A sparse grid based method for generative dimensionality reduction of high-dimensional data

Science.gov (United States)

Bohn, Bastian; Garcke, Jochen; Griebel, Michael

2016-03-01

Generative dimensionality reduction methods play an important role in machine learning applications because they construct an explicit mapping from a low-dimensional space to the high-dimensional data space. We discuss a general framework to describe generative dimensionality reduction methods, where the main focus lies on a regularized principal manifold learning variant. Since most generative dimensionality reduction algorithms exploit the representer theorem for reproducing kernel Hilbert spaces, their computational costs grow at least quadratically in the number n of data. Instead, we introduce a grid-based discretization approach which automatically scales just linearly in n. To circumvent the curse of dimensionality of full tensor product grids, we use the concept of sparse grids. Furthermore, in real-world applications, some embedding directions are usually more important than others and it is reasonable to refine the underlying discretization space only in these directions. To this end, we employ a dimension-adaptive algorithm which is based on the ANOVA (analysis of variance) decomposition of a function. In particular, the reconstruction error is used to measure the quality of an embedding. As an application, the study of large simulation data from an engineering application in the automotive industry (car crash simulation) is performed.

Fermion masses from dimensional reduction

International Nuclear Information System (INIS)

Kapetanakis, D.; Zoupanos, G.

1990-01-01

We consider the fermion masses in gauge theories obtained from ten dimensions through dimensional reduction on coset spaces. We calculate the general fermion mass matrix and we apply the mass formula in illustrative examples. (orig.)

Fermion masses from dimensional reduction

Energy Technology Data Exchange (ETDEWEB)

Kapetanakis, D. (National Research Centre for the Physical Sciences Democritos, Athens (Greece)); Zoupanos, G. (European Organization for Nuclear Research, Geneva (Switzerland))

1990-10-11

We consider the fermion masses in gauge theories obtained from ten dimensions through dimensional reduction on coset spaces. We calculate the general fermion mass matrix and we apply the mass formula in illustrative examples. (orig.).

Fukunaga-Koontz transform based dimensionality reduction for hyperspectral imagery

Science.gov (United States)

Ochilov, S.; Alam, M. S.; Bal, A.

2006-05-01

Fukunaga-Koontz Transform based technique offers some attractive properties for desired class oriented dimensionality reduction in hyperspectral imagery. In FKT, feature selection is performed by transforming into a new space where feature classes have complimentary eigenvectors. Dimensionality reduction technique based on these complimentary eigenvector analysis can be described under two classes, desired class and background clutter, such that each basis function best represent one class while carrying the least amount of information from the second class. By selecting a few eigenvectors which are most relevant to desired class, one can reduce the dimension of hyperspectral cube. Since the FKT based technique reduces data size, it provides significant advantages for near real time detection applications in hyperspectral imagery. Furthermore, the eigenvector selection approach significantly reduces computation burden via the dimensionality reduction processes. The performance of the proposed dimensionality reduction algorithm has been tested using real-world hyperspectral dataset.

Dimensional Reduction and Hadronic Processes

International Nuclear Information System (INIS)

Signer, Adrian; Stoeckinger, Dominik

2008-01-01

We consider the application of regularization by dimensional reduction to NLO corrections of hadronic processes. The general collinear singularity structure is discussed, the origin of the regularization-scheme dependence is identified and transition rules to other regularization schemes are derived.

Coset space dimensional reduction of gauge theories

Energy Technology Data Exchange (ETDEWEB)

Kapetanakis, D. (Physik Dept., Technische Univ. Muenchen, Garching (Germany)); Zoupanos, G. (CERN, Geneva (Switzerland))

1992-10-01

We review the attempts to construct unified theories defined in higher dimensions which are dimensionally reduced over coset spaces. We employ the coset space dimensional reduction scheme, which permits the detailed study of the resulting four-dimensional gauge theories. In the context of this scheme we present the difficulties and the suggested ways out in the attempts to describe the observed interactions in a realistic way. (orig.).

Coset space dimensional reduction of gauge theories

International Nuclear Information System (INIS)

Kapetanakis, D.; Zoupanos, G.

1992-01-01

We review the attempts to construct unified theories defined in higher dimensions which are dimensionally reduced over coset spaces. We employ the coset space dimensional reduction scheme, which permits the detailed study of the resulting four-dimensional gauge theories. In the context of this scheme we present the difficulties and the suggested ways out in the attempts to describe the observed interactions in a realistic way. (orig.)

General dimensional reduction of ten-dimensional supergravity and superstring

International Nuclear Information System (INIS)

Ferrara, S.; Porrati, M.

1986-01-01

Dimensional reductions of supergravity theories are shown to yield to specific glasses of four-dimensional no-scale models with N=4, 2 or 1 residual supersymmetry. N=1 ''maximal'' supergravity lagrangian, corresponding to the ''untwisted'' sector of orbifold compactification of superstrings, contains nine families and has a no-scale structure based on the Kaehler manifold [SU(3, 3+3n)/SU(3)xSU(3+3n)]x[SU(1, 1)/U(1)]. The quantum consistency of the resulting theories give information on the non Kaluza-Klein (string) ''twisted'' sector. (orig.)

Dimensional reduction of a generalized flux problem

International Nuclear Information System (INIS)

Moroz, A.

1992-01-01

In this paper, a generalized flux problem with Abelian and non-Abelian fluxes is considered. In the Abelian case we shall show that the generalized flux problem for tight-binding models of noninteracting electrons on either 2n- or (2n + 1)-dimensional lattice can always be reduced to an n-dimensional hopping problem. A residual freedom in this reduction enables one to identify equivalence classes of hopping Hamiltonians which have the same spectrum. In the non-Abelian case, the reduction is not possible in general unless the flux tensor factorizes into an Abelian one times are element of the corresponding algebra

Metric dimensional reduction at singularities with implications to Quantum Gravity

International Nuclear Information System (INIS)

Stoica, Ovidiu Cristinel

2014-01-01

A series of old and recent theoretical observations suggests that the quantization of gravity would be feasible, and some problems of Quantum Field Theory would go away if, somehow, the spacetime would undergo a dimensional reduction at high energy scales. But an identification of the deep mechanism causing this dimensional reduction would still be desirable. The main contribution of this article is to show that dimensional reduction effects are due to General Relativity at singularities, and do not need to be postulated ad-hoc. Recent advances in understanding the geometry of singularities do not require modification of General Relativity, being just non-singular extensions of its mathematics to the limit cases. They turn out to work fine for some known types of cosmological singularities (black holes and FLRW Big-Bang), allowing a choice of the fundamental geometric invariants and physical quantities which remain regular. The resulting equations are equivalent to the standard ones outside the singularities. One consequence of this mathematical approach to the singularities in General Relativity is a special, (geo)metric type of dimensional reduction: at singularities, the metric tensor becomes degenerate in certain spacetime directions, and some properties of the fields become independent of those directions. Effectively, it is like one or more dimensions of spacetime just vanish at singularities. This suggests that it is worth exploring the possibility that the geometry of singularities leads naturally to the spontaneous dimensional reduction needed by Quantum Gravity. - Highlights: • The singularities we introduce are described by finite geometric/physical objects. • Our singularities are accompanied by dimensional reduction effects. • They affect the metric, the measure, the topology, the gravitational DOF (Weyl = 0). • Effects proposed in other approaches to Quantum Gravity are obtained naturally. • The geometric dimensional reduction obtained

Dimensional reduction in quantum gravity

Energy Technology Data Exchange (ETDEWEB)

Hooft, G [Rijksuniversiteit Utrecht (Netherlands). Inst. voor Theoretische Fysica

1994-12-31

The requirement that physical phenomena associated with gravitational collapse should be duly reconciled with the postulates of quantum mechanics implies that at a Planckian scale our world is not 3+1 dimensional. Rather, the observable degrees of freedom can best be described as if they were Boolean variables defined on a two- dimensional lattice, evolving with time. This observation, deduced from not much more than unitarity, entropy and counting arguments, implies severe restrictions on possible models of quantum gravity. Using cellular automata as an example it is argued that this dimensional reduction implies more constraints than the freedom we have in constructing models. This is the main reason why so-far no completely consistent mathematical models of quantum black holes have been found. (author). 13 refs, 2 figs.

Construction of N=8 supergravity theories by dimensional reduction

International Nuclear Information System (INIS)

Boucher, W.

1985-01-01

In this paper I ask which N=8 supergravity theories in four dimensions can be obtained by dimensional reduction of the N=1 supergravity theory in eleven dimensions. Several years ago Scherk and Schwarz produced a particular class of N = 8 theories by giving a dimensional reduction scheme on the restricted class of coset spaces, G/H, with dim H=0 (and therefore dim G=7). I generalize their considerations by looking at arbitrary (seven-dimensional) coset spaces. Also, instead of giving a particular ansatz which happens to work, I set about the distinctly more difficult task of determining all ansatzes which produce N=8 theories. The basic ingredient of my dimensional reduction scheme is the demand that certain symmetries, including supersymmetry, be truncated consistently. I find the surprising result that the only N=8 theories obtainable within the contexts of my scheme are those theories already written down by Scherk and Schwarz. In particular dim H=0 and dim G=7. Independently of these considerations, I prove that any dimensional reduction scheme which consistently truncates supersymmetry must also be consistent with the equations of motion. I discuss Lorentz-invariant solutions of the theories of Scherk and Schwarz, pointing out that since the ansatz of Scherk and Schwarz consistently truncates supersymmetry, any solution of these theories is also a solution of the N=1 supergravity theory in eleven dimensions and, hence, in particular that there is a Freund-Rubin-type ansatz for these theories. However I demonstrate that for most gauge groups the ansatz must be trivial which implies that for these theories the cosmological constant of any Lorentz-invariant solution must be zero (classically). Finally, I make some comparisons with work by Manton on dimensional reduction. (orig.)

Dimensionality reduction with unsupervised nearest neighbors

CERN Document Server

Kramer, Oliver

2013-01-01

This book is devoted to a novel approach for dimensionality reduction based on the famous nearest neighbor method that is a powerful classification and regression approach. It starts with an introduction to machine learning concepts and a real-world application from the energy domain. Then, unsupervised nearest neighbors (UNN) is introduced as efficient iterative method for dimensionality reduction. Various UNN models are developed step by step, reaching from a simple iterative strategy for discrete latent spaces to a stochastic kernel-based algorithm for learning submanifolds with independent parameterizations. Extensions that allow the embedding of incomplete and noisy patterns are introduced. Various optimization approaches are compared, from evolutionary to swarm-based heuristics. Experimental comparisons to related methodologies taking into account artificial test data sets and also real-world data demonstrate the behavior of UNN in practical scenarios. The book contains numerous color figures to illustr...

Nonlinear dimensionality reduction methods for synthetic biology biobricks' visualization.

Science.gov (United States)

Yang, Jiaoyun; Wang, Haipeng; Ding, Huitong; An, Ning; Alterovitz, Gil

2017-01-19

Visualizing data by dimensionality reduction is an important strategy in Bioinformatics, which could help to discover hidden data properties and detect data quality issues, e.g. data noise, inappropriately labeled data, etc. As crowdsourcing-based synthetic biology databases face similar data quality issues, we propose to visualize biobricks to tackle them. However, existing dimensionality reduction methods could not be directly applied on biobricks datasets. Hereby, we use normalized edit distance to enhance dimensionality reduction methods, including Isomap and Laplacian Eigenmaps. By extracting biobricks from synthetic biology database Registry of Standard Biological Parts, six combinations of various types of biobricks are tested. The visualization graphs illustrate discriminated biobricks and inappropriately labeled biobricks. Clustering algorithm K-means is adopted to quantify the reduction results. The average clustering accuracy for Isomap and Laplacian Eigenmaps are 0.857 and 0.844, respectively. Besides, Laplacian Eigenmaps is 5 times faster than Isomap, and its visualization graph is more concentrated to discriminate biobricks. By combining normalized edit distance with Isomap and Laplacian Eigenmaps, synthetic biology biobircks are successfully visualized in two dimensional space. Various types of biobricks could be discriminated and inappropriately labeled biobricks could be determined, which could help to assess crowdsourcing-based synthetic biology databases' quality, and make biobricks selection.

Behavioural Biometrics for Multi-factor Authentication in Biomedicine

Czech Academy of Sciences Publication Activity Database

Schlenker, Anna; Šárek, M.

2012-01-01

Roč. 8, č. 5 (2012), s. 19-24 ISSN 1801-5603 Grant - others:GA MŠk(CZ) LM2010005; GA UK(CZ) SVV-2012-264513 Institutional support: RVO:67985807 Keywords : biometric s * anatomical-physiological biometric s * behavioural biometric s * multi-factor authentication * keystroke dynamics * mouse dynamics Subject RIV: IN - Informatics, Computer Science http://www.ejbi.org/img/ejbi/2012/5/Schlenker_en.pdf

Scaling Properties of Dimensionality Reduction for Neural Populations and Network Models.

Directory of Open Access Journals (Sweden)

Ryan C Williamson

2016-12-01

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

A Tannakian approach to dimensional reduction of principal bundles

Science.gov (United States)

Álvarez-Cónsul, Luis; Biswas, Indranil; García-Prada, Oscar

2017-08-01

Let P be a parabolic subgroup of a connected simply connected complex semisimple Lie group G. Given a compact Kähler manifold X, the dimensional reduction of G-equivariant holomorphic vector bundles over X × G / P was carried out in Álvarez-Cónsul and García-Prada (2003). This raises the question of dimensional reduction of holomorphic principal bundles over X × G / P. The method of Álvarez-Cónsul and García-Prada (2003) is special to vector bundles; it does not generalize to principal bundles. In this paper, we adapt to equivariant principal bundles the Tannakian approach of Nori, to describe the dimensional reduction of G-equivariant principal bundles over X × G / P, and to establish a Hitchin-Kobayashi type correspondence. In order to be able to apply the Tannakian theory, we need to assume that X is a complex projective manifold.

Method of dimensionality reduction in contact mechanics and friction

CERN Document Server

Popov, Valentin L

2015-01-01

This book describes for the first time a simulation method for the fast calculation of contact properties and friction between rough surfaces in a complete form. In contrast to existing simulation methods, the method of dimensionality reduction (MDR) is based on the exact mapping of various types of three-dimensional contact problems onto contacts of one-dimensional foundations. Within the confines of MDR, not only are three dimensional systems reduced to one-dimensional, but also the resulting degrees of freedom are independent from another. Therefore, MDR results in an enormous reduction of the development time for the numerical implementation of contact problems as well as the direct computation time and can ultimately assume a similar role in tribology as FEM has in structure mechanics or CFD methods, in hydrodynamics. Furthermore, it substantially simplifies analytical calculation and presents a sort of “pocket book edition” of the entirety contact mechanics. Measurements of the rheology of bodies in...

Using Artificial Intelligence Techniques to Implement a Multifactor Authentication System

Directory of Open Access Journals (Sweden)

Jackson Phiri

2011-08-01

Full Text Available The recent years have seen a rise in the number of cases of cyber-crime committed through identity theft and fraud. To address this problem, this paper uses adaptive neural-fuzzy inference system, fuzzy logic and artificial neural network to implement a multifactor authentication system through a technique of information fusion. To begin with, the identity attributes are mined using the three corpora from three major sources namely the social networks, a set of questionnaires and application forms from the various services offered both in the real and cyberspace. The statistical information generated by the corpora is then used to compose an identity attribute metric model. The composed identity attributes metrics values classified as biometrics, device metrics and pseudo metrics are then fused at the score level through a technique of information fusion in a multifactor authentication system by using each of the above artificial intelligence technologies and the results compared.

Security enhanced multi-factor biometric authentication scheme using bio-hash function.

Directory of Open Access Journals (Sweden)

Younsung Choi

Full Text Available With the rapid development of personal information and wireless communication technology, user authentication schemes have been crucial to ensure that wireless communications are secure. As such, various authentication schemes with multi-factor authentication have been proposed to improve the security of electronic communications. Multi-factor authentication involves the use of passwords, smart cards, and various biometrics to provide users with the utmost privacy and data protection. Cao and Ge analyzed various authentication schemes and found that Younghwa An's scheme was susceptible to a replay attack where an adversary masquerades as a legal server and a user masquerading attack where user anonymity is not provided, allowing an adversary to execute a password change process by intercepting the user's ID during login. Cao and Ge improved upon Younghwa An's scheme, but various security problems remained. This study demonstrates that Cao and Ge's scheme is susceptible to a biometric recognition error, slow wrong password detection, off-line password attack, user impersonation attack, ID guessing attack, a DoS attack, and that their scheme cannot provide session key agreement. Then, to address all weaknesses identified in Cao and Ge's scheme, this study proposes a security enhanced multi-factor biometric authentication scheme and provides a security analysis and formal analysis using Burrows-Abadi-Needham logic. Finally, the efficiency analysis reveals that the proposed scheme can protect against several possible types of attacks with only a slightly high computational cost.

Security enhanced multi-factor biometric authentication scheme using bio-hash function.

Science.gov (United States)

Choi, Younsung; Lee, Youngsook; Moon, Jongho; Won, Dongho

2017-01-01

With the rapid development of personal information and wireless communication technology, user authentication schemes have been crucial to ensure that wireless communications are secure. As such, various authentication schemes with multi-factor authentication have been proposed to improve the security of electronic communications. Multi-factor authentication involves the use of passwords, smart cards, and various biometrics to provide users with the utmost privacy and data protection. Cao and Ge analyzed various authentication schemes and found that Younghwa An's scheme was susceptible to a replay attack where an adversary masquerades as a legal server and a user masquerading attack where user anonymity is not provided, allowing an adversary to execute a password change process by intercepting the user's ID during login. Cao and Ge improved upon Younghwa An's scheme, but various security problems remained. This study demonstrates that Cao and Ge's scheme is susceptible to a biometric recognition error, slow wrong password detection, off-line password attack, user impersonation attack, ID guessing attack, a DoS attack, and that their scheme cannot provide session key agreement. Then, to address all weaknesses identified in Cao and Ge's scheme, this study proposes a security enhanced multi-factor biometric authentication scheme and provides a security analysis and formal analysis using Burrows-Abadi-Needham logic. Finally, the efficiency analysis reveals that the proposed scheme can protect against several possible types of attacks with only a slightly high computational cost.

Security enhanced multi-factor biometric authentication scheme using bio-hash function

Science.gov (United States)

Lee, Youngsook; Moon, Jongho

2017-01-01

With the rapid development of personal information and wireless communication technology, user authentication schemes have been crucial to ensure that wireless communications are secure. As such, various authentication schemes with multi-factor authentication have been proposed to improve the security of electronic communications. Multi-factor authentication involves the use of passwords, smart cards, and various biometrics to provide users with the utmost privacy and data protection. Cao and Ge analyzed various authentication schemes and found that Younghwa An’s scheme was susceptible to a replay attack where an adversary masquerades as a legal server and a user masquerading attack where user anonymity is not provided, allowing an adversary to execute a password change process by intercepting the user’s ID during login. Cao and Ge improved upon Younghwa An’s scheme, but various security problems remained. This study demonstrates that Cao and Ge’s scheme is susceptible to a biometric recognition error, slow wrong password detection, off-line password attack, user impersonation attack, ID guessing attack, a DoS attack, and that their scheme cannot provide session key agreement. Then, to address all weaknesses identified in Cao and Ge’s scheme, this study proposes a security enhanced multi-factor biometric authentication scheme and provides a security analysis and formal analysis using Burrows-Abadi-Needham logic. Finally, the efficiency analysis reveals that the proposed scheme can protect against several possible types of attacks with only a slightly high computational cost. PMID:28459867

A Multifactor Secure Authentication System for Wireless Payment

Science.gov (United States)

Sanyal, Sugata; Tiwari, Ayu; Sanyal, Sudip

Organizations are deploying wireless based online payment applications to expand their business globally, it increases the growing need of regulatory requirements for the protection of confidential data, and especially in internet based financial areas. Existing internet based authentication systems often use either the Web or the Mobile channel individually to confirm the claimed identity of the remote user. The vulnerability is that access is based on only single factor authentication which is not secure to protect user data, there is a need of multifactor authentication. This paper proposes a new protocol based on multifactor authentication system that is both secure and highly usable. It uses a novel approach based on Transaction Identification Code and SMS to enforce another security level with the traditional Login/password system. The system provides a highly secure environment that is simple to use and deploy with in a limited resources that does not require any change in infrastructure or underline protocol of wireless network. This Protocol for Wireless Payment is extended as a two way authentications system to satisfy the emerging market need of mutual authentication and also supports secure B2B communication which increases faith of the user and business organizations on wireless financial transaction using mobile devices.

N-Dimensional LLL Reduction Algorithm with Pivoted Reflection

Directory of Open Access Journals (Sweden)

Zhongliang Deng

2018-01-01

Full Text Available The Lenstra-Lenstra-Lovász (LLL lattice reduction algorithm and many of its variants have been widely used by cryptography, multiple-input-multiple-output (MIMO communication systems and carrier phase positioning in global navigation satellite system (GNSS to solve the integer least squares (ILS problem. In this paper, we propose an n-dimensional LLL reduction algorithm (n-LLL, expanding the Lovász condition in LLL algorithm to n-dimensional space in order to obtain a further reduced basis. We also introduce pivoted Householder reflection into the algorithm to optimize the reduction time. For an m-order positive definite matrix, analysis shows that the n-LLL reduction algorithm will converge within finite steps and always produce better results than the original LLL reduction algorithm with n > 2. The simulations clearly prove that n-LLL is better than the original LLL in reducing the condition number of an ill-conditioned input matrix with 39% improvement on average for typical cases, which can significantly reduce the searching space for solving ILS problem. The simulation results also show that the pivoted reflection has significantly declined the number of swaps in the algorithm by 57%, making n-LLL a more practical reduction algorithm.

Rough electricity: a new fractal multi-factor model of electricity spot prices

DEFF Research Database (Denmark)

Bennedsen, Mikkel

We introduce a new mathematical model of electricity spot prices which accounts for the most important stylized facts of these time series: seasonality, spikes, stochastic volatility and mean reversion. Empirical studies have found a possible fifth stylized fact, fractality, and our approach...... explicitly incorporates this into the model of the prices. Our setup generalizes the popular Ornstein Uhlenbeck-based multi-factor framework of Benth et al. (2007) and allows us to perform statistical tests to distinguish between an Ornstein Uhlenbeck-based model and a fractal model. Further, through...... the multi-factor approach we account for seasonality and spikes before estimating - and making inference on - the degree of fractality. This is novel in the literature and we present simulation evidence showing that these precautions are crucial to accurate estimation. Lastly, we estimate our model...

A trace ratio maximization approach to multiple kernel-based dimensionality reduction.

Science.gov (United States)

Jiang, Wenhao; Chung, Fu-lai

2014-01-01

Most dimensionality reduction techniques are based on one metric or one kernel, hence it is necessary to select an appropriate kernel for kernel-based dimensionality reduction. Multiple kernel learning for dimensionality reduction (MKL-DR) has been recently proposed to learn a kernel from a set of base kernels which are seen as different descriptions of data. As MKL-DR does not involve regularization, it might be ill-posed under some conditions and consequently its applications are hindered. This paper proposes a multiple kernel learning framework for dimensionality reduction based on regularized trace ratio, termed as MKL-TR. Our method aims at learning a transformation into a space of lower dimension and a corresponding kernel from the given base kernels among which some may not be suitable for the given data. The solutions for the proposed framework can be found based on trace ratio maximization. The experimental results demonstrate its effectiveness in benchmark datasets, which include text, image and sound datasets, for supervised, unsupervised as well as semi-supervised settings. Copyright © 2013 Elsevier Ltd. All rights reserved.

Dimensional reduction in anomaly mediation

International Nuclear Information System (INIS)

Boyda, Ed; Murayama, Hitoshi; Pierce, Aaron

2002-01-01

We offer a guide to dimensional reduction in theories with anomaly-mediated supersymmetry breaking. Evanescent operators proportional to ε arise in the bare Lagrangian when it is reduced from d=4 to d=4-2ε dimensions. In the course of a detailed diagrammatic calculation, we show that inclusion of these operators is crucial. The evanescent operators conspire to drive the supersymmetry-breaking parameters along anomaly-mediation trajectories across heavy particle thresholds, guaranteeing the ultraviolet insensitivity

Adaptive Sampling for Nonlinear Dimensionality Reduction Based on Manifold Learning

DEFF Research Database (Denmark)

Franz, Thomas; Zimmermann, Ralf; Goertz, Stefan

2017-01-01

We make use of the non-intrusive dimensionality reduction method Isomap in order to emulate nonlinear parametric flow problems that are governed by the Reynolds-averaged Navier-Stokes equations. Isomap is a manifold learning approach that provides a low-dimensional embedding space that is approxi...... to detect and fill up gaps in the sampling in the embedding space. The performance of the proposed manifold filling method will be illustrated by numerical experiments, where we consider nonlinear parameter-dependent steady-state Navier-Stokes flows in the transonic regime.......We make use of the non-intrusive dimensionality reduction method Isomap in order to emulate nonlinear parametric flow problems that are governed by the Reynolds-averaged Navier-Stokes equations. Isomap is a manifold learning approach that provides a low-dimensional embedding space...

Dimensional reduction from entanglement in Minkowski space

International Nuclear Information System (INIS)

Brustein, Ram; Yarom, Amos

2005-01-01

Using a quantum field theoretic setting, we present evidence for dimensional reduction of any sub-volume of Minkowksi space. First, we show that correlation functions of a class of operators restricted to a sub-volume of D-dimensional Minkowski space scale as its surface area. A simple example of such area scaling is provided by the energy fluctuations of a free massless quantum field in its vacuum state. This is reminiscent of area scaling of entanglement entropy but applies to quantum expectation values in a pure state, rather than to statistical averages over a mixed state. We then show, in a specific case, that fluctuations in the bulk have a lower-dimensional representation in terms of a boundary theory at high temperature. (author)

Cautionary Note on Reporting Eta-Squared Values from Multifactor ANOVA Designs

Science.gov (United States)

Pierce, Charles A.; Block, Richard A.; Aguinis, Herman

2004-01-01

The authors provide a cautionary note on reporting accurate eta-squared values from multifactor analysis of variance (ANOVA) designs. They reinforce the distinction between classical and partial eta-squared as measures of strength of association. They provide examples from articles published in premier psychology journals in which the authors…

Dimensional reduction in field theory and hidden symmetries in extended supergravity

International Nuclear Information System (INIS)

Kremmer, E.

1985-01-01

Dimensional reduction in field theories is discussed both in theories which do not include gravity and in gravity theories. In particular, 11-dimensional supergravity and its reduction to 4 dimensions is considered. Hidden symmetries of supergravity with N=8 in 4 dimensions, global E 7 and local SU(8)-invariances in particular are detected. The hidden symmmetries permit to interpret geometrically the scalar fields

Coupled dimensionality reduction and classification for supervised and semi-supervised multilabel learning.

Science.gov (United States)

Gönen, Mehmet

2014-03-01

Coupled training of dimensionality reduction and classification is proposed previously to improve the prediction performance for single-label problems. Following this line of research, in this paper, we first introduce a novel Bayesian method that combines linear dimensionality reduction with linear binary classification for supervised multilabel learning and present a deterministic variational approximation algorithm to learn the proposed probabilistic model. We then extend the proposed method to find intrinsic dimensionality of the projected subspace using automatic relevance determination and to handle semi-supervised learning using a low-density assumption. We perform supervised learning experiments on four benchmark multilabel learning data sets by comparing our method with baseline linear dimensionality reduction algorithms. These experiments show that the proposed approach achieves good performance values in terms of hamming loss, average AUC, macro F 1 , and micro F 1 on held-out test data. The low-dimensional embeddings obtained by our method are also very useful for exploratory data analysis. We also show the effectiveness of our approach in finding intrinsic subspace dimensionality and semi-supervised learning tasks.

Supersymmetry and the Parisi-Sourlas dimensional reduction: A rigorous proof

International Nuclear Information System (INIS)

Klein, A.; Landau, L.J.; Perez, J.F.

1984-01-01

Functional integrals that are formally related to the average correlation functions of a classical field theory in the presence of random external sources are given a rigorous meaning. Their dimensional reduction to the Schwinger functions of the corresponding quantum field theory in two fewer dimensions is proven. This is done by reexpressing those functional integrals as expectations of a supersymmetric field theory. The Parisi-Sourlas dimensional reduction of a supersymmetric field theory to a usual quantum field theory in two fewer dimensions is proven. (orig.)

Dimensional reduction in Bose-Einstein-condensed alkali-metal vapors

International Nuclear Information System (INIS)

Salasnich, L.; Reatto, L.; Parola, A.

2004-01-01

We investigate the effects of dimensional reduction in atomic Bose-Einstein condensates (BECs) induced by a strong harmonic confinement in the cylindric radial direction or in the cylindric axial direction. The former case corresponds to a transition from three dimensions (3D) to 1D in cigar-shaped BECs, while the latter case corresponds to a transition from 3D to 2D in disk-shaped BECs. We analyze the first sound velocity in axially homogeneous cigar-shaped BECs and in radially homogeneous disk-shaped BECs. We consider also the dimensional reduction in a BEC confined by a harmonic potential both in the radial direction and in the axial direction. By using a variational approach, we calculate monopole and quadrupole collective oscillations of the BEC. We find that the frequencies of these collective oscillations are related to the dimensionality and to the repulsive or attractive interatomic interaction

Aggregate Multi-Factor Productivity: Measurement Issues in OECD Countries

OpenAIRE

Egert, Balazs

2018-01-01

This paper analyses for 34 OECD countries the extent to which the calculation of aggregate multi-factor productivity (MFP) is sensitive to alternative parameterisations. The starting point is the definition of MFP used in previous work in the OECD’s Economics Department (e.g. Johansson et al. 2013). They include alternative MFP measures, with human capital included or excluded, with different measures of Purchasing Power Parity (PPP) exchange rates, using time-varying capital depreciation rat...

Pole masses of quarks in dimensional reduction

International Nuclear Information System (INIS)

Avdeev, L.V.; Kalmykov, M.Yu.

1997-01-01

Pole masses of quarks in quantum chromodynamics are calculated to the two-loop order in the framework of the regularization by dimensional reduction. For the diagram with a light quark loop, the non-Euclidean asymptotic expansion is constructed with the external momentum on the mass shell of a heavy quark

Perturbative QCD Lagrangian at large distances and stochastic dimensionality reduction. Pt. 2

International Nuclear Information System (INIS)

Shintani, M.

1986-11-01

Using the method of stochastic dimensional reduction, we derive a four-dimensional quantum effective Lagrangian for the classical Yang-Mills system coupled to the Gaussian white noise. It is found that the Lagrangian coincides with the perturbative QCD at large distances constructed in our previous paper. That formalism is based on the local covariant operator formalism which maintains the unitarity of the S-matrix. Furthermore, we show the non-perturbative equivalence between super-Lorentz invariant sectors of the effective Lagrangian and two dimensional QCD coupled to the adjoint pseudo-scalars. This implies that stochastic dimensionality reduction by two is approximately operative in QCD at large distances. (orig.)

Effects of Single and Multifactor Treatments with Elevated Temperature, CO2 and Ozone on Oilseed Rape and Barley

DEFF Research Database (Denmark)

Clausen, Sabine Karin; Frenck, Georg; van der Linden, Leon Gareth

2011-01-01

We investigated the effect of elevated [CO2], [O3] and temperature on plant productivity and if these climate factors interacted with each other in multifactor treatments. The climate effects were studied in 14 different cultivars/lines of European spring oilseed rape (Brassica napus L.) and spring...... barley (Hordeum vulgare L.). Seven genotypes of each species were cultivated in six single- and multifactor treatments with ambient or elevated CO2 (385 ppm and 700 ppm), O3 (20 ppb and 60 ppb) and temperature (12/19 °C and 17/24 °C). Growth and production parameters were measured. Elevated CO2 increased....... A significantly decreased yield and thousand grain weight was also seen in barley due to elevated O3. The multifactor combination of elevated CO2, O3 and temperature showed a decrease in growth and production in the two species, though not statistically significant for all parameters. This trend suggests...

TPSLVM: a dimensionality reduction algorithm based on thin plate splines.

Science.gov (United States)

Jiang, Xinwei; Gao, Junbin; Wang, Tianjiang; Shi, Daming

2014-10-01

Dimensionality reduction (DR) has been considered as one of the most significant tools for data analysis. One type of DR algorithms is based on latent variable models (LVM). LVM-based models can handle the preimage problem easily. In this paper we propose a new LVM-based DR model, named thin plate spline latent variable model (TPSLVM). Compared to the well-known Gaussian process latent variable model (GPLVM), our proposed TPSLVM is more powerful especially when the dimensionality of the latent space is low. Also, TPSLVM is robust to shift and rotation. This paper investigates two extensions of TPSLVM, i.e., the back-constrained TPSLVM (BC-TPSLVM) and TPSLVM with dynamics (TPSLVM-DM) as well as their combination BC-TPSLVM-DM. Experimental results show that TPSLVM and its extensions provide better data visualization and more efficient dimensionality reduction compared to PCA, GPLVM, ISOMAP, etc.

Symmetries, integrals, and three-dimensional reductions of Plebanski's second heavenly equation

International Nuclear Information System (INIS)

Neyzi, F.; Sheftel, M. B.; Yazici, D.

2007-01-01

We study symmetries and conservation laws for Plebanski's second heavenly equation written as a first-order nonlinear evolutionary system which admits a multi-Hamiltonian structure. We construct an optimal system of one-dimensional subalgebras and all inequivalent three-dimensional symmetry reductions of the original four-dimensional system. We consider these two-component evolutionary systems in three dimensions as natural candidates for integrable systems

A finite-dimensional reduction method for slightly supercritical elliptic problems

Directory of Open Access Journals (Sweden)

Riccardo Molle

2004-01-01

Full Text Available We describe a finite-dimensional reduction method to find solutions for a class of slightly supercritical elliptic problems. A suitable truncation argument allows us to work in the usual Sobolev space even in the presence of supercritical nonlinearities: we modify the supercritical term in such a way to have subcritical approximating problems; for these problems, the finite-dimensional reduction can be obtained applying the methods already developed in the subcritical case; finally, we show that, if the truncation is realized at a sufficiently large level, then the solutions of the approximating problems, given by these methods, also solve the supercritical problems when the parameter is small enough.

The (2+1)-dimensional axial universes—solutions to the Einstein equations, dimensional reduction points and Klein–Fock–Gordon waves

International Nuclear Information System (INIS)

Fiziev, P P; Shirkov, D V

2012-01-01

The paper presents a generalization and further development of our recent publications, where solutions of the Klein–Fock–Gordon equation defined on a few particular D = (2 + 1)-dimensional static spacetime manifolds were considered. The latter involve toy models of two-dimensional spaces with axial symmetry, including dimensional reduction to the one-dimensional space as a singular limiting case. Here, the non-static models of space geometry with axial symmetry are under consideration. To make these models closer to physical reality, we define a set of ‘admissible’ shape functions ρ(t, z) as the (2 + 1)-dimensional Einstein equation solutions in the vacuum spacetime, in the presence of the Λ-term and for the spacetime filled with the standard ‘dust’. It is curious that in the last case the Einstein equations reduce to the well-known Monge–Ampère equation, thus enabling one to obtain the general solution of the Cauchy problem, as well as a set of other specific solutions involving one arbitrary function. A few explicit solutions of the Klein–Fock–Gordon equation in this set are given. An interesting qualitative feature of these solutions relates to the dimensional reduction points, their classification and time behavior. In particular, these new entities could provide us with novel insight into the nature of P- and T-violations and of the Big Bang. A short comparison with other attempts to utilize the dimensional reduction of the spacetime is given. (paper)

Reduction formalism for dimensionally regulated one-loop N-point integrals

International Nuclear Information System (INIS)

Binoth, T.; Guillet, J.Ph.; Heinrich, G.

2000-01-01

We consider one-loop scalar and tensor integrals with an arbitrary number of external legs relevant for multi-parton processes in massless theories. We present a procedure to reduce N-point scalar functions with generic 4-dimensional external momenta to box integrals in (4-2ε) dimensions. We derive a formula valid for arbitrary N and give an explicit expression for N=6. Further a tensor reduction method for N-point tensor integrals is presented. We prove that generically higher dimensional integrals contribute only to order ε for N≥5. The tensor reduction can be solved iteratively such that any tensor integral is expressible in terms of scalar integrals. Explicit formulas are given up to N=6

Effect evaluation of a multifactor community intervention to reduce falls among older persons

NARCIS (Netherlands)

Wijlhuizen, G.J.; Bois, P. du; Dommelen, P. van; Hopman-Rock, M.

2007-01-01

The objective of the study was to evaluate the effectiveness of a multifactor and multimethod community intervention programme to reduce falls among older persons by at least 20%. In a pre-test-post test design, self-reported falls were registered for 10 months in the intervention community and two

Multifactor-Driven Hierarchical Routing on Enterprise Service Bus

Science.gov (United States)

Mi, Xueqiang; Tang, Xinhuai; Yuan, Xiaozhou; Chen, Delai; Luo, Xiangfeng

Message Routing is the foremost functionality on Enterprise Service Bus (ESB), but current ESB products don't provide an expected solution for it, especially in the aspects of runtime route change mechanism and service orchestration model. In order to solve the above drawbacks, this paper proposes a multifactor-driven hierarchical routing (MDHR) model. MDHR defines three layers for message routing on ESB. Message layer gives the original support for message delivery. Application layer can integration or encapsulate some legacy applications or un-standard services. Business layer introduces business model to supplies developers with a business rule configuration, which supports enterprise integration patterns and simplifies the service orchestration on ESB.

Kantowski-Sachs multidimensional cosmological models and dynamical dimensional reduction

International Nuclear Information System (INIS)

Demianski, M.; Rome Univ.; Golda, Z.A.; Heller, M.; Szydlowski, M.

1988-01-01

Einstein's field equations are solved for a multidimensional spacetime (KS) x Tsup(m), where (KS) is a four-dimensional Kantowski-Sachs spacetime and Tsup(m) is an m-dimensional torus. Among all possible vacuum solutions there is a large class of spacetimes in which the macroscopic space expands and the microscopic space contracts to a finite volume. We also consider a non-vacuum case and we explicitly solve the field equations for the matter satisfying the Zel'dovich equation of state. In non-vacuum models, with matter satisfying an equation of state p = γρ, O ≤ γ < 1, at a sufficiently late stage of evolution the microspace always expands and the dynamical dimensional reduction does not occur. (author)

Center-vortex dominance after dimensional reduction of SU(2) lattice gauge theory

OpenAIRE

Gattnar, J.; Langfeld, K.; Schafke, A.; Reinhardt, H.

2000-01-01

The high-temperature phase of SU(2) Yang-Mills theory is addressed by means of dimensional reduction with a special emphasis on the properties of center vortices. For this purpose, the vortex vacuum which arises from center projection is studied in pure 3-dimensional Yang-Mills theory as well as in the 3-dimensional adjoint Higgs model which describes the high temperature phase of the 4-dimensional SU(2) gauge theory. We find center-dominance within the numerical accuracy of 10%.

Probabilistic Multi-Factor Interaction Model for Complex Material Behavior

Science.gov (United States)

Abumeri, Galib H.; Chamis, Christos C.

2010-01-01

Complex material behavior is represented by a single equation of product form to account for interaction among the various factors. The factors are selected by the physics of the problem and the environment that the model is to represent. For example, different factors will be required for each to represent temperature, moisture, erosion, corrosion, etc. It is important that the equation represent the physics of the behavior in its entirety accurately. The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the external launch tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points - the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation, the data used were obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated. The problem lies in how to represent the divot weight with a single equation. A unique solution to this problem is a multi-factor equation of product form. Each factor is of the following form (1 xi/xf)ei, where xi is the initial value, usually at ambient conditions, xf the final value, and ei the exponent that makes the curve represented unimodal that meets the initial and final values. The exponents are either evaluated by test data or by technical judgment. A minor disadvantage may be the selection of exponents in the absence of any empirical data. This form has been used successfully in describing the foam ejected in simulated space environmental conditions. Seven factors were required

Assessment of Multifactor Gene-Environment Interactions and Ovarian Cancer Risk

DEFF Research Database (Denmark)

Usset, Joseph L; Raghavan, Rama; Tyrer, Jonathan P

2016-01-01

and non-obese women. METHODS: We considered interactions between 11,441 SNPs within 80 candidate genes related to hormone biosynthesis and metabolism and insulin-like growth factors with six hormone-related factors (oral contraceptive use, parity, endometriosis, tubal ligation, hormone replacement therapy...... Future work is needed to develop powerful statistical methods able to detect these complex interactions. IMPACT: Assessment of multifactor interaction is feasible, and, here, suggests that the relationship between genetic variants within candidate genes and hormone-related risk factors may vary EOC...

Chaotic oscillator containing memcapacitor and meminductor and its dimensionality reduction analysis.

Science.gov (United States)

Yuan, Fang; Wang, Guangyi; Wang, Xiaowei

2017-03-01

In this paper, smooth curve models of meminductor and memcapacitor are designed, which are generalized from a memristor. Based on these models, a new five-dimensional chaotic oscillator that contains a meminductor and memcapacitor is proposed. By dimensionality reducing, this five-dimensional system can be transformed into a three-dimensional system. The main work of this paper is to give the comparisons between the five-dimensional system and its dimensionality reduction model. To investigate dynamics behaviors of the two systems, equilibrium points and stabilities are analyzed. And the bifurcation diagrams and Lyapunov exponent spectrums are used to explore their properties. In addition, digital signal processing technologies are used to realize this chaotic oscillator, and chaotic sequences are generated by the experimental device, which can be used in encryption applications.

Comparison of dimensionality reduction techniques for the fault diagnosis of mono block centrifugal pump using vibration signals

Directory of Open Access Journals (Sweden)

N.R. Sakthivel

2014-03-01

Full Text Available Bearing fault, Impeller fault, seal fault and cavitation are the main causes of breakdown in a mono block centrifugal pump and hence, the detection and diagnosis of these mechanical faults in a mono block centrifugal pump is very crucial for its reliable operation. Based on a continuous acquisition of signals with a data acquisition system, it is possible to classify the faults. This is achieved by the extraction of features from the measured data and employing data mining approaches to explore the structural information hidden in the signals acquired. In the present study, statistical features derived from the vibration data are used as the features. In order to increase the robustness of the classifier and to reduce the data processing load, dimensionality reduction is necessary. In this paper dimensionality reduction is performed using traditional dimensionality reduction techniques and nonlinear dimensionality reduction techniques. The effectiveness of each dimensionality reduction technique is also verified using visual analysis. The reduced feature set is then classified using a decision tree. The results obtained are compared with those generated by classifiers such as Naïve Bayes, Bayes Net and kNN. The effort is to bring out the better dimensionality reduction technique–classifier combination.

Dynamic Multi-Factor Credit Risk Model with Fat-Tailed Factors

Czech Academy of Sciences Publication Activity Database

Gapko, Petr; Šmíd, Martin

2012-01-01

Roč. 62, č. 2 (2012), s. 125-140 ISSN 0015-1920 R&D Projects: GA ČR GD402/09/H045; GA ČR GA402/09/0965 Grant - others:Univerzita Karlova(CZ) GAUK 46108 Institutional research plan: CEZ:AV0Z10750506 Keywords : credit risk * probability of default * loss given default * credit loss * credit loss distribution * Basel II Subject RIV: AH - Economics Impact factor: 0.340, year: 2012 http://library.utia.cas.cz/separaty/2012/E/smid-dynamic multi-factor credit risk model with fat-tailed factors.pdf

Restoration of dimensional reduction in the random-field Ising model at five dimensions

Science.gov (United States)

Fytas, Nikolaos G.; Martín-Mayor, Víctor; Picco, Marco; Sourlas, Nicolas

2017-04-01

The random-field Ising model is one of the few disordered systems where the perturbative renormalization group can be carried out to all orders of perturbation theory. This analysis predicts dimensional reduction, i.e., that the critical properties of the random-field Ising model in D dimensions are identical to those of the pure Ising ferromagnet in D -2 dimensions. It is well known that dimensional reduction is not true in three dimensions, thus invalidating the perturbative renormalization group prediction. Here, we report high-precision numerical simulations of the 5D random-field Ising model at zero temperature. We illustrate universality by comparing different probability distributions for the random fields. We compute all the relevant critical exponents (including the critical slowing down exponent for the ground-state finding algorithm), as well as several other renormalization-group invariants. The estimated values of the critical exponents of the 5D random-field Ising model are statistically compatible to those of the pure 3D Ising ferromagnet. These results support the restoration of dimensional reduction at D =5 . We thus conclude that the failure of the perturbative renormalization group is a low-dimensional phenomenon. We close our contribution by comparing universal quantities for the random-field problem at dimensions 3 ≤D equality at all studied dimensions.

Multifactor Screener in the 2000 National Health Interview Survey Cancer Control Supplement: Uses of Screener Estimates

Science.gov (United States)

Dietary intake estimates derived from the Multifactor Screener are rough estimates of usual intake of fruits and vegetables, fiber, calcium, servings of dairy, and added sugar. These estimates are not as accurate as those from more detailed methods (e.g., 24-hour recalls).

Dimensionality Reduction Methods: Comparative Analysis of methods PCA, PPCA and KPCA

Directory of Open Access Journals (Sweden)

Jorge Arroyo-Hernández

2016-01-01

Full Text Available The dimensionality reduction methods are algorithms mapping the set of data in subspaces derived from the original space, of fewer dimensions, that allow a description of the data at a lower cost. Due to their importance, they are widely used in processes associated with learning machine. This article presents a comparative analysis of PCA, PPCA and KPCA dimensionality reduction methods. A reconstruction experiment of worm-shape data was performed through structures of landmarks located in the body contour, with methods having different number of main components. The results showed that all methods can be seen as alternative processes. Nevertheless, thanks to the potential for analysis in the features space and the method for calculation of its preimage presented, KPCA offers a better method for recognition process and pattern extraction

Multi-Factor Authentication: A Survey

Directory of Open Access Journals (Sweden)

Aleksandr Ometov

2018-01-01

Full Text Available Today, digitalization decisively penetrates all the sides of the modern society. One of the key enablers to maintain this process secure is authentication. It covers many different areas of a hyper-connected world, including online payments, communications, access right management, etc. This work sheds light on the evolution of authentication systems towards Multi-Factor Authentication (MFA starting from Single-Factor Authentication (SFA and through Two-Factor Authentication (2FA. Particularly, MFA is expected to be utilized for human-to-everything interactions by enabling fast, user-friendly, and reliable authentication when accessing a service. This paper surveys the already available and emerging sensors (factor providers that allow for authenticating a user with the system directly or by involving the cloud. The corresponding challenges from the user as well as the service provider perspective are also reviewed. The MFA system based on reversed Lagrange polynomial within Shamir’s Secret Sharing (SSS scheme is further proposed to enable more flexible authentication. This solution covers the cases of authenticating the user even if some of the factors are mismatched or absent. Our framework allows for qualifying the missing factors by authenticating the user without disclosing sensitive biometric data to the verification entity. Finally, a vision of the future trends in MFA is discussed.

Superfluid hydrodynamics of polytropic gases: dimensional reduction and sound velocity

International Nuclear Information System (INIS)

Bellomo, N; Mazzarella, G; Salasnich, L

2014-01-01

Motivated by the fact that two-component confined fermionic gases in Bardeen–Cooper–Schrieffer–Bose–Einstein condensate (BCS–BEC) crossover can be described through an hydrodynamical approach, we study these systems—both in the cigar-shaped configuration and in the disc-shaped one—by using a polytropic Lagrangian density. We start from the Popov Lagrangian density and obtain, after a dimensional reduction process, the equations that control the dynamics of such systems. By solving these equations we study the sound velocity as a function of the density by analyzing how the dimensionality affects this velocity. (paper)

Ultraviolet finiteness of N = 8 supergravity, spontaneously broken by dimensional reduction

International Nuclear Information System (INIS)

Sezgin, E.; Nieuwenhuizen, P. van

1982-06-01

The one-loop corrections to scalar-scalar scattering in N = 8 supergravity with 4 masses from dimensional reduction, are finite. We discuss various mechanisms that cancel the cosmological constant and infra-red divergences due to finite but non-vanishing tadpoles. (author)

Anisotropic inflation in a 5D standing wave braneworld and effective dimensional reduction

Energy Technology Data Exchange (ETDEWEB)

Gogberashvili, Merab, E-mail: gogber@gmail.com [Andronikashvili Institute of Physics, 6 Tamarashvili St., Tbilisi 0177, Georgia (United States); Javakhishvili State University, 3 Chavchavadze Ave., Tbilisi 0128, Georgia (United States); Herrera-Aguilar, Alfredo, E-mail: aha@fis.unam.mx [Instituto de Ciencias Físicas, Universidad Nacional Autónoma de México, Apdo. Postal 48-3, 62251 Cuernavaca, Morelos (Mexico); Instituto de Física y Matemáticas, Universidad Michoacana de San Nicolás de Hidalgo, Edificio C-3, Ciudad Universitaria, CP 58040, Morelia, Michoacán (Mexico); Malagón-Morejón, Dagoberto, E-mail: malagon@fis.unam.mx [Instituto de Ciencias Físicas, Universidad Nacional Autónoma de México, Apdo. Postal 48-3, 62251 Cuernavaca, Morelos (Mexico); Instituto de Física y Matemáticas, Universidad Michoacana de San Nicolás de Hidalgo, Edificio C-3, Ciudad Universitaria, CP 58040, Morelia, Michoacán (Mexico); Mora-Luna, Refugio Rigel, E-mail: rigel@ifm.umich.mx [Instituto de Física y Matemáticas, Universidad Michoacana de San Nicolás de Hidalgo, Edificio C-3, Ciudad Universitaria, CP 58040, Morelia, Michoacán (Mexico)

2013-10-01

We investigate a cosmological solution within the framework of a 5D standing wave braneworld model generated by gravity coupled to a massless scalar phantom-like field. By obtaining a full exact solution of the model we found a novel dynamical mechanism in which the anisotropic nature of the primordial metric gives rise to (i) inflation along certain spatial dimensions, and (ii) deflation and a shrinking reduction of the number of spatial dimensions along other directions. This dynamical mechanism can be relevant for dimensional reduction in string and other higher-dimensional theories in the attempt of getting a 4D isotropic expanding space–time.

Anisotropic inflation in a 5D standing wave braneworld and effective dimensional reduction

International Nuclear Information System (INIS)

Gogberashvili, Merab; Herrera-Aguilar, Alfredo; Malagón-Morejón, Dagoberto; Mora-Luna, Refugio Rigel

2013-01-01

We investigate a cosmological solution within the framework of a 5D standing wave braneworld model generated by gravity coupled to a massless scalar phantom-like field. By obtaining a full exact solution of the model we found a novel dynamical mechanism in which the anisotropic nature of the primordial metric gives rise to (i) inflation along certain spatial dimensions, and (ii) deflation and a shrinking reduction of the number of spatial dimensions along other directions. This dynamical mechanism can be relevant for dimensional reduction in string and other higher-dimensional theories in the attempt of getting a 4D isotropic expanding space–time

Potential barriers to the application of multi-factor portfolio analysis in public hospitals: evidence from a pilot study in the Netherlands.

Science.gov (United States)

Pavlova, Milena; Tsiachristas, Apostolos; Vermaeten, Gerhard; Groot, Wim

2009-01-01

Portfolio analysis is a business management tool that can assist health care managers to develop new organizational strategies. The application of portfolio analysis to US hospital settings has been frequently reported. In Europe however, the application of this technique has received little attention, especially concerning public hospitals. Therefore, this paper examines the peculiarities of portfolio analysis and its applicability to the strategic management of European public hospitals. The analysis is based on a pilot application of a multi-factor portfolio analysis in a Dutch university hospital. The nature of portfolio analysis and the steps in a multi-factor portfolio analysis are reviewed along with the characteristics of the research setting. Based on these data, a multi-factor portfolio model is developed and operationalized. The portfolio model is applied in a pilot investigation to analyze the market attractiveness and hospital strengths with regard to the provision of three orthopedic services: knee surgery, hip surgery, and arthroscopy. The pilot portfolio analysis is discussed to draw conclusions about potential barriers to the overall adoption of portfolio analysis in the management of a public hospital. Copyright (c) 2008 John Wiley & Sons, Ltd.

Use of dimensionality reduction for structural mapping of hip joint osteoarthritis data

International Nuclear Information System (INIS)

Theoharatos, C; Fotopoulos, S; Boniatis, I; Panayiotakis, G; Panagiotopoulos, E

2009-01-01

A visualization-based, computer-oriented, classification scheme is proposed for assessing the severity of hip osteoarthritis (OA) using dimensionality reduction techniques. The introduced methodology tries to cope with the confined ability of physicians to structurally organize the entire available set of medical data into semantically similar categories and provide the capability to make visual observations among the ensemble of data using low-dimensional biplots. In this work, 18 pelvic radiographs of patients with verified unilateral hip OA are evaluated by experienced physicians and assessed into Normal, Mild and Severe following the Kellgren and Lawrence scale. Two regions of interest corresponding to radiographic hip joint spaces are determined and representative features are extracted using a typical texture analysis technique. The structural organization of all hip OA data is accomplished using distance and topology preservation-based dimensionality reduction techniques. The resulting map is a low-dimensional biplot that reflects the intrinsic organization of the ensemble of available data and which can be directly accessed by the physician. The conceivable visualization scheme can potentially reveal critical data similarities and help the operator to visually estimate their initial diagnosis. In addition, it can be used to detect putative clustering tendencies, examine the presence of data similarities and indicate the existence of possible false alarms in the initial perceptual evaluation

The Research of Regression Method for Forecasting Monthly Electricity Sales Considering Coupled Multi-factor

Science.gov (United States)

Wang, Jiangbo; Liu, Junhui; Li, Tiantian; Yin, Shuo; He, Xinhui

2018-01-01

The monthly electricity sales forecasting is a basic work to ensure the safety of the power system. This paper presented a monthly electricity sales forecasting method which comprehensively considers the coupled multi-factors of temperature, economic growth, electric power replacement and business expansion. The mathematical model is constructed by using regression method. The simulation results show that the proposed method is accurate and effective.

Optimal dimensionality reduction of complex dynamics: the chess game as diffusion on a free-energy landscape.

Science.gov (United States)

Krivov, Sergei V

2011-07-01

Dimensionality reduction is ubiquitous in the analysis of complex dynamics. The conventional dimensionality reduction techniques, however, focus on reproducing the underlying configuration space, rather than the dynamics itself. The constructed low-dimensional space does not provide a complete and accurate description of the dynamics. Here I describe how to perform dimensionality reduction while preserving the essential properties of the dynamics. The approach is illustrated by analyzing the chess game--the archetype of complex dynamics. A variable that provides complete and accurate description of chess dynamics is constructed. The winning probability is predicted by describing the game as a random walk on the free-energy landscape associated with the variable. The approach suggests a possible way of obtaining a simple yet accurate description of many important complex phenomena. The analysis of the chess game shows that the approach can quantitatively describe the dynamics of processes where human decision-making plays a central role, e.g., financial and social dynamics.

Dimensional reduction and BRST approach to the description of a Regge trajectory

International Nuclear Information System (INIS)

Pashnev, A.I.; Tsulaya, M.M.

1997-01-01

The local free field theory for Regge trajectory is described in the framework of the BRST-quantization method. The corresponding BRST-charge is constructed with the help of the method of dimensional reduction

Perturbative QCD lagrangian at large distances and stochastic dimensionality reduction

International Nuclear Information System (INIS)

Shintani, M.

1986-10-01

We construct a Lagrangian for perturbative QCD at large distances within the covariant operator formalism which explains the color confinement of quarks and gluons while maintaining unitarity of the S-matrix. It is also shown that when interactions are switched off, the mechanism of stochastic dimensionality reduction is operative in the system due to exact super-Lorentz symmetries. (orig.)

Object-based Dimensionality Reduction in Land Surface Phenology Classification

Directory of Open Access Journals (Sweden)

Brian E. Bunker

2016-11-01

Full Text Available Unsupervised classification or clustering of multi-decadal land surface phenology provides a spatio-temporal synopsis of natural and agricultural vegetation response to environmental variability and anthropogenic activities. Notwithstanding the detailed temporal information available in calibrated bi-monthly normalized difference vegetation index (NDVI and comparable time series, typical pre-classification workflows average a pixel’s bi-monthly index within the larger multi-decadal time series. While this process is one practical way to reduce the dimensionality of time series with many hundreds of image epochs, it effectively dampens temporal variation from both intra and inter-annual observations related to land surface phenology. Through a novel application of object-based segmentation aimed at spatial (not temporal dimensionality reduction, all 294 image epochs from a Moderate Resolution Imaging Spectroradiometer (MODIS bi-monthly NDVI time series covering the northern Fertile Crescent were retained (in homogenous landscape units as unsupervised classification inputs. Given the inherent challenges of in situ or manual image interpretation of land surface phenology classes, a cluster validation approach based on transformed divergence enabled comparison between traditional and novel techniques. Improved intra-annual contrast was clearly manifest in rain-fed agriculture and inter-annual trajectories showed increased cluster cohesion, reducing the overall number of classes identified in the Fertile Crescent study area from 24 to 10. Given careful segmentation parameters, this spatial dimensionality reduction technique augments the value of unsupervised learning to generate homogeneous land surface phenology units. By combining recent scalable computational approaches to image segmentation, future work can pursue new global land surface phenology products based on the high temporal resolution signatures of vegetation index time series.

Target oriented dimensionality reduction of hyperspectral data by Kernel Fukunaga-Koontz Transform

Science.gov (United States)

Binol, Hamidullah; Ochilov, Shuhrat; Alam, Mohammad S.; Bal, Abdullah

2017-02-01

Principal component analysis (PCA) is a popular technique in remote sensing for dimensionality reduction. While PCA is suitable for data compression, it is not necessarily an optimal technique for feature extraction, particularly when the features are exploited in supervised learning applications (Cheriyadat and Bruce, 2003) [1]. Preserving features belonging to the target is very crucial to the performance of target detection/recognition techniques. Fukunaga-Koontz Transform (FKT) based supervised band reduction technique can be used to provide this requirement. FKT achieves feature selection by transforming into a new space in where feature classes have complimentary eigenvectors. Analysis of these eigenvectors under two classes, target and background clutter, can be utilized for target oriented band reduction since each basis functions best represent target class while carrying least information of the background class. By selecting few eigenvectors which are the most relevant to the target class, dimension of hyperspectral data can be reduced and thus, it presents significant advantages for near real time target detection applications. The nonlinear properties of the data can be extracted by kernel approach which provides better target features. Thus, we propose constructing kernel FKT (KFKT) to present target oriented band reduction. The performance of the proposed KFKT based target oriented dimensionality reduction algorithm has been tested employing two real-world hyperspectral data and results have been reported consequently.

