Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications. (C) 2005 Elsevier B. V. All rights reserved.

Properties of Toeplitz operators on analytic function spaces : from function symbols to distributions

Toeplitz operators are among the most important classes of concrete operators with applications to several branches of pure and applied mathematics. This doctoral thesis deals with Toeplitz operators on analytic Bergman, Bloch and Fock spaces. Usually, a Toeplitz operator is a composition of multiplication by a function and a suitable projection. The present work deals with generalizing the notion to the case where the function is replaced by a distributional symbol. Fredholm theory for Toeplitz operators with matrix-valued symbols is also considered. The subject of this thesis belongs to the areas of complex analysis, functional analysis and operator theory. This work contains five research articles. The articles one, three and four deal with finding suitable distributional classes in Bergman, Fock and Bloch spaces, respectively. In each case the symbol class to be considered turns out to be a certain weighted Sobolev-type space of distributions. The Bergman space setting is the most straightforward. When dealing with Fock spaces, some difficulties arise due to unboundedness of the complex plane and the properties of the Gaussian measure in the definition. In the Bloch-type spaces an additional logarithmic weight must be introduced. Sufficient conditions for boundedness and compactness are derived. The article two contains a portion showing that under additional assumptions, the condition for Bergman spaces is also necessary. The fifth article deals with Fredholm theory for Toeplitz operators having matrix-valued symbols. The essential spectra and index theorems are obtained with the help of Hardy space factorization and the Berezin transform, for instance. The article two also has a part dealing with matrix-valued symbols in a non-reflexive Bergman space, in which case a condition on the oscillation of the symbol (a logarithmic VMO-condition) must be added.

Single-molecule thermodynamics: the heat distribution function of a charged particle in a static magnetic field

Interest in the applicability of fluctuation theorems to the thermodynamics of single molecules in external potentials has recently led to calculations of the work and total entropy distributions of Brownian oscillators in static and time-dependent electromagnetic fields. These calculations, which are based on solutions to a Smoluchowski equation, are not easily extended to a consideration of the other thermodynamic quantity of interest in such systems-the heat exchanges of the particle alone-because of the nonlinear dependence of the heat on a particle's stochastic trajectory. In this paper, we show that a path integral approach provides an exact expression for the distribution of the heat fluctuations of a charged Brownian oscillator in a static magnetic field. This approach is an extension of a similar path integral approach applied earlier by our group to the calculation of the heat distribution function of a trapped Brownian particle, which was found, in the limit of long times, to be consistent with experimental data on the thermal interactions of single micron-sized colloids in a viscous solvent.

Reinforcement Learning With Function Approximation for Traffic Signal Control

We propose, for the first time, a reinforcement learning (RL) algorithm with function approximation for traffic signal control. Our algorithm incorporates state-action features and is easily implementable in high-dimensional settings. Prior work, e. g., the work of Abdulhai et al., on the application of RL to traffic signal control requires full-state representations and cannot be implemented, even in moderate-sized road networks, because the computational complexity exponentially grows in the numbers of lanes and junctions. We tackle this problem of the curse of dimensionality by effectively using feature-based state representations that use a broad characterization of the level of congestion as low, medium, or high. One advantage of our algorithm is that, unlike prior work based on RL, it does not require precise information on queue lengths and elapsed times at each lane but instead works with the aforementioned described features. The number of features that our algorithm requires is linear to the number of signaled lanes, thereby leading to several orders of magnitude reduction in the computational complexity. We perform implementations of our algorithm on various settings and show performance comparisons with other algorithms in the literature, including the works of Abdulhai et al. and Cools et al., as well as the fixed-timing and the longest queue algorithms. For comparison, we also develop an RL algorithm that uses full-state representation and incorporates prioritization of traffic, unlike the work of Abdulhai et al. We observe that our algorithm outperforms all the other algorithms on all the road network settings that we consider.

Tensile flow and work hardening behavior of hot cross-rolled AA7010 aluminum alloy sheets

