Marin Quintero, Maider J.
2013-01-01
The structure tensor for vector valued images is most often defined as the average of the scalar structure tensors in each band. The problem with this definition is the assumption that all bands provide the same amount of edge information giving them the same weights. As a result non-edge pixels can be reinforced and edges can be weakened…
Tensor structure for Nori motives
Barbieri-Viale, Luca; Huber, Annette; Prest, Mike
2018-01-01
We construct a tensor product on Freyd's universal abelian category attached to an additive tensor category or a tensor quiver and establish a universal property. This is used to give an alternative construction for the tensor product on Nori motives.
A General Sparse Tensor Framework for Electronic Structure Theory.
Manzer, Samuel; Epifanovsky, Evgeny; Krylov, Anna I; Head-Gordon, Martin
2017-03-14
Linear-scaling algorithms must be developed in order to extend the domain of applicability of electronic structure theory to molecules of any desired size. However, the increasing complexity of modern linear-scaling methods makes code development and maintenance a significant challenge. A major contributor to this difficulty is the lack of robust software abstractions for handling block-sparse tensor operations. We therefore report the development of a highly efficient symbolic block-sparse tensor library in order to provide access to high-level software constructs to treat such problems. Our implementation supports arbitrary multi-dimensional sparsity in all input and output tensors. We avoid cumbersome machine-generated code by implementing all functionality as a high-level symbolic C++ language library and demonstrate that our implementation attains very high performance for linear-scaling sparse tensor contractions.
Tensor based structure estimation in multi-channel images
DEFF Research Database (Denmark)
Schou, Jesper; Dierking, Wolfgang; Skriver, Henning
2000-01-01
. In the second part tensors are used for representing the structure information. This approach has the advantage, that tensors can be averaged either spatially or by applying several images, and the resulting tensor provides information of the average strength as well as orientation of the structure...
He, Lifang; Kong, Xiangnan; Yu, Philip S.; Ragin, Ann B.; Hao, Zhifeng; Yang, Xiaowei
2015-01-01
With advances in data collection technologies, tensor data is assuming increasing prominence in many applications and the problem of supervised tensor learning has emerged as a topic of critical significance in the data mining and machine learning community. Conventional methods for supervised tensor learning mainly focus on learning kernels by flattening the tensor into vectors or matrices, however structural information within the tensors will be lost. In this paper, we introduce a new scheme to design structure-preserving kernels for supervised tensor learning. Specifically, we demonstrate how to leverage the naturally available structure within the tensorial representation to encode prior knowledge in the kernel. We proposed a tensor kernel that can preserve tensor structures based upon dual-tensorial mapping. The dual-tensorial mapping function can map each tensor instance in the input space to another tensor in the feature space while preserving the tensorial structure. Theoretically, our approach is an extension of the conventional kernels in the vector space to tensor space. We applied our novel kernel in conjunction with SVM to real-world tensor classification problems including brain fMRI classification for three different diseases (i.e., Alzheimer's disease, ADHD and brain damage by HIV). Extensive empirical studies demonstrate that our proposed approach can effectively boost tensor classification performances, particularly with small sample sizes. PMID:25927014
He, Lifang; Kong, Xiangnan; Yu, Philip S; Ragin, Ann B; Hao, Zhifeng; Yang, Xiaowei
With advances in data collection technologies, tensor data is assuming increasing prominence in many applications and the problem of supervised tensor learning has emerged as a topic of critical significance in the data mining and machine learning community. Conventional methods for supervised tensor learning mainly focus on learning kernels by flattening the tensor into vectors or matrices, however structural information within the tensors will be lost. In this paper, we introduce a new scheme to design structure-preserving kernels for supervised tensor learning. Specifically, we demonstrate how to leverage the naturally available structure within the tensorial representation to encode prior knowledge in the kernel. We proposed a tensor kernel that can preserve tensor structures based upon dual-tensorial mapping. The dual-tensorial mapping function can map each tensor instance in the input space to another tensor in the feature space while preserving the tensorial structure. Theoretically, our approach is an extension of the conventional kernels in the vector space to tensor space. We applied our novel kernel in conjunction with SVM to real-world tensor classification problems including brain fMRI classification for three different diseases ( i.e ., Alzheimer's disease, ADHD and brain damage by HIV). Extensive empirical studies demonstrate that our proposed approach can effectively boost tensor classification performances, particularly with small sample sizes.
Quadratic third-order tensor optimization problem with quadratic constraints
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Lixing Yang
2014-05-01
Full Text Available Quadratically constrained quadratic programs (QQPs problems play an important modeling role for many diverse problems. These problems are in general NP hard and numerically intractable. Semidenite programming (SDP relaxations often provide good approximate solutions to these hard problems. For several special cases of QQP, e.g., convex programs and trust region subproblems, SDP relaxation provides the exact optimal value, i.e., there is a zero duality gap. However, this is not true for the general QQP, or even the QQP with two convex constraints, but a nonconvex objective.In this paper, we consider a certain QQP where the variable is neither vector nor matrix but a third-order tensor. This problem can be viewed as a generalization of the ordinary QQP with vector or matrix as it's variant. Under some mild conditions, we rst show that SDP relaxation provides exact optimal solutions for the original problem. Then we focus on two classes of homogeneous quadratic tensor programming problems which have no requirements on the constraints number. For one, we provide an easily implemental polynomial time algorithm to approximately solve the problem and discuss the approximation ratio. For the other, we show there is no gap between the SDP relaxation and itself.
A Tensor-Based Structural Damage Identification and Severity Assessment
Anaissi, Ali; Makki Alamdari, Mehrisadat; Rakotoarivelo, Thierry; Khoa, Nguyen Lu Dang
2018-01-01
Early damage detection is critical for a large set of global ageing infrastructure. Structural Health Monitoring systems provide a sensor-based quantitative and objective approach to continuously monitor these structures, as opposed to traditional engineering visual inspection. Analysing these sensed data is one of the major Structural Health Monitoring (SHM) challenges. This paper presents a novel algorithm to detect and assess damage in structures such as bridges. This method applies tensor analysis for data fusion and feature extraction, and further uses one-class support vector machine on this feature to detect anomalies, i.e., structural damage. To evaluate this approach, we collected acceleration data from a sensor-based SHM system, which we deployed on a real bridge and on a laboratory specimen. The results show that our tensor method outperforms a state-of-the-art approach using the wavelet energy spectrum of the measured data. In the specimen case, our approach succeeded in detecting 92.5% of induced damage cases, as opposed to 61.1% for the wavelet-based approach. While our method was applied to bridges, its algorithm and computation can be used on other structures or sensor-data analysis problems, which involve large series of correlated data from multiple sensors. PMID:29301314
Towards overcoming the Monte Carlo sign problem with tensor networks
Directory of Open Access Journals (Sweden)
Bañuls Mari Carmen
2017-01-01
Full Text Available The study of lattice gauge theories with Monte Carlo simulations is hindered by the infamous sign problem that appears under certain circumstances, in particular at non-zero chemical potential. So far, there is no universal method to overcome this problem. However, recent years brought a new class of non-perturbative Hamiltonian techniques named tensor networks, where the sign problem is absent. In previous work, we have demonstrated that this approach, in particular matrix product states in 1+1 dimensions, can be used to perform precise calculations in a lattice gauge theory, the massless and massive Schwinger model. We have computed the mass spectrum of this theory, its thermal properties and real-time dynamics. In this work, we review these results and we extend our calculations to the case of two flavours and non-zero chemical potential. We are able to reliably reproduce known analytical results for this model, thus demonstrating that tensor networks can tackle the sign problem of a lattice gauge theory at finite density.
Tensor products of process matrices with indefinite causal structure
Jia, Ding; Sakharwade, Nitica
2018-03-01
Theories with indefinite causal structure have been studied from both the fundamental perspective of quantum gravity and the practical perspective of information processing. In this paper we point out a restriction in forming tensor products of objects with indefinite causal structure in certain models: there exist both classical and quantum objects the tensor products of which violate the normalization condition of probabilities, if all local operations are allowed. We obtain a necessary and sufficient condition for when such unrestricted tensor products of multipartite objects are (in)valid. This poses a challenge to extending communication theory to indefinite causal structures, as the tensor product is the fundamental ingredient in the asymptotic setting of communication theory. We discuss a few options to evade this issue. In particular, we show that the sequential asymptotic setting does not suffer the violation of normalization.
Teh, Irvin; McClymont, Darryl; Zdora, Marie-Christine; Whittington, Hannah J; Davidoiu, Valentina; Lee, Jack; Lygate, Craig A; Rau, Christoph; Zanette, Irene; Schneider, Jürgen E
2017-03-10
Diffusion tensor imaging (DTI) is widely used to assess tissue microstructure non-invasively. Cardiac DTI enables inference of cell and sheetlet orientations, which are altered under pathological conditions. However, DTI is affected by many factors, therefore robust validation is critical. Existing histological validation is intrinsically flawed, since it requires further tissue processing leading to sample distortion, is routinely limited in field-of-view and requires reconstruction of three-dimensional volumes from two-dimensional images. In contrast, synchrotron radiation imaging (SRI) data enables imaging of the heart in 3D without further preparation following DTI. The objective of the study was to validate DTI measurements based on structure tensor analysis of SRI data. One isolated, fixed rat heart was imaged ex vivo with DTI and X-ray phase contrast SRI, and reconstructed at 100 μm and 3.6 μm isotropic resolution respectively. Structure tensors were determined from the SRI data and registered to the DTI data. Excellent agreement in helix angles (HA) and transverse angles (TA) was observed between the DTI and structure tensor synchrotron radiation imaging (STSRI) data, where HA DTI-STSRI = -1.4° ± 23.2° and TA DTI-STSRI = -1.4° ± 35.0° (mean ± 1.96 standard deviation across all voxels in the left ventricle). STSRI confirmed that the primary eigenvector of the diffusion tensor corresponds with the cardiomyocyte long-axis across the whole myocardium. We have used STSRI as a novel and high-resolution gold standard for the validation of DTI, allowing like-with-like comparison of three-dimensional tissue structures in the same intact heart free of distortion. This represents a critical step forward in independently verifying the structural basis and informing the interpretation of cardiac DTI data, thereby supporting the further development and adoption of DTI in structure-based electro-mechanical modelling and routine clinical
Retinal Vessel Segmentation via Structure Tensor Coloring and Anisotropy Enhancement
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Mehmet Nergiz
2017-11-01
Full Text Available Retinal vessel segmentation is one of the preliminary tasks for developing diagnosis software systems related to various retinal diseases. In this study, a fully automated vessel segmentation system is proposed. Firstly, the vessels are enhanced using a Frangi Filter. Afterwards, Structure Tensor is applied to the response of the Frangi Filter and a 4-D tensor field is obtained. After decomposing the Eigenvalues of the tensor field, the anisotropy between the principal Eigenvalues are enhanced exponentially. Furthermore, this 4-D tensor field is converted to the 3-D space which is composed of energy, anisotropy and orientation and then a Contrast Limited Adaptive Histogram Equalization algorithm is applied to the energy space. Later, the obtained energy space is multiplied by the enhanced mean surface curvature of itself and the modified 3-D space is converted back to the 4-D tensor field. Lastly, the vessel segmentation is performed by using Otsu algorithm and tensor coloring method which is inspired by the ellipsoid tensor visualization technique. Finally, some post-processing techniques are applied to the segmentation result. In this study, the proposed method achieved mean sensitivity of 0.8123, 0.8126, 0.7246 and mean specificity of 0.9342, 0.9442, 0.9453 as well as mean accuracy of 0.9183, 0.9442, 0.9236 for DRIVE, STARE and CHASE_DB1 datasets, respectively. The mean execution time of this study is 6.104, 6.4525 and 18.8370 s for the aforementioned three datasets respectively.
Structural equations for Killing tensors of order two. II
International Nuclear Information System (INIS)
Hauser, I.; Malhiot, R.J.
1975-01-01
In a preceding paper, a new form of the structural equations for any Killing tensor of order two have been derived; these equations constitute a system analogous to the Killing vector equations Nabla/sub alpha/ K/sub beta/ = ω/sub alpha beta/ = -ω/sub beta alpha/ and Nabla/sub gamma/ ω/sub alpha beta = R/sub alpha beta gamma delta/ K/sup delta/. The first integrability condition for the Killing tensor structural equations is now derived. The structural equations and the integrability condition have forms which can readily be expressed in terms of a null tetrad to furnish a Killing tensor parallel of the Newman--Penrose equations; this is briefly described. The integrability condition implies the new result, for any given space--time, that the dimension of the set of second-order Killing tensors attains its maximum possible value of 50 only if the space--time is of constant curvature. Potential applications of the structural equations are discussed
Inflationary tensor fossils in large-scale structure
Energy Technology Data Exchange (ETDEWEB)
Dimastrogiovanni, Emanuela [School of Physics and Astronomy, University of Minnesota, Minneapolis, MN 55455 (United States); Fasiello, Matteo [Department of Physics, Case Western Reserve University, Cleveland, OH 44106 (United States); Jeong, Donghui [Department of Astronomy and Astrophysics, The Pennsylvania State University, University Park, PA 16802 (United States); Kamionkowski, Marc, E-mail: ema@physics.umn.edu, E-mail: mrf65@case.edu, E-mail: duj13@psu.edu, E-mail: kamion@jhu.edu [Department of Physics and Astronomy, 3400 N. Charles St., Johns Hopkins University, Baltimore, MD 21218 (United States)
2014-12-01
Inflation models make specific predictions for a tensor-scalar-scalar three-point correlation, or bispectrum, between one gravitational-wave (tensor) mode and two density-perturbation (scalar) modes. This tensor-scalar-scalar correlation leads to a local power quadrupole, an apparent departure from statistical isotropy in our Universe, as well as characteristic four-point correlations in the current mass distribution in the Universe. So far, the predictions for these observables have been worked out only for single-clock models in which certain consistency conditions between the tensor-scalar-scalar correlation and tensor and scalar power spectra are satisfied. Here we review the requirements on inflation models for these consistency conditions to be satisfied. We then consider several examples of inflation models, such as non-attractor and solid-inflation models, in which these conditions are put to the test. In solid inflation the simplest consistency conditions are already violated whilst in the non-attractor model we find that, contrary to the standard scenario, the tensor-scalar-scalar correlator probes directly relevant model-dependent information. We work out the predictions for observables in these models. For non-attractor inflation we find an apparent local quadrupolar departure from statistical isotropy in large-scale structure but that this power quadrupole decreases very rapidly at smaller scales. The consistency of the CMB quadrupole with statistical isotropy then constrains the distance scale that corresponds to the transition from the non-attractor to attractor phase of inflation to be larger than the currently observable horizon. Solid inflation predicts clustering fossils signatures in the current galaxy distribution that may be large enough to be detectable with forthcoming, and possibly even current, galaxy surveys.
STRUCTURAL STUDY AND INVESTIGATION OF NMR TENSORS ...
African Journals Online (AJOL)
theory. The structural and vibrational properties of dopamine-4-N7GUA and ... There is evidence, however, that DA is involved in the ... spectra to the results of ab initio gauge-invariant atomic orbital (GIAO) [14-17] and continuous- ..... Nicholls, G. Proteins, transmitter & synapses, Blackwell Scientific Publication: Scotland;.
STRUCTURE TENSOR IMAGE FILTERING USING RIEMANNIAN L1 AND L∞ CENTER-OF-MASS
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Jesus Angulo
2014-06-01
Full Text Available Structure tensor images are obtained by a Gaussian smoothing of the dyadic product of gradient image. These images give at each pixel a n×n symmetric positive definite matrix SPD(n, representing the local orientation and the edge information. Processing such images requires appropriate algorithms working on the Riemannian manifold on the SPD(n matrices. This contribution deals with structure tensor image filtering based on Lp geometric averaging. In particular, L1 center-of-mass (Riemannian median or Fermat-Weber point and L∞ center-of-mass (Riemannian circumcenter can be obtained for structure tensors using recently proposed algorithms. Our contribution in this paper is to study the interest of L1 and L∞ Riemannian estimators for structure tensor image processing. In particular, we compare both for two image analysis tasks: (i structure tensor image denoising; (ii anomaly detection in structure tensor images.
Beyond Low Rank: A Data-Adaptive Tensor Completion Method
Zhang, Lei; Wei, Wei; Shi, Qinfeng; Shen, Chunhua; Hengel, Anton van den; Zhang, Yanning
2017-01-01
Low rank tensor representation underpins much of recent progress in tensor completion. In real applications, however, this approach is confronted with two challenging problems, namely (1) tensor rank determination; (2) handling real tensor data which only approximately fulfils the low-rank requirement. To address these two issues, we develop a data-adaptive tensor completion model which explicitly represents both the low-rank and non-low-rank structures in a latent tensor. Representing the no...
Recognition by symmetry derivatives and the generalized structure tensor.
Bigun, Josef; Bigun, Tomas; Nilsson, Kenneth
2004-12-01
We suggest a set of complex differential operators that can be used to produce and filter dense orientation (tensor) fields for feature extraction, matching, and pattern recognition. We present results on the invariance properties of these operators, that we call symmetry derivatives. These show that, in contrast to ordinary derivatives, all orders of symmetry derivatives of Gaussians yield a remarkable invariance: They are obtained by replacing the original differential polynomial with the same polynomial, but using ordinary coordinates x and y corresponding to partial derivatives. Moreover, the symmetry derivatives of Gaussians are closed under the convolution operator and they are invariant to the Fourier transform. The equivalent of the structure tensor, representing and extracting orientations of curve patterns, had previously been shown to hold in harmonic coordinates in a nearly identical manner. As a result, positions, orientations, and certainties of intricate patterns, e.g., spirals, crosses, parabolic shapes, can be modeled by use of symmetry derivatives of Gaussians with greater analytical precision as well as computational efficiency. Since Gaussians and their derivatives are utilized extensively in image processing, the revealed properties have practical consequences for local orientation based feature extraction. The usefulness of these results is demonstrated by two applications: 1) tracking cross markers in long image sequences from vehicle crash tests and 2) alignment of noisy fingerprints.
Diffusion Tensor Tractography Reveals Disrupted Structural Connectivity during Brain Aging
Lin, Lan; Tian, Miao; Wang, Qi; Wu, Shuicai
2017-10-01
Brain aging is one of the most crucial biological processes that entail many physical, biological, chemical, and psychological changes, and also a major risk factor for most common neurodegenerative diseases. To improve the quality of life for the elderly, it is important to understand how the brain is changed during the normal aging process. We compared diffusion tensor imaging (DTI)-based brain networks in a cohort of 75 healthy old subjects by using graph theory metrics to describe the anatomical networks and connectivity patterns, and network-based statistic (NBS) analysis was used to identify pairs of regions with altered structural connectivity. The NBS analysis revealed a significant network comprising nine distinct fiber bundles linking 10 different brain regions showed altered white matter structures in young-old group compare with middle-aged group (p < .05, family-wise error-corrected). Our results might guide future studies and help to gain a better understanding of brain aging.
Structural Identification Problem
Directory of Open Access Journals (Sweden)
Suvorov Aleksei
2016-01-01
Full Text Available The identification problem of the existing structures though the Quasi-Newton and its modification, Trust region algorithms is discussed. For the structural problems, which could be represented by means of the mathematical modelling of the finite element code discussed method is extremely useful. The nonlinear minimization problem of the L2 norm for the structures with linear elastic behaviour is solved by using of the Optimization Toolbox of Matlab. The direct and inverse procedures for the composition of the desired function to minimize are illustrated for the spatial 3D truss structure as well as for the problem of plane finite elements. The truss identification problem is solved with 2 and 3 unknown parameters in order to compare the computational efforts and for the graphical purposes. The particular commands of the Matlab codes are present in this paper.
Structural connectivity via the tensor-based morphometry
Kim, S.; Chung, M.; Hanson, J.; Avants, B.; Gee, J.; Davidson, R.; Pollak, S.
2011-01-01
The tensor-based morphometry (TBM) has been widely used in characterizing tissue volume difference between populations at voxel level. We present a novel computational framework for investigating the white matter connectivity using TBM. Unlike other diffusion tensor imaging (DTI) based white matter connectivity studies, we do not use DTI but only T1-weighted magnetic resonance imaging (MRI). To construct brain network graphs, we have developed a new data-driven approach called the ε-neighbor ...
Analyzing vortex breakdown flow structures by assignment of colors to tensor invariants.
Rütten, Markus; Chong, Min S
2006-01-01
Topological methods are often used to describe flow structures in fluid dynamics and topological flow field analysis usually relies on the invariants of the associated tensor fields. A visual impression of the local properties of tensor fields is often complex and the search of a suitable technique for achieving this is an ongoing topic in visualization. This paper introduces and assesses a method of representing the topological properties of tensor fields and their respective flow patterns with the use of colors. First, a tensor norm is introduced, which preserves the properties of the tensor and assigns the tensor invariants to values of the RGB color space. Secondly, the RGB colors of the tensor invariants are transferred to corresponding hue values as an alternative color representation. The vectorial tensor invariants field is reduced to a scalar hue field and visualization of iso-surfaces of this hue value field allows us to identify locations with equivalent flow topology. Additionally highlighting by the maximum of the eigenvalue difference field reflects the magnitude of the structural change of the flow. The method is applied on a vortex breakdown flow structure inside a cylinder with a rotating lid.
Fibre bundles associated with fields of geometric objects and a structure tensor
International Nuclear Information System (INIS)
Konderak, J.
1987-08-01
A construction of a k th structure tensor of a field of geometric objects is presented here (k is a non-negative integer). For a given field σ we construct a vector bundle H k,2 (σ). The k th structure tensor is defined as a section of H k,2 (σ) generated by the torsion of σ. It is then shown that vanishing of the k th structure tensor is a necessary and sufficient condition for the field to be (k + 1)-flat. (author). 16 refs
Cyganek, Boguslaw; Smolka, Bogdan
2015-02-01
In this paper a system for real-time recognition of objects in multidimensional video signals is proposed. Object recognition is done by pattern projection into the tensor subspaces obtained from the factorization of the signal tensors representing the input signal. However, instead of taking only the intensity signal the novelty of this paper is first to build the Extended Structural Tensor representation from the intensity signal that conveys information on signal intensities, as well as on higher-order statistics of the input signals. This way the higher-order input pattern tensors are built from the training samples. Then, the tensor subspaces are built based on the Higher-Order Singular Value Decomposition of the prototype pattern tensors. Finally, recognition relies on measurements of the distance of a test pattern projected into the tensor subspaces obtained from the training tensors. Due to high-dimensionality of the input data, tensor based methods require high memory and computational resources. However, recent achievements in the technology of the multi-core microprocessors and graphic cards allows real-time operation of the multidimensional methods as is shown and analyzed in this paper based on real examples of object detection in digital images.
A higher-order tensor vessel tractography for segmentation of vascular structures.
Cetin, Suheyla; Unal, Gozde
2015-10-01
A new vascular structure segmentation method, which is based on a cylindrical flux-based higher order tensor (HOT), is presented. On a vessel structure, the HOT naturally models branching points, which create challenges for vessel segmentation algorithms. In a general linear HOT model embedded in 3D, one has to work with an even order tensor due to an enforced antipodal-symmetry on the unit sphere. However, in scenarios such as in a bifurcation, the antipodally-symmetric tensor embedded in 3D will not be useful. In order to overcome that limitation, we embed the tensor in 4D and obtain a structure that can model asymmetric junction scenarios. During construction of a higher order tensor (e.g. third or fourth order) in 4D, the orientation vectors lie on the unit 3-sphere, in contrast to the unit 2-sphere in 3D tensor modeling. This 4D tensor is exploited in a seed-based vessel segmentation algorithm, where the principal directions of the 4D HOT is obtained by decomposition, and used in a HOT tractography approach. We demonstrate quantitative validation of the proposed algorithm on both synthetic complex tubular structures as well as real cerebral vasculature in Magnetic Resonance Angiography (MRA) datasets and coronary arteries from Computed Tomography Angiography (CTA) volumes.
Heidsieck, David S P; Smarius, Bram J A; Oomen, Karin P Q; Breugem, Corstiaan C
2016-09-01
Otitis media with effusion is common in infants with an unrepaired cleft palate. Although its prevalence is reduced after cleft surgery, many children continue to suffer from middle ear problems during childhood. While the tensor veli palatini muscle is thought to be involved in middle ear ventilation, evidence about its exact anatomy, function, and role in cleft palate surgery is limited. This study aimed to perform a thorough review of the literature on (1) the role of the tensor veli palatini muscle in the Eustachian tube opening and middle ear ventilation, (2) anatomical anomalies in cleft palate infants related to middle ear disease, and (3) their implications for surgical techniques used in cleft palate repair. A literature search on the MEDLINE database was performed using a combination of the keywords "tensor veli palatini muscle," "Eustachian tube," "otitis media with effusion," and "cleft palate." Several studies confirm the important role of the tensor veli palatini muscle in the Eustachian tube opening mechanism. Maintaining the integrity of the tensor veli palatini muscle during cleft palate surgery seems to improve long-term otological outcome. However, anatomical variations in cleft palate children may alter the effect of the tensor veli palatini muscle on the Eustachian tube's dilatation mechanism. More research is warranted to clarify the role of the tensor veli palatini muscle in cleft palate-associated Eustachian tube dysfunction and development of middle ear problems. Optimized surgical management of cleft palate could potentially reduce associated middle ear problems.
STRUCTURAL CONNECTIVITY VIA THE TENSOR-BASED MORPHOMETRY.
Kim, Seung-Goo; Chung, Moo K; Hanson, Jamie L; Avants, Brian B; Gee, James C; Davidson, Richard J; Pollak, Seth D
2011-01-01
The tensor-based morphometry (TBM) has been widely used in characterizing tissue volume difference between populations at voxel level. We present a novel computational framework for investigating the white matter connectivity using TBM. Unlike other diffusion tensor imaging (DTI) based white matter connectivity studies, we do not use DTI but only T1-weighted magnetic resonance imaging (MRI). To construct brain network graphs, we have developed a new data-driven approach called the ε -neighbor method that does not need any predetermined parcellation. The proposed pipeline is applied in detecting the topological alteration of the white matter connectivity in maltreated children.
Spectral Method with the Tensor-Product Nodal Basis for the Steklov Eigenvalue Problem
Directory of Open Access Journals (Sweden)
Xuqing Zhang
2013-01-01
Full Text Available This paper discusses spectral method with the tensor-product nodal basis at the Legendre-Gauss-Lobatto points for solving the Steklov eigenvalue problem. A priori error estimates of spectral method are discussed, and based on the work of Melenk and Wohlmuth (2001, a posterior error estimator of the residual type is given and analyzed. In addition, this paper combines the shifted-inverse iterative method and spectral method to establish an efficient scheme. Finally, numerical experiments with MATLAB program are reported.
Tensor eigenvalues and their applications
Qi, Liqun; Chen, Yannan
2018-01-01
This book offers an introduction to applications prompted by tensor analysis, especially by the spectral tensor theory developed in recent years. It covers applications of tensor eigenvalues in multilinear systems, exponential data fitting, tensor complementarity problems, and tensor eigenvalue complementarity problems. It also addresses higher-order diffusion tensor imaging, third-order symmetric and traceless tensors in liquid crystals, piezoelectric tensors, strong ellipticity for elasticity tensors, and higher-order tensors in quantum physics. This book is a valuable reference resource for researchers and graduate students who are interested in applications of tensor eigenvalues.
Structural properties of the self-conjugate SU(3) tensor operators
International Nuclear Information System (INIS)
Lohe, M.A.; Biedenharn, L.C.; Louck, J.D.
1977-01-01
Denominator functions for the set of self-conjugate SU(3) tensor operators are explicitly obtained and shown to be uniquely related to SU(3) -invariant structural properties. This relationship becomes manifest through the appearance of zeroes of the denominator functions which thereby express the fundamental null space properties of SU(3) tensor operators. It is demonstrated that there exist characteristic denominator functions whose zeroes, in position and multiplicity, possess the interesting, and unexpected, property of forming SU(3) weight space patterns
Product numerical range in a space with tensor product structure
Puchała, Zbigniew; Gawron, Piotr; Miszczak, Jarosław Adam; Skowronek, Łukasz; Choi, Man-Duen; Życzkowski, Karol
2010-01-01
We study operators acting on a tensor product Hilbert space and investigate their product numerical range, product numerical radius and separable numerical range. Concrete bounds for the product numerical range for Hermitian operators are derived. Product numerical range of a non-Hermitian operator forms a subset of the standard numerical range containing the barycenter of the spectrum. While the latter set is convex, the product range needs not to be convex nor simply connected. The product ...
Tensor Factorization for Low-Rank Tensor Completion.
Zhou, Pan; Lu, Canyi; Lin, Zhouchen; Zhang, Chao
2018-03-01
Recently, a tensor nuclear norm (TNN) based method was proposed to solve the tensor completion problem, which has achieved state-of-the-art performance on image and video inpainting tasks. However, it requires computing tensor singular value decomposition (t-SVD), which costs much computation and thus cannot efficiently handle tensor data, due to its natural large scale. Motivated by TNN, we propose a novel low-rank tensor factorization method for efficiently solving the 3-way tensor completion problem. Our method preserves the low-rank structure of a tensor by factorizing it into the product of two tensors of smaller sizes. In the optimization process, our method only needs to update two smaller tensors, which can be more efficiently conducted than computing t-SVD. Furthermore, we prove that the proposed alternating minimization algorithm can converge to a Karush-Kuhn-Tucker point. Experimental results on the synthetic data recovery, image and video inpainting tasks clearly demonstrate the superior performance and efficiency of our developed method over state-of-the-arts including the TNN and matricization methods.
The initial value problem of scalar-tensor theories of gravity
Energy Technology Data Exchange (ETDEWEB)
Salgado, Marcelo; Martinez del Rio, David [Instituto de Ciencias Nucleares Universidad Nacional Autonoma de Mexico Apdo. Postal 70-543 Mexico 04510 D.F. (Mexico)
2007-11-15
The initial value problem of scalar-tensor theories of gravity (STT) is analyzed in the physical (Jordan) frame using a 3+1 decomposition of spacetime. A first order strongly hyperbolic system is obtained for which the well posedness of the Cauchy problem can be established. We provide two simple applications of the 3+1 system of equations: one for static and spherically symmetric spacetimes which allows the construction of unstable initial data (compact objects) for which a further black hole formation and scalar gravitational wave emission can be analyzed, and another application is for homogeneous and isotropic spacetimes that permits to study the dynamics of the Universe in the framework of STT.
Tensor decomposition in electronic structure calculations on 3D Cartesian grids
International Nuclear Information System (INIS)
Khoromskij, B.N.; Khoromskaia, V.; Chinnamsetty, S.R.; Flad, H.-J.
2009-01-01
In this paper, we investigate a novel approach based on the combination of Tucker-type and canonical tensor decomposition techniques for the efficient numerical approximation of functions and operators in electronic structure calculations. In particular, we study applicability of tensor approximations for the numerical solution of Hartree-Fock and Kohn-Sham equations on 3D Cartesian grids. We show that the orthogonal Tucker-type tensor approximation of electron density and Hartree potential of simple molecules leads to low tensor rank representations. This enables an efficient tensor-product convolution scheme for the computation of the Hartree potential using a collocation-type approximation via piecewise constant basis functions on a uniform nxnxn grid. Combined with the Richardson extrapolation, our approach exhibits O(h 3 ) convergence in the grid-size h=O(n -1 ). Moreover, this requires O(3rn+r 3 ) storage, where r denotes the Tucker rank of the electron density with r=O(logn), almost uniformly in n. For example, calculations of the Coulomb matrix and the Hartree-Fock energy for the CH 4 molecule, with a pseudopotential on the C atom, achieved accuracies of the order of 10 -6 hartree with a grid-size n of several hundreds. Since the tensor-product convolution in 3D is performed via 1D convolution transforms, our scheme markedly outperforms the 3D-FFT in both the computing time and storage requirements.
3D structure tensor analysis of light microscopy data for validating diffusion MRI.
Khan, Ahmad Raza; Cornea, Anda; Leigland, Lindsey A; Kohama, Steven G; Jespersen, Sune Nørhøj; Kroenke, Christopher D
2015-05-01
Diffusion magnetic resonance imaging (d-MRI) is a powerful non-invasive and non-destructive technique for characterizing brain tissue on the microscopic scale. However, the lack of validation of d-MRI by independent experimental means poses an obstacle to accurate interpretation of data acquired using this method. Recently, structure tensor analysis has been applied to light microscopy images, and this technique holds promise to be a powerful validation strategy for d-MRI. Advantages of this approach include its similarity to d-MRI in terms of averaging the effects of a large number of cellular structures, and its simplicity, which enables it to be implemented in a high-throughput manner. However, a drawback of previous implementations of this technique arises from it being restricted to 2D. As a result, structure tensor analyses have been limited to tissue sectioned in a direction orthogonal to the direction of interest. Here we describe the analytical framework for extending structure tensor analysis to 3D, and utilize the results to analyze serial image "stacks" acquired with confocal microscopy of rhesus macaque hippocampal tissue. Implementation of 3D structure tensor procedures requires removal of sources of anisotropy introduced in tissue preparation and confocal imaging. This is accomplished with image processing steps to mitigate the effects of anisotropic tissue shrinkage, and the effects of anisotropy in the point spread function (PSF). In order to address the latter confound, we describe procedures for measuring the dependence of PSF anisotropy on distance from the microscope objective within tissue. Prior to microscopy, ex vivo d-MRI measurements performed on the hippocampal tissue revealed three regions of tissue with mutually orthogonal directions of least restricted diffusion that correspond to CA1, alveus and inferior longitudinal fasciculus. We demonstrate the ability of 3D structure tensor analysis to identify structure tensor orientations that
An enhanced structure tensor method for sea ice ridge detection from GF-3 SAR imagery
Zhu, T.; Li, F.; Zhang, Y.; Zhang, S.; Spreen, G.; Dierking, W.; Heygster, G.
2017-12-01
In SAR imagery, ridges or leads are shown as the curvilinear features. The proposed ridge detection method is facilitated by their curvilinear shapes. The bright curvilinear features are recognized as the ridges while the dark curvilinear features are classified as the leads. In dual-polarization HH or HV channel of C-band SAR imagery, the bright curvilinear feature may be false alarm because the frost flowers of young leads may show as bright pixels associated with changes in the surface salinity under calm surface conditions. Wind roughened leads also trigger the backscatter increasing that can be misclassified as ridges [1]. Thus the width limitation is considered in this proposed structure tensor method [2], since only shape feature based method is not enough for detecting ridges. The ridge detection algorithm is based on the hypothesis that the bright pixels are ridges with curvilinear shapes and the ridge width is less 30 meters. Benefited from GF-3 with high spatial resolution of 3 meters, we provide an enhanced structure tensor method for detecting the significant ridge. The preprocessing procedures including the calibration and incidence angle normalization are also investigated. The bright pixels will have strong response to the bandpass filtering. The ridge training samples are delineated from the SAR imagery in the Log-Gabor filters to construct structure tensor. From the tensor, the dominant orientation of the pixel representing the ridge is determined by the dominant eigenvector. For the post-processing of structure tensor, the elongated kernel is desired to enhance the ridge curvilinear shape. Since ridge presents along a certain direction, the ratio of the dominant eigenvector will be used to measure the intensity of local anisotropy. The convolution filter has been utilized in the constructed structure tensor is used to model spatial contextual information. Ridge detection results from GF-3 show the proposed method performs better compared to the
TensorLy: Tensor Learning in Python
Kossaifi, Jean; Panagakis, Yannis; Pantic, Maja
2016-01-01
Tensor methods are gaining increasing traction in machine learning. However, there are scant to no resources available to perform tensor learning and decomposition in Python. To answer this need we developed TensorLy. TensorLy is a state of the art general purpose library for tensor learning.
Decomposing tensors with structured matrix factors reduces to rank-1 approximations
DEFF Research Database (Denmark)
Comon, Pierre; Sørensen, Mikael; Tsigaridas, Elias
2010-01-01
Tensor decompositions permit to estimate in a deterministic way the parameters in a multi-linear model. Applications have been already pointed out in antenna array processing and digital communications, among others, and are extremely attractive provided some diversity at the receiver is availabl....... As opposed to the widely used ALS algorithm, non-iterative algorithms are proposed in this paper to compute the required tensor decomposition into a sum of rank-1 terms, when some factor matrices enjoy some structure, such as block-Hankel, triangular, band, etc....
A locally convergent Jacobi iteration for the tensor singular value problem
Shekhawat, Hanumant Singh; Weiland, Siep
2018-01-01
Multi-linear functionals or tensors are useful in study and analysis multi-dimensional signal and system. Tensor approximation, which has various applications in signal processing and system theory, can be achieved by generalizing the notion of singular values and singular vectors of matrices to
Energy Technology Data Exchange (ETDEWEB)
Bouaricha, A. [Argonne National Lab., IL (United States). Mathematics and Computer Science Div.; Schnabel, R.B. [Colorado Univ., Boulder, CO (United States). Dept. of Computer Science
1996-12-31
This paper describes a modular software package for solving systems of nonlinear equations and nonlinear least squares problems, using a new class of methods called tensor methods. It is intended for small to medium-sized problems, say with up to 100 equations and unknowns, in cases where it is reasonable to calculate the Jacobian matrix or approximate it by finite differences at each iteration. The software allows the user to select between a tensor method and a standard method based upon a linear model. The tensor method models F({ital x}) by a quadratic model, where the second-order term is chosen so that the model is hardly more expensive to form, store, or solve than the standard linear model. Moreover, the software provides two different global strategies, a line search and a two- dimensional trust region approach. Test results indicate that, in general, tensor methods are significantly more efficient and robust than standard methods on small and medium-sized problems in iterations and function evaluations.
Loss, Leandro A.; Bebis, George; Parvin, Bahram
2012-01-01
In this paper, a novel approach is proposed for perceptual grouping and localization of ill-defined curvilinear structures. Our approach builds upon the tensor voting and the iterative voting frameworks. Its efficacy lies on iterative refinements of curvilinear structures by gradually shifting from an exploratory to an exploitative mode. Such a mode shifting is achieved by reducing the aperture of the tensor voting fields, which is shown to improve curve grouping and inference by enhancing the concentration of the votes over promising, salient structures. The proposed technique is applied to delineation of adherens junctions imaged through fluorescence microscopy. This class of membrane-bound macromolecules maintains tissue structural integrity and cell-cell interactions. Visually, it exhibits fibrous patterns that may be diffused, punctate and frequently perceptual. Besides the application to real data, the proposed method is compared to prior methods on synthetic and annotated real data, showing high precision rates. PMID:21421432
Collaborative problem structuring using MARVEL
Veldhuis, G.A.; Scheepstal, P.G.M. van; Rouwette, E.A.J.A.; Logtens, T.W.A.
2015-01-01
When faced with wicked and messy problems, practitioners can rely on a variety of problem structuring methods (PSMs). Although previous efforts have been made to combine such methods with simulation, currently, few exist that integrate a simulation capability within problem structuring. Our
Tensor-based morphometry of fibrous structures with application to human brain white matter.
Zhang, Hui; Yushkevich, Paul A; Rueckert, Daniel; Gee, James C
2009-01-01
Tensor-based morphometry (TBM) is a powerful approach for examining shape changes in anatomy both across populations and in time. Our work extends the standard TBM for quantifying local volumetric changes to establish both rich and intuitive descriptors of shape changes in fibrous structures. It leverages the data from diffusion tensor imaging to determine local spatial configuration of fibrous structures and combines this information with spatial transformations derived from image registration to quantify fibrous structure-specific changes, such as local changes in fiber length and in thickness of fiber bundles. In this paper, we describe the theoretical framework of our approach in detail and illustrate its application to study brain white matter. Our results show that additional insights can be gained with the proposed analysis.
Grid-based electronic structure calculations: The tensor decomposition approach
Energy Technology Data Exchange (ETDEWEB)
Rakhuba, M.V., E-mail: rakhuba.m@gmail.com [Skolkovo Institute of Science and Technology, Novaya St. 100, 143025 Skolkovo, Moscow Region (Russian Federation); Oseledets, I.V., E-mail: i.oseledets@skoltech.ru [Skolkovo Institute of Science and Technology, Novaya St. 100, 143025 Skolkovo, Moscow Region (Russian Federation); Institute of Numerical Mathematics, Russian Academy of Sciences, Gubkina St. 8, 119333 Moscow (Russian Federation)
2016-05-01
We present a fully grid-based approach for solving Hartree–Fock and all-electron Kohn–Sham equations based on low-rank approximation of three-dimensional electron orbitals. Due to the low-rank structure the total complexity of the algorithm depends linearly with respect to the one-dimensional grid size. Linear complexity allows for the usage of fine grids, e.g. 8192{sup 3} and, thus, cheap extrapolation procedure. We test the proposed approach on closed-shell atoms up to the argon, several molecules and clusters of hydrogen atoms. All tests show systematical convergence with the required accuracy.
Structure of Pioncare covariant tensor operators in quantum mechanical models
International Nuclear Information System (INIS)
Polyzou, W.N.; Klink, W.H.
1988-01-01
The structure of operators that transform covariantly in Poincare invariant quantum mechanical models is analyzed. These operators are shown to have an interaction dependence that comes from the geometry of the Poincare group. The operators can be expressed in terms of matrix elements in a complete set of eigenstates of the mass and spin operators associated with the dynamical representation of the Poincare group. The matrix elements are factored into geometrical coefficients (Clebsch--Gordan coefficients for the Poincare group) and invariant matrix elements. The geometrical coefficients are fixed by the transformation properties of the operator and the eigenvalue spectrum of the mass and spin. The invariant matrix elements, which distinguish between different operators with the same transformation properties, are given in terms of a set of invariant form factors. copyright 1988 Academic Press, Inc
3D reconstruction of tensors and vectors
International Nuclear Information System (INIS)
Defrise, Michel; Gullberg, Grant T.
2005-01-01
Here we have developed formulations for the reconstruction of 3D tensor fields from planar (Radon) and line-integral (X-ray) projections of 3D vector and tensor fields. Much of the motivation for this work is the potential application of MRI to perform diffusion tensor tomography. The goal is to develop a theory for the reconstruction of both Radon planar and X-ray or line-integral projections because of the flexibility of MRI to obtain both of these type of projections in 3D. The development presented here for the linear tensor tomography problem provides insight into the structure of the nonlinear MRI diffusion tensor inverse problem. A particular application of tensor imaging in MRI is the potential application of cardiac diffusion tensor tomography for determining in vivo cardiac fiber structure. One difficulty in the cardiac application is the motion of the heart. This presents a need for developing future theory for tensor tomography in a motion field. This means developing a better understanding of the MRI signal for diffusion processes in a deforming media. The techniques developed may allow the application of MRI tensor tomography for the study of structure of fiber tracts in the brain, atherosclerotic plaque, and spine in addition to fiber structure in the heart. However, the relations presented are also applicable to other fields in medical imaging such as diffraction tomography using ultrasound. The mathematics presented can also be extended to exponential Radon transform of tensor fields and to other geometric acquisitions such as cone beam tomography of tensor fields
Colored Tensor Models - a Review
Directory of Open Access Journals (Sweden)
Razvan Gurau
2012-04-01
Full Text Available Colored tensor models have recently burst onto the scene as a promising conceptual and computational tool in the investigation of problems of random geometry in dimension three and higher. We present a snapshot of the cutting edge in this rapidly expanding research field. Colored tensor models have been shown to share many of the properties of their direct ancestor, matrix models, which encode a theory of fluctuating two-dimensional surfaces. These features include the possession of Feynman graphs encoding topological spaces, a 1/N expansion of graph amplitudes, embedded matrix models inside the tensor structure, a resumable leading order with critical behavior and a continuum large volume limit, Schwinger-Dyson equations satisfying a Lie algebra (akin to the Virasoro algebra in two dimensions, non-trivial classical solutions and so on. In this review, we give a detailed introduction of colored tensor models and pointers to current and future research directions.
Ialongo, S.; Cella, F.; Fedi, M.; Florio, G.
2011-12-01
Most geophysical inversion problems are characterized by a number of data considerably higher than the number of the unknown parameters. This corresponds to solve highly underdetermined systems. To get a unique solution, a priori information must be therefore introduced. We here analyze the inversion of the gravity gradient tensor (GGT). Previous approaches to invert jointly or independently more gradient components are by Li (2001) proposing an algorithm using a depth weighting function and Zhdanov et alii (2004), providing a well focused inversion of gradient data. Both the methods give a much-improved solution compared with the minimum length solution, which is invariably shallow and not representative of the true source distribution. For very undetermined problems, this feature is due to the role of the depth weighting matrices used by both the methods. Recently, Cella and Fedi (2011) showed however that for magnetic and gravity data the depth weighting function has to be defined carefully, under a preliminary application of Euler Deconvolution or Depth from Extreme Point methods, yielding the appropriate structural index and then using it as the rate decay of the weighting function. We therefore propose to extend this last approach to invert jointly or independently the GGT tensor using the structural index as weighting function rate decay. In case of a joint inversion, gravity data can be added as well. This multicomponent case is also relevant because the simultaneous use of several components and gravity increase the number of data and reduce the algebraic ambiguity compared to the inversion of a single component. The reduction of such ambiguity was shown in Fedi et al, (2005) decisive to get an improved depth resolution in inverse problems, independently from any form of depth weighting function. The method is demonstrated to synthetic cases and applied to real cases, such as the Vredefort impact area (South Africa), characterized by a complex density
Delineating Neural Structures of Developmental Human Brains with Diffusion Tensor Imaging
Directory of Open Access Journals (Sweden)
Hao Huang
2010-01-01
Full Text Available The human brain anatomy is characterized by dramatic structural changes during fetal development. It is extraordinarily complex and yet its origin is a simple tubular structure. Revealing detailed anatomy at different stages of brain development not only aids in understanding this highly ordered process, but also provides clues to detect abnormalities caused by genetic or environmental factors. However, anatomical studies of human brain development during the fetal period are surprisingly scarce and histology-based atlases have become available only recently. Diffusion tensor imaging (DTI measures water diffusion to delineate the underlying neural structures. The high contrasts derived from DTI can be used to establish the brain atlas. With DTI tractography, coherent neural structures, such as white matter tracts, can be three-dimensionally reconstructed. The primary eigenvector of the diffusion tensor can be further explored to characterize microstructures in the cerebral wall of the developmental brains. In this mini-review, the application of DTI in order to reveal the structures of developmental fetal brains has been reviewed in the above-mentioned aspects. The fetal brain DTI provides a unique insight for delineating the neural structures in both macroscopic and microscopic levels. The resultant DTI database will provide structural guidance for the developmental study of human fetal brains in basic neuroscience, and reference standards for diagnostic radiology of premature newborns.
Quaternionic contact Einstein structures and the quaternionic contact Yamabe problem
Ivanov, Stefan; Vassilev, Dimiter
2014-01-01
A partial solution of the quaternionic contact Yamabe problem on the quaternionic sphere is given. It is shown that the torsion of the Biquard connection vanishes exactly when the trace-free part of the horizontal Ricci tensor of the Biquard connection is zero and this occurs precisely on 3-Sasakian manifolds. All conformal transformations sending the standard flat torsion-free quaternionic contact structure on the quaternionic Heisenberg group to a quaternionic contact structure with vanishing torsion of the Biquard connection are explicitly described. A "3-Hamiltonian form" of infinitesimal conformal automorphisms of quaternionic contact structures is presented.
TensorLy: Tensor Learning in Python
Kossaifi, Jean; Panagakis, Yannis; Pantic, Maja
2016-01-01
Tensors are higher-order extensions of matrices. While matrix methods form the cornerstone of machine learning and data analysis, tensor methods have been gaining increasing traction. However, software support for tensor operations is not on the same footing. In order to bridge this gap, we have developed \\emph{TensorLy}, a high-level API for tensor methods and deep tensorized neural networks in Python. TensorLy aims to follow the same standards adopted by the main projects of the Python scie...
Iterative tensor voting for perceptual grouping of ill-defined curvilinear structures.
Loss, Leandro A; Bebis, George; Parvin, Bahram
2011-08-01
In this paper, a novel approach is proposed for perceptual grouping and localization of ill-defined curvilinear structures. Our approach builds upon the tensor voting and the iterative voting frameworks. Its efficacy lies on iterative refinements of curvilinear structures by gradually shifting from an exploratory to an exploitative mode. Such a mode shifting is achieved by reducing the aperture of the tensor voting fields, which is shown to improve curve grouping and inference by enhancing the concentration of the votes over promising, salient structures. The proposed technique is validated on delineating adherens junctions that are imaged through fluorescence microscopy. However, the method is also applicable for screening other organisms based on characteristics of their cell wall structures. Adherens junctions maintain tissue structural integrity and cell-cell interactions. Visually, they exhibit fibrous patterns that may be diffused, heterogeneous in fluorescence intensity, or punctate and frequently perceptual. Besides the application to real data, the proposed method is compared to prior methods on synthetic and annotated real data, showing high precision rates.
Stability of cosmic structures in scalar-tensor theories of gravity
Energy Technology Data Exchange (ETDEWEB)
Panotopoulos, Grigoris [Universidade de Lisboa, Centro Multidisciplinar de Astrofisica, Instituto Superior Tecnico, Lisbon (Portugal); Rincon, Angel [Pontificia Universidad Catolica de Chile, Instituto de Fisica, Santiago (Chile)
2018-01-15
In the present work we study a concrete model of scalar-tensor theory of gravity characterized by two free parameters, and we compare its predictions to observational data and constraints coming from supernovae, solar system tests and the stability of cosmic structures. First an exact analytical solution at the background level is obtained. Using that solution the expression for the turnaround radius is computed. Finally we show graphically how current data and limits put bounds on the parameters of the model at hand. (orig.)
Gauvin, Laetitia; Panisson, André; Cattuto, Ciro
2014-01-01
The increasing availability of temporal network data is calling for more research on extracting and characterizing mesoscopic structures in temporal networks and on relating such structure to specific functions or properties of the system. An outstanding challenge is the extension of the results achieved for static networks to time-varying networks, where the topological structure of the system and the temporal activity patterns of its components are intertwined. Here we investigate the use of a latent factor decomposition technique, non-negative tensor factorization, to extract the community-activity structure of temporal networks. The method is intrinsically temporal and allows to simultaneously identify communities and to track their activity over time. We represent the time-varying adjacency matrix of a temporal network as a three-way tensor and approximate this tensor as a sum of terms that can be interpreted as communities of nodes with an associated activity time series. We summarize known computational techniques for tensor decomposition and discuss some quality metrics that can be used to tune the complexity of the factorized representation. We subsequently apply tensor factorization to a temporal network for which a ground truth is available for both the community structure and the temporal activity patterns. The data we use describe the social interactions of students in a school, the associations between students and school classes, and the spatio-temporal trajectories of students over time. We show that non-negative tensor factorization is capable of recovering the class structure with high accuracy. In particular, the extracted tensor components can be validated either as known school classes, or in terms of correlated activity patterns, i.e., of spatial and temporal coincidences that are determined by the known school activity schedule. PMID:24497935
Exterior domain problems and decomposition of tensor fields in weighted Sobolev spaces
Schwarz, Günter
1996-01-01
The Hodge decompOsition is a useful tool for tensor analysis on compact manifolds with boundary. This paper aims at generalising the decomposition to exterior domains G ⊂ IR n. Let L 2a Ω k(G) be the space weighted square integrable differential forms with weight function (1 + |χ|²)a, let d a be the weighted perturbation of the exterior derivative and δ a its adjoint. Then L 2a Ω k(G) splits into the orthogonal sum of the subspaces of the d a-exact forms with vanishi...
Seely, Jeffrey S; Kaufman, Matthew T; Ryu, Stephen I; Shenoy, Krishna V; Cunningham, John P; Churchland, Mark M
2016-11-01
Cortical firing rates frequently display elaborate and heterogeneous temporal structure. One often wishes to compute quantitative summaries of such structure-a basic example is the frequency spectrum-and compare with model-based predictions. The advent of large-scale population recordings affords the opportunity to do so in new ways, with the hope of distinguishing between potential explanations for why responses vary with time. We introduce a method that assesses a basic but previously unexplored form of population-level structure: when data contain responses across multiple neurons, conditions, and times, they are naturally expressed as a third-order tensor. We examined tensor structure for multiple datasets from primary visual cortex (V1) and primary motor cortex (M1). All V1 datasets were 'simplest' (there were relatively few degrees of freedom) along the neuron mode, while all M1 datasets were simplest along the condition mode. These differences could not be inferred from surface-level response features. Formal considerations suggest why tensor structure might differ across modes. For idealized linear models, structure is simplest across the neuron mode when responses reflect external variables, and simplest across the condition mode when responses reflect population dynamics. This same pattern was present for existing models that seek to explain motor cortex responses. Critically, only dynamical models displayed tensor structure that agreed with the empirical M1 data. These results illustrate that tensor structure is a basic feature of the data. For M1 the tensor structure was compatible with only a subset of existing models.
Directory of Open Access Journals (Sweden)
Jeffrey S Seely
2016-11-01
Full Text Available Cortical firing rates frequently display elaborate and heterogeneous temporal structure. One often wishes to compute quantitative summaries of such structure-a basic example is the frequency spectrum-and compare with model-based predictions. The advent of large-scale population recordings affords the opportunity to do so in new ways, with the hope of distinguishing between potential explanations for why responses vary with time. We introduce a method that assesses a basic but previously unexplored form of population-level structure: when data contain responses across multiple neurons, conditions, and times, they are naturally expressed as a third-order tensor. We examined tensor structure for multiple datasets from primary visual cortex (V1 and primary motor cortex (M1. All V1 datasets were 'simplest' (there were relatively few degrees of freedom along the neuron mode, while all M1 datasets were simplest along the condition mode. These differences could not be inferred from surface-level response features. Formal considerations suggest why tensor structure might differ across modes. For idealized linear models, structure is simplest across the neuron mode when responses reflect external variables, and simplest across the condition mode when responses reflect population dynamics. This same pattern was present for existing models that seek to explain motor cortex responses. Critically, only dynamical models displayed tensor structure that agreed with the empirical M1 data. These results illustrate that tensor structure is a basic feature of the data. For M1 the tensor structure was compatible with only a subset of existing models.
Structure of the Einstein tensor for class-1 embedded space time
Energy Technology Data Exchange (ETDEWEB)
Krause, J [Universidad Central de Venezuela, Caracas
1976-04-11
Continuing previous work, some features of the flat embedding theory of class-1 curved space-time are further discussed. In the two-metric formalism provided by the embedding approach the Gauss tensor obtains as the flat-covariant gradient of a fundamental vector potential. The Einstein tensor is then examined in terms of the Gauss tensor. It is proved that the Einstein tensor is divergence free in flat space-time, i.e. a true Lorentz-covariant conservation law for the Einstein tensor is shown to hold. The form of the Einstein tensor in flat space-time also appears as a canonical energy-momentum tensor of the vector potential. The corresponding Lagrangian density, however, does not provide us with a set of field equations for the fundamental vector potential; indeed, the Euler-Lagrange ''equations'' collapse to a useless identity, while the Lagrangian density has the form of a flat divergence.
Entanglement beyond tensor product structure: algebraic aspects of quantum non-separability
International Nuclear Information System (INIS)
Derkacz, Łukasz; Gwóźdź, Marek; Jakóbczyk, Lech
2012-01-01
An algebraic approach to quantum non-separability is applied to the case of two qubits. It is based on the partition of the algebra of observables into independent subalgebras and the tensor product structure of the Hilbert space is not exploited. Even in this simple case, such a general formulation has some advantages. Using algebraic formalism, we can explicitly show the relativity of the notion of entanglement to the observables measured in the system and characterize separable and non-separable pure states. As a universal measure of non-separability of pure states, we propose to take the so-called total correlation. This quantity depends on the state as well as on the algebraic partition. Its numerical value is given by the norm of the corresponding correlation matrix. (paper)
Effect of cocaine on structural changes in brain: MRI volumetry using tensor-based morphometry.
Narayana, Ponnada A; Datta, Sushmita; Tao, Guozhi; Steinberg, Joel L; Moeller, F Gerard
2010-10-01
Magnetic resonance imaging (MRI) was performed in cocaine-dependent subjects to determine the structural changes in brain compared to non-drug using controls. Cocaine-dependent subjects and controls were carefully screened to rule out brain pathology of undetermined origin. Magnetic resonance images were analyzed using tensor-based morphometry (TBM) and voxel-based morphometry (VBM) without and with modulation to adjust for volume changes during normalization. For TBM analysis, unbiased atlases were generated using two different inverse consistent and diffeomorphic nonlinear registration techniques. Two different control groups were used for generating unbiased atlases. Independent of the nonlinear registration technique and normal cohorts used for creating the unbiased atlases, our analysis failed to detect any statistically significant effect of cocaine on brain volumes. These results show that cocaine-dependent subjects do not show differences in regional brain volumes compared to non-drug using controls. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.