One-loop dimensional reduction of the linear σ model

International Nuclear Information System (INIS)

Malbouisson, A.P.C.; Silva-Neto, M.B.; Svaiter, N.F.

1997-05-01

We perform the dimensional reduction of the linear σ model at one-loop level. The effective of the reduced theory obtained from the integration over the nonzero Matsubara frequencies is exhibited. Thermal mass and coupling constant renormalization constants are given, as well as the thermal renormalization group which controls the dependence of the counterterms on the temperature. We also recover, for the reduced theory, the vacuum instability of the model for large N. (author)

Dimensional Reduction for the General Markov Model on Phylogenetic Trees.

Science.gov (United States)

Sumner, Jeremy G

2017-03-01

We present a method of dimensional reduction for the general Markov model of sequence evolution on a phylogenetic tree. We show that taking certain linear combinations of the associated random variables (site pattern counts) reduces the dimensionality of the model from exponential in the number of extant taxa, to quadratic in the number of taxa, while retaining the ability to statistically identify phylogenetic divergence events. A key feature is the identification of an invariant subspace which depends only bilinearly on the model parameters, in contrast to the usual multi-linear dependence in the full space. We discuss potential applications including the computation of split (edge) weights on phylogenetic trees from observed sequence data.

Kernel Based Nonlinear Dimensionality Reduction and Classification for Genomic Microarray

Directory of Open Access Journals (Sweden)

Lan Shu

2008-07-01

Full Text Available Genomic microarrays are powerful research tools in bioinformatics and modern medicinal research because they enable massively-parallel assays and simultaneous monitoring of thousands of gene expression of biological samples. However, a simple microarray experiment often leads to very high-dimensional data and a huge amount of information, the vast amount of data challenges researchers into extracting the important features and reducing the high dimensionality. In this paper, a nonlinear dimensionality reduction kernel method based locally linear embedding(LLE is proposed, and fuzzy K-nearest neighbors algorithm which denoises datasets will be introduced as a replacement to the classical LLE’s KNN algorithm. In addition, kernel method based support vector machine (SVM will be used to classify genomic microarray data sets in this paper. We demonstrate the application of the techniques to two published DNA microarray data sets. The experimental results confirm the superiority and high success rates of the presented method.

MULTI-FACTOR ANALYSIS FOR SELECTING LUNAR EXPLORATION SOFT LANDING AREA AND THE BEST CRUISE ROUTE

Directory of Open Access Journals (Sweden)

N. Mou

2018-04-01

Full Text Available Selecting the right soft landing area and planning a reasonable cruise route are the basic tasks of lunar exploration. In this paper, the Von Karman crater in the Antarctic Aitken basin on the back of the moon is used as the study area, and multi-factor analysis is used to evaluate the landing area and cruise route of lunar exploration. The evaluation system mainly includes the factors such as the density of craters, the impact area of craters, the formation of the whole area and the formation of some areas, such as the vertical structure, rock properties and the content of (FeO + TiO2, which can reflect the significance of scientific exploration factor. And the evaluation of scientific exploration is carried out on the basis of safety and feasibility. On the basis of multi-factor superposition analysis, three landing zones A, B and C are selected, and the appropriate cruising route is analyzed through scientific research factors. This study provides a scientific basis for the lunar probe landing and cruise route planning, and it provides technical support for the subsequent lunar exploration.

Multi-Factor Analysis for Selecting Lunar Exploration Soft Landing Area and the best Cruise Route

Science.gov (United States)

Mou, N.; Li, J.; Meng, Z.; Zhang, L.; Liu, W.

2018-04-01

Selecting the right soft landing area and planning a reasonable cruise route are the basic tasks of lunar exploration. In this paper, the Von Karman crater in the Antarctic Aitken basin on the back of the moon is used as the study area, and multi-factor analysis is used to evaluate the landing area and cruise route of lunar exploration. The evaluation system mainly includes the factors such as the density of craters, the impact area of craters, the formation of the whole area and the formation of some areas, such as the vertical structure, rock properties and the content of (FeO + TiO2), which can reflect the significance of scientific exploration factor. And the evaluation of scientific exploration is carried out on the basis of safety and feasibility. On the basis of multi-factor superposition analysis, three landing zones A, B and C are selected, and the appropriate cruising route is analyzed through scientific research factors. This study provides a scientific basis for the lunar probe landing and cruise route planning, and it provides technical support for the subsequent lunar exploration.

Lifetime of rho meson in correlation with magnetic-dimensional reduction

Energy Technology Data Exchange (ETDEWEB)

Kawaguchi, Mamiya [Nagoya University, Department of Physics, Nagoya (Japan); Matsuzaki, Shinya [Nagoya University, Department of Physics, Nagoya (Japan); Nagoya University, Institute for Advanced Research, Nagoya (Japan)

2017-04-15

It is naively expected that in a strong magnetic configuration, the Landau quantization ceases the neutral rho meson to decay to the charged pion pair, so the neutral rho meson will be long-lived. To closely access this naive observation, we explicitly compute the charged pion loop in the magnetic field at the one-loop level, to evaluate the magnetic dependence of the lifetime for the neutral rho meson as well as its mass. Due to the dimensional reduction induced by the magnetic field (violation of the Lorentz invariance), the polarization (spin s{sub z} = 0, ±1) modes of the rho meson, as well as the corresponding pole mass and width, are decomposed in a nontrivial manner compared to the vacuum case. To see the significance of the reduction effect, we simply take the lowest Landau level approximation to analyze the spin-dependent rho masses and widths. We find that the ''fate'' of the rho meson may be more complicated because of the magnetic-dimensional reduction: as the magnetic field increases, the rho width for the spin s{sub z} = 0 starts to develop, reaches a peak, then vanishes at the critical magnetic field to which the folklore refers. On the other side, the decay rates of the other rhos for s{sub z} = ±1 monotonically increase as the magnetic field develops. The correlation between the polarization dependence and the Landau level truncation is also addressed. (orig.)

Relation between the pole and the minimally subtracted mass in dimensional regularization and dimensional reduction to three-loop order

Energy Technology Data Exchange (ETDEWEB)

Marquard, P.; Mihaila, L.; Steinhauser, M. [Karlsruhe Univ. (T.H.) (Germany). Inst. fuer Theoretische Teilchenphysik; Piclum, J.H. [Karlsruhe Univ. (T.H.) (Germany). Inst. fuer Theoretische Teilchenphysik]|[Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik

2007-02-15

We compute the relation between the pole quark mass and the minimally subtracted quark mass in the framework of QCD applying dimensional reduction as a regularization scheme. Special emphasis is put on the evanescent couplings and the renormalization of the {epsilon}-scalar mass. As a by-product we obtain the three-loop on-shell renormalization constants Z{sub m}{sup OS} and Z{sub 2}{sup OS} in dimensional regularization and thus provide the first independent check of the analytical results computed several years ago. (orig.)

Participatory three dimensional mapping for the preparation of landslide disaster risk reduction program

Science.gov (United States)

Kusratmoko, Eko; Wibowo, Adi; Cholid, Sofyan; Pin, Tjiong Giok

2017-07-01

This paper presents the results of applications of participatory three dimensional mapping (P3DM) method for fqcilitating the people of Cibanteng' village to compile a landslide disaster risk reduction program. Physical factors, as high rainfall, topography, geology and land use, and coupled with the condition of demographic and social-economic factors, make up the Cibanteng region highly susceptible to landslides. During the years 2013-2014 has happened 2 times landslides which caused economic losses, as a result of damage to homes and farmland. Participatory mapping is one part of the activities of community-based disaster risk reduction (CBDRR)), because of the involvement of local communities is a prerequisite for sustainable disaster risk reduction. In this activity, participatory mapping method are done in two ways, namely participatory two-dimensional mapping (P2DM) with a focus on mapping of disaster areas and participatory three-dimensional mapping (P3DM) with a focus on the entire territory of the village. Based on the results P3DM, the ability of the communities in understanding the village environment spatially well-tested and honed, so as to facilitate the preparation of the CBDRR programs. Furthermore, the P3DM method can be applied to another disaster areas, due to it becomes a medium of effective dialogue between all levels of involved communities.

Gaussian processes with built-in dimensionality reduction: Applications to high-dimensional uncertainty propagation

International Nuclear Information System (INIS)

Tripathy, Rohit; Bilionis, Ilias; Gonzalez, Marcial

2016-01-01

Uncertainty quantification (UQ) tasks, such as model calibration, uncertainty propagation, and optimization under uncertainty, typically require several thousand evaluations of the underlying computer codes. To cope with the cost of simulations, one replaces the real response surface with a cheap surrogate based, e.g., on polynomial chaos expansions, neural networks, support vector machines, or Gaussian processes (GP). However, the number of simulations required to learn a generic multivariate response grows exponentially as the input dimension increases. This curse of dimensionality can only be addressed, if the response exhibits some special structure that can be discovered and exploited. A wide range of physical responses exhibit a special structure known as an active subspace (AS). An AS is a linear manifold of the stochastic space characterized by maximal response variation. The idea is that one should first identify this low dimensional manifold, project the high-dimensional input onto it, and then link the projection to the output. If the dimensionality of the AS is low enough, then learning the link function is a much easier problem than the original problem of learning a high-dimensional function. The classic approach to discovering the AS requires gradient information, a fact that severely limits its applicability. Furthermore, and partly because of its reliance to gradients, it is not able to handle noisy observations. The latter is an essential trait if one wants to be able to propagate uncertainty through stochastic simulators, e.g., through molecular dynamics codes. In this work, we develop a probabilistic version of AS which is gradient-free and robust to observational noise. Our approach relies on a novel Gaussian process regression with built-in dimensionality reduction. In particular, the AS is represented as an orthogonal projection matrix that serves as yet another covariance function hyper-parameter to be estimated from the data. To train the

Gaussian processes with built-in dimensionality reduction: Applications to high-dimensional uncertainty propagation

Science.gov (United States)

Tripathy, Rohit; Bilionis, Ilias; Gonzalez, Marcial

2016-09-01

Uncertainty quantification (UQ) tasks, such as model calibration, uncertainty propagation, and optimization under uncertainty, typically require several thousand evaluations of the underlying computer codes. To cope with the cost of simulations, one replaces the real response surface with a cheap surrogate based, e.g., on polynomial chaos expansions, neural networks, support vector machines, or Gaussian processes (GP). However, the number of simulations required to learn a generic multivariate response grows exponentially as the input dimension increases. This curse of dimensionality can only be addressed, if the response exhibits some special structure that can be discovered and exploited. A wide range of physical responses exhibit a special structure known as an active subspace (AS). An AS is a linear manifold of the stochastic space characterized by maximal response variation. The idea is that one should first identify this low dimensional manifold, project the high-dimensional input onto it, and then link the projection to the output. If the dimensionality of the AS is low enough, then learning the link function is a much easier problem than the original problem of learning a high-dimensional function. The classic approach to discovering the AS requires gradient information, a fact that severely limits its applicability. Furthermore, and partly because of its reliance to gradients, it is not able to handle noisy observations. The latter is an essential trait if one wants to be able to propagate uncertainty through stochastic simulators, e.g., through molecular dynamics codes. In this work, we develop a probabilistic version of AS which is gradient-free and robust to observational noise. Our approach relies on a novel Gaussian process regression with built-in dimensionality reduction. In particular, the AS is represented as an orthogonal projection matrix that serves as yet another covariance function hyper-parameter to be estimated from the data. To train the

Gaussian processes with built-in dimensionality reduction: Applications to high-dimensional uncertainty propagation

Energy Technology Data Exchange (ETDEWEB)

Tripathy, Rohit, E-mail: rtripath@purdue.edu; Bilionis, Ilias, E-mail: ibilion@purdue.edu; Gonzalez, Marcial, E-mail: marcial-gonzalez@purdue.edu

2016-09-15

Uncertainty quantification (UQ) tasks, such as model calibration, uncertainty propagation, and optimization under uncertainty, typically require several thousand evaluations of the underlying computer codes. To cope with the cost of simulations, one replaces the real response surface with a cheap surrogate based, e.g., on polynomial chaos expansions, neural networks, support vector machines, or Gaussian processes (GP). However, the number of simulations required to learn a generic multivariate response grows exponentially as the input dimension increases. This curse of dimensionality can only be addressed, if the response exhibits some special structure that can be discovered and exploited. A wide range of physical responses exhibit a special structure known as an active subspace (AS). An AS is a linear manifold of the stochastic space characterized by maximal response variation. The idea is that one should first identify this low dimensional manifold, project the high-dimensional input onto it, and then link the projection to the output. If the dimensionality of the AS is low enough, then learning the link function is a much easier problem than the original problem of learning a high-dimensional function. The classic approach to discovering the AS requires gradient information, a fact that severely limits its applicability. Furthermore, and partly because of its reliance to gradients, it is not able to handle noisy observations. The latter is an essential trait if one wants to be able to propagate uncertainty through stochastic simulators, e.g., through molecular dynamics codes. In this work, we develop a probabilistic version of AS which is gradient-free and robust to observational noise. Our approach relies on a novel Gaussian process regression with built-in dimensionality reduction. In particular, the AS is represented as an orthogonal projection matrix that serves as yet another covariance function hyper-parameter to be estimated from the data. To train the

Multi-factor evaluation indicator method for the risk assessment of atmospheric and oceanic hazard group due to the attack of tropical cyclones

Science.gov (United States)

Qi, Peng; Du, Mei

2018-06-01

China's southeast coastal areas frequently suffer from storm surge due to the attack of tropical cyclones (TCs) every year. Hazards induced by TCs are complex, such as strong wind, huge waves, storm surge, heavy rain, floods, and so on. The atmospheric and oceanic hazards cause serious disasters and substantial economic losses. This paper, from the perspective of hazard group, sets up a multi-factor evaluation method for the risk assessment of TC hazards using historical extreme data of concerned atmospheric and oceanic elements. Based on the natural hazard dynamic process, the multi-factor indicator system is composed of nine natural hazard factors representing intensity and frequency, respectively. Contributing to the indicator system, in order of importance, are maximum wind speed by TCs, attack frequency of TCs, maximum surge height, maximum wave height, frequency of gusts ≥ Scale 8, rainstorm intensity, maximum tidal range, rainstorm frequency, then sea-level rising rate. The first four factors are the most important, whose weights exceed 10% in the indicator system. With normalization processing, all the single-hazard factors are superposed by multiplying their weights to generate a superposed TC hazard. The multi-factor evaluation indicator method was applied to the risk assessment of typhoon-induced atmospheric and oceanic hazard group in typhoon-prone southeast coastal cities of China.

Some remarks on dimensional reduction of Gauge theories and model building

International Nuclear Information System (INIS)

Rudolph, G.; Karl-Marx-Universitaet, Leipzig; Volobujev, I.P.

1989-01-01

We study the group-theoretical aspect of dimensional reduction of pure gauge theories and propose a method of solving the constraint equations for scalar fields. We show that there are possibilities of model building which differ from those commonly used. In particular, we give examples in which the resulting potential is not of Higgs type. (orig.)

Lie symmetry analysis and reduction for exact solution of (2+1)-dimensional Bogoyavlensky-Konopelchenko equation by geometric approach

Science.gov (United States)

Ray, S. Saha

2018-04-01

In this paper, the symmetry analysis and similarity reduction of the (2+1)-dimensional Bogoyavlensky-Konopelchenko (B-K) equation are investigated by means of the geometric approach of an invariance group, which is equivalent to the classical Lie symmetry method. Using the extended Harrison and Estabrook’s differential forms approach, the infinitesimal generators for (2+1)-dimensional B-K equation are obtained. Firstly, the vector field associated with the Lie group of transformation is derived. Then the symmetry reduction and the corresponding explicit exact solution of (2+1)-dimensional B-K equation is obtained.

On symmetry reduction and exact solutions of the linear one-dimensional Schroedinger equation

International Nuclear Information System (INIS)

Barannik, L.L.

1996-01-01

Symmetry reduction of the Schroedinger equation with potential is carried out on subalgebras of the Lie algebra which is the direct sum of the special Galilei algebra and one-dimensional algebra. Some new exact solutions are obtained

Dutch Multifactor Fatigue Scale : A New Scale to Measure the Different Aspects of Fatigue After Acquired Brain Injury

NARCIS (Netherlands)

Visser-Keizer, Annemarie C.; Hogenkamp, Antoinette; Westerhof-Evers, Herma J.; Egberink, Iris J. L.; Spikman, Jacoba M.

Objectives: To develop the Dutch Multifactor Fatigue Scale (DMFS), a new scale to assess the nature and impact of fatigue and coping with fatigue in the chronic phase after acquired brain injury (ABI) and to analyze the psychometric properties of this scale in a mixed group of patients with ABI.

A method of integration of atomistic simulations and continuum mechanics by collecting of dynamical systems with dimensional reduction

International Nuclear Information System (INIS)

Kaczmarek, J.

2002-01-01

Elementary processes responsible for phenomena in material are frequently related to scale close to atomic one. Therefore atomistic simulations are important for material sciences. On the other hand continuum mechanics is widely applied in mechanics of materials. It seems inevitable that both methods will gradually integrate. A multiscale method of integration of these approaches called collection of dynamical systems with dimensional reduction is introduced in this work. The dimensional reduction procedure realizes transition between various scale models from an elementary dynamical system (EDS) to a reduced dynamical system (RDS). Mappings which transform variables and forces, skeletal dynamical system (SDS) and a set of approximation and identification methods are main components of this procedure. The skeletal dynamical system is a set of dynamical systems parameterized by some constants and has variables related to the dimensionally reduced model. These constants are identified with the aid of solutions of the elementary dynamical system. As a result we obtain a dimensionally reduced dynamical system which describes phenomena in an averaged way in comparison with the EDS. Concept of integration of atomistic simulations with continuum mechanics consists in using a dynamical system describing evolution of atoms as an elementary dynamical system. Then, we introduce a continuum skeletal dynamical system within the dimensional reduction procedure. In order to construct such a system we have to modify a continuum mechanics formulation to some degree. Namely, we formalize scale of averaging for continuum theory and as a result we consider continuum with finite-dimensional fields only. Then, realization of dimensional reduction is possible. A numerical example of realization of the dimensional reduction procedure is shown. We consider a one dimensional chain of atoms interacting by Lennard-Jones potential. Evolution of this system is described by an elementary

Wideband radar cross section reduction using two-dimensional phase gradient metasurfaces

Energy Technology Data Exchange (ETDEWEB)

Li, Yongfeng; Qu, Shaobo; Wang, Jiafu; Chen, Hongya [College of Science, Air Force Engineering University, Xi' an, Shaanxi 710051 (China); Zhang, Jieqiu [College of Science, Air Force Engineering University, Xi' an, Shaanxi 710051 (China); Electronic Materials Research Laboratory, Key Laboratory of Ministry of Education, Xi' an Jiaotong University, Xi' an, Shaanxi 710049 (China); Xu, Zhuo [Electronic Materials Research Laboratory, Key Laboratory of Ministry of Education, Xi' an Jiaotong University, Xi' an, Shaanxi 710049 (China); Zhang, Anxue [School of Electronics and Information Engineering, Xi' an Jiaotong University, Xi' an, Shaanxi 710049 (China)

2014-06-02

Phase gradient metasurface (PGMs) are artificial surfaces that can provide pre-defined in-plane wave-vectors to manipulate the directions of refracted/reflected waves. In this Letter, we propose to achieve wideband radar cross section (RCS) reduction using two-dimensional (2D) PGMs. A 2D PGM was designed using a square combination of 49 split-ring sub-unit cells. The PGM can provide additional wave-vectors along the two in-plane directions simultaneously, leading to either surface wave conversion, deflected reflection, or diffuse reflection. Both the simulation and experiment results verified the wide-band, polarization-independent, high-efficiency RCS reduction induced by the 2D PGM.

Wideband radar cross section reduction using two-dimensional phase gradient metasurfaces

International Nuclear Information System (INIS)

Li, Yongfeng; Qu, Shaobo; Wang, Jiafu; Chen, Hongya; Zhang, Jieqiu; Xu, Zhuo; Zhang, Anxue

2014-01-01

Phase gradient metasurface (PGMs) are artificial surfaces that can provide pre-defined in-plane wave-vectors to manipulate the directions of refracted/reflected waves. In this Letter, we propose to achieve wideband radar cross section (RCS) reduction using two-dimensional (2D) PGMs. A 2D PGM was designed using a square combination of 49 split-ring sub-unit cells. The PGM can provide additional wave-vectors along the two in-plane directions simultaneously, leading to either surface wave conversion, deflected reflection, or diffuse reflection. Both the simulation and experiment results verified the wide-band, polarization-independent, high-efficiency RCS reduction induced by the 2D PGM.

Measurement Invariance of Second-Order Factor Model of the Multifactor Leadership Questionnaire (MLQ) across K-12 Principal Gender

Science.gov (United States)

Xu, Lihua; Wubbena, Zane; Stewart, Trae

2016-01-01

Purpose: The purpose of this paper is to investigate the factor structure and the measurement invariance of the Multifactor Leadership Questionnaire (MLQ) across gender of K-12 school principals (n=6,317) in the USA. Design/methodology/approach: Nine first-order factor models and four second-order factor models were tested using confirmatory…

Puzzle Imaging: Using Large-Scale Dimensionality Reduction Algorithms for Localization.

Science.gov (United States)

Glaser, Joshua I; Zamft, Bradley M; Church, George M; Kording, Konrad P

2015-01-01

Current high-resolution imaging techniques require an intact sample that preserves spatial relationships. We here present a novel approach, "puzzle imaging," that allows imaging a spatially scrambled sample. This technique takes many spatially disordered samples, and then pieces them back together using local properties embedded within the sample. We show that puzzle imaging can efficiently produce high-resolution images using dimensionality reduction algorithms. We demonstrate the theoretical capabilities of puzzle imaging in three biological scenarios, showing that (1) relatively precise 3-dimensional brain imaging is possible; (2) the physical structure of a neural network can often be recovered based only on the neural connectivity matrix; and (3) a chemical map could be reproduced using bacteria with chemosensitive DNA and conjugative transfer. The ability to reconstruct scrambled images promises to enable imaging based on DNA sequencing of homogenized tissue samples.

Multi-Factor Impact Analysis of Agricultural Production in Bangladesh with Climate Change

Science.gov (United States)

Ruane, Alex C.; Major, David C.; Yu, Winston H.; Alam, Mozaharul; Hussain, Sk. Ghulam; Khan, Abu Saleh; Hassan, Ahmadul; Al Hossain, Bhuiya Md. Tamim; Goldberg, Richard; Horton, Radley M.;

Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO2 Enrichment experiment.

Science.gov (United States)

De Kauwe, Martin G; Medlyn, Belinda E; Walker, Anthony P; Zaehle, Sönke; Asao, Shinichi; Guenet, Bertrand; Harper, Anna B; Hickler, Thomas; Jain, Atul K; Luo, Yiqi; Lu, Xingjie; Luus, Kristina; Parton, William J; Shu, Shijie; Wang, Ying-Ping; Werner, Christian; Xia, Jianyang; Pendall, Elise; Morgan, Jack A; Ryan, Edmund M; Carrillo, Yolima; Dijkstra, Feike A; Zelikova, Tamara J; Norby, Richard J

2017-09-01

Multifactor experiments are often advocated as important for advancing terrestrial biosphere models (TBMs), yet to date, such models have only been tested against single-factor experiments. We applied 10 TBMs to the multifactor Prairie Heating and CO 2 Enrichment (PHACE) experiment in Wyoming, USA. Our goals were to investigate how multifactor experiments can be used to constrain models and to identify a road map for model improvement. We found models performed poorly in ambient conditions; there was a wide spread in simulated above-ground net primary productivity (range: 31-390 g C m -2  yr -1 ). Comparison with data highlighted model failures particularly with respect to carbon allocation, phenology, and the impact of water stress on phenology. Performance against the observations from single-factors treatments was also relatively poor. In addition, similar responses were predicted for different reasons across models: there were large differences among models in sensitivity to water stress and, among the N cycle models, N availability during the experiment. Models were also unable to capture observed treatment effects on phenology: they overestimated the effect of warming on leaf onset and did not allow CO 2 -induced water savings to extend the growing season length. Observed interactive (CO 2  × warming) treatment effects were subtle and contingent on water stress, phenology, and species composition. As the models did not correctly represent these processes under ambient and single-factor conditions, little extra information was gained by comparing model predictions against interactive responses. We outline a series of key areas in which this and future experiments could be used to improve model predictions of grassland responses to global change. © 2017 John Wiley & Sons Ltd.

Cosmological string solutions by dimensional reduction

International Nuclear Information System (INIS)

Behrndt, K.; Foerste, S.

1993-12-01

We obtain cosmological four dimensional solutions of the low energy effective string theory by reducing a five dimensional black hole, and black hole-de Sitter solution of the Einstein gravity down to four dimensions. The appearance of a cosmological constant in the five dimensional Einstein-Hilbert produces a special dilaton potential in the four dimensional effective string action. Cosmological scenarios implement by our solutions are discussed

Dimensional reduction for D3-brane moduli

International Nuclear Information System (INIS)

Cownden, Brad; Frey, Andrew R.; Marsh, M.C. David; Underwood, Bret

2016-01-01

Warped string compactifications are central to many attempts to stabilize moduli and connect string theory with cosmology and particle phenomenology. We present a first-principles derivation of the low-energy 4D effective theory from dimensional reduction of a D3-brane in a warped Calabi-Yau compactification of type IIB string theory with imaginary self-dual 3-form flux, including effects of D3-brane motion beyond the probe approximation, and find the metric on the moduli space of brane positions, the universal volume modulus, and axions descending from the 4-form potential. As D3-branes may be considered as carrying either electric or magnetic charges for the self-dual 5-form field strength, we present calculations in both duality frames. Our results are consistent with, but extend significantly, earlier results on the low-energy effective theory arising from D3-branes in string compactifications.

Three-dimensional assessment of unilateral subcondylar fracture using computed tomography after open reduction

Directory of Open Access Journals (Sweden)

Sathya Kumar Devireddy

2014-01-01

Full Text Available Objective: The aim was to assess the accuracy of three-dimensional anatomical reductions achieved by open method of treatment in cases of displaced unilateral mandibular subcondylar fractures using preoperative (pre op and postoperative (post op computed tomography (CT scans. Materials and Methods: In this prospective study, 10 patients with unilateral sub condylar fractures confirmed by an orthopantomogram were included. A pre op and post op CT after 1 week of surgical procedure was taken in axial, coronal and sagittal plane along with three-dimensional reconstruction. Standard anatomical parameters, which undergo changes due to fractures of the mandibular condyle were measured in pre and post op CT scans in three planes and statistically analysed for the accuracy of the reduction comparing the following variables: (a Pre op fractured and nonfractured side (b post op fractured and nonfractured side (c pre op fractured and post op fractured side. P < 0.05 was considered as significant. Results: Three-dimensional anatomical reduction was possible in 9 out of 10 cases (90%. The statistical analysis of each parameter in three variables revealed (P < 0.05 that there was a gross change in the dimensions of the parameters obtained in pre op fractured and nonfractured side. When these parameters were assessed in post op CT for the three variables there was no statistical difference between the post op fractured side and non fractured side. The same parameters were analysed for the three variables in pre op fractured and post op fractured side and found significant statistical difference suggesting a considerable change in the dimensions of the fractured side post operatively. Conclusion: The statistical and clinical results in our study emphasised that it is possible to fix the condyle in three-dimensional anatomical positions with open method of treatment and avoid post op degenerative joint changes. CT is the ideal imaging tool and should be used on

Neural networks for the dimensionality reduction of GOME measurement vector in the estimation of ozone profiles

International Nuclear Information System (INIS)

Del Frate, F.; Iapaolo, M.; Casadio, S.; Godin-Beekmann, S.; Petitdidier, M.

2005-01-01

Dimensionality reduction can be of crucial importance in the application of inversion schemes to atmospheric remote sensing data. In this study the problem of dimensionality reduction in the retrieval of ozone concentration profiles from the radiance measurements provided by the instrument Global Ozone Monitoring Experiment (GOME) on board of ESA satellite ERS-2 is considered. By means of radiative transfer modelling, neural networks and pruning algorithms, a complete procedure has been designed to extract the GOME spectral ranges most crucial for the inversion. The quality of the resulting retrieval algorithm has been evaluated by comparing its performance to that yielded by other schemes and co-located profiles obtained with lidar measurements

Reduction of multi-dimensional laboratory data to a two-dimensional plot: a novel technique for the identification of laboratory error.

Science.gov (United States)

Kazmierczak, Steven C; Leen, Todd K; Erdogmus, Deniz; Carreira-Perpinan, Miguel A

2007-01-01

The clinical laboratory generates large amounts of patient-specific data. Detection of errors that arise during pre-analytical, analytical, and post-analytical processes is difficult. We performed a pilot study, utilizing a multidimensional data reduction technique, to assess the utility of this method for identifying errors in laboratory data. We evaluated 13,670 individual patient records collected over a 2-month period from hospital inpatients and outpatients. We utilized those patient records that contained a complete set of 14 different biochemical analytes. We used two-dimensional generative topographic mapping to project the 14-dimensional record to a two-dimensional space. The use of a two-dimensional generative topographic mapping technique to plot multi-analyte patient data as a two-dimensional graph allows for the rapid identification of potentially anomalous data. Although we performed a retrospective analysis, this technique has the benefit of being able to assess laboratory-generated data in real time, allowing for the rapid identification and correction of anomalous data before they are released to the physician. In addition, serial laboratory multi-analyte data for an individual patient can also be plotted as a two-dimensional plot. This tool might also be useful for assessing patient wellbeing and prognosis.

Dimensionality Reduction of Hyperspectral Image with Graph-Based Discriminant Analysis Considering Spectral Similarity

Directory of Open Access Journals (Sweden)

Fubiao Feng

2017-03-01

Full Text Available Recently, graph embedding has drawn great attention for dimensionality reduction in hyperspectral imagery. For example, locality preserving projection (LPP utilizes typical Euclidean distance in a heat kernel to create an affinity matrix and projects the high-dimensional data into a lower-dimensional space. However, the Euclidean distance is not sufficiently correlated with intrinsic spectral variation of a material, which may result in inappropriate graph representation. In this work, a graph-based discriminant analysis with spectral similarity (denoted as GDA-SS measurement is proposed, which fully considers curves changing description among spectral bands. Experimental results based on real hyperspectral images demonstrate that the proposed method is superior to traditional methods, such as supervised LPP, and the state-of-the-art sparse graph-based discriminant analysis (SGDA.

ANALYSIS OF IMPACT ON COMPOSITE STRUCTURES WITH THE METHOD OF DIMENSIONALITY REDUCTION

Directory of Open Access Journals (Sweden)

Valentin L. Popov

2015-04-01

Full Text Available In the present paper, we discuss the impact of rigid profiles on continua with non-local criteria for plastic yield. For the important case of media whose hardness is inversely proportional to the indentation radius, we suggest a rigorous treatment based on the method of dimensionality reduction (MDR and study the example of indentation by a conical profile.

Dimensional reduction of 10d heterotic string effective lagrangian with higher derivative terms

International Nuclear Information System (INIS)

Lalak, Z.; Pawelczyk, J.

1989-11-01

Dimensional reduction of the 10d Supergravity-Yang-Mills theories containing up to four derivatives is described. Unexpected nondiagonal corrections to 4d gauge kinetic function and negative contributions to scalar potential are found. We analyzed the general structure of the resulting lagrangian and discuss the possible phenomenological consequences. (author)

Spectroscopically Enhanced Method and System for Multi-Factor Biometric Authentication

Science.gov (United States)

Pishva, Davar

This paper proposes a spectroscopic method and system for preventing spoofing of biometric authentication. One of its focus is to enhance biometrics authentication with a spectroscopic method in a multifactor manner such that a person's unique ‘spectral signatures’ or ‘spectral factors’ are recorded and compared in addition to a non-spectroscopic biometric signature to reduce the likelihood of imposter getting authenticated. By using the ‘spectral factors’ extracted from reflectance spectra of real fingers and employing cluster analysis, it shows how the authentic fingerprint image presented by a real finger can be distinguished from an authentic fingerprint image embossed on an artificial finger, or molded on a fingertip cover worn by an imposter. This paper also shows how to augment two widely used biometrics systems (fingerprint and iris recognition devices) with spectral biometrics capabilities in a practical manner and without creating much overhead or inconveniencing their users.

Changes of platelet GMP-140 in diabetic nephropathy and its multi-factor regression analysis

International Nuclear Information System (INIS)

Wang Zizheng; Du Tongxin; Wang Shukui

2001-01-01

The relation of platelet GMP-140 and its related factors with diabetic nephropathy was studied. 144 patients of diabetic mellitus without nephropathy (group without DN, mean suffering duration of 25.5 +- 18.6 months); 80 with diabetic nephropathy (group DN, mean suffering duration of 58.7 +- 31.6 months) and 50 normal controls were chosen in the research. Platelet GMP-140, plasma α 1 -MG, β 2 -MG, and 24 hour urine albumin (ALB), IgG, α 1 -MG, β 2 -MG were detected by RIA, while HBA 1 C via chromatographic separation and FBG, PBG, Ch, TG, HDL, FG via biochemical methods. All the data had been processed with software on computer with t-test and linear regression, and multi-factor analysis were done also. The levels of platelet GMP-140, FG, DBP, TG, HBA 1 C and PBG in group DN were significantly higher than those of group without DN and normal control (P 0.05), while they were higher than those of normal controls. Multi-factor analysis of platelet GMP-140 with TG, DBP and HBA 1 C were performed in 80 patients with DN (P 1 C are the independent factors enhancing the activation of platelets. The disturbance of lipid metabolism in type II diabetic mellitus may also enhance the activation of platelets. Elevation of blood pressure may accelerate the initiation and deterioration of DN in which change of platelet GMP-140 is an independent factor. Elevation of HBA 1 C and blood glucose are related closely to the diabetic nephropathy

The equivalence of information-theoretic and likelihood-based methods for neural dimensionality reduction.

Directory of Open Access Journals (Sweden)

Ross S Williamson

2015-04-01

Full Text Available Stimulus dimensionality-reduction methods in neuroscience seek to identify a low-dimensional space of stimulus features that affect a neuron's probability of spiking. One popular method, known as maximally informative dimensions (MID, uses an information-theoretic quantity known as "single-spike information" to identify this space. Here we examine MID from a model-based perspective. We show that MID is a maximum-likelihood estimator for the parameters of a linear-nonlinear-Poisson (LNP model, and that the empirical single-spike information corresponds to the normalized log-likelihood under a Poisson model. This equivalence implies that MID does not necessarily find maximally informative stimulus dimensions when spiking is not well described as Poisson. We provide several examples to illustrate this shortcoming, and derive a lower bound on the information lost when spiking is Bernoulli in discrete time bins. To overcome this limitation, we introduce model-based dimensionality reduction methods for neurons with non-Poisson firing statistics, and show that they can be framed equivalently in likelihood-based or information-theoretic terms. Finally, we show how to overcome practical limitations on the number of stimulus dimensions that MID can estimate by constraining the form of the non-parametric nonlinearity in an LNP model. We illustrate these methods with simulations and data from primate visual cortex.

A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis.

Science.gov (United States)

Hayashi, Hideaki; Shibanoki, Taro; Shima, Keisuke; Kurita, Yuichi; Tsuji, Toshio

2015-12-01

This paper proposes a probabilistic neural network (NN) developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-series patterns. TSDCA involves the compression of high-dimensional time series into a lower dimensional space using a set of orthogonal transformations and the calculation of posterior probabilities based on a continuous-density hidden Markov model with a Gaussian mixture model expressed in the reduced-dimensional space. The analysis can be incorporated into an NN, which is named a time-series discriminant component network (TSDCN), so that parameters of dimensionality reduction and classification can be obtained simultaneously as network coefficients according to a backpropagation through time-based learning algorithm with the Lagrange multiplier method. The TSDCN is considered to enable high-accuracy classification of high-dimensional time-series patterns and to reduce the computation time taken for network training. The validity of the TSDCN is demonstrated for high-dimensional artificial data and electroencephalogram signals in the experiments conducted during the study.

The N=4 supersymmetric E8 gauge theory and coset space dimensional reduction

International Nuclear Information System (INIS)

Olive, D.; West, P.

1983-01-01

Reasons are given to suggest that the N=4 supersymmetric E 8 gauge theory be considered as a serious candidate for a physical theory. The symmetries of this theory are broken by a scheme based on coset space dimensional reduction. The resulting theory possesses four conventional generations of low-mass fermions together with their mirror particles. (orig.)

Denoising and dimensionality reduction of genomic data

Science.gov (United States)

Capobianco, Enrico

2005-05-01

Genomics represents a challenging research field for many quantitative scientists, and recently a vast variety of statistical techniques and machine learning algorithms have been proposed and inspired by cross-disciplinary work with computational and systems biologists. In genomic applications, the researcher deals with noisy and complex high-dimensional feature spaces; a wealth of genes whose expression levels are experimentally measured, can often be observed for just a few time points, thus limiting the available samples. This unbalanced combination suggests that it might be hard for standard statistical inference techniques to come up with good general solutions, likewise for machine learning algorithms to avoid heavy computational work. Thus, one naturally turns to two major aspects of the problem: sparsity and intrinsic dimensionality. These two aspects are studied in this paper, where for both denoising and dimensionality reduction, a very efficient technique, i.e., Independent Component Analysis, is used. The numerical results are very promising, and lead to a very good quality of gene feature selection, due to the signal separation power enabled by the decomposition technique. We investigate how the use of replicates can improve these results, and deal with noise through a stabilization strategy which combines the estimated components and extracts the most informative biological information from them. Exploiting the inherent level of sparsity is a key issue in genetic regulatory networks, where the connectivity matrix needs to account for the real links among genes and discard many redundancies. Most experimental evidence suggests that real gene-gene connections represent indeed a subset of what is usually mapped onto either a huge gene vector or a typically dense and highly structured network. Inferring gene network connectivity from the expression levels represents a challenging inverse problem that is at present stimulating key research in biomedical

Three-dimensional assemblies of graphene prepared by a novel chemical reduction-induced self-assembly method

KAUST Repository

Zhang, Lianbin; Chen, Guoying; Hedhili, Mohamed N.; Zhang, Hongnan; Wang, Peng

2012-01-01

In this study, three-dimensional (3D) graphene assemblies are prepared from graphene oxide (GO) by a facile in situ reduction-assembly method, using a novel, low-cost, and environment-friendly reducing medium which is a combination of oxalic acid

Exploring the effects of dimensionality reduction in deep networks for force estimation in robotic-assisted surgery

Science.gov (United States)

Aviles, Angelica I.; Alsaleh, Samar; Sobrevilla, Pilar; Casals, Alicia

2016-03-01

Robotic-Assisted Surgery approach overcomes the limitations of the traditional laparoscopic and open surgeries. However, one of its major limitations is the lack of force feedback. Since there is no direct interaction between the surgeon and the tissue, there is no way of knowing how much force the surgeon is applying which can result in irreversible injuries. The use of force sensors is not practical since they impose different constraints. Thus, we make use of a neuro-visual approach to estimate the applied forces, in which the 3D shape recovery together with the geometry of motion are used as input to a deep network based on LSTM-RNN architecture. When deep networks are used in real time, pre-processing of data is a key factor to reduce complexity and improve the network performance. A common pre-processing step is dimensionality reduction which attempts to eliminate redundant and insignificant information by selecting a subset of relevant features to use in model construction. In this work, we show the effects of dimensionality reduction in a real-time application: estimating the applied force in Robotic-Assisted Surgeries. According to the results, we demonstrated positive effects of doing dimensionality reduction on deep networks including: faster training, improved network performance, and overfitting prevention. We also show a significant accuracy improvement, ranging from about 33% to 86%, over existing approaches related to force estimation.

A Novel Four-Dimensional Energy-Saving and Emission-Reduction System and Its Linear Feedback Control

Directory of Open Access Journals (Sweden)

Minggang Wang

2012-01-01

Full Text Available This paper reports a new four-dimensional energy-saving and emission-reduction chaotic system. The system is obtained in accordance with the complicated relationship between energy saving and emission reduction, carbon emission, economic growth, and new energy development. The dynamics behavior of the system will be analyzed by means of Lyapunov exponents and equilibrium points. Linear feedback control methods are used to suppress chaos to unstable equilibrium. Numerical simulations are presented to show these results.

Rhythmic dynamics and synchronization via dimensionality reduction: application to human gait.

Directory of Open Access Journals (Sweden)

Jie Zhang

Full Text Available Reliable characterization of locomotor dynamics of human walking is vital to understanding the neuromuscular control of human locomotion and disease diagnosis. However, the inherent oscillation and ubiquity of noise in such non-strictly periodic signals pose great challenges to current methodologies. To this end, we exploit the state-of-the-art technology in pattern recognition and, specifically, dimensionality reduction techniques, and propose to reconstruct and characterize the dynamics accurately on the cycle scale of the signal. This is achieved by deriving a low-dimensional representation of the cycles through global optimization, which effectively preserves the topology of the cycles that are embedded in a high-dimensional Euclidian space. Our approach demonstrates a clear advantage in capturing the intrinsic dynamics and probing the subtle synchronization patterns from uni/bivariate oscillatory signals over traditional methods. Application to human gait data for healthy subjects and diabetics reveals a significant difference in the dynamics of ankle movements and ankle-knee coordination, but not in knee movements. These results indicate that the impaired sensory feedback from the feet due to diabetes does not influence the knee movement in general, and that normal human walking is not critically dependent on the feedback from the peripheral nervous system.

Reduction of infinite dimensional equations

Directory of Open Access Journals (Sweden)

Zhongding Li

2006-02-01

Full Text Available In this paper, we use the general Legendre transformation to show the infinite dimensional integrable equations can be reduced to a finite dimensional integrable Hamiltonian system on an invariant set under the flow of the integrable equations. Then we obtain the periodic or quasi-periodic solution of the equation. This generalizes the results of Lax and Novikov regarding the periodic or quasi-periodic solution of the KdV equation to the general case of isospectral Hamiltonian integrable equation. And finally, we discuss the AKNS hierarchy as a special example.

Supervised linear dimensionality reduction with robust margins for object recognition

Science.gov (United States)

Dornaika, F.; Assoum, A.

2013-01-01

Linear Dimensionality Reduction (LDR) techniques have been increasingly important in computer vision and pattern recognition since they permit a relatively simple mapping of data onto a lower dimensional subspace, leading to simple and computationally efficient classification strategies. Recently, many linear discriminant methods have been developed in order to reduce the dimensionality of visual data and to enhance the discrimination between different groups or classes. Many existing linear embedding techniques relied on the use of local margins in order to get a good discrimination performance. However, dealing with outliers and within-class diversity has not been addressed by margin-based embedding method. In this paper, we explored the use of different margin-based linear embedding methods. More precisely, we propose to use the concepts of Median miss and Median hit for building robust margin-based criteria. Based on such margins, we seek the projection directions (linear embedding) such that the sum of local margins is maximized. Our proposed approach has been applied to the problem of appearance-based face recognition. Experiments performed on four public face databases show that the proposed approach can give better generalization performance than the classic Average Neighborhood Margin Maximization (ANMM). Moreover, thanks to the use of robust margins, the proposed method down-grades gracefully when label outliers contaminate the training data set. In particular, we show that the concept of Median hit was crucial in order to get robust performance in the presence of outliers.

Quality management of airport services – An analysis of the multifactor structure of customer satisfaction

Directory of Open Access Journals (Sweden)

Josip Mikulić

2007-07-01

Full Text Available The purpose of this paper is to get an insight into the multifactor structure of satisfaction of the customers of a Croatian airport. Based on data from the primary research (n=1053, an importance-performance analysis was conducted that resulted in the categorization of airport services into the satisfaction factors according to Kano’s model of quality. Basic factors, performance factors and excitement factors were identified. The results of this analysis enrich the standard information basis which is obtained through customer satisfaction surveys. Furthermore, they represent a valuable resource for decision-making within the domain of service quality management.

The supersymmetric Adler-Bardeen theorem and regularization by dimensional reduction

International Nuclear Information System (INIS)

Ensign, P.; Mahanthappa, K.T.

1987-01-01

We examine the subtraction scheme dependence of the anomaly of the supersymmetric, gauge singlet axial current in pure and coupled supersymmetric Yang-Mills theories. Preserving supersymmetry and gauge invariance explicitly by using supersymmetric background field theory and dimensional reduction, we show that only the one-loop value of the axial anomaly is subtraction scheme independent, and that one can always define a subtraction scheme in which the Adler-Bardeen theorem is satisfied to all orders in perturbation theory. In general this subtraction scheme may be non-minimal, but in both the pure and the coupled theories, the Adler-Bardeen theorem is satisfied to two loops in minimal subtraction. (orig.)

On dimensional reduction over coset spaces

International Nuclear Information System (INIS)

Kapetanakis, D.; Zoupanos, G.

1990-01-01

Gauge theories defined in higher dimensions can be dimensionally reduced over coset spaces giving definite predictions for the resulting four-dimensional theory. We present the most interesting features of these theories as well as an attempt to construct a model with realistic low energy behaviour within this framework. (author)

Multifactor dimensionality reduction reveals a three-locus epistatic interaction associated with susceptibility to pulmonary tuberculosis

DEFF Research Database (Denmark)

Collins, Ryan L; Hu, Ting; Wejse, Christian

2013-01-01

for this problem. The goal of the present study was to apply MDR to mining high-order epistatic interactions in a population-based genetic study of tuberculosis (TB). Results The study used a previously published data set consisting of 19 candidate single-nucleotide polymorphisms (SNPs) in 321 pulmonary TB cases...

Fractional exclusion and braid statistics in one dimension: a study via dimensional reduction of Chern–Simons theory

International Nuclear Information System (INIS)

Ye, Fei; Marchetti, P A; Su, Z B; Yu, L

2017-01-01

The relation between braid and exclusion statistics is examined in one-dimensional systems, within the framework of Chern–Simons statistical transmutation in gauge invariant form with an appropriate dimensional reduction. If the matter action is anomalous, as for chiral fermions, a relation between braid and exclusion statistics can be established explicitly for both mutual and nonmutual cases. However, if it is not anomalous, the exclusion statistics of emergent low energy excitations is not necessarily connected to the braid statistics of the physical charged fields of the system. Finally, we also discuss the bosonization of one-dimensional anyonic systems through T-duality. (paper)

Discrete symmetries and coset space dimensional reduction

International Nuclear Information System (INIS)

Kapetanakis, D.; Zoupanos, G.

1989-01-01

We consider the discrete symmetries of all the six-dimensional coset spaces and we apply them in gauge theories defined in ten dimensions which are dimensionally reduced over these homogeneous spaces. Particular emphasis is given in the consequences of the discrete symmetries on the particle content as well as on the symmetry breaking a la Hosotani of the resulting four-dimensional theory. (orig.)

Computational genetic neuroanatomy of the developing mouse brain: dimensionality reduction, visualization, and clustering

Science.gov (United States)

2013-01-01

Background The structured organization of cells in the brain plays a key role in its functional efficiency. This delicate organization is the consequence of unique molecular identity of each cell gradually established by precise spatiotemporal gene expression control during development. Currently, studies on the molecular-structural association are beginning to reveal how the spatiotemporal gene expression patterns are related to cellular differentiation and structural development. Results In this article, we aim at a global, data-driven study of the relationship between gene expressions and neuroanatomy in the developing mouse brain. To enable visual explorations of the high-dimensional data, we map the in situ hybridization gene expression data to a two-dimensional space by preserving both the global and the local structures. Our results show that the developing brain anatomy is largely preserved in the reduced gene expression space. To provide a quantitative analysis, we cluster the reduced data into groups and measure the consistency with neuroanatomy at multiple levels. Our results show that the clusters in the low-dimensional space are more consistent with neuroanatomy than those in the original space. Conclusions Gene expression patterns and developing brain anatomy are closely related. Dimensionality reduction and visual exploration facilitate the study of this relationship. PMID:23845024

Three-dimensional porous hollow fibre copper electrodes for efficient and high-rate electrochemical carbon dioxide reduction

NARCIS (Netherlands)

Kas, Recep; Hummadi, Khalid Khazzal; Kortlever, Ruud; de Wit, Patrick; Milbrat, Alexander; Luiten-Olieman, Maria W.J.; Benes, Nieck Edwin; Koper, Marc T.M.; Mul, Guido

2016-01-01

Aqueous-phase electrochemical reduction of carbon dioxide requires an active, earth-abundant electrocatalyst, as well as highly efficient mass transport. Here we report the design of a porous hollow fibre copper electrode with a compact three-dimensional geometry, which provides a large area,

Fractional exclusion and braid statistics in one dimension: a study via dimensional reduction of Chern-Simons theory

Science.gov (United States)

Ye, Fei; Marchetti, P. A.; Su, Z. B.; Yu, L.

2017-09-01

The relation between braid and exclusion statistics is examined in one-dimensional systems, within the framework of Chern-Simons statistical transmutation in gauge invariant form with an appropriate dimensional reduction. If the matter action is anomalous, as for chiral fermions, a relation between braid and exclusion statistics can be established explicitly for both mutual and nonmutual cases. However, if it is not anomalous, the exclusion statistics of emergent low energy excitations is not necessarily connected to the braid statistics of the physical charged fields of the system. Finally, we also discuss the bosonization of one-dimensional anyonic systems through T-duality. Dedicated to the memory of Mario Tonin.

'Marginal Employment' and the Demand for Heterogenous Labour: Empirical Evidence from a Multi-factor Labour Demand Model for Germany

OpenAIRE

Ronny Freier; Viktor Steiner

2007-01-01

We develop a structural multi-factor labour demand model which distinguishes between eight labour categories including non-standard types of employment such as marginal employment. The model is estimated for both the number of workers and total working hours using a new panel data set. For unskilled and skilled workers in full-time employment, we find labour demand elasticities similar to previous estimates for the west German economy. Our new estimates of own-wage elasticities for marginal e...

Stochastic confinement and dimensional reduction. 1

International Nuclear Information System (INIS)

Ambjoern, J.; Olesen, P.; Peterson, C.

1984-03-01

By Monte Carlo calculations on a 16 4 lattice the authors investigate four dimensional SU(2) lattice guage theory with respect to the conjecture that at large distances this theory reduces approximately to two dimensional SU(2) lattice gauge theory. Good numerical evidence is found for this conjecture. As a by-product the SU(2) string tension is also measured and good agreement is found with scaling. The 'adjoint string tension' is also found to have a reasonable scaling behaviour. (Auth.)

Genetic effects of sterol regulatory element binding proteins and fatty acid-binding protein4 on the fatty acid composition of Korean cattle (Hanwoo

Directory of Open Access Journals (Sweden)

Dong-Yep Oh

2017-02-01

Full Text Available Objective This study identifies single-nucleotide polymorphisms (SNP or gene combinations that affect the flavor and quality of Korean cattle (Hanwoo by using the SNP Harvester method. Methods Four economic traits (oleic acid [C18:1], saturated fatty acids, monounsaturated fatty acids, and marbling score were adjusted for environmental factors in order to focus solely on genetic effects. The SNP Harvester method was used to investigate gene combinations (two-way gene interactions associated with these economic traits. Further, a multifactor dimensionality reduction method was used to identify superior genotypes in gene combinations. Results Table 3 to 4 show the analysis results for differences between superior genotypes and others for selected major gene combinations using the multifactor dimensionality reduction method. Environmental factors were adjusted for in order to evaluate only the genetic effect. Table 5 shows the adjustment effect by comparing the accuracy before and after correction in two-way gene interactions. Conclusion The g.3977-325 T>C and (g.2988 A>G, g.3977-325 T>C combinations of fatty acid-binding protein4 were the superior gene, and the superior genotype combinations across all economic traits were the CC genotype at g.3977-325 T>C and the AACC, GACC, GGCC genotypes of (g.2988 A>G, g.3977-325 T>C.

METHOD OF DIMENSIONALITY REDUCTION IN CONTACT MECHANICS AND FRICTION: A USERS HANDBOOK. I. AXIALLY-SYMMETRIC CONTACTS

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Valentin L. Popov

2014-04-01

Full Text Available The Method of Dimensionality Reduction (MDR is a method of calculation and simulation of contacts of elastic and viscoelastic bodies. It consists essentially of two simple steps: (a substitution of the three-dimensional continuum by a uniquely defined one-dimensional linearly elastic or viscoelastic foundation (Winkler foundation and (b transformation of the three-dimensional profile of the contacting bodies by means of the MDR-transformation. As soon as these two steps are completed, the contact problem can be considered to be solved. For axial symmetric contacts, only a small calculation by hand is required which does not exceed elementary calculus and will not be a barrier for any practically-oriented engineer. Alternatively, the MDR can be implemented numerically, which is almost trivial due to the independence of the foundation elements. In spite of their simplicity, all the results are exact. The present paper is a short practical guide to the MDR.

Dimensionality reduction based on distance preservation to local mean for symmetric positive definite matrices and its application in brain-computer interfaces

Science.gov (United States)

Davoudi, Alireza; Shiry Ghidary, Saeed; Sadatnejad, Khadijeh

2017-06-01

Objective. In this paper, we propose a nonlinear dimensionality reduction algorithm for the manifold of symmetric positive definite (SPD) matrices that considers the geometry of SPD matrices and provides a low-dimensional representation of the manifold with high class discrimination in a supervised or unsupervised manner. Approach. The proposed algorithm tries to preserve the local structure of the data by preserving distances to local means (DPLM) and also provides an implicit projection matrix. DPLM is linear in terms of the number of training samples. Main results. We performed several experiments on the multi-class dataset IIa from BCI competition IV and two other datasets from BCI competition III including datasets IIIa and IVa. The results show that our approach as dimensionality reduction technique—leads to superior results in comparison with other competitors in the related literature because of its robustness against outliers and the way it preserves the local geometry of the data. Significance. The experiments confirm that the combination of DPLM with filter geodesic minimum distance to mean as the classifier leads to superior performance compared with the state of the art on brain-computer interface competition IV dataset IIa. Also the statistical analysis shows that our dimensionality reduction method performs significantly better than its competitors.

N=2-Maxwell-Chern-Simons model with anomalous magnetic moment coupling via dimensional reduction

International Nuclear Information System (INIS)

Christiansen, H.R.; Cunha, M.S.; Helayel Neto, Jose A.; Manssur, L.R.U; Nogueira, A.L.M.A.

1998-02-01

An N=1-supersymmetric version of the Cremmer-Scherk-Kalb-Ramond model with non-minimal coupling to matter is built up both in terms of superfields and in a component field formalism. By adopting a dimensional reduction procedure, the N=2-D=3 counterpart of the model comes out, with two main features: a genuine (diagonal) Chern-Simons term and an anomalous magnetic moment coupling between matter and the gauge potential. (author)

Transformative piezoelectric enhancement of P(VDF-TrFE) synergistically driven by nanoscale dimensional reduction and thermal treatment.

Science.gov (United States)

Ico, G; Myung, A; Kim, B S; Myung, N V; Nam, J

2018-02-08

Despite the significant potential of organic piezoelectric materials in the electro-mechanical or mechano-electrical applications that require light and flexible material properties, the intrinsically low piezoelectric performance as compared to traditional inorganic materials has limited their full utilization. In this study, we demonstrate that dimensional reduction of poly(vinylidene fluoride trifluoroethylene) (P(VDF-TrFE)) at the nanoscale by electrospinning, combined with an appropriate thermal treatment, induces a transformative enhancement in piezoelectric performance. Specifically, the piezoelectric coefficient (d 33 ) reached up to -108 pm V -1 , approaching that of inorganic counterparts. Electrospun mats composed of thermo-treated 30 nm nanofibers with a thickness of 15 μm produced a consistent peak-to-peak voltage of 38.5 V and a power output of 74.1 μW at a strain of 0.26% while sustaining energy production over 10k repeated actuations. The exceptional piezoelectric performance was realized by the enhancement of piezoelectric dipole alignment and the materialization of flexoelectricity, both from the synergistic effects of dimensional reduction and thermal treatment. Our findings suggest that dimensionally controlled and thermally treated electrospun P(VDF-TrFE) nanofibers provide an opportunity to exploit their flexibility and durability for mechanically challenging applications while matching the piezoelectric performance of brittle, inorganic piezoelectric materials.

The multi-factor energy input–output model

International Nuclear Information System (INIS)

Guevara, Zeus; Domingos, Tiago

2017-01-01

Energy input–output analysis (EIO analysis) is a noteworthy tool for the analysis of the role of energy in the economy. However, it has relied on models that provide a limited description of energy flows in the economic system and do not allow an adequate analysis of energy efficiency. This paper introduces a novel energy input–output model, the multi-factor energy input–output model (MF-EIO model), which is obtained from a partitioning of a hybrid-unit input–output system of the economy. This model improves on current models by describing the energy flows according to the processes of energy conversion and the levels of energy use in the economy. It characterizes the vector of total energy output as a function of seven factors: two energy efficiency indicators; two characteristics of end-use energy consumption; and three economic features of the rest of the economy. Moreover, it is consistent with the standard model for EIO analysis, i.e., the hybrid-unit model. This paper also introduces an approximate version of the MF-EIO model, which is equivalent to the former under equal energy prices for industries and final consumers, but requires less data processing. The latter is composed by two linked models: a model of the energy sector in physical units, and a model of the rest of the economy in monetary units. In conclusion, the proposed modelling framework improves EIO analysis and extends EIO applications to the accounting for energy efficiency of the economy. - Highlights: • A novel energy input–output model is introduced. • It allows a more adequate analysis of energy flows than current models. • It describes energy flows according to processes of energy conversion and use. • It can be used for other environmental applications (material use and emissions). • An approximate version of the model is introduced, simpler and less data intensive.

