OPTICAL FLOW ESTIMATION USING APPROXIMATE NEAREST NEIGHBOR FIELD FUSION

This paper proposes an optical flow algorithm by adapting Approximate Nearest Neighbor Fields (ANNF) to obtain a pixel level optical flow between image sequence. Patch similarity based coherency is performed to refine the ANNF maps. Further improvement in mapping between the two images are obtained by fusing bidirectional ANNF maps between pair of images. Thus a highly accurate pixel level flow is obtained between the pair of images. Using pyramidal cost optimization, the pixel level optical flow is further optimized to a sub-pixel level. The proposed approach is evaluated on the middlebury dataset and the performance obtained is comparable with the state of the art approaches. Furthermore, the proposed approach can be used to compute large displacement optical flow as evaluated using MPI Sintel dataset.

Zinc oxide based photocatalysis: tailoring surface-bulk structure and related interfacial charge carrier dynamics for better environmental applications

As an alternative to the gold standard TiO2 photocatalyst, the use of zinc oxide (ZnO) as a robust candidate for wastewater treatment is widespread due to its similarity in charge carrier dynamics upon bandgap excitation and the generation of reactive oxygen species in aqueous suspensions with TiO2. However, the large bandgap of ZnO, the massive charge carrier recombination, and the photoinduced corrosion-dissolution at extreme pH conditions, together with the formation of inert Zn(OH)(2) during photocatalytic reactions act as barriers for its extensive applicability. To this end, research has been intensified to improve the performance of ZnO by tailoring its surface-bulk structure and by altering its photogenerated charge transfer pathways with an intention to inhibit the surface-bulk charge carrier recombination. For the first time, the several strategies, such as tailoring the intrinsic defects, surface modification with organic compounds, doping with foreign ions, noble metal deposition, heterostructuring with other semiconductors and modification with carbon nanostructures, which have been successfully employed to improve the photoactivity and stability of ZnO are critically reviewed. Such modifications enhance the charge separation and facilitate the generation of reactive oxygenated free radicals, and also the interaction with the pollutant molecules. The synthetic route to obtain hierarchical nanostructured morphologies and study their impact on the photocatalytic performance is explained by considering the morphological influence and the defect-rich chemistry of ZnO. Finally, the crystal facet engineering of polar and non-polar facets and their relevance in photocatalysis is outlined. It is with this intention that the present review directs the further design, tailoring and tuning of the physico-chemical and optoelectronic properties of ZnO for better applications, ranging from photocatalysis to photovoltaics.

Structural and Magnetic Phase Transformations of Hydroxyapatite-Magnetite Composites under Inert and Ambient Sintering Atmospheres

The present work reports the impact of sintering conditions on the phase stability in hydroxyapatite (HA) magnetite (Fe3O4) bulk composites, which were densified using either pressureless sintering in air or by rapid densification via hot pressing in inert atmosphere. In particular, the phase abundances, structural and magnetic properties of the (1-x)HA-xFe(3)O(4) (x = 5, 10, 20, and 40 wt %) composites were quantified by corroborating results obtained from Rietveld refinement of the X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and Mossbauer spectroscopy. Post heat treatment phase analysis revealed a major retention of Fe3O4 in argon atmosphere, while it was partially/completely oxidized to hematite (alpha-Fe2O3) in air. Mossbauer results suggest the high-temperature diffusion of Fe3+ into hydroxyapatite lattice, leading to the formation of Fe-doped HA. A preferential occupancy of Fe3+ at the Ca(1) and Ca(2) sites under hot-pressing and conventional sintering conditions, respectively, was observed. The lattice expansion in HA from Rietveld analysis correlated well with the amounts of Fe-doped HA determined from the Mossbauer spectra. Furthermore, hydroxyapatite in the monoliths and composites was delineated to exist in the monoclinic (P2(1)/b) structure as against the widely reported hexagonal (P6(3)/m) crystal lattice. The compositional similarity of iron doping in hydroxyapatite to that of tooth enamel and bone presents HA-Fe3O4 composites as potential orthopedic and dental implant materials.

Dynamics of 3D view invariance in monkey inferotemporal cortex

Rotations in depth are challenging for object vision because features can appear, disappear, be stretched or compressed. Yet we easily recognize objects across views. Are the underlying representations view invariant or dependent? This question has been intensely debated in human vision, but the neuronal representations remain poorly understood. Here, we show that for naturalistic objects, neurons in the monkey inferotemporal (IT) cortex undergo a dynamic transition in time, whereby they are initially sensitive to viewpoint and later encode view-invariant object identity. This transition depended on two aspects of object structure: it was strongest when objects foreshortened strongly across views and were similar to each other. View invariance in IT neurons was present even when objects were reduced to silhouettes, suggesting that it can arise through similarity between external contours of objects across views. Our results elucidate the viewpoint debate by showing that view invariance arises dynamically in IT neurons out of a representation that is initially view dependent.

