Expert system for the assessment of power transformer insulation condition based on type-2 fuzzy logic systems

An efficient expert system for the power transformer condition assessment is presented in this paper. Through the application of Duval`s triangle and the method of the gas ratios a first assessment of the transformer condition is obtained in the form of a dissolved gas analysis (DGA) diagnosis according IEC 60599. As a second step, a knowledge mining procedure is performed, by conducting surveys whose results are fed into a first Type-2 Fuzzy Logic System (T2-FLS), in order to initially evaluate the condition of the equipment taking only the results of dissolved gas analysis into account. The output of this first T2-FLS is used as the input of a second T2-FLS, which additionally weighs up the condition of the paper-oil system. The output of this last T2-FLS is given in terms of words easily understandable by the maintenance personnel. The proposed assessing methodology has been validated for several cases of transformers in service. (C) 2010 Elsevier Ltd. All rights reserved.

Dynamic Imaging in Electrical Impedance Tomography of the Human Chest With Online Transition Matrix Identification

One of the electrical impedance tomography objectives is to estimate the electrical resistivity distribution in a domain based only on electrical potential measurements at its boundary generated by an imposed electrical current distribution into the boundary. One of the methods used in dynamic estimation is the Kalman filter. In biomedical applications, the random walk model is frequently used as evolution model and, under this conditions, poor tracking ability of the extended Kalman filter (EKF) is achieved. An analytically developed evolution model is not feasible at this moment. The paper investigates the identification of the evolution model in parallel to the EKF and updating the evolution model with certain periodicity. The evolution model transition matrix is identified using the history of the estimated resistivity distribution obtained by a sensitivity matrix based algorithm and a Newton-Raphson algorithm. To numerically identify the linear evolution model, the Ibrahim time-domain method is used. The investigation is performed by numerical simulations of a domain with time-varying resistivity and by experimental data collected from the boundary of a human chest during normal breathing. The obtained dynamic resistivity values lie within the expected values for the tissues of a human chest. The EKF results suggest that the tracking ability is significantly improved with this approach.

A ductile damage criterion at various stress triaxialities

The paper discusses the effect of stress triaxiality on the onset and evolution of damage in ductile metals. A series of tests including shear tests and experiments oil smooth and pre-notched tension specimens wits carried Out for it wide range of stress triaxialities. The underlying continuum damage model is based oil kinematic definition of damage tensors. The modular structure of the approach is accomplished by the decomposition of strain rates into elastic, plastic and damage parts. Free energy functions with respect to fictitious undamaged configurations as well as damaged ones are introduced separately leading to elastic material laws which are affected by increasing damage. In addition, a macroscopic yield condition and a flow rule are used to adequately describe the plastic behavior. Numerical simulations of the experiments are performed and good correlation of tests and numerical results is achieved. Based oil experimental and numerical data the damage criterion formulated in stress space is quantified. Different branches of this function are taken into account corresponding to different damage modes depending oil stress triaxiality and Lode parameter. In addition, identification of material parameters is discussed ill detail. (C) 2007 Elsevier Ltd. All rights reserved.

Robust model predictive controller with output feedback and target tracking

A model predictive controller (MPC) is proposed, which is robustly stable for some classes of model uncertainty and to unknown disturbances. It is considered as the case of open-loop stable systems, where only the inputs and controlled outputs are measured. It is assumed that the controller will work in a scenario where target tracking is also required. Here, it is extended to the nominal infinite horizon MPC with output feedback. The method considers an extended cost function that can be made globally convergent for any finite input horizon considered for the uncertain system. The method is based on the explicit inclusion of cost contracting constraints in the control problem. The controller considers the output feedback case through a non-minimal state-space model that is built using past output measurements and past input increments. The application of the robust output feedback MPC is illustrated through the simulation of a low-order multivariable system.

