On the origin of and phylogenetic relationships among living amphibians

The phylogenetic relationships among the three orders of modern amphibians (Caudata, Gymnophiona, and Anura) have been estimated based on both morphological and molecular evidence. Most morphological and paleontological studies of living and fossil amphibians support the hypothesis that salamanders and frogs are sister lineages (the Batrachia hypothesis) and that caecilians are more distantly related. Previous interpretations of molecular data based on nuclear and mitochondrial rRNA sequences suggested that salamanders and caecilians are sister groups to the exclusion of frogs. In an attempt to resolve this apparent conflict, the complete mitochondrial genomes of a salamander (Mertensiella luschani) and a caecilian (Typhlonectes natans) were determined (16,656 and 17,005 bp, respectively) and compared with previously published sequences from a frog (Xenopus laevis) and several other groups of vertebrates. Phylogenetic analyses of the mitochondrial data supported with high bootstrap values the monophyly of living amphibians with respect to other living groups of tetrapods, and a sister group relationship of salamanders and frogs. The lack of phylogenetically informative sites in the previous rRNA data sets (because of its shorter size and higher among-site rate variation) likely explains the discrepancy between our results and those based on previous molecular data. Strong support of the Batrachia hypothesis from both molecule- and morphology-based studies provides a robust phylogenetic framework that will be helpful to comparative studies among the three living orders of amphibians and will permit better understanding of the considerably divergent vertebral, brain, and digit developmental patterns found in frogs and salamanders.

Perspectives on archaeal diversity, thermophily and monophyly from environmental rRNA sequences.

Phylogenetic analysis of ribosomal RNA sequences obtained from uncultivated organisms of a hot spring in Yellowstone National Park reveals several novel groups of Archaea, many of which diverged from the crenarchaeal line of descent prior to previously characterized members of that kingdom. Universal phylogenetic trees constructed with the addition of these sequences indicate monophyly of Archaea, with modest bootstrap support. The data also show a specific relationship between low-temperature marine Archaea and some hot spring Archaea. Two of the environmental sequences are enigmatic: depending upon the data set and analytical method used, these sequences branch deeply within the Crenarchaeota, below the bifurcation between Crenarchaeota and Euryarchaeota, or even as the sister group to Eukaryotes. If additional data confirm either of the latter two placements, then the organisms represented by these ribosomal RNA sequences would merit recognition as a new kingdom, provisionally named "Korarchaeota."

The root of the universal tree and the origin of eukaryotes based on elongation factor phylogeny.

The genes for the protein synthesis elongation factors Tu (EF-Tu) and G (EF-G) are the products of an ancient gene duplication, which appears to predate the divergence of all extant organismal lineages. Thus, it should be possible to root a universal phylogeny based on either protein using the second protein as an outgroup. This approach was originally taken independently with two separate gene duplication pairs, (i) the regulatory and catalytic subunits of the proton ATPases and (ii) the protein synthesis elongation factors EF-Tu and EF-G. Questions about the orthology of the ATPase genes have obscured the former results, and the elongation factor data have been criticized for inadequate taxonomic representation and alignment errors. We have expanded the latter analysis using a broad representation of taxa from all three domains of life. All phylogenetic methods used strongly place the root of the universal tree between two highly distinct groups, the archaeons/eukaryotes and the eubacteria. We also find that a combined data set of EF-Tu and EF-G sequences favors placement of the eukaryotes within the Archaea, as the sister group to the Crenarchaeota. This relationship is supported by bootstrap values of 60-89% with various distance and maximum likelihood methods, while unweighted parsimony gives 58% support for archaeal monophyly.

Randomness and degrees of irregularity.

