Correction for Bias in Downscaling GCM Simulations for Hydrologic Impact Assessment

In a statistical downscaling model, it is important to remove the bias of General Circulations Model (GCM) outputs resulting from various assumptions about the geophysical processes. One conventional method for correcting such bias is standardisation, which is used prior to statistical downscaling to reduce systematic bias in the mean and variances of GCM predictors relative to the observations or National Centre for Environmental Prediction/ National Centre for Atmospheric Research (NCEP/NCAR) reanalysis data. A major drawback of standardisation is that it may reduce the bias in the mean and variance of the predictor variable but it is much harder to accommodate the bias in large-scale patterns of atmospheric circulation in GCMs (e.g. shifts in the dominant storm track relative to observed data) or unrealistic inter-variable relationships. While predicting hydrologic scenarios, such uncorrected bias should be taken care of; otherwise it will propagate in the computations for subsequent years. A statistical method based on equi-probability transformation is applied in this study after downscaling, to remove the bias from the predicted hydrologic variable relative to the observed hydrologic variable for a baseline period. The model is applied in prediction of monsoon stream flow of Mahanadi River in India, from GCM generated large scale climatological data.

Probable maximum precipitation estimation for catchments in Mahanadi river basin

Probable maximum precipitation (PMP) is a theoretical concept that is widely used by hydrologists to arrive at estimates for probable maximum flood (PMF) that find use in planning, design and risk assessment of high-hazard hydrological structures such as flood control dams upstream of populated areas. The PMP represents the greatest depth of precipitation for a given duration that is meteorologically possible for a watershed or an area at a particular time of year, with no allowance made for long-term climatic trends. Various methods are in use for estimation of PMP over a target location corresponding to different durations. Moisture maximization method and Hershfield method are two widely used methods. The former method maximizes the observed storms assuming that the atmospheric moisture would rise up to a very high value estimated based on the maximum daily dew point temperature. On the other hand, the latter method is a statistical method based on a general frequency equation given by Chow. The present study provides one-day PMP estimates and PMP maps for Mahanadi river basin based on the aforementioned methods. There is a need for such estimates and maps, as the river basin is prone to frequent floods. Utility of the constructed PMP maps in computing PMP for various catchments in the river basin is demonstrated. The PMP estimates can eventually be used to arrive at PMF estimates for those catchments. (C) 2015 The Authors. Published by Elsevier B.V.

Independent component analysis of microarray data in the study of endometrial cancer.

Gene microarray technology is highly effective in screening for differential gene expression and has hence become a popular tool in the molecular investigation of cancer. When applied to tumours, molecular characteristics may be correlated with clinical features such as response to chemotherapy. Exploitation of the huge amount of data generated by microarrays is difficult, however, and constitutes a major challenge in the advancement of this methodology. Independent component analysis (ICA), a modern statistical method, allows us to better understand data in such complex and noisy measurement environments. The technique has the potential to significantly increase the quality of the resulting data and improve the biological validity of subsequent analysis. We performed microarray experiments on 31 postmenopausal endometrial biopsies, comprising 11 benign and 20 malignant samples. We compared ICA to the established methods of principal component analysis (PCA), Cyber-T, and SAM. We show that ICA generated patterns that clearly characterized the malignant samples studied, in contrast to PCA. Moreover, ICA improved the biological validity of the genes identified as differentially expressed in endometrial carcinoma, compared to those found by Cyber-T and SAM. In particular, several genes involved in lipid metabolism that are differentially expressed in endometrial carcinoma were only found using this method. This report highlights the potential of ICA in the analysis of microarray data.

Multiple SNP Markers Reveal Fine-Scale Population and Deep Phylogeographic Structure in European Anchovy (Engraulis encrasicolus L.)

10 p.

Numerical methods for ill-posed, linear problems

A means of assessing the effectiveness of methods used in the numerical solution of various linear ill-posed problems is outlined. Two methods: Tikhonov' s method of regularization and the quasireversibility method of Lattès and Lions are appraised from this point of view.

In the former method, Tikhonov provides a useful means for incorporating a constraint into numerical algorithms. The analysis suggests that the approach can be generalized to embody constraints other than those employed by Tikhonov. This is effected and the general "T-method" is the result.

A T-method is used on an extended version of the backwards heat equation with spatially variable coefficients. Numerical computations based upon it are performed.

The statistical method developed by Franklin is shown to have an interpretation as a T-method. This interpretation, although somewhat loose, does explain some empirical convergence properties which are difficult to pin down via a purely statistical argument.

Black holes in the early universe, in compact binaries, and as energy sources inside solar-type stars

This thesis consists of three separate studies of roles that black holes might play in our universe.

In the first part we formulate a statistical method for inferring the cosmological parameters of our universe from LIGO/VIRGO measurements of the gravitational waves produced by coalescing black-hole/neutron-star binaries. This method is based on the cosmological distance-redshift relation, with "luminosity distances" determined directly, and redshifts indirectly, from the gravitational waveforms. Using the current estimates of binary coalescence rates and projected "advanced" LIGO noise spectra, we conclude that by our method the Hubble constant should be measurable to within an error of a few percent. The errors for the mean density of the universe and the cosmological constant will depend strongly on the size of the universe, varying from about 10% for a "small" universe up to and beyond 100% for a "large" universe. We further study the effects of random gravitational lensing and find that it may strongly impair the determination of the cosmological constant.

