Mode matches and their locations in the hydrophobic free energy sequences of peptide ligands and their receptor eigenfunctions

Patterns in sequences of amino acid hydrophobic free energies predict secondary structures in proteins. In protein folding, matches in hydrophobic free energy statistical wavelengths appear to contribute to selective aggregation of secondary structures in “hydrophobic zippers.” In a similar setting, the use of Fourier analysis to characterize the dominant statistical wavelengths of peptide ligands’ and receptor proteins’ hydrophobic modes to predict such matches has been limited by the aliasing and end effects of short peptide lengths, as well as the broad-band, mode multiplicity of many of their frequency (power) spectra. In addition, the sequence locations of the matching modes are lost in this transformation. We make new use of three techniques to address these difficulties: (i) eigenfunction construction from the linear decomposition of the lagged covariance matrices of the ligands and receptors as hydrophobic free energy sequences; (ii) maximum entropy, complex poles power spectra, which select the dominant modes of the hydrophobic free energy sequences or their eigenfunctions; and (iii) discrete, best bases, trigonometric wavelet transformations, which confirm the dominant spectral frequencies of the eigenfunctions and locate them as (absolute valued) moduli in the peptide or receptor sequence. The leading eigenfunction of the covariance matrix of a transmembrane receptor sequence locates the same transmembrane segments seen in n-block-averaged hydropathy plots while leaving the remaining hydrophobic modes unsmoothed and available for further analyses as secondary eigenfunctions. In these receptor eigenfunctions, we find a set of statistical wavelength matches between peptide ligands and their G-protein and tyrosine kinase coupled receptors, ranging across examples from 13.10 amino acids in acid fibroblast growth factor to 2.18 residues in corticotropin releasing factor. We find that the wavelet-located receptor modes in the extracellular loops are compatible with studies of receptor chimeric exchanges and point mutations. A nonbinding corticotropin-releasing factor receptor mutant is shown to have lost the signatory mode common to the normal receptor and its ligand. Hydrophobic free energy eigenfunctions and their transformations offer new quantitative physical homologies in database searches for peptide-receptor matches.

Métodos de adequação e diagnóstico em modelos de sobrevivência dinâmicos

A análise de dados de sobrevivência tem sido tradicionalmente baseada no modelo de regressão de Cox (COX, 1972). No entanto, a suposição de taxas de falha proporcionais assumida para esse modelo pode não ser atendida em diversas situações práticas. Essa restrição do modelo de Cox tem gerado interesse em abordagens alternativas, dentre elas os modelos dinâmicos que permitem efeito das covariáveis variando no tempo. Neste trabalho, foram revisados os principais modelos de sobrevivência dinâmicos com estrutura aditiva e multiplicativa nos contextos não paramétrico e semiparamétrico. Métodos gráficos baseados em resíduos foram apresentados com a finalidade de avaliar a qualidade de ajuste desses modelos. Uma versão tempo-dependente da área sob a curva ROC, denotada por AUC(t), foi proposta com a finalidade de avaliar e comparar a qualidade de predição entre modelos de sobrevivência com estruturas aditiva e multiplicativa. O desempenho da AUC(t) foi avaliado por meio de um estudo de simulação. Dados de três estudos descritos na literatura foram também analisados para ilustrar ou complementar os cenários que foram considerados no estudo de simulação. De modo geral, os resultados obtidos indicaram que os métodos gráficos apresentados para avaliar a adequação dos modelos em conjunto com a AUC(t) se constituem em um conjunto de ferramentas estatísticas úteis para o próposito de avaliar modelos de sobrevivência dinâmicos nos contextos não paramétrico e semiparamétrico. Além disso, a aplicação desse conjunto de ferramentas em alguns conjuntos de dados evidenciou que se, por um lado, os modelos dinâmicos são atrativos por permitirem covariáveis tempo-dependentes, por outro lado podem não ser apropriados para todos os conjuntos de dados, tendo em vista que estimação pode apresentar restrições para alguns deles.