The fundamental question "Are sequential data random?" arises in myriad contexts, often with severe data length constraints. Furthermore, there is frequently a critical need to delineate nonrandom sequences in terms of closeness to randomness--e.g., to evaluate the efficacy of therapy in medicine. We address both these issues from a computable framework via a quantification of regularity. ApEn (approximate entropy), defining maximal randomness for sequences of arbitrary length, indicating the applicability to sequences as short as N = 5 points. An infinite sequence formulation of randomness is introduced that retains the operational (and computable) features of the finite case. In the infinite sequence setting, we indicate how the "foundational" definition of independence in probability theory, and the definition of normality in number theory, reduce to limit theorems without rates of convergence, from which we utilize ApEn to address rates of convergence (of a deficit from maximal randomness), refining the aforementioned concepts in a computationally essential manner. Representative applications among many are indicated to assess (i) random number generation output; (ii) well-shuffled arrangements; and (iii) (the quality of) bootstrap replicates.

Calculating the probability of multitaxon evolutionary trees: bootstrappers Gambit.

The reconstruction of multitaxon trees from molecular sequences is confounded by the variety of algorithms and criteria used to evaluate trees, making it difficult to compare the results of different analyses. A global method of multitaxon phylogenetic reconstruction described here, Bootstrappers Gambit, can be used with any four-taxon algorithm, including distance, maximum likelihood, and parsimony methods. It incorporates a Bayesian-Jeffreys'-bootstrap analysis to provide a uniform probability-based criterion for comparing the results from diverse algorithms. To examine the usefulness of the method, the origin of the eukaryotes has been investigated by the analysis of ribosomal small subunit RNA sequences. Three common algorithms (paralinear distances, Jukes-Cantor distances, and Kimura distances) support the eocyte topology, whereas one (maximum parsimony) supports the archaebacterial topology, suggesting that the eocyte prokaryotes are the closest prokaryotic relatives of the eukaryotes.

Avaliação de linguagem por ressonância magnética funcional em pacientes com epilepsia associada à esclerose mesial temporal unilateral: correlação com avaliação clínica de linguagem

Introdução: A esclerose mesial temporal (EMT) é a principal causa de epilepsia resistente ao tratamento medicamentoso. Pacientes com EMT apresentam dificuldades no processamento semântico e fonológico de linguagem e maior incidência de reorganização cerebral da linguagem (bilateral ou à direita) em relação à população geral. A ressonância magnética funcional (RMf) permite avaliar a reorganização cerebral das redes de linguagem, comparando padrões de ativação cerebral entre diversas regiões cerebrais. Objetivo: Investigar o desempenho linguístico de pacientes com EMT unilateral esquerda e direita e a ocorrência de reorganização das redes de linguagem com RMf para avaliar se a reorganização foi benéfica para a linguagem nestes pacientes. Métodos: Utilizamos provas clínicas de linguagem e paradigmas de nomeação visual e responsiva para RMf, desenvolvidos para este estudo. Foram avaliados 24 pacientes com EMTe, 22 pacientes com EMTd e 24 controles saudáveis, submetidos a provas de linguagem (fluência semântica e fonológica, nomeação de objetos, verbos, nomes próprios e responsiva, e compreensão de palavras) e a três paradigmas de linguagem por RMf [nomeação por confrontação visual (NCV), nomeação responsiva à leitura (NRL) e geração de palavras (GP)]. Seis regiões cerebrais de interesse (ROI) foram selecionadas (giro frontal inferior, giro frontal médio, giro frontal superior, giro temporal inferior, giro temporal médio e giro temporal superior). Índices de Lateralidade (ILs) foram calculados com dois métodos: bootstrap, do programa LI-Toolbox, independe de limiar, e PSC, que indica a intensidade da ativação cerebral de cada voxel. Cada grupo de pacientes (EMTe e EMTd) foi dividido em dois subgrupos, de acordo com o desempenho em relação aos controles na avaliação clinica de linguagem. O <= -1,5 foi utilizado como nota de corte para dividir os grupos em pacientes com bom e com mau desempenho de linguagem. Em seguida, comparou-se o desempenho linguístico dos subgrupos ao índices IL-boot. Resultados: Pacientes com EMT esquerda e direita mostraram pior desempenho que controles nas provas clínicas de nomeação de verbos, nomeação de nomes próprios, nomeação responsiva e fluência verbal. Os mapas de ativação cerebral por RMf mostraram efeito BOLD em regiões frontais e temporoparietais de linguagem. Os mapas de comparação de ativação cerebral entre os grupos revelaram que pacientes com EMT esquerda e direita apresentam maior ativação em regiões homólogas do hemisfério direito em relação aos controles. Os ILs corroboraram estes resultados, mostrando valores médios menores para os pacientes em relação aos controles e, portanto, maior simetria na representação da linguagem. A comparação entre o IL-boot e o desempenho nas provas clínicas de linguagem indicou que, no paradigma de nomeação responsiva à leitura, a reorganização funcional no giro temporal médio, e possivelmente, nos giros temporal inferior e superior associou-se a desempenho preservado em provas de nomeação. Conclusão: Pacientes com EMT direita e esquerda apresentam comprometimento de nomeação e fluência verbal e reorganização da rede cerebral de linguagem. A reorganização funcional de linguagem em regiões temporais, especialmente o giro temporal médio associou-se a desempenho preservado em provas de nomeação em pacientes com EMT esquerda no paradigma de RMf de nomeação responsiva à leitura

