Consensus embedding: theory, algorithms and application to segmentation and classification of biomedical data

PubMed Central

2012-01-01

Background Dimensionality reduction (DR) enables the construction of a lower dimensional space (embedding) from a higher dimensional feature space while preserving object-class discriminability. However several popular DR approaches suffer from sensitivity to choice of parameters and/or presence of noise in the data. In this paper, we present a novel DR technique known as consensus embedding that aims to overcome these problems by generating and combining multiple low-dimensional embeddings, hence exploiting the variance among them in a manner similar to ensemble classifier schemes such as Bagging. We demonstrate theoretical properties of consensus embedding which show that it will result in a single stable embedding solution that preserves information more accurately as compared to any individual embedding (generated via DR schemes such as Principal Component Analysis, Graph Embedding, or Locally Linear Embedding). Intelligent sub-sampling (via mean-shift) and code parallelization are utilized to provide for an efficient implementation of the scheme. Results Applications of consensus embedding are shown in the context of classification and clustering as applied to: (1) image partitioning of white matter and gray matter on 10 different synthetic brain MRI images corrupted with 18 different combinations of noise and bias field inhomogeneity, (2) classification of 4 high-dimensional gene-expression datasets, (3) cancer detection (at a pixel-level) on 16 image slices obtained from 2 different high-resolution prostate MRI datasets. In over 200 different experiments concerning classification and segmentation of biomedical data, consensus embedding was found to consistently outperform both linear and non-linear DR methods within all applications considered. Conclusions We have presented a novel framework termed consensus embedding which leverages ensemble classification theory within dimensionality reduction, allowing for application to a wide range of high-dimensional biomedical data classification and segmentation problems. Our generalizable framework allows for improved representation and classification in the context of both imaging and non-imaging data. The algorithm offers a promising solution to problems that currently plague DR methods, and may allow for extension to other areas of biomedical data analysis. PMID:22316103

Locally Linear Embedding of Local Orthogonal Least Squares Images for Face Recognition

NASA Astrophysics Data System (ADS)

Hafizhelmi Kamaru Zaman, Fadhlan

2018-03-01

Dimensionality reduction is very important in face recognition since it ensures that high-dimensionality data can be mapped to lower dimensional space without losing salient and integral facial information. Locally Linear Embedding (LLE) has been previously used to serve this purpose, however, the process of acquiring LLE features requires high computation and resources. To overcome this limitation, we propose a locally-applied Local Orthogonal Least Squares (LOLS) model can be used as initial feature extraction before the application of LLE. By construction of least squares regression under orthogonal constraints we can preserve more discriminant information in the local subspace of facial features while reducing the overall features into a more compact form that we called LOLS images. LLE can then be applied on the LOLS images to maps its representation into a global coordinate system of much lower dimensionality. Several experiments carried out using publicly available face datasets such as AR, ORL, YaleB, and FERET under Single Sample Per Person (SSPP) constraint demonstrates that our proposed method can reduce the time required to compute LLE features while delivering better accuracy when compared to when either LLE or OLS alone is used. Comparison against several other feature extraction methods and more recent feature-learning method such as state-of-the-art Convolutional Neural Networks (CNN) also reveal the superiority of the proposed method under SSPP constraint.

Analysis of hyperspectral scattering images using locally linear embedding algorithm for apple mealiness classification

USDA-ARS?s Scientific Manuscript database

Hyperspectral scattering technique provides a means for assessing the structural and/or physical properties of apples. It could thus be useful for detection of apple mealiness, which is a symptom of physiological disorder, resulting in an undesirable texture and taste for apples and degrading their ...

Learning linear transformations between counting-based and prediction-based word embeddings

PubMed Central

Hayashi, Kohei; Kawarabayashi, Ken-ichi

2017-01-01

Despite the growing interest in prediction-based word embedding learning methods, it remains unclear as to how the vector spaces learnt by the prediction-based methods differ from that of the counting-based methods, or whether one can be transformed into the other. To study the relationship between counting-based and prediction-based embeddings, we propose a method for learning a linear transformation between two given sets of word embeddings. Our proposal contributes to the word embedding learning research in three ways: (a) we propose an efficient method to learn a linear transformation between two sets of word embeddings, (b) using the transformation learnt in (a), we empirically show that it is possible to predict distributed word embeddings for novel unseen words, and (c) empirically it is possible to linearly transform counting-based embeddings to prediction-based embeddings, for frequent words, different POS categories, and varying degrees of ambiguities. PMID:28926629

Manifolds for pose tracking from monocular video

NASA Astrophysics Data System (ADS)

Basu, Saurav; Poulin, Joshua; Acton, Scott T.

2015-03-01

We formulate a simple human-pose tracking theory from monocular video based on the fundamental relationship between changes in pose and image motion vectors. We investigate the natural embedding of the low-dimensional body pose space into a high-dimensional space of body configurations that behaves locally in a linear manner. The embedded manifold facilitates the decomposition of the image motion vectors into basis motion vector fields of the tangent space to the manifold. This approach benefits from the style invariance of image motion flow vectors, and experiments to validate the fundamental theory show reasonable accuracy (within 4.9 deg of the ground truth).

A consensus embedding approach for segmentation of high resolution in vivo prostate magnetic resonance imagery

NASA Astrophysics Data System (ADS)

Viswanath, Satish; Rosen, Mark; Madabhushi, Anant

2008-03-01

Current techniques for localization of prostatic adenocarcinoma (CaP) via blinded trans-rectal ultrasound biopsy are associated with a high false negative detection rate. While high resolution endorectal in vivo Magnetic Resonance (MR) prostate imaging has been shown to have improved contrast and resolution for CaP detection over ultrasound, similarity in intensity characteristics between benign and cancerous regions on MR images contribute to a high false positive detection rate. In this paper, we present a novel unsupervised segmentation method that employs manifold learning via consensus schemes for detection of cancerous regions from high resolution 1.5 Tesla (T) endorectal in vivo prostate MRI. A significant contribution of this paper is a method to combine multiple weak, lower-dimensional representations of high dimensional feature data in a way analogous to classifier ensemble schemes, and hence create a stable and accurate reduced dimensional representation. After correcting for MR image intensity artifacts, such as bias field inhomogeneity and intensity non-standardness, our algorithm extracts over 350 3D texture features at every spatial location in the MR scene at multiple scales and orientations. Non-linear dimensionality reduction schemes such as Locally Linear Embedding (LLE) and Graph Embedding (GE) are employed to create multiple low dimensional data representations of this high dimensional texture feature space. Our novel consensus embedding method is used to average object adjacencies from within the multiple low dimensional projections so that class relationships are preserved. Unsupervised consensus clustering is then used to partition the objects in this consensus embedding space into distinct classes. Quantitative evaluation on 18 1.5 T prostate MR data against corresponding histology obtained from the multi-site ACRIN trials show a sensitivity of 92.65% and a specificity of 82.06%, which suggests that our method is successfully able to detect suspicious regions in the prostate.

Design and implementation of non-linear image processing functions for CMOS image sensor

NASA Astrophysics Data System (ADS)

Musa, Purnawarman; Sudiro, Sunny A.; Wibowo, Eri P.; Harmanto, Suryadi; Paindavoine, Michel

2012-11-01

Today, solid state image sensors are used in many applications like in mobile phones, video surveillance systems, embedded medical imaging and industrial vision systems. These image sensors require the integration in the focal plane (or near the focal plane) of complex image processing algorithms. Such devices must meet the constraints related to the quality of acquired images, speed and performance of embedded processing, as well as low power consumption. To achieve these objectives, low-level analog processing allows extracting the useful information in the scene directly. For example, edge detection step followed by a local maxima extraction will facilitate the high-level processing like objects pattern recognition in a visual scene. Our goal was to design an intelligent image sensor prototype achieving high-speed image acquisition and non-linear image processing (like local minima and maxima calculations). For this purpose, we present in this article the design and test of a 64×64 pixels image sensor built in a standard CMOS Technology 0.35 μm including non-linear image processing. The architecture of our sensor, named nLiRIC (non-Linear Rapid Image Capture), is based on the implementation of an analog Minima/Maxima Unit. This MMU calculates the minimum and maximum values (non-linear functions), in real time, in a 2×2 pixels neighbourhood. Each MMU needs 52 transistors and the pitch of one pixel is 40×40 mu m. The total area of the 64×64 pixels is 12.5mm2. Our tests have shown the validity of the main functions of our new image sensor like fast image acquisition (10K frames per second), minima/maxima calculations in less then one ms.

One Shot Detection with Laplacian Object and Fast Matrix Cosine Similarity.

PubMed

Biswas, Sujoy Kumar; Milanfar, Peyman

2016-03-01

One shot, generic object detection involves searching for a single query object in a larger target image. Relevant approaches have benefited from features that typically model the local similarity patterns. In this paper, we combine local similarity (encoded by local descriptors) with a global context (i.e., a graph structure) of pairwise affinities among the local descriptors, embedding the query descriptors into a low dimensional but discriminatory subspace. Unlike principal components that preserve global structure of feature space, we actually seek a linear approximation to the Laplacian eigenmap that permits us a locality preserving embedding of high dimensional region descriptors. Our second contribution is an accelerated but exact computation of matrix cosine similarity as the decision rule for detection, obviating the computationally expensive sliding window search. We leverage the power of Fourier transform combined with integral image to achieve superior runtime efficiency that allows us to test multiple hypotheses (for pose estimation) within a reasonably short time. Our approach to one shot detection is training-free, and experiments on the standard data sets confirm the efficacy of our model. Besides, low computation cost of the proposed (codebook-free) object detector facilitates rather straightforward query detection in large data sets including movie videos.

Calculating hyperfine couplings in large ionic crystals containing hundreds of QM atoms: subsystem DFT is the key.

PubMed

Kevorkyants, Ruslan; Wang, Xiqiao; Close, David M; Pavanello, Michele

2013-11-14

We present an application of the linear scaling frozen density embedding (FDE) formulation of subsystem DFT to the calculation of isotropic hyperfine coupling constants (hfcc's) of atoms belonging to a guanine radical cation embedded in a guanine hydrochloride monohydrate crystal. The model systems range from an isolated guanine to a 15,000 atom QM/MM cluster where the QM region is comprised of 36 protonated guanine cations, 36 chlorine anions, and 42 water molecules. Our calculations show that the embedding effects of the surrounding crystal cannot be reproduced by small model systems nor by a pure QM/MM procedure. Instead, a large QM region is needed to fully capture the complicated nature of the embedding effects in this system. The unprecedented system size for a relativistic all-electron isotropic hfcc calculation can be approached in this work because the local nature of the electronic structure of the organic crystals considered is fully captured by the FDE approach.

Near-Edge X-ray Absorption Fine Structure within Multilevel Coupled Cluster Theory.

PubMed

Myhre, Rolf H; Coriani, Sonia; Koch, Henrik

2016-06-14

Core excited states are challenging to calculate, mainly because they are embedded in a manifold of high-energy valence-excited states. However, their locality makes their determination ideal for local correlation methods. In this paper, we demonstrate the performance of multilevel coupled cluster theory in computing core spectra both within the core-valence separated and the asymmetric Lanczos implementations of coupled cluster linear response theory. We also propose a visualization tool to analyze the excitations using the difference between the ground-state and excited-state electron densities.

A dynamic model of a cantilever beam with a closed, embedded horizontal crack including local flexibilities at crack tips

NASA Astrophysics Data System (ADS)

Liu, J.; Zhu, W. D.; Charalambides, P. G.; Shao, Y. M.; Xu, Y. F.; Fang, X. M.

2016-11-01

As one of major failure modes of mechanical structures subjected to periodic loads, embedded cracks due to fatigue can cause catastrophic failure of machineries. Understanding the dynamic characteristics of a structure with an embedded crack is helpful for early crack detection and diagnosis. In this work, a new three-segment beam model with local flexibilities at crack tips is developed to investigate the vibration of a cantilever beam with a closed, fully embedded horizontal crack, which is assumed to be not located at its clamped or free end or distributed near its top or bottom side. The three-segment beam model is assumed to be a linear elastic system, and it does not account for the nonlinear crack closure effect; the top and bottom segments always stay in contact at their interface during the beam vibration. It can model the effects of local deformations in the vicinity of the crack tips, which cannot be captured by previous methods in the literature. The middle segment of the beam containing the crack is modeled by a mechanically consistent, reduced bending moment. Each beam segment is assumed to be an Euler-Bernoulli beam, and the compliances at the crack tips are analytically determined using a J-integral approach and verified using commercial finite element software. Using compatibility conditions at the crack tips and the transfer matrix method, the nature frequencies and mode shapes of the cracked cantilever beam are obtained. The three-segment beam model is used to investigate the effects of local flexibilities at crack tips on the first three natural frequencies and mode shapes of the cracked cantilever beam. A stationary wavelet transform (SWT) method is used to process the mode shapes of the cracked cantilever beam; jumps in single-level SWT decomposition detail coefficients can be used to identify the length and location of an embedded horizontal crack.

Flow of Funds Modeling for Localized Financial Markets: An Application of Spatial Price and Allocation Activity Analysis Models.

DTIC Science & Technology

1981-01-01

on modeling the managerial aspects of the firm. The second has been the application to economic theory led by ...individual portfolio optimization problems which were embedded in a larger global optimization problem. In the global problem, portfolios were linked by market ...demand quantities or be given by linear demand relationships. As in~ the source markets , the model

Orthogonality of embedded wave functions for different states in frozen-density embedding theory

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

Zech, Alexander; Wesolowski, Tomasz A.; Aquilante, Francesco

2015-10-28

Other than lowest-energy stationary embedded wave functions obtained in Frozen-Density Embedding Theory (FDET) [T. A. Wesolowski, Phys. Rev. A 77, 012504 (2008)] can be associated with electronic excited states but they can be mutually non-orthogonal. Although this does not violate any physical principles — embedded wave functions are only auxiliary objects used to obtain stationary densities — working with orthogonal functions has many practical advantages. In the present work, we show numerically that excitation energies obtained using conventional FDET calculations (allowing for non-orthogonality) can be obtained using embedded wave functions which are strictly orthogonal. The used method preserves the mathematicalmore » structure of FDET and self-consistency between energy, embedded wave function, and the embedding potential (they are connected through the Euler-Lagrange equations). The orthogonality is built-in through the linearization in the embedded density of the relevant components of the total energy functional. Moreover, we show formally that the differences between the expectation values of the embedded Hamiltonian are equal to the excitation energies, which is the exact result within linearized FDET. Linearized FDET is shown to be a robust approximation for a large class of reference densities.« less

A Comparison of Two-Stage Approaches for Fitting Nonlinear Ordinary Differential Equation (ODE) Models with Mixed Effects

PubMed Central

Chow, Sy-Miin; Bendezú, Jason J.; Cole, Pamela M.; Ram, Nilam

2016-01-01

Several approaches currently exist for estimating the derivatives of observed data for model exploration purposes, including functional data analysis (FDA), generalized local linear approximation (GLLA), and generalized orthogonal local derivative approximation (GOLD). These derivative estimation procedures can be used in a two-stage process to fit mixed effects ordinary differential equation (ODE) models. While the performance and utility of these routines for estimating linear ODEs have been established, they have not yet been evaluated in the context of nonlinear ODEs with mixed effects. We compared properties of the GLLA and GOLD to an FDA-based two-stage approach denoted herein as functional ordinary differential equation with mixed effects (FODEmixed) in a Monte Carlo study using a nonlinear coupled oscillators model with mixed effects. Simulation results showed that overall, the FODEmixed outperformed both the GLLA and GOLD across all the embedding dimensions considered, but a novel use of a fourth-order GLLA approach combined with very high embedding dimensions yielded estimation results that almost paralleled those from the FODEmixed. We discuss the strengths and limitations of each approach and demonstrate how output from each stage of FODEmixed may be used to inform empirical modeling of young children’s self-regulation. PMID:27391255

A Comparison of Two-Stage Approaches for Fitting Nonlinear Ordinary Differential Equation Models with Mixed Effects.

PubMed

Chow, Sy-Miin; Bendezú, Jason J; Cole, Pamela M; Ram, Nilam

2016-01-01

Several approaches exist for estimating the derivatives of observed data for model exploration purposes, including functional data analysis (FDA; Ramsay & Silverman, 2005 ), generalized local linear approximation (GLLA; Boker, Deboeck, Edler, & Peel, 2010 ), and generalized orthogonal local derivative approximation (GOLD; Deboeck, 2010 ). These derivative estimation procedures can be used in a two-stage process to fit mixed effects ordinary differential equation (ODE) models. While the performance and utility of these routines for estimating linear ODEs have been established, they have not yet been evaluated in the context of nonlinear ODEs with mixed effects. We compared properties of the GLLA and GOLD to an FDA-based two-stage approach denoted herein as functional ordinary differential equation with mixed effects (FODEmixed) in a Monte Carlo (MC) study using a nonlinear coupled oscillators model with mixed effects. Simulation results showed that overall, the FODEmixed outperformed both the GLLA and GOLD across all the embedding dimensions considered, but a novel use of a fourth-order GLLA approach combined with very high embedding dimensions yielded estimation results that almost paralleled those from the FODEmixed. We discuss the strengths and limitations of each approach and demonstrate how output from each stage of FODEmixed may be used to inform empirical modeling of young children's self-regulation.

Exact density functional and wave function embedding schemes based on orbital localization

NASA Astrophysics Data System (ADS)

Hégely, Bence; Nagy, Péter R.; Ferenczy, György G.; Kállay, Mihály

2016-08-01

Exact schemes for the embedding of density functional theory (DFT) and wave function theory (WFT) methods into lower-level DFT or WFT approaches are introduced utilizing orbital localization. First, a simple modification of the projector-based embedding scheme of Manby and co-workers [J. Chem. Phys. 140, 18A507 (2014)] is proposed. We also use localized orbitals to partition the system, but instead of augmenting the Fock operator with a somewhat arbitrary level-shift projector we solve the Huzinaga-equation, which strictly enforces the Pauli exclusion principle. Second, the embedding of WFT methods in local correlation approaches is studied. Since the latter methods split up the system into local domains, very simple embedding theories can be defined if the domains of the active subsystem and the environment are treated at a different level. The considered embedding schemes are benchmarked for reaction energies and compared to quantum mechanics (QM)/molecular mechanics (MM) and vacuum embedding. We conclude that for DFT-in-DFT embedding, the Huzinaga-equation-based scheme is more efficient than the other approaches, but QM/MM or even simple vacuum embedding is still competitive in particular cases. Concerning the embedding of wave function methods, the clear winner is the embedding of WFT into low-level local correlation approaches, and WFT-in-DFT embedding can only be more advantageous if a non-hybrid density functional is employed.

A Fast Variational Approach for Learning Markov Random Field Language Models

DTIC Science & Technology

2015-01-01

the same distribution as n- gram models, but utilize a non-linear neural network pa- rameterization. NLMs have been shown to produce com- petitive...to either resort to local optimiza- tion methods, such as those used in neural lan- guage models, or work with heavily constrained distributions. In...embeddings learned through neural language models. Central to the language modelling problem is the challenge Proceedings of the 32nd International

Three dimensional quantitative characterization of magnetite nanoparticles embedded in mesoporous silicon: local curvature, demagnetizing factors and magnetic Monte Carlo simulations.

PubMed

Uusimäki, Toni; Margaris, Georgios; Trohidou, Kalliopi; Granitzer, Petra; Rumpf, Klemens; Sezen, Meltem; Kothleitner, Gerald

2013-12-07

Magnetite nanoparticles embedded within the pores of a mesoporous silicon template have been characterized using electron tomography. Linear least squares optimization was used to fit an arbitrary ellipsoid to each segmented particle from the three dimensional reconstruction. It was then possible to calculate the demagnetizing factors and the direction of the shape anisotropy easy axis for every particle. The demagnetizing factors, along with the knowledge of spatial and volume distribution of the superparamagnetic nanoparticles, were used as a model for magnetic Monte Carlo simulations, yielding zero field cooling/field cooling and magnetic hysteresis curves, which were compared to the measured ones. Additionally, the local curvature of the magnetite particles' docking site within the mesoporous silicon's surface was obtained in two different ways and a comparison will be given. A new iterative semi-automatic image alignment program was written and the importance of image segmentation for a truly objective analysis is also addressed.

Active learning for semi-supervised clustering based on locally linear propagation reconstruction.

PubMed

Chang, Chin-Chun; Lin, Po-Yi

2015-03-01

The success of semi-supervised clustering relies on the effectiveness of side information. To get effective side information, a new active learner learning pairwise constraints known as must-link and cannot-link constraints is proposed in this paper. Three novel techniques are developed for learning effective pairwise constraints. The first technique is used to identify samples less important to cluster structures. This technique makes use of a kernel version of locally linear embedding for manifold learning. Samples neither important to locally linear propagation reconstructions of other samples nor on flat patches in the learned manifold are regarded as unimportant samples. The second is a novel criterion for query selection. This criterion considers not only the importance of a sample to expanding the space coverage of the learned samples but also the expected number of queries needed to learn the sample. To facilitate semi-supervised clustering, the third technique yields inferred must-links for passing information about flat patches in the learned manifold to semi-supervised clustering algorithms. Experimental results have shown that the learned pairwise constraints can capture the underlying cluster structures and proven the feasibility of the proposed approach. Copyright © 2014 Elsevier Ltd. All rights reserved.

Estimating Extracellular Spike Waveforms from CA1 Pyramidal Cells with Multichannel Electrodes

PubMed Central

Molden, Sturla; Moldestad, Olve; Storm, Johan F.

2013-01-01

Extracellular (EC) recordings of action potentials from the intact brain are embedded in background voltage fluctuations known as the “local field potential” (LFP). In order to use EC spike recordings for studying biophysical properties of neurons, the spike waveforms must be separated from the LFP. Linear low-pass and high-pass filters are usually insufficient to separate spike waveforms from LFP, because they have overlapping frequency bands. Broad-band recordings of LFP and spikes were obtained with a 16-channel laminar electrode array (silicone probe). We developed an algorithm whereby local LFP signals from spike-containing channel were modeled using locally weighted polynomial regression analysis of adjoining channels without spikes. The modeled LFP signal was subtracted from the recording to estimate the embedded spike waveforms. We tested the method both on defined spike waveforms added to LFP recordings, and on in vivo-recorded extracellular spikes from hippocampal CA1 pyramidal cells in anaesthetized mice. We show that the algorithm can correctly extract the spike waveforms embedded in the LFP. In contrast, traditional high-pass filters failed to recover correct spike shapes, albeit produceing smaller standard errors. We found that high-pass RC or 2-pole Butterworth filters with cut-off frequencies below 12.5 Hz, are required to retrieve waveforms comparable to our method. The method was also compared to spike-triggered averages of the broad-band signal, and yielded waveforms with smaller standard errors and less distortion before and after the spike. PMID:24391714

The use of kernel local Fisher discriminant analysis for the channelization of the Hotelling model observer

NASA Astrophysics Data System (ADS)

Wen, Gezheng; Markey, Mia K.

2015-03-01

It is resource-intensive to conduct human studies for task-based assessment of medical image quality and system optimization. Thus, numerical model observers have been developed as a surrogate for human observers. The Hotelling observer (HO) is the optimal linear observer for signal-detection tasks, but the high dimensionality of imaging data results in a heavy computational burden. Channelization is often used to approximate the HO through a dimensionality reduction step, but how to produce channelized images without losing significant image information remains a key challenge. Kernel local Fisher discriminant analysis (KLFDA) uses kernel techniques to perform supervised dimensionality reduction, which finds an embedding transformation that maximizes betweenclass separability and preserves within-class local structure in the low-dimensional manifold. It is powerful for classification tasks, especially when the distribution of a class is multimodal. Such multimodality could be observed in many practical clinical tasks. For example, primary and metastatic lesions may both appear in medical imaging studies, but the distributions of their typical characteristics (e.g., size) may be very different. In this study, we propose to use KLFDA as a novel channelization method. The dimension of the embedded manifold (i.e., the result of KLFDA) is a counterpart to the number of channels in the state-of-art linear channelization. We present a simulation study to demonstrate the potential usefulness of KLFDA for building the channelized HOs (CHOs) and generating reliable decision statistics for clinical tasks. We show that the performance of the CHO with KLFDA channels is comparable to that of the benchmark CHOs.

A novel C-shaped, gold nanoparticle coated, embedded polymer waveguide for localized surface plasmon resonance based detection.

PubMed

Prabhakar, Amit; Mukherji, Soumyo

2010-12-21

In this study, a novel embedded optical waveguide based sensor which utilizes localized surface plasmon resonance of gold nanoparticles coated on a C-shaped polymer waveguide is being reported. The sensor, as designed, can be used as an analysis chip for detection of minor variations in the refractive index of its microenvironment, which makes it suitable for wide scale use as an affinity biosensor. The C-shaped waveguide coupled with microfluidic channel was fabricated by single step patterning of SU8 on an oxidized silicon wafer. The absorbance due to the localized surface plasmon resonance (LSPR) of SU8 waveguide bound gold nano particle (GNP) was found to be linear with refractive index changes between 1.33 and 1.37. A GNP coated C-bent waveguide of 200 μ width with a bend radius of 1 mm gave rise to a sensitivity of ~5 ΔA/RIU at 530 nm as compared to the ~2.5 ΔA/RIU (refractive index units) of the same dimension bare C-bend SU8 waveguide. The resolution of the sensor probe was ~2 × 10(-4) RIU.

Unsteady MHD free convection flow of casson fluid over an inclined vertical plate embedded in a porous media

NASA Astrophysics Data System (ADS)

Manideep, P.; Raju, R. Srinivasa; Rao, T. Siva Nageswar; Reddy, G. Jithender

2018-05-01

This paper deals, an unsteady magnetohydrodynamic heat transfer natural convection flow of non-Newtonian Casson fluid over an inclined vertical plate embedded in a porous media with the presence of boundary conditions such as oscillating velocity, constant wall temperature. The governing dimensionless boundary layer partial differential equations are reduced to simultaneous algebraic linear equation for velocity, temperature of Casson fluid through finite element method. Those equations are solved by Thomas algorithm after imposing the boundary conditions through MATLAB for analyzing the behavior of Casson fluid velocity and temperature with various physical parameters. Also analyzed the local skin-friction and rate of heat transfer. Compared the present results with earlier reported studies, the results are comprehensively authenticated and robust FEM.

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

Hégely, Bence; Nagy, Péter R.; Kállay, Mihály, E-mail: kallay@mail.bme.hu

Exact schemes for the embedding of density functional theory (DFT) and wave function theory (WFT) methods into lower-level DFT or WFT approaches are introduced utilizing orbital localization. First, a simple modification of the projector-based embedding scheme of Manby and co-workers [J. Chem. Phys. 140, 18A507 (2014)] is proposed. We also use localized orbitals to partition the system, but instead of augmenting the Fock operator with a somewhat arbitrary level-shift projector we solve the Huzinaga-equation, which strictly enforces the Pauli exclusion principle. Second, the embedding of WFT methods in local correlation approaches is studied. Since the latter methods split up themore » system into local domains, very simple embedding theories can be defined if the domains of the active subsystem and the environment are treated at a different level. The considered embedding schemes are benchmarked for reaction energies and compared to quantum mechanics (QM)/molecular mechanics (MM) and vacuum embedding. We conclude that for DFT-in-DFT embedding, the Huzinaga-equation-based scheme is more efficient than the other approaches, but QM/MM or even simple vacuum embedding is still competitive in particular cases. Concerning the embedding of wave function methods, the clear winner is the embedding of WFT into low-level local correlation approaches, and WFT-in-DFT embedding can only be more advantageous if a non-hybrid density functional is employed.« less

Self-Avoiding Walks Over Adaptive Triangular Grids

NASA Technical Reports Server (NTRS)

Heber, Gerd; Biswas, Rupak; Gao, Guang R.; Saini, Subhash (Technical Monitor)

1999-01-01

Space-filling curves is a popular approach based on a geometric embedding for linearizing computational meshes. We present a new O(n log n) combinatorial algorithm for constructing a self avoiding walk through a two dimensional mesh containing n triangles. We show that for hierarchical adaptive meshes, the algorithm can be locally adapted and easily parallelized by taking advantage of the regularity of the refinement rules. The proposed approach should be very useful in the runtime partitioning and load balancing of adaptive unstructured grids.

Enhancement of spin polarization induced by Coulomb on-site repulsion between localized pz electrons in graphene embedded with line defects.

PubMed

Ren, Ji-Chang; Wang, Zhigang; Zhang, Rui-Qin; Ding, Zejun; Van Hove, Michel A

2015-11-11

It is well known that the effect of Coulomb on-site repulsion can significantly alter the physical properties of the systems that contain localized d and/or f electrons. However, little attention has been paid to the Coulomb on-site repulsion between localized p electrons. In this study, we demonstrated that Coulomb on-site repulsion between localized pz electrons also plays an important role in graphene embedded with line defects. It is shown that the magnetism of the system largely depends on the choice of the effective Coulomb on-site parameter Ueff. Ueff at the edges of the defect enhances the exchange splitting, which increases the magnetic moment and stabilizes a ferromagnetic state of the system. In contrast, Ueff at the center of the defect weakens the spin polarization of the system. The behavior of the magnetism is explained with the Stoner criterion and the charge accumulation at the edges of the defect. Based on the linear response approach, we estimate reasonable values of Ueff to be 2.55 eV (2.3 eV) at the center (edges) of the defects. More importantly, using a DFT+U+J method, we find that exchange interactions between localized p electrons also play an important role in the spin polarization of the system. These results imply that Coulomb on-site repulsion is necessary to describe the strong interaction between localized pz electrons of carbon related materials.

Subjective audio quality evaluation of embedded-optimization-based distortion precompensation algorithms.

PubMed

Defraene, Bruno; van Waterschoot, Toon; Diehl, Moritz; Moonen, Marc

2016-07-01

Subjective audio quality evaluation experiments have been conducted to assess the performance of embedded-optimization-based precompensation algorithms for mitigating perceptible linear and nonlinear distortion in audio signals. It is concluded with statistical significance that the perceived audio quality is improved by applying an embedded-optimization-based precompensation algorithm, both in case (i) nonlinear distortion and (ii) a combination of linear and nonlinear distortion is present. Moreover, a significant positive correlation is reported between the collected subjective and objective PEAQ audio quality scores, supporting the validity of using PEAQ to predict the impact of linear and nonlinear distortion on the perceived audio quality.

A family of four stages embedded explicit six-step methods with eliminated phase-lag and its derivatives for the numerical solution of the second order problems

NASA Astrophysics Data System (ADS)

Simos, T. E.

2017-11-01

A family of four stages high algebraic order embedded explicit six-step methods, for the numerical solution of second order initial or boundary-value problems with periodical and/or oscillating solutions, are studied in this paper. The free parameters of the new proposed methods are calculated solving the linear system of equations which is produced by requesting the vanishing of the phase-lag of the methods and the vanishing of the phase-lag's derivatives of the schemes. For the new obtained methods we investigate: • Its local truncation error (LTE) of the methods.• The asymptotic form of the LTE obtained using as model problem the radial Schrödinger equation.• The comparison of the asymptotic forms of LTEs for several methods of the same family. This comparison leads to conclusions on the efficiency of each method of the family.• The stability and the interval of periodicity of the obtained methods of the new family of embedded finite difference pairs.• The applications of the new obtained family of embedded finite difference pairs to the numerical solution of several second order problems like the radial Schrödinger equation, astronomical problems etc. The above applications lead to conclusion on the efficiency of the methods of the new family of embedded finite difference pairs.

Structural control of nonlinear optical absorption and refraction in dense metal nanoparticle arrays.

PubMed

Kohlgraf-Owens, Dana C; Kik, Pieter G

2009-08-17

The linear and nonlinear optical properties of a composite containing interacting spherical silver nanoparticles embedded in a dielectric host are studied as a function of interparticle separation using three dimensional frequency domain simulations. It is shown that for a fixed amount of metal, the effective third-order nonlinear susceptibility of the composite chi((3))(omega) can be significantly enhanced with respect to the linear optical properties, due to a combination of resonant surface plasmon excitation and local field redistribution. It is shown that this geometry-dependent susceptibility enhancement can lead to an improved figure of merit for nonlinear absorption. Enhancement factors for the nonlinear susceptibility of the composite are calculated, and the complex nature of the enhancement factors is discussed.

Localized attacks on spatially embedded networks with dependencies.

PubMed

Berezin, Yehiel; Bashan, Amir; Danziger, Michael M; Li, Daqing; Havlin, Shlomo

2015-03-11

Many real world complex systems such as critical infrastructure networks are embedded in space and their components may depend on one another to function. They are also susceptible to geographically localized damage caused by malicious attacks or natural disasters. Here, we study a general model of spatially embedded networks with dependencies under localized attacks. We develop a theoretical and numerical approach to describe and predict the effects of localized attacks on spatially embedded systems with dependencies. Surprisingly, we find that a localized attack can cause substantially more damage than an equivalent random attack. Furthermore, we find that for a broad range of parameters, systems which appear stable are in fact metastable. Though robust to random failures-even of finite fraction-if subjected to a localized attack larger than a critical size which is independent of the system size (i.e., a zero fraction), a cascading failure emerges which leads to complete system collapse. Our results demonstrate the potential high risk of localized attacks on spatially embedded network systems with dependencies and may be useful for designing more resilient systems.

Linearly polarized emission from an embedded quantum dot using nanowire morphology control.

PubMed

Foster, Andrew P; Bradley, John P; Gardner, Kirsty; Krysa, Andrey B; Royall, Ben; Skolnick, Maurice S; Wilson, Luke R

2015-03-11

GaAs nanowires with elongated cross sections are formed using a catalyst-free growth technique. This is achieved by patterning elongated nanoscale openings within a silicon dioxide growth mask on a (111)B GaAs substrate. It is observed that MOVPE-grown vertical nanowires with cross section elongated in the [21̅1̅] and [1̅12] directions remain faithful to the geometry of the openings. An InGaAs quantum dot with weak radial confinement is realized within each nanowire by briefly introducing indium into the reactor during nanowire growth. Photoluminescence emission from an embedded nanowire quantum dot is strongly linearly polarized (typically >90%) with the polarization direction coincident with the axis of elongation. Linearly polarized PL emission is a result of embedding the quantum dot in an anisotropic nanowire structure that supports a single strongly confined, linearly polarized optical mode. This research provides a route to the bottom-up growth of linearly polarized single photon sources of interest for quantum information applications.

Ionic Driven Embedment of Hyaluronic Acid Coated Liposomes in Polyelectrolyte Multilayer Films for Local Therapeutic Delivery

NASA Astrophysics Data System (ADS)

Hayward, Stephen L.; Francis, David M.; Sis, Matthew J.; Kidambi, Srivatsan

2015-10-01

The ability to control the spatial distribution and temporal release of a therapeutic remains a central challenge for biomedical research. Here, we report the development and optimization of a novel substrate mediated therapeutic delivery system comprising of hyaluronic acid covalently functionalized liposomes (HALNPs) embedded into polyelectrolyte multilayer (PEM) platform via ionic stabilization. The PEM platform was constructed from sequential deposition of Poly-L-Lysine (PLL) and Poly(Sodium styrene sulfonate) (SPS) “(PLL/SPS)4.5” followed by adsorption of anionic HALNPs. An adsorption affinity assay and saturation curve illustrated the preferential HALNP deposition density for precise therapeutic loading. (PLL/SPS)2.5 capping layer on top of the deposited HALNP monolayer further facilitated complete nanoparticle immobilization, cell adhesion, and provided nanoparticle confinement for controlled linear release profiles of the nanocarrier and encapsulated cargo. To our knowledge, this is the first study to demonstrate the successful embedment of a translatable lipid based nanocarrier into a substrate that allows for temporal and spatial release of both hydrophobic and hydrophilic drugs. Specifically, we have utilized our platform to deliver chemotherapeutic drug Doxorubicin from PEM confined HALNPs. Overall, we believe the development of our HALNP embedded PEM system is significant and will catalyze the usage of substrate mediated delivery platforms in biomedical applications.

Embedding of multidimensional time-dependent observations.

PubMed

Barnard, J P; Aldrich, C; Gerber, M

2001-10-01

A method is proposed to reconstruct dynamic attractors by embedding of multivariate observations of dynamic nonlinear processes. The Takens embedding theory is combined with independent component analysis to transform the embedding into a vector space of linearly independent vectors (phase variables). The method is successfully tested against prediction of the unembedded state vector in two case studies of simulated chaotic processes.

Embedding of multidimensional time-dependent observations

NASA Astrophysics Data System (ADS)

Barnard, Jakobus P.; Aldrich, Chris; Gerber, Marius

2001-10-01

A method is proposed to reconstruct dynamic attractors by embedding of multivariate observations of dynamic nonlinear processes. The Takens embedding theory is combined with independent component analysis to transform the embedding into a vector space of linearly independent vectors (phase variables). The method is successfully tested against prediction of the unembedded state vector in two case studies of simulated chaotic processes.

Image segmentation-based robust feature extraction for color image watermarking

NASA Astrophysics Data System (ADS)

Li, Mianjie; Deng, Zeyu; Yuan, Xiaochen

2018-04-01

This paper proposes a local digital image watermarking method based on Robust Feature Extraction. The segmentation is achieved by Simple Linear Iterative Clustering (SLIC) based on which an Image Segmentation-based Robust Feature Extraction (ISRFE) method is proposed for feature extraction. Our method can adaptively extract feature regions from the blocks segmented by SLIC. This novel method can extract the most robust feature region in every segmented image. Each feature region is decomposed into low-frequency domain and high-frequency domain by Discrete Cosine Transform (DCT). Watermark images are then embedded into the coefficients in the low-frequency domain. The Distortion-Compensated Dither Modulation (DC-DM) algorithm is chosen as the quantization method for embedding. The experimental results indicate that the method has good performance under various attacks. Furthermore, the proposed method can obtain a trade-off between high robustness and good image quality.

A framework for optimal kernel-based manifold embedding of medical image data.

PubMed

Zimmer, Veronika A; Lekadir, Karim; Hoogendoorn, Corné; Frangi, Alejandro F; Piella, Gemma

2015-04-01

Kernel-based dimensionality reduction is a widely used technique in medical image analysis. To fully unravel the underlying nonlinear manifold the selection of an adequate kernel function and of its free parameters is critical. In practice, however, the kernel function is generally chosen as Gaussian or polynomial and such standard kernels might not always be optimal for a given image dataset or application. In this paper, we present a study on the effect of the kernel functions in nonlinear manifold embedding of medical image data. To this end, we first carry out a literature review on existing advanced kernels developed in the statistics, machine learning, and signal processing communities. In addition, we implement kernel-based formulations of well-known nonlinear dimensional reduction techniques such as Isomap and Locally Linear Embedding, thus obtaining a unified framework for manifold embedding using kernels. Subsequently, we present a method to automatically choose a kernel function and its associated parameters from a pool of kernel candidates, with the aim to generate the most optimal manifold embeddings. Furthermore, we show how the calculated selection measures can be extended to take into account the spatial relationships in images, or used to combine several kernels to further improve the embedding results. Experiments are then carried out on various synthetic and phantom datasets for numerical assessment of the methods. Furthermore, the workflow is applied to real data that include brain manifolds and multispectral images to demonstrate the importance of the kernel selection in the analysis of high-dimensional medical images. Copyright © 2014 Elsevier Ltd. All rights reserved.

Unsupervised MRI segmentation of brain tissues using a local linear model and level set.

PubMed

Rivest-Hénault, David; Cheriet, Mohamed

2011-02-01

Real-world magnetic resonance imaging of the brain is affected by intensity nonuniformity (INU) phenomena which makes it difficult to fully automate the segmentation process. This difficult task is accomplished in this work by using a new method with two original features: (1) each brain tissue class is locally modeled using a local linear region representative, which allows us to account for the INU in an implicit way and to more accurately position the region's boundaries; and (2) the region models are embedded in the level set framework, so that the spatial coherence of the segmentation can be controlled in a natural way. Our new method has been tested on the ground-truthed Internet Brain Segmentation Repository (IBSR) database and gave promising results, with Tanimoto indexes ranging from 0.61 to 0.79 for the classification of the white matter and from 0.72 to 0.84 for the gray matter. To our knowledge, this is the first time a region-based level set model has been used to perform the segmentation of real-world MRI brain scans with convincing results. Copyright © 2011 Elsevier Inc. All rights reserved.

H.264/AVC digital fingerprinting based on spatio-temporal just noticeable distortion

NASA Astrophysics Data System (ADS)

Ait Saadi, Karima; Bouridane, Ahmed; Guessoum, Abderrezak

2014-01-01

This paper presents a robust adaptive embedding scheme using a modified Spatio-Temporal noticeable distortion (JND) model that is designed for tracing the distribution of the H.264/AVC video content and protecting them from unauthorized redistribution. The Embedding process is performed during coding process in selected macroblocks type Intra 4x4 within I-Frame. The method uses spread-spectrum technique in order to obtain robustness against collusion attacks and the JND model to dynamically adjust the embedding strength and control the energy of the embedded fingerprints so as to ensure their imperceptibility. Linear and non linear collusion attacks are performed to show the robustness of the proposed technique against collusion attacks while maintaining visual quality unchanged.

QuEST: Robust Quantum Gadgets

DTIC Science & Technology

2013-02-28

the size of the entangled states. Publications for 2011-12: S . T. Flammia , A. W. Harrow and J. Shi. “Local Embeddings of Quantum Codes” in...Publications (published) during reporting period: S . T. Flammia , A. W. Harrow and J. Shi. "Local Embeddings of Quantum Codes," in preparation, 2013. A. W...Publications: S . T. Flammia , A. W. Harrow and J. Shi. "Local Embeddings of Quantum Codes," in preparation, 2013. A. W. Harrow. "Testing Entanglement

Embedded promotions in online services: how goal-relevance ambiguity shapes response and affect.

PubMed

Brasel, S Adam

2010-09-01

Adding promotions to online services is increasingly commonplace, yet consumers may have difficulty determining whether service-embedded promotions are goal-relevant, due to the linear and transactional nature of online services. This contextual effect of goal-relevance ambiguity on promotions is explored across three studies. An exploratory study utilizing actual service websites and a broad range of consumers as participants showed promotional elements in online services generated considerable confusion, and instructions labeling promotions as optional did little to relieve goal-relevance ambiguity. A second study using student participants inserted promotions into an online airline ticket service, a shopping site, a local news blog, and a news headline aggregator, to explore how linear and transactional sites such as online services compared to more exploratory or informational online environments. Results showed that service-embedded promotions enjoyed initial compliance far beyond promotions in traditional websites but also generated increased confusion, frustration, and anger. A third study utilizing student participants explored how varying levels of online service experience created differing responses to promotions in services; novices were less able to judge promotional goal-relevance and experienced more confusion, whereas experienced searchers were more likely to respond with frustration and anger. Many participants complied with promotional offers at the time of the service transaction, but stated intentions to use the promotion postservice were very low. The overall results spotlight goal-relevance ambiguity as an important driver of consumer response to online promotions, and highlight the role website context can play in the processing of online promotional elements. PsycINFO Database Record (c) 2010 APA, all rights reserved.

Streamflow Prediction based on Chaos Theory

NASA Astrophysics Data System (ADS)

Li, X.; Wang, X.; Babovic, V. M.

2015-12-01

Chaos theory is a popular method in hydrologic time series prediction. Local model (LM) based on this theory utilizes time-delay embedding to reconstruct the phase-space diagram. For this method, its efficacy is dependent on the embedding parameters, i.e. embedding dimension, time lag, and nearest neighbor number. The optimal estimation of these parameters is thus critical to the application of Local model. However, these embedding parameters are conventionally estimated using Average Mutual Information (AMI) and False Nearest Neighbors (FNN) separately. This may leads to local optimization and thus has limitation to its prediction accuracy. Considering about these limitation, this paper applies a local model combined with simulated annealing (SA) to find the global optimization of embedding parameters. It is also compared with another global optimization approach of Genetic Algorithm (GA). These proposed hybrid methods are applied in daily and monthly streamflow time series for examination. The results show that global optimization can contribute to the local model to provide more accurate prediction results compared with local optimization. The LM combined with SA shows more advantages in terms of its computational efficiency. The proposed scheme here can also be applied to other fields such as prediction of hydro-climatic time series, error correction, etc.

Positron confinement in embedded lithium nanoclusters

NASA Astrophysics Data System (ADS)

van Huis, M. A.; van Veen, A.; Schut, H.; Falub, C. V.; Eijt, S. W.; Mijnarends, P. E.; Kuriplach, J.

2002-02-01

Quantum confinement of positrons in nanoclusters offers the opportunity to obtain detailed information on the electronic structure of nanoclusters by application of positron annihilation spectroscopy techniques. In this work, positron confinement is investigated in lithium nanoclusters embedded in monocrystalline MgO. These nanoclusters were created by means of ion implantation and subsequent annealing. It was found from the results of Doppler broadening positron beam analysis that approximately 92% of the implanted positrons annihilate in lithium nanoclusters rather than in the embedding MgO, while the local fraction of lithium at the implantation depth is only 1.3 at. %. The results of two-dimensional angular correlation of annihilation radiation confirm the presence of crystalline bulk lithium. The confinement of positrons is ascribed to the difference in positron affinity between lithium and MgO. The nanocluster acts as a potential well for positrons, where the depth of the potential well is equal to the difference in the positron affinities of lithium and MgO. These affinities were calculated using the linear muffin-tin orbital atomic sphere approximation method. This yields a positronic potential step at the MgO||Li interface of 1.8 eV using the generalized gradient approximation and 2.8 eV using the insulator model.

Effect of off-fault low-velocity elastic inclusions on supershear rupture dynamics

NASA Astrophysics Data System (ADS)

Ma, Xiao; Elbanna, A. E.

2015-10-01

Heterogeneous velocity structures are expected to affect fault rupture dynamics. To quantitatively evaluate some of these effects, we examine a model of dynamic rupture on a frictional fault embedded in an elastic full space, governed by plane strain elasticity, with a pair of off-fault inclusions that have a lower rigidity than the background medium. We solve the elastodynamic problem using the Finite Element software Pylith. The fault operates under linear slip-weakening friction law. We initiate the rupture by artificially overstressing a localized region near the left edge of the fault. We primarily consider embedded soft inclusions with 20 per cent reduction in both the pressure wave and shear wave speeds. The embedded inclusions are placed at different distances from the fault surface and have different sizes. We show that the existence of a soft inclusion may significantly shorten the transition length to supershear propagation through the Burridge-Andrews mechanism. We also observe that supershear rupture is generated at pre-stress values that are lower than what is theoretically predicted for a homogeneous medium. We discuss the implications of our results for dynamic rupture propagation in complex velocity structures as well as supershear propagation on understressed faults.

Signal separation by nonlinear projections: The fetal electrocardiogram

NASA Astrophysics Data System (ADS)

Schreiber, Thomas; Kaplan, Daniel T.

1996-05-01

We apply a locally linear projection technique which has been developed for noise reduction in deterministically chaotic signals to extract the fetal component from scalar maternal electrocardiographic (ECG) recordings. Although we do not expect the maternal ECG to be deterministic chaotic, typical signals are effectively confined to a lower-dimensional manifold when embedded in delay space. The method is capable of extracting fetal heart rate even when the fetal component and the noise are of comparable amplitude. If the noise is small, more details of the fetal ECG, like P and T waves, can be recovered.

Computer-aided linear-circuit design.

NASA Technical Reports Server (NTRS)

Penfield, P.

1971-01-01

Usually computer-aided design (CAD) refers to programs that analyze circuits conceived by the circuit designer. Among the services such programs should perform are direct network synthesis, analysis, optimization of network parameters, formatting, storage of miscellaneous data, and related calculations. The program should be embedded in a general-purpose conversational language such as BASIC, JOSS, or APL. Such a program is MARTHA, a general-purpose linear-circuit analyzer embedded in APL.

An accurate and linear-scaling method for calculating charge-transfer excitation energies and diabatic couplings

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

Pavanello, Michele; Van Voorhis, Troy; Visscher, Lucas

2013-02-07

Quantum-mechanical methods that are both computationally fast and accurate are not yet available for electronic excitations having charge transfer character. In this work, we present a significant step forward towards this goal for those charge transfer excitations that take place between non-covalently bound molecules. In particular, we present a method that scales linearly with the number of non-covalently bound molecules in the system and is based on a two-pronged approach: The molecular electronic structure of broken-symmetry charge-localized states is obtained with the frozen density embedding formulation of subsystem density-functional theory; subsequently, in a post-SCF calculation, the full-electron Hamiltonian and overlapmore » matrix elements among the charge-localized states are evaluated with an algorithm which takes full advantage of the subsystem DFT density partitioning technique. The method is benchmarked against coupled-cluster calculations and achieves chemical accuracy for the systems considered for intermolecular separations ranging from hydrogen-bond distances to tens of Angstroms. Numerical examples are provided for molecular clusters comprised of up to 56 non-covalently bound molecules.« less

An accurate and linear-scaling method for calculating charge-transfer excitation energies and diabatic couplings.

PubMed

Pavanello, Michele; Van Voorhis, Troy; Visscher, Lucas; Neugebauer, Johannes

2013-02-07

Quantum-mechanical methods that are both computationally fast and accurate are not yet available for electronic excitations having charge transfer character. In this work, we present a significant step forward towards this goal for those charge transfer excitations that take place between non-covalently bound molecules. In particular, we present a method that scales linearly with the number of non-covalently bound molecules in the system and is based on a two-pronged approach: The molecular electronic structure of broken-symmetry charge-localized states is obtained with the frozen density embedding formulation of subsystem density-functional theory; subsequently, in a post-SCF calculation, the full-electron Hamiltonian and overlap matrix elements among the charge-localized states are evaluated with an algorithm which takes full advantage of the subsystem DFT density partitioning technique. The method is benchmarked against coupled-cluster calculations and achieves chemical accuracy for the systems considered for intermolecular separations ranging from hydrogen-bond distances to tens of Ångstroms. Numerical examples are provided for molecular clusters comprised of up to 56 non-covalently bound molecules.

Comparative analysis of nonlinear dimensionality reduction techniques for breast MRI segmentation

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

Akhbardeh, Alireza; Jacobs, Michael A.; Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205

2012-04-15

Purpose: Visualization of anatomical structures using radiological imaging methods is an important tool in medicine to differentiate normal from pathological tissue and can generate large amounts of data for a radiologist to read. Integrating these large data sets is difficult and time-consuming. A new approach uses both supervised and unsupervised advanced machine learning techniques to visualize and segment radiological data. This study describes the application of a novel hybrid scheme, based on combining wavelet transform and nonlinear dimensionality reduction (NLDR) methods, to breast magnetic resonance imaging (MRI) data using three well-established NLDR techniques, namely, ISOMAP, local linear embedding (LLE), andmore » diffusion maps (DfM), to perform a comparative performance analysis. Methods: Twenty-five breast lesion subjects were scanned using a 3T scanner. MRI sequences used were T1-weighted, T2-weighted, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) imaging. The hybrid scheme consisted of two steps: preprocessing and postprocessing of the data. The preprocessing step was applied for B{sub 1} inhomogeneity correction, image registration, and wavelet-based image compression to match and denoise the data. In the postprocessing step, MRI parameters were considered data dimensions and the NLDR-based hybrid approach was applied to integrate the MRI parameters into a single image, termed the embedded image. This was achieved by mapping all pixel intensities from the higher dimension to a lower dimensional (embedded) space. For validation, the authors compared the hybrid NLDR with linear methods of principal component analysis (PCA) and multidimensional scaling (MDS) using synthetic data. For the clinical application, the authors used breast MRI data, comparison was performed using the postcontrast DCE MRI image and evaluating the congruence of the segmented lesions. Results: The NLDR-based hybrid approach was able to define and segment both synthetic and clinical data. In the synthetic data, the authors demonstrated the performance of the NLDR method compared with conventional linear DR methods. The NLDR approach enabled successful segmentation of the structures, whereas, in most cases, PCA and MDS failed. The NLDR approach was able to segment different breast tissue types with a high accuracy and the embedded image of the breast MRI data demonstrated fuzzy boundaries between the different types of breast tissue, i.e., fatty, glandular, and tissue with lesions (>86%). Conclusions: The proposed hybrid NLDR methods were able to segment clinical breast data with a high accuracy and construct an embedded image that visualized the contribution of different radiological parameters.« less

Identification of temporal variations in mental workload using locally-linear-embedding-based EEG feature reduction and support-vector-machine-based clustering and classification techniques.

PubMed

Yin, Zhong; Zhang, Jianhua

2014-07-01

Identifying the abnormal changes of mental workload (MWL) over time is quite crucial for preventing the accidents due to cognitive overload and inattention of human operators in safety-critical human-machine systems. It is known that various neuroimaging technologies can be used to identify the MWL variations. In order to classify MWL into a few discrete levels using representative MWL indicators and small-sized training samples, a novel EEG-based approach by combining locally linear embedding (LLE), support vector clustering (SVC) and support vector data description (SVDD) techniques is proposed and evaluated by using the experimentally measured data. The MWL indicators from different cortical regions are first elicited by using the LLE technique. Then, the SVC approach is used to find the clusters of these MWL indicators and thereby to detect MWL variations. It is shown that the clusters can be interpreted as the binary class MWL. Furthermore, a trained binary SVDD classifier is shown to be capable of detecting slight variations of those indicators. By combining the two schemes, a SVC-SVDD framework is proposed, where the clear-cut (smaller) cluster is detected by SVC first and then a subsequent SVDD model is utilized to divide the overlapped (larger) cluster into two classes. Finally, three-class MWL levels (low, normal and high) can be identified automatically. The experimental data analysis results are compared with those of several existing methods. It has been demonstrated that the proposed framework can lead to acceptable computational accuracy and has the advantages of both unsupervised and supervised training strategies. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Conserved Quantities in General Relativity: From the Quasi-Local Level to Spatial Infinity

NASA Astrophysics Data System (ADS)

Chen, Po-Ning; Wang, Mu-Tao; Yau, Shing-Tung

2015-08-01

We define quasi-local conserved quantities in general relativity by using the optimal isometric embedding in Wang and Yau (Commun Math Phys 288(3):919-942, 2009) to transplant Killing fields in the Minkowski spacetime back to the 2-surface of interest in a physical spacetime. To each optimal isometric embedding, a dual element of the Lie algebra of the Lorentz group is assigned. Quasi-local angular momentum and quasi-local center of mass correspond to pairing this element with rotation Killing fields and boost Killing fields, respectively. They obey classical transformation laws under the action of the Poincaré group. We further justify these definitions by considering their limits as the total angular momentum and the total center of mass of an isolated system. These expressions were derived from the Hamilton-Jacobi analysis of the gravitational action and thus satisfy conservation laws. As a result, we obtained an invariant total angular momentum theorem in the Kerr spacetime. For a vacuum asymptotically flat initial data set of order 1, it is shown that the limits are always finite without any extra assumptions. We also study these total conserved quantities on a family of asymptotically flat initial data sets evolving by the vacuum Einstein evolution equation. It is shown that the total angular momentum is conserved under the evolution. For the total center of mass, the classical dynamical formula relating the center of mass, energy, and linear momentum is recovered, in the nonlinear context of initial data sets evolving by the vacuum Einstein evolution equation. The definition of quasi-local angular momentum provides an answer to the second problem in classical general relativity on Penrose's list (Proc R Soc Lond Ser A 381(1780):53-63, 1982).

Multilinear Graph Embedding: Representation and Regularization for Images.

PubMed

Chen, Yi-Lei; Hsu, Chiou-Ting

2014-02-01

Given a set of images, finding a compact and discriminative representation is still a big challenge especially when multiple latent factors are hidden in the way of data generation. To represent multifactor images, although multilinear models are widely used to parameterize the data, most methods are based on high-order singular value decomposition (HOSVD), which preserves global statistics but interprets local variations inadequately. To this end, we propose a novel method, called multilinear graph embedding (MGE), as well as its kernelization MKGE to leverage the manifold learning techniques into multilinear models. Our method theoretically links the linear, nonlinear, and multilinear dimensionality reduction. We also show that the supervised MGE encodes informative image priors for image regularization, provided that an image is represented as a high-order tensor. From our experiments on face and gait recognition, the superior performance demonstrates that MGE better represents multifactor images than classic methods, including HOSVD and its variants. In addition, the significant improvement in image (or tensor) completion validates the potential of MGE for image regularization.

Spectral Regression Discriminant Analysis for Hyperspectral Image Classification

NASA Astrophysics Data System (ADS)

Pan, Y.; Wu, J.; Huang, H.; Liu, J.

2012-08-01

Dimensionality reduction algorithms, which aim to select a small set of efficient and discriminant features, have attracted great attention for Hyperspectral Image Classification. The manifold learning methods are popular for dimensionality reduction, such as Locally Linear Embedding, Isomap, and Laplacian Eigenmap. However, a disadvantage of many manifold learning methods is that their computations usually involve eigen-decomposition of dense matrices which is expensive in both time and memory. In this paper, we introduce a new dimensionality reduction method, called Spectral Regression Discriminant Analysis (SRDA). SRDA casts the problem of learning an embedding function into a regression framework, which avoids eigen-decomposition of dense matrices. Also, with the regression based framework, different kinds of regularizes can be naturally incorporated into our algorithm which makes it more flexible. It can make efficient use of data points to discover the intrinsic discriminant structure in the data. Experimental results on Washington DC Mall and AVIRIS Indian Pines hyperspectral data sets demonstrate the effectiveness of the proposed method.

Uncovering Droop Control Laws Embedded Within the Nonlinear Dynamics of Van der Pol Oscillators

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

Sinha, Mohit; Dorfler, Florian; Johnson, Brian B.

This paper examines the dynamics of power-electronic inverters in islanded microgrids that are controlled to emulate the dynamics of Van der Pol oscillators. The general strategy of controlling inverters to emulate the behavior of nonlinear oscillators presents a compelling time-domain alternative to ubiquitous droop control methods which presume the existence of a quasistationary sinusoidal steady state and operate on phasor quantities. We present two main results in this paper. First, by leveraging the method of periodic averaging, we demonstrate that droop laws are intrinsically embedded within a slower time scale in the nonlinear dynamics of Van der Pol oscillators. Second,more » we establish the global convergence of amplitude and phase dynamics in a resistive network interconnecting inverters controlled as Van der Pol oscillators. Furthermore, under a set of nonrestrictive decoupling approximations, we derive sufficient conditions for local exponential stability of desirable equilibria of the linearized amplitude and phase dynamics.« less

Application of Microrheology in Food Science.

PubMed

Yang, Nan; Lv, Ruihe; Jia, Junji; Nishinari, Katsuyoshi; Fang, Yapeng

2017-02-28

Microrheology provides a technique to probe the local viscoelastic properties and dynamics of soft materials at the microscopic level by observing the motion of tracer particles embedded within them. It is divided into passive and active microrheology according to the force exerted on the embedded particles. Particles are driven by thermal fluctuations in passive microrheology, and the linear viscoelasticity of samples can be obtained on the basis of the generalized Stokes-Einstein equation. In active microrheology, tracer particles are controlled by external forces, and measurements can be extended to the nonlinear regime. Microrheology techniques have many advantages such as the need for only small sample amounts and a wider measurable frequency range. In particular, microrheology is able to examine the spatial heterogeneity of samples at the microlevel, which is not possible using traditional rheology. Therefore, microrheology has considerable potential for studying the local mechanical properties and dynamics of soft matter, particularly complex fluids, including solutions, dispersions, and other colloidal systems. Food products such as emulsions, foams, or gels are complex fluids with multiple ingredients and phases. Their macroscopic properties, such as stability and texture, are closely related to the structure and mechanical properties at the microlevel. In this article, the basic principles and methods of microrheology are reviewed, and the latest developments and achievements of microrheology in the field of food science are presented.

Forecasting Geomagnetic Activity Using Kalman Filters

NASA Astrophysics Data System (ADS)

Veeramani, T.; Sharma, A.

2006-05-01

The coupling of energy from the solar wind to the magnetosphere leads to the geomagnetic activity in the form of storms and substorms and are characterized by indices such as AL, Dst and Kp. The geomagnetic activity has been predicted near-real time using local linear filter models of the system dynamics wherein the time series of the input solar wind and the output magnetospheric response were used to reconstruct the phase space of the system by a time-delay embedding technique. Recently, the radiation belt dynamics have been studied using a adaptive linear state space model [Rigler et al. 2004]. This was achieved by assuming a linear autoregressive equation for the underlying process and an adaptive identification of the model parameters using a Kalman filter approach. We use such a model for predicting the geomagnetic activity. In the case of substorms, the Bargatze et al [1985] data set yields persistence like behaviour when a time resolution of 2.5 minutes was used to test the model for the prediction of the AL index. Unlike the local linear filters, which are driven by the solar wind input without feedback from the observations, the Kalman filter makes use of the observations as and when available to optimally update the model parameters. The update procedure requires the prediction intervals to be long enough so that the forecasts can be used in practice. The time resolution of the data suitable for such forecasting is studied by taking averages over different durations.

Virtual network embedding in cross-domain network based on topology and resource attributes

NASA Astrophysics Data System (ADS)

Zhu, Lei; Zhang, Zhizhong; Feng, Linlin; Liu, Lilan

2018-03-01

Aiming at the network architecture ossification and the diversity of access technologies issues, this paper researches the cross-domain virtual network embedding algorithm. By analysing the topological attribute from the local and global perspective of nodes in the virtual network and the physical network, combined with the local network resource property, we rank the embedding priority of the nodes with PCA and TOPSIS methods. Besides, the link load distribution is considered. Above all, We proposed an cross-domain virtual network embedding algorithm based on topology and resource attributes. The simulation results depicts that our algorithm increases the acceptance rate of multi-domain virtual network requests, compared with the existing virtual network embedding algorithm.

Minimizing embedding impact in steganography using trellis-coded quantization

NASA Astrophysics Data System (ADS)

Filler, Tomáš; Judas, Jan; Fridrich, Jessica

2010-01-01

In this paper, we propose a practical approach to minimizing embedding impact in steganography based on syndrome coding and trellis-coded quantization and contrast its performance with bounds derived from appropriate rate-distortion bounds. We assume that each cover element can be assigned a positive scalar expressing the impact of making an embedding change at that element (single-letter distortion). The problem is to embed a given payload with minimal possible average embedding impact. This task, which can be viewed as a generalization of matrix embedding or writing on wet paper, has been approached using heuristic and suboptimal tools in the past. Here, we propose a fast and very versatile solution to this problem that can theoretically achieve performance arbitrarily close to the bound. It is based on syndrome coding using linear convolutional codes with the optimal binary quantizer implemented using the Viterbi algorithm run in the dual domain. The complexity and memory requirements of the embedding algorithm are linear w.r.t. the number of cover elements. For practitioners, we include detailed algorithms for finding good codes and their implementation. Finally, we report extensive experimental results for a large set of relative payloads and for different distortion profiles, including the wet paper channel.

Transverse thermopherotic MHD Oldroyd-B fluid with Newtonian heating

NASA Astrophysics Data System (ADS)

Mehmood, R.; Rana, S.; Nadeem, S.

2018-03-01

Hydromagnetic transverse flow of an Oldroyd-B type fluid with suspension of nanoparticles and Newtonian heating effects is conferred in this article. Relaxation and Retardation time effects are taken into consideration. Using suitable transformations physical problem is converted into non-linear ordinary differential equations which are tackled numerically via Runge-Kutta Fehlberg integration scheme. Illustration of embedded constraints on flow characteristics are extracted through graphs. The physical response of velocity, temperature and concentration are investigated computationally. Momentum boundary layer thickness decreases but local heat and mass flux rises for Deborah number and Hartman number. The results provide interesting insights into certain applicable transport phenomena involving hydromagnetic rheological fluids.

Privacy-Preserving Predictive Modeling: Harmonization of Contextual Embeddings From Different Sources.

PubMed

Huang, Yingxiang; Lee, Junghye; Wang, Shuang; Sun, Jimeng; Liu, Hongfang; Jiang, Xiaoqian

2018-05-16

Data sharing has been a big challenge in biomedical informatics because of privacy concerns. Contextual embedding models have demonstrated a very strong representative capability to describe medical concepts (and their context), and they have shown promise as an alternative way to support deep-learning applications without the need to disclose original data. However, contextual embedding models acquired from individual hospitals cannot be directly combined because their embedding spaces are different, and naive pooling renders combined embeddings useless. The aim of this study was to present a novel approach to address these issues and to promote sharing representation without sharing data. Without sacrificing privacy, we also aimed to build a global model from representations learned from local private data and synchronize information from multiple sources. We propose a methodology that harmonizes different local contextual embeddings into a global model. We used Word2Vec to generate contextual embeddings from each source and Procrustes to fuse different vector models into one common space by using a list of corresponding pairs as anchor points. We performed prediction analysis with harmonized embeddings. We used sequential medical events extracted from the Medical Information Mart for Intensive Care III database to evaluate the proposed methodology in predicting the next likely diagnosis of a new patient using either structured data or unstructured data. Under different experimental scenarios, we confirmed that the global model built from harmonized local models achieves a more accurate prediction than local models and global models built from naive pooling. Such aggregation of local models using our unique harmonization can serve as the proxy for a global model, combining information from a wide range of institutions and information sources. It allows information unique to a certain hospital to become available to other sites, increasing the fluidity of information flow in health care. ©Yingxiang Huang, Junghye Lee, Shuang Wang, Jimeng Sun, Hongfang Liu, Xiaoqian Jiang. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 16.05.2018.

A Kernel Embedding-Based Approach for Nonstationary Causal Model Inference.

