Template-based quadrilateral meshing

Generating quadrilateral meshes is a highly non-trivial task, as design decisions are frequently driven by specific application demands. Automatic techniques can optimize objective quality metrics, such as mesh regularity, orthogonality, alignment and adaptivity; however, they cannot make subjective design decisions. There are a few quad meshing approaches that offer some mechanisms to include the user in the mesh generation process; however, these techniques either require a large amount of user interaction or do not provide necessary or easy to use inputs. Here, we propose a template-based approach for generating quad-only meshes from triangle surfaces. Our approach offers a flexible mechanism to allow external input, through the definition of alignment features that are respected during the mesh generation process. While allowing user inputs to support subjective design decisions, our approach also takes into account objective quality metrics to produce semi-regular, quad-only meshes that align well to desired surface features. Published by Elsevier Ltd.

Template-based quadrilateral mesh generation from imaging data

This paper describes a novel template-based meshing approach for generating good quality quadrilateral meshes from 2D digital images. This approach builds upon an existing image-based mesh generation technique called Imeshp, which enables us to create a segmented triangle mesh from an image without the need for an image segmentation step. Our approach generates a quadrilateral mesh using an indirect scheme, which converts the segmented triangle mesh created by the initial steps of the Imesh technique into a quadrilateral one. The triangle-to-quadrilateral conversion makes use of template meshes of triangles. To ensure good element quality, the conversion step is followed by a smoothing step, which is based on a new optimization-based procedure. We show several examples of meshes generated by our approach, and present a thorough experimental evaluation of the quality of the meshes given as examples.

A pattern recognition approach to complex networks

Complex networks exist in many areas of science such as biology, neuroscience, engineering, and sociology. The growing development of this area has led to the introduction of several topological and dynamical measurements, which describe and quantify the structure of networks. Such characterization is essential not only for the modeling of real systems but also for the study of dynamic processes that may take place in them. However, it is not easy to use several measurements for the analysis of complex networks, due to the correlation between them and the difficulty of their visualization. To overcome these limitations, we propose an effective and comprehensive approach for the analysis of complex networks, which allows the visualization of several measurements in a few projections that contain the largest data variance and the classification of networks into three levels of detail, vertices, communities, and the global topology. We also demonstrate the efficiency and the universality of the proposed methods in a series of real-world networks in the three levels.

Crystal Engineering of an Anti-HIV Drug Based on the Recognition of Assembling Molecular Frameworks

A rational strategy was employed for design of an orthorhombic structure of lamivudine with maleic acid. On the basis of the lamivudine saccharinate structure reported in the literature, maleic acid was chosen to synthesize a salt with the anti-HIV drug because of the structural similarities between the salt formers. Maleic acid has an acid-ionization constant of the anti first proton and an arrangement of their hydrogen bonding functionalities similar to those of saccharin. Likewise, there is a saccharin-like conformational rigidity in maleic acid because of the hydrogen-bonded ring formation and the Z-configuration around the C=C double bond. As was conceivably predicted, lamivudine maleate assembles into a structure whose intermolecular architecture is related to that of saccharinate salt of the drug. Therefore, a molecular framework responsible for crystal assembly into a lamivudine saccharinate-like structure could be recognized in the salt formers. Furthermore, structural correlations and structure-solubility relationships were established for lamivudine maleate and saccharinate. Although there is a same molecular framework in maleic acid and saccharin, these salt formers are Structurally different in some aspects. When compared to saccharin, neither out-of-plane SO(2) oxygens nor a benzene group occur in maleic acid. Both features could be related to higher solubility of lamivudine maleate. Here, we also anticipate that multicomponent molecular crystals of lamivudine with other salt formers possessing the molecular framework responsible for crystal assembly can be engineered successfully.

Ionic Recognition by 7-Nitro-1,3,5-triaza Adamantane: First Thermodynamic Study

A thermodynamic study involving 7-nitro-1,3,5-triaza adamantane, 1, and its interaction with metal cations in nonaqueous media is first reported. Solubility data of 1 in various solvents were used to derive the standard Gibbs energies of solution, Delta G(s)degrees in these solvents. The effect of solvation in the different media was assessed from the Gibbs energy of transfer taking acetonitrile as a reference solvent. (1)H NMR studies of the interaction of 1 and metal cations were carried out in CD(3)CN and CD(3)OD and the data are reported. Conductance measurements revealed that this ligand forms lead(II) or zinc complexes of 1: 1 stoichiometry in acetonitrile. It also revealed a stoichiometry of two molecules of 1 per mercury(II) and two cadmiu (II) ions per molecule of 1. The addition of silver salt to 1 led to the precipitation of the silver-1 complex which was isolated and characterized by X-ray crystallography. At variance with conductance measurements in solution, in the solid state the X-ray structure show`s a 1:1 stoichiometry in the Hg(II) complex. The themiodynamics of complexation of 1 and these cations provide a quantitative assessment of the selective behavior of this ligand for ions of environmental relevance.