The present work describes the tensile flow and work hardening behavior of a high strength 7010 aluminum alloy by constitutive relations. The alloy has been hot rolled by three different cross-rolling schedules. Room temperature tensile properties have been evaluated as a function of tensile axis orientation in the as-hot rolled as well as peak aged conditions. It is found that both the Ludwigson and a generalized Voce-Bergstrom relation adequately describe the tensile flow behavior of the present alloy in all conditions compared to the Hollomon relation. The variation in the Ludwigson fitting parameter could be correlated well with the microstructural features and anisotropic contribution of strengthening precipitates in the as-rolled and peak aged conditions, respectively. The hardening rate and the saturation stress of the first Voce-Bergstrom parameter, on the other hand, depend mainly on the crystallographic texture of the specimens. It is further shown that for the peak aged specimens the uniform elongation (epsilon(u)) derived from the Ludwigson relation matches well with the measured epsilon(u) irrespective of processing and loading directions. However, the Ludwigson fit overestimates the epsilon(u) in case of the as-rolled specimens. The Hollomon fit, on the other hand, predicts well the measured epsilon(u), of the as-rolled specimens but severely underestimates the epsilon(u), for the peak aged specimens. Contrarily, both the relations significantly overestimate the UTS of the as-rolled and the peak aged specimens. The Voce-Bergstrom parameters define the slope of e Theta-sigma plots in the stage-III regime when the specimens show a classical linear decrease in hardening rate in stage-III. Further analysis of work hardening behavior throws some light on the effect of texture on the dislocation storage and dynamic recovery.

Synthesis and application of weight function for edge cracked semicircular disk (ECSD)

We analyze the utility of edge cracked semicircular disk (ECSD) for rapid assessment of fracture toughness using compressive loading. Continuing our earlier work on ECSD, a theoretical examination here leads to a novel way for synthesizing weight functions using two distinct form factors. The efficacy of ECSD mode-I weight function synthesized using displacement and form factor methods is demonstrated by comparing with finite element results. Theory of elasticity in conjunction with finite element method is utilized to analyze crack opening potency of ECSD under eccentric compression to explore newer configurations of ECSD for fracture testing.

Form and Function of Proteins. Historical Background and the Indian Effort in Macromolecular Crystallography

Global efforts in macromolecular crystallography started in the thirties of the last century. However, definitive results began to emerge only in the late fifties and the early sixties. India has a long tradition in crystallography. The country had a head start in theoretical and computational structural biology, thanks to the efforts of G.N. Ramachandran and his colleagues in the fifties and the sixties. However, macromolecular crystallography got off the ground in India only in the eighties, particularly after the Bangalore group received adequate support from the Department of Science and Technology under their Thrust Area Programme. The Bangalore centre was also identified as a national nucleus for the development of the area in the country. Since then work in the area has spread widely and is being carried out by several groups, mainly led by scientists trained at Bangalore or their descendents, in about thirty institutions in India. In addition to the Department of Science and Technology, the effort is now supported by other agencies like the Department of Biotechnology and the Council of Scientific and Industrial Research. The problems addressed by macromolecular crystallographers in India encompass almost all aspects of modern biology. Indian efforts in macromolecular crystallography have also become an important component of the international efforts in the area.

Structure-function hierarchies and von Karman-Howarth relations for turbulence in magnetohydrodynamical equations

We generalize the method of A. M. Polyakov, Phys. Rev. E 52, 6183 (1995)] for obtaining structure-function relations in turbulence in the stochastically forced Burgers equation, to develop structure-function hierarchies for turbulence in three models for magnetohydrodynamics (MHD). These are the Burgers analogs of MHD in one dimension Eur. Phys. J.B 9, 725 (1999)], and in three dimensions (3DMHD and 3D Hall MHD). Our study provides a convenient and unified scheme for the development of structure-function hierarchies for turbulence in a variety of coupled hydrodynamical equations. For turbulence in the three sets of MHD equations mentioned above, we obtain exact relations for third-order structure functions and their derivatives; these expressions are the analogs of the von Karman-Howarth relations for fluid turbulence. We compare our work with earlier studies of such relations in 3DMHD and 3D Hall MHD.

Style and the “Idea” of the sophist after Plato : the impact of form typology on sophistic teaching and writing on interdisciplinary scholarly work

Resumen: Después de la primera sofística, los sofistas actuaron entre el resto de los pensadores del Mediterráneo como un grupo definido. Dado que hay muchos ejemplos que muestran que los sofistas ejercían sus prácticas y que también eran personas comprometidas en otras actividades, vamos a examinar aquí diversos casos de semejanzas y diferencias entre ellos y otros grupos de pensadores. Nuestras tres preguntas fundamentales son: qué, cómo y por qué los sofistas escribían y enseñaban. Intentaremos responder haciendo un análisis diacrónico de las principales formas y géneros de escritura que produjeron (qué). El cómo lo responderemos en su desenvolvimiento como una actividad comunicativa más allá de las fronteras de las disciplinas de la época. El por qué tendrá su respuesta al enfatizar la necesidad de la actividad de los sofistas en la socialización de la época y en la educación de la antigüedad. Al aseverar que el estilo era la idea de los sofistas, ponemos la noción de idea en Platón en el contexto de idea derivado de los sofistas contemporáneos a él y de los sofistas posteriores (segunda sofística) y centramos el foco en la función de visualidad expresada en su concepto de idea desde las obras sofísticas más tempranas en la época de Platón hasta las contribuciones posteriores.

