Vegetative phenology of tropical montane forests in the Nilgiris, South India

Spatial and temporal variation in foliar phenology plays a significant role in growth and reproduction of a plant species. Foliar phenology is strongly influenced by environmental factors such as rainfall. A study on phenology of tropical montane forests was undertaken in three different forest patches of the Nilgiri Mountains in peninsular India above 2000 meters ASL. Since August 2000, 500 trees belonging to 70 species of angiosperms were monitored for both vegetative and reproductive phenologies on a monthly basis. Climate data were collected from nearby weather stations. This paper reports results of the study from August 2000 - August 2003 on foliar phenology. Non-parametric correlations and multiple regressions were performed to analyse the influence of environmental factors such as rainfall, temperature and sunshine on foliar phenology. It was found that moisture related factors had a negative influence on the leaf initiation. Circular statistical analyses were performed to understand the seasonality in different phenophases of foliar phenology. Different phenophases of leafing were not significantly seasonal. Results are discussed and compared among three different forest patches on the Nilgiri plateau and also with other montane forest patches across the globe.

Comparative statistical aging studies on an oil-pressboard insulation model

Accelerated aging experiments have been conducted on a representative oil-pressboard insulation model to investigate the effect of constant and sequential stresses on the PD behavior using a built-in phase resolved partial discharge analyzer. A cycle of the applied voltage starting from the zero of the positive half cycle was divided into 16 equal phase windows (Φ1 to Φ16) and partial discharge (PD) magnitude distribution in each phase was determined. Based on the experimental results, three stages of aging mechanism were identified. Gumbel's extreme value distribution of the largest element was used to model the first stage of aging process. Second and subsequent stages were modeled using two-parameter Weibull distribution. Spearman's non-parametric rank correlation test statistic and Kolmogrov-Smirnov two sample test were used to relate the aging process of each phase with the corresponding process of the full cycle. To bring out clearly the effect of stress level, its duration and test procedure on the distribution parameters and hence of the aging process, non-parametric ANOVA techniques like Kruskal-Wallis and Fisher's LSD multiple comparison tests were used. Results of the analysis show that two phases (Φ13 and Φ14) near the vicinity of the negative voltage peak were found to contribute significantly to the aging process and their aging mechanism also correlated well with that of the corresponding full cycle mechanism. Attempts have been made to relate these results with the published work of other workers

MPI-based parallel synchronous vector evaluated particle swarm optimization for multi-objective design optimization of composite structures

This paper presents a decentralized/peer-to-peer architecture-based parallel version of the vector evaluated particle swarm optimization (VEPSO) algorithm for multi-objective design optimization of laminated composite plates using message passing interface (MPI). The design optimization of laminated composite plates being a combinatorially explosive constrained non-linear optimization problem (CNOP), with many design variables and a vast solution space, warrants the use of non-parametric and heuristic optimization algorithms like PSO. Optimization requires minimizing both the weight and cost of these composite plates, simultaneously, which renders the problem multi-objective. Hence VEPSO, a multi-objective variant of the PSO algorithm, is used. Despite the use of such a heuristic, the application problem, being computationally intensive, suffers from long execution times due to sequential computation. Hence, a parallel version of the PSO algorithm for the problem has been developed to run on several nodes of an IBM P720 cluster. The proposed parallel algorithm, using MPI's collective communication directives, establishes a peer-to-peer relationship between the constituent parallel processes, deviating from the more common master-slave approach, in achieving reduction of computation time by factor of up to 10. Finally we show the effectiveness of the proposed parallel algorithm by comparing it with a serial implementation of VEPSO and a parallel implementation of the vector evaluated genetic algorithm (VEGA) for the same design problem. (c) 2012 Elsevier Ltd. All rights reserved.

