Neural Networks: A Diagnostic Tool for Gastric Electrical Uncoupling?

Neural Networks have been successfully employed in different biomedical settings. They have been useful for feature extractions from images and biomedical data in a variety of diagnostic applications. In this paper, they are applied as a diagnostic tool for classifying different levels of gastric electrical uncoupling in controlled acute experiments on dogs. Data was collected from 16 dogs using six bipolar electrodes inserted into the serosa of the antral wall. Each dog underwent three recordings under different conditions: (1) basal state, (2) mild surgically-induced uncoupling, and (3) severe surgically-induced uncoupling. For each condition half-hour recordings were made. The neural network was implemented according to the Learning Vector Quantization model. This is a supervised learning model of the Kohonen Self-Organizing Maps. Majority of the recordings collected from the dogs were used for network training. Remaining recordings served as a testing tool to examine the validity of the training procedure. Approximately 90% of the dogs from the neural network training set were classified properly. However, only 31% of the dogs not included in the training process were accurately diagnosed. The poor neural-network based diagnosis of recordings that did not participate in the training process might have been caused by inappropriate representation of input data. Previous research has suggested characterizing signals according to certain features of the recorded data. This method, if employed, would reduce the noise and possibly improve the diagnostic abilities of the neural network.

Weak form equation–based finite-element modeling of viscoelastic asphalt mixtures

The objective of this study is to demonstrate using weak form partial differential equation (PDE) method for a finite-element (FE) modeling of a new constitutive relation without the need of user subroutine programming. The viscoelastic asphalt mixtures were modeled by the weak form PDE-based FE method as the examples in the paper. A solid-like generalized Maxwell model was used to represent the deforming mechanism of a viscoelastic material, the constitutive relations of which were derived and implemented in the weak form PDE module of Comsol Multiphysics, a commercial FE program. The weak form PDE modeling of viscoelasticity was verified by comparing Comsol and Abaqus simulations, which employed the same loading configurations and material property inputs in virtual laboratory test simulations. Both produced identical results in terms of axial and radial strain responses. The weak form PDE modeling of viscoelasticity was further validated by comparing the weak form PDE predictions with real laboratory test results of six types of asphalt mixtures with two air void contents and three aging periods. The viscoelastic material properties such as the coefficients of a Prony series model for the relaxation modulus were obtained by converting from the master curves of dynamic modulus and phase angle. Strain responses of compressive creep tests at three temperatures and cyclic load tests were predicted using the weak form PDE modeling and found to be comparable with the measurements of the real laboratory tests. It was demonstrated that the weak form PDE-based FE modeling can serve as an efficient method to implement new constitutive models and can free engineers from user subroutine programming.

Knowledge-based Virtual Reconstruction of Museum Artifacts

Within the framework of heritage preservation, 3D scanning and modeling for heritage documentation has increased significantly in recent years, mainly due to the evolution of laser and image-based techniques, modeling software, powerful computers and virtual reality. 3D laser acquisition constitutes a real development opportunity for 3D modeling based previously on theoretical data. The representation of the object information rely on the knowledge of its historic and theoretical frame to reconstitute a posteriori its previous states. This project proposes an approach dealing with data extraction based on architectural knowledge and Laser statement informing measurements, the whole leading to 3D reconstruction. The experimented Khmer objects are exposed at Guimet museum in Paris. The purpose of this digital modeling meets the need of exploitable models for simulation projects, prototyping, exhibitions, promoting cultural tourism and particularly for archiving against any likely disaster and as an aided tool for the formulation of virtual museum concept.

