NALDB: nucleic acid ligand database for small molecules targeting nucleic acid

PubMed Central

Kumar Mishra, Subodh; Kumar, Amit

2016-01-01

Nucleic acid ligand database (NALDB) is a unique database that provides detailed information about the experimental data of small molecules that were reported to target several types of nucleic acid structures. NALDB is the first ligand database that contains ligand information for all type of nucleic acid. NALDB contains more than 3500 ligand entries with detailed pharmacokinetic and pharmacodynamic information such as target name, target sequence, ligand 2D/3D structure, SMILES, molecular formula, molecular weight, net-formal charge, AlogP, number of rings, number of hydrogen bond donor and acceptor, potential energy along with their Ki, Kd, IC50 values. All these details at single platform would be helpful for the development and betterment of novel ligands targeting nucleic acids that could serve as a potential target in different diseases including cancers and neurological disorders. With maximum 255 conformers for each ligand entry, our database is a multi-conformer database and can facilitate the virtual screening process. NALDB provides powerful web-based search tools that make database searching efficient and simplified using option for text as well as for structure query. NALDB also provides multi-dimensional advanced search tool which can screen the database molecules on the basis of molecular properties of ligand provided by database users. A 3D structure visualization tool has also been included for 3D structure representation of ligands. NALDB offers an inclusive pharmacological information and the structurally flexible set of small molecules with their three-dimensional conformers that can accelerate the virtual screening and other modeling processes and eventually complement the nucleic acid-based drug discovery research. NALDB can be routinely updated and freely available on bsbe.iiti.ac.in/bsbe/naldb/HOME.php. Database URL: http://bsbe.iiti.ac.in/bsbe/naldb/HOME.php PMID:26896846

Structure Size Enhanced Histogram

NASA Astrophysics Data System (ADS)

Wesarg, Stefan; Kirschner, Matthias

Direct volume visualization requires the definition of transfer functions (TFs) for the assignment of opacity and color. Multi-dimensional TFs are based on at least two image properties, and are specified by means of 2D histograms. In this work we propose a new type of a 2D histogram which combines gray value with information about the size of the structures. This structure size enhanced (SSE) histogram is an intuitive approach for representing anatomical features. Clinicians — the users we are focusing on — are much more familiar with selecting features by their size than by their gradient magnitude value. As a proof of concept, we employ the SSE histogram for the definition of two-dimensional TFs for the visualization of 3D MRI and CT image data.

Studies for the 3-Dimensional Structure, Composition, and Dynamic of Io's Atmosphere

NASA Technical Reports Server (NTRS)

Smyth, William H.

2001-01-01

Research work is discussed for the following: (1) the exploration of new H and Cl chemistry in Io's atmosphere using the already developed two-dimensional multi-species hydrodynamic model of Wong and Smyth; and (2) for the development of a new three-dimensional multi-species hydrodynamic model for Io's atmosphere.

Failure analysis of fuel cell electrodes using three-dimensional multi-length scale X-ray computed tomography

NASA Astrophysics Data System (ADS)

Pokhrel, A.; El Hannach, M.; Orfino, F. P.; Dutta, M.; Kjeang, E.

2016-10-01

X-ray computed tomography (XCT), a non-destructive technique, is proposed for three-dimensional, multi-length scale characterization of complex failure modes in fuel cell electrodes. Comparative tomography data sets are acquired for a conditioned beginning of life (BOL) and a degraded end of life (EOL) membrane electrode assembly subjected to cathode degradation by voltage cycling. Micro length scale analysis shows a five-fold increase in crack size and 57% thickness reduction in the EOL cathode catalyst layer, indicating widespread action of carbon corrosion. Complementary nano length scale analysis shows a significant reduction in porosity, increased pore size, and dramatically reduced effective diffusivity within the remaining porous structure of the catalyst layer at EOL. Collapsing of the structure is evident from the combination of thinning and reduced porosity, as uniquely determined by the multi-length scale approach. Additionally, a novel image processing based technique developed for nano scale segregation of pore, ionomer, and Pt/C dominated voxels shows an increase in ionomer volume fraction, Pt/C agglomerates, and severe carbon corrosion at the catalyst layer/membrane interface at EOL. In summary, XCT based multi-length scale analysis enables detailed information needed for comprehensive understanding of the complex failure modes observed in fuel cell electrodes.

Multi-dimensional knowledge translation: enabling health informatics capacity audits using patient journey models.

PubMed

Catley, Christina; McGregor, Carolyn; Percival, Jennifer; Curry, Joanne; James, Andrew

2008-01-01

This paper presents a multi-dimensional approach to knowledge translation, enabling results obtained from a survey evaluating the uptake of Information Technology within Neonatal Intensive Care Units to be translated into knowledge, in the form of health informatics capacity audits. Survey data, having multiple roles, patient care scenarios, levels, and hospitals, is translated using a structured data modeling approach, into patient journey models. The data model is defined such that users can develop queries to generate patient journey models based on a pre-defined Patient Journey Model architecture (PaJMa). PaJMa models are then analyzed to build capacity audits. Capacity audits offer a sophisticated view of health informatics usage, providing not only details of what IT solutions a hospital utilizes, but also answering the questions: when, how and why, by determining when the IT solutions are integrated into the patient journey, how they support the patient information flow, and why they improve the patient journey.

Multi-Hamiltonian structure of the Born-Infeld equation

NASA Astrophysics Data System (ADS)

Arik, Metin; Neyzi, Fahrünisa; Nutku, Yavuz; Olver, Peter J.; Verosky, John M.

1989-06-01

The multi-Hamiltonian structure, conservation laws, and higher order symmetries for the Born-Infeld equation are exhibited. A new transformation of the Born-Infeld equation to the equations of a Chaplygin gas is presented and explored. The Born-Infeld equation is distinguished among two-dimensional hyperbolic systems by its wealth of such multi-Hamiltonian structures.

Two-dimensional fourier transform spectrometer

DOEpatents

DeFlores, Lauren; Tokmakoff, Andrei

2016-10-25

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

Two-dimensional fourier transform spectrometer

DOEpatents

DeFlores, Lauren; Tokmakoff, Andrei

2013-09-03

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

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.

Three-dimensional distribution of polymorphs and magnesium in a calcified underwater attachment system by diffraction tomography

PubMed Central

Leemreize, Hanna; Almer, Jonathan D.; Stock, Stuart R.; Birkedal, Henrik

2013-01-01

Biological materials display complicated three-dimensional hierarchical structures. Determining these structures is essential in understanding the link between material design and properties. Herein, we show how diffraction tomography can be used to determine the relative placement of the calcium carbonate polymorphs calcite and aragonite in the highly mineralized holdfast system of the bivalve Anomia simplex. In addition to high fidelity and non-destructive mapping of polymorphs, we use detailed analysis of X-ray diffraction peak positions in reconstructed powder diffraction data to determine the local degree of Mg substitution in the calcite phase. These data show how diffraction tomography can provide detailed multi-length scale information on complex materials in general and of biomineralized tissues in particular. PMID:23804437

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

NALDB: nucleic acid ligand database for small molecules targeting nucleic acid.

PubMed

Kumar Mishra, Subodh; Kumar, Amit

2016-01-01

Nucleic acid ligand database (NALDB) is a unique database that provides detailed information about the experimental data of small molecules that were reported to target several types of nucleic acid structures. NALDB is the first ligand database that contains ligand information for all type of nucleic acid. NALDB contains more than 3500 ligand entries with detailed pharmacokinetic and pharmacodynamic information such as target name, target sequence, ligand 2D/3D structure, SMILES, molecular formula, molecular weight, net-formal charge, AlogP, number of rings, number of hydrogen bond donor and acceptor, potential energy along with their Ki, Kd, IC50 values. All these details at single platform would be helpful for the development and betterment of novel ligands targeting nucleic acids that could serve as a potential target in different diseases including cancers and neurological disorders. With maximum 255 conformers for each ligand entry, our database is a multi-conformer database and can facilitate the virtual screening process. NALDB provides powerful web-based search tools that make database searching efficient and simplified using option for text as well as for structure query. NALDB also provides multi-dimensional advanced search tool which can screen the database molecules on the basis of molecular properties of ligand provided by database users. A 3D structure visualization tool has also been included for 3D structure representation of ligands. NALDB offers an inclusive pharmacological information and the structurally flexible set of small molecules with their three-dimensional conformers that can accelerate the virtual screening and other modeling processes and eventually complement the nucleic acid-based drug discovery research. NALDB can be routinely updated and freely available on bsbe.iiti.ac.in/bsbe/naldb/HOME.php. Database URL: http://bsbe.iiti.ac.in/bsbe/naldb/HOME.php. © The Author(s) 2016. Published by Oxford University Press.

Multiscale modeling of three-dimensional genome

NASA Astrophysics Data System (ADS)

Zhang, Bin; Wolynes, Peter

The genome, the blueprint of life, contains nearly all the information needed to build and maintain an entire organism. A comprehensive understanding of the genome is of paramount interest to human health and will advance progress in many areas, including life sciences, medicine, and biotechnology. The overarching goal of my research is to understand the structure-dynamics-function relationships of the human genome. In this talk, I will be presenting our efforts in moving towards that goal, with a particular emphasis on studying the three-dimensional organization, the structure of the genome with multi-scale approaches. Specifically, I will discuss the reconstruction of genome structures at both interphase and metaphase by making use of data from chromosome conformation capture experiments. Computationally modeling of chromatin fiber at atomistic level from first principles will also be presented as our effort for studying the genome structure from bottom up.

Westward tilt of low-latitude plasma blobs as observed by the Swarm constellation

NASA Astrophysics Data System (ADS)

Park, Jaeheung; Lühr, Hermann; Michaelis, Ingo; Stolle, Claudia; Rauberg, Jan; Buchert, Stephan; Gill, Reine; Merayo, Jose M. G.; Brauer, Peter

2015-04-01

In this study we investigate the three-dimensional structure of low-latitude plasma blobs using multi-instrument and multisatellite observations of the Swarm constellation. During the early commissioning phase the Swarm satellites were flying at the same altitude with zonal separation of about 0.5∘ in geographic longitude. Electron density data from the three satellites constrain the blob morphology projected onto the horizontal plane. Magnetic field deflections around blobs, which originate from field-aligned currents near the irregularity boundaries, constrain the blob structure projected onto the plane perpendicular to the ambient magnetic field. As the two constraints are given for two noncoplanar surfaces, we can get information on the three-dimensional structure of blobs. Combined observation results suggest that blobs are contained within tilted shells of geomagnetic flux tubes, which are similar to the shell structure of equatorial plasma bubbles suggested by previous studies.

Förster resonance energy transfer and protein-induced fluorescence enhancement as synergetic multi-scale molecular rulers

NASA Astrophysics Data System (ADS)

Ploetz, Evelyn; Lerner, Eitan; Husada, Florence; Roelfs, Martin; Chung, Sangyoon; Hohlbein, Johannes; Weiss, Shimon; Cordes, Thorben

2016-09-01

Advanced microscopy methods allow obtaining information on (dynamic) conformational changes in biomolecules via measuring a single molecular distance in the structure. It is, however, extremely challenging to capture the full depth of a three-dimensional biochemical state, binding-related structural changes or conformational cross-talk in multi-protein complexes using one-dimensional assays. In this paper we address this fundamental problem by extending the standard molecular ruler based on Förster resonance energy transfer (FRET) into a two-dimensional assay via its combination with protein-induced fluorescence enhancement (PIFE). We show that donor brightness (via PIFE) and energy transfer efficiency (via FRET) can simultaneously report on e.g., the conformational state of double stranded DNA (dsDNA) following its interaction with unlabelled proteins (BamHI, EcoRV, and T7 DNA polymerase gp5/trx). The PIFE-FRET assay uses established labelling protocols and single molecule fluorescence detection schemes (alternating-laser excitation, ALEX). Besides quantitative studies of PIFE and FRET ruler characteristics, we outline possible applications of ALEX-based PIFE-FRET for single-molecule studies with diffusing and immobilized molecules. Finally, we study transcription initiation and scrunching of E. coli RNA-polymerase with PIFE-FRET and provide direct evidence for the physical presence and vicinity of the polymerase that causes structural changes and scrunching of the transcriptional DNA bubble.

Application Perspective of 2D+SCALE Dimension

NASA Astrophysics Data System (ADS)

Karim, H.; Rahman, A. Abdul

2016-09-01

Different applications or users need different abstraction of spatial models, dimensionalities and specification of their datasets due to variations of required analysis and output. Various approaches, data models and data structures are now available to support most current application models in Geographic Information System (GIS). One of the focuses trend in GIS multi-dimensional research community is the implementation of scale dimension with spatial datasets to suit various scale application needs. In this paper, 2D spatial datasets that been scaled up as the third dimension are addressed as 2D+scale (or 3D-scale) dimension. Nowadays, various data structures, data models, approaches, schemas, and formats have been proposed as the best approaches to support variety of applications and dimensionality in 3D topology. However, only a few of them considers the element of scale as their targeted dimension. As the scale dimension is concerned, the implementation approach can be either multi-scale or vario-scale (with any available data structures and formats) depending on application requirements (topology, semantic and function). This paper attempts to discuss on the current and new potential applications which positively could be integrated upon 3D-scale dimension approach. The previous and current works on scale dimension as well as the requirements to be preserved for any given applications, implementation issues and future potential applications forms the major discussion of this paper.

Förster resonance energy transfer and protein-induced fluorescence enhancement as synergetic multi-scale molecular rulers

PubMed Central

Ploetz, Evelyn; Lerner, Eitan; Husada, Florence; Roelfs, Martin; Chung, SangYoon; Hohlbein, Johannes; Weiss, Shimon; Cordes, Thorben

2016-01-01

Advanced microscopy methods allow obtaining information on (dynamic) conformational changes in biomolecules via measuring a single molecular distance in the structure. It is, however, extremely challenging to capture the full depth of a three-dimensional biochemical state, binding-related structural changes or conformational cross-talk in multi-protein complexes using one-dimensional assays. In this paper we address this fundamental problem by extending the standard molecular ruler based on Förster resonance energy transfer (FRET) into a two-dimensional assay via its combination with protein-induced fluorescence enhancement (PIFE). We show that donor brightness (via PIFE) and energy transfer efficiency (via FRET) can simultaneously report on e.g., the conformational state of double stranded DNA (dsDNA) following its interaction with unlabelled proteins (BamHI, EcoRV, and T7 DNA polymerase gp5/trx). The PIFE-FRET assay uses established labelling protocols and single molecule fluorescence detection schemes (alternating-laser excitation, ALEX). Besides quantitative studies of PIFE and FRET ruler characteristics, we outline possible applications of ALEX-based PIFE-FRET for single-molecule studies with diffusing and immobilized molecules. Finally, we study transcription initiation and scrunching of E. coli RNA-polymerase with PIFE-FRET and provide direct evidence for the physical presence and vicinity of the polymerase that causes structural changes and scrunching of the transcriptional DNA bubble. PMID:27641327

Non-classical photon correlation in a two-dimensional photonic lattice.

PubMed

Gao, Jun; Qiao, Lu-Feng; Lin, Xiao-Feng; Jiao, Zhi-Qiang; Feng, Zhen; Zhou, Zheng; Gao, Zhen-Wei; Xu, Xiao-Yun; Chen, Yuan; Tang, Hao; Jin, Xian-Min

2016-06-13

Quantum interference and quantum correlation, as two main features of quantum optics, play an essential role in quantum information applications, such as multi-particle quantum walk and boson sampling. While many experimental demonstrations have been done in one-dimensional waveguide arrays, it remains unexplored in higher dimensions due to tight requirement of manipulating and detecting photons in large-scale. Here, we experimentally observe non-classical correlation of two identical photons in a fully coupled two-dimensional structure, i.e. photonic lattice manufactured by three-dimensional femtosecond laser writing. Photon interference consists of 36 Hong-Ou-Mandel interference and 9 bunching. The overlap between measured and simulated distribution is up to 0.890 ± 0.001. Clear photon correlation is observed in the two-dimensional photonic lattice. Combining with controllably engineered disorder, our results open new perspectives towards large-scale implementation of quantum simulation on integrated photonic chips.

Combustion Dynamics in Multi-Nozzle Combustors Operating on High-Hydrogen Fuels

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

Santavicca, Dom; Lieuwen, Tim

Actual gas turbine combustors for power generation applications employ multi-nozzle combustor configurations. Researchers at Penn State and Georgia Tech have extended previous work on the flame response in single-nozzle combustors to the more realistic case of multi-nozzle combustors. Research at Georgia Tech has shown that asymmetry of both the flow field and the acoustic forcing can have a significant effect on flame response and that such behavior is important in multi-flame configurations. As a result, the structure of the flame and its response to forcing is three-dimensional. Research at Penn State has led to the development of a three-dimensional chemiluminescencemore » flame imaging technique that can be used to characterize the unforced (steady) and forced (unsteady) flame structure of multi-nozzle combustors. Important aspects of the flame response in multi-nozzle combustors which are being studied include flame-flame and flame-wall interactions. Research at Penn State using the recently developed three-dimensional flame imaging technique has shown that spatial variations in local flame confinement must be accounted for to accurately predict global flame response in a multi-nozzle can combustor.« less

Neurovision processor for designing intelligent sensors

NASA Astrophysics Data System (ADS)

Gupta, Madan M.; Knopf, George K.

1992-03-01

A programmable multi-task neuro-vision processor, called the Positive-Negative (PN) neural processor, is proposed as a plausible hardware mechanism for constructing robust multi-task vision sensors. The computational operations performed by the PN neural processor are loosely based on the neural activity fields exhibited by certain nervous tissue layers situated in the brain. The neuro-vision processor can be programmed to generate diverse dynamic behavior that may be used for spatio-temporal stabilization (STS), short-term visual memory (STVM), spatio-temporal filtering (STF) and pulse frequency modulation (PFM). A multi- functional vision sensor that performs a variety of information processing operations on time- varying two-dimensional sensory images can be constructed from a parallel and hierarchical structure of numerous individually programmed PN neural processors.

TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions

PubMed Central

2017-01-01

Although deep learning approaches have had tremendous success in image, video and audio processing, computer vision, and speech recognition, their applications to three-dimensional (3D) biomolecular structural data sets have been hindered by the geometric and biological complexity. To address this problem we introduce the element-specific persistent homology (ESPH) method. ESPH represents 3D complex geometry by one-dimensional (1D) topological invariants and retains important biological information via a multichannel image-like representation. This representation reveals hidden structure-function relationships in biomolecules. We further integrate ESPH and deep convolutional neural networks to construct a multichannel topological neural network (TopologyNet) for the predictions of protein-ligand binding affinities and protein stability changes upon mutation. To overcome the deep learning limitations from small and noisy training sets, we propose a multi-task multichannel topological convolutional neural network (MM-TCNN). We demonstrate that TopologyNet outperforms the latest methods in the prediction of protein-ligand binding affinities, mutation induced globular protein folding free energy changes, and mutation induced membrane protein folding free energy changes. Availability: weilab.math.msu.edu/TDL/ PMID:28749969

Developing a Hypothetical Multi-Dimensional Learning Progression for the Nature of Matter

ERIC Educational Resources Information Center

Stevens, Shawn Y.; Delgado, Cesar; Krajcik, Joseph S.

2010-01-01

We describe efforts toward the development of a hypothetical learning progression (HLP) for the growth of grade 7-14 students' models of the structure, behavior and properties of matter, as it relates to nanoscale science and engineering (NSE). This multi-dimensional HLP, based on empirical research and standards documents, describes how students…

Practical Methods for Including Torsional Anharmonicity in Thermochemical Calculations on Complex Molecules: The Internal-Coordinate Multi-Structural Approximation

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

Zheng, J.; Yu, T.; Papajak, E.

2011-01-01

Many methods for correcting harmonic partition functions for the presence of torsional motions employ some form of one-dimensional torsional treatment to replace the harmonic contribution of a specific normal mode. However, torsions are often strongly coupled to other degrees of freedom, especially other torsions and low-frequency bending motions, and this coupling can make assigning torsions to specific normal modes problematic. Here, we present a new class of methods, called multi-structural (MS) methods, that circumvents the need for such assignments by instead adjusting the harmonic results by torsional correction factors that are determined using internal coordinates. We present three versions ofmore » the MS method: (i) MS-AS based on including all structures (AS), i.e., all conformers generated by internal rotations; (ii) MS-ASCB based on all structures augmented with explicit conformational barrier (CB) information, i.e., including explicit calculations of all barrier heights for internal-rotation barriers between the conformers; and (iii) MS-RS based on including all conformers generated from a reference structure (RS) by independent torsions. In the MS-AS scheme, one has two options for obtaining the local periodicity parameters, one based on consideration of the nearly separable limit and one based on strongly coupled torsions. The latter involves assigning the local periodicities on the basis of Voronoi volumes. The methods are illustrated with calculations for ethanol, 1-butanol, and 1-pentyl radical as well as two one-dimensional torsional potentials. The MS-AS method is particularly interesting because it does not require any information about conformational barriers or about the paths that connect the various structures.« less

Practical methods for including torsional anharmonicity in thermochemical calculations on complex molecules: the internal-coordinate multi-structural approximation.

PubMed

Zheng, Jingjing; Yu, Tao; Papajak, Ewa; Alecu, I M; Mielke, Steven L; Truhlar, Donald G

2011-06-21

Many methods for correcting harmonic partition functions for the presence of torsional motions employ some form of one-dimensional torsional treatment to replace the harmonic contribution of a specific normal mode. However, torsions are often strongly coupled to other degrees of freedom, especially other torsions and low-frequency bending motions, and this coupling can make assigning torsions to specific normal modes problematic. Here, we present a new class of methods, called multi-structural (MS) methods, that circumvents the need for such assignments by instead adjusting the harmonic results by torsional correction factors that are determined using internal coordinates. We present three versions of the MS method: (i) MS-AS based on including all structures (AS), i.e., all conformers generated by internal rotations; (ii) MS-ASCB based on all structures augmented with explicit conformational barrier (CB) information, i.e., including explicit calculations of all barrier heights for internal-rotation barriers between the conformers; and (iii) MS-RS based on including all conformers generated from a reference structure (RS) by independent torsions. In the MS-AS scheme, one has two options for obtaining the local periodicity parameters, one based on consideration of the nearly separable limit and one based on strongly coupled torsions. The latter involves assigning the local periodicities on the basis of Voronoi volumes. The methods are illustrated with calculations for ethanol, 1-butanol, and 1-pentyl radical as well as two one-dimensional torsional potentials. The MS-AS method is particularly interesting because it does not require any information about conformational barriers or about the paths that connect the various structures.

Human development VIII: a theory of "deep" quantum chemistry and cell consciousness: quantum chemistry controls genes and biochemistry to give cells and higher organisms consciousness and complex behavior.

PubMed

Ventegodt, Søren; Hermansen, Tyge Dahl; Flensborg-Madsen, Trine; Nielsen, Maj Lyck; Merrick, Joav

2006-11-14

Deep quantum chemistry is a theory of deeply structured quantum fields carrying the biological information of the cell, making it able to remember, intend, represent the inner and outer world for comparison, understand what it "sees", and make choices on its structure, form, behavior and division. We suggest that deep quantum chemistry gives the cell consciousness and all the qualities and abilities related to consciousness. We use geometric symbolism, which is a pre-mathematical and philosophical approach to problems that cannot yet be handled mathematically. Using Occam's razor we have started with the simplest model that works; we presume this to be a many-dimensional, spiral fractal. We suggest that all the electrons of the large biological molecules' orbitals make one huge "cell-orbital", which is structured according to the spiral fractal nature of quantum fields. Consciousness of single cells, multi cellular structures as e.g. organs, multi-cellular organisms and multi-individual colonies (like ants) and human societies can thus be explained by deep quantum chemistry. When biochemical activity is strictly controlled by the quantum-mechanical super-orbital of the cell, this orbital can deliver energetic quanta as biological information, distributed through many fractal levels of the cell to guide form and behavior of an individual single or a multi-cellular organism. The top level of information is the consciousness of the cell or organism, which controls all the biochemical processes. By this speculative work inspired by Penrose and Hameroff we hope to inspire other researchers to formulate more strict and mathematically correct hypothesis on the complex and coherence nature of matter, life and consciousness.

Human Development VIII: A Theory of “Deep” Quantum Chemistry and Cell Consciousness: Quantum Chemistry Controls Genes and Biochemistry to Give Cells and Higher Organisms Consciousness and Complex Behavior

PubMed Central

Ventegodt, Søren; Hermansen, Tyge Dahl; Flensborg-Madsen, Trine; Nielsen, Maj Lyck; Merrick, Joav

2006-01-01

Deep quantum chemistry is a theory of deeply structured quantum fields carrying the biological information of the cell, making it able to remember, intend, represent the inner and outer world for comparison, understand what it “sees”, and make choices on its structure, form, behavior and division. We suggest that deep quantum chemistry gives the cell consciousness and all the qualities and abilities related to consciousness. We use geometric symbolism, which is a pre-mathematical and philosophical approach to problems that cannot yet be handled mathematically. Using Occams razor we have started with the simplest model that works; we presume this to be a many-dimensional, spiral fractal. We suggest that all the electrons of the large biological molecules orbitals make one huge “cell-orbital”, which is structured according to the spiral fractal nature of quantum fields. Consciousness of single cells, multi cellular structures as e.g. organs, multi-cellular organisms and multi-individual colonies (like ants) and human societies can thus be explained by deep quantum chemistry. When biochemical activity is strictly controlled by the quantum-mechanical super-orbital of the cell, this orbital can deliver energetic quanta as biological information, distributed through many fractal levels of the cell to guide form and behavior of an individual single or a multi-cellular organism. The top level of information is the consciousness of the cell or organism, which controls all the biochemical processes. By this speculative work inspired by Penrose and Hameroff we hope to inspire other researchers to formulate more strict and mathematically correct hypothesis on the complex and coherence nature of matter, life and consciousness. PMID:17115084

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

PubMed Central

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

2016-01-01

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

Method and structure for skewed block-cyclic distribution of lower-dimensional data arrays in higher-dimensional processor grids

DOEpatents

Chatterjee, Siddhartha [Yorktown Heights, NY; Gunnels, John A [Brewster, NY

2011-11-08

A method and structure of distributing elements of an array of data in a computer memory to a specific processor of a multi-dimensional mesh of parallel processors includes designating a distribution of elements of at least a portion of the array to be executed by specific processors in the multi-dimensional mesh of parallel processors. The pattern of the designating includes a cyclical repetitive pattern of the parallel processor mesh, as modified to have a skew in at least one dimension so that both a row of data in the array and a column of data in the array map to respective contiguous groupings of the processors such that a dimension of the contiguous groupings is greater than one.

ASTROP2 Users Manual: A Program for Aeroelastic Stability Analysis of Propfans

NASA Technical Reports Server (NTRS)

Reddy, T. S. R.; Lucero, John M.

1996-01-01

This manual describes the input data required for using the second version of the ASTROP2 (Aeroelastic STability and Response Of Propulsion systems - 2 dimensional analysis) computer code. In ASTROP2, version 2.0, the program is divided into two modules: 2DSTRIP, which calculates the structural dynamic information; and 2DASTROP, which calculates the unsteady aerodynamic force coefficients from which the aeroelastic stability can be determined. In the original version of ASTROP2, these two aspects were performed in a single program. The improvements to version 2.0 include an option to account for counter rotation, improved numerical integration, accommodation for non-uniform inflow distribution, and an iterative scheme to flutter frequency convergence. ASTROP2 can be used for flutter analysis of multi-bladed structures such as those found in compressors, turbines, counter rotating propellers or propfans. The analysis combines a two-dimensional, unsteady cascade aerodynamics model and a three dimensional, normal mode structural model using strip theory. The flutter analysis is formulated in the frequency domain resulting in an eigenvalue determinant. The flutter frequency and damping can be inferred from the eigenvalues.

Strong efficiency improvement in dye-sensitized solar cells by novel multi-dimensional TiO2 photoelectrode

NASA Astrophysics Data System (ADS)

Zhao, Fengyang; Ma, Rong; Jiang, Yongjian

2018-03-01

Titanium dioxide (TiO2) based dye-sensitized solar cells (DSSCs) often exhibit superior power conversion performance. Here we report a DSSC with novel hierarchical TiO2 composite structure (TCS) composed of anatase TiO2 micro-spheres and rutile TiO2 nanobelt framework by hydrothermal approach for high-performance. As photoanode, the TCS based DSSC shows a strong efficiency enhancement by 58% compared with Degussa TiO2 (P25)-DSSC (4.33%). The excellent performance is mainly attribute to its special multi-dimensional structures of TiO2: much active sites of 0D nanoparticle with exposed excellent {001} facet, special electronic transmission channel of 1D nanobelt, good dye adsorption capacity of 2D nanosheet and high light scattering ability of 3D micro-spheres. The novel multi-dimensional TCS materials will open up a new avenue to the electronic devices fields.

Characterization and classification of vegetation canopy structure and distribution within the Great Smoky Mountains National Park using LiDAR

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

Kumar, Jitendra; HargroveJr., William Walter; Norman, Steven P

Vegetation canopy structure is a critically important habit characteristic for many threatened and endangered birds and other animal species, and it is key information needed by forest and wildlife managers for monitoring and managing forest resources, conservation planning and fostering biodiversity. Advances in Light Detection and Ranging (LiDAR) technologies have enabled remote sensing-based studies of vegetation canopies by capturing three-dimensional structures, yielding information not available in two-dimensional images of the landscape pro- vided by traditional multi-spectral remote sensing platforms. However, the large volume data sets produced by airborne LiDAR instruments pose a significant computational challenge, requiring algorithms to identify andmore » analyze patterns of interest buried within LiDAR point clouds in a computationally efficient manner, utilizing state-of-art computing infrastructure. We developed and applied a computationally efficient approach to analyze a large volume of LiDAR data and to characterize and map the vegetation canopy structures for 139,859 hectares (540 sq. miles) in the Great Smoky Mountains National Park. This study helps improve our understanding of the distribution of vegetation and animal habitats in this extremely diverse ecosystem.« less

A novel framework for change detection in bi-temporal polarimetric SAR images

NASA Astrophysics Data System (ADS)

Pirrone, Davide; Bovolo, Francesca; Bruzzone, Lorenzo

2016-10-01

Last years have seen relevant increase of polarimetric Synthetic Aperture Radar (SAR) data availability, thanks to satellite sensors like Sentinel-1 or ALOS-2 PALSAR-2. The augmented information lying in the additional polarimetric channels represents a possibility for better discriminate different classes of changes in change detection (CD) applications. This work aims at proposing a framework for CD in multi-temporal multi-polarization SAR data. The framework includes both a tool for an effective visual representation of the change information and a method for extracting the multiple-change information. Both components are designed to effectively handle the multi-dimensionality of polarimetric data. In the novel representation, multi-temporal intensity SAR data are employed to compute a polarimetric log-ratio. The multitemporal information of the polarimetric log-ratio image is represented in a multi-dimensional features space, where changes are highlighted in terms of magnitude and direction. This representation is employed to design a novel unsupervised multi-class CD approach. This approach considers a sequential two-step analysis of the magnitude and the direction information for separating non-changed and changed samples. The proposed approach has been validated on a pair of Sentinel-1 data acquired before and after the flood in Tamil-Nadu in 2015. Preliminary results demonstrate that the representation tool is effective and that the use of polarimetric SAR data is promising in multi-class change detection applications.

Medical image registration based on normalized multidimensional mutual information

NASA Astrophysics Data System (ADS)

Li, Qi; Ji, Hongbing; Tong, Ming

2009-10-01

Registration of medical images is an essential research topic in medical image processing and applications, and especially a preliminary and key step for multimodality image fusion. This paper offers a solution to medical image registration based on normalized multi-dimensional mutual information. Firstly, affine transformation with translational and rotational parameters is applied to the floating image. Then ordinal features are extracted by ordinal filters with different orientations to represent spatial information in medical images. Integrating ordinal features with pixel intensities, the normalized multi-dimensional mutual information is defined as similarity criterion to register multimodality images. Finally the immune algorithm is used to search registration parameters. The experimental results demonstrate the effectiveness of the proposed registration scheme.

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.

A novel approach to internal crown characterization for coniferous tree species classification

NASA Astrophysics Data System (ADS)

Harikumar, A.; Bovolo, F.; Bruzzone, L.

2016-10-01

The knowledge about individual trees in forest is highly beneficial in forest management. High density small foot- print multi-return airborne Light Detection and Ranging (LiDAR) data can provide a very accurate information about the structural properties of individual trees in forests. Every tree species has a unique set of crown structural characteristics that can be used for tree species classification. In this paper, we use both the internal and external crown structural information of a conifer tree crown, derived from a high density small foot-print multi-return LiDAR data acquisition for species classification. Considering the fact that branches are the major building blocks of a conifer tree crown, we obtain the internal crown structural information using a branch level analysis. The structure of each conifer branch is represented using clusters in the LiDAR point cloud. We propose the joint use of the k-means clustering and geometric shape fitting, on the LiDAR data projected onto a novel 3-dimensional space, to identify branch clusters. After mapping the identified clusters back to the original space, six internal geometric features are estimated using a branch-level analysis. The external crown characteristics are modeled by using six least correlated features based on cone fitting and convex hull. Species classification is performed using a sparse Support Vector Machines (sparse SVM) classifier.

Multi-view non-negative tensor factorization as relation learning in healthcare data.

PubMed

Hang Wu; Wang, May D

2016-08-01

Discovering patterns in co-occurrences data between objects and groups of concepts is a useful task in many domains, such as healthcare data analysis, information retrieval, and recommender systems. These relational representations come from objects' behaviors in different views, posing a challenging task of integrating information from these views to uncover the shared latent structures. The problem is further complicated by the high dimension of data and the large ratio of missing data. We propose a new paradigm of learning semantic relations using tensor factorization, by jointly factorizing multi-view tensors and searching for a consistent underlying semantic space across each views. We formulate the idea as an optimization problem and propose efficient optimization algorithms, with a special treatment of missing data as well as high-dimensional data. Experiments results show the potential and effectiveness of our algorithms.

Applications to car bodies - Generalized layout design of three-dimensional shells

NASA Technical Reports Server (NTRS)

Fukushima, Junichi; Suzuki, Katsuyuki; Kikuchi, Noboru

1993-01-01

We shall describe applications of the homogenization method, formulated in Part 1, to design layout of car bodies represented by three-dimensional shell structures based on a multi-loading optimization.

Ultra-wideband three-dimensional optoacoustic tomography.

PubMed

Gateau, Jérôme; Chekkoury, Andrei; Ntziachristos, Vasilis

2013-11-15

Broadband optoacoustic waves generated by biological tissues excited with nanosecond laser pulses carry information corresponding to a wide range of geometrical scales. Typically, the frequency content present in the signals generated during optoacoustic imaging is much larger compared to the frequency band captured by common ultrasonic detectors, the latter typically acting as bandpass filters. To image optical absorption within structures ranging from entire organs to microvasculature in three dimensions, we implemented optoacoustic tomography with two ultrasound linear arrays featuring a center frequency of 6 and 24 MHz, respectively. In the present work, we show that complementary information on anatomical features could be retrieved and provide a better understanding on the localization of structures in the general anatomy by analyzing multi-bandwidth datasets acquired on a freshly excised kidney.

Defect-Repairable Latent Feature Extraction of Driving Behavior via a Deep Sparse Autoencoder

PubMed Central

Taniguchi, Tadahiro; Takenaka, Kazuhito; Bando, Takashi

2018-01-01

Data representing driving behavior, as measured by various sensors installed in a vehicle, are collected as multi-dimensional sensor time-series data. These data often include redundant information, e.g., both the speed of wheels and the engine speed represent the velocity of the vehicle. Redundant information can be expected to complicate the data analysis, e.g., more factors need to be analyzed; even varying the levels of redundancy can influence the results of the analysis. We assume that the measured multi-dimensional sensor time-series data of driving behavior are generated from low-dimensional data shared by the many types of one-dimensional data of which multi-dimensional time-series data are composed. Meanwhile, sensor time-series data may be defective because of sensor failure. Therefore, another important function is to reduce the negative effect of defective data when extracting low-dimensional time-series data. This study proposes a defect-repairable feature extraction method based on a deep sparse autoencoder (DSAE) to extract low-dimensional time-series data. In the experiments, we show that DSAE provides high-performance latent feature extraction for driving behavior, even for defective sensor time-series data. In addition, we show that the negative effect of defects on the driving behavior segmentation task could be reduced using the latent features extracted by DSAE. PMID:29462931

RNA FRABASE 2.0: an advanced web-accessible database with the capacity to search the three-dimensional fragments within RNA structures

PubMed Central

2010-01-01

Background Recent discoveries concerning novel functions of RNA, such as RNA interference, have contributed towards the growing importance of the field. In this respect, a deeper knowledge of complex three-dimensional RNA structures is essential to understand their new biological functions. A number of bioinformatic tools have been proposed to explore two major structural databases (PDB, NDB) in order to analyze various aspects of RNA tertiary structures. One of these tools is RNA FRABASE 1.0, the first web-accessible database with an engine for automatic search of 3D fragments within PDB-derived RNA structures. This search is based upon the user-defined RNA secondary structure pattern. In this paper, we present and discuss RNA FRABASE 2.0. This second version of the system represents a major extension of this tool in terms of providing new data and a wide spectrum of novel functionalities. An intuitionally operated web server platform enables very fast user-tailored search of three-dimensional RNA fragments, their multi-parameter conformational analysis and visualization. Description RNA FRABASE 2.0 has stored information on 1565 PDB-deposited RNA structures, including all NMR models. The RNA FRABASE 2.0 search engine algorithms operate on the database of the RNA sequences and the new library of RNA secondary structures, coded in the dot-bracket format extended to hold multi-stranded structures and to cover residues whose coordinates are missing in the PDB files. The library of RNA secondary structures (and their graphics) is made available. A high level of efficiency of the 3D search has been achieved by introducing novel tools to formulate advanced searching patterns and to screen highly populated tertiary structure elements. RNA FRABASE 2.0 also stores data and conformational parameters in order to provide "on the spot" structural filters to explore the three-dimensional RNA structures. An instant visualization of the 3D RNA structures is provided. RNA FRABASE 2.0 is freely available at http://rnafrabase.cs.put.poznan.pl. Conclusions RNA FRABASE 2.0 provides a novel database and powerful search engine which is equipped with new data and functionalities that are unavailable elsewhere. Our intention is that this advanced version of the RNA FRABASE will be of interest to all researchers working in the RNA field. PMID:20459631

RNA FRABASE 2.0: an advanced web-accessible database with the capacity to search the three-dimensional fragments within RNA structures.

PubMed

Popenda, Mariusz; Szachniuk, Marta; Blazewicz, Marek; Wasik, Szymon; Burke, Edmund K; Blazewicz, Jacek; Adamiak, Ryszard W

2010-05-06

Recent discoveries concerning novel functions of RNA, such as RNA interference, have contributed towards the growing importance of the field. In this respect, a deeper knowledge of complex three-dimensional RNA structures is essential to understand their new biological functions. A number of bioinformatic tools have been proposed to explore two major structural databases (PDB, NDB) in order to analyze various aspects of RNA tertiary structures. One of these tools is RNA FRABASE 1.0, the first web-accessible database with an engine for automatic search of 3D fragments within PDB-derived RNA structures. This search is based upon the user-defined RNA secondary structure pattern. In this paper, we present and discuss RNA FRABASE 2.0. This second version of the system represents a major extension of this tool in terms of providing new data and a wide spectrum of novel functionalities. An intuitionally operated web server platform enables very fast user-tailored search of three-dimensional RNA fragments, their multi-parameter conformational analysis and visualization. RNA FRABASE 2.0 has stored information on 1565 PDB-deposited RNA structures, including all NMR models. The RNA FRABASE 2.0 search engine algorithms operate on the database of the RNA sequences and the new library of RNA secondary structures, coded in the dot-bracket format extended to hold multi-stranded structures and to cover residues whose coordinates are missing in the PDB files. The library of RNA secondary structures (and their graphics) is made available. A high level of efficiency of the 3D search has been achieved by introducing novel tools to formulate advanced searching patterns and to screen highly populated tertiary structure elements. RNA FRABASE 2.0 also stores data and conformational parameters in order to provide "on the spot" structural filters to explore the three-dimensional RNA structures. An instant visualization of the 3D RNA structures is provided. RNA FRABASE 2.0 is freely available at http://rnafrabase.cs.put.poznan.pl. RNA FRABASE 2.0 provides a novel database and powerful search engine which is equipped with new data and functionalities that are unavailable elsewhere. Our intention is that this advanced version of the RNA FRABASE will be of interest to all researchers working in the RNA field.

Inertial objects in complex flows

NASA Astrophysics Data System (ADS)

Syed, Rayhan; Ho, George; Cavas, Samuel; Bao, Jialun; Yecko, Philip

2017-11-01

Chaotic Advection and Finite Time Lyapunov Exponents both describe stirring and transport in complex and time-dependent flows, but FTLE analysis has been largely limited to either purely kinematic flow models or high Reynolds number flow field data. The neglect of dynamic effects in FTLE and Lagrangian Coherent Structure studies has stymied detailed information about the role of pressure, Coriolis effects and object inertia. We present results of laboratory and numerical experiments on time-dependent and multi-gyre Stokes flows. In the lab, a time-dependent effectively two-dimensional low Re flow is used to distinguish transport properties of passive tracer from those of small paramagnetic spheres. Companion results of FTLE calculations for inertial particles in a time-dependent multi-gyre flow are presented, illustrating the critical roles of density, Stokes number and Coriolis forces on their transport. Results of Direct Numerical Simulations of fully resolved inertial objects (spheroids) immersed in a three dimensional (ABC) flow show the role of shape and finite size in inertial transport at small finite Re. We acknowledge support of NSF DMS-1418956.

Ultra-high aggregate bandwidth two-dimensional multiple-wavelength diode laser arrays

NASA Astrophysics Data System (ADS)

Chang-Hasnain, Connie

1994-04-01

Two-dimensional (2D) multi-wavelength vertical cavity surface emitting laser (VCSEL) arrays is promising for ultrahigh aggregate capacity optical networks. A 2D VCSEL array emitting 140 distinct wavelengths was reported by implementing a spatially graded layer in the VCSEL structure, which in turn creates a wavelength spread. In this program, we concentrated on novel epitaxial growth techniques to make reproducible and repeatable multi-wavelength VCSEL arrays.

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.

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

PubMed

Chen Peng; Ao Li

2017-01-01

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

Electrical transport via variable range hopping in an individual multi-wall carbon nanotube

NASA Astrophysics Data System (ADS)

Husain Khan, Zishan; Husain, M.; Perng, T. P.; Salah, Numan; Habib, Sami

2008-11-01

E-beam lithography is used to make four leads on an individual multi-wall carbon nanotube for carrying out electrical transport measurements. Temperature dependence of conductance of an individual multi-wall carbon nanotube (MWNT) is studied over a temperature range of (297 4.8 K). The results indicate that the conduction is governed by variable range hopping (VRH) for the entire temperature range (297 4.8 K). This VRH mechanism changes from three dimensions (3D) to two dimensions (2D) as we go down to 70 K. Three-dimensional variable range hopping (3D VRH) is responsible for conduction in the temperature range (297 70 K), which changes to two-dimensional VRH for much lower temperatures (70 4.8 K). For 3D VRH, various Mott parameters such as density of states, hopping distance and hopping energy have been calculated. The 2D VRH mechanism has been applied for the temperature range (70 4.8 K) and, with the help of this model, the parameters such as localization length and hopping distance are calculated. All these parameters give interesting information about this complex structure, which may be useful for many applications.

Geospatial Information from Satellite Imagery for Geovisualisation of Smart Cities in India

NASA Astrophysics Data System (ADS)

Mohan, M.

2016-06-01

In the recent past, there have been large emphasis on extraction of geospatial information from satellite imagery. The Geospatial information are being processed through geospatial technologies which are playing important roles in developing of smart cities, particularly in developing countries of the world like India. The study is based on the latest geospatial satellite imagery available for the multi-date, multi-stage, multi-sensor, and multi-resolution. In addition to this, the latest geospatial technologies have been used for digital image processing of remote sensing satellite imagery and the latest geographic information systems as 3-D GeoVisualisation, geospatial digital mapping and geospatial analysis for developing of smart cities in India. The Geospatial information obtained from RS and GPS systems have complex structure involving space, time and presentation. Such information helps in 3-Dimensional digital modelling for smart cities which involves of spatial and non-spatial information integration for geographic visualisation of smart cites in context to the real world. In other words, the geospatial database provides platform for the information visualisation which is also known as geovisualisation. So, as a result there have been an increasing research interest which are being directed to geospatial analysis, digital mapping, geovisualisation, monitoring and developing of smart cities using geospatial technologies. However, the present research has made an attempt for development of cities in real world scenario particulary to help local, regional and state level planners and policy makers to better understand and address issues attributed to cities using the geospatial information from satellite imagery for geovisualisation of Smart Cities in emerging and developing country, India.

Multi-dimensional construction of a novel active yolk@conductive shell nanofiber web as a self-standing anode for high-performance lithium-ion batteries

NASA Astrophysics Data System (ADS)

Liu, Hao; Chen, Luyi; Liang, Yeru; Fu, Ruowen; Wu, Dingcai

2015-11-01

A novel active yolk@conductive shell nanofiber web with a unique synergistic advantage of various hierarchical nanodimensional objects including the 0D monodisperse SiO2 yolks, the 1D continuous carbon shell and the 3D interconnected non-woven fabric web has been developed by an innovative multi-dimensional construction method, and thus demonstrates excellent electrochemical properties as a self-standing LIB anode.A novel active yolk@conductive shell nanofiber web with a unique synergistic advantage of various hierarchical nanodimensional objects including the 0D monodisperse SiO2 yolks, the 1D continuous carbon shell and the 3D interconnected non-woven fabric web has been developed by an innovative multi-dimensional construction method, and thus demonstrates excellent electrochemical properties as a self-standing LIB anode. Electronic supplementary information (ESI) available: Experimental details and additional information about material characterization. See DOI: 10.1039/c5nr06531c

Big Data Analytics for Scanning Transmission Electron Microscopy Ptychography

NASA Astrophysics Data System (ADS)

Jesse, S.; Chi, M.; Belianinov, A.; Beekman, C.; Kalinin, S. V.; Borisevich, A. Y.; Lupini, A. R.

2016-05-01

Electron microscopy is undergoing a transition; from the model of producing only a few micrographs, through the current state where many images and spectra can be digitally recorded, to a new mode where very large volumes of data (movies, ptychographic and multi-dimensional series) can be rapidly obtained. Here, we discuss the application of so-called “big-data” methods to high dimensional microscopy data, using unsupervised multivariate statistical techniques, in order to explore salient image features in a specific example of BiFeO3 domains. Remarkably, k-means clustering reveals domain differentiation despite the fact that the algorithm is purely statistical in nature and does not require any prior information regarding the material, any coexisting phases, or any differentiating structures. While this is a somewhat trivial case, this example signifies the extraction of useful physical and structural information without any prior bias regarding the sample or the instrumental modality. Further interpretation of these types of results may still require human intervention. However, the open nature of this algorithm and its wide availability, enable broad collaborations and exploratory work necessary to enable efficient data analysis in electron microscopy.

Copula based flexible modeling of associations between clustered event times.

PubMed

Geerdens, Candida; Claeskens, Gerda; Janssen, Paul

2016-07-01

Multivariate survival data are characterized by the presence of correlation between event times within the same cluster. First, we build multi-dimensional copulas with flexible and possibly symmetric dependence structures for such data. In particular, clustered right-censored survival data are modeled using mixtures of max-infinitely divisible bivariate copulas. Second, these copulas are fit by a likelihood approach where the vast amount of copula derivatives present in the likelihood is approximated by finite differences. Third, we formulate conditions for clustered right-censored survival data under which an information criterion for model selection is either weakly consistent or consistent. Several of the familiar selection criteria are included. A set of four-dimensional data on time-to-mastitis is used to demonstrate the developed methodology.

The 'cube' meta-model for the information system of large health sector organizations--a (platform neutral) mapping tool to integrate information system development with changing business functions and organizational development.

PubMed

Balkányi, László

2002-01-01

To develop information systems (IS) in the changing environment of the health sector, a simple but throughout model, avoiding the techno-jargon of informatics, might be useful for the top management. A platform neutral, extensible, transparent conceptual model should be established. Limitations of current methods lead to a simple, but comprehensive mapping, in the form of a three-dimensional cube. The three 'orthogonal' views are (a) organization functionality, (b) organizational structures and (c) information technology. Each of the cube-sides is described according to its nature. This approach enables to define any kind of an IS component as a certain point/layer/domain of the cube and enables also the management to label all IS components independently form any supplier(s) and/or any specific platform. The model handles changes in organization structure, business functionality and the serving info-system independently form each other. Practical application extends to (a) planning complex, new ISs, (b) guiding development of multi-vendor, multi-site ISs, (c) supporting large-scale public procurement procedures and the contracting, implementation phase by establishing a platform neutral reference, (d) keeping an exhaustive inventory of an existing large-scale system, that handles non-tangible aspects of the IS.

Enhanced multi-protocol analysis via intelligent supervised embedding (EMPrAvISE): detecting prostate cancer on multi-parametric MRI

NASA Astrophysics Data System (ADS)

Viswanath, Satish; Bloch, B. Nicholas; Chappelow, Jonathan; Patel, Pratik; Rofsky, Neil; Lenkinski, Robert; Genega, Elizabeth; Madabhushi, Anant

2011-03-01

Currently, there is significant interest in developing methods for quantitative integration of multi-parametric (structural, functional) imaging data with the objective of building automated meta-classifiers to improve disease detection, diagnosis, and prognosis. Such techniques are required to address the differences in dimensionalities and scales of individual protocols, while deriving an integrated multi-parametric data representation which best captures all disease-pertinent information available. In this paper, we present a scheme called Enhanced Multi-Protocol Analysis via Intelligent Supervised Embedding (EMPrAvISE); a powerful, generalizable framework applicable to a variety of domains for multi-parametric data representation and fusion. Our scheme utilizes an ensemble of embeddings (via dimensionality reduction, DR); thereby exploiting the variance amongst multiple uncorrelated embeddings in a manner similar to ensemble classifier schemes (e.g. Bagging, Boosting). We apply this framework to the problem of prostate cancer (CaP) detection on 12 3 Tesla pre-operative in vivo multi-parametric (T2-weighted, Dynamic Contrast Enhanced, and Diffusion-weighted) magnetic resonance imaging (MRI) studies, in turn comprising a total of 39 2D planar MR images. We first align the different imaging protocols via automated image registration, followed by quantification of image attributes from individual protocols. Multiple embeddings are generated from the resultant high-dimensional feature space which are then combined intelligently to yield a single stable solution. Our scheme is employed in conjunction with graph embedding (for DR) and probabilistic boosting trees (PBTs) to detect CaP on multi-parametric MRI. Finally, a probabilistic pairwise Markov Random Field algorithm is used to apply spatial constraints to the result of the PBT classifier, yielding a per-voxel classification of CaP presence. Per-voxel evaluation of detection results against ground truth for CaP extent on MRI (obtained by spatially registering pre-operative MRI with available whole-mount histological specimens) reveals that EMPrAvISE yields a statistically significant improvement (AUC=0.77) over classifiers constructed from individual protocols (AUC=0.62, 0.62, 0.65, for T2w, DCE, DWI respectively) as well as one trained using multi-parametric feature concatenation (AUC=0.67).

Life Origination Hydrate Theory (LOH-Theory) and Mitosis and Replication Hydrate Theory (MRH-Theory): three-dimensional PC validation

NASA Astrophysics Data System (ADS)

Kadyshevich, E. A.; Dzyabchenko, A. V.; Ostrovskii, V. E.

2014-04-01

Size compatibility of the CH4-hydrate structure II and multi-component DNA fragments is confirmed by three-dimensional simulation; it is validation of the Life Origination Hydrate Theory (LOH-Theory).

Optimal multi-community network modularity for information diffusion

NASA Astrophysics Data System (ADS)

Wu, Jiaocan; Du, Ruping; Zheng, Yingying; Liu, Dong

2016-02-01

Studies demonstrate that community structure plays an important role in information spreading recently. In this paper, we investigate the impact of multi-community structure on information diffusion with linear threshold model. We utilize extended GN network that contains four communities and analyze dynamic behaviors of information that spreads on it. And we discover the optimal multi-community network modularity for information diffusion based on the social reinforcement. Results show that, within the appropriate range, multi-community structure will facilitate information diffusion instead of hindering it, which accords with the results derived from two-community network.

Feedback-Based, System-Level Properties of Vertebrate-Microbial Interactions

PubMed Central

Rivas, Ariel L.; Jankowski, Mark D.; Piccinini, Renata; Leitner, Gabriel; Schwarz, Daniel; Anderson, Kevin L.; Fair, Jeanne M.; Hoogesteijn, Almira L.; Wolter, Wilfried; Chaffer, Marcelo; Blum, Shlomo; Were, Tom; Konah, Stephen N.; Kempaiah, Prakash; Ong’echa, John M.; Diesterbeck, Ulrike S.; Pilla, Rachel; Czerny, Claus-Peter; Hittner, James B.; Hyman, James M.; Perkins, Douglas J.

2013-01-01

Background Improved characterization of infectious disease dynamics is required. To that end, three-dimensional (3D) data analysis of feedback-like processes may be considered. Methods To detect infectious disease data patterns, a systems biology (SB) and evolutionary biology (EB) approach was evaluated, which utilizes leukocyte data structures designed to diminish data variability and enhance discrimination. Using data collected from one avian and two mammalian (human and bovine) species infected with viral, parasite, or bacterial agents (both sensitive and resistant to antimicrobials), four data structures were explored: (i) counts or percentages of a single leukocyte type, such as lymphocytes, neutrophils, or macrophages (the classic approach), and three levels of the SB/EB approach, which assessed (ii) 2D, (iii) 3D, and (iv) multi-dimensional (rotating 3D) host-microbial interactions. Results In all studies, no classic data structure discriminated disease-positive (D+, or observations in which a microbe was isolated) from disease-negative (D–, or microbial-negative) groups: D+ and D– data distributions overlapped. In contrast, multi-dimensional analysis of indicators designed to possess desirable features, such as a single line of observations, displayed a continuous, circular data structure, whose abrupt inflections facilitated partitioning into subsets statistically significantly different from one another. In all studies, the 3D, SB/EB approach distinguished three (steady, positive, and negative) feedback phases, in which D– data characterized the steady state phase, and D+ data were found in the positive and negative phases. In humans, spatial patterns revealed false-negative observations and three malaria-positive data classes. In both humans and bovines, methicillin-resistant Staphylococcus aureus (MRSA) infections were discriminated from non-MRSA infections. Conclusions More information can be extracted, from the same data, provided that data are structured, their 3D relationships are considered, and well-conserved (feedback-like) functions are estimated. Patterns emerging from such structures may distinguish well-conserved from recently developed host-microbial interactions. Applications include diagnosis, error detection, and modeling. PMID:23437039

Feedback-based, system-level properties of vertebrate-microbial interactions.

PubMed

Rivas, Ariel L; Jankowski, Mark D; Piccinini, Renata; Leitner, Gabriel; Schwarz, Daniel; Anderson, Kevin L; Fair, Jeanne M; Hoogesteijn, Almira L; Wolter, Wilfried; Chaffer, Marcelo; Blum, Shlomo; Were, Tom; Konah, Stephen N; Kempaiah, Prakash; Ong'echa, John M; Diesterbeck, Ulrike S; Pilla, Rachel; Czerny, Claus-Peter; Hittner, James B; Hyman, James M; Perkins, Douglas J

2013-01-01

Improved characterization of infectious disease dynamics is required. To that end, three-dimensional (3D) data analysis of feedback-like processes may be considered. To detect infectious disease data patterns, a systems biology (SB) and evolutionary biology (EB) approach was evaluated, which utilizes leukocyte data structures designed to diminish data variability and enhance discrimination. Using data collected from one avian and two mammalian (human and bovine) species infected with viral, parasite, or bacterial agents (both sensitive and resistant to antimicrobials), four data structures were explored: (i) counts or percentages of a single leukocyte type, such as lymphocytes, neutrophils, or macrophages (the classic approach), and three levels of the SB/EB approach, which assessed (ii) 2D, (iii) 3D, and (iv) multi-dimensional (rotating 3D) host-microbial interactions. In all studies, no classic data structure discriminated disease-positive (D+, or observations in which a microbe was isolated) from disease-negative (D-, or microbial-negative) groups: D+ and D- data distributions overlapped. In contrast, multi-dimensional analysis of indicators designed to possess desirable features, such as a single line of observations, displayed a continuous, circular data structure, whose abrupt inflections facilitated partitioning into subsets statistically significantly different from one another. In all studies, the 3D, SB/EB approach distinguished three (steady, positive, and negative) feedback phases, in which D- data characterized the steady state phase, and D+ data were found in the positive and negative phases. In humans, spatial patterns revealed false-negative observations and three malaria-positive data classes. In both humans and bovines, methicillin-resistant Staphylococcus aureus (MRSA) infections were discriminated from non-MRSA infections. More information can be extracted, from the same data, provided that data are structured, their 3D relationships are considered, and well-conserved (feedback-like) functions are estimated. Patterns emerging from such structures may distinguish well-conserved from recently developed host-microbial interactions. Applications include diagnosis, error detection, and modeling.

Assessment of Computer and Information Literacy in ICILS 2013: Do Different Item Types Measure the Same Construct?

ERIC Educational Resources Information Center

Ihme, Jan Marten; Senkbeil, Martin; Goldhammer, Frank; Gerick, Julia

2017-01-01

The combination of different item formats is found quite often in large scale assessments, and analyses on the dimensionality often indicate multi-dimensionality of tests regarding the task format. In ICILS 2013, three different item types (information-based response tasks, simulation tasks, and authoring tasks) were used to measure computer and…

Mechanical exfoliation of two-dimensional materials

NASA Astrophysics Data System (ADS)

Gao, Enlai; Lin, Shao-Zhen; Qin, Zhao; Buehler, Markus J.; Feng, Xi-Qiao; Xu, Zhiping

2018-06-01

Two-dimensional materials such as graphene and transition metal dichalcogenides have been identified and drawn much attention over the last few years for their unique structural and electronic properties. However, their rise begins only after these materials are successfully isolated from their layered assemblies or adhesive substrates into individual monolayers. Mechanical exfoliation and transfer are the most successful techniques to obtain high-quality single- or few-layer nanocrystals from their native multi-layer structures or their substrate for growth, which involves interfacial peeling and intralayer tearing processes that are controlled by material properties, geometry and the kinetics of exfoliation. This procedure is rationalized in this work through theoretical analysis and atomistic simulations. We propose a criterion to assess the feasibility for the exfoliation of two-dimensional sheets from an adhesive substrate without fracturing itself, and explore the effects of material and interface properties, as well as the geometrical, kinetic factors on the peeling behaviors and the torn morphology. This multi-scale approach elucidates the microscopic mechanism of the mechanical processes, offering predictive models and tools for the design of experimental procedures to obtain single- or few-layer two-dimensional materials and structures.

Examining the relationships between resources and online health information seeking among patients with chronic diseases and healthy people.

PubMed

Oh, Young Sam; Cho, Youngmin

2015-01-01

The Internet is increasingly used as an important source of health and medical-related information for people with chronic diseases. It is recognized that online health information seeking (OHIS) is influenced by individuals' multi-dimensional factors, such as demographics, socio-economic factors, perceptions of the Internet, and health conditions. This study applies the conservation of resource theory to examine relationships between various multi-dimensional factors, daily challenges, and OHIS depending on individuals' health conditions. The data used in this study was taken from the U.S. Health Tracking Survey (2012). In this study, Internet users aged 18 and older were classified into patients (N = 518) and healthy people (N = 677) based on their health status related to chronic diseases. Multiple regression analysis was used to examine the relationships between multi-dimensional factors (resources), self-rated health, and OHIS. Patients' various resources (e.g., age, income, education, having a smartphone, and health tracking) significantly predicted their self-rated health and OHIS; in addition, self-rated health significantly mediated the relationships between focal resources and OHIS. However, the mediating effects of self-rated health were not found in healthy people.

Two-Dimensional Signal Processing, Optical Information Storage and Processing, and Electromagnetic Measurements

DTIC Science & Technology

1994-05-16

analysis of anisotropic grating diffraction, perfor- mance analysis of Givens rotation integrated optical interdigitated-electrode cross- channel Bragg...11. T. R. Gardos and R. M. Mersereau, "FIR filtering on a lattice with periodically deleted samples," Proc. 1991 IEEE Int. Conf. on Acoustics...pp. vol. 1, pp. 301-311, July 1992. 23. T. R. Gardos , K. Nayebi, and R. M. Mersereau, "Time domain analysis of multi- dimensional multi-rate filter

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…

Detection of Rossby Waves in Multi-Parameters in Multi-Mission Satellite Observations and HYCOM Simulations in the Indian Ocean

NASA Technical Reports Server (NTRS)

Subrahmanyam, Bulusu; Heffner, David M.; Cromwell, David; Shriver, Jay F.

2009-01-01

Rossby waves are difficult to detect with in situ methods. However, as we show in this paper, they can be clearly identified in multi-parameters in multi-mission satellite observations of sea surface height (SSH), sea surface temperature (SST) and ocean color observations of chlorophyll-a (chl-a), as well as 1/12-deg global HYbrid Coordinate Ocean Model (HYCOM) simulations of SSH, SST and sea surface salinity (SSS) in the Indian Ocean. While the surface structure of Rossby waves can be elucidated from comparisons of the signal in different sea surface parameters, models are needed to gain direct information about how these waves affect the ocean at depth. The first three baroclinic modes of the Rossby waves are inferred from the Fast Fourier Transform (FFT), and two-dimensional Radon Transform (2D RT). At many latitudes the first and second baroclinic mode Rossby wave phase speeds from satellite observations and model parameters are identified.

Wavepacket dynamics and the multi-configurational time-dependent Hartree approach

NASA Astrophysics Data System (ADS)

Manthe, Uwe

2017-06-01

Multi-configurational time-dependent Hartree (MCTDH) based approaches are efficient, accurate, and versatile methods for high-dimensional quantum dynamics simulations. Applications range from detailed investigations of polyatomic reaction processes in the gas phase to high-dimensional simulations studying the dynamics of condensed phase systems described by typical solid state physics model Hamiltonians. The present article presents an overview of the different areas of application and provides a comprehensive review of the underlying theory. The concepts and guiding ideas underlying the MCTDH approach and its multi-mode and multi-layer extensions are discussed in detail. The general structure of the equations of motion is highlighted. The representation of the Hamiltonian and the correlated discrete variable representation (CDVR), which provides an efficient multi-dimensional quadrature in MCTDH calculations, are discussed. Methods which facilitate the calculation of eigenstates, the evaluation of correlation functions, and the efficient representation of thermal ensembles in MCTDH calculations are described. Different schemes for the treatment of indistinguishable particles in MCTDH calculations and recent developments towards a unified multi-layer MCTDH theory for systems including bosons and fermions are discussed.