Review of trend detection methods and their application to detect temperature changes in India

Present study performs the spatial and temporal trend analysis of annual, monthly and seasonal maximum and minimum temperatures (t(max), t(min)) in India. Recent trends in annual, monthly, winter, pre-monsoon, monsoon and post-monsoon extreme temperatures (t(max), t(min)) have been analyzed for three time slots viz. 1901-2003,1948-2003 and 1970-2003. For this purpose, time series of extreme temperatures of India as a whole and seven homogeneous regions, viz. Western Himalaya (WH), Northwest (NW), Northeast (NE), North Central (NC), East coast (EC), West coast (WC) and Interior Peninsula (IP) are considered. Rigorous trend detection analysis has been exercised using variety of non-parametric methods which consider the effect of serial correlation during analysis. During the last three decades minimum temperature trend is present in All India as well as in all temperature homogeneous regions of India either at annual or at any seasonal level (winter, pre-monsoon, monsoon, post-monsoon). Results agree with the earlier observation that the trend in minimum temperature is significant in the last three decades over India (Kothawale et al., 2010). Sequential MK test reveals that most of the trend both in maximum and minimum temperature began after 1970 either in annual or seasonal levels. (C) 2012 Elsevier B.V. All rights reserved.

Narrowband signal detection techniques in shallow ocean by acoustic vector sensor array

This paper presents the formulation and performance analysis of four techniques for detection of a narrowband acoustic source in a shallow range-independent ocean using an acoustic vector sensor (AVS) array. The array signal vector is not known due to the unknown location of the source. Hence all detectors are based on a generalized likelihood ratio test (GLRT) which involves estimation of the array signal vector. One non-parametric and three parametric (model-based) signal estimators are presented. It is shown that there is a strong correlation between the detector performance and the mean-square signal estimation error. Theoretical expressions for probability of false alarm and probability of detection are derived for all the detectors, and the theoretical predictions are compared with simulation results. It is shown that the detection performance of an AVS array with a certain number of sensors is equal to or slightly better than that of a conventional acoustic pressure sensor array with thrice as many sensors.

Dynamic multi-relational Chinese restaurant process for analyzing influences on users in social media

We study the problem of analyzing influence of various factors affecting individual messages posted in social media. The problem is challenging because of various types of influences propagating through the social media network that act simultaneously on any user. Additionally, the topic composition of the influencing factors and the susceptibility of users to these influences evolve over time. This problem has not been studied before, and off-the-shelf models are unsuitable for this purpose. To capture the complex interplay of these various factors, we propose a new non-parametric model called the Dynamic Multi-Relational Chinese Restaurant Process. This accounts for the user network for data generation and also allows the parameters to evolve over time. Designing inference algorithms for this model suited for large scale social-media data is another challenge. To this end, we propose a scalable and multi-threaded inference algorithm based on online Gibbs Sampling. Extensive evaluations on large-scale Twitter and Face book data show that the extracted topics when applied to authorship and commenting prediction outperform state-of-the-art baselines. More importantly, our model produces valuable insights on topic trends and user personality trends beyond the capability of existing approaches.

Connectivity analysis of multichannel EEG signals using recurrence based phase synchronization technique

Real world biological systems such as the human brain are inherently nonlinear and difficult to model. However, most of the previous studies have either employed linear models or parametric nonlinear models for investigating brain function. In this paper, a novel application of a nonlinear measure of phase synchronization based on recurrences, correlation between probabilities of recurrence (CPR), to study connectivity in the brain has been proposed. Being non-parametric, this method makes very few assumptions, making it suitable for investigating brain function in a data-driven way. CPR's utility with application to multichannel electroencephalographic (EEG) signals has been demonstrated. Brain connectivity obtained using thresholded CPR matrix of multichannel EEG signals showed clear differences in the number and pattern of connections in brain connectivity between (a) epileptic seizure and pre-seizure and (b) eyes open and eyes closed states. Corresponding brain headmaps provide meaningful insights about synchronization in the brain in those states. K-means clustering of connectivity parameters of CPR and linear correlation obtained from global epileptic seizure and pre-seizure showed significantly larger cluster centroid distances for CPR as opposed to linear correlation, thereby demonstrating the superior ability of CPR for discriminating seizure from pre-seizure. The headmap in the case of focal epilepsy clearly enables us to identify the focus of the epilepsy which provides certain diagnostic value. (C) 2013 Elsevier Ltd. All rights reserved.