Categorical Tensor Network States
Directory of Open Access Journals (Sweden)
Jacob D. Biamonte
2011-12-01
Full Text Available We examine the use of string diagrams and the mathematics of category theory in the description of quantum states by tensor networks. This approach lead to a unification of several ideas, as well as several results and methods that have not previously appeared in either side of the literature. Our approach enabled the development of a tensor network framework allowing a solution to the quantum decomposition problem which has several appealing features. Specifically, given an n-body quantum state |ψ〉, we present a new and general method to factor |ψ〉 into a tensor network of clearly defined building blocks. We use the solution to expose a previously unknown and large class of quantum states which we prove can be sampled efficiently and exactly. This general framework of categorical tensor network states, where a combination of generic and algebraically defined tensors appear, enhances the theory of tensor network states.
Kowalczyk, Natalia; Shi, Feng; Magnuski, Mikolaj; Skorko, Maciek; Dobrowolski, Pawel; Kossowski, Bartosz; Marchewka, Artur; Bielecki, Maksymilian; Kossut, Malgorzata; Brzezicka, Aneta
2018-06-20
Experienced video game players exhibit superior performance in visuospatial cognition when compared to non-players. However, very little is known about the relation between video game experience and structural brain plasticity. To address this issue, a direct comparison of the white matter brain structure in RTS (real time strategy) video game players (VGPs) and non-players (NVGPs) was performed. We hypothesized that RTS experience can enhance connectivity within and between occipital and parietal regions, as these regions are likely to be involved in the spatial and visual abilities that are trained while playing RTS games. The possible influence of long-term RTS game play experience on brain structural connections was investigated using diffusion tensor imaging (DTI) and a region of interest (ROI) approach in order to describe the experience-related plasticity of white matter. Our results revealed significantly more total white matter connections between occipital and parietal areas and within occipital areas in RTS players compared to NVGPs. Additionally, the RTS group had an altered topological organization of their structural network, expressed in local efficiency within the occipito-parietal subnetwork. Furthermore, the positive association between network metrics and time spent playing RTS games suggests a close relationship between extensive, long-term RTS game play and neuroplastic changes. These results indicate that long-term and extensive RTS game experience induces alterations along axons that link structures of the occipito-parietal loop involved in spatial and visual processing. © 2018 Wiley Periodicals, Inc.
Colom, Roberto; Hua, Xue; Martínez, Kenia; Burgaleta, Miguel; Román, Francisco J; Gunter, Jeffrey L; Carmona, Susanna; Jaeggi, Susanne M; Thompson, Paul M
2016-10-01
Tensor-Based Morphometry (TBM) allows the automatic mapping of brain changes across time building 3D deformation maps. This technique has been applied for tracking brain degeneration in Alzheimer's and other neurodegenerative diseases with high sensitivity and reliability. Here we applied TBM to quantify changes in brain structure after completing a challenging adaptive cognitive training program based on the n-back task. Twenty-six young women completed twenty-four training sessions across twelve weeks and they showed, on average, large cognitive improvements. High-resolution MRI scans were obtained before and after training. The computed longitudinal deformation maps were analyzed for answering three questions: (a) Are there differential brain structural changes in the training group as compared with a matched control group? (b) Are these changes related to performance differences in the training program? (c) Are standardized changes in a set of psychological factors (fluid and crystallized intelligence, working memory, and attention control) measured before and after training, related to structural changes in the brain? Results showed (a) greater structural changes for the training group in the temporal lobe, (b) a negative correlation between these changes and performance across training sessions (the greater the structural change, the lower the cognitive performance improvements), and (c) negligible effects regarding the psychological factors measured before and after training. Copyright © 2016 Elsevier Ltd. All rights reserved.
The Topology of Three-Dimensional Symmetric Tensor Fields
Lavin, Yingmei; Levy, Yuval; Hesselink, Lambertus
1994-01-01
We study the topology of 3-D symmetric tensor fields. The goal is to represent their complex structure by a simple set of carefully chosen points and lines analogous to vector field topology. The basic constituents of tensor topology are the degenerate points, or points where eigenvalues are equal to each other. First, we introduce a new method for locating 3-D degenerate points. We then extract the topological skeletons of the eigenvector fields and use them for a compact, comprehensive description of the tensor field. Finally, we demonstrate the use of tensor field topology for the interpretation of the two-force Boussinesq problem.
Paniagua, Beatriz; Ehlers, Cindy; Crews, Fulton; Budin, Francois; Larson, Garrett; Styner, Martin; Oguz, Ipek
2011-03-01
Understanding the effects of adolescent binge drinking that persist into adulthood is a crucial public health issue. Adolescent intermittent ethanol exposure (AIE) is an animal model that can be used to investigate these effects in rodents. In this work, we investigate the application of a particular image analysis technique, tensor-based morphometry, for detecting anatomical differences between AIE and control rats using Diffusion Tensor Imaging (DTI). Deformation field analysis is a popular method for detecting volumetric changes analyzing Jacobian determinants calculated on deformation fields. Recent studies showed that computing deformation field metrics on the full deformation tensor, often referred to as tensor-based morphometry (TBM), increases the sensitivity to anatomical differences. In this paper we conduct a comprehensive TBM study for precisely locating differences between control and AIE rats. Using a DTI RARE sequence designed for minimal geometric distortion, 12-directional images were acquired postmortem for control and AIE rats (n=9). After preprocessing, average images for the two groups were constructed using an unbiased atlas building approach. We non-rigidly register the two atlases using Large Deformation Diffeomorphic Metric Mapping, and analyze the resulting deformation field using TBM. In particular, we evaluate the tensor determinant, geodesic anisotropy, and deformation direction vector (DDV) on the deformation field to detect structural differences. This yields data on the local amount of growth, shrinkage and the directionality of deformation between the groups. We show that TBM can thus be used to measure group morphological differences between rat populations, demonstrating the potential of the proposed framework.
Tensor gauge condition and tensor field decomposition
Zhu, Ben-Chao; Chen, Xiang-Song
2015-10-01
We discuss various proposals of separating a tensor field into pure-gauge and gauge-invariant components. Such tensor field decomposition is intimately related to the effort of identifying the real gravitational degrees of freedom out of the metric tensor in Einstein’s general relativity. We show that as for a vector field, the tensor field decomposition has exact correspondence to and can be derived from the gauge-fixing approach. The complication for the tensor field, however, is that there are infinitely many complete gauge conditions in contrast to the uniqueness of Coulomb gauge for a vector field. The cause of such complication, as we reveal, is the emergence of a peculiar gauge-invariant pure-gauge construction for any gauge field of spin ≥ 2. We make an extensive exploration of the complete tensor gauge conditions and their corresponding tensor field decompositions, regarding mathematical structures, equations of motion for the fields and nonlinear properties. Apparently, no single choice is superior in all aspects, due to an awkward fact that no gauge-fixing can reduce a tensor field to be purely dynamical (i.e. transverse and traceless), as can the Coulomb gauge in a vector case.
Formalev, V. F.; Kolesnik, S. A.
2017-11-01
The authors are the first to present a closed procedure for numerical solution of inverse coefficient problems of heat conduction in anisotropic materials used as heat-shielding ones in rocket and space equipment. The reconstructed components of the thermal-conductivity tensor depend on temperature (are nonlinear). The procedure includes the formation of experimental data, the implicit gradient-descent method, the economical absolutely stable method of numerical solution of parabolic problems containing mixed derivatives, the parametric identification, construction, and numerical solution of the problem for elements of sensitivity matrices, the development of a quadratic residual functional and regularizing functionals, and also the development of algorithms and software systems. The implicit gradient-descent method permits expanding the quadratic functional in a Taylor series with retention of the linear terms for the increments of the sought functions. This substantially improves the exactness and stability of solution of the inverse problems. Software systems are developed with account taken of the errors in experimental data and disregarding them. On the basis of a priori assumptions of the qualitative behavior of the functional dependences of the components of the thermal-conductivity tensor on temperature, regularizing functionals are constructed by means of which one can reconstruct the components of the thermal-conductivity tensor with an error no higher than the error of the experimental data. Results of the numerical solution of the inverse coefficient problems on reconstruction of nonlinear components of the thermal-conductivity tensor have been obtained and are discussed.
Cartesian tensors an introduction
Temple, G
2004-01-01
This undergraduate text provides an introduction to the theory of Cartesian tensors, defining tensors as multilinear functions of direction, and simplifying many theorems in a manner that lends unity to the subject. The author notes the importance of the analysis of the structure of tensors in terms of spectral sets of projection operators as part of the very substance of quantum theory. He therefore provides an elementary discussion of the subject, in addition to a view of isotropic tensors and spinor analysis within the confines of Euclidean space. The text concludes with an examination of t
Tu, Ye; Yu, Tian; Wei, Yongxu; Sun, Kun; Zhao, Weiguo; Yu, Buwei
2016-02-01
Hemifacial spasm (HFS) is characterized by involuntary, irregular clonic or tonic movement of muscles innervated by the facial nerve. We evaluated structural reorganization in brain gray matter and white matter and whether neuroplasticity is linked to clinical features in HFS patients. High-resolution structural magnetic resonance imaging and diffusion tensor imaging data were acquired by 3.0 T MRI from 42 patients with HFS and 30 healthy subjects. The severity of the spasm was assessed according to Jankovic disability rating scale. Voxel-based morphometry (VBM) and tract-based spatial statistics (TBSS) analysis were performed to identify regional grey matter volume (GMV) changes and whole-brain microstructural integrity disruption measured by fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD). The VBM analysis showed that patients with HFS reduced GMV in the right inferior parietal lobule and increased GMV in the cerebellar lobule VIII, when compared with healthy subjects. Furthermore, within the HFS disease group, GMV decreased with the disease duration in the right inferior parietal lobule. TBSS did not identify group differences in diffusivity parameters. While no white matter integrity disruption was detected in the brain of patients with HFS, our study identified evident GMV changes in brain areas which were known to be involved in motor control. Our results suggest that HFS, a chronic neurovascular conflict disease, is related to structural reorganization in the brain. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Long, Zhiliang; Duan, Xujun; Xie, Bing; Du, Handan; Li, Rong; Xu, Qiang; Wei, Luqing; Zhang, Shao-xiang; Wu, Yi; Gao, Qing; Chen, Huafu
2013-09-25
Post-traumatic stress disorder (PTSD) is characterized by dysfunction of several discrete brain regions such as medial prefrontal gyrus with hypoactivation and amygdala with hyperactivation. However, alterations of large-scale whole brain topological organization of structural networks remain unclear. Seventeen patients with PTSD in motor vehicle accident survivors and 15 normal controls were enrolled in our study. Large-scale structural connectivity network (SCN) was constructed using diffusion tensor tractography, followed by thresholding the mean factional anisotropy matrix of 90 brain regions. Graph theory analysis was then employed to investigate their aberrant topological properties. Both patient and control group showed small-world topology in their SCNs. However, patients with PTSD exhibited abnormal global properties characterized by significantly decreased characteristic shortest path length and normalized characteristic shortest path length. Furthermore, the patient group showed enhanced nodal centralities predominately in salience network including bilateral anterior cingulate and pallidum, and hippocampus/parahippocamus gyrus, and decreased nodal centralities mainly in medial orbital part of superior frontal gyrus. The main limitation of this study is the small sample of PTSD patients, which may lead to decrease the statistic power. Consequently, this study should be considered an exploratory analysis. These results are consistent with the notion that PTSD can be understood by investigating the dysfunction of large-scale, spatially distributed neural networks, and also provide structural evidences for further exploration of neurocircuitry models in PTSD. © 2013 Elsevier B.V. All rights reserved.
di Lauro, C.
2018-03-01
Transformations of vector or tensor properties from a space-fixed to a molecule-fixed axis system are often required in the study of rotating molecules. Spherical components λμ,ν of a first rank irreducible tensor can be obtained from the direction cosines between the two axis systems, and a second rank tensor with spherical components λμ,ν(2) can be built from the direct product λ × λ. It is shown that the treatment of the interaction between molecular rotation and the electric quadrupole of a nucleus is greatly simplified, if the coefficients in the axis-system transformation of the gradient of the electric field of the outer charges at the coupled nucleus are arranged as spherical components λμ,ν(2). Then the reduced matrix elements of the field gradient operators in a symmetric top eigenfunction basis, including their dependence on the molecule-fixed z-angular momentum component k, can be determined from the knowledge of those of λ(2) . The hyperfine structure Hamiltonian Hq is expressed as the sum of terms characterized each by a value of the molecule-fixed index ν, whose matrix elements obey the rule Δk = ν. Some of these terms may vanish because of molecular symmetry, and the specific cases of linear and symmetric top molecules, orthorhombic molecules, and molecules with symmetry lower than orthorhombic are considered. Each ν-term consists of a contraction of the rotational tensor λ(2) and the nuclear quadrupole tensor in the space-fixed frame, and its matrix elements in the rotation-nuclear spin coupled representation can be determined by the standard spherical tensor methods.
A Review of Tensors and Tensor Signal Processing
Cammoun, L.; Castaño-Moraga, C. A.; Muñoz-Moreno, E.; Sosa-Cabrera, D.; Acar, B.; Rodriguez-Florido, M. A.; Brun, A.; Knutsson, H.; Thiran, J. P.
Tensors have been broadly used in mathematics and physics, since they are a generalization of scalars or vectors and allow to represent more complex properties. In this chapter we present an overview of some tensor applications, especially those focused on the image processing field. From a mathematical point of view, a lot of work has been developed about tensor calculus, which obviously is more complex than scalar or vectorial calculus. Moreover, tensors can represent the metric of a vector space, which is very useful in the field of differential geometry. In physics, tensors have been used to describe several magnitudes, such as the strain or stress of materials. In solid mechanics, tensors are used to define the generalized Hooke’s law, where a fourth order tensor relates the strain and stress tensors. In fluid dynamics, the velocity gradient tensor provides information about the vorticity and the strain of the fluids. Also an electromagnetic tensor is defined, that simplifies the notation of the Maxwell equations. But tensors are not constrained to physics and mathematics. They have been used, for instance, in medical imaging, where we can highlight two applications: the diffusion tensor image, which represents how molecules diffuse inside the tissues and is broadly used for brain imaging; and the tensorial elastography, which computes the strain and vorticity tensor to analyze the tissues properties. Tensors have also been used in computer vision to provide information about the local structure or to define anisotropic image filters.
Aye, Tandy; Barnea-Goraly, Naama; Ambler, Christian; Hoang, Sherry; Schleifer, Kristin; Park, Yaena; Drobny, Jessica; Wilson, Darrell M.; Reiss, Allan L.; Buckingham, Bruce A.
2012-01-01
OBJECTIVE To detect clinical correlates of cognitive abilities and white matter (WM) microstructural changes using diffusion tensor imaging (DTI) in young children with type 1 diabetes. RESEARCH DESIGN AND METHODS Children, ages 3 to <10 years, with type 1 diabetes (n = 22) and age- and sex-matched healthy control subjects (n = 14) completed neurocognitive testing and DTI scans. RESULTS Compared with healthy controls, children with type 1 diabetes had lower axial diffusivity (AD) values (P = 0.046) in the temporal and parietal lobe regions. There were no significant differences between groups in fractional anisotropy and radial diffusivity (RD). Within the diabetes group, there was a significant, positive correlation between time-weighted HbA1c and RD (P = 0.028). A higher, time-weighted HbA1c value was significantly correlated with lower overall intellectual functioning measured by the full-scale intelligence quotient (P = 0.03). CONCLUSIONS Children with type 1 diabetes had significantly different WM structure (as measured by AD) when compared with controls. In addition, WM structural differences (as measured by RD) were significantly correlated with their HbA1c values. Additional studies are needed to determine if WM microstructural differences in young children with type 1 diabetes predict future neurocognitive outcome. PMID:22966090
A vorticity based approach to handle the fluid-structure interaction problems
Energy Technology Data Exchange (ETDEWEB)
Farahbakhsh, Iman; Ghassemi, Hassan [Department of Ocean Engineering, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of); Sabetghadam, Fereidoun, E-mail: i.farahbakhsh@aut.ac.ir [Mechanical and Aerospace Engineering Department, Science and Research Branch, Islamic Azad University (IAU), Tehran (Iran, Islamic Republic of)
2016-02-15
A vorticity based approach for the numerical solution of the fluid-structure interaction problems is introduced in which the fluid and structure(s) can be viewed as a continuum. Retrieving the vorticity field and recalculating a solenoidal velocity field, specially at the fluid-structure interface, are the kernel of the proposed algorithm. In the suggested method, a variety of constitutive equations as a function of left Cauchy–Green deformation tensor can be applied for modeling the structure domain. A nonlinear Mooney–Rivlin and Saint Venant–Kirchhoff model are expressed in terms of the left Cauchy–Green deformation tensor and the presented method is able to model the behavior of a visco-hyperelastic structure in the incompressible flow. Some numerical experiments, with considering the neo-Hookean model for structure domain, are executed and the results are validated via the available results from literature. (paper)
Ueda, Ryo; Yamada, Naoki; Kakuda, Wataru; Abo, Masahiro; Senoo, Atsushi
2016-03-15
Fractional anisotropy has been used in many studies that examined post-stroke changes in white matter. This study was performed to clarify cerebral white matter changes after stroke using generalized fractional anisotropy (GFA). White matter structure was visualized using diffusion tensor imaging in 72 patients with post-stroke arm paralysis. Exercise-related brain regions were examined in cerebral white matter using GFA. The relationship between GFA and clinical characteristics was examined. Overall, the mean GFA of the lesioned hemisphere was significantly lower than that of the non-lesioned hemisphere (PBrodmann area 5 of the non-lesioned hemisphere. Age correlated negatively with GFA in Brodmann areas 5 and 7 of the lesioned hemisphere. Though these results may be due to a decrease in the frequency of use of the paralyzed limb over time, GFA overall was significantly and negatively affected by the subject's age. The GFA values of patients with paralysis of the dominant hand were significantly different from those of patients with paralysis of the nondominant hand in Brodmann areas 4 and 6 of the non-lesioned hemisphere and Brodmann area 4 of the lesioned hemisphere (P<0.05). The stroke size and location were not associated with GFA differences. Differences between the GFA of the lesioned and non-lesioned hemispheres varied depending on the affected brain region, age at onset of paralysis, and paralysis of the dominant or non-dominant hand. Copyright © 2016 Elsevier B.V. All rights reserved.
Kim, Junghoon; Avants, Brian; Patel, Sunil; Whyte, John; Coslett, H. Branch; Pluta, John; Detre, John A.; Gee, James C.
2008-01-01
Traumatic brain injury (TBI) is one of the most common causes of long-term disability. Despite the importance of identifying neuropathology in individuals with chronic TBI, methodological challenges posed at the stage of inter-subject image registration have hampered previous voxel-based MRI studies from providing a clear pattern of structural atrophy after TBI. We used a novel symmetric diffeomorphic image normalization method to conduct a tensor-based morphometry (TBM) study of TBI. The key advantage of this method is that it simultaneously estimates an optimal template brain and topology preserving deformations between this template and individual subject brains. Detailed patterns of atrophies are then revealed by statistically contrasting control and subject deformations to the template space. Participants were 29 survivors of TBI and 20 control subjects who were matched in terms of age, gender, education, and ethnicity. Localized volume losses were found most prominently in white matter regions and the subcortical nuclei including the thalamus, the midbrain, the corpus callosum, the mid- and posterior cingulate cortices, and the caudate. Significant voxel-wise volume loss clusters were also detected in the cerebellum and the frontal/temporal neocortices. Volume enlargements were identified largely in ventricular regions. A similar pattern of results was observed in a subgroup analysis where we restricted our analysis to the 17 TBI participants who had no macroscopic focal lesions (total lesion volume> 1.5 cm 3). The current study confirms, extends, and partly challenges previous structural MRI studies in chronic TBI. By demonstrating that a large deformation image registration technique can be successfully combined with TBM to identify TBI-induced diffuse structural changes with greater precision, our approach is expected to increase the sensitivity of future studies examining brain-behavior relationships in the TBI population. PMID:17999940
Tensor surgery and tensor rank
M. Christandl (Matthias); J. Zuiddam (Jeroen)
2018-01-01
textabstractWe introduce a method for transforming low-order tensors into higher-order tensors and apply it to tensors defined by graphs and hypergraphs. The transformation proceeds according to a surgery-like procedure that splits vertices, creates and absorbs virtual edges and inserts new vertices
Tensor surgery and tensor rank
M. Christandl (Matthias); J. Zuiddam (Jeroen)
2016-01-01
textabstractWe introduce a method for transforming low-order tensors into higher-order tensors and apply it to tensors defined by graphs and hypergraphs. The transformation proceeds according to a surgery-like procedure that splits vertices, creates and absorbs virtual edges and inserts new
Structures and Nuclear Quadrupole Coupling Tensors of a Series of Chlorine-Containing Hydrocarbons
Dikkumbura, Asela S.; Webster, Erica R.; Dorris, Rachel E.; Peebles, Rebecca A.; Peebles, Sean A.; Seifert, Nathan A.; Pate, Brooks
2016-06-01
Rotational spectra for gauche-1,2-dichloroethane (12DCE), gauche-1-chloro-2-fluoroethane (1C2FE) and both anti- and gauche-2,3-dichloropropene (23DCP) have been observed using chirped-pulse Fourier-transform microwave (FTMW) spectroscopy in the 6-18 GHz region. Although the anti conformers for all three species are predicted to be more stable than the gauche forms, they are nonpolar (12DCE) or nearly nonpolar (predicted dipole components for anti-1C2FE: μ_a = 0.11 D, μ_b = 0.02 D and for anti-23DCP: μ_a = 0.25 D, μ_b = 0.02 D); nevertheless, it was also possible to observe and assign the spectrum of anti-23DCP. Assignments of parent spectra and 37Cl and 13C substituted isotopologues utilized predictions at the MP2/6-311++G(2d,2p) level and Pickett's SPCAT/SPFIT programs. For the weak anti-23DCP spectra, additional measurements also utilized a resonant-cavity FTMW spectrometer. Full chlorine nuclear quadrupole coupling tensors for gauche-12DCE and both anti- and gauche-23DCP have been diagonalized to allow comparison of coupling constants. Kraitchman's equations were used to determine r_s coordinates of isotopically substituted atoms and r_0 structures were also deduced for gauche conformers of 12DCE and 1C2FE. Structural details and chlorine nuclear quadrupole coupling constants of all three molecules will be compared, and effects of differing halogen substitution and carbon chain length on molecular properties will be evaluated.
Energy Technology Data Exchange (ETDEWEB)
Zeng, Dong; Zhang, Xinyu; Bian, Zhaoying, E-mail: zybian@smu.edu.cn, E-mail: jhma@smu.edu.cn; Huang, Jing; Zhang, Hua; Lu, Lijun; Lyu, Wenbing; Feng, Qianjin; Chen, Wufan; Ma, Jianhua, E-mail: zybian@smu.edu.cn, E-mail: jhma@smu.edu.cn [Department of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong 510515, China and Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, Guangdong 510515 (China); Zhang, Jing [Department of Radiology, Tianjin Medical University General Hospital, Tianjin 300052 (China)
2016-05-15
Purpose: Cerebral perfusion computed tomography (PCT) imaging as an accurate and fast acute ischemic stroke examination has been widely used in clinic. Meanwhile, a major drawback of PCT imaging is the high radiation dose due to its dynamic scan protocol. The purpose of this work is to develop a robust perfusion deconvolution approach via structure tensor total variation (STV) regularization (PD-STV) for estimating an accurate residue function in PCT imaging with the low-milliampere-seconds (low-mAs) data acquisition. Methods: Besides modeling the spatio-temporal structure information of PCT data, the STV regularization of the present PD-STV approach can utilize the higher order derivatives of the residue function to enhance denoising performance. To minimize the objective function, the authors propose an effective iterative algorithm with a shrinkage/thresholding scheme. A simulation study on a digital brain perfusion phantom and a clinical study on an old infarction patient were conducted to validate and evaluate the performance of the present PD-STV approach. Results: In the digital phantom study, visual inspection and quantitative metrics (i.e., the normalized mean square error, the peak signal-to-noise ratio, and the universal quality index) assessments demonstrated that the PD-STV approach outperformed other existing approaches in terms of the performance of noise-induced artifacts reduction and accurate perfusion hemodynamic maps (PHM) estimation. In the patient data study, the present PD-STV approach could yield accurate PHM estimation with several noticeable gains over other existing approaches in terms of visual inspection and correlation analysis. Conclusions: This study demonstrated the feasibility and efficacy of the present PD-STV approach in utilizing STV regularization to improve the accuracy of residue function estimation of cerebral PCT imaging in the case of low-mAs.
Directory of Open Access Journals (Sweden)
Yu Sun
Full Text Available Sexual dimorphism in the brain maturation during childhood and adolescence has been repeatedly documented, which may underlie the differences in behaviors and cognitive performance. However, our understanding of how gender modulates the development of structural connectome in healthy adults is still not entirely clear. Here we utilized graph theoretical analysis of longitudinal diffusion tensor imaging data over a five-year period to investigate the progressive gender differences of brain network topology. The brain networks of both genders showed prominent economical "small-world" architecture (high local clustering and short paths between nodes. Additional analysis revealed a more economical "small-world" architecture in females as well as a greater global efficiency in males regardless of scan time point. At the regional level, both increased and decreased efficiency were found across the cerebral cortex for both males and females, indicating a compensation mechanism of cortical network reorganization over time. Furthermore, we found that weighted clustering coefficient exhibited significant gender-time interactions, implying different development trends between males and females. Moreover, several specific brain regions (e.g., insula, superior temporal gyrus, cuneus, putamen, and parahippocampal gyrus exhibited different development trajectories between males and females. Our findings further prove the presence of sexual dimorphism in brain structures that may underlie gender differences in behavioral and cognitive functioning. The sex-specific progress trajectories in brain connectome revealed in this work provide an important foundation to delineate the gender related pathophysiological mechanisms in various neuropsychiatric disorders, which may potentially guide the development of sex-specific treatments for these devastating brain disorders.
Sun, Yu; Lee, Renick; Chen, Yu; Collinson, Simon; Thakor, Nitish; Bezerianos, Anastasios; Sim, Kang
2015-01-01
Sexual dimorphism in the brain maturation during childhood and adolescence has been repeatedly documented, which may underlie the differences in behaviors and cognitive performance. However, our understanding of how gender modulates the development of structural connectome in healthy adults is still not entirely clear. Here we utilized graph theoretical analysis of longitudinal diffusion tensor imaging data over a five-year period to investigate the progressive gender differences of brain network topology. The brain networks of both genders showed prominent economical "small-world" architecture (high local clustering and short paths between nodes). Additional analysis revealed a more economical "small-world" architecture in females as well as a greater global efficiency in males regardless of scan time point. At the regional level, both increased and decreased efficiency were found across the cerebral cortex for both males and females, indicating a compensation mechanism of cortical network reorganization over time. Furthermore, we found that weighted clustering coefficient exhibited significant gender-time interactions, implying different development trends between males and females. Moreover, several specific brain regions (e.g., insula, superior temporal gyrus, cuneus, putamen, and parahippocampal gyrus) exhibited different development trajectories between males and females. Our findings further prove the presence of sexual dimorphism in brain structures that may underlie gender differences in behavioral and cognitive functioning. The sex-specific progress trajectories in brain connectome revealed in this work provide an important foundation to delineate the gender related pathophysiological mechanisms in various neuropsychiatric disorders, which may potentially guide the development of sex-specific treatments for these devastating brain disorders.
Marami, Bahram; Mohseni Salehi, Seyed Sadegh; Afacan, Onur; Scherrer, Benoit; Rollins, Caitlin K; Yang, Edward; Estroff, Judy A; Warfield, Simon K; Gholipour, Ali
2017-08-01
Diffusion weighted magnetic resonance imaging, or DWI, is one of the most promising tools for the analysis of neural microstructure and the structural connectome of the human brain. The application of DWI to map early development of the human connectome in-utero, however, is challenged by intermittent fetal and maternal motion that disrupts the spatial correspondence of data acquired in the relatively long DWI acquisitions. Fetuses move continuously during DWI scans. Reliable and accurate analysis of the fetal brain structural connectome requires careful compensation of motion effects and robust reconstruction to avoid introducing bias based on the degree of fetal motion. In this paper we introduce a novel robust algorithm to reconstruct in-vivo diffusion-tensor MRI (DTI) of the moving fetal brain and show its effect on structural connectivity analysis. The proposed algorithm involves multiple steps of image registration incorporating a dynamic registration-based motion tracking algorithm to restore the spatial correspondence of DWI data at the slice level and reconstruct DTI of the fetal brain in the standard (atlas) coordinate space. A weighted linear least squares approach is adapted to remove the effect of intra-slice motion and reconstruct DTI from motion-corrected data. The proposed algorithm was tested on data obtained from 21 healthy fetuses scanned in-utero at 22-38 weeks gestation. Significantly higher fractional anisotropy values in fiber-rich regions, and the analysis of whole-brain tractography and group structural connectivity, showed the efficacy of the proposed method compared to the analyses based on original data and previously proposed methods. The results of this study show that slice-level motion correction and robust reconstruction is necessary for reliable in-vivo structural connectivity analysis of the fetal brain. Connectivity analysis based on graph theoretic measures show high degree of modularity and clustering, and short average
Khoromskaia, Venera; Khoromskij, Boris N.
2014-12-01
Our recent method for low-rank tensor representation of sums of the arbitrarily positioned electrostatic potentials discretized on a 3D Cartesian grid reduces the 3D tensor summation to operations involving only 1D vectors however retaining the linear complexity scaling in the number of potentials. Here, we introduce and study a novel tensor approach for fast and accurate assembled summation of a large number of lattice-allocated potentials represented on 3D N × N × N grid with the computational requirements only weakly dependent on the number of summed potentials. It is based on the assembled low-rank canonical tensor representations of the collected potentials using pointwise sums of shifted canonical vectors representing the single generating function, say the Newton kernel. For a sum of electrostatic potentials over L × L × L lattice embedded in a box the required storage scales linearly in the 1D grid-size, O(N) , while the numerical cost is estimated by O(NL) . For periodic boundary conditions, the storage demand remains proportional to the 1D grid-size of a unit cell, n = N / L, while the numerical cost reduces to O(N) , that outperforms the FFT-based Ewald-type summation algorithms of complexity O(N3 log N) . The complexity in the grid parameter N can be reduced even to the logarithmic scale O(log N) by using data-sparse representation of canonical N-vectors via the quantics tensor approximation. For justification, we prove an upper bound on the quantics ranks for the canonical vectors in the overall lattice sum. The presented approach is beneficial in applications which require further functional calculus with the lattice potential, say, scalar product with a function, integration or differentiation, which can be performed easily in tensor arithmetics on large 3D grids with 1D cost. Numerical tests illustrate the performance of the tensor summation method and confirm the estimated bounds on the tensor ranks.
Pieper, C C; Konrad, C; Sommer, J; Teismann, I; Schiffbauer, H
2013-05-01
Spinobulbar muscular atrophy [Kennedy's disease (KD)] is a rare X-linked neurodegenerative disorder of mainly spinal and bulbar motoneurons. Recent studies suggest a multisystem character of this disease. The aim of this study was to identify and characterize structural changes of gray (GM) and white matter (WM) in the central nervous system. Whole-brain-based voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) analyses were applied to MRI data of eight genetically proven patients with KD and compared with 16 healthy age-matched controls. Diffusion tensor imaging analysis showed not only decreased fractional anisotropy (FA) values in the brainstem, but also widespread changes in central WM tracts, whereas VBM analysis of the WM showed alterations primarily in the brainstem and cerebellum. There were no changes in GM volume. The FA value decrease in the brainstem correlated with the disease duration. Diffusion tensor imaging analysis revealed subtle changes of central WM tract integrity, while GM and WM volume remained unaffected. In our patient sample, KD had more extended effects than previously reported. These changes could either be attributed primarily to neurodegeneration or reflect secondary plastic changes due to atrophy of lower motor neurons and reorganization of cortical structures. © 2012 John Wiley & Sons A/S.
Kronecker-Basis-Representation Based Tensor Sparsity and Its Applications to Tensor Recovery.
Xie, Qi; Zhao, Qian; Meng, Deyu; Xu, Zongben
2017-08-02
It is well known that the sparsity/low-rank of a vector/matrix can be rationally measured by nonzero-entries-number ($l_0$ norm)/nonzero- singular-values-number (rank), respectively. However, data from real applications are often generated by the interaction of multiple factors, which obviously cannot be sufficiently represented by a vector/matrix, while a high order tensor is expected to provide more faithful representation to deliver the intrinsic structure underlying such data ensembles. Unlike the vector/matrix case, constructing a rational high order sparsity measure for tensor is a relatively harder task. To this aim, in this paper we propose a measure for tensor sparsity, called Kronecker-basis-representation based tensor sparsity measure (KBR briefly), which encodes both sparsity insights delivered by Tucker and CANDECOMP/PARAFAC (CP) low-rank decompositions for a general tensor. Then we study the KBR regularization minimization (KBRM) problem, and design an effective ADMM algorithm for solving it, where each involved parameter can be updated with closed-form equations. Such an efficient solver makes it possible to extend KBR to various tasks like tensor completion and tensor robust principal component analysis. A series of experiments, including multispectral image (MSI) denoising, MSI completion and background subtraction, substantiate the superiority of the proposed methods beyond state-of-the-arts.
Considerations on field problem structure
International Nuclear Information System (INIS)
Pavelescu, M.
1977-01-01
A survey of the three field problem types known today: equilibrium, eigen value and propagation problems is presented. The place occupied by neutron field in the nuclear reactor systems both statics and dynamics is shown. The special class of approximate solution method concerning the solving of field and boundary equations is analysed. The residual and variational method and the finite element method which presents a special interest are examined as well. (author)
Tensor Completion Algorithms in Big Data Analytics
Song, Qingquan; Ge, Hancheng; Caverlee, James; Hu, Xia
2017-01-01
Tensor completion is a problem of filling the missing or unobserved entries of partially observed tensors. Due to the multidimensional character of tensors in describing complex datasets, tensor completion algorithms and their applications have received wide attention and achievement in areas like data mining, computer vision, signal processing, and neuroscience. In this survey, we provide a modern overview of recent advances in tensor completion algorithms from the perspective of big data an...
Czarnik, Piotr; Dziarmaga, Jacek; Oleś, Andrzej M.
2017-07-01
The variational tensor network renormalization approach to two-dimensional (2D) quantum systems at finite temperature is applied to a model suffering the notorious quantum Monte Carlo sign problem—the orbital eg model with spatially highly anisotropic orbital interactions. Coarse graining of the tensor network along the inverse temperature β yields a numerically tractable 2D tensor network representing the Gibbs state. Its bond dimension D —limiting the amount of entanglement—is a natural refinement parameter. Increasing D we obtain a converged order parameter and its linear susceptibility close to the critical point. They confirm the existence of finite order parameter below the critical temperature Tc, provide a numerically exact estimate of Tc, and give the critical exponents within 1 % of the 2D Ising universality class.
Inference problems in structural biology
DEFF Research Database (Denmark)
Olsson, Simon
The structure and dynamics of biological molecules are essential for their function. Consequently, a wealth of experimental techniques have been developed to study these features. However, while experiments yield detailed information about geometrical features of molecules, this information is of...
Tensor-GMRES method for large sparse systems of nonlinear equations
Feng, Dan; Pulliam, Thomas H.
1994-01-01
This paper introduces a tensor-Krylov method, the tensor-GMRES method, for large sparse systems of nonlinear equations. This method is a coupling of tensor model formation and solution techniques for nonlinear equations with Krylov subspace projection techniques for unsymmetric systems of linear equations. Traditional tensor methods for nonlinear equations are based on a quadratic model of the nonlinear function, a standard linear model augmented by a simple second order term. These methods are shown to be significantly more efficient than standard methods both on nonsingular problems and on problems where the Jacobian matrix at the solution is singular. A major disadvantage of the traditional tensor methods is that the solution of the tensor model requires the factorization of the Jacobian matrix, which may not be suitable for problems where the Jacobian matrix is large and has a 'bad' sparsity structure for an efficient factorization. We overcome this difficulty by forming and solving the tensor model using an extension of a Newton-GMRES scheme. Like traditional tensor methods, we show that the new tensor method has significant computational advantages over the analogous Newton counterpart. Consistent with Krylov subspace based methods, the new tensor method does not depend on the factorization of the Jacobian matrix. As a matter of fact, the Jacobian matrix is never needed explicitly.
Diffusion tensor image registration using hybrid connectivity and tensor features.
Wang, Qian; Yap, Pew-Thian; Wu, Guorong; Shen, Dinggang
2014-07-01
Most existing diffusion tensor imaging (DTI) registration methods estimate structural correspondences based on voxelwise matching of tensors. The rich connectivity information that is given by DTI, however, is often neglected. In this article, we propose to integrate complementary information given by connectivity features and tensor features for improved registration accuracy. To utilize connectivity information, we place multiple anchors representing different brain anatomies in the image space, and define the connectivity features for each voxel as the geodesic distances from all anchors to the voxel under consideration. The geodesic distance, which is computed in relation to the tensor field, encapsulates information of brain connectivity. We also extract tensor features for every voxel to reflect the local statistics of tensors in its neighborhood. We then combine both connectivity features and tensor features for registration of tensor images. From the images, landmarks are selected automatically and their correspondences are determined based on their connectivity and tensor feature vectors. The deformation field that deforms one tensor image to the other is iteratively estimated and optimized according to the landmarks and their associated correspondences. Experimental results show that, by using connectivity features and tensor features simultaneously, registration accuracy is increased substantially compared with the cases using either type of features alone. Copyright © 2013 Wiley Periodicals, Inc.
Currents and the energy-momentum tensor in classical field theory: a fresh look at an old problem
International Nuclear Information System (INIS)
Forger, Michael; Roemer, Hartmann
2004-01-01
We give a comprehensive review of various methods to define currents and the energy-momentum tensor in classical field theory, with emphasis on a geometric point of view. The necessity of 'improving' the expressions provided by the canonical Noether procedure is addressed and given an adequate geometric framework. The main new ingredient is the explicit formulation of a principle of 'ultralocality' with respect to the symmetry generators, which is shown to fix the ambiguity inherent in the procedure of improvement and guide it towards a unique answer: when combined with the appropriate splitting of the fields into sectors, it leads to the well-known expressions for the current as the variational derivative of the matter field Lagrangian with respect to the gauge field and for the energy-momentum tensor as the variational derivative of the matter field Lagrangian with respect to the metric tensor. In the second case, the procedure is shown to work even when the matter field Lagrangian depends explicitly on the curvature, thus establishing the correct relation between scale invariance, in the form of local Weyl invariance 'on shell', and tracelessness of the energy-momentum tensor, required for a consistent definition of the concept of a conformal field theory
Exploring the tensor networks/AdS correspondence
Energy Technology Data Exchange (ETDEWEB)
Bhattacharyya, Arpan [Department of Physics and Center for Field Theory and Particle Physics, Fudan University,220 Handan Road, 200433 Shanghai (China); Centre For High Energy Physics, Indian Institute of Science,560012 Bangalore (India); Gao, Zhe-Shen [Department of Physics and Center for Field Theory and Particle Physics, Fudan University,220 Handan Road, 200433 Shanghai (China); Hung, Ling-Yan [Department of Physics and Center for Field Theory and Particle Physics, Fudan University,220 Handan Road, 200433 Shanghai (China); State Key Laboratory of Surface Physics and Department of Physics, Fudan University,220 Handan Road, 200433 Shanghai (China); Collaborative Innovation Center of Advanced Microstructures, Nanjing University,Nanjing, 210093 (China); Liu, Si-Nong [Department of Physics and Center for Field Theory and Particle Physics, Fudan University,220 Handan Road, 200433 Shanghai (China)
2016-08-11
In this paper we study the recently proposed tensor networks/AdS correspondence. We found that the Coxeter group is a useful tool to describe tensor networks in a negatively curved space. Studying generic tensor network populated by perfect tensors, we find that the physical wave function generically do not admit any connected correlation functions of local operators. To remedy the problem, we assume that wavefunctions admitting such semi-classical gravitational interpretation are composed of tensors close to, but not exactly perfect tensors. Computing corrections to the connected two point correlation functions, we find that the leading contribution is given by structures related to geodesics connecting the operators inserted at the boundary physical dofs. Such considerations admit generalizations at least to three point functions. This is highly suggestive of the emergence of the analogues of Witten diagrams in the tensor network. The perturbations alone however do not give the right entanglement spectrum. Using the Coxeter construction, we also constructed the tensor network counterpart of the BTZ black hole, by orbifolding the discrete lattice on which the network resides. We found that the construction naturally reproduces some of the salient features of the BTZ black hole, such as the appearance of RT surfaces that could wrap the horizon, depending on the size of the entanglement region A.
Diffusion tensor smoothing through weighted Karcher means
Carmichael, Owen; Chen, Jun; Paul, Debashis; Peng, Jie
2014-01-01
Diffusion tensor magnetic resonance imaging (MRI) quantifies the spatial distribution of water Diffusion at each voxel on a regular grid of locations in a biological specimen by Diffusion tensors– 3 × 3 positive definite matrices. Removal of noise from DTI is an important problem due to the high scientific relevance of DTI and relatively low signal to noise ratio it provides. Leading approaches to this problem amount to estimation of weighted Karcher means of Diffusion tensors within spatial neighborhoods, under various metrics imposed on the space of tensors. However, it is unclear how the behavior of these estimators varies with the magnitude of DTI sensor noise (the noise resulting from the thermal e!ects of MRI scanning) as well as the geometric structure of the underlying Diffusion tensor neighborhoods. In this paper, we combine theoretical analysis, empirical analysis of simulated DTI data, and empirical analysis of real DTI scans to compare the noise removal performance of three kernel-based DTI smoothers that are based on Euclidean, log-Euclidean, and affine-invariant metrics. The results suggest, contrary to conventional wisdom, that imposing a simplistic Euclidean metric may in fact provide comparable or superior noise removal, especially in relatively unstructured regions and/or in the presence of moderate to high levels of sensor noise. On the contrary, log-Euclidean and affine-invariant metrics may lead to better noise removal in highly structured anatomical regions, especially when the sensor noise is of low magnitude. These findings emphasize the importance of considering the interplay of sensor noise magnitude and tensor field geometric structure when assessing Diffusion tensor smoothing options. They also point to the necessity for continued development of smoothing methods that perform well across a large range of scenarios. PMID:25419264
Problems of structural mechanics in nuclear design
International Nuclear Information System (INIS)
Patwardhan, V.M.; Kakodkar, Anil
1975-01-01
A very careful and detailed stress analysis of nuclear presure vessels and components is essential for ensuring the safety and integrity of nuclear power plants. The nuclear designer, therefore, relies heavily on structural mechanics for application of the most advanced stress analysis techniques to practical design problems. The paper reviews the inter-relation between structural mechanics and nuclear design and discusses a few of the specific structural mechanics problems faced by the nuclear designers in the Department of Atomic Energy, India. (author)
Second benchmark problem for WIPP structural computations
International Nuclear Information System (INIS)
Krieg, R.D.; Morgan, H.S.; Hunter, T.O.
1980-12-01
This report describes the second benchmark problem for comparison of the structural codes used in the WIPP project. The first benchmark problem consisted of heated and unheated drifts at a depth of 790 m, whereas this problem considers a shallower level (650 m) more typical of the repository horizon. But more important, the first problem considered a homogeneous salt configuration, whereas this problem considers a configuration with 27 distinct geologic layers, including 10 clay layers - 4 of which are to be modeled as possible slip planes. The inclusion of layering introduces complications in structural and thermal calculations that were not present in the first benchmark problem. These additional complications will be handled differently by the various codes used to compute drift closure rates. This second benchmark problem will assess these codes by evaluating the treatment of these complications
Tensor Train Neighborhood Preserving Embedding
Wang, Wenqi; Aggarwal, Vaneet; Aeron, Shuchin
2018-05-01
In this paper, we propose a Tensor Train Neighborhood Preserving Embedding (TTNPE) to embed multi-dimensional tensor data into low dimensional tensor subspace. Novel approaches to solve the optimization problem in TTNPE are proposed. For this embedding, we evaluate novel trade-off gain among classification, computation, and dimensionality reduction (storage) for supervised learning. It is shown that compared to the state-of-the-arts tensor embedding methods, TTNPE achieves superior trade-off in classification, computation, and dimensionality reduction in MNIST handwritten digits and Weizmann face datasets.
1987-03-01
holds an economical advantage. We now formulate 1. from (65) in conjunction with (57): IH]T T I TI (4 L [I R)T(I + RR ) (L*4) where the positive...sizes of the matrices to be inverted, an economical edge of the analytical formulation hecomes apparent as well. Chapter 3 contains one such matrix of...the relat ions Sthat can tie iibta i ned via the tensor vers ion of adjustment quant it ies. Alt Iihut t . ho’ ) mpu it iona I merits of the CholeskI
Indicial tensor manipulation on MACSYMA
International Nuclear Information System (INIS)
Bogen, R.A.; Pavelle, R.
1977-01-01
A new computational tool for physical calculations is described. It is the first computer system capable of performing indicial tensor calculus (as opposed to component tensor calculus). It is now operational on the symbolic manipulation system MACSYMA. The authors outline the capabilities of the system and describe some of the physical problems considered as well as others being examined at this time. (Auth.)
Tensor force and delta excitation for the structure of light nuclei
International Nuclear Information System (INIS)
Horii, K; Myo, T; Toki, H
2014-01-01
We treat explicitly Δ(1232) isobar degrees of freedom using a bare nucleon-nucleon interaction for few-body systems, where Δ excitations can be the origin of the three-body force via the pion exchange. We adopt the Argonne two-body potential including Δ, named as AV28 potential, and study the role of Δ explicitly in two-body and three-body systems. It was found that the additional Δ states generate strong tensor correlations caused by the transitions between N and Δ states, and change tensor matrix elements largely from the results with only nucleons. We studied the effects of three-body force in the triton and obtained 0.8 MeV attraction due to the intermediate Δ excitation. Due to the lack of the total binding energy for the triton in the delta model, we further studied carefully the effects of the delta excitation in various two body channels and compared with the nucleon only model in the AV14 potential. We modified slightly the AV28 potential in the singlet S channel so that we could reproduce the triton binding energy due to the appropriate amount of the three-body force effects
Structural priority approach to fluid-structure interaction problems
International Nuclear Information System (INIS)
Au-Yang, M.K.; Galford, J.E.
1981-01-01
In a large class of dynamic problems occurring in nuclear reactor safety analysis, the forcing function is derived from the fluid enclosed within the structure itself. Since the structural displacement depends on the fluid pressure, which in turn depends on the structural boundaries, a rigorous approach to this class of problems involves simultaneous solution of the coupled fluid mechanics and structural dynamics equations with the structural response and the fluid pressure as unknowns. This paper offers an alternate approach to the foregoing problems. 8 refs
Distance Adaptive Tensor Discriminative Geometry Preserving Projection for Face Recognition
Directory of Open Access Journals (Sweden)
Ziqiang Wang
2012-09-01
Full Text Available There is a growing interest in dimensionality reduction techniques for face recognition, however, the traditional dimensionality reduction algorithms often transform the input face image data into vectors before embedding. Such vectorization often ignores the underlying data structure and leads to higher computational complexity. To effectively cope with these problems, a novel dimensionality reduction algorithm termed distance adaptive tensor discriminative geometry preserving projection (DATDGPP is proposed in this paper. The key idea of DATDGPP is as follows: first, the face image data are directly encoded in high-order tensor structure so that the relationships among the face image data can be preserved; second, the data-adaptive tensor distance is adopted to model the correlation among different coordinates of tensor data; third, the transformation matrix which can preserve discrimination and local geometry information is obtained by an iteration algorithm. Experimental results on three face databases show that the proposed algorithm outperforms other representative dimensionality reduction algorithms.
International Nuclear Information System (INIS)
Levashov, V. A.
2016-01-01
It is possible to associate with every atom or molecule in a liquid its own atomic stress tensor. These atomic stress tensors can be used to describe liquids’ structures and to investigate the connection between structural and dynamic properties. In particular, atomic stresses allow to address atomic scale correlations relevant to the Green-Kubo expression for viscosity. Previously correlations between the atomic stresses of different atoms were studied using the Cartesian representation of the stress tensors or the representation based on spherical harmonics. In this paper we address structural correlations in a 3D model binary liquid using the eigenvalues and eigenvectors of the atomic stress tensors. This approach allows to interpret correlations relevant to the Green-Kubo expression for viscosity in a simple geometric way. On decrease of temperature the changes in the relevant stress correlation function between different atoms are significantly more pronounced than the changes in the pair density function. We demonstrate that this behaviour originates from the orientational correlations between the eigenvectors of the atomic stress tensors. We also found correlations between the eigenvalues of the same atomic stress tensor. For the studied system, with purely repulsive interactions between the particles, the eigenvalues of every atomic stress tensor are positive and they can be ordered: λ 1 ≥ λ 2 ≥ λ 3 ≥ 0. We found that, for the particles of a given type, the probability distributions of the ratios (λ 2 /λ 1 ) and (λ 3 /λ 2 ) are essentially identical to each other in the liquids state. We also found that λ 2 tends to be equal to the geometric average of λ 1 and λ 3 . In our view, correlations between the eigenvalues may represent “the Poisson ratio effect” at the atomic scale.
Energy Technology Data Exchange (ETDEWEB)
Levashov, V. A. [Technological Design Institute of Scientific Instrument Engineering, Novosibirsk 630058 (Russian Federation)
2016-03-07
It is possible to associate with every atom or molecule in a liquid its own atomic stress tensor. These atomic stress tensors can be used to describe liquids’ structures and to investigate the connection between structural and dynamic properties. In particular, atomic stresses allow to address atomic scale correlations relevant to the Green-Kubo expression for viscosity. Previously correlations between the atomic stresses of different atoms were studied using the Cartesian representation of the stress tensors or the representation based on spherical harmonics. In this paper we address structural correlations in a 3D model binary liquid using the eigenvalues and eigenvectors of the atomic stress tensors. This approach allows to interpret correlations relevant to the Green-Kubo expression for viscosity in a simple geometric way. On decrease of temperature the changes in the relevant stress correlation function between different atoms are significantly more pronounced than the changes in the pair density function. We demonstrate that this behaviour originates from the orientational correlations between the eigenvectors of the atomic stress tensors. We also found correlations between the eigenvalues of the same atomic stress tensor. For the studied system, with purely repulsive interactions between the particles, the eigenvalues of every atomic stress tensor are positive and they can be ordered: λ{sub 1} ≥ λ{sub 2} ≥ λ{sub 3} ≥ 0. We found that, for the particles of a given type, the probability distributions of the ratios (λ{sub 2}/λ{sub 1}) and (λ{sub 3}/λ{sub 2}) are essentially identical to each other in the liquids state. We also found that λ{sub 2} tends to be equal to the geometric average of λ{sub 1} and λ{sub 3}. In our view, correlations between the eigenvalues may represent “the Poisson ratio effect” at the atomic scale.
Fluid Structure Interaction for Hydraulic Problems
International Nuclear Information System (INIS)
Souli, Mhamed; Aquelet, Nicolas
2011-01-01
Fluid Structure interaction plays an important role in engineering applications. Physical phenomena such as flow induced vibration in nuclear industry, fuel sloshing tank in automotive industry or rotor stator interaction in turbo machinery, can lead to structure deformation and sometimes to failure. In order to solve fluid structure interaction problems, the majority of numerical tests consists in using two different codes to separately solve pressure of the fluid and structural displacements. In this paper, a unique code with an ALE formulation approach is used to implicitly calculate the pressure of an incompressible fluid applied to the structure. The development of the ALE method as well as the coupling in a computational structural dynamic code, allows to solve more large industrial problems related to fluid structure coupling. (authors)
Notes on super Killing tensors
Energy Technology Data Exchange (ETDEWEB)
Howe, P.S. [Department of Mathematics, King’s College London,The Strand, London WC2R 2LS (United Kingdom); Lindström, University [Department of Physics and Astronomy, Theoretical Physics, Uppsala University,SE-751 20 Uppsala (Sweden); Theoretical Physics, Imperial College London,Prince Consort Road, London SW7 2AZ (United Kingdom)
2016-03-14
The notion of a Killing tensor is generalised to a superspace setting. Conserved quantities associated with these are defined for superparticles and Poisson brackets are used to define a supersymmetric version of the even Schouten-Nijenhuis bracket. Superconformal Killing tensors in flat superspaces are studied for spacetime dimensions 3,4,5,6 and 10. These tensors are also presented in analytic superspaces and super-twistor spaces for 3,4 and 6 dimensions. Algebraic structures associated with superconformal Killing tensors are also briefly discussed.
All-at-once Optimization for Coupled Matrix and Tensor Factorizations
DEFF Research Database (Denmark)
Evrim, Acar Ataman; Kolda, Tamara G.; Dunlavy, Daniel M.
2011-01-01
.g., the person by person social network matrix or the restaurant by category matrix, and higher-order tensors, e.g., the "ratings" tensor of the form restaurant by meal by person. In this paper, we are particularly interested in fusing data sets with the goal of capturing their underlying latent structures. We...... formulate this problem as a coupled matrix and tensor factorization (CMTF) problem where heterogeneous data sets are modeled by fitting outer-product models to higher-order tensors and matrices in a coupled manner. Unlike traditional approaches solving this problem using alternating algorithms, we propose...... an all-at-once optimization approach called CMTF-OPT (CMTF-OPTimization), which is a gradient-based optimization approach for joint analysis of matrices and higher-order tensors. We also extend the algorithm to handle coupled incomplete data sets. Using numerical experiments, we demonstrate...
Spatio-Temporal Video Object Segmentation via Scale-Adaptive 3D Structure Tensor
Directory of Open Access Journals (Sweden)
Hai-Yun Wang
2004-06-01
Full Text Available To address multiple motions and deformable objects' motions encountered in existing region-based approaches, an automatic video object (VO segmentation methodology is proposed in this paper by exploiting the duality of image segmentation and motion estimation such that spatial and temporal information could assist each other to jointly yield much improved segmentation results. The key novelties of our method are (1 scale-adaptive tensor computation, (2 spatial-constrained motion mask generation without invoking dense motion-field computation, (3 rigidity analysis, (4 motion mask generation and selection, and (5 motion-constrained spatial region merging. Experimental results demonstrate that these novelties jointly contribute much more accurate VO segmentation both in spatial and temporal domains.
Ding, Zi'ang
2016-01-01
Both vector and tensor fields are important mathematical tools used to describe the physics of many phenomena in science and engineering. Effective vector and tensor field visualization techniques are therefore needed to interpret and analyze the corresponding data and achieve new insight into the considered problem. This dissertation is concerned with the extraction of important structural properties from vector and tensor datasets. Specifically, we present a unified approach for the charact...
Tensor Rank Preserving Discriminant Analysis for Facial Recognition.
Tao, Dapeng; Guo, Yanan; Li, Yaotang; Gao, Xinbo
2017-10-12
Facial recognition, one of the basic topics in computer vision and pattern recognition, has received substantial attention in recent years. However, for those traditional facial recognition algorithms, the facial images are reshaped to a long vector, thereby losing part of the original spatial constraints of each pixel. In this paper, a new tensor-based feature extraction algorithm termed tensor rank preserving discriminant analysis (TRPDA) for facial image recognition is proposed; the proposed method involves two stages: in the first stage, the low-dimensional tensor subspace of the original input tensor samples was obtained; in the second stage, discriminative locality alignment was utilized to obtain the ultimate vector feature representation for subsequent facial recognition. On the one hand, the proposed TRPDA algorithm fully utilizes the natural structure of the input samples, and it applies an optimization criterion that can directly handle the tensor spectral analysis problem, thereby decreasing the computation cost compared those traditional tensor-based feature selection algorithms. On the other hand, the proposed TRPDA algorithm extracts feature by finding a tensor subspace that preserves most of the rank order information of the intra-class input samples. Experiments on the three facial databases are performed here to determine the effectiveness of the proposed TRPDA algorithm.
The overshoot problem and giant structures
International Nuclear Information System (INIS)
Itzhaki, Nissan
2008-01-01
Models of small-field inflation often suffer from the overshoot problem. A particularly efficient resolution to the problem was proposed recently in the context of string theory. We show that this resolution predicts the existence of giant spherically symmetric overdense regions with radius of at least 110 Mpc. We argue that if such structures will be found they could offer an experimental window into string theory.
On Helmholtz Problem for Plane Periodical Structures
International Nuclear Information System (INIS)
Akishin, P.G.; Vinitskij, S.I.
