mapping: the geographic-time transformation, the cognition-time transformation and the time-cognition transformation. The transformations in our research provide a better understanding of the interactions of these three spaces and beneficial knowledge is discovered to help the transportation analysis and decision supports.

Study of multi-dimensional radiative energy transfer in molecular gases

NASA Technical Reports Server (NTRS)

Liu, Jiwen; Tiwari, S. N.

1993-01-01

The Monte Carlo method (MCM) is applied to analyze radiative heat transfer in nongray gases. The nongray model employed is based on the statistical arrow band model with an exponential-tailed inverse intensity distribution. Consideration of spectral correlation results in some distinguishing features of the Monte Carlo formulations. Validation of the Monte Carlo formulations has been conducted by comparing results of this method with other solutions. Extension of a one-dimensional problem to a multi-dimensional problem requires some special treatments in the Monte Carlo analysis. Use of different assumptions results in different sets of Monte Carlo formulations. The nongray narrow band formulations provide the most accurate results.

On the use of multi-dimensional scaling and electromagnetic tracking in high dose rate brachytherapy

NASA Astrophysics Data System (ADS)

Götz, Th I.; Ermer, M.; Salas-González, D.; Kellermeier, M.; Strnad, V.; Bert, Ch; Hensel, B.; Tomé, A. M.; Lang, E. W.

2017-10-01

High dose rate brachytherapy affords a frequent reassurance of the precise dwell positions of the radiation source. The current investigation proposes a multi-dimensional scaling transformation of both data sets to estimate dwell positions without any external reference. Furthermore, the related distributions of dwell positions are characterized by uni—or bi—modal heavy—tailed distributions. The latter are well represented by α—stable distributions. The newly proposed data analysis provides dwell position deviations with high accuracy, and, furthermore, offers a convenient visualization of the actual shapes of the catheters which guide the radiation source during the treatment.

Analysis of World Economic Variables Using Multidimensional Scaling

PubMed Central

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

Assortativity Patterns in Multi-dimensional Inter-organizational Networks: A Case Study of the Humanitarian Relief Sector

NASA Astrophysics Data System (ADS)

Zhao, Kang; Ngamassi, Louis-Marie; Yen, John; Maitland, Carleen; Tapia, Andrea

We use computational tools to study assortativity patterns in multi-dimensional inter-organizational networks on the basis of different node attributes. In the case study of an inter-organizational network in the humanitarian relief sector, we consider not only macro-level topological patterns, but also assortativity on the basis of micro-level organizational attributes. Unlike assortative social networks, this inter-organizational network exhibits disassortative or random patterns on three node attributes. We believe organizations' seek of complementarity is one of the main reasons for the special patterns. Our analysis also provides insights on how to promote collaborations among the humanitarian relief organizations.

Composite scores in comparative effectiveness research: counterbalancing parsimony and dimensionality in patient-reported outcomes.

PubMed

Schwartz, Carolyn E; Patrick, Donald L

2014-07-01

When planning a comparative effectiveness study comparing disease-modifying treatments, competing demands influence choice of outcomes. Current practice emphasizes parsimony, although understanding multidimensional treatment impact can help to personalize medical decision-making. We discuss both sides of this 'tug of war'. We discuss the assumptions, advantages and drawbacks of composite scores and multidimensional outcomes. We describe possible solutions to the multiple comparison problem, including conceptual hierarchy distinctions, statistical approaches, 'real-world' benchmarks of effectiveness and subgroup analysis. We conclude that comparative effectiveness research should consider multiple outcome dimensions and compare different approaches that fit the individual context of study objectives.

Value-based formulas for purchasing. PEHP's designated service provider program: value-based purchasing through global fees.

PubMed

Emery, D W

1997-01-01

In many circles, managed care and capitation have become synonymous; unfortunately, the assumptions informing capitation are based on a flawed unidimensional model of risk. PEHP of Utah has rejected the unidimensional model and has therefore embraced a multidimensional model of risk that suggests that global fees are the optimal purchasing modality. A globally priced episode of care forms a natural unit of analysis that enhances purchasing clarity, allows providers to more efficiently focus on the Marginal Rate of Technical Substitution, and conforms to the multidimensional reality of risk. Most importantly, global fees simultaneously maximize patient choice and provider cost consciousness.

Phenomenology of COMPASS data: Multiplicities and phenomenology - part II

DOE PAGES

Anselmino, M.; Boglione, M.; Gonzalez H., J. O.; ...

2015-01-23

In this study, we present some of the main features of the multidimensional COMPASS multiplicities, via our analysis using the simple Gaussian model. We briefly discuss these results in connection with azimuthal asymmetries.

Understanding the Self in Individuals with Autism Spectrum Disorders (ASD): A Review of Literature.

PubMed

Huang, Ann X; Hughes, Tammy L; Sutton, Lawrence R; Lawrence, Marissa; Chen, Xiaohan; Ji, Zhe; Zeleke, Waganesh

2017-01-01

When the system of self is explored in individuals with Autism Spectrum Disorders (ASDs), it is important to measure it via both their own perceptions of the self and their understanding of others' perceptions on themselves at a multidimensional level. This paper reviews existing research in this area using a three-dimension approach. Researchers have found that impairments in the self-system are usually correlated with these individuals' social and cognitive functioning levels: high functioning individuals with ASD who have higher IQ are found to have better awareness of their limitations in social and communication domains than those with lower IQ. Many researchers believe that there are impairments in the psychological (but not physical) self in individuals with ASD, such as theory of mind deficits due to social and communicative impairments. On the other hand, some researchers argue that individuals with ASD have selective rather than global impairments in the self. In other words, the impairment usually lies in a specific aspect of functioning in individuals with ASD. Insights from the review of existing literature on this topic may be able to shed some lights on the development of effective intervention programs to improve social communication deficits in this population.

Estimator banks: a new tool for direction-of-arrival estimation

NASA Astrophysics Data System (ADS)

Gershman, Alex B.; Boehme, Johann F.

1997-10-01

A new powerful tool for improving the threshold performance of direction-of-arrival (DOA) estimation is considered. The essence of our approach is to reduce the number of outliers in the threshold domain using the so-called estimator bank containing multiple 'parallel' underlying DOA estimators which are based on pseudorandom resampling of the MUSIC spatial spectrum for given data batch or sample covariance matrix. To improve the threshold performance relative to conventional MUSIC, evolutionary principles are used, i.e., only 'successful' underlying estimators (having no failure in the preliminary estimated source localization sectors) are exploited in the final estimate. An efficient beamspace root implementation of the estimator bank approach is developed, combined with the array interpolation technique which enables the application to arbitrary arrays. A higher-order extension of our approach is also presented, where the cumulant-based MUSIC estimator is exploited as a basic technique for spatial spectrum resampling. Simulations and experimental data processing show that our algorithm performs well below the MUSIC threshold, namely, has the threshold performance similar to that of the stochastic ML method. At the same time, the computational cost of our algorithm is much lower than that of stochastic ML because no multidimensional optimization is involved.

Multidimensional Perfectionism and Burnout: A Meta-Analysis.

PubMed

Hill, Andrew P; Curran, Thomas

2016-08-01

A meta-analysis of research examining the relationships between multidimensional perfectionism and burnout is provided. In doing so, relationships before and after controlling for the relationship between dimensions of perfectionism were examined along with whether relationships were moderated by domain (work, sport, or education). A literature search yielded 43 studies (N = 9,838) and 663 effect sizes. Meta-analysis using random-effects models revealed that perfectionistic strivings had small negative or non-significant relationships with overall burnout and symptoms of burnout. By contrast, perfectionistic concerns displayed medium-to-large and medium positive relationships with overall burnout and symptoms of burnout. After controlling for the relationship between dimensions of perfectionism, "pure" perfectionistic strivings displayed notably larger negative relationships. In terms of moderation, in some cases, perfectionistic strivings were less adaptive and perfectionistic concerns more maladaptive in the work domain. Future research should examine explanatory mechanisms, adopt longitudinal designs, and develop interventions to reduce perfectionistic concerns fueled burnout. © 2015 by the Society for Personality and Social Psychology, Inc.

Time-varying nonstationary multivariate risk analysis using a dynamic Bayesian copula

NASA Astrophysics Data System (ADS)

Sarhadi, Ali; Burn, Donald H.; Concepción Ausín, María.; Wiper, Michael P.

2016-03-01

A time-varying risk analysis is proposed for an adaptive design framework in nonstationary conditions arising from climate change. A Bayesian, dynamic conditional copula is developed for modeling the time-varying dependence structure between mixed continuous and discrete multiattributes of multidimensional hydrometeorological phenomena. Joint Bayesian inference is carried out to fit the marginals and copula in an illustrative example using an adaptive, Gibbs Markov Chain Monte Carlo (MCMC) sampler. Posterior mean estimates and credible intervals are provided for the model parameters and the Deviance Information Criterion (DIC) is used to select the model that best captures different forms of nonstationarity over time. This study also introduces a fully Bayesian, time-varying joint return period for multivariate time-dependent risk analysis in nonstationary environments. The results demonstrate that the nature and the risk of extreme-climate multidimensional processes are changed over time under the impact of climate change, and accordingly the long-term decision making strategies should be updated based on the anomalies of the nonstationary environment.

Enhancing the ABAQUS thermomechanics code to simulate multipellet steady and transient LWR fuel rod behavior

DOE Office of Scientific and Technical Information (OSTI.GOV)

R. L. Williamson

A powerful multidimensional fuels performance analysis capability, applicable to both steady and transient fuel behavior, is developed based on enhancements to the commercially available ABAQUS general-purpose thermomechanics code. Enhanced capabilities are described, including: UO2 temperature and burnup dependent thermal properties, solid and gaseous fission product swelling, fuel densification, fission gas release, cladding thermal and irradiation creep, cladding irradiation growth, gap heat transfer, and gap/plenum gas behavior during irradiation. This new capability is demonstrated using a 2D axisymmetric analysis of the upper section of a simplified multipellet fuel rod, during both steady and transient operation. Comparisons are made between discrete andmore » smeared-pellet simulations. Computational results demonstrate the importance of a multidimensional, multipellet, fully-coupled thermomechanical approach. Interestingly, many of the inherent deficiencies in existing fuel performance codes (e.g., 1D thermomechanics, loose thermomechanical coupling, separate steady and transient analysis, cumbersome pre- and post-processing) are, in fact, ABAQUS strengths.« less

Young friendship in HFASD and typical development: friend versus non-friend comparisons.

PubMed

Bauminger-Zviely, Nirit; Agam-Ben-Artzi, Galit

2014-07-01

This study conducted comparative assessment of friendship in preschoolers with high-functioning autism spectrum disorder (HFASD, n = 29) versus preschoolers with typical development (n = 30), focusing on interactions with friends versus acquaintances. Groups were matched on SES, verbal/nonverbal MA, IQ, and CA. Multidimensional assessments included: mothers' and teachers' reports about friends' and friendship characteristics and observed individual and dyadic behaviors throughout interactions with friends versus non-friends during construction, drawing, and free-play situations. Findings revealed group differences in peer interaction favoring the typical development group, thus supporting the neuropsychological profile of HFASD. However, both groups' interactions with friends surpassed interactions with acquaintances on several key socio-communicative and intersubjective capabilities, thus suggesting that friendship may contribute to enhancement and practice of social interaction in HFASD.

Dual-comb spectroscopy of molecular electronic transitions in condensed phases

NASA Astrophysics Data System (ADS)

Cho, Byungmoon; Yoon, Tai Hyun; Cho, Minhaeng

2018-03-01

Dual-comb spectroscopy (DCS) utilizes two phase-locked optical frequency combs to allow scanless acquisition of spectra using only a single point detector. Although recent DCS measurements demonstrate rapid acquisition of absolutely calibrated spectral lines with unprecedented precision and accuracy, complex phase-locking schemes and multiple coherent averaging present significant challenges for widespread adoption of DCS. Here, we demonstrate Global Positioning System (GPS) disciplined DCS of a molecular electronic transition in solution at around 800 nm, where the absorption spectrum is recovered by using a single time-domain interferogram. We anticipate that this simplified dual-comb technique with absolute time interval measurement and ultrabroad bandwidth will allow adoption of DCS to tackle molecular dynamics investigation through its implementation in time-resolved nonlinear spectroscopic studies and coherent multidimensional spectroscopy of coupled chromophore systems.

The Stability of Self-Reported Anxiety in Youth with Autism Versus ADHD or Typical Development.

PubMed

Schiltz, Hillary; McIntyre, Nancy; Swain-Lerro, Lindsay; Zajic, Matthew; Mundy, Peter

2017-12-01

Children with autism spectrum disorder (ASD) are at risk for anxiety symptoms. Few anxiety measures are validated for individuals with ASD, and the nature of ASD raises questions about reliability of self-reported anxiety. This study examined longitudinal stability and change of self-reported anxiety in higher functioning youth with ASD (HFASD) compared to youth with symptoms of attention deficit hyperactivity disorder and typical development (TD) using the Multidimensional Anxiety Scale for Children (March, 2012; March et al. J Am Acad Child Adolesc Psychiatry 36(4):554-565, 1997). Diagnostic groups demonstrated comparable evidence of stability for most dimensions of anxiety. The HFASD group displayed higher anxiety than both comparison groups, especially physical symptoms. These findings have implications for identification and measurement of anxiety in ASD.

Physiological correlates of mental workload

NASA Technical Reports Server (NTRS)

Zacharias, G. L.

1980-01-01

A literature review was conducted to assess the basis of and techniques for physiological assessment of mental workload. The study findings reviewed had shortcomings involving one or more of the following basic problems: (1) physiologic arousal can be easily driven by nonworkload factors, confounding any proposed metric; (2) the profound absence of underlying physiologic models has promulgated a multiplicity of seemingly arbitrary signal processing techniques; (3) the unspecified multidimensional nature of physiological "state" has given rise to a broad spectrum of competing noncommensurate metrics; and (4) the lack of an adequate definition of workload compels physiologic correlations to suffer either from the vagueness of implicit workload measures or from the variance of explicit subjective assessments. Using specific studies as examples, two basic signal processing/data reduction techniques in current use, time and ensemble averaging are discussed.

Conjoint Analysis: A Preference-Based Approach for the Accounting of Multiple Benefits in Southern Forest Management

Treesearch

F. Christian Zinkhan; Thomas P. Holmes; D. Evan Mercer

1997-01-01

Conjoint analysis, which enables a manager to measure the relative importance of a forest's multidimensional attributes, is critically reviewed and assessed. Special attention is given to the feasibility of using conjoint analysis for measuring the utility of market and nonmarket outputs from southern forests. Also, an application to a case of designing a nature...

Multidimensional Unfolding by Nonmetric Multidimensional Scaling of Spearman Distances in the Extended Permutation Polytope

ERIC Educational Resources Information Center

Van Deun, Katrijn; Heiser, Willem J.; Delbeke, Luc

2007-01-01

A multidimensional unfolding technique that is not prone to degenerate solutions and is based on multidimensional scaling of a complete data matrix is proposed: distance information about the unfolding data and about the distances both among judges and among objects is included in the complete matrix. The latter information is derived from the…

ICM: a web server for integrated clustering of multi-dimensional biomedical data.