Machine Learning-based Techniques to Address Spectral Distortions in Photon Counting X-ray Computed Tomography

Spectral CT using a photon counting x-ray detector (PCXD) shows great potential for measuring material composition based on energy dependent x-ray attenuation. Spectral CT is especially suited for imaging with K-edge contrast agents to address the otherwise limited contrast in soft tissues. We have developed a micro-CT system based on a PCXD. This system enables full spectrum CT in which the energy thresholds of the PCXD are swept to sample the full energy spectrum for each detector element and projection angle. Measurements provided by the PCXD, however, are distorted due to undesirable physical eects in the detector and are very noisy due to photon starvation. In this work, we proposed two methods based on machine learning to address the spectral distortion issue and to improve the material decomposition. This rst approach is to model distortions using an articial neural network (ANN) and compensate for the distortion in a statistical reconstruction. The second approach is to directly correct for the distortion in the projections. Both technique can be done as a calibration process where the neural network can be trained using 3D printed phantoms data to learn the distortion model or the correction model of the spectral distortion. This replaces the need for synchrotron measurements required in conventional technique to derive the distortion model parametrically which could be costly and time consuming. The results demonstrate experimental feasibility and potential advantages of ANN-based distortion modeling and correction for more accurate K-edge imaging with a PCXD. Given the computational eciency with which the ANN can be applied to projection data, the proposed scheme can be readily integrated into existing CT reconstruction pipelines.

Physical modeling of processes of sediment transport in inlets

During the transformation of the low tide to the high tide, an exactly inverse phenomenon is occurred and the high tidal delta is formed at the mouth upstream. Increasing the tidal range does not affect the nature of this phenomenon and just change its intensity. In this situation, the inlet will be balance over time. A new relationship between equilibrium cross section and tidal prism for different tidal levels as well as sediment grading has been provided which its results are corresponded with results of numerical modeling. In the combination state, the wave height significantly affects the current and sedimentary pattern such that the wave height dimensionless index (Hw/Ht) determines the dominant parameter (the short period wave or tide) in the inlet. It is notable that in this state, the inlet will be balanced over the time. In order to calculate sedimentary phenomena, each of which are individually determined under solely wave and only tide conditions and then they are added. Estimated values are similar to numerical modeling results of the combination state considering nonlinear terms. Also, it is clear that the wave and tide performance is of meaning in the direct relationship with the water level. The water level change causes variations of the position of the breaking line and sedimentary active area. It changes the current and sedimentary pattern coastward while does not change anything seaward. Based on modeling results of sediment transport due to the wave, tide and their combination, it could be said that the erosion at the mouth due to the wave is less than that due to the wave and tide combination. In these situations, tide and wave-tide combination increase the low tidal and high tidal delta volume, respectively. Hence, tide plays an effective role in changing sedimentary phenomena at the channel and mouth downstream. Whereas, short period and combined waves have a crucial role in varying the morphology and sediment transport coast ward.

Model-Predicted Performance of Second-Trimester Down Syndrome Screening With Sonographic Prenasal Thickness

Objective. The purpose of this study was to estimate the Down syndrome detection and false-positive rates for second-trimester sonographic prenasal thickness (PT) measurement alone and in combination with other markers. Methods. Multivariate log Gaussian modeling was performed using numerical integration. Parameters for the PT distribution, in multiples of the normal gestation-specific median (MoM), were derived from 105 Down syndrome and 1385 unaffected pregnancies scanned at 14 to 27 weeks. The data included a new series of 25 cases and 535 controls combined with 4 previously published series. The means were estimated by the median and the SDs by the 10th to 90th range divided by 2.563. Parameters for other markers were obtained from the literature. Results. A log Gaussian model fitted the distribution of PT values well in Down syndrome and unaffected pregnancies. The distribution parameters were as follows: Down syndrome, mean, 1.334 MoM; log(10) SD, 0.0772; unaffected pregnancies, 0.995 and 0.0752, respectively. The model-predicted detection rates for 1%, 3%, and 5% false-positive rates for PT alone were 35%, 51%, and 60%, respectively. The addition of PT to a 4 serum marker protocol increased detection by 14% to 18% compared with serum alone. The simultaneous sonographic measurement of PT and nasal bone length increased detection by 19% to 26%, and with a third sonographic marker, nuchal skin fold, performance was comparable with first-trimester protocols. Conclusions. Second-trimester screening with sonographic PT and serum markers is predicted to have a high detection rate, and further sonographic markers could perform comparably with first-trimester screening protocols.

