Damage detection in a benchmark structure using AR-ARX models and statistical pattern recognition

Structural health monitoring (SHM) is related to the ability of monitoring the state and deciding the level of damage or deterioration within aerospace, civil and mechanical systems. In this sense, this paper deals with the application of a two-step auto-regressive and auto-regressive with exogenous inputs (AR-ARX) model for linear prediction of damage diagnosis in structural systems. This damage detection algorithm is based on the. monitoring of residual error as damage-sensitive indexes, obtained through vibration response measurements. In complex structures there are. many positions under observation and a large amount of data to be handed, making difficult the visualization of the signals. This paper also investigates data compression by using principal component analysis. In order to establish a threshold value, a fuzzy c-means clustering is taken to quantify the damage-sensitive index in an unsupervised learning mode. Tests are made in a benchmark problem, as proposed by IASC-ASCE with different damage patterns. The diagnosis that was obtained showed high correlation with the actual integrity state of the structure. Copyright © 2007 by ABCM.

A structure-activity relationship (SAR) study of neolignan compounds with anti-schistosomiasis activity

Um conjunto de dezoito compostos de neolignanas com atividade antiesquistossomose foi estudado com o método semi-empírico PM3 e outros métodos teóricos com o intuito de avaliar algumas propriedades (variáveis ou descritores) moleculares selecionadas e correlacioná-las com a atividade biológica. Análise exploratória dos dados (análise de componentes principais, PCA, e análise hierárquica de agrupamentos, HCA), análise discriminante (DA) e o método KNN foram utilizados na obtenção de possíveis correlações entre os descritores calculados e a atividade biológica em questão e na predição da atividade antiesquistossimose de algumas moléculas teste. Os descritores moleculares responsáveis pela separação entre os compostos ativos e inativos foram: energia de hidratação (HE), refratividade molecular (MR) e carga sobre o átomo C19 (Q19). Estes descritores fornecem informações a respeito do tipo de interação que pode ocorrer entre os compostos e seu respectivo receptor biológico. Após a construção do modelo para compostos ativos e inativos, os métodos PCA, HCA, DA e KNN foram empregados em um estudo de predição. Foram estudados 10 novos compostos e somente 5 deles foram classificados como ativos contra esquistossomose.

Assessment of in vitro sperm characteristics and their importance in the prediction of conception rate in a bovine timed-AI program

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Novel inorganic pyrophosphatase from soil metagenomic and family and subfamily prediction

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Prediction of genomic-enabled breeding values and genome-wide association study for feedlot average daily weight gain in Nelore cattle

Pós-graduação em Genética e Melhoramento Animal - FCAV

Structure of the N=50 As, Ge, Ga nuclei

The level structures of the N = 50 As-83, Ge-82, and Ga-81 isotones have been investigated by means of multi-nucleon transfer reactions. A first experiment was performed with the CLARA PRISMA setup to identify these nuclei. A second experiment was carried out with the GASP array in order to deduce the gamma-ray coincidence information. The results obtained on the high-spin states of such nuclei are used to test the stability of the N = 50 shell closure in the region of Ni-78 (Z = 28). The comparison of the experimental level schemes with the shell-model calculations yields an N = 50 energy gap value of 4.7(3) MeV at Z = 28. This value, in a good agreement with the prediction of the finite-range liquid-drop model as well as with the recent large-scale shell model calculations, does not support a weakening of the N = 50 shell gap down to Z = 28. (c) 2012 Elsevier B.V. All rights reserved.

