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.

GENERAL: Scattering Phase Correction for Semiclassical Quantization Rules in Multi-Dimensional Quantum Systems

NASA Astrophysics Data System (ADS)

Huang, Wen-Min; Mou, Chung-Yu; Chang, Cheng-Hung

2010-02-01

While the scattering phase for several one-dimensional potentials can be exactly derived, less is known in multi-dimensional quantum systems. This work provides a method to extend the one-dimensional phase knowledge to multi-dimensional quantization rules. The extension is illustrated in the example of Bogomolny's transfer operator method applied in two quantum wells bounded by step potentials of different heights. This generalized semiclassical method accurately determines the energy spectrum of the systems, which indicates the substantial role of the proposed phase correction. Theoretically, the result can be extended to other semiclassical methods, such as Gutzwiller trace formula, dynamical zeta functions, and semiclassical Landauer-Büttiker formula. In practice, this recipe enhances the applicability of semiclassical methods to multi-dimensional quantum systems bounded by general soft potentials.

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.

Findings of the International Nosocomial Infection Control Consortium (INICC), Part I: Effectiveness of a multidimensional infection control approach on catheter-associated urinary tract infection rates in pediatric intensive care units of 6 developing countries.

PubMed

Rosenthal, Victor D; Ramachandran, Bala; Dueñas, Lourdes; Alvarez-Moreno, Carlos; Navoa-Ng, J A; Armas-Ruiz, Alberto; Ersoz, Gulden; Matta-Cortés, Lorena; Pawar, Mandakini; Nevzat-Yalcin, Ata; Rodríguez-Ferrer, Marena; Bran de Casares, Ana Concepción; Linares, Claudia; Villanueva, Victoria D; Campuzano, Roberto; Kaya, Ali; Rendon-Campo, Luis Fernando; Gupta, Amit; Turhan, Ozge; Barahona-Guzmán, Nayide; de Jesús-Machuca, Lilian; Tolentino, María Corazon V; Mena-Brito, Jorge; Kuyucu, Necdet; Astudillo, Yamileth; Saini, Narinder; Gunay, Nurgul; Sarmiento-Villa, Guillermo; Gumus, Eylul; Lagares-Guzmán, Alfredo; Dursun, Oguz

2012-07-01

A before-after prospective surveillance study to assess the impact of a multidimensional infection control approach for the reduction of catheter-associated urinary tract infection (CAUTI) rates. Pediatric intensive care units (PICUs) of hospital members of the International Nosocomial Infection Control Consortium (INICC) from 10 cities of the following 6 developing countries: Colombia, El Salvador, India, Mexico, Philippines, and Turkey. PICU inpatients. We performed a prospective active surveillance to determine rates of CAUTI among 3,877 patients hospitalized in 10 PICUs for a total of 27,345 bed-days. The study was divided into a baseline period (phase 1) and an intervention period (phase 2). In phase 1, surveillance was performed without the implementation of the multidimensional approach. In phase 2, we implemented a multidimensional infection control approach that included outcome surveillance, process surveillance, feedback on CAUTI rates, feedback on performance, education, and a bundle of preventive measures. The rates of CAUTI obtained in phase 1 were compared with the rates obtained in phase 2, after interventions were implemented. During the study period, we recorded 8,513 urinary catheter (UC) days, including 1,513 UC-days in phase 1 and 7,000 UC-days in phase 2. In phase 1, the CAUTI rate was 5.9 cases per 1,000 UC-days, and in phase 2, after implementing the multidimensional infection control approach for CAUTI prevention, the rate of CAUTI decreased to 2.6 cases per 1,000 UC-days (relative risk, 0.43 [95% confidence interval, 0.21-1.0]), indicating a rate reduction of 57%. Our findings demonstrated that implementing a multidimensional infection control approach is associated with a significant reduction in the CAUTI rate of PICUs in developing countries.

Kinetic solvers with adaptive mesh in phase space

NASA Astrophysics Data System (ADS)

Arslanbekov, Robert R.; Kolobov, Vladimir I.; Frolova, Anna A.

2013-12-01

An adaptive mesh in phase space (AMPS) methodology has been developed for solving multidimensional kinetic equations by the discrete velocity method. A Cartesian mesh for both configuration (r) and velocity (v) spaces is produced using a “tree of trees” (ToT) data structure. The r mesh is automatically generated around embedded boundaries, and is dynamically adapted to local solution properties. The v mesh is created on-the-fly in each r cell. Mappings between neighboring v-space trees is implemented for the advection operator in r space. We have developed algorithms for solving the full Boltzmann and linear Boltzmann equations with AMPS. Several recent innovations were used to calculate the discrete Boltzmann collision integral with dynamically adaptive v mesh: the importance sampling, multipoint projection, and variance reduction methods. We have developed an efficient algorithm for calculating the linear Boltzmann collision integral for elastic and inelastic collisions of hot light particles in a Lorentz gas. Our AMPS technique has been demonstrated for simulations of hypersonic rarefied gas flows, ion and electron kinetics in weakly ionized plasma, radiation and light-particle transport through thin films, and electron streaming in semiconductors. We have shown that AMPS allows minimizing the number of cells in phase space to reduce the computational cost and memory usage for solving challenging kinetic problems.

Kinetic solvers with adaptive mesh in phase space.

PubMed

Arslanbekov, Robert R; Kolobov, Vladimir I; Frolova, Anna A

2013-12-01

An adaptive mesh in phase space (AMPS) methodology has been developed for solving multidimensional kinetic equations by the discrete velocity method. A Cartesian mesh for both configuration (r) and velocity (v) spaces is produced using a "tree of trees" (ToT) data structure. The r mesh is automatically generated around embedded boundaries, and is dynamically adapted to local solution properties. The v mesh is created on-the-fly in each r cell. Mappings between neighboring v-space trees is implemented for the advection operator in r space. We have developed algorithms for solving the full Boltzmann and linear Boltzmann equations with AMPS. Several recent innovations were used to calculate the discrete Boltzmann collision integral with dynamically adaptive v mesh: the importance sampling, multipoint projection, and variance reduction methods. We have developed an efficient algorithm for calculating the linear Boltzmann collision integral for elastic and inelastic collisions of hot light particles in a Lorentz gas. Our AMPS technique has been demonstrated for simulations of hypersonic rarefied gas flows, ion and electron kinetics in weakly ionized plasma, radiation and light-particle transport through thin films, and electron streaming in semiconductors. We have shown that AMPS allows minimizing the number of cells in phase space to reduce the computational cost and memory usage for solving challenging kinetic problems.

Face-infringement space: the frame of reference of the ventral intraparietal area.

PubMed

McCollum, Gin; Klam, François; Graf, Werner

2012-07-01

Experimental studies have shown that responses of ventral intraparietal area (VIP) neurons specialize in head movements and the environment near the head. VIP neurons respond to visual, auditory, and tactile stimuli, smooth pursuit eye movements, and passive and active movements of the head. This study demonstrates mathematical structure on a higher organizational level created within VIP by the integration of a complete set of variables covering face-infringement. Rather than positing dynamics in an a priori defined coordinate system such as those of physical space, we assemble neuronal receptive fields to find out what space of variables VIP neurons together cover. Section 1 presents a view of neurons as multidimensional mathematical objects. Each VIP neuron occupies or is responsive to a region in a sensorimotor phase space, thus unifying variables relevant to the disparate sensory modalities and movements. Convergence on one neuron joins variables functionally, as space and time are joined in relativistic physics to form a unified spacetime. The space of position and motion together forms a neuronal phase space, bridging neurophysiology and the physics of face-infringement. After a brief review of the experimental literature, the neuronal phase space natural to VIP is sequentially characterized, based on experimental data. Responses of neurons indicate variables that may serve as axes of neural reference frames, and neuronal responses have been so used in this study. The space of sensory and movement variables covered by VIP receptive fields joins visual and auditory space to body-bound sensory modalities: somatosensation and the inertial senses. This joining of allocentric and egocentric modalities is in keeping with the known relationship of the parietal lobe to the sense of self in space and to hemineglect, in both humans and monkeys. Following this inductive step, variables are formalized in terms of the mathematics of graph theory to deduce which combinations are complete as a multidimensional neural structure that provides the organism with a complete set of options regarding objects impacting the face, such as acceptance, pursuit, and avoidance. We consider four basic variable types: position and motion of the face and of an external object. Formalizing the four types of variables allows us to generalize to any sensory system and to determine the necessary and sufficient conditions for a neural center (for example, a cortical region) to provide a face-infringement space. We demonstrate that VIP includes at least one such face-infringement space.

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

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.

Simulation of 2D Kinetic Effects in Plasmas using the Grid Based Continuum Code LOKI

NASA Astrophysics Data System (ADS)

Banks, Jeffrey; Berger, Richard; Chapman, Tom; Brunner, Stephan

2016-10-01

Kinetic simulation of multi-dimensional plasma waves through direct discretization of the Vlasov equation is a useful tool to study many physical interactions and is particularly attractive for situations where minimal fluctuation levels are desired, for instance, when measuring growth rates of plasma wave instabilities. However, direct discretization of phase space can be computationally expensive, and as a result there are few examples of published results using Vlasov codes in more than a single configuration space dimension. In an effort to fill this gap we have developed the Eulerian-based kinetic code LOKI that evolves the Vlasov-Poisson system in 2+2-dimensional phase space. The code is designed to reduce the cost of phase-space computation by using fully 4th order accurate conservative finite differencing, while retaining excellent parallel scalability that efficiently uses large scale computing resources. In this poster I will discuss the algorithms used in the code as well as some aspects of their parallel implementation using MPI. I will also overview simulation results of basic plasma wave instabilities relevant to laser plasma interaction, which have been obtained using the code.

Students' Personal Connection with Science: Investigating the Multidimensional Phenomenological Structure of Self-Relevance

ERIC Educational Resources Information Center

Hartwell, Matthew; Kaplan, Avi

2018-01-01

This paper presents findings from a two-phase mixed methods study investigating the phenomenological structure of self-relevance among ninth-grade junior high school biology students (Phase 1: N = 118; Phase 2: N = 139). We begin with a phenomenological multidimensional definition of self-relevance as comprising three dimensions: the academic…

Edgelist phase unwrapping algorithm for time series InSAR analysis.

PubMed

Shanker, A Piyush; Zebker, Howard

2010-03-01

We present here a new integer programming formulation for phase unwrapping of multidimensional data. Phase unwrapping is a key problem in many coherent imaging systems, including time series synthetic aperture radar interferometry (InSAR), with two spatial and one temporal data dimensions. The minimum cost flow (MCF) [IEEE Trans. Geosci. Remote Sens. 36, 813 (1998)] phase unwrapping algorithm describes a global cost minimization problem involving flow between phase residues computed over closed loops. Here we replace closed loops by reliable edges as the basic construct, thus leading to the name "edgelist." Our algorithm has several advantages over current methods-it simplifies the representation of multidimensional phase unwrapping, it incorporates data from external sources, such as GPS, where available to better constrain the unwrapped solution, and it treats regularly sampled or sparsely sampled data alike. It thus is particularly applicable to time series InSAR, where data are often irregularly spaced in time and individual interferograms can be corrupted with large decorrelated regions. We show that, similar to the MCF network problem, the edgelist formulation also exhibits total unimodularity, which enables us to solve the integer program problem by using efficient linear programming tools. We apply our method to a persistent scatterer-InSAR data set from the creeping section of the Central San Andreas Fault and find that the average creep rate of 22 mm/Yr is constant within 3 mm/Yr over 1992-2004 but varies systematically with ground location, with a slightly higher rate in 1992-1998 than in 1999-2003.

Beyond the continuum: a multi-dimensional phase space for neutral-niche community assembly.

PubMed

Latombe, Guillaume; Hui, Cang; McGeoch, Melodie A

2015-12-22

Neutral and niche processes are generally considered to interact in natural communities along a continuum, exhibiting community patterns bounded by pure neutral and pure niche processes. The continuum concept uses niche separation, an attribute of the community, to test the hypothesis that communities are bounded by pure niche or pure neutral conditions. It does not accommodate interactions via feedback between processes and the environment. By contrast, we introduce the Community Assembly Phase Space (CAPS), a multi-dimensional space that uses community processes (such as dispersal and niche selection) to define the limiting neutral and niche conditions and to test the continuum hypothesis. We compare the outputs of modelled communities in a heterogeneous landscape, assembled by pure neutral, pure niche and composite processes. Differences in patterns under different combinations of processes in CAPS reveal hidden complexity in neutral-niche community dynamics. The neutral-niche continuum only holds for strong dispersal limitation and niche separation. For weaker dispersal limitation and niche separation, neutral and niche processes amplify each other via feedback with the environment. This generates patterns that lie well beyond those predicted by a continuum. Inferences drawn from patterns about community assembly processes can therefore be misguided when based on the continuum perspective. CAPS also demonstrates the complementary information value of different patterns for inferring community processes and captures the complexity of community assembly. It provides a general tool for studying the processes structuring communities and can be applied to address a range of questions in community and metacommunity ecology. © 2015 The Author(s).

Beyond the continuum: a multi-dimensional phase space for neutral–niche community assembly

PubMed Central

Latombe, Guillaume; McGeoch, Melodie A.

2015-01-01

Neutral and niche processes are generally considered to interact in natural communities along a continuum, exhibiting community patterns bounded by pure neutral and pure niche processes. The continuum concept uses niche separation, an attribute of the community, to test the hypothesis that communities are bounded by pure niche or pure neutral conditions. It does not accommodate interactions via feedback between processes and the environment. By contrast, we introduce the Community Assembly Phase Space (CAPS), a multi-dimensional space that uses community processes (such as dispersal and niche selection) to define the limiting neutral and niche conditions and to test the continuum hypothesis. We compare the outputs of modelled communities in a heterogeneous landscape, assembled by pure neutral, pure niche and composite processes. Differences in patterns under different combinations of processes in CAPS reveal hidden complexity in neutral–niche community dynamics. The neutral–niche continuum only holds for strong dispersal limitation and niche separation. For weaker dispersal limitation and niche separation, neutral and niche processes amplify each other via feedback with the environment. This generates patterns that lie well beyond those predicted by a continuum. Inferences drawn from patterns about community assembly processes can therefore be misguided when based on the continuum perspective. CAPS also demonstrates the complementary information value of different patterns for inferring community processes and captures the complexity of community assembly. It provides a general tool for studying the processes structuring communities and can be applied to address a range of questions in community and metacommunity ecology. PMID:26702047

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.

Spherical Panoramas for Astrophysical Data Visualization

NASA Astrophysics Data System (ADS)

Kent, Brian R.

2017-05-01

Data immersion has advantages in astrophysical visualization. Complex multi-dimensional data and phase spaces can be explored in a seamless and interactive viewing environment. Putting the user in the data is a first step toward immersive data analysis. We present a technique for creating 360° spherical panoramas with astrophysical data. The three-dimensional software package Blender and the Google Spatial Media module are used together to immerse users in data exploration. Several examples employing these methods exhibit how the technique works using different types of astronomical data.

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…

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.

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.

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.

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 display controller for displaying to a user an aspect of a multidimensional space visible from a base viewing location along a desired viewing orientation

DOEpatents

Davidson, George S.; Anderson, Thomas G.

2001-01-01

A display controller allows a user to control a base viewing location, a base viewing orientation, and a relative viewing orientation. The base viewing orientation and relative viewing orientation are combined to determine a desired viewing orientation. An aspect of a multidimensional space visible from the base viewing location along the desired viewing orientation is displayed to the user. The user can change the base viewing location, base viewing orientation, and relative viewing orientation by changing the location or other properties of input objects.

Multidimensional kinetic simulations using dissipative closures and other reduced Vlasov methods for differing particle magnetizations

NASA Astrophysics Data System (ADS)

Newman, David L.

2006-10-01

Kinetic plasma simulations in which the phase-space distribution functions are advanced directly via the coupled Vlasov and Poisson (or Maxwell) equations---better known simply as Vlasov simulations---provide a valuable low-noise complement to the more commonly employed Particle-in-Cell (PIC) simulations. However, in more than one spatial dimension Vlasov simulations become numerically demanding due to the high dimensionality of x--v phase-space. Methods that can reduce this computational demand are therefore highly desirable. Several such methods will be presented, which treat the phase-space dynamics along a dominant dimension (e.g., parallel to a beam or current) with the full Vlasov propagator, while employing a reduced description, such as moment equations, for the evolution perpendicular to the dominant dimension. A key difference between the moment-based (and other reduced) methods considered here and standard fluid methods is that the moments are now functions of a phase-space coordinate (e.g. moments of vy in z--vz--y phase space, where z is the dominant dimension), rather than functions of spatial coordinates alone. Of course, moment-based methods require closure. For effectively unmagnetized species, new dissipative closure methods inspired by those of Hammett and Perkins [PRL, 64, 3019 (1990)] have been developed, which exactly reproduce the linear electrostatic response for a broad class of distributions with power-law tails, as are commonly measured in space plasmas. The nonlinear response, which requires more care, will also be discussed. For weakly magnetized species (i.e., φs<φs) an alternative algorithm has been developed in which the distributions are assumed to gyrate about the magnetic field with a fixed nominal perpendicular ``thermal'' velocity, thereby reducing the required phase-space dimension by one. These reduced algorithms have been incorporated into 2-D codes used to study the evolution of nonlinear structures such as double layers and electron holes in Earth's auroral zone.

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.

Assessing Construct Validity Using Multidimensional Item Response Theory.

ERIC Educational Resources Information Center

Ackerman, Terry A.

The concept of a user-specified validity sector is discussed. The idea of the validity sector combines the work of M. D. Reckase (1986) and R. Shealy and W. Stout (1991). Reckase developed a methodology to represent an item in a multidimensional latent space as a vector. Item vectors are computed using multidimensional item response theory item…

Impact of a multidimensional infection control approach on catheter-associated urinary tract infection rates in an adult intensive care unit in Lebanon: International Nosocomial Infection Control Consortium (INICC) findings.

PubMed

Kanj, Souha S; Zahreddine, Nada; Rosenthal, Victor Daniel; Alamuddin, Lamia; Kanafani, Zeina; Molaeb, Bassel

2013-09-01

The objective of this study was to assess the impact of a multidimensional infection control approach for the reduction of catheter-associated urinary tract infection (CAUTI) in an adult intensive care unit (ICU) of a hospital member of the International Nosocomial Infection Control Consortium (INICC) in Lebanon. A before-after prospective active surveillance study was carried out to determine rates of CAUTI in 1506 ICU patients, hospitalized during 10 291 bed-days. The study period was divided into two phases: phase 1 (baseline) and phase 2 (intervention). During phase 1, surveillance was performed applying the definitions of the US Centers for Disease Control and Prevention National Healthcare Safety Network (CDC/NHSN). In phase 2, we adopted a multidimensional approach that included: (1) a bundle of infection control interventions, (2) education, (3) surveillance of CAUTI rates, (4) feedback on CAUTI rates, (5) process surveillance, and (6) performance feedback. We used random effects Poisson regression to account for clustering of CAUTI rates across time-periods. We recorded a total of 9829 urinary catheter-days: 306 in phase 1 and 9523 in phase 2. The rate of CAUTI was 13.07 per 1000 urinary catheter-days in phase 1, and was decreased by 83% in phase 2 to 2.21 per 1000 urinary catheter-days (risk ratio 0.17; 95% confidence interval 0.06-0.5; p=0.0002). Our multidimensional approach was associated with a significant reduction in the CAUTI rate. Copyright © 2013. Published by Elsevier Ltd.

Evolutionary multidimensional access architecture featuring cost-reduced components

NASA Astrophysics Data System (ADS)

Farjady, Farsheed; Parker, Michael C.; Walker, Stuart D.

1998-12-01

We describe a three-stage wavelength-routed optical access network, utilizing coarse passband-flattened arrayed- waveguide grating routers. An N-dimensional addressing strategy enables 6912 customers to be bi-directionally addressed with multi-Gb/s data using only 24 wavelengths spaced by 1.6 nm. Coarse wavelength separation allows use of increased tolerance WDM components at the exchange and customer premises. The architecture is designed to map onto standard access network topologies, allowing elegant upgradability from legacy PON infrastructures at low cost. Passband-flattening of the routers is achieved through phase apodization.

Low-discrepancy sampling of parametric surface using adaptive space-filling curves (SFC)

NASA Astrophysics Data System (ADS)

Hsu, Charles; Szu, Harold

2014-05-01

Space-Filling Curves (SFCs) are encountered in different fields of engineering and computer science, especially where it is important to linearize multidimensional data for effective and robust interpretation of the information. Examples of multidimensional data are matrices, images, tables, computational grids, and Electroencephalography (EEG) sensor data resulting from the discretization of partial differential equations (PDEs). Data operations like matrix multiplications, load/store operations and updating and partitioning of data sets can be simplified when we choose an efficient way of going through the data. In many applications SFCs present just this optimal manner of mapping multidimensional data onto a one dimensional sequence. In this report, we begin with an example of a space-filling curve and demonstrate how it can be used to find the most similarity using Fast Fourier transform (FFT) through a set of points. Next we give a general introduction to space-filling curves and discuss properties of them. Finally, we consider a discrete version of space-filling curves and present experimental results on discrete space-filling curves optimized for special tasks.

Impact of a multidimensional infection control strategy on catheter-associated urinary tract infection rates in the adult intensive care units of 15 developing countries: findings of the International Nosocomial Infection Control Consortium (INICC).

PubMed

Rosenthal, V D; Todi, S K; Álvarez-Moreno, C; Pawar, M; Karlekar, A; Zeggwagh, A A; Mitrev, Z; Udwadia, F E; Navoa-Ng, J A; Chakravarthy, M; Salomao, R; Sahu, S; Dilek, A; Kanj, S S; Guanche-Garcell, H; Cuéllar, L E; Ersoz, G; Nevzat-Yalcin, A; Jaggi, N; Medeiros, E A; Ye, G; Akan, Ö A; Mapp, T; Castañeda-Sabogal, A; Matta-Cortés, L; Sirmatel, F; Olarte, N; Torres-Hernández, H; Barahona-Guzmán, N; Fernández-Hidalgo, R; Villamil-Gómez, W; Sztokhamer, D; Forciniti, S; Berba, R; Turgut, H; Bin, C; Yang, Y; Pérez-Serrato, I; Lastra, C E; Singh, S; Ozdemir, D; Ulusoy, S

2012-10-01

We aimed to evaluate the impact of a multidimensional infection control strategy for the reduction of the incidence of catheter-associated urinary tract infection (CAUTI) in patients hospitalized in adult intensive care units (AICUs) of hospitals which are members of the International Nosocomial Infection Control Consortium (INICC), from 40 cities of 15 developing countries: Argentina, Brazil, China, Colombia, Costa Rica, Cuba, India, Lebanon, Macedonia, Mexico, Morocco, Panama, Peru, Philippines, and Turkey. We conducted a prospective before-after surveillance study of CAUTI rates on 56,429 patients hospitalized in 57 AICUs, during 360,667 bed-days. The study was divided into the baseline period (Phase 1) and the intervention period (Phase 2). In Phase 1, active surveillance was performed. In Phase 2, we implemented a multidimensional infection control approach that included: (1) a bundle of preventive measures, (2) education, (3) outcome surveillance, (4) process surveillance, (5) feedback of CAUTI rates, and (6) feedback of performance. The rates of CAUTI obtained in Phase 1 were compared with the rates obtained in Phase 2, after interventions were implemented. We recorded 253,122 urinary catheter (UC)-days: 30,390 in Phase 1 and 222,732 in Phase 2. In Phase 1, before the intervention, the CAUTI rate was 7.86 per 1,000 UC-days, and in Phase 2, after intervention, the rate of CAUTI decreased to 4.95 per 1,000 UC-days [relative risk (RR) 0.63 (95% confidence interval [CI] 0.55-0.72)], showing a 37% rate reduction. Our study showed that the implementation of a multidimensional infection control strategy is associated with a significant reduction in the CAUTI rate in AICUs from developing countries.

Unidimensional Vertical Scaling in Multidimensional Space. Research Report. ETS RR-17-29

ERIC Educational Resources Information Center

Carlson, James E.

2017-01-01

In this paper, I consider a set of test items that are located in a multidimensional space, S[subscript M], but are located along a curved line in S[subscript M] and can be scaled unidimensionally. Furthermore, I am demonstrating a case in which the test items are administered across 6 levels, such as occurs in K-12 assessment across 6 grade…

Multidimensional signal modulation and/or demodulation for data communications

DOEpatents

Smith, Stephen F [London, TN; Dress, William B [Camas, WA

2008-03-04

Systems and methods are described for multidimensional signal modulation and/or demodulation for data communications. A method includes modulating a carrier signal in a first domain selected from the group consisting of phase, frequency, amplitude, polarization and spread; modulating the carrier signal in a second domain selected from the group consisting of phase, frequency, amplitude, polarization and spread; and modulating the carrier signal in a third domain selected from the group consisting of phase, frequency, amplitude, polarization and spread.

Lost in space: design of experiments and scientific exploration in a Hogarth Universe.

PubMed

Lendrem, Dennis W; Lendrem, B Clare; Woods, David; Rowland-Jones, Ruth; Burke, Matthew; Chatfield, Marion; Isaacs, John D; Owen, Martin R

2015-11-01

A Hogarth, or 'wicked', universe is an irregular environment generating data to support erroneous beliefs. Here, we argue that development scientists often work in such a universe. We demonstrate that exploring these multidimensional spaces using small experiments guided by scientific intuition alone, gives rise to an illusion of validity and a misplaced confidence in that scientific intuition. By contrast, design of experiments (DOE) permits the efficient mapping of such complex, multidimensional spaces. We describe simulation tools that enable research scientists to explore these spaces in relative safety. Copyright © 2015 Elsevier Ltd. All rights reserved.

Approximating tunneling rates in multi-dimensional field spaces

NASA Astrophysics Data System (ADS)

Masoumi, Ali; Olum, Ken D.; Wachter, Jeremy M.

2017-10-01

Quantum mechanics makes the otherwise stable vacua of a theory metastable through the nucleation of bubbles of the new vacuum. This in turn causes a first order phase transition. These cosmological phase transitions may have played an important role in settling our universe into its current vacuum, and they may also happen in future. The most important frameworks where vacuum decay happens contain a large number of fields. Unfortunately, calculating the tunneling rates in these models is very time-consuming. In this paper we present a simple approximation for the tunneling rate by reducing it to a one-field problem which is easy to calculate. We demonstrate the validity of this approximation using our recent code "Anybubble" for several classes of potentials.

Approximating tunneling rates in multi-dimensional field spaces

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

Masoumi, Ali; Olum, Ken D.; Wachter, Jeremy M., E-mail: ali@cosmos.phy.tufts.edu, E-mail: kdo@cosmos.phy.tufts.edu, E-mail: Jeremy.Wachter@tufts.edu

Quantum mechanics makes the otherwise stable vacua of a theory metastable through the nucleation of bubbles of the new vacuum. This in turn causes a first order phase transition. These cosmological phase transitions may have played an important role in settling our universe into its current vacuum, and they may also happen in future. The most important frameworks where vacuum decay happens contain a large number of fields. Unfortunately, calculating the tunneling rates in these models is very time-consuming. In this paper we present a simple approximation for the tunneling rate by reducing it to a one-field problem which ismore » easy to calculate. We demonstrate the validity of this approximation using our recent code 'Anybubble' for several classes of potentials.« less

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.

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.

Quantum dynamics calculations using symmetrized, orthogonal Weyl-Heisenberg wavelets with a phase space truncation scheme. III. Representations and calculations.

PubMed

Poirier, Bill; Salam, A

2004-07-22

In a previous paper [J. Theo. Comput. Chem. 2, 65 (2003)], one of the authors (B.P.) presented a method for solving the multidimensional Schrodinger equation, using modified Wilson-Daubechies wavelets, and a simple phase space truncation scheme. Unprecedented numerical efficiency was achieved, enabling a ten-dimensional calculation of nearly 600 eigenvalues to be performed using direct matrix diagonalization techniques. In a second paper [J. Chem. Phys. 121, 1690 (2004)], and in this paper, we extend and elaborate upon the previous work in several important ways. The second paper focuses on construction and optimization of the wavelength functions, from theoretical and numerical viewpoints, and also examines their localization. This paper deals with their use in representations and eigenproblem calculations, which are extended to 15-dimensional systems. Even higher dimensionalities are possible using more sophisticated linear algebra techniques. This approach is ideally suited to rovibrational spectroscopy applications, but can be used in any context where differential equations are involved.

Multidimensional, mapping-based complex wavelet transforms.

PubMed

Fernandes, Felix C A; van Spaendonck, Rutger L C; Burrus, C Sidney

2005-01-01

Although the discrete wavelet transform (DWT) is a powerful tool for signal and image processing, it has three serious disadvantages: shift sensitivity, poor directionality, and lack of phase information. To overcome these disadvantages, we introduce multidimensional, mapping-based, complex wavelet transforms that consist of a mapping onto a complex function space followed by a DWT of the complex mapping. Unlike other popular transforms that also mitigate DWT shortcomings, the decoupled implementation of our transforms has two important advantages. First, the controllable redundancy of the mapping stage offers a balance between degree of shift sensitivity and transform redundancy. This allows us to create a directional, nonredundant, complex wavelet transform with potential benefits for image coding systems. To the best of our knowledge, no other complex wavelet transform is simultaneously directional and nonredundant. The second advantage of our approach is the flexibility to use any DWT in the transform implementation. As an example, we exploit this flexibility to create the complex double-density DWT: a shift-insensitive, directional, complex wavelet transform with a low redundancy of (3M - 1)/(2M - 1) in M dimensions. No other transform achieves all these properties at a lower redundancy, to the best of our knowledge. By exploiting the advantages of our multidimensional, mapping-based complex wavelet transforms in seismic signal-processing applications, we have demonstrated state-of-the-art results.

Hidden multidimensional social structure modeling applied to biased social perception

NASA Astrophysics Data System (ADS)

Maletić, Slobodan; Zhao, Yi

2018-02-01

Intricacies of the structure of social relations are realized by representing a collection of overlapping opinions as a simplicial complex, thus building latent multidimensional structures, through which agents are, virtually, moving as they exchange opinions. The influence of opinion space structure on the distribution of opinions is demonstrated by modeling consensus phenomena when the opinion exchange between individuals may be affected by the false consensus effect. The results indicate that in the cases with and without bias, the road toward consensus is influenced by the structure of multidimensional space of opinions, and in the biased case, complete consensus is achieved. The applications of proposed modeling framework can easily be generalized, as they transcend opinion formation modeling.

"Just another pretty face": a multidimensional scaling approach to face attractiveness and variability.

PubMed

Potter, Timothy; Corneille, Olivier; Ruys, Kirsten I; Rhodes, Ginwan

2007-04-01

Findings on both attractiveness and memory for faces suggest that people should perceive more similarity among attractive than among unattractive faces. A multidimensional scaling approach was used to test this hypothesis in two studies. In Study 1, we derived a psychological face space from similarity ratings of attractive and unattractive Caucasian female faces. In Study 2, we derived a face space for attractive and unattractive male faces of Caucasians and non-Caucasians. Both studies confirm that attractive faces are indeed more tightly clustered than unattractive faces in people's psychological face spaces. These studies provide direct and original support for theoretical assumptions previously made in the face space and face memory literatures.

On simplified application of multidimensional Savitzky-Golay filters and differentiators

NASA Astrophysics Data System (ADS)

Shekhar, Chandra

2016-02-01

I propose a simplified approach for multidimensional Savitzky-Golay filtering, to enable its fast and easy implementation in scientific and engineering applications. The proposed method, which is derived from a generalized framework laid out by Thornley (D. J. Thornley, "Novel anisotropic multidimensional convolution filters for derivative estimation and reconstruction" in Proceedings of International Conference on Signal Processing and Communications, November 2007), first transforms any given multidimensional problem into a unique one, by transforming coordinates of the sampled data nodes to unity-spaced, uniform data nodes, and then performs filtering and calculates partial derivatives on the unity-spaced nodes. It is followed by transporting the calculated derivatives back onto the original data nodes by using the chain rule of differentiation. The burden to performing the most cumbersome task, which is to carry out the filtering and to obtain derivatives on the unity-spaced nodes, is almost eliminated by providing convolution coefficients for a number of convolution kernel sizes and polynomial orders, up to four spatial dimensions. With the availability of the convolution coefficients, the task of filtering at a data node reduces merely to multiplication of two known matrices. Simplified strategies to adequately address near-boundary data nodes and to calculate partial derivatives there are also proposed. Finally, the proposed methodologies are applied to a three-dimensional experimentally obtained data set, which shows that multidimensional Savitzky-Golay filters and differentiators perform well in both the internal and the near-boundary regions of the domain.

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'…

Some applications of the multi-dimensional fractional order for the Riemann-Liouville derivative

NASA Astrophysics Data System (ADS)

Ahmood, Wasan Ajeel; Kiliçman, Adem

2017-01-01

In this paper, the aim of this work is to study theorem for the one-dimensional space-time fractional deriative, generalize some function for the one-dimensional fractional by table represents the fractional Laplace transforms of some elementary functions to be valid for the multi-dimensional fractional Laplace transform and give the definition of the multi-dimensional fractional Laplace transform. This study includes that, dedicate the one-dimensional fractional Laplace transform for functions of only one independent variable and develop of the one-dimensional fractional Laplace transform to multi-dimensional fractional Laplace transform based on the modified Riemann-Liouville derivative.

Variational Transition State Theory

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

Truhlar, Donald G.

2016-09-29

This is the final report on a project involving the development and applications of variational transition state theory. This project involved the development of variational transition state theory for gas-phase reactions, including optimized multidimensional tunneling contributions and the application of this theory to gas-phase reactions with a special emphasis on developing reaction rate theory in directions that are important for applications to combustion. The development of variational transition state theory with optimized multidimensional tunneling as a useful computational tool for combustion kinetics involved eight objectives.

Multidimensional Programming Methods for Energy Facility Siting: Alternative Approaches

NASA Technical Reports Server (NTRS)

Solomon, B. D.; Haynes, K. E.

1982-01-01

The use of multidimensional optimization methods in solving power plant siting problems, which are characterized by several conflicting, noncommensurable objectives is addressed. After a discussion of data requirements and exclusionary site screening methods for bounding the decision space, classes of multiobjective and goal programming models are discussed in the context of finite site selection. Advantages and limitations of these approaches are highlighted and the linkage of multidimensional methods with the subjective, behavioral components of the power plant siting process is emphasized.

Coherent (photon) vs incoherent (current) detection of multidimensional optical signals from single molecules in open junctions

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

Agarwalla, Bijay Kumar; Hua, Weijie; Zhang, Yu

2015-06-07

The nonlinear optical response of a current-carrying single molecule coupled to two metal leads and driven by a sequence of impulsive optical pulses with controllable phases and time delays is calculated. Coherent (stimulated, heterodyne) detection of photons and incoherent detection of the optically induced current are compared. Using a diagrammatic Liouville space superoperator formalism, the signals are recast in terms of molecular correlation functions which are then expanded in the many-body molecular states. Two dimensional signals in benzene-1,4-dithiol molecule show cross peaks involving charged states. The correlation between optical and charge current signal is also observed.

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

Kaufman, Allan N.; Tracy, Eugene R.; Brizard, Alain J.

The process of resonant wave conversion (often called linear mode conversion) has traditionally been analyzed with a spatially one-dimensional slab model, for which the rays propagate in a two-dimensional phase space. However, it has recently been shown [E. R. Tracy and A. N. Kaufman, Phys. Rev. Lett. 91, 130402 (2003)] that multidimensional rays have a helical structure for conversion in two or more spatial dimensions (if their dispersion matrix is generic). In that case, a one-dimensional model is inadequate; a correct analysis requires two spatial dimensions and, thus, four-dimensional phase space. A cold-plasma model is introduced in this paper whichmore » exhibits ray helicity in conversion regions where the density and magnetic field gradients are significantly nonparallel. For illustration, such regions are identified in a model of the poloidal plane of a deuterium-tritium tokamak plasma. In each conversion region, characterized by a six-sector topology, rays in the sector for incident and reflected magnetosonic waves exhibit significant helicity. A detailed analytic and numerical study of helical rays in this sector is developed for a 'symmetric-wedge' model.« less

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

Kaufman, Allan N.; Tracy, Eugene R.; Brizard, Alain J.

The process of resonant wave conversion (often called linear mode conversion) has traditionally been analyzed with a spatially one-dimensional slab model, for which the rays propagate in a two-dimensional phase space. However, it has recently been shown [E.R. Tracy and A.N. Kaufman, Phys. Rev. Lett. 91, 130402 (2003)] that multidimensional rays have a helical structure for conversion in two or more spatial dimensions (if their dispersion matrix is generic). In that case, a one-dimensional model is inadequate; a correct analysis requires two spatial dimensions and, thus, four-dimensional phase space. In this paper we show that a cold plasma model willmore » exhibit ray helicity in conversion regions where the density and magnetic field gradients are significantly non-parallel. For illustration, we examine a model of the poloidal plane of a deuterium-tritium tokamak plasma, and identify such a region. In this region, characterized by a six-sector topology, rays in the sector for incident and reflected magnetosonic waves exhibit significant helicity. We introduce a ''symmetric-wedge'' model, to develop a detailed analytic and numerical study of helical rays in this sector.« less

Phase diagram of the Shastry-Sutherland Kondo lattice model with classical localized spins: a variational calculation study

NASA Astrophysics Data System (ADS)

Shahzad, Munir; Sengupta, Pinaki

2017-08-01

We study the Shastry-Sutherland Kondo lattice model with additional Dzyaloshinskii-Moriya (DM) interactions, exploring the possible magnetic phases in its multi-dimensional parameter space. Treating the local moments as classical spins and using a variational ansatz, we identify the parameter ranges over which various common magnetic orderings are potentially stabilized. Our results reveal that the competing interactions result in a heightened susceptibility towards a wide range of spin configurations including longitudinal ferromagnetic and antiferromagnetic order, coplanar flux configurations and most interestingly, multiple non-coplanar configurations including a novel canted-flux state as the different Hamiltonian parameters like electron density, interaction strengths and degree of frustration are varied. The non-coplanar and non-collinear magnetic ordering of localized spins behave like emergent electromagnetic fields and drive unusual transport and electronic phenomena.

Four-dimensional key design in amplitude, phase, polarization and distance for optical encryption based on polarization digital holography and QR code.

PubMed

Lin, Chao; Shen, Xueju; Li, Baochen

2014-08-25

We demonstrate that all parameters of optical lightwave can be simultaneously designed as keys in security system. This multi-dimensional property of key can significantly enlarge the key space and further enhance the security level of the system. The single-shot off-axis digital holography with orthogonal polarized reference waves is employed to perform polarization state recording on object wave. Two pieces of polarization holograms are calculated and fabricated to be arranged in reference arms to generate random amplitude and phase distribution respectively. When reconstruction, original information which is represented with QR code can be retrieved using Fresnel diffraction with decryption keys and read out noise-free. Numerical simulation results for this cryptosystem are presented. An analysis on the key sensitivity and fault tolerance properties are also provided.

Reproducible, high-throughput synthesis of colloidal nanocrystals for optimization in multidimensional parameter space.

PubMed

Chan, Emory M; Xu, Chenxu; Mao, Alvin W; Han, Gang; Owen, Jonathan S; Cohen, Bruce E; Milliron, Delia J

2010-05-12

While colloidal nanocrystals hold tremendous potential for both enhancing fundamental understanding of materials scaling and enabling advanced technologies, progress in both realms can be inhibited by the limited reproducibility of traditional synthetic methods and by the difficulty of optimizing syntheses over a large number of synthetic parameters. Here, we describe an automated platform for the reproducible synthesis of colloidal nanocrystals and for the high-throughput optimization of physical properties relevant to emerging applications of nanomaterials. This robotic platform enables precise control over reaction conditions while performing workflows analogous to those of traditional flask syntheses. We demonstrate control over the size, size distribution, kinetics, and concentration of reactions by synthesizing CdSe nanocrystals with 0.2% coefficient of variation in the mean diameters across an array of batch reactors and over multiple runs. Leveraging this precise control along with high-throughput optical and diffraction characterization, we effectively map multidimensional parameter space to tune the size and polydispersity of CdSe nanocrystals, to maximize the photoluminescence efficiency of CdTe nanocrystals, and to control the crystal phase and maximize the upconverted luminescence of lanthanide-doped NaYF(4) nanocrystals. On the basis of these demonstrative examples, we conclude that this automated synthesis approach will be of great utility for the development of diverse colloidal nanomaterials for electronic assemblies, luminescent biological labels, electroluminescent devices, and other emerging applications.

On the chaotic diffusion in multidimensional Hamiltonian systems

NASA Astrophysics Data System (ADS)

Cincotta, P. M.; Giordano, C. M.; Martí, J. G.; Beaugé, C.

2018-01-01

We present numerical evidence that diffusion in the herein studied multidimensional near-integrable Hamiltonian systems departs from a normal process, at least for realistic timescales. Therefore, the derivation of a diffusion coefficient from a linear fit on the variance evolution of the unperturbed integrals fails. We review some topics on diffusion in the Arnold Hamiltonian and yield numerical and theoretical arguments to show that in the examples we considered, a standard coefficient would not provide a good estimation of the speed of diffusion. However, numerical experiments concerning diffusion would provide reliable information about the stability of the motion within chaotic regions of the phase space. In this direction, we present an extension of previous results concerning the dynamical structure of the Laplace resonance in Gliese-876 planetary system considering variations of the orbital parameters accordingly to the error introduced by the radial velocity determination. We found that a slight variation of the eccentricity of planet c would destabilize the inner region of the resonance that, though chaotic, shows stable when adopting the best fit values for the parameters.

Error control techniques for satellite and space communications

NASA Technical Reports Server (NTRS)

Costello, Daniel J., Jr.

1989-01-01

Two aspects of the work for NASA are examined: the construction of multi-dimensional phase modulation trellis codes and a performance analysis of these codes. A complete list is contained of all the best trellis codes for use with phase modulation. LxMPSK signal constellations are included for M = 4, 8, and 16 and L = 1, 2, 3, and 4. Spectral efficiencies range from 1 bit/channel symbol (equivalent to rate 1/2 coded QPSK) to 3.75 bits/channel symbol (equivalent to 15/16 coded 16-PSK). The parity check polynomials, rotational invariance properties, free distance, path multiplicities, and coding gains are given for all codes. These codes are considered to be the best candidates for implementation of a high speed decoder for satellite transmission. The design of a hardware decoder for one of these codes, viz., the 16-state 3x8-PSK code with free distance 4.0 and coding gain 3.75 dB is discussed. An exhaustive simulation study of the multi-dimensional phase modulation trellis codes is contained. This study was motivated by the fact that coding gains quoted for almost all codes found in literature are in fact only asymptotic coding gains, i.e., the coding gain at very high signal to noise ratios (SNRs) or very low BER. These asymptotic coding gains can be obtained directly from a knowledge of the free distance of the code. On the other hand, real coding gains at BERs in the range of 10(exp -2) to 10(exp -6), where these codes are most likely to operate in a concatenated system, must be done by simulation.

A General Multidimensional Model for the Measurement of Cultural Differences.

ERIC Educational Resources Information Center

Olmedo, Esteban L.; Martinez, Sergio R.

A multidimensional model for measuring cultural differences (MCD) based on factor analytic theory and techniques is proposed. The model assumes that a cultural space may be defined by means of a relatively small number of orthogonal dimensions which are linear combinations of a much larger number of cultural variables. Once a suitable,…

A nonlocal electron conduction model for multidimensional radiation hydrodynamics codes

NASA Astrophysics Data System (ADS)

Schurtz, G. P.; Nicolaï, Ph. D.; Busquet, M.

2000-10-01

Numerical simulation of laser driven Inertial Confinement Fusion (ICF) related experiments require the use of large multidimensional hydro codes. Though these codes include detailed physics for numerous phenomena, they deal poorly with electron conduction, which is the leading energy transport mechanism of these systems. Electron heat flow is known, since the work of Luciani, Mora, and Virmont (LMV) [Phys. Rev. Lett. 51, 1664 (1983)], to be a nonlocal process, which the local Spitzer-Harm theory, even flux limited, is unable to account for. The present work aims at extending the original formula of LMV to two or three dimensions of space. This multidimensional extension leads to an equivalent transport equation suitable for easy implementation in a two-dimensional radiation-hydrodynamic code. Simulations are presented and compared to Fokker-Planck simulations in one and two dimensions of space.

Electron Holes in phase-space: what they are and why they matter

NASA Astrophysics Data System (ADS)

Hutchinson, I. H.

2016-10-01

Plasma electron holes are soliton-like electric potential structures sustained self-consistently by a deficit of phase-space density on trapped orbits. They are a class of Bernstein Green and Kruskal (BGK)-mode phase-space vortices, long studied in basic analytic and computational theory and observed in some experiments. Recently it has become clear from space-craft observations that isolated potential structures with the character of electron holes constitute an important component of space-plasma turbulence. Modern computational simulations of collisionless plasmas also often observe electron holes to form as a nonlinear consequence of kinetic electron instabilities. This tutorial will explain the basic theory of electron hole structure, trace the development of the understanding of electron holes, and survey some of the observational evidence for their significance. It was found early on that unmagnetized multidimensional simulations of electron two-stream instabilities do not show the long lived holes that appear in one dimension. Deliberately-created 1-D slab holes in multiple dimensions experience a transverse instability unless the guiding magnetic field is strong enough. Analysis has yet to identify unequivocally the instability mechanism and threshold; but it can show that spherically symmetric holes in 3-D without magnetic field are essentially impossible. Recent simulations have studied holes' formation, self-acceleration, merging, splitting, and growth. Analytic understanding of many of these phenomena is gained from the kinematics of the hole regarded as a coherent entity, accounting for the plasma momentum changes it induces, and especially the interaction with the ions. Electron holes can travel at up to approximately the electron thermal speed, but not slower (relative to ions) than several times the ion acoustic speed. Some notable current research questions will be described.

An efficient sampling algorithm for uncertain abnormal data detection in biomedical image processing and disease prediction.

PubMed

Liu, Fei; Zhang, Xi; Jia, Yan

2015-01-01

In this paper, we propose a computer information processing algorithm that can be used for biomedical image processing and disease prediction. A biomedical image is considered a data object in a multi-dimensional space. Each dimension is a feature that can be used for disease diagnosis. We introduce a new concept of the top (k1,k2) outlier. It can be used to detect abnormal data objects in the multi-dimensional space. This technique focuses on uncertain space, where each data object has several possible instances with distinct probabilities. We design an efficient sampling algorithm for the top (k1,k2) outlier in uncertain space. Some improvement techniques are used for acceleration. Experiments show our methods' high accuracy and high efficiency.

Revealing determinants of two-phase dynamics of P53 network under gamma irradiation based on a reduced 2D relaxation oscillator model.

PubMed

Demirkıran, Gökhan; Kalaycı Demir, Güleser; Güzeliş, Cüneyt

2018-02-01

This study proposes a two-dimensional (2D) oscillator model of p53 network, which is derived via reducing the multidimensional two-phase dynamics model into a model of ataxia telangiectasia mutated (ATM) and Wip1 variables, and studies the impact of p53-regulators on cell fate decision. First, the authors identify a 6D core oscillator module, then reduce this module into a 2D oscillator model while preserving the qualitative behaviours. The introduced 2D model is shown to be an excitable relaxation oscillator. This oscillator provides a mechanism that leads diverse modes underpinning cell fate, each corresponding to a cell state. To investigate the effects of p53 inhibitors and the intrinsic time delay of Wip1 on the characteristics of oscillations, they introduce also a delay differential equation version of the 2D oscillator. They observe that the suppression of p53 inhibitors decreases the amplitudes of p53 oscillation, though the suppression increases the sustained level of p53. They identify Wip1 and P53DINP1 as possible targets for cancer therapies considering their impact on the oscillator, supported by biological findings. They model some mutations as critical changes of the phase space characteristics. Possible cancer therapeutic strategies are then proposed for preventing these mutations' effects using the phase space approach.

On-the-fly machine-learning for high-throughput experiments: search for rare-earth-free permanent magnets

PubMed Central

Kusne, Aaron Gilad; Gao, Tieren; Mehta, Apurva; Ke, Liqin; Nguyen, Manh Cuong; Ho, Kai-Ming; Antropov, Vladimir; Wang, Cai-Zhuang; Kramer, Matthew J.; Long, Christian; Takeuchi, Ichiro

2014-01-01

Advanced materials characterization techniques with ever-growing data acquisition speed and storage capabilities represent a challenge in modern materials science, and new procedures to quickly assess and analyze the data are needed. Machine learning approaches are effective in reducing the complexity of data and rapidly homing in on the underlying trend in multi-dimensional data. Here, we show that by employing an algorithm called the mean shift theory to a large amount of diffraction data in high-throughput experimentation, one can streamline the process of delineating the structural evolution across compositional variations mapped on combinatorial libraries with minimal computational cost. Data collected at a synchrotron beamline are analyzed on the fly, and by integrating experimental data with the inorganic crystal structure database (ICSD), we can substantially enhance the accuracy in classifying the structural phases across ternary phase spaces. We have used this approach to identify a novel magnetic phase with enhanced magnetic anisotropy which is a candidate for rare-earth free permanent magnet. PMID:25220062

A Nonequilibrium Rate Formula for Collective Motions of Complex Molecular Systems

NASA Astrophysics Data System (ADS)

Yanao, Tomohiro; Koon, Wang Sang; Marsden, Jerrold E.

2010-09-01

We propose a compact reaction rate formula that accounts for a non-equilibrium distribution of residence times of complex molecules, based on a detailed study of the coarse-grained phase space of a reaction coordinate. We take the structural transition dynamics of a six-atom Morse cluster between two isomers as a prototype of multi-dimensional molecular reactions. Residence time distribution of one of the isomers shows an exponential decay, while that of the other isomer deviates largely from the exponential form and has multiple peaks. Our rate formula explains such equilibrium and non-equilibrium distributions of residence times in terms of the rates of diffusions of energy and the phase of the oscillations of the reaction coordinate. Rapid diffusions of energy and the phase generally give rise to the exponential decay of residence time distribution, while slow diffusions give rise to a non-exponential decay with multiple peaks. We finally make a conjecture about a general relationship between the rates of the diffusions and the symmetry of molecular mass distributions.

Phase separation like dynamics during Myxococcus xanthus fruiting body formation

NASA Astrophysics Data System (ADS)

Liu, Guannan; Thutupalli, Shashi; Wigbers, Manon; Shaevitz, Joshua

2015-03-01

Collective motion exists in many living organisms as an advantageous strategy to help the entire group with predation, forage, and survival. However, the principles of self-organization underlying such collective motions remain unclear. During various developmental stages of the soil-dwelling bacterium, Myxococcus xanthus, different types of collective motions are observed. In particular, when starved, M. xanthus cells eventually aggregate together to form 3-dimensional structures (fruiting bodies), inside which cells sporulate in response to the stress. We study the fruiting body formation process as an out of equilibrium phase separation process. As local cell density increases, the dynamics of the aggregation M. xanthus cells switch from a spatio-temporally random process, resembling nucleation and growth, to an emergent pattern formation process similar to a spinodal decomposition. By employing high-resolution microscopy and a video analysis system, we are able to track the motion of single cells within motile collective groups, while separately tuning local cell density, cell velocity and reversal frequency, probing the multi-dimensional phase space of M. xanthus development.

Co-Creating Curriculum in Higher Education: Promoting Democratic Values and a Multidimensional View on Learning

ERIC Educational Resources Information Center

Bergmark, Ulrika; Westman, Susanne

2016-01-01

This paper discusses a case study in teacher education in Sweden, focusing on creating spaces for student engagement through co-creating curriculum. It highlights democratic values and a multidimensional learning view as underpinning such endeavors. The main findings are that co-creating curriculum is an ambiguous process entailing unpredictable,…

Speeded Old-New Recognition of Multidimensional Perceptual Stimuli: Modeling Performance at the Individual-Participant and Individual-Item Levels

ERIC Educational Resources Information Center

Nosofsky, Robert M.; Stanton, Roger D.

2006-01-01

Observers made speeded old-new recognition judgments of color stimuli embedded in a multidimensional similarity space. The paradigm used multiple lists but with the underlying similarity structures repeated across lists, to allow for quantitative modeling of the data at the individual-participant and individual-item levels. Correct rejection…

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.

High-Order Central WENO Schemes for Multi-Dimensional Hamilton-Jacobi Equations

NASA Technical Reports Server (NTRS)

Bryson, Steve; Levy, Doron; Biegel, Bryan (Technical Monitor)

2002-01-01

We present new third- and fifth-order Godunov-type central schemes for approximating solutions of the Hamilton-Jacobi (HJ) equation in an arbitrary number of space dimensions. These are the first central schemes for approximating solutions of the HJ equations with an order of accuracy that is greater than two. In two space dimensions we present two versions for the third-order scheme: one scheme that is based on a genuinely two-dimensional Central WENO reconstruction, and another scheme that is based on a simpler dimension-by-dimension reconstruction. The simpler dimension-by-dimension variant is then extended to a multi-dimensional fifth-order scheme. Our numerical examples in one, two and three space dimensions verify the expected order of accuracy of the schemes.

Mass media influence spreading in social networks with community structure

NASA Astrophysics Data System (ADS)

Candia, Julián; Mazzitello, Karina I.

2008-07-01

We study an extension of Axelrod's model for social influence, in which cultural drift is represented as random perturbations, while mass media are introduced by means of an external field. In this scenario, we investigate how the modular structure of social networks affects the propagation of mass media messages across a society. The community structure of social networks is represented by coupled random networks, in which two random graphs are connected by intercommunity links. Considering inhomogeneous mass media fields, we study the conditions for successful message spreading and find a novel phase diagram in the multidimensional parameter space. These findings show that social modularity effects are of paramount importance for designing successful, cost-effective advertising campaigns.