The binding of synthetic triiodo L-thyronine analogs to human transthyretin: Molecular basis of cooperative and non-cooperative ligand recognition

Transthyretin (TTR) is a tetrameric beta-sheet-rich transporter protein directly involved in human amyloid diseases. Several classes of small molecules can bind to TTR delaying its amyloid fibril formation, thus being promising drug candidates to treat TTR amyloidoses. In the present study, we characterized the interactions of the synthetic triiodo L-thyronine analogs and thyroid hormone nuclear receptor TR beta-selecfive agonists GC-1 and GC-24 with the wild type and V30M variant of human transthyretin (TTR). To achieve this aim, we conducted in vitro TTR acid-mediated aggregation and isothermal titration calorimetry experiments and determined the TTR:GC-1 and TTR:GC-24 crystal structures. Our data indicate that both GC-1 and GC-24 bind to TTR in a non-cooperative manner and are good inhibitors of TTR aggregation, with dissociation constants for both hormone binding sites (HBS) in the low micromolar range. Analysis of the crystal structures of TTRwt:GC-1(24) complexes and their comparison with the TTRwt X-ray structure bound to its natural ligand thyroxine (T4) suggests, at the molecular level, the basis for the cooperative process displayed by T4 and the non-cooperative process provoked by both GC-1 and GC-24 during binding to TTR. (C) 2010 Elsevier Inc. All rights reserved.

Novel Zn(2+)-binding Sites in Human Transthyretin IMPLICATIONS FOR AMYLOIDOGENESIS AND RETINOL-BINDING PROTEIN RECOGNITION

Human transthyretin (TTR) is a homotetrameric protein involved in several amyloidoses. Zn(2+) enhances TTR aggregation in vitro, and is a component of ex vivo TTR amyloid fibrils. We report the first crystal structure of human TTR in complex with Zn(2+) at pH 4.6-7.5. All four structures reveal three tetra-coordinated Zn(2+)-binding sites (ZBS 1-3) per monomer, plus a fourth site (ZBS 4) involving amino acid residues from a symmetry-related tetramer that is not visible in solution by NMR.Zn(2+) binding perturbs loop E-alpha-helix-loop F, the region involved in holo-retinol-binding protein (holo-RBP) recognition, mainly at acidic pH; TTR affinity for holo-RBP decreases similar to 5-fold in the presence of Zn(2+). Interestingly, this same region is disrupted in the crystal structure of the amyloidogenic intermediate of TTR formed at acidic pH in the absence of Zn(2+). HNCO and HNCA experiments performed in solution at pH 7.5 revealed that upon Zn(2+) binding, although the alpha-helix persists, there are perturbations in the resonances of the residues that flank this region, suggesting an increase in structural flexibility. While stability of the monomer of TTR decreases in the presence of Zn(2+), which is consistent with the tertiary structural perturbation provoked by Zn(2+) binding, tetramer stability is only marginally affected by Zn(2+). These data highlight structural and functional roles of Zn(2+) in TTR-related amyloidoses, as well as in holo-RBP recognition and vitamin A homeostasis.

Recognition by the Thyroid Hormone Receptor of Canonical DNA Response Elements

To shed more light on the molecular requirements for recognition of thyroid response elements (TRES) by thyroid receptors (TRs), we compared the specific aspects of DNA TRE recognition by different TR constructs. Using fluorescence anisotropy, we performed a detailed and hierarchical study of TR-TRE binding. This wits done by comparing the binding affinities of three different TR constructs for four different TRE DNA elements, including palindromic sequences and direct repeats (F2, PAL, DR-1, and DR-4) as well as their interactions with nonspecific DNA sequences. The effect of MgCl(2) on suppressing of nonselective DNA binding to TR was also investigated. Furthermore, we determined the dissociation constants of the hTR beta DBD (DNA binding domain) and hTR beta DBD-LBD (DNA binding and ligand binding domains) for specific TRES. We found that a minimum DNA recognition peptide derived from DBD (H1TR) is sufficient for recognition and interaction with TREs, whereas scrambled DNA sequences were unrecognized. Additionally, we determined that the TR DBD binds to F2, PAL, and DR-4 with high affinity and similar K(d) values. The TR DBD-LBD recognizes all the tested TRES but binds preferentially to F2, with even higher affinity. Finally, our results demonstrate the important role played by LBDs in modulating TR-DNA binding.