Relationship between global structural parameters and Enzyme Commission hierarchy: Implications for function prediction

In protein databases there is a substantial number of proteins structurally determined but without function annotation. Understanding the relationship between function and structure can be useful to predict function on a large scale. We have analyzed the similarities in global physicochemical parameters for a set of enzymes which were classified according to the four Enzyme Commission (EC) hierarchical levels. Using relevance theory we introduced a distance between proteins in the space of physicochemical characteristics. This was done by minimizing a cost function of the metric tensor built to reflect the EC classification system. Using an unsupervised clustering method on a set of 1025 enzymes, we obtained no relevant clustering formation compatible with EC classification. The distance distributions between enzymes from the same EC group and from different EC groups were compared by histograms. Such analysis was also performed using sequence alignment similarity as a distance. Our results suggest that global structure parameters are not sufficient to segregate enzymes according to EC hierarchy. This indicates that features essential for function are rather local than global. Consequently, methods for predicting function based on global attributes should not obtain high accuracy in main EC classes prediction without relying on similarities between enzymes from training and validation datasets. Furthermore, these results are consistent with a substantial number of studies suggesting that function evolves fundamentally by recruitment, i.e., a same protein motif or fold can be used to perform different enzymatic functions and a few specific amino acids (AAs) are actually responsible for enzyme activity. These essential amino acids should belong to active sites and an effective method for predicting function should be able to recognize them. (C) 2012 Elsevier Ltd. All rights reserved.

Identification of novel components of NAD-utilizing metabolic pathways and prediction of their biochemical functions

Nicotinamide adenine dinucleotide (NAD) is a ubiquitous cofactor participating in numerous redox reactions. It is also a substrate for regulatory modifications of proteins and nucleic acids via the addition of ADP-ribose moieties or removal of acyl groups by transfer to ADP-ribose. In this study, we use in-depth sequence, structure and genomic context analysis to uncover new enzymes and substrate-binding proteins in NAD-utilizing metabolic and macromolecular modification systems. We predict that Escherichia coli YbiA and related families of domains from diverse bacteria, eukaryotes, large DNA viruses and single strand RNA viruses are previously unrecognized components of NAD-utilizing pathways that probably operate on ADP-ribose derivatives. Using contextual analysis we show that some of these proteins potentially act in RNA repair, where NAD is used to remove 2'-3' cyclic phosphodiester linkages. Likewise, we predict that another family of YbiA-related enzymes is likely to comprise a novel NAD-dependent ADP-ribosylation system for proteins, in conjunction with a previously unrecognized ADP-ribosyltransferase. A similar ADP-ribosyltransferase is also coupled with MACRO or ADP-ribosylglycohydrolase domain proteins in other related systems, suggesting that all these novel systems are likely to comprise pairs of ADP-ribosylation and ribosylglycohydrolase enzymes analogous to the DraG-DraT system, and a novel group of bacterial polymorphic toxins. We present evidence that some of these coupled ADP-ribosyltransferases/ribosylglycohydrolases are likely to regulate certain restriction modification enzymes in bacteria. The ADP-ribosyltransferases found in these, the bacterial polymorphic toxin and host-directed toxin systems of bacteria such as Waddlia also throw light on the evolution of this fold and the origin of eukaryotic polyADP-ribosyltransferases and NEURL4-like ARTs, which might be involved in centrosomal assembly. We also infer a novel biosynthetic pathway that might be involved in the synthesis of a nicotinate-derived compound in conjunction with an asparagine synthetase and AMPylating peptide ligase. We use the data derived from this analysis to understand the origin and early evolutionary trajectories of key NAD-utilizing enzymes and present targets for future biochemical investigations.

A fragment-based approach for the in silico prediction of blood-brain barrier permeation

Blood-brain barrier (BBB) permeation is an essential property for drugs that act in the central nervous system (CNS) for the treatment of human diseases, such as epilepsy, depression, Alzheimer's disease, Parkinson disease, schizophrenia, among others. In the present work, quantitative structure-property relationship (QSPR) studies were conducted for the development and validation of in silico models for the prediction of BBB permeation. The data set used has substantial chemical diversity and a relatively wide distribution of property values. The generated QSPR models showed good statistical parameters and were successfully employed for the prediction of a test set containing 48 compounds. The predictive models presented herein are useful in the identification, selection and design of new drug candidates having improved pharmacokinetic properties.

