Inference, inquiry, evidence censorship, and explanation inconnectionist expert systems

The combination of the techniques of expert systems and neural networks has the potential of producing more powerful systems, for example, expert systems able to learn from experience. In this paper, we address the combinatorial neural model (CNM), a kind of fuzzy neural network able to accommodate in a simple framework the highly desirable property of incremental learning, as well as the usual capabilities of expert systems. We show how an interval-based representation for membership grades makes CNM capable of reasoning with several types of uncertainty: vagueness, ignorance, and relevance commonly found in practical applications. In addition, we show how basic functions of expert systems such as inference, inquiry, censorship of input information, and explanation may be implemented. We also report experimental results of the application of CNM to the problem of deforestation monitoring of the Amazon region using satellite images     

An expert system with temporal reasoning for alarm processing inpower system control centers

The alarm lists presented to control center operators are usually difficult to interpret. The authors present an expert system that processes the alarm lists in Portuguese control centers. This system makes an intelligent synthesis of the available information and presents it in a flexible and structured way. It uses an original approach to deal with temporal reasoning and real-time constraints. The system incorporates an explanation module that enables its use as a tutor for novice operators     

Multiple Testing Correction in Medical Image Analysis

We present a novel method for correcting the significance level of hypothesis testing that requires multiple comparisons. It is based on the spectral graph theory, in which the variables are seen as the vertices of a complete undirected graph and the correlation matrix as the adjacency matrix that weights its edges. The method increases the statistical power of the analysis by refuting the assumption of independence among variables, while keeping the probability of false positives low. By computing the eigenvalues of the correlation matrix, it is possible to obtain valuable information about the dependence levels among the variables of the problem, so that the effective number of independent variables can be estimated. The method is compared to other available models and its effectiveness illustrated in case studies involving high-dimensional sets of variables.     

Human autoantibodies reveal titin as a chromosomal protein

Assembly of the higher-order structure of mitotic chromosomes is a prerequisite for proper chromosome condensation, segregation and integrity. Understanding the details of this process has been limited because very few proteins involved in the assembly of chromosome structure have been discovered. Using a human autoimmune scleroderma serum that identifies a chromosomal protein in human cells and Drosophila embryos, we cloned the corresponding Drosophila gene that encodes the homologue of vertebrate titin based on protein size, sequence similarity, developmental expression and subcellular localization. Titin is a giant sarcomeric protein responsible for the elasticity of striated muscle that may also function as a molecular scaffold for myofibrillar assembly. Molecular analysis and immunostaining with antibodies to multiple titin epitopes indicates that the chromosomal and muscle forms of titin may vary in their NH2 termini. The identification of titin as a chromosomal component provides a molecular basis for chromosome structure and elasticity.     

Influence of ethylene‐co‐vinyl acetate copolymers on the flow properties of wax synthetic systems

Wax crystallization can cause serious damage to petroleum flow because as the viscosity increases, there is organic deposition in the pipe lines, which causes oil production reduction. Ethylene–vinyl acetate copolymers (EVA) are used as an alternative to prevent such problems. The influence of EVA copolymers on the properties of wax synthetic systems, composed of a solvent mixture and paraffin and petroleum asphalt residue (PAR), was evaluated in this work. The performance of EVA as a wax inhibitor depends on the molecular weight and vinyl acetate content of the copolymer and on the presence of the asphalt fraction. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 85: 1337–1348, 2002     

Innovation By Half-Measures in German Manufacturing

The Paper develops a critique of industrial restructuring measures from the perspective of social innovation theory. Three kinds of industrial restructure are discussed: business process re-engineering; computer-integrated manufacturing; and lean production. The paper argues that the dominant approaches to these restructuring initiatives are socially deficient in that they do not draw on the full potential of the workforce.     