Human Motion Analysis Based on Sequential Modeling of Radar Signal and Stereo Image Features

Falls are one of the greatest threats to elderly health in their daily living routines and activities. Therefore, it is very important to detect falls of an elderly in a timely and accurate manner, so that immediate response and proper care can be provided, by sending fall alarms to caregivers. Radar is an effective non-intrusive sensing modality which is well suited for this purpose, which can detect human motions in all types of environments, penetrate walls and fabrics, preserve privacy, and is insensitive to lighting conditions. Micro-Doppler features are utilized in radar signal corresponding to human body motions and gait to detect falls using a narrowband pulse-Doppler radar. Human motions cause time-varying Doppler signatures, which are analyzed using time-frequency representations and matching pursuit decomposition (MPD) for feature extraction and fall detection. The extracted features include MPD features and the principal components of the time-frequency signal representations. To analyze the sequential characteristics of typical falls, the extracted features are used for training and testing hidden Markov models (HMM) in different falling scenarios. Experimental results demonstrate that the proposed algorithm and method achieve fast and accurate fall detections. The risk of falls increases sharply when the elderly or patients try to exit beds. Thus, if a bed exit can be detected at an early stage of this motion, the related injuries can be prevented with a high probability. To detect bed exit for fall prevention, the trajectory of head movements is used for recognize such human motion. A head detector is trained using the histogram of oriented gradient (HOG) features of the head and shoulder areas from recorded bed exit images. A data association algorithm is applied on the head detection results to eliminate head detection false alarms. Then the three dimensional (3D) head trajectories are constructed by matching scale-invariant feature transform (SIFT) keypoints in the detected head areas from both the left and right stereo images. The extracted 3D head trajectories are used for training and testing an HMM based classifier for recognizing bed exit activities. The results of the classifier are presented and discussed in the thesis, which demonstrates the effectiveness of the proposed stereo vision based bed exit detection approach.

Sintonia automática do filtro de kalman unscented.

O filtro de Kalman estendido tem sido a mais popular ferramenta de filtragem não linear das últimas quatro décadas. É de fácil implementação e apresenta baixo custo computacional. Nos casos nos quais as não linearidades do sistema dinâmico são significativas, porém, o filtro de Kalman estendido pode apresentar resultados insatisfatórios. Nessas situações, o filtro de Kalman unscented substitui com vantagens o filtro de Kalman estendido, pois pode apresentar melhores estimativas de estado, embora ambos os filtros exibam complexidade computacional de mesma ordem. A qualidade das estimativas de estado do filtro unscented está intimamente ligada à sintonia dos parâmetros que controlam a transformada unscented. A versão escalada dessa transformada exibe três parâmetros escalares que determinam o posicionamento dos pontos sigma e, consequentemente, afetam diretamente a qualidade das estimativas produzidas pelo filtro. Apesar da importância do filtro de Kalman unscented, a sintonia ótima desses parâmetros é um problema para o qual ainda não há solução definitiva. Não há nem mesmo recomendações heurísticas que garantam o bom funcionamento do filtro unscented na maior parte dos problemas tratáveis por meio de filtros Gaussianos. Essa carência e a importância desse filtro para a área de filtragem não linear fazem da busca por mecanismos de sintonia automática do filtro unscented área de pesquisa ativa. Assim, este trabalho propõe técnicas para sintonia automática dos parâmetros da transformada unscented escalada. Além da sintonia desses parâmetros, também é abordado o problema de sintonizar as matrizes de covariância dos ruídos de processo e de medida demandadas pelo modelo do sistema dinâmico usado pelo filtro unscented. As técnicas propostas cobrem então a sintonia automática de todos os parâmetros do filtro.

Modelagem e análise de desempenho de sistema para geração de energia elétrica através de ondas marítimas.

Mediante a crescente necessidade de aumento na oferta de energia elétrica devido à constante elevação na demanda mundial, esta dissertação avalia o desempenho de um sistema conversor de energia de ondas marítimas em energia elétrica. O sistema em análise é o de coluna de água oscilante com turbina de dupla ação instalado na costa. Utiliza-se um modelo regular de ondas como perturbação à dinâmica de uma câmara semi-submersa gerando fluxo de ar através de uma turbina à ar de dupla ação. O sistema final é não linear e com parâmetros variantes no tempo. A dissertação investiga possibilidades para o aumento do rendimento da turbina em diferentes condições de mar através do método de simulação numérica. Após a modelagem física e matemática do sistema escolhido, inicia-se a síntese de um controlador proporcional derivativo para controle da pressão de ar na turbina em torno da pressão ideal de trabalho da mesma. A análise inclui o comparativo entre os resultados do sistema com e sem controlador e a avaliação de robustez utilizando ondas com amplitude variável. O trabalho apresenta ainda propostas de otimização do sistema para trabalhar em condições similares a região de Pecém no Brasil. Pelos resultados obtidos nas simulações, conclui-se que o rendimento e a robustez do sistema podem melhorar utilizando um sistema controlado. O rendimento do sistema poderá ainda ser otimizado para a região de instalação.