1994-01-01
The plane Helmholtz problem of the periodical disc structures with the phase shifts conditions of the solutions along the basis lattice vectors and the Dirichlet conditions on the basic boundaries is considered. The Green function satisfying the quasi periodical conditions on the lattice is constructed. The Helmholtz problem is reduced to the boundary integral equations for the simple layer potentials of this Green function. The methods of the discretization of the arising integral equations are proposed. The procedures of calculation of the matrix elements are discussed. The reality of the spectral parameter of the nonlinear continuous and discretized problems is shown. 8 refs., 2 figs
Directory of Open Access Journals (Sweden)
Feng-Mei Lu
2017-11-01
Full Text Available Neuroimaging studies have revealed that insomnia is characterized by aberrant neuronal connectivity in specific brain regions, but the topological disruptions in the white matter (WM structural connectivity networks remain largely unknown in insomnia. The current study uses diffusion tensor imaging (DTI tractography to construct the WM structural networks and graph theory analysis to detect alterations of the brain structural networks. The study participants comprised 30 healthy subjects with insomnia symptoms (IS and 62 healthy subjects without IS. Both the two groups showed small-world properties regarding their WM structural connectivity networks. By contrast, increased local efficiency and decreased global efficiency were identified in the IS group, indicating an insomnia-related shift in topology away from regular networks. In addition, the IS group exhibited disrupted nodal topological characteristics in regions involving the fronto-limbic and the default-mode systems. To our knowledge, this is the first study to explore the topological organization of WM structural network connectivity in insomnia. More importantly, the dysfunctions of large-scale brain systems including the fronto-limbic pathways, salience network and default-mode network in insomnia were identified, which provides new insights into the insomnia connectome. Topology-based brain network analysis thus could be a potential biomarker for IS.
Energy Technology Data Exchange (ETDEWEB)
Chatzistavrakidis, Athanasios [Van Swinderen Institute for Particle Physics and Gravity, University of Groningen,Nijenborgh 4, 9747 AG Groningen (Netherlands); Khoo, Fech Scen [Department of Physics and Earth Sciences, Jacobs University Bremen,Campus Ring 1, 28759 Bremen (Germany); Roest, Diederik [Van Swinderen Institute for Particle Physics and Gravity, University of Groningen,Nijenborgh 4, 9747 AG Groningen (Netherlands); Schupp, Peter [Department of Physics and Earth Sciences, Jacobs University Bremen,Campus Ring 1, 28759 Bremen (Germany)
2017-03-13
The particular structure of Galileon interactions allows for higher-derivative terms while retaining second order field equations for scalar fields and Abelian p-forms. In this work we introduce an index-free formulation of these interactions in terms of two sets of Grassmannian variables. We employ this to construct Galileon interactions for mixed-symmetry tensor fields and coupled systems thereof. We argue that these tensors are the natural generalization of scalars with Galileon symmetry, similar to p-forms and scalars with a shift-symmetry. The simplest case corresponds to linearised gravity with Lovelock invariants, relating the Galileon symmetry to diffeomorphisms. Finally, we examine the coupling of a mixed-symmetry tensor to gravity, and demonstrate in an explicit example that the inclusion of appropriate counterterms retains second order field equations.
Tensor-based spatiotemporal saliency detection
Dou, Hao; Li, Bin; Deng, Qianqian; Zhang, LiRui; Pan, Zhihong; Tian, Jinwen
2018-03-01
This paper proposes an effective tensor-based spatiotemporal saliency computation model for saliency detection in videos. First, we construct the tensor representation of video frames. Then, the spatiotemporal saliency can be directly computed by the tensor distance between different tensors, which can preserve the complete temporal and spatial structure information of object in the spatiotemporal domain. Experimental results demonstrate that our method can achieve encouraging performance in comparison with the state-of-the-art methods.
Tensor completion and low-n-rank tensor recovery via convex optimization
International Nuclear Information System (INIS)
Gandy, Silvia; Yamada, Isao; Recht, Benjamin
2011-01-01
In this paper we consider sparsity on a tensor level, as given by the n-rank of a tensor. In an important sparse-vector approximation problem (compressed sensing) and the low-rank matrix recovery problem, using a convex relaxation technique proved to be a valuable solution strategy. Here, we will adapt these techniques to the tensor setting. We use the n-rank of a tensor as a sparsity measure and consider the low-n-rank tensor recovery problem, i.e. the problem of finding the tensor of the lowest n-rank that fulfills some linear constraints. We introduce a tractable convex relaxation of the n-rank and propose efficient algorithms to solve the low-n-rank tensor recovery problem numerically. The algorithms are based on the Douglas–Rachford splitting technique and its dual variant, the alternating direction method of multipliers
Son, Shuraku; Kubota, Manabu; Miyata, Jun; Fukuyama, Hidenao; Aso, Toshihiko; Urayama, Shin-ichi; Murai, Toshiya; Takahashi, Hidehiko
2015-05-01
Both creativity and schizotypy are suggested to be manifestations of the hyperactivation of unusual or remote concepts/words. However, the results of studies on creativity in schizophrenia are diverse, possibly due to the multifaceted aspects of creativity and difficulties of differentiating adaptive creativity from pathological schizotypy/positive symptoms. To date, there have been no detailed studies comprehensively investigating creativity, positive symptoms including delusions, and their neural bases in schizophrenia. In this study, we investigated 43 schizophrenia and 36 healthy participants using diffusion tensor imaging. We used idea, design, and verbal (semantic and phonological) fluency tests as creativity scores and Peters Delusions Inventory as delusion scores. Subsequently, we investigated group differences in every psychological score, correlations between fluency and delusions, and relationships between these scores and white matter integrity using tract-based spatial statistics (TBSS). In schizophrenia, idea and verbal fluency were significantly lower in general, and delusion score was higher than in healthy controls, whereas there were no group differences in design fluency. We also found positive correlation between phonological fluency and delusions in schizophrenia. By correlation analyses using TBSS, we found that the anterior part of corpus callosum was the substantially overlapped area, negatively correlated with both phonological fluency and delusion severity. Our results suggest that the anterior interhemispheric dysconnectivity might be associated with executive dysfunction, and disinhibited automatic spreading activation in the semantic network was manifested as uncontrollable phonological fluency or delusions. This dysconnectivity could be one possible neural basis that differentiates pathological positive symptoms from adaptive creativity. Copyright © 2015 Elsevier B.V. All rights reserved.
Adiabatic quantum search algorithm for structured problems
International Nuclear Information System (INIS)
Roland, Jeremie; Cerf, Nicolas J.
2003-01-01
The study of quantum computation has been motivated by the hope of finding efficient quantum algorithms for solving classically hard problems. In this context, quantum algorithms by local adiabatic evolution have been shown to solve an unstructured search problem with a quadratic speedup over a classical search, just as Grover's algorithm. In this paper, we study how the structure of the search problem may be exploited to further improve the efficiency of these quantum adiabatic algorithms. We show that by nesting a partial search over a reduced set of variables into a global search, it is possible to devise quantum adiabatic algorithms with a complexity that, although still exponential, grows with a reduced order in the problem size
Standard problems for structural computer codes
International Nuclear Information System (INIS)
Philippacopoulos, A.J.; Miller, C.A.; Costantino, C.J.
1985-01-01
BNL is investigating the ranges of validity of the analytical methods used to predict the behavior of nuclear safety related structures under accidental and extreme environmental loadings. During FY 85, the investigations were concentrated on special problems that can significantly influence the outcome of the soil structure interaction evaluation process. Specially, limitations and applicability of the standard interaction methods when dealing with lift-off, layering and water table effects, were investigated. This paper describes the work and the results obtained during FY 85 from the studies on lift-off, layering and water-table effects in soil-structure interaction
Students’ Creativity: Problem Posing in Structured Situation
Amalina, I. K.; Amirudin, M.; Budiarto, M. T.
2018-01-01
This is a qualitative research concerning on students’ creativity on problem posing task. The study aimed at describing the students’ creative thinking ability to pose the mathematics problem in structured situations with varied condition of given problems. In order to find out the students’ creative thinking ability, an analysis of mathematics problem posing test based on fluency, novelty, and flexibility and interview was applied for categorizing students’ responses on that task. The data analysis used the quality of problem posing and categorized in 4 level of creativity. The results revealed from 29 secondary students grade 8, a student in CTL (Creative Thinking Level) 1 met the fluency. A student in CTL 2 met the novelty, while a student in CTL 3 met both fluency and novelty and no one in CTL 4. These results are affected by students’ mathematical experience. The findings of this study highlight that student’s problem posing creativity are dependent on their experience in mathematics learning and from the point of view of which students start to pose problem.
vhv supply networks, problems of network structure
Energy Technology Data Exchange (ETDEWEB)
Raimbault, J
1966-04-01
The present and future power requirements of the Paris area and the structure of the existing networks are discussed. The various limitations that will have to be allowed for to lay down the structure of a regional transmission network leading in the power of the large national transmission network to within the Paris built up area are described. The theoretical solution that has been adopted, and the features of its final achievement, which is planned for about the year 2000, and the intermediate stages are given. The problem of the structure of the National Power Transmission network which is to supply the regional network was studied. To solve this problem, a 730 kV voltage network will have to be introduced.
Welch, K A; Moorhead, T W; McIntosh, A M; Owens, D G C; Johnstone, E C; Lawrie, S M
2013-10-01
Schizophrenia is associated with various brain structural abnormalities, including reduced volume of the hippocampi, prefrontal lobes and thalami. Cannabis use increases the risk of schizophrenia but reports of brain structural abnormalities in the cannabis-using population have not been consistent. We used automated image analysis to compare brain structural changes over time in people at elevated risk of schizophrenia for familial reasons who did and did not use cannabis. Magnetic resonance imaging (MRI) scans were obtained from subjects at high familial risk of schizophrenia at entry to the Edinburgh High Risk Study (EHRS) and approximately 2 years later. Differential grey matter (GM) loss in those exposed (n=23) and not exposed to cannabis (n=32) in the intervening period was compared using tensor-based morphometry (TBM). Cannabis exposure was associated with significantly greater loss of right anterior hippocampal (pcorrected=0.029, t=3.88) and left superior frontal lobe GM (pcorrected=0.026, t=4.68). The former finding remained significant even after the exclusion of individuals who had used other drugs during the inter-scan interval. Using an automated analysis of longitudinal data, we demonstrate an association between cannabis use and GM loss in currently well people at familial risk of developing schizophrenia. This observation may be important in understanding the link between cannabis exposure and the subsequent development of schizophrenia.
PFEM application in fluid structure interaction problems
Celigueta Jordana, Miguel Ángel; Larese De Tetto, Antonia; Latorre, Salvador
2008-01-01
In the current paper the Particle Finite Element Method (PFEM), an innovative numerical method for solving a wide spectrum of problems involving the interaction of fluid and structures, is briefly presented. Many examples of the use of the PFEM with GiD support are shown. GiD framework provides a useful pre and post processor for the specific features of the method. Its advantages and shortcomings are pointed out in the present work. Peer Reviewed
Ambrosi, Elisa; Rossi-Espagnet, Maria Camilla; Kotzalidis, Georgios D; Comparelli, Anna; Del Casale, Antonio; Carducci, Filippo; Romano, Andrea; Manfredi, Giovanni; Tatarelli, Roberto; Bozzao, Alessandro; Girardi, Paolo
2013-09-05
Brain structural changes have been described in bipolar disorder (BP), but usually studies focused on both I and II subtypes indiscriminately and investigated changes in either brain volume or white matter (WM) integrity. We used combined voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) analysis to track changes in the grey matter (GM) and WM in the brains of patients affected by BPII, as compared to healthy controls. Using VBM and DTI, we scanned 20 DSM-IV-TR BPII patients in their euthymic phase and 21 healthy, age- and gender-matched volunteers with no psychiatric history. VBM showed decreases in GM of BPII patients, compared to controls, which were diffuse in nature and most prominent in the right middle frontal gyrus and in the right superior temporal gurus. DTI showed significant and widespread FA reduction in BPII patients in all major WM tracts, including cortico-cortical association tracts. The small sample size limits the generalisability of our findings. Reduced GM volumes and WM integrity changes in BPII patients are not prominent like those previously reported in bipolar disorder type-I and involve cortical structures and their related association tracts. Copyright © 2013 Elsevier B.V. All rights reserved.
Hoy, Erik P; Mazziotti, David A
2015-08-14
Tensor factorization of the 2-electron integral matrix is a well-known technique for reducing the computational scaling of ab initio electronic structure methods toward that of Hartree-Fock and density functional theories. The simplest factorization that maintains the positive semidefinite character of the 2-electron integral matrix is the Cholesky factorization. In this paper, we introduce a family of positive semidefinite factorizations that generalize the Cholesky factorization. Using an implementation of the factorization within the parametric 2-RDM method [D. A. Mazziotti, Phys. Rev. Lett. 101, 253002 (2008)], we study several inorganic molecules, alkane chains, and potential energy curves and find that this generalized factorization retains the accuracy and size extensivity of the Cholesky factorization, even in the presence of multi-reference correlation. The generalized family of positive semidefinite factorizations has potential applications to low-scaling ab initio electronic structure methods that treat electron correlation with a computational cost approaching that of the Hartree-Fock method or density functional theory.
Energy Technology Data Exchange (ETDEWEB)
Hoy, Erik P.; Mazziotti, David A., E-mail: damazz@uchicago.edu [Department of Chemistry and The James Franck Institute, The University of Chicago, Chicago, Illinois 60637 (United States)
2015-08-14
Tensor factorization of the 2-electron integral matrix is a well-known technique for reducing the computational scaling of ab initio electronic structure methods toward that of Hartree-Fock and density functional theories. The simplest factorization that maintains the positive semidefinite character of the 2-electron integral matrix is the Cholesky factorization. In this paper, we introduce a family of positive semidefinite factorizations that generalize the Cholesky factorization. Using an implementation of the factorization within the parametric 2-RDM method [D. A. Mazziotti, Phys. Rev. Lett. 101, 253002 (2008)], we study several inorganic molecules, alkane chains, and potential energy curves and find that this generalized factorization retains the accuracy and size extensivity of the Cholesky factorization, even in the presence of multi-reference correlation. The generalized family of positive semidefinite factorizations has potential applications to low-scaling ab initio electronic structure methods that treat electron correlation with a computational cost approaching that of the Hartree-Fock method or density functional theory.
Tensor Completion for Estimating Missing Values in Visual Data
Liu, Ji
2012-01-25
In this paper, we propose an algorithm to estimate missing values in tensors of visual data. The values can be missing due to problems in the acquisition process or because the user manually identified unwanted outliers. Our algorithm works even with a small amount of samples and it can propagate structure to fill larger missing regions. Our methodology is built on recent studies about matrix completion using the matrix trace norm. The contribution of our paper is to extend the matrix case to the tensor case by proposing the first definition of the trace norm for tensors and then by building a working algorithm. First, we propose a definition for the tensor trace norm that generalizes the established definition of the matrix trace norm. Second, similarly to matrix completion, the tensor completion is formulated as a convex optimization problem. Unfortunately, the straightforward problem extension is significantly harder to solve than the matrix case because of the dependency among multiple constraints. To tackle this problem, we developed three algorithms: simple low rank tensor completion (SiLRTC), fast low rank tensor completion (FaLRTC), and high accuracy low rank tensor completion (HaLRTC). The SiLRTC algorithm is simple to implement and employs a relaxation technique to separate the dependant relationships and uses the block coordinate descent (BCD) method to achieve a globally optimal solution; the FaLRTC algorithm utilizes a smoothing scheme to transform the original nonsmooth problem into a smooth one and can be used to solve a general tensor trace norm minimization problem; the HaLRTC algorithm applies the alternating direction method of multipliers (ADMMs) to our problem. Our experiments show potential applications of our algorithms and the quantitative evaluation indicates that our methods are more accurate and robust than heuristic approaches. The efficiency comparison indicates that FaLTRC and HaLRTC are more efficient than SiLRTC and between Fa
Tensor Completion for Estimating Missing Values in Visual Data
Liu, Ji; Musialski, Przemyslaw; Wonka, Peter; Ye, Jieping
2012-01-01
In this paper, we propose an algorithm to estimate missing values in tensors of visual data. The values can be missing due to problems in the acquisition process or because the user manually identified unwanted outliers. Our algorithm works even with a small amount of samples and it can propagate structure to fill larger missing regions. Our methodology is built on recent studies about matrix completion using the matrix trace norm. The contribution of our paper is to extend the matrix case to the tensor case by proposing the first definition of the trace norm for tensors and then by building a working algorithm. First, we propose a definition for the tensor trace norm that generalizes the established definition of the matrix trace norm. Second, similarly to matrix completion, the tensor completion is formulated as a convex optimization problem. Unfortunately, the straightforward problem extension is significantly harder to solve than the matrix case because of the dependency among multiple constraints. To tackle this problem, we developed three algorithms: simple low rank tensor completion (SiLRTC), fast low rank tensor completion (FaLRTC), and high accuracy low rank tensor completion (HaLRTC). The SiLRTC algorithm is simple to implement and employs a relaxation technique to separate the dependant relationships and uses the block coordinate descent (BCD) method to achieve a globally optimal solution; the FaLRTC algorithm utilizes a smoothing scheme to transform the original nonsmooth problem into a smooth one and can be used to solve a general tensor trace norm minimization problem; the HaLRTC algorithm applies the alternating direction method of multipliers (ADMMs) to our problem. Our experiments show potential applications of our algorithms and the quantitative evaluation indicates that our methods are more accurate and robust than heuristic approaches. The efficiency comparison indicates that FaLTRC and HaLRTC are more efficient than SiLRTC and between Fa
Tensor completion for estimating missing values in visual data.
Liu, Ji; Musialski, Przemyslaw; Wonka, Peter; Ye, Jieping
2013-01-01
In this paper, we propose an algorithm to estimate missing values in tensors of visual data. The values can be missing due to problems in the acquisition process or because the user manually identified unwanted outliers. Our algorithm works even with a small amount of samples and it can propagate structure to fill larger missing regions. Our methodology is built on recent studies about matrix completion using the matrix trace norm. The contribution of our paper is to extend the matrix case to the tensor case by proposing the first definition of the trace norm for tensors and then by building a working algorithm. First, we propose a definition for the tensor trace norm that generalizes the established definition of the matrix trace norm. Second, similarly to matrix completion, the tensor completion is formulated as a convex optimization problem. Unfortunately, the straightforward problem extension is significantly harder to solve than the matrix case because of the dependency among multiple constraints. To tackle this problem, we developed three algorithms: simple low rank tensor completion (SiLRTC), fast low rank tensor completion (FaLRTC), and high accuracy low rank tensor completion (HaLRTC). The SiLRTC algorithm is simple to implement and employs a relaxation technique to separate the dependent relationships and uses the block coordinate descent (BCD) method to achieve a globally optimal solution; the FaLRTC algorithm utilizes a smoothing scheme to transform the original nonsmooth problem into a smooth one and can be used to solve a general tensor trace norm minimization problem; the HaLRTC algorithm applies the alternating direction method of multipliers (ADMMs) to our problem. Our experiments show potential applications of our algorithms and the quantitative evaluation indicates that our methods are more accurate and robust than heuristic approaches. The efficiency comparison indicates that FaLTRC and HaLRTC are more efficient than SiLRTC and between FaLRTC an
Tensor voting for robust color edge detection
Moreno, Rodrigo; García, Miguel Ángel; Puig, Domenec
2014-01-01
The final publication is available at Springer via http://dx.doi.org/10.1007/978-94-007-7584-8_9 This chapter proposes two robust color edge detection methods based on tensor voting. The first method is a direct adaptation of the classical tensor voting to color images where tensors are initialized with either the gradient or the local color structure tensor. The second method is based on an extension of tensor voting in which the encoding and voting processes are specifically tailored to ...
Directory of Open Access Journals (Sweden)
Rishu Rathee
2016-01-01
Full Text Available The aim is to investigate the relationship between microstructural white matter (WM diffusivity indices and macrostructural WM volume (WMV among healthy individuals (20–85 years. Whole-brain diffusion measures were calculated from diffusion tensor imaging using FMRIB software library while WMV was estimated through voxel-based morphometry, and voxel-based analysis was carried out using tract-based spatial statistics. Our results revealed that mean diffusivity, axial diffusivity, and radial diffusivity had shown good correlation with WMV but not for fractional anisotropy (FA. Voxel-wise tract-based spatial statistics analysis for FA showed a significant decrease in four regions for middle-aged group compared to young-aged group, in 22 regions for old-aged group compared to middle-aged group, and in 26 regions for old-aged group compared to young-aged group ( P < 0.05. We found significantly lower WMV, FA, and mean diffusivity values in females than males and inverted-U trend for FA in males. We conclude differential age- and gender-related changes for structural WMV and WM diffusion indices.
Ouyang, Austin; Jeon, Tina; Sunkin, Susan M.; Pletikos, Mihovil; Sedmak, Goran; Sestan, Nenad; Lein, Ed S.; Huang, Hao
2014-01-01
During human brain development from fetal stage to adulthood, the white matter (WM) tracts undergo dramatic changes. Diffusion tensor imaging (DTI), a widely used magnetic resonance imaging (MRI) modality, offers insight into the dynamic changes of WM fibers as these fibers can be noninvasively traced and three-dimensionally (3D) reconstructed with DTI tractography. The DTI and conventional T1 weighted MRI images also provide sufficient cortical anatomical details for mapping the cortical regions of interests (ROIs). In this paper, we described basic concepts and methods of DTI techniques that can be used to trace major WM tracts noninvasively from fetal brain of 14 postconceptional weeks (pcw) to adult brain. We applied these techniques to acquire DTI data and trace, reconstruct and visualize major WM tracts during development. After categorizing major WM fiber bundles into five unique functional tract groups, namely limbic, brain stem, projection, commissural and association tracts, we revealed formation and maturation of these 3D reconstructed WM tracts of the developing human brain. The structural and connectional imaging data offered by DTI provides the anatomical backbone of transcriptional atlas of the developing human brain. PMID:25448302
Ouyang, Austin; Jeon, Tina; Sunkin, Susan M; Pletikos, Mihovil; Sedmak, Goran; Sestan, Nenad; Lein, Ed S; Huang, Hao
2015-02-01
During human brain development from fetal stage to adulthood, the white matter (WM) tracts undergo dramatic changes. Diffusion tensor imaging (DTI), a widely used magnetic resonance imaging (MRI) modality, offers insight into the dynamic changes of WM fibers as these fibers can be noninvasively traced and three-dimensionally (3D) reconstructed with DTI tractography. The DTI and conventional T1 weighted MRI images also provide sufficient cortical anatomical details for mapping the cortical regions of interests (ROIs). In this paper, we described basic concepts and methods of DTI techniques that can be used to trace major WM tracts noninvasively from fetal brain of 14 postconceptional weeks (pcw) to adult brain. We applied these techniques to acquire DTI data and trace, reconstruct and visualize major WM tracts during development. After categorizing major WM fiber bundles into five unique functional tract groups, namely limbic, brain stem, projection, commissural and association tracts, we revealed formation and maturation of these 3D reconstructed WM tracts of the developing human brain. The structural and connectional imaging data offered by DTI provides the anatomical backbone of transcriptional atlas of the developing human brain. Copyright © 2014 Elsevier Inc. All rights reserved.
The tensor structure on the representation category of the Wp triplet algebra
International Nuclear Information System (INIS)
Tsuchiya, Akihiro; Wood, Simon
2013-01-01
We study the braided monoidal structure that the fusion product induces on the Abelian category W p -mod, the category of representations of the triplet W-algebra W p . The W p -algebras are a family of vertex operator algebras that form the simplest known examples of symmetry algebras of logarithmic conformal field theories. We formalize the methods for computing fusion products, developed by Nahm, Gaberdiel and Kausch, that are widely used in the physics literature and illustrate a systematic approach to calculating fusion products in non-semi-simple representation categories. We apply these methods to the braided monoidal structure of W p -mod, previously constructed by Huang, Lepowsky and Zhang, to prove that this braided monoidal structure is rigid. The rigidity of W p -mod allows us to prove explicit formulae for the fusion product on the set of all simple and all projective W p -modules, which were first conjectured by Fuchs, Hwang, Semikhatov and Tipunin; and Gaberdiel and Runkel. (paper)
Hayakawa, Yayoi K; Sasaki, Hiroki; Takao, Hidemasa; Mori, Harushi; Hayashi, Naoto; Kunimatsu, Akira; Aoki, Shigeki; Ohtomo, Kuni
2013-01-25
Brain structural changes accompany major depressive disorder, but whether subclinical depression is accompanied by similar changes in brain volume and white matter integrity is unknown. By using voxel-based morphometry (VBM) of the gray matter and tract-specific analysis based on diffusion tensor imaging (DTI) of the white matter, we explored the extent to which abnormalities could be identified in specific brain structures of healthy adults with subclinical depression. The subjects were 21 community-dwelling adults with subclinical depression, as measured by their Center for Epidemiologic Studies Depression Scale (CES-D) scores. They were not demented and had no neurological or psychiatric history. We collected brain magnetic resonance images of the patients and of 21 matched control subjects, and we used VBM to analyze the differences in regional gray matter volume between the two groups. Moreover, we examined the white matter integrity by using tract-specific analysis based on the gray matter volume changes revealed by VBM. VBM revealed that the volumes of both anterior cingulate gyri and the right rectal gyrus were smaller in subclinically depressed women than in control women. Calculation of DTI measures in the anterior cingulum bundle revealed a positive correlation between CES-D scale score and radial diffusivity in the right anterior cingulum in subclinically depressed women. The small sample size limits the stability of the reported findings. Gray matter volume reduction and white matter integrity change in specific frontal brain regions may be associated with depressive symptoms in women, even at a subclinical level. Copyright © 2012 Elsevier B.V. All rights reserved.
Brun, Caroline C; Leporé, Natasha; Pennec, Xavier; Lee, Agatha D; Barysheva, Marina; Madsen, Sarah K; Avedissian, Christina; Chou, Yi-Yu; de Zubicaray, Greig I; McMahon, Katie L; Wright, Margaret J; Toga, Arthur W; Thompson, Paul M
2009-10-15
Genetic and environmental factors influence brain structure and function profoundly. The search for heritable anatomical features and their influencing genes would be accelerated with detailed 3D maps showing the degree to which brain morphometry is genetically determined. As part of an MRI study that will scan 1150 twins, we applied Tensor-Based Morphometry to compute morphometric differences in 23 pairs of identical twins and 23 pairs of same-sex fraternal twins (mean age: 23.8+/-1.8 SD years). All 92 twins' 3D brain MRI scans were nonlinearly registered to a common space using a Riemannian fluid-based warping approach to compute volumetric differences across subjects. A multi-template method was used to improve volume quantification. Vector fields driving each subject's anatomy onto the common template were analyzed to create maps of local volumetric excesses and deficits relative to the standard template. Using a new structural equation modeling method, we computed the voxelwise proportion of variance in volumes attributable to additive (A) or dominant (D) genetic factors versus shared environmental (C) or unique environmental factors (E). The method was also applied to various anatomical regions of interest (ROIs). As hypothesized, the overall volumes of the brain, basal ganglia, thalamus, and each lobe were under strong genetic control; local white matter volumes were mostly controlled by common environment. After adjusting for individual differences in overall brain scale, genetic influences were still relatively high in the corpus callosum and in early-maturing brain regions such as the occipital lobes, while environmental influences were greater in frontal brain regions that have a more protracted maturational time-course.
Tensor Transpose and Its Properties
Pan, Ran
2014-01-01
Tensor transpose is a higher order generalization of matrix transpose. In this paper, we use permutations and symmetry group to define? the tensor transpose. Then we discuss the classification and composition of tensor transposes. Properties of tensor transpose are studied in relation to tensor multiplication, tensor eigenvalues, tensor decompositions and tensor rank.
The 1/ N Expansion of Tensor Models with Two Symmetric Tensors
Gurau, Razvan
2018-06-01
It is well known that tensor models for a tensor with no symmetry admit a 1/ N expansion dominated by melonic graphs. This result relies crucially on identifying jackets, which are globally defined ribbon graphs embedded in the tensor graph. In contrast, no result of this kind has so far been established for symmetric tensors because global jackets do not exist. In this paper we introduce a new approach to the 1/ N expansion in tensor models adapted to symmetric tensors. In particular we do not use any global structure like the jackets. We prove that, for any rank D, a tensor model with two symmetric tensors and interactions the complete graph K D+1 admits a 1/ N expansion dominated by melonic graphs.
Directory of Open Access Journals (Sweden)
Lingjia Xu
2007-04-01
Full Text Available The interaction of dopamine with adenine and guanine were studied at the Hartree-Fock level theory. The structural and vibrational properties of dopamine-4-N7GUA and dopamine-4-N3ADE were studied at level of HF/6-31G*. Interaction energies (ΔE were calculated to be -11.49 and -11.92 kcal/mol, respectively. Some of bond lengths, angels and tortions are compared. NBO studies were performed to the second-order and perturbative estimates of donor-acceptor interaction have been done. The procedures of gauge-invariant atomic orbital (GIAO and continuous-set-of-gauge-transformation (CSGT were employed to calculate isotropic shielding, chemical shifts anisotropy and chemical shifts anisotropy asymmetry and effective anisotropy using 6-31G* basis set. These calculations yielded molecular geometries in good agreement with available experimental data.
International Nuclear Information System (INIS)
Littlejohn, R.G.
1982-01-01
The Hamiltonian structures discovered by Morrison and Greene for various fluid equations were obtained by guessing a Hamiltonian and a suitable Poisson bracket formula, expressed in terms of noncanonical (but physical) coordinates. In general, such a procedure for obtaining a Hamiltonian system does not produce a Hamiltonian phase space in the usual sense (a symplectic manifold), but rather a family of symplectic manifolds. To state the matter in terms of a system with a finite number of degrees of freedom, the family of symplectic manifolds is parametrized by a set of Casimir functions, which are characterized by having vanishing Poisson brackets with all other functions. The number of independent Casimir functions is the corank of the Poisson tensor J/sup ij/, the components of which are the Poisson brackets of the coordinates among themselves. Thus, these Casimir functions exist only when the Poisson tensor is singular
International Nuclear Information System (INIS)
Hong Fenglei; Zhang Yun; Ishikawa, Jun; Onae, Atsushi; Matsumoto, Hirokazu
2002-01-01
Hyperfine structures of the R(87)33-0, R(145)37-0, and P(132)36-0 transitions of molecular iodine near 532 nm are measured by observing the heterodyne beat-note signal of two I 2 -stabilized lasers, whose frequencies are bridged by an optical frequency comb generator. The measured hyperfine splittings are fit to a four-term Hamiltonian, which includes the electric quadrupole, spin-rotation, tensor spin-spin, and scalar spin-spin interactions, with an accuracy of ∼720 Hz. High-accurate hyperfine constants are obtained from this fit. Vibration dependences of the tensor spin-spin and scalar spin-spin hyperfine constants are determined for molecular iodine, for the first time to our knowledge. The observed hyperfine transitions are good optical frequency references in the 532-nm region
International Nuclear Information System (INIS)
Buchner, Abel-John; Kitsios, Vassili; Atkinson, Callum; Soria, Julio; Lozano-Durán, Adrián
2016-01-01
Previous works have shown that momentum transfer in the wall–normal direction within turbulent wall–bounded flows occurs primarily within coherent structures defined by regions of intense Reynolds stress [1]. Such structures may be classified into wall–attached and wall–detached structures with the latter being typically weak, small–scale, and isotropically oriented, while the former are larger and carry most of the Reynolds stresses. The mean velocity fluctuation within each structure may also be used to separate structures by their dynamic properties. This study aims to extract information regarding the scales, kinematics and dynamics of these structures within the topological framework of the invariants of the velocity gradient tensor (VGT). The local topological characteristics of these intense Reynolds stress structures are compared to the topological characteristics of vortex clusters defined by the discriminant of the velocity gradient tensor. The alignment of vorticity with the principal strain directions within these structures is also determined, and the implications of these findings are discussed. (paper)
Hess, Siegfried
2015-01-01
This book presents the science of tensors in a didactic way. The various types and ranks of tensors and the physical basis is presented. Cartesian Tensors are needed for the description of directional phenomena in many branches of physics and for the characterization the anisotropy of material properties. The first sections of the book provide an introduction to the vector and tensor algebra and analysis, with applications to physics, at undergraduate level. Second rank tensors, in particular their symmetries, are discussed in detail. Differentiation and integration of fields, including generalizations of the Stokes law and the Gauss theorem, are treated. The physics relevant for the applications in mechanics, quantum mechanics, electrodynamics and hydrodynamics is presented. The second part of the book is devoted to tensors of any rank, at graduate level. Special topics are irreducible, i.e. symmetric traceless tensors, isotropic tensors, multipole potential tensors, spin tensors, integration and spin-...
Gurau, Razvan
2017-01-01
Written by the creator of the modern theory of random tensors, this book is the first self-contained introductory text to this rapidly developing theory. Starting from notions familiar to the average researcher or PhD student in mathematical or theoretical physics, the book presents in detail the theory and its applications to physics. The recent detections of the Higgs boson at the LHC and gravitational waves at LIGO mark new milestones in Physics confirming long standing predictions of Quantum Field Theory and General Relativity. These two experimental results only reinforce today the need to find an underlying common framework of the two: the elusive theory of Quantum Gravity. Over the past thirty years, several alternatives have been proposed as theories of Quantum Gravity, chief among them String Theory. While these theories are yet to be tested experimentally, key lessons have already been learned. Whatever the theory of Quantum Gravity may be, it must incorporate random geometry in one form or another....
Tensor rank is not multiplicative under the tensor product
DEFF Research Database (Denmark)
Christandl, Matthias; Jensen, Asger Kjærulff; Zuiddam, Jeroen
2018-01-01
The tensor rank of a tensor t is the smallest number r such that t can be decomposed as a sum of r simple tensors. Let s be a k-tensor and let t be an ℓ-tensor. The tensor product of s and t is a (k+ℓ)-tensor. Tensor rank is sub-multiplicative under the tensor product. We revisit the connection b...
Tensor rank is not multiplicative under the tensor product
M. Christandl (Matthias); A. K. Jensen (Asger Kjærulff); J. Zuiddam (Jeroen)
2018-01-01
textabstractThe tensor rank of a tensor t is the smallest number r such that t can be decomposed as a sum of r simple tensors. Let s be a k-tensor and let t be an ℓ-tensor. The tensor product of s and t is a (k+ℓ)-tensor. Tensor rank is sub-multiplicative under the tensor product. We revisit the
Tensor rank is not multiplicative under the tensor product
M. Christandl (Matthias); A. K. Jensen (Asger Kjærulff); J. Zuiddam (Jeroen)
2017-01-01
textabstractThe tensor rank of a tensor is the smallest number r such that the tensor can be decomposed as a sum of r simple tensors. Let s be a k-tensor and let t be an l-tensor. The tensor product of s and t is a (k + l)-tensor (not to be confused with the "tensor Kronecker product" used in
The Topology of Symmetric Tensor Fields
Levin, Yingmei; Batra, Rajesh; Hesselink, Lambertus; Levy, Yuval
1997-01-01
Combinatorial topology, also known as "rubber sheet geometry", has extensive applications in geometry and analysis, many of which result from connections with the theory of differential equations. A link between topology and differential equations is vector fields. Recent developments in scientific visualization have shown that vector fields also play an important role in the analysis of second-order tensor fields. A second-order tensor field can be transformed into its eigensystem, namely, eigenvalues and their associated eigenvectors without loss of information content. Eigenvectors behave in a similar fashion to ordinary vectors with even simpler topological structures due to their sign indeterminacy. Incorporating information about eigenvectors and eigenvalues in a display technique known as hyperstreamlines reveals the structure of a tensor field. The simplify and often complex tensor field and to capture its important features, the tensor is decomposed into an isotopic tensor and a deviator. A tensor field and its deviator share the same set of eigenvectors, and therefore they have a similar topological structure. A a deviator determines the properties of a tensor field, while the isotopic part provides a uniform bias. Degenerate points are basic constituents of tensor fields. In 2-D tensor fields, there are only two types of degenerate points; while in 3-D, the degenerate points can be characterized in a Q'-R' plane. Compressible and incompressible flows share similar topological feature due to the similarity of their deviators. In the case of the deformation tensor, the singularities of its deviator represent the area of vortex core in the field. In turbulent flows, the similarities and differences of the topology of the deformation and the Reynolds stress tensors reveal that the basic addie-viscosity assuptions have their validity in turbulence modeling under certain conditions.
Rose, Jessica; Butler, Erin E; Lamont, Lauren E; Barnes, Patrick D; Atlas, Scott W; Stevenson, David K
2009-07-01
The neurological basis of an increased incidence of cerebral palsy (CP) in preterm males is unknown. This study examined neonatal brain structure on magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) at term-equivalent age, sex, and neurodevelopment at 1 year 6 months on the basis of the Amiel-Tison neurological examination, Gross Motor Function Classification System, and Bayley Scales of Infant Development in 78 very-low-birthweight preterm children (41 males, 37 females; mean gestational age 27.6 wks, SD 2.5; mean birthweight 1021 g, SD 339). Brain abnormalities on MRI and DTI were not different between males and females except in the splenium of the corpus callosum, where males had lower DTI fractional anisotropy (p=0.025) and a higher apparent diffusion coefficient (p=0.013), indicating delayed splenium development. In the 26 infants who were at higher risk on the basis of DTI, males had more abnormalities on MRI (p=0.034) and had lower fractional anisotropy and a higher apparent diffusion coefficient in the splenium (p=0.049; p=0.025) and right posterior limb of the internal capsule (PLIC; p=0.003; p=0.033). Abnormal neurodevelopment was more common in males (n=9) than in females (n=2; p=0.036). Children with abnormal neurodevelopment had more abnormalities on MRI (p=0.014) and reduced splenium and right PLIC fractional anisotropy (p=0.001; p=0.035). In children with abnormal neurodevelopment, right PLIC fractional anisotropy was lower than left (p=0.035), whereas in those with normal neurodevelopment right PLIC fractional anisotropy was higher than left (p=0.001). Right PLIC fractional anisotropy correlated to neurodevelopment (rho=0.371, p=0.002). Logistic regression predicted neurodevelopment with 94% accuracy; only right PLIC fractional anisotropy was a significant logistic coefficient. Results indicate that the higher incidence of abnormal neurodevelopment in preterm males relates to greater incidence and severity of brain abnormalities
Tensor fields on orbits of quantum states and applications
Energy Technology Data Exchange (ETDEWEB)
Volkert, Georg Friedrich
2010-07-19
On classical Lie groups, which act by means of a unitary representation on finite dimensional Hilbert spaces H, we identify two classes of tensor field constructions. First, as pull-back tensor fields of order two from modified Hermitian tensor fields, constructed on Hilbert spaces by means of the property of having the vertical distributions of the C{sub 0}-principal bundle H{sub 0} {yields} P(H) over the projective Hilbert space P(H) in the kernel. And second, directly constructed on the Lie group, as left-invariant representation-dependent operator-valued tensor fields (LIROVTs) of arbitrary order being evaluated on a quantum state. Within the NP-hard problem of deciding whether a given state in a n-level bi-partite quantum system is entangled or separable (Gurvits, 2003), we show that both tensor field constructions admit a geometric approach to this problem, which evades the traditional ambiguity on defining metrical structures on the convex set of mixed states. In particular by considering manifolds associated to orbits passing through a selected state when acted upon by the local unitary group U(n) x U(n) of Schmidt coefficient decomposition inducing transformations, we find the following results: In the case of pure states we show that Schmidt-equivalence classes which are Lagrangian submanifolds define maximal entangled states. This implies a stronger statement as the one proposed by Bengtsson (2007). Moreover, Riemannian pull-back tensor fields split on orbits of separable states and provide a quantitative characterization of entanglement which recover the entanglement measure proposed by Schlienz and Mahler (1995). In the case of mixed states we highlight a relation between LIROVTs of order two and a class of computable separability criteria based on the Bloch-representation (de Vicente, 2007). (orig.)
Tensor fields on orbits of quantum states and applications
International Nuclear Information System (INIS)
Volkert, Georg Friedrich
2010-01-01
On classical Lie groups, which act by means of a unitary representation on finite dimensional Hilbert spaces H, we identify two classes of tensor field constructions. First, as pull-back tensor fields of order two from modified Hermitian tensor fields, constructed on Hilbert spaces by means of the property of having the vertical distributions of the C 0 -principal bundle H 0 → P(H) over the projective Hilbert space P(H) in the kernel. And second, directly constructed on the Lie group, as left-invariant representation-dependent operator-valued tensor fields (LIROVTs) of arbitrary order being evaluated on a quantum state. Within the NP-hard problem of deciding whether a given state in a n-level bi-partite quantum system is entangled or separable (Gurvits, 2003), we show that both tensor field constructions admit a geometric approach to this problem, which evades the traditional ambiguity on defining metrical structures on the convex set of mixed states. In particular by considering manifolds associated to orbits passing through a selected state when acted upon by the local unitary group U(n) x U(n) of Schmidt coefficient decomposition inducing transformations, we find the following results: In the case of pure states we show that Schmidt-equivalence classes which are Lagrangian submanifolds define maximal entangled states. This implies a stronger statement as the one proposed by Bengtsson (2007). Moreover, Riemannian pull-back tensor fields split on orbits of separable states and provide a quantitative characterization of entanglement which recover the entanglement measure proposed by Schlienz and Mahler (1995). In the case of mixed states we highlight a relation between LIROVTs of order two and a class of computable separability criteria based on the Bloch-representation (de Vicente, 2007). (orig.)
Hiramatsu, Y.; Matsumoto, N.; Sawada, A.
2016-12-01
We analyze gravity anomalies in the focal area of the 2016 Kumamoto earthquake, evaluate the continuity, segmentation and faulting type of the active fault zones, and discuss relationships between those features and the aftershock distribution. We compile the gravity data published by the Gravity Research Group in Southwest Japan (2001), the Geographical Survey Institute (2006), Yamamoto et al. (2011), Honda et al. (2012), and the Geological Survey of Japan, AIST (2013). We apply terrain corrections with 10 m DEM and a low-pass filter, then remove a linear trend to obtain Bouguer anomalies. We calculate the first horizontal derivative (HD), the first vertical derivative (VD), the normalized total horizontal derivative (TDX) (Cooper and Cowan, 2006), the dimensionality index (Di) (Beki and Pedersen, 2010), and dip angle (β) (Beki, 2013) from a gravity gradient tensor. The HD, VD and TDX show the existence of the continuous fault structure along the Futagawa fault zone, extending from the Uto peninsula to the Beppu Bay except Mt. Aso area. Aftershocks are distributed along this structural boundary from the confluence of the Futagawa and the Hinagu fault zones to the east end of the Aso volcano. The distribution of dip angle β along the Futagawa fault zone implies a normal faulting, which corresponds to the coseismic faulting estimated geologically and geomorphologically. We observe the S-shaped distribution of the Bouguer anomalies around the southern part of the Hinagu segment, indicating a right lateral faulting. The VD and TDX support the existence of the fault structure along the segment but it is not so clear. We can recognize no clear structural boundaries along the Takano-Shirahata segment. TDX implies the existence of a structural boundary with a NW-SE trend around the boundary between the Hinagu and Takano-Shirahata segments. The Di shows that this boundary has a 3D-like structure rather than a 2D-like one, suggesting the discontinuity of 2D-like fault
Tensor rank is not multiplicative under the tensor product
Christandl, Matthias; Jensen, Asger Kjærulff; Zuiddam, Jeroen
2017-01-01
The tensor rank of a tensor t is the smallest number r such that t can be decomposed as a sum of r simple tensors. Let s be a k-tensor and let t be an l-tensor. The tensor product of s and t is a (k + l)-tensor. Tensor rank is sub-multiplicative under the tensor product. We revisit the connection between restrictions and degenerations. A result of our study is that tensor rank is not in general multiplicative under the tensor product. This answers a question of Draisma and Saptharishi. Specif...
Energy-momentum tensor in the fermion-pairing model
International Nuclear Information System (INIS)
Kawati, S.; Miyata, H.
1980-01-01
The symmetric energy-momentum tensor for the self-interacting fermion theory (psi-barpsi) 2 is expressed in terms of the collective mode within the Hartree approximation. The divergent part of the energy-momentum tensor for the fermion theory induces an effective energy-momentum tensor for the collective mode, and this effective energy-momentum tensor automatically has the Callan-Coleman-Jackiw improved form. The renormalized energy-momentum tensor is structurally equivalent to the Callan-Coleman-Jackiw improved tensor for the Yukawa theory
The structure of algebraic problem in high schools
Chio, José Angel; Álvarez, Aida; Estrada, Pablo
2010-01-01
The paper is aimed at discussing the importance of pupil’s knowledge of algebraic problem structure. The research started by diagnosing pupil’s actual command of algebraic problem structure. Finally suggestions to teachers of mathematics for facing difficulties in solving problems are given.
The structure of algebraic problem in high schools
Directory of Open Access Journals (Sweden)
Chio, José Angel
2010-01-01
Full Text Available The paper is aimed at discussing the importance of pupil’s knowledge of algebraic problem structure. The research started by diagnosing pupil’s actual command of algebraic problem structure. Finally suggestions to teachers of mathematics for facing difficulties in solving problems are given.
The tensor part of the Skyrme energy density functional. I. Spherical nuclei
Energy Technology Data Exchange (ETDEWEB)
Lesinski, T.; Meyer, J. [Universite de Lyon, F-69003 Lyon (France)]|[Institut de Physique Nucleaire de Lyon, CNRS/IN2P3, Universite Lyon 1, F-69622 Villeurbanne (France); Bender, M. [DSM/DAPNIA/SPhN, CEA Saclay, F-91191 Gif-sur-Yvette Cedex (France)]|[Universite Bordeaux, CNRS/IN2P3, Centre d' Etudes Nucleaires de Bordeaux Gradignan, UMR5797, Chemin du Solarium, BP120, F-33175 Gradignan (France); Bennaceur, K. [Universite de Lyon, F-69003 Lyon (France)]|[Institut de Physique Nucleaire de Lyon, CNRS/IN2P3, Universite Lyon 1, F-69622 Villeurbanne (France)]|[DSM/DAPNIA/SPhN, CEA Saclay, F-91191 Gif-sur-Yvette Cedex (France); Duguet, T. [National Superconducting Cyclotron Laboratory and Department of Physics and Astronomy, Michigan State University, East Lansing, MI 48824 (United States)
2007-04-15
We perform a systematic study of the impact of the J-vector{sup 2} tensor term in the Skyrme energy functional on properties of spherical nuclei. In the Skyrme energy functional, the tensor terms originate both from zero-range central and tensor forces. We build a set of 36 parameterizations which cover a wide range of the parameter space of the isoscalar and isovector tensor term coupling constants with a fit protocol very similar to that of the successful SLy parameterizations. We analyze the impact of the tensor terms on a large variety of observables in spherical mean-field calculations, such as the spin-orbit splittings and single-particle spectra of doubly-magic nuclei, the evolution of spin-orbit splittings along chains of semi-magic nuclei, mass residuals of spherical nuclei, and known anomalies of radii. The major findings of our study are (i) tensor terms should not be added perturbatively to existing parameterizations, a complete refit of the entire parameter set is imperative. (ii) The free variation of the tensor terms does not lower the {chi}{sup 2} within a standard Skyrme energy functional. (iii) For certain regions of the parameter space of their coupling constants, the tensor terms lead to instabilities of the spherical shell structure, or even the coexistence of two configurations with different spherical shell structure. (iv) The standard spin-orbit interaction does not scale properly with the principal quantum number, such that single-particle states with one or several nodes have too large spin-orbit splittings, while those of node-less intruder levels are tentatively too small. Tensor terms with realistic coupling constants cannot cure this problem. (v) Positive values of the coupling constants of proton-neutron and like-particle tensor terms allow for a qualitative description of the evolution of spin-orbit splittings in chains of Ca, Ni and Sn isotopes. (vi) For the same values of the tensor term coupling constants, however, the overall
Efficient Tensor Strategy for Recommendation
Directory of Open Access Journals (Sweden)
Aboagye Emelia Opoku
2017-07-01
Full Text Available The era of big data has witnessed the explosion of tensor datasets, and large scale Probabilistic Tensor Factorization (PTF analysis is important to accommodate such increasing trend of data. Sparsity, and Cold-Start are some of the inherent problems of recommender systems in the era of big data. This paper proposes a novel Sentiment-Based Probabilistic Tensor Analysis technique senti-PTF to address the problems. The propose framework first applies a Natural Language Processing technique to perform sentiment analysis taking advantage of the huge sums of textual data generated available from the social media which are predominantly left untouched. Although some current studies do employ review texts, many of them do not consider how sentiments in reviews influence recommendation algorithm for prediction. There is therefore this big data text analytics gap whose modeling is computationally expensive. From our experiments, our novel machine learning sentiment-based tensor analysis is computationally less expensive, and addresses the cold-start problem, for optimal recommendation prediction.
Directory of Open Access Journals (Sweden)
Richard Lewerissa
2017-12-01
Full Text Available In early 2017, the geothermal system in the Suli and Tulehu areas of Ambon (Indonesia was investigated using a gravity gradient tensor and analytic signal. The gravity gradient tensor and analytic signal were obtained through forward modeling based on a rectangular prism. It was applied to complete Bouguer anomaly data over the study area by using Fast Fourier Transform (FFT. The analysis was conducted to enhance the geological structure like faults as a pathway of geothermal fluid circulation that is not visible on the surface because it is covered by sediment. The complete Bouguer anomaly ranges of 93 mGal up to 105 mGal decrease from the southwest in Suli to the northeast in Tulehu. A high gravity anomaly indicates a strong magmatic intrusion below the Suli region. The gravity anomalies decrease occurs in the Eriwakang mountain and most of Tulehu, and it is associated with a coral limestone. The lower gravity anomalies are located in the north to the northeast part of Tulehu are associated with alluvium. The residual anomaly shows that the drill well TLU-01 and geothermal manifestations along with the Banda, and Banda-Hatuasa faults are associated with lowest gravity anomaly (negative zone. The gravity gradient tensor simulation and an analytic signal of Suli and Tulehu give more detailed information about the geological features. The gzz component allows accurate description of the shape structures, especially the Banda fault associated with a zero value. This result will be useful as a geophysical constraint to subsurface modeling according to gravity gradient inversion over the area.
Energy Technology Data Exchange (ETDEWEB)
Hohmann, Manuel [Physikalisches Institut, Universitaet Tartu (Estonia)
2016-07-01
Tensor harmonics are a useful mathematical tool for finding solutions to differential equations which transform under a particular representation of the rotation group SO(3). In order to make use of this tool also in the setting of Finsler geometry, where the objects of relevance are d-tensors instead of tensors, we construct a set of d-tensor harmonics for both SO(3) and SO(4) symmetries and show how these can be used for calculations in Finsler geometry and gravity.
An introduction to linear algebra and tensors
Akivis, M A; Silverman, Richard A
1978-01-01
Eminently readable, completely elementary treatment begins with linear spaces and ends with analytic geometry, covering multilinear forms, tensors, linear transformation, and more. 250 problems, most with hints and answers. 1972 edition.
Sirlin, Samuel W.
1993-01-01
Eight-page report describes systems of notation used most commonly to represent tensors of various ranks, with emphasis on tensors in Cartesian coordinate systems. Serves as introductory or refresher text for scientists, engineers, and others familiar with basic concepts of coordinate systems, vectors, and partial derivatives. Indicial tensor, vector, dyadic, and matrix notations, and relationships among them described.
Normal estimation for pointcloud using GPU based sparse tensor voting
Liu , Ming; Pomerleau , François; Colas , Francis; Siegwart , Roland
2012-01-01
International audience; Normal estimation is the basis for most applications using pointcloud, such as segmentation. However, it is still a challenging problem regarding computational complexity and observation noise. In this paper, we propose a normal estimation method for pointcloud using results from tensor voting. Comparing with other approaches, we show it has smaller estimation error. Moreover, by varying the voting kernel size, we find it is a flexible approach for structure extraction...
Structure problems in the analog computation
International Nuclear Information System (INIS)
Braffort, P.L.
1957-01-01
The recent mathematical development showed the importance of elementary structures (algebraic, topological, etc.) in abeyance under the great domains of classical analysis. Such structures in analog computation are put in evidence and possible development of applied mathematics are discussed. It also studied the topological structures of the standard representation of analog schemes such as additional triangles, integrators, phase inverters and functions generators. The analog method gives only the function of the variable: time, as results of its computations. But the course of computation, for systems including reactive circuits, introduces order structures which are called 'chronological'. Finally, it showed that the approximation methods of ordinary numerical and digital computation present the same structure as these analog computation. The structure analysis permits fruitful comparisons between the several domains of applied mathematics and suggests new important domains of application for analog method. (M.P.)
Dobaczewski, Jacek
2010-06-01
Nuclear structure theory is a domain of physics faced at present with great challenges and opportunities. A larger and larger body of high-precision experimental data has been and continues to be accumulated. Experiments on very exotic short-lived isotopes are the backbone of activity at numerous large-scale facilities. Over the years, tremendous progress has been made in understanding the basic features of nuclei. However, the theoretical description of nuclear systems is still far from being complete and is often not very precise. Many questions, both basic and practical, remain unanswered. The goal of publishing this special focus issue of Journal of Physics G: Nuclear and Particle Physics on Open Problems in Nuclear Structure Theory (OPeNST) is to construct a fundamental inventory thereof, so that the tasks and available options become more clearly exposed and that this will help to stimulate a boost in theoretical activity, commensurate with the experimental progress. The requested format and scope of the articles on OPeNST was quite flexible. The journal simply offered the possibility to provide a forum for the material, which is very often discussed at conferences during the coffee breaks but does not normally have sufficient substance to form regular publications. Nonetheless, very often formulating a problem provides a major step towards its solution, and it may constitute a scientific achievement on its own. Prospective authors were therefore invited to find their own balance between the two extremes of very general problems on the one hand (for example, to solve exactly the many-body equations for a hundred particles) and very specific problems on the other hand (for example, those that one could put in one's own grant proposal). The authors were also asked not to cover results already obtained, nor to limit their presentations to giving a review of the subject, although some elements of those could be included to properly introduce the subject matter
On some structure-turbulence interaction problems
Maekawa, S.; Lin, Y. K.
1976-01-01
The interactions between a turbulent flow structure; responding to its excitation were studied. The turbulence was typical of those associated with a boundary layer, having a cross-spectral density indicative of convection and statistical decay. A number of structural models were considered. Among the one-dimensional models were an unsupported infinite beam and a periodically supported infinite beam. The fuselage construction of an aircraft was then considered. For the two-dimensional case a simple membrane was used to illustrate the type of formulation applicable to most two-dimensional structures. Both the one-dimensional and two-dimensional structures studied were backed by a cavity filled with an initially quiescent fluid to simulate the acoustic environment when the structure forms one side of a cabin of a sea vessel or aircraft.
International Nuclear Information System (INIS)
Beig, Robert; Krammer, Werner
2004-01-01
For a conformally flat 3-space, we derive a family of linear second-order partial differential operators which sends vectors into trace-free, symmetric 2-tensors. These maps, which are parametrized by conformal Killing vectors on the 3-space, are such that the divergence of the resulting tensor field depends only on the divergence of the original vector field. In particular, these maps send source-free electric fields into TT tensors. Moreover, if the original vector field is the Coulomb field on R 3 {0}, the resulting tensor fields on R 3 {0} are nothing but the family of TT tensors originally written by Bowen and York
Problem communication (homeostatic structuring of information)
Energy Technology Data Exchange (ETDEWEB)
Bogdanov, N I
1982-01-01
This paper investigates the fundamental connection of intellectual and homeostatic levels of treating information which appear in information structuring. The laws obtained can be applied to artificial intelligence in studies of communication and education. 4 references.
Particle Swarm Optimization for Structural Design Problems
Directory of Open Access Journals (Sweden)
Hamit SARUHAN
2010-02-01
Full Text Available The aim of this paper is to employ the Particle Swarm Optimization (PSO technique to a mechanical engineering design problem which is minimizing the volume of a cantilevered beam subject to bending strength constraints. Mechanical engineering design problems are complex activities which are computing capability are more and more required. The most of these problems are solved by conventional mathematical programming techniques that require gradient information. These techniques have several drawbacks from which the main one is becoming trapped in local optima. As an alternative to gradient-based techniques, the PSO does not require the evaluation of gradients of the objective function. The PSO algorithm employs the generation of guided random positions when they search for the global optimum point. The PSO which is a nature inspired heuristics search technique imitates the social behavior of bird flocking. The results obtained by the PSO are compared with Mathematical Programming (MP. It is demonstrated that the PSO performed and obtained better convergence reliability on the global optimum point than the MP. Using the MP, the volume of 2961000 mm3 was obtained while the beam volume of 2945345 mm3 was obtained by the PSO.