PubMed

He, Song; He, Haochen; Xu, Wenjian; Huang, Xin; Jiang, Shuai; Li, Fei; He, Fuchu; Bo, Xiaochen

2016-07-08

Large-scale efforts for parallel acquisition of multi-omics profiling continue to generate extensive amounts of multi-dimensional biomedical data. Thus, integrated clustering of multiple types of omics data is essential for developing individual-based treatments and precision medicine. However, while rapid progress has been made, methods for integrated clustering are lacking an intuitive web interface that facilitates the biomedical researchers without sufficient programming skills. Here, we present a web tool, named Integrated Clustering of Multi-dimensional biomedical data (ICM), that provides an interface from which to fuse, cluster and visualize multi-dimensional biomedical data and knowledge. With ICM, users can explore the heterogeneity of a disease or a biological process by identifying subgroups of patients. The results obtained can then be interactively modified by using an intuitive user interface. Researchers can also exchange the results from ICM with collaborators via a web link containing a Project ID number that will directly pull up the analysis results being shared. ICM also support incremental clustering that allows users to add new sample data into the data of a previous study to obtain a clustering result. Currently, the ICM web server is available with no login requirement and at no cost at http://biotech.bmi.ac.cn/icm/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Improved p-type conductivity in Al-rich AlGaN using multidimensional Mg-doped superlattices

PubMed Central

Zheng, T. C.; Lin, W.; Liu, R.; Cai, D. J.; Li, J. C.; Li, S. P.; Kang, J. Y.

2016-01-01

A novel multidimensional Mg-doped superlattice (SL) is proposed to enhance vertical hole conductivity in conventional Mg-doped AlGaN SL which generally suffers from large potential barrier for holes. Electronic structure calculations within the first-principle theoretical framework indicate that the densities of states (DOS) of the valence band nearby the Fermi level are more delocalized along the c-axis than that in conventional SL, and the potential barrier significantly decreases. Hole concentration is greatly enhanced in the barrier of multidimensional SL. Detailed comparisons of partial charges and decomposed DOS reveal that the improvement of vertical conductance may be ascribed to the stronger pz hybridization between Mg and N. Based on the theoretical analysis, highly conductive p-type multidimensional Al0.63Ga0.37N/Al0.51Ga0.49N SLs are grown with identified steps via metalorganic vapor-phase epitaxy. The hole concentration reaches up to 3.5 × 1018 cm−3, while the corresponding resistivity reduces to 0.7 Ω cm at room temperature, which is tens times improvement in conductivity compared with that of conventional SLs. High hole concentration can be maintained even at 100 K. High p-type conductivity in Al-rich structural material is an important step for the future design of superior AlGaN-based deep ultraviolet devices. PMID:26906334

A Conceptual Modeling Approach for OLAP Personalization

NASA Astrophysics Data System (ADS)

Garrigós, Irene; Pardillo, Jesús; Mazón, Jose-Norberto; Trujillo, Juan

Data warehouses rely on multidimensional models in order to provide decision makers with appropriate structures to intuitively analyze data with OLAP technologies. However, data warehouses may be potentially large and multidimensional structures become increasingly complex to be understood at a glance. Even if a departmental data warehouse (also known as data mart) is used, these structures would be also too complex. As a consequence, acquiring the required information is more costly than expected and decision makers using OLAP tools may get frustrated. In this context, current approaches for data warehouse design are focused on deriving a unique OLAP schema for all analysts from their previously stated information requirements, which is not enough to lighten the complexity of the decision making process. To overcome this drawback, we argue for personalizing multidimensional models for OLAP technologies according to the continuously changing user characteristics, context, requirements and behaviour. In this paper, we present a novel approach to personalizing OLAP systems at the conceptual level based on the underlying multidimensional model of the data warehouse, a user model and a set of personalization rules. The great advantage of our approach is that a personalized OLAP schema is provided for each decision maker contributing to better satisfy their specific analysis needs. Finally, we show the applicability of our approach through a sample scenario based on our CASE tool for data warehouse development.

Utilization of the Discrete Differential Evolution for Optimization in Multidimensional Point Clouds.

PubMed

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.

Utilization of the Discrete Differential Evolution for Optimization in Multidimensional Point Clouds

PubMed Central

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

The Effect of Multidimensional Motivation Interventions on Cognitive and Behavioral Components of Motivation: Testing Martin's Model

PubMed Central

Pooragha Roodbarde, Fatemeh; Talepasand, Siavash; Rahimian Boogar, Issac

2017-01-01

Objective: The present study aimed at examining the effect of multidimensional motivation interventions based on Martin's model on cognitive and behavioral components of motivation. Method: The research design was prospective with pretest, posttest, and follow-up, and 2 experimental groups. In this study, 90 students (45 participants in the experimental group and 45 in the control group) constituted the sample of the study, and they were selected by available sampling method. Motivation interventions were implemented for fifteen 60-minute sessions 3 times a week, which lasted for about 2 months. Data were analyzed using repeated measures multivariate variance analysis test. Results: The findings revealed that multidimensional motivation interventions resulted in a significant increase in the scores of cognitive components such as self-efficacy, mastery goal, test anxiety, and feeling of lack of control, and behavioral components such as task management. The results of one-month follow-up indicated the stability of the created changes in test anxiety and cognitive strategies; however, no significant difference was found between the 2 groups at the follow-up in self-efficacy, mastery goals, source of control, and motivation. Conclusion: The research evidence indicated that academic motivation is a multidimensional component and is affected by cognitive and behavioral factors; therefore, researchers, teachers, and other authorities should attend to these factors to increase academic motivation. PMID:28659984

The Effect of Multidimensional Motivation Interventions on Cognitive and Behavioral Components of Motivation: Testing Martin's Model.

PubMed

Pooragha Roodbarde, Fatemeh; Talepasand, Siavash; Rahimian Boogar, Issac

2017-04-01

Objective: The present study aimed at examining the effect of multidimensional motivation interventions based on Martin's model on cognitive and behavioral components of motivation. Method: The research design was prospective with pretest, posttest, and follow-up, and 2 experimental groups. In this study, 90 students (45 participants in the experimental group and 45 in the control group) constituted the sample of the study, and they were selected by available sampling method. Motivation interventions were implemented for fifteen 60-minute sessions 3 times a week, which lasted for about 2 months. Data were analyzed using repeated measures multivariate variance analysis test. Results: The findings revealed that multidimensional motivation interventions resulted in a significant increase in the scores of cognitive components such as self-efficacy, mastery goal, test anxiety, and feeling of lack of control, and behavioral components such as task management. The results of one-month follow-up indicated the stability of the created changes in test anxiety and cognitive strategies; however, no significant difference was found between the 2 groups at the follow-up in self-efficacy, mastery goals, source of control, and motivation. Conclusion: The research evidence indicated that academic motivation is a multidimensional component and is affected by cognitive and behavioral factors; therefore, researchers, teachers, and other authorities should attend to these factors to increase academic motivation.

A Person-Centered Perspective on Multidimensional Perfectionism in Canadian and Chinese University Students: A Multigroup Latent Profile Analysis

ERIC Educational Resources Information Center

Smith, Martin M.; Saklofske, Donald H.; Yan, Gonggu; Sherry, Simon B.

2016-01-01

This study investigated the generalizability of the tripartite model of perfectionism across Canadian and Chinese university students. Using latent profile analysis and indicators of perfectionistic strivings, perfectionistic concerns, and neuroticism in both groups, the authors derived a 3-profile solution: adaptive perfectionists, maladaptive…

Convergence of Personality and Interests: Meta-Analysis of the Multidimensional Personality Questionnaire and the Strong Interest Inventory

ERIC Educational Resources Information Center

Staggs, Gena D.; Larson, Lisa M.; Borgen, Fred H.

2007-01-01

Using meta-analysis, we revised Ackerman and Heggestad's (1997) identification of four trait complexes that propose personality and interest (P-I) linkages. Studies that had reported correlations between general and specific measures of vocational interests (Strong Interest Inventory [Strong; Hansen & Campbell, 1985; Harmon, Hansen, Borgen,…

The Effects of Family Therapies for Adolescent Delinquency and Substance Abuse: A Meta-Analysis

ERIC Educational Resources Information Center

Baldwin, Scott A.; Christian, Sarah; Berkeljon, Arjan; Shadish, William R.

2012-01-01

This meta-analysis summarizes results from k = 24 studies comparing either Brief Strategic Family Therapy, Functional Family Therapy, Multidimensional Family Therapy, or Multisystemic Therapy to either treatment-as-usual, an alternative therapy, or a control group in the treatment of adolescent substance abuse and delinquency. Additionally, the…

Meta-Analysis of Biofeedback for Tension-Type Headache: Efficacy, Specificity, and Treatment Moderators

ERIC Educational Resources Information Center

Nestoriuc, Yvonne; Rief, Winfried; Martin, Alexandra

2008-01-01

The aims of the present meta-analysis were to investigate the short- and long-term efficacy, multidimensional outcome, and treatment moderators of biofeedback as a behavioral treatment option for tension-type headache. A literature search identified 74 outcome studies, of which 53 were selected according to predefined inclusion criteria.…

Diagnostic Classification Models: Are They Necessary? Commentary on Rupp and Templin (2008)

ERIC Educational Resources Information Center

Gorin, Joanna S.

2009-01-01

In their paper "Unique Characteristics of Diagnostic Classification Models: A Comprehensive Review of the Current State-of-the-Art," Andre Rupp and Jonathan Templin (2008) provide a comparative analysis of selected psychometric models useful for the analysis of multidimensional data for purposes of diagnostic score reporting. Recent assessment…

"Competing Conceptions of Globalization" Revisited: Relocating the Tension between World-Systems Analysis and Globalization Analysis

ERIC Educational Resources Information Center

Clayton, Thomas

2004-01-01

In recent years, many scholars have become fascinated by a contemporary, multidimensional process that has come to be known as "globalization." Globalization originally described economic developments at the world level. More specifically, scholars invoked the concept in reference to the process of global economic integration and the seemingly…

Multidimensional Analysis of Linguistic Networks

NASA Astrophysics Data System (ADS)

Araújo, Tanya; Banisch, Sven

Network-based approaches play an increasingly important role in the analysis of data even in systems in which a network representation is not immediately apparent. This is particularly true for linguistic networks, which use to be induced from a linguistic data set for which a network perspective is only one out of several options for representation. Here we introduce a multidimensional framework for network construction and analysis with special focus on linguistic networks. Such a framework is used to show that the higher is the abstraction level of network induction, the harder is the interpretation of the topological indicators used in network analysis. Several examples are provided allowing for the comparison of different linguistic networks as well as to networks in other fields of application of network theory. The computation and the intelligibility of some statistical indicators frequently used in linguistic networks are discussed. It suggests that the field of linguistic networks, by applying statistical tools inspired by network studies in other domains, may, in its current state, have only a limited contribution to the development of linguistic theory.

Multivariate Analysis of the Visual Information Processing of Numbers

ERIC Educational Resources Information Center

Levine, David M.

1977-01-01

Nonmetric multidimensional scaling and hierarchical clustering procedures are applied to a confusion matrix of numerals. Two dimensions were interpreted: straight versus curved, and locus of curvature. Four major clusters of numerals were developed. (Author/JKS)

LIS Professionals as Knowledge Engineers.

ERIC Educational Resources Information Center

Poulter, Alan; And Others

1994-01-01

Considers the role of library and information science professionals as knowledge engineers. Highlights include knowledge acquisition, including personal experience, interviews, protocol analysis, observation, multidimensional sorting, printed sources, and machine learning; knowledge representation, including production rules and semantic nets;…

Results of an Oncology Clinical Trial Nurse Role Delineation Study.

PubMed

Purdom, Michelle A; Petersen, Sandra; Haas, Barbara K

2017-09-01

To evaluate the relevance of a five-dimensional model of clinical trial nursing practice in an oncology clinical trial nurse population. 
. Web-based cross-sectional survey.
. Online via Qualtrics.
. 167 oncology nurses throughout the United States, including 41 study coordinators, 35 direct care providers, and 91 dual-role nurses who provide direct patient care and trial coordination.
. Principal components analysis was used to determine the dimensions of oncology clinical trial nursing practice.
. Self-reported frequency of 59 activities.
. The results did not support the original five-dimensional model of nursing care but revealed a more multidimensional model.
. An analysis of frequency data revealed an eight-dimensional model of oncology research nursing, including care, manage study, expert, lead, prepare, data, advance science, and ethics.
. This evidence-based model expands understanding of the multidimensional roles of oncology nurses caring for patients with cancer enrolled in clinical trials.

Multidimensional Interactive Radiology Report and Analysis: standardization of workflow and reporting for renal mass tracking and quantification

NASA Astrophysics Data System (ADS)

Hwang, Darryl H.; Ma, Kevin; Yepes, Fernando; Nadamuni, Mridula; Nayyar, Megha; Liu, Brent; Duddalwar, Vinay; Lepore, Natasha

2015-12-01

A conventional radiology report primarily consists of a large amount of unstructured text, and lacks clear, concise, consistent and content-rich information. Hence, an area of unmet clinical need consists of developing better ways to communicate radiology findings and information specific to each patient. Here, we design a new workflow and reporting system that combines and integrates advances in engineering technology with those from the medical sciences, the Multidimensional Interactive Radiology Report and Analysis (MIRRA). Until recently, clinical standards have primarily relied on 2D images for the purpose of measurement, but with the advent of 3D processing, many of the manually measured metrics can be automated, leading to better reproducibility and less subjective measurement placement. Hence, we make use this newly available 3D processing in our workflow. Our pipeline is used here to standardize the labeling, tracking, and quantifying of metrics for renal masses.

Multidimensional stock network analysis: An Escoufier's RV coefficient approach

NASA Astrophysics Data System (ADS)

Lee, Gan Siew; Djauhari, Maman A.

2013-09-01

The current practice of stocks network analysis is based on the assumption that the time series of closed stock price could represent the behaviour of the each stock. This assumption leads to consider minimal spanning tree (MST) and sub-dominant ultrametric (SDU) as an indispensible tool to filter the economic information contained in the network. Recently, there is an attempt where researchers represent stock not only as a univariate time series of closed price but as a bivariate time series of closed price and volume. In this case, they developed the so-called multidimensional MST to filter the important economic information. However, in this paper, we show that their approach is only applicable for that bivariate time series only. This leads us to introduce a new methodology to construct MST where each stock is represented by a multivariate time series. An example of Malaysian stock exchange will be presented and discussed to illustrate the advantages of the method.

Multidimensional Scaling Analysis of the Dynamics of a Country Economy

PubMed Central

Mata, Maria Eugénia

2013-01-01

This paper analyzes the Portuguese short-run business cycles over the last 150 years and presents the multidimensional scaling (MDS) for visualizing the results. The analytical and numerical assessment of this long-run perspective reveals periods with close connections between the macroeconomic variables related to government accounts equilibrium, balance of payments equilibrium, and economic growth. The MDS method is adopted for a quantitative statistical analysis. In this way, similarity clusters of several historical periods emerge in the MDS maps, namely, in identifying similarities and dissimilarities that identify periods of prosperity and crises, growth, and stagnation. Such features are major aspects of collective national achievement, to which can be associated the impact of international problems such as the World Wars, the Great Depression, or the current global financial crisis, as well as national events in the context of broad political blueprints for the Portuguese society in the rising globalization process. PMID:24294132

Do the BSRI and PAQ really measure masculinity and femininity?