PubMed

Hu, Shoubo; Chen, Zhitang; Chan, Laiwan

2018-05-01

Although nonstationary data are more common in the real world, most existing causal discovery methods do not take nonstationarity into consideration. In this letter, we propose a kernel embedding-based approach, ENCI, for nonstationary causal model inference where data are collected from multiple domains with varying distributions. In ENCI, we transform the complicated relation of a cause-effect pair into a linear model of variables of which observations correspond to the kernel embeddings of the cause-and-effect distributions in different domains. In this way, we are able to estimate the causal direction by exploiting the causal asymmetry of the transformed linear model. Furthermore, we extend ENCI to causal graph discovery for multiple variables by transforming the relations among them into a linear nongaussian acyclic model. We show that by exploiting the nonstationarity of distributions, both cause-effect pairs and two kinds of causal graphs are identifiable under mild conditions. Experiments on synthetic and real-world data are conducted to justify the efficacy of ENCI over major existing methods.

Improved prediction of residue flexibility by embedding optimized amino acid grouping into RSA-based linear models.

PubMed

Zhang, Hua; Kurgan, Lukasz

2014-12-01

Knowledge of protein flexibility is vital for deciphering the corresponding functional mechanisms. This knowledge would help, for instance, in improving computational drug design and refinement in homology-based modeling. We propose a new predictor of the residue flexibility, which is expressed by B-factors, from protein chains that use local (in the chain) predicted (or native) relative solvent accessibility (RSA) and custom-derived amino acid (AA) alphabets. Our predictor is implemented as a two-stage linear regression model that uses RSA-based space in a local sequence window in the first stage and a reduced AA pair-based space in the second stage as the inputs. This method is easy to comprehend explicit linear form in both stages. Particle swarm optimization was used to find an optimal reduced AA alphabet to simplify the input space and improve the prediction performance. The average correlation coefficients between the native and predicted B-factors measured on a large benchmark dataset are improved from 0.65 to 0.67 when using the native RSA values and from 0.55 to 0.57 when using the predicted RSA values. Blind tests that were performed on two independent datasets show consistent improvements in the average correlation coefficients by a modest value of 0.02 for both native and predicted RSA-based predictions.

Preparation of thick silica coatings on carbon fibers with fine-structured silica nanotubes induced by a self-assembly process

PubMed Central

Baumgärtner, Benjamin; Möller, Hendrik; Neumann, Thomas

2017-01-01

A facile method to coat carbon fibers with a silica shell is presented in this work. By immobilizing linear polyamines on the carbon fiber surface, the high catalytic activity of polyamines in the sol–gel-processing of silica precursors is used to deposit a silica coating directly on the fiber’s surface. The surface localization of the catalyst is achieved either by attaching short-chain polyamines (e.g., tetraethylenepentamine) via covalent bonds to the carbon fiber surface or by depositing long-chain polyamines (e.g., linear poly(ethylenimine)) on the carbon fiber by weak non-covalent bonding. The long-chain polyamine self-assembles onto the carbon fiber substrate in the form of nanoscopic crystallites, which serve as a template for the subsequent silica deposition. The silicification at close to neutral pH is spatially restricted to the localized polyamine and consequently to the fiber surface. In case of the linear poly(ethylenimine), silica shells of several micrometers in thickness can be obtained and their morphology is easily controlled by a considerable number of synthesis parameters. A unique feature is the hierarchical biomimetic structure of the silica coating which surrounds the embedded carbon fiber by fibrillar and interconnected silica fine-structures. The high surface area of the nanostructured composite fiber may be exploited for catalytic applications and adsorption purposes. PMID:28685115

Preparation of thick silica coatings on carbon fibers with fine-structured silica nanotubes induced by a self-assembly process.

PubMed

Baumgärtner, Benjamin; Möller, Hendrik; Neumann, Thomas; Volkmer, Dirk

2017-01-01

A facile method to coat carbon fibers with a silica shell is presented in this work. By immobilizing linear polyamines on the carbon fiber surface, the high catalytic activity of polyamines in the sol-gel-processing of silica precursors is used to deposit a silica coating directly on the fiber's surface. The surface localization of the catalyst is achieved either by attaching short-chain polyamines (e.g., tetraethylenepentamine) via covalent bonds to the carbon fiber surface or by depositing long-chain polyamines (e.g., linear poly(ethylenimine)) on the carbon fiber by weak non-covalent bonding. The long-chain polyamine self-assembles onto the carbon fiber substrate in the form of nanoscopic crystallites, which serve as a template for the subsequent silica deposition. The silicification at close to neutral pH is spatially restricted to the localized polyamine and consequently to the fiber surface. In case of the linear poly(ethylenimine), silica shells of several micrometers in thickness can be obtained and their morphology is easily controlled by a considerable number of synthesis parameters. A unique feature is the hierarchical biomimetic structure of the silica coating which surrounds the embedded carbon fiber by fibrillar and interconnected silica fine-structures. The high surface area of the nanostructured composite fiber may be exploited for catalytic applications and adsorption purposes.

Ensemble Grouping Strategies for Embedded Stochastic Collocation Methods Applied to Anisotropic Diffusion Problems

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

D'Elia, M.; Edwards, H. C.; Hu, J.

Previous work has demonstrated that propagating groups of samples, called ensembles, together through forward simulations can dramatically reduce the aggregate cost of sampling-based uncertainty propagation methods [E. Phipps, M. D'Elia, H. C. Edwards, M. Hoemmen, J. Hu, and S. Rajamanickam, SIAM J. Sci. Comput., 39 (2017), pp. C162--C193]. However, critical to the success of this approach when applied to challenging problems of scientific interest is the grouping of samples into ensembles to minimize the total computational work. For example, the total number of linear solver iterations for ensemble systems may be strongly influenced by which samples form the ensemble whenmore » applying iterative linear solvers to parameterized and stochastic linear systems. In this paper we explore sample grouping strategies for local adaptive stochastic collocation methods applied to PDEs with uncertain input data, in particular canonical anisotropic diffusion problems where the diffusion coefficient is modeled by truncated Karhunen--Loève expansions. Finally, we demonstrate that a measure of the total anisotropy of the diffusion coefficient is a good surrogate for the number of linear solver iterations for each sample and therefore provides a simple and effective metric for grouping samples.« less

Ensemble Grouping Strategies for Embedded Stochastic Collocation Methods Applied to Anisotropic Diffusion Problems

DOE PAGES

D'Elia, M.; Edwards, H. C.; Hu, J.; ...

2018-01-18

Previous work has demonstrated that propagating groups of samples, called ensembles, together through forward simulations can dramatically reduce the aggregate cost of sampling-based uncertainty propagation methods [E. Phipps, M. D'Elia, H. C. Edwards, M. Hoemmen, J. Hu, and S. Rajamanickam, SIAM J. Sci. Comput., 39 (2017), pp. C162--C193]. However, critical to the success of this approach when applied to challenging problems of scientific interest is the grouping of samples into ensembles to minimize the total computational work. For example, the total number of linear solver iterations for ensemble systems may be strongly influenced by which samples form the ensemble whenmore » applying iterative linear solvers to parameterized and stochastic linear systems. In this paper we explore sample grouping strategies for local adaptive stochastic collocation methods applied to PDEs with uncertain input data, in particular canonical anisotropic diffusion problems where the diffusion coefficient is modeled by truncated Karhunen--Loève expansions. Finally, we demonstrate that a measure of the total anisotropy of the diffusion coefficient is a good surrogate for the number of linear solver iterations for each sample and therefore provides a simple and effective metric for grouping samples.« less

Real-Time Distributed Embedded Oscillator Operating Frequency Monitoring

NASA Technical Reports Server (NTRS)

Pollock, Julie; Oliver, Brett; Brickner, Christopher

2012-01-01

A document discusses the utilization of embedded clocks inside of operating network data links as an auxiliary clock source to satisfy local oscillator monitoring requirements. Modem network interfaces, typically serial network links, often contain embedded clocking information of very tight precision to recover data from the link. This embedded clocking data can be utilized by the receiving device to monitor the local oscillator for tolerance to required specifications, often important in high-integrity fault-tolerant applications. A device can utilize a received embedded clock to determine if the local or the remote device is out of tolerance by using a single link. The local device can determine if it is failing, assuming a single fault model, with two or more active links. Network fabric components, containing many operational links, can potentially determine faulty remote or local devices in the presence of multiple faults. Two methods of implementation are described. In one method, a recovered clock can be directly used to monitor the local clock as a direct replacement of an external local oscillator. This scheme is consistent with a general clock monitoring function whereby clock sources are clocking two counters and compared over a fixed interval of time. In another method, overflow/underflow conditions can be used to detect clock relationships for monitoring. These network interfaces often provide clock compensation circuitry to allow data to be transferred from the received (network) clock domain to the internal clock domain. This circuit could be modified to detect overflow/underflow conditions of the buffering required and report a fast or slow receive clock, respectively.

Analytic integrable systems: Analytic normalization and embedding flows

NASA Astrophysics Data System (ADS)

Zhang, Xiang

In this paper we mainly study the existence of analytic normalization and the normal form of finite dimensional complete analytic integrable dynamical systems. More details, we will prove that any complete analytic integrable diffeomorphism F(x)=Bx+f(x) in (Cn,0) with B having eigenvalues not modulus 1 and f(x)=O(|) is locally analytically conjugate to its normal form. Meanwhile, we also prove that any complete analytic integrable differential system x˙=Ax+f(x) in (Cn,0) with A having nonzero eigenvalues and f(x)=O(|) is locally analytically conjugate to its normal form. Furthermore we will prove that any complete analytic integrable diffeomorphism defined on an analytic manifold can be embedded in a complete analytic integrable flow. We note that parts of our results are the improvement of Moser's one in J. Moser, The analytic invariants of an area-preserving mapping near a hyperbolic fixed point, Comm. Pure Appl. Math. 9 (1956) 673-692 and of Poincaré's one in H. Poincaré, Sur l'intégration des équations différentielles du premier order et du premier degré, II, Rend. Circ. Mat. Palermo 11 (1897) 193-239. These results also improve the ones in Xiang Zhang, Analytic normalization of analytic integrable systems and the embedding flows, J. Differential Equations 244 (2008) 1080-1092 in the sense that the linear part of the systems can be nonhyperbolic, and the one in N.T. Zung, Convergence versus integrability in Poincaré-Dulac normal form, Math. Res. Lett. 9 (2002) 217-228 in the way that our paper presents the concrete expression of the normal form in a restricted case.

Asymmetric distances for binary embeddings.

PubMed

Gordo, Albert; Perronnin, Florent; Gong, Yunchao; Lazebnik, Svetlana

2014-01-01

In large-scale query-by-example retrieval, embedding image signatures in a binary space offers two benefits: data compression and search efficiency. While most embedding algorithms binarize both query and database signatures, it has been noted that this is not strictly a requirement. Indeed, asymmetric schemes that binarize the database signatures but not the query still enjoy the same two benefits but may provide superior accuracy. In this work, we propose two general asymmetric distances that are applicable to a wide variety of embedding techniques including locality sensitive hashing (LSH), locality sensitive binary codes (LSBC), spectral hashing (SH), PCA embedding (PCAE), PCAE with random rotations (PCAE-RR), and PCAE with iterative quantization (PCAE-ITQ). We experiment on four public benchmarks containing up to 1M images and show that the proposed asymmetric distances consistently lead to large improvements over the symmetric Hamming distance for all binary embedding techniques.

Curved Displacement Transfer Functions for Geometric Nonlinear Large Deformation Structure Shape Predictions

NASA Technical Reports Server (NTRS)

Ko, William L.; Fleischer, Van Tran; Lung, Shun-Fat

2017-01-01

For shape predictions of structures under large geometrically nonlinear deformations, Curved Displacement Transfer Functions were formulated based on a curved displacement, traced by a material point from the undeformed position to deformed position. The embedded beam (depth-wise cross section of a structure along a surface strain-sensing line) was discretized into multiple small domains, with domain junctures matching the strain-sensing stations. Thus, the surface strain distribution could be described with a piecewise linear or a piecewise nonlinear function. The discretization approach enabled piecewise integrations of the embedded-beam curvature equations to yield the Curved Displacement Transfer Functions, expressed in terms of embedded beam geometrical parameters and surface strains. By entering the surface strain data into the Displacement Transfer Functions, deflections along each embedded beam can be calculated at multiple points for mapping the overall structural deformed shapes. Finite-element linear and nonlinear analyses of a tapered cantilever tubular beam were performed to generate linear and nonlinear surface strains and the associated deflections to be used for validation. The shape prediction accuracies were then determined by comparing the theoretical deflections with the finiteelement- generated deflections. The results show that the newly developed Curved Displacement Transfer Functions are very accurate for shape predictions of structures under large geometrically nonlinear deformations.

Effective scheme for partitioning covalent bonds in density-functional embedding theory: From molecules to extended covalent systems.

PubMed

Huang, Chen; Muñoz-García, Ana Belén; Pavone, Michele

2016-12-28

Density-functional embedding theory provides a general way to perform multi-physics quantum mechanics simulations of large-scale materials by dividing the total system's electron density into a cluster's density and its environment's density. It is then possible to compute the accurate local electronic structures and energetics of the embedded cluster with high-level methods, meanwhile retaining a low-level description of the environment. The prerequisite step in the density-functional embedding theory is the cluster definition. In covalent systems, cutting across the covalent bonds that connect the cluster and its environment leads to dangling bonds (unpaired electrons). These represent a major obstacle for the application of density-functional embedding theory to study extended covalent systems. In this work, we developed a simple scheme to define the cluster in covalent systems. Instead of cutting covalent bonds, we directly split the boundary atoms for maintaining the valency of the cluster. With this new covalent embedding scheme, we compute the dehydrogenation energies of several different molecules, as well as the binding energy of a cobalt atom on graphene. Well localized cluster densities are observed, which can facilitate the use of localized basis sets in high-level calculations. The results are found to converge faster with the embedding method than the other multi-physics approach ONIOM. This work paves the way to perform the density-functional embedding simulations of heterogeneous systems in which different types of chemical bonds are present.

Sensor Network Localization by Eigenvector Synchronization Over the Euclidean Group

PubMed Central

CUCURINGU, MIHAI; LIPMAN, YARON; SINGER, AMIT

2013-01-01

We present a new approach to localization of sensors from noisy measurements of a subset of their Euclidean distances. Our algorithm starts by finding, embedding, and aligning uniquely realizable subsets of neighboring sensors called patches. In the noise-free case, each patch agrees with its global positioning up to an unknown rigid motion of translation, rotation, and possibly reflection. The reflections and rotations are estimated using the recently developed eigenvector synchronization algorithm, while the translations are estimated by solving an overdetermined linear system. The algorithm is scalable as the number of nodes increases and can be implemented in a distributed fashion. Extensive numerical experiments show that it compares favorably to other existing algorithms in terms of robustness to noise, sparse connectivity, and running time. While our approach is applicable to higher dimensions, in the current article, we focus on the two-dimensional case. PMID:23946700

A meta-classifier for detecting prostate cancer by quantitative integration of in vivo magnetic resonance spectroscopy and magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Viswanath, Satish; Tiwari, Pallavi; Rosen, Mark; Madabhushi, Anant

2008-03-01

Recently, in vivo Magnetic Resonance Imaging (MRI) and Magnetic Resonance Spectroscopy (MRS) have emerged as promising new modalities to aid in prostate cancer (CaP) detection. MRI provides anatomic and structural information of the prostate while MRS provides functional data pertaining to biochemical concentrations of metabolites such as creatine, choline and citrate. We have previously presented a hierarchical clustering scheme for CaP detection on in vivo prostate MRS and have recently developed a computer-aided method for CaP detection on in vivo prostate MRI. In this paper we present a novel scheme to develop a meta-classifier to detect CaP in vivo via quantitative integration of multimodal prostate MRS and MRI by use of non-linear dimensionality reduction (NLDR) methods including spectral clustering and locally linear embedding (LLE). Quantitative integration of multimodal image data (MRI and PET) involves the concatenation of image intensities following image registration. However multimodal data integration is non-trivial when the individual modalities include spectral and image intensity data. We propose a data combination solution wherein we project the feature spaces (image intensities and spectral data) associated with each of the modalities into a lower dimensional embedding space via NLDR. NLDR methods preserve the relationships between the objects in the original high dimensional space when projecting them into the reduced low dimensional space. Since the original spectral and image intensity data are divorced from their original physical meaning in the reduced dimensional space, data at the same spatial location can be integrated by concatenating the respective embedding vectors. Unsupervised consensus clustering is then used to partition objects into different classes in the combined MRS and MRI embedding space. Quantitative results of our multimodal computer-aided diagnosis scheme on 16 sets of patient data obtained from the ACRIN trial, for which corresponding histological ground truth for spatial extent of CaP is known, show a marginally higher sensitivity, specificity, and positive predictive value compared to corresponding CAD results with the individual modalities.

Planar Embedding of Planar Graphs,

DTIC Science & Technology

1983-02-01

Stanford University and supported by a Chaim Wcismann postdoctoral fellowship and DARPA contract MDAOO3-C-0102. Current address: Institute of ...rectilinear embeddings (both with and without cross - overs), using the bounding box area cost. He proved that a tree of vertices with maximum degree 4 can...be laid out without crossovers in an area that is linear in the number of edges (or vertices). He also showed how Ato get a such an embedding for any

Prediction of CT Substitutes from MR Images Based on Local Diffeomorphic Mapping for Brain PET Attenuation Correction.

PubMed

Wu, Yao; Yang, Wei; Lu, Lijun; Lu, Zhentai; Zhong, Liming; Huang, Meiyan; Feng, Yanqiu; Feng, Qianjin; Chen, Wufan

2016-10-01

Attenuation correction is important for PET reconstruction. In PET/MR, MR intensities are not directly related to attenuation coefficients that are needed in PET imaging. The attenuation coefficient map can be derived from CT images. Therefore, prediction of CT substitutes from MR images is desired for attenuation correction in PET/MR. This study presents a patch-based method for CT prediction from MR images, generating attenuation maps for PET reconstruction. Because no global relation exists between MR and CT intensities, we propose local diffeomorphic mapping (LDM) for CT prediction. In LDM, we assume that MR and CT patches are located on 2 nonlinear manifolds, and the mapping from the MR manifold to the CT manifold approximates a diffeomorphism under a local constraint. Locality is important in LDM and is constrained by the following techniques. The first is local dictionary construction, wherein, for each patch in the testing MR image, a local search window is used to extract patches from training MR/CT pairs to construct MR and CT dictionaries. The k-nearest neighbors and an outlier detection strategy are then used to constrain the locality in MR and CT dictionaries. Second is local linear representation, wherein, local anchor embedding is used to solve MR dictionary coefficients when representing the MR testing sample. Under these local constraints, dictionary coefficients are linearly transferred from the MR manifold to the CT manifold and used to combine CT training samples to generate CT predictions. Our dataset contains 13 healthy subjects, each with T1- and T2-weighted MR and CT brain images. This method provides CT predictions with a mean absolute error of 110.1 Hounsfield units, Pearson linear correlation of 0.82, peak signal-to-noise ratio of 24.81 dB, and Dice in bone regions of 0.84 as compared with real CTs. CT substitute-based PET reconstruction has a regression slope of 1.0084 and R 2 of 0.9903 compared with real CT-based PET. In this method, no image segmentation or accurate registration is required. Our method demonstrates superior performance in CT prediction and PET reconstruction compared with competing methods. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Cell-Averaged discretization for incompressible Navier-Stokes with embedded boundaries and locally refined Cartesian meshes: a high-order finite volume approach

NASA Astrophysics Data System (ADS)

Bhalla, Amneet Pal Singh; Johansen, Hans; Graves, Dan; Martin, Dan; Colella, Phillip; Applied Numerical Algorithms Group Team

2017-11-01

We present a consistent cell-averaged discretization for incompressible Navier-Stokes equations on complex domains using embedded boundaries. The embedded boundary is allowed to freely cut the locally-refined background Cartesian grid. Implicit-function representation is used for the embedded boundary, which allows us to convert the required geometric moments in the Taylor series expansion (upto arbitrary order) of polynomials into an algebraic problem in lower dimensions. The computed geometric moments are then used to construct stencils for various operators like the Laplacian, divergence, gradient, etc., by solving a least-squares system locally. We also construct the inter-level data-transfer operators like prolongation and restriction for multi grid solvers using the same least-squares system approach. This allows us to retain high-order of accuracy near coarse-fine interface and near embedded boundaries. Canonical problems like Taylor-Green vortex flow and flow past bluff bodies will be presented to demonstrate the proposed method. U.S. Department of Energy, Office of Science, ASCR (Award Number DE-AC02-05CH11231).

A Locality-Constrained and Label Embedding Dictionary Learning Algorithm for Image Classification.

PubMed

Zhengming Li; Zhihui Lai; Yong Xu; Jian Yang; Zhang, David

2017-02-01

Locality and label information of training samples play an important role in image classification. However, previous dictionary learning algorithms do not take the locality and label information of atoms into account together in the learning process, and thus their performance is limited. In this paper, a discriminative dictionary learning algorithm, called the locality-constrained and label embedding dictionary learning (LCLE-DL) algorithm, was proposed for image classification. First, the locality information was preserved using the graph Laplacian matrix of the learned dictionary instead of the conventional one derived from the training samples. Then, the label embedding term was constructed using the label information of atoms instead of the classification error term, which contained discriminating information of the learned dictionary. The optimal coding coefficients derived by the locality-based and label-based reconstruction were effective for image classification. Experimental results demonstrated that the LCLE-DL algorithm can achieve better performance than some state-of-the-art algorithms.

Multi-model predictive control based on LMI: from the adaptation of the state-space model to the analytic description of the control law

NASA Astrophysics Data System (ADS)

Falugi, P.; Olaru, S.; Dumur, D.

2010-08-01

This article proposes an explicit robust predictive control solution based on linear matrix inequalities (LMIs). The considered predictive control strategy uses different local descriptions of the system dynamics and uncertainties and thus allows the handling of less conservative input constraints. The computed control law guarantees constraint satisfaction and asymptotic stability. The technique is effective for a class of nonlinear systems embedded into polytopic models. A detailed discussion of the procedures which adapt the partition of the state space is presented. For the practical implementation the construction of suitable (explicit) descriptions of the control law are described upon concrete algorithms.

Realistic Features in Analysing the Effect of the Seismic Motion upon Localized Structures Considering Base Isolation Influence on Their Dynamic Behaviour

NASA Astrophysics Data System (ADS)

Apostol, Bogdan Felix; Florin Balan, Stefan; Ionescu, Constantin

2017-12-01

The effects of the earthquakes on buildings and the concept of seismic base isolation are investigated by using the model of the vibrating bar embedded at one end. The normal modes and the eigenfrequencies of the bar are highlighted and the amplification of the response due to the excitation of the normal modes (eigenmodes) is computed. The effect is much enhanced at resonance, for oscillating shocks which contain eigenfrequencies of the bar. Also, the response of two linearly joined bars with one end embedded is calculated. It is shown that for very different elastic properties the eigenfrequencies are due mainly to the “softer” bar. The effect of the base isolation in seismic structural engineering is assessed by formulating the model of coupled harmonic oscillators, as a simplified model for the structure building-foundation viewed as two coupled vibrating bars. The coupling decreases the lower eigenfrequencies of the structure and increases the higher ones. Similar amplification factors are derived for coupled oscillators at resonance with an oscillating shock.

High-Resolution Mapping of Thermal History in Polymer Nanocomposites: Gold Nanorods as Microscale Temperature Sensors.

PubMed

Kennedy, W Joshua; Slinker, Keith A; Volk, Brent L; Koerner, Hilmar; Godar, Trenton J; Ehlert, Gregory J; Baur, Jeffery W

2015-12-23

A technique is reported for measuring and mapping the maximum internal temperature of a structural epoxy resin with high spatial resolution via the optically detected shape transformation of embedded gold nanorods (AuNRs). Spatially resolved absorption spectra of the nanocomposites are used to determine the frequencies of surface plasmon resonances. From these frequencies the AuNR aspect ratio is calculated using a new analytical approximation for the Mie-Gans scattering theory, which takes into account coincident changes in the local dielectric. Despite changes in the chemical environment, the calculated aspect ratio of the embedded nanorods is found to decrease over time to a steady-state value that depends linearly on the temperature over the range of 100-200 °C. Thus, the optical absorption can be used to determine the maximum temperature experienced at a particular location when exposure times exceed the temperature-dependent relaxation time. The usefulness of this approach is demonstrated by mapping the temperature of an internally heated structural epoxy resin with 10 μm lateral spatial resolution.

The temperature and tension characteristics of the FBGs embedded in the polythene sheath of an optical cable

NASA Astrophysics Data System (ADS)

Chen, Guanghui; Zhao, Ming; Sha, Jianbo; Zhang, Jun; Wu, Bingyan; Lin, Chen; Zhang, Mingliang; Gao, Kan

2015-10-01

The five of FBG were embedded in the PE sheath of a tether optical cable, which has about 18mm diameter and 7000mm length. The temperature and tension characteristics of the FBGs embedded in the polythene (PE) sheath had been demonstrated quantitatively. The Bragg wavelength of the embedded FBG shift linearly with the change of pulling force loaded on the tether optical cable and its tension sensitivity is about 3.75 pm/kg. The results of temperature experiment suggest the embedded FBG have been sensitized by PE material, so that its temperature sensitivity increase from 9.37pm/°C to about 12.51pm/°C.

Passive-quadrature demodulated localized-Michelson fiber-optic strain sensor embedded in composite materials

NASA Astrophysics Data System (ADS)

Valis, Tomas; Tapanes, Edward; Liu, Kexing; Measures, Raymond M.

1991-04-01

A strain sensor embedded in composite materials that is intrinsic, all fiber, local, and phase demodulated is described. It is the combination of these necessary elements that represents an advance in the state of the art. Sensor localization is achieved by using a pair of mirror-ended optical fibers of different lengths that are mechanically coupled up until the desired gauge length for common-mode suppression has been reached. This fiber-optic sensor has been embedded in both thermoset (Kevlar/epoxy and graphite/epoxy) and thermoplastic (graphite/PEEK) composite materials in order to make local strain measurements at the lamina level. The all-fiber system uses a 3 x 3 coupler for phase demodulation. Parameters such as strain sensitivity, transverse strain sensitivity, failure strain, and frequency response are discussed, along with applications.

Fiber Optic Sensor Embedment Study for Multi-Parameter Strain Sensing

PubMed Central

Drissi-Habti, Monssef; Raman, Venkadesh; Khadour, Aghiad; Timorian, Safiullah

2017-01-01

The fiber optic sensors (FOSs) are commonly used for large-scale structure monitoring systems for their small size, noise free and low electrical risk characteristics. Embedded fiber optic sensors (FOSs) lead to micro-damage in composite structures. This damage generation threshold is based on the coating material of the FOSs and their diameter. In addition, embedded FOSs are aligned parallel to reinforcement fibers to avoid micro-damage creation. This linear positioning of distributed FOS fails to provide all strain parameters. We suggest novel sinusoidal sensor positioning to overcome this issue. This method tends to provide multi-parameter strains in a large surface area. The effectiveness of sinusoidal FOS positioning over linear FOS positioning is studied under both numerical and experimental methods. This study proves the advantages of the sinusoidal positioning method for FOS in composite material’s bonding. PMID:28333117

Assessing frequency-dependent site polarisabilities in linear response polarisable embedding

NASA Astrophysics Data System (ADS)

Nørby, Morten S.; Vahtras, Olav; Norman, Patrick; Kongsted, Jacob

2017-01-01

In this paper, we discuss the impact of using a frequency-dependent embedding potential in quantum chemical embedding calculations of response properties. We show that the introduction of a frequency-dependent embedding potential leads to further model complications upon solving the central equations defining specific molecular properties. On the other hand, we also show from a numerical point of view that the consequences of using such a frequency-dependent embedding potential is almost negligible. Thus, for the kind of systems and processes studied in this paper the general recommendation is to use frequency-independent embedding potentials since this leads to less complicated model issues. However, larger effects are expected if the absorption bands of the environment are closer to that of the region treated using quantum mechanics.

Finite element formulation with embedded weak discontinuities for strain localization under dynamic conditions

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

Jin, Tao; Mourad, Hashem M.; Bronkhorst, Curt A.

Here, we present an explicit finite element formulation designed for the treatment of strain localization under highly dynamic conditions. We also used a material stability analysis to detect the onset of localization behavior. Finite elements with embedded weak discontinuities are employed with the aim of representing subsequent localized deformation accurately. The formulation and its algorithmic implementation are described in detail. Numerical results are presented to illustrate the usefulness of this computational framework in the treatment of strain localization under highly dynamic conditions, and to examine its performance characteristics in the context of two-dimensional plane-strain problems.

Finite element formulation with embedded weak discontinuities for strain localization under dynamic conditions

DOE PAGES

Jin, Tao; Mourad, Hashem M.; Bronkhorst, Curt A.; ...

2017-09-13

Here, we present an explicit finite element formulation designed for the treatment of strain localization under highly dynamic conditions. We also used a material stability analysis to detect the onset of localization behavior. Finite elements with embedded weak discontinuities are employed with the aim of representing subsequent localized deformation accurately. The formulation and its algorithmic implementation are described in detail. Numerical results are presented to illustrate the usefulness of this computational framework in the treatment of strain localization under highly dynamic conditions, and to examine its performance characteristics in the context of two-dimensional plane-strain problems.

Localized compliance of small airways in excised rat lungs using microfocal X-ray computed tomography.

PubMed

Sera, Toshihiro; Fujioka, Hideki; Yokota, Hideo; Makinouchi, Akitake; Himeno, Ryutaro; Schroter, Robert C; Tanishita, Kazuo

2004-05-01

Airway compliance is a key factor in understanding lung mechanics and is used as a clinical diagnostic index. Understanding such mechanics in small airways physiologically and clinically is critical. We have determined the "morphometric change" and "localized compliance" of small airways under "near"-physiological conditions; namely, the airways were embedded in parenchyma without dehydration and fixation. Previously, we developed a two-step method to visualize small airways in detail by staining the lung tissue with a radiopaque solution and then visualizing the tissue with a cone-beam microfocal X-ray computed tomography system (Sera et al. J Biomech 36: 1587-1594, 2003). In this study, we used this technique to analyze changes in diameter and length of the same small airways ( approximately 150 microm ID) and then evaluated the localized compliance as a function of airway generation (Z). For smaller (<300-microm-diameter) airways, diameter was 36% larger at end-tidal inspiration and 89% larger at total lung capacity; length was 18% larger at end-tidal inspiration and 43% larger at total lung capacity than at functional residual capacity. Diameter, especially at smaller airways, did not behave linearly with V(1/3) (where V is volume). With increasing lung pressure, diameter changed dramatically at a particular pressure and length changed approximately linearly during inflation and deflation. Percentage of airway volume for smaller airways did not behave linearly with that of lung volume. Smaller airways were generally more compliant than larger airways with increasing Z and exhibited hysteresis in their diameter behavior. Airways at higher Z deformed at a lower pressure than those at lower Z. These results indicated that smaller airways did not behave homogeneously.

Emphasizing Language and Visualization in Teaching Linear Algebra

ERIC Educational Resources Information Center

Hannah, John; Stewart, Sepideh; Thomas, Mike

2013-01-01

Linear algebra with its rich theoretical nature is a first step towards advanced mathematical thinking for many undergraduate students. In this paper, we consider the teaching approach of an experienced mathematician as he attempts to engage his students with the key ideas embedded in a second-year course in linear algebra. We describe his…

[Multi-Target Recognition of Internal and External Defects of Potato by Semi-Transmission Hyperspectral Imaging and Manifold Learning Algorithm].

PubMed

Huang, Tao; Li, Xiao-yu; Jin, Rui; Ku, Jing; Xu, Sen-miao; Xu, Meng-ling; Wu, Zhen-zhong; Kong, De-guo

2015-04-01

The present paper put forward a non-destructive detection method which combines semi-transmission hyperspectral imaging technology with manifold learning dimension reduction algorithm and least squares support vector machine (LSSVM) to recognize internal and external defects in potatoes simultaneously. Three hundred fifteen potatoes were bought in farmers market as research object, and semi-transmission hyperspectral image acquisition system was constructed to acquire the hyperspectral images of normal external defects (bud and green rind) and internal defect (hollow heart) potatoes. In order to conform to the actual production, defect part is randomly put right, side and back to the acquisition probe when the hyperspectral images of external defects potatoes are acquired. The average spectrums (390-1,040 nm) were extracted from the region of interests for spectral preprocessing. Then three kinds of manifold learning algorithm were respectively utilized to reduce the dimension of spectrum data, including supervised locally linear embedding (SLLE), locally linear embedding (LLE) and isometric mapping (ISOMAP), the low-dimensional data gotten by manifold learning algorithms is used as model input, Error Correcting Output Code (ECOC) and LSSVM were combined to develop the multi-target classification model. By comparing and analyzing results of the three models, we concluded that SLLE is the optimal manifold learning dimension reduction algorithm, and the SLLE-LSSVM model is determined to get the best recognition rate for recognizing internal and external defects potatoes. For test set data, the single recognition rate of normal, bud, green rind and hollow heart potato reached 96.83%, 86.96%, 86.96% and 95% respectively, and he hybrid recognition rate was 93.02%. The results indicate that combining the semi-transmission hyperspectral imaging technology with SLLE-LSSVM is a feasible qualitative analytical method which can simultaneously recognize the internal and external defects potatoes and also provide technical reference for rapid on-line non-destructive detecting of the internal and external defects potatoes.

Three-dimensional localization and optical imaging of objects in turbid media with independent component analysis.

PubMed

Xu, M; Alrubaiee, M; Gayen, S K; Alfano, R R

2005-04-01

A new approach for optical imaging and localization of objects in turbid media that makes use of the independent component analysis (ICA) from information theory is demonstrated. Experimental arrangement realizes a multisource illumination of a turbid medium with embedded objects and a multidetector acquisition of transmitted light on the medium boundary. The resulting spatial diversity and multiple angular observations provide robust data for three-dimensional localization and characterization of absorbing and scattering inhomogeneities embedded in a turbid medium. ICA of the perturbations in the spatial intensity distribution on the medium boundary sorts out the embedded objects, and their locations are obtained from Green's function analysis based on any appropriate light propagation model. Imaging experiments were carried out on two highly scattering samples of thickness approximately 50 times the transport mean-free path of the respective medium. One turbid medium had two embedded absorptive objects, and the other had four scattering objects. An independent component separation of the signal, in conjunction with diffusive photon migration theory, was used to locate the embedded inhomogeneities. In both cases, improved lateral and axial localizations of the objects over the result obtained by use of common photon migration reconstruction algorithms were achieved. The approach is applicable to different medium geometries, can be used with any suitable photon propagation model, and is amenable to near-real-time imaging applications.

Embedded Promotions in Online Services: How Goal-Relevance Ambiguity Shapes Response and Affect

ERIC Educational Resources Information Center

Brasel, S. Adam

2010-01-01

Adding promotions to online services is increasingly commonplace, yet consumers may have difficulty determining whether service-embedded promotions are goal-relevant, due to the linear and transactional nature of online services. This contextual effect of goal-relevance ambiguity on promotions is explored across three studies. An exploratory study…

Regional co-location pattern scoping on a street network considering distance decay effects of spatial interaction

PubMed Central

Yu, Wenhao

2017-01-01

Regional co-location scoping intends to identify local regions where spatial features of interest are frequently located together. Most of the previous researches in this domain are conducted on a global scale and they assume that spatial objects are embedded in a 2-D space, but the movement in urban space is actually constrained by the street network. In this paper we refine the scope of co-location patterns to 1-D paths consisting of nodes and segments. Furthermore, since the relations between spatial events are usually inversely proportional to their separation distance, the proposed method introduces the “Distance Decay Effects” to improve the result. Specifically, our approach first subdivides the street edges into continuous small linear segments. Then a value representing the local distribution intensity of events is estimated for each linear segment using the distance-decay function. Each kind of geographic feature can lead to a tessellated network with density attribute, and the generated multiple networks for the pattern of interest will be finally combined into a composite network by calculating the co-location prevalence measure values, which are based on the density variation between different features. Our experiments verify that the proposed approach is effective in urban analysis. PMID:28763496

A Hybrid Density Functional Theory/Molecular Mechanics Approach for Linear Response Properties in Heterogeneous Environments.

PubMed

Rinkevicius, Zilvinas; Li, Xin; Sandberg, Jaime A R; Mikkelsen, Kurt V; Ågren, Hans

2014-03-11

We introduce a density functional theory/molecular mechanical approach for computation of linear response properties of molecules in heterogeneous environments, such as metal surfaces or nanoparticles embedded in solvents. The heterogeneous embedding environment, consisting from metallic and nonmetallic parts, is described by combined force fields, where conventional force fields are used for the nonmetallic part and capacitance-polarization-based force fields are used for the metallic part. The presented approach enables studies of properties and spectra of systems embedded in or placed at arbitrary shaped metallic surfaces, clusters, or nanoparticles. The capability and performance of the proposed approach is illustrated by sample calculations of optical absorption spectra of thymidine absorbed on gold surfaces in an aqueous environment, where we study how different organizations of the gold surface and how the combined, nonadditive effect of the two environments is reflected in the optical absorption spectrum.

Visual EKF-SLAM from Heterogeneous Landmarks †

PubMed Central

Esparza-Jiménez, Jorge Othón; Devy, Michel; Gordillo, José L.

2016-01-01

Many applications require the localization of a moving object, e.g., a robot, using sensory data acquired from embedded devices. Simultaneous localization and mapping from vision performs both the spatial and temporal fusion of these data on a map when a camera moves in an unknown environment. Such a SLAM process executes two interleaved functions: the front-end detects and tracks features from images, while the back-end interprets features as landmark observations and estimates both the landmarks and the robot positions with respect to a selected reference frame. This paper describes a complete visual SLAM solution, combining both point and line landmarks on a single map. The proposed method has an impact on both the back-end and the front-end. The contributions comprehend the use of heterogeneous landmark-based EKF-SLAM (the management of a map composed of both point and line landmarks); from this perspective, the comparison between landmark parametrizations and the evaluation of how the heterogeneity improves the accuracy on the camera localization, the development of a front-end active-search process for linear landmarks integrated into SLAM and the experimentation methodology. PMID:27070602

Coupled multiview autoencoders with locality sensitivity for three-dimensional human pose estimation

NASA Astrophysics Data System (ADS)

Yu, Jialin; Sun, Jifeng; Luo, Shasha; Duan, Bichao

2017-09-01

Estimating three-dimensional (3D) human poses from a single camera is usually implemented by searching pose candidates with image descriptors. Existing methods usually suppose that the mapping from feature space to pose space is linear, but in fact, their mapping relationship is highly nonlinear, which heavily degrades the performance of 3D pose estimation. We propose a method to recover 3D pose from a silhouette image. It is based on the multiview feature embedding (MFE) and the locality-sensitive autoencoders (LSAEs). On the one hand, we first depict the manifold regularized sparse low-rank approximation for MFE and then the input image is characterized by a fused feature descriptor. On the other hand, both the fused feature and its corresponding 3D pose are separately encoded by LSAEs. A two-layer back-propagation neural network is trained by parameter fine-tuning and then used to map the encoded 2D features to encoded 3D poses. Our LSAE ensures a good preservation of the local topology of data points. Experimental results demonstrate the effectiveness of our proposed method.

Kinematic Localization for Global Navigation Satellite Systems: A Kalman Filtering Approach

NASA Astrophysics Data System (ADS)

Tabatabaee, Mohammad Hadi

Use of the Global Positioning System (GNSS) has expanded significantly in the past decade, especially with advances in embedded systems and the emergence of smartphones and the Internet of Things (IoT). The growing demand has stimulated research on development of GNSS techniques and programming tools. The focus of much of the research efforts have been on high-level algorithms and augmentations. This dissertation focuses on the low-level methods at the heart of GNSS systems and proposes a new methods for GNSS positioning problems based on concepts of distance geometry and the use of Kalman filters. The methods presented in this dissertation provide algebraic solutions to problems that have predominantly been solved using iterative methods. The proposed methods are highly efficient, provide accurate estimates, and exhibit a degree of robustness in the presence of unfavorable satellite geometry. The algorithm operates in two stages; an estimation of the receiver clock bias and removal of the bias from the pseudorange observables, followed by the localization of the GNSS receiver. The use of a Kalman filter in between the two stages allows for an improvement of the clock bias estimate with a noticeable impact on the position estimates. The receiver localization step has also been formulated in a linear manner allowing for the direct application of a Kalman filter without any need for linearization. The methodology has also been extended to double differential observables for high accuracy pseudorange and carrier phase position estimates.

Diverse power iteration embeddings: Theory and practice

DOE PAGES

Huang, Hao; Yoo, Shinjae; Yu, Dantong; ...

2015-11-09

Manifold learning, especially spectral embedding, is known as one of the most effective learning approaches on high dimensional data, but for real-world applications it raises a serious computational burden in constructing spectral embeddings for large datasets. To overcome this computational complexity, we propose a novel efficient embedding construction, Diverse Power Iteration Embedding (DPIE). DPIE shows almost the same effectiveness of spectral embeddings and yet is three order of magnitude faster than spectral embeddings computed from eigen-decomposition. Our DPIE is unique in that (1) it finds linearly independent embeddings and thus shows diverse aspects of dataset; (2) the proposed regularized DPIEmore » is effective if we need many embeddings; (3) we show how to efficiently orthogonalize DPIE if one needs; and (4) Diverse Power Iteration Value (DPIV) provides the importance of each DPIE like an eigen value. As a result, such various aspects of DPIE and DPIV ensure that our algorithm is easy to apply to various applications, and we also show the effectiveness and efficiency of DPIE on clustering, anomaly detection, and feature selection as our case studies.« less

Critical Friendship and Critical Orphanship: Embedded Research of an English Local Authority Initiative

ERIC Educational Resources Information Center

Duggan, James R.

2014-01-01

The article engages with the opportunities and constraints raised by embedded research during times of rapid and extensive organisational change. Embedded research is an increasingly common approach for funding PhD studentships. The rapid and extensive reforms of the English public sector pose significant and underexplored challenges for embedded…

An embedded face-classification system for infrared images on an FPGA

NASA Astrophysics Data System (ADS)

Soto, Javier E.; Figueroa, Miguel

2014-10-01

We present a face-classification architecture for long-wave infrared (IR) images implemented on a Field Programmable Gate Array (FPGA). The circuit is fast, compact and low power, can recognize faces in real time and be embedded in a larger image-processing and computer vision system operating locally on an IR camera. The algorithm uses Local Binary Patterns (LBP) to perform feature extraction on each IR image. First, each pixel in the image is represented as an LBP pattern that encodes the similarity between the pixel and its neighbors. Uniform LBP codes are then used to reduce the number of patterns to 59 while preserving more than 90% of the information contained in the original LBP representation. Then, the image is divided into 64 non-overlapping regions, and each region is represented as a 59-bin histogram of patterns. Finally, the algorithm concatenates all 64 regions to create a 3,776-bin spatially enhanced histogram. We reduce the dimensionality of this histogram using Linear Discriminant Analysis (LDA), which improves clustering and enables us to store an entire database of 53 subjects on-chip. During classification, the circuit applies LBP and LDA to each incoming IR image in real time, and compares the resulting feature vector to each pattern stored in the local database using the Manhattan distance. We implemented the circuit on a Xilinx Artix-7 XC7A100T FPGA and tested it with the UCHThermalFace database, which consists of 28 81 x 150-pixel images of 53 subjects in indoor and outdoor conditions. The circuit achieves a 98.6% hit ratio, trained with 16 images and tested with 12 images of each subject in the database. Using a 100 MHz clock, the circuit classifies 8,230 images per second, and consumes only 309mW.

Fast photoacoustic imaging system based on 320-element linear transducer array.

PubMed

Yin, Bangzheng; Xing, Da; Wang, Yi; Zeng, Yaguang; Tan, Yi; Chen, Qun

2004-04-07

A fast photoacoustic (PA) imaging system, based on a 320-transducer linear array, was developed and tested on a tissue phantom. To reconstruct a test tomographic image, 64 time-domain PA signals were acquired from a tissue phantom with embedded light-absorption targets. A signal acquisition was accomplished by utilizing 11 phase-controlled sub-arrays, each consisting of four transducers. The results show that the system can rapidly map the optical absorption of a tissue phantom and effectively detect the embedded light-absorbing target. By utilizing the multi-element linear transducer array and phase-controlled imaging algorithm, we thus can acquire PA tomography more efficiently, compared to other existing technology and algorithms. The methodology and equipment thus provide a rapid and reliable approach to PA imaging that may have potential applications in noninvasive imaging and clinic diagnosis.

Engendering Curriculum History. Studies in Curriculum Theory Series

ERIC Educational Resources Information Center

Hendry, Petra

2011-01-01

How can curriculum history be re-envisioned from a feminist, poststructuralist perspective? "Engendering Curriculum History" disrupts dominant notions of history as linear, as inevitable progress, and as embedded in the individual. This conversation requires a history that seeks "rememberance" not representation, "reflexivity" not linearity, and…

Visual Processing in Adolescents with Autism Spectrum Disorder: Evidence from Embedded Figures and Configural Superiority Tests

ERIC Educational Resources Information Center

Dillen, Claudia; Steyaert, Jean; Op de Beeck, Hans P.; Boets, Bart

2015-01-01

The embedded figures test has often been used to reveal weak central coherence in individuals with autism spectrum disorder (ASD). Here, we administered a more standardized automated version of the embedded figures test in combination with the configural superiority task, to investigate the effect of contextual modulation on local feature…

Mapping High Dimensional Sparse Customer Requirements into Product Configurations

NASA Astrophysics Data System (ADS)

Jiao, Yao; Yang, Yu; Zhang, Hongshan

2017-10-01

Mapping customer requirements into product configurations is a crucial step for product design, while, customers express their needs ambiguously and locally due to the lack of domain knowledge. Thus the data mining process of customer requirements might result in fragmental information with high dimensional sparsity, leading the mapping procedure risk uncertainty and complexity. The Expert Judgment is widely applied against that background since there is no formal requirements for systematic or structural data. However, there are concerns on the repeatability and bias for Expert Judgment. In this study, an integrated method by adjusted Local Linear Embedding (LLE) and Naïve Bayes (NB) classifier is proposed to map high dimensional sparse customer requirements to product configurations. The integrated method adjusts classical LLE to preprocess high dimensional sparse dataset to satisfy the prerequisite of NB for classifying different customer requirements to corresponding product configurations. Compared with Expert Judgment, the adjusted LLE with NB performs much better in a real-world Tablet PC design case both in accuracy and robustness.

Improving the durability of the optical fiber sensor based on strain transfer analysis

NASA Astrophysics Data System (ADS)

Wang, Huaping; Jiang, Lizhong; Xiang, Ping

2018-05-01

To realize the reliable and long-term strain detection, the durability of optical fiber sensors has attracted more and more attention. The packaging technique has been considered as an effective method, which can enhance the survival ratios of optical fiber sensors to resist the harsh construction and service environment in civil engineering. To monitor the internal strain of structures, the embedded installation is adopted. Due to the different material properties between host material and the protective layer, the monitored structure embedded with sensors can be regarded as a typical model containing inclusions. Interfacial characteristic between the sensor and host material exists obviously, and the contacted interface is prone to debonding failure induced by the large interfacial shear stress. To recognize the local interfacial debonding damage and extend the effective life cycle of the embedded sensor, strain transfer analysis of a general three-layered sensing model is conducted to investigate the failure mechanism. The perturbation of the embedded sensor on the local strain field of host material is discussed. Based on the theoretical analysis, the distribution of the interfacial shear stress along the sensing length is characterized and adopted for the diagnosis of local interfacial debonding, and the sensitive parameters influencing the interfacial shear stress are also investigated. The research in this paper explores the interfacial debonding failure mechanism of embedded sensors based on the strain transfer analysis and provides theoretical basis for enhancing the interfacial bonding properties and improving the durability of embedded optical fiber sensors.

Research and Design of Embedded Wireless Meal Ordering System Based on SQLite

NASA Astrophysics Data System (ADS)

Zhang, Jihong; Chen, Xiaoquan

The paper describes features and internal architecture and developing method of SQLite. And then it gives a design and program of meal ordering system. The system realizes the information interaction among the users and embedded devices with SQLite as database system. The embedded database SQLite manages the data and achieves wireless communication by using Bluetooth. A system program based on Qt/Embedded and Linux drivers realizes the local management of environmental data.

Design and implementation of embedded un-interruptible power supply system (EUPSS) for web-based mobile application

NASA Astrophysics Data System (ADS)

Zhang, De-gan; Zhang, Xiao-dan

2012-11-01

With the growth of the amount of information manipulated by embedded application systems, which are embedded into devices and offer access to the devices on the internet, the requirements of saving the information systemically is necessary so as to fulfil access from the client and the local processing more efficiently. For supporting mobile applications, a design and implementation solution of embedded un-interruptible power supply (UPS) system (in brief, EUPSS) is brought forward for long-distance monitoring and controlling of UPS based on Web. The implementation of system is based on ATmega161, RTL8019AS and Arm chips with TCP/IP protocol suite for communication. In the embedded UPS system, an embedded file system is designed and implemented which saves the data and index information on a serial EEPROM chip in a structured way and communicates with a microcontroller unit through I2C bus. By embedding the file system into UPS system or other information appliances, users can access and manipulate local data on the web client side. Embedded file system on chips will play a major role in the growth of IP networking. Based on our experiment tests, the mobile users can easily monitor and control UPS in different places of long-distance. The performance of EUPSS has satisfied the requirements of all kinds of Web-based mobile applications.

Embedded Strain Gauges for Condition Monitoring of Silicone Gaskets

PubMed Central

Schotzko, Timo; Lang, Walter

2014-01-01

A miniaturized strain gauge with a thickness of 5 µm is molded into a silicone O-ring. This is a first step toward embedding sensors in gaskets for structural health monitoring. The signal of the integrated sensor exhibits a linear correlation with the contact pressure of the O-ring. This affords the opportunity to monitor the gasket condition during installation. Thus, damages caused by faulty assembly can be detected instantly, and early failures, with their associated consequences, can be prevented. Through the embedded strain gauge, the contact pressure applied to the gasket can be directly measured. Excessive pressure and incorrect positioning of the gasket can cause structural damage to the material of the gasket, which can lead to an early outage. A platinum strain gauge is fabricated on a thin polyimide layer and is contacted through gold connections. The measured resistance pressure response exhibits hysteresis for the first few strain cycles, followed by a linear behavior. The short-term impact of the embedded sensor on the stability of the gasket is investigated. Pull-tests with O-rings and test specimens have indicated that the integration of the miniaturized sensors has no negative impact on the stability in the short term. PMID:25014099

Graph embedding and extensions: a general framework for dimensionality reduction.

PubMed

Yan, Shuicheng; Xu, Dong; Zhang, Benyu; Zhang, Hong-Jiang; Yang, Qiang; Lin, Stephen

2007-01-01

Over the past few decades, a large family of algorithms - supervised or unsupervised; stemming from statistics or geometry theory - has been designed to provide different solutions to the problem of dimensionality reduction. Despite the different motivations of these algorithms, we present in this paper a general formulation known as graph embedding to unify them within a common framework. In graph embedding, each algorithm can be considered as the direct graph embedding or its linear/kernel/tensor extension of a specific intrinsic graph that describes certain desired statistical or geometric properties of a data set, with constraints from scale normalization or a penalty graph that characterizes a statistical or geometric property that should be avoided. Furthermore, the graph embedding framework can be used as a general platform for developing new dimensionality reduction algorithms. By utilizing this framework as a tool, we propose a new supervised dimensionality reduction algorithm called Marginal Fisher Analysis in which the intrinsic graph characterizes the intraclass compactness and connects each data point with its neighboring points of the same class, while the penalty graph connects the marginal points and characterizes the interclass separability. We show that MFA effectively overcomes the limitations of the traditional Linear Discriminant Analysis algorithm due to data distribution assumptions and available projection directions. Real face recognition experiments show the superiority of our proposed MFA in comparison to LDA, also for corresponding kernel and tensor extensions.

[Development of an embedded mobile terminal for real-time remote monitoring of out-of-hospital cardiac patients].

PubMed

Xu, Zhi-min; Fang, Zu-Xiang; Lai, Da-Kun; Song, Hai-Lang

2007-05-01

A kind of real-time remote monitoring embedded terminal which is combined with mobile communication technology and GPS localization technology, has been developed. The results of preliminary experiments show that the terminal can transmit ECG signals and localization information in real time and continuously, supply a real-time monitoring of out-of-hospital cardiac patients and trace the patients.

Holographic interferometry of transparent media using light scattered by embedded test objects

NASA Technical Reports Server (NTRS)

Prikryl, I.; Vest, C. M.

1982-01-01

Fringe formation and localization in holographic interferometry of transparent media are discussed for configurations in which light enters the medium and is scattered back through it by an embedded diffuse object. Fringe order numbers are doubled, and the fringe localization region is translated and compressed by a factor of two. The results are applicable to tomographic reconstruction of aerodynamic density fields around opaque test objects.

Hyperspectral target detection using manifold learning and multiple target spectra

DOE PAGES

Ziemann, Amanda K.; Theiler, James; Messinger, David W.

2016-03-31

Imagery collected from satellites and airborne platforms provides an important tool for remotely analyzing the content of a scene. In particular, the ability to remotely detect a specific material within a scene is of critical importance in nonproliferation and other applications. The sensor systems that process hyperspectral images collect the high-dimensional spectral information necessary to perform these detection analyses. For a d-dimensional hyperspectral image, however, where d is the number of spectral bands, it is common for the data to inherently occupy an m-dimensional space with m << d. In the remote sensing community, this has led to recent interestmore » in the use of manifold learning, which seeks to characterize the embedded lower-dimensional, nonlinear manifold that the data discretely approximate. The research presented in this paper focuses on a graph theory and manifold learning approach to target detection, using an adaptive version of locally linear embedding that is biased to separate target pixels from background pixels. Finally, this approach incorporates multiple target signatures for a particular material, accounting for the spectral variability that is often present within a solid material of interest.« less

A manifold learning approach to target detection in high-resolution hyperspectral imagery

NASA Astrophysics Data System (ADS)

Ziemann, Amanda K.

Imagery collected from airborne platforms and satellites provide an important medium for remotely analyzing the content in a scene. In particular, the ability to detect a specific material within a scene is of high importance to both civilian and defense applications. This may include identifying "targets" such as vehicles, buildings, or boats. Sensors that process hyperspectral images provide the high-dimensional spectral information necessary to perform such analyses. However, for a d-dimensional hyperspectral image, it is typical for the data to inherently occupy an m-dimensional space, with m << d. In the remote sensing community, this has led to a recent increase in the use of manifold learning, which aims to characterize the embedded lower-dimensional, non-linear manifold upon which the hyperspectral data inherently lie. Classic hyperspectral data models include statistical, linear subspace, and linear mixture models, but these can place restrictive assumptions on the distribution of the data; this is particularly true when implementing traditional target detection approaches, and the limitations of these models are well-documented. With manifold learning based approaches, the only assumption is that the data reside on an underlying manifold that can be discretely modeled by a graph. The research presented here focuses on the use of graph theory and manifold learning in hyperspectral imagery. Early work explored various graph-building techniques with application to the background model of the Topological Anomaly Detection (TAD) algorithm, which is a graph theory based approach to anomaly detection. This led towards a focus on target detection, and in the development of a specific graph-based model of the data and subsequent dimensionality reduction using manifold learning. An adaptive graph is built on the data, and then used to implement an adaptive version of locally linear embedding (LLE). We artificially induce a target manifold and incorporate it into the adaptive LLE transformation; the artificial target manifold helps to guide the separation of the target data from the background data in the new, lower-dimensional manifold coordinates. Then, target detection is performed in the manifold space.

Trade in and Valuation of Virtual Water Impacts in a City: A Case Study Of Flagstaff, Arizona

NASA Astrophysics Data System (ADS)

Rushforth, R.; Ruddell, B. L.

2013-12-01

An increasingly intense component of the global coupled natural and human system (CNH) is the economic trade of various types of resources and the outsourcing of resource impacts between geographically distant economic systems. The human economy's trade arrangements allow specific localities, especially cities, to exceed spatially local resource stock sustainability and footprint constraints, as evidenced in the urban metabolism literature. Each movement or trade of a resource along a network is associated with an embedded or 'virtual' exchange of indirect impacts on the inputs to the production process. The networked trade of embedded resources, therefore, is an essential human adaptation to resource limitations. Using the Embedded Resource Impact Accounting (ERA) framework, we examine the network of embedded water flows created through the trade of goods and services and economic development in Flagstaff, Arizona, and associate these flows with the creation of value in sectors of the economy

Embedded ubiquitous services on hospital information systems.

PubMed

Kuroda, Tomohiro; Sasaki, Hiroshi; Suenaga, Takatoshi; Masuda, Yasushi; Yasumuro, Yoshihiro; Hori, Kenta; Ohboshi, Naoki; Takemura, Tadamasa; Chihara, Kunihiro; Yoshihara, Hiroyuki

2012-11-01

A Hospital Information Systems (HIS) have turned a hospital into a gigantic computer with huge computational power, huge storage and wired/wireless local area network. On the other hand, a modern medical device, such as echograph, is a computer system with several functional units connected by an internal network named a bus. Therefore, we can embed such a medical device into the HIS by simply replacing the bus with the local area network. This paper designed and developed two embedded systems, a ubiquitous echograph system and a networked digital camera. Evaluations of the developed systems clearly show that the proposed approach, embedding existing clinical systems into HIS, drastically changes productivity in the clinical field. Once a clinical system becomes a pluggable unit for a gigantic computer system, HIS, the combination of multiple embedded systems with application software designed under deep consideration about clinical processes may lead to the emergence of disruptive innovation in the clinical field.

Constraint Embedding for Multibody System Dynamics

NASA Technical Reports Server (NTRS)

Jain, Abhinandan

2009-01-01

This paper describes a constraint embedding approach for the handling of local closure constraints in multibody system dynamics. The approach uses spatial operator techniques to eliminate local-loop constraints from the system and effectively convert the system into tree-topology systems. This approach allows the direct derivation of recursive O(N) techniques for solving the system dynamics and avoiding the expensive steps that would otherwise be required for handling the closedchain dynamics. The approach is very effective for systems where the constraints are confined to small-subgraphs within the system topology. The paper provides background on the spatial operator O(N) algorithms, the extensions for handling embedded constraints, and concludes with some examples of such constraints.

Product-based Safety Certification for Medical Devices Embedded Software.

PubMed

Neto, José Augusto; Figueiredo Damásio, Jemerson; Monthaler, Paul; Morais, Misael

2015-01-01

Worldwide medical device embedded software certification practices are currently focused on manufacturing best practices. In Brazil, the national regulatory agency does not hold a local certification process for software-intensive medical devices and admits international certification (e.g. FDA and CE) from local and international industry to operate in the Brazilian health care market. We present here a product-based certification process as a candidate process to support the Brazilian regulatory agency ANVISA in medical device software regulation. Center of Strategic Technology for Healthcare (NUTES) medical device embedded software certification is based on a solid safety quality model and has been tested with reasonable success against the Class I risk device Generic Infusion Pump (GIP).

A novel metronidazole fluorescent nanosensor based on graphene quantum dots embedded silica molecularly imprinted polymer.

PubMed

Mehrzad-Samarin, Mina; Faridbod, Farnoush; Dezfuli, Amin Shiralizadeh; Ganjali, Mohammad Reza

2017-06-15

A novel optical nanosensor for detection of Metronidazole in biological samples was reported. Graphene quantum dots embedded silica molecular imprinted polymer (GQDs-embedded SMIP) was synthesized and used as a selective fluorescent probe for Metronidazole detection. The new synthesized GQDs-embedded SMIP showed strong fluorescent emission at 450nm excited at 365nm which quenched in presence of Metronidazole as a template molecule.. The quenching was proportional to the concentration of Metronidazole in a linear range of at least 0.2μM to 15μM. The limit of detection for metronidazole determination was obtained 0.15μM. The nanosensor successfully worked in plasma matrixes. Copyright © 2016 Elsevier B.V. All rights reserved.

Advances in metaheuristics for gene selection and classification of microarray data.

PubMed

Duval, Béatrice; Hao, Jin-Kao

2010-01-01

Gene selection aims at identifying a (small) subset of informative genes from the initial data in order to obtain high predictive accuracy for classification. Gene selection can be considered as a combinatorial search problem and thus be conveniently handled with optimization methods. In this article, we summarize some recent developments of using metaheuristic-based methods within an embedded approach for gene selection. In particular, we put forward the importance and usefulness of integrating problem-specific knowledge into the search operators of such a method. To illustrate the point, we explain how ranking coefficients of a linear classifier such as support vector machine (SVM) can be profitably used to reinforce the search efficiency of Local Search and Evolutionary Search metaheuristic algorithms for gene selection and classification.

A Review of Feature Extraction Software for Microarray Gene Expression Data

PubMed Central

Tan, Ching Siang; Ting, Wai Soon; Mohamad, Mohd Saberi; Chan, Weng Howe; Deris, Safaai; Ali Shah, Zuraini

2014-01-01

When gene expression data are too large to be processed, they are transformed into a reduced representation set of genes. Transforming large-scale gene expression data into a set of genes is called feature extraction. If the genes extracted are carefully chosen, this gene set can extract the relevant information from the large-scale gene expression data, allowing further analysis by using this reduced representation instead of the full size data. In this paper, we review numerous software applications that can be used for feature extraction. The software reviewed is mainly for Principal Component Analysis (PCA), Independent Component Analysis (ICA), Partial Least Squares (PLS), and Local Linear Embedding (LLE). A summary and sources of the software are provided in the last section for each feature extraction method. PMID:25250315

Teleportation of a Toffoli gate among distant solid-state qubits with quantum dots embedded in optical microcavities

PubMed Central

Hu, Shi; Cui, Wen-Xue; Wang, Dong-Yang; Bai, Cheng-Hua; Guo, Qi; Wang, Hong-Fu; Zhu, Ai-Dong; Zhang, Shou

2015-01-01

Teleportation of unitary operations can be viewed as a quantum remote control. The remote realization of robust multiqubit logic gates among distant long-lived qubit registers is a key challenge for quantum computation and quantum information processing. Here we propose a simple and deterministic scheme for teleportation of a Toffoli gate among three spatially separated electron spin qubits in optical microcavities by using local linear optical operations, an auxiliary electron spin, two circularly-polarized entangled photon pairs, photon measurements, and classical communication. We assess the feasibility of the scheme and show that the scheme can be achieved with high average fidelity under the current technology. The scheme opens promising perspectives for constructing long-distance quantum communication and quantum computation networks with solid-state qubits. PMID:26225781

Teleportation of a Toffoli gate among distant solid-state qubits with quantum dots embedded in optical microcavities.

PubMed

Hu, Shi; Cui, Wen-Xue; Wang, Dong-Yang; Bai, Cheng-Hua; Guo, Qi; Wang, Hong-Fu; Zhu, Ai-Dong; Zhang, Shou

2015-07-30

Teleportation of unitary operations can be viewed as a quantum remote control. The remote realization of robust multiqubit logic gates among distant long-lived qubit registers is a key challenge for quantum computation and quantum information processing. Here we propose a simple and deterministic scheme for teleportation of a Toffoli gate among three spatially separated electron spin qubits in optical microcavities by using local linear optical operations, an auxiliary electron spin, two circularly-polarized entangled photon pairs, photon measurements, and classical communication. We assess the feasibility of the scheme and show that the scheme can be achieved with high average fidelity under the current technology. The scheme opens promising perspectives for constructing long-distance quantum communication and quantum computation networks with solid-state qubits.

Flat bands in lattices with non-Hermitian coupling

NASA Astrophysics Data System (ADS)

Leykam, Daniel; Flach, Sergej; Chong, Y. D.

2017-08-01

We study non-Hermitian photonic lattices that exhibit competition between conservative and non-Hermitian (gain/loss) couplings. A bipartite sublattice symmetry enforces the existence of non-Hermitian flat bands, which are typically embedded in an auxiliary dispersive band and give rise to nondiffracting "compact localized states". Band crossings take the form of non-Hermitian degeneracies known as exceptional points. Excitations of the lattice can produce either diffracting or amplifying behaviors. If the non-Hermitian coupling is fine-tuned to generate an effective π flux, the lattice spectrum becomes completely flat, a non-Hermitian analog of Aharonov-Bohm caging in which the magnetic field is replaced by balanced gain and loss. When the effective flux is zero, the non-Hermitian band crossing points give rise to asymmetric diffraction and anomalous linear amplification.

EMBEDDED CLUSTERS IN THE LARGE MAGELLANIC CLOUD USING THE VISTA MAGELLANIC CLOUDS SURVEY

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

Romita, Krista; Lada, Elizabeth; Cioni, Maria-Rosa, E-mail: k.a.romita@ufl.edu, E-mail: elada@ufl.edu, E-mail: mcioni@aip.de

We present initial results of the first large-scale survey of embedded star clusters in molecular clouds in the Large Magellanic Cloud (LMC) using near-infrared imaging from the Visible and Infrared Survey Telescope for Astronomy Magellanic Clouds Survey. We explored a ∼1.65 deg{sup 2} area of the LMC, which contains the well-known star-forming region 30 Doradus as well as ∼14% of the galaxy’s CO clouds, and identified 67 embedded cluster candidates, 45 of which are newly discovered as clusters. We have determined the sizes, luminosities, and masses for these embedded clusters, examined the star formation rates (SFRs) of their corresponding molecularmore » clouds, and made a comparison between the LMC and the Milky Way. Our preliminary results indicate that embedded clusters in the LMC are generally larger, more luminous, and more massive than those in the local Milky Way. We also find that the surface densities of both embedded clusters and molecular clouds is ∼3 times higher than in our local environment, the embedded cluster mass surface density is ∼40 times higher, the SFR is ∼20 times higher, and the star formation efficiency is ∼10 times higher. Despite these differences, the SFRs of the LMC molecular clouds are consistent with the SFR scaling law presented in Lada et al. This consistency indicates that while the conditions of embedded cluster formation may vary between environments, the overall process within molecular clouds may be universal.« less

Free-Form Region Description with Second-Order Pooling.