Kikuchi, Kazufumi; Hiwatashi, Akio; Togao, Osamu; Yamashita, Koji; Somehara, Ryo; Kamei, Ryotaro; Baba, Shingo; Yamaguchi, Hiroo; Kira, Jun-Ichi; Honda, Hiroshi
2017-12-01
Patients with Parkinson's disease (PD) may exhibit symptoms of sympathetic dysfunction that can be measured using 123 I-metaiodobenzylguanidine (MIBG) myocardial scintigraphy. We investigated the relationship between microstructural brain changes and 123 I-MIBG uptake in patients with PD using voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) analyses. This retrospective study included 24 patients with PD who underwent 3 T magnetic resonance imaging and 123 I-MIBG scintigraphy. They were divided into two groups: 12 MIBG-positive and 12 MIBG-negative cases (10 men and 14 women; age range: 60-81 years, corrected for gender and age). The heart/mediastinum count (H/M) ratio was calculated on anterior planar 123 I-MIBG images obtained 4 h post-injection. VBM and DTI were performed to detect structural differences between these two groups. Patients with low H/M ratio had significantly reduced brain volume at the right inferior frontal gyrus (uncorrected p 90). Patients with low H/M ratios also exhibited significantly lower fractional anisotropy than those with high H/M ratios (p based morphometry can detect grey matter changes in Parkinson's disease. • Diffusion tensor imaging can detect white matter changes in Parkinson's disease.
Modeling the Structure and Complexity of Engineering Routine Design Problems
Jauregui Becker, Juan Manuel; Wits, Wessel Willems; van Houten, Frederikus J.A.M.
2011-01-01
This paper proposes a model to structure routine design problems as well as a model of its design complexity. The idea is that having a proper model of the structure of such problems enables understanding its complexity, and likewise, a proper understanding of its complexity enables the development
Structuring and assessing large and complex decision problems using MCDA
DEFF Research Database (Denmark)
Barfod, Michael Bruhn
This paper presents an approach for the structuring and assessing of large and complex decision problems using multi-criteria decision analysis (MCDA). The MCDA problem is structured in a decision tree and assessed using the REMBRANDT technique featuring a procedure for limiting the number of pair...
Asessing for Structural Understanding in Childrens' Combinatorial Problem Solving.
English, Lyn
1999-01-01
Assesses children's structural understanding of combinatorial problems when presented in a variety of task situations. Provides an explanatory model of students' combinatorial understandings that informs teaching and assessment. Addresses several components of children's structural understanding of elementary combinatorial problems. (Contains 50…
Scalable tensor factorizations for incomplete data
DEFF Research Database (Denmark)
Acar, Evrim; Dunlavy, Daniel M.; KOlda, Tamara G.
2011-01-01
to factorize data sets with missing values with the goal of capturing the underlying latent structure of the data and possibly reconstructing missing values (i.e., tensor completion). We focus on one of the most well-known tensor factorizations that captures multi-linear structure, CANDECOMP/PARAFAC (CP...... experiments, our algorithm is shown to successfully factorize tensors with noise and up to 99% missing data. A unique aspect of our approach is that it scales to sparse large-scale data, e.g., 1000 × 1000 × 1000 with five million known entries (0.5% dense). We further demonstrate the usefulness of CP...
Scalable Tensor Factorizations with Missing Data
DEFF Research Database (Denmark)
Acar, Evrim; Dunlavy, Daniel M.; Kolda, Tamara G.
2010-01-01
of missing data, many important data sets will be discarded or improperly analyzed. Therefore, we need a robust and scalable approach for factorizing multi-way arrays (i.e., tensors) in the presence of missing data. We focus on one of the most well-known tensor factorizations, CANDECOMP/PARAFAC (CP...... is shown to successfully factor tensors with noise and up to 70% missing data. Moreover, our approach is significantly faster than the leading alternative and scales to larger problems. To show the real-world usefulness of CP-WOPT, we illustrate its applicability on a novel EEG (electroencephalogram...
Zhong, Zhaoxi; Zhao, Tengda; Luo, Jia; Guo, Zhihua; Guo, Meng; Li, Ping; Sun, Jing; He, Yong; Li, Zhanjiang
2014-06-03
Obsessive-compulsive disorder (OCD) is a chronic psychiatric disorder defined by recurrent thoughts, intrusive and distressing impulses, or images and ritualistic behaviors. Although focal diverse regional abnormalities white matter integrity in specific brain regions have been widely studied in populations with OCD, alterations in the structural connectivities among them remain poorly understood. The aim was to investigate the abnormalities in the topological efficiency of the white matter networks and the correlation between the network metrics and Yale-Brown Obsessive-Compulsive Scale scores in unmedicated OCD patients, using diffusion tensor tractography and graph theoretical approaches. This study used diffusion tensor imaging and deterministic tractography to map the white matter structural networks in 26 OCD patients and 39 age- and gender-matched healthy controls; and then applied graph theoretical methods to investigate abnormalities in the global and regional properties of the white matter network in these patients. The patients and control participants both showed small-world organization of the white matter networks. However, the OCD patients exhibited significant abnormal global topology, including decreases in global efficiency (t = -2.32, p = 0.02) and increases in shortest path length, Lp (t = 2.30, p = 0.02), the normalized weighted shortest path length, λ (t = 2.08, p=0.04), and the normalized clustering coefficient, γ (t = 2.26, p = 0.03), of their white matter structural networks compared with healthy controls. Further, the OCD patients showed a reduction in nodal efficiency predominately in the frontal regions, the parietal regions and caudate nucleus. The normalized weighted shortest path length of the network metrics was significantly negatively correlated with obsessive subscale of the Yale-Brown Obsessive-Compulsive Scale (r = -0.57, p = 0.0058). These findings demonstrate the abnormal topological efficiency in the white matter networks
Prescribed curvature tensor in locally conformally flat manifolds
Pina, Romildo; Pieterzack, Mauricio
2018-01-01
A global existence theorem for the prescribed curvature tensor problem in locally conformally flat manifolds is proved for a special class of tensors R. Necessary and sufficient conditions for the existence of a metric g ¯ , conformal to Euclidean g, are determined such that R ¯ = R, where R ¯ is the Riemannian curvature tensor of the metric g ¯ . The solution to this problem is given explicitly for special cases of the tensor R, including the case where the metric g ¯ is complete on Rn. Similar problems are considered for locally conformally flat manifolds.
Heat structural problems in JT-60
International Nuclear Information System (INIS)
Takatsu, Hideyuki; Shimizu, Masaomi; Yamamoto, Masahiro; Nakamura, Hiroo; Miyauchi, Yasuyuki.
1980-01-01
The construction of JT-60 is in progress to study the behavior of hydrogen plasma. The D-T reaction does not occur in this device, therefore the considerations for neutron damage, tritium leakage and so on are not necessary. The long-pulse operation will be done, and the suppression of the production and mixing of impurity is considered in the design of the JT-60. The high temperature baking is possible, and the magnetic limiter is set. The vacuum container has the complex structure consists of 8 sector type thick rings and 8 U-shaped bellows, and has egg-shaped cross section. The main radius of the torus is about 3 m. The material of the vacuum container is INCONEL 625. The analyses of various stresses due to such as atmospheric pressure, eddy current and thermal expansion were made. It is also necessary to consider the thermal stress due to the leakage of neutral beam. The thermal input of about 20 MW per one discharge to the first wall is taken into consideration. The material of the first wall is molybdenum. (Kato, T.)
Deep learning and the electronic structure problem
Mills, Kyle; Spanner, Michael; Tamblyn, Isaac
In the past decade, the fields of artificial intelligence and computer vision have progressed remarkably. Supported by the enthusiasm of large tech companies, as well as significant hardware advances and the utilization of graphical processing units to accelerate computations, deep neural networks (DNN) are gaining momentum as a robust choice for many diverse machine learning applications. We have demonstrated the ability of a DNN to solve a quantum mechanical eigenvalue equation directly, without the need to compute a wavefunction, and without knowledge of the underlying physics. We have trained a convolutional neural network to predict the total energy of an electron in a confining, 2-dimensional electrostatic potential. We numerically solved the one-electron Schrödinger equation for millions of electrostatic potentials, and used this as training data for our neural network. Four classes of potentials were assessed: the canonical cases of the harmonic oscillator and infinite well, and two types of randomly generated potentials for which no analytic solution is known. We compare the performance of the neural network and consider how these results could lead to future advances in electronic structure theory.
On some fundamental properties of structural topology optimization problems
DEFF Research Database (Denmark)
Stolpe, Mathias
2010-01-01
We study some fundamental mathematical properties of discretized structural topology optimization problems. Either compliance is minimized with an upper bound on the volume of the structure, or volume is minimized with an upper bound on the compliance. The design variables are either continuous o....... The presented examples can be used as teaching material in graduate and undergraduate courses on structural topology optimization....
Linear Invariant Tensor Interpolation Applied to Cardiac Diffusion Tensor MRI
Gahm, Jin Kyu; Wisniewski, Nicholas; Kindlmann, Gordon; Kung, Geoffrey L.; Klug, William S.; Garfinkel, Alan; Ennis, Daniel B.
2015-01-01
Purpose Various methods exist for interpolating diffusion tensor fields, but none of them linearly interpolate tensor shape attributes. Linear interpolation is expected not to introduce spurious changes in tensor shape. Methods Herein we define a new linear invariant (LI) tensor interpolation method that linearly interpolates components of tensor shape (tensor invariants) and recapitulates the interpolated tensor from the linearly interpolated tensor invariants and the eigenvectors of a linearly interpolated tensor. The LI tensor interpolation method is compared to the Euclidean (EU), affine-invariant Riemannian (AI), log-Euclidean (LE) and geodesic-loxodrome (GL) interpolation methods using both a synthetic tensor field and three experimentally measured cardiac DT-MRI datasets. Results EU, AI, and LE introduce significant microstructural bias, which can be avoided through the use of GL or LI. Conclusion GL introduces the least microstructural bias, but LI tensor interpolation performs very similarly and at substantially reduced computational cost. PMID:23286085
Topology optimization for acoustic-structure interaction problems
DEFF Research Database (Denmark)
Yoon, Gil Ho; Jensen, Jakob Søndergaard; Sigmund, Ole
2006-01-01
We propose a gradient based topology optimization algorithm for acoustic-structure (vibro-acoustic) interaction problems without an explicit interfacing boundary representation. In acoustic-structure interaction problems, the pressure field and the displacement field are governed by the Helmholtz...... to subdomain interfaces evolving during the optimization process. In this paper, we propose to use a mixed finite element formulation with displacements and pressure as primary variables (u/p formulation) which eliminates the need for explicit boundary representation. In order to describe the Helmholtz......-dimensional acoustic-structure interaction problems are optimized to show the validity of the proposed method....
Low Multilinear Rank Approximation of Tensors and Application in Missing Traffic Data
Directory of Open Access Journals (Sweden)
Huachun Tan
2014-02-01
Full Text Available The problem of missing data in multiway arrays (i.e., tensors is common in many fields such as bibliographic data analysis, image processing, and computer vision. We consider the problems of approximating a tensor by another tensor with low multilinear rank in the presence of missing data and possibly reconstructing it (i.e., tensor completion. In this paper, we propose a weighted Tucker model which models only the known elements for capturing the latent structure of the data and reconstructing the missing elements. To treat the nonuniqueness of the proposed weighted Tucker model, a novel gradient descent algorithm based on a Grassmann manifold, which is termed Tucker weighted optimization (Tucker-Wopt, is proposed for guaranteeing the global convergence to a local minimum of the problem. Based on extensive experiments, Tucker-Wopt is shown to successfully reconstruct tensors with noise and up to 95% missing data. Furthermore, the experiments on traffic flow volume data demonstrate the usefulness of our algorithm on real-world application.
Efficient MATLAB computations with sparse and factored tensors.
Energy Technology Data Exchange (ETDEWEB)
Bader, Brett William; Kolda, Tamara Gibson (Sandia National Lab, Livermore, CA)
2006-12-01
In this paper, the term tensor refers simply to a multidimensional or N-way array, and we consider how specially structured tensors allow for efficient storage and computation. First, we study sparse tensors, which have the property that the vast majority of the elements are zero. We propose storing sparse tensors using coordinate format and describe the computational efficiency of this scheme for various mathematical operations, including those typical to tensor decomposition algorithms. Second, we study factored tensors, which have the property that they can be assembled from more basic components. We consider two specific types: a Tucker tensor can be expressed as the product of a core tensor (which itself may be dense, sparse, or factored) and a matrix along each mode, and a Kruskal tensor can be expressed as the sum of rank-1 tensors. We are interested in the case where the storage of the components is less than the storage of the full tensor, and we demonstrate that many elementary operations can be computed using only the components. All of the efficiencies described in this paper are implemented in the Tensor Toolbox for MATLAB.
Chang, Yu-Kai; Tsai, Jack Han-Chao; Wang, Chun-Chih; Chang, Erik Chihhung
2015-07-01
The aim of this study was to use diffusion tensor imaging (DTI) to characterize and compare microscopic differences in white matter integrity in the basal ganglia between elite professional athletes specializing in running and martial arts. Thirty-three young adults with sport-related skills as elite professional runners (n = 11) or elite professional martial artists (n = 11) were recruited and compared with non-athletic and healthy controls (n = 11). All participants underwent health- and skill-related physical fitness assessments. Fractional anisotropy (FA) and mean diffusivity (MD), the primary indices derived from DTI, were computed for five regions of interest in the bilateral basal ganglia, including the caudate nucleus, putamen, globus pallidus internal segment (GPi), globus pallidus external segment (GPe), and subthalamic nucleus. Results revealed that both athletic groups demonstrated better physical fitness indices compared with their control counterparts, with the running group exhibiting the highest cardiovascular fitness and the martial arts group exhibiting the highest muscular endurance and flexibility. With respect to the basal ganglia, both athletic groups showed significantly lower FA and marginally higher MD values in the GPi compared with the healthy control group. These findings suggest that professional sport or motor skill training is associated with changes in white matter integrity in specific regions of the basal ganglia, although these positive changes did not appear to depend on the type of sport-related motor skill being practiced.
Pastura, Giuseppe; Doering, Thomas; Gasparetto, Emerson Leandro; Mattos, Paulo; Araújo, Alexandra Prüfer
2016-06-01
Abnormalities in the white matter microstructure of the attentional system have been implicated in the aetiology of attention deficit hyperactivity disorder (ADHD). Diffusion tensor imaging (DTI) is a promising magnetic resonance imaging (MRI) technology that has increasingly been used in studies of white matter microstructure in the brain. The main objective of this work was to perform an exploratory analysis of white matter tracts in a sample of children with ADHD versus typically developing children (TDC). For this purpose, 13 drug-naive children with ADHD of both genders underwent MRI using DTI acquisition methodology and tract-based spatial statistics. The results were compared to those of a sample of 14 age- and gender-matched TDC. Lower fractional anisotropy was observed in the splenium of the corpus callosum, right superior longitudinal fasciculus, bilateral retrolenticular part of the internal capsule, bilateral inferior fronto-occipital fasciculus, left external capsule and posterior thalamic radiation (including right optic radiation). We conclude that white matter tracts in attentional and motor control systems exhibited signs of abnormal microstructure in this sample of drug-naive children with ADHD.
Madsen, Niels Kristian; Godtliebsen, Ian H.; Losilla, Sergio A.; Christiansen, Ove
2018-01-01
A new implementation of vibrational coupled-cluster (VCC) theory is presented, where all amplitude tensors are represented in the canonical polyadic (CP) format. The CP-VCC algorithm solves the non-linear VCC equations without ever constructing the amplitudes or error vectors in full dimension but still formally includes the full parameter space of the VCC[n] model in question resulting in the same vibrational energies as the conventional method. In a previous publication, we have described the non-linear-equation solver for CP-VCC calculations. In this work, we discuss the general algorithm for evaluating VCC error vectors in CP format including the rank-reduction methods used during the summation of the many terms in the VCC amplitude equations. Benchmark calculations for studying the computational scaling and memory usage of the CP-VCC algorithm are performed on a set of molecules including thiadiazole and an array of polycyclic aromatic hydrocarbons. The results show that the reduced scaling and memory requirements of the CP-VCC algorithm allows for performing high-order VCC calculations on systems with up to 66 vibrational modes (anthracene), which indeed are not possible using the conventional VCC method. This paves the way for obtaining highly accurate vibrational spectra and properties of larger molecules.
Tensor network method for reversible classical computation
Yang, Zhi-Cheng; Kourtis, Stefanos; Chamon, Claudio; Mucciolo, Eduardo R.; Ruckenstein, Andrei E.
2018-03-01
We develop a tensor network technique that can solve universal reversible classical computational problems, formulated as vertex models on a square lattice [Nat. Commun. 8, 15303 (2017), 10.1038/ncomms15303]. By encoding the truth table of each vertex constraint in a tensor, the total number of solutions compatible with partial inputs and outputs at the boundary can be represented as the full contraction of a tensor network. We introduce an iterative compression-decimation (ICD) scheme that performs this contraction efficiently. The ICD algorithm first propagates local constraints to longer ranges via repeated contraction-decomposition sweeps over all lattice bonds, thus achieving compression on a given length scale. It then decimates the lattice via coarse-graining tensor contractions. Repeated iterations of these two steps gradually collapse the tensor network and ultimately yield the exact tensor trace for large systems, without the need for manual control of tensor dimensions. Our protocol allows us to obtain the exact number of solutions for computations where a naive enumeration would take astronomically long times.
Invariant structures in gauge theories and confinement
International Nuclear Information System (INIS)
Prokhorov, L.V.; Shabanov, S.V.
1991-01-01
The problem of finding all gauge invariants is considered in connection with the problem of confinement. Polylocal gauge tensors are introduced and studied. It is shown (both in physical and pure geometrical approaches) that the path-ordered exponent is the only fundamental bilocal gauge tensor, which means that any irreducible polylocal gauge tensor is built of P-exponents and local tensors (matter fields). The simplest invariant structures in electrodynamics, chromodynamics and a theory with the gauge group SU(2) are considered separately. 23 refs.; 2 figs
Pathgroups, a dynamic data structure for genome reconstruction problems.
Zheng, Chunfang
2010-07-01
Ancestral gene order reconstruction problems, including the median problem, quartet construction, small phylogeny, guided genome halving and genome aliquoting, are NP hard. Available heuristics dedicated to each of these problems are computationally costly for even small instances. We present a data structure enabling rapid heuristic solution to all these ancestral genome reconstruction problems. A generic greedy algorithm with look-ahead based on an automatically generated priority system suffices for all the problems using this data structure. The efficiency of the algorithm is due to fast updating of the structure during run time and to the simplicity of the priority scheme. We illustrate with the first rapid algorithm for quartet construction and apply this to a set of yeast genomes to corroborate a recent gene sequence-based phylogeny. http://albuquerque.bioinformatics.uottawa.ca/pathgroup/Quartet.html chunfang313@gmail.com Supplementary data are available at Bioinformatics online.
Structural qualia: a solution to the hard problem of consciousness.
Loorits, Kristjan
2014-01-01
The hard problem of consciousness has been often claimed to be unsolvable by the methods of traditional empirical sciences. It has been argued that all the objects of empirical sciences can be fully analyzed in structural terms but that consciousness is (or has) something over and above its structure. However, modern neuroscience has introduced a theoretical framework in which also the apparently non-structural aspects of consciousness, namely the so called qualia or qualitative properties, can be analyzed in structural terms. That framework allows us to see qualia as something compositional with internal structures that fully determine their qualitative nature. Moreover, those internal structures can be identified which certain neural patterns. Thus consciousness as a whole can be seen as a complex neural pattern that misperceives some of its own highly complex structural properties as monadic and qualitative. Such neural pattern is analyzable in fully structural terms and thereby the hard problem is solved.
Structural qualia: a solution to the hard problem of consciousness
Directory of Open Access Journals (Sweden)
Kristjan eLoorits
2014-03-01
Full Text Available The hard problem of consciousness has been often claimed to be unsolvable by the methods of traditional empirical sciences. It has been argued that all the objects of empirical sciences can be fully analyzed in structural terms but that consciousness is (or has something over and above its structure. However, modern neuroscience has introduced a theoretical framework in which also the apparently non-structural aspects of consciousness, namely the so called qualia or qualitative properties, can be analyzed in structural terms. That framework allows us to see qualia as something compositional with internal structures that fully determine their qualitative nature. Moreover, those internal structures can be identified which certain neural patterns. Thus consciousness as a whole can be seen as a complex neural pattern that misperceives some of its own highly complex structural properties as monadic and qualitative. Such neural pattern is analyzable in fully structural terms and thereby the hard problem is solved.
Adaptive stochastic Galerkin FEM with hierarchical tensor representations
Eigel, Martin
2016-01-08
PDE with stochastic data usually lead to very high-dimensional algebraic problems which easily become unfeasible for numerical computations because of the dense coupling structure of the discretised stochastic operator. Recently, an adaptive stochastic Galerkin FEM based on a residual a posteriori error estimator was presented and the convergence of the adaptive algorithm was shown. While this approach leads to a drastic reduction of the complexity of the problem due to the iterative discovery of the sparsity of the solution, the problem size and structure is still rather limited. To allow for larger and more general problems, we exploit the tensor structure of the parametric problem by representing operator and solution iterates in the tensor train (TT) format. The (successive) compression carried out with these representations can be seen as a generalisation of some other model reduction techniques, e.g. the reduced basis method. We show that this approach facilitates the efficient computation of different error indicators related to the computational mesh, the active polynomial chaos index set, and the TT rank. In particular, the curse of dimension is avoided.
A Critical Systems Metamethodology for Problem Situation Structuring
Slavica P. Petrovic
2012-01-01
The increasing complexity and diversity of management problem situations in organizations, as well as the increasing variety of theories, methodologies, methods, techniques, and models that can be employed in problem situation structuring and solving, must be considered as relevant aspects of management process in contemporary circumstances. Creative holism in management problem situations in organizations is enabled by means of Critical Systems Thinking (CST) as well as Critical Systems Prac...
International Nuclear Information System (INIS)
Wit, B. de; Rocek, M.
1982-01-01
We construct a conformally invariant theory of the N = 1 supersymmetric tensor gauge multiplet and discuss the situation in N = 2. We show that our results give rise to the recently proposed variant of Poincare supergravity, and provide the complete tensor calculus for the theory. Finally, we argue that this theory cannot be quantized sensibly. (orig.)
Applicability Problem in Optimum Reinforced Concrete Structures Design
Directory of Open Access Journals (Sweden)
Ashara Assedeq
2016-01-01
Full Text Available Optimum reinforced concrete structures design is very complex problem, not only considering exactness of calculus but also because of questionable applicability of existing methods in practice. This paper presents the main theoretical mathematical and physical features of the problem formulation as well as the review and analysis of existing methods and solutions considering their exactness and applicability.
Time integration of tensor trains
Lubich, Christian; Oseledets, Ivan; Vandereycken, Bart
2014-01-01
A robust and efficient time integrator for dynamical tensor approximation in the tensor train or matrix product state format is presented. The method is based on splitting the projector onto the tangent space of the tensor manifold. The algorithm can be used for updating time-dependent tensors in the given data-sparse tensor train / matrix product state format and for computing an approximate solution to high-dimensional tensor differential equations within this data-sparse format. The formul...
Glyph-Based Comparative Visualization for Diffusion Tensor Fields.
Zhang, Changgong; Schultz, Thomas; Lawonn, Kai; Eisemann, Elmar; Vilanova, Anna
2016-01-01
Diffusion Tensor Imaging (DTI) is a magnetic resonance imaging modality that enables the in-vivo reconstruction and visualization of fibrous structures. To inspect the local and individual diffusion tensors, glyph-based visualizations are commonly used since they are able to effectively convey full aspects of the diffusion tensor. For several applications it is necessary to compare tensor fields, e.g., to study the effects of acquisition parameters, or to investigate the influence of pathologies on white matter structures. This comparison is commonly done by extracting scalar information out of the tensor fields and then comparing these scalar fields, which leads to a loss of information. If the glyph representation is kept, simple juxtaposition or superposition can be used. However, neither facilitates the identification and interpretation of the differences between the tensor fields. Inspired by the checkerboard style visualization and the superquadric tensor glyph, we design a new glyph to locally visualize differences between two diffusion tensors by combining juxtaposition and explicit encoding. Because tensor scale, anisotropy type, and orientation are related to anatomical information relevant for DTI applications, we focus on visualizing tensor differences in these three aspects. As demonstrated in a user study, our new glyph design allows users to efficiently and effectively identify the tensor differences. We also apply our new glyphs to investigate the differences between DTI datasets of the human brain in two different contexts using different b-values, and to compare datasets from a healthy and HIV-infected subject.
Tensoral for post-processing users and simulation authors
Dresselhaus, Eliot
1993-01-01
The CTR post-processing effort aims to make turbulence simulations and data more readily and usefully available to the research and industrial communities. The Tensoral language, which provides the foundation for this effort, is introduced here in the form of a user's guide. The Tensoral user's guide is presented in two main sections. Section one acts as a general introduction and guides database users who wish to post-process simulation databases. Section two gives a brief description of how database authors and other advanced users can make simulation codes and/or the databases they generate available to the user community via Tensoral database back ends. The two-part structure of this document conforms to the two-level design structure of the Tensoral language. Tensoral has been designed to be a general computer language for performing tensor calculus and statistics on numerical data. Tensoral's generality allows it to be used for stand-alone native coding of high-level post-processing tasks (as described in section one of this guide). At the same time, Tensoral's specialization to a minute task (namely, to numerical tensor calculus and statistics) allows it to be easily embedded into applications written partly in Tensoral and partly in other computer languages (here, C and Vectoral). Embedded Tensoral, aimed at advanced users for more general coding (e.g. of efficient simulations, for interfacing with pre-existing software, for visualization, etc.), is described in section two of this guide.
Correlators in tensor models from character calculus
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A. Mironov
2017-11-01
Full Text Available We explain how the calculations of [20], which provided the first evidence for non-trivial structures of Gaussian correlators in tensor models, are efficiently performed with the help of the (Hurwitz character calculus. This emphasizes a close similarity between technical methods in matrix and tensor models and supports a hope to understand the emerging structures in very similar terms. We claim that the 2m-fold Gaussian correlators of rank r tensors are given by r-linear combinations of dimensions with the Young diagrams of size m. The coefficients are made from the characters of the symmetric group Sm and their exact form depends on the choice of the correlator and on the symmetries of the model. As the simplest application of this new knowledge, we provide simple expressions for correlators in the Aristotelian tensor model as tri-linear combinations of dimensions.
Effects of tensor forces in nuclei
International Nuclear Information System (INIS)
Tanihata, Isao
2013-01-01
Recent studies of nuclei far from the stability line have revealed drastic changes in nuclear orbitals and reported the appearance of new magic numbers and the disappearance of magic numbers observed at the stability line. One of the important reasons for such changes is considered to be because of the effect of tensor forces on nuclear structure. Although the role of tensor forces in binding very light nuclei such as deuterons and 4 He has been known, direct experimental evidence for the effect on nuclear structure is scarce. In this paper, I review known effects of tensor forces in nuclei and then discuss the recently raised question of s–p wave mixing in a halo nucleus of 11 Li. Following these reviews, the development of a new experiment to see the high-momentum components due to the tensor forces is discussed and some of the new data are presented. (paper)
Muñoz-Ruiz, Miguel Ángel; Hartikainen, Päivi; Koikkalainen, Juha; Wolz, Robin; Julkunen, Valtteri; Niskanen, Eini; Herukka, Sanna-Kaisa; Kivipelto, Miia; Vanninen, Ritva; Rueckert, Daniel; Liu, Yawu; Lötjönen, Jyrki; Soininen, Hilkka
2012-01-01
MRI is an important clinical tool for diagnosing dementia-like diseases such as Frontemporal Dementia (FTD). However there is a need to develop more accurate and standardized MRI analysis methods. To compare FTD with Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI) with three automatic MRI analysis methods - Hippocampal Volumetry (HV), Tensor-based Morphometry (TBM) and Voxel-based Morphometry (VBM), in specific regions of interest in order to determine the highest classification accuracy. Thirty-seven patients with FTD, 46 patients with AD, 26 control subjects, 16 patients with progressive MCI (PMCI) and 48 patients with stable MCI (SMCI) were examined with HV, TBM for shape change, and VBM for gray matter density. We calculated the Correct Classification Rate (CCR), sensitivity (SS) and specificity (SP) between the study groups. We found unequivocal results differentiating controls from FTD with HV (hippocampus left side) (CCR = 0.83; SS = 0.84; SP = 0.80), with TBM (hippocampus and amygdala (CCR = 0.80/SS = 0.71/SP = 0.94), and with VBM (all the regions studied, especially in lateral ventricle frontal horn, central part and occipital horn) (CCR = 0.87/SS = 0.81/SP = 0.96). VBM achieved the highest accuracy in differentiating AD and FTD (CCR = 0.72/SS = 0.67/SP = 0.76), particularly in lateral ventricle (frontal horn, central part and occipital horn) (CCR = 0.73), whereas TBM in superior frontal gyrus also achieved a high accuracy (CCR = 0.71/SS = 0.68/SP = 0.73). TBM resulted in low accuracy (CCR = 0.62) in the differentiation of AD from FTD using all regions of interest, with similar results for HV (CCR = 0.55). Hippocampal atrophy is present not only in AD but also in FTD. Of the methods used, VBM achieved the highest accuracy in its ability to differentiate between FTD and AD.
Directory of Open Access Journals (Sweden)
Miguel Ángel Muñoz-Ruiz
Full Text Available BACKGROUND: MRI is an important clinical tool for diagnosing dementia-like diseases such as Frontemporal Dementia (FTD. However there is a need to develop more accurate and standardized MRI analysis methods. OBJECTIVE: To compare FTD with Alzheimer's Disease (AD and Mild Cognitive Impairment (MCI with three automatic MRI analysis methods - Hippocampal Volumetry (HV, Tensor-based Morphometry (TBM and Voxel-based Morphometry (VBM, in specific regions of interest in order to determine the highest classification accuracy. METHODS: Thirty-seven patients with FTD, 46 patients with AD, 26 control subjects, 16 patients with progressive MCI (PMCI and 48 patients with stable MCI (SMCI were examined with HV, TBM for shape change, and VBM for gray matter density. We calculated the Correct Classification Rate (CCR, sensitivity (SS and specificity (SP between the study groups. RESULTS: We found unequivocal results differentiating controls from FTD with HV (hippocampus left side (CCR = 0.83; SS = 0.84; SP = 0.80, with TBM (hippocampus and amygdala (CCR = 0.80/SS = 0.71/SP = 0.94, and with VBM (all the regions studied, especially in lateral ventricle frontal horn, central part and occipital horn (CCR = 0.87/SS = 0.81/SP = 0.96. VBM achieved the highest accuracy in differentiating AD and FTD (CCR = 0.72/SS = 0.67/SP = 0.76, particularly in lateral ventricle (frontal horn, central part and occipital horn (CCR = 0.73, whereas TBM in superior frontal gyrus also achieved a high accuracy (CCR = 0.71/SS = 0.68/SP = 0.73. TBM resulted in low accuracy (CCR = 0.62 in the differentiation of AD from FTD using all regions of interest, with similar results for HV (CCR = 0.55. CONCLUSION: Hippocampal atrophy is present not only in AD but also in FTD. Of the methods used, VBM achieved the highest accuracy in its ability to differentiate between FTD and AD.
Directory of Open Access Journals (Sweden)
Zoë A. Englander
2015-01-01
Full Text Available Cerebral Palsy (CP refers to a heterogeneous group of permanent but non-progressive movement disorders caused by injury to the developing fetal or infant brain (Bax et al., 2005. Because of its serious long-term consequences, effective interventions that can help improve motor function, independence, and quality of life are critically needed. Our ongoing longitudinal clinical trial to treat children with CP is specifically designed to meet this challenge. To maximize the potential for functional improvement, all children in this trial received autologous cord blood transfusions (with order randomized with a placebo administration over 2 years in conjunction with more standard physical and occupational therapies. As a part of this trial, magnetic resonance imaging (MRI is used to improve our understanding of how these interventions affect brain development, and to develop biomarkers of treatment efficacy. In this report, diffusion tensor imaging (DTI and subsequent brain connectome analyses were performed in a subset of children enrolled in the clinical trial (n = 17, who all exhibited positive but varying degrees of functional improvement over the first 2-year period of the study. Strong correlations between increases in white matter (WM connectivity and functional improvement were demonstrated; however no significant relationships between either of these factors with the age of the child at time of enrollment were identified. Thus, our data indicate that increases in brain connectivity reflect improved functional abilities in children with CP. In future work, this potential biomarker can be used to help differentiate the underlying mechanisms of functional improvement, as well as to identify treatments that can best facilitate functional improvement upon un-blinding of the timing of autologous cord blood transfusions at the completion of this study.
Englander, Zoë A; Sun, Jessica; Laura Case; Mikati, Mohamad A; Kurtzberg, Joanne; Song, Allen W
2015-01-01
Cerebral Palsy (CP) refers to a heterogeneous group of permanent but non-progressive movement disorders caused by injury to the developing fetal or infant brain (Bax et al., 2005). Because of its serious long-term consequences, effective interventions that can help improve motor function, independence, and quality of life are critically needed. Our ongoing longitudinal clinical trial to treat children with CP is specifically designed to meet this challenge. To maximize the potential for functional improvement, all children in this trial received autologous cord blood transfusions (with order randomized with a placebo administration over 2 years) in conjunction with more standard physical and occupational therapies. As a part of this trial, magnetic resonance imaging (MRI) is used to improve our understanding of how these interventions affect brain development, and to develop biomarkers of treatment efficacy. In this report, diffusion tensor imaging (DTI) and subsequent brain connectome analyses were performed in a subset of children enrolled in the clinical trial (n = 17), who all exhibited positive but varying degrees of functional improvement over the first 2-year period of the study. Strong correlations between increases in white matter (WM) connectivity and functional improvement were demonstrated; however no significant relationships between either of these factors with the age of the child at time of enrollment were identified. Thus, our data indicate that increases in brain connectivity reflect improved functional abilities in children with CP. In future work, this potential biomarker can be used to help differentiate the underlying mechanisms of functional improvement, as well as to identify treatments that can best facilitate functional improvement upon un-blinding of the timing of autologous cord blood transfusions at the completion of this study.
Existence problem of proton semi-bubble structure in the 2{sub 1}{sup +} state of {sup 34}Si
Energy Technology Data Exchange (ETDEWEB)
Wu, Feng [China Institute of Atomic Energy, Beijing (China); Sichuan University, Key Laboratory of Radiation Physics and Technology of Ministry of Education, School of Physics Science and Technology, Chengdu (China); Bai, C.L. [Sichuan University, Key Laboratory of Radiation Physics and Technology of Ministry of Education, School of Physics Science and Technology, Chengdu (China); Yao, J.M. [University of North Carolina, Department of Physics and Astronomy, Chapel Hill, NC (United States); Southwest University, School of Physical Science and Technology, Chongqing (China); Zhang, H.Q.; Zhang, X.Z. [China Institute of Atomic Energy, Beijing (China)
2017-09-15
The fully self-consistent Hartree-Fock (HF) plus random phase approximation (RPA) based on Skyrme-type interaction is used to study the existence problem of proton semi-bubble structure in the 2{sub 1}{sup +} state of {sup 34}Si. The experimental excitation energy and the transition strength of the 2{sub 1}{sup +} state in {sup 34}Si can be reproduced quite well. The tensor effect is also studied. It is shown that the tensor interaction has a notable impact on the excitation energy of the 2{sub 1}{sup +} state and a small effect on the B(E2) value. Besides, its effect on the density distributions in the ground and 2{sub 1}{sup +} state of {sup 34}Si is negligible. Our present results with T36 and T44 show that the 2{sub 1}{sup +} state of {sup 34}Si is mainly caused by proton transition from π1d{sub 5/2} orbit to π2s{sub 1/2} orbit, and the existence of a proton semi-bubble structure in this state is very unlikely. (orig.)
International Nuclear Information System (INIS)
Kobashigawa, Yoshihiro; Saio, Tomohide; Ushio, Masahiro; Sekiguchi, Mitsuhiro; Yokochi, Masashi; Ogura, Kenji; Inagaki, Fuyuhiko
2012-01-01
Pseudo contact shifts (PCSs) induced by paramagnetic lanthanide ions fixed in a protein frame provide long-range distance and angular information, and are valuable for the structure determination of protein–protein and protein–ligand complexes. We have been developing a lanthanide-binding peptide tag (hereafter LBT) anchored at two points via a peptide bond and a disulfide bond to the target proteins. However, the magnetic susceptibility tensor displays symmetry, which can cause multiple degenerated solutions in a structure calculation based solely on PCSs. Here we show a convenient method for resolving this degeneracy by changing the spacer length between the LBT and target protein. We applied this approach to PCS-based rigid body docking between the FKBP12-rapamycin complex and the mTOR FRB domain, and demonstrated that degeneracy could be resolved using the PCS restraints obtained from two-point anchored LBT with two different spacer lengths. The present strategy will markedly increase the usefulness of two-point anchored LBT for protein complex structure determination.
Energy Technology Data Exchange (ETDEWEB)
Kobashigawa, Yoshihiro; Saio, Tomohide [Hokkaido University, Department of Structural Biology, Faculty of Advanced Life Science (Japan); Ushio, Masahiro [Hokkaido University, Graduate School of Life Science (Japan); Sekiguchi, Mitsuhiro [Astellas Pharma Inc., Analysis and Pharmacokinetics Research Labs, Department of Drug Discovery (Japan); Yokochi, Masashi; Ogura, Kenji; Inagaki, Fuyuhiko, E-mail: finagaki@pharm.hokudai.ac.jp [Hokkaido University, Department of Structural Biology, Faculty of Advanced Life Science (Japan)
2012-05-15
Pseudo contact shifts (PCSs) induced by paramagnetic lanthanide ions fixed in a protein frame provide long-range distance and angular information, and are valuable for the structure determination of protein-protein and protein-ligand complexes. We have been developing a lanthanide-binding peptide tag (hereafter LBT) anchored at two points via a peptide bond and a disulfide bond to the target proteins. However, the magnetic susceptibility tensor displays symmetry, which can cause multiple degenerated solutions in a structure calculation based solely on PCSs. Here we show a convenient method for resolving this degeneracy by changing the spacer length between the LBT and target protein. We applied this approach to PCS-based rigid body docking between the FKBP12-rapamycin complex and the mTOR FRB domain, and demonstrated that degeneracy could be resolved using the PCS restraints obtained from two-point anchored LBT with two different spacer lengths. The present strategy will markedly increase the usefulness of two-point anchored LBT for protein complex structure determination.
Directory of Open Access Journals (Sweden)
Yayoi K. Hayakawa
2014-01-01
Full Text Available Depressive symptoms, even at a subclinical level, have been associated with structural brain abnormalities. However, previous studies have used regions of interest or small sample sizes, limiting the ability to generalize the results. In this study, we examined neuroanatomical structures of both gray matter and white matter associated with depressive symptoms across the whole brain in a large sample. A total of 810 community-dwelling adult participants underwent measurement of depressive symptoms with the Center for Epidemiologic Studies Depression Scale (CES-D. The participants were not demented and had no neurological or psychiatric history. To examine the gray and white matter volume, we used structural MRI scans and voxel-based morphometry (VBM; to examine the white matter integrity, we used diffusion tensor imaging with tract-based spatial statistics (TBSS. In female participants, VBM revealed a negative correlation between bilateral anterior cingulate gray matter volume and the CES-D score. TBSS showed a CES-D-related decrease in fractional anisotropy and increase in radial and mean diffusivity in several white matter regions, including the right anterior cingulum. In male participants, there was no significant correlation between gray or white matter volume or white matter integrity and the CES-D score. Our results indicate that the reduction in gray matter volume and differences in white matter integrity in specific brain regions, including the anterior cingulate, are associated with depressive symptoms in women.
Hayakawa, Yayoi K; Sasaki, Hiroki; Takao, Hidemasa; Hayashi, Naoto; Kunimatsu, Akira; Ohtomo, Kuni; Aoki, Shigeki
2014-01-01
Depressive symptoms, even at a subclinical level, have been associated with structural brain abnormalities. However, previous studies have used regions of interest or small sample sizes, limiting the ability to generalize the results. In this study, we examined neuroanatomical structures of both gray matter and white matter associated with depressive symptoms across the whole brain in a large sample. A total of 810 community-dwelling adult participants underwent measurement of depressive symptoms with the Center for Epidemiologic Studies Depression Scale (CES-D). The participants were not demented and had no neurological or psychiatric history. To examine the gray and white matter volume, we used structural MRI scans and voxel-based morphometry (VBM); to examine the white matter integrity, we used diffusion tensor imaging with tract-based spatial statistics (TBSS). In female participants, VBM revealed a negative correlation between bilateral anterior cingulate gray matter volume and the CES-D score. TBSS showed a CES-D-related decrease in fractional anisotropy and increase in radial and mean diffusivity in several white matter regions, including the right anterior cingulum. In male participants, there was no significant correlation between gray or white matter volume or white matter integrity and the CES-D score. Our results indicate that the reduction in gray matter volume and differences in white matter integrity in specific brain regions, including the anterior cingulate, are associated with depressive symptoms in women.
Kaufman, Jason A; Ahrens, Eric T; Laidlaw, David H; Zhang, Song; Allman, John M
2005-11-01
This report presents initial results of a multimodal analysis of tissue volume and microstructure in the brain of an aye-aye (Daubentonia madagascariensis). The left hemisphere of an aye-aye brain was scanned using T2-weighted structural magnetic resonance imaging (MRI) and diffusion-tensor imaging (DTI) prior to histological processing and staining for Nissl substance and myelinated fibers. The objectives of the experiment were to estimate the volume of gross brain regions for comparison with published data on other prosimians and to validate DTI data on fiber anisotropy with histological measurements of fiber spread. Measurements of brain structure volumes in the specimen are consistent with those reported in the literature: the aye-aye has a very large brain for its body size, a reduced volume of visual structures (V1 and LGN), and an increased volume of the olfactory lobe. This trade-off between visual and olfactory reliance is likely a reflection of the nocturnal extractive foraging behavior practiced by Daubentonia. Additionally, frontal cortex volume is large in the aye-aye, a feature that may also be related to its complex foraging behavior and sensorimotor demands. Analysis of DTI data in the anterior cingulum bundle demonstrates a strong correlation between fiber spread as measured from histological sections and fiber spread as measured from DTI. These results represent the first quantitative comparison of DTI data and fiber-stained histology in the brain. (c) 2005 Wiley-Liss, Inc.
Solving complex band structure problems with the FEAST eigenvalue algorithm
Laux, S. E.
2012-08-01
With straightforward extension, the FEAST eigenvalue algorithm [Polizzi, Phys. Rev. B 79, 115112 (2009)] is capable of solving the generalized eigenvalue problems representing traveling-wave problems—as exemplified by the complex band-structure problem—even though the matrices involved are complex, non-Hermitian, and singular, and hence outside the originally stated range of applicability of the algorithm. The obtained eigenvalues/eigenvectors, however, contain spurious solutions which must be detected and removed. The efficiency and parallel structure of the original algorithm are unaltered. The complex band structures of Si layers of varying thicknesses and InAs nanowires of varying radii are computed as test problems.
Muñoz-Ruiz, Miguel Ángel; Hartikainen, Päivi; Koikkalainen, Juha; Wolz, Robin; Julkunen, Valtteri; Niskanen, Eini; Herukka, Sanna-Kaisa; Kivipelto, Miia; Vanninen, Ritva; Rueckert, Daniel; Liu, Yawu; Lötjönen, Jyrki; Soininen, Hilkka
2012-01-01
Background MRI is an important clinical tool for diagnosing dementia-like diseases such as Frontemporal Dementia (FTD). However there is a need to develop more accurate and standardized MRI analysis methods. Objective To compare FTD with Alzheimer’s Disease (AD) and Mild Cognitive Impairment (MCI) with three automatic MRI analysis methods - Hippocampal Volumetry (HV), Tensor-based Morphometry (TBM) and Voxel-based Morphometry (VBM), in specific regions of interest in order to determine the highest classification accuracy. Methods Thirty-seven patients with FTD, 46 patients with AD, 26 control subjects, 16 patients with progressive MCI (PMCI) and 48 patients with stable MCI (SMCI) were examined with HV, TBM for shape change, and VBM for gray matter density. We calculated the Correct Classification Rate (CCR), sensitivity (SS) and specificity (SP) between the study groups. Results We found unequivocal results differentiating controls from FTD with HV (hippocampus left side) (CCR = 0.83; SS = 0.84; SP = 0.80), with TBM (hippocampus and amygdala (CCR = 0.80/SS = 0.71/SP = 0.94), and with VBM (all the regions studied, especially in lateral ventricle frontal horn, central part and occipital horn) (CCR = 0.87/SS = 0.81/SP = 0.96). VBM achieved the highest accuracy in differentiating AD and FTD (CCR = 0.72/SS = 0.67/SP = 0.76), particularly in lateral ventricle (frontal horn, central part and occipital horn) (CCR = 0.73), whereas TBM in superior frontal gyrus also achieved a high accuracy (CCR = 0.71/SS = 0.68/SP = 0.73). TBM resulted in low accuracy (CCR = 0.62) in the differentiation of AD from FTD using all regions of interest, with similar results for HV (CCR = 0.55). Conclusion Hippocampal atrophy is present not only in AD but also in FTD. Of the methods used, VBM achieved the highest accuracy in its ability to differentiate between FTD and AD. PMID:23285078
Augmented neural networks and problem structure-based heuristics for the bin-packing problem
Kasap, Nihat; Agarwal, Anurag
2012-08-01
In this article, we report on a research project where we applied augmented-neural-networks (AugNNs) approach for solving the classical bin-packing problem (BPP). AugNN is a metaheuristic that combines a priority rule heuristic with the iterative search approach of neural networks to generate good solutions fast. This is the first time this approach has been applied to the BPP. We also propose a decomposition approach for solving harder BPP, in which subproblems are solved using a combination of AugNN approach and heuristics that exploit the problem structure. We discuss the characteristics of problems on which such problem structure-based heuristics could be applied. We empirically show the effectiveness of the AugNN and the decomposition approach on many benchmark problems in the literature. For the 1210 benchmark problems tested, 917 problems were solved to optimality and the average gap between the obtained solution and the upper bound for all the problems was reduced to under 0.66% and computation time averaged below 33 s per problem. We also discuss the computational complexity of our approach.
Robust estimation of adaptive tensors of curvature by tensor voting.
Tong, Wai-Shun; Tang, Chi-Keung
2005-03-01
Although curvature estimation from a given mesh or regularly sampled point set is a well-studied problem, it is still challenging when the input consists of a cloud of unstructured points corrupted by misalignment error and outlier noise. Such input is ubiquitous in computer vision. In this paper, we propose a three-pass tensor voting algorithm to robustly estimate curvature tensors, from which accurate principal curvatures and directions can be calculated. Our quantitative estimation is an improvement over the previous two-pass algorithm, where only qualitative curvature estimation (sign of Gaussian curvature) is performed. To overcome misalignment errors, our improved method automatically corrects input point locations at subvoxel precision, which also rejects outliers that are uncorrectable. To adapt to different scales locally, we define the RadiusHit of a curvature tensor to quantify estimation accuracy and applicability. Our curvature estimation algorithm has been proven with detailed quantitative experiments, performing better in a variety of standard error metrics (percentage error in curvature magnitudes, absolute angle difference in curvature direction) in the presence of a large amount of misalignment noise.
Variational structure of inverse problems in wave propagation and vibration
Energy Technology Data Exchange (ETDEWEB)
Berryman, J.G.
1995-03-01
Practical algorithms for solving realistic inverse problems may often be viewed as problems in nonlinear programming with the data serving as constraints. Such problems are most easily analyzed when it is possible to segment the solution space into regions that are feasible (satisfying all the known constraints) and infeasible (violating some of the constraints). Then, if the feasible set is convex or at least compact, the solution to the problem will normally lie on the boundary of the feasible set. A nonlinear program may seek the solution by systematically exploring the boundary while satisfying progressively more constraints. Examples of inverse problems in wave propagation (traveltime tomography) and vibration (modal analysis) will be presented to illustrate how the variational structure of these problems may be used to create nonlinear programs using implicit variational constraints.
Lepore, N; Brun, C; Chou, Y Y; Chiang, M C; Dutton, R A; Hayashi, K M; Luders, E; Lopez, O L; Aizenstein, H J; Toga, A W; Becker, J T; Thompson, P M
2008-01-01
This paper investigates the performance of a new multivariate method for tensor-based morphometry (TBM). Statistics on Riemannian manifolds are developed that exploit the full information in deformation tensor fields. In TBM, multiple brain images are warped to a common neuroanatomical template via 3-D nonlinear registration; the resulting deformation fields are analyzed statistically to identify group differences in anatomy. Rather than study the Jacobian determinant (volume expansion factor) of these deformations, as is common, we retain the full deformation tensors and apply a manifold version of Hotelling's $T(2) test to them, in a Log-Euclidean domain. In 2-D and 3-D magnetic resonance imaging (MRI) data from 26 HIV/AIDS patients and 14 matched healthy subjects, we compared multivariate tensor analysis versus univariate tests of simpler tensor-derived indices: the Jacobian determinant, the trace, geodesic anisotropy, and eigenvalues of the deformation tensor, and the angle of rotation of its eigenvectors. We detected consistent, but more extensive patterns of structural abnormalities, with multivariate tests on the full tensor manifold. Their improved power was established by analyzing cumulative p-value plots using false discovery rate (FDR) methods, appropriately controlling for false positives. This increased detection sensitivity may empower drug trials and large-scale studies of disease that use tensor-based morphometry.
Structure problems in the analog computation; Problemes de structure dans le calcul analogique
Energy Technology Data Exchange (ETDEWEB)
Braffort, P L [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires
1957-07-01
The recent mathematical development showed the importance of elementary structures (algebraic, topological, etc.) in abeyance under the great domains of classical analysis. Such structures in analog computation are put in evidence and possible development of applied mathematics are discussed. It also studied the topological structures of the standard representation of analog schemes such as additional triangles, integrators, phase inverters and functions generators. The analog method gives only the function of the variable: time, as results of its computations. But the course of computation, for systems including reactive circuits, introduces order structures which are called 'chronological'. Finally, it showed that the approximation methods of ordinary numerical and digital computation present the same structure as these analog computation. The structure analysis permits fruitful comparisons between the several domains of applied mathematics and suggests new important domains of application for analog method. (M.P.)
Structure problems in the analog computation; Problemes de structure dans le calcul analogique
Energy Technology Data Exchange (ETDEWEB)
Braffort, P.L. [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires
1957-07-01
The recent mathematical development showed the importance of elementary structures (algebraic, topological, etc.) in abeyance under the great domains of classical analysis. Such structures in analog computation are put in evidence and possible development of applied mathematics are discussed. It also studied the topological structures of the standard representation of analog schemes such as additional triangles, integrators, phase inverters and functions generators. The analog method gives only the function of the variable: time, as results of its computations. But the course of computation, for systems including reactive circuits, introduces order structures which are called 'chronological'. Finally, it showed that the approximation methods of ordinary numerical and digital computation present the same structure as these analog computation. The structure analysis permits fruitful comparisons between the several domains of applied mathematics and suggests new important domains of application for analog method. (M.P.)
Tensor spherical harmonics and tensor multipoles. II. Minkowski space
International Nuclear Information System (INIS)
Daumens, M.; Minnaert, P.
1976-01-01
The bases of tensor spherical harmonics and of tensor multipoles discussed in the preceding paper are generalized in the Hilbert space of Minkowski tensor fields. The transformation properties of the tensor multipoles under Lorentz transformation lead to the notion of irreducible tensor multipoles. We show that the usual 4-vector multipoles are themselves irreducible, and we build the irreducible tensor multipoles of the second order. We also give their relations with the symmetric tensor multipoles defined by Zerilli for application to the gravitational radiation
Diffusion tensor optical coherence tomography
Marks, Daniel L.; Blackmon, Richard L.; Oldenburg, Amy L.
2018-01-01
In situ measurements of diffusive particle transport provide insight into tissue architecture, drug delivery, and cellular function. Analogous to diffusion-tensor magnetic resonance imaging (DT-MRI), where the anisotropic diffusion of water molecules is mapped on the millimeter scale to elucidate the fibrous structure of tissue, here we propose diffusion-tensor optical coherence tomography (DT-OCT) for measuring directional diffusivity and flow of optically scattering particles within tissue. Because DT-OCT is sensitive to the sub-resolution motion of Brownian particles as they are constrained by tissue macromolecules, it has the potential to quantify nanoporous anisotropic tissue structure at micrometer resolution as relevant to extracellular matrices, neurons, and capillaries. Here we derive the principles of DT-OCT, relating the detected optical signal from a minimum of six probe beams with the six unique diffusion tensor and three flow vector components. The optimal geometry of the probe beams is determined given a finite numerical aperture, and a high-speed hardware implementation is proposed. Finally, Monte Carlo simulations are employed to assess the ability of the proposed DT-OCT system to quantify anisotropic diffusion of nanoparticles in a collagen matrix, an extracellular constituent that is known to become highly aligned during tumor development.
Baust, Maximilian; Weinmann, Andreas; Wieczorek, Matthias; Lasser, Tobias; Storath, Martin; Navab, Nassir
2016-08-01
In this paper, we consider combined TV denoising and diffusion tensor fitting in DTI using the affine-invariant Riemannian metric on the space of diffusion tensors. Instead of first fitting the diffusion tensors, and then denoising them, we define a suitable TV type energy functional which incorporates the measured DWIs (using an inverse problem setup) and which measures the nearness of neighboring tensors in the manifold. To approach this functional, we propose generalized forward- backward splitting algorithms which combine an explicit and several implicit steps performed on a decomposition of the functional. We validate the performance of the derived algorithms on synthetic and real DTI data. In particular, we work on real 3D data. To our knowledge, the present paper describes the first approach to TV regularization in a combined manifold and inverse problem setup.
Klatt, Michael A; Schröder-Turk, Gerd E; Mecke, Klaus
2017-07-01
Structure-property relations, which relate the shape of the microstructure to physical properties such as transport or mechanical properties, need sensitive measures of structure. What are suitable fabric tensors to quantify the shape of anisotropic heterogeneous materials? The mean intercept length is among the most commonly used characteristics of anisotropy in porous media, e.g., of trabecular bone in medical physics. Yet, in this series of two papers we demonstrate that it has conceptual shortcomings that limit the validity of its results. We test the validity of general assumptions regarding the properties of the mean-intercept length tensor using analytical formulas for the mean-intercept lengths in anisotropic Boolean models (derived in part I of this series), augmented by numerical simulations. We discuss in detail the functional form of the mean intercept length as a function of the test line orientations. As the most prominent result, we find that, at least for the example of overlapping grains modeling porous media, the polar plot of the mean intercept length is in general not an ellipse and hence not represented by a second-rank tensor. This is in stark contrast to the common understanding that for a large collection of grains the mean intercept length figure averages to an ellipse. The standard mean intercept length tensor defined by a least-square fit of an ellipse is based on a model mismatch, which causes an intrinsic lack of accuracy. Our analysis reveals several shortcomings of the mean intercept length tensor analysis that pose conceptual problems and limitations on the information content of this commonly used analysis method. We suggest the Minkowski tensors from integral geometry as alternative sensitive measures of anisotropy. The Minkowski tensors allow for a robust, comprehensive, and systematic approach to quantify various aspects of structural anisotropy. We show the Minkowski tensors to be more sensitive, in the sense, that they can
Tensors and their applications
Islam, Nazrul
2006-01-01
About the Book: The book is written is in easy-to-read style with corresponding examples. The main aim of this book is to precisely explain the fundamentals of Tensors and their applications to Mechanics, Elasticity, Theory of Relativity, Electromagnetic, Riemannian Geometry and many other disciplines of science and engineering, in a lucid manner. The text has been explained section wise, every concept has been narrated in the form of definition, examples and questions related to the concept taught. The overall package of the book is highly useful and interesting for the people associated with the field. Contents: Preliminaries Tensor Algebra Metric Tensor and Riemannian Metric Christoffel`s Symbols and Covariant Differentiation Riemann-Christoffel Tensor The e-Systems and the Generalized Krönecker Deltas Geometry Analytical Mechanics Curvature of a Curve, Geodesic Parallelism of Vectors Ricci`s Coefficients of Rotation and Congruence Hyper Surfaces
Symmetric Tensor Decomposition
DEFF Research Database (Denmark)
Brachat, Jerome; Comon, Pierre; Mourrain, Bernard
2010-01-01
We present an algorithm for decomposing a symmetric tensor, of dimension n and order d, as a sum of rank-1 symmetric tensors, extending the algorithm of Sylvester devised in 1886 for binary forms. We recall the correspondence between the decomposition of a homogeneous polynomial in n variables...... of polynomial equations of small degree in non-generic cases. We propose a new algorithm for symmetric tensor decomposition, based on this characterization and on linear algebra computations with Hankel matrices. The impact of this contribution is two-fold. First it permits an efficient computation...... of the decomposition of any tensor of sub-generic rank, as opposed to widely used iterative algorithms with unproved global convergence (e.g. Alternate Least Squares or gradient descents). Second, it gives tools for understanding uniqueness conditions and for detecting the rank....