Anaesthetic impairment of immune function is mediated via GABA(A) receptors.

BACKGROUND: GABA(A) receptors are members of the Cys-loop family of neurotransmitter receptors, proteins which are responsible for fast synaptic transmission, and are the site of action of wide range of drugs. Recent work has shown that Cys-loop receptors are present on immune cells, but their physiological roles and the effects of drugs that modify their function in the innate immune system are currently unclear. We are interested in how and why anaesthetics increase infections in intensive care patients; a serious problem as more than 50% of patients with severe sepsis will die. As many anaesthetics act via GABA(A) receptors, the aim of this study was to determine if these receptors are present on immune cells, and could play a role in immunocompromising patients. PRINCIPAL FINDINGS: We demonstrate, using RT-PCR, that monocytes express GABA(A) receptors constructed of α1, α4, β2, γ1 and/or δ subunits. Whole cell patch clamp electrophysiological studies show that GABA can activate these receptors, resulting in the opening of a chloride-selective channel; activation is inhibited by the GABA(A) receptor antagonists bicuculline and picrotoxin, but not enhanced by the positive modulator diazepam. The anaesthetic drugs propofol and thiopental, which can act via GABA(A) receptors, impaired monocyte function in classic immunological chemotaxis and phagocytosis assays, an effect reversed by bicuculline and picrotoxin. SIGNIFICANCE: Our results show that functional GABA(A) receptors are present on monocytes with properties similar to CNS GABA(A) receptors. The functional data provide a possible explanation as to why chronic propofol and thiopental administration can increase the risk of infection in critically ill patients: their action on GABA(A) receptors inhibits normal monocyte behaviour. The data also suggest a potential solution: monocyte GABA(A) receptors are insensitive to diazepam, thus the use of benzodiazepines as an alternative anesthetising agent may be advantageous where infection is a life threatening problem.

Semi-weight function method on computation of stress intensity factors in dissimilar materials

Semi-weight function method is developed to solve the plane problem of two bonded dissimilar materials containing a crack along the bond. From equilibrium equation, stress and strain relationship, conditions of continuity across interface and free crack surface, the stress and displacement fields were obtained. The eigenvalue of these fields is lambda. Semi-weight functions were obtained as virtual displacement and stress fields with eigenvalue-lambda. Integral expression of fracture parameters, K-I and K-II, were obtained from reciprocal work theorem with semi-weight functions and approximate displacement and stress values on any integral path around crack tip. The calculation results of applications show that the semi-weight function method is a simple, convenient and high precision calculation method.

Structure-function studies of serine hydrolases: synthesis of a gene for ∝-lytic protease and the purification and characterization of a mutant β-lactamase

The author has constructed a synthetic gene for ∝-lytic protease. Since the DNA sequence of the protein is not known, the gene was designed by using the reverse translation of ∝-lytic protease's amino acid sequence. Unique restriction sites are carefully sought in the degenerate DNA sequence to aid in future mutagenesis studies. The unique restriction sites are designed approximately 50 base pairs apart and their appropriate codons used in the DNA sequence. The codons used to construct the DNA sequence of ∝-lytic protease are preferred codons in E-coli or used in the production of β-lactamase. Codon usage is also distributed evenly to ensure that one particular codon is not heavily used. The gene is essentially constructed from the outside in. The gene is built in a stepwise fashion using plasmids as the vehicles for the ∝-lytic oligomers. The use of plasmids allows the replication and isolation of large quantities of the intermediates during gene synthesis. The ∝-lytic DNA is a double-stranded oligomer that has sufficient overhang and sticky ends to anneal correctly in the vector. After six steps of incorporating ∝-lytic DNA, the gene is completed and sequenced to ensure that the correct DNA sequence is present and that no mutations occurred in the structural gene.

β-lactamase is the other serine hydrolase studied in this thesis. The author used the class A RTEM-1 β- lactamase encoded on the plasmid pBR322 to investigate the roll of the conserved threonine residue at position 71. Cassette mutagenesis was previously used to generate all possible amino acid substitutions at position 71. The work presented here describes the purification and kinetic characterization of a T71H mutant previously constructed by S. Schultz. The mutated gene was transferred into plasmid pJN for expression and induced with IPTG. The enzyme is purified by column chromatography and FPLC to homogeneity. Kinetic studies reveal that the mutant has lower k_(cat) values on benzylpenicillin, cephalothin and 6-aminopenicillanic acid but no changes in k_m except for cephalothin which is approximately 4 times higher. The mutant did not change siginificantly in its pH profile compared to the wild-type enzyme. Also, the mutant is more sensitive to thermal denaturation as compared to the wild-type enzyme. However, experimental evidence indicates that the probable generation of a positive charge at position 71 thermally stabilized the mutant.