Scale separation for multi-scale modeling of free-surface and two-phase flows with the conservative sharp interface method

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

Han, L.H., E-mail: Luhui.Han@tum.de; Hu, X.Y., E-mail: Xiangyu.Hu@tum.de; Adams, N.A., E-mail: Nikolaus.Adams@tum.de

In this paper we present a scale separation approach for multi-scale modeling of free-surface and two-phase flows with complex interface evolution. By performing a stimulus-response operation on the level-set function representing the interface, separation of resolvable and non-resolvable interface scales is achieved efficiently. Uniform positive and negative shifts of the level-set function are used to determine non-resolvable interface structures. Non-resolved interface structures are separated from the resolved ones and can be treated by a mixing model or a Lagrangian-particle model in order to preserve mass. Resolved interface structures are treated by the conservative sharp-interface model. Since the proposed scale separationmore » approach does not rely on topological information, unlike in previous work, it can be implemented in a straightforward fashion into a given level set based interface model. A number of two- and three-dimensional numerical tests demonstrate that the proposed method is able to cope with complex interface variations accurately and significantly increases robustness against underresolved interface structures.« less

Three-Dimensional Bayesian Geostatistical Aquifer Characterization at the Hanford 300 Area using Tracer Test Data

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

Chen, Xingyuan; Murakami, Haruko; Hahn, Melanie S.

2012-06-01

Tracer testing under natural or forced gradient flow holds the potential to provide useful information for characterizing subsurface properties, through monitoring, modeling and interpretation of the tracer plume migration in an aquifer. Non-reactive tracer experiments were conducted at the Hanford 300 Area, along with constant-rate injection tests and electromagnetic borehole flowmeter (EBF) profiling. A Bayesian data assimilation technique, the method of anchored distributions (MAD) [Rubin et al., 2010], was applied to assimilate the experimental tracer test data with the other types of data and to infer the three-dimensional heterogeneous structure of the hydraulic conductivity in the saturated zone of themore » Hanford formation. In this study, the Bayesian prior information on the underlying random hydraulic conductivity field was obtained from previous field characterization efforts using the constant-rate injection tests and the EBF data. The posterior distribution of the conductivity field was obtained by further conditioning the field on the temporal moments of tracer breakthrough curves at various observation wells. MAD was implemented with the massively-parallel three-dimensional flow and transport code PFLOTRAN to cope with the highly transient flow boundary conditions at the site and to meet the computational demands of MAD. A synthetic study proved that the proposed method could effectively invert tracer test data to capture the essential spatial heterogeneity of the three-dimensional hydraulic conductivity field. Application of MAD to actual field data shows that the hydrogeological model, when conditioned on the tracer test data, can reproduce the tracer transport behavior better than the field characterized without the tracer test data. This study successfully demonstrates that MAD can sequentially assimilate multi-scale multi-type field data through a consistent Bayesian framework.« less

Application of information-retrieval methods to the classification of physical data

NASA Technical Reports Server (NTRS)

Mamotko, Z. N.; Khorolskaya, S. K.; Shatrovskiy, L. I.

1975-01-01

Scientific data received from satellites are characterized as a multi-dimensional time series, whose terms are vector functions of a vector of measurement conditions. Information retrieval methods are used to construct lower dimensional samples on the basis of the condition vector, in order to obtain these data and to construct partial relations. The methods are applied to the joint Soviet-French Arkad project.

Measuring Developmental Students' Mathematics Anxiety

ERIC Educational Resources Information Center

Ding, Yanqing

2016-01-01

This study conducted an item-level analysis of mathematics anxiety and examined the dimensionality of mathematics anxiety in a sample of developmental mathematics students (N = 162) by Multi-dimensional Random Coefficients Multinominal Logit Model (MRCMLM). The results indicate a moderately correlated factor structure of mathematics anxiety (r =…

Multi-Dimensional Analysis of Dynamic Human Information Interaction

ERIC Educational Resources Information Center

Park, Minsoo

2013-01-01

Introduction: This study aims to understand the interactions of perception, effort, emotion, time and performance during the performance of multiple information tasks using Web information technologies. Method: Twenty volunteers from a university participated in this study. Questionnaires were used to obtain general background information and…

Large-area assembly of three-dimensional nanoparticle structures via ion assisted aerosol lithography with a multi-pin spark discharge generator.

PubMed

Ha, Kyungyeon; Choi, Hoseop; Jung, Kinam; Han, Kyuhee; Lee, Jong-Kwon; Ahn, KwangJun; Choi, Mansoo

2014-06-06

We present an approach utilizing ion assisted aerosol lithography (IAAL) with a newly designed multi-pin spark discharge generator (SDG) for fabricating large-area three-dimensional (3D) nanoparticle-structure (NPS) arrays. The design of the multi-pin SDG allows us to uniformly construct 3D NPSs on a large area of 50 mm × 50 mm in a parallel fashion at atmospheric pressure. The ion-induced focusing capability of IAAL significantly reduces the feature size of 3D NPSs compared to that of the original pre-patterns formed on a substrate. The spatial uniformity of 3D NPSs is above 95% using the present multi-pin SDG, which is far superior to that of the previous single-pin SDG with less than 32% uniformity. The effect of size distributions of nanoparticles generated via the multi-pin SDG on the 3D NPSs also has been studied. In addition, we measured spectral reflectance for the present 3D NPSs coated with Ag, demonstrating enhanced diffuse reflectance.

Large-area assembly of three-dimensional nanoparticle structures via ion assisted aerosol lithography with a multi-pin spark discharge generator

NASA Astrophysics Data System (ADS)

Ha, Kyungyeon; Choi, Hoseop; Jung, Kinam; Han, Kyuhee; Lee, Jong-Kwon; Ahn, KwangJun; Choi, Mansoo

2014-06-01

We present an approach utilizing ion assisted aerosol lithography (IAAL) with a newly designed multi-pin spark discharge generator (SDG) for fabricating large-area three-dimensional (3D) nanoparticle-structure (NPS) arrays. The design of the multi-pin SDG allows us to uniformly construct 3D NPSs on a large area of 50 mm × 50 mm in a parallel fashion at atmospheric pressure. The ion-induced focusing capability of IAAL significantly reduces the feature size of 3D NPSs compared to that of the original pre-patterns formed on a substrate. The spatial uniformity of 3D NPSs is above 95% using the present multi-pin SDG, which is far superior to that of the previous single-pin SDG with less than 32% uniformity. The effect of size distributions of nanoparticles generated via the multi-pin SDG on the 3D NPSs also has been studied. In addition, we measured spectral reflectance for the present 3D NPSs coated with Ag, demonstrating enhanced diffuse reflectance.

Reduced detonation kinetics and detonation structure in one- and multi-fuel gaseous mixtures

NASA Astrophysics Data System (ADS)

Fomin, P. A.; Trotsyuk, A. V.; Vasil'ev, A. A.

2017-10-01

Two-step approximate models of chemical kinetics of detonation combustion of (i) one-fuel (CH4/air) and (ii) multi-fuel gaseous mixtures (CH4/H2/air and CH4/CO/air) are developed for the first time. The models for multi-fuel mixtures are proposed for the first time. Owing to the simplicity and high accuracy, the models can be used in multi-dimensional numerical calculations of detonation waves in corresponding gaseous mixtures. The models are in consistent with the second law of thermodynamics and Le Chatelier’s principle. Constants of the models have a clear physical meaning. Advantages of the kinetic model for detonation combustion of methane has been demonstrated via numerical calculations of a two-dimensional structure of the detonation wave in a stoichiometric and fuel-rich methane-air mixtures and stoichiometric methane-oxygen mixture. The dominant size of the detonation cell, determines in calculations, is in good agreement with all known experimental data.

[Research on non-rigid registration of multi-modal medical image based on Demons algorithm].

PubMed

Hao, Peibo; Chen, Zhen; Jiang, Shaofeng; Wang, Yang

2014-02-01

Non-rigid medical image registration is a popular subject in the research areas of the medical image and has an important clinical value. In this paper we put forward an improved algorithm of Demons, together with the conservation of gray model and local structure tensor conservation model, to construct a new energy function processing multi-modal registration problem. We then applied the L-BFGS algorithm to optimize the energy function and solve complex three-dimensional data optimization problem. And finally we used the multi-scale hierarchical refinement ideas to solve large deformation registration. The experimental results showed that the proposed algorithm for large de formation and multi-modal three-dimensional medical image registration had good effects.

A portable extruder for in situ wide angle x-ray scattering study on multi-dimensional flow field induced crystallization of polymer

NASA Astrophysics Data System (ADS)

Chang, Jiarui; Wang, Zhen; Tang, Xiaoliang; Tian, Fucheng; Ye, Ke; Li, Liangbin

2018-02-01

We have designed and constructed a portable extruder with a rotatable mandrel, which can be employed to study the multi-dimensional flow field (MDFF) induced crystallization of polymer combined with in situ wide angle x-ray scattering (WAXS). With the piston driving the melt sample to flow along the channel, a direct axial shear field is achieved. At the same time, the central mandrel keeps rotating under a stable speed, providing the sample with an additional circumferential shear field. By presetting different proportions of the two shear fields, namely, axial and circumferential, various flow states of the sample can be obtained, which makes it capable of investigating the effects of MDFF on polymer crystallization. We have performed an in situ WAXS experiment of MDFF induced crystallization of isotactic polypropylene based on the portable extruder at the beam line BL16B in Shanghai Synchrotron Radiation Facility. The rheological and structural information is collected simultaneously, which manifests the viability of the portable extruder on regulating MDFF and can provide guidance for polymer processing.

Content Preserving Watermarking for Medical Images Using Shearlet Transform and SVD

NASA Astrophysics Data System (ADS)

Favorskaya, M. N.; Savchina, E. I.

2017-05-01

Medical Image Watermarking (MIW) is a special field of a watermarking due to the requirements of the Digital Imaging and COmmunications in Medicine (DICOM) standard since 1993. All 20 parts of the DICOM standard are revised periodically. The main idea of the MIW is to embed various types of information including the doctor's digital signature, fragile watermark, electronic patient record, and main watermark in a view of region of interest for the doctor into the host medical image. These four types of information are represented in different forms; some of them are encrypted according to the DICOM requirements. However, all types of information ought to be resulted into the generalized binary stream for embedding. The generalized binary stream may have a huge volume. Therefore, not all watermarking methods can be applied successfully. Recently, the digital shearlet transform had been introduced as a rigorous mathematical framework for the geometric representation of multi-dimensional data. Some modifications of the shearlet transform, particularly the non-subsampled shearlet transform, can be associated to a multi-resolution analysis that provides a fully shift-invariant, multi-scale, and multi-directional expansion. During experiments, a quality of the extracted watermarks under the JPEG compression and typical internet attacks was estimated using several metrics, including the peak signal to noise ratio, structural similarity index measure, and bit error rate.

Spatially Extended Relativistic Particles Out of Traveling Front Solutions of Sine-Gordon Equation in (1+2) Dimensions

PubMed Central

Zarmi, Yair

2016-01-01

Slower-than-light multi-front solutions of the Sine-Gordon in (1+2) dimensions, constructed through the Hirota algorithm, are mapped onto spatially localized structures, which emulate free, spatially extended, massive relativistic particles. A localized structure is an image of the junctions at which the fronts intersect. It propagates together with the multi-front solution at the velocity of the latter. The profile of the localized structure obeys the linear wave equation in (1+2) dimensions, to which a term that represents interaction with a slower-than-light, Sine-Gordon-multi-front solution has been added. This result can be also formulated in terms of a (1+2)-dimensional Lagrangian system, in which the Sine-Gordon and wave equations are coupled. Expanding the Euler-Lagrange equations in powers of the coupling constant, the zero-order part of the solution reproduces the (1+2)-dimensional Sine-Gordon fronts. The first-order part is the spatially localized structure. PACS: 02.30.Ik, 03.65.Pm, 05.45.Yv, 02.30.Ik. PMID:26930077

A discrete Fourier-encoded, diagonal-free experiment to simplify homonuclear 2D NMR correlations.

PubMed

Huang, Zebin; Guan, Quanshuai; Chen, Zhong; Frydman, Lucio; Lin, Yulan

2017-07-21

Nuclear magnetic resonance (NMR) spectroscopy has long served as an irreplaceable, versatile tool in physics, chemistry, biology, and materials sciences, owing to its ability to study molecular structure and dynamics in detail. In particular, the connectivity of chemical sites within molecules, and thereby molecular structure, becomes visible by multi-dimensional NMR. Homonuclear correlation experiments are a powerful tool for identifying coupled spins. Generally, diagonal peaks in these correlation spectra display the strongest intensities and do not offer any new information beyond the standard one-dimensional spectrum, whereas weaker, symmetrically placed cross peaks contain most of the coupling information. The cross peaks near the diagonal are often affected by the tails of strong diagonal peaks or even obscured entirely by the diagonal. In this paper, we demonstrate a homonuclear encoding approach based on imparting a discrete phase modulation of the targeted cross peaks and combine it with a site-selective sculpting scheme, capable of simplifying the patterns arising in these 2D correlation spectra. The theoretical principles of the new methods are laid out, and experimental observations are rationalized on the basis of theoretical analyses. The ensuing techniques provide a new way to retrieve 2D coupling information within homonuclear spin systems, with enhanced sensitivity, speed, and clarity.

A discrete Fourier-encoded, diagonal-free experiment to simplify homonuclear 2D NMR correlations

NASA Astrophysics Data System (ADS)

Huang, Zebin; Guan, Quanshuai; Chen, Zhong; Frydman, Lucio; Lin, Yulan

2017-07-01

Nuclear magnetic resonance (NMR) spectroscopy has long served as an irreplaceable, versatile tool in physics, chemistry, biology, and materials sciences, owing to its ability to study molecular structure and dynamics in detail. In particular, the connectivity of chemical sites within molecules, and thereby molecular structure, becomes visible by multi-dimensional NMR. Homonuclear correlation experiments are a powerful tool for identifying coupled spins. Generally, diagonal peaks in these correlation spectra display the strongest intensities and do not offer any new information beyond the standard one-dimensional spectrum, whereas weaker, symmetrically placed cross peaks contain most of the coupling information. The cross peaks near the diagonal are often affected by the tails of strong diagonal peaks or even obscured entirely by the diagonal. In this paper, we demonstrate a homonuclear encoding approach based on imparting a discrete phase modulation of the targeted cross peaks and combine it with a site-selective sculpting scheme, capable of simplifying the patterns arising in these 2D correlation spectra. The theoretical principles of the new methods are laid out, and experimental observations are rationalized on the basis of theoretical analyses. The ensuing techniques provide a new way to retrieve 2D coupling information within homonuclear spin systems, with enhanced sensitivity, speed, and clarity.

A unique GCN5-related glucosamine N-acetyltransferase region exist in the fungal multi-domain glycoside hydrolase family 3 β-N-acetylglucosaminidase

PubMed Central

Qin, Zhen; Xiao, Yibei; Yang, Xinbin; Mesters, Jeroen R.; Yang, Shaoqing; Jiang, Zhengqiang

2015-01-01

Glycoside hydrolase (GH) family 3 β-N-acetylglucosaminidases widely exist in the filamentous fungi, which may play a key role in chitin metabolism of fungi. A multi-domain GH family 3 β-N-acetylglucosaminidase from Rhizomucor miehei (RmNag), exhibiting a potential N-acetyltransferase region, has been recently reported to show great potential in industrial applications. In this study, the crystal structure of RmNag was determined at 2.80 Å resolution. The three-dimensional structure of RmNag showed four distinctive domains, which belong to two distinguishable functional regions — a GH family 3 β-N-acetylglucosaminidase region (N-terminal) and a N-acetyltransferase region (C-terminal). From structural and functional analysis, the C-terminal region of RmNag was identified as a unique tandem array linking general control non-derepressible 5 (GCN5)-related N-acetyltransferase (GNAT), which displayed glucosamine N-acetyltransferase activity. Structural analysis of this glucosamine N-acetyltransferase region revealed that a unique glucosamine binding pocket is located in the pantetheine arm binding terminal region of the conserved CoA binding pocket, which is different from all known GNAT members. This is the first structural report of a glucosamine N-acetyltransferase, which provides novel structural information about substrate specificity of GNATs. The structural and functional features of this multi-domain β-N-acetylglucosaminidase could be useful in studying the catalytic mechanism of GH family 3 proteins. PMID:26669854

A unique GCN5-related glucosamine N-acetyltransferase region exist in the fungal multi-domain glycoside hydrolase family 3 β-N-acetylglucosaminidase.

PubMed

Qin, Zhen; Xiao, Yibei; Yang, Xinbin; Mesters, Jeroen R; Yang, Shaoqing; Jiang, Zhengqiang

2015-12-16

Glycoside hydrolase (GH) family 3 β-N-acetylglucosaminidases widely exist in the filamentous fungi, which may play a key role in chitin metabolism of fungi. A multi-domain GH family 3 β-N-acetylglucosaminidase from Rhizomucor miehei (RmNag), exhibiting a potential N-acetyltransferase region, has been recently reported to show great potential in industrial applications. In this study, the crystal structure of RmNag was determined at 2.80 Å resolution. The three-dimensional structure of RmNag showed four distinctive domains, which belong to two distinguishable functional regions--a GH family 3 β-N-acetylglucosaminidase region (N-terminal) and a N-acetyltransferase region (C-terminal). From structural and functional analysis, the C-terminal region of RmNag was identified as a unique tandem array linking general control non-derepressible 5 (GCN5)-related N-acetyltransferase (GNAT), which displayed glucosamine N-acetyltransferase activity. Structural analysis of this glucosamine N-acetyltransferase region revealed that a unique glucosamine binding pocket is located in the pantetheine arm binding terminal region of the conserved CoA binding pocket, which is different from all known GNAT members. This is the first structural report of a glucosamine N-acetyltransferase, which provides novel structural information about substrate specificity of GNATs. The structural and functional features of this multi-domain β-N-acetylglucosaminidase could be useful in studying the catalytic mechanism of GH family 3 proteins.

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.

Predictive brain networks for major depression in a semi-multimodal fusion hierarchical feature reduction framework.

PubMed

Yang, Jie; Yin, Yingying; Zhang, Zuping; Long, Jun; Dong, Jian; Zhang, Yuqun; Xu, Zhi; Li, Lei; Liu, Jie; Yuan, Yonggui

2018-02-05

Major depressive disorder (MDD) is characterized by dysregulation of distributed structural and functional networks. It is now recognized that structural and functional networks are related at multiple temporal scales. The recent emergence of multimodal fusion methods has made it possible to comprehensively and systematically investigate brain networks and thereby provide essential information for influencing disease diagnosis and prognosis. However, such investigations are hampered by the inconsistent dimensionality features between structural and functional networks. Thus, a semi-multimodal fusion hierarchical feature reduction framework is proposed. Feature reduction is a vital procedure in classification that can be used to eliminate irrelevant and redundant information and thereby improve the accuracy of disease diagnosis. Our proposed framework primarily consists of two steps. The first step considers the connection distances in both structural and functional networks between MDD and healthy control (HC) groups. By adding a constraint based on sparsity regularization, the second step fully utilizes the inter-relationship between the two modalities. However, in contrast to conventional multi-modality multi-task methods, the structural networks were considered to play only a subsidiary role in feature reduction and were not included in the following classification. The proposed method achieved a classification accuracy, specificity, sensitivity, and area under the curve of 84.91%, 88.6%, 81.29%, and 0.91, respectively. Moreover, the frontal-limbic system contributed the most to disease diagnosis. Importantly, by taking full advantage of the complementary information from multimodal neuroimaging data, the selected consensus connections may be highly reliable biomarkers of MDD. Copyright © 2017 Elsevier B.V. All rights reserved.

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

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

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

2016-01-01

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

Anonymous voting for multi-dimensional CV quantum system

NASA Astrophysics Data System (ADS)

Rong-Hua, Shi; Yi, Xiao; Jin-Jing, Shi; Ying, Guo; Moon-Ho, Lee

2016-06-01

We investigate the design of anonymous voting protocols, CV-based binary-valued ballot and CV-based multi-valued ballot with continuous variables (CV) in a multi-dimensional quantum cryptosystem to ensure the security of voting procedure and data privacy. The quantum entangled states are employed in the continuous variable quantum system to carry the voting information and assist information transmission, which takes the advantage of the GHZ-like states in terms of improving the utilization of quantum states by decreasing the number of required quantum states. It provides a potential approach to achieve the efficient quantum anonymous voting with high transmission security, especially in large-scale votes. Project supported by the National Natural Science Foundation of China (Grant Nos. 61272495, 61379153, and 61401519), the Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20130162110012), and the MEST-NRF of Korea (Grant No. 2012-002521).

Learning structure-property relationship in crystalline materials: A study of lanthanide-transition metal alloys

NASA Astrophysics Data System (ADS)

Pham, Tien-Lam; Nguyen, Nguyen-Duong; Nguyen, Van-Doan; Kino, Hiori; Miyake, Takashi; Dam, Hieu-Chi

2018-05-01

We have developed a descriptor named Orbital Field Matrix (OFM) for representing material structures in datasets of multi-element materials. The descriptor is based on the information regarding atomic valence shell electrons and their coordination. In this work, we develop an extension of OFM called OFM1. We have shown that these descriptors are highly applicable in predicting the physical properties of materials and in providing insights on the materials space by mapping into a low embedded dimensional space. Our experiments with transition metal/lanthanide metal alloys show that the local magnetic moments and formation energies can be accurately reproduced using simple nearest-neighbor regression, thus confirming the relevance of our descriptors. Using kernel ridge regressions, we could accurately reproduce formation energies and local magnetic moments calculated based on first-principles, with mean absolute errors of 0.03 μB and 0.10 eV/atom, respectively. We show that meaningful low-dimensional representations can be extracted from the original descriptor using descriptive learning algorithms. Intuitive prehension on the materials space, qualitative evaluation on the similarities in local structures or crystalline materials, and inference in the designing of new materials by element substitution can be performed effectively based on these low-dimensional representations.

Big Data Analytics for Scanning Transmission Electron Microscopy Ptychography

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

Jesse, S.; Chi, M.; Belianinov, A.

Electron microscopy is undergoing a transition; from the model of producing only a few micrographs, through the current state where many images and spectra can be digitally recorded, to a new mode where very large volumes of data (movies, ptychographic and multi-dimensional series) can be rapidly obtained. In this paper, we discuss the application of so-called “big-data” methods to high dimensional microscopy data, using unsupervised multivariate statistical techniques, in order to explore salient image features in a specific example of BiFeO 3 domains. Remarkably, k-means clustering reveals domain differentiation despite the fact that the algorithm is purely statistical in naturemore » and does not require any prior information regarding the material, any coexisting phases, or any differentiating structures. While this is a somewhat trivial case, this example signifies the extraction of useful physical and structural information without any prior bias regarding the sample or the instrumental modality. Further interpretation of these types of results may still require human intervention. Finally, however, the open nature of this algorithm and its wide availability, enable broad collaborations and exploratory work necessary to enable efficient data analysis in electron microscopy.« less

Big Data Analytics for Scanning Transmission Electron Microscopy Ptychography

DOE PAGES

Jesse, S.; Chi, M.; Belianinov, A.; ...

2016-05-23

Electron microscopy is undergoing a transition; from the model of producing only a few micrographs, through the current state where many images and spectra can be digitally recorded, to a new mode where very large volumes of data (movies, ptychographic and multi-dimensional series) can be rapidly obtained. In this paper, we discuss the application of so-called “big-data” methods to high dimensional microscopy data, using unsupervised multivariate statistical techniques, in order to explore salient image features in a specific example of BiFeO 3 domains. Remarkably, k-means clustering reveals domain differentiation despite the fact that the algorithm is purely statistical in naturemore » and does not require any prior information regarding the material, any coexisting phases, or any differentiating structures. While this is a somewhat trivial case, this example signifies the extraction of useful physical and structural information without any prior bias regarding the sample or the instrumental modality. Further interpretation of these types of results may still require human intervention. Finally, however, the open nature of this algorithm and its wide availability, enable broad collaborations and exploratory work necessary to enable efficient data analysis in electron microscopy.« less

Big Data Analytics for Scanning Transmission Electron Microscopy Ptychography

PubMed Central

Jesse, S.; Chi, M.; Belianinov, A.; Beekman, C.; Kalinin, S. V.; Borisevich, A. Y.; Lupini, A. R.

2016-01-01

Electron microscopy is undergoing a transition; from the model of producing only a few micrographs, through the current state where many images and spectra can be digitally recorded, to a new mode where very large volumes of data (movies, ptychographic and multi-dimensional series) can be rapidly obtained. Here, we discuss the application of so-called “big-data” methods to high dimensional microscopy data, using unsupervised multivariate statistical techniques, in order to explore salient image features in a specific example of BiFeO3 domains. Remarkably, k-means clustering reveals domain differentiation despite the fact that the algorithm is purely statistical in nature and does not require any prior information regarding the material, any coexisting phases, or any differentiating structures. While this is a somewhat trivial case, this example signifies the extraction of useful physical and structural information without any prior bias regarding the sample or the instrumental modality. Further interpretation of these types of results may still require human intervention. However, the open nature of this algorithm and its wide availability, enable broad collaborations and exploratory work necessary to enable efficient data analysis in electron microscopy. PMID:27211523

Highly Transparent Water-Repelling Surfaces based on Biomimetic Hierarchical Structure

NASA Astrophysics Data System (ADS)

Wooh, Sanghyuk; Koh, Jai; Yoon, Hyunsik; Char, Kookheon

2013-03-01

Nature is a great source of inspiration for creating unique structures with special functions. The representative examples of water-repelling surfaces in nature, such as lotus leaves, rose petals, and insect wings, consist of an array of bumps (or long hairs) and nanoscale surface features with different dimension scales. Herein, we introduced a method of realizing multi-dimensional hierarchical structures and water-repellancy of the surfaces with different drop impact scenarios. The multi-dimensional hierarchical structures were fabricated by soft imprinting method with TiO2 nanoparticle pastes. In order to achieve the enhanced hydrophobicity, fluorinated moieties were attached to the etched surfaces to lower the surface energy. As a result, super-hydrophobic surfaces with high transparency were realized (over 176° water contact angle), and for further investigation, these hierarchical surfaces with different drop impact scenarios were characterized by varying the impact speed, drop size, and the geometry of the surfaces.

[Study on "multi-dimensional structure and process dynamics quality control system" of Danshen infusion solution based on component structure theory].

PubMed

Feng, Liang; Zhang, Ming-Hua; Gu, Jun-Fei; Wang, Gui-You; Zhao, Zi-Yu; Jia, Xiao-Bin

2013-11-01

As traditional Chinese medicine (TCM) preparation products feature complex compounds and multiple preparation processes, the implementation of quality control in line with the characteristics of TCM preparation products provides a firm guarantee for the clinical efficacy and safety of TCM preparation products. Danshen infusion solution is a preparation commonly used in clinic, but its quality control is restricted to indexes of finished products, which can not guarantee its inherent quality. Our study group has proposed "multi-dimensional structure and process dynamics quality control system" on the basis of "component structure theory", for the purpose of controlling the quality of Danshen infusion solution at multiple levels and in multiple links from the efficacy-related material basis, the safety-related material basis, the characteristics of dosage form to the preparation process. This article, we bring forth new ideas and models to the quality control of TCM preparation products.

Electronic structure of boron based single and multi-layer two dimensional materials

NASA Astrophysics Data System (ADS)

Miyazato, Itsuki; Takahashi, Keisuke

2017-09-01

Two dimensional nanosheets based on boron and Group VA elements are designed and characterized using first principles calculations. B-N, B-P, B-As, B-Sb, and B-Bi are found to possess honeycomb structures where formation energies indicate exothermic reactions. Contrary to B-N, the cases of B-P, B-As, B-Sb, and B-Bi nanosheets are calculated to possess narrow band gaps. In addition, calculations reveal that the electronegativity difference between B and Group VA elements in the designed materials is a good indicator to predict the charge transfer and band gap of the two dimensional materials. Hydrogen adsorption over defect-free B-Sb and B-Bi results in exothermic reactions, while defect-free B-N, B-P, and B-As result in endothermic reactions. The layerability of the designed two dimensional materials is also investigated where the electronic structure of two-layered two dimensional materials is strongly coupled with how the two dimensional materials are layered. Thus, one can consider that the properties of two dimensional materials can be controlled by the composition of two dimensional materials and the structure of layers.

a New Effective way on Vegetation Mornitoring Using Multi-Spectral Canopy LIDAR

NASA Astrophysics Data System (ADS)

Bo, Z.; Wei, G.; Shuo, S.; Shalei, S.; Yingying, M.

2012-07-01

Airborne Laser Scanning (ALS) has been a well-established tool for the measurement of surface topography as well as for the estimation of biophysical canopy variables, such as tree height and vegetation density. By combining GPS and INS together, ALS could acquire surface information effectively in getting the mass production of DEM and DOM. However, up to now most approaches are built upon single-wavelength Lidar system, which could only provide structure information of the vegetation canopy, the intensity information was rarely used to monitor vegetation growing state as its limitation on spectral characteristics. On the other hand, positive multi/hyper-spectral imaging instruments highly rely on the effects of weather, shadow and the background noise etc. The attempts to fuse single-wavelength Lidar data with multi/hyper-spectral data also been effected this way. Thus, a concept for a multi-wavelength, active canopy Lidar has been tested in this paper. The proposed instrument takes measurement at two vegetation-sensitive bands separately at 556 nm and 780 nm, which, according to the correlation analysis between the wavelengths and biochemical content with plenty of ground ASD reflectance dataset, showed a high correlation coefficient on the chlorophyll concentration as well as nitrogen content. The instrumentation of the multi-wavelength canopy Lidar employs low power, solid and semiconductor laser diodes as its laser source and the receiver consists of two channels, one for 556 nm back-scatter signal and the other for 780 nm. The system calibration has also been done by using a standard white board. Multi-wavelength back-scatter signals were collected from a scene consists of stones, healthy broad-leaf trees and unhealthy trees that suffer from disease(part of its leaves were yellow). It is shown that the multi-wavelength canopy Lidar could not only capture the structure information, but also could pick up the spectral characteristics. A further test of three dimensional reconstruction and SVM based classification were also done and the results showed that the spatial resolution could be as high as 5 mm and the accuracy of classification on those three features (woody/un-woody, healthy/unhealthy) reached to 86%. Therefore, the multi-wavelength canopy Lidar shows its potential capability on vegetation monitoring in a new effective way.

Efficient High Order Central Schemes for Multi-Dimensional Hamilton-Jacobi Equations: Talk Slides

NASA Technical Reports Server (NTRS)

Bryson, Steve; Levy, Doron; Biegel, Brian R. (Technical Monitor)

2002-01-01

This viewgraph presentation presents information on the attempt to produce high-order, efficient, central methods that scale well to high dimension. The central philosophy is that the equations should evolve to the point where the data is smooth. This is accomplished by a cyclic pattern of reconstruction, evolution, and re-projection. One dimensional and two dimensional representational methods are detailed, as well.

Development of an unstructured solution adaptive method for the quasi-three-dimensional Euler and Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Jiang, Yi-Tsann

1993-01-01

A general solution adaptive scheme-based on a remeshing technique is developed for solving the two-dimensional and quasi-three-dimensional Euler and Favre-averaged Navier-Stokes equations. The numerical scheme is formulated on an unstructured triangular mesh utilizing an edge-based pointer system which defines the edge connectivity of the mesh structure. Jameson's four-stage hybrid Runge-Kutta scheme is used to march the solution in time. The convergence rate is enhanced through the use of local time stepping and implicit residual averaging. As the solution evolves, the mesh is regenerated adaptively using flow field information. Mesh adaptation parameters are evaluated such that an estimated local numerical error is equally distributed over the whole domain. For inviscid flows, the present approach generates a complete unstructured triangular mesh using the advancing front method. For turbulent flows, the approach combines a local highly stretched structured triangular mesh in the boundary layer region with an unstructured mesh in the remaining regions to efficiently resolve the important flow features. One-equation and two-equation turbulence models are incorporated into the present unstructured approach. Results are presented for a wide range of flow problems including two-dimensional multi-element airfoils, two-dimensional cascades, and quasi-three-dimensional cascades. This approach is shown to gain flow resolution in the refined regions while achieving a great reduction in the computational effort and storage requirements since solution points are not wasted in regions where they are not required.

Development of an unstructured solution adaptive method for the quasi-three-dimensional Euler and Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Jiang, Yi-Tsann; Usab, William J., Jr.

1993-01-01

A general solution adaptive scheme based on a remeshing technique is developed for solving the two-dimensional and quasi-three-dimensional Euler and Favre-averaged Navier-Stokes equations. The numerical scheme is formulated on an unstructured triangular mesh utilizing an edge-based pointer system which defines the edge connectivity of the mesh structure. Jameson's four-stage hybrid Runge-Kutta scheme is used to march the solution in time. The convergence rate is enhanced through the use of local time stepping and implicit residual averaging. As the solution evolves, the mesh is regenerated adaptively using flow field information. Mesh adaptation parameters are evaluated such that an estimated local numerical error is equally distributed over the whole domain. For inviscid flows, the present approach generates a complete unstructured triangular mesh using the advancing front method. For turbulent flows, the approach combines a local highly stretched structured triangular mesh in the boundary layer region with an unstructured mesh in the remaining regions to efficiently resolve the important flow features. One-equation and two-equation turbulence models are incorporated into the present unstructured approach. Results are presented for a wide range of flow problems including two-dimensional multi-element airfoils, two-dimensional cascades, and quasi-three-dimensional cascades. This approach is shown to gain flow resolution in the refined regions while achieving a great reduction in the computational effort and storage requirements since solution points are not wasted in regions where they are not required.

A Review of Structure Construction of Silk Fibroin Biomaterials from Single Structures to Multi-Level Structures.

PubMed

Qi, Yu; Wang, Hui; Wei, Kai; Yang, Ya; Zheng, Ru-Yue; Kim, Ick Soo; Zhang, Ke-Qin

2017-03-03

The biological performance of artificial biomaterials is closely related to their structure characteristics. Cell adhesion, migration, proliferation, and differentiation are all strongly affected by the different scale structures of biomaterials. Silk fibroin (SF), extracted mainly from silkworms, has become a popular biomaterial due to its excellent biocompatibility, exceptional mechanical properties, tunable degradation, ease of processing, and sufficient supply. As a material with excellent processability, SF can be processed into various forms with different structures, including particulate, fiber, film, and three-dimensional (3D) porous scaffolds. This review discusses and summarizes the various constructions of SF-based materials, from single structures to multi-level structures, and their applications. In combination with single structures, new techniques for creating special multi-level structures of SF-based materials, such as micropatterning and 3D-printing, are also briefly addressed.

Flame-Generated Vorticity Production in Premixed Flame-Vortex Interactions

NASA Technical Reports Server (NTRS)

Patnaik, G.; Kailasanath, K.

2003-01-01

In this study, we use detailed time-dependent, multi-dimensional numerical simulations to investigate the relative importance of the processes leading to FGV in flame-vortex interactions in normal gravity and microgravity and to determine if the production of vorticity in flames in gravity is the same as that in zero gravity except for the contribution of the gravity term. The numerical simulations will be performed using the computational model developed at NRL, FLAME3D. FLAME3D is a parallel, multi-dimensional (either two- or three-dimensional) flame model based on FLIC2D, which has been used extensively to study the structure and stability of premixed hydrogen and methane flames.

Two-dimensional molybdenum disulphide nanosheet-covered metal nanoparticle array as a floating gate in multi-functional flash memories

NASA Astrophysics Data System (ADS)

Han, Su-Ting; Zhou, Ye; Chen, Bo; Zhou, Li; Yan, Yan; Zhang, Hua; Roy, V. A. L.

2015-10-01

Semiconducting two-dimensional materials appear to be excellent candidates for non-volatile memory applications. However, the limited controllability of charge trapping behaviors and the lack of multi-bit storage studies in two-dimensional based memory devices require further improvement for realistic applications. Here, we report a flash memory consisting of metal NPs-molybdenum disulphide (MoS2) as a floating gate by introducing a metal nanoparticle (NP) (Ag, Au, Pt) monolayer underneath the MoS2 nanosheets. Controlled charge trapping and long data retention have been achieved in a metal (Ag, Au, Pt) NPs-MoS2 floating gate flash memory. This controlled charge trapping is hypothesized to be attributed to band bending and a built-in electric field ξbi between the interface of the metal NPs and MoS2. The metal NPs-MoS2 floating gate flash memories were further proven to be multi-bit memory storage devices possessing a 3-bit storage capability and a good retention capability up to 104 s. We anticipate that these findings would provide scientific insight for the development of novel memory devices utilizing an atomically thin two-dimensional lattice structure.Semiconducting two-dimensional materials appear to be excellent candidates for non-volatile memory applications. However, the limited controllability of charge trapping behaviors and the lack of multi-bit storage studies in two-dimensional based memory devices require further improvement for realistic applications. Here, we report a flash memory consisting of metal NPs-molybdenum disulphide (MoS2) as a floating gate by introducing a metal nanoparticle (NP) (Ag, Au, Pt) monolayer underneath the MoS2 nanosheets. Controlled charge trapping and long data retention have been achieved in a metal (Ag, Au, Pt) NPs-MoS2 floating gate flash memory. This controlled charge trapping is hypothesized to be attributed to band bending and a built-in electric field ξbi between the interface of the metal NPs and MoS2. The metal NPs-MoS2 floating gate flash memories were further proven to be multi-bit memory storage devices possessing a 3-bit storage capability and a good retention capability up to 104 s. We anticipate that these findings would provide scientific insight for the development of novel memory devices utilizing an atomically thin two-dimensional lattice structure. Electronic supplementary information (ESI) available: Energy-dispersive X-ray spectroscopy (EDS) spectra of the metal NPs, SEM image of MoS2 on Au NPs, erasing operations of the metal NPs-MoS2 memory device, transfer characteristics of the standard FET devices and Ag NP devices under programming operation, tapping-mode AFM height image of the fabricated MoS2 film for pristine MoS2 flash memory, gate signals used for programming the Au NPs-MoS2 and Pt NPs-MoS2 flash memories, and data levels recorded for 100 sequential cycles. See DOI: 10.1039/c5nr05054e

Energy Landscapes of Folding Chromosomes

NASA Astrophysics Data System (ADS)

Zhang, Bin

The genome, the blueprint of life, contains nearly all the information needed to build and maintain an entire organism. A comprehensive understanding of the genome is of paramount interest to human health and will advance progress in many areas, including life sciences, medicine, and biotechnology. The overarching goal of my research is to understand the structure-dynamics-function relationships of the human genome. In this talk, I will be presenting our efforts in moving towards that goal, with a particular emphasis on studying the three-dimensional organization, the structure of the genome with multi-scale approaches. Specifically, I will discuss the reconstruction of genome structures at both interphase and metaphase by making use of data from chromosome conformation capture experiments. Computationally modeling of chromatin fiber at atomistic level from first principles will also be presented as our effort for studying the genome structure from bottom up.

Visualization of Sources in the Universe

NASA Astrophysics Data System (ADS)

Kafatos, M.; Cebral, J. R.

1993-12-01

We have begun to develop a series of visualization tools of importance to the display of astronomical data and have applied these to the visualization of cosmological sources in the recently formed Institute for Computational Sciences and Informatics at GMU. One can use a three-dimensional perspective plot of the density surface for three dimensional data and in this case the iso-level contours are three- dimensional surfaces. Sophisticated rendering algorithms combined with multiple source lighting allow us to look carefully at such density contours and to see fine structure on the surface of the density contours. Stereoscopic and transparent rendering can give an even more sophisticated approach with multi-layered surfaces providing information at different levels. We have applied these methods to looking at density surfaces of 3-D data such as 100 clusters of galaxies and 2500 galaxies in the CfA redshift survey. Our plots presented are based on three variables, right ascension, declination and redshift. We have also obtained density structures in 2-D for the distribution of gamma-ray bursts (where distances are unknown) and the distribution of a variety of sources such as clusters of galaxies. Our techniques allow for correlations to be done visually.

On the formalization of multi-scale and multi-science processes for integrative biology

PubMed Central

Díaz-Zuccarini, Vanessa; Pichardo-Almarza, César

2011-01-01

The aim of this work is to introduce the general concept of ‘Bond Graph’ (BG) techniques applied in the context of multi-physics and multi-scale processes. BG modelling has a natural place in these developments. BGs are inherently coherent as the relationships defined between the ‘elements’ of the graph are strictly defined by causality rules and power (energy) conservation. BGs clearly show how power flows between components of the systems they represent. The ‘effort’ and ‘flow’ variables enable bidirectional information flow in the BG model. When the power level of a system is low, BGs degenerate into signal flow graphs in which information is mainly one-dimensional and power is minimal, i.e. they find a natural limitation when dealing with populations of individuals or purely kinetic models, as the concept of energy conservation in these systems is no longer relevant. The aim of this work is twofold: on the one hand, we will introduce the general concept of BG techniques applied in the context of multi-science and multi-scale models and, on the other hand, we will highlight some of the most promising features in the BG methodology by comparing with examples developed using well-established modelling techniques/software that could suggest developments or refinements to the current state-of-the-art tools, by providing a consistent framework from a structural and energetic point of view. PMID:22670211

A review of direct numerical simulations of astrophysical detonations and their implications

DOE PAGES

Parete-Koon, Suzanne T.; Smith, Christopher R.; Papatheodore, Thomas L.; ...

2013-04-11

Multi-dimensional direct numerical simulations (DNS) of astrophysical detonations in degenerate matter have revealed that the nuclear burning is typically characterized by cellular structure caused by transverse instabilities in the detonation front. Type Ia supernova modelers often use one- dimensional DNS of detonations as inputs or constraints for their whole star simulations. While these one-dimensional studies are useful tools, the true nature of the detonation is multi-dimensional. The multi-dimensional structure of the burning influences the speed, stability, and the composition of the detonation and its burning products, and therefore, could have an impact on the spectra of Type Ia supernovae. Considerablemore » effort has been expended modeling Type Ia supernovae at densities above 1x10 7 g∙cm -3 where the complexities of turbulent burning dominate the flame propagation. However, most full star models turn the nuclear burning schemes off when the density falls below 1x10 7 g∙cm -3 and distributed burning begins. The deflagration to detonation transition (DDT) is believed to occur at just these densities and consequently they are the densities important for studying the properties of the subsequent detonation. In conclusion, this work reviews the status of DNS studies of detonations and their possible implications for Type Ia supernova models. It will cover the development of Detonation theory from the first simple Chapman-Jouguet (CJ) detonation models to the current models based on the time-dependent, compressible, reactive flow Euler equations of fluid dynamics.« less

A cross-diffusion system derived from a Fokker-Planck equation with partial averaging

NASA Astrophysics Data System (ADS)

Jüngel, Ansgar; Zamponi, Nicola

2017-02-01

A cross-diffusion system for two components with a Laplacian structure is analyzed on the multi-dimensional torus. This system, which was recently suggested by P.-L. Lions, is formally derived from a Fokker-Planck equation for the probability density associated with a multi-dimensional Itō process, assuming that the diffusion coefficients depend on partial averages of the probability density with exponential weights. A main feature is that the diffusion matrix of the limiting cross-diffusion system is generally neither symmetric nor positive definite, but its structure allows for the use of entropy methods. The global-in-time existence of positive weak solutions is proved and, under a simplifying assumption, the large-time asymptotics is investigated.

Integration of genomic and medical data into a 3D atlas of human anatomy.

PubMed

Turinsky, Andrei L; Fanea, Elena; Trinh, Quang; Dong, Xiaoli; Stromer, Julie N; Shu, Xueling; Wat, Stephen; Hallgrímsson, Benedikt; Hill, Jonathan W; Edwards, Carol; Grosenick, Brenda; Yajima, Masumi; Sensen, Christoph W

2008-01-01

We have developed a framework for the visual integration and exploration of multi-scale biomedical data, which includes anatomical and molecular components. We have also created a Java-based software system that integrates molecular information, such as gene expression data, into a three-dimensional digital atlas of the male adult human anatomy. Our atlas is structured according to the Terminologia Anatomica. The underlying data-indexing mechanism uses open standards and semantic ontology-processing tools to establish the associations between heterogeneous data types. The software system makes an extensive use of virtual reality visualization.

Coupled multi-disciplinary simulation of composite engine structures in propulsion environment

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Singhal, Surendra N.

1992-01-01

A computational simulation procedure is described for the coupled response of multi-layered multi-material composite engine structural components which are subjected to simultaneous multi-disciplinary thermal, structural, vibration, and acoustic loadings including the effect of hostile environments. The simulation is based on a three dimensional finite element analysis technique in conjunction with structural mechanics codes and with acoustic analysis methods. The composite material behavior is assessed at the various composite scales, i.e., the laminate/ply/constituents (fiber/matrix), via a nonlinear material characterization model. Sample cases exhibiting nonlinear geometrical, material, loading, and environmental behavior of aircraft engine fan blades, are presented. Results for deformed shape, vibration frequency, mode shapes, and acoustic noise emitted from the fan blade, are discussed for their coupled effect in hot and humid environments. Results such as acoustic noise for coupled composite-mechanics/heat transfer/structural/vibration/acoustic analyses demonstrate the effectiveness of coupled multi-disciplinary computational simulation and the various advantages of composite materials compared to metals.

Structural damage detection-oriented multi-type sensor placement with multi-objective optimization

NASA Astrophysics Data System (ADS)

Lin, Jian-Fu; Xu, You-Lin; Law, Siu-Seong

2018-05-01

A structural damage detection-oriented multi-type sensor placement method with multi-objective optimization is developed in this study. The multi-type response covariance sensitivity-based damage detection method is first introduced. Two objective functions for optimal sensor placement are then introduced in terms of the response covariance sensitivity and the response independence. The multi-objective optimization problem is formed by using the two objective functions, and the non-dominated sorting genetic algorithm (NSGA)-II is adopted to find the solution for the optimal multi-type sensor placement to achieve the best structural damage detection. The proposed method is finally applied to a nine-bay three-dimensional frame structure. Numerical results show that the optimal multi-type sensor placement determined by the proposed method can avoid redundant sensors and provide satisfactory results for structural damage detection. The restriction on the number of each type of sensors in the optimization can reduce the searching space in the optimization to make the proposed method more effective. Moreover, how to select a most optimal sensor placement from the Pareto solutions via the utility function and the knee point method is demonstrated in the case study.

A Review of Structure Construction of Silk Fibroin Biomaterials from Single Structures to Multi-Level Structures

PubMed Central

Qi, Yu; Wang, Hui; Wei, Kai; Yang, Ya; Zheng, Ru-Yue; Kim, Ick Soo; Zhang, Ke-Qin

2017-01-01

The biological performance of artificial biomaterials is closely related to their structure characteristics. Cell adhesion, migration, proliferation, and differentiation are all strongly affected by the different scale structures of biomaterials. Silk fibroin (SF), extracted mainly from silkworms, has become a popular biomaterial due to its excellent biocompatibility, exceptional mechanical properties, tunable degradation, ease of processing, and sufficient supply. As a material with excellent processability, SF can be processed into various forms with different structures, including particulate, fiber, film, and three-dimensional (3D) porous scaffolds. This review discusses and summarizes the various constructions of SF-based materials, from single structures to multi-level structures, and their applications. In combination with single structures, new techniques for creating special multi-level structures of SF-based materials, such as micropatterning and 3D-printing, are also briefly addressed. PMID:28273799

Effective 3-D surface modeling for geographic information systems

NASA Astrophysics Data System (ADS)

Yüksek, K.; Alparslan, M.; Mendi, E.

2013-11-01

In this work, we propose a dynamic, flexible and interactive urban digital terrain platform (DTP) with spatial data and query processing capabilities of Geographic Information Systems (GIS), multimedia database functionality and graphical modeling infrastructure. A new data element, called Geo-Node, which stores image, spatial data and 3-D CAD objects is developed using an efficient data structure. The system effectively handles data transfer of Geo-Nodes between main memory and secondary storage with an optimized Directional Replacement Policy (DRP) based buffer management scheme. Polyhedron structures are used in Digital Surface Modeling (DSM) and smoothing process is performed by interpolation. The experimental results show that our framework achieves high performance and works effectively with urban scenes independent from the amount of spatial data and image size. The proposed platform may contribute to the development of various applications such as Web GIS systems based on 3-D graphics standards (e.g. X3-D and VRML) and services which integrate multi-dimensional spatial information and satellite/aerial imagery.

Effective 3-D surface modeling for geographic information systems

NASA Astrophysics Data System (ADS)

Yüksek, K.; Alparslan, M.; Mendi, E.

2016-01-01

In this work, we propose a dynamic, flexible and interactive urban digital terrain platform with spatial data and query processing capabilities of geographic information systems, multimedia database functionality and graphical modeling infrastructure. A new data element, called Geo-Node, which stores image, spatial data and 3-D CAD objects is developed using an efficient data structure. The system effectively handles data transfer of Geo-Nodes between main memory and secondary storage with an optimized directional replacement policy (DRP) based buffer management scheme. Polyhedron structures are used in digital surface modeling and smoothing process is performed by interpolation. The experimental results show that our framework achieves high performance and works effectively with urban scenes independent from the amount of spatial data and image size. The proposed platform may contribute to the development of various applications such as Web GIS systems based on 3-D graphics standards (e.g., X3-D and VRML) and services which integrate multi-dimensional spatial information and satellite/aerial imagery.

Secondary Structures in a Freeze-Dried Lignite Humic Acid Fraction Caused by Hydrogen-Bonding of Acidic Protons with Aromatic Rings.

PubMed

Cao, Xiaoyan; Drosos, Marios; Leenheer, Jerry A; Mao, Jingdong

2016-02-16

A lignite humic acid (HA) was separated from inorganic and non-HA impurities (i.e., aluminosilicates, metals) and fractionated by a combination of dialysis and XAD-8 resin. Fractionation revealed a more homogeneous structure of lignite HA. New and more specific structural information on the main lignite HA fraction is obtained by solid-state nuclear magnetic resonance (NMR) spectroscopy. Quantitative (13)C multiple cross-polarization (multiCP) NMR indicated oxidized phenyl propane structures derived from lignin. MultiCP experiments, conducted on potassium HA salts titrated to pH 10 and pH 12, revealed shifts consistent with carboxylate and phenolate formation, but structural changes associated with enolate formation from aromatic beta keto acids were not detected. Two-dimensional (1)H-(13)C heteronuclear correlation (2D HETCOR) NMR indicated aryl-aliphatic ketones, aliphatic and aromatic carboxyl groups, phenol, and methoxy phenyl ethers. Acidic protons from carboxyl groups in both the lignite HA fraction and a synthetic HA-like polycondensate were found to be hydrogen-bonded with electron-rich aromatic rings. Our results coupled with published infrared spectra provide evidence for the preferential hydrogen bonding of acidic hydrogens with electron-rich aromatic rings rather than adjacent carbonyl groups. These hydrogen-bonding interactions likely result from stereochemical arrangements in primary structures and folding.

Visualizing phylogenetic tree landscapes.

PubMed

Wilgenbusch, James C; Huang, Wen; Gallivan, Kyle A

2017-02-02

Genomic-scale sequence alignments are increasingly used to infer phylogenies in order to better understand the processes and patterns of evolution. Different partitions within these new alignments (e.g., genes, codon positions, and structural features) often favor hundreds if not thousands of competing phylogenies. Summarizing and comparing phylogenies obtained from multi-source data sets using current consensus tree methods discards valuable information and can disguise potential methodological problems. Discovery of efficient and accurate dimensionality reduction methods used to display at once in 2- or 3- dimensions the relationship among these competing phylogenies will help practitioners diagnose the limits of current evolutionary models and potential problems with phylogenetic reconstruction methods when analyzing large multi-source data sets. We introduce several dimensionality reduction methods to visualize in 2- and 3-dimensions the relationship among competing phylogenies obtained from gene partitions found in three mid- to large-size mitochondrial genome alignments. We test the performance of these dimensionality reduction methods by applying several goodness-of-fit measures. The intrinsic dimensionality of each data set is also estimated to determine whether projections in 2- and 3-dimensions can be expected to reveal meaningful relationships among trees from different data partitions. Several new approaches to aid in the comparison of different phylogenetic landscapes are presented. Curvilinear Components Analysis (CCA) and a stochastic gradient decent (SGD) optimization method give the best representation of the original tree-to-tree distance matrix for each of the three- mitochondrial genome alignments and greatly outperformed the method currently used to visualize tree landscapes. The CCA + SGD method converged at least as fast as previously applied methods for visualizing tree landscapes. We demonstrate for all three mtDNA alignments that 3D projections significantly increase the fit between the tree-to-tree distances and can facilitate the interpretation of the relationship among phylogenetic trees. We demonstrate that the choice of dimensionality reduction method can significantly influence the spatial relationship among a large set of competing phylogenetic trees. We highlight the importance of selecting a dimensionality reduction method to visualize large multi-locus phylogenetic landscapes and demonstrate that 3D projections of mitochondrial tree landscapes better capture the relationship among the trees being compared.

Maximizing the Biochemical Resolving Power of Fluorescence Microscopy

PubMed Central

Esposito, Alessandro; Popleteeva, Marina; Venkitaraman, Ashok R.

2013-01-01

Most recent advances in fluorescence microscopy have focused on achieving spatial resolutions below the diffraction limit. However, the inherent capability of fluorescence microscopy to non-invasively resolve different biochemical or physical environments in biological samples has not yet been formally described, because an adequate and general theoretical framework is lacking. Here, we develop a mathematical characterization of the biochemical resolution in fluorescence detection with Fisher information analysis. To improve the precision and the resolution of quantitative imaging methods, we demonstrate strategies for the optimization of fluorescence lifetime, fluorescence anisotropy and hyperspectral detection, as well as different multi-dimensional techniques. We describe optimized imaging protocols, provide optimization algorithms and describe precision and resolving power in biochemical imaging thanks to the analysis of the general properties of Fisher information in fluorescence detection. These strategies enable the optimal use of the information content available within the limited photon-budget typically available in fluorescence microscopy. This theoretical foundation leads to a generalized strategy for the optimization of multi-dimensional optical detection, and demonstrates how the parallel detection of all properties of fluorescence can maximize the biochemical resolving power of fluorescence microscopy, an approach we term Hyper Dimensional Imaging Microscopy (HDIM). Our work provides a theoretical framework for the description of the biochemical resolution in fluorescence microscopy, irrespective of spatial resolution, and for the development of a new class of microscopes that exploit multi-parametric detection systems. PMID:24204821

In vivo, label-free, three-dimensional quantitative imaging of liver surface using multi-photon microscopy

NASA Astrophysics Data System (ADS)

Zhuo, Shuangmu; Yan, Jie; Kang, Yuzhan; Xu, Shuoyu; Peng, Qiwen; So, Peter T. C.; Yu, Hanry

2014-07-01

Various structural features on the liver surface reflect functional changes in the liver. The visualization of these surface features with molecular specificity is of particular relevance to understanding the physiology and diseases of the liver. Using multi-photon microscopy (MPM), we have developed a label-free, three-dimensional quantitative and sensitive method to visualize various structural features of liver surface in living rat. MPM could quantitatively image the microstructural features of liver surface with respect to the sinuosity of collagen fiber, the elastic fiber structure, the ratio between elastin and collagen, collagen content, and the metabolic state of the hepatocytes that are correlative with the pathophysiologically induced changes in the regions of interest. This study highlights the potential of this technique as a useful tool for pathophysiological studies and possible diagnosis of the liver diseases with further development.

In vivo, label-free, three-dimensional quantitative imaging of liver surface using multi-photon microscopy

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

Zhuo, Shuangmu, E-mail: shuangmuzhuo@gmail.com, E-mail: hanry-yu@nuhs.edu.sg; Institute of Laser and Optoelectronics Technology, Fujian Normal University, Fuzhou 350007; Yan, Jie

2014-07-14

Various structural features on the liver surface reflect functional changes in the liver. The visualization of these surface features with molecular specificity is of particular relevance to understanding the physiology and diseases of the liver. Using multi-photon microscopy (MPM), we have developed a label-free, three-dimensional quantitative and sensitive method to visualize various structural features of liver surface in living rat. MPM could quantitatively image the microstructural features of liver surface with respect to the sinuosity of collagen fiber, the elastic fiber structure, the ratio between elastin and collagen, collagen content, and the metabolic state of the hepatocytes that are correlativemore » with the pathophysiologically induced changes in the regions of interest. This study highlights the potential of this technique as a useful tool for pathophysiological studies and possible diagnosis of the liver diseases with further development.« 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.

Insights into the dissolution and the three-dimensional structure of insensitive munitions formulations.

PubMed

Taylor, Susan; Ringelberg, David B; Dontsova, Katerina; Daghlian, Charles P; Walsh, Marianne E; Walsh, Michael R

2013-11-01

Two compounds, 2,4-dinitroanisole (DNAN) and 3-nitro-1,2,4-triazol-5-one (NTO) are the main ingredients in a suite of explosive formulations that are being, or soon will be, fielded at military training ranges. We aim to understand the dissolution characteristics of DNAN and NTO and three insensitive muntions (IM) formulations that contain them. This information is needed to accurately predict the environmental fate of IM constituents, some of which may be toxic to people and the environment. We used Raman spectroscopy to identify the different constituents in the IM formulations and micro computed tomography to image their three-dimensional structure. These are the first three-dimensional images of detonated explosive particles. For multi-component explosives the solubility of the individual constituents and the fraction of each constituent wetted by water controls the dissolution. We found that the order of magnitude differences in solubility amongst the constituents of these IM formulations quickly produced hole-riddled particles when these were exposed to water. Micro-computed tomography showed that particles resulting from field detonations were fractured, producing conduits by which water could access the interior of the particle. We think that micro-computed tomography can also be used to determine the initial composition of IM particles and to track how their compositions change as the particles dissolve. This information is critical to quantifying dissolution and developing physically based dissolution models. Published by Elsevier Ltd.

Multiple resonant absorber with prism-incorporated graphene and one-dimensional photonic crystals in the visible and near-infrared spectral range

NASA Astrophysics Data System (ADS)

Zou, X. J.; Zheng, G. G.; Chen, Y. Y.; Xu, L. H.; Lai, M.

2018-04-01

A multi-band absorber constructed from prism-incorporated one-dimensional photonic crystal (1D-PhC) containing graphene defects is achieved theoretically in the visible and near-infrared (vis-NIR) spectral range. By means of the transfer matrix method (TMM), the effect of structural parameters on the optical response of the structure has been investigated. It is possible to achieve multi-peak and complete optical absorption. The simulations reveal that the light intensity is enhanced at the graphene plane, and the resonant wavelength and the absorption intensity can also be tuned by tilting the incidence angle of the impinging light. In particular, multiple graphene sheets are embedded in the arrays, without any demand of manufacture process to cut them into periodic patterns. The proposed concept can be extended to other two-dimensional (2D) materials and engineered for promising applications, including selective or multiplex filters, multiple channel sensors, and photodetectors.

Flow Structure and Force Variation with Aspect Ratio for a Two-Degree-of-Freedom Flapping Wing

NASA Astrophysics Data System (ADS)

Burge, Matthew; Favale, James; Ringuette, Matthew

2014-11-01

We investigate experimentally the effect of aspect ratio (AR) on the flow structure and forces of a two-degree-of-freedom flapping wing. Flapping wings are known to produce complex and unsteady vortex loop structures, and the objective is to characterize their variation with AR and how this influences the lift force. Previous results on rotating wings demonstrated that changes in AR significantly affect the three-dimensional flow structure and lift coefficient. This is primarily due to the relatively greater influence of the tip vortex for lower AR. At Reynolds number of order O(103) we test wings of AR = 2-4, values typically found in nature, with simplified planform shapes. The lift force is measured using a submersible transducer at the base of the wing in a glycerin-water mixture. The qualitative, three-dimensional vortex loop structure for different ARs is obtained using multi-color dye flow visualization. Guided by this, quantitative three-component flow information, namely vorticity, the Q-criterion, and circulation, is acquired from stereoscopic particle image velocimetry in key planes. Of interest is how these parameters and the vortex loop topology vary with AR, and their connection to features in the unsteady force signal. This work is supported by the National Science Foundation, Award Number 1336548, supervised by Dr. Dimitrios Papavassiliou.

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

Bergen, Ben; Moss, Nicholas; Charest, Marc Robert Joseph

FleCSI is a compile-time configurable framework designed to support multi-physics application development. As such, FleCSI attempts to provide a very general set of infrastructure design patterns that can be specialized and extended to suit the needs of a broad variety of solver and data requirements. Current support includes multi-dimensional mesh topology, mesh geometry, and mesh adjacency information, n-dimensional hashed-tree data structures, graph partitioning interfaces, and dependency closures. FleCSI also introduces a functional programming model with control, execution, and data abstractions that are consistent with both MPI and state-of-the-art task-based runtimes such as Legion and Charm++. The FleCSI abstraction layer providesmore » the developer with insulation from the underlying runtime, while allowing support for multiple runtime systems, including conventional models like asynchronous MPI. The intent is to give developers a concrete set of user-friendly programming tools that can be used now, while allowing flexibility in choosing runtime implementations and optimizations that can be applied to architectures and runtimes that arise in the future. The control and execution models in FleCSI also provide formal nomenclature for describing poorly understood concepts like kernels and tasks.« less

Taking sociality seriously: the structure of multi-dimensional social networks as a source of information for individuals

PubMed Central

Barrett, Louise; Henzi, S. Peter; Lusseau, David

2012-01-01

Understanding human cognitive evolution, and that of the other primates, means taking sociality very seriously. For humans, this requires the recognition of the sociocultural and historical means by which human minds and selves are constructed, and how this gives rise to the reflexivity and ability to respond to novelty that characterize our species. For other, non-linguistic, primates we can answer some interesting questions by viewing social life as a feedback process, drawing on cybernetics and systems approaches and using social network neo-theory to test these ideas. Specifically, we show how social networks can be formalized as multi-dimensional objects, and use entropy measures to assess how networks respond to perturbation. We use simulations and natural ‘knock-outs’ in a free-ranging baboon troop to demonstrate that changes in interactions after social perturbations lead to a more certain social network, in which the outcomes of interactions are easier for members to predict. This new formalization of social networks provides a framework within which to predict network dynamics and evolution, helps us highlight how human and non-human social networks differ and has implications for theories of cognitive evolution. PMID:22734054

High-harmonic spectroscopy of aligned molecules

NASA Astrophysics Data System (ADS)

Yun, Hyeok; Yun, Sang Jae; Lee, Gae Hwang; Nam, Chang Hee

2017-01-01

High harmonics emitted from aligned molecules driven by intense femtosecond laser pulses provide the opportunity to explore the structural information of molecules. The field-free molecular alignment technique is an expedient tool for investigating the structural characteristics of linear molecules. The underlying physics of field-free alignment, showing the characteristic revival structure specific to molecular species, is clearly explained from the quantum-phase analysis of molecular rotational states. The anisotropic nature of molecules is shown from the harmonic polarization measurement performed with spatial interferometry. The multi-orbital characteristics of molecules are investigated using high-harmonic spectroscopy, applied to molecules of N2 and CO2. In the latter case the two-dimensional high-harmonic spectroscopy, implemented using a two-color laser field, is applied to distinguish harmonics from different orbitals. Molecular high-harmonic spectroscopy will open a new route to investigate ultrafast dynamics of molecules.