Vehicle Color Recognition with Vehicle-Color Saliency Detection and Dual-Orientational Dimensionality Reduction of CNN Deep Features

Science.gov (United States)

Zhang, Qiang; Li, Jiafeng; Zhuo, Li; Zhang, Hui; Li, Xiaoguang

2017-12-01

Color is one of the most stable attributes of vehicles and often used as a valuable cue in some important applications. Various complex environmental factors, such as illumination, weather, noise and etc., result in the visual characteristics of the vehicle color being obvious diversity. Vehicle color recognition in complex environments has been a challenging task. The state-of-the-arts methods roughly take the whole image for color recognition, but many parts of the images such as car windows; wheels and background contain no color information, which will have negative impact on the recognition accuracy. In this paper, a novel vehicle color recognition method using local vehicle-color saliency detection and dual-orientational dimensionality reduction of convolutional neural network (CNN) deep features has been proposed. The novelty of the proposed method includes two parts: (1) a local vehicle-color saliency detection method has been proposed to determine the vehicle color region of the vehicle image and exclude the influence of non-color regions on the recognition accuracy; (2) dual-orientational dimensionality reduction strategy has been designed to greatly reduce the dimensionality of deep features that are learnt from CNN, which will greatly mitigate the storage and computational burden of the subsequent processing, while improving the recognition accuracy. Furthermore, linear support vector machine is adopted as the classifier to train the dimensionality reduced features to obtain the recognition model. The experimental results on public dataset demonstrate that the proposed method can achieve superior recognition performance over the state-of-the-arts methods.

Features in chemical kinetics. I. Signatures of self-emerging dimensional reduction from a general format of the evolution law.

Science.gov (United States)

Nicolini, Paolo; Frezzato, Diego

2013-06-21

Simplification of chemical kinetics description through dimensional reduction is particularly important to achieve an accurate numerical treatment of complex reacting systems, especially when stiff kinetics are considered and a comprehensive picture of the evolving system is required. To this aim several tools have been proposed in the past decades, such as sensitivity analysis, lumping approaches, and exploitation of time scales separation. In addition, there are methods based on the existence of the so-called slow manifolds, which are hyper-surfaces of lower dimension than the one of the whole phase-space and in whose neighborhood the slow evolution occurs after an initial fast transient. On the other hand, all tools contain to some extent a degree of subjectivity which seems to be irremovable. With reference to macroscopic and spatially homogeneous reacting systems under isothermal conditions, in this work we shall adopt a phenomenological approach to let self-emerge the dimensional reduction from the mathematical structure of the evolution law. By transforming the original system of polynomial differential equations, which describes the chemical evolution, into a universal quadratic format, and making a direct inspection of the high-order time-derivatives of the new dynamic variables, we then formulate a conjecture which leads to the concept of an "attractiveness" region in the phase-space where a well-defined state-dependent rate function ω has the simple evolution ω[over dot]=-ω(2) along any trajectory up to the stationary state. This constitutes, by itself, a drastic dimensional reduction from a system of N-dimensional equations (being N the number of chemical species) to a one-dimensional and universal evolution law for such a characteristic rate. Step-by-step numerical inspections on model kinetic schemes are presented. In the companion paper [P. Nicolini and D. Frezzato, J. Chem. Phys. 138, 234102 (2013)] this outcome will be naturally related to the

Dimensionality Reduction for Hyperspectral Data Based on Class-Aware Tensor Neighborhood Graph and Patch Alignment.

Science.gov (United States)

Gao, Yang; Wang, Xuesong; Cheng, Yuhu; Wang, Z Jane

2015-08-01

To take full advantage of hyperspectral information, to avoid data redundancy and to address the curse of dimensionality concern, dimensionality reduction (DR) becomes particularly important to analyze hyperspectral data. Exploring the tensor characteristic of hyperspectral data, a DR algorithm based on class-aware tensor neighborhood graph and patch alignment is proposed here. First, hyperspectral data are represented in the tensor form through a window field to keep the spatial information of each pixel. Second, using a tensor distance criterion, a class-aware tensor neighborhood graph containing discriminating information is obtained. In the third step, employing the patch alignment framework extended to the tensor space, we can obtain global optimal spectral-spatial information. Finally, the solution of the tensor subspace is calculated using an iterative method and low-dimensional projection matrixes for hyperspectral data are obtained accordingly. The proposed method effectively explores the spectral and spatial information in hyperspectral data simultaneously. Experimental results on 3 real hyperspectral datasets show that, compared with some popular vector- and tensor-based DR algorithms, the proposed method can yield better performance with less tensor training samples required.

Multifactor Assessment of Metabolic Syndrome Risk in Uzbek Children and Adolescents with Obesity

Directory of Open Access Journals (Sweden)

Gulnara N. Rakhimova

2016-03-01

Full Text Available Metabolic syndrome (MetS contributes to early atherosclerotic changes of blood vessels and type 2 diabetes mellitusnot only among adults, but among children and adolescents, causing onset and progression of severe diseases resulting in early disablement and death. Multifactor analysis of MetS risk in Uzbek children and adolescents with exogenous-constitutional obesity (ECO was the purpose of the study. The study included 100 Uzbek children and adolescents with ECO aged from 6 to 16 (mean age 11.7±0.25 years—54(54.0% boys and 46(46.0% girls. Prognostic matrix was made up by means of a modification of Bayesian probability by E. Shigan (1986. Mathematical analysis confirmed a high degree of risk for MetS onset and progression in obese patients with disorders of lipid profile and hemodynamics. MetS risk is 8.2 times higher with levels of HDL-C 3.0, HbA1c >6.7%, and obesity onset before 5 years of age.

Stochastic confinement and dimensional reduction. Pt. 1

International Nuclear Information System (INIS)

Ambjoern, J.; Olesen, P.; Peterson, C.

1984-01-01

By Monte Carlo calculations on a 12 4 lattice we investigate four-dimensional SU(2) lattice gauge theory with respect to the conjecture that at large distances this theory reduces approximately to two-dimensional SU(2) lattice gauge theory. We find good numerical evidence for this conjecture. As a by-product we also measure the SU(2) string tension and find reasonable agreement with scaling. The 'adjoint string tension' is also found to have a reasonable scaling behaviour. (orig.)

Research progress in machine learning methods for gene-gene interaction detection.

Science.gov (United States)

Peng, Zhe-Ye; Tang, Zi-Jun; Xie, Min-Zhu

2018-03-20

Complex diseases are results of gene-gene and gene-environment interactions. However, the detection of high-dimensional gene-gene interactions is computationally challenging. In the last two decades, machine-learning approaches have been developed to detect gene-gene interactions with some successes. In this review, we summarize the progress in research on machine learning methods, as applied to gene-gene interaction detection. It systematically examines the principles and limitations of the current machine learning methods used in genome wide association studies (GWAS) to detect gene-gene interactions, such as neural networks (NN), random forest (RF), support vector machines (SVM) and multifactor dimensionality reduction (MDR), and provides some insights on the future research directions in the field.

A Novel Medical Freehand Sketch 3D Model Retrieval Method by Dimensionality Reduction and Feature Vector Transformation

Directory of Open Access Journals (Sweden)

Zhang Jing

2016-01-01

Full Text Available To assist physicians to quickly find the required 3D model from the mass medical model, we propose a novel retrieval method, called DRFVT, which combines the characteristics of dimensionality reduction (DR and feature vector transformation (FVT method. The DR method reduces the dimensionality of feature vector; only the top M low frequency Discrete Fourier Transform coefficients are retained. The FVT method does the transformation of the original feature vector and generates a new feature vector to solve the problem of noise sensitivity. The experiment results demonstrate that the DRFVT method achieves more effective and efficient retrieval results than other proposed methods.

Water-Induced Dimensionality Reduction in Metal-Halide Perovskites

KAUST Repository

Turedi, Bekir; Lee, Kwangjae; Dursun, Ibrahim; Alamer, Badriah Jaber; Wu, Zhennan; Alarousu, Erkki; Mohammed, Omar F.; Cho, Namchul; Bakr, Osman

2018-01-01

. Here we employ water to directly transform films of the three-dimensional (3D) perovskite CsPbBr3 to stable two-dimensional (2D) perovskite-related CsPb2Br5. A sequential dissolution-recrystallization process governs this water induced transformation

Multifactor investigation of relative postirradiation changes in various types of behavioural reactions in rats

International Nuclear Information System (INIS)

Davydov, B.I.; Tikhonchuk, V.S.; Karpov, V.N.; Ushakov, I.B.

1989-01-01

The use of the methods of multifactor, orthogonal and composition planning in studying the behavioural disturbances in rats after γ-irradiation with doses of 0.258 to 1.29 C/kg and the application of the proposed method of discrimination of effects by empirical models permitted to establish the informative and adequate dependences of the probability of these disturbances on dose of nonuniform irradiation and the degree of strengthening of the conditioned reflex. Within the range of the studied factors both the value of the dose of whole-body irradiation and the degree of strengthening of the conditioned reflex significantly affected the probability of fulfilling the task by the animals the significance of the radiation dose being several times higher. The effects of the interaction of the two factors, that is, irradiation and the radiation affection, were insignificant in changing the behavioural reactions under study

Efficacy and safety of a multifactor intervention to improve therapeutic adherence in patients with chronic obstructive pulmonary disease (COPD: protocol for the ICEPOC study

Directory of Open Access Journals (Sweden)

Prados-Torres Daniel

2011-02-01

Full Text Available Abstract Background Low therapeutic adherence to medication is very common. Clinical effectiveness is related to dose rate and route of administration and so poor therapeutic adherence can reduce the clinical benefit of treatment. The therapeutic adherence of patients with chronic obstructive pulmonary disease (COPD is extremely poor according to most studies. The research about COPD adherence has mainly focussed on quantifying its effect, and few studies have researched factors that affect non-adherence. Our study will evaluate the effectiveness of a multifactor intervention to improve the therapeutic adherence of COPD patients. Methods/Design A randomized controlled clinical trial with 140 COPD diagnosed patients selected by a non-probabilistic method of sampling. Subjects will be randomly allocated into two groups, using the block randomization technique. Every patient in each group will be visited four times during the year of the study. Intervention: Motivational aspects related to adherence (beliefs and behaviour: group and individual interviews; cognitive aspects: information about illness; skills: inhaled technique training. Reinforcement of the cognitive-emotional aspects and inhaled technique training will be carried out in all visits of the intervention group. Discussion Adherence to a prescribed treatment involves a behavioural change. Cognitive, emotional and motivational aspects influence this change and so we consider the best intervention procedure to improve adherence would be a cognitive and emotional strategy which could be applied in daily clinical practice. Our hypothesis is that the application of a multifactor intervention (COPD information, dose reminders and reinforcing audiovisual material, motivational aspects and inhalation technique training to COPD patients taking inhaled treatment will give a 25% increase in the number of patients showing therapeutic adherence in this group compared to the control group. We will

Multichannel transfer function with dimensionality reduction

KAUST Repository

Kim, Han Suk; Schulze, Jü rgen P.; Cone, Angela C.; Sosinsky, Gina E.; Martone, Maryann E.

2010-01-01

. Our new method provides a framework to combine multiple approaches and pushes the boundary of gradient-based transfer functions to multiple channels, while still keeping the dimensionality of transfer functions to a manageable level, i.e., a maximum

Dual dimensionality reduction reveals independent encoding of motor features in a muscle synergy for insect flight control.

Science.gov (United States)

Sponberg, Simon; Daniel, Thomas L; Fairhall, Adrienne L

2015-04-01

What are the features of movement encoded by changing motor commands? Do motor commands encode movement independently or can they be represented in a reduced set of signals (i.e. synergies)? Motor encoding poses a computational and practical challenge because many muscles typically drive movement, and simultaneous electrophysiology recordings of all motor commands are typically not available. Moreover, during a single locomotor period (a stride or wingstroke) the variation in movement may have high dimensionality, even if only a few discrete signals activate the muscles. Here, we apply the method of partial least squares (PLS) to extract the encoded features of movement based on the cross-covariance of motor signals and movement. PLS simultaneously decomposes both datasets and identifies only the variation in movement that relates to the specific muscles of interest. We use this approach to explore how the main downstroke flight muscles of an insect, the hawkmoth Manduca sexta, encode torque during yaw turns. We simultaneously record muscle activity and turning torque in tethered flying moths experiencing wide-field visual stimuli. We ask whether this pair of muscles acts as a muscle synergy (a single linear combination of activity) consistent with their hypothesized function of producing a left-right power differential. Alternatively, each muscle might individually encode variation in movement. We show that PLS feature analysis produces an efficient reduction of dimensionality in torque variation within a wingstroke. At first, the two muscles appear to behave as a synergy when we consider only their wingstroke-averaged torque. However, when we consider the PLS features, the muscles reveal independent encoding of torque. Using these features we can predictably reconstruct the variation in torque corresponding to changes in muscle activation. PLS-based feature analysis provides a general two-sided dimensionality reduction that reveals encoding in high dimensional

Dual dimensionality reduction reveals independent encoding of motor features in a muscle synergy for insect flight control.

Directory of Open Access Journals (Sweden)

Simon Sponberg

2015-04-01

Full Text Available What are the features of movement encoded by changing motor commands? Do motor commands encode movement independently or can they be represented in a reduced set of signals (i.e. synergies? Motor encoding poses a computational and practical challenge because many muscles typically drive movement, and simultaneous electrophysiology recordings of all motor commands are typically not available. Moreover, during a single locomotor period (a stride or wingstroke the variation in movement may have high dimensionality, even if only a few discrete signals activate the muscles. Here, we apply the method of partial least squares (PLS to extract the encoded features of movement based on the cross-covariance of motor signals and movement. PLS simultaneously decomposes both datasets and identifies only the variation in movement that relates to the specific muscles of interest. We use this approach to explore how the main downstroke flight muscles of an insect, the hawkmoth Manduca sexta, encode torque during yaw turns. We simultaneously record muscle activity and turning torque in tethered flying moths experiencing wide-field visual stimuli. We ask whether this pair of muscles acts as a muscle synergy (a single linear combination of activity consistent with their hypothesized function of producing a left-right power differential. Alternatively, each muscle might individually encode variation in movement. We show that PLS feature analysis produces an efficient reduction of dimensionality in torque variation within a wingstroke. At first, the two muscles appear to behave as a synergy when we consider only their wingstroke-averaged torque. However, when we consider the PLS features, the muscles reveal independent encoding of torque. Using these features we can predictably reconstruct the variation in torque corresponding to changes in muscle activation. PLS-based feature analysis provides a general two-sided dimensionality reduction that reveals encoding in

Dual Dimensionality Reduction Reveals Independent Encoding of Motor Features in a Muscle Synergy for Insect Flight Control

Science.gov (United States)

Sponberg, Simon; Daniel, Thomas L.; Fairhall, Adrienne L.

2015-01-01

What are the features of movement encoded by changing motor commands? Do motor commands encode movement independently or can they be represented in a reduced set of signals (i.e. synergies)? Motor encoding poses a computational and practical challenge because many muscles typically drive movement, and simultaneous electrophysiology recordings of all motor commands are typically not available. Moreover, during a single locomotor period (a stride or wingstroke) the variation in movement may have high dimensionality, even if only a few discrete signals activate the muscles. Here, we apply the method of partial least squares (PLS) to extract the encoded features of movement based on the cross-covariance of motor signals and movement. PLS simultaneously decomposes both datasets and identifies only the variation in movement that relates to the specific muscles of interest. We use this approach to explore how the main downstroke flight muscles of an insect, the hawkmoth Manduca sexta, encode torque during yaw turns. We simultaneously record muscle activity and turning torque in tethered flying moths experiencing wide-field visual stimuli. We ask whether this pair of muscles acts as a muscle synergy (a single linear combination of activity) consistent with their hypothesized function of producing a left-right power differential. Alternatively, each muscle might individually encode variation in movement. We show that PLS feature analysis produces an efficient reduction of dimensionality in torque variation within a wingstroke. At first, the two muscles appear to behave as a synergy when we consider only their wingstroke-averaged torque. However, when we consider the PLS features, the muscles reveal independent encoding of torque. Using these features we can predictably reconstruct the variation in torque corresponding to changes in muscle activation. PLS-based feature analysis provides a general two-sided dimensionality reduction that reveals encoding in high dimensional

Multi-factor challenge/response approach for remote biometric authentication

Science.gov (United States)

Al-Assam, Hisham; Jassim, Sabah A.

2011-06-01

Although biometric authentication is perceived to be more reliable than traditional authentication schemes, it becomes vulnerable to many attacks when it comes to remote authentication over open networks and raises serious privacy concerns. This paper proposes a biometric-based challenge-response approach to be used for remote authentication between two parties A and B over open networks. In the proposed approach, a remote authenticator system B (e.g. a bank) challenges its client A who wants to authenticate his/her self to the system by sending a one-time public random challenge. The client A responds by employing the random challenge along with secret information obtained from a password and a token to produce a one-time cancellable representation of his freshly captured biometric sample. The one-time biometric representation, which is based on multi-factor, is then sent back to B for matching. Here, we argue that eavesdropping of the one-time random challenge and/or the resulting one-time biometric representation does not compromise the security of the system, and no information about the original biometric data is leaked. In addition to securing biometric templates, the proposed protocol offers a practical solution for the replay attack on biometric systems. Moreover, we propose a new scheme for generating a password-based pseudo random numbers/permutation to be used as a building block in the proposed approach. The proposed scheme is also designed to provide protection against repudiation. We illustrate the viability and effectiveness of the proposed approach by experimental results based on two biometric modalities: fingerprint and face biometrics.

Implementation of the Principal Component Analysis onto High-Performance Computer Facilities for Hyperspectral Dimensionality Reduction: Results and Comparisons

Directory of Open Access Journals (Sweden)

Ernestina Martel

2018-06-01

Full Text Available Dimensionality reduction represents a critical preprocessing step in order to increase the efficiency and the performance of many hyperspectral imaging algorithms. However, dimensionality reduction algorithms, such as the Principal Component Analysis (PCA, suffer from their computationally demanding nature, becoming advisable for their implementation onto high-performance computer architectures for applications under strict latency constraints. This work presents the implementation of the PCA algorithm onto two different high-performance devices, namely, an NVIDIA Graphics Processing Unit (GPU and a Kalray manycore, uncovering a highly valuable set of tips and tricks in order to take full advantage of the inherent parallelism of these high-performance computing platforms, and hence, reducing the time that is required to process a given hyperspectral image. Moreover, the achieved results obtained with different hyperspectral images have been compared with the ones that were obtained with a field programmable gate array (FPGA-based implementation of the PCA algorithm that has been recently published, providing, for the first time in the literature, a comprehensive analysis in order to highlight the pros and cons of each option.

Recursions of Symmetry Orbits and Reduction without Reduction

Directory of Open Access Journals (Sweden)

Andrei A. Malykh

2011-04-01

Full Text Available We consider a four-dimensional PDE possessing partner symmetries mainly on the example of complex Monge-Ampère equation (CMA. We use simultaneously two pairs of symmetries related by a recursion relation, which are mutually complex conjugate for CMA. For both pairs of partner symmetries, using Lie equations, we introduce explicitly group parameters as additional variables, replacing symmetry characteristics and their complex conjugates by derivatives of the unknown with respect to group parameters. We study the resulting system of six equations in the eight-dimensional space, that includes CMA, four equations of the recursion between partner symmetries and one integrability condition of this system. We use point symmetries of this extended system for performing its symmetry reduction with respect to group parameters that facilitates solving the extended system. This procedure does not imply a reduction in the number of physical variables and hence we end up with orbits of non-invariant solutions of CMA, generated by one partner symmetry, not used in the reduction. These solutions are determined by six linear equations with constant coefficients in the five-dimensional space which are obtained by a three-dimensional Legendre transformation of the reduced extended system. We present algebraic and exponential examples of such solutions that govern Legendre-transformed Ricci-flat Kähler metrics with no Killing vectors. A similar procedure is briefly outlined for Husain equation.

The Multi-factor Predictive Seis &Gis Model of Ecological, Genetical, Population Health Risk and Bio-geodynamic Processes In Geopathogenic Zones

Science.gov (United States)

Bondarenko, Y.

I. Goal and Scope. Human birth rate decrease, death-rate growth and increase of mu- tagenic deviations risk take place in geopathogenic and anthropogenic hazard zones. Such zones create unfavourable conditions for reproductive process of future genera- tions. These negative trends should be considered as a protective answer of the com- plex biosocial system to the appearance of natural and anthropogenic risk factors that are unfavourable for human health. The major goals of scientific evaluation and de- crease of risk of appearance of hazardous processes on the territory of Dnipropetrovsk, along with creation of the multi-factor predictive Spirit-Energy-Information Space "SEIS" & GIS Model of ecological, genetical and population health risk in connection with dangerous bio-geodynamic processes, were: multi-factor modeling and correla- tion of natural and anthropogenic environmental changes and those of human health; determination of indicators that show the risk of destruction structures appearance on different levels of organization and functioning of the city ecosystem (geophys- ical and geochemical fields, soil, hydrosphere, atmosphere, biosphere); analysis of regularities of natural, anthropogenic, and biological rhythms' interactions. II. Meth- ods. The long spatio-temporal researches (Y. Bondarenko, 1996, 2000) have proved that the ecological, genetic and epidemiological processes are in connection with de- velopment of dangerous bio-geophysical and bio-geodynamic processes. Mathemat- ical processing of space photos, lithogeochemical and geophysical maps with use of JEIS o and ERDAS o computer systems was executed at the first stage of forma- tion of multi-layer geoinformation model "Dnipropetrovsk ARC View GIS o. The multi-factor nonlinear correlation between solar activity and cosmic ray variations, geophysical, geodynamic, geochemical, atmospheric, technological, biological, socio- economical processes and oncologic case rate frequency, general and primary

The use of the bi-factor model to test the uni-dimensionality of a battery of reasoning tests.

Science.gov (United States)

Primi, Ricardo; Rocha da Silva, Marjorie Cristina; Rodrigues, Priscila; Muniz, Monalisa; Almeida, Leandro S

2013-02-01

The Battery of Reasoning Tests 5 (BPR-5) aims to assess the reasoning ability of individuals, using sub-tests with different formats and contents that require basic processes of inductive and deductive reasoning for their resolution. The BPR has three sequential forms: BPR-5i (for children from first to fifth grade), BPR-5 - Form A (for children from sixth to eighth grade) and BPR-5 - form B (for high school and undergraduate students). The present study analysed 412 questionnaires concerning BPR-5i, 603 questionnaires concerning BPR-5 - Form A and 1748 questionnaires concerning BPR-5 - Form B. The main goal was to test the uni-dimensionality of the battery and its tests in relation to items using the bi-factor model. Results suggest that the g factor loadings (extracted by the uni-dimensional model) do not change when the data is adjusted for a more flexible multi-factor model (bi-factor model). A general reasoning factor underlying different contents items is supported.

Three-dimensional iron, nitrogen-doped carbon foams as efficient electrocatalysts for oxygen reduction reaction in alkaline solution

International Nuclear Information System (INIS)

Ma, Yanjiao; Wang, Hui; Feng, Hanqing; Ji, Shan; Mao, Xuefeng; Wang, Rongfang

2014-01-01

Graphical abstract: Three-dimentional Fe, N-doped carbon foams prepared by two steps exhibited comparable catalytic activity for oxygen reduction reaction to commercial Pt/C due to the unique structure and the synergistic effect of Fe and N atoms. - Highlights: • Three-dimensional Fe, N-doped carbon foam (3D-CF) were prepared. • 3D-CF exhibits comparable catalytic activity to Pt/C for oxygen reduction reaction. • The enhanced activity of 3D-CF results of its unique structure. - Abstract: Three-dimensional (3D) Fe, N-doped carbon foams (3D-CF) as efficient cathode catalysts for the oxygen reduction reaction (ORR) in alkaline solution are reported. The 3D-CF exhibit interconnected hierarchical pore structure. In addition, Fe, N-doped carbon without porous strucuture (Fe-N-C) and 3D N-doped carbon without Fe (3D-CF’) are prepared to verify the electrocatalytic activity of 3D-CF. The electrocatalytic performance of as-prepared 3D-CF for ORR shows that the onset potential on 3D-CF electrode positively shifts about 41 mV than those of 3D-CF’ and Fe-N-C respectively. In addition, the onset potential on 3D-CF electrode for ORR is about 27 mV more negative than that on commercial Pt/C electrode. 3D-CF also show better methanol tolerance and durability than commercial Pt/C catalyst. These results show that to synthesize 3D hierarchical pores with high specific surface area is an efficient way to improve the ORR performance

Machine Learning Based Dimensionality Reduction Facilitates Ligand Diffusion Paths Assessment: A Case of Cytochrome P450cam.

Science.gov (United States)

Rydzewski, J; Nowak, W

2016-04-12

In this work we propose an application of a nonlinear dimensionality reduction method to represent the high-dimensional configuration space of the ligand-protein dissociation process in a manner facilitating interpretation. Rugged ligand expulsion paths are mapped into 2-dimensional space. The mapping retains the main structural changes occurring during the dissociation. The topological similarity of the reduced paths may be easily studied using the Fréchet distances, and we show that this measure facilitates machine learning classification of the diffusion pathways. Further, low-dimensional configuration space allows for identification of residues active in transport during the ligand diffusion from a protein. The utility of this approach is illustrated by examination of the configuration space of cytochrome P450cam involved in expulsing camphor by means of enhanced all-atom molecular dynamics simulations. The expulsion trajectories are sampled and constructed on-the-fly during molecular dynamics simulations using the recently developed memetic algorithms [ Rydzewski, J.; Nowak, W. J. Chem. Phys. 2015 , 143 ( 12 ), 124101 ]. We show that the memetic algorithms are effective for enforcing the ligand diffusion and cavity exploration in the P450cam-camphor complex. Furthermore, we demonstrate that machine learning techniques are helpful in inspecting ligand diffusion landscapes and provide useful tools to examine structural changes accompanying rare events.

Analysis and application of a novel three-dimensional energy-saving and emission-reduction dynamic evolution system

International Nuclear Information System (INIS)

Fang, Guochang; Tian, Lixin; Sun, Mei; Fu, Min

2012-01-01

A novel three-dimensional energy-saving and emission-reduction chaotic system is proposed, which has not yet been reported in present literature. The system is established in accordance with the complicated relationship between energy-saving and emission-reduction, carbon emissions and economic growth. The dynamic behavior of the system is analyzed by means of Lyapunov exponents and bifurcation diagrams. With undetermined coefficient method, expressions of homoclinic orbits of the system are obtained. The Šilnikov theorem guarantees that the system has Smale horseshoes and the horseshoes chaos. Artificial neural network (ANN) is used to identify the quantitative coefficients in the simulation models according to the statistical data of China, and an empirical study of the real system is carried out with the results in perfect agreement with actual situation. It is found that the sooner and more perfect energy-saving and emission-reduction is started, the easier and sooner the maximum of the carbon emissions will be achieved so as to reduce carbon emissions and energy intensity. Numerical simulations are presented to demonstrate the results. -- Highlights: ► Use non-linear dynamical method to model the energy-saving and emission-reduction system. ► The energy-saving and emission-reduction attractor is obtained. ► Identify the unknown parameters of the energy-saving and emission-reduction system based on the statistical data. ► Evaluating the achievements of energy-saving and emission-reduction by the time-varying energy intensity calculation formula. ► Some statistical results based on the statistical data in China are presented, which are vivid and adherent to the reality.

COVAR: Computer Program for Multifactor Relative Risks and Tests of Hypotheses Using a Variance-Covariance Matrix from Linear and Log-Linear Regression

Directory of Open Access Journals (Sweden)

Leif E. Peterson

1997-11-01

Full Text Available A computer program for multifactor relative risks, confidence limits, and tests of hypotheses using regression coefficients and a variance-covariance matrix obtained from a previous additive or multiplicative regression analysis is described in detail. Data used by the program can be stored and input from an external disk-file or entered via the keyboard. The output contains a list of the input data, point estimates of single or joint effects, confidence intervals and tests of hypotheses based on a minimum modified chi-square statistic. Availability of the program is also discussed.

Hidden symmetries in five-dimensional supergravity

International Nuclear Information System (INIS)

Poessel, M.

2003-05-01

This thesis is concerned with the study of hidden symmetries in supergravity, which play an important role in the present picture of supergravity and string theory. Concretely, the appearance of a hidden G 2(+2) /SO(4) symmetry is studied in the dimensional reduction of d=5, N=2 supergravity to three dimensions - a parallel model to the more famous E 8(+8) /SO(16) case in eleven-dimensional supergravity. Extending previous partial results for the bosonic part, I give a derivation that includes fermionic terms. This sheds new light on the appearance of the local hidden symmetry SO(4) in the reduction, and shows up an unusual feature which follows from an analysis of the R-symmetry associated with N=4 supergravity and of the supersymmetry variations, and which has no parallel in the eleven-dimensional case: The emergence of an additional SO(3) as part of the enhanced local symmetry, invisible in the dimensional reduction of the gravitino, and corresponding to the fact that, of the SO(4) used in the coset model, only the diagonal SO(3) is visible immediately upon dimensional reduction. The uncovering of the hidden symmetries proceeds via the construction of the proper coset gravity in three dimensions, and matching it with the Lagrangian obtained from the reduction. (orig.)

Multilinear Graph Embedding: Representation and Regularization for Images.

Science.gov (United States)

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.

Effect of Intraoperative Three-Dimensional Imaging During the Reduction and Fixation of Displaced Calcaneal Fractures on Articular Congruence and Implant Fixation

DEFF Research Database (Denmark)

Eckardt, Henrik; Lind, Marianne

2015-01-01

BACKGROUND: Operative treatment of displaced calcaneal fractures should restore joint congruence, but conventional fluoroscopy is unable to fully visualize the subtalar joint. We questioned whether intraoperative 3-dimensional (3D) imaging would aid in the reduction of calcaneal fractures......, resulting in improved articular congruence and implant positioning. METHOD: Sixty-two displaced calcaneal fractures were operated on using standard fluoroscopic views. When the surgeon had achieved a satisfactory reduction, an intraoperative 3D scan was conducted, malreductions or implant imperfections were...

Provincial carbon intensity abatement potential estimation in China: A PSO–GA-optimized multi-factor environmental learning curve method

International Nuclear Information System (INIS)

Yu, Shiwei; Zhang, Junjie; Zheng, Shuhong; Sun, Han

2015-01-01

This study aims to estimate carbon intensity abatement potential in China at the regional level by proposing a particle swarm optimization–genetic algorithm (PSO–GA) multivariate environmental learning curve estimation method. The model uses two independent variables, namely, per capita gross domestic product (GDP) and the proportion of the tertiary industry in GDP, to construct carbon intensity learning curves (CILCs), i.e., CO 2 emissions per unit of GDP, of 30 provinces in China. Instead of the traditional ordinary least squares (OLS) method, a PSO–GA intelligent optimization algorithm is used to optimize the coefficients of a learning curve. The carbon intensity abatement potentials of the 30 Chinese provinces are estimated via PSO–GA under the business-as-usual scenario. The estimation reveals the following results. (1) For most provinces, the abatement potentials from improving a unit of the proportion of the tertiary industry in GDP are higher than the potentials from raising a unit of per capita GDP. (2) The average potential of the 30 provinces in 2020 will be 37.6% based on the emission's level of 2005. The potentials of Jiangsu, Tianjin, Shandong, Beijing, and Heilongjiang are over 60%. Ningxia is the only province without intensity abatement potential. (3) The total carbon intensity in China weighted by the GDP shares of the 30 provinces will decline by 39.4% in 2020 compared with that in 2005. This intensity cannot achieve the 40%–45% carbon intensity reduction target set by the Chinese government. Additional mitigation policies should be developed to uncover the potentials of Ningxia and Inner Mongolia. In addition, the simulation accuracy of the CILCs optimized by PSO–GA is higher than that of the CILCs optimized by the traditional OLS method. - Highlights: • A PSO–GA-optimized multi-factor environmental learning curve method is proposed. • The carbon intensity abatement potentials of the 30 Chinese provinces are estimated by

A Comparative Study of 3-Dimensional Titanium Versus 2-Dimensional Titanium Miniplates for Open Reduction and Fixation of Mandibular Parasymphysis Fracture.

Science.gov (United States)

Mittal, Yogesh; Varghese, K George; Mohan, S; Jayakumar, N; Chhag, Somil

2016-03-01

Three dimensional titanium plating system was developed by Farmand in 1995 to meet the requirements of semi rigid fixation with lesser complication. The purpose of this in vivo prospective study was to evaluate and compare the clinical effectiveness of three dimensional and two dimensional Titanium miniplates for open reduction and fixation of mandibular parasymphysis fracture. Thirty patients with non-comminuted mandibular parasymphysis fractures were divided randomly into two equal groups and were treated with 2 mm 3D and 2D miniplate system respectively. All patients were systematically monitored at 1st, 2nd, 3rd, 6th week, 3rd and 6th month postoperatively. The outcome parameters recorded were severity of pain, infection, mobility, occlusion derangement, paresthesia and implant failure. The data so collected was analyzed using independent t test and Chi square test (α = .05). The results showed that one patient in each group had post-operative infection, occlusion derangement and mobility (p > .05). In Group A, one patient had paresthesia while in Group B, two patients had paresthesia (p > .05). None of the patients in both the groups had implant failure. There was no statistically significant difference between 3D and 2D miniplate system in all the recorded parameters at all the follow-ups (p > .05). 3D miniplates were found to be better than 2D miniplates in terms of cost, ease of surgery and operative time. However, 3D miniplates were unfavorable for cases where fracture line was oblique and in close proximity to mental foramen, where they were difficult to adapt and more chances for tooth-root damage and inadvertent injury to the mental nerve due to traction.

M-Isomap: Orthogonal Constrained Marginal Isomap for Nonlinear Dimensionality Reduction.

Science.gov (United States)

Zhang, Zhao; Chow, Tommy W S; Zhao, Mingbo

2013-02-01

Isomap is a well-known nonlinear dimensionality reduction (DR) method, aiming at preserving geodesic distances of all similarity pairs for delivering highly nonlinear manifolds. Isomap is efficient in visualizing synthetic data sets, but it usually delivers unsatisfactory results in benchmark cases. This paper incorporates the pairwise constraints into Isomap and proposes a marginal Isomap (M-Isomap) for manifold learning. The pairwise Cannot-Link and Must-Link constraints are used to specify the types of neighborhoods. M-Isomap computes the shortest path distances over constrained neighborhood graphs and guides the nonlinear DR through separating the interclass neighbors. As a result, large margins between both interand intraclass clusters are delivered and enhanced compactness of intracluster points is achieved at the same time. The validity of M-Isomap is examined by extensive simulations over synthetic, University of California, Irvine, and benchmark real Olivetti Research Library, YALE, and CMU Pose, Illumination, and Expression databases. The data visualization and clustering power of M-Isomap are compared with those of six related DR methods. The visualization results show that M-Isomap is able to deliver more separate clusters. Clustering evaluations also demonstrate that M-Isomap delivers comparable or even better results than some state-of-the-art DR algorithms.

Pareto-optimal multi-objective dimensionality reduction deep auto-encoder for mammography classification.

Science.gov (United States)

Taghanaki, Saeid Asgari; Kawahara, Jeremy; Miles, Brandon; Hamarneh, Ghassan

2017-07-01

Feature reduction is an essential stage in computer aided breast cancer diagnosis systems. Multilayer neural networks can be trained to extract relevant features by encoding high-dimensional data into low-dimensional codes. Optimizing traditional auto-encoders works well only if the initial weights are close to a proper solution. They are also trained to only reduce the mean squared reconstruction error (MRE) between the encoder inputs and the decoder outputs, but do not address the classification error. The goal of the current work is to test the hypothesis that extending traditional auto-encoders (which only minimize reconstruction error) to multi-objective optimization for finding Pareto-optimal solutions provides more discriminative features that will improve classification performance when compared to single-objective and other multi-objective approaches (i.e. scalarized and sequential). In this paper, we introduce a novel multi-objective optimization of deep auto-encoder networks, in which the auto-encoder optimizes two objectives: MRE and mean classification error (MCE) for Pareto-optimal solutions, rather than just MRE. These two objectives are optimized simultaneously by a non-dominated sorting genetic algorithm. We tested our method on 949 X-ray mammograms categorized into 12 classes. The results show that the features identified by the proposed algorithm allow a classification accuracy of up to 98.45%, demonstrating favourable accuracy over the results of state-of-the-art methods reported in the literature. We conclude that adding the classification objective to the traditional auto-encoder objective and optimizing for finding Pareto-optimal solutions, using evolutionary multi-objective optimization, results in producing more discriminative features. Copyright © 2017 Elsevier B.V. All rights reserved.

Water-Induced Dimensionality Reduction in Metal-Halide Perovskites

KAUST Repository

Turedi, Bekir

2018-03-30

Metal-halide perovskite materials are highly attractive materials for optoelectronic applications. However, the instability of perovskite materials caused by moisture and heat-induced degradation impairs future prospects of using these materials. Here we employ water to directly transform films of the three-dimensional (3D) perovskite CsPbBr3 to stable two-dimensional (2D) perovskite-related CsPb2Br5. A sequential dissolution-recrystallization process governs this water induced transformation under PbBr2 rich condition. We find that these post-synthesized 2D perovskite-related material films exhibit excellent stability against humidity and high photoluminescence quantum yield. We believe that our results provide a new synthetic method to generate stable 2D perovskite-related materials that could be applicable for light emitting device applications.

The Multifactor Measure of Performance: Its Development, Norming, and Validation.

Science.gov (United States)

Bar-On, Reuven

2018-01-01

This article describes the development as well as the initial norming and validation of the Multifactor Measure of Performance™ (MMP™), which is a psychometric instrument that is designed to study, assess and enhance key predictors of human performance to help individuals perform at a higher level. It was created by the author, for the purpose of going beyond existing conceptual and psychometric models that often focus on relatively few factors that are purported to assess performance at school, in the workplace and elsewhere. The relative sparsity of multifactorial pre-employment assessment instruments exemplifies, for the author, one of the important reasons for developing the MMP™, which attempts to comprehensively evaluate a wider array of factors that are thought to contribute to performance. In that this situation creates a need in the area of test-construction that should be addressed, the author sought to develop a multifactorial assessment and development instrument that could concomitantly evaluate a combination of physical, cognitive, intra-personal, inter-personal, and motivational factors that significantly contribute to performance. The specific aim of this article is to show why, how and if this could be done as well as to present and discuss the potential importance of the results obtained to date. The findings presented here will hopefully add to what is known about human performance and thus contribute to the professional literature, in addition to contribute to the continued development of the MMP™. The impetus for developing the MMP™ is first explained below, followed by a detailed description of the process involved and the findings obtained; and their potential application is then discussed as well as the possible limitations of the present research and the need for future studies to address them.

Multi-factor analysis on events related to hematological toxicity in 153Sm-EDTMP palliative therapy for skeletal metastases

International Nuclear Information System (INIS)

Zhan Hongwei; Yu Xiaoling; Ye Xiaojuan; Bao Chengkan; Sun Da; He Gangqiang

2006-01-01

Objective: To investigate the clinical factors related to hematological toxicity induced by intravenous samarium-153 ethylenediaminetetramethylene phosphonic acid ( 153 Sm-EDTMP) treatment. Methods A total of 206 patients with bony metastases treated with 153 Sm-EDTMP were retrospectively analyzed. Logistic regression (SPSS 10.0 for Windows) and correlation analysis were used to evaluate the factors concerned. Results: Age of the patient, number of bone metastatic lesion, chemotherapy before 153 Sm-EDTMP therapy, concurrent radiotherapy and repeat-times of 153 Sm-EDTMP treatments were found the individual factors related to hematological toxicity. Chemotherapy before 153 Sm-EDTMP, concurrent radiotherapy, medication for normal blood counting and repeat-times of 153 Sm-EDTMP treatments were the hematological toxicity factors in multi-factor analysis. Conclusion: In 153 Sm-EDTMP therapy, several factors were found related to hematological toxicity suggesting more attention be paid to the change of blood cell counting after the palliative therapy. (authors)

Multifactor leadership styles and new exposure to workplace bullying: a six-month prospective study

Science.gov (United States)

TSUNO, Kanami; KAWAKAMI, Norito

2014-01-01

This study investigated the prospective association between supervisor leadership styles and workplace bullying. Altogether 404 civil servants from a local government in Japan completed baseline and follow-up surveys. The leadership variables and exposure to bullying were measured by Multifactor Leadership Questionnaire and Negative Acts Questionnaire-Revised, respectively. The prevalence of workplace bullying was 14.8% at baseline and 15.1% at follow-up. Among respondents who did not experience bullying at baseline (n=216), those who worked under the supervisors as higher in passive laissez-faire leadership had a 4.3 times higher risk of new exposure to bullying. On the other hand, respondents whose supervisors with highly considerate of the individual had a 70% lower risk of new exposure to bullying. In the entire sample (n=317), passive laissez-faire leadership was significantly and positively associated, while charisma/inspiration, individual consideration, and contingent reward were negatively associated both after adjusting for demographic and occupational characteristics at baseline, life events during follow-up, and exposure to workplace bullying at baseline. Results indicated that passive laissez-faire and low individual consideration leadership style at baseline were strong predictors of new exposure to bullying and high individual consideration leadership of supervisors/managers could be a preventive factor against bullying. PMID:25382384

Multifactor leadership styles and new exposure to workplace bullying: a six-month prospective study.

Science.gov (United States)

Tsuno, Kanami; Kawakami, Norito

2015-01-01

This study investigated the prospective association between supervisor leadership styles and workplace bullying. Altogether 404 civil servants from a local government in Japan completed baseline and follow-up surveys. The leadership variables and exposure to bullying were measured by Multifactor Leadership Questionnaire and Negative Acts Questionnaire-Revised, respectively. The prevalence of workplace bullying was 14.8% at baseline and 15.1% at follow-up. Among respondents who did not experience bullying at baseline (n=216), those who worked under the supervisors as higher in passive laissez-faire leadership had a 4.3 times higher risk of new exposure to bullying. On the other hand, respondents whose supervisors with highly considerate of the individual had a 70% lower risk of new exposure to bullying. In the entire sample (n=317), passive laissez-faire leadership was significantly and positively associated, while charisma/inspiration, individual consideration, and contingent reward were negatively associated both after adjusting for demographic and occupational characteristics at baseline, life events during follow-up, and exposure to workplace bullying at baseline. Results indicated that passive laissez-faire and low individual consideration leadership style at baseline were strong predictors of new exposure to bullying and high individual consideration leadership of supervisors/managers could be a preventive factor against bullying.

Dimensionality Reduction and Information-Theoretic Divergence Between Sets of Ladar Images

National Research Council Canada - National Science Library

Gray, David M; Principe, Jose C

2008-01-01

... can be exploited while circumventing many of the problems associated with the so-called "curse of dimensionality." In this study, PCA techniques are used to find a low-dimensional sub-space representation of LADAR image sets...

Dimensional reduction near the deconfinement transition

International Nuclear Information System (INIS)

Kurkela, A.

2009-01-01

It is expected that incorporating the center symmetry in the conventional dimensionally reduced effective theory for high-temperature SU(N) Yang-Mills theory, EQCD, will considerably extend its applicability towards the deconfinement transition. In this talk, I will discuss the construction of such center-symmetric effective theories and present results from their lattice simulations in the case of two colors. The simulations demonstrate that unlike EQCD, the new center symmetric theory undergoes a second order confining phase transition in complete analogy with the full theory. I will also describe the perturbative and non-perturbative matching of the parameters of the effective theory, and outline ways to further improve its description of the physics near the deconfinement transition. (author)

Higher-dimensional Bianchi type-VIh cosmologies

Science.gov (United States)

Lorenz-Petzold, D.

1985-09-01

The higher-dimensional perfect fluid equations of a generalization of the (1 + 3)-dimensional Bianchi type-VIh space-time are discussed. Bianchi type-V and Bianchi type-III space-times are also included as special cases. It is shown that the Chodos-Detweiler (1980) mechanism of cosmological dimensional-reduction is possible in these cases.

A Corresponding Lie Algebra of a Reductive homogeneous Group and Its Applications

International Nuclear Information System (INIS)

Zhang Yu-Feng; Rui Wen-Juan; Wu Li-Xin

2015-01-01

With the help of a Lie algebra of a reductive homogeneous space G/K, where G is a Lie group and K is a resulting isotropy group, we introduce a Lax pair for which an expanding (2+1)-dimensional integrable hierarchy is obtained by applying the binormial-residue representation (BRR) method, whose Hamiltonian structure is derived from the trace identity for deducing (2+1)-dimensional integrable hierarchies, which was proposed by Tu, et al. We further consider some reductions of the expanding integrable hierarchy obtained in the paper. The first reduction is just right the (2+1)-dimensional AKNS hierarchy, the second-type reduction reveals an integrable coupling of the (2+1)-dimensional AKNS equation (also called the Davey-Stewartson hierarchy), a kind of (2+1)-dimensional Schrödinger equation, which was once reobtained by Tu, Feng and Zhang. It is interesting that a new (2+1)-dimensional integrable nonlinear coupled equation is generated from the reduction of the part of the (2+1)-dimensional integrable coupling, which is further reduced to the standard (2+1)-dimensional diffusion equation along with a parameter. In addition, the well-known (1+1)-dimensional AKNS hierarchy, the (1+1)-dimensional nonlinear Schrödinger equation are all special cases of the (2+1)-dimensional expanding integrable hierarchy. Finally, we discuss a few discrete difference equations of the diffusion equation whose stabilities are analyzed by making use of the von Neumann condition and the Fourier method. Some numerical solutions of a special stationary initial value problem of the (2+1)-dimensional diffusion equation are obtained and the resulting convergence and estimation formula are investigated. (paper)

Assessing Multiple Pathways for Achieving China’s National Emissions Reduction Target

Directory of Open Access Journals (Sweden)

Mingyue Wang

2018-06-01

Full Text Available In order to achieve China’s target of carbon intensity emissions reduction in 2030, there is a need to identify a scientific pathway and feasible strategies. In this study, we used stochastic frontier analysis method of energy efficiency, incorporating energy structure, economic structure, human capital, capital stock and potential energy efficiency to identify an efficient pathway for achieving emissions reduction target. We set up 96 scenarios including single factor scenarios and multi-factors combination scenarios for the simulation. The effects of each scenario on achieving the carbon intensity reduction target are then evaluated. It is found that: (1 Potential energy efficiency has the greatest contribution to the carbon intensity emissions reduction target; (2 they are unlikely to reach the 2030 carbon intensity reduction target of 60% by only optimizing a single factor; (3 in order to achieve the 2030 target, several aspects have to be adjusted: the fossil fuel ratio must be lower than 80%, and its average growth rate must be decreased by 2.2%; the service sector ratio in GDP must be higher than 58.3%, while the growth rate of non-service sectors must be lowered by 2.4%; and both human capital and capital stock must achieve and maintain a stable growth rate and a 1% increase annually in energy efficiency. Finally, the specific recommendations of this research were discussed, including constantly improved energy efficiency; the upgrading of China’s industrial structure must be accelerated; emissions reduction must be done at the root of energy sources; multi-level input mechanisms in overall levels of education and training to cultivate the human capital stock must be established; investment in emerging equipment and accelerate the closure of backward production capacity to accumulate capital stock.

An overview of a multifactor-system theory of personality and individual differences: III. Life span development and the heredity-environment issue.

Science.gov (United States)

Powell, A; Royce, J R

1981-12-01

In Part III of this three-part series on multifactor-system theory, multivariate, life-span development is approached from the standpoint of a quantitative and qualitative analysis of the ontogenesis of factors in each of the six systems. The pattern of quantitative development (described via the Gompertz equation and three developmental parameters) involves growth, stability, and decline, and qualitative development involves changes in the organization of factors (e.g., factor differentiation and convergence). Hereditary and environmental sources of variation are analyzed via the factor gene model and the concept of heredity-dominant factors, and the factor-learning model and environment-dominant factors. It is hypothesized that the sensory and motor systems are heredity dominant, that the style and value systems are environment dominant, and that the cognitive and affective systems are partially heredity dominant.

Three-dimensional MRI Analysis of Femoral Head Remodeling After Reduction in Patients With Developmental Dysplasia of the Hip.

Science.gov (United States)

Tsukagoshi, Yuta; Kamada, Hiroshi; Kamegaya, Makoto; Takeuchi, Ryoko; Nakagawa, Shogo; Tomaru, Yohei; Tanaka, Kenta; Onishi, Mio; Nishino, Tomofumi; Yamazaki, Masashi

2018-05-02

Previous reports on patients with developmental dysplasia of the hip (DDH) showed that the prereduced femoral head was notably smaller and more nonspherical than the intact head, with growth failure observed at the proximal posteromedial area. We evaluated the shape of the femoral head cartilage in patients with DDH before and after reduction, with size and sphericity assessed using 3-dimensional (3D) magnetic resonance imaging (MRI). We studied 10 patients with unilateral DDH (all female) who underwent closed reduction. Patients with avascular necrosis of the femoral head on the plain radiograph 1 year after reduction were excluded. 3D MRI was performed before reduction and after reduction, at 2 years of age. 3D-image analysis software was used to reconstruct the multiplanes. After setting the axial, coronal, and sagittal planes in the software (based on the femoral shaft and neck axes), the smallest sphere that included the femoral head cartilage was drawn, the diameter was measured, and the center of the sphere was defined as the femoral head center. We measured the distance between the center and cartilage surface every 30 degrees on the 3 reconstructed planes. Sphericity of the femoral head was calculated using a ratio (the distance divided by each radius) and compared between prereduction and postreduction. The mean patient age was 7±3 and 26±3 months at the first and second MRI, respectively. The mean duration between the reduction and second MRI was 18±3 months. The femoral head diameter was 26.7±1.5 and 26.0±1.6 mm on the diseased and intact sides, respectively (P=0.069). The ratios of the posteromedial area on the axial plane and the proximoposterior area on the sagittal plane after reduction were significantly larger than before reduction (P<0.01). We demonstrated that the size of the reduced femoral head was nearly equal to that of the intact femoral head and that the growth failure area of the head before reduction, in the proximal posteromedial

Four-dimensional Hall mechanics as a particle on CP3

International Nuclear Information System (INIS)

Bellucci, Stefano; Casteill, Pierre-Yves; Nersessian, Armen

2003-01-01

In order to establish an explicit connection between four-dimensional Hall effect on S 4 and six-dimensional Hall effect on CP 3 , we perform the Hamiltonian reduction of a particle moving on CP 3 in a constant magnetic field to the four-dimensional Hall mechanics (i.e., a-bar particle on S 4 in a SU(2) instanton field). This reduction corresponds to fixing the isospin of the latter system

Kaluza-Klein cosmology from five-dimensional Lovelock-Cartan theory

Science.gov (United States)

Castillo-Felisola, Oscar; Corral, Cristóbal; del Pino, Simón; Ramírez, Francisca

2016-12-01

We study the Kaluza-Klein dimensional reduction of the Lovelock-Cartan theory in five-dimensional spacetime, with a compact dimension of S1 topology. We find cosmological solutions of the Friedmann-Robertson-Walker class in the reduced spacetime. The torsion and the fields arising from the dimensional reduction induce a nonvanishing energy-momentum tensor in four dimensions. We find solutions describing expanding, contracting, and bouncing universes. The model shows a dynamical compactification of the extra dimension in some regions of the parameter space.

Dimensional reduction of exceptional E6,E8 gauge groups and flavour chirality

International Nuclear Information System (INIS)

Koca, M.

1984-01-01

Ten-dimensional Yang - Mills gauge theories based on the exceptional groups E 6 and E 8 are reduced to four-dimensional flavour-chiral Yang - Mills - Higgs theories where the extra six dimensions are identified with the compact G 2 /SU(3) and SO(7)/SO(6) coset spaces. A ten-dimensional E 8 theory leads to three families of SU(5), one of which lies in the 144-dimensional representation of SO(10)

Dimensional reduction of a general advection–diffusion equation in 2D channels

Science.gov (United States)

Kalinay, Pavol; Slanina, František

2018-06-01

Diffusion of point-like particles in a two-dimensional channel of varying width is studied. The particles are driven by an arbitrary space dependent force. We construct a general recurrence procedure mapping the corresponding two-dimensional advection-diffusion equation onto the longitudinal coordinate x. Unlike the previous specific cases, the presented procedure enables us to find the one-dimensional description of the confined diffusion even for non-conservative (vortex) forces, e.g. caused by flowing solvent dragging the particles. We show that the result is again the generalized Fick–Jacobs equation. Despite of non existing scalar potential in the case of vortex forces, the effective one-dimensional scalar potential, as well as the corresponding quasi-equilibrium and the effective diffusion coefficient can be always found.

Three-dimensional assemblies of graphene prepared by a novel chemical reduction-induced self-assembly method

KAUST Repository

Zhang, Lianbin

2012-01-01

In this study, three-dimensional (3D) graphene assemblies are prepared from graphene oxide (GO) by a facile in situ reduction-assembly method, using a novel, low-cost, and environment-friendly reducing medium which is a combination of oxalic acid (OA) and sodium iodide (NaI). It is demonstrated that the combination of a reducing acid, OA, and NaI is indispensable for effective reduction of GO in the current study and this unique combination (1) allows for tunable control over the volume of the thus-prepared graphene assemblies and (2) enables 3D graphene assemblies to be prepared from the GO suspension with a wide range of concentrations (0.1 to 4.5 mg mL-1). To the best of our knowledge, the GO concentration of 0.1 mg mL-1 is the lowest GO concentration ever reported for preparation of 3D graphene assemblies. The thus-prepared 3D graphene assemblies exhibit low density, highly porous structures, and electrically conducting properties. As a proof of concept, we show that by infiltrating a responsive polymer of polydimethylsiloxane (PDMS) into the as-resulted 3D conducting network of graphene, a conducting composite is obtained, which can be used as a sensing device for differentiating organic solvents with different polarity. © 2012 The Royal Society of Chemistry.

Supersymmetric dimensional regularization

International Nuclear Information System (INIS)

Siegel, W.; Townsend, P.K.; van Nieuwenhuizen, P.

1980-01-01

There is a simple modification of dimension regularization which preserves supersymmetry: dimensional reduction to real D < 4, followed by analytic continuation to complex D. In terms of component fields, this means fixing the ranges of all indices on the fields (and therefore the numbers of Fermi and Bose components). For superfields, it means continuing in the dimensionality of x-space while fixing the dimensionality of theta-space. This regularization procedure allows the simple manipulation of spinor derivatives in supergraph calculations. The resulting rules are: (1) First do all algebra exactly as in D = 4; (2) Then do the momentum integrals as in ordinary dimensional regularization. This regularization procedure needs extra rules before one can say that it is consistent. Such extra rules needed for superconformal anomalies are discussed. Problems associated with renormalizability and higher order loops are also discussed

New results for algebraic tensor reduction of Feynman integrals

Energy Technology Data Exchange (ETDEWEB)

Fleischer, Jochem [Bielefeld Univ. (Germany). Fakultaet fuer Physik; Riemann, Tord [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany); Yundin, Valery [Copenhagen Univ. (Denmark). Niels Bohr International Academy and Discovery Center

2012-02-15

We report on some recent developments in algebraic tensor reduction of one-loop Feynman integrals. For 5-point functions, an efficient tensor reduction was worked out recently and is now available as numerical C++ package, PJFry, covering tensor ranks until five. It is free of inverse 5- point Gram determinants and inverse small 4-point Gram determinants are treated by expansions in higher-dimensional 3-point functions. By exploiting sums over signed minors, weighted with scalar products of chords (or, equivalently, external momenta), extremely efficient expressions for tensor integrals contracted with external momenta were derived. The evaluation of 7-point functions is discussed. In the present approach one needs for the reductions a (d +2)-dimensional scalar 5-point function in addition to the usual scalar basis of 1- to 4-point functions in the generic dimension d=4-2{epsilon}. When exploiting the four-dimensionality of the kinematics, this basis is sufficient. We indicate how the (d+2)-dimensional 5-point function can be evaluated. (orig.)

New results for algebraic tensor reduction of Feynman integrals

International Nuclear Information System (INIS)

Fleischer, Jochem; Yundin, Valery

2012-02-01

We report on some recent developments in algebraic tensor reduction of one-loop Feynman integrals. For 5-point functions, an efficient tensor reduction was worked out recently and is now available as numerical C++ package, PJFry, covering tensor ranks until five. It is free of inverse 5- point Gram determinants and inverse small 4-point Gram determinants are treated by expansions in higher-dimensional 3-point functions. By exploiting sums over signed minors, weighted with scalar products of chords (or, equivalently, external momenta), extremely efficient expressions for tensor integrals contracted with external momenta were derived. The evaluation of 7-point functions is discussed. In the present approach one needs for the reductions a (d +2)-dimensional scalar 5-point function in addition to the usual scalar basis of 1- to 4-point functions in the generic dimension d=4-2ε. When exploiting the four-dimensionality of the kinematics, this basis is sufficient. We indicate how the (d+2)-dimensional 5-point function can be evaluated. (orig.)

Extended supersymmetry in four-dimensional Euclidean space

International Nuclear Information System (INIS)

McKeon, D.G.C.; Sherry, T.N.

2000-01-01

Since the generators of the two SU(2) groups which comprise SO(4) are not Hermitian conjugates of each other, the simplest supersymmetry algebra in four-dimensional Euclidean space more closely resembles the N=2 than the N=1 supersymmetry algebra in four-dimensional Minkowski space. An extended supersymmetry algebra in four-dimensional Euclidean space is considered in this paper; its structure resembles that of N=4 supersymmetry in four-dimensional Minkowski space. The relationship of this algebra to the algebra found by dimensionally reducing the N=1 supersymmetry algebra in ten-dimensional Euclidean space to four-dimensional Euclidean space is examined. The dimensional reduction of N=1 super Yang-Mills theory in ten-dimensional Minkowski space to four-dimensional Euclidean space is also considered

Hamiltonian reduction and supersymmetric mechanics with Dirac monopole

International Nuclear Information System (INIS)

Bellucci, Stefano; Nersessian, Armen; Yeranyan, Armen

2006-01-01

We apply the technique of Hamiltonian reduction for the construction of three-dimensional N=4 supersymmetric mechanics specified by the presence of a Dirac monopole. For this purpose we take the conventional N=4 supersymmetric mechanics on the four-dimensional conformally-flat spaces and perform its Hamiltonian reduction to three-dimensional system. We formulate the final system in the canonical coordinates, and present, in these terms, the explicit expressions of the Hamiltonian and supercharges. We show that, besides a magnetic monopole field, the resulting system is specified by the presence of a spin-orbit coupling term. A comparision with previous work is also carried out

Unlocking the Electrocatalytic Activity of Antimony for CO2 Reduction by Two-Dimensional Engineering of the Bulk Material.