Diseño y desarrollo de un servicio big data en la nube para búsqueda, compartición de ficheros y data mining

En esta memoria se presenta el diseño y desarrollo de una aplicación en la nube destinada a la compartición de objetos y servicios. El desarrollo de esta aplicación surge dentro del proyecto de I+D+i, SITAC: Social Internet of Things – Apps by and for the Crowd ITEA 2 11020, que trata de crear una arquitectura integradora y un “ecosistema” que incluya plataformas, herramientas y metodologías para facilitar la conexión y cooperación de entidades de distinto tipo conectadas a la red bien sean sistemas, máquinas, dispositivos o personas con dispositivos móviles personales como tabletas o teléfonos móviles. El proyecto innovará mediante la utilización de un modelo inspirado en las redes sociales para facilitar y unificar las interacciones tanto entre personas como entre personas y dispositivos. En este contexto surge la necesidad de desarrollar una aplicación destinada a la compartición de recursos en la nube que pueden ser tanto lógicos como físicos, y que esté orientada al big data. Ésta será la aplicación presentada en este trabajo, el “Resource Sharing Center”, que ofrece un servicio web para el intercambio y compartición de contenido, y un motor de recomendaciones basado en las preferencias de los usuarios. Con este objetivo, se han usado tecnologías de despliegue en la nube, como Elastic Beanstalk (el PaaS de Amazon Web Services), S3 (el sistema de almacenamiento de Amazon Web Services), SimpleDB (base de datos NoSQL) y HTML5 con JavaScript y Twitter Bootstrap para el desarrollo del front-end, siendo Python y Node.js las tecnologías usadas en el back end, y habiendo contribuido a la mejora de herramientas de clustering sobre big data. Por último, y de cara a realizar el estudio sobre las pruebas de carga de la aplicación se ha usado la herramienta ApacheJMeter.