A thermodynamic framework for the evolution of damage in concrete under fatigue

A closed-form expression for the dual of dissipation potential is derived within the framework of irreversible thermodynamics using the principles of dimensional analysis and self-similarity. Through this potential, a damage evolution law is proposed for concrete under fatigue loading using the concepts of damage mechanics in conjunction with fracture mechanics. The proposed law is used to compute damage in a volume element when a member is subjected to fatigue loading. The evolution of damage from microcracking to macrocracking of the entire member is captured through a series of volume elements failing one after the other. The number of loading cycles to failure of the member is obtained as the summation of number of cycles to failure for each individual volume element. A parametric study is conducted to determine the effect of the size of the volume element on the model's prediction of fatigue life. A global damage index is also defined, and the residual moment carrying capacity of damaged beams is evaluated. Through a deterministic sensitivity analysis, it is found that the load range and maximum aggregate size are the most influencing parameters on the fatigue life of a plain concrete beam.

Ranking general circulation models for India using TOPSIS

Eleven general circulation models/global climate models (GCMs) - BCCR-BCCM2.0, INGV-ECHAM4, GFDL2.0, GFDL2.1, GISS, IPSL-CM4, MIROC3, MRI-CGCM2, NCAR-PCMI, UKMO-HADCM3 and UKMO-HADGEM1 - are evaluated for Indian climate conditions using the performance indicator, skill score (SS). Two climate variables, temperature T (at three levels, i.e. 500, 700, 850 mb) and precipitation rate (Pr) are considered resulting in four SS-based evaluation criteria (T500, T700, T850, Pr). The multicriterion decision-making method, technique for order preference by similarity to an ideal solution, is applied to rank 11 GCMs. Efforts are made to rank GCMs for the Upper Malaprabha catchment and two river basins, namely, Krishna and Mahanadi (covered by 17 and 15 grids of size 2.5 degrees x 2.5 degrees, respectively). Similar efforts are also made for India (covered by 73 grid points of size 2.5 degrees x 2.5 degrees) for which an ensemble of GFDL2.0, INGV-ECHAM4, UKMO-HADCM3, MIROC3, BCCR-BCCM2.0 and GFDL2.1 is found to be suitable. It is concluded that the proposed methodology can be applied to similar situations with ease.

Halogen bonds in some dihalogenated phenols: applications to crystal engineering

3,4-Dichlorophenol (1) crystallizes in the tetragonal space group I4(1)/a with a short axis of 3.7926 (9) angstrom. The structure is unique in that both type I and type II Cl.....Cl interactions are present, these contact types being distinguished by the angle ranges of the respective C-Cl....Cl angles. The present study shows that these two types of contacts are utterly different. The crystal structures of 4-bromo-3-chlorophenol (2) and 3-bromo-4-chlorophenol (3) have been determined. The crystal structure of (2) is isomorphous to that of (1) with the Br atom in the 4-position participating in a type II interaction. However, the monoclinic P2(1)/c packing of compound (3) is different; while the structure still has O-H....O hydrogen bonds, the tetramer O-H.....O synthon seen in (1) and (2) is not seen. Rather than a type I Br....Br interaction which would have been mandated if (3) were isomorphous to (1) and (2), Br forms a Br....O contact wherein its electrophilic character is clearly evident. Crystal structures of the related compounds 4-chloro-3-iodophenol (4) and 3,5-dibromophenol (5) were also determined. A computational survey of the structural landscape was undertaken for (1), (2) and (3), using a crystal structure prediction protocol in space groups P2(1)/c and I4(1)/a with the COMPASS26 force field. While both tetragonal and monoclinic structures are energetically reasonable for all compounds, the fact that (3) takes the latter structure indicates that Br prefers type II over type I contacts. In order to differentiate further between type I and type II halogen contacts, which being chemically distinct are expected to have different distance fall-off properties, a variable-temperature crystallography study was performed on compounds (1), (2) and (4). Length variations with temperature are greater for type II contacts compared with type I. The type II Br....Br interaction in (2) is stronger than the corresponding type II Cl....Cl interaction in (1), leading to elastic bending of the former upon application of mechanical stress, which contrasts with the plastic deformation of (1). The observation of elastic deformation in (2) is noteworthy; in that it finds an explanation based on the strengths of the respective halogen bonds, it could also be taken as a good starting model for future property design. Cl/Br isostructurality is studied with the Cambridge Structural Database and it is indicated that this isostructurality is based on shape and size similarity of Cl and Br, rather than arising from any chemical resemblance.