Science.gov (United States)

Li, Fengwang; Xue, Mianqi; Li, Jiezhen; Ma, Xinlei; Chen, Lu; Zhang, Xueji; MacFarlane, Douglas R; Zhang, Jie

2017-11-13

Two-dimensional (2D) materials are known to be useful in catalysis. Engineering 3D bulk materials into the 2D form can enhance the exposure of the active edge sites, which are believed to be the origin of the high catalytic activity. Reported herein is the production of 2D "few-layer" antimony (Sb) nanosheets by cathodic exfoliation. Application of this 2D engineering method turns Sb, an inactive material for CO 2 reduction in its bulk form, into an active 2D electrocatalyst for reduction of CO 2 to formate with high efficiency. The high activity is attributed to the exposure of a large number of catalytically active edge sites. Moreover, this cathodic exfoliation process can be coupled with the anodic exfoliation of graphite in a single-compartment cell for in situ production of a few-layer Sb nanosheets and graphene composite. The observed increased activity of this composite is attributed to the strong electronic interaction between graphene and Sb. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Modeling of Alpine Grassland Cover Based on Unmanned Aerial Vehicle Technology and Multi-Factor Methods: A Case Study in the East of Tibetan Plateau, China

Directory of Open Access Journals (Sweden)

Baoping Meng

2018-02-01

Full Text Available Grassland cover and its temporal changes are key parameters in the estimation and monitoring of ecosystems and their functions, especially via remote sensing. However, the most suitable model for estimating grassland cover and the differences between models has rarely been studied in alpine meadow grasslands. In this study, field measurements of grassland cover in Gannan Prefecture, from 2014 to 2016, were acquired using unmanned aerial vehicle (UAV technology. Single-factor parametric and multi-factor parametric/non-parametric cover inversion models were then constructed based on 14 factors related to grassland cover, and the dynamic variation of the annual maximum cover was analyzed. The results show that (1 nine out of 14 factors (longitude, latitude, elevation, the concentrations of clay and sand in the surface and bottom soils, temperature, precipitation, enhanced vegetation index (EVI and normalized difference vegetation index (NDVI exert a significant effect on grassland cover in the study area. The logarithmic model based on EVI presents the best performance, with an R2 and RMSE of 0.52 and 16.96%, respectively. Single-factor grassland cover inversion models account for only 1–49% of the variation in cover during the growth season. (2 The optimum grassland cover inversion model is the artificial neural network (BP-ANN, with an R2 and RMSE of 0.72 and 13.38%, and SDs of 0.062% and 1.615%, respectively. Both the accuracy and the stability of the BP-ANN model are higher than those of the single-factor parametric models and multi-factor parametric/non-parametric models. (3 The annual maximum cover in Gannan Prefecture presents an increasing trend over 60.60% of the entire study area, while 36.54% is presently stable and 2.86% exhibits a decreasing trend.

Dimensional reduction of U(1) x SU(2) Chern-Simons bosonization: Application to the t - J model

International Nuclear Information System (INIS)

Marchetti, P.A.

1996-09-01

We perform a dimensional reduction of the U(1) x SU(2) Chern-Simons bosonization and apply it to the t - J model, relevant for high T c superconductors. This procedure yields a decomposition of the electron field into a product of two ''semionic'' fields, i.e. fields obeying Abelian braid statistics with statistics parameter θ = 1/4, one carrying the charge and the other the spin degrees of freedom. A mean field theory is then shown to reproduce correctly the large distance behaviour of the correlation functions of the 1D t - J model at >> J. This result shows that to capture the essential physical properties of the model one needs a specific ''semionic'' form of spin-charge separation. (author). 31 refs

On the dimensional reduction of a gravitational theory containing higher-derivative terms

International Nuclear Information System (INIS)

Pollock, M.D.

1990-02-01

From the higher-dimensional gravitational theory L-circumflex=R-circumflex-2Λ-circumflex-α-circumflex 1 R-circumflex 2 =α-circumflex 2 R-circumflex AB R-circumflex AB -α-circumflex 3 R-circumflex ABCD R-circumflex ABCD , we derive the effective four-dimensional Lagrangian L. (author). 12 refs

Comparative analysis of nonlinear dimensionality reduction techniques for breast MRI segmentation

Energy Technology Data Exchange (ETDEWEB)

Akhbardeh, Alireza; Jacobs, Michael A. [Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205 (United States); Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205 (United States) and Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205 (United States)

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), and 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

Comparative analysis of nonlinear dimensionality reduction techniques for breast MRI segmentation

International Nuclear Information System (INIS)

Akhbardeh, Alireza; Jacobs, Michael A.

2012-01-01

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), and 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 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

Robust methods for data reduction

CERN Document Server

Farcomeni, Alessio

2015-01-01

Robust Methods for Data Reduction gives a non-technical overview of robust data reduction techniques, encouraging the use of these important and useful methods in practical applications. The main areas covered include principal components analysis, sparse principal component analysis, canonical correlation analysis, factor analysis, clustering, double clustering, and discriminant analysis.The first part of the book illustrates how dimension reduction techniques synthesize available information by reducing the dimensionality of the data. The second part focuses on cluster and discriminant analy

On the integrability of a Hamiltonian reduction of a 2+1-dimensional non-isothermal rotating gas cloud system

International Nuclear Information System (INIS)

Rogers, C; Schief, W K

2011-01-01

A 2+1-dimensional version of a non-isothermal gas dynamic system with origins in the work of Ovsiannikov and Dyson on spinning gas clouds is shown to admit a Hamiltonian reduction which is completely integrable when the adiabatic index γ = 2. This nonlinear dynamical subsystem is obtained via an elliptic vortex ansatz which is intimately related to the construction of a Lax pair in the integrable case. The general solution of the gas dynamic system is derived in terms of Weierstrass (elliptic) functions. The latter derivation makes use of a connection with a stationary nonlinear Schrödinger equation and a Steen–Ermakov–Pinney equation, the superposition principle of which is based on the classical Lamé equation

Congruent reduction and mode conversion in 4-dimensional plasmas

International Nuclear Information System (INIS)

Friedland, L.; Kaufman, A.N.

1987-04-01

Standard eikonal theory reduces, to N=1, the order of the system of equations underlying wave propagation in inhomogeneous plasmas. The condition for this remarkable reducibility is that only one eigenvalue of the unreduced NxN dispersion matrix D(k,x) vanishes at a time. If, however, two or more eigenvalues of D become simultaneously small, the geometric optics reduction scheme becomes singular. These regions are associated with linear mode conversion, and are described by higher order systems. A new reduction scheme based on congruent transformations of D is developed, and it is shown that, in ''degenerate'' plasma regions, a partial reduction of order is possible. The method comprises a constructive step-by-step procedure, which, in the most frequent (doubly) degenerate case, yields a second order system, describing the pairwise mode conversion problems, the solution of which in general geometry has been found recently

Dimensional degression in AdSd

International Nuclear Information System (INIS)

Artsukevich, A. Yu.; Vasiliev, M. A.

2009-01-01

We analyze the pattern of fields in (d+1)-dimensional anti-de Sitter space in terms of those in d-dimensional anti-de Sitter space. The procedure, which is neither dimensional reduction nor dimensional compactification, is called dimensional degression. The analysis is performed group theoretically for all totally symmetric bosonic and fermionic representations of the anti-de Sitter algebra. The field-theoretical analysis is done for a massive scalar field in AdS d+d ' and massless spin-one-half, spin-one, and spin-two fields in AdS d+1 . The mass spectra of the resulting towers of fields in AdS d are found. For the scalar field case, the obtained results extend to the shadow sector those obtained by Metsaev [Nucl. Phys. B, Proc. Suppl. 102, 100 (2001)] by a different method.

arXiv Supersymmetric gauged matrix models from dimensional reduction on a sphere

CERN Document Server

Closset, Cyril; Seong, Rak-Kyeong

2018-05-04

It was recently proposed that $ \\mathcal{N} $ = 1 supersymmetric gauged matrix models have a duality of order four — that is, a quadrality — reminiscent of infrared dualities of SQCD theories in higher dimensions. In this note, we show that the zero-dimensional quadrality proposal can be inferred from the two-dimensional Gadde-Gukov-Putrov triality. We consider two-dimensional $ \\mathcal{N} $ = (0, 2) SQCD compactified on a sphere with the half-topological twist. For a convenient choice of R-charge, the zero-mode sector on the sphere gives rise to a simple $ \\mathcal{N} $ = 1 gauged matrix model. Triality on the sphere then implies a triality relation for the supersymmetric matrix model, which can be completed to the full quadrality.

Infinite dimensional gauge structure of Kaluza-Klein theories II: D>5

International Nuclear Information System (INIS)

Aulakh, C.S.; Sahdev, D.

1985-12-01

We carry out the dimensional reduction of the pure gravity sector of Kaluza Klein theories without making truncations of any sort. This generalizes our previous result for the 5-dimensional case to 4+d(>1) dimensions. The effective 4-dimensional action has the structure of an infinite dimensional gauge theory

A three-dimensional water quality modeling approach for exploring the eutrophication responses to load reduction scenarios in Lake Yilong (China)

International Nuclear Information System (INIS)

Zhao, Lei; Li, Yuzhao; Zou, Rui; He, Bin; Zhu, Xiang; Liu, Yong; Wang, Junsong; Zhu, Yongguan

2013-01-01

Lake Yilong in Southwestern China has been under serious eutrophication threat during the past decades; however, the lake water remained clear until sudden sharp increase in Chlorophyll a (Chl a) and turbidity in 2009 without apparent change in external loading levels. To investigate the causes as well as examining the underlying mechanism, a three-dimensional hydrodynamic and water quality model was developed, simulating the flow circulation, pollutant fate and transport, and the interactions between nutrients, phytoplankton and macrophytes. The calibrated and validated model was used to conduct three sets of scenarios for understanding the water quality responses to various load reduction intensities and ecological restoration measures. The results showed that (a) even if the nutrient loads is reduced by as much as 77%, the Chl a concentration decreased only by 50%; and (b) aquatic vegetation has strong interaction with phytoplankton, therefore requiring combined watershed and in-lake management for lake restoration. -- Highlights: ► We quantitatively investigated the non-linear lake responses to load reduction. ► The aquatic ecological condition had a great impact on algal blooms. ► Only water quality improvement cannot ensure the aquatic ecology restoration. -- The lake water quality responds to watershed load reduction in a nonlinear way, which requires combined watershed and in-lake management for lake restoration

A Fast and High-precision Orientation Algorithm for BeiDou Based on Dimensionality Reduction

Directory of Open Access Journals (Sweden)

ZHAO Jiaojiao

2015-05-01

Full Text Available A fast and high-precision orientation algorithm for BeiDou is proposed by deeply analyzing the constellation characteristics of BeiDou and GEO satellites features.With the advantage of good east-west geometry, the baseline vector candidate values were solved by the GEO satellites observations combined with the dimensionality reduction theory at first.Then, we use the ambiguity function to judge the values in order to obtain the optical baseline vector and get the wide lane integer ambiguities. On this basis, the B1 ambiguities were solved. Finally, the high-precision orientation was estimated by the determinating B1 ambiguities. This new algorithm not only can improve the ill-condition of traditional algorithm, but also can reduce the ambiguity search region to a great extent, thus calculating the integer ambiguities in a single-epoch.The algorithm is simulated by the actual BeiDou ephemeris and the result shows that the method is efficient and fast for orientation. It is capable of very high single-epoch success rate(99.31% and accurate attitude angle (the standard deviation of pitch and heading is respectively 0.07°and 0.13°in a real time and dynamic environment.

Three New (2+1)-dimensional Integrable Systems and Some Related Darboux Transformations

International Nuclear Information System (INIS)

Guo Xiu-Rong

2016-01-01

We introduce two operator commutators by using different-degree loop algebras of the Lie algebra A 1 , then under the framework of zero curvature equations we generate two (2+1)-dimensional integrable hierarchies, including the (2+1)-dimensional shallow water wave (SWW) hierarchy and the (2+1)-dimensional Kaup-Newell (KN) hierarchy. Through reduction of the (2+1)-dimensional hierarchies, we get a (2+1)-dimensional SWW equation and a (2+1)-dimensional KN equation. Furthermore, we obtain two Darboux transformations of the (2+1)-dimensional SWW equation. Similarly, the Darboux transformations of the (2+1)-dimensional KN equation could be deduced. Finally, with the help of the spatial spectral matrix of SWW hierarchy, we generate a (2+1) heat equation and a (2+1) nonlinear generalized SWW system containing inverse operators with respect to the variables x and y by using a reduction spectral problem from the self-dual Yang-Mills equations. (paper)

Hidden symmetries in minimal five-dimensional supergravity

International Nuclear Information System (INIS)

Poessel, Markus; Silva, Sebastian

2004-01-01

We study the hidden symmetries arising in the dimensional reduction of d=5, N=2 supergravity to three dimensions. Extending previous partial results for the bosonic part, we give a derivation that includes fermionic terms, shedding light on the appearance of the local hidden symmetry SO(4) in the reduction

Development of a two-dimensional high-performance liquid chromatography system coupled with on-line reduction as a new efficient analytical method of 3-nitrobenzanthrone, a potential human carcinogen.

Science.gov (United States)

Hasei, Tomohiro; Nakanishi, Haruka; Toda, Yumiko; Watanabe, Tetsushi

2012-08-31

3-Nitrobenzanthrone (3-NBA) is an extremely strong mutagen and carcinogen in rats inducing squamous cell carcinoma and adenocarcinoma. We developed a new sensitive analytical method, a two-dimensional HPLC system coupled with on-line reduction, to quantify non-fluorescent 3-NBA as fluorescent 3-aminobenzanthrone (3-ABA). The two-dimensional HPLC system consisted of reversed-phase HPLC and normal-phase HPLC, which were connected with a switch valve. 3-NBA was purified by reversed-phase HPLC and reduced to 3-ABA with a catalyst column, packed with alumina coated with platinum, in ethanol. An alcoholic solvent is necessary for reduction of 3-NBA, but 3-ABA is not fluorescent in the alcoholic solvent. Therefore, 3-ABA was separated from alcohol and impurities by normal-phase HPLC and detected with a fluorescence detector. Extracts from surface soil, airborne particles, classified airborne particles, and incinerator dust were applied to the two-dimensional HPLC system after clean-up with a silica gel column. 3-NBA, detected as 3-ABA, in the extracts was found as a single peak on the chromatograms without any interfering peaks. 3-NBA was detected in 4 incinerator dust samples (n=5). When classified airborne particles, that is, those 7.0 μm in size, were applied to the two-dimensional HPLC system after purified using a silica gel column, 3-NBA was detected in those particles with particle sizes NBA in airborne particles and the detection of 3-NBA in incinerator dust. Copyright © 2012 Elsevier B.V. All rights reserved.

Four-dimensional anti-de Sitter toroidal black holes from a three-dimensional perspective: Full complexity

International Nuclear Information System (INIS)

Zanchin, Vilson T.; Kleber, Antares; Lemos, Jose P.S.

2002-01-01

The dimensional reduction of black hole solutions in four-dimensional (4D) general relativity is performed and new 3D black hole solutions are obtained. Considering a 4D spacetime with one spacelike Killing vector, it is possible to split the Einstein-Hilbert-Maxwell action with a cosmological term in terms of 3D quantities. Definitions of quasilocal mass and charges in 3D spacetimes are reviewed. The analysis is then particularized to the toroidal charged rotating anti-de Sitter black hole. The reinterpretation of the fields and charges in terms of a three-dimensional point of view is given in each case, and the causal structure analyzed

Green functions and dimensional reduction of quantum fields on product manifolds

International Nuclear Information System (INIS)

Haba, Z

2008-01-01

We discuss Euclidean Green functions on product manifolds P=N x M. We show that if M is compact and N is not compact then the Euclidean field on P can be approximated by its zero mode which is a Euclidean field on N. We estimate the remainder of this approximation. We show that for large distances on N the remainder is small. If P=R D-1 x S β , where S β is a circle of radius β, then the result reduces to the well-known approximation of the D-dimensional finite temperature quantum field theory by (D - 1)-dimensional one in the high-temperature limit. Analytic continuation of Euclidean fields is discussed briefly

Hamiltonian formalism of two-dimensional Vlasov kinetic equation.

Science.gov (United States)

Pavlov, Maxim V

2014-12-08

In this paper, the two-dimensional Benney system describing long wave propagation of a finite depth fluid motion and the multi-dimensional Russo-Smereka kinetic equation describing a bubbly flow are considered. The Hamiltonian approach established by J. Gibbons for the one-dimensional Vlasov kinetic equation is extended to a multi-dimensional case. A local Hamiltonian structure associated with the hydrodynamic lattice of moments derived by D. J. Benney is constructed. A relationship between this hydrodynamic lattice of moments and the two-dimensional Vlasov kinetic equation is found. In the two-dimensional case, a Hamiltonian hydrodynamic lattice for the Russo-Smereka kinetic model is constructed. Simple hydrodynamic reductions are presented.

[Correlation of angiotensin-converting enzyme 2 gene polymorphism with antihypertensive effects of benazepril].

Science.gov (United States)

Chen, Qing; Tang, Xun; Yu, Can-qing; Chen, Da-fang; Tian, Jun; Cao, Yang; Fan, Wen-yi; Cao, Wei-hua; Zhan, Si-yan; Lv, Jun; Guo, Xiao-xia; Li, Li-ming; Hu, Yong-hua

2010-06-18

To explore the correlation of rs2106809 from angiotensin-converting enzyme 2 gene with antihypertensive effects of benazepril, as well as its interactions with polymorphisms of angiotensinogen(AGT) and angiotensin II type 1 receptor(AGTR1) gene. Correlation between rs2106809 and blood pressure reduction was estimated based on a field trail with 1 831 hypertensive patients using benazepril for 2 weeks. Generalized multifactor dimensionality reduction (GMDR) was used to explore the interactions of rs2106809 and 8 single nucleotide polymorphisms (SNPs) of AGTR1 gene and 3 SNPs of AGT gene. rs2106809 was found to be associated with reduction in systolic blood pressure and pulse pressure in women, as well as pulse pressure reduction in men. T allele carriers presented more blood pressure reduction (1.4, 1.3 and 0.9 mmHg/T allele respectively). Gene-gene interactions involving rs2106809 were found in systolic blood pressure reduction of men, and the response to benazepril of non-sensitive genotypes carriers was 8.2 (95% confidence interval: 6.6-9.7) mmHg, lower than that of sensitive genotypes carriers. rs2106809 might act as an independent influencing factor or component of gene-gene interaction in blood pressure reducing effects of benazepril.

Dimensionality reduction of quality of life indicators

Directory of Open Access Journals (Sweden)

Andrea Jindrová

2012-01-01

Full Text Available Selecting indicators for assessing the quality of life at the regional level is not unambigous. Currently, there are no precisely defined indicators that would give comprehensive information about the quality of life on a local level. In this paper we focus on the determination (selection of groups of indicators that can be interpreted, on the basis of studied literature, as factors characterizing the quality of life. Furthermore, on the application of methods to reduce the dimensionality of these indicators, from the source of the database CULS KROK, which provides statistics on the regional and districts level. To reduce the number of indicators and the subsequent creation of derived variables that capture the relationships between selected indicators multivariate statistical analysis methods, especially method of principal components and factor analysis were used. This paper also indicates the methodology grant project “Methodological Approaches to assess Subjective Aspects of the life quality in regions of the Czech Republic”.

Symmetry Reductions of a 1.5-Layer Ocean Circulation Model

International Nuclear Information System (INIS)

Huang Fei; Lou Senyue

2007-01-01

The (2+1)-dimensional nonlinear 1.5-layer ocean circulation model without external wind stress forcing is analyzed by using the classical Lie group approach. Some Lie point symmetries and their corresponding two-dimensional reduction equations are obtained.

Study of the X-Ray Diagnosis of Unstable Pelvic Fracture Displacements in Three-Dimensional Space and its Application in Closed Reduction.

Science.gov (United States)

Shi, Chengdi; Cai, Leyi; Hu, Wei; Sun, Junying

2017-09-19

ABSTRACTS Objective: To study the method of X-ray diagnosis of unstable pelvic fractures displaced in three-dimensional (3D) space and its clinical application in closed reduction. Five models of hemipelvic displacement were made in an adult pelvic specimen. Anteroposterior radiographs of the pelvis were analyzed in PACS. The method of X-ray diagnosis was applied in closed reductions. From February 2012 to June 2016, 23 patients (15 men, 8 women; mean age, 43.4 years) with unstable pelvic fractures were included. All patients were treated by closed reduction and percutaneous cannulate screw fixation of the pelvic ring. According to Tile's classification, the patients were classified into type B1 in 7 cases, B2 in 3, B3 in 3, C1 in 5, C2 in 3, and C3 in 2. The operation time and intraoperative blood loss were recorded. Postoperative images were evaluated by Matta radiographic standards. Five models of displacement were made successfully. The X-ray features of the models were analyzed. For clinical patients, the average operation time was 44.8 min (range, 20-90 min) and the average intraoperative blood loss was 35.7 (range, 20-100) mL. According to the Matta standards, 7 cases were excellent, 12 cases were good, and 4 were fair. The displacements in 3D space of unstable pelvic fractures can be diagnosed rapidly by X-ray analysis to guide closed reduction, with a satisfactory clinical outcome.

Coset Space Dimensional Reduction approach to the Standard Model

International Nuclear Information System (INIS)

Farakos, K.; Kapetanakis, D.; Koutsoumbas, G.; Zoupanos, G.

1988-01-01

We present a unified theory in ten dimensions based on the gauge group E 8 , which is dimensionally reduced to the Standard Mode SU 3c xSU 2 -LxU 1 , which breaks further spontaneously to SU 3L xU 1em . The model gives similar predictions for sin 2 θ w and proton decay as the minimal SU 5 G.U.T., while a natural choice of the coset space radii predicts light Higgs masses a la Coleman-Weinberg

Unitarity cuts and Reduction to master integrals in d dimensions for one-loop amplitudes

CERN Document Server

Anastasiou, C; Feng, B; Kunszt, Z; Mastrolia, Pierpaolo; Anastasiou, Charalampos; Britto, Ruth; Feng, Bo; Kunszt, Zoltan; Mastrolia, Pierpaolo

2007-01-01

We present an alternative reduction to master integrals for one-loop amplitudes using a unitarity cut method in arbitrary dimensions. We carry out the reduction in two steps. The first step is a pure four-dimensional cut-integration of tree amplitudes with a mass parameter, and the second step is applying dimensional shift identities to master integrals. This reduction is performed at the integrand level, so that coefficients can be read out algebraically.

Reduced order methods for modeling and computational reduction

CERN Document Server

Rozza, Gianluigi

2014-01-01

This monograph addresses the state of the art of reduced order methods for modeling and computational reduction of complex parametrized systems, governed by ordinary and/or partial differential equations, with a special emphasis on real time computing techniques and applications in computational mechanics, bioengineering and computer graphics.  Several topics are covered, including: design, optimization, and control theory in real-time with applications in engineering; data assimilation, geometry registration, and parameter estimation with special attention to real-time computing in biomedical engineering and computational physics; real-time visualization of physics-based simulations in computer science; the treatment of high-dimensional problems in state space, physical space, or parameter space; the interactions between different model reduction and dimensionality reduction approaches; the development of general error estimation frameworks which take into account both model and discretization effects. This...

The visualization and analysis of urban facility pois using network kernel density estimation constrained by multi-factors

Directory of Open Access Journals (Sweden)

Wenhao Yu

Full Text Available The urban facility, one of the most important service providers is usually represented by sets of points in GIS applications using POI (Point of Interest model associated with certain human social activities. The knowledge about distribution intensity and pattern of facility POIs is of great significance in spatial analysis, including urban planning, business location choosing and social recommendations. Kernel Density Estimation (KDE, an efficient spatial statistics tool for facilitating the processes above, plays an important role in spatial density evaluation, because KDE method considers the decay impact of services and allows the enrichment of the information from a very simple input scatter plot to a smooth output density surface. However, the traditional KDE is mainly based on the Euclidean distance, ignoring the fact that in urban street network the service function of POI is carried out over a network-constrained structure, rather than in a Euclidean continuous space. Aiming at this question, this study proposes a computational method of KDE on a network and adopts a new visualization method by using 3-D "wall" surface. Some real conditional factors are also taken into account in this study, such as traffic capacity, road direction and facility difference. In practical works the proposed method is implemented in real POI data in Shenzhen city, China to depict the distribution characteristic of services under impacts of multi-factors.

Reduction of metal artifact in three-dimensional computed tomography (3D CT) with dental impression materials.

Science.gov (United States)

Park, W S; Kim, K D; Shin, H K; Lee, S H

2007-01-01

Metal Artifact still remains one of the main drawbacks in craniofacial Three-Dimensional Computed Tomography (3D CT). In this study, we tried to test the efficacy of additional silicone dental impression materials as a "tooth shield" for the reduction of metal artifact caused by metal restorations and orthodontic appliances. 6 phantoms with 4 teeth were prepared for this in vitro study. Orthodontic bracket, bands and amalgam restorations were placed in each tooth to reproduce various intraoral conditions. Standardized silicone shields were fabricated and placed around the teeth. CT image acquisition was performed with and without silicone shields. Maximum value, mean, and standard deviation of Hounsfield Units (HU) were compared with the presence of silicone shields. In every situation, metal artifacts were reduced in quality and quantity when silicone shields are used. Amalgam restoration made most serious metal artifact. Silicone shields made by dental impression material might be effective way to reduce the metal artifact caused by dental restoration and orthodontic appliances. This will help more excellent 3D image from 3D CT in craniofacial area.

A Comparison of Machine Learning Methods in a High-Dimensional Classification Problem

OpenAIRE

Zekić-Sušac, Marijana; Pfeifer, Sanja; Šarlija, Nataša

2014-01-01

Background: Large-dimensional data modelling often relies on variable reduction methods in the pre-processing and in the post-processing stage. However, such a reduction usually provides less information and yields a lower accuracy of the model. Objectives: The aim of this paper is to assess the high-dimensional classification problem of recognizing entrepreneurial intentions of students by machine learning methods. Methods/Approach: Four methods were tested: artificial neural networks, CART ...

One-dimensional reduction of viscous jets. I. Theory

Science.gov (United States)

Pitrou, Cyril

2018-04-01

We build a general formalism to describe thin viscous jets as one-dimensional objects with an internal structure. We present in full generality the steps needed to describe the viscous jets around their central line, and we argue that the Taylor expansion of all fields around that line is conveniently expressed in terms of symmetric trace-free tensors living in the two dimensions of the fiber sections. We recover the standard results of axisymmetric jets and we report the first and second corrections to the lowest order description, also allowing for a rotational component around the axis of symmetry. When applied to generally curved fibers, the lowest order description corresponds to a viscous string model whose sections are circular. However, when including the first corrections, we find that curved jets generically develop elliptic sections. Several subtle effects imply that the first corrections cannot be described by a rod model since it amounts to selectively discard some corrections. However, in a fast rotating frame, we find that the dominant effects induced by inertial and Coriolis forces should be correctly described by rod models. For completeness, we also recover the constitutive relations for forces and torques in rod models and exhibit a missing term in the lowest order expression of viscous torque. Given that our method is based on tensors, the complexity of all computations has been beaten down by using an appropriate tensor algebra package such as xAct, allowing us to obtain a one-dimensional description of curved viscous jets with all the first order corrections consistently included. Finally, we find a description for straight fibers with elliptic sections as a special case of these results, and recover that ellipticity is dynamically damped by surface tension. An application to toroidal viscous fibers is presented in the companion paper [Pitrou, Phys. Rev. E 97, 043116 (2018), 10.1103/PhysRevE.97.043116].

Radioactive waste isolation in salt: Peer review of the Office of Nuclear Waste Isolation's draft report on a multifactor test design to investigate uniform corrosion of low-carbon steel

International Nuclear Information System (INIS)

Paddock, R.A.; Lerman, A.; Ditmars, J.D.; Macdonald, D.D.; Peerenboom, J.P.; Was, G.S.; Harrison, W.

1987-01-01

This report documents Argonne National Laboratory's review of an internal technical memorandum prepared by Battelle Memorial Institute's Office of Nuclear Waste Isolation (ONWI) entitled Multifactor Test Design to Investigate Uniform Corrosion of Low-Carbon Steel in a Nuclear Waste Salt Repository Environment. The several major areas of concern identified by peer review panelists are important to the credibility of the test design proposed in the memorandum and are to adequately addressed there. These areas of concern, along with specific recommendations to improve their treatment, are discussed in detail in Sec. 2 of this report. The twenty recommendations, which were abstracted from those discussions, are presented essentially in the order in which they are introduced in Sec. 2

Two-dimensional dynamics of elasto-inertial turbulence and its role in polymer drag reduction

Science.gov (United States)

Sid, S.; Terrapon, V. E.; Dubief, Y.

2018-02-01

The goal of the present study is threefold: (i) to demonstrate the two-dimensional nature of the elasto-inertial instability in elasto-inertial turbulence (EIT), (ii) to identify the role of the bidimensional instability in three-dimensional EIT flows, and (iii) to establish the role of the small elastic scales in the mechanism of self-sustained EIT. Direct numerical simulations of viscoelastic fluid flows are performed in both two- and three-dimensional straight periodic channels using the Peterlin finitely extensible nonlinear elastic model (FENE-P). The Reynolds number is set to Reτ=85 , which is subcritical for two-dimensional flows but beyond the transition for three-dimensional ones. The polymer properties selected correspond to those of typical dilute polymer solutions, and two moderate Weissenberg numbers, Wiτ=40 ,100 , are considered. The simulation results show that sustained turbulence can be observed in two-dimensional subcritical flows, confirming the existence of a bidimensional elasto-inertial instability. The same type of instability is also observed in three-dimensional simulations where both Newtonian and elasto-inertial turbulent structures coexist. Depending on the Wi number, one type of structure can dominate and drive the flow. For large Wi values, the elasto-inertial instability tends to prevail over the Newtonian turbulence. This statement is supported by (i) the absence of typical Newtonian near-wall vortices and (ii) strong similarities between two- and three-dimensional flows when considering larger Wi numbers. The role of small elastic scales is investigated by introducing global artificial diffusion (GAD) in the hyperbolic transport equation for polymers. The aim is to measure how the flow reacts when the smallest elastic scales are progressively filtered out. The study results show that the introduction of large polymer diffusion in the system strongly damps a significant part of the elastic scales that are necessary to feed

The Analysis of Dimensionality Reduction Techniques in Cryptographic Object Code Classification

Energy Technology Data Exchange (ETDEWEB)

Jason L. Wright; Milos Manic

2010-05-01

This paper compares the application of three different dimension reduction techniques to the problem of locating cryptography in compiled object code. A simple classi?er is used to compare dimension reduction via sorted covariance, principal component analysis, and correlation-based feature subset selection. The analysis concentrates on the classi?cation accuracy as the number of dimensions is increased.

Bubble dynamic templated deposition of three-dimensional palladium nanostructure catalysts: Approach to oxygen reduction using macro-, micro-, and nano-architectures on electrode surfaces

International Nuclear Information System (INIS)

Yang Guimei; Chen Xing; Li Jie; Guo Zheng; Liu Jinhuai; Huang Xingjiu

2011-01-01

Highlights: → We synthesize the Pd nanostructures by bubbles dynamic templated. → We obtain Pd nanobuds and Pd nanodendrites by changing the reaction precursor. → We obtain Pd macroelectrode voltammertric behavior using small amount of Pd materials. → We proved a ECE process. → The Pd nanostructures/GCE for O 2 reduction is a 2-step 4-electron process. - Abstract: Three-dimensional (3D) palladium (Pd) nanostructures (that is, nano-buds or nano-dendrites) are fabricated by bubble dynamic templated deposition of Pd onto a glassy carbon electrode (GCE). The morphology can be tailored by changing the precursor concentration and reaction time. Scanning electron microscopy images reveal that nano-buds or nano-dendrites consist of nanoparticles of 40-70 nm in diameter. The electrochemical reduction of oxygen is reported at such kinds of 3D nanostructure electrodes in aqueous solution. Data were collected using cyclic voltammetry. We demonstrate the Pd macroelectrode behavior of Pd nanostructure modified electrode by exploiting the diffusion model of macro-, micro-, and nano-architectures. In contrast to bare GCE, a significant positive shift and splitting of the oxygen reduction peak (vs Ag/AgCl/saturated KCl) at Pd nanostructure modified GCE was observed.

Benchmarking energy performance of residential buildings using two-stage multifactor data envelopment analysis with degree-day based simple-normalization approach

International Nuclear Information System (INIS)

Wang, Endong; Shen, Zhigang; Alp, Neslihan; Barry, Nate

2015-01-01

Highlights: • Two-stage DEA model is developed to benchmark building energy efficiency. • Degree-day based simple normalization is used to neutralize the climatic noise. • Results of a real case study validated the benefits of this new model. - Abstract: Being able to identify detailed meta factors of energy performance is essential for creating effective residential energy-retrofitting strategies. Compared to other benchmarking methods, nonparametric multifactor DEA (data envelopment analysis) is capable of discriminating scale factors from management factors to reveal more details to better guide retrofitting practices. A two-stage DEA energy benchmarking method is proposed in this paper. This method includes (1) first-stage meta DEA which integrates the common degree day metrics for neutralizing noise energy effects of exogenous climatic variables; and (2) second-stage Tobit regression for further detailed efficiency analysis. A case study involving 3-year longitudinal panel data of 189 residential buildings indicated the proposed method has advantages over existing methods in terms of its efficiency in data processing and results interpretation. The results of the case study also demonstrated high consistency with existing linear regression based DEA.

Effective Image Database Search via Dimensionality Reduction

DEFF Research Database (Denmark)

Dahl, Anders Bjorholm; Aanæs, Henrik

2008-01-01

Image search using the bag-of-words image representation is investigated further in this paper. This approach has shown promising results for large scale image collections making it relevant for Internet applications. The steps involved in the bag-of-words approach are feature extraction, vocabul......Image search using the bag-of-words image representation is investigated further in this paper. This approach has shown promising results for large scale image collections making it relevant for Internet applications. The steps involved in the bag-of-words approach are feature extraction......, vocabulary building, and searching with a query image. It is important to keep the computational cost low through all steps. In this paper we focus on the efficiency of the technique. To do that we substantially reduce the dimensionality of the features by the use of PCA and addition of color. Building...... of the visual vocabulary is typically done using k-means. We investigate a clustering algorithm based on the leader follower principle (LF-clustering), in which the number of clusters is not fixed. The adaptive nature of LF-clustering is shown to improve the quality of the visual vocabulary using this...

Reduction of Large Dynamical Systems by Minimization of Evolution Rate

Science.gov (United States)

Girimaji, Sharath S.

1999-01-01

Reduction of a large system of equations to a lower-dimensional system of similar dynamics is investigated. For dynamical systems with disparate timescales, a criterion for determining redundant dimensions and a general reduction method based on the minimization of evolution rate are proposed.

The one-loop Green's functions of dimensionally reduced gauge theories

International Nuclear Information System (INIS)

Ketov, S.V.; Prager, Y.S.

1988-01-01

The dimensional regularization technique as well as that by dimensional reduction is applied to the calculation of the regularized one-loop Green's functions in dsub(o)-dimensional Yang-Mills theory with real massless scalars and spinors in arbitrary (real) representations of a gauge group G. As a particular example, the super-symmetrically regularized one-loop Green's functions of the N=4 supersymmetric Yang-Mills model are derived. (author). 17 refs

One-dimensional structures behind twisted and untwisted superYang-Mills theory

CERN Document Server

Baulieu, Laurent

2011-01-01

We give a one-dimensional interpretation of the four-dimensional twisted N=1 superYang-Mills theory on a Kaehler manifold by performing an appropriate dimensional reduction. We prove the existence of a 6-generator superalgebra, which does not possess any invariant Lagrangian but contains two different subalgebras that determine the twisted and untwisted formulations of the N=1 superYang-Mills theory.

Reduced basis ANOVA methods for partial differential equations with high-dimensional random inputs

Energy Technology Data Exchange (ETDEWEB)

Liao, Qifeng, E-mail: liaoqf@shanghaitech.edu.cn [School of Information Science and Technology, ShanghaiTech University, Shanghai 200031 (China); Lin, Guang, E-mail: guanglin@purdue.edu [Department of Mathematics & School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907 (United States)

2016-07-15

In this paper we present a reduced basis ANOVA approach for partial deferential equations (PDEs) with random inputs. The ANOVA method combined with stochastic collocation methods provides model reduction in high-dimensional parameter space through decomposing high-dimensional inputs into unions of low-dimensional inputs. In this work, to further reduce the computational cost, we investigate spatial low-rank structures in the ANOVA-collocation method, and develop efficient spatial model reduction techniques using hierarchically generated reduced bases. We present a general mathematical framework of the methodology, validate its accuracy and demonstrate its efficiency with numerical experiments.

Topological aspects of classical and quantum (2+1)-dimensional gravity

International Nuclear Information System (INIS)

Soda, Jiro.

1990-03-01

In order to understand (3+1)-dimensional gravity, (2+1)-dimensional gravity is studied as a toy model. Our emphasis is on its topological aspects, because (2+1)-dimensional gravity without matter fields has no local dynamical degrees of freedom. Starting from a review of the canonical ADM formalism and York's formalism for the initial value problem, we will solve the evolution equations of (2+1)-dimensional gravity with a cosmological constant in the case of g=0 and g=1, where g is the genus of Riemann surface. The dynamics of it is understood as the geodesic motion in the moduli space. This remarkable fact is the same with the case of (2+1)-dimensional pure gravity and seen more apparently from the action level. Indeed we will show the phase space reduction of (2+1)-dimensional gravity in the case of g=1. For g ≥ 2, unfortunately we are not able to explicitly perform the phase space reduction of (2+1)-dimensional gravity due to the complexity of the Hamiltonian constraint equation. Based on this result, we will attempt to incorporate matter fields into (2+1)-dimensional pure gravity. The linearization and mini-superspace methods are used for this purpose. By using the linearization method, we conclude that the transverse-traceless part of the energy-momentum tensor affects the geodesic motion. In the case of the Einstein-Maxwell theory, we observe that the Wilson lines interact with the geometry to bend the geodesic motion. We analyze the mini-superspace model of (2+1)-dimensional gravity with the matter fields in the case of g=0 and g=1. For g=0, a wormhole solution is found but for g=1 we can not find an analogous solution. Quantum gravity is also considered and we succeed to perform the phase space reduction of (2+1)-dimensional gravity in the case of g=1 at the quantum level. From this analysis we argue that the conformal rotation is not necessary in the sense that the Euclidean quantum gravity is inappropriate for the full gravity. (author)

High-dimensional data in economics and their (robust) analysis

Czech Academy of Sciences Publication Activity Database

Kalina, Jan

2017-01-01

Roč. 12, č. 1 (2017), s. 171-183 ISSN 1452-4864 R&D Projects: GA ČR GA17-07384S Institutional support: RVO:67985556 Keywords : econometrics * high-dimensional data * dimensionality reduction * linear regression * classification analysis * robustness Subject RIV: BA - General Mathematics OBOR OECD: Business and management http://library.utia.cas.cz/separaty/2017/SI/kalina-0474076.pdf

Higher-order gravity in higher dimensions: geometrical origins of four-dimensional cosmology?

Energy Technology Data Exchange (ETDEWEB)

Troisi, Antonio [Universita degli Studi di Salerno, Dipartimento di Fisica ' ' E.R. Caianiello' ' , Salerno (Italy)

2017-03-15

Determining the cosmological field equations is still very much debated and led to a wide discussion around different theoretical proposals. A suitable conceptual scheme could be represented by gravity models that naturally generalize Einstein theory like higher-order gravity theories and higher-dimensional ones. Both of these two different approaches allow one to define, at the effective level, Einstein field equations equipped with source-like energy-momentum tensors of geometrical origin. In this paper, the possibility is discussed to develop a five-dimensional fourth-order gravity model whose lower-dimensional reduction could provide an interpretation of cosmological four-dimensional matter-energy components. We describe the basic concepts of the model, the complete field equations formalism and the 5-D to 4-D reduction procedure. Five-dimensional f(R) field equations turn out to be equivalent, on the four-dimensional hypersurfaces orthogonal to the extra coordinate, to an Einstein-like cosmological model with three matter-energy tensors related with higher derivative and higher-dimensional counter-terms. By considering the gravity model with f(R) = f{sub 0}R{sup n} the possibility is investigated to obtain five-dimensional power law solutions. The effective four-dimensional picture and the behaviour of the geometrically induced sources are finally outlined in correspondence to simple cases of such higher-dimensional solutions. (orig.)

KK-monopoles and G-structures in M-theory/type IIA reductions

International Nuclear Information System (INIS)

Danielsson, Ulf; Dibitetto, Giuseppe; Guarino, Adolfo

2015-01-01

We argue that M-theory/massive IIA backgrounds including KK-monopoles are suitably described in the language of G-structures and their intrinsic torsion. To this end, we study classes of minimal supergravity models that admit an interpretation as twisted reductions in which the twist parameters are not restricted to satisfy the Jacobi constraints ω ω=0 required by an ordinary Scherk-Schwarz reduction. We first derive the correspondence between four-dimensional data and torsion classes of the internal space and, then, check the one-to-one correspondence between higher-dimensional and four-dimensional equations of motion. Remarkably, the whole construction holds regardless of the Jacobi constraints, thus shedding light upon the string/M-theory interpretation of (smeared) KK-monopoles.

Thermogravimetric study of the kinetics of lithium titanate reduction by hydrogen

International Nuclear Information System (INIS)

Sonak, Sagar; Rakesh, R.; Jain, Uttam; Mukherjee, Abhishek; Kumar, Sanjay; Krishnamurthy, Nagaiyar

2014-01-01

Highlights: • Li 2 TiO 3 powder is synthesized by the gel combustion route. • Activation energy of reduction of Li 2 TiO 3 by H 2 found out to be 27.45 kJ/mol H 2 . • Non-stoichiometric phase of Li 2 TiO 3 is formed in hydrogen atmosphere. • One-dimensional diffusion appears to be the most probable mechanism of reduction. - Abstract: The lithium titanate powder was synthesized by gel-combustion route. The mechanism and the kinetics of hydrogen interaction with lithium titanate powder were studied using non-isothermal thermogravimetric technique. Lithium titanate underwent reduction in hydrogen atmosphere which led to the formation of oxygen deficient non-stoichiometric compound in lithium titanate. One-dimensional diffusion appeared to be the most probable reaction mechanism. The activation energy for reduction of lithium titanate under hydrogen atmosphere was found to be 27.4 kJ/mol/K. Structural changes after hydrogen reduction in lithium titanate were observed in X-ray diffraction analysis

Dimensionality reduction for the quantitative evaluation of a smartphone-based Timed Up and Go test.

Science.gov (United States)

Palmerini, Luca; Mellone, Sabato; Rocchi, Laura; Chiari, Lorenzo

2011-01-01

The Timed Up and Go is a clinical test to assess mobility in the elderly and in Parkinson's disease. Lately instrumented versions of the test are being considered, where inertial sensors assess motion. To improve the pervasiveness, ease of use, and cost, we consider a smartphone's accelerometer as the measurement system. Several parameters (usually highly correlated) can be computed from the signals recorded during the test. To avoid redundancy and obtain the features that are most sensitive to the locomotor performance, a dimensionality reduction was performed through principal component analysis (PCA). Forty-nine healthy subjects of different ages were tested. PCA was performed to extract new features (principal components) which are not redundant combinations of the original parameters and account for most of the data variability. They can be useful for exploratory analysis and outlier detection. Then, a reduced set of the original parameters was selected through correlation analysis with the principal components. This set could be recommended for studies based on healthy adults. The proposed procedure could be used as a first-level feature selection in classification studies (i.e. healthy-Parkinson's disease, fallers-non fallers) and could allow, in the future, a complete system for movement analysis to be incorporated in a smartphone.

One-dimensional structures behind twisted and untwisted super Yang-Mills theory

Energy Technology Data Exchange (ETDEWEB)

Baulieu, Laurent [CERN, Geneve (Switzerland). Theoretical Div.; Toppan, Francesco, E-mail: baulieu@lpthe.jussieu.f, E-mail: toppan@cbpf.b [Centro Brasileiro de Pesquisas Fisicas (CBPF), Rio de Janeiro, RJ (Brazil)

2010-07-01

We give a one-dimensional interpretation of the four-dimensional twisted N = 1 super Yang-Mills theory on a Kaehler manifold by performing an appropriate dimensional reduction. We prove the existence of a 6-generator superalgebra, which does not possess any invariant Lagrangian but contains two different subalgebras that determine the twisted and untwisted formulations of the N = 1 super Yang-Mills theory. (author)

One-dimensional structures behind twisted and untwisted super Yang-Mills theory

International Nuclear Information System (INIS)

Baulieu, Laurent

2010-01-01

We give a one-dimensional interpretation of the four-dimensional twisted N = 1 super Yang-Mills theory on a Kaehler manifold by performing an appropriate dimensional reduction. We prove the existence of a 6-generator superalgebra, which does not possess any invariant Lagrangian but contains two different subalgebras that determine the twisted and untwisted formulations of the N = 1 super Yang-Mills theory. (author)

An iterated Laplacian based semi-supervised dimensionality reduction for classification of breast cancer on ultrasound images.

Science.gov (United States)

Liu, Xiao; Shi, Jun; Zhou, Shichong; Lu, Minhua

2014-01-01

The dimensionality reduction is an important step in ultrasound image based computer-aided diagnosis (CAD) for breast cancer. A newly proposed l2,1 regularized correntropy algorithm for robust feature selection (CRFS) has achieved good performance for noise corrupted data. Therefore, it has the potential to reduce the dimensions of ultrasound image features. However, in clinical practice, the collection of labeled instances is usually expensive and time costing, while it is relatively easy to acquire the unlabeled or undetermined instances. Therefore, the semi-supervised learning is very suitable for clinical CAD. The iterated Laplacian regularization (Iter-LR) is a new regularization method, which has been proved to outperform the traditional graph Laplacian regularization in semi-supervised classification and ranking. In this study, to augment the classification accuracy of the breast ultrasound CAD based on texture feature, we propose an Iter-LR-based semi-supervised CRFS (Iter-LR-CRFS) algorithm, and then apply it to reduce the feature dimensions of ultrasound images for breast CAD. We compared the Iter-LR-CRFS with LR-CRFS, original supervised CRFS, and principal component analysis. The experimental results indicate that the proposed Iter-LR-CRFS significantly outperforms all other algorithms.

Three-dimensional oscillator and Coulomb systems reduced from Kaehler spaces

International Nuclear Information System (INIS)

Nersessian, Armen; Yeranyan, Armen

2004-01-01

We define the oscillator and Coulomb systems on four-dimensional spaces with U(2)-invariant Kaehler metric and perform their Hamiltonian reduction to the three-dimensional oscillator and Coulomb systems specified by the presence of Dirac monopoles. We find the Kaehler spaces with conic singularity, where the oscillator and Coulomb systems on three-dimensional sphere and two-sheet hyperboloid originate. Then we construct the superintegrable oscillator system on three-dimensional sphere and hyperboloid, coupled to a monopole, and find their four-dimensional origins. In the latter case the metric of configuration space is a non-Kaehler one. Finally, we extend these results to the family of Kaehler spaces with conic singularities

High-dimensional Data in Economics and their (Robust) Analysis

Czech Academy of Sciences Publication Activity Database

Kalina, Jan

2017-01-01

Roč. 12, č. 1 (2017), s. 171-183 ISSN 1452-4864 R&D Projects: GA ČR GA17-07384S Grant - others:GA ČR(CZ) GA13-01930S Institutional support: RVO:67985807 Keywords : econometrics * high-dimensional data * dimensionality reduction * linear regression * classification analysis * robustness Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Statistics and probability

Gauged supergravities from M-theory reductions

Science.gov (United States)

Katmadas, Stefanos; Tomasiello, Alessandro

2018-04-01

In supergravity compactifications, there is in general no clear prescription on how to select a finite-dimensional family of metrics on the internal space, and a family of forms on which to expand the various potentials, such that the lower-dimensional effective theory is supersymmetric. We propose a finite-dimensional family of deformations for regular Sasaki-Einstein seven-manifolds M 7, relevant for M-theory compactifications down to four dimensions. It consists of integrable Cauchy-Riemann structures, corresponding to complex deformations of the Calabi-Yau cone M 8 over M 7. The non-harmonic forms we propose are the ones contained in one of the Kohn-Rossi cohomology groups, which is finite-dimensional and naturally controls the deformations of Cauchy-Riemann structures. The same family of deformations can be also described in terms of twisted cohomology of the base M 6, or in terms of Milnor cycles arising in deformations of M 8. Using existing results on SU(3) structure compactifications, we briefly discuss the reduction of M-theory on our class of deformed Sasaki-Einstein manifolds to four-dimensional gauged supergravity.

One-dimensional reduction of viscous jets. II. Applications

Science.gov (United States)

Pitrou, Cyril

2018-04-01

In a companion paper [Phys. Rev. E 97, 043115 (2018), 10.1103/PhysRevE.97.043115], a formalism allowing to describe viscous fibers as one-dimensional objects was developed. We apply it to the special case of a viscous fluid torus. This allows to highlight the differences with the basic viscous string model and with its viscous rod model extension. In particular, an elliptic deformation of the torus section appears because of surface tension effects, and this cannot be described by viscous string nor viscous rod models. Furthermore, we study the Rayleigh-Plateau instability for periodic deformations around the perfect torus, and we show that the instability is not sufficient to lead to the torus breakup in several droplets before it collapses to a single spherical drop. Conversely, a rotating torus is dynamically attracted toward a stationary solution, around which the instability can develop freely and split the torus in multiple droplets.

Facile Synthesis of Quasi-One-Dimensional Au/PtAu Heterojunction Nanotubes and Their Application as Catalysts in an Oxygen-Reduction Reaction.

Science.gov (United States)

Cai, Kai; Liu, Jiawei; Zhang, Huan; Huang, Zhao; Lu, Zhicheng; Foda, Mohamed F; Li, Tingting; Han, Heyou

2015-05-11

An intermediate-template-directed method has been developed for the synthesis of quasi-one-dimensional Au/PtAu heterojunction nanotubes by the heterogeneous nucleation and growth of Au on Te/Pt core-shell nanostructures in aqueous solution. The synthesized porous Au/PtAu bimetallic nanotubes (PABNTs) consist of porous tubular framework and attached Au nanoparticles (AuNPs). The reaction intermediates played an important role in the preparation, which fabricated the framework and provided a localized reducing agent for the reduction of the Au and Pt precursors. The Pt7 Au PABNTs showed higher electrocatalytic activity and durability in the oxygen-reduction reaction (ORR) in 0.1 M HClO4 than porous Pt nanotubes (PtNTs) and commercially available Pt/C. The mass activity of PABNTs was 218 % that of commercial Pt/C after an accelerated durability test. This study demonstrates the potential of PABNTs as highly efficient electrocatalysts. In addition, this method provides a facile strategy for the synthesis of desirable hetero-nanostructures with controlled size and shape by utilizing an intermediate template. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Facile fabrication of three-dimensional mesoporous Si/SiC composites via one-step magnesiothermic reduction at relative low temperature

Energy Technology Data Exchange (ETDEWEB)

Jiang, Zhihang; Ma, Yongjun [State Key Laboratory Cultivation Base for Nonmetal Composites and Functional Materials, Southwest University of Science and Technology, Mianyang 621010 (China); Zhou, Yong [Eco-materials and Renewable Energy Research Center (ERERC), School of Physics, National Lab of Solid State Microstructure, ERERC, Nanjing University, Nanjing 210093 (China); Hu, Shanglian [School of Life Science and Engineering, Southwest University of Science and Technology, Mianyang 621010 (China); Han, Chaojiang [State Key Laboratory Cultivation Base for Nonmetal Composites and Functional Materials, Southwest University of Science and Technology, Mianyang 621010 (China); Pei, Chonghua, E-mail: peichonghua@swust.edu.cn [State Key Laboratory Cultivation Base for Nonmetal Composites and Functional Materials, Southwest University of Science and Technology, Mianyang 621010 (China)

2013-10-15

Graphical abstract: - Highlights: • The Si/SiC composites were synthesized by one-step magnesiothermic reduction. • The mesoporous composites have a high specific surface area (655.7 m{sup 2} g{sup −1}). • The composites exhibited a strong photoluminescence and better biocompatibility. • The mechanisms of formation and photoluminescence of sample were discussed. - Abstract: By converting modified silica aerogels to the corresponding silicon/silicon carbide (Si/SiC) without losing its nanostructure, three-dimensional mesoporous (3DM) Si/SiC composites are successfully synthesized via one-step magnesothermic reduction at relative low temperature (650 °C). The phase composition and microstructure of the resulting samples are measured by X-ray diffraction (XRD), energy dispersive X-ray spectroscopy (EDX), Raman spectra, scanning electron microscopy (SEM) and transmission electron microscopy (TEM). N{sub 2}-sorption isotherms results show that the products have high Brunauer–Emmett–Teller (BET) specific surface areas (up to 656 m{sup 2} g{sup −1}) and narrow pore-size distributions (1.5–30 nm). The composites exhibit a strong photoluminescence (PL) in blue-green light region (peak centered at 533 nm). We have set out work on the biocompatibility and enhancing PL of samples. As a result of excellent performances of the composites, it can be expected to have significant application in optoelectronics, biosensors, biological tracer and so on.

On reductions of the discrete Kadomtsev-Petviashvili-type equations

Science.gov (United States)

Fu, Wei; Nijhoff, Frank W.

2017-12-01

The reduction by restricting the spectral parameters k and k\\prime on a generic algebraic curve of degree N is performed for the discrete AKP, BKP and CKP equations, respectively. A variety of two-dimensional discrete integrable systems possessing a more general solution structure arise from the reduction, and in each case a unified formula for the generic positive integer N≥slant 2 is given to express the corresponding reduced integrable lattice equations. The obtained extended two-dimensional lattice models give rise to many important integrable partial difference equations as special degenerations. Some new integrable lattice models such as the discrete Sawada-Kotera, Kaup-Kupershmidt and Hirota-Satsuma equations in extended form are given as examples within the framework.

Effects of applying three-dimensional seismic isolation system on the seismic design of FBR

International Nuclear Information System (INIS)

Hirata, Kazuta; Yabana, Shuichi; Kanazawa, Kenji; Matsuda, Akihiro

1997-01-01

In this study conceptional three-dimensional seismic isolation system for fast breeder reactor (FBR) is proposed. Effects of applying three-dimensional seismic isolation system on the seismic design for the FBR equipment are evaluated quantitatively. From the evaluation, it is concluded following effects are expected by applying the three-dimensional seismic isolation system to the FBR and the effects are evaluated quantitatively. (1) Reduction of membrane thickness of the reactor vessel (2) Suppression of uplift of fuels by reducing vertical seismic response of the core (3) Reduction of the supports for the piping system (4) Three-dimensional base isolation system for the whole reactor building is advantageous to the combined isolation system of horizontal base isolation for the reactor building and vertical isolation for the equipment. (author)

Exact solutions for the (2+1)-dimensional Boiti-Leon-Pempielli system

International Nuclear Information System (INIS)

Hu, Y H; Zheng, C L

2008-01-01

The object reduction approach is applied to the (2+1)-dimensional Boiti-Leon-Pempielli system using a special conditional similarity reduction. Abundant exact solutions of this system, including the hyperboloid function solutions, the trigonometric function solutions and a rational function solution, are obtained

Visualizing histopathologic deep learning classification and anomaly detection using nonlinear feature space dimensionality reduction.

Science.gov (United States)

Faust, Kevin; Xie, Quin; Han, Dominick; Goyle, Kartikay; Volynskaya, Zoya; Djuric, Ugljesa; Diamandis, Phedias

2018-05-16

There is growing interest in utilizing artificial intelligence, and particularly deep learning, for computer vision in histopathology. While accumulating studies highlight expert-level performance of convolutional neural networks (CNNs) on focused classification tasks, most studies rely on probability distribution scores with empirically defined cutoff values based on post-hoc analysis. More generalizable tools that allow humans to visualize histology-based deep learning inferences and decision making are scarce. Here, we leverage t-distributed Stochastic Neighbor Embedding (t-SNE) to reduce dimensionality and depict how CNNs organize histomorphologic information. Unique to our workflow, we develop a quantitative and transparent approach to visualizing classification decisions prior to softmax compression. By discretizing the relationships between classes on the t-SNE plot, we show we can super-impose randomly sampled regions of test images and use their distribution to render statistically-driven classifications. Therefore, in addition to providing intuitive outputs for human review, this visual approach can carry out automated and objective multi-class classifications similar to more traditional and less-transparent categorical probability distribution scores. Importantly, this novel classification approach is driven by a priori statistically defined cutoffs. It therefore serves as a generalizable classification and anomaly detection tool less reliant on post-hoc tuning. Routine incorporation of this convenient approach for quantitative visualization and error reduction in histopathology aims to accelerate early adoption of CNNs into generalized real-world applications where unanticipated and previously untrained classes are often encountered.

Super integrable four-dimensional autonomous mappings

International Nuclear Information System (INIS)

Capel, H W; Sahadevan, R; Rajakumar, S

2007-01-01

A systematic investigation of the complete integrability of a fourth-order autonomous difference equation of the type w(n + 4) = w(n)F(w(n + 1), w(n + 2), w(n + 3)) is presented. We identify seven distinct families of four-dimensional mappings which are super integrable and have three (independent) integrals via a duality relation as introduced in a recent paper by Quispel, Capel and Roberts (2005 J. Phys. A: Math. Gen. 38 3965-80). It is observed that these seven families can be related to the four-dimensional symplectic mappings with two integrals including all the four-dimensional periodic reductions of the integrable double-discrete modified Korteweg-deVries and sine-Gordon equations treated in an earlier paper by two of us (Capel and Sahadevan 2001 Physica A 289 86-106)

Formulation of 11-dimensional supergravity in superspace

International Nuclear Information System (INIS)

Cremmer, E.; Ferrara, S.

1980-01-01

We formulate on-shell 11-dimensional supergravity in superspace and express its equations of motion in terms of purely geometrical quantities. All torsion and curvature components are solved in terms of a single superfield Wsub(rstu), totally antisymmetric in its (flat vector) indices. The dimensional reduction of this formulation is expected to be related to the superspace formulation of N = 8 extended supergravity and might explain the origin of the hidden (local) SU(8) and (global) E 7 symmetries present in this theory. (orig.)

Wake Management Strategies for Reduction of Turbomachinery Fan Noise

Science.gov (United States)

Waitz, Ian A.

1998-01-01

The primary objective of our work was to evaluate and test several wake management schemes for the reduction of turbomachinery fan noise. Throughout the course of this work we relied on several tools. These include 1) Two-dimensional steady boundary-layer and wake analyses using MISES (a thin-shear layer Navier-Stokes code), 2) Two-dimensional unsteady wake-stator interaction simulations using UNSFLO, 3) Three-dimensional, steady Navier-Stokes rotor simulations using NEWT, 4) Internal blade passage design using quasi-one-dimensional passage flow models developed at MIT, 5) Acoustic modeling using LINSUB, 6) Acoustic modeling using VO72, 7) Experiments in a low-speed cascade wind-tunnel, and 8) ADP fan rig tests in the MIT Blowdown Compressor.