Similarity of the Multidimensional Space Defined by Parallel Forms of a Mathematics Test.

ERIC Educational Resources Information Center

Reckase, Mark D.; And Others

The purpose of the paper is to determine whether test forms of the Mathematics Usage Test (AAP Math) of the American College Testing Program are parallel in a multidimensional sense. The AAP Math is an achievement test of mathematics concepts acquired by high school students by the end of their third year. To determine the dimensionality of the…

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…

Macroscopically constrained Wang-Landau method for systems with multiple order parameters and its application to drawing complex phase diagrams

NASA Astrophysics Data System (ADS)

Chan, C. H.; Brown, G.; Rikvold, P. A.

2017-05-01

A generalized approach to Wang-Landau simulations, macroscopically constrained Wang-Landau, is proposed to simulate the density of states of a system with multiple macroscopic order parameters. The method breaks a multidimensional random-walk process in phase space into many separate, one-dimensional random-walk processes in well-defined subspaces. Each of these random walks is constrained to a different set of values of the macroscopic order parameters. When the multivariable density of states is obtained for one set of values of fieldlike model parameters, the density of states for any other values of these parameters can be obtained by a simple transformation of the total system energy. All thermodynamic quantities of the system can then be rapidly calculated at any point in the phase diagram. We demonstrate how to use the multivariable density of states to draw the phase diagram, as well as order-parameter probability distributions at specific phase points, for a model spin-crossover material: an antiferromagnetic Ising model with ferromagnetic long-range interactions. The fieldlike parameters in this model are an effective magnetic field and the strength of the long-range interaction.

Recent advances in multidimensional ultrafast spectroscopy

NASA Astrophysics Data System (ADS)

Oliver, Thomas A. A.

2018-01-01

Multidimensional ultrafast spectroscopies are one of the premier tools to investigate condensed phase dynamics of biological, chemical and functional nanomaterial systems. As they reach maturity, the variety of frequency domains that can be explored has vastly increased, with experimental techniques capable of correlating excitation and emission frequencies from the terahertz through to the ultraviolet. Some of the most recent innovations also include extreme cross-peak spectroscopies that directly correlate the dynamics of electronic and vibrational states. This review article summarizes the key technological advances that have permitted these recent advances, and the insights gained from new multidimensional spectroscopic probes.

Recent advances in multidimensional ultrafast spectroscopy

PubMed Central

2018-01-01

Multidimensional ultrafast spectroscopies are one of the premier tools to investigate condensed phase dynamics of biological, chemical and functional nanomaterial systems. As they reach maturity, the variety of frequency domains that can be explored has vastly increased, with experimental techniques capable of correlating excitation and emission frequencies from the terahertz through to the ultraviolet. Some of the most recent innovations also include extreme cross-peak spectroscopies that directly correlate the dynamics of electronic and vibrational states. This review article summarizes the key technological advances that have permitted these recent advances, and the insights gained from new multidimensional spectroscopic probes. PMID:29410844

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.

Efficient and Accurate Optimal Linear Phase FIR Filter Design Using Opposition-Based Harmony Search Algorithm

PubMed Central

Saha, S. K.; Dutta, R.; Choudhury, R.; Kar, R.; Mandal, D.; Ghoshal, S. P.

2013-01-01

In this paper, opposition-based harmony search has been applied for the optimal design of linear phase FIR filters. RGA, PSO, and DE have also been adopted for the sake of comparison. The original harmony search algorithm is chosen as the parent one, and opposition-based approach is applied. During the initialization, randomly generated population of solutions is chosen, opposite solutions are also considered, and the fitter one is selected as a priori guess. In harmony memory, each such solution passes through memory consideration rule, pitch adjustment rule, and then opposition-based reinitialization generation jumping, which gives the optimum result corresponding to the least error fitness in multidimensional search space of FIR filter design. Incorporation of different control parameters in the basic HS algorithm results in the balancing of exploration and exploitation of search space. Low pass, high pass, band pass, and band stop FIR filters are designed with the proposed OHS and other aforementioned algorithms individually for comparative optimization performance. A comparison of simulation results reveals the optimization efficacy of the OHS over the other optimization techniques for the solution of the multimodal, nondifferentiable, nonlinear, and constrained FIR filter design problems. PMID:23844390

Efficient and accurate optimal linear phase FIR filter design using opposition-based harmony search algorithm.

PubMed

Saha, S K; Dutta, R; Choudhury, R; Kar, R; Mandal, D; Ghoshal, S P

2013-01-01

In this paper, opposition-based harmony search has been applied for the optimal design of linear phase FIR filters. RGA, PSO, and DE have also been adopted for the sake of comparison. The original harmony search algorithm is chosen as the parent one, and opposition-based approach is applied. During the initialization, randomly generated population of solutions is chosen, opposite solutions are also considered, and the fitter one is selected as a priori guess. In harmony memory, each such solution passes through memory consideration rule, pitch adjustment rule, and then opposition-based reinitialization generation jumping, which gives the optimum result corresponding to the least error fitness in multidimensional search space of FIR filter design. Incorporation of different control parameters in the basic HS algorithm results in the balancing of exploration and exploitation of search space. Low pass, high pass, band pass, and band stop FIR filters are designed with the proposed OHS and other aforementioned algorithms individually for comparative optimization performance. A comparison of simulation results reveals the optimization efficacy of the OHS over the other optimization techniques for the solution of the multimodal, nondifferentiable, nonlinear, and constrained FIR filter design problems.

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.

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.

Framework for analyzing ecological trait-based models in multidimensional niche spaces

NASA Astrophysics Data System (ADS)

Biancalani, Tommaso; DeVille, Lee; Goldenfeld, Nigel

2015-05-01

We develop a theoretical framework for analyzing ecological models with a multidimensional niche space. Our approach relies on the fact that ecological niches are described by sequences of symbols, which allows us to include multiple phenotypic traits. Ecological drivers, such as competitive exclusion, are modeled by introducing the Hamming distance between two sequences. We show that a suitable transform diagonalizes the community interaction matrix of these models, making it possible to predict the conditions for niche differentiation and, close to the instability onset, the asymptotically long time population distributions of niches. We exemplify our method using the Lotka-Volterra equations with an exponential competition kernel.

Investigation of multidimensional control systems in the state space and wavelet medium

NASA Astrophysics Data System (ADS)

Fedosenkov, D. B.; Simikova, A. A.; Fedosenkov, B. A.

2018-05-01

The notions are introduced of “one-dimensional-point” and “multidimensional-point” automatic control systems. To demonstrate the joint use of approaches based on the concepts of state space and wavelet transforms, a method for optimal control in a state space medium represented in the form of time-frequency representations (maps), is considered. The computer-aided control system is formed on the basis of the similarity transformation method, which makes it possible to exclude the use of reduced state variable observers. 1D-material flow signals formed by primary transducers are converted by means of wavelet transformations into multidimensional concentrated-at-a point variables in the form of time-frequency distributions of Cohen’s class. The algorithm for synthesizing a stationary controller for feeding processes is given here. The conclusion is made that the formation of an optimal control law with time-frequency distributions available contributes to the improvement of transient processes quality in feeding subsystems and the mixing unit. Confirming the efficiency of the method presented is illustrated by an example of the current registration of material flows in the multi-feeding unit. The first section in your paper.

Interactions across Multiple Stimulus Dimensions in Primary Auditory Cortex.

PubMed

Sloas, David C; Zhuo, Ran; Xue, Hongbo; Chambers, Anna R; Kolaczyk, Eric; Polley, Daniel B; Sen, Kamal

2016-01-01

Although sensory cortex is thought to be important for the perception of complex objects, its specific role in representing complex stimuli remains unknown. Complex objects are rich in information along multiple stimulus dimensions. The position of cortex in the sensory hierarchy suggests that cortical neurons may integrate across these dimensions to form a more gestalt representation of auditory objects. Yet, studies of cortical neurons typically explore single or few dimensions due to the difficulty of determining optimal stimuli in a high dimensional stimulus space. Evolutionary algorithms (EAs) provide a potentially powerful approach for exploring multidimensional stimulus spaces based on real-time spike feedback, but two important issues arise in their application. First, it is unclear whether it is necessary to characterize cortical responses to multidimensional stimuli or whether it suffices to characterize cortical responses to a single dimension at a time. Second, quantitative methods for analyzing complex multidimensional data from an EA are lacking. Here, we apply a statistical method for nonlinear regression, the generalized additive model (GAM), to address these issues. The GAM quantitatively describes the dependence between neural response and all stimulus dimensions. We find that auditory cortical neurons in mice are sensitive to interactions across dimensions. These interactions are diverse across the population, indicating significant integration across stimulus dimensions in auditory cortex. This result strongly motivates using multidimensional stimuli in auditory cortex. Together, the EA and the GAM provide a novel quantitative paradigm for investigating neural coding of complex multidimensional stimuli in auditory and other sensory cortices.

Column Liquid Chromatography.

ERIC Educational Resources Information Center

Majors, Ronald E.; And Others

1984-01-01

Reviews literature covering developments of column liquid chromatography during 1982-83. Areas considered include: books and reviews; general theory; columns; instrumentation; detectors; automation and data handling; multidimensional chromatographic and column switching techniques; liquid-solid chromatography; normal bonded-phase, reversed-phase,…

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.

Simulation of a Multidimensional Input Quantum Perceptron

NASA Astrophysics Data System (ADS)

Yamamoto, Alexandre Y.; Sundqvist, Kyle M.; Li, Peng; Harris, H. Rusty

2018-06-01

In this work, we demonstrate the improved data separation capabilities of the Multidimensional Input Quantum Perceptron (MDIQP), a fundamental cell for the construction of more complex Quantum Artificial Neural Networks (QANNs). This is done by using input controlled alterations of ancillary qubits in combination with phase estimation and learning algorithms. The MDIQP is capable of processing quantum information and classifying multidimensional data that may not be linearly separable, extending the capabilities of the classical perceptron. With this powerful component, we get much closer to the achievement of a feedforward multilayer QANN, which would be able to represent and classify arbitrary sets of data (both quantum and classical).

Coupling Front-End Separations, Ion Mobility Spectrometry, and Mass Spectrometry For Enhanced Multidimensional Biological and Environmental Analyses

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

Zheng, Xueyun; Wojcik, Roza; Zhang, Xing

Ion mobility spectrometry (IMS) is a widely used analytical technique for rapid molecular separations in the gas phase. IMS alone is useful, but its coupling with mass spectrometry (MS) and front-end separations has been extremely beneficial for increasing measurement sensitivity, peak capacity of complex mixtures, and the scope of molecular information in biological and environmental sample analyses. Multiple studies in disease screening and environmental evaluations have even shown these IMS-based multidimensional separations extract information not possible with each technique individually. This review highlights 3-dimensional separations using IMS-MS in conjunction with a range of front-end techniques, such as gas chromatography (GC),more » supercritical fluid chromatography (SFC), liquid chromatography (LC), solid phase extractions (SPE), capillary electrophoresis (CE), field asymmetric ion mobility spectrometry (FAIMS), and microfluidic devices. The origination, current state, various applications, and future capabilities for these multidimensional approaches are described to provide insight into the utility and potential of each technique.« less

Coupling Front-End Separations, Ion Mobility Spectrometry, and Mass Spectrometry For Enhanced Multidimensional Biological and Environmental Analyses

PubMed Central

Zheng, Xueyun; Wojcik, Roza; Zhang, Xing; Ibrahim, Yehia M.; Burnum-Johnson, Kristin E.; Orton, Daniel J.; Monroe, Matthew E.; Moore, Ronald J.; Smith, Richard D.; Baker, Erin S.

2017-01-01

Ion mobility spectrometry (IMS) is a widely used analytical technique for rapid molecular separations in the gas phase. Though IMS alone is useful, its coupling with mass spectrometry (MS) and front-end separations is extremely beneficial for increasing measurement sensitivity, peak capacity of complex mixtures, and the scope of molecular information available from biological and environmental sample analyses. In fact, multiple disease screening and environmental evaluations have illustrated that the IMS-based multidimensional separations extract information that cannot be acquired with each technique individually. This review highlights three-dimensional separations using IMS-MS in conjunction with a range of front-end techniques, such as gas chromatography, supercritical fluid chromatography, liquid chromatography, solid-phase extractions, capillary electrophoresis, field asymmetric ion mobility spectrometry, and microfluidic devices. The origination, current state, various applications, and future capabilities of these multidimensional approaches are described in detail to provide insight into their uses and benefits. PMID:28301728

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.

Phase-space finite elements in a least-squares solution of the transport equation

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

Drumm, C.; Fan, W.; Pautz, S.

2013-07-01

The linear Boltzmann transport equation is solved using a least-squares finite element approximation in the space, angular and energy phase-space variables. The method is applied to both neutral particle transport and also to charged particle transport in the presence of an electric field, where the angular and energy derivative terms are handled with the energy/angular finite elements approximation, in a manner analogous to the way the spatial streaming term is handled. For multi-dimensional problems, a novel approach is used for the angular finite elements: mapping the surface of a unit sphere to a two-dimensional planar region and using a meshingmore » tool to generate a mesh. In this manner, much of the spatial finite-elements machinery can be easily adapted to handle the angular variable. The energy variable and the angular variable for one-dimensional problems make use of edge/beam elements, also building upon the spatial finite elements capabilities. The methods described here can make use of either continuous or discontinuous finite elements in space, angle and/or energy, with the use of continuous finite elements resulting in a smaller problem size and the use of discontinuous finite elements resulting in more accurate solutions for certain types of problems. The work described in this paper makes use of continuous finite elements, so that the resulting linear system is symmetric positive definite and can be solved with a highly efficient parallel preconditioned conjugate gradients algorithm. The phase-space finite elements capability has been built into the Sceptre code and applied to several test problems, including a simple one-dimensional problem with an analytic solution available, a two-dimensional problem with an isolated source term, showing how the method essentially eliminates ray effects encountered with discrete ordinates, and a simple one-dimensional charged-particle transport problem in the presence of an electric field. (authors)« less

A New Time-Space Accurate Scheme for Hyperbolic Problems. 1; Quasi-Explicit Case

NASA Technical Reports Server (NTRS)

Sidilkover, David

1998-01-01

This paper presents a new discretization scheme for hyperbolic systems of conservations laws. It satisfies the TVD property and relies on the new high-resolution mechanism which is compatible with the genuinely multidimensional approach proposed recently. This work can be regarded as a first step towards extending the genuinely multidimensional approach to unsteady problems. Discontinuity capturing capabilities and accuracy of the scheme are verified by a set of numerical tests.

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.

The multidimensional behavioural hypervolumes of two interacting species predict their space use and survival

PubMed Central

Lichtenstein, James L. L.; Wright, Colin M; McEwen, Brendan; Pinter-Wollman, Noa; Pruitt, Jonathan N.

2018-01-01

Individual animals differ consistently in their behaviour, thus impacting a wide variety of ecological outcomes. Recent advances in animal personality research have established the ecological importance of the multidimensional behavioural volume occupied by individuals and by multispecies communities. Here, we examine the degree to which the multidimensional behavioural volume of a group predicts the outcome of both intra- and interspecific interactions. In particular, we test the hypothesis that a population of conspecifics will experience low intraspecific competition when the population occupies a large volume in behavioural space. We further hypothesize that populations of interacting species will exhibit greater interspecific competition when one or both species occupy large volumes in behavioural space. We evaluate these hypotheses by studying groups of katydids (Scudderia nymphs) and froghoppers (Philaenus spumarius), which compete for food and space on their shared host plant, Solidago canadensis. We found that individuals in single-species groups of katydids positioned themselves closer to one another, suggesting reduced competition, when groups occupied a large behavioural volume. When both species were placed together, we found that the survival of froghoppers was greatest when both froghoppers and katydids occupied a small volume in behavioural space, particularly at high froghopper densities. These results suggest that groups that occupy large behavioural volumes can have low intraspecific competition but high interspecific competition. Thus, behavioural hypervolumes appear to have ecological consequences at both the level of the population and the community and may help to predict the intensity of competition both within and across species. PMID:29681647

Multidimensional flamelet-generated manifolds for partially premixed combustion

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

Nguyen, Phuc-Danh; Vervisch, Luc; Subramanian, Vallinayagam

2010-01-15

Flamelet-generated manifolds have been restricted so far to premixed or diffusion flame archetypes, even though the resulting tables have been applied to nonpremixed and partially premixed flame simulations. By using a projection of the full set of mass conservation species balance equations into a restricted subset of the composition space, unsteady multidimensional flamelet governing equations are derived from first principles, under given hypotheses. During the projection, as in usual one-dimensional flamelets, the tangential strain rate of scalar isosurfaces is expressed in the form of the scalar dissipation rates of the control parameters of the multidimensional flamelet-generated manifold (MFM), which ismore » tested in its five-dimensional form for partially premixed combustion, with two composition space directions and three scalar dissipation rates. It is shown that strain-rate-induced effects can hardly be fully neglected in chemistry tabulation of partially premixed combustion, because of fluxes across iso-equivalence-ratio and iso-progress-of-reaction surfaces. This is illustrated by comparing the 5D flamelet-generated manifold with one-dimensional premixed flame and unsteady strained diffusion flame composition space trajectories. The formal links between the asymptotic behavior of MFM and stratified flame, weakly varying partially premixed front, triple-flame, premixed and nonpremixed edge flames are also evidenced. (author)« less

Evidence of Second-Order Factor Structure in a Diagnostic Problem Space: Implications for Medical Education.

ERIC Educational Resources Information Center

Papa, Frank J.; And Others

1997-01-01

Chest pain was identified as a specific medical problem space, and disease classes were modeled to define it. Results from a test taken by 628 medical residents indicate a second-order factor structure that suggests that chest pain is a multidimensional problem space. Implications for medical education are discussed. (SLD)

Multidimensional entropic uncertainty relation based on a commutator matrix in position and momentum spaces

NASA Astrophysics Data System (ADS)

Hertz, Anaelle; Vanbever, Luc; Cerf, Nicolas J.

2018-01-01

The uncertainty relation for continuous variables due to Byałinicki-Birula and Mycielski [I. Białynicki-Birula and J. Mycielski, Commun. Math. Phys. 44, 129 (1975), 10.1007/BF01608825] expresses the complementarity between two n -tuples of canonically conjugate variables (x1,x2,...,xn) and (p1,p2,...,pn) in terms of Shannon differential entropy. Here we consider the generalization to variables that are not canonically conjugate and derive an entropic uncertainty relation expressing the balance between any two n -variable Gaussian projective measurements. The bound on entropies is expressed in terms of the determinant of a matrix of commutators between the measured variables. This uncertainty relation also captures the complementarity between any two incompatible linear canonical transforms, the bound being written in terms of the corresponding symplectic matrices in phase space. Finally, we extend this uncertainty relation to Rényi entropies and also prove a covariance-based uncertainty relation which generalizes the Robertson relation.

Multidimensional poverty and child survival in India.

PubMed

Mohanty, Sanjay K

2011-01-01

Though the concept of multidimensional poverty has been acknowledged cutting across the disciplines (among economists, public health professionals, development thinkers, social scientists, policy makers and international organizations) and included in the development agenda, its measurement and application are still limited. OBJECTIVES AND METHODOLOGY: Using unit data from the National Family and Health Survey 3, India, this paper measures poverty in multidimensional space and examine the linkages of multidimensional poverty with child survival. The multidimensional poverty is measured in the dimension of knowledge, health and wealth and the child survival is measured with respect to infant mortality and under-five mortality. Descriptive statistics, principal component analyses and the life table methods are used in the analyses. The estimates of multidimensional poverty are robust and the inter-state differentials are large. While infant mortality rate and under-five mortality rate are disproportionately higher among the abject poor compared to the non-poor, there are no significant differences in child survival among educationally, economically and health poor at the national level. State pattern in child survival among the education, economical and health poor are mixed. Use of multidimensional poverty measures help to identify abject poor who are unlikely to come out of poverty trap. The child survival is significantly lower among abject poor compared to moderate poor and non-poor. We urge to popularize the concept of multiple deprivations in research and program so as to reduce poverty and inequality in the population.

Error control techniques for satellite and space communications

NASA Technical Reports Server (NTRS)

Costello, Daniel J., Jr.

1991-01-01

Shannon's capacity bound shows that coding can achieve large reductions in the required signal to noise ratio per information bit (E sub b/N sub 0 where E sub b is the energy per bit and (N sub 0)/2 is the double sided noise density) in comparison to uncoded schemes. For bandwidth efficiencies of 2 bit/sym or greater, these improvements were obtained through the use of Trellis Coded Modulation and Block Coded Modulation. A method of obtaining these high efficiencies using multidimensional Multiple Phase Shift Keying (MPSK) and Quadrature Amplitude Modulation (QAM) signal sets with trellis coding is described. These schemes have advantages in decoding speed, phase transparency, and coding gain in comparison to other trellis coding schemes. Finally, a general parity check equation for rotationally invariant trellis codes is introduced from which non-linear codes for two dimensional MPSK and QAM signal sets are found. These codes are fully transparent to all rotations of the signal set.

Multi-attribute subjective evaluations of manual tracking tasks vs. objective performance of the human operator

NASA Technical Reports Server (NTRS)

Siapkaras, A.

1977-01-01

A computational method to deal with the multidimensional nature of tracking and/or monitoring tasks is developed. Operator centered variables, including the operator's perception of the task, are considered. Matrix ratings are defined based on multidimensional scaling techniques and multivariate analysis. The method consists of two distinct steps: (1) to determine the mathematical space of subjective judgements of a certain individual (or group of evaluators) for a given set of tasks and experimental conditionings; and (2) to relate this space with respect to both the task variables and the objective performance criteria used. Results for a variety of second-order trackings with smoothed noise-driven inputs indicate that: (1) many of the internally perceived task variables form a nonorthogonal set; and (2) the structure of the subjective space varies among groups of individuals according to the degree of familiarity they have with such tasks.

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.

Dynamic mapping of conical intersection seams: A general method for incorporating the geometric phase in adiabatic dynamics in polyatomic systems

NASA Astrophysics Data System (ADS)

Xie, Changjian; Malbon, Christopher L.; Yarkony, David R.; Guo, Hua

2017-07-01

The incorporation of the geometric phase in single-state adiabatic dynamics near a conical intersection (CI) seam has so far been restricted to molecular systems with high symmetry or simple model Hamiltonians. This is due to the fact that the ab initio determined derivative coupling (DC) in a multi-dimensional space is not curl-free, thus making its line integral path dependent. In a recent work [C. L. Malbon et al., J. Chem. Phys. 145, 234111 (2016)], we proposed a new and general approach based on an ab initio determined diabatic representation consisting of only two electronic states, in which the DC is completely removable, so that its line integral is path independent in the simply connected domains that exclude the CI seam. Then with the CIs included, the line integral of the single-valued DC can be used to construct the complex geometry-dependent phase needed to exactly eliminate the double-valued character of the real-valued adiabatic electronic wavefunction. This geometry-dependent phase gives rise to a vector potential which, when included in the adiabatic representation, rigorously accounts for the geometric phase in a system with an arbitrary locus of the CI seam and an arbitrary number of internal coordinates. In this work, we demonstrate this approach in a three-dimensional treatment of the tunneling facilitated dissociation of the S1 state of phenol, which is affected by a Cs symmetry allowed but otherwise accidental seam of CI. Here, since the space is three-dimensional rather than two-dimensional, the seam is a curve rather than a point. The nodal structure of the ground state vibronic wavefunction is shown to map out the seam of CI.

Membership determination of open clusters based on a spectral clustering method

NASA Astrophysics Data System (ADS)

Gao, Xin-Hua

2018-06-01

We present a spectral clustering (SC) method aimed at segregating reliable members of open clusters in multi-dimensional space. The SC method is a non-parametric clustering technique that performs cluster division using eigenvectors of the similarity matrix; no prior knowledge of the clusters is required. This method is more flexible in dealing with multi-dimensional data compared to other methods of membership determination. We use this method to segregate the cluster members of five open clusters (Hyades, Coma Ber, Pleiades, Praesepe, and NGC 188) in five-dimensional space; fairly clean cluster members are obtained. We find that the SC method can capture a small number of cluster members (weak signal) from a large number of field stars (heavy noise). Based on these cluster members, we compute the mean proper motions and distances for the Hyades, Coma Ber, Pleiades, and Praesepe clusters, and our results are in general quite consistent with the results derived by other authors. The test results indicate that the SC method is highly suitable for segregating cluster members of open clusters based on high-precision multi-dimensional astrometric data such as Gaia data.

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.

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

Vahala, G.; Tracy, E.

During the past year, the authors have concentrated on (1) divertor physics, (2) thermo-lattice Boltzmann (TLBE) approach to turbulence, and (3) phase space techniques in gyro-resonance problems in collaboration with Dieter Sigmar (MIT), Sergei Krasheninnikov (MIT), Linda Vahala (ODU), Joseph Morrison (AS and M/NASA-Langley), Pavol Pavlo and Josef Preinhaelter (institute of Plasma Physics, Czech Academy of Sciences) and Allan Kaufman (LBL/U.C.Berkeley). Using a 2-equation compressible closure model with a 2D mean flow, the authors are investigating the effects of 3D neutral turbulence on reducing the heat load to the divertor plate by various toroidal cavity geometries. These studies are beingmore » extended to examine 3D mean flows. Thermal Lattice Boltzmann (TLBE) methods are being investigated to handle 3D turbulent flows in nontrivial geometries. It is planned to couple the TLBE collisional regime to the weakly collisional regime and so be able to tackle divertor physics. In the application of phase space techniques to minority-ion RF heating, resonance heating is treated as a multi-stage process. A generalization of the Case-van Kampen analysis is presented for multi-dimensional non-uniform plasmas. Effects such as particle trapping and the ray propagation dynamics in tokamak geometry can now be handled using Weyl calculus.« less

Improved surface-wave retrieval from ambient seismic noise by multi-dimensional deconvolution

NASA Astrophysics Data System (ADS)

Wapenaar, Kees; Ruigrok, Elmer; van der Neut, Joost; Draganov, Deyan

2011-01-01

The methodology of surface-wave retrieval from ambient seismic noise by crosscorrelation relies on the assumption that the noise field is equipartitioned. Deviations from equipartitioning degrade the accuracy of the retrieved surface-wave Green's function. A point-spread function, derived from the same ambient noise field, quantifies the smearing in space and time of the virtual source of the Green's function. By multidimensionally deconvolving the retrieved Green's function by the point-spread function, the virtual source becomes better focussed in space and time and hence the accuracy of the retrieved surface-wave Green's function may improve significantly. We illustrate this at the hand of a numerical example and discuss the advantages and limitations of this new methodology.

The use of multidimensional scaling for facilities layout - An application to the design of the Space Station

NASA Technical Reports Server (NTRS)

Tullis, Thomas S.; Bied Sperling, Barbra; Steinberg, A. L.

1986-01-01

Before an optimum layout of the facilities for the proposed Space Station can be designed, it is necessary to understand the functions that will be performed by the Space Station crew and the relationships among those functions. Five criteria for assessing functional relationships were identified. For each of these criteria, a matrix representing the degree of association of all pairs of functions was developed. The key to making inferences about the layout of the Space Station from these matrices was the use of multidimensional scaling (MDS). Applying MDS to these matrices resulted in spatial configurations of the crew functions in which smaller distances in the MDS configuration reflected closer associations. An MDS analysis of a composite matrix formed by combining the five individual matrices resulted in two dimensions that describe the configuration: a 'private-public' dimension and a 'group-individual' dimension. Seven specific recommendations for Space Station layout were derived from analyses of the MDS configurations. Although these techniques have been applied to the design of the Space Station, they can be applied to the design of any facility where people live or work.

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

A chaotic modified-DFT encryption scheme for physical layer security and PAPR reduction in OFDM-PON

NASA Astrophysics Data System (ADS)

Fu, Xiaosong; Bi, Meihua; Zhou, Xuefang; Yang, Guowei; Li, Qiliang; Zhou, Zhao; Yang, Xuelin

2018-05-01

This letter proposes a modified discrete Fourier transform (DFT) encryption scheme with multi-dimensional chaos for the physical layer security and peak-to-average power ratio (PAPR) reduction in orthogonal frequency division multiplexing passive optical network (OFDM-PON) system. This multiple-fold encryption algorithm is mainly composed by using the column vectors permutation and the random phase encryption in the standard DFT matrix, which can create ∼10551 key space. The transmission of ∼10 Gb/s encrypted OFDM signal is verified over 20-km standard single mode fiber (SMF). Moreover, experimental results show that, the proposed scheme can achieve ∼2.6-dB PAPR reduction and ∼1-dB improvement of receiver sensitivity if compared with the common OFDM-PON.

Multidimensional stability of traveling fronts in combustion and non-KPP monostable equations

NASA Astrophysics Data System (ADS)

Bu, Zhen-Hui; Wang, Zhi-Cheng

2018-02-01

This paper is concerned with the multidimensional stability of traveling fronts for the combustion and non-KPP monostable equations. Our study contains two parts: in the first part, we first show that the two-dimensional V-shaped traveling fronts are asymptotically stable in R^{n+2} with n≥1 under any (possibly large) initial perturbations that decay at space infinity, and then, we prove that there exists a solution that oscillates permanently between two V-shaped traveling fronts, which implies that even very small perturbations to the V-shaped traveling front can lead to permanent oscillation. In the second part, we establish the multidimensional stability of planar traveling front in R^{n+1} with n≥1.

Knowledge Space: A Conceptual Basis for the Organization of Knowledge

ERIC Educational Resources Information Center

Meincke, Peter P. M.; Atherton, Pauline

1976-01-01

Proposes a new conceptual basis for visualizing the organization of information, or knowledge, which differentiates between the concept "vectors" for a field of knowledge represented in a multidimensional space, and the state "vectors" for a person based on his understanding of these concepts, and the representational…

One-Dimensional, Two-Phase Flow Modeling Toward Interpreting Motor Slag Expulsion Phenomena

NASA Technical Reports Server (NTRS)

Kibbey, Timothy P.

2012-01-01

Aluminum oxide slag accumulation and expulsion was previously shown to be a player in various solid rocket motor phenomena, including the Space Shuttle's Reusable Solid Rocket Motor (RSRM) pressure perturbation, or "blip," and phantom moment. In the latter case, such un ]commanded side accelerations near the end of burn have also been identified in several other motor systems. However, efforts to estimate the mass expelled during a given event have come up short. Either bulk calculations are performed without enough physics present, or multiphase, multidimensional Computational Fluid Dynamic analyses are performed that give a snapshot in time and space but do not always aid in grasping the general principle. One ]dimensional, two ]phase compressible flow calculations yield an analytical result for nozzle flow under certain assumptions. This can be carried further to relate the bulk motor parameters of pressure, thrust, and mass flow rate under the different exhaust conditions driven by the addition of condensed phase mass flow. An unknown parameter is correlated to airflow testing with water injection where mass flow rates and pressure are known. Comparison is also made to full ]scale static test motor data where thrust and pressure changes are known and similar behavior is shown. The end goal is to be able to include the accumulation and flow of slag in internal ballistics predictions. This will allow better prediction of the tailoff when much slag is ejected and of mass retained versus time, believed to be a contributor to the widely-observed "flight knockdown" parameter.

Multidimensional Poverty and Child Survival in India

PubMed Central

Mohanty, Sanjay K.

2011-01-01

Background Though the concept of multidimensional poverty has been acknowledged cutting across the disciplines (among economists, public health professionals, development thinkers, social scientists, policy makers and international organizations) and included in the development agenda, its measurement and application are still limited. Objectives and Methodology Using unit data from the National Family and Health Survey 3, India, this paper measures poverty in multidimensional space and examine the linkages of multidimensional poverty with child survival. The multidimensional poverty is measured in the dimension of knowledge, health and wealth and the child survival is measured with respect to infant mortality and under-five mortality. Descriptive statistics, principal component analyses and the life table methods are used in the analyses. Results The estimates of multidimensional poverty are robust and the inter-state differentials are large. While infant mortality rate and under-five mortality rate are disproportionately higher among the abject poor compared to the non-poor, there are no significant differences in child survival among educationally, economically and health poor at the national level. State pattern in child survival among the education, economical and health poor are mixed. Conclusion Use of multidimensional poverty measures help to identify abject poor who are unlikely to come out of poverty trap. The child survival is significantly lower among abject poor compared to moderate poor and non-poor. We urge to popularize the concept of multiple deprivations in research and program so as to reduce poverty and inequality in the population. PMID:22046384

Symmetric convolution of asymmetric multidimensional sequences using discrete trigonometric transforms.

PubMed

Foltz, T M; Welsh, B M

1999-01-01

This paper uses the fact that the discrete Fourier transform diagonalizes a circulant matrix to provide an alternate derivation of the symmetric convolution-multiplication property for discrete trigonometric transforms. Derived in this manner, the symmetric convolution-multiplication property extends easily to multiple dimensions using the notion of block circulant matrices and generalizes to multidimensional asymmetric sequences. The symmetric convolution of multidimensional asymmetric sequences can then be accomplished by taking the product of the trigonometric transforms of the sequences and then applying an inverse trigonometric transform to the result. An example is given of how this theory can be used for applying a two-dimensional (2-D) finite impulse response (FIR) filter with nonlinear phase which models atmospheric turbulence.

Density-based clustering: A 'landscape view' of multi-channel neural data for inference and dynamic complexity analysis.

PubMed

Baglietto, Gabriel; Gigante, Guido; Del Giudice, Paolo

2017-01-01

Two, partially interwoven, hot topics in the analysis and statistical modeling of neural data, are the development of efficient and informative representations of the time series derived from multiple neural recordings, and the extraction of information about the connectivity structure of the underlying neural network from the recorded neural activities. In the present paper we show that state-space clustering can provide an easy and effective option for reducing the dimensionality of multiple neural time series, that it can improve inference of synaptic couplings from neural activities, and that it can also allow the construction of a compact representation of the multi-dimensional dynamics, that easily lends itself to complexity measures. We apply a variant of the 'mean-shift' algorithm to perform state-space clustering, and validate it on an Hopfield network in the glassy phase, in which metastable states are largely uncorrelated from memories embedded in the synaptic matrix. In this context, we show that the neural states identified as clusters' centroids offer a parsimonious parametrization of the synaptic matrix, which allows a significant improvement in inferring the synaptic couplings from the neural activities. Moving to the more realistic case of a multi-modular spiking network, with spike-frequency adaptation inducing history-dependent effects, we propose a procedure inspired by Boltzmann learning, but extending its domain of application, to learn inter-module synaptic couplings so that the spiking network reproduces a prescribed pattern of spatial correlations; we then illustrate, in the spiking network, how clustering is effective in extracting relevant features of the network's state-space landscape. Finally, we show that the knowledge of the cluster structure allows casting the multi-dimensional neural dynamics in the form of a symbolic dynamics of transitions between clusters; as an illustration of the potential of such reduction, we define and analyze a measure of complexity of the neural time series.

An Operational Definition of Learning

ERIC Educational Resources Information Center

Harel, Guershon; Koichu, Boris

2010-01-01

An operational definition offered in this paper posits learning as a multi-dimensional and multi-phase phenomenon occurring when individuals attempt to solve what they view as a problem. To model someone's learning accordingly to the definition, it suffices to characterize a particular sequence of that person's disequilibrium-equilibrium phases in…

The Thinking-about-Derivative Test for Undergraduate Students: Development and Validation

ERIC Educational Resources Information Center

Aydin, Utkun; Ubuz, Behiye

2015-01-01

Two studies were conducted for the development and validation of a multidimensional test to assess undergraduate students' mathematical thinking about derivative. The first study involved two phases: question generation and refinement of the Thinking-about-Derivative Test (TDT). The second study included four phases as follows: test…

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.

Development and Application of Methods for Estimating Operating Characteristics of Discrete Test Item Responses without Assuming any Mathematical Form.

ERIC Educational Resources Information Center

Samejima, Fumiko

In latent trait theory the latent space, or space of the hypothetical construct, is usually represented by some unidimensional or multi-dimensional continuum of real numbers. Like the latent space, the item response can either be treated as a discrete variable or as a continuous variable. Latent trait theory relates the item response to the latent…

Initiating heavy-atom-based phasing by multi-dimensional molecular replacement.

PubMed

Pedersen, Bjørn Panyella; Gourdon, Pontus; Liu, Xiangyu; Karlsen, Jesper Lykkegaard; Nissen, Poul

2016-03-01

To obtain an electron-density map from a macromolecular crystal the phase problem needs to be solved, which often involves the use of heavy-atom derivative crystals and concomitant heavy-atom substructure determination. This is typically performed by dual-space methods, direct methods or Patterson-based approaches, which however may fail when only poorly diffracting derivative crystals are available. This is often the case for, for example, membrane proteins. Here, an approach for heavy-atom site identification based on a molecular-replacement parameter matrix (MRPM) is presented. It involves an n-dimensional search to test a wide spectrum of molecular-replacement parameters, such as different data sets and search models with different conformations. Results are scored by the ability to identify heavy-atom positions from anomalous difference Fourier maps. The strategy was successfully applied in the determination of a membrane-protein structure, the copper-transporting P-type ATPase CopA, when other methods had failed to determine the heavy-atom substructure. MRPM is well suited to proteins undergoing large conformational changes where multiple search models should be considered, and it enables the identification of weak but correct molecular-replacement solutions with maximum contrast to prime experimental phasing efforts.

Initiating heavy-atom-based phasing by multi-dimensional molecular replacement

PubMed Central

Pedersen, Bjørn Panyella; Gourdon, Pontus; Liu, Xiangyu; Karlsen, Jesper Lykkegaard; Nissen, Poul

2016-01-01

To obtain an electron-density map from a macromolecular crystal the phase problem needs to be solved, which often involves the use of heavy-atom derivative crystals and concomitant heavy-atom substructure determination. This is typically performed by dual-space methods, direct methods or Patterson-based approaches, which however may fail when only poorly diffracting derivative crystals are available. This is often the case for, for example, membrane proteins. Here, an approach for heavy-atom site identification based on a molecular-replacement parameter matrix (MRPM) is presented. It involves an n-dimensional search to test a wide spectrum of molecular-replacement parameters, such as different data sets and search models with different conformations. Results are scored by the ability to identify heavy-atom positions from anomalous difference Fourier maps. The strategy was successfully applied in the determination of a membrane-protein structure, the copper-transporting P-type ATPase CopA, when other methods had failed to determine the heavy-atom substructure. MRPM is well suited to proteins undergoing large conformational changes where multiple search models should be considered, and it enables the identification of weak but correct molecular-replacement solutions with maximum contrast to prime experimental phasing efforts. PMID:26960131

Alfvén simple waves

NASA Astrophysics Data System (ADS)

Webb, G. M.; Zank, G. P.; Burrows, R. H.; Ratkiewicz, R. E.

2011-02-01

Multi-dimensional Alfvén simple waves in magnetohydrodynamics (MHD) are investigated using Boillat's formalism. For simple wave solutions, all physical variables (the gas density, pressure, fluid velocity, entropy, and magnetic field induction in the MHD case) depend on a single phase function ϕ, which is a function of the space and time variables. The simple wave ansatz requires that the wave normal and the normal speed of the wave front depend only on the phase function ϕ. This leads to an implicit equation for the phase function and a generalization of the concept of a plane wave. We obtain examples of Alfvén simple waves, based on the right eigenvector solutions for the Alfvén mode. The Alfvén mode solutions have six integrals, namely that the entropy, density, magnetic pressure, and the group velocity (the sum of the Alfvén and fluid velocity) are constant throughout the wave. The eigenequations require that the rate of change of the magnetic induction B with ϕ throughout the wave is perpendicular to both the wave normal n and B. Methods to construct simple wave solutions based on specifying either a solution ansatz for n(ϕ) or B(ϕ) are developed.

Alfven Simple Waves

NASA Astrophysics Data System (ADS)

Webb, G. M.; Zank, G. P.; Burrows, R.

2009-12-01

Multi-dimensional Alfvén simple waves in magnetohydrodynamics (MHD) are investigated using Boillat's formalism. For simple wave solutions, all physical variables (the gas density, pressure, fluid velocity, entropy, and magnetic field induction in the MHD case) depend on a single phase function ǎrphi which is a function of the space and time variables. The simple wave ansatz requires that the wave normal and the normal speed of the wave front depend only on the phase function ǎrphi. This leads to an implicit equation for the phase function, and a generalisation of the concept of a plane wave. We obtain examples of Alfvén simple waves, based on the right eigenvector solutions for the Alfvén mode. The Alfvén mode solutions have six integrals, namely that the entropy, density, magnetic pressure and the group velocity (the sum of the Alfvén and fluid velocity) are constant throughout the wave. The eigen-equations require that the rate of change of the magnetic induction B with ǎrphi throughout the wave is perpendicular to both the wave normal n and B. Methods to construct simple wave solutions based on specifying either a solution ansatz for n(ǎrphi) or B(ǎrphi) are developed.

Subjective evaluation with FAA criteria: A multidimensional scaling approach. [ground track control management

NASA Technical Reports Server (NTRS)

Kreifeldt, J. G.; Parkin, L.; Wempe, T. E.; Huff, E. F.

1975-01-01

Perceived orderliness in the ground tracks of five A/C during their simulated flights was studied. Dynamically developing ground tracks for five A/C from 21 separate runs were reproduced from computer storage and displayed on CRTS to professional pilots and controllers for their evaluations and preferences under several criteria. The ground tracks were developed in 20 seconds as opposed to the 5 minutes of simulated flight using speedup techniques for display. Metric and nonmetric multidimensional scaling techniques are being used to analyze the subjective responses in an effort to: (1) determine the meaningfulness of basing decisions on such complex subjective criteria; (2) compare pilot/controller perceptual spaces; (3) determine the dimensionality of the subjects' perceptual spaces; and thereby (4) determine objective measures suitable for comparing alternative traffic management simulations.

Multidimensional electron beam-plasma instabilities in the relativistic regime

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

Bret, A.; Gremillet, L.; Dieckmann, M. E.

2010-12-15

The interest in relativistic beam-plasma instabilities has been greatly rejuvenated over the past two decades by novel concepts in laboratory and space plasmas. Recent advances in this long-standing field are here reviewed from both theoretical and numerical points of view. The primary focus is on the two-dimensional spectrum of unstable electromagnetic waves growing within relativistic, unmagnetized, and uniform electron beam-plasma systems. Although the goal is to provide a unified picture of all instability classes at play, emphasis is put on the potentially dominant waves propagating obliquely to the beam direction, which have received little attention over the years. First, themore » basic derivation of the general dielectric function of a kinetic relativistic plasma is recalled. Next, an overview of two-dimensional unstable spectra associated with various beam-plasma distribution functions is given. Both cold-fluid and kinetic linear theory results are reported, the latter being based on waterbag and Maxwell-Juettner model distributions. The main properties of the competing modes (developing parallel, transverse, and oblique to the beam) are given, and their respective region of dominance in the system parameter space is explained. Later sections address particle-in-cell numerical simulations and the nonlinear evolution of multidimensional beam-plasma systems. The elementary structures generated by the various instability classes are first discussed in the case of reduced-geometry systems. Validation of linear theory is then illustrated in detail for large-scale systems, as is the multistaged character of the nonlinear phase. Finally, a collection of closely related beam-plasma problems involving additional physical effects is presented, and worthwhile directions of future research are outlined.« less

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.

Trajectories of Smooth: The Multidimensionality of Spatial Relations and Autism Spectrum

ERIC Educational Resources Information Center

Reddington, Sarah; Price, Deborah

2017-01-01

This paper examines how two men with autism spectrum (AS) experience educational spaces having attended public school in Nova Scotia, Canada. Smooth and striated space is mobilised as the main conceptual framework to account for the men's affectivities when experiencing the educational terrain. The central aim when applying smooth and striated…

Invisible and Hypervisible Academics: The Experiences of Black and Minority Ethnic Teacher Educators

ERIC Educational Resources Information Center

Lander, Vini; Santoro, Ninetta

2017-01-01

This qualitative study investigated the experiences of Black and Minority Ethnic (BME) teacher educators in England and Australia working within the predominantly white space of the academy. Data analysis was informed by a multidimensional theoretical framework drawing on Critical Race Theory, whiteness and Puwar's concept of the Space Invader.…

The effects of context on multidimensional spatial cognitive models. Ph.D. Thesis - Arizona Univ.

NASA Technical Reports Server (NTRS)

Dupnick, E. G.

1979-01-01

Spatial cognitive models obtained by multidimensional scaling represent cognitive structure by defining alternatives as points in a coordinate space based on relevant dimensions such that interstimulus dissimilarities perceived by the individual correspond to distances between the respective alternatives. The dependence of spatial models on the context of the judgments required of the individual was investigated. Context, which is defined as a perceptual interpretation and cognitive understanding of a judgment situation, was analyzed and classified with respect to five characteristics: physical environment, social environment, task definition, individual perspective, and temporal setting. Four experiments designed to produce changes in the characteristics of context and to test the effects of these changes upon individual cognitive spaces are described with focus on experiment design, objectives, statistical analysis, results, and conclusions. The hypothesis is advanced that an individual can be characterized as having a master cognitive space for a set of alternatives. When the context changes, the individual appears to change the dimension weights to give a new spatial configuration. Factor analysis was used in the interpretation and labeling of cognitive space dimensions.

Multidimensional quantitative analysis of mRNA expression within intact vertebrate embryos.

PubMed

Trivedi, Vikas; Choi, Harry M T; Fraser, Scott E; Pierce, Niles A

2018-01-08

For decades, in situ hybridization methods have been essential tools for studies of vertebrate development and disease, as they enable qualitative analyses of mRNA expression in an anatomical context. Quantitative mRNA analyses typically sacrifice the anatomy, relying on embryo microdissection, dissociation, cell sorting and/or homogenization. Here, we eliminate the trade-off between quantitation and anatomical context, using quantitative in situ hybridization chain reaction (qHCR) to perform accurate and precise relative quantitation of mRNA expression with subcellular resolution within whole-mount vertebrate embryos. Gene expression can be queried in two directions: read-out from anatomical space to expression space reveals co-expression relationships in selected regions of the specimen; conversely, read-in from multidimensional expression space to anatomical space reveals those anatomical locations in which selected gene co-expression relationships occur. As we demonstrate by examining gene circuits underlying somitogenesis, quantitative read-out and read-in analyses provide the strengths of flow cytometry expression analyses, but by preserving subcellular anatomical context, they enable bi-directional queries that open a new era for in situ hybridization. © 2018. Published by The Company of Biologists Ltd.

The organization of conspecific face space in nonhuman primates

PubMed Central

Parr, Lisa A.; Taubert, Jessica; Little, Anthony C.; Hancock, Peter J. B.

2013-01-01

Humans and chimpanzees demonstrate numerous cognitive specializations for processing faces, but comparative studies with monkeys suggest that these may be the result of recent evolutionary adaptations. The present study utilized the novel approach of face space, a powerful theoretical framework used to understand the representation of face identity in humans, to further explore species differences in face processing. According to the theory, faces are represented by vectors in a multidimensional space, the centre of which is defined by an average face. Each dimension codes features important for describing a face’s identity, and vector length codes the feature’s distinctiveness. Chimpanzees and rhesus monkeys discriminated male and female conspecifics’ faces, rated by humans for their distinctiveness, using a computerized task. Multidimensional scaling analyses showed that the organization of face space was similar between humans and chimpanzees. Distinctive faces had the longest vectors and were the easiest for chimpanzees to discriminate. In contrast, distinctiveness did not correlate with the performance of rhesus monkeys. The feature dimensions for each species’ face space were visualized and described using morphing techniques. These results confirm species differences in the perceptual representation of conspecific faces, which are discussed within an evolutionary framework. PMID:22670823

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.

Subdimensions of Adolescent Belonging in High School

ERIC Educational Resources Information Center

Wallace, Tanner LeBaron; Ye, Feifei; Chhuon, Vichet

2012-01-01

Adolescents' sense of belonging in high school may serve a protective function, linking school-based relationships to positive youth outcomes. To advance the study of sense of belonging, we conducted a mixed method, factor analytic study (Phase 1 focus groups, N = 72; Phase 2 cross-sectional survey, N = 890) to explore the multidimensionality of…

A General Formulation for Robust and Efficient Integration of Finite Differences and Phase Unwrapping on Sparse Multidimensional Domains

NASA Astrophysics Data System (ADS)

Costantini, Mario; Malvarosa, Fabio; Minati, Federico

2010-03-01

Phase unwrapping and integration of finite differences are key problems in several technical fields. In SAR interferometry and differential and persistent scatterers interferometry digital elevation models and displacement measurements can be obtained after unambiguously determining the phase values and reconstructing the mean velocities and elevations of the observed targets, which can be performed by integrating differential estimates of these quantities (finite differences between neighboring points).In this paper we propose a general formulation for robust and efficient integration of finite differences and phase unwrapping, which includes standard techniques methods as sub-cases. The proposed approach allows obtaining more reliable and accurate solutions by exploiting redundant differential estimates (not only between nearest neighboring points) and multi-dimensional information (e.g. multi-temporal, multi-frequency, multi-baseline observations), or external data (e.g. GPS measurements). The proposed approach requires the solution of linear or quadratic programming problems, for which computationally efficient algorithms exist.The validation tests obtained on real SAR data confirm the validity of the method, which was integrated in our production chain and successfully used also in massive productions.

Imaging nanoscale lattice variations by machine learning of x-ray diffraction microscopy data

DOE PAGES

Laanait, Nouamane; Zhang, Zhan; Schlepütz, Christian M.

2016-08-09

In this paper, we present a novel methodology based on machine learning to extract lattice variations in crystalline materials, at the nanoscale, from an x-ray Bragg diffraction-based imaging technique. By employing a full-field microscopy setup, we capture real space images of materials, with imaging contrast determined solely by the x-ray diffracted signal. The data sets that emanate from this imaging technique are a hybrid of real space information (image spatial support) and reciprocal lattice space information (image contrast), and are intrinsically multidimensional (5D). By a judicious application of established unsupervised machine learning techniques and multivariate analysis to this multidimensional datamore » cube, we show how to extract features that can be ascribed physical interpretations in terms of common structural distortions, such as lattice tilts and dislocation arrays. Finally, we demonstrate this 'big data' approach to x-ray diffraction microscopy by identifying structural defects present in an epitaxial ferroelectric thin-film of lead zirconate titanate.« less

Imaging nanoscale lattice variations by machine learning of x-ray diffraction microscopy data

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

Laanait, Nouamane; Zhang, Zhan; Schlepütz, Christian M.

In this paper, we present a novel methodology based on machine learning to extract lattice variations in crystalline materials, at the nanoscale, from an x-ray Bragg diffraction-based imaging technique. By employing a full-field microscopy setup, we capture real space images of materials, with imaging contrast determined solely by the x-ray diffracted signal. The data sets that emanate from this imaging technique are a hybrid of real space information (image spatial support) and reciprocal lattice space information (image contrast), and are intrinsically multidimensional (5D). By a judicious application of established unsupervised machine learning techniques and multivariate analysis to this multidimensional datamore » cube, we show how to extract features that can be ascribed physical interpretations in terms of common structural distortions, such as lattice tilts and dislocation arrays. Finally, we demonstrate this 'big data' approach to x-ray diffraction microscopy by identifying structural defects present in an epitaxial ferroelectric thin-film of lead zirconate titanate.« less

Multidimensional Space-Time Methodology for Development of Planetary and Space Sciences, S-T Data Management and S-T Computational Tomography

NASA Astrophysics Data System (ADS)

Andonov, Zdravko

This R&D represent innovative multidimensional 6D-N(6n)D Space-Time (S-T) Methodology, 6D-6nD Coordinate Systems, 6D Equations, new 6D strategy and technology for development of Planetary Space Sciences, S-T Data Management and S-T Computational To-mography. . . The Methodology is actual for brain new RS Microwaves' Satellites and Compu-tational Tomography Systems development, aimed to defense sustainable Earth, Moon, & Sun System evolution. Especially, extremely important are innovations for monitoring and protec-tion of strategic threelateral system H-OH-H2O Hydrogen, Hydroxyl and Water), correspond-ing to RS VHRS (Very High Resolution Systems) of 1.420-1.657-22.089GHz microwaves. . . One of the Greatest Paradox and Challenge of World Science is the "transformation" of J. L. Lagrange 4D Space-Time (S-T) System to H. Minkovski 4D S-T System (O-X,Y,Z,icT) for Einstein's "Theory of Relativity". As a global result: -In contemporary Advanced Space Sciences there is not real adequate 4D-6D Space-Time Coordinate System and 6D Advanced Cosmos Strategy & Methodology for Multidimensional and Multitemporal Space-Time Data Management and Tomography. . . That's one of the top actual S-T Problems. Simple and optimal nD S-T Methodology discovery is extremely important for all Universities' Space Sci-ences' Education Programs, for advances in space research and especially -for all young Space Scientists R&D!... The top ten 21-Century Challenges ahead of Planetary and Space Sciences, Space Data Management and Computational Space Tomography, important for successfully de-velopment of Young Scientist Generations, are following: 1. R&D of W. R. Hamilton General Idea for transformation all Space Sciences to Time Sciences, beginning with 6D Eukonal for 6D anisotropic mediums & velocities. Development of IERS Earth & Space Systems (VLBI; LLR; GPS; SLR; DORIS Etc.) for Planetary-Space Data Management & Computational Planetary & Space Tomography. 2. R&D of S. W. Hawking Paradigm for 2D Complex Time and Quan-tum Wave Cosmology Paradigm for Decision of the Main Problem of Contemporary Physics. 3. R&D of Einstein-Minkowski Geodesies' Paradigm in the 4D-Space-Time Continuum to 6D-6nD Space-Time Continuum Paradigms and 6D S-T Equations. . . 4. R&D of Erwin Schrüdinger 4D S-T Universe' Evolutional Equation; It's David Bohm 4D generalization for anisotropic mediums and innovative 6D -for instantaneously quantum measurement -Bohm-Schrüdinger 6D S-T Universe' Evolutional Equation. 5. R&D of brain new 6D Planning of S-T Experi-ments, brain new 6D Space Technicks and Space Technology Generalizations, especially for 6D RS VHRS Research, Monitoring and 6D Computational Tomography. 6. R&D of "6D Euler-Poisson Equations" and "6D Kolmogorov Turbulence Theory" for GeoDynamics and for Space Dynamics as evolution of Gauss-Riemann Paradigms. 7. R&D of N. Boneff NASA RD for Asteroid "Eros" & Space Science' Laws Evolution. 8. R&D of H. Poincare Paradigm for Nature and Cosmos as 6D Group of Transferences. 9. R&D of K. Popoff N-Body General Problem & General Thermodynamic S-T Theory as Einstein-Prigogine-Landau' Paradigms Development. ü 10. R&D of 1st GUT since 1958 by N. S. Kalitzin (Kalitzin N. S., 1958: Uber eine einheitliche Feldtheorie. ZAHeidelberg-ARI, WZHUmnR-B., 7 (2), 207-215) and "Multitemporal Theory of Relativity" -With special applications to Photon Rockets and all Space-Time R&D. GENERAL CONCLUSION: Multidimensional Space-Time Methodology is advance in space research, corresponding to the IAF-IAA-COSPAR Innovative Strategy and R&D Programs -UNEP, UNDP, GEOSS, GMES, Etc.