Development of disabled, replication-defective gene transfer vectors from the Jembrana disease virus, a new infectious agent of cattle

Jembrana disease virus (JDV) is a newly isolated and characterised bovine lentivirus. It causes an acute disease in Ball cattle (Bos javanicus). which can be readily transmitted to susceptible cattle with 17% mortality. There is as yet no treatment or preventive vaccine. We have developed a gene transfer vector system based on JDV that has three components. The first of the components is a bicistronic transfer vector plasmid that was constructed to contain cis-sequences from the JDV genome, including 5 '- and 3 ' -long terminal repeats (LTRs), 0.4 kb of truncated gag and 1.1 kb of 3 ' -env, a multiple cloning site to accommodate the gene(s) of interest for transfer, and an internal ribosome entry site plus the neomycin phosphotransferase (Neo) gene cassette for antibiotic selection. The second element is a packaging plasmid that contains trans-sequences. including gag, pol. vif, tar and rev: but without the env and packaging signals. The third is a plasmid encoding the G glycoprotein of vesicular stomatitis virus (VSV-G) to supply the vector an envelope for pseudotyping. Cotransfection of 293T cells with these three plasmid components produced VSV-G pseudotyped. disabled, replication defective, bicistronic JDV vectors encoding the green fluorescent protein (EGFP) and the Neo resistance selection maker simultaneously with a titre range of (0.4-1.2) x 10(6) CFU/ml. Transduction of several replicating primary and transformed cells from cattle, primate and human sources and importantly growth-arrested cells with the JDV vectors showed high efficiency of EGFP gene transfer at 35-75%, which was stable and the expression of EGFP was long term. Furthermore, these JDV vectors were designed to suit the inclusion and expression of genes corresponding to JDV specific proteins, such as gag or env, for the development of vaccines for Jembrana disease. This strategy should also be applicable to other bovine diseases as wall. The design and construction of the JDV vector system should facilitate the study of the lentivirology and pathogenesis of the diseases associated with JDV or other bovine virus infections. To our knowledge, this is the first such vector system developed from a cattle virus. (C) 2001 Elsevier Science B.V. All rights reserved.

A framework for table driven testing of Java classes

With the advent of object-oriented languages and the portability of Java, the development and use of class libraries has become widespread. Effective class reuse depends on class reliability which in turn depends on thorough testing. This paper describes a class testing approach based on modeling each test case with a tuple and then generating large numbers of tuples to thoroughly cover an input space with many interesting combinations of values. The testing approach is supported by the Roast framework for the testing of Java classes. Roast provides automated tuple generation based on boundary values, unit operations that support driver standardization, and test case templates used for code generation. Roast produces thorough, compact test drivers with low development and maintenance cost. The framework and tool support are illustrated on a number of non-trivial classes, including a graphical user interface policy manager. Quantitative results are presented to substantiate the practicality and effectiveness of the approach. Copyright (C) 2002 John Wiley Sons, Ltd.

Insights into the structural basis for zinc inhibition of the glycine receptor

Histidines 107 and 109 in the glycine receptor ( GlyR) alpha(1) subunit have previously been identified as determinants of the inhibitory zinc-binding site. Based on modeling of the GlyR alpha(1) subunit extracellular domain by homology to the acetylcholine-binding protein crystal structure, we hypothesized that inhibitory zinc is bound within the vestibule lumen at subunit interfaces, where it is ligated by His(107) from one subunit and His(109) from an adjacent subunit. This was tested by co-expressing alpha(1) subunits containing the H107A mutation with alpha(1) subunits containing the H109A mutation. Although sensitivity to zinc inhibition is markedly reduced when either mutation is individually incorporated into all five subunits, the GlyRs formed by the co-expression of H107A mutant subunits with H109A mutant subunits exhibited an inhibitory zinc sensitivity similar to that of the wild type alpha(1) homomeric GlyR. This constitutes strong evidence that inhibitory zinc is coordinated at the interface between adjacent alpha(1) subunits. No evidence was found for beta subunit involvement in the coordination of inhibitory zinc, indicating that a maximum of two zinc-binding sites per alpha(1)beta receptor is sufficient for maximal zinc inhibition. Our data also show that two zinc-binding sites are sufficient for significant inhibition of alpha(1) homomers. The binding of zinc at the interface between adjacent alpha(1) subunits could restrict intersubunit movements, providing a feasible mechanism for the inhibition of channel activation by zinc.