Spinors and supersymmetry in four-dimensional Euclidean space

International Nuclear Information System (INIS)

McKeon, D.G.C.; Sherry, T.N.

2001-01-01

Spinors in four-dimensional Euclidean space are treated using the decomposition of the Euclidean space SO(4) symmetry group into SU(2)xSU(2). Both 2- and 4-spinor representations of this SO(4) symmetry group are shown to differ significantly from the corresponding spinor representations of the SO(3, 1) symmetry group in Minkowski space. The simplest self conjugate supersymmetry algebra allowed in four-dimensional Euclidean space is demonstrated to be an N=2 supersymmetry algebra which resembles the N=2 supersymmetry algebra in four-dimensional Minkowski space. The differences between the two supersymmetry algebras gives rise to different representations; in particular an analysis of the Clifford algebra structure shows that the momentum invariant is bounded above by the central charges in 4dE, while in 4dM the central charges bound the momentum invariant from below. Dimensional reduction of the N=1 SUSY algebra in six-dimensional Minkowski space (6dM) to 4dE reproduces our SUSY algebra in 4dE. This dimensional reduction can be used to introduce additional generators into the SUSY algebra in 4dE. Well known interpolating maps are used to relate the N=2 SUSY algebra in 4dE derived in this paper to the N=2 SUSY algebra in 4dM. The nature of the spinors in 4dE allows us to write an axially gauge invariant model which is shown to be both Hermitian and anomaly-free. No equivalent model exists in 4dM. Useful formulae in 4dE are collected together in two appendixes

Gauss-Bonnet actions and their dimensionally reduced descendants

International Nuclear Information System (INIS)

Mueller-Hoissen, F.

1989-01-01

A brief introduction to Gauss-Bonnet type generalizations of the Einstein-Hilbert gravity action in more than four dimensions is given and the structure of associated (effective) theories obtained by dimensional reduction is discussed. (author)

Specific Features of Diagnostics of Efficiency of Management of Innovation Risks at Enterprises of the Baking Industry (Cost-is-no-object Approach

Directory of Open Access Journals (Sweden)

Bilynska Juliana V.

2014-03-01

Full Text Available The article analyses diagnostics of efficiency of management of innovation risks through cost optimisation. Management of costs on innovation grounds is carried out with the aim of their reduction. In order to realise measures on reduction of influence of innovation risks in the system of cost management the article specifies the most important factors and builds multi-factor models. The process of study of influence of the innovation risk upon the cost value of the sold products of bakeries is presented in the form of a scheme of logically united stages. The article takes into account all restrictions and requirements, eliminates multi-collinearity and uses MS Excel Regression analysis for modelling dynamic multi-factor models of cost value of sold products of the studied bakeries. In the result of the study the article obtains main factors that would be used for forecasting tendencies of development of the studied enterprises, development of the decision making system and improvement of methodical provision of innovation risk management.

Euclidean D-branes and higher-dimensional gauge theory

International Nuclear Information System (INIS)

Acharya, B.S.; Figueroa-O'Farrill, J.M.; Spence, B.; O'Loughlin, M.

1997-07-01

We consider euclidean D-branes wrapping around manifolds of exceptional holonomy in dimensions seven and eight. The resulting theory on the D-brane-that is, the dimensional reduction of 10-dimensional supersymmetric Yang-Mills theory-is a cohomological field theory which describes the topology of the moduli space of instantons. The 7-dimensional theory is an N T =2 (or balanced) cohomological theory given by an action potential of Chern-Simons type. As a by-product of this method, we construct a related cohomological field theory which describes the monopole moduli space on a 7-manifold of G 2 holonomy. (author). 22 refs, 3 tabs

System reduction for nanoscale IC design

CERN Document Server

2017-01-01

This book describes the computational challenges posed by the progression toward nanoscale electronic devices and increasingly short design cycles in the microelectronics industry, and proposes methods of model reduction which facilitate circuit and device simulation for specific tasks in the design cycle. The goal is to develop and compare methods for system reduction in the design of high dimensional nanoelectronic ICs, and to test these methods in the practice of semiconductor development. Six chapters describe the challenges for numerical simulation of nanoelectronic circuits and suggest model reduction methods for constituting equations. These include linear and nonlinear differential equations tailored to circuit equations and drift diffusion equations for semiconductor devices. The performance of these methods is illustrated with numerical experiments using real-world data. Readers will benefit from an up-to-date overview of the latest model reduction methods in computational nanoelectronics.

Dimension reduction methods for microarray data: a review

Directory of Open Access Journals (Sweden)

Rabia Aziz

2017-03-01

Full Text Available Dimension reduction has become inevitable for pre-processing of high dimensional data. “Gene expression microarray data” is an instance of such high dimensional data. Gene expression microarray data displays the maximum number of genes (features simultaneously at a molecular level with a very small number of samples. The copious numbers of genes are usually provided to a learning algorithm for producing a complete characterization of the classification task. However, most of the times the majority of the genes are irrelevant or redundant to the learning task. It will deteriorate the learning accuracy and training speed as well as lead to the problem of overfitting. Thus, dimension reduction of microarray data is a crucial preprocessing step for prediction and classification of disease. Various feature selection and feature extraction techniques have been proposed in the literature to identify the genes, that have direct impact on the various machine learning algorithms for classification and eliminate the remaining ones. This paper describes the taxonomy of dimension reduction methods with their characteristics, evaluation criteria, advantages and disadvantages. It also presents a review of numerous dimension reduction approaches for microarray data, mainly those methods that have been proposed over the past few years.

AN EFFECTIVE MULTI-CLUSTERING ANONYMIZATION APPROACH USING DISCRETE COMPONENT TASK FOR NON-BINARY HIGH DIMENSIONAL DATA SPACES

Directory of Open Access Journals (Sweden)

L.V. Arun Shalin

2016-01-01

Full Text Available Clustering is a process of grouping elements together, designed in such a way that the elements assigned to similar data points in a cluster are more comparable to each other than the remaining data points in a cluster. During clustering certain difficulties related when dealing with high dimensional data are ubiquitous and abundant. Works concentrated using anonymization method for high dimensional data spaces failed to address the problem related to dimensionality reduction during the inclusion of non-binary databases. In this work we study methods for dimensionality reduction for non-binary database. By analyzing the behavior of dimensionality reduction for non-binary database, results in performance improvement with the help of tag based feature. An effective multi-clustering anonymization approach called Discrete Component Task Specific Multi-Clustering (DCTSM is presented for dimensionality reduction on non-binary database. To start with we present the analysis of attribute in the non-binary database and cluster projection identifies the sparseness degree of dimensions. Additionally with the quantum distribution on multi-cluster dimension, the solution for relevancy of attribute and redundancy on non-binary data spaces is provided resulting in performance improvement on the basis of tag based feature. Multi-clustering tag based feature reduction extracts individual features and are correspondingly replaced by the equivalent feature clusters (i.e. tag clusters. During training, the DCTSM approach uses multi-clusters instead of individual tag features and then during decoding individual features is replaced by corresponding multi-clusters. To measure the effectiveness of the method, experiments are conducted on existing anonymization method for high dimensional data spaces and compared with the DCTSM approach using Statlog German Credit Data Set. Improved tag feature extraction and minimum error rate compared to conventional anonymization

Apparent destruction of superconductivity in the disordered one-dimensional limit

International Nuclear Information System (INIS)

Graybeal, J.M.; Mankiewich, P.M.; Dynes, R.C.; Beasley, M.R.

1987-01-01

We present the results of a model-system study of the competition between superconductivity and disorder in narrow superconducting wires. As one moves from the two-dimensional regime toward the one-dimensional limit, large and systematic reductions in the superconducting transition temperature are obtained. The observed behavior extrapolates to the total destruction of superconductivity in the disordered one-dimensional limit. Our findings are in clear disagreement with a recent theoretical treatment. In addition, the superconducting fluctuations appear to be modified by disorder for the narrowest samples

8q24 sequence variants in relation to prostate cancer risk among men of African descent: A case-control study

Directory of Open Access Journals (Sweden)

VanCleave Tiva T

2010-06-01

Full Text Available Abstract Background Human chromosome 8q24 has been implicated in prostate tumorigenesis. Methods Consequently, we evaluated seven 8q24 sequence variants relative to prostate cancer (PCA in a case-control study involving men of African descent. Genetic alterations were detected in germ-line DNA from 195 incident PCA cases and 531 controls using TaqMan polymerase chain reaction (PCR. Results Inheritance of the 8q24 rs16901979 T allele corresponded to a 2.5-fold increase in the risk of developing PCA for our test group. These findings were validated using multifactor dimensionality reduction (MDR and permutation testing (p = 0.038. The remaining 8q24 targets were not significantly related to PCA outcomes. Conclusions Although compelling evidence suggests that the 8q24 rs16901979 locus may serve as an effective PCA predictor, our findings require additional evaluation in larger studies.

A polyacrylonitrile copolymer-silica template for three-dimensional hierarchical porous carbon as a Pt catalyst support for the oxygen reduction reaction.

Science.gov (United States)

Liu, Minmin; Li, Jian; Cai, Chao; Zhou, Ziwei; Ling, Yun; Liu, Rui

2017-08-01

Herein, we report a novel route to construct a hierarchical three-dimensional porous carbon (3DC) through a copolymer-silica assembly. In the synthesis, silica acts as a hard template and leads to the formation of an interconnected 3D macropore, whereas styrene-co-acrylonitrile polymer has been used as both a carbon source and a soft template for micro- and meso-pores. The obtained 3DC materials possess a large surface area (∼550.5 m 2 g -1 ), which facilitates high dispersion of Pt nanoparticles on the carbon support. The 3DC-supported Pt electrocatalyst shows excellent performance in the oxygen reduction reaction (ORR). The easy processing ability along with the characteristics of hierarchical porosity offers a new strategy for the preparation of carbon nanomaterials for energy application.

Facile preparation of three-dimensional Co1-xS/sulfur and nitrogen-codoped graphene/carbon foam for highly efficient oxygen reduction reaction

Science.gov (United States)

Liang, Hui; Li, Chenwei; Chen, Tao; Cui, Liang; Han, Jingrui; Peng, Zhi; Liu, Jingquan

2018-02-01

Because of the urgent need for renewable resources, oxygen reduction reaction (ORR) has been widely studied. Finding efficient and low cost non-precious metal catalyst is increasingly critical. In this study, melamine foam is used as template to obtain porous sulfur and nitrogen-codoped graphene/carbon foam with uniformly distributed cobalt sulfide nanoparticles (Co1-xS/SNG/CF) which is prepared by a simple infiltration-drying-sulfuration method. It is noteworthy that melamine foam not only works as a three-dimensional support skeleton, but also provides a nitrogen source without any environmental pollution. Such Co1-xS/SNG/CF catalyst shows excellent oxygen reduction catalytic performance with an onset potential of only 0.99 V, which is the same as that of Pt/C catalyst (Eonset = 0.99 V). Furthermore, the stability and methanol tolerance of Co1-xS/SNG/CF are more outstanding than those of Pt/C catalyst. Our work manifests a facile method to prepare S and N-codoped 3D graphene network decorated with Co1-xS nanoparticles, which may be utilized as potential alternative to the expensive Pt/C catalysts toward ORR.

ldr: An R Software Package for Likelihood-Based Su?cient Dimension Reduction

Directory of Open Access Journals (Sweden)

Kofi Placid Adragni

2014-11-01

Full Text Available In regression settings, a su?cient dimension reduction (SDR method seeks the core information in a p-vector predictor that completely captures its relationship with a response. The reduced predictor may reside in a lower dimension d < p, improving ability to visualize data and predict future observations, and mitigating dimensionality issues when carrying out further analysis. We introduce ldr, a new R software package that implements three recently proposed likelihood-based methods for SDR: covariance reduction, likelihood acquired directions, and principal fitted components. All three methods reduce the dimensionality of the data by pro jection into lower dimensional subspaces. The package also implements a variable screening method built upon principal ?tted components which makes use of ?exible basis functions to capture the dependencies between the predictors and the response. Examples are given to demonstrate likelihood-based SDR analyses using ldr, including estimation of the dimension of reduction subspaces and selection of basis functions. The ldr package provides a framework that we hope to grow into a comprehensive library of likelihood-based SDR methodologies.

Posterior Reduction and Monosegmental Fusion with Intraoperative Three-dimensional Navigation System in the Treatment of High-grade Developmental Spondylolisthesis

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Wei Tian

2015-01-01

Full Text Available Background: The treatment of high-grade developmental spondylolisthesis (HGDS is still challenging and controversial. In this study, we investigated the efficacy of the posterior reduction and monosegmental fusion assisted by intraoperative three-dimensional (3D navigation system in managing the HGDS. Methods: Thirteen consecutive HGDS patients were treated with posterior decompression, reduction and monosegmental fusion of L5/S1, assisted by intraoperative 3D navigation system. The clinical and radiographic outcomes were evaluated, with a minimum follow-up of 2 years. The differences between the pre- and post-operative measures were statistically analyzed using a two-tailed, paired t-test. Results: At most recent follow-up, 12 patients were pain-free. Only 1 patient had moderate pain. There were no permanent neurological complications or pseudarthrosis. The magnetic resonance imaging showed that there was no obvious disc degeneration in the adjacent segment. All radiographic parameters were improved. Mean slippage improved from 63.2% before surgery to 12.2% after surgery and 11.0% at latest follow-up. Lumbar lordosis changed from preoperative 34.9 ± 13.3° to postoperative 50.4 ± 9.9°, and 49.3 ± 7.8° at last follow-up. L5 incidence improved from 71.0 ± 11.3° to 54.0 ± 11.9° and did not change significantly at the last follow-up 53.1 ± 15.4°. While pelvic incidence remained unchanged, sacral slip significantly decreased from preoperative 32.7 ± 12.5° to postoperative 42.6 ± 9.8°and remained constant to the last follow-up 44.4 ± 6.9°. Pelvic tilt significantly decreased from 38.4 ± 12.5° to 30.9 ± 8.1° and remained unchanged at the last follow-up 28.1 ± 11.2°. Conclusions: Posterior reduction and monosegmental fusion of L5/S1 assisted by intraoperative 3D navigation are an effective technique for managing high-grade dysplastic spondylolisthesis. A complete reduction of local deformity and excellent correction of overall

Radioactive waste isolation in salt: Peer review of the Office of Nuclear Waste Isolation's draft report on a multifactor test design to investigate uniform corrosion of low-carbon steel

Energy Technology Data Exchange (ETDEWEB)

Paddock, R.A.; Lerman, A.; Ditmars, J.D.; Macdonald, D.D.; Peerenboom, J.P.; Was, G.S.; Harrison, W.

1987-01-01

This report documents Argonne National Laboratory's review of an internal technical memorandum prepared by Battelle Memorial Institute's Office of Nuclear Waste Isolation (ONWI) entitled Multifactor Test Design to Investigate Uniform Corrosion of Low-Carbon Steel in a Nuclear Waste Salt Repository Environment. The several major areas of concern identified by peer review panelists are important to the credibility of the test design proposed in the memorandum and are to adequately addressed there. These areas of concern, along with specific recommendations to improve their treatment, are discussed in detail in Sec. 2 of this report. The twenty recommendations, which were abstracted from those discussions, are presented essentially in the order in which they are introduced in Sec. 2.

Integration of metabolomics and proteomics in molecular plant physiology--coping with the complexity by data-dimensionality reduction.

Science.gov (United States)

Weckwerth, Wolfram

2008-02-01

In recent years, genomics has been extended to functional genomics. Toward the characterization of organisms or species on the genome level, changes on the metabolite and protein level have been shown to be essential to assign functions to genes and to describe the dynamic molecular phenotype. Gas chromatography (GC) and liquid chromatography coupled to mass spectrometry (GC- and LC-MS) are well suited for the fast and comprehensive analysis of ultracomplex metabolite samples. For the integration of metabolite profiles with quantitative protein profiles, a high throughput (HTP) shotgun proteomics approach using LC-MS and label-free quantification of unique proteins in a complex protein digest is described. Multivariate statistics are applied to examine sample pattern recognition based on data-dimensionality reduction and biomarker identification in plant systems biology. The integration of the data reveal multiple correlative biomarkers providing evidence for an increase of information in such holistic approaches. With computational simulation of metabolic networks and experimental measurements, it can be shown that biochemical regulation is reflected by metabolite network dynamics measured in a metabolomics approach. Examples in molecular plant physiology are presented to substantiate the integrative approach.

Model reduction of parametrized systems

CERN Document Server

Ohlberger, Mario; Patera, Anthony; Rozza, Gianluigi; Urban, Karsten

2017-01-01

The special volume offers a global guide to new concepts and approaches concerning the following topics: reduced basis methods, proper orthogonal decomposition, proper generalized decomposition, approximation theory related to model reduction, learning theory and compressed sensing, stochastic and high-dimensional problems, system-theoretic methods, nonlinear model reduction, reduction of coupled problems/multiphysics, optimization and optimal control, state estimation and control, reduced order models and domain decomposition methods, Krylov-subspace and interpolatory methods, and applications to real industrial and complex problems. The book represents the state of the art in the development of reduced order methods. It contains contributions from internationally respected experts, guaranteeing a wide range of expertise and topics. Further, it reflects an important effor t, carried out over the last 12 years, to build a growing research community in this field. Though not a textbook, some of the chapters ca...

Three New (2+1)-dimensional Integrable Systems and Some Related Darboux Transformations

Science.gov (United States)

Guo, Xiu-Rong

2016-06-01

We introduce two operator commutators by using different-degree loop algebras of the Lie algebra A1, then under the framework of zero curvature equations we generate two (2+1)-dimensional integrable hierarchies, including the (2+1)-dimensional shallow water wave (SWW) hierarchy and the (2+1)-dimensional Kaup-Newell (KN) hierarchy. Through reduction of the (2+1)-dimensional hierarchies, we get a (2+1)-dimensional SWW equation and a (2+1)-dimensional KN equation. Furthermore, we obtain two Darboux transformations of the (2+1)-dimensional SWW equation. Similarly, the Darboux transformations of the (2+1)-dimensional KN equation could be deduced. Finally, with the help of the spatial spectral matrix of SWW hierarchy, we generate a (2+1) heat equation and a (2+1) nonlinear generalized SWW system containing inverse operators with respect to the variables x and y by using a reduction spectral problem from the self-dual Yang-Mills equations. Supported by the National Natural Science Foundation of China under Grant No. 11371361, the Shandong Provincial Natural Science Foundation of China under Grant Nos. ZR2012AQ011, ZR2013AL016, ZR2015EM042, National Social Science Foundation of China under Grant No. 13BJY026, the Development of Science and Technology Project under Grant No. 2015NS1048 and A Project of Shandong Province Higher Educational Science and Technology Program under Grant No. J14LI58

Reduction of the N-component scalar model at the two-loop level

International Nuclear Information System (INIS)

Jakovac, A.

1996-01-01

Dimensional reduction of high temperature field theories improves IR features of their perturbative treatment. A crucial question is the following: What three-dimensional theory is representing the full system the most faithful way? A careful investigation of the induced three-dimensional counterterm structure of the finite temperature 4D O(N) symmetric scalar theory at the two-loop level leads to proposing the presence of nonlocal operators in the effective theory. A three-dimensional matching process is applied for the construction of the optimal local, superrenormalizable approximation. copyright 1996 The American Physical Society

Two-dimensional field theory description of a disoriented chiral condensate

International Nuclear Information System (INIS)

Kogan, I.I.

1993-01-01

We consider the effective (1+1)-dimensional chiral theory describing fluctuations of the order parameter of the disoriented chiral condensate (DCC) which can be formed in the central rapidity region in relativistic nucleus-nucleus or nucleon-nucleon collisions at high energy. Using (1+1)-dimensional reduction of QCD at high energies and assuming spin polarization of the DDC one can find the Wess-Zumino-Novikov-Witten model at the level k=3 as the effective chiral theory for the one-dimensional DDC. Some possible phenomenological consequences are briefly discussed

State-space dimensionality in short-memory hidden-variable theories

International Nuclear Information System (INIS)

Montina, Alberto

2011-01-01

Recently we have presented a hidden-variable model of measurements for a qubit where the hidden-variable state-space dimension is one-half the quantum-state manifold dimension. The absence of a short memory (Markov) dynamics is the price paid for this dimensional reduction. The conflict between having the Markov property and achieving the dimensional reduction was proved by Montina [A. Montina, Phys. Rev. A 77, 022104 (2008)] using an additional hypothesis of trajectory relaxation. Here we analyze in more detail this hypothesis introducing the concept of invertible process and report a proof that makes clearer the role played by the topology of the hidden-variable space. This is accomplished by requiring suitable properties of regularity of the conditional probability governing the dynamics. In the case of minimal dimension the set of continuous hidden variables is identified with an object living an N-dimensional Hilbert space whose dynamics is described by the Schroedinger equation. A method for generating the economical non-Markovian model for the qubit is also presented.

A Dimensionality Reduction-Based Multi-Step Clustering Method for Robust Vessel Trajectory Analysis

Directory of Open Access Journals (Sweden)

Huanhuan Li

2017-08-01

Full Text Available The Shipboard Automatic Identification System (AIS is crucial for navigation safety and maritime surveillance, data mining and pattern analysis of AIS information have attracted considerable attention in terms of both basic research and practical applications. Clustering of spatio-temporal AIS trajectories can be used to identify abnormal patterns and mine customary route data for transportation safety. Thus, the capacities of navigation safety and maritime traffic monitoring could be enhanced correspondingly. However, trajectory clustering is often sensitive to undesirable outliers and is essentially more complex compared with traditional point clustering. To overcome this limitation, a multi-step trajectory clustering method is proposed in this paper for robust AIS trajectory clustering. In particular, the Dynamic Time Warping (DTW, a similarity measurement method, is introduced in the first step to measure the distances between different trajectories. The calculated distances, inversely proportional to the similarities, constitute a distance matrix in the second step. Furthermore, as a widely-used dimensional reduction method, Principal Component Analysis (PCA is exploited to decompose the obtained distance matrix. In particular, the top k principal components with above 95% accumulative contribution rate are extracted by PCA, and the number of the centers k is chosen. The k centers are found by the improved center automatically selection algorithm. In the last step, the improved center clustering algorithm with k clusters is implemented on the distance matrix to achieve the final AIS trajectory clustering results. In order to improve the accuracy of the proposed multi-step clustering algorithm, an automatic algorithm for choosing the k clusters is developed according to the similarity distance. Numerous experiments on realistic AIS trajectory datasets in the bridge area waterway and Mississippi River have been implemented to compare our

A Dimensionality Reduction-Based Multi-Step Clustering Method for Robust Vessel Trajectory Analysis.

Science.gov (United States)

Li, Huanhuan; Liu, Jingxian; Liu, Ryan Wen; Xiong, Naixue; Wu, Kefeng; Kim, Tai-Hoon

2017-08-04

The Shipboard Automatic Identification System (AIS) is crucial for navigation safety and maritime surveillance, data mining and pattern analysis of AIS information have attracted considerable attention in terms of both basic research and practical applications. Clustering of spatio-temporal AIS trajectories can be used to identify abnormal patterns and mine customary route data for transportation safety. Thus, the capacities of navigation safety and maritime traffic monitoring could be enhanced correspondingly. However, trajectory clustering is often sensitive to undesirable outliers and is essentially more complex compared with traditional point clustering. To overcome this limitation, a multi-step trajectory clustering method is proposed in this paper for robust AIS trajectory clustering. In particular, the Dynamic Time Warping (DTW), a similarity measurement method, is introduced in the first step to measure the distances between different trajectories. The calculated distances, inversely proportional to the similarities, constitute a distance matrix in the second step. Furthermore, as a widely-used dimensional reduction method, Principal Component Analysis (PCA) is exploited to decompose the obtained distance matrix. In particular, the top k principal components with above 95% accumulative contribution rate are extracted by PCA, and the number of the centers k is chosen. The k centers are found by the improved center automatically selection algorithm. In the last step, the improved center clustering algorithm with k clusters is implemented on the distance matrix to achieve the final AIS trajectory clustering results. In order to improve the accuracy of the proposed multi-step clustering algorithm, an automatic algorithm for choosing the k clusters is developed according to the similarity distance. Numerous experiments on realistic AIS trajectory datasets in the bridge area waterway and Mississippi River have been implemented to compare our proposed method with

Diffusion trajectory of self-propagating innovations interacting with institutions-incorporation of multi-factors learning function to model PV diffusion in Japan

International Nuclear Information System (INIS)

Nagamatsu, Akira; Watanabe, Chihiro; Shum, Kwok L.

2006-01-01

This paper first proposes a modeling framework to study diffusion of innovations which exhibit strong interaction with the institution systems across which they diffuse. A unique character of such generic innovation is that specific applications are continually developed during its diffusion. This self-propagation in continual applications generation, which is dependent upon the cumulative installed base of the technological innovation, can be modeled to lead to a dynamic changing carrying capacity in an otherwise simple logistic diffusion curve. The cumulative installed base is dependent upon the price of technology and the cost learning dynamics. This paper utilizes a multi-factors learning function to represent such learning dynamics. Empirical estimates from our model are compared with those from other logistics curve formulations and are shown to better fit the annual PV production data during the past quarter century in the case of Japan. The very fact that the potential of this class of innovation can be leveraged only if it interacts closely with the institution highlights the importance of institutional determinants of adoption and diffusion of such innovations like PV. We therefore attempt to put forward an institutional framework, based on viewing PV as a technology platform, to consider PV diffusion beyond mathematical and empirical modeling. Some future research directions are also proposed. (author)

DataHigh: Graphical user interface for visualizing and interacting with high-dimensional neural activity

OpenAIRE

Cowley, Benjamin R.; Kaufman, Matthew T.; Churchland, Mark M.; Ryu, Stephen I.; Shenoy, Krishna V.; Yu, Byron M.

2012-01-01

The activity of tens to hundreds of neurons can be succinctly summarized by a smaller number of latent variables extracted using dimensionality reduction methods. These latent variables define a reduced-dimensional space in which we can study how population activity varies over time, across trials, and across experimental conditions. Ideally, we would like to visualize the population activity directly in the reduced-dimensional space, whose optimal dimensionality (as determined from the data)...

Density prediction and dimensionality reduction of mid-term electricity demand in China: A new semiparametric-based additive model

International Nuclear Information System (INIS)

Shao, Zhen; Yang, Shan-Lin; Gao, Fei

2014-01-01

Highlights: • A new stationary time series smoothing-based semiparametric model is established. • A novel semiparametric additive model based on piecewise smooth is proposed. • We model the uncertainty of data distribution for mid-term electricity forecasting. • We provide efficient long horizon simulation and extraction for external variables. • We provide stable and accurate density predictions for mid-term electricity demand. - Abstract: Accurate mid-term electricity demand forecasting is critical for efficient electric planning, budgeting and operating decisions. Mid-term electricity demand forecasting is notoriously complicated, since the demand is subject to a range of external drivers, such as climate change, economic development, which will exhibit monthly, seasonal, and annual complex variations. Conventional models are based on the assumption that original data is stable and normally distributed, which is generally insignificant in explaining actual demand pattern. This paper proposes a new semiparametric additive model that, in addition to considering the uncertainty of the data distribution, includes practical discussions covering the applications of the external variables. To effectively detach the multi-dimensional volatility of mid-term demand, a novel piecewise smooth method which allows reduction of the data dimensionality is developed. Besides, a semi-parametric procedure that makes use of bootstrap algorithm for density forecast and model estimation is presented. Two typical cases in China are presented to verify the effectiveness of the proposed methodology. The results suggest that both meteorological and economic variables play a critical role in mid-term electricity consumption prediction in China, while the extracted economic factor is adequate to reveal the potentially complex relationship between electricity consumption and economic fluctuation. Overall, the proposed model can be easily applied to mid-term demand forecasting, and

Low-dimensional gravities as gauge theories with non-compact groups

International Nuclear Information System (INIS)

Cangeni, D.

1993-01-01

In another note presented in these Proceedings it is shown that the two main lineal gravities can be given a gauge formulation. If it is already known that one of them the Sitter model - is a dimensional reduction of a Chern-Simons model in (2+1) dimensions, it was not clear whether the other one - the extended Poincare model follows from a similar reduction. The purpose of this note is to show that this is indeed the case provide we start in 2+1 dimensions with an extension ISO(2,1) of the Poincare groups as gauge group of a Chern-Simons model. We first show that this model gives a new proposal for gravity in 2*1 dimensions, since we get classically the Einstein's equations. Performing then a dimensional reduction, we recover not only the extended Poincare model but also the de Sitter one; hence, both lineal gravities get unified in the reduced model. (Author) 6 refs

The (2+1)-dimensional nonisospectral relativistic Toda hierarchy related to the generalized discrete Painleve hierarchy

International Nuclear Information System (INIS)

Zhu Zuonong

2007-01-01

In this paper, we will concentrate on the topic of integrable discrete hierarchies in 2+1 dimensions, and their connection with discrete Painleve hierarchies. By considering a (2+1)-dimensional nonisospectral discrete linear problem, two new (2+1)-dimensional nonisospectral integrable lattice hierarchies-the 2+1 nonisospectral relativistic Toda lattice hierarchy and the 2+1 nonisospectral negative relativistic Toda lattice hierarchy-are constructed. It is shown that the reductions of the two new 2+1 nonisospectral lattice hierarchies lead to the (2+1)-dimensional nonisospectral Volterra lattice hierarchy and the (2+1)-dimensional nonisospectral negative Volterra lattice hierarchy. We also obtain two new (1+1)-dimensional nonisospectral integrable lattice hierarchies and two new ordinary difference hierarchies which are direct reductions of the two 2+1 nonisospectral integrable lattice hierarchies. One of the two difference hierarchies yields our previously obtained generalized discrete first Painleve (dP I ) hierarchy and another one yields a generalized alternative discrete second Painleve (alt-dP II ) hierarchy

A multi-factor model of panic disorder: results of a preliminary study integrating the role of perfectionism, stress, physiological anxiety and anxiety sensitivity

Directory of Open Access Journals (Sweden)

Cristina M. Wood

2015-05-01

Full Text Available Background: Panic disorder (PD is a highly prevalent and disabling mental health problem associated with different factors including perfectionism, stress, physiological anxiety, and anxiety sensitivity regarding physical concerns; however, no studies have analyzed the joint relationship between these factors and PD in a multi-factor model using structural equation modeling. Method: A cross-sectional study was carried out to collect data on these factors and self-reported DSM-IV past-year PD symptoms in a large sample of the general population (N=936. Results: Perceived stress had a significant effect in increasing physiological anxiety, which in turn had an important association with physical concerns. Perfectionism and perceived stress had an indirect relation with past year PD via the mediator role of physiological anxiety and physical concerns. Physical concerns, on one hand, seemed to mediate the impact between perfectionism and PD and, on the other, partially mediated the role between physiological anxiety and PD. Conclusions: Although there is considerable evidence on the association between each of these factors and PD, this model can be considered a broader and productive framework of research on the nature and treatment of PD.

Sharpening the weak gravity conjecture with dimensional reduction

International Nuclear Information System (INIS)

Heidenreich, Ben; Reece, Matthew; Rudelius, Tom

2016-01-01

We investigate the behavior of the Weak Gravity Conjecture (WGC) under toroidal compactification and RG flows, finding evidence that WGC bounds for single photons become weaker in the infrared. By contrast, we find that a photon satisfying the WGC will not necessarily satisfy it after toroidal compactification when black holes charged under the Kaluza-Klein photons are considered. Doing so either requires an infinite number of states of different charges to satisfy the WGC in the original theory or a restriction on allowed compactification radii. These subtleties suggest that if the Weak Gravity Conjecture is true, we must seek a stronger form of the conjecture that is robust under compactification. We propose a “Lattice Weak Gravity Conjecture” that meets this requirement: a superextremal particle should exist for every charge in the charge lattice. The perturbative heterotic string satisfies this conjecture. We also use compactification to explore the extent to which the WGC applies to axions. We argue that gravitational instanton solutions in theories of axions coupled to dilaton-like fields are analogous to extremal black holes, motivating a WGC for axions. This is further supported by a match between the instanton action and that of wrapped black branes in a higher-dimensional UV completion.

Three-dimensional laparoscopy vs 2-dimensional laparoscopy with high-definition technology for abdominal surgery

DEFF Research Database (Denmark)

Fergo, Charlotte; Burcharth, Jakob; Pommergaard, Hans-Christian

2017-01-01

BACKGROUND: This systematic review investigates newer generation 3-dimensional (3D) laparoscopy vs 2-dimensional (2D) laparoscopy in terms of error rating, performance time, and subjective assessment as early comparisons have shown contradictory results due to technological shortcomings. DATA...... Central Register of Controlled Trials database. CONCLUSIONS: Of 643 articles, 13 RCTs were included, of which 2 were clinical trials. Nine of 13 trials (69%) and 10 of 13 trials (77%) found a significant reduction in performance time and error, respectively, with the use of 3D-laparoscopy. Overall, 3D......-laparoscopy was found to be superior or equal to 2D-laparoscopy. All trials featuring subjective evaluation found a superiority of 3D-laparoscopy. More clinical RCTs are still awaited for the convincing results to be reproduced....

Towards realistic models from Higher-Dimensional theories with Fuzzy extra dimensions

CERN Document Server

Gavriil, D.; Zoupanos, G.

2014-01-01

We briefly review the Coset Space Dimensional Reduction (CSDR) programme and the best model constructed so far and then we present some details of the corresponding programme in the case that the extra dimensions are considered to be fuzzy. In particular, we present a four-dimensional $\\mathcal{N} = 4$ Super Yang Mills Theory, orbifolded by $\\mathbb{Z}_3$, which mimics the behaviour of a dimensionally reduced $\\mathcal{N} = 1$, 10-dimensional gauge theory over a set of fuzzy spheres at intermediate high scales and leads to the trinification GUT $SU(3)^3$ at slightly lower, which in turn can be spontaneously broken to the MSSM in low scales.

Experiments with three-dimensional riblets as an idealized model of shark skin

Energy Technology Data Exchange (ETDEWEB)

Bechert, D.W.; Bruse, M.; Hage, W. [DLR Deutsches Zentrum fuer Luft- und Raumfahrt e.V., Berlin (Germany). Dept. of Turbulence Res.

2000-05-01

The skin of fast sharks exhibits a rather intriguing three-dimensional rib pattern. Therefore, the question arises whether or not such three-dimensional riblet surfaces may produce an equivalent or even higher drag reduction than straight two-dimensional riblets. Previously, the latter have been shown to reduce turbulent wall shear stress by up to 10%. Hence, the drag reduction by three-dimensional riblet surfaces is investigated experimentally. Our idealized 3D-surface consists of sharp-edged fin-shaped elements arranged in an interlocking array. The turbulent wall shear stress on this surface is measured using direct force balances. In a first attempt, wind tunnel experiments with about 365000 tiny fin elements per test surface have been carried out. Due to the complexity of the surface manufacturing process, a comprehensive parametric study was not possible. These initial wind tunnel data, however, hinted at an appreciable drag reduction. Subsequently, in order to have a better judgement on the potential of these 3D-surfaces, oil channel experiments are carried out. In our new oil channel, the geometrical dimensions of the fins can be magnified 10 times in size as compared to the initial wind tunnel experiments, i.e., from typically 0.5 mm to 5 mm. For these latter oil channel experiments, novel test plates with variable fin configuration have been manufactured, with 1920-4000 fins. This enhanced variability permits measurements with a comparatively large parameter range. As a result of our measurements, it can be concluded, that 3D-riblet surfaces do indeed produce an appreciable drag reduction. We found as much as 7.3% decreased turbulent shear stress, as compared to a smooth reference plate.

A supersymmetric reduction on the three-sphere

International Nuclear Information System (INIS)

Deger, Nihat Sadik; Samtleben, Henning; Sarıoğlu, Özgür; Van den Bleeken, Dieter

2015-01-01

We present the embedding of three-dimensional SO(4)⋉R 6 gauged N=4 supergravity with quaternionic target space SO(4,4)/(SO(4)×SO(4)) into D=6, N=(1,0) supergravity coupled to a single chiral tensor multiplet through a consistent reduction on AdS 3 ×S 3

Chronoprojective invariance of the five-dimensional Schroedinger formalism

International Nuclear Information System (INIS)

Perrin, M.; Burdet, G.; Duval, C.

1984-10-01

Invariance properties of the five-dimensional Schroedinger formalism describing a quantum test particle in the Newton-Cartan theory of gravitation are studied. The geometry which underlies these invariance properties is presented as a reduction of the 0(5,2) conformal geometry various applications are given

Adjunctive dental therapy via tooth plaque reduction and gingivitis treatment by blue light-emitting diodes tooth brushing

Science.gov (United States)

Genina, Elina A.; Titorenko, Vladimir A.; Belikov, Andrey V.; Bashkatov, Alexey N.; Tuchin, Valery V.

2015-12-01

The efficacy of blue light-emitting toothbrushes (B-LETBs) (405 to 420 nm, power density 2 mW/cm2) for reduction of dental plaques and gingival inflammation has been evaluated. Microbiological study has shown the multifactor therapeutic action of the B-LETBs on oral pathological microflora: in addition to partial mechanical removal of bacteria, photodynamic action suppresses them up to 97.5%. In the pilot clinical studies, subjects with mild to moderate gingivitis have been randomly divided into two groups: a treatment group that used the B-LETBs and a control group that used standard toothbrushes. Indices of plaque, gingival bleeding, and inflammation have been evaluated. A significant improvement of all dental indices in comparison with the baseline (by 59%, 66%, and 82% for plaque, gingival bleeding, and inflammation, respectively) has been found. The treatment group has demonstrated up to 50% improvement relative to the control group. We have proposed the B-LETBs to serve for prevention of gingivitis or as an alternative to conventional antibiotic treatment of this disease due to their effectiveness and the absence of drug side effects and bacterial resistance.

A two-dimensional lattice equation as an extension of the Heideman-Hogan recurrence

Science.gov (United States)

Kamiya, Ryo; Kanki, Masataka; Mase, Takafumi; Tokihiro, Tetsuji

2018-03-01

We consider a two dimensional extension of the so-called linearizable mappings. In particular, we start from the Heideman-Hogan recurrence, which is known as one of the linearizable Somos-like recurrences, and introduce one of its two dimensional extensions. The two dimensional lattice equation we present is linearizable in both directions, and has the Laurent and the coprimeness properties. Moreover, its reduction produces a generalized family of the Heideman-Hogan recurrence. Higher order examples of two dimensional linearizable lattice equations related to the Dana Scott recurrence are also discussed.

Dispersion in two dimensional channels—the Fick-Jacobs approximation revisited

Science.gov (United States)

Mangeat, M.; Guérin, T.; Dean, D. S.

2017-12-01

We examine the dispersion of Brownian particles in a symmetric two dimensional channel, this classical problem has been widely studied in the literature using the so called Fick-Jacobs’ approximation and its various improvements. Most studies rely on the reduction to an effective one dimensional diffusion equation, here we derive an explicit formula for the diffusion constant which avoids this reduction. Using this formula the effective diffusion constant can be evaluated numerically without resorting to Brownian simulations. In addition, a perturbation theory can be developed in \\varepsilon = h_0/L where h 0 is the characteristic channel height and L the period. This perturbation theory confirms the results of Kalinay and Percus (2006 Phys. Rev. E 74 041203), based on the reduction, to one dimensional diffusion are exact at least to {{ O}}(\\varepsilon^6) . Furthermore, we show how the Kalinay and Percus pseudo-linear approximation can be straightforwardly recovered. The approach proposed here can also be exploited to yield exact results in the limit \\varepsilon \\to ∞ , we show that here the diffusion constant remains finite and show how the result can be obtained with a simple physical argument. Moreover, we show that the correction to the effective diffusion constant is of order 1/\\varepsilon and remarkably has some universal characteristics. Numerically we compare the analytic results obtained with exact numerical calculations for a number of interesting channel geometries.

Quantum transport in d -dimensional lattices

International Nuclear Information System (INIS)

Manzano, Daniel; Chuang, Chern; Cao, Jianshu

2016-01-01

We show that both fermionic and bosonic uniform d -dimensional lattices can be reduced to a set of independent one-dimensional chains. This reduction leads to the expression for ballistic energy fluxes in uniform fermionic and bosonic lattices. By the use of the Jordan–Wigner transformation we can extend our analysis to spin lattices, proving the coexistence of both ballistic and non-ballistic subspaces in any dimension and for any system size. We then relate the nature of transport to the number of excitations in the homogeneous spin lattice, indicating that a single excitation always propagates ballistically and that the non-ballistic behaviour of uniform spin lattices is a consequence of the interaction between different excitations. (paper)

Extended inflation from higher-dimensional theories

International Nuclear Information System (INIS)

Holman, R.; Kolb, E.W.; Vadas, S.L.; Wang, Y.

1991-01-01

We consider the possibility that higher-dimensional theories may, upon reduction to four dimensions, allow extended inflation to occur. We analyze two separate models. One is a very simple toy model consisting of higher-dimensional gravity coupled to a scalar field whose potential allows for a first-order phase transition. The other is a more sophisticated model incorporating the effects of nontrivial field configurations (monopole, Casimir, and fermion bilinear condensate effects) that yield a nontrivial potential for the radius of the internal space. We find that extended inflation does not occur in these models. We also find that the bubble nucleation rate in these theories is time dependent unlike the case in the original version of extended inflation

Algorithm for statistical noise reduction in three-dimensional ion implant simulations

International Nuclear Information System (INIS)

Hernandez-Mangas, J.M.; Arias, J.; Jaraiz, M.; Bailon, L.; Barbolla, J.

2001-01-01

As integrated circuit devices scale into the deep sub-micron regime, ion implantation will continue to be the primary means of introducing dopant atoms into silicon. Different types of impurity profiles such as ultra-shallow profiles and retrograde profiles are necessary for deep submicron devices in order to realize the desired device performance. A new algorithm to reduce the statistical noise in three-dimensional ion implant simulations both in the lateral and shallow/deep regions of the profile is presented. The computational effort in BCA Monte Carlo ion implant simulation is also reduced

Interactions of renin-angiotensin system gene polymorphisms and antihypertensive effect of benazepril in Chinese population.

Science.gov (United States)

Chen, Qing; Yu, Can-Qing; Tang, Xun; Chen, Da-Fang; Tian, Jun; Cao, Yang; Fan, Wen-Yi; Cao, Wei-Hua; Zhan, Si-Yan; Lv, Jun; Guo, Xiao-Xia; Hu, Yong-Hua; Lee, Li-Ming

2011-05-01

Angiotensin-converting enzyme inhibitors are widely used antihypertensive drugs with individual response variation. We studied whether interactions of AGT, AGTR1 and ACE2 gene polymorphisms affect this response. Our study is based on a 3-year field trial with 1831 hypertensive patients prescribed benazepril. Generalized multifactor dimensionality reduction was used to explore interaction models and logistic regressions were used to confirm them. A two-locus model involving the AGT and ACE2 genes was found in males, the sensitive genotypes showed an odds ratio (OR) of 1.9 (95% CI: 1.3-2.8) when compared with nonsensitive genotypes. Two AGT-AGTR1 models were found in females, with an OR of 3.5 (95% CI: 2.0-5.9) and 3.1 (95% CI: 1.8-5.3). Gender-specific gene-gene interactions of the AGT, AGTR1 and ACE2 genes were associated with individual variation of response to benazepril. Further studies are needed to confirm this finding.

A survey about methods dedicated to epistasis detection

Directory of Open Access Journals (Sweden)

Clément eNiel

2015-09-01

Full Text Available During the past decade, findings of genome-wide association studies (GWAS improved our knowledge and understanding of disease genetics. To date, thousands of SNPs have been associated to diseases and other complex traits. Statistical analysis typically looks for association between a phenotype and a SNP taken individually via single-locus tests. However, geneticists admit this is an oversimplified approach to tackle the complexity of underlying biological mechanisms. Interaction between SNPs, namely epistasis, must be considered. Unfortunately, epistasis detection gives rise to analytic challenges since analyzing every SNP combination is at present impractical at a genome-wide scale. In this review, we will present the main strategies recently proposed to detect epistatic interactions, along with their operating principle. Some of these methods are exhaustive, such as multifactor dimensionality reduction, likelihood ratio-based tests or receiver operating characteristic curve analysis; some are non-exhaustive, such as machine learning techniques (random forests, Bayesian networks or combinatorial optimization approaches (ant colony optimization, computational evolution system.

Dixon-Souriau equations from a 5-dimensional spinning particle in a Kaluza-Klein framework

International Nuclear Information System (INIS)

Cianfrani, F.; Milillo, I.; Montani, G.

2007-01-01

The dimensional reduction of Papapetrou equations is performed in a 5-dimensional Kaluza-Klein background and Dixon-Souriau results for the motion of a charged spinning body are obtained. The splitting provides an electric dipole moment, and, for elementary particles, the induced parity and time-reversal violations are explained

On reduction and exact solutions of nonlinear many-dimensional Schroedinger equations

International Nuclear Information System (INIS)

Barannik, A.F.; Marchenko, V.A.; Fushchich, V.I.

1991-01-01

With the help of the canonical decomposition of an arbitrary subalgebra of the orthogonal algebra AO(n) the rank n and n-1 maximal subalgebras of the extended isochronous Galileo algebra, the rank n maximal subalgebras of the generalized extended classical Galileo algebra AG(a,n) the extended special Galileo algebra AG(2,n) and the extended whole Galileo algebra AG(3,n) are described. By using the rank n subalgebras, ansatze reducing the many dimensional Schroedinger equations to ordinary differential equations is found. With the help of the reduced equation solutions exact solutions of the Schroedinger equation are considered

Associations of Polymorphisms in WNT9B and PBX1 with Mayer-Rokitansky-Kuster-Hauser Syndrome in Chinese Han.

Directory of Open Access Journals (Sweden)

Wenqing Ma

Full Text Available Mayer-Rokitansky-Küster-Hauser (MRKH syndrome is a rare syndrome that is characterized by congenital aplasia of the uterus and the upper portion (2/3 of the vagina. Previous attempts to identify causal mutations of MRKH syndrome have primarily resulted in negative outcomes. We investigated whether these reported variants are associated with MRKH syndrome (types I and II in a relatively large sample size of Chinese Han patients, and whether any gene-gene epistatic interactions exist among these variants.This study included 182 unrelated Chinese women with MRKH syndrome (155 with type I and 27 with type II and 228 randomized female controls. Seventeen candidate loci in the AMH, PBX1, WNT4, WNT7A, WNT9B, HOXA10, HOXA11, LHXA1 and GALT genes were genotyped using the Sequenom MassARRAY iPLEX platform. Single-marker association, additive effects and multifactor interactions were investigated.The gene frequency distributions of MRKH type 1 and type 2 were similar. Rs34072914 in WNT9B was found to be associated with MRKH syndrome (P = 0.024, OR = 2.65, 95%CI = 1.14-6.17. The dominant models of rs34072914 and rs2275558 in WNT9B and PBX1, respectively, were significantly associated with MRKH syndrome risk in the Chinese Han patients. Additive gene-gene interaction analyses indicated a significant synergetic interaction between WNT9B and PBX1 (RERI = 1.397, AP = 0.493, SI = 4.204. Multifactor dimensionality reduction (MDR analysis revealed novel dimensional epistatic four-gene effects (AMH, PBX1, WNT7A and WNT9B in MRKH syndrome.This association study successfully identified two susceptibility SNPs (WNT9B and PBX1 associated with MRKH syndrome risk, both separately and interactively. The discovery of a four-gene epistatic effect (AMH, PBX1, WNT7A and WNT9B in MRKH syndrome provides novel information for the elucidation of the genetic mechanism underlying the etiology of MRKH syndrome.

Two-dimensional filtering of SPECT images using the Metz and Wiener filters

International Nuclear Information System (INIS)

King, M.A.; Schwinger, R.B.; Penney, B.C.; Doherty, P.W.

1984-01-01

Presently, single photon emission computed tomographic (SPECT) images are usually reconstructed by arbitrarily selecting a one-dimensional ''window'' function for use in reconstruction. A better method would be to automatically choose among a family of two-dimensional image restoration filters in such a way as to produce ''optimum'' image quality. Two-dimensional image processing techniques offer the advantages of a larger statistical sampling of the data for better noise reduction, and two-dimensional image deconvolution to correct for blurring during acquisition. An investigation of two such ''optimal'' digital image restoration techniques (the count-dependent Metz filter and the Wiener filter) was made. They were applied both as two-dimensional ''window'' functions for preprocessing SPECT images, and for filtering reconstructed images. Their performance was compared by measuring image contrast and per cent fractional standard deviation (% FSD) in multiple-acquisitions of the Jaszczak SPECT phantom at two different count levels. A statistically significant increase in image contrast and decrease in % FSD was observed with these techniques when compared to the results of reconstruction with a ramp filter. The adaptability of the techniques was manifested in a lesser % reduction in % FSD at the high count level coupled with a greater enhancement in image contrast. Using an array processor, processing time was 0.2 sec per image for the Metz filter and 3 sec for the Wiener filter. It is concluded that two-dimensional digital image restoration with these techniques can produce a significant increase in SPECT image quality

Extended inflation from higher dimensional theories

International Nuclear Information System (INIS)

Holman, R.; Kolb, E.W.; Vadas, S.L.; Wang, Yun.

1990-04-01

The possibility is considered that higher dimensional theories may, upon reduction to four dimensions, allow extended inflation to occur. Two separate models are analayzed. One is a very simple toy model consisting of higher dimensional gravity coupled to a scalar field whose potential allows for a first-order phase transition. The other is a more sophisticated model incorporating the effects of non-trivial field configurations (monopole, Casimir, and fermion bilinear condensate effects) that yield a non-trivial potential for the radius of the internal space. It was found that extended inflation does not occur in these models. It was also found that the bubble nucleation rate in these theories is time dependent unlike the case in the original version of extended inflation

Instability in near-horizon geometries of even-dimensional Myers–Perry black holes

International Nuclear Information System (INIS)

Tanahashi, Norihiro; Murata, Keiju

2012-01-01

We study the gravitational, electromagnetic and scalar field perturbations on the near-horizon geometries of the even-dimensional extremal Myers–Perry black holes. By dimensional reduction, the perturbation equations are reduced to effective equations of motion in AdS 2 . We find that some modes in the gravitational perturbations violate the Breitenlöhner–Freedman bound in AdS 2 . This result suggests that the even-dimensional (near-)extremal Myers–Perry black holes are unstable against gravitational perturbations. We also discuss implications of our results to the Kerr–CFT correspondence. (paper)

Evaluation of Orthopedic Metal Artifact Reduction Application in Three-Dimensional Computed Tomography Reconstruction of Spinal Instrumentation: A Single Saudi Center Experience.

Science.gov (United States)

Ali, Amir Monir

2018-01-01

The aim of the study was to evaluate the commercially available orthopedic metal artifact reduction (OMAR) technique in postoperative three-dimensional computed tomography (3DCT) reconstruction studies after spinal instrumentation and to investigate its clinical application. One hundred and twenty (120) patients with spinal metallic implants were included in the study. All had 3DCT reconstruction examinations using the OMAR software after obtaining the informed consents and approval of the Institution Ethical Committee. The degree of the artifacts, the related muscular density, the clearness of intermuscular fat planes, and definition of the adjacent vertebrae were qualitatively evaluated. The diagnostic satisfaction and quality of the 3D reconstruction images were thoroughly assessed. The majority (96.7%) of 3DCT reconstruction images performed were considered satisfactory to excellent for diagnosis. Only 3.3% of the reconstructed images had rendered unacceptable diagnostic quality. OMAR can effectively reduce metallic artifacts in patients with spinal instrumentation with highly diagnostic 3DCT reconstruction images.

Fast Multiscale Reservoir Simulations using POD-DEIM Model Reduction

KAUST Repository

Ghasemi, Mohammadreza

2015-02-23

In this paper, we present a global-local model reduction for fast multiscale reservoir simulations in highly heterogeneous porous media with applications to optimization and history matching. Our proposed approach identifies a low dimensional structure of the solution space. We introduce an auxiliary variable (the velocity field) in our model reduction that allows achieving a high degree of model reduction. The latter is due to the fact that the velocity field is conservative for any low-order reduced model in our framework. Because a typical global model reduction based on POD is a Galerkin finite element method, and thus it can not guarantee local mass conservation. This can be observed in numerical simulations that use finite volume based approaches. Discrete Empirical Interpolation Method (DEIM) is used to approximate the nonlinear functions of fine-grid functions in Newton iterations. This approach allows achieving the computational cost that is independent of the fine grid dimension. POD snapshots are inexpensively computed using local model reduction techniques based on Generalized Multiscale Finite Element Method (GMsFEM) which provides (1) a hierarchical approximation of snapshot vectors (2) adaptive computations by using coarse grids (3) inexpensive global POD operations in a small dimensional spaces on a coarse grid. By balancing the errors of the global and local reduced-order models, our new methodology can provide an error bound in simulations. Our numerical results, utilizing a two-phase immiscible flow, show a substantial speed-up and we compare our results to the standard POD-DEIM in finite volume setup.

Quantum fluctuations and spontaneous compactification of eleven-dimensional gravity

International Nuclear Information System (INIS)

Nguen Van Hieu.

1985-01-01

The reduction of the eleven-dimensional pure gravity to the field theory in the four-dimensional Minkowski space-time by means of the spontaneous compactification of the extra dimensions is investigated. The contribution of the quantum fluctuations of the eleven-dimen-- sonal second rank symmetric tensor field to the curvatures of the space-time and the compactified space of the extra dimensions are calculated in the one-loop approximation. It is shown that there exist the values of the cosmological constant for which tachions are absent. As a result, self-consistent quantum field theory is obtained in spontaneous compactified Minkowski space M 4 xS 7 ,is where M 4 is Minkowski space-time, and S 7 is seven-dimensional sphere

Isostable reduction with applications to time-dependent partial differential equations.

Science.gov (United States)

Wilson, Dan; Moehlis, Jeff

2016-07-01

Isostables and isostable reduction, analogous to isochrons and phase reduction for oscillatory systems, are useful in the study of nonlinear equations which asymptotically approach a stationary solution. In this work, we present a general method for isostable reduction of partial differential equations, with the potential power to reduce the dimensionality of a nonlinear system from infinity to 1. We illustrate the utility of this reduction by applying it to two different models with biological relevance. In the first example, isostable reduction of the Fokker-Planck equation provides the necessary framework to design a simple control strategy to desynchronize a population of pathologically synchronized oscillatory neurons, as might be relevant to Parkinson's disease. Another example analyzes a nonlinear reaction-diffusion equation with relevance to action potential propagation in a cardiac system.

Bioconductor workflow for single-cell RNA sequencing: Normalization, dimensionality reduction, clustering, and lineage inference [version 1; referees: 1 approved, 2 approved with reservations

Directory of Open Access Journals (Sweden)

Fanny Perraudeau

2017-07-01

Full Text Available Novel single-cell transcriptome sequencing assays allow researchers to measure gene expression levels at the resolution of single cells and offer the unprecendented opportunity to investigate at the molecular level fundamental biological questions, such as stem cell differentiation or the discovery and characterization of rare cell types. However, such assays raise challenging statistical and computational questions and require the development of novel methodology and software. Using stem cell differentiation in the mouse olfactory epithelium as a case study, this integrated workflow provides a step-by-step tutorial to the methodology and associated software for the following four main tasks: (1 dimensionality reduction accounting for zero inflation and over dispersion and adjusting for gene and cell-level covariates; (2 cell clustering using resampling-based sequential ensemble clustering; (3 inference of cell lineages and pseudotimes; and (4 differential expression analysis along lineages.

Giant Andreev backscattering and reentrant resistance in a 2- dimensional electron gas coupled to superconductors

NARCIS (Netherlands)

den Hartog, Sander; Wees, B.J. van; Nazarov, Yu.V.; Klapwijk, T.M.; Borghs, G.

1998-01-01

We have investigated the superconducting-phase modulated reduction in the resistance of a ballistic quantum point contact (QPC) connected via a disordered 2-dimensional electron gas (2DEG) to superconductors. We show that this reduction is caused by coherent Andreev back scattering of holes through

Big Data, Biostatistics and Complexity Reduction

Czech Academy of Sciences Publication Activity Database

Kalina, Jan

2018-01-01

Roč. 14, č. 2 (2018), s. 24-32 ISSN 1801-5603 R&D Projects: GA MZd(CZ) NV15-29835A Institutional support: RVO:67985807 Keywords : Biostatistics * Big data * Multivariate statistics * Dimensionality * Variable selection Subject RIV: IN - Informatics, Computer Science OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) https://www.ejbi.org/scholarly-articles/big-data-biostatistics-and-complexity-reduction.pdf

Five-dimensional Nernst branes from special geometry

Energy Technology Data Exchange (ETDEWEB)

Dempster, P.; Errington, D. [Department of Mathematical Sciences, University of LiverpoolPeach Street, Liverpool L69 7ZL (United Kingdom); Gutowski, J. [Department of Mathematics, University of Surrey,Guildford, GU2 7XH (United Kingdom); Mohaupt, T. [Department of Mathematical Sciences, University of LiverpoolPeach Street, Liverpool L69 7ZL (United Kingdom)

2016-11-21

We construct Nernst brane solutions, that is black branes with zero entropy density in the extremal limit, of FI-gauged minimal five-dimensional supergravity coupled to an arbitrary number of vector multiplets. While the scalars take specific constant values and dynamically determine the value of the cosmological constant in terms of the FI-parameters, the metric takes the form of a boosted AdS Schwarzschild black brane. This metric can be brought to the Carter-Novotný-Horský form that has previously been observed to occur in certain limits of boosted D3-branes. By dimensional reduction to four dimensions we recover the four-dimensional Nernst branes of arXiv:1501.07863 and show how the five-dimensional lift resolves all their UV singularities. The dynamics of the compactification circle, which expands both in the UV and in the IR, plays a crucial role. At asymptotic infinity, the curvature singularity of the four-dimensional metric and the run-away behaviour of the four-dimensional scalar combine in such a way that the lifted solution becomes asymptotic to AdS{sub 5}. Moreover, the existence of a finite chemical potential in four dimensions is related to fact that the compactification circle has a finite minimal value. While it is not clear immediately how to embed our solutions into string theory, we argue that the same type of dictionary as proposed for boosted D3-branes should apply, although with a lower amount of supersymmetry.