Identification of protein coding regions using the modified Gabor-wavelet transform

An important topic in genomic sequence analysis is the identification of protein coding regions. In this context, several coding DNA model-independent methods based on the occurrence of specific patterns of nucleotides at coding regions have been proposed. Nonetheless, these methods have not been completely suitable due to their dependence on an empirically predefined window length required for a local analysis of a DNA region. We introduce a method based on a modified Gabor-wavelet transform (MGWT) for the identification of protein coding regions. This novel transform is tuned to analyze periodic signal components and presents the advantage of being independent of the window length. We compared the performance of the MGWT with other methods by using eukaryote data sets. The results show that MGWT outperforms all assessed model-independent methods with respect to identification accuracy. These results indicate that the source of at least part of the identification errors produced by the previous methods is the fixed working scale. The new method not only avoids this source of errors but also makes a tool available for detailed exploration of the nucleotide occurrence.

Molecular dynamics, density functional, ADMET predictions, virtual screening, and molecular interaction field studies for identification and evaluation of novel potential CDK2 inhibitors in cancer therapy

In this work, we have used molecular dynamics, density functional theory, virtual screening, ADMET predictions, and molecular interaction field studies to design and propose eight novel potential inhibitors of CDK2. The eight molecules proposed showed interesting structural characteristics that are required for inhibiting the CDK2 activity and show potential as drug candidates for the treatment of cancer. The parameters related to the Rule of Five were calculated, and only one of the molecules violated more than one parameter. One of the proposals and one of the drug-like compounds selected by virtual screening indicated to be promising candidates for CDK2-based cancer therapy.

Anthropometric-based selection and sprint kayak training in children

A 12 week kayak training programme was evaluated in children who either had or did not have the anthropometric characteristics identified as being unique to senior elite sprint kayakers. Altogether, 234 male and female school children were screened to select 10 children with and 10 children without the identified key anthropometric characteristics. Before and after training, the children completed an all-out 2 min kayak ergometer simulation test; measures of oxygen consumption, plasma lactate and total work accomplished were recorded. In addition, a 500 m time trial was performed at weeks 3 and 12. The coaches were unaware which 20 children possessed those anthropometric characteristics deemed to favour development of kayak ability. All children improved in both the 2 min ergometer simulation test and 500 m time trial. However, boys who were selected according to favourable anthropometric characteristics showed greater improvement than those without such characteristics in the 2 min ergometer test only. In summary, in a small group of children selected according to anthropometric data unique to elite adult kayakers, 12 weeks of intensive kayak training did not influence the rate of improvement of on-water sprint kayak performance.

Analysis of dynamic process models for structural insight and model reduction .1. Structural identification measures

An important consideration in the development of mathematical models for dynamic simulation, is the identification of the appropriate mathematical structure. By building models with an efficient structure which is devoid of redundancy, it is possible to create simple, accurate and functional models. This leads not only to efficient simulation, but to a deeper understanding of the important dynamic relationships within the process. In this paper, a method is proposed for systematic model development for startup and shutdown simulation which is based on the identification of the essential process structure. The key tool in this analysis is the method of nonlinear perturbations for structural identification and model reduction. Starting from a detailed mathematical process description both singular and regular structural perturbations are detected. These techniques are then used to give insight into the system structure and where appropriate to eliminate superfluous model equations or reduce them to other forms. This process retains the ability to interpret the reduced order model in terms of the physico-chemical phenomena. Using this model reduction technique it is possible to attribute observable dynamics to particular unit operations within the process. This relationship then highlights the unit operations which must be accurately modelled in order to develop a robust plant model. The technique generates detailed insight into the dynamic structure of the models providing a basis for system re-design and dynamic analysis. The technique is illustrated on the modelling for an evaporator startup. Copyright (C) 1996 Elsevier Science Ltd

Generation and phenotypic characterization of new human ovarian cancer cell lines with the identification of antigens potentially recognizable by HLA-restricted cytotoxic T cells