PubMed

Fernández, Juan; Coello, Ma Teresa

2010-11-01

The two most used instruments to assess masculinity (M) and femininity (F) are the Bem Sex Role Inventory (BSRI) and the Personality Attributes Questionnaire (PAQ). Two hypotheses will be tested: a) multidimensionality versus bidimensionality, and b) to what extent the two instruments, elaborated to measure the same constructs, classify subjects in the same way. Participants were 420 high school students, 198 women and 222 men, aged 12-15 years. Exploratory factor analysis and internal consistency analysis were carried out and log-linear models were tested. The data support a) the multidimensionality of both instruments and b) the lack of full concordance in the classification of persons according to the fourfold typology. Implications of the results are discussed regarding the supposed theory behind instrumentality/ expressiveness and masculinity/femininity, as well as for the use of both instruments to classify different subjects into the four distinct types.

Enhancing the ABAQUS Thermomechanics Code to Simulate Steady and Transient Fuel Rod Behavior

DOE Office of Scientific and Technical Information (OSTI.GOV)

R. L. Williamson; D. A. Knoll

2009-09-01

A powerful multidimensional fuels performance capability, applicable to both steady and transient fuel behavior, is developed based on enhancements to the commercially available ABAQUS general-purpose thermomechanics code. Enhanced capabilities are described, including: UO2 temperature and burnup dependent thermal properties, solid and gaseous fission product swelling, fuel densification, fission gas release, cladding thermal and irradiation creep, cladding irradiation growth , gap heat transfer, and gap/plenum gas behavior during irradiation. The various modeling capabilities are demonstrated using a 2D axisymmetric analysis of the upper section of a simplified multi-pellet fuel rod, during both steady and transient operation. Computational results demonstrate the importancemore » of a multidimensional fully-coupled thermomechanics treatment. Interestingly, many of the inherent deficiencies in existing fuel performance codes (e.g., 1D thermomechanics, loose thermo-mechanical coupling, separate steady and transient analysis, cumbersome pre- and post-processing) are, in fact, ABAQUS strengths.« less

Multidimensional Processing and Visual Rendering of Complex 3D Biomedical Images

NASA Technical Reports Server (NTRS)

Sams, Clarence F.

2016-01-01

The proposed technology uses advanced image analysis techniques to maximize the resolution and utility of medical imaging methods being used during spaceflight. We utilize COTS technology for medical imaging, but our applications require higher resolution assessment of the medical images than is routinely applied with nominal system software. By leveraging advanced data reduction and multidimensional imaging techniques utilized in analysis of Planetary Sciences and Cell Biology imaging, it is possible to significantly increase the information extracted from the onboard biomedical imaging systems. Year 1 focused on application of these techniques to the ocular images collected on ground test subjects and ISS crewmembers. Focus was on the choroidal vasculature and the structure of the optic disc. Methods allowed for increased resolution and quantitation of structural changes enabling detailed assessment of progression over time. These techniques enhance the monitoring and evaluation of crew vision issues during space flight.

A spectrum fractal feature classification algorithm for agriculture crops with hyper spectrum image

NASA Astrophysics Data System (ADS)

Su, Junying

2011-11-01

A fractal dimension feature analysis method in spectrum domain for hyper spectrum image is proposed for agriculture crops classification. Firstly, a fractal dimension calculation algorithm in spectrum domain is presented together with the fast fractal dimension value calculation algorithm using the step measurement method. Secondly, the hyper spectrum image classification algorithm and flowchart is presented based on fractal dimension feature analysis in spectrum domain. Finally, the experiment result of the agricultural crops classification with FCL1 hyper spectrum image set with the proposed method and SAM (spectral angle mapper). The experiment results show it can obtain better classification result than the traditional SAM feature analysis which can fulfill use the spectrum information of hyper spectrum image to realize precision agricultural crops classification.

Defect-Repairable Latent Feature Extraction of Driving Behavior via a Deep Sparse Autoencoder

PubMed Central

Taniguchi, Tadahiro; Takenaka, Kazuhito; Bando, Takashi

2018-01-01

Data representing driving behavior, as measured by various sensors installed in a vehicle, are collected as multi-dimensional sensor time-series data. These data often include redundant information, e.g., both the speed of wheels and the engine speed represent the velocity of the vehicle. Redundant information can be expected to complicate the data analysis, e.g., more factors need to be analyzed; even varying the levels of redundancy can influence the results of the analysis. We assume that the measured multi-dimensional sensor time-series data of driving behavior are generated from low-dimensional data shared by the many types of one-dimensional data of which multi-dimensional time-series data are composed. Meanwhile, sensor time-series data may be defective because of sensor failure. Therefore, another important function is to reduce the negative effect of defective data when extracting low-dimensional time-series data. This study proposes a defect-repairable feature extraction method based on a deep sparse autoencoder (DSAE) to extract low-dimensional time-series data. In the experiments, we show that DSAE provides high-performance latent feature extraction for driving behavior, even for defective sensor time-series data. In addition, we show that the negative effect of defects on the driving behavior segmentation task could be reduced using the latent features extracted by DSAE. PMID:29462931

Is the mental wellbeing of young Australians best represented by a single, multidimensional or bifactor model?

PubMed

Hides, Leanne; Quinn, Catherine; Stoyanov, Stoyan; Cockshaw, Wendell; Mitchell, Tegan; Kavanagh, David J

2016-07-30

Internationally there is a growing interest in the mental wellbeing of young people. However, it is unclear whether mental wellbeing is best conceptualized as a general wellbeing factor or a multidimensional construct. This paper investigated whether mental wellbeing, measured by the Mental Health Continuum-Short Form (MHC-SF), is best represented by: (1) a single-factor general model; (2) a three-factor multidimensional model or (3) a combination of both (bifactor model). 2220 young Australians aged between 16 and 25 years completed an online survey including the MHC-SF and a range of other wellbeing and mental ill-health measures. Exploratory factor analysis supported a bifactor solution, comprised of a general wellbeing factor, and specific group factors of psychological, social and emotional wellbeing. Confirmatory factor analysis indicated that the bifactor model had a better fit than competing single and three-factor models. The MHC-SF total score was more strongly associated with other wellbeing and mental ill-health measures than the social, emotional or psychological subscale scores. Findings indicate that the mental wellbeing of young people is best conceptualized as an overarching latent construct (general wellbeing) to which emotional, social and psychological domains contribute. The MHC-SF total score is a valid and reliable measure of this general wellbeing factor. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Arthritis and the Risk of Falling Into Poverty: A Survival Analysis Using Australian Data.

PubMed

Callander, Emily J; Schofield, Deborah J

2016-01-01

Low income is known to be associated with having arthritis. However, no longitudinal studies have documented the relationship between developing arthritis and falling into poverty. The purpose of this study was to evaluate Australians who developed arthritis to determine if they had an elevated risk of falling into poverty. Survival analysis using Cox regression models was applied to nationally representative, longitudinal survey data obtained between January 1, 2007 and December 31, 2012 from Australian adults who were ages 21 years and older in 2007. The hazard ratio for falling into income poverty was 1.08 (95% confidence interval [95% CI] 1.06-1.09) in women who were diagnosed as having arthritis and 1.15 (95% CI 1.13-1.16) in men who were diagnosed as having arthritis, as compared to those who were never diagnosed as having arthritis. The hazard ratio for falling into multidimensional poverty was 1.15 (95% CI 1.14-1.17) in women who were diagnosed as having arthritis and 1.88 (95% CI 1.85-1.91) in men who were diagnosed as having arthritis. Developing arthritis increases the risk of falling into income poverty and multidimensional poverty. The risk of multidimensional poverty is greater than the risk of income poverty. Given the high prevalence of arthritis, the condition is likely an overlooked driver of poverty. © 2016, American College of Rheumatology.

The nature of self-esteem and its relationship to anxiety and depression in adult acquired brain injury.

PubMed

Longworth, Catherine; Deakins, Joseph; Rose, David; Gracey, Fergus

2016-08-31

Acquired brain injury (ABI) has a negative impact on self-esteem, which is in turn associated with mood disorders, maladaptive coping and reduced community participation. The aim of the current research was to explore self-esteem as a multi-dimensional construct and identify which factors are associated with symptoms of anxiety or depression. Eighty adults with ABI aged 17-56 years completed the Robson Self-Esteem Scale (RSES), of whom 65 also completed the Hospital Anxiety and Depression Scale; 57.5% of the sample had clinically low self-esteem. The RSES had good internal consistency (α =   .89), and factor analysis identified four factors, which differed from those found previously in other populations. Multiple regression analysis revealed anxiety was differentially predicted by "Self-Worth" and "Self-Efficacy", R 2  =   .44, F(4, 58) =   9, p <   .001, and depression by "Self-Regard", R 2  =   .38, F(4, 58) =   9, p <   .001. A fourth factor, "Confidence", did not predict depression or anxiety. In conclusion, the RSES is a reliable measure of self-esteem after ABI. Self-esteem after ABI is multidimensional and differs in structure from self-esteem in the general population. A multidimensional model of self-esteem may be helpful in development of transdiagnostic cognitive behavioural accounts of adjustment.

Multidimensional effects in nonadiabatic statistical theories of spin- forbidden kinetics. A case study of 3O + CO → CO 2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jasper, Ahren

2015-04-14

The appropriateness of treating crossing seams of electronic states of different spins as nonadiabatic transition states in statistical calculations of spin-forbidden reaction rates is considered. We show that the spin-forbidden reaction coordinate, the nuclear coordinate perpendicular to the crossing seam, is coupled to the remaining nuclear degrees of freedom. We found that this coupling gives rise to multidimensional effects that are not typically included in statistical treatments of spin-forbidden kinetics. Three qualitative categories of multidimensional effects may be identified: static multidimensional effects due to the geometry-dependence of the local shape of the crossing seam and of the spin–orbit coupling, dynamicalmore » multidimensional effects due to energy exchange with the reaction coordinate during the seam crossing, and nonlocal(history-dependent) multidimensional effects due to interference of the electronic variables at second, third, and later seam crossings. Nonlocal multidimensional effects are intimately related to electronic decoherence, where electronic dephasing acts to erase the history of the system. A semiclassical model based on short-time full-dimensional trajectories that includes all three multidimensional effects as well as a model for electronic decoherence is presented. The results of this multidimensional nonadiabatic statistical theory (MNST) for the 3O + CO → CO 2 reaction are compared with the results of statistical theories employing one-dimensional (Landau–Zener and weak coupling) models for the transition probability and with those calculated previously using multistate trajectories. The MNST method is shown to accurately reproduce the multistate decay-of-mixing trajectory results, so long as consistent thresholds are used. Furthermore, the MNST approach has several advantages over multistate trajectory approaches and is more suitable in chemical kinetics calculations at low temperatures and for complex systems. The error in statistical calculations that neglect multidimensional effects is shown to be as large as a factor of 2 for this system, with static multidimensional effects identified as the largest source of error.« less

Students' proficiency scores within multitrait item response theory

NASA Astrophysics Data System (ADS)

Scott, Terry F.; Schumayer, Daniel

2015-12-01

In this paper we present a series of item response models of data collected using the Force Concept Inventory. The Force Concept Inventory (FCI) was designed to poll the Newtonian conception of force viewed as a multidimensional concept, that is, as a complex of distinguishable conceptual dimensions. Several previous studies have developed single-trait item response models of FCI data; however, we feel that multidimensional models are also appropriate given the explicitly multidimensional design of the inventory. The models employed in the research reported here vary in both the number of fitting parameters and the number of underlying latent traits assumed. We calculate several model information statistics to ensure adequate model fit and to determine which of the models provides the optimal balance of information and parsimony. Our analysis indicates that all item response models tested, from the single-trait Rasch model through to a model with ten latent traits, satisfy the standard requirements of fit. However, analysis of model information criteria indicates that the five-trait model is optimal. We note that an earlier factor analysis of the same FCI data also led to a five-factor model. Furthermore the factors in our previous study and the traits identified in the current work match each other well. The optimal five-trait model assigns proficiency scores to all respondents for each of the five traits. We construct a correlation matrix between the proficiencies in each of these traits. This correlation matrix shows strong correlations between some proficiencies, and strong anticorrelations between others. We present an interpretation of this correlation matrix.

Multidimensional Single-Cell Analysis of BCR Signaling Reveals Proximal Activation Defect As a Hallmark of Chronic Lymphocytic Leukemia B Cells

PubMed Central

Palomba, M. Lia; Piersanti, Kelly; Ziegler, Carly G. K.; Decker, Hugo; Cotari, Jesse W.; Bantilan, Kurt; Rijo, Ivelise; Gardner, Jeff R.; Heaney, Mark; Bemis, Debra; Balderas, Robert; Malek, Sami N.; Seymour, Erlene; Zelenetz, Andrew D.

2014-01-01

Purpose Chronic Lymphocytic Leukemia (CLL) is defined by a perturbed B-cell receptor-mediated signaling machinery. We aimed to model differential signaling behavior between B cells from CLL and healthy individuals to pinpoint modes of dysregulation. Experimental Design We developed an experimental methodology combining immunophenotyping, multiplexed phosphospecific flow cytometry, and multifactorial statistical modeling. Utilizing patterns of signaling network covariance, we modeled BCR signaling in 67 CLL patients using Partial Least Squares Regression (PLSR). Results from multidimensional modeling were validated using an independent test cohort of 38 patients. Results We identified a dynamic and variable imbalance between proximal (pSYK, pBTK) and distal (pPLCγ2, pBLNK, ppERK) phosphoresponses. PLSR identified the relationship between upstream tyrosine kinase SYK and its target, PLCγ2, as maximally predictive and sufficient to distinguish CLL from healthy samples, pointing to this juncture in the signaling pathway as a hallmark of CLL B cells. Specific BCR pathway signaling signatures that correlate with the disease and its degree of aggressiveness were identified. Heterogeneity in the PLSR response variable within the B cell population is both a characteristic mark of healthy samples and predictive of disease aggressiveness. Conclusion Single-cell multidimensional analysis of BCR signaling permitted focused analysis of the variability and heterogeneity of signaling behavior from patient-to-patient, and from cell-to-cell. Disruption of the pSYK/pPLCγ2 relationship is uncovered as a robust hallmark of CLL B cell signaling behavior. Together, these observations implicate novel elements of the BCR signal transduction as potential therapeutic targets. PMID:24489640

Nursing care systematization as a multidimensional and interactive phenomenon.

PubMed

Backes, Dirce Stein; Koerich, Magda Santos; Nascimento, Keyla Cristiane do; Erdmann, Alacoque Lorenzini

2008-01-01

This study aimed to understand the meaning of Nursing Care Systematization (NCS) for multiprofessional health team professionals based on the relationships, interactions and associations of Complex thought. This qualitative study uses Grounded Theory as a methodological reference framework. Data were obtained through interviews with three sample groups, totaling 15 professionals from different institutions. Simultaneous data codification and analysis identified the central theme: 'Glimpsing nursing care systematization as an interactive and multidimensional phenomenon' and the respective reference model. NCS appoints, in addition to interactivity and professional complementarity, the importance of dialog and connection between the academy, health practices and regulatory offices, based on new reference frameworks for the organization of health practices.

Development and empirical validation of symmetric component measures of multidimensional constructs: customer and competitor orientation.

PubMed

Sørensen, Hans Eibe; Slater, Stanley F

2008-08-01

Atheoretical measure purification may lead to construct deficient measures. The purpose of this paper is to provide a theoretically driven procedure for the development and empirical validation of symmetric component measures of multidimensional constructs. Particular emphasis is placed on establishing a formalized three-step procedure for achieving a posteriori content validity. Then the procedure is applied to development and empirical validation of two symmetrical component measures of market orientation, customer orientation and competitor orientation. Analysis suggests that average variance extracted is particularly critical to reliability in the respecification of multi-indicator measures. In relation to this, the results also identify possible deficiencies in using Cronbach alpha for establishing reliable and valid measures.