Eficiencia técnica de las universidades argentinas de gestión estatal

Resumen: En el presente trabajo se examina la eficiencia técnica de las universidades argentinas de gestión estatal utilizando una metodología no paramétrica. A través del Análisis Envolvente de Datos se caracteriza a cada universidad mediante una única puntuación de eficiencia técnica relativa, lo que permite estimar las mejoras necesarias por comparación con un grupo de referencia. Se considera el modelo básico con orientación al producto, cuyos resultados muestran que las universidades tienen en promedio entre un 23,2% y un 23,9% de ineficiencia. Estos resultados son de utilidad para el diseño de políticas universitarias.

Probabilistic inference for fast learning in control

A novel framework is provided for very fast model-based reinforcement learning in continuous state and action spaces. It requires probabilistic models that explicitly characterize their levels of condence. Within the framework, exible, non-parametric models are used to describe the world based on previously collected experience. It demonstrates learning on the cart-pole problem in a setting where very limited prior knowledge about the task has been provided. Learning progressed rapidly, and a good policy found after only a small number of iterations.

A predictive model of the export behaviour of small and medium sized firms: an application to the case of Castilla-La Mancha

[EN] Based on an extensive theoretical review, the aim of this paper is to carry out a closer examination of the differences between exporters according to their commitment to the international market. Once the main disparities are identified by means of a non-parametric test, a logistic analysis based upon data collected from small and medium sized manufacturing firms is conducted in order to construct a classificatory model.

Life History, Diet, Abundance and Distribution, and Length-Frequencies of Selected Invertebrates in Florida Bay, Everglades National Park, Florida

This report presents information on the life history, diet, abundance and distribution, and length-frequency distributions of five invertebrates in Florida Bay, Everglades National Park. Collections were made with an otter trawl in basins on a bi-monthly basis. Non-parametric statistics were used to test spatial and temporal differences in the abundance of invertebrates when numbers were appropriate (i. e., $25). Invertebrate species are presented in four sections. The sections on Life History, and Diet were derived from the literature. The section on Abundance and Distribution consists of data from otter-trawl collections. In addition, comparisons with other studies are included here following our results. The section on Length-frequency Distributions consists of length measurements from all collections, except 1984-1985 when no measurements were taken. Length-frequency distributions were used, when possible, to estimate life stage captured, spawning times, recruitment into Florida Bay for those species which spawn outside the Bay, and growth. Additional material from the literature was added when appropriate. (PDF contains 39 pages)

Demographic studies of extrasolar planets

Uncovering the demographics of extrasolar planets is crucial to understanding the processes of their formation and evolution. In this thesis, we present four studies that contribute to this end, three of which relate to NASA's Kepler mission, which has revolutionized the field of exoplanets in the last few years.

In the pre-Kepler study, we investigate a sample of exoplanet spin-orbit measurements---measurements of the inclination of a planet's orbit relative to the spin axis of its host star---to determine whether a dominant planet migration channel can be identified, and at what confidence. Applying methods of Bayesian model comparison to distinguish between the predictions of several different migration models, we find that the data strongly favor a two-mode migration scenario combining planet-planet scattering and disk migration over a single-mode Kozai migration scenario. While we test only the predictions of particular Kozai and scattering migration models in this work, these methods may be used to test the predictions of any other spin-orbit misaligning mechanism.

We then present two studies addressing astrophysical false positives in Kepler data. The Kepler mission has identified thousands of transiting planet candidates, and only relatively few have yet been dynamically confirmed as bona fide planets, with only a handful more even conceivably amenable to future dynamical confirmation. As a result, the ability to draw detailed conclusions about the diversity of exoplanet systems from Kepler detections relies critically on understanding the probability that any individual candidate might be a false positive. We show that a typical a priori false positive probability for a well-vetted Kepler candidate is only about 5-10%, enabling confidence in demographic studies that treat candidates as true planets. We also present a detailed procedure that can be used to securely and efficiently validate any individual transit candidate using detailed information of the signal's shape as well as follow-up observations, if available.