Modeling of convection phenomena in Bridgman-Stockbarger crystal growth

NASA Technical Reports Server (NTRS)

Carlson, F. M.; Eraslan, A. H.; Sheu, J. Z.

1985-01-01

Thermal convection phenomena in a vertically oriented Bridgman-Stockbarger apparatus were modeled by computer simulations for different gravity conditions, ranging from earth conditions to extremely low gravity, approximate space conditions. The modeling results were obtained by the application of a state-of-the art, transient, multi-dimensional, completely densimetrically coupled, discrete-element computational model which was specifically developed for the simulation of flow, temperature, and species concentration conditions in two-phase (solid-liquid) systems. The computational model was applied to the simulation of the flow and the thermal conditions associated with the convection phenomena in a modified Germanium-Silicon charge enclosed in a stationary fused-silica ampoule. The results clearly indicated that the gravitational field strength influences the characteristics of the coherent vortical flow patterns, interface shape and position, maximum melt velocity, and interfacial normal temperature gradient.

Two-dimensional numerical simulation of a Stirling engine heat exchanger

NASA Technical Reports Server (NTRS)

Ibrahim, Mounir; Tew, Roy C.; Dudenhoefer, James E.

1989-01-01

The first phase of an effort to develop multidimensional models of Stirling engine components is described. The ultimate goal is to model an entire engine working space. Parallel plate and tubular heat exchanger models are described, with emphasis on the central part of the channel (i.e., ignoring hydrodynamic and thermal end effects). The model assumes laminar, incompressible flow with constant thermophysical properties. In addition, a constant axial temperature gradient is imposed. The governing equations describing the model have been solved using the Crack-Nicloson finite-difference scheme. Model predictions are compared with analytical solutions for oscillating/reversing flow and heat transfer in order to check numerical accuracy. Excellent agreement is obtained for flow both in circular tubes and between parallel plates. The computational heat transfer results are in good agreement with the analytical heat transfer results for parallel plates.

Using Virtual Worlds to Identify Multidimensional Student Engagement in High School Foreign Language Learning Classrooms

ERIC Educational Resources Information Center

Jacob, Laura Beth

2012-01-01

Virtual world environments have evolved from object-oriented, text-based online games to complex three-dimensional immersive social spaces where the lines between reality and computer-generated begin to blur. Educators use virtual worlds to create engaging three-dimensional learning spaces for students, but the impact of virtual worlds in…

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.

Quasicrystals and Quantum Computing

NASA Astrophysics Data System (ADS)

Berezin, Alexander A.

1997-03-01

In Quantum (Q) Computing qubits form Q-superpositions for macroscopic times. One scheme for ultra-fast (Q) computing can be based on quasicrystals. Ultrafast processing in Q-coherent structures (and the very existence of durable Q-superpositions) may be 'consequence' of presence of entire manifold of integer arithmetic (A0, aleph-naught of Georg Cantor) at any 4-point of space-time, furthermore, at any point of any multidimensional phase space of (any) N-particle Q-system. The latter, apart from quasicrystals, can include dispersed and/or diluted systems (Berezin, 1994). In such systems such alleged centrepieces of Q-Computing as ability for fast factorization of long integers can be processed by sheer virtue of the fact that entire infinite pattern of prime numbers is instantaneously available as 'free lunch' at any instant/point. Infinitely rich pattern of A0 (including pattern of primes and almost primes) acts as 'independent' physical effect which directly generates Q-dynamics (and physical world) 'out of nothing'. Thus Q-nonlocality can be ultimately based on instantaneous interconnectedness through ever- the-same structure of A0 ('Platonic field' of integers).

Multidimensional Trellis Coded Phase Modulation Using a Multilevel Concatenation Approach. Part 2; Codes for AWGN and Fading Channels

NASA Technical Reports Server (NTRS)

Rajpal, Sandeep; Rhee, DoJun; Lin, Shu

1997-01-01

In this paper, we will use the construction technique proposed in to construct multidimensional trellis coded modulation (TCM) codes for both the additive white Gaussian noise (AWGN) and the fading channels. Analytical performance bounds and simulation results show that these codes perform very well and achieve significant coding gains over uncoded reference modulation systems. In addition, the proposed technique can be used to construct codes which have a performance/decoding complexity advantage over the codes listed in literature.

Selective Data Acquisition in NMR. The Quantification of Anti-phase Scalar Couplings

NASA Astrophysics Data System (ADS)

Hodgkinson, P.; Holmes, K. J.; Hore, P. J.

Almost all time-domain NMR experiments employ "linear sampling," in which the NMR response is digitized at equally spaced times, with uniform signal averaging. Here, the possibilities of nonlinear sampling are explored using anti-phase doublets in the indirectly detected dimensions of multidimensional COSY-type experiments as an example. The Cramér-Rao lower bounds are used to evaluate and optimize experiments in which the sampling points, or the extent of signal averaging at each point, or both, are varied. The optimal nonlinear sampling for the estimation of the coupling constant J, by model fitting, turns out to involve just a few key time points, for example, at the first node ( t= 1/ J) of the sin(π Jt) modulation. Such sparse sampling patterns can be used to derive more practical strategies, in which the sampling or the signal averaging is distributed around the most significant time points. The improvements in the quantification of NMR parameters can be quite substantial especially when, as is often the case for indirectly detected dimensions, the total number of samples is limited by the time available.

Ultrasonic attenuation and phase velocity of high-density polyethylene pipe material.

PubMed

Egerton, J S; Lowe, M J S; Huthwaite, P; Halai, H V

2017-03-01

Knowledge of acoustic properties is crucial for ultrasonic or sonic imaging and signal detection in nondestructive evaluation (NDE), medical imaging, and seismology. Accurately and reliably obtaining these is particularly challenging for the NDE of high-density polyethylene (HDPE), such as is used in many water or gas pipes, because the properties vary greatly with frequency, temperature, direction and spatial location. Therefore the work reported here was undertaken in order to establish a basis for such a multiparameter description. The approach is general but the study specifically addresses HDPE and includes measured data values. Applicable to any such multiparameter acoustic properties dataset is a devised regression method that uses a neural network algorithm. This algorithm includes constraints to respect the Kramers-Kronig causality relationship between speed and attenuation of waves in a viscoelastic medium. These constrained acoustic properties are fully described in a multidimensional parameter space to vary with frequency, depth, temperature, and direction. The resulting uncertainties in acoustic properties dependence on the above variables are better than 4% and 2%, respectively, for attenuation and phase velocity and therefore can prevent major defect imaging errors.

Integrated multidimensional and comprehensive 2D GC analysis of fatty acid methyl esters.

PubMed

Zeng, Annie Xu; Chin, Sung-Tong; Marriott, Philip J

2013-03-01

Fatty acid methyl ester (FAME) profiling in complex fish oil and milk fat samples was studied using integrated comprehensive 2D GC (GC × GC) and multidimensional GC (MDGC). Using GC × GC, FAME compounds--cis- and trans-isomers, and essential fatty acid isomers--ranging from C18 to C22 in fish oil and C18 in milk fat were clearly displayed in contour plot format according to structural properties and patterns, further identified based on authentic standards. Incompletely resolved regions were subjected to MDGC, with Cn (n = 18, 20) zones transferred to a (2)D column. Elution behavior of C18 FAME on various (2)D column phases (ionic liquids IL111, IL100, IL76, and modified PEG) was evaluated. Individual isolated Cn zones demonstrated about four-fold increased peak capacities. The IL100 provided superior separation, good peak shape, and utilization of elution space. For milk fat-derived FAME, the (2)D chromatogram revealed at least three peaks corresponding to C18:1, more than six peaks for cis/trans-C18:2 isomers, and two peaks for C18:3. More than 17 peaks were obtained for the C20 region of fish oil-derived FAMEs using MDGC, compared with ten peaks using GC × GC. The MDGC strategy is useful for improved FAME isomer separation and confirmation. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Spectral Eclipse Timing

NASA Astrophysics Data System (ADS)

Dobbs-Dixon, Ian; Agol, Eric; Deming, Drake

2015-12-01

We utilize multi-dimensional simulations of varying equatorial jet strength to predict wavelength-dependent variations in the eclipse times of gas-giant planets. A displaced hot spot introduces an asymmetry in the secondary eclipse light curve that manifests itself as a measured offset in the timing of the center of eclipse. A multi-wavelength observation of secondary eclipse, one probing the timing of barycentric eclipse at short wavelengths and another probing at longer wavelengths, will reveal the longitudinal displacement of the hot spot and break the degeneracy between this effect and that associated with the asymmetry due to an eccentric orbit. The effect of time offsets was first explored in the IRAC wavebands by Williams et al. Here we improve upon their methodology, extend to a broad range of wavelengths, and demonstrate our technique on a series of multi-dimensional radiative-hydrodynamical simulations of HD 209458b with varying equatorial jet strength and hot-spot displacement. Simulations with the largest hot-spot displacement result in timing offsets of up to 100 s in the infrared. Though we utilize a particular radiative hydrodynamical model to demonstrate this effect, the technique is model independent. This technique should allow a much larger survey of hot-spot displacements with the James Webb Space Telescope than currently accessible with time-intensive phase curves, hopefully shedding light on the physical mechanisms associated with thermal energy advection in irradiated gas giants.

A second-order cell-centered Lagrangian ADER-MOOD finite volume scheme on multidimensional unstructured meshes for hydrodynamics

NASA Astrophysics Data System (ADS)

Boscheri, Walter; Dumbser, Michael; Loubère, Raphaël; Maire, Pierre-Henri

2018-04-01

In this paper we develop a conservative cell-centered Lagrangian finite volume scheme for the solution of the hydrodynamics equations on unstructured multidimensional grids. The method is derived from the Eucclhyd scheme discussed in [47,43,45]. It is second-order accurate in space and is combined with the a posteriori Multidimensional Optimal Order Detection (MOOD) limiting strategy to ensure robustness and stability at shock waves. Second-order of accuracy in time is achieved via the ADER (Arbitrary high order schemes using DERivatives) approach. A large set of numerical test cases is proposed to assess the ability of the method to achieve effective second order of accuracy on smooth flows, maintaining an essentially non-oscillatory behavior on discontinuous profiles, general robustness ensuring physical admissibility of the numerical solution, and precision where appropriate.

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.

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.

Random phase detection in multidimensional NMR.

PubMed

Maciejewski, Mark W; Fenwick, Matthew; Schuyler, Adam D; Stern, Alan S; Gorbatyuk, Vitaliy; Hoch, Jeffrey C

2011-10-04

Despite advances in resolution accompanying the development of high-field superconducting magnets, biomolecular applications of NMR require multiple dimensions in order to resolve individual resonances, and the achievable resolution is typically limited by practical constraints on measuring time. In addition to the need for measuring long evolution times to obtain high resolution, the need to distinguish the sign of the frequency constrains the ability to shorten measuring times. Sign discrimination is typically accomplished by sampling the signal with two different receiver phases or by selecting a reference frequency outside the range of frequencies spanned by the signal and then sampling at a higher rate. In the parametrically sampled (indirect) time dimensions of multidimensional NMR experiments, either method imposes an additional factor of 2 sampling burden for each dimension. We demonstrate that by using a single detector phase at each time sample point, but randomly altering the phase for different points, the sign ambiguity that attends fixed single-phase detection is resolved. Random phase detection enables a reduction in experiment time by a factor of 2 for each indirect dimension, amounting to a factor of 8 for a four-dimensional experiment, albeit at the cost of introducing sampling artifacts. Alternatively, for fixed measuring time, random phase detection can be used to double resolution in each indirect dimension. Random phase detection is complementary to nonuniform sampling methods, and their combination offers the potential for additional benefits. In addition to applications in biomolecular NMR, random phase detection could be useful in magnetic resonance imaging and other signal processing contexts.

Task-specific stability in muscle activation space during unintentional movements.

PubMed

Falaki, Ali; Towhidkhah, Farzad; Zhou, Tao; Latash, Mark L

2014-11-01

We used robot-generated perturbations applied during position-holding tasks to explore stability of induced unintentional movements in a multidimensional space of muscle activations. Healthy subjects held the handle of a robot against a constant bias force and were instructed not to interfere with hand movements produced by changes in the external force. Transient force changes were applied leading to handle displacement away from the initial position and then back toward the initial position. Intertrial variance in the space of muscle modes (eigenvectors in the muscle activations space) was quantified within two subspaces, corresponding to unchanged handle coordinate and to changes in the handle coordinate. Most variance was confined to the former subspace in each of the three phases of movement, the initial steady state, the intermediate position, and the final steady state. The same result was found when the changes in muscle activation were analyzed between the initial and final steady states. Changes in the dwell time between the perturbation force application and removal led to different final hand locations undershooting the initial position. The magnitude of the undershot scaled with the dwell time, while the structure of variance in the muscle activation space did not depend on the dwell time. We conclude that stability of the hand coordinate is ensured during both intentional and unintentional actions via similar mechanisms. Relative equifinality in the external space after transient perturbations may be associated with varying states in the redundant space of muscle activations. The results fit a hierarchical scheme for the control of voluntary movements with referent configurations and redundant mapping between the levels of the hierarchy.

Two-dimensional Manifold with Point-like Defects

NASA Astrophysics Data System (ADS)

Gani, V. A.; Dmitriev, A. E.; Rubin, S. G.

We study a class of two-dimensional compact extra spaces isomorphic to the sphere S 2 in the framework of multidimensional gravitation. We show that there exists a family of stationary metrics that depend on the initial (boundary) conditions. All these geometries have a singular point. We also discuss the possibility for these deformed extra spaces to be considered as dark matter candidates.

Studying Relational Spaces in Secondary School: Applying a Spatial Framework for the Study of Borderlands and Relational Work in School Improvement Processes

ERIC Educational Resources Information Center

Frelin, Anneli; Grannäs, Jan

2014-01-01

This article introduces a theoretical framework for studying school improvement processes such as making school environments safer. Using concepts from spatial theory, in which distinctions between mental, social and physical space are applied makes for a multidimensional analysis of processes of change. In a multilevel case study, these were…

Multidimensionally encoded magnetic resonance imaging.

PubMed

Lin, Fa-Hsuan

2013-07-01

Magnetic resonance imaging (MRI) typically achieves spatial encoding by measuring the projection of a q-dimensional object over q-dimensional spatial bases created by linear spatial encoding magnetic fields (SEMs). Recently, imaging strategies using nonlinear SEMs have demonstrated potential advantages for reconstructing images with higher spatiotemporal resolution and reducing peripheral nerve stimulation. In practice, nonlinear SEMs and linear SEMs can be used jointly to further improve the image reconstruction performance. Here, we propose the multidimensionally encoded (MDE) MRI to map a q-dimensional object onto a p-dimensional encoding space where p > q. MDE MRI is a theoretical framework linking imaging strategies using linear and nonlinear SEMs. Using a system of eight surface SEM coils with an eight-channel radiofrequency coil array, we demonstrate the five-dimensional MDE MRI for a two-dimensional object as a further generalization of PatLoc imaging and O-space imaging. We also present a method of optimizing spatial bases in MDE MRI. Results show that MDE MRI with a higher dimensional encoding space can reconstruct images more efficiently and with a smaller reconstruction error when the k-space sampling distribution and the number of samples are controlled. Copyright © 2012 Wiley Periodicals, Inc.

MM-MDS: a multidimensional scaling database with similarity ratings for 240 object categories from the Massive Memory picture database.

PubMed

Hout, Michael C; Goldinger, Stephen D; Brady, Kyle J

2014-01-01

Cognitive theories in visual attention and perception, categorization, and memory often critically rely on concepts of similarity among objects, and empirically require measures of "sameness" among their stimuli. For instance, a researcher may require similarity estimates among multiple exemplars of a target category in visual search, or targets and lures in recognition memory. Quantifying similarity, however, is challenging when everyday items are the desired stimulus set, particularly when researchers require several different pictures from the same category. In this article, we document a new multidimensional scaling database with similarity ratings for 240 categories, each containing color photographs of 16-17 exemplar objects. We collected similarity ratings using the spatial arrangement method. Reports include: the multidimensional scaling solutions for each category, up to five dimensions, stress and fit measures, coordinate locations for each stimulus, and two new classifications. For each picture, we categorized the item's prototypicality, indexed by its proximity to other items in the space. We also classified pairs of images along a continuum of similarity, by assessing the overall arrangement of each MDS space. These similarity ratings will be useful to any researcher that wishes to control the similarity of experimental stimuli according to an objective quantification of "sameness."

Structural diversity: a multi-dimensional approach to assess recreational services in urban parks.

PubMed

Voigt, Annette; Kabisch, Nadja; Wurster, Daniel; Haase, Dagmar; Breuste, Jürgen

2014-05-01

Urban green spaces provide important recreational services for urban residents. In general, when park visitors enjoy "the green," they are in actuality appreciating a mix of biotic, abiotic, and man-made park infrastructure elements and qualities. We argue that these three dimensions of structural diversity have an influence on how people use and value urban parks. We present a straightforward approach for assessing urban parks that combines multi-dimensional landscape mapping and questionnaire surveys. We discuss the method as well the results from its application to differently sized parks in Berlin and Salzburg.

Systems and Methods for Data Visualization Using Three-Dimensional Displays

NASA Technical Reports Server (NTRS)

Davidoff, Scott (Inventor); Djorgovski, Stanislav G. (Inventor); Estrada, Vicente (Inventor); Donalek, Ciro (Inventor)

2017-01-01

Data visualization systems and methods for generating 3D visualizations of a multidimensional data space are described. In one embodiment a 3D data visualization application directs a processing system to: load a set of multidimensional data points into a visualization table; create representations of a set of 3D objects corresponding to the set of data points; receive mappings of data dimensions to visualization attributes; determine the visualization attributes of the set of 3D objects based upon the selected mappings of data dimensions to 3D object attributes; update a visibility dimension in the visualization table for each of the plurality of 3D object to reflect the visibility of each 3D object based upon the selected mappings of data dimensions to visualization attributes; and interactively render 3D data visualizations of the 3D objects within the virtual space from viewpoints determined based upon received user input.

Density-functional theory computer simulations of CZTS0.25Se0.75 alloy phase diagrams

NASA Astrophysics Data System (ADS)

Chagarov, E.; Sardashti, K.; Haight, R.; Mitzi, D. B.; Kummel, A. C.

2016-08-01

Density-functional theory simulations of CZTS, CZTSe, and CZTS0.25Se0.75 photovoltaic compounds have been performed to investigate the stability of the CZTS0.25Se0.75 alloy vs. decomposition into CZTS, CZTSe, and other secondary compounds. The Gibbs energy for vibrational contributions was estimated by calculating phonon spectra and thermodynamic properties at finite temperatures. It was demonstrated that the CZTS0.25Se0.75 alloy is stabilized not by enthalpy of formation but primarily by the mixing contributions to the Gibbs energy. The Gibbs energy gains/losses for several decomposition reactions were calculated as a function of temperature with/without intermixing and vibration contributions to the Gibbs energy. A set of phase diagrams was built in the multidimensional space of chemical potentials at 300 K and 900 K temperatures to demonstrate alloy stability and boundary compounds at various chemical conditions. It demonstrated for CZTS0.25Se0.75 that the chemical potentials for stability differ between typical processing temperature (˜900 K) and operating temperature (300 K). This implies that as cooling progresses, the flux/concentration of S should be increased in MBE growth to maintain the CZTS0.25Se0.75 in a thermodynamically stable state to minimize phase decomposition.

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.

Variational calculation of macrostate transition rates

NASA Astrophysics Data System (ADS)

Ulitsky, Alex; Shalloway, David

1998-08-01

We develop the macrostate variational method (MVM) for computing reaction rates of diffusive conformational transitions in multidimensional systems by a variational coarse-grained "macrostate" decomposition of the Smoluchowski equation. MVM uses multidimensional Gaussian packets to identify and focus computational effort on the "transition region," a localized, self-consistently determined region in conformational space positioned roughly between the macrostates. It also determines the "transition direction" which optimally specifies the projected potential of mean force for mean first-passage time calculations. MVM is complementary to variational transition state theory in that it can efficiently solve multidimensional problems but does not accommodate memory-friction effects. It has been tested on model 1- and 2-dimensional potentials and on the 12-dimensional conformational transition between the isoforms of a microcluster of six-atoms having only van der Waals interactions. Comparison with Brownian dynamics calculations shows that MVM obtains equivalent results at a fraction of the computational cost.

Behavioural hypervolumes of spider communities predict community performance and disbandment

PubMed Central

Sih, Andrew; DiRienzo, Nicholas; Pinter-Wollman, Noa

2016-01-01

Trait-based ecology argues that an understanding of the traits of interactors can enhance the predictability of ecological outcomes. We examine here whether the multidimensional behavioural-trait diversity of communities influences community performance and stability in situ. We created experimental communities of web-building spiders, each with an identical species composition. Communities contained one individual of each of five different species. Prior to establishing these communities in the field, we examined three behavioural traits for each individual spider. These behavioural measures allowed us to estimate community-wide behavioural diversity, as inferred by the multidimensional behavioural volume occupied by the entire community. Communities that occupied a larger region of behavioural-trait space (i.e. where spiders differed more from each other behaviourally) gained more mass and were less likely to disband. Thus, there is a community-wide benefit to multidimensional behavioural diversity in this system that might translate to other multispecies assemblages. PMID:27974515

A Machine Learns to Predict the Stability of Tightly Packed Planetary Systems

NASA Astrophysics Data System (ADS)

Tamayo, Daniel; Silburt, Ari; Valencia, Diana; Menou, Kristen; Ali-Dib, Mohamad; Petrovich, Cristobal; Huang, Chelsea X.; Rein, Hanno; van Laerhoven, Christa; Paradise, Adiv; Obertas, Alysa; Murray, Norman

2016-12-01

The requirement that planetary systems be dynamically stable is often used to vet new discoveries or set limits on unconstrained masses or orbital elements. This is typically carried out via computationally expensive N-body simulations. We show that characterizing the complicated and multi-dimensional stability boundary of tightly packed systems is amenable to machine-learning methods. We find that training an XGBoost machine-learning algorithm on physically motivated features yields an accurate classifier of stability in packed systems. On the stability timescale investigated (107 orbits), it is three orders of magnitude faster than direct N-body simulations. Optimized machine-learning classifiers for dynamical stability may thus prove useful across the discipline, e.g., to characterize the exoplanet sample discovered by the upcoming Transiting Exoplanet Survey Satellite. This proof of concept motivates investing computational resources to train algorithms capable of predicting stability over longer timescales and over broader regions of phase space.

Two-dimensional numerical simulation of a Stirling engine heat exchanger

NASA Technical Reports Server (NTRS)

Ibrahim, Mounir B.; Tew, Roy C.; Dudenhoefer, James E.

1989-01-01

The first phase of an effort to develop multidimensional models of Stirling engine components is described; the ultimate goal is to model an entire engine working space. More specifically, parallel plate and tubular heat exchanger models with emphasis on the central part of the channel (i.e., ignoring hydrodynamic and thermal end effects) are described. The model assumes: laminar, incompressible flow with constant thermophysical properties. In addition, a constant axial temperature gradient is imposed. The governing equations, describing the model, were solved using Crank-Nicloson finite-difference scheme. Model predictions were compared with analytical solutions for oscillating/reversing flow and heat transfer in order to check numerical accuracy. Excellent agreement was obtained for the model predictions with analytical solutions available for both flow in circular tubes and between parallel plates. Also the heat transfer computational results are in good agreement with the heat transfer analytical results for parallel plates.

McSnow: A Monte-Carlo Particle Model for Riming and Aggregation of Ice Particles in a Multidimensional Microphysical Phase Space

NASA Astrophysics Data System (ADS)

Brdar, S.; Seifert, A.

2018-01-01

We present a novel Monte-Carlo ice microphysics model, McSnow, to simulate the evolution of ice particles due to deposition, aggregation, riming, and sedimentation. The model is an application and extension of the super-droplet method of Shima et al. (2009) to the more complex problem of rimed ice particles and aggregates. For each individual super-particle, the ice mass, rime mass, rime volume, and the number of monomers are predicted establishing a four-dimensional particle-size distribution. The sensitivity of the model to various assumptions is discussed based on box model and one-dimensional simulations. We show that the Monte-Carlo method provides a feasible approach to tackle this high-dimensional problem. The largest uncertainty seems to be related to the treatment of the riming processes. This calls for additional field and laboratory measurements of partially rimed snowflakes.

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).

Using a multidimensional unfolding approach to assess multiple sclerosis patient preferences for disease-modifying therapy: a pilot study

PubMed Central

Sempere, Angel Perez; Vera-Lopez, Vanesa; Gimenez-Martinez, Juana; Ruiz-Beato, Elena; Cuervo, Jesús; Maurino, Jorge

2017-01-01

Purpose Multidimensional unfolding is a multivariate method to assess preferences using a small sample size, a geometric model locating individuals and alternatives as points in a joint space. The objective was to evaluate relapsing–remitting multiple sclerosis (RRMS) patient preferences toward key disease-modifying therapy (DMT) attributes using multidimensional unfolding. Patients and methods A cross-sectional pilot study in RRMS patients was conducted. Drug attributes included relapse prevention, disease progression prevention, side-effect risk and route and schedule of administration. Assessment of preferences was performed through a five-card game. Patients were asked to value attributes from 1 (most preferred) to 5 (least preferred). Results A total of 37 patients were included; the mean age was 38.6 years, and 78.4% were female. Disease progression prevention was the most important factor (51.4%), followed by relapse prevention (40.5%). The frequency of administration had the lowest preference rating for 56.8% of patients. Finally, 19.6% valued the side-effect risk attribute as having low/very low importance. Conclusion Patients’ perspective for DMT attributes may provide valuable information to facilitate shared decision-making. Efficacy attributes were the most important drug characteristics for RRMS patients. Multidimensional unfolding seems to be a feasible approach to assess preferences in multiple sclerosis patients. Further elicitation studies using multidimensional unfolding with other stated choice methods are necessary to confirm these findings. PMID:28615928

An advanced process-based distributed model for the investigation of rainfall-induced landslides: The effect of process representation and boundary conditions

NASA Astrophysics Data System (ADS)

Anagnostopoulos, Grigorios G.; Fatichi, Simone; Burlando, Paolo

2015-09-01

Extreme rainfall events are the major driver of shallow landslide occurrences in mountainous and steep terrain regions around the world. Subsurface hydrology has a dominant role on the initiation of rainfall-induced shallow landslides, since changes in the soil water content affect significantly the soil shear strength. Rainfall infiltration produces an increase of soil water potential, which is followed by a rapid drop in apparent cohesion. Especially on steep slopes of shallow soils, this loss of shear strength can lead to failure even in unsaturated conditions before positive water pressures are developed. We present HYDROlisthisis, a process-based model, fully distributed in space with fine time resolution, in order to investigate the interactions between surface and subsurface hydrology and shallow landslides initiation. Fundamental elements of the approach are the dependence of shear strength on the three-dimensional (3-D) field of soil water potential, as well as the temporal evolution of soil water potential during the wetting and drying phases. Specifically, 3-D variably saturated flow conditions, including soil hydraulic hysteresis and preferential flow phenomena, are simulated for the subsurface flow, coupled with a surface runoff routine based on the kinematic wave approximation. 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. A series of numerical simulations were carried out with various boundary conditions and using different hydrological and geotechnical components. Boundary conditions in terms of distributed soil depth were generated using both empirical and process-based models. The effect of including preferential flow and soil hydraulic hysteresis was tested together with the replacement of the infinite slope assumption with the multidimensional limit equilibrium analysis. 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) significantly improve predictive capabilities in the presented case study.

Multi-Dimensional Scaling based grouping of known complexes and intelligent protein complex detection.

PubMed

Rehman, Zia Ur; Idris, Adnan; Khan, Asifullah

2018-06-01

Protein-Protein Interactions (PPI) play a vital role in cellular processes and are formed because of thousands of interactions among proteins. Advancements in proteomics technologies have resulted in huge PPI datasets that need to be systematically analyzed. Protein complexes are the locally dense regions in PPI networks, which extend important role in metabolic pathways and gene regulation. In this work, a novel two-phase protein complex detection and grouping mechanism is proposed. In the first phase, topological and biological features are extracted for each complex, and prediction performance is investigated using Bagging based Ensemble classifier (PCD-BEns). Performance evaluation through cross validation shows improvement in comparison to CDIP, MCode, CFinder and PLSMC methods Second phase employs Multi-Dimensional Scaling (MDS) for the grouping of known complexes by exploring inter complex relations. It is experimentally observed that the combination of topological and biological features in the proposed approach has greatly enhanced prediction performance for protein complex detection, which may help to understand various biological processes, whereas application of MDS based exploration may assist in grouping potentially similar complexes. Copyright © 2018 Elsevier Ltd. All rights reserved.

Scientific Visualization of Radio Astronomy Data using Gesture Interaction

NASA Astrophysics Data System (ADS)

Mulumba, P.; Gain, J.; Marais, P.; Woudt, P.

2015-09-01

MeerKAT in South Africa (Meer = More Karoo Array Telescope) will require software to help visualize, interpret and interact with multidimensional data. While visualization of multi-dimensional data is a well explored topic, little work has been published on the design of intuitive interfaces to such systems. More specifically, the use of non-traditional interfaces (such as motion tracking and multi-touch) has not been widely investigated within the context of visualizing astronomy data. We hypothesize that a natural user interface would allow for easier data exploration which would in turn lead to certain kinds of visualizations (volumetric, multidimensional). To this end, we have developed a multi-platform scientific visualization system for FITS spectral data cubes using VTK (Visualization Toolkit) and a natural user interface to explore the interaction between a gesture input device and multidimensional data space. Our system supports visual transformations (translation, rotation and scaling) as well as sub-volume extraction and arbitrary slicing of 3D volumetric data. These tasks were implemented across three prototypes aimed at exploring different interaction strategies: standard (mouse/keyboard) interaction, volumetric gesture tracking (Leap Motion controller) and multi-touch interaction (multi-touch monitor). A Heuristic Evaluation revealed that the volumetric gesture tracking prototype shows great promise for interfacing with the depth component (z-axis) of 3D volumetric space across multiple transformations. However, this is limited by users needing to remember the required gestures. In comparison, the touch-based gesture navigation is typically more familiar to users as these gestures were engineered from standard multi-touch actions. Future work will address a complete usability test to evaluate and compare the different interaction modalities against the different visualization tasks.

Phase stabilization of multidimensional amplification architectures for ultrashort pulses

NASA Astrophysics Data System (ADS)

Müller, M.; Kienel, M.; Klenke, A.; Eidam, T.; Limpert, J.; Tünnermann, A.

2015-03-01

The active phase stabilization of spatially and temporally combined ultrashort pulses is investigated theoretically and experimentally. Particularly, considering a combining scheme applying 2 amplifier channels and 4 divided-pulse replicas a bistable behavior is observed. The reason is mutual influence of the optical error signals that is intrinsic to temporal polarization beam combining. A successful mitigation strategy is proposed and is analyzed theoretically and experimentally.

Phase coupling in the cardiorespiratory interaction.

PubMed

Bahraminasab, A; Kenwright, D; Stefanovska, A; Ghasemi, F; McClintock, P V E

2008-01-01

Markovian analysis is applied to derive nonlinear stochastic equations for the reconstruction of heart rate and respiration rate variability data. A model of their 'phase' interactions is obtained for the first time, thereby gaining new insights into the strength and direction of the cardiorespiratory phase coupling. The reconstructed model can reproduce synchronisation phenomena between the cardiac and the respiratory systems, including switches in synchronisation ratio. The technique is equally applicable to the extraction of the multi-dimensional couplings between many interacting subsystems.

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.

Fully adaptive propagation of the quantum-classical Liouville equation

NASA Astrophysics Data System (ADS)

Horenko, Illia; Weiser, Martin; Schmidt, Burkhard; Schütte, Christof

2004-05-01

In mixed quantum-classical molecular dynamics few but important degrees of freedom of a dynamical system are modeled quantum-mechanically while the remaining ones are treated within the classical approximation. Rothe methods established in the theory of partial differential equations are used to control both temporal and spatial discretization errors on grounds of a global tolerance criterion. The TRAIL (trapezoidal rule for adaptive integration of Liouville dynamics) scheme [I. Horenko and M. Weiser, J. Comput. Chem. 24, 1921 (2003)] has been extended to account for nonadiabatic effects in molecular dynamics described by the quantum-classical Liouville equation. In the context of particle methods, the quality of the spatial approximation of the phase-space distributions is maximized while the numerical condition of the least-squares problem for the parameters of particles is minimized. The resulting dynamical scheme is based on a simultaneous propagation of moving particles (Gaussian and Dirac deltalike trajectories) in phase space employing a fully adaptive strategy to upgrade Dirac to Gaussian particles and, vice versa, downgrading Gaussians to Dirac-type trajectories. This allows for the combination of Monte-Carlo-based strategies for the sampling of densities and coherences in multidimensional problems with deterministic treatment of nonadiabatic effects. Numerical examples demonstrate the application of the method to spin-boson systems in different dimensionality. Nonadiabatic effects occurring at conical intersections are treated in the diabatic representation. By decreasing the global tolerance, the numerical solution obtained from the TRAIL scheme are shown to converge towards exact results.

Fully adaptive propagation of the quantum-classical Liouville equation.

PubMed

Horenko, Illia; Weiser, Martin; Schmidt, Burkhard; Schütte, Christof

2004-05-15

In mixed quantum-classical molecular dynamics few but important degrees of freedom of a dynamical system are modeled quantum-mechanically while the remaining ones are treated within the classical approximation. Rothe methods established in the theory of partial differential equations are used to control both temporal and spatial discretization errors on grounds of a global tolerance criterion. The TRAIL (trapezoidal rule for adaptive integration of Liouville dynamics) scheme [I. Horenko and M. Weiser, J. Comput. Chem. 24, 1921 (2003)] has been extended to account for nonadiabatic effects in molecular dynamics described by the quantum-classical Liouville equation. In the context of particle methods, the quality of the spatial approximation of the phase-space distributions is maximized while the numerical condition of the least-squares problem for the parameters of particles is minimized. The resulting dynamical scheme is based on a simultaneous propagation of moving particles (Gaussian and Dirac deltalike trajectories) in phase space employing a fully adaptive strategy to upgrade Dirac to Gaussian particles and, vice versa, downgrading Gaussians to Dirac-type trajectories. This allows for the combination of Monte-Carlo-based strategies for the sampling of densities and coherences in multidimensional problems with deterministic treatment of nonadiabatic effects. Numerical examples demonstrate the application of the method to spin-boson systems in different dimensionality. Nonadiabatic effects occurring at conical intersections are treated in the diabatic representation. By decreasing the global tolerance, the numerical solution obtained from the TRAIL scheme are shown to converge towards exact results.

Trajectories and traversal times in quantum tunneling

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

Huang, Zhi Hong.

1989-01-01

The classical concepts of trajectories and traversal times applied to quantum tunneling are discussed. By using the Wentzel-Kramers-Brillouin approximation, it is found that in a forbidden region of a multidimensional space the wave function can be described by two sets of trajectories, or equivalently by two sets of wave fronts. The trajectories belonging to different sets are mutually orthogonal. An extended Huygens construction is proposed to determine these wave fronts and trajectories. In contrast to the classical results in the allowed region, these trajectories couple to each other. However, if the incident wave is normal to the turning surface, themore » trajectories are found to be independent and can be determined by Newton's equations of motion with inverted potential and energy. The multidimensional tunneling theory is then applied to the scanning tunneling microscope to calculate the current density distribution and to derive the expressions for the lateral resolution and the surface corrugation amplitude. The traversal time in quantum tunneling, i.e. tunneling time, is found to depend on model calculations and simulations. Computer simulation of a wave packet tunneling through a square barrier is performed. Several approaches, including the phase method, Larmor clock, and time-dependent barrier model, are investigated. For a square barrier, two characteristic times are found: One is equal to the barrier width divided by the magnitude of the imaginary velocity; the other is equal to the decay length divided by the incident velocity. It is believed that the tunneling time can only be defined operationally.« less

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.

Entropy production due to gravitational-wave viscosity in a Kaluza-Klein inflationary universe

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

Tomita, K.; Ishihara, H.

1985-10-15

The role of viscosity due to the transport of gravitational radiation in a Kaluza-Klein multidimensional universe is considered, and it is shown that vast entropy may be produced by it owing to inflation of the external (ordinary) space and collapse of the internal (compact) space. The inflation and collapse factors necessary for increasing the total entropy by a factor approx.10/sup 88/ are derived.

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...

A New Approach to Monte Carlo Simulations in Statistical Physics

NASA Astrophysics Data System (ADS)

Landau, David P.

2002-08-01

Monte Carlo simulations [1] have become a powerful tool for the study of diverse problems in statistical/condensed matter physics. Standard methods sample the probability distribution for the states of the system, most often in the canonical ensemble, and over the past several decades enormous improvements have been made in performance. Nonetheless, difficulties arise near phase transitions-due to critical slowing down near 2nd order transitions and to metastability near 1st order transitions, and these complications limit the applicability of the method. We shall describe a new Monte Carlo approach [2] that uses a random walk in energy space to determine the density of states directly. Once the density of states is known, all thermodynamic properties can be calculated. This approach can be extended to multi-dimensional parameter spaces and should be effective for systems with complex energy landscapes, e.g., spin glasses, protein folding models, etc. Generalizations should produce a broadly applicable optimization tool. 1. A Guide to Monte Carlo Simulations in Statistical Physics, D. P. Landau and K. Binder (Cambridge U. Press, Cambridge, 2000). 2. Fugao Wang and D. P. Landau, Phys. Rev. Lett. 86, 2050 (2001); Phys. Rev. E64, 056101-1 (2001).

Curvilinear component analysis: a self-organizing neural network for nonlinear mapping of data sets.

PubMed

Demartines, P; Herault, J

1997-01-01

We present a new strategy called "curvilinear component analysis" (CCA) for dimensionality reduction and representation of multidimensional data sets. The principle of CCA is a self-organized neural network performing two tasks: vector quantization (VQ) of the submanifold in the data set (input space); and nonlinear projection (P) of these quantizing vectors toward an output space, providing a revealing unfolding of the submanifold. After learning, the network has the ability to continuously map any new point from one space into another: forward mapping of new points in the input space, or backward mapping of an arbitrary position in the output space.

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.

Nonlinear optical cryptosystem based on joint Fresnel transform correlator under vector wave illumination

NASA Astrophysics Data System (ADS)

Xueju, Shen; Chao, Lin; Xiao, Zou; Jianjun, Cai

2015-05-01

We present a nonlinear optical cryptosystem with multi-dimensional keys including phase, polarization and diffraction distance. To make full use of the degrees of freedom that optical processing offers, an elaborately designed vector wave with both a space-variant phase and locally linear polarization is generated with a common-path interferometer for illumination. The joint transform correlator in the Fresnel domain, implemented with a double optical wedge, is utilized as the encryption framework which provides an additional key known as the Fresnel diffraction distance. Two nonlinear operations imposed on the recorded joint Fresnel power distribution (JFPD) by a charge coupled device (CCD) are adopted. The first one is the division of power distribution of the reference window random function which is previously proposed by researchers and can improve the quality of the decrypted image. The second one is the recording of a hybrid JFPD using a micro-polarizers array with orthogonal and random transmissive axes attached to the CCD. Then the hybrid JFPD is further scrambled by substituting random noise for partial power distribution. The two nonlinear operations break the linearity of this cryptosystem and provide ultra security. We verify our proposal using a quick response code for noise-free recovery.

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

Noncollinear wave mixing of attosecond XUV and few-cycle optical laser pulses in gas-phase atoms: Toward multidimensional spectroscopy involving XUV excitations

NASA Astrophysics Data System (ADS)

Cao, Wei; Warrick, Erika R.; Fidler, Ashley; Neumark, Daniel M.; Leone, Stephen R.

2016-11-01

Ultrafast nonlinear spectroscopy, which records transient wave-mixing signals in a medium, is a powerful tool to access microscopic information using light sources in the radio-frequency and optical regimes. The extension of this technique towards the extreme ultraviolet (XUV) or even x-ray regimes holds the promise to uncover rich structural or dynamical information with even higher spatial or temporal resolution. Here, we demonstrate noncollinear wave mixing between weak XUV attosecond pulses and a strong near-infrared (NIR) few-cycle laser pulse in gas phase atoms (one photon of XUV and two photons of NIR). In the noncollinear geometry the attosecond and either one or two NIR pulses interact with argon atoms. Nonlinear XUV signals are generated in a spatially resolved fashion as required by phase matching. Different transition pathways can be identified from these background-free nonlinear signals according to the specific phase-matching conditions. Time-resolved measurements of the spatially gated XUV signals reveal electronic coherences of Rydberg wave packets prepared by a single XUV photon or XUV-NIR two-photon excitation, depending on the applied pulse sequences. These measurements open possible applications of tabletop multidimensional spectroscopy to the study of dynamics associated with valence or core excitation with XUV photons.

Dynamic Cross-Entropy.

PubMed

Aur, Dorian; Vila-Rodriguez, Fidel

2017-01-01

Complexity measures for time series have been used in many applications to quantify the regularity of one dimensional time series, however many dynamical systems are spatially distributed multidimensional systems. We introduced Dynamic Cross-Entropy (DCE) a novel multidimensional complexity measure that quantifies the degree of regularity of EEG signals in selected frequency bands. Time series generated by discrete logistic equations with varying control parameter r are used to test DCE measures. Sliding window DCE analyses are able to reveal specific period doubling bifurcations that lead to chaos. A similar behavior can be observed in seizures triggered by electroconvulsive therapy (ECT). Sample entropy data show the level of signal complexity in different phases of the ictal ECT. The transition to irregular activity is preceded by the occurrence of cyclic regular behavior. A significant increase of DCE values in successive order from high frequencies in gamma to low frequencies in delta band reveals several phase transitions into less ordered states, possible chaos in the human brain. To our knowledge there are no reliable techniques able to reveal the transition to chaos in case of multidimensional times series. In addition, DCE based on sample entropy appears to be robust to EEG artifacts compared to DCE based on Shannon entropy. The applied technique may offer new approaches to better understand nonlinear brain activity. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Tensor-Train Split-Operator Fourier Transform (TT-SOFT) Method: Multidimensional Nonadiabatic Quantum Dynamics.

PubMed

Greene, Samuel M; Batista, Victor S

2017-09-12

We introduce the "tensor-train split-operator Fourier transform" (TT-SOFT) method for simulations of multidimensional nonadiabatic quantum dynamics. TT-SOFT is essentially the grid-based SOFT method implemented in dynamically adaptive tensor-train representations. In the same spirit of all matrix product states, the tensor-train format enables the representation, propagation, and computation of observables of multidimensional wave functions in terms of the grid-based wavepacket tensor components, bypassing the need of actually computing the wave function in its full-rank tensor product grid space. We demonstrate the accuracy and efficiency of the TT-SOFT method as applied to propagation of 24-dimensional wave packets, describing the S 1 /S 2 interconversion dynamics of pyrazine after UV photoexcitation to the S 2 state. Our results show that the TT-SOFT method is a powerful computational approach for simulations of quantum dynamics of polyatomic systems since it avoids the exponential scaling problem of full-rank grid-based representations.

Robustness of multidimensional Brownian ratchets as directed transport mechanisms.

PubMed

González-Candela, Ernesto; Romero-Rochín, Víctor; Del Río, Fernando

2011-08-07

Brownian ratchets have recently been considered as models to describe the ability of certain systems to locate very specific states in multidimensional configuration spaces. This directional process has particularly been proposed as an alternative explanation for the protein folding problem, in which the polypeptide is driven toward the native state by a multidimensional Brownian ratchet. Recognizing the relevance of robustness in biological systems, in this work we analyze such a property of Brownian ratchets by pushing to the limits all the properties considered essential to produce directed transport. Based on the results presented here, we can state that Brownian ratchets are able to deliver current and locate funnel structures under a wide range of conditions. As a result, they represent a simple model that solves the Levinthal's paradox with great robustness and flexibility and without requiring any ad hoc biased transition probability. The behavior of Brownian ratchets shown in this article considerably enhances the plausibility of the model for at least part of the structural mechanism behind protein folding process.

Multistability inspired by the oblique, pennate architectures of skeletal muscle

NASA Astrophysics Data System (ADS)

Kidambi, Narayanan; Harne, Ryan L.; Wang, K. W.

2017-04-01

Skeletal muscle mechanics exhibit a range of noteworthy characteristics, providing great inspiration for the development of advanced structural and material systems. These characteristics arise from the synergies demonstrated between muscle's constituents across the various length scales. From the macroscale oblique orientation of muscle fibers to the microscale lattice spacing of sarcomeres, muscle takes advantage of geometries and multidimensionality for force generation or length change along a desired axis. Inspired by these behaviors, this research investigates how the incorporation of multidimensionality afforded by oblique, pennate architectures can uncover novel mechanics in structures exhibiting multistability. Experimental investigation of these mechanics is undertaken using specimens of molded silicone rubber with patterned voids, and results reveal tailorable mono-, bi-, and multi-stability under axial displacements by modulation of transverse confinement. If the specimen is considered as an architected material, these results show its ability to generate intriguing, non-monotonic shear stresses. The outcomes would foster the development of novel, advanced mechanical metamaterials that exploit pennation and multidimensionality.

Experimental Study on the Perception Characteristics of Haptic Texture by Multidimensional Scaling.

PubMed

Wu, Juan; Li, Na; Liu, Wei; Song, Guangming; Zhang, Jun

2015-01-01

Recent works regarding real texture perception demonstrate that physical factors such as stiffness and spatial period play a fundamental role in texture perception. This research used a multidimensional scaling (MDS) analysis to further characterize and quantify the effects of the simulation parameters on haptic texture rendering and perception. In a pilot experiment, 12 haptic texture samples were generated by using a 3-degrees-of-freedom (3-DOF) force-feedback device with varying spatial period, height, and stiffness coefficient parameter values. The subjects' perceptions of the virtual textures indicate that roughness, denseness, flatness and hardness are distinguishing characteristics of texture. In the main experiment, 19 participants rated the dissimilarities of the textures and estimated the magnitudes of their characteristics. The MDS method was used to recover the underlying perceptual space and reveal the significance of the space from the recorded data. The physical parameters and their combinations have significant effects on the perceptual characteristics. A regression model was used to quantitatively analyze the parameters and their effects on the perceptual characteristics. This paper is to illustrate that haptic texture perception based on force feedback can be modeled in two- or three-dimensional space and provide suggestions on improving perception-based haptic texture rendering.

Data Visualization in Information Retrieval and Data Mining (SIG VIS).

ERIC Educational Resources Information Center

Efthimiadis, Efthimis

2000-01-01

Presents abstracts that discuss using data visualization for information retrieval and data mining, including immersive information space and spatial metaphors; spatial data using multi-dimensional matrices with maps; TREC (Text Retrieval Conference) experiments; users' information needs in cartographic information retrieval; and users' relevance…

Defining and Differentiating the Makerspace

ERIC Educational Resources Information Center

Dousay, Tonia A.

2017-01-01

Many resources now punctuate the maker movement landscape. However, some schools and communities still struggle to understand this burgeoning movement. How do we define these spaces and differentiate them from previous labs and shops? Through a multidimensional framework, stakeholders should consider how the structure, access, staffing, and tools…

A Computational Model of Multidimensional Shape

PubMed Central

Liu, Xiuwen; Shi, Yonggang; Dinov, Ivo

2010-01-01

We develop a computational model of shape that extends existing Riemannian models of curves to multidimensional objects of general topological type. We construct shape spaces equipped with geodesic metrics that measure how costly it is to interpolate two shapes through elastic deformations. The model employs a representation of shape based on the discrete exterior derivative of parametrizations over a finite simplicial complex. We develop algorithms to calculate geodesics and geodesic distances, as well as tools to quantify local shape similarities and contrasts, thus obtaining a formulation that accounts for regional differences and integrates them into a global measure of dissimilarity. The Riemannian shape spaces provide a common framework to treat numerous problems such as the statistical modeling of shapes, the comparison of shapes associated with different individuals or groups, and modeling and simulation of shape dynamics. We give multiple examples of geodesic interpolations and illustrations of the use of the models in brain mapping, particularly, the analysis of anatomical variation based on neuroimaging data. PMID:21057668

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.

A multidimensional analysis of the epistemic origins of nursing theories, models, and frameworks.

PubMed

Beckstead, Jason W; Beckstead, Laura Grace

2006-01-01

The purpose of this article is to introduce our notion of epistemic space and to demonstrate its utility for understanding the origins and trajectories of nursing theory in the 20th century using multidimensional scaling (MDS). A literature review was conducted on primary and secondary sources written by and about 20 nurse theorists to investigate whether or not they cited 129 different scholars in the fields of anthropology, biology, nursing, philosophy, psychology, and sociology. Seventy-four scholars were identified as having been cited by at least two nurse theorists (319 citations total). Proximity scores, quantifying the similarity among nurse theorists based on proportions of shared citations, were calculated and analyzed using MDS. The emergent model of epistemic space that accommodated these similarities among nurse theorists revealed the systematic influence of scholars from various fields, notably psychology, biology, and philosophy. We believe that this schema and resulting taxonomy will prove useful for furthering our understanding of the relationships among nursing theories and theories in other fields of science.

Density-functional theory computer simulations of CZTS{sub 0.25}Se{sub 0.75} alloy phase diagrams

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

Chagarov, E.; Sardashti, K.; Kummel, A. C.

2016-08-14

Density-functional theory simulations of CZTS, CZTSe, and CZTS{sub 0.25}Se{sub 0.75} photovoltaic compounds have been performed to investigate the stability of the CZTS{sub 0.25}Se{sub 0.75} alloy vs. decomposition into CZTS, CZTSe, and other secondary compounds. The Gibbs energy for vibrational contributions was estimated by calculating phonon spectra and thermodynamic properties at finite temperatures. It was demonstrated that the CZTS{sub 0.25}Se{sub 0.75} alloy is stabilized not by enthalpy of formation but primarily by the mixing contributions to the Gibbs energy. The Gibbs energy gains/losses for several decomposition reactions were calculated as a function of temperature with/without intermixing and vibration contributions to themore » Gibbs energy. A set of phase diagrams was built in the multidimensional space of chemical potentials at 300 K and 900 K temperatures to demonstrate alloy stability and boundary compounds at various chemical conditions. It demonstrated for CZTS{sub 0.25}Se{sub 0.75} that the chemical potentials for stability differ between typical processing temperature (∼900 K) and operating temperature (300 K). This implies that as cooling progresses, the flux/concentration of S should be increased in MBE growth to maintain the CZTS{sub 0.25}Se{sub 0.75} in a thermodynamically stable state to minimize phase decomposition.« less

Capillary trap column with strong cation-exchange monolith for automated shotgun proteome analysis.

PubMed

Wang, Fangjun; Dong, Jing; Jiang, Xiaogang; Ye, Mingliang; Zou, Hanfa

2007-09-01

A 150 microm internal diameter capillary monolithic column with a strong cation-exchange stationary phase was prepared by direct in situ polymerization of ethylene glycol methacrylate phosphate and bisacrylamide in a trinary porogenic solvent consisting dimethylsulfoxide, dodecanol, and N,N'-dimethylformamide. This phosphate monolithic column exhibits higher dynamic binding capacity, faster kinetic adsorption of peptides, and more than 10 times higher permeability than the column packed with commercially available strong cation-exchange particles. It was applied as a trap column in a nanoflow liquid chromatography-tandem mass spectrometry system for automated sample injection and online multidimensional separation. It was observed that the sample could be loaded at a flow rate as high as 40 microL/min with a back pressure of approximately 1300 psi and without compromising the separation efficiency. Because of its good orthogonality to the reversed phase separation mechanism, the phosphate monolithic trap column was coupled with a reversed-phase column for online multidimensional separation of 19 microg of the tryptic digest of yeast proteins. A total of 1522 distinct proteins were identified from 5608 unique peptides (total of 54,780 peptides) at the false positive rate only 0.46%.