Australian water mass variations from GRACE data linked to Indo-Pacific climate variability

Time-variable gravity data from the Gravity Recovery And Climate Experiment (GRACE) mission are used to study total water content over Australia for the period 2002–2010. A time-varying annual signal explains 61% of the variance of the data, in good agreement with two independent estimates of the same quantity from hydrological models. Water mass content variations across Australia are linked to Pacific and Indian Ocean variability, associated with El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), respectively. From 1989, positive (negative) IOD phases were related to anomalously low (high) precipitation in southeastern Australia, associated with a reduced (enhanced) tropical moisture flux. In particular, the sustained water mass content reduction over central and southern regions of Australia during the period 2006–2008 is associated with three consecutive positive IOD events.

Inflation persistence in Central and Eastern European countries. Bruegel Working Paper 2013/04, 22 July 2013

This paper studies inflation persistence with time-varying coefficient autoregressions for twelve central European countries,in comparison with the United States and the euro area. Inflation persistence tends to be higher in times of high inflation. Since the oil price shocks, inflation persistence has declined both in the US and euro-area. In most central and eastern European countries, for which our study covers 1993-2012, inflation persistence has also declined, with the main exceptions of the Czech Republic, Slovakia and Slovenia, where persistence seems to be rather stable.

Phase relationships between orbital forcing and the composition of air trapped in Antarctic ice cores

Orbital tuning is central for ice core chronologies beyond annual layer counting, available back to 60 ka (i.e. thousands of years before 1950) for Greenland ice cores. While several complementary orbital tuning tools have recently been developed using δ¹⁸Oatm, δO₂⁄N₂ and air content with different orbital targets, quantifying their uncertainties remains a challenge. Indeed, the exact processes linking variations of these parameters, measured in the air trapped in ice, to their orbital targets are not yet fully understood. Here, we provide new series of δO₂∕N₂ and δ¹⁸Oatm data encompassing Marine Isotopic Stage (MIS) 5 (between 100 and 160 ka) and the oldest part (340–800 ka) of the East Antarctic EPICA Dome C (EDC) ice core. For the first time, the measurements over MIS 5 allow an inter-comparison of δO₂∕N₂ and δ¹⁸Oatm records from three East Antarctic ice core sites (EDC, Vostok and Dome F). This comparison highlights some site-specific δO₂∕N₂ variations. Such an observation, the evidence of a 100 ka periodicity in the δO₂∕N₂ signal and the difficulty to identify extrema and mid-slopes in δO2∕N2 increase the uncertainty associated with the use of δO₂∕N₂ as an orbital tuning tool, now calculated to be 3–4 ka. When combining records of δ¹⁸Oatm and δO₂∕N₂ from Vostok and EDC, we find a loss of orbital signature for these two parameters during periods of minimum eccentricity (∼ 400 ka, ∼ 720–800 ka). Our data set reveals a time-varying offset between δO₂∕N₂ and δ¹⁸Oatm records over the last 800 ka that we interpret as variations in the lagged response of δ¹⁸Oatm to precession. The largest offsets are identified during Terminations II, MIS 8 and MIS 16, corresponding to periods of destabilization of the Northern polar ice sheets. We therefore suggest that the occurrence of Heinrich–like events influences the response of δ¹⁸Oatm to precession.