Theoretical studies of Membrane Proteins : Properties, Prediction Methods and Genome-wide analysis

Membrane proteins are a large and important class of proteins. They are responsible for several of the key functions in a living cell, e.g. transport of nutrients and ions, cell-cell signaling, and cell-cell adhesion. Despite their importance it has not been possible to study their structure and organization in much detail because of the difficulty to obtain 3D structures. In this thesis theoretical studies of membrane protein sequences and structures have been carried out by analyzing existing experimental data. The data comes from several sources including sequence databases, genome sequencing projects, and 3D structures. Prediction of the membrane spanning regions by hydrophobicity analysis is a key technique used in several of the studies. A novel method for this is also presented and compared to other methods. The primary questions addressed in the thesis are: What properties are common to all membrane proteins? What is the overall architecture of a membrane protein? What properties govern the integration into the membrane? How many membrane proteins are there and how are they distributed in different organisms? Several of the findings have now been backed up by experiments. An analysis of the large family of G-protein coupled receptors pinpoints differences in length and amino acid composition of loops between proteins with and without a signal peptide and also differences between extra- and intracellular loops. Known 3D structures of membrane proteins have been studied in terms of hydrophobicity, distribution of secondary structure and amino acid types, position specific residue variability, and differences between loops and membrane spanning regions. An analysis of several fully and partially sequenced genomes from eukaryotes, prokaryotes, and archaea has been carried out. Several differences in the membrane protein content between organisms were found, the most important being the total number of membrane proteins and the distribution of membrane proteins with a given number of transmembrane segments. Of the properties that were found to be similar in all organisms, the most obvious is the bias in the distribution of positive charges between the extra- and intracellular loops. Finally, an analysis of homologues to membrane proteins with known topology uncovered two related, multi-spanning proteins with opposite predicted orientations. The predicted topologies were verified experimentally, providing a first example of "divergent topology evolution".

Pore structure and column efficiency of silica monoliths in high performance liquid chromatography (HPLC)

Five different methods were critically examined to characterize the pore structure of the silica monoliths. The mesopore characterization was performed using: a) the classical BJH method of nitrogen sorption data, which showed overestimated values in the mesopore distribution and was improved by using the NLDFT method, b) the ISEC method implementing the PPM and PNM models, which were especially developed for monolithic silicas, that contrary to the particulate supports, demonstrate the two inflection points in the ISEC curve, enabling the calculation of pore connectivity, a measure for the mass transfer kinetics in the mesopore network, c) the mercury porosimetry using a new recommended mercury contact angle values. rnThe results of the characterization of mesopores of monolithic silica columns by the three methods indicated that all methods were useful with respect to the pore size distribution by volume, but only the ISEC method with implemented PPM and PNM models gave the average pore size and distribution based on the number average and the pore connectivity values.rnThe characterization of the flow-through pore was performed by two different methods: a) the mercury porosimetry, which was used not only for average flow-through pore value estimation, but also the assessment of entrapment. It was found that the mass transfer from the flow-through pores to mesopores was not hindered in case of small sized flow-through pores with a narrow distribution, b) the liquid penetration where the average flow-through pore values were obtained via existing equations and improved by the additional methods developed according to Hagen-Poiseuille rules. The result was that not the flow-through pore size influences the column bock pressure, but the surface area to volume ratio of silica skeleton is most decisive. Thus the monolith with lowest ratio values will be the most permeable. rnThe flow-through pore characterization results obtained by mercury porosimetry and liquid permeability were compared with the ones from imaging and image analysis. All named methods enable a reliable characterization of the flow-through pore diameters for the monolithic silica columns, but special care should be taken about the chosen theoretical model.rnThe measured pore characterization parameters were then linked with the mass transfer properties of monolithic silica columns. As indicated by the ISEC results, no restrictions in mass transfer resistance were noticed in mesopores due to their high connectivity. The mercury porosimetry results also gave evidence that no restrictions occur for mass transfer from flow-through pores to mesopores in the small scaled silica monoliths with narrow distribution. rnThe prediction of the optimum regimes of the pore structural parameters for the given target parameters in HPLC separations was performed. It was found that a low mass transfer resistance in the mesopore volume is achieved when the nominal diameter of the number average size distribution of the mesopores is appr. an order of magnitude larger that the molecular radius of the analyte. The effective diffusion coefficient of an analyte molecule in the mesopore volume is strongly dependent on the value of the nominal pore diameter of the number averaged pore size distribution. The mesopore size has to be adapted to the molecular size of the analyte, in particular for peptides and proteins. rnThe study on flow-through pores of silica monoliths demonstrated that the surface to volume of the skeletons ratio and external porosity are decisive for the column efficiency. The latter is independent from the flow-through pore diameter. The flow-through pore characteristics by direct and indirect approaches were assessed and theoretical column efficiency curves were derived. The study showed that next to the surface to volume ratio, the total porosity and its distribution of the flow-through pores and mesopores have a substantial effect on the column plate number, especially as the extent of adsorption increases. The column efficiency is increasing with decreasing flow through pore diameter, decreasing with external porosity, and increasing with total porosity. Though this tendency has a limit due to heterogeneity of the studied monolithic samples. We found that the maximum efficiency of the studied monolithic research columns could be reached at a skeleton diameter of ~ 0.5 µm. Furthermore when the intention is to maximize the column efficiency, more homogeneous monoliths should be prepared.rn

