Identification of New Zealand bats in flight from analysis of echolocation calls by artificial neural networks.

Time-expanded and heterodyned echolocation calls of the New Zealand long-tailed Chalinolobus tuberculatus and lesser short-tailed bat Mystacina tuberculata were recorded and digitally analysed. Temporal and spectral parameters were measured from time-expanded calls and power spectra generated for both time-expanded and heterodyned calls. Artificial neural networks were trained to classify the calls of both species using temporal and spectral parameters and power spectra as input data. Networks were then tested using data not previously seen. Calls could be unambiguously identified using parameters and power spectra from time-expanded calls. A neural network, trained and tested using power spectra of calls from both species recorded using a heterodyne detector set to 40 kHz (the frequency with the most energy of the fundamental of C. tuberculatus call), could identify 99% and 84% of calls of C. tuberculatus and M. tuberculata, respectively. A second network, trained and tested using power spectra of calls from both species recorded using a heterodyne detector set to 27 kHz (the frequency with the most energy of the fundamental of M. tuberculata call), could identify 34% and 100% of calls of C. tuberculatus and M. tuberculata, respectively. This study represents the first use of neural networks for the identification of bats from their echolocation calls. It is also the first study to use power spectra of time-expanded and heterodyned calls for identification of chiropteran species. The ability of neural networks to identify bats from their echolocation calls is discussed, as is the ecology of both species in relation to the design of their echolocation calls.

Structural identification of a laboratory-based steel through truss cantilevered bridge with suspended span using a layered genetic algorithm with patternsearch step (GAPS)

Structural identification (St-Id) can be considered as the process of updating a finite element (FE) model of a structural system to match the measured response of the structure. This paper presents the St-Id of a laboratory-based steel through-truss cantilevered bridge with suspended span. There are a total of 600 degrees of freedom (DOFs) in the superstructure plus additional DOFs in the substructure. The St-Id of the bridge model used the modal parameters from a preliminary modal test in the objective function of a global optimisation technique using a layered genetic algorithm with patternsearch step (GAPS). Each layer of the St-Id process involved grouping of the structural parameters into a number of updating parameters and running parallel optimisations. The number of updating parameters was increased at each layer of the process. In order to accelerate the optimisation and ensure improved diversity within the population, a patternsearch step was applied to the fittest individuals at the end of each generation of the GA. The GAPS process was able to replicate the mode shapes for the first two lateral sway modes and the first vertical bending mode to a high degree of accuracy and, to a lesser degree, the mode shape of the first lateral bending mode. The mode shape and frequency of the torsional mode did not match very well. The frequencies of the first lateral bending mode, the first longitudinal mode and the first vertical mode matched very well. The frequency of the first sway mode was lower and that of the second sway mode was higher than the true values, indicating a possible problem with the FE model. Improvements to the model and the St-Id process will be presented at the upcoming conference and compared to the results presented in this paper. These improvements will include the use of multiple FE models in a multi-layered, multi-solution, GAPS St-Id approach.

Identification of major loci controlling clinical manifestations of ankylosing spondylitis

Objective. To identify genomic regions linked with determinants of age at symptom onset, disease activity, and functional impairment in ankylosing spondylitis (AS). Methods. A whole genome linkage scan was performed in 188 affected sibling pair families with 454 affected individuals. Traits assessed were age at symptom onset, disease activity assessed by the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), and functional impairment assessed by the Bath Ankylosing Spondylitis Functional Index (BASFI). Parametric and nonparametric quantitative linkage analysis was performed using parameters defined in a previous segregation study. Results. Heritabilities of the traits studied in this data set were as follows: BASDAI 0.49 (P = 0.0001, 95% confidence interval [95% CI] 0.23-0.75), BASFI 0.76 (P = 10-7, 95% CI 0.49-1.0), and age at symptom onset 0.33 (P = 0.005, 95% CI 0.04-0.62). No linkage was observed between the major histocompatibility complex (MHC) and any of the traits studied (logarithm of odds [LOD] score <1.0). "Significant" linkage (LOD score 4.0) was observed between a region on chromosome 18p and the BASDAI. Age at symptom onset showed "suggestive" linkage to chromosome 11p (LOD score 3.3). Maximum linkage with the BASFI was seen at chromosome 2q (LOD score 2.9). Conclusion. In contrast to the genetic determinants of susceptibility to AS, clinical manifestations of the disease measured by the BASDAI, BASFI, and age at symptom onset are largely determined by a small number of genes not encoded within the MHC.

