Divide and Conquer: Efficient Large-Scale Structure from Motion Using Graph Partitioning

Despite significant advances in recent years, structure-from-motion (SfM) pipelines suffer from two important drawbacks. Apart from requiring significant computational power to solve the large-scale computations involved, such pipelines sometimes fail to correctly reconstruct when the accumulated error in incremental reconstruction is large or when the number of 3D to 2D correspondences are insufficient. In this paper we present a novel approach to mitigate the above-mentioned drawbacks. Using an image match graph based on matching features we partition the image data set into smaller sets or components which are reconstructed independently. Following such reconstructions we utilise the available epipolar relationships that connect images across components to correctly align the individual reconstructions in a global frame of reference. This results in both a significant speed up of at least one order of magnitude and also mitigates the problems of reconstruction failures with a marginal loss in accuracy. The effectiveness of our approach is demonstrated on some large-scale real world data sets.

Crystal structure from packing studies: application to the triclinic structure of the cyclic hexapeptide cyclo-(gly-tyr-gly)2

The paper describes a novel method of finding the position and orientation of a relatively rigid molecule in the unit cell from criteria concerning allowed contact distances between atoms. On application to the crystal structure of a hexapeptide, C25H31N6O8.2H2O, it was possible to solve the structure from this starting point, by a series of SFLS refinements with an increasingly larger number of reflexions at successive stages. The packing analysis succeeded, even though the water molecules were not included to start with.

Understanding Protein Structure from a Percolation Perspective

Underlying the unique structures and diverse functions of proteins area vast range of amino-acid sequences and a highly limited number of folds taken up by the polypeptide backbone. By investigating the role of noncovalent connections at the backbone level and at the detailed side-chain level, we show that these unique structures emerge from interplay between random and selected features. Primarily, the protein structure network formed by these connections shows simple (bond) and higher order (clique) percolation behavior distinctly reminiscent of random network models. However, the clique percolation specific to the side-chain interaction network bears signatures unique to proteins characterized by a larger degree of connectivity than in random networks. These studies reflect some salient features of the manner in which amino acid sequences select the unique structure of proteins from the pool of a limited number of available folds.

A model based factorization approach for dense 3D recovery from monocular video

Feature track matrix factorization based methods have been attractive solutions to the Structure-front-motion (Sfnl) problem. Group motion of the feature points is analyzed to get the 3D information. It is well known that the factorization formulations give rise to rank deficient system of equations. Even when enough constraints exist, the extracted models are sparse due the unavailability of pixel level tracks. Pixel level tracking of 3D surfaces is a difficult problem, particularly when the surface has very little texture as in a human face. Only sparsely located feature points can be tracked and tracking error arc inevitable along rotating lose texture surfaces. However, the 3D models of an object class lie in a subspace of the set of all possible 3D models. We propose a novel solution to the Structure-from-motion problem which utilizes the high-resolution 3D obtained from range scanner to compute a basis for this desired subspace. Adding subspace constraints during factorization also facilitates removal of tracking noise which causes distortions outside the subspace. We demonstrate the effectiveness of our formulation by extracting dense 3D structure of a human face and comparing it with a well known Structure-front-motion algorithm due to Brand.

Action Recognition from Motion Capture Data using Meta-cognitive RBF Network Classifier

Action recognition plays an important role in various applications, including smart homes and personal assistive robotics. In this paper, we propose an algorithm for recognizing human actions using motion capture action data. Motion capture data provides accurate three dimensional positions of joints which constitute the human skeleton. We model the movement of the skeletal joints temporally in order to classify the action. The skeleton in each frame of an action sequence is represented as a 129 dimensional vector, of which each component is a 31) angle made by each joint with a fixed point on the skeleton. Finally, the video is represented as a histogram over a codebook obtained from all action sequences. Along with this, the temporal variance of the skeletal joints is used as additional feature. The actions are classified using Meta-Cognitive Radial Basis Function Network (McRBFN) and its Projection Based Learning (PBL) algorithm. We achieve over 97% recognition accuracy on the widely used Berkeley Multimodal Human Action Database (MHAD).