Task Design for Students' Work with Basic Theory in Analysis: The Cases of Multidimensional Differentiability and Curve Integrals

ERIC Educational Resources Information Center

Gravesen, Katrine Frovin; Grønbaek, Niels; Winsløw, Carl

2017-01-01

We investigate the challenges students face in the transition from calculus courses, focusing on methods related to the analysis of real valued functions given in closed form, to more advanced courses on analysis where focus is on theoretical structure, including proof. We do so based on task design aiming for a number of generic potentials for…

Network structure of multivariate time series.

PubMed

Lacasa, Lucas; Nicosia, Vincenzo; Latora, Vito

2015-10-21

Our understanding of a variety of phenomena in physics, biology and economics crucially depends on the analysis of multivariate time series. While a wide range tools and techniques for time series analysis already exist, the increasing availability of massive data structures calls for new approaches for multidimensional signal processing. We present here a non-parametric method to analyse multivariate time series, based on the mapping of a multidimensional time series into a multilayer network, which allows to extract information on a high dimensional dynamical system through the analysis of the structure of the associated multiplex network. The method is simple to implement, general, scalable, does not require ad hoc phase space partitioning, and is thus suitable for the analysis of large, heterogeneous and non-stationary time series. We show that simple structural descriptors of the associated multiplex networks allow to extract and quantify nontrivial properties of coupled chaotic maps, including the transition between different dynamical phases and the onset of various types of synchronization. As a concrete example we then study financial time series, showing that a multiplex network analysis can efficiently discriminate crises from periods of financial stability, where standard methods based on time-series symbolization often fail.

A Review of Multidimensional, Multifluid Intermediate-scale Experiments: Flow Behavior, Saturation Imaging, and Tracer Detection and Quantification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oostrom, Mart; Dane, J. H.; Wietsma, Thomas W.

2007-08-01

A review is presented of original multidimensional, intermediate-scale experiments involving non-aqueous phase liquid (NAPL) flow behavior, imaging, and detection/quantification with solute tracers. In a companion paper (Oostrom, M., J.H. Dane, and T.W. Wietsma. 2006. A review of multidimensional, multifluid intermediate-scale experiments: Nonaqueous phase dissolution and enhanced remediation. Vadose Zone Journal 5:570-598) experiments related to aqueous dissolution and enhanced remediation were discussed. The experiments investigating flow behavior include infiltration and redistribution experiments with both light and dense NAPLs in homogeneous and heterogeneous porous medium systems. The techniques used for NAPL saturation mapping for intermediate-scale experiments include photon-attenuation methods such as gammamore » and X-ray techniques, and photographic methods such as the light reflection, light transmission, and multispectral image analysis techniques. Solute tracer methods used for detection and quantification of NAPL in the subsurface are primarily limited to variations of techniques comparing the behavior of conservative and partitioning tracers. Besides a discussion of the experimental efforts, recommendations for future research at this laboratory scale are provided.« less

The relationships of coping, negative thinking, life satisfaction, social support, and selected demographics with anxiety of young adult college students.

PubMed

Mahmoud, Jihan S R; Staten, Ruth Topsy; Lennie, Terry A; Hall, Lynne A

2015-05-01

Understanding young adults' anxiety requires applying a multidimensional approach to assess the psychosocial, behavioral, and cognitive aspects of this phenomenon. A hypothesized model of the relationships among coping style, thinking style, life satisfaction, social support, and selected demographics and anxiety among college students was tested using path analysis. A total of 257 undergraduate students aged 18-24 years completed an online survey. The independent variables were measured using the Multidimensional Scale of Perceived Social Support, the Brief Students' Multidimensional Life Satisfaction Scale, the Brief COPE Inventory, the Positive Automatic Thoughts Questionnaire, and the Cognition Checklist-Anxiety. The outcome, anxiety, was measured using the Anxiety subscale of the 21-item Depression Anxiety and Stress Scale. Only negative thinking and maladaptive coping had a direct relationship with anxiety. Negative thinking was the strongest predictor of both maladaptive coping and anxiety. These findings suggest that helping undergraduates manage their anxiety by reducing their negative thinking is critical. Designing and testing interventions to decrease negative thinking in college students is recommended for future research. © 2015 Wiley Periodicals, Inc.

Multidimensional assessment of awareness in early-stage dementia: a cluster analytic approach.

PubMed

Clare, Linda; Whitaker, Christopher J; Nelis, Sharon M; Martyr, Anthony; Markova, Ivana S; Roth, Ilona; Woods, Robert T; Morris, Robin G

2011-01-01

Research on awareness in dementia has yielded variable and inconsistent associations between awareness and other factors. This study examined awareness using a multidimensional approach and applied cluster analytic techniques to identify associations between the level of awareness and other variables. Participants were 101 individuals with early-stage dementia (PwD) and their carers. Explicit awareness was assessed at 3 levels: performance monitoring in relation to memory, evaluative judgement in relation to memory, everyday activities and socio-emotional functioning, and metacognitive reflection in relation to the experience and impact of the condition. Implicit awareness was assessed with an emotional Stroop task. Different measures of explicit awareness scores were related only to a limited extent. Cluster analysis yielded 3 groups with differing degrees of explicit awareness. These groups showed no differences in implicit awareness. Lower explicit awareness was associated with greater age, lower MMSE scores, poorer recall and naming scores, lower anxiety and greater carer stress. Multidimensional assessment offers a more robust approach to classifying PwD according to level of awareness and hence to examining correlates and predictors of awareness. Copyright © 2011 S. Karger AG, Basel.

The Four Faces of Competition: The Development of the Multidimensional Competitive Orientation Inventory

PubMed Central

Orosz, Gábor; Tóth-Király, István; Büki, Noémi; Ivaskevics, Krisztián; Bőthe, Beáta; Fülöp, Márta

2018-01-01

To date, no short scale exists with established factor structure that can assess individual differences in competition. The aim of the present study was to uncover and operationalize the facets of competitive orientations with theoretical underpinning and strong psychometric properties. A total of 2676 respondents were recruited for four studies. The items were constructed based on qualitative research in different cultural contexts. A combined method of exploratory structural equation modeling (ESEM) and confirmatory factor analysis (CFA) was employed. ESEM resulted in a four-factor structure of the competitive orientations and this structure was supported by a series of CFAs on different comprehensive samples. The Multidimensional Competitive Orientation Inventory (MCOI) included 12 items and four factors: hypercompetitive orientation, self-developmental competitive orientation, anxiety-driven competition avoidance, and lack of interest toward competition. Strong gender invariance was established. The four facets of competition have differentiated relationship patterns with adaptive and maladaptive personality and motivational constructs. The MCOI can assess the adaptive and maladaptive facets of competitive orientations with a short, reliable, valid and theoretically underlined multidimensional measure. PMID:29872415

HEAVY AND THERMAL OIL RECOVERY PRODUCTION MECHANISMS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anthony R. Kovscek

2003-04-01

This technical progress report describes work performed from January 1 through March 31, 2003 for the project ''Heavy and Thermal Oil Recovery Production Mechanisms,'' DE-FC26-00BC15311. In this project, a broad spectrum of research is undertaken related to thermal and heavy-oil recovery. The research tools and techniques span from pore-level imaging of multiphase fluid flow to definition of reservoir-scale features through streamline-based history matching techniques. During this period, previous analysis of experimental data regarding multidimensional imbibition to obtain shape factors appropriate for dual-porosity simulation was verified by comparison among analytic, dual-porosity simulation, and fine-grid simulation. We continued to study the mechanismsmore » by which oil is produced from fractured porous media at high pressure and high temperature. Temperature has a beneficial effect on recovery and reduces residual oil saturation. A new experiment was conducted on diatomite core. Significantly, we show that elevated temperature induces fines release in sandstone cores and this behavior may be linked to wettability. Our work in the area of primary production of heavy oil continues with field cores and crude oil. On the topic of reservoir definition, work continued on developing techniques that integrate production history into reservoir models using streamline-based properties.« less

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.

Single-cell codetection of metabolic activity, intracellular functional proteins, and genetic mutations from rare circulating tumor cells.

PubMed

Zhang, Yu; Tang, Yin; Sun, Shuai; Wang, Zhihua; Wu, Wenjun; Zhao, Xiaodong; Czajkowsky, Daniel M; Li, Yan; Tian, Jianhui; Xu, Ling; Wei, Wei; Deng, Yuliang; Shi, Qihui

2015-10-06

The high glucose uptake and activation of oncogenic signaling pathways in cancer cells has long made these features, together with the mutational spectrum, prime diagnostic targets of circulating tumor cells (CTCs). Further, an ability to characterize these properties at a single cell resolution is widely believed to be essential, as the known extensive heterogeneity in CTCs can obscure important correlations in data obtained from cell population-based methods. However, to date, it has not been possible to quantitatively measure metabolic, proteomic, and genetic data from a single CTC. Here we report a microchip-based approach that allows for the codetection of glucose uptake, intracellular functional proteins, and genetic mutations at the single-cell level from rare tumor cells. The microchip contains thousands of nanoliter grooves (nanowells) that isolate individual CTCs and allow for the assessment of their glucose uptake via imaging of a fluorescent glucose analog, quantification of a panel of intracellular signaling proteins using a miniaturized antibody barcode microarray, and retrieval of the individual cell nuclei for subsequent off-chip genome amplification and sequencing. This approach integrates molecular-scale information on the metabolic, proteomic, and genetic status of single cells and permits the inference of associations between genetic signatures, energy consumption, and phosphoproteins oncogenic signaling activities in CTCs isolated from blood samples of patients. Importantly, this microchip chip-based approach achieves this multidimensional molecular analysis with minimal cell loss (<20%), which is the bottleneck of the rare cell analysis.

Multidimensional Scaling in the Poincare Disk

DTIC Science & Technology

2011-05-01

REPORT Multidimensional Scaling in the Poincare Dis 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: Multidimensional scaling (MDS) is a class of projective...DATES COVERED (From - To) Standard Form 298 (Rev 8/98) Prescribed by ANSI Std. Z39.18 - Multidimensional Scaling in the Poincare Dis Report Title... plane . Our construction is based on an approximate hyperbolic line search and exempli?es some of the particulars that need to be addressed when

Item Parameter Estimation for the MIRT Model: Bias and Precision of Confirmatory Factor Analysis-Based Models

ERIC Educational Resources Information Center

Finch, Holmes

2010-01-01

The accuracy of item parameter estimates in the multidimensional item response theory (MIRT) model context is one that has not been researched in great detail. This study examines the ability of two confirmatory factor analysis models specifically for dichotomous data to properly estimate item parameters using common formulae for converting factor…

Changes among Israeli Youth Movements: A Structural Analysis Based on Kahane's Code of Informality

ERIC Educational Resources Information Center

Cohen, Erik H.

2015-01-01

Multi-dimensional data analysis tools are applied to Reuven Kahane's data on the informality of youth organizations, yielding a graphic portrayal of Kahane's code of informality. This structure helps address questions of the whether the eight structural components exhaustively cover the field without redundancy. Further, the structure is used to…

Confirmatory Factor Analysis of Persian Adaptation of Multidimensional Students' Life Satisfaction Scale (MSLSS)

ERIC Educational Resources Information Center

Hatami, Gissou; Motamed, Niloofar; Ashrafzadeh, Mahshid

2010-01-01

Validity and reliability of Persian adaptation of MSLSS in the 12-18 years, middle and high school students (430 students in grades 6-12 in Bushehr port, Iran) using confirmatory factor analysis by means of LISREL statistical package were checked. Internal consistency reliability estimates (Cronbach's coefficient [alpha]) were all above the…

A Spreadsheet for a 2 x 3 x 2 Log-Linear Analysis. AIR 1991 Annual Forum Paper.

ERIC Educational Resources Information Center

Saupe, Joe L.

This paper describes a personal computer spreadsheet set up to carry out hierarchical log-linear analyses, a type of analysis useful for institutional research into multidimensional frequency tables formed from categorical variables such as faculty rank, student class level, gender, or retention status. The spreadsheet provides a concrete vehicle…

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.

Models of multidimensional discrete distribution of probabilities of random variables in information systems

NASA Astrophysics Data System (ADS)

Gromov, Yu Yu; Minin, Yu V.; Ivanova, O. G.; Morozova, O. N.

2018-03-01

Multidimensional discrete distributions of probabilities of independent random values were received. Their one-dimensional distribution is widely used in probability theory. Producing functions of those multidimensional distributions were also received.

A New Time-varying Concept of Risk in a Changing Climate.

PubMed

Sarhadi, Ali; Ausín, María Concepción; Wiper, Michael P

2016-10-20

In a changing climate arising from anthropogenic global warming, the nature of extreme climatic events is changing over time. Existing analytical stationary-based risk methods, however, assume multi-dimensional extreme climate phenomena will not significantly vary over time. To strengthen the reliability of infrastructure designs and the management of water systems in the changing environment, multidimensional stationary risk studies should be replaced with a new adaptive perspective. The results of a comparison indicate that current multi-dimensional stationary risk frameworks are no longer applicable to projecting the changing behaviour of multi-dimensional extreme climate processes. Using static stationary-based multivariate risk methods may lead to undesirable consequences in designing water system infrastructures. The static stationary concept should be replaced with a flexible multi-dimensional time-varying risk framework. The present study introduces a new multi-dimensional time-varying risk concept to be incorporated in updating infrastructure design strategies under changing environments arising from human-induced climate change. The proposed generalized time-varying risk concept can be applied for all stochastic multi-dimensional systems that are under the influence of changing environments.

How children with specific language impairment view social situations: an eye tracking study.

PubMed

Hosozawa, Mariko; Tanaka, Kyoko; Shimizu, Toshiaki; Nakano, Tamami; Kitazawa, Shigeru

2012-06-01

Children with specific language impairment (SLI) face risks for social difficulties. However, the nature and developmental course of these difficulties remain unclear. Gaze behaviors have been studied by using eye tracking among those with autism spectrum disorders (ASDs). Using this method, we compared the gaze behaviors of children with SLI with those of individuals with ASD and typically developing (TD) children to explore the social perception of children with SLI. The eye gazes of 66 children (16 with SLI, 25 with ASD, and 25 TD) were studied while viewing videos of social interactions. Gaze behaviors were summarized with multidimensional scaling, and participants with similar gaze behaviors were represented proximally in a 2-dimensional plane. The SLI and TD groups each formed a cluster near the center of the multidimensional scaling plane, whereas the ASD group was distributed around the periphery. Frame-by-frame analyses showed that children with SLI and TD children viewed faces in a manner consistent with the story line, but children with ASD devoted less attention to faces and social interactions. During speech scenes, children with SLI were significantly more fixated on the mouth, whereas TD children viewed the eyes and the mouth. Children with SLI viewed social situations in ways similar to those of TD children but different from those of children with ASD. However, children with SLI concentrated on the speaker's mouth, possibly to compensate for audiovisual processing deficits. Because eyes carry important information, this difference may influence the social development of children with SLI.

Multidimensional Knowledge Structures.

ERIC Educational Resources Information Center

Schuh, Kathy L.

Multidimensional knowledge structures, described from a constructivist perspective and aligned with the "Mind as Rhizome" metaphor, provide support for constructivist learning strategies. This qualitative study was conducted to seek empirical support for a description of multidimensional knowledge structures, focusing on the…

Multidimensional quantum entanglement with large-scale integrated optics.