PubMed

Carreira, João; Caseiro, Rui; Batista, Jorge; Sminchisescu, Cristian

2015-06-01

Semantic segmentation and object detection are nowadays dominated by methods operating on regions obtained as a result of a bottom-up grouping process (segmentation) but use feature extractors developed for recognition on fixed-form (e.g. rectangular) patches, with full images as a special case. This is most likely suboptimal. In this paper we focus on feature extraction and description over free-form regions and study the relationship with their fixed-form counterparts. Our main contributions are novel pooling techniques that capture the second-order statistics of local descriptors inside such free-form regions. We introduce second-order generalizations of average and max-pooling that together with appropriate non-linearities, derived from the mathematical structure of their embedding space, lead to state-of-the-art recognition performance in semantic segmentation experiments without any type of local feature coding. In contrast, we show that codebook-based local feature coding is more important when feature extraction is constrained to operate over regions that include both foreground and large portions of the background, as typical in image classification settings, whereas for high-accuracy localization setups, second-order pooling over free-form regions produces results superior to those of the winning systems in the contemporary semantic segmentation challenges, with models that are much faster in both training and testing.

Raman measurements of Kevlar-29 fiber pull-out test at different strain levels

NASA Astrophysics Data System (ADS)

Wang, Quan; Lei, Zhenkun; Kang, Yilan; Qiu, Wei

2008-11-01

This paper adopted Kevlar-29 fiber monofilament embedding technology to prepare fiber/ epoxy resin tensile specimen. The specimen was pulled on a homemade and portable mini-loading device. At the same time micro-Raman spectroscopy is introduced to detect the distributions of stress on the embedded fiber at different strain levels. The characteristic peak shift of the 1610 cm-1 in Raman band has a linear relationship with the strain or stress. The experimental results show that the fiber axial stress decreases gradually from the embedded fiber-start to the embedded fiber-end at the same strain level. At different strain levels, the fiber axial stress increases along with the applied load. It reveals that there is a larger fiber axial stress distribution under a larger strain level. And the stress transfer is realized gradually from the embedded fiber-start to the fiber-end. Stress concentration exists in the embedded fiber-end, which is a dangerous region for interfacial debonding easily.

Variable neighborhood search to solve the vehicle routing problem for hazardous materials transportation.

PubMed

Bula, Gustavo Alfredo; Prodhon, Caroline; Gonzalez, Fabio Augusto; Afsar, H Murat; Velasco, Nubia

2017-02-15

This work focuses on the Heterogeneous Fleet Vehicle Routing problem (HFVRP) in the context of hazardous materials (HazMat) transportation. The objective is to determine a set of routes that minimizes the total expected routing risk. This is a nonlinear function, and it depends on the vehicle load and the population exposed when an incident occurs. Thus, a piecewise linear approximation is used to estimate it. For solving the problem, a variant of the Variable Neighborhood Search (VNS) algorithm is employed. To improve its performance, a post-optimization procedure is implemented via a Set Partitioning (SP) problem. The SP is solved on a pool of routes obtained from executions of the local search procedure embedded on the VNS. The algorithm is tested on two sets of HFVRP instances based on literature with up to 100 nodes, these instances are modified to include vehicle and arc risk parameters. The results are competitive in terms of computational efficiency and quality attested by a comparison with Mixed Integer Linear Programming (MILP) previously proposed. Copyright © 2016 Elsevier B.V. All rights reserved.

Three dimensional modelling of earthquake rupture cycles on frictional faults

NASA Astrophysics Data System (ADS)

Simpson, Guy; May, Dave

2017-04-01

We are developing an efficient MPI-parallel numerical method to simulate earthquake sequences on preexisting faults embedding within a three dimensional viscoelastic half-space. We solve the velocity form of the elasto(visco)dynamic equations using a continuous Galerkin Finite Element Method on an unstructured pentahedral mesh, which thus permits local spatial refinement in the vicinity of the fault. Friction sliding is coupled to the viscoelastic solid via rate- and state-dependent friction laws using the split-node technique. Our coupled formulation employs a picard-type non-linear solver with a fully implicit, first order accurate time integrator that utilises an adaptive time step that efficiently evolves the system through multiple seismic cycles. The implementation leverages advanced parallel solvers, preconditioners and linear algebra from the Portable Extensible Toolkit for Scientific Computing (PETSc) library. The model can treat heterogeneous frictional properties and stress states on the fault and surrounding solid as well as non-planar fault geometries. Preliminary tests show that the model successfully reproduces dynamic rupture on a vertical strike-slip fault in a half-space governed by rate-state friction with the ageing law.

Brain tumor segmentation based on local independent projection-based classification.

PubMed

Huang, Meiyan; Yang, Wei; Wu, Yao; Jiang, Jun; Chen, Wufan; Feng, Qianjin

2014-10-01

Brain tumor segmentation is an important procedure for early tumor diagnosis and radiotherapy planning. Although numerous brain tumor segmentation methods have been presented, enhancing tumor segmentation methods is still challenging because brain tumor MRI images exhibit complex characteristics, such as high diversity in tumor appearance and ambiguous tumor boundaries. To address this problem, we propose a novel automatic tumor segmentation method for MRI images. This method treats tumor segmentation as a classification problem. Additionally, the local independent projection-based classification (LIPC) method is used to classify each voxel into different classes. A novel classification framework is derived by introducing the local independent projection into the classical classification model. Locality is important in the calculation of local independent projections for LIPC. Locality is also considered in determining whether local anchor embedding is more applicable in solving linear projection weights compared with other coding methods. Moreover, LIPC considers the data distribution of different classes by learning a softmax regression model, which can further improve classification performance. In this study, 80 brain tumor MRI images with ground truth data are used as training data and 40 images without ground truth data are used as testing data. The segmentation results of testing data are evaluated by an online evaluation tool. The average dice similarities of the proposed method for segmenting complete tumor, tumor core, and contrast-enhancing tumor on real patient data are 0.84, 0.685, and 0.585, respectively. These results are comparable to other state-of-the-art methods.

Strain monitoring of bismaleimide composites using embedded microcavity sensor

NASA Astrophysics Data System (ADS)

Kaur, Amardeep; Anandan, Sudharshan; Yuan, Lei; Watkins, Steve E.; Chandrashekhara, K.; Xiao, Hai; Phan, Nam

2016-03-01

A type of extrinsic Fabry-Perot interferometer (EFPI) fiber optic sensor, i.e., the microcavity strain sensor, is demonstrated for embedded, high-temperature applications. The sensor is fabricated using a femtosecond (fs) laser. The fs-laser-based fabrication makes the sensor thermally stable to sustain operating temperatures as high as 800°C. The sensor has low sensitivity toward the temperature as compared to its response toward the applied strain. The performance of the EFPI sensor is tested in an embedded application. The host material is carbon fiber/bismaleimide (BMI) composite laminate that offer thermally stable characteristics at high ambient temperatures. The sensor exhibits highly linear response toward the temperature and strain. Analytical work done with embedded optical-fiber sensors using the out-of-autoclave BMI laminate was limited until now. The work presented in this paper offers an insight into the strain and temperature interactions of the embedded sensors with the BMI composites.

Plasmonic nanoparticles embedded in single crystals synthesized by gold ion implantation for enhanced optical nonlinearity and efficient Q-switched lasing.

PubMed

Nie, W J; Zhang, Y X; Yu, H H; Li, R; He, R Y; Dong, N N; Wang, J; Hübner, R; Böttger, R; Zhou, S Q; Amekura, H; Chen, F

2018-03-01

We report on the synthesis of embedded gold (Au) nanoparticles (NPs) in Nd:YAG single crystals using ion implantation and subsequent thermal annealing. Both linear and nonlinear absorption of the Nd:YAG crystals have been enhanced significantly due to the embedded Au NPs, which is induced by the surface plasmon resonance (SPR) effect in the visible light wavelength band. Particularly, through a typical Z-scan system excited by a femtosecond laser at 515 nm within the SPR band, the nonlinear absorption coefficients of crystals with Au NPs have been observed to be nearly 5 orders of magnitude larger than that without Au NPs. This giant enhancement of nonlinear absorption properties is correlated with the saturable absorption (SA) effect, which is the basis of passive Q-switching or mode-locking for pulsed laser generation. In addition, the linear and nonlinear absorption enhancement could be tailored by varying the fluence of implanted Au + ions, corresponding to the NP size and concentration modulation. Finally, the Nd:YAG wafer with embedded Au NPs has been applied as a saturable absorber in a Pr:LuLiF 4 crystal laser cavity, and efficient pulsed laser generation at 639 nm has been realized, which presents superior performance to the MoS 2 saturable absorber based system. This work opens an avenue to enhance and modulate the nonlinearities of dielectrics by embedding plasmonic Au NPs for efficient pulsed laser operation.

Permutation entropy with vector embedding delays

NASA Astrophysics Data System (ADS)

Little, Douglas J.; Kane, Deb M.

2017-12-01

Permutation entropy (PE) is a statistic used widely for the detection of structure within a time series. Embedding delay times at which the PE is reduced are characteristic timescales for which such structure exists. Here, a generalized scheme is investigated where embedding delays are represented by vectors rather than scalars, permitting PE to be calculated over a (D -1 ) -dimensional space, where D is the embedding dimension. This scheme is applied to numerically generated noise, sine wave and logistic map series, and experimental data sets taken from a vertical-cavity surface emitting laser exhibiting temporally localized pulse structures within the round-trip time of the laser cavity. Results are visualized as PE maps as a function of embedding delay, with low PE values indicating combinations of embedding delays where correlation structure is present. It is demonstrated that vector embedding delays enable identification of structure that is ambiguous or masked, when the embedding delay is constrained to scalar form.

Multiscale Methods for Nuclear Reactor Analysis

NASA Astrophysics Data System (ADS)

Collins, Benjamin S.

The ability to accurately predict local pin powers in nuclear reactors is necessary to understand the mechanisms that cause fuel pin failure during steady state and transient operation. In the research presented here, methods are developed to improve the local solution using high order methods with boundary conditions from a low order global solution. Several different core configurations were tested to determine the improvement in the local pin powers compared to the standard techniques, that use diffusion theory and pin power reconstruction (PPR). Two different multiscale methods were developed and analyzed; the post-refinement multiscale method and the embedded multiscale method. The post-refinement multiscale methods use the global solution to determine boundary conditions for the local solution. The local solution is solved using either a fixed boundary source or an albedo boundary condition; this solution is "post-refinement" and thus has no impact on the global solution. The embedded multiscale method allows the local solver to change the global solution to provide an improved global and local solution. The post-refinement multiscale method is assessed using three core designs. When the local solution has more energy groups, the fixed source method has some difficulties near the interface: however the albedo method works well for all cases. In order to remedy the issue with boundary condition errors for the fixed source method, a buffer region is used to act as a filter, which decreases the sensitivity of the solution to the boundary condition. Both the albedo and fixed source methods benefit from the use of a buffer region. Unlike the post-refinement method, the embedded multiscale method alters the global solution. The ability to change the global solution allows for refinement in areas where the errors in the few group nodal diffusion are typically large. The embedded method is shown to improve the global solution when it is applied to a MOX/LEU assembly interface, the fuel/reflector interface, and assemblies where control rods are inserted. The embedded method also allows for multiple solution levels to be applied in a single calculation. The addition of intermediate levels to the solution improves the accuracy of the method. Both multiscale methods considered here have benefits and drawbacks, but both can provide improvements over the current PPR methodology.

Self-consistent calculations for the electronic structure of a vacancy in copper. A solution of the embedding problem

NASA Astrophysics Data System (ADS)

Zeller, R.; Braspenning, P. J.

1982-06-01

The charge density and the local density of states for a vacancy in Cu and for the first shell of Cu neighbours are calculated by the KKR-Green's function technique. The muffin-tin potentials for the vacancy and the neighbour shell atoms are determined self-consistently in the local density approximation of density functional theory. By the use of the proper host Green's function the embedding of this cluster of 13 perturbed muffin-tins into the infinite array of bulk Cu muffin-tin potentials is described rigorously, thus representing a solution of the embedding problem. The calculations demonstrate a rather large charge transfer of 1.1 electrons from the first neighbour shell to the vacancy.

Global embeddings for branes at toric singularities

NASA Astrophysics Data System (ADS)

Balasubramanian, Vijay; Berglund, Per; Braun, Volker; García-Etxebarria, Iñaki

2012-10-01

We describe how local toric singularities, including the Toric Lego construction, can be embedded in compact Calabi-Yau manifolds. We study in detail the addition of D-branes, including non-compact flavor branes as typically used in semi-realistic model building. The global geometry provides constraints on allowable local models. As an illustration of our discussion we focus on D3 and D7-branes on (the partially resolved) ( dP 0)3 singularity, its embedding in a specific Calabi-Yau manifold as a hypersurface in a toric variety, the related type IIB orientifold compactification, as well as the corresponding F-theory uplift. Our techniques generalize naturally to complete intersections, and to a large class of F-theory backgrounds with singularities.

Minimum curvilinearity to enhance topological prediction of protein interactions by network embedding

PubMed Central

Cannistraci, Carlo Vittorio; Alanis-Lobato, Gregorio; Ravasi, Timothy

2013-01-01

Motivation: Most functions within the cell emerge thanks to protein–protein interactions (PPIs), yet experimental determination of PPIs is both expensive and time-consuming. PPI networks present significant levels of noise and incompleteness. Predicting interactions using only PPI-network topology (topological prediction) is difficult but essential when prior biological knowledge is absent or unreliable. Methods: Network embedding emphasizes the relations between network proteins embedded in a low-dimensional space, in which protein pairs that are closer to each other represent good candidate interactions. To achieve network denoising, which boosts prediction performance, we first applied minimum curvilinear embedding (MCE), and then adopted shortest path (SP) in the reduced space to assign likelihood scores to candidate interactions. Furthermore, we introduce (i) a new valid variation of MCE, named non-centred MCE (ncMCE); (ii) two automatic strategies for selecting the appropriate embedding dimension; and (iii) two new randomized procedures for evaluating predictions. Results: We compared our method against several unsupervised and supervisedly tuned embedding approaches and node neighbourhood techniques. Despite its computational simplicity, ncMCE-SP was the overall leader, outperforming the current methods in topological link prediction. Conclusion: Minimum curvilinearity is a valuable non-linear framework that we successfully applied to the embedding of protein networks for the unsupervised prediction of novel PPIs. The rationale for our approach is that biological and evolutionary information is imprinted in the non-linear patterns hidden behind the protein network topology, and can be exploited for predicting new protein links. The predicted PPIs represent good candidates for testing in high-throughput experiments or for exploitation in systems biology tools such as those used for network-based inference and prediction of disease-related functional modules. Availability: https://sites.google.com/site/carlovittoriocannistraci/home Contact: kalokagathos.agon@gmail.com or timothy.ravasi@kaust.edu.sa Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23812985

EMBEDDED LENSING TIME DELAYS, THE FERMAT POTENTIAL, AND THE INTEGRATED SACHS–WOLFE EFFECT

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

Chen, Bin; Kantowski, Ronald; Dai, Xinyu, E-mail: bchen3@fsu.edu

2015-05-01

We derive the Fermat potential for a spherically symmetric lens embedded in a Friedman–Lemaître–Robertson–Walker cosmology and use it to investigate the late-time integrated Sachs–Wolfe (ISW) effect, i.e., secondary temperature fluctuations in the cosmic microwave background (CMB) caused by individual large-scale clusters and voids. We present a simple analytical expression for the temperature fluctuation in the CMB across such a lens as a derivative of the lens’ Fermat potential. This formalism is applicable to both linear and nonlinear density evolution scenarios, to arbitrarily large density contrasts, and to all open and closed background cosmologies. It is much simpler to use andmore » makes the same predictions as conventional approaches. In this approach the total temperature fluctuation can be split into a time-delay part and an evolutionary part. Both parts must be included for cosmic structures that evolve and both can be equally important. We present very simple ISW models for cosmic voids and galaxy clusters to illustrate the ease of use of our formalism. We use the Fermat potentials of simple cosmic void models to compare predicted ISW effects with those recently extracted from WMAP and Planck data by stacking large cosmic voids using the aperture photometry method. If voids in the local universe with large density contrasts are no longer evolving we find that the time delay contribution alone predicts values consistent with the measurements. However, we find that for voids still evolving linearly, the evolutionary contribution cancels a significant part of the time delay contribution and results in predicted signals that are much smaller than recently observed.« less

A set-covering based heuristic algorithm for the periodic vehicle routing problem.

PubMed

Cacchiani, V; Hemmelmayr, V C; Tricoire, F

2014-01-30

We present a hybrid optimization algorithm for mixed-integer linear programming, embedding both heuristic and exact components. In order to validate it we use the periodic vehicle routing problem (PVRP) as a case study. This problem consists of determining a set of minimum cost routes for each day of a given planning horizon, with the constraints that each customer must be visited a required number of times (chosen among a set of valid day combinations), must receive every time the required quantity of product, and that the number of routes per day (each respecting the capacity of the vehicle) does not exceed the total number of available vehicles. This is a generalization of the well-known vehicle routing problem (VRP). Our algorithm is based on the linear programming (LP) relaxation of a set-covering-like integer linear programming formulation of the problem, with additional constraints. The LP-relaxation is solved by column generation, where columns are generated heuristically by an iterated local search algorithm. The whole solution method takes advantage of the LP-solution and applies techniques of fixing and releasing of the columns as a local search, making use of a tabu list to avoid cycling. We show the results of the proposed algorithm on benchmark instances from the literature and compare them to the state-of-the-art algorithms, showing the effectiveness of our approach in producing good quality solutions. In addition, we report the results on realistic instances of the PVRP introduced in Pacheco et al. (2011)  [24] and on benchmark instances of the periodic traveling salesman problem (PTSP), showing the efficacy of the proposed algorithm on these as well. Finally, we report the new best known solutions found for all the tested problems.

A set-covering based heuristic algorithm for the periodic vehicle routing problem

PubMed Central

Cacchiani, V.; Hemmelmayr, V.C.; Tricoire, F.

2014-01-01

We present a hybrid optimization algorithm for mixed-integer linear programming, embedding both heuristic and exact components. In order to validate it we use the periodic vehicle routing problem (PVRP) as a case study. This problem consists of determining a set of minimum cost routes for each day of a given planning horizon, with the constraints that each customer must be visited a required number of times (chosen among a set of valid day combinations), must receive every time the required quantity of product, and that the number of routes per day (each respecting the capacity of the vehicle) does not exceed the total number of available vehicles. This is a generalization of the well-known vehicle routing problem (VRP). Our algorithm is based on the linear programming (LP) relaxation of a set-covering-like integer linear programming formulation of the problem, with additional constraints. The LP-relaxation is solved by column generation, where columns are generated heuristically by an iterated local search algorithm. The whole solution method takes advantage of the LP-solution and applies techniques of fixing and releasing of the columns as a local search, making use of a tabu list to avoid cycling. We show the results of the proposed algorithm on benchmark instances from the literature and compare them to the state-of-the-art algorithms, showing the effectiveness of our approach in producing good quality solutions. In addition, we report the results on realistic instances of the PVRP introduced in Pacheco et al. (2011)  [24] and on benchmark instances of the periodic traveling salesman problem (PTSP), showing the efficacy of the proposed algorithm on these as well. Finally, we report the new best known solutions found for all the tested problems. PMID:24748696

Local electric dipole moments for periodic systems via density functional theory embedding.

PubMed

Luber, Sandra

2014-12-21

We describe a novel approach for the calculation of local electric dipole moments for periodic systems. Since the position operator is ill-defined in periodic systems, maximally localized Wannier functions based on the Berry-phase approach are usually employed for the evaluation of local contributions to the total electric dipole moment of the system. We propose an alternative approach: within a subsystem-density functional theory based embedding scheme, subset electric dipole moments are derived without any additional localization procedure, both for hybrid and non-hybrid exchange-correlation functionals. This opens the way to a computationally efficient evaluation of local electric dipole moments in (molecular) periodic systems as well as their rigorous splitting into atomic electric dipole moments. As examples, Infrared spectra of liquid ethylene carbonate and dimethyl carbonate are presented, which are commonly employed as solvents in Lithium ion batteries.

Electromagnetic Scattering by Multiple Cavities Embedded in the Infinite 2D Ground Plane

DTIC Science & Technology

2014-07-01

Electromagnetic Scattering by Multiple Cavities Embedded in the Infinite 2D Ground Plane Peijun Li 1 and Aihua W. Wood 2 1 Department of...of the electromagnetic wave scattering by multiple open cavities, which are embedded in an infinite two-dimensional ground plane . By introducing a...equation, variational formulation. I. INTRODUCTION A cavity is referred to as a local perturbation of the infinite ground plane . Given the cavity

Support for a Link between the Local Processing Bias and Social Deficits in Autism: An Investigation of Embedded Figures Test Performance in Non-Clinical Individuals

ERIC Educational Resources Information Center

Russell-Smith, Suzanna N.; Maybery, Murray T.; Bayliss, Donna M.; Sng, Adelln A. H.

2012-01-01

The aim of this investigation was to explore the degree to which specific subsets of autistic-like traits relate to performance on the Embedded Figures Test (Witkin et al. in A manual for the embedded figures test. Consulting Psychologists Press, Palo Alto, CA, 1971). In the first group-based investigation with this focus, students were selected…

Embedded I&C for Extreme Environments

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

Kisner, Roger A.

2016-04-01

This project uses embedded instrumentation and control (I&C) technologies to demonstrate potential performance gains of nuclear power plant components in extreme environments. Extreme environments include high temperature, radiation, high pressure, high vibration, and high EMI conditions. For extreme environments, performance gains arise from moment-to-moment sensing of local variables and immediate application of local feedback control. Planning for embedding I&C during early system design phases contrasts with the traditional, serial design approach that incorporates minimal I&C after mechanical and electrical design is complete. The demonstration application involves the development and control of a novel, proof-of-concept motor/pump design. The motor and pumpmore » combination operate within the fluid environment, eliminating the need for rotating seals. Actively controlled magnetic bearings also replace failure-prone mechanical contact bearings that typically suspend rotating components. Such as design has the potential to significantly enhance the reliability and life of the pumping system and would not be possible without embedded I&C.« less

Diamond Nanogel-Embedded Contact Lenses Mediate Lysozyme-Dependent Therapeutic Release

PubMed Central

2015-01-01

Temporarily implanted devices, such as drug-loaded contact lenses, are emerging as the preferred treatment method for ocular diseases like glaucoma. Localizing the delivery of glaucoma drugs, such as timolol maleate (TM), can minimize adverse effects caused by systemic administration. Although eye drops and drug-soaked lenses allow for local treatment, their utility is limited by burst release and a lack of sustained therapeutic delivery. Additionally, wet transportation and storage of drug-soaked lenses result in drug loss due to elution from the lenses. Here we present a nanodiamond (ND)-embedded contact lens capable of lysozyme-triggered release of TM for sustained therapy. We find that ND-embedded lenses composed of enzyme-cleavable polymers allow for controlled and sustained release of TM in the presence of lysozyme. Retention of drug activity is verified in primary human trabecular meshwork cells. These results demonstrate the translational potential of an ND-embedded lens capable of drug sequestration and enzyme activation. PMID:24506583

Topology optimization of embedded piezoelectric actuators considering control spillover effects

NASA Astrophysics Data System (ADS)

Gonçalves, Juliano F.; De Leon, Daniel M.; Perondi, Eduardo A.

2017-02-01

This article addresses the problem of active structural vibration control by means of embedded piezoelectric actuators. The topology optimization method using the solid isotropic material with penalization (SIMP) approach is employed in this work to find the optimum design of actuators taken into account the control spillover effects. A coupled finite element model of the structure is derived assuming a two-phase material and this structural model is written into the state-space representation. The proposed optimization formulation aims to determine the distribution of piezoelectric material which maximizes the controllability for a given vibration mode. The undesirable effects of the feedback control on the residual modes are limited by including a spillover constraint term containing the residual controllability Gramian eigenvalues. The optimization of the shape and placement of the conventionally embedded piezoelectric actuators are performed using a Sequential Linear Programming (SLP) algorithm. Numerical examples are presented considering the control of the bending vibration modes for a cantilever and a fixed beam. A Linear-Quadratic Regulator (LQR) is synthesized for each case of controlled structure in order to compare the influence of the additional constraint.

PdCo alloy nanoparticle-embedded carbon nanofiber for ultrasensitive nonenzymatic detection of hydrogen peroxide and nitrite.

PubMed

Liu, Dong; Guo, Qiaohui; Zhang, Xueping; Hou, Haoqing; You, Tianyan

2015-07-15

PdCo alloy nanoparticle-embedded carbon nanofiber (PdCo/CNF) prepared by electrospinning and thermal treatment was employed as a high-performance platform for the determination of hydrogen peroxide and nitrite. The as-obtained PdCo/CNF were characterized by transmission electron microscopy, energy-dispersive X-ray spectroscopy and X-ray diffraction. Electrochemical impedance spectroscopy, cyclic voltammetry and differential pulse voltammetry were employed to investigate the electrochemical behaviors of the resultant biosensor. The proposed PdCo/CNF-based biosensor showed excellent analytical performances toward hydrogen peroxide (detection limit: 0.1 μM; linear range: 0.2 μM-23.5 mM) and nitrite (detection limit: 0.2 μM; linear range: 0.4-30 μM and 30-400 μM). The superior analytical properties could be attributed to the synergic effect and firmly embedment of well-dispersed PdCo alloy nanoparticles. These attractive electrochemical properties make this robust electrode material promising for the development of effective electrochemical sensors. Copyright © 2015 Elsevier Inc. All rights reserved.

Experimental analysis of a mobile health system for mood disorders.

PubMed

Massey, Tammara; Marfia, Gustavo; Potkonjak, Miodrag; Sarrafzadeh, Majid

2010-03-01

Depression is one of the leading causes of disability. Methods are needed to quantitatively classify emotions in order to better understand and treat mood disorders. This research proposes techniques to improve communication in body sensor network (BSN) that gathers data on the affective states of the patient. These BSNs can continuously monitor, discretely quantify, and classify a patient's depressive states. In addition, data on the patient's lifestyle can be correlated with his/her physiological conditions to identify how various stimuli trigger symptoms. This continuous stream of data is an improvement over a snapshot of localized symptoms that a doctor often collects during a medical examination. Our research first quantifies how the body interferes with communication in a BSN and detects a pattern between the line of sight of an embedded device and its reception rate. Then, a mathematical model of the data using linear programming techniques determines the optimal placement and number of sensors in a BSN to improve communication. Experimental results show that the optimal placement of embedded devices can reduce power cost up to 27% and reduce hardware costs up to 47%. This research brings researchers a step closer to continuous, real-time systemic monitoring that will allow one to analyze the dynamic human physiology and understand, diagnosis, and treat mood disorders.

A novel sample preparation method to avoid influence of embedding medium during nano-indentation

NASA Astrophysics Data System (ADS)

Meng, Yujie; Wang, Siqun; Cai, Zhiyong; Young, Timothy M.; Du, Guanben; Li, Yanjun

2013-02-01

The effect of the embedding medium on the nano-indentation measurements of lignocellulosic materials was investigated experimentally using nano-indentation. Both the reduced elastic modulus and the hardness of non-embedded cell walls were found to be lower than those of the embedded samples, proving that the embedding medium used for specimen preparation on cellulosic material during nano-indentation can modify cell-wall properties. This leads to structural and chemical changes in the cell-wall constituents, changes that may significantly alter the material properties. Further investigation was carried out to detect the influence of different vacuum times on the cell-wall mechanical properties during the embedding procedure. Interpretation of the statistical analysis revealed no linear relationships between vacuum time and the mechanical properties of cell walls. The quantitative measurements confirm that low-viscosity resin has a rapid penetration rate early in the curing process. Finally, a novel sample preparation method aimed at preventing resin diffusion into lignocellulosic cell walls was developed using a plastic film to wrap the sample before embedding. This method proved to be accessible and straightforward for many kinds of lignocellulosic material, but is especially suitable for small, soft samples.

Visual processing in adolescents with autism spectrum disorder: evidence from embedded figures and configural superiority tests.

PubMed

Dillen, Claudia; Steyaert, Jean; Op de Beeck, Hans P; Boets, Bart

2015-05-01

The embedded figures test has often been used to reveal weak central coherence in individuals with autism spectrum disorder (ASD). Here, we administered a more standardized automated version of the embedded figures test in combination with the configural superiority task, to investigate the effect of contextual modulation on local feature detection in 23 adolescents with ASD and 26 matched typically developing controls. On both tasks both groups performed largely similarly in terms of accuracy and reaction time, and both displayed the contextual modulation effect. This indicates that individuals with ASD are equally sensitive compared to typically developing individuals to the contextual effects of the task and that there is no evidence for a local processing bias in adolescents with ASD.

Detection, Localization and Quantification of Impact Events on a Stiffened Composite Panel with Embedded Fiber Bragg Grating Sensor Networks

PubMed Central

Lamberti, Alfredo; Luyckx, Geert; Van Paepegem, Wim; Rezayat, Ali; Vanlanduit, Steve

2017-01-01

Nowadays, it is possible to manufacture smart composite materials with embedded fiber optic sensors. These sensors can be exploited during the composites’ operating life to identify occurring damages such as delaminations. For composite materials adopted in the aviation and wind energy sector, delaminations are most often caused by impacts with external objects. The detection, localization and quantification of such impacts are therefore crucial for the prevention of catastrophic events. In this paper, we demonstrate the feasibility to perform impact identification in smart composite structures with embedded fiber optic sensors. For our analyses, we manufactured a carbon fiber reinforced plate in which we embedded a distributed network of fiber Bragg grating (FBG) sensors. We impacted the plate with a modal hammer and we identified the impacts by processing the FBG data with an improved fast phase correlation (FPC) algorithm in combination with a variable selective least squares (VS-LS) inverse solver approach. A total of 164 impacts distributed on 41 possible impact locations were analyzed. We compared our methodology with the traditional P-Inv based approach. In terms of impact localization, our methodology performed better in 70.7% of the cases. An improvement on the impact time domain reconstruction was achieved in 95.1% of the cases. PMID:28368319

Detection, Localization and Quantification of Impact Events on a Stiffened Composite Panel with Embedded Fiber Bragg Grating Sensor Networks.

PubMed

Lamberti, Alfredo; Luyckx, Geert; Van Paepegem, Wim; Rezayat, Ali; Vanlanduit, Steve

2017-04-01

Nowadays, it is possible to manufacture smart composite materials with embedded fiber optic sensors. These sensors can be exploited during the composites' operating life to identify occurring damages such as delaminations. For composite materials adopted in the aviation and wind energy sector, delaminations are most often caused by impacts with external objects. The detection, localization and quantification of such impacts are therefore crucial for the prevention of catastrophic events. In this paper, we demonstrate the feasibility to perform impact identification in smart composite structures with embedded fiber optic sensors. For our analyses, we manufactured a carbon fiber reinforced plate in which we embedded a distributed network of fiber Bragg grating (FBG) sensors. We impacted the plate with a modal hammer and we identified the impacts by processing the FBG data with an improved fast phase correlation (FPC) algorithm in combination with a variable selective least squares (VS-LS) inverse solver approach. A total of 164 impacts distributed on 41 possible impact locations were analyzed. We compared our methodology with the traditional P-Inv based approach. In terms of impact localization, our methodology performed better in 70.7% of the cases. An improvement on the impact time domain reconstruction was achieved in 95 . 1 % of the cases.

Correlative Imaging of Fluorescent Proteins in Resin-Embedded Plant Material1

PubMed Central

Bell, Karen; Mitchell, Steve; Paultre, Danae; Posch, Markus; Oparka, Karl

2013-01-01

Fluorescent proteins (FPs) were developed for live-cell imaging and have revolutionized cell biology. However, not all plant tissues are accessible to live imaging using confocal microscopy, necessitating alternative approaches for protein localization. An example is the phloem, a tissue embedded deep within plant organs and sensitive to damage. To facilitate accurate localization of FPs within recalcitrant tissues, we developed a simple method for retaining FPs after resin embedding. This method is based on low-temperature fixation and dehydration, followed by embedding in London Resin White, and avoids the need for cryosections. We show that a palette of FPs can be localized in plant tissues while retaining good structural cell preservation, and that the polymerized block face can be counterstained with cell wall probes. Using this method we have been able to image green fluorescent protein-labeled plasmodesmata to a depth of more than 40 μm beneath the resin surface. Using correlative light and electron microscopy of the phloem, we were able to locate the same FP-labeled sieve elements in semithin and ultrathin sections. Sections were amenable to antibody labeling, and allowed a combination of confocal and superresolution imaging (three-dimensional-structured illumination microscopy) on the same cells. These correlative imaging methods should find several uses in plant cell biology. PMID:23457228

The role of axis embedding on rigid rotor decomposition analysis of variational rovibrational wave functions.

PubMed

Szidarovszky, Tamás; Fábri, Csaba; Császár, Attila G

2012-05-07

Approximate rotational characterization of variational rovibrational wave functions via the rigid rotor decomposition (RRD) protocol is developed for Hamiltonians based on arbitrary sets of internal coordinates and axis embeddings. An efficient and general procedure is given that allows employing the Eckart embedding with arbitrary polyatomic Hamiltonians through a fully numerical approach. RRD tables formed by projecting rotational-vibrational wave functions into products of rigid-rotor basis functions and previously determined vibrational eigenstates yield rigid-rotor labels for rovibrational eigenstates by selecting the largest overlap. Embedding-dependent RRD analyses are performed, up to high energies and rotational excitations, for the H(2) (16)O isotopologue of the water molecule. Irrespective of the embedding chosen, the RRD procedure proves effective in providing unambiguous rotational assignments at low energies and J values. Rotational labeling of rovibrational states of H(2) (16)O proves to be increasingly difficult beyond about 10,000 cm(-1), close to the barrier to linearity of the water molecule. For medium energies and excitations the Eckart embedding yields the largest RRD coefficients, thus providing the largest number of unambiguous rotational labels.

Effect of Age on Complexity and Causality of the Cardiovascular Control: Comparison between Model-Based and Model-Free Approaches

PubMed Central

Porta, Alberto; Faes, Luca; Bari, Vlasta; Marchi, Andrea; Bassani, Tito; Nollo, Giandomenico; Perseguini, Natália Maria; Milan, Juliana; Minatel, Vinícius; Borghi-Silva, Audrey; Takahashi, Anielle C. M.; Catai, Aparecida M.

2014-01-01

The proposed approach evaluates complexity of the cardiovascular control and causality among cardiovascular regulatory mechanisms from spontaneous variability of heart period (HP), systolic arterial pressure (SAP) and respiration (RESP). It relies on construction of a multivariate embedding space, optimization of the embedding dimension and a procedure allowing the selection of the components most suitable to form the multivariate embedding space. Moreover, it allows the comparison between linear model-based (MB) and nonlinear model-free (MF) techniques and between MF approaches exploiting local predictability (LP) and conditional entropy (CE). The framework was applied to study age-related modifications of complexity and causality in healthy humans in supine resting (REST) and during standing (STAND). We found that: 1) MF approaches are more efficient than the MB method when nonlinear components are present, while the reverse situation holds in presence of high dimensional embedding spaces; 2) the CE method is the least powerful in detecting age-related trends; 3) the association of HP complexity on age suggests an impairment of cardiac regulation and response to STAND; 4) the relation of SAP complexity on age indicates a gradual increase of sympathetic activity and a reduced responsiveness of vasomotor control to STAND; 5) the association from SAP to HP on age during STAND reveals a progressive inefficiency of baroreflex; 6) the reduced connection from HP to SAP with age might be linked to the progressive exploitation of Frank-Starling mechanism at REST and to the progressive increase of peripheral resistances during STAND; 7) at REST the diminished association from RESP to HP with age suggests a vagal withdrawal and a gradual uncoupling between respiratory activity and heart; 8) the weakened connection from RESP to SAP with age might be related to the progressive increase of left ventricular thickness and vascular stiffness and to the gradual decrease of respiratory sinus arrhythmia. PMID:24586796

An orthodontic bracket embedded in the medial pterygoid surface: a case report.

PubMed

Wilmott, Sheryl E; Ikeagwuani, Okechukwu; McLeod, Niall M H

2016-01-08

There is a potential risk that orthodontic brackets can become dislodged into the aerodigestive tract. This case illustrates the management of an orthodontic bracket, which became embedded in the deep tissues of the oropharynx. We aim to highlight the potential risk misplaced dental instruments and materials pose, including that they may become embedded in the soft tissues of the throat and suggest that that this possibility should be considered when they cannot be localized.

An orthodontic bracket embedded in the medial pterygoid surface: a case report.

PubMed

Wilmott, Sheryl E; Ikeagwuani, Okechukwu; McLeod, Niall M H

2016-03-01

There is a potential risk that orthodontic brackets can become dislodged into the aerodigestive tract. This case illustrates the management of an orthodontic bracket, which became embedded in the deep tissues of the oropharynx. We aim to highlight the potential risk misplaced dental instruments and materials pose, including that they may become embedded in the soft tissues of the throat and suggest that that this possibility should be considered when they cannot be localized.

Embedded System Implementation of Sound Localization in Proximal Region

NASA Astrophysics Data System (ADS)

Iwanaga, Nobuyuki; Matsumura, Tomoya; Yoshida, Akihiro; Kobayashi, Wataru; Onoye, Takao

A sound localization method in the proximal region is proposed, which is based on a low-cost 3D sound localization algorithm with the use of head-related transfer functions (HRTFs). The auditory parallax model is applied to the current algorithm so that more accurate HRTFs can be used for sound localization in the proximal region. In addition, head-shadowing effects based on rigid-sphere model are reproduced in the proximal region by means of a second-order IIR filter. A subjective listening test demonstrates the effectiveness of the proposed method. Embedded system implementation of the proposed method is also described claiming that the proposed method improves sound effects in the proximal region only with 5.1% increase of memory capacity and 8.3% of computational costs.

Localization of Stable and Chaotic Nonpropagating Structures in Nonlinear Mesoscopic Lattices.

NASA Astrophysics Data System (ADS)

Greenfield, Alan Barry

Recent developments in the study of non-linear localized states, especially non-propagating ones, are outlined. Theoretical models of linear and nonlinear states in a lattice of coupled pendulums and related systems are reviewed. Particular attention is paid to those states which can be described by the Nonlinear Schrodinger equation as well as states where two modes can coexist and states exhibiting chaos. Measurement of localized stable and chaotic states in a 35 site physical pendulum lattice is reported. Various measurement techniques that were used are explained. States that were measured include the tanh profile or kink soliton, and the corresponding uniform state in the wavelength 2 mode, a similar soliton and uniform state in the wavelength 4 mode, a domain wall between the wavelength 2 and 4 modes and a domain wall between a chaotic state and the wavelength 2 mode. Amplitude profiles were measured for the stable kink and domain wall states and smooth curves were obtained by dividing the kink states by the corresponding uniform states. Return maps were measured for two sites in the chaotic domain wall. Simulation of a chaotic domain wall in a 50 site numerical lattice is reported. This system has the advantage that its parameters can be modified much more easily than those of the physical lattice. An attempt is made at quantifying the level of chaos as a function of lattice site with fractal dimension calculations on return maps embedded in a three dimensional space. The drive plane of the chaotic domain wall is mapped out in the drive amplitude - drive frequency plane. Transitions to various stable and quasiperiodic domain walls are noted.

Fault Tolerant Paradigms

DTIC Science & Technology

2016-02-26

say that A is a JL(m,d,)-embedding of S into Cm. Linear JL(m,d,)-embeddings are closely related to the Restricted Isometry Property [9, 4, 18...holds ∀x ∈ Cd containing at most s nonzero coordinates. In this case we will say that A is RIP(s,). In particular, the following theorem due to Krahmer...implement reliable edge detector functions, especially in the presence of noise. Needless to say , the same issues exist in two dimensions, as

The Effects of the Concrete-Representational-Abstract Integration Strategy on the Ability of Students with Learning Disabilities to Multiply Linear Expressions within Area Problems

ERIC Educational Resources Information Center

Strickland, Tricia K.; Maccini, Paula

2013-01-01

We examined the effects of the Concrete-Representational-Abstract Integration strategy on the ability of secondary students with learning disabilities to multiply linear algebraic expressions embedded within contextualized area problems. A multiple-probe design across three participants was used. Results indicated that the integration of the…

Lattice distortion and electron charge redistribution induced by defects in graphene

DOE PAGES

Zhang, Wei; Lu, Wen -Cai; Zhang, Hong -Xing; ...

2016-09-14

Lattice distortion and electronic charge localization induced by vacancy and embedded-atom defects in graphene were studied by tight-binding (TB) calculations using the recently developed three-center TB potential model. We showed that the formation energies of the defects are strongly correlated with the number of dangling bonds and number of embedded atoms, as well as the magnitude of the graphene lattice distortion induced by the defects. Lastly, we also showed that the defects introduce localized electronic states in the graphene which would affect the electron transport properties of graphene.

Energy-aware virtual network embedding in flexi-grid optical networks

NASA Astrophysics Data System (ADS)

Lin, Rongping; Luo, Shan; Wang, Haoran; Wang, Sheng; Chen, Bin

2018-01-01

Virtual network embedding (VNE) problem is to map multiple heterogeneous virtual networks (VN) on a shared substrate network, which mitigate the ossification of the substrate network. Meanwhile, energy efficiency has been widely considered in the network design. In this paper, we aim to solve the energy-aware VNE problem in flexi-grid optical networks. We provide an integer linear programming (ILP) formulation to minimize the power increment of each arriving VN request. We also propose a polynomial-time heuristic algorithm where virtual links are embedded sequentially to keep a reasonable acceptance ratio and maintain a low energy consumption. Numerical results show the functionality of the heuristic algorithm in a 24-node network.

A Metascalable Computing Framework for Large Spatiotemporal-Scale Atomistic Simulations

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

Nomura, K; Seymour, R; Wang, W

2009-02-17

A metascalable (or 'design once, scale on new architectures') parallel computing framework has been developed for large spatiotemporal-scale atomistic simulations of materials based on spatiotemporal data locality principles, which is expected to scale on emerging multipetaflops architectures. The framework consists of: (1) an embedded divide-and-conquer (EDC) algorithmic framework based on spatial locality to design linear-scaling algorithms for high complexity problems; (2) a space-time-ensemble parallel (STEP) approach based on temporal locality to predict long-time dynamics, while introducing multiple parallelization axes; and (3) a tunable hierarchical cellular decomposition (HCD) parallelization framework to map these O(N) algorithms onto a multicore cluster based onmore » hybrid implementation combining message passing and critical section-free multithreading. The EDC-STEP-HCD framework exposes maximal concurrency and data locality, thereby achieving: (1) inter-node parallel efficiency well over 0.95 for 218 billion-atom molecular-dynamics and 1.68 trillion electronic-degrees-of-freedom quantum-mechanical simulations on 212,992 IBM BlueGene/L processors (superscalability); (2) high intra-node, multithreading parallel efficiency (nanoscalability); and (3) nearly perfect time/ensemble parallel efficiency (eon-scalability). The spatiotemporal scale covered by MD simulation on a sustained petaflops computer per day (i.e. petaflops {center_dot} day of computing) is estimated as NT = 2.14 (e.g. N = 2.14 million atoms for T = 1 microseconds).« less

Effect of using different cover image quality to obtain robust selective embedding in steganography

NASA Astrophysics Data System (ADS)

Abdullah, Karwan Asaad; Al-Jawad, Naseer; Abdulla, Alan Anwer

2014-05-01

One of the common types of steganography is to conceal an image as a secret message in another image which normally called a cover image; the resulting image is called a stego image. The aim of this paper is to investigate the effect of using different cover image quality, and also analyse the use of different bit-plane in term of robustness against well-known active attacks such as gamma, statistical filters, and linear spatial filters. The secret messages are embedded in higher bit-plane, i.e. in other than Least Significant Bit (LSB), in order to resist active attacks. The embedding process is performed in three major steps: First, the embedding algorithm is selectively identifying useful areas (blocks) for embedding based on its lighting condition. Second, is to nominate the most useful blocks for embedding based on their entropy and average. Third, is to select the right bit-plane for embedding. This kind of block selection made the embedding process scatters the secret message(s) randomly around the cover image. Different tests have been performed for selecting a proper block size and this is related to the nature of the used cover image. Our proposed method suggests a suitable embedding bit-plane as well as the right blocks for the embedding. Experimental results demonstrate that different image quality used for the cover images will have an effect when the stego image is attacked by different active attacks. Although the secret messages are embedded in higher bit-plane, but they cannot be recognised visually within the stegos image.

Improving the CD linearity and proximity performance of photomasks written on the Sigma7500-II DUV laser writer through embedded OPC

NASA Astrophysics Data System (ADS)

Österberg, Anders; Ivansen, Lars; Beyerl, Angela; Newman, Tom; Bowhill, Amanda; Sahouria, Emile; Schulze, Steffen

2007-10-01

Optical proximity correction (OPC) is widely used in wafer lithography to produce a printed image that best matches the design intent while optimizing CD control. OPC software applies corrections to the mask pattern data, but in general it does not compensate for the mask writer and mask process characteristics. The Sigma7500-II deep-UV laser mask writer projects the image of a programmable spatial light modulator (SLM) using partially coherent optics similar to wafer steppers, and the optical proximity effects of the mask writer are in principle correctable with established OPC methods. To enhance mask patterning, an embedded OPC function, LinearityEqualize TM, has been developed for the Sigma7500- II that is transparent to the user and which does not degrade mask throughput. It employs a Calibre TM rule-based OPC engine from Mentor Graphics, selected for the computational speed necessary for mask run-time execution. A multinode cluster computer applies optimized table-based CD corrections to polygonized pattern data that is then fractured into an internal writer format for subsequent data processing. This embedded proximity correction flattens the linearity behavior for all linewidths and pitches, which targets to improve the CD uniformity on production photomasks. Printing results show that the CD linearity is reduced to below 5 nm for linewidths down to 200 nm, both for clear and dark and for isolated and dense features, and that sub-resolution assist features (SRAF) are reliably printed down to 120 nm. This reduction of proximity effects for main mask features and the extension of the practical resolution for SRAFs expands the application space of DUV laser mask writing.

Mechanics of instability-related delimination growth

NASA Technical Reports Server (NTRS)

Whitcomb, John D.

1988-01-01

Local buckling of a delaminated group of plies can lead to higher interlaminar stresses and delamination growth. The mechanics of instability-related delamination growth (IRDG) had been described previously for the through-width delamination. This paper describes the mechanics of IRDG for the embedded delamination subjected to either uniaxial or axisymmetric loads. The mechanics of IRDG are used to explain the dramatic differences in strain-energy release rates observed for the through-width, the axisymmetrically loaded embedded delamination, and the uniaxially loaded embedded delamination.

Use of a novel smart heating sleeping bag to improve wearers’ local thermal comfort in the feet

PubMed Central

Song, W. F.; Zhang, C. J.; Lai, D. D.; Wang, F. M.; Kuklane, K.

2016-01-01

Previous studies have revealed that wearers had low skin temperatures and cold and pain sensations in the feet, when using sleeping bags under defined comfort and limit temperatures. To improve wearers’ local thermal comfort in the feet, a novel heating sleeping bag (i.e., MARHT) was developed by embedding two heating pads into the traditional sleeping bag (i.e., MARCON) in this region. Seven female and seven male volunteers underwent two tests on different days. Each test lasted for three hours and was performed in a climate chamber with a setting temperature deduced from EN 13537 (2012) (for females: comfort temperature of −0.4 °C, and for males: the limit temperature of −6.4 °C). MARHT was found to be effective in maintaining the toe and feet temperatures within the thermoneutral range for both sex groups compared to the linearly decreased temperatures in MARCON during the 3-hour exposure. In addition, wearing MARHT elevated the toe blood flow significantly for most females and all males. Thermal and comfort sensations showed a large improvement in feet and a small to moderate improvement in the whole body for both sex groups in MARHT. It was concluded that MARHT is effective in improving local thermal comfort in the feet. PMID:26759077

Use of a novel smart heating sleeping bag to improve wearers’ local thermal comfort in the feet

NASA Astrophysics Data System (ADS)

Song, W. F.; Zhang, C. J.; Lai, D. D.; Wang, F. M.; Kuklane, K.

2016-01-01

Previous studies have revealed that wearers had low skin temperatures and cold and pain sensations in the feet, when using sleeping bags under defined comfort and limit temperatures. To improve wearers’ local thermal comfort in the feet, a novel heating sleeping bag (i.e., MARHT) was developed by embedding two heating pads into the traditional sleeping bag (i.e., MARCON) in this region. Seven female and seven male volunteers underwent two tests on different days. Each test lasted for three hours and was performed in a climate chamber with a setting temperature deduced from EN 13537 (2012) (for females: comfort temperature of -0.4 °C, and for males: the limit temperature of -6.4 °C). MARHT was found to be effective in maintaining the toe and feet temperatures within the thermoneutral range for both sex groups compared to the linearly decreased temperatures in MARCON during the 3-hour exposure. In addition, wearing MARHT elevated the toe blood flow significantly for most females and all males. Thermal and comfort sensations showed a large improvement in feet and a small to moderate improvement in the whole body for both sex groups in MARHT. It was concluded that MARHT is effective in improving local thermal comfort in the feet.

Use of a novel smart heating sleeping bag to improve wearers' local thermal comfort in the feet.

PubMed

Song, W F; Zhang, C J; Lai, D D; Wang, F M; Kuklane, K

2016-01-13

Previous studies have revealed that wearers had low skin temperatures and cold and pain sensations in the feet, when using sleeping bags under defined comfort and limit temperatures. To improve wearers' local thermal comfort in the feet, a novel heating sleeping bag (i.e., MARHT) was developed by embedding two heating pads into the traditional sleeping bag (i.e., MARCON) in this region. Seven female and seven male volunteers underwent two tests on different days. Each test lasted for three hours and was performed in a climate chamber with a setting temperature deduced from EN 13537 (2012) (for females: comfort temperature of -0.4 °C, and for males: the limit temperature of -6.4 °C). MARHT was found to be effective in maintaining the toe and feet temperatures within the thermoneutral range for both sex groups compared to the linearly decreased temperatures in MARCON during the 3-hour exposure. In addition, wearing MARHT elevated the toe blood flow significantly for most females and all males. Thermal and comfort sensations showed a large improvement in feet and a small to moderate improvement in the whole body for both sex groups in MARHT. It was concluded that MARHT is effective in improving local thermal comfort in the feet.

Extracting Independent Local Oscillatory Geophysical Signals by Geodetic Tropospheric Delay

NASA Technical Reports Server (NTRS)

Botai, O. J.; Combrinck, L.; Sivakumar, V.; Schuh, H.; Bohm, J.

2010-01-01

Zenith Tropospheric Delay (ZTD) due to water vapor derived from space geodetic techniques and numerical weather prediction simulated-reanalysis data exhibits non-linear and non-stationary properties akin to those in the crucial geophysical signals of interest to the research community. These time series, once decomposed into additive (and stochastic) components, have information about the long term global change (the trend) and other interpretable (quasi-) periodic components such as seasonal cycles and noise. Such stochastic component(s) could be a function that exhibits at most one extremum within a data span or a monotonic function within a certain temporal span. In this contribution, we examine the use of the combined Ensemble Empirical Mode Decomposition (EEMD) and Independent Component Analysis (ICA): the EEMD-ICA algorithm to extract the independent local oscillatory stochastic components in the tropospheric delay derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) over six geodetic sites (HartRAO, Hobart26, Wettzell, Gilcreek, Westford, and Tsukub32). The proposed methodology allows independent geophysical processes to be extracted and assessed. Analysis of the quality index of the Independent Components (ICs) derived for each cluster of local oscillatory components (also called the Intrinsic Mode Functions (IMFs)) for all the geodetic stations considered in the study demonstrate that they are strongly site dependent. Such strong dependency seems to suggest that the localized geophysical signals embedded in the ZTD over the geodetic sites are not correlated. Further, from the viewpoint of non-linear dynamical systems, four geophysical signals the Quasi-Biennial Oscillation (QBO) index derived from the NCEP/NCAR reanalysis, the Southern Oscillation Index (SOI) anomaly from NCEP, the SIDC monthly Sun Spot Number (SSN), and the Length of Day (LoD) are linked to the extracted signal components from ZTD. Results from the synchronization analysis show that ZTD and the geophysical signals exhibit (albeit subtle) site dependent phase synchronization index.

LDFT-based watermarking resilient to local desynchronization attacks.

PubMed

Tian, Huawei; Zhao, Yao; Ni, Rongrong; Qin, Lunming; Li, Xuelong

2013-12-01

Up to now, a watermarking scheme that is robust against desynchronization attacks (DAs) is still a grand challenge. Most image watermarking resynchronization schemes in literature can survive individual global DAs (e.g., rotation, scaling, translation, and other affine transforms), but few are resilient to challenging cropping and local DAs. The main reason is that robust features for watermark synchronization are only globally invariable rather than locally invariable. In this paper, we present a blind image watermarking resynchronization scheme against local transform attacks. First, we propose a new feature transform named local daisy feature transform (LDFT), which is not only globally but also locally invariable. Then, the binary space partitioning (BSP) tree is used to partition the geometrically invariant LDFT space. In the BSP tree, the location of each pixel is fixed under global transform, local transform, and cropping. Lastly, the watermarking sequence is embedded bit by bit into each leaf node of the BSP tree by using the logarithmic quantization index modulation watermarking embedding method. Simulation results show that the proposed watermarking scheme can survive numerous kinds of distortions, including common image-processing attacks, local and global DAs, and noninvertible cropping.

Continuum description of ionic and dielectric shielding for molecular-dynamics simulations of proteins in solution

NASA Astrophysics Data System (ADS)

Egwolf, Bernhard; Tavan, Paul

2004-01-01

We extend our continuum description of solvent dielectrics in molecular-dynamics (MD) simulations [B. Egwolf and P. Tavan, J. Chem. Phys. 118, 2039 (2003)], which has provided an efficient and accurate solution of the Poisson equation, to ionic solvents as described by the linearized Poisson-Boltzmann (LPB) equation. We start with the formulation of a general theory for the electrostatics of an arbitrarily shaped molecular system, which consists of partially charged atoms and is embedded in a LPB continuum. This theory represents the reaction field induced by the continuum in terms of charge and dipole densities localized within the molecular system. Because these densities cannot be calculated analytically for systems of arbitrary shape, we introduce an atom-based discretization and a set of carefully designed approximations. This allows us to represent the densities by charges and dipoles located at the atoms. Coupled systems of linear equations determine these multipoles and can be rapidly solved by iteration during a MD simulation. The multipoles yield the reaction field forces and energies. Finally, we scrutinize the quality of our approach by comparisons with an analytical solution restricted to perfectly spherical systems and with results of a finite difference method.

First-principles calculations of 17O nuclear magnetic resonance chemical shielding in Pb(Zr(1/2)Ti(1/2))O3 and Pb(Mg(1/3)Nb(2/3))O3: linear dependence on transition-metal/oxygen bond lengths.

PubMed

Pechkis, Daniel L; Walter, Eric J; Krakauer, Henry

2011-09-21

First-principles density functional theory oxygen chemical shift tensors were calculated for A(B,B')O(3) perovskite alloys Pb(Zr(1/2)Ti(1/2))O(3) (PZT) and Pb(Mg(1/3)Nb(2/3))O(3) (PMN). Quantum chemistry methods for embedded clusters and the gauge including projector augmented waves (GIPAW) method [C. J. Pickard and F. Mauri, Phys. Rev. B 63, 245101 (2001)] for periodic boundary conditions were used. Results from both methods are in good agreement for PZT and prototypical perovskites. PMN results were obtained using only GIPAW. Both isotropic δ(iso) and axial δ(ax) chemical shifts were found to vary approximately linearly as a function of the nearest-distance transition-metal/oxygen bond length, r(s). Using these results, we argue against Ti clustering in PZT, as conjectured from recent (17)O NMR magic-angle-spinning measurements. Our findings indicate that (17)O NMR measurements, coupled with first-principles calculations, can be an important probe of local structure in complex perovskite solid solutions.

First-principles calculations of 17O nuclear magnetic resonance chemical shielding in Pb(Zr1/2Ti1/2)O3 and Pb(Mg1/3Nb2/3)O3: Linear dependence on transition-metal/oxygen bond lengths

NASA Astrophysics Data System (ADS)

Pechkis, Daniel L.; Walter, Eric J.; Krakauer, Henry

2011-09-01

First-principles density functional theory oxygen chemical shift tensors were calculated for A(B,B')O3 perovskite alloys Pb(Zr1/2Ti1/2)O3 (PZT) and Pb(Mg1/3Nb2/3)O3 (PMN). Quantum chemistry methods for embedded clusters and the gauge including projector augmented waves (GIPAW) method [C. J. Pickard and F. Mauri, Phys. Rev. B 63, 245101 (2001)], 10.1103/PhysRevB.63.245101 for periodic boundary conditions were used. Results from both methods are in good agreement for PZT and prototypical perovskites. PMN results were obtained using only GIPAW. Both isotropic δiso and axial δax chemical shifts were found to vary approximately linearly as a function of the nearest-distance transition-metal/oxygen bond length, rs. Using these results, we argue against Ti clustering in PZT, as conjectured from recent 17O NMR magic-angle-spinning measurements. Our findings indicate that 17O NMR measurements, coupled with first-principles calculations, can be an important probe of local structure in complex perovskite solid solutions.

Variational approach to stability boundary for the Taylor-Goldstein equation

NASA Astrophysics Data System (ADS)

Hirota, Makoto; Morrison, Philip J.

2015-11-01

Linear stability of inviscid stratified shear flow is studied by developing an efficient method for finding neutral (i.e., marginally stable) solutions of the Taylor-Goldstein equation. The classical Miles-Howard criterion states that stratified shear flow is stable if the local Richardson number JR is greater than 1/4 everywhere. In this work, the case of JR > 0 everywhere is considered by assuming strictly monotonic and smooth profiles of the ambient shear flow and density. It is shown that singular neutral modes that are embedded in the continuous spectrum can be found by solving one-parameter families of self-adjoint eigenvalue problems. The unstable ranges of wavenumber are searched for accurately and efficiently by adopting this method in a numerical algorithm. Because the problems are self-adjoint, the variational method can be applied to ascertain the existence of singular neutral modes. For certain shear flow and density profiles, linear stability can be proven by showing the non-existence of a singular neutral mode. New sufficient conditions, extensions of the Rayleigh-Fjortoft stability criterion for unstratified shear flows, are derived in this manner. This work was supported by JSPS Strategic Young Researcher Overseas Visits Program for Accelerating Brain Circulation # 55053270.

Time Delay Embedding Increases Estimation Precision of Models of Intraindividual Variability

ERIC Educational Resources Information Center

von Oertzen, Timo; Boker, Steven M.

2010-01-01

This paper investigates the precision of parameters estimated from local samples of time dependent functions. We find that "time delay embedding," i.e., structuring data prior to analysis by constructing a data matrix of overlapping samples, increases the precision of parameter estimates and in turn statistical power compared to standard…

On second harmonic generation and multiphoton-absorption induced luminescence from laser-reshaped silver nanoparticles embedded in glass.

PubMed

Zolotovskaya, S A; Tyrk, M A; Stalmashonak, A; Gillespie, W A; Abdolvand, A

2016-10-28

Spherical silver nanoparticles (NPs) of 30 nm diameter embedded in soda-lime glass were uniformly reshaped (elongated) after irradiation by a linearly polarised 250 fs pulsed laser operating within the NPs' surface plasmon resonance band. We observed second harmonic generation (SHG) and multiphoton-absorption-induced luminescence (MAIL) in the embedded laser-reshaped NPs upon picosecond (10 ps) pulsed laser excitation at 1064 nm. A complementary study of SHG and MAIL was conducted in soda-lime glass containing embedded, mechanically-reshaped silver NPs of a similar elongation ratio (aspect ratio) to the laser-reshaped NPs. This supports the notion that the observed difference in SHG and MAIL in the studied nanocomposite systems is due to the shape modification mechanism. The discrete dipole approximation method was used to assess the absorption and scattering cross-sections of the reshaped NPs with different elongation ratios.

Groundwater connectivity of upland-embedded wetlands in the Prairie Pothole Region

USGS Publications Warehouse

Neff, Brian; Rosenberry, Donald O.

2018-01-01

Groundwater connections from upland-embedded wetlands to downstream waterbodies remain poorly understood. In principle, water from upland-embedded wetlands situated high in a landscape should flow via groundwater to waterbodies situated lower in the landscape. However, the degree of groundwater connectivity varies across systems due to factors such as geologic setting, hydrologic conditions, and topography. We use numerical models to evaluate the conditions suitable for groundwater connectivity between upland-embedded wetlands and downstream waterbodies in the prairie pothole region of North Dakota (USA). Results show groundwater connectivity between upland-embedded wetlands and other waterbodies is restricted when these wetlands are surrounded by a mounding water table. However, connectivity exists among adjacent upland-embedded wetlands where water–table mounds do not form. In addition, the presence of sand layers greatly facilitates groundwater connectivity of upland-embedded wetlands. Anisotropy can facilitate connectivity via groundwater flow, but only if it becomes unrealistically large. These findings help consolidate previously divergent views on the significance of local and regional groundwater flow in the prairie pothole region.

Impairment in local and global processing and set-shifting in body dysmorphic disorder

PubMed Central

Kerwin, Lauren; Hovav, Sarit; Helleman, Gerhard; Feusner, Jamie D.

2014-01-01

Body dysmorphic disorder (BDD) is characterized by distressing and often debilitating preoccupations with misperceived defects in appearance. Research suggests that aberrant visual processing may contribute to these misperceptions. This study used two tasks to probe global and local visual processing as well as set shifting in individuals with BDD. Eighteen unmedicated individuals with BDD and 17 non-clinical controls completed two global-local tasks. The embedded figures task requires participants to determine which of three complex figures contained a simpler figure embedded within it. The Navon task utilizes incongruent stimuli comprised of a large letter (global level) made up of smaller letters (local level). The outcome measures were response time and accuracy rate. On the embedded figures task, BDD individuals were slower and less accurate than controls. On the Navon task, BDD individuals processed both global and local stimuli slower and less accurately than controls, and there was a further decrement in performance when shifting attention between the different levels of stimuli. Worse insight correlated with poorer performance on both tasks. Taken together, these results suggest abnormal global and local processing for non-appearance related stimuli among BDD individuals, in addition to evidence of poor set-shifting abilities. Moreover, these abnormalities appear to relate to the important clinical variable of poor insight. Further research is needed to explore these abnormalities and elucidate their possible role in the development and/or persistence of BDD symptoms. PMID:24972487

Structured sparse linear graph embedding.

PubMed

Wang, Haixian

2012-03-01

Subspace learning is a core issue in pattern recognition and machine learning. Linear graph embedding (LGE) is a general framework for subspace learning. In this paper, we propose a structured sparse extension to LGE (SSLGE) by introducing a structured sparsity-inducing norm into LGE. Specifically, SSLGE casts the projection bases learning into a regression-type optimization problem, and then the structured sparsity regularization is applied to the regression coefficients. The regularization selects a subset of features and meanwhile encodes high-order information reflecting a priori structure information of the data. The SSLGE technique provides a unified framework for discovering structured sparse subspace. Computationally, by using a variational equality and the Procrustes transformation, SSLGE is efficiently solved with closed-form updates. Experimental results on face image show the effectiveness of the proposed method. Copyright © 2011 Elsevier Ltd. All rights reserved.

Excitons emissions and Raman scattering of ZnO nanoparticles embedded in BaF2 matrices by reactive magnetron sputtering.

PubMed

Zang, C H; Su, J F; Liu, Y C; Tang, C J; Fang, S J; Zhang, D M; Zhang, Y S

2011-11-01

ZnO nanoparticles embedded in BaF2 matrix were fabricated by rf magnetic sputtering technology. The optical properties of high quality ZnO nanoparticles, thermally post treated in a N2 atmosphere, were investigated by temperature-dependence photoluminescence measurement. Free exciton and localized exciton were observed at the low temperature. Free exciton peak was at 3.374 eV and localized exciton peak was at 3.420 eV, dominating the PL spectrum at 77 K. Free exciton transition was observed at 3.310 eV at room temperature, whereas the localized exciton transition was at 3.378 eV. The multiple-phonon Raman scattering spectrum showed that ZnO nanoparticles embedded in BaF2 matrix had a large deformation energy originated from lattice mismatch between ZnO and BaF2 matrix. Analysis of the fitting results from the temperature dependence of FWHM of ZnO exciton illustrated that the large value of gamma(ph) was good qualitative agreement with the large deformation potential.

A self-consistent density based embedding scheme applied to the adsorption of CO on Pd(111)

NASA Astrophysics Data System (ADS)

Lahav, D.; Klüner, T.

2007-06-01

We derive a variant of a density based embedded cluster approach as an improvement to a recently proposed embedding theory for metallic substrates (Govind et al 1999 J. Chem. Phys. 110 7677; Klüner et al 2001 Phys. Rev. Lett. 86 5954). In this scheme, a local region in space is represented by a small cluster which is treated by accurate quantum chemical methodology. The interaction of the cluster with the infinite solid is taken into account by an effective one-electron embedding operator representing the surrounding region. We propose a self-consistent embedding scheme which resolves intrinsic problems of the former theory, in particular a violation of strict density conservation. The proposed scheme is applied to the well-known benchmark system CO/Pd(111).