Solution structure of O-glycosylated C-terminal leucine zipper domain of human salivary mucin (MUC7)

Solution structures of a 23 residue glycopeptide II (KIS* RFLLYMKNLLNRIIDDMVEQ, where * denotes the glycan Gal-beta-(1-3)-alpha-GalNAc) and its deglycosylated counterpart I derived from the C-terminal leucine zipper domain of low molecular weight human salivary mucin (MUC7) were studied using CD, NMR spectroscopy and molecular modeling. The peptide I was synthesized using the Fmoc chemistry following the conventional procedure and the glycopeptide II was synthesized incorporating the O-glycosylated building block (N alpha-Fmoc-Ser-[Ac-4,-beta-D-Gal-(1,3)-Ac(2)alpha-D-GalN(3)]-OPfp) at the appropriate position in stepwise assembly of peptide chain. Solution structures of these glycosylated and nonglycosylated peptides were studied in water and in the presence of 50% of an organic cosolvent, trifluoroethanol (TFE) using circular dichroism (CD), and in 50% TFE using two-dimensional proton nuclear magnetic resonance (2D H-1 NMR) spectroscopy. CD spectra in aqueous medium indicate that the apopeptide I adapts, mostly, a beta-sheet conformation whereas the glycopeptide II assumes helical structure. This transition in the secondary structure, upon glycosylation, demonstrates that the carbohydrate moiety exerts significant effect on the peptide backbone conformation. However, in 50% TFE both the peptides show pronounced helical structure. Sequential and medium range NOEs, C alpha H chemical shift perturbations, (3)J(NH:C alpha H) couplings and deuterium exchange rates of the amide proton resonances in water containing 50% TFE indicate that the peptide I adapts alpha-helical structure from Ile2-Val21 and the glycopeptide II adapts alpha-helical structure from Ser3-Glu22. The observation of continuous stretch of helix in both the peptides as observed by both NMR and CD spectroscopy strongly suggests that the C-terminal domain of MUC7 with heptad repeats of leucines or methionine residues may be stabilized by dimeric leucine zipper motif. The results reported herein may be invaluable in understanding the aggregation (or dimerization) of MUC7 glycoprotein which would eventually have implications in determining its structure-function relationship.

Biochemical and structural characterization of recombinant hyoscyamine 6 beta-hydroxylase from Datura metel L.

Hyoscyamine 6 beta-hydroxylase (H6H; EC 1.14.11.11), an important enzyme in the biosynthesis of tropane alkaloids, catalyzes the hydroxylation of hyoscyamine to give 6 beta-hydroxyhyoscyamine and its epoxidation in the biosynthetic pathway leading to scopolamine. Datura metel produces scopolamine as the predominant tropane alkaloid. The cDNA encoding H6H from D. mete! (DmH6H) was cloned, heterologously expressed and biochemically characterized. The purified recombinant His-tagged H6H from D. mete! (DmrH6H) was capable of converting hyoscyamine to scopolamine. The functionally expressed DmrH6H was confirmed by HPLC and ESI-MS verification of the products, 6 beta-hydroxyhyoscyamine and its derivative, scopolamine; the DmrH6H epoxidase activity was low compared to the hydroxylase activity. The K-m values for both the substrates, hyoscyamine and 2-oxoglutarate, were 50 mu M each. The CD (circular dichroism) spectrum of the DmrH6H indicated a preponderance of alpha-helicity in the secondary structure. From the fluorescence studies, Stern-Volmer constants for hyoscyamine and 2-oxoglutarate were found to be 0.14 M-1 and 0.56 M-1, respectively. These data suggested that the binding of the substrates, hyoscyamine and 2-oxoglutarate, to the enzyme induced significant conformational changes. (C) 2010 Elsevier Masson SAS. All rights reserved.

