Interaction of catechin with poly(L-proline)

Summary Catechin binds strongly to both poly(vinylpyrrolidone) and poly(L-proline) in dilute aqueous solution, inducing a collapse of the more flexible poly(vinylpyrrolidone) chains, but forming a microgel with the more extended poly(L-proline) chains. Low concentrations of poly(L-proline) inhibit the discoloration of aqueous solutions of catechin, thereby implicating the ortho hydroxyyl groups in the catechol moiety in the binding process. Modeling shows that the likely binding sites on poly(L-proline) arise from two minor local conformations. These minor conformations are less frequent in poly(-hydroxy-L-proline) than in poly(L-proline), which may explain why catechin interacts more strongly with poly(L-proline) than with poly(-hydroxy-L-proline).     

Design sensitivity analysis and optimization of nonlinear dynamic response for a motorcycle driving on a half-sine bump road

This paper analyses the design sensitivity of a suspension system with material and geometric nonlinearities for a motorcycle structure. The main procedures include nonlinear structural analysis, formulation of the problem with nonlinear dynamic response, design sensitivity analysis, and optimization. The incremental finite element method is used in structural analysis. The stiffness and damping parameters of the suspension system are considered as design variables. The maximum amplitude of nonlinear transient response at the seat is taken as the objective function during the optimization simulation. A more realistic finite element model for the motorcycle structure with elasto-damping elements of different material models is presented. A comparison is made of the optimum designs with and without geometric nonlinear response and is discussed.Nomenclature A amplitude of the excitation function - a ₀,a ₁ time integration constants for the Newmark method - ^t+t C _s secant viscous damping matrix at timet+t - ^t C _T tangent viscous damping matrix at timet - C linear part of ^t C _T - D _i ⁰ initial value of thei-th design variable - D _i instanenous value of thei-th design variables - ^t+t F^(t–1) total internal force vector at the end of iteration (i–1) and timet+t - ^t+t F _(NL) ^(i–1) nonlinear part of ^t+t F^(i–1) - f frequency of the excitation function - ^t+t K _s secant stiffness matrix at timet+t - ^t K _T tangent stiffness matrix at timet - K linear part of ^t K _T - effective stiffness matrix at timet - L distance between the wheel centres - M constant mass matrix - m _T number of solution time steps - NC number of constraint equations - Q nonlinear dynamic equilibrium equation of the structural system - ^t+t R external applied load vector at timet+t - t _e active time interval for the excitation function - ^t U displacement vector of the finite element assemblage at timet - velocity of the finite element assemblage at timet - ^t Ü acceleration vector of the finite element assemblage at timet - ^t+t U ⁽ⁱ⁾ displacement vector of the finite element assemblage at the end of iterationi and timet+t - velocity vector of the finite element assemblage at the end of iterationi and timet+t - ^t+t Ü⁽ⁱ⁾ acceleration vector of the finite element assemblage at the end of iterationi and timet+t - U ⁽ⁱ⁾ vector of displacement increments from the end of iteration (i–1) to the end of iterationi at timet+t - V driving speed of motorcycle - x vector of design variable - () quantities of variation - ₀ objective function - _i i-th constraint equation     

Stability analysis for multi-agent systems using the incidence matrix: Quantized communication and formation control

The spectral properties of the incidence matrix of the communication graph are exploited to provide solutions to two multi-agent control problems. In particular, we consider the problem of state agreement with quantized communication and the problem of distance-based formation control. In both cases, stabilizing control laws are provided when the communication graph is a tree. It is shown how the relation between tree graphs and the null space of the corresponding incidence matrix encode fundamental properties for these two multi-agent control problems.     

Multi-level hierarchical interface-based supervisory control

Hierarchical Interface-Based Supervisory Control employs interfaces that allow properties of a monolithic system to be verified through local analysis. By avoiding the need to verify properties globally, significant computational savings can be achieved. In this paper we provide local requirements for a multi-level architecture employing command-pair type interfaces. This multi-level architecture allows for a greater reduction in complexity and improved reconfigurability over the two-level case that has been previously studied since it allows the global system to be partitioned into smaller modules. This paper also provides results for synthesizing supervisors in the multi-level architecture that are locally maximally permissive with respect to a given specification and set of interfaces.     

A level set method based on the Bayesian risk for medical image segmentation

This paper proposes an alternative criterion derived from the Bayesian risk classification error for image segmentation. The proposed model introduces a region-based force determined through the difference of the posterior image densities for the different classes, a term based on the prior probability derived from Kullback-Leibler information number, and a regularity term adopted to avoid the generation of excessively irregular and small segmented regions. Compared with other level set methods, the proposed approach relies on the optimum decision of pixel classification and the estimates of prior probabilities; thus the approach has more reliability in theory and practice. Experiments show that the proposed approach is able to extract the complicated shapes of targets and robust for various types of medical images. Moreover, the algorithm can be easily extendable for multiphase segmentation.     