PubMed

Wang, Jianwei; Paesani, Stefano; Ding, Yunhong; Santagati, Raffaele; Skrzypczyk, Paul; Salavrakos, Alexia; Tura, Jordi; Augusiak, Remigiusz; Mančinska, Laura; Bacco, Davide; Bonneau, Damien; Silverstone, Joshua W; Gong, Qihuang; Acín, Antonio; Rottwitt, Karsten; Oxenløwe, Leif K; O'Brien, Jeremy L; Laing, Anthony; Thompson, Mark G

2018-04-20

The ability to control multidimensional quantum systems is central to the development of advanced quantum technologies. We demonstrate a multidimensional integrated quantum photonic platform able to generate, control, and analyze high-dimensional entanglement. A programmable bipartite entangled system is realized with dimensions up to 15 × 15 on a large-scale silicon photonics quantum circuit. The device integrates more than 550 photonic components on a single chip, including 16 identical photon-pair sources. We verify the high precision, generality, and controllability of our multidimensional technology, and further exploit these abilities to demonstrate previously unexplored quantum applications, such as quantum randomness expansion and self-testing on multidimensional states. Our work provides an experimental platform for the development of multidimensional quantum technologies. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Impact of the International Nosocomial Infection Control Consortium (INICC) Multidimensional Hand Hygiene Approach in five intensive care units in three cities of China.

PubMed

Su, D; Hu, B; Rosenthal, V D; Li, R; Hao, C; Pan, W; Tao, L; Gao, X; Liu, K

2015-07-01

To evaluate the impact of the International Nosocomial Infection Control Consortium (INICC) Multidimensional Hand Hygiene (HH) Approach in three hospitals in three cities of China, and analyze predictors of poor hand hygiene compliance. A prospective before-after study from May 2009 to December 2010 in five intensive care units members of the INICC in China. The study was divided into two periods: a 3-month baseline period and a follow-up period. A Multidimensional HH Approach was implemented, which included the following elements: 1- administrative support, 2- supplies availability, 3- education and training, 4- reminders in the workplace, 5- process surveillance and 6- performance feedback. Observations were done for HH compliance in each ICU, during randomly selected 30-min periods. A total of 2079 opportunities for HH were recorded. Overall HH compliance increased from 51.5% to 80.1% (95% CI 73.2-87.8; P = 0.004). Multivariate analysis indicated that several variables were significantly associated with poor HH compliance: females vs males (64% vs 55%; 95% CI 0.81-0.94; P = 0.0005), nurses vs physicians (64% vs 57%, P = 0.004), among others. Adherence to HH was increased significantly with the INICC multidimensional approach. Specific programs directed to improve HH in variables found to be predictors of poor HH compliance should be implemented. Copyright © 2015 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Reciprocal Effects of Self-Concept and Performance From a Multidimensional Perspective: Beyond Seductive Pleasure and Unidimensional Perspectives.

PubMed

Marsh, Herbert W; Craven, Rhonda G

2006-06-01

We (Marsh & Craven, 1997) have claimed that academic self-concept and achievement are mutually reinforcing, each leading to gains in the other. Baumeister, Campbell, Krueger, and Vohs (2003) have claimed that self-esteem has no benefits beyond seductive pleasure and may even be detrimental to subsequent performance. Integrating these seemingly contradictory conclusions, we distinguish between (a) older, unidimensional perspectives that focus on global self-esteem and underpin the Baumeister et al. review and (b) more recent, multidimensional perspectives that focus on specific components of self-concept and are the basis of our claim. Supporting the construct validity of a multidimensional perspective, studies show that academic achievement is substantially related to academic self-concept, but nearly unrelated to self-esteem. Consistent with this distinction, research based on our reciprocal-effects model (REM) and a recent meta-analysis show that prior academic self-concept (as opposed to self-esteem) and achievement both have positive effects on subsequent self-concept and achievement. We provide an overview of new support for the generality of the REM for young children, cross-cultural research in non-Western countries, health (physical activity), and nonelite (gymnastics) and elite (international swimming championships) sport. We conclude that future reviews elucidating the significant implications of self-concept for theory, policy, and practice need to account for current research supporting the REM and a multidimensional perspective of self-concept. © 2006 Association for Psychological Science.

Categorization and Characterization of American Driving Conditions (Phase I)

DOT National Transportation Integrated Search

1978-11-01

The objectives of the study were: (1) to develop a multidimensional matrix as an analysis framework to classify travel of personal motor vehicles according to fuel consumption, (2) to identify and assess available information on travel and fuel consu...

Rapid acquisition of data dense solid-state CPMG NMR spectral sets using multi-dimensional statistical analysis

DOE PAGES

Mason, H. E.; Uribe, E. C.; Shusterman, J. A.

2018-01-01

Tensor-rank decomposition methods have been applied to variable contact time 29 Si{ 1 H} CP/CPMG NMR data sets to extract NMR dynamics information and dramatically decrease conventional NMR acquisition times.

Multi-Dimensional Signal Processing Research Program

DTIC Science & Technology

1981-09-30

applications to real-time image processing and analysis. A specific long-range application is the automated processing of aerial reconnaissance imagery...Non-supervised image segmentation is a potentially im- portant operation in the automated processing of aerial reconnaissance pho- tographs since it

Replication of Structure Findings regarding the Interpersonal Reactivity Index.

ERIC Educational Resources Information Center

Carey, John C.; And Others

1988-01-01

Attempted to verify multidimensional nature and item composition of Interpersonal Reactivity Index (IRI) subscales through factor analysis. IRI responses from 365 female clinical dieticians and dietetic interns supported contention that IRI subscales measure four discernibly different empathy dimensions. (NB)

Rapid acquisition of data dense solid-state CPMG NMR spectral sets using multi-dimensional statistical analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mason, H. E.; Uribe, E. C.; Shusterman, J. A.

Tensor-rank decomposition methods have been applied to variable contact time 29 Si{ 1 H} CP/CPMG NMR data sets to extract NMR dynamics information and dramatically decrease conventional NMR acquisition times.

Experimental Aspects of Polarization Optimized Experiments (POE) for Magic Angle Spinning Solid-State NMR of Microcrystalline and Membrane-Bound Proteins.

PubMed

Gopinath, T; Veglia, Gianluigi

2018-01-01

Conventional NMR pulse sequences record one spectrum per experiment, while spending most of the time waiting for the spin system to return to the equilibrium. As a result, a full set of multidimensional NMR experiments for biological macromolecules may take up to several months to complete. Here, we present a practical guide for setting up a new class of MAS solid-state NMR experiments (POE or polarization optimized experiments) that enable the simultaneous acquisition of multiple spectra of proteins, accelerating data acquisition. POE exploit the long-lived 15 N polarization of isotopically labeled proteins and enable one to obtain up to eight spectra, by concatenating classical NMR pulse sequences. This new strategy propels data throughput of solid-state NMR spectroscopy of fibers, microcrystalline preparations, as well as membrane proteins.

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…

Chemical space visualization: transforming multidimensional chemical spaces into similarity-based molecular networks.

PubMed

de la Vega de León, Antonio; Bajorath, Jürgen

2016-09-01

The concept of chemical space is of fundamental relevance for medicinal chemistry and chemical informatics. Multidimensional chemical space representations are coordinate-based. Chemical space networks (CSNs) have been introduced as a coordinate-free representation. A computational approach is presented for the transformation of multidimensional chemical space into CSNs. The design of transformation CSNs (TRANS-CSNs) is based upon a similarity function that directly reflects distance relationships in original multidimensional space. TRANS-CSNs provide an immediate visualization of coordinate-based chemical space and do not require the use of dimensionality reduction techniques. At low network density, TRANS-CSNs are readily interpretable and make it possible to evaluate structure-activity relationship information originating from multidimensional chemical space.

Injection Locking Techniques for Spectrum Analysis

NASA Astrophysics Data System (ADS)

Gathma, Timothy D.; Buckwalter, James F.

2011-04-01

Wideband spectrum analysis supports future communication systems that reconfigure and adapt to the capacity of the spectral environment. While test equipment manufacturers offer wideband spectrum analyzers with excellent sensitivity and resolution, these spectrum analyzers typically cannot offer acceptable size, weight, and power (SWAP). CMOS integrated circuits offer the potential to fully integrate spectrum analysis capability with analog front-end circuitry and digital signal processing on a single chip. Unfortunately, CMOS lacks high-Q passives and wideband resonator tunability that is necessary for heterodyne implementations of spectrum analyzers. As an alternative to the heterodyne receiver architectures, two nonlinear methods for performing wideband, low-power spectrum analysis are presented. The first method involves injecting the spectrum of interest into an array of injection-locked oscillators. The second method employs the closed loop dynamics of both injection locking and phase locking to independently estimate the injected frequency and power.

Multidimensional poverty and catastrophic health spending in the mountainous regions of Myanmar, Nepal and India.

PubMed

Mohanty, Sanjay K; Agrawal, Nand Kishor; Mahapatra, Bidhubhusan; Choudhury, Dhrupad; Tuladhar, Sabarnee; Holmgren, E Valdemar

2017-01-18

Economic burden to households due to out-of-pocket expenditure (OOPE) is large in many Asian countries. Though studies suggest increasing household poverty due to high OOPE in developing countries, studies on association of multidimensional poverty and household health spending is limited. This paper tests the hypothesis that the multidimensionally poor are more likely to incur catastrophic health spending cutting across countries. Data from the Poverty and Vulnerability Assessment (PVA) Survey carried out by the International Center for Integrated Mountain Development (ICIMOD) has been used in the analyses. The PVA survey was a comprehensive household survey that covered the mountainous regions of India, Nepal and Myanmar. A total of 2647 households from India, 2310 households in Nepal and 4290 households in Myanmar covered under the PVA survey. Poverty is measured in a multidimensional framework by including the dimensions of education, income and energy, water and sanitation using the Alkire and Foster method. Health shock is measured using the frequency of illness, family sickness and death of any family member in a reference period of one year. Catastrophic health expenditure is defined as 40% above the household's capacity to pay. Results suggest that about three-fifths of the population in Myanmar, two-fifths of the population in Nepal and one-third of the population in India are multidimensionally poor. About 47% of the multidimensionally poor in India had incurred catastrophic health spending compared to 35% of the multidimensionally non-poor and the pattern was similar in both Nepal and Myanmar. The odds of incurring catastrophic health spending was 56% more among the multidimensionally poor than among the multidimensionally non-poor [95% CI: 1.35-1.76]. While health shocks to households are consistently significant predictors of catastrophic health spending cutting across country of residence, the educational attainment of the head of the household is not significant. The multidimensionally poor in the poorer regions are more likely to face health shocks and are less likely to afford professional health services. Increasing government spending on health and increasing households' access to health insurance can reduce catastrophic health spending and multidimensional poverty.

The positive mental health instrument: development and validation of a culturally relevant scale in a multi-ethnic Asian population.

PubMed

Vaingankar, Janhavi Ajit; Subramaniam, Mythily; Chong, Siow Ann; Abdin, Edimansyah; Orlando Edelen, Maria; Picco, Louisa; Lim, Yee Wei; Phua, Mei Yen; Chua, Boon Yiang; Tee, Joseph Y S; Sherbourne, Cathy

2011-10-31

Instruments to measure mental health and well-being are largely developed and often used within Western populations and this compromises their validity in other cultures. A previous qualitative study in Singapore demonstrated the relevance of spiritual and religious practices to mental health, a dimension currently not included in exiting multi-dimensional measures. The objective of this study was to develop a self-administered measure that covers all key and culturally appropriate domains of mental health, which can be applied to compare levels of mental health across different age, gender and ethnic groups. We present the item reduction and validation of the Positive Mental Health (PMH) instrument in a community-based adult sample in Singapore. Surveys were conducted among adult (21-65 years) residents belonging to Chinese, Malay and Indian ethnicities. Exploratory and confirmatory factor analysis (EFA, CFA) were conducted and items were reduced using item response theory tests (IRT). The final version of the PMH instrument was tested for internal consistency and criterion validity. Items were tested for differential item functioning (DIF) to check if items functioned in the same way across all subgroups. EFA and CFA identified six first-order factor structure (General coping, Personal growth and autonomy, Spirituality, Interpersonal skills, Emotional support, and Global affect) under one higher-order dimension of Positive Mental Health (RMSEA=0.05, CFI=0.96, TLI=0.96). A 47-item self-administered multi-dimensional instrument with a six-point Likert response scale was constructed. The slope estimates and strength of the relation to the theta for all items in each six PMH subscales were high (range:1.39 to 5.69), suggesting good discrimination properties. The threshold estimates for the instrument ranged from -3.45 to 1.61 indicating that the instrument covers entire spectrums for the six dimensions. The instrument demonstrated high internal consistency and had significant and expected correlations with other well-being measures. Results confirmed absence of DIF. The PMH instrument is a reliable and valid instrument that can be used to measure and compare level of mental health across different age, gender and ethnic groups in Singapore.

[Lack of insight in schizophrenia: a review].

PubMed

Raffard, S; Bayard, S; Capdevielle, D; Garcia, F; Boulenger, J-P; Gely-Nargeot, M-C

2008-10-01

Relative to other psychiatric disorders, patients with schizophrenia are often unaware of the consequences of their disease and their need for treatment. These deficits in awareness referred in general in the English literature as "poor insight", have been the focus of many clinical studies over recent years. This phenomenon, which is considered as fundamental in clinical evaluations of schizophrenia, should be understood as a multidimensional process rather than a dichotomic phenomenon, as is presently the case. The links between insight deficits and responses to vocational rehabilitation efforts represent a major interest in research, including those related to medication compliance and clinical outcome. To conduct such studies, various evaluation tools have been developed, enabling the assessment of insight, of its time-course and of its components in psychosis and schizophrenia spectrum disorders. The Scale to Assess Unawareness of illness in Mental Disorders (SUMD) developed by Amador and Strauss appears to be the most frequently used scale for the evaluation of awareness of the disorder in schizophrenia. Although the model proposed by Amador and Strauss is considered as the privileged model in the multidimensional approach of insight, it corresponds only to a phenomenological analysis of this concept. In the second part of this article, we thus review the current models attempting to explain the lack of insight in schizophrenia. Four current explanatory models of lack of insight will be described as follows: resulting either from adaptation or defence mechanisms to environmental stressors, resulting from cognitive bias of data processing, resulting from neuropsychological functional deficits and resulting from metacognitive deficits. Several hypotheses concerning these deficits arise from clinical studies. Although coping, and defence mechanisms to the consequences and stigmatization of the disease were hardly studied, the fact that poor insight does not appear related to the severity of symptomatology or to the emotional state of the patients argue against this hypothesis. Conversely, a considerable body of literature emphasized how unawareness may result from cognitive deficits. Research in neuropsychology and cognitive psychology has provided consistent results concerning the link between deficit in executive functions, frontal lobe dysfunction and poor insight. Recent studies on bias in cognitive information treatment and social cognition theories currently open new prospects.

Citation Patterns of Engineering, Statistics, and Computer Science Researchers: An Internal and External Citation Analysis across Multiple Engineering Subfields

ERIC Educational Resources Information Center

Kelly, Madeline

2015-01-01

This study takes a multidimensional approach to citation analysis, examining citations in multiple subfields of engineering, from both scholarly journals and doctoral dissertations. The three major goals of the study are to determine whether there are differences between citations drawn from dissertations and those drawn from journal articles; to…

A Technique of Two-Stage Clustering Applied to Environmental and Civil Engineering and Related Methods of Citation Analysis.

ERIC Educational Resources Information Center

Miyamoto, S.; Nakayama, K.