Structure property relations in complex copolymer systems

A thorough investigation was made of the structure-property relation of well-defined statistical, gradient and block copolymers of various compositions. Among the copolymers studied were those which were synthesized using isobornyl acrylate (IBA) and n-butyl acrylate (nBA) monomer units. The copolymers exhibited several unique properties that make them suitable materials for a range of applications. The thermomechanical properties of these new materials were compared to acrylate homopolymers. By the proper choice of the IBA/nBA monomer ratio, it was possible to tune the glass transition temperature of the statistical P(IBA-co-nBA) copolymers. The measured Tg’s of the copolymers with different IBA/nBA monomer ratios followed a trend that fitted well with the Fox equation prediction. While statistical copolymers showed a single glass transition (Tg between -50 and 90 ºC depending on composition), DSC block copolymers showed two Tg’s and the gradient copolymer showed a single, but very broad, glass transition. PMBL-PBA-PMBL triblock copolymers of different composition ratios were also studied and revealed a microphase separated morphology of mostly cylindrical PMBL domains hexagonally arranged in the PBA matrix. DMA studies confirmed the phase separated morphology of the copolymers. Tensile studies showed the linear PMBL-PBA-PMBL triblock copolymers having a relatively low elongation at break that was increased by replacing the PMBL hard blocks with the less brittle random PMBL-r-PMMA blocks. The 10- and 20-arm PBA-PMBL copolymers which were studied revealed even more unique properties. SAXS results showed a mixture of cylindrical PMBL domains hexagonally arranged in the PBA matrix, as well as lamellar. Despite PMBL’s brittleness, the triblock and multi-arm PBA-PMBL copolymers could become suitable materials for high temperature applications due to PMBL’s high glass transition temperature and high thermal stability. The structure-property relation of multi-arm star PBA-PMMA block copolymers was also investigated. Small-angle X-ray scattering revealed a phase separated morphology of cylindrical PMMA domains hexagonally arranged in the PBA matrix. DMA studies found that these materials possess typical elastomeric behavior in a broad range of service temperatures up to at least 250°C. The ultimate tensile strength and the elastic modulus of the 10- and 20-arm star PBA-PMMA block copolymers are significantly higher than those of their 3-arm or linear ABA type counterparts with similar composition, indicating a strong effect of the number of arms on the tensile properties. Siloxane-based copolymers were also studied and one of the main objectives here was to examine the possibility to synthesize trifluoropropyl-containing siloxane copolymers of gradient distribution of trifluoropropyl groups along the chain. DMA results of the PDMS-PMTFPS siloxane copolymers synthesized via simultaneous copolymerization showed that due to the large difference in reactivity rates of 2,4,6-tris(3,3,3-trifluoropropyl)-2,4,6-trimethylcyclotrisiloxane (F) and hexamethylcyclotrisiloxane (D), a copolymer of almost block structure containing only a narrow intermediate fragment with gradient distribution of the component units was obtained. A more dispersed distribution of the trifluoropropyl groups was obtained by the semi-batch copolymerization process, as the DMA results revealed more ‘‘pure gradient type’’ features for the siloxane copolymers which were synthesized by adding F at a controlled rate to the polymerization of the less reactive D. As with trifluoropropyl-containing siloxane copolymers, vinyl-containing polysiloxanes may be converted to a variety of useful polysiloxane materials by chemical modification. But much like the trifluoropropyl-containing siloxane copolymers, as a result of so much difference in the reactivities between the component units 2,4,6-trivinyl-2,4,6-trimethylcyclotrisiloxane (V) and hexamethylcyclotrisiloxane (D), thermal and mechanical properties of the PDMS-PMVS copolymers obtained by simultaneous copolymerization was similar to those of block copolymers. Only the copolymers obtained by semi-batch method showed properties typical for gradient copolymers.