An improved method for voice pathology detection by means of a HMM-based feature space transformation

This paper presents new a feature transformation technique applied to improve the screening accuracy for the automatic detection of pathological voices. The statistical transformation is based on Hidden Markov Models, obtaining a transformation and classification stage simultaneously and adjusting the parameters of the model with a criterion that minimizes the classification error. The original feature vectors are built up using classic short-term noise parameters and mel-frequency cepstral coefficients. With respect to conventional approaches found in the literature of automatic detection of pathological voices, the proposed feature space transformation technique demonstrates a significant improvement of the performance with no addition of new features to the original input space. In view of the results, it is expected that this technique could provide good results in other areas such as speaker verification and/or identification.     

Action categorization with modified hidden conditional random field

In this paper, we present a method for action categorization with a modified hidden conditional random field (HCRF). Specifically, effective silhouette-based action features are extracted using motion moments and spectrum of chain code. We formulate a modified HCRF (mHCRF) to have a guaranteed global optimum in the modelling of the temporal action dependencies after the HMM pathing stage. Experimental results on action categorization using this model are compared favorably against several existing model-based methods including GMM, SVM, Logistic Regression, HMM, CRF and HCRF.     

An improved new error estimation algorithm for optimal filter lengths for stereophonic acoustic echo cancellation

In this paper, we propose an new error estimate algorithm (NEEA) for stereophonic acoustic echo cancellation (SAEC) that is based on the error estimation algorithm (EEA) in [Nguyen-Ky T, Leis J, Xiang W. An improved error estimate algorithm for stereophonic acoustic echo cancellation system. In: International conference on signal processing and communication systems, ICSPCS’2007, Australia; December 2007]. In the EEA and NEEA, with the minimum error signal fixed, we compute the filter lengths so that the error signal may approximate the minimum error signal. When the echo paths change, the adaptive filter automatically adjusts the filter lengths to the optimum values. We also investigate the difference between the adaptive filter lengths. In contrast with the conclusions in [Khong AWH, Naylor PA. Stereophonic acoustic echo cancellation employing selective-tap adaptive algorithms. IEEE Trans Audio, Speech, Lang Process 2006;14(3):785-96, Gansler T, Benesty J. Stereophonic acoustic echo cancellation and two channel adaptive filtering: an overview. Int J Adapt Control Signal Process 2000;4:565-86, Benesty J, Gansler T. A multichannel acoustic echo canceler double-talk detector based on a normalized cross-correlation matrix. Acoust Echo Noise Control 2002;13(2):95-101, Gansler T, Benesty J. A frequency-domain double-talk detector based on a normalized cross-correlation vector. Signal Process 2001;81:1783-7, Eneroth P, Gay SL, Gansler T, Benesty J. A real-time implementation of a stereophonic acoustic echo canceler. IEEE Trans. Speech Audio Process 2001;9(5):513-23, Gansler T, Benesty J. New insights into the stereophonic acoustic echo cancellation problem and an adaptive nonlinearity solution. IEEE Trans. Speech Audio Process 2002; 10(5):257-67, Benesty J, Gansler T, Morgan DR, Sondhi MM, Gay SL. Advances in network and acoustic echo cancellation. Berlin: Springer-Verlag; 2001], our simulation results have shown that the filter lengths can be different. Our simulation results also confirm that the NEEA is better than EEA and SM-NLMS algorithm in terms of echo return loss enhancement.     

Modular analysis and modelling of risk scenarios with dependencies

The risk analysis of critical infrastructures such as the electric power supply or telecommunications is complicated by the fact that such infrastructures are mutually dependent. We propose a modular approach to the modelling and analysis of risk scenarios with dependencies. Our approach may be used to deduce the risk level of an overall system from previous risk analyses of its constituent systems. A custom made assumption-guarantee style is put forward as a means to describe risk scenarios with external dependencies. We also define a set of deduction rules facilitating various kinds of reasoning, including the analysis of mutual dependencies between risk scenarios expressed in the assumption-guarantee style.     

FacetAtlas: multifaceted visualization for rich text corpora

Documents in rich text corpora usually contain multiple facets of information. For example, an article about a specific disease often consists of different facets such as symptom, treatment, cause, diagnosis, prognosis, and prevention. Thus, documents may have different relations based on different facets. Powerful search tools have been developed to help users locate lists of individual documents that are most related to specific keywords. However, there is a lack of effective analysis tools that reveal the multifaceted relations of documents within or cross the document clusters. In this paper, we present FacetAtlas, a multifaceted visualization technique for visually analyzing rich text corpora. FacetAtlas combines search technology with advanced visual analytical tools to convey both global and local patterns simultaneously. We describe several unique aspects of FacetAtlas, including (1) node cliques and multifaceted edges, (2) an optimized density map, and (3) automated opacity pattern enhancement for highlighting visual patterns, (4) interactive context switch between facets. In addition, we demonstrate the power of FacetAtlas through a case study that targets patient education in the health care domain. Our evaluation shows the benefits of this work, especially in support of complex multifaceted data analysis.