1983-01-01

A method of two-stage clustering of literature based on citation frequency is applied to 5,065 articles from 57 journals in environmental and civil engineering. Results of related methods of citation analysis (hierarchical graph, clustering of journals, multidimensional scaling) applied to same set of articles are compared. Ten references are…

The method of trend analysis of parameters time series of gas-turbine engine state

NASA Astrophysics Data System (ADS)

Hvozdeva, I.; Myrhorod, V.; Derenh, Y.

2017-10-01

This research substantiates an approach to interval estimation of time series trend component. The well-known methods of spectral and trend analysis are used for multidimensional data arrays. The interval estimation of trend component is proposed for the time series whose autocorrelation matrix possesses a prevailing eigenvalue. The properties of time series autocorrelation matrix are identified.

Multidimensional System Analysis of Electro-Optic Sensors with Sampled Deterministic Output.

DTIC Science & Technology

1987-12-18

System descriptions of scanning and staring electro - optic sensors with sampled output are developed as follows. Functions representing image...to complete the system descriptions. The results should be useful for designing electro - optic sensor systems and correcting data for instrumental...effects and other experimental conditions. Keywords include: Electro - optic system analysis, Scanning sensors, Staring sensors, Spatial sampling, and Temporal sampling.

Has the Bologna Process Been Worthwhile? An Analysis of the Learning Society-Adapted Outcome Index through Quantile Regression

ERIC Educational Resources Information Center

Fernandez-Sainz, A.; García-Merino, J. D.; Urionabarrenetxea, S.

2016-01-01

This paper seeks to discover whether the performance of university students has improved in the wake of the changes in higher education introduced by the Bologna Declaration of 1999 and the construction of the European Higher Education Area. A principal component analysis is used to construct a multi-dimensional performance variable called the…

Confirmatory Factor Analysis of the "World Health Organization Quality of Life Questionnaire--Brief Version" for Individuals with Spinal Cord Injury

ERIC Educational Resources Information Center

Miller, Susan M.; Chan, Fong; Ferrin, James M.; Lin, Chen-Ping; Chan, Jacob Y. C.

2008-01-01

This study examined the factorial structure of the "World Health Organization Quality of Life Questionnaire--Brief Version" in a community sample of Canadians with spinal cord injuries. A confirmatory factor analysis provides evidence that the instrument is a multidimensional measure of quality of life. Additionally, the questionnaire is…

Creating Indices from the Control Structure Interview Through Data Collapsing and Multidimensional Scaling: Approaches to Data Analysis in Project MITT.

ERIC Educational Resources Information Center

Jovick, Thomas D.

This paper discribes the analysis of data in the Management Implications of Team Teaching Project (MITT). It touches on the interviews conducted with teachers and principals, presents the breadth of information obtained in the questionnaire, and explains how the data were aggregated and how issues were grouped. Information collected in the…

A General Program for Item-Response Analysis That Employs the Stabilized Newton-Raphson Algorithm. Research Report. ETS RR-13-32

ERIC Educational Resources Information Center

Haberman, Shelby J.

2013-01-01

A general program for item-response analysis is described that uses the stabilized Newton-Raphson algorithm. This program is written to be compliant with Fortran 2003 standards and is sufficiently general to handle independent variables, multidimensional ability parameters, and matrix sampling. The ability variables may be either polytomous or…

Enabling Efficient Intelligence Analysis in Degraded Environments

DTIC Science & Technology

2013-06-01

Magnets Grid widget for multidimensional information exploration ; and a record browser of Visual Summary Cards widget for fast visual identification of...evolution analysis; a Magnets Grid widget for multi- dimensional information exploration ; and a record browser of Visual Summary Cards widget for fast...attention and inattentional blindness. It also explores and develops various techniques to represent information in a salient way and provide efficient

Dimensions of Nutrition Knowledge among Preadolescent Girls.

ERIC Educational Resources Information Center

Moxley, Robert L.; Wimberley, Ronald C.

1982-01-01

Examines the underlying dimensionality of a nutrition knowledge test for preadolescent girls. In contrast to the manner in which nutrition knowledge has previously been measured in research, analysis of the results indicates that their nutrition knowledge is multidimensional. The dimensions include "differentiated eating" and…

Multidimensional Analysis of High-School Students' Perceptions about Biotechnology

ERIC Educational Resources Information Center

Fonseca, Maria Joao; Costa, Patricio; Lencastre, Leonor; Tavares, Fernando

2012-01-01

Concerns about public understanding of biotechnology have motivated educational initiatives to improve students' competency to make scientifically sustained decisions regarding controversial issues. Understanding students' perceptions about biotechnology is essential to determine the effectiveness of these programmes. To assess how students'…

An introduction to multidimensional measurement using Rasch models.

PubMed

Briggs, Derek C; Wilson, Mark

2003-01-01

The act of constructing a measure requires a number of important assumptions. Principle among these assumptions is that the construct is unidimensional. In practice there are many instances when the assumption of unidimensionality does not hold, and where the application of a multidimensional measurement model is both technically appropriate and substantively advantageous. In this paper we illustrate the usefulness of a multidimensional approach to measurement with the Multidimensional Random Coefficient Multinomial Logit (MRCML) model, an extension of the unidimensional Rasch model. An empirical example is taken from a collection of embedded assessments administered to 541 students enrolled in middle school science classes with a hands-on science curriculum. Student achievement on these assessments are multidimensional in nature, but can also be treated as consecutive unidimensional estimates, or as is most common, as a composite unidimensional estimate. Structural parameters are estimated for each model using ConQuest, and model fit is compared. Student achievement in science is also compared across models. The multidimensional approach has the best fit to the data, and provides more reliable estimates of student achievement than under the consecutive unidimensional approach. Finally, at an interpretational level, the multidimensional approach may well provide richer information to the classroom teacher about the nature of student achievement.

A multidimensional platform for the purification of non-coding RNA species

PubMed Central

Chionh, Yok Hian; Ho, Chia-Hua; Pruksakorn, Dumnoensun; Ramesh Babu, I.; Ng, Chee Sheng; Hia, Fabian; McBee, Megan E.; Su, Dan; Pang, Yan Ling Joy; Gu, Chen; Dong, Hongping; Prestwich, Erin G.; Shi, Pei-Yong; Preiser, Peter Rainer; Alonso, Sylvie; Dedon, Peter C.

2013-01-01

A renewed interest in non-coding RNA (ncRNA) has led to the discovery of novel RNA species and post-transcriptional ribonucleoside modifications, and an emerging appreciation for the role of ncRNA in RNA epigenetics. Although much can be learned by amplification-based analysis of ncRNA sequence and quantity, there is a significant need for direct analysis of RNA, which has led to numerous methods for purification of specific ncRNA molecules. However, no single method allows purification of the full range of cellular ncRNA species. To this end, we developed a multidimensional chromatographic platform to resolve, isolate and quantify all canonical ncRNAs in a single sample of cells or tissue, as well as novel ncRNA species. The applicability of the platform is demonstrated in analyses of ncRNA from bacteria, human cells and plasmodium-infected reticulocytes, as well as a viral RNA genome. Among the many potential applications of this platform are a system-level analysis of the dozens of modified ribonucleosides in ncRNA, characterization of novel long ncRNA species, enhanced detection of rare transcript variants and analysis of viral genomes. PMID:23907385

Evaluation of Two Crew Module Boilerplate Tests Using Newly Developed Calibration Metrics

NASA Technical Reports Server (NTRS)

Horta, Lucas G.; Reaves, Mercedes C.

2012-01-01

The paper discusses a application of multi-dimensional calibration metrics to evaluate pressure data from water drop tests of the Max Launch Abort System (MLAS) crew module boilerplate. Specifically, three metrics are discussed: 1) a metric to assess the probability of enveloping the measured data with the model, 2) a multi-dimensional orthogonality metric to assess model adequacy between test and analysis, and 3) a prediction error metric to conduct sensor placement to minimize pressure prediction errors. Data from similar (nearly repeated) capsule drop tests shows significant variability in the measured pressure responses. When compared to expected variability using model predictions, it is demonstrated that the measured variability cannot be explained by the model under the current uncertainty assumptions.

A Multidimensional Scaling Analysis of Students' Attitudes about Science Careers

NASA Astrophysics Data System (ADS)

Masnick, Amy M.; Stavros Valenti, S.; Cox, Brian D.; Osman, Christopher J.

2010-03-01

To encourage students to seek careers in Science, Technology, Engineering and Mathematics (STEM) fields, it is important to gauge students' implicit and explicit attitudes towards scientific professions. We asked high school and college students to rate the similarity of pairs of occupations, and then used multidimensional scaling (MDS) to create a spatial representation of occupational similarity. Other students confirmed the emergent MDS map by rating each of the occupations along several dimensions. We found that participants across age and sex considered scientific professions to be less creative and less people-oriented than other popular career choices. We conclude that students may be led away from STEM careers by common misperceptions that science is a difficult, uncreative, and socially isolating pursuit.

Multidimensional Separation of Natural Products Using Liquid Chromatography Coupled to Hadamard Transform Ion Mobility Mass Spectrometry

NASA Astrophysics Data System (ADS)

Liu, Wenjie; Zhang, Xing; Knochenmuss, Richard; Siems, William F.; Hill, Herbert H.

2016-05-01

A high performance liquid chromatograph (HPLC)was interfaced to an atmospheric drift tube ion mobility time of flight mass spectrometry. The power of multidimensional separation was demonstrated using chili pepper extracts. The ambient pressure drift tube ion mobility provided high resolving powers up to 166 for the HPLC eluent. With implementation of Hadamard transform (HT), the duty cycle for the ion mobility drift tube was increased from less than 1% to 50%, and the ion transmission efficiency was improved by over 200 times compared with pulsed mode, improving signal to noise ratio 10 times. HT ion mobility and TOF mass spectrometry provide an additional dimension of separation for complex samples without increasing the analysis time compared with conventional HPLC.

An Examination of the Multidimensionality of Situational Interest in Elementary School Physical Education

PubMed Central

Sun, Haichun; Chen, Ang; Ennis, Catherine; Martin, Robert; Shen, Bo

2015-01-01

It has been demonstrated that situational interest in physical activity may derive from five dimensional sources, Novelty, Optimal Challenge, Attention Demand, Exploration Intent, and Instant Enjoyment. The purpose of this study was to examine the multidimensional sources in elementary school physical education. The five dimensions were measured in 5,717 students in third, fourth, and fifth grades from a random sample of 30 elementary schools. Students’ responses were randomly divided into two samples for a two-step confirmatory factor analysis. The results confirmed that the five dimensions are primary sources of situational interest for elementary school physical education. The findings implied that situational interest should be taken into account as a necessary curricular component in elementary physical education. PMID:18431952

Bring NASA Scientific Data into GIS

NASA Astrophysics Data System (ADS)

Xu, H.

2016-12-01

NASA's Earth Observation System (EOS) and many other missions produce data of huge volume and near real time which drives the research and understanding of climate change. Geographic Information System (GIS) is a technology used for the management, visualization and analysis of spatial data. Since it's inception in the 1960s, GIS has been applied to many fields at the city, state, national, and world scales. People continue to use it today to analyze and visualize trends, patterns, and relationships from the massive datasets of scientific data. There is great interest in both the scientific and GIS communities in improving technologies that can bring scientific data into a GIS environment, where scientific research and analysis can be shared through the GIS platform to the public. Most NASA scientific data are delivered in the Hierarchical Data Format (HDF), a format is both flexible and powerful. However, this flexibility results in challenges when trying to develop supported GIS software - data stored with HDF formats lack a unified standard and convention among these products. The presentation introduces an information model that enables ArcGIS software to ingest NASA scientific data and create a multidimensional raster - univariate and multivariate hypercubes - for scientific visualization and analysis. We will present the framework how ArcGIS leverages the open source GDAL (Geospatial Data Abstract Library) to support its raster data access, discuss how we overcame the GDAL drivers limitations in handing scientific products that are stored with HDF4 and HDF5 formats and how we improve the way in modeling the multidimensionality with GDAL. In additional, we will talk about the direction of ArcGIS handling NASA products and demonstrate how the multidimensional information model can help scientists work with various data products such as MODIS, MOPPIT, SMAP as well as many data products in a GIS environment.

On the importance of variable soil depth and process representation in the modeling of shallow landslide initiation

NASA Astrophysics Data System (ADS)

Fatichi, S.; Burlando, P.; Anagnostopoulos, G.

2014-12-01

Sub-surface hydrology has a dominant role on the initiation of rainfall-induced landslides, since changes in the soil water potential affect soil shear strength and thus apparent cohesion. Especially on steep slopes and shallow soils, loss of shear strength can lead to failure even in unsaturated conditions. A process based model, HYDROlisthisis, characterized by high resolution in space and, time is developed to investigate the interactions between surface and subsurface hydrology and shallow landslide initiation. Specifically, 3D variably saturated flow conditions, including soil hydraulic hysteresis and preferential flow, are simulated for the subsurface flow, coupled with a surface runoff routine. Evapotranspiration and specific root water uptake are taken into account for continuous simulations of soil water content during storm and inter-storm periods. The geotechnical component of the model is based on a multidimensional limit equilibrium analysis, which takes into account the basic principles of unsaturated soil mechanics. The model is applied to a small catchment in Switzerland historically prone to rainfall-triggered landslides. A series of numerical simulations were carried out with various boundary conditions (soil depths) and using hydrological and geotechnical components of different complexity. Specifically, the sensitivity to the inclusion of preferential flow and soil hydraulic hysteresis was tested together with the replacement of the infinite slope assumption with a multi-dimensional limit equilibrium analysis. The effect of the different model components on model performance was assessed using accuracy statistics and Receiver Operating Characteristic (ROC) curve. The results show that boundary conditions play a crucial role in the model performance and that the introduced hydrological (preferential flow and soil hydraulic hysteresis) and geotechnical components (multidimensional limit equilibrium analysis) considerably improve predictive capabilities in the presented case study.

Comprehensive drought characteristics analysis based on a nonlinear multivariate drought index

NASA Astrophysics Data System (ADS)

Yang, Jie; Chang, Jianxia; Wang, Yimin; Li, Yunyun; Hu, Hui; Chen, Yutong; Huang, Qiang; Yao, Jun

2018-02-01

It is vital to identify drought events and to evaluate multivariate drought characteristics based on a composite drought index for better drought risk assessment and sustainable development of water resources. However, most composite drought indices are constructed by the linear combination, principal component analysis and entropy weight method assuming a linear relationship among different drought indices. In this study, the multidimensional copulas function was applied to construct a nonlinear multivariate drought index (NMDI) to solve the complicated and nonlinear relationship due to its dependence structure and flexibility. The NMDI was constructed by combining meteorological, hydrological, and agricultural variables (precipitation, runoff, and soil moisture) to better reflect the multivariate variables simultaneously. Based on the constructed NMDI and runs theory, drought events for a particular area regarding three drought characteristics: duration, peak, and severity were identified. Finally, multivariate drought risk was analyzed as a tool for providing reliable support in drought decision-making. The results indicate that: (1) multidimensional copulas can effectively solve the complicated and nonlinear relationship among multivariate variables; (2) compared with single and other composite drought indices, the NMDI is slightly more sensitive in capturing recorded drought events; and (3) drought risk shows a spatial variation; out of the five partitions studied, the Jing River Basin as well as the upstream and midstream of the Wei River Basin are characterized by a higher multivariate drought risk. In general, multidimensional copulas provides a reliable way to solve the nonlinear relationship when constructing a comprehensive drought index and evaluating multivariate drought characteristics.