Study of Composite Plate Damages Using Embedded PZT Sensors with Various Center Frequency

NASA Astrophysics Data System (ADS)

Kang, Kyoung-Tak; Chun, Heoung-Jae; Son, Ju-Hyun; Byun, Joon-Hyung; Um, Moon-Kwang; Lee, Sang-Kwan

This study presents part of an experimental and analytical survey of candidate methods for damage detection of composite structural. Embedded piezoceramic (PZT) sensors were excited with the high power ultrasonic wave generator generating a propagation of stress wave along the composite plate. The same embedded piezoceramic (PZT) sensors are used as receivers for acquiring stress signals. The effects of center frequency of embedded sensor were evaluated for the damage identification capability with known localized defects. The study was carried out to assess damage in composite plate by fusing information from multiple sensing paths of the embedded network. It was based on the Hilbert transform, signal correlation and probabilistic searching. The obtained results show that satisfactory detection of defects could be achieved by proposed method.

Quantifying and visualizing variations in sets of images using continuous linear optimal transport

NASA Astrophysics Data System (ADS)

Kolouri, Soheil; Rohde, Gustavo K.

2014-03-01

Modern advancements in imaging devices have enabled us to explore the subcellular structure of living organisms and extract vast amounts of information. However, interpreting the biological information mined in the captured images is not a trivial task. Utilizing predetermined numerical features is usually the only hope for quantifying this information. Nonetheless, direct visual or biological interpretation of results obtained from these selected features is non-intuitive and difficult. In this paper, we describe an automatic method for modeling visual variations in a set of images, which allows for direct visual interpretation of the most significant differences, without the need for predefined features. The method is based on a linearized version of the continuous optimal transport (OT) metric, which provides a natural linear embedding for the image data set, in which linear combination of images leads to a visually meaningful image. This enables us to apply linear geometric data analysis techniques such as principal component analysis and linear discriminant analysis in the linearly embedded space and visualize the most prominent modes, as well as the most discriminant modes of variations, in the dataset. Using the continuous OT framework, we are able to analyze variations in shape and texture in a set of images utilizing each image at full resolution, that otherwise cannot be done by existing methods. The proposed method is applied to a set of nuclei images segmented from Feulgen stained liver tissues in order to investigate the major visual differences in chromatin distribution of Fetal-Type Hepatoblastoma (FHB) cells compared to the normal cells.

An embedded real-time red peach detection system based on an OV7670 camera, ARM cortex-M4 processor and 3D look-up tables.

PubMed

Teixidó, Mercè; Font, Davinia; Pallejà, Tomàs; Tresanchez, Marcel; Nogués, Miquel; Palacín, Jordi

2012-10-22

This work proposes the development of an embedded real-time fruit detection system for future automatic fruit harvesting. The proposed embedded system is based on an ARM Cortex-M4 (STM32F407VGT6) processor and an Omnivision OV7670 color camera. The future goal of this embedded vision system will be to control a robotized arm to automatically select and pick some fruit directly from the tree. The complete embedded system has been designed to be placed directly in the gripper tool of the future robotized harvesting arm. The embedded system will be able to perform real-time fruit detection and tracking by using a three-dimensional look-up-table (LUT) defined in the RGB color space and optimized for fruit picking. Additionally, two different methodologies for creating optimized 3D LUTs based on existing linear color models and fruit histograms were implemented in this work and compared for the case of red peaches. The resulting system is able to acquire general and zoomed orchard images and to update the relative tracking information of a red peach in the tree ten times per second.

An Embedded Real-Time Red Peach Detection System Based on an OV7670 Camera, ARM Cortex-M4 Processor and 3D Look-Up Tables

PubMed Central

Teixidó, Mercè; Font, Davinia; Pallejà, Tomàs; Tresanchez, Marcel; Nogués, Miquel; Palacín, Jordi

2012-01-01

This work proposes the development of an embedded real-time fruit detection system for future automatic fruit harvesting. The proposed embedded system is based on an ARM Cortex-M4 (STM32F407VGT6) processor and an Omnivision OV7670 color camera. The future goal of this embedded vision system will be to control a robotized arm to automatically select and pick some fruit directly from the tree. The complete embedded system has been designed to be placed directly in the gripper tool of the future robotized harvesting arm. The embedded system will be able to perform real-time fruit detection and tracking by using a three-dimensional look-up-table (LUT) defined in the RGB color space and optimized for fruit picking. Additionally, two different methodologies for creating optimized 3D LUTs based on existing linear color models and fruit histograms were implemented in this work and compared for the case of red peaches. The resulting system is able to acquire general and zoomed orchard images and to update the relative tracking information of a red peach in the tree ten times per second. PMID:23202040

Visual Exploration of Semantic Relationships in Neural Word Embeddings

DOE PAGES

Liu, Shusen; Bremer, Peer-Timo; Thiagarajan, Jayaraman J.; ...

2017-08-29

Constructing distributed representations for words through neural language models and using the resulting vector spaces for analysis has become a crucial component of natural language processing (NLP). But, despite their widespread application, little is known about the structure and properties of these spaces. To gain insights into the relationship between words, the NLP community has begun to adapt high-dimensional visualization techniques. Particularly, researchers commonly use t-distributed stochastic neighbor embeddings (t-SNE) and principal component analysis (PCA) to create two-dimensional embeddings for assessing the overall structure and exploring linear relationships (e.g., word analogies), respectively. Unfortunately, these techniques often produce mediocre or evenmore » misleading results and cannot address domain-specific visualization challenges that are crucial for understanding semantic relationships in word embeddings. We introduce new embedding techniques for visualizing semantic and syntactic analogies, and the corresponding tests to determine whether the resulting views capture salient structures. Additionally, we introduce two novel views for a comprehensive study of analogy relationships. Finally, we augment t-SNE embeddings to convey uncertainty information in order to allow a reliable interpretation. Combined, the different views address a number of domain-specific tasks difficult to solve with existing tools.« less

Visual Exploration of Semantic Relationships in Neural Word Embeddings

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

Liu, Shusen; Bremer, Peer-Timo; Thiagarajan, Jayaraman J.

Constructing distributed representations for words through neural language models and using the resulting vector spaces for analysis has become a crucial component of natural language processing (NLP). But, despite their widespread application, little is known about the structure and properties of these spaces. To gain insights into the relationship between words, the NLP community has begun to adapt high-dimensional visualization techniques. Particularly, researchers commonly use t-distributed stochastic neighbor embeddings (t-SNE) and principal component analysis (PCA) to create two-dimensional embeddings for assessing the overall structure and exploring linear relationships (e.g., word analogies), respectively. Unfortunately, these techniques often produce mediocre or evenmore » misleading results and cannot address domain-specific visualization challenges that are crucial for understanding semantic relationships in word embeddings. We introduce new embedding techniques for visualizing semantic and syntactic analogies, and the corresponding tests to determine whether the resulting views capture salient structures. Additionally, we introduce two novel views for a comprehensive study of analogy relationships. Finally, we augment t-SNE embeddings to convey uncertainty information in order to allow a reliable interpretation. Combined, the different views address a number of domain-specific tasks difficult to solve with existing tools.« less

Development of a steady potential solver for use with linearized, unsteady aerodynamic analyses

NASA Technical Reports Server (NTRS)

Hoyniak, Daniel; Verdon, Joseph M.

1991-01-01

A full potential steady flow solver (SFLOW) developed explicitly for use with an inviscid unsteady aerodynamic analysis (LINFLO) is described. The steady solver uses the nonconservative form of the nonlinear potential flow equations together with an implicit, least squares, finite difference approximation to solve for the steady flow field. The difference equations were developed on a composite mesh which consists of a C grid embedded in a rectilinear (H grid) cascade mesh. The composite mesh is capable of resolving blade to blade and far field phenomena on the H grid, while accurately resolving local phenomena on the C grid. The resulting system of algebraic equations is arranged in matrix form using a sparse matrix package and solved by Newton's method. Steady and unsteady results are presented for two cascade configurations: a high speed compressor and a turbine with high exit Mach number.

Remotely powered distributed microfluidic pumps and mixers based on miniature diodes.

PubMed

Chang, Suk Tai; Beaumont, Erin; Petsev, Dimiter N; Velev, Orlin D

2008-01-01

We demonstrate new principles of microfluidic pumping and mixing by electronic components integrated into a microfluidic chip. The miniature diodes embedded into the microchannel walls rectify the voltage induced between their electrodes from an external alternating electric field. The resulting electroosmotic flows, developed in the vicinity of the diode surfaces, were utilized for pumping or mixing of the fluid in the microfluidic channel. The flow velocity of liquid pumped by the diodes facing in the same direction linearly increased with the magnitude of the applied voltage and the pumping direction could be controlled by the pH of the solutions. The transverse flow driven by the localized electroosmotic flux between diodes oriented oppositely on the microchannel was used in microfluidic mixers. The experimental results were interpreted by numerical simulations of the electrohydrodynamic flows. The techniques may be used in novel actively controlled microfluidic-electronic chips.

Chaos and Forecasting - Proceedings of the Royal Society Discussion Meeting

NASA Astrophysics Data System (ADS)

Tong, Howell

1995-04-01

The Table of Contents for the full book PDF is as follows: * Preface * Orthogonal Projection, Embedding Dimension and Sample Size in Chaotic Time Series from a Statistical Perspective * A Theory of Correlation Dimension for Stationary Time Series * On Prediction and Chaos in Stochastic Systems * Locally Optimized Prediction of Nonlinear Systems: Stochastic and Deterministic * A Poisson Distribution for the BDS Test Statistic for Independence in a Time Series * Chaos and Nonlinear Forecastability in Economics and Finance * Paradigm Change in Prediction * Predicting Nonuniform Chaotic Attractors in an Enzyme Reaction * Chaos in Geophysical Fluids * Chaotic Modulation of the Solar Cycle * Fractal Nature in Earthquake Phenomena and its Simple Models * Singular Vectors and the Predictability of Weather and Climate * Prediction as a Criterion for Classifying Natural Time Series * Measuring and Characterising Spatial Patterns, Dynamics and Chaos in Spatially-Extended Dynamical Systems and Ecologies * Non-Linear Forecasting and Chaos in Ecology and Epidemiology: Measles as a Case Study

Dynamics of poroelastic foams

NASA Astrophysics Data System (ADS)

Forterre, Yoel; Sobac, Benjamin

2010-11-01

Soft poroelastic structures are widespread in biological tissues such as cartilaginous joints in bones, blood-filled placentae or plant organs. Here we investigate the dynamics of open elastic foams immersed in viscous fluids, as model soft poroelastic materials. The experiment consists in slowly compacting blocs of polyurethane solid foam embedded in silicon oil-tanks and studying their relaxation to equilibrium when the confining stress is suddenly released. Measurements of the local fluid pressure and foam velocity field are compared with a simple two-phase flow approach. For small initial compactions, the results show quantitative agreement with the classical diffusion theory of soil consolidation (Terzaghi, Biot). On the other hand, for large initial compactions, the dynamics exhibits long relaxation times and decompaction fronts, which are mainly controlled by the highly non-linear mechanical response of the foam. The analogy between this process and the evaporation of a polymer melt close to the glass transition will be briefly discussed.

Research on unsteady transonic flow theory

NASA Technical Reports Server (NTRS)

Revell, J. D.

1973-01-01

A two-dimensional theory is considered for the unsteady flow disturbances caused by aeroelastic deformations of a thick wing at high subsonic freestream Mach numbers, having a single, internally embedded supercritical (locally supersonic) steady flow region adjacent to the low pressure side of the wing. The theory develops a matrix of unsteady aerodynamic influence coefficients (AICs) suitable as a strip theory for aeroelastic analysis of large aspect ratio thick wings of moderate sweep, typical of a wide class of current and future aircraft. The theory derives the linearized unsteady flow solutions separately for both the subcritical and supercritical regions. These solutions are coupled together to give the requisite (wing pressure-downwash) AICs by the intermediate step of defining flow disturbances on the sonic line, and at the shock wave; these intermediate quantities are then algebraically eliminated by expressing them in terms of the wing surface downwash.

Shear-banding and superdiffusivity in entangled polymer solutions

NASA Astrophysics Data System (ADS)

Shin, Seunghwan; Dorfman, Kevin D.; Cheng, Xiang

2017-12-01

Using high-resolution confocal rheometry, we study the shear profiles of well-entangled DNA solutions under large-amplitude oscillatory shear in a rectilinear planar shear cell. With increasing Weissenberg number (Wi), we observe successive transitions from normal Newtonian linear shear profiles to wall-slip dominant shear profiles and, finally, to shear-banding profiles at high Wi. To investigate the microscopic origin of the observed shear banding, we study the dynamics of micron-sized tracers embedded in DNA solutions. Surprisingly, tracer particles in the shear frame exhibit transient superdiffusivity and strong dynamic heterogeneity. The probability distribution functions of particle displacements follow a power-law scaling at large displacements, indicating a Lévy-walk-type motion, reminiscent of tracer dynamics in entangled wormlike micelle solutions and sheared colloidal glasses. We further characterize the length and time scales associated with the abnormal dynamics of tracer particles. We hypothesize that the unusual particle dynamics arise from localized shear-induced chain disentanglement.

Finite element analysis and optimization of composite structures

NASA Technical Reports Server (NTRS)

Thomsen, Jan

1990-01-01

Linearly elastic fiber reinforced composite discs and laminates in plane stress with variable local orientation and concentration of one or two fiber fields embedded in the matrix material, are considered. The thicknesses and the domain of the discs or laminates are assumed to be given, together with prescribed boundary conditions and in-plane loading along the edge. The problem under study consists in determining throughout the structural domain the optimum orientations and concentrations of the fiber fields in such a way as to maximize the integral stiffness of the composite disc or laminate under the seven loading. Minimization of the integral stiffness can also be performed. The optimization is performed subject to a prescribed bound on the total cost or weight of the composite that for given unit cost factors or specific weights determines the amounts of fiber and matrix materials in the structure. Examples are presented.

Nonlinear focusing of ultrasonic waves by an axisymmetric diffraction grating embedded in water

NASA Astrophysics Data System (ADS)

Jiménez, N.; Romero-García, V.; Picó, R.; Garcia-Raffi, L. M.; Staliunas, K.

2015-11-01

We report the nonlinear focusing of ultrasonic waves by an axisymmetric diffraction grating immersed in water. In the linear regime, the system presents high focal gain (32 dB), with a narrow beam-width and intense side lobes as it is common in focusing by Fresnel-like lenses. Activating the nonlinearity of the host medium by using high amplitude incident waves, the focusing properties of the lens dramatically change. Theoretical predictions show that the focal gain of the system extraordinary increases in the strongly nonlinear regime (Mach number of 6.1 × 10-4). Particularly, the harmonic generation is locally activated at the focal spot, and the second harmonic beam is characterized by strongly reduced side-lobes and an excellent beam profile as experiments show in agreement with theory. The results can motivate applications in medical therapy or second harmonic imaging.

Delay differential analysis of time series.

PubMed

Lainscsek, Claudia; Sejnowski, Terrence J

2015-03-01

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

Long-term radon concentrations estimated from 210Po embedded in glass

USGS Publications Warehouse

Lively, R.S.; Steck, D.J.

1993-01-01

Measured surface-alpha activity on glass exposed in radon chambers and houses has a linear correlation to the integrated radon exposure. Experimental results in chambers and houses have been obtained on glass exposed to radon concentrations between 100 Bq m-3 and 9 MBq m-3 for periods of a few days to several years. Theoretical calculations support the experimental results through a model that predicts the fractions of airborne activity that deposit and become embedded or adsorbed. The combination of measured activity and calculated embedded fraction for a given deposition environment can be applied to most indoor areas and produces a better estimate for lifetime radon exposure than estimates based on short-term indoor radon measurements.

Developing robust recurrence plot analysis techniques for investigating infant respiratory patterns.

PubMed

Terrill, Philip I; Wilson, Stephen; Suresh, Sadasivam; Cooper, David M

2007-01-01

Recurrence plot analysis is a useful non-linear analysis tool. There are still no well formalised procedures for carrying out this analysis on measured physiological data, and systemising analysis is often difficult. In this paper, the recurrence based embedding is compared to radius based embedding by studying a logistic attractor and measured breathing data collected from sleeping human infants. Recurrence based embedding appears to be a more robust method of carrying out a recurrence analysis when attractor size is likely to be different between datasets. In the infant breathing data, the radius measure calculated at a fixed recurrence, scaled by average respiratory period, allows the accurate discrimination of active sleep from quiet sleep states (AUC=0.975, Sn=098, Sp=0.94).

A local crack-tracking strategy to model three-dimensional crack propagation with embedded methods

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

Annavarapu, Chandrasekhar; Settgast, Randolph R.; Vitali, Efrem

We develop a local, implicit crack tracking approach to propagate embedded failure surfaces in three-dimensions. We build on the global crack-tracking strategy of Oliver et al. (Int J. Numer. Anal. Meth. Geomech., 2004; 28:609–632) that tracks all potential failure surfaces in a problem at once by solving a Laplace equation with anisotropic conductivity. We discuss important modifications to this algorithm with a particular emphasis on the effect of the Dirichlet boundary conditions for the Laplace equation on the resultant crack path. Algorithmic and implementational details of the proposed method are provided. Finally, several three-dimensional benchmark problems are studied and resultsmore » are compared with available literature. Lastly, the results indicate that the proposed method addresses pathological cases, exhibits better behavior in the presence of closely interacting fractures, and provides a viable strategy to robustly evolve embedded failure surfaces in 3D.« less

A local crack-tracking strategy to model three-dimensional crack propagation with embedded methods

DOE PAGES

Annavarapu, Chandrasekhar; Settgast, Randolph R.; Vitali, Efrem; ...

2016-09-29

We develop a local, implicit crack tracking approach to propagate embedded failure surfaces in three-dimensions. We build on the global crack-tracking strategy of Oliver et al. (Int J. Numer. Anal. Meth. Geomech., 2004; 28:609–632) that tracks all potential failure surfaces in a problem at once by solving a Laplace equation with anisotropic conductivity. We discuss important modifications to this algorithm with a particular emphasis on the effect of the Dirichlet boundary conditions for the Laplace equation on the resultant crack path. Algorithmic and implementational details of the proposed method are provided. Finally, several three-dimensional benchmark problems are studied and resultsmore » are compared with available literature. Lastly, the results indicate that the proposed method addresses pathological cases, exhibits better behavior in the presence of closely interacting fractures, and provides a viable strategy to robustly evolve embedded failure surfaces in 3D.« less

Community-Embedded Learning Experiences: Putting the Pedagogy of Service-Learning to Work in Online Courses

ERIC Educational Resources Information Center

Becnel, Kim; Moeller, Robin A.

2017-01-01

This paper considers the applicability and adaptability of service-learning pedagogy to online and distance education teaching environments. More specifically, it looks at the community-embedded learning model (CEL), which asks distance students to conduct service projects in their local communities, as manifested in a project undertaken by online…

Acoustic Emission Behavior of Early Age Concrete Monitored by Embedded Sensors.

PubMed

Qin, Lei; Ren, Hong-Wei; Dong, Bi-Qin; Xing, Feng

2014-10-02

Acoustic emission (AE) is capable of monitoring the cracking activities inside materials. In this study, embedded sensors were employed to monitor the AE behavior of early age concrete. Type 1-3 cement-based piezoelectric composites, which had lower mechanical quality factor and acoustic impedance, were fabricated and used to make sensors. Sensors made of the composites illustrated broadband frequency response. In a laboratory, the cracking of early age concrete was monitored to recognize different hydration stages. The sensors were also embedded in a mass concrete foundation to localize the temperature gradient cracks.

Molecular Dynamics Simulation Studies of Fracture in Two Dimensions

DTIC Science & Technology

1980-05-01

reversibility of trajectories. The microscopic elastic constants, dispersion relation and phonon spectrum of the system were determined by lattice dynamics. These... linear elasticity theory of a two-dimensional crack embedded in an infinite medium. System con- sists of 436 particles arranged in a tri- angular lattice ...satisfying these demands. In evaluating the mechanical energy of his model, Griffith used a result from linear elasticity theory, namely that for any body

An embedded formula of the Chebyshev collocation method for stiff problems

NASA Astrophysics Data System (ADS)

Piao, Xiangfan; Bu, Sunyoung; Kim, Dojin; Kim, Philsu

2017-12-01

In this study, we have developed an embedded formula of the Chebyshev collocation method for stiff problems, based on the zeros of the generalized Chebyshev polynomials. A new strategy for the embedded formula, using a pair of methods to estimate the local truncation error, as performed in traditional embedded Runge-Kutta schemes, is proposed. The method is performed in such a way that not only the stability region of the embedded formula can be widened, but by allowing the usage of larger time step sizes, the total computational costs can also be reduced. In terms of concrete convergence and stability analysis, the constructed algorithm turns out to have an 8th order convergence and it exhibits A-stability. Through several numerical experimental results, we have demonstrated that the proposed method is numerically more efficient, compared to several existing implicit methods.

Efficient solutions to the Euler equations for supersonic flow with embedded subsonic regions

NASA Technical Reports Server (NTRS)

Walters, Robert W.; Dwoyer, Douglas L.

1987-01-01

A line Gauss-Seidel (LGS) relaxation algorithm in conjunction with a one-parameter family of upwind discretizations of the Euler equations in two dimensions is described. Convergence of the basic algorithm to the steady state is quadratic for fully supersonic flows and is linear for other flows. This is in contrast to the block alternating direction implicit methods (either central or upwind differenced) and the upwind biased relaxation schemes, all of which converge linearly, independent of the flow regime. Moreover, the algorithm presented herein is easily coupled with methods to detect regions of subsonic flow embedded in supersonic flow. This allows marching by lines in the supersonic regions, converging each line quadratically, and iterating in the subsonic regions, and yields a very efficient iteration strategy. Numerical results are presented for two-dimensional supersonic and transonic flows containing oblique and normal shock waves which confirm the efficiency of the iteration strategy.

Estimation of Energy Expenditure Using a Patch-Type Sensor Module with an Incremental Radial Basis Function Neural Network

PubMed Central

Li, Meina; Kwak, Keun-Chang; Kim, Youn Tae

2016-01-01

Conventionally, indirect calorimetry has been used to estimate oxygen consumption in an effort to accurately measure human body energy expenditure. However, calorimetry requires the subject to wear a mask that is neither convenient nor comfortable. The purpose of our study is to develop a patch-type sensor module with an embedded incremental radial basis function neural network (RBFNN) for estimating the energy expenditure. The sensor module contains one ECG electrode and a three-axis accelerometer, and can perform real-time heart rate (HR) and movement index (MI) monitoring. The embedded incremental network includes linear regression (LR) and RBFNN based on context-based fuzzy c-means (CFCM) clustering. This incremental network is constructed by building a collection of information granules through CFCM clustering that is guided by the distribution of error of the linear part of the LR model. PMID:27669249

Experimental investigation of a general real-time 3D target localization method using sequential kV imaging combined with respiratory monitoring.

PubMed

Cho, Byungchul; Poulsen, Per; Ruan, Dan; Sawant, Amit; Keall, Paul J

2012-11-21

The goal of this work was to experimentally quantify the geometric accuracy of a novel real-time 3D target localization method using sequential kV imaging combined with respiratory monitoring for clinically realistic arc and static field treatment delivery and target motion conditions. A general method for real-time target localization using kV imaging and respiratory monitoring was developed. Each dimension of internal target motion T(x, y, z; t) was estimated from the external respiratory signal R(t) through the correlation between R(t(i)) and the projected marker positions p(x(p), y(p); t(i)) on kV images by a state-augmented linear model: T(x, y, z; t) = aR(t) + bR(t - τ) + c. The model parameters, a, b, c, were determined by minimizing the squared fitting error ∑‖p(x(p), y(p); t(i)) - P(θ(i)) · (aR(t(i)) + bR(t(i) - τ) + c)‖(2) with the projection operator P(θ(i)). The model parameters were first initialized based on acquired kV arc images prior to MV beam delivery. This method was implemented on a trilogy linear accelerator consisting of an OBI x-ray imager (operating at 1 Hz) and real-time position monitoring (RPM) system (30 Hz). Arc and static field plans were delivered to a moving phantom programmed with measured lung tumour motion from ten patients. During delivery, the localization method determined the target position and the beam was adjusted in real time via dynamic multileaf collimator (DMLC) adaptation. The beam-target alignment error was quantified by segmenting the beam aperture and a phantom-embedded fiducial marker on MV images and analysing their relative position. With the localization method, the root-mean-squared errors of the ten lung tumour traces ranged from 0.7-1.3 mm and 0.8-1.4 mm during the single arc and five-field static beam delivery, respectively. Without the localization method, these errors ranged from 3.1-7.3 mm. In summary, a general method for real-time target localization using kV imaging and respiratory monitoring has been experimentally investigated for arc and static field delivery. The average beam-target error was 1 mm.

Experimental investigation of a general real-time 3D target localization method using sequential kV imaging combined with respiratory monitoring

NASA Astrophysics Data System (ADS)

Cho, Byungchul; Poulsen, Per; Ruan, Dan; Sawant, Amit; Keall, Paul J.

2012-11-01

The goal of this work was to experimentally quantify the geometric accuracy of a novel real-time 3D target localization method using sequential kV imaging combined with respiratory monitoring for clinically realistic arc and static field treatment delivery and target motion conditions. A general method for real-time target localization using kV imaging and respiratory monitoring was developed. Each dimension of internal target motion T(x, y, z; t) was estimated from the external respiratory signal R(t) through the correlation between R(ti) and the projected marker positions p(xp, yp; ti) on kV images by a state-augmented linear model: T(x, y, z; t) = aR(t) + bR(t - τ) + c. The model parameters, a, b, c, were determined by minimizing the squared fitting error ∑‖p(xp, yp; ti) - P(θi) · (aR(ti) + bR(ti - τ) + c)‖2 with the projection operator P(θi). The model parameters were first initialized based on acquired kV arc images prior to MV beam delivery. This method was implemented on a trilogy linear accelerator consisting of an OBI x-ray imager (operating at 1 Hz) and real-time position monitoring (RPM) system (30 Hz). Arc and static field plans were delivered to a moving phantom programmed with measured lung tumour motion from ten patients. During delivery, the localization method determined the target position and the beam was adjusted in real time via dynamic multileaf collimator (DMLC) adaptation. The beam-target alignment error was quantified by segmenting the beam aperture and a phantom-embedded fiducial marker on MV images and analysing their relative position. With the localization method, the root-mean-squared errors of the ten lung tumour traces ranged from 0.7-1.3 mm and 0.8-1.4 mm during the single arc and five-field static beam delivery, respectively. Without the localization method, these errors ranged from 3.1-7.3 mm. In summary, a general method for real-time target localization using kV imaging and respiratory monitoring has been experimentally investigated for arc and static field delivery. The average beam-target error was 1 mm.

Flexible embedding of networks

NASA Astrophysics Data System (ADS)

Fernandez-Gracia, Juan; Buckee, Caroline; Onnela, Jukka-Pekka

We introduce a model for embedding one network into another, focusing on the case where network A is much bigger than network B. Nodes from network A are assigned to the nodes in network B using an algorithm where we control the extent of localization of node placement in network B using a single parameter. Starting from an unassigned node in network A, called the source node, we first map this node to a randomly chosen node in network B, called the target node. We then assign the neighbors of the source node to the neighborhood of the target node using a random walk based approach. To assign each neighbor of the source node to one of the nodes in network B, we perform a random walk starting from the target node with stopping probability α. We repeat this process until all nodes in network A have been mapped to the nodes of network B. The simplicity of the model allows us to calculate key quantities of interest in closed form. By varying the parameter α, we are able to produce embeddings from very local (α = 1) to very global (α --> 0). We show how our calculations fit the simulated results, and we apply the model to study how social networks are embedded in geography and how the neurons of C. Elegans are embedded in the surrounding volume.

Fabrication and evaluation of plasmonic light-emitting diodes with thin p-type layer and localized Ag particles embedded by ITO

NASA Astrophysics Data System (ADS)

Okada, N.; Morishita, N.; Mori, A.; Tsukada, T.; Tateishi, K.; Okamoto, K.; Tadatomo, K.

2017-04-01

Light-emitting diodes (LEDs) have been demonstrated with a thin p-type layer using the plasmonic effect. Optimal LED device operation was found when using a 20-nm-thick p+-GaN layer. Ag of different thicknesses was deposited on the thin p-type layer and annealed to form the localized Ag particles. The localized Ag particles were embedded by indium tin oxide to form a p-type electrode in the LED structure. By optimization of the plasmonic LED, the significant electroluminescence enhancement was observed when the thickness of Ag was 9.5 nm. Both upward and downward electroluminescence intensities were improved, and the external quantum efficiency was approximately double that of LEDs without the localized Ag particles. The time-resolved photoluminescence (PL) decay time for the LED with the localized Ag particles was shorter than that without the localized Ag particles. The faster PL decay time should cause the increase in internal quantum efficiency by adopting the localized Ag particles. To validate the localized surface plasmon resonance coupling effect, the absorption of the LEDs was investigated experimentally and using simulations.

Spatial network surrogates for disentangling complex system structure from spatial embedding of nodes

NASA Astrophysics Data System (ADS)

Wiedermann, Marc; Donges, Jonathan F.; Kurths, Jürgen; Donner, Reik V.

2016-04-01

Networks with nodes embedded in a metric space have gained increasing interest in recent years. The effects of spatial embedding on the networks' structural characteristics, however, are rarely taken into account when studying their macroscopic properties. Here, we propose a hierarchy of null models to generate random surrogates from a given spatially embedded network that can preserve certain global and local statistics associated with the nodes' embedding in a metric space. Comparing the original network's and the resulting surrogates' global characteristics allows one to quantify to what extent these characteristics are already predetermined by the spatial embedding of the nodes and links. We apply our framework to various real-world spatial networks and show that the proposed models capture macroscopic properties of the networks under study much better than standard random network models that do not account for the nodes' spatial embedding. Depending on the actual performance of the proposed null models, the networks are categorized into different classes. Since many real-world complex networks are in fact spatial networks, the proposed approach is relevant for disentangling the underlying complex system structure from spatial embedding of nodes in many fields, ranging from social systems over infrastructure and neurophysiology to climatology.

Ensemble Manifold Rank Preserving for Acceleration-Based Human Activity Recognition.

PubMed

Tao, Dapeng; Jin, Lianwen; Yuan, Yuan; Xue, Yang

2016-06-01

With the rapid development of mobile devices and pervasive computing technologies, acceleration-based human activity recognition, a difficult yet essential problem in mobile apps, has received intensive attention recently. Different acceleration signals for representing different activities or even a same activity have different attributes, which causes troubles in normalizing the signals. We thus cannot directly compare these signals with each other, because they are embedded in a nonmetric space. Therefore, we present a nonmetric scheme that retains discriminative and robust frequency domain information by developing a novel ensemble manifold rank preserving (EMRP) algorithm. EMRP simultaneously considers three aspects: 1) it encodes the local geometry using the ranking order information of intraclass samples distributed on local patches; 2) it keeps the discriminative information by maximizing the margin between samples of different classes; and 3) it finds the optimal linear combination of the alignment matrices to approximate the intrinsic manifold lied in the data. Experiments are conducted on the South China University of Technology naturalistic 3-D acceleration-based activity dataset and the naturalistic mobile-devices based human activity dataset to demonstrate the robustness and effectiveness of the new nonmetric scheme for acceleration-based human activity recognition.

Continuum description of solvent dielectrics in molecular-dynamics simulations of proteins

NASA Astrophysics Data System (ADS)

Egwolf, Bernhard; Tavan, Paul

2003-02-01

We present a continuum approach for efficient and accurate calculation of reaction field forces and energies in classical molecular-dynamics (MD) simulations of proteins in water. The derivation proceeds in two steps. First, we reformulate the electrostatics of an arbitrarily shaped molecular system, which contains partially charged atoms and is embedded in a dielectric continuum representing the water. A so-called fuzzy partition is used to exactly decompose the system into partial atomic volumes. The reaction field is expressed by means of dipole densities localized at the atoms. Since these densities cannot be calculated analytically for general systems, we introduce and carefully analyze a set of approximations in a second step. These approximations allow us to represent the dipole densities by simple dipoles localized at the atoms. We derive a system of linear equations for these dipoles, which can be solved numerically by iteration. After determining the two free parameters of our approximate method we check its quality by comparisons (i) with an analytical solution, which is available for a perfectly spherical system, (ii) with forces obtained from a MD simulation of a soluble protein in water, and (iii) with reaction field energies of small molecules calculated by a finite difference method.

Bearing diagnostics: A method based on differential geometry

NASA Astrophysics Data System (ADS)

Tian, Ye; Wang, Zili; Lu, Chen; Wang, Zhipeng

2016-12-01

The structures around bearings are complex, and the working environment is variable. These conditions cause the collected vibration signals to become nonlinear, non-stationary, and chaotic characteristics that make noise reduction, feature extraction, fault diagnosis, and health assessment significantly challenging. Thus, a set of differential geometry-based methods with superiorities in nonlinear analysis is presented in this study. For noise reduction, the Local Projection method is modified by both selecting the neighborhood radius based on empirical mode decomposition and determining noise subspace constrained by neighborhood distribution information. For feature extraction, Hessian locally linear embedding is introduced to acquire manifold features from the manifold topological structures, and singular values of eigenmatrices as well as several specific frequency amplitudes in spectrograms are extracted subsequently to reduce the complexity of the manifold features. For fault diagnosis, information geometry-based support vector machine is applied to classify the fault states. For health assessment, the manifold distance is employed to represent the health information; the Gaussian mixture model is utilized to calculate the confidence values, which directly reflect the health status. Case studies on Lorenz signals and vibration datasets of bearings demonstrate the effectiveness of the proposed methods.

Embedded and conventional ultrasonic sensors for monitoring acoustic emission during thermal fatigue

NASA Astrophysics Data System (ADS)

Trujillo, Blaine; Zagrai, Andrei

2016-04-01

Acoustic emission is widely used for monitoring pressure vessels, pipes, critical infrastructure, as well as land, sea and air vehicles. It is one of dominant approaches to explore material degradation under fatigue and events leading to material fracture. Addressing a recent interest in structural health monitoring of space vehicles, a need has emerged to evaluate material deterioration due to thermal fatigue during spacecraft atmospheric reentry. Thermal fatigue experiments were conducted, in which aluminum plates were subjected to localized heating and acoustic emission was monitoring by embedded and conventional acoustic emission sensors positioned at various distances from a heat source. At the same time, surface temperature of aluminum plates was monitored using an IR camera. Acoustic emission counts collected by embedded sensors were compared to counts measured with conventional acoustic emission sensors. Both types of sensors show noticeable increase of acoustic emission activity as localized heating source was applied to aluminum plates. Experimental data demonstrate correlation between temperature increase on the surface of the plates and increase in measured acoustic emission activity. It is concluded that under particular conditions, embedded piezoelectric wafer active sensors can be used for acoustic emission monitoring of thermally-induced structural degradation.

Identity Formation of American Indian Adolescents: Local, National, and Global Considerations

ERIC Educational Resources Information Center

Markstrom, Carol A.

2011-01-01

A conceptual model is presented that approaches identity formation of American Indian adolescents according to 3 levels of social contextual influence--local, national, and global--relative to types of identity, dynamics of identity, and sources of influence. Ethnic identity of American Indians is embedded within the local cultural milieu and…

Implementation of software-based sensor linearization algorithms on low-cost microcontrollers.

PubMed

Erdem, Hamit

2010-10-01

Nonlinear sensors and microcontrollers are used in many embedded system designs. As the input-output characteristic of most sensors is nonlinear in nature, obtaining data from a nonlinear sensor by using an integer microcontroller has always been a design challenge. This paper discusses the implementation of six software-based sensor linearization algorithms for low-cost microcontrollers. The comparative study of the linearization algorithms is performed by using a nonlinear optical distance-measuring sensor. The performance of the algorithms is examined with respect to memory space usage, linearization accuracy and algorithm execution time. The implementation and comparison results can be used for selection of a linearization algorithm based on the sensor transfer function, expected linearization accuracy and microcontroller capacity. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Metascalable molecular dynamics simulation of nano-mechano-chemistry

NASA Astrophysics Data System (ADS)

Shimojo, F.; Kalia, R. K.; Nakano, A.; Nomura, K.; Vashishta, P.

2008-07-01

We have developed a metascalable (or 'design once, scale on new architectures') parallel application-development framework for first-principles based simulations of nano-mechano-chemical processes on emerging petaflops architectures based on spatiotemporal data locality principles. The framework consists of (1) an embedded divide-and-conquer (EDC) algorithmic framework based on spatial locality to design linear-scaling algorithms, (2) a space-time-ensemble parallel (STEP) approach based on temporal locality to predict long-time dynamics, and (3) a tunable hierarchical cellular decomposition (HCD) parallelization framework to map these scalable algorithms onto hardware. The EDC-STEP-HCD framework exposes and expresses maximal concurrency and data locality, thereby achieving parallel efficiency as high as 0.99 for 1.59-billion-atom reactive force field molecular dynamics (MD) and 17.7-million-atom (1.56 trillion electronic degrees of freedom) quantum mechanical (QM) MD in the framework of the density functional theory (DFT) on adaptive multigrids, in addition to 201-billion-atom nonreactive MD, on 196 608 IBM BlueGene/L processors. We have also used the framework for automated execution of adaptive hybrid DFT/MD simulation on a grid of six supercomputers in the US and Japan, in which the number of processors changed dynamically on demand and tasks were migrated according to unexpected faults. The paper presents the application of the framework to the study of nanoenergetic materials: (1) combustion of an Al/Fe2O3 thermite and (2) shock initiation and reactive nanojets at a void in an energetic crystal.

Lectin-binding histochemistry of non-decalcified growth plate cartilage: a postembedment method for light microscopy of epon-embedded tissue.

PubMed

Farnum, C E; Wilsman, N J

1984-06-01

A postembedment method for the localization of lectin-binding glycoconjugates was developed using Epon-embedded growth plate cartilage from Yucatan miniature swine. By testing a variety of etching, blocking, and incubation procedures, a standard protocol was developed for 1 micron thick sections that allowed visualization of both intracellular and extracellular glycoconjugates with affinity for wheat germ agglutinin and concanavalin A. Both fluorescent and peroxidase techniques were used, and comparisons were made between direct methods and indirect methods using the biotin-avidin bridging system. Differential extracellular lectin binding allowed visualization of interterritorial , territorial, and pericellular matrices. Double labeling experiments showed the precision with which intracellular binding could be localized to specific cytoplasmic compartments, with resolution of binding to the Golgi apparatus, endoplasmic reticulum, and nuclear membrane at the light microscopic level. This method allows the localization of both intracellular and extracellular lectin-binding glycoconjugates using fixation and embedment procedures that are compatible with simultaneous ultrastructural analysis. As such it should have applicability both to the morphological analysis of growth plate organization during normal endochondral ossification, as well as to the diagnostic pathology of matrix abnormalities in disease states of growing cartilage.

The Leuven Embedded Figures Test (L-EFT): measuring perception, intelligence or executive function?

PubMed Central

Van der Hallen, Ruth; Wagemans, Johan; de-Wit, Lee; Chamberlain, Rebecca

2018-01-01

Performance on the Embedded Figures Test (EFT) has been interpreted as a reflection of local/global perceptual style, weak central coherence and/or field independence, as well as a measure of intelligence and executive function. The variable ways in which EFT findings have been interpreted demonstrate that the construct validity of this measure is unclear. In order to address this lack of clarity, we investigated to what extent performance on a new Embedded Figures Test (L-EFT) correlated with measures of intelligence, executive functions and estimates of local/global perceptual styles. In addition, we compared L-EFT performance to the original group EFT to directly contrast both tasks. Taken together, our results indicate that performance on the L-EFT does not correlate strongly with estimates of local/global perceptual style, intelligence or executive functions. Additionally, the results show that performance on the L-EFT is similarly associated with memory span and fluid intelligence as the group EFT. These results suggest that the L-EFT does not reflect a general perceptual or cognitive style/ability. These results further emphasize that empirical data on the construct validity of a task do not always align with the face validity of a task. PMID:29607257

Gravitational energy in the framework of embedding and splitting theories

NASA Astrophysics Data System (ADS)

Grad, D. A.; Ilin, R. V.; Paston, S. A.; Sheykin, A. A.

We study various definitions of the gravitational field energy based on the usage of isometric embeddings in the Regge-Teitelboim approach. For the embedding theory, we consider the coordinate translations on the surface as well as the coordinate translations in the flat bulk. In the latter case, the independent definition of gravitational energy-momentum tensor appears as a Noether current corresponding to global inner symmetry. In the field-theoretic form of this approach (splitting theory), we consider Noether procedure and the alternative method of energy-momentum tensor defining by varying the action of the theory with respect to flat bulk metric. As a result, we obtain energy definition in field-theoretic form of embedding theory which, among the other features, gives a nontrivial result for the solutions of embedding theory which are also solutions of Einstein equations. The question of energy localization is also discussed.

Internship Abstract and Final Reflection

NASA Technical Reports Server (NTRS)

Sandor, Edward

2016-01-01

The primary objective for this internship is the evaluation of an embedded natural language processor (NLP) as a way to introduce voice control into future space suits. An embedded natural language processor would provide an astronaut hands-free control for making adjustments to the environment of the space suit and checking status of consumables procedures and navigation. Additionally, the use of an embedded NLP could potentially reduce crew fatigue, increase the crewmember's situational awareness during extravehicular activity (EVA) and improve the ability to focus on mission critical details. The use of an embedded NLP may be valuable for other human spaceflight applications desiring hands-free control as well. An embedded NLP is unique because it is a small device that performs language tasks, including speech recognition, which normally require powerful processors. The dedicated device could perform speech recognition locally with a smaller form-factor and lower power consumption than traditional methods.

Percolation of spatially constraint networks

NASA Astrophysics Data System (ADS)

Li, Daqing; Li, Guanliang; Kosmidis, Kosmas; Stanley, H. E.; Bunde, Armin; Havlin, Shlomo

2011-03-01

We study how spatial constraints are reflected in the percolation properties of networks embedded in one-dimensional chains and two-dimensional lattices. We assume long-range connections between sites on the lattice where two sites at distance r are chosen to be linked with probability p(r)~r-δ. Similar distributions have been found in spatially embedded real networks such as social and airline networks. We find that for networks embedded in two dimensions, with 2<δ<4, the percolation properties show new intermediate behavior different from mean field, with critical exponents that depend on δ. For δ<2, the percolation transition belongs to the universality class of percolation in Erdös-Rényi networks (mean field), while for δ>4 it belongs to the universality class of percolation in regular lattices. For networks embedded in one dimension, we find that, for δ<1, the percolation transition is mean field. For 1<δ<2, the critical exponents depend on δ, while for δ>2 there is no percolation transition as in regular linear chains.

Positron accumulation effect in particles embedded in a low-density matrix

NASA Astrophysics Data System (ADS)

Dryzek, Jerzy; Siemek, Krzysztof

2015-02-01

Systematic studies of the so-called positron accumulation effect for samples with particles embedded in a matrix are reported. This effect is related to energetic positrons which penetrate inhomogeneous medium. Due to differences in the linear absorption coefficient, different amounts of positrons are accumulated and annihilate in the identical volume of both materials. Positron lifetime spectroscopy and Doppler broadening of the annihilation line using Na-22 positrons were applied to the studies of the epoxy resin samples with embedded micro-sized particles of transition metals, i.e., Ni, Sn, Mo, W, and nonmetal particles, i.e., Si and NaF. The significant difference between the determined fraction of positrons annihilating in the particles and the particle volume fraction indicates the positron accumulation effect. The simple phenomenological model and Monte Carlo simulations are able to describe the main features of the obtained dependencies. The aluminum alloy with embedded Sn nanoparticles is also considered for demonstration differences between the accumulation and another related effect, i.e., the positron affinity.

Non-linear dynamics of human locomotion: effects of rhythmic auditory cueing on local dynamic stability.

PubMed

Terrier, Philippe; Dériaz, Olivier

2013-01-01

It has been observed that times series of gait parameters [stride length (SL), stride time (ST), and stride speed (SS)], exhibit long-term persistence and fractal-like properties. Synchronizing steps with rhythmic auditory stimuli modifies the persistent fluctuation pattern to anti-persistence. Another non-linear method estimates the degree of resilience of gait control to small perturbations, i.e., the local dynamic stability (LDS). The method makes use of the maximal Lyapunov exponent, which estimates how fast a non-linear system embedded in a reconstructed state space (attractor) diverges after an infinitesimal perturbation. We propose to use an instrumented treadmill to simultaneously measure basic gait parameters (time series of SL, ST, and SS from which the statistical persistence among consecutive strides can be assessed), and the trajectory of the center of pressure (from which the LDS can be estimated). In 20 healthy participants, the response to rhythmic auditory cueing (RAC) of LDS and of statistical persistence [assessed with detrended fluctuation analysis (DFA)] was compared. By analyzing the divergence curves, we observed that long-term LDS (computed as the reverse of the average logarithmic rate of divergence between the 4th and the 10th strides downstream from nearest neighbors in the reconstructed attractor) was strongly enhanced (relative change +73%). That is likely the indication of a more dampened dynamics. The change in short-term LDS (divergence over one step) was smaller (+3%). DFA results (scaling exponents) confirmed an anti-persistent pattern in ST, SL, and SS. Long-term LDS (but not short-term LDS) and scaling exponents exhibited a significant correlation between them (r = 0.7). Both phenomena probably result from the more conscious/voluntary gait control that is required by RAC. We suggest that LDS and statistical persistence should be used to evaluate the efficiency of cueing therapy in patients with neurological gait disorders.

Efficient Measurement of Multiparticle Entanglement with Embedding Quantum Simulator.

PubMed

Chen, Ming-Cheng; Wu, Dian; Su, Zu-En; Cai, Xin-Dong; Wang, Xi-Lin; Yang, Tao; Li, Li; Liu, Nai-Le; Lu, Chao-Yang; Pan, Jian-Wei

2016-02-19

The quantum measurement of entanglement is a demanding task in the field of quantum information. Here, we report the direct and scalable measurement of multiparticle entanglement with embedding photonic quantum simulators. In this embedding framework [R. Di Candia et al. Phys. Rev. Lett. 111, 240502 (2013)], the N-qubit entanglement, which does not associate with a physical observable directly, can be efficiently measured with only two (for even N) and six (for odd N) local measurement settings. Our experiment uses multiphoton quantum simulators to mimic dynamical concurrence and three-tangle entangled systems and to track their entanglement evolutions.

Local Laplacian Coding From Theoretical Analysis of Local Coding Schemes for Locally Linear Classification.

PubMed

Pang, Junbiao; Qin, Lei; Zhang, Chunjie; Zhang, Weigang; Huang, Qingming; Yin, Baocai

2015-12-01

Local coordinate coding (LCC) is a framework to approximate a Lipschitz smooth function by combining linear functions into a nonlinear one. For locally linear classification, LCC requires a coding scheme that heavily determines the nonlinear approximation ability, posing two main challenges: 1) the locality making faraway anchors have smaller influences on current data and 2) the flexibility balancing well between the reconstruction of current data and the locality. In this paper, we address the problem from the theoretical analysis of the simplest local coding schemes, i.e., local Gaussian coding and local student coding, and propose local Laplacian coding (LPC) to achieve the locality and the flexibility. We apply LPC into locally linear classifiers to solve diverse classification tasks. The comparable or exceeded performances of state-of-the-art methods demonstrate the effectiveness of the proposed method.

Influence of the geometric configuration of accretion flow on the black hole spin dependence of relativistic acoustic geometry

NASA Astrophysics Data System (ADS)

Tarafdar, Pratik; Das, Tapas K.

Linear perturbation of general relativistic accretion of low angular momentum hydrodynamic fluid onto a Kerr black hole leads to the formation of curved acoustic geometry embedded within the background flow. Characteristic features of such sonic geometry depend on the black hole spin. Such dependence can be probed by studying the correlation of the acoustic surface gravity κ with the Kerr parameter a. The κ-a relationship further gets influenced by the geometric configuration of the accretion flow structure. In this work, such influence has been studied for multitransonic shocked accretion where linear perturbation of general relativistic flow profile leads to the formation of two analogue black hole-type horizons formed at the sonic points and one analogue white hole-type horizon which is formed at the shock location producing divergent acoustic surface gravity. Dependence of the κ-a relationship on the geometric configuration has also been studied for monotransonic accretion, over the entire span of the Kerr parameter including retrograde flow. For accreting astrophysical black holes, the present work thus investigates how the salient features of the embedded relativistic sonic geometry may be determined not only by the background spacetime, but also by the flow configuration of the embedding matter.

Multimodal Bio-Inspired Tactile Sensing Module for Surface Characterization †

PubMed Central

Alves de Oliveira, Thiago Eustaquio; Cretu, Ana-Maria; Petriu, Emil M.

2017-01-01

Robots are expected to recognize the properties of objects in order to handle them safely and efficiently in a variety of applications, such as health and elder care, manufacturing, or high-risk environments. This paper explores the issue of surface characterization by monitoring the signals acquired by a novel bio-inspired tactile probe in contact with ridged surfaces. The tactile module comprises a nine Degree of Freedom Microelectromechanical Magnetic, Angular Rate, and Gravity system (9-DOF MEMS MARG) and a deep MEMS pressure sensor embedded in a compliant structure that mimics the function and the organization of mechanoreceptors in human skin as well as the hardness of the human skin. When the modules tip slides over a surface, the MARG unit vibrates and the deep pressure sensor captures the overall normal force exerted. The module is evaluated in two experiments. The first experiment compares the frequency content of the data collected in two setups: one when the module is mounted over a linear motion carriage that slides four grating patterns at constant velocities; the second when the module is carried by a robotic finger in contact with the same grating patterns while performing a sliding motion, similar to the exploratory motion employed by humans to detect object roughness. As expected, in the linear setup, the magnitude spectrum of the sensors’ output shows that the module can detect the applied stimuli with frequencies ranging from 3.66 Hz to 11.54 Hz with an overall maximum error of ±0.1 Hz. The second experiment shows how localized features extracted from the data collected by the robotic finger setup over seven synthetic shapes can be used to classify them. The classification method consists on applying multiscale principal components analysis prior to the classification with a multilayer neural network. Achieved accuracies from 85.1% to 98.9% for the various sensor types demonstrate the usefulness of traditional MEMS as tactile sensors embedded into flexible substrates. PMID:28545245

Season-modulated responses of Neotropical bats to forest fragmentation.

PubMed

Ferreira, Diogo F; Rocha, Ricardo; López-Baucells, Adrià; Farneda, Fábio Z; Carreiras, João M B; Palmeirim, Jorge M; Meyer, Christoph F J

2017-06-01

Seasonality causes fluctuations in resource availability, affecting the presence and abundance of animal species. The impacts of these oscillations on wildlife populations can be exacerbated by habitat fragmentation. We assessed differences in bat species abundance between the wet and dry season in a fragmented landscape in the Central Amazon characterized by primary forest fragments embedded in a secondary forest matrix. We also evaluated whether the relative importance of local vegetation structure versus landscape characteristics (composition and configuration) in shaping bat abundance patterns varied between seasons. Our working hypotheses were that abundance responses are species as well as season specific, and that in the wet season, local vegetation structure is a stronger determinant of bat abundance than landscape-scale attributes. Generalized linear mixed-effects models in combination with hierarchical partitioning revealed that relationships between species abundances and local vegetation structure and landscape characteristics were both season specific and scale dependent. Overall, landscape characteristics were more important than local vegetation characteristics, suggesting that landscape structure is likely to play an even more important role in landscapes with higher fragment-matrix contrast. Responses varied between frugivores and animalivores. In the dry season, frugivores responded more to compositional metrics, whereas during the wet season, local and configurational metrics were more important. Animalivores showed similar patterns in both seasons, responding to the same group of metrics in both seasons. Differences in responses likely reflect seasonal differences in the phenology of flowering and fruiting between primary and secondary forests, which affected the foraging behavior and habitat use of bats. Management actions should encompass multiscale approaches to account for the idiosyncratic responses of species to seasonal variation in resource abundance and consequently to local and landscape scale attributes.

Corrosion Monitors for Embedded Evaluation

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

Robinson, Alex L.; Pfeifer, Kent B.; Casias, Adrian L.

2017-05-01

We have developed and characterized novel in-situ corrosion sensors to monitor and quantify the corrosive potential and history of localized environments. Embedded corrosion sensors can provide information to aid health assessments of internal electrical components including connectors, microelectronics, wires, and other susceptible parts. When combined with other data (e.g. temperature and humidity), theory, and computational simulation, the reliability of monitored systems can be predicted with higher fidelity.

C2 at the Edge: Operating in a Disconnected Low-Bandwidth Environment

DTIC Science & Technology

2015-06-01

using their embedded Bluetooth communications capability. This thesis tests the throughput of the system at the maximum connection distances between...users with real-time chat capability of all locally available devices. 14. SUBJECT TERMS Infrastructure-less, mobile, network, Bluetooth , scatternet...thesis aims to create a communications network of smart devices, using their embedded Bluetooth communica- tions capability. This thesis tests the

Radar Based Navigation in Unknown Terrain

DTIC Science & Technology

2012-12-31

localization and mapping ( SLAM ) approach. The radar processing algorithms detect strong, persistent, and stationary reflectors embedded in the...Global System for Mobile Communications . . . . . . . . . 2 LIDAR Light Detection and Ranging . . . . . . . . . . . . . . . . 2 SAR Synthetic Aperture...22 SLAM Simultaneous Localization and Mapping . . . . . . . . . . 25 FDM Frequency Division Multiplexing

Anisotropic piezoelectric twist actuation of helicopter rotor blades: Aeroelastic analysis and design optimization

NASA Astrophysics Data System (ADS)

Wilkie, William Keats

1997-12-01

An aeroelastic model suitable for control law and preliminary structural design of composite helicopter rotor blades incorporating embedded anisotropic piezoelectric actuator laminae is developed. The aeroelasticity model consists of a linear, nonuniform beam representation of the blade structure, including linear piezoelectric actuation terms, coupled with a nonlinear, finite-state unsteady aerodynamics model. A Galerkin procedure and numerical integration in the time domain are used to obtain a soluti An aeroelastic model suitable for control law and preliminary structural design of composite helicopter rotor blades incorporating embedded anisotropic piezoelectric actuator laminae is developed. The aeroelasticity model consists of a linear, nonuniform beam representation of the blade structure, including linear piezoelectric actuation terms, coupled with a nonlinear, finite-state unsteady aerodynamics model. A Galerkin procedure and numerical integration in the time domain are used to obtain amited additional piezoelectric material mass, it is shown that blade twist actuation approaches which exploit in-plane piezoelectric free-stain anisotropies are capable of producing amplitudes of oscillatory blade twisting sufficient for rotor vibration reduction applications. The second study examines the effectiveness of using embedded piezoelectric actuator laminae to alleviate vibratory loads due to retreating blade stall. A 10 to 15 percent improvement in dynamic stall limited forward flight speed, and a 5 percent improvement in stall limited rotor thrust were numerically demonstrated for the active twist rotor blade relative to a conventional blade design. The active twist blades are also demonstrated to be more susceptible than the conventional blades to dynamic stall induced vibratory loads when not operating with twist actuation. This is the result of designing the active twist blades with low torsional stiffness in order to maximize piezoelectric twist authority. Determining the optimum tradeoff between blade torsional stiffness and piezoelectric twist actuation authority is the subject of the third study. For this investigation, a linearized hovering-flight eigenvalue analysis is developed. Linear optimal control theory is then utilized to develop an optimum active twist blade design in terms of reducing structural energy and control effort cost. The forward flight vibratory loads characteristics of the torsional stiffness optimized active twist blade are then examined using the nonlinear, forward flight aeroelastic analysis. The optimized active twist rotor blade is shown to have improved passive and active vibratory loads characteristics relative to the baseline active twist blades.

Design of UAV-Embedded Microphone Array System for Sound Source Localization in Outdoor Environments †

PubMed Central

Hoshiba, Kotaro; Washizaki, Kai; Wakabayashi, Mizuho; Ishiki, Takahiro; Bando, Yoshiaki; Gabriel, Daniel; Nakadai, Kazuhiro; Okuno, Hiroshi G.

2017-01-01

In search and rescue activities, unmanned aerial vehicles (UAV) should exploit sound information to compensate for poor visual information. This paper describes the design and implementation of a UAV-embedded microphone array system for sound source localization in outdoor environments. Four critical development problems included water-resistance of the microphone array, efficiency in assembling, reliability of wireless communication, and sufficiency of visualization tools for operators. To solve these problems, we developed a spherical microphone array system (SMAS) consisting of a microphone array, a stable wireless network communication system, and intuitive visualization tools. The performance of SMAS was evaluated with simulated data and a demonstration in the field. Results confirmed that the SMAS provides highly accurate localization, water resistance, prompt assembly, stable wireless communication, and intuitive information for observers and operators. PMID:29099790

Design of UAV-Embedded Microphone Array System for Sound Source Localization in Outdoor Environments.

PubMed

Hoshiba, Kotaro; Washizaki, Kai; Wakabayashi, Mizuho; Ishiki, Takahiro; Kumon, Makoto; Bando, Yoshiaki; Gabriel, Daniel; Nakadai, Kazuhiro; Okuno, Hiroshi G

2017-11-03

In search and rescue activities, unmanned aerial vehicles (UAV) should exploit sound information to compensate for poor visual information. This paper describes the design and implementation of a UAV-embedded microphone array system for sound source localization in outdoor environments. Four critical development problems included water-resistance of the microphone array, efficiency in assembling, reliability of wireless communication, and sufficiency of visualization tools for operators. To solve these problems, we developed a spherical microphone array system (SMAS) consisting of a microphone array, a stable wireless network communication system, and intuitive visualization tools. The performance of SMAS was evaluated with simulated data and a demonstration in the field. Results confirmed that the SMAS provides highly accurate localization, water resistance, prompt assembly, stable wireless communication, and intuitive information for observers and operators.

Spatially localized convection in a rotating layer

NASA Astrophysics Data System (ADS)

Knobloch, Edgar; Beaume, Cedric; Bergeon, Alain; Kao, Hsien-Ching

2014-11-01

We study two-dimensional stationary convection in a horizontal fluid layer heated from below and rotating about the vertical. With stress-free boundary conditions at top and bottom, spatially localized states can be found that are embedded in a self-generated background shear zone and lie on a pair of intertwined solution branches exhibiting ``slanted snaking.'' States of this type are present even in the absence of bistability between conduction and periodic convection - a consequence of the conservation of zonal momentum. With no-slip boundary conditions this quantity is no longer conserved but localized states continue to exist. These are no longer embedded in a background shear zone and exhibit standard snaking. Homotopic continuation from free-slip to no-slip boundary conditions is used to track the changes in the properties of the solutions and the associated bifurcation diagrams.

Rio Grande Basin and the modern world: Understanding scale and context

Treesearch

Joseph A. Tainter

1999-01-01

Environmental problems are social issues, embedded in economic and political contexts at the local, regional, national, and global levels. Placing environmental issues on the scale from local to global clarifies conflicts between the level at which problems originate and the level at which they must be addressed. Local issues today often originate in sources distant in...

A nonlinear Kalman filtering approach to embedded control of turbocharged diesel engines

NASA Astrophysics Data System (ADS)

Rigatos, Gerasimos; Siano, Pierluigi; Arsie, Ivan

2014-10-01

The development of efficient embedded control for turbocharged Diesel engines, requires the programming of elaborated nonlinear control and filtering methods. To this end, in this paper nonlinear control for turbocharged Diesel engines is developed with the use of Differential flatness theory and the Derivative-free nonlinear Kalman Filter. It is shown that the dynamic model of the turbocharged Diesel engine is differentially flat and admits dynamic feedback linearization. It is also shown that the dynamic model can be written in the linear Brunovsky canonical form for which a state feedback controller can be easily designed. To compensate for modeling errors and external disturbances the Derivative-free nonlinear Kalman Filter is used and redesigned as a disturbance observer. The filter consists of the Kalman Filter recursion on the linearized equivalent of the Diesel engine model and of an inverse transformation based on differential flatness theory which enables to obtain estimates for the state variables of the initial nonlinear model. Once the disturbances variables are identified it is possible to compensate them by including an additional control term in the feedback loop. The efficiency of the proposed control method is tested through simulation experiments.

Graphene-embedded 3D TiO2 inverse opal electrodes for highly efficient dye-sensitized solar cells: morphological characteristics and photocurrent enhancement.

PubMed

Kim, Hye-Na; Yoo, Haemin; Moon, Jun Hyuk

2013-05-21

We demonstrated the preparation of graphene-embedded 3D inverse opal electrodes for use in DSSCs. The graphene was incorporated locally into the top layers of the inverse opal structures and was embedded into the TiO2 matrix via post-treatment of the TiO2 precursors. DSSCs comprising the bare and 1-5 wt% graphene-incorporated TiO2 inverse opal electrodes were compared. We observed that the local arrangement of graphene sheets effectively enhanced electron transport without significantly reducing light harvesting by the dye molecules. A high efficiency of 7.5% was achieved in DSSCs prepared with the 3 wt% graphene-incorporated TiO2 inverse opal electrodes, constituting a 50% increase over the efficiencies of DSSCs prepared without graphene. The increase in efficiency was mainly attributed to an increase in J(SC), as determined by the photovoltaic parameters and the electrochemical impedance spectroscopy analysis.

Fluorescence tomography characterization for sub-surface imaging with protoporphyrin IX

PubMed Central

Kepshire, Dax; Davis, Scott C.; Dehghani, Hamid; Paulsen, Keith D.; Pogue, Brian W.

2009-01-01

Optical imaging of fluorescent objects embedded in a tissue simulating medium was characterized using non-contact based approaches to fluorescence remittance imaging (FRI) and sub-surface fluorescence diffuse optical tomography (FDOT). Using Protoporphyrin IX as a fluorescent agent, experiments were performed on tissue phantoms comprised of typical in-vivo tumor to normal tissue contrast ratios, ranging from 3.5:1 up to 10:1. It was found that tomographic imaging was able to recover interior inclusions with high contrast relative to the background; however, simple planar fluorescence imaging provided a superior contrast to noise ratio. Overall, FRI performed optimally when the object was located on or close to the surface and, perhaps most importantly, FDOT was able to recover specific depth information about the location of embedded regions. The results indicate that an optimal system for localizing embedded fluorescent regions should combine fluorescence reflectance imaging for high sensitivity and sub-surface tomography for depth detection, thereby allowing more accurate localization in all three directions within the tissue. PMID:18545571

Identification of the Rice Wines with Different Marked Ages by Electronic Nose Coupled with Smartphone and Cloud Storage Platform

PubMed Central

Wei, Zhebo; Xiao, Xize

2017-01-01

In this study, a portable electronic nose (E-nose) was self-developed to identify rice wines with different marked ages—all the operations of the E-nose were controlled by a special Smartphone Application. The sensor array of the E-nose was comprised of 12 MOS sensors and the obtained response values were transmitted to the Smartphone thorough a wireless communication module. Then, Aliyun worked as a cloud storage platform for the storage of responses and identification models. The measurement of the E-nose was composed of the taste information obtained phase (TIOP) and the aftertaste information obtained phase (AIOP). The area feature data obtained from the TIOP and the feature data obtained from the TIOP-AIOP were applied to identify rice wines by using pattern recognition methods. Principal component analysis (PCA), locally linear embedding (LLE) and linear discriminant analysis (LDA) were applied for the classification of those wine samples. LDA based on the area feature data obtained from the TIOP-AIOP proved a powerful tool and showed the best classification results. Partial least-squares regression (PLSR) and support vector machine (SVM) were applied for the predictions of marked ages and SVM (R2 = 0.9942) worked much better than PLSR. PMID:29088076

Kinetic solvers with adaptive mesh in phase space

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Identification of the Rice Wines with Different Marked Ages by Electronic Nose Coupled with Smartphone and Cloud Storage Platform.

PubMed

Wei, Zhebo; Xiao, Xize; Wang, Jun; Wang, Hui

2017-10-31

In this study, a portable electronic nose (E-nose) was self-developed to identify rice wines with different marked ages-all the operations of the E-nose were controlled by a special Smartphone Application. The sensor array of the E-nose was comprised of 12 MOS sensors and the obtained response values were transmitted to the Smartphone thorough a wireless communication module. Then, Aliyun worked as a cloud storage platform for the storage of responses and identification models. The measurement of the E-nose was composed of the taste information obtained phase (TIOP) and the aftertaste information obtained phase (AIOP). The area feature data obtained from the TIOP and the feature data obtained from the TIOP-AIOP were applied to identify rice wines by using pattern recognition methods. Principal component analysis (PCA), locally linear embedding (LLE) and linear discriminant analysis (LDA) were applied for the classification of those wine samples. LDA based on the area feature data obtained from the TIOP-AIOP proved a powerful tool and showed the best classification results. Partial least-squares regression (PLSR) and support vector machine (SVM) were applied for the predictions of marked ages and SVM (R² = 0.9942) worked much better than PLSR.

Kinetic solvers with adaptive mesh in phase space.

PubMed

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

2013-12-01

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

Microstructure of the smart composite structures with embedded fiber optic sensing nerves

NASA Astrophysics Data System (ADS)

Liu, Jingyuan; Luo, Fei; Li, Changchun; Ma, Naibin

1997-11-01

The composite structures with embedded optical fiber sensors construct a smart composite structure system, which may have the characteristics of the in-service self-measurement, self- recognition and self-judgement action. In the present work, we studied the microstructures of carbon/epoxy composite laminates with embedded sensing optical fibers, and the integration of optical fiber with composites was also discussed. The preliminary experiment results show that because of the difference between the sensing optical fibers and the reinforcing fibers in their size, the microstructure of the composites with embedded optical fibers will produce partial local changes in the area of embedded optical fiber, these changes may affect the mechanical properties of composite structures. When the optical fibers are embedded parallel to the reinforcing fibers, due to the composite prepregs are formed under a press action during its curing process, the reinforcing fibers can be arranged equably around the optical fibers. But when the optical fibers are embedded perpendicularly to the reinforcement fibers, the resin rich pocket will appear in the composite laminates surrounding the embedded optical fiber. The gas holes will be easily produced in these zones which may produce a premature failure of the composite structure. The photoelastic experiments are also given in the paper.