Finally, we calculate an empirical, non-parametric estimate of the shape of the radius distribution of small planets with periods less than 90 days orbiting cool (less than 4000K) dwarf stars in the Kepler catalog. This effort reveals several notable features of the distribution, in particular a maximum in the radius function around 1-1.25 Earth radii and a steep drop-off in the distribution larger than 2 Earth radii. Even more importantly, the methods presented in this work can be applied to a broader subsample of Kepler targets to understand how the radius function of planets changes across different types of host stars.

Impacto da terapia mecânica não cirúrgica em pacientes com periodontite crônica e agressiva generalizadas

O objetivo deste estudo foi avaliar o impacto do tratamento periodontal não cirúrgico sobre a atividade de elastase e o volume de fluido gengival nos pacientes portadores de periodontite crônica e agressiva generalizadas. Foram avaliados 18 pacientes com periodontite crônica (idade média 48,6 DP 7,5 anos), e 11 com periodontite agressiva (idade média 27,9 DP 6,54 anos). Foram utilizados os parâmetros clínicos de avaliação de profundidade de bolsa à sondagem (PB) (mm), nível de inserção (NI) (mm) e sangramento à sondagem (SS). As medidas clínicas e as amostras de fluido gengival foram colhidas a partir dos cinco sítios mais profundos (P) e de cinco sítios rasos com gengivite (G) de cada paciente, antes e 90 dias após o término do tratamento. As etapas clínicas obedeceram ao seguinte cronograma: seleção e exame periodontal; coleta de fluido gengival; tratamento periodontal; reavaliação, compreendendo o exame periodontal e coleta de fluido gengival. O tratamento levou, em média, 4 sessões de 40 minutos cada por paciente, com intervalo de 1 semana entre elas. As consultas para reavaliação foram feitas 90 dias após o término do tratamento. O teste de Wilcoxon foi utilizado para comparar os dados antes e depois do tratamento e o teste não pareado de Mann-Whitney U-test foi utilizado para comparar os grupos de periodontite crônica e agressiva. A amostra analisada antes e após o tratamento não apresentou diferenças significativas entre o grupo com periodontite crônica e agressiva, que responderam de forma similar a todos os indicadores avaliados, exceto para a profundidade de bolsa à sondagem nos sítios rasos com gengivite (p = 0,039) e para o sangramento à sondagem (p = 0,021) nos sítios profundos, ambos mais reduzidos na periodontite crônica após o tratamento. A elastase apresentou, após o tratamento, redução significativa nos sítios profundos, para a periodontite crônica (p = 0,012) e agressiva (p = 0,02). Em relação ao volume de fluido gengival, houve significativa redução após o tratamento nos pacientes com periodontite crônica e agressiva, tanto nos sítios rasos (p = 0,03 e p = 0,03) como nos profundos (p ˂ 0,001 e p = 0,003), respectivamente. Concluindo, os grupos com periodontite crônica e agressiva generalizadas comportaram- se de maneira semelhante frente à terapia mecânica não cirúrgica. Ainda, a terapia periodontal mecânica não cirúrgica mostrou redução significativa do volume de fluido gengival em todos os sítios analisados, e da atividade neutrofílica, nos sítios profundos, associada a reduções significativas em todos os indicadores clínicos analisados após o tratamento.

Essays in revealed preference theory and behavioral economics

Time, risk, and attention are all integral to economic decision making. The aim of this work is to understand those key components of decision making using a variety of approaches: providing axiomatic characterizations to investigate time discounting, generating measures of visual attention to infer consumers' intentions, and examining data from unique field settings.

Chapter 2, co-authored with Federico Echenique and Kota Saito, presents the first revealed-preference characterizations of exponentially-discounted utility model and its generalizations. My characterizations provide non-parametric revealed-preference tests. I apply the tests to data from a recent experiment, and find that the axiomatization delivers new insights on a dataset that had been analyzed by traditional parametric methods.

Chapter 3, co-authored with Min Jeong Kang and Colin Camerer, investigates whether "pre-choice" measures of visual attention improve in prediction of consumers' purchase intentions. We measure participants' visual attention using eyetracking or mousetracking while they make hypothetical as well as real purchase decisions. I find that different patterns of visual attention are associated with hypothetical and real decisions. I then demonstrate that including information on visual attention improves prediction of purchase decisions when attention is measured with mousetracking.