The assessment of structural dynamics problems in nuclear reactor safety
International Nuclear Information System (INIS)
Liebe, R.
1978-10-01
The paper discusses important physical features of structural dynamics problems in reactor safety. First a general characterization is given of the following problems: Containment deformation due to pool-dynamics during BWR-blowdown; behavior of the core internals due to PWR-blowdown loads; dynamic response of a nuclear power plant during an earthquake; fuel element deformation due to local pressure pulses in an LMFBR core. Several criterias are formulated to classify typical problems so that a better choise can be made both of appropriate mathematical/numerical as well as experimental techniques. The degree of physical coupling between structural dynamics and fluid dynamics is discussed in more detail since it requires particular attention when selecting problem-oriented methods of solution. Some examples are given to illustrate the application and to compare advantages and disadvantages of several numerical methods. Then description is given of experimental techniques in structural dynamics and typical problem areas are identified. Finally some results are presented concerning the fuel element deformation problem in LMFBRs and from the general considerations some important conclusions are summarized. (orig.) 891 RW 892 AP [de
International Nuclear Information System (INIS)
Scheunert, M.
1982-10-01
We develop a graded tensor calculus corresponding to arbitrary Abelian groups of degrees and arbitrary commutation factors. The standard basic constructions and definitions like tensor products, spaces of multilinear mappings, contractions, symmetrization, symmetric algebra, as well as the transpose, adjoint, and trace of a linear mapping, are generalized to the graded case and a multitude of canonical isomorphisms is presented. Moreover, the graded versions of the classical Lie algebras are introduced and some of their basic properties are described. (orig.)
Topology optimization of coated structures and material interface problems
DEFF Research Database (Denmark)
Clausen, Anders; Aage, Niels; Sigmund, Ole
2015-01-01
This paper presents a novel method for including coated structures and prescribed material interface properties into the minimum compliance topology optimization problem. Several elements of the method are applicable to a broader range of interface problems. The approach extends the standard SIMP......-step filtering/projection approach. The modeled coating thickness is derived analytically, and the coating is shown to be accurately controlled and applied in a highly uniform manner over the structure. An alternative interpretation of the model is to perform single-material design for additive manufacturing...
Lazzeretti, Paolo
2018-04-01
It is shown that nonsymmetric second-rank current density tensors, related to the current densities induced by magnetic fields and nuclear magnetic dipole moments, are fundamental properties of a molecule. Together with magnetizability, nuclear magnetic shielding, and nuclear spin-spin coupling, they completely characterize its response to magnetic perturbations. Gauge invariance, resolution into isotropic, deviatoric, and antisymmetric parts, and contributions of current density tensors to magnetic properties are discussed. The components of the second-rank tensor properties are rationalized via relationships explicitly connecting them to the direction of the induced current density vectors and to the components of the current density tensors. The contribution of the deviatoric part to the average value of magnetizability, nuclear shielding, and nuclear spin-spin coupling, uniquely determined by the antisymmetric part of current density tensors, vanishes identically. The physical meaning of isotropic and anisotropic invariants of current density tensors has been investigated, and the connection between anisotropy magnitude and electron delocalization has been discussed.
Topology optimization of fluid-structure-interaction problems in poroelasticity
DEFF Research Database (Denmark)
Andreasen, Casper Schousboe; Sigmund, Ole
2013-01-01
This paper presents a method for applying topology optimization to fluid-structure interaction problems in saturated poroelastic media. The method relies on a multiple-scale method applied to periodic media. The resulting model couples the Stokes flow in the pores of the structure with the deform...... by topology optimization in order to optimize the performance of a shock absorber and test the pressure loading capabilities and optimization of an internally pressurized lid. © 2013 Published by Elsevier B.V....
Tensor calculus for engineers and physicists
de Souza Sánchez Filho, Emil
2016-01-01
This textbook provides a rigorous approach to tensor manifolds in several aspects relevant for Engineers and Physicists working in industry or academia. With a thorough, comprehensive, and unified presentation, this book offers insights into several topics of tensor analysis, which covers all aspects of N dimensional spaces. The main purpose of this book is to give a self-contained yet simple, correct and comprehensive mathematical explanation of tensor calculus for undergraduate and graduate students and for professionals. In addition to many worked problems, this book features a selection of examples, solved step by step. Although no emphasis is placed on special and particular problems of Engineering or Physics, the text covers the fundamentals of these fields of science. The book makes a brief introduction into the basic concept of the tensorial formalism so as to allow the reader to make a quick and easy review of the essential topics that enable having the grounds for the subsequent themes, without need...
The Similar Structures and Control Problems of Complex Systems
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
In this paper, the naturally evolving complex systems, such as biotic and social ones, are considered. Focusing on their structures, a feature is noteworthy, i.e., the similarity in structures. The relations between the functions and behaviors of these systems and their similar structures will be studied. Owing to the management of social systems and the course of evolution of biotic systems may be regarded as control processes, the researches will be within the scope of control problems. Moreover, since it is difficult to model for biotic and social systems, it will start with the control problems of complex systems, possessing similar structures, in engineering.The obtained results show that for either linear or nonlinear systems and for a lot of control problemssimilar structures lead to a series of simplifications. In general, the original system may be decomposed into reduced amount of subsystems with lower dimensions and simpler structures. By virtue of such subsystems, the control problems of original system can be solved more simply.At last, it turns round to observe the biotic and social systems and some analyses are given.
A Closed-Form Solution to Tensor Voting: Theory and Applications
Wu, Tai-Pang; Yeung, Sai-Kit; Jia, Jiaya; Tang, Chi-Keung; Medioni, Gerard
2016-01-01
We prove a closed-form solution to tensor voting (CFTV): given a point set in any dimensions, our closed-form solution provides an exact, continuous and efficient algorithm for computing a structure-aware tensor that simultaneously achieves salient structure detection and outlier attenuation. Using CFTV, we prove the convergence of tensor voting on a Markov random field (MRF), thus termed as MRFTV, where the structure-aware tensor at each input site reaches a stationary state upon convergence...
Energy Technology Data Exchange (ETDEWEB)
Kikuchi, Kazufumi; Hiwatashi, Akio; Togao, Osamu; Yamashita, Koji; Somehara, Ryo; Kamei, Ryotaro; Baba, Shingo; Honda, Hiroshi [Kyushu University, Department of Clinical Radiology, Graduate School of Medical Sciences, Fukuoka (Japan); Yamaguchi, Hiroo; Kira, Jun-ichi [Kyushu University, Department of Neurology, Graduate School of Medical Sciences, Fukuoka (Japan)
2017-12-15
Patients with Parkinson's disease (PD) may exhibit symptoms of sympathetic dysfunction that can be measured using {sup 123}I-metaiodobenzylguanidine (MIBG) myocardial scintigraphy. We investigated the relationship between microstructural brain changes and {sup 123}I-MIBG uptake in patients with PD using voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) analyses. This retrospective study included 24 patients with PD who underwent 3 T magnetic resonance imaging and {sup 123}I-MIBG scintigraphy. They were divided into two groups: 12 MIBG-positive and 12 MIBG-negative cases (10 men and 14 women; age range: 60-81 years, corrected for gender and age). The heart/mediastinum count (H/M) ratio was calculated on anterior planar {sup 123}I-MIBG images obtained 4 h post-injection. VBM and DTI were performed to detect structural differences between these two groups. Patients with low H/M ratio had significantly reduced brain volume at the right inferior frontal gyrus (uncorrected p < 0.0001, K > 90). Patients with low H/M ratios also exhibited significantly lower fractional anisotropy than those with high H/M ratios (p < 0.05) at the left anterior thalamic radiation, the left inferior fronto-occipital fasciculus, the left superior longitudinal fasciculus, and the left uncinate fasciculus. VBM and DTI may reveal microstructural changes related to the degree of {sup 123}I-MIBG uptake in patients with PD. (orig.)
International Nuclear Information System (INIS)
Kikuchi, Kazufumi; Hiwatashi, Akio; Togao, Osamu; Yamashita, Koji; Somehara, Ryo; Kamei, Ryotaro; Baba, Shingo; Honda, Hiroshi; Yamaguchi, Hiroo; Kira, Jun-ichi
2017-01-01
Patients with Parkinson's disease (PD) may exhibit symptoms of sympathetic dysfunction that can be measured using 123 I-metaiodobenzylguanidine (MIBG) myocardial scintigraphy. We investigated the relationship between microstructural brain changes and 123 I-MIBG uptake in patients with PD using voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) analyses. This retrospective study included 24 patients with PD who underwent 3 T magnetic resonance imaging and 123 I-MIBG scintigraphy. They were divided into two groups: 12 MIBG-positive and 12 MIBG-negative cases (10 men and 14 women; age range: 60-81 years, corrected for gender and age). The heart/mediastinum count (H/M) ratio was calculated on anterior planar 123 I-MIBG images obtained 4 h post-injection. VBM and DTI were performed to detect structural differences between these two groups. Patients with low H/M ratio had significantly reduced brain volume at the right inferior frontal gyrus (uncorrected p < 0.0001, K > 90). Patients with low H/M ratios also exhibited significantly lower fractional anisotropy than those with high H/M ratios (p < 0.05) at the left anterior thalamic radiation, the left inferior fronto-occipital fasciculus, the left superior longitudinal fasciculus, and the left uncinate fasciculus. VBM and DTI may reveal microstructural changes related to the degree of 123 I-MIBG uptake in patients with PD. (orig.)
Martino, M; Magioncalda, P; Saiote, C; Conio, B; Escelsior, A; Rocchi, G; Piaggio, N; Marozzi, V; Huang, Z; Ferri, F; Amore, M; Inglese, M; Northoff, G
2016-10-01
The objective of the study was to investigate the relationship between structural connectivity (SC) and functional connectivity (FC) in the cingulum in bipolar disorder (BD) and its various phases. We combined resting-state functional magnetic resonance imaging and probabilistic tractographic diffusion tensor imaging to investigate FC and SC of the cingulum and its portions, the SC-FC relationship, and their correlations with clinical and neurocognitive measures on sustained attention in manic (n = 21), depressed (n = 20), and euthymic (n = 20) bipolar patients and healthy controls (HC) (n = 42). First, we found decreased FC between the anterior and posterior parts of the cingulum in manic patients when compared to depressed patients and HC. Second, we observed decreased SC of the cingulum bundle, particularly in its anterior part, in manic patients when compared to HC. Finally, alterations in the cingulum FC (but not SC) correlated with clinical severity scores while changes in the cingulum SC (but not FC) were related with neurocognitive deficits in sustained attention in BD. We demonstrate for the first time a reduction in FC and concomitantly in SC of the cingulum in mania, which correlated with psychopathological and neurocognitive parameters, respectively, in BD. This supports the central role of cingulum connectivity specifically in mania. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Properties of the tensor correlation in He isotopes
International Nuclear Information System (INIS)
Myo, Takayuki; Sugimoto, Satoru; Kato, Kiyoshi; Toki, Hiroshi; Ikeda, Kiyomi
2006-01-01
We investigate the roles of the tensor correlation on the structures of 4,5 He. For 4 He, we take the high angular momentum states as much as possible with the 2p2h excitations of the shell model type method to describe the tensor correlation. Three specific configurations are found to be favored for the tensor correlation. This correlation is also important to describe the scattering phenomena of the 4 He+nsystem including the higher partial waves consistently
Subtracting a best rank-1 approximation may increase tensor rank
Stegeman, Alwin; Comon, Pierre
2010-01-01
It has been shown that a best rank-R approximation of an order-k tensor may not exist when R >= 2 and k >= 3. This poses a serious problem to data analysts using tensor decompositions it has been observed numerically that, generally, this issue cannot be solved by consecutively computing and
Data fusion in metabolomics using coupled matrix and tensor factorizations
DEFF Research Database (Denmark)
Evrim, Acar Ataman; Bro, Rasmus; Smilde, Age Klaas
2015-01-01
of heterogeneous (i.e., in the form of higher order tensors and matrices) data sets with shared/unshared factors. In order to jointly analyze such heterogeneous data sets, we formulate data fusion as a coupled matrix and tensor factorization (CMTF) problem, which has already proved useful in many data mining...
Measuring Nematic Susceptibilities from the Elastoresistivity Tensor
Hristov, A. T.; Shapiro, M. C.; Hlobil, Patrick; Maharaj, Akash; Chu, Jiun-Haw; Fisher, Ian
The elastoresistivity tensor mijkl relates changes in resistivity to the strain on a material. As a fourth-rank tensor, it contains considerably more information about the material than the simpler (second-rank) resistivity tensor; in particular, certain elastoresistivity coefficients can be related to thermodynamic susceptibilities and serve as a direct probe of symmetry breaking at a phase transition. The aim of this talk is twofold. First, we enumerate how symmetry both constrains the structure of the elastoresistivity tensor into an easy-to-understand form and connects tensor elements to thermodynamic susceptibilities. In the process, we generalize previous studies of elastoresistivity to include the effects of magnetic field. Second, we describe an approach to measuring quantities in the elastoresistivity tensor with a novel transverse measurement, which is immune to relative strain offsets. These techniques are then applied to BaFe2As2 in a proof of principle measurement. This work is supported by the Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division, under Contract DE-AC02-76SF00515.
Poverty—A structural problem of developing countries
Wülker, Gabriele
1981-01-01
The contrast between industrialized and developing countries is often seen as one between two opposites: Rich countries—poor countries. But the poverty in the developing countries is by no means identical with the need for help as perceived in the industrialized societies. Poverty in the Third World is, as the following article shows, a structural problem.
Jitendra, Asha K.; Petersen-Brown, Shawna; Lein, Amy E.; Zaslofsky, Anne F.; Kunkel, Amy K.; Jung, Pyung-Gang; Egan, Andrea M.
2015-01-01
This study examined the quality of the research base related to strategy instruction priming the underlying mathematical problem structure for students with learning disabilities and those at risk for mathematics difficulties. We evaluated the quality of methodological rigor of 18 group research studies using the criteria proposed by Gersten et…
Tensor network decompositions in the presence of a global symmetry
International Nuclear Information System (INIS)
Singh, Sukhwinder; Pfeifer, Robert N. C.; Vidal, Guifre
2010-01-01
Tensor network decompositions offer an efficient description of certain many-body states of a lattice system and are the basis of a wealth of numerical simulation algorithms. We discuss how to incorporate a global symmetry, given by a compact, completely reducible group G, in tensor network decompositions and algorithms. This is achieved by considering tensors that are invariant under the action of the group G. Each symmetric tensor decomposes into two types of tensors: degeneracy tensors, containing all the degrees of freedom, and structural tensors, which only depend on the symmetry group. In numerical calculations, the use of symmetric tensors ensures the preservation of the symmetry, allows selection of a specific symmetry sector, and significantly reduces computational costs. On the other hand, the resulting tensor network can be interpreted as a superposition of exponentially many spin networks. Spin networks are used extensively in loop quantum gravity, where they represent states of quantum geometry. Our work highlights their importance in the context of tensor network algorithms as well, thus setting the stage for cross-fertilization between these two areas of research.
Reading the problem family: post-structuralism and the analysis of social problems.
Reekie, G
1994-01-01
Post-structuralist theory questions the rational pursuit of an underlying 'truth' that often characterizes social scientific inquiry, proposing instead the simultaneous existence of multiple and often contradictory truths. The problem family can, from this perspective, only be known through the different discourses that produce it. This paper suggests some of the political advantages of developing methods of reading 'problems' related to drugs and alcohol. Without this critical attention to language, we risk perpetuating the ways in which problems are talked about and thought about. Drawing on examples from debates surrounding teenage pregnancy and youth drinking, the paper argues that post-structuralism allows us to analyse the specific ways in which professional discourses write social problems, and hence to own them and to re-write them.
Tensor SOM and tensor GTM: Nonlinear tensor analysis by topographic mappings.
Iwasaki, Tohru; Furukawa, Tetsuo
2016-05-01
In this paper, we propose nonlinear tensor analysis methods: the tensor self-organizing map (TSOM) and the tensor generative topographic mapping (TGTM). TSOM is a straightforward extension of the self-organizing map from high-dimensional data to tensorial data, and TGTM is an extension of the generative topographic map, which provides a theoretical background for TSOM using a probabilistic generative model. These methods are useful tools for analyzing and visualizing tensorial data, especially multimodal relational data. For given n-mode relational data, TSOM and TGTM can simultaneously organize a set of n-topographic maps. Furthermore, they can be used to explore the tensorial data space by interactively visualizing the relationships between modes. We present the TSOM algorithm and a theoretical description from the viewpoint of TGTM. Various TSOM variations and visualization techniques are also described, along with some applications to real relational datasets. Additionally, we attempt to build a comprehensive description of the TSOM family by adapting various data structures. Copyright © 2016 Elsevier Ltd. All rights reserved.
Tensor spaces and exterior algebra
Yokonuma, Takeo
1992-01-01
This book explains, as clearly as possible, tensors and such related topics as tensor products of vector spaces, tensor algebras, and exterior algebras. You will appreciate Yokonuma's lucid and methodical treatment of the subject. This book is useful in undergraduate and graduate courses in multilinear algebra. Tensor Spaces and Exterior Algebra begins with basic notions associated with tensors. To facilitate understanding of the definitions, Yokonuma often presents two or more different ways of describing one object. Next, the properties and applications of tensors are developed, including the classical definition of tensors and the description of relative tensors. Also discussed are the algebraic foundations of tensor calculus and applications of exterior algebra to determinants and to geometry. This book closes with an examination of algebraic systems with bilinear multiplication. In particular, Yokonuma discusses the theory of replicas of Chevalley and several properties of Lie algebras deduced from them.
Cost-effective use of minicomputers to solve structural problems
Storaasli, O. O.; Foster, E. P.
1978-01-01
Minicomputers are receiving increased use throughout the aerospace industry. Until recently, their use focused primarily on process control and numerically controlled tooling applications, while their exposure to and the opportunity for structural calculations has been limited. With the increased availability of this computer hardware, the question arises as to the feasibility and practicality of carrying out comprehensive structural analysis on a minicomputer. This paper presents results on the potential for using minicomputers for structural analysis by (1) selecting a comprehensive, finite-element structural analysis system in use on large mainframe computers; (2) implementing the system on a minicomputer; and (3) comparing the performance of the minicomputers with that of a large mainframe computer for the solution to a wide range of finite element structural analysis problems.
I. M. Levashkina; S. S. Aleksanin; S. V. Serebryakova; T. G. Gribanova
2017-01-01
To evaluate correlation between brain structural damages and radiation exposure level for the Chernobyl nuclear power plant accident liquidators, routine and diffusion tensor magnetic resonance imaging methods are efficient to visualize and evaluate those damages; it is also important to compare magnetic resonance imaging data of liquidators with results, received for people of the same age and the same stage of cerebral vascular disease (the discirculatory encephalopathy of I and II stage), ...
Tensor analysis for physicists
Schouten, J A
1989-01-01
This brilliant study by a famed mathematical scholar and former professor of mathematics at the University of Amsterdam integrates a concise exposition of the mathematical basis of tensor analysis with admirably chosen physical examples of the theory. The first five chapters incisively set out the mathematical theory underlying the use of tensors. The tensor algebra in EN and RN is developed in Chapters I and II. Chapter II introduces a sub-group of the affine group, then deals with the identification of quantities in EN. The tensor analysis in XN is developed in Chapter IV. In chapters VI through IX, Professor Schouten presents applications of the theory that are both intrinsically interesting and good examples of the use and advantages of the calculus. Chapter VI, intimately connected with Chapter III, shows that the dimensions of physical quantities depend upon the choice of the underlying group, and that tensor calculus is the best instrument for dealing with the properties of anisotropic media. In Chapte...
Generalized dielectric permittivity tensor
International Nuclear Information System (INIS)
Borzdov, G.N.; Barkovskii, L.M.; Fedorov, F.I.
1986-01-01
The authors deal with the question of what is to be done with the formalism of the electrodynamics of dispersive media based on the introduction of dielectric-permittivity tensors for purely harmonic fields when Voigt waves and waves of more general form exist. An attempt is made to broaden and generalize the formalism to take into account dispersion of waves of the given type. In dispersive media, the polarization, magnetization, and conduction current-density vectors of point and time are determined by the values of the electromagnetic field vectors in the vicinity of this point (spatial dispersion) in the preceding instants of time (time dispersion). The dielectric-permittivity tensor and other tensors of electrodynamic parameters of the medium are introduced in terms of a set of evolution operators and not the set of harmonic function. It is noted that a magnetic-permeability tensor and an elastic-modulus tensor may be introduced for an acoustic field in dispersive anisotropic media with coupling equations of general form
Shi, Jie; Collignon, Olivier; Xu, Liang; Wang, Gang; Kang, Yue; Leporé, Franco; Lao, Yi; Joshi, Anand A; Leporé, Natasha; Wang, Yalin
2015-07-01
Blindness represents a unique model to study how visual experience may shape the development of brain organization. Exploring how the structure of the corpus callosum (CC) reorganizes ensuing visual deprivation is of particular interest due to its important functional implication in vision (e.g., via the splenium of the CC). Moreover, comparing early versus late visually deprived individuals has the potential to unravel the existence of a sensitive period for reshaping the CC structure. Here, we develop a novel framework to capture a complete set of shape differences in the CC between congenitally blind (CB), late blind (LB) and sighted control (SC) groups. The CCs were manually segmented from T1-weighted brain MRI and modeled by 3D tetrahedral meshes. We statistically compared the combination of local area and thickness at each point between subject groups. Differences in area are found using surface tensor-based morphometry; thickness is estimated by tracing the streamlines in the volumetric harmonic field. Group differences were assessed on this combined measure using Hotelling's T(2) test. Interestingly, we observed that the total callosal volume did not differ between the groups. However, our fine-grained analysis reveals significant differences mostly localized around the splenium areas between both blind groups and the sighted group (general effects of blindness) and, importantly, specific dissimilarities between the LB and CB groups, illustrating the existence of a sensitive period for reorganization. The new multivariate statistics also gave better effect sizes for detecting morphometric differences, relative to other statistics. They may boost statistical power for CC morphometric analyses.
Theoretical study of lithium clusters by electronic stress tensor
International Nuclear Information System (INIS)
Ichikawa, Kazuhide; Nozaki, Hiroo; Komazawa, Naoya; Tachibana, Akitomo
2012-01-01
We study the electronic structure of small lithium clusters Li_n (n = 2 ∼ 8) using the electronic stress tensor. We find that the three eigenvalues of the electronic stress tensor of the Li clusters are negative and degenerate, just like the stress tensor of liquid. This leads us to propose that we may characterize a metallic bond in terms of the electronic stress tensor. Our proposal is that in addition to the negativity of the three eigenvalues of the electronic stress tensor, their degeneracy characterizes some aspects of the metallic nature of chemical bonding. To quantify the degree of degeneracy, we use the differential eigenvalues of the electronic stress tensor. By comparing the Li clusters and hydrocarbon molecules, we show that the sign of the largest eigenvalue and the differential eigenvalues could be useful indices to evaluate the metallicity or covalency of a chemical bond.
QCD vacuum tensor susceptibility and properties of transversely polarized mesons
International Nuclear Information System (INIS)
Bakulev, A.P.; Mikhajlov, S.V.
1999-01-01
We re-estimate the tensor susceptibility of QCD vacuum, χ, and to this end, we re-estimate the leptonic decay constants for transversely polarized ρ-, ρ'- and b 1 -mesons. The origin of the susceptibility is analyzed using duality between ρ- and b 1 -channels in a 2-point correlator of tensor currents and disagree with [2] on both OPE expansion and the value of QCD vacuum tensor susceptibility. Using our value for the latter we determine new estimations of nucleon tensor charges related to the first moment of the transverse structure functions h 1 of a nucleon
TENSOR MODELING BASED FOR AIRBORNE LiDAR DATA CLASSIFICATION
Directory of Open Access Journals (Sweden)
N. Li
2016-06-01
Full Text Available Feature selection and description is a key factor in classification of Earth observation data. In this paper a classification method based on tensor decomposition is proposed. First, multiple features are extracted from raw LiDAR point cloud, and raster LiDAR images are derived by accumulating features or the “raw” data attributes. Then, the feature rasters of LiDAR data are stored as a tensor, and tensor decomposition is used to select component features. This tensor representation could keep the initial spatial structure and insure the consideration of the neighborhood. Based on a small number of component features a k nearest neighborhood classification is applied.
Mechanical structure and problem of thorium molten salt reactor
International Nuclear Information System (INIS)
Kamei, Takashi
2011-01-01
After Fukushima Daiichi accident, there became great interest in Thorium Molten Salt Reactor (MSR) for the safety as station blackout leading to auto drainage of molten salts with freeze valve. This article described mechanical structure of MSR and problems of materials and pipes. Material corrosion problem by molten salts would be solved using modified Hastelloy N with Ti and Nb added, which should be confirmed by operation of an experimental reactor. Trends in international activities of MSR were also referred including China declaring MSR development in January 2011 to solve thorium contamination issues at rare earth production and India rich in thorium resources. (T. Tanaka)
Tensors, differential forms, and variational principles
Lovelock, David
1989-01-01
Incisive, self-contained account of tensor analysis and the calculus of exterior differential forms, interaction between the concept of invariance and the calculus of variations. Emphasis is on analytical techniques, with large number of problems, from routine manipulative exercises to technically difficult assignments.
Killing tensors and conformal Killing tensors from conformal Killing vectors
International Nuclear Information System (INIS)
Rani, Raffaele; Edgar, S Brian; Barnes, Alan
2003-01-01
Koutras has proposed some methods to construct reducible proper conformal Killing tensors and Killing tensors (which are, in general, irreducible) when a pair of orthogonal conformal Killing vectors exist in a given space. We give the completely general result demonstrating that this severe restriction of orthogonality is unnecessary. In addition, we correct and extend some results concerning Killing tensors constructed from a single conformal Killing vector. A number of examples demonstrate that it is possible to construct a much larger class of reducible proper conformal Killing tensors and Killing tensors than permitted by the Koutras algorithms. In particular, by showing that all conformal Killing tensors are reducible in conformally flat spaces, we have a method of constructing all conformal Killing tensors, and hence all the Killing tensors (which will in general be irreducible) of conformally flat spaces using their conformal Killing vectors
Tensors, relativity, and cosmology
Dalarsson, Mirjana
2015-01-01
Tensors, Relativity, and Cosmology, Second Edition, combines relativity, astrophysics, and cosmology in a single volume, providing a simplified introduction to each subject that is followed by detailed mathematical derivations. The book includes a section on general relativity that gives the case for a curved space-time, presents the mathematical background (tensor calculus, Riemannian geometry), discusses the Einstein equation and its solutions (including black holes and Penrose processes), and considers the energy-momentum tensor for various solutions. In addition, a section on relativistic astrophysics discusses stellar contraction and collapse, neutron stars and their equations of state, black holes, and accretion onto collapsed objects, with a final section on cosmology discussing cosmological models, observational tests, and scenarios for the early universe. This fully revised and updated second edition includes new material on relativistic effects, such as the behavior of clocks and measuring rods in m...
The tensor network theory library
Al-Assam, S.; Clark, S. R.; Jaksch, D.
2017-09-01
In this technical paper we introduce the tensor network theory (TNT) library—an open-source software project aimed at providing a platform for rapidly developing robust, easy to use and highly optimised code for TNT calculations. The objectives of this paper are (i) to give an overview of the structure of TNT library, and (ii) to help scientists decide whether to use the TNT library in their research. We show how to employ the TNT routines by giving examples of ground-state and dynamical calculations of one-dimensional bosonic lattice system. We also discuss different options for gaining access to the software available at www.tensornetworktheory.org.
Beacher, F D; Minati, L; Baron-Cohen, S; Lombardo, M V; Lai, M-C; Gray, M A; Harrison, N A; Critchley, H D
2012-01-01
It has been proposed that autism spectrums condition may represent a form of extreme male brain (EMB), a notion supported by psychometric, behavioral, and endocrine evidence. Yet, limited data are presently available evaluating this hypothesis in terms of neuroanatomy. Here, we investigated sex-related anatomic features in adults with AS, a "pure" form of autism not involving major developmental delay. Males and females with AS and healthy controls (n = 28 and 30, respectively) were recruited. Structural MR imaging was performed to measure overall gray and white matter volume and to assess regional effects by means of VBM. DTI was used to investigate the integrity of the main white matter tracts. Significant interactions were found between sex and diagnosis in total white matter volume, regional gray matter volume in the right parietal operculum, and fractional anisotropy (FA) in the body of the CC, cingulum, and CR. Post hoc comparisons indicated that the typical sexual dimorphism found in controls, whereby males have larger FA and total white matter volume, was absent or attenuated in participants with AS. Our results point to a fundamental role of the factors that underlie sex-specific brain differentiation in the etiology of autism.
Standard problems to evaluate soil structure interaction computer codes
International Nuclear Information System (INIS)
Miller, C.A.; Costantino, C.J.; Philippacopoulos, A.J.
1979-01-01
The seismic response of nuclear power plant structures is often calculated using lumped parameter methods. A finite element model of the structure is coupled to the soil with a spring-dashpot system used to represent the interaction process. The parameters of the interaction model are based on analytic solutions to simple problems which are idealizations of the actual problems of interest. The objective of the work reported in this paper is to compare predicted responses using the standard lumped parameter models with experimental data. These comparisons are shown to be good for a fairly uniform soil system and for loadings which do not result in nonlinear interaction effects such as liftoff. 7 references, 7 figures
Jitendra, Asha K; Petersen-Brown, Shawna; Lein, Amy E; Zaslofsky, Anne F; Kunkel, Amy K; Jung, Pyung-Gang; Egan, Andrea M
2015-01-01
This study examined the quality of the research base related to strategy instruction priming the underlying mathematical problem structure for students with learning disabilities and those at risk for mathematics difficulties. We evaluated the quality of methodological rigor of 18 group research studies using the criteria proposed by Gersten et al. and 10 single case design (SCD) research studies using criteria suggested by Horner et al. and the What Works Clearinghouse. Results indicated that 14 group design studies met the criteria for high-quality or acceptable research, whereas SCD studies did not meet the standards for an evidence-based practice. Based on these findings, strategy instruction priming the mathematics problem structure is considered an evidence-based practice using only group design methodological criteria. Implications for future research and for practice are discussed. © Hammill Institute on Disabilities 2013.
Bond portfolio's duration and investment term-structure management problem
Liu, Daobai
2006-01-01
In the considered bond market, there are N zero-coupon bonds transacted continuously, which will mature at equally spaced dates. A duration of bond portfolios under stochastic interest rate model is introduced, which provides a measurement for the interest rate risk. Then we consider an optimal bond investment term-structure management problem using this duration as a performance index, and with the short-term interest rate process satisfying some stochastic differential ...
Structural problems in the construction of natural draught cooling towers
International Nuclear Information System (INIS)
Zerna, W.
1977-01-01
The paper deals with the structural requirements and development possibilities for large cooling towers, and in particular discusses parameter investigations into the reinforcement of cooling tower shells and problems of optimisation. In conclusion proposals are made as to how concrete cooling towers of very large dimensions reinforced with steel, as for example are required in dry cooling for large capacity plant, can be developed economically. (orig.) [de
Exploring extra dimensions through inflationary tensor modes
Im, Sang Hui; Nilles, Hans Peter; Trautner, Andreas
2018-03-01
Predictions of inflationary schemes can be influenced by the presence of extra dimensions. This could be of particular relevance for the spectrum of gravitational waves in models where the extra dimensions provide a brane-world solution to the hierarchy problem. Apart from models of large as well as exponentially warped extra dimensions, we analyze the size of tensor modes in the Linear Dilaton scheme recently revived in the discussion of the "clockwork mechanism". The results are model dependent, significantly enhanced tensor modes on one side and a suppression on the other. In some cases we are led to a scheme of "remote inflation", where the expansion is driven by energies at a hidden brane. In all cases where tensor modes are enhanced, the requirement of perturbativity of gravity leads to a stringent upper limit on the allowed Hubble rate during inflation.
Black holes with surrounding matter in scalar-tensor theories.
Cardoso, Vitor; Carucci, Isabella P; Pani, Paolo; Sotiriou, Thomas P
2013-09-13
We uncover two mechanisms that can render Kerr black holes unstable in scalar-tensor gravity, both associated with the presence of matter in the vicinity of the black hole and the fact that this introduces an effective mass for the scalar. Our results highlight the importance of understanding the structure of spacetime in realistic, astrophysical black holes in scalar-tensor theories.
The superspace-translation tensor and linearized N = 1 supergravities
International Nuclear Information System (INIS)
Bedding, S.P.; Lang, W.
1982-01-01
The recently proposed superspace-translation tensor is considered as the source of supergravities in the context of N = 1 supersymmetry. It is shown how the structure of this tensor leads to a complete evaluation of the linearized supervielbein in terms of unconstrained prepotentials with derived transformation laws. Connection with formulations using torsion constraints is made. (orig.)
Zou, Liwei; Su, Lianzi; Xu, Jiajia; Xiang, Li; Wang, Longsheng; Zhai, Zhimin; Zheng, Suisheng
2017-03-01
To assess structural brain changes in survivors of acute lymphoblastic leukemia (ALL) with chemotherapy treatment by combining voxel-based morphometry (VBM) and tract-based spatial statistics (TBSS). 28 ALL patients (mean age: 40.71±8.58years, years since diagnosis: 7-38) and 20 age-matched control subjects (mean age: 42.95±6.39years) selected in this study with 3D T1 and diffusion tensor imaging acquired on a 3.0T Siemens MRI scanner. The ALL group had a history of chemotherapy treatment and off-therapy at least for 3years was enrolled. VBM and TBSS analysis were performed to detect regional grey matter (GM) volume changes and white matter (WM) alternation measured by fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD). VBM revealed decreased GM volume in ALL patients in lingual gyrus, left occipital middle gyrus, left temporal middle gyrus, left postcentral gyrus, left parietal inferior gyrus, left precentral gyrus, left frontal superior gyrus and increased GM volume in right caudate and frontal lobe. WM integrity changes measured by TBSS which showed decreased FA and AD in several WM regions, and increased MD and RD in ALL patients with chemotherapy treatment. Our results indicate that ALL patients had smaller GM volume and WM integrity changes in several regions. The current study may shed further light on the potential brain effects of chemotherapy treatment in ALL patients. Copyright © 2017 Elsevier B.V. All rights reserved.
Bryant, P L; Harwell, C R; Mrse, A A; Emery, E F; Gan, Z; Caldwell, T; Reyes, A P; Kuhns, P; Hoyt, D W; Simeral, L S; Hall, R W; Butler, L G
2001-12-05
Experimental and ab initio molecular orbital techniques are developed for study of aluminum species with large quadrupole coupling constants to test structural models for methylaluminoxanes (MAO). The techniques are applied to nitrogen- and oxygen-containing complexes of aluminum and to solid MAO isolated from active commercial MAO preparations. (Aminato)- and (propanolato)aluminum clusters with 3-, 4-, and 6-coordinate aluminum sites are studied with three (27)Al NMR techniques optimized for large (27)Al quadrupole coupling constants: field-swept, frequency-stepped, and high-field MAS NMR. Four-membered (aminato)aluminum complexes with AlN(4) coordination yield slightly smaller C(q) values than similar AlN(2)C(2) sites: 12.2 vs 15.8 MHz. Planar 3-coordinate AlN(2)C sites have the largest C(q) values, 37 MHz. In all cases, molecular orbital calculations of the electric field gradient tensors yields C(q) and eta values that match with experiment, even for a large hexameric (aminato)aluminum cage. A D(3d) symmetry hexaaluminum oxane cluster, postulated as a model for MAO, yields a calculated C(q) of -23.7 MHz, eta = 0.7474, and predicts a spectrum that is too broad to match the field-swept NMR of methylaluminoxane, which shows at least three sites, all with C(q) values greater than 15 MHz but less than 21 MHz. Thus, the proposed hexaaluminum cluster, with its strained four-membered rings, is not a major component of MAO. However, calculations for dimers of the cage complex, either edge-bridged or face-bridged, show a much closer match to experiment. Also, MAO preparations differ, with a gel form of MAO having significantly larger (27)Al C(q) values than a nongel form, a conclusion reached on the basis of (27)Al NMR line widths in field-swept NMR spectra acquired from 13 to 24 T.
Fundamental problem in the relativistic approach to atomic structure theory
International Nuclear Information System (INIS)
Kagawa, Takashi
1987-01-01
It is known that the relativistic atomic structure theory contains a serious fundamental problem, so-called the Brown-Ravenhall (BR) problem or variational collapse. This problem arises from the fact that the energy spectrum of the relativistic Hamiltonian for many-electron systems is not bounded from below because the negative-energy solutions as well as the positive-energy ones are obtained from the relativistic equation. This report outlines two methods to avoid the BR problem in the relativistic calculation, that is, the projection operator method and the general variation method. The former method is described first. The use of a modified Hamiltonian containing a projection operator which projects the positive-energy solutions in the relativistic wave equation has been proposed to remove the BR difficulty. The problem in the use of the projection operator method is that the projection operator for the system cannot be determined uniquely. The final part of this report outlines the general variation method. This method can be applied to any system, such as relativistic ones whose Hamiltonian is not bounded from below. (Nogami, K.)
International Nuclear Information System (INIS)
Alsing, Paul M; McDonald, Jonathan R; Miller, Warner A
2011-01-01
The Ricci tensor (Ric) is fundamental to Einstein's geometric theory of gravitation. The three-dimensional Ric of a spacelike surface vanishes at the moment of time symmetry for vacuum spacetimes. The four-dimensional Ric is the Einstein tensor for such spacetimes. More recently, the Ric was used by Hamilton to define a nonlinear, diffusive Ricci flow (RF) that was fundamental to Perelman's proof of the Poincare conjecture. Analytic applications of RF can be found in many fields including general relativity and mathematics. Numerically it has been applied broadly to communication networks, medical physics, computer design and more. In this paper, we use Regge calculus (RC) to provide the first geometric discretization of the Ric. This result is fundamental for higher dimensional generalizations of discrete RF. We construct this tensor on both the simplicial lattice and its dual and prove their equivalence. We show that the Ric is an edge-based weighted average of deficit divided by an edge-based weighted average of dual area-an expression similar to the vertex-based weighted average of the scalar curvature reported recently. We use this Ric in a third and independent geometric derivation of the RC Einstein tensor in arbitrary dimensions.
Alsing, Paul M.; McDonald, Jonathan R.; Miller, Warner A.
2011-08-01
The Ricci tensor (Ric) is fundamental to Einstein's geometric theory of gravitation. The three-dimensional Ric of a spacelike surface vanishes at the moment of time symmetry for vacuum spacetimes. The four-dimensional Ric is the Einstein tensor for such spacetimes. More recently, the Ric was used by Hamilton to define a nonlinear, diffusive Ricci flow (RF) that was fundamental to Perelman's proof of the Poincarè conjecture. Analytic applications of RF can be found in many fields including general relativity and mathematics. Numerically it has been applied broadly to communication networks, medical physics, computer design and more. In this paper, we use Regge calculus (RC) to provide the first geometric discretization of the Ric. This result is fundamental for higher dimensional generalizations of discrete RF. We construct this tensor on both the simplicial lattice and its dual and prove their equivalence. We show that the Ric is an edge-based weighted average of deficit divided by an edge-based weighted average of dual area—an expression similar to the vertex-based weighted average of the scalar curvature reported recently. We use this Ric in a third and independent geometric derivation of the RC Einstein tensor in arbitrary dimensions.
DEFF Research Database (Denmark)
Ziegel, Johanna; Nyengaard, Jens Randel; Jensen, Eva B. Vedel
In the present paper, statistical procedures for estimating shape and orientation of arbitrary three-dimensional particles are developed. The focus of this work is on the case where the particles cannot be observed directly, but only via sections. Volume tensors are used for describing particle s...
Applications of Asymptotic Sampling on High Dimensional Structural Dynamic Problems
DEFF Research Database (Denmark)
Sichani, Mahdi Teimouri; Nielsen, Søren R.K.; Bucher, Christian
2011-01-01
The paper represents application of the asymptotic sampling on various structural models subjected to random excitations. A detailed study on the effect of different distributions of the so-called support points is performed. This study shows that the distribution of the support points has consid...... dimensional reliability problems in structural dynamics.......The paper represents application of the asymptotic sampling on various structural models subjected to random excitations. A detailed study on the effect of different distributions of the so-called support points is performed. This study shows that the distribution of the support points has...... is minimized. Next, the method is applied on different cases of linear and nonlinear systems with a large number of random variables representing the dynamic excitation. The results show that asymptotic sampling is capable of providing good approximations of low failure probability events for very high...
The evolution of tensor polarization
International Nuclear Information System (INIS)
Huang, H.; Lee, S.Y.; Ratner, L.
1993-01-01
By using the equation of motion for the vector polarization, the spin transfer matrix for spin tensor polarization, the spin transfer matrix for spin tensor polarization is derived. The evolution equation for the tensor polarization is studied in the presence of an isolate spin resonance and in the presence of a spin rotor, or snake
Tensor Calculus: Unlearning Vector Calculus
Lee, Wha-Suck; Engelbrecht, Johann; Moller, Rita
2018-01-01
Tensor calculus is critical in the study of the vector calculus of the surface of a body. Indeed, tensor calculus is a natural step-up for vector calculus. This paper presents some pitfalls of a traditional course in vector calculus in transitioning to tensor calculus. We show how a deeper emphasis on traditional topics such as the Jacobian can…
Use of Lanczos vectors in fluid/structure interaction problems
International Nuclear Information System (INIS)
Jeans, R.; Mathews, I.C.
1992-01-01
The goals of any numerical computational technique used for the solution of structural acoustics problems in the exterior infinite domain should be of accuracy with rapid convergence, robustness, and computational efficiency. A computer program has been developed to achieve each of these three goals. Accuracy and robustness in the numerical representation of the integral equations used to represent the infinite fluid was attained through the use of boundary element implementations of the surface Helmholtz integral equations. The computational efficiency was resolved through the use of Lanczos vectors to model the deformation characteristics of the structure. The authors have developed collocation and variational techniques to overcome the difficulties previously encountered in the numerical implementation of the hypersingular integral operator. The Cauchy singularity present in the integral formulation is made numerically amenable through the use of tangential derivatives in both the collocation and variational techniques. The variational approach has the advantage that the resulting added fluid mass term is symmetric and combines efficiently with a finite element approximation of the structural elastic response. Several different strategies making use of the Lanczos vectors have been investigated. The first involved the use of Lanczos vectors solely to characterize the structural response. This reduced form of the structural dynamical matrix was then substituted back into a Burton and Miller formulation of the acoustic problem. The second strategy investigated involved forming the complex Lanzcos vectors of the dynamical matrix formed from the addition of a symmetrical added fluid matrix to the structural mass matrix. The size of resultant matrix equation set solved at each frequency for this strategy is determined by the number of Lanczos vectors used. 19 refs., 10 figs., 2 tabs
Snap-Through Buckling Problem of Spherical Shell Structure
Directory of Open Access Journals (Sweden)
Sumirin Sumirin
2014-12-01
Full Text Available This paper presents results of a numerical study on the nonlinear behavior of shells undergoing snap-through instability. This research investigates the problem of snap-through buckling of spherical shells applying nonlinear finite element analysis utilizing ANSYS Program. The shell structure was modeled by axisymmetric thin shell of finite elements. Shells undergoing snap-through buckling meet with significant geometric change of their physical configuration, i.e. enduring large deflections during their deformation process. Therefore snap-through buckling of shells basically is a nonlinear problem. Nonlinear numerical operations need to be applied in their analysis. The problem was solved by a scheme of incremental iterative procedures applying Newton-Raphson method in combination with the known line search as well as the arc- length methods. The effects of thickness and depth variation of the shell is taken care of by considering their geometrical parameter l. The results of this study reveal that spherical shell structures subjected to pressure loading experience snap-through instability for values of l≥2.15. A form of ‘turn-back’ of the load-displacement curve took place at load levels prior to the achievement of the critical point. This phenomenon was observed for values of l=5.0 to l=7.0.
Ab initio nuclear structure - the large sparse matrix eigenvalue problem
Energy Technology Data Exchange (ETDEWEB)
Vary, James P; Maris, Pieter [Department of Physics, Iowa State University, Ames, IA, 50011 (United States); Ng, Esmond; Yang, Chao [Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States); Sosonkina, Masha, E-mail: jvary@iastate.ed [Scalable Computing Laboratory, Ames Laboratory, Iowa State University, Ames, IA, 50011 (United States)
2009-07-01
The structure and reactions of light nuclei represent fundamental and formidable challenges for microscopic theory based on realistic strong interaction potentials. Several ab initio methods have now emerged that provide nearly exact solutions for some nuclear properties. The ab initio no core shell model (NCSM) and the no core full configuration (NCFC) method, frame this quantum many-particle problem as a large sparse matrix eigenvalue problem where one evaluates the Hamiltonian matrix in a basis space consisting of many-fermion Slater determinants and then solves for a set of the lowest eigenvalues and their associated eigenvectors. The resulting eigenvectors are employed to evaluate a set of experimental quantities to test the underlying potential. For fundamental problems of interest, the matrix dimension often exceeds 10{sup 10} and the number of nonzero matrix elements may saturate available storage on present-day leadership class facilities. We survey recent results and advances in solving this large sparse matrix eigenvalue problem. We also outline the challenges that lie ahead for achieving further breakthroughs in fundamental nuclear theory using these ab initio approaches.
Ab initio nuclear structure - the large sparse matrix eigenvalue problem
International Nuclear Information System (INIS)
Vary, James P; Maris, Pieter; Ng, Esmond; Yang, Chao; Sosonkina, Masha
2009-01-01
The structure and reactions of light nuclei represent fundamental and formidable challenges for microscopic theory based on realistic strong interaction potentials. Several ab initio methods have now emerged that provide nearly exact solutions for some nuclear properties. The ab initio no core shell model (NCSM) and the no core full configuration (NCFC) method, frame this quantum many-particle problem as a large sparse matrix eigenvalue problem where one evaluates the Hamiltonian matrix in a basis space consisting of many-fermion Slater determinants and then solves for a set of the lowest eigenvalues and their associated eigenvectors. The resulting eigenvectors are employed to evaluate a set of experimental quantities to test the underlying potential. For fundamental problems of interest, the matrix dimension often exceeds 10 10 and the number of nonzero matrix elements may saturate available storage on present-day leadership class facilities. We survey recent results and advances in solving this large sparse matrix eigenvalue problem. We also outline the challenges that lie ahead for achieving further breakthroughs in fundamental nuclear theory using these ab initio approaches.
Generalized Artificial Life Structure for Time-dependent Problems
Institute of Scientific and Technical Information of China (English)
TSAU Minhe; KAO Weiwen; CHANG Albert
2009-01-01
In recent years, more attention has been paid on artificial life researches. Artificial life(AL) is a research on regulating gene parameters of digital organisms under complicated problematic environments through natural selections and evolutions to achieve the final emergence of intelligence. Most recent studies focused on solving certain real problems by artificial life methods, yet without much address on the AL life basic mechanism. The real problems are often very complicated, and the proposed methods sometimes seem too simple to handle those problems. This study proposed a new approach in AL research, named "generalized artificial life structure(GALS)", in which the traditional "gene bits" in genetic algorithms is first replaced by "gene parameters", which could appear anywhere in GALS. A modeling procedure is taken to normalize the input data, and AL "tissue" is innovated to make AL more complex. GALS is anticipated to contribute significantly to the fitness of AL evolution. The formation of"tissue" begins with some different AL basic cells, and then tissue is produced by the casual selections of one or several of these cells. As a result, the gene parameters, represented by "tissues", could become highly diversified. This diversification should have obvious effects on improving gene fitness. This study took the innovative method of GALS in a stock forecasting problem under a carefully designed manipulating platform. And the researching results verify that the GALS is successful in improving the gene evolution fitness.
Structure of Matter An Introductory Course with Problems and Solutions
Rigamonti, Attilio
2009-01-01
This is the second edition of this textbook, the original of which was published in 2007. Initial undergraduate studies in physics are usually in an organized format devoted to elementary aspects, which is then followed by advanced programmes in specialized fields. A difficult task is to provide a formative introduction in the early period, suitable as a base for courses more complex, thus bridging the wide gap between elementary physics and topics pertaining to research activities. This textbook remains an endeavour toward that goal, and is based on a mixture of simplified institutional theory and solved problems. In this way, the hope is to provide physical insight, basic knowledge and motivation, without impeding advanced learning. The choice has been to limit the focus to key concepts and to those aspects most typical of atoms, molecules and compounds, by looking at the basic, structural components, without paying detailed attention to the properties possessed by them. Problems are intertwined with formal...
Structure of Matter An Introductory Course with Problems and Solutions
Rigamonti, Attilio
2007-01-01
This is the second edition of this textbook, the original of which was published in 2007. Initial undergraduate studies in physics are usually in an organized format devoted to elementary aspects, which is then followed by advanced programmes in specialized fields. A difficult task is to provide a formative introduction in the early period, suitable as a base for courses more complex, thus bridging the wide gap between elementary physics and topics pertaining to research activities. This textbook remains an endeavour toward that goal, and is based on a mixture of simplified institutional theory and solved problems. In this way, the hope is to provide physical insight, basic knowledge and motivation, without impeding advanced learning. The choice has been to limit the focus to key concepts and to those aspects most typical of atoms, molecules and compounds, by looking at the basic, structural components, without paying detailed attention to the properties possessed by them. Problems are intertwined with formal...
On energy-momentum tensors of gravitational field
International Nuclear Information System (INIS)
Nikishov, A.I.
2001-01-01
The phenomenological approach to gravitation is discussed in which the 3-graviton interaction is reduced to the interaction of each graviton with the energy-momentum tensor of two others. If this is so, (and in general relativity this is not so), then the problem of choosing the correct energy-momentum tensor comes to finding the right 3-graviton vertex. Several energy-momentum tensors od gravitational field are considered and compared in the lowest approximation. Each of them together with the energy-momentum tensor of point-like particles satisfies the conservation laws when equations of motion of particles are the same as in general relativity. It is shown that in Newtonian approximation the considered tensors differ one from other in the way their energy density is distributed between energy density of interaction (nonzero only at locations of particles) and energy density of gravitational field. Stating from Lorentz invariance, the Lagrangians for spin-2, mass-0 field are considered [ru
Tensor Based Representation and Analysis of Diffusion-Weighted Magnetic Resonance Images
Barmpoutis, Angelos
2009-01-01
Cartesian tensor bases have been widely used to model spherical functions. In medical imaging, tensors of various orders can approximate the diffusivity function at each voxel of a diffusion-weighted MRI data set. This approximation produces tensor-valued datasets that contain information about the underlying local structure of the scanned tissue.…
Structural analysis for diagnosis with application to ship propulsion problem
DEFF Research Database (Denmark)
Izadi-Zamanabadi, Roozbeh; Blanke, Mogens
2002-01-01
Aiming at design of algorithms for fault diagnosis, structural analysis of systems offers concise yet easy overall analysis. Graph-based matching, which is the essential tech-nique to obtain redundant information for diagnosis, is reconsidered in this paper. Matching is reformulated as a problem...... of relating faults to known parameters and measurements of a system. Using explicit fault modelling, minimal overdetermined subsystems are shown to provide necessary redundancy relations from the matching. Details of the method are presented and a realistic example used to clearly describe individual steps....
Detection of antisymmetric tensor contribution to the magnetic screening of 13C nuclei
International Nuclear Information System (INIS)
Kuhn, W.
1983-01-01
In the present thesis for the first time a practicable way for the detection of antisymmetric contributions to the tensor of the magnetic screening of atomic nuclei is indicated. The detection is based on the relaxation efficiency of the antisymmetric screening. The measurements were performed on the 13 C nuclei of phthalic acid anhydride. Measured were the spin-lattice relaxation times of all 13 C nuclei of the molecule at field strengths between 4.69 T and 11.74 T, this corresponds to 1 H resonance frequencies in the range from 200 MHz to 500 MHz. From this the interaction-specific relaxation rates could be determined without problems. The space-group of the crystal and the molecule geometry were determined by X-ray structure analysis. For the accurate determination of the hydrogen position on a deuterated monocrystal by means of deuterium nuclear resonance measurements the electric field gradient tensors were measured and from the orientation of the main axes of these tensors the bonding angles calculated. On a monocrystal enriched in the C(7) respectively C(8) position with 13 C the symmetric part of the tensor of the magnetic screening of these two nuclei was measured. With these values and the relaxation rates of the 13 C nuclei by an iterative procedure from the equations for the theoretical relaxation rates of all 13 C nuclei of the molecule the main values of the rotation-diffusion tensor could be determined. On the base of the plane molecule geometry from this the tensor element sigmasub(xz)sup(A) could be explicety detected according to an amount of 11.7 ppm. (orig.) [de
Aspects of the Antisymmetric Tensor Field
Lahiri, Amitabha
1991-02-01
With the possible exception of gravitation, fundamental interactions are generally described by theories of point particles interacting via massless gauge fields. Since the advent of string theories the picture of physical interaction has changed to accommodate one in which extended objects interact with each other. The generalization of the gauge theories to extended objects leads to theories of antisymmetric tensor fields. At scales corresponding to present-day laboratory experiments one expects to see only point particles, their interactions modified by the presence of antisymmetric tensor fields in the theory. Therefore, in order to establish the validity of any theory with antisymmetric tensor fields one needs to look for manifestations of these fields at low energies. The principal problem of gauge theories is the failure to provide a suitable explanation for the generation of masses for the fields in the theory. While there is a known mechanism (spontaneous symmetry breaking) for generating masses for both the matter fields and the gauge fields, the lack of experimental evidence in support of an elementary scalar field suggests that one look for alternative ways of generating masses for the fields. The interaction of gauge fields with an antisymmetric tensor field seems to be an attractive way of doing so, especially since all indications point to the possibility that there will be no remnant degrees of freedom. On the other hand the interaction of such a field with black holes suggest an independent way of verifying the existence of such fields. In this dissertation the origins of the antisymmetric tensor field are discussed in terms of string theory. The interaction of black holes with such a field is discussed next. The last chapter discusses the effects of an antisymmetric tensor field on quantum electrodynamics when the fields are minimally coupled.
Gogny interactions with tensor terms
Energy Technology Data Exchange (ETDEWEB)
Anguiano, M.; Lallena, A.M.; Bernard, R.N. [Universidad de Granada, Departamento de Fisica Atomica, Molecular y Nuclear, Granada (Spain); Co' , G. [INFN, Lecce (Italy); De Donno, V. [Universita del Salento, Dipartimento di Matematica e Fisica ' ' E. De Giorgi' ' , Lecce (Italy); Grasso, M. [Universite Paris-Sud, Institut de Physique Nucleaire, IN2P3-CNRS, Orsay (France)
2016-07-15
We present a perturbative approach to include tensor terms in the Gogny interaction. We do not change the values of the usual parameterisations, with the only exception of the spin-orbit term, and we add tensor terms whose only free parameters are the strengths of the interactions. We identify observables sensitive to the presence of the tensor force in Hartree-Fock, Hartree-Fock-Bogoliubov and random phase approximation calculations. We show the need of including two tensor contributions, at least: a pure tensor term and a tensor-isospin term. We show results relevant for the inclusion of the tensor term for single-particle energies, charge-conserving magnetic excitations and Gamow-Teller excitations. (orig.)
The geomagnetic field gradient tensor
DEFF Research Database (Denmark)
Kotsiaros, Stavros; Olsen, Nils
2012-01-01
We develop the general mathematical basis for space magnetic gradiometry in spherical coordinates. The magnetic gradient tensor is a second rank tensor consisting of 3 × 3 = 9 spatial derivatives. Since the geomagnetic field vector B is always solenoidal (∇ · B = 0) there are only eight independent...... tensor elements. Furthermore, in current free regions the magnetic gradient tensor becomes symmetric, further reducing the number of independent elements to five. In that case B is a Laplacian potential field and the gradient tensor can be expressed in series of spherical harmonics. We present properties...... of the magnetic gradient tensor and provide explicit expressions of its elements in terms of spherical harmonics. Finally we discuss the benefit of using gradient measurements for exploring the Earth’s magnetic field from space, in particular the advantage of the various tensor elements for a better determination...