Coherent multi-dimensional spectroscopy at optical frequencies in a single beam with optical readout

NASA Astrophysics Data System (ADS)

Seiler, Hélène; Palato, Samuel; Kambhampati, Patanjali

2017-09-01

Ultrafast coherent multi-dimensional spectroscopies form a powerful set of techniques to unravel complex processes, ranging from light-harvesting, chemical exchange in biological systems to many-body interactions in quantum-confined materials. Yet these spectroscopies remain complex to implement at the high frequencies of vibrational and electronic transitions, thereby limiting their widespread use. Here we demonstrate the feasibility of two-dimensional spectroscopy at optical frequencies in a single beam. Femtosecond optical pulses are spectrally broadened to a relevant bandwidth and subsequently shaped into phase coherent pulse trains. By suitably modulating the phases of the pulses within the beam, we show that it is possible to directly read out the relevant optical signals. This work shows that one needs neither complex beam geometries nor complex detection schemes in order to measure two-dimensional spectra at optical frequencies. Our setup provides not only a simplified experimental design over standard two-dimensional spectrometers but its optical readout also enables novel applications in microscopy.

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.

The Structure of Integral Dimensions: Contrasting Topological and Cartesian Representations

ERIC Educational Resources Information Center

Jones, Matt; Goldstone, Robert L.

2013-01-01

Diverse evidence shows that perceptually integral dimensions, such as those composing color, are represented holistically. However, the nature of these holistic representations is poorly understood. Extant theories, such as those founded on multidimensional scaling or general recognition theory, model integral stimulus spaces using a Cartesian…

A Re-Unification of Two Competing Models for Document Retrieval.

ERIC Educational Resources Information Center

Bodoff, David

1999-01-01

Examines query-oriented versus document-oriented information retrieval and feedback learning. Highlights include a reunification of the two approaches for probabilistic document retrieval and for vector space model (VSM) retrieval; learning in VSM and in probabilistic models; multi-dimensional scaling; and ongoing field studies. (LRW)

Synthesis of Joint Volumes, Visualization of Paths, and Revision of Viewing Sequences in a Multi-dimensional Seismic Data Viewer

NASA Astrophysics Data System (ADS)

Chen, D. M.; Clapp, R. G.; Biondi, B.

2006-12-01

Ricksep is a freely-available interactive viewer for multi-dimensional data sets. The viewer is very useful for simultaneous display of multiple data sets from different viewing angles, animation of movement along a path through the data space, and selection of local regions for data processing and information extraction. Several new viewing features are added to enhance the program's functionality in the following three aspects. First, two new data synthesis algorithms are created to adaptively combine information from a data set with mostly high-frequency content, such as seismic data, and another data set with mainly low-frequency content, such as velocity data. Using the algorithms, these two data sets can be synthesized into a single data set which resembles the high-frequency data set on a local scale and at the same time resembles the low- frequency data set on a larger scale. As a result, the originally separated high and low-frequency details can now be more accurately and conveniently studied together. Second, a projection algorithm is developed to display paths through the data space. Paths are geophysically important because they represent wells into the ground. Two difficulties often associated with tracking paths are that they normally cannot be seen clearly inside multi-dimensional spaces and depth information is lost along the direction of projection when ordinary projection techniques are used. The new algorithm projects samples along the path in three orthogonal directions and effectively restores important depth information by using variable projection parameters which are functions of the distance away from the path. Multiple paths in the data space can be generated using different character symbols as positional markers, and users can easily create, modify, and view paths in real time. Third, a viewing history list is implemented which enables Ricksep's users to create, edit and save a recipe for the sequence of viewing states. Then, the recipe can be loaded into an active Ricksep session, after which the user can navigate to any state in the sequence and modify the sequence from that state. Typical uses of this feature are undoing and redoing viewing commands and animating a sequence of viewing states. The theoretical discussion are carried out and several examples using real seismic data are provided to show how these new Ricksep features provide more convenient, accurate ways to manipulate multi-dimensional data sets.

Modeling Age-Related Differences in Immediate Memory Using SIMPLE

ERIC Educational Resources Information Center

Surprenant, Aimee M.; Neath, Ian; Brown, Gordon D. A.

2006-01-01

In the SIMPLE model (Scale Invariant Memory and Perceptual Learning), performance on memory tasks is determined by the locations of items in multidimensional space, and better performance is associated with having fewer close neighbors. Unlike most previous simulations with SIMPLE, the ones reported here used measured, rather than assumed,…

Multi-Dimensional Optimization for Cloud Based Multi-Tier Applications

ERIC Educational Resources Information Center

Jung, Gueyoung

2010-01-01

Emerging trends toward cloud computing and virtualization have been opening new avenues to meet enormous demands of space, resource utilization, and energy efficiency in modern data centers. By being allowed to host many multi-tier applications in consolidated environments, cloud infrastructure providers enable resources to be shared among these…

Discovering Middle Space: Distinctions of Sex and Gender in Resilient Leadership

ERIC Educational Resources Information Center

Christman, Dana E.; McClellan, Rhonda L.

2012-01-01

This study contrasts findings from two Delphi studies that investigated how women and men who are higher education academic administrators in educational leadership programs and colleges define and describe resiliency in their leadership. Using gender theories, both studies revealed a multidimensional gendering of leadership, a gendering more…

Visual reconciliation of alternative similarity spaces in climate modeling

Treesearch

J Poco; A Dasgupta; Y Wei; William Hargrove; C.R. Schwalm; D.N. Huntzinger; R Cook; E Bertini; C.T. Silva

2015-01-01

Visual data analysis often requires grouping of data objects based on their similarity. In many application domains researchers use algorithms and techniques like clustering and multidimensional scaling to extract groupings from data. While extracting these groups using a single similarity criteria is relatively straightforward, comparing alternative criteria poses...

Multi-Dimensional Perception of Parental Involvement

ERIC Educational Resources Information Center

Fisher, Yael

2016-01-01

The main purpose of this study was to define and conceptualize the term parental involvement. A questionnaire was administrated to parents (140), teachers (145), students (120) and high ranking civil servants in the Ministry of Education (30). Responses were analyzed through Smallest Space Analysis (SSA). The SSA solution among all groups rendered…

Using Visual Information to Determine the Subjective Valuation of Public Space for Transportation : Application to Subway Crowding Costs in NYC

DOT National Transportation Integrated Search

2017-11-30

The objective of this project is to explore the role of visual information in determining the users subjective valuation of multidimensional trip attributes that are relevant in decision-making, but are neglected in standard travel demand models. ...

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.

The "Why" of Learning

ERIC Educational Resources Information Center

Geary, David C.

2009-01-01

Alexander, Schallert, and Reynolds's (2009/this issue) "what," "where," "who," and "when" framework situates different perspectives on learning in different places in this multidimensional space and by doing so helps us to better understand seemingly disparate approaches to learning. The framework is in need of a fifth, "why" dimension. The "why"…

"Pedagogy of Third Space": A Multidimensional Early Childhood Curriculum

ERIC Educational Resources Information Center

Gupta, Amita

2015-01-01

This paper will illustrate how philosophical and pedagogical boundaries that are defined by diverse cultures and ideologies might be navigated in the practical implementation of an early childhood curriculum in postcolonial urban India. Findings from a qualitative naturalistic inquiry indicated that a complex, multifaceted curriculum shaped by…

Knowledge and Vision in Teaching

ERIC Educational Resources Information Center

Kennedy, Mary M.

2006-01-01

The author challenges the role of knowledge in teaching by pointing out the variety of issues and concerns teachers must simultaneously address. Teachers use two strategies to manage their multidimensional space: They develop integrated habits and rules of thumb for handling situations as they arise, and they plan their lessons by envisioning them…

Measuring the Effectiveness of Educational Technology: What Are We Attempting to Measure?

ERIC Educational Resources Information Center

Jenkinson, Jodie

2009-01-01

In many academic areas, students' success depends upon their ability to envision and manipulate complex multidimensional information spaces. Fields in which students struggle with mastering these types of representations include (but are by no means limited to) mathematics, science, medicine, and engineering. There has been some educational…

Forecasting and analyzing high O3 time series in educational area through an improved chaotic approach

NASA Astrophysics Data System (ADS)

Hamid, Nor Zila Abd; Adenan, Nur Hamiza; Noorani, Mohd Salmi Md

2017-08-01

Forecasting and analyzing the ozone (O3) concentration time series is important because the pollutant is harmful to health. This study is a pilot study for forecasting and analyzing the O3 time series in one of Malaysian educational area namely Shah Alam using chaotic approach. Through this approach, the observed hourly scalar time series is reconstructed into a multi-dimensional phase space, which is then used to forecast the future time series through the local linear approximation method. The main purpose is to forecast the high O3 concentrations. The original method performed poorly but the improved method addressed the weakness thereby enabling the high concentrations to be successfully forecast. The correlation coefficient between the observed and forecasted time series through the improved method is 0.9159 and both the mean absolute error and root mean squared error are low. Thus, the improved method is advantageous. The time series analysis by means of the phase space plot and Cao method identified the presence of low-dimensional chaotic dynamics in the observed O3 time series. Results showed that at least seven factors affect the studied O3 time series, which is consistent with the listed factors from the diurnal variations investigation and the sensitivity analysis from past studies. In conclusion, chaotic approach has been successfully forecast and analyzes the O3 time series in educational area of Shah Alam. These findings are expected to help stakeholders such as Ministry of Education and Department of Environment in having a better air pollution management.

Detection of chaotic dynamics in human gait signals from mobile devices

NASA Astrophysics Data System (ADS)

DelMarco, Stephen; Deng, Yunbin

2017-05-01

The ubiquity of mobile devices offers the opportunity to exploit device-generated signal data for biometric identification, health monitoring, and activity recognition. In particular, mobile devices contain an Inertial Measurement Unit (IMU) that produces acceleration and rotational rate information from the IMU accelerometers and gyros. These signals reflect motion properties of the human carrier. It is well-known that the complexity of bio-dynamical systems gives rise to chaotic dynamics. Knowledge of chaotic properties of these systems has shown utility, for example, in detecting abnormal medical conditions and neurological disorders. Chaotic dynamics has been found, in the lab, in bio-dynamical systems data such as electrocardiogram (heart), electroencephalogram (brain), and gait data. In this paper, we investigate the following question: can we detect chaotic dynamics in human gait as measured by IMU acceleration and gyro data from mobile phones? To detect chaotic dynamics, we perform recurrence analysis on real gyro and accelerometer signal data obtained from mobile devices. We apply the delay coordinate embedding approach from Takens' theorem to reconstruct the phase space trajectory of the multi-dimensional gait dynamical system. We use mutual information properties of the signal to estimate the appropriate delay value, and the false nearest neighbor approach to determine the phase space embedding dimension. We use a correlation dimension-based approach together with estimation of the largest Lyapunov exponent to make the chaotic dynamics detection decision. We investigate the ability to detect chaotic dynamics for the different one-dimensional IMU signals, across human subject and walking modes, and as a function of different phone locations on the human carrier.

Characterization of the pigment fraction in sweet bell peppers (Capsicum annuum L.) harvested at green and overripe yellow and red stages by offline multidimensional convergence chromatography/liquid chromatography-mass spectrometry.

PubMed

Bonaccorsi, Ivana; Cacciola, Francesco; Utczas, Margita; Inferrera, Veronica; Giuffrida, Daniele; Donato, Paola; Dugo, Paola; Mondello, Luigi

2016-09-01

Offline multidimensional supercritical fluid chromatography combined with reversed-phase liquid chromatography was employed for the carotenoid and chlorophyll characterization in different sweet bell peppers (Capsicum annuum L.) for the first time. The first dimension consisted of an Acquity HSS C18 SB (100 × 3 mm id, 1.8 μm particles) column operated with a supercritical mobile phase in an ultra-performance convergence chromatography system, whereas the second dimension was performed in reversed-phase mode with a C30 (250 × 4.6 mm id, 3.0 μm particles) stationary phase combined with photodiode array and mass spectrometry detection. This approach allowed the determination of 115 different compounds belonging to chlorophylls, free xanthophylls, free carotenes, xanthophyll monoesters, and xanthophyll diesters, and proved to be a significant improvement in the pigments determination compared to the conventional one-dimensional liquid chromatography approach so far applied to the carotenoid analysis in the studied species. Moreover, the present study also aimed to investigate and to compare the carotenoid stability and composition in overripe yellow and red bell peppers collected directly from the plant, thus also evaluating whether biochemical changes are linked to carotenoid degradation in the nonclimacteric investigated fruits, for the first time. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A reduced basis approach for implementing thermodynamic phase-equilibria information in geophysical and geodynamic studies

NASA Astrophysics Data System (ADS)

Afonso, J. C.; Zlotnik, S.; Diez, P.

2015-12-01

We present a flexible, general and efficient approach for implementing thermodynamic phase equilibria information (in the form of sets of physical parameters) into geophysical and geodynamic studies. The approach is based on multi-dimensional decomposition methods, which transform the original multi-dimensional discrete information into a dimensional-separated representation. This representation has the property of increasing the number of coefficients to be stored linearly with the number of dimensions (opposite to a full multi-dimensional cube requiring exponential storage depending on the number of dimensions). Thus, the amount of information to be stored in memory during a numerical simulation or geophysical inversion is drastically reduced. Accordingly, the amount and resolution of the thermodynamic information that can be used in a simulation or inversion increases substantially. In addition, the method is independent of the actual software used to obtain the primary thermodynamic information, and therefore it can be used in conjunction with any thermodynamic modeling program and/or database. Also, the errors associated with the decomposition procedure are readily controlled by the user, depending on her/his actual needs (e.g. preliminary runs vs full resolution runs). We illustrate the benefits, generality and applicability of our approach with several examples of practical interest for both geodynamic modeling and geophysical inversion/modeling. Our results demonstrate that the proposed method is a competitive and attractive candidate for implementing thermodynamic constraints into a broad range of geophysical and geodynamic studies.

Gravitational wave-Gauge field oscillations

NASA Astrophysics Data System (ADS)

Caldwell, R. R.; Devulder, C.; Maksimova, N. A.

2016-09-01

Gravitational waves propagating through a stationary gauge field transform into gauge field waves and back again. When multiple families of flavor-space locked gauge fields are present, the gravitational and gauge field waves exhibit novel dynamics. At high frequencies, the system behaves like coupled oscillators in which the gravitational wave is the central pacemaker. Due to energy conservation and exchange among the oscillators, the wave amplitudes lie on a multidimensional sphere, reminiscent of neutrino flavor oscillations. This phenomenon has implications for cosmological scenarios based on flavor-space locked gauge fields.

Reconciling long-term cultural diversity and short-term collective social behavior.

PubMed

Valori, Luca; Picciolo, Francesco; Allansdottir, Agnes; Garlaschelli, Diego

2012-01-24

An outstanding open problem is whether collective social phenomena occurring over short timescales can systematically reduce cultural heterogeneity in the long run, and whether offline and online human interactions contribute differently to the process. Theoretical models suggest that short-term collective behavior and long-term cultural diversity are mutually excluding, since they require very different levels of social influence. The latter jointly depends on two factors: the topology of the underlying social network and the overlap between individuals in multidimensional cultural space. However, while the empirical properties of social networks are intensively studied, little is known about the large-scale organization of real societies in cultural space, so that random input specifications are necessarily used in models. Here we use a large dataset to perform a high-dimensional analysis of the scientific beliefs of thousands of Europeans. We find that interopinion correlations determine a nontrivial ultrametric hierarchy of individuals in cultural space. When empirical data are used as inputs in models, ultrametricity has strong and counterintuitive effects. On short timescales, it facilitates a symmetry-breaking phase transition triggering coordinated social behavior. On long timescales, it suppresses cultural convergence by restricting it within disjoint groups. Moreover, ultrametricity implies that these results are surprisingly robust to modifications of the dynamical rules considered. Thus the empirical distribution of individuals in cultural space appears to systematically optimize the coexistence of short-term collective behavior and long-term cultural diversity, which can be realized simultaneously for the same moderate level of mutual influence in a diverse range of online and offline settings.

A Generic multi-dimensional feature extraction method using multiobjective genetic programming.

PubMed

Zhang, Yang; Rockett, Peter I

2009-01-01

In this paper, we present a generic feature extraction method for pattern classification using multiobjective genetic programming. This not only evolves the (near-)optimal set of mappings from a pattern space to a multi-dimensional decision space, but also simultaneously optimizes the dimensionality of that decision space. The presented framework evolves vector-to-vector feature extractors that maximize class separability. We demonstrate the efficacy of our approach by making statistically-founded comparisons with a wide variety of established classifier paradigms over a range of datasets and find that for most of the pairwise comparisons, our evolutionary method delivers statistically smaller misclassification errors. At very worst, our method displays no statistical difference in a few pairwise comparisons with established classifier/dataset combinations; crucially, none of the misclassification results produced by our method is worse than any comparator classifier. Although principally focused on feature extraction, feature selection is also performed as an implicit side effect; we show that both feature extraction and selection are important to the success of our technique. The presented method has the practical consequence of obviating the need to exhaustively evaluate a large family of conventional classifiers when faced with a new pattern recognition problem in order to attain a good classification accuracy.

A Structure-Based Distance Metric for High-Dimensional Space Exploration with Multi-Dimensional Scaling

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

Lee, Hyun Jung; McDonnell, Kevin T.; Zelenyuk, Alla

2014-03-01

Although the Euclidean distance does well in measuring data distances within high-dimensional clusters, it does poorly when it comes to gauging inter-cluster distances. This significantly impacts the quality of global, low-dimensional space embedding procedures such as the popular multi-dimensional scaling (MDS) where one can often observe non-intuitive layouts. We were inspired by the perceptual processes evoked in the method of parallel coordinates which enables users to visually aggregate the data by the patterns the polylines exhibit across the dimension axes. We call the path of such a polyline its structure and suggest a metric that captures this structure directly inmore » high-dimensional space. This allows us to better gauge the distances of spatially distant data constellations and so achieve data aggregations in MDS plots that are more cognizant of existing high-dimensional structure similarities. Our MDS plots also exhibit similar visual relationships as the method of parallel coordinates which is often used alongside to visualize the high-dimensional data in raw form. We then cast our metric into a bi-scale framework which distinguishes far-distances from near-distances. The coarser scale uses the structural similarity metric to separate data aggregates obtained by prior classification or clustering, while the finer scale employs the appropriate Euclidean distance.« less

A cross-sectional analysis of green space prevalence and mental wellbeing in England.

PubMed

Houlden, Victoria; Weich, Scott; Jarvis, Stephen

2017-05-17

With urbanisation increasing, it is important to understand how to design changing environments to promote mental wellbeing. Evidence suggests that local-area proportions of green space may be associated with happiness and life satisfaction; however, the available evidence on such associations with more broadly defined mental wellbeing in still very scarce. This study aimed to establish whether the amount of neighbourhood green space was associated with mental wellbeing. Data were drawn from Understanding Society, a national survey of 30,900 individuals across 11,096 Census Lower-Layer Super Output Areas (LSOAs) in England, over the period 2009-2010. Measures included the multi-dimensional Warwick-Edinburgh Mental Well-Being Scale (SWEMWBS) and LSOA proportion of green space, which was derived from the General Land Use Database (GLUD), and were analysed using linear regression, while controlling for individual, household and area-level factors. Those living in areas with greater proportions of green space had significantly higher mental wellbeing scores in unadjusted analyses (an expected increase of 0.17 points (95% CI 0.11, 0.23) in the SWEMWBS score for a standard deviation increase of green space). However, after adjustment for confounding by respondent sociodemographic characteristics and urban/rural location, the association was attenuated to the null (regression coefficient B = - 0.01, 95% CI -0.08, 0.05, p = 0.712). While the green space in an individual's local area has been shown through other research to be related to aspects of mental health such as happiness and life satisfaction, the association with multidimensional mental wellbeing is much less clear from our results. While we did not find a statistically significant association between the amount of green space in residents' local areas and mental wellbeing, further research is needed to understand whether other features of green space, such as accessibility, aesthetics or use, are important for mental wellbeing.

Self-Learning Adaptive Umbrella Sampling Method for the Determination of Free Energy Landscapes in Multiple Dimensions

PubMed Central

Wojtas-Niziurski, Wojciech; Meng, Yilin; Roux, Benoit; Bernèche, Simon

2013-01-01

The potential of mean force describing conformational changes of biomolecules is a central quantity that determines the function of biomolecular systems. Calculating an energy landscape of a process that depends on three or more reaction coordinates might require a lot of computational power, making some of multidimensional calculations practically impossible. Here, we present an efficient automatized umbrella sampling strategy for calculating multidimensional potential of mean force. The method progressively learns by itself, through a feedback mechanism, which regions of a multidimensional space are worth exploring and automatically generates a set of umbrella sampling windows that is adapted to the system. The self-learning adaptive umbrella sampling method is first explained with illustrative examples based on simplified reduced model systems, and then applied to two non-trivial situations: the conformational equilibrium of the pentapeptide Met-enkephalin in solution and ion permeation in the KcsA potassium channel. With this method, it is demonstrated that a significant smaller number of umbrella windows needs to be employed to characterize the free energy landscape over the most relevant regions without any loss in accuracy. PMID:23814508

The Wang-Landau Sampling Algorithm

NASA Astrophysics Data System (ADS)

Landau, David P.

2003-03-01

Over the past several decades Monte Carlo simulations[1] have evolved into a powerful tool for the study of wide-ranging problems in statistical/condensed matter physics. Standard methods sample the probability distribution for the states of the system, usually in the canonical ensemble, and enormous improvements have been made in performance through the implementation of novel algorithms. Nonetheless, difficulties arise near phase transitions, either due to critical slowing down near 2nd order transitions or to metastability near 1st order transitions, thus limiting the applicability of the method. We shall describe a new and different Monte Carlo approach [2] that uses a random walk in energy space to determine the density of states directly. Once the density of states is estimated, all thermodynamic properties can be calculated at all temperatures. This approach can be extended to multi-dimensional parameter spaces and has already found use in classical models of interacting particles including systems with complex energy landscapes, e.g., spin glasses, protein folding models, etc., as well as for quantum models. 1. A Guide to Monte Carlo Simulations in Statistical Physics, D. P. Landau and K. Binder (Cambridge U. Press, Cambridge, 2000). 2. Fugao Wang and D. P. Landau, Phys. Rev. Lett. 86, 2050 (2001); Phys. Rev. E64, 056101-1 (2001).

The effects of tones in noise on human annoyance and performance

NASA Astrophysics Data System (ADS)

Lee, Joonhee

Building mechanical equipment often generates prominent tones because most systems include rotating parts like fans and pumps. These tonal noises can cause unpleasant user experiences in spaces and, in turn, lead to increased complaints by building occupants. Currently, architectural engineers can apply the noise criteria guidelines in standards or publications to achieve acceptable noise conditions for assorted types of spaces. However, these criteria do not apply well if the noise contains perceptible tones. The annoyance thresholds experienced by the general population with regards to the degree of tones in noise is a significant piece of knowledge that has not been well-established. Thus, this dissertation addresses the relationship between human perception and noises with tones in the built environment. Four phases of subjective testing were conducted in an indoor acoustic testing chamber at the University of Nebraska to achieve the research objective. The results indicate that even the least prominent tones in noises can significantly decrease the cognitive performance of participants on a mentally demanding task. Factorial repeated-measures analysis of variance of test results have proven that tonality has a crucial influence on working memory capacity of subjects, whereas loudness levels alone did not. A multidimensional annoyance model, incorporating psycho-acoustical attributes of noise in addition to loudness and tonality, has been proposed as a more accurate annoyance model.

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

New multidimensional functional diversity indices for a multifaceted framework in functional ecology.

PubMed

Villéger, Sébastien; Mason, Norman W H; Mouillot, David

2008-08-01

Functional diversity is increasingly identified as an important driver of ecosystem functioning. Various indices have been proposed to measure the functional diversity of a community, but there is still no consensus on which are most suitable. Indeed, none of the existing indices meets all the criteria required for general use. The main criteria are that they must be designed to deal with several traits, take into account abundances, and measure all the facets of functional diversity. Here we propose three indices to quantify each facet of functional diversity for a community with species distributed in a multidimensional functional space: functional richness (volume of the functional space occupied by the community), functional evenness (regularity of the distribution of abundance in this volume), and functional divergence (divergence in the distribution of abundance in this volume). Functional richness is estimated using the existing convex hull volume index. The new functional evenness index is based on the minimum spanning tree which links all the species in the multidimensional functional space. Then this new index quantifies the regularity with which species abundances are distributed along the spanning tree. Functional divergence is measured using a novel index which quantifies how species diverge in their distances (weighted by their abundance) from the center of gravity in the functional space. We show that none of the indices meets all the criteria required for a functional diversity index, but instead we show that the set of three complementary indices meets these criteria. Through simulations of artificial data sets, we demonstrate that functional divergence and functional evenness are independent of species richness and that the three functional diversity indices are independent of each other. Overall, our study suggests that decomposition of functional diversity into its three primary components provides a meaningful framework for its quantification and for the classification of existing functional diversity indices. This decomposition has the potential to shed light on the role of biodiversity on ecosystem functioning and on the influence of biotic and abiotic filters on the structure of species communities. Finally, we propose a general framework for applying these three functional diversity indices.

The Development of Voiceless Sibilant Fricatives in Putonghua-Speaking Children

ERIC Educational Resources Information Center

Li, Fangfang; Munson, Benjamin

2016-01-01

Purpose The aims of the present study are (a) to quantify the developmental sequence of fricative mastery in Putonghua-speaking children and discuss the observed pattern in relation to existing theoretical positions, and (b) to describe the acquisition of the fine-articulatory/acoustic details of fricatives in the multidimensional acoustic space.…

Chlorofluoromethanes and the Stratosphere

NASA Technical Reports Server (NTRS)

Hudson, R. D. (Editor)

1977-01-01

The conclusions of a workshop held by the National Aeronautics and Space Administration to assess the current knowledge of the impact of chlorofluoromethane release in the troposphere on stratospheric ozone concentrations. The following topics are discussed; (1) Laboratory measurements; (2) Ozone measurements and trends; (3) Minor species and aerosol measurements; (4) One dimensional modeling; and (5) Multidimensional modeling.

Diverse applications of advanced man-telerobot interfaces

NASA Technical Reports Server (NTRS)

Mcaffee, Douglas A.

1991-01-01

Advancements in man-machine interfaces and control technologies used in space telerobotics and teleoperators have potential application wherever human operators need to manipulate multi-dimensional spatial relationships. Bilateral six degree-of-freedom position and force cues exchanged between the user and a complex system can broaden and improve the effectiveness of several diverse man-machine interfaces.

Dynamic State Estimation of Terrestrial and Solar Plasmas

NASA Astrophysics Data System (ADS)

Kamalabadi, Farzad

A pervasive problem in virtually all branches of space science is the estimation of multi-dimensional state parameters of a dynamical system from a collection of indirect, often incomplete, and imprecise measurements. Subsequent scientific inference is predicated on rigorous analysis, interpretation, and understanding of physical observations and on the reliability of the associated quantitative statistical bounds and performance characteristics of the algorithms used. In this work, we focus on these dynamic state estimation problems and illustrate their importance in the context of two timely activities in space remote sensing. First, we discuss the estimation of multi-dimensional ionospheric state parameters from UV spectral imaging measurements anticipated to be acquired the recently selected NASA Heliophysics mission, Ionospheric Connection Explorer (ICON). Next, we illustrate that similar state-space formulations provide the means for the estimation of 3D, time-dependent densities and temperatures in the solar corona from a series of white-light and EUV measurements. We demonstrate that, while a general framework for the stochastic formulation of the state estimation problem is suited for systematic inference of the parameters of a hidden Markov process, several challenges must be addressed in the assimilation of an increasing volume and diversity of space observations. These challenges are: (1) the computational tractability when faced with voluminous and multimodal data, (2) the inherent limitations of the underlying models which assume, often incorrectly, linear dynamics and Gaussian noise, and (3) the unavailability or inaccuracy of transition probabilities and noise statistics. We argue that pursuing answers to these questions necessitates cross-disciplinary research that enables progress toward systematically reconciling observational and theoretical understanding of the space environment.

Non-uniform sampling: post-Fourier era of NMR data collection and processing.

PubMed

Kazimierczuk, Krzysztof; Orekhov, Vladislav

2015-11-01

The invention of multidimensional techniques in the 1970s revolutionized NMR, making it the general tool of structural analysis of molecules and materials. In the most straightforward approach, the signal sampling in the indirect dimensions of a multidimensional experiment is performed in the same manner as in the direct dimension, i.e. with a grid of equally spaced points. This results in lengthy experiments with a resolution often far from optimum. To circumvent this problem, numerous sparse-sampling techniques have been developed in the last three decades, including two traditionally distinct approaches: the radial sampling and non-uniform sampling. This mini review discusses the sparse signal sampling and reconstruction techniques from the point of view of an underdetermined linear algebra problem that arises when a full, equally spaced set of sampled points is replaced with sparse sampling. Additional assumptions that are introduced to solve the problem, as well as the shape of the undersampled Fourier transform operator (visualized as so-called point spread function), are shown to be the main differences between various sparse-sampling methods. Copyright © 2015 John Wiley & Sons, Ltd.

Informatics in radiology (infoRAD): navigating the fifth dimension: innovative interface for multidimensional multimodality image navigation.

PubMed

Rosset, Antoine; Spadola, Luca; Pysher, Lance; Ratib, Osman

2006-01-01

The display and interpretation of images obtained by combining three-dimensional data acquired with two different modalities (eg, positron emission tomography and computed tomography) in the same subject require complex software tools that allow the user to adjust the image parameters. With the current fast imaging systems, it is possible to acquire dynamic images of the beating heart, which add a fourth dimension of visual information-the temporal dimension. Moreover, images acquired at different points during the transit of a contrast agent or during different functional phases add a fifth dimension-functional data. To facilitate real-time image navigation in the resultant large multidimensional image data sets, the authors developed a Digital Imaging and Communications in Medicine-compliant software program. The open-source software, called OsiriX, allows the user to navigate through multidimensional image series while adjusting the blending of images from different modalities, image contrast and intensity, and the rate of cine display of dynamic images. The software is available for free download at http://homepage.mac.com/rossetantoine/osirix. (c) RSNA, 2006.

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

Raman Spectroscopy as the Method of Detection for Constructing a Binary Liquid-Vapor Phase Diagram

ERIC Educational Resources Information Center

Scardino, Debra J.; Howard, Austin A.; McDowell, Matthew D.; Hammer, Nathan I.

2011-01-01

The physical chemistry laboratory is sometimes constrained to one semester, resulting in pedagogical deficiencies for the students taking the course. The use of a multidimensional laboratory exercise offers students the opportunity to encounter multiple experimental techniques and physical chemistry concepts while not sacrificing a significant…

Multidimensional In Vivo Hazard Assessment Using Zebrafish

PubMed Central

Tanguay, Robert L.

2014-01-01

There are tens of thousands of man-made chemicals in the environment; the inherent safety of most of these chemicals is not known. Relevant biological platforms and new computational tools are needed to prioritize testing of chemicals with limited human health hazard information. We describe an experimental design for high-throughput characterization of multidimensional in vivo effects with the power to evaluate trends relating to commonly cited chemical predictors. We evaluated all 1060 unique U.S. EPA ToxCast phase 1 and 2 compounds using the embryonic zebrafish and found that 487 induced significant adverse biological responses. The utilization of 18 simultaneously measured endpoints means that the entire system serves as a robust biological sensor for chemical hazard. The experimental design enabled us to describe global patterns of variation across tested compounds, evaluate the concordance of the available in vitro and in vivo phase 1 data with this study, highlight specific mechanisms/value-added/novel biology related to notochord development, and demonstrate that the developmental zebrafish detects adverse responses that would be missed by less comprehensive testing strategies. PMID:24136191

Energy-efficient spatial-domain-based hybrid multidimensional coded-modulations enabling multi-Tb/s optical transport.

PubMed

Djordjevic, Ivan B

2011-08-15

In addition to capacity, the future high-speed optical transport networks will also be constrained by energy consumption. In order to solve the capacity and energy constraints simultaneously, in this paper we propose the use of energy-efficient hybrid D-dimensional signaling (D>4) by employing all available degrees of freedom for conveyance of the information over a single carrier including amplitude, phase, polarization and orbital angular momentum (OAM). Given the fact that the OAM eigenstates, associated with the azimuthal phase dependence of the complex electric field, are orthogonal, they can be used as basis functions for multidimensional signaling. Since the information capacity is a linear function of number of dimensions, through D-dimensional signal constellations we can significantly improve the overall optical channel capacity. The energy-efficiency problem is solved, in this paper, by properly designing the D-dimensional signal constellation such that the mutual information is maximized, while taking the energy constraint into account. We demonstrate high-potential of proposed energy-efficient hybrid D-dimensional coded-modulation scheme by Monte Carlo simulations. © 2011 Optical Society of America

A support vector machine based test for incongruence between sets of trees in tree space

PubMed Central

2012-01-01

Background The increased use of multi-locus data sets for phylogenetic reconstruction has increased the need to determine whether a set of gene trees significantly deviate from the phylogenetic patterns of other genes. Such unusual gene trees may have been influenced by other evolutionary processes such as selection, gene duplication, or horizontal gene transfer. Results Motivated by this problem we propose a nonparametric goodness-of-fit test for two empirical distributions of gene trees, and we developed the software GeneOut to estimate a p-value for the test. Our approach maps trees into a multi-dimensional vector space and then applies support vector machines (SVMs) to measure the separation between two sets of pre-defined trees. We use a permutation test to assess the significance of the SVM separation. To demonstrate the performance of GeneOut, we applied it to the comparison of gene trees simulated within different species trees across a range of species tree depths. Applied directly to sets of simulated gene trees with large sample sizes, GeneOut was able to detect very small differences between two set of gene trees generated under different species trees. Our statistical test can also include tree reconstruction into its test framework through a variety of phylogenetic optimality criteria. When applied to DNA sequence data simulated from different sets of gene trees, results in the form of receiver operating characteristic (ROC) curves indicated that GeneOut performed well in the detection of differences between sets of trees with different distributions in a multi-dimensional space. Furthermore, it controlled false positive and false negative rates very well, indicating a high degree of accuracy. Conclusions The non-parametric nature of our statistical test provides fast and efficient analyses, and makes it an applicable test for any scenario where evolutionary or other factors can lead to trees with different multi-dimensional distributions. The software GeneOut is freely available under the GNU public license. PMID:22909268

New functionalities of potassium tantalate niobate deflectors enabled by the coexistence of pre-injected space charge and composition gradient

NASA Astrophysics Data System (ADS)

Zhu, Wenbin; Chao, Ju-Hung; Chen, Chang-Jiang; Campbell, Adrian L.; Henry, Michael G.; Yin, Stuart Shizhuo; Hoffman, Robert C.

2017-10-01

In most beam steering applications such as 3D printing and in vivo imaging, one of the essential challenges has been high-resolution high-speed multi-dimensional optical beam scanning. Although the pre-injected space charge controlled potassium tantalate niobate (KTN) deflectors can achieve speeds in the nanosecond regime, they deflect in only one dimension. In order to develop a high-resolution high-speed multi-dimensional KTN deflector, we studied the deflection behavior of KTN deflectors in the case of coexisting pre-injected space charge and composition gradient. We find that such coexistence can enable new functionalities of KTN crystal based electro-optic deflectors. When the direction of the composition gradient is parallel to the direction of the external electric field, the zero-deflection position can be shifted, which can reduce the internal electric field induced beam distortion, and thus enhance the resolution. When the direction of the composition gradient is perpendicular to the direction of the external electric field, two-dimensional beam scanning can be achieved by harnessing only one single piece of KTN crystal, which can result in a compact, high-speed two-dimensional deflector. Both theoretical analyses and experiments are conducted, which are consistent with each other. These new functionalities can expedite the usage of KTN deflection in many applications such as high-speed 3D printing, high-speed, high-resolution imaging, and free space broadband optical communication.

Numerical modeling for dilute and dense sprays

NASA Technical Reports Server (NTRS)

Chen, C. P.; Kim, Y. M.; Shang, H. M.; Ziebarth, J. P.; Wang, T. S.

1992-01-01

We have successfully implemented a numerical model for spray-combustion calculations. In this model, the governing gas-phase equations in Eulerian coordinate are solved by a time-marching multiple pressure correction procedure based on the operator-splitting technique. The droplet-phase equations in Lagrangian coordinate are solved by a stochastic discrete particle technique. In order to simplify the calculation procedure for the circulating droplets, the effective conductivity model is utilized. The k-epsilon models are utilized to characterize the time and length scales of the gas phase in conjunction with turbulent modulation by droplets and droplet dispersion by turbulence. This method entails random sampling of instantaneous gas flow properties and the stochastic process requires a large number of computational parcels to produce the satisfactory dispersion distributions even for rather dilute sprays. Two major improvements in spray combustion modelings were made. Firstly, we have developed a probability density function approach in multidimensional space to represent a specific computational particle. Secondly, we incorporate the Taylor Analogy Breakup (TAB) model for handling the dense spray effects. This breakup model is based on the reasonable assumption that atomization and drop breakup are indistinguishable processes within a dense spray near the nozzle exit. Accordingly, atomization is prescribed by injecting drops which have a characteristic size equal to the nozzle exit diameter. Example problems include the nearly homogeneous and inhomogeneous turbulent particle dispersion, and the non-evaporating, evaporating, and burning dense sprays. Comparison with experimental data will be discussed in detail.

Assessing Psycho-social Barriers to Rehabilitation in Injured Workers with Chronic Musculoskeletal Pain: Development and Item Properties of the Yellow Flag Questionnaire (YFQ).

PubMed

Salathé, Cornelia Rolli; Trippolini, Maurizio Alen; Terribilini, Livio Claudio; Oliveri, Michael; Elfering, Achim

2018-06-01

Purpose To develop a multidimensional scale to asses psychosocial beliefs-the Yellow Flag Questionnaire (YFQ)-aimed at guiding interventions for workers with chronic musculoskeletal (MSK) pain. Methods Phase 1 consisted of item selection based on literature search, item development and expert consensus rounds. In phase 2, items were reduced with calculating a quality-score per item, using structure equation modeling and confirmatory factor analysis on data from 666 workers. In phase 3, Cronbach's α, and Pearson correlations coefficients were computed to compare YFQ with disability, anxiety, depression and self-efficacy and the YFQ score based on data from 253 injured workers. Regressions of YFQ total score on disability, anxiety, depression and self-efficacy were calculated. Results After phase 1, the YFQ included 116 items and 15 domains. Further reductions of items in phase 2 by applying the item quality criteria reduced the total to 48 items. Phase factor analysis with structural equation modeling confirmed 32 items in seven domains: activity, work, emotions, harm & blame, diagnosis beliefs, co-morbidity and control. Cronbach α was 0.91 for the total score, between 0.49 and 0.81 for the 7 distinct scores of each domain, respectively. Correlations between YFQ total score ranged with disability, anxiety, depression and self-efficacy was .58, .66, .73, -.51, respectively. After controlling for age and gender the YFQ total score explained between R2 27% and R2 53% variance of disability, anxiety, depression and self-efficacy. Conclusions The YFQ, a multidimensional screening scale is recommended for use to assess psychosocial beliefs of workers with chronic MSK pain. Further evaluation of the measurement properties such as the test-retest reliability, responsiveness and prognostic validity is warranted.

Development and testing of the Multidimensional Trust in Health Care Systems Scale.

PubMed

Egede, Leonard E; Ellis, Charles

2008-06-01

To describe the development and psychometric testing of the Multidimensional Trust in Health Care Systems Scale (MTHCSS). Scale development occurred in 2 phases. In phase 1, a pilot instrument with 70 items was generated from the review of the trust literature, focus groups, and expert opinion. The 70 items were pilot tested in a sample of 256 students. Exploratory factor analysis was used to derive an orthogonal set of correlated factors. In phase 2, the final scale was administered to 301 primary care patients to assess reliability and validity. Phase 2 participants also completed validated measures of patient-centered care, health locus of control, medication nonadherence, social support, and patient satisfaction. In phase 1, a 17-item scale (MTHCSS) was developed with 10 items measuring trust in health care providers, 4 items measuring trust in health care payers, and 3 items measuring trust in health care institutions. In phase 2, the 17-item MTHCSS had a mean score of 63.0 (SD 8.8); the provider subscale had a mean of 40.0 (SD 6.2); the payers subscale had a mean of 12.8 (SD 3.0); and the institutions subscale had a mean of 10.3 (SD 2.1). Cronbach's alpha for the MTHCSS was 0.89 and 0.92, 0.74, and 0.64 for the 3 subscales. The MTHCSS was significantly correlated with patient-centered care (r = .22 to .62), locus of control-chance (r = .42), medication nonadherence (r = -.22), social support (r = .25), and patient satisfaction (r = .67). The MTHCSS is a valid and reliable instrument for measuring the 3 objects of trust in health care and is correlated with patient-level health outcomes.

Quantifying multi-dimensional attributes of human activities at various geographic scales based on smartphone tracking.

PubMed

Zhou, Xiaolu; Li, Dongying

2018-05-09

Advancement in location-aware technologies, and information and communication technology in the past decades has furthered our knowledge of the interaction between human activities and the built environment. An increasing number of studies have collected data regarding individual activities to better understand how the environment shapes human behavior. Despite this growing interest, some challenges exist in collecting and processing individual's activity data, e.g., capturing people's precise environmental contexts and analyzing data at multiple spatial scales. In this study, we propose and implement an innovative system that integrates smartphone-based step tracking with an app and the sequential tile scan techniques to collect and process activity data. We apply the OpenStreetMap tile system to aggregate positioning points at various scales. We also propose duration, step and probability surfaces to quantify the multi-dimensional attributes of activities. Results show that, by running the app in the background, smartphones can measure multi-dimensional attributes of human activities, including space, duration, step, and location uncertainty at various spatial scales. By coordinating Global Positioning System (GPS) sensor with accelerometer sensor, this app can save battery which otherwise would be drained by GPS sensor quickly. Based on a test dataset, we were able to detect the recreational center and sports center as the space where the user was most active, among other places visited. The methods provide techniques to address key issues in analyzing human activity data. The system can support future studies on behavioral and health consequences related to individual's environmental exposure.

A Computational Methodology for Simulating Thermal Loss Testing of the Advanced Stirling Convertor

NASA Technical Reports Server (NTRS)

Reid, Terry V.; Wilson, Scott D.; Schifer, Nicholas A.; Briggs, Maxwell H.

2012-01-01

The U.S. Department of Energy (DOE) and Lockheed Martin Space Systems Company (LMSSC) have been developing the Advanced Stirling Radioisotope Generator (ASRG) for use as a power system for space science missions. This generator would use two highefficiency Advanced Stirling Convertors (ASCs), developed by Sunpower Inc. and NASA Glenn Research Center (GRC). The ASCs convert thermal energy from a radioisotope heat source into electricity. As part of ground testing of these ASCs, different operating conditions are used to simulate expected mission conditions. These conditions require achieving a particular operating frequency, hot end and cold end temperatures, and specified electrical power output for a given net heat input. In an effort to improve net heat input predictions, numerous tasks have been performed which provided a more accurate value for net heat input into the ASCs, including the use of multidimensional numerical models. Validation test hardware has also been used to provide a direct comparison of numerical results and validate the multi-dimensional numerical models used to predict convertor net heat input and efficiency. These validation tests were designed to simulate the temperature profile of an operating Stirling convertor and resulted in a measured net heat input of 244.4 W. The methodology was applied to the multi-dimensional numerical model which resulted in a net heat input of 240.3 W. The computational methodology resulted in a value of net heat input that was 1.7 percent less than that measured during laboratory testing. The resulting computational methodology and results are discussed.

Rapid Computation of Thermodynamic Properties over Multidimensional Nonbonded Parameter Spaces Using Adaptive Multistate Reweighting.

PubMed

Naden, Levi N; Shirts, Michael R

2016-04-12

We show how thermodynamic properties of molecular models can be computed over a large, multidimensional parameter space by combining multistate reweighting analysis with a linear basis function approach. This approach reduces the computational cost to estimate thermodynamic properties from molecular simulations for over 130,000 tested parameter combinations from over 1000 CPU years to tens of CPU days. This speed increase is achieved primarily by computing the potential energy as a linear combination of basis functions, computed from either modified simulation code or as the difference of energy between two reference states, which can be done without any simulation code modification. The thermodynamic properties are then estimated with the Multistate Bennett Acceptance Ratio (MBAR) as a function of multiple model parameters without the need to define a priori how the states are connected by a pathway. Instead, we adaptively sample a set of points in parameter space to create mutual configuration space overlap. The existence of regions of poor configuration space overlap are detected by analyzing the eigenvalues of the sampled states' overlap matrix. The configuration space overlap to sampled states is monitored alongside the mean and maximum uncertainty to determine convergence, as neither the uncertainty or the configuration space overlap alone is a sufficient metric of convergence. This adaptive sampling scheme is demonstrated by estimating with high precision the solvation free energies of charged particles of Lennard-Jones plus Coulomb functional form with charges between -2 and +2 and generally physical values of σij and ϵij in TIP3P water. We also compute entropy, enthalpy, and radial distribution functions of arbitrary unsampled parameter combinations using only the data from these sampled states and use the estimates of free energies over the entire space to examine the deviation of atomistic simulations from the Born approximation to the solvation free energy.

Asymptotical AdS space from nonlinear gravitational models with stabilized extra dimensions

NASA Astrophysics Data System (ADS)

Günther, U.; Moniz, P.; Zhuk, A.

2002-08-01

We consider nonlinear gravitational models with a multidimensional warped product geometry. Particular attention is payed to models with quadratic scalar curvature terms. It is shown that for certain parameter ranges, the extra dimensions are stabilized if the internal spaces have a negative constant curvature. In this case, the four-dimensional effective cosmological constant as well as the bulk cosmological constant become negative. As a consequence, the homogeneous and isotropic external space is asymptotically AdS4. The connection between the D-dimensional and the four-dimensional fundamental mass scales sets a restriction on the parameters of the considered nonlinear models.

Relevance in the science classroom: A multidimensional analysis

NASA Astrophysics Data System (ADS)

Hartwell, Matthew F.

While perceived relevance is considered a fundamental component of adaptive learning, the experience of relevance and its conceptual definition have not been well described. The mixed-methods research presented in this dissertation aimed to clarify the conceptual meaning of relevance by focusing on its phenomenological experience from the students' perspective. Following a critical literature review, I propose an identity-based model of perceived relevance that includes three components: a contextual target, an identity target, and a connection type, or lens. An empirical investigation of this model that consisted of two general phases was implemented in four 9th grade-biology classrooms. Participants in Phase 1 (N = 118) completed a series of four open-ended writing activities focused on eliciting perceived personal connections to academic content. Exploratory qualitative content analysis of a 25% random sample of the student responses was used to identify the main meaning-units of the proposed model as well as different dimensions of student relevance perceptions. These meaning-units and dimensions provided the basis for the construction of a conceptual mapping sentence capturing students' perceived relevance, which was then applied in a confirmatory analysis to all other student responses. Participants in Phase 2 (N = 139) completed a closed survey designed based on the mapping sentence to assess their perceived relevance of a biology unit. The survey also included scales assessing other domain-level motivational processes. Exploratory factor analysis and non-metric multidimensional scaling indicated a coherent conceptual structure, which included a primary interpretive relevance dimension. Comparison of the conceptual structure across various groups (randomly-split sample, gender, academic level, domain-general motivational profiles) provided support for its ubiquity and insight into variation in the experience of perceived relevance among students of different groups. The findings combine to support a multidimensional perspective of relevance in the 9th grade biology classroom; offering researchers a useful model for future investigation and educators with insights into the students' classroom experience.

Current Status on the use of Parallel Computing in Turbulent Reacting Flow Computations Involving Sprays, Monte Carlo PDF and Unstructured Grids. Chapter 4

NASA Technical Reports Server (NTRS)

Raju, M. S.

1998-01-01

The state of the art in multidimensional combustor modeling as evidenced by the level of sophistication employed in terms of modeling and numerical accuracy considerations, is also dictated by the available computer memory and turnaround times afforded by present-day computers. With the aim of advancing the current multi-dimensional computational tools used in the design of advanced technology combustors, a solution procedure is developed that combines the novelty of the coupled CFD/spray/scalar Monte Carlo PDF (Probability Density Function) computations on unstructured grids with the ability to run on parallel architectures. In this approach, the mean gas-phase velocity and turbulence fields are determined from a standard turbulence model, the joint composition of species and enthalpy from the solution of a modeled PDF transport equation, and a Lagrangian-based dilute spray model is used for the liquid-phase representation. The gas-turbine combustor flows are often characterized by a complex interaction between various physical processes associated with the interaction between the liquid and gas phases, droplet vaporization, turbulent mixing, heat release associated with chemical kinetics, radiative heat transfer associated with highly absorbing and radiating species, among others. The rate controlling processes often interact with each other at various disparate time 1 and length scales. In particular, turbulence plays an important role in determining the rates of mass and heat transfer, chemical reactions, and liquid phase evaporation in many practical combustion devices.

Off-Line Multidimensional Liquid Chromatography and Auto Sampling Result in Sample Loss in LC/LC–MS/MS

PubMed Central

2015-01-01

Large-scale proteomics often employs two orthogonal separation methods to fractionate complex peptide mixtures. Fractionation can involve ion exchange separation coupled to reversed-phase separation or, more recently, two reversed-phase separations performed at different pH values. When multidimensional separations are combined with tandem mass spectrometry for protein identification, the strategy is often referred to as multidimensional protein identification technology (MudPIT). MudPIT has been used in either an automated (online) or manual (offline) format. In this study, we evaluated the performance of different MudPIT strategies by both label-free and tandem mass tag (TMT) isobaric tagging. Our findings revealed that online MudPIT provided more peptide/protein identifications and higher sequence coverage than offline platforms. When employing an off-line fractionation method with direct loading of samples onto the column from an eppendorf tube via a high-pressure device, a 5.3% loss in protein identifications is observed. When off-line fractionated samples are loaded via an autosampler, a 44.5% loss in protein identifications is observed compared with direct loading of samples onto a triphasic capillary column. Moreover, peptide recovery was significantly lower after offline fractionation than in online fractionation. Signal-to-noise (S/N) ratio, however, was not significantly altered between experimental groups. It is likely that offline sample collection results in stochastic peptide loss due to noncovalent adsorption to solid surfaces. Therefore, the use of the offline approaches should be considered carefully when processing minute quantities of valuable samples. PMID:25040086

Using Multidimensional Grief Theory to Explore Effects of Deployment, Reintegration, and Death on Military Youth and Families

PubMed Central

Kaplow, Julie B.; Layne, Christopher M.; Saltzman, William R.; Cozza, Stephen J.; Pynoos, Robert S.

2015-01-01

To date, the U.S. military has made major strides in acknowledging and therapeutically addressing trauma and Posttraumatic Stress Disorder (PTSD) in service members and their families. However, given the nature of warfare and high rates of losses sustained by both military members (e.g., deaths of fellow unit members) and military families (e.g., loss of a young parent who served in the military), as well as the ongoing threat of loss that military families face during deployment, we propose that a similar focus on grief is also needed to properly understand and address many of the challenges encountered by bereaved service members, spouses, and children. In this article, we describe a newly developed theory of grief (Multidimensional Grief Theory) and apply it to the task of exploring major features of military-related experiences during the phases of deployment, reintegration, and the aftermath of combat death—especially as they impact children. We also describe implications for designing preventive interventions during each phase and conclude with recommended avenues for future research. Primary aims are to illustrate: (1) the indispensable role of theory in guiding efforts to describe, explain, predict, prevent, and treat maladaptive grief in military service members, children, and families; (2) the relevance of multidimensional grief theory for addressing both losses due to physical death as well as losses brought about by extended physical separations to which military children and families are exposed during and after deployment; and (3) a focus on military-related grief as a much-needed complement to an already-established focus on military-related PTSD. PMID:23760905

Using multidimensional grief theory to explore the effects of deployment, reintegration, and death on military youth and families.

PubMed

Kaplow, Julie B; Layne, Christopher M; Saltzman, William R; Cozza, Stephen J; Pynoos, Robert S

2013-09-01

To date, the US military has made major strides in acknowledging and therapeutically addressing trauma and post-traumatic stress disorder (PTSD) in service members and their families. However, given the nature of warfare and high rates of losses sustained by both military members (e.g., deaths of fellow unit members) and military families (e.g., loss of a young parent who served in the military), as well as the ongoing threat of loss that military families face during deployment, we propose that a similar focus on grief is also needed to properly understand and address many of the challenges encountered by bereaved service members, spouses, and children. In this article, we describe a newly developed theory of grief (multidimensional grief theory) and apply it to the task of exploring major features of military-related experiences during the phases of deployment, reintegration, and the aftermath of combat death--especially as they impact children. We also describe implications for designing preventive interventions during each phase and conclude with recommended avenues for future research. Primary aims are to illustrate: (1) the indispensable role of theory in guiding efforts to describe, explain, predict, prevent, and treat maladaptive grief in military service members, children, and families; (2) the relevance of multidimensional grief theory for addressing both losses due to physical death as well as losses brought about by extended physical separations to which military children and families are exposed during and after deployment; and (3) a focus on military-related grief as a much-needed complement to an already-established focus on military-related PTSD.

A Multidimensional B-Spline Correction for Accurate Modeling Sugar Puckering in QM/MM Simulations.

PubMed

Huang, Ming; Dissanayake, Thakshila; Kuechler, Erich; Radak, Brian K; Lee, Tai-Sung; Giese, Timothy J; York, Darrin M

2017-09-12

The computational efficiency of approximate quantum mechanical methods allows their use for the construction of multidimensional reaction free energy profiles. It has recently been demonstrated that quantum models based on the neglect of diatomic differential overlap (NNDO) approximation have difficulty modeling deoxyribose and ribose sugar ring puckers and thus limit their predictive value in the study of RNA and DNA systems. A method has been introduced in our previous work to improve the description of the sugar puckering conformational landscape that uses a multidimensional B-spline correction map (BMAP correction) for systems involving intrinsically coupled torsion angles. This method greatly improved the adiabatic potential energy surface profiles of DNA and RNA sugar rings relative to high-level ab initio methods even for highly problematic NDDO-based models. In the present work, a BMAP correction is developed, implemented, and tested in molecular dynamics simulations using the AM1/d-PhoT semiempirical Hamiltonian for biological phosphoryl transfer reactions. Results are presented for gas-phase adiabatic potential energy surfaces of RNA transesterification model reactions and condensed-phase QM/MM free energy surfaces for nonenzymatic and RNase A-catalyzed transesterification reactions. The results show that the BMAP correction is stable, efficient, and leads to improvement in both the potential energy and free energy profiles for the reactions studied, as compared with ab initio and experimental reference data. Exploration of the effect of the size of the quantum mechanical region indicates the best agreement with experimental reaction barriers occurs when the full CpA dinucleotide substrate is treated quantum mechanically with the sugar pucker correction.