Combining Bayes Classification and Point Group Symmetry under Boolean Framework for Enhanced Protein Quaternary Structure Inference

Our ability to infer the protein quaternary structure automatically from atom and lattice information is inadequate, especially for weak complexes, and heteromeric quaternary structures. Several approaches exist, but they have limited performance. Here, we present a new scheme to infer protein quaternary structure from lattice and protein information, with all-around coverage for strong, weak and very weak affinity homomeric and heteromeric complexes. The scheme combines naive Bayes classifier and point group symmetry under Boolean framework to detect quaternary structures in crystal lattice. It consistently produces >= 90% coverage across diverse benchmarking data sets, including a notably superior 95% coverage for recognition heteromeric complexes, compared with 53% on the same data set by current state-of-the-art method. The detailed study of a limited number of prediction-failed cases offers interesting insights into the intriguing nature of protein contacts in lattice. The findings have implications for accurate inference of quaternary states of proteins, especially weak affinity complexes.

Distribution of transverse chain fluctuations in harmonically confined semiflexible polymers

Two different experimental studies of polymer dynamics based on single-molecule fluorescence imaging have recently found evidence of heterogeneities in the widths of the putative tubes that surround filaments of F-actin during their motion in concentrated solution. In one J. Glaser, D. Chakraborty, K. Kroy, I. Lauter, M. Degawa, N. Kirchesner, B. Hoffmann, R. Merkel, and M. Giesen, Phys. Rev. Lett. 105, 037801 (2010)], the observations were explained in terms of the statistics of a worm-like chain confined to a potential determined self-consistently by a binary collision approximation, and in the other B. Wang, J. Guan, S. M. Anthony, S. C. Bae, K. S. Schweizer, and S. Granick, Phys. Rev. Lett. 104, 118301 (2010)], they were explained in terms of the scaling properties of a random fluid of thin rods. In this paper, we show, using an exact path integral calculation, that the distribution of the length-averaged transverse fluctuations of a harmonically confined weakly bendable rod (one possible realization of a semiflexible chain in a tube), is in good qualitative agreement with the experimental data, although it is qualitatively different in analytic structure from the earlier theoretical predictions. We also show that similar path integral techniques can be used to obtain an exact expression for the time correlation function of fluctuations in the tube cross section. (C) 2012 American Institute of Physics. http://dx.doi.org/10.1063/1.4712306]

Growing length and time scales in glass-forming liquids

The glass transition, whereby liquids transform into amorphous solids at low temperatures, is a subject of intense research despite decades of investigation. Explaining the enormous increase in relaxation times of a liquid upon supercooling is essential for understanding the glass transition. Although many theories, such as the Adam-Gibbs theory, have sought to relate growing relaxation times to length scales associated with spatial correlations in liquid structure or motion of molecules, the role of length scales in glassy dynamics is not well established. Recent studies of spatially correlated rearrangements of molecules leading to structural relaxation, termed ``spatially heterogeneous dynamics,'' provide fresh impetus in this direction. A powerful approach to extract length scales in critical phenomena is finite-size scaling, wherein a system is studied for sizes traversing the length scales of interest. We perform finite-size scaling for a realistic glass-former, using computer simulations, to evaluate the length scale associated with spatially heterogeneous dynamics, which grows as temperature decreases. However, relaxation times that also grow with decreasing temperature do not exhibit standard finite-size scaling with this length. We show that relaxation times are instead determined, for all studied system sizes and temperatures, by configurational entropy, in accordance with the Adam-Gibbs relation, but in disagreement with theoretical expectations based on spin-glass models that configurational entropy is not relevant at temperatures substantially above the critical temperature of mode-coupling theory. Our results provide new insights into the dynamics of glass-forming liquids and pose serious challenges to existing theoretical descriptions.

Structured model-following neuro-adaptive design for attitude maneuver of rigid bodies

A new structured model-following adaptive approach is presented in this paper to achieve large attitude maneuvers of rigid bodies. First, a nominal controller is designed using the dynamic inversion philosophy. Next, a neuro- adaptive design is proposed to augment the nominal design in order to assure robust performance in the presence of parameter inaccuracies as well as unknown constant external disturbances. The structured approach proposed in this paper (where kinematic and dynamic equations are handled separately), reduces the complexity of the controller structure. From simulation studies, this adaptive controller is found to be very effective in assuring robust performance.