Identification of dynamical systems with fractional derivative damping models using inverse sensitivity analysis

The problem of identifying parameters of time invariant linear dynamical systems with fractional derivative damping models, based on a spatially incomplete set of measured frequency response functions and experimentally determined eigensolutions, is considered. Methods based on inverse sensitivity analysis of damped eigensolutions and frequency response functions are developed. It is shown that the eigensensitivity method requires the development of derivatives of solutions of an asymmetric generalized eigenvalue problem. Both the first and second order inverse sensitivity analyses are considered. The study demonstrates the successful performance of the identification algorithms developed based on synthetic data on one, two and a 33 degrees of freedom vibrating systems with fractional dampers. Limited studies have also been conducted by combining finite element modeling with experimental data on accelerances measured in laboratory conditions on a system consisting of two steel beams rigidly joined together by a rubber hose. The method based on sensitivity of frequency response functions is shown to be more efficient than the eigensensitivity based method in identifying system parameters, especially for large scale systems.

Optimal simultaneous maximum a posterioriestimation of states, noise statistics and parameters II. Numerical performance

A very general and numerically quite robust algorithm has been proposed by Sastry and Gauvrit (1980) for system identification. The present paper takes it up and examines its performance on a real test example. The example considered is the lateral dynamics of an aircraft. This is used as a vehicle for demonstrating the performance of various aspects of the algorithm in several possible modes.

Identification of a class of non-linear systems

This paper considers the on-line identification of a non-linear system in terms of a Hammerstein model, with a zero-memory non-linear gain followed by a linear system. The linear part is represented by a Laguerre expansion of its impulse response and the non-linear part by a polynomial. The identification procedure involves determination of the coefficients of the Laguerre expansion of correlation functions and an iterative adjustment of the parameters of the non-linear gain by gradient methods. The method is applicable to situations involving a wide class of input signals. Even in the presence of additive correlated noise, satisfactory performance is achieved with the variance of the error converging to a value close to the variance of the noise. Digital computer simulation establishes the practicability of the scheme in different situations.

Computational Identification of Recessive Mutations in Cancers using High Throughput SNP-arrays

This thesis presents a highly sensitive genome wide search method for recessive mutations. The method is suitable for distantly related samples that are divided into phenotype positives and negatives. High throughput genotype arrays are used to identify and compare homozygous regions between the cohorts. The method is demonstrated by comparing colorectal cancer patients against unaffected references. The objective is to find homozygous regions and alleles that are more common in cancer patients. We have designed and implemented software tools to automate the data analysis from genotypes to lists of candidate genes and to their properties. The programs have been designed in respect to a pipeline architecture that allows their integration to other programs such as biological databases and copy number analysis tools. The integration of the tools is crucial as the genome wide analysis of the cohort differences produces many candidate regions not related to the studied phenotype. CohortComparator is a genotype comparison tool that detects homozygous regions and compares their loci and allele constitutions between two sets of samples. The data is visualised in chromosome specific graphs illustrating the homozygous regions and alleles of each sample. The genomic regions that may harbour recessive mutations are emphasised with different colours and a scoring scheme is given for these regions. The detection of homozygous regions, cohort comparisons and result annotations are all subjected to presumptions many of which have been parameterized in our programs. The effect of these parameters and the suitable scope of the methods have been evaluated. Samples with different resolutions can be balanced with the genotype estimates of their haplotypes and they can be used within the same study.