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 upwind hydrodynamics on unstructured meshes using graphics processing units - I. Two-dimensional uniform meshes

NASA Astrophysics Data System (ADS)

Paardekooper, S.-J.

2017-08-01

We present a new method for numerical hydrodynamics which uses a multidimensional generalization of the Roe solver and operates on an unstructured triangular mesh. The main advantage over traditional methods based on Riemann solvers, which commonly use one-dimensional flux estimates as building blocks for a multidimensional integration, is its inherently multidimensional nature, and as a consequence its ability to recognize multidimensional stationary states that are not hydrostatic. A second novelty is the focus on graphics processing units (GPUs). By tailoring the algorithms specifically to GPUs, we are able to get speedups of 100-250 compared to a desktop machine. We compare the multidimensional upwind scheme to a traditional, dimensionally split implementation of the Roe solver on several test problems, and we find that the new method significantly outperforms the Roe solver in almost all cases. This comes with increased computational costs per time-step, which makes the new method approximately a factor of 2 slower than a dimensionally split scheme acting on a structured grid.

The Influence of Dimensionality on Estimation in the Partial Credit Model.

ERIC Educational Resources Information Center

De Ayala, R. J.

1995-01-01

The effect of multidimensionality on partial credit model parameter estimation was studied with noncompensatory and compensatory data. Analysis results, consisting of root mean square error bias, Pearson product-moment corrections, standardized root mean squared differences, standardized differences between means, and descriptive statistics…

Classification of Marital Relationships: An Empirical Approach.

ERIC Educational Resources Information Center

Snyder, Douglas K.; Smith, Gregory T.

1986-01-01

Derives an empirically based classification system of marital relationships, employing a multidimensional self-report measure of marital interaction. Spouses' profiles on the Marital Satisfaction Inventory for samples of clinic and nonclinic couples were subjected to cluster analysis, resulting in separate five-group typologies for husbands and…

Measuring Developmental Students' Mathematics Anxiety

ERIC Educational Resources Information Center

Ding, Yanqing

2016-01-01

This study conducted an item-level analysis of mathematics anxiety and examined the dimensionality of mathematics anxiety in a sample of developmental mathematics students (N = 162) by Multi-dimensional Random Coefficients Multinominal Logit Model (MRCMLM). The results indicate a moderately correlated factor structure of mathematics anxiety (r =…

Multi-Dimensional Analysis of Dynamic Human Information Interaction

ERIC Educational Resources Information Center

Park, Minsoo

2013-01-01

Introduction: This study aims to understand the interactions of perception, effort, emotion, time and performance during the performance of multiple information tasks using Web information technologies. Method: Twenty volunteers from a university participated in this study. Questionnaires were used to obtain general background information and…

SOCIAL STABILITY AND HIV RISK BEHAVIOR: EVALUATING THE ROLE OF ACCUMULATED VULNERABILITY

PubMed Central

German, Danielle; Latkin, Carl A.

2011-01-01

This study evaluated a cumulative and syndromic relationship among commonly co-occurring vulnerabilites (homelessness, incarceration, low-income, residential transition) in association with HIV-related risk behaviors among 635 low-income women in Baltimore. Analysis included descriptive statistics, logistic regression, latent class analysis and latent class regression. Both methods of assessing multidimensional instability showed significant associations with risk indicators. Risk of multiple partners, sex exchange, and drug use decreased significantly with each additional domain. Higher stability class membership (77%) was associated with decreased likelihood of multiple partners, exchange partners, recent drug use, and recent STI. Multidimensional social vulnerabilities were cumulatively and synergistically linked to HIV risk behavior. Independent instability measures may miss important contextual determinants of risk. Social stability offers a useful framework to understand the synergy of social vulnerabilities that shape sexual risk behavior. Social policies and programs aiming to enhance housing and overall social stability are likely to be beneficial for HIV prevention. PMID:21259043

Big Data and Deep data in scanning and electron microscopies: functionality from multidimensional data sets

DOE PAGES

Belianinov, Alex; Vasudevan, Rama K; Strelcov, Evgheni; ...

2015-05-13

The development of electron, and scanning probe microscopies in the second half of the twentieth century have produced spectacular images of internal structure and composition of matter with, at nanometer, molecular, and atomic resolution. Largely, this progress was enabled by computer-assisted methods of microscope operation, data acquisition and analysis. The progress in imaging technologies in the beginning of the twenty first century has opened the proverbial floodgates of high-veracity information on structure and functionality. High resolution imaging now allows information on atomic positions with picometer precision, allowing for quantitative measurements of individual bond length and angles. Functional imaging often leadsmore » to multidimensional data sets containing partial or full information on properties of interest, acquired as a function of multiple parameters (time, temperature, or other external stimuli). Here, we review several recent applications of the big and deep data analysis methods to visualize, compress, and translate this data into physically and chemically relevant information from imaging data.« less

Regaining a sense of agency and shared self-reliance: the experience of advanced disease cancer patients participating in a multidimensional exercise intervention while undergoing chemotherapy--analysis of patient diaries.

PubMed

Midtgaard, Julie; Stelter, Reinhard; Rørth, Mikael; Adamsen, Lis

2007-04-01

Evidence is emerging that exercise can reduce psychological distress in cancer patients undergoing treatment. The present study aimed to (qualitatively) explore the experiences of advanced disease cancer patients participating in a 6-week, 9-hours weekly, structured, group-based multidimensional exercise intervention while undergoing chemotherapy. Unstructured diaries from a purposive sample of three females and two males (28-52 years old) who participated in the program served as the database. Data were analyzed using a phenomenological, narrative method. The analysis yielded three themes: shifting position, self-surveillance, and negotiated strength. The intervention highlighted situations making it possible for the participants to negate psychological and physical constraints. The concept of structured exercise contains viable psychotherapeutic potentials by allowing the development of alternative bodily and mental realities complying with cancer patients' demands and abilities to regain autonomy and commitment to discover and adopt a sense of agency and shared self-reliance.

Confirmatory factor analysis and psychometric properties of the Spanish version of the Multidimensional Body-Self Relations Questionnaire-Appearance Scales.

PubMed

Roncero, María; Perpiñá, Conxa; Marco, Jose H; Sánchez-Reales, Sergio

2015-06-01

The Multidimensional Body-Self Relations Questionnaire (MBSRQ) is the most comprehensive instrument to assess body image. The MBSRQ-Appearance Scales (MBSRQ-AS) is a reduced version that has been validated in other languages. The main aim of the present study was to confirm the factor structure of the Spanish version of the MBSRQ-AS and analyze its psychometric properties in 1041 nonclinical individuals. Confirmatory factor analysis showed excellent goodness of fit indices for the five-factor structure (Appearance Evaluation, Appearance Orientation, Body Areas Satisfaction, Overweight Preoccupation, and Self-Classified Weight). Factors possessed adequate scale score reliability indices. Some of the factors showed significant associations with the Eating Attitudes Test. Significant differences were found between boys/men and girls/women, and among age groups. The Spanish version of the MBSRQ-AS is a valid instrument for use in nonclinical population settings in people from 15 to 46 years old. Copyright © 2015 Elsevier Ltd. All rights reserved.

An examination of the psychometric structure of the Multidimensional Pain Inventory in temporomandibular disorder patients: a confirmatory factor analysis

PubMed Central

Andreu, Yolanda; Galdon, Maria J; Durá, Estrella; Ferrando, Maite; Pascual, Juan; Turk, Dennis C; Jiménez, Yolanda; Poveda, Rafael

2006-01-01

Background This paper seeks to analyse the psychometric and structural properties of the Multidimensional Pain Inventory (MPI) in a sample of temporomandibular disorder patients. Methods The internal consistency of the scales was obtained. Confirmatory Factor Analysis was carried out to test the MPI structure section by section in a sample of 114 temporomandibular disorder patients. Results Nearly all scales obtained good reliability indexes. The original structure could not be totally confirmed. However, with a few adjustments we obtained a satisfactory structural model of the MPI which was slightly different from the original: certain items and the Self control scale were eliminated; in two cases, two original scales were grouped in one factor, Solicitous and Distracting responses on the one hand, and Social activities and Away from home activities, on the other. Conclusion The MPI has been demonstrated to be a reliable tool for the assessment of pain in temporomandibular disorder patients. Some divergences to be taken into account have been clarified. PMID:17169143

Big Data and Deep data in scanning and electron microscopies: functionality from multidimensional data sets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Belianinov, Alex; Vasudevan, Rama K; Strelcov, Evgheni

The development of electron, and scanning probe microscopies in the second half of the twentieth century have produced spectacular images of internal structure and composition of matter with, at nanometer, molecular, and atomic resolution. Largely, this progress was enabled by computer-assisted methods of microscope operation, data acquisition and analysis. The progress in imaging technologies in the beginning of the twenty first century has opened the proverbial floodgates of high-veracity information on structure and functionality. High resolution imaging now allows information on atomic positions with picometer precision, allowing for quantitative measurements of individual bond length and angles. Functional imaging often leadsmore » to multidimensional data sets containing partial or full information on properties of interest, acquired as a function of multiple parameters (time, temperature, or other external stimuli). Here, we review several recent applications of the big and deep data analysis methods to visualize, compress, and translate this data into physically and chemically relevant information from imaging data.« less

Gender roles, eating pathology, and body dissatisfaction in men: a meta-analysis.

PubMed

Blashill, Aaron J

2011-01-01

The current study reviewed relationships between gender roles and (a) eating pathology, (b) body dissatisfaction, and (c) muscle dissatisfaction among men via meta-analysis. Moderators of sexual orientation and type of gender role measure were also investigated. Results revealed the relationship between femininity and eating and body-related variables did not significantly differ from zero. Sexual orientation moderated the relationship between femininity and muscle dissatisfaction (i.e., femininity was negatively related to muscle dissatisfaction for heterosexual but not gay men). Masculinity was negatively associated with eating pathology and body dissatisfaction. Type of masculinity measure moderated the relationship between masculinity and body dissatisfaction (i.e., trait-based measures produced a negative association, multidimensional measures yielded nonsignificant relationships). Type of masculinity measure produced a cross-over interaction when examining muscle dissatisfaction (i.e., trait-based instruments yielded a negative association and multidimensional instruments revealed a positive relationship). Findings highlight the salience of masculinity in men's eating and body concerns. Copyright © 2010 Elsevier Ltd. All rights reserved.

Report order and identification of multidimensional stimuli: a study of event-related brain potentials.

PubMed

Shieh, Kong-King; Shen, I-Hsuan

2004-06-01

An experiment was conducted to investigate the effect of order of report on multidimensional stimulus identification. Subjects were required to identify each two-dimensional symbol by pushing corresponding buttons on the keypad on which there were two columns representing the two dimensions. Order of report was manipulated for the dimension represented by the left or right column. Both behavioral data and event-related potentials were recorded from 14 college students. Behavioral data analysis showed that order of report had a significant effect on response times. Such results were consistent with those of previous studies. Analysis of event-related brain potentials showed significant differences in peak amplitude and mean amplitude at time windows of 120-250 msec. at Fz, F3, and F4 and of 350-750 msec. at Fz, F3, F4, Cz, and Pz. Data provided neurophysiological evidence that reporting dimensional values according to natural language habits was appropriate and less cognitively demanding.

Enhancing Student Motivation and Engagement: The Effects of a Multidimensional Intervention

ERIC Educational Resources Information Center

Martin, Andrew J.

2008-01-01

The present study sought to investigate the effects of a multidimensional educational intervention on high school students' motivation and engagement. The intervention incorporated: (a) multidimensional targets of motivation and engagement, (b) empirically derived intervention methodology, (c) research-based risk and protective factors, (d)…

The use of the multi-cumulant tensor analysis for the algorithmic optimisation of investment portfolios

NASA Astrophysics Data System (ADS)

Domino, Krzysztof

2017-02-01

The cumulant analysis plays an important role in non Gaussian distributed data analysis. The shares' prices returns are good example of such data. The purpose of this research is to develop the cumulant based algorithm and use it to determine eigenvectors that represent investment portfolios with low variability. Such algorithm is based on the Alternating Least Square method and involves the simultaneous minimisation 2'nd- 6'th cumulants of the multidimensional random variable (percentage shares' returns of many companies). Then the algorithm was tested during the recent crash on the Warsaw Stock Exchange. To determine incoming crash and provide enter and exit signal for the investment strategy the Hurst exponent was calculated using the local DFA. It was shown that introduced algorithm is on average better that benchmark and other portfolio determination methods, but only within examination window determined by low values of the Hurst exponent. Remark that the algorithm is based on cumulant tensors up to the 6'th order calculated for a multidimensional random variable, what is the novel idea. It can be expected that the algorithm would be useful in the financial data analysis on the world wide scale as well as in the analysis of other types of non Gaussian distributed data.

Characterization of Atypical Off-Flavor Compounds in Natural Cork Stoppers by Multidimensional Gas Chromatographic Techniques.

PubMed

Slabizki, Petra; Fischer, Claus; Legrum, Charlotte; Schmarr, Hans-Georg

2015-09-09

Natural cork stoppers with sensory deviations other than the typical cork taint were subgrouped according to their sensory descriptions and compared with unaffected control cork stoppers. The assessment of purge and trap extracts obtained from corresponding cork soaks was performed by heart-cut multidimensional gas chromatography-olfactometry (MDGC-O). The identification of compounds responsible for atypical cork taint detected in MDGC-O was further supported with additional multidimensional GC analysis in combination with mass spectrometric detection. Geosmin and 2-methylisoborneol were mainly found in cork stoppers described as moldy and cellarlike; 3-isopropyl-2-methoxypyrazine and 3-isobutyl-2-methoxypyrazine were found in cork stoppers described with green attributes. Across all cork subgroups, the impact compound for typical cork taint, 2,4,6-trichloroanisole (TCA), was present and is therefore a good marker for cork taint in general. Another potent aroma compound, 3,5-dimethyl-2-methoxypyrazine (MDMP), was also detected in each subgroup, obviously playing an important role with regard to the atypical cork taint. Sensory deviations possibly affecting the wine could be generated by MDMP and its presence should thus be monitored in routine quality control.

NMRPipe: a multidimensional spectral processing system based on UNIX pipes.

PubMed

Delaglio, F; Grzesiek, S; Vuister, G W; Zhu, G; Pfeifer, J; Bax, A

1995-11-01

The NMRPipe system is a UNIX software environment of processing, graphics, and analysis tools designed to meet current routine and research-oriented multidimensional processing requirements, and to anticipate and accommodate future demands and developments. The system is based on UNIX pipes, which allow programs running simultaneously to exchange streams of data under user control. In an NMRPipe processing scheme, a stream of spectral data flows through a pipeline of processing programs, each of which performs one component of the overall scheme, such as Fourier transformation or linear prediction. Complete multidimensional processing schemes are constructed as simple UNIX shell scripts. The processing modules themselves maintain and exploit accurate records of data sizes, detection modes, and calibration information in all dimensions, so that schemes can be constructed without the need to explicitly define or anticipate data sizes or storage details of real and imaginary channels during processing. The asynchronous pipeline scheme provides other substantial advantages, including high flexibility, favorable processing speeds, choice of both all-in-memory and disk-bound processing, easy adaptation to different data formats, simpler software development and maintenance, and the ability to distribute processing tasks on multi-CPU computers and computer networks.