Exploration of the Medicinal Peptide Space.

PubMed

Gevaert, Bert; Stalmans, Sofie; Wynendaele, Evelien; Taevernier, Lien; Bracke, Nathalie; D'Hondt, Matthias; De Spiegeleer, Bart

2016-01-01

The chemical properties of peptide medicines, known as the 'medicinal peptide space' is considered a multi-dimensional subset of the global peptide space, where each dimension represents a chemical descriptor. These descriptors can be linked to biofunctional, medicinal properties to varying degrees. Knowledge of this space can increase the efficiency of the peptide-drug discovery and development process, as well as advance our understanding and classification of peptide medicines. For 245 peptide drugs, already available on the market or in clinical development, multivariate dataexploration was performed using peptide relevant physicochemical descriptors, their specific peptidedrug target and their clinical use. Our retrospective analysis indicates that clusters in the medicinal peptide space are located in a relatively narrow range of the physicochemical space: dense and empty regions were found, which can be explored for the discovery of novel peptide drugs.

Amyloid PET in clinical practice: Its place in the multidimensional space of Alzheimer's disease☆

PubMed Central

Vandenberghe, Rik; Adamczuk, Katarzyna; Dupont, Patrick; Laere, Koen Van; Chételat, Gaël

2013-01-01

Amyloid imaging is currently introduced to the market for clinical use. We will review the evidence demonstrating that the different amyloid PET ligands that are currently available are valid biomarkers for Alzheimer-related β amyloidosis. Based on recent findings from cross-sectional and longitudinal imaging studies using different modalities, we will incorporate amyloid imaging into a multidimensional model of Alzheimer's disease. Aside from the critical role in improving clinical trial design for amyloid-lowering drugs, we will also propose a tentative algorithm for when it may be useful in a memory clinic environment. Gaps in our evidence-based knowledge of the added value of amyloid imaging in a clinical context will be identified and will need to be addressed by dedicated studies of clinical utility. PMID:24179802

Validity Study in Multidimensional Latent Space and Efficient Computerized Adaptive Testing. Final Report.

ERIC Educational Resources Information Center

Samejima, Fumiko

This paper is the final report of a multi-year project sponsored by the Office of Naval Research (ONR) in 1987 through 1990. The main objectives of the research summarized were to: investigate the non-parametric approach to the estimation of the operating characteristics of discrete item responses; revise and strengthen the package computer…

The National Mapping of Teacher Professional Learning Project: A Multi-Dimensional Space?

ERIC Educational Resources Information Center

Doecke, Brenton; Parr, Graham

2011-01-01

This essay focuses on the "National Mapping of Teacher Professional Learning" (2008), a report that we co-authored along with a number of other researchers on the basis of extensive surveys and interviews relating to the policies and practices of teacher professional learning in Australia. The report is an update of an earlier survey…

Separation of the atmospheric variability into non-Gaussian multidimensional sources by projection pursuit techniques

NASA Astrophysics Data System (ADS)

Pires, Carlos A. L.; Ribeiro, Andreia F. S.

2017-02-01

We develop an expansion of space-distributed time series into statistically independent uncorrelated subspaces (statistical sources) of low-dimension and exhibiting enhanced non-Gaussian probability distributions with geometrically simple chosen shapes (projection pursuit rationale). The method relies upon a generalization of the principal component analysis that is optimal for Gaussian mixed signals and of the independent component analysis (ICA), optimized to split non-Gaussian scalar sources. The proposed method, supported by information theory concepts and methods, is the independent subspace analysis (ISA) that looks for multi-dimensional, intrinsically synergetic subspaces such as dyads (2D) and triads (3D), not separable by ICA. Basically, we optimize rotated variables maximizing certain nonlinear correlations (contrast functions) coming from the non-Gaussianity of the joint distribution. As a by-product, it provides nonlinear variable changes `unfolding' the subspaces into nearly Gaussian scalars of easier post-processing. Moreover, the new variables still work as nonlinear data exploratory indices of the non-Gaussian variability of the analysed climatic and geophysical fields. The method (ISA, followed by nonlinear unfolding) is tested into three datasets. The first one comes from the Lorenz'63 three-dimensional chaotic model, showing a clear separation into a non-Gaussian dyad plus an independent scalar. The second one is a mixture of propagating waves of random correlated phases in which the emergence of triadic wave resonances imprints a statistical signature in terms of a non-Gaussian non-separable triad. Finally the method is applied to the monthly variability of a high-dimensional quasi-geostrophic (QG) atmospheric model, applied to the Northern Hemispheric winter. We find that quite enhanced non-Gaussian dyads of parabolic shape, perform much better than the unrotated variables in which concerns the separation of the four model's centroid regimes (positive and negative phases of the Arctic Oscillation and of the North Atlantic Oscillation). Triads are also likely in the QG model but of weaker expression than dyads due to the imposed shape and dimension. The study emphasizes the existence of nonlinear dyadic and triadic nonlinear teleconnections.

Mode-Selective Photon Counting Via Quantum Frequency Conversion Using Spectrally-Engineered Pump Pulses

NASA Astrophysics Data System (ADS)

Manurkar, Paritosh

Most of the existing protocols for quantum communication operate in a two-dimensional Hilbert space where their manipulation and measurement have been routinely investigated. Moving to higher-dimensional Hilbert spaces is desirable because of advantages in terms of longer distance communication capabilities, higher channel capacity and better information security. We can exploit the spatio-temporal degrees of freedom for the quantum optical signals to provide the higher-dimensional signals. But this necessitates the need for measurement and manipulation of multidimensional quantum states. To that end, there have been significant theoretical studies based on quantum frequency conversion (QFC) in recent years even though the experimental progress has been limited. QFC is a process that allows preservation of the quantum information while changing the frequency of the input quantum state. It has deservedly garnered a lot of attention because it serves as the connecting bridge between the communications band (C-band near 1550 nm) where the fiber-optic infrastructure is already established and the visible spectrum where high efficiency single-photon detectors and optical memories have been demonstrated. In this experimental work, we demonstrate mode-selective frequency conversion as a means to measure and manipulate photonic signals occupying d -dimensional Hilbert spaces where d=2 and 4. In the d=2 case, we demonstrate mode contrast between two temporal modes (TMs) which serves as the proof-of-concept demonstration. In the d=4 version, we employ six different TMs for our detailed experimental study. These TMs also include superposition modes which are a crucial component in many quantum key distribution protocols. Our method is based on producing pump pulses which allow us to upconvert the TM of interest while ideally preserving the other modes. We use MATLAB simulations to determine the pump pulse shapes which are subsequently produced by controlling the amplitude and phase of each spectral frequency from an optical frequency comb. The latter is generated using a cascaded configuration of phase and amplitude modulators. We characterize the mode selectivity using classical signals by arranging the six TMs into two orthogonal signal sets. Furthermore, we also demonstrate that mode selectivity is preserved if we use sub-photon signals (weak coherent light). Thus, this work supports the idea that QFC has the basic properties needed for advanced multi-dimensional quantum measurements given that we have demonstrated for the first time the ability to move to high dimensions (d=4), measure coherent superposition modes, and measure sub-photon signal levels. In addition to mode-selective photon counting, we also experimentally demonstrate a method of reshaping optical pulses based on QFC. Such a method has the potential to serve as the interface between quantum memories and the existing fiber infrastructure. At the same time, it can be employed in all-optical systems for optical signal regeneration.

Evolutionary profiles derived from the QR factorization of multiple structural alignments gives an economy of information.

PubMed

O'Donoghue, Patrick; Luthey-Schulten, Zaida

2005-02-25

We present a new algorithm, based on the multidimensional QR factorization, to remove redundancy from a multiple structural alignment by choosing representative protein structures that best preserve the phylogenetic tree topology of the homologous group. The classical QR factorization with pivoting, developed as a fast numerical solution to eigenvalue and linear least-squares problems of the form Ax=b, was designed to re-order the columns of A by increasing linear dependence. Removing the most linear dependent columns from A leads to the formation of a minimal basis set which well spans the phase space of the problem at hand. By recasting the problem of redundancy in multiple structural alignments into this framework, in which the matrix A now describes the multiple alignment, we adapted the QR factorization to produce a minimal basis set of protein structures which best spans the evolutionary (phase) space. The non-redundant and representative profiles obtained from this procedure, termed evolutionary profiles, are shown in initial results to outperform well-tested profiles in homology detection searches over a large sequence database. A measure of structural similarity between homologous proteins, Q(H), is presented. By properly accounting for the effect and presence of gaps, a phylogenetic tree computed using this metric is shown to be congruent with the maximum-likelihood sequence-based phylogeny. The results indicate that evolutionary information is indeed recoverable from the comparative analysis of protein structure alone. Applications of the QR ordering and this structural similarity metric to analyze the evolution of structure among key, universally distributed proteins involved in translation, and to the selection of representatives from an ensemble of NMR structures are also discussed.

Systematization of actinides using cluster analysis

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

Kopyrin, A.A.; Terent`eva, T.N.; Khramov, N.N.

1994-11-01

A representation of the actinides in multidimensional property space is proposed for systematization of these elements using cluster analysis. Literature data for their atomic properties are used. Owing to the wide variation of published ionization potentials, medians are used to estimate them. Vertical dendograms are used for classification on the basis of distances between the actinides in atomic-property space. The properties of actinium and lawrencium are furthest removed from the main group. Thorium and mendelevium exhibit individualized properties. A cluster based on the einsteinium-fermium pair is joined by californium.

On the enhanced sampling over energy barriers in molecular dynamics simulations.

PubMed

Gao, Yi Qin; Yang, Lijiang

2006-09-21

We present here calculations of free energies of multidimensional systems using an efficient sampling method. The method uses a transformed potential energy surface, which allows an efficient sampling of both low and high energy spaces and accelerates transitions over barriers. It allows efficient sampling of the configuration space over and only over the desired energy range(s). It does not require predetermined or selected reaction coordinate(s). We apply this method to study the dynamics of slow barrier crossing processes in a disaccharide and a dipeptide system.

The COSMIC-DANCE project: Unravelling the origin of the mass function

NASA Astrophysics Data System (ADS)

Bouy, H.; Bertin, E.; Sarro, L. M.; Barrado, D.; Berihuete, A.; Olivares, J.; Moraux, E.; Bouvier, J.; Tamura, M.; Cuillandre, J.-C.; Beletsky, Y.; Wright, N.; Huelamo, N.; Allen, L.; Solano, E.; Brandner, B.

2017-03-01

The COSMIC-DANCE project is an observational program aiming at understanding the origin and evolution of ultracool objects by measuring the mass function and internal dynamics of young nearby associations down to the fragmentation limit. The least massive members of young nearby associations are identified using modern statistical methods in a multi-dimensional space made of optical and infrared luminosities and colors and proper motions. The photometry and astrometry are obtained by combining ground and in some case space based archival observations with new observations, covering between one and two decades.

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.

Core-collapse supernovae as supercomputing science: A status report toward six-dimensional simulations with exact Boltzmann neutrino transport in full general relativity

NASA Astrophysics Data System (ADS)

Kotake, Kei; Sumiyoshi, Kohsuke; Yamada, Shoichi; Takiwaki, Tomoya; Kuroda, Takami; Suwa, Yudai; Nagakura, Hiroki

2012-08-01

This is a status report on our endeavor to reveal the mechanism of core-collapse supernovae (CCSNe) by large-scale numerical simulations. Multi-dimensionality of the supernova engine, general relativistic magnetohydrodynamics, energy and lepton number transport by neutrinos emitted from the forming neutron star, as well as nuclear interactions there, are all believed to play crucial roles in repelling infalling matter and producing energetic explosions. These ingredients are non-linearly coupled with one another in the dynamics of core collapse, bounce, and shock expansion. Serious quantitative studies of CCSNe hence make extensive numerical computations mandatory. Since neutrinos are neither in thermal nor in chemical equilibrium in general, their distributions in the phase space should be computed. This is a six-dimensional (6D) neutrino transport problem and quite a challenge, even for those with access to the most advanced numerical resources such as the "K computer". To tackle this problem, we have embarked on efforts on multiple fronts. In particular, we report in this paper our recent progresses in the treatment of multidimensional (multi-D) radiation hydrodynamics. We are currently proceeding on two different paths to the ultimate goal. In one approach, we employ an approximate but highly efficient scheme for neutrino transport and treat 3D hydrodynamics and/or general relativity rigorously; some neutrino-driven explosions will be presented and quantitative comparisons will be made between 2D and 3D models. In the second approach, on the other hand, exact, but so far Newtonian, Boltzmann equations are solved in two and three spatial dimensions; we will show some example test simulations. We will also address the perspectives of exascale computations on the next generation supercomputers.

EOSCUBE: A Constraint Database System for High-Level Specification and Efficient Generation of EOSDIS Products. Phase 1; Proof-of-Concept

NASA Technical Reports Server (NTRS)

Brodsky, Alexander; Segal, Victor E.

1999-01-01

The EOSCUBE constraint database system is designed to be a software productivity tool for high-level specification and efficient generation of EOSDIS and other scientific products. These products are typically derived from large volumes of multidimensional data which are collected via a range of scientific instruments.

Multi-dimensional free-electron laser simulation codes : a comparison study.

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

Biedron, S. G.; Chae, Y. C.; Dejus, R. J.

A self-amplified spontaneous emission (SASE) free-electron laser (FEL) is under construction at the Advanced Photon Source (APS). Five FEL simulation codes were used in the design phase: GENESIS, GINGER, MEDUSA, RON, and TDA3D. Initial comparisons between each of these independent formulations show good agreement for the parameters of the APS SASE FEL.

Multi-Dimensional Free-Electron Laser Simulation Codes: A Comparison Study

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

Nuhn, Heinz-Dieter

A self-amplified spontaneous emission (SASE) free-electron laser (FEL) is under construction at the Advanced Photon Source (APS). Five FEL simulation codes were used in the design phase: GENESIS, GINGER, MEDUSA, RON, and TDA3D. Initial comparisons between each of these independent formulations show good agreement for the parameters of the APS SASE FEL.

Visualization of anisotropic-isotropic phase transformation dynamics in battery electrode particles

DOE PAGES

Wang, Jiajun; Karen Chen-Wiegart, Yu-chen; Eng, Christopher; ...

2016-08-12

Anisotropy, or alternatively, isotropy of phase transformations extensively exist in a number of solid-state materials, with performance depending on the three-dimensional transformation features. Fundamental insights into internal chemical phase evolution allow manipulating materials with desired functionalities, and can be developed via real-time multi-dimensional imaging methods. In this paper, we report a five-dimensional imaging method to track phase transformation as a function of charging time in individual lithium iron phosphate battery cathode particles during delithiation. The electrochemically driven phase transformation is initially anisotropic with a preferred boundary migration direction, but becomes isotropic as delithiation proceeds further. We also observe the expectedmore » two-phase coexistence throughout the entire charging process. Finally, we expect this five-dimensional imaging method to be broadly applicable to problems in energy, materials, environmental and life sciences.« less

Variational transition state theory: theoretical framework and recent developments.

PubMed

Bao, Junwei Lucas; Truhlar, Donald G

2017-12-11

This article reviews the fundamentals of variational transition state theory (VTST), its recent theoretical development, and some modern applications. The theoretical methods reviewed here include multidimensional quantum mechanical tunneling, multistructural VTST (MS-VTST), multi-path VTST (MP-VTST), both reaction-path VTST (RP-VTST) and variable reaction coordinate VTST (VRC-VTST), system-specific quantum Rice-Ramsperger-Kassel theory (SS-QRRK) for predicting pressure-dependent rate constants, and VTST in the solid phase, liquid phase, and enzymes. We also provide some perspectives regarding the general applicability of VTST.

The multiuniverse transition in superfluid 3He

NASA Astrophysics Data System (ADS)

Bunkov, Yury

2013-10-01

The symmetry-breaking phase transitions of the universe and of superfluid 3He may lead to the formation of different states with different order parameters. In both cases the energy potential below the transition temperature has a complicated multidimensional profile with many local minima and saddle points, which correspond to different states. Consequently, not only topological defects, but also islands of different metastable states can be created. Using 3He we can analyse the properties and experimental consequences of such transitions and, in particular, the first-order phase transition between the two low symmetry states.

The multiuniverse transition in superfluid 3He.

PubMed

Bunkov, Yury

2013-10-09

The symmetry-breaking phase transitions of the universe and of superfluid (3)He may lead to the formation of different states with different order parameters. In both cases the energy potential below the transition temperature has a complicated multidimensional profile with many local minima and saddle points, which correspond to different states. Consequently, not only topological defects, but also islands of different metastable states can be created. Using (3)He we can analyse the properties and experimental consequences of such transitions and, in particular, the first-order phase transition between the two low symmetry states.

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.

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.

Manycore Performance-Portability: Kokkos Multidimensional Array Library

DOE PAGES

Edwards, H. Carter; Sunderland, Daniel; Porter, Vicki; ...

2012-01-01

Large, complex scientific and engineering application code have a significant investment in computational kernels to implement their mathematical models. Porting these computational kernels to the collection of modern manycore accelerator devices is a major challenge in that these devices have diverse programming models, application programming interfaces (APIs), and performance requirements. The Kokkos Array programming model provides library-based approach to implement computational kernels that are performance-portable to CPU-multicore and GPGPU accelerator devices. This programming model is based upon three fundamental concepts: (1) manycore compute devices each with its own memory space, (2) data parallel kernels and (3) multidimensional arrays. Kernel executionmore » performance is, especially for NVIDIA® devices, extremely dependent on data access patterns. Optimal data access pattern can be different for different manycore devices – potentially leading to different implementations of computational kernels specialized for different devices. The Kokkos Array programming model supports performance-portable kernels by (1) separating data access patterns from computational kernels through a multidimensional array API and (2) introduce device-specific data access mappings when a kernel is compiled. An implementation of Kokkos Array is available through Trilinos [Trilinos website, http://trilinos.sandia.gov/, August 2011].« less

Application of musical timbre discrimination features to active sonar classification

NASA Astrophysics Data System (ADS)

Young, Victor W.; Hines, Paul C.; Pecknold, Sean

2005-04-01

In musical acoustics significant effort has been devoted to uncovering the physical basis of timbre perception. Most investigations into timbre rely on multidimensional scaling (MDS), in which different musical sounds are arranged as points in multidimensional space. The Euclidean distance between points corresponds to the perceptual distance between sounds and the multidimensional axes are linked to measurable properties of the sounds. MDS has identified numerous temporal and spectral features believed to be important to timbre perception. There is reason to believe that some of these features may have wider application in the disparate field of underwater acoustics, since anecdotal evidence suggests active sonar returns from metallic objects sound different than natural clutter returns when auralized by human operators. This is particularly encouraging since attempts to develop robust automatic classifiers capable of target-clutter discrimination over a wide range of operational conditions have met with limited success. Spectral features relevant to target-clutter discrimination are believed to include click-pitch and envelope irregularity; relevant temporal features are believed to include duration, sub-band attack/decay time, and time separation pitch. Preliminary results from an investigation into the role of these timbre features in target-clutter discrimination will be presented. [Work supported by NSERC and GDC.

Multidimensional Conservation Laws and Low Regularity Solutions

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

Barbara Lee Keyfitz

This is the concluding report for the project, a continuation of research by Keyfitz and co-workers on multidimensional conservation laws, and applications of nonhyperbolic conservation laws in the two-fluid model for multiphase flow. The multidimensional research project was started with Suncica Canic, at the University of Houston and with Eun Heui Kim, now at California State University Long Beach. Two postdoctoral researchers, Katarina Jegdic and Allen Tesdall, also worked on this research. Jegdic's research was supported (for a total of one year) by this grant. Work on nonhyperbolic models for two-phase flows is being pursued jointly with Michael Sever, Hebrewmore » University. Background for the project is contained in earlier reports. Note that in 2006, the project received a one-year no-cost extension that will end in September, 2007. A new proposal, for continuation of the research and for new projects, will be submitted in the Fall of 2007, with funding requested to begin in the summer of 2008. The reason for the 'funding gap' is Keyfitz's four-year stint as Director of the Fields Institute in Toronto, Canada. The research has continued, but has been supported by Canadian grant funds, as seems appropriate during this period.« less

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.

Plasticity of Arabidopsis root gravitropism throughout a multidimensional condition space quantified by automated image analysis.

PubMed

Brooks, Tessa L Durham; Miller, Nathan D; Spalding, Edgar P

2010-01-01

Plant development is genetically determined but it is also plastic, a fundamental duality that can be investigated provided large number of measurements can be made in various conditions. Plasticity of gravitropism in wild-type Arabidopsis (Arabidopsis thaliana) seedling roots was investigated using automated image acquisition and analysis. A bank of computer-controlled charge-coupled device cameras acquired images with high spatiotemporal resolution. Custom image analysis algorithms extracted time course measurements of tip angle and growth rate. Twenty-two discrete conditions defined by seedling age (2, 3, or 4 d), seed size (extra small, small, medium, or large), and growth medium composition (simple or rich) formed the condition space sampled with 1,216 trials. Computational analyses including dimension reduction by principal components analysis, classification by k-means clustering, and differentiation by wavelet convolution showed distinct response patterns within the condition space, i.e. response plasticity. For example, 2-d-old roots (regardless of seed size) displayed a response time course similar to those of roots from large seeds (regardless of age). Enriching the growth medium with nutrients suppressed response plasticity along the seed size and age axes, possibly by ameliorating a mineral deficiency, although analysis of seeds did not identify any elements with low levels on a per weight basis. Characterizing relationships between growth rate and tip swing rate as a function of condition cast gravitropism in a multidimensional response space that provides new mechanistic insights as well as conceptually setting the stage for mutational analysis of plasticity in general and root gravitropism in particular.

Plasticity of Arabidopsis Root Gravitropism throughout a Multidimensional Condition Space Quantified by Automated Image Analysis1[W][OA

PubMed Central

Durham Brooks, Tessa L.; Miller, Nathan D.; Spalding, Edgar P.

2010-01-01

Plant development is genetically determined but it is also plastic, a fundamental duality that can be investigated provided large number of measurements can be made in various conditions. Plasticity of gravitropism in wild-type Arabidopsis (Arabidopsis thaliana) seedling roots was investigated using automated image acquisition and analysis. A bank of computer-controlled charge-coupled device cameras acquired images with high spatiotemporal resolution. Custom image analysis algorithms extracted time course measurements of tip angle and growth rate. Twenty-two discrete conditions defined by seedling age (2, 3, or 4 d), seed size (extra small, small, medium, or large), and growth medium composition (simple or rich) formed the condition space sampled with 1,216 trials. Computational analyses including dimension reduction by principal components analysis, classification by k-means clustering, and differentiation by wavelet convolution showed distinct response patterns within the condition space, i.e. response plasticity. For example, 2-d-old roots (regardless of seed size) displayed a response time course similar to those of roots from large seeds (regardless of age). Enriching the growth medium with nutrients suppressed response plasticity along the seed size and age axes, possibly by ameliorating a mineral deficiency, although analysis of seeds did not identify any elements with low levels on a per weight basis. Characterizing relationships between growth rate and tip swing rate as a function of condition cast gravitropism in a multidimensional response space that provides new mechanistic insights as well as conceptually setting the stage for mutational analysis of plasticity in general and root gravitropism in particular. PMID:19923240

Visualizing Structure and Dynamics of Disaccharide Simulations

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

Matthews, J. F.; Beckham, G. T.; Himmel, M. E.

2012-01-01

We examine the effect of several solvent models on the conformational properties and dynamics of disaccharides such as cellobiose and lactose. Significant variation in timescale for large scale conformational transformations are observed. Molecular dynamics simulation provides enough detail to enable insight through visualization of multidimensional data sets. We present a new way to visualize conformational space for disaccharides with Ramachandran plots.

The Circumplex Model of the Questionnaire on Teacher Interaction among Hong Kong Students: A Multidimensional Scaling Solution

ERIC Educational Resources Information Center

Sivan, Atara; Cohen, Arie; Chan, Dennis W.; Kwan, Yee Wan

2017-01-01

The Questionnaire on Teacher Interaction (QTI) is a teacher--student relationship measure whose underlying two-dimensional structure is represented in a circumplex model with eight sectors. Using Smallest Space Analysis (SSA), this study examined the circumplex structure of the Chinese version of the QTI among a convenience sample of 731…

The Earth Is Flat when Personally Significant Experiences with the Sphericity of the Earth Are Absent

ERIC Educational Resources Information Center

Carbon, Claus-Christian

2010-01-01

Participants with personal and without personal experiences with the Earth as a sphere estimated large-scale distances between six cities located on different continents. Cognitive distances were submitted to a specific multidimensional scaling algorithm in the 3D Euclidean space with the constraint that all cities had to lie on the same sphere. A…

A Latent Class Multidimensional Scaling Model for Two-Way One-Mode Continuous Rating Dissimilarity Data

ERIC Educational Resources Information Center

Vera, J. Fernando; Macias, Rodrigo; Heiser, Willem J.

2009-01-01

In this paper, we propose a cluster-MDS model for two-way one-mode continuous rating dissimilarity data. The model aims at partitioning the objects into classes and simultaneously representing the cluster centers in a low-dimensional space. Under the normal distribution assumption, a latent class model is developed in terms of the set of…

The Integration of Delta Prime (f)in a Multidimensional Space

NASA Technical Reports Server (NTRS)

Farassat, F.

1999-01-01

Consideration is given to the thickness noise term of the Ffowcs Williams-Hawkings equation when the time derivative is taken explicitly. An interpretation is presented of the integral I = function phi(x)delta-prime(f) dx, where it is initially assumed that the absolute value of Del-f is not equal to 1 on the surface f = 0.

The Role of Student Loan Programs in Higher Education Policy in the United States

ERIC Educational Resources Information Center

Amatya, Sachi

2009-01-01

The increasing cost of higher education, coupled with the inability of federal and state governments to sustain parallel increases in levels of funding for student financial aid, has led to significant growth of student loans. This project analyzes the multidimensional student loans space in the US. This project also compares and contrasts some of…

Male/Female Preferences for Masculine-Feminine Trait Clusters Derived from a Multidimensional Scaling of Hypothesized Masculine-Feminine and Creative-Noncreative Trait Terms.

ERIC Educational Resources Information Center

Hyman, Ruth Bernstein

There still remains in our social institutions and individual lives a considerable splitting between feminine and masculine gender distinctions. The present study determined the dimensionality of the space of 53 admirable personality traits hypothesized to relate to femininity-masculinity and creativity, and assessed preferences of females versus…

Fast and high-order numerical algorithms for the solution of multidimensional nonlinear fractional Ginzburg-Landau equation

NASA Astrophysics Data System (ADS)

Mohebbi, Akbar

2018-02-01

In this paper we propose two fast and accurate numerical methods for the solution of multidimensional space fractional Ginzburg-Landau equation (FGLE). In the presented methods, to avoid solving a nonlinear system of algebraic equations and to increase the accuracy and efficiency of method, we split the complex problem into simpler sub-problems using the split-step idea. For a homogeneous FGLE, we propose a method which has fourth-order of accuracy in time component and spectral accuracy in space variable and for nonhomogeneous one, we introduce another scheme based on the Crank-Nicolson approach which has second-order of accuracy in time variable. Due to using the Fourier spectral method for fractional Laplacian operator, the resulting schemes are fully diagonal and easy to code. Numerical results are reported in terms of accuracy, computational order and CPU time to demonstrate the accuracy and efficiency of the proposed methods and to compare the results with the analytical solutions. The results show that the present methods are accurate and require low CPU time. It is illustrated that the numerical results are in good agreement with the theoretical ones.

Shape determination and control for large space structures

NASA Technical Reports Server (NTRS)

Weeks, C. J.

1981-01-01

An integral operator approach is used to derive solutions to static shape determination and control problems associated with large space structures. Problem assumptions include a linear self-adjoint system model, observations and control forces at discrete points, and performance criteria for the comparison of estimates or control forms. Results are illustrated by simulations in the one dimensional case with a flexible beam model, and in the multidimensional case with a finite model of a large space antenna. Modal expansions for terms in the solution algorithms are presented, using modes from the static or associated dynamic mode. These expansions provide approximated solutions in the event that a used form analytical solution to the system boundary value problem is not available.

Dissociation of performance and subjective measures of workload

NASA Technical Reports Server (NTRS)

Yeh, Yei-Yu; Wickens, Christopher D.

1988-01-01

A theory is presented to identify sources that produce dissociations between performance and subjective measures of workload. The theory states that performance is determined by (1) amount of resources invested, (2) resource efficiency, and (3) degree of competition for common resources in a multidimensional space described in the multiple-resources model. Subjective perception of workload, multidimensional in nature, increases with greater amounts of resource investment and with greater demands on working memory. Performance and subjective workload measures dissociate when greater resources are invested to improve performance of a resource-limited task; when demands on working memory are increased by time-sharing between concurrent tasks or between display elements; and when performance is sensitive to resource competition and subjective measures are more sensitive to total investment. These dissociation findings and their implications are discussed and directions for future research are suggested.

A Robust Absorbing Boundary Condition for Compressible Flows

NASA Technical Reports Server (NTRS)

Loh, Ching Y.; orgenson, Philip C. E.

2005-01-01

An absorbing non-reflecting boundary condition (NRBC) for practical computations in fluid dynamics and aeroacoustics is presented with theoretical proof. This paper is a continuation and improvement of a previous paper by the author. The absorbing NRBC technique is based on a first principle of non reflecting, which contains the essential physics that a plane wave solution of the Euler equations remains intact across the boundary. The technique is theoretically shown to work for a large class of finite volume approaches. When combined with the hyperbolic conservation laws, the NRBC is simple, robust and truly multi-dimensional; no additional implementation is needed except the prescribed physical boundary conditions. Several numerical examples in multi-dimensional spaces using two different finite volume schemes are illustrated to demonstrate its robustness in practical computations. Limitations and remedies of the technique are also discussed.

High-Order Semi-Discrete Central-Upwind Schemes for Multi-Dimensional Hamilton-Jacobi Equations

NASA Technical Reports Server (NTRS)

Bryson, Steve; Levy, Doron; Biegel, Bryan (Technical Monitor)

2002-01-01

We present the first fifth order, semi-discrete central upwind method for approximating solutions of multi-dimensional Hamilton-Jacobi equations. Unlike most of the commonly used high order upwind schemes, our scheme is formulated as a Godunov-type scheme. The scheme is based on the fluxes of Kurganov-Tadmor and Kurganov-Tadmor-Petrova, and is derived for an arbitrary number of space dimensions. A theorem establishing the monotonicity of these fluxes is provided. The spacial discretization is based on a weighted essentially non-oscillatory reconstruction of the derivative. The accuracy and stability properties of our scheme are demonstrated in a variety of examples. A comparison between our method and other fifth-order schemes for Hamilton-Jacobi equations shows that our method exhibits smaller errors without any increase in the complexity of the computations.

Multidimensional fractional Schrödinger equation

NASA Astrophysics Data System (ADS)

Rodrigues, M. M.; Vieira, N.

2012-11-01

This work is intended to investigate the multi-dimensional space-time fractional Schrödinger equation of the form (CDt0+αu)(t,x) = iħ/2m(C∇βu)(t,x), with ħ the Planck's constant divided by 2π, m is the mass and u(t,x) is a wave function of the particle. Here (CDt0+α,C∇β are operators of the Caputo fractional derivatives, where α ∈]0,1] and β ∈]1,2]. The wave function is obtained using Laplace and Fourier transforms methods and a symbolic operational form of solutions in terms of the Mittag-Leffler functions is exhibited. It is presented an expression for the wave function and for the quantum mechanical probability density. Using Banach fixed point theorem, the existence and uniqueness of solutions is studied for this kind of fractional differential equations.

Sequential memory: Binding dynamics

NASA Astrophysics Data System (ADS)

Afraimovich, Valentin; Gong, Xue; Rabinovich, Mikhail

2015-10-01

Temporal order memories are critical for everyday animal and human functioning. Experiments and our own experience show that the binding or association of various features of an event together and the maintaining of multimodality events in sequential order are the key components of any sequential memories—episodic, semantic, working, etc. We study a robustness of binding sequential dynamics based on our previously introduced model in the form of generalized Lotka-Volterra equations. In the phase space of the model, there exists a multi-dimensional binding heteroclinic network consisting of saddle equilibrium points and heteroclinic trajectories joining them. We prove here the robustness of the binding sequential dynamics, i.e., the feasibility phenomenon for coupled heteroclinic networks: for each collection of successive heteroclinic trajectories inside the unified networks, there is an open set of initial points such that the trajectory going through each of them follows the prescribed collection staying in a small neighborhood of it. We show also that the symbolic complexity function of the system restricted to this neighborhood is a polynomial of degree L - 1, where L is the number of modalities.

Applying the methodology of Design of Experiments to stability studies: a Partial Least Squares approach for evaluation of drug stability.

PubMed

Jordan, Nika; Zakrajšek, Jure; Bohanec, Simona; Roškar, Robert; Grabnar, Iztok

2018-05-01

The aim of the present research is to show that the methodology of Design of Experiments can be applied to stability data evaluation, as they can be seen as multi-factor and multi-level experimental designs. Linear regression analysis is usually an approach for analyzing stability data, but multivariate statistical methods could also be used to assess drug stability during the development phase. Data from a stability study for a pharmaceutical product with hydrochlorothiazide (HCTZ) as an unstable drug substance was used as a case example in this paper. The design space of the stability study was modeled using Umetrics MODDE 10.1 software. We showed that a Partial Least Squares model could be used for a multi-dimensional presentation of all data generated in a stability study and for determination of the relationship among factors that influence drug stability. It might also be used for stability predictions and potentially for the optimization of the extent of stability testing needed to determine shelf life and storage conditions, which would be time and cost-effective for the pharmaceutical industry.

Improving the signal subtle feature extraction performance based on dual improved fractal box dimension eigenvectors

NASA Astrophysics Data System (ADS)

Chen, Xiang; Li, Jingchao; Han, Hui; Ying, Yulong

2018-05-01

Because of the limitations of the traditional fractal box-counting dimension algorithm in subtle feature extraction of radiation source signals, a dual improved generalized fractal box-counting dimension eigenvector algorithm is proposed. First, the radiation source signal was preprocessed, and a Hilbert transform was performed to obtain the instantaneous amplitude of the signal. Then, the improved fractal box-counting dimension of the signal instantaneous amplitude was extracted as the first eigenvector. At the same time, the improved fractal box-counting dimension of the signal without the Hilbert transform was extracted as the second eigenvector. Finally, the dual improved fractal box-counting dimension eigenvectors formed the multi-dimensional eigenvectors as signal subtle features, which were used for radiation source signal recognition by the grey relation algorithm. The experimental results show that, compared with the traditional fractal box-counting dimension algorithm and the single improved fractal box-counting dimension algorithm, the proposed dual improved fractal box-counting dimension algorithm can better extract the signal subtle distribution characteristics under different reconstruction phase space, and has a better recognition effect with good real-time performance.

Sequential memory: Binding dynamics.

PubMed

Afraimovich, Valentin; Gong, Xue; Rabinovich, Mikhail

2015-10-01

Temporal order memories are critical for everyday animal and human functioning. Experiments and our own experience show that the binding or association of various features of an event together and the maintaining of multimodality events in sequential order are the key components of any sequential memories-episodic, semantic, working, etc. We study a robustness of binding sequential dynamics based on our previously introduced model in the form of generalized Lotka-Volterra equations. In the phase space of the model, there exists a multi-dimensional binding heteroclinic network consisting of saddle equilibrium points and heteroclinic trajectories joining them. We prove here the robustness of the binding sequential dynamics, i.e., the feasibility phenomenon for coupled heteroclinic networks: for each collection of successive heteroclinic trajectories inside the unified networks, there is an open set of initial points such that the trajectory going through each of them follows the prescribed collection staying in a small neighborhood of it. We show also that the symbolic complexity function of the system restricted to this neighborhood is a polynomial of degree L - 1, where L is the number of modalities.

Uncertainty in modeled upper ocean heat content change

NASA Astrophysics Data System (ADS)

Tokmakian, Robin; Challenor, Peter

2014-02-01

This paper examines the uncertainty in the change in the heat content in the ocean component of a general circulation model. We describe the design and implementation of our statistical methodology. Using an ensemble of model runs and an emulator, we produce an estimate of the full probability distribution function (PDF) for the change in upper ocean heat in an Atmosphere/Ocean General Circulation Model, the Community Climate System Model v. 3, across a multi-dimensional input space. We show how the emulator of the GCM's heat content change and hence, the PDF, can be validated and how implausible outcomes from the emulator can be identified when compared to observational estimates of the metric. In addition, the paper describes how the emulator outcomes and related uncertainty information might inform estimates of the same metric from a multi-model Coupled Model Intercomparison Project phase 3 ensemble. We illustrate how to (1) construct an ensemble based on experiment design methods, (2) construct and evaluate an emulator for a particular metric of a complex model, (3) validate the emulator using observational estimates and explore the input space with respect to implausible outcomes and (4) contribute to the understanding of uncertainties within a multi-model ensemble. Finally, we estimate the most likely value for heat content change and its uncertainty for the model, with respect to both observations and the uncertainty in the value for the input parameters.

Multidimensional gray-wavelet processing in interferometric fiber-optic gyroscopes

NASA Astrophysics Data System (ADS)

Yang, Yi; Wang, Zinan; Peng, Chao; Li, Zhengbin

2013-11-01

A multidimensional signal processing method for a single interferometric fiber-optic gyroscope (IFOG) is proposed, to the best of our knowledge, for the first time. The proposed method, based on a novel IFOG structure with quadrature demodulation, combines a multidimensional gray model (GM) and a wavelet compression technique for noise suppression and sensitivity enhancement. In the IFOG, two series of measured rotation rates are obtained simultaneously: an in-phase component and a quadrature component. Together with the traditionally measured rate, the three measured rates are processed by the combined gray-wavelet method. Simulations show that the intensity noise and non-reciprocal phase fluctuations are effectively suppressed by this method. Experimental comparisons with a one-dimensional GM(1, 1) model show that the proposed three-dimensional method achieves much better denoising performance. This advantage is validated by the Allan variance analysis: in a low-SNR (signal-to-noise ratio) experiment, our method reduces the angle random walk (ARW) and the bias instability (BI) from 1 × 10-2 deg h-1/2 and 3 × 10-2 deg h-1 to 1 × 10-3 deg h-1/2 and 3 × 10-3 deg h-1, respectively; in a high-SNR experiment, our method reduces the ARW and the BI from 9 × 10-4 deg h-1/2 and 5 × 10-3 deg h-1 to 4 × 10-4 deg h-1/2 and 3 × 10-3 deg h-1, respectively. Further, our method increases the dimension of the state-of-the-art IFOG technique from one to three, thus obtaining higher IFOG sensitivity and stability by exploiting the increase in available information.

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.

Lab-X-ray multidimensional imaging of processes inside porous media

NASA Astrophysics Data System (ADS)

Godinho, Jose

2017-04-01

Time-lapse and other multidimensional X-ray imaging techniques have mostly been applied using synchrotron radiation, which limits accessibility and complicates data analysis. Here, we present new time-lapse imaging approaches using laboratory X-ray computed microtomography (CT) to study transformations inside porous media. Specifically, three methods will be presented: 1) Quantitative time-lapse radiography to study sub-second processes. For example to study the penetration of particles into fractures and pores, which is essential to understand how proppants keep fractures opened during hydraulic fracturing and how filter cakes form during borehole drilling. 2) Combination of time-lapse CT with diffraction tomography to study the transformation between bio-inspired polymorphs in 6D, e.g. mineral phase transformation between ACC, Vaterite and Calcite - CaCO3, and between ACS, Anhydrite and Gypsum - CaSO4. Crystals can be resolved in nanopores down to 7 nm (over 100 times smaller than the resolution of CT), which allows studying the effect of confinement on phase stability and growth rates. 3) Fast iterative helical micro-CT scanning to study samples of high ratio height to width (e.g. long cores) with optimal resolution. Here we show how this can be useful to study the distribution of the products from fluid-mediated mineral reactions throughout longer reaction paths and more representative volumes. Using state of the art reconstruction algorithms allows reducing the scanning times from over ten hours to below two hours enabling time-lapse studies. It is expected that these new techniques will open new possibilities for time-lapse imaging of a wider range of geological processes using laboratory X-ray CT, thereby increasing the accessibility of multidimensional imaging to a larger number of users and applications in geology.

Multidimensional profiling of plasma lipoproteins by size exclusion chromatography followed by reverse-phase protein arrays

PubMed Central

Dernick, Gregor; Obermüller, Stefan; Mangold, Cyrill; Magg, Christine; Matile, Hugues; Gutmann, Oliver; von der Mark, Elisabeth; Handschin, Corinne; Maugeais, Cyrille; Niesor, Eric J.

2011-01-01

The composition of lipoproteins and the association of proteins with various particles are of much interest in the context of cardiovascular disease. Here, we describe a technique for the multidimensional analysis of lipoproteins and their associated apolipoproteins. Plasma is separated by size exclusion chromatography (SEC), and fractions are analyzed by reverse-phase arrays. SEC fractions are spotted on nitrocellulose slides and incubated with different antibodies against individual apolipoproteins or antibodies against various apolipoproteins. In this way, tens of analytes can be measured simultaneously in 100 μl of plasma from a single SEC separation. This methodology is particularly suited to simultaneous analysis of multiple proteins that may change their distribution to lipoproteins or alter their conformation, depending on factors that influence circulating lipoprotein size or composition. We observed changes in the distribution of exchangeable apolipoproteins following addition of recombinant apolipoproteins or interaction with exogenous compounds. While the cholesteryl ester transfer protein (CETP)-dependent formation of pre-β-HDL was inhibited by the CETP inhibitors torcetrapib and anacetrapib, it was not reduced by the CETP modulator dalcetrapib. This finding was elucidated using this technique. PMID:21971713

Collaborative Sharing of Multidimensional Space-time Data Using HydroShare

NASA Astrophysics Data System (ADS)

Gan, T.; Tarboton, D. G.; Horsburgh, J. S.; Dash, P. K.; Idaszak, R.; Yi, H.; Blanton, B.

2015-12-01

HydroShare is a collaborative environment being developed for sharing hydrological data and models. It includes capability to upload data in many formats as resources that can be shared. The HydroShare data model for resources uses a specific format for the representation of each type of data and specifies metadata common to all resource types as well as metadata unique to specific resource types. The Network Common Data Form (NetCDF) was chosen as the format for multidimensional space-time data in HydroShare. NetCDF is widely used in hydrological and other geoscience modeling because it contains self-describing metadata and supports the creation of array-oriented datasets that may include three spatial dimensions, a time dimension and other user defined dimensions. For example, NetCDF may be used to represent precipitation or surface air temperature fields that have two dimensions in space and one dimension in time. This presentation will illustrate how NetCDF files are used in HydroShare. When a NetCDF file is loaded into HydroShare, header information is extracted using the "ncdump" utility. Python functions developed for the Django web framework on which HydroShare is based, extract science metadata present in the NetCDF file, saving the user from having to enter it. Where the file follows Climate Forecast (CF) convention and Attribute Convention for Dataset Discovery (ACDD) standards, metadata is thus automatically populated. Users also have the ability to add metadata to the resource that may not have been present in the original NetCDF file. HydroShare's metadata editing functionality then writes this science metadata back into the NetCDF file to maintain consistency between the science metadata in HydroShare and the metadata in the NetCDF file. This further helps researchers easily add metadata information following the CF and ACDD conventions. Additional data inspection and subsetting functions were developed, taking advantage of Python and command line libraries for working with NetCDF files. We describe the design and implementation of these features and illustrate how NetCDF files from a modeling application may be curated in HydroShare and thus enhance reproducibility of the associated research. We also discuss future development planned for multidimensional space-time data in HydroShare.

Analysis of crew functions as an aid in Space Station interior layout

NASA Technical Reports Server (NTRS)

Steinberg, A. L.; Tullis, Thomas S.; Bied, Barbra

1986-01-01

The Space Station must be designed to facilitate all of the functions that its crew will perform, both on-duty and off-duty, as efficiently and comfortably as possible. This paper examines the functions to be performed by the Space Station crew in order to make inferences about the design of an interior layout that optimizes crew productivity. Twenty-seven crew functions were defined, as well as five criteria for assessing relationships among all pairs of those functions. Hierarchical clustering and multidimensional scaling techniques were used to visually summarize the relationships. A key result was the identification of two dimensions for describing the configuration of crew functions: 'Private-Public' and 'Group-Individual'. Seven specific recommendations for Space Station interior layout were derived from the analyses.

Efficient multidimensional free energy calculations for ab initio molecular dynamics using classical bias potentials

NASA Astrophysics Data System (ADS)

VandeVondele, Joost; Rothlisberger, Ursula

2000-09-01

We present a method for calculating multidimensional free energy surfaces within the limited time scale of a first-principles molecular dynamics scheme. The sampling efficiency is enhanced using selected terms of a classical force field as a bias potential. This simple procedure yields a very substantial increase in sampling accuracy while retaining the high quality of the underlying ab initio potential surface and can thus be used for a parameter free calculation of free energy surfaces. The success of the method is demonstrated by the applications to two gas phase molecules, ethane and peroxynitrous acid, as test case systems. A statistical analysis of the results shows that the entire free energy landscape is well converged within a 40 ps simulation at 500 K, even for a system with barriers as high as 15 kcal/mol.

Face-space: A unifying concept in face recognition research.

PubMed

Valentine, Tim; Lewis, Michael B; Hills, Peter J

2016-10-01

The concept of a multidimensional psychological space, in which faces can be represented according to their perceived properties, is fundamental to the modern theorist in face processing. Yet the idea was not clearly expressed until 1991. The background that led to the development of face-space is explained, and its continuing influence on theories of face processing is discussed. Research that has explored the properties of the face-space and sought to understand caricature, including facial adaptation paradigms, is reviewed. Face-space as a theoretical framework for understanding the effect of ethnicity and the development of face recognition is evaluated. Finally, two applications of face-space in the forensic setting are discussed. From initially being presented as a model to explain distinctiveness, inversion, and the effect of ethnicity, face-space has become a central pillar in many aspects of face processing. It is currently being developed to help us understand adaptation effects with faces. While being in principle a simple concept, face-space has shaped, and continues to shape, our understanding of face perception.

Lorentz-like force emerging from kinematic interactions between electrons and nuclei in molecules: A quantum mechanical origin of symmetry breaking that can trigger molecular chirality.

PubMed

Takatsuka, Kazuo

2017-02-28

The Longuet-Higgins (Berry) phase arising from nonadiabatic dynamics and the Aharonov-Bohm phase associated with the dynamics of a charged particle in the electromagnetic vector potential are well known to be individually a manifestation of a class of the so-called geometrical phase. We herein discuss another similarity between the force working on a charged particle moving in a magnetic field, the Lorentz force, and a force working on nuclei while passing across a region where they have a strong quantum mechanical kinematic (nonadiabatic) coupling with electrons in a molecule. This kinematic force is indeed akin to the Lorentz force in that its magnitude is proportional to the velocity of the relevant nuclei and works in the direction perpendicular to its translational motion. Therefore this Lorentz-like nonadiabatic force is realized only in space of more or equal to three dimensions, thereby highlighting a truly multi-dimensional effect of nonadiabatic interaction. We investigate its physical significance qualitatively in the context of breaking of molecular spatial symmetry, which is not seen otherwise without this force. This particular symmetry breaking is demonstrated in application to a coplanar collision between a planar molecule and an atom sharing the same plane. We show that the atom is guided by this force to the direction out from the plane, resulting in a configuration that distinguishes one side of the mirror plane from the other. This can serve as a trigger for the dynamics towards molecular chirality.

Assessment of urban green space structures and their quality from a multidimensional perspective.

PubMed

Daniels, Benjamin; Zaunbrecher, Barbara S; Paas, Bastian; Ottermanns, Richard; Ziefle, Martina; Roß-Nickoll, Martina

2018-02-15

Facing the growing amount of people living in cities and, at the same time, the need for a compact and sustainable urban development to mitigate urban sprawl, it becomes increasingly important that green spaces in compact cities are designed to meet the various needs within an urban environment. Urban green spaces have a multitude of functions: Maintaining ecological processes and resulting services, e.g. providing habitat for animals and plants, providing a beneficial city microclimate as well as recreational space for citizens. Regarding these requirements, currently existing assessment procedures for green spaces have some major shortcomings, which are discussed in this paper. It is argued why a more detailed spatial level as well as a distinction between natural and artificial varieties of structural elements is justified and needed and how the assessment of urban green spaces benefits from the multidimensional perspective that is applied. By analyzing a selection of structural elements from an ecological, microclimatic and social perspective, indicator values are derived and a new, holistic metrics 1 is proposed. The results of the integrated analysis led to two major findings: first, that for some elements, the evaluation differs to a great extent between the different perspectives (disciplines) and second, that natural and artificial varieties are, in most cases, evaluated considerably different from each other. The differences between the perspectives call for an integrative planning policy which acknowledges the varying contribution of a structural element to different purposes (ecological, microclimatic, social) as well as a discussion about the prioritization of those purposes. The differences in the evaluation of natural vs. artificial elements verify the assumption that indicators which consider only generic elements fail to account for those refinements and are thus less suitable for planning and assessment purposes. Implications, challenges and scenarios for the application of such a metrics are finally discussed. Copyright © 2017 Elsevier B.V. All rights reserved.

The cancellous bone multiscale morphology-elasticity relationship.

PubMed

Agić, Ante; Nikolić, Vasilije; Mijović, Budimir

2006-06-01

The cancellous bone effective properties relations are analysed on multiscale across two aspects; properties of representative volume element on micro scale and statistical measure of trabecular trajectory orientation on mesoscale. Anisotropy of the microstructure is described across fabric tensor measure with trajectory orientation tensor as bridging scale connection. The scatter measured data (elastic modulus, trajectory orientation, apparent density) from compression test are fitted by stochastic interpolation procedure. The engineering constants of the elasticity tensor are estimated by last square fitt procedure in multidimensional space by Nelder-Mead simplex. The multiaxial failure surface in strain space is constructed and interpolated by modified super-ellipsoid.

Study of premixing phase of steam explosion with JASMINE code in ALPHA program

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

Moriyama, Kiyofumi; Yamano, Norihiro; Maruyama, Yu

Premixing phase of steam explosion has been studied in ALPHA Program at Japan Atomic Energy Research Institute (JAERI). An analytical model to simulate the premixing phase, JASMINE (JAERI Simulator for Multiphase Interaction and Explosion), has been developed based on a multi-dimensional multi-phase thermal hydraulics code MISTRAL (by Fuji Research Institute Co.). The original code was extended to simulate the physics in the premixing phenomena. The first stage of the code validation was performed by analyzing two mixing experiments with solid particles and water: the isothermal experiment by Gilbertson et al. (1992) and the hot particle experiment by Angelini et al.more » (1993) (MAGICO). The code predicted reasonably well the experiments. Effectiveness of the TVD scheme employed in the code was also demonstrated.« less

Phase retrieval using regularization method in intensity correlation imaging

NASA Astrophysics Data System (ADS)

Li, Xiyu; Gao, Xin; Tang, Jia; Lu, Changming; Wang, Jianli; Wang, Bin

2014-11-01

Intensity correlation imaging(ICI) method can obtain high resolution image with ground-based low precision mirrors, in the imaging process, phase retrieval algorithm should be used to reconstituted the object's image. But the algorithm now used(such as hybrid input-output algorithm) is sensitive to noise and easy to stagnate. However the signal-to-noise ratio of intensity interferometry is low especially in imaging astronomical objects. In this paper, we build the mathematical model of phase retrieval and simplified it into a constrained optimization problem of a multi-dimensional function. New error function was designed by noise distribution and prior information using regularization method. The simulation results show that the regularization method can improve the performance of phase retrieval algorithm and get better image especially in low SNR condition

A method of using cluster analysis to study statistical dependence in multivariate data

NASA Technical Reports Server (NTRS)

Borucki, W. J.; Card, D. H.; Lyle, G. C.

1975-01-01

A technique is presented that uses both cluster analysis and a Monte Carlo significance test of clusters to discover associations between variables in multidimensional data. The method is applied to an example of a noisy function in three-dimensional space, to a sample from a mixture of three bivariate normal distributions, and to the well-known Fisher's Iris data.

Femtosecond pulse shaping using the geometric phase.

PubMed

Gökce, Bilal; Li, Yanming; Escuti, Michael J; Gundogdu, Kenan

2014-03-15

We demonstrate a femtosecond pulse shaper that utilizes polarization gratings to manipulate the geometric phase of an optical pulse. This unique approach enables circular polarization-dependent shaping of femtosecond pulses. As a result, it is possible to create coherent pulse pairs with orthogonal polarizations in a 4f pulse shaper setup, something until now that, to our knowledge, was only achieved via much more complex configurations. This approach could be used to greatly simplify and enhance the functionality of multidimensional spectroscopy and coherent control experiments, in which multiple coherent pulses are used to manipulate quantum states in materials of interest.

A theoretical framework for the associations between identity and psychopathology.