A tensor-based dictionary learning approach to tomographic image reconstruction
DEFF Research Database (Denmark)
Soltani, Sara; Kilmer, Misha E.; Hansen, Per Christian
2016-01-01
We consider tomographic reconstruction using priors in the form of a dictionary learned from training images. The reconstruction has two stages: first we construct a tensor dictionary prior from our training data, and then we pose the reconstruction problem in terms of recovering the expansion...... coefficients in that dictionary. Our approach differs from past approaches in that (a) we use a third-order tensor representation for our images and (b) we recast the reconstruction problem using the tensor formulation. The dictionary learning problem is presented as a non-negative tensor factorization problem...... with sparsity constraints. The reconstruction problem is formulated in a convex optimization framework by looking for a solution with a sparse representation in the tensor dictionary. Numerical results show that our tensor formulation leads to very sparse representations of both the training images...
Solving some problems of engineering seismology by structural method
International Nuclear Information System (INIS)
Ishtev, K.G.; Hadjikov, L.M.; Dineva, P.S.; Jordanov, P.P.
1983-01-01
The work suggests a method for solving the direct and inverse problems of the engineer seismology by means of the structural approach of the systems theory. This approach gives a possibility for a simultaneous accounting of the two basic types of damping of the seismic signals in the earth foundation-geometrical damping and a damping in consequence of a dissipative energy loss. By the structural scheme an automatic account is made of the geometric damping of the signals. The damping from a dissipative energy loss on the other hand is accounted for through a choice of the type of frequency characteristics or the transmission functions of the different layers. With a few examples the advantages of the model including the two types of attenuation of the seismic signal are illustrated. An integral coefficient of damping is calculated which analogously to the frequency functions represents a generalized characteristic of is the whole earth foundation. (orig./HP)
Structure of matter an introductory course with problems and solutions
Rigamonti, Attilio
2015-01-01
This textbook, now in its third edition, provides a formative introduction to the structure of matter that will serve as a sound basis for students proceeding to more complex courses, thus bridging the gap between elementary physics and topics pertaining to research activities. The focus is deliberately limited to key concepts of atoms, molecules and solids, examining the basic structural aspects without paying detailed attention to the related properties. For many topics the aim has been to start from the beginning and to guide the reader to the threshold of advanced research. This edition includes four new chapters dealing with relevant phases of solid matter (magnetic, electric and superconductive) and the related phase transitions. The book is based on a mixture of theory and solved problems that are integrated into the formal presentation of the arguments. Readers will find it invaluable in enabling them to acquire basic knowledge in the wide and wonderful field of condensed matter and to understand how ...
Data Structures: Sequence Problems, Range Queries, and Fault Tolerance
DEFF Research Database (Denmark)
Jørgensen, Allan Grønlund
performance and money in the design of todays high speed memory technologies. Hardware, power failures, and environmental conditions such as cosmic rays and alpha particles can all alter the memory in unpredictable ways. In applications where large memory capacities are needed at low cost, it makes sense......The focus of this dissertation is on algorithms, in particular data structures that give provably ecient solutions for sequence analysis problems, range queries, and fault tolerant computing. The work presented in this dissertation is divided into three parts. In Part I we consider algorithms...... to assume that the algorithms themselves are in charge for dealing with memory faults. We investigate searching, sorting and counting algorithms and data structures that provably returns sensible information in spite of memory corruptions....
Tensor estimation for double-pulsed diffusional kurtosis imaging.
Shaw, Calvin B; Hui, Edward S; Helpern, Joseph A; Jensen, Jens H
2017-07-01
Double-pulsed diffusional kurtosis imaging (DP-DKI) represents the double diffusion encoding (DDE) MRI signal in terms of six-dimensional (6D) diffusion and kurtosis tensors. Here a method for estimating these tensors from experimental data is described. A standard numerical algorithm for tensor estimation from conventional (i.e. single diffusion encoding) diffusional kurtosis imaging (DKI) data is generalized to DP-DKI. This algorithm is based on a weighted least squares (WLS) fit of the signal model to the data combined with constraints designed to minimize unphysical parameter estimates. The numerical algorithm then takes the form of a quadratic programming problem. The principal change required to adapt the conventional DKI fitting algorithm to DP-DKI is replacing the three-dimensional diffusion and kurtosis tensors with the 6D tensors needed for DP-DKI. In this way, the 6D diffusion and kurtosis tensors for DP-DKI can be conveniently estimated from DDE data by using constrained WLS, providing a practical means for condensing DDE measurements into well-defined mathematical constructs that may be useful for interpreting and applying DDE MRI. Data from healthy volunteers for brain are used to demonstrate the DP-DKI tensor estimation algorithm. In particular, representative parametric maps of selected tensor-derived rotational invariants are presented. Copyright © 2017 John Wiley & Sons, Ltd.
Directory of Open Access Journals (Sweden)
I. M. Levashkina
2017-01-01
Full Text Available To evaluate correlation between brain structural damages and radiation exposure level for the Chernobyl nuclear power plant accident liquidators, routine and diffusion tensor magnetic resonance imaging methods are efficient to visualize and evaluate those damages; it is also important to compare magnetic resonance imaging data of liquidators with results, received for people of the same age and the same stage of cerebral vascular disease (the discirculatory encephalopathy of I and II stage, but who did not participate in the Chernobyl accident liquidation and did not suffer from other liquidation factors and radiation catastrophe aftermaths. As a result, the Chernobyl accident liquidators group (49 subjects and group of control (50 subjects were examined with routine magnetic resonance imaging methods and standard protocols. In addition, the innovative method of diffusion tensor magnetic resonance imaging was applied to examine 11 cerebral tracts, bilaterally (22 tracts in both hemispheres for every subject of the research. It was for the first time when diffusion tensor magnetic resonance imaging was applied to conduct visual analysis of polymorphic brain changes for the Chernobyl accident liquidators and special research conducted to find correlation between fractional anisotropy coefficient and radiation exposure for these patients. The results of diffusion tensor magnetic resonance imaging indicated no statistically significant (p > 0,05 difference in the level of cerebral morphological changes and between average fraction anisotropy coefficient value in any cerebral tract for both sub-groups of liquidators with different level of irradiation: 28 subjects, who were exposed by low and very low radiation doses (0–100 micro-Sv, sub-group A and 21 subjects, who were exposed by mean radiation doses (100–1000 micro-Sv, sub-group B. However, comparing diffusion tensor magnetic resonance imaging results of control group and liquidators group
Dillon, Joshua V.; Langmore, Ian; Tran, Dustin; Brevdo, Eugene; Vasudevan, Srinivas; Moore, Dave; Patton, Brian; Alemi, Alex; Hoffman, Matt; Saurous, Rif A.
2017-01-01
The TensorFlow Distributions library implements a vision of probability theory adapted to the modern deep-learning paradigm of end-to-end differentiable computation. Building on two basic abstractions, it offers flexible building blocks for probabilistic computation. Distributions provide fast, numerically stable methods for generating samples and computing statistics, e.g., log density. Bijectors provide composable volume-tracking transformations with automatic caching. Together these enable...
The tensor distribution function.
Leow, A D; Zhu, S; Zhan, L; McMahon, K; de Zubicaray, G I; Meredith, M; Wright, M J; Toga, A W; Thompson, P M
2009-01-01
Diffusion weighted magnetic resonance imaging is a powerful tool that can be employed to study white matter microstructure by examining the 3D displacement profile of water molecules in brain tissue. By applying diffusion-sensitized gradients along a minimum of six directions, second-order tensors (represented by three-by-three positive definite matrices) can be computed to model dominant diffusion processes. However, conventional DTI is not sufficient to resolve more complicated white matter configurations, e.g., crossing fiber tracts. Recently, a number of high-angular resolution schemes with more than six gradient directions have been employed to address this issue. In this article, we introduce the tensor distribution function (TDF), a probability function defined on the space of symmetric positive definite matrices. Using the calculus of variations, we solve the TDF that optimally describes the observed data. Here, fiber crossing is modeled as an ensemble of Gaussian diffusion processes with weights specified by the TDF. Once this optimal TDF is determined, the orientation distribution function (ODF) can easily be computed by analytic integration of the resulting displacement probability function. Moreover, a tensor orientation distribution function (TOD) may also be derived from the TDF, allowing for the estimation of principal fiber directions and their corresponding eigenvalues.
Tensor Permutation Matrices in Finite Dimensions
Christian, Rakotonirina
2005-01-01
We have generalised the properties with the tensor product, of one 4x4 matrix which is a permutation matrix, and we call a tensor commutation matrix. Tensor commutation matrices can be constructed with or without calculus. A formula allows us to construct a tensor permutation matrix, which is a generalisation of tensor commutation matrix, has been established. The expression of an element of a tensor commutation matrix has been generalised in the case of any element of a tensor permutation ma...
Inductive Framework for Multi-Aspect Streaming Tensor Completion with Side Information
Nimishakavi, Madhav; Mishra, Bamdev; Gupta, Manish; Talukdar, Partha
2018-01-01
Low-rank tensor completion is a well-studied problem and has applications in various fields. However, in many real-world applications the data is dynamic, i.e., the tensor grows as new data arrives. Besides the tensor, in many real-world scenarios, side information is also available in the form of matrices which also grow. Existing work on dynamic tensor completion do not incorporate side information and most of the previous work is based on the assumption that the tensor grows only in one mo...
Visualizing Tensor Normal Distributions at Multiple Levels of Detail.
Abbasloo, Amin; Wiens, Vitalis; Hermann, Max; Schultz, Thomas
2016-01-01
Despite the widely recognized importance of symmetric second order tensor fields in medicine and engineering, the visualization of data uncertainty in tensor fields is still in its infancy. A recently proposed tensorial normal distribution, involving a fourth order covariance tensor, provides a mathematical description of how different aspects of the tensor field, such as trace, anisotropy, or orientation, vary and covary at each point. However, this wealth of information is far too rich for a human analyst to take in at a single glance, and no suitable visualization tools are available. We propose a novel approach that facilitates visual analysis of tensor covariance at multiple levels of detail. We start with a visual abstraction that uses slice views and direct volume rendering to indicate large-scale changes in the covariance structure, and locations with high overall variance. We then provide tools for interactive exploration, making it possible to drill down into different types of variability, such as in shape or orientation. Finally, we allow the analyst to focus on specific locations of the field, and provide tensor glyph animations and overlays that intuitively depict confidence intervals at those points. Our system is demonstrated by investigating the effects of measurement noise on diffusion tensor MRI, and by analyzing two ensembles of stress tensor fields from solid mechanics.
OPERATOR NORM INEQUALITIES BETWEEN TENSOR UNFOLDINGS ON THE PARTITION LATTICE.
Wang, Miaoyan; Duc, Khanh Dao; Fischer, Jonathan; Song, Yun S
2017-05-01
Interest in higher-order tensors has recently surged in data-intensive fields, with a wide range of applications including image processing, blind source separation, community detection, and feature extraction. A common paradigm in tensor-related algorithms advocates unfolding (or flattening) the tensor into a matrix and applying classical methods developed for matrices. Despite the popularity of such techniques, how the functional properties of a tensor changes upon unfolding is currently not well understood. In contrast to the body of existing work which has focused almost exclusively on matricizations, we here consider all possible unfoldings of an order- k tensor, which are in one-to-one correspondence with the set of partitions of {1, …, k }. We derive general inequalities between the l p -norms of arbitrary unfoldings defined on the partition lattice. In particular, we demonstrate how the spectral norm ( p = 2) of a tensor is bounded by that of its unfoldings, and obtain an improved upper bound on the ratio of the Frobenius norm to the spectral norm of an arbitrary tensor. For specially-structured tensors satisfying a generalized definition of orthogonal decomposability, we prove that the spectral norm remains invariant under specific subsets of unfolding operations.
One-loop tensor Feynman integral reduction with signed minors
DEFF Research Database (Denmark)
Fleischer, Jochem; Riemann, Tord; Yundin, Valery
2012-01-01
of the formalism is the immediate evaluation of complete contractions of the tensor integrals with external momenta. This leads to the problem of evaluating sums over products of signed minors with scalar products of chords. Chords are differences of external momenta. These sums may be evaluated analytically......We present an algebraic approach to one-loop tensor integral reduction. The integrals are presented in terms of scalar one- to four-point functions. The reduction is worked out explicitly until five-point functions of rank five. The numerical C++ package PJFry evaluates tensor coefficients in terms...
Dark energy in scalar-tensor theories
Energy Technology Data Exchange (ETDEWEB)
Moeller, J.
2007-12-15
We investigate several aspects of dynamical dark energy in the framework of scalar-tensor theories of gravity. We provide a classification of scalar-tensor coupling functions admitting cosmological scaling solutions. In particular, we recover that Brans-Dicke theory with inverse power-law potential allows for a sequence of background dominated scaling regime and scalar field dominated, accelerated expansion. Furthermore, we compare minimally and non-minimally coupled models, with respect to the small redshift evolution of the dark energy equation of state. We discuss the possibility to discriminate between different models by a reconstruction of the equation-of-state parameter from available observational data. The non-minimal coupling characterizing scalar-tensor models can - in specific cases - alleviate fine tuning problems, which appear if (minimally coupled) quintessence is required to mimic a cosmological constant. Finally, we perform a phase-space analysis of a family of biscalar-tensor models characterized by a specific type of {sigma}-model metric, including two examples from recent literature. In particular, we generalize an axion-dilaton model of Sonner and Townsend, incorporating a perfect fluid background consisting of (dark) matter and radiation. (orig.)
Dark energy in scalar-tensor theories
International Nuclear Information System (INIS)
Moeller, J.
2007-12-01
We investigate several aspects of dynamical dark energy in the framework of scalar-tensor theories of gravity. We provide a classification of scalar-tensor coupling functions admitting cosmological scaling solutions. In particular, we recover that Brans-Dicke theory with inverse power-law potential allows for a sequence of background dominated scaling regime and scalar field dominated, accelerated expansion. Furthermore, we compare minimally and non-minimally coupled models, with respect to the small redshift evolution of the dark energy equation of state. We discuss the possibility to discriminate between different models by a reconstruction of the equation-of-state parameter from available observational data. The non-minimal coupling characterizing scalar-tensor models can - in specific cases - alleviate fine tuning problems, which appear if (minimally coupled) quintessence is required to mimic a cosmological constant. Finally, we perform a phase-space analysis of a family of biscalar-tensor models characterized by a specific type of σ-model metric, including two examples from recent literature. In particular, we generalize an axion-dilaton model of Sonner and Townsend, incorporating a perfect fluid background consisting of (dark) matter and radiation. (orig.)
Liu, Chunlei; Murphy, Nicole E.; Li, Wei
2012-01-01
Diffusion MRI has become an invaluable tool for studying white matter microstructure and brain connectivity. The emergence of quantitative susceptibility mapping and susceptibility tensor imaging (STI) has provided another unique tool for assessing the structure of white matter. In the highly ordered white matter structure, diffusion MRI measures hindered water mobility induced by various tissue and cell membranes, while susceptibility sensitizes to the molecular composition and axonal arrangement. Integrating these two methods may produce new insights into the complex physiology of white matter. In this study, we investigated the relationship between diffusion and magnetic susceptibility in the white matter. Experiments were conducted on phantoms and human brains in vivo. Diffusion properties were quantified with the diffusion tensor model and also with the higher order tensor model based on the cumulant expansion. Frequency shift and susceptibility tensor were measured with quantitative susceptibility mapping and susceptibility tensor imaging. These diffusion and susceptibility quantities were compared and correlated in regions of single fiber bundles and regions of multiple fiber orientations. Relationships were established with similarities and differences identified. It is believed that diffusion MRI and susceptibility MRI provide complementary information of the microstructure of white matter. Together, they allow a more complete assessment of healthy and diseased brains. PMID:23507987
Energy-momentum-tensor in quantumelectrodynamics
Energy Technology Data Exchange (ETDEWEB)
Schott, T
1974-01-01
This work deals with the operator properties of the energy-momentum-tensor (ET) in the framework of quantum electrodynamics. The principles of construction of the ET are discussed for quantized fields in the Schwinger variation principle. Dealing with the conserved quantities for quantized fields operator problems are coming up in the Coulomb gauge because Dirac- and Maxwellfield do not commute completely. Further on contemporary commutators of the ET components are investigated mutually. Finally non-canonical methods are developed.
Problem statement for optimal design of steel structures
Directory of Open Access Journals (Sweden)
Ginzburg Aleksandr Vital'evich
2014-07-01
Full Text Available The presented article considers the following complex of tasks. The main stages of the life cycle of a building construction with the indication of process entrance and process exit are described. Requirements imposed on steel constructions are considered. The optimum range of application for steel designs is specified, as well as merits and demerits of a design material. The nomenclature of metal designs is listed - the block diagram is constructed. Possible optimality criteria of steel designs, offered by various authors for various types of constructions are considered. It is established that most often the criterion of a minimum of design mass is accepted as criterion of optimality; more rarely - a minimum of the given expenses, a minimum of a design cost in business. In the present article special attention is paid to a type of objective function of optimization problem. It is also established that depending on the accepted optimality criterion, the use of different types of functions is possible. This complexity of objective function depends on completeness of optimality criterion application. In the work the authors consider the following objective functions: the mass of the main element of a design; objective function by criterion of factory cost; objective function by criterion of cost in business. According to these examples it can be seen that objective functions by the criteria of labor expenses for production of designs are generally non-linear, which complicates solving the optimization problem. Another important factor influencing the problem of optimal design solution for steel designs, which is analyzed, is account for operating restrictions. In the article 8 groups of restrictions are analyzed. Attempts to completely account for the parameters of objective function optimized by particular optimality criteria, taking into account all the operating restrictions, considerably complicates the problem of designing. For solving this
Structuring students’ analogical reasoning in solving algebra problem
Lailiyah, S.; Nusantara, T.; Sa'dijah, C.; Irawan, E. B.; Kusaeri; Asyhar, A. H.
2018-01-01
The average achievement of Indonesian students’ mathematics skills according to Benchmark International Trends in Mathematics and Science Study (TIMSS) is ranked at the 38th out of 42 countries and according to the survey result in Program for International Student Assessment (PISA) is ranked at the 64th out of 65 countries. The low mathematics skill of Indonesian student has become an important reason to research more deeply about reasoning and algebra in mathematics. Analogical reasoning is a very important component in mathematics because it is the key to creativity and it can make the learning process in the classroom become effective. The major part of the analogical reasoning is about structuring including the processes of inferencing and decision-making happens. Those processes involve base domain and target domain. Methodologically, the subjects of this research were 42 students from class XII. The sources of data were derived from the results of thinks aloud, the transcribed interviews, and the videos taken while the subject working on the instruments and interviews. The collected data were analyzed using qualitative techniques. The result of this study described the structuring characteristics of students’ analogical reasoning in solving algebra problems from all the research subjects.
On deformed tensor potential for inelastic deuteron scattering
International Nuclear Information System (INIS)
Raynal, Jacques.
1980-08-01
Tensor analysing powers for inelastic deuteron scattering have been measured around 12 to 15 MeV. There is no problem to use such a tensor potential for the excited states in coupled channel calculations. However, for transition potentials, form factors are very different. A fit has been done with the first order vibrational model for 64 Ni(d,d') 64 Ni*, 2 + at 1,344 MeV
Tensor norms and operator ideals
Defant, A; Floret, K
1992-01-01
The three chapters of this book are entitled Basic Concepts, Tensor Norms, and Special Topics. The first may serve as part of an introductory course in Functional Analysis since it shows the powerful use of the projective and injective tensor norms, as well as the basics of the theory of operator ideals. The second chapter is the main part of the book: it presents the theory of tensor norms as designed by Grothendieck in the Resumé and deals with the relation between tensor norms and operator ideals. The last chapter deals with special questions. Each section is accompanied by a series of exer
The future demand for and structural problems of Japanese Radiotherapy
International Nuclear Information System (INIS)
Imai, Atsushi; Inoue, Toshihiko; Teshima, Teruki; Ohno, Yuko; Yamashita, Takashi; Mitsuhashi, Norio; Hiraoka, Masahiro; Sumi, Minako
2001-01-01
Recently, as the number of elderly people in Japan is growing, so is the number of new cancer cases. The number of patients treated with radiotherapy is therefore also on the increase, so that it is important to estimate the future demand for radiotherapy and to make preparations for it. All the surveys were conducted for 106 facilities selected randomly out of 556 radiotherapy facilities in Japan. To obtain trends in the number of new cancer patients treated with radiotherapy in Japan, we conducted a survey with a self-administered mail questionnaire designed to obtain the number of new patients treated with radiotherapy for each year of the past decade (1990-99). The future number of new patients treated with radiotherapy was estimated from the data thus obtained. To investigate structural problems of Japanese radiotherapy, surveys about the number of treatment machines and full-time equivalent (FTE) radiation oncologists were conducted according to data from the Japanese Society for Therapeutic Radiology and Oncology (JASTRO) structure survey and the Patterns of Care Study (PCS). We also compared the structure of Japanese radiotherapy with that in the USA. The number of patients treated with radiotherapy has increased for every institutional stratum, with an overall increase of 1.4-fold over the past 10 years in Japan. It is estimated that the number of cancer patients treated with radiotherapy will reach 190000 in 2015. In Japanese non-academic institutions, less than one FTE radiation oncologist has been managing many of these patients. In both equipment and manpower, academic institutions exceed non-academic institutions. The future demand for Japanese radiotherapy will grow substantially, so that it is of vital importance to prepare for it. Specifically, the number of FTE radiation oncologists must be increased. (author)
Endoscopic Anatomy of the Tensor Fold and Anterior Attic.
Li, Bin; Doan, Phi; Gruhl, Robert R; Rubini, Alessia; Marchioni, Daniele; Fina, Manuela
2018-02-01
Objectives The objectives of the study were to (1) study the anatomical variations of the tensor fold and its anatomic relation with transverse crest, supratubal recess, and anterior epitympanic space and (2) explore the most appropriate endoscopic surgical approach to each type of the tensor fold variants. Study Design Cadaver dissection study. Setting Temporal bone dissection laboratory. Subjects and Methods Twenty-eight human temporal bones (26 preserved and 2 fresh) were dissected through an endoscopic transcanal approach between September 2016 and June 2017. The anatomical variations of the tensor fold, transverse crest, supratubal recess, and anterior epitympanic space were studied before and after removing ossicles. Results Three different tensor fold orientations were observed: vertical (type A, 11/28, 39.3%) with attachment to the transverse crest, oblique (type B, 13/28, 46.4%) with attachment to the anterior tegmen tympani, and horizontal (type C, 4/28, 14.3%) with attachment to the tensor tympani canal. The tensor fold was a complete membrane in 20 of 28 (71.4%) specimens, preventing direct ventilation between the supratubal recess and anterior epitympanic space. We identified 3 surgical endoscopic approaches, which allowed visualization of the tensor fold without removing the ossicles. Conclusions The orientation of the tensor fold is the determining structure that dictates the conformation and limits of the epitympanic space. We propose a classification of the tensor fold based on 3 anatomical variants. We also describe 3 different minimally invasive endoscopic approaches to identify the orientation of the tensor fold while maintaining ossicular chain continuity.
Research Projects in Physics: A Mechanism for Teaching Ill-Structured Problem Solving
Milbourne, Jeff; Bennett, Jonathan
2017-10-01
Physics education research has a tradition of studying problem solving, exploring themes such as physical intuition and differences between expert and novice problem solvers. However, most of this work has focused on traditional, or well-structured, problems, similar to what might appear in a textbook. Less work has been done with open-ended, or ill-structured, problems, similar to the types of problems students might face in their professional lives. Given the national discourse on educational system reform aligned with 21st century skills, including problem solving, it is critical to provide educational experiences that help students learn to solve all types of problems, including ill-structured problems.
Thermorheological behavior and coupling problem of structural materials
International Nuclear Information System (INIS)
Bychawski, Z.
1975-01-01
The rheological behavior of structural materials is considerably stimulated in the presence of a temperature field. This influence is manifested by the changes in their thermodynamic characteristics. Two alternatives of substantial behavior are investigated. One is concerned with comparatively small influence of dissipative properties on the amount of internal energy while the other one related to the deformation state characterized by almost total dissipation process. The above problems mentioned are discussed in connection with the meaning of thermomechanical coupling. A double significance may be prescribed to the latter. One follows from the appearence of heat fluxes due to deformation changes and the other is concerned with total or specified responses of the material. The corresponding constitutive equation for the body considered is derived by using the generalized superposition principle. On the basis of the functional obtained the form of dissipative function is obtained. It follows directly from superposing energetic phenomena of dissipative character. As both the procedures are effected at the differential level, the resulting integral forms are obtained by assuming the integrability conditions to be valid. The results are discussed on the basis of premises which follow from the law of thermodynamics of irreversible processes. It is concluded that dissipative ability of the material may constitute a certain measure of its actual stability. In particular, the amount of dissipated energy may indicate the attainment of certain state of the material in question which should be considered as critical
Typesafe Abstractions for Tensor Operations
Chen, Tongfei
2017-01-01
We propose a typesafe abstraction to tensors (i.e. multidimensional arrays) exploiting the type-level programming capabilities of Scala through heterogeneous lists (HList), and showcase typesafe abstractions of common tensor operations and various neural layers such as convolution or recurrent neural networks. This abstraction could lay the foundation of future typesafe deep learning frameworks that runs on Scala/JVM.
Using Digital Mapping Tool in Ill-Structured Problem Solving
Bai, Hua
2013-01-01
Scaffolding students' problem solving and helping them to improve problem solving skills are critical in instructional design courses. This study investigated the effects of students' uses of a digital mapping tool on their problem solving performance in a design case study. It was found that the students who used the digital mapping tool…
Ge, Xun; Law, Victor; Huang, Kun
2016-01-01
One of the goals for problem-based learning (PBL) is to promote self-regulation. Although self-regulation has been studied extensively, its interrelationships with ill-structured problem solving have been unclear. In order to clarify the interrelationships, this article proposes a conceptual framework illustrating the iterative processes among…
Killing-Yano tensors and Nambu mechanics
International Nuclear Information System (INIS)
Baleanu, D.
1998-01-01
Killing-Yano tensors were introduced in 1952 by Kentaro-Yano from mathematical point of view. The physical interpretation of Killing-Yano tensors of rank higher than two was unclear. We found that all Killing-Yano tensors η i 1 i 2 . .. i n with covariant derivative zero are Nambu tensors. We found that in the case of flat space case all Killing-Yano tensors are Nambu tensors. In the case of Taub-NUT and Kerr-Newmann metric Killing-Yano tensors of order two generate Nambu tensors of rank 3
Embryo Cell Membranes Reconstruction by Tensor Voting
Michelin , Gaël; Guignard , Léo; Fiuza , Ulla-Maj; Malandain , Grégoire
2014-01-01
International audience; Image-based studies of developing organs or embryos produce a huge quantity of data. To handle such high-throughput experimental protocols, automated computer-assisted methods are highly desirable. This article aims at designing an efficient cell segmentation method from microscopic images. The proposed approach is twofold: first, cell membranes are enhanced or extracted by the means of structure-based filters, and then perceptual grouping (i.e. tensor voting) allows t...
Bayesian CP Factorization of Incomplete Tensors with Automatic Rank Determination.
Zhao, Qibin; Zhang, Liqing; Cichocki, Andrzej
2015-09-01
CANDECOMP/PARAFAC (CP) tensor factorization of incomplete data is a powerful technique for tensor completion through explicitly capturing the multilinear latent factors. The existing CP algorithms require the tensor rank to be manually specified, however, the determination of tensor rank remains a challenging problem especially for CP rank . In addition, existing approaches do not take into account uncertainty information of latent factors, as well as missing entries. To address these issues, we formulate CP factorization using a hierarchical probabilistic model and employ a fully Bayesian treatment by incorporating a sparsity-inducing prior over multiple latent factors and the appropriate hyperpriors over all hyperparameters, resulting in automatic rank determination. To learn the model, we develop an efficient deterministic Bayesian inference algorithm, which scales linearly with data size. Our method is characterized as a tuning parameter-free approach, which can effectively infer underlying multilinear factors with a low-rank constraint, while also providing predictive distributions over missing entries. Extensive simulations on synthetic data illustrate the intrinsic capability of our method to recover the ground-truth of CP rank and prevent the overfitting problem, even when a large amount of entries are missing. Moreover, the results from real-world applications, including image inpainting and facial image synthesis, demonstrate that our method outperforms state-of-the-art approaches for both tensor factorization and tensor completion in terms of predictive performance.
Scalar-tensor approach to the construction of theory of topological transformations
International Nuclear Information System (INIS)
Konstantinov, M.Yu.
1985-01-01
Problem of construction of the classical gravitational theory, which solutions in the explicit form contain description of topological transformations, is under study. With this object in view, the scalar-tensor formalism is considered based on a representation of some subclass of space-like hypersurfaces as surfaces of a smooth function level in four-dimensional manifolds. Solutions of the theory along with the Lorentz space-time structure and space-like surface topology define some reference system, but the type of topological transformations is not dependent on the reference system option. All these facts prove the above approach correctness. Two variants of the scalar-tensor theory of topological transformations are considered as an example; one of them is reduced to the Einstein gravitational theory in the regular space region and another represents a nontrivial modification of the Brans-Dikker theory
MATLAB tensor classes for fast algorithm prototyping.
Energy Technology Data Exchange (ETDEWEB)
Bader, Brett William; Kolda, Tamara Gibson (Sandia National Laboratories, Livermore, CA)
2004-10-01
Tensors (also known as mutidimensional arrays or N-way arrays) are used in a variety of applications ranging from chemometrics to psychometrics. We describe four MATLAB classes for tensor manipulations that can be used for fast algorithm prototyping. The tensor class extends the functionality of MATLAB's multidimensional arrays by supporting additional operations such as tensor multiplication. The tensor as matrix class supports the 'matricization' of a tensor, i.e., the conversion of a tensor to a matrix (and vice versa), a commonly used operation in many algorithms. Two additional classes represent tensors stored in decomposed formats: cp tensor and tucker tensor. We descibe all of these classes and then demonstrate their use by showing how to implement several tensor algorithms that have appeared in the literature.
Tensor-based Dictionary Learning for Dynamic Tomographic Reconstruction
Tan, Shengqi; Zhang, Yanbo; Wang, Ge; Mou, Xuanqin; Cao, Guohua; Wu, Zhifang; Yu, Hengyong
2015-01-01
In dynamic computed tomography (CT) reconstruction, the data acquisition speed limits the spatio-temporal resolution. Recently, compressed sensing theory has been instrumental in improving CT reconstruction from far few-view projections. In this paper, we present an adaptive method to train a tensor-based spatio-temporal dictionary for sparse representation of an image sequence during the reconstruction process. The correlations among atoms and across phases are considered to capture the characteristics of an object. The reconstruction problem is solved by the alternating direction method of multipliers. To recover fine or sharp structures such as edges, the nonlocal total variation is incorporated into the algorithmic framework. Preclinical examples including a sheep lung perfusion study and a dynamic mouse cardiac imaging demonstrate that the proposed approach outperforms the vectorized dictionary-based CT reconstruction in the case of few-view reconstruction. PMID:25779991
Tensor-based dictionary learning for dynamic tomographic reconstruction
International Nuclear Information System (INIS)
Tan, Shengqi; Wu, Zhifang; Zhang, Yanbo; Mou, Xuanqin; Wang, Ge; Cao, Guohua; Yu, Hengyong
2015-01-01
In dynamic computed tomography (CT) reconstruction, the data acquisition speed limits the spatio-temporal resolution. Recently, compressed sensing theory has been instrumental in improving CT reconstruction from far few-view projections. In this paper, we present an adaptive method to train a tensor-based spatio-temporal dictionary for sparse representation of an image sequence during the reconstruction process. The correlations among atoms and across phases are considered to capture the characteristics of an object. The reconstruction problem is solved by the alternating direction method of multipliers. To recover fine or sharp structures such as edges, the nonlocal total variation is incorporated into the algorithmic framework. Preclinical examples including a sheep lung perfusion study and a dynamic mouse cardiac imaging demonstrate that the proposed approach outperforms the vectorized dictionary-based CT reconstruction in the case of few-view reconstruction. (paper)
Efficient tensor completion for color image and video recovery: Low-rank tensor train
Bengua, Johann A.; Phien, Ho N.; Tuan, Hoang D.; Do, Minh N.
2016-01-01
This paper proposes a novel approach to tensor completion, which recovers missing entries of data represented by tensors. The approach is based on the tensor train (TT) rank, which is able to capture hidden information from tensors thanks to its definition from a well-balanced matricization scheme. Accordingly, new optimization formulations for tensor completion are proposed as well as two new algorithms for their solution. The first one called simple low-rank tensor completion via tensor tra...
Random SU(2) invariant tensors
Li, Youning; Han, Muxin; Ruan, Dong; Zeng, Bei
2018-04-01
SU(2) invariant tensors are states in the (local) SU(2) tensor product representation but invariant under the global group action. They are of importance in the study of loop quantum gravity. A random tensor is an ensemble of tensor states. An average over the ensemble is carried out when computing any physical quantities. The random tensor exhibits a phenomenon known as ‘concentration of measure’, which states that for any bipartition the average value of entanglement entropy of its reduced density matrix is asymptotically the maximal possible as the local dimensions go to infinity. We show that this phenomenon is also true when the average is over the SU(2) invariant subspace instead of the entire space for rank-n tensors in general. It is shown in our earlier work Li et al (2017 New J. Phys. 19 063029) that the subleading correction of the entanglement entropy has a mild logarithmic divergence when n = 4. In this paper, we show that for n > 4 the subleading correction is not divergent but a finite number. In some special situation, the number could be even smaller than 1/2, which is the subleading correction of random state over the entire Hilbert space of tensors.
On the Structure of the Fixed Charge Transportation Problem
Kowalski, K.
2005-01-01
This work extends the theory of the fixed charge transportation problem (FCTP), currently based mostly on a forty-year-old publication by Hirsch and Danzig. This paper presents novel properties that need to be considered by those using existing, or those developing new methods for optimizing FCTP. It also defines the problem in an easier way,…
Features for Exploiting Black-Box Optimization Problem Structure
DEFF Research Database (Denmark)
Tierney, Kevin; Malitsky, Yuri; Abell, Tinus
2013-01-01
landscape of BBO problems and show how an algorithm portfolio approach can exploit these general, problem indepen- dent features and outperform the utilization of any single minimization search strategy. We test our methodology on data from the GECCO Workshop on BBO Benchmarking 2012, which contains 21...
De Corte, E.; And Others
One important finding from recent research on multiplication word problems is that children's performances are strongly affected by the nature of the multiplier (whether it is an integer, decimal larger than 1 or a decimal smaller than 1). On the other hand, the size of the multiplicand has little or no effect on problem difficulty. The aim of the…
Wu, Jibing; Meng, Qinggang; Deng, Su; Huang, Hongbin; Wu, Yahui; Badii, Atta
2017-01-01
Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS) algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic.
Pre-Service Elementary Teachers' Motivation and Ill-Structured Problem Solving in Korea
Kim, Min Kyeong; Cho, Mi Kyung
2016-01-01
This article examines the use and application of an ill-structured problem to pre-service elementary teachers in Korea in order to find implications of pre-service teacher education with regard to contextualized problem solving by analyzing experiences of ill-structured problem solving. Participants were divided into small groups depending on the…
Hong, Jee Yun; Kim, Min Kyeong
2016-01-01
Ill-structured problems can be regarded as one of the measures that meet recent social needs emphasizing students' abilities to solve real-life problems. This study aimed to analyze the mathematical abstraction process in solving such problems, and to identify the mathematical abstraction level ([I] Recognition of mathematical structure through…
A defect in holographic interpretations of tensor networks
Energy Technology Data Exchange (ETDEWEB)
Czech, Bartłomiej [Institute for Advanced Study,Princeton, NJ 08540 (United States); Nguyen, Phuc H.; Swaminathan, Sivaramakrishnan [Theory Group, Department of Physics and Texas Cosmology Center,The University of Texas at Austin,Austin, TX 78712 (United States)
2017-03-16
We initiate the study of how tensor networks reproduce properties of static holographic space-times, which are not locally pure anti-de Sitter. We consider geometries that are holographically dual to ground states of defect, interface and boundary CFTs and compare them to the structure of the requisite MERA networks predicted by the theory of minimal updates. When the CFT is deformed, certain tensors require updating. On the other hand, even identical tensors can contribute differently to estimates of entanglement entropies. We interpret these facts holographically by associating tensor updates to turning on non-normalizable modes in the bulk. In passing, we also clarify and complement existing arguments in support of the theory of minimal updates, propose a novel ansatz called rayed MERA that applies to a class of generalized interface CFTs, and analyze the kinematic spaces of the thin wall and AdS{sub 3}-Janus geometries.
Propagation of uncertainties in problems of structural reliability
International Nuclear Information System (INIS)
Mazumdar, M.; Marshall, J.A.; Chay, S.C.
1978-01-01
The problem of controlling a variable Y such that the probability of its exceeding a specified design limit L is very small, is treated. This variable is related to a set of random variables Xsub(i) by means of a known function Y=f(Xsub(i)). The following approximate methods are considered for estimating the propagation of error in the Xsub(i)'s through the function f(-): linearization; method of moments; Monte Carlo methods; numerical integration. Response surface and associated design of experiments problems as well as statistical inference problems are discussed. (Auth.)
Electrical tensor Green functions for cylindrical waveguides
International Nuclear Information System (INIS)
Prijmenko, S.D.; Papkovich, V.G.; Khizhnyak, N.A.
1988-01-01
Formation of electrical tensor Green functions for cylindrical waveguides is considered. Behaviour of these functions in the source region is studied. Cases of electrical tensor Green functions for vector potential G E (r-vector, r'-vector) and electric field G e (r-vector, r'-vector) are analysed. When forming G E (r-vector, r'-vector), its dependence on lateral coordinates is taken into account by means of two-dimensional fundamental vector Hansen functions, several methods are used to take into account the dependence on transverse coordinate. When forming G e (r-vector, r'-vector) we use the fact that G E (r-vector, r'-vector) and G e (r-vector, r'-vector) are the generalized functions. It is shown that G e (r-vector, r'-vector) behaviour in the source region is defined by a singular term, which properties are described by the delta-function. Two variants of solving the problem of defining singular and regular sides of tensor function G E (r-vector, r'-vector) are presented. 23 refs
The Role of Content Knowledge in Ill-Structured Problem Solving for High School Physics Students
Milbourne, Jeff; Wiebe, Eric
2018-01-01
While Physics Education Research has a rich tradition of problem-solving scholarship, most of the work has focused on more traditional, well-defined problems. Less work has been done with ill-structured problems, problems that are better aligned with the engineering and design-based scenarios promoted by the Next Generation Science Standards. This…
Tensor Product of Polygonal Cell Complexes
Chien, Yu-Yen
2017-01-01
We introduce the tensor product of polygonal cell complexes, which interacts nicely with the tensor product of link graphs of complexes. We also develop the unique factorization property of polygonal cell complexes with respect to the tensor product, and study the symmetries of tensor products of polygonal cell complexes.
The Einstein tensor characterizing some Riemann spaces
International Nuclear Information System (INIS)
Rahman, M.S.
1993-07-01
A formal definition of the Einstein tensor is given. Mention is made of how this tensor plays a role of expressing certain conditions in a precise form. The cases of reducing the Einstein tensor to a zero tensor are studied on its merit. A lucid account of results, formulated as theorems, on Einstein symmetric and Einstein recurrent spaces is then presented. (author). 5 refs
X-ray strain tensor imaging: FEM simulation and experiments with a micro-CT.
Kim, Jae G; Park, So E; Lee, Soo Y
2014-01-01
In tissue elasticity imaging, measuring the strain tensor components is necessary to solve the inverse problem. However, it is impractical to measure all the tensor components in ultrasound or MRI elastography because of their anisotropic spatial resolution. The objective of this study is to compute 3D strain tensor maps from the 3D CT images of a tissue-mimicking phantom. We took 3D micro-CT images of the phantom twice with applying two different mechanical compressions to it. Applying the 3D image correlation technique to the CT images under different compression, we computed 3D displacement vectors and strain tensors at every pixel. To evaluate the accuracy of the strain tensor maps, we made a 3D FEM model of the phantom, and we computed strain tensor maps through FEM simulation. Experimentally obtained strain tensor maps showed similar patterns to the FEM-simulated ones in visual inspection. The correlation between the strain tensor maps obtained from the experiment and the FEM simulation ranges from 0.03 to 0.93. Even though the strain tensor maps suffer from high level noise, we expect the x-ray strain tensor imaging may find some biomedical applications such as malignant tissue characterization and stress analysis inside the tissues.
Direct solution of the Chemical Master Equation using quantized tensor trains.
Directory of Open Access Journals (Sweden)
Vladimir Kazeev
2014-03-01
Full Text Available The Chemical Master Equation (CME is a cornerstone of stochastic analysis and simulation of models of biochemical reaction networks. Yet direct solutions of the CME have remained elusive. Although several approaches overcome the infinite dimensional nature of the CME through projections or other means, a common feature of proposed approaches is their susceptibility to the curse of dimensionality, i.e. the exponential growth in memory and computational requirements in the number of problem dimensions. We present a novel approach that has the potential to "lift" this curse of dimensionality. The approach is based on the use of the recently proposed Quantized Tensor Train (QTT formatted numerical linear algebra for the low parametric, numerical representation of tensors. The QTT decomposition admits both, algorithms for basic tensor arithmetics with complexity scaling linearly in the dimension (number of species and sub-linearly in the mode size (maximum copy number, and a numerical tensor rounding procedure which is stable and quasi-optimal. We show how the CME can be represented in QTT format, then use the exponentially-converging hp-discontinuous Galerkin discretization in time to reduce the CME evolution problem to a set of QTT-structured linear equations to be solved at each time step using an algorithm based on Density Matrix Renormalization Group (DMRG methods from quantum chemistry. Our method automatically adapts the "basis" of the solution at every time step guaranteeing that it is large enough to capture the dynamics of interest but no larger than necessary, as this would increase the computational complexity. Our approach is demonstrated by applying it to three different examples from systems biology: independent birth-death process, an example of enzymatic futile cycle, and a stochastic switch model. The numerical results on these examples demonstrate that the proposed QTT method achieves dramatic speedups and several orders of
PROBLEMS OF MATHEMATICAL MODELING OF THE ENTERPRISES ORGANIZATIONAL STRUCTURE
Directory of Open Access Journals (Sweden)
N. V. Andrianov
2006-01-01
Full Text Available The analysis of the mathematical models which can be used at optimization of the control system of the enterprise organizational structure is presented. The new approach to the mathematical modeling of the enterprise organizational structure, based on using of temporary characteristics of the control blocks working, is formulated
Wu, H; Wang, X; Gao, Y; Lin, F; Song, T; Zou, Y; Xu, L; Lei, H
2016-05-13
Animal models of N-methyl-d-aspartate receptor (NMDAR) antagonism have been widely used for schizophrenia research. Less is known whether these models are associated with macroscopic brain structural changes that resemble those in clinical schizophrenia. Magnetic resonance imaging (MRI) was used to measure brain structural changes in rats subjected to repeated administration of MK801 in a regimen (daily dose of 0.2mg/kg for 14 consecutive days) known to be able to induce schizophrenia-like cognitive impairments. Voxel-based morphometry (VBM) revealed significant gray matter (GM) atrophy in the hippocampus, ventral striatum (vStr) and cortex. Diffusion tensor imaging (DTI) demonstrated microstructural impairments in the corpus callosum (cc). Histopathological results corroborated the MRI findings. Treatment-induced behavioral abnormalities were not measured such that correlation between the brain structural changes observed and schizophrenia-like behaviors could not be established. Chronic MK801 administration induces MRI-observable brain structural changes that are comparable to those observed in schizophrenia patients, supporting the notion that NMDAR hypofunction contributes to the pathology of schizophrenia. Imaging-derived brain structural changes in animal models of NMDAR antagonism may be useful measurements for studying the effects of treatments and interventions targeting schizophrenia. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.
McCrum, Daniel Patrick
2017-11-01
For a structural engineer, effective communication and interaction with architects cannot be underestimated as a key skill to success throughout their professional career. Structural engineers and architects have to share a common language and understanding of each other in order to achieve the most desirable architectural and structural designs. This interaction and engagement develops during their professional career but needs to be nurtured during their undergraduate studies. The objective of this paper is to present the strategies employed to engage higher order thinking in structural engineering students in order to help them solve complex problem-based learning (PBL) design scenarios presented by architecture students. The strategies employed were applied in the experimental setting of an undergraduate module in structural engineering at Queen's University Belfast in the UK. The strategies employed were active learning to engage with content knowledge, the use of physical conceptual structural models to reinforce key concepts and finally, reinforcing the need for hand sketching of ideas to promote higher order problem-solving. The strategies employed were evaluated through student survey, student feedback and module facilitator (this author) reflection. The strategies were qualitatively perceived by the tutor and quantitatively evaluated by students in a cross-sectional study to help interaction with the architecture students, aid interdisciplinary learning and help students creatively solve problems (through higher order thinking). The students clearly enjoyed this module and in particular interacting with structural engineering tutors and students from another discipline.
The solution of location problems with certain existing facility structures
DEFF Research Database (Denmark)
Juel, Henrik; Love, Robert F.
1983-01-01
It is known that in the Euclidean distance case, the optimal minisum location of a new facility in relation to four existing facilities is at the intersection of the two lines joining two pairs of the facilities. The authors extend this concept to minisum problems having any even number of existing...... facilities and characterized by generalized distance norms...
Structured pigeonhole principle, search problems and hard tautologies
Czech Academy of Sciences Publication Activity Database
Krajíček, Jan
2005-01-01
Roč. 70, č. 2 (2005), s. 619-630 ISSN 0022-4812 R&D Projects: GA AV ČR(CZ) IAA1019401; GA MŠk(CZ) LN00A056 Institutional research plan: CEZ:AV0Z10190503 Keywords : proof complexity * pigeonhole principle * serch problems Subject RIV: BA - General Mathematics Impact factor: 0.470, year: 2005
solution of confined seepage problems below hydraulic structures
African Journals Online (AJOL)
user
1985-09-01
Sep 1, 1985 ... boundaries are used for solving the seepage problem beneath practical profiles of ... 1. INTRODUCTION. The study of flow through porous media has a wide range of .... free surface flow [3, 4, 5] and unconfined flow situations ...
Seismic data interpolation and denoising by learning a tensor tight frame
International Nuclear Information System (INIS)
Liu, Lina; Ma, Jianwei; Plonka, Gerlind
2017-01-01
Seismic data interpolation and denoising plays a key role in seismic data processing. These problems can be understood as sparse inverse problems, where the desired data are assumed to be sparsely representable within a suitable dictionary. In this paper, we present a new method based on a data-driven tight frame (DDTF) of Kronecker type (KronTF) that avoids the vectorization step and considers the multidimensional structure of data in a tensor-product way. It takes advantage of the structure contained in all different modes (dimensions) simultaneously. In order to overcome the limitations of a usual tensor-product approach we also incorporate data-driven directionality. The complete method is formulated as a sparsity-promoting minimization problem. It includes two main steps. In the first step, a hard thresholding algorithm is used to update the frame coefficients of the data in the dictionary; in the second step, an iterative alternating method is used to update the tight frame (dictionary) in each different mode. The dictionary that is learned in this way contains the principal components in each mode. Furthermore, we apply the proposed KronTF to seismic interpolation and denoising. Examples with synthetic and real seismic data show that the proposed method achieves better results than the traditional projection onto convex sets method based on the Fourier transform and the previous vectorized DDTF methods. In particular, the simple structure of the new frame construction makes it essentially more efficient. (paper)
Seismic data interpolation and denoising by learning a tensor tight frame
Liu, Lina; Plonka, Gerlind; Ma, Jianwei
2017-10-01
Seismic data interpolation and denoising plays a key role in seismic data processing. These problems can be understood as sparse inverse problems, where the desired data are assumed to be sparsely representable within a suitable dictionary. In this paper, we present a new method based on a data-driven tight frame (DDTF) of Kronecker type (KronTF) that avoids the vectorization step and considers the multidimensional structure of data in a tensor-product way. It takes advantage of the structure contained in all different modes (dimensions) simultaneously. In order to overcome the limitations of a usual tensor-product approach we also incorporate data-driven directionality. The complete method is formulated as a sparsity-promoting minimization problem. It includes two main steps. In the first step, a hard thresholding algorithm is used to update the frame coefficients of the data in the dictionary; in the second step, an iterative alternating method is used to update the tight frame (dictionary) in each different mode. The dictionary that is learned in this way contains the principal components in each mode. Furthermore, we apply the proposed KronTF to seismic interpolation and denoising. Examples with synthetic and real seismic data show that the proposed method achieves better results than the traditional projection onto convex sets method based on the Fourier transform and the previous vectorized DDTF methods. In particular, the simple structure of the new frame construction makes it essentially more efficient.
Development of the Tensoral Computer Language
Ferziger, Joel; Dresselhaus, Eliot
1996-01-01
The research scientist or engineer wishing to perform large scale simulations or to extract useful information from existing databases is required to have expertise in the details of the particular database, the numerical methods and the computer architecture to be used. This poses a significant practical barrier to the use of simulation data. The goal of this research was to develop a high-level computer language called Tensoral, designed to remove this barrier. The Tensoral language provides a framework in which efficient generic data manipulations can be easily coded and implemented. First of all, Tensoral is general. The fundamental objects in Tensoral represent tensor fields and the operators that act on them. The numerical implementation of these tensors and operators is completely and flexibly programmable. New mathematical constructs and operators can be easily added to the Tensoral system. Tensoral is compatible with existing languages. Tensoral tensor operations co-exist in a natural way with a host language, which may be any sufficiently powerful computer language such as Fortran, C, or Vectoral. Tensoral is very-high-level. Tensor operations in Tensoral typically act on entire databases (i.e., arrays) at one time and may, therefore, correspond to many lines of code in a conventional language. Tensoral is efficient. Tensoral is a compiled language. Database manipulations are simplified optimized and scheduled by the compiler eventually resulting in efficient machine code to implement them.
The 1/ N Expansion of Tensor Models Beyond Perturbation Theory
Gurau, Razvan
2014-09-01
We analyze in full mathematical rigor the most general quartically perturbed invariant probability measure for a random tensor. Using a version of the Loop Vertex Expansion (which we call the mixed expansion) we show that the cumulants write as explicit series in 1/ N plus bounded rest terms. The mixed expansion recasts the problem of determining the subleading corrections in 1/ N into a simple combinatorial problem of counting trees decorated by a finite number of loop edges. As an aside, we use the mixed expansion to show that the (divergent) perturbative expansion of the tensor models is Borel summable and to prove that the cumulants respect an uniform scaling bound. In particular the quartically perturbed measures fall, in the N→ ∞ limit, in the universality class of Gaussian tensor models.
Physical and Geometric Interpretations of the Riemann Tensor, Ricci Tensor, and Scalar Curvature
Loveridge, Lee C.
2004-01-01
Various interpretations of the Riemann Curvature Tensor, Ricci Tensor, and Scalar Curvature are described. Also, the physical meanings of the Einstein Tensor and Einstein's Equations are discussed. Finally a derivation of Newtonian Gravity from Einstein's Equations is given.
Coulomb two-body problem with internal structure
International Nuclear Information System (INIS)
Kuperin, Yu.A.; Makarov, K.A.; Mel'nikov, Yu.B.
1988-01-01
The methods of the theory of extensions to an enlarged Hilbert space are used to construct a model of the interaction of the external (Coulomb) and internal (quark) channels in the two-body problem. The mutual influence of the spectra of the corresponding channel Hamiltonians is studied: it leads, in particular, to a rearrangement of the spectra of hadronic atoms. An explicit representation is obtained for the S matrix, and its singularities on the energy shell are studied
A Multiobjective Approach Applied to the Protein Structure Prediction Problem
2002-03-07
local conformations [38]. Moreover, all these models have the same theme in trying to define the properties a real protein has when folding. Today , it...attempted to solve the PSP problem with a real valued GA and found better results than a competitor (Scheraga, et al) [50]; however, today we know that...ACM Symposium on Applied computing (SAC01) (March 11-14 2001). Las Vegas, Nevada. [22] Derrida , B. “Random Energy Model: Limit of a Family of
Nash evolutionary algorithms : Testing problem size in reconstruction problems in frame structures
Greiner, D.; Periaux, Jacques; Emperador, J.M.; Galván, B.; Winter, G.
2016-01-01
The use of evolutionary algorithms has been enhanced in recent years for solving real engineering problems, where the requirements of intense computational calculations are needed, especially when computational engineering simulations are involved (use of finite element method, boundary element method, etc). The coupling of game-theory concepts in evolutionary algorithms has been a recent line of research which could enhance the efficiency of the optimum design procedure and th...
Green's tensor calculations of plasmon resonances of single holes and hole pairs in thin gold films
International Nuclear Information System (INIS)
Alegret, Joan; Kaell, Mikael; Johansson, Peter
2008-01-01
We present numerical calculations of the plasmon properties of single-hole and hole-pair structures in optically thin gold films obtained with the Green's tensor formalism for stratified media. The method can be used to obtain the optical properties of a given hole system, without problems associated with the truncation of the infinite metal film. The calculations are compared with previously published experimental data and an excellent agreement is found. In particular, the calculations are shown to reproduce the evolution of the hole plasmon resonance spectrum as a function of hole diameter, film thickness and hole separation.
FLAPW Study of the EFG Tensor at Cd Impurities in In2O3
International Nuclear Information System (INIS)
Errico, L. A.; Renteria, M.; Fabricius, G.; Darriba, G. N.
2004-01-01
We report an ab initio study of the electric-field gradient tensor (EFG) at Cd impurities located at both nonequivalent cationic sites in the semiconductor In 2 O 3 . Calculations were performed with the FLAPW method that allows us to treat the electronic structure of the doped system and the atomic relaxations introduced by the impurities in the host in a fully self-consistent way. From our results for the EFG (in excellent agreement with the experiments), it is clear that the problem of the EFG at Cd impurities in In 2 O 3 cannot be described by the point-charge model and antishielding factors.
James, Jija S; Kumari, Sheela R; Sreedharan, Ruma Madhu; Thomas, Bejoy; Radhkrishnan, Ashalatha; Kesavadas, Chandrasekharan
2015-01-01
To evaluate the efficacy of diffusion fiber tractography (DFT) and voxel-based morphometry (VBM) for lateralizing language in comparison with functional magnetic resonance imaging (fMRI) to noninvasively assess hemispheric language lateralization in normal healthy volunteers. The aim of the present study is to evaluate the concordance of language lateralization obtained by diffusion tensor imaging (DTI) and VBM to fMRI, and thus to see whether there exists an anatomical correlate for language lateralization result obtained using fMRI. This is an advanced neuroimaging study conducted in normal healthy volunteers. Fifty-seven normal healthy subjects (39 males and 18 females; age range: 15-40 years) underwent language fMRI and 30 underwent direction DTI. fMRI language laterality index (LI), fiber tract asymmetry index (AI), and tract-based statistics of dorsal and ventral language pathways were calculated. The combined results were correlated with VBM-based volumetry of Heschl's gyrus (HG), planum temporale (PT), and insula for lateralization of language function. A linear regression analysis was done to study the correlation between fMRI, DTI, and VBM measurements. A good agreement was found between language fMRI LI and fiber tract AI, more specifically for arcuate fasciculus (ArcF) and inferior longitudinal fasciculus (ILF). The study demonstrated significant correlations (P based statistics, and PT and HG volumetry for determining language lateralization. A strong one-to-one correlation between fMRI, laterality index, DTI tractography measures, and VBM-based volumetry measures for determining language lateralization exists.
Utilizing Problem Structure in Optimization of Radiation Therapy
International Nuclear Information System (INIS)
Carlsson, Fredrik
2008-04-01
In this thesis, optimization approaches for intensity-modulated radiation therapy are developed and evaluated with focus on numerical efficiency and treatment delivery aspects. The first two papers deal with strategies for solving fluence map optimization problems efficiently while avoiding solutions with jagged fluence profiles. The last two papers concern optimization of step-and-shoot parameters with emphasis on generating treatment plans that can be delivered efficiently and accurately. In the first paper, the problem dimension of a fluence map optimization problem is reduced through a spectral decomposition of the Hessian of the objective function. The weights of the eigenvectors corresponding to the p largest eigenvalues are introduced as optimization variables, and the impact on the solution of varying p is studied. Including only a few eigenvector weights results in faster initial decrease of the objective value, but with an inferior solution, compared to optimization of the bixel weights. An approach combining eigenvector weights and bixel weights produces improved solutions, but at the expense of the pre-computational time for the spectral decomposition. So-called iterative regularization is performed on fluence map optimization problems in the second paper. The idea is to find regular solutions by utilizing an optimization method that is able to find near-optimal solutions with non-jagged fluence profiles in few iterations. The suitability of a quasi-Newton sequential quadratic programming method is demonstrated by comparing the treatment quality of deliverable step-and-shoot plans, generated through leaf sequencing with a fixed number of segments, for different number of bixel-weight iterations. A conclusion is that over-optimization of the fluence map optimization problem prior to leaf sequencing should be avoided. An approach for dynamically generating multileaf collimator segments using a column generation approach combined with optimization of
The tensor rank of tensor product of two three-qubit W states is eight
Chen, Lin; Friedland, Shmuel
2017-01-01
We show that the tensor rank of tensor product of two three-qubit W states is not less than eight. Combining this result with the recent result of M. Christandl, A. K. Jensen, and J. Zuiddam that the tensor rank of tensor product of two three-qubit W states is at most eight, we deduce that the tensor rank of tensor product of two three-qubit W states is eight. We also construct the upper bound of the tensor rank of tensor product of many three-qubit W states.