Deciphering complex patterns of class-I HLA-peptide cross-reactivity via hierarchical grouping

T-cell responses in humans are initiated by the binding of a peptide antigen to a human leukocyte antigen (HLA) molecule. The peptide-HLA complex then recruits an appropriate T cell, leading to cell-mediated immunity. More than 2000 HLA class-I alleles are known in humans, and they vary only in their peptide-binding grooves. The polymorphism they exhibit enables them to bind a wide range of peptide antigens from diverse sources. HLA molecules and peptides present a complex molecular recognition pattern, as many peptides bind to a given allele and a given peptide can be recognized by many alleles. A powerful grouping scheme that not only provides an insightful classification, but is also capable of dissecting the physicochemical basis of recognition specificity is necessary to address this complexity. We present a hierarchical classification of 2010 class-I alleles by using a systematic divisive clustering method. All-pair distances of alleles were obtained by comparing binding pockets in the structural models. By varying the similarity thresholds, a multilevel classification was obtained, with 7 supergroups, each further subclassifying to yield 72 groups. An independent clustering performed based only on similarities in their epitope pools correlated highly with pocket-based clustering. Physicochemical feature combinations that best explain the basis of clustering are identified. Mutual information calculated for the set of peptide ligands enables identification of binding site residues contributing to peptide specificity. The grouping of HLA molecules achieved here will be useful for rational vaccine design, understanding disease susceptibilities and predicting risk of organ transplants.

An Optimizing Code Generator for a Class of Lattice-Boltzmann Computations

The Lattice-Boltzmann method (LBM), a promising new particle-based simulation technique for complex and multiscale fluid flows, has seen tremendous adoption in recent years in computational fluid dynamics. Even with a state-of-the-art LBM solver such as Palabos, a user has to still manually write the program using library-supplied primitives. We propose an automated code generator for a class of LBM computations with the objective to achieve high performance on modern architectures. Few studies have looked at time tiling for LBM codes. We exploit a key similarity between stencils and LBM to enable polyhedral optimizations and in turn time tiling for LBM. We also characterize the performance of LBM with the Roofline performance model. Experimental results for standard LBM simulations like Lid Driven Cavity, Flow Past Cylinder, and Poiseuille Flow show that our scheme consistently outperforms Palabos-on average by up to 3x while running on 16 cores of an Intel Xeon (Sandybridge). We also obtain an improvement of 2.47x on the SPEC LBM benchmark.

De-DUFing the DUFs: Deciphering distant evolutionary relationships of Domains of Unknown Function using sensitive homology detection methods

Background: In the post-genomic era where sequences are being determined at a rapid rate, we are highly reliant on computational methods for their tentative biochemical characterization. The Pfam database currently contains 3,786 families corresponding to ``Domains of Unknown Function'' (DUF) or ``Uncharacterized Protein Family'' (UPF), of which 3,087 families have no reported three-dimensional structure, constituting almost one-fourth of the known protein families in search for both structure and function. Results: We applied a `computational structural genomics' approach using five state-of-the-art remote similarity detection methods to detect the relationship between uncharacterized DUFs and domain families of known structures. The association with a structural domain family could serve as a start point in elucidating the function of a DUF. Amongst these five methods, searches in SCOP-NrichD database have been applied for the first time. Predictions were classified into high, medium and low-confidence based on the consensus of results from various approaches and also annotated with enzyme and Gene ontology terms. 614 uncharacterized DUFs could be associated with a known structural domain, of which high confidence predictions, involving at least four methods, were made for 54 families. These structure-function relationships for the 614 DUF families can be accessed on-line at http://proline.biochem.iisc.ernet.in/RHD_DUFS/. For potential enzymes in this set, we assessed their compatibility with the associated fold and performed detailed structural and functional annotation by examining alignments and extent of conservation of functional residues. Detailed discussion is provided for interesting assignments for DUF3050, DUF1636, DUF1572, DUF2092 and DUF659. Conclusions: This study provides insights into the structure and potential function for nearly 20 % of the DUFs. Use of different computational approaches enables us to reliably recognize distant relationships, especially when they converge to a common assignment because the methods are often complementary. We observe that while pointers to the structural domain can offer the right clues to the function of a protein, recognition of its precise functional role is still `non-trivial' with many DUF domains conserving only some of the critical residues. It is not clear whether these are functional vestiges or instances involving alternate substrates and interacting partners. Reviewers: This article was reviewed by Drs Eugene Koonin, Frank Eisenhaber and Srikrishna Subramanian.