PubMed

Klimstra, Theo A; Denissen, Jaap J A

2017-11-01

Identity research largely emerged from clinical observations. Decades of empirical work advanced the field in refining existing approaches and adding new approaches. Furthermore, the existence of linkages of identity with psychopathology is now well established. Unfortunately, both the directionality of effects between identity aspects and psychopathology symptoms, and the mechanisms underlying associations are unclear. In the present paper, we present a new framework to inspire hypothesis-driven empirical research to overcome this limitation. The framework has a basic resemblance to theoretical models for the study of personality and psychopathology, so we provide examples of how these might apply to the study of identity. Next, we explain that unique features of identity may come into play in individuals suffering from psychopathology that are mostly related to the content of one's identity. These include pros and cons of identifying with one's diagnostic label. Finally, inspired by Hermans' dialogical self theory and principles derived from Piaget's, Swann's and Kelly's work, we delineate a framework with identity at the core of an individual multidimensional space. In this space, psychopathology symptoms have a known distance (representing relevance) to one's identity, and individual multidimensional spaces are connected to those of other individuals in one's social network. We discuss methodological (quantitative and qualitative, idiographic and nomothetic) and statistical procedures (multilevel models and network models) to test the framework. Resulting evidence can boost the field of identity research in demonstrating its high practical relevance for the emergence and conservation of psychopathology. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Nonaxial hexadecapole deformation effects on the fission barrier

NASA Astrophysics Data System (ADS)

Kardan, A.; Nejati, S.

2016-06-01

Fission barrier of the heavy nucleus 250Cf is analyzed in a multi-dimensional deformation space. This space includes two quadrupole (ɛ2,γ) and three hexadecapole deformation (ɛ40,ɛ42,ɛ44) parameters. The analysis is performed within an unpaired macroscopic-microscopic approach. Special attention is given to the effects of the axial and non-axial hexadecapole deformation shapes. It is found that the inclusion of the nonaxial hexadecapole shapes does not change the fission barrier heights, so it should be sufficient to minimize the energy in only one degree of freedom in the hexadecapole space ɛ4. The role of hexadecapole deformation parameters is also discussed on the Lublin-Strasbourg drop (LSD) macroscopic and the Strutinsky shell energies.

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.

SCORE-EVET: a computer code for the multidimensional transient thermal-hydraulic analysis of nuclear fuel rod arrays. [BWR; PWR

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

Benedetti, R. L.; Lords, L. V.; Kiser, D. M.

1978-02-01

The SCORE-EVET code was developed to study multidimensional transient fluid flow in nuclear reactor fuel rod arrays. The conservation equations used were derived by volume averaging the transient compressible three-dimensional local continuum equations in Cartesian coordinates. No assumptions associated with subchannel flow have been incorporated into the derivation of the conservation equations. In addition to the three-dimensional fluid flow equations, the SCORE-EVET code ocntains: (a) a one-dimensional steady state solution scheme to initialize the flow field, (b) steady state and transient fuel rod conduction models, and (c) comprehensive correlation packages to describe fluid-to-fuel rod interfacial energy and momentum exchange. Velocitymore » and pressure boundary conditions can be specified as a function of time and space to model reactor transient conditions such as a hypothesized loss-of-coolant accident (LOCA) or flow blockage.« less

Nonlinear multidimensional cosmological models with form fields: Stabilization of extra dimensions and the cosmological constant problem

NASA Astrophysics Data System (ADS)

Günther, U.; Moniz, P.; Zhuk, A.

2003-08-01

We consider multidimensional gravitational models with a nonlinear scalar curvature term and form fields in the action functional. In our scenario it is assumed that the higher dimensional spacetime undergoes a spontaneous compactification to a warped product manifold. Particular attention is paid to models with quadratic scalar curvature terms and a Freund-Rubin-like ansatz for solitonic form fields. It is shown that for certain parameter ranges the extra dimensions are stabilized. In particular, stabilization is possible for any sign of the internal space curvature, the bulk cosmological constant, and of the effective four-dimensional cosmological constant. Moreover, the effective cosmological constant can satisfy the observable limit on the dark energy density. Finally, we discuss the restrictions on the parameters of the considered nonlinear models and how they follow from the connection between the D-dimensional and the four-dimensional fundamental mass scales.

New generic indexing technology

NASA Technical Reports Server (NTRS)

Freeston, Michael

1996-01-01

There has been no fundamental change in the dynamic indexing methods supporting database systems since the invention of the B-tree twenty-five years ago. And yet the whole classical approach to dynamic database indexing has long since become inappropriate and increasingly inadequate. We are moving rapidly from the conventional one-dimensional world of fixed-structure text and numbers to a multi-dimensional world of variable structures, objects and images, in space and time. But, even before leaving the confines of conventional database indexing, the situation is highly unsatisfactory. In fact, our research has led us to question the basic assumptions of conventional database indexing. We have spent the past ten years studying the properties of multi-dimensional indexing methods, and in this paper we draw the strands of a number of developments together - some quite old, some very new, to show how we now have the basis for a new generic indexing technology for the next generation of database systems.

Multidimensional heuristic process for high-yield production of astaxanthin and fragrance molecules in Escherichia coli.

PubMed

Zhang, Congqiang; Seow, Vui Yin; Chen, Xixian; Too, Heng-Phon

2018-05-11

Optimization of metabolic pathways consisting of large number of genes is challenging. Multivariate modular methods (MMMs) are currently available solutions, in which reduced regulatory complexities are achieved by grouping multiple genes into modules. However, these methods work well for balancing the inter-modules but not intra-modules. In addition, application of MMMs to the 15-step heterologous route of astaxanthin biosynthesis has met with limited success. Here, we expand the solution space of MMMs and develop a multidimensional heuristic process (MHP). MHP can simultaneously balance different modules by varying promoter strength and coordinating intra-module activities by using ribosome binding sites (RBSs) and enzyme variants. Consequently, MHP increases enantiopure 3S,3'S-astaxanthin production to 184 mg l -1 day -1 or 320 mg l -1 . Similarly, MHP improves the yields of nerolidol and linalool. MHP may be useful for optimizing other complex biochemical pathways.

A Multidimensional Diversity‐Oriented Synthesis Strategy for Structurally Diverse and Complex Macrocycles

PubMed Central

Nie, Feilin; Kunciw, Dominique L.; Wilcke, David; Stokes, Jamie E.; Galloway, Warren R. J. D.; Bartlett, Sean; Sore, Hannah F.

2016-01-01

Abstract Synthetic macrocycles are an attractive area in drug discovery. However, their use has been hindered by a lack of versatile platforms for the generation of structurally (and thus shape) diverse macrocycle libraries. Herein, we describe a new concept in library synthesis, termed multidimensional diversity‐oriented synthesis, and its application towards macrocycles. This enabled the step‐efficient generation of a library of 45 novel, structurally diverse, and highly‐functionalized macrocycles based around a broad range of scaffolds and incorporating a wide variety of biologically relevant structural motifs. The synthesis strategy exploited the diverse reactivity of aza‐ylides and imines, and featured eight different macrocyclization methods, two of which were novel. Computational analyses reveal a broad coverage of molecular shape space by the library and provides insight into how the various diversity‐generating steps of the synthesis strategy impact on molecular shape. PMID:27484830

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.

AdS and stabilized extra dimensions in multi-dimensional gravitational models with nonlinear scalar curvature terms R-1 and R4

NASA Astrophysics Data System (ADS)

Günther, Uwe; Zhuk, Alexander; Bezerra, Valdir B.; Romero, Carlos

2005-08-01

We study multi-dimensional gravitational models with scalar curvature nonlinearities of types R-1 and R4. It is assumed that the corresponding higher dimensional spacetime manifolds undergo a spontaneous compactification to manifolds with a warped product structure. Special attention has been paid to the stability of the extra-dimensional factor spaces. It is shown that for certain parameter regions the systems allow for a freezing stabilization of these spaces. In particular, we find for the R-1 model that configurations with stabilized extra dimensions do not provide a late-time acceleration (they are AdS), whereas the solution branch which allows for accelerated expansion (the dS branch) is incompatible with stabilized factor spaces. In the case of the R4 model, we obtain that the stability region in parameter space depends on the total dimension D = dim(M) of the higher dimensional spacetime M. For D > 8 the stability region consists of a single (absolutely stable) sector which is shielded from a conformal singularity (and an antigravity sector beyond it) by a potential barrier of infinite height and width. This sector is smoothly connected with the stability region of a curvature-linear model. For D < 8 an additional (metastable) sector exists which is separated from the conformal singularity by a potential barrier of finite height and width so that systems in this sector are prone to collapse into the conformal singularity. This second sector is not smoothly connected with the first (absolutely stable) one. Several limiting cases and the possibility of inflation are discussed for the R4 model.

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.

Analysis of cardiac interventricular septum motion in different respiratory states

NASA Astrophysics Data System (ADS)

Tautz, Lennart; Feng, Li; Otazo, Ricardo; Hennemuth, Anja; Axel, Leon

2016-03-01

The interaction between the left and right heart ventricles (LV and RV) depends on load and pressure conditions that are affected by cardiac contraction and respiration cycles. A novel MRI sequence, XD-GRASP, allows the acquisition of multi-dimensional, respiration-sorted and cardiac-synchronized free-breathing image data. In these data, effects of the cardiac and respiratory cycles on the LV/RV interaction can be observed independently. To enable the analysis of such data, we developed a semi-automatic exploration workflow. After tracking a cross-sectional line positioned over the heart, over all motion states, the septum and heart wall border locations are detected by analyzing the grey-value profile under the lines. These data are used to quantify septum motion, both in absolute units and as a fraction of the heart size, to compare values for different subjects. In addition to conventional visualization techniques, we used color maps for intuitive exploration of the variable values for this multi-dimensional data set. We acquired short-axis image data of nine healthy volunteers, to analyze the position and the motion of the interventricular septum in different breathing states and different cardiac cycle phases. The results indicate a consistent range of normal septum motion values, and also suggest that respiratory phase-dependent septum motion is greatest near end-diastolic phases. These new methods are a promising tool to assess LV/RV ventricle interaction and the effects of respiration on this interaction.

Subjective health literacy: Development of a brief instrument for school-aged children.

PubMed

Paakkari, Olli; Torppa, Minna; Kannas, Lasse; Paakkari, Leena

2016-12-01

The present paper focuses on the measurement of health literacy (HL), which is an important determinant of health and health behaviours. HL starts to develop in childhood and adolescence; hence, there is a need for instruments to monitor HL among younger age groups. These instruments are still rare. The aim of the project reported here was, therefore, to develop a brief, multidimensional, theory-based instrument to measure subjective HL among school-aged children. The development of the instrument covered four phases: item generation based on a conceptual framework; a pilot study ( n = 405); test-retest ( n = 117); and construction of the instrument ( n = 3853). All the samples were taken from Finnish 7th and 9th graders. Initially, 65 items were generated, of which 32 items were selected for the pilot study. After item reduction, the instrument contained 16 items. The test-retest phase produced estimates of stability. In the final phase a 10-item instrument was constructed, referred to as Health Literacy for School-Aged Children (HLSAC). The instrument exhibited a high Cronbach alpha (0.93), and included two items from each of the five predetermined theoretical components (theoretical knowledge, practical knowledge, critical thinking, self-awareness, citizenship). The iterative and validity-driven development process made it possible to construct a brief multidimensional HLSAC instrument. Such instruments are suitable for large-scale studies, and for use with children and adolescents. Validation will require further testing for use in other countries.

Spin and wavelength multiplexed nonlinear metasurface holography

NASA Astrophysics Data System (ADS)

Ye, Weimin; Zeuner, Franziska; Li, Xin; Reineke, Bernhard; He, Shan; Qiu, Cheng-Wei; Liu, Juan; Wang, Yongtian; Zhang, Shuang; Zentgraf, Thomas

2016-06-01

Metasurfaces, as the ultrathin version of metamaterials, have caught growing attention due to their superior capability in controlling the phase, amplitude and polarization states of light. Among various types of metasurfaces, geometric metasurface that encodes a geometric or Pancharatnam-Berry phase into the orientation angle of the constituent meta-atoms has shown great potential in controlling light in both linear and nonlinear optical regimes. The robust and dispersionless nature of the geometric phase simplifies the wave manipulation tremendously. Benefitting from the continuous phase control, metasurface holography has exhibited advantages over conventional depth controlled holography with discretized phase levels. Here we report on spin and wavelength multiplexed nonlinear metasurface holography, which allows construction of multiple target holographic images carried independently by the fundamental and harmonic generation waves of different spins. The nonlinear holograms provide independent, nondispersive and crosstalk-free post-selective channels for holographic multiplexing and multidimensional optical data storages, anti-counterfeiting, and optical encryption.

Spin and wavelength multiplexed nonlinear metasurface holography

PubMed Central

Ye, Weimin; Zeuner, Franziska; Li, Xin; Reineke, Bernhard; He, Shan; Qiu, Cheng-Wei; Liu, Juan; Wang, Yongtian; Zhang, Shuang; Zentgraf, Thomas

2016-01-01

Metasurfaces, as the ultrathin version of metamaterials, have caught growing attention due to their superior capability in controlling the phase, amplitude and polarization states of light. Among various types of metasurfaces, geometric metasurface that encodes a geometric or Pancharatnam–Berry phase into the orientation angle of the constituent meta-atoms has shown great potential in controlling light in both linear and nonlinear optical regimes. The robust and dispersionless nature of the geometric phase simplifies the wave manipulation tremendously. Benefitting from the continuous phase control, metasurface holography has exhibited advantages over conventional depth controlled holography with discretized phase levels. Here we report on spin and wavelength multiplexed nonlinear metasurface holography, which allows construction of multiple target holographic images carried independently by the fundamental and harmonic generation waves of different spins. The nonlinear holograms provide independent, nondispersive and crosstalk-free post-selective channels for holographic multiplexing and multidimensional optical data storages, anti-counterfeiting, and optical encryption. PMID:27306147

Emotion Recognition from EEG Signals Using Multidimensional Information in EMD Domain.

PubMed

Zhuang, Ning; Zeng, Ying; Tong, Li; Zhang, Chi; Zhang, Hanming; Yan, Bin

2017-01-01

This paper introduces a method for feature extraction and emotion recognition based on empirical mode decomposition (EMD). By using EMD, EEG signals are decomposed into Intrinsic Mode Functions (IMFs) automatically. Multidimensional information of IMF is utilized as features, the first difference of time series, the first difference of phase, and the normalized energy. The performance of the proposed method is verified on a publicly available emotional database. The results show that the three features are effective for emotion recognition. The role of each IMF is inquired and we find that high frequency component IMF1 has significant effect on different emotional states detection. The informative electrodes based on EMD strategy are analyzed. In addition, the classification accuracy of the proposed method is compared with several classical techniques, including fractal dimension (FD), sample entropy, differential entropy, and discrete wavelet transform (DWT). Experiment results on DEAP datasets demonstrate that our method can improve emotion recognition performance.

Parametric instabilities and their control in multidimensional nonuniform gain media

NASA Astrophysics Data System (ADS)

Charbonneau-Lefort, Mathieu; Afeyan, Bedros; Fejer, Martin

2007-11-01

In order to control parametric instabilities in large scale long pulse laser produced plasmas, optical mixing techniques seem most promising [1]. We examine ways of controlling the growth of some modes while creating other unstable ones in nonuniform gain media, including the effects of transverse localization of the pump wave. We show that multidimensional effects are essential to understand laser-gain medium interactions [2] and that one dimensional models such as the celebrated Rosenbluth result [3] can be misleading [4]. These findings are verified in experiments carried out in a chirped quasi-phase-matched gratings in optical parametric amplifiers where thousands of shots can be taken and statistically significant and stable results obtained. [1] B. Afeyan, et al., IFSA Proceedings, 2003. [2] M. M. Sushchik and G. I. Freidman, Radiofizika 13, 1354 (1970). [3] M. N. Rosenbluth, Phys. Rev. Lett. 29, 565 (1972). [4] M. Charbonneau-Lefort, PhD thesis, Stanford University, 2007.

Mixed-bed ion exchange chromatography employing a salt-free pH gradient for improved sensitivity and compatibility in MudPIT.

PubMed

Mommen, Geert P M; Meiring, Hugo D; Heck, Albert J R; de Jong, Ad P J M

2013-07-16

In proteomics, comprehensive analysis of peptides mixtures necessitates multiple dimensions of separation prior to mass spectrometry analysis to reduce sample complexity and increase the dynamic range of analysis. The main goal of this work was to improve the performance of (online) multidimensional protein identification technology (MudPIT) in terms of sensitivity, compatibility and recovery. The method employs weak anion and strong cation mixed-bed ion exchange chromatography (ACE) in the first separation dimension and reversed phase chromatography (RP) in the second separation dimension (Motoyama et.al. Anal. Chem 2007, 79, 3623-34.). We demonstrated that the chromatographic behavior of peptides in ACE chromatography depends on both the WAX/SCX mixing ratio as the ionic strength of the mobile phase system. This property allowed us to replace the conventional salt gradient by a (discontinuous) salt-free, pH gradient. First dimensional separation of peptides was accomplished with mixtures of aqueous formic acid and dimethylsulfoxide with increasing concentrations. The overall performance of this mobile phase system was found comparable to ammonium acetate buffers in application to ACE chromatography, but clearly outperformed strong cation exchange for use in first dimensional peptide separation. The dramatically improved compatibility between (salt-free) ion exchange chromatography and reversed phase chromatography-mass spectrometry allowed us to downscale the dimensions of the RP analytical column down to 25 μm i.d. for an additional 2- to 3-fold improvement in performance compared to current technology. The achieved levels of sensitivity, orthogonality, and compatibility demonstrates the potential of salt-free ACE MudPIT for the ultrasensitive, multidimensional analysis of very modest amounts of sample material.

III Potsdam-V Kiev International Workshop on Nonlinear Processes in Physics. Held in Potsdam, New York on August 1-11, 1991

DTIC Science & Technology

1991-08-01

Bona, Burke, Grundbaum, Hasagawa, Horton, Krichever, Kruskal, Kuznetsov , Lax, McLaughlin, Mikhailov., Rubenchik, Sabatier, Tabor, Zabusky) for their...British Telecom Lab., GB Fibers Oleg Bogoyavlenskij Breaking Solitons Steklov Mathematical Institute USSR Marco Boiti Real and Virtual Multidimensional...Beyond Rutgers University, USA Boris Kupershmidt Relativistic Analogs of Lax Equations Tennessee Space Institute, USA E.A. Kuznetsov Weak MHD Turbulence

Compressed Semi-Discrete Central-Upwind Schemes for Hamilton-Jacobi Equations

NASA Technical Reports Server (NTRS)

Bryson, Steve; Kurganov, Alexander; Levy, Doron; Petrova, Guergana

2003-01-01

We introduce a new family of Godunov-type semi-discrete central schemes for multidimensional Hamilton-Jacobi equations. These schemes are a less dissipative generalization of the central-upwind schemes that have been recently proposed in series of works. We provide the details of the new family of methods in one, two, and three space dimensions, and then verify their expected low-dissipative property in a variety of examples.

Multivariate analysis of light scattering spectra of liquid dairy products

NASA Astrophysics Data System (ADS)

Khodasevich, M. A.

2010-05-01

Visible light scattering spectra from the surface layer of samples of commercial liquid dairy products are recorded with a colorimeter. The principal component method is used to analyze these spectra. Vectors representing the samples of dairy products in a multidimensional space of spectral counts are projected onto a three-dimensional subspace of principal components. The magnitudes of these projections are found to depend on the type of dairy product.

A software package for the data-independent management of multidimensional data

NASA Technical Reports Server (NTRS)

Treinish, Lloyd A.; Gough, Michel L.

1987-01-01

The Common Data Format (CDF), a structure which provides true data independence for applications software and has been developed at the National Space Science Data Center, is discussed. The background to the CDF is reviewed, and the CDF is described. The conceptual organization of the CDF is discussed, and a sample CDF structure is shown and described. The implementation of CDF, its status, and its applications are examined.

Implicit face prototype learning from geometric information.

PubMed

Or, Charles C-F; Wilson, Hugh R

2013-04-19

There is evidence that humans implicitly learn an average or prototype of previously studied faces, as the unseen face prototype is falsely recognized as having been learned (Solso & McCarthy, 1981). Here we investigated the extent and nature of face prototype formation where observers' memory was tested after they studied synthetic faces defined purely in geometric terms in a multidimensional face space. We found a strong prototype effect: The basic results showed that the unseen prototype averaged from the studied faces was falsely identified as learned at a rate of 86.3%, whereas individual studied faces were identified correctly 66.3% of the time and the distractors were incorrectly identified as having been learned only 32.4% of the time. This prototype learning lasted at least 1 week. Face prototype learning occurred even when the studied faces were further from the unseen prototype than the median variation in the population. Prototype memory formation was evident in addition to memory formation of studied face exemplars as demonstrated in our models. Additional studies showed that the prototype effect can be generalized across viewpoints, and head shape and internal features separately contribute to prototype formation. Thus, implicit face prototype extraction in a multidimensional space is a very general aspect of geometric face learning. Copyright © 2013 Elsevier Ltd. All rights reserved.

CALIBRATION OF SEMI-ANALYTIC MODELS OF GALAXY FORMATION USING PARTICLE SWARM OPTIMIZATION

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

Ruiz, Andrés N.; Domínguez, Mariano J.; Yaryura, Yamila

2015-03-10

We present a fast and accurate method to select an optimal set of parameters in semi-analytic models of galaxy formation and evolution (SAMs). Our approach compares the results of a model against a set of observables applying a stochastic technique called Particle Swarm Optimization (PSO), a self-learning algorithm for localizing regions of maximum likelihood in multidimensional spaces that outperforms traditional sampling methods in terms of computational cost. We apply the PSO technique to the SAG semi-analytic model combined with merger trees extracted from a standard Lambda Cold Dark Matter N-body simulation. The calibration is performed using a combination of observedmore » galaxy properties as constraints, including the local stellar mass function and the black hole to bulge mass relation. We test the ability of the PSO algorithm to find the best set of free parameters of the model by comparing the results with those obtained using a MCMC exploration. Both methods find the same maximum likelihood region, however, the PSO method requires one order of magnitude fewer evaluations. This new approach allows a fast estimation of the best-fitting parameter set in multidimensional spaces, providing a practical tool to test the consequences of including other astrophysical processes in SAMs.« less

Convergence in the Bilingual Lexicon: A Pre-registered Replication of Previous Studies.

PubMed

White, Anne; Malt, Barbara C; Storms, Gert

2016-01-01

Naming patterns of bilinguals have been found to converge and form a new intermediate language system from elements of both the bilinguals' languages. This converged naming pattern differs from the monolingual naming patterns of both a bilingual's languages. We conducted a pre-registered replication study of experiments addressing the question whether there is a convergence between a bilingual's both lexicons. The replication used an enlarged set of stimuli of common household containers, providing generalizability, and more reliable representations of the semantic domain. Both an analysis at the group-level and at the individual level of the correlations between naming patterns reject the two-pattern hypothesis that poses that bilinguals use two monolingual-like naming patterns, one for each of their two languages. However, the results of the original study and the replication comply with the one-pattern hypothesis, which poses that bilinguals converge the naming patterns of their two languages and form a compromise. Since this convergence is only partial the naming pattern in bilinguals corresponds to a moderate version of the one-pattern hypothesis. These findings are further confirmed by a representation of the semantic domain in a multidimensional space and the finding of shorter distances between bilingual category centers than monolingual category centers in this multidimensional space both in the original and in the replication study.

Phase Helps Find Geometrically Optimal Gaits

NASA Astrophysics Data System (ADS)

Revzen, Shai; Hatton, Ross

Geometric motion planning describes motions of animals and machines governed by g ˙ = gA (q) q ˙ - a connection A (.) relating shape q and shape velocity q ˙ to body frame velocity g-1 g ˙ ∈ se (3) . Measuring the entire connection over a multidimensional q is often unfeasible with current experimental methods. We show how using a phase estimator can make tractable measuring the local structure of the connection surrounding a periodic motion q (φ) driven by a phase φ ∈S1 . This approach reduces the complexity of the estimation problem by a factor of dimq . The results suggest that phase estimation can be combined with geometric optimization into an iterative gait optimization algorithm usable on experimental systems, or alternatively, to allow the geometric optimality of an observed gait to be detected. ARO W911NF-14-1-0573, NSF 1462555.

Investigating Pharmacological Similarity by Charting Chemical Space.

PubMed

Buonfiglio, Rosa; Engkvist, Ola; Várkonyi, Péter; Henz, Astrid; Vikeved, Elisabet; Backlund, Anders; Kogej, Thierry

2015-11-23

In this study, biologically relevant areas of the chemical space were analyzed using ChemGPS-NP. This application enables comparing groups of ligands within a multidimensional space based on principle components derived from physicochemical descriptors. Also, 3D visualization of the ChemGPS-NP global map can be used to conveniently evaluate bioactive compound similarity and visually distinguish between different types or groups of compounds. To further establish ChemGPS-NP as a method to accurately represent the chemical space, a comparison with structure-based fingerprint has been performed. Interesting complementarities between the two descriptions of molecules were observed. It has been shown that the accuracy of describing molecules with physicochemical descriptors like in ChemGPS-NP is similar to the accuracy of structural fingerprints in retrieving bioactive molecules. Lastly, pharmacological similarity of structurally diverse compounds has been investigated in ChemGPS-NP space. These results further strengthen the case of using ChemGPS-NP as a tool to explore and visualize chemical space.

A spatially informative optic flow model of bee colony with saccadic flight strategy for global optimization.

PubMed

Das, Swagatam; Biswas, Subhodip; Panigrahi, Bijaya K; Kundu, Souvik; Basu, Debabrota

2014-10-01

This paper presents a novel search metaheuristic inspired from the physical interpretation of the optic flow of information in honeybees about the spatial surroundings that help them orient themselves and navigate through search space while foraging. The interpreted behavior combined with the minimal foraging is simulated by the artificial bee colony algorithm to develop a robust search technique that exhibits elevated performance in multidimensional objective space. Through detailed experimental study and rigorous analysis, we highlight the statistical superiority enjoyed by our algorithm over a wide variety of functions as compared to some highly competitive state-of-the-art methods.

Quality by Design: Multidimensional exploration of the design space in high performance liquid chromatography method development for better robustness before validation.

PubMed

Monks, K; Molnár, I; Rieger, H-J; Bogáti, B; Szabó, E

2012-04-06

Robust HPLC separations lead to fewer analysis failures and better method transfer as well as providing an assurance of quality. This work presents the systematic development of an optimal, robust, fast UHPLC method for the simultaneous assay of two APIs of an eye drop sample and their impurities, in accordance with Quality by Design principles. Chromatography software is employed to effectively generate design spaces (Method Operable Design Regions), which are subsequently employed to determine the final method conditions and to evaluate robustness prior to validation. Copyright © 2011 Elsevier B.V. All rights reserved.

Metaheuristics-Assisted Combinatorial Screening of Eu2+-Doped Ca-Sr-Ba-Li-Mg-Al-Si-Ge-N Compositional Space in Search of a Narrow-Band Green Emitting Phosphor and Density Functional Theory Calculations.

PubMed

Lee, Jin-Woong; Singh, Satendra Pal; Kim, Minseuk; Hong, Sung Un; Park, Woon Bae; Sohn, Kee-Sun

2017-08-21

A metaheuristics-based design would be of great help in relieving the enormous experimental burdens faced during the combinatorial screening of a huge, multidimensional search space, while providing the same effect as total enumeration. In order to tackle the high-throughput powder processing complications and to secure practical phosphors, metaheuristics, an elitism-reinforced nondominated sorting genetic algorithm (NSGA-II), was employed in this study. The NSGA-II iteration targeted two objective functions. The first was to search for a higher emission efficacy. The second was to search for narrow-band green color emissions. The NSGA-II iteration finally converged on BaLi 2 Al 2 Si 2 N 6 :Eu 2+ phosphors in the Eu 2+ -doped Ca-Sr-Ba-Li-Mg-Al-Si-Ge-N compositional search space. The BaLi 2 Al 2 Si 2 N 6 :Eu 2+ phosphor, which was synthesized with no human intervention via the assistance of NSGA-II, was a clear single phase and gave an acceptable luminescence. The BaLi 2 Al 2 Si 2 N 6 :Eu 2+ phosphor as well as all other phosphors that appeared during the NSGA-II iterations were examined in detail by employing powder X-ray diffraction-based Rietveld refinement, X-ray absorption near edge structure, density functional theory calculation, and time-resolved photoluminescence. The thermodynamic stability and the band structure plausibility were confirmed, and more importantly a novel approach to the energy transfer analysis was also introduced for BaLi 2 Al 2 Si 2 N 6 :Eu 2+ phosphors.

Phase reduction approach to synchronisation of nonlinear oscillators

NASA Astrophysics Data System (ADS)

Nakao, Hiroya

2016-04-01

Systems of dynamical elements exhibiting spontaneous rhythms are found in various fields of science and engineering, including physics, chemistry, biology, physiology, and mechanical and electrical engineering. Such dynamical elements are often modelled as nonlinear limit-cycle oscillators. In this article, we briefly review phase reduction theory, which is a simple and powerful method for analysing the synchronisation properties of limit-cycle oscillators exhibiting rhythmic dynamics. Through phase reduction theory, we can systematically simplify the nonlinear multi-dimensional differential equations describing a limit-cycle oscillator to a one-dimensional phase equation, which is much easier to analyse. Classical applications of this theory, i.e. the phase locking of an oscillator to a periodic external forcing and the mutual synchronisation of interacting oscillators, are explained. Further, more recent applications of this theory to the synchronisation of non-interacting oscillators induced by common noise and the dynamics of coupled oscillators on complex networks are discussed. We also comment on some recent advances in phase reduction theory for noise-driven oscillators and rhythmic spatiotemporal patterns.

The eigenvalue problem in phase space.

PubMed

Cohen, Leon

2018-06-30

We formulate the standard quantum mechanical eigenvalue problem in quantum phase space. The equation obtained involves the c-function that corresponds to the quantum operator. We use the Wigner distribution for the phase space function. We argue that the phase space eigenvalue equation obtained has, in addition to the proper solutions, improper solutions. That is, solutions for which no wave function exists which could generate the distribution. We discuss the conditions for ascertaining whether a position momentum function is a proper phase space distribution. We call these conditions psi-representability conditions, and show that if these conditions are imposed, one extracts the correct phase space eigenfunctions. We also derive the phase space eigenvalue equation for arbitrary phase space distributions functions. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

The mixing of particle clouds plunging into water

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

Angelini, S.; Theofanous, T.G.; Yuen, W.W.

This work addresses certain fundamental aspects of the premixing phase of steam explosions, At issue are the multifield interaction aspects under highly transient, multidimensional conditions, and in presence of strong phase changes. They are addressed in an experiment (the MAGICO-2000) involving well-characterized particle clouds mixing with water, and detailed measurements on both external and internal characteristics of the mixing zone. Both cold and hot (up to 1500{degrees}C) particle clouds are considered in conjunction with saturated and subcooled water pools. The PMALPHA code is used as an aid in interpreting the experimental results, and the exercise reveals good predictive capabilities formore » it.« less

Research on the relation of EEG signal chaos characteristics with high-level intelligence activity of human brain

PubMed Central

2010-01-01

Using phase space reconstruct technique from one-dimensional and multi-dimensional time series and the quantitative criterion rule of system chaos, and combining the neural network; analyses, computations and sort are conducted on electroencephalogram (EEG) signals of five kinds of human consciousness activities (relaxation, mental arithmetic of multiplication, mental composition of a letter, visualizing a 3-dimensional object being revolved about an axis, and visualizing numbers being written or erased on a blackboard). Through comparative studies on the determinacy, the phase graph, the power spectra, the approximate entropy, the correlation dimension and the Lyapunov exponent of EEG signals of 5 kinds of consciousness activities, the following conclusions are shown: (1) The statistic results of the deterministic computation indicate that chaos characteristic may lie in human consciousness activities, and central tendency measure (CTM) is consistent with phase graph, so it can be used as a division way of EEG attractor. (2) The analyses of power spectra show that ideology of single subject is almost identical but the frequency channels of different consciousness activities have slight difference. (3) The approximate entropy between different subjects exist discrepancy. Under the same conditions, the larger the approximate entropy of subject is, the better the subject's innovation is. (4) The results of the correlation dimension and the Lyapunov exponent indicate that activities of human brain exist in attractors with fractional dimensions. (5) Nonlinear quantitative criterion rule, which unites the neural network, can classify different kinds of consciousness activities well. In this paper, the results of classification indicate that the consciousness activity of arithmetic has better differentiation degree than that of abstract. PMID:20420714

Research on the relation of EEG signal chaos characteristics with high-level intelligence activity of human brain.

PubMed

Wang, Xingyuan; Meng, Juan; Tan, Guilin; Zou, Lixian

2010-04-27

Using phase space reconstruct technique from one-dimensional and multi-dimensional time series and the quantitative criterion rule of system chaos, and combining the neural network; analyses, computations and sort are conducted on electroencephalogram (EEG) signals of five kinds of human consciousness activities (relaxation, mental arithmetic of multiplication, mental composition of a letter, visualizing a 3-dimensional object being revolved about an axis, and visualizing numbers being written or erased on a blackboard). Through comparative studies on the determinacy, the phase graph, the power spectra, the approximate entropy, the correlation dimension and the Lyapunov exponent of EEG signals of 5 kinds of consciousness activities, the following conclusions are shown: (1) The statistic results of the deterministic computation indicate that chaos characteristic may lie in human consciousness activities, and central tendency measure (CTM) is consistent with phase graph, so it can be used as a division way of EEG attractor. (2) The analyses of power spectra show that ideology of single subject is almost identical but the frequency channels of different consciousness activities have slight difference. (3) The approximate entropy between different subjects exist discrepancy. Under the same conditions, the larger the approximate entropy of subject is, the better the subject's innovation is. (4) The results of the correlation dimension and the Lyapunov exponent indicate that activities of human brain exist in attractors with fractional dimensions. (5) Nonlinear quantitative criterion rule, which unites the neural network, can classify different kinds of consciousness activities well. In this paper, the results of classification indicate that the consciousness activity of arithmetic has better differentiation degree than that of abstract.

On the Use of Accelerated Molecular Dynamics to Enhance Configurational Sampling in Ab Initio Simulations.

PubMed

Bucher, Denis; Pierce, Levi C T; McCammon, J Andrew; Markwick, Phineus R L

2011-04-12

We have implemented the accelerated molecular dynamics approach (Hamelberg, D.; Mongan, J.; McCammon, J. A. J. Chem. Phys. 2004, 120 (24), 11919) in the framework of ab initio MD (AIMD). Using three simple examples, we demonstrate that accelerated AIMD (A-AIMD) can be used to accelerate solvent relaxation in AIMD simulations and facilitate the detection of reaction coordinates: (i) We show, for one cyclohexane molecule in the gas phase, that the method can be used to accelerate the rate of the chair-to-chair interconversion by a factor of ∼1 × 10(5), while allowing for the reconstruction of the correct canonical distribution of low-energy states; (ii) We then show, for a water box of 64 H(2)O molecules, that A-AIMD can also be used in the condensed phase to accelerate the sampling of water conformations, without affecting the structural properties of the solvent; and (iii) The method is then used to compute the potential of mean force (PMF) for the dissociation of Na-Cl in water, accelerating the convergence by a factor of ∼3-4 compared to conventional AIMD simulations.(2) These results suggest that A-AIMD is a useful addition to existing methods for enhanced conformational and phase-space sampling in solution. While the method does not make the use of collective variables superfluous, it also does not require the user to define a set of collective variables that can capture all the low-energy minima on the potential energy surface. This property may prove very useful when dealing with highly complex multidimensional systems that require a quantum mechanical treatment.

Multi-dimensional modeling of a thermal energy storage canister. M.S. Thesis - Cleveland State Univ., Dec. 1990

NASA Technical Reports Server (NTRS)

Kerslake, Thomas W.

1991-01-01

The Solar Dynamic Power Module being developed for Space Station Freedom uses a eutectic mixture of LiF-CaF2 phase change material (PCM) contained in toroidal canisters for thermal energy storage. Presented are the results from heat transfer analyses of a PCM containment canister. One and two dimensional finite difference computer models are developed to analyze heat transfer in the canister walls, PCM, void, and heat engine working fluid coolant. The modes of heat transfer considered include conduction in canister walls and solid PCM, conduction and pseudo-free convection in liquid PCM, conduction and radiation across PCM vapor filled void regions, and forced convection in the heat engine working fluid. Void shape, location, growth or shrinkage (due to density difference between the solid and liquid PCM phases) are prescribed based on engineering judgment. The PCM phase change process is analyzed using the enthalpy method. The discussion of the results focuses on how canister thermal performance is affected by free convection in the liquid PCM and void heat transfer. Characterizing these effects is important for interpreting the relationship between ground-based canister performance (in 1-g) and expected on-orbit performance (in micro-g). Void regions accentuate canister hot spots and temperature gradients due to their large thermal resistance. Free convection reduces the extent of PCM superheating and lowers canister temperatures during a portion of the PCM thermal charge period. Surprisingly small differences in canister thermal performance result from operation on the ground and operation on-orbit. This lack of a strong gravity dependency is attributed to the large contribution of container walls in overall canister energy redistribution by conduction.

Brain Time and Physical Time

NASA Astrophysics Data System (ADS)

Fidelman, Uri

The hemispheric paradigm verifies Kant's suggestion that time and space are our subjective modes of perceiving experience. Time and space are two modes of organizing the sensory input by the l- and right-hemispheric neural mechanisms, respectively. The neural structures of the l- and right-hemispheric mechanisms force our consciousness to perceive time as one-dimensional and propagating from the past towards the future, and space as a simultaneously perceived multidimensional structure. The introduction of temporal propagation from the future towards the past by Feynman and other physicists caused the transfer of the concept time from the l hemisphere (which cannot perceive this change of the temporal direction) to the right one. This transfer requires and allows for the introduction of additional temporal axes in order to solve paradoxes in physics.

Spatially organized «vertical city» as a synthesis of tall buildings and airships

NASA Astrophysics Data System (ADS)

Gagulina, Olga; Matovnikov, Sergei

2018-03-01

The paper explores the compact city concept based on the «spatial» urban development principles and describes the prerequisites and possible methods to move from «horizontal» planning to «vertical» urban environments. It highlights the close connection between urban space, high-rise city landscape and conveyance options and sets out the ideas for upgrading the existing architectural and urban planning principles. It also conceptualizes the use of airships to create additional spatial connections between urban structure elements and high-rise buildings. Functional changes are considered in creating both urban environment and internal space of tall buildings, and the environmental aspects of the new spatial model are brought to light. The paper delineates the prospects for making a truly «spatial» multidimensional city space.

Visualization of the operational space of edge-localized modes through low-dimensional embedding of probability distributions

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

Shabbir, A., E-mail: aqsa.shabbir@ugent.be; Noterdaeme, J. M.; Max-Planck-Institut für Plasmaphysik, Garching D-85748

2014-11-15

Information visualization aimed at facilitating human perception is an important tool for the interpretation of experiments on the basis of complex multidimensional data characterizing the operational space of fusion devices. This work describes a method for visualizing the operational space on a two-dimensional map and applies it to the discrimination of type I and type III edge-localized modes (ELMs) from a series of carbon-wall ELMy discharges at JET. The approach accounts for stochastic uncertainties that play an important role in fusion data sets, by modeling measurements with probability distributions in a metric space. The method is aimed at contributing tomore » physical understanding of ELMs as well as their control. Furthermore, it is a general method that can be applied to the modeling of various other plasma phenomena as well.« less

Gaze-informed, task-situated representation of space in primate hippocampus during virtual navigation

PubMed Central

Wirth, Sylvia; Baraduc, Pierre; Planté, Aurélie; Pinède, Serge; Duhamel, Jean-René

2017-01-01

To elucidate how gaze informs the construction of mental space during wayfinding in visual species like primates, we jointly examined navigation behavior, visual exploration, and hippocampal activity as macaque monkeys searched a virtual reality maze for a reward. Cells sensitive to place also responded to one or more variables like head direction, point of gaze, or task context. Many cells fired at the sight (and in anticipation) of a single landmark in a viewpoint- or task-dependent manner, simultaneously encoding the animal’s logical situation within a set of actions leading to the goal. Overall, hippocampal activity was best fit by a fine-grained state space comprising current position, view, and action contexts. Our findings indicate that counterparts of rodent place cells in primates embody multidimensional, task-situated knowledge pertaining to the target of gaze, therein supporting self-awareness in the construction of space. PMID:28241007

Categorical dimensions of human odor descriptor space revealed by non-negative matrix factorization

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

Chennubhotla, Chakra; Castro, Jason

2013-01-01

In contrast to most other sensory modalities, the basic perceptual dimensions of olfaction remain un- clear. Here, we use non-negative matrix factorization (NMF) - a dimensionality reduction technique - to uncover structure in a panel of odor profiles, with each odor defined as a point in multi-dimensional descriptor space. The properties of NMF are favorable for the analysis of such lexical and perceptual data, and lead to a high-dimensional account of odor space. We further provide evidence that odor di- mensions apply categorically. That is, odor space is not occupied homogenously, but rather in a discrete and intrinsically clustered manner.more » We discuss the potential implications of these results for the neural coding of odors, as well as for developing classifiers on larger datasets that may be useful for predicting perceptual qualities from chemical structures.« less

The use of minimal spanning trees in particle physics

DOE PAGES

Rainbolt, J. Lovelace; Schmitt, M.

2017-02-14

Minimal spanning trees (MSTs) have been used in cosmology and astronomy to distinguish distributions of points in a multi-dimensional space. They are essentially unknown in particle physics, however. We briefly define MSTs and illustrate their properties through a series of examples. We show how they might be applied to study a typical event sample from a collider experiment and conclude that MSTs may prove useful in distinguishing different classes of events.

The use of minimal spanning trees in particle physics

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

Rainbolt, J. Lovelace; Schmitt, M.

Minimal spanning trees (MSTs) have been used in cosmology and astronomy to distinguish distributions of points in a multi-dimensional space. They are essentially unknown in particle physics, however. We briefly define MSTs and illustrate their properties through a series of examples. We show how they might be applied to study a typical event sample from a collider experiment and conclude that MSTs may prove useful in distinguishing different classes of events.

The Hyperwall

NASA Technical Reports Server (NTRS)

Biegel, Bryan A. (Technical Monitor); Sandstrom, Timothy A.; Henze, Chris; Levit, Creon

2003-01-01

This paper presents the hyperwall, a visualization cluster that uses coordinated visualizations for interactive exploration of multidimensional data and simulations. The system strongly leverages the human eye-brain system with a generous 7x7 array offlat panel LCD screens powered by a beowulf clustel: With each screen backed by a workstation class PC, graphic and compute intensive applications can be applied to a broad range of data. Navigational tools are presented that allow for investigation of high dimensional spaces.

Experimental demonstration of a flexible time-domain quantum channel.

PubMed

Xing, Xingxing; Feizpour, Amir; Hayat, Alex; Steinberg, Aephraim M

2014-10-20

We present an experimental realization of a flexible quantum channel where the Hilbert space dimensionality can be controlled electronically. Using electro-optical modulators (EOM) and narrow-band optical filters, quantum information is encoded and decoded in the temporal degrees of freedom of photons from a long-coherence-time single-photon source. Our results demonstrate the feasibility of a generic scheme for encoding and transmitting multidimensional quantum information over the existing fiber-optical telecommunications infrastructure.

Planning Robot-Control Parameters With Qualitative Reasoning

NASA Technical Reports Server (NTRS)

Peters, Stephen F.

1993-01-01

Qualitative-reasoning planning algorithm helps to determine quantitative parameters controlling motion of robot. Algorithm regarded as performing search in multidimensional space of control parameters from starting point to goal region in which desired result of robotic manipulation achieved. Makes use of directed graph representing qualitative physical equations describing task, and interacts, at each sampling period, with history of quantitative control parameters and sensory data, to narrow search for reliable values of quantitative control parameters.

Anharmonic quantum mechanical systems do not feature phase space trajectories

NASA Astrophysics Data System (ADS)

Oliva, Maxime; Kakofengitis, Dimitris; Steuernagel, Ole

2018-07-01

Phase space dynamics in classical mechanics is described by transport along trajectories. Anharmonic quantum mechanical systems do not allow for a trajectory-based description of their phase space dynamics. This invalidates some approaches to quantum phase space studies. We first demonstrate the absence of trajectories in general terms. We then give an explicit proof for all quantum phase space distributions with negative values: we show that the generation of coherences in anharmonic quantum mechanical systems is responsible for the occurrence of singularities in their phase space velocity fields, and vice versa. This explains numerical problems repeatedly reported in the literature, and provides deeper insight into the nature of quantum phase space dynamics.

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.

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.

From Neutron Star Observables to the Equation of State. II. Bayesian Inference of Equation of State Pressures

NASA Astrophysics Data System (ADS)

Raithel, Carolyn A.; Özel, Feryal; Psaltis, Dimitrios

2017-08-01

One of the key goals of observing neutron stars is to infer the equation of state (EoS) of the cold, ultradense matter in their interiors. Here, we present a Bayesian statistical method of inferring the pressures at five fixed densities, from a sample of mock neutron star masses and radii. We show that while five polytropic segments are needed for maximum flexibility in the absence of any prior knowledge of the EoS, regularizers are also necessary to ensure that simple underlying EoS are not over-parameterized. For ideal data with small measurement uncertainties, we show that the pressure at roughly twice the nuclear saturation density, {ρ }{sat}, can be inferred to within 0.3 dex for many realizations of potential sources of uncertainties. The pressures of more complicated EoS with significant phase transitions can also be inferred to within ˜30%. We also find that marginalizing the multi-dimensional parameter space of pressure to infer a mass-radius relation can lead to biases of nearly 1 km in radius, toward larger radii. Using the full, five-dimensional posterior likelihoods avoids this bias.

Spatial averaging for small molecule diffusion in condensed phase environments

NASA Astrophysics Data System (ADS)

Plattner, Nuria; Doll, J. D.; Meuwly, Markus

2010-07-01

Spatial averaging is a new approach for sampling rare-event problems. The approach modifies the importance function which improves the sampling efficiency while keeping a defined relation to the original statistical distribution. In this work, spatial averaging is applied to multidimensional systems for typical problems arising in physical chemistry. They include (I) a CO molecule diffusing on an amorphous ice surface, (II) a hydrogen molecule probing favorable positions in amorphous ice, and (III) CO migration in myoglobin. The systems encompass a wide range of energy barriers and for all of them spatial averaging is found to outperform conventional Metropolis Monte Carlo. It is also found that optimal simulation parameters are surprisingly similar for the different systems studied, in particular, the radius of the point cloud over which the potential energy function is averaged. For H2 diffusing in amorphous ice it is found that facile migration is possible which is in agreement with previous suggestions from experiment. The free energy barriers involved are typically lower than 1 kcal/mol. Spatial averaging simulations for CO in myoglobin are able to locate all currently characterized metastable states. Overall, it is found that spatial averaging considerably improves the sampling of configurational space.

Spray and High-Pressure Flow Computations in the National Combustion Code (NCC) Improved

NASA Technical Reports Server (NTRS)

Raju, Manthena S.

2002-01-01

Sprays occur in a wide variety of industrial and power applications and in materials processing. A liquid spray is a two-phase flow with a gas as the continuous phase and a liquid as the dispersed phase in the form of droplets or ligaments. The interactions between the two phases--which are coupled through exchanges of mass, momentum, and energy--can occur in different ways at disparate time and length scales involving various thermal, mass, and fluid dynamic factors. An understanding of the flow, combustion, and thermal properties of a rapidly vaporizing spray requires careful modeling of the ratecontrolling processes associated with turbulent transport, mixing, chemical kinetics, evaporation, and spreading rates of the spray, among many other factors. With the aim of developing an efficient solution procedure for use in multidimensional combustor modeling, researchers at the NASA Glenn Research Center have advanced the state-of-the-art in spray computations in several important ways.

Selecting Soldiers and Civilians into the U.S. Army Officer Candidate School : Developing Empirical Selection Composites

DTIC Science & Technology

2014-07-01

a biographical instrument measuring personality ; (b) a Work Values instrument representing work preferences investigated in prior officer and...items used in SelectOCS Phase 2 (see Table 2.5). TAPAS uses multidimensional pairwise preference (MDPP) personality items scored using item response...presented respondents with a list of 30 traits and 30 skills (derived from leadership and personality literature) and instructed them to rate the

Next-Generation MDAC Discrimination Procedure Using Multi-Dimensional Spectral Analyses

DTIC Science & Technology

2007-09-01

explosions near the Lop Nor, Novaya Zemlya, Semipalatinsk , Nevada, and Indian test sites . We have computed regional phase spectra and are correcting... test sites as mainly due to differences in explosion P and S corner frequencies. Fisk (2007) used source model fits to estimate Pn, Pg, and Lg corner...frequencies for Nevada Test Site (NTS) explosions and found that Lg corner frequencies exhibit similar scaling with source size as for Pn and Pg

Meta-modelling, visualization and emulation of multi-dimensional data for virtual production intelligence

NASA Astrophysics Data System (ADS)

Schulz, Wolfgang; Hermanns, Torsten; Al Khawli, Toufik

2017-07-01

Decision making for competitive production in high-wage countries is a daily challenge where rational and irrational methods are used. The design of decision making processes is an intriguing, discipline spanning science. However, there are gaps in understanding the impact of the known mathematical and procedural methods on the usage of rational choice theory. Following Benjamin Franklin's rule for decision making formulated in London 1772, he called "Prudential Algebra" with the meaning of prudential reasons, one of the major ingredients of Meta-Modelling can be identified finally leading to one algebraic value labelling the results (criteria settings) of alternative decisions (parameter settings). This work describes the advances in Meta-Modelling techniques applied to multi-dimensional and multi-criterial optimization by identifying the persistence level of the corresponding Morse-Smale Complex. Implementations for laser cutting and laser drilling are presented, including the generation of fast and frugal Meta-Models with controlled error based on mathematical model reduction Reduced Models are derived to avoid any unnecessary complexity. Both, model reduction and analysis of multi-dimensional parameter space are used to enable interactive communication between Discovery Finders and Invention Makers. Emulators and visualizations of a metamodel are introduced as components of Virtual Production Intelligence making applicable the methods of Scientific Design Thinking and getting the developer as well as the operator more skilled.

Hörmander multipliers on two-dimensional dyadic Hardy spaces

NASA Astrophysics Data System (ADS)

Daly, J.; Fridli, S.

2008-12-01

In this paper we are interested in conditions on the coefficients of a two-dimensional Walsh multiplier operator that imply the operator is bounded on certain of the Hardy type spaces Hp, 0

Defining process design space for a hydrophobic interaction chromatography (HIC) purification step: application of quality by design (QbD) principles.

PubMed

Jiang, Canping; Flansburg, Lisa; Ghose, Sanchayita; Jorjorian, Paul; Shukla, Abhinav A

2010-12-15

The concept of design space has been taking root under the quality by design paradigm as a foundation of in-process control strategies for biopharmaceutical manufacturing processes. This paper outlines the development of a design space for a hydrophobic interaction chromatography (HIC) process step. The design space included the impact of raw material lot-to-lot variability and variations in the feed stream from cell culture. A failure modes and effects analysis was employed as the basis for the process characterization exercise. During mapping of the process design space, the multi-dimensional combination of operational variables were studied to quantify the impact on process performance in terms of yield and product quality. Variability in resin hydrophobicity was found to have a significant influence on step yield and high-molecular weight aggregate clearance through the HIC step. A robust operating window was identified for this process step that enabled a higher step yield while ensuring acceptable product quality. © 2010 Wiley Periodicals, Inc.

Chemical Space: Big Data Challenge for Molecular Diversity.

PubMed

Awale, Mahendra; Visini, Ricardo; Probst, Daniel; Arús-Pous, Josep; Reymond, Jean-Louis

2017-10-25

Chemical space describes all possible molecules as well as multi-dimensional conceptual spaces representing the structural diversity of these molecules. Part of this chemical space is available in public databases ranging from thousands to billions of compounds. Exploiting these databases for drug discovery represents a typical big data problem limited by computational power, data storage and data access capacity. Here we review recent developments of our laboratory, including progress in the chemical universe databases (GDB) and the fragment subset FDB-17, tools for ligand-based virtual screening by nearest neighbor searches, such as our multi-fingerprint browser for the ZINC database to select purchasable screening compounds, and their application to discover potent and selective inhibitors for calcium channel TRPV6 and Aurora A kinase, the polypharmacology browser (PPB) for predicting off-target effects, and finally interactive 3D-chemical space visualization using our online tools WebDrugCS and WebMolCS. All resources described in this paper are available for public use at www.gdb.unibe.ch.

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.

Phase-space networks of geometrically frustrated systems.

PubMed

Han, Yilong

2009-11-01

We illustrate a network approach to the phase-space study by using two geometrical frustration models: antiferromagnet on triangular lattice and square ice. Their highly degenerated ground states are mapped as discrete networks such that the quantitative network analysis can be applied to phase-space studies. The resulting phase spaces share some comon features and establish a class of complex networks with unique Gaussian spectral densities. Although phase-space networks are heterogeneously connected, the systems are still ergodic due to the random Poisson processes. This network approach can be generalized to phase spaces of some other complex systems.