A combinatorial enumeration problem of RNA secondary structures
African Journals Online (AJOL)
use
2011-12-21
Dec 21, 2011 ... connection between Discrete Mathematics and Compu- tational Molecular Biology (Chen et al, 2005; Hofacker et ... in Computational Molecular Biology. An RNA molecule is described by its sequences of bases ... Here, a mathematical definition of secondary structure is given (Stein and Waterman 1978).
Measuring self-control problems: a structural estimation
Bucciol, A.
2009-01-01
We perform a structural estimation of the preference parameters in a buffer-stock consumption model augmented with temptation disutility. We adopt a two-stage Method of Simulated Moments methodology to match our simulated moments with those observed in the US Survey of Consumer Finances. To identify
Problems of solidificated radioactive wastes burial into deep geological structures
International Nuclear Information System (INIS)
Kedrovskij, O.L.; Leonov, E.A.; Romadin, N.M.; Shishcits, I.Yu.
1981-01-01
Perspectives are noted of the radioactive wastes burial into deep geopogical structures. For these purposes it has been proposed to investigate severap types of rocks, which do not have intensive gas-generation when beeng heated; salt deposits and clays. Basing on the results of calculations it has been shown that the dimentions of zones of substantial deformations in the case of the high-level radioactive wastes burial to not exceed several hundreds of meters. Conclusion is made that in the case of choosing the proper geotogicat structure for burial and ir the case of inclusion in the structure of the burial site a zone of sanitary alienation, it is possible to isolate wastes safely for all the period of preservation. Preliminary demands have been formulated to geological structures and underground burial sites. As main tasks for optimizatiop of burial sited are considered: determination of necessary types, number and reliability of barriers which ensure isolation of wastes; to make prognoses of the stressed and deformed state of a geological massif on the influence of thermal field; investigation in changes of chemical and physical properties of rocks under heat, radiative and chemical influence; estimation of possible diffusion of radioactivity in a mountin massif; development of a rational mining-thechnological schemes of the burual of wastes of different types. A row of tasks in the farmeworks of this probtem are sotved successfutty. Some resutts are given of the theoretical investigations in determination of zones of distructions of rocks because of heat-load [ru
A combinatorial enumeration problem of RNA secondary structures
African Journals Online (AJOL)
use
2011-12-21
Dec 21, 2011 ... interesting combinatorial questions (Chen et al., 2005;. Liu, 2006; Schmitt and Waterman 1994; Stein and. Waterman 1978). The research on the enumeration of. RNA secondary structures becomes one of the hot topics in Computational Molecular Biology. An RNA molecule is described by its sequences of.
State Confessional Relations: Problem of the Subject Structure
Directory of Open Access Journals (Sweden)
Alexandra A. Dorskaya
2014-06-01
Full Text Available In the article various existing definitions of the concept "state and confessional relations" are analyzed, also author's definition is offered. Three levels of the state and confessional relations are revealed: conceptual, legislative and administrative-managerial. In the article it is shown that in Russia a tradition of only two subjects of the state and confessional relations – government bodies and the religious organizations allocation exists. It is revealed that at the present stage many researchers are dissatisfied with such situation. Scientific sources of the problem of the state and church relations within the psychological school of the law, which are addressed to the personality and experiences in the legal sphere are studied and revealed. Special attention is paid to scientific heritage of the M.A. Reysner, who was one of the first to begin study of this problem. In the article the question of the school of three subjects of the state and confessional relations allocation formation, what adds the faithful or faithless personality in addition to two traditional subjects is analyzed. The state and confessional relations are considered in the context of the human rights development. The question of new type of the believer possessing high education level and knowledge formation is considered. In the article it is shown that at the present stage relations of any regulation between the state and religious organizations is based on the basis of international legal standards, domestic legislation and norms of canon law.
Winschel, Grace A.; Everett, Renata K.; Coppola, Brian P.; Shultz, Ginger V.
2015-01-01
Cooperative learning was employed as an instructional approach to facilitate student development of spectroscopy problem solving skills. An interactive online environment was used as a framework to structure weekly discussions around spectroscopy problems outside of class. Weekly discussions consisted of modified jigsaw-style problem solving…
Analyzing Pre-Service Primary Teachers' Fraction Knowledge Structures through Problem Posing
Kilic, Cigdem
2015-01-01
In this study it was aimed to determine pre-service primary teachers' knowledge structures of fraction through problem posing activities. A total of 90 pre-service primary teachers participated in this study. A problem posing test consisting of two questions was used and the participants were asked to generate as many as problems based on the…
Research Projects in Physics: A Mechanism for Teaching Ill-Structured Problem Solving
Milbourne, Jeff; Bennett, Jonathan
2017-01-01
Physics education research has a tradition of studying problem solving, exploring themes such as physical intuition and differences between expert and novice problem solvers. However, most of this work has focused on traditional, or well-structured, problems, similar to what might appear in a textbook. Less work has been done with open-ended, or…
Decorated tensor network renormalization for lattice gauge theories and spin foam models
International Nuclear Information System (INIS)
Dittrich, Bianca; Mizera, Sebastian; Steinhaus, Sebastian
2016-01-01
Tensor network techniques have proved to be powerful tools that can be employed to explore the large scale dynamics of lattice systems. Nonetheless, the redundancy of degrees of freedom in lattice gauge theories (and related models) poses a challenge for standard tensor network algorithms. We accommodate for such systems by introducing an additional structure decorating the tensor network. This allows to explicitly preserve the gauge symmetry of the system under coarse graining and straightforwardly interpret the fixed point tensors. We propose and test (for models with finite Abelian groups) a coarse graining algorithm for lattice gauge theories based on decorated tensor networks. We also point out that decorated tensor networks are applicable to other models as well, where they provide the advantage to give immediate access to certain expectation values and correlation functions. (paper)
Decorated tensor network renormalization for lattice gauge theories and spin foam models
Dittrich, Bianca; Mizera, Sebastian; Steinhaus, Sebastian
2016-05-01
Tensor network techniques have proved to be powerful tools that can be employed to explore the large scale dynamics of lattice systems. Nonetheless, the redundancy of degrees of freedom in lattice gauge theories (and related models) poses a challenge for standard tensor network algorithms. We accommodate for such systems by introducing an additional structure decorating the tensor network. This allows to explicitly preserve the gauge symmetry of the system under coarse graining and straightforwardly interpret the fixed point tensors. We propose and test (for models with finite Abelian groups) a coarse graining algorithm for lattice gauge theories based on decorated tensor networks. We also point out that decorated tensor networks are applicable to other models as well, where they provide the advantage to give immediate access to certain expectation values and correlation functions.
Relative Effects of Three Questioning Strategies in Ill-Structured, Small Group Problem Solving
Byun, Hyunjung; Lee, Jung; Cerreto, Frank A.
2014-01-01
The purpose of this research is to investigate the relative effectiveness of using three different question-prompt strategies on promoting metacognitive skills and performance in ill-structured problem solving by examining the interplay between peer interaction and cognitive scaffolding. An ill-structured problem-solving task was given to three…
DEFF Research Database (Denmark)
Niss, Martin
2017-01-01
This paper studies the cognitive obstacles related to one aspect of mathematization in physics problem-solving, namely, what might be called structuring for mathematization, where the problem situation is structured in such a way that a translation to a mathematical universe can be done. We report...
Thermal shock problems of bonded structure for plasma facing components
International Nuclear Information System (INIS)
Shibui, M.; Kuroda, T.; Kubota, Y.
1991-01-01
Thermal shock tests have been performed on W(Re)/Cu and Mo/Cu duplex structures with a particular emphasis on two failure modes: failure on the heated surface and failure near the bonding interface. The results indicate that failure of the duplex structure largely depends on the constraint of thermal strain on the heated surface and on the ductility changes of armour materials. Rapid debonding of the bonding interface may be attributed to the yielding of armour materials. This leads to a residual bending deformation when the armour cools down. Arguments are also presented in this paper on two parameter characterization of the failure of armour materials and on stress distribution near the free edge of the bonding interface. (orig.)
State vector labelling problem: a review of structural principles
International Nuclear Information System (INIS)
Louck, J.D.
1976-01-01
The technique of labeling state vectors by use of the simultaneous eigenvalues of a complete set of commuting Hermitian operators stems from the early days of quantum theory. In sharp contrast to the classical method, there stands the nonorthogonal bases methods of Moshinsky and Bargmann and the null space methods of Biedenharn and Louck. The structural principles underlying these various methods are presented and discussed. 2 figures
The problem of helium in structural materials for fusion reactor
International Nuclear Information System (INIS)
Nikiforov, A.S.; Zakharov, A.P.; Chuev, V.I.
1982-01-01
The processes of helium buildup in some metals and alloys at different energy neutron flux irradiation under thermonuclear reactor conditions are considered. The data on high temperature helium embrittlement of a number of stainless steels, titanium and aluminium alloys etc. are given A review of experiments concerning the implanted helium behaviour is presented. Possible reactions between helium atoms and point defects or their clusters are discussed. Analysed are material structure variations upon buildup in them up to 1 at % of helium
Link prediction via generalized coupled tensor factorisation
DEFF Research Database (Denmark)
Ermiş, Beyza; Evrim, Acar Ataman; Taylan Cemgil, A.
2012-01-01
and higher-order tensors. We propose to use an approach based on probabilistic interpretation of tensor factorisation models, i.e., Generalised Coupled Tensor Factorisation, which can simultaneously fit a large class of tensor models to higher-order tensors/matrices with com- mon latent factors using...... different loss functions. Numerical experiments demonstrate that joint analysis of data from multiple sources via coupled factorisation improves the link prediction performance and the selection of right loss function and tensor model is crucial for accurately predicting missing links....
A scalar-tensor bimetric brane world cosmology
International Nuclear Information System (INIS)
Youm, Donam
2001-08-01
We study a scalar-tensor bimetric cosmology in the Randall-Sundrum model with one positive tension brane, where the biscalar field is assumed to be confined on the brane. The effective Friedmann equations on the brane are obtained and analyzed. We comment on resolution of cosmological problems in this bimetric model. (author)
THE COMPOSER AND FOLKLORE PROBLEM: FACTORS OF STYLISTIC STRUCTURE
Directory of Open Access Journals (Sweden)
COCEAROVA GALINA
2017-12-01
Full Text Available This paper continues the author’s earlier study of the Composer and Folklore problem from the stylistic point of view. It is noted that in academic music, where the attention is focused not only on the speech or text characteristics, but primarily on the linguistic and stylistic material of folklore, the appeal to folk sources leads to the emergence of a number of stylistic factors, both, in the formation of the national style, and in the field of ethnic culture as a whole and integral stable system. The research points to the role of folklore as the genetic code of ethnic culture, as well as to other factors acting at on the level ,of musical discourse and musical language, contributing to the formation of „language flexibility” (A. Kolmogorov and, as a result, „flexibility of style”.
Sun oscillations and the problem of its internal structure
International Nuclear Information System (INIS)
Severnyj, A.B.; Kotov, V.A.; Tsap, T.T.
1979-01-01
Analysis of global solar oscillation measurements for five years (1974-1978, more than 1000 hours of observations, 215 days) is given. It is shown that the period of oscillations is 160sup(m)x0.10+-0sup(m)x004 and the amplitude is 1 m/s. The phases of oscillations, obtained at the Crimea, Stanford, Kitt Peak and Pic du Midi, are in good agreement, thus making the assumption on ''telluric origin'' of the oscillations improbable. It has been found: 1) slow, synchronous (at Crimea and Stanford) drift of the phase of velocity maximum from year to year and 2) the dependence of amplitude on the phase of 27-day rotational period of the Sun which favours the assumption on the quadrupole character of oscillations. It is pointed out that these facts, as well as the absence of oscillation waves in the telluric line observed simultaneously with the solar line, exclude the possibility of explaining the results as a statistical artifact. It has also been shown that the differential extinction effect produces an oscillation effect which is by an order of magnitude lower than the observed one. The following preliminary results are noted: a) the appearance of synchronous oscillations of the mean solar magnetic field of the brightness of the Sun and of the solar radio emission; b) the disappearance of the oscillations from time to time, possibly due to the effect of the supergranulation passage across the solar disk. The oscillations observed imply new important restrictions on the problem of the internal constitution of the Sun, and point to the possibility of non-radiative heat-transfer inside the Sun which might help the solution of the low neutrino flux problem
Study of the tensor correlation in oxygen isotopes using mean-field-type and shell model methods
International Nuclear Information System (INIS)
Sugimoto, Satoru
2007-01-01
The tensor force plays important roles in nuclear structure. Recently, we have developed a mean-field-type model which can treat the two-particle-two-hole correlation induced by the tensor force. We applied the model to sub-closed-shell oxygen isotopes and found that an sizable attractive energy comes from the tensor force. We also studied the tensor correlation in 16O using a shell model including two-particle-two-hole configurations. In this case, quite a large attractive energy is obtained for the correlation energy from the tensor force
International Nuclear Information System (INIS)
Antoci, S.; Mihich, L.
1997-01-01
Given the present status of the problem of the electromagnetic energy tensor in matter, there is perhaps use in recalling a forgotten argument given in 1923 by W. Gordon. Let us consider a material medium which is homogeneous and isotropic when observed in its rest frame. For such a medium, Gordon's argument allows to reduce the above-mentioned problem to an analogous one, defined in a general relativistic vacuum. For the latter problem the form of the Lagrangian is known already, hence the determination of the energy tensor is a straightforward matter. One just performs the Hamiltonian derivative of the Lagrangian chosen in this way with respect to the true metric g ik . Abraham's tensor is thus selected as the electromagnetic energy tensor for a medium which is homogeneous and isotropic in its rest frame
The cosmic-ray shock structure problem for relativistic shocks
Webb, G. M.
1985-01-01
The time asymptotic behaviour of a relativistic (parallel) shock wave significantly modified by the diffusive acceleration of cosmic-rays is investigated by means of relativistic hydrodynamical equations for both the cosmic-rays and thermal gas. The form of the shock structure equation and the dispersion relation for both long and short wavelength waves in the system are obtained. The dependence of the shock acceleration efficiency on the upstream fluid spped, long wavelength Mach number and the ratio N = P sub co/cP sub co+P sub go)(Psub co and P sub go are the upstream cosmic-ray and thermal gas pressures respectively) are studied.
Tensor rank of the tripartite state |W>xn
International Nuclear Information System (INIS)
Yu Nengkun; Guo Cheng; Duan Runyao; Chitambar, Eric
2010-01-01
Tensor rank refers to the number of product states needed to express a given multipartite quantum state. Its nonadditivity as an entanglement measure has recently been observed. In this Brief Report, we estimate the tensor rank of multiple copies of the tripartite state |W>=(1/√(3))(|100>+|010>+|001>). Both an upper bound and a lower bound of this rank are derived. In particular, it is proven that the rank of |W> x 2 is 7, thus resolving a previously open problem. Some implications of this result are discussed in terms of transformation rates between |W> xn and multiple copies of the state |GHZ>=(1/√(2))(|000>+|111>).
Tensor Network Wavefunctions for Topological Phases
Ware, Brayden Alexander
The combination of quantum effects and interactions in quantum many-body systems can result in exotic phases with fundamentally entangled ground state wavefunctions--topological phases. Topological phases come in two types, both of which will be studied in this thesis. In topologically ordered phases, the pattern of entanglement in the ground state wavefunction encodes the statistics of exotic emergent excitations, a universal indicator of a phase that is robust to all types of perturbations. In symmetry protected topological phases, the entanglement instead encodes a universal response of the system to symmetry defects, an indicator that is robust only to perturbations respecting the protecting symmetry. Finding and creating these phases in physical systems is a motivating challenge that tests all aspects--analytical, numerical, and experimental--of our understanding of the quantum many-body problem. Nearly three decades ago, the creation of simple ansatz wavefunctions--such as the Laughlin fractional quantum hall state, the AKLT state, and the resonating valence bond state--spurred analytical understanding of both the role of entanglement in topological physics and physical mechanisms by which it can arise. However, quantitative understanding of the relevant phase diagrams is still challenging. For this purpose, tensor networks provide a toolbox for systematically improving wavefunction ansatz while still capturing the relevant entanglement properties. In this thesis, we use the tools of entanglement and tensor networks to analyze ansatz states for several proposed new phases. In the first part, we study a featureless phase of bosons on the honeycomb lattice and argue that this phase can be topologically protected under any one of several distinct subsets of the crystalline lattice symmetries. We discuss methods of detecting such phases with entanglement and without. In the second part, we consider the problem of constructing fixed-point wavefunctions for
TENSOR DECOMPOSITIONS AND SPARSE LOG-LINEAR MODELS
Johndrow, James E.; Bhattacharya, Anirban; Dunson, David B.
2017-01-01
Contingency table analysis routinely relies on log-linear models, with latent structure analysis providing a common alternative. Latent structure models lead to a reduced rank tensor factorization of the probability mass function for multivariate categorical data, while log-linear models achieve dimensionality reduction through sparsity. Little is known about the relationship between these notions of dimensionality reduction in the two paradigms. We derive several results relating the support of a log-linear model to nonnegative ranks of the associated probability tensor. Motivated by these findings, we propose a new collapsed Tucker class of tensor decompositions, which bridge existing PARAFAC and Tucker decompositions, providing a more flexible framework for parsimoniously characterizing multivariate categorical data. Taking a Bayesian approach to inference, we illustrate empirical advantages of the new decompositions. PMID:29332971
Endomorphism Algebras of Tensor Powers of Modules for Quantum Groups
DEFF Research Database (Denmark)
Andersen, Therese Søby
We determine the ring structure of the endomorphism algebra of certain tensor powers of modules for the quantum group of sl2 in the case where the quantum parameter is allowed to be a root of unity. In this case there exists -- under a suitable localization of our ground ring -- a surjection from...... the group algebra of the braid group to the endomorphism algebra of any tensor power of the Weyl module with highest weight 2. We take a first step towards determining the kernel of this map by reformulating well-known results on the semisimplicity of the Birman-Murakami-Wenzl algebra in terms of the order...... of the quantum parameter. Before we arrive at these main results, we investigate the structure of the endomorphism algebra of the tensor square of any Weyl module....
Simultaneous tensor decomposition and completion using factor priors.
Chen, Yi-Lei; Hsu, Chiou-Ting; Liao, Hong-Yuan Mark
2014-03-01
The success of research on matrix completion is evident in a variety of real-world applications. Tensor completion, which is a high-order extension of matrix completion, has also generated a great deal of research interest in recent years. Given a tensor with incomplete entries, existing methods use either factorization or completion schemes to recover the missing parts. However, as the number of missing entries increases, factorization schemes may overfit the model because of incorrectly predefined ranks, while completion schemes may fail to interpret the model factors. In this paper, we introduce a novel concept: complete the missing entries and simultaneously capture the underlying model structure. To this end, we propose a method called simultaneous tensor decomposition and completion (STDC) that combines a rank minimization technique with Tucker model decomposition. Moreover, as the model structure is implicitly included in the Tucker model, we use factor priors, which are usually known a priori in real-world tensor objects, to characterize the underlying joint-manifold drawn from the model factors. By exploiting this auxiliary information, our method leverages two classic schemes and accurately estimates the model factors and missing entries. We conducted experiments to empirically verify the convergence of our algorithm on synthetic data and evaluate its effectiveness on various kinds of real-world data. The results demonstrate the efficacy of the proposed method and its potential usage in tensor-based applications. It also outperforms state-of-the-art methods on multilinear model analysis and visual data completion tasks.
Spectral Tensor-Train Decomposition
DEFF Research Database (Denmark)
Bigoni, Daniele; Engsig-Karup, Allan Peter; Marzouk, Youssef M.
2016-01-01
The accurate approximation of high-dimensional functions is an essential task in uncertainty quantification and many other fields. We propose a new function approximation scheme based on a spectral extension of the tensor-train (TT) decomposition. We first define a functional version of the TT...... adaptive Smolyak approach. The method is also used to approximate the solution of an elliptic PDE with random input data. The open source software and examples presented in this work are available online (http://pypi.python.org/pypi/TensorToolbox/)....
Confinement through tensor gauge fields
International Nuclear Information System (INIS)
Salam, A.; Strathdee, J.
1977-12-01
Using the 0(3,2)-symmetric de Sitter solution of Einstein's equation describing a strongly interacting tensor field it is shown that hadronic bags confining quarks can be represented as de Sitter ''micro-universes'' with radii given 1/R 2 =lambdak 2 /6. Here k 2 and lambda are the strong coupling and the ''cosmological'' constant which apear in the Einstein equation used. Surprisingly the energy spectrum for the two-body hadronic states is the same as that for a harmonic oscillator potential, though the wave functions are completely different. The Einstein equation can be extended to include colour for the tensor fields
Tensor product of quantum logics
Pulmannová, Sylvia
1985-01-01
A quantum logic is the couple (L,M) where L is an orthomodular σ-lattice and M is a strong set of states on L. The Jauch-Piron property in the σ-form is also supposed for any state of M. A ``tensor product'' of quantum logics is defined. This definition is compared with the definition of a free orthodistributive product of orthomodular σ-lattices. The existence and uniqueness of the tensor product in special cases of Hilbert space quantum logics and one quantum and one classical logic are studied.
Some special problems of steel reinforcement in nuclear structural engineering
International Nuclear Information System (INIS)
Bazant, B.; Smejkal, P.; Vetchy, J.
1986-01-01
A comparison is made of the mechanical and design characteristics of reinforcing steels for reinforced concrete structures of classes A-0 to A-IV under Czechoslovak State Standard CSN 73 1201 and Soviet standard SNiP II-21-75. Tests were performed to study changes in the values of the yield point, breaking strength, the tensile strength limit and the module of elasticity in selected Czechoslovak steels. The comparison showed that the steels behave in the same manner at high temperatures as Soviet steels of corresponding strength characteristics. Dynamic design strength of Czechoslovak materials also corresponds to values given in the Soviet standard. The technology and evaluation of welded joints equal for both Czechoslovak and Soviet steels. The manufacture was started of tempered wires with a high strength limit for prestressed wire reinforcement. All tests and comparisons showed that Czechoslovak reinforcing steels meet Soviet prescriptions, in some instances Czechoslovak standards are even more strict. (J.B.)
Entanglement and tensor product decomposition for two fermions
International Nuclear Information System (INIS)
Caban, P; Podlaski, K; Rembielinski, J; Smolinski, K A; Walczak, Z
2005-01-01
The problem of the choice of tensor product decomposition in a system of two fermions with the help of Bogoliubov transformations of creation and annihilation operators is discussed. The set of physical states of the composite system is restricted by the superselection rule forbidding the superposition of fermions and bosons. It is shown that the Wootters concurrence is not the proper entanglement measure in this case. The explicit formula for the entanglement of formation is found. This formula shows that the entanglement of a given state depends on the tensor product decomposition of a Hilbert space. It is shown that the set of separable states is narrower than in the two-qubit case. Moreover, there exist states which are separable with respect to all tensor product decompositions of the Hilbert space. (letter to the editor)
Frames, the Loewner order and eigendecomposition for morphological operators on tensor fields
van de Gronde, Jasper; Roerdink, Jos B. T. M.
2014-01-01
Rotation invariance is an important property for operators on tensor fields, but up to now, most methods for morphology on tensor fields had to either sacrifice rotation invariance, or do without the foundation of mathematical morphology: a lattice structure. Recently, we proposed a framework for
Becerra-Labra, Carlos; Gras-Martí, Albert; Martínez Torregrosa, Joaquín
2012-05-01
A model of teaching/learning is proposed based on a 'problem-based structure' of the contents of the course, in combination with a training in paper and pencil problem solving that emphasizes discussion and quantitative analysis, rather than formulae plug-in. The aim is to reverse the high failure and attrition rate among engineering undergraduates taking physics. A number of tests and questionnaires were administered to a group of students following a traditional lecture-based instruction, as well as to another group that was following an instruction scheme based on the proposed approach and the teaching materials developed ad hoc. The results show that students following the new method can develop scientific reasoning habits in problem-solving skills, and show gains in conceptual learning, attitudes and interests, and that the effects of this approach on learning are noticeable several months after the course is over.
The 'gravitating' tensor in the dualistic theory
International Nuclear Information System (INIS)
Mahanta, M.N.
1989-01-01
The exact microscopic system of Einstein-type field equations of the dualistic gravitation theory is investigated as well as an analysis of the modified energy-momentum tensor or so called 'gravitating' tensor is presented
Tensor calculus for physics a concise guide
Neuenschwander, Dwight E
2015-01-01
Understanding tensors is essential for any physics student dealing with phenomena where causes and effects have different directions. A horizontal electric field producing vertical polarization in dielectrics; an unbalanced car wheel wobbling in the vertical plane while spinning about a horizontal axis; an electrostatic field on Earth observed to be a magnetic field by orbiting astronauts—these are some situations where physicists employ tensors. But the true beauty of tensors lies in this fact: When coordinates are transformed from one system to another, tensors change according to the same rules as the coordinates. Tensors, therefore, allow for the convenience of coordinates while also transcending them. This makes tensors the gold standard for expressing physical relationships in physics and geometry. Undergraduate physics majors are typically introduced to tensors in special-case applications. For example, in a classical mechanics course, they meet the "inertia tensor," and in electricity and magnetism...
Mean template for tensor-based morphometry using deformation tensors.
Leporé, Natasha; Brun, Caroline; Pennec, Xavier; Chou, Yi-Yu; Lopez, Oscar L; Aizenstein, Howard J; Becker, James T; Toga, Arthur W; Thompson, Paul M
2007-01-01
Tensor-based morphometry (TBM) studies anatomical differences between brain images statistically, to identify regions that differ between groups, over time, or correlate with cognitive or clinical measures. Using a nonlinear registration algorithm, all images are mapped to a common space, and statistics are most commonly performed on the Jacobian determinant (local expansion factor) of the deformation fields. In, it was shown that the detection sensitivity of the standard TBM approach could be increased by using the full deformation tensors in a multivariate statistical analysis. Here we set out to improve the common space itself, by choosing the shape that minimizes a natural metric on the deformation tensors from that space to the population of control subjects. This method avoids statistical bias and should ease nonlinear registration of new subjects data to a template that is 'closest' to all subjects' anatomies. As deformation tensors are symmetric positive-definite matrices and do not form a vector space, all computations are performed in the log-Euclidean framework. The control brain B that is already the closest to 'average' is found. A gradient descent algorithm is then used to perform the minimization that iteratively deforms this template and obtains the mean shape. We apply our method to map the profile of anatomical differences in a dataset of 26 HIV/AIDS patients and 14 controls, via a log-Euclidean Hotelling's T2 test on the deformation tensors. These results are compared to the ones found using the 'best' control, B. Statistics on both shapes are evaluated using cumulative distribution functions of the p-values in maps of inter-group differences.
A new approach for applying residual dipolar couplings as restraints in structure elucidation
International Nuclear Information System (INIS)
Meiler, Jens; Blomberg, Niklas; Nilges, Michael; Griesinger, Christian
2000-01-01
Residual dipolar couplings are useful global structural restraints. The dipolar couplings define the orientation of a vector with respect to the alignment tensor. Although the size of the alignment tensor can be derived from the distribution of the experimental dipolar couplings, its orientation with respect to the coordinate system of the molecule is unknown at the beginning of structure determination. This causes convergence problems in the simulated annealing process. We therefore propose a protocol that translates dipolar couplings into intervector projection angles, which are independent of the orientation of the alignment tensor with respect to the molecule. These restraints can be used during the whole simulated annealing protocol
Directory of Open Access Journals (Sweden)
John A. DeRuntz Jr.
2005-01-01
Full Text Available The numerical solution of underwater shock fluid – structure interaction problems using boundary element/finite element techniques became tractable through the development of the family of Doubly Asymptotic Approximations (DAA. Practical implementation of the method has relied on the so-called augmentation of the DAA equations. The fluid and structural systems are respectively coupled by the structural acceleration vector in the surface normal direction on the right hand side of the DAA equations, and the total pressure applied to the structural equations on its right hand side. By formally solving for the acceleration vector from the structural system and substituting it into its place in the DAA equations, the augmentation introduces a term involving the inverse of the structural mass matrix. However there exist at least two important classes of problems in which the structural mass matrix is singular. This paper develops a method to carry out the augmentation for such problems using a generalized inverse technique.
Reciprocal mass tensor : a general form
International Nuclear Information System (INIS)
Roy, C.L.
1978-01-01
Using the results of earlier treatment of wave packets, a general form of reciprocal mass tensor has been obtained. The elements of this tensor are seen to be dependent on momentum as well as space coordinates of the particle under consideration. The conditions under which the tensor would reduce to the usual space-independent form, are discussed and the impact of the space-dependence of this tensor on the motion of Bloch electrons, is examined. (author)
A new deteriorated energy-momentum tensor
International Nuclear Information System (INIS)
Duff, M.J.
1982-01-01
The stress-tensor of a scalar field theory is not unique because of the possibility of adding an 'improvement term'. In supersymmetric field theories the stress-tensor will appear in a super-current multiplet along with the sypersymmetry current. The general question of the supercurrent multiplet for arbitrary deteriorated stress tensors and their relationship to supercurrent multiplets for models with gauge antisymmetric tensors is answered for various models of N = 1, 2 and 4 supersymmetry. (U.K.)
Akkerman, Erik M.
2010-01-01
Both in diffusion tensor imaging (DTI) and in generalized diffusion tensor imaging (GDTI) the relation between the diffusion tensor and the measured apparent diffusion coefficients is given by a tensorial equation, which needs to be inverted in order to solve the diffusion tensor. The traditional
DEFF Research Database (Denmark)
Quaglia, Alberto; Sarup, Bent; Sin, Gürkan
2013-01-01
structure for efficient formulation of enterprise-wide optimization problems is presented. Through the integration of the described data structure in our synthesis and design framework, the problem formulation workflow is automated in a software tool, reducing time and resources needed to formulate large......The formulation of Enterprise-Wide Optimization (EWO) problems as mixed integer nonlinear programming requires collecting, consolidating and systematizing large amount of data, coming from different sources and specific to different disciplines. In this manuscript, a generic and flexible data...... problems, while ensuring at the same time data consistency and quality at the application stage....
A Multi-Model Reduction Technique for Optimization of Coupled Structural-Acoustic Problems
DEFF Research Database (Denmark)
Creixell Mediante, Ester; Jensen, Jakob Søndergaard; Brunskog, Jonas
2016-01-01
Finite Element models of structural-acoustic coupled systems can become very large for complex structures with multiple connected parts. Optimization of the performance of the structure based on harmonic analysis of the system requires solving the coupled problem iteratively and for several frequ....... Several methods are compared in terms of accuracy and size of the reduced systems for optimization of simple models....
Zalaletdinov, R. M.
1998-04-01
The averaging problem in general relativity is briefly discussed. A new setting of the problem as that of macroscopic description of gravitation is proposed. A covariant space-time averaging procedure is described. The structure of the geometry of macroscopic space-time, which follows from averaging Cartan's structure equations, is described and the correlation tensors present in the theory are discussed. The macroscopic field equations (averaged Einstein's equations) derived in the framework of the approach are presented and their structure is analysed. The correspondence principle for macroscopic gravity is formulated and a definition of the stress-energy tensor for the macroscopic gravitational field is proposed. It is shown that the physical meaning of using Einstein's equations with a hydrodynamic stress-energy tensor in looking for cosmological models means neglecting all gravitational field correlations. The system of macroscopic gravity equations to be solved when the correlations are taken into consideration is given and described.
Weyl tensors for asymmetric complex curvatures
International Nuclear Information System (INIS)
Oliveira, C.G.
Considering a second rank Hermitian field tensor and a general Hermitian connection the associated complex curvature tensor is constructed. The Weyl tensor that corresponds to this complex curvature is determined. The formalism is applied to the Weyl unitary field theory and to the Moffat gravitational theory. (Author) [pt
Spherical Tensor Calculus for Local Adaptive Filtering
Reisert, Marco; Burkhardt, Hans
In 3D image processing tensors play an important role. While rank-1 and rank-2 tensors are well understood and commonly used, higher rank tensors are rare. This is probably due to their cumbersome rotation behavior which prevents a computationally efficient use. In this chapter we want to introduce the notion of a spherical tensor which is based on the irreducible representations of the 3D rotation group. In fact, any ordinary cartesian tensor can be decomposed into a sum of spherical tensors, while each spherical tensor has a quite simple rotation behavior. We introduce so called tensorial harmonics that provide an orthogonal basis for spherical tensor fields of any rank. It is just a generalization of the well known spherical harmonics. Additionally we propose a spherical derivative which connects spherical tensor fields of different degree by differentiation. Based on the proposed theory we present two applications. We propose an efficient algorithm for dense tensor voting in 3D, which makes use of tensorial harmonics decomposition of the tensor-valued voting field. In this way it is possible to perform tensor voting by linear-combinations of convolutions in an efficient way. Secondly, we propose an anisotropic smoothing filter that uses a local shape and orientation adaptive filter kernel which can be computed efficiently by the use spherical derivatives.
Directory of Open Access Journals (Sweden)
Hyeonseok S Jeong
Full Text Available In animal models of Parkinson's disease (PD, 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP is one of the most widely used agents that damages the nigrostriatal dopaminergic pathway. However, brain structural changes in response to MPTP remain unclear. This study aimed to investigate in vivo longitudinal changes in gray matter (GM volume and white matter (WM microstructure in primate models administered with MPTP. In six cynomolgus monkeys, high-resolution magnetic resonance imaging (MRI and diffusion tensor imaging (DTI scans were acquired 7 times over 32 weeks, and assessments of motor symptoms were conducted over 15 months, before and after the MPTP injection. Changes in GM volume and WM microstructure were estimated on a voxel-by-voxel basis. Mixed-effects regression models were used to examine the trajectories of these structural changes. GM volume initially increased after the MPTP injection and gradually decreased in the striatum, midbrain, and other dopaminergic areas. The cerebellar volume temporarily decreased and returned to its baseline level. The rate of midbrain volume increase was positively correlated with the increase rate of motor symptom severity (Spearman rho = 0.93, p = 0.008. Mean, axial, and radial diffusivity in the striatum and frontal areas demonstrated initial increases and subsequent decreases. The current multi-modal imaging study of MPTP-administered monkeys revealed widespread and dynamic structural changes not only in the nigrostriatal pathway but also in other cortical, subcortical, and cerebellar areas. Our findings may suggest the need to further investigate the roles of inflammatory reactions and glial activation as potential underlying mechanisms of these structural changes.
Jeong, Hyeonseok S; Lee, Sang-Rae; Kim, Jieun E; Lyoo, In Kyoon; Yoon, Sujung; Namgung, Eun; Chang, Kyu-Tae; Kim, Bom Sahn; Yang, Sejung; Im, Jooyeon J; Jeon, Saerom; Kang, Ilhyang; Ma, Jiyoung; Chung, Yong-An; Lim, Soo Mee
2018-01-01
In animal models of Parkinson's disease (PD), 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) is one of the most widely used agents that damages the nigrostriatal dopaminergic pathway. However, brain structural changes in response to MPTP remain unclear. This study aimed to investigate in vivo longitudinal changes in gray matter (GM) volume and white matter (WM) microstructure in primate models administered with MPTP. In six cynomolgus monkeys, high-resolution magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) scans were acquired 7 times over 32 weeks, and assessments of motor symptoms were conducted over 15 months, before and after the MPTP injection. Changes in GM volume and WM microstructure were estimated on a voxel-by-voxel basis. Mixed-effects regression models were used to examine the trajectories of these structural changes. GM volume initially increased after the MPTP injection and gradually decreased in the striatum, midbrain, and other dopaminergic areas. The cerebellar volume temporarily decreased and returned to its baseline level. The rate of midbrain volume increase was positively correlated with the increase rate of motor symptom severity (Spearman rho = 0.93, p = 0.008). Mean, axial, and radial diffusivity in the striatum and frontal areas demonstrated initial increases and subsequent decreases. The current multi-modal imaging study of MPTP-administered monkeys revealed widespread and dynamic structural changes not only in the nigrostriatal pathway but also in other cortical, subcortical, and cerebellar areas. Our findings may suggest the need to further investigate the roles of inflammatory reactions and glial activation as potential underlying mechanisms of these structural changes.
International Nuclear Information System (INIS)
Rao, J.R.; Tiwari, R.N.
1974-01-01
A theorem on obtaining exact solutions for a particular field structure from those of vacuum field equations of general theory as well as from some simpler solutions of unified theories is derived. With the help of this result the most general solution for the particular field structure is developed from the already known simpler solutions. The physical implications of this theorem in relation to some of the parallel work of other authors is discussed. (author)
DEFF Research Database (Denmark)
Stolpe, Mathias; Stidsen, Thomas K.
2005-01-01
In this paper we present a hierarchical optimization method for finding feasible true 0-1 solutions to finite element based topology design problems. The topology design problems are initially modeled as non-convex mixed 0-1 programs. The hierarchical optimization method is applied to the problem...... and then successively refined as needed. At each level of design mesh refinement, a neighborhood optimization method is used to solve the problem considered. The non-convex topology design problems are equivalently reformulated as convex all-quadratic mixed 0-1 programs. This reformulation enables the use of methods...... of minimizing the weight of a structure subject to displacement and local design-dependent stress constraints. The method iteratively solves a sequence of problems of increasing size of the same type as the original problem. The problems are defined on a design mesh which is initially coarse...
DEFF Research Database (Denmark)
Stolpe, Mathias; Stidsen, Thomas K.
2007-01-01
In this paper, we present a hierarchical optimization method for finding feasible true 0-1 solutions to finite-element-based topology design problems. The topology design problems are initially modelled as non-convex mixed 0-1 programs. The hierarchical optimization method is applied to the problem...... and then successively refined as needed. At each level of design mesh refinement, a neighbourhood optimization method is used to treat the problem considered. The non-convex topology design problems are equivalently reformulated as convex all-quadratic mixed 0-1 programs. This reformulation enables the use of methods...... of minimizing the weight of a structure subject to displacement and local design-dependent stress constraints. The method iteratively treats a sequence of problems of increasing size of the same type as the original problem. The problems are defined on a design mesh which is initially coarse...
Interactive Volume Rendering of Diffusion Tensor Data
Energy Technology Data Exchange (ETDEWEB)
Hlawitschka, Mario; Weber, Gunther; Anwander, Alfred; Carmichael, Owen; Hamann, Bernd; Scheuermann, Gerik
2007-03-30
As 3D volumetric images of the human body become an increasingly crucial source of information for the diagnosis and treatment of a broad variety of medical conditions, advanced techniques that allow clinicians to efficiently and clearly visualize volumetric images become increasingly important. Interaction has proven to be a key concept in analysis of medical images because static images of 3D data are prone to artifacts and misunderstanding of depth. Furthermore, fading out clinically irrelevant aspects of the image while preserving contextual anatomical landmarks helps medical doctors to focus on important parts of the images without becoming disoriented. Our goal was to develop a tool that unifies interactive manipulation and context preserving visualization of medical images with a special focus on diffusion tensor imaging (DTI) data. At each image voxel, DTI provides a 3 x 3 tensor whose entries represent the 3D statistical properties of water diffusion locally. Water motion that is preferential to specific spatial directions suggests structural organization of the underlying biological tissue; in particular, in the human brain, the naturally occuring diffusion of water in the axon portion of neurons is predominantly anisotropic along the longitudinal direction of the elongated, fiber-like axons [MMM+02]. This property has made DTI an emerging source of information about the structural integrity of axons and axonal connectivity between brain regions, both of which are thought to be disrupted in a broad range of medical disorders including multiple sclerosis, cerebrovascular disease, and autism [Mos02, FCI+01, JLH+99, BGKM+04, BJB+03].
Emergent symmetries in the canonical tensor model
Obster, Dennis; Sasakura, Naoki
2018-04-01
The canonical tensor model (CTM) is a tensor model proposing a classically and quantum mechanically consistent description of gravity, formulated as a first-class constraint system with structural similarities to the ADM formalism of general relativity. The classical CTM produces a general relativistic system in a formal continuum limit, the emergence of which should be explained by the quantum CTM. In this paper we study the symmetry properties of a wave function that exactly solves the quantum constraints of the CTM. We have found that it has strong peaks at configurations invariant under some Lie groups, as predicted by a mechanism described in our previous paper. A surprising result is the preference for configurations invariant not only under Lie groups with positive definite signature, but also with Lorentzian signature. Such symmetries could characterize the global structures of spacetimes, and our results are encouraging towards showing spacetime emergence in the CTM. To verify the asymptotic convergence of the wave function we have also analyzed the asymptotic behavior, which for the most part seems to be well under control.
A new Weyl-like tensor of geometric origin
Vishwakarma, Ram Gopal
2018-04-01
A set of new tensors of purely geometric origin have been investigated, which form a hierarchy. A tensor of a lower rank plays the role of the potential for the tensor of one rank higher. The tensors have interesting mathematical and physical properties. The highest rank tensor of the hierarchy possesses all the geometrical properties of the Weyl tensor.
Pre-service mathematics teachers’ ability in solving well-structured problem
Paradesa, R.
2018-01-01
This study aimed to describe the mathematical problem-solving ability of undergraduate students of mathematics education in solving the well-structured problem. The type of this study was qualitative descriptive. The subjects in this study were 100 undergraduate students of Mathematics Education at one of the private universities in Palembang city. The data in this study was collected through two test items with essay form. The results of this study showed that, from the first problem, only 8% students can solve it, but do not check back again to validate the process. Based on a scoring rubric that follows Polya strategy, their answer satisfied 2 4 2 0 patterns. But, from the second problem, 45% students satisfied it. This is because the second problem imitated from the example that was given in learning process. The average score of undergraduate students mathematical problem-solving ability in solving well-structured problems showed 56.00 with standard deviation was 13.22. It means that, from 0 - 100 scale, undergraduate students mathematical problem-solving ability can be categorized low. From this result, the conclusion was undergraduate students of mathematics education in Palembang still have a problem in solving mathematics well-structured problem.
Diffusion tensor MR microscopy of tissues with low diffusional anisotropy.
Bajd, Franci; Mattea, Carlos; Stapf, Siegfried; Sersa, Igor
2016-06-01
Diffusion tensor imaging exploits preferential diffusional motion of water molecules residing within tissue compartments for assessment of tissue structural anisotropy. However, instrumentation and post-processing errors play an important role in determination of diffusion tensor elements. In the study, several experimental factors affecting accuracy of diffusion tensor determination were analyzed. Effects of signal-to-noise ratio and configuration of the applied diffusion-sensitizing gradients on fractional anisotropy bias were analyzed by means of numerical simulations. In addition, diffusion tensor magnetic resonance microscopy experiments were performed on a tap water phantom and bovine articular cartilage-on-bone samples to verify the simulation results. In both, the simulations and the experiments, the multivariate linear regression of the diffusion-tensor analysis yielded overestimated fractional anisotropy with low SNRs and with low numbers of applied diffusion-sensitizing gradients. An increase of the apparent fractional anisotropy due to unfavorable experimental conditions can be overcome by applying a larger number of diffusion sensitizing gradients with small values of the condition number of the transformation matrix. This is in particular relevant in magnetic resonance microscopy, where imaging gradients are high and the signal-to-noise ratio is low.
Nonperturbative loop quantization of scalar-tensor theories of gravity
International Nuclear Information System (INIS)
Zhang Xiangdong; Ma Yongge
2011-01-01
The Hamiltonian formulation of scalar-tensor theories of gravity is derived from their Lagrangian formulation by Hamiltonian analysis. The Hamiltonian formalism marks off two sectors of the theories by the coupling parameter ω(φ). In the sector of ω(φ)=-(3/2), the feasible theories are restricted and a new primary constraint generating conformal transformations of spacetime is obtained, while in the other sector of ω(φ)≠-(3/2), the canonical structure and constraint algebra of the theories are similar to those of general relativity coupled with a scalar field. By canonical transformations, we further obtain the connection-dynamical formalism of the scalar-tensor theories with real su(2) connections as configuration variables in both sectors. This formalism enables us to extend the scheme of nonperturbative loop quantum gravity to the scalar-tensor theories. The quantum kinematical framework for the scalar-tensor theories is rigorously constructed. Both the Hamiltonian constraint operator and master constraint operator are well defined and proposed to represent quantum dynamics. Thus the loop quantum gravity method is also valid for general scalar-tensor theories.
Micromechanics based framework with second-order damage tensors
Desmorat, R.; Desmorat, B.; Olive, M.; Kolev, B.
2018-05-01
The harmonic product of tensors---leading to the concept of harmonic factorization---has been defined in a previous work (Olive et al, 2017). In the practical case of 3D crack density measurements on thin or thick walled structures, this mathematical tool allows us to factorize the harmonic (irreducible) part of the fourth-order damage tensor as an harmonic square: an exact harmonic square in 2D, an harmonic square over the set of so-called mechanically accessible directions for measurements in the 3D case. The corresponding micro-mechanics framework based on second---instead of fourth---order damage tensors is derived. An illustrating example is provided showing how the proposed framework allows for the modeling of the so-called hydrostatic sensitivity up to high damage levels.
Moment tensor decompositions revisited
Czech Academy of Sciences Publication Activity Database
Vavryčuk, Václav
2015-01-01
Roč. 19, č. 1 (2015), s. 231-252 ISSN 1383-4649 R&D Projects: GA ČR(CZ) GAP210/12/1491 Institutional support: RVO:67985530 Keywords : dynamics and mechanics of faulting * earthquake source observations * seismic anisotropy * theoretical seismology Subject RIV: DC - Siesmology, Volcanology, Earth Structure Impact factor: 1.550, year: 2015
Comparison of Magnetic Susceptibility Tensor and Diffusion Tensor of the Brain.
Li, Wei; Liu, Chunlei
2013-10-01
Susceptibility tensor imaging (STI) provides a novel approach for noninvasive assessment of the white matter pathways of the brain. Using mouse brain ex vivo , we compared STI with diffusion tensor imaging (DTI), in terms of tensor values, principal tensor values, anisotropy values, and tensor orientations. Despite the completely different biophysical underpinnings, magnetic susceptibility tensors and diffusion tensors show many similarities in the tensor and principal tensor images, for example, the tensors perpendicular to the fiber direction have the highest gray-white matter contrast, and the largest principal tensor is along the fiber direction. Comparison to DTI fractional anisotropy, the susceptibility anisotropy provides much higher sensitivity to the chemical composition of the white matter, especially myelin. The high sensitivity can be further enhanced with the perfusion of ProHance, a gadolinium-based contrast agent. Regarding the tensor orientations, the direction of the largest principal susceptibility tensor agrees with that of diffusion tensors in major white matter fiber bundles. The STI fiber tractography can reconstruct the fiber pathways for the whole corpus callosum and for white matter fiber bundles that are in close contact but in different orientations. There are some differences between susceptibility and diffusion tensor orientations, which are likely due to the limitations in the current STI reconstruction. With the development of more accurate reconstruction methods, STI holds the promise for probing the white matter micro-architectures with more anatomical details and higher chemical sensitivity.
Rosetta Structure Prediction as a Tool for Solving Difficult Molecular Replacement Problems.
DiMaio, Frank
2017-01-01
Molecular replacement (MR), a method for solving the crystallographic phase problem using phases derived from a model of the target structure, has proven extremely valuable, accounting for the vast majority of structures solved by X-ray crystallography. However, when the resolution of data is low, or the starting model is very dissimilar to the target protein, solving structures via molecular replacement may be very challenging. In recent years, protein structure prediction methodology has emerged as a powerful tool in model building and model refinement for difficult molecular replacement problems. This chapter describes some of the tools available in Rosetta for model building and model refinement specifically geared toward difficult molecular replacement cases.
The Physical Interpretation of the Lanczos Tensor
Roberts, Mark D.
1999-01-01
The field equations of general relativity can be written as first order differential equations in the Weyl tensor, the Weyl tensor in turn can be written as a first order differential equation in a three index tensor called the Lanczos tensor. The Lanczos tensor plays a similar role in general relativity to that of the vector potential in electro-magnetic theory. The Aharonov-Bohm effect shows that when quantum mechanics is applied to electro-magnetic theory the vector potential is dynamicall...
International Nuclear Information System (INIS)
Mukashev, K.M.; Sarsenbinov, Sh. Sh.
2000-01-01
Fundamental problems and nature of electron-positron annihilation phenomenon, problems of its application in studies of condensed matter, development of various methodic based on this phenomenon for structural studies in solids, mathematical aspects of experimental deta decoding and program means for computer data processing are discussed. (author)
THE DECISION OF FORM FOR DIFFRACTIVE STRUCTURES IN THE PROBLEM OF SCATTERING OF RADIO WAVES.
Directory of Open Access Journals (Sweden)
A. P. Preobrazhensky
2017-02-01
Full Text Available This paper considers the problem of scattering of electromagnetic waves in different diffraction structures. The solution of the scattering problem is based on the method of integral equations. On diagrams of backscattering at various frequencies of the incident wave, the decision about the form of the object is carried out.
Structured Parenting of Toddlers at High versus Low Genetic Risk: Two Pathways to Child Problems
Leve, Leslie D.; Harold, Gordon T.; Ge, Xiaojia; Neiderhiser, Jenae M.; Shaw, Daniel; Scaramella, Laura V.; Reiss, David
2009-01-01
Objective: Little is known about how parenting might offset genetic risk to prevent the onset of child problems during toddlerhood. We used a prospective adoption design to separate genetic and environmental influences and test whether associations between structured parenting and toddler behavior problems were conditioned by genetic risk for…
Thai, Khanh-Phuong; Son, Ji Y.; Hoffman, Jessica; Devers, Christopher; Kellman, Philip J.
2014-01-01
Mathematics is the study of structure but students think of math as solving problems according to rules. Students can learn procedures, but they often have trouble knowing when to apply learned procedures, especially to problems unlike those they trained with. In this study, the authors rely on the psychological mechanism of perceptual learning…
Structured parenting of toddlers at high versus low genetic risk: two pathways to child problems.
Leve, Leslie D; Harold, Gordon T; Ge, Xiaojia; Neiderhiser, Jenae M; Shaw, Daniel; Scaramella, Laura V; Reiss, David
2009-11-01
Little is known about how parenting might offset genetic risk to prevent the onset of child problems during toddlerhood. We used a prospective adoption design to separate genetic and environmental influences and test whether associations between structured parenting and toddler behavior problems were conditioned by genetic risk for psychopathology. The sample included 290 linked sets of adoptive families and birth mothers and 95 linked birth fathers. Genetic risk was assessed via birth mother and birth father psychopathology (anxiety, depression, antisociality, and drug use). Structured parenting was assessed via microsocial coding of adoptive mothers' behavior during a cleanup task. Toddler behavior problems were assessed with the Child Behavior Checklist. Controlling for temperamental risk at 9 months, there was an interaction between birth mother psychopathology and adoptive mothers' parenting on toddler behavior problems at 18 months. The interaction indicated two pathways to child problems: structured parenting was beneficial for toddlers at high genetic risk but was related to behavior problems for toddlers at low genetic risk. This crossover interaction pattern was replicated with birth father psychopathology as the index of genetic risk. The effects of structured parenting on toddler behavior problems varied as a function of genetic risk. Children at genetic risk might benefit from parenting interventions during toddlerhood that enhance structured parenting.
Holographic duality from random tensor networks
Energy Technology Data Exchange (ETDEWEB)
Hayden, Patrick; Nezami, Sepehr; Qi, Xiao-Liang; Thomas, Nathaniel; Walter, Michael; Yang, Zhao [Stanford Institute for Theoretical Physics, Department of Physics, Stanford University,382 Via Pueblo, Stanford, CA 94305 (United States)
2016-11-02
Tensor networks provide a natural framework for exploring holographic duality because they obey entanglement area laws. They have been used to construct explicit toy models realizing many of the interesting structural features of the AdS/CFT correspondence, including the non-uniqueness of bulk operator reconstruction in the boundary theory. In this article, we explore the holographic properties of networks of random tensors. We find that our models naturally incorporate many features that are analogous to those of the AdS/CFT correspondence. When the bond dimension of the tensors is large, we show that the entanglement entropy of all boundary regions, whether connected or not, obey the Ryu-Takayanagi entropy formula, a fact closely related to known properties of the multipartite entanglement of assistance. We also discuss the behavior of Rényi entropies in our models and contrast it with AdS/CFT. Moreover, we find that each boundary region faithfully encodes the physics of the entire bulk entanglement wedge, i.e., the bulk region enclosed by the boundary region and the minimal surface. Our method is to interpret the average over random tensors as the partition function of a classical ferromagnetic Ising model, so that the minimal surfaces of Ryu-Takayanagi appear as domain walls. Upon including the analog of a bulk field, we find that our model reproduces the expected corrections to the Ryu-Takayanagi formula: the bulk minimal surface is displaced and the entropy is augmented by the entanglement of the bulk field. Increasing the entanglement of the bulk field ultimately changes the minimal surface behavior topologically, in a way similar to the effect of creating a black hole. Extrapolating bulk correlation functions to the boundary permits the calculation of the scaling dimensions of boundary operators, which exhibit a large gap between a small number of low-dimension operators and the rest. While we are primarily motivated by the AdS/CFT duality, the main
Antisymmetric tensor generalizations of affine vector fields.
Houri, Tsuyoshi; Morisawa, Yoshiyuki; Tomoda, Kentaro
2016-02-01
Tensor generalizations of affine vector fields called symmetric and antisymmetric affine tensor fields are discussed as symmetry of spacetimes. We review the properties of the symmetric ones, which have been studied in earlier works, and investigate the properties of the antisymmetric ones, which are the main theme in this paper. It is shown that antisymmetric affine tensor fields are closely related to one-lower-rank antisymmetric tensor fields which are parallelly transported along geodesics. It is also shown that the number of linear independent rank- p antisymmetric affine tensor fields in n -dimensions is bounded by ( n + 1)!/ p !( n - p )!. We also derive the integrability conditions for antisymmetric affine tensor fields. Using the integrability conditions, we discuss the existence of antisymmetric affine tensor fields on various spacetimes.
Matrix and Tensor Completion on a Human Activity Recognition Framework.
Savvaki, Sofia; Tsagkatakis, Grigorios; Panousopoulou, Athanasia; Tsakalides, Panagiotis
2017-11-01
Sensor-based activity recognition is encountered in innumerable applications of the arena of pervasive healthcare and plays a crucial role in biomedical research. Nonetheless, the frequent situation of unobserved measurements impairs the ability of machine learning algorithms to efficiently extract context from raw streams of data. In this paper, we study the problem of accurate estimation of missing multimodal inertial data and we propose a classification framework that considers the reconstruction of subsampled data during the test phase. We introduce the concept of forming the available data streams into low-rank two-dimensional (2-D) and 3-D Hankel structures, and we exploit data redundancies using sophisticated imputation techniques, namely matrix and tensor completion. Moreover, we examine the impact of reconstruction on the classification performance by experimenting with several state-of-the-art classifiers. The system is evaluated with respect to different data structuring scenarios, the volume of data available for reconstruction, and various levels of missing values per device. Finally, the tradeoff between subsampling accuracy and energy conservation in wearable platforms is examined. Our analysis relies on two public datasets containing inertial data, which extend to numerous activities, multiple sensing parameters, and body locations. The results highlight that robust classification accuracy can be achieved through recovery, even for extremely subsampled data streams.
Energy Technology Data Exchange (ETDEWEB)
Bryant, Pamela L.; Harwell, Chris; Mrse, Anthony A.; Emery, Earl F.; Gan, Zhedong; Caldwell, Tod; Reyes, Arneil P.; Kuhns, Philip; Hoyt, David W.; Simeral, Larry S.; Hall, Randall W.; Butler, Leslie G.
2001-11-07
Aminato and propanolato aluminum clusters with 3-, 4-, and 6-coordinate aluminum sites are studied with three 27Al NMR techniques optimized for large 27Al Quadrupole coupling constants: field-swept, frequency-stepped, and high-field MAS NMR. The 27Al quadrupole coupling constants and asymmetry parameters of molecular species, both experimental and derived from ab initio molecular orbital calculations, are correlated with structure.