Utilizing Multidimensional Measures of Race in Education Research: The Case of Teacher Perceptions

PubMed Central

Irizarry, Yasmiyn

2015-01-01

Education scholarship on race using quantitative data analysis consists largely of studies on the black-white dichotomy, and more recently, on the experiences of student within conventional racial/ethnic categories (white, Hispanic/Latina/o, Asian, black). Despite substantial shifts in the racial and ethnic composition of American children, studies continue to overlook the diverse racialized experiences for students of Asian and Latina/o descent, the racialization of immigration status, and the educational experiences of Native American students. This study provides one possible strategy for developing multidimensional measures of race using large-scale datasets and demonstrates the utility of multidimensional measures for examining educational inequality, using teacher perceptions of student behavior as a case in point. With data from the first grade wave of the Early Childhood Longitudinal Study, Kindergarten Cohort of 1998–1999, I examine differences in teacher ratings of Externalizing Problem Behaviors and Approaches to Learning across fourteen racialized subgroups at the intersections of race, ethnicity, and immigrant status. Results show substantial subgroup variation in teacher perceptions of problem and learning behaviors, while also highlighting key points of divergence and convergence within conventional racial/ethnic categories. PMID:26413559

Psychometric properties of the Multidimensional Assessment of Fatigue scale in traumatic brain injury: an NIDRR Traumatic Brain Injury Model Systems study.

PubMed

Lequerica, Anthony; Bushnik, Tamara; Wright, Jerry; Kolakowsky-Hayner, Stephanie A; Hammond, Flora M; Dijkers, Marcel P; Cantor, Joshua

2012-01-01

To investigate the psychometric properties of the Multidimensional Assessment of Fatigue (MAF) scale in a traumatic brain injury (TBI) sample. Prospective survey study. Community. One hundred sixty-seven individuals with TBI admitted for inpatient rehabilitation, enrolled into the TBI Model Systems national database, and followed up at either the first or second year postinjury. Not applicable. Multidimensional Assessment of Fatigue. The initial analysis, using items 1 to 14, which are based on a 10-point rating scale, found that only 1 item ("walking") misfit the overall construct of fatigue in this TBI population. However, this 10-point rating scale was found to have disordered thresholds. When ratings were collapsed into 4 response categories, all MAF items used to calculate the Global Fatigue Index formed a unidimensional scale. Findings generally support the unidimensionality of the MAF when used in a TBI population but call into question the use of a 10-point rating scale for items 1 to 14. Further study is needed to investigate the use of a 4-category rating scale across all items and the fit of the "walking" item for a measure of fatigue among individuals with TBI.

Plasma-assisted quadruple-channel optosensing of proteins and cells with Mn-doped ZnS quantum dots.

PubMed

Li, Chenghui; Wu, Peng; Hou, Xiandeng

2016-02-21

Information extraction from nano-bio-systems is crucial for understanding their inner molecular level interactions and can help in the development of multidimensional/multimodal sensing devices to realize novel or expanded functionalities. The intrinsic fluorescence (IF) of proteins has long been considered as an effective tool for studying protein structures and dynamics, but not for protein recognition analysis partially because it generally contributes to the fluorescence background in bioanalysis. Here we explored the use of IF as the fourth channel optical input for a multidimensional optosensing device, together with the triple-channel optical output of Mn-doped ZnS QDs (fluorescence from ZnS host, phosphorescence from Mn(2+) dopant, and Rayleigh light scattering from the QDs), to dramatically improve the protein recognition and discrimination resolution. To further increase the cross-reactivity of the multidimensional optosensing device, plasma modification of proteins was explored to enhance the IF difference as well as their interactions with Mn-doped ZnS QDs. Such a sensor device was demonstrated for highly discriminative and precise identification of proteins in human serum and urine samples, and for cancer and normal cells as well.

Examining the relationships between resources and online health information seeking among patients with chronic diseases and healthy people.

PubMed

Oh, Young Sam; Cho, Youngmin

2015-01-01

The Internet is increasingly used as an important source of health and medical-related information for people with chronic diseases. It is recognized that online health information seeking (OHIS) is influenced by individuals' multi-dimensional factors, such as demographics, socio-economic factors, perceptions of the Internet, and health conditions. This study applies the conservation of resource theory to examine relationships between various multi-dimensional factors, daily challenges, and OHIS depending on individuals' health conditions. The data used in this study was taken from the U.S. Health Tracking Survey (2012). In this study, Internet users aged 18 and older were classified into patients (N = 518) and healthy people (N = 677) based on their health status related to chronic diseases. Multiple regression analysis was used to examine the relationships between multi-dimensional factors (resources), self-rated health, and OHIS. Patients' various resources (e.g., age, income, education, having a smartphone, and health tracking) significantly predicted their self-rated health and OHIS; in addition, self-rated health significantly mediated the relationships between focal resources and OHIS. However, the mediating effects of self-rated health were not found in healthy people.

Utilizing Multidimensional Measures of Race in Education Research: The Case of Teacher Perceptions.

PubMed

Irizarry, Yasmiyn

2015-10-01

Education scholarship on race using quantitative data analysis consists largely of studies on the black-white dichotomy, and more recently, on the experiences of student within conventional racial/ethnic categories (white, Hispanic/Latina/o, Asian, black). Despite substantial shifts in the racial and ethnic composition of American children, studies continue to overlook the diverse racialized experiences for students of Asian and Latina/o descent, the racialization of immigration status, and the educational experiences of Native American students. This study provides one possible strategy for developing multidimensional measures of race using large-scale datasets and demonstrates the utility of multidimensional measures for examining educational inequality, using teacher perceptions of student behavior as a case in point. With data from the first grade wave of the Early Childhood Longitudinal Study, Kindergarten Cohort of 1998-1999, I examine differences in teacher ratings of Externalizing Problem Behaviors and Approaches to Learning across fourteen racialized subgroups at the intersections of race, ethnicity, and immigrant status. Results show substantial subgroup variation in teacher perceptions of problem and learning behaviors, while also highlighting key points of divergence and convergence within conventional racial/ethnic categories.

[External and internal validity of a multidimensional Locus of control scale of eating attitudes for athletes (LOCSCAS)].

PubMed

Paquet, Y; Scoffier, S; d'Arripe-Longueville, F

2016-10-01

In the field of health psychology, the control has consistently been considered as a protective factor. This protective role has been also highlighted in eating attitudes' domain. However, current studies use the one-dimensional scale of Rotter or the multidimensional health locus of control scale, and no specific eating attitudes' scale in the sport context exists. Moreover, the social influence in previous scales is limited. According to recent works, the purpose of this study was to test the internal and external validity of a multidimensional locus of control scale of eating attitudes for athletes. One hundred and seventy-nine participants were solicited. A confirmatory factorial analysis was conducted in order to test the internal validity of the scale. The scale external validity was tested in relation to eating attitudes. The internal validity of the scale was verified as well as the external validity, which confirmed the importance of taking into consideration social influences. Indeed, the 2 subscales "Trainers, friends" and "Parents, family" are related respectively positively and negatively in eating disorders. Copyright © 2016 L'Encéphale, Paris. Published by Elsevier Masson SAS. All rights reserved.

Fast Fourier Transform Spectral Analysis Program

NASA Technical Reports Server (NTRS)

Daniel, J. A., Jr.; Graves, M. L.; Hovey, N. M.

1969-01-01

Fast Fourier Transform Spectral Analysis Program is used in frequency spectrum analysis of postflight, space vehicle telemetered trajectory data. This computer program with a digital algorithm can calculate power spectrum rms amplitudes and cross spectrum of sampled parameters at even time increments.

Toward a definition of blueprint of virgin olive oil by comprehensive two-dimensional gas chromatography.

PubMed

Purcaro, Giorgia; Cordero, Chiara; Liberto, Erica; Bicchi, Carlo; Conte, Lanfranco S

2014-03-21

This study investigates the applicability of an iterative approach aimed at defining a chemical blueprint of virgin olive oil volatiles to be correlated to the product sensory quality. The investigation strategy proposed allows to fully exploit the informative content of a comprehensive multidimensional gas chromatography (GC×GC) coupled to a mass spectrometry (MS) data set. Olive oil samples (19), including 5 reference standards, obtained from the International Olive Oil Council, and commercial samples, were submitted to a sensory evaluation by a Panel test, before being analyzed in two laboratories using different instrumentation, column set, and software elaboration packages in view of a cross-validation of the entire methodology. A first classification of samples based on untargeted peak features information, was obtained on raw data from two different column combinations (apolar×polar and polar×apolar) by applying unsupervised multivariate analysis (i.e., principal component analysis-PCA). However, to improve effectiveness and specificity of this classification, peak features were reliably identified (261 compounds), on the basis of the MS spectrum and linear retention index matching, and subjected to successive pair-wise comparisons based on 2D patterns, which revealed peculiar distribution of chemicals correlated with samples sensory classification. The most informative compounds were thus identified and collected in a "blueprint" of specific defects (or combination of defects) successively adopted to discriminate Extra Virgin from defected oils (i.e., lampante oil) with the aid of a supervised approach, i.e., partial least squares-discriminant analysis (PLS-DA). In this last step, the principles of sensomics, which assigns higher information potential to analytes with lower odor threshold proved to be successful, and a much more powerful discrimination of samples was obtained in view of a sensory quality assessment. Copyright © 2014 Elsevier B.V. All rights reserved.

Classification of arterial and venous cerebral vasculature based on wavelet postprocessing of CT perfusion data.

PubMed

Havla, Lukas; Schneider, Moritz J; Thierfelder, Kolja M; Beyer, Sebastian E; Ertl-Wagner, Birgit; Reiser, Maximilian F; Sommer, Wieland H; Dietrich, Olaf

2016-02-01

The purpose of this study was to propose and evaluate a new wavelet-based technique for classification of arterial and venous vessels using time-resolved cerebral CT perfusion data sets. Fourteen consecutive patients (mean age 73 yr, range 17-97) with suspected stroke but no pathology in follow-up MRI were included. A CT perfusion scan with 32 dynamic phases was performed during intravenous bolus contrast-agent application. After rigid-body motion correction, a Paul wavelet (order 1) was used to calculate voxelwise the wavelet power spectrum (WPS) of each attenuation-time course. The angiographic intensity A was defined as the maximum of the WPS, located at the coordinates T (time axis) and W (scale/width axis) within the WPS. Using these three parameters (A, T, W) separately as well as combined by (1) Fisher's linear discriminant analysis (FLDA), (2) logistic regression (LogR) analysis, or (3) support vector machine (SVM) analysis, their potential to classify 18 different arterial and venous vessel segments per subject was evaluated. The best vessel classification was obtained using all three parameters A and T and W [area under the curve (AUC): 0.953 with FLDA and 0.957 with LogR or SVM]. In direct comparison, the wavelet-derived parameters provided performance at least equal to conventional attenuation-time-course parameters. The maximum AUC obtained from the proposed wavelet parameters was slightly (although not statistically significantly) higher than the maximum AUC (0.945) obtained from the conventional parameters. A new method to classify arterial and venous cerebral vessels with high statistical accuracy was introduced based on the time-domain wavelet transform of dynamic CT perfusion data in combination with linear or nonlinear multidimensional classification techniques.

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…

Compressed Continuous Computation v. 12/20/2016

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gorodetsky, Alex

2017-02-17

A library for performing numerical computation with low-rank functions. The (C3) library enables performing continuous linear and multilinear algebra with multidimensional functions. Common tasks include taking "matrix" decompositions of vector- or matrix-valued functions, approximating multidimensional functions in low-rank format, adding or multiplying functions together, integrating multidimensional functions.

The Discriminating Power of Items that Measure More than One Dimension.

ERIC Educational Resources Information Center

Reckase, Mark D.

The work presented in this paper defined conceptually the concepts of multidimensional discrimination and information, derived mathematical expressions for the concepts for a particular multidimensional item response theory (IRT) model, and applied the concepts to actual test data. Multidimensional discrimination was defined as a function of the…

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…

Supervised and Unsupervised Learning of Multidimensional Acoustic Categories

ERIC Educational Resources Information Center

Goudbeek, Martijn; Swingley, Daniel; Smits, Roel

2009-01-01

Learning to recognize the contrasts of a language-specific phonemic repertoire can be viewed as forming categories in a multidimensional psychophysical space. Research on the learning of distributionally defined visual categories has shown that categories defined over 1 dimension are easy to learn and that learning multidimensional categories is…

Health, Wealth and Wisdom: Exploring Multidimensional Inequality in a Developing Country

ERIC Educational Resources Information Center

Nilsson, Therese

2010-01-01

Despite a broad theoretical literature on multidimensional inequality and a widespread belief that welfare is not synonymous to income--not the least in a developing context--empirical inequality examinations rarely includes several welfare attributes. We explore three techniques on how to evaluate multidimensional inequality using Zambian…

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 =…

Method of data mining including determining multidimensional coordinates of each item using a predetermined scalar similarity value for each item pair

DOEpatents

Meyers, Charles E.; Davidson, George S.; Johnson, David K.; Hendrickson, Bruce A.; Wylie, Brian N.

1999-01-01

A method of data mining represents related items in a multidimensional space. Distance between items in the multidimensional space corresponds to the extent of relationship between the items. The user can select portions of the space to perceive. The user also can interact with and control the communication of the space, focusing attention on aspects of the space of most interest. The multidimensional spatial representation allows more ready comprehension of the structure of the relationships among the items.

A review of snapshot multidimensional optical imaging: measuring photon tags in parallel

PubMed Central

Gao, Liang; Wang, Lihong V.

2015-01-01

Multidimensional optical imaging has seen remarkable growth in the past decade. Rather than measuring only the two-dimensional spatial distribution of light, as in conventional photography, multidimensional optical imaging captures light in up to nine dimensions, providing unprecedented information about incident photons’ spatial coordinates, emittance angles, wavelength, time, and polarization. Multidimensional optical imaging can be accomplished either by scanning or parallel acquisition. Compared with scanning-based imagers, parallel acquisition—also dubbed snapshot imaging—has a prominent advantage in maximizing optical throughput, particularly when measuring a datacube of high dimensions. Here, we first categorize snapshot multidimensional imagers based on their acquisition and image reconstruction strategies, then highlight the snapshot advantage in the context of optical throughput, and finally we discuss their state-of-the-art implementations and applications. PMID:27134340

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.

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.

The Impact of Time Perspective Latent Profiles on College Drinking: A Multidimensional Approach

PubMed Central

Braitman, Abby L.; Henson, James M.

2015-01-01

Background Zimbardo and Boyd’s1 time perspective, or the temporal framework individuals use to process information, has been shown to predict health behaviors such as alcohol use. Previous studies supported the predictive validity of individual dimensions of time perspective, with some dimensions acting as protective factors and others as risk factors. However, some studies produced findings contrary to the general body of literature. In addition, time perspective is a multidimensional construct, and the combination of perspectives may be more predictive than individual dimensions in isolation; consequently, multidimensional profiles are a more accurate measure of individual differences and more appropriate for predicting health behaviors. Objectives The current study identified naturally occurring profiles of time perspective and examined their association with risky alcohol use. Methods Data were collected from a college student sample (n = 431, mean age = 20.41 years) using an online survey. Time perspective profiles were identified using latent profile analysis. Results Bootstrapped regression models identified a protective class that engaged in significantly less overall drinking (β = −0.254) as well as engaging in significantly less episodic high risk drinking (β = −0.274). There was also emerging evidence of a high risk time perspective profile that was linked to more overall drinking (β = 0.198) and engaging in more high risk drinking (β = 0.245), though these differences were not significant. Conclusions/Importance These findings support examining time perspective in a multidimensional framework rather than individual dimensions in isolation. Implications include identifying students most in need of interventions, and tailoring interventions to target temporal framing in decision-making. PMID:25607806