Learning with Kernels on Graphs: DAG-based kernels, data streams and RNA function prediction.

In many application domains data can be naturally represented as graphs. When the application of analytical solutions for a given problem is unfeasible, machine learning techniques could be a viable way to solve the problem. Classical machine learning techniques are defined for data represented in a vectorial form. Recently some of them have been extended to deal directly with structured data. Among those techniques, kernel methods have shown promising results both from the computational complexity and the predictive performance point of view. Kernel methods allow to avoid an explicit mapping in a vectorial form relying on kernel functions, which informally are functions calculating a similarity measure between two entities. However, the definition of good kernels for graphs is a challenging problem because of the difficulty to find a good tradeoff between computational complexity and expressiveness. Another problem we face is learning on data streams, where a potentially unbounded sequence of data is generated by some sources. There are three main contributions in this thesis. The first contribution is the definition of a new family of kernels for graphs based on Directed Acyclic Graphs (DAGs). We analyzed two kernels from this family, achieving state-of-the-art results from both the computational and the classification point of view on real-world datasets. The second contribution consists in making the application of learning algorithms for streams of graphs feasible. Moreover,we defined a principled way for the memory management. The third contribution is the application of machine learning techniques for structured data to non-coding RNA function prediction. In this setting, the secondary structure is thought to carry relevant information. However, existing methods considering the secondary structure have prohibitively high computational complexity. We propose to apply kernel methods on this domain, obtaining state-of-the-art results.

Structure and properties of quaternary and tetragonal Heusler compounds for spintronics and spin transfer torque applications