GO(vis), a gene ontology visualization tool based on multi-dimensional values.

PubMed

Ning, Zi; Jiang, Zhenran

2010-05-01

Most of gene product similarity measurements concentrate on the information content of Gene Ontology (GO) terms or use a path-based similarity between GO terms, which may ignore other important information contained in the structure of the ontology. In our study, we integrate different GO similarity measure approaches to analyze the functional relationship of genes and gene products with a new triangle-based visualization tool called GO(Vis). The purpose of this tool is to demonstrate the effect of three important information factors when measuring the similarity between gene products. One advantage of this tool is that its important ratio can be adjusted to meet different measuring requirements according to the biological knowledge of each factor. The experimental results demonstrate that GO(Vis) can display diagrams of the functional relationship for gene products effectively.

Fast Detection of Material Deformation through Structural Dissimilarity

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

Ushizima, Daniela; Perciano, Talita; Parkinson, Dilworth

2015-10-29

Designing materials that are resistant to extreme temperatures and brittleness relies on assessing structural dynamics of samples. Algorithms are critically important to characterize material deformation under stress conditions. Here, we report on our design of coarse-grain parallel algorithms for image quality assessment based on structural information and on crack detection of gigabyte-scale experimental datasets. We show how key steps can be decomposed into distinct processing flows, one based on structural similarity (SSIM) quality measure, and another on spectral content. These algorithms act upon image blocks that fit into memory, and can execute independently. We discuss the scientific relevance of themore » problem, key developments, and decomposition of complementary tasks into separate executions. We show how to apply SSIM to detect material degradation, and illustrate how this metric can be allied to spectral analysis for structure probing, while using tiled multi-resolution pyramids stored in HDF5 chunked multi-dimensional arrays. Results show that the proposed experimental data representation supports an average compression rate of 10X, and data compression scales linearly with the data size. We also illustrate how to correlate SSIM to crack formation, and how to use our numerical schemes to enable fast detection of deformation from 3D datasets evolving in time.« less

Three-Dimensional Bayesian Geostatistical Aquifer Characterization at the Hanford 300 Area using Tracer Test Data

NASA Astrophysics Data System (ADS)

Chen, X.; Murakami, H.; Hahn, M. S.; Hammond, G. E.; Rockhold, M. L.; Rubin, Y.

2010-12-01

Tracer testing under natural or forced gradient flow provides useful information for characterizing subsurface properties, by monitoring and modeling the tracer plume migration in a heterogeneous aquifer. At the Hanford 300 Area, non-reactive tracer experiments, in addition to constant-rate injection tests and electromagnetic borehole flowmeter (EBF) profiling, were conducted to characterize the heterogeneous hydraulic conductivity field. A Bayesian data assimilation technique, method of anchored distributions (MAD), is applied to assimilate the experimental tracer test data and to infer the three-dimensional heterogeneous structure of the hydraulic conductivity in the saturated zone of the Hanford formation. In this study, the prior information of the underlying random hydraulic conductivity field was obtained from previous field characterization efforts using the constant-rate injection tests and the EBF data. The posterior distribution of the random field is obtained by further conditioning the field on the temporal moments of tracer breakthrough curves at various observation wells. The parallel three-dimensional flow and transport code PFLOTRAN is implemented to cope with the highly transient flow boundary conditions at the site and to meet the computational demand of the proposed method. The validation results show that the field conditioned on the tracer test data better reproduces the tracer transport behavior compared to the field characterized previously without the tracer test data. A synthetic study proves that the proposed method can effectively assimilate tracer test data to capture the essential spatial heterogeneity of the three-dimensional hydraulic conductivity field. These characterization results will improve conceptual models developed for the site, including reactive transport models. The study successfully demonstrates the capability of MAD to assimilate multi-scale multi-type field data within a consistent Bayesian framework. The MAD framework can potentially be applied to combine geophysical data with other types of data in site characterization.

Cluster Analysis and Gaussian Mixture Estimation of Correlated Time-Series by Means of Multi-dimensional Scaling

NASA Astrophysics Data System (ADS)

Ibuki, Takero; Suzuki, Sei; Inoue, Jun-ichi

We investigate cross-correlations between typical Japanese stocks collected through Yahoo!Japan website ( http://finance.yahoo.co.jp/ ). By making use of multi-dimensional scaling (MDS) for the cross-correlation matrices, we draw two-dimensional scattered plots in which each point corresponds to each stock. To make a clustering for these data plots, we utilize the mixture of Gaussians to fit the data set to several Gaussian densities. By minimizing the so-called Akaike Information Criterion (AIC) with respect to parameters in the mixture, we attempt to specify the best possible mixture of Gaussians. It might be naturally assumed that all the two-dimensional data points of stocks shrink into a single small region when some economic crisis takes place. The justification of this assumption is numerically checked for the empirical Japanese stock data, for instance, those around 11 March 2011.

Buckling Analysis of Single and Multi Delamination In Composite Beam Using Finite Element Method

NASA Astrophysics Data System (ADS)

Simanjorang, Hans Charles; Syamsudin, Hendri; Giri Suada, Muhammad

2018-04-01

Delamination is one type of imperfection in structure which found usually in the composite structure. Delamination may exist due to some factors namely in-service condition where the foreign objects hit the composite structure and creates inner defect and poor manufacturing that causes the initial imperfections. Composite structure is susceptible to the compressive loading. Compressive loading leads the instability phenomenon in the composite structure called buckling. The existence of delamination inside of the structure will cause reduction in buckling strength. This paper will explain the effect of delamination location to the buckling strength. The analysis will use the one-dimensional modelling approach using two- dimensional finite element method.

Development of flood routing simulation system of digital Qingjiang based on integrated spatial information technology

NASA Astrophysics Data System (ADS)

Yuan, Yanbin; Zhou, You; Zhu, Yaqiong; Yuan, Xiaohui; Sælthun, N. R.

2007-11-01

Based on digital technology, flood routing simulation system development is an important component of "digital catchment". Taking QingJiang catchment as a pilot case, in-depth analysis on informatization of Qingjiang catchment management being the basis, aiming at catchment data's multi-source, - dimension, -element, -subject, -layer and -class feature, the study brings the design thought and method of "subject-point-source database" (SPSD) to design system structure in order to realize the unified management of catchments data in great quantity. Using the thought of integrated spatial information technology for reference, integrating hierarchical structure development model of digital catchment is established. The model is general framework of the flood routing simulation system analysis, design and realization. In order to satisfy the demands of flood routing three-dimensional simulation system, the object-oriented spatial data model are designed. We can analyze space-time self-adapting relation between flood routing and catchments topography, express grid data of terrain by using non-directed graph, apply breadth first search arithmetic, set up search method for the purpose of dynamically searching stream channel on the basis of simulated three-dimensional terrain. The system prototype is therefore realized. Simulation results have demonstrated that the proposed approach is feasible and effective in the application.

Multi-Dimensional Damage Detection for Surfaces and Structures

NASA Technical Reports Server (NTRS)

Williams, Martha; Lewis, Mark; Roberson, Luke; Medelius, Pedro; Gibson, Tracy; Parks, Steen; Snyder, Sarah

2013-01-01

Current designs for inflatable or semi-rigidized structures for habitats and space applications use a multiple-layer construction, alternating thin layers with thicker, stronger layers, which produces a layered composite structure that is much better at resisting damage. Even though such composite structures or layered systems are robust, they can still be susceptible to penetration damage. The ability to detect damage to surfaces of inflatable or semi-rigid habitat structures is of great interest to NASA. Damage caused by impacts of foreign objects such as micrometeorites can rupture the shell of these structures, causing loss of critical hardware and/or the life of the crew. While not all impacts will have a catastrophic result, it will be very important to identify and locate areas of the exterior shell that have been damaged by impacts so that repairs (or other provisions) can be made to reduce the probability of shell wall rupture. This disclosure describes a system that will provide real-time data regarding the health of the inflatable shell or rigidized structures, and information related to the location and depth of impact damage. The innovation described here is a method of determining the size, location, and direction of damage in a multilayered structure. In the multi-dimensional damage detection system, layers of two-dimensional thin film detection layers are used to form a layered composite, with non-detection layers separating the detection layers. The non-detection layers may be either thicker or thinner than the detection layers. The thin-film damage detection layers are thin films of materials with a conductive grid or striped pattern. The conductive pattern may be applied by several methods, including printing, plating, sputtering, photolithography, and etching, and can include as many detection layers that are necessary for the structure construction or to afford the detection detail level required. The damage is detected using a detector or sensory system, which may include a time domain reflectometer, resistivity monitoring hardware, or other resistance-based systems. To begin, a layered composite consisting of thin-film damage detection layers separated by non-damage detection layers is fabricated. The damage detection layers are attached to a detector that provides details regarding the physical health of each detection layer individually. If damage occurs to any of the detection layers, a change in the electrical properties of the detection layers damaged occurs, and a response is generated. Real-time analysis of these responses will provide details regarding the depth, location, and size estimation of the damage. Multiple damages can be detected, and the extent (depth) of the damage can be used to generate prognostic information related to the expected lifetime of the layered composite system. The detection system can be fabricated very easily using off-the-shelf equipment, and the detection algorithms can be written and updated (as needed) to provide the level of detail needed based on the system being monitored. Connecting to the thin film detection layers is very easy as well. The truly unique feature of the system is its flexibility; the system can be designed to gather as much (or as little) information as the end user feels necessary. Individual detection layers can be turned on or off as necessary, and algorithms can be used to optimize performance. The system can be used to generate both diagnostic and prognostic information related to the health of layer composite structures, which will be essential if such systems are utilized for space exploration. The technology is also applicable to other in-situ health monitoring systems for structure integrity.

Persistent Topology and Metastable State in Conformational Dynamics

PubMed Central

Chang, Huang-Wei; Bacallado, Sergio; Pande, Vijay S.; Carlsson, Gunnar E.

2013-01-01

The large amount of molecular dynamics simulation data produced by modern computational models brings big opportunities and challenges to researchers. Clustering algorithms play an important role in understanding biomolecular kinetics from the simulation data, especially under the Markov state model framework. However, the ruggedness of the free energy landscape in a biomolecular system makes common clustering algorithms very sensitive to perturbations of the data. Here, we introduce a data-exploratory tool which provides an overview of the clustering structure under different parameters. The proposed Multi-Persistent Clustering analysis combines insights from recent studies on the dynamics of systems with dominant metastable states with the concept of multi-dimensional persistence in computational topology. We propose to explore the clustering structure of the data based on its persistence on scale and density. The analysis provides a systematic way to discover clusters that are robust to perturbations of the data. The dominant states of the system can be chosen with confidence. For the clusters on the borderline, the user can choose to do more simulation or make a decision based on their structural characteristics. Furthermore, our multi-resolution analysis gives users information about the relative potential of the clusters and their hierarchical relationship. The effectiveness of the proposed method is illustrated in three biomolecules: alanine dipeptide, Villin headpiece, and the FiP35 WW domain. PMID:23565139

Investigation of upwind, multigrid, multiblock numerical schemes for three dimensional flows. Volume 1: Runge-Kutta methods for a thin layer Navier-Stokes solver

NASA Technical Reports Server (NTRS)

Cannizzaro, Frank E.; Ash, Robert L.

1992-01-01

A state-of-the-art computer code has been developed that incorporates a modified Runge-Kutta time integration scheme, upwind numerical techniques, multigrid acceleration, and multi-block capabilities (RUMM). A three-dimensional thin-layer formulation of the Navier-Stokes equations is employed. For turbulent flow cases, the Baldwin-Lomax algebraic turbulence model is used. Two different upwind techniques are available: van Leer's flux-vector splitting and Roe's flux-difference splitting. Full approximation multi-grid plus implicit residual and corrector smoothing were implemented to enhance the rate of convergence. Multi-block capabilities were developed to provide geometric flexibility. This feature allows the developed computer code to accommodate any grid topology or grid configuration with multiple topologies. The results shown in this dissertation were chosen to validate the computer code and display its geometric flexibility, which is provided by the multi-block structure.

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

Gougar, Hans

This document outlines the development of a high fidelity, best estimate nuclear power plant severe transient simulation capability that will complement or enhance the integral system codes historically used for licensing and analysis of severe accidents. As with other tools in the Risk Informed Safety Margin Characterization (RISMC) Toolkit, the ultimate user of Enhanced Severe Transient Analysis and Prevention (ESTAP) capability is the plant decision-maker; the deliverable to that customer is a modern, simulation-based safety analysis capability, applicable to a much broader class of safety issues than is traditional Light Water Reactor (LWR) licensing analysis. Currently, the RISMC pathway’s majormore » emphasis is placed on developing RELAP-7, a next-generation safety analysis code, and on showing how to use RELAP-7 to analyze margin from a modern point of view: that is, by characterizing margin in terms of the probabilistic spectra of the “loads” applied to systems, structures, and components (SSCs), and the “capacity” of those SSCs to resist those loads without failing. The first objective of the ESTAP task, and the focus of one task of this effort, is to augment RELAP-7 analyses with user-selected multi-dimensional, multi-phase models of specific plant components to simulate complex phenomena that may lead to, or exacerbate, severe transients and core damage. Such phenomena include: coolant crossflow between PWR assemblies during a severe reactivity transient, stratified single or two-phase coolant flow in primary coolant piping, inhomogeneous mixing of emergency coolant water or boric acid with hot primary coolant, and water hammer. These are well-documented phenomena associated with plant transients but that are generally not captured in system codes. They are, however, generally limited to specific components, structures, and operating conditions. The second ESTAP task is to similarly augment a severe (post-core damage) accident integral analyses code with high fidelity simulations that would allow investigation of multi-dimensional, multi-phase containment phenomena that are only treated approximately in established codes.« less

Cosmic mass spectrometer

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Homology modeling and docking analyses of M. leprae Mur ligases reveals the common binding residues for structure based drug designing to eradicate leprosy.

PubMed

Shanmugam, Anusuya; Natarajan, Jeyakumar

2012-06-01

Multi drug resistance capacity for Mycobacterium leprae (MDR-Mle) demands the profound need for developing new anti-leprosy drugs. Since most of the drugs target a single enzyme, mutation in the active site renders the antibiotic ineffective. However, structural and mechanistic information on essential bacterial enzymes in a pathway could lead to the development of antibiotics that targets multiple enzymes. Peptidoglycan is an important component of the cell wall of M. leprae. The biosynthesis of bacterial peptidoglycan represents important targets for the development of new antibacterial drugs. Biosynthesis of peptidoglycan is a multi-step process that involves four key Mur ligase enzymes: MurC (EC:6.3.2.8), MurD (EC:6.3.2.9), MurE (EC:6.3.2.13) and MurF (EC:6.3.2.10). Hence in our work, we modeled the three-dimensional structure of the above Mur ligases using homology modeling method and analyzed its common binding features. The residues playing an important role in the catalytic activity of each of the Mur enzymes were predicted by docking these Mur ligases with their substrates and ATP. The conserved sequence motifs significant for ATP binding were predicted as the probable residues for structure based drug designing. Overall, the study was successful in listing significant and common binding residues of Mur enzymes in peptidoglycan pathway for multi targeted therapy.

Dimensional flow and fuzziness in quantum gravity: Emergence of stochastic spacetime

NASA Astrophysics Data System (ADS)

Calcagni, Gianluca; Ronco, Michele

2017-10-01

We show that the uncertainty in distance and time measurements found by the heuristic combination of quantum mechanics and general relativity is reproduced in a purely classical and flat multi-fractal spacetime whose geometry changes with the probed scale (dimensional flow) and has non-zero imaginary dimension, corresponding to a discrete scale invariance at short distances. Thus, dimensional flow can manifest itself as an intrinsic measurement uncertainty and, conversely, measurement-uncertainty estimates are generally valid because they rely on this universal property of quantum geometries. These general results affect multi-fractional theories, a recent proposal related to quantum gravity, in two ways: they can fix two parameters previously left free (in particular, the value of the spacetime dimension at short scales) and point towards a reinterpretation of the ultraviolet structure of geometry as a stochastic foam or fuzziness. This is also confirmed by a correspondence we establish between Nottale scale relativity and the stochastic geometry of multi-fractional models.

Fiber-based three-dimensional multi-mode interference device as efficient power divider and vector curvature sensor

NASA Astrophysics Data System (ADS)

Zhang, Ziyang; Fiebrandt, Julia; Haynes, Dionne; Sun, Kai; Madhav, Kalaga; Stoll, Andreas; Makan, Kirill; Makan, Vadim; Roth, Martin

2018-03-01

Three-dimensional multi-mode interference devices are demonstrated using a single-mode fiber (SMF) center-spliced to a section of polygon-shaped core multimode fiber (MMF). This simple structure can effectively generate well-localized self-focusing spots that match to the layout of a chosen multi-core fiber (MCF) as a launcher device. An optimized hexagon-core MMF can provide efficient coupling from a SMF to a 7-core MCF with an insertion loss of 0.6 dB and a power imbalance of 0.5 dB, while a square-core MMF can form a self-imaging pattern with symmetrically distributed 2 × 2, 3 × 3 or 4 × 4 spots. These spots can be directly received by a two-dimensional detector array. The device can work as a vector curvature sensor by comparing the relative power among the spots with a resolution of ∼0.1° over a 1.8 mm-long MMF.

Xarray: multi-dimensional data analysis in Python

NASA Astrophysics Data System (ADS)

Hoyer, Stephan; Hamman, Joe; Maussion, Fabien

2017-04-01

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

CELL5M: A geospatial database of agricultural indicators for Africa South of the Sahara.

PubMed

Koo, Jawoo; Cox, Cindy M; Bacou, Melanie; Azzarri, Carlo; Guo, Zhe; Wood-Sichra, Ulrike; Gong, Queenie; You, Liangzhi

2016-01-01

Recent progress in large-scale georeferenced data collection is widening opportunities for combining multi-disciplinary datasets from biophysical to socioeconomic domains, advancing our analytical and modeling capacity. Granular spatial datasets provide critical information necessary for decision makers to identify target areas, assess baseline conditions, prioritize investment options, set goals and targets and monitor impacts. However, key challenges in reconciling data across themes, scales and borders restrict our capacity to produce global and regional maps and time series. This paper provides overview, structure and coverage of CELL5M-an open-access database of geospatial indicators at 5 arc-minute grid resolution-and introduces a range of analytical applications and case-uses. CELL5M covers a wide set of agriculture-relevant domains for all countries in Africa South of the Sahara and supports our understanding of multi-dimensional spatial variability inherent in farming landscapes throughout the region.

Storage and retrieval of electromagnetic waves with orbital angular momentum via plasmon-induced transparency.

PubMed

Bai, Zhengyang; Xu, Datang; Huang, Guoxiang

2017-01-23

We propose a scheme to realize the storage and retrieval of high-dimensional electromagnetic waves with orbital angular momentum (OAM) via plasmon-induced transparency (PIT) in a metamaterial, which consists of an array of meta-atoms constructed by a metallic structure loaded with two varactors. We show that due to PIT effect the system allows the existence of shape-preserving dark-mode plasmonic polaritons, which are mixture of electromagnetic-wave modes and dark oscillatory modes of the meta-atoms and may carry various OAMs. We demonstrate that the slowdown, storage and retrieval of multi-mode electromagnetic waves with OAMs can be achieved through the active manipulation of a control field. Our work raises the possibility for realizing PIT-based spatial multi-mode memory of electromagnetic waves and is promising for practical application of information processing with large capacity by using room-temperature metamaterials.

Behavior analysis of video object in complicated background

NASA Astrophysics Data System (ADS)

Zhao, Wenting; Wang, Shigang; Liang, Chao; Wu, Wei; Lu, Yang

2016-10-01

This paper aims to achieve robust behavior recognition of video object in complicated background. Features of the video object are described and modeled according to the depth information of three-dimensional video. Multi-dimensional eigen vector are constructed and used to process high-dimensional data. Stable object tracing in complex scenes can be achieved with multi-feature based behavior analysis, so as to obtain the motion trail. Subsequently, effective behavior recognition of video object is obtained according to the decision criteria. What's more, the real-time of algorithms and accuracy of analysis are both improved greatly. The theory and method on the behavior analysis of video object in reality scenes put forward by this project have broad application prospect and important practical significance in the security, terrorism, military and many other fields.

Fast 2D NMR Spectroscopy for In vivo Monitoring of Bacterial Metabolism in Complex Mixtures.

PubMed

Dass, Rupashree; Grudzia Ż, Katarzyna; Ishikawa, Takao; Nowakowski, Michał; Dȩbowska, Renata; Kazimierczuk, Krzysztof

2017-01-01

The biological toolbox is full of techniques developed originally for analytical chemistry. Among them, spectroscopic experiments are very important source of atomic-level structural information. Nuclear magnetic resonance (NMR) spectroscopy, although very advanced in chemical and biophysical applications, has been used in microbiology only in a limited manner. So far, mostly one-dimensional 1 H experiments have been reported in studies of bacterial metabolism monitored in situ . However, low spectral resolution and limited information on molecular topology limits the usability of these methods. These problems are particularly evident in the case of complex mixtures, where spectral peaks originating from many compounds overlap and make the interpretation of changes in a spectrum difficult or even impossible. Often a suite of two-dimensional (2D) NMR experiments is used to improve resolution and extract structural information from internuclear correlations. However, for dynamically changing sample, like bacterial culture, the time-consuming sampling of so-called indirect time dimensions in 2D experiments is inefficient. Here, we propose the technique known from analytical chemistry and structural biology of proteins, i.e., time-resolved non-uniform sampling. The method allows application of 2D (and multi-D) experiments in the case of quickly varying samples. The indirect dimension here is sparsely sampled resulting in significant reduction of experimental time. Compared to conventional approach based on a series of 1D measurements, this method provides extraordinary resolution and is a real-time approach to process monitoring. In this study, we demonstrate the usability of the method on a sample of Escherichia coli culture affected by ampicillin and on a sample of Propionibacterium acnes , an acne causing bacterium, mixed with a dose of face tonic, which is a complicated, multi-component mixture providing complex NMR spectrum. Through our experiments we determine the exact concentration and time at which the anti-bacterial agents affect the bacterial metabolism. We show, that it is worth to extend the NMR toolbox for microbiology by including techniques of 2D z-TOCSY, for total "fingerprinting" of a sample and 2D 13 C-edited HSQC to monitor changes in concentration of metabolites in selected metabolic pathways.

Teaching Three-Dimensional Structural Chemistry Using Crystal Structure Databases. 3. The Cambridge Structural Database System: Information Content and Access Software in Educational Applications

ERIC Educational Resources Information Center

Battle, Gary M.; Allen, Frank H.; Ferrence, Gregory M.

2011-01-01

Parts 1 and 2 of this series described the educational value of experimental three-dimensional (3D) chemical structures determined by X-ray crystallography and retrieved from the crystallographic databases. In part 1, we described the information content of the Cambridge Structural Database (CSD) and discussed a representative teaching subset of…

Active Subspaces of Airfoil Shape Parameterizations

NASA Astrophysics Data System (ADS)

Grey, Zachary J.; Constantine, Paul G.

2018-05-01

Design and optimization benefit from understanding the dependence of a quantity of interest (e.g., a design objective or constraint function) on the design variables. A low-dimensional active subspace, when present, identifies important directions in the space of design variables; perturbing a design along the active subspace associated with a particular quantity of interest changes that quantity more, on average, than perturbing the design orthogonally to the active subspace. This low-dimensional structure provides insights that characterize the dependence of quantities of interest on design variables. Airfoil design in a transonic flow field with a parameterized geometry is a popular test problem for design methodologies. We examine two particular airfoil shape parameterizations, PARSEC and CST, and study the active subspaces present in two common design quantities of interest, transonic lift and drag coefficients, under each shape parameterization. We mathematically relate the two parameterizations with a common polynomial series. The active subspaces enable low-dimensional approximations of lift and drag that relate to physical airfoil properties. In particular, we obtain and interpret a two-dimensional approximation of both transonic lift and drag, and we show how these approximation inform a multi-objective design problem.

Teacher Effectiveness Examined as a System: Interpretive Structural Modeling and Facilitation Sessions with U.S. and Japanese Students

ERIC Educational Resources Information Center

Georgakopoulos, Alexia

2009-01-01

This study challenges narrow definitions of teacher effectiveness and uses a systems approach to investigate teacher effectiveness as a multi-dimensional, holistic phenomenon. The methods of Nominal Group Technique and Interpretive Structural Modeling were used to assist U.S. and Japanese students separately construct influence structures during…

DocCube: Multi-Dimensional Visualization and Exploration of Large Document Sets.

ERIC Educational Resources Information Center

Mothe, Josiane; Chrisment, Claude; Dousset, Bernard; Alaux, Joel

2003-01-01

Describes a user interface that provides global visualizations of large document sets to help users formulate the query that corresponds to their information needs. Highlights include concept hierarchies that users can browse to specify and refine information needs; knowledge discovery in databases and texts; and multidimensional modeling.…

Determination of secondary flow morphologies by wavelet analysis in a curved artery model with physiological inflow

NASA Astrophysics Data System (ADS)

Bulusu, Kartik V.; Hussain, Shadman; Plesniak, Michael W.

2014-11-01

Secondary flow vortical patterns in arterial curvatures have the potential to affect several cardiovascular phenomena, e.g., progression of atherosclerosis by altering wall shear stresses, carotid atheromatous disease, thoracic aortic aneurysms and Marfan's syndrome. Temporal characteristics of secondary flow structures vis-à-vis physiological (pulsatile) inflow waveform were explored by continuous wavelet transform (CWT) analysis of phase-locked, two-component, two-dimensional particle image velocimeter data. Measurements were made in a 180° curved artery test section upstream of the curvature and at the 90° cross-sectional plane. Streamwise, upstream flow rate measurements were analyzed using a one-dimensional antisymmetric wavelet. Cross-stream measurements at the 90° location of the curved artery revealed interesting multi-scale, multi-strength coherent secondary flow structures. An automated process for coherent structure detection and vortical feature quantification was applied to large ensembles of PIV data. Metrics such as the number of secondary flow structures, their sizes and strengths were generated at every discrete time instance of the physiological inflow waveform. An autonomous data post-processing method incorporating two-dimensional CWT for coherent structure detection was implemented. Loss of coherence in secondary flow structures during the systolic deceleration phase is observed in accordance with previous research. The algorithmic approach presented herein further elucidated the sensitivity and dependence of morphological changes in secondary flow structures on quasiperiodicity and magnitude of temporal gradients in physiological inflow conditions.

Computer simulation of ion beam analysis of laterally inhomogeneous materials

NASA Astrophysics Data System (ADS)

Mayer, M.

2016-03-01

The program STRUCTNRA for the simulation of ion beam analysis charged particle spectra from arbitrary two-dimensional distributions of materials is described. The code is validated by comparison to experimental backscattering data from a silicon grating on tantalum at different orientations and incident angles. Simulated spectra for several types of rough thin layers and a chessboard-like arrangement of materials as example for a multi-phase agglomerate material are presented. Ambiguities between back-scattering spectra from two-dimensional and one-dimensional sample structures are discussed.

Supramolecular self-assembly of graphene oxide and metal nanoparticles into stacked multilayers by means of a multitasking protein ring

NASA Astrophysics Data System (ADS)

Ardini, Matteo; Golia, Giordana; Passaretti, Paolo; Cimini, Annamaria; Pitari, Giuseppina; Giansanti, Francesco; Leandro, Luana Di; Ottaviano, Luca; Perrozzi, Francesco; Santucci, Sandro; Morandi, Vittorio; Ortolani, Luca; Christian, Meganne; Treossi, Emanuele; Palermo, Vincenzo; Angelucci, Francesco; Ippoliti, Rodolfo

2016-03-01

Graphene oxide (GO) is rapidly emerging worldwide as a breakthrough precursor material for next-generation devices. However, this requires the transition of its two-dimensional layered structure into more accessible three-dimensional (3D) arrays. Peroxiredoxins (Prx) are a family of multitasking redox enzymes, self-assembling into ring-like architectures. Taking advantage of both their symmetric structure and function, 3D reduced GO-based composites are hereby built up. Results reveal that the ``double-faced'' Prx rings can adhere flat on single GO layers and partially reduce them by their sulfur-containing amino acids, driving their stacking into 3D multi-layer reduced GO-Prx composites. This process occurs in aqueous solution at a very low GO concentration, i.e. 0.2 mg ml-1. Further, protein engineering allows the Prx ring to be enriched with metal binding sites inside its lumen. This feature is exploited to both capture presynthesized gold nanoparticles and grow in situ palladium nanoparticles paving the way to straightforward and ``green'' routes to 3D reduced GO-metal composite materials.Graphene oxide (GO) is rapidly emerging worldwide as a breakthrough precursor material for next-generation devices. However, this requires the transition of its two-dimensional layered structure into more accessible three-dimensional (3D) arrays. Peroxiredoxins (Prx) are a family of multitasking redox enzymes, self-assembling into ring-like architectures. Taking advantage of both their symmetric structure and function, 3D reduced GO-based composites are hereby built up. Results reveal that the ``double-faced'' Prx rings can adhere flat on single GO layers and partially reduce them by their sulfur-containing amino acids, driving their stacking into 3D multi-layer reduced GO-Prx composites. This process occurs in aqueous solution at a very low GO concentration, i.e. 0.2 mg ml-1. Further, protein engineering allows the Prx ring to be enriched with metal binding sites inside its lumen. This feature is exploited to both capture presynthesized gold nanoparticles and grow in situ palladium nanoparticles paving the way to straightforward and ``green'' routes to 3D reduced GO-metal composite materials. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr08632a

Modeling change from large-scale high-dimensional spatio-temporal array data

NASA Astrophysics Data System (ADS)

Lu, Meng; Pebesma, Edzer

2014-05-01

The massive data that come from Earth observation satellite and other sensors provide significant information for modeling global change. At the same time, the high dimensionality of the data has brought challenges in data acquisition, management, effective querying and processing. In addition, the output of earth system modeling tends to be data intensive and needs methodologies for storing, validation, analyzing and visualization, e.g. as maps. An important proportion of earth system observations and simulated data can be represented as multi-dimensional array data, which has received increasingly attention in big data management and spatial-temporal analysis. Study cases will be developed in natural science such as climate change, hydrological modeling, sediment dynamics, from which the addressing of big data problems is necessary. Multi-dimensional array-based database management and analytics system such as Rasdaman, SciDB, and R will be applied to these cases. From these studies will hope to learn the strengths and weaknesses of these systems, how they might work together or how semantics of array operations differ, through addressing the problems associated with big data. Research questions include: • How can we reduce dimensions spatially and temporally, or thematically? • How can we extend existing GIS functions to work on multidimensional arrays? • How can we combine data sets of different dimensionality or different resolutions? • Can map algebra be extended to an intelligible array algebra? • What are effective semantics for array programming of dynamic data driven applications? • In which sense are space and time special, as dimensions, compared to other properties? • How can we make the analysis of multi-spectral, multi-temporal and multi-sensor earth observation data easy?

A Three-Dimensional Target Depth-Resolution Method with a Single-Vector Sensor

PubMed Central

Zhao, Anbang; Bi, Xuejie; Hui, Juan; Zeng, Caigao; Ma, Lin

2018-01-01

This paper mainly studies and verifies the target number category-resolution method in multi-target cases and the target depth-resolution method of aerial targets. Firstly, target depth resolution is performed by using the sign distribution of the reactive component of the vertical complex acoustic intensity; the target category and the number resolution in multi-target cases is realized with a combination of the bearing-time recording information; and the corresponding simulation verification is carried out. The algorithm proposed in this paper can distinguish between the single-target multi-line spectrum case and the multi-target multi-line spectrum case. This paper presents an improved azimuth-estimation method for multi-target cases, which makes the estimation results more accurate. Using the Monte Carlo simulation, the feasibility of the proposed target number and category-resolution algorithm in multi-target cases is verified. In addition, by studying the field characteristics of the aerial and surface targets, the simulation results verify that there is only amplitude difference between the aerial target field and the surface target field under the same environmental parameters, and an aerial target can be treated as a special case of a surface target; the aerial target category resolution can then be realized based on the sign distribution of the reactive component of the vertical acoustic intensity so as to realize three-dimensional target depth resolution. By processing data from a sea experiment, the feasibility of the proposed aerial target three-dimensional depth-resolution algorithm is verified. PMID:29649173

A Three-Dimensional Target Depth-Resolution Method with a Single-Vector Sensor.

PubMed

Zhao, Anbang; Bi, Xuejie; Hui, Juan; Zeng, Caigao; Ma, Lin

2018-04-12

This paper mainly studies and verifies the target number category-resolution method in multi-target cases and the target depth-resolution method of aerial targets. Firstly, target depth resolution is performed by using the sign distribution of the reactive component of the vertical complex acoustic intensity; the target category and the number resolution in multi-target cases is realized with a combination of the bearing-time recording information; and the corresponding simulation verification is carried out. The algorithm proposed in this paper can distinguish between the single-target multi-line spectrum case and the multi-target multi-line spectrum case. This paper presents an improved azimuth-estimation method for multi-target cases, which makes the estimation results more accurate. Using the Monte Carlo simulation, the feasibility of the proposed target number and category-resolution algorithm in multi-target cases is verified. In addition, by studying the field characteristics of the aerial and surface targets, the simulation results verify that there is only amplitude difference between the aerial target field and the surface target field under the same environmental parameters, and an aerial target can be treated as a special case of a surface target; the aerial target category resolution can then be realized based on the sign distribution of the reactive component of the vertical acoustic intensity so as to realize three-dimensional target depth resolution. By processing data from a sea experiment, the feasibility of the proposed aerial target three-dimensional depth-resolution algorithm is verified.

Multi-target parallel processing approach for gene-to-structure determination of the influenza polymerase PB2 subunit.

PubMed

Armour, Brianna L; Barnes, Steve R; Moen, Spencer O; Smith, Eric; Raymond, Amy C; Fairman, James W; Stewart, Lance J; Staker, Bart L; Begley, Darren W; Edwards, Thomas E; Lorimer, Donald D

2013-06-28

Pandemic outbreaks of highly virulent influenza strains can cause widespread morbidity and mortality in human populations worldwide. In the United States alone, an average of 41,400 deaths and 1.86 million hospitalizations are caused by influenza virus infection each year (1). Point mutations in the polymerase basic protein 2 subunit (PB2) have been linked to the adaptation of the viral infection in humans (2). Findings from such studies have revealed the biological significance of PB2 as a virulence factor, thus highlighting its potential as an antiviral drug target. The structural genomics program put forth by the National Institute of Allergy and Infectious Disease (NIAID) provides funding to Emerald Bio and three other Pacific Northwest institutions that together make up the Seattle Structural Genomics Center for Infectious Disease (SSGCID). The SSGCID is dedicated to providing the scientific community with three-dimensional protein structures of NIAID category A-C pathogens. Making such structural information available to the scientific community serves to accelerate structure-based drug design. Structure-based drug design plays an important role in drug development. Pursuing multiple targets in parallel greatly increases the chance of success for new lead discovery by targeting a pathway or an entire protein family. Emerald Bio has developed a high-throughput, multi-target parallel processing pipeline (MTPP) for gene-to-structure determination to support the consortium. Here we describe the protocols used to determine the structure of the PB2 subunit from four different influenza A strains.

Information theoretic partitioning and confidence based weight assignment for multi-classifier decision level fusion in hyperspectral target recognition applications

NASA Astrophysics Data System (ADS)

Prasad, S.; Bruce, L. M.

2007-04-01

There is a growing interest in using multiple sources for automatic target recognition (ATR) applications. One approach is to take multiple, independent observations of a phenomenon and perform a feature level or a decision level fusion for ATR. This paper proposes a method to utilize these types of multi-source fusion techniques to exploit hyperspectral data when only a small number of training pixels are available. Conventional hyperspectral image based ATR techniques project the high dimensional reflectance signature onto a lower dimensional subspace using techniques such as Principal Components Analysis (PCA), Fisher's linear discriminant analysis (LDA), subspace LDA and stepwise LDA. While some of these techniques attempt to solve the curse of dimensionality, or small sample size problem, these are not necessarily optimal projections. In this paper, we present a divide and conquer approach to address the small sample size problem. The hyperspectral space is partitioned into contiguous subspaces such that the discriminative information within each subspace is maximized, and the statistical dependence between subspaces is minimized. We then treat each subspace as a separate source in a multi-source multi-classifier setup and test various decision fusion schemes to determine their efficacy. Unlike previous approaches which use correlation between variables for band grouping, we study the efficacy of higher order statistical information (using average mutual information) for a bottom up band grouping. We also propose a confidence measure based decision fusion technique, where the weights associated with various classifiers are based on their confidence in recognizing the training data. To this end, training accuracies of all classifiers are used for weight assignment in the fusion process of test pixels. The proposed methods are tested using hyperspectral data with known ground truth, such that the efficacy can be quantitatively measured in terms of target recognition accuracies.

Similarity from multi-dimensional scaling: solving the accuracy and diversity dilemma in information filtering.

PubMed

Zeng, Wei; Zeng, An; Liu, Hao; Shang, Ming-Sheng; Zhang, Yi-Cheng

2014-01-01

Recommender systems are designed to assist individual users to navigate through the rapidly growing amount of information. One of the most successful recommendation techniques is the collaborative filtering, which has been extensively investigated and has already found wide applications in e-commerce. One of challenges in this algorithm is how to accurately quantify the similarities of user pairs and item pairs. In this paper, we employ the multidimensional scaling (MDS) method to measure the similarities between nodes in user-item bipartite networks. The MDS method can extract the essential similarity information from the networks by smoothing out noise, which provides a graphical display of the structure of the networks. With the similarity measured from MDS, we find that the item-based collaborative filtering algorithm can outperform the diffusion-based recommendation algorithms. Moreover, we show that this method tends to recommend unpopular items and increase the global diversification of the networks in long term.

Extended Information Ratio for Portfolio Optimization Using Simulated Annealing with Constrained Neighborhood

NASA Astrophysics Data System (ADS)

Orito, Yukiko; Yamamoto, Hisashi; Tsujimura, Yasuhiro; Kambayashi, Yasushi

The portfolio optimizations are to determine the proportion-weighted combination in the portfolio in order to achieve investment targets. This optimization is one of the multi-dimensional combinatorial optimizations and it is difficult for the portfolio constructed in the past period to keep its performance in the future period. In order to keep the good performances of portfolios, we propose the extended information ratio as an objective function, using the information ratio, beta, prime beta, or correlation coefficient in this paper. We apply the simulated annealing (SA) to optimize the portfolio employing the proposed ratio. For the SA, we make the neighbor by the operation that changes the structure of the weights in the portfolio. In the numerical experiments, we show that our portfolios keep the good performances when the market trend of the future period becomes different from that of the past period.

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.

A quantitative study on magnesium alloy stent biodegradation.

PubMed

Gao, Yuanming; Wang, Lizhen; Gu, Xuenan; Chu, Zhaowei; Guo, Meng; Fan, Yubo

2018-06-06

Insufficient scaffolding time in the process of rapid corrosion is the main problem of magnesium alloy stent (MAS). Finite element method had been used to investigate corrosion of MAS. However, related researches mostly described all elements suffered corrosion in view of one-dimensional corrosion. Multi-dimensional corrosions significantly influence mechanical integrity of MAS structures such as edges and corners. In this study, the effects of multi-dimensional corrosion were studied using experiment quantitatively, then a phenomenological corrosion model was developed to consider these effects. We implemented immersion test with magnesium alloy (AZ31B) cubes, which had different numbers of exposed surfaces to analyze differences of dimension. It was indicated that corrosion rates of cubes are almost proportional to their exposed-surface numbers, especially when pitting corrosions are not marked. The cubes also represented the hexahedron elements in simulation. In conclusion, corrosion rate of every element accelerates by increasing corrosion-surface numbers in multi-dimensional corrosion. The damage ratios among elements with the same size are proportional to the ratios of corrosion-surface numbers under uniform corrosion. The finite element simulation using proposed model provided more details of changes of morphology and mechanics in scaffolding time by removing 25.7% of elements of MAS. The proposed corrosion model reflected the effects of multi-dimension on corrosions. It would be used to predict degradation process of MAS quantitatively. Copyright © 2018 Elsevier Ltd. All rights reserved.

Bridging the gap between supernovae and their remnants through multi-dimensional hydrodynamic modeling

NASA Astrophysics Data System (ADS)

Orlando, S.; Miceli, M.; Petruk, O.

2017-02-01

Supernova remnants (SNRs) are diffuse extended sources characterized by a complex morphology and a non-uniform distribution of ejecta. Such a morphology reflects pristine structures and features of the progenitor supernova (SN) and the early interaction of the SN blast wave with the inhomogeneous circumstellar medium (CSM). Deciphering the observations of SNRs might open the possibility to investigate the physical properties of both the interacting ejecta and the shocked CSM. This requires accurate numerical models which describe the evolution from the SN explosion to the remnant development and which connect the emission properties of the remnants to the progenitor SNe. Here we show how multi-dimensional SN-SNR hydrodynamic models have been very effective in deciphering observations of SNR Cassiopeia A and SN 1987A, thus unveiling the structure of ejecta in the immediate aftermath of the SN explosion and constraining the 3D pre-supernova structure and geometry of the environment surrounding the progenitor SN.

The role of the cubic structure in freezing of a supercooled water droplet on an ice substrate

NASA Astrophysics Data System (ADS)

Takahashi, T.; Kobayashi, T.

1983-12-01

The possibility of the formation of a metastable cubic (diamond) structure and its role in freezing of a supercooled water droplet on an ice substrate are discussed in terms of two-dimensional nucleation. The mode of stacking sequence of new layers formed by two-dimensional nucleation is divided into single and multi-nucleation according to the degree of supercooling and to the size of the supercooled droplet. In the case of single nucleation a frozen droplet develops into a complete hexagonal single crystal or an optically single crystal (containing discontinuous stacking faults). In the case of multi-nucleation attention is paid to the size effect and the stacking direction of the nucleus to calculate the waiting time in the nucleation. Then the frozen droplets are crystallographically divided into three categories: completely single crystals, optically single crystals (containing a small cubic structure, i.e. stacking faults) and polycrystals with a misorientation of 70.53° between the c-axes.

Quantitative Analysis of Cotton Canopy Size in Field Conditions Using a Consumer-Grade RGB-D Camera.

PubMed

Jiang, Yu; Li, Changying; Paterson, Andrew H; Sun, Shangpeng; Xu, Rui; Robertson, Jon

2017-01-01

Plant canopy structure can strongly affect crop functions such as yield and stress tolerance, and canopy size is an important aspect of canopy structure. Manual assessment of canopy size is laborious and imprecise, and cannot measure multi-dimensional traits such as projected leaf area and canopy volume. Field-based high throughput phenotyping systems with imaging capabilities can rapidly acquire data about plants in field conditions, making it possible to quantify and monitor plant canopy development. The goal of this study was to develop a 3D imaging approach to quantitatively analyze cotton canopy development in field conditions. A cotton field was planted with 128 plots, including four genotypes of 32 plots each. The field was scanned by GPhenoVision (a customized field-based high throughput phenotyping system) to acquire color and depth images with GPS information in 2016 covering two growth stages: canopy development, and flowering and boll development. A data processing pipeline was developed, consisting of three steps: plot point cloud reconstruction, plant canopy segmentation, and trait extraction. Plot point clouds were reconstructed using color and depth images with GPS information. In colorized point clouds, vegetation was segmented from the background using an excess-green (ExG) color filter, and cotton canopies were further separated from weeds based on height, size, and position information. Static morphological traits were extracted on each day, including univariate traits (maximum and mean canopy height and width, projected canopy area, and concave and convex volumes) and a multivariate trait (cumulative height profile). Growth rates were calculated for univariate static traits, quantifying canopy growth and development. Linear regressions were performed between the traits and fiber yield to identify the best traits and measurement time for yield prediction. The results showed that fiber yield was correlated with static traits after the canopy development stage ( R 2 = 0.35-0.71) and growth rates in early canopy development stages ( R 2 = 0.29-0.52). Multi-dimensional traits (e.g., projected canopy area and volume) outperformed one-dimensional traits, and the multivariate trait (cumulative height profile) outperformed univariate traits. The proposed approach would be useful for identification of quantitative trait loci (QTLs) controlling canopy size in genetics/genomics studies or for fiber yield prediction in breeding programs and production environments.

Enabling Efficient Intelligence Analysis in Degraded Environments

DTIC Science & Technology

2013-06-01

Magnets Grid widget for multidimensional information exploration ; and a record browser of Visual Summary Cards widget for fast visual identification of...evolution analysis; a Magnets Grid widget for multi- dimensional information exploration ; and a record browser of Visual Summary Cards widget for fast...attention and inattentional blindness. It also explores and develops various techniques to represent information in a salient way and provide efficient

Weighted similarity-based clustering of chemical structures and bioactivity data in early drug discovery.

PubMed

Perualila-Tan, Nolen Joy; Shkedy, Ziv; Talloen, Willem; Göhlmann, Hinrich W H; Moerbeke, Marijke Van; Kasim, Adetayo

2016-08-01

The modern process of discovering candidate molecules in early drug discovery phase includes a wide range of approaches to extract vital information from the intersection of biology and chemistry. A typical strategy in compound selection involves compound clustering based on chemical similarity to obtain representative chemically diverse compounds (not incorporating potency information). In this paper, we propose an integrative clustering approach that makes use of both biological (compound efficacy) and chemical (structural features) data sources for the purpose of discovering a subset of compounds with aligned structural and biological properties. The datasets are integrated at the similarity level by assigning complementary weights to produce a weighted similarity matrix, serving as a generic input in any clustering algorithm. This new analysis work flow is semi-supervised method since, after the determination of clusters, a secondary analysis is performed wherein it finds differentially expressed genes associated to the derived integrated cluster(s) to further explain the compound-induced biological effects inside the cell. In this paper, datasets from two drug development oncology projects are used to illustrate the usefulness of the weighted similarity-based clustering approach to integrate multi-source high-dimensional information to aid drug discovery. Compounds that are structurally and biologically similar to the reference compounds are discovered using this proposed integrative approach.

TOXCAST, A TOOL FOR CATEGORIZATION AND PRIORITIZATION OF CHEMICAL HAZARD BASED ON MULTI-DIMENSIONAL INFORMATION DOMAINS

EPA Science Inventory

Across several EPA Program Offices (e.g., OPPTS, OW, OAR), there is a clear need to develop strategies and methods to screen large numbers of chemicals for potential toxicity, and to use the resulting information to prioritize the use of testing resources towards those entities a...

Multi-Dimensional Pattern Discovery of Trajectories Using Contextual Information

NASA Astrophysics Data System (ADS)

Sharif, M.; Alesheikh, A. A.

2017-10-01

Movement of point objects are highly sensitive to the underlying situations and conditions during the movement, which are known as contexts. Analyzing movement patterns, while accounting the contextual information, helps to better understand how point objects behave in various contexts and how contexts affect their trajectories. One potential solution for discovering moving objects patterns is analyzing the similarities of their trajectories. This article, therefore, contextualizes the similarity measure of trajectories by not only their spatial footprints but also a notion of internal and external contexts. The dynamic time warping (DTW) method is employed to assess the multi-dimensional similarities of trajectories. Then, the results of similarity searches are utilized in discovering the relative movement patterns of the moving point objects. Several experiments are conducted on real datasets that were obtained from commercial airplanes and the weather information during the flights. The results yielded the robustness of DTW method in quantifying the commonalities of trajectories and discovering movement patterns with 80 % accuracy. Moreover, the results revealed the importance of exploiting contextual information because it can enhance and restrict movements.

The multi-dimensional measure of informed choice: a validation study.

PubMed

Michie, Susan; Dormandy, Elizabeth; Marteau, Theresa M

2002-09-01

The aim of this prospective study is to assess the reliability and validity of a multi-dimensional measure of informed choice (MMIC). Participants were 225 pregnant women in two general hospitals in the UK, women receiving low-risk results following serum screening for Down syndrome. The MMIC was administered before testing and the Ottawa Decisional Conflict Scale was administered 6 weeks later. The component scales of the MMIC, knowledge and attitude, were internally consistent (alpha values of 0.68 and 0.78, respectively). Those who made a choice categorised as informed using the MMIC rated their decision 6 weeks later as being more informed, better supported and of higher quality than women whose choice was categorised as uninformed. This provides evidence of predictive validity, whilst the lack of association between the MMIC and anxiety shows construct (discriminant) validity. Thus, the MMIC has been shown to be psychometrically robust in pregnant women offered the choice to undergo prenatal screening for Down syndrome and receiving a low-risk result. Replication of this finding in other groups, facing other decisions, with other outcomes, should be assessed in future research.

Some theorems and properties of multi-dimensional fractional Laplace transforms

NASA Astrophysics Data System (ADS)

Ahmood, Wasan Ajeel; Kiliçman, Adem

2016-06-01

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

Control electronics for a multi-laser/multi-detector scanning system

NASA Technical Reports Server (NTRS)

Kennedy, W.

1980-01-01

The Mars Rover Laser Scanning system uses a precision laser pointing mechanism, a photodetector array, and the concept of triangulation to perform three dimensional scene analysis. The system is used for real time terrain sensing and vision. The Multi-Laser/Multi-Detector laser scanning system is controlled by a digital device called the ML/MD controller. A next generation laser scanning system, based on the Level 2 controller, is microprocessor based. The new controller capabilities far exceed those of the ML/MD device. The first draft circuit details and general software structure are presented.

Scaling Properties of Dimensionality Reduction for Neural Populations and Network Models

PubMed Central

Cowley, Benjamin R.; Doiron, Brent; Kohn, Adam

2016-01-01

Recent studies have applied dimensionality reduction methods to understand how the multi-dimensional structure of neural population activity gives rise to brain function. It is unclear, however, how the results obtained from dimensionality reduction generalize to recordings with larger numbers of neurons and trials or how these results relate to the underlying network structure. We address these questions by applying factor analysis to recordings in the visual cortex of non-human primates and to spiking network models that self-generate irregular activity through a balance of excitation and inhibition. We compared the scaling trends of two key outputs of dimensionality reduction—shared dimensionality and percent shared variance—with neuron and trial count. We found that the scaling properties of networks with non-clustered and clustered connectivity differed, and that the in vivo recordings were more consistent with the clustered network. Furthermore, recordings from tens of neurons were sufficient to identify the dominant modes of shared variability that generalize to larger portions of the network. These findings can help guide the interpretation of dimensionality reduction outputs in regimes of limited neuron and trial sampling and help relate these outputs to the underlying network structure. PMID:27926936

Stationary Wavelet-based Two-directional Two-dimensional Principal Component Analysis for EMG Signal Classification

NASA Astrophysics Data System (ADS)

Ji, Yi; Sun, Shanlin; Xie, Hong-Bo

2017-06-01

Discrete wavelet transform (WT) followed by principal component analysis (PCA) has been a powerful approach for the analysis of biomedical signals. Wavelet coefficients at various scales and channels were usually transformed into a one-dimensional array, causing issues such as the curse of dimensionality dilemma and small sample size problem. In addition, lack of time-shift invariance of WT coefficients can be modeled as noise and degrades the classifier performance. In this study, we present a stationary wavelet-based two-directional two-dimensional principal component analysis (SW2D2PCA) method for the efficient and effective extraction of essential feature information from signals. Time-invariant multi-scale matrices are constructed in the first step. The two-directional two-dimensional principal component analysis then operates on the multi-scale matrices to reduce the dimension, rather than vectors in conventional PCA. Results are presented from an experiment to classify eight hand motions using 4-channel electromyographic (EMG) signals recorded in healthy subjects and amputees, which illustrates the efficiency and effectiveness of the proposed method for biomedical signal analysis.

Numerical simulation of two-dimensional flow over a heated carbon surface with coupled heterogeneous and homogeneous reactions

NASA Astrophysics Data System (ADS)

Johnson, Ryan Federick; Chelliah, Harsha Kumar

2017-01-01

For a range of flow and chemical timescales, numerical simulations of two-dimensional laminar flow over a reacting carbon surface were performed to understand further the complex coupling between heterogeneous and homogeneous reactions. An open-source computational package (OpenFOAM®) was used with previously developed lumped heterogeneous reaction models for carbon surfaces and a detailed homogeneous reaction model for CO oxidation. The influence of finite-rate chemical kinetics was explored by varying the surface temperatures from 1800 to 2600 K, while flow residence time effects were explored by varying the free-stream velocity up to 50 m/s. The reacting boundary layer structure dependence on the residence time was analysed by extracting the ratio of chemical source and species diffusion terms. The important contributions of radical species reactions on overall carbon removal rate, which is often neglected in multi-dimensional simulations, are highlighted. The results provide a framework for future development and validation of lumped heterogeneous reaction models based on multi-dimensional reacting flow configurations.

Development of Multi-perspective Diagnostics and Analysis Algorithms with Applications to Subsonic and Supersonic Combustors

NASA Astrophysics Data System (ADS)

Wickersham, Andrew Joseph

There are two critical research needs for the study of hydrocarbon combustion in high speed flows: 1) combustion diagnostics with adequate temporal and spatial resolution, and 2) mathematical techniques that can extract key information from large datasets. The goal of this work is to address these needs, respectively, by the use of high speed and multi-perspective chemiluminescence and advanced mathematical algorithms. To obtain the measurements, this work explored the application of high speed chemiluminescence diagnostics and the use of fiber-based endoscopes (FBEs) for non-intrusive and multi-perspective chemiluminescence imaging up to 20 kHz. Non-intrusive and full-field imaging measurements provide a wealth of information for model validation and design optimization of propulsion systems. However, it is challenging to obtain such measurements due to various implementation difficulties such as optical access, thermal management, and equipment cost. This work therefore explores the application of FBEs for non-intrusive imaging to supersonic propulsion systems. The FBEs used in this work are demonstrated to overcome many of the aforementioned difficulties and provided datasets from multiple angular positions up to 20 kHz in a supersonic combustor. The combustor operated on ethylene fuel at Mach 2 with an inlet stagnation temperature and pressure of approximately 640 degrees Fahrenheit and 70 psia, respectively. The imaging measurements were obtained from eight perspectives simultaneously, providing full-field datasets under such flow conditions for the first time, allowing the possibility of inferring multi-dimensional measurements. Due to the high speed and multi-perspective nature, such new diagnostic capability generates a large volume of data and calls for analysis algorithms that can process the data and extract key physics effectively. To extract the key combustion dynamics from the measurements, three mathematical methods were investigated in this work: Fourier analysis, proper orthogonal decomposition (POD), and wavelet analysis (WA). These algorithms were first demonstrated and tested on imaging measurements obtained from one perspective in a sub-sonic combustor (up to Mach 0.2). The results show that these algorithms are effective in extracting the key physics from large datasets, including the characteristic frequencies of flow-flame interactions especially during transient processes such as lean blow off and ignition. After these relatively simple tests and demonstrations, these algorithms were applied to process the measurements obtained from multi-perspective in the supersonic combustor. compared to past analyses (which have been limited to data obtained from one perspective only), the availability of data at multiple perspective provide further insights into the flame and flow structures in high speed flows. In summary, this work shows that high speed chemiluminescence is a simple yet powerful combustion diagnostic. Especially when combined with FBEs and the analyses algorithms described in this work, such diagnostics provide full-field imaging at high repetition rate in challenging flows. Based on such measurements, a wealth of information can be obtained from proper analysis algorithms, including characteristic frequency, dominating flame modes, and even multi-dimensional flame and flow structures.

Electrical Capacitance Volume Tomography: Design and Applications

PubMed Central

Wang, Fei; Marashdeh, Qussai; Fan, Liang-Shih; Warsito, Warsito

2010-01-01

This article reports recent advances and progress in the field of electrical capacitance volume tomography (ECVT). ECVT, developed from the two-dimensional electrical capacitance tomography (ECT), is a promising non-intrusive imaging technology that can provide real-time three-dimensional images of the sensing domain. Images are reconstructed from capacitance measurements acquired by electrodes placed on the outside boundary of the testing vessel. In this article, a review of progress on capacitance sensor design and applications to multi-phase flows is presented. The sensor shape, electrode configuration, and the number of electrodes that comprise three key elements of three-dimensional capacitance sensors are illustrated. The article also highlights applications of ECVT sensors on vessels of various sizes from 1 to 60 inches with complex geometries. Case studies are used to show the capability and validity of ECVT. The studies provide qualitative and quantitative real-time three-dimensional information of the measuring domain under study. Advantages of ECVT render it a favorable tool to be utilized for industrial applications and fundamental multi-phase flow research. PMID:22294905

Effect of randomness on multi-frequency aeroelastic responses resolved by Unsteady Adaptive Stochastic Finite Elements

NASA Astrophysics Data System (ADS)

Witteveen, Jeroen A. S.; Bijl, Hester

2009-10-01

The Unsteady Adaptive Stochastic Finite Elements (UASFE) method resolves the effect of randomness in numerical simulations of single-mode aeroelastic responses with a constant accuracy in time for a constant number of samples. In this paper, the UASFE framework is extended to multi-frequency responses and continuous structures by employing a wavelet decomposition pre-processing step to decompose the sampled multi-frequency signals into single-frequency components. The effect of the randomness on the multi-frequency response is then obtained by summing the results of the UASFE interpolation at constant phase for the different frequency components. Results for multi-frequency responses and continuous structures show a three orders of magnitude reduction of computational costs compared to crude Monte Carlo simulations in a harmonically forced oscillator, a flutter panel problem, and the three-dimensional transonic AGARD 445.6 wing aeroelastic benchmark subject to random fields and random parameters with various probability distributions.

Early differential sensitivity of evoked-potentials to local and global shape during the perception of three-dimensional objects.

PubMed

Leek, E Charles; Roberts, Mark; Oliver, Zoe J; Cristino, Filipe; Pegna, Alan J

2016-08-01

Here we investigated the time course underlying differential processing of local and global shape information during the perception of complex three-dimensional (3D) objects. Observers made shape matching judgments about pairs of sequentially presented multi-part novel objects. Event-related potentials (ERPs) were used to measure perceptual sensitivity to 3D shape differences in terms of local part structure and global shape configuration - based on predictions derived from hierarchical structural description models of object recognition. There were three types of different object trials in which stimulus pairs (1) shared local parts but differed in global shape configuration; (2) contained different local parts but shared global configuration or (3) shared neither local parts nor global configuration. Analyses of the ERP data showed differential amplitude modulation as a function of shape similarity as early as the N1 component between 146-215ms post-stimulus onset. These negative amplitude deflections were more similar between objects sharing global shape configuration than local part structure. Differentiation among all stimulus types was reflected in N2 amplitude modulations between 276-330ms. sLORETA inverse solutions showed stronger involvement of left occipitotemporal areas during the N1 for object discrimination weighted towards local part structure. The results suggest that the perception of 3D object shape involves parallel processing of information at local and global scales. This processing is characterised by relatively slow derivation of 'fine-grained' local shape structure, and fast derivation of 'coarse-grained' global shape configuration. We propose that the rapid early derivation of global shape attributes underlies the observed patterns of N1 amplitude modulations. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Enhancing multi-spot structured illumination microscopy with fluorescence difference

NASA Astrophysics Data System (ADS)

Ward, Edward N.; Torkelsen, Frida H.; Pal, Robert

2018-03-01

Structured illumination microscopy is a super-resolution technique used extensively in biological research. However, this technique is limited in the maximum possible resolution increase. Here we report the results of simulations of a novel enhanced multi-spot structured illumination technique. This method combines the super-resolution technique of difference microscopy with structured illumination deconvolution. Initial results give at minimum a 1.4-fold increase in resolution over conventional structured illumination in a low-noise environment. This new technique also has the potential to be expanded to further enhance axial resolution with three-dimensional difference microscopy. The requirement for precise pattern determination in this technique also led to the development of a new pattern estimation algorithm which proved more efficient and reliable than other methods tested.

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

USGS Publications Warehouse

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

2003-01-01

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

Design and Analysis of the Measurement Characteristics of a Bidirectional-Decoupling Over-Constrained Six-Dimensional Parallel-Mechanism Force Sensor

PubMed Central

Zhao, Tieshi; Zhao, Yanzhi; Hu, Qiangqiang; Ding, Shixing

2017-01-01

The measurement of large forces and the presence of errors due to dimensional coupling are significant challenges for multi-dimensional force sensors. To address these challenges, this paper proposes an over-constrained six-dimensional force sensor based on a parallel mechanism of steel ball structures as a measurement module. The steel ball structure can be subject to rolling friction instead of sliding friction, thus reducing the influence of friction. However, because the structure can only withstand unidirectional pressure, the application of steel balls in a six-dimensional force sensor is difficult. Accordingly, a new design of the sensor measurement structure was designed in this study. The static equilibrium and displacement compatibility equations of the sensor prototype’s over-constrained structure were established to obtain the transformation function, from which the forces in the measurement branches of the proposed sensor were then analytically derived. The sensor’s measurement characteristics were then analysed through numerical examples. Finally, these measurement characteristics were confirmed through calibration and application experiments. The measurement accuracy of the proposed sensor was determined to be 1.28%, with a maximum coupling error of 1.98%, indicating that the proposed sensor successfully overcomes the issues related to steel ball structures and provides sufficient accuracy. PMID:28867812

Cardiac Light-Sheet Fluorescent Microscopy for Multi-Scale and Rapid Imaging of Architecture and Function

NASA Astrophysics Data System (ADS)

Fei, Peng; Lee, Juhyun; Packard, René R. Sevag; Sereti, Konstantina-Ioanna; Xu, Hao; Ma, Jianguo; Ding, Yichen; Kang, Hanul; Chen, Harrison; Sung, Kevin; Kulkarni, Rajan; Ardehali, Reza; Kuo, C.-C. Jay; Xu, Xiaolei; Ho, Chih-Ming; Hsiai, Tzung K.

2016-03-01

Light Sheet Fluorescence Microscopy (LSFM) enables multi-dimensional and multi-scale imaging via illuminating specimens with a separate thin sheet of laser. It allows rapid plane illumination for reduced photo-damage and superior axial resolution and contrast. We hereby demonstrate cardiac LSFM (c-LSFM) imaging to assess the functional architecture of zebrafish embryos with a retrospective cardiac synchronization algorithm for four-dimensional reconstruction (3-D space + time). By combining our approach with tissue clearing techniques, we reveal the entire cardiac structures and hypertrabeculation of adult zebrafish hearts in response to doxorubicin treatment. By integrating the resolution enhancement technique with c-LSFM to increase the resolving power under a large field-of-view, we demonstrate the use of low power objective to resolve the entire architecture of large-scale neonatal mouse hearts, revealing the helical orientation of individual myocardial fibers. Therefore, our c-LSFM imaging approach provides multi-scale visualization of architecture and function to drive cardiovascular research with translational implication in congenital heart diseases.