Roadmap on optical security

NASA Astrophysics Data System (ADS)

Javidi, Bahram; Carnicer, Artur; Yamaguchi, Masahiro; Nomura, Takanori; Pérez-Cabré, Elisabet; Millán, María S.; Nishchal, Naveen K.; Torroba, Roberto; Fredy Barrera, John; He, Wenqi; Peng, Xiang; Stern, Adrian; Rivenson, Yair; Alfalou, A.; Brosseau, C.; Guo, Changliang; Sheridan, John T.; Situ, Guohai; Naruse, Makoto; Matsumoto, Tsutomu; Juvells, Ignasi; Tajahuerce, Enrique; Lancis, Jesús; Chen, Wen; Chen, Xudong; Pinkse, Pepijn W. H.; Mosk, Allard P.; Markman, Adam

2016-08-01

Information security and authentication are important challenges facing society. Recent attacks by hackers on the databases of large commercial and financial companies have demonstrated that more research and development of advanced approaches are necessary to deny unauthorized access to critical data. Free space optical technology has been investigated by many researchers in information security, encryption, and authentication. The main motivation for using optics and photonics for information security is that optical waveforms possess many complex degrees of freedom such as amplitude, phase, polarization, large bandwidth, nonlinear transformations, quantum properties of photons, and multiplexing that can be combined in many ways to make information encryption more secure and more difficult to attack. This roadmap article presents an overview of the potential, recent advances, and challenges of optical security and encryption using free space optics. The roadmap on optical security is comprised of six categories that together include 16 short sections written by authors who have made relevant contributions in this field. The first category of this roadmap describes novel encryption approaches, including secure optical sensing which summarizes double random phase encryption applications and flaws [Yamaguchi], the digital holographic encryption in free space optical technique which describes encryption using multidimensional digital holography [Nomura], simultaneous encryption of multiple signals [Pérez-Cabré], asymmetric methods based on information truncation [Nishchal], and dynamic encryption of video sequences [Torroba]. Asymmetric and one-way cryptosystems are analyzed by Peng. The second category is on compression for encryption. In their respective contributions, Alfalou and Stern propose similar goals involving compressed data and compressive sensing encryption. The very important area of cryptanalysis is the topic of the third category with two sections: Sheridan reviews phase retrieval algorithms to perform different attacks, whereas Situ discusses nonlinear optical encryption techniques and the development of a rigorous optical information security theory. The fourth category with two contributions reports how encryption could be implemented at the nano- or micro-scale. Naruse discusses the use of nanostructures in security applications and Carnicer proposes encoding information in a tightly focused beam. In the fifth category, encryption based on ghost imaging using single-pixel detectors is also considered. In particular, the authors [Chen, Tajahuerce] emphasize the need for more specialized hardware and image processing algorithms. Finally, in the sixth category, Mosk and Javidi analyze in their corresponding papers how quantum imaging can benefit optical encryption systems. Sources that use few photons make encryption systems much more difficult to attack, providing a secure method for authentication.

Multiobjective optimization in a pseudometric objective space as applied to a general model of business activities

NASA Astrophysics Data System (ADS)

Khachaturov, R. V.

2016-09-01

It is shown that finding the equivalence set for solving multiobjective discrete optimization problems is advantageous over finding the set of Pareto optimal decisions. An example of a set of key parameters characterizing the economic efficiency of a commercial firm is proposed, and a mathematical model of its activities is constructed. In contrast to the classical problem of finding the maximum profit for any business, this study deals with a multiobjective optimization problem. A method for solving inverse multiobjective problems in a multidimensional pseudometric space is proposed for finding the best project of firm's activities. The solution of a particular problem of this type is presented.

Evaluation of comprehensive multidimensional separations using reversed-phase, reversed-phase liquid chromatography/mass spectrometry for shotgun proteomics.

PubMed

Nakamura, Tatsuji; Kuromitsu, Junro; Oda, Yoshiya

2008-03-01

Two-dimensional liquid-chromatographic (LC) separation followed by mass spectrometric (MS) analysis was examined for the identification of peptides in complex mixtures as an alternative to widely used two-dimensional gel electrophoresis followed by MS analysis for use in proteomics. The present method involves the off-line coupling of a narrow-bore, polymer-based, reversed-phase column using an acetonitrile gradient in an alkaline mobile phase in the first dimension with octadecylsilanized silica (ODS)-based nano-LC/MS in the second dimension. After the first separation, successive fractions were acidified and dried off-line, then loaded on the second dimension column. Both columns separate peptides according to hydrophobicity under different pH conditions, but more peptides were identified than with the conventional technique for shotgun proteomics, that is, the combination of a strong cation exchange column with an ODS column, and the system was robust because no salts were included in the mobile phases. The suitability of the method for proteomics measurements was evaluated.

Improving the Accessibility and Use of NASA Earth Science Data

NASA Technical Reports Server (NTRS)

Tisdale, Matthew; Tisdale, Brian

2015-01-01

Many of the NASA Langley Atmospheric Science Data Center (ASDC) Distributed Active Archive Center (DAAC) multidimensional tropospheric and atmospheric chemistry data products are stored in HDF4, HDF5 or NetCDF format, which traditionally have been difficult to analyze and visualize with geospatial tools. With the rising demand from the diverse end-user communities for geospatial tools to handle multidimensional products, several applications, such as ArcGIS, have refined their software. Many geospatial applications now have new functionalities that enable the end user to: Store, serve, and perform analysis on each individual variable, its time dimension, and vertical dimension. Use NetCDF, GRIB, and HDF raster data formats across applications directly. Publish output within REST image services or WMS for time and space enabled web application development. During this webinar, participants will learn how to leverage geospatial applications such as ArcGIS, OPeNDAP and ncWMS in the production of Earth science information, and in increasing data accessibility and usability.

Multidimensional scaling of D15 caps: color-vision defects among tobacco smokers?

PubMed

Bimler, David; Kirkland, John

2004-01-01

Tobacco smoke contains a range of toxins including carbon monoxide and cyanide. With specialized cells and high metabolic demands, the optic nerve and retina are vulnerable to toxic exposure. We examined the possible effects of smoking on color vision: specifically, whether smokers perceive a different pattern of suprathreshold color dissimilarities from nonsmokers. It is already known that smokers differ in threshold color discrimination, with elevated scores on the Roth 28-Hue Desaturated panel test. Groups of smokers and nonsmokers, matched for sex and age, followed a triadic procedure to compare dissimilarities among 32 pigmented stimuli (the caps of the saturated and desaturated versions of the D15 panel test). Multidimensional scaling was applied to quantify individual variations in the salience of the axes of color space. Despite the briefness, simplicity, and "low-tech" nature of the procedure, subtle but statistically significant differences did emerge: on average the smoking group were significantly less sensitive to red-green differences. This is consistent with some form of injury to the optic nerve.

The Earth is flat when personally significant experiences with the sphericity of the Earth are absent.

PubMed

Carbon, Claus-Christian

2010-07-01

Participants with personal and without personal experiences with the Earth as a sphere estimated large-scale distances between six cities located on different continents. Cognitive distances were submitted to a specific multidimensional scaling algorithm in the 3D Euclidean space with the constraint that all cities had to lie on the same sphere. A simulation was run that calculated respective 3D configurations of the city positions for a wide range of radii of the proposed sphere. People who had personally experienced the Earth as a sphere, at least once in their lifetime, showed a clear optimal solution of the multidimensional scaling (MDS) routine with a mean radius deviating only 8% from the actual radius of the Earth. In contrast, the calculated configurations for people without any personal experience with the Earth as a sphere were compatible with a cognitive concept of a flat Earth. 2010 Elsevier B.V. All rights reserved.

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.

Shift-Variant Multidimensional Systems.

DTIC Science & Technology

1985-05-29

i=0,1,** *N-1 in (3.1), one will get 0() i_0,1,* ,N-1 which is nonnegative due to the Perron - Frobenius Theorem [24]. That is, the A nonnegativity ...and the current input. The state-space model was extended in order to model 2-D discrete LSV systems with support on a causality cone . Subsequently...formulated as a special system of linear equations with nonnegative coefficients whose solution is required to satisfy con- straints like nonnegativity in

Accurate Finite Difference Algorithms

NASA Technical Reports Server (NTRS)

Goodrich, John W.

1996-01-01

Two families of finite difference algorithms for computational aeroacoustics are presented and compared. All of the algorithms are single step explicit methods, they have the same order of accuracy in both space and time, with examples up to eleventh order, and they have multidimensional extensions. One of the algorithm families has spectral like high resolution. Propagation with high order and high resolution algorithms can produce accurate results after O(10(exp 6)) periods of propagation with eight grid points per wavelength.

High Definition Information Systems. Hearings before the Subcommittee on Technology and Competitiveness of the Committee on Science, Space, and Technology. U.S. House of Representatives, One Hundred Second Congress, First Session (May 14, 21, 1991).

ERIC Educational Resources Information Center

Congress of the U.S., Washington, DC. House Committee on Science, Space and Technology.

The report of these two hearings on high definition information systems begins by noting that they are digital, and that they are likely to handle computing, telecommunications, home security, computer imaging, storage, fiber optics networks, multi-dimensional libraries, and many other local, national, and international systems. (It is noted that…

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.

Noninvasive Electroencephalogram Based Control of a Robotic Arm for Writing Task Using Hybrid BCI System.

PubMed

Gao, Qiang; Dou, Lixiang; Belkacem, Abdelkader Nasreddine; Chen, Chao

2017-01-01

A novel hybrid brain-computer interface (BCI) based on the electroencephalogram (EEG) signal which consists of a motor imagery- (MI-) based online interactive brain-controlled switch, "teeth clenching" state detector, and a steady-state visual evoked potential- (SSVEP-) based BCI was proposed to provide multidimensional BCI control. MI-based BCI was used as single-pole double throw brain switch (SPDTBS). By combining the SPDTBS with 4-class SSEVP-based BCI, movement of robotic arm was controlled in three-dimensional (3D) space. In addition, muscle artifact (EMG) of "teeth clenching" condition recorded from EEG signal was detected and employed as interrupter, which can initialize the statement of SPDTBS. Real-time writing task was implemented to verify the reliability of the proposed noninvasive hybrid EEG-EMG-BCI. Eight subjects participated in this study and succeeded to manipulate a robotic arm in 3D space to write some English letters. The mean decoding accuracy of writing task was 0.93 ± 0.03. Four subjects achieved the optimal criteria of writing the word "HI" which is the minimum movement of robotic arm directions (15 steps). Other subjects had needed to take from 2 to 4 additional steps to finish the whole process. These results suggested that our proposed hybrid noninvasive EEG-EMG-BCI was robust and efficient for real-time multidimensional robotic arm control.

Noninvasive Electroencephalogram Based Control of a Robotic Arm for Writing Task Using Hybrid BCI System

PubMed Central

Gao, Qiang

2017-01-01

A novel hybrid brain-computer interface (BCI) based on the electroencephalogram (EEG) signal which consists of a motor imagery- (MI-) based online interactive brain-controlled switch, “teeth clenching” state detector, and a steady-state visual evoked potential- (SSVEP-) based BCI was proposed to provide multidimensional BCI control. MI-based BCI was used as single-pole double throw brain switch (SPDTBS). By combining the SPDTBS with 4-class SSEVP-based BCI, movement of robotic arm was controlled in three-dimensional (3D) space. In addition, muscle artifact (EMG) of “teeth clenching” condition recorded from EEG signal was detected and employed as interrupter, which can initialize the statement of SPDTBS. Real-time writing task was implemented to verify the reliability of the proposed noninvasive hybrid EEG-EMG-BCI. Eight subjects participated in this study and succeeded to manipulate a robotic arm in 3D space to write some English letters. The mean decoding accuracy of writing task was 0.93 ± 0.03. Four subjects achieved the optimal criteria of writing the word “HI” which is the minimum movement of robotic arm directions (15 steps). Other subjects had needed to take from 2 to 4 additional steps to finish the whole process. These results suggested that our proposed hybrid noninvasive EEG-EMG-BCI was robust and efficient for real-time multidimensional robotic arm control. PMID:28660211

Animated computer graphics models of space and earth sciences data generated via the massively parallel processor

NASA Technical Reports Server (NTRS)

Treinish, Lloyd A.; Gough, Michael L.; Wildenhain, W. David

1987-01-01

The capability was developed of rapidly producing visual representations of large, complex, multi-dimensional space and earth sciences data sets via the implementation of computer graphics modeling techniques on the Massively Parallel Processor (MPP) by employing techniques recently developed for typically non-scientific applications. Such capabilities can provide a new and valuable tool for the understanding of complex scientific data, and a new application of parallel computing via the MPP. A prototype system with such capabilities was developed and integrated into the National Space Science Data Center's (NSSDC) Pilot Climate Data System (PCDS) data-independent environment for computer graphics data display to provide easy access to users. While developing these capabilities, several problems had to be solved independently of the actual use of the MPP, all of which are outlined.

Illustration of microphysical processes in Amazonian deep convective clouds in the gamma phase space: introduction and potential applications

NASA Astrophysics Data System (ADS)

Cecchini, Micael A.; Machado, Luiz A. T.; Wendisch, Manfred; Costa, Anja; Krämer, Martina; Andreae, Meinrat O.; Afchine, Armin; Albrecht, Rachel I.; Artaxo, Paulo; Borrmann, Stephan; Fütterer, Daniel; Klimach, Thomas; Mahnke, Christoph; Martin, Scot T.; Minikin, Andreas; Molleker, Sergej; Pardo, Lianet H.; Pöhlker, Christopher; Pöhlker, Mira L.; Pöschl, Ulrich; Rosenfeld, Daniel; Weinzierl, Bernadett

2017-12-01

The behavior of tropical clouds remains a major open scientific question, resulting in poor representation by models. One challenge is to realistically reproduce cloud droplet size distributions (DSDs) and their evolution over time and space. Many applications, not limited to models, use the gamma function to represent DSDs. However, even though the statistical characteristics of the gamma parameters have been widely studied, there is almost no study dedicated to understanding the phase space of this function and the associated physics. This phase space can be defined by the three parameters that define the DSD intercept, shape, and curvature. Gamma phase space may provide a common framework for parameterizations and intercomparisons. Here, we introduce the phase space approach and its characteristics, focusing on warm-phase microphysical cloud properties and the transition to the mixed-phase layer. We show that trajectories in this phase space can represent DSD evolution and can be related to growth processes. Condensational and collisional growth may be interpreted as pseudo-forces that induce displacements in opposite directions within the phase space. The actually observed movements in the phase space are a result of the combination of such pseudo-forces. Additionally, aerosol effects can be evaluated given their significant impact on DSDs. The DSDs associated with liquid droplets that favor cloud glaciation can be delimited in the phase space, which can help models to adequately predict the transition to the mixed phase. We also consider possible ways to constrain the DSD in two-moment bulk microphysics schemes, in which the relative dispersion parameter of the DSD can play a significant role. Overall, the gamma phase space approach can be an invaluable tool for studying cloud microphysical evolution and can be readily applied in many scenarios that rely on gamma DSDs.

Cost-effective accurate coarse-grid method for highly convective multidimensional unsteady flows

NASA Technical Reports Server (NTRS)

Leonard, B. P.; Niknafs, H. S.

1991-01-01

A fundamentally multidimensional convection scheme is described based on vector transient interpolation modeling rewritten in conservative control-volume form. Vector third-order upwinding is used as the basis of the algorithm; this automatically introduces important cross-difference terms that are absent from schemes using component-wise one-dimensional formulas. Third-order phase accuracy is good; this is important for coarse-grid large-eddy or full simulation. Potential overshoots or undershoots are avoided by using a recently developed universal limiter. Higher order accuracy is obtained locally, where needed, by the cost-effective strategy of adaptive stencil expansion in a direction normal to each control-volume face; this is controlled by monitoring the absolute normal gradient and curvature across the face. Higher (than third) order cross-terms do not appear to be needed. Since the wider stencil is used only in isolated narrow regions (near discontinuities), extremely high (in this case, seventh) order accuracy can be achieved for little more than the cost of a globally third-order scheme.

Successful aging as a multidimensional concept: An integrative review

PubMed Central

Zanjari, Nasibeh; Sharifian Sani, Maryam; Chavoshi, Meimanat Hosseini; Rafiey, Hassan; Mohammadi Shahboulaghi, Farahnaz

2017-01-01

Background: Successful aging as an umbrella term with a large amount of literature has emerged with a variety of meanings and dimensions in different studies. This article aims at determining what dimensions contribute to constructing the concept of successful aging. Methods: The method used in this study is an integrative review of published literature related to successful aging. This method includes both qualitative and quantitative studies. Data searching was conducted during November and December 2014 and was then updated in October 2015. First, 2543 articles were identified, and after the screening phase, 76 articles were eligible for inclusion in the integrative review. Results: The results specified 14 subcategories and 5 main categories of successful aging: social well-being, psychological wellbeing, physical health, spirituality and transcendence, and environment and economic security. Conclusion: The present study provides a thorough understanding of successful aging dimensions and proposes the importance of the multidimensional concept of successful aging at the individual, interpersonal, and environmental levels for future studies and policymaking on population aging.

Data-driven Green's function retrieval and application to imaging with multidimensional deconvolution

NASA Astrophysics Data System (ADS)

Broggini, Filippo; Wapenaar, Kees; van der Neut, Joost; Snieder, Roel

2014-01-01

An iterative method is presented that allows one to retrieve the Green's function originating from a virtual source located inside a medium using reflection data measured only at the acquisition surface. In addition to the reflection response, an estimate of the travel times corresponding to the direct arrivals is required. However, no detailed information about the heterogeneities in the medium is needed. The iterative scheme generalizes the Marchenko equation for inverse scattering to the seismic reflection problem. To give insight in the mechanism of the iterative method, its steps for a simple layered medium are analyzed using physical arguments based on the stationary phase method. The retrieved Green's wavefield is shown to correctly contain the multiples due to the inhomogeneities present in the medium. Additionally, a variant of the iterative scheme enables decomposition of the retrieved wavefield into its downgoing and upgoing components. These wavefields then enable creation of a ghost-free image of the medium with either cross correlation or multidimensional deconvolution, presenting an advantage over standard prestack migration.

Magnetic superlattices and their nanoscale phase transition effects

PubMed Central

Cheon, Jinwoo; Park, Jong-Il; Choi, Jin-sil; Jun, Young-wook; Kim, Sehun; Kim, Min Gyu; Kim, Young-Min; Kim, Youn Joong

2006-01-01

The systematic assembly of nanoscale constituents into highly ordered superlattices is of significant interest because of the potential of their multifunctionalities and the discovery of new collective properties. However, successful observations of such superlattice-associated nanoscale phenomena are still elusive. Here, we present magnetic superlattices of Co and Fe3O4 nanoparticles with multidimensional symmetry of either AB (NaCl) or AB2 (AlB2). The discovery of significant enhancement (≈25 times) of ferrimagnetism is further revealed by forming previously undescribed superlattices of magnetically soft–hard Fe3O4@CoFe2O4 through the confined geometrical effect of thermally driven intrasuperlattice phase transition between the nanoparticulate components. PMID:16492783

Multidimensional spectrometer

DOEpatents

Zanni, Martin Thomas; Damrauer, Niels H.

2010-07-20

A multidimensional spectrometer for the infrared, visible, and ultraviolet regions of the electromagnetic spectrum, and a method for making multidimensional spectroscopic measurements in the infrared, visible, and ultraviolet regions of the electromagnetic spectrum. The multidimensional spectrometer facilitates measurements of inter- and intra-molecular interactions.

Phase Space Exchange in Thick Wedge Absorbers

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

Neuffer, David

The problem of phase space exchange in wedge absorbers with ionization cooling is discussed. The wedge absorber exchanges transverse and longitudinal phase space by introducing a position-dependent energy loss. In this paper we note that the wedges used with ionization cooling are relatively thick, so that single wedges cause relatively large changes in beam phase space. Calculation methods adapted to such “thick wedge” cases are presented, and beam phase-space transformations through such wedges are discussed.

Phase-space topography characterization of nonlinear ultrasound waveforms.

PubMed

Dehghan-Niri, Ehsan; Al-Beer, Helem

2018-03-01

Fundamental understanding of ultrasound interaction with material discontinuities having closed interfaces has many engineering applications such as nondestructive evaluation of defects like kissing bonds and cracks in critical structural and mechanical components. In this paper, to analyze the acoustic field nonlinearities due to defects with closed interfaces, the use of a common technique in nonlinear physics, based on a phase-space topography construction of ultrasound waveform, is proposed. The central idea is to complement the "time" and "frequency" domain analyses with the "phase-space" domain analysis of nonlinear ultrasound waveforms. A nonlinear time series method known as pseudo phase-space topography construction is used to construct equivalent phase-space portrait of measured ultrasound waveforms. Several nonlinear models are considered to numerically simulate nonlinear ultrasound waveforms. The phase-space response of the simulated waveforms is shown to provide different topographic information, while the frequency domain shows similar spectral behavior. Thus, model classification can be substantially enhanced in the phase-space domain. Experimental results on high strength aluminum samples show that the phase-space transformation provides a unique detection and classification capabilities. The Poincaré map of the phase-space domain is also used to better understand the nonlinear behavior of ultrasound waveforms. It is shown that the analysis of ultrasound nonlinearities is more convenient and informative in the phase-space domain than in the frequency domain. Copyright © 2017 Elsevier B.V. All rights reserved.

Gymnastics in Phase Space

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

Chao, Alexander Wu; /SLAC

2012-03-01

As accelerator technology advances, the requirements on accelerator beam quality become increasingly demanding. Facing these new demands, the topic of phase space gymnastics is becoming a new focus of accelerator physics R&D. In a phase space gymnastics, the beam's phase space distribution is manipulated and precision tailored to meet the required beam qualities. On the other hand, all realization of such gymnastics will have to obey accelerator physics principles as well as technological limitations. Recent examples of phase space gymnastics include Emittance exchanges, Phase space exchanges, Emittance partitioning, Seeded FELs and Microbunched beams. The emittance related topics of this listmore » are reviewed in this report. The accelerator physics basis, the optics design principles that provide these phase space manipulations, and the possible applications of these gymnastics, are discussed. This fascinating new field promises to be a powerful tool of the future.« less

Phase-space evolution of x-ray coherence in phase-sensitive imaging.

PubMed

Wu, Xizeng; Liu, Hong

2008-08-01

X-ray coherence evolution in the imaging process plays a key role for x-ray phase-sensitive imaging. In this work we present a phase-space formulation for the phase-sensitive imaging. The theory is reformulated in terms of the cross-spectral density and associated Wigner distribution. The phase-space formulation enables an explicit and quantitative account of partial coherence effects on phase-sensitive imaging. The presented formulas for x-ray spectral density at the detector can be used for performing accurate phase retrieval and optimizing the phase-contrast visibility. The concept of phase-space shearing length derived from this phase-space formulation clarifies the spatial coherence requirement for phase-sensitive imaging with incoherent sources. The theory has been applied to x-ray Talbot interferometric imaging as well. The peak coherence condition derived reveals new insights into three-grating-based Talbot-interferometric imaging and gratings-based x-ray dark-field imaging.

PMv Neuronal Firing May Be Driven by a Movement Command Trajectory within Multidimensional Gaussian Fields.

PubMed

Agarwal, Rahul; Thakor, Nitish V; Sarma, Sridevi V; Massaquoi, Steve G

2015-06-24

The premotor cortex (PM) is known to be a site of visuo-somatosensory integration for the production of movement. We sought to better understand the ventral PM (PMv) by modeling its signal encoding in greater detail. Neuronal firing data was obtained from 110 PMv neurons in two male rhesus macaques executing four reach-grasp-manipulate tasks. We found that in the large majority of neurons (∼90%) the firing patterns across the four tasks could be explained by assuming that a high-dimensional position/configuration trajectory-like signal evolving ∼250 ms before movement was encoded within a multidimensional Gaussian field (MGF). Our findings are consistent with the possibility that PMv neurons process a visually specified reference command for the intended arm/hand position trajectory with respect to a proprioceptively or visually sensed initial configuration. The estimated MGF were (hyper) disc-like, such that each neuron's firing modulated strongly only with commands that evolved along a single direction within position/configuration space. Thus, many neurons appeared to be tuned to slices of this input signal space that as a collection appeared to well cover the space. The MGF encoding models appear to be consistent with the arm-referent, bell-shaped, visual target tuning curves and target selectivity patterns observed in PMV visual-motor neurons. These findings suggest that PMv may implement a lookup table-like mechanism that helps translate intended movement trajectory into time-varying patterns of activation in motor cortex and spinal cord. MGFs provide an improved nonlinear framework for potentially decoding visually specified, intended multijoint arm/hand trajectories well in advance of movement. Copyright © 2015 the authors 0270-6474/15/359508-18$15.00/0.

Machine learning–enabled identification of material phase transitions based on experimental data: Exploring collective dynamics in ferroelectric relaxors

DOE PAGES

Li, Linglong; Yang, Yaodong; Zhang, Dawei; ...

2018-03-30

Exploration of phase transitions and construction of associated phase diagrams are of fundamental importance for condensed matter physics and materials science alike, and remain the focus of extensive research for both theoretical and experimental studies. For the latter, comprehensive studies involving scattering, thermodynamics, and modeling are typically required. We present a new approach to data mining multiple realizations of collective dynamics, measured through piezoelectric relaxation studies, to identify the onset of a structural phase transition in nanometer-scale volumes, that is, the probed volume of an atomic force microscope tip. Machine learning is used to analyze the multidimensional data sets describingmore » relaxation to voltage and thermal stimuli, producing the temperature-bias phase diagram for a relaxor crystal without the need to measure (or know) the order parameter. The suitability of the approach to determine the phase diagram is shown with simulations based on a two-dimensional Ising model. Finally, these results indicate that machine learning approaches can be used to determine phase transitions in ferroelectrics, providing a general, statistically significant, and robust approach toward determining the presence of critical regimes and phase boundaries.« less

Machine learning–enabled identification of material phase transitions based on experimental data: Exploring collective dynamics in ferroelectric relaxors

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

Li, Linglong; Yang, Yaodong; Zhang, Dawei

Exploration of phase transitions and construction of associated phase diagrams are of fundamental importance for condensed matter physics and materials science alike, and remain the focus of extensive research for both theoretical and experimental studies. For the latter, comprehensive studies involving scattering, thermodynamics, and modeling are typically required. We present a new approach to data mining multiple realizations of collective dynamics, measured through piezoelectric relaxation studies, to identify the onset of a structural phase transition in nanometer-scale volumes, that is, the probed volume of an atomic force microscope tip. Machine learning is used to analyze the multidimensional data sets describingmore » relaxation to voltage and thermal stimuli, producing the temperature-bias phase diagram for a relaxor crystal without the need to measure (or know) the order parameter. The suitability of the approach to determine the phase diagram is shown with simulations based on a two-dimensional Ising model. Finally, these results indicate that machine learning approaches can be used to determine phase transitions in ferroelectrics, providing a general, statistically significant, and robust approach toward determining the presence of critical regimes and phase boundaries.« less

The theory of n-scales

NASA Astrophysics Data System (ADS)

Dündar, Furkan Semih

2018-01-01

We provide a theory of n-scales previously called as n dimensional time scales. In previous approaches to the theory of time scales, multi-dimensional scales were taken as product space of two time scales [1, 2]. n-scales make the mathematical structure more flexible and appropriate to real world applications in physics and related fields. Here we define an n-scale as an arbitrary closed subset of ℝn. Modified forward and backward jump operators, Δ-derivatives and Δ-integrals on n-scales are defined.

The nonconvex multi-dimensional Riemann problem for Hamilton-Jacobi equations

NASA Technical Reports Server (NTRS)

Osher, Stanley

1989-01-01

Simple inequalities for the Riemann problem for a Hamilton-Jacobi equation in N space dimension when neither the initial data nor the Hamiltonian need be convex (or concave) are presented. The initial data is globally continuous, affine in each orthant, with a possible jump in normal derivative across each coordinate plane, x sub i = 0. The inequalities become equalities wherever a maxmin equals a minmax and thus an exact closed form solution to this problem is then obtained.

Displays, instruments, and the multi-dimensional world of cartography

NASA Technical Reports Server (NTRS)

Mccleary, George F., Jr.

1989-01-01

Cartographers are creators and purveyors of maps. Maps are representations of space, geographical images of the environment. Maps organize spatial information for convenience, particularly for use in performing tasks which involve the environment. There are many different kinds of maps, and there are as many different uses of maps as there are spatial problems to be solved. Maps and the display instrument dichotomy are examined. Also examined are the categories of map use along with the characteristics of maps.

In search of the best match: probing a multi-dimensional cloud microphysical parameter space to better understand what controls cloud thermodynamic phase

NASA Astrophysics Data System (ADS)

Tan, Ivy; Storelvmo, Trude

2015-04-01

Substantial improvements have been made to the cloud microphysical schemes used in the latest generation of global climate models (GCMs), however, an outstanding weakness of these schemes lies in the arbitrariness of their tuning parameters, which are also notoriously fraught with uncertainties. Despite the growing effort in improving the cloud microphysical schemes in GCMs, most of this effort has neglected to focus on improving the ability of GCMs to accurately simulate the present-day global distribution of thermodynamic phase partitioning in mixed-phase clouds. Liquid droplets and ice crystals not only influence the Earth's radiative budget and hence climate sensitivity via their contrasting optical properties, but also through the effects of their lifetimes in the atmosphere. The current study employs NCAR's CAM5.1, and uses observations of cloud phase obtained by NASA's CALIOP lidar over a 79-month period (November 2007 to June 2014) guide the accurate simulation of the global distribution of mixed-phase clouds in 20∘ latitudinal bands at the -10∘ C, -20∘C and -30∘C isotherms, by adjusting six relevant cloud microphysical tuning parameters in the CAM5.1 via Quasi-Monte Carlo sampling. Among the parameters include those that control the Wegener-Bergeron-Findeisen (WBF) timescale for the conversion of supercooled liquid droplets to ice and snow in mixed-phase clouds, the fraction of ice nuclei that nucleate ice in the atmosphere, ice crystal sedimentation speed, and wet scavenging in stratiform and convective clouds. Using a Generalized Linear Model as a variance-based sensitivity analysis, the relative contributions of each of the six parameters are quantified to gain a better understanding of the importance of their individual and two-way interaction effects on the liquid to ice proportion in mixed-phase clouds. Thus, the methodology implemented in the current study aims to search for the combination of cloud microphysical parameters in a GCM that produce the most accurate reproduction of observations of cloud thermodynamic phase, while simultaneously assessing the weaknesses of the parameterizations in the model. We find that the simulated proportion of liquid to ice in mixed-phase clouds is dominated by the fraction of active ice nuclei in the atmosphere and the WBF timescale. In a follow-up to this study, we apply these results to a fully-coupled GCM, CESM, and find that cloud thermodynamic phase has profound ramifications for the uncertainty associated with climate sensitivity estimates.

A Source Area Approach Demonstrates Moderate Predictive Ability but Pronounced Variability of Invasive Species Traits

PubMed Central

Essl, Franz; Dullinger, Stefan

2016-01-01

The search for traits that make alien species invasive has mostly concentrated on comparing successful invaders and different comparison groups with respect to average trait values. By contrast, little attention has been paid to trait variability among invaders. Here, we combine an analysis of trait differences between invasive and non-invasive species with a comparison of multidimensional trait variability within these two species groups. We collected data on biological and distributional traits for 1402 species of the native, non-woody vascular plant flora of Austria. We then compared the subsets of species recorded and not recorded as invasive aliens anywhere in the world, respectively, first, with respect to the sampled traits using univariate and multiple regression models; and, second, with respect to their multidimensional trait diversity by calculating functional richness and dispersion metrics. Attributes related to competitiveness (strategy type, nitrogen indicator value), habitat use (agricultural and ruderal habitats, occurrence under the montane belt), and propagule pressure (frequency) were most closely associated with invasiveness. However, even the best multiple model, including interactions, only explained a moderate fraction of the differences in invasive success. In addition, multidimensional variability in trait space was even larger among invasive than among non-invasive species. This pronounced variability suggests that invasive success has a considerable idiosyncratic component and is probably highly context specific. We conclude that basing risk assessment protocols on species trait profiles will probably face hardly reducible uncertainties. PMID:27187616

A Source Area Approach Demonstrates Moderate Predictive Ability but Pronounced Variability of Invasive Species Traits.

PubMed

Klonner, Günther; Fischer, Stefan; Essl, Franz; Dullinger, Stefan

2016-01-01

The search for traits that make alien species invasive has mostly concentrated on comparing successful invaders and different comparison groups with respect to average trait values. By contrast, little attention has been paid to trait variability among invaders. Here, we combine an analysis of trait differences between invasive and non-invasive species with a comparison of multidimensional trait variability within these two species groups. We collected data on biological and distributional traits for 1402 species of the native, non-woody vascular plant flora of Austria. We then compared the subsets of species recorded and not recorded as invasive aliens anywhere in the world, respectively, first, with respect to the sampled traits using univariate and multiple regression models; and, second, with respect to their multidimensional trait diversity by calculating functional richness and dispersion metrics. Attributes related to competitiveness (strategy type, nitrogen indicator value), habitat use (agricultural and ruderal habitats, occurrence under the montane belt), and propagule pressure (frequency) were most closely associated with invasiveness. However, even the best multiple model, including interactions, only explained a moderate fraction of the differences in invasive success. In addition, multidimensional variability in trait space was even larger among invasive than among non-invasive species. This pronounced variability suggests that invasive success has a considerable idiosyncratic component and is probably highly context specific. We conclude that basing risk assessment protocols on species trait profiles will probably face hardly reducible uncertainties.

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

A multidimensional anisotropic strength criterion based on Kelvin modes

NASA Astrophysics Data System (ADS)

Arramon, Yves Pierre

A new theory for the prediction of multiaxial strength of anisotropic elastic materials was proposed by Biegler and Mehrabadi (1993). This theory is based on the premise that the total elastic strain energy of an anisotropic material subjected to multiaxial stress can be decomposed into dilatational and deviatoric modes. A multidimensional strength criterion may thus be formulated by postulating that the failure would occur when the energy stored in one of these modes has reached a critical value. However, the logic employed by these authors to formulate a failure criterion based on this theory could not be extended to multiaxial stress. In this thesis, an alternate criterion is presented which redresses the biaxial restriction by reformulating the surfaces of constant modal energy as surfaces of constant eigenstress magnitude. The resulting failure envelope, in a multidimensional stress space, is piecewise smooth. Each facet of the envelope is expected to represent the locus of failure data by a particular Kelvin mode. It is further shown that the Kelvin mode theory alone provides an incomplete description of the failure of some materials, but that this weakness can be addressed by the introduction of a set of complementary modes. A revised theory which combines both Kelvin and complementary modes is thus proposed and applied seven example materials: an isotropic concrete, tetragonal paperboard, two orthotropic softwoods, two orthotropic hardwoods and an orthotropic cortical bone. The resulting failure envelopes for these examples were plotted and, with the exception of concrete, shown to produce intuitively correct failure predictions.

Alisse : Advanced life support system evaluator

NASA Astrophysics Data System (ADS)

Brunet, Jean; Gerbi, Olivier; André, Philippe; Davin, Elisabeth; Avezuela Rodriguez, Raul; Carbonero, Fernando; Soumalainen, Emilia; Lasseur, Christophe

Long duration missions, such as the establishment of permanent bases on the lunar surface or the travel to Mars, require such an amount of life support consumables (e.g. food, water and oxygen) that direct supply or re-supply from Earth is not an option anymore. Regenerative Life Support Systems are therefore necessary to sustain long-term manned space mission to increase recycling rates and so reduce the launched mass. The architecture of an Environmental Controlled Life Support System widely depends on the mission scenario. Even for a given mission scenario, different architectures could be envisaged which need to be evaluated and compared with appropriate tools. As these evaluation and comparison, based on the single criterion of Equivalent System Mass, was not considered com-prehensive enough, ESA is developing a multi-criteria evaluation tool: ALISSE (Advanced Life Support System Evaluator). The main objective of ALISSE, and of the work presented here, is the definition and implemen-tation of a metrics system, addressing the complexity of any ECLSS along its Life Cycle phases. A multi-dimensional and multi-criteria (i.e. mass, energy, efficiency, risk to human, reliability, crew time, sustainability, life cycle cost) approach is proposed through the development of a computing support platform. Each criterion being interrelated with the others, a model based system approach is used. ALISSE is expected to provide significant inputs to the ESA Concurrent Design Facility and, as a consequence, to be a highly valuable tool for decision process linked to any manned space mission. Full contact detail for the contact author : Jean Brunet Sherpa Engineering General Manager Phone : 0033(0)608097480 j.brunet@sherpa-eng.com

State-space grid analysis: applications for clinical whole systems complementary and alternative medicine research.

PubMed

Howerter, Amy; Hollenstein, Tom; Boon, Heather; Niemeyer, Kathryn; Brule, David

2012-01-01

This paper presents state space grids (SSGs) as a mathematically less intensive methodology for process-oriented research beyond traditional qualitative and quantitative approaches in whole systems of complementary and alternative medicine (WS-CAM). SSGs, originally applied in developmental psychology research, offer a logical, flexible, and accessible tool for capturing emergent changes in the temporal dynamics of patient behaviors, manifestations of resilience, and outcomes. The SSG method generates a two-dimensional visualization and quantification of the inter-relationships between variables on a moment-to-moment basis. SSGs can describe dyadic interactive behavior in real time and, followed longitudinally, allow evaluation of how change occurs over extended time periods. Practice theories of WS-CAM encompass the holistic health concept of whole-person outcomes, including nonlinear pathways to complex, multidimensional changes. Understanding how the patient as a living system arrives at these outcomes requires studying the process of healing, e.g., sudden abrupt worsening and/or improvements, 'healing crises', and 'unstuckness', from which the multiple inter-personal and intra-personal outcomes emerge. SSGs can document the indirect, emergent dynamic effects of interventions, transitional phases, and the mutual interaction of patient and environment that underlie the healing process. Two WS-CAM research exemplars are provided to demonstrate the feasibility of using SSGs in both dyadic and within-patient contexts, and to illustrate the possibilities for clinically relevant, process-focused hypotheses. This type of research has the potential to help clinicians select, modify and optimize treatment plans earlier in the course of care and produce more successful outcomes for more patients. Copyright © 2012 S. Karger AG, Basel.

Exploring short-GRB afterglow parameter space for observations in coincidence with gravitational waves

NASA Astrophysics Data System (ADS)

Saleem, M.; Resmi, L.; Misra, Kuntal; Pai, Archana; Arun, K. G.

2018-03-01

Short duration Gamma Ray Bursts (SGRB) and their afterglows are among the most promising electromagnetic (EM) counterparts of Neutron Star (NS) mergers. The afterglow emission is broad-band, visible across the entire electromagnetic window from γ-ray to radio frequencies. The flux evolution in these frequencies is sensitive to the multidimensional afterglow physical parameter space. Observations of gravitational wave (GW) from BNS mergers in spatial and temporal coincidence with SGRB and associated afterglows can provide valuable constraints on afterglow physics. We run simulations of GW-detected BNS events and assuming that all of them are associated with a GRB jet which also produces an afterglow, investigate how detections or non-detections in X-ray, optical and radio frequencies can be influenced by the parameter space. We narrow down the regions of afterglow parameter space for a uniform top-hat jet model, which would result in different detection scenarios. We list inferences which can be drawn on the physics of GRB afterglows from multimessenger astronomy with coincident GW-EM observations.

SciSpark's SRDD : A Scientific Resilient Distributed Dataset for Multidimensional Data

NASA Astrophysics Data System (ADS)

Palamuttam, R. S.; Wilson, B. D.; Mogrovejo, R. M.; Whitehall, K. D.; Mattmann, C. A.; McGibbney, L. J.; Ramirez, P.

2015-12-01

Remote sensing data and climate model output are multi-dimensional arrays of massive sizes locked away in heterogeneous file formats (HDF5/4, NetCDF 3/4) and metadata models (HDF-EOS, CF) making it difficult to perform multi-stage, iterative science processing since each stage requires writing and reading data to and from disk. We have developed SciSpark, a robust Big Data framework, that extends ApacheTM Spark for scaling scientific computations. Apache Spark improves the map-reduce implementation in ApacheTM Hadoop for parallel computing on a cluster, by emphasizing in-memory computation, "spilling" to disk only as needed, and relying on lazy evaluation. Central to Spark is the Resilient Distributed Dataset (RDD), an in-memory distributed data structure that extends the functional paradigm provided by the Scala programming language. However, RDDs are ideal for tabular or unstructured data, and not for highly dimensional data. The SciSpark project introduces the Scientific Resilient Distributed Dataset (sRDD), a distributed-computing array structure which supports iterative scientific algorithms for multidimensional data. SciSpark processes data stored in NetCDF and HDF files by partitioning them across time or space and distributing the partitions among a cluster of compute nodes. We show usability and extensibility of SciSpark by implementing distributed algorithms for geospatial operations on large collections of multi-dimensional grids. In particular we address the problem of scaling an automated method for finding Mesoscale Convective Complexes. SciSpark provides a tensor interface to support the pluggability of different matrix libraries. We evaluate performance of the various matrix libraries in distributed pipelines, such as Nd4jTM and BreezeTM. We detail the architecture and design of SciSpark, our efforts to integrate climate science algorithms, parallel ingest and partitioning (sharding) of A-Train satellite observations from model grids. These solutions are encompassed in SciSpark, an open-source software framework for distributed computing on scientific data.

A general formalism for phase space calculations

NASA Technical Reports Server (NTRS)

Norbury, John W.; Deutchman, Philip A.; Townsend, Lawrence W.; Cucinotta, Francis A.

1988-01-01

General formulas for calculating the interactions of galactic cosmic rays with target nuclei are presented. Methods for calculating the appropriate normalization volume elements and phase space factors are presented. Particular emphasis is placed on obtaining correct phase space factors for 2-, and 3-body final states. Calculations for both Lorentz-invariant and noninvariant phase space are presented.

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…

Nonequilibrium life-cycles in Ocean Heat Content

NASA Astrophysics Data System (ADS)

Weiss, Jeffrey B.; Fox-Kemper, Baylor; Mandal, Dibyendu; Zia, Royce K. P.

2014-03-01

Natural climate variability can be considered as fluctuations in a nonequilibrium steady state. A fundamental property of nonequilibrium steady states is the phase space current which provides a preferred direction for fluctuations, and is manifested as preferred life-cycles for climate fluctuations. We propose a new quantity, the phase space angular momentum, to quantify the phase space rotation. In analogy with traditional angular momentum, which quantifies the rotation of mass in physical space, the phase space angular momentum quantifies the rotation of probability in phase space. It has the additional advantage that it is straightforward to calculate from a time series. We investigate the phase space angular momentum for fluctuations in ocean heat content in both observations and ocean general circulation models. We gratefully acknowledge financial support from the National Science Foundation (USA) under grant OCE 1245944.

Quantum mechanics on phase space: The hydrogen atom and its Wigner functions

NASA Astrophysics Data System (ADS)

Campos, P.; Martins, M. G. R.; Fernandes, M. C. B.; Vianna, J. D. M.

2018-03-01

Symplectic quantum mechanics (SQM) considers a non-commutative algebra of functions on a phase space Γ and an associated Hilbert space HΓ, to construct a unitary representation for the Galilei group. From this unitary representation the Schrödinger equation is rewritten in phase space variables and the Wigner function can be derived without the use of the Liouville-von Neumann equation. In this article the Coulomb potential in three dimensions (3D) is resolved completely by using the phase space Schrödinger equation. The Kustaanheimo-Stiefel(KS) transformation is applied and the Coulomb and harmonic oscillator potentials are connected. In this context we determine the energy levels, the amplitude of probability in phase space and correspondent Wigner quasi-distribution functions of the 3D-hydrogen atom described by Schrödinger equation in phase space.

Space station MSFC-DPD-235/DR no. MA-05 phase C/D program development plan. Volume 2: Phase C/D, programmatic requirements

NASA Technical Reports Server (NTRS)

1971-01-01

The design plan requirements define the design implementation and control requirements for Phase C/D of the Modular Space Station Project and specifically address the Initial Space Station phase of the Space Station Program (modular). It is based primarily on the specific objective of translating the requirements of the Space Station Program, Project, Interface, and Support Requirements and preliminary contract end x item specifications into detail design of the operational systems which comprise the initial space station. This document is designed to guide aerospace contractors in the planning and bidding for Phase C/D.

Particle-in-cell/accelerator code for space-charge dominated beam simulation

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

2012-05-08

Warp is a multidimensional discrete-particle beam simulation program designed to be applicable where the beam space-charge is non-negligible or dominant. It is being developed in a collaboration among LLNL, LBNL and the University of Maryland. It was originally designed and optimized for heave ion fusion accelerator physics studies, but has received use in a broader range of applications, including for example laser wakefield accelerators, e-cloud studies in high enery accelerators, particle traps and other areas. At present it incorporates 3-D, axisymmetric (r,z) planar (x-z) and transverse slice (x,y) descriptions, with both electrostatic and electro-magnetic fields, and a beam envelope model.more » The code is guilt atop the Python interpreter language.« less

Precision Attitude Determination for an Infrared Space Telescope

NASA Technical Reports Server (NTRS)

Benford, Dominic J.

2008-01-01

We have developed performance simulations for a precision attitude determination system using a focal plane star tracker on an infrared space telescope. The telescope is being designed for the Destiny mission to measure cosmologically distant supernovae as one of the candidate implementations for the Joint Dark Energy Mission. Repeat observations of the supernovae require attitude control at the level of 0.010 arcseconds (0.05 microradians) during integrations and at repeat intervals up to and over a year. While absolute accuracy is not required, the repoint precision is challenging. We have simulated the performance of a focal plane star tracker in a multidimensional parameter space, including pixel size, read noise, and readout rate. Systematic errors such as proper motion, velocity aberration, and parallax can be measured and compensated out. Our prediction is that a relative attitude determination accuracy of 0.001 to 0.002 arcseconds (0.005 to 0.010 microradians) will be achievable.

Comparison Analysis of Recognition Algorithms of Forest-Cover Objects on Hyperspectral Air-Borne and Space-Borne Images

NASA Astrophysics Data System (ADS)

Kozoderov, V. V.; Kondranin, T. V.; Dmitriev, E. V.

2017-12-01

The basic model for the recognition of natural and anthropogenic objects using their spectral and textural features is described in the problem of hyperspectral air-borne and space-borne imagery processing. The model is based on improvements of the Bayesian classifier that is a computational procedure of statistical decision making in machine-learning methods of pattern recognition. The principal component method is implemented to decompose the hyperspectral measurements on the basis of empirical orthogonal functions. Application examples are shown of various modifications of the Bayesian classifier and Support Vector Machine method. Examples are provided of comparing these classifiers and a metrical classifier that operates on finding the minimal Euclidean distance between different points and sets in the multidimensional feature space. A comparison is also carried out with the " K-weighted neighbors" method that is close to the nonparametric Bayesian classifier.

MIDAS (Modafinil in Debilitating Fatigue After Stroke): A Randomized, Double-Blind, Placebo-Controlled, Cross-Over Trial.

PubMed

Bivard, Andrew; Lillicrap, Thomas; Krishnamurthy, Venkatesh; Holliday, Elizabeth; Attia, John; Pagram, Heather; Nilsson, Michael; Parsons, Mark; Levi, Christopher R

2017-05-01

This study aimed to assess the efficacy of modafinil, a wakefulness-promoting agent in alleviating post-stroke fatigue ≥3 months after stroke. We hypothesized that 200 mg of modafinil daily for 6 weeks would result in reduced symptoms of fatigue compared with placebo. This single-center phase 2 trial used a randomized, double-blind, placebo-controlled, crossover design. The key inclusion criterion was a multidimensional fatigue inventory score of ≥60. Patients were randomized to either modafinil or placebo for 6 weeks of therapy, then after a 1 week washout period swapped treatment arms for a second 6 weeks of therapy. The primary outcome was the multidimensional fatigue inventory; secondary outcomes included the Montreal cognitive assessment, the Depression, Anxiety, and Stress Scale (DASS), and the Stroke-Specific Quality of Life (SSQoL) scale. The multidimensional fatigue inventory is a self-administered questionnaire with a range of 0 to 100. Treatment efficacy was assessed using linear regression by estimating within-person, baseline-adjusted differences in mean outcomes after therapy. This trial was registered with the Australian New Zealand Clinical Trials Registry (ACTRN12615000350527). A total of 232 stroke survivors were screened and 36 were randomized. Participants receiving modafinil reported a significant decrease in fatigue (multidimensional fatigue inventory, -7.38; 95% CI, -21.76 to -2.99; P <0.001) and improved quality of life (SSQoL, 11.81; 95% CI, 2.31 to 21.31; P =0.0148) compared with placebo. Montreal cognitive assessment and DASS were not significantly improved with modafinil therapy during the study period ( P >0.05). Stroke survivors with nonresolving fatigue reported reduced fatigue and improved quality of life after taking 200 mg daily treatment with modafinil. URL: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=368268. Unique identifier: ACTRN12615000350527. © 2017 The Authors.

Structural changes in cross-border liabilities: A multidimensional approach

NASA Astrophysics Data System (ADS)

Araújo, Tanya; Spelta, Alessandro

2014-01-01

We study the international interbank market through a geometric analysis of empirical data. The geometric analysis of the time series of cross-country liabilities shows that the systematic information of the interbank international market is contained in a space of small dimension. Geometric spaces of financial relations across countries are developed, for which the space volume, multivariate skewness and multivariate kurtosis are computed. The behavior of these coefficients reveals an important modification acting in the financial linkages since 1997 and allows us to relate the shape of the geometric space that emerges in recent years to the globally turbulent period that has characterized financial systems since the late 1990s. Here we show that, besides a persistent decrease in the volume of the geometric space since 1997, the observation of a generalized increase in the values of the multivariate skewness and kurtosis sheds some light on the behavior of cross-border interdependencies during periods of financial crises. This was found to occur in such a systematic fashion, that these coefficients may be used as a proxy for systemic risk.

Programming Nanoparticles in Multiscale: Optically Modulated Assembly and Phase Switching of Silicon Nanoparticle Array.

PubMed

Wang, Letian; Rho, Yoonsoo; Shou, Wan; Hong, Sukjoon; Kato, Kimihiko; Eliceiri, Matthew; Shi, Meng; Grigoropoulos, Costas P; Pan, Heng; Carraro, Carlo; Qi, Dongfeng

2018-03-27

Manipulating and tuning nanoparticles by means of optical field interactions is of key interest for nanoscience and applications in electronics and photonics. We report scalable, direct, and optically modulated writing of nanoparticle patterns (size, number, and location) of high precision using a pulsed nanosecond laser. The complex nanoparticle arrangement is modulated by the laser pulse energy and polarization with the particle size ranging from 60 to 330 nm. Furthermore, we report fast cooling-rate induced phase switching of crystalline Si nanoparticles to the amorphous state. Such phase switching has usually been observed in compound phase change materials like GeSbTe. The ensuing modification of atomic structure leads to dielectric constant switching. Based on these effects, a multiscale laser-assisted method of fabricating Mie resonator arrays is proposed. The number of Mie resonators, as well as the resonance peaks and dielectric constants of selected resonators, can be programmed. The programmable light-matter interaction serves as a mechanism to fabricate optical metasurfaces, structural color, and multidimensional optical storage devices.

Further development of the talent development environment questionnaire for sport.

PubMed

Li, Chunxiao; Wang, Chee Keng John; Pyun, Do Young; Martindale, Russell

2015-01-01

Given the significance of monitoring the critical environmental factors that facilitate athlete performance, this two-phase research aimed to validate and refine the revised talent development environment questionnaire (TDEQ). The TDEQ is a multidimensional self-report scale that assesses talented athletes' environmental experiences. Study 1 (the first phase) involved the examination of the revised TDEQ through an exploratory factor analysis (n = 363). This exploratory investigation identified a 28-item five-factor structure (i.e., TDEQ-5) with adequate internal consistency. Study 2 (the second phase) examined the factorial structure of the TDEQ-5, including convergent validity, discriminant validity, and group invariance (i.e., gender and sports type). The second phase was carried out with 496 talented athletes through the application of confirmatory factor analyses and multigroup invariance tests. The results supported the convergent validity, discriminant validity, and group invariance of the TDEQ-5. In conclusion, the TDEQ-5 with 25 items appears to be a reliable and valid scale for use in talent development environments.

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.

Laser pulses for coherent xuv Raman excitation

NASA Astrophysics Data System (ADS)

Greenman, Loren; Koch, Christiane P.; Whaley, K. Birgitta

2015-07-01

We combine multichannel electronic structure theory with quantum optimal control to derive femtosecond-time-scale Raman pulse sequences that coherently populate a valence excited state. For a neon atom, Raman target populations of up to 13% are obtained. Superpositions of the ground and valence Raman states with a controllable relative phase are found to be reachable with up to 4.5% population and arbitrary phase control facilitated by the pump pulse carrier-envelope phase. Analysis of the optimized pulse structure reveals a sequential mechanism in which the valence excitation is reached via a fast (femtosecond) population transfer through an intermediate resonance state in the continuum rather than avoiding intermediate-state population with simultaneous or counterintuitive (stimulated Raman adiabatic passage) pulse sequences. Our results open a route to coupling valence excitations and core-hole excitations in molecules and aggregates that locally address specific atoms and represent an initial step towards realization of multidimensional spectroscopy in the xuv and x-ray regimes.