A Robust Supervised Variable Selection for Noisy High-Dimensional Data

Czech Academy of Sciences Publication Activity Database

Kalina, Jan; Schlenker, Anna

2015-01-01

Roč. 2015, Article 320385 (2015), s. 1-10 ISSN 2314-6133 R&D Projects: GA ČR GA13-17187S Institutional support: RVO:67985807 Keywords : dimensionality reduction * variable selection * robustness Subject RIV: BA - General Mathematics Impact factor: 2.134, year: 2015

Understanding decay resistance, dimensional stability and strength changes in heat treated and acetylated wood

Science.gov (United States)

Roger M. Rowell; Rebecca E. Ibach; James McSweeny; Thomas Nilsson

2009-01-01

Reductions in hygroscopicity, increased dimensional stability and decay resistance of heat-treated wood depend on decomposition of a large portion of the hemicelluloses in the wood cell wall. In theory, these hemicelluloses are converted to small organic molecules, water and volatile furan-type intermediates that can polymerize in the cell wall. Reductions in...

Space-time least-squares Petrov-Galerkin projection in nonlinear model reduction.

Energy Technology Data Exchange (ETDEWEB)

Choi, Youngsoo [Sandia National Laboratories (SNL-CA), Livermore, CA (United States). Extreme-scale Data Science and Analytics Dept.; Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Carlberg, Kevin Thomas [Sandia National Laboratories (SNL-CA), Livermore, CA (United States). Extreme-scale Data Science and Analytics Dept.

2017-09-01

Our work proposes a space-time least-squares Petrov-Galerkin (ST-LSPG) projection method for model reduction of nonlinear dynamical systems. In contrast to typical nonlinear model-reduction methods that first apply Petrov-Galerkin projection in the spatial dimension and subsequently apply time integration to numerically resolve the resulting low-dimensional dynamical system, the proposed method applies projection in space and time simultaneously. To accomplish this, the method first introduces a low-dimensional space-time trial subspace, which can be obtained by computing tensor decompositions of state-snapshot data. The method then computes discrete-optimal approximations in this space-time trial subspace by minimizing the residual arising after time discretization over all space and time in a weighted ℓ²-norm. This norm can be de ned to enable complexity reduction (i.e., hyper-reduction) in time, which leads to space-time collocation and space-time GNAT variants of the ST-LSPG method. Advantages of the approach relative to typical spatial-projection-based nonlinear model reduction methods such as Galerkin projection and least-squares Petrov-Galerkin projection include: (1) a reduction of both the spatial and temporal dimensions of the dynamical system, (2) the removal of spurious temporal modes (e.g., unstable growth) from the state space, and (3) error bounds that exhibit slower growth in time. Numerical examples performed on model problems in fluid dynamics demonstrate the ability of the method to generate orders-of-magnitude computational savings relative to spatial-projection-based reduced-order models without sacrificing accuracy.

Reentrant resistance and giant Andreev back scattering in a two-dimensional electron gas coupled to superconductors

NARCIS (Netherlands)

den Hartog, Sander; Wees, B.J. van; Nazarov, Yu.V.; Klapwijk, T.M.; Borghs, G.

1998-01-01

We first present the bias-voltage dependence of the superconducting phase-dependent reduction in the differential resistance of a disordered T-shaped two-dimensional electron gas (2DEG) coupled to two superconductors. This reduction exhibits a reentrant behavior, since it first increases upon

Symmetry Analysis and Exact Solutions of (2+1)-Dimensional Sawada-Kotera Equation

International Nuclear Information System (INIS)

Zhi Hongyan; Zhang Hongqing

2008-01-01

Based on the symbolic computation system Maple, the infinite-dimensional symmetry group of the (2+1)-dimensional Sawada-Kotera equation is found by the classical Lie group method and the characterization of the group properties is given. The symmetry groups are used to perform the symmetry reduction. Moreover, with Lou's direct method that is based on Lax pairs, we obtain the symmetry transformations of the Sawada-Kotera and Konopelchenko-Dubrovsky equations, respectively.

Reduction theories elucidate the origins of complex biological rhythms generated by interacting delay-induced oscillations.

Directory of Open Access Journals (Sweden)

Ikuhiro Yamaguchi

Full Text Available Time delay is known to induce sustained oscillations in many biological systems such as electroencephalogram (EEG activities and gene regulations. Furthermore, interactions among delay-induced oscillations can generate complex collective rhythms, which play important functional roles. However, due to their intrinsic infinite dimensionality, theoretical analysis of interacting delay-induced oscillations has been limited. Here, we show that the two primary methods for finite-dimensional limit cycles, namely, the center manifold reduction in the vicinity of the Hopf bifurcation and the phase reduction for weak interactions, can successfully be applied to interacting infinite-dimensional delay-induced oscillations. We systematically derive the complex Ginzburg-Landau equation and the phase equation without delay for general interaction networks. Based on the reduced low-dimensional equations, we demonstrate that diffusive (linearly attractive coupling between a pair of delay-induced oscillations can exhibit nontrivial amplitude death and multimodal phase locking. Our analysis provides unique insights into experimentally observed EEG activities such as sudden transitions among different phase-locked states and occurrence of epileptic seizures.

Reduction of the dimensionality and comparative analysis of multivariate radiological data

International Nuclear Information System (INIS)

Seddeek, M.K.; Kozae, A.M.; Sharshar, T.; Badran, H.M.

2009-01-01

Computational methods were used to reduce the dimensionality and to find clusters of multivariate data. The variables were the natural radioactivity contents and the texture characteristics of sand samples. The application of discriminate analysis revealed that samples with high negative values of the former score have the highest contamination with black sand. Principal component analysis (PCA) revealed that radioactivity concentrations alone are sufficient for the classification. Rough set analysis (RSA) showed that the concentration of 238 U, 226 Ra or 232 Th, combined with the concentration of 40 K, can specify the clusters and characteristics of the sand. Both PCA and RSA show that 238 U, 226 Ra and 232 Th behave similarly. RSA revealed that one or two of them can be omitted without degrading predictions.

BioXTAS RAW, a software program for high-throughput automated small-angle X-ray scattering data reduction and preliminary analysis

DEFF Research Database (Denmark)

Nielsen, S.S.; Toft, K.N.; Snakenborg, Detlef

2009-01-01

A fully open source software program for automated two-dimensional and one-dimensional data reduction and preliminary analysis of isotropic small-angle X-ray scattering (SAXS) data is presented. The program is freely distributed, following the open-source philosophy, and does not rely on any...... commercial software packages. BioXTAS RAW is a fully automated program that, via an online feature, reads raw two-dimensional SAXS detector output files and processes and plots data as the data files are created during measurement sessions. The software handles all steps in the data reduction. This includes...... mask creation, radial averaging, error bar calculation, artifact removal, normalization and q calibration. Further data reduction such as background subtraction and absolute intensity scaling is fast and easy via the graphical user interface. BioXTAS RAW also provides preliminary analysis of one...

Dimensional Reduction of N=1, E_8 SYM over SU(3)/U(1) x U(1) x Z_3 and its four-dimensional effective action

CERN Document Server

Irges, Nikos; Zoupanos, George

2011-01-01

We present an extension of the Standard Model inspired by the E_8 x E_8 Heterotic String. In order that a reasonable effective Lagrangian is presented we neglect everything else other than the ten-dimensional N=1 supersymmetric Yang-Mills sector associated with one of the gauge factors and certain couplings necessary for anomaly cancellation. We consider a compactified space-time M_4 x B_0 / Z_3, where B_0 is the nearly-Kaehler manifold SU(3)/U(1) x U(1) and Z_3 is a freely acting discrete group on B_0. Then we reduce dimensionally the E_8 on this manifold and we employ the Wilson flux mechanism leading in four dimensions to an SU(3)^3 gauge theory with the spectrum of a N=1 supersymmetric theory. We compute the effective four-dimensional Lagrangian and demonstrate that an extension of the Standard Model is obtained with interesting features including a conserved baryon number and fixed tree level Yukawa couplings and scalar potential. The spectrum contains new states such as right handed neutrinos and heavy ...

Symmetry Reduction and Cauchy Problems for a Class of Fourth-Order Evolution Equations

International Nuclear Information System (INIS)

Li Jina; Zhang Shunli

2008-01-01

We exploit higher-order conditional symmetry to reduce initial-value problems for evolution equations to Cauchy problems for systems of ordinary differential equations (ODEs). We classify a class of fourth-order evolution equations which admit certain higher-order generalized conditional symmetries (GCSs) and give some examples to show the main reduction procedure. These reductions cannot be derived within the framework of the standard Lie approach, which hints that the technique presented here is something essential for the dimensional reduction of evolution equations

A reduction method for phase equilibrium calculations with cubic equations of state

Directory of Open Access Journals (Sweden)

D. V. Nichita

2006-09-01

Full Text Available In this work we propose a new reduction method for phase equilibrium calculations using a general form of cubic equations of state (CEOS. The energy term in the CEOS is a quadratic form, which is diagonalized by applying a linear transformation. The number of the reduction parameters is related to the rank of the matrix C with elements (1-Cij, where Cij denotes the binary interaction parameters (BIPs. The dimensionality of the problem depends only on the number of reduction parameters, and is independent of the number of components in the mixture.

Investigating reduction of dimensionality during single-joint elbow movements: a case study on muscle synergies

Directory of Open Access Journals (Sweden)

Enrico eChiovetto

2013-02-01

Full Text Available A long standing hypothesis in the neuroscience community is that the CNS generates the muscle activities to accomplish movements by combining a relatively small number of stereotyped patterns of muscle activations, often referred to as muscle synergies. Different definitions of synergies have been given in the literature. The most well-known are those of synchronous, time-varying and temporal muscle synergies. Each one of them is based on a different mathematical model used to factor some EMG array recordings collected during the execution of variety of motor tasks into a well-determined spatial, temporal or spatio-temporal organization. This plurality of definitions and their separate application to complex tasks have so far complicated the comparison and interpretation of the results obtained across studies, and it has always remained unclear why and when one synergistic decomposition should be preferred to another one. By using well-understood motor tasks such as elbow flexions and extensions, we aimed in this study to clarify better what are the motor features characterized by each kind of decomposition and to assess whether, when and why one of them should be preferred to the others. We found that three temporal synergies, each one of them accounting for specific temporal phases of the movements could account for the majority of the data variation. Similar performances could be achieved by two synchronous synergies, encoding the agonist-antagonist nature of the two muscles considered, and by two time-varying muscle synergies, encoding each one a task-related feature of the elbow movements, specifically their direction. Our findings support the notion that each EMG decomposition provides a set of well-interpretable muscle synergies, identifying reduction of dimensionality in different aspects of the movements. Taken together, our findings suggest that all decompositions are not equivalent and may imply different neurophysiological substrates

Effective Hamiltonian for 2-dimensional arbitrary spin Ising model

International Nuclear Information System (INIS)

Sznajd, J.; Polska Akademia Nauk, Wroclaw. Inst. Niskich Temperatur i Badan Strukturalnych)

1983-08-01

The method of the reduction of the generalized arbitrary-spin 2-dimensional Ising model to spin-half Ising model is presented. The method is demonstrated in detail by calculating the effective interaction constants to the third order in cumulant expansion for the triangular spin-1 Ising model (the Blume-Emery-Griffiths model). (author)

Model reduction for circuit simulation

CERN Document Server

Hinze, Michael; Maten, E Jan W Ter

2011-01-01

Simulation based on mathematical models plays a major role in computer aided design of integrated circuits (ICs). Decreasing structure sizes, increasing packing densities and driving frequencies require the use of refined mathematical models, and to take into account secondary, parasitic effects. This leads to very high dimensional problems which nowadays require simulation times too large for the short time-to-market demands in industry. Modern Model Order Reduction (MOR) techniques present a way out of this dilemma in providing surrogate models which keep the main characteristics of the devi

How to Reduce Dimensionality of Data: Robustness Point of View

Czech Academy of Sciences Publication Activity Database

Kalina, Jan; Rensová, D.

2015-01-01

Roč. 10, č. 1 (2015), s. 131-140 ISSN 1452-4864 R&D Projects: GA ČR GA13-17187S Institutional support: RVO:67985807 Keywords : data analysis * dimensionality reduction * robust statistics * principal component analysis * robust classification analysis Subject RIV: BB - Applied Statistics, Operational Research

An MPCA/LDA Based Dimensionality Reduction Algorithm for Face Recognition

Directory of Open Access Journals (Sweden)

Jun Huang

2014-01-01

Full Text Available We proposed a face recognition algorithm based on both the multilinear principal component analysis (MPCA and linear discriminant analysis (LDA. Compared with current traditional existing face recognition methods, our approach treats face images as multidimensional tensor in order to find the optimal tensor subspace for accomplishing dimension reduction. The LDA is used to project samples to a new discriminant feature space, while the K nearest neighbor (KNN is adopted for sample set classification. The results of our study and the developed algorithm are validated with face databases ORL, FERET, and YALE and compared with PCA, MPCA, and PCA + LDA methods, which demonstrates an improvement in face recognition accuracy.

Coset space dimension reduction of gauge theories

International Nuclear Information System (INIS)

Farakos, K.; Kapetanakis, D.; Koutsoumbas, G.; Zoupanos, G.

1989-01-01

A very interesting approach in the attempts to unify all the interactions is to consider that a unification takes place in higher than four dimensions. The most ambitious program based on the old Kaluza-Klein idea is not able to reproduce the low energy chiral nature of the weak interactions. A suggested way out was the introduction of Yang-Mills fields in the higher dimensional theory. From the particle physics point of view the most important question is how such a theory behaves in four dimensions and in particular in low energies. Therefore most of our efforts concern studies of the properties of an attractive scheme, the Coset-Space-Dimensional-Reduction (C.S.D.R.) scheme, which permits the study of the effective four dimensional theory coming from a gauge theory defined in higher dimensions. Here we summarize the C.S.D.R. procedure the main the rems which are obeyed and to present a realistic model which is the result of the model building efforts that take into account all the C.S.D.R. properties. (orig./HSI)

Kinetics of hydrogen reduction of titanium-doped molybdenum dioxide

International Nuclear Information System (INIS)

He, Qian; Marin-Flores, Oscar; Hu, Shuozhen; Scudiero, Louis; Ha, Su; Norton, M. Grant

2015-01-01

Ti-doped MoO 2 was synthesized to broaden the oxygen-to-carbon ratio operating range of MoO 2 for partial oxidation of long-chain hydrocarbons by increasing the redox stability. The structure modification causes the hydrogen reduction mechanism to change from three-dimensional nuclei growth with an activation energy of 61.3 kJ mol −1 to a three-dimensional hydrogen diffusion limited model with an activation energy of 317.9 kJ mol −1 . Because of the enhanced redox stability, Ti-doped MoO 2 has potential as an alternative anode in direct liquid-fed solid oxide fuel cells

Chemical Reduction Synthesis of Iron Aluminum Powders

Science.gov (United States)

Zurita-Méndez, N. N.; la Torre, G. Carbajal-De; Ballesteros-Almanza, L.; Villagómez-Galindo, M.; Sánchez-Castillo, A.; Espinosa-Medina, M. A.

In this study, a chemical reduction synthesis method of iron aluminum (FeAl) nano-dimensional intermetallic powders is described. The process has two stages: a salt reduction and solvent evaporation by a heat treatment at 1100°C. The precursors of the synthesis are ferric chloride, aluminum foil chips, a mix of Toluene/THF in a 75/25 volume relationship, and concentrated hydrochloric acid as initiator of the reaction. The reaction time was 20 days, the product obtained was dried at 60 °C for 2 h and calcined at 400, 800, and 1100 °C for 4 h each. To characterize and confirm the obtained synthesis products, X-Ray Diffraction (XRD), and Scanning Electron Microscopy (SEM) techniques were used. The results of morphology and chemical characterization of nano-dimensional powders obtained showed a formation of agglomerated particles of a size range of approximately 150 nm to 1.0 μm. Composition of powders was identified as corundum (Al2O3), iron aluminide (FeAl3), and iron-aluminum oxides (Fe0. 53Al0. 47)2O3 phases. The oxide phases formation were associated with the reaction of atmospheric concentration-free oxygen during synthesis and sintering steps, reducing the concentration of the iron aluminum phase.

Discovering Hidden Controlling Parameters using Data Analytics and Dimensional Analysis

Science.gov (United States)

Del Rosario, Zachary; Lee, Minyong; Iaccarino, Gianluca

2017-11-01

Dimensional Analysis is a powerful tool, one which takes a priori information and produces important simplifications. However, if this a priori information - the list of relevant parameters - is missing a relevant quantity, then the conclusions from Dimensional Analysis will be incorrect. In this work, we present novel conclusions in Dimensional Analysis, which provide a means to detect this failure mode of missing or hidden parameters. These results are based on a restated form of the Buckingham Pi theorem that reveals a ridge function structure underlying all dimensionless physical laws. We leverage this structure by constructing a hypothesis test based on sufficient dimension reduction, allowing for an experimental data-driven detection of hidden parameters. Both theory and examples will be presented, using classical turbulent pipe flow as the working example. Keywords: experimental techniques, dimensional analysis, lurking variables, hidden parameters, buckingham pi, data analysis. First author supported by the NSF GRFP under Grant Number DGE-114747.

Tumor Volume Changes Assessed by Three-Dimensional Magnetic Resonance Volumetry in Rectal Cancer Patients After Preoperative Chemoradiation: The Impact of the Volume Reduction Ratio on the Prediction of Pathologic Complete Response

International Nuclear Information System (INIS)

Kang, Jeong Hyun; Kim, Young Chul; Kim, Hyunki; Kim, Young Wan; Hur, Hyuk; Kim, Jin Soo; Min, Byung Soh; Kim, Hogeun; Lim, Joon Seok; Seong, Jinsil; Keum, Ki Chang; Kim, Nam Kyu

2010-01-01

Purpose: The aim of this study was to determine the correlation between tumor volume changes assessed by three-dimensional (3D) magnetic resonance (MR) volumetry and the histopathologic tumor response in rectal cancer patients undergoing preoperative chemoradiation therapy (CRT). Methods and Materials: A total of 84 patients who underwent preoperative CRT followed by radical surgery were prospectively enrolled in the study. The post-treatment tumor volume and tumor volume reduction ratio (% decrease ratio), as shown by 3D MR volumetry, were compared with the histopathologic response, as shown by T and N downstaging and the tumor regression grade (TRG). Results: There were no significant differences in the post-treatment tumor volume and the volume reduction ratio shown by 3D MR volumetry with respect to T and N downstaging and the tumor regression grade. In a multivariate analysis, the tumor volume reduction ratio was not significantly associated with T and N downstaging. The volume reduction ratio (>75%, p = 0.01) and the pretreatment carcinoembryonic antigen level (≤3 ng/ml, p = 0.01), but not the post-treatment volume shown by 3D MR (≤ 5ml), were, however, significantly associated with an increased pathologic complete response rate. Conclusion: More than 75% of the tumor volume reduction ratios were significantly associated with a high pathologic complete response rate. Therefore, limited treatment options such as local excision or simple observation might be considered after preoperative CRT in this patient population.

Low-Dimensional Feature Representation for Instrument Identification

Science.gov (United States)

Ihara, Mizuki; Maeda, Shin-Ichi; Ikeda, Kazushi; Ishii, Shin

For monophonic music instrument identification, various feature extraction and selection methods have been proposed. One of the issues toward instrument identification is that the same spectrum is not always observed even in the same instrument due to the difference of the recording condition. Therefore, it is important to find non-redundant instrument-specific features that maintain information essential for high-quality instrument identification to apply them to various instrumental music analyses. For such a dimensionality reduction method, the authors propose the utilization of linear projection methods: local Fisher discriminant analysis (LFDA) and LFDA combined with principal component analysis (PCA). After experimentally clarifying that raw power spectra are actually good for instrument classification, the authors reduced the feature dimensionality by LFDA or by PCA followed by LFDA (PCA-LFDA). The reduced features achieved reasonably high identification performance that was comparable or higher than those by the power spectra and those achieved by other existing studies. These results demonstrated that our LFDA and PCA-LFDA can successfully extract low-dimensional instrument features that maintain the characteristic information of the instruments.

Global sensitivity analysis by polynomial dimensional decomposition

Energy Technology Data Exchange (ETDEWEB)

Rahman, Sharif, E-mail: rahman@engineering.uiowa.ed [College of Engineering, The University of Iowa, Iowa City, IA 52242 (United States)

2011-07-15

This paper presents a polynomial dimensional decomposition (PDD) method for global sensitivity analysis of stochastic systems subject to independent random input following arbitrary probability distributions. The method involves Fourier-polynomial expansions of lower-variate component functions of a stochastic response by measure-consistent orthonormal polynomial bases, analytical formulae for calculating the global sensitivity indices in terms of the expansion coefficients, and dimension-reduction integration for estimating the expansion coefficients. Due to identical dimensional structures of PDD and analysis-of-variance decomposition, the proposed method facilitates simple and direct calculation of the global sensitivity indices. Numerical results of the global sensitivity indices computed for smooth systems reveal significantly higher convergence rates of the PDD approximation than those from existing methods, including polynomial chaos expansion, random balance design, state-dependent parameter, improved Sobol's method, and sampling-based methods. However, for non-smooth functions, the convergence properties of the PDD solution deteriorate to a great extent, warranting further improvements. The computational complexity of the PDD method is polynomial, as opposed to exponential, thereby alleviating the curse of dimensionality to some extent.

Artificial Neural Network-Based Clutter Reduction Systems for Ship Size Estimation in Maritime Radars

Directory of Open Access Journals (Sweden)

M. P. Jarabo-Amores

2010-01-01

Full Text Available The existence of clutter in maritime radars deteriorates the estimation of some physical parameters of the objects detected over the sea surface. For that reason, maritime radars should incorporate efficient clutter reduction techniques. Due to the intrinsic nonlinear dynamic of sea clutter, nonlinear signal processing is needed, what can be achieved by artificial neural networks (ANNs. In this paper, an estimation of the ship size using an ANN-based clutter reduction system followed by a fixed threshold is proposed. High clutter reduction rates are achieved using 1-dimensional (horizontal or vertical integration modes, although inaccurate ship width estimations are achieved. These estimations are improved using a 2-dimensional (rhombus integration mode. The proposed system is compared with a CA-CFAR system, denoting a great performance improvement and a great robustness against changes in sea clutter conditions and ship parameters, independently of the direction of movement of the ocean waves and ships.

Hypergraph-based anomaly detection of high-dimensional co-occurrences.

Science.gov (United States)

Silva, Jorge; Willett, Rebecca

2009-03-01

This paper addresses the problem of detecting anomalous multivariate co-occurrences using a limited number of unlabeled training observations. A novel method based on using a hypergraph representation of the data is proposed to deal with this very high-dimensional problem. Hypergraphs constitute an important extension of graphs which allow edges to connect more than two vertices simultaneously. A variational Expectation-Maximization algorithm for detecting anomalies directly on the hypergraph domain without any feature selection or dimensionality reduction is presented. The resulting estimate can be used to calculate a measure of anomalousness based on the False Discovery Rate. The algorithm has O(np) computational complexity, where n is the number of training observations and p is the number of potential participants in each co-occurrence event. This efficiency makes the method ideally suited for very high-dimensional settings, and requires no tuning, bandwidth or regularization parameters. The proposed approach is validated on both high-dimensional synthetic data and the Enron email database, where p > 75,000, and it is shown that it can outperform other state-of-the-art methods.

Geometric subspace updates with applications to online adaptive nonlinear model reduction

DEFF Research Database (Denmark)

Zimmermann, Ralf; Peherstorfer, Benjamin; Willcox, Karen

2018-01-01

In many scientific applications, including model reduction and image processing, subspaces are used as ansatz spaces for the low-dimensional approximation and reconstruction of the state vectors of interest. We introduce a procedure for adapting an existing subspace based on information from...... Estimation (GROUSE). We establish for GROUSE a closed-form expression for the residual function along the geodesic descent direction. Specific applications of subspace adaptation are discussed in the context of image processing and model reduction of nonlinear partial differential equation systems....

Two dimensional generalizations of the Newcomb equation

International Nuclear Information System (INIS)

Dewar, R.L.; Pletzer, A.

1989-11-01

The Bineau reduction to scalar form of the equation governing ideal, zero frequency linearized displacements from a hydromagnetic equilibrium possessing a continuous symmetry is performed in 'universal coordinates', applicable to both the toroidal and helical cases. The resulting generalized Newcomb equation (GNE) has in general a more complicated form than the corresponding one dimensional equation obtained by Newcomb in the case of circular cylindrical symmetry, but in this cylindrical case , the equation can be transformed to that of Newcomb. In the two dimensional case there is a transformation which leaves the form of the GNE invariant and simplifies the Frobenius expansion about a rational surface, especially in the limit of zero pressure gradient. The Frobenius expansions about a mode rational surface is developed and the connection with Hamiltonian transformation theory is shown. 17 refs

Controllable one-pot synthesis of various one-dimensional Bi2S3 nanostructures and their enhanced visible-light-driven photocatalytic reduction of Cr(VI)

International Nuclear Information System (INIS)

Hu, Enlai; Gao, Xuehui; Etogo, Atangana; Xie, Yunlong; Zhong, Yijun; Hu, Yong

2014-01-01

Highlights: • 1D Bi 2 S 3 nanostructures were prepared by a facile ethanol-assisted one-pot reaction. • The size and morphology of the products can be conveniently varied. • The sulfur source plays a crucial role in determining the morphologies of products. • 1D Bi 2 S 3 nanostructures exhibit enhanced photocatalytic reduction of Cr(VI). • Bi 2 S 3 nanowires exhibit the highest photoreduction activity among three samples. - Abstract: One-dimensional (1D) Bi 2 S 3 nanostructures with various morphologies, including nanowires, nanorods, and nanotubes, have been successfully synthesized through a facile ethanol-assisted one-pot reaction. It is found that the size, morphology and structure of the products can be conveniently varied or controlled by simply adjusting the volume ratio of ethanol and water in the reaction system. Further experimental results indicate that sulfur source also plays the other crucial role in determining the product morphology. The synthetic strategy developed in this work is highly efficient in producing 1D Bi 2 S 3 nanostructures with high quality and large quantity. Photocatalysis experiments show the as-prepared 1D Bi 2 S 3 nanostructures possess significantly enhanced photocatalytic reduction of Cr(VI) when exposed to visible light irradiation. Especially, Bi 2 S 3 nanowires exhibit the highest photocatalytic activity and can be used repeatedly after washed with dilute HCl

N = 2 local and N = 4 non-local reductions of supersymmetric KP hierarchy in N = 2 superspace

International Nuclear Information System (INIS)

Delduc, F.; Gallot, L.; Sorin, A.

1999-01-01

An N = 4 supersymmetric matrix KP hierarchy is proposed and a wide class of its reductions which are characterized by a finite number of fields are described. This class includes the one-dimensional reduction of the two-dimensional N = (2,2) superconformal Toda lattice hierarchy possessing the N = 4 supersymmetry -- the N = 4 Toda chain hierarchy - which may be relevant in the construction of supersymmetric matrix models. The Lax-pair representations of the bosonic and fermionic flows, corresponding local and non-local Hamiltonians, finite and infinite discrete symmetries, the first two Hamiltonian structures and the recursion operator connecting all evolution equations and the Hamiltonian structures of the N = 4 Toda chain hierarchy are constructed in explicit form. Is secondary reduction to the N 4 supersymmetric α = - 2 KdV hierarchy is

Classification of molecular structure images by using ANN, RF, LBP, HOG, and size reduction methods for early stomach cancer detection

Science.gov (United States)

Aytaç Korkmaz, Sevcan; Binol, Hamidullah

2018-03-01

Patients who die from stomach cancer are still present. Early diagnosis is crucial in reducing the mortality rate of cancer patients. Therefore, computer aided methods have been developed for early detection in this article. Stomach cancer images were obtained from Fırat University Medical Faculty Pathology Department. The Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG) features of these images are calculated. At the same time, Sammon mapping, Stochastic Neighbor Embedding (SNE), Isomap, Classical multidimensional scaling (MDS), Local Linear Embedding (LLE), Linear Discriminant Analysis (LDA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Laplacian Eigenmaps methods are used for dimensional the reduction of the features. The high dimension of these features has been reduced to lower dimensions using dimensional reduction methods. Artificial neural networks (ANN) and Random Forest (RF) classifiers were used to classify stomach cancer images with these new lower feature sizes. New medical systems have developed to measure the effects of these dimensions by obtaining features in different dimensional with dimensional reduction methods. When all the methods developed are compared, it has been found that the best accuracy results are obtained with LBP_MDS_ANN and LBP_LLE_ANN methods.

Model reduction for the dynamics and control of large structural systems via neutral network processing direct numerical optimization

Science.gov (United States)

Becus, Georges A.; Chan, Alistair K.

1993-01-01

Three neural network processing approaches in a direct numerical optimization model reduction scheme are proposed and investigated. Large structural systems, such as large space structures, offer new challenges to both structural dynamicists and control engineers. One such challenge is that of dimensionality. Indeed these distributed parameter systems can be modeled either by infinite dimensional mathematical models (typically partial differential equations) or by high dimensional discrete models (typically finite element models) often exhibiting thousands of vibrational modes usually closely spaced and with little, if any, damping. Clearly, some form of model reduction is in order, especially for the control engineer who can actively control but a few of the modes using system identification based on a limited number of sensors. Inasmuch as the amount of 'control spillover' (in which the control inputs excite the neglected dynamics) and/or 'observation spillover' (where neglected dynamics affect system identification) is to a large extent determined by the choice of particular reduced model (RM), the way in which this model reduction is carried out is often critical.

Two-dimensional mapping of three-dimensional SPECT data: a preliminary step to the quantitation of thallium myocardial perfusion single photon emission tomography

International Nuclear Information System (INIS)

Goris, M.L.; Boudier, S.; Briandet, P.A.

1987-01-01

A method is presented by which tomographic myocardial perfusion data are prepared for quantitative analysis. The method is characterized by an interrogation of the original data, which results in a size and shape normalization. The method is analogous to the circumferential profile methods used in planar scintigraphy but requires a polar-to-cartesian transformation from three to two dimensions. As was the case in the planar situation, centering and reorientation are explicit. The degree of data reduction is evaluated by reconstructing idealized three-dimensional data from the two-dimensional sampling vectors. The method differs from previously described approaches by the absence in the resulting vector of a coordinate reflecting cartesian coordinate in the original data (slice number)

Cohomological reduction of sigma models

Energy Technology Data Exchange (ETDEWEB)

Candu, Constantin; Mitev, Vladimir; Schomerus, Volker [DESY, Hamburg (Germany). Theory Group; Creutzig, Thomas [North Carolina Univ., Chapel Hill, NC (United States). Dept. of Physics and Astronomy

2010-01-15

This article studies some features of quantum field theories with internal supersymmetry, focusing mainly on 2-dimensional non-linear sigma models which take values in a coset superspace. It is discussed how BRST operators from the target space super- symmetry algebra can be used to identify subsectors which are often simpler than the original model and may allow for an explicit computation of correlation functions. After an extensive discussion of the general reduction scheme, we present a number of interesting examples, including symmetric superspaces G/G{sup Z{sub 2}} and coset superspaces of the form G/G{sup Z{sub 4}}. (orig.)

A general reduction method for one-loop N-point integrals

International Nuclear Information System (INIS)

Heinrich, G.; Binoth, T.

2000-01-01

In order to calculate cross sections with a large number of particles/jets in the final state at next-to-leading order, one has to reduce the occurring scalar and tensor one-loop integrals to a small set of known integrals. In massless theories, this reduction procedure is complicated by the presence of infrared divergences. Working in n = 4 - 2ε dimensions, it will be outlined how to achieve such a reduction for diagrams with an arbitrary number of external legs. As a result, any integral with more than four propagators and generic 4-dimensional external momenta can be reduced to box integrals

Parallel accelerated cyclic reduction preconditioner for three-dimensional elliptic PDEs with variable coefficients

KAUST Repository

Chavez Chavez, Gustavo Ivan; Turkiyyah, George; Zampini, Stefano; Keyes, David E.

2017-01-01

and the cyclic reduction method. The setup and application phases of the preconditioner achieve log-linear complexity in memory footprint and number of operations, and numerical experiments exhibit good weak and strong scalability at large processor counts in a

Face recognition based on two-dimensional discriminant sparse preserving projection

Science.gov (United States)

Zhang, Dawei; Zhu, Shanan

2018-04-01

In this paper, a supervised dimensionality reduction algorithm named two-dimensional discriminant sparse preserving projection (2DDSPP) is proposed for face recognition. In order to accurately model manifold structure of data, 2DDSPP constructs within-class affinity graph and between-class affinity graph by the constrained least squares (LS) and l1 norm minimization problem, respectively. Based on directly operating on image matrix, 2DDSPP integrates graph embedding (GE) with Fisher criterion. The obtained projection subspace preserves within-class neighborhood geometry structure of samples, while keeping away samples from different classes. The experimental results on the PIE and AR face databases show that 2DDSPP can achieve better recognition performance.

Feature Space Dimensionality Reduction for Real-Time Vision-Based Food Inspection

Directory of Open Access Journals (Sweden)

Mai Moussa CHETIMA

2009-03-01

Full Text Available Machine vision solutions are becoming a standard for quality inspection in several manufacturing industries. In the processed-food industry where the appearance attributes of the product are essential to customer’s satisfaction, visual inspection can be reliably achieved with machine vision. But such systems often involve the extraction of a larger number of features than those actually needed to ensure proper quality control, making the process less efficient and difficult to tune. This work experiments with several feature selection techniques in order to reduce the number of attributes analyzed by a real-time vision-based food inspection system. Identifying and removing as much irrelevant and redundant information as possible reduces the dimensionality of the data and allows classification algorithms to operate faster. In some cases, accuracy on classification can even be improved. Filter-based and wrapper-based feature selectors are experimentally evaluated on different bakery products to identify the best performing approaches.

Universal contributions to scalar masses from five dimensional supergravity

CERN Document Server

Dudas, Emilian

2012-01-01

We compute the effective Kahler potential for matter fields in warped compactifications, starting from five dimensional gauged supergravity, as a function of the matter fields localization. We show that truncation to zero modes is inconsistent and the tree-level exchange of the massive gravitational multiplet is needed for consistency of the four-dimensional theory. In addition to the standard Kahler coming from dimensional reduction, we find the quartic correction coming from integrating out the gravity multiplet. We apply our result to the computation of scalar masses, by assuming that the SUSY breaking field is a bulk hypermultiplet. In the limit of extreme opposite localization of the matter and the spurion fields, we find zero scalar masses, consistent with sequestering arguments. Surprisingly enough, for all the other cases the scalar masses are tachyonic. This suggests the holographic interpretation that a CFT sector always generates operators contributing in a tachyonic way to scalar masses. Viability...

Improving feature selection process resistance to failures caused by curse-of-dimensionality effects

Czech Academy of Sciences Publication Activity Database

Somol, Petr; Grim, Jiří; Novovičová, Jana; Pudil, P.

2011-01-01

Roč. 47, č. 3 (2011), s. 401-425 ISSN 0023-5954 R&D Projects: GA MŠk 1M0572; GA ČR GA102/08/0593 Grant - others:GA MŠk(CZ) 2C06019 Institutional research plan: CEZ:AV0Z10750506 Keywords : feature selection * curse of dimensionality * over-fitting * stability * machine learning * dimensionality reduction Subject RIV: IN - Informatics, Computer Science Impact factor: 0.454, year: 2011 http://library.utia.cas.cz/separaty/2011/RO/somol-0368741.pdf

Three-dimensional anisotropic adaptive filtering of projection data for noise reduction in cone beam CT

Energy Technology Data Exchange (ETDEWEB)

Maier, Andreas; Wigstroem, Lars; Hofmann, Hannes G.; Hornegger, Joachim; Zhu Lei; Strobel, Norbert; Fahrig, Rebecca [Department of Radiology, Stanford University, Stanford, California 94305 (United States); Department of Radiology, Stanford University, Stanford, California 94305 (United States) and Center for Medical Image Science and Visualization, Linkoeping University, Linkoeping (Sweden); Pattern Recognition Laboratory, Department of Computer Science, Friedrich-Alexander University of Erlangen-Nuremberg, 91054, Erlangen (Germany); Nuclear and Radiological Engineering and Medical Physics Programs, George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332 (United States); Siemens AG Healthcare, Forchheim 91301 (Germany); Department of Radiology, Stanford University, Stanford, California 94305 (United States)

2011-11-15

Purpose: The combination of quickly rotating C-arm gantry with digital flat panel has enabled the acquisition of three-dimensional data (3D) in the interventional suite. However, image quality is still somewhat limited since the hardware has not been optimized for CT imaging. Adaptive anisotropic filtering has the ability to improve image quality by reducing the noise level and therewith the radiation dose without introducing noticeable blurring. By applying the filtering prior to 3D reconstruction, noise-induced streak artifacts are reduced as compared to processing in the image domain. Methods: 3D anisotropic adaptive filtering was used to process an ensemble of 2D x-ray views acquired along a circular trajectory around an object. After arranging the input data into a 3D space (2D projections + angle), the orientation of structures was estimated using a set of differently oriented filters. The resulting tensor representation of local orientation was utilized to control the anisotropic filtering. Low-pass filtering is applied only along structures to maintain high spatial frequency components perpendicular to these. The evaluation of the proposed algorithm includes numerical simulations, phantom experiments, and in-vivo data which were acquired using an AXIOM Artis dTA C-arm system (Siemens AG, Healthcare Sector, Forchheim, Germany). Spatial resolution and noise levels were compared with and without adaptive filtering. A human observer study was carried out to evaluate low-contrast detectability. Results: The adaptive anisotropic filtering algorithm was found to significantly improve low-contrast detectability by reducing the noise level by half (reduction of the standard deviation in certain areas from 74 to 30 HU). Virtually no degradation of high contrast spatial resolution was observed in the modulation transfer function (MTF) analysis. Although the algorithm is computationally intensive, hardware acceleration using Nvidia's CUDA Interface provided an 8

Three-dimensional anisotropic adaptive filtering of projection data for noise reduction in cone beam CT

International Nuclear Information System (INIS)

Maier, Andreas; Wigstroem, Lars; Hofmann, Hannes G.; Hornegger, Joachim; Zhu Lei; Strobel, Norbert; Fahrig, Rebecca

2011-01-01

Purpose: The combination of quickly rotating C-arm gantry with digital flat panel has enabled the acquisition of three-dimensional data (3D) in the interventional suite. However, image quality is still somewhat limited since the hardware has not been optimized for CT imaging. Adaptive anisotropic filtering has the ability to improve image quality by reducing the noise level and therewith the radiation dose without introducing noticeable blurring. By applying the filtering prior to 3D reconstruction, noise-induced streak artifacts are reduced as compared to processing in the image domain. Methods: 3D anisotropic adaptive filtering was used to process an ensemble of 2D x-ray views acquired along a circular trajectory around an object. After arranging the input data into a 3D space (2D projections + angle), the orientation of structures was estimated using a set of differently oriented filters. The resulting tensor representation of local orientation was utilized to control the anisotropic filtering. Low-pass filtering is applied only along structures to maintain high spatial frequency components perpendicular to these. The evaluation of the proposed algorithm includes numerical simulations, phantom experiments, and in-vivo data which were acquired using an AXIOM Artis dTA C-arm system (Siemens AG, Healthcare Sector, Forchheim, Germany). Spatial resolution and noise levels were compared with and without adaptive filtering. A human observer study was carried out to evaluate low-contrast detectability. Results: The adaptive anisotropic filtering algorithm was found to significantly improve low-contrast detectability by reducing the noise level by half (reduction of the standard deviation in certain areas from 74 to 30 HU). Virtually no degradation of high contrast spatial resolution was observed in the modulation transfer function (MTF) analysis. Although the algorithm is computationally intensive, hardware acceleration using Nvidia's CUDA Interface provided an 8.9-fold

Three-dimensional versus two-dimensional vision in laparoscopy

DEFF Research Database (Denmark)

Sørensen, Stine D; Savran, Mona Meral; Konge, Lars

2016-01-01

were cohort size and characteristics, skill trained or operation performed, instrument used, outcome measures, and conclusions. Two independent authors performed the search and data extraction. RESULTS: Three hundred and forty articles were screened for eligibility, and 31 RCTs were included...... through a two-dimensional (2D) projection on a monitor, which results in loss of depth perception. To counter this problem, 3D imaging for laparoscopy was developed. A systematic review of the literature was performed to assess the effect of 3D laparoscopy. METHODS: A systematic search of the literature...... in the review. Three trials were carried out in a clinical setting, and 28 trials used a simulated setting. Time was used as an outcome measure in all of the trials, and number of errors was used in 19 out of 31 trials. Twenty-two out of 31 trials (71 %) showed a reduction in performance time, and 12 out of 19...

Incomplete Dirac reduction of constrained Hamiltonian systems

Energy Technology Data Exchange (ETDEWEB)

Chandre, C., E-mail: chandre@cpt.univ-mrs.fr

2015-10-15

First-class constraints constitute a potential obstacle to the computation of a Poisson bracket in Dirac’s theory of constrained Hamiltonian systems. Using the pseudoinverse instead of the inverse of the matrix defined by the Poisson brackets between the constraints, we show that a Dirac–Poisson bracket can be constructed, even if it corresponds to an incomplete reduction of the original Hamiltonian system. The uniqueness of Dirac brackets is discussed. The relevance of this procedure for infinite dimensional Hamiltonian systems is exemplified.

Reduction of respiratory ghosting motion artifacts in conventional two-dimensional multi-slice Cartesian turbo spin-echo: which k-space filling order is the best?

Science.gov (United States)

Inoue, Yuuji; Yoneyama, Masami; Nakamura, Masanobu; Takemura, Atsushi

2018-06-01

The two-dimensional Cartesian turbo spin-echo (TSE) sequence is widely used in routine clinical studies, but it is sensitive to respiratory motion. We investigated the k-space orders in Cartesian TSE that can effectively reduce motion artifacts. The purpose of this study was to demonstrate the relationship between k-space order and degree of motion artifacts using a moving phantom. We compared the degree of motion artifacts between linear and asymmetric k-space orders. The actual spacing of ghost artifacts in the asymmetric order was doubled compared with that in the linear order in the free-breathing situation. The asymmetric order clearly showed less sensitivity to incomplete breath-hold at the latter half of the imaging period. Because of the actual number of partitions of the k-space and the temporal filling order, the asymmetric k-space order of Cartesian TSE was superior to the linear k-space order for reduction of ghosting motion artifacts.

Similarity measurement method of high-dimensional data based on normalized net lattice subspace

Institute of Scientific and Technical Information of China (English)

Li Wenfa; Wang Gongming; Li Ke; Huang Su

2017-01-01

The performance of conventional similarity measurement methods is affected seriously by the curse of dimensionality of high-dimensional data.The reason is that data difference between sparse and noisy dimensionalities occupies a large proportion of the similarity, leading to the dissimilarities between any results.A similarity measurement method of high-dimensional data based on normalized net lattice subspace is proposed.The data range of each dimension is divided into several intervals, and the components in different dimensions are mapped onto the corresponding interval.Only the component in the same or adjacent interval is used to calculate the similarity.To validate this meth-od, three data types are used, and seven common similarity measurement methods are compared. The experimental result indicates that the relative difference of the method is increasing with the di-mensionality and is approximately two or three orders of magnitude higher than the conventional method.In addition, the similarity range of this method in different dimensions is [0, 1], which is fit for similarity analysis after dimensionality reduction.

Canonical reduction of self-dual Yang-Mills equations to Fitzhugh-Nagumo equation and exact solutions

International Nuclear Information System (INIS)

Sayed, S.M.; Gharib, G.M.

2009-01-01

The (constrained) canonical reduction of four-dimensional self-dual Yang-Mills theory to two-dimensional Fitzhugh-Nagumo and the real Newell-Whitehead equations are considered. On the other hand, other methods and transformations are developed to obtain exact solutions for the original two-dimensional Fitzhugh-Nagumo and Newell-Whitehead equations. The corresponding gauge potential A μ and the gauge field strengths F μν are also obtained. New explicit and exact traveling wave and solitary solutions (for Fitzhugh-Nagumo and Newell-Whitehead equations) are obtained by using an improved sine-cosine method and the Wu's elimination method with the aid of Mathematica.

Complete algebraic reduction of one-loop tensor Feynman integrals

International Nuclear Information System (INIS)

Fleischer, J.; Riemann, T.

2011-01-01

We set up a new, flexible approach for the tensor reduction of one-loop Feynman integrals. The 5-point tensor integrals up to rank R=5 are expressed by 4-point tensor integrals of rank R-1, such that the appearance of the inverse 5-point Gram determinant is avoided. The 4-point tensor coefficients are represented in terms of 4-point integrals, defined in d dimensions, 4-2ε≤d≤4-2ε+2(R-1), with higher powers of the propagators. They can be further reduced to expressions which stay free of the inverse 4-point Gram determinants but contain higher-dimensional 4-point integrals with only the first power of scalar propagators, plus 3-point tensor coefficients. A direct evaluation of the higher-dimensional 4-point functions would avoid the appearance of inverse powers of the Gram determinants completely. The simplest approach, however, is to apply here dimensional recurrence relations in order to reduce them to the familiar 2- to 4-point functions in generic dimension d=4-2ε, introducing thereby coefficients with inverse 4-point Gram determinants up to power R for tensors of rank R. For small or vanishing Gram determinants--where this reduction is not applicable--we use analytic expansions in positive powers of the Gram determinants. Improving the convergence of the expansions substantially with Pade approximants we close up to the evaluation of the 4-point tensor coefficients for larger Gram determinants. Finally, some relations are discussed which may be useful for analytic simplifications of Feynman diagrams.

Twisted spin Sutherland models from quantum Hamiltonian reduction

International Nuclear Information System (INIS)

Feher, L; Pusztai, B G

2008-01-01

Recent general results on Hamiltonian reductions under polar group actions are applied to study some reductions of the free particle governed by the Laplace-Beltrami operator of a compact, connected, simple Lie group. The reduced systems associated with arbitrary finite-dimensional irreducible representations of the group by using the symmetry induced by twisted conjugations are described in detail. These systems generically yield integrable Sutherland-type many-body models with spin, which are called twisted spin Sutherland models if the underlying twisted conjugations are built on non-trivial Dynkin diagram automorphisms. The spectra of these models can be calculated, in principle, by solving certain Clebsch-Gordan problems, and the result is presented for the models associated with the symmetric tensorial powers of the defining representation of SU(N)

Three-dimensional quantum electrodynamics as an effective interaction

International Nuclear Information System (INIS)

Abdalla, E.; Carvalho Filho, F.M. de

1995-10-01

We obtain a Quantum Electrodynamics in 2 + 1 dimensions by applying a Kaluza-Klein type method of dimensional reduction to Quantum Electrodynamics in 3 + 1 dimensions rendering the model more realistic to application in solid-state systems, invariant under translations in one direction. We show that the model obtained leads to an effective action exhibiting an interesting phase structure and that the generated Chern-Simons term survives only in the broken phase. (author). 20 refs

Equivariant Reduction of Gauge Theories over Fuzzy Extra Dimensions

International Nuclear Information System (INIS)

Kürkçüoglu, Seçkin

2012-01-01

In SU(N) Yang-Mills theories on a manifold M, which are suitably coupled to a set of scalars, fuzzy spheres may be generated as extra dimensions by spontaneous symmetry breaking. This process results in gauge theories over the product space of the manifold M and the fuzzy spheres with smaller gauge groups. Here we present the SU(2)– and SU(2) × SU(2)-equivariant parametrization of U(2) and U(4) gauge fields on S 2 F and S 2 F × S 2 F respectively and outline the dimensional reduction of these theories over the fuzzy extra dimensions. The emerging dimensionally reduced theories are Higgs type models. Some vortex type solutions of these theories are briefly discussed.

Dimensional reduction of a Lorentz and CPT-violating Maxwell-Chern-Simons model

International Nuclear Information System (INIS)

Belich, H. Jr.; Helayel Neto, J.A.; Ferreira, M.M. Jr.; Maranhao Univ., Sao Luiz, MA; Orlando, M.T.D.; Espirito Santo Univ., Vitoria, ES

2003-01-01

Taking as starting point a Lorentz and CPT non-invariant Chern-Simons-like model defined in 1+3 dimensions, we proceed realizing its dimensional to D = 1+2. One then obtains a new planar model, composed by the Maxwell-Chern-Simons (MCS) sector, a Klein-Gordon massless scalar field, and a coupling term that mixes the gauge field to the external vector, ν μ . In spite of breaking Lorentz invariance in the particle frame, this model may preserve the CPT symmetry for a single particular choice of ν μ . Analyzing the dispersion relations, one verifies that the reduced model exhibits stability, but the causality can be jeopardized by some modes. The unitary of the gauge sector is assured without any restriction , while the scalar sector is unitary only in the space-like case. (author)

Open reduction and internal fixation aided by intraoperative 3-dimensional imaging improved the articular reduction in 72 displaced acetabular fractures

DEFF Research Database (Denmark)

Eckardt, Henrik; Lind, Dennis; Toendevold, Erik

2015-01-01

was evaluated on reconstructed coronal and sagittal images of the acetabulum. Results - The fracture severity and patient characteristics were similar in the 2 groups. In the 3D group, 46 of 72 patients (0.6) had a perfect result after open reduction and internal fixation, and in the control group, 17 of 42 (0...

Solid-state Water-mediated Transport Reduction of Nanostructured Iron Oxides

International Nuclear Information System (INIS)

Smirnov, Vladimir M.; Povarov, Vladimir G.; Voronkov, Gennadii P.; Semenov, Valentin G.; Murin, Igor' V.; Gittsovich, Viktor N.; Sinel'nikov, Boris M.

2001-01-01

The Fe 2+ /Fe 3+ ratio in two-dimensional iron oxide nanosructures (nanolayers with a thickness of 0.3-1.5 nm on silica surface) may be precisely controlled using the transport reduction (TR) technique. The species ≡-O-Fe(OH) 2 and (≡Si-O-) 2 -FeOH forming the surface monolayer are not reduced at 400-600 deg. C because of their covalent bonding to the silica surface, as demonstrated by Moessbauer spectroscopy. Iron oxide microparticles (microstructures) obtained by the impregnation technique, being chemically unbound to silica, are subjected to reduction at T ≥ 500 deg. C with formation of metallic iron in the form of α-Fe. Transport reduction of supported nanostructures (consisting of 1 or 4 monolayers) at T ≥ 600 deg. C produces bulk iron(II) silicate and metallic iron phases. The structural-chemical transformations occurring in transport reduction of supported iron oxide nanolayers are proved to be governed by specific phase processes in the nanostructures themselves

Low-resistance gateless high electron mobility transistors using three-dimensional inverted pyramidal AlGaN/GaN surfaces

International Nuclear Information System (INIS)

So, Hongyun; Senesky, Debbie G.

2016-01-01

In this letter, three-dimensional gateless AlGaN/GaN high electron mobility transistors (HEMTs) were demonstrated with 54% reduction in electrical resistance and 73% increase in surface area compared with conventional gateless HEMTs on planar substrates. Inverted pyramidal AlGaN/GaN surfaces were microfabricated using potassium hydroxide etched silicon with exposed (111) surfaces and metal-organic chemical vapor deposition of coherent AlGaN/GaN thin films. In addition, electrical characterization of the devices showed that a combination of series and parallel connections of the highly conductive two-dimensional electron gas along the pyramidal geometry resulted in a significant reduction in electrical resistance at both room and high temperatures (up to 300 °C). This three-dimensional HEMT architecture can be leveraged to realize low-power and reliable power electronics, as well as harsh environment sensors with increased surface area

Low-resistance gateless high electron mobility transistors using three-dimensional inverted pyramidal AlGaN/GaN surfaces

Energy Technology Data Exchange (ETDEWEB)

So, Hongyun, E-mail: hyso@stanford.edu [Department of Aeronautics and Astronautics, Stanford University, Stanford, California 94305 (United States); Senesky, Debbie G. [Department of Aeronautics and Astronautics, Stanford University, Stanford, California 94305 (United States); Department of Electrical Engineering, Stanford University, Stanford, California 94305 (United States)

2016-01-04

In this letter, three-dimensional gateless AlGaN/GaN high electron mobility transistors (HEMTs) were demonstrated with 54% reduction in electrical resistance and 73% increase in surface area compared with conventional gateless HEMTs on planar substrates. Inverted pyramidal AlGaN/GaN surfaces were microfabricated using potassium hydroxide etched silicon with exposed (111) surfaces and metal-organic chemical vapor deposition of coherent AlGaN/GaN thin films. In addition, electrical characterization of the devices showed that a combination of series and parallel connections of the highly conductive two-dimensional electron gas along the pyramidal geometry resulted in a significant reduction in electrical resistance at both room and high temperatures (up to 300 °C). This three-dimensional HEMT architecture can be leveraged to realize low-power and reliable power electronics, as well as harsh environment sensors with increased surface area.

Dimensional reduction of the Standard Model coupled to a new singlet scalar field

Energy Technology Data Exchange (ETDEWEB)

Brauner, Tomáš [Faculty of Science and Technology, University of Stavanger,N-4036 Stavanger (Norway); Tenkanen, Tuomas V.I. [Department of Physics and Helsinki Institute of Physics,P.O. Box 64, FI-00014 University of Helsinki (Finland); Tranberg, Anders [Faculty of Science and Technology, University of Stavanger,N-4036 Stavanger (Norway); Vuorinen, Aleksi [Department of Physics and Helsinki Institute of Physics,P.O. Box 64, FI-00014 University of Helsinki (Finland); Weir, David J. [Faculty of Science and Technology, University of Stavanger,N-4036 Stavanger (Norway); Department of Physics and Helsinki Institute of Physics,P.O. Box 64, FI-00014 University of Helsinki (Finland)

2017-03-01

We derive an effective dimensionally reduced theory for the Standard Model augmented by a real singlet scalar. We treat the singlet as a superheavy field and integrate it out, leaving an effective theory involving only the Higgs and SU(2){sub L}×U(1){sub Y} gauge fields, identical to the one studied previously for the Standard Model. This opens up the possibility of efficiently computing the order and strength of the electroweak phase transition, numerically and nonperturbatively, in this extension of the Standard Model. Understanding the phase diagram is crucial for models of electroweak baryogenesis and for studying the production of gravitational waves at thermal phase transitions.

Single-time reduction of bethe-salpeter formalism for two-fermion system

International Nuclear Information System (INIS)

Arkhipov, A.A.

1988-01-01

The single-time reduction method proposed in other refs. for the system of two scalar particles is generalized for the case of two-fermion system. A self-consistent procedure of single-time reduction has been constructed both in terms of the Bethe-Salpeter wave function and in terms of the Green's function of two-fermion system. Three-dimensional dynamic equations have been obtained for single-time wave functions and two-time Green's functions of a two-fermion system and the Schroedinger structure of the equations obtained is shown to be a consequence of the causality structure of the local QFT. 32 refs

Low Overpotential and High Current CO2 Reduction with Surface Reconstructed Cu Foam Electrodess

KAUST Repository

Min, Shixiong; Yang, Xiulin; Lu, Ang-Yu; Tseng, Chien-Chih; Hedhili, Mohamed N.; Li, Lain-Jong; Huang, Kuo-Wei

2016-01-01

for large-scale fuel synthesis. Here we report an extremely high current density for CO2 reduction at low overpotential using a Cu foam electrode prepared by air-oxidation and subsequent electroreduction. Apart from possessing three-dimensional (3D) open

Relativistic formulations with Blankenbecler-Sugar reduction technique for the three-particle system

International Nuclear Information System (INIS)

Morioka, S.; Afnan, I.R.

1980-05-01

A critical comparison for two-types of three-dimensional covariant equations for the three-particle system obtained by the Blankenbecler-Sugar reduction technique with the Whitghtman-Garding momenta and the usual Jacobi variables is presented. The relations between the relativistic and non-relativistic equations in the low energy limit are discussed

Canonical reduction of self-dual Yang-Mills equations to Fitzhugh-Nagumo equation and exact solutions

Energy Technology Data Exchange (ETDEWEB)

Sayed, S.M. [Mathematics Department, Faculty of Science, Beni-Suef University, Beni-Suef (Egypt); Mathematics Department, P.O. Box 1144, Tabouk Teacher College, Ministry of Education (Saudi Arabia)], E-mail: eaashour@lycos.com; Gharib, G.M. [Mathematics Department, P.O. Box 1144, Tabouk Teacher College, Ministry of Education (Saudi Arabia)

2009-01-30

The (constrained) canonical reduction of four-dimensional self-dual Yang-Mills theory to two-dimensional Fitzhugh-Nagumo and the real Newell-Whitehead equations are considered. On the other hand, other methods and transformations are developed to obtain exact solutions for the original two-dimensional Fitzhugh-Nagumo and Newell-Whitehead equations. The corresponding gauge potential A{sub {mu}} and the gauge field strengths F{sub {mu}}{sub {nu}} are also obtained. New explicit and exact traveling wave and solitary solutions (for Fitzhugh-Nagumo and Newell-Whitehead equations) are obtained by using an improved sine-cosine method and the Wu's elimination method with the aid of Mathematica.

Dimensional reduction of a Lorentz and CPT-violating Maxwell-Chern-Simons model

Energy Technology Data Exchange (ETDEWEB)

Belich, H. Jr.; Helayel Neto, J.A. [Centro Brasileiro de Pesquisas Fisicas (CBPF), Rio de Janeiro, RJ (Brazil). Coordenacao de Teoria de Campos e Particulas; Grupo de Fisica Teorica Jose Leite Lopes, Petropolis, RJ (Brazil); E-mails: belich@cbpf.br; helayel@cbpf.br; Ferreira, M.M. Jr. [Grupo de Fisica Teorica Jose Leite Lopes, Petropolis, RJ (Brazil); Maranhao Univ., Sao Luiz, MA (Brazil). Dept. de Fisica]. E-mail: manojr@cbpf.br; Orlando, M.T.D. [Grupo de Fisica Teorica Jose Leite Lopes, Petropolis, RJ (Brazil); Espirito Santo Univ., Vitoria, ES (Brazil). Dept. de Fisica e Quimica; E-mail: orlando@cce.ufes.br

2003-01-01

Taking as starting point a Lorentz and CPT non-invariant Chern-Simons-like model defined in 1+3 dimensions, we proceed realizing its dimensional to D = 1+2. One then obtains a new planar model, composed by the Maxwell-Chern-Simons (MCS) sector, a Klein-Gordon massless scalar field, and a coupling term that mixes the gauge field to the external vector, {nu}{sup {mu}}. In spite of breaking Lorentz invariance in the particle frame, this model may preserve the CPT symmetry for a single particular choice of {nu}{sup {mu}} . Analyzing the dispersion relations, one verifies that the reduced model exhibits stability, but the causality can be jeopardized by some modes. The unitary of the gauge sector is assured without any restriction , while the scalar sector is unitary only in the space-like case. (author)

Efficient two-dimensional compressive sensing in MIMO radar

Science.gov (United States)

Shahbazi, Nafiseh; Abbasfar, Aliazam; Jabbarian-Jahromi, Mohammad

2017-12-01

Compressive sensing (CS) has been a way to lower sampling rate leading to data reduction for processing in multiple-input multiple-output (MIMO) radar systems. In this paper, we further reduce the computational complexity of a pulse-Doppler collocated MIMO radar by introducing a two-dimensional (2D) compressive sensing. To do so, we first introduce a new 2D formulation for the compressed received signals and then we propose a new measurement matrix design for our 2D compressive sensing model that is based on minimizing the coherence of sensing matrix using gradient descent algorithm. The simulation results show that our proposed 2D measurement matrix design using gradient decent algorithm (2D-MMDGD) has much lower computational complexity compared to one-dimensional (1D) methods while having better performance in comparison with conventional methods such as Gaussian random measurement matrix.