Involvement of regional lymph nodes after penetration of Schistosoma mansoni cercariae in naive and infected mice

The very low density lipoprotein receptor (VLDL-r) is a cell-surface molecule specialized for the internalization of multiple diverse ligands, including apolipoprotein E (apoE)-containing lipoprotein particles, via clathrin-coated pits. Its structure is similar to the low-density lipoprotein receptor (LDL-r), although the two have substantially different systemic distributions and regulatory pathways. The present work examines the distribution of VLDL-r in the central nervous system (CNS) and in relation to senile plaques in Alzheimer disease (AD). VLDL-r is present on resting and activated microglia, particularly those associated with senile plaques (SPs). VLDL-r immunoreactivity is also found in cortical neurons. Two exons of VLDL-r mRNA are differentially spliced in the mature receptor mRNA. One set of splice forms gives rise to receptors containing (or lacking) an extracellular O-linked glycosylation domain near the transmembrane portion of the molecule. The other set of splice forms appears to be brain-specific, and is responsible for the presence or absence of one of the cysteine-rich repeat regions in the binding region of the molecule. Ratios of the receptor variants generated from these splice forms do not differ substantially across different cortical areas or in AD. We hypothesize that VLDL-r might contribute to metabolism of apoE and apoE/A beta complexes in the brain. Further characterizations of apoE receptors in Alzheimer brain may help lay the groundwork for understanding the role of apoE in the CNS and in the pathophysiology of AD.     

Artificial added mass instabilities in sequential staggered coupling of nonlinear structures and incompressible viscous flows

Within this paper the so-called artificial added mass effect is investigated which is responsible for devastating instabilities within sequentially staggered Fluid-structure Interaction (FSI) simulations where incompressible fluids are considered.A discrete representation of the added mass operator M_A is given and ‘instability conditions’ are evaluated for different temporal discretisation schemes. It is proven that for every sequentially staggered scheme and given spatial discretisation of a problem, a mass ratio between fluid and structural mass density can be found at which the coupled system becomes unstable. The analysis is quite general and does not depend upon the particular spatial discretisation schemes used. However here special attention is given to stabilised finite elements employed on the fluid partition. Numerical investigations further highlight the results.     

Improved Accuracy of High-Order WENO Finite Volume Methods on Cartesian Grids

We propose a simple modification of standard weighted essentially non-oscillatory (WENO) finite volume methods for Cartesian grids, which retains the full spatial order of accuracy of the one-dimensional discretization when applied to nonlinear multidimensional systems of conservation laws. We derive formulas, which allow us to compute high-order accurate point values of the conserved quantities at grid cell interfaces. Using those point values, we can compute a high-order flux at the center of a grid cell interface. Finally, we use those point values to compute high-order accurate averaged fluxes at cell interfaces as needed by a finite volume method. The method is described in detail for the two-dimensional Euler equations of gas dynamics. An extension to the three-dimensional case as well as to other nonlinear systems of conservation laws in divergence form is straightforward. Furthermore, similar ideas can be used to improve the accuracy of WENO type methods for hyperbolic systems which are not in divergence form. Several test computations confirm the high-order accuracy for smooth nonlinear problems.     

A Distributed O(1)-Approximation Algorithm for the Uniform Facility Location Problem

We investigate a metric facility location problem in a distributed setting. In this problem, we assume that each point is a client as well as a potential location for a facility and that the opening costs for the facilities and the demands of the clients are uniform. The goal is to open a subset of the input points as facilities such that the accumulated cost for the whole point set, consisting of the opening costs for the facilities and the connection costs for the clients, is minimized. We present a randomized distributed algorithm that computes in expectation an ${\mathcal {O}}(1)$ -approximate solution to the metric facility location problem described above. Our algorithm works in a synchronous message passing model, where each point is an autonomous computational entity that has its own local memory and that communicates with the other entities by message passing. We assume that each entity knows the distance to all the other entities, but does not know any of the other pairwise distances. Our algorithm uses three rounds of all-to-all communication with message sizes bounded to $\mathcal{O}(\log(n))$ bits, where n is the number of input points. We extend our distributed algorithm to constant powers of metric spaces. For a metric exponent ?≥1, we obtain a randomized ${\mathcal {O}}(1)$ -approximation algorithm that uses three rounds of all-to-all communication with message sizes bounded to $\mathcal{O}(\log(n))$ bits.