MOREMATA: Stata module (Mata) to provide various functions

This package includes various Mata functions. kern(): various kernel functions; kint(): kernel integral functions; kdel0(): canonical bandwidth of kernel; quantile(): quantile function; median(): median; iqrange(): inter-quartile range; ecdf(): cumulative distribution function; relrank(): grade transformation; ranks(): ranks/cumulative frequencies; freq(): compute frequency counts; histogram(): produce histogram data; mgof(): multinomial goodness-of-fit tests; collapse(): summary statistics by subgroups; _collapse(): summary statistics by subgroups; gini(): Gini coefficient; sample(): draw random sample; srswr(): SRS with replacement; srswor(): SRS without replacement; upswr(): UPS with replacement; upswor(): UPS without replacement; bs(): bootstrap estimation; bs2(): bootstrap estimation; bs_report(): report bootstrap results; jk(): jackknife estimation; jk_report(): report jackknife results; subset(): obtain subsets, one at a time; composition(): obtain compositions, one by one; ncompositions(): determine number of compositions; partition(): obtain partitions, one at a time; npartitionss(): determine number of partitions; rsubset(): draw random subset; rcomposition(): draw random composition; colvar(): variance, by column; meancolvar(): mean and variance, by column; variance0(): population variance; meanvariance0(): mean and population variance; mse(): mean squared error; colmse(): mean squared error, by column; sse(): sum of squared errors; colsse(): sum of squared errors, by column; benford(): Benford distribution; cauchy(): cumulative Cauchy-Lorentz dist.; cauchyden(): Cauchy-Lorentz density; cauchytail(): reverse cumulative Cauchy-Lorentz; invcauchy(): inverse cumulative Cauchy-Lorentz; rbinomial(): generate binomial random numbers; cebinomial(): cond. expect. of binomial r.v.; root(): Brent's univariate zero finder; nrroot(): Newton-Raphson zero finder; finvert(): univariate function inverter; integrate_sr(): univariate function integration (Simpson's rule); integrate_38(): univariate function integration (Simpson's 3/8 rule); ipolate(): linear interpolation; polint(): polynomial inter-/extrapolation; plot(): Draw twoway plot; _plot(): Draw twoway plot; panels(): identify nested panel structure; _panels(): identify panel sizes; npanels(): identify number of panels; nunique(): count number of distinct values; nuniqrows(): count number of unique rows; isconstant(): whether matrix is constant; nobs(): number of observations; colrunsum(): running sum of each column; linbin(): linear binning; fastlinbin(): fast linear binning; exactbin(): exact binning; makegrid(): equally spaced grid points; cut(): categorize data vector; posof(): find element in vector; which(): positions of nonzero elements; locate(): search an ordered vector; hunt(): consecutive search; cond(): matrix conditional operator; expand(): duplicate single rows/columns; _expand(): duplicate rows/columns in place; repeat(): duplicate contents as a whole; _repeat(): duplicate contents in place; unorder2(): stable version of unorder(); jumble2(): stable version of jumble(); _jumble2(): stable version of _jumble(); pieces(): break string into pieces; npieces(): count number of pieces; _npieces(): count number of pieces; invtokens(): reverse of tokens(); realofstr(): convert string into real; strexpand(): expand string argument; matlist(): display a (real) matrix; insheet(): read spreadsheet file; infile(): read free-format file; outsheet(): write spreadsheet file; callf(): pass optional args to function; callf_setup(): setup for mm_callf().

Dois ensaios em finanças

In the first chapter, we test some stochastic volatility models using options on the S&P 500 index. First, we demonstrate the presence of a short time-scale, on the order of days, and a long time-scale, on the order of months, in the S&P 500 volatility process using the empirical structure function, or variogram. This result is consistent with findings of previous studies. The main contribution of our paper is to estimate the two time-scales in the volatility process simultaneously by using nonlinear weighted least-squares technique. To test the statistical significance of the rates of mean-reversion, we bootstrap pairs of residuals using the circular block bootstrap of Politis and Romano (1992). We choose the block-length according to the automatic procedure of Politis and White (2004). After that, we calculate a first-order correction to the Black-Scholes prices using three different first-order corrections: (i) a fast time scale correction; (ii) a slow time scale correction; and (iii) a multiscale (fast and slow) correction. To test the ability of our model to price options, we simulate options prices using five different specifications for the rates or mean-reversion. We did not find any evidence that these asymptotic models perform better, in terms of RMSE, than the Black-Scholes model. In the second chapter, we use Brazilian data to compute monthly idiosyncratic moments (expected skewness, realized skewness, and realized volatility) for equity returns and assess whether they are informative for the cross-section of future stock returns. Since there is evidence that lagged skewness alone does not adequately forecast skewness, we estimate a cross-sectional model of expected skewness that uses additional predictive variables. Then, we sort stocks each month according to their idiosyncratic moments, forming quintile portfolios. We find a negative relationship between higher idiosyncratic moments and next-month stock returns. The trading strategy that sells stocks in the top quintile of expected skewness and buys stocks in the bottom quintile generates a significant monthly return of about 120 basis points. Our results are robust across sample periods, portfolio weightings, and to Fama and French (1993)’s risk adjustment factors. Finally, we identify a return reversal of stocks with high idiosyncratic skewness. Specifically, stocks with high idiosyncratic skewness have high contemporaneous returns. That tends to reverse, resulting in negative abnormal returns in the following month.