Dynamic D-Vine copula model with applications to Value-at-Risk (VaR)

Regular vine copulas are multivariate dependence models constructed from pair-copulas (bivariate copulas). In this paper, we allow the dependence parameters of the pair-copulas in a D-vine decomposition to be potentially time-varying, following a nonlinear restricted ARMA(1,m) process, in order to obtain a very flexible dependence model for applications to multivariate financial return data. We investigate the dependence among the broad stock market indexes from Germany (DAX), France (CAC 40), Britain (FTSE 100), the United States (S&P 500) and Brazil (IBOVESPA) both in a crisis and in a non-crisis period. We find evidence of stronger dependence among the indexes in bear markets. Surprisingly, though, the dynamic D-vine copula indicates the occurrence of a sharp decrease in dependence between the indexes FTSE and CAC in the beginning of 2011, and also between CAC and DAX during mid-2011 and in the beginning of 2008, suggesting the absence of contagion in these cases. We also evaluate the dynamic D-vine copula with respect to Value-at-Risk (VaR) forecasting accuracy in crisis periods. The dynamic D-vine outperforms the static D-vine in terms of predictive accuracy for our real data sets.

Proton pump inhibitors and the risk of fractures in older adults: a population-based retrospective cohort study

Thesis (Master's)--University of Washington, 2016-06

Hypertension and diabetes treatments and risk of adverse outcomes among breast cancer patients

Thesis (Ph.D.)--University of Washington, 2016-06

A metafrontier production function for estimation of technical efficiencies and technology gaps for firms operating under different technologies

This paper presents a metafrontier production function model for firms in different groups having different technologies. The metafrontier model enables the calculation of comparable technical efficiencies for firms operating under different technologies. The model also enables the technology gaps to be estimated for firms under different technologies relative to the potential technology available to the industry as a whole. The metafrontier model is applied in the analysis of panel data on garment firms in five different regions of Indonesia, assuming that the regional stochastic frontier production function models have technical inefficiency effects with the time-varying structure proposed by Battese and Coelli ( 1992).

Phenotypic divergence along lines of genetic variance

Natural populations inhabiting the same environment often independently evolve the same phenotype. Is this replicated evolution a result of genetic constraints imposed by patterns of genetic covariation? We looked for associations between directions of morphological divergence and the orientation of the genetic variance-covariance matrix (G) by using an experimental system of morphological evolution in two allopatric nonsister species of rainbow fish. Replicate populations of both Melanotaenia eachamensis and Melanotaenia duboulayi have independently adapted to lake versus stream hydrodynamic environments. The major axis of divergence (z) among all eight study populations was closely associated with the direction of greatest genetic variance (g(max)), suggesting directional genetic constraint on evolution. However, the direction of hydrodynamic adaptation was strongly associated with vectors of G describing relatively small proportions of the total genetic variance, and was only weakly associated with g(max). In contrast, divergence between replicate populations within each habitat was approximately proportional to the level of genetic variance, a result consistent with theoretical predictions for neutral phenotypic divergence. Divergence between the two species was also primarily along major eigenvectors of G. Our results therefore suggest that hydrodynamic adaptation in rainbow fish was not directionally constrained by the dominant eigenvector of G. Without partitioning divergence as a consequence of the adaptation of interest (here, hydrodynamic adaptation) from divergence due to other processes, empirical studies are likely to overestimate the potential for the major eigenvectors of G to directionally constrain adaptive evolution.

Consumption habit and international stock returns

We use the consumption-based asset pricing model with habit formation to study the predictability and cross-section of returns from the international equity markets. We find that the predictability of returns from many developed countries' equity markets is explained in part by changing prices of risks associated with consumption relative to habit at the world as well as local levels. We also provide an exploratory investigation of the cross-sectional implications of the model under the complete world market integration hypothesis and find that the model performs mildly better than the traditional consumption-based model. the unconditional and conditional world CAPMs and a three-factor international asset pricing model. (C) 2004 Elsevier B.V. All rights reserved.

Cluster analysis of high-dimensional data: A case study

Normal mixture models are often used to cluster continuous data. However, conventional approaches for fitting these models will have problems in producing nonsingular estimates of the component-covariance matrices when the dimension of the observations is large relative to the number of observations. In this case, methods such as principal components analysis (PCA) and the mixture of factor analyzers model can be adopted to avoid these estimation problems. We examine these approaches applied to the Cabernet wine data set of Ashenfelter (1999), considering the clustering of both the wines and the judges, and comparing our results with another analysis. The mixture of factor analyzers model proves particularly effective in clustering the wines, accurately classifying many of the wines by location.