Visualization of clusters in geo-referenced data using three-dimensional self-organizing maps

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Analysis of Natural and Artificial Phenomena Using Signal Processing and Fractional Calculus

In this paper we study several natural and man-made complex phenomena in the perspective of dynamical systems. For each class of phenomena, the system outputs are time-series records obtained in identical conditions. The time-series are viewed as manifestations of the system behavior and are processed for analyzing the system dynamics. First, we use the Fourier transform to process the data and we approximate the amplitude spectra by means of power law functions. We interpret the power law parameters as a phenomenological signature of the system dynamics. Second, we adopt the techniques of non-hierarchical clustering and multidimensional scaling to visualize hidden relationships between the complex phenomena. Third, we propose a vector field based analogy to interpret the patterns unveiled by the PL parameters.

Avaliação do transporte sedimentar na bacia do rio Lima baseada em ferramentas de modelação

Dissertação de mestrado integrado em Engenharia Civil

Developing new approaches for detecting and preventing Aedes aegypti population outbreaks: basis for surveillance, alert and control system

A new approach to dengue vector surveillance based on permanent egg-collection using a modified ovitrap and Bacillus thuringiensis israelensis(Bti) was evaluated in different urban landscapes in Recife, Northeast Brazil. From April 2004 to April 2005, 13 egg-collection cycles of four weeks were carried out. Geo-referenced ovitraps containing grass infusion, Bti and three paddles were placed at fixed sampling stations distributed over five selected sites. Continuous egg-collections yielded more than four million eggs laid into 464 sentinel-ovitraps over one year. The overall positive ovitrap index was 98.5% (over 5,616 trap observations). The egg density index ranged from 100 to 2,500 eggs per trap-cycle, indicating a wide spread and high density of Aedes aegypti (Diptera: Culicidae) breeding populations in all sites. Fluctuations in population density over time were observed, particularly a marked increase from January on, or later, according to site. Massive egg-collection carried out at one of the sites prevented such a population outbreak. At intra-site level, egg counts made it possible to identify spots where the vector population is consistently concentrated over the time, pinpointing areas that should be considered high priority for control activities. The results indicate that these could be promising strategies for detecting and preventing Ae. aegypti population outbreaks.

Cluster kernels for semisupervised classification of VHR urban images

In this paper, we present and apply a semisupervised support vector machine based on cluster kernels for the problem of very high resolution image classification. In the proposed setting, a base kernel working with labeled samples only is deformed by a likelihood kernel encoding similarities between unlabeled examples. The resulting kernel is used to train a standard support vector machine (SVM) classifier. Experiments carried out on very high resolution (VHR) multispectral and hyperspectral images using very few labeled examples show the relevancy of the method in the context of urban image classification. Its simplicity and the small number of parameters involved make it versatile and workable by unexperimented users.

N-dimensional dynamical systems exploiting instabilities in full

We report experimental and numerical results showing how certain N-dimensional dynamical systems are able to exhibit complex time evolutions based on the nonlinear combination of N-1 oscillation modes. The experiments have been done with a family of thermo-optical systems of effective dynamical dimension varying from 1 to 6. The corresponding mathematical model is an N-dimensional vector field based on a scalar-valued nonlinear function of a single variable that is a linear combination of all the dynamic variables. We show how the complex evolutions appear associated with the occurrence of successive Hopf bifurcations in a saddle-node pair of fixed points up to exhaust their instability capabilities in N dimensions. For this reason the observed phenomenon is denoted as the full instability behavior of the dynamical system. The process through which the attractor responsible for the observed time evolution is formed may be rather complex and difficult to characterize. Nevertheless, the well-organized structure of the time signals suggests some generic mechanism of nonlinear mode mixing that we associate with the cluster of invariant sets emerging from the pair of fixed points and with the influence of the neighboring saddle sets on the flow nearby the attractor. The generation of invariant tori is likely during the full instability development and the global process may be considered as a generalized Landau scenario for the emergence of irregular and complex behavior through the nonlinear superposition of oscillatory motions