Simultaneous Learning of Nonlinear Manifold and Dynamical Models for High-dimensional Time Series

The goal of this work is to learn a parsimonious and informative representation for high-dimensional time series. Conceptually, this comprises two distinct yet tightly coupled tasks: learning a low-dimensional manifold and modeling the dynamical process. These two tasks have a complementary relationship as the temporal constraints provide valuable neighborhood information for dimensionality reduction and conversely, the low-dimensional space allows dynamics to be learnt efficiently. Solving these two tasks simultaneously allows important information to be exchanged mutually. If nonlinear models are required to capture the rich complexity of time series, then the learning problem becomes harder as the nonlinearities in both tasks are coupled. The proposed solution approximates the nonlinear manifold and dynamics using piecewise linear models. The interactions among the linear models are captured in a graphical model. By exploiting the model structure, efficient inference and learning algorithms are obtained without oversimplifying the model of the underlying dynamical process. Evaluation of the proposed framework with competing approaches is conducted in three sets of experiments: dimensionality reduction and reconstruction using synthetic time series, video synthesis using a dynamic texture database, and human motion synthesis, classification and tracking on a benchmark data set. In all experiments, the proposed approach provides superior performance.

Simultaneous Learning of Non-Linear Manifold and Dynamical Models for High-Dimensional Time Series

The goal of this work is to learn a parsimonious and informative representation for high-dimensional time series. Conceptually, this comprises two distinct yet tightly coupled tasks: learning a low-dimensional manifold and modeling the dynamical process. These two tasks have a complementary relationship as the temporal constraints provide valuable neighborhood information for dimensionality reduction and conversely, the low-dimensional space allows dynamics to be learnt efficiently. Solving these two tasks simultaneously allows important information to be exchanged mutually. If nonlinear models are required to capture the rich complexity of time series, then the learning problem becomes harder as the nonlinearities in both tasks are coupled. The proposed solution approximates the nonlinear manifold and dynamics using piecewise linear models. The interactions among the linear models are captured in a graphical model. The model structure setup and parameter learning are done using a variational Bayesian approach, which enables automatic Bayesian model structure selection, hence solving the problem of over-fitting. By exploiting the model structure, efficient inference and learning algorithms are obtained without oversimplifying the model of the underlying dynamical process. Evaluation of the proposed framework with competing approaches is conducted in three sets of experiments: dimensionality reduction and reconstruction using synthetic time series, video synthesis using a dynamic texture database, and human motion synthesis, classification and tracking on a benchmark data set. In all experiments, the proposed approach provides superior performance.

Mono- and dimethyl-1,2,4-triazolate as ligands for the mercuric ion in the cationic three-dimensional coordination polymer of [Hg-2(Mmt)(Dmt)(2)](NO3)(H2O))

Colourless crystals of [Hg-2(Mmt)(Dmt)(2)](NO3)(H2O) were obtained from a reaction of mercuric nitrate with nionomethyl- and dimethyl-1,2.4-triazolate (Mmt(-) and Dmt(-), respectively). In the crystal structure (monoclinic, C2/c (no. 15), a = 2579.4(4) b = 1231.1(2), c = 1634.8(2) pm, beta = 128.32(1)degrees V = 4073.3(11).10(6).pm(3): Z = 8, R-1 [I-0 > 2 sigma(I-0)]: 0.0355), half of the mercuric ions are essentially two-coordinate (Hg-N: 210-215 pm), the other half are tetrahedrally surrounded by N-donor atoms (Hg-N: 221, 225 pm) of the Mmt(-) and Dmt(-) anions. These three-N ligands construct a three-dimensional framework.

Automatic dimensional reduction and meshing of stiffened thin-wall structures

The creation of idealised, dimensionally reduced meshes for preliminary design and optimisation remains a time-consuming, manual task. A dimensionally reduced model is ideal for assessing design changes through modification of element properties without the need to create a new geometry or mesh. In this paper, a novel approach for automating the creation of mixed dimensional meshes is presented. The input to the process is a solid model which has been decomposed into a non-manifold assembly of smaller volumes with different meshing significance. Associativity between the original solid model and the dimensionally reduced equivalent is maintained. The approach is validated by means of a free-free modal analysis on an output mesh of a gas turbine engine component of industrial complexity. Extensions and enhancements to this work are also discussed.