Abundance estimates for landbirds and seabirds extracted and compiled from annual reports of the Skokholm bird observatory

Long-term ecological data are essential for conservation and to monitor and evaluate the effects of environmental change. Bird populations have been routinely assessed on islands off the British coast for many years and here long term data for one such island, Skokholm, is evaluated for robustness in the light of some 20 changes in observers (wardens) on the island over nearly eight decades. It was found that the dataset was robust when compared to bootstrap data with no species showing significant changes in abundance in years when wardens changed. It is concluded that the breeding bird populations on Skokholm and other British offshore islands are an important scientific resource and that protocols should be enacted to ensure the archiving of records, the continuance of data collection using standardised protocols into the future, and the recognition of such long-term data for science in terms of an appropriate conservation designation.

SPECTRAL DOMAIN-OPTICAL COHERENCE TOMOGRAPHY IMAGE CONTRAST AND BACKGROUND COLOR SETTINGS INFLUENCE IDENTIFICATION OF RETINAL STRUCTURES.

PURPOSE To evaluate image contrast and color setting on assessment of retinal structures and morphology in spectral-domain optical coherence tomography. METHODS Two hundred and forty-eight Spectralis spectral-domain optical coherence tomography B-scans of 62 patients were analyzed by 4 readers. B-scans were extracted in 4 settings: W + N = white background with black image at normal contrast 9; W + H = white background with black image at maximum contrast 16; B + N = black background with white image at normal contrast 12; B + H = black background with white image at maximum contrast 16. Readers analyzed the images to identify morphologic features. Interreader correlation was calculated. Differences between Fleiss-kappa correlation coefficients were examined using bootstrap method. Any setting with significantly higher correlation coefficient was deemed superior for evaluating specific features. RESULTS Correlation coefficients differed among settings. No single setting was superior for all respective spectral-domain optical coherence tomography parameters (P = 0.3773). Some variables showed no differences among settings. Hard exudates and subretinal fluid were best seen with B + H (κ = 0.46, P = 0.0237 and κ = 0.78, P = 0.002). Microaneurysms were best seen with W + N (κ = 0.56, P = 0.025). Vitreomacular interface, enhanced transmission signal, and epiretinal membrane were best identified using all color/contrast settings together (κ = 0.44, P = 0.042, κ = 0.57, P = 0.01, and κ = 0.62, P ≤ 0.0001). CONCLUSION Contrast and background affect the evaluation of retinal structures on spectral-domain optical coherence tomography images. No single setting was superior for all features, though certain changes were best seen with specific settings.

