Stochastic molecular descriptors for polymers. 4. Study of complex mixtures with topological indices of mass spectra spiral and star networks: The blood proteome case

The Quantitative Structure-Property Relationships (QSPRs) based on Graph or Network Theory are important for predicting the properties of polymeric systems. In the three previous papers of this series (Polymer 45 (2004) 3845-3853; Polymer 46 (2005) 2791-2798; and Polymer 46 (2005) 6461-6473) we focused on the uses of molecular graph parameters called topological indices (TIs) to link the structure of polymers with their biological properties. However, there has been little effort to extend these TIs to the study of complex mixtures of artificial polymers or biopolymers such as nucleic acids and proteins. In this sense, Blood Proteome (BP) is one of the most important and complex mixtures containing protein polymers. For instance, outcomes obtained by Mass Spectrometry (MS) analysis of BP are very useful for the early detection of diseases and drug-induced toxicities. Here, we use two Spiral and Star Network representations of the MS outcomes and defined a new type of TIs. The new TIs introduced here are the spectral moments (π_k) of the stochastic matrix associated to the Spiral graph and describe non-linear relationships between the different regions of the MS characteristic of BP. We used the MARCH-INSIDE approach to calculate the π_k(SN) of different BP samples and S2SNet to determine several Star graph TIs. In the second step, we develop the corresponding Quantitative Proteome-Property Relationship (QPPR) models using the Linear Discriminant Analysis (LDA). QPPRs are the analogues of QSPRs in the case of complex biopolymer mixtures. Specifically, the new QPPRs derived here may be used to detect drug-induced cardiac toxicities from BP samples. Different Machine Learning classification algorithms were used to fit the QPPRs based on π_k(SN), showing J48 decision tree classifier to have the best performance. These results suggest that the present approach captures important features of the complex biopolymers mixtures and opens new opportunities to the application of the idea supporting classic QSPRs in polymer sciences.     

Predictive control architecture for real-time image moments based servoing of robot manipulators

This paper presents a real-time architecture for visual servoing of robot manipulators using nonlinear based predictive control. In order to increase the robustness of the control algorithm, image moments were chosen to be the visual features which describe the objects from the image. A visual predictive architecture is designed to solve tasks addressed to robot manipulators with an eye-in-hand configuration. An implementation of the proposed architecture is done so that the capabilities of a 6 d.o.f robot manipulator are extended. The results of different experiments conducted with two types of image moments based controllers (proportional and predictive with reference trajectory) are presented and discussed.     

Probabilistic motion-compensated prediction in distributed video coding

Distributed video coding (DVC) constitutes an original coding framework to meet the stringent requirements imposed by uplink-oriented and low-power mobile video applications. The quality of the side information available to the decoder and the efficiency of the employed channel codes are primary factors determining the success of a DVC system. This contribution introduces two novel techniques for probabilistic motion compensation in order to generate side information at the Wyner-Ziv decoder. The employed DVC scheme uses a base layer, serving as a hash to facilitate overlapped block motion estimation at the decoder side. On top of the base layer, a supplementary Wyner-Ziv layer is coded in the DCT domain. Both proposed probabilistic motion compensation techniques are driven by the actual correlation channel statistics and reuse information contained in the hash. Experimental results report significant rate savings caused by the novel side information generation methods compared to previous techniques. Moreover, the compression performance of the presented DVC architecture, featuring the proposed side-information generation techniques, delivers state-of-the-art compression performance.     

Experimental characterization of electrostatically actuated in-plane bending of microcantilevers

Experimental validation of numerical models developed by the authors to predict the static behaviour of microelectrostatic actuators is described. Cantilever microbeams, currently used in connection with RF-MEMS and micro-scale material testing were analysed. A set of microcantilevers, bending in the plane of the wafer, i.e. in the same plane as the profiling system’s target, was tested. This differs from the popular case of out-of-plane microbeams, usually studied in the literature. Geometry nonlinearity caused by large deflection of the microbeam was investigated and nonlinear coupled formulation of electromechanical equilibrium was performed. Coupled-field analysis was implemented using the Finite Element Method (FEM), to predict displacements and pull-in voltage measured by Fogale Zoomsurf 3D, subsequently plotting the displacement-versus-voltage curve to complete model validation. FEM nonlinear analysis, based on iterative approach with mesh morphing, and FEM non-incremental approach, including a special element proposed by the authors, are compared to the linear solution and to experimental results. Geometry nonlinearity appears relevant in microbeam modelling and requires a nonlinear solution of the coupled problem. Investigative work, which compared the results of 2D and 3D models to experimental data, revealed that some three dimensional effects are significant in model validation, but the 2D approach may be effective in predicting static behaviour provided that at least a microbeam thickness equivalent is adopted.     