Semi-Supervised Tensor-Based Graph Embedding Learning and Its Application to Visual Discriminant Tracking.

PubMed

Hu, Weiming; Gao, Jin; Xing, Junliang; Zhang, Chao; Maybank, Stephen

2017-01-01

An appearance model adaptable to changes in object appearance is critical in visual object tracking. In this paper, we treat an image patch as a two-order tensor which preserves the original image structure. We design two graphs for characterizing the intrinsic local geometrical structure of the tensor samples of the object and the background. Graph embedding is used to reduce the dimensions of the tensors while preserving the structure of the graphs. Then, a discriminant embedding space is constructed. We prove two propositions for finding the transformation matrices which are used to map the original tensor samples to the tensor-based graph embedding space. In order to encode more discriminant information in the embedding space, we propose a transfer-learning- based semi-supervised strategy to iteratively adjust the embedding space into which discriminative information obtained from earlier times is transferred. We apply the proposed semi-supervised tensor-based graph embedding learning algorithm to visual tracking. The new tracking algorithm captures an object's appearance characteristics during tracking and uses a particle filter to estimate the optimal object state. Experimental results on the CVPR 2013 benchmark dataset demonstrate the effectiveness of the proposed tracking algorithm.

The broader cognitive phenotype of autism in parents: how specific is the tendency for local processing and executive dysfunction?

PubMed

Bölte, Sven; Poustka, Fritz

2006-06-01

The objective of this study was to investigate the tendency for local processing style ('weak central coherence') and executive dysfunction in parents of subjects with an autism spectrum disorder (ASD) compared with parents of individuals with early onset schizophrenia (EOS) and mental retardation (MR). Sixty-two parents of subjects with ASD, 36 parents of subjects with EOS and 30 parents of subjects with MR were examined. Data on two scales indicative of local visual processing (Embedded Figures Test, Block Design) and on three executive function tests (Wisconsin Card Sorting Test, Tower of Hanoi, Trailmaking Test) were collected for all participants. Parents of subjects with ASD performed significantly faster on the Embedded Figures Test compared with both control samples. No other substantial group differences were observed. The findings indicate that an increased tendency for local processing in terms of visual disembedding could be a relatively specific core feature of the broader cognitive phenotype of autism in parents.

A novel versatile microbiosensor for local hydrogen detection by means of scanning photoelectrochemical microscopy.

PubMed

Zhao, Fangyuan; Conzuelo, Felipe; Hartmann, Volker; Li, Huaiguang; Stapf, Stefanie; Nowaczyk, Marc M; Rögner, Matthias; Plumeré, Nicolas; Lubitz, Wolfgang; Schuhmann, Wolfgang

2017-08-15

The development of a versatile microbiosensor for hydrogen detection is reported. Carbon-based microelectrodes were modified with a [NiFe]-hydrogenase embedded in a viologen-modified redox hydrogel for the fabrication of a sensitive hydrogen biosensor By integrating the microbiosensor in a scanning photoelectrochemical microscope, it was capable of serving simultaneously as local light source to initiate photo(bio)electrochemical reactions while acting as sensitive biosensor for the detection of hydrogen. A hydrogen evolution biocatalyst based on photosystem 1-platinum nanoparticle biocomplexes embedded into a specifically designed redox polymer was used as a model for proving the capability of the developed hydrogen biosensor for the detection of hydrogen upon localized illumination. The versatility and sensitivity of the proposed microbiosensor as probe tip allows simplification of the set-up used for the evaluation of complex electrochemical processes and the rapid investigation of local photoelectrocatalytic activity of biocatalysts towards light-induced hydrogen evolution. Copyright © 2017 Elsevier B.V. All rights reserved.

Locating damage using integrated global-local approach with wireless sensing system and single-chip impedance measurement device.

PubMed

Lin, Tzu-Hsuan; Lu, Yung-Chi; Hung, Shih-Lin

2014-01-01

This study developed an integrated global-local approach for locating damage on building structures. A damage detection approach with a novel embedded frequency response function damage index (NEFDI) was proposed and embedded in the Imote2.NET-based wireless structural health monitoring (SHM) system to locate global damage. Local damage is then identified using an electromechanical impedance- (EMI-) based damage detection method. The electromechanical impedance was measured using a single-chip impedance measurement device which has the advantages of small size, low cost, and portability. The feasibility of the proposed damage detection scheme was studied with reference to a numerical example of a six-storey shear plane frame structure and a small-scale experimental steel frame. Numerical and experimental analysis using the integrated global-local SHM approach reveals that, after NEFDI indicates the approximate location of a damaged area, the EMI-based damage detection approach can then identify the detailed damage location in the structure of the building.

A minimization method on the basis of embedding the feasible set and the epigraph

NASA Astrophysics Data System (ADS)

Zabotin, I. Ya; Shulgina, O. N.; Yarullin, R. S.

2016-11-01

We propose a conditional minimization method of the convex nonsmooth function which belongs to the class of cutting-plane methods. During constructing iteration points a feasible set and an epigraph of the objective function are approximated by the polyhedral sets. In this connection, auxiliary problems of constructing iteration points are linear programming problems. In optimization process there is some opportunity of updating sets which approximate the epigraph. These updates are performed by periodically dropping of cutting planes which form embedding sets. Convergence of the proposed method is proved, some realizations of the method are discussed.

An Augmented Lagrangian Filter Method for Real-Time Embedded Optimization

DOE PAGES

Chiang, Nai -Yuan; Huang, Rui; Zavala, Victor M.

2017-04-17

We present a filter line-search algorithm for nonconvex continuous optimization that combines an augmented Lagrangian function and a constraint violation metric to accept and reject steps. The approach is motivated by real-time optimization applications that need to be executed on embedded computing platforms with limited memory and processor speeds. The proposed method enables primal–dual regularization of the linear algebra system that in turn permits the use of solution strategies with lower computing overheads. We prove that the proposed algorithm is globally convergent and we demonstrate the developments using a nonconvex real-time optimization application for a building heating, ventilation, and airmore » conditioning system. Our numerical tests are performed on a standard processor and on an embedded platform. Lastly, we demonstrate that the approach reduces solution times by a factor of over 1000.« less

Realization of Chinese word segmentation based on deep learning method

NASA Astrophysics Data System (ADS)

Wang, Xuefei; Wang, Mingjiang; Zhang, Qiquan

2017-08-01

In recent years, with the rapid development of deep learning, it has been widely used in the field of natural language processing. In this paper, I use the method of deep learning to achieve Chinese word segmentation, with large-scale corpus, eliminating the need to construct additional manual characteristics. In the process of Chinese word segmentation, the first step is to deal with the corpus, use word2vec to get word embedding of the corpus, each character is 50. After the word is embedded, the word embedding feature is fed to the bidirectional LSTM, add a linear layer to the hidden layer of the output, and then add a CRF to get the model implemented in this paper. Experimental results show that the method used in the 2014 People's Daily corpus to achieve a satisfactory accuracy.

An Augmented Lagrangian Filter Method for Real-Time Embedded Optimization

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

Chiang, Nai -Yuan; Huang, Rui; Zavala, Victor M.

We present a filter line-search algorithm for nonconvex continuous optimization that combines an augmented Lagrangian function and a constraint violation metric to accept and reject steps. The approach is motivated by real-time optimization applications that need to be executed on embedded computing platforms with limited memory and processor speeds. The proposed method enables primal–dual regularization of the linear algebra system that in turn permits the use of solution strategies with lower computing overheads. We prove that the proposed algorithm is globally convergent and we demonstrate the developments using a nonconvex real-time optimization application for a building heating, ventilation, and airmore » conditioning system. Our numerical tests are performed on a standard processor and on an embedded platform. Lastly, we demonstrate that the approach reduces solution times by a factor of over 1000.« less

Connes' embedding problem and winning strategies for quantum XOR games

NASA Astrophysics Data System (ADS)

Harris, Samuel J.

2017-12-01

We consider quantum XOR games, defined in the work of Regev and Vidick [ACM Trans. Comput. Theory 7, 43 (2015)], from the perspective of unitary correlations defined in the work of Harris and Paulsen [Integr. Equations Oper. Theory 89, 125 (2017)]. We show that the winning bias of a quantum XOR game in the tensor product model (respectively, the commuting model) is equal to the norm of its associated linear functional on the unitary correlation set from the appropriate model. We show that Connes' embedding problem has a positive answer if and only if every quantum XOR game has entanglement bias equal to the commuting bias. In particular, the embedding problem is equivalent to determining whether every quantum XOR game G with a winning strategy in the commuting model also has a winning strategy in the approximate finite-dimensional model.

Phonon dispersion and local density of states in NiPd alloy using modified embedded atom method potential

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

Joshi, Subodh, E-mail: subodhssgk@gmail.com; Chand, Manesh, E-mail: maneshchand@gmail.com; Dabral, Krishna, E-mail: kmkrishna.dabral@gmail.com

2016-05-06

A modified embedded atom method (MEAM) potential model up to second neighbours has been used to calculate the phonon dispersions for Ni{sub 0.55}Pd{sub 0.45} alloy in which Pd is introduced as substitutional impurity. Using the force-constants obtained from MEAM potential, the local vibrational density of states in host Ni and substitutional Pd atoms using Green’s function method has been calculated. The calculation of phonon dispersions of NiPd alloy shows a good agreement with the experimental results. Condition of resonance mode has also been investigated and resonance mode in the frequency spectrum of impurity atom at low frequency is observed.

Compressor Performance Scaling in the Presence of Non-Uniform Flow

NASA Astrophysics Data System (ADS)

Hill, David Jarrod

Fuselage-embedded engines in future aircraft will see increased flow distortions due to the ingestion of airframe boundary layers. This reduces the required propulsive power compared to podded engines. Inlet flow distortions mean that localized regions of flow within the fan and first stage compressor are operating at off-design conditions. It is important to weigh the benefit of increased vehicle propulsive efficiency against the resultant reduction in engine efficiency. High computational cost has limited most past research to single distortion studies. The objective of this thesis is to extract scaling laws for transonic compressor performance in the presence of various distortion patterns and intensities. The machine studied is the NASA R67 transonic compressor. Volumetric source terms are used to model rotor and stator blade rows. The modelling approach is an innovative combination of existing flow turning and loss models, combined with a compressible flow correction. This approach allows for a steady calculation to capture distortion transfer; as a result, the computational cost is reduced by two orders of magnitude. At peak efficiency, the rotor work coefficient and isentropic efficiency are matched within 1.4% of previously published experimental results. A key finding of this thesis is that, in non-uniform flow, the state-of-the-art loss model employed is unable to capture the impact of variations in local flow coefficient, limiting the analysis of local entropy generation. New insight explains the mechanism governing the interaction between a total temperature distortion and a compressor rotor. A parametric study comprising 16 inlet distortions reveals that for total temperature distortions, upstream flow redistribution and rotor diffusion factor changes are shown to scale linearly with distortion severity. Linear diffusion factor scaling does not hold true for total pressure distortions. For combined total temperature and total pressure distortions, the changes in rotor diffusion factor are predicted by the summation of the individual distortions, within 3.65%.

Evaluating Small Sphere Limit of the Wang-Yau Quasi-Local Energy

NASA Astrophysics Data System (ADS)

Chen, Po-Ning; Wang, Mu-Tao; Yau, Shing-Tung

2018-01-01

In this article, we study the small sphere limit of the Wang-Yau quasi-local energy defined in Wang and Yau (Phys Rev Lett 102(2):021101, 2009, Commun Math Phys 288(3):919-942, 2009). Given a point p in a spacetime N, we consider a canonical family of surfaces approaching p along its future null cone and evaluate the limit of the Wang-Yau quasi-local energy. The evaluation relies on solving an "optimal embedding equation" whose solutions represent critical points of the quasi-local energy. For a spacetime with matter fields, the scenario is similar to that of the large sphere limit found in Chen et al. (Commun Math Phys 308(3):845-863, 2011). Namely, there is a natural solution which is a local minimum, and the limit of its quasi-local energy recovers the stress-energy tensor at p. For a vacuum spacetime, the quasi-local energy vanishes to higher order and the solution of the optimal embedding equation is more complicated. Nevertheless, we are able to show that there exists a solution that is a local minimum and that the limit of its quasi-local energy is related to the Bel-Robinson tensor. Together with earlier work (Chen et al. 2011), this completes the consistency verification of the Wang-Yau quasi-local energy with all classical limits.

Instability-related delamination growth of embedded and edge delaminations. Ph.D. Thesis - Virginia Polytechnic Inst. and State Univ.

NASA Technical Reports Server (NTRS)

Whitcomb, John D.

1988-01-01

Compressive loads can cause local buckling in composite laminates that have a near surface delamination. This buckling causes load redistribution and secondary loads, which in turn cause interlaminar stresses and delamination growth. The goal of this research was to enhance the understanding of this instability-related delamination growth in laminates containing either an embedded or an edge delamination.

Localized Temperature Variations in Laser-Irradiated Composites with Embedded Fiber Bragg Grating Sensors.

PubMed

Jenkins, R Brian; Joyce, Peter; Mechtel, Deborah

2017-01-27

Fiber Bragg grating (FBG) temperature sensors are embedded in composites to detect localized temperature gradients resulting from high energy infrared laser radiation. The goal is to detect the presence of radiation on a composite structure as rapidly as possible and to identify its location, much the same way human skin senses heat. A secondary goal is to determine how a network of sensors can be optimized to detect thermal damage in laser-irradiated composite materials or structures. Initial tests are conducted on polymer matrix composites reinforced with either carbon or glass fiber with a single optical fiber embedded into each specimen. As many as three sensors in each optical fiber measure the temporal and spatial thermal response of the composite to high energy radiation incident on the surface. Additional tests use a 2 × 2 × 3 array of 12 sensors embedded in a carbon fiber/epoxy composite to simultaneously measure temperature variations at locations on the composite surface and through the thickness. Results indicate that FBGs can be used to rapidly detect temperature gradients in a composite and their location, even for a direct strike of laser radiation on a sensor, when high temperatures can cause a non-uniform thermal response and FBG decay.

Enhancing acoustic signal response and absorption of an underwater coated plate by embedding periodical inhomogeneities.

PubMed

Zhang, Yanni; Pan, Jie

2017-12-01

An underwater structure is proposed for simultaneous detection and stealth purposes by embedding periodic signal conditioning plates (SCPs) at the interface of two elastic coatings attached to an elastic plate. Results show that the embedded SCPs can enhance sound absorption at frequencies below the coincidence frequency of the plate (f c ). Significantly enhanced absorption occurs at five peaks, of which the peak due to excited localized bending resonance in the outer coating between SCPs is the most significant. When the dilatational velocity of the outer coating equals that of the inner coating, nearly total absorption occurs in a wideband, owing to strong coupling between the localized waveguide resonance in the outer coating and that in the inner coating, and the diffraction waves by the SCPs. Meanwhile, an amplified acoustic signal of over 14 dB is observed at most frequencies within 0 ∼ f c at the coatings' interface close to the SCPs' edges, owing to focused stress formed there. Peaks in the signal response at maximal 30 dB are also observed. These peak frequencies are coincident with or close to the peak frequencies of absorption, demonstrating that significantly enhanced acoustic signal and absorption can be achieved simultaneously through the use of embedded periodic SCPs.

Localized Temperature Variations in Laser-Irradiated Composites with Embedded Fiber Bragg Grating Sensors

PubMed Central

Jenkins, R. Brian; Joyce, Peter; Mechtel, Deborah

2017-01-01

Fiber Bragg grating (FBG) temperature sensors are embedded in composites to detect localized temperature gradients resulting from high energy infrared laser radiation. The goal is to detect the presence of radiation on a composite structure as rapidly as possible and to identify its location, much the same way human skin senses heat. A secondary goal is to determine how a network of sensors can be optimized to detect thermal damage in laser-irradiated composite materials or structures. Initial tests are conducted on polymer matrix composites reinforced with either carbon or glass fiber with a single optical fiber embedded into each specimen. As many as three sensors in each optical fiber measure the temporal and spatial thermal response of the composite to high energy radiation incident on the surface. Additional tests use a 2 × 2 × 3 array of 12 sensors embedded in a carbon fiber/epoxy composite to simultaneously measure temperature variations at locations on the composite surface and through the thickness. Results indicate that FBGs can be used to rapidly detect temperature gradients in a composite and their location, even for a direct strike of laser radiation on a sensor, when high temperatures can cause a non-uniform thermal response and FBG decay. PMID:28134815

Localized temperature stability of low temperature cofired ceramics

DOEpatents

Dai, Steven Xunhu

2013-11-26

The present invention is directed to low temperature cofired ceramic modules having localized temperature stability by incorporating temperature coefficient of resonant frequency compensating materials locally into a multilayer LTCC module. Chemical interactions can be minimized and physical compatibility between the compensating materials and the host LTCC dielectrics can be achieved. The invention enables embedded resonators with nearly temperature-independent resonance frequency.

Surface plasmon-enhanced light-emitting diodes using silver nanoparticles embedded in p-GaN.

PubMed

Cho, Chu-Young; Kwon, Min-Ki; Lee, Sang-Jun; Han, Sang-Heon; Kang, Jang-Won; Kang, Se-Eun; Lee, Dong-Yul; Park, Seong-Ju

2010-05-21

We demonstrate the surface plasmon-enhanced blue light-emitting diodes (LEDs) using Ag nanoparticles embedded in p-GaN. A large increase in optical output power of 38% is achieved at an injection current of 20 mA due to an improved internal quantum efficiency of the LEDs. The enhancement of optical output power is dependent on the density of the Ag nanoparticles. This improvement can be attributed to an increase in the spontaneous emission rate through resonance coupling between the excitons in multiple quantum wells and localized surface plasmons in Ag nanoparticles embedded in p-GaN.

Controlling the Localization of Liquid Droplets in Polymer Matrices by Evaporative Lithography.

PubMed

Zhao, Huaixia; Xu, Jiajia; Jing, Guangyin; Prieto-López, Lizbeth Ofelia; Deng, Xu; Cui, Jiaxi

2016-08-26

Localized inclusions of liquids provide solid materials with many functions, such as self-healing, secretion, and tunable mechanical properties, in a spatially controlled mode. However, a strategy to control the distribution of liquid droplets in solid matrices directly obtained from a homogeneous solution has not been reported thus far. Herein, we describe an approach to selectively localize liquid droplets in a supramolecular gel directly obtained from its solution by using evaporative lithography. In this process, the formation of droplet-embedded domains occurs in regions of free evaporation where the non-volatile liquid is concentrated and undergoes a phase separation to create liquid droplets prior to gelation, while a homogeneous gel matrix is formed in the regions of hindered evaporation. The different regions of a coating with droplet embedment patterns display different secretion abilities, enabling the control of the directional movement of water droplets. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Visual analysis of mass cytometry data by hierarchical stochastic neighbour embedding reveals rare cell types.

PubMed

van Unen, Vincent; Höllt, Thomas; Pezzotti, Nicola; Li, Na; Reinders, Marcel J T; Eisemann, Elmar; Koning, Frits; Vilanova, Anna; Lelieveldt, Boudewijn P F

2017-11-23

Mass cytometry allows high-resolution dissection of the cellular composition of the immune system. However, the high-dimensionality, large size, and non-linear structure of the data poses considerable challenges for the data analysis. In particular, dimensionality reduction-based techniques like t-SNE offer single-cell resolution but are limited in the number of cells that can be analyzed. Here we introduce Hierarchical Stochastic Neighbor Embedding (HSNE) for the analysis of mass cytometry data sets. HSNE constructs a hierarchy of non-linear similarities that can be interactively explored with a stepwise increase in detail up to the single-cell level. We apply HSNE to a study on gastrointestinal disorders and three other available mass cytometry data sets. We find that HSNE efficiently replicates previous observations and identifies rare cell populations that were previously missed due to downsampling. Thus, HSNE removes the scalability limit of conventional t-SNE analysis, a feature that makes it highly suitable for the analysis of massive high-dimensional data sets.

Optical colour image watermarking based on phase-truncated linear canonical transform and image decomposition

NASA Astrophysics Data System (ADS)

Su, Yonggang; Tang, Chen; Li, Biyuan; Lei, Zhenkun

2018-05-01

This paper presents a novel optical colour image watermarking scheme based on phase-truncated linear canonical transform (PT-LCT) and image decomposition (ID). In this proposed scheme, a PT-LCT-based asymmetric cryptography is designed to encode the colour watermark into a noise-like pattern, and an ID-based multilevel embedding method is constructed to embed the encoded colour watermark into a colour host image. The PT-LCT-based asymmetric cryptography, which can be optically implemented by double random phase encoding with a quadratic phase system, can provide a higher security to resist various common cryptographic attacks. And the ID-based multilevel embedding method, which can be digitally implemented by a computer, can make the information of the colour watermark disperse better in the colour host image. The proposed colour image watermarking scheme possesses high security and can achieve a higher robustness while preserving the watermark’s invisibility. The good performance of the proposed scheme has been demonstrated by extensive experiments and comparison with other relevant schemes.

Embedded Carbide-derived Carbon (CDC) particles in polypyrrole (PPy) for linear actuator

NASA Astrophysics Data System (ADS)

Zondaka, Zane; Valner, Robert; Aabloo, Alvo; Tamm, Tarmo; Kiefer, Rudolf

2016-04-01

Conducting polymer linear actuators, for example sodium dodecylbenzenesulfonate (NaDBS) doped polypyrrole (PPy/DBS), have shown moderate strain and stress. The goal of this work was to increase the obtainable strain and stress by adding additional active material to PPy/DBS. In recent year's carbide-derived carbon (CDC)-based materials have been applied in actuators; however, the obtained displacement and actuation speed has been low comparing to conducting polymer based actuators. In the present work, a CDC-PPy hybrid was synthesized electrochemically and polyoxometalate (POM) - phosphotungstic acid - was used to attach charge to CDC particles. The CDC-POM served in the presence of NaDBS as an additional electrolyte. Cyclic voltammetry and chronopotentiometric electrochemomechanical deformation (ECMD) measurements were performed in Lithium bis(trifluoromethanesulfonyl)- imide (LiTFSI) aqueous electrolyte. The ECMD measurements revealed that the hybrid CDC-PPy material exhibited higher force and strain in comparison to PPy/DBS films. The new material was investigated by scanning electron microscopy (SEM) to evaluate CDC particle embedding in the polymer network.

Ultrametric properties of the attractor spaces for random iterated linear function systems

NASA Astrophysics Data System (ADS)

Buchovets, A. G.; Moskalev, P. V.

2018-03-01

We investigate attractors of random iterated linear function systems as independent spaces embedded in the ordinary Euclidean space. The introduction on the set of attractor points of a metric that satisfies the strengthened triangle inequality makes this space ultrametric. Then inherent in ultrametric spaces the properties of disconnectedness and hierarchical self-similarity make it possible to define an attractor as a fractal. We note that a rigorous proof of these properties in the case of an ordinary Euclidean space is very difficult.

Application of linearized inverse scattering methods for the inspection in steel plates embedded in concrete structures

NASA Astrophysics Data System (ADS)

Tsunoda, Takaya; Suzuki, Keigo; Saitoh, Takahiro

2018-04-01

This study develops a method to visualize the state of steel-concrete interface with ultrasonic testing. Scattered waves are obtained by the UT pitch-catch mode from the surface of the concrete. Discrete wavelet transform is applied in order to extract echoes scattered from the steel-concrete interface. Then Linearized Inverse Scattering Methods are used for imaging the interface. The results show that LISM with Born and Kirchhoff approximation provide clear images for the target.

Estimating contrast transfer function and associated parameters by constrained non-linear optimization.

PubMed

Yang, C; Jiang, W; Chen, D-H; Adiga, U; Ng, E G; Chiu, W

2009-03-01

The three-dimensional reconstruction of macromolecules from two-dimensional single-particle electron images requires determination and correction of the contrast transfer function (CTF) and envelope function. A computational algorithm based on constrained non-linear optimization is developed to estimate the essential parameters in the CTF and envelope function model simultaneously and automatically. The application of this estimation method is demonstrated with focal series images of amorphous carbon film as well as images of ice-embedded icosahedral virus particles suspended across holes.

Fusion of multichannel local and global structural cues for photo aesthetics evaluation.

PubMed

Luming Zhang; Yue Gao; Zimmermann, Roger; Qi Tian; Xuelong Li

2014-03-01

Photo aesthetic quality evaluation is a fundamental yet under addressed task in computer vision and image processing fields. Conventional approaches are frustrated by the following two drawbacks. First, both the local and global spatial arrangements of image regions play an important role in photo aesthetics. However, existing rules, e.g., visual balance, heuristically define which spatial distribution among the salient regions of a photo is aesthetically pleasing. Second, it is difficult to adjust visual cues from multiple channels automatically in photo aesthetics assessment. To solve these problems, we propose a new photo aesthetics evaluation framework, focusing on learning the image descriptors that characterize local and global structural aesthetics from multiple visual channels. In particular, to describe the spatial structure of the image local regions, we construct graphlets small-sized connected graphs by connecting spatially adjacent atomic regions. Since spatially adjacent graphlets distribute closely in their feature space, we project them onto a manifold and subsequently propose an embedding algorithm. The embedding algorithm encodes the photo global spatial layout into graphlets. Simultaneously, the importance of graphlets from multiple visual channels are dynamically adjusted. Finally, these post-embedding graphlets are integrated for photo aesthetics evaluation using a probabilistic model. Experimental results show that: 1) the visualized graphlets explicitly capture the aesthetically arranged atomic regions; 2) the proposed approach generalizes and improves four prominent aesthetic rules; and 3) our approach significantly outperforms state-of-the-art algorithms in photo aesthetics prediction.

Emphasizing language and visualization in teaching linear algebra

NASA Astrophysics Data System (ADS)

Hannah, John; Stewart, Sepideh; Thomas, Mike

2013-06-01

Linear algebra with its rich theoretical nature is a first step towards advanced mathematical thinking for many undergraduate students. In this paper, we consider the teaching approach of an experienced mathematician as he attempts to engage his students with the key ideas embedded in a second-year course in linear algebra. We describe his approach in both lectures and tutorials, and how he employed visualization and an emphasis on language to encourage conceptual thinking. We use Tall's framework of three worlds of mathematical thinking to reflect on the effect of these activities in students' learning. An analysis of students' attitudes to the course and their test and examination results help to answer questions about the value of such an approach, suggesting ways forward in teaching linear algebra.

Twisted versus braided magnetic flux ropes in coronal geometry. II. Comparative behaviour

NASA Astrophysics Data System (ADS)

Prior, C.; Yeates, A. R.

2016-06-01

Aims: Sigmoidal structures in the solar corona are commonly associated with magnetic flux ropes whose magnetic field lines are twisted about a mutual axis. Their dynamical evolution is well studied, with sufficient twisting leading to large-scale rotation (writhing) and vertical expansion, possibly leading to ejection. Here, we investigate the behaviour of flux ropes whose field lines have more complex entangled/braided configurations. Our hypothesis is that this internal structure will inhibit the large-scale morphological changes. Additionally, we investigate the influence of the background field within which the rope is embedded. Methods: A technique for generating tubular magnetic fields with arbitrary axial geometry and internal structure, introduced in part I of this study, provides the initial conditions for resistive-MHD simulations. The tubular fields are embedded in a linear force-free background, and we consider various internal structures for the tubular field, including both twisted and braided topologies. These embedded flux ropes are then evolved using a 3D MHD code. Results: Firstly, in a background where twisted flux ropes evolve through the expected non-linear writhing and vertical expansion, we find that flux ropes with sufficiently braided/entangled interiors show no such large-scale changes. Secondly, embedding a twisted flux rope in a background field with a sigmoidal inversion line leads to eventual reversal of the large-scale rotation. Thirdly, in some cases a braided flux rope splits due to reconnection into two twisted flux ropes of opposing chirality - a phenomenon previously observed in cylindrical configurations. Conclusions: Sufficiently complex entanglement of the magnetic field lines within a flux rope can suppress large-scale morphological changes of its axis, with magnetic energy reduced instead through reconnection and expansion. The structure of the background magnetic field can significantly affect the changing morphology of a flux rope.

Interpretation of Time Series from Nonlinear Systems. Volume 58. Proceedings of the IUTAM Symposium and NATO Advanced Research Workshop on the Interpretation of Time Series from Nonlinear Mechanical Systems Held in England on 26 - 30 August 1991,

DTIC Science & Technology

1992-01-01

VM and the correlation entropy K,(M) versus the embedding dimension M for both the linear and non-linear signals. Crosses refer to the linear signal...mensions, leading to a correlation dimension v=2.7. A similar structure was observed bv Voges et al. [461 in the analysis of the X-ray variability of...0 + 7 1j, and its recurrence plots often indicates whether a where A 0 = 10 and 71, is uniformly random dis- meaningful correlation integral analysis

Bifurcations and stability of standing waves in the nonlinear Schrödinger equation on the tadpole graph

NASA Astrophysics Data System (ADS)

Noja, Diego; Pelinovsky, Dmitry; Shaikhova, Gaukhar

2015-07-01

We develop a detailed analysis of edge bifurcations of standing waves in the nonlinear Schrödinger (NLS) equation on a tadpole graph (a ring attached to a semi-infinite line subject to the Kirchhoff boundary conditions at the junction). It is shown in the recent work [7] by using explicit Jacobi elliptic functions that the cubic NLS equation on a tadpole graph admits a rich structure of standing waves. Among these, there are different branches of localized waves bifurcating from the edge of the essential spectrum of an associated Schrödinger operator. We show by using a modified Lyapunov-Schmidt reduction method that the bifurcation of localized standing waves occurs for every positive power nonlinearity. We distinguish a primary branch of never vanishing standing waves bifurcating from the trivial solution and an infinite sequence of higher branches with oscillating behavior in the ring. The higher branches bifurcate from the branches of degenerate standing waves with vanishing tail outside the ring. Moreover, we analyze stability of bifurcating standing waves. Namely, we show that the primary branch is composed by orbitally stable standing waves for subcritical power nonlinearities, while all nontrivial higher branches are linearly unstable near the bifurcation point. The stability character of the degenerate branches remains inconclusive at the analytical level, whereas heuristic arguments based on analysis of embedded eigenvalues of negative Krein signatures support the conjecture of their linear instability at least near the bifurcation point. Numerical results for the cubic NLS equation show that this conjecture is valid and that the degenerate branches become spectrally stable far away from the bifurcation point.

Wh-filler-gap dependency formation guides reflexive antecedent search

PubMed Central

Frazier, Michael; Ackerman, Lauren; Baumann, Peter; Potter, David; Yoshida, Masaya

2015-01-01

Prior studies on online sentence processing have shown that the parser can resolve non-local dependencies rapidly and accurately. This study investigates the interaction between the processing of two such non-local dependencies: wh-filler-gap dependencies (WhFGD) and reflexive-antecedent dependencies. We show that reflexive-antecedent dependency resolution is sensitive to the presence of a WhFGD, and argue that the filler-gap dependency established by WhFGD resolution is selected online as the antecedent of a reflexive dependency. We investigate the processing of constructions like (1), where two NPs might be possible antecedents for the reflexive, namely which cowgirl and Mary. Even though Mary is linearly closer to the reflexive, the only grammatically licit antecedent for the reflexive is the more distant wh-NP, which cowgirl. (1). Which cowgirl did Mary expect to have injured herself due to negligence? Four eye-tracking text-reading experiments were conducted on examples like (1), differing in whether the embedded clause was non-finite (1 and 3) or finite (2 and 4), and in whether the tail of the wh-dependency intervened between the reflexive and its closest overt antecedent (1 and 2) or the wh-dependency was associated with a position earlier in the sentence (3 and 4). The results of Experiments 1 and 2 indicate the parser accesses the result of WhFGD formation during reflexive antecedent search. The resolution of a wh-dependency alters the representation that reflexive antecedent search operates over, allowing the grammatical but linearly distant antecedent to be accessed rapidly. In the absence of a long-distance WhFGD (Experiments 3 and 4), wh-NPs were not found to impact reading times of the reflexive, indicating that the parser's ability to select distant wh-NPs as reflexive antecedents crucially involves syntactic structure. PMID:26500579

Nonlinear vs. linear biasing in Trp-cage folding simulations

NASA Astrophysics Data System (ADS)

Spiwok, Vojtěch; Oborský, Pavel; Pazúriková, Jana; Křenek, Aleš; Králová, Blanka

2015-03-01

Biased simulations have great potential for the study of slow processes, including protein folding. Atomic motions in molecules are nonlinear, which suggests that simulations with enhanced sampling of collective motions traced by nonlinear dimensionality reduction methods may perform better than linear ones. In this study, we compare an unbiased folding simulation of the Trp-cage miniprotein with metadynamics simulations using both linear (principle component analysis) and nonlinear (Isomap) low dimensional embeddings as collective variables. Folding of the mini-protein was successfully simulated in 200 ns simulation with linear biasing and non-linear motion biasing. The folded state was correctly predicted as the free energy minimum in both simulations. We found that the advantage of linear motion biasing is that it can sample a larger conformational space, whereas the advantage of nonlinear motion biasing lies in slightly better resolution of the resulting free energy surface. In terms of sampling efficiency, both methods are comparable.

Nonlinear vs. linear biasing in Trp-cage folding simulations.

PubMed

Spiwok, Vojtěch; Oborský, Pavel; Pazúriková, Jana; Křenek, Aleš; Králová, Blanka

2015-03-21

Biased simulations have great potential for the study of slow processes, including protein folding. Atomic motions in molecules are nonlinear, which suggests that simulations with enhanced sampling of collective motions traced by nonlinear dimensionality reduction methods may perform better than linear ones. In this study, we compare an unbiased folding simulation of the Trp-cage miniprotein with metadynamics simulations using both linear (principle component analysis) and nonlinear (Isomap) low dimensional embeddings as collective variables. Folding of the mini-protein was successfully simulated in 200 ns simulation with linear biasing and non-linear motion biasing. The folded state was correctly predicted as the free energy minimum in both simulations. We found that the advantage of linear motion biasing is that it can sample a larger conformational space, whereas the advantage of nonlinear motion biasing lies in slightly better resolution of the resulting free energy surface. In terms of sampling efficiency, both methods are comparable.

Assessing Weather-Yield Relationships in Rice at Local Scale Using Data Mining Approaches

PubMed Central

Delerce, Sylvain; Dorado, Hugo; Grillon, Alexandre; Rebolledo, Maria Camila; Prager, Steven D.; Patiño, Victor Hugo; Garcés Varón, Gabriel; Jiménez, Daniel

2016-01-01

Seasonal and inter-annual climate variability have become important issues for farmers, and climate change has been shown to increase them. Simultaneously farmers and agricultural organizations are increasingly collecting observational data about in situ crop performance. Agriculture thus needs new tools to cope with changing environmental conditions and to take advantage of these data. Data mining techniques make it possible to extract embedded knowledge associated with farmer experiences from these large observational datasets in order to identify best practices for adapting to climate variability. We introduce new approaches through a case study on irrigated and rainfed rice in Colombia. Preexisting observational datasets of commercial harvest records were combined with in situ daily weather series. Using Conditional Inference Forest and clustering techniques, we assessed the relationships between climatic factors and crop yield variability at the local scale for specific cultivars and growth stages. The analysis showed clear relationships in the various location-cultivar combinations, with climatic factors explaining 6 to 46% of spatiotemporal variability in yield, and with crop responses to weather being non-linear and cultivar-specific. Climatic factors affected cultivars differently during each stage of development. For instance, one cultivar was affected by high nighttime temperatures in the reproductive stage but responded positively to accumulated solar radiation during the ripening stage. Another was affected by high nighttime temperatures during both the vegetative and reproductive stages. Clustering of the weather patterns corresponding to individual cropping events revealed different groups of weather patterns for irrigated and rainfed systems with contrasting yield levels. Best-suited cultivars were identified for some weather patterns, making weather-site-specific recommendations possible. This study illustrates the potential of data mining for adding value to existing observational data in agriculture by allowing embedded knowledge to be quickly leveraged. It generates site-specific information on cultivar response to climatic factors and supports on-farm management decisions for adaptation to climate variability. PMID:27560980

Assessing Weather-Yield Relationships in Rice at Local Scale Using Data Mining Approaches.

PubMed

Delerce, Sylvain; Dorado, Hugo; Grillon, Alexandre; Rebolledo, Maria Camila; Prager, Steven D; Patiño, Victor Hugo; Garcés Varón, Gabriel; Jiménez, Daniel

2016-01-01

Seasonal and inter-annual climate variability have become important issues for farmers, and climate change has been shown to increase them. Simultaneously farmers and agricultural organizations are increasingly collecting observational data about in situ crop performance. Agriculture thus needs new tools to cope with changing environmental conditions and to take advantage of these data. Data mining techniques make it possible to extract embedded knowledge associated with farmer experiences from these large observational datasets in order to identify best practices for adapting to climate variability. We introduce new approaches through a case study on irrigated and rainfed rice in Colombia. Preexisting observational datasets of commercial harvest records were combined with in situ daily weather series. Using Conditional Inference Forest and clustering techniques, we assessed the relationships between climatic factors and crop yield variability at the local scale for specific cultivars and growth stages. The analysis showed clear relationships in the various location-cultivar combinations, with climatic factors explaining 6 to 46% of spatiotemporal variability in yield, and with crop responses to weather being non-linear and cultivar-specific. Climatic factors affected cultivars differently during each stage of development. For instance, one cultivar was affected by high nighttime temperatures in the reproductive stage but responded positively to accumulated solar radiation during the ripening stage. Another was affected by high nighttime temperatures during both the vegetative and reproductive stages. Clustering of the weather patterns corresponding to individual cropping events revealed different groups of weather patterns for irrigated and rainfed systems with contrasting yield levels. Best-suited cultivars were identified for some weather patterns, making weather-site-specific recommendations possible. This study illustrates the potential of data mining for adding value to existing observational data in agriculture by allowing embedded knowledge to be quickly leveraged. It generates site-specific information on cultivar response to climatic factors and supports on-farm management decisions for adaptation to climate variability.

Optimization of immunohistochemical and fluorescent antibody techniques for localization of foot-and-mouth disease virus in animal tissues

USDA-ARS?s Scientific Manuscript database

Immunohistochemical (IHC) and immunofluorescent (IF) techniques were optimized for the detection of foot-and-mouth disease virus (FMDV) structural and non-structural proteins in frozen and paraformaldehyde-fixed paraffin embedded (PFPE) tissues of bovine and porcine origin. Immunohistochemical local...

Electromagnetic Evidence of Altered Visual Processing in Autism

ERIC Educational Resources Information Center

Neumann, Nicola; Dubischar-Krivec, Anna M.; Poustka, Fritz; Birbaumer, Niels; Bolte, Sven; Braun, Christoph

2011-01-01

Individuals with autism spectrum disorder (ASD) demonstrate intact or superior local processing of visual-spatial tasks. We investigated the hypothesis that in a disembedding task, autistic individuals exhibit a more local processing style than controls, which is reflected by altered electromagnetic brain activity in response to embedded stimuli…

Slum Definitions in Urban India: Implications for the Measurement of Health Inequalities.

PubMed

Nolan, Laura B

2015-03-01

Half the population of low- and middle-income countries will live in urban areas by 2030, and poverty and inequality in these contexts is rising. Slum dwelling is one way in which to conceptualize and characterize urban deprivation but there are many definitions of what constitutes a slum. This paper presents four different slum definitions used in India alone, demonstrating that assessments of both the distribution and extent of urban deprivation depends on the way in which it is characterized, as does slum dwelling's association with common child health indicators. Using data from India's National Family and Health Survey from 2005-2006, two indictors of slum dwelling embedded in the survey and two constructed from the household questionnaire are compared using descriptive statistics and linear regression models of height- and weight-for-age z-scores. The results highlight a tension between international and local slum definitions, and underscore the importance of improving empirical representations of the dynamism of slum and city residents.

Slum Definitions in Urban India: Implications for the Measurement of Health Inequalities

PubMed Central

Nolan, Laura B.

2015-01-01

Half the population of low- and middle-income countries will live in urban areas by 2030, and poverty and inequality in these contexts is rising. Slum dwelling is one way in which to conceptualize and characterize urban deprivation but there are many definitions of what constitutes a slum. This paper presents four different slum definitions used in India alone, demonstrating that assessments of both the distribution and extent of urban deprivation depends on the way in which it is characterized, as does slum dwelling’s association with common child health indicators. Using data from India’s National Family and Health Survey from 2005–2006, two indictors of slum dwelling embedded in the survey and two constructed from the household questionnaire are compared using descriptive statistics and linear regression models of height- and weight-for-age z-scores. The results highlight a tension between international and local slum definitions, and underscore the importance of improving empirical representations of the dynamism of slum and city residents. PMID:26877568

Nanorheology of Entangled Polymer Melts

DOE PAGES

Ge, Ting; Grest, Gary S.; Rubinstein, Michael

2018-02-01

In this study, we use molecular simulations to probe the local viscoelasticity of an entangled polymer melt by tracking the motion of embedded nonsticky nanoparticles (NPs). As in conventional microrheology, the generalized Stokes-Einstein relation is employed to extract an effective stress relaxation function G GSE(t) from the mean square displacement of NPs. G GSE(t) for different NP diameters d are compared with the stress relaxation function G(t) of a pure polymer melt. The deviation of G GSE(t) from G(t) reflects the incomplete coupling between NPs and the dynamic modes of the melt. For linear polymers, a plateau in G GSE(t)more » emerges as d exceeds the entanglement mesh size a and approaches the entanglement plateau in G(t) for a pure melt with increasing d. For ring polymers, as d increases towards the spanning size R of ring polymers, G GSE(t) approaches G(t) of the ring melt with no entanglement plateau.« less

The Cosmic V-Web

NASA Astrophysics Data System (ADS)

Pomarède, Daniel; Hoffman, Yehuda; Courtois, Hélène M.; Tully, R. Brent

2017-08-01

The network of filaments with embedded clusters surrounding voids, which has been seen in maps derived from redshift surveys and reproduced in simulations, has been referred to as the cosmic web. A complementary description is provided by considering the shear in the velocity field of galaxies. The eigenvalues of the shear provide information regarding whether or not a region is collapsing in three dimensions, which is the condition for a knot, expanding in three dimensions, which is the condition for a void, or in the intermediate condition of a filament or sheet. The structures that are quantitatively defined by the eigenvalues can be approximated by iso-contours that provide a visual representation of the cosmic velocity (V) web. The current application is based on radial peculiar velocities from the Cosmicflows-2 collection of distances. The three-dimensional velocity field is constructed using the Wiener filter methodology in the linear approximation. Eigenvalues of the velocity shear are calculated at each point on a grid. Here, knots and filaments are visualized across a local domain of diameter ˜ 0.1c.

Nanorheology of Entangled Polymer Melts

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

Ge, Ting; Grest, Gary S.; Rubinstein, Michael

In this study, we use molecular simulations to probe the local viscoelasticity of an entangled polymer melt by tracking the motion of embedded nonsticky nanoparticles (NPs). As in conventional microrheology, the generalized Stokes-Einstein relation is employed to extract an effective stress relaxation function G GSE(t) from the mean square displacement of NPs. G GSE(t) for different NP diameters d are compared with the stress relaxation function G(t) of a pure polymer melt. The deviation of G GSE(t) from G(t) reflects the incomplete coupling between NPs and the dynamic modes of the melt. For linear polymers, a plateau in G GSE(t)more » emerges as d exceeds the entanglement mesh size a and approaches the entanglement plateau in G(t) for a pure melt with increasing d. For ring polymers, as d increases towards the spanning size R of ring polymers, G GSE(t) approaches G(t) of the ring melt with no entanglement plateau.« less

Active sensing of fatigue damage using embedded ultrasonics

NASA Astrophysics Data System (ADS)

Zagrai, Andrei; Kruse, Walter A.; Gigineishvili, Vlasi

2009-03-01

Embedded ultrasonics has demonstrated considerable utility in structural health monitoring of aeronautical vehicle. This active sensing approach has been widely used to detect and monitor cracks, delaminations, and disbonds in a broad spectrum of metallic and composite structures. However, application of the embedded ultrasonics for active sensing of incipient damage before fracture has received limited attention. The aim of this study was to investigate the suitability of embedded ultrasonics and nonlinear acoustic signatures for monitoring pre-crack fatigue damage in aerospace structural material. A harmonic load was applied to structural specimens in order to induce fatigue damage accumulation and growth. Specimens of simple geometry were considered and piezoelectric active sensors were employed for generation and reception of elastic waves. The elastic wave signatures were analyzed in the frequency domain using nonlinear impedance and nonlinear resonance methods. A relationship between fatigue severity and linear as well as nonlinear acoustic signatures was investigated and considered in the damage classification procedure. Practical aspects of the active sensing of the fatigue damage before fracture were discussed and prospective avenues for future research were suggested.

Assessment of Embedded Conjugated Polymer Sensor Arrays for Potential Load Transmission Measurement in Orthopaedic Implants

PubMed Central

Micolini, Carolina; Holness, Frederick Benjamin; Johnson, James A.

2017-01-01

Load transfer through orthopaedic joint implants is poorly understood. The longer-term outcomes of these implants are just starting to be studied, making it imperative to monitor contact loads across the entire joint implant interface to elucidate the force transmission and distribution mechanisms exhibited by these implants in service. This study proposes and demonstrates the design, implementation, and characterization of a 3D-printed smart polymer sensor array using conductive polyaniline (PANI) structures embedded within a polymeric parent phase. The piezoresistive characteristics of PANI were investigated to characterize the sensing behaviour inherent to these embedded pressure sensor arrays, including the experimental determination of the stable response of PANI to continuous loading, stability throughout the course of loading and unloading cycles, and finally sensor repeatability and linearity in response to incremental loading cycles. This specially developed multi-material additive manufacturing process for PANI is shown be an attractive approach for the fabrication of implant components having embedded smart-polymer sensors, which could ultimately be employed for the measurement and analysis of joint loads in orthopaedic implants for in vitro testing. PMID:29186079

Embedding silica and polymer fibre Bragg gratings (FBG) in plastic 3D-printed sensing patches

NASA Astrophysics Data System (ADS)

Zubel, Michal G.; Sugden, Kate; Webb, David J.; Sáez-Rodríguez, David; Nielsen, Kristian; Bang, Ole

2016-04-01

This paper reports the first demonstration of a silica fibre Bragg grating (SOFBG) embedded in an FDM 3-D printed housing to yield a dual grating temperature-compensated strain sensor. We also report the first ever integration of polymer fibre Bragg grating (POFBG) within a 3-D printed sensing patch for strain or temperature sensing. The cyclic strain performance and temperature characteristics of both devices are examined and discussed. The strain sensitivities of the sensing patches were 0.40 and 0.95 pm/μɛ for SOFBG embedded in ABS, 0.38 pm/μɛ for POFBG in PLA, and 0.15 pm/μɛ for POFBG in ABS. The strain response was linear above a threshold and repeatable. The temperature sensitivity of the SOFBG sensing patch was found to be up to 169 pm/°C, which was up to 17 times higher than for an unembedded silica grating. Unstable temperature response POFBG embedded in PLA was reported, with temperature sensitivity values varying between 30 and 40 pm/°C.

Fundamental Theory of Crystal Decomposition

DTIC Science & Technology

1991-05-01

rather than combine them as is often the case in a computation based on the density functional method.4 In the Case of a cluster embedded in a...classical lattice, special care needs to be taken to ensure that mathematical consistency is achieved between the cluster and the embedding lattice. This has...localizing potential or KKLP. Simulation of a large crystallite or an infinite lattice containing a point defect represented by a cluster and a

Dissecting psychiatric spectrum disorders by generative embedding☆☆☆

PubMed Central

Brodersen, Kay H.; Deserno, Lorenz; Schlagenhauf, Florian; Lin, Zhihao; Penny, Will D.; Buhmann, Joachim M.; Stephan, Klaas E.

2013-01-01

This proof-of-concept study examines the feasibility of defining subgroups in psychiatric spectrum disorders by generative embedding, using dynamical system models which infer neuronal circuit mechanisms from neuroimaging data. To this end, we re-analysed an fMRI dataset of 41 patients diagnosed with schizophrenia and 42 healthy controls performing a numerical n-back working-memory task. In our generative-embedding approach, we used parameter estimates from a dynamic causal model (DCM) of a visual–parietal–prefrontal network to define a model-based feature space for the subsequent application of supervised and unsupervised learning techniques. First, using a linear support vector machine for classification, we were able to predict individual diagnostic labels significantly more accurately (78%) from DCM-based effective connectivity estimates than from functional connectivity between (62%) or local activity within the same regions (55%). Second, an unsupervised approach based on variational Bayesian Gaussian mixture modelling provided evidence for two clusters which mapped onto patients and controls with nearly the same accuracy (71%) as the supervised approach. Finally, when restricting the analysis only to the patients, Gaussian mixture modelling suggested the existence of three patient subgroups, each of which was characterised by a different architecture of the visual–parietal–prefrontal working-memory network. Critically, even though this analysis did not have access to information about the patients' clinical symptoms, the three neurophysiologically defined subgroups mapped onto three clinically distinct subgroups, distinguished by significant differences in negative symptom severity, as assessed on the Positive and Negative Syndrome Scale (PANSS). In summary, this study provides a concrete example of how psychiatric spectrum diseases may be split into subgroups that are defined in terms of neurophysiological mechanisms specified by a generative model of network dynamics such as DCM. The results corroborate our previous findings in stroke patients that generative embedding, compared to analyses of more conventional measures such as functional connectivity or regional activity, can significantly enhance both the interpretability and performance of computational approaches to clinical classification. PMID:24363992

Visual Search Targeting Either Local or Global Perceptual Processes Differs as a Function of Autistic-Like Traits in the Typically Developing Population

ERIC Educational Resources Information Center

Almeida, Renita A.; Dickinson, J. Edwin; Maybery, Murray T.; Badcock, Johanna C.; Badcock, David R.

2013-01-01

Relative to low scorers, high scorers on the Autism-Spectrum Quotient (AQ) show enhanced performance on the Embedded Figures Test and the Radial Frequency search task (RFST), which has been attributed to both enhanced local processing and differences in combining global percepts. We investigate the role of local and global processing further using…

Nonlinear model identification and spectral submanifolds for multi-degree-of-freedom mechanical vibrations

NASA Astrophysics Data System (ADS)

Szalai, Robert; Ehrhardt, David; Haller, George

2017-06-01

In a nonlinear oscillatory system, spectral submanifolds (SSMs) are the smoothest invariant manifolds tangent to linear modal subspaces of an equilibrium. Amplitude-frequency plots of the dynamics on SSMs provide the classic backbone curves sought in experimental nonlinear model identification. We develop here, a methodology to compute analytically both the shape of SSMs and their corresponding backbone curves from a data-assimilating model fitted to experimental vibration signals. This model identification utilizes Taken's delay-embedding theorem, as well as a least square fit to the Taylor expansion of the sampling map associated with that embedding. The SSMs are then constructed for the sampling map using the parametrization method for invariant manifolds, which assumes that the manifold is an embedding of, rather than a graph over, a spectral subspace. Using examples of both synthetic and real experimental data, we demonstrate that this approach reproduces backbone curves with high accuracy.

Energy-aware virtual network embedding in flexi-grid networks.

PubMed

Lin, Rongping; Luo, Shan; Wang, Haoran; Wang, Sheng

2017-11-27

Network virtualization technology has been proposed to allow multiple heterogeneous virtual networks (VNs) to coexist on a shared substrate network, which increases the utilization of the substrate network. Efficiently mapping VNs on the substrate network is a major challenge on account of the VN embedding (VNE) problem. Meanwhile, energy efficiency has been widely considered in the network design in terms of operation expenses and the ecological awareness. In this paper, we aim to solve the energy-aware VNE problem in flexi-grid optical networks. We provide an integer linear programming (ILP) formulation to minimize the electricity cost of each arriving VN request. We also propose a polynomial-time heuristic algorithm where virtual links are embedded sequentially to keep a reasonable acceptance ratio and maintain a low electricity cost. Numerical results show that the heuristic algorithm performs closely to the ILP for a small size network, and we also demonstrate its applicability to larger networks.

Conductivity and structure of ErAs nanoparticles embedded in GaAs pn junctions analyzed via conductive atomic force microscopy

NASA Astrophysics Data System (ADS)

Park, K. W.; Dasika, V. D.; Nair, H. P.; Crook, A. M.; Bank, S. R.; Yu, E. T.

2012-06-01

We have used conductive atomic force microscopy to investigate the influence of growth temperature on local current flow in GaAs pn junctions with embedded ErAs nanoparticles grown by molecular beam epitaxy. Three sets of samples, one with 1 ML ErAs deposited at different growth temperatures and two grown at 530 °C and 575 °C with varying ErAs depositions, were characterized. Statistical analysis of local current images suggests that the structures grown at 575 °C have about 3 times thicker ErAs nanoparticles than structures grown at 530 °C, resulting in degradation of conductivity due to reduced ErAs coverage. These findings explain previous studies of macroscopic tunnel junctions.

In Vivo Microscopy Reveals Extensive Embedding of Capillaries within the Sarcolemma of Skeletal Muscle Fibers

PubMed Central

Glancy, Brian; Hsu, Li-Yueh; Dao, Lam; Bakalar, Matthew; French, Stephanie; Chess, David J.; Taylor, Joni L.; Picard, Martin; Aponte, Angel; Daniels, Mathew P.; Esfahani, Shervin; Cushman, Samuel; Balaban, Robert S.

2013-01-01

Objective To provide insight into mitochondrial function in vivo, we evaluated the 3D spatial relationship between capillaries, mitochondria, and muscle fibers in live mice. Methods 3D volumes of in vivo murine Tibialis anterior muscles were imaged by multi-photon microscopy (MPM). Muscle fiber type, mitochondrial distribution, number of capillaries, and capillary-to-fiber contact were assessed. The role of myoglobin-facilitated diffusion was examined in myoglobin knockout mice. Distribution of GLUT4 was also evaluated in the context of the capillary and mitochondrial network. Results MPM revealed that 43.6 ± 3.3% of oxidative fiber capillaries had ≥ 50% of their circumference embedded in a groove in the sarcolemma, in vivo. Embedded capillaries were tightly associated with dense mitochondrial populations lateral to capillary grooves and nearly absent below the groove. Mitochondrial distribution, number of embedded capillaries, and capillary-to-fiber contact were proportional to fiber oxidative capacity and unaffected by myoglobin knockout. GLUT4 did not preferentially localize to embedded capillaries. Conclusions Embedding capillaries in the sarcolemma may provide a regulatory mechanism to optimize delivery of oxygen to heterogeneous groups of muscle fibers. We hypothesize that mitochondria locate to paravascular regions due to myofibril voids created by embedded capillaries, not to enhance the delivery of oxygen to the mitochondria. PMID:25279425

Variable-Domain Displacement Transfer Functions for Converting Surface Strains into Deflections for Structural Deformed Shape Predictions

NASA Technical Reports Server (NTRS)

Ko, William L.; Fleischer, Van Tran

2015-01-01

Variable-Domain Displacement Transfer Functions were formulated for shape predictions of complex wing structures, for which surface strain-sensing stations must be properly distributed to avoid jointed junctures, and must be increased in the high strain gradient region. Each embedded beam (depth-wise cross section of structure along a surface strain-sensing line) was discretized into small variable domains. Thus, the surface strain distribution can be described with a piecewise linear or a piecewise nonlinear function. Through discretization, the embedded beam curvature equation can be piece-wisely integrated to obtain the Variable-Domain Displacement Transfer Functions (for each embedded beam), which are expressed in terms of geometrical parameters of the embedded beam and the surface strains along the strain-sensing line. By inputting the surface strain data into the Displacement Transfer Functions, slopes and deflections along each embedded beam can be calculated for mapping out overall structural deformed shapes. A long tapered cantilever tubular beam was chosen for shape prediction analysis. The input surface strains were analytically generated from finite-element analysis. The shape prediction accuracies of the Variable- Domain Displacement Transfer Functions were then determined in light of the finite-element generated slopes and deflections, and were fofound to be comparable to the accuracies of the constant-domain Displacement Transfer Functions

Multispectral photoacoustic decomposition with localized regularization for detecting targeted contrast agent

NASA Astrophysics Data System (ADS)

Tavakoli, Behnoosh; Chen, Ying; Guo, Xiaoyu; Kang, Hyun Jae; Pomper, Martin; Boctor, Emad M.

2015-03-01

Targeted contrast agents can improve the sensitivity of imaging systems for cancer detection and monitoring the treatment. In order to accurately detect contrast agent concentration from photoacoustic images, we developed a decomposition algorithm to separate photoacoustic absorption spectrum into components from individual absorbers. In this study, we evaluated novel prostate-specific membrane antigen (PSMA) targeted agents for imaging prostate cancer. Three agents were synthesized through conjugating PSMA-targeting urea with optical dyes ICG, IRDye800CW and ATTO740 respectively. In our preliminary PA study, dyes were injected in a thin wall plastic tube embedded in water tank. The tube was illuminated with pulsed laser light using a tunable Q-switch ND-YAG laser. PA signal along with the B-mode ultrasound images were detected with a diagnostic ultrasound probe in orthogonal mode. PA spectrums of each dye at 0.5 to 20 μM concentrations were estimated using the maximum PA signal extracted from images which are obtained at illumination wavelengths of 700nm-850nm. Subsequently, we developed nonnegative linear least square optimization method along with localized regularization to solve the spectral unmixing. The algorithm was tested by imaging mixture of those dyes. The concentration of each dye was estimated with about 20% error on average from almost all mixtures albeit the small separation between dyes spectrums.

Quantitative sensing of corroded steel rebar embedded in cement mortar specimens using ultrasonic testing

NASA Astrophysics Data System (ADS)

Owusu Twumasi, Jones; Le, Viet; Tang, Qixiang; Yu, Tzuyang

2016-04-01

Corrosion of steel reinforcing bars (rebars) is the primary cause for the deterioration of reinforced concrete structures. Traditional corrosion monitoring methods such as half-cell potential and linear polarization resistance can only detect the presence of corrosion but cannot quantify it. This study presents an experimental investigation of quantifying degree of corrosion of steel rebar inside cement mortar specimens using ultrasonic testing (UT). A UT device with two 54 kHz transducers was used to measure ultrasonic pulse velocity (UPV) of cement mortar, uncorroded and corroded reinforced cement mortar specimens, utilizing the direct transmission method. The results obtained from the study show that UPV decreases linearly with increase in degree of corrosion and corrosion-induced cracks (surface cracks). With respect to quantifying the degree of corrosion, a model was developed by simultaneously fitting UPV and surface crack width measurements to a two-parameter linear model. The proposed model can be used for predicting the degree of corrosion of steel rebar embedded in cement mortar under similar conditions used in this study up to 3.03%. Furthermore, the modeling approach can be applied to corroded reinforced concrete specimens with additional modification. The findings from this study show that UT has the potential of quantifying the degree of corrosion inside reinforced cement mortar specimens.

Molecular dynamics for near melting temperatures simulations of metals using modified embedded-atom method

NASA Astrophysics Data System (ADS)

Etesami, S. Alireza; Asadi, Ebrahim

2018-01-01

Availability of a reliable interatomic potential is one of the major challenges in utilizing molecular dynamics (MD) for simulations of metals at near the melting temperatures and melting point (MP). Here, we propose a novel approach to address this challenge in the concept of modified-embedded-atom (MEAM) interatomic potential; also, we apply the approach on iron, nickel, copper, and aluminum as case studies. We propose adding experimentally available high temperature elastic constants and MP of the element to the list of typical low temperature properties used for the development of MD interatomic potential parameters. We show that the proposed approach results in a reasonable agreement between the MD calculations of melting properties such as latent heat, expansion in melting, liquid structure factor, and solid-liquid interface stiffness and their experimental/computational counterparts. Then, we present the physical properties of mentioned elements near melting temperatures using the new MEAM parameters. We observe that the behavior of elastic constants, heat capacity and thermal linear expansion coefficient at room temperature compared to MP follows an empirical linear relation (α±β × MP) for transition metals. Furthermore, a linear relation between the tetragonal shear modulus and the enthalpy change from room temperature to MP is observed for face-centered cubic materials.

Large-Deformation Displacement Transfer Functions for Shape Predictions of Highly Flexible Slender Aerospace Structures

NASA Technical Reports Server (NTRS)

Ko, William L.; Fleischer, Van Tran

2013-01-01

Large deformation displacement transfer functions were formulated for deformed shape predictions of highly flexible slender structures like aircraft wings. In the formulation, the embedded beam (depth wise cross section of structure along the surface strain sensing line) was first evenly discretized into multiple small domains, with surface strain sensing stations located at the domain junctures. Thus, the surface strain (bending strains) variation within each domain could be expressed with linear of nonlinear function. Such piecewise approach enabled piecewise integrations of the embedded beam curvature equations [classical (Eulerian), physical (Lagrangian), and shifted curvature equations] to yield closed form slope and deflection equations in recursive forms.

Boson localization and universality in YBa2Cu(3-x)M(x)O(7-delta)

NASA Technical Reports Server (NTRS)

Kallio, A.; Apaja, V.; Poykko, S.

1995-01-01

We consider a two component mixture of charged fermions on neutralizing background with all sign combinations and arbitrarily small mass ratios. In the two impurity limit for the heavier component we show that the pair forms a bound state for all charge combinations. In the lowest order approximation we derive a closed form expression Veff(r) for the binding potential which has short-range repulsion followed by attraction. In the classical limit, when the mass of embedded particles is large m2 much greater than m, we can calculate from Veff(r) also the cohesive energy E and the bond length R of a metallic crystal such as lithium. The lowest order result is R = 3.1 A, E = -0.9 eV, not entirely different from the experimental result for lithium metal. The same interaction for two holes on a parabolic band with m2 greater than m gives the quantum mechanical bound state which one may interpret as a boson or local pair in the case of high-Te and heavy fermion superconductors. We also show that for compounds of the type YBa2Cu(3 - x)M(x)O(7 - delta) one can understand most of the experimental results for the superconducting and normal states with a single temperature dependent boson breaking function f(T) for each impurity content x governing the decay of bosons into pairing fermions. In the normal state f(T) turns out to be a linear, universal function, independent of the impurity content I and the oxygen content delta. We predict with universality a depression in Tc(x) with slight down bending in agreement with experiment. As a natural consequence of the model the bosons become localized slightly above Tc due to the Wigner crystallization, enhanced with lattice local field minima. The holes remain delocalized with a linearly increasing concentration in the normal state, thus explaining the rising Hall density. The boson localization temperature T(sub BL) shows up as a minimum in the Hall density R(sub ab)(exp -1). We also give explanation for very recently observed scaling of temperature dependent Hall effect in La(2 - x)Sr(x)CuO4.

Boson localization and universality in YBa2Cu(3-x)M(x)O(7-delta)

NASA Astrophysics Data System (ADS)

Kallio, A.; Apaja, V.; Poykko, S.

1995-04-01

We consider a two component mixture of charged fermions on neutralizing background with all sign combinations and arbitrarily small mass ratios. In the two impurity limit for the heavier component we show that the pair forms a bound state for all charge combinations. In the lowest order approximation we derive a closed form expression Veff(r) for the binding potential which has short-range repulsion followed by attraction. In the classical limit, when the mass of embedded particles is large m2 much greater than m, we can calculate from Veff(r) also the cohesive energy E and the bond length R of a metallic crystal such as lithium. The lowest order result is R = 3.1 A, E = -0.9 eV, not entirely different from the experimental result for lithium metal. The same interaction for two holes on a parabolic band with m2 greater than m gives the quantum mechanical bound state which one may interpret as a boson or local pair in the case of high-Te and heavy fermion superconductors. We also show that for compounds of the type YBa2Cu(3 - x)M(x)O(7 - delta) one can understand most of the experimental results for the superconducting and normal states with a single temperature dependent boson breaking function f(T) for each impurity content x governing the decay of bosons into pairing fermions. In the normal state f(T) turns out to be a linear, universal function, independent of the impurity content I and the oxygen content delta. We predict with universality a depression in Tc(x) with slight down bending in agreement with experiment. As a natural consequence of the model the bosons become localized slightly above Tc due to the Wigner crystallization, enhanced with lattice local field minima. The holes remain delocalized with a linearly increasing concentration in the normal state, thus explaining the rising Hall density. The boson localization temperature T(sub BL) shows up as a minimum in the Hall density R(sub ab)(exp -1). We also give explanation for very recently observed scaling of temperature dependent Hall effect in La(2 - x)Sr(x)CuO4.

Similarity-balanced discriminant neighbor embedding and its application to cancer classification based on gene expression data.

PubMed

Zhang, Li; Qian, Liqiang; Ding, Chuntao; Zhou, Weida; Li, Fanzhang

2015-09-01

The family of discriminant neighborhood embedding (DNE) methods is typical graph-based methods for dimension reduction, and has been successfully applied to face recognition. This paper proposes a new variant of DNE, called similarity-balanced discriminant neighborhood embedding (SBDNE) and applies it to cancer classification using gene expression data. By introducing a novel similarity function, SBDNE deals with two data points in the same class and the different classes with different ways. The homogeneous and heterogeneous neighbors are selected according to the new similarity function instead of the Euclidean distance. SBDNE constructs two adjacent graphs, or between-class adjacent graph and within-class adjacent graph, using the new similarity function. According to these two adjacent graphs, we can generate the local between-class scatter and the local within-class scatter, respectively. Thus, SBDNE can maximize the between-class scatter and simultaneously minimize the within-class scatter to find the optimal projection matrix. Experimental results on six microarray datasets show that SBDNE is a promising method for cancer classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

A telemetry system embedded in clothes for indoor localization and elderly health monitoring.