An effective three-dimensional ordered mesoporous ZnCo2O4 as electrocatalyst for Li-O2 batteries

Three-dimensional ordered mesoporous (3DOM) ZnCo₂O₄ materials have been synthesized via a hard template and used as bifunctional electrocatalysts for rechargeable Li-O₂ batteries. The as-prepared ZnCo₂O₄ nanoparticles possess a high specific surface area of 127.2 m² g^-1 and a spinel crystalline structure. The Li-O₂ battery utilizing 3DOM ZnCo₂O₄ shows a higher specific capacity of 6024 mAh g^-1 than that with pure Ketjen black (KB). Moreover, the ZnCo₂O₄-based electrode enables much enhanced cyclability with a smaller discharge-recharge voltage gap than that of the carbon-only cathode. Such excellent catalytic performance of ZnCo₂O₄ could be associated with its larger surface area and 3D ordered mesoporous structure

Three-dimensional graphene-Co3O4 cathodes for rechargeable Li-O2 batteries

A three-dimensional (3D) graphene-Co₃O₄ electrode was prepared by a two-step method in which graphene was initially deposited on a Ni foam with Co₃O₄ then grown on the resulting graphene structure. Cross-linked Co₃O₄ nanosheets with an open pore structure were fully and vertically distributed throughout the graphene skeleton. The free-standing and binder-free monolithic electrode was used directly as a cathode in a Li-O₂ battery. This composite structure exhibited enhanced performance with a specific capacity of 2453 mA h g^-1 at 0.1 mA cm^-2 and 62 stable cycles with 583 mA h g^-1 (1000 mA h g_carbon^-1). The excellent electrochemical performance is associated with the unique architecture and superior catalytic activity of the 3D electrode. 

Catena-Poly[bis(ethane-1,2-diammonium) [manganese(II)-di-mu-phosphato-kappa O-4 : O ']]: a one-dimensional manganese phosphate

The title compound,{(C2H10N2)(2)[Mn(PO4)(2)]}(n), contains anionic square-twisted chains of formula [Mn(PO4)(2)](4-) constructed from corner-sharing four-membered rings of alternating MnO4 and PO4 units. The Mn and P atoms have distorted tetrahedral coordination and the Mn atom lies on a twofold axis. The linear manganese-phosphate chains are held together by hydrogen-bonding interactions involving the framework O atoms and the H atoms of the ethane-1,2-diammonium cations, which lie in the interchain spaces.

4,4 '-Dipyridyl-N,N '-dioxide complexes of metal-thiocyanate/selenocyanate: pi-stacked molecular rods as three-dimensional support for two-dimensional polymeric sheets and intra/interchain S center dot center dot center dot S interaction dependent architecture of the R-2(2)(8) synthon driven assembly of one-dimensional polymeric chains

Three supramolecular complexes of Co(II) using SCN-/SeCN- in combination with 4,4'-dipyridyl-N,N'-dioxide (dpyo), i.e., {[Co(SCN)(2)(dpyo)(2)].(dpyo)}(n) ( 1), {[Co(SCN)(2)(dpyo)(H2O)(2)].(H2O)}(n) ( 2), {[Co(SeCN)(2)(dpyo)(H2O)(2)]center dot(H2O)}(n) ( 3), have been synthesized and characterized by single-crystal X-ray analysis. Complex 1 is a rare example of a dpyo bridged two-dimensional (2D) coordination polymer, and pi-stacked dpyo supramolecular rods are generated by the lattice dpyo, passing through the rhombic grid of stacked layers, resulting in a three-dimensional (3D) superstructure. Complexes 2 and 3 are isomorphous one-dimensional (1D) coordination polymers [-Co-dpyo-Co-] that undergo self-assembly leading to a bilayer architecture derived through an R-2(2)(8) H-bonding synthon between coordinated water and dpyo oxygen. A reinvestigation of coordination polymers [Mn(SCN)(2)(dpyo)( H2O)(MeOH)](n) ( 4) and {[Fe(SCN)(2)(dpyo)(H2O)(2)]center dot(H2O)}(n) ( 5) reported recently by our group [ Manna et al. Indian J. Chem. 2006, 45A, 1813] reveals brick wall topology rather than bilayer architecture is due to the decisive role of S center dot center dot center dot S/Se center dot center dot center dot Se interactions in determining the helical nature in 4 and 5 as compared to zigzag polymeric chains in 2 and 3, although the same R-2(2)(8) synthon is responsible for supramolecular assembly in these complexes.