A search space “cartography” for guiding graph coloring heuristics

We present a search space analysis and its application in improving local search algorithms for the graph coloring problem. Using a classical distance measure between colorings, we introduce the following clustering hypothesis: the high quality solutions are not randomly scattered in the search space, but rather grouped in clusters within spheres of specific diameter. We first provide intuitive evidence for this hypothesis by presenting a projection of a large set of local minima in the 3D space. An experimental confirmation is also presented: we introduce two algorithms that exploit the hypothesis by guiding an underlying Tabu Search (TS) process. The first algorithm (TS-Div) uses a learning process to guide the basic TS process toward as-yet-unvisited spheres. The second algorithm (TS-Int) makes deep investigations within a bounded region by organizing it as a tree-like structure of connected spheres. We experimentally demonstrate that if such a region contains a global optimum, TS-Int does not fail in eventually finding it. This pair of algorithms significantly outperforms the underlying basic TS algorithm; it can even improve some of the best-known solutions ever reported in the literature (e.g. for dsjc1000.9).     

Deblurring by Matching

Restoration of the photographs damaged by the camera shake is a challenging task that manifested increasing attention in the recent period. Despite of the important progress of the blind deconvolution techniques, due to the ill-posed nature of the problem, the finest details of the kernel blur cannot be recovered entirely. Moreover, the additional constraints and prior assumptions make these approaches to be relative limited.
In this paper we introduce a novel technique that removes the undesired blur artifacts from photographs taken by hand-held digital cameras. Our approach is based on the observation that in general several consecutive photographs taken by the users share image regions that project the same scene content. Therefore, we took advantage of additional sharp photographs of the same scene. Based on several invariant local feature points, filtered from the given blurred/non-blurred images, our approach matches the keypoints and estimates the blur kernel using additional statistical constraints.
We also present a simple deconvolution technique that preserves edges while minimizing the ringing artifacts in the restored latent image. The experimental results prove that our technique is able to infer accurately the blur kernel while reducing significantly the artifacts of the spoilt images.     

Treatment of Point Defects in Nanowire MOSFETs Using the Nonequilibrium Green’s Function Formalism

A program to numerically simulate point defects in nanowire metal-oxide-semiconductor field-effect transistors is described. The simulation scheme is based on the non-equilibrium Green’s function method self-consistently being obtained via the resolution of 3D Poisson’s equation. A tight-binding hamiltonian is used and the point defect is characterized by a macroscopic coulombic tail treated in the mode-space approach, plus a short range on-site perturbation potential energy, treated exactly. The effect on internal quantities and on the transistor characteristics is studied as a function of the strength and the location of the defect potential. Subthreshold current is found to vary in a factor 10 according to the position of the impurity.Also With Institut Universitaire De France (IUF).     

Low-voltage improved accuracy Gaussian function generator with fourth-order approximation

An original realization of a CMOS Gaussian function generator is presented. The proposed method is based on a new approximation function that is able to fourth-order match the Gaussian function. The current-mode operation of the circuit strongly reduces the technological-caused errors and the errors introduced by temperature variations, with the result of an important increasing of the accuracy for the squaring circuit that represents the functional core of the Gaussian generator (0.1%). Additionally, the bandwidth of the generator is increased as a result of its current-mode operation. Because of the utilization of the new fourth-order approximation function, the deviation from the ideal Gaussian function is smaller than 1 dB for an extended range of the input variable. The circuit is designed for implementing in 0.18 μm CMOS technology, its proposed architecture being compatible with a low-voltage operation (V_DD=1 V). The proposed Gaussian function generator based on the new approximation function allows to extend its capability of generating any continuous mathematical functions, this feature being obtained by changing the approximation function coefficients.     

3D reconstruction of existing concrete bridges using optical methods

Routine bridge inspections usually consist of visual observations. These inspections are time-consuming and subjective. There is a need to identify new inspection techniques for infrastructure that reduce traffic disturbance, and improve the efficiency and reliability of the acquired data. This study compared the performance of three different imaging technologies for the three-dimensional (3D) geometric modeling of existing structures: terrestrial laser scanning, close-range photogrammetry, and infrared scanning. Each technology was used to assess six existing concrete railway bridges. The technologies were compared in terms of geometric deviations, visualization capabilities, the level of the inspector’s experience, and degree of automation. The results suggest that all methods investigated can be used to create 3D models, however, with different level of completeness. Measurements such as span length, deck widths, etc. can be extracted with good accuracy. Although promising, a full off-site inspection is currently not feasible as some areas of the bridges were difficult to capture mainly due to restricted access and narrow spaces. Measurements based on terrestrial laser scanning were closer to the reality compared to photogrammetry and infrared scanning. The study indicates the no special training is needed for photogrammetry and infrared scanning to generate a 3D geometric model.