A PPP AND CNDO Study of Dithiocarbonic Antonic Derivatives

The application of the CNDO and PPP-CI methods to N,N-dimethyl dithiocarbamate, O-methyl dithiocarbonate (methyl xanthate) and methyl trithiocarbonate ions for the elucidation of electronic structure and electronic spectra is described. The CNDO/2 calculations have been used to obtain the one centre core integrals of the ionic compounds required in calculating the pi electronic spectra of these molecules using the PPP method. The calculated spectra are in good agreement with the experiment. The atomic charge densities determined for alkyl xanthate, dithiocarbamate and trithiocarbonate ions support the earlier qualitative predictions regarding electronic structure from spectroscopic and other studies.

Protein sequence design on the basis of topology optimization techniques -Using continuous modeling of discrete amino acid types

The notion of optimization is inherent in protein design. A long linear chain of twenty types of amino acid residues are known to fold to a 3-D conformation that minimizes the combined inter-residue energy interactions. There are two distinct protein design problems, viz. predicting the folded structure from a given sequence of amino acid monomers (folding problem) and determining a sequence for a given folded structure (inverse folding problem). These two problems have much similarity to engineering structural analysis and structural optimization problems respectively. In the folding problem, a protein chain with a given sequence folds to a conformation, called a native state, which has a unique global minimum energy value when compared to all other unfolded conformations. This involves a search in the conformation space. This is somewhat akin to the principle of minimum potential energy that determines the deformed static equilibrium configuration of an elastic structure of given topology, shape, and size that is subjected to certain boundary conditions. In the inverse-folding problem, one has to design a sequence with some objectives (having a specific feature of the folded structure, docking with another protein, etc.) and constraints (sequence being fixed in some portion, a particular composition of amino acid types, etc.) while obtaining a sequence that would fold to the desired conformation satisfying the criteria of folding. This requires a search in the sequence space. This is similar to structural optimization in the design-variable space wherein a certain feature of structural response is optimized subject to some constraints while satisfying the governing static or dynamic equilibrium equations. Based on this similarity, in this work we apply the topology optimization methods to protein design, discuss modeling issues and present some initial results.

Synthesis, characterization and photoluminescence properties of Gd2O3:Eu3+ nanophosphors prepared by solution combustion method

Gd2O3:Eu3+ (0.5-8.0 mol%) nanophosphors have been prepared by low temperature solution combustion method using metal nitrates as oxidizers and oxalyl dihydrazide (ODH) as a fuel. The phosphors are well characterized by powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR) and photoluminescence (PL) techniques. PXRD patterns of as-formed and calcined (800 degrees C, 3 h) Gd2O3 powders exhibit monoclinic phase with mean crystallite sizes ranging from 20 to 50 nm. Eu3+ doping changes the structure from monoclinic to mixed phase of monoclinic and cubic. SEM micrographs shows the products are foamy, agglomerated and fluffy in nature due to the large amount of gases liberated during combustion reaction. Upon 254 nm excitation the photoluminescence of the Gd2O3:Eu3+ particles show red emission at 611 nm corresponding to D-5(0)-> F-7(2) transition. It is observed that PL intensity increases with calcination temperature. This might be attributed to better crystallization and eliminates the defects, which serve as centers of non-radiative relaxation for nanomaterials. It is observed that the optical energy gap (E-g) is widened with increase Eu3+ content. (C) 2010 Elsevier B.V. All rights reserved.

Thermal expansion of doped lanthanum gallates

Thermal expansion of several compositions of Sr and Mg-doped LaGaO3 including an A-site deficient composition (La0.9Sr0.1)(0.98)(Ga0.8Mg0.2)O-2.821 were measured in the temperature range from 298 to 1273 K. The effect of doping on thermal expansion was studied by varying the composition at one site of the perovskite structure (either A or B), while keeping the composition at the other site invariant. Thermal expansion varied nonlinearly with temperature and exhibited an inflexion between 550 and 620 K, probably related to the change in crystal structure from orthorhombic to rhombohedral. The dependence of average thermal expansion coefficient (alpha (av)) on the dopant concentration on either A or B site of the perovskite structure was found to be linear, when the composition at the other site was kept constant. Mg doping on the B-site had a greater effect on the average thermal expansion coefficient than Sr doping on the A-site. Cation deficiency at the A-site decreases thermal expansion when compositions at both sites are held constant.