This study describes a simple method for long-term establishment of human ovarian tumor lines and prediction of T-cell epitopes that could be potentially useful in the generation of tumor-specific cytotoxic T lymphocytes (CTLs), Nine ovarian tumor lines (INT.Ov) were generated from solid primary or metastatic tumors as well as from ascitic fluid, Notably all lines expressed HLA class I, intercellular adhesion molecule-1 (ICAM-1), polymorphic epithelial mucin (PEM) and cytokeratin (CK), but not HLA class II, B7.1 (CD80) or BAGE, While of the 9 lines tested 4 (INT.Ov1, 2, 5 and 6) expressed the folate receptor (FR-alpha) and 6 (INT.Ov1, 2, 5, 6, 7 and 9) expressed the epidermal growth factor receptor (EGFR); MAGE-1 and p185(HER-2/neu) were only found in 2 lines (INT.Ov1 and 2) and GAGE-1 expression in 1 line (INT.Ov2). The identification of class I MHC ligands and T-cell epitopes within protein antigens was achieved by applying several theoretical methods including: 1) similarity or homology searches to MHCPEP; 2) BIMAS and 3) artificial neural network-based predictions of proteins MACE, GAGE, EGFR, p185(HER-2/neu) and FR-alpha expressed in INT.Ov lines, Because of the high frequency of expression of some of these proteins in ovarian cancer and the ability to determine HLA binding peptides efficiently, it is expected that after appropriate screening, a large cohort of ovarian cancer patients may become candidates to receive peptide based vaccines. (C) 1997 Wiley-Liss, Inc.

Classification model based on Raman spectra of selected morphological and biochemical tissue constituents for identification of atherosclerosis in human coronary arteries

This study presents the results of Raman spectroscopy applied to the classification of arterial tissue based on a simplified model using basal morphological and biochemical information extracted from the Raman spectra of arteries. The Raman spectrograph uses an 830-nm diode laser, imaging spectrograph, and a CCD camera. A total of 111 Raman spectra from arterial fragments were used to develop the model, and those spectra were compared to the spectra of collagen, fat cells, smooth muscle cells, calcification, and cholesterol in a linear fit model. Non-atherosclerotic (NA), fatty and fibrous-fatty atherosclerotic plaques (A) and calcified (C) arteries exhibited different spectral signatures related to different morphological structures presented in each tissue type. Discriminant analysis based on Mahalanobis distance was employed to classify the tissue type with respect to the relative intensity of each compound. This model was subsequently tested prospectively in a set of 55 spectra. The simplified diagnostic model showed that cholesterol, collagen, and adipocytes were the tissue constituents that gave the best classification capability and that those changes were correlated to histopathology. The simplified model, using spectra obtained from a few tissue morphological and biochemical constituents, showed feasibility by using a small amount of variables, easily extracted from gross samples.

Identification and minisequencing-based discrimination of SHV beta-lactamases in nosocomial infection-associated Klebsiella pneumoniae in Brisbane, Australia

Extended-spectrum beta-lactamases (ESBLs) are active against oxyimino cephalosporins and monobactams. Twenty-one Klebsiella pneumoniae isolates obtained between 1991 and 1995 at the Princess Alexandra Hospital in Brisbane, Australia, were subject to amplification and sequencing of the SHV beta-lactamase-encoding genes. Thirteen strains were phenotypically ESBL positive. Of these, six strains carried the bla(SHV-2a) gene and seven strains carried the bla(SHV-12) gene. Eight strains were phenotypically ESBL negative. Of these, seven strains carried the non-ESBL bla(SHV-11) gene and one strain carried the non-ESBL bla(SHV-1) gene. There was complete correspondence between the ESBL phenotype and the presence or absence of an ESBL-encoding gene(s). In addition, it was determined that of the 13 ESBL-positive strains, at least 4 carried copies of a non-ESBL-encoding gene in addition to the bla(SHV-2a) or bla(SHV12) gene. A minisequencing-based assay was developed to discriminate the different SHV classes. This technique, termed first-nucleotide change, involves the identification of the base added to a primer in a single-nucleotide extension reaction. The assay targeted polymorphisms at the first bases of codons 238 and 240 and reliably discriminated ESBL-positive strains from ESBL-negative strains and also distinguished strains carrying bla(SHV-2a) from strains carrying bla(SHV-12). In addition, this method was used to demonstrated an association between the relative copy numbers of bla(SHV) genes in individual strains and the levels of antibiotic resistance.