Behavioral Hypervolumes of Predator Groups and Predator-Predator Interactions Shape Prey Survival Rates and Selection on Prey Behavior

PubMed Central

Pruitt, Jonathan N.; Howell, Kimberly A.; Gladney, Shaniqua J.; Yang, Yusan; Lichtenstein, James L. L.; Spicer, Michelle Elise; Echeverri, Sebastian A.; Pinter-Wollman, Noa

2017-01-01

Predator-prey interactions often vary on the basis of the traits of the individual predators and prey involved. Here we examine whether the multidimensional behavioral diversity of predator groups shapes prey mortality rates and selection on prey behavior. We ran individual sea stars (Pisaster ochraceus) through three behavioral assays to characterize individuals’ behavioral phenotype along three axes. We then created groups that varied in the volume of behavioral space that they occupied. We further manipulated the ability of predators to interact with one another physically via the addition of barriers. Prey snails (Chlorostome funebralis) were also run through an assay to evaluate their predator avoidance behavior before their use in mesocosm experiments. We then subjected pools of prey to predator groups and recorded the number of prey consumed and their behavioral phenotypes. We found that predator-predator interactions changed survival selection on prey traits: when predators were prevented from interacting, more fearful snails had higher survival rates, whereas prey fearfulness had no effect on survival when predators were free to interact. We also found that groups of predators that occupied a larger volume in behavioral trait space consumed 35% more prey snails than homogeneous predator groups. Finally, we found that behavioral hypervolumes were better predictors of prey survival rates than single behavioral traits or other multivariate statistics (i.e., principal component analysis). Taken together, predator-predator interactions and multidimensional behavioral diversity determine prey survival rates and selection on prey traits in this system. PMID:28221831

Behavioral Hypervolumes of Predator Groups and Predator-Predator Interactions Shape Prey Survival Rates and Selection on Prey Behavior.

PubMed

Pruitt, Jonathan N; Howell, Kimberly A; Gladney, Shaniqua J; Yang, Yusan; Lichtenstein, James L L; Spicer, Michelle Elise; Echeverri, Sebastian A; Pinter-Wollman, Noa

2017-03-01

Predator-prey interactions often vary on the basis of the traits of the individual predators and prey involved. Here we examine whether the multidimensional behavioral diversity of predator groups shapes prey mortality rates and selection on prey behavior. We ran individual sea stars (Pisaster ochraceus) through three behavioral assays to characterize individuals' behavioral phenotype along three axes. We then created groups that varied in the volume of behavioral space that they occupied. We further manipulated the ability of predators to interact with one another physically via the addition of barriers. Prey snails (Chlorostome funebralis) were also run through an assay to evaluate their predator avoidance behavior before their use in mesocosm experiments. We then subjected pools of prey to predator groups and recorded the number of prey consumed and their behavioral phenotypes. We found that predator-predator interactions changed survival selection on prey traits: when predators were prevented from interacting, more fearful snails had higher survival rates, whereas prey fearfulness had no effect on survival when predators were free to interact. We also found that groups of predators that occupied a larger volume in behavioral trait space consumed 35% more prey snails than homogeneous predator groups. Finally, we found that behavioral hypervolumes were better predictors of prey survival rates than single behavioral traits or other multivariate statistics (i.e., principal component analysis). Taken together, predator-predator interactions and multidimensional behavioral diversity determine prey survival rates and selection on prey traits in this system.

Topological data analysis of financial time series: Landscapes of crashes

NASA Astrophysics Data System (ADS)

Gidea, Marian; Katz, Yuri

2018-02-01

We explore the evolution of daily returns of four major US stock market indices during the technology crash of 2000, and the financial crisis of 2007-2009. Our methodology is based on topological data analysis (TDA). We use persistence homology to detect and quantify topological patterns that appear in multidimensional time series. Using a sliding window, we extract time-dependent point cloud data sets, to which we associate a topological space. We detect transient loops that appear in this space, and we measure their persistence. This is encoded in real-valued functions referred to as a 'persistence landscapes'. We quantify the temporal changes in persistence landscapes via their Lp-norms. We test this procedure on multidimensional time series generated by various non-linear and non-equilibrium models. We find that, in the vicinity of financial meltdowns, the Lp-norms exhibit strong growth prior to the primary peak, which ascends during a crash. Remarkably, the average spectral density at low frequencies of the time series of Lp-norms of the persistence landscapes demonstrates a strong rising trend for 250 trading days prior to either dotcom crash on 03/10/2000, or to the Lehman bankruptcy on 09/15/2008. Our study suggests that TDA provides a new type of econometric analysis, which complements the standard statistical measures. The method can be used to detect early warning signals of imminent market crashes. We believe that this approach can be used beyond the analysis of financial time series presented here.

TU-AB-BRC-07: Efficiency of An IAEA Phase-Space Source for a Low Energy X-Ray Tube Using Egs++

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

Watson, PGF; Renaud, MA; Seuntjens, J

Purpose: To extend the capability of the EGSnrc C++ class library (egs++) to write and read IAEA phase-space files as a particle source, and to assess the relative efficiency gain in dose calculation using an IAEA phase-space source for modelling a miniature low energy x-ray source. Methods: We created a new ausgab object to score particles exiting a user-defined geometry and write them to an IAEA phase-space file. A new particle source was created to read from IAEA phase-space data. With these tools, a phase-space file was generated for particles exiting a miniature 50 kVp x-ray tube (The INTRABEAM System,more » Carl Zeiss). The phase-space source was validated by comparing calculated PDDs with a full electron source simulation of the INTRABEAM. The dose calculation efficiency gain of the phase-space source was determined relative to the full simulation. The efficiency gain as a function of i) depth in water, and ii) job parallelization was investigated. Results: The phase-space and electron source PDDs were found to agree to 0.5% RMS, comparable to statistical uncertainties. The use of a phase-space source for the INTRABEAM led to a relative efficiency gain of greater than 20 over the full electron source simulation, with an increase of up to a factor of 196. The efficiency gain was found to decrease with depth in water, due to the influence of scattering. Job parallelization (across 2 to 256 cores) was not found to have any detrimental effect on efficiency gain. Conclusion: A set of tools has been developed for writing and reading IAEA phase-space files, which can be used with any egs++ user code. For simulation of a low energy x-ray tube, the use of a phase-space source was found to increase the relative dose calculation efficiency by factor of up to 196. The authors acknowledge partial support by the CREATE Medical Physics Research Training Network grant of the Natural Sciences and Engineering Research Council (Grant No. 432290).« less

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…

Quantifying Stream-Aquifer Exchanges Over Scales: the Concept of Nested Interfaces

NASA Astrophysics Data System (ADS)

Flipo, N.; Mouhri, A.; Labarthe, B.; Saleh, F. S.

2013-12-01

Recent developments in hydrological modelling are based on a view of the interface being a single continuum through which water flows. These coupled hydrological-hydrogeological models, emphasizing the importance of the stream-aquifer interface (SAI), are more and more used in hydrological sciences for pluri-disciplinary studies aiming at questioning environmental issues. This notion of a single continuum comes from the historical modelling of hydrosystems based on the hypothesis of a homogeneous media that led to the Darcy law. Nowadays, there is a need to first bridge the gap between hydrological and eco-hydrological views of the SAIs, and, second, to rationalize the modelling of SAI within a consistent framework that fully takes into account the multi-dimensionality of the SAIs. We first define the concept of nested SAIs as a key transitional component of continental hydrosystem. We then demonstrate the usefulness of the concept for the multi-dimensional study of the SAI, with a special emphasis on the stream network which is identified as the key component for scaling hydrological processes occurring at the interface. Finally we focus on SAI modelling at various scales with up-to-date methodologies and give some guidance for the multi-dimensional modelling of the interface using the innovative methodology MIM (Measurements-Interpolation-Modelling), which is graphically developed. MIM scales in space three pools of methods needed to fully understand SAIs. The outcome of MIM is the localization in space of the type of SAI that can be studied by a given approach. The efficiency of the method is illustrated from the local (approx. 1m) to the regional scale (> 10 000 km2) with two examples from the Paris basin (France). The first one consists in the implementation of a sampling system of stream-aquifer exchanges, which is coupled with local 2D thermo-hydro models and a pseudo 3D hydro(geo)logical model at the watershed scale (40 km2). The quantification of monthly stream-aquifer exchanges over 14 000 km of river network in the Paris basin (74 000 km2) corresponds to a unique regional scale example.

Stargate GTM: Bridging Descriptor and Activity Spaces.

PubMed

Gaspar, Héléna A; Baskin, Igor I; Marcou, Gilles; Horvath, Dragos; Varnek, Alexandre

2015-11-23

Predicting the activity profile of a molecule or discovering structures possessing a specific activity profile are two important goals in chemoinformatics, which could be achieved by bridging activity and molecular descriptor spaces. In this paper, we introduce the "Stargate" version of the Generative Topographic Mapping approach (S-GTM) in which two different multidimensional spaces (e.g., structural descriptor space and activity space) are linked through a common 2D latent space. In the S-GTM algorithm, the manifolds are trained simultaneously in two initial spaces using the probabilities in the 2D latent space calculated as a weighted geometric mean of probability distributions in both spaces. S-GTM has the following interesting features: (1) activities are involved during the training procedure; therefore, the method is supervised, unlike conventional GTM; (2) using molecular descriptors of a given compound as input, the model predicts a whole activity profile, and (3) using an activity profile as input, areas populated by relevant chemical structures can be detected. To assess the performance of S-GTM prediction models, a descriptor space (ISIDA descriptors) of a set of 1325 GPCR ligands was related to a B-dimensional (B = 1 or 8) activity space corresponding to pKi values for eight different targets. S-GTM outperforms conventional GTM for individual activities and performs similarly to the Lasso multitask learning algorithm, although it is still slightly less accurate than the Random Forest method.

Development of a model of the tobacco industry's interference with tobacco control programmes

PubMed Central

Trochim, W; Stillman, F; Clark, P; Schmitt, C

2003-01-01

Objective: To construct a conceptual model of tobacco industry tactics to undermine tobacco control programmes for the purposes of: (1) developing measures to evaluate industry tactics, (2) improving tobacco control planning, and (3) supplementing current or future frameworks used to classify and analyse tobacco industry documents. Design: Web based concept mapping was conducted, including expert brainstorming, sorting, and rating of statements describing industry tactics. Statistical analyses used multidimensional scaling and cluster analysis. Interpretation of the resulting maps was accomplished by an expert panel during a face-to-face meeting. Subjects: 34 experts, selected because of their previous encounters with industry resistance or because of their research into industry tactics, took part in some or all phases of the project. Results: Maps with eight non-overlapping clusters in two dimensional space were developed, with importance ratings of the statements and clusters. Cluster and quadrant labels were agreed upon by the experts. Conclusions: The conceptual maps summarise the tactics used by the industry and their relationships to each other, and suggest a possible hierarchy for measures that can be used in statistical modelling of industry tactics and for review of industry documents. Finally, the maps enable hypothesis of a likely progression of industry reactions as public health programmes become more successful, and therefore more threatening to industry profits. PMID:12773723

Developing Present-day Proxy Cases Based on NARVAL Data for Investigating Low Level Cloud Responses to Future Climate Change.

NASA Astrophysics Data System (ADS)

Reilly, Stephanie

2017-04-01

The energy budget of the entire global climate is significantly influenced by the presence of boundary layer clouds. The main aim of the High Definition Clouds and Precipitation for Advancing Climate Prediction (HD(CP)2) project is to improve climate model predictions by means of process studies of clouds and precipitation. This study makes use of observed elevated moisture layers as a proxy of future changes in tropospheric humidity. The associated impact on radiative transfer triggers fast responses in boundary layer clouds, providing a framework for investigating this phenomenon. The investigation will be carried out using data gathered during the Next-generation Aircraft Remote-sensing for VALidation (NARVAL) South campaigns. Observational data will be combined with ECMWF reanalysis data to derive the large scale forcings for the Large Eddy Simulations (LES). Simulations will be generated for a range of elevated moisture layers, spanning a multi-dimensional phase space in depth, amplitude, elevation, and cloudiness. The NARVAL locations will function as anchor-points. The results of the large eddy simulations and the observations will be studied and compared in an attempt to determine how simulated boundary layer clouds react to changes in radiative transfer from the free troposphere. Preliminary LES results will be presented and discussed.

Replica exchange and expanded ensemble simulations as Gibbs sampling: simple improvements for enhanced mixing.

PubMed

Chodera, John D; Shirts, Michael R

2011-11-21

The widespread popularity of replica exchange and expanded ensemble algorithms for simulating complex molecular systems in chemistry and biophysics has generated much interest in discovering new ways to enhance the phase space mixing of these protocols in order to improve sampling of uncorrelated configurations. Here, we demonstrate how both of these classes of algorithms can be considered as special cases of Gibbs sampling within a Markov chain Monte Carlo framework. Gibbs sampling is a well-studied scheme in the field of statistical inference in which different random variables are alternately updated from conditional distributions. While the update of the conformational degrees of freedom by Metropolis Monte Carlo or molecular dynamics unavoidably generates correlated samples, we show how judicious updating of the thermodynamic state indices--corresponding to thermodynamic parameters such as temperature or alchemical coupling variables--can substantially increase mixing while still sampling from the desired distributions. We show how state update methods in common use can lead to suboptimal mixing, and present some simple, inexpensive alternatives that can increase mixing of the overall Markov chain, reducing simulation times necessary to obtain estimates of the desired precision. These improved schemes are demonstrated for several common applications, including an alchemical expanded ensemble simulation, parallel tempering, and multidimensional replica exchange umbrella sampling.

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

Analysis of Odorants in Marking Fluid of Siberian Tiger (Panthera tigris altaica) Using Simultaneous Sensory and Chemical Analysis with Headspace Solid-Phase Microextraction and Multidimensional Gas Chromatography-Mass Spectrometry-Olfactometry.

PubMed

Soso, Simone B; Koziel, Jacek A

2016-06-25

Scent-marking is the most effective method of communication in the presence or absence of a signaler. These complex mixtures result in a multifaceted interaction triggered by the sense of smell. The objective was to identify volatile organic compound (VOC) composition and odors emitted by total marking fluid (MF) associated with Siberian tigers (Panthera tigris altaica). Siberian tiger, an endangered species, was chosen because its MF had never been analyzed. Solid phase microextraction (SPME) for headspace volatile collection combined with multidimensional gas chromatography-mass spectrometry-olfactometry for simultaneous chemical and sensory analyses were used. Thirty-two VOCs emitted from MF were identified. 2-acetyl-1-pyrroline, the sole previously identified compound responsible for the "characteristic" odor of P. tigris MF, was identified along with two additional compounds confirmed with standards (urea, furfural) and four tentatively identified compounds (3-methylbutanamine, (R)-3-methylcyclopentanone, propanedioic acid, and 3-hydroxybutanal) as being responsible for the characteristic aroma of Siberian tiger MF. Simultaneous chemical and sensory analyses improved characterization of scent-markings and identified compounds not previously reported in MF of other tiger species. This research will assist animal ecologists, behaviorists, and zookeepers in understanding how scents from specific MF compounds impact tiger and wildlife communication and improve management practices related to animal behavior. Simultaneous chemical and sensory analyses is applicable to unlocking scent-marking information for other species.

Multidimensional Analysis of Direct-Drive Plastic-Shell Implosions on OMEGA

NASA Astrophysics Data System (ADS)

Radha, P. B.

2004-11-01

Direct-drive implosions of plastic shells with the OMEGA laser are used as energy-scaled warm surrogates for ignition cryogenic targets designed for use on the National Ignition Facility. Plastic targets involve varying shell thickness (15 to 33 μm), fill pressures (3 to 15 atm), and shell adiabats. The multidimensional hydrodynamics code DRACO is used to evaluate the effects of capsule-surface roughness and illumination nonuniformities on target performance. These simulations indicate that shell stability during the acceleration phase plays a critical role in determining fusion yields. For shells that are thick enough to survive the Rayleigh--Taylor growth, target yields are significantly reduced by growth of the long (ℓ < 10) and intermediate modes (20 < ℓ < 50) occurring from single-beam laser nonuniformities. The neutron production rate for these thick shells truncates relative to one-dimensional (1-D) predictions. The neutron-rate curves for the thinner shells, however, have significantly lower amplitudes and widths closer to 1-D results, indicating shell breakup during the acceleration phase. The simulation results are consistent with experimental observations. Previously, the stability of plastic-shell implosions had been correlated to a static ``mix-width'' at the boundary of the gas and plastic pusher estimated using a variety of experimental observables and an assumption of spherical symmetry. Results of these 2-D simulations provide a comprehensive understanding of warm-target implosion dynamics without assumptions of spherical symmetry and serve to answer the question of the hydrodynamic surrogacy between these plastic-shell implosions and the cryogenic ignition designs.

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

Li, Minghai; Duan, Mojie; Fan, Jue

The thermodynamics and kinetics of protein folding and protein conformational changes are governed by the underlying free energy landscape. However, the multidimensional nature of the free energy landscape makes it difficult to describe. We propose to use a weighted-graph approach to depict the free energy landscape with the nodes on the graph representing the conformational states and the edge weights reflecting the free energy barriers between the states. Our graph is constructed from a molecular dynamics trajectory and does not involve projecting the multi-dimensional free energy landscape onto a low-dimensional space defined by a few order parameters. The calculation ofmore » free energy barriers was based on transition-path theory using the MSMBuilder2 package. We compare our graph with the widely used transition disconnectivity graph (TRDG) which is constructed from the same trajectory and show that our approach gives more accurate description of the free energy landscape than the TRDG approach even though the latter can be organized into a simple tree representation. The weighted-graph is a general approach and can be used on any complex system.« less

Multi-dimensional spatial light communication made with on-chip InGaN photonic integration

NASA Astrophysics Data System (ADS)

Yang, Yongchao; Zhu, Bingcheng; Shi, Zheng; Wang, Jinyuan; Li, Xin; Gao, Xumin; Yuan, Jialei; Li, Yuanhang; Jiang, Yan; Wang, Yongjin

2017-04-01

Here, we propose, fabricate and characterize suspended photonic integration of InGaN multiple-quantum-well light-emitting diode (MQW-LED), waveguide and InGaN MQW-photodetector on a single chip. The unique light emission property of InGaN MQW-LED makes it feasible to establish multi-dimensional spatial data transmission using visible light. The in-plane light communication system is comprised of InGaN MQW-LED, waveguide and InGaN MQW-photodetector, and the out-of-plane data transmission is realized by detecting the free-space light emission via a commercial photodiode module. Moreover, a full-duplex light communication is experimentally demonstrated at a data transmission rate of 50 Mbps when both InGaN MQW-diodes operate under simultaneous light emission and detection mode. The in-plane superimposed signals are able to be extracted through the self-interference cancellation method, and the out-of-plane superimposed signals are in good agreement with the calculated signals according to the extracted transmitted signals. These results are promising for the development of on-chip InGaN photonic integration for diverse applications.

Stochastic Evolutionary Algorithms for Planning Robot Paths

NASA Technical Reports Server (NTRS)

Fink, Wolfgang; Aghazarian, Hrand; Huntsberger, Terrance; Terrile, Richard

2006-01-01

A computer program implements stochastic evolutionary algorithms for planning and optimizing collision-free paths for robots and their jointed limbs. Stochastic evolutionary algorithms can be made to produce acceptably close approximations to exact, optimal solutions for path-planning problems while often demanding much less computation than do exhaustive-search and deterministic inverse-kinematics algorithms that have been used previously for this purpose. Hence, the present software is better suited for application aboard robots having limited computing capabilities (see figure). The stochastic aspect lies in the use of simulated annealing to (1) prevent trapping of an optimization algorithm in local minima of an energy-like error measure by which the fitness of a trial solution is evaluated while (2) ensuring that the entire multidimensional configuration and parameter space of the path-planning problem is sampled efficiently with respect to both robot joint angles and computation time. Simulated annealing is an established technique for avoiding local minima in multidimensional optimization problems, but has not, until now, been applied to planning collision-free robot paths by use of low-power computers.

Machine Learning of Human Pluripotent Stem Cell-Derived Engineered Cardiac Tissue Contractility for Automated Drug Classification.

PubMed

Lee, Eugene K; Tran, David D; Keung, Wendy; Chan, Patrick; Wong, Gabriel; Chan, Camie W; Costa, Kevin D; Li, Ronald A; Khine, Michelle

2017-11-14

Accurately predicting cardioactive effects of new molecular entities for therapeutics remains a daunting challenge. Immense research effort has been focused toward creating new screening platforms that utilize human pluripotent stem cell (hPSC)-derived cardiomyocytes and three-dimensional engineered cardiac tissue constructs to better recapitulate human heart function and drug responses. As these new platforms become increasingly sophisticated and high throughput, the drug screens result in larger multidimensional datasets. Improved automated analysis methods must therefore be developed in parallel to fully comprehend the cellular response across a multidimensional parameter space. Here, we describe the use of machine learning to comprehensively analyze 17 functional parameters derived from force readouts of hPSC-derived ventricular cardiac tissue strips (hvCTS) electrically paced at a range of frequencies and exposed to a library of compounds. A generated metric is effective for then determining the cardioactivity of a given drug. Furthermore, we demonstrate a classification model that can automatically predict the mechanistic action of an unknown cardioactive drug. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Software Defined Networking (SDN) controlled all optical switching networks with multi-dimensional switching architecture

NASA Astrophysics Data System (ADS)

Zhao, Yongli; Ji, Yuefeng; Zhang, Jie; Li, Hui; Xiong, Qianjin; Qiu, Shaofeng

2014-08-01

Ultrahigh throughout capacity requirement is challenging the current optical switching nodes with the fast development of data center networks. Pbit/s level all optical switching networks need to be deployed soon, which will cause the high complexity of node architecture. How to control the future network and node equipment together will become a new problem. An enhanced Software Defined Networking (eSDN) control architecture is proposed in the paper, which consists of Provider NOX (P-NOX) and Node NOX (N-NOX). With the cooperation of P-NOX and N-NOX, the flexible control of the entire network can be achieved. All optical switching network testbed has been experimentally demonstrated with efficient control of enhanced Software Defined Networking (eSDN). Pbit/s level all optical switching nodes in the testbed are implemented based on multi-dimensional switching architecture, i.e. multi-level and multi-planar. Due to the space and cost limitation, each optical switching node is only equipped with four input line boxes and four output line boxes respectively. Experimental results are given to verify the performance of our proposed control and switching architecture.

Bayesian nonparametric clustering in phylogenetics: modeling antigenic evolution in influenza.

PubMed

Cybis, Gabriela B; Sinsheimer, Janet S; Bedford, Trevor; Rambaut, Andrew; Lemey, Philippe; Suchard, Marc A

2018-01-30

Influenza is responsible for up to 500,000 deaths every year, and antigenic variability represents much of its epidemiological burden. To visualize antigenic differences across many viral strains, antigenic cartography methods use multidimensional scaling on binding assay data to map influenza antigenicity onto a low-dimensional space. Analysis of such assay data ideally leads to natural clustering of influenza strains of similar antigenicity that correlate with sequence evolution. To understand the dynamics of these antigenic groups, we present a framework that jointly models genetic and antigenic evolution by combining multidimensional scaling of binding assay data, Bayesian phylogenetic machinery and nonparametric clustering methods. We propose a phylogenetic Chinese restaurant process that extends the current process to incorporate the phylogenetic dependency structure between strains in the modeling of antigenic clusters. With this method, we are able to use the genetic information to better understand the evolution of antigenicity throughout epidemics, as shown in applications of this model to H1N1 influenza. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Correlative visualization techniques for multidimensional data

NASA Technical Reports Server (NTRS)

Treinish, Lloyd A.; Goettsche, Craig

1989-01-01

Critical to the understanding of data is the ability to provide pictorial or visual representation of those data, particularly in support of correlative data analysis. Despite the advancement of visualization techniques for scientific data over the last several years, there are still significant problems in bringing today's hardware and software technology into the hands of the typical scientist. For example, there are other computer science domains outside of computer graphics that are required to make visualization effective such as data management. Well-defined, flexible mechanisms for data access and management must be combined with rendering algorithms, data transformation, etc. to form a generic visualization pipeline. A generalized approach to data visualization is critical for the correlative analysis of distinct, complex, multidimensional data sets in the space and Earth sciences. Different classes of data representation techniques must be used within such a framework, which can range from simple, static two- and three-dimensional line plots to animation, surface rendering, and volumetric imaging. Static examples of actual data analyses will illustrate the importance of an effective pipeline in data visualization system.

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

Akkelin, S.V.; Sinyukov, Yu.M.

A method allowing analysis of the overpopulation of phase space in heavy ion collisions in a model-independent way is proposed within the hydrodynamic approach. It makes it possible to extract a chemical potential of thermal pions at freeze-out, irrespective of the form of freeze-out (isothermal) hypersurface in Minkowski space and transverse flows on it. The contributions of resonance (with masses up to 2 GeV) decays to spectra, interferometry volumes, and phase-space densities are calculated and discussed in detail. The estimates of average phase-space densities and chemical potentials of thermal pions are obtained for SPS and RHIC energies. They demonstrate thatmore » multibosonic phenomena at those energies might be considered as a correction factor rather than as a significant physical effect. The analysis of the evolution of the pion average phase-space density in chemically frozen hadron systems shows that it is almost constant or slightly increases with time while the particle density and phase-space density at each space point decreases rapidly during the system's expansion. We found that, unlike the particle density, the average phase-space density has no direct link to the freeze-out criterion and final thermodynamic parameters, being connected rather to the initial phase-space density of hadronic matter formed in relativistic nucleus-nucleus collisions.« less

Disentangling the Cosmic Web with Lagrangian Submanifold

NASA Astrophysics Data System (ADS)

Shandarin, Sergei F.; Medvedev, Mikhail V.

2016-10-01

The Cosmic Web is a complicated highly-entangled geometrical object. Remarkably it has formed from practically Gaussian initial conditions, which may be regarded as the simplest departure from exactly uniform universe in purely deterministic mapping. The full complexity of the web is revealed neither in configuration no velocity spaces considered separately. It can be fully appreciated only in six-dimensional (6D) phase space. However, studies of the phase space is complicated by the fact that every projection of it on a three-dimensional (3D) space is multivalued and contained caustics. In addition phase space is not a metric space that complicates studies of geometry. We suggest to use Lagrangian submanifold i.e., x = x(q), where both x and q are 3D vectors instead of the phase space for studies the complexity of cosmic web in cosmological N-body dark matter simulations. Being fully equivalent in dynamical sense to the phase space it has an advantage of being a single valued and also metric space.

The Behavioral Space of Zebrafish Locomotion and Its Neural Network Analog.

PubMed

Girdhar, Kiran; Gruebele, Martin; Chemla, Yann R

2015-01-01

How simple is the underlying control mechanism for the complex locomotion of vertebrates? We explore this question for the swimming behavior of zebrafish larvae. A parameter-independent method, similar to that used in studies of worms and flies, is applied to analyze swimming movies of fish. The motion itself yields a natural set of fish "eigenshapes" as coordinates, rather than the experimenter imposing a choice of coordinates. Three eigenshape coordinates are sufficient to construct a quantitative "postural space" that captures >96% of the observed zebrafish locomotion. Viewed in postural space, swim bouts are manifested as trajectories consisting of cycles of shapes repeated in succession. To classify behavioral patterns quantitatively and to understand behavioral variations among an ensemble of fish, we construct a "behavioral space" using multi-dimensional scaling (MDS). This method turns each cycle of a trajectory into a single point in behavioral space, and clusters points based on behavioral similarity. Clustering analysis reveals three known behavioral patterns-scoots, turns, rests-but shows that these do not represent discrete states, but rather extremes of a continuum. The behavioral space not only classifies fish by their behavior but also distinguishes fish by age. With the insight into fish behavior from postural space and behavioral space, we construct a two-channel neural network model for fish locomotion, which produces strikingly similar postural space and behavioral space dynamics compared to real zebrafish.

The Behavioral Space of Zebrafish Locomotion and Its Neural Network Analog

PubMed Central

Girdhar, Kiran; Gruebele, Martin; Chemla, Yann R.

2015-01-01

How simple is the underlying control mechanism for the complex locomotion of vertebrates? We explore this question for the swimming behavior of zebrafish larvae. A parameter-independent method, similar to that used in studies of worms and flies, is applied to analyze swimming movies of fish. The motion itself yields a natural set of fish "eigenshapes" as coordinates, rather than the experimenter imposing a choice of coordinates. Three eigenshape coordinates are sufficient to construct a quantitative "postural space" that captures >96% of the observed zebrafish locomotion. Viewed in postural space, swim bouts are manifested as trajectories consisting of cycles of shapes repeated in succession. To classify behavioral patterns quantitatively and to understand behavioral variations among an ensemble of fish, we construct a "behavioral space" using multi-dimensional scaling (MDS). This method turns each cycle of a trajectory into a single point in behavioral space, and clusters points based on behavioral similarity. Clustering analysis reveals three known behavioral patterns—scoots, turns, rests—but shows that these do not represent discrete states, but rather extremes of a continuum. The behavioral space not only classifies fish by their behavior but also distinguishes fish by age. With the insight into fish behavior from postural space and behavioral space, we construct a two-channel neural network model for fish locomotion, which produces strikingly similar postural space and behavioral space dynamics compared to real zebrafish. PMID:26132396

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

Multi-dimensional optimization of a terawatt seeded tapered Free Electron Laser with a Multi-Objective Genetic Algorithm

DOE PAGES

Wu, Juhao; Hu, Newman; Setiawan, Hananiel; ...

2016-11-20

There is a great interest in generating high-power hard X-ray Free Electron Laser (FEL) in the terawatt (TW) level that can enable coherent diffraction imaging of complex molecules like proteins and probe fundamental high-field physics. A feasibility study of producing such X-ray pulses was carried out in this paper employing a configuration beginning with a Self-Amplified Spontaneous Emission FEL, followed by a “self-seeding” crystal monochromator generating a fully coherent seed, and finishing with a long tapered undulator where the coherent seed recombines with the electron bunch and is amplified to high power. The undulator tapering profile, the phase advance inmore » the undulator break sections, the quadrupole focusing strength, etc. are parameters to be optimized. A Genetic Algorithm (GA) is adopted for this multi-dimensional optimization. Concrete examples are given for LINAC Coherent Light Source (LCLS) and LCLS-II-type systems. Finally, analytical estimate is also developed to cross check the simulation and optimization results as a quick and complimentary tool.« less

Phase space methods in HMD systems

NASA Astrophysics Data System (ADS)

Babington, James

2017-06-01

We consider using phase space techniques and methods in analysing optical ray propagation in head mounted display systems. Two examples are considered that illustrate the concepts and methods. Firstly, a shark tooth freeform geometry, and secondly, a waveguide geometry that replicates a pupil in one dimension. Classical optics and imaging in particular provide a natural stage to employ phase space techniques, albeit as a constrained system. We consider how phase space provides a global picture of the physical ray trace data. As such, this gives a complete optical world history of all of the rays propagating through the system. Using this data one can look at, for example, how aberrations arise on a surface by surface basis. These can be extracted numerically from phase space diagrams in the example of a freeform imaging prism. For the waveguide geometry, phase space diagrams provide a way of illustrating how replicated pupils behave and what these imply for design considerations such as tolerances.

Heterogeneous Two-Phase Pillars in Epitaxial NiFe 2 O 4 -LaFeO 3 Nanocomposites

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

Comes, Ryan B.; Perea, Daniel E.; Spurgeon, Steven R.

2017-07-10

Self-assembled epitaxial oxide nanocomposites have been explored for a wide range of applications, including multiferroic and magnetoelectric properties, plasmonics, and catalysis. These so-called “vertically aligned nanocomposites” form spontaneously during the deposition process when segregation into two phases is energetically favorable as compared to a solid solution. However, there has been surprisingly little work understanding the driving forces that govern the synthesis of these materials, which can include point defect energetics, surface diffusion, and interfacial energies. To explore these factors, La-Ni-Fe-O films have been synthesized by molecular beam epitaxy and it is shown that these phase segregate into spinel-perovskite nanocomposites. Usingmore » complementary scanning transmission electron microscopy and atom-probe tomography, the elemental composition of each phase is examined and found that Ni ions are exclusively found in the spinel phase. From correlative analysis, a model for the relative favorability of the Ni2+ and Ni3+ valences under the growth conditions is developed. It is shown that multidimensional characterization techniques provide previously unobserved insight into the growth process and complex driving forces for phase segregation.« less

Development of an EORTC quality of life phase III module measuring cancer-related fatigue (EORTC QLQ-FA13).

PubMed

Weis, Joachim; Arraras, Juan Ignacio; Conroy, Thierry; Efficace, Fabio; Fleissner, Claudia; Görög, Attila; Hammerlid, Eva; Holzner, Bernhard; Jones, Louise; Lanceley, Anne; Singer, Susanne; Wirtz, Markus; Flechtner, Henning; Bottomley, Andrew

2013-05-01

European Organisation for Research and Treatment of Cancer (EORTC) has developed a new multidimensional instrument measuring cancer-related fatigue that can be used in conjunction with the quality of life core questionnaire, EORTC QLQ-C30. The paper focuses on the development of the phase III module, collaborating with seven European countries, including a patient sample of 318 patients. The methodology followed the EORTC guidelines for developing phase III modules. Patients were assessed by questionnaires (EORTC QLQ-C30 with the EORTC Fatigue Module FA15) followed by an interview, asking for their opinions on the difficulty in understanding, on annoyance and on intrusiveness. The phase II FA15 was revised on the basis of qualitative analyses (comments of the patients), quantitative results (descriptive statistics) as well as the multi-item response theory analyses. The three dimensions (physical, emotional and cognitive) of the scale could be confirmed. As a result, EORTC QLQ-FA13 is now available as a valid phase III module measuring cancer-related fatigue in clinical trials and will be psychometrically improved in the upcoming phase IV. Copyright © 2012 John Wiley & Sons, Ltd.

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

Optical multidimensional multiple access(O-MDMA): a new concept for free-space laser communication based on photonic mixer devices

NASA Astrophysics Data System (ADS)

Hess, Holger; Albrecht, Martin; Grothof, Markus; Hussmann, Stephan; Schwarte, Rudolf

2004-01-01

Working on optical distance measurement a new optical correlator was developed at the Institute for Data Processing of the University of Siegen in the last years. The so called Photonic Mixer Device (PMD), to be meant originally for laser ranging systems, offers a lot of advantages for wireless optical data communication like high speed spatial light demodulation up to the GHz range and inherent backlight suppression. This contribution describes the application of such PMDs in a free space interconnect based on the principle of Multi Dimensional Multiple Access (MDMA) and the advantages of this new approach, starting from the MDMA principle and followed by the fundamental functionality of PMDs. After that an Optical MDMA (O-MDMA) demonstrator and first measurement results will be presented.

An Integrated Framework for Parameter-based Optimization of Scientific Workflows.

PubMed

Kumar, Vijay S; Sadayappan, P; Mehta, Gaurang; Vahi, Karan; Deelman, Ewa; Ratnakar, Varun; Kim, Jihie; Gil, Yolanda; Hall, Mary; Kurc, Tahsin; Saltz, Joel

2009-01-01

Data analysis processes in scientific applications can be expressed as coarse-grain workflows of complex data processing operations with data flow dependencies between them. Performance optimization of these workflows can be viewed as a search for a set of optimal values in a multi-dimensional parameter space. While some performance parameters such as grouping of workflow components and their mapping to machines do not a ect the accuracy of the output, others may dictate trading the output quality of individual components (and of the whole workflow) for performance. This paper describes an integrated framework which is capable of supporting performance optimizations along multiple dimensions of the parameter space. Using two real-world applications in the spatial data analysis domain, we present an experimental evaluation of the proposed framework.

Free-energy landscape for cage breaking of three hard disks.

PubMed

Hunter, Gary L; Weeks, Eric R

2012-03-01

We investigate cage breaking in dense hard-disk systems using a model of three Brownian disks confined within a circular corral. This system has a six-dimensional configuration space, but can be equivalently thought to explore a symmetric one-dimensional free-energy landscape containing two energy minima separated by an energy barrier. The exact free-energy landscape can be calculated as a function of system size by a direct enumeration of states. Results of simulations show the average time between cage breaking events follows an Arrhenius scaling when the energy barrier is large. We also discuss some of the consequences of using a one-dimensional representation to understand dynamics through a multidimensional space, such as diffusion acquiring spatial dependence and discontinuities in spatial derivatives of free energy.

Minimum Action Path Theory Reveals the Details of Stochastic Transitions Out of Oscillatory States

NASA Astrophysics Data System (ADS)

de la Cruz, Roberto; Perez-Carrasco, Ruben; Guerrero, Pilar; Alarcon, Tomas; Page, Karen M.

2018-03-01

Cell state determination is the outcome of intrinsically stochastic biochemical reactions. Transitions between such states are studied as noise-driven escape problems in the chemical species space. Escape can occur via multiple possible multidimensional paths, with probabilities depending nonlocally on the noise. Here we characterize the escape from an oscillatory biochemical state by minimizing the Freidlin-Wentzell action, deriving from it the stochastic spiral exit path from the limit cycle. We also use the minimized action to infer the escape time probability density function.

Detonation initiation in a model of explosive: Comparative atomistic and hydrodynamics simulations

NASA Astrophysics Data System (ADS)

Murzov, S. A.; Sergeev, O. V.; Dyachkov, S. A.; Egorova, M. S.; Parshikov, A. N.; Zhakhovsky, V. V.

2016-11-01

Here we extend consistent simulations to reactive materials by the example of AB model explosive. The kinetic model of chemical reactions observed in a molecular dynamics (MD) simulation of self-sustained detonation wave can be used in hydrodynamic simulation of detonation initiation. Kinetic coefficients are obtained by minimization of difference between profiles of species calculated from the kinetic model and observed in MD simulations of isochoric thermal decomposition with a help of downhill simplex method combined with random walk in multidimensional space of fitting kinetic model parameters.

The nonconvex multi-dimensional Riemann problem for Hamilton-Jacobi equations

NASA Technical Reports Server (NTRS)

Bardi, Martino; Osher, Stanley

1991-01-01

Simple inequalities are presented for the viscosity solution of a Hamilton-Jacobi equation in N space dimensions when neither the initial data nor the Hamiltonian need be convex (or concave). The initial data are uniformly Lipschitz and can be written as the sum of a convex function in a group of variables and a concave function in the remaining variables, therefore including the nonconvex Riemann problem. The inequalities become equalities wherever a 'maxmin' equals a 'minmax', and thus a representation formula for this problem is obtained, generalizing the classical Hopi formulas.

On the quantum-channel capacity for orbital angular momentum-based free-space optical communications.

PubMed

Zhang, Yequn; Djordjevic, Ivan B; Gao, Xin

2012-08-01

Inspired by recent demonstrations of orbital angular momentum-(OAM)-based single-photon communications, we propose two quantum-channel models: (i) the multidimensional quantum-key distribution model and (ii) the quantum teleportation model. Both models employ operator-sum representation for Kraus operators derived from OAM eigenkets transition probabilities. These models are highly important for future development of quantum-error correction schemes to extend the transmission distance and improve date rates of OAM quantum communications. By using these models, we calculate corresponding quantum-channel capacities in the presence of atmospheric turbulence.

Four-level conservative finite-difference schemes for Boussinesq paradigm equation

NASA Astrophysics Data System (ADS)

Kolkovska, N.

2013-10-01

In this paper a two-parametric family of four level conservative finite difference schemes is constructed for the multidimensional Boussinesq paradigm equation. The schemes are explicit in the sense that no inner iterations are needed for evaluation of the numerical solution. The preservation of the discrete energy with this method is proved. The schemes have been numerically tested on one soliton propagation model and two solitons interaction model. The numerical experiments demonstrate that the proposed family of schemes has second order of convergence in space and time steps in the discrete maximal norm.

Minimum Action Path Theory Reveals the Details of Stochastic Transitions Out of Oscillatory States.

PubMed

de la Cruz, Roberto; Perez-Carrasco, Ruben; Guerrero, Pilar; Alarcon, Tomas; Page, Karen M

2018-03-23

Cell state determination is the outcome of intrinsically stochastic biochemical reactions. Transitions between such states are studied as noise-driven escape problems in the chemical species space. Escape can occur via multiple possible multidimensional paths, with probabilities depending nonlocally on the noise. Here we characterize the escape from an oscillatory biochemical state by minimizing the Freidlin-Wentzell action, deriving from it the stochastic spiral exit path from the limit cycle. We also use the minimized action to infer the escape time probability density function.

Towards a capability approach to child growth: A theoretical framework.

PubMed

Haisma, Hinke; Yousefzadeh, Sepideh; Boele Van Hensbroek, Pieter

2018-04-01

Child malnutrition is an important cause of under-5 mortality and morbidity around the globe. Despite the partial success of (inter)national efforts to reduce child mortality, under-5 mortality rates continue to be high. The multidimensional approaches of the Sustainable Development Goals may suggest new directions for rethinking strategies for reducing child mortality and malnutrition. We propose a theoretical framework for developing a "capability" approach to child growth. The current child growth monitoring practices are based on 2 assumptions: (a) that anthropometric and motor development measures are the appropriate indicators; and (b) that child growth can be assessed using a single universal standard that is applicable around the world. These practices may be further advanced by applying a capability approach to child growth, whereby growth is redefined as the achievement of certain capabilities (of society, parents, and children). This framework is similar to the multidimensional approach to societal development presented in the seminal work of Amartya Sen. To identify the dimensions of healthy child growth, we draw upon theories from the social sciences and evolutionary biology. Conceptually, we consider growth as a plural space and propose assessing growth by means of a child growth matrix in which the context is embedded in the assessment. This approach will better address the diversities and the inequalities in child growth. Such a multidimensional measure will have implications for interventions and policy, including prevention and counselling, and could have an impact on child malnutrition and mortality. © 2017 The Authors. Maternal and Child Nutrition Published by John Wiley & Sons, Ltd.

DataFed: A Federated Data System for Visualization and Analysis of Spatio-Temporal Air Quality Data

NASA Astrophysics Data System (ADS)

Husar, R. B.; Hoijarvi, K.

2017-12-01

DataFed is a distributed web-services-based computing environment for accessing, processing, and visualizing atmospheric data in support of air quality science and management. The flexible, adaptive environment facilitates the access and flow of atmospheric data from provider to users by enabling the creation of user-driven data processing/visualization applications. DataFed `wrapper' components, non-intrusively wrap heterogeneous, distributed datasets for access by standards-based GIS web services. The mediator components (also web services) map the heterogeneous data into a spatio-temporal data model. Chained web services provide homogeneous data views (e.g., geospatial, time views) using a global multi-dimensional data model. In addition to data access and rendering, the data processing component services can be programmed for filtering, aggregation, and fusion of multidimensional data. A complete application software is written in a custom made data flow language. Currently, the federated data pool consists of over 50 datasets originating from globally distributed data providers delivering surface-based air quality measurements, satellite observations, emissions data as well as regional and global-scale air quality models. The web browser-based user interface allows point and click navigation and browsing the XYZT multi-dimensional data space. The key applications of DataFed are for exploring spatial pattern of pollutants, seasonal, weekly, diurnal cycles and frequency distributions for exploratory air quality research. Since 2008, DataFed has been used to support EPA in the implementation of the Exceptional Event Rule. The data system is also used at universities in the US, Europe and Asia.

Knowledge-based nonuniform sampling in multidimensional NMR.

PubMed

Schuyler, Adam D; Maciejewski, Mark W; Arthanari, Haribabu; Hoch, Jeffrey C

2011-07-01

The full resolution afforded by high-field magnets is rarely realized in the indirect dimensions of multidimensional NMR experiments because of the time cost of uniformly sampling to long evolution times. Emerging methods utilizing nonuniform sampling (NUS) enable high resolution along indirect dimensions by sampling long evolution times without sampling at every multiple of the Nyquist sampling interval. While the earliest NUS approaches matched the decay of sampling density to the decay of the signal envelope, recent approaches based on coupled evolution times attempt to optimize sampling by choosing projection angles that increase the likelihood of resolving closely-spaced resonances. These approaches employ knowledge about chemical shifts to predict optimal projection angles, whereas prior applications of tailored sampling employed only knowledge of the decay rate. In this work we adapt the matched filter approach as a general strategy for knowledge-based nonuniform sampling that can exploit prior knowledge about chemical shifts and is not restricted to sampling projections. Based on several measures of performance, we find that exponentially weighted random sampling (envelope matched sampling) performs better than shift-based sampling (beat matched sampling). While shift-based sampling can yield small advantages in sensitivity, the gains are generally outweighed by diminished robustness. Our observation that more robust sampling schemes are only slightly less sensitive than schemes highly optimized using prior knowledge about chemical shifts has broad implications for any multidimensional NMR study employing NUS. The results derived from simulated data are demonstrated with a sample application to PfPMT, the phosphoethanolamine methyltransferase of the human malaria parasite Plasmodium falciparum.

Upscaling the Coupled Water and Heat Transport in the Shallow Subsurface

NASA Astrophysics Data System (ADS)

Sviercoski, R. F.; Efendiev, Y.; Mohanty, B. P.

2018-02-01

Predicting simultaneous movement of liquid water, water vapor, and heat in the shallow subsurface has many practical interests. The demand for multidimensional multiscale models for this region is important given: (a) the critical role that these processes play in the global water and energy balances, (b) that more data from air-borne and space-borne sensors are becoming available for parameterizations of modeling efforts. On the other hand, numerical models that consider spatial variations of the soil properties, termed here as multiscale, are prohibitively expensive. Thus, there is a need for upscaled models that take into consideration these features, and be computationally affordable. In this paper, a multidimensional multiscale model coupling the water flow and heat transfer and its respective upscaled version are proposed. The formulation is novel as it describes the multidimensional and multiscale tensorial versions of the hydraulic conductivity and the vapor diffusivity, taking into account the tortuosity and porosity properties of the medium. It also includes the coupling with the energy balance equation as a boundary describing atmospheric influences at the shallow subsurface. To demonstrate the accuracy of both models, comparisons were made between simulation and field experiments for soil moisture and temperature at 2, 7, and 12 cm deep, during 11 days. The root-mean-square errors showed that the upscaled version of the system captured the multiscale features with similar accuracy. Given the good matching between simulated and field data for near-surface soil temperature, the results suggest that it can be regarded as a 1-D variable.

Husimi function and phase-space analysis of bilayer quantum Hall systems at ν = 2/λ

NASA Astrophysics Data System (ADS)

Calixto, M.; Peón-Nieto, C.

2018-05-01

We propose localization measures in phase space of the ground state of bilayer quantum Hall systems at fractional filling factors , to characterize the three quantum phases (shortly denoted by spin, canted and ppin) for arbitrary -isospin λ. We use a coherent state (Bargmann) representation of quantum states, as holomorphic functions in the 8-dimensional Grassmannian phase-space (a higher-dimensional generalization of the Haldane’s 2-dimensional sphere ). We quantify the localization (inverse volume) of the ground state wave function in phase-space throughout the phase diagram (i.e. as a function of Zeeman, tunneling, layer distance, etc, control parameters) with the Husimi function second moment, a kind of inverse participation ratio that behaves as an order parameter. Then we visualize the different ground state structure in phase space of the three quantum phases, the canted phase displaying a much higher delocalization (a Schrödinger cat structure) than the spin and ppin phases, where the ground state is highly coherent. We find a good agreement between analytic (variational) and numeric diagonalization results.

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.

On the importance of an accurate representation of the initial state of the system in classical dynamics simulations

NASA Astrophysics Data System (ADS)

García-Vela, A.

2000-05-01

A definition of a quantum-type phase-space distribution is proposed in order to represent the initial state of the system in a classical dynamics simulation. The central idea is to define an initial quantum phase-space state of the system as the direct product of the coordinate and momentum representations of the quantum initial state. The phase-space distribution is then obtained as the square modulus of this phase-space state. The resulting phase-space distribution closely resembles the quantum nature of the system initial state. The initial conditions are sampled with the distribution, using a grid technique in phase space. With this type of sampling the distribution of initial conditions reproduces more faithfully the shape of the original phase-space distribution. The method is applied to generate initial conditions describing the three-dimensional state of the Ar-HCl cluster prepared by ultraviolet excitation. The photodissociation dynamics is simulated by classical trajectories, and the results are compared with those of a wave packet calculation. The classical and quantum descriptions are found in good agreement for those dynamical events less subject to quantum effects. The classical result fails to reproduce the quantum mechanical one for the more strongly quantum features of the dynamics. The properties and applicability of the phase-space distribution and the sampling technique proposed are discussed.

An approach to the development of numerical algorithms for first order linear hyperbolic systems in multiple space dimensions: The constant coefficient case

NASA Technical Reports Server (NTRS)

Goodrich, John W.

1995-01-01

Two methods for developing high order single step explicit algorithms on symmetric stencils with data on only one time level are presented. Examples are given for the convection and linearized Euler equations with up to the eighth order accuracy in both space and time in one space dimension, and up to the sixth in two space dimensions. The method of characteristics is generalized to nondiagonalizable hyperbolic systems by using exact local polynominal solutions of the system, and the resulting exact propagator methods automatically incorporate the correct multidimensional wave propagation dynamics. Multivariate Taylor or Cauchy-Kowaleskaya expansions are also used to develop algorithms. Both of these methods can be applied to obtain algorithms of arbitrarily high order for hyperbolic systems in multiple space dimensions. Cross derivatives are included in the local approximations used to develop the algorithms in this paper in order to obtain high order accuracy, and improved isotropy and stability. Efficiency in meeting global error bounds is an important criterion for evaluating algorithms, and the higher order algorithms are shown to be up to several orders of magnitude more efficient even though they are more complex. Stable high order boundary conditions for the linearized Euler equations are developed in one space dimension, and demonstrated in two space dimensions.

Euclidean chemical spaces from molecular fingerprints: Hamming distance and Hempel's ravens.

PubMed

Martin, Eric; Cao, Eddie

2015-05-01

Molecules are often characterized by sparse binary fingerprints, where 1s represent the presence of substructures and 0s represent their absence. Fingerprints are especially useful for similarity calculations, such as database searching or clustering, generally measuring similarity as the Tanimoto coefficient. In other cases, such as visualization, design of experiments, or latent variable regression, a low-dimensional Euclidian "chemical space" is more useful, where proximity between points reflects chemical similarity. A temptation is to apply principal components analysis (PCA) directly to these fingerprints to obtain a low dimensional continuous chemical space. However, Gower has shown that distances from PCA on bit vectors are proportional to the square root of Hamming distance. Unlike Tanimoto similarity, Hamming similarity (HS) gives equal weight to shared 0s as to shared 1s, that is, HS gives as much weight to substructures that neither molecule contains, as to substructures which both molecules contain. Illustrative examples show that proximity in the corresponding chemical space reflects mainly similar size and complexity rather than shared chemical substructures. These spaces are ill-suited for visualizing and optimizing coverage of chemical space, or as latent variables for regression. A more suitable alternative is shown to be Multi-dimensional scaling on the Tanimoto distance matrix, which produces a space where proximity does reflect structural similarity.

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

Why do Ladybugs Smell Bad? In-vivo Quantification of Odorous Insect Kairomones with SPME and Multidimensional GC-MS-Olfactometry

NASA Astrophysics Data System (ADS)

Cai, Lingshuang; Koziel, Jacek A.; O'Neal, Matthew E.

2009-05-01

Winemakers, small fruit growers, and homeowners are concerned with noxious compounds released by multicolored Asian ladybird beetles (Harmonia axyridis, Coleoptera: Coccinellidae). New method based on headspace solid phase microextraction (HS-SPME) coupled with multidimensional gas chromatography mass spectrometry—olfactometry (MDGC-MS-O) system was developed for extraction, isolation and simultaneous identification of compounds responsible for the characteristic odor of live H. axyridis. Four methoxypyrazines (MPs) were identified in headspace volatiles of live H. axyridis as those responsible for the characteristic odor: 2, 5-dimethy1-3-methoxypyrazine (DMMP), 2-isopropy1-3-methoxypyrazine (IPMP), 2-sec-buty1-3-methoxypyrazine (SBMP), and 2-isobuty1-3-methoxypyrazine (IBMP). To the best of our knowledge this is the first report of H. axyridis releasing DMMP and the first report of this compound being a component of the H. axyridis characteristic odor. Quantification of three MPs (IPMP, SBMP and IBMP) emitted from live H. axyridis were performed using external calibration with HS-SPME and direct injections. A linear relationship (R2>0.9958 for all 3 MPs) between MS response and concentration of standard was observed over a concentration range from 0.1 ng L-1 to 0.05 μg L-1 for HS-SPME-GC-MS. The method detection limits (MDL) based on multidimensional GC-MS approach for three MPs were estimated to be between 0.020 ng L-1. to 0.022 ng L-1. This methodology is applicable for in vivo determination of odor-causing chemicals associated with emissions of volatiles from insects.

An integrated quality by design and mixture-process variable approach in the development of a capillary electrophoresis method for the analysis of almotriptan and its impurities.

PubMed

Orlandini, S; Pasquini, B; Stocchero, M; Pinzauti, S; Furlanetto, S

2014-04-25

The development of a capillary electrophoresis (CE) method for the assay of almotriptan (ALM) and its main impurities using an integrated Quality by Design and mixture-process variable (MPV) approach is described. A scouting phase was initially carried out by evaluating different CE operative modes, including the addition of pseudostationary phases and additives to the background electrolyte, in order to approach the analytical target profile. This step made it possible to select normal polarity microemulsion electrokinetic chromatography (MEEKC) as operative mode, which allowed a good selectivity to be achieved in a low analysis time. On the basis of a general Ishikawa diagram for MEEKC methods, a screening asymmetric matrix was applied in order to screen the effects of the process variables (PVs) voltage, temperature, buffer concentration and buffer pH, on critical quality attributes (CQAs), represented by critical separation values and analysis time. A response surface study was then carried out considering all the critical process parameters, including both the PVs and the mixture components (MCs) of the microemulsion (borate buffer, n-heptane as oil, sodium dodecyl sulphate/n-butanol as surfactant/cosurfactant). The values of PVs and MCs were simultaneously changed in a MPV study, making it possible to find significant interaction effects. The design space (DS) was defined as the multidimensional combination of PVs and MCs where the probability for the different considered CQAs to be acceptable was higher than a quality level π=90%. DS was identified by risk of failure maps, which were drawn on the basis of Monte-Carlo simulations, and verification points spanning the design space were tested. Robustness testing of the method, performed by a D-optimal design, and system suitability criteria allowed a control strategy to be designed. The optimized method was validated following ICH Guideline Q2(R1) and was applied to a real sample of ALM coated tablets. Copyright © 2014 Elsevier B.V. All rights reserved.