A Kalman filter based strategy for linear structural system identification based on multiple static and dynamic test data

The problem of identification of stiffness, mass and damping properties of linear structural systems, based on multiple sets of measurement data originating from static and dynamic tests is considered. A strategy, within the framework of Kalman filter based dynamic state estimation, is proposed to tackle this problem. The static tests consists of measurement of response of the structure to slowly moving loads, and to static loads whose magnitude are varied incrementally; the dynamic tests involve measurement of a few elements of the frequency response function (FRF) matrix. These measurements are taken to be contaminated by additive Gaussian noise. An artificial independent variable τ, that simultaneously parameterizes the point of application of the moving load, the magnitude of the incrementally varied static load and the driving frequency in the FRFs, is introduced. The state vector is taken to consist of system parameters to be identified. The fact that these parameters are independent of the variable τ is taken to constitute the set of ‘process’ equations. The measurement equations are derived based on the mechanics of the problem and, quantities, such as displacements and/or strains, are taken to be measured. A recursive algorithm that employs a linearization strategy based on Neumann’s expansion of structural static and dynamic stiffness matrices, and, which provides posterior estimates of the mean and covariance of the unknown system parameters, is developed. The satisfactory performance of the proposed approach is illustrated by considering the problem of the identification of the dynamic properties of an inhomogeneous beam and the axial rigidities of members of a truss structure.

Novel melody line identification algorithm for polyphonic MIDI music

The problem of automatic melody line identification in a MIDI file plays an important role towards taking QBH systems to the next level. We present here, a novel algorithm to identify the melody line in a polyphonic MIDI file. A note pruning and track/channel ranking method is used to identify the melody line. We use results from musicology to derive certain simple heuristics for the note pruning stage. This helps in the robustness of the algorithm, by way of discarding "spurious" notes. A ranking based on the melodic information in each track/channel enables us to choose the melody line accurately. Our algorithm makes no assumption about MIDI performer specific parameters, is simple and achieves an accuracy of 97% in identifying the melody line correctly. This algorithm is currently being used by us in a QBH system built in our lab.

Nonlinear structural dynamical system identification using adaptive particle filters

The problem of identifying parameters of nonlinear vibrating systems using spatially incomplete, noisy, time-domain measurements is considered. The problem is formulated within the framework of dynamic state estimation formalisms that employ particle filters. The parameters of the system, which are to be identified, are treated as a set of random variables with finite number of discrete states. The study develops a procedure that combines a bank of self-learning particle filters with a global iteration strategy to estimate the probability distribution of the system parameters to be identified. Individual particle filters are based on the sequential importance sampling filter algorithm that is readily available in the existing literature. The paper develops the requisite recursive formulary for evaluating the evolution of weights associated with system parameter states. The correctness of the formulations developed is demonstrated first by applying the proposed procedure to a few linear vibrating systems for which an alternative solution using adaptive Kalman filter method is possible. Subsequently, illustrative examples on three nonlinear vibrating systems, using synthetic vibration data, are presented to reveal the correct functioning of the method. (c) 2007 Elsevier Ltd. All rights reserved.

A particle filtering approach for structural system identification in vehicle–structure interaction problems

The problem of identification of parameters of a beam-moving oscillator system based on measurement of time histories of beam strains and displacements is considered. The governing equations of motion here have time varying coefficients. The parameters to be identified are however time invariant and consist of mass, stiffness and damping characteristics of the beam and oscillator subsystems. A strategy based on dynamic state estimation method, that employs particle filtering algorithms, is proposed to tackle the identification problem. The method can take into account measurement noise, guideway unevenness, spatially incomplete measurements, finite element models for supporting structure and moving vehicle, and imperfections in the formulation of the mathematical models. Numerical illustrations based on synthetic data on beam-oscillator system are presented to demonstrate the satisfactory performance of the proposed procedure.

Identification of Specific DNA Binding Residues in the TCP Family of Transcription Factors in Arabidopsis

The TCP transcription factors control multiple developmental traits in diverse plant species. Members of this family share an similar to 60-residue-long TCP domain that binds to DNA. The TCP domain is predicted to form a basic helix-loop-helix ( bHLH) structure but shares little sequence similarity with canonical bHLH domain. This classifies the TCP domain as a novel class of DNA binding domain specific to the plant kingdom. Little is known about how the TCP domain interacts with its target DNA. We report biochemical characterization and DNA binding properties of a TCP member in Arabidopsis thaliana, TCP4. We have shown that the 58-residue domain of TCP4 is essential and sufficient for binding to DNA and possesses DNA binding parameters comparable to canonical bHLH proteins. Using a yeast-based random mutagenesis screen and site-directed mutants, we identified the residues important for DNA binding and dimer formation. Mutants defective in binding and dimerization failed to rescue the phenotype of an Arabidopsis line lacking the endogenous TCP4 activity. By combining structure prediction, functional characterization of the mutants, and molecular modeling, we suggest a possible DNA binding mechanism for this class of transcription factors.