Wavelet-based dynamic time warping

Dynamic Time Warping (DTW), a pattern matching technique traditionally used for restricted vocabulary speech recognition, is based on a temporal alignment of the input signal with the template models. The principal drawback of DTW is its high computational cost as the lengths of the signals increase. This paper shows extended results over our previously published conference paper, which introduces an optimized version of the DTW I hat is based on the Discrete Wavelet Transform (DWT). (C) 2008 Elsevier B.V. All rights reserved.

Statistical coupling analysis of aspartic proteinases based on crystal structures of the Trichoderma reesei enzyme and its complex with pepstatin A

The crystal structures of an aspartic proteinase from Trichoderma reesei (TrAsP) and of its complex with a competitive inhibitor, pepstatin A, were solved and refined to crystallographic R-factors of 17.9% (R(free)=21.2%) at 1.70 angstrom resolution and 15.81% (R(free) = 19.2%) at 1.85 angstrom resolution, respectively. The three-dimensional structure of TrAsP is similar to structures of other members of the pepsin-like family of aspartic proteinases. Each molecule is folded in a predominantly beta-sheet bilobal structure with the N-terminal and C-terminal domains of about the same size. Structural comparison of the native structure and the TrAsP-pepstatin complex reveals that the enzyme undergoes an induced-fit, rigid-body movement upon inhibitor binding, with the N-terminal and C-terminal lobes tightly enclosing the inhibitor. Upon recognition and binding of pepstatin A, amino acid residues of the enzyme active site form a number of short hydrogen bonds to the inhibitor that may play an important role in the mechanism of catalysis and inhibition. The structures of TrAsP were used as a template for performing statistical coupling analysis of the aspartic protease family. This approach permitted, for the first time, the identification of a network of structurally linked residues putatively mediating conformational changes relevant to the function of this family of enzymes. Statistical coupling analysis reveals coevolved continuous clusters of amino acid residues that extend from the active site into the hydrophobic cores of each of the two domains and include amino acid residues from the flap regions, highlighting the importance of these parts of the protein for its enzymatic activity. (C) 2008 Elsevier Ltd. All rights reserved.

Dynamic Changes in the Mental Rotation Network Revealed by Pattern Recognition Analysis of fMRI Data

We investigated the temporal dynamics and changes in connectivity in the mental rotation network through the application of spatio-temporal support vector machines (SVMs). The spatio-temporal SVM [Mourao-Miranda, J., Friston, K. J., et al. (2007). Dynamic discrimination analysis: A spatial-temporal SVM. Neuroimage, 36, 88-99] is a pattern recognition approach that is suitable for investigating dynamic changes in the brain network during a complex mental task. It does not require a model describing each component of the task and the precise shape of the BOLD impulse response. By defining a time window including a cognitive event, one can use spatio-temporal fMRI observations from two cognitive states to train the SVM. During the training, the SVM finds the discriminating pattern between the two states and produces a discriminating weight vector encompassing both voxels and time (i.e., spatio-temporal maps). We showed that by applying spatio-temporal SVM to an event-related mental rotation experiment, it is possible to discriminate between different degrees of angular disparity (0 degrees vs. 20 degrees, 0 degrees vs. 60 degrees, and 0 degrees vs. 100 degrees), and the discrimination accuracy is correlated with the difference in angular disparity between the conditions. For the comparison with highest accuracy (08 vs. 1008), we evaluated how the most discriminating areas (visual regions, parietal regions, supplementary, and premotor areas) change their behavior over time. The frontal premotor regions became highly discriminating earlier than the superior parietal cortex. There seems to be a parcellation of the parietal regions with an earlier discrimination of the inferior parietal lobe in the mental rotation in relation to the superior parietal. The SVM also identified a network of regions that had a decrease in BOLD responses during the 100 degrees condition in relation to the 0 degrees condition (posterior cingulate, frontal, and superior temporal gyrus). This network was also highly discriminating between the two conditions. In addition, we investigated changes in functional connectivity between the most discriminating areas identified by the spatio-temporal SVM. We observed an increase in functional connectivity between almost all areas activated during the 100 degrees condition (bilateral inferior and superior parietal lobe, bilateral premotor area, and SMA) but not between the areas that showed a decrease in BOLD response during the 100 degrees condition.