Analysis of the mouse transcriptome based on functional annotation of 60,770 full-length cDNAs

Only a small proportion of the mouse genome is transcribed into mature messenger RNA transcripts. There is an international collaborative effort to identify all full-length mRNA transcripts from the mouse, and to ensure that each is represented in a physical collection of clones. Here we report the manual annotation of 60,770 full-length mouse complementary DNA sequences. These are clustered into 33,409 'transcriptional units', contributing 90.1% of a newly established mouse transcriptome database. Of these transcriptional units, 4,258 are new protein-coding and 11,665 are new non-coding messages, indicating that non-coding RNA is a major component of the transcriptome. 41% of all transcriptional units showed evidence of alternative splicing. In protein-coding transcripts, 79% of splice variations altered the protein product. Whole-transcriptome analyses resulted in the identification of 2,431 sense-antisense pairs. The present work, completely supported by physical clones, provides the most comprehensive survey of a mammalian transcriptome so far, and is a valuable resource for functional genomics.

Cuticular hydrocarbons of Drosophila birchii and D-serrata: Identification and role in mate choice in D-serrata

The cuticular hydrocarbon compositions of two sympatric species of Australian Drosophila in the montium subgroup of the melanogaster group that use cuticular hydrocarbons in mate recognition have been characterized. Drosophila birchii has 34 components in greater than trace amounts, with a carbon number range of C-20 to C-33. Drosophila serrata has 21 components above trace level and a carbon number range of C-24 to C-31. These two species share eight hydrocarbon components, with all but two of them being monoenes. For both species, the (Z)-9-monoenes are the predominant positional isomer. The hydrocarbons of D. birchii are n-alkanes, n-alkenes (Z)-5-, (Z)-7-, (Z)-9-, and (Z)-11-), low to trace levels of homologous (Z,Z)-7,11- and (Z,Z)-9,13-dienes; and trace amounts of (Z,Z)-5,9- C-25:2, a major component of D. serrata. Only one methyl branched hydrocarbon was detected (2-methyl C-28), and it occurred at very low levels. The hydrocarbons of D. serrata are dominated by a homologous series of (Z,Z)-5,9-dienes, and notably, are characterized by the apparent absence of n-alkanes. Homologous series of (Z)-5-, (Z)-7-, and (Z)-9- alkenes are also present in D. serrata as well as 2-methyl alkanes. Drosophila serrata females display strong directional mate choice based on male cuticular hydrocarbons and prefer D. serrata males with higher relative abundances of the 2-methyl alkanes, but lower relative abundances of (Z,Z)-5,9- C-24:2 and (Z)-9-C-25:1.

Identification of residues and domains of Raf important for function in vivo and in vitro

Random mutagenesis and genetic screens for impaired Raf function in Caenorhabditis elegans were used to identify six loss-of-function alleles of lin-45 raf that result in a substitution of a single amino acid. The mutations were classified as weak, intermediate, and strong based on phenotypic severity. We engineered these mutations into the homologous residues of vertebrate Raf-1 and analyzed the mutant proteins for their underlying biochemical defects. Surprisingly, phenotype strength did not correlate with the catalytic activity of the mutant proteins. Amino acid substitutions Val-589 and Ser-619 severely compromised Raf kinase activity, yet these mutants displayed weak phenotypes in the genetic screen. Interestingly, this is because these mutant Raf proteins efficiently activate the MAPK (mitogen-activated protein kinase) cascade in living cells, a result that may inform the analysis of knockout mice. Equally intriguing was the observation that mutant proteins with non-functional Ras-binding domains, and thereby deficient in Ras-mediated membrane recruitment, displayed only intermediate strength phenotypes. This confirms that secondary mechanisms exist to couple Ras to Raf in vivo. The strongest phenotype in the genetic screens was displayed by a S508N mutation that again did not correlate with a significant loss of kinase activity or membrane recruitment by oncogenic Ras in biochemical assays. Ser-508 lies within the Raf-1 activation loop, and mutation of this residue in Raf-1 and the equivalent Ser-615 in B-Raf revealed that this residue regulates Raf binding to MEK. Further characterization revealed that in response to activation by epidermal growth factor, the Raf-S508N mutant protein displayed both reduced catalytic activity and aberrant activation kinetics: characteristics that may explain the C. elegans phenotype.