Progress in multi-dimensional upwind differencing

NASA Technical Reports Server (NTRS)

Vanleer, Bram

1992-01-01

Multi-dimensional upwind-differencing schemes for the Euler equations are reviewed. On the basis of the first-order upwind scheme for a one-dimensional convection equation, the two approaches to upwind differencing are discussed: the fluctuation approach and the finite-volume approach. The usual extension of the finite-volume method to the multi-dimensional Euler equations is not entirely satisfactory, because the direction of wave propagation is always assumed to be normal to the cell faces. This leads to smearing of shock and shear waves when these are not grid-aligned. Multi-directional methods, in which upwind-biased fluxes are computed in a frame aligned with a dominant wave, overcome this problem, but at the expense of robustness. The same is true for the schemes incorporating a multi-dimensional wave model not based on multi-dimensional data but on an 'educated guess' of what they could be. The fluctuation approach offers the best possibilities for the development of genuinely multi-dimensional upwind schemes. Three building blocks are needed for such schemes: a wave model, a way to achieve conservation, and a compact convection scheme. Recent advances in each of these components are discussed; putting them all together is the present focus of a worldwide research effort. Some numerical results are presented, illustrating the potential of the new multi-dimensional schemes.

A lock-free priority queue design based on multi-dimensional linked lists

DOE PAGES

Dechev, Damian; Zhang, Deli

2015-04-03

The throughput of concurrent priority queues is pivotal to multiprocessor applications such as discrete event simulation, best-first search and task scheduling. Existing lock-free priority queues are mostly based on skiplists, which probabilistically create shortcuts in an ordered list for fast insertion of elements. The use of skiplists eliminates the need of global rebalancing in balanced search trees and ensures logarithmic sequential search time on average, but the worst-case performance is linear with respect to the input size. In this paper, we propose a quiescently consistent lock-free priority queue based on a multi-dimensional list that guarantees worst-case search time of O(logN)more » for key universe of size N. The novel multi-dimensional list (MDList) is composed of nodes that contain multiple links to child nodes arranged by their dimensionality. The insertion operation works by first injectively mapping the scalar key to a high-dimensional vector, then uniquely locating the target position by using the vector as coordinates. Nodes in MDList are ordered by their coordinate prefixes and the ordering property of the data structure is readily maintained during insertion without rebalancing nor randomization. Furthermore, in our experimental evaluation using a micro-benchmark, our priority queue achieves an average of 50% speedup over the state of the art approaches under high concurrency.« less

A lock-free priority queue design based on multi-dimensional linked lists

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

Dechev, Damian; Zhang, Deli

The throughput of concurrent priority queues is pivotal to multiprocessor applications such as discrete event simulation, best-first search and task scheduling. Existing lock-free priority queues are mostly based on skiplists, which probabilistically create shortcuts in an ordered list for fast insertion of elements. The use of skiplists eliminates the need of global rebalancing in balanced search trees and ensures logarithmic sequential search time on average, but the worst-case performance is linear with respect to the input size. In this paper, we propose a quiescently consistent lock-free priority queue based on a multi-dimensional list that guarantees worst-case search time of O(logN)more » for key universe of size N. The novel multi-dimensional list (MDList) is composed of nodes that contain multiple links to child nodes arranged by their dimensionality. The insertion operation works by first injectively mapping the scalar key to a high-dimensional vector, then uniquely locating the target position by using the vector as coordinates. Nodes in MDList are ordered by their coordinate prefixes and the ordering property of the data structure is readily maintained during insertion without rebalancing nor randomization. Furthermore, in our experimental evaluation using a micro-benchmark, our priority queue achieves an average of 50% speedup over the state of the art approaches under high concurrency.« less

Experimental violation of Bell inequalities for multi-dimensional systems

PubMed Central

Lo, Hsin-Pin; Li, Che-Ming; Yabushita, Atsushi; Chen, Yueh-Nan; Luo, Chih-Wei; Kobayashi, Takayoshi

2016-01-01

Quantum correlations between spatially separated parts of a d-dimensional bipartite system (d ≥ 2) have no classical analog. Such correlations, also called entanglements, are not only conceptually important, but also have a profound impact on information science. In theory the violation of Bell inequalities based on local realistic theories for d-dimensional systems provides evidence of quantum nonlocality. Experimental verification is required to confirm whether a quantum system of extremely large dimension can possess this feature, however it has never been performed for large dimension. Here, we report that Bell inequalities are experimentally violated for bipartite quantum systems of dimensionality d = 16 with the usual ensembles of polarization-entangled photon pairs. We also estimate that our entanglement source violates Bell inequalities for extremely high dimensionality of d > 4000. The designed scenario offers a possible new method to investigate the entanglement of multipartite systems of large dimensionality and their application in quantum information processing. PMID:26917246

An information model for managing multi-dimensional gridded data in a GIS

NASA Astrophysics Data System (ADS)

Xu, H.; Abdul-Kadar, F.; Gao, P.

2016-04-01

Earth observation agencies like NASA and NOAA produce huge volumes of historical, near real-time, and forecasting data representing terrestrial, atmospheric, and oceanic phenomena. The data drives climatological and meteorological studies, and underpins operations ranging from weather pattern prediction and forest fire monitoring to global vegetation analysis. These gridded data sets are distributed mostly as files in HDF, GRIB, or netCDF format and quantify variables like precipitation, soil moisture, or sea surface temperature, along one or more dimensions like time and depth. Although the data cube is a well-studied model for storing and analyzing multi-dimensional data, the GIS community remains in need of a solution that simplifies interactions with the data, and elegantly fits with existing database schemas and dissemination protocols. This paper presents an information model that enables Geographic Information Systems (GIS) to efficiently catalog very large heterogeneous collections of geospatially-referenced multi-dimensional rasters—towards providing unified access to the resulting multivariate hypercubes. We show how the implementation of the model encapsulates format-specific variations and provides unified access to data along any dimension. We discuss how this framework lends itself to familiar GIS concepts like image mosaics, vector field visualization, layer animation, distributed data access via web services, and scientific computing. Global data sources like MODIS from USGS and HYCOM from NOAA illustrate how one would employ this framework for cataloging, querying, and intuitively visualizing such hypercubes. ArcGIS—an established platform for processing, analyzing, and visualizing geospatial data—serves to demonstrate how this integration brings the full power of GIS to the scientific community.

A reflection TIE system for 3D inspection of wafer structures

NASA Astrophysics Data System (ADS)

Yan, Yizhen; Qu, Weijuan; Yan, Lei; Wang, Zhaomin; Zhao, Hongying

2017-10-01

A reflection TIE system consisting of a reflecting microscope and a 4f relay system is presented in this paper, with which the transport of intensity equation (TIE) is applied to reconstruct the three-dimensional (3D) profile of opaque micro objects like wafer structures for 3D inspection. As the shape of an object can affect the phases of waves, the 3D information of the object can be easily acquired with the multiple phases at different refocusing planes. By electronically controlled refocusing, multi-focal images can be captured and used in solving TIE to obtain the phase and depth of the object. In order to validate the accuracy and efficiency of the proposed system, the phase and depth values of several samples are calculated, and the experimental results is presented to demonstrate the performance of the system.

Enriching semantic knowledge bases for opinion mining in big data applications.

PubMed

Weichselbraun, A; Gindl, S; Scharl, A

2014-10-01

This paper presents a novel method for contextualizing and enriching large semantic knowledge bases for opinion mining with a focus on Web intelligence platforms and other high-throughput big data applications. The method is not only applicable to traditional sentiment lexicons, but also to more comprehensive, multi-dimensional affective resources such as SenticNet. It comprises the following steps: (i) identify ambiguous sentiment terms, (ii) provide context information extracted from a domain-specific training corpus, and (iii) ground this contextual information to structured background knowledge sources such as ConceptNet and WordNet. A quantitative evaluation shows a significant improvement when using an enriched version of SenticNet for polarity classification. Crowdsourced gold standard data in conjunction with a qualitative evaluation sheds light on the strengths and weaknesses of the concept grounding, and on the quality of the enrichment process.

The forced vibration of one-dimensional multi-coupled periodic structures: An application to finite element analysis

NASA Astrophysics Data System (ADS)

Mead, Denys J.

2009-01-01

A general theory for the forced vibration of multi-coupled one-dimensional periodic structures is presented as a sequel to a much earlier general theory for free vibration. Starting from the dynamic stiffness matrix of a single multi-coupled periodic element, it derives matrix equations for the magnitudes of the characteristic free waves excited in the whole structure by prescribed harmonic forces and/or displacements acting at a single periodic junction. The semi-infinite periodic system excited at its end is first analysed to provide the basis for analysing doubly infinite and finite periodic systems. In each case, total responses are found by considering just one periodic element. An already-known method of reducing the size of the computational problem is reexamined, expanded and extended in detail, involving reduction of the dynamic stiffness matrix of the periodic element through a wave-coordinate transformation. Use of the theory is illustrated in a combined periodic structure+finite element analysis of the forced harmonic in-plane motion of a uniform flat plate. Excellent agreement between the computed low-frequency responses and those predicted by simple engineering theories validates the detailed formulations of the paper. The primary purpose of the paper is not towards a specific application but to present a systematic and coherent forced vibration theory, carefully linked with the existing free-wave theory.

Generation Algorithm of Discrete Line in Multi-Dimensional Grids

NASA Astrophysics Data System (ADS)

Du, L.; Ben, J.; Li, Y.; Wang, R.

2017-09-01

Discrete Global Grids System (DGGS) is a kind of digital multi-resolution earth reference model, in terms of structure, it is conducive to the geographical spatial big data integration and mining. Vector is one of the important types of spatial data, only by discretization, can it be applied in grids system to make process and analysis. Based on the some constraint conditions, this paper put forward a strict definition of discrete lines, building a mathematic model of the discrete lines by base vectors combination method. Transforming mesh discrete lines issue in n-dimensional grids into the issue of optimal deviated path in n-minus-one dimension using hyperplane, which, therefore realizing dimension reduction process in the expression of mesh discrete lines. On this basis, we designed a simple and efficient algorithm for dimension reduction and generation of the discrete lines. The experimental results show that our algorithm not only can be applied in the two-dimensional rectangular grid, also can be applied in the two-dimensional hexagonal grid and the three-dimensional cubic grid. Meanwhile, when our algorithm is applied in two-dimensional rectangular grid, it can get a discrete line which is more similar to the line in the Euclidean space.

Three-Dimensional Structure and Evolution of Extreme-Ultraviolet Bright Points Observed by STEREO/SECCHI/EUVI

NASA Technical Reports Server (NTRS)

Kwon, Ryun Young; Chae, Jongchul; Davila, Joseph M.; Zhang, Jie; Moon, Yong-Jae; Poomvises, Watanachak; Jones, Shaela I.

2012-01-01

We unveil the three-dimensional structure of quiet-Sun EUV bright points and their temporal evolution by applying a triangulation method to time series of images taken by SECCHI/EUVI on board the STEREO twin spacecraft. For this study we examine the heights and lengths as the components of the three-dimensional structure of EUV bright points and their temporal evolutions. Among them we present three bright points which show three distinct changes in the height and length: decreasing, increasing, and steady. We show that the three distinct changes are consistent with the motions (converging, diverging, and shearing, respectively) of their photospheric magnetic flux concentrations. Both growth and shrinkage of the magnetic fluxes occur during their lifetimes and they are dominant in the initial and later phases, respectively. They are all multi-temperature loop systems which have hot loops (approx. 10(exp 6.2) K) overlying cooler ones (approx 10(exp 6.0) K) with cool legs (approx 10(exp 4.9) K) during their whole evolutionary histories. Our results imply that the multi-thermal loop system is a general character of EUV bright points. We conclude that EUV bright points are flaring loops formed by magnetic reconnection and their geometry may represent the reconnected magnetic field lines rather than the separator field lines.

Multi-Autonomous Ground-robotic International Challenge (MAGIC) 2010

DTIC Science & Technology

2010-12-14

SLAM technique since this setup, having a LIDAR with long-range high-accuracy measurement capability, allows accurate localization and mapping more...achieve the accuracy of 25cm due to the use of multi-dimensional information. OGM is, similarly to SLAM , carried out by using LIDAR data. The OGM...a result of the development and implementation of the hybrid feature-based/scan-matching Simultaneous Localization and Mapping ( SLAM ) technique, the

From supramolecular polymers to multi-component biomaterials.

PubMed

Goor, Olga J G M; Hendrikse, Simone I S; Dankers, Patricia Y W; Meijer, E W

2017-10-30

The most striking and general property of the biological fibrous architectures in the extracellular matrix (ECM) is the strong and directional interaction between biologically active protein subunits. These fibers display rich dynamic behavior without losing their architectural integrity. The complexity of the ECM taking care of many essential properties has inspired synthetic chemists to mimic these properties in artificial one-dimensional fibrous structures with the aim to arrive at multi-component biomaterials. Due to the dynamic character required for interaction with natural tissue, supramolecular biomaterials are promising candidates for regenerative medicine. Depending on the application area, and thereby the design criteria of these multi-component fibrous biomaterials, they are used as elastomeric materials or hydrogel systems. Elastomeric materials are designed to have load bearing properties whereas hydrogels are proposed to support in vitro cell culture. Although the chemical structures and systems designed and studied today are rather simple compared to the complexity of the ECM, the first examples of these functional supramolecular biomaterials reaching the clinic have been reported. The basic concept of many of these supramolecular biomaterials is based on their ability to adapt to cell behavior as a result of dynamic non-covalent interactions. In this review, we show the translation of one-dimensional supramolecular polymers into multi-component functional biomaterials for regenerative medicine applications.

Tissue Cartography: Compressing Bio-Image Data by Dimensional Reduction

PubMed Central

Heemskerk, Idse; Streichan, Sebastian J

2017-01-01

High data volumes produced by state-of-the-art optical microscopes encumber research. Taking advantage of the laminar structure of many biological specimens we developed a method that reduces data size and processing time by orders of magnitude, while disentangling signal. The Image Surface Analysis Environment that we implemented automatically constructs an atlas of 2D images for arbitrary shaped, dynamic, and possibly multi-layered “Surfaces of Interest”. Built-in correction for cartographic distortion assures no information on the surface is lost, making it suitable for quantitative analysis. We demonstrate our approach by application to 4D imaging of the D. melanogaster embryo and D. rerio beating heart. PMID:26524242

Chiral tunneling in gated inversion symmetric Weyl semimetal.

PubMed

Bai, Chunxu; Yang, Yanling; Chang, Kai

2016-02-18

Based on the chirality-resolved transfer-matrix method, we evaluate the chiral transport tunneling through Weyl semimetal multi-barrier structures created by periodic gates. It is shown that, in sharp contrast to the cases of three dimensional normal semimetals, the tunneling coefficient as a function of incident angle shows a strong anisotropic behavior. Importantly, the tunneling coefficients display an interesting periodic oscillation as a function of the crystallographic angle of the structures. With the increasement of the barriers, the tunneling current shows a Fabry-Perot type interferences. For superlattice structures, the fancy miniband effect has been revealed. Our results show that the angular dependence of the first bandgap can be reduced into a Lorentz formula. The disorder suppresses the oscillation of the tunneling conductance, but would not affect its average amplitude. This is in sharp contrast to that in multi-barrier conventional semiconductor structures. Moreover, numerical results for the dependence of the angularly averaged conductance on the incident energy and the structure parameters are presented and contrasted with those in two dimensional relativistic materials. Our work suggests that the gated Weyl semimetal opens a possible new route to access to new type nanoelectronic device.

Chiral tunneling in gated inversion symmetric Weyl semimetal

PubMed Central

Bai, Chunxu; Yang, Yanling; Chang, Kai

2016-01-01

Based on the chirality-resolved transfer-matrix method, we evaluate the chiral transport tunneling through Weyl semimetal multi-barrier structures created by periodic gates. It is shown that, in sharp contrast to the cases of three dimensional normal semimetals, the tunneling coefficient as a function of incident angle shows a strong anisotropic behavior. Importantly, the tunneling coefficients display an interesting periodic oscillation as a function of the crystallographic angle of the structures. With the increasement of the barriers, the tunneling current shows a Fabry-Perot type interferences. For superlattice structures, the fancy miniband effect has been revealed. Our results show that the angular dependence of the first bandgap can be reduced into a Lorentz formula. The disorder suppresses the oscillation of the tunneling conductance, but would not affect its average amplitude. This is in sharp contrast to that in multi-barrier conventional semiconductor structures. Moreover, numerical results for the dependence of the angularly averaged conductance on the incident energy and the structure parameters are presented and contrasted with those in two dimensional relativistic materials. Our work suggests that the gated Weyl semimetal opens a possible new route to access to new type nanoelectronic device. PMID:26888491

Evaluation of sequence alignments and oligonucleotide probes with respect to three-dimensional structure of ribosomal RNA using ARB software package

PubMed Central

Kumar, Yadhu; Westram, Ralf; Kipfer, Peter; Meier, Harald; Ludwig, Wolfgang

2006-01-01

Background Availability of high-resolution RNA crystal structures for the 30S and 50S ribosomal subunits and the subsequent validation of comparative secondary structure models have prompted the biologists to use three-dimensional structure of ribosomal RNA (rRNA) for evaluating sequence alignments of rRNA genes. Furthermore, the secondary and tertiary structural features of rRNA are highly useful and successfully employed in designing rRNA targeted oligonucleotide probes intended for in situ hybridization experiments. RNA3D, a program to combine sequence alignment information with three-dimensional structure of rRNA was developed. Integration into ARB software package, which is used extensively by the scientific community for phylogenetic analysis and molecular probe designing, has substantially extended the functionality of ARB software suite with 3D environment. Results Three-dimensional structure of rRNA is visualized in OpenGL 3D environment with the abilities to change the display and overlay information onto the molecule, dynamically. Phylogenetic information derived from the multiple sequence alignments can be overlaid onto the molecule structure in a real time. Superimposition of both statistical and non-statistical sequence associated information onto the rRNA 3D structure can be done using customizable color scheme, which is also applied to a textual sequence alignment for reference. Oligonucleotide probes designed by ARB probe design tools can be mapped onto the 3D structure along with the probe accessibility models for evaluation with respect to secondary and tertiary structural conformations of rRNA. Conclusion Visualization of three-dimensional structure of rRNA in an intuitive display provides the biologists with the greater possibilities to carry out structure based phylogenetic analysis. Coupled with secondary structure models of rRNA, RNA3D program aids in validating the sequence alignments of rRNA genes and evaluating probe target sites. Superimposition of the information derived from the multiple sequence alignment onto the molecule dynamically allows the researchers to observe any sequence inherited characteristics (phylogenetic information) in real-time environment. The extended ARB software package is made freely available for the scientific community via . PMID:16672074

CNNH_PSS: protein 8-class secondary structure prediction by convolutional neural network with highway.

PubMed

Zhou, Jiyun; Wang, Hongpeng; Zhao, Zhishan; Xu, Ruifeng; Lu, Qin

2018-05-08

Protein secondary structure is the three dimensional form of local segments of proteins and its prediction is an important problem in protein tertiary structure prediction. Developing computational approaches for protein secondary structure prediction is becoming increasingly urgent. We present a novel deep learning based model, referred to as CNNH_PSS, by using multi-scale CNN with highway. In CNNH_PSS, any two neighbor convolutional layers have a highway to deliver information from current layer to the output of the next one to keep local contexts. As lower layers extract local context while higher layers extract long-range interdependencies, the highways between neighbor layers allow CNNH_PSS to have ability to extract both local contexts and long-range interdependencies. We evaluate CNNH_PSS on two commonly used datasets: CB6133 and CB513. CNNH_PSS outperforms the multi-scale CNN without highway by at least 0.010 Q8 accuracy and also performs better than CNF, DeepCNF and SSpro8, which cannot extract long-range interdependencies, by at least 0.020 Q8 accuracy, demonstrating that both local contexts and long-range interdependencies are indeed useful for prediction. Furthermore, CNNH_PSS also performs better than GSM and DCRNN which need extra complex model to extract long-range interdependencies. It demonstrates that CNNH_PSS not only cost less computer resource, but also achieves better predicting performance. CNNH_PSS have ability to extracts both local contexts and long-range interdependencies by combing multi-scale CNN and highway network. The evaluations on common datasets and comparisons with state-of-the-art methods indicate that CNNH_PSS is an useful and efficient tool for protein secondary structure prediction.

Assessing the Suitability of Process and Information Technology in Supporting Tacit Knowledge Transfer

ERIC Educational Resources Information Center

Wu, Chien-Hsing; Kao, Shu-Chen; Shih, Lan-Hsin

2010-01-01

The transfer of tacit knowledge, one of the most important issues in the knowledge sharing context, needs a multi-dimensional perception in its process. Information technology's (IT) supporting role has already been addressed in the process of tacit knowledge transfer. However, IT has its own characteristics, and in turn, may have dissimilar…

Pair Formation of Hard Core Bosons in Flat Band Systems

NASA Astrophysics Data System (ADS)

Mielke, Andreas

2018-05-01

Hard core bosons in a large class of one or two dimensional flat band systems have an upper critical density, below which the ground states can be described completely. At the critical density, the ground states are Wigner crystals. If one adds a particle to the system at the critical density, the ground state and the low lying multi particle states of the system can be described as a Wigner crystal with an additional pair of particles. The energy band for the pair is separated from the rest of the multi-particle spectrum. The proofs use a Gerschgorin type of argument for block diagonally dominant matrices. In certain one-dimensional or tree-like structures one can show that the pair is localised, for example in the chequerboard chain. For this one-dimensional system with periodic boundary condition the energy band for the pair is flat, the pair is localised.

Application of high-resolution, two-dimensional 1H and 13C nuclear magnetic resonance techniques to the characterization of lipid oxidation products in autoxidized linoleoyl/linolenoylglycerols.

PubMed

Silwood, C J; Grootveld, M

1999-07-01

Subjection of polyunsaturated fatty acid (PUFA)-rich culinary oils to standard frying episodes generates a range of lipid oxidation products (LOP), including saturated and alpha,beta-unsaturated aldehydes which arise from the thermally induced fragmentation of conjugated hydroperoxydiene precursors. Since such LOP are damaging to human health, we have employed high-resolution, two-dimensional 1H-1H relayed coherence transfer, 1H-1H total correlation, 1H-13C heteronuclear multiple quantum correlation, and 1H-1H J-resolved nuclear magnetic resonance (NMR) spectroscopic techniques to further elucidate the molecular structures of these components present in (i) a model linoleoylglycerol compound (1,3-dilinolein) allowed to autoxidize at ambient temperature and (ii) PUFA-rich culinary oils subjected to repeated frying episodes. The above techniques readily facilitate the resolution of selected vinylic and aldehydic resonances of LOP which appear as complex overlapping patterns in conventional one-dimensional spectra, particularly when employed in combination with solvent-induced spectral shift modifications. Hence, much useful multi-component information regarding the identity and/or classification of glycerol-bound conjugated hydroperoxydiene and hydroxydiene adducts, and saturated and alpha,beta-unsaturated aldehydes, present in autoxidized PUFA matrices is provided by these NMR methods. Such molecular information is of much value to researchers investigating the deleterious health effects of LOP available in the diet.

Evolutionary tabu search strategies for the simultaneous registration of multiple atomic structures in cryo-EM reconstructions.

PubMed

Rusu, Mirabela; Birmanns, Stefan

2010-04-01

A structural characterization of multi-component cellular assemblies is essential to explain the mechanisms governing biological function. Macromolecular architectures may be revealed by integrating information collected from various biophysical sources - for instance, by interpreting low-resolution electron cryomicroscopy reconstructions in relation to the crystal structures of the constituent fragments. A simultaneous registration of multiple components is beneficial when building atomic models as it introduces additional spatial constraints to facilitate the native placement inside the map. The high-dimensional nature of such a search problem prevents the exhaustive exploration of all possible solutions. Here we introduce a novel method based on genetic algorithms, for the efficient exploration of the multi-body registration search space. The classic scheme of a genetic algorithm was enhanced with new genetic operations, tabu search and parallel computing strategies and validated on a benchmark of synthetic and experimental cryo-EM datasets. Even at a low level of detail, for example 35-40 A, the technique successfully registered multiple component biomolecules, measuring accuracies within one order of magnitude of the nominal resolutions of the maps. The algorithm was implemented using the Sculptor molecular modeling framework, which also provides a user-friendly graphical interface and enables an instantaneous, visual exploration of intermediate solutions. (c) 2009 Elsevier Inc. All rights reserved.

Multi-dimensional distribution of near-field ionospheric disturbances produced by the 2015 Mw7.8 Nepal earthquake

NASA Astrophysics Data System (ADS)

Tang, Jun; Yuan, Yunbin

2017-10-01

Ionospheric anomalies possibly associated with large earthquakes, particularly coseismic ionospheric disturbances, have been detected by global positioning system (GPS). A large Nepal earthquake with magnitude Mw7.8 occurred on April 25, 2015. In this paper, we investigate the multi-dimensional distribution of near-field coseismic ionospheric disturbances (CIDs) using total electron content (TEC) and computerized ionospheric tomography (CIT) from regional GPS observational data. The results show significant ionospheric TEC disturbances and interesting multi-dimensional structures around the main shock. Regarding the TEC changes, coseismic ionospheric disturbances occur approximately 10-20 min after the earthquake northeast and northwest of epicentre. The maximum ridge-to-trough amplitude of CIDs is up to approximately 0.90 TECU/min. Propagation velocities of the TEC disturbances are 1.27 ± 0.06 km/s and 1.91 ± 0.38 km/s. It is believed that the ionospheric disturbances are triggered by acoustic and Rayleigh waves. Tomographic results show that the three-dimensional distribution of ionospheric disturbances obviously increases at an altitude of 300 km above the surrounding epicentre, predominantly in the entire region between 200 km and 400 km. Significant ionospheric disturbances appear at 06:30 UT from tomographic images. This study reveals characteristics of an ionospheric anomaly caused by the Nepal earthquake.

A small molecule-based strategy for endothelial differentiation and three-dimensional morphogenesis from human embryonic stem cells.

PubMed

Geng, Yijie; Feng, Bradley

2016-07-01

The emerging models of human embryonic stem cell (hESC) self-organizing organoids provide a valuable in vitro platform for studying self-organizing processes that presumably mimic in vivo human developmental events. Here we report that through a chemical screen, we identified two novel and structurally similar small molecules BIR1 and BIR2 which robustly induced the self-organization of a balloon-shaped three-dimensional structure when applied to two-dimensional adherent hESC cultures in the absence of growth factors. Gene expression analyses and functional assays demonstrated an endothelial identity of this balloon-like structure, while cell surface marker analyses revealed a VE-cadherin(+)CD31(+)CD34(+)KDR(+)CD43(-) putative endothelial progenitor population. Furthermore, molecular marker labeling and morphological examinations characterized several other distinct DiI-Ac-LDL(+) multi-cellular modules and a VEGFR3(+) sprouting structure in the balloon cultures that likely represented intermediate structures of balloon-formation.

X-Ray Crystallography as a Tool to Determine Three-Dimensional Structures of Commercial Enzymes Subjected to Treatment in Pressurized Fluids.

PubMed

Feiten, Mirian Cristina; Di Luccio, Marco; Santos, Karine F; de Oliveira, Débora; Oliveira, J Vladimir

2017-06-01

The study of enzyme function often involves a multi-disciplinary approach. Several techniques are documented in the literature towards determining secondary and tertiary structures of enzymes, and X-ray crystallography is the most explored technique for obtaining three-dimensional structures of proteins. Knowledge of three-dimensional structures is essential to understand reaction mechanisms at the atomic level. Additionally, structures can be used to modulate or improve functional activity of enzymes by the production of small molecules that act as substrates/cofactors or by engineering selected mutants with enhanced biological activity. This paper presentes a short overview on how to streamline sample preparation for crystallographic studies of treated enzymes. We additionally revise recent developments on the effects of pressurized fluid treatment on activity and stability of commercial enzymes. Future directions and perspectives on the the role of crystallography as a tool to access the molecular mechanisms underlying enzymatic activity modulation upon treatment in pressurized fluids are also addressed.

One-pot growth of two-dimensional lateral heterostructures via sequential edge-epitaxy

NASA Astrophysics Data System (ADS)

Sahoo, Prasana K.; Memaran, Shahriar; Xin, Yan; Balicas, Luis; Gutiérrez, Humberto R.

2018-01-01

Two-dimensional heterojunctions of transition-metal dichalcogenides have great potential for application in low-power, high-performance and flexible electro-optical devices, such as tunnelling transistors, light-emitting diodes, photodetectors and photovoltaic cells. Although complex heterostructures have been fabricated via the van der Waals stacking of different two-dimensional materials, the in situ fabrication of high-quality lateral heterostructures with multiple junctions remains a challenge. Transition-metal-dichalcogenide lateral heterostructures have been synthesized via single-step, two-step or multi-step growth processes. However, these methods lack the flexibility to control, in situ, the growth of individual domains. In situ synthesis of multi-junction lateral heterostructures does not require multiple exchanges of sources or reactors, a limitation in previous approaches as it exposes the edges to ambient contamination, compromises the homogeneity of domain size in periodic structures, and results in long processing times. Here we report a one-pot synthetic approach, using a single heterogeneous solid source, for the continuous fabrication of lateral multi-junction heterostructures consisting of monolayers of transition-metal dichalcogenides. The sequential formation of heterojunctions is achieved solely by changing the composition of the reactive gas environment in the presence of water vapour. This enables selective control of the water-induced oxidation and volatilization of each transition-metal precursor, as well as its nucleation on the substrate, leading to sequential edge-epitaxy of distinct transition-metal dichalcogenides. Photoluminescence maps confirm the sequential spatial modulation of the bandgap, and atomic-resolution images reveal defect-free lateral connectivity between the different transition-metal-dichalcogenide domains within a single crystal structure. Electrical transport measurements revealed diode-like responses across the junctions. Our new approach offers greater flexibility and control than previous methods for continuous growth of transition-metal-dichalcogenide-based multi-junction lateral heterostructures. These findings could be extended to other families of two-dimensional materials, and establish a foundation for the development of complex and atomically thin in-plane superlattices, devices and integrated circuits.

Hybrid Grid Techniques for Propulsion Applications

NASA Technical Reports Server (NTRS)

Koomullil, Roy P.; Soni, Bharat K.; Thornburg, Hugh J.

1996-01-01

During the past decade, computational simulation of fluid flow for propulsion activities has progressed significantly, and many notable successes have been reported in the literature. However, the generation of a high quality mesh for such problems has often been reported as a pacing item. Hence, much effort has been expended to speed this portion of the simulation process. Several approaches have evolved for grid generation. Two of the most common are structured multi-block, and unstructured based procedures. Structured grids tend to be computationally efficient, and have high aspect ratio cells necessary for efficently resolving viscous layers. Structured multi-block grids may or may not exhibit grid line continuity across the block interface. This relaxation of the continuity constraint at the interface is intended to ease the grid generation process, which is still time consuming. Flow solvers supporting non-contiguous interfaces require specialized interpolation procedures which may not ensure conservation at the interface. Unstructured or generalized indexing data structures offer greater flexibility, but require explicit connectivity information and are not easy to generate for three dimensional configurations. In addition, unstructured mesh based schemes tend to be less efficient and it is difficult to resolve viscous layers. Recently hybrid or generalized element solution and grid generation techniques have been developed with the objective of combining the attractive features of both structured and unstructured techniques. In the present work, recently developed procedures for hybrid grid generation and flow simulation are critically evaluated, and compared to existing structured and unstructured procedures in terms of accuracy and computational requirements.

A light-trapping strategy for nanocrystalline silicon thin-film solar cells using three-dimensionally assembled nanoparticle structures.

PubMed

Ha, Kyungyeon; Jang, Eunseok; Jang, Segeun; Lee, Jong-Kwon; Jang, Min Seok; Choi, Hoseop; Cho, Jun-Sik; Choi, Mansoo

2016-02-05

We report three-dimensionally assembled nanoparticle structures inducing multiple plasmon resonances for broadband light harvesting in nanocrystalline silicon (nc-Si:H) thin-film solar cells. A three-dimensional multiscale (3DM) assembly of nanoparticles generated using a multi-pin spark discharge method has been accomplished over a large area under atmospheric conditions via ion-assisted aerosol lithography. The multiscale features of the sophisticated 3DM structures exhibit surface plasmon resonances at multiple frequencies, which increase light scattering and absorption efficiency over a wide spectral range from 350-1100 nm. The multiple plasmon resonances, together with the antireflection functionality arising from the conformally deposited top surface of the 3D solar cell, lead to a 22% and an 11% improvement in power conversion efficiency of the nc-Si:H thin-film solar cells compared to flat cells and cells employing nanoparticle clusters, respectively. Finite-difference time-domain simulations were also carried out to confirm that the improved device performance mainly originates from the multiple plasmon resonances generated from three-dimensionally assembled nanoparticle structures.

COREPA-M: NEW MULTI-DIMENSIONAL FUNCTIONALITY OF THE COREPA METHOD

EPA Science Inventory

The COmmon REactivity PAttern (COREPA) method is a recently developed pattern recognition technique accounting for conformational flexibility of chemicals in 3-D quantitative structure-activity relationships (QSARs). The method is based on the assumption that non-congeneric chemi...

Two-dimensional correlation infrared spectroscopy applied to analyzing and identifying the extracts of Baeckea frutescens medicinal materials.

PubMed

Adib, Adiana Mohamed; Jamaludin, Fadzureena; Kiong, Ling Sui; Hashim, Nuziah; Abdullah, Zunoliza

2014-08-05

Baeckea frutescens or locally known as Cucur atap is used as antibacterial, antidysentery, antipyretic and diuretic agent. In Malaysia and Indonesia, they are used as an ingredient of the traditional medicine given to mothers during confinement. A three-steps infra-red (IR) macro-fingerprinting method combining conventional IR spectra, and the secondary derivative spectra with two dimensional infrared correlation spectroscopy (2D-IR) have been proved to be effective methods to examine a complicated mixture such as herbal medicines. This study investigated the feasibility of employing multi-steps IR spectroscopy in order to study the main constituents of B. frutescens and its different extracts (extracted by chloroform, ethyl acetate, methanol and aqueous in turn). The findings indicated that FT-IR and 2D-IR can provide many holistic variation rules of chemical constituents. The structural information of the samples indicated that B. frutescens and its extracts contain a large amount of flavonoids, since some characteristic absorption peaks of flavonoids, such as ∼1600cm(-1), ∼1500cm(-1), ∼1450cm(-1), and ∼1270cm(-1) can be observed. The macroscopical fingerprint characters of FT-IR and 2D-IR spectra can not only provide the information of main chemical constituents in medicinal materials and their different extracts, but also compare the components differences among the similar samples. In conclusion, the multi-steps IR macro-fingerprint method is rapid, effective, visual and accurate for pharmaceutical research. Copyright © 2014 Elsevier B.V. All rights reserved.

Rapid acquisition of data dense solid-state CPMG NMR spectral sets using multi-dimensional statistical analysis

DOE PAGES

Mason, H. E.; Uribe, E. C.; Shusterman, J. A.

2018-01-01

Tensor-rank decomposition methods have been applied to variable contact time 29 Si{ 1 H} CP/CPMG NMR data sets to extract NMR dynamics information and dramatically decrease conventional NMR acquisition times.

Rapid acquisition of data dense solid-state CPMG NMR spectral sets using multi-dimensional statistical analysis

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

Mason, H. E.; Uribe, E. C.; Shusterman, J. A.

Tensor-rank decomposition methods have been applied to variable contact time 29 Si{ 1 H} CP/CPMG NMR data sets to extract NMR dynamics information and dramatically decrease conventional NMR acquisition times.

Multi-target Parallel Processing Approach for Gene-to-structure Determination of the Influenza Polymerase PB2 Subunit

PubMed Central

Moen, Spencer O.; Smith, Eric; Raymond, Amy C.; Fairman, James W.; Stewart, Lance J.; Staker, Bart L.; Begley, Darren W.; Edwards, Thomas E.; Lorimer, Donald D.

2013-01-01

Pandemic outbreaks of highly virulent influenza strains can cause widespread morbidity and mortality in human populations worldwide. In the United States alone, an average of 41,400 deaths and 1.86 million hospitalizations are caused by influenza virus infection each year 1. Point mutations in the polymerase basic protein 2 subunit (PB2) have been linked to the adaptation of the viral infection in humans 2. Findings from such studies have revealed the biological significance of PB2 as a virulence factor, thus highlighting its potential as an antiviral drug target. The structural genomics program put forth by the National Institute of Allergy and Infectious Disease (NIAID) provides funding to Emerald Bio and three other Pacific Northwest institutions that together make up the Seattle Structural Genomics Center for Infectious Disease (SSGCID). The SSGCID is dedicated to providing the scientific community with three-dimensional protein structures of NIAID category A-C pathogens. Making such structural information available to the scientific community serves to accelerate structure-based drug design. Structure-based drug design plays an important role in drug development. Pursuing multiple targets in parallel greatly increases the chance of success for new lead discovery by targeting a pathway or an entire protein family. Emerald Bio has developed a high-throughput, multi-target parallel processing pipeline (MTPP) for gene-to-structure determination to support the consortium. Here we describe the protocols used to determine the structure of the PB2 subunit from four different influenza A strains. PMID:23851357

3DSEM++: Adaptive and intelligent 3D SEM surface reconstruction.

PubMed

Tafti, Ahmad P; Holz, Jessica D; Baghaie, Ahmadreza; Owen, Heather A; He, Max M; Yu, Zeyun

2016-08-01

Structural analysis of microscopic objects is a longstanding topic in several scientific disciplines, such as biological, mechanical, and materials sciences. The scanning electron microscope (SEM), as a promising imaging equipment has been around for decades to determine the surface properties (e.g., compositions or geometries) of specimens by achieving increased magnification, contrast, and resolution greater than one nanometer. Whereas SEM micrographs still remain two-dimensional (2D), many research and educational questions truly require knowledge and facts about their three-dimensional (3D) structures. 3D surface reconstruction from SEM images leads to remarkable understanding of microscopic surfaces, allowing informative and qualitative visualization of the samples being investigated. In this contribution, we integrate several computational technologies including machine learning, contrario methodology, and epipolar geometry to design and develop a novel and efficient method called 3DSEM++ for multi-view 3D SEM surface reconstruction in an adaptive and intelligent fashion. The experiments which have been performed on real and synthetic data assert the approach is able to reach a significant precision to both SEM extrinsic calibration and its 3D surface modeling. Copyright © 2016 Elsevier Ltd. All rights reserved.

Heteroleptic metallosupramolecular racks, rectangles, and trigonal prisms: stoichiometry-controlled reversible interconversion.

PubMed

Neogi, Subhadip; Lorenz, Yvonne; Engeser, Marianne; Samanta, Debabrata; Schmittel, Michael

2013-06-17

A simple approach toward preparation of heteroleptic two-dimensional (2D) rectangles and three-dimensional (3D) triangular prisms is described utilizing the HETPYP (HETeroleptic PYridyl and Phenanthroline metal complexes) concept. By mixing metal-loaded linear bisphenanthrolines of varying lengths with diverse (multi)pyridine (py) ligands in a proper ratio, six different self-assembled architectures arise cleanly and spontaneously in the absence of any template. They are characterized by (1)H and DOSY NMR, ESI-FT-ICR mass spectrometry as well as by Job plots and UV-vis titrations. Density functional theory (DFT) computations provide information about each structure. A stoichiometry-controlled supramolecule-to-supramolecule interconversion based on the relative amounts of metal bisphenanthroline and bipyridine forces the rectangular assembly to reorganize to a rack architecture and back to the rectangle, as clearly supported by variable temperature and DOSY NMR as well as dynamic light scattering data. The highly dynamic nature of the assemblies represents a promising starting point for constitutional dynamic materials.

Beyond Low-Rank Representations: Orthogonal clustering basis reconstruction with optimized graph structure for multi-view spectral clustering.

PubMed

Wang, Yang; Wu, Lin

2018-07-01

Low-Rank Representation (LRR) is arguably one of the most powerful paradigms for Multi-view spectral clustering, which elegantly encodes the multi-view local graph/manifold structures into an intrinsic low-rank self-expressive data similarity embedded in high-dimensional space, to yield a better graph partition than their single-view counterparts. In this paper we revisit it with a fundamentally different perspective by discovering LRR as essentially a latent clustered orthogonal projection based representation winged with an optimized local graph structure for spectral clustering; each column of the representation is fundamentally a cluster basis orthogonal to others to indicate its members, which intuitively projects the view-specific feature representation to be the one spanned by all orthogonal basis to characterize the cluster structures. Upon this finding, we propose our technique with the following: (1) We decompose LRR into latent clustered orthogonal representation via low-rank matrix factorization, to encode the more flexible cluster structures than LRR over primal data objects; (2) We convert the problem of LRR into that of simultaneously learning orthogonal clustered representation and optimized local graph structure for each view; (3) The learned orthogonal clustered representations and local graph structures enjoy the same magnitude for multi-view, so that the ideal multi-view consensus can be readily achieved. The experiments over multi-view datasets validate its superiority, especially over recent state-of-the-art LRR models. Copyright © 2018 Elsevier Ltd. All rights reserved.

Enhancing multi-spot structured illumination microscopy with fluorescence difference

PubMed Central

Torkelsen, Frida H.

2018-01-01

Structured illumination microscopy is a super-resolution technique used extensively in biological research. However, this technique is limited in the maximum possible resolution increase. Here we report the results of simulations of a novel enhanced multi-spot structured illumination technique. This method combines the super-resolution technique of difference microscopy with structured illumination deconvolution. Initial results give at minimum a 1.4-fold increase in resolution over conventional structured illumination in a low-noise environment. This new technique also has the potential to be expanded to further enhance axial resolution with three-dimensional difference microscopy. The requirement for precise pattern determination in this technique also led to the development of a new pattern estimation algorithm which proved more efficient and reliable than other methods tested. PMID:29657751

Can all heritable biology really be reduced to a single dimension?

PubMed

Babbitt, Gregory A; Coppola, Erin E; Alawad, Mohammed A; Hudson, André O

2016-03-10

A long-held presupposition in the field of bioinformatics holds that genetic, and now even epigenetic 'information' can be abstracted from the physicochemical details of the macromolecular polymers in which it resides. It is perhaps rather ironic that this basic conjecture originated upon the first observations of DNA structure itself. This static model of DNA led very quickly to the conclusion that only the nucleobase sequence itself is rich enough in molecular complexity to replicate a complex biology. This idea has been pervasive throughout genomic science, higher education and popular culture ever since; to the point that most of us would accept it unquestioningly as fact. What is more alarming is that this conjecture is driving a significant portion of the technological development in modern genomics towards methods strongly rooted in DNA sequencing, thereby reducing a dynamic multi-dimensional biology into single-dimensional forms of data. Evidence countering this central tenet of bioinformatics has been quietly mounting over many decades, prompting some to propose that the genome must be studied from the perspective of its molecular reality, rather than as a body of information to be represented symbolically. Here, we explore the epistemological boundary between bioinformatics and molecular biology, and warn against an 'overtly' bioinformatic perspective. We review a selection of new bioinformatic methods that move beyond sequence-based approaches to include consideration of databased three dimensional structures. However, we also note that these hybrid methods still ignore the most important element of gene function when attempting to improve outcomes; the fourth dimension of molecular dynamics over time. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Satellite Imagery Analysis for Automated Global Food Security Forecasting

NASA Astrophysics Data System (ADS)

Moody, D.; Brumby, S. P.; Chartrand, R.; Keisler, R.; Mathis, M.; Beneke, C. M.; Nicholaeff, D.; Skillman, S.; Warren, M. S.; Poehnelt, J.

2017-12-01

The recent computing performance revolution has driven improvements in sensor, communication, and storage technology. Multi-decadal remote sensing datasets at the petabyte scale are now available in commercial clouds, with new satellite constellations generating petabytes/year of daily high-resolution global coverage imagery. Cloud computing and storage, combined with recent advances in machine learning, are enabling understanding of the world at a scale and at a level of detail never before feasible. We present results from an ongoing effort to develop satellite imagery analysis tools that aggregate temporal, spatial, and spectral information and that can scale with the high-rate and dimensionality of imagery being collected. We focus on the problem of monitoring food crop productivity across the Middle East and North Africa, and show how an analysis-ready, multi-sensor data platform enables quick prototyping of satellite imagery analysis algorithms, from land use/land cover classification and natural resource mapping, to yearly and monthly vegetative health change trends at the structural field level.

Multi-modal STEM-based tomography of HT-9 irradiated in FFTF

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

Field, Kevin G.; Eftink, Benjamin Paul; Saleh, Tarik A.

Under irradiation, point defects and defect clusters can agglomerate to form extended two and three dimensional (2D/3D) defects. The formation of defects can be synergistic in nature with one defect or defect-type influencing the formation and/or evolution of another. The resul is a need exists to perform advanced characterization where microstructures are accurately reproduced in 3D. Here, HT-9 neutron irradiated in the FFTF was used to evaluate the ability of multi-tilt STEM-based tomography to reproduce the fine-scale radiation-induced microstructure. High-efficiency STEM-EDS was used to provide both structural and chemical information during the 3D reconstruction. The results show similar results tomore » a previous two-tilt tomography study on the same material; the α' phase is denuded around the Ni-Si-Mn rich G-phase and cavities. It is concluded both tomography reconstruction techniques are readily viable and could add significant value to the advanced characterization capabilities for irradiated materials.« less

Quantification of source impact to PM using three-dimensional weighted factor model analysis on multi-site data

NASA Astrophysics Data System (ADS)

Shi, Guoliang; Peng, Xing; Huangfu, Yanqi; Wang, Wei; Xu, Jiao; Tian, Yingze; Feng, Yinchang; Ivey, Cesunica E.; Russell, Armistead G.

2017-07-01

Source apportionment technologies are used to understand the impacts of important sources of particulate matter (PM) air quality, and are widely used for both scientific studies and air quality management. Generally, receptor models apportion speciated PM data from a single sampling site. With the development of large scale monitoring networks, PM speciation are observed at multiple sites in an urban area. For these situations, the models should account for three factors, or dimensions, of the PM, including the chemical species concentrations, sampling periods and sampling site information, suggesting the potential power of a three-dimensional source apportionment approach. However, the principle of three-dimensional Parallel Factor Analysis (Ordinary PARAFAC) model does not always work well in real environmental situations for multi-site receptor datasets. In this work, a new three-way receptor model, called "multi-site three way factor analysis" model is proposed to deal with the multi-site receptor datasets. Synthetic datasets were developed and introduced into the new model to test its performance. Average absolute error (AAE, between estimated and true contributions) for extracted sources were all less than 50%. Additionally, three-dimensional ambient datasets from a Chinese mega-city, Chengdu, were analyzed using this new model to assess the application. Four factors are extracted by the multi-site WFA3 model: secondary source have the highest contributions (64.73 and 56.24 μg/m3), followed by vehicular exhaust (30.13 and 33.60 μg/m3), crustal dust (26.12 and 29.99 μg/m3) and coal combustion (10.73 and 14.83 μg/m3). The model was also compared to PMF, with general agreement, though PMF suggested a lower crustal contribution.

The Edinburgh Postnatal Depression Scale: Screening Tool for Postpartum Anxiety as Well? Findings from a Confirmatory Factor Analysis of the Hebrew Version.

PubMed

Bina, Rena; Harrington, Donna

2016-04-01

The Edinburgh Postnatal Depression Scale (EPDS) was originally created as a uni-dimensional scale to screen for postpartum depression (PPD); however, evidence from various studies suggests that it is a multi-dimensional scale measuring mainly anxiety in addition to depression. The factor structure of the EPDS seems to differ across various language translations, raising questions regarding its stability. This study examined the factor structure of the Hebrew version of the EPDS to assess whether it is uni- or multi-dimensional. Seven hundred and fifteen (n = 715) women were screened at 6 weeks postpartum using the Hebrew version of the EPDS. Confirmatory factor analysis (CFA) was used to test four models derived from the literature. Of the four CFA models tested, a 9-item two factor model fit the data best, with one factor representing an underlying depression construct and the other representing an underlying anxiety construct. for Practice The Hebrew version of the EPDS appears to consist of depression and anxiety sub-scales. Given the widespread PPD screening initiatives, anxiety symptoms should be addressed in addition to depressive symptoms, and a short scale, such as the EPDS, assessing both may be efficient.

ITQ-54: a multi-dimensional extra-large pore zeolite with 20 × 14 × 12-ring channels

DOE PAGES

Jiang, Jiuxing; Yun, Yifeng; Zou, Xiaodong; ...

2015-01-01

A multi-dimensional extra-large pore silicogermanate zeolite, named ITQ-54, has been synthesised by in situ decomposition of the N,N-dicyclohexylisoindolinium cation into the N-cyclohexylisoindolinium cation. Its structure was solved by 3D rotation electron diffraction (RED) from crystals of ca. 1 μm in size. The structure of ITQ-54 contains straight intersecting 20 × 14 × 12-ring channels along the three crystallographic axes and it is one of the few zeolites with extra-large channels in more than one direction. ITQ-54 has a framework density of 11.1 T atoms per 1000 Å 3, which is one of the lowest among the known zeolites. ITQ-54 wasmore » obtained together with GeO 2 as an impurity. A heavy liquid separation method was developed and successfully applied to remove this impurity from the zeolite. ITQ-54 is stable up to 600 °C and exhibits permanent porosity. The structure was further refined using powder X-ray diffraction (PXRD) data for both as-made and calcined samples.« less

Three-dimensional reconstruction of single-cell chromosome structure using recurrence plots.

PubMed

Hirata, Yoshito; Oda, Arisa; Ohta, Kunihiro; Aihara, Kazuyuki

2016-10-11

Single-cell analysis of the three-dimensional (3D) chromosome structure can reveal cell-to-cell variability in genome activities. Here, we propose to apply recurrence plots, a mathematical method of nonlinear time series analysis, to reconstruct the 3D chromosome structure of a single cell based on information of chromosomal contacts from genome-wide chromosome conformation capture (Hi-C) data. This recurrence plot-based reconstruction (RPR) method enables rapid reconstruction of a unique structure in single cells, even from incomplete Hi-C information.

Three-dimensional reconstruction of single-cell chromosome structure using recurrence plots

NASA Astrophysics Data System (ADS)

Hirata, Yoshito; Oda, Arisa; Ohta, Kunihiro; Aihara, Kazuyuki

2016-10-01

Single-cell analysis of the three-dimensional (3D) chromosome structure can reveal cell-to-cell variability in genome activities. Here, we propose to apply recurrence plots, a mathematical method of nonlinear time series analysis, to reconstruct the 3D chromosome structure of a single cell based on information of chromosomal contacts from genome-wide chromosome conformation capture (Hi-C) data. This recurrence plot-based reconstruction (RPR) method enables rapid reconstruction of a unique structure in single cells, even from incomplete Hi-C information.

Three-dimensional structures in the design of therapeutics targeting parasitic protozoa: reflections on the past, present and future.

PubMed

Hol, Wim G J

2015-05-01

Parasitic protozoa cause a range of diseases which threaten billions of human beings. They are responsible for tremendous mortality and morbidity in the least-developed areas of the world. Presented here is an overview of the evolution over the last three to four decades of structure-guided design of inhibitors, leads and drug candidates aiming at targets from parasitic protozoa. Target selection is a crucial and multi-faceted aspect of structure-guided drug design. The major impact of advances in molecular biology, genome sequencing and high-throughput screening is touched upon. The most advanced crystallographic techniques, including XFEL, have already been applied to structure determinations of drug targets from parasitic protozoa. Even cryo-electron microscopy is contributing to our understanding of the mode of binding of inhibitors to parasite ribosomes. A number of projects have been selected to illustrate how structural information has assisted in arriving at promising compounds that are currently being evaluated by pharmacological, pharmacodynamic and safety tests to assess their suitability as pharmaceutical agents. Structure-guided approaches are also applied to incorporate properties into compounds such that they are less likely to become the victim of resistance mechanisms. A great increase in the number of novel antiparasitic compounds will be needed in the future. These should then be combined into various multi-compound therapeutics to circumvent the diverse resistance mechanisms that render single-compound, or even multi-compound, drugs ineffective. The future should also see (i) an increase in the number of projects with a tight integration of structural biology, medicinal chemistry, parasitology and pharmaceutical sciences; (ii) the education of more `medicinal structural biologists' who are familiar with the properties that compounds need to have for a high probability of success in the later steps of the drug-development process; and (iii) the expansion of drug-development capabilities in middle- and low-income countries.

Three-dimensional structures in the design of therapeutics targeting parasitic protozoa: reflections on the past, present and future

PubMed Central

Hol, Wim G. J.

2015-01-01

Parasitic protozoa cause a range of diseases which threaten billions of human beings. They are responsible for tremendous mortality and morbidity in the least-developed areas of the world. Presented here is an overview of the evolution over the last three to four decades of structure-guided design of inhibitors, leads and drug candidates aiming at targets from parasitic protozoa. Target selection is a crucial and multi-faceted aspect of structure-guided drug design. The major impact of advances in molecular biology, genome sequencing and high-throughput screening is touched upon. The most advanced crystallographic techniques, including XFEL, have already been applied to structure determinations of drug targets from parasitic protozoa. Even cryo-electron microscopy is contributing to our understanding of the mode of binding of inhibitors to parasite ribosomes. A number of projects have been selected to illustrate how structural information has assisted in arriving at promising compounds that are currently being evaluated by pharmacological, pharmacodynamic and safety tests to assess their suitability as pharmaceutical agents. Structure-guided approaches are also applied to incorporate properties into compounds such that they are less likely to become the victim of resistance mechanisms. A great increase in the number of novel antiparasitic compounds will be needed in the future. These should then be combined into various multi-compound therapeutics to circumvent the diverse resistance mechanisms that render single-compound, or even multi-compound, drugs ineffective. The future should also see (i) an increase in the number of projects with a tight integration of structural biology, medicinal chemistry, parasitology and pharmaceutical sciences; (ii) the education of more ‘medicinal structural biologists’ who are familiar with the properties that compounds need to have for a high probability of success in the later steps of the drug-development process; and (iii) the expansion of drug-development capabilities in middle- and low-income countries. PMID:25945701

Multi-dimensional optical and laser-based diagnostics of low-temperature ionized plasma discharges

DOE PAGES

Barnat, Edward V.

2011-09-15

In this paper, a review of work centered on the utilization of multi-dimensional optical diagnostics to study phenomena arising in radiofrequency plasma discharges is given. The diagnostics range from passive techniques such as optical emission to more active techniques utilizing nanosecond lasers capable of both high temporal and spatial resolution. In this review, emphasis is placed on observations that would have been more difficult, if not impossible, to make without the use of such diagnostic techniques. Examples include the sheath structure around an electrode consisting of two different metals, double layers that arise in magnetized hydrogen discharges, or a largemore » region of depleted argon 1s 4 levels around a biased probe in an rf discharge.« less

MODELING SPATIAL VARIABILITY WITH ONE- AND MULTI-DIMENSIONAL MARKOV CHAINS. (R825433)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

Resistance and Security Index of Networks: Structural Information Perspective of Network Security

NASA Astrophysics Data System (ADS)

Li, Angsheng; Hu, Qifu; Liu, Jun; Pan, Yicheng

2016-06-01

Recently, Li and Pan defined the metric of the K-dimensional structure entropy of a structured noisy dataset G to be the information that controls the formation of the K-dimensional structure of G that is evolved by the rules, order and laws of G, excluding the random variations that occur in G. Here, we propose the notion of resistance of networks based on the one- and two-dimensional structural information of graphs. Given a graph G, we define the resistance of G, written , as the greatest overall number of bits required to determine the code of the module that is accessible via random walks with stationary distribution in G, from which the random walks cannot escape. We show that the resistance of networks follows the resistance law of networks, that is, for a network G, the resistance of G is , where and are the one- and two-dimensional structure entropies of G, respectively. Based on the resistance law, we define the security index of a network G to be the normalised resistance of G, that is, . We show that the resistance and security index are both well-defined measures for the security of the networks.

Resistance and Security Index of Networks: Structural Information Perspective of Network Security.

PubMed

Li, Angsheng; Hu, Qifu; Liu, Jun; Pan, Yicheng

2016-06-03

Recently, Li and Pan defined the metric of the K-dimensional structure entropy of a structured noisy dataset G to be the information that controls the formation of the K-dimensional structure of G that is evolved by the rules, order and laws of G, excluding the random variations that occur in G. Here, we propose the notion of resistance of networks based on the one- and two-dimensional structural information of graphs. Given a graph G, we define the resistance of G, written , as the greatest overall number of bits required to determine the code of the module that is accessible via random walks with stationary distribution in G, from which the random walks cannot escape. We show that the resistance of networks follows the resistance law of networks, that is, for a network G, the resistance of G is , where and are the one- and two-dimensional structure entropies of G, respectively. Based on the resistance law, we define the security index of a network G to be the normalised resistance of G, that is, . We show that the resistance and security index are both well-defined measures for the security of the networks.

Resistance and Security Index of Networks: Structural Information Perspective of Network Security

PubMed Central

Li, Angsheng; Hu, Qifu; Liu, Jun; Pan, Yicheng

2016-01-01

Recently, Li and Pan defined the metric of the K-dimensional structure entropy of a structured noisy dataset G to be the information that controls the formation of the K-dimensional structure of G that is evolved by the rules, order and laws of G, excluding the random variations that occur in G. Here, we propose the notion of resistance of networks based on the one- and two-dimensional structural information of graphs. Given a graph G, we define the resistance of G, written , as the greatest overall number of bits required to determine the code of the module that is accessible via random walks with stationary distribution in G, from which the random walks cannot escape. We show that the resistance of networks follows the resistance law of networks, that is, for a network G, the resistance of G is , where and are the one- and two-dimensional structure entropies of G, respectively. Based on the resistance law, we define the security index of a network G to be the normalised resistance of G, that is, . We show that the resistance and security index are both well-defined measures for the security of the networks. PMID:27255783

Corpus callosum segmentation using deep neural networks with prior information from multi-atlas images

NASA Astrophysics Data System (ADS)

Park, Gilsoon; Hong, Jinwoo; Lee, Jong-Min

2018-03-01

In human brain, Corpus Callosum (CC) is the largest white matter structure, connecting between right and left hemispheres. Structural features such as shape and size of CC in midsagittal plane are of great significance for analyzing various neurological diseases, for example Alzheimer's disease, autism and epilepsy. For quantitative and qualitative studies of CC in brain MR images, robust segmentation of CC is important. In this paper, we present a novel method for CC segmentation. Our approach is based on deep neural networks and the prior information generated from multi-atlas images. Deep neural networks have recently shown good performance in various image processing field. Convolutional neural networks (CNN) have shown outstanding performance for classification and segmentation in medical image fields. We used convolutional neural networks for CC segmentation. Multi-atlas based segmentation model have been widely used in medical image segmentation because atlas has powerful information about the target structure we want to segment, consisting of MR images and corresponding manual segmentation of the target structure. We combined the prior information, such as location and intensity distribution of target structure (i.e. CC), made from multi-atlas images in CNN training process for more improving training. The CNN with prior information showed better segmentation performance than without.

Investigating Hydrocarbon Seep Environments with High-Resolution, Three-Dimensional Geographic Visualizations.

NASA Astrophysics Data System (ADS)

Doolittle, D. F.; Gharib, J. J.; Mitchell, G. A.

2015-12-01

Detailed photographic imagery and bathymetric maps of the seafloor acquired by deep submergence vehicles such as Autonomous Underwater Vehicles (AUV) and Remotely Operated Vehicles (ROV) are expanding how scientists and the public view and ultimately understand the seafloor and the processes that modify it. Several recently acquired optical and acoustic datasets, collected during ECOGIG (Ecosystem Impacts of Oil and Gas Inputs to the Gulf) and other Gulf of Mexico expeditions using the National Institute for Undersea Science Technology (NIUST) Eagle Ray, and Mola Mola AUVs, have been fused with lower resolution data to create unique three-dimensional geovisualizations. Included in these data are multi-scale and multi-resolution visualizations over hydrocarbon seeps and seep related features. Resolution of the data range from 10s of mm to 10s of m. When multi-resolution data is integrated into a single three-dimensional visual environment, new insights into seafloor and seep processes can be obtained from the intuitive nature of three-dimensional data exploration. We provide examples and demonstrate how integration of multibeam bathymetry, seafloor backscatter data, sub-bottom profiler data, textured photomosaics, and hull-mounted multibeam acoustic midwater imagery are made into a series a three-dimensional geovisualizations of actively seeping sites and associated chemosynthetic communities. From these combined and merged datasets, insights on seep community structure, morphology, ecology, fluid migration dynamics, and process geomorphology can be investigated from new spatial perspectives. Such datasets also promote valuable inter-comparisons of sensor resolution and performance.

Nonlinear damping model for flexible structures. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Zang, Weijian

1990-01-01

The study of nonlinear damping problem of flexible structures is addressed. Both passive and active damping, both finite dimensional and infinite dimensional models are studied. In the first part, the spectral density and the correlation function of a single DOF nonlinear damping model is investigated. A formula for the spectral density is established with O(Gamma(sub 2)) accuracy based upon Fokker-Planck technique and perturbation. The spectral density depends upon certain first order statistics which could be obtained if the stationary density is known. A method is proposed to find the approximate stationary density explicitly. In the second part, the spectral density of a multi-DOF nonlinear damping model is investigated. In the third part, energy type nonlinear damping model in an infinite dimensional setting is studied.

A High-Order Transport Scheme for Collisional-Radiative and Nonequilibrium Plasma

DTIC Science & Technology

2009-02-06

of change of the temperature is obtained, ∂E ∂T ∂T ∂t = ∂ ∂x ( κs ∂T ∂x ) (7.6) Assuming a one- dimensional discretization on a uniformly- spaced ...oscillations nor a quantitative analysis of the multi- dimensional shock structure has been provided to date. This dissertation builds upon previous...high-enthalpy nonequilibrium plasmas and is the focus of much of this work. The plasma is described as

Multi-Step Lithiation of Tin Sulfide: An Investigation Using In Situ Electron Microscopy

DOE PAGES

Hwang, Sooyeon; Yao, Zhenpeng; Zhang, Lei; ...