Using Correlated Parameters for Improved Ranking of Protein-Protein Docking Decoys

A successful protein-protein docking study culminates in identification of decoys at top ranks with near-native quaternary structures. However, this task remains enigmatic because no generalized scoring functions exist that effectively infer decoys according to the similarity to near-native quaternary structures. Difficulties arise because of the highly irregular nature of the protein surface and the significant variation of the nonbonding and solvation energies based on the chemical composition of the protein-protein interface. In this work, we describe a novel method combining an interface-size filter, a regression model for geometric compatibility (based on two correlated surface and packing parameters), and normalized interaction energy (calculated from correlated nonbonded and solvation energies), to effectively rank decoys from a set of 10,000 decoys. Tests on 30 unbound binary protein-protein complexes show that in 16 cases we can identify at least one decoy in top three ranks having <= 10 angstrom backbone root mean square deviation from true binding geometry. Comparisons with other state-of-art methods confirm the improved ranking power of our method without the use of any experiment-guided restraints, evolutionary information, statistical propensities, or modified interaction energy equations. Tests on 118 less-difficult bound binary protein-protein complexes with <= 35% sequence redundancy at the interface showed that in 77% cases, at least 1 in 10,000 decoys were identified with <= 5 angstrom backbone root mean square deviation from true geometry at first rank. The work will promote the use of new concepts where correlations among parameters provide more robust scoring models. It will facilitate studies involving molecular interactions, including modeling of large macromolecular assemblies and protein structure prediction. (C) 2010 Wiley Periodicals, Inc. J Comput Chem 32: 787-796, 2011.

FIR system identification based on subspaces of a higher order cumulant matrix

A new linear algebraic approach for identification of a nonminimum phase FIR system of known order using only higher order (>2) cumulants of the output process is proposed. It is first shown that a matrix formed from a set of cumulants of arbitrary order can be expressed as a product of structured matrices. The subspaces of this matrix are then used to obtain the parameters of the FIR system using a set of linear equations. Theoretical analysis and numerical simulation studies are presented to characterize the performance of the proposed methods.

Identification of the active-site peptide of 2,3-dihydroxybenzoic acid decarboxylase from Aspergillus oryzae

The non-oxidative decarboxylation of aromatic acids is a poorly understood reaction. The transformation of 2,3-dihydroxybenzoic acid to catechol in the fungal metabolism of indole is a prototype of such a reaction. 2,3-Dihydroxybenzoic acid decarboxylase (EC 4.1.1.46) which catalyzes this reaction was purified to homogeneity from anthranilate induced cultures of Aspergillus oryzae using affinity chromatography. The enzyme did not require cofactors like NAD(+), PLP, TPP or metal ions for its activity. There was no spectral evidence for the presence of enzyme bound cofactors. The preparation, which was adjudged homogeneous by the criteria of SDS-PAGE, sedimentation analysis and N-terminal analysis, was characterized for its physicochemical and kinetic parameters. The enzyme was inactivated by group-specific modifiers like diethyl pyrocarbonate (DEPC) and N-ethylmaleimide (NEM). The kinetics of inactivation by DEPC suggested the presence of a single class of essential histidine residues, the second order rate constant of inactivation for which was 12.5 M(-1) min(-1). A single class of cysteine residues was modified by NEM with a second order rate constant of 33 M(-1) min(-1). Substrate analogues protected the enzyme against inactivation by both DEPC and NEM, suggesting the Location of the essential histidine and cysteine to be at the active site of the enzyme. The incorporation of radiolabelled NEM in a differential labelling experiment was 0.73 mol per mol subunit confirming the presence of a single essential cysteine per active-site. Differentially labelled enzyme was enzymatically cleaved and the peptide bearing the label was purified and sequenced. The active-site peptide LLGLAETCK and the N-terminal sequence MLGKIALEEAFALPRFEEKT did not bear any similarity to sequences reported in the Swiss-Prot Protein Sequence Databank, a reflection probably of the unique primary structure of this novel enzyme. The sequences reported in this study will appear in the Swiss-Prot Protein Sequence Databank under the accession number P80402.