Modeling Depression Progression Dynamics from Electronic Health Record

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

Reliability measures for local nodes assessment in classification trees

Most of the modem developments with classification trees are aimed at improving their predictive capacity. This article considers a curiously neglected aspect of classification trees, namely the reliability of predictions that come from a given classification tree. In the sense that a node of a tree represents a point in the predictor space in the limit, the aim of this article is the development of localized assessment of the reliability of prediction rules. A classification tree may be used either to provide a probability forecast, where for each node the membership probabilities for each class constitutes the prediction, or a true classification where each new observation is predictively assigned to a unique class. Correspondingly, two types of reliability measure will be derived-namely, prediction reliability and classification reliability. We use bootstrapping methods as the main tool to construct these measures. We also provide a suite of graphical displays by which they may be easily appreciated. In addition to providing some estimate of the reliability of specific forecasts of each type, these measures can also be used to guide future data collection to improve the effectiveness of the tree model. The motivating example we give has a binary response, namely the presence or absence of a species of Eucalypt, Eucalyptus cloeziana, at a given sampling location in response to a suite of environmental covariates, (although the methods are not restricted to binary response data).

Validation of a food-frequency questionnaire assessment of carotenoid and vitamin E intake using weighed food records and plasma biomarkers: The method of triads model

Background: Reliability or validity studies are important for the evaluation of measurement error in dietary assessment methods. An approach to validation known as the method of triads uses triangulation techniques to calculate the validity coefficient of a food-frequency questionnaire (FFQ). Objective: To assess the validity of an FFQ estimates of carotenoid and vitamin E intake against serum biomarker measurements and weighed food records (WFRs), by applying the method of triads. Design: The study population was a sub-sample of adult participants in a randomised controlled trial of beta-carotene and sunscreen in the prevention of skin cancer. Dietary intake was assessed by a self-administered FFQ and a WFR. Nonfasting blood samples were collected and plasma analysed for five carotenoids (alpha-carotene, beta-carotene, beta-cryptoxanthin, lutein, lycopene) and vitamin E. Correlation coefficients were calculated between each of the dietary methods and the validity coefficient was calculated using the method of triads. The 95% confidence intervals for the validity coefficients were estimated using bootstrap sampling. Results: The validity coefficients of the FFQ were highest for alpha-carotene (0.85) and lycopene (0.62), followed by beta- carotene (0.55) and total carotenoids (0.55), while the lowest validity coefficient was for lutein (0.19). The method of triads could not be used for b- cryptoxanthin and vitamin E, as one of the three underlying correlations was negative. Conclusions: Results were similar to other studies of validity using biomarkers and the method of triads. For many dietary factors, the upper limit of the validity coefficients was less than 0.5 and therefore only strong relationships between dietary exposure and disease will be detected.

Advantage of single-trial models for response to selection in wheat breeding multi-environment trials

An investigation was conducted to evaluate the impact of experimental designs and spatial analyses (single-trial models) of the response to selection for grain yield in the northern grains region of Australia (Queensland and northern New South Wales). Two sets of multi-environment experiments were considered. One set, based on 33 trials conducted from 1994 to 1996, was used to represent the testing system of the wheat breeding program and is referred to as the multi-environment trial (MET). The second set, based on 47 trials conducted from 1986 to 1993, sampled a more diverse set of years and management regimes and was used to represent the target population of environments (TPE). There were 18 genotypes in common between the MET and TPE sets of trials. From indirect selection theory, the phenotypic correlation coefficient between the MET and TPE single-trial adjusted genotype means [r(p(MT))] was used to determine the effect of the single-trial model on the expected indirect response to selection for grain yield in the TPE based on selection in the MET. Five single-trial models were considered: randomised complete block (RCB), incomplete block (IB), spatial analysis (SS), spatial analysis with a measurement error (SSM) and a combination of spatial analysis and experimental design information to identify the preferred (PF) model. Bootstrap-resampling methodology was used to construct multiple MET data sets, ranging in size from 2 to 20 environments per MET sample. The size and environmental composition of the MET and the single-trial model influenced the r(p(MT)). On average, the PF model resulted in a higher r(p(MT)) than the IB, SS and SSM models, which were in turn superior to the RCB model for MET sizes based on fewer than ten environments. For METs based on ten or more environments, the r(p(MT)) was similar for all single-trial models.