The geometry of optimal control solutions on some six dimensional lie groups

This paper examines optimal solutions of control systems with drift defined on the orthonormal frame bundle of particular Riemannian manifolds of constant curvature. The manifolds considered here are the space forms Euclidean space E-3, the spheres S-3 and the hyperboloids H-3 with the corresponding frame bundles equal to the Euclidean group of motions SE(3), the rotation group SO(4) and the Lorentz group SO(1,3). The optimal controls of these systems are solved explicitly in terms of elliptic functions. In this paper, a geometric interpretation of the extremal solutions is given with particular emphasis to a singularity in the explicit solutions. Using a reduced form of the Casimir functions the geometry of these solutions are illustrated.

Three dimensional picture of the local structure of 1,4-Polybutadiene from a complete atomistic model and neutron scattering data

An efficient method of combining neutron diffraction data over an extended Q range with detailed atomistic models is presented. A quantitative and qualitative mapping of the organization of the chain conformation in both glass and liquid phase has been performed. The proposed structural refinement method is based on the exploitation of the intrachain features of the diffraction pattern by the use of internal coordinates for bond lengths, valence angles and torsion rotations. Models are built stochastically by assignment of these internal coordinates from probability distributions with limited variable parameters. Variation of these parameters is used in the construction of models that minimize the differences between the observed and calculated structure factors. A series of neutron scattering data of 1,4-polybutadiene at the region 20320 K is presented. Analysis of the experimental data yield bond lengths for C-C and C=C of 1.54 and 1.35 Å respectively. Valence angles of the backbone were found to be at 112 and 122.8 for the CCC and CC=C respectively. Three torsion angles corresponding to the double bond and the adjacent R and β bonds were found to occupy cis and trans, s(, trans and g( and trans states, respectively. We compare our results with theoretical predictions, computer simulations, RIS models, and previously reported experimental results.

Genericity of Nondegenerate Critical Points and Morse Geodesic Functionals

We consider a family of variational problems on a Hilbert manifold parameterized by an open subset of a Banach manifold, and we discuss the genericity of the nondegeneracy condition for the critical points. Using classical techniques, we prove an abstract genericity result that employs the infinite dimensional Sard-Smale theorem, along the lines of an analogous result of B. White [29]. Applications are given by proving the genericity of metrics without degenerate geodesics between fixed endpoints in general (non compact) semi-Riemannian manifolds, in orthogonally split semi-Riemannian manifolds and in globally hyperbolic Lorentzian manifolds. We discuss the genericity property also in stationary Lorentzian manifolds.

The Gauss-Kronecker curvature of minimal hypersurfaces in four-dimensional space forms

LetQ(4)( c) be a four-dimensional space form of constant curvature c. In this paper we show that the infimum of the absolute value of the Gauss-Kronecker curvature of a complete minimal hypersurface in Q(4)(c), c <= 0, whose Ricci curvature is bounded from below, is equal to zero. Further, we study the connected minimal hypersurfaces M(3) of a space form Q(4)( c) with constant Gauss-Kronecker curvature K. For the case c <= 0, we prove, by a local argument, that if K is constant, then K must be equal to zero. We also present a classification of complete minimal hypersurfaces of Q(4)( c) with K constant.

Geometrical Lagrangian for a supersymmetric Yang-Mills theory on the group manifold

Perhaps one of the main features of Einstein's General Theory of Relativity is that spacetime is not flat itself but curved. Nowadays, however, many of the unifying theories like superstrings on even alternative gravity theories such as teleparalell geometric theories assume flat spacetime for their calculations. This article, an extended account of an earlier author's contribution, it is assumed a curved group manifold as a geometrical background from which a Lagrangian for a supersymmetric N = 2, d = 5 Yang-Mills - SYM, N = 2, d = 5 - is built up. The spacetime is a hypersurface embedded in this geometrical scenario, and the geometrical action here obtained can be readily coupled to the five-dimensional supergravity action. The essential idea that underlies this work has its roots in the Einstein-Cartan formulation of gravity and in the 'group manifold approach to gravity and supergravity theories'. The group SYM, N = 2, d = 5, turns out to be the direct product of supergravity and a general gauge group g: G = g circle times <(SU(2, 2/1))over bar>.

Efeito da desinfecção química e do envelhecimento acelerado sobre a estabilidade dimensional, reprodução e manutenção de detalhes e estabilidade de cor do silicone facial Silastic MDX 4-4210 com opacificador

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)