2018-04-03

Two-dimensional metal sulfides have been widely explored as promising electrodes for lithium ion batteries since their two-dimensional layered structure allows lithium ions to intercalate between layers. For tin disulfide, the lithiation process proceeds via a sequence of three different types of reactions: intercalation, conversion, and alloying but the full scenario of reaction dynamics remains nebulous. In this paper, we investigate the dynamical process of the multi-step reactions using in situ electron microscopy and discover an intermediate rock-salt phase with the disordering of Li and Sn cations, after the initial 2-dimensional intercalation. The disordered cations occupy all the octahedral sites andmore » block the channels for intercalation, which alter the reaction pathways during further lithiation. Our first principles calculations of the non-equilibrium lithiation of SnS2 corroborate the energetic preference of the disordered rock-salt structure over known layered polymorphs. The in situ observations and calculations suggest a two-phase reaction nature for intercalation, disordering, and following conversion reactions. In addition, in situ de-lithiation observation confirms that the alloying reaction is reversible while the conversion reaction is not, which is consistent to the ex situ analysis. This work reveals the full lithiation characteristic of SnS2 and sheds light on the understanding of complex multistep reactions in two-dimensional materials.« less

Multi-Step Lithiation of Tin Sulfide: An Investigation Using In Situ Electron Microscopy

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

Hwang, Sooyeon; Yao, Zhenpeng; Zhang, Lei

Two-dimensional metal sulfides have been widely explored as promising electrodes for lithium ion batteries since their two-dimensional layered structure allows lithium ions to intercalate between layers. For tin disulfide, the lithiation process proceeds via a sequence of three different types of reactions: intercalation, conversion, and alloying but the full scenario of reaction dynamics remains nebulous. In this paper, we investigate the dynamical process of the multi-step reactions using in situ electron microscopy and discover an intermediate rock-salt phase with the disordering of Li and Sn cations, after the initial 2-dimensional intercalation. The disordered cations occupy all the octahedral sites andmore » block the channels for intercalation, which alter the reaction pathways during further lithiation. Our first principles calculations of the non-equilibrium lithiation of SnS2 corroborate the energetic preference of the disordered rock-salt structure over known layered polymorphs. The in situ observations and calculations suggest a two-phase reaction nature for intercalation, disordering, and following conversion reactions. In addition, in situ de-lithiation observation confirms that the alloying reaction is reversible while the conversion reaction is not, which is consistent to the ex situ analysis. This work reveals the full lithiation characteristic of SnS2 and sheds light on the understanding of complex multistep reactions in two-dimensional materials.« less

System for definition of the central-chest vasculature

NASA Astrophysics Data System (ADS)

Taeprasartsit, Pinyo; Higgins, William E.

2009-02-01

Accurate definition of the central-chest vasculature from three-dimensional (3D) multi-detector CT (MDCT) images is important for pulmonary applications. For instance, the aorta and pulmonary artery help in automatic definition of the Mountain lymph-node stations for lung-cancer staging. This work presents a system for defining major vascular structures in the central chest. The system provides automatic methods for extracting the aorta and pulmonary artery and semi-automatic methods for extracting the other major central chest arteries/veins, such as the superior vena cava and azygos vein. Automatic aorta and pulmonary artery extraction are performed by model fitting and selection. The system also extracts certain vascular structure information to validate outputs. A semi-automatic method extracts vasculature by finding the medial axes between provided important sites. Results of the system are applied to lymph-node station definition and guidance of bronchoscopic biopsy.

Development of a methodology for the detection of hospital financial outliers using information systems.

PubMed

Okada, Sachiko; Nagase, Keisuke; Ito, Ayako; Ando, Fumihiko; Nakagawa, Yoshiaki; Okamoto, Kazuya; Kume, Naoto; Takemura, Tadamasa; Kuroda, Tomohiro; Yoshihara, Hiroyuki

2014-01-01

Comparison of financial indices helps to illustrate differences in operations and efficiency among similar hospitals. Outlier data tend to influence statistical indices, and so detection of outliers is desirable. Development of a methodology for financial outlier detection using information systems will help to reduce the time and effort required, eliminate the subjective elements in detection of outlier data, and improve the efficiency and quality of analysis. The purpose of this research was to develop such a methodology. Financial outliers were defined based on a case model. An outlier-detection method using the distances between cases in multi-dimensional space is proposed. Experiments using three diagnosis groups indicated successful detection of cases for which the profitability and income structure differed from other cases. Therefore, the method proposed here can be used to detect outliers. Copyright © 2013 John Wiley & Sons, Ltd.

Enriching semantic knowledge bases for opinion mining in big data applications

PubMed Central

Weichselbraun, A.; Gindl, S.; Scharl, A.

2014-01-01

This paper presents a novel method for contextualizing and enriching large semantic knowledge bases for opinion mining with a focus on Web intelligence platforms and other high-throughput big data applications. The method is not only applicable to traditional sentiment lexicons, but also to more comprehensive, multi-dimensional affective resources such as SenticNet. It comprises the following steps: (i) identify ambiguous sentiment terms, (ii) provide context information extracted from a domain-specific training corpus, and (iii) ground this contextual information to structured background knowledge sources such as ConceptNet and WordNet. A quantitative evaluation shows a significant improvement when using an enriched version of SenticNet for polarity classification. Crowdsourced gold standard data in conjunction with a qualitative evaluation sheds light on the strengths and weaknesses of the concept grounding, and on the quality of the enrichment process. PMID:25431524

Multifocal microlens for bionic compound eye

NASA Astrophysics Data System (ADS)

Cao, Axiu; Wang, Jiazhou; Pang, Hui; Zhang, Man; Shi, Lifang; Deng, Qiling; Hu, Song

2017-10-01

Bionic compound eye optical element composed of multi-dimensional sub-eye microlenses plays an important role in miniaturizing the volume and weight of an imaging system. In this manuscript, we present a novel structure of the bionic compound eye with multiple focal lengths. By the division of the microlens into two concentric radial zones including the inner zone and the outer zone with independent radius, the sub-eye which is a multi-level micro-scale structure can be formed with multiple focal lengths. The imaging capability of the structure has been simulated. The results show that the optical information in different depths can be acquired by the structure. Meanwhile, the parameters including aperture and radius of the two zones, which have an influence on the imaging quality have been analyzed and discussed. With the increasing of the ratio of inner and outer aperture, the imaging quality of the inner zone is becoming better, and instead the outer zone will become worse. In addition, through controlling the radius of the inner and outer zone independently, the design of sub-eye with different focal lengths can be realized. With the difference between the radius of the inner and outer zone becoming larger, the imaging resolution of the sub-eye will decrease. Therefore, the optimization of the multifocal structure should be carried out according to the actual imaging quality demands. Meanwhile, this study can provide references for the further applications of multifocal microlens in bionic compound eye.

Multi-resonant scatterers in sonic crystals: Locally multi-resonant acoustic metamaterial

NASA Astrophysics Data System (ADS)

Romero-García, V.; Krynkin, A.; Garcia-Raffi, L. M.; Umnova, O.; Sánchez-Pérez, J. V.

2013-01-01

An acoustic metamaterial made of a two-dimensional (2D) periodic array of multi-resonant acoustic scatterers is analyzed both experimentally and theoretically. The building blocks consist of a combination of elastic beams of low-density polyethylene foam (LDPF) with cavities of known area. Elastic resonances of the beams and acoustic resonances of the cavities can be excited by sound producing several attenuation peaks in the low frequency range. Due to this behavior the periodic array with long wavelength multi-resonant structural units can be classified as a locally multi-resonant acoustic metamaterial (LMRAM) with strong dispersion of its effective properties.The results presented in this paper could be used to design effective tunable acoustic filters for the low frequency range.

Information networks in the stock market based on the distance of the multi-attribute dimensions between listed companies

NASA Astrophysics Data System (ADS)

Liu, Qian; Li, Huajiao; Liu, Xueyong; Jiang, Meihui

2018-04-01

In the stock market, there are widespread information connections between economic agents. Listed companies can obtain mutual information about investment decisions from common shareholders, and the extent of sharing information often determines the relationships between listed companies. Because different shareholder compositions and investment shares lead to different formations of the company's governance mechanisms, we map the investment relationships between shareholders to the multi-attribute dimensional spaces of the listed companies (each shareholder investment in a company is a company dimension). Then, we construct the listed company's information network based on co-shareholder relationships. The weights for the edges in the information network are measured with the Euclidean distance between the listed companies in the multi-attribute dimension space. We define two indices to analyze the information network's features. We conduct an empirical study that analyzes Chinese listed companies' information networks. The results from the analysis show that with the diversification and decentralization of shareholder investments, almost all Chinese listed companies exchanged information through common shareholder relationships, and there is a gradual reduction in information sharing capacity between listed companies that have common shareholders. This network analysis has benefits for risk management and portfolio investments.

Communications for Engineers: A Multi-Dimensional Approach.

ERIC Educational Resources Information Center

Winkler, Victoria M.

The development and content of a freshman engineering program that stresses writing, speaking, and listening skills are described. In conjunction with writing expository essays and research reports, the students make demonstrations, deliver informative and persuasive speeches, and participate in panel discussions and debates. Videotaping,…

Learning Analytics for Networked Learning Models

ERIC Educational Resources Information Center

Joksimovic, Srecko; Hatala, Marek; Gaševic, Dragan

2014-01-01

Teaching and learning in networked settings has attracted significant attention recently. The central topic of networked learning research is human-human and human-information interactions occurring within a networked learning environment. The nature of these interactions is highly complex and usually requires a multi-dimensional approach to…

Sandwiched polymer fibre in fibrin matrices for the dictation of endothelial cells undergoing angiogenesis

NASA Astrophysics Data System (ADS)

Sukmana, I.; Djuansjah, J. R. P.

2013-04-01

We present here a three-dimensional (3D) sandwich system made by poly(ethylene terephthalate) (PET) fibre and fibrin extracellular matrix (ECM) for endothelial cell dictation and angiogenesis guidance. In this three-dimensional system, Human Umbilical Vein Endothelial cells (HUVECs) were firstly cultured for 2 (two) days to cover the PET fibre before sandwiched in two layer fibrin gel containing HUVECs. After 4 (four) days of culture, cel-to-cel connection, tube-like structure and multi-cellular lumen formation were then assessed and validated. Phase contrast and fluorescence imaging using an inverted microscope were used to determine cell-to-cell and cell-ECM interactions. Laser scanning confocal microscopy and histological techniques were used to confirm the development of tube-like structure and multi-cellular lumen formation. This study shows that polymer fibres sandwiched in fibrin gel can be used to dictate endothelial cells undergoing angiogenesis with potential application in cancer and cardiovascular study and tissue engineering vascularisation.

Three-dimensional minority-carrier collection channels at shunt locations in silicon solar cells

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

Guthrey, Harvey; Johnston, Steve; Weiss, Dirk N.

2016-10-01

In this contribution, we demonstrate the value of using a multiscale multi-technique characterization approach to study the performance-limiting defects in multi-crystalline silicon (mc-Si) photovoltaic devices. The combination of dark lock-in thermography (DLIT) imaging, electron beam induced current imaging, and both transmission and scanning transmission electron microscopy (TEM/STEM) on the same location revealed the nanoscale origin of the optoelectronic properties of shunts visible at the device scale. Our site-specific correlative approach identified the shunt behavior to be a result of three-dimensional inversion channels around structural defects decorated with oxide precipitates. These inversion channels facilitate enhanced minority-carrier transport that results in themore » increased heating observed through DLIT imaging. The definitive connection between the nanoscale structure and chemistry of the type of shunt investigated here allows photovoltaic device manufacturers to immediately address the oxygen content of their mc-Si absorber material when such features are present, instead of engaging in costly characterization.« less

Enhanced use of phylogenetic data to inform public health approaches to HIV among MSM

PubMed Central

German, Danielle; Grabowski, Mary Kate; Beyrer, Chris

2017-01-01

The multi-dimensional nature and continued evolution of HIV epidemics among men who have sex with men (MSM) requires innovative intervention approaches. Strategies are needed that recognize the individual, social, and structural factors driving HIV transmission; that can pinpoint networks with heightened transmission risk; and that can help target intervention in real-time. HIV phylogenetics is a rapidly evolving field with strong promise for informing innovative responses to the HIV epidemic among MSM. Currently, HIV phylogenetic insights are providing new understandings of characteristics of HIV epidemics involving MSM, social networks influencing transmission, characteristics of HIV transmission clusters involving MSM, targets for antiretroviral and other prevention strategies, and dynamics of emergent epidemics. Maximizing the potential of HIV phylogenetics for HIV responses among MSM will require attention to key methodological challenges and ethical considerations, as well as resolving key implementation and scientific questions. Enhanced and integrated use of HIV surveillance, socio-behavioral, and phylogenetic data resources are becoming increasingly critical for informing public health approaches to HIV among MSM. PMID:27584826

Similarity from Multi-Dimensional Scaling: Solving the Accuracy and Diversity Dilemma in Information Filtering

PubMed Central

Zeng, Wei; Zeng, An; Liu, Hao; Shang, Ming-Sheng; Zhang, Yi-Cheng

2014-01-01

Recommender systems are designed to assist individual users to navigate through the rapidly growing amount of information. One of the most successful recommendation techniques is the collaborative filtering, which has been extensively investigated and has already found wide applications in e-commerce. One of challenges in this algorithm is how to accurately quantify the similarities of user pairs and item pairs. In this paper, we employ the multidimensional scaling (MDS) method to measure the similarities between nodes in user-item bipartite networks. The MDS method can extract the essential similarity information from the networks by smoothing out noise, which provides a graphical display of the structure of the networks. With the similarity measured from MDS, we find that the item-based collaborative filtering algorithm can outperform the diffusion-based recommendation algorithms. Moreover, we show that this method tends to recommend unpopular items and increase the global diversification of the networks in long term. PMID:25343243

Situation exploration in a persistent surveillance system with multidimensional data

NASA Astrophysics Data System (ADS)

Habibi, Mohammad S.

2013-03-01

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

Forward modeling and inversion of tensor CSAMT in 3D anisotropic media

NASA Astrophysics Data System (ADS)

Wang, Tao; Wang, Kun-Peng; Tan, Han-Dong

2017-12-01

Tensor controlled-source audio-frequency magnetotellurics (CSAMT) can yield information about electric and magnetic fields owing to its multi-transmitter configuration compared with the common scalar CSAMT. The most current theories, numerical simulations, and inversion of tensor CSAMT are based on far-field measurements and the assumption that underground media have isotropic resistivity. We adopt a three-dimensional (3D) staggered-grid finite difference numerical simulation method to analyze the resistivity in axial anisotropic and isotropic media. We further adopt the limited-memory Broyden-Fletcher-Goldfarb-Shanno (LBFGS) method to perform 3D tensor CSAMT axial anisotropic inversion. The inversion results suggest that when the underground structure is anisotropic, the isotropic inversion will introduce errors to the interpretation.

An Efficient G-XML Data Management Method using XML Spatial Index for Mobile Devices

NASA Astrophysics Data System (ADS)

Tamada, Takashi; Momma, Kei; Seo, Kazuo; Hijikata, Yoshinori; Nishida, Shogo

This paper presents an efficient G-XML data management method for mobile devices. G-XML is XML based encoding for the transport of geographic information. Mobile devices, such as PDA and mobile-phone, performance trail desktop machines, so some techniques are needed for processing G-XML data on mobile devices. In this method, XML-format spatial index file is used to improve an initial display time of G-XML data. This index file contains XML pointer of each feature in G-XML data and classifies these features by multi-dimensional data structures. From the experimental result, we can prove this method speed up about 3-7 times an initial display time of G-XML data on mobile devices.

Multigrid for Staggered Lattice Fermions

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

Brower, Richard C.; Clark, M. A.; Strelchenko, Alexei

Critical slowing down in Krylov methods for the Dirac operator presents a major obstacle to further advances in lattice field theory as it approaches the continuum solution. Here we formulate a multi-grid algorithm for the Kogut-Susskind (or staggered) fermion discretization which has proven difficult relative to Wilson multigrid due to its first-order anti-Hermitian structure. The solution is to introduce a novel spectral transformation by the K\\"ahler-Dirac spin structure prior to the Galerkin projection. We present numerical results for the two-dimensional, two-flavor Schwinger model, however, the general formalism is agnostic to dimension and is directly applicable to four-dimensional lattice QCD.

The supernova - supernova remnant connection through multi-dimensional magnetohydrodynamic modeling

NASA Astrophysics Data System (ADS)

Orlando, S.; Miceli, M.; Petruk, O.; Ono, M.

2017-10-01

Supernova remnants (SNRs) are diffuse extended sources often characterized by a rather complex morphology and a highly non-uniform distribution of ejecta. General consensus is that such a morphology reflects, on one hand, pristine structures and features of the progenitor supernova (SN) explosion and, on the other hand, the early interaction of the SN blast wave with the inhomogeneous circumstellar medium (CSM) formed in the latest stages of the progenitor star's evolution. Deciphering X-ray observations of SNRs, therefore, might open the possibility to reconstruct the ejecta structure as it was soon after the SN explosion and the structure and geometry of the medium immediately surrounding the progenitor star. This requires accurate and detailed models which describe the evolution from the on-set of the SN to the full remnant development and which connect the X-ray emission properties of the remnants to the progenitor SNe. Here we show how multi-dimensional SN-SNR magnetohydrodynamic models have been very effective in deciphering X-ray observations of SNR Cassiopeia A and SN 1987A. This has allowed us to unveil the average structure of ejecta in the immediate aftermath of the SN explosion and to constrain the 3D pre-supernova structure and geometry of the environment surrounding the progenitor SN.

Predicting human immunodeficiency virus inhibitors using multi-dimensional Bayesian network classifiers.

PubMed

Borchani, Hanen; Bielza, Concha; Toro, Carlos; Larrañaga, Pedro

2013-03-01

Our aim is to use multi-dimensional Bayesian network classifiers in order to predict the human immunodeficiency virus type 1 (HIV-1) reverse transcriptase and protease inhibitors given an input set of respective resistance mutations that an HIV patient carries. Multi-dimensional Bayesian network classifiers (MBCs) are probabilistic graphical models especially designed to solve multi-dimensional classification problems, where each input instance in the data set has to be assigned simultaneously to multiple output class variables that are not necessarily binary. In this paper, we introduce a new method, named MB-MBC, for learning MBCs from data by determining the Markov blanket around each class variable using the HITON algorithm. Our method is applied to both reverse transcriptase and protease data sets obtained from the Stanford HIV-1 database. Regarding the prediction of antiretroviral combination therapies, the experimental study shows promising results in terms of classification accuracy compared with state-of-the-art MBC learning algorithms. For reverse transcriptase inhibitors, we get 71% and 11% in mean and global accuracy, respectively; while for protease inhibitors, we get more than 84% and 31% in mean and global accuracy, respectively. In addition, the analysis of MBC graphical structures lets us gain insight into both known and novel interactions between reverse transcriptase and protease inhibitors and their respective resistance mutations. MB-MBC algorithm is a valuable tool to analyze the HIV-1 reverse transcriptase and protease inhibitors prediction problem and to discover interactions within and between these two classes of inhibitors. Copyright © 2012 Elsevier B.V. All rights reserved.

High resolution multidetector CT aided tissue analysis and quantification of lung fibrosis

NASA Astrophysics Data System (ADS)

Zavaletta, Vanessa A.; Karwoski, Ronald A.; Bartholmai, Brian; Robb, Richard A.

2006-03-01

Idiopathic pulmonary fibrosis (IPF, also known as Idiopathic Usual Interstitial Pneumontis, pathologically) is a progressive diffuse lung disease which has a median survival rate of less than four years with a prevalence of 15-20/100,000 in the United States. Global function changes are measured by pulmonary function tests and the diagnosis and extent of pulmonary structural changes are typically assessed by acquiring two-dimensional high resolution CT (HRCT) images. The acquisition and analysis of volumetric high resolution Multi-Detector CT (MDCT) images with nearly isotropic pixels offers the potential to measure both lung function and structure. This paper presents a new approach to three dimensional lung image analysis and classification of normal and abnormal structures in lungs with IPF.

Experimental study and numerical simulation on the structural and mechanical properties of Typha leaves through multimodal microscopy approaches.

PubMed

Liu, Jingjing; Zhang, Zhihui; Yu, Zhenglei; Liang, Yunhong; Li, Xiujuan; Ren, Luquan

2018-01-01

The Typha leaf, with special multi-level structure, low density and excellent mechanical properties, is an ideal bionic prototype utilized for lightweight design. In order to further study the relationship between the structure and mechanical properties, the three-dimensional macroscopic morphology of Typha leaves was characterized by micro computed tomography (Micro-CT) and its internal microstructure was observed by scanning electron microscopy (SEM). The combination of experimental and computational research was carried out in this paper, to reveal and verify the effect of multi-level structure on the mechanical properties. A universal testing machine and a self-developed mechanical testing apparatus with high precision and low load were used to measure the mechanical properties of the axial compression and lateral bending of the leaves, respectively. Three models with different internal structures were established based on the above-mentioned three-dimensional morphologies. The result demonstrated that the structure of partitions and diaphragms within the Typha leaf could form a reinforcement ribs structure which could provide multiple load paths and make the process of compression and bending difficult. The further nonlinear finite element analysis through LS-DYNA proved that internal structure could improve the ability of the models to resist compression and deformation. The investigation can be the reference for lightweight thin-walled structure design and inspire the application of the bionic structural materials. Copyright © 2017 Elsevier Ltd. All rights reserved.

Tunable two-dimensional acoustic meta-structure composed of funnel-shaped unit cells with multi-band negative acoustic property

NASA Astrophysics Data System (ADS)

Cho, Sungjin; Kim, Boseung; Min, Dongki; Park, Junhong

2015-10-01

This paper presents a two-dimensional heat-exhaust and sound-proof acoustic meta-structure exhibiting tunable multi-band negative effective mass density. The meta-structure was composed of periodic funnel-shaped units in a square lattice. Each unit cell operates simultaneously as a Helmholtz resonator (HR) and an extended pipe chamber resonator (EPCR), leading to a negative effective mass density creating bandgaps for incident sound energy dissipation without transmission. This structure allowed large heat-flow through the cross-sectional area of the extended pipe since the resonance was generated by acoustic elements without using solid membranes. The pipes were horizontally directed to a flow source to enable small flow resistance for cooling. Measurements of the sound transmission were performed using a two-load, four-microphone method for a unit cell and small reverberation chamber for two-dimensional panel to characterize the acoustic performance. The effective mass density showed significant frequency dependent variation exhibiting negative values at the specific bandgaps, while the effective bulk modulus was not affected by the resonator. Theoretical models incorporating local resonances in the multiple resonator units were proposed to analyze the noise reduction mechanism. The acoustic meta-structure parameters to create broader frequency bandgaps were investigated using the theoretical model. The negative effective mass density was calculated to investigate the creation of the bandgaps. The effects of design parameters such as length, cross-sectional area, and volume of the HR; length and cross-sectional area of the EPCR were analyzed. To maximize the frequency band gap, the suggested acoustic meta-structure panel, small neck length, and cross-sectional area of the HR, large EPCR length was advantageous. The bandgaps became broader when the two resonant frequencies were similar.

Three-Dimensional Gene Map of Cancer Cell Types: Structural Entropy Minimisation Principle for Defining Tumour Subtypes

PubMed Central

Li, Angsheng; Yin, Xianchen; Pan, Yicheng

2016-01-01

In this study, we propose a method for constructing cell sample networks from gene expression profiles, and a structural entropy minimisation principle for detecting natural structure of networks and for identifying cancer cell subtypes. Our method establishes a three-dimensional gene map of cancer cell types and subtypes. The identified subtypes are defined by a unique gene expression pattern, and a three-dimensional gene map is established by defining the unique gene expression pattern for each identified subtype for cancers, including acute leukaemia, lymphoma, multi-tissue, lung cancer and healthy tissue. Our three-dimensional gene map demonstrates that a true tumour type may be divided into subtypes, each defined by a unique gene expression pattern. Clinical data analyses demonstrate that most cell samples of an identified subtype share similar survival times, survival indicators and International Prognostic Index (IPI) scores and indicate that distinct subtypes identified by our algorithms exhibit different overall survival times, survival ratios and IPI scores. Our three-dimensional gene map establishes a high-definition, one-to-one map between the biologically and medically meaningful tumour subtypes and the gene expression patterns, and identifies remarkable cells that form singleton submodules. PMID:26842724

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.

A New Time-varying Concept of Risk in a Changing Climate.

PubMed

Sarhadi, Ali; Ausín, María Concepción; Wiper, Michael P

2016-10-20

In a changing climate arising from anthropogenic global warming, the nature of extreme climatic events is changing over time. Existing analytical stationary-based risk methods, however, assume multi-dimensional extreme climate phenomena will not significantly vary over time. To strengthen the reliability of infrastructure designs and the management of water systems in the changing environment, multidimensional stationary risk studies should be replaced with a new adaptive perspective. The results of a comparison indicate that current multi-dimensional stationary risk frameworks are no longer applicable to projecting the changing behaviour of multi-dimensional extreme climate processes. Using static stationary-based multivariate risk methods may lead to undesirable consequences in designing water system infrastructures. The static stationary concept should be replaced with a flexible multi-dimensional time-varying risk framework. The present study introduces a new multi-dimensional time-varying risk concept to be incorporated in updating infrastructure design strategies under changing environments arising from human-induced climate change. The proposed generalized time-varying risk concept can be applied for all stochastic multi-dimensional systems that are under the influence of changing environments.

Sparse representation of multi parametric DCE-MRI features using K-SVD for classifying gene expression based breast cancer recurrence risk

NASA Astrophysics Data System (ADS)

Mahrooghy, Majid; Ashraf, Ahmed B.; Daye, Dania; Mies, Carolyn; Rosen, Mark; Feldman, Michael; Kontos, Despina

2014-03-01

We evaluate the prognostic value of sparse representation-based features by applying the K-SVD algorithm on multiparametric kinetic, textural, and morphologic features in breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). K-SVD is an iterative dimensionality reduction method that optimally reduces the initial feature space by updating the dictionary columns jointly with the sparse representation coefficients. Therefore, by using K-SVD, we not only provide sparse representation of the features and condense the information in a few coefficients but also we reduce the dimensionality. The extracted K-SVD features are evaluated by a machine learning algorithm including a logistic regression classifier for the task of classifying high versus low breast cancer recurrence risk as determined by a validated gene expression assay. The features are evaluated using ROC curve analysis and leave one-out cross validation for different sparse representation and dimensionality reduction numbers. Optimal sparse representation is obtained when the number of dictionary elements is 4 (K=4) and maximum non-zero coefficients is 2 (L=2). We compare K-SVD with ANOVA based feature selection for the same prognostic features. The ROC results show that the AUC of the K-SVD based (K=4, L=2), the ANOVA based, and the original features (i.e., no dimensionality reduction) are 0.78, 0.71. and 0.68, respectively. From the results, it can be inferred that by using sparse representation of the originally extracted multi-parametric, high-dimensional data, we can condense the information on a few coefficients with the highest predictive value. In addition, the dimensionality reduction introduced by K-SVD can prevent models from over-fitting.

Fabrication of two-dimensional periodic structures on silicon after scanning irradiation with femtosecond laser multi-beams

NASA Astrophysics Data System (ADS)

Pan, An; Si, Jinhai; Chen, Tao; Li, Cunxia; Hou, Xun

2016-04-01

Two-dimensional (2D) periodic structures were fabricated on silicon surfaces by femtosecond laser irradiation in air and water, with the assistance of a microlens array (MLA) placed in the beam's path. By scanning the laser beam along the silicon surface, multiple grooves were simultaneously fabricated in parallel along with smaller laser-induced ripples. The 2D periodic structures contained long-periodic grooves and perpendicular short-periodic laser-induced ripples, which had periods of several microns and several hundred nanometers, respectively. We investigated the influence of laser power and scanning velocity on the morphological evolution of the 2D periodic structures in air and water. Large-area grid-like structures with ripples were fabricated by successively scanning once along each direction of the silicon's surface, which showed enhanced optical absorption. Hydrofluoric acid was then used to remove any oxygen and laser-induced defects for all-silicon structures.

Central Schemes for Multi-Dimensional Hamilton-Jacobi Equations

NASA Technical Reports Server (NTRS)

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

2002-01-01

We present new, efficient central schemes for multi-dimensional Hamilton-Jacobi equations. These non-oscillatory, non-staggered schemes are first- and second-order accurate and are designed to scale well with an increasing dimension. Efficiency is obtained by carefully choosing the location of the evolution points and by using a one-dimensional projection step. First-and second-order accuracy is verified for a variety of multi-dimensional, convex and non-convex problems.

Assessment of Resources and Needs for Water Development

ERIC Educational Resources Information Center

United Nations and Water, 1977

1977-01-01

Presents a brief history of water resource utilization, the present availability and uses of water, and strategies for water management. Three characteristic features of water demand management are explained: (1) emphasis on non-structural measures; (2) multi-dimensional organization and policies; (3) emphasis on research. (MA)

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)

ADJOINT-DERIVED LOCATION AND TRAVEL TIME PROBABILITIES FOR A MULTI-DIMENSIONAL GROUNDWATER SYSTEM. (U915324)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

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.

A dimensionally split Cartesian cut cell method for hyperbolic conservation laws

NASA Astrophysics Data System (ADS)

Gokhale, Nandan; Nikiforakis, Nikos; Klein, Rupert

2018-07-01

We present a dimensionally split method for solving hyperbolic conservation laws on Cartesian cut cell meshes. The approach combines local geometric and wave speed information to determine a novel stabilised cut cell flux, and we provide a full description of its three-dimensional implementation in the dimensionally split framework of Klein et al. [1]. The convergence and stability of the method are proved for the one-dimensional linear advection equation, while its multi-dimensional numerical performance is investigated through the computation of solutions to a number of test problems for the linear advection and Euler equations. When compared to the cut cell flux of Klein et al., it was found that the new flux alleviates the problem of oscillatory boundary solutions produced by the former at higher Courant numbers, and also enables the computation of more accurate solutions near stagnation points. Being dimensionally split, the method is simple to implement and extends readily to multiple dimensions.

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.

An existence criterion for low-dimensional materials

NASA Astrophysics Data System (ADS)

Chen, Jiapeng; Wang, Biao; Hu, Yangfan

2017-10-01

The discovery of graphene and other two-dimensional (2-D) materials has stimulated a general interest in low-dimensional (low-D) materials. Whereas long time ago, Peierls (1935) and Landau's (1937) theoretical work demonstrated that any one- and two-dimensional materials could not exist in any finite temperature environment. Then, two basic issues became a central concern for many researchers: How can stable low-D materials exist? What kind of low-D materials are stable? Here, we establish an energy stability criterion for low-D materials, which seeks to provide a clear answer to these questions. For a certain kind of element, the stability of its specific low-D structure is determined by several derivatives of its interatomic potential. This atomistic-based approach is then applied to study any straight/planar, low-D, equal-bond-length elemental materials. We found that 1-D monatomic chains, 2-D honeycomb lattices, square lattices, and triangular lattices are the only four permissible structures, and the stability of these structures can only be understood by assuming multi-body interatomic potentials. Using this approach, the stable existence of graphene, silicene and germanene can be explained.

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

WebCSD: the online portal to the Cambridge Structural Database

PubMed Central

Thomas, Ian R.; Bruno, Ian J.; Cole, Jason C.; Macrae, Clare F.; Pidcock, Elna; Wood, Peter A.

2010-01-01

WebCSD, a new web-based application developed by the Cambridge Crystallographic Data Centre, offers fast searching of the Cambridge Structural Database using only a standard internet browser. Search facilities include two-dimensional substructure, molecular similarity, text/numeric and reduced cell searching. Text, chemical diagrams and three-dimensional structural information can all be studied in the results browser using the efficient entry summaries and embedded three-dimensional viewer. PMID:22477776

Towards a Holistic Cortical Thickness Descriptor: Heat Kernel-Based Grey Matter Morphology Signatures.

PubMed

Wang, Gang; Wang, Yalin

2017-02-15

In this paper, we propose a heat kernel based regional shape descriptor that may be capable of better exploiting volumetric morphological information than other available methods, thereby improving statistical power on brain magnetic resonance imaging (MRI) analysis. The mechanism of our analysis is driven by the graph spectrum and the heat kernel theory, to capture the volumetric geometry information in the constructed tetrahedral meshes. In order to capture profound brain grey matter shape changes, we first use the volumetric Laplace-Beltrami operator to determine the point pair correspondence between white-grey matter and CSF-grey matter boundary surfaces by computing the streamlines in a tetrahedral mesh. Secondly, we propose multi-scale grey matter morphology signatures to describe the transition probability by random walk between the point pairs, which reflects the inherent geometric characteristics. Thirdly, a point distribution model is applied to reduce the dimensionality of the grey matter morphology signatures and generate the internal structure features. With the sparse linear discriminant analysis, we select a concise morphology feature set with improved classification accuracies. In our experiments, the proposed work outperformed the cortical thickness features computed by FreeSurfer software in the classification of Alzheimer's disease and its prodromal stage, i.e., mild cognitive impairment, on publicly available data from the Alzheimer's Disease Neuroimaging Initiative. The multi-scale and physics based volumetric structure feature may bring stronger statistical power than some traditional methods for MRI-based grey matter morphology analysis. Copyright © 2016 Elsevier Inc. All rights reserved.

Three-dimensional fuel pin model validation by prediction of hydrogen distribution in cladding and comparison with experiment

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

Aly, A.; Avramova, Maria; Ivanov, Kostadin

To correctly describe and predict this hydrogen distribution there is a need for multi-physics coupling to provide accurate three-dimensional azimuthal, radial, and axial temperature distributions in the cladding. Coupled high-fidelity reactor-physics codes with a sub-channel code as well as with a computational fluid dynamics (CFD) tool have been used to calculate detailed temperature distributions. These high-fidelity coupled neutronics/thermal-hydraulics code systems are coupled further with the fuel-performance BISON code with a kernel (module) for hydrogen. Both hydrogen migration and precipitation/dissolution are included in the model. Results from this multi-physics analysis is validated utilizing calculations of hydrogen distribution using models informed bymore » data from hydrogen experiments and PIE data.« less

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.

Belief in a Just What? Demystifying Just World Beliefs by Distinguishing Sources of Justice

PubMed Central

Stroebe, Katherine; Postmes, Tom; Täuber, Susanne; Stegeman, Alwin; John, Melissa-Sue

2015-01-01

People’s Belief in a Just World (BJW) plays an important role in coping with misfortune and unfairness. This paper demonstrates that understanding of the BJW concept, and its consequences for behavior, is enhanced if we specify what (or who) the source of justice might be. We introduce a new scale, the 5-Dimensional Belief in a Just Treatment Scale (BJT5), which distinguishes five causal dimensions of BJW (God, Nature, Other People, Self, Chance). We confirm the 5-factor structure of the BJT5. We then address whether the BJW should be considered a uni- and/or multi-dimensional construct and find support for our multi-dimensional approach. Finally, we demonstrate convergent and discriminant validity with respect to important correlates of BJW as well as action in response to important negative life events and societal attitudes. This work illustrates the importance of distinguishing causal dimensions with regard to who distributes justice. PMID:25803025

Image matrix processor for fast multi-dimensional computations

DOEpatents

Roberson, George P.; Skeate, Michael F.

1996-01-01

An apparatus for multi-dimensional computation which comprises a computation engine, including a plurality of processing modules. The processing modules are configured in parallel and compute respective contributions to a computed multi-dimensional image of respective two dimensional data sets. A high-speed, parallel access storage system is provided which stores the multi-dimensional data sets, and a switching circuit routes the data among the processing modules in the computation engine and the storage system. A data acquisition port receives the two dimensional data sets representing projections through an image, for reconstruction algorithms such as encountered in computerized tomography. The processing modules include a programmable local host, by which they may be configured to execute a plurality of different types of multi-dimensional algorithms. The processing modules thus include an image manipulation processor, which includes a source cache, a target cache, a coefficient table, and control software for executing image transformation routines using data in the source cache and the coefficient table and loading resulting data in the target cache. The local host processor operates to load the source cache with a two dimensional data set, loads the coefficient table, and transfers resulting data out of the target cache to the storage system, or to another destination.

Ferroelectric nanostructure having switchable multi-stable vortex states

DOEpatents

Naumov, Ivan I [Fayetteville, AR; Bellaiche, Laurent M [Fayetteville, AR; Prosandeev, Sergey A [Fayetteville, AR; Ponomareva, Inna V [Fayetteville, AR; Kornev, Igor A [Fayetteville, AR

2009-09-22

A ferroelectric nanostructure formed as a low dimensional nano-scale ferroelectric material having at least one vortex ring of polarization generating an ordered toroid moment switchable between multi-stable states. A stress-free ferroelectric nanodot under open-circuit-like electrical boundary conditions maintains such a vortex structure for their local dipoles when subject to a transverse inhomogeneous static electric field controlling the direction of the macroscopic toroidal moment. Stress is also capable of controlling the vortex's chirality, because of the electromechanical coupling that exists in ferroelectric nanodots.

IUTAM Symposium and NATO Advanced Research Workshop on Interpretation of Time Series from Nonlinear Mechanical Systems Held in Coventry, England on 26-30 August 1991. Conference Abstracts

DTIC Science & Technology

1991-08-01

day oscillation in the extratropical atmosphere as identified by multi-channel singular spectrum analysis 10:25 Coffee Break 10:50 Read Chaotic...day oscillation in the extratropical atmosphere as identified by multi-channel singular spectrum analysis M. Kimoto, M. Ghil and K.-C. Mo ABSTRACT...The three-dimensional spatial structure of an oscillatory mode in the Northern Hemisphere (NH) extratropics will be describe.d The oscillation is

Connected Component Model for Multi-Object Tracking.

PubMed

He, Zhenyu; Li, Xin; You, Xinge; Tao, Dacheng; Tang, Yuan Yan

2016-08-01

In multi-object tracking, it is critical to explore the data associations by exploiting the temporal information from a sequence of frames rather than the information from the adjacent two frames. Since straightforwardly obtaining data associations from multi-frames is an NP-hard multi-dimensional assignment (MDA) problem, most existing methods solve this MDA problem by either developing complicated approximate algorithms, or simplifying MDA as a 2D assignment problem based upon the information extracted only from adjacent frames. In this paper, we show that the relation between associations of two observations is the equivalence relation in the data association problem, based on the spatial-temporal constraint that the trajectories of different objects must be disjoint. Therefore, the MDA problem can be equivalently divided into independent subproblems by equivalence partitioning. In contrast to existing works for solving the MDA problem, we develop a connected component model (CCM) by exploiting the constraints of the data association and the equivalence relation on the constraints. Based upon CCM, we can efficiently obtain the global solution of the MDA problem for multi-object tracking by optimizing a sequence of independent data association subproblems. Experiments on challenging public data sets demonstrate that our algorithm outperforms the state-of-the-art approaches.

A MUSIC-based method for SSVEP signal processing.

PubMed

Chen, Kun; Liu, Quan; Ai, Qingsong; Zhou, Zude; Xie, Sheng Quan; Meng, Wei

2016-03-01

The research on brain computer interfaces (BCIs) has become a hotspot in recent years because it offers benefit to disabled people to communicate with the outside world. Steady state visual evoked potential (SSVEP)-based BCIs are more widely used because of higher signal to noise ratio and greater information transfer rate compared with other BCI techniques. In this paper, a multiple signal classification based method was proposed for multi-dimensional SSVEP feature extraction. 2-second data epochs from four electrodes achieved excellent accuracy rates including idle state detection. In some asynchronous mode experiments, the recognition accuracy reached up to 100%. The experimental results showed that the proposed method attained good frequency resolution. In most situations, the recognition accuracy was higher than canonical correlation analysis, which is a typical method for multi-channel SSVEP signal processing. Also, a virtual keyboard was successfully controlled by different subjects in an unshielded environment, which proved the feasibility of the proposed method for multi-dimensional SSVEP signal processing in practical applications.

Intelligent feature selection techniques for pattern classification of Lamb wave signals

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

Hinders, Mark K.; Miller, Corey A.

2014-02-18

Lamb wave interaction with flaws is a complex, three-dimensional phenomenon, which often frustrates signal interpretation schemes based on mode arrival time shifts predicted by dispersion curves. As the flaw severity increases, scattering and mode conversion effects will often dominate the time-domain signals, obscuring available information about flaws because multiple modes may arrive on top of each other. Even for idealized flaw geometries the scattering and mode conversion behavior of Lamb waves is very complex. Here, multi-mode Lamb waves in a metal plate are propagated across a rectangular flat-bottom hole in a sequence of pitch-catch measurements corresponding to the double crossholemore » tomography geometry. The flaw is sequentially deepened, with the Lamb wave measurements repeated at each flaw depth. Lamb wave tomography reconstructions are used to identify which waveforms have interacted with the flaw and thereby carry information about its depth. Multiple features are extracted from each of the Lamb wave signals using wavelets, which are then fed to statistical pattern classification algorithms that identify flaw severity. In order to achieve the highest classification accuracy, an optimal feature space is required but it’s never known a priori which features are going to be best. For structural health monitoring we make use of the fact that physical flaws, such as corrosion, will only increase over time. This allows us to identify feature vectors which are topologically well-behaved by requiring that sequential classes “line up” in feature vector space. An intelligent feature selection routine is illustrated that identifies favorable class distributions in multi-dimensional feature spaces using computational homology theory. Betti numbers and formal classification accuracies are calculated for each feature space subset to establish a correlation between the topology of the class distribution and the corresponding classification accuracy.« less

The factor structure and clinical utility of formal thought disorder in first episode psychosis.

PubMed

Roche, Eric; Lyne, John Paul; O'Donoghue, Brian; Segurado, Ricardo; Kinsella, Anthony; Hannigan, Ailish; Kelly, Brendan D; Malone, Kevin; Clarke, Mary

2015-10-01

Formal thought disorder (FTD) is a core feature of psychosis, however there are gaps in our knowledge about its prevalence and factor structure. We had two aims: first, to establish the factor structure of FTD; second, to explore the clinical utility of dimensions of FTD in order to further the understanding of its nosology. A cross-validation study was undertaken to establish the factor structure of FTD in first episode psychosis (FEP). The relative utility of FTD categories vs. dimensions across diagnostic categories was investigated. The prevalence of clinically significant FTD in this FEP sample was 21%, although 41% showed evidence of disorganised speech, 20% displayed verbosity and 24% displayed impoverished speech. A 3-factor model was identified as the best fit for FTD, with disorganisation, poverty and verbosity dimensions (GFI=0.99, RMR=0.07). These dimensions of FTD accurately distinguished affective from non-affective diagnostic categories. A categorical approach to FTD assessment was useful in identifying markers of clinical acuteness, as identified by short duration of untreated psychosis (OR=2.94, P<0.01) and inpatient treatment status (OR=3.98, P<0.01). FTD is moderately prevalent and multi-dimensional in FEP. Employing both a dimensional and categorical assessment of FTD gives valuable clinical information, however there may be a need to revise our conceptualisation of the nosology of FTD. The prognostic value of FTD, as well as its neural basis, requires elucidation. Copyright © 2015 Elsevier B.V. All rights reserved.

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

PubMed

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

2017-04-01

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

Teaching Three-Dimensional Structural Chemistry Using Crystal Structure Databases. 4. Examples of Discovery-Based Learning Using the Complete Cambridge Structural Database

ERIC Educational Resources Information Center

Battle, Gary M.; Allen, Frank H.; Ferrence, Gregory M.

2011-01-01

Parts 1 and 2 of this series described the educational value of experimental three-dimensional (3D) chemical structures determined by X-ray crystallography and retrieved from the crystallographic databases. In part 1, we described the information content of the Cambridge Structural Database (CSD) and discussed a representative teaching subset of…

Time-marching multi-grid seismic tomography

NASA Astrophysics Data System (ADS)

Tong, P.; Yang, D.; Liu, Q.

2016-12-01

From the classic ray-based traveltime tomography to the state-of-the-art full waveform inversion, because of the nonlinearity of seismic inverse problems, a good starting model is essential for preventing the convergence of the objective function toward local minima. With a focus on building high-accuracy starting models, we propose the so-called time-marching multi-grid seismic tomography method in this study. The new seismic tomography scheme consists of a temporal time-marching approach and a spatial multi-grid strategy. We first divide the recording period of seismic data into a series of time windows. Sequentially, the subsurface properties in each time window are iteratively updated starting from the final model of the previous time window. There are at least two advantages of the time-marching approach: (1) the information included in the seismic data of previous time windows has been explored to build the starting models of later time windows; (2) seismic data of later time windows could provide extra information to refine the subsurface images. Within each time window, we use a multi-grid method to decompose the scale of the inverse problem. Specifically, the unknowns of the inverse problem are sampled on a coarse mesh to capture the macro-scale structure of the subsurface at the beginning. Because of the low dimensionality, it is much easier to reach the global minimum on a coarse mesh. After that, finer meshes are introduced to recover the micro-scale properties. That is to say, the subsurface model is iteratively updated on multi-grid in every time window. We expect that high-accuracy starting models should be generated for the second and later time windows. We will test this time-marching multi-grid method by using our newly developed eikonal-based traveltime tomography software package tomoQuake. Real application results in the 2016 Kumamoto earthquake (Mw 7.0) region in Japan will be demonstrated.

Rapid construction of mechanically- confined multi- cellular structures using dendrimeric intercellular linker.

PubMed

Mo, Xuejun; Li, Qiushi; Yi Lui, Lena Wai; Zheng, Baixue; Kang, Chiang Huen; Nugraha, Bramasta; Yue, Zhilian; Jia, Rui Rui; Fu, Hong Xia; Choudhury, Deepak; Arooz, Talha; Yan, Jie; Lim, Chwee Teck; Shen, Shali; Hong Tan, Choon; Yu, Hanry

2010-10-01

Tissue constructs that mimic the in vivo cell-cell and cell-matrix interactions are especially useful for applications involving the cell- dense and matrix- poor internal organs. Rapid and precise arrangement of cells into functional tissue constructs remains a challenge in tissue engineering. We demonstrate rapid assembly of C3A cells into multi- cell structures using a dendrimeric intercellular linker. The linker is composed of oleyl- polyethylene glycol (PEG) derivatives conjugated to a 16 arms- polypropylenimine hexadecaamine (DAB) dendrimer. The positively charged multivalent dendrimer concentrates the linker onto the negatively charged cell surface to facilitate efficient insertion of the hydrophobic oleyl groups into the cellular membrane. Bringing linker- treated cells into close proximity to each other via mechanical means such as centrifugation and micromanipulation enables their rapid assembly into multi- cellular structures within minutes. The cells exhibit high levels of viability, proliferation, three- dimensional (3D) cell morphology and other functions in the constructs. We constructed defined multi- cellular structures such as rings, sheets or branching rods that can serve as potential tissue building blocks to be further assembled into complex 3D tissue constructs for biomedical applications. 2010 Elsevier Ltd. All rights reserved.

Evidence for a Multi-Dimensional Latent Structural Model of Externalizing Disorders

ERIC Educational Resources Information Center

Witkiewitz, Katie; King, Kevin; McMahon, Robert J.; Wu, Johnny; Luk, Jeremy; Bierman, Karen L.; Coie, John D.; Dodge, Kenneth A.; Greenberg, Mark T.; Lochman, John E.; Pinderhughes, Ellen E.

2013-01-01

Strong associations between conduct disorder (CD), antisocial personality disorder (ASPD) and substance use disorders (SUD) seem to reflect a general vulnerability to externalizing behaviors. Recent studies have characterized this vulnerability on a continuous scale, rather than as distinct categories, suggesting that the revision of the…

Relationship between Service Quality, Satisfaction, Motivation and Loyalty: A Multi-Dimensional Perspective

ERIC Educational Resources Information Center

Subrahmanyam, Annamdevula

2017-01-01

Purpose: This paper aims to identify and test four competing models with the interrelationships between students' perceived service quality, students' satisfaction, loyalty and motivation using structural equation modeling (SEM), and to select the best model using chi-square difference (??2) statistic test. Design/methodology/approach: The study…

Informing Scotland's Mental Health Strategy from the Classroom Context

ERIC Educational Resources Information Center

Marie, Dannette; Christian, Brittany M.; Lumsden, Joanne; Miles, Lynden K.

2014-01-01

Although conventional psychology is often characterised as the science of the individual mind, it is also important to introduce students to the potential interdisciplinary and multi-dimensional nature of psychology. In this paper we outline the design, development, and delivery of an innovative course that employed an ecological framework to…

MULTI-SCALE GRID DEFINITION IMPACTS ON REGIONAL, THREE-DIMENSIONAL AIR QUALITY MODEL PREDICTIONS AND PERFORMANCE. (R825821)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

A Graphics Design Framework to Visualize Multi-Dimensional Economic Datasets

ERIC Educational Resources Information Center

Chandramouli, Magesh; Narayanan, Badri; Bertoline, Gary R.

2013-01-01

This study implements a prototype graphics visualization framework to visualize multidimensional data. This graphics design framework serves as a "visual analytical database" for visualization and simulation of economic models. One of the primary goals of any kind of visualization is to extract useful information from colossal volumes of…

"Don't Sweat the Small Stuff:" Understanding Teacher Resilience at the Chalkface

ERIC Educational Resources Information Center

Mansfield, Caroline F.; Beltman, Susan; Price, Anne; McConney, Andrew

2012-01-01

This study investigates how graduating and early career teachers perceive resilient teachers. Informed by survey data from 200 graduating and early career teachers, the study's results indicate that graduating and early career teachers perceive that resilience for teachers comprises characteristics that are multi-dimensional and overlapping, and…

Domestic Violence: Issues and Dynamics. Informal Series No. 7.

ERIC Educational Resources Information Center

D'Oyley, Vincent, Ed.

The proceedings from the Toronto Conference present an overview of domestic violence, the roles of the police and judicial system, male/female relationships in domestic violence, the clinical treatment of domestic violence, domestic violence and education, social services, and a bibliography on battered wives. The multi-dimensionality of, and the…

Excitation, response, and fatigue life estimation methods for the structural design of externally blown flaps

NASA Technical Reports Server (NTRS)

Ungar, E. E.; Chandiramani, K. L.; Barger, J. E.

1972-01-01

Means for predicting the fluctuating pressures acting on externally blown flap surfaces are developed on the basis of generalizations derived from non-dimensionalized empirical data. Approaches for estimation of the fatigue lives of skin-stringer and honeycomb-core sandwich flap structures are derived from vibration response analyses and panel fatigue data. Approximate expressions for fluctuating pressures, structural response, and fatigue life are combined to reveal the important parametric dependences. The two-dimensional equations of motion of multi-element flap systems are derived in general form, so that they can be specialized readily for any particular system. An introduction is presented of an approach to characterizing the excitation pressures and structural responses which makes use of space-time spectral concepts and promises to provide useful insights, as well as experimental and analytical savings.

Validating two-dimensional leadership models on three-dimensionally structured fish schools

PubMed Central

Nagy, Máté; Holbrook, Robert I.; Biro, Dora; Burt de Perera, Theresa

2017-01-01

Identifying leader–follower interactions is crucial for understanding how a group decides where or when to move, and how this information is transferred between members. Although many animal groups have a three-dimensional structure, previous studies investigating leader–follower interactions have often ignored vertical information. This raises the question of whether commonly used two-dimensional leader–follower analyses can be used justifiably on groups that interact in three dimensions. To address this, we quantified the individual movements of banded tetra fish (Astyanax mexicanus) within shoals by computing the three-dimensional trajectories of all individuals using a stereo-camera technique. We used these data firstly to identify and compare leader–follower interactions in two and three dimensions, and secondly to analyse leadership with respect to an individual's spatial position in three dimensions. We show that for 95% of all pairwise interactions leadership identified through two-dimensional analysis matches that identified through three-dimensional analysis, and we reveal that fish attend to the same shoalmates for vertical information as they do for horizontal information. Our results therefore highlight that three-dimensional analyses are not always required to identify leader–follower relationships in species that move freely in three dimensions. We discuss our results in terms of the importance of taking species' sensory capacities into account when studying interaction networks within groups. PMID:28280582

An Optimization-based Framework to Learn Conditional Random Fields for Multi-label Classification

PubMed Central

Naeini, Mahdi Pakdaman; Batal, Iyad; Liu, Zitao; Hong, CharmGil; Hauskrecht, Milos

2015-01-01

This paper studies multi-label classification problem in which data instances are associated with multiple, possibly high-dimensional, label vectors. This problem is especially challenging when labels are dependent and one cannot decompose the problem into a set of independent classification problems. To address the problem and properly represent label dependencies we propose and study a pairwise conditional random Field (CRF) model. We develop a new approach for learning the structure and parameters of the CRF from data. The approach maximizes the pseudo likelihood of observed labels and relies on the fast proximal gradient descend for learning the structure and limited memory BFGS for learning the parameters of the model. Empirical results on several datasets show that our approach outperforms several multi-label classification baselines, including recently published state-of-the-art methods. PMID:25927015

Synergistic effects from graphene and carbon nanotubes endow ordered hierarchical structure foams with a combination of compressibility, super-elasticity and stability and potential application as pressure sensors

NASA Astrophysics Data System (ADS)

Kuang, Jun; Dai, Zhaohe; Liu, Luqi; Yang, Zhou; Jin, Ming; Zhang, Zhong

2015-05-01

Nanostructured carbon material based three-dimensional porous architectures have been increasingly developed for various applications, e.g. sensors, elastomer conductors, and energy storage devices. Maintaining architectures with good mechanical performance, including elasticity, load-bearing capacity, fatigue resistance and mechanical stability, is prerequisite for realizing these functions. Though graphene and CNT offer opportunities as nanoscale building blocks, it still remains a great challenge to achieve good mechanical performance in their microarchitectures because of the need to precisely control the structure at different scales. Herein, we fabricate a hierarchical honeycomb-like structured hybrid foam based on both graphene and CNT. The resulting materials possess excellent properties of combined high specific strength, elasticity and mechanical stability, which cannot be achieved in neat CNT and graphene foams. The improved mechanical properties are attributed to the synergistic-effect-induced highly organized, multi-scaled hierarchical architectures. Moreover, with their excellent electrical conductivity, we demonstrated that the hybrid foams could be used as pressure sensors in the fields related to artificial skin.Nanostructured carbon material based three-dimensional porous architectures have been increasingly developed for various applications, e.g. sensors, elastomer conductors, and energy storage devices. Maintaining architectures with good mechanical performance, including elasticity, load-bearing capacity, fatigue resistance and mechanical stability, is prerequisite for realizing these functions. Though graphene and CNT offer opportunities as nanoscale building blocks, it still remains a great challenge to achieve good mechanical performance in their microarchitectures because of the need to precisely control the structure at different scales. Herein, we fabricate a hierarchical honeycomb-like structured hybrid foam based on both graphene and CNT. The resulting materials possess excellent properties of combined high specific strength, elasticity and mechanical stability, which cannot be achieved in neat CNT and graphene foams. The improved mechanical properties are attributed to the synergistic-effect-induced highly organized, multi-scaled hierarchical architectures. Moreover, with their excellent electrical conductivity, we demonstrated that the hybrid foams could be used as pressure sensors in the fields related to artificial skin. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr00841g

Detection of surface cracking in steel pipes based on vibration data using a multi-class support vector machine classifier

NASA Astrophysics Data System (ADS)

Mustapha, S.; Braytee, A.; Ye, L.

2017-04-01

In this study, we focused at the development and verification of a robust framework for surface crack detection in steel pipes using measured vibration responses; with the presence of multiple progressive damage occurring in different locations within the structure. Feature selection, dimensionality reduction, and multi-class support vector machine were established for this purpose. Nine damage cases, at different locations, orientations and length, were introduced into the pipe structure. The pipe was impacted 300 times using an impact hammer, after each damage case, the vibration data were collected using 3 PZT wafers which were installed on the outer surface of the pipe. At first, damage sensitive features were extracted using the frequency response function approach followed by recursive feature elimination for dimensionality reduction. Then, a multi-class support vector machine learning algorithm was employed to train the data and generate a statistical model. Once the model is established, decision values and distances from the hyper-plane were generated for the new collected data using the trained model. This process was repeated on the data collected from each sensor. Overall, using a single sensor for training and testing led to a very high accuracy reaching 98% in the assessment of the 9 damage cases used in this study.

Small Angle Neutron Scattering (SANS) Studies on the Structural Evolution of Pyromellitamide Self-assembled Gels

DOE PAGES

Scott, Jamieson; Tong, Katie; William, Hamilton; ...

2014-10-31

The kinetics of aggregation of two pyromellitamide gelators; tetrabutyl- (C4) and tetrahexylpyromellitamide (C6), in deuterated cyclohexane has been investigated by small angle neutron scattering (SANS) for up to six days. The purpose of this study was to improve our understanding of how self-assembled gels are formed. Short-term (< 3 hour) time scales revealed multiple phases with the data for the tetrabutylpyromellitamide C4 indicating one dimensional stacking and aggregation corresponding to a multi-fiber braided cluster arrangement that is about 35 Å in diameter. The corresponding tetrahexylpyromellitamide C6 data suggests that the C6 also forms one-dimensional stacks but that these aggregate tomore » a thicker multi-fiber braided cluster that have a diameter of 61.8 Å. Over a longer period of time, the radius, persistence length and contour length all continue to increase in 6 days after cooling. This data suggests that structural changes in self-assembled gels occur over a period exceeding several days and that fairly subtle changes in the structure (e.g. tail-length) can influence the packing of molecules in self-assembled gels on the single-to-few fiber bundle stage.« less

Small Angle Neutron Scattering (SANS) Studies on the Structural Evolution of Pyromellitamide Self-assembled Gels

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

Scott, Jamieson; Tong, Katie; William, Hamilton

The kinetics of aggregation of two pyromellitamide gelators; tetrabutyl- (C4) and tetrahexylpyromellitamide (C6), in deuterated cyclohexane has been investigated by small angle neutron scattering (SANS) for up to six days. The purpose of this study was to improve our understanding of how self-assembled gels are formed. Short-term (< 3 hour) time scales revealed multiple phases with the data for the tetrabutylpyromellitamide C4 indicating one dimensional stacking and aggregation corresponding to a multi-fiber braided cluster arrangement that is about 35 Å in diameter. The corresponding tetrahexylpyromellitamide C6 data suggests that the C6 also forms one-dimensional stacks but that these aggregate tomore » a thicker multi-fiber braided cluster that have a diameter of 61.8 Å. Over a longer period of time, the radius, persistence length and contour length all continue to increase in 6 days after cooling. This data suggests that structural changes in self-assembled gels occur over a period exceeding several days and that fairly subtle changes in the structure (e.g. tail-length) can influence the packing of molecules in self-assembled gels on the single-to-few fiber bundle stage.« less

Pedagogical Factors Stimulating the Self-Development of Students' Multi-Dimensional Thinking in Terms of Subject-Oriented Teaching

ERIC Educational Resources Information Center

Andreev, Valentin I.

2014-01-01

The main aim of this research is to disclose the essence of students' multi-dimensional thinking, also to reveal the rating of factors which stimulate the raising of effectiveness of self-development of students' multi-dimensional thinking in terms of subject-oriented teaching. Subject-oriented learning is characterized as a type of learning where…

Exaggeration and suppression of iridescence: the evolution of two-dimensional butterfly structural colours

PubMed Central

Wickham, Shelley; Large, Maryanne C.J; Poladian, Leon; Jermiin, Lars S

2005-01-01

Many butterfly species possess ‘structural’ colour, where colour is due to optical microstructures found in the wing scales. A number of such structures have been identified in butterfly scales, including three variations on a simple multi-layer structure. In this study, we optically characterize examples of all three types of multi-layer structure, as found in 10 species. The optical mechanism of the suppression and exaggeration of the angle-dependent optical properties (iridescence) of these structures is described. In addition, we consider the phylogeny of the butterflies, and are thus able to relate the optical properties of the structures to their evolutionary development. By applying two different types of analysis, the mechanism of adaptation is addressed. A simple parsimony analysis, in which all evolutionary changes are given an equal weighting, suggests convergent evolution of one structure. A Dollo parsimony analysis, in which the evolutionary ‘cost’ of losing a structure is less than that of gaining it, implies that ‘latent’ structures can be reused. PMID:16849221

Spiked Models of Large Dimensional Random Matrices Applied to Wireless Communications and Array Signal Processing

DTIC Science & Technology

2013-12-14

population covariance matrix with application to array signal processing; and 5) a sample covariance matrix for which a CLT is studied on linear...Applications , (01 2012): 1150004. doi: Walid Hachem, Malika Kharouf, Jamal Najim, Jack W. Silverstein. A CLT FOR INFORMATION- THEORETIC STATISTICS...for Multi-source Power Estimation, (04 2010) Malika Kharouf, Jamal Najim, Jack W. Silverstein, Walid Hachem. A CLT FOR INFORMATION- THEORETIC

High dimensional model representation method for fuzzy structural dynamics

NASA Astrophysics Data System (ADS)

Adhikari, S.; Chowdhury, R.; Friswell, M. I.

2011-03-01

Uncertainty propagation in multi-parameter complex structures possess significant computational challenges. This paper investigates the possibility of using the High Dimensional Model Representation (HDMR) approach when uncertain system parameters are modeled using fuzzy variables. In particular, the application of HDMR is proposed for fuzzy finite element analysis of linear dynamical systems. The HDMR expansion is an efficient formulation for high-dimensional mapping in complex systems if the higher order variable correlations are weak, thereby permitting the input-output relationship behavior to be captured by the terms of low-order. The computational effort to determine the expansion functions using the α-cut method scales polynomically with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is first illustrated for multi-parameter nonlinear mathematical test functions with fuzzy variables. The method is then integrated with a commercial finite element software (ADINA). Modal analysis of a simplified aircraft wing with fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations. It is shown that using the proposed HDMR approach, the number of finite element function calls can be reduced without significantly compromising the accuracy.

Evidencing Learning Outcomes: A Multi-Level, Multi-Dimensional Course Alignment Model

ERIC Educational Resources Information Center

Sridharan, Bhavani; Leitch, Shona; Watty, Kim

2015-01-01

This conceptual framework proposes a multi-level, multi-dimensional course alignment model to implement a contextualised constructive alignment of rubric design that authentically evidences and assesses learning outcomes. By embedding quality control mechanisms at each level for each dimension, this model facilitates the development of an aligned…

Photoemission study of the electronic structure and charge density waves of Na₂Ti₂Sb₂O

DOE PAGES

Tan, S. Y.; Jiang, J.; Ye, Z. R.; ...