PubMed

Charlon, Yoann; Fourty, Nicolas; Campo, Eric

2013-09-04

This paper presents a telemetry system used in a combined trilateration method for the precise indoor localization of the elderly who need health monitoring. The system is based on the association of two wireless technologies: ultrasonic and 802.15.4. The use of the 802.15.4 RF signal gives the reference starting time of the ultrasonic emission (time difference of arrival method). A time of flight measurement of the ultrasonic pulses provides the distances between the mobile node and three anchor points. These distance measurements are then used to locate the mobile node using the trilateration method with an accuracy of a few centimetres. The originality of our work lies in embedding the mobile node in clothes. The system is embedded in clothes in two ways: on a shoe in order to form a "smart" shoe and in a hat in order to form a "smart" hat. Both accessories allow movements, gait speed and distance covered to be monitored for health applications. Experiments in a test room are presented to show the effectiveness of our system.

Nanospherical-lens lithographical Ag nanodisk arrays embedded in p-GaN for localized surface plasmon-enhanced blue light emitting diodes

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

Wei, Tongbo, E-mail: tbwei@semi.ac.cn; Wu, Kui; Sun, Bo

2014-06-15

Large-scale Ag nanodisks (NDs) arrays fabricated using nanospherical-lens lithography (NLL) are embedded in p-GaN layer of an InGaN/GaN light-emitting diode (LED) for generating localized surface plasmon (LSP) coupling with the radiating dipoles in the quantum-well (QWs). Based on the Ag NDs with the controlled surface coverage, LSP leads to the improved crystalline quality of regrowth p-GaN, increased photoluminescence (PL) intensity, reduced PL decay time, and enhanced output power of LED. Compared with the LED without Ag NDs, the optical output power at a current of 350 mA of the LSP-enhanced LEDs with Ag NDs having a distance of 20 andmore » 35 nm to QWs is increased by 26.7% and 31.1%, respectively. The electrical characteristics and optical properties of LEDs with embedded Ag NPs are dependent on the distance of between Ag NPs and QWs region. The LED with Ag NDs array structure is also found to exhibit reduced emission divergence, compared to that without Ag NDs.« less

QR images: optimized image embedding in QR codes.

PubMed

Garateguy, Gonzalo J; Arce, Gonzalo R; Lau, Daniel L; Villarreal, Ofelia P

2014-07-01

This paper introduces the concept of QR images, an automatic method to embed QR codes into color images with bounded probability of detection error. These embeddings are compatible with standard decoding applications and can be applied to any color image with full area coverage. The QR information bits are encoded into the luminance values of the image, taking advantage of the immunity of QR readers against local luminance disturbances. To mitigate the visual distortion of the QR image, the algorithm utilizes halftoning masks for the selection of modified pixels and nonlinear programming techniques to locally optimize luminance levels. A tractable model for the probability of error is developed and models of the human visual system are considered in the quality metric used to optimize the luminance levels of the QR image. To minimize the processing time, the optimization techniques proposed to consider the mechanics of a common binarization method and are designed to be amenable for parallel implementations. Experimental results show the graceful degradation of the decoding rate and the perceptual quality as a function the embedding parameters. A visual comparison between the proposed and existing methods is presented.

Scanning capacitance microscopy of ErAs nanoparticles embedded in GaAs pn junctions

NASA Astrophysics Data System (ADS)

Park, K. W.; Nair, H. P.; Crook, A. M.; Bank, S. R.; Yu, E. T.

2011-09-01

Scanning capacitance microscopy is used to characterize the electronic properties of ErAs nanoparticles embedded in GaAs pn junctions grown by molecular beam epitaxy. Voltage-dependent capacitance images reveal localized variations in subsurface electronic structure near buried ErAs nanoparticles at lateral length scales of 20-30 nm. Numerical modeling indicates that these variations arise from inhomogeneities in charge modulation due to Fermi level pinning behavior associated with the embedded ErAs nanoparticles. Statistical analysis of image data yields an average particle radius of 6-8 nm—well below the direct resolution limit in scanning capacitance microscopy but discernible via analysis of patterns in nanoscale capacitance images.

Dimensional oscillation. A fast variation of energy embedding gives good results with the AMBER potential energy function.

PubMed

Snow, M E; Crippen, G M

1991-08-01

The structure of the AMBER potential energy surface of the cyclic tetrapeptide cyclotetrasarcosyl is analyzed as a function of the dimensionality of coordinate space. It is found that the number of local energy minima decreases as the dimensionality of the space increases until some limit at which point equipotential subspaces appear. The applicability of energy embedding methods to finding global energy minima in this type of energy-conformation space is explored. Dimensional oscillation, a computationally fast variant of energy embedding is introduced and found to sample conformation space widely and to do a good job of finding global and near-global energy minima.

Extending density functional embedding theory for covalently bonded systems.

PubMed

Yu, Kuang; Carter, Emily A

2017-12-19

Quantum embedding theory aims to provide an efficient solution to obtain accurate electronic energies for systems too large for full-scale, high-level quantum calculations. It adopts a hierarchical approach that divides the total system into a small embedded region and a larger environment, using different levels of theory to describe each part. Previously, we developed a density-based quantum embedding theory called density functional embedding theory (DFET), which achieved considerable success in metals and semiconductors. In this work, we extend DFET into a density-matrix-based nonlocal form, enabling DFET to study the stronger quantum couplings between covalently bonded subsystems. We name this theory density-matrix functional embedding theory (DMFET), and we demonstrate its performance in several test examples that resemble various real applications in both chemistry and biochemistry. DMFET gives excellent results in all cases tested thus far, including predicting isomerization energies, proton transfer energies, and highest occupied molecular orbital-lowest unoccupied molecular orbital gaps for local chromophores. Here, we show that DMFET systematically improves the quality of the results compared with the widely used state-of-the-art methods, such as the simple capped cluster model or the widely used ONIOM method.

Linearized Programming of Memristors for Artificial Neuro-Sensor Signal Processing

PubMed Central

Yang, Changju; Kim, Hyongsuk

2016-01-01

A linearized programming method of memristor-based neural weights is proposed. Memristor is known as an ideal element to implement a neural synapse due to its embedded functions of analog memory and analog multiplication. Its resistance variation with a voltage input is generally a nonlinear function of time. Linearization of memristance variation about time is very important for the easiness of memristor programming. In this paper, a method utilizing an anti-serial architecture for linear programming is proposed. The anti-serial architecture is composed of two memristors with opposite polarities. It linearizes the variation of memristance due to complimentary actions of two memristors. For programming a memristor, additional memristor with opposite polarity is employed. The linearization effect of weight programming of an anti-serial architecture is investigated and memristor bridge synapse which is built with two sets of anti-serial memristor architecture is taken as an application example of the proposed method. Simulations are performed with memristors of both linear drift model and nonlinear model. PMID:27548186

Linearized Programming of Memristors for Artificial Neuro-Sensor Signal Processing.

PubMed

Yang, Changju; Kim, Hyongsuk

2016-08-19

A linearized programming method of memristor-based neural weights is proposed. Memristor is known as an ideal element to implement a neural synapse due to its embedded functions of analog memory and analog multiplication. Its resistance variation with a voltage input is generally a nonlinear function of time. Linearization of memristance variation about time is very important for the easiness of memristor programming. In this paper, a method utilizing an anti-serial architecture for linear programming is proposed. The anti-serial architecture is composed of two memristors with opposite polarities. It linearizes the variation of memristance due to complimentary actions of two memristors. For programming a memristor, additional memristor with opposite polarity is employed. The linearization effect of weight programming of an anti-serial architecture is investigated and memristor bridge synapse which is built with two sets of anti-serial memristor architecture is taken as an application example of the proposed method. Simulations are performed with memristors of both linear drift model and nonlinear model.

Local time asymmetries and toroidal field line resonances: Global magnetospheric modeling in SWMF

NASA Astrophysics Data System (ADS)

Ellington, S. M.; Moldwin, M. B.; Liemohn, M. W.

2016-03-01

We present evidence of resonant wave-wave coupling via toroidal field line resonance (FLR) signatures in the Space Weather Modeling Framework's (SWMF) global, terrestrial magnetospheric model in one simulation driven by a synthetic upstream solar wind with embedded broadband dynamic pressure fluctuations. Using in situ, stationary point measurements of the radial electric field along the 1500 LT meridian, we show that SWMF reproduces a multiharmonic, continuous distribution of FLRs exemplified by 180° phase reversals and amplitude peaks across the resonant L shells. By linearly increasing the amplitude of the dynamic pressure fluctuations in time, we observe a commensurate increase in the amplitude of the radial electric and azimuthal magnetic field fluctuations, which is consistent with the solar wind driver being the dominant source of the fast mode energy. While we find no discernible local time changes in the FLR frequencies despite large-scale, monotonic variations in the dayside equatorial mass density, in selectively sampling resonant points and examining spectral resonance widths, we observe significant radial, harmonic, and time-dependent local time asymmetries in the radial electric field amplitudes. A weak but persistent local time asymmetry exists in measures of the estimated coupling efficiency between the fast mode and toroidal wave fields, which exhibits a radial dependence consistent with the coupling strength examined by Mann et al. (1999) and Zhu and Kivelson (1988). We discuss internal structural mechanisms and additional external energy sources that may account for these asymmetries as we find that local time variations in the strength of the compressional driver are not the predominant source of the FLR amplitude asymmetries. These include resonant mode coupling of observed Kelvin-Helmholtz surface wave generated Pc5 band ultralow frequency pulsations, local time differences in local ionospheric dampening rates, and variations in azimuthal mode number, which may impact the partitioning of spectral energy between the toroidal and poloidal wave modes.

Closed-form solution of temperature and heat flux in embedded cooling channels

NASA Astrophysics Data System (ADS)

Griggs, Steven Craig

1997-11-01

An analytical method is discussed for predicting temperature in a layered composite material with embedded cooling channels. The cooling channels are embedded in the material to maintain its temperature at acceptable levels. Problems of this type are encountered in the aerospace industry and include high-temperature or high-heat-flux protection for advanced composite-material skins of high-speed air vehicles; thermal boundary-layer flow control on supersonic transports; or infrared signature suppression on military vehicles. A Green's function solution of the diffusion equation is used to simultaneously predict the global and localized effects of temperature in the material and in the embedded cooling channels. The integral method is used to solve the energy equation with fluid flow to find the solution of temperature and heat flux in the cooling fluid and material simultaneously. This method of calculation preserves the three-dimensional nature of this problem.

Gestalt Perception and Local-Global Processing in High-Functioning Autism

ERIC Educational Resources Information Center

Bolte, Sven; Holtmann, Martin; Poustka, Fritz; Scheurich, Armin; Schmidt, Lutz

2007-01-01

This study examined gestalt perception in high-functioning autism (HFA) and its relation to tasks indicative of local visual processing. Data on of gestalt perception, visual illusions (VI), hierarchical letters (HL), Block Design (BD) and the Embedded Figures Test (EFT) were collected in adult males with HFA, schizophrenia, depression and…

Are the Autism and Positive Schizotypy Spectra Diametrically Opposed in Local versus Global Processing?

ERIC Educational Resources Information Center

Russell-Smith, Suzanna N.; Maybery, Murray T.; Bayliss, Donna M.

2010-01-01

Crespi and Badcock (2008) proposed that autism and psychosis represent two extremes on a cognitive spectrum with normality at its center. Their specific claim that autistic and positive schizophrenia traits contrastingly affect preference for local versus global processing was investigated by examining Embedded Figures Test performance in two…

Accuracy improvement in the TDR-based localization of water leaks

NASA Astrophysics Data System (ADS)

Cataldo, Andrea; De Benedetto, Egidio; Cannazza, Giuseppe; Monti, Giuseppina; Demitri, Christian

A time domain reflectometry (TDR)-based system for the localization of water leaks has been recently developed by the authors. This system, which employs wire-like sensing elements to be installed along the underground pipes, has proven immune to the limitations that affect the traditional, acoustic leak-detection systems. Starting from the positive results obtained thus far, in this work, an improvement of this TDR-based system is proposed. More specifically, the possibility of employing a low-cost, water-absorbing sponge to be placed around the sensing element for enhancing the accuracy in the localization of the leak is addressed. To this purpose, laboratory experiments were carried out mimicking a water leakage condition, and two sensing elements (one embedded in a sponge and one without sponge) were comparatively used to identify the position of the leak through TDR measurements. Results showed that, thanks to the water retention capability of the sponge (which maintains the leaked water more localized), the sensing element embedded in the sponge leads to a higher accuracy in the evaluation of the position of the leak.

UV-crosslinkable and thermo-responsive chitosan hybrid hydrogel for NIR-triggered localized on-demand drug delivery.

PubMed

Wang, Lei; Li, Baoqiang; Xu, Feng; Xu, Zheheng; Wei, Daqing; Feng, Yujie; Wang, Yaming; Jia, Dechang; Zhou, Yu

2017-10-15

Innovative drug delivery technologies based on smart hydrogels for localized on-demand drug delivery had aroused great interest. To acquire smart UV-crosslinkable chitosan hydrogel for NIR-triggered localized on-demanded drug release, a novel UV-crosslinkable and thermo-responsive chitosan was first designed and synthesized by grafting with poly N-isopropylacrylamide, acetylation of methacryloyl groups and embedding with photothermal carbon. The UV-crosslinkable unit (methacryloyl groups) endowed chitosan with gelation via UV irradiation. The thermo-responsive unit (poly N-isopropylacrylamide) endowed chitosan hydrogel with temperature-triggered volume shrinkage and reversible swelling/de-swelling behavior. The chitosan hybrid hydrogel embedded with photothermal carbon exhibited distinct NIR-triggered volume shrinkage (∼42% shrinkage) in response to temperature elevation as induced by NIR laser irradiation. As a demonstration, doxorubicin release rate was accelerated and approximately 40 times higher than that from non-irradiated hydrogels. The UV-crosslinkable and thermal-responsive hybrid hydrogel served as in situ forming hydrogel-based drug depot is developed for NIR-triggered localized on-demand release. Copyright © 2017 Elsevier Ltd. All rights reserved.

Relation of the lunar volcano complexes lying on the identical linear gravity anomaly

NASA Astrophysics Data System (ADS)

Yamamoto, K.; Haruyama, J.; Ohtake, M.; Iwata, T.; Ishihara, Y.

2015-12-01

There are several large-scale volcanic complexes, e.g., Marius Hills, Aristarchus Plateau, Rumker Hills, and Flamsteed area in western Oceanus Procellarum of the lunar nearside. For better understanding of the lunar thermal history, it is important to study these areas intensively. The magmatisms and volcanic eruption mechanisms of these volcanic complexes have been discussed from geophysical and geochemical perspectives using data sets acquired by lunar explorers. In these data sets, precise gravity field data obtained by Gravity Recovery and Interior Laboratory (GRAIL) gives information on mass anomalies below the lunar surface, and useful to estimate location and mass of the embedded magmas. Using GRAIL data, Andrews-Hanna et al. (2014) prepared gravity gradient map of the Moon. They discussed the origin of the quasi-rectangular pattern of narrow linear gravity gradient anomalies located along the border of Oceanus Procellarum and suggested that the underlying dikes played important roles in magma plumbing system. In the gravity gradient map, we found that there are also several small linear gravity gradient anomaly patterns in the inside of the large quasi-rectangular pattern, and that one of the linear anomalies runs through multiple gravity anomalies in the vicinity of Aristarchus, Marius and Flamstead volcano complexes. Our concern is whether the volcanisms of these complexes are caused by common factors or not. To clarify this, we firstly estimated the mass and depth of the embedded magmas as well as the directions of the linear gravity anomalies. The results were interpreted by comparing with the chronological and KREEP distribution maps on the lunar surface. We suggested providing mechanisms of the magma to these regions and finally discussed whether the volcanisms of these multiple volcano complex regions are related with each other or not.

Evaluation of Enhanced Attention to Local Detail in Anorexia Nervosa Using the Embedded Figures Test; an fMRI Study

PubMed Central

Giampietro, Vincent; Van den Eynde, Frederique; Davies, Helen; Lounes, Naima; Andrew, Christopher; Dalton, Jeffrey; Simmons, Andrew; Williams, Steven C.R.; Baron-Cohen, Simon; Tchanturia, Kate

2013-01-01

The behavioural literature in anorexia nervosa and autism spectrum disorders has indicated an overlap in cognitive profiles. One such domain is the enhancement of local processing over global processing. While functional imaging studies of autism spectrum disorder have revealed differential neural patterns compared to controls in response to tests of local versus global processing, no studies have explored such effects in anorexia nervosa. This study uses functional magnetic resonance imaging in conjunction with the embedded figures test, to explore the neural correlates of this enhanced attention to detail in the largest anorexia nervosa cohort to date. On the embedded figures tests participants are required to indicate which of two complex figures contains a simple geometrical shape. The findings indicate that whilst healthy controls showed greater accuracy on the task than people with anorexia nervosa, different brain regions were recruited. Healthy controls showed greater activation in the precuneus whilst people with anorexia nervosa showed greater activation in the fusiform gyrus. This suggests that different cognitive strategies were used to perform the task, i.e. healthy controls demonstrated greater emphasis on visuospatial searching and people with anorexia nervosa employed a more object recognition-based approach. This is in accordance with previous findings in autism spectrum disorder using a similar methodology and has implications for therapies addressing the appropriate adjustment of cognitive strategies in anorexia nervosa. PMID:23691129

Evaluation of enhanced attention to local detail in anorexia nervosa using the embedded figures test; an FMRI study.

PubMed

Fonville, Leon; Lao-Kaim, Nick P; Giampietro, Vincent; Van den Eynde, Frederique; Davies, Helen; Lounes, Naima; Andrew, Christopher; Dalton, Jeffrey; Simmons, Andrew; Williams, Steven C R; Baron-Cohen, Simon; Tchanturia, Kate

2013-01-01

The behavioural literature in anorexia nervosa and autism spectrum disorders has indicated an overlap in cognitive profiles. One such domain is the enhancement of local processing over global processing. While functional imaging studies of autism spectrum disorder have revealed differential neural patterns compared to controls in response to tests of local versus global processing, no studies have explored such effects in anorexia nervosa. This study uses functional magnetic resonance imaging in conjunction with the embedded figures test, to explore the neural correlates of this enhanced attention to detail in the largest anorexia nervosa cohort to date. On the embedded figures tests participants are required to indicate which of two complex figures contains a simple geometrical shape. The findings indicate that whilst healthy controls showed greater accuracy on the task than people with anorexia nervosa, different brain regions were recruited. Healthy controls showed greater activation in the precuneus whilst people with anorexia nervosa showed greater activation in the fusiform gyrus. This suggests that different cognitive strategies were used to perform the task, i.e. healthy controls demonstrated greater emphasis on visuospatial searching and people with anorexia nervosa employed a more object recognition-based approach. This is in accordance with previous findings in autism spectrum disorder using a similar methodology and has implications for therapies addressing the appropriate adjustment of cognitive strategies in anorexia nervosa.

Improvement of the ab initio embedded cluster method for luminescence properties of doped materials by taking into account impurity induced distortions: the example of Y2O3:Bi(3+).

PubMed

Réal, Florent; Ordejón, Belén; Vallet, Valérie; Flament, Jean-Pierre; Schamps, Joël

2009-11-21

New ab initio embedded-cluster calculations devoted to simulating the electronic spectroscopy of Bi(3+) impurities in Y(2)O(3) sesquioxide for substitutions in either S(6) or C(2) cationic sites have been carried out taking special care of the quality of the environment. A considerable quantitative improvement with respect to previous studies [F. Real et al. J. Chem. Phys. 125, 174709 (2006); F. Real et al. J. Chem. Phys. 127, 104705 (2007)] is brought by using environments of the impurities obtained via supercell techniques that allow the whole (pseudo) crystal to relax (WCR geometries) instead of environments obtained from local relaxation of the first coordination shell only (FSR geometries) within the embedded cluster approach, as was done previously. In particular the uniform 0.4 eV discrepancy of absorption energies found previously with FSR environments disappears completely when the new WCR environments of the impurities are employed. Moreover emission energies and hence Stokes shifts are in much better agreement with experiment. These decisive improvements are mainly due to a lowering of the local point-group symmetry (S(6)-->C(3) and C(2)-->C(1)) when relaxing the geometry of the emitting (lowest) triplet state. This symmetry lowering was not observed in FSR embedded cluster relaxations because the crystal field of the embedding frozen at the genuine pure crystal positions seems to be a more important driving force than the interactions within the cluster, thus constraining the overall symmetry of the system. Variations of the doping rate are found to have negligible influence on the spectra. In conclusion, the use of WCR environments may be crucial to render the structural distortions occurring in a doped crystal and it may help to significantly improve the embedded-cluster methodology to reach the quantitative accuracy necessary to interpret and predict luminescence properties of doped materials of this type.

2D constant-loss taper for mode conversion

NASA Astrophysics Data System (ADS)

Horth, Alexandre; Kashyap, Raman; Quitoriano, Nathaniel J.

2015-03-01

Proposed in this manuscript is a novel taper geometry, the constant-loss taper (CLT). This geometry is derived with 1D slabs of silicon embedded in silicon dioxide using coupled-mode theory (CMT). The efficiency of the CLT is compared to both linear and parabolic tapers using CMT and 2D finite-difference time-domain simulations. It is shown that over a short 2D, 4.45 μm long taper the CLT's mode conversion efficiency is ~90% which is 10% and 18% more efficient than a 2D parabolic or linear taper, respectively.

The effects of embedded piezoelectric fiber composite sensors on the structural integrity of glass-fiber-epoxy composite laminate

NASA Astrophysics Data System (ADS)

Konka, Hari P.; Wahab, M. A.; Lian, K.

2012-01-01

Piezoelectric fiber composite sensors (PFCSs) made from micro-sized lead zirconate titanate (PZT) fibers have many advantages over the traditional bulk PZT sensors for embedded sensor applications. PFCSs as embedded sensors will be an ideal choice to continuously monitor the stress/strain levels and health conditions of composite structures. PFCSs are highly flexible, easily embeddable, have high compatibility with composite structures, and also provides manufacturing flexibility. This research is focused on examining the effects of embedding PFCS sensors (macro-fiber composite (MFC) and piezoelectric fiber composite (PFC)) on the structural integrity of glass-fiber-epoxy composite laminates. The strengths of composite materials with embedded PFCSs and conventional PZT sensors were compared, and the advantages of PFCS sensors over PZTs were demonstrated. Initially a numerical simulation study is performed to understand the local stress/strain field near the embedded sensor region inside a composite specimen. High stress concentration regions were observed near the embedded sensor corner edge. Using PFCS leads to a reduction of 56% in longitudinal stress concentration and 38% in transverse stress concentration, when compared to using the conventional PZTs as embedded sensors. In-plane tensile, in-plane tension-tension fatigue, and short beam strength tests are performed to evaluate the strengths/behavior of the composite specimens containing embedded PFCS. From the tensile test it is observed that embedding PFCS and PZT sensors in the composite structures leads to a reduction in ultimate strength by 3 and 6% respectively. From the fatigue test results it is concluded that both embedded PFCS and PZT sensors do not have a significant effect on the fatigue behavior of the composite specimens. From the short beam strength test it is found that embedding PFCS and PZT sensors leads to a reduction in shear strength by 7 and 15% respectively. Overall the pure PZT sensors seem to have low compatibility with composites when compared to PFCSs.

ETHERNET BASED EMBEDDED SYSTEM FOR FEL DIAGNOSTICS AND CONTROLS

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

Jianxun Yan; Daniel Sexton; Steven Moore

2006-10-24

An Ethernet based embedded system has been developed to upgrade the Beam Viewer and Beam Position Monitor (BPM) systems within the free-electron laser (FEL) project at Jefferson Lab. The embedded microcontroller was mounted on the front-end I/O cards with software packages such as Experimental Physics and Industrial Control System (EPICS) and Real Time Executive for Multiprocessor System (RTEMS) running as an Input/Output Controller (IOC). By cross compiling with the EPICS, the RTEMS kernel, IOC device supports, and databases all of these can be downloaded into the microcontroller. The first version of the BPM electronics based on the embedded controller wasmore » built and is currently running in our FEL system. The new version of BPM that will use a Single Board IOC (SBIOC), which integrates with an Field Programming Gate Array (FPGA) and a ColdFire embedded microcontroller, is presently under development. The new system has the features of a low cost IOC, an open source real-time operating system, plug&play-like ease of installation and flexibility, and provides a much more localized solution.« less

An Efficient Semi-fragile Watermarking Scheme for Tamper Localization and Recovery

NASA Astrophysics Data System (ADS)

Hou, Xiang; Yang, Hui; Min, Lianquan

2018-03-01

To solve the problem that remote sensing images are vulnerable to be tampered, a semi-fragile watermarking scheme was proposed. Binary random matrix was used as the authentication watermark, which was embedded by quantizing the maximum absolute value of directional sub-bands coefficients. The average gray level of every non-overlapping 4×4 block was adopted as the recovery watermark, which was embedded in the least significant bit. Watermarking detection could be done directly without resorting to the original images. Experimental results showed our method was robust against rational distortions to a certain extent. At the same time, it was fragile to malicious manipulation, and realized accurate localization and approximate recovery of the tampered regions. Therefore, this scheme can protect the security of remote sensing image effectively.

Elasto-plastic bond mechanics of embedded fiber optic sensors in concrete under uniaxial tension with strain localization

NASA Astrophysics Data System (ADS)

Li, Qingbin; Li, Guang; Wang, Guanglun

2003-12-01

Brittleness of the glass core inside fiber optic sensors limits their practical usage, and therefore they are coated with low-modulus softer protective materials. Protective coatings absorb a portion of the strain, and hence part of the structural strain is sensed. The study reported here corrects for this error through development of a theoretical model to account for the loss of strain in the protective coating of optical fibers. The model considers the coating as an elasto-plastic material and formulates strain transfer coefficients for elastic, elasto-plastic and strain localization phases of coating deformations in strain localization in concrete. The theoretical findings were verified through laboratory experimentation. The experimental program involved fabrication of interferometric optical fiber sensors, embedding within mortar samples and tensile tests in a closed-loop servo-hydraulic testing machine. The elasto-plastic strain transfer coefficients were employed for correction of optical fiber sensor data and results were compared with those of conventional extensometers.

Novel localized heating technique on centrifugal microfluidic disc with wireless temperature monitoring system.

PubMed

Joseph, Karunan; Ibrahim, Fatimah; Cho, Jongman

2015-01-01

Recent advances in the field of centrifugal microfluidic disc suggest the need for electrical interface in the disc to perform active biomedical assays. In this paper, we have demonstrated an active application powered by the energy harvested from the rotation of the centrifugal microfluidic disc. A novel integration of power harvester disc onto centrifugal microfluidic disc to perform localized heating technique is the main idea of our paper. The power harvester disc utilizing electromagnetic induction mechanism generates electrical energy from the rotation of the disc. This contributes to the heat generation by the embedded heater on the localized heating disc. The main characteristic observed in our experiment is the heating pattern in relative to the rotation of the disc. The heating pattern is monitored wirelessly with a digital temperature sensing system also embedded on the disc. Maximum temperature achieved is 82 °C at rotational speed of 2000 RPM. The technique proves to be effective for continuous heating without the need to stop the centrifugal motion of the disc.

Localized lossless authentication watermark (LAW)

NASA Astrophysics Data System (ADS)

Celik, Mehmet U.; Sharma, Gaurav; Tekalp, A. Murat; Saber, Eli S.

2003-06-01

A novel framework is proposed for lossless authentication watermarking of images which allows authentication and recovery of original images without any distortions. This overcomes a significant limitation of traditional authentication watermarks that irreversibly alter image data in the process of watermarking and authenticate the watermarked image rather than the original. In particular, authenticity is verified before full reconstruction of the original image, whose integrity is inferred from the reversibility of the watermarking procedure. This reduces computational requirements in situations when either the verification step fails or the zero-distortion reconstruction is not required. A particular instantiation of the framework is implemented using a hierarchical authentication scheme and the lossless generalized-LSB data embedding mechanism. The resulting algorithm, called localized lossless authentication watermark (LAW), can localize tampered regions of the image; has a low embedding distortion, which can be removed entirely if necessary; and supports public/private key authentication and recovery options. The effectiveness of the framework and the instantiation is demonstrated through examples.

Superbubbles and Local Cosmic Rays

NASA Technical Reports Server (NTRS)

Streitmatter, Robert E.; Jones, Frank C.

2005-01-01

We consider the possibility that distinctive features of the local cosmic ray spectra and composition are influenced by the Solar system being embedded within the cavity of an ancient superbubble. Shifts in the measured cosmic ray composition between 10(exp 11) and 10(exp 20) eV as well as the "knee" and "second knee" may be understood in this picture.

Putting History in Its Place: Grounding the Australian Curriculum--History in Local Community

ERIC Educational Resources Information Center

Harrison, Neil

2012-01-01

This position paper develops the case for a greater focus on the teaching of local histories in the Australian Curriculum: History. It takes as its starting point an Indigenous epistemology that understands knowledge to be embedded in the land. This connection between knowledge and country is used to examine recent literature on whether the…

Fluorescence in situ hybridization for phytoplasma and endophytic bacteria localization in plant tissues.

PubMed

Bulgari, Daniela; Casati, Paola; Faoro, Franco

2011-11-01

In the present study, we developed a rapid and efficient fluorescence in situ hybridization assay (FISH) in non-embedded tissues of the model plant Catharanthus roseus for co-localizing phytoplasmas and endophytic bacteria, opening new perspectives for studying the interaction between these microorganisms. Copyright © 2011 Elsevier B.V. All rights reserved.

Shape Control of Plates with Piezo Actuators and Collocated Position/Rate Sensors

NASA Technical Reports Server (NTRS)

Balakrishnan, A. V.

1994-01-01

This paper treats the control problem of shaping the surface deformation of a circular plate using embedded piezo-electric actuators and collocated rate sensors. An explicit Linear Quadratic Gaussian (LQG) optimizer stability augmentation compensator is derived as well as the optimal feed-forward control. Corresponding performance evaluation formulas are also derived.

Shape Control of Plates with Piezo Actuators and Collocated Position/Rate Sensors

NASA Technical Reports Server (NTRS)

Balakrishnan, A. V.

1994-01-01

This paper treats the control problem of shaping the surface deformation of a circular plate using embedded piezo-electric actuator and collocated rate sensors. An explicit Linear Quadratic Gaussian (LQG) optimizer stability augmentation compensator is derived as well as the optimal feed-forward control. Corresponding performance evaluation formulas are also derived.

A Psychophysical Test of the Visual Pathway of Children with Autism

ERIC Educational Resources Information Center

Sanchez-Marin, Francisco J.; Padilla-Medina, Jose A.

2008-01-01

Signal detection psychophysical experiments were conducted to investigate the visual path of children with autism. Computer generated images with Gaussian noise were used. Simple signals, still and in motion were embedded in the background noise. The computer monitor was linearized to properly display the contrast changes. To our knowledge, this…

Embedded Incremental Feature Selection for Reinforcement Learning

DTIC Science & Technology

2012-05-01

Prior to this work, feature selection for reinforce- ment learning has focused on linear value function ap- proximation ( Kolter and Ng, 2009; Parr et al...InProceed- ings of the the 23rd International Conference on Ma- chine Learning, pages 449–456. Kolter , J. Z. and Ng, A. Y. (2009). Regularization and feature

Multidimensional biochemical information processing of dynamical patterns

NASA Astrophysics Data System (ADS)

Hasegawa, Yoshihiko

2018-02-01

Cells receive signaling molecules by receptors and relay information via sensory networks so that they can respond properly depending on the type of signal. Recent studies have shown that cells can extract multidimensional information from dynamical concentration patterns of signaling molecules. We herein study how biochemical systems can process multidimensional information embedded in dynamical patterns. We model the decoding networks by linear response functions, and optimize the functions with the calculus of variations to maximize the mutual information between patterns and output. We find that, when the noise intensity is lower, decoders with different linear response functions, i.e., distinct decoders, can extract much information. However, when the noise intensity is higher, distinct decoders do not provide the maximum amount of information. This indicates that, when transmitting information by dynamical patterns, embedding information in multiple patterns is not optimal when the noise intensity is very large. Furthermore, we explore the biochemical implementations of these decoders using control theory and demonstrate that these decoders can be implemented biochemically through the modification of cascade-type networks, which are prevalent in actual signaling pathways.

Flatness-based embedded adaptive fuzzy control of turbocharged diesel engines

NASA Astrophysics Data System (ADS)

Rigatos, Gerasimos; Siano, Pierluigi; Arsie, Ivan

2014-10-01

In this paper nonlinear embedded control for turbocharged Diesel engines is developed with the use of Differential flatness theory and adaptive fuzzy control. It is shown that the dynamic model of the turbocharged Diesel engine is differentially flat and admits dynamic feedback linearization. It is also shown that the dynamic model can be written in the linear Brunovsky canonical form for which a state feedback controller can be easily designed. To compensate for modeling errors and external disturbances an adaptive fuzzy control scheme is implemanted making use of the transformed dynamical system of the diesel engine that is obtained through the application of differential flatness theory. Since only the system's output is measurable the complete state vector has to be reconstructed with the use of a state observer. It is shown that a suitable learning law can be defined for neuro-fuzzy approximators, which are part of the controller, so as to preserve the closed-loop system stability. With the use of Lyapunov stability analysis it is proven that the proposed observer-based adaptive fuzzy control scheme results in H∞ tracking performance.

Tin oxide quantum dots embedded iron oxide composite as efficient lead sensor

NASA Astrophysics Data System (ADS)

Dutta, Dipa; Bahadur, Dhirendra

2018-04-01

SnO2 quantum dots (QDs) embedded iron oxide (IO) nanocomposite is fabricated and explored as a capable sensor for lead detection. Square wave anodic stripping voltammetry (SWASV) and amperometry have been used to explore the proposed sensor's response towards lead detection. The modified electrode shows linear current response for concentration of lead ranging from 99 nM to 6.6 µM with limit of detection 0.42 µM (34 ppb). Amperometry shows a detection limit as low as 0.18 nM (0.015 ppb); which is far below the permissible limit of lead in drinking water by World Health Organization. This proposed sensor shows linear current response (R2 = 0.98) for the lead concentration ranging from 133 × 10-9 to 4.4 × 10-6M. It also exhibits rapid response time of 12 sec with an ultra high sensitivity of 5.5 µA/nM. These detection properties promise the use of SnO2 QDs -IO composite for detection of lead in environmental sample with great ease.

Multidimensional biochemical information processing of dynamical patterns.

PubMed

Hasegawa, Yoshihiko

2018-02-01

Cells receive signaling molecules by receptors and relay information via sensory networks so that they can respond properly depending on the type of signal. Recent studies have shown that cells can extract multidimensional information from dynamical concentration patterns of signaling molecules. We herein study how biochemical systems can process multidimensional information embedded in dynamical patterns. We model the decoding networks by linear response functions, and optimize the functions with the calculus of variations to maximize the mutual information between patterns and output. We find that, when the noise intensity is lower, decoders with different linear response functions, i.e., distinct decoders, can extract much information. However, when the noise intensity is higher, distinct decoders do not provide the maximum amount of information. This indicates that, when transmitting information by dynamical patterns, embedding information in multiple patterns is not optimal when the noise intensity is very large. Furthermore, we explore the biochemical implementations of these decoders using control theory and demonstrate that these decoders can be implemented biochemically through the modification of cascade-type networks, which are prevalent in actual signaling pathways.

An Embedded Microretroreflector-Based Microfluidic Immunoassay Platform

PubMed Central

Raja, Balakrishnan; Pascente, Carmen; Knoop, Jennifer; Shakarisaz, David; Sherlock, Tim; Kemper, Steven; Kourentzi, Katerina; Renzi, Ronald F.; Hatch, Anson V.; Olano, Juan; Peng, Bi-Hung; Ruchhoeft, Paul; Willson, Richard

2017-01-01

We present a microfluidic immunoassay platform based on the use of linear microretroreflectors embedded in a transparent polymer layer as an optical sensing surface, and micron-sized magnetic particles as light-blocking labels. Retroreflectors return light directly to its source and are highly detectable using inexpensive optics. The analyte is immuno-magnetically pre-concentrated from a sample and then captured on an antibody-modified microfluidic substrate comprised of embedded microretroreflectors, thereby blocking reflected light. Fluidic force discrimination is used to increase specificity of the assay, following which a difference imaging algorithm that can see single 3 μm magnetic particles without optical calibration is used to detect and quantify signal intensity from each sub-array of retroreflectors. We demonstrate the utility of embedded microretroreflectors as a new sensing modality through a proof-of-concept immunoassay for a small, obligate intracellular bacterial pathogen, Rickettsia conorii, the causative agent of Mediterranean Spotted Fever. The combination of large sensing area, optimized surface chemistry and microfluidic protocols, automated image capture and analysis, and high sensitivity of the difference imaging results in a sensitive immunoassay with a limit of detection of roughly 4000 R. conorii per mL. PMID:27025227

Nonlinear vs. linear biasing in Trp-cage folding simulations

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

Spiwok, Vojtěch, E-mail: spiwokv@vscht.cz; Oborský, Pavel; Králová, Blanka

2015-03-21

Biased simulations have great potential for the study of slow processes, including protein folding. Atomic motions in molecules are nonlinear, which suggests that simulations with enhanced sampling of collective motions traced by nonlinear dimensionality reduction methods may perform better than linear ones. In this study, we compare an unbiased folding simulation of the Trp-cage miniprotein with metadynamics simulations using both linear (principle component analysis) and nonlinear (Isomap) low dimensional embeddings as collective variables. Folding of the mini-protein was successfully simulated in 200 ns simulation with linear biasing and non-linear motion biasing. The folded state was correctly predicted as the free energymore » minimum in both simulations. We found that the advantage of linear motion biasing is that it can sample a larger conformational space, whereas the advantage of nonlinear motion biasing lies in slightly better resolution of the resulting free energy surface. In terms of sampling efficiency, both methods are comparable.« less

Integrated MOSFET-Embedded-Cantilever-Based Biosensor Characteristic for Detection of Anthrax Simulant

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

Mostafa, Salwa; Lee, Ida; Islam, Syed K

2011-01-01

In this work, MOSFET-embedded cantilevers are configured as microbial sensors for detection of anthrax simulants, Bacillus thuringiensis. Anthrax simulants attached to the chemically treated gold-coated cantilever cause changes in the MOSFET drain current due to the bending of the cantilever which indicates the detection of anthrax simulant. Electrical properties of the anthrax simulant are also responsible for the change in the drain current. The test results suggest a detection range of 10 L of stimulant test solution (a suspension population of 1.3 107 colony-forming units/mL diluted in 40% ethanol and 60% deionized water) with a linear response of 31 A/more » L.« less

Linear enhancement after radio-frequency ablation for hepatocellular carcinoma: is it a sign of recurrence?

PubMed

Takahashi, Masanori; Maruyama, Hitoshi; Shimada, Taro; Kamezaki, Hidehiro; Okabe, Shinichiro; Kanai, Fumihiko; Yoshikawa, Masaharu; Yokosuka, Osamu

2012-11-01

This prospective study was performed in 179 hepatocellular carcinoma (HCC) lesions treated by radio-frequency ablation (RFA) to explore the clinical outcome of "linear enhancement" on contrast-enhanced sonogram. Thirty-three lesions (18.4%) showed linear enhancement, a linear-shaped positive enhancement in the RFA-treated area. Seventeen of them were followed up with no treatment (remaining 16; dropout in eight, additional RFA in six and ineffective treatment in two) and three lesions (3/17, 17.6%) showed local tumor progression corresponding to linear enhancement at 7, 14, 19 months after RFA. Although there was no significant difference in local recurrence rate between the lesions with (3/17) and without linear enhancement (10/35), local tumor progression inside the ablation zone occurred only in the lesions with linear enhancement. In conclusion, linear enhancement inside the RFA-treated area should be followed up within 7 months because it has a risk of local tumor progression. Histology of linear enhancement and its influence on distant recurrence remain to be solved. Copyright © 2012 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Nonlinear time series analysis of normal and pathological human walking

NASA Astrophysics Data System (ADS)

Dingwell, Jonathan B.; Cusumano, Joseph P.

2000-12-01

Characterizing locomotor dynamics is essential for understanding the neuromuscular control of locomotion. In particular, quantifying dynamic stability during walking is important for assessing people who have a greater risk of falling. However, traditional biomechanical methods of defining stability have not quantified the resistance of the neuromuscular system to perturbations, suggesting that more precise definitions are required. For the present study, average maximum finite-time Lyapunov exponents were estimated to quantify the local dynamic stability of human walking kinematics. Local scaling exponents, defined as the local slopes of the correlation sum curves, were also calculated to quantify the local scaling structure of each embedded time series. Comparisons were made between overground and motorized treadmill walking in young healthy subjects and between diabetic neuropathic (NP) patients and healthy controls (CO) during overground walking. A modification of the method of surrogate data was developed to examine the stochastic nature of the fluctuations overlying the nominally periodic patterns in these data sets. Results demonstrated that having subjects walk on a motorized treadmill artificially stabilized their natural locomotor kinematics by small but statistically significant amounts. Furthermore, a paradox previously present in the biomechanical literature that resulted from mistakenly equating variability with dynamic stability was resolved. By slowing their self-selected walking speeds, NP patients adopted more locally stable gait patterns, even though they simultaneously exhibited greater kinematic variability than CO subjects. Additionally, the loss of peripheral sensation in NP patients was associated with statistically significant differences in the local scaling structure of their walking kinematics at those length scales where it was anticipated that sensory feedback would play the greatest role. Lastly, stride-to-stride fluctuations in the walking patterns of all three subject groups were clearly distinguishable from linearly autocorrelated Gaussian noise. As a collateral benefit of the methodological approach taken in this study, some of the first steps at characterizing the underlying structure of human locomotor dynamics have been taken. Implications for understanding the neuromuscular control of locomotion are discussed.

DISTING: A web application for fast algorithmic computation of alternative indistinguishable linear compartmental models.

PubMed

Davidson, Natalie R; Godfrey, Keith R; Alquaddoomi, Faisal; Nola, David; DiStefano, Joseph J

2017-05-01

We describe and illustrate use of DISTING, a novel web application for computing alternative structurally identifiable linear compartmental models that are input-output indistinguishable from a postulated linear compartmental model. Several computer packages are available for analysing the structural identifiability of such models, but DISTING is the first to be made available for assessing indistinguishability. The computational algorithms embedded in DISTING are based on advanced versions of established geometric and algebraic properties of linear compartmental models, embedded in a user-friendly graphic model user interface. Novel computational tools greatly speed up the overall procedure. These include algorithms for Jacobian matrix reduction, submatrix rank reduction, and parallelization of candidate rank computations in symbolic matrix analysis. The application of DISTING to three postulated models with respectively two, three and four compartments is given. The 2-compartment example is used to illustrate the indistinguishability problem; the original (unidentifiable) model is found to have two structurally identifiable models that are indistinguishable from it. The 3-compartment example has three structurally identifiable indistinguishable models. It is found from DISTING that the four-compartment example has five structurally identifiable models indistinguishable from the original postulated model. This example shows that care is needed when dealing with models that have two or more compartments which are neither perturbed nor observed, because the numbering of these compartments may be arbitrary. DISTING is universally and freely available via the Internet. It is easy to use and circumvents tedious and complicated algebraic analysis previously done by hand. Copyright © 2017 Elsevier B.V. All rights reserved.

Recurrence plot statistics and the effect of embedding

NASA Astrophysics Data System (ADS)

March, T. K.; Chapman, S. C.; Dendy, R. O.

2005-01-01

Recurrence plots provide a graphical representation of the recurrent patterns in a timeseries, the quantification of which is a relatively new field. Here we derive analytical expressions which relate the values of key statistics, notably determinism and entropy of line length distribution, to the correlation sum as a function of embedding dimension. These expressions are obtained by deriving the transformation which generates an embedded recurrence plot from an unembedded plot. A single unembedded recurrence plot thus provides the statistics of all possible embedded recurrence plots. If the correlation sum scales exponentially with embedding dimension, we show that these statistics are determined entirely by the exponent of the exponential. This explains the results of Iwanski and Bradley [J.S. Iwanski, E. Bradley, Recurrence plots of experimental data: to embed or not to embed? Chaos 8 (1998) 861-871] who found that certain recurrence plot statistics are apparently invariant to embedding dimension for certain low-dimensional systems. We also examine the relationship between the mutual information content of two timeseries and the common recurrent structure seen in their recurrence plots. This allows time-localized contributions to mutual information to be visualized. This technique is demonstrated using geomagnetic index data; we show that the AU and AL geomagnetic indices share half their information, and find the timescale on which mutual features appear.

Breaking and Fixing Origin-Based Access Control in Hybrid Web/Mobile Application Frameworks.

PubMed

Georgiev, Martin; Jana, Suman; Shmatikov, Vitaly

2014-02-01

Hybrid mobile applications (apps) combine the features of Web applications and "native" mobile apps. Like Web applications, they are implemented in portable, platform-independent languages such as HTML and JavaScript. Like native apps, they have direct access to local device resources-file system, location, camera, contacts, etc. Hybrid apps are typically developed using hybrid application frameworks such as PhoneGap. The purpose of the framework is twofold. First, it provides an embedded Web browser (for example, WebView on Android) that executes the app's Web code. Second, it supplies "bridges" that allow Web code to escape the browser and access local resources on the device. We analyze the software stack created by hybrid frameworks and demonstrate that it does not properly compose the access-control policies governing Web code and local code, respectively. Web code is governed by the same origin policy, whereas local code is governed by the access-control policy of the operating system (for example, user-granted permissions in Android). The bridges added by the framework to the browser have the same local access rights as the entire application, but are not correctly protected by the same origin policy. This opens the door to fracking attacks, which allow foreign-origin Web content included into a hybrid app (e.g., ads confined in iframes) to drill through the layers and directly access device resources. Fracking vulnerabilities are generic: they affect all hybrid frameworks, all embedded Web browsers, all bridge mechanisms, and all platforms on which these frameworks are deployed. We study the prevalence of fracking vulnerabilities in free Android apps based on the PhoneGap framework. Each vulnerability exposes sensitive local resources-the ability to read and write contacts list, local files, etc.-to dozens of potentially malicious Web domains. We also analyze the defenses deployed by hybrid frameworks to prevent resource access by foreign-origin Web content and explain why they are ineffectual. We then present NoFrak, a capability-based defense against fracking attacks. NoFrak is platform-independent, compatible with any framework and embedded browser, requires no changes to the code of the existing hybrid apps, and does not break their advertising-supported business model.

Linearly polarized photoluminescence of InGaN quantum disks embedded in GaN nanorods.

PubMed

Park, Youngsin; Chan, Christopher C S; Nuttall, Luke; Puchtler, Tim J; Taylor, Robert A; Kim, Nammee; Jo, Yongcheol; Im, Hyunsik

2018-05-25

We have investigated the emission from InGaN/GaN quantum disks grown on the tip of GaN nanorods. The emission at 3.21 eV from the InGaN quantum disk doesn't show a Stark shift, and it is linearly polarized when excited perpendicular to the growth direction. The degree of linear polarization is about 39.3% due to the anisotropy of the nanostructures. In order to characterize a single nanostructure, the quantum disks were dispersed on a SiO 2 substrate patterned with a metal reference grid. By rotating the excitation polarization angle from parallel to perpendicular relative to the nanorods, the variation of overall PL for the 3.21 eV peak was recorded and it clearly showed the degree of linear polarization (DLP) of 51.5%.

Localization and characterization of carbohydrates in adrenal medullary cells

PubMed Central

1975-01-01

The localization and characterization of carbohydrates in adrenal medullary cells were studied by histochemical and cytochemical methods. Adrenaline (A)-and noradrenaline (N)-storing granules were argentaphobic when ultrathin sections of Araldite-embedded medullae were stained according to the periodic acid-thiocarbohydrazide-silver proteinate technique of Thiery. A small amount of glycogen in the form of single beta-particles as well as lysosomes were, however, visualized by this technique. The entire core of the A granules was markedly positive after ultrathin sections of glutaraldehyde-fixed, glycol methacrylate (GMA)-embedded medullae were stained with phosphotungstic acid (PTA) at low pH (0.3). The N granules, in contrast, were mostly unreactive. In the A cells, PTA stained a large part of the Golgi complex, whereas in the N cells the Golgi complex was mostly unstained. In both cell types, the cell coat, lysosomes, and multivesticular bodies reacted to PTA. The periodic acid-Schiff (PAS) technique showed A but not N granules in semithin sections of GMA- or Araldite-embedded medullae. The PTA and PAS stains were abolished by acetylation, restored by saponification, unchanged by methylation, and greatly diminished by sulfation. In ultrathin sections of GMA- or Araldite- embedded medullae incubated with colloidal iron according to various techniques, the cell coat and lysosomes of both cell types were stained, unlike all the other cytoplasmic organelles. These results indicate that A granules and the Golgi complex of A cells, unlike the same structures in N cells, are rich in glycoproteins which are probably not acidic. PMID:47862

Evaluation and application of the ROMS 1-way embedding procedure to the central california upwelling system

NASA Astrophysics Data System (ADS)

Penven, Pierrick; Debreu, Laurent; Marchesiello, Patrick; McWilliams, James C.

What most clearly distinguishes near-shore and off-shore currents is their dominant spatial scale, O (1-30) km near-shore and O (30-1000) km off-shore. In practice, these phenomena are usually both measured and modeled with separate methods. In particular, it is infeasible for any regular computational grid to be large enough to simultaneously resolve well both types of currents. In order to obtain local solutions at high resolution while preserving the regional-scale circulation at an affordable computational cost, a 1-way grid embedding capability has been integrated into the Regional Oceanic Modeling System (ROMS). It takes advantage of the AGRIF (Adaptive Grid Refinement in Fortran) Fortran 90 package based on the use of pointers. After a first evaluation in a baroclinic vortex test case, the embedding procedure has been applied to a domain that covers the central upwelling region off California, around Monterey Bay, embedded in a domain that spans the continental U.S. Pacific Coast. Long-term simulations (10 years) have been conducted to obtain mean-seasonal statistical equilibria. The final solution shows few discontinuities at the parent-child domain boundary and a valid representation of the local upwelling structure, at a CPU cost only slightly greater than for the inner region alone. The solution is assessed by comparison with solutions for the whole US Pacific Coast at both low and high resolutions and to solutions for only the inner region at high resolution with mean-seasonal boundary conditions.

In situ hybridization at the electron microscope level: localization of transcripts on ultrathin sections of Lowicryl K4M-embedded tissue using biotinylated probes and protein A-gold complexes

PubMed Central

1986-01-01

A technique has been developed for localizing hybrids formed in situ on semi-thin and ultrathin sections of Lowicryl K4M-embedded tissue. Biotinylated dUTP (Bio-11-dUTP and/or Bio-16-dUTP) was incorporated into mitochondrial rDNA and small nuclear U1 probes by nick- translation. The probes were hybridized to sections of Drosophila ovaries and subsequently detected with an anti-biotin antibody and protein A-gold complex. On semi-thin sections, probe detection was achieved by amplification steps with anti-protein A antibody and protein A-gold with subsequent silver enhancement. At the electron microscope level, specific labeling was obtained over structures known to be the site of expression of the appropriate genes (i.e., either over mitochondria or over nuclei). The labeling pattern at the light microscope level (semi-thin sections) was consistent with that obtained at the electron microscope level. The described nonradioactive procedures for hybrid detection on Lowicryl K4M-embedded tissue sections offer several advantages: rapid signal detection: superior morphological preservation and spatial resolution; and signal-to-noise ratios equivalent to radiolabeling. PMID:3084498

Multilabel user classification using the community structure of online networks

PubMed Central

Papadopoulos, Symeon; Kompatsiaris, Yiannis

2017-01-01

We study the problem of semi-supervised, multi-label user classification of networked data in the online social platform setting. We propose a framework that combines unsupervised community extraction and supervised, community-based feature weighting before training a classifier. We introduce Approximate Regularized Commute-Time Embedding (ARCTE), an algorithm that projects the users of a social graph onto a latent space, but instead of packing the global structure into a matrix of predefined rank, as many spectral and neural representation learning methods do, it extracts local communities for all users in the graph in order to learn a sparse embedding. To this end, we employ an improvement of personalized PageRank algorithms for searching locally in each user’s graph structure. Then, we perform supervised community feature weighting in order to boost the importance of highly predictive communities. We assess our method performance on the problem of user classification by performing an extensive comparative study among various recent methods based on graph embeddings. The comparison shows that ARCTE significantly outperforms the competition in almost all cases, achieving up to 35% relative improvement compared to the second best competing method in terms of F1-score. PMID:28278242

Multilabel user classification using the community structure of online networks.

PubMed

Rizos, Georgios; Papadopoulos, Symeon; Kompatsiaris, Yiannis

2017-01-01

We study the problem of semi-supervised, multi-label user classification of networked data in the online social platform setting. We propose a framework that combines unsupervised community extraction and supervised, community-based feature weighting before training a classifier. We introduce Approximate Regularized Commute-Time Embedding (ARCTE), an algorithm that projects the users of a social graph onto a latent space, but instead of packing the global structure into a matrix of predefined rank, as many spectral and neural representation learning methods do, it extracts local communities for all users in the graph in order to learn a sparse embedding. To this end, we employ an improvement of personalized PageRank algorithms for searching locally in each user's graph structure. Then, we perform supervised community feature weighting in order to boost the importance of highly predictive communities. We assess our method performance on the problem of user classification by performing an extensive comparative study among various recent methods based on graph embeddings. The comparison shows that ARCTE significantly outperforms the competition in almost all cases, achieving up to 35% relative improvement compared to the second best competing method in terms of F1-score.

A high-resolution method for the localization of proanthocyanidins in plant tissues

PubMed Central

2011-01-01

Background Histochemical staining of plant tissues with 4-dimethylaminocinnamaldehyde (DMACA) or vanillin-HCl is widely used to characterize spatial patterns of proanthocyanidin accumulation in plant tissues. These methods are limited in their ability to allow high-resolution imaging of proanthocyanidin deposits. Results Tissue embedding techniques were used in combination with DMACA staining to analyze the accumulation of proanthocyanidins in Lotus corniculatus (L.) and Trifolium repens (L.) tissues. Embedding of plant tissues in LR White or paraffin matrices, with or without DMACA staining, preserved the physical integrity of the plant tissues, allowing high-resolution imaging that facilitated cell-specific localization of proanthocyanidins. A brown coloration was seen in proanthocyanidin-producing cells when plant tissues were embedded without DMACA staining and this was likely to have been due to non-enzymatic oxidation of proanthocyanidins and the formation of colored semiquinones and quinones. Conclusions This paper presents a simple, high-resolution method for analysis of proanthocyanidin accumulation in organs, tissues and cells of two plant species with different patterns of proanthocyanidin accumulation, namely Lotus corniculatus (birdsfoot trefoil) and Trifolium repens (white clover). This technique was used to characterize cell type-specific patterns of proanthocyanidin accumulation in white clover flowers at different stages of development. PMID:21595992

Clean image synthesis and target numerical marching for optical imaging with backscattering light

PubMed Central

Pu, Yang; Wang, Wubao

2011-01-01

Scanning backscattering imaging and independent component analysis (ICA) are used to probe targets hidden in the subsurface of a turbid medium. A new correction procedure is proposed and used to synthesize a “clean” image of a homogeneous host medium numerically from a set of raster-scanned “dirty” backscattering images of the medium with embedded targets. The independent intensity distributions on the surface of the medium corresponding to individual targets are then unmixed using ICA of the difference between the set of dirty images and the clean image. The target positions are localized by a novel analytical method, which marches the target to the surface of the turbid medium until a match with the retrieved independent component is accomplished. The unknown surface property of the turbid medium is automatically accounted for by this method. Employing clean image synthesis and target numerical marching, three-dimensional (3D) localization of objects embedded inside a turbid medium using independent component analysis in a backscattering geometry is demonstrated for the first time, using as an example, imaging a small piece of cancerous prostate tissue embedded in a host consisting of normal prostate tissue. PMID:21483608

A Kinematical Detection of Two Embedded Jupiter-mass Planets in HD 163296

NASA Astrophysics Data System (ADS)

Teague, Richard; Bae, Jaehan; Bergin, Edwin A.; Birnstiel, Tilman; Foreman-Mackey, Daniel

2018-06-01

We present the first kinematical detection of embedded protoplanets within a protoplanetary disk. Using archival Atacama Large Millimetre Array (ALMA) observations of HD 163296, we demonstrate a new technique to measure the rotation curves of CO isotopologue emission to sub-percent precision relative to the Keplerian rotation. These rotation curves betray substantial deviations caused by local perturbations in the radial pressure gradient, likely driven by gaps carved in the gas surface density by Jupiter-mass planets. Comparison with hydrodynamic simulations shows excellent agreement with the gas rotation profile when the disk surface density is perturbed by two Jupiter-mass planets at 83 and 137 au. As the rotation of the gas is dependent upon the pressure of the total gas component, this method provides a unique probe of the gas surface density profile without incurring significant uncertainties due to gas-to-dust ratios or local chemical abundances that plague other methods. Future analyses combining both methods promise to provide the most accurate and robust measures of embedded planetary mass. Furthermore, this method provides a unique opportunity to explore wide-separation planets beyond the mm continuum edge and to trace the gas pressure profile essential in modeling grain evolution in disks.

The role of local interaction mechanics in fiber optic smart structures

NASA Astrophysics Data System (ADS)

Sirkis, J. S.; Dasgupta, A.

1993-04-01

The concept of using 'smart' composite materials/structures with built-in self-diagnostic capabilities for health monitoring involves embedding discrete and/or distributed sensory networks in the host composite material, along with a central and/or distributed artificial intelligence capability for signal processing, data collection, interpretation and diagnostic evaluations. This article concentrates on the sensory functions in 'smart' structure applications and concentrates in particular on optical fiber sensors. Specifically, we present an overview of recent research dealing with the basic mechanics of local interactions between the embedded optical fiber sensors and the surrounding host composite. The term 'local' is defined by length scales on the order of several optical fiber diameters. We examine some generic issues, such as the 'calibration' and 'obtrusivity' of the sensor, and the inherent damage caused by the sensor inclusions to the surrounding host and vice-versa under internal and/or external applied loads. Analytical, numerical and experimental results are presented regarding the influence of local strain concentrations caused by the sensory inclusions on sensor and host performance. The important issues examined are the local mechanistic effects of optical fiber coatings on the behavior of the sensor and the host, and mechanical survivability of optical fibers experiencing quasi-static and time-varying thermomechanical loading.

Computation of multi-dimensional viscous supersonic jet flow

NASA Technical Reports Server (NTRS)

Kim, Y. N.; Buggeln, R. C.; Mcdonald, H.

1986-01-01

A new method has been developed for two- and three-dimensional computations of viscous supersonic flows with embedded subsonic regions adjacent to solid boundaries. The approach employs a reduced form of the Navier-Stokes equations which allows solution as an initial-boundary value problem in space, using an efficient noniterative forward marching algorithm. Numerical instability associated with forward marching algorithms for flows with embedded subsonic regions is avoided by approximation of the reduced form of the Navier-Stokes equations in the subsonic regions of the boundary layers. Supersonic and subsonic portions of the flow field are simultaneously calculated by a consistently split linearized block implicit computational algorithm. The results of computations for a series of test cases relevant to internal supersonic flow is presented and compared with data. Comparison between data and computation are in general excellent thus indicating that the computational technique has great promise as a tool for calculating supersonic flow with embedded subsonic regions. Finally, a User's Manual is presented for the computer code used to perform the calculations.

Soliton solutions to the fifth-order Korteweg-de Vries equation and their applications to surface and internal water waves

NASA Astrophysics Data System (ADS)

Khusnutdinova, K. R.; Stepanyants, Y. A.; Tranter, M. R.

2018-02-01

We study solitary wave solutions of the fifth-order Korteweg-de Vries equation which contains, besides the traditional quadratic nonlinearity and third-order dispersion, additional terms including cubic nonlinearity and fifth order linear dispersion, as well as two nonlinear dispersive terms. An exact solitary wave solution to this equation is derived, and the dependence of its amplitude, width, and speed on the parameters of the governing equation is studied. It is shown that the derived solution can represent either an embedded or regular soliton depending on the equation parameters. The nonlinear dispersive terms can drastically influence the existence of solitary waves, their nature (regular or embedded), profile, polarity, and stability with respect to small perturbations. We show, in particular, that in some cases embedded solitons can be stable even with respect to interactions with regular solitons. The results obtained are applicable to surface and internal waves in fluids, as well as to waves in other media (plasma, solid waveguides, elastic media with microstructure, etc.).

Localized rotating convection with no-slip boundary conditions

NASA Astrophysics Data System (ADS)

Beaume, Cédric; Kao, Hsien-Ching; Knobloch, Edgar; Bergeon, Alain

2013-12-01

Localized patches of stationary convection embedded in a background conduction state are called convectons. Multiple states of this type have recently been found in two-dimensional Boussinesq convection in a horizontal fluid layer with stress-free boundary conditions at top and bottom, and rotating about the vertical. The convectons differ in their lengths and in the strength of the self-generated shear within which they are embedded, and exhibit slanted snaking. We use homotopic continuation of the boundary conditions to show that similar structures exist in the presence of no-slip boundary conditions at the top and bottom of the layer and show that such structures exhibit standard snaking. The homotopic continuation allows us to study the transformation from slanted snaking characteristic of systems with a conserved quantity, here the zonal momentum, to standard snaking characteristic of systems with no conserved quantity.

Discrimination of nuclear explosions and earthquakes from teleseismic distances with a local network of short period seismic stations using artificial neural networks

NASA Astrophysics Data System (ADS)

Tiira, Timo

1996-10-01

Seismic discrimination capability of artificial neural networks (ANNs) was studied using earthquakes and nuclear explosions from teleseismic distances. The events were selected from two areas, which were analyzed separately. First, 23 nuclear explosions from Semipalatinsk and Lop Nor test sites were compared with 46 earthquakes from adjacent areas. Second, 39 explosions from Nevada test site were compared with 27 earthquakes from close-by areas. The basic discriminants were complexity, spectral ratio and third moment of frequency. The spectral discriminants were computed in five different ways to obtain all the information embedded in the signals, some of which were relatively weak. The discriminants were computed using data from six short period stations in Central and southern Finland. The spectral contents of the signals of both classes varied considerably between the stations. The 66 discriminants were formed into 65 optimum subsets of different sizes by using stepwise linear regression. A type of ANN called multilayer perceptron (MLP) was applied to each of the subsets. As a comparison the classification was repeated using linear discrimination analysis (LDA). Since the number of events was small the testing was made with the leave-one-out method. The ANN gave significantly better results than LDA. As a final tool for discrimination a combination of the ten neural nets with the best performance were used. All events from Central Asia were clearly discriminated and over 90% of the events from Nevada region were confidently discriminated. The better performance of ANNs was attributed to its ability to form complex decision regions between the groups and to its highly non-linear nature.

Change as Challenge for Shop-Floor Learning: The Case of Western and Local Manufacturing Companies in South China.

ERIC Educational Resources Information Center

Hong, Jianzhong

2000-01-01

Explores the process of workplace learning and problem solving by examining Western and local enterprises in South China. Discusses whether the managerial concepts embedded in Chinese culture help or impede collective learning and concludes that new ways of working and learning are emerging through the interaction of Western and Chinese culture.…

Embedding Local Places in Global Spaces: Geographical Indications as a Territorial Development Strategy

ERIC Educational Resources Information Center

Bowen, Sarah

2010-01-01

Geographical indications (GIs) are place-based names that convey the geographical origin, as well as the cultural and historical identity, of agricultural products. GIs are unique, in that they provide a means of ensuring that control over production and sales of a product stays within a local area, but at the same time they make use of extralocal…

With or without a Script? Comparing Two Styles of Participatory Video on Enhancing Local Seed Innovation System in Bangladesh

ERIC Educational Resources Information Center

Chowdhury, Ataharul Huq; Odame, Helen Hambly; Hauser, Michael

2010-01-01

Recent experiences in participatory video-making raise the question of how best to use this medium for enhancing local seed innovation systems. Embedded in a mini-process of participatory action research, two styles of participatory video--scripted and scriptless--were tested and assessed together with farmers and facilitators in Bogra District,…

Local hyperspectral data multisharpening based on linear/linear-quadratic nonnegative matrix factorization by integrating lidar data

NASA Astrophysics Data System (ADS)

Benhalouche, Fatima Zohra; Karoui, Moussa Sofiane; Deville, Yannick; Ouamri, Abdelaziz

2015-10-01

In this paper, a new Spectral-Unmixing-based approach, using Nonnegative Matrix Factorization (NMF), is proposed to locally multi-sharpen hyperspectral data by integrating a Digital Surface Model (DSM) obtained from LIDAR data. In this new approach, the nature of the local mixing model is detected by using the local variance of the object elevations. The hyper/multispectral images are explored using small zones. In each zone, the variance of the object elevations is calculated from the DSM data in this zone. This variance is compared to a threshold value and the adequate linear/linearquadratic spectral unmixing technique is used in the considered zone to independently unmix hyperspectral and multispectral data, using an adequate linear/linear-quadratic NMF-based approach. The obtained spectral and spatial information thus respectively extracted from the hyper/multispectral images are then recombined in the considered zone, according to the selected mixing model. Experiments based on synthetic hyper/multispectral data are carried out to evaluate the performance of the proposed multi-sharpening approach and literature linear/linear-quadratic approaches used on the whole hyper/multispectral data. In these experiments, real DSM data are used to generate synthetic data containing linear and linear-quadratic mixed pixel zones. The DSM data are also used for locally detecting the nature of the mixing model in the proposed approach. Globally, the proposed approach yields good spatial and spectral fidelities for the multi-sharpened data and significantly outperforms the used literature methods.