High index surfaces of Au-nanocrystals supported on one-dimensional MoO3-nanorod as a bi-functional electrocatalyst for ethanol oxidation and oxygen reduction

International Nuclear Information System (INIS)

Karuppasamy, L.; Chen, C.Y.; Anandan, S.; Wu, J.J.

2017-01-01

Highlights: •Synthesis of a new class of Au nanocrystals enclosed with high index surface supported on MoO 3 nanorods by ultrasonic probe method. •The role of supporting materials reduces the loading of Au and acts as a co-catalyst. •The as prepared electrocatalyst exhibits enhanced catalytic activity and stability towards both EOR and ORR. -- Abstract: The design of highly active electrocatalyst for ethanol electrooxidation (EOR) and oxygen reduction reaction (ORR) is of great significance for the improvement of efficient direct ethanol fuel cells (DEFCs). Therefore, creating high index facets nanocrystals with abundant catalytic active sites of stepped atoms is an effective way to enhance the electrocatalytic performance. In this article, we prepared the high index surface structures of Au nanocrystals supported on one-dimensional (1-D) MoO 3 nanorods by using two steps ultrasonic probe irradiation method. The size and physical properties of as electrocatalysts were studied by using field emission scanning electron microscopy (FE-SEM), high-resolution transmission electron microscopy (HR-TEM), and x-ray diffraction (XRD) instrumentation. Besides, the catalytic activity of as Au-MoO 3 electrocatalyst was determined by using cyclic voltammetry (CV), chronoamperometric (CA), electrochemical impedance spectroscopy (EIS), CO-stripping, and linear sweep voltammetry-rotating disk electrode (LSV-RDE). As a consequence, the Au-MoO 3 nanocomposites has been considered as an effective electrocatalyst for both ethanol oxidation and oxygen reduction reaction.

Evaluation and Development of Chemical Kinetic Mechanism Reduction Scheme for Biodiesel and Diesel Fuel Surrogates

DEFF Research Database (Denmark)

Poon, Hiew Mun; Ng, Hoon Kiat; Gan, Suyin

2013-01-01

The aim of this study is to evaluate the existing chemical kinetic mechanism reduction techniques. From here, an appropriate reduction scheme was developed to create compact yet comprehensive surrogate models for both diesel and biodiesel fuels for diesel engine applications. The reduction...... techniques applied here were Directed Relation Graph (DRG), DRG with Error Propagation, DRG-aided Sensitivity Analysis, and DRG with Error Propagation and Sensitivity Analysis. Nonetheless, the reduced mechanisms generated via these techniques were not sufficiently small for application in multi......-dimensional computational fluid dynamics (CFD) study. A new reduction scheme was therefore formulated. A 68-species mechanism for biodiesel surrogate and a 49-species mechanism for diesel surrogate were successfully derived from the respective detailed mechanisms. An overall 97% reduction in species number...

Ensemble Classification of Data Streams Based on Attribute Reduction and a Sliding Window

Directory of Open Access Journals (Sweden)

Yingchun Chen

2018-04-01

Full Text Available With the current increasing volume and dimensionality of data, traditional data classification algorithms are unable to satisfy the demands of practical classification applications of data streams. To deal with noise and concept drift in data streams, we propose an ensemble classification algorithm based on attribute reduction and a sliding window in this paper. Using mutual information, an approximate attribute reduction algorithm based on rough sets is used to reduce data dimensionality and increase the diversity of reduced results in the algorithm. A double-threshold concept drift detection method and a three-stage sliding window control strategy are introduced to improve the performance of the algorithm when dealing with both noise and concept drift. The classification precision is further improved by updating the base classifiers and their nonlinear weights. Experiments on synthetic datasets and actual datasets demonstrate the performance of the algorithm in terms of classification precision, memory use, and time efficiency.

Scalable posterior approximations for large-scale Bayesian inverse problems via likelihood-informed parameter and state reduction

Science.gov (United States)

Cui, Tiangang; Marzouk, Youssef; Willcox, Karen

2016-06-01

Two major bottlenecks to the solution of large-scale Bayesian inverse problems are the scaling of posterior sampling algorithms to high-dimensional parameter spaces and the computational cost of forward model evaluations. Yet incomplete or noisy data, the state variation and parameter dependence of the forward model, and correlations in the prior collectively provide useful structure that can be exploited for dimension reduction in this setting-both in the parameter space of the inverse problem and in the state space of the forward model. To this end, we show how to jointly construct low-dimensional subspaces of the parameter space and the state space in order to accelerate the Bayesian solution of the inverse problem. As a byproduct of state dimension reduction, we also show how to identify low-dimensional subspaces of the data in problems with high-dimensional observations. These subspaces enable approximation of the posterior as a product of two factors: (i) a projection of the posterior onto a low-dimensional parameter subspace, wherein the original likelihood is replaced by an approximation involving a reduced model; and (ii) the marginal prior distribution on the high-dimensional complement of the parameter subspace. We present and compare several strategies for constructing these subspaces using only a limited number of forward and adjoint model simulations. The resulting posterior approximations can rapidly be characterized using standard sampling techniques, e.g., Markov chain Monte Carlo. Two numerical examples demonstrate the accuracy and efficiency of our approach: inversion of an integral equation in atmospheric remote sensing, where the data dimension is very high; and the inference of a heterogeneous transmissivity field in a groundwater system, which involves a partial differential equation forward model with high dimensional state and parameters.

A computational intelligent approach to multi-factor analysis of violent crime information system

Science.gov (United States)

Liu, Hongbo; Yang, Chao; Zhang, Meng; McLoone, Seán; Sun, Yeqing

2017-02-01

Various scientific studies have explored the causes of violent behaviour from different perspectives, with psychological tests, in particular, applied to the analysis of crime factors. The relationship between bi-factors has also been extensively studied including the link between age and crime. In reality, many factors interact to contribute to criminal behaviour and as such there is a need to have a greater level of insight into its complex nature. In this article we analyse violent crime information systems containing data on psychological, environmental and genetic factors. Our approach combines elements of rough set theory with fuzzy logic and particle swarm optimisation to yield an algorithm and methodology that can effectively extract multi-knowledge from information systems. The experimental results show that our approach outperforms alternative genetic algorithm and dynamic reduct-based techniques for reduct identification and has the added advantage of identifying multiple reducts and hence multi-knowledge (rules). Identified rules are consistent with classical statistical analysis of violent crime data and also reveal new insights into the interaction between several factors. As such, the results are helpful in improving our understanding of the factors contributing to violent crime and in highlighting the existence of hidden and intangible relationships between crime factors.

Green reduction of graphene oxide by ascorbic acid

Science.gov (United States)

Khosroshahi, Zahra; Kharaziha, Mahshid; Karimzadeh, Fathallah; Allafchian, Alireza

2018-01-01

Graphene, a single layer of sp2-hybridized carbon atoms in a hexagonal (two-dimensional honey-comb) lattice, has attracted strong scientific and technological interest due to its novel and excellent optical, chemical, electrical, mechanical and thermal properties. The solution-processable chemical reduction of Graphene oxide (GO is considered as the most favorable method regarding mass production of graphene. Generally, the reduction of GO is carried out by chemical approaches using different reductants such as hydrazine and sodium borohydride. These components are corrosive, combustible and highly toxic which may be dangerous for personnel health and the environment. Hence, these reducing agents are not promising choice for reducing of graphene oxide (GO). As a consequence, it is necessary for further development and optimization of eco-friendly, natural reducing agent for clean and effective reduction of GO. Ascorbic acid, an eco-friendly and natural reducing agents, having a mild reductive ability and nontoxic property. So, the aim of this research was to green synthesis of GO with ascorbic acid. For this purpose, the required amount of NaOH and ascorbic acid were added to GO solution (0.5 mg/ml) and were heated at 95 °C for 1 hour. According to the X-ray powder diffraction (XRD), scanning electron microscopy (SEM), and electrochemical results, GO were reduced with ascorbic acid like hydrazine with better electrochemical properties and ascorbic acid is an ideal substitute for hydrazine in the reduction of graphene oxide process.

Reduction of the Glauber amplitude for electron impact rotational excitation of quadrupolar molecular ions

International Nuclear Information System (INIS)

Mathur, K.C.; Gupta, G.P.; Pundir, R.S.

1981-06-01

A reduction of the Glauber amplitude for the rotational excitation of pure quadrupolar molecular ions by electron impact is presented in a form suitable for numerical evaluation. The differential cross-section is expressed in terms of one dimensional integrals over impact parameter. (author)

The multicomponent (2+1)-dimensional Glachette–Johnson (GJ) equation hierarchy and its super-integrable coupling system

International Nuclear Information System (INIS)

Yu Fajun; Zhang Hongqing

2008-01-01

This paper presents a set of multicomponent matrix Lie algebra, which is used to construct a new loop algebra à M . By using the Tu scheme, a Liouville integrable multicomponent equation hierarchy is generated, which possesses the Hamiltonian structure. As its reduction cases, the multicomponent (2+1)-dimensional Glachette–Johnson (GJ) hierarchy is given. Finally, the super-integrable coupling system of multicomponent (2+1)-dimensional GJ hierarchy is established through enlarging the spectral problem

Renormalization Group Reduction of Non Integrable Hamiltonian Systems

International Nuclear Information System (INIS)

Tzenov, Stephan I.

2002-01-01

Based on Renormalization Group method, a reduction of non integratable multi-dimensional Hamiltonian systems has been performed. The evolution equations for the slowly varying part of the angle-averaged phase space density and for the amplitudes of the angular modes have been derived. It has been shown that these equations are precisely the Renormalization Group equations. As an application of the approach developed, the modulational diffusion in one-and-a-half degrees of freedom dynamical system has been studied in detail

One-loop infinities in dimensionally reduced supergravities

International Nuclear Information System (INIS)

Fradkin, E.S.; Tseytlin, A.A.

1983-11-01

It is proved explicitly in the paper that d=4 theory following via reduction from N=1, d=10 supergravities is not finite at one loop while the version of N=8 supergravity directly following from N=1, d=11 theory is one-loop finite. The method used is based on quantization of initial higher dimensional theory as a first step. The results also suggest possible existence of non-standard (higher N) d>4 supergravities which reduce to d=4 theories with finite N=8 supergravity sector. (author)

Three-dimensional laparoscopy vs 2-dimensional laparoscopy with high-definition technology for abdominal surgery: a systematic review.

Science.gov (United States)

Fergo, Charlotte; Burcharth, Jakob; Pommergaard, Hans-Christian; Kildebro, Niels; Rosenberg, Jacob

2017-01-01

This systematic review investigates newer generation 3-dimensional (3D) laparoscopy vs 2-dimensional (2D) laparoscopy in terms of error rating, performance time, and subjective assessment as early comparisons have shown contradictory results due to technological shortcomings. This systematic review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Randomized controlled trials (RCTs) comparing newer generation 3D-laparoscopy with 2D-laparoscopy were included through searches in Pubmed, EMBASE, and Cochrane Central Register of Controlled Trials database. Of 643 articles, 13 RCTs were included, of which 2 were clinical trials. Nine of 13 trials (69%) and 10 of 13 trials (77%) found a significant reduction in performance time and error, respectively, with the use of 3D-laparoscopy. Overall, 3D-laparoscopy was found to be superior or equal to 2D-laparoscopy. All trials featuring subjective evaluation found a superiority of 3D-laparoscopy. More clinical RCTs are still awaited for the convincing results to be reproduced. Copyright © 2016 Elsevier Inc. All rights reserved.

Artificial neural network-based exploration of gene-nutrient interactions in folate and xenobiotic metabolic pathways that modulate susceptibility to breast cancer.

Science.gov (United States)

Naushad, Shaik Mohammad; Ramaiah, M Janaki; Pavithrakumari, Manickam; Jayapriya, Jaganathan; Hussain, Tajamul; Alrokayan, Salman A; Gottumukkala, Suryanarayana Raju; Digumarti, Raghunadharao; Kutala, Vijay Kumar

2016-04-15

In the current study, an artificial neural network (ANN)-based breast cancer prediction model was developed from the data of folate and xenobiotic pathway genetic polymorphisms along with the nutritional and demographic variables to investigate how micronutrients modulate susceptibility to breast cancer. The developed ANN model explained 94.2% variability in breast cancer prediction. Fixed effect models of folate (400 μg/day) and B12 (6 μg/day) showed 33.3% and 11.3% risk reduction, respectively. Multifactor dimensionality reduction analysis showed the following interactions in responders to folate: RFC1 G80A × MTHFR C677T (primary), COMT H108L × CYP1A1 m2 (secondary), MTR A2756G (tertiary). The interactions among responders to B12 were RFC1G80A × cSHMT C1420T and CYP1A1 m2 × CYP1A1 m4. ANN simulations revealed that increased folate might restore ER and PR expression and reduce the promoter CpG island methylation of extra cellular superoxide dismutase and BRCA1. Dietary intake of folate appears to confer protection against breast cancer through its modulating effects on ER and PR expression and methylation of EC-SOD and BRCA1. Copyright © 2016 Elsevier B.V. All rights reserved.

An analytical approach for a nodal scheme of two-dimensional neutron transport problems

International Nuclear Information System (INIS)

Barichello, L.B.; Cabrera, L.C.; Prolo Filho, J.F.

2011-01-01

Research highlights: → Nodal equations for a two-dimensional neutron transport problem. → Analytical Discrete Ordinates Method. → Numerical results compared with the literature. - Abstract: In this work, a solution for a two-dimensional neutron transport problem, in cartesian geometry, is proposed, on the basis of nodal schemes. In this context, one-dimensional equations are generated by an integration process of the multidimensional problem. Here, the integration is performed for the whole domain such that no iterative procedure between nodes is needed. The ADO method is used to develop analytical discrete ordinates solution for the one-dimensional integrated equations, such that final solutions are analytical in terms of the spatial variables. The ADO approach along with a level symmetric quadrature scheme, lead to a significant order reduction of the associated eigenvalues problems. Relations between the averaged fluxes and the unknown fluxes at the boundary are introduced as the usually needed, in nodal schemes, auxiliary equations. Numerical results are presented and compared with test problems.

On a class of reductions of the Manakov-Santini hierarchy connected with the interpolating system

International Nuclear Information System (INIS)

Bogdanov, L V

2010-01-01

Using the Lax-Sato formulation of the Manakov-Santini hierarchy, we introduce a class of reductions such that the zero-order reduction of this class corresponds to the dKP hierarchy, and the first-order reduction gives the hierarchy associated with the interpolating system introduced by Dunajski. We present the Lax-Sato form of a reduced hierarchy for the interpolating system and also for the reduction of arbitrary order. Similar to the dKP hierarchy, the Lax-Sato equations for L (the Lax function) split from the Lax-Sato equations for M (the Orlov function) due to the reduction, and the reduced hierarchy for an arbitrary order of reduction is defined by Lax-Sato equations for L only. A characterization of the class of reductions in terms of the dressing data is given. We also consider a waterbag reduction of the interpolating system hierarchy, which defines (1+1)-dimensional systems of hydrodynamic type.

An adaptive Kalman filter for speckle reductions in ultrasound images

International Nuclear Information System (INIS)

Castellini, G.; Labate, D.; Masotti, L.; Mannini, E.; Rocchi, S.

1988-01-01

Speckle is the term used to describe the granular appearance found in ultrasound images. The presence of speckle reduces the diagnostic potential of the echographic technique because it tends to mask small inhomogeneities of the investigated tissue. We developed a new method of speckle reductions that utilizes an adaptive one-dimensional Kalman filter based on the assumption that the observed image can be considered as a superimposition of speckle on a ''true images''. The filter adaptivity, necessary to avoid loss of resolution, has been obtained by statistical considerations on the local signal variations. The results of the applications of this particular Kalman filter, both on A-Mode and B-MODE images, show a significant speckle reduction

Large Reduction of Hot Spot Temperature in Graphene Electronic Devices with Heat-Spreading Hexagonal Boron Nitride.

Science.gov (United States)

Choi, David; Poudel, Nirakar; Park, Saungeun; Akinwande, Deji; Cronin, Stephen B; Watanabe, Kenji; Taniguchi, Takashi; Yao, Zhen; Shi, Li

2018-04-04

Scanning thermal microscopy measurements reveal a significant thermal benefit of including a high thermal conductivity hexagonal boron nitride (h-BN) heat-spreading layer between graphene and either a SiO 2 /Si substrate or a 100 μm thick Corning flexible Willow glass (WG) substrate. At the same power density, an 80 nm thick h-BN layer on the silicon substrate can yield a factor of 2.2 reduction of the hot spot temperature, whereas a 35 nm thick h-BN layer on the WG substrate is sufficient to obtain a factor of 4.1 reduction. The larger effect of the h-BN heat spreader on WG than on SiO 2 /Si is attributed to a smaller effective heat transfer coefficient per unit area for three-dimensional heat conduction into the thick, low-thermal conductivity WG substrate than for one-dimensional heat conduction through the thin oxide layer on silicon. Consequently, the h-BN lateral heat-spreading length is much larger on WG than on SiO 2 /Si, resulting in a larger degree of temperature reduction.

Rational solutions to two- and one-dimensional multicomponent Yajima–Oikawa systems

International Nuclear Information System (INIS)

Chen, Junchao; Chen, Yong; Feng, Bao-Feng; Maruno, Ken-ichi

2015-01-01

Exact explicit rational solutions of two- and one-dimensional multicomponent Yajima–Oikawa (YO) systems, which contain multi-short-wave components and single long-wave one, are presented by using the bilinear method. For two-dimensional system, the fundamental rational solution first describes the localized lumps, which have three different patterns: bright, intermediate and dark states. Then, rogue waves can be obtained under certain parameter conditions and their behaviors are also classified to above three patterns with different definition. It is shown that the simplest (fundamental) rogue waves are line localized waves which arise from the constant background with a line profile and then disappear into the constant background again. In particular, two-dimensional intermediate and dark counterparts of rogue wave are found with the different parameter requirements. We demonstrate that multirogue waves describe the interaction of several fundamental rogue waves, in which interesting curvy wave patterns appear in the intermediate times. Different curvy wave patterns form in the interaction of different types fundamental rogue waves. Higher-order rogue waves exhibit the dynamic behaviors that the wave structures start from lump and then retreat back to it, and this transient wave possesses the patterns such as parabolas. Furthermore, different states of higher-order rogue wave result in completely distinguishing lumps and parabolas. Moreover, one-dimensional rogue wave solutions with three states are constructed through the further reduction. Specifically, higher-order rogue wave in one-dimensional case is derived under the parameter constraints. - Highlights: • Exact explicit rational solutions of two-and one-dimensional multicomponent Yajima–Oikawa systems. • Two-dimensional rogue wave contains three different patterns: bright, intermediate and dark states. • Multi- and higher-order rogue waves exhibit distinct dynamic behaviors in two-dimensional case

ONE-DIMENSIONAL AND TWO-DIMENSIONAL LEADERSHIP STYLES

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Nikola Stefanović

2007-06-01

Full Text Available In order to motivate their group members to perform certain tasks, leaders use different leadership styles. These styles are based on leaders' backgrounds, knowledge, values, experiences, and expectations. The one-dimensional styles, used by many world leaders, are autocratic and democratic styles. These styles lie on the two opposite sides of the leadership spectrum. In order to precisely define the leadership styles on the spectrum between the autocratic leadership style and the democratic leadership style, leadership theory researchers use two dimensional matrices. The two-dimensional matrices define leadership styles on the basis of different parameters. By using these parameters, one can identify two-dimensional styles.

Light-cone reduction vs. TsT transformations: a fluid dynamics perspective

Science.gov (United States)

Dutta, Suvankar; Krishna, Hare

2018-05-01

We compute constitutive relations for a charged (2+1) dimensional Schrödinger fluid up to first order in derivative expansion, using holographic techniques. Starting with a locally boosted, asymptotically AdS, 4 + 1 dimensional charged black brane geometry, we uplift that to ten dimensions and perform TsT transformations to obtain an effective five dimensional local black brane solution with asymptotically Schrödinger isometries. By suitably implementing the holographic techniques, we compute the constitutive relations for the effective fluid living on the boundary of this space-time and extract first order transport coefficients from these relations. Schrödinger fluid can also be obtained by reducing a charged relativistic conformal fluid over light-cone. It turns out that both the approaches result the same system at the end. Fluid obtained by light-cone reduction satisfies a restricted class of thermodynamics. Here, we see that the charged fluid obtained holographically also belongs to the same restricted class.

Optimal dose reduction in computed tomography methodologies predicted from real-time dosimetry

Science.gov (United States)

Tien, Christopher Jason

Over the past two decades, computed tomography (CT) has become an increasingly common and useful medical imaging technique. CT is a noninvasive imaging modality with three-dimensional volumetric viewing abilities, all in sub-millimeter resolution. Recent national scrutiny on radiation dose from medical exams has spearheaded an initiative to reduce dose in CT. This work concentrates on dose reduction of individual exams through two recently-innovated dose reduction techniques: organ dose modulation (ODM) and tube current modulation (TCM). ODM and TCM tailor the phase and amplitude of x-ray current, respectively, used by the CT scanner during the scan. These techniques are unique because they can be used to achieve patient dose reduction without any appreciable loss in image quality. This work details the development of the tools and methods featuring real-time dosimetry which were used to provide pioneering measurements of ODM or TCM in dose reduction for CT.

Model Reduction of Fuzzy Logic Systems

Directory of Open Access Journals (Sweden)

Zhandong Yu

2014-01-01

Full Text Available This paper deals with the problem of ℒ2-ℒ∞ model reduction for continuous-time nonlinear uncertain systems. The approach of the construction of a reduced-order model is presented for high-order nonlinear uncertain systems described by the T-S fuzzy systems, which not only approximates the original high-order system well with an ℒ2-ℒ∞ error performance level γ but also translates it into a linear lower-dimensional system. Then, the model approximation is converted into a convex optimization problem by using a linearization procedure. Finally, a numerical example is presented to show the effectiveness of the proposed method.

Pixel-based analysis of comprehensive two-dimensional gas chromatograms (color plots) of petroleum

DEFF Research Database (Denmark)

Furbo, Søren; Hansen, Asger B.; Skov, Thomas

2014-01-01

We demonstrate how to process comprehensive two-dimensional gas chromatograms (GC × GC chromatograms) to remove nonsample information (artifacts), including background and retention time shifts. We also demonstrate how this, combined with further reduction of the influence of irrelevant informati......, allows for data analysis without integration or peak deconvolution (pixelbased analysis)....

New exact solutions of (2 + 1)-dimensional Gardner equation via the new sine-Gordon equation expansion method

International Nuclear Information System (INIS)

Chen Yong; Yan Zhenya

2005-01-01

In this paper (2 + 1)-dimensional Gardner equation is investigated using a sine-Gordon equation expansion method, which was presented via a generalized sine-Gordon reduction equation and a new transformation. As a consequence, it is shown that the method is more powerful to obtain many types of new doubly periodic solutions of (2 + 1)-dimensional Gardner equation. In particular, solitary wave solutions are also given as simple limits of doubly periodic solutions

Advantages of three-dimensional treatment planning in radiation therapy

International Nuclear Information System (INIS)

Attalla, E.M.; ELSAyed, A.A.; ElGantiry, M.; ElTahher, Z.

2003-01-01

This study was designed to demonstrate the feasibility of three-dimensional (3-D) treatment planning in-patients maxilla, breast, bladder, and lung tumors to explore its potential therapeutic advantage over the traditional dimensional (2-D) approach in these diseases. Conventional two-dimensional (2-D) treatment planning was compared to three-dimensional (3-D) treatment planning. In five selected disease sites, plans calculated with both types of treatment planning were compared. The (3-D) treatment planning system used in this work TMS version 5.1 B from helax AB is based on a monte Carlo-based pencil beam model. The other treatment planning system (2-D 0, introduced in this study was the multi data treatment planning system version 2.35. For the volumes of interest; quality of dose distribution concerning homogeneity in the target volume and the isodose distribution in organs at risk, was discussed. Qualitative and quantitative comparisons between the two planning systems were made using dose volume histograms (DVH's) . For comparisons of dose distributions in real-patient cases, differences ranged from 0.8% to 6.4% for 6 MV, while in case of 18 MV photon, it ranged from 1,8% to 6.5% and was within -+3 standard deviations for the dose between the two planning systems.Dose volume histogram (DVH) shows volume reduction of the radiation-related organs at risk 3-D planning

Survival dimensionality reduction (SDR: development and clinical application of an innovative approach to detect epistasis in presence of right-censored data

Directory of Open Access Journals (Sweden)

Beretta Lorenzo

2010-08-01

Full Text Available Abstract Background Epistasis is recognized as a fundamental part of the genetic architecture of individuals. Several computational approaches have been developed to model gene-gene interactions in case-control studies, however, none of them is suitable for time-dependent analysis. Herein we introduce the Survival Dimensionality Reduction (SDR algorithm, a non-parametric method specifically designed to detect epistasis in lifetime datasets. Results The algorithm requires neither specification about the underlying survival distribution nor about the underlying interaction model and proved satisfactorily powerful to detect a set of causative genes in synthetic epistatic lifetime datasets with a limited number of samples and high degree of right-censorship (up to 70%. The SDR method was then applied to a series of 386 Dutch patients with active rheumatoid arthritis that were treated with anti-TNF biological agents. Among a set of 39 candidate genes, none of which showed a detectable marginal effect on anti-TNF responses, the SDR algorithm did find that the rs1801274 SNP in the FcγRIIa gene and the rs10954213 SNP in the IRF5 gene non-linearly interact to predict clinical remission after anti-TNF biologicals. Conclusions Simulation studies and application in a real-world setting support the capability of the SDR algorithm to model epistatic interactions in candidate-genes studies in presence of right-censored data. Availability: http://sourceforge.net/projects/sdrproject/

Higher (odd dimensional quantum Hall effect and extended dimensional hierarchy

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Kazuki Hasebe

2017-07-01

Full Text Available We demonstrate dimensional ladder of higher dimensional quantum Hall effects by exploiting quantum Hall effects on arbitrary odd dimensional spheres. Non-relativistic and relativistic Landau models are analyzed on S2k−1 in the SO(2k−1 monopole background. The total sub-band degeneracy of the odd dimensional lowest Landau level is shown to be equal to the winding number from the base-manifold S2k−1 to the one-dimension higher SO(2k gauge group. Based on the chiral Hopf maps, we clarify the underlying quantum Nambu geometry for odd dimensional quantum Hall effect and the resulting quantum geometry is naturally embedded also in one-dimension higher quantum geometry. An origin of such dimensional ladder connecting even and odd dimensional quantum Hall effects is illuminated from a viewpoint of the spectral flow of Atiyah–Patodi–Singer index theorem in differential topology. We also present a BF topological field theory as an effective field theory in which membranes with different dimensions undergo non-trivial linking in odd dimensional space. Finally, an extended version of the dimensional hierarchy for higher dimensional quantum Hall liquids is proposed, and its relationship to quantum anomaly and D-brane physics is discussed.

Sensitive electrochemical immunosensor based on three-dimensional nanostructure gold electrode

Directory of Open Access Journals (Sweden)

Zhong G

2015-03-01

Full Text Available Guangxian Zhong,1,2,* Ruilong Lan,3,* Wenxin Zhang,1,4 Feihuan Fu,5 Yiming Sun,1,4 Huaping Peng,1,4 Tianbin Chen,3 Yishan Cai,6 Ailin Liu,1,4 Jianhua Lin,2 Xinhua Lin1,4 1Department of Pharmaceutical Analysis, Faculty of Pharmacy, Fujian Medical University, 2Department of Orthopaedics, 3The Centralab, First Affiliated Hospital of Fujian Medical University, 4Nano Medical Technology Research Institute, Fujian Medical University, Fuzhou, 5Department of Endocrinology, The County Hospital of Anxi, Anxi, 6Fujian International Travel Healthcare Center, Fujian Entry-Exit Inspection and Quarantine Bureau, Fuzhou, People’s Republic of China *These authors contributed equally to this work Abstract: A sensitive electrochemical immunosensor was developed for detection of alpha-fetoprotein (AFP based on a three-dimensional nanostructure gold electrode using a facile, rapid, “green” square-wave oxidation-reduction cycle technique. The resulting three-dimensional gold nanocomposites were characterized by scanning electron microscopy and cyclic voltammetry. A “sandwich-type” detection strategy using an electrochemical immunosensor was employed. Under optimal conditions, a good linear relationship between the current response signal and the AFP concentrations was observed in the range of 10–50 ng/mL with a detection limit of 3 pg/mL. This new immunosensor showed a fast amperometric response and high sensitivity and selectivity. It was successfully used to determine AFP in a human serum sample with a relative standard deviation of <5% (n=5. The proposed immunosensor represents a significant step toward practical application in clinical diagnosis and monitoring of prognosis. Keywords: electrochemical immunosensors, three-dimensional nanostructure gold electrode, square-wave oxidation-reduction cycle, alpha-fetoprotein 

Full two-dimensional rotor plane inflow measurements by a spinner-integrated wind lidar

DEFF Research Database (Denmark)

Sjöholm, Mikael; Pedersen, Anders Tegtmeier; Angelou, Nikolas

2013-01-01

Introduction Wind turbine load reduction and power performance optimization via advanced control strategies is an active area in the wind energy community. In particular, feed-forward control using upwind inflow measurements by lidar (light detection and ranging) remote sensing instruments has...... novel full two-dimensional radial inflow measurements. Approach In order to achieve full two-dimensional radial inflow measurements, a special laser beam scanner has been developed at the DTU Wind Energy Department. It is based on two rotating prisms that each deviate the beam by 15°, resulting......, a proof-of-concept trial with a blade mounted lidar was performed during the measurement campaign and is reported in a separate EWEA 2013 contribution. Conclusion The study presented here is the novel full two-dimensional continuation of the previous inflow measurements on a circle presented in the paper...

Contribution to modeling and dynamic risk hedging in energy markets

International Nuclear Information System (INIS)

Noufel, Frikha

2010-12-01

This thesis is concerned with probabilistic numerical problems about modeling, risk control and risk hedging motivated by applications to energy markets. The main tool is based on stochastic approximation and simulation methods. This thesis consists of three parts. The first one is devoted to the computation of two risk measures of the portfolio loss distribution L: the Value-at-Risk (VaR) and the Conditional Value-at-Risk (CVaR). This computation uses a stochastic algorithm combined with an adaptive variance reduction technique. The first part of this chapter deals with the finite dimensional case, the second part extends the results of the first part to the case of a path-dependency process and the last one deals low discrepancy sequences. The second chapter is devoted with risk minimizing hedging strategies in an incomplete market operating in discrete time using quantization based stochastic approximation. Theoretical results on CVaR hedging are presented then numerical aspects are addressed in a Markovian framework. The last part deals with joint modeling of Gas and Electricity spot prices. The multi-factor model presented is based on stationary Ornstein process with parameterized diffusion coefficient. (author)

Capturing pair-wise epistatic effects associated with three agronomic traits in barley.

Science.gov (United States)

Xu, Yi; Wu, Yajun; Wu, Jixiang

2018-04-01

Genetic association mapping has been widely applied to determine genetic markers favorably associated with a trait of interest and provide information for marker-assisted selection. Many association mapping studies commonly focus on main effects due to intolerable computing intensity. This study aims to select several sets of DNA markers with potential epistasis to maximize genetic variations of some key agronomic traits in barley. By doing so, we integrated a MDR (multifactor dimensionality reduction) method with a forward variable selection approach. This integrated approach was used to determine single nucleotide polymorphism pairs with epistasis effects associated with three agronomic traits: heading date, plant height, and grain yield in barley from the barley Coordinated Agricultural Project. Our results showed that four, seven, and five SNP pairs accounted for 51.06, 45.66 and 40.42% for heading date, plant height, and grain yield, respectively with epistasis being considered, while corresponding contributions to these three traits were 45.32, 31.39, 31.31%, respectively without epistasis being included. The results suggested that epistasis model was more effective than non-epistasis model in this study and can be more preferred for other applications.

Detection of superior genotype of fatty acid synthase in Korean native cattle by an environment-adjusted statistical model

Directory of Open Access Journals (Sweden)

Jea-Young Lee

2017-06-01

Full Text Available Objective This study examines the genetic factors influencing the phenotypes (four economic traits:oleic acid [C18:1], monounsaturated fatty acids, carcass weight, and marbling score of Hanwoo. Methods To enhance the accuracy of the genetic analysis, the study proposes a new statistical model that excludes environmental factors. A statistically adjusted, analysis of covariance model of environmental and genetic factors was developed, and estimated environmental effects (covariate effects of age and effects of calving farms were excluded from the model. Results The accuracy was compared before and after adjustment. The accuracy of the best single nucleotide polymorphism (SNP in C18:1 increased from 60.16% to 74.26%, and that of the two-factor interaction increased from 58.69% to 87.19%. Also, superior SNPs and SNP interactions were identified using the multifactor dimensionality reduction method in Table 1 to 4. Finally, high- and low-risk genotypes were compared based on their mean scores for each trait. Conclusion The proposed method significantly improved the analysis accuracy and identified superior gene-gene interactions and genotypes for each of the four economic traits of Hanwoo.

Three-dimensional friction measurement during hip simulation.

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Robert Sonntag

Full Text Available Wear of total hip replacements has been the focus of many studies. However, frictional effects, such as high loading on intramodular connections or the interface to the bone, as well as friction associated squeaking have recently increased interest about the amount of friction that is generated during daily activities. The aim of this study was thus to establish and validate a three-dimensional friction setup under standardized conditions.A standard hip simulator was modified to allow for high precision measurements of small frictional effects in the hip during three-dimensional hip articulation. The setup was verified by an ideal hydrostatic bearing and validated with a static-load physical pendulum and an extension-flexion rotation with a dynamic load profile. Additionally, a pendulum model was proposed for screening measurement of frictional effects based on the damping behavior of the angular oscillation without the need for any force/moment transducer. Finally, three-dimensional friction measurements have been realized for ceramic-on-polyethylene bearings of three different sizes (28, 36 and 40 mm.A precision of less than 0.2 Nm during three-dimensional friction measurements was reported, while increased frictional torque (resultant as well as taper torque was measured for larger head diameters. These effects have been confirmed by simple pendulum tests and the theoretical model. A comparison with current literature about friction measurements is presented.This investigation of friction is able to provide more information about a field that has been dominated by the reduction of wear. It should be considered in future pre-clinical testing protocols given by international organizations of standardization.

The additive hazards model with high-dimensional regressors

DEFF Research Database (Denmark)

Martinussen, Torben; Scheike, Thomas

2009-01-01

This paper considers estimation and prediction in the Aalen additive hazards model in the case where the covariate vector is high-dimensional such as gene expression measurements. Some form of dimension reduction of the covariate space is needed to obtain useful statistical analyses. We study...... model. A standard PLS algorithm can also be constructed, but it turns out that the resulting predictor can only be related to the original covariates via time-dependent coefficients. The methods are applied to a breast cancer data set with gene expression recordings and to the well known primary biliary...

ODF Maxima Extraction in Spherical Harmonic Representation via Analytical Search Space Reduction

Science.gov (United States)

Aganj, Iman; Lenglet, Christophe; Sapiro, Guillermo

2015-01-01

By revealing complex fiber structure through the orientation distribution function (ODF), q-ball imaging has recently become a popular reconstruction technique in diffusion-weighted MRI. In this paper, we propose an analytical dimension reduction approach to ODF maxima extraction. We show that by expressing the ODF, or any antipodally symmetric spherical function, in the common fourth order real and symmetric spherical harmonic basis, the maxima of the two-dimensional ODF lie on an analytically derived one-dimensional space, from which we can detect the ODF maxima. This method reduces the computational complexity of the maxima detection, without compromising the accuracy. We demonstrate the performance of our technique on both artificial and human brain data. PMID:20879302

Analysis and Reduction of Complex Networks Under Uncertainty

Energy Technology Data Exchange (ETDEWEB)

Knio, Omar M

2014-04-09

This is a collaborative proposal that aims at developing new methods for the analysis and reduction of complex multiscale networks under uncertainty. The approach is based on combining methods of computational singular perturbation (CSP) and probabilistic uncertainty quantification. In deterministic settings, CSP yields asymptotic approximations of reduced-dimensionality “slow manifolds” on which a multiscale dynamical system evolves. Introducing uncertainty raises fundamentally new issues, particularly concerning its impact on the topology of slow manifolds, and means to represent and quantify associated variability. To address these challenges, this project uses polynomial chaos (PC) methods to reformulate uncertain network models, and to analyze them using CSP in probabilistic terms. Specific objectives include (1) developing effective algorithms that can be used to illuminate fundamental and unexplored connections among model reduction, multiscale behavior, and uncertainty, and (2) demonstrating the performance of these algorithms through applications to model problems.

Change in CANDU-6 reactivity following a power reduction at low PHT purity

International Nuclear Information System (INIS)

Whitlock, J.J.; Soulard, M.R.; Baudouin, A.

1995-01-01

The reactivity effect of a power reduction in CANDU-6 is examined using a three-dimensional, steady-state, coupled neutronics/thermalhydraulics methodology, starting from a global irradiation distribution matched to site data. The power reduction is sufficient to suppress coolant boiling in the fuel channels, and thus the significant parameters affecting reactivity are an increase in coolant density and a decrease in fuel temperature. These individual components are estimated using infinite-lattice-cell methodology. The effect of using newer methodology, particularly for the thermalhydraulic analysis, is examined by comparison with previous simulations. (author). 10 refs., 7 tabs., 1 fig

Comparison of two dimensional and three dimensional radiotherapy treatment planning in locally advanced non-small cell lung cancer treated with continuous hyperfractionated accelerated radiotherapy weekend less

International Nuclear Information System (INIS)

Wilson, Elena M.; Joy Williams, Frances; Ethan Lyn, Basil; Aird, Edwin G.A.

2005-01-01

Background and purpose: Patients with inoperable non-small cell lung cancer being treated with continuous hyperfractionated accelerated radiotherapy weekend less (CHARTWEL) were planned and treated with a three dimensional (3D) conformal protocol and comparison made with two dimensional (2D) planning, as used previously, to compare past practice and methods. Patients and methods: Twenty-four patients were planned initially using 3D and then replanned using a 2D system. The 2D plans were transferred onto the 3D system and recalculated. Dose volume histograms could then be constructed of planning target volumes for phases 1 and 2 (PTV 1 and 2, respectively), lung and spinal cord for the 2D plans and compared with the 3D plans. Results: There was a significantly lower absolute dose to the isocentre with 2D compared to 3D planning with dose reductions of 3.9% for phase 1, 4.4% for phase 2 and 4.7% for those treated with a single phase. Maximum dose to spinal cord was greater in 17 of the 24 2D plans with a median dose reduction of 0.82 Gy for 3D (P=0.04). The percentage volume of whole lung receiving ≥20 Gy (V 20 ) was greater in 16 of the 24 2D plans with a median reduction in V 20 of 2.4% for 3D (P=0.03). Conclusions: A lower dose to tumour was obtained using 2D planning due to the method of dose calculation and spinal cord and lung doses were significantly higher

Dimensional behavior of Ni-YSZ composites during redox cycling

DEFF Research Database (Denmark)

Pihlatie, Mikko; Kaiser, Andreas; Larsen, Peter Halvor

2009-01-01

The dimensional behavior of Ni-yttria-stabilized zirconia (YSZ) cermets during redox cycling was tested in dilatometry within the temperature range 600-1000 degrees C. The effect Of humidity oil redox stability was investigated at intermediate and low temperatures. We show that both the sintering...... of nickel depending on temperature of the initial reduction and the operating conditions, and the temperature of reoxidation are very important for the size of the dimensional change. Cumulative redox strain (CRS) is shown to be correlated with temperature. Measured maximum CRS after three redox cycles...... varies within 0.25-3.2% dL/L in dry gas and respective temperature range of 600-1000 degrees C. A high degree of redox reversibility was reached at low temperature. however. reversibility is lost at elevated temperatures. We found that at 850 degrees C, 6% steam and a very high p(H2O)/p(H2) ratio...

Some polarization properties of many-fermion systems for N-dimensional worlds in the framework of self-consistent renormalization

International Nuclear Information System (INIS)

Kucheryavy, V.I.

1997-01-01

Using the self-consistent renormalization we calculate five types of quantities (having the mass anisotropy in general) associated with the canonical Ward identities and reduction identities for two-point chronological fermion current correlators which describe most general polarization properties of fermionic sector for all n-dimensional quantum field theories incorporating fermions with both degenerate and nondegenerate fermion mass spectrum. The analysis of the vector and axial-vector Ward identities and the reduction ones for regular values of these quantities is carried out. The effective formulae for nontrivial quantum corrections (NQC) to the canonical Ward identities are obtained for any space-time dimension. The properties of the NQC are investigated in detail. The emphasis on the space-time dimension and the signature dependence has been made. Particular properties of the two-dimensional words are pointed out

PCA based feature reduction to improve the accuracy of decision tree c4.5 classification

Science.gov (United States)

Nasution, M. Z. F.; Sitompul, O. S.; Ramli, M.

2018-03-01

Splitting attribute is a major process in Decision Tree C4.5 classification. However, this process does not give a significant impact on the establishment of the decision tree in terms of removing irrelevant features. It is a major problem in decision tree classification process called over-fitting resulting from noisy data and irrelevant features. In turns, over-fitting creates misclassification and data imbalance. Many algorithms have been proposed to overcome misclassification and overfitting on classifications Decision Tree C4.5. Feature reduction is one of important issues in classification model which is intended to remove irrelevant data in order to improve accuracy. The feature reduction framework is used to simplify high dimensional data to low dimensional data with non-correlated attributes. In this research, we proposed a framework for selecting relevant and non-correlated feature subsets. We consider principal component analysis (PCA) for feature reduction to perform non-correlated feature selection and Decision Tree C4.5 algorithm for the classification. From the experiments conducted using available data sets from UCI Cervical cancer data set repository with 858 instances and 36 attributes, we evaluated the performance of our framework based on accuracy, specificity and precision. Experimental results show that our proposed framework is robust to enhance classification accuracy with 90.70% accuracy rates.

Dimensional and Compositional Change of 1D Chalcogen Nanostructures Leading to Tunable Localized Surface Plasmon Resonances.

Science.gov (United States)

Min, Yuho; Seo, Ho Jun; Choi, Jong-Jin; Hahn, Byung-Dong; Moon, Geon Dae

2018-05-31

As the oxygen family, chalcogen (Se, Te) nanostructures have been considered important elements for various practical fields and further exploited to constitute metal chalcogenides for each targeted application. Here we report a controlled synthesis of well-defined one-dimensional chalcogen nanostructures such as nanowries, nanorods, and nanotubes by controlling reduction reaction rate to fine-tune the dimension and composition of the products. Tunable optical properties (localized surface plasmon resonances) of these chalcogen nanostructures are observed depending on their morphological, dimensional, and compositional variation. © 2018 IOP Publishing Ltd.

An Out-of-Core GPU based dimensionality reduction algorithm for Big Mass Spectrometry Data and its application in bottom-up Proteomics.

Science.gov (United States)

Awan, Muaaz Gul; Saeed, Fahad

2017-08-01

Modern high resolution Mass Spectrometry instruments can generate millions of spectra in a single systems biology experiment. Each spectrum consists of thousands of peaks but only a small number of peaks actively contribute to deduction of peptides. Therefore, pre-processing of MS data to detect noisy and non-useful peaks are an active area of research. Most of the sequential noise reducing algorithms are impractical to use as a pre-processing step due to high time-complexity. In this paper, we present a GPU based dimensionality-reduction algorithm, called G-MSR, for MS2 spectra. Our proposed algorithm uses novel data structures which optimize the memory and computational operations inside GPU. These novel data structures include Binary Spectra and Quantized Indexed Spectra (QIS) . The former helps in communicating essential information between CPU and GPU using minimum amount of data while latter enables us to store and process complex 3-D data structure into a 1-D array structure while maintaining the integrity of MS data. Our proposed algorithm also takes into account the limited memory of GPUs and switches between in-core and out-of-core modes based upon the size of input data. G-MSR achieves a peak speed-up of 386x over its sequential counterpart and is shown to process over a million spectra in just 32 seconds. The code for this algorithm is available as a GPL open-source at GitHub at the following link: https://github.com/pcdslab/G-MSR.

QUADRO: A SUPERVISED DIMENSION REDUCTION METHOD VIA RAYLEIGH QUOTIENT OPTIMIZATION.

Science.gov (United States)

Fan, Jianqing; Ke, Zheng Tracy; Liu, Han; Xia, Lucy

We propose a novel Rayleigh quotient based sparse quadratic dimension reduction method-named QUADRO (Quadratic Dimension Reduction via Rayleigh Optimization)-for analyzing high-dimensional data. Unlike in the linear setting where Rayleigh quotient optimization coincides with classification, these two problems are very different under nonlinear settings. In this paper, we clarify this difference and show that Rayleigh quotient optimization may be of independent scientific interests. One major challenge of Rayleigh quotient optimization is that the variance of quadratic statistics involves all fourth cross-moments of predictors, which are infeasible to compute for high-dimensional applications and may accumulate too many stochastic errors. This issue is resolved by considering a family of elliptical models. Moreover, for heavy-tail distributions, robust estimates of mean vectors and covariance matrices are employed to guarantee uniform convergence in estimating non-polynomially many parameters, even though only the fourth moments are assumed. Methodologically, QUADRO is based on elliptical models which allow us to formulate the Rayleigh quotient maximization as a convex optimization problem. Computationally, we propose an efficient linearized augmented Lagrangian method to solve the constrained optimization problem. Theoretically, we provide explicit rates of convergence in terms of Rayleigh quotient under both Gaussian and general elliptical models. Thorough numerical results on both synthetic and real datasets are also provided to back up our theoretical results.

3D gauged supergravity from SU(2) reduction of $N=1$ 6D supergravity

CERN Document Server

Gava, Edi; Narain, K S

2010-01-01

We obtain Yang-Mills $SU(2)\\times G$ gauged supergravity in three dimensions from $SU(2)$ group manifold reduction of (1,0) six dimensional supergravity coupled to an anti-symmetric tensor multiplet and gauge vector multiplets in the adjoint of $G$. The reduced theory is consistently truncated to $N=4$ 3D supergravity coupled to $4(1+\\textrm{dim}\\, G)$ bosonic and $4(1+\\textrm{dim}\\, G)$ fermionic propagating degrees of freedom. This is in contrast to the reduction in which there are also massive vector fields. The scalar manifold is $\\mathbf{R}\\times \\frac{SO(3,\\, \\textrm{dim}\\, G)}{SO(3)\\times SO(\\textrm{dim}\\, G)}$, and there is a $SU(2)\\times G$ gauge group. We then construct $N=4$ Chern-Simons $(SO(3)\\ltimes \\mathbf{R}^3)\\times (G\\ltimes \\mathbf{R}^{\\textrm{dim}G})$ three dimensional gauged supergravity with scalar manifold $\\frac{SO(4,\\,1+\\textrm{dim}G)}{SO(4)\\times SO(1+\\textrm{dim}G)}$ and explicitly show that this theory is on-shell equivalent to the Yang-Mills $SO(3)\\times G$ gauged supergravity the...

Quantization of coset space σ-models coupled to two-dimensional gravity

International Nuclear Information System (INIS)

Korotkin, D.; Samtleben, H.

1996-07-01

The mathematical framework for an exact quantization of the two-dimensional coset space σ-models coupled to dilaton gravity, that arise from dimensional reduction of gravity and supergravity theories, is presented. The two-time Hamiltonian formulation is obtained, which describes the complete phase space of the model in the whole isomonodromic sector. The Dirac brackets arising from the coset constraints are calculated. Their quantization allows to relate exact solutions of the corresponding Wheeler-DeWitt equations to solutions of a modified (Coset) Knizhnik-Zamolodchikov system. On the classical level, a set of observables is identified, that is complete for essential sectors of the theory. Quantum counterparts of these observables and their algebraic structure are investigated. Their status in alternative quantization procedures is discussed, employing the link with Hamiltonian Chern-Simons theory. (orig.)

Simulation of multivariate stationary stochastic processes using dimension-reduction representation methods

Science.gov (United States)

Liu, Zhangjun; Liu, Zenghui; Peng, Yongbo

2018-03-01

In view of the Fourier-Stieltjes integral formula of multivariate stationary stochastic processes, a unified formulation accommodating spectral representation method (SRM) and proper orthogonal decomposition (POD) is deduced. By introducing random functions as constraints correlating the orthogonal random variables involved in the unified formulation, the dimension-reduction spectral representation method (DR-SRM) and the dimension-reduction proper orthogonal decomposition (DR-POD) are addressed. The proposed schemes are capable of representing the multivariate stationary stochastic process with a few elementary random variables, bypassing the challenges of high-dimensional random variables inherent in the conventional Monte Carlo methods. In order to accelerate the numerical simulation, the technique of Fast Fourier Transform (FFT) is integrated with the proposed schemes. For illustrative purposes, the simulation of horizontal wind velocity field along the deck of a large-span bridge is proceeded using the proposed methods containing 2 and 3 elementary random variables. Numerical simulation reveals the usefulness of the dimension-reduction representation methods.

Spherical and planar three-dimensional anti-de Sitter black holes

International Nuclear Information System (INIS)

Zanchin, Vilson T; Miranda, Alex S

2004-01-01

The technique of dimensional reduction was used in a recent paper (Zanchin V T, Kleber A and Lemos J P S 2002 Phys. Rev. D 66 064022) where a three-dimensional (3D) Einstein-Maxwell-dilaton theory was built from the usual four-dimensional (4D) Einstein-Maxwell-Hilbert action for general relativity. Starting from a class of 4D toroidal black holes in asymptotically anti-de Sitter (AdS) spacetimes several 3D black holes were obtained and studied in such a context. In the present work we choose a particular case of the 3D action which presents Maxwell field, dilaton field and an extra scalar field, besides gravity field and a negative cosmological constant, and obtain new 3D static black hole solutions whose horizons may have spherical or planar topology. We show that there is a 3D static spherically symmetric solution analogous to the 4D Reissner-Nordstroem-AdS black hole, and obtain other new 3D black holes with planar topology. From the static spherical solutions, new rotating 3D black holes are also obtained and analysed in some detail

Dimensional BCS-BEC crossover in ultracold Fermi gases

Energy Technology Data Exchange (ETDEWEB)

Boettcher, Igor

2014-12-10

We investigate thermodynamics and phase structure of ultracold Fermi gases, which can be realized and measured in the laboratory with modern trapping techniques. We approach the subject from a both theoretical and experimental perspective. Central to the analysis is the systematic comparison of the BCS-BEC crossover of two-component fermions in both three and two dimensions. A dimensional reduction can be achieved in experiments by means of highly anisotropic traps. The Functional Renormalization Group (FRG) allows for a description of both cases in a unified theoretical framework. In three dimensions we discuss with the FRG the influence of high momentum particles onto the density, extend previous approaches to the Unitary Fermi Gas to reach quantitative precision, and study the breakdown of superfluidity due to an asymmetry in the population of the two fermion components. In this context we also investigate the stability of the Sarma phase. For the two-dimensional system scattering theory in reduced dimension plays an important role. We present both the theoretically as well as experimentally relevant aspects thereof. After a qualitative analysis of the phase diagram and the equation of state in two dimensions with the FRG we describe the experimental determination of the phase diagram of the two-dimensional BCS-BEC crossover in collaboration with the group of S. Jochim at PI Heidelberg.

Numerical simulation of aerodynamic sound radiated from a two-dimensional airfoil

OpenAIRE

飯田, 明由; 大田黒, 俊夫; 加藤, 千幸; Akiyoshi, Iida; Toshio, Otaguro; Chisachi, Kato; 日立機研; 日立機研; 東大生研; Mechanical Engineering Research Laboratory, Hitachi Ltd.; Mechanical Engineering Research Laboratory, Hitachi Ltd.; University of Tokyo

2000-01-01

An aerodynamic sound radiated from a two-dimensional airfoil has been computed with the Lighthill-Curle's theory. The predicted sound pressure level is agreement with the measured one. Distribution of vortex sound sources is also estimated based on the correlation between the unsteady vorticity fluctuations and the aerodynamic sound. The distribution of vortex sound source reveals that separated shear layers generate aerodynamic sound. This result is help to understand noise reduction method....

Multi-dimensional instability of electrostatic solitary structures in magnetized nonthermal dusty plasmas

International Nuclear Information System (INIS)

Mamun, A.A.; Russel, S.M.; Mendoza-Briceno, C.A.; Alam, M.N.; Datta, T.K.; Das, A.K.

1999-05-01

A rigorous theoretical investigation has been made of multi-dimensional instability of obliquely propagating electrostatic solitary structures in a hot magnetized nonthermal dusty plasma which consists of a negatively charged hot dust fluid, Boltzmann distributed electrons, and nonthermally distributed ions. The Zakharov-Kuznetsov equation for the electrostatic solitary structures that exist in such a dusty plasma system is derived by the reductive perturbation method. The multi-dimensional instability of these solitary waves is also studied by the small-k (long wavelength plane wave) perturbation expansion method. The nature of these solitary structures, the instability criterion, and their growth rate depending on dust-temperature, external magnetic field, and obliqueness are discussed. The implications of these results to some space and astrophysical dusty plasma situations are briefly mentioned. (author)

Two-dimensional collective electron magnetotransport, oscillations, and chaos in a semiconductor superlattice.

Science.gov (United States)

Bonilla, L L; Carretero, M; Segura, A

2017-12-01

When quantized, traces of classically chaotic single-particle systems include eigenvalue statistics and scars in eigenfuntions. Since 2001, many theoretical and experimental works have argued that classically chaotic single-electron dynamics influences and controls collective electron transport. For transport in semiconductor superlattices under tilted magnetic and electric fields, these theories rely on a reduction to a one-dimensional self-consistent drift model. A two-dimensional theory based on self-consistent Boltzmann transport does not support that single-electron chaos influences collective transport. This theory agrees with existing experimental evidence of current self-oscillations, predicts spontaneous collective chaos via a period doubling scenario, and could be tested unambiguously by measuring the electric potential inside the superlattice under a tilted magnetic field.

Two-dimensional collective electron magnetotransport, oscillations, and chaos in a semiconductor superlattice

Science.gov (United States)

Bonilla, L. L.; Carretero, M.; Segura, A.

2017-12-01

When quantized, traces of classically chaotic single-particle systems include eigenvalue statistics and scars in eigenfuntions. Since 2001, many theoretical and experimental works have argued that classically chaotic single-electron dynamics influences and controls collective electron transport. For transport in semiconductor superlattices under tilted magnetic and electric fields, these theories rely on a reduction to a one-dimensional self-consistent drift model. A two-dimensional theory based on self-consistent Boltzmann transport does not support that single-electron chaos influences collective transport. This theory agrees with existing experimental evidence of current self-oscillations, predicts spontaneous collective chaos via a period doubling scenario, and could be tested unambiguously by measuring the electric potential inside the superlattice under a tilted magnetic field.

Three-dimensional display by computer graphics method of hepatocellular carcinoma using seen with the hepatic arteriogram

International Nuclear Information System (INIS)

Itsubo, Mariko; Kameda, Haruo; Suzuki, Naoki; Okamura, Tetsuo

1989-01-01

The method of three-dimensional display of hepatocellular carcinoma using conventional hepatic arteriogram by computer graphics method was newly exploited and applied in clinical use. Three-dimensional models were reconstructed from contour lines of tumors demonstrated as hypervascular lesions by hepatic arteriography. Although objects were limited by angiographic images in which tumors need to be demonstrated as nodules with hypervascularity, this method of three-dimensional display was not worse on accuracy than that using computed tomographic images. According to this method property of the tumor expressed by vascularity was demonstrated clear and in addition volume of the tumor was calculated easily. When the tumor arose in necrotic changes in which demonstrated as a vascular lesion by hepatic arteriography with reduction of size in usual by conservative treatment such as transcathter arterial embolization therapy, this three-dimensional display was able to demonstrate such changes clear. This preliminary study demonstrates the feasibility and clinical usefulness of three-dimensional display of hepatocellular carcinoma using hepatic arteriogram by computer graphics method. (author)

Three dimensional illustrating - three-dimensional vision and deception of sensibility

Directory of Open Access Journals (Sweden)

Anita Gánóczy

2009-03-01

Full Text Available The wide-spread digital photography and computer use gave the opportunity for everyone to make three-dimensional pictures and to make them public. The new opportunities with three-dimensional techniques give chance for the birth of new artistic photographs. We present in detail the biological roots of three-dimensional visualization, the phenomena of movement parallax, which can be used efficiently in making three-dimensional graphics, the Zöllner- and Corridor-illusion. There are present in this paper the visual elements, which contribute to define a plane two-dimensional image in three-dimension: coherent lines, the covering, the measurement changes, the relative altitude state, the abatement of detail profusion, the shadings and the perspective effects of colors.

A Three-Dimensional Statistical Average Skull: Application of Biometric Morphing in Generating Missing Anatomy.