2015-04-30

The electronic structure of Na₂Ti₂Sb₂O single crystal is studied by photon energy and polarization dependent angle-resolved photoemission spectroscopy (ARPES). The obtained band structure and Fermi surface agree well with the band structure calculation of Na₂Ti₂Sb₂O in the non-magnetic state, which indicates that there is no magnetic order in Na₂Ti₂Sb₂O and the electronic correlation is weak. Polarization dependent ARPES results suggest the multi-band and multi-orbital nature of Na₂Ti₂Sb₂O. Photon energy dependent ARPES results suggest that the electronic structure of Na₂Ti₂Sb₂O is rather two-dimensional. Moreover, we find a density wave energy gap forms below the transition temperature and reaches 65 meV atmore » 7 K, indicating that Na₂Ti₂Sb₂O is likely a weakly correlated CDW material in the strong electron-phonon interaction regime. (author)« less

Thermostructural Analysis of Carbon Cloth Phenolic Material Tested at the Laser Hardened Material Evaluation Laboratory

NASA Technical Reports Server (NTRS)

Clayton, J. Louie; Ehle, Curt; Saxon, Jeff (Technical Monitor)

2002-01-01

RSRM nozzle liner components have been analyzed and tested to explore the occurrence of anomalous material performance known as pocketing erosion. Primary physical factors that contribute to pocketing seem to include the geometric permeability, which governs pore pressure magnitudes and hence load, and carbon fiber high temperature tensile strength, which defines a material limiting capability. The study reports on the results of a coupled thermostructural finite element analysis of Carbon Cloth Phenolic (CCP) material tested at the Laser Hardened Material Evaluation Laboratory (the LHMEL facility). Modeled test configurations will be limited to the special case of where temperature gradients are oriented perpendicular to the composite material ply angle. Analyses were conducted using a transient, one-dimensional flow/thermal finite element code that models pore pressure and temperature distributions and in an explicitly coupled formulation, passes this information to a 2-dimensional finite element structural model for determination of the stress/deformation behavior of the orthotropic fiber/matrix CCP. Pore pressures are generated by thermal decomposition of the phenolic resin which evolve as a multi-component gas phase which is partially trapped in the porous microstructure of the composite. The nature of resultant pressures are described by using the Darcy relationships which have been modified to permit a multi-specie mass and momentum balance including water vapor condensation. Solution to the conjugate flow/thermal equations were performed using the SINDA code. Of particular importance to this problem was the implementation of a char and deformation state dependent (geometric) permeability as describing a first order interaction between the flow/thermal and structural models. Material property models are used to characterize the solid phase mechanical stiffness and failure. Structural calculations were performed using the ABAQUS code. Iterations were made between the two codes involving the dependent variables temperature, pressure and across-ply strain level. Model results comparisons are made for three different surface heat rates and dependent variable sensitivities discussed for the various cases.

Analysis of the phase transition in the two-dimensional Ising ferromagnet using a Lempel-Ziv string-parsing scheme and black-box data-compression utilities

NASA Astrophysics Data System (ADS)

Melchert, O.; Hartmann, A. K.

2015-02-01

In this work we consider information-theoretic observables to analyze short symbolic sequences, comprising time series that represent the orientation of a single spin in a two-dimensional (2D) Ising ferromagnet on a square lattice of size L2=1282 for different system temperatures T . The latter were chosen from an interval enclosing the critical point Tc of the model. At small temperatures the sequences are thus very regular; at high temperatures they are maximally random. In the vicinity of the critical point, nontrivial, long-range correlations appear. Here we implement estimators for the entropy rate, excess entropy (i.e., "complexity"), and multi-information. First, we implement a Lempel-Ziv string-parsing scheme, providing seemingly elaborate entropy rate and multi-information estimates and an approximate estimator for the excess entropy. Furthermore, we apply easy-to-use black-box data-compression utilities, providing approximate estimators only. For comparison and to yield results for benchmarking purposes, we implement the information-theoretic observables also based on the well-established M -block Shannon entropy, which is more tedious to apply compared to the first two "algorithmic" entropy estimation procedures. To test how well one can exploit the potential of such data-compression techniques, we aim at detecting the critical point of the 2D Ising ferromagnet. Among the above observables, the multi-information, which is known to exhibit an isolated peak at the critical point, is very easy to replicate by means of both efficient algorithmic entropy estimation procedures. Finally, we assess how good the various algorithmic entropy estimates compare to the more conventional block entropy estimates and illustrate a simple modification that yields enhanced results.

Dynamic chromosomal rearrangements in Hodgkin's lymphoma are due to ongoing three-dimensional nuclear remodeling and breakage-bridge-fusion cycles.

PubMed

Guffei, Amanda; Sarkar, Rahul; Klewes, Ludger; Righolt, Christiaan; Knecht, Hans; Mai, Sabine

2010-12-01

Hodgkin's lymphoma is characterized by the presence of mono-nucleated Hodgkin cells and bi- to multi-nucleated Reed-Sternberg cells. We have recently shown telomere dysfunction and aberrant synchronous/asynchronous cell divisions during the transition of Hodgkin cells to Reed-Sternberg cells.1 To determine whether overall changes in nuclear architecture affect genomic instability during the transition of Hodgkin cells to Reed-Sternberg cells, we investigated the nuclear organization of chromosomes in these cells. Three-dimensional fluorescent in situ hybridization revealed irregular nuclear positioning of individual chromosomes in Hodgkin cells and, more so, in Reed-Sternberg cells. We characterized an increasingly unequal distribution of chromosomes as mono-nucleated cells became multi-nucleated cells, some of which also contained chromosome-poor 'ghost' cell nuclei. Measurements of nuclear chromosome positions suggested chromosome overlaps in both types of cells. Spectral karyotyping then revealed both aneuploidy and complex chromosomal rearrangements: multiple breakage-bridge-fusion cycles were at the origin of the multiple rearranged chromosomes. This conclusion was challenged by super resolution three-dimensional structured illumination imaging of Hodgkin and Reed-Sternberg nuclei. Three-dimensional super resolution microscopy data documented inter-nuclear DNA bridges in multi-nucleated cells but not in mono-nucleated cells. These bridges consisted of chromatids and chromosomes shared by two Reed-Sternberg nuclei. The complexity of chromosomal rearrangements increased as Hodgkin cells developed into multi-nucleated cells, thus indicating tumor progression and evolution in Hodgkin's lymphoma, with Reed-Sternberg cells representing the highest complexity in chromosomal rearrangements in this disease. This is the first study to demonstrate nuclear remodeling and associated genomic instability leading to the generation of Reed-Sternberg cells of Hodgkin's lymphoma. We defined nuclear remodeling as a key feature of Hodgkin's lymphoma, highlighting the relevance of nuclear architecture in cancer.

Augmented reality on poster presentations, in the field and in the classroom

NASA Astrophysics Data System (ADS)

Hawemann, Friedrich; Kolawole, Folarin

2017-04-01

Augmented reality (AR) is the direct addition of virtual information through an interface to a real-world environment. In practice, through a mobile device such as a tablet or smartphone, information can be projected onto a target- for example, an image on a poster. Mobile devices are widely distributed today such that augmented reality is easily accessible to almost everyone. Numerous studies have shown that multi-dimensional visualization is essential for efficient perception of the spatial, temporal and geometrical configuration of geological structures and processes. Print media, such as posters and handouts lack the ability to display content in the third and fourth dimensions, which might be in space-domain as seen in three-dimensional (3-D) objects, or time-domain (four-dimensional, 4-D) expressible in the form of videos. Here, we show that augmented reality content can be complimentary to geoscience poster presentations, hands-on material and in the field. In the latter example, location based data is loaded and for example, a virtual geological profile can be draped over a real-world landscape. In object based AR, the application is trained to recognize an image or object through the camera of the user's mobile device, such that specific content is automatically downloaded and displayed on the screen of the device, and positioned relative to the trained image or object. We used ZapWorks, a commercially-available software application to create and present examples of content that is poster-based, in which important supplementary information is presented as interactive virtual images, videos and 3-D models. We suggest that the flexibility and real-time interactivity offered by AR makes it an invaluable tool for effective geoscience poster presentation, class-room and field geoscience learning.

A preliminary investigation of the growth of an aneurysm with a multiscale monolithic Fluid-Structure interaction solver

NASA Astrophysics Data System (ADS)

Cerroni, D.; Manservisi, S.; Pozzetti, G.

2015-11-01

In this work we investigate the potentialities of multi-scale engineering techniques to approach complex problems related to biomedical and biological fields. In particular we study the interaction between blood and blood vessel focusing on the presence of an aneurysm. The study of each component of the cardiovascular system is very difficult due to the fact that the movement of the fluid and solid is determined by the rest of system through dynamical boundary conditions. The use of multi-scale techniques allows us to investigate the effect of the whole loop on the aneurysm dynamic. A three-dimensional fluid-structure interaction model for the aneurysm is developed and coupled to a mono-dimensional one for the remaining part of the cardiovascular system, where a point zero-dimensional model for the heart is provided. In this manner it is possible to achieve rigorous and quantitative investigations of the cardiovascular disease without loosing the system dynamic. In order to study this biomedical problem we use a monolithic fluid-structure interaction (FSI) model where the fluid and solid equations are solved together. The use of a monolithic solver allows us to handle the convergence issues caused by large deformations. By using this monolithic approach different solid and fluid regions are treated as a single continuum and the interface conditions are automatically taken into account. In this way the iterative process characteristic of the commonly used segregated approach, it is not needed any more.

Accurate facade feature extraction method for buildings from three-dimensional point cloud data considering structural information

NASA Astrophysics Data System (ADS)

Wang, Yongzhi; Ma, Yuqing; Zhu, A.-xing; Zhao, Hui; Liao, Lixia

2018-05-01

Facade features represent segmentations of building surfaces and can serve as a building framework. Extracting facade features from three-dimensional (3D) point cloud data (3D PCD) is an efficient method for 3D building modeling. By combining the advantages of 3D PCD and two-dimensional optical images, this study describes the creation of a highly accurate building facade feature extraction method from 3D PCD with a focus on structural information. The new extraction method involves three major steps: image feature extraction, exploration of the mapping method between the image features and 3D PCD, and optimization of the initial 3D PCD facade features considering structural information. Results show that the new method can extract the 3D PCD facade features of buildings more accurately and continuously. The new method is validated using a case study. In addition, the effectiveness of the new method is demonstrated by comparing it with the range image-extraction method and the optical image-extraction method in the absence of structural information. The 3D PCD facade features extracted by the new method can be applied in many fields, such as 3D building modeling and building information modeling.

Multi Length Scale Imaging of Flocculated Estuarine Sediments; Insights into their Complex 3D Structure

NASA Astrophysics Data System (ADS)

Wheatland, Jonathan; Bushby, Andy; Droppo, Ian; Carr, Simon; Spencer, Kate

2015-04-01

Suspended estuarine sediments form flocs that are compositionally complex, fragile and irregularly shaped. The fate and transport of suspended particulate matter (SPM) is determined by the size, shape, density, porosity and stability of these flocs and prediction of SPM transport requires accurate measurements of these three-dimensional (3D) physical properties. However, the multi-scaled nature of flocs in addition to their fragility makes their characterisation in 3D problematic. Correlative microscopy is a strategy involving the spatial registration of information collected at different scales using several imaging modalities. Previously, conventional optical microscopy (COM) and transmission electron microscopy (TEM) have enabled 2-dimensional (2D) floc characterisation at the gross (> 1 µm) and sub-micron scales respectively. Whilst this has proven insightful there remains a critical spatial and dimensional gap preventing the accurate measurement of geometric properties and an understanding of how structures at different scales are related. Within life sciences volumetric imaging techniques such as 3D micro-computed tomography (3D µCT) and focused ion beam scanning electron microscopy [FIB-SEM (or FIB-tomography)] have been combined to characterise materials at the centimetre to micron scale. Combining these techniques with TEM enables an advanced correlative study, allowing material properties across multiple spatial and dimensional scales to be visualised. The aims of this study are; 1) to formulate an advanced correlative imaging strategy combining 3D µCT, FIB-tomography and TEM; 2) to acquire 3D datasets; 3) to produce a model allowing their co-visualisation; 4) to interpret 3D floc structure. To reduce the chance of structural alterations during analysis samples were first 'fixed' in 2.5% glutaraldehyde/2% formaldehyde before being embedding in Durcupan resin. Intermediate steps were implemented to improve contrast and remove pore water, achieved by the addition of heavy metal stains and washing samples in a series of ethanol solutions and acetone. Gross-scale characterisation involved scanning samples using a Nikon Metrology HM X 225 µCT. For micro-scale analysis a working surface was revealed by microtoming the sample. Ultrathin sections were then collected and analysed using a JEOL 1200 Ex II TEM, and FIB-tomography datasets obtained using an FEI Quanta 3D FIB-SEM. Finally, to locate the surface and relate TEM and FIB-tomography datasets to the original floc, samples were rescanned using the µCT. Image processing was initially conducted in ImageJ. Following this datasets were imported into Amira 5.5 where pixel intensity thresholding allowed particle-matrix boundaries to be defined. Using 'landmarks' datasets were then registered to enable their co-visualisation in 3D models. Analysis of registered datasets reveals the complex non-fractal nature of flocs, whose properties span several of orders of magnitude. Primary particles are organised into discrete 'bundles', the arrangement of which directly influences their gross morphology. This strategy, which allows the co-visualisation of spatially registered multi-scale 3D datasets, provides unique insights into the true nature floc which would other have been impossible.

Analysing the magnetopause internal structure: new possibilities offered by MMS

NASA Astrophysics Data System (ADS)

Belmont, G.; Rezeau, L.; Manuzzo, R.; Aunai, N.; Dargent, J.

2017-12-01

We explore the structure of the magnetopause using a crossing observed by the MMS spacecraft on October 16th, 2015. Several methods (MVA, BV, CVA) are first applied to compute the normal to the magnetopause considered as a whole. The different results obtained are not identical and we show that the whole boundary is not stationary and not planar, so that basic assumptions of these methods are not well satisfied. We then analyse more finely the internal structure for investigating the departures from planarity. Using the basic mathematical definition of what is a one-dimensional physical problem, we introduce a new method, called LNA (Local Normal Analysis) for determining the varying normal, and we compare the results so obtained with those coming from the MDD tool developed by [Shi et al., 2005]. This method gives the dimensionality of the magnetic variations from multi-point measurements and allows estimating the direction of the local normal using the magnetic field. On the other hand, LNA is a single-spacecraft method which gives the local normal from the magnetic field and particle data. This study shows that the magnetopause does include approximate one-dimensional sub-structures but also two and three dimensional intervals. It also shows that the dimensionality of the magnetic variations can differ from the variations of the other fields so that, at some places, the magnetic field can have a 1D structure although all the plasma variations do not verify the properties of a global one-dimensional problem. Finally a generalisation and a systematic application of the MDD method to the physical quantities of interest is shown.

Image matrix processor for fast multi-dimensional computations

DOEpatents

Roberson, G.P.; Skeate, M.F.

1996-10-15

An apparatus for multi-dimensional computation is disclosed which comprises a computation engine, including a plurality of processing modules. The processing modules are configured in parallel and compute respective contributions to a computed multi-dimensional image of respective two dimensional data sets. A high-speed, parallel access storage system is provided which stores the multi-dimensional data sets, and a switching circuit routes the data among the processing modules in the computation engine and the storage system. A data acquisition port receives the two dimensional data sets representing projections through an image, for reconstruction algorithms such as encountered in computerized tomography. The processing modules include a programmable local host, by which they may be configured to execute a plurality of different types of multi-dimensional algorithms. The processing modules thus include an image manipulation processor, which includes a source cache, a target cache, a coefficient table, and control software for executing image transformation routines using data in the source cache and the coefficient table and loading resulting data in the target cache. The local host processor operates to load the source cache with a two dimensional data set, loads the coefficient table, and transfers resulting data out of the target cache to the storage system, or to another destination. 10 figs.

Three-dimensional compound comparison methods and their application in drug discovery.

PubMed

Shin, Woong-Hee; Zhu, Xiaolei; Bures, Mark Gregory; Kihara, Daisuke

2015-07-16

Virtual screening has been widely used in the drug discovery process. Ligand-based virtual screening (LBVS) methods compare a library of compounds with a known active ligand. Two notable advantages of LBVS methods are that they do not require structural information of a target receptor and that they are faster than structure-based methods. LBVS methods can be classified based on the complexity of ligand structure information utilized: one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D). Unlike 1D and 2D methods, 3D methods can have enhanced performance since they treat the conformational flexibility of compounds. In this paper, a number of 3D methods will be reviewed. In addition, four representative 3D methods were benchmarked to understand their performance in virtual screening. Specifically, we tested overall performance in key aspects including the ability to find dissimilar active compounds, and computational speed.

Direct writing of tunable multi-wavelength polymer lasers on a flexible substrate.

PubMed

Zhai, Tianrui; Wang, Yonglu; Chen, Li; Zhang, Xinping

2015-08-07

Tunable multi-wavelength polymer lasers based on two-dimensional distributed feedback structures are fabricated on a transparent flexible substrate using interference ablation. A scalene triangular lattice structure was designed to support stable tri-wavelength lasing emission and was achieved through multiple exposure processes. Three wavelengths were controlled by three periods of the compound cavity. Mode competition among different cavity modes was observed by changing the pump fluence. Both a redshift and blueshift of the laser wavelength could be achieved by bending the soft substrate. These results not only provide insight into the physical mechanisms behind co-cavity polymer lasers but also introduce new laser sources and laser designs for white light lasers.

A rudimentary database for three-dimensional objects using structural representation

NASA Technical Reports Server (NTRS)

Sowers, James P.

1987-01-01

A database which enables users to store and share the description of three-dimensional objects in a research environment is presented. The main objective of the design is to make it a compact structure that holds sufficient information to reconstruct the object. The database design is based on an object representation scheme which is information preserving, reasonably efficient, and yet economical in terms of the storage requirement. The determination of the needed data for the reconstruction process is guided by the belief that it is faster to do simple computations to generate needed data/information for construction than to retrieve everything from memory. Some recent techniques of three-dimensional representation that influenced the design of the database are discussed. The schema for the database and the structural definition used to define an object are given. The user manual for the software developed to create and maintain the contents of the database is included.

Observer-based distributed adaptive iterative learning control for linear multi-agent systems

NASA Astrophysics Data System (ADS)

Li, Jinsha; Liu, Sanyang; Li, Junmin

2017-10-01

This paper investigates the consensus problem for linear multi-agent systems from the viewpoint of two-dimensional systems when the state information of each agent is not available. Observer-based fully distributed adaptive iterative learning protocol is designed in this paper. A local observer is designed for each agent and it is shown that without using any global information about the communication graph, all agents achieve consensus perfectly for all undirected connected communication graph when the number of iterations tends to infinity. The Lyapunov-like energy function is employed to facilitate the learning protocol design and property analysis. Finally, simulation example is given to illustrate the theoretical analysis.

Structural Optimization of a Force Balance Using a Computational Experiment Design

NASA Technical Reports Server (NTRS)

Parker, P. A.; DeLoach, R.

2002-01-01

This paper proposes a new approach to force balance structural optimization featuring a computational experiment design. Currently, this multi-dimensional design process requires the designer to perform a simplification by executing parameter studies on a small subset of design variables. This one-factor-at-a-time approach varies a single variable while holding all others at a constant level. Consequently, subtle interactions among the design variables, which can be exploited to achieve the design objectives, are undetected. The proposed method combines Modern Design of Experiments techniques to direct the exploration of the multi-dimensional design space, and a finite element analysis code to generate the experimental data. To efficiently search for an optimum combination of design variables and minimize the computational resources, a sequential design strategy was employed. Experimental results from the optimization of a non-traditional force balance measurement section are presented. An approach to overcome the unique problems associated with the simultaneous optimization of multiple response criteria is described. A quantitative single-point design procedure that reflects the designer's subjective impression of the relative importance of various design objectives, and a graphical multi-response optimization procedure that provides further insights into available tradeoffs among competing design objectives are illustrated. The proposed method enhances the intuition and experience of the designer by providing new perspectives on the relationships between the design variables and the competing design objectives providing a systematic foundation for advancements in structural design.

Multi-atlas learner fusion: An efficient segmentation approach for large-scale data.

PubMed

Asman, Andrew J; Huo, Yuankai; Plassard, Andrew J; Landman, Bennett A

2015-12-01

We propose multi-atlas learner fusion (MLF), a framework for rapidly and accurately replicating the highly accurate, yet computationally expensive, multi-atlas segmentation framework based on fusing local learners. In the largest whole-brain multi-atlas study yet reported, multi-atlas segmentations are estimated for a training set of 3464 MR brain images. Using these multi-atlas estimates we (1) estimate a low-dimensional representation for selecting locally appropriate example images, and (2) build AdaBoost learners that map a weak initial segmentation to the multi-atlas segmentation result. Thus, to segment a new target image we project the image into the low-dimensional space, construct a weak initial segmentation, and fuse the trained, locally selected, learners. The MLF framework cuts the runtime on a modern computer from 36 h down to 3-8 min - a 270× speedup - by completely bypassing the need for deformable atlas-target registrations. Additionally, we (1) describe a technique for optimizing the weak initial segmentation and the AdaBoost learning parameters, (2) quantify the ability to replicate the multi-atlas result with mean accuracies approaching the multi-atlas intra-subject reproducibility on a testing set of 380 images, (3) demonstrate significant increases in the reproducibility of intra-subject segmentations when compared to a state-of-the-art multi-atlas framework on a separate reproducibility dataset, (4) show that under the MLF framework the large-scale data model significantly improve the segmentation over the small-scale model under the MLF framework, and (5) indicate that the MLF framework has comparable performance as state-of-the-art multi-atlas segmentation algorithms without using non-local information. Copyright © 2015 Elsevier B.V. All rights reserved.

Dual wing, swept forward swept rearward wing, and single wing design optimization for high performance business airplanes

NASA Technical Reports Server (NTRS)

Rhodes, M. D.; Selberg, B. P.

1982-01-01

An investigation was performed to compare closely coupled dual wing and swept forward swept rearward wing aircraft to corresponding single wing 'baseline' designs to judge the advantages offered by aircraft designed with multiple wing systems. The optimum multiple wing geometry used on the multiple wing designs was determined in an analytic study which investigated the two- and three-dimensional aerodynamic behavior of a wide range of multiple wing configurations in order to find the wing geometry that created the minimum cruise drag. This analysis used a multi-element inviscid vortex panel program coupled to a momentum integral boundary layer analysis program to account for the aerodynamic coupling between the wings and to provide the two-dimensional aerodynamic data, which was then used as input for a three-dimensional vortex lattice program, which calculated the three-dimensional aerodynamic data. The low drag of the multiple wing configurations is due to a combination of two dimensional drag reductions, tailoring the three dimensional drag for the swept forward swept rearward design, and the structural advantages of the two wings that because of the structural connections permitted higher aspect ratios.

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

A novel framework to alleviate the sparsity problem in context-aware recommender systems

NASA Astrophysics Data System (ADS)

Yu, Penghua; Lin, Lanfen; Wang, Jing

2017-04-01

Recommender systems have become indispensable for services in the era of big data. To improve accuracy and satisfaction, context-aware recommender systems (CARSs) attempt to incorporate contextual information into recommendations. Typically, valid and influential contexts are determined in advance by domain experts or feature selection approaches. Most studies have focused on utilizing the unitary context due to the differences between various contexts. Meanwhile, multi-dimensional contexts will aggravate the sparsity problem, which means that the user preference matrix would become extremely sparse. Consequently, there are not enough or even no preferences in most multi-dimensional conditions. In this paper, we propose a novel framework to alleviate the sparsity issue for CARSs, especially when multi-dimensional contextual variables are adopted. Motivated by the intuition that the overall preferences tend to show similarities among specific groups of users and conditions, we first explore to construct one contextual profile for each contextual condition. In order to further identify those user and context subgroups automatically and simultaneously, we apply a co-clustering algorithm. Furthermore, we expand user preferences in a given contextual condition with the identified user and context clusters. Finally, we perform recommendations based on expanded preferences. Extensive experiments demonstrate the effectiveness of the proposed framework.

Urban air quality forecasting based on multi-dimensional collaborative Support Vector Regression (SVR): A case study of Beijing-Tianjin-Shijiazhuang

PubMed Central

Liu, Bing-Chun; Binaykia, Arihant; Chang, Pei-Chann; Tiwari, Manoj Kumar; Tsao, Cheng-Chin

2017-01-01

Today, China is facing a very serious issue of Air Pollution due to its dreadful impact on the human health as well as the environment. The urban cities in China are the most affected due to their rapid industrial and economic growth. Therefore, it is of extreme importance to come up with new, better and more reliable forecasting models to accurately predict the air quality. This paper selected Beijing, Tianjin and Shijiazhuang as three cities from the Jingjinji Region for the study to come up with a new model of collaborative forecasting using Support Vector Regression (SVR) for Urban Air Quality Index (AQI) prediction in China. The present study is aimed to improve the forecasting results by minimizing the prediction error of present machine learning algorithms by taking into account multiple city multi-dimensional air quality information and weather conditions as input. The results show that there is a decrease in MAPE in case of multiple city multi-dimensional regression when there is a strong interaction and correlation of the air quality characteristic attributes with AQI. Also, the geographical location is found to play a significant role in Beijing, Tianjin and Shijiazhuang AQI prediction. PMID:28708836

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.

Development and validation of a multi-dimensional measure of intellectual humility

PubMed Central

Alfano, Mark; Iurino, Kathryn; Stey, Paul; Robinson, Brian; Christen, Markus; Yu, Feng; Lapsley, Daniel

2017-01-01

This paper presents five studies on the development and validation of a scale of intellectual humility. This scale captures cognitive, affective, behavioral, and motivational components of the construct that have been identified by various philosophers in their conceptual analyses of intellectual humility. We find that intellectual humility has four core dimensions: Open-mindedness (versus Arrogance), Intellectual Modesty (versus Vanity), Corrigibility (versus Fragility), and Engagement (versus Boredom). These dimensions display adequate self-informant agreement, and adequate convergent, divergent, and discriminant validity. In particular, Open-mindedness adds predictive power beyond the Big Six for an objective behavioral measure of intellectual humility, and Intellectual Modesty is uniquely related to Narcissism. We find that a similar factor structure emerges in Germanophone participants, giving initial evidence for the model’s cross-cultural generalizability. PMID:28813478

Cloud/web mapping and geoprocessing services - Intelligently linking geoinformation

NASA Astrophysics Data System (ADS)

Veenendaal, Bert; Brovelli, Maria Antonia; Wu, Lixin

2016-04-01

We live in a world that is alive with information and geographies. "Everything happens somewhere" (Tosta, 2001). This reality is being exposed in the digital earth technologies providing a multi-dimensional, multi-temporal and multi-resolution model of the planet, based on the needs of diverse actors: from scientists to decision makers, communities and citizens (Brovelli et al., 2015). We are building up a geospatial information infrastructure updated in real time thanks to mobile, positioning and sensor observations. Users can navigate, not only through space but also through time, to access historical data and future predictions based on social and/or environmental models. But how do we find the information about certain geographic locations or localities when it is scattered in the cloud and across the web of data behind a diversity of databases, web services and hyperlinked pages? We need to be able to link geoinformation together in order to integrate it, make sense of it, and use it appropriately for managing the world and making decisions.

Two Dimensional (2D) P-Aramid Dry Multi-Layered Woven Fabrics Deformational Behaviour for Technical Applications

NASA Astrophysics Data System (ADS)

Abtew, M. A.; Loghin, C.; Cristian, I.; Boussu, F.; Bruniaux, P.; Chen, Y.; Wang, L.

2018-06-01

In today’s scenario for the various technical applications, from composites to body armour, the material mouldability along with its mechanical property become very important. In the present study, two dimensional (2D) woven fabrics made of para-aramid high performance fibres in multi-layer dry structure were used for investigating different forming characteristics. The different layers were arranged with 0°/90° orientation for deep drawing formability test to analyse the effect of number of layers and blank-holder pressure (BHP) during the test. Specific preforming device with low speed forming process and predefined hemispherical shape of punch has been applied. Using fine photographic analysis, some important 2D multi-layer fabrics forming characteristics i.e., material drawing-in, surface shear angle etc. from the imposed deformation have been observed, measured and analysed for better understanding and co MPa rison. The result revealed that the mouldability behaviour of the multi-layered dry textile fabric preforms is directional, and closely dependent on blank-holding pressure and number of layers. This indicates both parameters should be carefully considered while material deformation to avoid the formation of wrinkling and maintain other mechanical properties on final application.

Sound transmission through stiffened double-panel structures lined with elastic porous materials

NASA Astrophysics Data System (ADS)

Mathur, Gopal P.; Tran, Boi N.; Bolton, J. S.; Shiau, Nae-Ming

This paper presents transmission loss prediction models for a periodically stiffened panel and stiffened double-panel structures using the periodic structure theory. The inter-panel cavity in the double-panels structures can be modeled as being separated by an airspace or filled with an elastic porous layer in various configurations. The acoustic behavior of elastic porous layer is described by a theory capable of accounting fully for multi-dimensional wave propagation in such materials. The predicted transmission loss of a single stiffened panel is compared with the measured data.

Multi-dimensional quantum state sharing based on quantum Fourier transform

NASA Astrophysics Data System (ADS)

Qin, Huawang; Tso, Raylin; Dai, Yuewei

2018-03-01

A scheme of multi-dimensional quantum state sharing is proposed. The dealer performs the quantum SUM gate and the quantum Fourier transform to encode a multi-dimensional quantum state into an entanglement state. Then the dealer distributes each participant a particle of the entanglement state, to share the quantum state among n participants. In the recovery, n-1 participants measure their particles and supply their measurement results; the last participant performs the unitary operation on his particle according to these measurement results and can reconstruct the initial quantum state. The proposed scheme has two merits: It can share the multi-dimensional quantum state and it does not need the entanglement measurement.

Final Technical Report: Mathematical Foundations for Uncertainty Quantification in Materials Design

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

Plechac, Petr; Vlachos, Dionisios G.

We developed path-wise information theory-based and goal-oriented sensitivity analysis and parameter identification methods for complex high-dimensional dynamics and in particular of non-equilibrium extended molecular systems. The combination of these novel methodologies provided the first methods in the literature which are capable to handle UQ questions for stochastic complex systems with some or all of the following features: (a) multi-scale stochastic models such as (bio)chemical reaction networks, with a very large number of parameters, (b) spatially distributed systems such as Kinetic Monte Carlo or Langevin Dynamics, (c) non-equilibrium processes typically associated with coupled physico-chemical mechanisms, driven boundary conditions, hybrid micro-macro systems,more » etc. A particular computational challenge arises in simulations of multi-scale reaction networks and molecular systems. Mathematical techniques were applied to in silico prediction of novel materials with emphasis on the effect of microstructure on model uncertainty quantification (UQ). We outline acceleration methods to make calculations of real chemistry feasible followed by two complementary tasks on structure optimization and microstructure-induced UQ.« less

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

Psychometrican analysis and dimensional structure of the Brazilian version of melasma quality of life scale (MELASQoL-BP)*

PubMed Central

Maranzatto, Camila Fernandes Pollo; Miot, Hélio Amante; Miot, Luciane Donida Bartoli; Meneguin, Silmara

2016-01-01

Background Although asymptomatic, melasma inflicts significant impact on quality of life. MELASQoL is the main instrument used to assess quality of life associated with melasma, it has been validated in several languages, but its latent dimensional structure and psychometric properties haven´t been fully explored. Objectives To evaluate psychometric characteristics, information and dimensional structure of the Brazilian version of MELASQoL. Methods Survey with patients with facial melasma through socio-demographic questionnaire, DLQI-BRA, MASI and MELASQoL-BP, exploratory and confirmatory factor analysis, internal consistency of MELASQoL and latent dimensions (Cronbach's alpha). The informativeness of the model and items were investigated by the Rasch model (ordinal data). Results We evaluated 154 patients, 134 (87%) were female, mean age (± SD) of 39 (± 8) years, the onset of melasma at 27 (± 8) years, median (p25-p75) of MASI scores , DLQI and MELASQoL 8 (5-15) 2 (1-6) and 30 (17-44). The correlation (rho) of MELASQoL with DLQI and MASI were: 0.70 and 0.36. Exploratory factor analysis identified two latent dimensions: Q1-Q3 and Q4-Q10, which had significantly more adjusted factor structure than the one-dimensional model: Χ2 / gl = 2.03, CFI = 0.95, AGFI = 0.94, RMSEA = 0.08. Cronbach's coefficient for the one-dimensional model and the factors were: 0.95, 0.92 and 0.93. Rasch analysis demonstrated that the use of seven alternatives per item resulted in no increase in the model informativeness. Conclusions MELASQoL-BP showed good psychometric performance and a latent structure of two dimensions. We also identified an oversizing of item alternatives to characterize the aggregate information to each dimension. PMID:27579735

Inference of multi-Gaussian property fields by probabilistic inversion of crosshole ground penetrating radar data using an improved dimensionality reduction

NASA Astrophysics Data System (ADS)

Hunziker, Jürg; Laloy, Eric; Linde, Niklas

2016-04-01

Deterministic inversion procedures can often explain field data, but they only deliver one final subsurface model that depends on the initial model and regularization constraints. This leads to poor insights about the uncertainties associated with the inferred model properties. In contrast, probabilistic inversions can provide an ensemble of model realizations that accurately span the range of possible models that honor the available calibration data and prior information allowing a quantitative description of model uncertainties. We reconsider the problem of inferring the dielectric permittivity (directly related to radar velocity) structure of the subsurface by inversion of first-arrival travel times from crosshole ground penetrating radar (GPR) measurements. We rely on the DREAM_(ZS) algorithm that is a state-of-the-art Markov chain Monte Carlo (MCMC) algorithm. Such algorithms need several orders of magnitude more forward simulations than deterministic algorithms and often become infeasible in high parameter dimensions. To enable high-resolution imaging with MCMC, we use a recently proposed dimensionality reduction approach that allows reproducing 2D multi-Gaussian fields with far fewer parameters than a classical grid discretization. We consider herein a dimensionality reduction from 5000 to 257 unknowns. The first 250 parameters correspond to a spectral representation of random and uncorrelated spatial fluctuations while the remaining seven geostatistical parameters are (1) the standard deviation of the data error, (2) the mean and (3) the variance of the relative electric permittivity, (4) the integral scale along the major axis of anisotropy, (5) the anisotropy angle, (6) the ratio of the integral scale along the minor axis of anisotropy to the integral scale along the major axis of anisotropy and (7) the shape parameter of the Matérn function. The latter essentially defines the type of covariance function (e.g., exponential, Whittle, Gaussian). We present an improved formulation of the dimensionality reduction, and numerically show how it reduces artifacts in the generated models and provides better posterior estimation of the subsurface geostatistical structure. We next show that the results of the method compare very favorably against previous deterministic and stochastic inversion results obtained at the South Oyster Bacterial Transport Site in Virginia, USA. The long-term goal of this work is to enable MCMC-based full waveform inversion of crosshole GPR data.

Multi-level diffractive optics for single laser exposure fabrication of telecom-band diamond-like 3-dimensional photonic crystals.

PubMed

Chanda, Debashis; Abolghasemi, Ladan E; Haque, Moez; Ng, Mi Li; Herman, Peter R

2008-09-29

We present a novel multi-level diffractive optical element for diffractive optic near-field lithography based fabrication of large-area diamond-like photonic crystal structure in a single laser exposure step. A multi-level single-surface phase element was laser fabricated on a thin polymer film by two-photon polymerization. A quarter-period phase shift was designed into the phase elements to generate a 3D periodic intensity distribution of double basis diamond-like structure. Finite difference time domain calculation of near-field diffraction patterns and associated isointensity surfaces are corroborated by definitive demonstration of a diamond-like woodpile structure formed inside thick photoresist. A large number of layers provided a strong stopband in the telecom band that matched predictions of numerical band calculation. SEM and spectral observations indicate good structural uniformity over large exposure area that promises 3D photonic crystal devices with high optical quality for a wide range of motif shapes and symmetries. Optical sensing is demonstrated by spectral shifts of the Gamma-Zeta stopband under liquid emersion.

Developing a Multi-Dimensional Early Elementary Mathematics Screener and Diagnostic Tool: The Primary Mathematics Assessment

ERIC Educational Resources Information Center

Brendefur, Jonathan L.; Johnson, Evelyn S.; Thiede, Keith W.; Strother, Sam; Severson, Herb H.

2018-01-01

There is a critical need to identify primary level students experiencing difficulties in mathematics to provide immediate and targeted instruction that remediates their deficits. However, most early math screening instruments focus only on the concept of number, resulting in inadequate and incomplete information for teachers to design intervention…

PIV measurements in a compact return diffuser under multi-conditions

NASA Astrophysics Data System (ADS)

Zhou, L.; Lu, W. G.; Shi, W. D.

2013-12-01

Due to the complex three-dimensional geometries of impellers and diffusers, their design is a delicate and difficult task. Slight change could lead to significant changes in hydraulic performance and internal flow structure. Conversely, the grasp of the pump's internal flow pattern could benefit from pump design improvement. The internal flow fields in a compact return diffuser have been investigated experimentally under multi-conditions. A special Particle Image Velocimetry (PIV) test rig is designed, and the two-dimensional PIV measurements are successfully conducted in the diffuser mid-plane to capture the complex flow patterns. The analysis of the obtained results has been focused on the flow structure in diffuser, especially under part-load conditions. The vortex and recirculation flow patterns in diffuser are captured and analysed accordingly. Strong flow separation and back flow appeared at the part-load flow rates. Under the design and over-load conditions, the flow fields in diffuser are uniform, and the flow separation and back flow appear at the part-load flow rates, strong back flow is captured at one diffuser passage under 0.2Qdes.

Reduced signal crosstalk multi neurotransmitter image sensor by microhole array structure

NASA Astrophysics Data System (ADS)

Ogaeri, Yuta; Lee, You-Na; Mitsudome, Masato; Iwata, Tatsuya; Takahashi, Kazuhiro; Sawada, Kazuaki

2018-06-01

A microhole array structure combined with an enzyme immobilization method using magnetic beads can enhance the target discernment capability of a multi neurotransmitter image sensor. Here we report the fabrication and evaluation of the H+-diffusion-preventing capability of the sensor with the array structure. The structure with an SU-8 photoresist has holes with a size of 24.5 × 31.6 µm2. Sensors were prepared with the array structure of three different heights: 0, 15, and 60 µm. When the sensor has the structure of 60 µm height, 48% reduced output voltage is measured at a H+-sensitive null pixel that is located 75 µm from the acetylcholinesterase (AChE)-immobilized pixel, which is the starting point of H+ diffusion. The suppressed H+ immigration is shown in a two-dimensional (2D) image in real time. The sensor parameters, such as height of the array structure and measuring time, are optimized experimentally. The sensor is expected to effectively distinguish various neurotransmitters in biological samples.

Three-dimensional wet-electrospun poly(lactic acid)/multi-wall carbon nanotubes scaffold induces differentiation of human menstrual blood-derived stem cells into germ-like cells.

PubMed

Eyni, Hossein; Ghorbani, Sadegh; Shirazi, Reza; Salari Asl, Leila; P Beiranvand, Shahram; Soleimani, Masoud

2017-09-01

Infertility caused by the disruption or absence of germ cells is a major and largely incurable medical problem. Germ cells (i.e., sperm or egg) play a key role in the transmission of genetic and epigenetic information across generations. Generation of gametes derived in vitro from stem cells hold promising prospects which could potentially help infertile men and women. Menstrual blood-derived stem cells are a unique stem cell source. Evidence suggests that menstrual blood-derived stem cells exhibit a multi-lineage potential and have attracted extensive attention in regenerative medicine. To maintain the three-dimensional structure of natural extra cellular matrices in vitro, scaffolds can do this favor and mimic a microenvironment for cell proliferation and differentiation. According to previous studies, poly(lactic acid) and multi-wall carbon nanotubes have been introduced as novel and promising biomaterials for the proliferation and differentiation of stem cells. Some cell types have been successfully grown on a matrix containing carbon nanotubes in tissue engineering but there is no report for this material to support stem cells differentiation into germ cells lineage. This study designed a 3D wet-electrospun poly(lactic acid) and poly(lactic acid)/multi-wall carbon nanotubes composite scaffold to compare infiltration, proliferation, and differentiation potential of menstrual blood-derived stem cells toward germ cell lineage with 2D culture. Our primary data revealed that the fabricated scaffold has mechanical and biological suitable qualities for supporting and attachments of stem cells. The differentiated menstrual blood-derived stem cells tracking in scaffolds using scanning electron microscopy confirmed cell attachment, aggregation, and distribution on the porous scaffold. Based on the differentiation assay by RT-PCR analysis, stem cells and germ-like cells markers were expressed in 3D groups as well as 2D one. It seems that poly(lactic acid)/multi-wall carbon nanotubes scaffold-seeded menstrual blood-derived stem cells could be viewed as a novel, safe, and accessible construct for these cells, as they enhance germ-like generation from menstrual blood-derived stem cells.

Measuring the Perception of the Teachers' Autonomy-Supportive Behavior in Physical Education: Development and Initial Validation of a Multi-Dimensional Instrument

ERIC Educational Resources Information Center

Tilga, Henri; Hein, Vello; Koka, Andre

2017-01-01

This research aimed to develop and validate an instrument to assess the students' perceptions of the teachers' autonomy-supportive behavior by the multi-dimensional scale (Multi-Dimensional Perceived Autonomy Support Scale for Physical Education). The participants were 1,476 students aged 12- to 15-years-old. In Study 1, a pool of 37 items was…

Current Scientific Approaches to Decision Making in Complex Systems. 3. Volume 2. Conference Position Papers

DTIC Science & Technology

1980-01-01

Search: Traffic on a Multi- dimensional Structure R. i. Atkin, University of Essex, England b. Annex. Volume 3: Decision: Foundation and Practice Brian R...Gaines, University of Essex, England Volume 4: Competing Modes of Cognition and Communication in Simulated and Self-Reflective Systems Stein Braten... University of Oslo, Norway Volume 5: On the Spontaneous Emergence of Decision Making Constraints in Communicating Hierarchical Structure John S

3-Dimensional Nano-Scale Reinforcement Architecture for Advanced Composite Structures

DTIC Science & Technology

2008-10-01

textile structures on 3TEX equipment. Conduct experimental studies of the spinnability of Multi-Wall Carbon Nanotube ( MWCNT ) forests and...adjacent inner wall when MWNT length is one centimeter (Fig. 1.8). Complete stress transfer to all walls by going to longer nanotube lengths could...between regular IK T300 carbon yarn and 25-ply carbon nanotube yarn. Fig. 5.8 shows the nanotube yarns going through the heddles during weaving with

UNIX: A Tool for Information Management.

ERIC Educational Resources Information Center

Frey, Dean

1989-01-01

Describes UNIX, a computer operating system that supports multi-task and multi-user operations. Characteristics that make it especially suitable for library applications are discussed, including a hierarchical file structure and utilities for text processing, database activities, and bibliographic work. Sources of information on hardware…

D Nearest Neighbour Search Using a Clustered Hierarchical Tree Structure

NASA Astrophysics Data System (ADS)

Suhaibah, A.; Uznir, U.; Anton, F.; Mioc, D.; Rahman, A. A.

2016-06-01

Locating and analysing the location of new stores or outlets is one of the common issues facing retailers and franchisers. This is due to assure that new opening stores are at their strategic location to attract the highest possible number of customers. Spatial information is used to manage, maintain and analyse these store locations. However, since the business of franchising and chain stores in urban areas runs within high rise multi-level buildings, a three-dimensional (3D) method is prominently required in order to locate and identify the surrounding information such as at which level of the franchise unit will be located or is the franchise unit located is at the best level for visibility purposes. One of the common used analyses used for retrieving the surrounding information is Nearest Neighbour (NN) analysis. It uses a point location and identifies the surrounding neighbours. However, with the immense number of urban datasets, the retrieval and analysis of nearest neighbour information and their efficiency will become more complex and crucial. In this paper, we present a technique to retrieve nearest neighbour information in 3D space using a clustered hierarchical tree structure. Based on our findings, the proposed approach substantially showed an improvement of response time analysis compared to existing approaches of spatial access methods in databases. The query performance was tested using a dataset consisting of 500,000 point locations building and franchising unit. The results are presented in this paper. Another advantage of this structure is that it also offers a minimal overlap and coverage among nodes which can reduce repetitive data entry.

Automated integration of lidar into the LANDFIRE product suite

Treesearch

Birgit Peterson; Kurtis J. Nelson; Carl Seielstad; Jason Stoker; W. Matt Jolly; Russell Parsons

2015-01-01

Accurate information about three-dimensional canopy structure and wildland fuel across the landscape is necessary for fire behaviour modelling system predictions. Remotely sensed data are invaluable for assessing these canopy characteristics over large areas; lidar data, in particular, are uniquely suited for quantifying three-dimensional canopy structure. Although...

Two-dimensional imaging of gas temperature and concentration based on hyperspectral tomography

NASA Astrophysics Data System (ADS)

Xin, Ming-yuan; Jin, Xing; Wang, Guang-yu; Song, Junling

2016-10-01

Two-dimensional imaging of gas temperature and concentration is realized by hyperspectral tomography, which has the characteristics of using multi-wavelengths absorption spectral information, so that the imaging could be accomplished in a small number of projections and viewing angles. A temperature and concentration model is established to simulate the combustion conditions and a total number of 10 near-infrared absorption spectral information of H2O is used. An improved simulated annealing algorithm by adjusting search step is performed the main search algorithm for the tomography. By adding random errors into the absorption area information, the stability of the algorithm is tested, and the results are compared with the reconstructions provided by algebraic reconstruction technique which takes advantage of 2 spectral information contents in imaging. The results show that the two methods perform equivalent in low-level noise environment, but at high-level, hyperspectral tomography turns out to be more stable.

A Noncontact FMCW Radar Sensor for Displacement Measurement in Structural Health Monitoring

PubMed Central

Li, Cunlong; Chen, Weimin; Liu, Gang; Yan, Rong; Xu, Hengyi; Qi, Yi

2015-01-01

This paper investigates the Frequency Modulation Continuous Wave (FMCW) radar sensor for multi-target displacement measurement in Structural Health Monitoring (SHM). The principle of three-dimensional (3-D) displacement measurement of civil infrastructures is analyzed. The requirements of high-accuracy displacement and multi-target identification for the measuring sensors are discussed. The fundamental measuring principle of FMCW radar is presented with rigorous mathematical formulas, and further the multiple-target displacement measurement is analyzed and simulated. In addition, a FMCW radar prototype is designed and fabricated based on an off-the-shelf radar frontend and data acquisition (DAQ) card, and the displacement error induced by phase asynchronism is analyzed. The conducted outdoor experiments verify the feasibility of this sensing method applied to multi-target displacement measurement, and experimental results show that three targets located at different distances can be distinguished simultaneously with millimeter level accuracy. PMID:25822139

A noncontact FMCW radar sensor for displacement measurement in structural health monitoring.

PubMed

Li, Cunlong; Chen, Weimin; Liu, Gang; Yan, Rong; Xu, Hengyi; Qi, Yi

2015-03-26

This paper investigates the Frequency Modulation Continuous Wave (FMCW) radar sensor for multi-target displacement measurement in Structural Health Monitoring (SHM). The principle of three-dimensional (3-D) displacement measurement of civil infrastructures is analyzed. The requirements of high-accuracy displacement and multi-target identification for the measuring sensors are discussed. The fundamental measuring principle of FMCW radar is presented with rigorous mathematical formulas, and further the multiple-target displacement measurement is analyzed and simulated. In addition, a FMCW radar prototype is designed and fabricated based on an off-the-shelf radar frontend and data acquisition (DAQ) card, and the displacement error induced by phase asynchronism is analyzed. The conducted outdoor experiments verify the feasibility of this sensing method applied to multi-target displacement measurement, and experimental results show that three targets located at different distances can be distinguished simultaneously with millimeter level accuracy.

The BioIntelligence Framework: a new computational platform for biomedical knowledge computing.

PubMed

Farley, Toni; Kiefer, Jeff; Lee, Preston; Von Hoff, Daniel; Trent, Jeffrey M; Colbourn, Charles; Mousses, Spyro

2013-01-01

Breakthroughs in molecular profiling technologies are enabling a new data-intensive approach to biomedical research, with the potential to revolutionize how we study, manage, and treat complex diseases. The next great challenge for clinical applications of these innovations will be to create scalable computational solutions for intelligently linking complex biomedical patient data to clinically actionable knowledge. Traditional database management systems (DBMS) are not well suited to representing complex syntactic and semantic relationships in unstructured biomedical information, introducing barriers to realizing such solutions. We propose a scalable computational framework for addressing this need, which leverages a hypergraph-based data model and query language that may be better suited for representing complex multi-lateral, multi-scalar, and multi-dimensional relationships. We also discuss how this framework can be used to create rapid learning knowledge base systems to intelligently capture and relate complex patient data to biomedical knowledge in order to automate the recovery of clinically actionable information.

Multi-path variational transition state theory for chemical reaction rates of complex polyatomic species: ethanol + OH reactions.

PubMed

Zheng, Jingjing; Truhlar, Donald G

2012-01-01

Complex molecules often have many structures (conformations) of the reactants and the transition states, and these structures may be connected by coupled-mode torsions and pseudorotations; some but not all structures may have hydrogen bonds in the transition state or reagents. A quantitative theory of the reaction rates of complex molecules must take account of these structures, their coupled-mode nature, their qualitatively different character, and the possibility of merging reaction paths at high temperature. We have recently developed a coupled-mode theory called multi-structural variational transition state theory (MS-VTST) and an extension, called multi-path variational transition state theory (MP-VTST), that includes a treatment of the differences in the multi-dimensional tunneling paths and their contributions to the reaction rate. The MP-VTST method was presented for unimolecular reactions in the original paper and has now been extended to bimolecular reactions. The MS-VTST and MP-VTST formulations of variational transition state theory include multi-faceted configuration-space dividing surfaces to define the variational transition state. They occupy an intermediate position between single-conformation variational transition state theory (VTST), which has been used successfully for small molecules, and ensemble-averaged variational transition state theory (EA-VTST), which has been used successfully for enzyme kinetics. The theories are illustrated and compared here by application to three thermal rate constants for reactions of ethanol with hydroxyl radical--reactions with 4, 6, and 14 saddle points.

Discovering Hidden Controlling Parameters using Data Analytics and Dimensional Analysis

NASA Astrophysics Data System (ADS)

Del Rosario, Zachary; Lee, Minyong; Iaccarino, Gianluca

2017-11-01

Dimensional Analysis is a powerful tool, one which takes a priori information and produces important simplifications. However, if this a priori information - the list of relevant parameters - is missing a relevant quantity, then the conclusions from Dimensional Analysis will be incorrect. In this work, we present novel conclusions in Dimensional Analysis, which provide a means to detect this failure mode of missing or hidden parameters. These results are based on a restated form of the Buckingham Pi theorem that reveals a ridge function structure underlying all dimensionless physical laws. We leverage this structure by constructing a hypothesis test based on sufficient dimension reduction, allowing for an experimental data-driven detection of hidden parameters. Both theory and examples will be presented, using classical turbulent pipe flow as the working example. Keywords: experimental techniques, dimensional analysis, lurking variables, hidden parameters, buckingham pi, data analysis. First author supported by the NSF GRFP under Grant Number DGE-114747.

A stereo remote sensing feature selection method based on artificial bee colony algorithm

NASA Astrophysics Data System (ADS)

Yan, Yiming; Liu, Pigang; Zhang, Ye; Su, Nan; Tian, Shu; Gao, Fengjiao; Shen, Yi

2014-05-01

To improve the efficiency of stereo information for remote sensing classification, a stereo remote sensing feature selection method is proposed in this paper presents, which is based on artificial bee colony algorithm. Remote sensing stereo information could be described by digital surface model (DSM) and optical image, which contain information of the three-dimensional structure and optical characteristics, respectively. Firstly, three-dimensional structure characteristic could be analyzed by 3D-Zernike descriptors (3DZD). However, different parameters of 3DZD could descript different complexity of three-dimensional structure, and it needs to be better optimized selected for various objects on the ground. Secondly, features for representing optical characteristic also need to be optimized. If not properly handled, when a stereo feature vector composed of 3DZD and image features, that would be a lot of redundant information, and the redundant information may not improve the classification accuracy, even cause adverse effects. To reduce information redundancy while maintaining or improving the classification accuracy, an optimized frame for this stereo feature selection problem is created, and artificial bee colony algorithm is introduced for solving this optimization problem. Experimental results show that the proposed method can effectively improve the computational efficiency, improve the classification accuracy.

Pharmacy Information Systems in Teaching Hospitals: A Multi-dimensional Evaluation Study.

PubMed

Kazemi, Alireza; Rabiei, Reza; Moghaddasi, Hamid; Deimazar, Ghasem

2016-07-01

In hospitals, the pharmacy information system (PIS) is usually a sub-system of the hospital information system (HIS). The PIS supports the distribution and management of drugs, shows drug and medical device inventory, and facilitates preparing needed reports. In this study, pharmacy information systems implemented in general teaching hospitals affiliated to medical universities in Tehran (Iran) were evaluated using a multi-dimensional tool. This was an evaluation study conducted in 2015. To collect data, a checklist was developed by reviewing the relevant literature; this checklist included both general and specific criteria to evaluate pharmacy information systems. The checklist was then validated by medical informatics experts and pharmacists. The sample of the study included five PIS in general-teaching hospitals affiliated to three medical universities in Tehran (Iran). Data were collected using the checklist and through observing the systems. The findings were presented as tables. Five PIS were evaluated in the five general-teaching hospitals that had the highest bed numbers. The findings showed that the evaluated pharmacy information systems lacked some important general and specific criteria. Among the general evaluation criteria, it was found that only two of the PIS studied were capable of restricting repeated attempts made for unauthorized access to the systems. With respect to the specific evaluation criteria, no attention was paid to the patient safety aspect. The PIS studied were mainly designed to support financial tasks; little attention was paid to clinical and patient safety features.

Nonlinear Conservation Laws and Finite Volume Methods

NASA Astrophysics Data System (ADS)

Leveque, Randall J.

Introduction Software Notation Classification of Differential Equations Derivation of Conservation Laws The Euler Equations of Gas Dynamics Dissipative Fluxes Source Terms Radiative Transfer and Isothermal Equations Multi-dimensional Conservation Laws The Shock Tube Problem Mathematical Theory of Hyperbolic Systems Scalar Equations Linear Hyperbolic Systems Nonlinear Systems The Riemann Problem for the Euler Equations Numerical Methods in One Dimension Finite Difference Theory Finite Volume Methods Importance of Conservation Form - Incorrect Shock Speeds Numerical Flux Functions Godunov's Method Approximate Riemann Solvers High-Resolution Methods Other Approaches Boundary Conditions Source Terms and Fractional Steps Unsplit Methods Fractional Step Methods General Formulation of Fractional Step Methods Stiff Source Terms Quasi-stationary Flow and Gravity Multi-dimensional Problems Dimensional Splitting Multi-dimensional Finite Volume Methods Grids and Adaptive Refinement Computational Difficulties Low-Density Flows Discrete Shocks and Viscous Profiles Start-Up Errors Wall Heating Slow-Moving Shocks Grid Orientation Effects Grid-Aligned Shocks Magnetohydrodynamics The MHD Equations One-Dimensional MHD Solving the Riemann Problem Nonstrict Hyperbolicity Stiffness The Divergence of B Riemann Problems in Multi-dimensional MHD Staggered Grids The 8-Wave Riemann Solver Relativistic Hydrodynamics Conservation Laws in Spacetime The Continuity Equation The 4-Momentum of a Particle The Stress-Energy Tensor Finite Volume Methods Multi-dimensional Relativistic Flow Gravitation and General Relativity References

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.

Scientific Visualization and Simulation for Multi-dimensional Marine Environment Data

NASA Astrophysics Data System (ADS)

Su, T.; Liu, H.; Wang, W.; Song, Z.; Jia, Z.

2017-12-01

As higher attention on the ocean and rapid development of marine detection, there are increasingly demands for realistic simulation and interactive visualization of marine environment in real time. Based on advanced technology such as GPU rendering, CUDA parallel computing and rapid grid oriented strategy, a series of efficient and high-quality visualization methods, which can deal with large-scale and multi-dimensional marine data in different environmental circumstances, has been proposed in this paper. Firstly, a high-quality seawater simulation is realized by FFT algorithm, bump mapping and texture animation technology. Secondly, large-scale multi-dimensional marine hydrological environmental data is virtualized by 3d interactive technologies and volume rendering techniques. Thirdly, seabed terrain data is simulated with improved Delaunay algorithm, surface reconstruction algorithm, dynamic LOD algorithm and GPU programming techniques. Fourthly, seamless modelling in real time for both ocean and land based on digital globe is achieved by the WebGL technique to meet the requirement of web-based application. The experiments suggest that these methods can not only have a satisfying marine environment simulation effect, but also meet the rendering requirements of global multi-dimension marine data. Additionally, a simulation system for underwater oil spill is established by OSG 3D-rendering engine. It is integrated with the marine visualization method mentioned above, which shows movement processes, physical parameters, current velocity and direction for different types of deep water oil spill particle (oil spill particles, hydrates particles, gas particles, etc.) dynamically and simultaneously in multi-dimension. With such application, valuable reference and decision-making information can be provided for understanding the progress of oil spill in deep water, which is helpful for ocean disaster forecasting, warning and emergency response.

Highly cytocompatible and flexible three-dimensional graphene/polydimethylsiloxane composite for culture and electrochemical detection of L929 fibroblast cells.

PubMed

Waiwijit, Uraiwan; Maturos, Thitima; Pakapongpan, Saithip; Phokharatkul, Ditsayut; Wisitsoraat, Anurat; Tuantranont, Adisorn

2016-08-01

Recently, three-dimensional graphene interconnected network has attracted great interest as a scaffold structure for tissue engineering due to its high biocompatibility, high electrical conductivity, high specific surface area and high porosity. However, free-standing three-dimensional graphene exhibits poor flexibility and stability due to ease of disintegration during processing. In this work, three-dimensional graphene is composited with polydimethylsiloxane to improve the structural flexibility and stability by a new simple two-step process comprising dip coating of polydimethylsiloxane on chemical vapor deposited graphene/Ni foam and wet etching of nickel foam. Structural characterizations confirmed an interconnected three-dimensional multi-layer graphene structure with thin polydimethylsiloxane scaffold. The composite was employed as a substrate for culture of L929 fibroblast cells and its cytocompatibility was evaluated by cell viability (Alamar blue assay), reactive oxygen species production and vinculin immunofluorescence imaging. The result revealed that cell viability on three-dimensional graphene/polydimethylsiloxane composite increased with increasing culture time and was slightly different from a polystyrene substrate (control). Moreover, cells cultured on three-dimensional graphene/polydimethylsiloxane composite generated less ROS than the control at culture times of 3-6 h. The results of immunofluorescence staining demonstrated that fibroblast cells expressed adhesion protein (vinculin) and adhered well on three-dimensional graphene/polydimethylsiloxane surface. Good cell adhesion could be attributed to suitable surface properties of three-dimensional graphene/polydimethylsiloxane with moderate contact angle and small negative zeta potential in culture solution. The results of electrochemical study by cyclic voltammetry showed that an oxidation current signal with no apparent peak was induced by fibroblast cells and the oxidation current at an oxidation potential of +0.9 V increased linearly with increasing cell number. Therefore, the three-dimensional graphene/polydimethylsiloxane composite exhibits high cytocompatibility and can potentially be used as a conductive substrate for cell-based electrochemical sensing. © The Author(s) 2016.

Assessing Structure and Condition of Temperate And Tropical Forests: Fusion of Terrestrial Lidar and Airborne Multi-Angle and Lidar Remote Sensing

NASA Astrophysics Data System (ADS)

Saenz, Edward J.

Forests provide vital ecosystem functions and services that maintain the integrity of our natural and human environment. Understanding the structural components of forests (extent, tree density, heights of multi-story canopies, biomass, etc.) provides necessary information to preserve ecosystem services. Increasingly, remote sensing resources have been used to map and monitor forests globally. However, traditional satellite and airborne multi-angle imagery only provide information about the top of the canopy and little about the forest structure and understory. In this research, we investigative the use of rapidly evolving lidar technology, and how the fusion of aerial and terrestrial lidar data can be utilized to better characterize forest stand information. We further apply a novel terrestrial lidar methodology to characterize a Hemlock Woolly Adelgid infestation in Harvard Forest, Massachusetts, and adapt a dynamic terrestrial lidar sampling scheme to identify key structural vegetation profiles of tropical rainforests in La Selva, Costa Rica.

Fiber bundle endomicroscopy with multi-illumination for three-dimensional reflectance image reconstruction

NASA Astrophysics Data System (ADS)

Ando, Yoriko; Sawahata, Hirohito; Kawano, Takeshi; Koida, Kowa; Numano, Rika

2018-02-01

Bundled fiber optics allow in vivo imaging at deep sites in a body. The intrinsic optical contrast detects detailed structures in blood vessels and organs. We developed a bundled-fiber-coupled endomicroscope, enabling stereoscopic three-dimensional (3-D) reflectance imaging with a multipositional illumination scheme. Two illumination sites were attached to obtain reflectance images with left and right illumination. Depth was estimated by the horizontal disparity between the two images under alternative illuminations and was calibrated by the targets with known depths. This depth reconstruction was applied to an animal model to obtain the 3-D structure of blood vessels of the cerebral cortex (Cereb cortex) and preputial gland (Pre gla). The 3-D endomicroscope could be instrumental to microlevel reflectance imaging, improving the precision in subjective depth perception, spatial orientation, and identification of anatomical structures.

Autocorrelation structure of convective rainfall in semiarid-arid climate derived from high-resolution X-Band radar estimates

NASA Astrophysics Data System (ADS)

Marra, Francesco; Morin, Efrat

2018-02-01

Small scale rainfall variability is a key factor driving runoff response in fast responding systems, such as mountainous, urban and arid catchments. In this paper, the spatial-temporal autocorrelation structure of convective rainfall is derived with extremely high resolutions (60 m, 1 min) using estimates from an X-Band weather radar recently installed in a semiarid-arid area. The 2-dimensional spatial autocorrelation of convective rainfall fields and the temporal autocorrelation of point-wise and distributed rainfall fields are examined. The autocorrelation structures are characterized by spatial anisotropy, correlation distances 1.5-2.8 km and rarely exceeding 5 km, and time-correlation distances 1.8-6.4 min and rarely exceeding 10 min. The observed spatial variability is expected to negatively affect estimates from rain gauges and microwave links rather than satellite and C-/S-Band radars; conversely, the temporal variability is expected to negatively affect remote sensing estimates rather than rain gauges. The presented results provide quantitative information for stochastic weather generators, cloud-resolving models, dryland hydrologic and agricultural models, and multi-sensor merging techniques.

Hydraulic head estimation at unobserved locations: Approximating the distribution of the absolute error based on geologic interpretations

NASA Astrophysics Data System (ADS)

Langousis, Andreas; Kaleris, Vassilios; Xeygeni, Vagia; Magkou, Foteini

2017-04-01

Assessing the availability of groundwater reserves at a regional level, requires accurate and robust hydraulic head estimation at multiple locations of an aquifer. To that extent, one needs groundwater observation networks that can provide sufficient information to estimate the hydraulic head at unobserved locations. The density of such networks is largely influenced by the spatial distribution of the hydraulic conductivity in the aquifer, and it is usually determined through trial-and-error, by solving the groundwater flow based on a properly selected set of alternative but physically plausible geologic structures. In this work, we use: 1) dimensional analysis, and b) a pulse-based stochastic model for simulation of synthetic aquifer structures, to calculate the distribution of the absolute error in hydraulic head estimation as a function of the standardized distance from the nearest measuring locations. The resulting distributions are proved to encompass all possible small-scale structural dependencies, exhibiting characteristics (bounds, multi-modal features etc.) that can be explained using simple geometric arguments. The obtained results are promising, pointing towards the direction of establishing design criteria based on large-scale geologic maps.