Untangling Brain-Wide Dynamics in Consciousness by Cross-Embedding

PubMed Central

Tajima, Satohiro; Yanagawa, Toru; Fujii, Naotaka; Toyoizumi, Taro

2015-01-01

Brain-wide interactions generating complex neural dynamics are considered crucial for emergent cognitive functions. However, the irreducible nature of nonlinear and high-dimensional dynamical interactions challenges conventional reductionist approaches. We introduce a model-free method, based on embedding theorems in nonlinear state-space reconstruction, that permits a simultaneous characterization of complexity in local dynamics, directed interactions between brain areas, and how the complexity is produced by the interactions. We demonstrate this method in large-scale electrophysiological recordings from awake and anesthetized monkeys. The cross-embedding method captures structured interaction underlying cortex-wide dynamics that may be missed by conventional correlation-based analysis, demonstrating a critical role of time-series analysis in characterizing brain state. The method reveals a consciousness-related hierarchy of cortical areas, where dynamical complexity increases along with cross-area information flow. These findings demonstrate the advantages of the cross-embedding method in deciphering large-scale and heterogeneous neuronal systems, suggesting a crucial contribution by sensory-frontoparietal interactions to the emergence of complex brain dynamics during consciousness. PMID:26584045

Development of EPA Protocol Information Enquiry Service System Based on Embedded ARM Linux

NASA Astrophysics Data System (ADS)

Peng, Daogang; Zhang, Hao; Weng, Jiannian; Li, Hui; Xia, Fei

Industrial Ethernet is a new technology for industrial network communications developed in recent years. In the field of industrial automation in China, EPA is the first standard accepted and published by ISO, and has been included in the fourth edition IEC61158 Fieldbus of NO.14 type. According to EPA standard, Field devices such as industrial field controller, actuator and other instruments are all able to realize communication based on the Ethernet standard. The Atmel AT91RM9200 embedded development board and open source embedded Linux are used to develop an information inquiry service system of EPA protocol based on embedded ARM Linux in this paper. The system is capable of designing an EPA Server program for EPA data acquisition procedures, the EPA information inquiry service is available for programs in local or remote host through Socket interface. The EPA client can access data and information of other EPA equipments on the EPA network when it establishes connection with the monitoring port of the server.

Sensitivity vector fields in time-delay coordinate embeddings: theory and experiment.

PubMed

Sloboda, A R; Epureanu, B I

2013-02-01

Identifying changes in the parameters of a dynamical system can be vital in many diagnostic and sensing applications. Sensitivity vector fields (SVFs) are one way of identifying such parametric variations by quantifying their effects on the morphology of a dynamical system's attractor. In many cases, SVFs are a more effective means of identification than commonly employed modal methods. Previously, it has only been possible to construct SVFs for a given dynamical system when a full set of state variables is available. This severely restricts SVF applicability because it may be cost prohibitive, or even impossible, to measure the entire state in high-dimensional systems. Thus, the focus of this paper is constructing SVFs with only partial knowledge of the state by using time-delay coordinate embeddings. Local models are employed in which the embedded states of a neighborhood are weighted in a way referred to as embedded point cloud averaging. Application of the presented methodology to both simulated and experimental time series demonstrates its utility and reliability.

Normal and radial impact of composites with embedded penny-shaped cracks

NASA Technical Reports Server (NTRS)

Sih, G. C.

1979-01-01

A method is developed for the dynamic stress analysis of a layered composite containing an embedded penny-shaped crack and subjected to normal and radial impact. The material properties of the layers are chosen such that the crack lies in a layer of matrix material while the surrounding material possesses the average elastic properties of a two-phase medium consisting of a large number of fibers embedded in the matrix. Quantitatively, the time-dependent stresses near the crack border can be described by the dynamic stress intensity factors. Their magnitude depends on time, on the material properties of the composite and on the relative size of the crack compared to the composite local geometry. Results obtained show that, for the same material properties and geometry of the composite, the dynamic stress intensity factors for an embedded (penny-shaped) crack reach their peak values within a shorter period of time and with a lower magnitude than the corresponding dynamic stress intensity factors for a through-crack.

Is the local linearity of space-time inherited from the linearity of probabilities?

NASA Astrophysics Data System (ADS)

Müller, Markus P.; Carrozza, Sylvain; Höhn, Philipp A.

2017-02-01

The appearance of linear spaces, describing physical quantities by vectors and tensors, is ubiquitous in all of physics, from classical mechanics to the modern notion of local Lorentz invariance. However, as natural as this seems to the physicist, most computer scientists would argue that something like a ‘local linear tangent space’ is not very typical and in fact a quite surprising property of any conceivable world or algorithm. In this paper, we take the perspective of the computer scientist seriously, and ask whether there could be any inherently information-theoretic reason to expect this notion of linearity to appear in physics. We give a series of simple arguments, spanning quantum information theory, group representation theory, and renormalization in quantum gravity, that supports a surprising thesis: namely, that the local linearity of space-time might ultimately be a consequence of the linearity of probabilities. While our arguments involve a fair amount of speculation, they have the virtue of being independent of any detailed assumptions on quantum gravity, and they are in harmony with several independent recent ideas on emergent space-time in high-energy physics.

Instability of fiber-reinforced viscoelastic composite plates to in-plane compressive loads

NASA Technical Reports Server (NTRS)

Chandiramani, N. K.; Librescu, L.

1990-01-01

This study analyzes the stability behavior of unidirectional fiber-reinforced composite plates with viscoelastic material behavior subject to in-plane biaxial compressive edge loads. To predict the effective time-dependent material properties, elastic fibers embedded in a linearly viscoelastic matrix are examined. The micromechanical relations developed for a transversely isotropic medium are discussed along with the correspondence principle of linear viscoelasticity. It is concluded that the stability boundary obtained for a viscoelastic plate is lower (more critical) than its elastic counterpart, and the transverse shear deformation effects are more pronounced in viscoelastic plates than in their elastic counterparts.

Review Question Formats and Web Design Usability in Computer-Assisted Instruction

ERIC Educational Resources Information Center

Green, Rebecca S.; Eppler, Marion A.; Ironsmith, Marsha; Wuensch, Karl L.

2007-01-01

We tested the effects of two embedded review question formats and the application of web design guidelines in a computer-assisted mastery learning course in developmental psychology. Students used either a branching review question format that redirected them to relevant portions of the study module after incorrect answers or a linear format that…

When Does Evidence-Based Policy Turn into Policy-Based Evidence? Configurations, Contexts and Mechanisms

ERIC Educational Resources Information Center

Strassheim, Holger; Kettunen, Pekka

2014-01-01

Many studies on evidence-based policy are still clinging to a linear model. Instead, we propose to understand expertise and evidence as "socially embedded" in authority relations and cultural contexts. Policy-relevant facts are the result of an intensive and complex struggle for political and epistemic authority. This is especially true…

Fabrication of nano piezoelectric based vibration accelerometer for mechanical sensing

NASA Astrophysics Data System (ADS)

Murugan, S.; Prasad, M. V. N.; Jayakumar, K.

2016-05-01

An electromechanical sensor unit has been fabricated using nano PZT embedded in PVDF polymer. Such a polymer nano composite has been used as vibration sensor element and sensitivity, detection of mechanical vibration, and linearity measurements have been investigated. It is found from its performance, that this nano composite sensor is suitable for mechanical sensing applications.

A Grassmann graph embedding framework for gait analysis

NASA Astrophysics Data System (ADS)

Connie, Tee; Goh, Michael Kah Ong; Teoh, Andrew Beng Jin

2014-12-01

Gait recognition is important in a wide range of monitoring and surveillance applications. Gait information has often been used as evidence when other biometrics is indiscernible in the surveillance footage. Building on recent advances of the subspace-based approaches, we consider the problem of gait recognition on the Grassmann manifold. We show that by embedding the manifold into reproducing kernel Hilbert space and applying the mechanics of graph embedding on such manifold, significant performance improvement can be obtained. In this work, the gait recognition problem is studied in a unified way applicable for both supervised and unsupervised configurations. Sparse representation is further incorporated in the learning mechanism to adaptively harness the local structure of the data. Experiments demonstrate that the proposed method can tolerate variations in appearance for gait identification effectively.

Identification of oleoresin in epoxy-embedded slash pine tissue

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

Birchem, R.; Brown, C.L.

1978-01-01

Sudan black B stains oleoresin blue-black in epoxy-embedded material as well as in living tissue. The Sudan black B staining properties of oleoresin are similar to those of lipid, but it can be distinguished from tannin, which stains brown. Practically all oleoresin present in resin ducts and intercellular spaces, and much of that contained in epithelial and ray cells, is extracted in preparatory procedures for electron microscopy. A fixation procedure is proposed which preserves significantly more oleoresin in situ. The use of Sudan black B enables one to localize oleoresin by light microscopy, and permits direct comparison of adjacent sectionsmore » of epoxy-embedded material at the ultrastructure level. Ultrastructurally oleoresin and lipid possess similar electron densities and can be distinguished from the highly electron-opaque tannin deposits.« less

Axisymmetric elastodynamic response from normal and radial impact of layered composites with embedded penny-shaped cracks

NASA Technical Reports Server (NTRS)

Sih, G. C.; Chen, E. P.

1980-01-01

A method is developed for the dynamic stress analysis of a layered composite containing an embedded penny-shaped crack and subjected to normal and radial impact. Quantitatively, the time-dependent stresses near the crack border can be described by the dynamic stress intensity factors. Their magnitude depends on time, on the material properties of the composite and on the relative size of the crack compared to the composite local geometry. Results obtained show that, for the same material properties and geometry of the composite, the dynamic stress intensity factors for an embedded (penny-shaped) crack reach their peak values within a shorter period of time and with a lower magnitude than the corresponding dynamic stress factors for a through-crack.

Spatial effects in meta-foodwebs.

PubMed

Barter, Edmund; Gross, Thilo

2017-08-30

In ecology it is widely recognised that many landscapes comprise a network of discrete patches of habitat. The species that inhabit the patches interact with each other through a foodweb, the network of feeding interactions. The meta-foodweb model proposed by Pillai et al. combines the feeding relationships at each patch with the dispersal of species between patches, such that the whole system is represented by a network of networks. Previous work on meta-foodwebs has focussed on landscape networks that do not have an explicit spatial embedding, but in real landscapes the patches are usually distributed in space. Here we compare the dispersal of a meta-foodweb on Erdős-Rényi networks, that do not have a spatial embedding, and random geometric networks, that do have a spatial embedding. We found that local structure and large network distances in spatially embedded networks, lead to meso-scale patterns of patch occupation by both specialist and omnivorous species. In particular, we found that spatial separations make the coexistence of competing species more likely. Our results highlight the effects of spatial embeddings for meta-foodweb models, and the need for new analytical approaches to them.

Expanded polyglutamine embedded in the endoplasmic reticulum causes membrane distortion and coincides with Bax insertion

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

Ueda, Masashi; Li, Shimo; Itoh, Masanori

The endoplasmic reticulum (ER) is important in various cellular functions, such as secretary and membrane protein biosynthesis, lipid synthesis, and calcium storage. ER stress, including membrane distortion, is associated with many diseases such as Huntington's disease. In particular, nuclear envelope distortion is related to neuronal cell death associated with polyglutamine. However, the mechanism by which polyglutamine causes ER membrane distortion remains unclear. We used electron microscopy, fluorescence protease protection assay, and alkaline treatment to analyze the localization of polyglutamine in cells. We characterized polyglutamine embedded in the ER membrane and noted an effect on morphology, including the dilation of ERmore » luminal space and elongation of ER-mitochondria contact sites, in addition to the distortion of the nuclear envelope. The polyglutamine embedded in the ER membrane was observed at the same time as Bax insertion. These results demonstrated that the ER membrane may be a target of polyglutamine, which triggers cell death through Bax. -- Highlights: •We characterized polyglutamine embedded in the ER membrane. •The polyglutamine embedded in the ER membrane was observed at the same time as Bax insertion. •The ER membrane may be a target of polyglutamine, which triggers cell death.« less

Trouble with diffusion: Reassessing hillslope erosion laws with a particle-based model

NASA Astrophysics Data System (ADS)

Tucker, Gregory E.; Bradley, D. Nathan

2010-03-01

Many geomorphic systems involve a broad distribution of grain motion length scales, ranging from a few particle diameters to the length of an entire hillslope or stream. Studies of analogous physical systems have revealed that such broad motion distributions can have a significant impact on macroscale dynamics and can violate the assumptions behind standard, local gradient flux laws. Here, a simple particle-based model of sediment transport on a hillslope is used to study the relationship between grain motion statistics and macroscopic landform evolution. Surface grains are dislodged by random disturbance events with probabilities and distances that depend on local microtopography. Despite its simplicity, the particle model reproduces a surprisingly broad range of slope forms, including asymmetric degrading scarps and cinder cone profiles. At low slope angles the dynamics are diffusion like, with a short-range, thin-tailed hop length distribution, a parabolic, convex upward equilibrium slope form, and a linear relationship between transport rate and gradient. As slope angle steepens, the characteristic grain motion length scale begins to approach the length of the slope, leading to planar equilibrium forms that show a strongly nonlinear correlation between transport rate and gradient. These high-probability, long-distance motions violate the locality assumption embedded in many common gradient-based geomorphic transport laws. The example of a degrading scarp illustrates the potential for grain motion dynamics to vary in space and time as topography evolves. This characteristic renders models based on independent, stationary statistics inapplicable. An accompanying analytical framework based on treating grain motion as a survival process is briefly outlined.

Fluorescent BODIPY Rotor: Viscometer for Cellular Organelles and Membrane-Mimicking Vesicles

NASA Astrophysics Data System (ADS)

Kimball, J.; Raut, S.; Fudala, R.; Doan, H.; Maliwal, B.; Sabnis, N.; Lacko, A.; Gryczynski, I.; Dzyuba, S.; Gryczynski, Z.

2015-03-01

Many cellular processes, such as mass and signal transport, metabolism and protein-protein interactions are governed in part by diffusion, and thus affected by their local microviscosity. Changes in this microviscosity has also been linked to various diseases, including atherosclerosis, Alzheimer's disease and diabetes. Therefore, directly measuring the heterogeneous viscosity of cellular constitutes can lead to greater understanding of these processes. To this effect, a novel homodiemeric BODIPY dye was evaluated as a fluorescent rotor probe for this application. A linear dependence on viscosity in the range of typical cellular microviscosity was established for steady-state and time-resolved properties of the dye. It was then embedded in vitro to membrane-mimicking lipid vesicles (DPPC, POPC, and POPC plus cholesterol) and results indicated it to be a viable sensor for lifetime-based determination of microviscosity. The BODIPY dye was lastly endocytosed by SKOV3 cells and Fluorescence Lifetime Imaging Microscopy (FLIM) was performed, successfully mapping the viscosity of internal cell components. This work was supported by the NIH Grant R01EB12003, the NSF Grant CBET-1264608, and the INFOR Grant from TCU.

Modeling Progressive Failure of Bonded Joints Using a Single Joint Finite Element

NASA Technical Reports Server (NTRS)

Stapleton, Scott E.; Waas, Anthony M.; Bednarcyk, Brett A.

2010-01-01

Enhanced finite elements are elements with an embedded analytical solution which can capture detailed local fields, enabling more efficient, mesh-independent finite element analysis. In the present study, an enhanced finite element is applied to generate a general framework capable of modeling an array of joint types. The joint field equations are derived using the principle of minimum potential energy, and the resulting solutions for the displacement fields are used to generate shape functions and a stiffness matrix for a single joint finite element. This single finite element thus captures the detailed stress and strain fields within the bonded joint, but it can function within a broader structural finite element model. The costs associated with a fine mesh of the joint can thus be avoided while still obtaining a detailed solution for the joint. Additionally, the capability to model non-linear adhesive constitutive behavior has been included within the method, and progressive failure of the adhesive can be modeled by using a strain-based failure criteria and re-sizing the joint as the adhesive fails. Results of the model compare favorably with experimental and finite element results.

Branching points in the low-temperature dipolar hard sphere fluid

NASA Astrophysics Data System (ADS)

Rovigatti, Lorenzo; Kantorovich, Sofia; Ivanov, Alexey O.; Tavares, José Maria; Sciortino, Francesco

2013-10-01

In this contribution, we investigate the low-temperature, low-density behaviour of dipolar hard-sphere (DHS) particles, i.e., hard spheres with dipoles embedded in their centre. We aim at describing the DHS fluid in terms of a network of chains and rings (the fundamental clusters) held together by branching points (defects) of different nature. We first introduce a systematic way of classifying inter-cluster connections according to their topology, and then employ this classification to analyse the geometric and thermodynamic properties of each class of defects, as extracted from state-of-the-art equilibrium Monte Carlo simulations. By computing the average density and energetic cost of each defect class, we find that the relevant contribution to inter-cluster interactions is indeed provided by (rare) three-way junctions and by four-way junctions arising from parallel or anti-parallel locally linear aggregates. All other (numerous) defects are either intra-cluster or associated to low cluster-cluster interaction energies, suggesting that these defects do not play a significant part in the thermodynamic description of the self-assembly processes of dipolar hard spheres.

SLLE for predicting membrane protein types.

PubMed

Wang, Meng; Yang, Jie; Xu, Zhi-Jie; Chou, Kuo-Chen

2005-01-07

Introduction of the concept of pseudo amino acid composition (PROTEINS: Structure, Function, and Genetics 43 (2001) 246; Erratum: ibid. 44 (2001) 60) has made it possible to incorporate a considerable amount of sequence-order effects by representing a protein sample in terms of a set of discrete numbers, and hence can significantly enhance the prediction quality of membrane protein type. As a continuous effort along such a line, the Supervised Locally Linear Embedding (SLLE) technique for nonlinear dimensionality reduction is introduced (Science 22 (2000) 2323). The advantage of using SLLE is that it can reduce the operational space by extracting the essential features from the high-dimensional pseudo amino acid composition space, and that the cluster-tolerant capacity can be increased accordingly. As a consequence by combining these two approaches, high success rates have been observed during the tests of self-consistency, jackknife and independent data set, respectively, by using the simplest nearest neighbour classifier. The current approach represents a new strategy to deal with the problems of protein attribute prediction, and hence may become a useful vehicle in the area of bioinformatics and proteomics.

Natural Silk as a Photonics Component: a Study on Its Light Guiding and Nonlinear Optical Properties

NASA Astrophysics Data System (ADS)

Kujala, Sami; Mannila, Anna; Karvonen, Lasse; Kieu, Khanh; Sun, Zhipei

2016-03-01

Silk fibers are expected to become a pathway to biocompatible and bioresorbable waveguides, which could be used to deliver localized optical power for various applications, e.g., optical therapy or imaging inside living tissue. Here, for the first time, the linear and nonlinear optical properties of natural silk fibers have been studied. The waveguiding properties of silk fibroin of largely unprocessed Bombyx mori silkworm silk are assessed using two complementary methods, and found to be on the average 2.8 dB mm-1. The waveguide losses of degummed silk are to a large extent due to scattering from debris on fiber surface and helical twisting of the fiber. Nonlinear optical microscopy reveals both configurational defects such as torsional twisting, and strong symmetry breaking at the center of the fiber, which provides potential for various nonlinear applications. Our results show that nonregenerated B. mori silk can be used for delivering optical power over short distances, when the waveguide needs to be biocompatible and bioresorbable, such as embedding the waveguide inside living tissue.

Characteristic classes, singular embeddings, and intersection homology.

PubMed

Cappell, S E; Shaneson, J L

1987-06-01

This note announces some results on the relationship between global invariants and local topological structure. The first section gives a local-global formula for Pontrjagin classes or L-classes. The second section describes a corresponding decomposition theorem on the level of complexes of sheaves. A final section mentions some related aspects of "singular knot theory" and the study of nonisolated singularities. Analogous equivariant analogues, with local-global formulas for Atiyah-Singer classes and their relations to G-signatures, will be presented in a future paper.

Stellar populations in local star-forming galaxies

NASA Astrophysics Data System (ADS)

Perez-Gonzalez, P. G.

2003-11-01

The main goal of this thesis work is studying the main properties of the stellar populations embedded in a statistically complete sample of local active star-forming galaxies: the Universidad Complutense de Madrid (UCM) Survey of emission-line galaxies. This sample contains 191 local star-forming galaxies at an average redshift of 0.026. The survey was carried out using an objective-prism technique centered at the wavelength of the Halpha nebular emission-line (a common tracer of recent star formation). (continues)

Circular polarization beam splitter that uses frustrated total internal reflection by an embedded symmetric achiral multilayer coating.

PubMed

Azzam, R M A; De, A

2003-03-01

A symmetric achiral trilayer structure, which consists of a high-index center layer sandwiched between two identical low-index films and embedded in a high-index prism, is designed to produce equal and opposite quarter-wave retardation in reflection and transmission and equal throughput for the p and s polarization at oblique incidence. Such a device splits a beam of incident linearly polarized light into two orthogonally circularly polarized components of equal power that travel in different directions. A visible (633-nm) design that operates at a 60 degree angle of incidence and an infrared (10.6-microm) 45 degree cube design are presented. The spectral and angular sensitivities of the device are also considered.

Effect of Fly-Ash on Corrosion Resistance Characteristics of Rebar Embedded in Recycled Aggregate Concrete

NASA Astrophysics Data System (ADS)

Revathi, Purushothaman; Nikesh, P.

2018-04-01

In the frame of an extended research programme dealing with the utilization of recycled aggregate in concrete, the corrosion resistance characteristics of rebars embedded in recycled aggregate concrete is studied. Totally five series of concrete mixtures were prepared with fly-ash as replacement for cement in the levels of 10-30% by weight of cement. Corrosion studies by 90 days ponding test, linear polarization test and impressed voltage tests were carried out, in order to investigate whether corrosion behaviour of the rebars has improved due to the replacement of cement with fly-ash. Results showed that the replacement of cement with fly-ash in the range of 20-30% improves the corrosion resistance characteristics of recycled aggregate concrete.

Chromatographic behaviour predicts the ability of potential nootropics to permeate the blood-brain barrier.

PubMed

Farsa, Oldřich

2013-01-01

The log BB parameter is the logarithm of the ratio of a compound's equilibrium concentrations in the brain tissue versus the blood plasma. This parameter is a useful descriptor in assessing the ability of a compound to permeate the blood-brain barrier. The aim of this study was to develop a Hansch-type linear regression QSAR model that correlates the parameter log BB and the retention time of drugs and other organic compounds on a reversed-phase HPLC containing an embedded amide moiety. The retention time was expressed by the capacity factor log k'. The second aim was to estimate the brain's absorption of 2-(azacycloalkyl)acetamidophenoxyacetic acids, which are analogues of piracetam, nefiracetam, and meclofenoxate. Notably, these acids may be novel nootropics. Two simple regression models that relate log BB and log k' were developed from an assay performed using a reversed-phase HPLC that contained an embedded amide moiety. Both the quadratic and linear models yielded statistical parameters comparable to previously published models of log BB dependence on various structural characteristics. The models predict that four members of the substituted phenoxyacetic acid series have a strong chance of permeating the barrier and being absorbed in the brain. The results of this study show that a reversed-phase HPLC system containing an embedded amide moiety is a functional in vitro surrogate of the blood-brain barrier. These results suggest that racetam-type nootropic drugs containing a carboxylic moiety could be more poorly absorbed than analogues devoid of the carboxyl group, especially if the compounds penetrate the barrier by a simple diffusion mechanism.

Enhanced performance of microfluidic soft pressure sensors with embedded solid microspheres

NASA Astrophysics Data System (ADS)

Shin, Hee-Sup; Ryu, Jaiyoung; Majidi, Carmel; Park, Yong-Lae

2016-02-01

The cross-sectional geometry of an embedded microchannel influences the electromechanical response of a soft microfluidic sensor to applied surface pressure. When a pressure is exerted on the surface of the sensor deforming the soft structure, the cross-sectional area of the embedded channel filled with a conductive fluid decreases, increasing the channel’s electrical resistance. This electromechanical coupling can be tuned by adding solid microspheres into the channel. In order to determine the influence of microspheres, we use both analytic and computational methods to predict the pressure responses of soft microfluidic sensors with two different channel cross-sections: a square and an equilateral triangular. The analytical models were derived from contact mechanics in which microspheres were regarded as spherical indenters, and finite element analysis (FEA) was used for simulation. For experimental validation, sensor samples with the two different channel cross-sections were prepared and tested. For comparison, the sensor samples were tested both with and without microspheres. All three results from the analytical models, the FEA simulations, and the experiments showed reasonable agreement confirming that the multi-material soft structure significantly improved its pressure response in terms of both linearity and sensitivity. The embedded solid particles enhanced the performance of soft sensors while maintaining their flexible and stretchable mechanical characteristic. We also provide analytical and experimental analyses of hysteresis of microfluidic soft sensors considering a resistive force to the shape recovery of the polymer structure by the embedded viscous fluid.

Injectable hydrogels embedded with alginate microspheres for controlled delivery of bone morphogenetic protein-2.

PubMed

Zhu, Youjia; Wang, Jiulong; Wu, Jingjing; Zhang, Jun; Wan, Ying; Wu, Hua

2016-03-23

Some delivery carriers with injectable characteristics were built using the thermosensitive chitosan/dextran-polylactide/glycerophosphate hydrogel and selected alginate microspheres for the controllable release of bone morphogenetic protein-2 (BMP-2). BMP-2 was first loaded into the microspheres with an average size of around 20 μm and the resulting microspheres were then embedded into the gel in order to achieve well-controlled BMP-2 release. The microsphere-embedded gels show their incipient gelation temperature at around 32 °C and pH at about 7.1. Some gels had their elastic modulus close to 1400 Pa and the ratio of elastic modulus to viscous modulus at around 34, revealing that they behaved like mechanically strong gels. Optimized microsphere-embedded gels were found to be able to administer the BMP-2 release without significant initial burst release in an approximately linear manner over a period of time longer than four weeks. The release rate and the released amount of BMP-2 from these gels could be regulated individually or cooperatively by the initial BMP-2 load and the dextran-polylactide content in the gels. Measurements of the BMP-2 induced alkaline phosphatase activity in C2C12 cells confirmed that C2C12 cells responded to BMP-2 in a dose-dependent way and the released BMP-2 from the microsphere-embedded gels well retained their bioactivity. In vivo assessment of some gels revealed that the released BMP-2 maintained its osteogenesis functions.

Evolution of the Orszag-Tang vortex system in a compressible medium. II - Supersonic flow

NASA Technical Reports Server (NTRS)

Picone, J. Michael; Dahlburg, Russell B.

1991-01-01

A study is presented on the effect of embedded supersonic flows and the resulting emerging shock waves on phenomena associated with MHD turbulence, including reconnection, the formation of current sheets and vortex structures, and the evolution of spatial and temporal correlations among physical variables. A two-dimensional model problem, the Orszag-Tang (1979) vortex system, is chosen, which involves decay from nonrandom initial conditions. The system is doubly periodic, and the initial conditions consist of single-mode solenoidal velocity and magnetic fields, each containing X points and O points. The initial mass density is flat, and the initial pressure fluctuations are incompressible, balancing the local forces for a magnetofluid of unit mass density. Results on the evolution of the local structure of the flow field, the global properties of the system, and spectral correlations are presented. The important dynamical properties and observational consequences of embedded supersonic regions and emerging shocks in the Orszag-Tang model of an MHD system undergoing reconnection are discussed. Conclusions are drawn regarding the effects of local supersonic regions on MHD turbulence.

Does a Local B-Minimum Appear in the Tail Current Sheet During a Substorm Growth Phase?

NASA Astrophysics Data System (ADS)

Sergeev, V. A.; Gordeev, E. I.; Merkin, V. G.; Sitnov, M. I.

2018-03-01

Magnetic configurations with dBz/dr > 0 in the midtail current sheet are potentially unstable to various instabilities associated with the explosive substorm onset. Their existence is hard to confirm with observations of magnetospheric spacecraft. Here we use remote sensing by low-altitude spacecraft that measured the loss cone filling rate during electron-rich solar particle event, providing information about magnetic properties of the tail current sheet. We found a latitudinally localized anisotropic 30 keV electron loss cone region embedded inside an extended region of isotropic solar electron precipitation. It was persistently observed for more than 0.5 h during isolated growth phase event by six Polar Operational Environmental Satellites spacecraft, which crossed the premidnight auroral oval. The embedded anisotropic region was observed 1° poleward of the outer radiation belt boundary over 4-5 h wide magnetic local time sector, suggesting a persistent ridge-type Bz2/j maximum in the equatorial plasma sheet at distances 15-20 RE. We discuss infrequent observations of such events taking into account recent results of global magnetohydrodynamic simulations.

Fault diagnosis of sensor networked structures with multiple faults using a virtual beam based approach

NASA Astrophysics Data System (ADS)

Wang, H.; Jing, X. J.

2017-07-01

This paper presents a virtual beam based approach suitable for conducting diagnosis of multiple faults in complex structures with limited prior knowledge of the faults involved. The "virtual beam", a recently-proposed concept for fault detection in complex structures, is applied, which consists of a chain of sensors representing a vibration energy transmission path embedded in the complex structure. Statistical tests and adaptive threshold are particularly adopted for fault detection due to limited prior knowledge of normal operational conditions and fault conditions. To isolate the multiple faults within a specific structure or substructure of a more complex one, a 'biased running' strategy is developed and embedded within the bacterial-based optimization method to construct effective virtual beams and thus to improve the accuracy of localization. The proposed method is easy and efficient to implement for multiple fault localization with limited prior knowledge of normal conditions and faults. With extensive experimental results, it is validated that the proposed method can localize both single fault and multiple faults more effectively than the classical trust index subtract on negative add on positive (TI-SNAP) method.

Atmospheric Characteristics of Cool Season Intermittent Precipitation Near Portland, Oregon

NASA Astrophysics Data System (ADS)

Cunningham, Jeffrey Glenn

Pacific Northwest cool season precipitation is often described as mostly stratiform (i.e. steady and continuous). While most regional precipitation is stratiform in terms of area and duration, embedded convective cells within stratiform precipitation occur frequently enough to warrant study. Embedded cells locally increase rain rate, total precipitation, and streamflow discharge and hence raise the risk of flooding, landslides, and debris flows. Analysis of vertically pointing radar data near Portland, Oregon for three cool seasons (2005 to 2008) indicates that fallstreaks in the snow layer, locally enhanced precipitation regions a few kilometers in size indicated in radar reflectivity data above the 0° C altitude, are nearly ubiquitous on days with significant rainfall accumulation and large areas of precipitation. The observed fallstreaks in snow enhance rainfall immediately below the snow fallstreak. Compared to stratiform periods, embedded convective periods include higher Doppler vertical velocity values and higher variability in velocities especially in the snow layer. The combination of these findings points to generating cells within the snow layer and the seeder-feeder mechanism as important sources of surface precipitation variability for periods of embedded convective cells within stratiform precipitation. The primary goal of this study was to determine the sources of instability typically associated with convective cells embedded within stratiform precipitation for Pacific Northwest cool season storms. Storm periods occurring over six cool seasons (2002 to 2008, totaling 1923 hours) of operational radar data (KRTX) and 166 upper air soundings (KSLE) are analyzed. A new method was employed to objectively determine the degree of precipitation intermittency in sequences of radar scans. The resulting continuum of intermittency values was grouped into four categories: mostly convective precipitation, mostly stratiform precipitation, embedded convective cells within stratiform precipitation, and other. Atmospheric soundings during periods with embedded convective cells within stratiform precipitation are more likely to have convective available potential energy (CAPE) than soundings during periods of mostly stratiform precipitation. Specifically, most unstable parcel CAPE (MUCAPE) > 0 J kg-1 occurs 2.8 more frequently during embedded periods than for mostly stratiform periods. Over 90% of embedded periods have MUCAPE > 0 J kg-1 or at least two 500 meter layers of potential instability. In contrast to the near surface based instability most commonly associated with the mostly convective precipitation, embedded convection is elevated. The median most unstable parcel height of origin for embedded convective periods is 2.5 km compared to 0.5 km for mostly convective periods. Although this present research did not deal directly with orographic precipitation enhancement, it does address synoptic and mesoscale precipitation processes that frequently occur near terrain in the Pacific Northwest. The exclusion of the seeder-feeder mechanism as a mode of cellularity for orographic precipitation in recent work is inconsistent with the observations presented here and inconsistent with much of the pre-2000 literature, which show the seeder-feeder mechanism directly modulating surface rain rate with or without terrain present. Numerical models, whether operational or idealized, need to represent the seeder-feeder process in order to accurately simulate precipitation variability at small spatial scales (less than < 5-10 km) and temporal scales (< 3 hours) within the warm sector of Pacific Northwest extratropical cyclones.

Design of nonlinear PID controller and nonlinear model predictive controller for a continuous stirred tank reactor.

PubMed

Prakash, J; Srinivasan, K

2009-07-01

In this paper, the authors have represented the nonlinear system as a family of local linear state space models, local PID controllers have been designed on the basis of linear models, and the weighted sum of the output from the local PID controllers (Nonlinear PID controller) has been used to control the nonlinear process. Further, Nonlinear Model Predictive Controller using the family of local linear state space models (F-NMPC) has been developed. The effectiveness of the proposed control schemes has been demonstrated on a CSTR process, which exhibits dynamic nonlinearity.

Dynamical localization of coupled relativistic kicked rotors

NASA Astrophysics Data System (ADS)

Rozenbaum, Efim B.; Galitski, Victor

2017-02-01

A periodically driven rotor is a prototypical model that exhibits a transition to chaos in the classical regime and dynamical localization (related to Anderson localization) in the quantum regime. In a recent work [Phys. Rev. B 94, 085120 (2016), 10.1103/PhysRevB.94.085120], A. C. Keser et al. considered a many-body generalization of coupled quantum kicked rotors, and showed that in the special integrable linear case, dynamical localization survives interactions. By analogy with many-body localization, the phenomenon was dubbed dynamical many-body localization. In the present work, we study nonintegrable models of single and coupled quantum relativistic kicked rotors (QRKRs) that bridge the gap between the conventional quadratic rotors and the integrable linear models. For a single QRKR, we supplement the recent analysis of the angular-momentum-space dynamics with a study of the spin dynamics. Our analysis of two and three coupled QRKRs along with the proved localization in the many-body linear model indicate that dynamical localization exists in few-body systems. Moreover, the relation between QRKR and linear rotor models implies that dynamical many-body localization can exist in generic, nonintegrable many-body systems. And localization can generally result from a complicated interplay between Anderson mechanism and limiting integrability, since the many-body linear model is a high-angular-momentum limit of many-body QRKRs. We also analyze the dynamics of two coupled QRKRs in the highly unusual superballistic regime and find that the resonance conditions are relaxed due to interactions. Finally, we propose experimental realizations of the QRKR model in cold atoms in optical lattices.

Localization of puroindoline-a and lipids in bread dough using confocal scanning laser microscopy.

PubMed

Dubreil, Laurence; Biswas, Samares C; Marion, Didier

2002-10-09

Puroindolines are lipid-binding proteins from wheat flour that play a significant role in bread crumb texture. The localization of wheat flour lipids and puroindoline-a (PIN-a) in bread dough was studied by confocal scanning laser microscopy (CSLM). Wheat lipids were located around gas cells (GC) and embedded within the protein-starch matrix (SPM) of the dough. PIN-a was mainly located in the matrix of dough, where it was associated with lipids. In contrast, in defatted dough, PIN-a was found around GC. Addition of puroindolines in bread dough induced a defatting of the gas bubble surface and a decrease of the lipid vesicles and/or droplet size embedded within the SPM. Therefore, puroindolines control the lipid partitioning within the different phases of dough, a phenomenon that should have important consequence on the gas bubble expansion and GC formation in the further stages (fermentation, baking) of the bread-making process.

Local density approximation in site-occupation embedding theory

NASA Astrophysics Data System (ADS)

Senjean, Bruno; Tsuchiizu, Masahisa; Robert, Vincent; Fromager, Emmanuel

2017-01-01

Site-occupation embedding theory (SOET) is a density functional theory (DFT)-based method which aims at modelling strongly correlated electrons. It is in principle exact and applicable to model and quantum chemical Hamiltonians. The theory is presented here for the Hubbard Hamiltonian. In contrast to conventional DFT approaches, the site (or orbital) occupations are deduced in SOET from a partially interacting system consisting of one (or more) impurity site(s) and non-interacting bath sites. The correlation energy of the bath is then treated implicitly by means of a site-occupation functional. In this work, we propose a simple impurity-occupation functional approximation based on the two-level (2L) Hubbard model which is referred to as two-level impurity local density approximation (2L-ILDA). Results obtained on a prototypical uniform eight-site Hubbard ring are promising. The extension of the method to larger systems and more sophisticated model Hamiltonians is currently in progress.

Individual electron and hole localization in submonolayer InN quantum sheets embedded in GaN

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

Feix, F., E-mail: feix@pdi-berlin.de; Flissikowski, T.; Chèze, C.

2016-07-25

We investigate sub-monolayer InN quantum sheets embedded in GaN(0001) by temperature-dependent photoluminescence spectroscopy under both continuous-wave and pulsed excitation. Both the peak energy and the linewidth of the emission band associated with the quantum sheets exhibit an anomalous dependence on temperature indicative of carrier localization. Photoluminescence transients reveal a power law decay at low temperatures reflecting that the recombining electrons and holes occupy spatially separate, individual potential minima reminiscent of conventional (In,Ga)N(0001) quantum wells exhibiting the characteristic disorder of a random alloy. At elevated temperatures, carrier delocalization sets in and is accompanied by a thermally activated quenching of the emission.more » We ascribe the strong nonradiative recombination to extended states in the GaN barriers and confirm our assumption by a simple rate-equation model.« less

Matrix-assisted relaxation in Fe(phen)2(NCS)2 spin-crossover microparticles, experimental and theoretical investigations

NASA Astrophysics Data System (ADS)

Enachescu, Cristian; Tanasa, Radu; Stancu, Alexandru; Tissot, Antoine; Laisney, Jérôme; Boillot, Marie-Laure

2016-07-01

In this study, we present the influence of the embedding matrix on the relaxation of Fe(phen)2(NCS)2 (phen = 1,10-phenanthroline) spin-transition microparticles as revealed by experiments and provide an explanation within the framework of an elastic model based on a Monte-Carlo method. Experiments show that the shape of the high-spin → low-spin relaxation curves is drastically changed when the particles are dispersed in glycerol. This effect was considered in the model by means of interactions between the microparticles and the matrix. A faster start of the relaxation for microparticles embedded in glycerol is due to an initial positive local pressure acting on the edge spin-crossover molecules from the matrix side. This local pressure diminishes and eventually becomes negative during relaxation, as an effect of the decrease of the volume of spin-crossover microparticles from high-spin to low-spin.

Assessment of Schrodinger Eigenmaps for target detection

NASA Astrophysics Data System (ADS)

Dorado Munoz, Leidy P.; Messinger, David W.; Czaja, Wojtek

2014-06-01

Non-linear dimensionality reduction methods have been widely applied to hyperspectral imagery due to its structure as the information can be represented in a lower dimension without losing information, and because the non-linear methods preserve the local geometry of the data while the dimension is reduced. One of these methods is Laplacian Eigenmaps (LE), which assumes that the data lies on a low dimensional manifold embedded in a high dimensional space. LE builds a nearest neighbor graph, computes its Laplacian and performs the eigendecomposition of the Laplacian. These eigenfunctions constitute a basis for the lower dimensional space in which the geometry of the manifold is preserved. In addition to the reduction problem, LE has been widely used in tasks such as segmentation, clustering, and classification. In this regard, a new Schrodinger Eigenmaps (SE) method was developed and presented as a semi-supervised classification scheme in order to improve the classification performance and take advantage of the labeled data. SE is an algorithm built upon LE, where the former Laplacian operator is replaced by the Schrodinger operator. The Schrodinger operator includes a potential term V, that, taking advantage of the additional information such as labeled data, allows clustering of similar points. In this paper, we explore the idea of using SE in target detection. In this way, we present a framework where the potential term V is defined as a barrier potential: a diagonal matrix encoding the spatial position of the target, and the detection performance is evaluated by using different targets and different hyperspectral scenes.

Double-use linear polarization convertor using hybrid metamaterial based on VO2 phase transition in the terahertz region

NASA Astrophysics Data System (ADS)

Zou, Huanling; Xiao, Zhongyin; Li, Wei; Li, Chuan

2018-04-01

A number of polarization convertors based on metamaterials(MMs) have been investigated recently, but no one has proposed a high-efficiency linear polarization transformer both in transmission and reflection modes. Here, a bilayered MM embedded with vanadium dioxide (VO2) composed of a pair of sloping gold patches, bottom hybrid layer and a dielectric spacer is proposed as a double-use linear polarization convertor. It has been demonstrated numerically that this device has advantages of switching between transmission polarization conversion and reflection polarization conversion based on the phase transition of the VO2 film in the terahertz (THz) regime and the polarization conversion ratios (PCR) in both cases are higher than 90% in wide bands. The simulated linear polarization transmission/reflection coefficients and the surface current distributions give insight into the mechanism of the linear polarization conversions. Moreover, the physical mechanism of polarization sensitivity of the designed structure is investigated by the distributions of electric field. The proposed double-use linear polarization convertor shows great prospects in polarization imaging, and polarized light communications.

A new formulation for anisotropic radiative transfer problems. I - Solution with a variational technique

NASA Technical Reports Server (NTRS)

Cheyney, H., III; Arking, A.

1976-01-01

The equations of radiative transfer in anisotropically scattering media are reformulated as linear operator equations in a single independent variable. The resulting equations are suitable for solution by a variety of standard mathematical techniques. The operators appearing in the resulting equations are in general nonsymmetric; however, it is shown that every bounded linear operator equation can be embedded in a symmetric linear operator equation and a variational solution can be obtained in a straightforward way. For purposes of demonstration, a Rayleigh-Ritz variational method is applied to three problems involving simple phase functions. It is to be noted that the variational technique demonstrated is of general applicability and permits simple solutions for a wide range of otherwise difficult mathematical problems in physics.

One of the Boys: Constructions of Disengagement and Criteria for Being a Successful Student

ERIC Educational Resources Information Center

Grønborg, Lisbeth

2013-01-01

The article discusses how a peer group culture in the school setting, embedded in conflicting fields of work and education, co-constructs student disengagement. Disengagement is traditionally linked with dropout and engagement with completion, but the study shows that this relation is not so linear. The data are based on a field study, where the…

Communication: A simplified coupled-cluster Lagrangian for polarizable embedding.

PubMed

Krause, Katharina; Klopper, Wim

2016-01-28

A simplified coupled-cluster Lagrangian, which is linear in the Lagrangian multipliers, is proposed for the coupled-cluster treatment of a quantum mechanical system in a polarizable environment. In the simplified approach, the amplitude equations are decoupled from the Lagrangian multipliers and the energy obtained from the projected coupled-cluster equation corresponds to a stationary point of the Lagrangian.

Bubbles in Sediments

DTIC Science & Technology

1999-09-30

saturated poroelastic medium. The transition matrix scattering formalism was used to develop the scattered acoustic field(s) such that appropriate...sediment increases from a fluid model (simplest) to a fluid-saturated poroelastic model (most complex). Laboratory experiments in carefully quantified...of a linear acoustic field from a bubble, collection of bubbles, or other targets embedded in a fluid-saturated sediment are not well known. This

Communication: A simplified coupled-cluster Lagrangian for polarizable embedding

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

Krause, Katharina; Klopper, Wim, E-mail: klopper@kit.edu

A simplified coupled-cluster Lagrangian, which is linear in the Lagrangian multipliers, is proposed for the coupled-cluster treatment of a quantum mechanical system in a polarizable environment. In the simplified approach, the amplitude equations are decoupled from the Lagrangian multipliers and the energy obtained from the projected coupled-cluster equation corresponds to a stationary point of the Lagrangian.

Design a software real-time operation platform for wave piercing catamarans motion control using linear quadratic regulator based genetic algorithm.

PubMed

Liang, Lihua; Yuan, Jia; Zhang, Songtao; Zhao, Peng

2018-01-01

This work presents optimal linear quadratic regulator (LQR) based on genetic algorithm (GA) to solve the two degrees of freedom (2 DoF) motion control problem in head seas for wave piercing catamarans (WPC). The proposed LQR based GA control strategy is to select optimal weighting matrices (Q and R). The seakeeping performance of WPC based on proposed algorithm is challenged because of multi-input multi-output (MIMO) system of uncertain coefficient problems. Besides the kinematical constraint problems of WPC, the external conditions must be considered, like the sea disturbance and the actuators (a T-foil and two flaps) control. Moreover, this paper describes the MATLAB and LabVIEW software plats to simulate the reduction effects of WPC. Finally, the real-time (RT) NI CompactRIO embedded controller is selected to test the effectiveness of the actuators based on proposed techniques. In conclusion, simulation and experimental results prove the correctness of the proposed algorithm. The percentage of heave and pitch reductions are more than 18% in different high speeds and bad sea conditions. And the results also verify the feasibility of NI CompactRIO embedded controller.

Design a software real-time operation platform for wave piercing catamarans motion control using linear quadratic regulator based genetic algorithm

PubMed Central

Liang, Lihua; Zhang, Songtao; Zhao, Peng

2018-01-01

This work presents optimal linear quadratic regulator (LQR) based on genetic algorithm (GA) to solve the two degrees of freedom (2 DoF) motion control problem in head seas for wave piercing catamarans (WPC). The proposed LQR based GA control strategy is to select optimal weighting matrices (Q and R). The seakeeping performance of WPC based on proposed algorithm is challenged because of multi-input multi-output (MIMO) system of uncertain coefficient problems. Besides the kinematical constraint problems of WPC, the external conditions must be considered, like the sea disturbance and the actuators (a T-foil and two flaps) control. Moreover, this paper describes the MATLAB and LabVIEW software plats to simulate the reduction effects of WPC. Finally, the real-time (RT) NI CompactRIO embedded controller is selected to test the effectiveness of the actuators based on proposed techniques. In conclusion, simulation and experimental results prove the correctness of the proposed algorithm. The percentage of heave and pitch reductions are more than 18% in different high speeds and bad sea conditions. And the results also verify the feasibility of NI CompactRIO embedded controller. PMID:29709008

Wave scattering from random sets of closely spaced objects through linear embedding via Green's operators

NASA Astrophysics Data System (ADS)

Lancellotti, V.; de Hon, B. P.; Tijhuis, A. G.

2011-08-01

In this paper we present the application of linear embedding via Green's operators (LEGO) to the solution of the electromagnetic scattering from clusters of arbitrary (both conducting and penetrable) bodies randomly placed in a homogeneous background medium. In the LEGO method the objects are enclosed within simple-shaped bricks described in turn via scattering operators of equivalent surface current densities. Such operators have to be computed only once for a given frequency, and hence they can be re-used to perform the study of many distributions comprising the same objects located in different positions. The surface integral equations of LEGO are solved via the Moments Method combined with Adaptive Cross Approximation (to save memory) and Arnoldi basis functions (to compress the system). By means of purposefully selected numerical experiments we discuss the time requirements with respect to the geometry of a given distribution. Besides, we derive an approximate relationship between the (near-field) accuracy of the computed solution and the number of Arnoldi basis functions used to obtain it. This result endows LEGO with a handy practical criterion for both estimating the error and keeping it in check.

Localization of a mobile laser scanner via dimensional reduction

NASA Astrophysics Data System (ADS)

Lehtola, Ville V.; Virtanen, Juho-Pekka; Vaaja, Matti T.; Hyyppä, Hannu; Nüchter, Andreas

2016-11-01

We extend the concept of intrinsic localization from a theoretical one-dimensional (1D) solution onto a 2D manifold that is embedded in a 3D space, and then recover the full six degrees of freedom for a mobile laser scanner with a simultaneous localization and mapping algorithm (SLAM). By intrinsic localization, we mean that no reference coordinate system, such as global navigation satellite system (GNSS), nor inertial measurement unit (IMU) are used. Experiments are conducted with a 2D laser scanner mounted on a rolling prototype platform, VILMA. The concept offers potential in being extendable to other wheeled platforms.

Local Linear Observed-Score Equating

ERIC Educational Resources Information Center

Wiberg, Marie; van der Linden, Wim J.

2011-01-01

Two methods of local linear observed-score equating for use with anchor-test and single-group designs are introduced. In an empirical study, the two methods were compared with the current traditional linear methods for observed-score equating. As a criterion, the bias in the equated scores relative to true equating based on Lord's (1980)…

Synchronous correlation matrices and Connes’ embedding conjecture

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

Dykema, Kenneth J., E-mail: kdykema@math.tamu.edu; Paulsen, Vern, E-mail: vern@math.uh.edu

In the work of Paulsen et al. [J. Funct. Anal. (in press); preprint arXiv:1407.6918], the concept of synchronous quantum correlation matrices was introduced and these were shown to correspond to traces on certain C*-algebras. In particular, synchronous correlation matrices arose in their study of various versions of quantum chromatic numbers of graphs and other quantum versions of graph theoretic parameters. In this paper, we develop these ideas further, focusing on the relations between synchronous correlation matrices and microstates. We prove that Connes’ embedding conjecture is equivalent to the equality of two families of synchronous quantum correlation matrices. We prove thatmore » if Connes’ embedding conjecture has a positive answer, then the tracial rank and projective rank are equal for every graph. We then apply these results to more general non-local games.« less

Ultrastructural identification of peripheral myelin proteins by a pre-embedding immunogold labeling method.

PubMed

Canron, Marie-Hélène; Bouillot, Sandrine; Favereaux, Alexandre; Petry, Klaus G; Vital, Anne

2003-03-01

Ultrastructural immunolabeling of peripheral nervous system components is an important tool to study the relation between structure and function. Owing to the scarcity of certain antigens and the dense structure of the peripheral nerve, a pre-embedding technique is likely appropriate. After several investigations on procedures for pre-embedding immunolabeling, we propose a method that offers a good compromise between detection of antigenic sites and preservation of morphology at the ultrastructural level, and that is easy to use and suitable for investigations on peripheral nerve biopsies from humans. Pre-fixation by immersion in paraformaldehyde/glutaraldehyde is necessary to stabilize the ultrastructure. Then, ultrasmall gold particles with silver enhancement are advised. Antibodies against myelin protein zero and myelin basic protein were chosen for demonstration. The same technique was applied to localize a 35 kDa myelin protein.

The Properties of Lion Roars and Electron Dynamics in Mirror Mode Waves Observed by the Magnetospheric MultiScale Mission

NASA Astrophysics Data System (ADS)

Breuillard, H.; Le Contel, O.; Chust, T.; Berthomier, M.; Retino, A.; Turner, D. L.; Nakamura, R.; Baumjohann, W.; Cozzani, G.; Catapano, F.; Alexandrova, A.; Mirioni, L.; Graham, D. B.; Argall, M. R.; Fischer, D.; Wilder, F. D.; Gershman, D. J.; Varsani, A.; Lindqvist, P.-A.; Khotyaintsev, Yu. V.; Marklund, G.; Ergun, R. E.; Goodrich, K. A.; Ahmadi, N.; Burch, J. L.; Torbert, R. B.; Needell, G.; Chutter, M.; Rau, D.; Dors, I.; Russell, C. T.; Magnes, W.; Strangeway, R. J.; Bromund, K. R.; Wei, H.; Plaschke, F.; Anderson, B. J.; Le, G.; Moore, T. E.; Giles, B. L.; Paterson, W. R.; Pollock, C. J.; Dorelli, J. C.; Avanov, L. A.; Saito, Y.; Lavraud, B.; Fuselier, S. A.; Mauk, B. H.; Cohen, I. J.; Fennell, J. F.

2018-01-01

Mirror mode waves are ubiquitous in the Earth's magnetosheath, in particular behind the quasi-perpendicular shock. Embedded in these nonlinear structures, intense lion roars are often observed. Lion roars are characterized by whistler wave packets at a frequency ˜100 Hz, which are thought to be generated in the magnetic field minima. In this study, we make use of the high time resolution instruments on board the Magnetospheric MultiScale mission to investigate these waves and the associated electron dynamics in the quasi-perpendicular magnetosheath on 22 January 2016. We show that despite a core electron parallel anisotropy, lion roars can be generated locally in the range 0.05-0.2fce by the perpendicular anisotropy of electrons in a particular energy range. We also show that intense lion roars can be observed up to higher frequencies due to the sharp nonlinear peaks of the signal, which appear as sharp spikes in the dynamic spectra. As a result, a high sampling rate is needed to estimate correctly their amplitude, and the latter might have been underestimated in previous studies using lower time resolution instruments. We also present for the first-time 3-D high time resolution electron velocity distribution functions in mirror modes. We demonstrate that the dynamics of electrons trapped in the mirror mode structures are consistent with the Kivelson and Southwood (1996) model. However, these electrons can also interact with the embedded lion roars: first signatures of electron quasi-linear pitch angle diffusion and possible signatures of nonlinear interaction with high-amplitude wave packets are presented. These processes can lead to electron untrapping from mirror modes.

Bounded Linear Stability Analysis - A Time Delay Margin Estimation Approach for Adaptive Control

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Ishihara, Abraham K.; Krishnakumar, Kalmanje Srinlvas; Bakhtiari-Nejad, Maryam

2009-01-01

This paper presents a method for estimating time delay margin for model-reference adaptive control of systems with almost linear structured uncertainty. The bounded linear stability analysis method seeks to represent the conventional model-reference adaptive law by a locally bounded linear approximation within a small time window using the comparison lemma. The locally bounded linear approximation of the combined adaptive system is cast in a form of an input-time-delay differential equation over a small time window. The time delay margin of this system represents a local stability measure and is computed analytically by a matrix measure method, which provides a simple analytical technique for estimating an upper bound of time delay margin. Based on simulation results for a scalar model-reference adaptive control system, both the bounded linear stability method and the matrix measure method are seen to provide a reasonably accurate and yet not too conservative time delay margin estimation.

Breaking and Fixing Origin-Based Access Control in Hybrid Web/Mobile Application Frameworks

PubMed Central

Georgiev, Martin; Jana, Suman; Shmatikov, Vitaly

2014-01-01

Hybrid mobile applications (apps) combine the features of Web applications and “native” mobile apps. Like Web applications, they are implemented in portable, platform-independent languages such as HTML and JavaScript. Like native apps, they have direct access to local device resources—file system, location, camera, contacts, etc. Hybrid apps are typically developed using hybrid application frameworks such as PhoneGap. The purpose of the framework is twofold. First, it provides an embedded Web browser (for example, WebView on Android) that executes the app's Web code. Second, it supplies “bridges” that allow Web code to escape the browser and access local resources on the device. We analyze the software stack created by hybrid frameworks and demonstrate that it does not properly compose the access-control policies governing Web code and local code, respectively. Web code is governed by the same origin policy, whereas local code is governed by the access-control policy of the operating system (for example, user-granted permissions in Android). The bridges added by the framework to the browser have the same local access rights as the entire application, but are not correctly protected by the same origin policy. This opens the door to fracking attacks, which allow foreign-origin Web content included into a hybrid app (e.g., ads confined in iframes) to drill through the layers and directly access device resources. Fracking vulnerabilities are generic: they affect all hybrid frameworks, all embedded Web browsers, all bridge mechanisms, and all platforms on which these frameworks are deployed. We study the prevalence of fracking vulnerabilities in free Android apps based on the PhoneGap framework. Each vulnerability exposes sensitive local resources—the ability to read and write contacts list, local files, etc.—to dozens of potentially malicious Web domains. We also analyze the defenses deployed by hybrid frameworks to prevent resource access by foreign-origin Web content and explain why they are ineffectual. We then present NoFrak, a capability-based defense against fracking attacks. NoFrak is platform-independent, compatible with any framework and embedded browser, requires no changes to the code of the existing hybrid apps, and does not break their advertising-supported business model. PMID:25485311

Management of asymptomatic intracardiac missiles using echocardiography.

PubMed

Robison, R J; Brown, J W; Caldwell, R; Stone, K S; King, H

1988-09-01

A child sustained a low-velocity airgun pellet injury to the left ventricle. No cardiovascular compromise was produced. The foreign body was localized by two-dimensional echocardiography to the left ventricular chamber near the mitral valve, and subsequently removed through a left atriotomy incision. In asymptomatic patients, missiles clearly embedded within a chamber wall may be observed; all others should be removed. Two-dimensional echocardiography is recommended for localization.

Laser-Based Trespassing Prediction in Restrictive Environments: A Linear Approach

PubMed Central

Cheein, Fernando Auat; Scaglia, Gustavo

2012-01-01

Stationary range laser sensors for intruder monitoring, restricted space violation detections and workspace determination are extensively used in risky environments. In this work we present a linear based approach for predicting the presence of moving agents before they trespass a laser-based restricted space. Our approach is based on the Taylor's series expansion of the detected objects' movements. The latter makes our proposal suitable for embedded applications. In the experimental results (carried out in different scenarios) presented herein, our proposal shows 100% of effectiveness in predicting trespassing situations. Several implementation results and statistics analysis showing the performance of our proposal are included in this work.

Single Image Super-Resolution Using Global Regression Based on Multiple Local Linear Mappings.

PubMed

Choi, Jae-Seok; Kim, Munchurl

2017-03-01

Super-resolution (SR) has become more vital, because of its capability to generate high-quality ultra-high definition (UHD) high-resolution (HR) images from low-resolution (LR) input images. Conventional SR methods entail high computational complexity, which makes them difficult to be implemented for up-scaling of full-high-definition input images into UHD-resolution images. Nevertheless, our previous super-interpolation (SI) method showed a good compromise between Peak-Signal-to-Noise Ratio (PSNR) performances and computational complexity. However, since SI only utilizes simple linear mappings, it may fail to precisely reconstruct HR patches with complex texture. In this paper, we present a novel SR method, which inherits the large-to-small patch conversion scheme from SI but uses global regression based on local linear mappings (GLM). Thus, our new SR method is called GLM-SI. In GLM-SI, each LR input patch is divided into 25 overlapped subpatches. Next, based on the local properties of these subpatches, 25 different local linear mappings are applied to the current LR input patch to generate 25 HR patch candidates, which are then regressed into one final HR patch using a global regressor. The local linear mappings are learned cluster-wise in our off-line training phase. The main contribution of this paper is as follows: Previously, linear-mapping-based conventional SR methods, including SI only used one simple yet coarse linear mapping to each patch to reconstruct its HR version. On the contrary, for each LR input patch, our GLM-SI is the first to apply a combination of multiple local linear mappings, where each local linear mapping is found according to local properties of the current LR patch. Therefore, it can better approximate nonlinear LR-to-HR mappings for HR patches with complex texture. Experiment results show that the proposed GLM-SI method outperforms most of the state-of-the-art methods, and shows comparable PSNR performance with much lower computational complexity when compared with a super-resolution method based on convolutional neural nets (SRCNN15). Compared with the previous SI method that is limited with a scale factor of 2, GLM-SI shows superior performance with average 0.79 dB higher in PSNR, and can be used for scale factors of 3 or higher.

Vibrational properties of TaW alloy using modified embedded atom method potential

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

Chand, Manesh, E-mail: maneshchand@gmail.com; Uniyal, Shweta; Joshi, Subodh

2016-05-06

Force-constants up to second neighbours of pure transition metal Ta and TaW alloy are determined using the modified embedded atom method (MEAM) potential. The obtained force-constants are used to calculate the phonon dispersion of pure Ta and TaW alloy. As a further application of MEAM potential, the force-constants are used to calculate the local vibrational density of states and mean square thermal displacements of pure Ta and W impurity atoms with Green’s function method. The calculated results are found to be in agreement with the experimental measurements.

Scalar-Tensor Black Holes Embedded in an Expanding Universe

NASA Astrophysics Data System (ADS)

Tretyakova, Daria; Latosh, Boris

2018-02-01

In this review we focus our attention on scalar-tensor gravity models and their empirical verification in terms of black hole and wormhole physics. We focus on a black hole, embedded in an expanding universe, describing both cosmological and astrophysical scales. We show that in scalar-tensor gravity it is quite common that the local geometry is isolated from the cosmological expansion, so that it does not backreact on the black hole metric. We try to extract common features of scalar-tensor black holes in an expanding universe and point out the gaps that must be filled.

A General Exponential Framework for Dimensionality Reduction.

PubMed

Wang, Su-Jing; Yan, Shuicheng; Yang, Jian; Zhou, Chun-Guang; Fu, Xiaolan

2014-02-01

As a general framework, Laplacian embedding, based on a pairwise similarity matrix, infers low dimensional representations from high dimensional data. However, it generally suffers from three issues: 1) algorithmic performance is sensitive to the size of neighbors; 2) the algorithm encounters the well known small sample size (SSS) problem; and 3) the algorithm de-emphasizes small distance pairs. To address these issues, here we propose exponential embedding using matrix exponential and provide a general framework for dimensionality reduction. In the framework, the matrix exponential can be roughly interpreted by the random walk over the feature similarity matrix, and thus is more robust. The positive definite property of matrix exponential deals with the SSS problem. The behavior of the decay function of exponential embedding is more significant in emphasizing small distance pairs. Under this framework, we apply matrix exponential to extend many popular Laplacian embedding algorithms, e.g., locality preserving projections, unsupervised discriminant projections, and marginal fisher analysis. Experiments conducted on the synthesized data, UCI, and the Georgia Tech face database show that the proposed new framework can well address the issues mentioned above.

Self-sensing concrete-filled FRP tubes using FBG strain sensors

NASA Astrophysics Data System (ADS)

Yan, Xin; Li, Hui

2007-07-01

Concrete-filled fiber-reinforced polymer (FRP) tube is a type of newly developed structural column. It behaves brittle failure at its peak strength, and so the health monitoring on the hoop strain of the FRP tube is essential for the life cycle safety of the structure. Herein, three types of FRP tubes including 5-ply tube, 2-ply tube with local reinforcement and FRP-steel composite tube were embedded with the optic fiber Bragg grating (FBG) strain sensors in the inter-ply of FRP or the interface between FRP and steel in the middle height and the hoop direction. The compressive behaviors of the concrete-filled FRP tubes were experimentally studied. The hoop strains of the FRP tubes were recorded in real time using the embedded FBG strain sensors as well as the embedded or surface electric resistance strain gauges. Results indicated that the FBG strain sensors can faithfully record the hoop strains of the FRP tubes in compression as compared with the embedded or surface electric resistance strain gauges, and the strains recorded can reach more than μɛ.

Site-occupation embedding theory using Bethe ansatz local density approximations

NASA Astrophysics Data System (ADS)

Senjean, Bruno; Nakatani, Naoki; Tsuchiizu, Masahisa; Fromager, Emmanuel

2018-06-01

Site-occupation embedding theory (SOET) is an alternative formulation of density functional theory (DFT) for model Hamiltonians where the fully interacting Hubbard problem is mapped, in principle exactly, onto an impurity-interacting (rather than a noninteracting) one. It provides a rigorous framework for combining wave-function (or Green function)-based methods with DFT. In this work, exact expressions for the per-site energy and double occupation of the uniform Hubbard model are derived in the context of SOET. As readily seen from these derivations, the so-called bath contribution to the per-site correlation energy is, in addition to the latter, the key density functional quantity to model in SOET. Various approximations based on Bethe ansatz and perturbative solutions to the Hubbard and single-impurity Anderson models are constructed and tested on a one-dimensional ring. The self-consistent calculation of the embedded impurity wave function has been performed with the density-matrix renormalization group method. It has been shown that promising results are obtained in specific regimes of correlation and density. Possible further developments have been proposed in order to provide reliable embedding functionals and potentials.

Development of intelligent instruments with embedded HTTP servers for control and data acquisition in a cryogenic setup--The hardware, firmware, and software implementation.

PubMed

Antony, Joby; Mathuria, D S; Datta, T S; Maity, Tanmoy

2015-12-01

The power of Ethernet for control and automation technology is being largely understood by the automation industry in recent times. Ethernet with HTTP (Hypertext Transfer Protocol) is one of the most widely accepted communication standards today. Ethernet is best known for being able to control through internet from anywhere in the globe. The Ethernet interface with built-in on-chip embedded servers ensures global connections for crate-less model of control and data acquisition systems which have several advantages over traditional crate-based control architectures for slow applications. This architecture will completely eliminate the use of any extra PLC (Programmable Logic Controller) or similar control hardware in any automation network as the control functions are firmware coded inside intelligent meters itself. Here, we describe the indigenously built project of a cryogenic control system built for linear accelerator at Inter University Accelerator Centre, known as "CADS," which stands for "Complete Automation of Distribution System." CADS deals with complete hardware, firmware, and software implementation of the automated linac cryogenic distribution system using many Ethernet based embedded cryogenic instruments developed in-house. Each instrument works as an intelligent meter called device-server which has the control functions and control loops built inside the firmware itself. Dedicated meters with built-in servers were designed out of ARM (Acorn RISC (Reduced Instruction Set Computer) Machine) and ATMEL processors and COTS (Commercially Off-the-Shelf) SMD (Surface Mount Devices) components, with analog sensor front-end and a digital back-end web server implementing remote procedure call over HTTP for digital control and readout functions. At present, 24 instruments which run 58 embedded servers inside, each specific to a particular type of sensor-actuator combination for closed loop operations, are now deployed and distributed across control LAN (Local Area Network). A group of six categories of such instruments have been identified for all cryogenic applications required for linac operation which were designed to build this medium-scale cryogenic automation setup. These devices have special features like remote rebooters, daughter boards for PIDs (Proportional Integral Derivative), etc., to operate them remotely in radiation areas and also have emergency switches by which each device can be taken to emergency mode temporarily. Finally, all the data are monitored, logged, controlled, and analyzed online at a central control room which has a user-friendly control interface developed using LabVIEW(®). This paper discusses the overall hardware, firmware, software design, and implementation for the cryogenics setup.