Characterization of the human SCF ubiquitin ligases - structure, function, and regulation

The SCF ubiquitin ligase complex of budding yeast triggers DNA replication by cata lyzi ng ubiquitination of the S phase CDK inhibitor SIC1. SCF is composed of several evolutionarily conserved proteins, including ySKP1, CDC53 (Cullin), and the F-box protein CDC4. We isolated hSKP1 in a two-hybrid screen with hCUL1, the human homologue of CDC53. We showed that hCUL1 associates with hSKP1 in vivo and directly interacts with hSKP1 and the human F-box protein SKP2 in vitro, forming an SCF-Iike particle. Moreover, hCUL1 complements the growth defect of yeast CDC53^(ts) mutants, associates with ubiquitination-promoting activity in human cell extracts, and can assemble into functional, chimeric ubiquitin ligase complexes with yeast SCF components. These data demonstrated that hCUL1 functions as part of an SCF ubiquitin ligase complex in human cells. However, purified human SCF complexes consisting of CUL1, SKP1, and SKP2 are inactive in vitro, suggesting that additional factors are required.

Subsequently, mammalian SCF ubiquitin ligases were shown to regulate various physiological processes by targeting important cellular regulators, like lĸBα, β-catenin, and p27, for ubiquitin-dependent proteolysis by the 26S proteasome. Little, however, is known about the regulation of various SCF complexes. By using sequential immunoaffinity purification and mass spectrometry, we identified proteins that interact with human SCF components SKP2 and CUL1 in vivo. Among them we identified two additional SCF subunits: HRT1, present in all SCF complexes, and CKS1, that binds to SKP2 and is likely to be a subunit of SCF5^(SKP2) complexes. Subsequent work by others demonstrated that these proteins are essential for SCF activity. We also discovered that COP9 Signalosome (CSN), previously described in plants as a suppressor of photomorphogenesis, associates with CUL1 and other SCF subunits in vivo. This interaction is evolutionarily conserved and is also observed with other Cullins, suggesting that all Cullin based ubiquitin ligases are regulated by CSN. CSN regulates Cullin Neddylation presumably through CSNS/JAB1, a stochiometric Signalosome subunit and a putative deneddylating enzyme. This work sheds light onto an intricate connection that exists between signal transduction pathways and protein degradation machinery inside the cell and sets stage for gaining further insights into regulation of protein degradation.

Sequence-function relationships in E. coli transcriptional regulation

Understanding how transcriptional regulatory sequence maps to regulatory function remains a difficult problem in regulatory biology. Given a particular DNA sequence for a bacterial promoter region, we would like to be able to say which transcription factors bind there, how strongly they bind, and whether they interact with each other and/or RNA polymerase, with the ultimate objective of integrating knowledge of these parameters into a prediction of gene expression levels. The theoretical framework of statistical thermodynamics provides a useful framework for doing so, enabling us to predict how gene expression levels depend on transcription factor binding energies and concentrations. We used thermodynamic models, coupled with models of the sequence-dependent binding energies of transcription factors and RNAP, to construct a genotype to phenotype map for the level of repression exhibited by the lac promoter, and tested it experimentally using a set of promoter variants from E. coli strains isolated from different natural environments. For this work, we sought to ``reverse engineer'' naturally occurring promoter sequences to understand how variations in promoter sequence affects gene expression. The natural inverse of this approach is to ``forward engineer'' promoter sequences to obtain targeted levels of gene expression. We used a high precision model of RNAP-DNA sequence dependent binding energy, coupled with a thermodynamic model relating binding energy to gene expression, to predictively design and verify a suite of synthetic E. coli promoters whose expression varied over nearly three orders of magnitude.

However, although thermodynamic models enable predictions of mean levels of gene expression, it has become evident that cell-to-cell variability or ``noise'' in gene expression can also play a biologically important role. In order to address this aspect of gene regulation, we developed models based on the chemical master equation framework and used them to explore the noise properties of a number of common E. coli regulatory motifs; these properties included the dependence of the noise on parameters such as transcription factor binding strength and copy number. We then performed experiments in which these parameters were systematically varied and measured the level of variability using mRNA FISH. The results showed a clear dependence of the noise on these parameters, in accord with model predictions.

Finally, one shortcoming of the preceding modeling frameworks is that their applicability is largely limited to systems that are already well-characterized, such as the lac promoter. Motivated by this fact, we used a high throughput promoter mutagenesis assay called Sort-Seq to explore the completely uncharacterized transcriptional regulatory DNA of the E. coli mechanosensitive channel of large conductance (MscL). We identified several candidate transcription factor binding sites, and work is continuing to identify the associated proteins.