Science.gov (United States)

Teshima, Tara Lynn; Patel, Vaibhav; Mainprize, James G; Edwards, Glenn; Antonyshyn, Oleh M

2015-07-01

The utilization of three-dimensional modeling technology in craniomaxillofacial surgery has grown exponentially during the last decade. Future development, however, is hindered by the lack of a normative three-dimensional anatomic dataset and a statistical mean three-dimensional virtual model. The purpose of this study is to develop and validate a protocol to generate a statistical three-dimensional virtual model based on a normative dataset of adult skulls. Two hundred adult skull CT images were reviewed. The average three-dimensional skull was computed by processing each CT image in the series using thin-plate spline geometric morphometric protocol. Our statistical average three-dimensional skull was validated by reconstructing patient-specific topography in cranial defects. The experiment was repeated 4 times. In each case, computer-generated cranioplasties were compared directly to the original intact skull. The errors describing the difference between the prediction and the original were calculated. A normative database of 33 adult human skulls was collected. Using 21 anthropometric landmark points, a protocol for three-dimensional skull landmarking and data reduction was developed and a statistical average three-dimensional skull was generated. Our results show the root mean square error (RMSE) for restoration of a known defect using the native best match skull, our statistical average skull, and worst match skull was 0.58, 0.74, and 4.4  mm, respectively. The ability to statistically average craniofacial surface topography will be a valuable instrument for deriving missing anatomy in complex craniofacial defects and deficiencies as well as in evaluating morphologic results of surgery.

The Effect of Thickness and Chemical Reduction of Graphene Oxide on Nanoscale Friction.

Science.gov (United States)

Kwon, Sangku; Lee, Kyung Eun; Lee, Hyunsoo; Koh, Sang Joon; Ko, Jae-Hyeon; Kim, Yong-Hyun; Kim, Sang Ouk; Park, Jeong Young

2018-01-18

The tribological properties of two-dimensional (2D) atomic layers are quite different from three-dimensional continuum materials because of the unique mechanical responses of 2D layers. It is known that friction on graphene shows a remarkable decreasing behavior as the number of layers increases, which is caused by the puckering effect. On other graphene derivatives, such as graphene oxide (GO) or reduced graphene oxide (rGO), the thickness dependence of friction is important because of the possibilities for technical applications. In this report, we demonstrate unexpected layer-dependent friction behavior on GO and rGO layers. Friction force microscopy measurements show that nanoscale friction on GO does not depend on the number of layers; however, after reduction, friction on rGO shows an inverse thickness dependence compared with pristine graphene. We show that the friction on rGO is higher than that on SiO 2 at low load, and that an interesting crossover behavior at higher load occurs because of the lower friction coefficient and higher adhesion of the rGO. We provide a relevant interpretation that explains the effect of thickness and chemical reduction on nanoscale friction.

Ecosystem Approach To Flood Disaster Risk Reduction

Directory of Open Access Journals (Sweden)

RK Kamble

2013-12-01

Full Text Available India is one of the ten worst disaster prone countries of the world. The country is prone to disasters due to number of factors; both natural and anthropogenic, including adverse geo-climatic conditions, topographical features, environmental degradation, population growth, urbanisation, industrlisation, non-scientific development practices etc. The factors either in original or by accelerating the intensity and frequency of disasters are responsible for heavy toll of human lives and disrupting the life support systems in the country. India has 40 million hectares of the flood-prone area, on an average, flood affect an area of around 7.5 million hectares per year. Knowledge of environmental systems and processes are key factors in the management of disasters, particularly the hydro-metrological ones. Management of flood risk and disaster is a multi-dimensional affair that calls for interdisciplinary approach. Ecosystem based disaster risk reduction builds on ecosystem management principles, strategies and tools in order to maximise ecosystem services for risk reduction. This perspective takes into account the integration of social and ecological systems, placing people at the centre of decision making. The present paper has been attempted to demonstrate how ecosystem-based approach can help in flood disaster risk reduction. International Journal of Environment, Volume-2, Issue-1, Sep-Nov 2013, Pages 70-82 DOI: http://dx.doi.org/10.3126/ije.v2i1.9209

Dimensional cosmological principles

International Nuclear Information System (INIS)

Chi, L.K.

1985-01-01

The dimensional cosmological principles proposed by Wesson require that the density, pressure, and mass of cosmological models be functions of the dimensionless variables which are themselves combinations of the gravitational constant, the speed of light, and the spacetime coordinates. The space coordinate is not the comoving coordinate. In this paper, the dimensional cosmological principle and the dimensional perfect cosmological principle are reformulated by using the comoving coordinate. The dimensional perfect cosmological principle is further modified to allow the possibility that mass creation may occur. Self-similar spacetimes are found to be models obeying the new dimensional cosmological principle

Numerical relativity for D dimensional axially symmetric space-times: Formalism and code tests

International Nuclear Information System (INIS)

Zilhao, Miguel; Herdeiro, Carlos; Witek, Helvi; Nerozzi, Andrea; Sperhake, Ulrich; Cardoso, Vitor; Gualtieri, Leonardo

2010-01-01

The numerical evolution of Einstein's field equations in a generic background has the potential to answer a variety of important questions in physics: from applications to the gauge-gravity duality, to modeling black hole production in TeV gravity scenarios, to analysis of the stability of exact solutions, and to tests of cosmic censorship. In order to investigate these questions, we extend numerical relativity to more general space-times than those investigated hitherto, by developing a framework to study the numerical evolution of D dimensional vacuum space-times with an SO(D-2) isometry group for D≥5, or SO(D-3) for D≥6. Performing a dimensional reduction on a (D-4) sphere, the D dimensional vacuum Einstein equations are rewritten as a 3+1 dimensional system with source terms, and presented in the Baumgarte, Shapiro, Shibata, and Nakamura formulation. This allows the use of existing 3+1 dimensional numerical codes with small adaptations. Brill-Lindquist initial data are constructed in D dimensions and a procedure to match them to our 3+1 dimensional evolution equations is given. We have implemented our framework by adapting the Lean code and perform a variety of simulations of nonspinning black hole space-times. Specifically, we present a modified moving puncture gauge, which facilitates long-term stable simulations in D=5. We further demonstrate the internal consistency of the code by studying convergence and comparing numerical versus analytic results in the case of geodesic slicing for D=5, 6.

Principal Angle Enrichment Analysis (PAEA): Dimensionally Reduced Multivariate Gene Set Enrichment Analysis Tool.

Science.gov (United States)

Clark, Neil R; Szymkiewicz, Maciej; Wang, Zichen; Monteiro, Caroline D; Jones, Matthew R; Ma'ayan, Avi

2015-11-01

Gene set analysis of differential expression, which identifies collectively differentially expressed gene sets, has become an important tool for biology. The power of this approach lies in its reduction of the dimensionality of the statistical problem and its incorporation of biological interpretation by construction. Many approaches to gene set analysis have been proposed, but benchmarking their performance in the setting of real biological data is difficult due to the lack of a gold standard. In a previously published work we proposed a geometrical approach to differential expression which performed highly in benchmarking tests and compared well to the most popular methods of differential gene expression. As reported, this approach has a natural extension to gene set analysis which we call Principal Angle Enrichment Analysis (PAEA). PAEA employs dimensionality reduction and a multivariate approach for gene set enrichment analysis. However, the performance of this method has not been assessed nor its implementation as a web-based tool. Here we describe new benchmarking protocols for gene set analysis methods and find that PAEA performs highly. The PAEA method is implemented as a user-friendly web-based tool, which contains 70 gene set libraries and is freely available to the community.

MR-NTD: Manifold Regularization Nonnegative Tucker Decomposition for Tensor Data Dimension Reduction and Representation.

Science.gov (United States)

Li, Xutao; Ng, Michael K; Cong, Gao; Ye, Yunming; Wu, Qingyao

2017-08-01

With the advancement of data acquisition techniques, tensor (multidimensional data) objects are increasingly accumulated and generated, for example, multichannel electroencephalographies, multiview images, and videos. In these applications, the tensor objects are usually nonnegative, since the physical signals are recorded. As the dimensionality of tensor objects is often very high, a dimension reduction technique becomes an important research topic of tensor data. From the perspective of geometry, high-dimensional objects often reside in a low-dimensional submanifold of the ambient space. In this paper, we propose a new approach to perform the dimension reduction for nonnegative tensor objects. Our idea is to use nonnegative Tucker decomposition (NTD) to obtain a set of core tensors of smaller sizes by finding a common set of projection matrices for tensor objects. To preserve geometric information in tensor data, we employ a manifold regularization term for the core tensors constructed in the Tucker decomposition. An algorithm called manifold regularization NTD (MR-NTD) is developed to solve the common projection matrices and core tensors in an alternating least squares manner. The convergence of the proposed algorithm is shown, and the computational complexity of the proposed method scales linearly with respect to the number of tensor objects and the size of the tensor objects, respectively. These theoretical results show that the proposed algorithm can be efficient. Extensive experimental results have been provided to further demonstrate the effectiveness and efficiency of the proposed MR-NTD algorithm.

Neural Network Machine Learning and Dimension Reduction for Data Visualization

Science.gov (United States)

Liles, Charles A.

2014-01-01

Neural network machine learning in computer science is a continuously developing field of study. Although neural network models have been developed which can accurately predict a numeric value or nominal classification, a general purpose method for constructing neural network architecture has yet to be developed. Computer scientists are often forced to rely on a trial-and-error process of developing and improving accurate neural network models. In many cases, models are constructed from a large number of input parameters. Understanding which input parameters have the greatest impact on the prediction of the model is often difficult to surmise, especially when the number of input variables is very high. This challenge is often labeled the "curse of dimensionality" in scientific fields. However, techniques exist for reducing the dimensionality of problems to just two dimensions. Once a problem's dimensions have been mapped to two dimensions, it can be easily plotted and understood by humans. The ability to visualize a multi-dimensional dataset can provide a means of identifying which input variables have the highest effect on determining a nominal or numeric output. Identifying these variables can provide a better means of training neural network models; models can be more easily and quickly trained using only input variables which appear to affect the outcome variable. The purpose of this project is to explore varying means of training neural networks and to utilize dimensional reduction for visualizing and understanding complex datasets.

Reduction in thermal conductivity of BiSbTe lump

Energy Technology Data Exchange (ETDEWEB)

Ahmad, Kaleem [King Saud University, Sustainable Energy Technologies Center, College of Engineering, PO Box 800, Riyadh (Saudi Arabia); Wan, C. [Tsinghua University, State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Beijing (China); Al-Eshaikh, M.A.; Kadachi, A.N. [King Saud University, Research Center, College of Engineering, PO Box 800, Riyadh (Saudi Arabia)

2017-03-15

In this work, systematic investigations on the thermal conductivities of BiSbTe lump, microstructured pristine BiSbTe bulk and single wall carbon nanotubes (SWCNTs)/BiSbTe bulk nanocomposites were performed. BiSbTe lumps were crushed to form a coarse powder (200 μm) and effect of particle size reduction on the effective thermal conductivity of BiSbTe (200 μm) bulk were analyzed. For further reduction in the conductivity, a two pronged strategy has been employed. First, additional refinement of BiSbTe (200 μm) were performed through ball milling in an inert environment. Second, SWCNTs in 0.75, and 1.0 vol% were distributed uniformly in the fine BiSbTe ball milled powder. The results showed that the effective thermal conductivities decrease with the reduction in the particle size from lump to BiSbTe (200 μm) bulk as well as with the addition of SWCNTs accompanied by further refinement of BiSbTe particles. The significant reduction in thermal conductivities of the lump was achieved for pure BiSbTe (200 μm) bulk and 0.75 vol% of SWCNTs/BiSbTe composite. This can be ascribed to the enhanced phonon scattering by the grain boundaries between the nanostructured BiSbTe particles as well as the interfaces between BiSbTe and the low dimensional carbon nanotubes. (orig.)

Re-establishing filtering capabilities of machined porous beryllium via chemical reduction and cleaning

International Nuclear Information System (INIS)

Randall, W.L.

1975-01-01

Porous beryllium is furnished in sheets of varying sizes and thickness; it is therefore necessary that it be machined into specified sizes. A chemical reduction and cleaning procedure was devised to remove the disrupted surface, open the sealed pores of the material, and clean entrapped contaminates from the internal structure. Dimensional stability can be closely controlled and material size is of no consequence. (U.S.)

Study on design procedure of three-dimensional building base isolation system using thick rubber bearing

International Nuclear Information System (INIS)

Yabana, Shuichi; Matsuda, Akihiro

2003-01-01

In this study, design procedure on three-dimensional base isolation system is developed. Base isolation system proposed by CRIEPI uses thick rubber bearing and damper as isolation device. As for thick rubber bearings, design formula for evaluating vertical stiffness is proposed, and design conditions regarding size and vertical pressure are investigated. Figure-U type lead damper is proposed as three-dimensional damper and by loading tests its mechanical characteristics is evaluated. The concept of multi-layered interconnected rubber bearing, which is advantageous over large scale bearing in manufacturability, is proposed and its good performance is confirmed by the loading test. Through the response analyses, it is shown the rocking response of the proposed three-dimensional base isolation system is very small and not influential to the system, and the reduction of the vertical response is attained using the proposed isolation device. (author)

Dimensional comparison theory.

Science.gov (United States)

Möller, Jens; Marsh, Herb W

2013-07-01

Although social comparison (Festinger, 1954) and temporal comparison (Albert, 1977) theories are well established, dimensional comparison is a largely neglected yet influential process in self-evaluation. Dimensional comparison entails a single individual comparing his or her ability in a (target) domain with his or her ability in a standard domain (e.g., "How good am I in math compared with English?"). This article reviews empirical findings from introspective, path-analytic, and experimental studies on dimensional comparisons, categorized into 3 groups according to whether they address the "why," "with what," or "with what effect" question. As the corresponding research shows, dimensional comparisons are made in everyday life situations. They impact on domain-specific self-evaluations of abilities in both domains: Dimensional comparisons reduce self-concept in the worse off domain and increase self-concept in the better off domain. The motivational basis for dimensional comparisons, their integration with recent social cognitive approaches, and the interdependence of dimensional, temporal, and social comparisons are discussed. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Unified Gauge Theories and Reduction of Couplings: from Finiteness to Fuzzy Extra Dimensions

Directory of Open Access Journals (Sweden)

George Zoupanos

2008-02-01

Full Text Available Finite Unified Theories (FUTs are N = 1 supersymmetric Grand Unified Theories, which can be made all-loop finite, both in the dimensionless (gauge and Yukawa couplings and dimensionful (soft supersymmetry breaking terms sectors. This remarkable property, based on the reduction of couplings at the quantum level, provides a drastic reduction in the number of free parameters, which in turn leads to an accurate prediction of the top quark mass in the dimensionless sector, and predictions for the Higgs boson mass and the supersymmetric spectrum in the dimensionful sector. Here we examine the predictions of two such FUTs. Next we consider gauge theories defined in higher dimensions, where the extra dimensions form a fuzzy space (a finite matrix manifold. We reinterpret these gauge theories as four-dimensional theories with Kaluza-Klein modes. We then perform a generalized à la Forgacs-Manton dimensional reduction. We emphasize some striking features emerging such as (i the appearance of non-Abelian gauge theories in four dimensions starting from an Abelian gauge theory in higher dimensions, (ii the fact that the spontaneous symmetry breaking of the theory takes place entirely in the extra dimensions and (iii the renormalizability of the theory both in higher as well as in four dimensions. Then reversing the above approach we present a renormalizable four dimensional SU(N gauge theory with a suitable multiplet of scalar fields, which via spontaneous symmetry breaking dynamically develops extra dimensions in the form of a fuzzy sphere SN2. We explicitly find the tower of massive Kaluza-Klein modes consistent with an interpretation as gauge theory on M4 × S2, the scalars being interpreted as gauge fields on S2. Depending on the parameters of the model the low-energy gauge group can be SU(n, or broken further to SU(n1 × SU(n2 × U(1. Therefore the second picture justifies the first one in a renormalizable framework but in addition has the potential to

The relationship between leadership behaviour, outcomes of leadership and emotional intelligence

Directory of Open Access Journals (Sweden)

C Coetzee

2005-10-01

Full Text Available The aim of the study was to explore relationship between leadership behaviour, the outcomes of leadership and the emotional intelligence of managers. The “Multifactor Emotional Intelligence Scale�? and the "Multifactor Leadership Questionnaire" were applied to a convenience sample of 100 managers working for various companies in South Africa. The study yielded significant correlations between managers’ level of emotional intelligence, leadership behaviour and the outcomes of leadership. Opsomming Die doel van die studie was om die verband tussen die leierskapsgedrag, uitkoms van leierskap en die emosionele intelligensie van bestuurders te ondersoek. Die “Multifactor Emotional Intelligence Scale�? en die “Multifactor Leadership Questionnaire�? is op ’n gerieflikheidsteekproef van 100 bestuurders wat in verskeie organisasies in Suid-Afrika werksaam is, toegepas. Die resultate dui op ’n beduidende korrelasie tussen die vlak van emosionele intelligensie, leierskapsgedrag en die uitkoms van leierskap van bestuurders.

Numerical analysis of biological clogging in two-dimensional sand box experiments

DEFF Research Database (Denmark)

Kildsgaard, J.; Engesgaard, Peter Knudegaard

2001-01-01

Two-dimensional models for biological clogging and sorptive tracer transport were used to study the progress of clogging in a sand box experiment. The sand box had been inoculated with a strip of bacteria and exposed to a continuous injection of nitrate and acetate. Brilliant Blue was regularly...... injected during the clogging experiment and digital images of the tracer movement had been converted to concentration maps using an image analysis. The calibration of the models to the Brilliant Blue observations shows that Brilliant Blue has a solid biomass dependent sorption that is not compliant...... with the assumed linear constant Kd behaviour. It is demonstrated that the dimensionality of sand box experiments in comparison to column experiments results in a much lower reduction in hydraulic conductivity Žfactor of 100. and that the bulk hydraulic conductivity of the sand box decreased only slightly. However...

Form factors of descendant operators: reduction to perturbed M(2,2s+1) models

International Nuclear Information System (INIS)

Lashkevich, Michael; Pugai, Yaroslav

2015-01-01

In the framework of the algebraic approach to form factors in two-dimensional integrable models of quantum field theory we consider the reduction of the sine-Gordon model to the Φ 13 -perturbation of minimal conformal models of the M(2,2s+1) series. We find in an algebraic form the condition of compatibility of local operators with the reduction. We propose a construction that make it possible to obtain reduction compatible local operators in terms of screening currents. As an application we obtain exact multiparticle form factors for the compatible with the reduction conserved currents T ±2k , Θ ±(2k−2) , which correspond to the spin ±(2k−1) integrals of motion, for any positive integer k. Furthermore, we obtain all form factors of the operators T 2k T −2l , which generalize the famous TT̄ operator. The construction is analytic in the s parameter and, therefore, makes sense in the sine-Gordon theory.

A Comparison of Machine Learning Methods in a High-Dimensional Classification Problem

Directory of Open Access Journals (Sweden)

Zekić-Sušac Marijana

2014-09-01

Full Text Available Background: Large-dimensional data modelling often relies on variable reduction methods in the pre-processing and in the post-processing stage. However, such a reduction usually provides less information and yields a lower accuracy of the model. Objectives: The aim of this paper is to assess the high-dimensional classification problem of recognizing entrepreneurial intentions of students by machine learning methods. Methods/Approach: Four methods were tested: artificial neural networks, CART classification trees, support vector machines, and k-nearest neighbour on the same dataset in order to compare their efficiency in the sense of classification accuracy. The performance of each method was compared on ten subsamples in a 10-fold cross-validation procedure in order to assess computing sensitivity and specificity of each model. Results: The artificial neural network model based on multilayer perceptron yielded a higher classification rate than the models produced by other methods. The pairwise t-test showed a statistical significance between the artificial neural network and the k-nearest neighbour model, while the difference among other methods was not statistically significant. Conclusions: Tested machine learning methods are able to learn fast and achieve high classification accuracy. However, further advancement can be assured by testing a few additional methodological refinements in machine learning methods.

Two-Dimensional N,S-Codoped Carbon/Co ₉ S ₈ Catalysts Derived from Co(OH) ₂ Nanosheets for Oxygen Reduction Reaction

Energy Technology Data Exchange (ETDEWEB)

Fu, Shaofang [School of Mechanical; Zhu, Chengzhou [School of Mechanical; Song, Junhua [School of Mechanical; Feng, Shuo [School of Mechanical; Du, Dan [School of Mechanical; Key Laboratory of Pesticide and Chemical; Engelhard, Mark H. [Environmental Molecular Science Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States; Xiao, Dongdong [Environmental Molecular Science Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States; Li, Dongsheng [Environmental Molecular Science Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States; Lin, Yuehe [School of Mechanical

2017-10-12

Investigation of highly active and cost-efficient electrocatalysts for oxygen reduction reaction is of great importance in a wide range of clean energy devices, including fuel cells and metal-air batteries. Herein, the simultaneous formation of Co9S8 and N,S-codoped carbon was achieved in a dual templates system. First, Co(OH)2 nanosheets and tetraethyl orthosilicate were utilized to direct the formation of two-dimensional carbon precursors, which were then dispersed into thiourea solution. After subsequent pyrolysis and templates removal, N/S-codoped porous carbon sheets confined Co9S8 catalysts (Co9S8/NSC) were obtained. Owing to the morphological and compositional advantages as well as the synergistic effects, the resultant Co9S8/NSC catalysts with modified doping level and pyrolysis degree exhibit superior ORR catalytic activity and long-term stability compared with the state-of-the-art Pt/C catalyst in alkaline media. Remarkably, the as-prepared carbon composites also reveal exceptional tolerance of methanol, indicating their potential applications in fuel cells.

Towards 4-loop NSPT result for a 3-dimensional condensate-contribution to hot QCD pressure

CERN Document Server

Torrero, C.; Schroder, Y.; Di Renzo, F.; Miccio, V.

2007-01-01

Thanks to dimensional reduction, the contributions to the hot QCD pressure coming from so-called soft modes can be studied via an effective three-dimensional theory named Electrostatic QCD (spatial Yang-Mills fields plus an adjoint Higgs scalar). The poor convergence of the perturbative series within EQCD suggests to perform lattice measurements of some of the associated gluon condensates. These turn out, however, to be plagued by large discretization artifacts. We discuss how Numerical Stochastic Perturbation Theory can be exploited to determine the full lattice spacing dependence of one of these condensates up to 4-loop order, and sharpen our tools on a concrete 2-loop example.

Assessment of metal artifact reduction methods in pelvic CT

Energy Technology Data Exchange (ETDEWEB)

Abdoli, Mehrsima [Department of Radiation Oncology, The Netherlands Cancer Institute, Plesmanlaan 121, Amsterdam 1066 CX (Netherlands); Mehranian, Abolfazl [Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva CH-1211 (Switzerland); Ailianou, Angeliki; Becker, Minerva [Division of Radiology, Geneva University Hospital, Geneva CH-1211 (Switzerland); Zaidi, Habib, E-mail: habib.zaidi@hcuge.ch [Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva CH-1211 (Switzerland); Geneva Neuroscience Center, Geneva University, Geneva CH-1205 (Switzerland); Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Hanzeplein 1, Groningen 9700 RB (Netherlands)

2016-04-15

Purpose: Metal artifact reduction (MAR) produces images with improved quality potentially leading to confident and reliable clinical diagnosis and therapy planning. In this work, the authors evaluate the performance of five MAR techniques for the assessment of computed tomography images of patients with hip prostheses. Methods: Five MAR algorithms were evaluated using simulation and clinical studies. The algorithms included one-dimensional linear interpolation (LI) of the corrupted projection bins in the sinogram, two-dimensional interpolation (2D), a normalized metal artifact reduction (NMAR) technique, a metal deletion technique, and a maximum a posteriori completion (MAPC) approach. The algorithms were applied to ten simulated datasets as well as 30 clinical studies of patients with metallic hip implants. Qualitative evaluations were performed by two blinded experienced radiologists who ranked overall artifact severity and pelvic organ recognition for each algorithm by assigning scores from zero to five (zero indicating totally obscured organs with no structures identifiable and five indicating recognition with high confidence). Results: Simulation studies revealed that 2D, NMAR, and MAPC techniques performed almost equally well in all regions. LI falls behind the other approaches in terms of reducing dark streaking artifacts as well as preserving unaffected regions (p < 0.05). Visual assessment of clinical datasets revealed the superiority of NMAR and MAPC in the evaluated pelvic organs and in terms of overall image quality. Conclusions: Overall, all methods, except LI, performed equally well in artifact-free regions. Considering both clinical and simulation studies, 2D, NMAR, and MAPC seem to outperform the other techniques.

Noise Reduction Evaluation of Multi-Layered Viscoelastic Infinite Cylinder under Acoustical Wave Excitation

Directory of Open Access Journals (Sweden)

M.R. Mofakhami

2008-01-01

Full Text Available In this paper sound transmission through the multilayered viscoelastic air filled cylinders subjected to the incident acoustic wave is studied using the technique of separation of variables on the basis of linear three dimensional theory of elasticity. The effect of interior acoustic medium on the mode maps (frequency vs geometry and noise reduction is investigated. The effects of internal absorption and external moving medium on noise reduction are also evaluated. The dynamic viscoelastic properties of the structure are rigorously taken into account with a power law technique that models the viscoelastic damping of the cylinder. A parametric study is also performed for the two layered infinite cylinders to obtain the effect of viscoelastic layer characteristics such as thickness, material type and frequency dependency of viscoelastic properties on the noise reduction. It is shown that using constant and frequency dependent viscoelastic material with high loss factor leads to the uniform noise reduction in the frequency domain. It is also shown that the noise reduction obtained for constant viscoelastic material property is subjected to some errors in the low frequency range with respect to those obtained for the frequency dependent viscoelastic material.

Loop groups, Kaluza-Klein reduction and M-theory

International Nuclear Information System (INIS)

Bergman, Aaron; Varadarajan, Uday

2005-01-01

We show that the data of a principal G-bundle over a principal circle bundle is equivalent to that of a LG-circumflex (def)/= U(1) x LG-bundle over the base of the circle bundle. We apply this to the Kaluza-Klein reduction of M-theory to IIA and show that certain generalized characteristic classes of the loop group bundle encode the Bianchi identities of the antisymmetric tensor fields of IIA supergravity. We further show that the low dimensional characteristic classes of the central extension of the loop group encode the Bianchi identities of massive IIA, thereby adding support to the conjectures given elsewhere

Observation of Zero-Dimensional States in a One-Dimensional Electron Interferometer

NARCIS (Netherlands)

Wees, B.J. van; Kouwenhoven, L.P.; Harmans, C.J.P.M.; Williamson, J.G.; Timmering, C.E.; Broekaart, M.E.I.; Foxon, C.T.; Harris, J.J.

1989-01-01

We have studied the electron transport in a one-dimensional electron interferometer. It consists of a disk-shaped two-dimensional electron gas, to which quantum point contacts are attached. Discrete zero-dimensional states are formed due to constructive interference of electron waves traveling along

Lower dimensional gravity

International Nuclear Information System (INIS)

Brown, J.D.

1988-01-01

This book addresses the subject of gravity theories in two and three spacetime dimensions. The prevailing philosophy is that lower dimensional models of gravity provide a useful arena for developing new ideas and insights, which are applicable to four dimensional gravity. The first chapter consists of a comprehensive introduction to both two and three dimensional gravity, including a discussion of their basic structures. In the second chapter, the asymptotic structure of three dimensional Einstein gravity with a negative cosmological constant is analyzed. The third chapter contains a treatment of the effects of matter sources in classical two dimensional gravity. The fourth chapter gives a complete analysis of particle pair creation by electric and gravitational fields in two dimensions, and the resulting effect on the cosmological constant

Minimal Representations and Reductive Dual Pairs in Conformal Field Theory

International Nuclear Information System (INIS)

Todorov, Ivan

2010-01-01

A minimal representation of a simple non-compact Lie group is obtained by 'quantizing' the minimal nilpotent coadjoint orbit of its Lie algebra. It provides context for Roger Howe's notion of a reductive dual pair encountered recently in the description of global gauge symmetry of a (4-dimensional) conformal observable algebra. We give a pedagogical introduction to these notions and point out that physicists have been using both minimal representations and dual pairs without naming them and hence stand a chance to understand their theory and to profit from it.

Manifold learning to interpret JET high-dimensional operational space

International Nuclear Information System (INIS)

Cannas, B; Fanni, A; Pau, A; Sias, G; Murari, A

2013-01-01

In this paper, the problem of visualization and exploration of JET high-dimensional operational space is considered. The data come from plasma discharges selected from JET campaigns from C15 (year 2005) up to C27 (year 2009). The aim is to learn the possible manifold structure embedded in the data and to create some representations of the plasma parameters on low-dimensional maps, which are understandable and which preserve the essential properties owned by the original data. A crucial issue for the design of such mappings is the quality of the dataset. This paper reports the details of the criteria used to properly select suitable signals downloaded from JET databases in order to obtain a dataset of reliable observations. Moreover, a statistical analysis is performed to recognize the presence of outliers. Finally data reduction, based on clustering methods, is performed to select a limited and representative number of samples for the operational space mapping. The high-dimensional operational space of JET is mapped using a widely used manifold learning method, the self-organizing maps. The results are compared with other data visualization methods. The obtained maps can be used to identify characteristic regions of the plasma scenario, allowing to discriminate between regions with high risk of disruption and those with low risk of disruption. (paper)

Variational group-PCA for intrinsic dimensionality determination in fMRI data

DEFF Research Database (Denmark)

Hinrich, Jesper Løve; Nielsen, Søren Føns Vind; Madsen, Kristoffer Hougaard

2016-01-01

. Furthermore, in an fMRI-context it is not fully understood how information from multiple subjects should best be incorporated when applying dimensionality reduction. We propose a Bayesian group principal component analysis (Group-BPCA) model with an automatic relevance determination (ARD) prior to determine...... on the spatial maps are shared, leads to pruning components, but provide better generalization in two of three scenarios. We show that the right level of subject variability is highly dependent on the chosen validation scheme....

Whitham modulation theory for the two-dimensional Benjamin-Ono equation.

Science.gov (United States)

Ablowitz, Mark; Biondini, Gino; Wang, Qiao

2017-09-01

Whitham modulation theory for the two-dimensional Benjamin-Ono (2DBO) equation is presented. A system of five quasilinear first-order partial differential equations is derived. The system describes modulations of the traveling wave solutions of the 2DBO equation. These equations are transformed to a singularity-free hydrodynamic-like system referred to here as the 2DBO-Whitham system. Exact reductions of this system are discussed, the formulation of initial value problems is considered, and the system is used to study the transverse stability of traveling wave solutions of the 2DBO equation.

A comparison of linear and nonlinear statistical techniques in performance attribution.

Science.gov (United States)

Chan, N H; Genovese, C R

2001-01-01

Performance attribution is usually conducted under the linear framework of multifactor models. Although commonly used by practitioners in finance, linear multifactor models are known to be less than satisfactory in many situations. After a brief survey of nonlinear methods, nonlinear statistical techniques are applied to performance attribution of a portfolio constructed from a fixed universe of stocks using factors derived from some commonly used cross sectional linear multifactor models. By rebalancing this portfolio monthly, the cumulative returns for procedures based on standard linear multifactor model and three nonlinear techniques-model selection, additive models, and neural networks-are calculated and compared. It is found that the first two nonlinear techniques, especially in combination, outperform the standard linear model. The results in the neural-network case are inconclusive because of the great variety of possible models. Although these methods are more complicated and may require some tuning, toolboxes are developed and suggestions on calibration are proposed. This paper demonstrates the usefulness of modern nonlinear statistical techniques in performance attribution.

Combined untargeted and targeted fingerprinting by comprehensive two-dimensional gas chromatography: revealing fructose-induced changes in mice urinary metabolic signatures.

Science.gov (United States)

Bressanello, Davide; Liberto, Erica; Collino, Massimo; Chiazza, Fausto; Mastrocola, Raffaella; Reichenbach, Stephen E; Bicchi, Carlo; Cordero, Chiara

2018-04-01

This study exploits the information potential of comprehensive two-dimensional gas chromatography configured with a parallel dual secondary column-dual detection by mass spectrometry and flame ionization (GC×2GC-MS/FID) to study changes in urinary metabolic signatures of mice subjected to high-fructose diets. Samples are taken from mice fed with normal or fructose-enriched diets provided either in aqueous solution or in solid form and analyzed at three stages of the dietary intervention (1, 6, and 12 weeks). Automated Untargeted and Targeted fingerprinting for 2D data elaboration is adopted for the most inclusive data mining of GC×GC patterns. The UT fingerprinting strategy performs a fully automated peak-region features fingerprinting and combines results from pre-targeted compounds and unknowns across the sample-set. The most informative metabolites, with statistically relevant differences between sample groups, are obtained by unsupervised multivariate analysis (MVA) and cross-validated by multi-factor analysis (MFA) with external standard quantitation by GC-MS. Results indicate coherent clustering of mice urine signatures according to dietary manipulation. Notably, the metabolite fingerprints of mice fed with liquid fructose exhibited greater derangement in fructose, glucose, citric, pyruvic, malic, malonic, gluconic, cis-aconitic, succinic and 2-keto glutaric acids, glycine acyl derivatives (N-carboxy glycine, N-butyrylglycine, N-isovaleroylglycine, N-phenylacetylglycine), and hippuric acid. Untargeted fingerprinting indicates some analytes which were not a priori pre-targeted which provide additional insights: N-acetyl glucosamine, N-acetyl glutamine, malonyl glycine, methyl malonyl glycine, and glutaric acid. Visual features fingerprinting is used to track individual variations during experiments, thereby extending the panorama of possible data elaboration tools. Graphical abstract ᅟ.

South African Universities and Human Development: Towards a Theorisation and Operationalisation of Professional Capabilities for Poverty Reduction

Science.gov (United States)

Walker, Melanie; McLean, Monica; Dison, Arona; Peppin-Vaughan, Rosie

2009-01-01

This paper reports on a research project investigating the role of universities in South Africa in contributing to poverty reduction through the quality of their professional education programmes. The focus here is on theorising and the early operationalisation of multi-layered, multi-dimensional transformation based on ideas from Amartya Sen's…

Two-dimensional errors

International Nuclear Information System (INIS)

Anon.

1991-01-01

This chapter addresses the extension of previous work in one-dimensional (linear) error theory to two-dimensional error analysis. The topics of the chapter include the definition of two-dimensional error, the probability ellipse, the probability circle, elliptical (circular) error evaluation, the application to position accuracy, and the use of control systems (points) in measurements

One-dimensional reduction of the three-dimenstional Gross-Pitaevskii equation with two- and three-body interactions

International Nuclear Information System (INIS)

Cardoso, W. B.; Avelar, A. T.; Bazeia, D.

2011-01-01

We deal with the three-dimensional Gross-Pitaevskii equation which is used to describe a cloud of dilute bosonic atoms that interact under competing two- and three-body scattering potentials. We study the case where the cloud of atoms is strongly confined in two spatial dimensions, allowing us to build an unidimensional nonlinear equation,controlled by the nonlinearities and the confining potentials that trap the system along the longitudinal coordinate. We focus attention on specific limits dictated by the cubic and quintic coefficients, and we implement numerical simulations to help us to quantify the validity of the procedure.

Error reduction techniques for Monte Carlo neutron transport calculations

International Nuclear Information System (INIS)

Ju, J.H.W.

1981-01-01

Monte Carlo methods have been widely applied to problems in nuclear physics, mathematical reliability, communication theory, and other areas. The work in this thesis is developed mainly with neutron transport applications in mind. For nuclear reactor and many other applications, random walk processes have been used to estimate multi-dimensional integrals and obtain information about the solution of integral equations. When the analysis is statistically based such calculations are often costly, and the development of efficient estimation techniques plays a critical role in these applications. All of the error reduction techniques developed in this work are applied to model problems. It is found that the nearly optimal parameters selected by the analytic method for use with GWAN estimator are nearly identical to parameters selected by the multistage method. Modified path length estimation (based on the path length importance measure) leads to excellent error reduction in all model problems examined. Finally, it should be pointed out that techniques used for neutron transport problems may be transferred easily to other application areas which are based on random walk processes. The transport problems studied in this dissertation provide exceptionally severe tests of the error reduction potential of any sampling procedure. It is therefore expected that the methods of this dissertation will prove useful in many other application areas

Perturbed Partial Cavity Drag Reduction at High Reynolds Numbers

Science.gov (United States)

Makiharju, Simo; Elbing, Brian; Wiggins, Andrew; Dowling, David; Perlin, Marc; Ceccio, Steven

2010-11-01

Ventilated partial cavities were investigated at Reynolds numbers to 80 million. These cavities could be suitable for friction drag reduction on ocean going vessels and thereby lead to environmental and economical benefits. The test model was a 3.05 m wide by 12.9 m long flat plate, with a 0.18 m backward-facing step and a cavity-terminating beach, which had an adjustable slope, tilt and height. The step and beach trapped a ventilated partial cavity over the longitudinal mid-section of the model. Large-scale flow perturbations, mimicking the effect of ambient ocean waves were investigated. For the conditions tested a cavity could be maintained under perturbed flow conditions when the gas flux supplied was greater than the minimum required to maintain a cavity under steady conditions, with larger perturbations requiring more excess gas flux to maintain the cavity. High-speed video was used to observe the unsteady three dimensional cavity closure, the overall cavity shape, and the cavity oscillations. Cavities with friction drag reduction exceeding 95% were attained at optimal conditions. A simplified energy cost-benefit analysis of partial cavity drag reduction was also performed. The results suggest that PCDR could potentially lead to energy savings.

Highly active Pd-In/mesoporous alumina catalyst for nitrate reduction.

Science.gov (United States)

Gao, Zhenwei; Zhang, Yonggang; Li, Deyi; Werth, Charles J; Zhang, Yalei; Zhou, Xuefei

2015-04-09

The catalytic reduction of nitrate is a promising technology for groundwater purification because it transforms nitrate into nitrogen and water. Recent studies have mainly focused on new catalysts with higher activities for the reduction of nitrate. Consequently, metal nanoparticles supported on mesoporous metal oxides have become a major research direction. However, the complex surface chemistry and porous structures of mesoporous metal oxides lead to a non-uniform distribution of metal nanoparticles, thereby resulting in a low catalytic efficiency. In this paper, a method for synthesizing the sustainable nitrate reduction catalyst Pd-In/Al2O3 with a dimensional structure is introduced. The TEM results indicated that Pd and In nanoparticles could efficiently disperse into the mesopores of the alumina. At room temperature in CO2-buffered water and under continuous H2 as the electron donor, the synthesized material (4.9 wt% Pd) was the most active at a Pd-In ratio of 4, with a first-order rate constant (k(obs) = 0.241 L min(-1) g(cata)(-1)) that was 1.3× higher than that of conventional Pd-In/Al2O3 (5 wt% Pd; 0.19 L min(-1) g(cata)(-1)). The Pd-In/mesoporous alumina is a promising catalyst for improving the catalytic reduction of nitrate. Copyright © 2015 Elsevier B.V. All rights reserved.

Giant Andreev Backscattering through a Quantum Point Contact Coupled via a Disordered Two-Dimensional Electron Gas to Superconductors

International Nuclear Information System (INIS)

den Hartog, S.G.; van Wees, B.J.; Klapwijk, T.M.; Nazarov, Y.V.; Borghs, G.

1997-01-01

We have investigated the superconducting-phase-modulated reduction in the resistance of a ballistic quantum point contact (QPC) connected via a disordered two-dimensional electron gas (2DEG) to superconductors. We show that this reduction is caused by coherent Andreev backscattering of holes through the QPC, which increases monotonically by reducing the bias voltage to zero. In contrast, the magnitude of the phase-dependent resistance of the disordered 2DEG displays a nonmonotonic reentrant behavior versus bias voltage. copyright 1997 The American Physical Society

Drag reduction effects facilitated by microridges inside the mouthparts of honeybee workers and drones.

Science.gov (United States)

Li, Chu-Chu; Wu, Jia-Ning; Yang, Yun-Qiang; Zhu, Ren-Gao; Yan, Shao-Ze

2016-01-21

The mouthpart of a honeybee is a natural well-designed micropump that uses a reciprocating glossa through a temporary tube comprising a pair of galeae and labial palpi for loading nectar. The shapes and sizes of mouthparts differ among castes of honeybees, but the diversities of the functional microstructures inside the mouthparts of honeybee workers and drones remain poorly understood. Through scanning electron microscopy, we found the dimensional difference of uniformly distributed microridges on the inner galeae walls of Apis mellifera ligustica workers and drones. Subsequently, we recorded the feeding process of live honeybees by using a specially designed high-speed camera system. Considering the microridges and kinematics of the glossa, we constructed a hydrodynamic model to calculate the friction coefficient of the mouthpart. In addition, we test the drag reduction through the dimensional variations of the microridges on the inner walls of mouthparts. Theoretical estimations of the friction coefficient with respect to dipping frequency show that inner microridges can reduce friction during the feeding process of honeybees. The effects of drag reduction regulated by specific microridges were then compared. The friction coefficients of the workers and drones were found to be 0.011±0.007 (mean±s.d.) and 0.045±0.010, respectively. These results indicate that the mouthparts of workers are more capable of drag reduction compared with those of drones. The difference was analyzed by comparing the foraging behavior of the workers and drones. Workers are equipped with well-developed hypopharyngeal, and their dipping frequency is higher than that of drones. Our research establishes a critical link between microridge dimensions and drag reduction capability during the nectar feeding of honeybees. Our results reveal that microridges inside the mouthparts of honeybee workers and drones reflect the caste-related life cycles of honeybees. Copyright © 2015 Elsevier Ltd

Gauge theory for finite-dimensional dynamical systems

International Nuclear Information System (INIS)

Gurfil, Pini

2007-01-01

Gauge theory is a well-established concept in quantum physics, electrodynamics, and cosmology. This concept has recently proliferated into new areas, such as mechanics and astrodynamics. In this paper, we discuss a few applications of gauge theory in finite-dimensional dynamical systems. We focus on the concept of rescriptive gauge symmetry, which is, in essence, rescaling of an independent variable. We show that a simple gauge transformation of multiple harmonic oscillators driven by chaotic processes can render an apparently ''disordered'' flow into a regular dynamical process, and that there exists a strong connection between gauge transformations and reduction theory of ordinary differential equations. Throughout the discussion, we demonstrate the main ideas by considering examples from diverse fields, including quantum mechanics, chemistry, rigid-body dynamics, and information theory

Synthesis of molecular hexatechnetium clusters by means of dimensional reduction of their polymeric complexes

International Nuclear Information System (INIS)

Ikai, T.; Yoshimura, T.; Shinohara, A.; Takayama, T.; Sekine, T.

2006-01-01

Selenide capping hexatechnetium cluster complex [Tc 6 (μ 3 -Se) 8 CN 6 ] 4- (1) was prepared by the reactions of one-dimensional polymer complex [Tc 6 (μ 3 -Se) 8 Br 4 ] 2- and cyanides at high temperature. Similar reaction of sulfide capping hexatechnetium cluster complex, [Tc 6 (μ 3 -S) 8 Br 6 ] 4- with cyanide gave the terminal substituted complex [Tc 6 (μ 3 -S) 8 CN 6 ] 4- (2). The single-crystal X-ray analysis of 1 and 2, showed that the Tc-Tc bond lengths become longer with lager ionic radius of the face capping ligands in the order S -1 , and that of 2 showed it at 2119 cm -1 . Each of cyclic voltammogram of 1 and 2 showed a reversible one electron redox wave assignable to the Tc 6 III /Tc 5 III Tc IV process. These redox potentials shift to the positive about 0.4V compared to those of the Re cluster analogs. (author)

From zinc selenate to zinc selenide nano structures synthesized by reduction process

International Nuclear Information System (INIS)

Hutagalung, S.D.; Eng, S.T.; Ahmad, Z.A.; Ishak Mat; Yussof Wahab

2009-01-01

One-dimensional nano structure materials are very attractive because of their electronic and optical properties depending on their size. It is well known that properties of material can be tuned by reducing size to nano scale because at the small sizes, that they behave differently with its bulk materials and the band gap will control by the size. The tunability of the band gap makes nano structured materials useful for many applications. As one of the wide band gaps semiconductor compounds, zinc selenide (ZnSe) nano structures (nanoparticles, nano wires, nano rods) have received much attention for the application in optoelectronic devices, such as blue laser diode, light emitting diodes, solar cells and IR optical windows. In this study, ZnSe nano structures have been synthesized by reduction process of zinc selenate using hydrazine hydrate (N 2 H 4 .2H 2 O). The reductive agent of hydrazine hydrate was added to the starting materials of zinc selenate were heat treated at 500 degree Celsius for 1 hour under argon flow to form one-dimensional nano structures. The SEM and TEM images show the formation of nano composite-like structure, which some small nano bar and nano pellets stick to the rod. The x-ray diffraction and elemental composition analysis confirm the formation of mixture zinc oxide and zinc selenide phases. (author)

Three-dimensional scapular dyskinesis in hook-plated acromioclavicular dislocation including hook motion.

Science.gov (United States)

Kim, Eugene; Lee, Seunghee; Jeong, Hwa-Jae; Park, Jai Hyung; Park, Se-Jin; Lee, Jaewook; Kim, Woosub; Park, Hee Jin; Lee, So Yeon; Murase, Tsuyoshi; Sugamoto, Kazuomi; Ikemoto, Sumika

2018-06-01

The purpose of this study is to analyze the 3-dimensional scapular dyskinesis and the kinematics of a hook plate relative to the acromion after hook-plated acromioclavicular dislocation in vivo. Reported complications of acromioclavicular reduction using a hook plate include subacromial erosion and impingement. However, there are few reports of the 3-dimensional kinematics of the hook and scapula after the aforementioned surgical procedure. We studied 15 cases of acromioclavicular dislocation treated with a hook plate and 15 contralateral normal shoulders using computed tomography in the neutral and full forward flexion positions. Three-dimensional motion of the scapula relative to the thorax during arm elevation was analyzed using a computer simulation program. We also measured the distance from the tip of the hook plate to the greater tuberosity, as well as the angular motion of the plate tip in the subacromial space. Decreased posterior tilting (22° ± 10° vs 31° ± 8°) in the sagittal plane and increased external rotation (19° ± 9° vs 7° ± 5°) in the axial plane were evident in the affected shoulders. The mean values of translation of the hook plate and angular motion against the acromion were 4.0 ± 1.6 mm and 15° ± 8°, respectively. The minimum value of the distance from the hook plate to the humeral head tuberosity was 6.9 mm during arm elevation. Acromioclavicular reduction using a hook plate may cause scapular dyskinesis. Translational and angular motion of the hook plate against the acromion could lead to subacromial erosion. However, the hook does not seem to impinge directly on the humeral head. Copyright © 2017 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

Study on Data Clustering and Intelligent Decision Algorithm of Indoor Localization

Science.gov (United States)

Liu, Zexi

2018-01-01

Indoor positioning technology enables the human beings to have the ability of positional perception in architectural space, and there is a shortage of single network coverage and the problem of location data redundancy. So this article puts forward the indoor positioning data clustering algorithm and intelligent decision-making research, design the basic ideas of multi-source indoor positioning technology, analyzes the fingerprint localization algorithm based on distance measurement, position and orientation of inertial device integration. By optimizing the clustering processing of massive indoor location data, the data normalization pretreatment, multi-dimensional controllable clustering center and multi-factor clustering are realized, and the redundancy of locating data is reduced. In addition, the path is proposed based on neural network inference and decision, design the sparse data input layer, the dynamic feedback hidden layer and output layer, low dimensional results improve the intelligent navigation path planning.

FPGA Implementation of one-dimensional and two-dimensional cellular automata

International Nuclear Information System (INIS)

D'Antone, I.

1999-01-01

This report describes the hardware implementation of one-dimensional and two-dimensional cellular automata (CAs). After a general introduction to the cellular automata, we consider a one-dimensional CA used to implement pseudo-random techniques in built-in self test for VLSI. Due to the increase in digital ASIC complexity, testing is becoming one of the major costs in the VLSI production. The high electronics complexity, used in particle physics experiments, demands higher reliability than in the past time. General criterions are given to evaluate the feasibility of the circuit used for testing and some quantitative parameters are underlined to optimize the architecture of the cellular automaton. Furthermore, we propose a two-dimensional CA that performs a peak finding algorithm in a matrix of cells mapping a sub-region of a calorimeter. As in a two-dimensional filtering process, the peaks of the energy clusters are found in one evolution step. This CA belongs to Wolfram class II cellular automata. Some quantitative parameters are given to optimize the architecture of the cellular automaton implemented in a commercial field programmable gate array (FPGA)

hdm: High-dimensional metrics

OpenAIRE

Chernozhukov, Victor; Hansen, Christian; Spindler, Martin

2016-01-01

In this article the package High-dimensional Metrics (\\texttt{hdm}) is introduced. It is a collection of statistical methods for estimation and quantification of uncertainty in high-dimensional approximately sparse models. It focuses on providing confidence intervals and significance testing for (possibly many) low-dimensional subcomponents of the high-dimensional parameter vector. Efficient estimators and uniformly valid confidence intervals for regression coefficients on target variables (e...

Low Dimensionality Effects in Complex Magnetic Oxides

Science.gov (United States)

Kelley, Paula J. Lampen

Complex magnetic oxides represent a unique intersection of immense technological importance and fascinating physical phenomena originating from interwoven structural, electronic and magnetic degrees of freedom. The resulting energetically close competing orders can be controllably selected through external fields. Competing interactions and disorder represent an additional opportunity to systematically manipulate the properties of pure magnetic systems, leading to frustration, glassiness, and other novel phenomena while finite sample dimension plays a similar role in systems with long-range cooperative effects or large correlation lengths. A rigorous understanding of these effects in strongly correlated oxides is key to manipulating their functionality and device performance, but remains a challenging task. In this dissertation, we examine a number of problems related to intrinsic and extrinsic low dimensionality, disorder, and competing interactions in magnetic oxides by applying a unique combination of standard magnetometry techniques and unconventional magnetocaloric effect and transverse susceptibility measurements. The influence of dimensionality and disorder on the nature and critical properties of phase transitions in manganites is illustrated in La0.7 Ca0.3MnO3, in which both size reduction to the nanoscale and chemically-controlled quenched disorder are observed to induce a progressive weakening of the first-order nature of the transition, despite acting through the distinct mechanisms of surface effects and site dilution. In the second-order material La0.8Ca0.2MnO3, a strong magnetic field is found to drive the system toward its tricritical point as competition between exchange interactions in the inhomogeneous ground state is suppressed. In the presence of large phase separation stabilized by chemical disorder and long-range strain, dimensionality has a profound effect. With the systematic reduction of particle size in microscale-phase-separated (La, Pr

Two-dimensional NMR spectrometry

International Nuclear Information System (INIS)

Farrar, T.C.

1987-01-01

This article is the second in a two-part series. In part one (ANALYTICAL CHEMISTRY, May 15) the authors discussed one-dimensional nuclear magnetic resonance (NMR) spectra and some relatively advanced nuclear spin gymnastics experiments that provide a capability for selective sensitivity enhancements. In this article and overview and some applications of two-dimensional NMR experiments are presented. These powerful experiments are important complements to the one-dimensional experiments. As in the more sophisticated one-dimensional experiments, the two-dimensional experiments involve three distinct time periods: a preparation period, t 0 ; an evolution period, t 1 ; and a detection period, t 2

Mining High-Dimensional Data

Science.gov (United States)

Wang, Wei; Yang, Jiong

With the rapid growth of computational biology and e-commerce applications, high-dimensional data becomes very common. Thus, mining high-dimensional data is an urgent problem of great practical importance. However, there are some unique challenges for mining data of high dimensions, including (1) the curse of dimensionality and more crucial (2) the meaningfulness of the similarity measure in the high dimension space. In this chapter, we present several state-of-art techniques for analyzing high-dimensional data, e.g., frequent pattern mining, clustering, and classification. We will discuss how these methods deal with the challenges of high dimensionality.

TH-CD-207A-07: Prediction of High Dimensional State Subject to Respiratory Motion: A Manifold Learning Approach

International Nuclear Information System (INIS)

Liu, W; Sawant, A; Ruan, D

2016-01-01

Purpose: The development of high dimensional imaging systems (e.g. volumetric MRI, CBCT, photogrammetry systems) in image-guided radiotherapy provides important pathways to the ultimate goal of real-time volumetric/surface motion monitoring. This study aims to develop a prediction method for the high dimensional state subject to respiratory motion. Compared to conventional linear dimension reduction based approaches, our method utilizes manifold learning to construct a descriptive feature submanifold, where more efficient and accurate prediction can be performed. Methods: We developed a prediction framework for high-dimensional state subject to respiratory motion. The proposed method performs dimension reduction in a nonlinear setting to permit more descriptive features compared to its linear counterparts (e.g., classic PCA). Specifically, a kernel PCA is used to construct a proper low-dimensional feature manifold, where low-dimensional prediction is performed. A fixed-point iterative pre-image estimation method is applied subsequently to recover the predicted value in the original state space. We evaluated and compared the proposed method with PCA-based method on 200 level-set surfaces reconstructed from surface point clouds captured by the VisionRT system. The prediction accuracy was evaluated with respect to root-mean-squared-error (RMSE) for both 200ms and 600ms lookahead lengths. Results: The proposed method outperformed PCA-based approach with statistically higher prediction accuracy. In one-dimensional feature subspace, our method achieved mean prediction accuracy of 0.86mm and 0.89mm for 200ms and 600ms lookahead lengths respectively, compared to 0.95mm and 1.04mm from PCA-based method. The paired t-tests further demonstrated the statistical significance of the superiority of our method, with p-values of 6.33e-3 and 5.78e-5, respectively. Conclusion: The proposed approach benefits from the descriptiveness of a nonlinear manifold and the prediction

Nonlocal Reformulations of Water and Internal Waves and Asymptotic Reductions

Science.gov (United States)

Ablowitz, Mark J.

2009-09-01

Nonlocal reformulations of the classical equations of water waves and two ideal fluids separated by a free interface, bounded above by either a rigid lid or a free surface, are obtained. The kinematic equations may be written in terms of integral equations with a free parameter. By expressing the pressure, or Bernoulli, equation in terms of the surface/interface variables, a closed system is obtained. An advantage of this formulation, referred to as the nonlocal spectral (NSP) formulation, is that the vertical component is eliminated, thus reducing the dimensionality and fixing the domain in which the equations are posed. The NSP equations and the Dirichlet-Neumann operators associated with the water wave or two-fluid equations can be related to each other and the Dirichlet-Neumann series can be obtained from the NSP equations. Important asymptotic reductions obtained from the two-fluid nonlocal system include the generalizations of the Benney-Luke and Kadomtsev-Petviashvili (KP) equations, referred to as intermediate-long wave (ILW) generalizations. These 2+1 dimensional equations possess lump type solutions. In the water wave problem high-order asymptotic series are obtained for two and three dimensional gravity-capillary solitary waves. In two dimensions, the first term in the asymptotic series is the well-known hyperbolic secant squared solution of the KdV equation; in three dimensions, the first term is the rational lump solution of the KP equation.

Application of a CADIS-like variance reduction technique to electron transport

International Nuclear Information System (INIS)

Dionne, B.; Haghighat, A.

2004-01-01

This paper studies the use of approximate deterministic importance functions to calculate the lower-weight bounds of the MCNP5 weight-window variance reduction technique when applied to electron transport simulations. This approach follows the CADIS (Consistent Adjoint Driven Importance Sampling) methodology developed for neutral particles shielding calculations. The importance functions are calculated using the one-dimensional CEPXS/ONELD code package. Considering a simple 1-D problem, this paper shows that our methodology can produce speedups up to ∼82 using an approximate electron importance function distributions computed in ∼8 seconds. (author)

On four-derivative terms in IIB Calabi-Yau orientifold reductions

Energy Technology Data Exchange (ETDEWEB)

Weissenbacher, Matthias [Kavli Institute for the Physics and Mathematics of the Universe, University of Tokyo,Kashiwa-no-ha 5-1-5, 277-8583 (Japan)

2017-04-11

We perform a Kaluza-Klein reduction of IIB supergravity including purely gravitational α{sup ′3}-corrections on a Calabi-Yau threefold, and perform the orientifold projection accounting for the presence of O3/O7-planes. We consider infinitesimal Kähler deformations of the Calabi-Yau background and derive the complete set of four-derivative couplings quadratic in these fluctuations coupled to gravity. In particular, we find four-derivative couplings of the Kähler moduli fields in the four-dimensional effective supergravity theory, which are referred to as friction couplings in the context of inflation.

Prediction With Dimension Reduction of Multiple Molecular Data Sources for Patient Survival

Directory of Open Access Journals (Sweden)

Adam Kaplan

2017-07-01

Full Text Available Predictive modeling from high-dimensional genomic data is often preceded by a dimension reduction step, such as principal component analysis (PCA. However, the application of PCA is not straightforward for multisource data, wherein multiple sources of ‘omics data measure different but related biological components. In this article, we use recent advances in the dimension reduction of multisource data for predictive modeling. In particular, we apply exploratory results from Joint and Individual Variation Explained (JIVE, an extension of PCA for multisource data, for prediction of differing response types. We conduct illustrative simulations to illustrate the practical advantages and interpretability of our approach. As an application example, we consider predicting survival for patients with glioblastoma multiforme from 3 data sources measuring messenger RNA expression, microRNA expression, and DNA methylation. We also introduce a method to estimate JIVE scores for new samples that were not used in the initial dimension reduction and study its theoretical properties; this method is implemented in the R package R.JIVE on CRAN, in the function jive.predict.

Dimensional control of die castings

Science.gov (United States)

Karve, Aniruddha Ajit

The demand for net shape die castings, which require little or no machining, is steadily increasing. Stringent customer requirements are forcing die casters to deliver high quality castings in increasingly short lead times. Dimensional conformance to customer specifications is an inherent part of die casting quality. The dimensional attributes of a die casting are essentially dependent upon many factors--the quality of the die and the degree of control over the process variables being the two major sources of dimensional error in die castings. This study focused on investigating the nature and the causes of dimensional error in die castings. The two major components of dimensional error i.e., dimensional variability and die allowance were studied. The major effort of this study was to qualitatively and quantitatively study the effects of casting geometry and process variables on die casting dimensional variability and die allowance. This was accomplished by detailed dimensional data collection at production die casting sites. Robust feature characterization schemes were developed to describe complex casting geometry in quantitative terms. Empirical modeling was utilized to quantify the effects of the casting variables on dimensional variability and die allowance for die casting features. A number of casting geometry and process variables were found to affect dimensional variability in die castings. The dimensional variability was evaluated by comparisons with current published dimensional tolerance standards. The casting geometry was found to play a significant role in influencing the die allowance of the features measured. The predictive models developed for dimensional variability and die allowance were evaluated to test their effectiveness. Finally, the relative impact of all the components of dimensional error in die castings was put into perspective, and general guidelines for effective dimensional control in the die casting plant were laid out. The results of