Development of intelligent instruments with embedded HTTP servers for control and data acquisition in a cryogenic setup—The hardware, firmware, and software implementation

NASA Astrophysics Data System (ADS)

Antony, Joby; Mathuria, D. S.; Datta, T. S.; Maity, Tanmoy

2015-12-01

The power of Ethernet for control and automation technology is being largely understood by the automation industry in recent times. Ethernet with HTTP (Hypertext Transfer Protocol) is one of the most widely accepted communication standards today. Ethernet is best known for being able to control through internet from anywhere in the globe. The Ethernet interface with built-in on-chip embedded servers ensures global connections for crate-less model of control and data acquisition systems which have several advantages over traditional crate-based control architectures for slow applications. This architecture will completely eliminate the use of any extra PLC (Programmable Logic Controller) or similar control hardware in any automation network as the control functions are firmware coded inside intelligent meters itself. Here, we describe the indigenously built project of a cryogenic control system built for linear accelerator at Inter University Accelerator Centre, known as "CADS," which stands for "Complete Automation of Distribution System." CADS deals with complete hardware, firmware, and software implementation of the automated linac cryogenic distribution system using many Ethernet based embedded cryogenic instruments developed in-house. Each instrument works as an intelligent meter called device-server which has the control functions and control loops built inside the firmware itself. Dedicated meters with built-in servers were designed out of ARM (Acorn RISC (Reduced Instruction Set Computer) Machine) and ATMEL processors and COTS (Commercially Off-the-Shelf) SMD (Surface Mount Devices) components, with analog sensor front-end and a digital back-end web server implementing remote procedure call over HTTP for digital control and readout functions. At present, 24 instruments which run 58 embedded servers inside, each specific to a particular type of sensor-actuator combination for closed loop operations, are now deployed and distributed across control LAN (Local Area Network). A group of six categories of such instruments have been identified for all cryogenic applications required for linac operation which were designed to build this medium-scale cryogenic automation setup. These devices have special features like remote rebooters, daughter boards for PIDs (Proportional Integral Derivative), etc., to operate them remotely in radiation areas and also have emergency switches by which each device can be taken to emergency mode temporarily. Finally, all the data are monitored, logged, controlled, and analyzed online at a central control room which has a user-friendly control interface developed using LabVIEW®. This paper discusses the overall hardware, firmware, software design, and implementation for the cryogenics setup.

Development of intelligent instruments with embedded HTTP servers for control and data acquisition in a cryogenic setup—The hardware, firmware, and software implementation

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

Antony, Joby; Mathuria, D. S.; Datta, T. S.

The power of Ethernet for control and automation technology is being largely understood by the automation industry in recent times. Ethernet with HTTP (Hypertext Transfer Protocol) is one of the most widely accepted communication standards today. Ethernet is best known for being able to control through internet from anywhere in the globe. The Ethernet interface with built-in on-chip embedded servers ensures global connections for crate-less model of control and data acquisition systems which have several advantages over traditional crate-based control architectures for slow applications. This architecture will completely eliminate the use of any extra PLC (Programmable Logic Controller) or similarmore » control hardware in any automation network as the control functions are firmware coded inside intelligent meters itself. Here, we describe the indigenously built project of a cryogenic control system built for linear accelerator at Inter University Accelerator Centre, known as “CADS,” which stands for “Complete Automation of Distribution System.” CADS deals with complete hardware, firmware, and software implementation of the automated linac cryogenic distribution system using many Ethernet based embedded cryogenic instruments developed in-house. Each instrument works as an intelligent meter called device-server which has the control functions and control loops built inside the firmware itself. Dedicated meters with built-in servers were designed out of ARM (Acorn RISC (Reduced Instruction Set Computer) Machine) and ATMEL processors and COTS (Commercially Off-the-Shelf) SMD (Surface Mount Devices) components, with analog sensor front-end and a digital back-end web server implementing remote procedure call over HTTP for digital control and readout functions. At present, 24 instruments which run 58 embedded servers inside, each specific to a particular type of sensor-actuator combination for closed loop operations, are now deployed and distributed across control LAN (Local Area Network). A group of six categories of such instruments have been identified for all cryogenic applications required for linac operation which were designed to build this medium-scale cryogenic automation setup. These devices have special features like remote rebooters, daughter boards for PIDs (Proportional Integral Derivative), etc., to operate them remotely in radiation areas and also have emergency switches by which each device can be taken to emergency mode temporarily. Finally, all the data are monitored, logged, controlled, and analyzed online at a central control room which has a user-friendly control interface developed using LabVIEW{sup ®}. This paper discusses the overall hardware, firmware, software design, and implementation for the cryogenics setup.« less

Localization of the eigenvalues of linear integral equations with applications to linear ordinary differential equations.

NASA Technical Reports Server (NTRS)

Sloss, J. M.; Kranzler, S. K.

1972-01-01

The equivalence of a considered integral equation form with an infinite system of linear equations is proved, and the localization of the eigenvalues of the infinite system is expressed. Error estimates are derived, and the problems of finding upper bounds and lower bounds for the eigenvalues are solved simultaneously.

Dimensionality reduction of collective motion by principal manifolds

NASA Astrophysics Data System (ADS)

Gajamannage, Kelum; Butail, Sachit; Porfiri, Maurizio; Bollt, Erik M.

2015-01-01

While the existence of low-dimensional embedding manifolds has been shown in patterns of collective motion, the current battery of nonlinear dimensionality reduction methods is not amenable to the analysis of such manifolds. This is mainly due to the necessary spectral decomposition step, which limits control over the mapping from the original high-dimensional space to the embedding space. Here, we propose an alternative approach that demands a two-dimensional embedding which topologically summarizes the high-dimensional data. In this sense, our approach is closely related to the construction of one-dimensional principal curves that minimize orthogonal error to data points subject to smoothness constraints. Specifically, we construct a two-dimensional principal manifold directly in the high-dimensional space using cubic smoothing splines, and define the embedding coordinates in terms of geodesic distances. Thus, the mapping from the high-dimensional data to the manifold is defined in terms of local coordinates. Through representative examples, we show that compared to existing nonlinear dimensionality reduction methods, the principal manifold retains the original structure even in noisy and sparse datasets. The principal manifold finding algorithm is applied to configurations obtained from a dynamical system of multiple agents simulating a complex maneuver called predator mobbing, and the resulting two-dimensional embedding is compared with that of a well-established nonlinear dimensionality reduction method.

Metric Optimization for Surface Analysis in the Laplace-Beltrami Embedding Space

PubMed Central

Lai, Rongjie; Wang, Danny J.J.; Pelletier, Daniel; Mohr, David; Sicotte, Nancy; Toga, Arthur W.

2014-01-01

In this paper we present a novel approach for the intrinsic mapping of anatomical surfaces and its application in brain mapping research. Using the Laplace-Beltrami eigen-system, we represent each surface with an isometry invariant embedding in a high dimensional space. The key idea in our system is that we realize surface deformation in the embedding space via the iterative optimization of a conformal metric without explicitly perturbing the surface or its embedding. By minimizing a distance measure in the embedding space with metric optimization, our method generates a conformal map directly between surfaces with highly uniform metric distortion and the ability of aligning salient geometric features. Besides pairwise surface maps, we also extend the metric optimization approach for group-wise atlas construction and multi-atlas cortical label fusion. In experimental results, we demonstrate the robustness and generality of our method by applying it to map both cortical and hippocampal surfaces in population studies. For cortical labeling, our method achieves excellent performance in a cross-validation experiment with 40 manually labeled surfaces, and successfully models localized brain development in a pediatric study of 80 subjects. For hippocampal mapping, our method produces much more significant results than two popular tools on a multiple sclerosis study of 109 subjects. PMID:24686245

Nonlinear secret image sharing scheme.

PubMed

Shin, Sang-Ho; Lee, Gil-Je; Yoo, Kee-Young

2014-01-01

Over the past decade, most of secret image sharing schemes have been proposed by using Shamir's technique. It is based on a linear combination polynomial arithmetic. Although Shamir's technique based secret image sharing schemes are efficient and scalable for various environments, there exists a security threat such as Tompa-Woll attack. Renvall and Ding proposed a new secret sharing technique based on nonlinear combination polynomial arithmetic in order to solve this threat. It is hard to apply to the secret image sharing. In this paper, we propose a (t, n)-threshold nonlinear secret image sharing scheme with steganography concept. In order to achieve a suitable and secure secret image sharing scheme, we adapt a modified LSB embedding technique with XOR Boolean algebra operation, define a new variable m, and change a range of prime p in sharing procedure. In order to evaluate efficiency and security of proposed scheme, we use the embedding capacity and PSNR. As a result of it, average value of PSNR and embedding capacity are 44.78 (dB) and 1.74t⌈log2 m⌉ bit-per-pixel (bpp), respectively.

Nonlinear Secret Image Sharing Scheme

PubMed Central

Shin, Sang-Ho; Yoo, Kee-Young

2014-01-01

Over the past decade, most of secret image sharing schemes have been proposed by using Shamir's technique. It is based on a linear combination polynomial arithmetic. Although Shamir's technique based secret image sharing schemes are efficient and scalable for various environments, there exists a security threat such as Tompa-Woll attack. Renvall and Ding proposed a new secret sharing technique based on nonlinear combination polynomial arithmetic in order to solve this threat. It is hard to apply to the secret image sharing. In this paper, we propose a (t, n)-threshold nonlinear secret image sharing scheme with steganography concept. In order to achieve a suitable and secure secret image sharing scheme, we adapt a modified LSB embedding technique with XOR Boolean algebra operation, define a new variable m, and change a range of prime p in sharing procedure. In order to evaluate efficiency and security of proposed scheme, we use the embedding capacity and PSNR. As a result of it, average value of PSNR and embedding capacity are 44.78 (dB) and 1.74t⌈log2⁡m⌉ bit-per-pixel (bpp), respectively. PMID:25140334

STRONG ORACLE OPTIMALITY OF FOLDED CONCAVE PENALIZED ESTIMATION.

PubMed

Fan, Jianqing; Xue, Lingzhou; Zou, Hui

2014-06-01

Folded concave penalization methods have been shown to enjoy the strong oracle property for high-dimensional sparse estimation. However, a folded concave penalization problem usually has multiple local solutions and the oracle property is established only for one of the unknown local solutions. A challenging fundamental issue still remains that it is not clear whether the local optimum computed by a given optimization algorithm possesses those nice theoretical properties. To close this important theoretical gap in over a decade, we provide a unified theory to show explicitly how to obtain the oracle solution via the local linear approximation algorithm. For a folded concave penalized estimation problem, we show that as long as the problem is localizable and the oracle estimator is well behaved, we can obtain the oracle estimator by using the one-step local linear approximation. In addition, once the oracle estimator is obtained, the local linear approximation algorithm converges, namely it produces the same estimator in the next iteration. The general theory is demonstrated by using four classical sparse estimation problems, i.e., sparse linear regression, sparse logistic regression, sparse precision matrix estimation and sparse quantile regression.

STRONG ORACLE OPTIMALITY OF FOLDED CONCAVE PENALIZED ESTIMATION

PubMed Central

Fan, Jianqing; Xue, Lingzhou; Zou, Hui

2014-01-01

Folded concave penalization methods have been shown to enjoy the strong oracle property for high-dimensional sparse estimation. However, a folded concave penalization problem usually has multiple local solutions and the oracle property is established only for one of the unknown local solutions. A challenging fundamental issue still remains that it is not clear whether the local optimum computed by a given optimization algorithm possesses those nice theoretical properties. To close this important theoretical gap in over a decade, we provide a unified theory to show explicitly how to obtain the oracle solution via the local linear approximation algorithm. For a folded concave penalized estimation problem, we show that as long as the problem is localizable and the oracle estimator is well behaved, we can obtain the oracle estimator by using the one-step local linear approximation. In addition, once the oracle estimator is obtained, the local linear approximation algorithm converges, namely it produces the same estimator in the next iteration. The general theory is demonstrated by using four classical sparse estimation problems, i.e., sparse linear regression, sparse logistic regression, sparse precision matrix estimation and sparse quantile regression. PMID:25598560

Preface: Introductory Remarks: Linear Scaling Methods

NASA Astrophysics Data System (ADS)

Bowler, D. R.; Fattebert, J.-L.; Gillan, M. J.; Haynes, P. D.; Skylaris, C.-K.

2008-07-01

It has been just over twenty years since the publication of the seminal paper on molecular dynamics with ab initio methods by Car and Parrinello [1], and the contribution of density functional theory (DFT) and the related techniques to physics, chemistry, materials science, earth science and biochemistry has been huge. Nevertheless, significant improvements are still being made to the performance of these standard techniques; recent work suggests that speed improvements of one or even two orders of magnitude are possible [2]. One of the areas where major progress has long been expected is in O(N), or linear scaling, DFT, in which the computer effort is proportional to the number of atoms. Linear scaling DFT methods have been in development for over ten years [3] but we are now in an exciting period where more and more research groups are working on these methods. Naturally there is a strong and continuing effort to improve the efficiency of the methods and to make them more robust. But there is also a growing ambition to apply them to challenging real-life problems. This special issue contains papers submitted following the CECAM Workshop 'Linear-scaling ab initio calculations: applications and future directions', held in Lyon from 3-6 September 2007. A noteworthy feature of the workshop is that it included a significant number of presentations involving real applications of O(N) methods, as well as work to extend O(N) methods into areas of greater accuracy (correlated wavefunction methods, quantum Monte Carlo, TDDFT) and large scale computer architectures. As well as explicitly linear scaling methods, the conference included presentations on techniques designed to accelerate and improve the efficiency of standard (that is non-linear-scaling) methods; this highlights the important question of crossover—that is, at what size of system does it become more efficient to use a linear-scaling method? As well as fundamental algorithmic questions, this brings up implementation questions relating to parallelization (particularly with multi-core processors starting to dominate the market) and inherent scaling and basis sets (in both normal and linear scaling codes). For now, the answer seems to lie between 100-1,000 atoms, though this depends on the type of simulation used among other factors. Basis sets are still a problematic question in the area of electronic structure calculations. The linear scaling community has largely split into two camps: those using relatively small basis sets based on local atomic-like functions (where systematic convergence to the full basis set limit is hard to achieve); and those that use necessarily larger basis sets which allow convergence systematically and therefore are the localised equivalent of plane waves. Related to basis sets is the study of Wannier functions, on which some linear scaling methods are based and which give a good point of contact with traditional techniques; they are particularly interesting for modelling unoccupied states with linear scaling methods. There are, of course, as many approaches to linear scaling solution for the density matrix as there are groups in the area, though there are various broad areas: McWeeny-based methods, fragment-based methods, recursion methods, and combinations of these. While many ideas have been in development for several years, there are still improvements emerging, as shown by the rich variety of the talks below. Applications using O(N) DFT methods are now starting to emerge, though they are still clearly not trivial. Once systems to be simulated cross the 10,000 atom barrier, only linear scaling methods can be applied, even with the most efficient standard techniques. One of the most challenging problems remaining, now that ab initio methods can be applied to large systems, is the long timescale problem. Although much of the work presented was concerned with improving the performance of the codes, and applying them to scientificallyimportant problems, there was another important theme: extending functionality. The search for greater accuracy has given an implementation of density functional designed to model van der Waals interactions accurately as well as local correlation, TDDFT and QMC and GW methods which, while not explicitly O(N), take advantage of localisation. All speakers at the workshop were invited to contribute to this issue, but not all were able to do this. Hence it is useful to give a complete list of the talks presented, with the names of the sessions; however, many talks fell within more than one area. This is an exciting time for linear scaling methods, which are already starting to contribute significantly to important scientific problems. Applications to nanostructures and biomolecules A DFT study on the structural stability of Ge 3D nanostructures on Si(001) using CONQUEST Tsuyoshi Miyazaki, D R Bowler, M J Gillan, T Otsuka and T Ohno Large scale electronic structure calculation theory and several applications Takeo Fujiwara and Takeo Hoshi ONETEP:Linear-scaling DFT with plane waves Chris-Kriton Skylaris, Peter D Haynes, Arash A Mostofi, Mike C Payne Maximally-localised Wannier functions as building blocks for large-scale electronic structure calculations Arash A Mostofi and Nicola Marzari A linear scaling three dimensional fragment method for ab initio calculations Lin-Wang Wang, Zhengji Zhao, Juan Meza Peta-scalable reactive Molecular dynamics simulation of mechanochemical processes Aiichiro Nakano, Rajiv K. Kalia, Ken-ichi Nomura, Fuyuki Shimojo and Priya Vashishta Recent developments and applications of the real-space multigrid (RMG) method Jerzy Bernholc, M Hodak, W Lu, and F Ribeiro Energy minimisation functionals and algorithms CONQUEST: A linear scaling DFT Code David R Bowler, Tsuyoshi Miyazaki, Antonio Torralba, Veronika Brazdova, Milica Todorovic, Takao Otsuka and Mike Gillan Kernel optimisation and the physical significance of optimised local orbitals in the ONETEP code Peter Haynes, Chris-Kriton Skylaris, Arash Mostofi and Mike Payne A miscellaneous overview of SIESTA algorithms Jose M Soler Wavelets as a basis set for electronic structure calculations and electrostatic problems Stefan Goedecker Wavelets as a basis set for linear scaling electronic structure calculationsMark Rayson O(N) Krylov subspace method for large-scale ab initio electronic structure calculations Taisuke Ozaki Linear scaling calculations with the divide-and-conquer approach and with non-orthogonal localized orbitals Weitao Yang Toward efficient wavefunction based linear scaling energy minimization Valery Weber Accurate O(N) first-principles DFT calculations using finite differences and confined orbitals Jean-Luc Fattebert Linear-scaling methods in dynamics simulations or beyond DFT and ground state properties An O(N) time-domain algorithm for TDDFT Guan Hua Chen Local correlation theory and electronic delocalization Joseph Subotnik Ab initio molecular dynamics with linear scaling: foundations and applications Eiji Tsuchida Towards a linear scaling Car-Parrinello-like approach to Born-Oppenheimer molecular dynamics Thomas Kühne, Michele Ceriotti, Matthias Krack and Michele Parrinello Partial linear scaling for quantum Monte Carlo calculations on condensed matter Mike Gillan Exact embedding of local defects in crystals using maximally localized Wannier functions Eric Cancès Faster GW calculations in larger model structures using ultralocalized nonorthogonal Wannier functions Paolo Umari Other approaches for linear-scaling, including methods formetals Partition-of-unity finite element method for large, accurate electronic-structure calculations of metals John E Pask and Natarajan Sukumar Semiclassical approach to density functional theory Kieron Burke Ab initio transport calculations in defected carbon nanotubes using O(N) techniques Blanca Biel, F J Garcia-Vidal, A Rubio and F Flores Large-scale calculations with the tight-binding (screened) KKR method Rudolf Zeller Acknowledgments We gratefully acknowledge funding for the workshop from the UK CCP9 network, CECAM and the ESF through the PsiK network. DRB, PDH and CKS are funded by the Royal Society. References [1] Car R and Parrinello M 1985 Phys. Rev. Lett. 55 2471 [2] Kühne T D, Krack M, Mohamed F R and Parrinello M 2007 Phys. Rev. Lett. 98 066401 [3] Goedecker S 1999 Rev. Mod. Phys. 71 1085

Immunocytochemistry by electron spectroscopic imaging using a homogeneously boronated peptide.

PubMed

Kessels, M M; Qualmann, B; Klobasa, F; Sierralta, W D

1996-05-01

A linear all-L-oligopeptide containing five carboranyl amino acids (corresponding to 50 boron atoms) was synthesized and specifically attached to the free thiol group of monovalent antibody fragments F(ab)'. The boronated immunoreagent was used for the direct post-embedding detection of somatotrophic hormone in ultrathin sections of porcine pituitary embedded in Spurr resin. The specific boron-labelling of secretory vesicles in somatotrophs was detected by electron spectroscopic imaging and confirmed by conventional immunogold labelling run in parallel. In comparison with immunogold, boron-labelled F(ab)'-fragments showed higher tagging frequencies, as was expected; the small uncharged immunoreagents have an elongated shape and carry the antigen-combining structure and the detection tag at opposite ends, thus allowing for high spatial resolution in electron spectroscopic imaging.

Misalignment tolerant efficient inverse taper coupler for silicon waveguide

NASA Astrophysics Data System (ADS)

Wang, Peng; Michael, Aron; Kwok, Chee Yee; Chen, Ssu-Han

2015-12-01

This paper describes an efficient fiber to submicron silicon waveguide coupling based on an inversely tapered silicon waveguide embedded in a SiO2 waveguide that is suspended in air. The inverse taper waveguide consist of a 50um long and 240nm thick silicon that linearly taper in width from 500nm to 120nm, which is embedded in SiO2. The SiO2 waveguide is 6um wide and 10um long. The simulation results show that the coupling loss of this new approach is 2.7dB including the interface loss at the input and output. The tolerance to fiber misalignment at the input of the coupler is 2um in both horizontal and vertical directions for only 1.5dB additional loss.

Estimating the remaining useful life of bearings using a neuro-local linear estimator-based method.

PubMed

Ahmad, Wasim; Ali Khan, Sheraz; Kim, Jong-Myon

2017-05-01

Estimating the remaining useful life (RUL) of a bearing is required for maintenance scheduling. While the degradation behavior of a bearing changes during its lifetime, it is usually assumed to follow a single model. In this letter, bearing degradation is modeled by a monotonically increasing function that is globally non-linear and locally linearized. The model is generated using historical data that is smoothed with a local linear estimator. A neural network learns this model and then predicts future levels of vibration acceleration to estimate the RUL of a bearing. The proposed method yields reasonably accurate estimates of the RUL of a bearing at different points during its operational life.

Hippocampus Segmentation Based on Local Linear Mapping

PubMed Central

Pang, Shumao; Jiang, Jun; Lu, Zhentai; Li, Xueli; Yang, Wei; Huang, Meiyan; Zhang, Yu; Feng, Yanqiu; Huang, Wenhua; Feng, Qianjin

2017-01-01

We propose local linear mapping (LLM), a novel fusion framework for distance field (DF) to perform automatic hippocampus segmentation. A k-means cluster method is propose for constructing magnetic resonance (MR) and DF dictionaries. In LLM, we assume that the MR and DF samples are located on two nonlinear manifolds and the mapping from the MR manifold to the DF manifold is differentiable and locally linear. We combine the MR dictionary using local linear representation to present the test sample, and combine the DF dictionary using the corresponding coefficients derived from local linear representation procedure to predict the DF of the test sample. We then merge the overlapped predicted DF patch to obtain the DF value of each point in the test image via a confidence-based weighted average method. This approach enabled us to estimate the label of the test image according to the predicted DF. The proposed method was evaluated on brain images of 35 subjects obtained from SATA dataset. Results indicate the effectiveness of the proposed method, which yields mean Dice similarity coefficients of 0.8697, 0.8770 and 0.8734 for the left, right and bi-lateral hippocampus, respectively. PMID:28368016

Hippocampus Segmentation Based on Local Linear Mapping.

PubMed

Pang, Shumao; Jiang, Jun; Lu, Zhentai; Li, Xueli; Yang, Wei; Huang, Meiyan; Zhang, Yu; Feng, Yanqiu; Huang, Wenhua; Feng, Qianjin

2017-04-03

We propose local linear mapping (LLM), a novel fusion framework for distance field (DF) to perform automatic hippocampus segmentation. A k-means cluster method is propose for constructing magnetic resonance (MR) and DF dictionaries. In LLM, we assume that the MR and DF samples are located on two nonlinear manifolds and the mapping from the MR manifold to the DF manifold is differentiable and locally linear. We combine the MR dictionary using local linear representation to present the test sample, and combine the DF dictionary using the corresponding coefficients derived from local linear representation procedure to predict the DF of the test sample. We then merge the overlapped predicted DF patch to obtain the DF value of each point in the test image via a confidence-based weighted average method. This approach enabled us to estimate the label of the test image according to the predicted DF. The proposed method was evaluated on brain images of 35 subjects obtained from SATA dataset. Results indicate the effectiveness of the proposed method, which yields mean Dice similarity coefficients of 0.8697, 0.8770 and 0.8734 for the left, right and bi-lateral hippocampus, respectively.

Hippocampus Segmentation Based on Local Linear Mapping

NASA Astrophysics Data System (ADS)

Pang, Shumao; Jiang, Jun; Lu, Zhentai; Li, Xueli; Yang, Wei; Huang, Meiyan; Zhang, Yu; Feng, Yanqiu; Huang, Wenhua; Feng, Qianjin

2017-04-01

We propose local linear mapping (LLM), a novel fusion framework for distance field (DF) to perform automatic hippocampus segmentation. A k-means cluster method is propose for constructing magnetic resonance (MR) and DF dictionaries. In LLM, we assume that the MR and DF samples are located on two nonlinear manifolds and the mapping from the MR manifold to the DF manifold is differentiable and locally linear. We combine the MR dictionary using local linear representation to present the test sample, and combine the DF dictionary using the corresponding coefficients derived from local linear representation procedure to predict the DF of the test sample. We then merge the overlapped predicted DF patch to obtain the DF value of each point in the test image via a confidence-based weighted average method. This approach enabled us to estimate the label of the test image according to the predicted DF. The proposed method was evaluated on brain images of 35 subjects obtained from SATA dataset. Results indicate the effectiveness of the proposed method, which yields mean Dice similarity coefficients of 0.8697, 0.8770 and 0.8734 for the left, right and bi-lateral hippocampus, respectively.

Co-sputter deposited nickel-copper bimetallic nanoalloy embedded carbon films for electrocatalytic biomarker detection

NASA Astrophysics Data System (ADS)

Shiba, Shunsuke; Kato, Dai; Kamata, Tomoyuki; Niwa, Osamu

2016-06-01

We report the fabrication of a nickel (Ni)-copper (Cu) bimetallic nanoalloy (~3 nm) embedded carbon film electrode with the unbalanced magnetron (UBM) co-sputtering technique, which requires only a one-step process at room temperature. Most of each nanoalloy body was firmly embedded in a chemically stable carbon matrix with an atomically flat surface (Ra: 0.21 nm), suppressing the aggregation and/or detachment of the nanoalloy from the electrode surface. The nanoalloy size and composition can be controlled simply by individually controlling the target powers of carbon, Ni and Cu, which also makes it possible to localize the nanoalloys near the electrode surface. This electrode exhibited excellent electrocatalytic activity for d-mannitol, which should be detected with a low detection limit in urine samples for the diagnosis of severe intestinal diseases. With a Ni/Cu ratio of around 64/36, the electrocatalytic current per metal area was 3.4 times larger than that of an alloy film electrode with a similar composition (~70/30). This improved electrocatalytic activity realized higher stability (n = 60, relative standard deviation (RSD): 4.6%) than the alloy film (RSD: 32.2%) as demonstrated by continuous measurements of d-mannitol.We report the fabrication of a nickel (Ni)-copper (Cu) bimetallic nanoalloy (~3 nm) embedded carbon film electrode with the unbalanced magnetron (UBM) co-sputtering technique, which requires only a one-step process at room temperature. Most of each nanoalloy body was firmly embedded in a chemically stable carbon matrix with an atomically flat surface (Ra: 0.21 nm), suppressing the aggregation and/or detachment of the nanoalloy from the electrode surface. The nanoalloy size and composition can be controlled simply by individually controlling the target powers of carbon, Ni and Cu, which also makes it possible to localize the nanoalloys near the electrode surface. This electrode exhibited excellent electrocatalytic activity for d-mannitol, which should be detected with a low detection limit in urine samples for the diagnosis of severe intestinal diseases. With a Ni/Cu ratio of around 64/36, the electrocatalytic current per metal area was 3.4 times larger than that of an alloy film electrode with a similar composition (~70/30). This improved electrocatalytic activity realized higher stability (n = 60, relative standard deviation (RSD): 4.6%) than the alloy film (RSD: 32.2%) as demonstrated by continuous measurements of d-mannitol. Electronic supplementary information (ESI) available: The concept of UBM co-sputtering for fabricating nanoalloy embedded carbon films. HRTEM images of the NiNP and Ni32Cu68 nanoalloy embedded carbon films. The experimental conditions for sputter deposition, HRTEM, HAADF-STEM, STEM-EDS measurements and continuous flow injection analysis. XPS analysis of the nanoalloy embedded carbon film. Repeated CVs of both the nanoalloy embedded carbon film and the alloy film. Amperometric detection of d-mannitol in the presence of chloride ions. See DOI: 10.1039/c6nr02287a

Voids in Gravitational Instability Scenarios - Part One - Global Density and Velocity Fields in an Einstein - De-Sitter Universe

NASA Astrophysics Data System (ADS)

van de Weygaert, R.; van Kampen, E.

1993-07-01

The first results of an extensive study of the structure and dynamics of underdense regions in gravitational instability scenarios are presented. Instead of adopting spherically symmetric voids with some idealized initial density and velocity profile, underdense regions of a given size and depth, embedded in an initial density fluctuation field, are generated. In order to accomplish this in a consistent way, these initial conditions are set up by means of Bertschinger's constrained random field code. The generated particle samples of 64^3^ particles in a box of side 100 Mpc are followed into the non-linear regime by Bertschinger's PM N- body code. In this way we address the dependence of the structure and kinematics of the void both on the initial depth of the void and on the fluctuation field in which it is embedded. In particular, this study provides some understanding of how far fluctuations on small scales modify the dynamics of the large-scale void, and especially of how far the properties of small structures inside the void are affected by the global properties of the void. One of the conspicuous features of the initial density fields inside protovoids appears to be the existence of a `void hierarchy', with small voids embedded in larger voids. The survival of this hierarchy during the riot evolution of the void depends critically on the initial depth as well as on the clustering scenario involved. As well as presenting a qualitative discussion of the structure of underdense regions in initial density fields in different scenarios, and the results of simulations of the ensuing non-linear evolution, we concentrate in particular on a comparison of the global density and velocity fields in voids with predictions from linear theory as well as from the spherical outflow model. The relation between the initial linear depth, the resulting non-linear depth and the excess expansion velocities in voids is addressed. In addition, we find that, while near its centre a void becomes more and more spherical, the shape of its boundary is influenced to a large extent by the structures surrounding the void and therefore is generally more irregular. In this first study we concentrate on single voids in Einstein-de Sitter universes. The underdense regions considered are linear 1 σ_0_, 2 σ_0_ and 3 σ_0_ dips in fields that are Gaussian-smoothed on a scale of R_G_ = 10 h^-1^ Mpc, approximately half the size of the Bootes void. These regions are studied in terms of the Cold Dark Matter and Hot Dark Matter scenarios as well as in terms of the scale-free scenarios P(k) is proportional to k^0^, k^-1^ and k^-2^. The Hubble constant is taken to be H_0_ = 100 h km s^-1^ Mpc^-1^.

Increases in Perspective Embedding Increase Reading Time Even with Typical Text Presentation: Implications for the Reading of Literature

PubMed Central

Whalen, D. H.; Zunshine, Lisa; Holquist, Michael

2015-01-01

Reading fiction is a major component of intellectual life, yet it has proven difficult to study experimentally. One aspect of literature that has recently come to light is perspective embedding (“she thought I left” embedding her perspective on “I left”), which seems to be a defining feature of fiction. Previous work (Whalen et al., 2012) has shown that increasing levels of embedment affects the time that it takes readers to read and understand short vignettes in a moving window paradigm. With increasing levels of embedment from 1 to 5, reading times in a moving window paradigm rose almost linearly. However, level 0 was as slow as 3–4. Accuracy on probe questions was relatively constant until dropping at the fifth level. Here, we assessed this effect in a more ecologically valid (“typical”) reading paradigm, in which the entire vignette was visible at once, either for as long as desired (Experiment 1) or a fixed time (Experiment 2). In Experiment 1, reading times followed a pattern similar to that of the previous experiment, with some differences in absolute speed. Accuracy matched previous results: fairly consistent accuracy until a decline at level 5, indicating that both presentation methods allowed understanding. In Experiment 2, accuracy was somewhat reduced, perhaps because participants were less successful at allocating their attention than they were during the earlier experiment; however, the pattern was the same. It seems that literature does not, on average, use easiest reading level but rather uses a middle ground that challenges the reader, but not too much. PMID:26635684

Determinism in synthesized chaotic waveforms.

PubMed

Corron, Ned J; Blakely, Jonathan N; Hayes, Scott T; Pethel, Shawn D

2008-03-01

The output of a linear filter driven by a randomly polarized square wave, when viewed backward in time, is shown to exhibit determinism at all times when embedded in a three-dimensional state space. Combined with previous results establishing exponential divergence equivalent to a positive Lyapunov exponent, this result rigorously shows that such reverse-time synthesized waveforms appear equally to have been produced by a deterministic chaotic system.

Chromatographic Behaviour Predicts the Ability of Potential Nootropics to Permeate the Blood-Brain Barrier

PubMed Central

Farsa, Oldřich

2013-01-01

The log BB parameter is the logarithm of the ratio of a compound’s equilibrium concentrations in the brain tissue versus the blood plasma. This parameter is a useful descriptor in assessing the ability of a compound to permeate the blood-brain barrier. The aim of this study was to develop a Hansch-type linear regression QSAR model that correlates the parameter log BB and the retention time of drugs and other organic compounds on a reversed-phase HPLC containing an embedded amide moiety. The retention time was expressed by the capacity factor log k′. The second aim was to estimate the brain’s absorption of 2-(azacycloalkyl)acetamidophenoxyacetic acids, which are analogues of piracetam, nefiracetam, and meclofenoxate. Notably, these acids may be novel nootropics. Two simple regression models that relate log BB and log k′ were developed from an assay performed using a reversed-phase HPLC that contained an embedded amide moiety. Both the quadratic and linear models yielded statistical parameters comparable to previously published models of log BB dependence on various structural characteristics. The models predict that four members of the substituted phenoxyacetic acid series have a strong chance of permeating the barrier and being absorbed in the brain. The results of this study show that a reversed-phase HPLC system containing an embedded amide moiety is a functional in vitro surrogate of the blood-brain barrier. These results suggest that racetam-type nootropic drugs containing a carboxylic moiety could be more poorly absorbed than analogues devoid of the carboxyl group, especially if the compounds penetrate the barrier by a simple diffusion mechanism. PMID:23641330

Chen-Nester-Tung quasi-local energy and Wang-Yau quasi-local mass

NASA Astrophysics Data System (ADS)

Liu, Jian-Liang; Yu, Chengjie

2017-10-01

In this paper, we show that the Chen-Nester-Tung (CNT) quasi-local energy with 4D isometric matching references is closely related to the Wang-Yau (WY) quasi-local energy. As a particular example, we compute the second variation of the CNT quasi-local energy for axially symmetric Kerr-like spacetimes with axially symmetric embeddings at the obvious critical point (0 , 0) and find that it is a saddle critical point in most of the cases. Also, as a byproduct, we generalize a previous result about the coincidence of the CNT quasi-local energy and Brown-York mass for axially symmetric Kerr-like spacetimes by Tam and the first author Liu and Tam (2016) to general spacetimes.

Watermarking scheme for authentication of compressed image

NASA Astrophysics Data System (ADS)

Hsieh, Tsung-Han; Li, Chang-Tsun; Wang, Shuo

2003-11-01

As images are commonly transmitted or stored in compressed form such as JPEG, to extend the applicability of our previous work, a new scheme for embedding watermark in compressed domain without resorting to cryptography is proposed. In this work, a target image is first DCT transformed and quantised. Then, all the coefficients are implicitly watermarked in order to minimize the risk of being attacked on the unwatermarked coefficients. The watermarking is done through registering/blending the zero-valued coefficients with a binary sequence to create the watermark and involving the unembedded coefficients during the process of embedding the selected coefficients. The second-order neighbors and the block itself are considered in the process of the watermark embedding in order to thwart different attacks such as cover-up, vector quantisation, and transplantation. The experiments demonstrate the capability of the proposed scheme in thwarting local tampering, geometric transformation such as cropping, and common signal operations such as lowpass filtering.

Surgical removal of coronal fragment of tooth embedded in lower lip and esthetic management of fractured crown segment.

PubMed

Avinash, Alok; Dubey, Alok; Singh, Rajeev Kumar; Prasad, Swati

2014-01-01

Dental fractures of the permanent maxillary anterior teeth are relatively frequent accidents during childhood. The Efficient diagnosis and treatment of dental injury are important elements in clinical dentistry. This article describes a case of trauma in permanent right central maxillary incisors with tooth fragments embedded in the lower lip. Thorough clinical examination followed by soft tissue radiographs confirmed the presence of a fractured incisal fragment, which was surgically retrieved under local anesthesia. Direct composite restoration was placed. After finishing and polishing, an esthetic and natural-looking restoration was achieved; this completely satisfied the functional and esthetic expectation of the patient and dental team. How to cite this article: Avinash A, Dubey A, Singh RK, Prasad S. Surgical Removal of Coronal Fragment of Tooth Embedded in Lower Lip and Esthetic Management of Fractured Crown Segment. Int J Clin Pediatr Dent 2014;7(1):65-68.

Graphite nanoplatelet enabled embeddable fiber sensor for in situ curing monitoring and structural health monitoring of polymeric composites.

PubMed

Luo, Sida; Liu, Tao

2014-06-25

A graphite nanoplatelet (GNP) thin film enabled 1D fiber sensor (GNP-FibSen) was fabricated by a continuous roll-to-roll spray coating process, characterized by scanning electron microscopy and Raman spectroscopy and evaluated by coupled electrical-mechanical tensile testing. The neat GNP-FibSen sensor shows very high gauge sensitivity with a gauge factor of ∼17. By embedding the sensor in fiberglass prepreg laminate parts, the dual functionalities of the GNP-FibSen sensor were demonstrated. In the manufacturing process, the resistance change of the embedded sensor provides valuable local resin curing information. After the manufacturing process, the same sensor is able to map the strain/stress states and detect the failure of the host composite. The superior durability of the embedded GNP-FibSen sensor has been demonstrated through 10,000 cycles of coupled electromechanical tests.

Contrast effects on speed perception for linear and radial motion.

PubMed

Champion, Rebecca A; Warren, Paul A

2017-11-01

Speed perception is vital for safe activity in the environment. However, considerable evidence suggests that perceived speed changes as a function of stimulus contrast, with some investigators suggesting that this might have meaningful real-world consequences (e.g. driving in fog). In the present study we investigate whether the neural effects of contrast on speed perception occur at the level of local or global motion processing. To do this we examine both speed discrimination thresholds and contrast-dependent speed perception for two global motion configurations that have matched local spatio-temporal structure. Specifically we compare linear and radial configurations, the latter of which arises very commonly due to self-movement. In experiment 1 the stimuli comprised circular grating patches. In experiment 2, to match stimuli even more closely, motion was presented in multiple local Gabor patches equidistant from central fixation. Each patch contained identical linear motion but the global configuration was either consistent with linear or radial motion. In both experiments 1 and 2, discrimination thresholds and contrast-induced speed biases were similar in linear and radial conditions. These results suggest that contrast-based speed effects occur only at the level of local motion processing, irrespective of global structure. This result is interpreted in the context of previous models of speed perception and evidence suggesting differences in perceived speed of locally matched linear and radial stimuli. Copyright © 2017 Elsevier Ltd. All rights reserved.

System for generating a beam of acoustic energy from a borehole, and applications thereof

DOEpatents

Vu, Cung Khac; Sinha, Dipen N.; Pantea, Cristian; Nihei, Kurt T.; Schmitt, Denis P.; Skelt, Christopher

2012-09-04

In some aspects of the invention, a device, positioned within a well bore, configured to generate and direct an acoustic beam into a rock formation around a borehole is disclosed. The device comprises a source configured to generate a first signal at a first frequency and a second signal at a second frequency; a transducer configured to receive the generated first and the second signals and produce acoustic waves at the first frequency and the second frequency; and a non-linear material, coupled to the transducer, configured to generate a collimated beam with a frequency equal to the difference between the first frequency and the second frequency by a non-linear mixing process, wherein the non-linear material includes one or more of a mixture of liquids, a solid, a granular material, embedded microspheres, or an emulsion.

System for generating a beam of acoustic energy from a borehole, and applications thereof

DOEpatents

Vu, Cung Khac [Houston, TX; Sinha, Dipen N [Los Alamos, NM; Pantea, Cristian [Los Alamos, NM; Nihei, Kurt T [Oakland, CA; Schmitt, Denis P [Katy, TX; Skelt, Christopher [Houston, TX

2012-07-31

In some aspects of the invention, a device, positioned within a well bore, configured to generate and direct an acoustic beam into a rock formation around a borehole is disclosed. The device comprises a source configured to generate a first signal at a first frequency and a second signal at a second frequency; a transducer configured to receive the generated first and the second signals and produce acoustic waves at the first frequency and the second frequency; and a non-linear material, coupled to the transducer, configured to generate a collimated beam with a frequency equal to the difference between the first frequency and the second frequency by a non-linear mixing process, wherein the non-linear material includes one or more of a mixture of liquids, a solid, a granular material, embedded microspheres, or an emulsion.

Secular evolution of eccentricity in protoplanetary discs with gap-opening planets

NASA Astrophysics Data System (ADS)

Teyssandier, Jean; Ogilvie, Gordon I.

2017-06-01

We explore the evolution of the eccentricity of an accretion disc perturbed by an embedded planet whose mass is sufficient to open a large gap in the disc. Various methods for representing the orbit-averaged motion of an eccentric disc are discussed. We characterize the linear instability that leads to the growth of eccentricity by means of hydrodynamical simulations. We numerically recover the known result that eccentricity growth in the disc is possible when the planet-to-star mass ratio exceeds 3 × 10-3. For mass ratios larger than this threshold, the precession rates and growth rates derived from simulations, as well as the shape of the eccentric mode, compare well with the predictions of a linear theory of eccentric discs. We study mechanisms by which the eccentricity growth eventually saturates into a non-linear regime.

Prediction of breast cancer risk using a machine learning approach embedded with a locality preserving projection algorithm.

PubMed

Heidari, Morteza; Khuzani, Abolfazl Zargari; Hollingsworth, Alan B; Danala, Gopichandh; Mirniaharikandehei, Seyedehnafiseh; Qiu, Yuchen; Liu, Hong; Zheng, Bin

2018-01-30

In order to automatically identify a set of effective mammographic image features and build an optimal breast cancer risk stratification model, this study aims to investigate advantages of applying a machine learning approach embedded with a locally preserving projection (LPP) based feature combination and regeneration algorithm to predict short-term breast cancer risk. A dataset involving negative mammograms acquired from 500 women was assembled. This dataset was divided into two age-matched classes of 250 high risk cases in which cancer was detected in the next subsequent mammography screening and 250 low risk cases, which remained negative. First, a computer-aided image processing scheme was applied to segment fibro-glandular tissue depicted on mammograms and initially compute 44 features related to the bilateral asymmetry of mammographic tissue density distribution between left and right breasts. Next, a multi-feature fusion based machine learning classifier was built to predict the risk of cancer detection in the next mammography screening. A leave-one-case-out (LOCO) cross-validation method was applied to train and test the machine learning classifier embedded with a LLP algorithm, which generated a new operational vector with 4 features using a maximal variance approach in each LOCO process. Results showed a 9.7% increase in risk prediction accuracy when using this LPP-embedded machine learning approach. An increased trend of adjusted odds ratios was also detected in which odds ratios increased from 1.0 to 11.2. This study demonstrated that applying the LPP algorithm effectively reduced feature dimensionality, and yielded higher and potentially more robust performance in predicting short-term breast cancer risk.

Prediction of breast cancer risk using a machine learning approach embedded with a locality preserving projection algorithm

NASA Astrophysics Data System (ADS)

Heidari, Morteza; Zargari Khuzani, Abolfazl; Hollingsworth, Alan B.; Danala, Gopichandh; Mirniaharikandehei, Seyedehnafiseh; Qiu, Yuchen; Liu, Hong; Zheng, Bin

2018-02-01

In order to automatically identify a set of effective mammographic image features and build an optimal breast cancer risk stratification model, this study aims to investigate advantages of applying a machine learning approach embedded with a locally preserving projection (LPP) based feature combination and regeneration algorithm to predict short-term breast cancer risk. A dataset involving negative mammograms acquired from 500 women was assembled. This dataset was divided into two age-matched classes of 250 high risk cases in which cancer was detected in the next subsequent mammography screening and 250 low risk cases, which remained negative. First, a computer-aided image processing scheme was applied to segment fibro-glandular tissue depicted on mammograms and initially compute 44 features related to the bilateral asymmetry of mammographic tissue density distribution between left and right breasts. Next, a multi-feature fusion based machine learning classifier was built to predict the risk of cancer detection in the next mammography screening. A leave-one-case-out (LOCO) cross-validation method was applied to train and test the machine learning classifier embedded with a LLP algorithm, which generated a new operational vector with 4 features using a maximal variance approach in each LOCO process. Results showed a 9.7% increase in risk prediction accuracy when using this LPP-embedded machine learning approach. An increased trend of adjusted odds ratios was also detected in which odds ratios increased from 1.0 to 11.2. This study demonstrated that applying the LPP algorithm effectively reduced feature dimensionality, and yielded higher and potentially more robust performance in predicting short-term breast cancer risk.

Individuals with 22q11.2 Deletion Syndrome Are Impaired at Explicit, but Not Implicit, Discrimination of Local Forms Embedded in Global Structures

ERIC Educational Resources Information Center

Giersch, Anne; Glaser, Bronwyn; Pasca, Catherine; Chabloz, Mélanie; Debbané, Martin; Eliez, Stephan

2014-01-01

Individuals with 22q11.2 deletion syndrome (22q11.2DS) are impaired at exploring visual information in space; however, not much is known about visual form discrimination in the syndrome. Thirty-five individuals with 22q11.2DS and 41 controls completed a form discrimination task with global forms made up of local elements. Affected individuals…

Local Linear Regression for Data with AR Errors.

PubMed

Li, Runze; Li, Yan

2009-07-01

In many statistical applications, data are collected over time, and they are likely correlated. In this paper, we investigate how to incorporate the correlation information into the local linear regression. Under the assumption that the error process is an auto-regressive process, a new estimation procedure is proposed for the nonparametric regression by using local linear regression method and the profile least squares techniques. We further propose the SCAD penalized profile least squares method to determine the order of auto-regressive process. Extensive Monte Carlo simulation studies are conducted to examine the finite sample performance of the proposed procedure, and to compare the performance of the proposed procedures with the existing one. From our empirical studies, the newly proposed procedures can dramatically improve the accuracy of naive local linear regression with working-independent error structure. We illustrate the proposed methodology by an analysis of real data set.

Experimental and numeric stress analysis of titanium and zirconia one-piece dental implants.

PubMed

Mobilio, Nicola; Stefanoni, Filippo; Contiero, Paolo; Mollica, Francesco; Catapano, Santo

2013-01-01

To compare the stress in bone around zirconia and titanium implants under loading. A one-piece zirconia implant and a replica of the same implant made of commercially pure titanium were embedded in two self-curing acrylic resin blocks. To measure strain, a strain gauge was applied on the surface of the two samples. Loads of 50, 100, and 150 N, with orientations of 30, 45, and 60 degrees with respect to the implant axis were applied on the implant. Strain under all loading conditions on both samples was measured. Three-dimensional virtual replicas of both the implants were reproduced using the finite element method and inserted into a virtual acrylic resin block. All the materials were considered isotropic, linear, and elastic. The same geometry and loading conditions of the experimental setup were used to realize two new models, with the implants embedded within a virtual bone block. Very close values of strain in the two implants embedded in acrylic resin were obtained both experimentally and numerically. The stress states generated by the implants embedded in virtual bone were also very similar, even if the two implants moved differently. Moreover, the stress levels were higher on cortical bone than on trabecular bone. The stress levels in bone, generated by the two implants, appeared to be very similar. From a mechanical point of view, zirconia is a feasible substitute for titanium.

A systematic approach to embedded biomedical decision making.

PubMed

Song, Zhe; Ji, Zhongkai; Ma, Jian-Guo; Sputh, Bernhard; Acharya, U Rajendra; Faust, Oliver

2012-11-01

An embedded decision making is a key feature for many biomedical systems. In most cases human life directly depends on correct decisions made by these systems, therefore they have to work reliably. This paper describes how we applied systems engineering principles to design a high performance embedded classification system in a systematic and well structured way. We introduce the structured design approach by discussing requirements capturing, specifications refinement, implementation and testing. Thereby, we follow systems engineering principles and execute each of these processes as formal as possible. The requirements, which motivate the system design, describe an automated decision making system for diagnostic support. These requirements are refined into the implementation of a support vector machine (SVM) algorithm which enables us to integrate automated decision making in embedded systems. With a formal model we establish functionality, stability and reliability of the system. Furthermore, we investigated different parallel processing configurations of this computationally complex algorithm. We found that, by adding SVM processes, an almost linear speedup is possible. Once we established these system properties, we translated the formal model into an implementation. The resulting implementation was tested using XMOS processors with both normal and failure cases, to build up trust in the implementation. Finally, we demonstrated that our parallel implementation achieves the speedup, predicted by the formal model. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Distributed digital signal processors for multi-body flexible structures

NASA Technical Reports Server (NTRS)

Lee, Gordon K. F.

1992-01-01

Multi-body flexible structures, such as those currently under investigation in spacecraft design, are large scale (high-order) dimensional systems. Controlling and filtering such structures is a computationally complex problem. This is particularly important when many sensors and actuators are located along the structure and need to be processed in real time. This report summarizes research activity focused on solving the signal processing (that is, information processing) issues of multi-body structures. A distributed architecture is developed in which single loop processors are employed for local filtering and control. By implementing such a philosophy with an embedded controller configuration, a supervising controller may be used to process global data and make global decisions as the local devices are processing local information. A hardware testbed, a position controller system for a servo motor, is employed to illustrate the capabilities of the embedded controller structure. Several filtering and control structures which can be modeled as rational functions can be implemented on the system developed in this research effort. Thus the results of the study provide a support tool for many Control/Structure Interaction (CSI) NASA testbeds such as the Evolutionary model and the nine-bay truss structure.

Object matching using a locally affine invariant and linear programming techniques.

PubMed

Li, Hongsheng; Huang, Xiaolei; He, Lei

2013-02-01

In this paper, we introduce a new matching method based on a novel locally affine-invariant geometric constraint and linear programming techniques. To model and solve the matching problem in a linear programming formulation, all geometric constraints should be able to be exactly or approximately reformulated into a linear form. This is a major difficulty for this kind of matching algorithm. We propose a novel locally affine-invariant constraint which can be exactly linearized and requires a lot fewer auxiliary variables than other linear programming-based methods do. The key idea behind it is that each point in the template point set can be exactly represented by an affine combination of its neighboring points, whose weights can be solved easily by least squares. Errors of reconstructing each matched point using such weights are used to penalize the disagreement of geometric relationships between the template points and the matched points. The resulting overall objective function can be solved efficiently by linear programming techniques. Our experimental results on both rigid and nonrigid object matching show the effectiveness of the proposed algorithm.

Comparison of multi-fluid moment models with particle-in-cell simulations of collisionless magnetic reconnection

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

Wang, Liang, E-mail: liang.wang@unh.edu; Germaschewski, K.; Hakim, Ammar H.

2015-01-15

We introduce an extensible multi-fluid moment model in the context of collisionless magnetic reconnection. This model evolves full Maxwell equations and simultaneously moments of the Vlasov-Maxwell equation for each species in the plasma. Effects like electron inertia and pressure gradient are self-consistently embedded in the resulting multi-fluid moment equations, without the need to explicitly solving a generalized Ohm's law. Two limits of the multi-fluid moment model are discussed, namely, the five-moment limit that evolves a scalar pressures for each species and the ten-moment limit that evolves the full anisotropic, non-gyrotropic pressure tensor for each species. We first demonstrate analytically andmore » numerically that the five-moment model reduces to the widely used Hall magnetohydrodynamics (Hall MHD) model under the assumptions of vanishing electron inertia, infinite speed of light, and quasi-neutrality. Then, we compare ten-moment and fully kinetic particle-in-cell (PIC) simulations of a large scale Harris sheet reconnection problem, where the ten-moment equations are closed with a local linear collisionless approximation for the heat flux. The ten-moment simulation gives reasonable agreement with the PIC results regarding the structures and magnitudes of the electron flows, the polarities and magnitudes of elements of the electron pressure tensor, and the decomposition of the generalized Ohm's law. Possible ways to improve the simple local closure towards a nonlocal fully three-dimensional closure are also discussed.« less

A Non-invasive Real-time Localization System for Enhanced Efficacy in Nasogastric Intubation.

PubMed

Sun, Zhenglong; Foong, Shaohui; Maréchal, Luc; Tan, U-Xuan; Teo, Tee Hui; Shabbir, Asim

2015-12-01

Nasogastric (NG) intubation is one of the most commonly performed clinical procedures. Real-time localization and tracking of the NG tube passage at the larynx region into the esophagus is crucial for safety, but is lacking in current practice. In this paper, we present the design, analysis and evaluation of a non-invasive real-time localization system using passive magnetic tracking techniques to improve efficacy of the clinical NG intubation process. By embedding a small permanent magnet at the insertion tip of the NG tube, a wearable system containing embedded sensors around the neck can determine the absolute position of the NG tube inside the body in real-time to assist in insertion. In order to validate the feasibility of the proposed system in detecting erroneous tube placement, typical reference intubation trajectories are first analyzed using anatomically correct models and localization accuracy of the system are evaluated using a precise robotic platform. It is found that the root-mean-squared tracking accuracy is within 5.3 mm for both the esophagus and trachea intubation pathways. Experiments were also designed and performed to demonstrate that the system is capable of tracking the NG tube accurately in biological environments even in presence of stationary ferromagnetic objects (such as clinical instruments). With minimal physical modification to the NG tube and clinical process, this system allows accurate and efficient localization and confirmation of correct NG tube placement without supplemental radiographic methods which is considered the current clinical standard.

The whole number axis integer linear transformation reversible information hiding algorithm on wavelet domain

NASA Astrophysics Data System (ADS)

Jiang, Zhuo; Xie, Chengjun

2013-12-01

This paper improved the algorithm of reversible integer linear transform on finite interval [0,255], which can realize reversible integer linear transform in whole number axis shielding data LSB (least significant bit). Firstly, this method use integer wavelet transformation based on lifting scheme to transform the original image, and select the transformed high frequency areas as information hiding area, meanwhile transform the high frequency coefficients blocks in integer linear way and embed the secret information in LSB of each coefficient, then information hiding by embedding the opposite steps. To extract data bits and recover the host image, a similar reverse procedure can be conducted, and the original host image can be lossless recovered. The simulation experimental results show that this method has good secrecy and concealment, after conducted the CDF (m, n) and DD (m, n) series of wavelet transformed. This method can be applied to information security domain, such as medicine, law and military.

Variational and robust density fitting of four-center two-electron integrals in local metrics

NASA Astrophysics Data System (ADS)

Reine, Simen; Tellgren, Erik; Krapp, Andreas; Kjærgaard, Thomas; Helgaker, Trygve; Jansik, Branislav; Høst, Stinne; Salek, Paweł

2008-09-01

Density fitting is an important method for speeding up quantum-chemical calculations. Linear-scaling developments in Hartree-Fock and density-functional theories have highlighted the need for linear-scaling density-fitting schemes. In this paper, we present a robust variational density-fitting scheme that allows for solving the fitting equations in local metrics instead of the traditional Coulomb metric, as required for linear scaling. Results of fitting four-center two-electron integrals in the overlap and the attenuated Gaussian damped Coulomb metric are presented, and we conclude that density fitting can be performed in local metrics at little loss of chemical accuracy. We further propose to use this theory in linear-scaling density-fitting developments.

Variational and robust density fitting of four-center two-electron integrals in local metrics.

PubMed

Reine, Simen; Tellgren, Erik; Krapp, Andreas; Kjaergaard, Thomas; Helgaker, Trygve; Jansik, Branislav; Host, Stinne; Salek, Paweł

2008-09-14

Density fitting is an important method for speeding up quantum-chemical calculations. Linear-scaling developments in Hartree-Fock and density-functional theories have highlighted the need for linear-scaling density-fitting schemes. In this paper, we present a robust variational density-fitting scheme that allows for solving the fitting equations in local metrics instead of the traditional Coulomb metric, as required for linear scaling. Results of fitting four-center two-electron integrals in the overlap and the attenuated Gaussian damped Coulomb metric are presented, and we conclude that density fitting can be performed in local metrics at little loss of chemical accuracy. We further propose to use this theory in linear-scaling density-fitting developments.

Micromechanics of brain white matter tissue: A fiber-reinforced hyperelastic model using embedded element technique.

PubMed

Yousefsani, Seyed Abdolmajid; Shamloo, Amir; Farahmand, Farzam

2018-04-01

A transverse-plane hyperelastic micromechanical model of brain white matter tissue was developed using the embedded element technique (EET). The model consisted of a histology-informed probabilistic distribution of axonal fibers embedded within an extracellular matrix, both described using the generalized Ogden hyperelastic material model. A correcting method, based on the strain energy density function, was formulated to resolve the stiffness redundancy problem of the EET in large deformation regime. The model was then used to predict the homogenized tissue behavior and the associated localized responses of the axonal fibers under quasi-static, transverse, large deformations. Results indicated that with a sufficiently large representative volume element (RVE) and fine mesh, the statistically randomized microstructure implemented in the RVE exhibits directional independency in transverse plane, and the model predictions for the overall and local tissue responses, characterized by the normalized strain energy density and Cauchy and von Mises stresses, are independent from the modeling parameters. Comparison of the responses of the probabilistic model with that of a simple uniform RVE revealed that only the first one is capable of representing the localized behavior of the tissue constituents. The validity test of the model predictions for the corona radiata against experimental data from the literature indicated a very close agreement. In comparison with the conventional direct meshing method, the model provided almost the same results after correcting the stiffness redundancy, however, with much less computational cost and facilitated geometrical modeling, meshing, and boundary conditions imposing. It was concluded that the EET can be used effectively for detailed probabilistic micromechanical modeling of the white matter in order to provide more accurate predictions for the axonal responses, which are of great importance when simulating the brain trauma or tumor growth. Copyright © 2018 Elsevier Ltd. All rights reserved.

Chaos as an intermittently forced linear system.

PubMed

Brunton, Steven L; Brunton, Bingni W; Proctor, Joshua L; Kaiser, Eurika; Kutz, J Nathan

2017-05-30

Understanding the interplay of order and disorder in chaos is a central challenge in modern quantitative science. Approximate linear representations of nonlinear dynamics have long been sought, driving considerable interest in Koopman theory. We present a universal, data-driven decomposition of chaos as an intermittently forced linear system. This work combines delay embedding and Koopman theory to decompose chaotic dynamics into a linear model in the leading delay coordinates with forcing by low-energy delay coordinates; this is called the Hankel alternative view of Koopman (HAVOK) analysis. This analysis is applied to the Lorenz system and real-world examples including Earth's magnetic field reversal and measles outbreaks. In each case, forcing statistics are non-Gaussian, with long tails corresponding to rare intermittent forcing that precedes switching and bursting phenomena. The forcing activity demarcates coherent phase space regions where the dynamics are approximately linear from those that are strongly nonlinear.The huge amount of data generated in fields like neuroscience or finance calls for effective strategies that mine data to reveal underlying dynamics. Here Brunton et al.develop a data-driven technique to analyze chaotic systems and predict their dynamics in terms of a forced linear model.

Adjoint Sensitivity Computations for an Embedded-Boundary Cartesian Mesh Method and CAD Geometry

NASA Technical Reports Server (NTRS)

Nemec, Marian; Aftosmis,Michael J.

2006-01-01

Cartesian-mesh methods are perhaps the most promising approach for addressing the issues of flow solution automation for aerodynamic design problems. In these methods, the discretization of the wetted surface is decoupled from that of the volume mesh. This not only enables fast and robust mesh generation for geometry of arbitrary complexity, but also facilitates access to geometry modeling and manipulation using parametric Computer-Aided Design (CAD) tools. Our goal is to combine the automation capabilities of Cartesian methods with an eficient computation of design sensitivities. We address this issue using the adjoint method, where the computational cost of the design sensitivities, or objective function gradients, is esseutially indepeudent of the number of design variables. In previous work, we presented an accurate and efficient algorithm for the solution of the adjoint Euler equations discretized on Cartesian meshes with embedded, cut-cell boundaries. Novel aspects of the algorithm included the computation of surface shape sensitivities for triangulations based on parametric-CAD models and the linearization of the coupling between the surface triangulation and the cut-cells. The objective of the present work is to extend our adjoint formulation to problems involving general shape changes. Central to this development is the computation of volume-mesh sensitivities to obtain a reliable approximation of the objective finction gradient. Motivated by the success of mesh-perturbation schemes commonly used in body-fitted unstructured formulations, we propose an approach based on a local linearization of a mesh-perturbation scheme similar to the spring analogy. This approach circumvents most of the difficulties that arise due to non-smooth changes in the cut-cell layer as the boundary shape evolves and provides a consistent approximation tot he exact gradient of the discretized abjective function. A detailed gradient accurace study is presented to verify our approach. Thereafter, we focus on a shape optimization problem for an Apollo-like reentry capsule. The optimization seeks to enhance the lift-to-drag ratio of the capsule by modifyjing the shape of its heat-shield in conjunction with a center-of-gravity (c.g.) offset. This multipoint and multi-objective optimization problem is used to demonstrate the overall effectiveness of the Cartesian adjoint method for addressing the issues of complex aerodynamic design. This abstract presents only a brief outline of the numerical method and results; full details will be given in the final paper.

The role of molecular conformation and polarizable embedding for one- and two-photon absorption of disperse orange 3 in solution.

PubMed

Silva, Daniel L; Murugan, N Arul; Kongsted, Jacob; Rinkevicius, Zilvinas; Canuto, Sylvio; Ågren, Hans

2012-07-19

Solvent effects on the one- and two-photon absorption (1PA and 2PA) of disperse orange 3 (DO3) in dimethyl sulfoxide (DMSO) are studied using a discrete polarizable embedding (PE) response theory. The scheme comprises a quantum region containing the chromophore and an atomically granulated classical region for the solvent accounting for full interactions within and between the two regions. Either classical molecular dynamics (MD) or hybrid Car-Parrinello (CP) quantum/classical (QM/MM) molecular dynamics simulations are employed to describe the solvation of DO3 in DMSO, allowing for an analysis of the effect of the intermolecular short-range repulsion, long-range attraction, and electrostatic interactions on the conformational changes of the chromophore and also the effect of the solute-solvent polarization. PE linear response calculations are performed to verify the character, solvatochromic shift, and overlap of the two lowest energy transitions responsible for the linear absorption spectrum of DO3 in DMSO in the visible spectral region. Results of the PE linear and quadratic response calculations, performed using uncorrelated solute-solvent configurations sampled from either the classical or hybrid CP QM/MM MD simulations, are used to estimate the width of the line shape function of the two electronic lowest energy excited states, which allow a prediction of the 2PA cross-sections without the use of empirical parameters. Appropriate exchange-correlation functionals have been employed in order to describe the charge-transfer process following the electronic transitions of the chromophore in solution.

Application-oriented programming model for sensor networks embedded in the human body.

PubMed

Barbosa, Talles M G de A; Sene, Iwens G; da Rocha, Adson F; Nascimento, Fransisco A de O; Carvalho, Hervaldo S; Camapum, Juliana F

2006-01-01

This work presents a new programming model for sensor networks embedded in the human body which is based on the concept of multi-programming application-oriented software. This model was conceived with a top-down approach of four layers and its main goal is to allow the healthcare professionals to program and to reconfigure the network locally or by the Internet. In order to evaluate this hypothesis, a benchmarking was executed in order to allow the assessment of the mean time spent in the programming of a multi-functional sensor node used for the measurement and transmission of the electrocardiogram.

Curvature and temperature of complex networks.

PubMed

Krioukov, Dmitri; Papadopoulos, Fragkiskos; Vahdat, Amin; Boguñá, Marián

2009-09-01

We show that heterogeneous degree distributions in observed scale-free topologies of complex networks can emerge as a consequence of the exponential expansion of hidden hyperbolic space. Fermi-Dirac statistics provides a physical interpretation of hyperbolic distances as energies of links. The hidden space curvature affects the heterogeneity of the degree distribution, while clustering is a function of temperature. We embed the internet into the hyperbolic plane and find a remarkable congruency between the embedding and our hyperbolic model. Besides proving our model realistic, this embedding may be used for routing with only local information, which holds significant promise for improving the performance of internet routing.

Enhanced Circular Dichroism of Gold Bilayered Slit Arrays Embedded with Rectangular Holes.

PubMed

Zhang, Hao; Wang, Yongkai; Luo, Lina; Wang, Haiqing; Zhang, Zhongyue

2017-01-01

Gold bilayered slit arrays with rectangular holes embedded into the metal surface are designed to enhance the circular dichroism (CD) effect of gold bilayered slit arrays. The rectangular holes in these arrays block electric currents and generate localized surface plasmons around these holes, thereby strengthening the CD effect. The CD enhancement factor depends strongly on the rotational angle and the structural parameters of the rectangular holes; this factor can be enhanced further by drilling two additional rectangular holes into the metal surfaces of the arrays. These results help facilitate the design of chiral structures to produce a strong CD effect and large electric fields.

Propagation of sound waves through a linear shear layer: A closed form solution

NASA Technical Reports Server (NTRS)

Scott, J. N.

1978-01-01

Closed form solutions are presented for sound propagation from a line source in or near a shear layer. The analysis was exact for all frequencies and was developed assuming a linear velocity profile in the shear layer. This assumption allowed the solution to be expressed in terms of parabolic cyclinder functions. The solution is presented for a line monopole source first embedded in the uniform flow and then in the shear layer. Solutions are also discussed for certain types of dipole and quadrupole sources. Asymptotic expansions of the exact solutions for small and large values of Strouhal number gave expressions which correspond to solutions previously obtained for these limiting cases.