A comprehensive simulation framework for imaging single particles and biomolecules at the European X-ray Free-Electron Laser

NASA Astrophysics Data System (ADS)

Yoon, Chun Hong; Yurkov, Mikhail V.; Schneidmiller, Evgeny A.; Samoylova, Liubov; Buzmakov, Alexey; Jurek, Zoltan; Ziaja, Beata; Santra, Robin; Loh, N. Duane; Tschentscher, Thomas; Mancuso, Adrian P.

2016-04-01

The advent of newer, brighter, and more coherent X-ray sources, such as X-ray Free-Electron Lasers (XFELs), represents a tremendous growth in the potential to apply coherent X-rays to determine the structure of materials from the micron-scale down to the Angstrom-scale. There is a significant need for a multi-physics simulation framework to perform source-to-detector simulations for a single particle imaging experiment, including (i) the multidimensional simulation of the X-ray source; (ii) simulation of the wave-optics propagation of the coherent XFEL beams; (iii) atomistic modelling of photon-material interactions; (iv) simulation of the time-dependent diffraction process, including incoherent scattering; (v) assembling noisy and incomplete diffraction intensities into a three-dimensional data set using the Expansion-Maximisation-Compression (EMC) algorithm and (vi) phase retrieval to obtain structural information. We demonstrate the framework by simulating a single-particle experiment for a nitrogenase iron protein using parameters of the SPB/SFX instrument of the European XFEL. This exercise demonstrably yields interpretable consequences for structure determination that are crucial yet currently unavailable for experiment design.

Two antenna, two pass interferometric synthetic aperture radar

DOEpatents

Martinez, Ana; Doerry, Armin W.; Bickel, Douglas L.

2005-06-28

A multi-antenna, multi-pass IFSAR mode utilizing data driven alignment of multiple independent passes can combine the scaling accuracy of a two-antenna, one-pass IFSAR mode with the height-noise performance of a one-antenna, two-pass IFSAR mode. A two-antenna, two-pass IFSAR mode can accurately estimate the larger antenna baseline from the data itself and reduce height-noise, allowing for more accurate information about target ground position locations and heights. The two-antenna, two-pass IFSAR mode can use coarser IFSAR data to estimate the larger antenna baseline. Multi-pass IFSAR can be extended to more than two (2) passes, thereby allowing true three-dimensional radar imaging from stand-off aircraft and satellite platforms.

Method and system for data clustering for very large databases

NASA Technical Reports Server (NTRS)

Livny, Miron (Inventor); Zhang, Tian (Inventor); Ramakrishnan, Raghu (Inventor)

1998-01-01

Multi-dimensional data contained in very large databases is efficiently and accurately clustered to determine patterns therein and extract useful information from such patterns. Conventional computer processors may be used which have limited memory capacity and conventional operating speed, allowing massive data sets to be processed in a reasonable time and with reasonable computer resources. The clustering process is organized using a clustering feature tree structure wherein each clustering feature comprises the number of data points in the cluster, the linear sum of the data points in the cluster, and the square sum of the data points in the cluster. A dense region of data points is treated collectively as a single cluster, and points in sparsely occupied regions can be treated as outliers and removed from the clustering feature tree. The clustering can be carried out continuously with new data points being received and processed, and with the clustering feature tree being restructured as necessary to accommodate the information from the newly received data points.

Simultaneous reconstruction of 3D refractive index, temperature, and intensity distribution of combustion flame by double computed tomography technologies based on spatial phase-shifting method

NASA Astrophysics Data System (ADS)

Guo, Zhenyan; Song, Yang; Yuan, Qun; Wulan, Tuya; Chen, Lei

2017-06-01

In this paper, a transient multi-parameter three-dimensional (3D) reconstruction method is proposed to diagnose and visualize a combustion flow field. Emission and transmission tomography based on spatial phase-shifted technology are combined to reconstruct, simultaneously, the various physical parameter distributions of a propane flame. Two cameras triggered by the internal trigger mode capture the projection information of the emission and moiré tomography, respectively. A two-step spatial phase-shifting method is applied to extract the phase distribution in the moiré fringes. By using the filtered back-projection algorithm, we reconstruct the 3D refractive-index distribution of the combustion flow field. Finally, the 3D temperature distribution of the flame is obtained from the refractive index distribution using the Gladstone-Dale equation. Meanwhile, the 3D intensity distribution is reconstructed based on the radiation projections from the emission tomography. Therefore, the structure and edge information of the propane flame are well visualized.

Band warping, band non-parabolicity, and Dirac points in electronic and lattice structures

NASA Astrophysics Data System (ADS)

Resca, Lorenzo; Mecholsky, Nicholas A.; Pegg, Ian L.

2017-10-01

We illustrate at a fundamental level the physical and mathematical origins of band warping and band non-parabolicity in electronic and vibrational structures. We point out a robust presence of pairs of topologically induced Dirac points in a primitive-rectangular lattice using a p-type tight-binding approximation. We analyze two-dimensional primitive-rectangular and square Bravais lattices with implications that are expected to generalize to more complex structures. Band warping is shown to arise at the onset of a singular transition to a crystal lattice with a larger symmetry group, which allows the possibility of irreducible representations of higher dimensions, hence band degeneracy, at special symmetry points in reciprocal space. Band warping is incompatible with a multi-dimensional Taylor series expansion, whereas band non-parabolicities are associated with multi-dimensional Taylor series expansions to all orders. Still band non-parabolicities may merge into band warping at the onset of a larger symmetry group. Remarkably, while still maintaining a clear connection with that merging, band non-parabolicities may produce pairs of conical intersections at relatively low-symmetry points. Apparently, such conical intersections are robustly maintained by global topology requirements, rather than any local symmetry protection. For two p-type tight-binding bands, we find such pairs of conical intersections drifting along the edges of restricted Brillouin zones of primitive-rectangular Bravais lattices as lattice constants vary relatively to each other, until these conical intersections merge into degenerate warped bands at high-symmetry points at the onset of a square lattice. The conical intersections that we found appear to have similar topological characteristics as Dirac points extensively studied in graphene and other topological insulators, even though our conical intersections have none of the symmetry complexity and protection afforded by the latter more complex structures.

Three-dimensional Crustal Structure beneath the Tibetan Plateau Revealed by Multi-scale Gravity Analysis

NASA Astrophysics Data System (ADS)

Xu, C.; Luo, Z.; Sun, R.; Li, Q.

2017-12-01

The Tibetan Plateau, the largest and highest plateau on Earth, was uplifted, shorten and thicken by the collision and continuous convergence of the Indian and Eurasian plates since 50 million years ago, the Eocene epoch. Fine three-dimensional crustal structure of the Tibetan Plateau is helpful in understanding the tectonic development. At present, the ordinary method used for revealing crustal structure is seismic method, which is inhibited by poor seismic station coverage, especially in the central and western plateau primarily due to the rugged terrain. Fortunately, with the implementation of satellite gravity missions, gravity field models have demonstrated unprecedented global-scale accuracy and spatial resolution, which can subsequently be employed to study the crustal structure of the entire Tibetan Plateau. This study inverts three-dimensional crustal density and Moho topography of the Tibetan Plateau from gravity data using multi-scale gravity analysis. The inverted results are in agreement with those provided by the previous works. Besides, they can reveal rich tectonic development of the Tibetan Plateau: (1) The low-density channel flow can be observed from the inverted crustal density; (2) The Moho depth in the west is deeper than that in the east, and the deepest Moho, which is approximately 77 km, is located beneath the western Qiangtang Block; (3) The Moho fold, the directions of which are in agreement with the results of surface movement velocities estimated from Global Positioning System, exists clearly on the Moho topography.This study is supported by the National Natural Science Foundation of China (Grant No. 41504015), the China Postdoctoral Science Foundation (Grant No. 2015M572146), and the Surveying and Mapping Basic Research Programme of the National Administration of Surveying, Mapping and Geoinformation (Grant No. 15-01-08).

Array-based Hierarchical Mesh Generation in Parallel

DOE PAGES

Ray, Navamita; Grindeanu, Iulian; Zhao, Xinglin; ...

2015-11-03

In this paper, we describe an array-based hierarchical mesh generation capability through uniform refinement of unstructured meshes for efficient solution of PDE's using finite element methods and multigrid solvers. A multi-degree, multi-dimensional and multi-level framework is designed to generate the nested hierarchies from an initial mesh that can be used for a number of purposes such as multi-level methods to generating large meshes. The capability is developed under the parallel mesh framework “Mesh Oriented dAtaBase” a.k.a MOAB. We describe the underlying data structures and algorithms to generate such hierarchies and present numerical results for computational efficiency and mesh quality. Inmore » conclusion, we also present results to demonstrate the applicability of the developed capability to a multigrid finite-element solver.« less

Laser direct-write for fabrication of three-dimensional paper-based devices.

PubMed

He, P J W; Katis, I N; Eason, R W; Sones, C L

2016-08-16

We report the use of a laser-based direct-write (LDW) technique that allows the design and fabrication of three-dimensional (3D) structures within a paper substrate that enables implementation of multi-step analytical assays via a 3D protocol. The technique is based on laser-induced photo-polymerisation, and through adjustment of the laser writing parameters such as the laser power and scan speed we can control the depths of hydrophobic barriers that are formed within a substrate which, when carefully designed and integrated, produce 3D flow paths. So far, we have successfully used this depth-variable patterning protocol for stacking and sealing of multi-layer substrates, for assembly of backing layers for two-dimensional (2D) lateral flow devices and finally for fabrication of 3D devices. Since the 3D flow paths can also be formed via a single laser-writing process by controlling the patterning parameters, this is a distinct improvement over other methods that require multiple complicated and repetitive assembly procedures. This technique is therefore suitable for cheap, rapid and large-scale fabrication of 3D paper-based microfluidic devices.

Topology of large-scale structure. IV - Topology in two dimensions

NASA Technical Reports Server (NTRS)

Melott, Adrian L.; Cohen, Alexander P.; Hamilton, Andrew J. S.; Gott, J. Richard, III; Weinberg, David H.

1989-01-01

In a recent series of papers, an algorithm was developed for quantitatively measuring the topology of the large-scale structure of the universe and this algorithm was applied to numerical models and to three-dimensional observational data sets. In this paper, it is shown that topological information can be derived from a two-dimensional cross section of a density field, and analytic expressions are given for a Gaussian random field. The application of a two-dimensional numerical algorithm for measuring topology to cross sections of three-dimensional models is demonstrated.

Simulating multi-spacecraft Heliospheric Imager observations for tomographic reconstruction of interplanetary CMEs

NASA Astrophysics Data System (ADS)

Barnes, D.

2017-12-01

The multiple, spatially separated vantage points afforded by the STEREO and SOHO missions provide physicists with a means to infer the three-dimensional structure of the solar corona via tomographic imaging. The reconstruction process combines these multiple projections of the optically thin plasma to constrain its three-dimensional density structure and has been successfully applied to the low corona using the STEREO and SOHO coronagraphs. However, the technique is also possible at larger, inter-planetary distances using wide-angle imagers, such as the STEREO Heliospheric Imagers (HIs), to observe faint solar wind plasma and Coronal Mass Ejections (CMEs). Limited small-scale structure may be inferred from only three, or fewer, viewpoints and the work presented here is done so with the aim of establishing techniques for observing CMEs with upcoming and future HI-like technology. We use simulated solar wind densities to compute realistic white-light HI observations, with which we explore the requirements of such instruments for determining solar wind plasma density structure via tomography. We exploit this information to investigate the optimal orbital characteristics, such as spacecraft number, separation, inclination and eccentricity, necessary to perform the technique with HIs. Further to this we argue that tomography may be greatly enhanced by means of improved instrumentation; specifically, the use of wide-angle imagers capable of measuring polarised light. This work has obvious space weather applications, serving as a demonstration for potential future missions (such as at L1 and L5) and will prove timely in fully exploiting the science return from the upcoming Solar Orbiter and Parker Solar Probe missions.

Probabilistic classification method on multi wavelength chromatographic data for photosynthetic pigments identification

NASA Astrophysics Data System (ADS)

Prilianti, K. R.; Setiawan, Y.; Indriatmoko, Adhiwibawa, M. A. S.; Limantara, L.; Brotosudarmo, T. H. P.

2014-02-01

Environmental and health problem caused by artificial colorant encourages the increasing usage of natural colorant nowadays. Natural colorant refers to the colorant that is derivate from living organism or minerals. Extensive research topic has been done to exploit these colorant, but recent data shows that only 0.5% of the wide range of plant pigments in the earth has been exhaustively used. Hence development of the pigment characterization technique is an important consideration. High-performance liquid chromatography (HPLC) is a widely used technique to separate pigments in a mixture and identify it. In former HPLC fingerprinting, pigment characterization was based on a single chromatogram from a fixed wavelength (one dimensional) and discard the information contained at other wavelength. Therefore, two dimensional fingerprints have been proposed to use more chromatographic information. Unfortunately this method leads to the data processing problem due to the size of its data matrix. The other common problem in the chromatogram analysis is the subjectivity of the researcher in recognizing the chromatogram pattern. In this research an automated analysis method of the multi wavelength chromatographic data was proposed. Principal component analysis (PCA) was used to compress the data matrix and Maximum Likelihood (ML) classification was applied to identify the chromatogram pattern of the existing pigments in a mixture. Three photosynthetic pigments were selected to show the proposed method. Those pigments are β-carotene, fucoxanthin and zeaxanthin. The result suggests that the method could well inform the existence of the pigments in a particular mixture. A simple computer application was also developed to facilitate real time analysis. Input of the application is multi wavelength chromatographic data matrix and the output is information about the existence of the three pigments.

Tile-Based Fisher-Ratio Software for Improved Feature Selection Analysis of Comprehensive Two-Dimensional Gas Chromatography Time-of-Flight Mass Spectrometry Data

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

Marney, Luke C.; Siegler, William C.; Parsons, Brendon A.

Two-dimensional (2D) gas chromatography coupled with time-of-flight mass spectrometry (GC × GC – TOFMS) is a highly capable instrumental platform that produces complex and information-rich multi-dimensional chemical data. The complex data can be overwhelming, especially when many samples (of various sample classes) are analyzed with multiple injections for each sample. Thus, the data must be analyzed in such a way to extract the most meaningful information. The pixel-based and peak table-based algorithmic use of Fisher ratios has been used successfully in the past to reduce the multi-dimensional data down to those chemical compounds that are changing between classes relative tomore » those that are not (i.e., chemical feature selection). We report on the initial development of a computationally fast novel tile-based Fisher-ratio software that addresses challenges due to 2D retention time misalignment without explicitly aligning the data, which is a problem for both pixel-based and peak table- based methods. Concurrently, the tile-based Fisher-ratio software maximizes the sensitivity contrast of true positives against a background of potential false positives and noise. To study this software, eight compounds, plus one internal standard, were spiked into diesel at various concentrations. The tile-based F-ratio software was able to discover all spiked analytes, within the complex diesel sample matrix with thousands of potential false positives, in each possible concentration comparison, even at the lowest absolute spiked analyte concentration ratio of 1.06.« less

Cross-flow vortex structure and transition measurements using multi-element hot films

NASA Technical Reports Server (NTRS)

Agarwal, Naval K.; Mangalam, Siva M.; Maddalon, Dal V.; Collier, Fayette S., Jr.

1991-01-01

An experiment on a 45-degree swept wing was conducted to study three-dimensional boundary-layer characteristics using surface-mounted, micro-thin, multi-element hot-film sensors. Cross-flow vortex structure and boundary-layer transition were measured from the simultaneously acquired signals of the hot films. Spanwise variation of the root-mean-square (RMS) hot-film signal show a local minima and maxima. The distance between two minima corresponds to the stationary cross-flow vortex wavelength and agrees with naphthalene flow-visualization results. The chordwise and spanwise variation of amplified traveling (nonstationary) cross-flow disturbance characteristics were measured as Reynolds number was varied. The frequency of the most amplified cross-flow disturbances agrees with linear stability theory.

A Model Based Approach to Increase the Part Accuracy in Robot Based Incremental Sheet Metal Forming

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

Meier, Horst; Laurischkat, Roman; Zhu Junhong

One main influence on the dimensional accuracy in robot based incremental sheet metal forming results from the compliance of the involved robot structures. Compared to conventional machine tools the low stiffness of the robot's kinematic results in a significant deviation of the planned tool path and therefore in a shape of insufficient quality. To predict and compensate these deviations offline, a model based approach, consisting of a finite element approach, to simulate the sheet forming, and a multi body system, modeling the compliant robot structure, has been developed. This paper describes the implementation and experimental verification of the multi bodymore » system model and its included compensation method.« less

The Impact of Stereoscopic Imagery and Motion on Anatomical Structure Recognition and Visual Attention Performance

ERIC Educational Resources Information Center

Remmele, Martin; Schmidt, Elena; Lingenfelder, Melissa; Martens, Andreas

2018-01-01

Gross anatomy is located in a three-dimensional space. Visualizing aspects of structures in gross anatomy education should aim to provide information that best resembles their original spatial proportions. Stereoscopic three-dimensional imagery might offer possibilities to implement this aim, though some research has revealed potential impairments…

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

PubMed Central

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

2008-01-01

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

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

PubMed

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

2008-01-01

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

Real-space finite-difference approach for multi-body systems: path-integral renormalization group method and direct energy minimization method.

PubMed

Sasaki, Akira; Kojo, Masashi; Hirose, Kikuji; Goto, Hidekazu

2011-11-02

The path-integral renormalization group and direct energy minimization method of practical first-principles electronic structure calculations for multi-body systems within the framework of the real-space finite-difference scheme are introduced. These two methods can handle higher dimensional systems with consideration of the correlation effect. Furthermore, they can be easily extended to the multicomponent quantum systems which contain more than two kinds of quantum particles. The key to the present methods is employing linear combinations of nonorthogonal Slater determinants (SDs) as multi-body wavefunctions. As one of the noticeable results, the same accuracy as the variational Monte Carlo method is achieved with a few SDs. This enables us to study the entire ground state consisting of electrons and nuclei without the need to use the Born-Oppenheimer approximation. Recent activities on methodological developments aiming towards practical calculations such as the implementation of auxiliary field for Coulombic interaction, the treatment of the kinetic operator in imaginary-time evolutions, the time-saving double-grid technique for bare-Coulomb atomic potentials and the optimization scheme for minimizing the total-energy functional are also introduced. As test examples, the total energy of the hydrogen molecule, the atomic configuration of the methylene and the electronic structures of two-dimensional quantum dots are calculated, and the accuracy, availability and possibility of the present methods are demonstrated.

Multi-dimensional coherent optical spectroscopy of semiconductor nanostructures: Collinear and non-collinear approaches

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

Nardin, Gaël; Li, Hebin; Autry, Travis M.

2015-03-21

We review our recent work on multi-dimensional coherent optical spectroscopy (MDCS) of semiconductor nanostructures. Two approaches, appropriate for the study of semiconductor materials, are presented and compared. A first method is based on a non-collinear geometry, where the Four-Wave-Mixing (FWM) signal is detected in the form of a radiated optical field. This approach works for samples with translational symmetry, such as Quantum Wells (QWs) or large and dense ensembles of Quantum Dots (QDs). A second method detects the FWM in the form of a photocurrent in a collinear geometry. This second approach extends the horizon of MDCS to sub-diffraction nanostructures,more » such as single QDs, nanowires, or nanotubes, and small ensembles thereof. Examples of experimental results obtained on semiconductor QW structures are given for each method. In particular, it is shown how MDCS can assess coupling between excitons confined in separated QWs.« less

Implementation of a Multi-Robot Coverage Algorithm on a Two-Dimensional, Grid-Based Environment

DTIC Science & Technology

2017-06-01

two planar laser range finders with a 180-degree field of view , color camera, vision beacons, and wireless communicator. In their system, the robots...Master’s thesis 4. TITLE AND SUBTITLE IMPLEMENTATION OF A MULTI -ROBOT COVERAGE ALGORITHM ON A TWO -DIMENSIONAL, GRID-BASED ENVIRONMENT 5. FUNDING NUMBERS...path planning coverage algorithm for a multi -robot system in a two -dimensional, grid-based environment. We assess the applicability of a topology

Extending the Implicit Association Test (IAT): Assessing Consumer Attitudes Based on Multi-Dimensional Implicit Associations

PubMed Central

Gattol, Valentin; Sääksjärvi, Maria; Carbon, Claus-Christian

2011-01-01

Background The authors present a procedural extension of the popular Implicit Association Test (IAT; [1]) that allows for indirect measurement of attitudes on multiple dimensions (e.g., safe–unsafe; young–old; innovative–conventional, etc.) rather than on a single evaluative dimension only (e.g., good–bad). Methodology/Principal Findings In two within-subjects studies, attitudes toward three automobile brands were measured on six attribute dimensions. Emphasis was placed on evaluating the methodological appropriateness of the new procedure, providing strong evidence for its reliability, validity, and sensitivity. Conclusions/Significance This new procedure yields detailed information on the multifaceted nature of brand associations that can add up to a more abstract overall attitude. Just as the IAT, its multi-dimensional extension/application (dubbed md-IAT) is suited for reliably measuring attitudes consumers may not be consciously aware of, able to express, or willing to share with the researcher [2], [3]. PMID:21246037

MULTI-DIMENSIONAL MASS SPECTROMETRY-BASED SHOTGUN LIPIDOMICS AND NOVEL STRATEGIES FOR LIPIDOMIC ANALYSES

PubMed Central

Han, Xianlin; Yang, Kui; Gross, Richard W.

2011-01-01

Since our last comprehensive review on multi-dimensional mass spectrometry-based shotgun lipidomics (Mass Spectrom. Rev. 24 (2005), 367), many new developments in the field of lipidomics have occurred. These developments include new strategies and refinements for shotgun lipidomic approaches that use direct infusion, including novel fragmentation strategies, identification of multiple new informative dimensions for mass spectrometric interrogation, and the development of new bioinformatic approaches for enhanced identification and quantitation of the individual molecular constituents that comprise each cell’s lipidome. Concurrently, advances in liquid chromatography-based platforms and novel strategies for quantitative matrix-assisted laser desorption/ionization mass spectrometry for lipidomic analyses have been developed. Through the synergistic use of this repertoire of new mass spectrometric approaches, the power and scope of lipidomics has been greatly expanded to accelerate progress toward the comprehensive understanding of the pleiotropic roles of lipids in biological systems. PMID:21755525

Multi-dimensional single-spin nano-optomechanics with a levitated nanodiamond

NASA Astrophysics Data System (ADS)

Neukirch, Levi P.; von Haartman, Eva; Rosenholm, Jessica M.; Nick Vamivakas, A.

2015-10-01

Considerable advances made in the development of nanomechanical and nano-optomechanical devices have enabled the observation of quantum effects, improved sensitivity to minute forces, and provided avenues to probe fundamental physics at the nanoscale. Concurrently, solid-state quantum emitters with optically accessible spin degrees of freedom have been pursued in applications ranging from quantum information science to nanoscale sensing. Here, we demonstrate a hybrid nano-optomechanical system composed of a nanodiamond (containing a single nitrogen-vacancy centre) that is levitated in an optical dipole trap. The mechanical state of the diamond is controlled by modulation of the optical trapping potential. We demonstrate the ability to imprint the multi-dimensional mechanical motion of the cavity-free mechanical oscillator into the nitrogen-vacancy centre fluorescence and manipulate the mechanical system's intrinsic spin. This result represents the first step towards a hybrid quantum system based on levitating nanoparticles that simultaneously engages optical, phononic and spin degrees of freedom.

Facilitating Learning in SPI through Co-design

NASA Astrophysics Data System (ADS)

Seigerroth, Ulf; Lind, Mikael

Information system development (ISD) is not a stable discipline. On the contrary, ISD must constantly cope with rapidly changing and diversifying technologies, application domains, and organizational contexts [14]. ISD is a complex and a multi dimensional phenomenon [5, 15]. As a consequence of this. Software Process Improvement (SPI) can also be regarded as a complex and multi dimensional phenomenon [16]. Problems that are accentuated in relation to SPI are: SPI is in its current shape a quite young discipline [15], there is a sparse amount of SPI-theories that can guide SPI initiatives [19], SPI-initiatives often focus on the system development (SD)-process, methods and tools which is a narrow focus that leave out important aspects such as business orientation [6], organization and social factors [4, 5] and the learning process [19]. Arguments have therefore been raised that there is a need for both researchers and practitioners to better understand SD-organisations and their practice [5].

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…

Application of firefly algorithm to the dynamic model updating problem

NASA Astrophysics Data System (ADS)

Shabbir, Faisal; Omenzetter, Piotr

2015-04-01

Model updating can be considered as a branch of optimization problems in which calibration of the finite element (FE) model is undertaken by comparing the modal properties of the actual structure with these of the FE predictions. The attainment of a global solution in a multi dimensional search space is a challenging problem. The nature-inspired algorithms have gained increasing attention in the previous decade for solving such complex optimization problems. This study applies the novel Firefly Algorithm (FA), a global optimization search technique, to a dynamic model updating problem. This is to the authors' best knowledge the first time FA is applied to model updating. The working of FA is inspired by the flashing characteristics of fireflies. Each firefly represents a randomly generated solution which is assigned brightness according to the value of the objective function. The physical structure under consideration is a full scale cable stayed pedestrian bridge with composite bridge deck. Data from dynamic testing of the bridge was used to correlate and update the initial model by using FA. The algorithm aimed at minimizing the difference between the natural frequencies and mode shapes of the structure. The performance of the algorithm is analyzed in finding the optimal solution in a multi dimensional search space. The paper concludes with an investigation of the efficacy of the algorithm in obtaining a reference finite element model which correctly represents the as-built original structure.

Angular difference feature extraction for urban scene classification using ZY-3 multi-angle high-resolution satellite imagery

NASA Astrophysics Data System (ADS)

Huang, Xin; Chen, Huijun; Gong, Jianya

2018-01-01

Spaceborne multi-angle images with a high-resolution are capable of simultaneously providing spatial details and three-dimensional (3D) information to support detailed and accurate classification of complex urban scenes. In recent years, satellite-derived digital surface models (DSMs) have been increasingly utilized to provide height information to complement spectral properties for urban classification. However, in such a way, the multi-angle information is not effectively exploited, which is mainly due to the errors and difficulties of the multi-view image matching and the inaccuracy of the generated DSM over complex and dense urban scenes. Therefore, it is still a challenging task to effectively exploit the available angular information from high-resolution multi-angle images. In this paper, we investigate the potential for classifying urban scenes based on local angular properties characterized from high-resolution ZY-3 multi-view images. Specifically, three categories of angular difference features (ADFs) are proposed to describe the angular information at three levels (i.e., pixel, feature, and label levels): (1) ADF-pixel: the angular information is directly extrapolated by pixel comparison between the multi-angle images; (2) ADF-feature: the angular differences are described in the feature domains by comparing the differences between the multi-angle spatial features (e.g., morphological attribute profiles (APs)). (3) ADF-label: label-level angular features are proposed based on a group of urban primitives (e.g., buildings and shadows), in order to describe the specific angular information related to the types of primitive classes. In addition, we utilize spatial-contextual information to refine the multi-level ADF features using superpixel segmentation, for the purpose of alleviating the effects of salt-and-pepper noise and representing the main angular characteristics within a local area. The experiments on ZY-3 multi-angle images confirm that the proposed ADF features can effectively improve the accuracy of urban scene classification, with a significant increase in overall accuracy (3.8-11.7%) compared to using the spectral bands alone. Furthermore, the results indicated the superiority of the proposed ADFs in distinguishing between the spectrally similar and complex man-made classes, including roads and various types of buildings (e.g., high buildings, urban villages, and residential apartments).

Amplitude interpretation and visualization of three-dimensional reflection data

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

Enachescu, M.E.

1994-07-01

Digital recording and processing of modern three-dimensional surveys allow for relative good preservation and correct spatial positioning of seismic reflection amplitude. A four-dimensional seismic reflection field matrix R (x,y,t,A), which can be computer visualized (i.e., real-time interactively rendered, edited, and animated), is now available to the interpreter. The amplitude contains encoded geological information indirectly related to lithologies and reservoir properties. The magnitude of the amplitude depends not only on the acoustic impedance contrast across a boundary, but is also strongly affected by the shape of the reflective boundary. This allows the interpreter to image subtle tectonic and structural elements notmore » obvious on time-structure maps. The use of modern workstations allows for appropriate color coding of the total available amplitude range, routine on-screen time/amplitude extraction, and late display of horizon amplitude maps (horizon slices) or complex amplitude-structure spatial visualization. Stratigraphic, structural, tectonic, fluid distribution, and paleogeographic information are commonly obtained by displaying the amplitude variation A = A(x,y,t) associated with a particular reflective surface or seismic interval. As illustrated with several case histories, traditional structural and stratigraphic interpretation combined with a detailed amplitude study generally greatly enhance extraction of subsurface geological information from a reflection data volume. In the context of three-dimensional seismic surveys, the horizon amplitude map (horizon slice), amplitude attachment to structure and [open quotes]bright clouds[close quotes] displays are very powerful tools available to the interpreter.« less

Multi-Ferroic Polymer Nanoparticle Composites for Next Generation Metamaterials

DTIC Science & Technology

2016-05-23

another application, electromagnetic wave shielding . Electromagnetic wave induces current which results in loss of energy. Thus magnetic nanoparticles...applicable for electromagnetic wave shielding . For better electromagnetic wave shielding capability, i) high dielectric constant, ii) high magnetic ...electromagnetic wave shielding properties7,8. In such point of view, designing a structure, magnetic nanoparticles in two dimensional electric conductive matrix

The Impact of a Discipline-Based Learning Community on Transfer Students: A Multi-Dimensional Pilot Study

ERIC Educational Resources Information Center

Lord, Vivian B.; Coston, Charisse T. M.; Blowers, Anita N.; Davis, Boyd; Johannes, Kenia S.

2012-01-01

Learning communities (LCs) have become a popular strategy for developing structured programming aimed at enhancing student success and retention. While most LCs have focused on improving the quality of education for first-year students, little attention has been placed on addressing their usefulness for enhancing the success of transfer students.…

Terrain Classification Using Multi-Wavelength Lidar Data

DTIC Science & Technology

2015-09-01

Figure 9. Pseudo- NDVI of three layers within the vertical structure of the forest. (Top) First return from the LiDAR instrument, including the ground...in NDVI throughout the vertical canopy. ........................................................17 Figure 10. Optech Titan operating wavelengths...and Ranging LMS LiDAR Mapping Suite ML Maximum Likelihood NIR Near Infrared N-D VIS n-Dimensional Visualizer NDVI Normalized Difference

Action detection by double hierarchical multi-structure space-time statistical matching model

NASA Astrophysics Data System (ADS)

Han, Jing; Zhu, Junwei; Cui, Yiyin; Bai, Lianfa; Yue, Jiang

2018-03-01

Aimed at the complex information in videos and low detection efficiency, an actions detection model based on neighboring Gaussian structure and 3D LARK features is put forward. We exploit a double hierarchical multi-structure space-time statistical matching model (DMSM) in temporal action localization. First, a neighboring Gaussian structure is presented to describe the multi-scale structural relationship. Then, a space-time statistical matching method is proposed to achieve two similarity matrices on both large and small scales, which combines double hierarchical structural constraints in model by both the neighboring Gaussian structure and the 3D LARK local structure. Finally, the double hierarchical similarity is fused and analyzed to detect actions. Besides, the multi-scale composite template extends the model application into multi-view. Experimental results of DMSM on the complex visual tracker benchmark data sets and THUMOS 2014 data sets show the promising performance. Compared with other state-of-the-art algorithm, DMSM achieves superior performances.

Action detection by double hierarchical multi-structure space–time statistical matching model

NASA Astrophysics Data System (ADS)

Han, Jing; Zhu, Junwei; Cui, Yiyin; Bai, Lianfa; Yue, Jiang

2018-06-01

Aimed at the complex information in videos and low detection efficiency, an actions detection model based on neighboring Gaussian structure and 3D LARK features is put forward. We exploit a double hierarchical multi-structure space-time statistical matching model (DMSM) in temporal action localization. First, a neighboring Gaussian structure is presented to describe the multi-scale structural relationship. Then, a space-time statistical matching method is proposed to achieve two similarity matrices on both large and small scales, which combines double hierarchical structural constraints in model by both the neighboring Gaussian structure and the 3D LARK local structure. Finally, the double hierarchical similarity is fused and analyzed to detect actions. Besides, the multi-scale composite template extends the model application into multi-view. Experimental results of DMSM on the complex visual tracker benchmark data sets and THUMOS 2014 data sets show the promising performance. Compared with other state-of-the-art algorithm, DMSM achieves superior performances.

Data processing for soft X-ray diagnostics based on GEM detector measurements for fusion plasma imaging

NASA Astrophysics Data System (ADS)

Czarski, T.; Chernyshova, M.; Pozniak, K. T.; Kasprowicz, G.; Byszuk, A.; Juszczyk, B.; Wojenski, A.; Zabolotny, W.; Zienkiewicz, P.

2015-12-01

The measurement system based on GEM - Gas Electron Multiplier detector is developed for X-ray diagnostics of magnetic confinement fusion plasmas. The Triple Gas Electron Multiplier (T-GEM) is presented as soft X-ray (SXR) energy and position sensitive detector. The paper is focused on the measurement subject and describes the fundamental data processing to obtain reliable characteristics (histograms) useful for physicists. So, it is the software part of the project between the electronic hardware and physics applications. The project is original and it was developed by the paper authors. Multi-channel measurement system and essential data processing for X-ray energy and position recognition are considered. Several modes of data acquisition determined by hardware and software processing are introduced. Typical measuring issues are deliberated for the enhancement of data quality. The primary version based on 1-D GEM detector was applied for the high-resolution X-ray crystal spectrometer KX1 in the JET tokamak. The current version considers 2-D detector structures initially for the investigation purpose. Two detector structures with single-pixel sensors and multi-pixel (directional) sensors are considered for two-dimensional X-ray imaging. Fundamental output characteristics are presented for one and two dimensional detector structure. Representative results for reference source and tokamak plasma are demonstrated.

Periodic metallo-dielectric structure in diamond.

PubMed

Shimizu, M; Shimotsuma, Y; Sakakura, M; Yuasa, T; Homma, H; Minowa, Y; Tanaka, K; Miura, K; Hirao, K

2009-01-05

Intense ultrashort light pulses induce three dimensional localized phase transformation of diamond. Photoinduced amorphous structures have electrical conducting properties of a maximum of 64 S/m based on a localized transition from sp(3) to sp(2) in diamond. The laser parameters of fluence and scanning speed affect the resultant electrical conductivities due to recrystallization and multi-filamentation phenomena. We demonstrate that the laser-processed diamond with the periodic cylinder arrays have the characteristic transmission properties in terahertz region, which are good agreement with theoretical calculations. The fabricated periodic structures act as metallo-dielectric photonic crystal.

Near-field thermal radiation of deep- subwavelength slits in the near infrared range.

PubMed

Guo, Yan; Li, Kuanbiao; Xu, Ying; Wei, Kaihua

2017-09-18

We numerically investigate the thermal radiation of one-dimensional deep subwavelength slits in the near infrared range. Using numerical calculations of single-slit and multi-slit structures, we find that high-level radiation efficiency can be achieved for a wide spectrum when ultra-thin intermediate layers are used, and it is less affected by structure parameters. The underlying mechanisms involve Surface Plasmon Polaritons resonance and Fabry-Perot interference at each slit and the interaction between adjacent slits. This structure helps understand and improve the design of thermal radiation control devices.

Adagio 4.20 User’s Guide

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

Spencer, Benjamin Whiting; Crane, Nathan K.; Heinstein, Martin W.

2011-03-01

Adagio is a Lagrangian, three-dimensional, implicit code for the analysis of solids and structures. It uses a multi-level iterative solver, which enables it to solve problems with large deformations, nonlinear material behavior, and contact. It also has a versatile library of continuum and structural elements, and an extensive library of material models. Adagio is written for parallel computing environments, and its solvers allow for scalable solutions of very large problems. Adagio uses the SIERRA Framework, which allows for coupling with other SIERRA mechanics codes. This document describes the functionality and input structure for Adagio.

Multi-dimensional simulations of core-collapse supernova explosions with CHIMERA

NASA Astrophysics Data System (ADS)

Messer, O. E. B.; Harris, J. A.; Hix, W. R.; Lentz, E. J.; Bruenn, S. W.; Mezzacappa, A.

2018-04-01

Unraveling the core-collapse supernova (CCSN) mechanism is a problem that remains essentially unsolved despite more than four decades of effort. Spherically symmetric models with otherwise high physical fidelity generally fail to produce explosions, and it is widely accepted that CCSNe are inherently multi-dimensional. Progress in realistic modeling has occurred recently through the availability of petascale platforms and the increasing sophistication of supernova codes. We will discuss our most recent work on understanding neutrino-driven CCSN explosions employing multi-dimensional neutrino-radiation hydrodynamics simulations with the Chimera code. We discuss the inputs and resulting outputs from these simulations, the role of neutrino radiation transport, and the importance of multi-dimensional fluid flows in shaping the explosions. We also highlight the production of 48Ca in long-running Chimera simulations.

A Weld Position Recognition Method Based on Directional and Structured Light Information Fusion in Multi-Layer/Multi-Pass Welding.

PubMed

Zeng, Jinle; Chang, Baohua; Du, Dong; Wang, Li; Chang, Shuhe; Peng, Guodong; Wang, Wenzhu

2018-01-05

Multi-layer/multi-pass welding (MLMPW) technology is widely used in the energy industry to join thick components. During automatic welding using robots or other actuators, it is very important to recognize the actual weld pass position using visual methods, which can then be used not only to perform reasonable path planning for actuators, but also to correct any deviations between the welding torch and the weld pass position in real time. However, due to the small geometrical differences between adjacent weld passes, existing weld position recognition technologies such as structured light methods are not suitable for weld position detection in MLMPW. This paper proposes a novel method for weld position detection, which fuses various kinds of information in MLMPW. First, a synchronous acquisition method is developed to obtain various kinds of visual information when directional light and structured light sources are on, respectively. Then, interferences are eliminated by fusing adjacent images. Finally, the information from directional and structured light images is fused to obtain the 3D positions of the weld passes. Experiment results show that each process can be done in 30 ms and the deviation is less than 0.6 mm. The proposed method can be used for automatic path planning and seam tracking in the robotic MLMPW process as well as electron beam freeform fabrication process.

MultiLIS: A Description of the System Design and Operational Features.

ERIC Educational Resources Information Center

Kelly, Glen J.; And Others

1988-01-01

Describes development, hardware requirements, and features of the MultiLIS integrated library software package. A system profile provides pricing information, operational characteristics, and technical specifications. Sidebars discuss MultiLIS integration structure, incremental architecture, and NCR Tower Computers. (4 references) (MES)

HOTCFGM-1D: A Coupled Higher-Order Theory for Cylindrical Structural Components with Through-Thickness Functionally Graded Microstructures

NASA Technical Reports Server (NTRS)

Pindera, Marek-Jerzy; Aboudi, Jacob

1998-01-01

The objective of this three-year project was to develop and deliver to NASA Lewis one-dimensional and two-dimensional higher-order theories, and related computer codes, for the analysis, optimization and design of cylindrical functionally graded materials/structural components for use in advanced aircraft engines (e.g., combustor linings, rotor disks, heat shields, blisk blades). To satisfy this objective, a quasi one-dimensional version of the higher-order theory, HOTCFGM-1D, and four computer codes based on this theory, for the analysis, design and optimization of cylindrical structural components functionally graded in the radial direction were developed. The theory is applicable to thin multi-phased composite shell/cylinders subjected to macroscopically axisymmetric thermomechanical and inertial loading applied uniformly along the axial direction such that the overall deformation is characterized by a constant average axial strain. The reinforcement phases are uniformly distributed in the axial and circumferential directions, and arbitrarily distributed in the radial direction, thereby allowing functional grading of the internal reinforcement in this direction.

Coupled multi-disciplinary composites behavior simulation

NASA Technical Reports Server (NTRS)

Singhal, Surendra N.; Murthy, Pappu L. N.; Chamis, Christos C.

1993-01-01

The capabilities of the computer code CSTEM (Coupled Structural/Thermal/Electro-Magnetic Analysis) are discussed and demonstrated. CSTEM computationally simulates the coupled response of layered multi-material composite structures subjected to simultaneous thermal, structural, vibration, acoustic, and electromagnetic loads and includes the effect of aggressive environments. The composite material behavior and structural response is determined at its various inherent scales: constituents (fiber/matrix), ply, laminate, and structural component. The thermal and mechanical properties of the constituents are considered to be nonlinearly dependent on various parameters such as temperature and moisture. The acoustic and electromagnetic properties also include dependence on vibration and electromagnetic wave frequencies, respectively. The simulation is based on a three dimensional finite element analysis in conjunction with composite mechanics and with structural tailoring codes, and with acoustic and electromagnetic analysis methods. An aircraft engine composite fan blade is selected as a typical structural component to demonstrate the CSTEM capabilities. Results of various coupled multi-disciplinary heat transfer, structural, vibration, acoustic, and electromagnetic analyses for temperature distribution, stress and displacement response, deformed shape, vibration frequencies, mode shapes, acoustic noise, and electromagnetic reflection from the fan blade are discussed for their coupled effects in hot and humid environments. Collectively, these results demonstrate the effectiveness of the CSTEM code in capturing the coupled effects on the various responses of composite structures subjected to simultaneous multiple real-life loads.

Photoemission study of the electronic structure and charge density waves of Na2Ti2Sb2O.

PubMed

Tan, S Y; Jiang, J; Ye, Z R; Niu, X H; Song, Y; Zhang, C L; Dai, P C; Xie, B P; Lai, X C; Feng, D L

2015-04-30

The electronic structure of Na2Ti2Sb2O single crystal is studied by photon energy and polarization dependent angle-resolved photoemission spectroscopy (ARPES). The obtained band structure and Fermi surface agree well with the band structure calculation of Na2Ti2Sb2O in the non-magnetic state, which indicates that there is no magnetic order in Na2Ti2Sb2O and the electronic correlation is weak. Polarization dependent ARPES results suggest the multi-band and multi-orbital nature of Na2Ti2Sb2O. Photon energy dependent ARPES results suggest that the electronic structure of Na2Ti2Sb2O is rather two-dimensional. Moreover, we find a density wave energy gap forms below the transition temperature and reaches 65 meV at 7 K, indicating that Na2Ti2Sb2O is likely a weakly correlated CDW material in the strong electron-phonon interaction regime.

Control/structure interaction conceptual design tool

NASA Technical Reports Server (NTRS)

Briggs, Hugh C.

1990-01-01

The JPL Control/Structure Interaction Program is developing new analytical methods for designing micro-precision spacecraft with controlled structures. One of these, the Conceptual Design Tool, will illustrate innovative new approaches to the integration of multi-disciplinary analysis and design methods. The tool will be used to demonstrate homogeneity of presentation, uniform data representation across analytical methods, and integrated systems modeling. The tool differs from current 'integrated systems' that support design teams most notably in its support for the new CSI multi-disciplinary engineer. The design tool will utilize a three dimensional solid model of the spacecraft under design as the central data organization metaphor. Various analytical methods, such as finite element structural analysis, control system analysis, and mechanical configuration layout, will store and retrieve data from a hierarchical, object oriented data structure that supports assemblies of components with associated data and algorithms. In addition to managing numerical model data, the tool will assist the designer in organizing, stating, and tracking system requirements.

The Governance of Indigenous Natural Products in Namibia: A Policy Network Analysis.

PubMed

Ndeinoma, Albertina; Wiersum, K Freerk; Arts, Bas

2018-01-09

At the end of the 20th century, optimism existed that non-timber forest products (NTFPs) can form an integral part in conservation and development strategies. However, there is limited knowledge on how the different stakeholders could relate to the state or to each other in promoting commercialization of NTFPs. Applying the policy network as an analytical framework, we investigated the structural patterns of actor relations in the governance structure of indigenous natural products (INPs) in Namibia, to understand the implications of such relations on INP policy process. The findings indicate that the INP policy network in Namibia is multi-dimensional, consisting of the Indigenous Plant Task Team (IPTT)-the key governance structure for resource mobilization and information sharing; and functional relations which serve specific roles in the INP value chain. The existing relations have facilitated policy development particularly for heavily regulated species, such as devil's claw; but for other species, only incremental changes are observed in terms of small-scale processing facilities for value addition and exclusive purchase agreements for sustainable sourcing of INPs. Participation of primary producers, private actors and quality standardization bodies is limited in INPs governance structures, which narrow the scope of information sharing. Consequently, despite that the IPTT has fostered publicly funded explorative pilot projects, ranging from production to marketing of INPs, there are no clear guidelines how these projects results can be transferred to private entities for possible commercialization. Further collaboration and information sharing is needed to guide public sector relations with the private entities and cooperatives.

Investigation of the influence of the proximity effect and randomness on a photolithographically fabricated photonic crystal nanobeam cavity

NASA Astrophysics Data System (ADS)

Tetsumoto, Tomohiro; Kumazaki, Hajime; Ishida, Rammaru; Tanabe, Takasumi

2018-01-01

Recent progress on the fabrication techniques used in silicon photonics foundries has enabled us to fabricate photonic crystal (PhC) nanocavities using a complementary metal-oxide-semiconductor (CMOS) compatible process. A high Q two-dimensional PhC nanocavity and a one-dimensional nanobeam PhC cavity with a Q exceeding 100 thousand have been fabricated using ArF excimer laser immersion lithography. These are important steps toward the fusion of silicon photonics devices and PhC devices. Although the fabrication must be reproducible for industrial applications, the properties of PhC nanocavities are sensitively affected by the proximity effect and randomness. In this study, we quantitatively investigated the influence of the proximity effect and randomness on a silicon nanobeam PhC cavity. First, we discussed the optical properties of cavities defined with one- and two-step exposure methods, which revealed the necessity of a multi-stage exposure process for our structure. Then, we investigated the impact of block structures placed next to the cavities. The presence of the blocks modified the resonant wavelength of the cavities by about 10 nm. The highest Q we obtained was over 100 thousand. We also discussed the influence of photomask misalignment, which is also a possible cause of disorders in the photolithographic fabrication process. This study will provide useful information for fabricating integrated photonic circuits with PhC nanocavities using a photolithographic process.

Phase space interrogation of the empirical response modes for seismically excited structures

NASA Astrophysics Data System (ADS)

Paul, Bibhas; George, Riya C.; Mishra, Sudib K.

2017-07-01

Conventional Phase Space Interrogation (PSI) for structural damage assessment relies on exciting the structure with low dimensional chaotic waveform, thereby, significantly limiting their applicability to large structures. The PSI technique is presently extended for structure subjected to seismic excitations. The high dimensionality of the phase space for seismic response(s) are overcome by the Empirical Mode Decomposition (EMD), decomposing the responses to a number of intrinsic low dimensional oscillatory modes, referred as Intrinsic Mode Functions (IMFs). Along with their low dimensionality, a few IMFs, retain sufficient information of the system dynamics to reflect the damage induced changes. The mutually conflicting nature of low-dimensionality and the sufficiency of dynamic information are taken care by the optimal choice of the IMF(s), which is shown to be the third/fourth IMFs. The optimal IMF(s) are employed for the reconstruction of the Phase space attractor following Taken's embedding theorem. The widely referred Changes in Phase Space Topology (CPST) feature is then employed on these Phase portrait(s) to derive the damage sensitive feature, referred as the CPST of the IMFs (CPST-IMF). The legitimacy of the CPST-IMF is established as a damage sensitive feature by assessing its variation with a number of damage scenarios benchmarked in the IASC-ASCE building. The damage localization capability, remarkable tolerance to noise contamination and the robustness under different seismic excitations of the feature are demonstrated.

GRAMPS: a graphics language interpreter for real-time, interactive, three-dimensional picture editing and animation

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

O'Donnell, T.J.; Olson, A.J.

1981-08-01

GRAMPS, a graphics language interpreter has been developed in FORTRAN 77 to be used in conjunction with an interactive vector display list processor (Evans and Sutherland Multi-Picture-System). Several of the features of the language make it very useful and convenient for real-time scene construction, manipulation and animation. The GRAMPS language syntax allows natural interaction with scene elements as well as easy, interactive assignment of graphics input devices. GRAMPS facilitates the creation, manipulation and copying of complex nested picture structures. The language has a powerful macro feature that enables new graphics commands to be developed and incorporated interactively. Animation may bemore » achieved in GRAMPS by two different, yet mutually compatible means. Picture structures may contain framed data, which consist of a sequence of fixed objects. These structures may be displayed sequentially to give a traditional frame animation effect. In addition, transformation information on picture structures may be saved at any time in the form of new macro commands that will transform these structures from one saved state to another in a specified number of steps, yielding an interpolated transformation animation effect. An overview of the GRAMPS command structure is given and several examples of application of the language to molecular modeling and animation are presented.« less

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

Kim, Sang Beom; Dsilva, Carmeline J.; Debenedetti, Pablo G., E-mail: pdebene@princeton.edu

Understanding the mechanisms by which proteins fold from disordered amino-acid chains to spatially ordered structures remains an area of active inquiry. Molecular simulations can provide atomistic details of the folding dynamics which complement experimental findings. Conventional order parameters, such as root-mean-square deviation and radius of gyration, provide structural information but fail to capture the underlying dynamics of the protein folding process. It is therefore advantageous to adopt a method that can systematically analyze simulation data to extract relevant structural as well as dynamical information. The nonlinear dimensionality reduction technique known as diffusion maps automatically embeds the high-dimensional folding trajectories inmore » a lower-dimensional space from which one can more easily visualize folding pathways, assuming the data lie approximately on a lower-dimensional manifold. The eigenvectors that parametrize the low-dimensional space, furthermore, are determined systematically, rather than chosen heuristically, as is done with phenomenological order parameters. We demonstrate that diffusion maps can effectively characterize the folding process of a Trp-cage miniprotein. By embedding molecular dynamics simulation trajectories of Trp-cage folding in diffusion maps space, we identify two folding pathways and intermediate structures that are consistent with the previous studies, demonstrating that this technique can be employed as an effective way of analyzing and constructing protein folding pathways from molecular simulations.« less

A gantry-based tri-modality system for bioluminescence tomography

PubMed Central

Yan, Han; Lin, Yuting; Barber, William C.; Unlu, Mehmet Burcin; Gulsen, Gultekin

2012-01-01

A gantry-based tri-modality system that combines bioluminescence (BLT), diffuse optical (DOT), and x-ray computed tomography (XCT) into the same setting is presented here. The purpose of this system is to perform bioluminescence tomography using a multi-modality imaging approach. As parts of this hybrid system, XCT and DOT provide anatomical information and background optical property maps. This structural and functional a priori information is used to guide and restrain bioluminescence reconstruction algorithm and ultimately improve the BLT results. The performance of the combined system is evaluated using multi-modality phantoms. In particular, a cylindrical heterogeneous multi-modality phantom that contains regions with higher optical absorption and x-ray attenuation is constructed. We showed that a 1.5 mm diameter bioluminescence inclusion can be localized accurately with the functional a priori information while its source strength can be recovered more accurately using both structural and the functional a priori information. PMID:22559540

Multi-level analysis in information systems research: the case of enterprise resource planning system usage in China

NASA Astrophysics Data System (ADS)

Sun, Yuan; Bhattacherjee, Anol

2011-11-01

Information technology (IT) usage within organisations is a multi-level phenomenon that is influenced by individual-level and organisational-level variables. Yet, current theories, such as the unified theory of acceptance and use of technology, describe IT usage as solely an individual-level phenomenon. This article postulates a model of organisational IT usage that integrates salient organisational-level variables such as user training, top management support and technical support within an individual-level model to postulate a multi-level model of IT usage. The multi-level model was then empirically validated using multi-level data collected from 128 end users and 26 managers in 26 firms in China regarding their use of enterprise resource planning systems and analysed using the multi-level structural equation modelling (MSEM) technique. We demonstrate the utility of MSEM analysis of multi-level data relative to the more common structural equation modelling analysis of single-level data and show how single-level data can be aggregated to approximate multi-level analysis when multi-level data collection is not possible. We hope that this article will motivate future scholars to employ multi-level data and multi-level analysis for understanding organisational phenomena that are truly multi-level in nature.

Multi-Scale Modeling of an Integrated 3D Braided Composite with Applications to Helicopter Arm

NASA Astrophysics Data System (ADS)

Zhang, Diantang; Chen, Li; Sun, Ying; Zhang, Yifan; Qian, Kun

2017-10-01

A study is conducted with the aim of developing multi-scale analytical method for designing the composite helicopter arm with three-dimensional (3D) five-directional braided structure. Based on the analysis of 3D braided microstructure, the multi-scale finite element modeling is developed. Finite element analysis on the load capacity of 3D five-directional braided composites helicopter arm is carried out using the software ABAQUS/Standard. The influences of the braiding angle and loading condition on the stress and strain distribution of the helicopter arm are simulated. The results show that the proposed multi-scale method is capable of accurately predicting the mechanical properties of 3D braided composites, validated by the comparison the stress-strain curves of meso-scale RVCs. Furthermore, it is found that the braiding angle is an important factor affecting the mechanical properties of 3D five-directional braided composite helicopter arm. Based on the optimized structure parameters, the nearly net-shaped composite helicopter arm is fabricated using a novel resin transfer mould (RTM) process.

Scalability of surrogate-assisted multi-objective optimization of antenna structures exploiting variable-fidelity electromagnetic simulation models

NASA Astrophysics Data System (ADS)

Koziel, Slawomir; Bekasiewicz, Adrian

2016-10-01

Multi-objective optimization of antenna structures is a challenging task owing to the high computational cost of evaluating the design objectives as well as the large number of adjustable parameters. Design speed-up can be achieved by means of surrogate-based optimization techniques. In particular, a combination of variable-fidelity electromagnetic (EM) simulations, design space reduction techniques, response surface approximation models and design refinement methods permits identification of the Pareto-optimal set of designs within a reasonable timeframe. Here, a study concerning the scalability of surrogate-assisted multi-objective antenna design is carried out based on a set of benchmark problems, with the dimensionality of the design space ranging from six to 24 and a CPU cost of the EM antenna model from 10 to 20 min per simulation. Numerical results indicate that the computational overhead of the design process increases more or less quadratically with the number of adjustable geometric parameters of the antenna structure at hand, which is a promising result from the point of view of handling even more complex problems.

Two-dimensional wind tunnel

NASA Technical Reports Server (NTRS)

1982-01-01

Information on the Japanese National Aerospace Laboratory two dimensional transonic wind tunnel, completed at the end of 1979 is presented. Its construction is discussed in detail, and the wind tunnel structure, operation, test results, and future plans are presented.

Transition from two-dimensional photonic crystals to dielectric metasurfaces in the optical diffraction with a fine structure

PubMed Central

Rybin, Mikhail V.; Samusev, Kirill B.; Lukashenko, Stanislav Yu.; Kivshar, Yuri S.; Limonov, Mikhail F.

2016-01-01

We study experimentally a fine structure of the optical Laue diffraction from two-dimensional periodic photonic lattices. The periodic photonic lattices with the C4v square symmetry, orthogonal C2v symmetry, and hexagonal C6v symmetry are composed of submicron dielectric elements fabricated by the direct laser writing technique. We observe surprisingly strong optical diffraction from a finite number of elements that provides an excellent tool to determine not only the symmetry but also exact number of particles in the finite-length structure and the sample shape. Using different samples with orthogonal C2v symmetry and varying the lattice spacing, we observe experimentally a transition between the regime of multi-order diffraction, being typical for photonic crystals to the regime where only the zero-order diffraction can be observed, being is a clear fingerprint of dielectric metasurfaces characterized by effective parameters. PMID:27491952

What did Erwin mean? The physics of information from the materials genomics of aperiodic crystals and water to molecular information catalysts and life.

PubMed

Varn, D P; Crutchfield, J P

2016-03-13

Erwin Schrödinger famously and presciently ascribed the vehicle transmitting the hereditary information underlying life to an 'aperiodic crystal'. We compare and contrast this, only later discovered to be stored in the linear biomolecule DNA, with the information-bearing, layered quasi-one-dimensional materials investigated by the emerging field of chaotic crystallography. Despite differences in functionality, the same information measures capture structure and novelty in both, suggesting an intimate coherence between the information character of biotic and abiotic matter-a broadly applicable physics of information. We review layered solids and consider three examples of how information- and computation-theoretic techniques are being applied to understand their structure. In particular, (i) we review recent efforts to apply new kinds of information measures to quantify disordered crystals; (ii) we discuss the structure of ice I in information-theoretic terms; and (iii) we recount recent investigations into the structure of tris(bicyclo[2.1.1]hexeno)benzene, showing how an information-theoretic analysis yields additional insight into its structure. We then illustrate a new Second Law of Thermodynamics that describes information processing in active low-dimensional materials, reviewing Maxwell's Demon and a new class of molecular devices that act as information catalysts. Lastly, we conclude by speculating on how these ideas from informational materials science may impact biology. © 2016 The Author(s).

Multi-pixel high-resolution three-dimensional imaging radar

NASA Technical Reports Server (NTRS)

Cooper, Ken B. (Inventor); Dengler, Robert J. (Inventor); Siegel, Peter H. (Inventor); Chattopadhyay, Goutam (Inventor); Ward, John S. (Inventor); Juan, Nuria Llombart (Inventor); Bryllert, Tomas E. (Inventor); Mehdi, Imran (Inventor); Tarsala, Jan A. (Inventor)

2012-01-01

A three-dimensional imaging radar operating at high frequency e.g., 670 GHz radar using low phase-noise synthesizers and a fast chirper to generate a frequency-modulated continuous-wave (FMCW) waveform, is disclosed that operates with a multiplexed beam to obtain range information simultaneously on multiple pixels of a target. A source transmit beam may be divided by a hybrid coupler into multiple transmit beams multiplexed together and directed to be reflected off a target and return as a single receive beam which is demultiplexed and processed to reveal range information of separate pixels of the target associated with each transmit beam simultaneously. The multiple transmit beams may be developed with appropriate optics to be temporally and spatially differentiated before being directed to the target. Temporal differentiation corresponds to a different intermediate frequencies separating the range information of the multiple pixels. Collinear transmit beams having differentiated polarizations may also be implemented.

Three-dimensional photonic crystals created by single-step multi-directional plasma etching.

PubMed

Suzuki, Katsuyoshi; Kitano, Keisuke; Ishizaki, Kenji; Noda, Susumu

2014-07-14

We fabricate 3D photonic nanostructures by simultaneous multi-directional plasma etching. This simple and flexible method is enabled by controlling the ion-sheath in reactive-ion-etching equipment. We realize 3D photonic crystals on single-crystalline silicon wafers and show high reflectance (>95%) and low transmittance (<-15dB) at optical communication wavelengths, suggesting the formation of a complete photonic bandgap. Moreover, our method simply demonstrates Si-based 3D photonic crystals that show the photonic bandgap effect in a shorter wavelength range around 0.6 μm, where further fine structures are required.

Ames Infusion Stories for NASA Annual Technology Report: Development of an Ablative 3D Quartz / Cyanate Ester Composite Multi-Functional Material for the Orion Spacecraft Compression Pad

NASA Technical Reports Server (NTRS)

Smith, Brandon; Jan, Darrell Leslie; Venkatapathy, Ethiraj

2015-01-01

Vehicles re-entering Earth's atmosphere require protection from the heat of atmospheric friction. The Orion Multi-Purpose Crew Vehicle (MPCV) has more demanding thermal protection system (TPS) requirements than the Low Earth Orbit (LEO) missions, especially in regions where the structural load passes through. The use of 2-dimensional laminate materials along with a metal insert, used in EFT1 flight test for the compression pad region, are deemed adequate but cannot be extended for Lunar return missions.

Structure of junctions of multiwalled carbon nanotubes with tetragonal cross section and flattened nanotubes revealed by electron-beam tomography

NASA Astrophysics Data System (ADS)

Nagano, Yuta; Kohno, Hideo

2017-11-01

Multiwalled carbon nanotubes with tetragonal cross section frequently form junctions with flattened multi-walled carbon nanotubes, a kind of carbon nanoribbon. The three-dimensional structure of the junctions is revealed by transmission-electron-microscopy-based tomography. Two types of junction, parallel and diagonal, are found. The formation mechanism of these two types of junction is discussed in terms of the origami mechanism that was previously proposed to explain the formation of carbon nanoribbons and nanotetrahedra.

Multi-stack InAs/InGaAs Sub-monolayer Quantum Dots Infrared Photodetectors

DTIC Science & Technology

2013-01-01

013110 (2013) Demonstration of high performance bias-selectable dual- band short-/mid-wavelength infrared photodetectors based on type-II InAs/ GaSb ...been used for the growth of QD structures . These include the formation of self-assembled QD, for example, Stranski-Krastanov (SK) growth mode,8,9 atomic...confinement in SML-QD and the reduction in the amount of InAs used per layer of QD can help stack more layers in a 3-dimensional QD structure . Several

Multi-dimensional simulations of core-collapse supernova explosions with CHIMERA

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

Messer, Bronson; Harris, James Austin; Hix, William Raphael

Unraveling the core-collapse supernova (CCSN) mechanism is a problem that remains essentially unsolved despite more than four decades of effort. Spherically symmetric models with otherwise high physical fidelity generally fail to produce explosions, and it is widely accepted that CCSNe are inherently multi-dimensional. Progress in realistic modeling has occurred recently through the availability of petascale platforms and the increasing sophistication of supernova codes. We will discuss our most recent work on understanding neutrino-driven CCSN explosions employing multi-dimensional neutrino-radiation hydrodynamics simulations with the Chimera code. We discuss the inputs and resulting outputs from these simulations, the role of neutrino radiation transport,more » and the importance of multi-dimensional fluid flows in shaping the explosions. We also highlight the production of 48Ca in long-running Chimera simulations.« less

Controllable 3D architectures of aligned carbon nanotube arrays by multi-step processes

NASA Astrophysics Data System (ADS)

Huang, Shaoming

2003-06-01

An effective way to fabricate large area three-dimensional (3D) aligned CNTs pattern based on pyrolysis of iron(II) phthalocyanine (FePc) by two-step processes is reported. The controllable generation of different lengths and selective growth of the aligned CNT arrays on metal-patterned (e.g., Ag and Au) substrate are the bases for generating such 3D aligned CNTs architectures. By controlling experimental conditions 3D aligned CNT arrays with different lengths/densities and morphologies/structures as well as multi-layered architectures can be fabricated in large scale by multi-step pyrolysis of FePc. These 3D architectures could have interesting properties and be applied for developing novel nanotube-based devices.