Fabrication of disposable voltammetric electronic tongues by using Prussian Blue films electrodeposited onto CD-R gold surfaces and recognition of milk adulteration

A new approach to fabricate a disposable electronic tongue is reported. The fabrication of the disposable sensor aimed the integration of all electrodes necessary for measurement in the same device. The disposable device was constructed with gold CD-R and copper sheets substrates and the sensing elements were gold, copper and a gold surface modified with a layer of Prussian Blue. The relative standard deviation for signals obtained from 20 different disposable gold and 10 different disposable copper electrodes was below 3.5%. The performance, electrode materials and the capability of the device to differentiate samples were evaluated for taste substances model, milk with different pasteurization processes (homogenized/pasteurized, ultra high temperature (UHT) pasteurized and UHT pasteurized with low fat content) and adulterated with hydrogen peroxide. In all analysed cases, a good separation between different samples was noticed in the score plots obtained from the principal component analysis (PCA). Crown Copyright (C) 2008 Published by Elsevier B.V. All rights reserved.

Road and Traffic Signs Recognition using Vector Machines

Intelligent Transportation System (ITS) is a system that builds a safe, effective and integrated transportation environment based on advanced technologies. Road signs detection and recognition is an important part of ITS, which offer ways to collect the real time traffic data for processing at a central facility.This project is to implement a road sign recognition model based on AI and image analysis technologies, which applies a machine learning method, Support Vector Machines, to recognize road signs. We focus on recognizing seven categories of road sign shapes and five categories of speed limit signs. Two kinds of features, binary image and Zernike moments, are used for representing the data to the SVM for training and test. We compared and analyzed the performances of SVM recognition model using different features and different kernels. Moreover, the performances using different recognition models, SVM and Fuzzy ARTMAP, are observed.

Road Sign Recognition based onInvariant Features using SupportVector Machine

Since last two decades researches have been working on developing systems that can assistsdrivers in the best way possible and make driving safe. Computer vision has played a crucialpart in design of these systems. With the introduction of vision techniques variousautonomous and robust real-time traffic automation systems have been designed such asTraffic monitoring, Traffic related parameter estimation and intelligent vehicles. Among theseautomatic detection and recognition of road signs has became an interesting research topic.The system can assist drivers about signs they don’t recognize before passing them.Aim of this research project is to present an Intelligent Road Sign Recognition System basedon state-of-the-art technique, the Support Vector Machine. The project is an extension to thework done at ITS research Platform at Dalarna University [25]. Focus of this research work ison the recognition of road signs under analysis. When classifying an image its location, sizeand orientation in the image plane are its irrelevant features and one way to get rid of thisambiguity is to extract those features which are invariant under the above mentionedtransformation. These invariant features are then used in Support Vector Machine forclassification. Support Vector Machine is a supervised learning machine that solves problemin higher dimension with the help of Kernel functions and is best know for classificationproblems.

Real-Time Recognition System for Traffic Signs

The aim of this thesis project is to develop the Traffic Sign Recognition algorithm for real time. Inreal time environment, vehicles move at high speed on roads. For the vehicle intelligent system itbecomes essential to detect, process and recognize the traffic sign which is coming in front ofvehicle with high relative velocity, at the right time, so that the driver would be able to pro-actsimultaneously on instructions given in the Traffic Sign. The system assists drivers about trafficsigns they did not recognize before passing them. With the Traffic Sign Recognition system, thevehicle becomes aware of the traffic environment and reacts according to the situation.The objective of the project is to develop a system which can recognize the traffic signs in real time.The three target parameters are the system’s response time in real-time video streaming, the trafficsign recognition speed in still images and the recognition accuracy. The system consists of threeprocesses; the traffic sign detection, the traffic sign recognition and the traffic sign tracking. Thedetection process uses physical properties of traffic signs based on a priori knowledge to detect roadsigns. It generates the road sign image as the input to the recognition process. The recognitionprocess is implemented using the Pattern Matching algorithm. The system was first tested onstationary images where it showed on average 97% accuracy with the average processing time of0.15 seconds for traffic sign recognition. This procedure was then applied to the real time videostreaming. Finally the tracking of traffic signs was developed using Blob tracking which showed theaverage recognition accuracy to 95% in real time and improved the system’s average response timeto 0.04 seconds. This project has been implemented in C-language using the Open Computer VisionLibrary.