Chapter 4 investigates individuals' attitudes towards risk in a high-stakes environment using data from a TV game show, Jeopardy!. I first quantify players' subjective beliefs about answering questions correctly. Using those beliefs in estimation, I find that the representative player is risk averse. I then find that trailing players tend to wager more than "folk" strategies that are known among the community of contestants and fans, and this tendency is related to their confidence. I also find gender differences: male players take more risk than female players, and even more so when they are competing against two other male players.

Chapter 5, co-authored with Colin Camerer, investigates the dynamics of the favorite-longshot bias (FLB) using data on horse race betting from an online exchange that allows bettors to trade "in-play." I find that probabilistic forecasts implied by market prices before start of the races are well-calibrated, but the degree of FLB increases significantly as the events approach toward the end.

Associações da espessura do complexo médio-intimal da carótida com o estado oxidativo, metabólico e nutricional em crianças pré-púberes obesas e eutróficas

A prevalência de obesidade infantil vem crescendo em todo o mundo e está associada com aumento da morbimortalidade por doenças cardiovasculares na vida adulta. A obesidade na infância, somada às alterações no metabolismo glicêmico e lipídico e ao aumento do estresse oxidativo e estado inflamatório contribuem para o aumento da espessura do complexo médio-intimal da carótida (carotid artery intima-medial thickness - cIMT) em tenra idade, possibilitando o desenvolvimento precoce do processo aterosclerótico. O objetivo deste estudo foi avaliar e comparar a cIMT, os indicadores do metabolismo glicídico e lipídico, o estado oxidativo e antioxidante, a composição corporal e o consumo alimentar em crianças pré-púberes obesas e eutróficas e determinar as inter-relações entre as variáveis. Foram medidos massa corporal total (MCT), estatura (E), circunferência da cintura (CC); glicemia, insulina, colesterol total (CT), lipoproteína de baixa densidade (LDL-colesterol), lipoproteína de alta densidade (HDL-colesterol), ácido úrico, proteína C-reativa ultra-sensível (PCR-us) e capacidade antioxidante (DPPH) sanguíneos; cIMT (USG, General Eletric); consumo alimentar (3 recordatórios de 24 h) para análise de macronutrientes e ácidos graxos. Foram, ainda, calculados o índice de massa corporal por idade (IMC/I) e HOMA-IR. O grupo de crianças obesas (n = 30) apresentava IMC/I acima do p97 (WHO, 2007) cujos dados foram comparados com os de um grupo controle (n = 25), composto por crianças eutróficas, da mesma faixa etária. As análises estatísticas acompanharam as características da amostra para dados não-paramétricos, com graus de significância de p < 0,05. A idade das crianças, em média, foi de 7,8 1,3 anos. A comparação dos indicadores entre os grupos mostrou valores significativamente maiores de MCT, IMC/I, CC, consumo calórico e de carboidratos, CT, LDL-colesterol, insulina, HOMA-IR, ácido úrico, PCR-us e cIMT no grupo de crianças obesas. Foram encontradas associações positivas da cIMT com MCT, IMC/I e CC. Essa última associou-se positivamente com ácido úrico, insulina e HOMA-IR. A PCR-us mostrou associação positiva com MCT, IMC/I, CC, ácido úrico, insulina e HOMA-IR. Os resultados analisados nos permitem concluir que as crianças obesas apresentaram maior massa adiposa abdominal, maior consumo energético, proveniente de carboidratos e valores maiores dos fatores de risco para doenças cardiovasculares do que seus pares eutróficos. Nossos resultados analisados em conjunto, mostram que a obesidade infantil acarreta danos cardiometabólicos que poderão causar prejuízos a saúde na vida adulta. O processo de aterosclerose precoce sofre influência da massa de gordura total e abdominal, a qual está diretamente relacionada à resistência à insulina, ao estado inflamatório e antioxidante. O conhecimento dos fatores de risco desta população deverá embasar estratégias de tratamento com o objetivo de reduzir a morbimortalidade por doenças cardiovasculares na idade adulta.