Quantum chaos and holographic tensor models
Energy Technology Data Exchange (ETDEWEB)
Krishnan, Chethan [Center for High Energy Physics, Indian Institute of Science,Bangalore 560012 (India); Sanyal, Sambuddha [International Center for Theoretical Sciences, Tata Institute of Fundamental Research,Bangalore 560089 (India); Subramanian, P.N. Bala [Center for High Energy Physics, Indian Institute of Science,Bangalore 560012 (India)
2017-03-10
A class of tensor models were recently outlined as potentially calculable examples of holography: their perturbative large-N behavior is similar to the Sachdev-Ye-Kitaev (SYK) model, but they are fully quantum mechanical (in the sense that there is no quenched disorder averaging). These facts make them intriguing tentative models for quantum black holes. In this note, we explicitly diagonalize the simplest non-trivial Gurau-Witten tensor model and study its spectral and late-time properties. We find parallels to (a single sample of) SYK where some of these features were recently attributed to random matrix behavior and quantum chaos. In particular, the spectral form factor exhibits a dip-ramp-plateau structure after a running time average, in qualitative agreement with SYK. But we also observe that even though the spectrum has a unique ground state, it has a huge (quasi-?)degeneracy of intermediate energy states, not seen in SYK. If one ignores the delta function due to the degeneracies however, there is level repulsion in the unfolded spacing distribution hinting chaos. Furthermore, there are gaps in the spectrum. The system also has a spectral mirror symmetry which we trace back to the presence of a unitary operator with which the Hamiltonian anticommutes. We use it to argue that to the extent that the model exhibits random matrix behavior, it is controlled not by the Dyson ensembles, but by the BDI (chiral orthogonal) class in the Altland-Zirnbauer classification.
Quantum chaos and holographic tensor models
International Nuclear Information System (INIS)
Krishnan, Chethan; Sanyal, Sambuddha; Subramanian, P.N. Bala
2017-01-01
A class of tensor models were recently outlined as potentially calculable examples of holography: their perturbative large-N behavior is similar to the Sachdev-Ye-Kitaev (SYK) model, but they are fully quantum mechanical (in the sense that there is no quenched disorder averaging). These facts make them intriguing tentative models for quantum black holes. In this note, we explicitly diagonalize the simplest non-trivial Gurau-Witten tensor model and study its spectral and late-time properties. We find parallels to (a single sample of) SYK where some of these features were recently attributed to random matrix behavior and quantum chaos. In particular, the spectral form factor exhibits a dip-ramp-plateau structure after a running time average, in qualitative agreement with SYK. But we also observe that even though the spectrum has a unique ground state, it has a huge (quasi-?)degeneracy of intermediate energy states, not seen in SYK. If one ignores the delta function due to the degeneracies however, there is level repulsion in the unfolded spacing distribution hinting chaos. Furthermore, there are gaps in the spectrum. The system also has a spectral mirror symmetry which we trace back to the presence of a unitary operator with which the Hamiltonian anticommutes. We use it to argue that to the extent that the model exhibits random matrix behavior, it is controlled not by the Dyson ensembles, but by the BDI (chiral orthogonal) class in the Altland-Zirnbauer classification.
Image denoising using non linear diffusion tensors
International Nuclear Information System (INIS)
Benzarti, F.; Amiri, H.
2011-01-01
Image denoising is an important pre-processing step for many image analysis and computer vision system. It refers to the task of recovering a good estimate of the true image from a degraded observation without altering and changing useful structure in the image such as discontinuities and edges. In this paper, we propose a new approach for image denoising based on the combination of two non linear diffusion tensors. One allows diffusion along the orientation of greatest coherences, while the other allows diffusion along orthogonal directions. The idea is to track perfectly the local geometry of the degraded image and applying anisotropic diffusion mainly along the preferred structure direction. To illustrate the effective performance of our model, we present some experimental results on a test and real photographic color images.
Poisson-Jacobi reduction of homogeneous tensors
International Nuclear Information System (INIS)
Grabowski, J; Iglesias, D; Marrero, J C; Padron, E; Urbanski, P
2004-01-01
The notion of homogeneous tensors is discussed. We show that there is a one-to-one correspondence between multivector fields on a manifold M, homogeneous with respect to a vector field Δ on M, and first-order polydifferential operators on a closed submanifold N of codimension 1 such that Δ is transversal to N. This correspondence relates the Schouten-Nijenhuis bracket of multivector fields on M to the Schouten-Jacobi bracket of first-order polydifferential operators on N and generalizes the Poissonization of Jacobi manifolds. Actually, it can be viewed as a super-Poissonization. This procedure of passing from a homogeneous multivector field to a first-order polydifferential operator can also be understood as a sort of reduction; in the standard case-a half of a Poisson reduction. A dual version of the above correspondence yields in particular the correspondence between Δ-homogeneous symplectic structures on M and contact structures on N
Extended vector-tensor theories
Energy Technology Data Exchange (ETDEWEB)
Kimura, Rampei; Naruko, Atsushi; Yoshida, Daisuke, E-mail: rampei@th.phys.titech.ac.jp, E-mail: naruko@th.phys.titech.ac.jp, E-mail: yoshida@th.phys.titech.ac.jp [Department of Physics, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, Tokyo 152-8551 (Japan)
2017-01-01
Recently, several extensions of massive vector theory in curved space-time have been proposed in many literatures. In this paper, we consider the most general vector-tensor theories that contain up to two derivatives with respect to metric and vector field. By imposing a degeneracy condition of the Lagrangian in the context of ADM decomposition of space-time to eliminate an unwanted mode, we construct a new class of massive vector theories where five degrees of freedom can propagate, corresponding to three for massive vector modes and two for massless tensor modes. We find that the generalized Proca and the beyond generalized Proca theories up to the quartic Lagrangian, which should be included in this formulation, are degenerate theories even in curved space-time. Finally, introducing new metric and vector field transformations, we investigate the properties of thus obtained theories under such transformations.
Scalar-tensor linear inflation
Energy Technology Data Exchange (ETDEWEB)
Artymowski, Michał [Institute of Physics, Jagiellonian University, Łojasiewicza 11, 30-348 Kraków (Poland); Racioppi, Antonio, E-mail: Michal.Artymowski@uj.edu.pl, E-mail: Antonio.Racioppi@kbfi.ee [National Institute of Chemical Physics and Biophysics, Rävala 10, 10143 Tallinn (Estonia)
2017-04-01
We investigate two approaches to non-minimally coupled gravity theories which present linear inflation as attractor solution: a) the scalar-tensor theory approach, where we look for a scalar-tensor theory that would restore results of linear inflation in the strong coupling limit for a non-minimal coupling to gravity of the form of f (φ) R /2; b) the particle physics approach, where we motivate the form of the Jordan frame potential by loop corrections to the inflaton field. In both cases the Jordan frame potentials are modifications of the induced gravity inflationary scenario, but instead of the Starobinsky attractor they lead to linear inflation in the strong coupling limit.
The Role of Content Knowledge in Ill-Structured Problem Solving for High School Physics Students
Milbourne, Jeff; Wiebe, Eric
2018-02-01
While Physics Education Research has a rich tradition of problem-solving scholarship, most of the work has focused on more traditional, well-defined problems. Less work has been done with ill-structured problems, problems that are better aligned with the engineering and design-based scenarios promoted by the Next Generation Science Standards. This study explored the relationship between physics content knowledge and ill-structured problem solving for two groups of high school students with different levels of content knowledge. Both groups of students completed an ill-structured problem set, using a talk-aloud procedure to narrate their thought process as they worked. Analysis of the data focused on identifying students' solution pathways, as well as the obstacles that prevented them from reaching "reasonable" solutions. Students with more content knowledge were more successful reaching reasonable solutions for each of the problems, experiencing fewer obstacles. These students also employed a greater variety of solution pathways than those with less content knowledge. Results suggest that a student's solution pathway choice may depend on how she perceives the problem.
Hidese, Shinsuke; Ota, Miho; Matsuo, Junko; Ishida, Ikki; Hiraishi, Moeko; Teraishi, Toshiya; Hattori, Kotaro; Kunugi, Hiroshi
2017-12-01
The Brief Assessment of Cognition in Schizophrenia (BACS) is a concise tool designed to evaluate cognitive deficits in schizophrenia. We examined the possible association between BACS scores and whole-brain structure, as observed using magnetic resonance imaging with a relatively large sample. The study sample comprised 116 patients with schizophrenia (mean age, 39.3 ± 11.1 years; 66 men) and 118 healthy controls (HC; mean age, 40.0 ± 13.6 years; 58 men) who completed the Japanese version of the BACS (BACS-J). All participants were of Japanese ethnicity. The magnetic resonance imaging volume and diffusion tensor imaging data were processed with voxel-based morphometry and tract-based spatial statistics, respectively. There were significant reductions in the regional gray matter volumes and white matter fractional anisotropy values in patients with schizophrenia compared to HC. For the gray matter areas, the working memory score had a significant positive correlation with the anterior cingulate and medial frontal cortices volumes in the patients. For the white matter areas, the motor speed score had a significant positive correlation with fractional anisotropy values in the corpus callosum, internal capsule, superior corona radiata, and superior longitudinal fasciculus in the patients. However, there was no significant correlation among either the gray or white matter areas in the HC. Our results suggest that among the BACS-J measures, the working memory and motor speed scores are associated with several structural alterations in the brains of patients with schizophrenia. © 2017 The Authors. Psychiatry and Clinical Neurosciences © 2017 Japanese Society of Psychiatry and Neurology.
Opportunity Structure for Gambling and Problem Gambling among Employees in the Transport Industry
Revheim, Tevje; Buvik, Kristin
2009-01-01
Working conditions for employees in the transport sector might present an opportunity structure for gambling by providing access to gambling during the workday. This study investigates connections between opportunity structure, gambling during the workday, and gambling problems among employees in the transport sector. Data has been collected from…
Chao, Lo-Hsin; Tsai, Meng-Che; Liang, Ya-Lun; Strong, Carol; Lin, Chung-Ying
2018-01-01
Childhood adversity (CA) is associated with problem behaviors in adolescence, but the mediators, that is, those factors that help build resilience and prevent some children who experience CA from engaging in problem behaviors, await more exploration, including social integration. The aim of this study was to identify the association between CA and adolescent problem behaviors, and to further examine the mediating role of social integration distinctly as psychological and structural integration. Data used were from the Taiwan Education Panel Survey, a core panel of 4,261 students (age 13) surveyed in 2001 and followed for three more waves until age 18. For psychological integration, an average score was calculated to represent adolescents' feelings about their school. Structural integration was constructed using several items about adolescents' school and extracurricular activities. We used structural equation modeling with the diagonally weighted least squares method to examine the effect of CA on the primary outcome: adolescent problem behaviors via social integration. The hypothesized structural equation model specifying the path from CA to adolescent problem behavior had good fit. Respondents with one CA were indirectly linked to problem behaviors via psychological but not structural integration (e.g. the level of participation in school and non-school activities). On mediation analysis, psychological integration significantly mediated the paths from one CA to all six problem behaviors (all P integration; two or more CA were not associated with significant paths to problem behaviors. The contribution of social integration is crucial to an adolescent's development from CA to problem behaviors. To form supportive social relationships to achieve better health, we suggest that those adolescents who have been exposed to CA should be helped to join more teams and take part in more activities, thereby increasing their opportunities for social interaction, and improving
Directory of Open Access Journals (Sweden)
Eloy Guerrero Seide
2004-11-01
Full Text Available This article summarizes the results obtained in an exploratory and comparative study of two ways of structuring the mathematical content of a B.S. program in Agronomic Engineering at Guantanamo University, Cuba: the formal systematization of the presentation of the knowledge, and an organization through problems. The sign test is used in the proof of the hypothesis. In a preliminary form, at least, it was demonstrated that the variant of systemic structuring of knowledge through problems is more conducive to the efficiency of the knowledge acquired by students than the structure presented by means of the logical exposition of achieved knowledge.
International Nuclear Information System (INIS)
Milton, Graeme W
2010-01-01
We show that any pair of real symmetric tensors ε and μ can be realized as the effective electric permittivity and effective magnetic permeability of a metamaterial at a given fixed frequency. The construction starts with two extremely low-loss metamaterials, with arbitrarily small microstructure, whose existence is ensured by the work of Bouchitte and Bourel and Bouchitte and Schweizer: one having, at the given frequency, a permittivity tensor with exactly one negative eigenvalue, and a positive permeability tensor; and the other having a positive permittivity tensor, and a permeability tensor having exactly one negative eigenvalue. To achieve the desired effective properties, these materials are laminated together in a hierarchical multiple rank laminate structure, with widely separated length scales, and varying directions of lamination, but with the largest length scale still much shorter than the wavelengths and attenuation lengths in the macroscopic effective medium.
DeRuntz Jr., John A.
2005-01-01
The numerical solution of underwater shock fluid – structure interaction problems using boundary element/finite element techniques became tractable through the development of the family of Doubly Asymptotic Approximations (DAA). Practical implementation of the method has relied on the so-called augmentation of the DAA equations. The fluid and structural systems are respectively coupled by the structural acceleration vector in the surface normal direction on the right hand side of the DAA equa...
Sparse alignment for robust tensor learning.
Lai, Zhihui; Wong, Wai Keung; Xu, Yong; Zhao, Cairong; Sun, Mingming
2014-10-01
Multilinear/tensor extensions of manifold learning based algorithms have been widely used in computer vision and pattern recognition. This paper first provides a systematic analysis of the multilinear extensions for the most popular methods by using alignment techniques, thereby obtaining a general tensor alignment framework. From this framework, it is easy to show that the manifold learning based tensor learning methods are intrinsically different from the alignment techniques. Based on the alignment framework, a robust tensor learning method called sparse tensor alignment (STA) is then proposed for unsupervised tensor feature extraction. Different from the existing tensor learning methods, L1- and L2-norms are introduced to enhance the robustness in the alignment step of the STA. The advantage of the proposed technique is that the difficulty in selecting the size of the local neighborhood can be avoided in the manifold learning based tensor feature extraction algorithms. Although STA is an unsupervised learning method, the sparsity encodes the discriminative information in the alignment step and provides the robustness of STA. Extensive experiments on the well-known image databases as well as action and hand gesture databases by encoding object images as tensors demonstrate that the proposed STA algorithm gives the most competitive performance when compared with the tensor-based unsupervised learning methods.
Shape anisotropy: tensor distance to anisotropy measure
Weldeselassie, Yonas T.; El-Hilo, Saba; Atkins, M. S.
2011-03-01
Fractional anisotropy, defined as the distance of a diffusion tensor from its closest isotropic tensor, has been extensively studied as quantitative anisotropy measure for diffusion tensor magnetic resonance images (DT-MRI). It has been used to reveal the white matter profile of brain images, as guiding feature for seeding and stopping in fiber tractography and for the diagnosis and assessment of degenerative brain diseases. Despite its extensive use in DT-MRI community, however, not much attention has been given to the mathematical correctness of its derivation from diffusion tensors which is achieved using Euclidean dot product in 9D space. But, recent progress in DT-MRI has shown that the space of diffusion tensors does not form a Euclidean vector space and thus Euclidean dot product is not appropriate for tensors. In this paper, we propose a novel and robust rotationally invariant diffusion anisotropy measure derived using the recently proposed Log-Euclidean and J-divergence tensor distance measures. An interesting finding of our work is that given a diffusion tensor, its closest isotropic tensor is different for different tensor distance metrics used. We demonstrate qualitatively that our new anisotropy measure reveals superior white matter profile of DT-MR brain images and analytically show that it has a higher signal to noise ratio than fractional anisotropy.
Transposes, L-Eigenvalues and Invariants of Third Order Tensors
Qi, Liqun
2017-01-01
Third order tensors have wide applications in mechanics, physics and engineering. The most famous and useful third order tensor is the piezoelectric tensor, which plays a key role in the piezoelectric effect, first discovered by Curie brothers. On the other hand, the Levi-Civita tensor is famous in tensor calculus. In this paper, we study third order tensors and (third order) hypermatrices systematically, by regarding a third order tensor as a linear operator which transforms a second order t...
How (not) to use the Palatini formulation of scalar-tensor gravity
International Nuclear Information System (INIS)
Iglesias, Alberto; Kaloper, Nemanja; Park, Minjoon; Padilla, Antonio
2007-01-01
We revisit the problem of defining nonminimal gravity in the first order formalism. Specializing to scalar-tensor theories, which may be disguised as ''higher-derivative'' models with the gravitational Lagrangians that depend only on the Ricci scalar, we show how to recast these theories as Palatini-like gravities. The correct formulation utilizes the Lagrange multiplier method, which preserves the canonical structure of the theory, and yields the conventional metric scalar-tensor gravity. We explain the discrepancies between the naieve Palatini and the Lagrange multiplier approach, showing that the naieve Palatini approach really swaps the theory for another. The differences disappear only in the limit of ordinary general relativity, where an accidental redundancy ensures that the naieve Palatini approach works there. We outline the correct decoupling limits and the strong coupling regimes. As a corollary we find that the so-called ''modified source gravity'' models suffer from strong coupling problems at very low scales, and hence cannot be a realistic approximation of our universe. We also comment on a method to decouple the extra scalar using the chameleon mechanism
Tensor categories and the mathematics of rational and logarithmic conformal field theory
International Nuclear Information System (INIS)
Huang, Yi-Zhi; Lepowsky, James
2013-01-01
We review the construction of braided tensor categories and modular tensor categories from representations of vertex operator algebras, which correspond to chiral algebras in physics. The extensive and general theory underlying this construction also establishes the operator product expansion for intertwining operators, which correspond to chiral vertex operators, and more generally, it establishes the logarithmic operator product expansion for logarithmic intertwining operators. We review the main ideas in the construction of the tensor product bifunctors and the associativity isomorphisms. For rational and logarithmic conformal field theories, we review the precise results that yield braided tensor categories, and in the rational case, modular tensor categories as well. In the case of rational conformal field theory, we also briefly discuss the construction of the modular tensor categories for the Wess–Zumino–Novikov–Witten models and, especially, a recent discovery concerning the proof of the fundamental rigidity property of the modular tensor categories for this important special case. In the case of logarithmic conformal field theory, we mention suitable categories of modules for the triplet W-algebras as an example of the applications of our general construction of the braided tensor category structure. (review)
Directory of Open Access Journals (Sweden)
Milev Jordan
2016-01-01
Full Text Available The main purpose of the paper is to present practical application of Eurocodes in the field of RC structures design. The selected examples represent the main problems in practical application of Eurocodes for seismic analysis and design of RC Structures in Bulgarian construction practice. The analysis is focused on some structural and economic problems as well as on some contradictions in Eurocode 8 itself. Special attention is paid to the practical solution of the following problems: recognition of torsionally flexible systems, stiffness reduction of RC elements for linear analysis dimensions and detailing of confined boundary areas of shear walls, detailing of wall structures, etc. Those problems appear during the practical design of some buildings in Bulgaria. Several proposals for solving some problems defined in the paper are presented through some practical examples. Some conclusions are made for further application of Eurocode 8 in the design and construction practice. The importance of some rules and procedures in Eurocode 8 is supported by the examples of damaged RC members during the past earthquakes. The problems of Eurocode 8 and their solutions are illustrated through the experience of Bulgarian construction practice.
International Nuclear Information System (INIS)
Matthees, W.; Magiera, G.
1982-01-01
A sensitivity study for the interaction effects of adjacent structures of nuclear power plants caused by horizontal seismic excitation has been performed. The key structural and soil parameters for linear and for nonlinear behaviour were varied within their applicable bandwidth. It has been shown that the interaction phenomena can contribute to the response of structures to such a large extent that it cannot be disregarded. (orig.)
MULTISCALE TENSOR ANISOTROPIC FILTERING OF FLUORESCENCE MICROSCOPY FOR DENOISING MICROVASCULATURE.
Prasath, V B S; Pelapur, R; Glinskii, O V; Glinsky, V V; Huxley, V H; Palaniappan, K
2015-04-01
Fluorescence microscopy images are contaminated by noise and improving image quality without blurring vascular structures by filtering is an important step in automatic image analysis. The application of interest here is to automatically extract the structural components of the microvascular system with accuracy from images acquired by fluorescence microscopy. A robust denoising process is necessary in order to extract accurate vascular morphology information. For this purpose, we propose a multiscale tensor with anisotropic diffusion model which progressively and adaptively updates the amount of smoothing while preserving vessel boundaries accurately. Based on a coherency enhancing flow with planar confidence measure and fused 3D structure information, our method integrates multiple scales for microvasculature preservation and noise removal membrane structures. Experimental results on simulated synthetic images and epifluorescence images show the advantage of our improvement over other related diffusion filters. We further show that the proposed multiscale integration approach improves denoising accuracy of different tensor diffusion methods to obtain better microvasculature segmentation.
Advances in Rosetta structure prediction for difficult molecular-replacement problems
International Nuclear Information System (INIS)
DiMaio, Frank
2013-01-01
Modeling advances using Rosetta structure prediction to aid in solving difficult molecular-replacement problems are discussed. Recent work has shown the effectiveness of structure-prediction methods in solving difficult molecular-replacement problems. The Rosetta protein structure modeling suite can aid in the solution of difficult molecular-replacement problems using templates from 15 to 25% sequence identity; Rosetta refinement guided by noisy density has consistently led to solved structures where other methods fail. In this paper, an overview of the use of Rosetta for these difficult molecular-replacement problems is provided and new modeling developments that further improve model quality are described. Several variations to the method are introduced that significantly reduce the time needed to generate a model and the sampling required to improve the starting template. The improvements are benchmarked on a set of nine difficult cases and it is shown that this improved method obtains consistently better models in less running time. Finally, strategies for best using Rosetta to solve difficult molecular-replacement problems are presented and future directions for the role of structure-prediction methods in crystallography are discussed
Site response - a critical problem in soil-structure interaction analyses for embedded structures
International Nuclear Information System (INIS)
Seed, H.B.; Lysmer, J.
1986-01-01
Soil-structure interaction analyses for embedded structures must necessarily be based on a knowledge of the manner in which the soil would behave in the absence of any structure - that is on a knowledge and understanding of the spatial distribution of motions in the ground within the depth of embedment of the structure. The nature of these spatial variations is discussed and illustrated by examples of recorded motions. It is shown that both the amplitude of peak acceleration and the form of the acceleration response spectrum for earthquake motions will necessarily vary with depth and failure to take these variations into account may introduce an unwarranted degree of conservatism into the soil-structure interaction analysis procedure
International Nuclear Information System (INIS)
Biedenharn, L.C.; Lohe, M.A.; Louck, J.D.
1975-01-01
The multiplicity problem for tensor operators in U(3) has a unique (canonical) resolution which is utilized to effect the explicit construction of all U(3) Wigner and Racah coefficients. Methods are employed which elucidate the structure of the results; in particular, the significance of the denominator functions entering the structure of these coefficients, and the relation of these denominator functions to the null space of the canonical tensor operators. An interesting feature of the denominator functions is the appearance of new, group theoretical, polynomials exhibiting several remarkable and quite unexpected properties. (U.S.)
A closed-form solution to tensor voting: theory and applications.
Wu, Tai-Pang; Yeung, Sai-Kit; Jia, Jiaya; Tang, Chi-Keung; Medioni, Gérard
2012-08-01
We prove a closed-form solution to tensor voting (CFTV): Given a point set in any dimensions, our closed-form solution provides an exact, continuous, and efficient algorithm for computing a structure-aware tensor that simultaneously achieves salient structure detection and outlier attenuation. Using CFTV, we prove the convergence of tensor voting on a Markov random field (MRF), thus termed as MRFTV, where the structure-aware tensor at each input site reaches a stationary state upon convergence in structure propagation. We then embed structure-aware tensor into expectation maximization (EM) for optimizing a single linear structure to achieve efficient and robust parameter estimation. Specifically, our EMTV algorithm optimizes both the tensor and fitting parameters and does not require random sampling consensus typically used in existing robust statistical techniques. We performed quantitative evaluation on its accuracy and robustness, showing that EMTV performs better than the original TV and other state-of-the-art techniques in fundamental matrix estimation for multiview stereo matching. The extensions of CFTV and EMTV for extracting multiple and nonlinear structures are underway.
Applications of tensor functions in creep mechanics
International Nuclear Information System (INIS)
Betten, J.
1991-01-01
Within this contribution a short survey is given of some recent advances in the mathematical modelling of materials behaviour under creep conditions. The mechanical behaviour of anisotropic solids requires a suitable mathematical modelling. The properties of tensor functions with several argument tensors constitute a rational basis for a consistent mathematical modelling of complex material behaviour. This paper presents certain principles, methods, and recent successfull applications of tensor functions in solid mechanics. The rules for specifying irreducible sets of tensor invariants and tensor generators for material tensors of rank two and four are also discussed. Furthermore, it is very important that the scalar coefficients in constitutive and evolutional equations are determined as functions of the integrity basis and experimental data. It is explained in detail that these coefficients can be determined by using tensorial interpolation methods. Some examples for practical use are discussed. (orig./RHM)
Seamless warping of diffusion tensor fields
DEFF Research Database (Denmark)
Xu, Dongrong; Hao, Xuejun; Bansal, Ravi
2008-01-01
To warp diffusion tensor fields accurately, tensors must be reoriented in the space to which the tensors are warped based on both the local deformation field and the orientation of the underlying fibers in the original image. Existing algorithms for warping tensors typically use forward mapping...... of seams, including voxels in which the deformation is extensive. Backward mapping, however, cannot reorient tensors in the template space because information about the directional orientation of fiber tracts is contained in the original, unwarped imaging space only, and backward mapping alone cannot...... transfer that information to the template space. To combine the advantages of forward and backward mapping, we propose a novel method for the spatial normalization of diffusion tensor (DT) fields that uses a bijection (a bidirectional mapping with one-to-one correspondences between image spaces) to warp DT...
Tensor numerical methods in quantum chemistry: from Hartree-Fock to excitation energies.
Khoromskaia, Venera; Khoromskij, Boris N
2015-12-21
We resume the recent successes of the grid-based tensor numerical methods and discuss their prospects in real-space electronic structure calculations. These methods, based on the low-rank representation of the multidimensional functions and integral operators, first appeared as an accurate tensor calculus for the 3D Hartree potential using 1D complexity operations, and have evolved to entirely grid-based tensor-structured 3D Hartree-Fock eigenvalue solver. It benefits from tensor calculation of the core Hamiltonian and two-electron integrals (TEI) in O(n log n) complexity using the rank-structured approximation of basis functions, electron densities and convolution integral operators all represented on 3D n × n × n Cartesian grids. The algorithm for calculating TEI tensor in a form of the Cholesky decomposition is based on multiple factorizations using algebraic 1D "density fitting" scheme, which yield an almost irreducible number of product basis functions involved in the 3D convolution integrals, depending on a threshold ε > 0. The basis functions are not restricted to separable Gaussians, since the analytical integration is substituted by high-precision tensor-structured numerical quadratures. The tensor approaches to post-Hartree-Fock calculations for the MP2 energy correction and for the Bethe-Salpeter excitation energies, based on using low-rank factorizations and the reduced basis method, were recently introduced. Another direction is towards the tensor-based Hartree-Fock numerical scheme for finite lattices, where one of the numerical challenges is the summation of electrostatic potentials of a large number of nuclei. The 3D grid-based tensor method for calculation of a potential sum on a L × L × L lattice manifests the linear in L computational work, O(L), instead of the usual O(L(3) log L) scaling by the Ewald-type approaches.
The structure of spectral problems and geometry: hyperbolic surfaces in E sup 3
Cieslinski, J L
2003-01-01
Working in the framework of Sym's soliton surfaces approach we point out that some simple assumptions about the structure of linear (spectral) problems of the theory of solitons lead uniquely to the geometry of some special immersions. In this paper we consider general su(2) spectral problems. Under some very weak assumptions they turn out to be associated with hyperbolic surfaces (surfaces of negative Gaussian curvature) immersed in three-dimensional Euclidean space, and especially with the so-called Bianchi surfaces.
On improving the efficiency of tensor voting
Moreno, Rodrigo; Garcia, Miguel Angel; Puig, Domenec; Pizarro, Luis; Burgeth, Bernhard; Weickert, Joachim
2011-01-01
This paper proposes two alternative formulations to reduce the high computational complexity of tensor voting, a robust perceptual grouping technique used to extract salient information from noisy data. The first scheme consists of numerical approximations of the votes, which have been derived from an in-depth analysis of the plate and ball voting processes. The second scheme simplifies the formulation while keeping the same perceptual meaning of the original tensor voting: The stick tensor v...
Schrimpf, Martin
2016-01-01
Google's Machine Learning framework TensorFlow was open-sourced in November 2015 [1] and has since built a growing community around it. TensorFlow is supposed to be flexible for research purposes while also allowing its models to be deployed productively. This work is aimed towards people with experience in Machine Learning considering whether they should use TensorFlow in their environment. Several aspects of the framework important for such a decision are examined, such as the heterogenity,...
Efficient Low Rank Tensor Ring Completion
Wang, Wenqi; Aggarwal, Vaneet; Aeron, Shuchin
2017-01-01
Using the matrix product state (MPS) representation of the recently proposed tensor ring decompositions, in this paper we propose a tensor completion algorithm, which is an alternating minimization algorithm that alternates over the factors in the MPS representation. This development is motivated in part by the success of matrix completion algorithms that alternate over the (low-rank) factors. In this paper, we propose a spectral initialization for the tensor ring completion algorithm and ana...
The Riemann-Lovelock Curvature Tensor
Kastor, David
2012-01-01
In order to study the properties of Lovelock gravity theories in low dimensions, we define the kth-order Riemann-Lovelock tensor as a certain quantity having a total 4k-indices, which is kth-order in the Riemann curvature tensor and shares its basic algebraic and differential properties. We show that the kth-order Riemann-Lovelock tensor is determined by its traces in dimensions 2k \\le D
Tensor Fields for Use in Fractional-Order Viscoelasticity
Freed, Alan D.; Diethelm, Kai
2003-01-01
To be able to construct viscoelastic material models from fractional0order differentegral equations that are applicable for 3D finite-strain analysis requires definitions for fractional derivatives and integrals for symmetric tensor fields, like stress and strain. We define these fields in the body manifold. We then map them ito spatial fields expressed in terms of an Eulerian or Lagrangian reference frame where most analysts prefer to solve boundary problems.
The Scalar-Tensor Theory of Gravitation
International Nuclear Information System (INIS)
Ibanez, J
2003-01-01
Since the scalar-tensor theory of gravitation was proposed almost 50 years ago, it has recently become a robust alternative theory to Einstein's general relativity due to the fact that it appears to represent the lower level of a more fundamental theory and can serve both as a phenomenological theory to explain the recently observed acceleration of the universe, and to solve the cosmological constant problem. To my knowledge The Scalar-Tensor Theory of Gravitation by Y Fujii and K Maeda is the first book to develop a modern view on this topic and is one of the latest titles in the well-presented Cambridge Monographs on Mathematical Physics series. This book is an excellent readable introduction and up-to-date review of the subject. The discussion is well organized; after a comprehensible introduction to the Brans-Dicke theory and the important role played by conformal transformations, the authors review cosmologies with the cosmological constant and how the scalar-tensor theory can serve to explain the accelerating universe, including discussions on dark energy, quintessence and braneworld cosmologies. The book ends with a chapter devoted to quantum effects. To make easy the lectures of the book, each chapter starts with a summary of the subject to be dealt with. As the book proceeds, important issues like conformal frames and the weak equivalence principle are fully discussed. As the authors warn in the preface, the book is not encyclopedic (from my point of view the list of references is fairly short, for example, but this is a minor drawback) and the choice of included topics corresponds to the authors' interests. Nevertheless, the book seems to cover a broad range of the most essential aspects of the subject. Long and 'boring' mathematical derivations are left to appendices so as not to interrupt the flow of the reasoning, allowing the reader to focus on the physical aspects of each subject. These appendices are a valuable help in entering into the mathematical
Generalized Pattern Search methods for a class of nonsmooth optimization problems with structure
Bogani, C.; Gasparo, M. G.; Papini, A.
2009-07-01
We propose a Generalized Pattern Search (GPS) method to solve a class of nonsmooth minimization problems, where the set of nondifferentiability is included in the union of known hyperplanes and, therefore, is highly structured. Both unconstrained and linearly constrained problems are considered. At each iteration the set of poll directions is enforced to conform to the geometry of both the nondifferentiability set and the boundary of the feasible region, near the current iterate. This is the key issue to guarantee the convergence of certain subsequences of iterates to points which satisfy first-order optimality conditions. Numerical experiments on some classical problems validate the method.
THE PROBLEM OF THE FEASIBILITY STUDY IN RESPECT OF DESIGN OF JOINTS OF METAL STRUCTURES
Directory of Open Access Journals (Sweden)
Morozova Dina Vol'demarovna
2012-12-01
It is noteworthy that this problem enjoyed much attention back in the past when the country suffered from steel deficit, and metal processing plants could not keep up with the needs of consumers. This problem was dealt with by Y.M. Lihtarnikov, a Soviet scientist, who published his work "Variant design and optimization of steel structures" in 1979. The authors employ the theoretical base developed by the scientist to perform their research into the optimum solutions to the problems of several types of metal joints.
Dictionary-Based Tensor Canonical Polyadic Decomposition
Cohen, Jeremy Emile; Gillis, Nicolas
2018-04-01
To ensure interpretability of extracted sources in tensor decomposition, we introduce in this paper a dictionary-based tensor canonical polyadic decomposition which enforces one factor to belong exactly to a known dictionary. A new formulation of sparse coding is proposed which enables high dimensional tensors dictionary-based canonical polyadic decomposition. The benefits of using a dictionary in tensor decomposition models are explored both in terms of parameter identifiability and estimation accuracy. Performances of the proposed algorithms are evaluated on the decomposition of simulated data and the unmixing of hyperspectral images.
Bayesian regularization of diffusion tensor images
DEFF Research Database (Denmark)
Frandsen, Jesper; Hobolth, Asger; Østergaard, Leif
2007-01-01
Diffusion tensor imaging (DTI) is a powerful tool in the study of the course of nerve fibre bundles in the human brain. Using DTI, the local fibre orientation in each image voxel can be described by a diffusion tensor which is constructed from local measurements of diffusion coefficients along...... several directions. The measured diffusion coefficients and thereby the diffusion tensors are subject to noise, leading to possibly flawed representations of the three dimensional fibre bundles. In this paper we develop a Bayesian procedure for regularizing the diffusion tensor field, fully utilizing...
A RENORMALIZATION PROCEDURE FOR TENSOR MODELS AND SCALAR-TENSOR THEORIES OF GRAVITY
SASAKURA, NAOKI
2010-01-01
Tensor models are more-index generalizations of the so-called matrix models, and provide models of quantum gravity with the idea that spaces and general relativity are emergent phenomena. In this paper, a renormalization procedure for the tensor models whose dynamical variable is a totally symmetric real three-tensor is discussed. It is proven that configurations with certain Gaussian forms are the attractors of the three-tensor under the renormalization procedure. Since these Gaussian config...
Dirac tensor with heavy photon
Energy Technology Data Exchange (ETDEWEB)
Bytev, V.V.; Kuraev, E.A. [Joint Institute of Nuclear Research, Moscow (Russian Federation). Bogoliubov Lab. of Theoretical Physics; Scherbakova, E.S. [Hamburg Univ. (Germany). 1. Inst. fuer Theoretische Physik
2012-01-15
For the large-angles hard photon emission by initial leptons in process of high energy annihilation of e{sup +}e{sup -} {yields} to hadrons the Dirac tensor is obtained, taking into account the lowest order radiative corrections. The case of large-angles emission of two hard photons by initial leptons is considered. This result is being completed by the kinematics case of collinear hard photons emission as well as soft virtual and real photons and can be used for construction of Monte-Carlo generators. (orig.)
Tensor models, Kronecker coefficients and permutation centralizer algebras
Geloun, Joseph Ben; Ramgoolam, Sanjaye
2017-11-01
We show that the counting of observables and correlators for a 3-index tensor model are organized by the structure of a family of permutation centralizer algebras. These algebras are shown to be semi-simple and their Wedderburn-Artin decompositions into matrix blocks are given in terms of Clebsch-Gordan coefficients of symmetric groups. The matrix basis for the algebras also gives an orthogonal basis for the tensor observables which diagonalizes the Gaussian two-point functions. The centres of the algebras are associated with correlators which are expressible in terms of Kronecker coefficients (Clebsch-Gordan multiplicities of symmetric groups). The color-exchange symmetry present in the Gaussian model, as well as a large class of interacting models, is used to refine the description of the permutation centralizer algebras. This discussion is extended to a general number of colors d: it is used to prove the integrality of an infinite family of number sequences related to color-symmetrizations of colored graphs, and expressible in terms of symmetric group representation theory data. Generalizing a connection between matrix models and Belyi maps, correlators in Gaussian tensor models are interpreted in terms of covers of singular 2-complexes. There is an intriguing difference, between matrix and higher rank tensor models, in the computational complexity of superficially comparable correlators of observables parametrized by Young diagrams.
Numerical evaluation of tensor Feynman integrals in Euclidean kinematics
Energy Technology Data Exchange (ETDEWEB)
Gluza, J.; Kajda [Silesia Univ., Katowice (Poland). Inst. of Physics; Riemann, T.; Yundin, V. [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany)
2010-10-15
For the investigation of higher order Feynman integrals, potentially with tensor structure, it is highly desirable to have numerical methods and automated tools for dedicated, but sufficiently 'simple' numerical approaches. We elaborate two algorithms for this purpose which may be applied in the Euclidean kinematical region and in d=4-2{epsilon} dimensions. One method uses Mellin-Barnes representations for the Feynman parameter representation of multi-loop Feynman integrals with arbitrary tensor rank. Our Mathematica package AMBRE has been extended for that purpose, and together with the packages MB (M. Czakon) or MBresolve (A. V. Smirnov and V. A. Smirnov) one may perform automatically a numerical evaluation of planar tensor Feynman integrals. Alternatively, one may apply sector decomposition to planar and non-planar multi-loop {epsilon}-expanded Feynman integrals with arbitrary tensor rank. We automatized the preparations of Feynman integrals for an immediate application of the package sectordecomposition (C. Bogner and S. Weinzierl) so that one has to give only a proper definition of propagators and numerators. The efficiency of the two implementations, based on Mellin-Barnes representations and sector decompositions, is compared. The computational packages are publicly available. (orig.)
Directory of Open Access Journals (Sweden)
Samir Dey
2015-07-01
Full Text Available This paper proposes a new multi-objective intuitionistic fuzzy goal programming approach to solve a multi-objective nonlinear programming problem in context of a structural design. Here we describe some basic properties of intuitionistic fuzzy optimization. We have considered a multi-objective structural optimization problem with several mutually conflicting objectives. The design objective is to minimize weight of the structure and minimize the vertical deflection at loading point of a statistically loaded three-bar planar truss subjected to stress constraints on each of the truss members. This approach is used to solve the above structural optimization model based on arithmetic mean and compare with the solution by intuitionistic fuzzy goal programming approach. A numerical solution is given to illustrate our approach.
Hoffmann, Michael; Borenstein, Jason
2014-03-01
As a committee of the National Academy of Engineering recognized, ethics education should foster the ability of students to analyze complex decision situations and ill-structured problems. Building on the NAE's insights, we report about an innovative teaching approach that has two main features: first, it places the emphasis on deliberation and on self-directed, problem-based learning in small groups of students; and second, it focuses on understanding ill-structured problems. The first innovation is motivated by an abundance of scholarly research that supports the value of deliberative learning practices. The second results from a critique of the traditional case-study approach in engineering ethics. A key problem with standard cases is that they are usually described in such a fashion that renders the ethical problem as being too obvious and simplistic. The practitioner, by contrast, may face problems that are ill-structured. In the collaborative learning environment described here, groups of students use interactive and web-based argument visualization software called "AGORA-net: Participate - Deliberate!". The function of the software is to structure communication and problem solving in small groups. Students are confronted with the task of identifying possible stakeholder positions and reconstructing their legitimacy by constructing justifications for these positions in the form of graphically represented argument maps. The argument maps are then presented in class so that these stakeholder positions and their respective justifications become visible and can be brought into a reasoned dialogue. Argument mapping provides an opportunity for students to collaborate in teams and to develop critical thinking and argumentation skills.
Conservation laws and stress-energy-momentum tensors for systems with background fields
Energy Technology Data Exchange (ETDEWEB)
Gratus, Jonathan, E-mail: j.gratus@lancaster.ac.uk [Lancaster University, Lancaster LA1 4YB (United Kingdom); The Cockcroft Institute, Daresbury Laboratory, Warrington WA4 4AD (United Kingdom); Obukhov, Yuri N., E-mail: yo@thp.uni-koeln.de [Institute for Theoretical Physics, University of Cologne, 50923 Koeln (Germany); Tucker, Robin W., E-mail: r.tucker@lancaster.ac.uk [Lancaster University, Lancaster LA1 4YB (United Kingdom); The Cockcroft Institute, Daresbury Laboratory, Warrington WA4 4AD (United Kingdom)
2012-10-15
This article attempts to delineate the roles played by non-dynamical background structures and Killing symmetries in the construction of stress-energy-momentum tensors generated from a diffeomorphism invariant action density. An intrinsic coordinate independent approach puts into perspective a number of spurious arguments that have historically lead to the main contenders, viz the Belinfante-Rosenfeld stress-energy-momentum tensor derived from a Noether current and the Einstein-Hilbert stress-energy-momentum tensor derived in the context of Einstein's theory of general relativity. Emphasis is placed on the role played by non-dynamical background (phenomenological) structures that discriminate between properties of these tensors particularly in the context of electrodynamics in media. These tensors are used to construct conservation laws in the presence of Killing Lie-symmetric background fields. - Highlights: Black-Right-Pointing-Pointer The role of background fields in diffeomorphism invariant actions is demonstrated. Black-Right-Pointing-Pointer Interrelations between different stress-energy-momentum tensors are emphasised. Black-Right-Pointing-Pointer The Abraham and Minkowski electromagnetic tensors are discussed in this context. Black-Right-Pointing-Pointer Conservation laws in the presence of nondynamic background fields are formulated. Black-Right-Pointing-Pointer The discussion is facilitated by the development of a new variational calculus.
Volume illustration of muscle from diffusion tensor images.
Chen, Wei; Yan, Zhicheng; Zhang, Song; Crow, John Allen; Ebert, David S; McLaughlin, Ronald M; Mullins, Katie B; Cooper, Robert; Ding, Zi'ang; Liao, Jun
2009-01-01
Medical illustration has demonstrated its effectiveness to depict salient anatomical features while hiding the irrelevant details. Current solutions are ineffective for visualizing fibrous structures such as muscle, because typical datasets (CT or MRI) do not contain directional details. In this paper, we introduce a new muscle illustration approach that leverages diffusion tensor imaging (DTI) data and example-based texture synthesis techniques. Beginning with a volumetric diffusion tensor image, we reformulate it into a scalar field and an auxiliary guidance vector field to represent the structure and orientation of a muscle bundle. A muscle mask derived from the input diffusion tensor image is used to classify the muscle structure. The guidance vector field is further refined to remove noise and clarify structure. To simulate the internal appearance of the muscle, we propose a new two-dimensional example based solid texture synthesis algorithm that builds a solid texture constrained by the guidance vector field. Illustrating the constructed scalar field and solid texture efficiently highlights the global appearance of the muscle as well as the local shape and structure of the muscle fibers in an illustrative fashion. We have applied the proposed approach to five example datasets (four pig hearts and a pig leg), demonstrating plausible illustration and expressiveness.
Eloy Guerrero Seide
2004-01-01
This article summarizes the results obtained in an exploratory and comparative study of two ways of structuring the mathematical content of a B.S. program in Agronomic Engineering at Guantanamo University, Cuba: the formal systematization of the presentation of the knowledge, and an organization through problems. The sign test is used in the proof of the hypothesis. In a preliminary form, at least, it was demonstrated that the variant of systemic structuring of knowledge through proble...
Social problem solving among depressed adolescents is enhanced by structured psychotherapies
Dietz, Laura J.; Marshal, Michael P.; Burton, Chad M.; Bridge, Jeffrey A.; Birmaher, Boris; Kolko, David; Duffy, Jamira N.; Brent, David A.
2014-01-01
Objective Changes in adolescent interpersonal behavior before and after an acute course of psychotherapy were investigated as outcomes and mediators of remission status in a previously described treatment study of depressed adolescents. Maternal depressive symptoms were examined as moderators of the association between psychotherapy condition and changes in adolescents’ interpersonal behavior. Method Adolescents (n = 63, mean age = 15.6 years, 77.8% female, 84.1% Caucasian) engaged in videotaped interactions with their mothers before randomization to cognitive behavior therapy (CBT), systemic behavior family therapy (SBFT), or nondirective supportive therapy (NST), and after 12–16 weeks of treatment. Adolescent involvement, problem solving and dyadic conflict were examined. Results Improvements in adolescent problem solving were significantly associated with CBT and SBFT. Maternal depressive symptoms moderated the effect of CBT, but not SBFT, on adolescents’ problem solving; adolescents experienced increases in problem solving only when their mothers had low or moderate levels of depressive symptoms. Improvements in adolescents’ problem solving were associated with higher rates of remission across treatment conditions, but there were no significant indirect effects of SBFT on remission status through problem solving. Exploratory analyses revealed a significant indirect effect of CBT on remission status through changes in adolescent problem solving, but only when maternal depressive symptoms at study entry were low. Conclusions Findings provide preliminary support for problem solving as an active treatment component of structured psychotherapies for depressed adolescents and suggest one Pathway by which maternal depression may disrupt treatment efficacy for depressed adolescents treated with CBT. PMID:24491077
Hancher, M.
2017-12-01
Recent years have seen promising results from many research teams applying deep learning techniques to geospatial data processing. In that same timeframe, TensorFlow has emerged as the most popular framework for deep learning in general, and Google has assembled petabytes of Earth observation data from a wide variety of sources and made them available in analysis-ready form in the cloud through Google Earth Engine. Nevertheless, developing and applying deep learning to geospatial data at scale has been somewhat cumbersome to date. We present a new set of tools and techniques that simplify this process. Our approach combines the strengths of several underlying tools: TensorFlow for its expressive deep learning framework; Earth Engine for data management, preprocessing, postprocessing, and visualization; and other tools in Google Cloud Platform to train TensorFlow models at scale, perform additional custom parallel data processing, and drive the entire process from a single familiar Python development environment. These tools can be used to easily apply standard deep neural networks, convolutional neural networks, and other custom model architectures to a variety of geospatial data structures. We discuss our experiences applying these and related tools to a range of machine learning problems, including classic problems like cloud detection, building detection, land cover classification, as well as more novel problems like illegal fishing detection. Our improved tools will make it easier for geospatial data scientists to apply modern deep learning techniques to their own problems, and will also make it easier for machine learning researchers to advance the state of the art of those techniques.
STRUCTURAL STUDY AND INVESTIGATION OF NMR TENSORS ...
African Journals Online (AJOL)
NBO studies were performed to the second-order and perturbative estimates of donor-acceptor interaction have been done. The procedures of gauge-invariant atomic orbital (GIAO) and continuous-set-of-gauge-transformation (CSGT) were employed to calculate isotropic shielding, chemical shifts anisotropy and chemical ...
Raman scattering tensors of tyrosine.
Tsuboi, M; Ezaki, Y; Aida, M; Suzuki, M; Yimit, A; Ushizawa, K; Ueda, T
1998-01-01
Polarized Raman scattering measurements have been made of a single crystal of L-tyrosine by the use of a Raman microscope with the 488.0-nm exciting beam from an argon ion laser. The L-tyrosine crystal belongs to the space group P2(1)2(1)2(1) (orthorhombic), and Raman scattering intensities corresponding to the aa, bb, cc, ab and ac components of the crystal Raman tensor have been determined for each prominent Raman band. A similar set of measurements has been made of L-tyrosine-d4, in which four hydrogen atoms on the benzene ring are replaced by deuterium atoms. The effects of NH3-->ND3 and OH-->OD on the Raman spectrum have also been examined. In addition, depolarization ratios of some bands of L-tyrosine in aqueous solutions of pH 13 and pH 1 were examined. For comparison with these experimental results, on the other hand, ab initio molecular orbital calculations have been made of the normal modes of vibration and their associated polarizability oscillations of the L-tyrosine molecule. On the basis of these experimental data and by referring to the results of the calculations, discussions have been presented on the Raman tensors associated to some Raman bands, including those at 829 cm-1 (benzene ring breathing), 642 cm-1 (benzene ring deformation), and 432 cm-1 (C alpha-C beta-C gamma bending).
Energy-momentum tensor and definition of particle states for Robertson-Walker space-time
International Nuclear Information System (INIS)
Brown, M.R.; Dutton, C.R.
1978-01-01
A new regularization scheme is developed for calculating expectation values of the energy-momentum tensor of a quantized scalar field in Robertson-Walker space-times. Using this regularized stress tensor we consider a definition for the vacuum state of the scalar field on any initial hypersurface. Asymptotic methods are developed to investigate the structure of both the divergent and finite terms of the stress tensor when evaluated in this state. The conformal anomaly is discussed in the context of this model. It does not naturally enter into the analysis and we argue that its inclusion is unnecessary
Hintermüller, Michael; Holler, Martin; Papafitsoros, Kostas
2018-06-01
In this work, we introduce a function space setting for a wide class of structural/weighted total variation (TV) regularization methods motivated by their applications in inverse problems. In particular, we consider a regularizer that is the appropriate lower semi-continuous envelope (relaxation) of a suitable TV type functional initially defined for sufficiently smooth functions. We study examples where this relaxation can be expressed explicitly, and we also provide refinements for weighted TV for a wide range of weights. Since an integral characterization of the relaxation in function space is, in general, not always available, we show that, for a rather general linear inverse problems setting, instead of the classical Tikhonov regularization problem, one can equivalently solve a saddle-point problem where no a priori knowledge of an explicit formulation of the structural TV functional is needed. In particular, motivated by concrete applications, we deduce corresponding results for linear inverse problems with norm and Poisson log-likelihood data discrepancy terms. Finally, we provide proof-of-concept numerical examples where we solve the saddle-point problem for weighted TV denoising as well as for MR guided PET image reconstruction.
Rouwette, E.A.J.A.; Vennix, J.A.M.; Felling, A.J.A.
2009-01-01
In the past decade there has been a discussion on the need for and degree of empirical evidence for the effectiveness of problem structuring methods (PSMs). Some authors propose that PSMs are used in unique situations which are difficult to study, both from a methodological and a practical
Rouwette, E.A.J.A.; Vennix, J.A.M.; Felling, A.J.A.
2009-01-01
In the past decade there has been a discussion on the need for and degree of empirical evidence for the effectiveness of problem structuring methods (PSMs). Some authors propose that PSMs are used in unique situations which are difficult to study, both from a methodological and a practical
Photonic Band Structure of Dispersive Metamaterials Formulated as a Hermitian Eigenvalue Problem
Raman, Aaswath; Fan, Shanhui
2010-01-01
We formulate the photonic band structure calculation of any lossless dispersive photonic crystal and optical metamaterial as a Hermitian eigenvalue problem. We further show that the eigenmodes of such lossless systems provide an orthonormal basis, which can be used to rigorously describe the behavior of lossy dispersive systems in general. © 2010 The American Physical Society.
Case Designs for Ill-Structured Problems: Analysis and Implications for Practice
Dabbagh, Nada; Blijd, Cecily Williams
2009-01-01
This study is a third in a series of studies that examined students' information seeking and problem solving behaviors while interacting with one of two types of web-based representations of an ill-structured instructional design case: hierarchical (tree-like) and heterarchical (network-like). A Java program was used to track students' hypermedia…
Photonic Band Structure of Dispersive Metamaterials Formulated as a Hermitian Eigenvalue Problem
Raman, Aaswath
2010-02-26
We formulate the photonic band structure calculation of any lossless dispersive photonic crystal and optical metamaterial as a Hermitian eigenvalue problem. We further show that the eigenmodes of such lossless systems provide an orthonormal basis, which can be used to rigorously describe the behavior of lossy dispersive systems in general. © 2010 The American Physical Society.
Developing Ill-Structured Problem-Solving Skills through Wilderness Education
Collins, Rachel H.; Sibthorp, Jim; Gookin, John
2016-01-01
In a society that is becoming more dynamic, complex, and diverse, the ability to solve ill-structured problems (ISPs) has become an increasingly critical skill. Students who enter adult roles with the cognitive skills to address ISPs will be better able to assume roles in the emerging economies. Opportunities to develop and practice these skills…
Earthworms (Aporrectodea spp.; Lumbricidae) cause soil structure problems in young Dutch polders
Ester, A.; Rozen, van K.
2002-01-01
The presence of earthworms in relation to clay soil structure problems in arable fields in the Flevopolders (the Netherlands) was studied. Recently, farmers in this area have had difficulty in harvesting potatoes in predominantly wet years. After a dry period, soil particles in the top layer of the
is noticing an answer to the problem of unacquirable structures in ...
African Journals Online (AJOL)
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According to Fodor (1983), human cognitive processes can be divided into two .... is making the learner sensitive to the problem structure without explicitly ... If an L2 learner pays attention to and notices a certain form in the L2 input, then the.
M.J. Huiskes (Mark)
2004-01-01
textabstractIn this paper we focus on a number of issues regarding special structure in the relevance feedback learning problem, most notably the effects of image selection based on partial relevance on the clustering behavior of examples. We propose a simple scheme, aspect-based image search, which
Complete stress tensor determination by microearthquake analysis
Slunga, R.
2010-12-01
Jones 1984 found that half of the shallow strike-slip EQ in California had at least one M>2 foreshock. By the Gutenberg law this means at least 3-20 M>0 (low b-value 0.4-0.8). deformations within the crust. This was confirmed by observations in Iceland after 1990 when anew seismic network in Iceland operated by IMO started. Like the Parkfield project in California the SIL network in Iceland was established in an area predicted (Einarsson et al 1981, Stefansson and Halldorsson 1988) to be struck by major EQs within decades of years. The area of main interest have a detection threshold of M=0. A physical approach was chosen to the earthquake warning problem (Stefansson et al 1993) and therefore all microearthquakes were analyzed for FPS by the spectral amplitude method (Slunga 1981). As the shear slip is caused by the in situ stress it is logical to investigate what bounds the FPS puts on the stress tensor. McKenzie 1969 assumed that the earthquake takes place in a crust containing only one fracture, the fault plane. He found that in s uch a case only very weak constraints could be put on the stress. This was widely accepted t o be valid also for microearthquakes in the real crust and lead to methods (Angelier 1978, G ephart and Forsythe 1984 etc) to put four constraints on the stress tensor by assuming that the same stress tensor is causing the slip on four or more different fractures. Another and more realistic approach is to assume that the crust have frequent fractures with almost all orientations. In such a case one can rely on Coulomb's failure criterion for isotropic mat erial (gives four constraints) instead of the weaker Bolt's criterion (giving only one const raint). One obvious fifth constraint is to require the vertical stress to equal the lithosta tic pressure. A sixth constraint is achieved by requiring that the deviatoric elastic energy is minimized. The water pressure is also needed for the fourth constraint by Coulomb (CFS=0 ). It can be related to
Algebraic classification of the Weyl tensor in higher dimensions based on its 'superenergy' tensor
International Nuclear Information System (INIS)
Senovilla, Jose M M
2010-01-01
The algebraic classification of the Weyl tensor in the arbitrary dimension n is recovered by means of the principal directions of its 'superenergy' tensor. This point of view can be helpful in order to compute the Weyl aligned null directions explicitly, and permits one to obtain the algebraic type of the Weyl tensor by computing the principal eigenvalue of rank-2 symmetric future tensors. The algebraic types compatible with states of intrinsic gravitational radiation can then be explored. The underlying ideas are general, so that a classification of arbitrary tensors in the general dimension can be achieved. (fast track communication)
Gravitational Metric Tensor Exterior to Rotating Homogeneous ...
African Journals Online (AJOL)
The covariant and contravariant metric tensors exterior to a homogeneous spherical body rotating uniformly about a common φ axis with constant angular velocity ω is constructed. The constructed metric tensors in this gravitational field have seven non-zero distinct components.The Lagrangian for this gravitational field is ...
Tensor Network Quantum Virtual Machine (TNQVM)
Energy Technology Data Exchange (ETDEWEB)
2016-11-18
There is a lack of state-of-the-art quantum computing simulation software that scales on heterogeneous systems like Titan. Tensor Network Quantum Virtual Machine (TNQVM) provides a quantum simulator that leverages a distributed network of GPUs to simulate quantum circuits in a manner that leverages recent results from tensor network theory.