Diese Dissertation ist in zwei Teile aufgeteilt: Teil 1 befasst sich mit der Vorhersage von Halb-Metallizität in quarternären Heuslerverbindungen und deren Potential für Spintronik-Anwendungen. Teil 2 befasst sich mit den strukturellen Eigenschaften der Mn2-basierenden Heuslerverbindungen und dem Tuning von ihrer magnetischen Eigenschaften bzgl. Koerzitivfeldstärke und Remanenz. Diese Verbindungen sind geeignet für Spin-Transfer Torque-Anwendungen.rnrnIn Teil 1 wurden die folgenden drei Probenserien quarternärer Heuslerverbindungen untersucht: XX´MnGa (X = Cu, Ni und X´ = Fe, Co), CoFeMnZ (Z = Al, Ga, Si, Ge) und Co2−xRhxMnZ (Z = Ga, Sn, Sb). Abgesehen von CuCoMnGa wurden alle diese Verbindungen mittels ab-initio Bandstrukturrechnungen als halbmetallische Ferromagnete prognostiziert. In der XX´MnGa-Verbindungsklasse besitzt NiFeMnGa zwar eine zu niedrige Curie-Temperatur für technologische Anwendungen, jedoch NiCoMnGa mit seiner hohen Spinpolarisation, einem hohen magnetischen Moment und einer hohen Curie-Temperatur stellt ein neues Material für Spintronik-Anwendungen dar. Alle CoFeMnZ-Verbindungen kristallisieren in der kubischen Heuslerstruktur und ihre magnetischen Momente folgen der Slater-Pauling-Regel, was Halbmetalizität und eine hohe Spinpolarisation impliziert. Die ebenfalls hohen Curie-Temperaturen ermöglichen einen Einsatz weit über Raumtemperatur hinaus. In der strukturellen Charakterisierung wurde festgestellt, dass sämtliche Co2−xRhxMnZ abgesehen von CoRhMnSn verschiedene Typen von Unordnung aufweisen; daher war die ermittelte Abweichung von der Slater-Pauling-Regel sowie von der 100%-igen Spinpolarisation dieser Verbindungen zu erwarten. Die Halbmetallizität der geordneten CoRhMnSn-Verbindung sollte nach den durchgeführten magnetischen Messungen vorhanden sein.rnrnIm zweiten Teil wurden Mn3−xCoxGa und Mn2−xRh1+xSn synthetisiert und charakterisiert. Es wurde gezeigt, dass Mn3−xCoxGa im Bereich x = 0.1 − 0.4 in einer tetragonal verzerrten inversen Heuslerstruktur kristallisiert und im Bereich x = 0.6−1 in einer kubisch inversen Heuslerstruktur. Während die tetragonalen Materialien hartmagnetisch sind und Charakeristika aufweisen, die typischerweise für Spin-Transfer Torque-Anwengungen attraktiv sind, repräsentieren die weichmagnetischen kubischen Vertreter die 100% spinpolarisierten Materialien, die der Slater-Pauling-Regel folgen. Mn2RhSn kristallisiert in der inversen tetragonal verzerrten Heuslerstruktur, weist einernhartmagnetische Hystereseschleife auf und folgt nicht der Slater-Pauling-Regel. Bei hohen Rh-Gehalt wird die kubische inverse Heuslerstruktur gebildet. Alle kubischen Proben sind weichmagnetisch und folgen der Slater-Pauling-Regel.

Microemulsion: prediction of the phase diagram with a modified Helfrich free energy

Microemulsions are thermodynamically stable, macroscopically homogeneous but microscopically heterogeneous, mixtures of water and oil stabilised by surfactant molecules. They have unique properties like ultralow interfacial tension, large interfacial area and the ability to solubilise other immiscible liquids. Depending on the temperature and concentration, non-ionic surfactants self assemble to micelles, flat lamellar, hexagonal and sponge like bicontinuous morphologies. Microemulsions have three different macroscopic phases (a) 1phase- microemulsion (isotropic), (b) 2phase-microemulsion coexisting with either expelled water or oil and (c) 3phase- microemulsion coexisting with expelled water and oil.rnrnOne of the most important fundamental questions in this field is the relation between the properties of the surfactant monolayer at water-oil interface and those of microemulsion. This monolayer forms an extended interface whose local curvature determines the structure of the microemulsion. The main part of my thesis deals with the quantitative measurements of the temperature induced phase transitions of water-oil-nonionic microemulsions and their interpretation using the temperature dependent spontaneous curvature [c0(T)] of the surfactant monolayer. In a 1phase- region, conservation of the components determines the droplet (domain) size (R) whereas in 2phase-region, it is determined by the temperature dependence of c0(T). The Helfrich bending free energy density includes the dependence of the droplet size on c0(T) as