A Microfluidic Route to Breaking Chiral Symmetry: Theory and Experiment

NASA Astrophysics Data System (ADS)

Ocko, Samuel; Adams, Laura

A robust route for the biased production of single handed chiral structures has been found in generating non-spherical, multi-component double emulsions using glass microfluidic devices. The specific type of handedness is determined by the final packing geometry of four different inner drops inside an ultra-thin sheath of oil. Before the three dimensional chiral structures are formed, the quasi-one dimensional chain of four inner drops re-arranges in two dimensions into either checkerboard or stripe patterns. We derive an analytical model predicting which pattern is more likely and assembles in the least amount of time. Moreover, our model accurately predicts our experimental results and is based on local bending dynamics, rather than global surface energy minimization. We gratefully acknowledge Professors D. Weitz and L. Mahadevan's support.

APPLE - An aeroelastic analysis system for turbomachines and propfans

NASA Technical Reports Server (NTRS)

Reddy, T. S. R.; Bakhle, Milind A.; Srivastava, R.; Mehmed, Oral

1992-01-01

This paper reviews aeroelastic analysis methods for propulsion elements (advanced propellers, compressors and turbines) being developed and used at NASA Lewis Research Center. These aeroelastic models include both structural and aerodynamic components. The structural models include the typical section model, the beam model with and without disk flexibility, and the finite element blade model with plate bending elements. The aerodynamic models are based on the solution of equations ranging from the two-dimensional linear potential equation for a cascade to the three-dimensional Euler equations for multi-blade configurations. Typical results are presented for each aeroelastic model. Suggestions for further research are indicated. All the available aeroelastic models and analysis methods are being incorporated into a unified computer program named APPLE (Aeroelasticity Program for Propulsion at LEwis).

Fully automated multifunctional ultrahigh pressure liquid chromatography system for advanced proteome analyses

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

Lee, Jung Hwa; Hyung, Seok-Won; Mun, Dong-Gi

2012-08-03

A multi-functional liquid chromatography system that performs 1-dimensional, 2-dimensional (strong cation exchange/reverse phase liquid chromatography, or SCX/RPLC) separations, and online phosphopeptides enrichment using a single binary nano-flow pump has been developed. With a simple operation of a function selection valve, which is equipped with a SCX column and a TiO2 (titanium dioxide) column, a fully automated selection of three different experiment modes was achieved. Because the current system uses essentially the same solvent flow paths, the same trap column, and the same separation column for reverse-phase separation of 1D, 2D, and online phosphopeptides enrichment experiments, the elution time information obtainedmore » from these experiments is in excellent agreement, which facilitates correlating peptide information from different experiments.« less

Advanced BCD technology with vertical DMOS based on a semi-insulation structure

NASA Astrophysics Data System (ADS)

Kui, Ma; Xinghua, Fu; Jiexin, Lin; Fashun, Yang

2016-07-01

A new semi-insulation structure in which one isolated island is connected to the substrate was proposed. Based on this semi-insulation structure, an advanced BCD technology which can integrate a vertical device without extra internal interconnection structure was presented. The manufacturing of the new semi-insulation structure employed multi-epitaxy and selectively multi-doping. Isolated islands are insulated with the substrate by reverse-biased PN junctions. Adjacent isolated islands are insulated by isolation wall or deep dielectric trenches. The proposed semi-insulation structure and devices fixed in it were simulated through two-dimensional numerical computer simulators. Based on the new BCD technology, a smart power integrated circuit was designed and fabricated. The simulated and tested results of Vertical DMOS, MOSFETs, BJTs, resistors and diodes indicated that the proposed semi-insulation structure is reasonable and the advanced BCD technology is validated. Project supported by the National Natural Science Foundation of China (No. 61464002), the Science and Technology Fund of Guizhou Province (No. Qian Ke He J Zi [2014]2066), and the Dr. Fund of Guizhou University (No. Gui Da Ren Ji He Zi (2013)20Hao).

Three-dimensional density and compressible magnetic structure in solar wind turbulence

NASA Astrophysics Data System (ADS)

Roberts, Owen W.; Narita, Yasuhito; Escoubet, C.-Philippe

2018-03-01

The three-dimensional structure of both compressible and incompressible components of turbulence is investigated at proton characteristic scales in the solar wind. Measurements of the three-dimensional structure are typically difficult, since the majority of measurements are performed by a single spacecraft. However, the Cluster mission consisting of four spacecraft in a tetrahedral formation allows for a fully three-dimensional investigation of turbulence. Incompressible turbulence is investigated by using the three vector components of the magnetic field. Meanwhile compressible turbulence is investigated by considering the magnitude of the magnetic field as a proxy for the compressible fluctuations and electron density data deduced from spacecraft potential. Application of the multi-point signal resonator technique to intervals of fast and slow wind shows that both compressible and incompressible turbulence are anisotropic with respect to the mean magnetic field direction P⟂ ≫ P∥ and are sensitive to the value of the plasma beta (β; ratio of thermal to magnetic pressure) and the wind type. Moreover, the incompressible fluctuations of the fast and slow solar wind are revealed to be different with enhancements along the background magnetic field direction present in the fast wind intervals. The differences in the fast and slow wind and the implications for the presence of different wave modes in the plasma are discussed.

Predicting Student Performance in Sonographic Scanning Using Spatial Ability as an Ability Determinent of Skill Acquisition

ERIC Educational Resources Information Center

Clem, Douglas Wayne

2012-01-01

Spatial ability refers to an individual's capacity to visualize and mentally manipulate three dimensional objects. Since sonographers manually manipulate 2D and 3D sonographic images to generate multi-viewed, logical, sequential renderings of an anatomical structure, it can be assumed that spatial ability is central to the perception and…

Epistemological Beliefs of Prospective Preschool Teachers and Their Relation to Knowledge, Perception, and Planning Abilities in the Field of Mathematics: A Process Model

ERIC Educational Resources Information Center

Dunekacke, Simone; Jenßen, Lars; Eilerts, Katja; Blömeke, Sigrid

2016-01-01

Teacher competence is a multi-dimensional construct that includes beliefs as well as knowledge. The present study investigated the structure of prospective preschool teachers' mathematics-related beliefs and their relation to content knowledge and pedagogical content knowledge. In addition, prospective preschool teachers' perception and planning…

Social Capital and Stability Operations

DTIC Science & Technology

2008-03-26

defined as an instantiated set of informal values or norms that permit cooperation between two or more individuals, is the sine qua non of stable... multi -dimensional research, and editorial opinions, relate to the means (resources) by which to accomplish stability operations: unified action...development phase requires weaning indigenous institutions from reliance on external assistance. Fukuyama asserts that this is hard for three reasons

Scoring nuclear pleomorphism using a visual BoF modulated by a graph structure

NASA Astrophysics Data System (ADS)

Moncayo-Martínez, Ricardo; Romo-Bucheli, David; Arias, Viviana; Romero, Eduardo

2017-11-01

Nuclear pleomorphism has been recognized as a key histological criterium in breast cancer grading systems (such as Bloom Richardson and Nothingham grading systems). However, the nuclear pleomorphism assessment is subjective and presents high inter-reader variability. Automatic algorithms might facilitate quantitative estimation of nuclear variations in shape and size. Nevertheless, the automatic segmentation of the nuclei is difficult and still and open research problem. This paper presents a method using a bag of multi-scale visual features, modulated by a graph structure, to grade nuclei in breast cancer microscopical fields. This strategy constructs hematoxylin-eosin image patches, each containing a nucleus that is represented by a set of visual words in the BoF. The contribution of each visual word is computed by examining the visual words in an associated graph built when projecting the multi-dimensional BoF to a bi-dimensional plane where local relationships are conserved. The methodology was evaluated using 14 breast cancer cases of the Cancer Genome Atlas database. From these cases, a set of 134 microscopical fields was extracted, and under a leave-one-out validation scheme, an average F-score of 0.68 was obtained.

[Establishment and application of "multi-dimensional structure and process dynamic quality control technology system" in preparation products of traditional Chinese medicine (I)].

PubMed

Gu, Jun-Fei; Feng, Liang; Zhang, Ming-Hua; Wu, Chan; Jia, Xiao-Bin

2013-11-01

Safety is an important component of the quality control of traditional Chinese medicine (TCM) preparation products, as well as an important guarantee for clinical application. Currently, the quality control of TCMs in Chinese Pharmacopoeia mostly focuses on indicative compounds for TCM efficacy. TCM preparations are associated with multiple links, from raw materials to products, and each procedure may have impacts on the safety of preparation. We make a summary and analysis on the factors impacting safety during the preparation of TCM products, and then expound the important role of the "multi-dimensional structure and process dynamic quality control technology system" in the quality safety of TCM preparations. Because the product quality of TCM preparation is closely related to the safety, the control over safety-related material basis is an important component of the product quality control of TCM preparations. The implementation of the quality control over the dynamic process of TCM preparations from raw materials to products, and the improvement of the TCM quality safety control at the microcosmic level help lay a firm foundation for the development of the modernization process of TCM preparations.

An enhanced data visualization method for diesel engine malfunction classification using multi-sensor signals.

PubMed

Li, Yiqing; Wang, Yu; Zi, Yanyang; Zhang, Mingquan

2015-10-21

The various multi-sensor signal features from a diesel engine constitute a complex high-dimensional dataset. The non-linear dimensionality reduction method, t-distributed stochastic neighbor embedding (t-SNE), provides an effective way to implement data visualization for complex high-dimensional data. However, irrelevant features can deteriorate the performance of data visualization, and thus, should be eliminated a priori. This paper proposes a feature subset score based t-SNE (FSS-t-SNE) data visualization method to deal with the high-dimensional data that are collected from multi-sensor signals. In this method, the optimal feature subset is constructed by a feature subset score criterion. Then the high-dimensional data are visualized in 2-dimension space. According to the UCI dataset test, FSS-t-SNE can effectively improve the classification accuracy. An experiment was performed with a large power marine diesel engine to validate the proposed method for diesel engine malfunction classification. Multi-sensor signals were collected by a cylinder vibration sensor and a cylinder pressure sensor. Compared with other conventional data visualization methods, the proposed method shows good visualization performance and high classification accuracy in multi-malfunction classification of a diesel engine.

An Enhanced Data Visualization Method for Diesel Engine Malfunction Classification Using Multi-Sensor Signals

PubMed Central

Li, Yiqing; Wang, Yu; Zi, Yanyang; Zhang, Mingquan

2015-01-01

The various multi-sensor signal features from a diesel engine constitute a complex high-dimensional dataset. The non-linear dimensionality reduction method, t-distributed stochastic neighbor embedding (t-SNE), provides an effective way to implement data visualization for complex high-dimensional data. However, irrelevant features can deteriorate the performance of data visualization, and thus, should be eliminated a priori. This paper proposes a feature subset score based t-SNE (FSS-t-SNE) data visualization method to deal with the high-dimensional data that are collected from multi-sensor signals. In this method, the optimal feature subset is constructed by a feature subset score criterion. Then the high-dimensional data are visualized in 2-dimension space. According to the UCI dataset test, FSS-t-SNE can effectively improve the classification accuracy. An experiment was performed with a large power marine diesel engine to validate the proposed method for diesel engine malfunction classification. Multi-sensor signals were collected by a cylinder vibration sensor and a cylinder pressure sensor. Compared with other conventional data visualization methods, the proposed method shows good visualization performance and high classification accuracy in multi-malfunction classification of a diesel engine. PMID:26506347

Multi-Scale Analyses of Three Dimensional Woven Composite 3D Shell With a Cut Out Circle

NASA Astrophysics Data System (ADS)

Nguyen, Duc Hai; Wang, Hu

2018-06-01

A composite material are made by combining two or more constituent materials to obtain the desired material properties of each product type. The matrix material which can be polymer and fiber is used as reinforcing material. Currently, the polymer matrix is widely used in many different fields with differently designed structures such as automotive structures and aviation, aerospace, marine, etc. because of their excellent mechanical properties; in addition, they possess the high level of hardness and durability together with a significant reduction in weight compared to traditional materials. However, during design process of structure, there will be many interruptions created for the purpose of assembling the structures together or for many other design purposes. Therefore, when this structure is subject to load-bearing, its failure occurs at these interruptions due to stress concentration. This paper proposes multi-scale modeling and optimization strategies in evaluation of the effectiveness of fiber orientation in an E-glass/Epoxy woven composite 3D shell with circular holes at the center investigated by FEA results. A multi-scale model approach was developed to predict the mechanical behavior of woven composite 3D shell with circular holes at the center with different designs of material and structural parameters. Based on the analysis result of laminae, we have found that the 3D shell with fiber direction of 450 shows the best stress and strain bearing capacity. Thus combining several layers of 450 fiber direction in a multi-layer composite 3D shell reduces the stresses concentrated on the cuts of the structures.

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

Three-dimensional electron diffraction as a complementary technique to powder X-ray diffraction for phase identification and structure solution of powders.

PubMed

Yun, Yifeng; Zou, Xiaodong; Hovmöller, Sven; Wan, Wei

2015-03-01

Phase identification and structure determination are important and widely used techniques in chemistry, physics and materials science. Recently, two methods for automated three-dimensional electron diffraction (ED) data collection, namely automated diffraction tomography (ADT) and rotation electron diffraction (RED), have been developed. Compared with X-ray diffraction (XRD) and two-dimensional zonal ED, three-dimensional ED methods have many advantages in identifying phases and determining unknown structures. Almost complete three-dimensional ED data can be collected using the ADT and RED methods. Since each ED pattern is usually measured off the zone axes by three-dimensional ED methods, dynamic effects are much reduced compared with zonal ED patterns. Data collection is easy and fast, and can start at any arbitrary orientation of the crystal, which facilitates automation. Three-dimensional ED is a powerful technique for structure identification and structure solution from individual nano- or micron-sized particles, while powder X-ray diffraction (PXRD) provides information from all phases present in a sample. ED suffers from dynamic scattering, while PXRD data are kinematic. Three-dimensional ED methods and PXRD are complementary and their combinations are promising for studying multiphase samples and complicated crystal structures. Here, two three-dimensional ED methods, ADT and RED, are described. Examples are given of combinations of three-dimensional ED methods and PXRD for phase identification and structure determination over a large number of different materials, from Ni-Se-O-Cl crystals, zeolites, germanates, metal-organic frameworks and organic compounds to intermetallics with modulated structures. It is shown that three-dimensional ED is now as feasible as X-ray diffraction for phase identification and structure solution, but still needs further development in order to be as accurate as X-ray diffraction. It is expected that three-dimensional ED methods will become crucially important in the near future.

Study of the structure of 3-D composites based on carbon nanotubes in bovine serum albumin matrix by X-ray microtomography

NASA Astrophysics Data System (ADS)

Ignatov, D.; Zhurbina, N.; Gerasimenko, A.

2017-01-01

3-D composites are widely used in tissue engineering. A comprehensive analysis by X-ray microtomography was conducted to study the structure of the 3-D composites. Comprehensive analysis of the structure of the 3-D composites consisted of scanning, image reconstruction of shadow projections, two-dimensional and three-dimensional visualization of the reconstructed images and quantitative analysis of the samples. Experimental samples of composites were formed by laser vaporization of the aqueous dispersion BSA and single-walled (SWCNTs) and multi-layer (MWCNTs) carbon nanotubes. The samples have a homogeneous structure over the entire volume, the percentage of porosity of 3-D composites based on SWCNTs and MWCNTs - 16.44%, 28.31%, respectively. An average pore diameter of 3-D composites based on SWCNTs and MWCNTs - 45 μm 93 μm. 3-D composites based on carbon nanotubes in bovine serum albumin matrix can be used in tissue engineering of bone and cartilage, providing cell proliferation and blood vessel sprouting.

The multi-layer multi-configuration time-dependent Hartree method for bosons: theory, implementation, and applications.

PubMed

Cao, Lushuai; Krönke, Sven; Vendrell, Oriol; Schmelcher, Peter

2013-10-07

We develop the multi-layer multi-configuration time-dependent Hartree method for bosons (ML-MCTDHB), a variational numerically exact ab initio method for studying the quantum dynamics and stationary properties of general bosonic systems. ML-MCTDHB takes advantage of the permutation symmetry of identical bosons, which allows for investigations of the quantum dynamics from few to many-body systems. Moreover, the multi-layer feature enables ML-MCTDHB to describe mixed bosonic systems consisting of arbitrary many species. Multi-dimensional as well as mixed-dimensional systems can be accurately and efficiently simulated via the multi-layer expansion scheme. We provide a detailed account of the underlying theory and the corresponding implementation. We also demonstrate the superior performance by applying the method to the tunneling dynamics of bosonic ensembles in a one-dimensional double well potential, where a single-species bosonic ensemble of various correlation strengths and a weakly interacting two-species bosonic ensemble are considered.

Three-dimensional periodic dielectric structures having photonic Dirac points

DOEpatents

Bravo-Abad, Jorge; Joannopoulos, John D.; Soljacic, Marin

2015-06-02

The dielectric, three-dimensional photonic materials disclosed herein feature Dirac-like dispersion in quasi-two-dimensional systems. Embodiments include a face-centered cubic (fcc) structure formed by alternating layers of dielectric rods and dielectric slabs patterned with holes on respective triangular lattices. This fcc structure also includes a defect layer, which may comprise either dielectric rods or a dielectric slab with patterned with holes. This defect layer introduces Dirac cone dispersion into the fcc structure's photonic band structure. Examples of these fcc structures enable enhancement of the spontaneous emission coupling efficiency (the .beta.-factor) over large areas, contrary to the conventional wisdom that the .beta.-factor degrades as the system's size increases. These results enable large-area, low-threshold lasers; single-photon sources; quantum information processing devices; and energy harvesting systems.

Structural and Practical Identifiability Issues of Immuno-Epidemiological Vector-Host Models with Application to Rift Valley Fever.

PubMed

Tuncer, Necibe; Gulbudak, Hayriye; Cannataro, Vincent L; Martcheva, Maia

2016-09-01

In this article, we discuss the structural and practical identifiability of a nested immuno-epidemiological model of arbovirus diseases, where host-vector transmission rate, host recovery, and disease-induced death rates are governed by the within-host immune system. We incorporate the newest ideas and the most up-to-date features of numerical methods to fit multi-scale models to multi-scale data. For an immunological model, we use Rift Valley Fever Virus (RVFV) time-series data obtained from livestock under laboratory experiments, and for an epidemiological model we incorporate a human compartment to the nested model and use the number of human RVFV cases reported by the CDC during the 2006-2007 Kenya outbreak. We show that the immunological model is not structurally identifiable for the measurements of time-series viremia concentrations in the host. Thus, we study the non-dimensionalized and scaled versions of the immunological model and prove that both are structurally globally identifiable. After fixing estimated parameter values for the immunological model derived from the scaled model, we develop a numerical method to fit observable RVFV epidemiological data to the nested model for the remaining parameter values of the multi-scale system. For the given (CDC) data set, Monte Carlo simulations indicate that only three parameters of the epidemiological model are practically identifiable when the immune model parameters are fixed. Alternatively, we fit the multi-scale data to the multi-scale model simultaneously. Monte Carlo simulations for the simultaneous fitting suggest that the parameters of the immunological model and the parameters of the immuno-epidemiological model are practically identifiable. We suggest that analytic approaches for studying the structural identifiability of nested models are a necessity, so that identifiable parameter combinations can be derived to reparameterize the nested model to obtain an identifiable one. This is a crucial step in developing multi-scale models which explain multi-scale data.

Three dimensional, multi-chip module

DOEpatents

Bernhardt, A.F.; Petersen, R.W.

1993-08-31

A plurality of multi-chip modules are stacked and bonded around the perimeter by sold-bump bonds to adjacent modules on, for instance, three sides of the perimeter. The fourth side can be used for coolant distribution, for more interconnect structures, or other features, depending on particular design considerations of the chip set. The multi-chip modules comprise a circuit board, having a planarized interconnect structure formed on a first major surface, and integrated circuit chips bonded to the planarized interconnect surface. Around the periphery of each circuit board, long, narrow dummy chips'' are bonded to the finished circuit board to form a perimeter wall. The wall is higher than any of the chips on the circuit board, so that the flat back surface of the board above will only touch the perimeter wall. Module-to-module interconnect is laser-patterned on the sides of the boards and over the perimeter wall in the same way and at the same time that chip to board interconnect may be laser-patterned.

Three dimensional, multi-chip module

DOEpatents

Bernhardt, Anthony F.; Petersen, Robert W.

1993-01-01

A plurality of multi-chip modules are stacked and bonded around the perimeter by sold-bump bonds to adjacent modules on, for instance, three sides of the perimeter. The fourth side can be used for coolant distribution, for more interconnect structures, or other features, depending on particular design considerations of the chip set. The multi-chip modules comprise a circuit board, having a planarized interconnect structure formed on a first major surface, and integrated circuit chips bonded to the planarized interconnect surface. Around the periphery of each circuit board, long, narrow "dummy chips" are bonded to the finished circuit board to form a perimeter wall. The wall is higher than any of the chips on the circuit board, so that the flat back surface of the board above will only touch the perimeter wall. Module-to-module interconnect is laser-patterned o the sides of the boards and over the perimeter wall in the same way and at the same time that chip to board interconnect may be laser-patterned.

The BioIntelligence Framework: a new computational platform for biomedical knowledge computing

PubMed Central

Farley, Toni; Kiefer, Jeff; Lee, Preston; Von Hoff, Daniel; Trent, Jeffrey M; Colbourn, Charles

2013-01-01

Breakthroughs in molecular profiling technologies are enabling a new data-intensive approach to biomedical research, with the potential to revolutionize how we study, manage, and treat complex diseases. The next great challenge for clinical applications of these innovations will be to create scalable computational solutions for intelligently linking complex biomedical patient data to clinically actionable knowledge. Traditional database management systems (DBMS) are not well suited to representing complex syntactic and semantic relationships in unstructured biomedical information, introducing barriers to realizing such solutions. We propose a scalable computational framework for addressing this need, which leverages a hypergraph-based data model and query language that may be better suited for representing complex multi-lateral, multi-scalar, and multi-dimensional relationships. We also discuss how this framework can be used to create rapid learning knowledge base systems to intelligently capture and relate complex patient data to biomedical knowledge in order to automate the recovery of clinically actionable information. PMID:22859646

Non-iterative volumetric particle reconstruction near moving bodies

NASA Astrophysics Data System (ADS)

Mendelson, Leah; Techet, Alexandra

2017-11-01

When multi-camera 3D PIV experiments are performed around a moving body, the body often obscures visibility of regions of interest in the flow field in a subset of cameras. We evaluate the performance of non-iterative particle reconstruction algorithms used for synthetic aperture PIV (SAPIV) in these partially-occluded regions. We show that when partial occlusions are present, the quality and availability of 3D tracer particle information depends on the number of cameras and reconstruction procedure used. Based on these findings, we introduce an improved non-iterative reconstruction routine for SAPIV around bodies. The reconstruction procedure combines binary masks, already required for reconstruction of the body's 3D visual hull, and a minimum line-of-sight algorithm. This approach accounts for partial occlusions without performing separate processing for each possible subset of cameras. We combine this reconstruction procedure with three-dimensional imaging on both sides of the free surface to reveal multi-fin wake interactions generated by a jumping archer fish. Sufficient particle reconstruction in near-body regions is crucial to resolving the wake structures of upstream fins (i.e., dorsal and anal fins) before and during interactions with the caudal tail.

Couplings between hierarchical conformational dynamics from multi-time correlation functions and two-dimensional lifetime spectra: Application to adenylate kinase

NASA Astrophysics Data System (ADS)

Ono, Junichi; Takada, Shoji; Saito, Shinji

2015-06-01

An analytical method based on a three-time correlation function and the corresponding two-dimensional (2D) lifetime spectrum is developed to elucidate the time-dependent couplings between the multi-timescale (i.e., hierarchical) conformational dynamics in heterogeneous systems such as proteins. In analogy with 2D NMR, IR, electronic, and fluorescence spectroscopies, the waiting-time dependence of the off-diagonal peaks in the 2D lifetime spectra can provide a quantitative description of the dynamical correlations between the conformational motions with different lifetimes. The present method is applied to intrinsic conformational changes of substrate-free adenylate kinase (AKE) using long-time coarse-grained molecular dynamics simulations. It is found that the hierarchical conformational dynamics arise from the intra-domain structural transitions among conformational substates of AKE by analyzing the one-time correlation functions and one-dimensional lifetime spectra for the donor-acceptor distances corresponding to single-molecule Förster resonance energy transfer experiments with the use of the principal component analysis. In addition, the complicated waiting-time dependence of the off-diagonal peaks in the 2D lifetime spectra for the donor-acceptor distances is attributed to the fact that the time evolution of the couplings between the conformational dynamics depends upon both the spatial and temporal characters of the system. The present method is expected to shed light on the biological relationship among the structure, dynamics, and function.

Couplings between hierarchical conformational dynamics from multi-time correlation functions and two-dimensional lifetime spectra: Application to adenylate kinase

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

Ono, Junichi; Takada, Shoji; Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto 606-8502

2015-06-07

An analytical method based on a three-time correlation function and the corresponding two-dimensional (2D) lifetime spectrum is developed to elucidate the time-dependent couplings between the multi-timescale (i.e., hierarchical) conformational dynamics in heterogeneous systems such as proteins. In analogy with 2D NMR, IR, electronic, and fluorescence spectroscopies, the waiting-time dependence of the off-diagonal peaks in the 2D lifetime spectra can provide a quantitative description of the dynamical correlations between the conformational motions with different lifetimes. The present method is applied to intrinsic conformational changes of substrate-free adenylate kinase (AKE) using long-time coarse-grained molecular dynamics simulations. It is found that the hierarchicalmore » conformational dynamics arise from the intra-domain structural transitions among conformational substates of AKE by analyzing the one-time correlation functions and one-dimensional lifetime spectra for the donor-acceptor distances corresponding to single-molecule Förster resonance energy transfer experiments with the use of the principal component analysis. In addition, the complicated waiting-time dependence of the off-diagonal peaks in the 2D lifetime spectra for the donor-acceptor distances is attributed to the fact that the time evolution of the couplings between the conformational dynamics depends upon both the spatial and temporal characters of the system. The present method is expected to shed light on the biological relationship among the structure, dynamics, and function.« less

A SOLAR CORONAL JET EVENT TRIGGERS A CORONAL MASS EJECTION

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

Liu, Jiajia; Wang, Yuming; Shen, Chenglong

2015-11-10

In this paper, we present multi-point, multi-wavelength observations and analysis of a solar coronal jet and coronal mass ejection (CME) event. Employing the GCS model, we obtained the real (three-dimensional) heliocentric distance and direction of the CME and found it to propagate at a high speed of over 1000 km s{sup −1}. The jet erupted before the CME and shared the same source region. The temporal and spacial relationship between these two events lead us to the possibility that the jet triggered the CME and became its core. This scenario hold the promise of enriching our understanding of the triggeringmore » mechanism of CMEs and their relations to coronal large-scale jets. On the other hand, the magnetic field configuration of the source region observed by the Solar Dynamics Observatory (SDO)/HMI instrument along with the off-limb inverse Y-shaped configuration observed by SDO/AIA in the 171 Å passband provide the first detailed observation of the three-dimensional reconnection process of a large-scale jet as simulated in Pariat et al. The eruption process of the jet highlights the importance of filament-like material during the eruption of not only small-scale X-ray jets, but likely also of large-scale EUV jets. Based on our observations and analysis, we propose the most probable mechanism for the whole event, with a blob structure overlaying the three-dimensional structure of the jet, to describe the interaction between the jet and the CME.« less

Summary of Research Report

NASA Technical Reports Server (NTRS)

Elishakoff, Isaac

1998-01-01

Ten papers, published in various publications, on buckling, and the effects of imperfections on various structures are presented. These papers are: (1) Buckling mode localization in elastic plates due to misplacement in the stiffner location; (2) On vibrational imperfection sensitivity on Augusti's model structure in the vicinity of a non-linear static state; (3) Imperfection sensitivity due to elastic moduli in the Roorda Koiter frame; (4) Buckling mode localization in a multi-span periodic structure with a disorder in a single span; (5) Prediction of natural frequency and buckling load variability due to uncertainty in material properties by convex modeling; (6) Derivation of multi-dimensional ellipsoidal convex model for experimental data; (7) Passive control of buckling deformation via Anderson localization phenomenon; (8)Effect of the thickness and initial im perfection on buckling on composite cylindrical shells: asymptotic analysis and numerical results by BOSOR4 and PANDA2; (9) Worst case estimation of homology design by convex analysis; (10) Buckling of structures with uncertain imperfections - Personal perspective.

Analysis and design of numerical schemes for gas dynamics 1: Artificial diffusion, upwind biasing, limiters and their effect on accuracy and multigrid convergence

NASA Technical Reports Server (NTRS)

Jameson, Antony

1994-01-01

The theory of non-oscillatory scalar schemes is developed in this paper in terms of the local extremum diminishing (LED) principle that maxima should not increase and minima should not decrease. This principle can be used for multi-dimensional problems on both structured and unstructured meshes, while it is equivalent to the total variation diminishing (TVD) principle for one-dimensional problems. A new formulation of symmetric limited positive (SLIP) schemes is presented, which can be generalized to produce schemes with arbitrary high order of accuracy in regions where the solution contains no extrema, and which can also be implemented on multi-dimensional unstructured meshes. Systems of equations lead to waves traveling with distinct speeds and possibly in opposite directions. Alternative treatments using characteristic splitting and scalar diffusive fluxes are examined, together with modification of the scalar diffusion through the addition of pressure differences to the momentum equations to produce full upwinding in supersonic flow. This convective upwind and split pressure (CUSP) scheme exhibits very rapid convergence in multigrid calculations of transonic flow, and provides excellent shock resolution at very high Mach numbers.

Streamflow hindcasting in European river basins via multi-parametric ensemble of the mesoscale hydrologic model (mHM)

NASA Astrophysics Data System (ADS)

Noh, Seong Jin; Rakovec, Oldrich; Kumar, Rohini; Samaniego, Luis

2016-04-01

There have been tremendous improvements in distributed hydrologic modeling (DHM) which made a process-based simulation with a high spatiotemporal resolution applicable on a large spatial scale. Despite of increasing information on heterogeneous property of a catchment, DHM is still subject to uncertainties inherently coming from model structure, parameters and input forcing. Sequential data assimilation (DA) may facilitate improved streamflow prediction via DHM using real-time observations to correct internal model states. In conventional DA methods such as state updating, parametric uncertainty is, however, often ignored mainly due to practical limitations of methodology to specify modeling uncertainty with limited ensemble members. If parametric uncertainty related with routing and runoff components is not incorporated properly, predictive uncertainty by DHM may be insufficient to capture dynamics of observations, which may deteriorate predictability. Recently, a multi-scale parameter regionalization (MPR) method was proposed to make hydrologic predictions at different scales using a same set of model parameters without losing much of the model performance. The MPR method incorporated within the mesoscale hydrologic model (mHM, http://www.ufz.de/mhm) could effectively represent and control uncertainty of high-dimensional parameters in a distributed model using global parameters. In this study, we present a global multi-parametric ensemble approach to incorporate parametric uncertainty of DHM in DA to improve streamflow predictions. To effectively represent and control uncertainty of high-dimensional parameters with limited number of ensemble, MPR method is incorporated with DA. Lagged particle filtering is utilized to consider the response times and non-Gaussian characteristics of internal hydrologic processes. The hindcasting experiments are implemented to evaluate impacts of the proposed DA method on streamflow predictions in multiple European river basins having different climate and catchment characteristics. Because augmentation of parameters is not required within an assimilation window, the approach could be stable with limited ensemble members and viable for practical uses.

A tool for multi-scale modelling of the renal nephron

PubMed Central

Nickerson, David P.; Terkildsen, Jonna R.; Hamilton, Kirk L.; Hunter, Peter J.

2011-01-01

We present the development of a tool, which provides users with the ability to visualize and interact with a comprehensive description of a multi-scale model of the renal nephron. A one-dimensional anatomical model of the nephron has been created and is used for visualization and modelling of tubule transport in various nephron anatomical segments. Mathematical models of nephron segments are embedded in the one-dimensional model. At the cellular level, these segment models use models encoded in CellML to describe cellular and subcellular transport kinetics. A web-based presentation environment has been developed that allows the user to visualize and navigate through the multi-scale nephron model, including simulation results, at the different spatial scales encompassed by the model description. The Zinc extension to Firefox is used to provide an interactive three-dimensional view of the tubule model and the native Firefox rendering of scalable vector graphics is used to present schematic diagrams for cellular and subcellular scale models. The model viewer is embedded in a web page that dynamically presents content based on user input. For example, when viewing the whole nephron model, the user might be presented with information on the various embedded segment models as they select them in the three-dimensional model view. Alternatively, the user chooses to focus the model viewer on a cellular model located in a particular nephron segment in order to view the various membrane transport proteins. Selecting a specific protein may then present the user with a description of the mathematical model governing the behaviour of that protein—including the mathematical model itself and various simulation experiments used to validate the model against the literature. PMID:22670210

Intelligent Data Analysis in the EMERCOM Information System

NASA Astrophysics Data System (ADS)

Elena, Sharafutdinova; Tatiana, Avdeenko; Bakaev, Maxim

2017-01-01

The paper describes an information system development project for the Russian Ministry of Emergency Situations (MES, whose international operations body is known as EMERCOM), which was attended by the representatives of both the IT industry and the academia. Besides the general description of the system, we put forward OLAP and Data Mining-based approaches towards the intelligent analysis of the data accumulated in the database. In particular, some operational OLAP reports and an example of multi-dimensional information space based on OLAP Data Warehouse are presented. Finally, we outline Data Mining application to support decision-making regarding security inspections planning and results consideration.

FleCSPH notes

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

Lim, Hyun; Loiseau, Julien

FleCSI is a compile-time con gurable framework designed to support multi-physics application development. As such, FleCSI provides a very general set of infrastructure design patterns that can be specialized and extended to suit the needs of a broad variety of solver and data requirements. FleCSI currently supports multi-dimensional mesh topology, geometry, and adjacency information, as well as n-dimensional hashed-tree data structures, graph partitioning interfaces, and dependency closures. FleCSI introduces a functional programming model with control, execution, and data abstractions that are consistent both with MPI and with state-of-the-art, task-based runtimes such as Legion and Charm++. The abstraction layer insulates developersmore » from the underlying runtime, while allowing support for multiple runtime systems including conventional models like asynchronous MPI. The intent is to provide developers with a concrete set of user-friendly programming tools that can be used now, while allowing exibility in choosing runtime implementations and optimization that can be applied to future architectures and runtimes. FleCSI's control and execution models provide formal nomenclature for describing poorly understood concepts such as kernels and tasks. FleCSI's data model provides a low-buy-in approach that makes it an attractive option for many application projects, as developers are not locked into particular layouts or data structure representations. FleCSI currently provides a parallel but not distributed implementation of Binary, Quad and Oct-tree topology. This implementation is base on space lling curves domain decomposition, the Morton order. The current FleCSI version requires the implementation of a driver and a specialization driver. The role of the specialization driver is to provide the data distribution. This feature is not complete in FleCSI code and we provide it. The next step will be to incorporate it directly from FleCSPH to FleCSI as we reach a good level of performance. Then the driver represent the general execution of the resolution without worrying of the data locality and communications. As FleCSI is an On-Development code the structure may change in the future and we keep track of these changes in FleCSPH.« less

Gender approaches to evolutionary multi-objective optimization using pre-selection of criteria

NASA Astrophysics Data System (ADS)

Kowalczuk, Zdzisław; Białaszewski, Tomasz

2018-01-01

A novel idea to perform evolutionary computations (ECs) for solving highly dimensional multi-objective optimization (MOO) problems is proposed. Following the general idea of evolution, it is proposed that information about gender is used to distinguish between various groups of objectives and identify the (aggregate) nature of optimality of individuals (solutions). This identification is drawn out of the fitness of individuals and applied during parental crossover in the processes of evolutionary multi-objective optimization (EMOO). The article introduces the principles of the genetic-gender approach (GGA) and virtual gender approach (VGA), which are not just evolutionary techniques, but constitute a completely new rule (philosophy) for use in solving MOO tasks. The proposed approaches are validated against principal representatives of the EMOO algorithms of the state of the art in solving benchmark problems in the light of recognized EC performance criteria. The research shows the superiority of the gender approach in terms of effectiveness, reliability, transparency, intelligibility and MOO problem simplification, resulting in the great usefulness and practicability of GGA and VGA. Moreover, an important feature of GGA and VGA is that they alleviate the 'curse' of dimensionality typical of many engineering designs.

Sine-Gordon Equation in (1+2) and (1+3) dimensions: Existence and Classification of Traveling-Wave Solutions.

PubMed

Zarmi, Yair

2015-01-01

The (1+1)-dimensional Sine-Gordon equation passes integrability tests commonly applied to nonlinear evolution equations. Its kink solutions (one-dimensional fronts) are obtained by a Hirota algorithm. In higher space-dimensions, the equation does not pass these tests. Although it has been derived over the years for quite a few physical systems that have nothing to do with Special Relativity, the Sine-Gordon equation emerges as a non-linear relativistic wave equation. This opens the way for exploiting the tools of the Theory of Special Relativity. Using no more than the relativistic kinematics of tachyonic momentum vectors, from which the solutions are constructed through the Hirota algorithm, the existence and classification of N-moving-front solutions of the (1+2)- and (1+3)-dimensional equations for all N ≥ 1 are presented. In (1+2) dimensions, each multi-front solution propagates rigidly at one velocity. The solutions are divided into two subsets: Solutions whose velocities are lower than a limiting speed, c = 1, or are greater than or equal to c. To connect with concepts of the Theory of Special Relativity, c will be called "the speed of light." In (1+3)-dimensions, multi-front solutions are characterized by spatial structure and by velocity composition. The spatial structure is either planar (rotated (1+2)-dimensional solutions), or genuinely three-dimensional--branes. Planar solutions, propagate rigidly at one velocity, which is lower than, equal to, or higher than c. Branes must contain clusters of fronts whose speed exceeds c = 1. Some branes are "hybrids": different clusters of fronts propagate at different velocities. Some velocities may be lower than c but some must be equal to, or exceed, c. Finally, the speed of light cannot be approached from within the subset of slower-than-light solutions in both (1+2) and (1+3) dimensions.

Tomography and Purification of the Temporal-Mode Structure of Quantum Light

NASA Astrophysics Data System (ADS)

Ansari, Vahid; Donohue, John M.; Allgaier, Markus; Sansoni, Linda; Brecht, Benjamin; Roslund, Jonathan; Treps, Nicolas; Harder, Georg; Silberhorn, Christine

2018-05-01

High-dimensional quantum information processing promises capabilities beyond the current state of the art, but addressing individual information-carrying modes presents a significant experimental challenge. Here we demonstrate effective high-dimensional operations in the time-frequency domain of nonclassical light. We generate heralded photons with tailored temporal-mode structures through the pulse shaping of a broadband parametric down-conversion pump. We then implement a quantum pulse gate, enabled by dispersion-engineered sum-frequency generation, to project onto programmable temporal modes, reconstructing the quantum state in seven dimensions. We also manipulate the time-frequency structure by selectively removing temporal modes, explicitly demonstrating the effectiveness of engineered nonlinear processes for the mode-selective manipulation of quantum states.

Multi-particle three-dimensional coordinate estimation in real-time optical manipulation

NASA Astrophysics Data System (ADS)

Dam, J. S.; Perch-Nielsen, I.; Palima, D.; Gluckstad, J.

2009-11-01

We have previously shown how stereoscopic images can be obtained in our three-dimensional optical micromanipulation system [J. S. Dam et al, Opt. Express 16, 7244 (2008)]. Here, we present an extension and application of this principle to automatically gather the three-dimensional coordinates for all trapped particles with high tracking range and high reliability without requiring user calibration. Through deconvolving of the red, green, and blue colour planes to correct for bleeding between colour planes, we show that we can extend the system to also utilize green illumination, in addition to the blue and red. Applying the green colour as on-axis illumination yields redundant information for enhanced error correction, which is used to verify the gathered data, resulting in reliable coordinates as well as producing visually attractive images.

Fully three-dimensional analysis of high-speed train-track-soil-structure dynamic interaction

NASA Astrophysics Data System (ADS)

Galvín, P.; Romero, A.; Domínguez, J.

2010-11-01

In this paper, a general and fully three dimensional multi-body-finite element-boundary element model, formulated in the time domain to predict vibrations due to train passage at the vehicle, the track and the free field, is presented. The vehicle is modelled as a multi-body system and, therefore, the quasi-static and the dynamic excitation mechanisms due to train passage can be considered. The track is modelled using finite elements. The soil is considered as a homogeneous half-space by the boundary element method. This methodology could be used to take into account local soil discontinuities, underground constructions such as underpasses, and coupling with nearby structures that break the uniformity of the geometry along the track line. The nonlinear behaviour of the structures could be also considered. In the present paper, in order to test the model, vibrations induced by high-speed train passage are evaluated for a ballasted track. The quasi-static and dynamic load components are studied and the influence of the suspended mass on the vertical loads is analyzed. The numerical model is validated by comparison with experimental records from two HST lines. Finally, the dynamic behaviour of a transition zone between a ballast track and a slab track is analyzed and the obtained results from the proposed model are compared with those obtained from a model with invariant geometry with respect to the track direction.

Use of electromagnetic-terrain conductivity and DC-resistivity profiling techniques for bedrock characterization at the 15th-of-May City extension, Cairo, Egypt

NASA Astrophysics Data System (ADS)

Aly, Said A.; Farag, Karam S. I.; Atya, Magdy A.; Badr, Mohamed A. M.

2018-06-01

A joint multi-spacing electromagnetic-terrain conductivity meter and DC-resistivity horizontal profiling survey was conducted at the anticipated eastern extensional area of the 15th-of-May City, southeastern Cairo, Egypt. The main objective of the survey was to highlight the applicability, efficiency, and reliability of utilizing such non-invasive surface techniques in a field like geologic mapping, and hence to image both the vertical and lateral electrical resistivity structures of the subsurface bedrock. Consequently, a total of reliable 6 multi-spacing electromagnetic-terrain conductivity meter and 7 DC-resistivity horizontal profiles were carried out between August 2016 and February 2017. All data sets were transformed-inverted extensively and consistently in terms of two-dimensional (2D) electrical resistivity smoothed-earth models. They could be used effectively and inexpensively to interpret the area's bedrock geologic sequence using the encountered consecutive electrically resistive and conductive anomalies. Notably, the encountered subsurface electrical resistivity structures, below all surveying profiles, are correlated well with the mapped geological faults in the field. They even could provide a useful understanding of their faulting fashion. Absolute resistivity values were not necessarily diagnostic, but their vertical and lateral variations could provide more diagnostic information about the layer lateral extensions and thicknesses, and hence suggested reliable geo-electric earth models. The study demonstrated that a detailed multi-spacing electromagnetic-terrain conductivity meter and DC-resistivity horizontal profiling survey can help design an optimal geotechnical investigative program, not only for the whole eastern extensional area of the 15th-of-May City, but also for the other new urban communities within the Egyptian desert.

L1-norm locally linear representation regularization multi-source adaptation learning.

PubMed

Tao, Jianwen; Wen, Shiting; Hu, Wenjun

2015-09-01

In most supervised domain adaptation learning (DAL) tasks, one has access only to a small number of labeled examples from target domain. Therefore the success of supervised DAL in this "small sample" regime needs the effective utilization of the large amounts of unlabeled data to extract information that is useful for generalization. Toward this end, we here use the geometric intuition of manifold assumption to extend the established frameworks in existing model-based DAL methods for function learning by incorporating additional information about the target geometric structure of the marginal distribution. We would like to ensure that the solution is smooth with respect to both the ambient space and the target marginal distribution. In doing this, we propose a novel L1-norm locally linear representation regularization multi-source adaptation learning framework which exploits the geometry of the probability distribution, which has two techniques. Firstly, an L1-norm locally linear representation method is presented for robust graph construction by replacing the L2-norm reconstruction measure in LLE with L1-norm one, which is termed as L1-LLR for short. Secondly, considering the robust graph regularization, we replace traditional graph Laplacian regularization with our new L1-LLR graph Laplacian regularization and therefore construct new graph-based semi-supervised learning framework with multi-source adaptation constraint, which is coined as L1-MSAL method. Moreover, to deal with the nonlinear learning problem, we also generalize the L1-MSAL method by mapping the input data points from the input space to a high-dimensional reproducing kernel Hilbert space (RKHS) via a nonlinear mapping. Promising experimental results have been obtained on several real-world datasets such as face, visual video and object. Copyright © 2015 Elsevier Ltd. All rights reserved.

Single-particle cryo-EM using alignment by classification (ABC): the structure of Lumbricus terrestris haemoglobin.

PubMed

Afanasyev, Pavel; Seer-Linnemayr, Charlotte; Ravelli, Raimond B G; Matadeen, Rishi; De Carlo, Sacha; Alewijnse, Bart; Portugal, Rodrigo V; Pannu, Navraj S; Schatz, Michael; van Heel, Marin

2017-09-01

Single-particle cryogenic electron microscopy (cryo-EM) can now yield near-atomic resolution structures of biological complexes. However, the reference-based alignment algorithms commonly used in cryo-EM suffer from reference bias, limiting their applicability (also known as the 'Einstein from random noise' problem). Low-dose cryo-EM therefore requires robust and objective approaches to reveal the structural information contained in the extremely noisy data, especially when dealing with small structures. A reference-free pipeline is presented for obtaining near-atomic resolution three-dimensional reconstructions from heterogeneous ('four-dimensional') cryo-EM data sets. The methodologies integrated in this pipeline include a posteriori camera correction, movie-based full-data-set contrast transfer function determination, movie-alignment algorithms, (Fourier-space) multivariate statistical data compression and unsupervised classification, 'random-startup' three-dimensional reconstructions, four-dimensional structural refinements and Fourier shell correlation criteria for evaluating anisotropic resolution. The procedures exclusively use information emerging from the data set itself, without external 'starting models'. Euler-angle assignments are performed by angular reconstitution rather than by the inherently slower projection-matching approaches. The comprehensive 'ABC-4D' pipeline is based on the two-dimensional reference-free 'alignment by classification' (ABC) approach, where similar images in similar orientations are grouped by unsupervised classification. Some fundamental differences between X-ray crystallography versus single-particle cryo-EM data collection and data processing are discussed. The structure of the giant haemoglobin from Lumbricus terrestris at a global resolution of ∼3.8 Å is presented as an example of the use of the ABC-4D procedure.

Interpretable dimensionality reduction of single cell transcriptome data with deep generative models.

PubMed

Ding, Jiarui; Condon, Anne; Shah, Sohrab P

2018-05-21

Single-cell RNA-sequencing has great potential to discover cell types, identify cell states, trace development lineages, and reconstruct the spatial organization of cells. However, dimension reduction to interpret structure in single-cell sequencing data remains a challenge. Existing algorithms are either not able to uncover the clustering structures in the data or lose global information such as groups of clusters that are close to each other. We present a robust statistical model, scvis, to capture and visualize the low-dimensional structures in single-cell gene expression data. Simulation results demonstrate that low-dimensional representations learned by scvis preserve both the local and global neighbor structures in the data. In addition, scvis is robust to the number of data points and learns a probabilistic parametric mapping function to add new data points to an existing embedding. We then use scvis to analyze four single-cell RNA-sequencing datasets, exemplifying interpretable two-dimensional representations of the high-dimensional single-cell RNA-sequencing data.

Geometrical structure of Neural Networks: Geodesics, Jeffrey's Prior and Hyper-ribbons

NASA Astrophysics Data System (ADS)

Hayden, Lorien; Alemi, Alex; Sethna, James

2014-03-01

Neural networks are learning algorithms which are employed in a host of Machine Learning problems including speech recognition, object classification and data mining. In practice, neural networks learn a low dimensional representation of high dimensional data and define a model manifold which is an embedding of this low dimensional structure in the higher dimensional space. In this work, we explore the geometrical structure of a neural network model manifold. A Stacked Denoising Autoencoder and a Deep Belief Network are trained on handwritten digits from the MNIST database. Construction of geodesics along the surface and of slices taken from the high dimensional manifolds reveal a hierarchy of widths corresponding to a hyper-ribbon structure. This property indicates that neural networks fall into the class of sloppy models, in which certain parameter combinations dominate the behavior. Employing this information could prove valuable in designing both neural network architectures and training algorithms. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No . DGE-1144153.

Percolated microstructures for multi-modal transport enhancement in porous active materials

DOEpatents

McKay, Ian Salmon; Yang, Sungwoo; Wang, Evelyn N.; Kim, Hyunho

2018-03-13

A method of forming a composite material for use in multi-modal transport includes providing three-dimensional graphene having hollow channels, enabling a polymer to wick into the hollow channels of the three-dimensional graphene, curing the polymer to form a cured three-dimensional graphene, adding an active material to the cured three-dimensional graphene to form a composite material, and removing the polymer from within the hollow channels. A composite material formed according to the method is also provided.

A Comparative Distributed Evaluation of the NWS-RDHM using Shape Matching and Traditional Measures with In Situ and Remotely Sensed Information

NASA Astrophysics Data System (ADS)

KIM, J.; Bastidas, L. A.

2011-12-01

We evaluate, calibrate and diagnose the performance of National Weather Service RDHM distributed model over the Durango River Basin in Colorado using simultaneously in situ and remotely sensed information from different discharge gaging stations (USGS), information about snow cover (SCV) and snow water equivalent (SWE) in situ from several SNOTEL sites and snow information distributed over the catchment from remotely sensed information (NOAA-NASA). In the process of evaluation we attempt to establish the optimal degree of parameter distribution over the catchment by calibration. A multi-criteria approach based on traditional measures (RMSE) and similarity based pattern comparisons using the Hausdorff and Earth Movers Distance approaches is used for the overall evaluation of the model performance. These pattern based approaches (shape matching) are found to be extremely relevant to account for the relatively large degree of inaccuracy in the remotely sensed SWE (judged inaccurate in terms of the value but reliable in terms of the distribution pattern) and the high reliability of the SCV (yes/no situation) while at the same time allow for an evaluation that quantifies the accuracy of the model over the entire catchment considering the different types of observations. The Hausdorff norm, due to its intrinsically multi-dimensional nature, allows for the incorporation of variables such as the terrain elevation as one of the variables for evaluation. The EMD, because of its extremely high computational overburden, requires the mapping of the set of evaluation variables into a two dimensional matrix for computation.

Data related to the experimental design for powder bed binder jetting additive manufacturing of silicone.

PubMed

Liravi, Farzad; Vlasea, Mihaela

2018-06-01

The data included in this article provides additional supporting information on our recent publication (Liravi et al., 2018 [1]) on a novel hybrid additive manufacturing (AM) method for fabrication of three-dimensional (3D) structures from silicone powder. A design of experiments (DoE) study has been carried out to optimize the geometrical fidelity of AM-made parts. This manuscript includes the details of a multi-level factorial DOE and the response optimization results. The variation in the temperature of powder-bed when exposed to heat is plotted as well. Furthermore, the effect of blending ratio of two parts of silicone binder on its curing speed was investigated by conducting DSC tests on a silicone binder with 100:2 precursor to curing agent ratio. The hardness of parts fabricated with non-optimum printing conditions are included and compared.

Hybrid quantum systems: Outsourcing superconducting qubits

NASA Astrophysics Data System (ADS)

Cleland, Andrew

Superconducting qubits offer excellent prospects for manipulating quantum information, with good qubit lifetimes, high fidelity single- and two-qubit gates, and straightforward scalability (admittedly with multi-dimensional interconnect challenges). One interesting route for experimental development is the exploration of hybrid systems, i.e. coupling superconducting qubits to other systems. I will report on our group's efforts to develop approaches that will allow interfacing superconducting qubits in a quantum-coherent fashion to spin defects in solids, to optomechanical devices, and to resonant nanomechanical structures. The longer term goals of these efforts include transferring quantum states between different qubit systems; generating and receiving ``flying'' acoustic phonon-based as well as optical photon-based qubits; and ultimately developing systems that can be used for quantum memory, quantum computation and quantum communication, the last in both the microwave and fiber telecommunications bands. Work is supported by Grants from AFOSR, ARO, DOE and NSF.

Transcending the slow bimolecular recombination in lead-halide perovskites for electroluminescence

PubMed Central

Xing, Guichuan; Wu, Bo; Wu, Xiangyang; Li, Mingjie; Du, Bin; Wei, Qi; Guo, Jia; Yeow, Edwin K. L.; Sum, Tze Chien; Huang, Wei

2017-01-01

The slow bimolecular recombination that drives three-dimensional lead-halide perovskites' outstanding photovoltaic performance is conversely a fundamental limitation for electroluminescence. Under electroluminescence working conditions with typical charge densities lower than 1015 cm−3, defect-states trapping in three-dimensional perovskites competes effectively with the bimolecular radiative recombination. Herein, we overcome this limitation using van-der-Waals-coupled Ruddlesden-Popper perovskite multi-quantum-wells. Injected charge carriers are rapidly localized from adjacent thin few layer (n≤4) multi-quantum-wells to the thick (n≥5) multi-quantum-wells with extremely high efficiency (over 85%) through quantum coupling. Light emission originates from excitonic recombination in the thick multi-quantum-wells at much higher decay rate and efficiency than bimolecular recombination in three-dimensional perovskites. These multi-quantum-wells retain the simple solution processability and high charge carrier mobility of two-dimensional lead-halide perovskites. Importantly, these Ruddlesden-Popper perovskites offer new functionalities unavailable in single phase constituents, permitting the transcendence of the slow bimolecular recombination bottleneck in lead-halide perovskites for efficient electroluminescence. PMID:28239146

Transcending the slow bimolecular recombination in lead-halide perovskites for electroluminescence.

PubMed

Xing, Guichuan; Wu, Bo; Wu, Xiangyang; Li, Mingjie; Du, Bin; Wei, Qi; Guo, Jia; Yeow, Edwin K L; Sum, Tze Chien; Huang, Wei

2017-02-27

The slow bimolecular recombination that drives three-dimensional lead-halide perovskites' outstanding photovoltaic performance is conversely a fundamental limitation for electroluminescence. Under electroluminescence working conditions with typical charge densities lower than 10 15  cm -3 , defect-states trapping in three-dimensional perovskites competes effectively with the bimolecular radiative recombination. Herein, we overcome this limitation using van-der-Waals-coupled Ruddlesden-Popper perovskite multi-quantum-wells. Injected charge carriers are rapidly localized from adjacent thin few layer (n≤4) multi-quantum-wells to the thick (n≥5) multi-quantum-wells with extremely high efficiency (over 85%) through quantum coupling. Light emission originates from excitonic recombination in the thick multi-quantum-wells at much higher decay rate and efficiency than bimolecular recombination in three-dimensional perovskites. These multi-quantum-wells retain the simple solution processability and high charge carrier mobility of two-dimensional lead-halide perovskites. Importantly, these Ruddlesden-Popper perovskites offer new functionalities unavailable in single phase constituents, permitting the transcendence of the slow bimolecular recombination bottleneck in lead-halide perovskites for efficient electroluminescence.

One-Dimensional Contact Mode Interdigitated Center of Pressure Sensor (CMIPS)

NASA Technical Reports Server (NTRS)

Xu, Tian-Bing; Kang, Jinho; Park, Cheol; Harrison, Joycelyn S.; Guerreiro, Nelson M.; Hubbard, James E.

2009-01-01

A one dimensional contact mode interdigitated center of pressure sensor (CMIPS) has been developed. The experimental study demonstrated that the CMIPS has the capability to measure the overall pressure as well as the center of pressure in one dimension, simultaneously. A theoretical model for the CMIPS is established here based on the equivalent circuit of the configuration of the CMIPS as well as the material properties of the sensor. The experimental results match well with theoretical modeling predictions. A system mapped with two or more pieces of the CMIPS can be used to obtain information from the pressure distribution in multi-dimensions.

Secure coherent optical multi-carrier system with four-dimensional modulation space and Stokes vector scrambling.

PubMed

Zhang, Lijia; Liu, Bo; Xin, Xiangjun

2015-06-15

A secure enhanced coherent optical multi-carrier system based on Stokes vector scrambling is proposed and experimentally demonstrated. The optical signal with four-dimensional (4D) modulation space has been scrambled intra- and inter-subcarriers, where a multi-layer logistic map is adopted as the chaotic model. An experiment with 61.71-Gb/s encrypted multi-carrier signal is successfully demonstrated with the proposed method. The results indicate a promising solution for the physical secure optical communication.

A three-dimensional non-isothermal model for a membraneless direct methanol redox fuel cell

NASA Astrophysics Data System (ADS)

Wei, Lin; Yuan, Xianxia; Jiang, Fangming

2018-05-01

In the membraneless direct methanol redox fuel cell (DMRFC), three-dimensional electrodes contribute to the reduction of methanol crossover and the open separator design lowers the system cost and extends its service life. In order to better understand the mechanisms of this configuration and further optimize its performance, the development of a three-dimensional numerical model is reported in this work. The governing equations of the multi-physics field are solved based on computational fluid dynamics methodology, and the influence of the CO2 gas is taken into consideration through the effective diffusivities. The numerical results are in good agreement with experimental data, and the deviation observed for cases of large current density may be related to the single-phase assumption made. The three-dimensional electrode is found to be effective in controlling methanol crossover in its multi-layer structure, while it also increases the flow resistance for the discharging products. It is found that the current density distribution is affected by both the electronic conductivity and the concentration of reactants, and the temperature rise can be primarily attributed to the current density distribution. The sensitivity and reliability of the model are analyzed through the investigation of the effects of cell parameters, including porosity values of gas diffusion layers and catalyst layers, methanol concentration and CO2 volume fraction, on the polarization characteristics.

Coherent diffraction imaging: consistency of the assembled three-dimensional distribution.

PubMed

Tegze, Miklós; Bortel, Gábor

2016-07-01

The short pulses of X-ray free-electron lasers can produce diffraction patterns with structural information before radiation damage destroys the particle. From the recorded diffraction patterns the structure of particles or molecules can be determined on the nano- or even atomic scale. In a coherent diffraction imaging experiment thousands of diffraction patterns of identical particles are recorded and assembled into a three-dimensional distribution which is subsequently used to solve the structure of the particle. It is essential to know, but not always obvious, that the assembled three-dimensional reciprocal-space intensity distribution is really consistent with the measured diffraction patterns. This paper shows that, with the use of correlation maps and a single parameter calculated from them, the consistency of the three-dimensional distribution can be reliably validated.

Application of Hyperspectral Techniques to Monitoring and Management of Invasive Plant Species Infestation

DTIC Science & Technology

2008-01-01

the sensor is a data cloud in multi- dimensional space with each band generating an axis of dimension. When the data cloud is viewed in two or three...endmember of interest is not a true endmember in the data space . A ) B) Figure 8: Linear mixture models. A ) two- dimensional ...multi- dimensional space . A classifier is a computer algorithm that takes

A comprehensive simulation framework for imaging single particles and biomolecules at the European X-ray Free-Electron Laser

PubMed Central

Yoon, Chun Hong; Yurkov, Mikhail V.; Schneidmiller, Evgeny A.; Samoylova, Liubov; Buzmakov, Alexey; Jurek, Zoltan; Ziaja, Beata; Santra, Robin; Loh, N. Duane; Tschentscher, Thomas; Mancuso, Adrian P.

2016-01-01

The advent of newer, brighter, and more coherent X-ray sources, such as X-ray Free-Electron Lasers (XFELs), represents a tremendous growth in the potential to apply coherent X-rays to determine the structure of materials from the micron-scale down to the Angstrom-scale. There is a significant need for a multi-physics simulation framework to perform source-to-detector simulations for a single particle imaging experiment, including (i) the multidimensional simulation of the X-ray source; (ii) simulation of the wave-optics propagation of the coherent XFEL beams; (iii) atomistic modelling of photon-material interactions; (iv) simulation of the time-dependent diffraction process, including incoherent scattering; (v) assembling noisy and incomplete diffraction intensities into a three-dimensional data set using the Expansion-Maximisation-Compression (EMC) algorithm and (vi) phase retrieval to obtain structural information. We demonstrate the framework by simulating a single-particle experiment for a nitrogenase iron protein using parameters of the SPB/SFX instrument of the European XFEL. This exercise demonstrably yields interpretable consequences for structure determination that are crucial yet currently unavailable for experiment design. PMID:27109208

A comprehensive simulation framework for imaging single particles and biomolecules at the European X-ray Free-Electron Laser

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

Yoon, Chun Hong; Yurkov, Mikhail V.; Schneidmiller, Evgeny A.

The advent of newer, brighter, and more coherent X-ray sources, such as X-ray Free-Electron Lasers (XFELs), represents a tremendous growth in the potential to apply coherent X-rays to determine the structure of materials from the micron-scale down to the Angstrom-scale. There is a significant need for a multi-physics simulation framework to perform source-to-detector simulations for a single particle imaging experiment, including (i) the multidimensional simulation of the X-ray source; (ii) simulation of the wave-optics propagation of the coherent XFEL beams; (iii) atomistic modelling of photon-material interactions; (iv) simulation of the time-dependent diffraction process, including incoherent scattering; (v) assembling noisy andmore » incomplete diffraction intensities into a three-dimensional data set using the Expansion-Maximisation-Compression (EMC) algorithm and (vi) phase retrieval to obtain structural information. Furthermore, we demonstrate the framework by simulating a single-particle experiment for a nitrogenase iron protein using parameters of the SPB/SFX instrument of the European XFEL. This exercise demonstrably yields interpretable consequences for structure determination that are crucial yet currently unavailable for experiment design.« less

A comprehensive simulation framework for imaging single particles and biomolecules at the European X-ray Free-Electron Laser

DOE PAGES

Yoon, Chun Hong; Yurkov, Mikhail V.; Schneidmiller, Evgeny A.; ...

2016-04-25

The advent of newer, brighter, and more coherent X-ray sources, such as X-ray Free-Electron Lasers (XFELs), represents a tremendous growth in the potential to apply coherent X-rays to determine the structure of materials from the micron-scale down to the Angstrom-scale. There is a significant need for a multi-physics simulation framework to perform source-to-detector simulations for a single particle imaging experiment, including (i) the multidimensional simulation of the X-ray source; (ii) simulation of the wave-optics propagation of the coherent XFEL beams; (iii) atomistic modelling of photon-material interactions; (iv) simulation of the time-dependent diffraction process, including incoherent scattering; (v) assembling noisy andmore » incomplete diffraction intensities into a three-dimensional data set using the Expansion-Maximisation-Compression (EMC) algorithm and (vi) phase retrieval to obtain structural information. Furthermore, we demonstrate the framework by simulating a single-particle experiment for a nitrogenase iron protein using parameters of the SPB/SFX instrument of the European XFEL. This exercise demonstrably yields interpretable consequences for structure determination that are crucial yet currently unavailable for experiment design.« less