Prediction of Fatigue Life in Plain Concrete Using Entropy Production

An energy approach within the framework of thermodynamics is used to model the fatigue process in plain concrete. Fatigue crack growth is an irreversible process associated with an irreversible entropy gain. A closed-form expression for entropy generated during fatigue in terms of energy dissipated is derived using principles of dimensional analysis and self-similarity. An increase in compliance is considered as a measure of damage accumulated during fatigue. The entropy at final fatigue failure is shown to be independent of loading and geometry and is proposed as a material property. A relationship between energy dissipated and number of cycles of fatigue loading is obtained. (C) 2015 American Society of Civil Engineers.

Structure-Based Phylogenetic Analysis of the Lipocalin Superfamily

Lipocalins constitute a superfamily of extracellular proteins that are found in all three kingdoms of life. Although very divergent in their sequences and functions, they show remarkable similarity in 3-D structures. Lipocalins bind and transport small hydrophobic molecules. Earlier sequence-based phylogenetic studies of lipocalins highlighted that they have a long evolutionary history. However the molecular and structural basis of their functional diversity is not completely understood. The main objective of the present study is to understand functional diversity of the lipocalins using a structure-based phylogenetic approach. The present study with 39 protein domains from the lipocalin superfamily suggests that the clusters of lipocalins obtained by structure-based phylogeny correspond well with the functional diversity. The detailed analysis on each of the clusters and sub-clusters reveals that the 39 lipocalin domains cluster based on their mode of ligand binding though the clustering was performed on the basis of gross domain structure. The outliers in the phylogenetic tree are often from single member families. Also structure-based phylogenetic approach has provided pointers to assign putative function for the domains of unknown function in lipocalin family. The approach employed in the present study can be used in the future for the functional identification of new lipocalin proteins and may be extended to other protein families where members show poor sequence similarity but high structural similarity.

Average Overlap for Clustering Incomplete Data using Symmetric Non-Negative Matrix Factorization

Clustering techniques which can handle incomplete data have become increasingly important due to varied applications in marketing research, medical diagnosis and survey data analysis. Existing techniques cope up with missing values either by using data modification/imputation or by partial distance computation, often unreliable depending on the number of features available. In this paper, we propose a novel approach for clustering data with missing values, which performs the task by Symmetric Non-Negative Matrix Factorization (SNMF) of a complete pair-wise similarity matrix, computed from the given incomplete data. To accomplish this, we define a novel similarity measure based on Average Overlap similarity metric which can effectively handle missing values without modification of data. Further, the similarity measure is more reliable than partial distances and inherently possesses the properties required to perform SNMF. The experimental evaluation on real world datasets demonstrates that the proposed approach is efficient, scalable and shows significantly better performance compared to the existing techniques.

SeamSeg: Video Object Segmentation using Patch Seams

In this paper, we propose a technique for video object segmentation using patch seams across frames. Typically, seams, which are connected paths of low energy, are utilised for retargeting, where the primary aim is to reduce the image size while preserving the salient image contents. Here, we adapt the formulation of seams for temporal label propagation. The energy function associated with the proposed video seams provides temporal linking of patches across frames, to accurately segment the object. The proposed energy function takes into account the similarity of patches along the seam, temporal consistency of motion and spatial coherency of seams. Label propagation is achieved with high fidelity in the critical boundary regions, utilising the proposed patch seams. To achieve this without additional overheads, we curtail the error propagation by formulating boundary regions as rough-sets. The proposed approach out-perform state-of-the-art supervised and unsupervised algorithms, on benchmark datasets.

Spectral Clustering with Jensen-type kernels and their multi-point extensions

Motivated by multi-distribution divergences, which originate in information theory, we propose a notion of `multipoint' kernels, and study their applications. We study a class of kernels based on Jensen type divergences and show that these can be extended to measure similarity among multiple points. We study tensor flattening methods and develop a multi-point (kernel) spectral clustering (MSC) method. We further emphasize on a special case of the proposed kernels, which is a multi-point extension of the linear (dot-product) kernel and show the existence of cubic time tensor flattening algorithm in this case. Finally, we illustrate the usefulness of our contributions using standard data sets and image segmentation tasks.