In the second part of this thesis we disprove a conjecture that black holes cannot form in an early, inflationary era of our universe, because of a quantum-field-theory induced instability of the black-hole horizon. This instability was supposed to arise from the difference in temperatures of any black-hole horizon and the inflationary cosmological horizon; it was thought that this temperature difference would make every quantum state that is regular at the cosmological horizon be singular at the black-hole horizon. We disprove this conjecture by explicitly constructing a quantum vacuum state that is everywhere regular for a massless scalar field. We further show that this quantum state has all the nice thermal properties that one has come to expect of "good" vacuum states, both at the black-hole horizon and at the cosmological horizon.

In the third part of the thesis we study the evolution and implications of a hypothetical primordial black hole that might have found its way into the center of the Sun or any other solar-type star. As a foundation for our analysis, we generalize the mixing-length theory of convection to an optically thick, spherically symmetric accretion flow (and find in passing that the radial stretching of the inflowing fluid elements leads to a modification of the standard Schwarzschild criterion for convection). When the accretion is that of solar matter onto the primordial hole, the rotation of the Sun causes centrifugal hangup of the inflow near the hole, resulting in an "accretion torus" which produces an enhanced outflow of heat. We find, however, that the turbulent viscosity, which accompanies the convective transport of this heat, extracts angular momentum from the inflowing gas, thereby buffering the torus into a lower luminosity than one might have expected. As a result, the solar surface will not be influenced noticeably by the torus's luminosity until at most three days before the Sun is finally devoured by the black hole. As a simple consequence, accretion onto a black hole inside the Sun cannot be an answer to the solar neutrino puzzle.

Estudo da correlação entre as características da matéria-prima graxa e as propriedades físico-químicas do biodiesel

A possibilidade de utilização de várias matérias graxas na produção do biodiesel nacional é um fator diferencial em relação aos outros países e requer um conhecimento mais profundo das particularidades do biodiesel obtido a partir de matérias-primas tão distintas. Neste contexto, se insere a presente pesquisa, em que se buscou estabelecer correlações entre algumas propriedades do biodiesel e a fonte oleaginosa que lhe deu origem. O biodiesel foi obtido a partir da reação de transesterificação etílica de dez diferentes matérias-primas graxas (óleos refinados de soja, arroz, canola, girassol, milho, oliva, cyclus (mistura contendo óleos de canola, milho e girassol); óleos brutos de mamona e murumuru, além de resíduo de fritura), utilizando etanolato de potássio como agente catalítico, em um reator com sistema de refluxo a 70C durante uma hora. Após purificação, foram determinadas algumas propriedades do biodiesel (massa específica, viscosidade, índice de acidez e índice de iodo) e da matéria-prima (massa específica, viscosidade, índice de acidez, índice de iodo e composição) que lhe deu origem. Os resultados obtidos nas caracterizações geraram gráficos de correlações entre os diversos parâmetros e os dados foram analisados estatisticamente pelo método de correlações canônicas. Para todas as amostras de biodiesel, os valores obtidos nas caracterizações foram compatíveis com as especificações estabelecidas pela ANP para o produto, com exceção do biodiesel de murumuru (índice de acidez elevado e viscosidade baixa) e do biodiesel de mamona (viscosidade e massa específica elevadas). Os dados estatísticos demonstram altas correlações entre o biodiesel (massa específica (87,4%), viscosidade (98,5%) e índice de acidez (82,8%)) e as matérias-primas (massa específica (92,1%) e viscosidade (99,3%)). Além disso, existe uma grande correlação entre o índice de iodo (84,5%) do biodiesel e o índice de iodo (77,2%) e a massa molar dos ésteres na faixa de C16-C18 (MMTG) presentes na matéria-prima (89,1%). Estes resultados estatísticos ratificam as observações analíticas

Study on the layer structure of W/C multilayers deposited by magnetron sputtering using x-ray reflectivity

A study on the layer structure of W/C multilayers deposited by magnetron sputtering is reported. In the study, soft x-ray resonant reflectivity and hard x-ray grazing incidence reflectivity of the W/C multilayers were measured. The imperfections at the interface such as interdiffusion and formation of compounds were dealt with by two methods. On analyzing the experimental results, we found that the incorporation of an interlayer was a more suitable method than the traditional statistical method to describe the layer structure of a W/C system we fabricated. The optical constants of each layer at a wavelength of 4.48 nm were also obtained from the analysis. Copyright (C) 2008 John Wiley & Sons, Ltd.

Exposição cambial: o impacto do câmbio nas ações das empresas brasileiras internacionalizadas

O aumento da internacionalização das economias emergentes e a tendência de financeirização da economia mundial motivaram este estudo que tem como principal objetivo analisar estatisticamente o impacto das variações cambiais no retorno das ações das principais empresas brasileiras internacionalizadas, segundo o ranking realizado pela Fundação Dom Cabral, no período entre 2000 e 2012. Além disso, buscou-se, também, descrever o processo inicial de internacionalização dessas mesmas companhias. Para isso, foi realizada uma pesquisa descritiva e quantitativa, por meio da utilização do método estatístico de regressão linear múltipla. Constatou-se que nas 28 empresas analisadas não há correlação entre variações nas taxas de câmbio e variações no retorno das ações das empresas brasileiras internacionalizadas, evidenciando assim, que outras variáveis são as responsáveis por impactarem o retorno dessas ações. Verificou-se, ainda, que a maior parte das empresas brasileiras iniciam seu processo de internacionalização por meio da instalação de linhas de produção no exterior, seguida de exportação e fusões e aquisições com outras companhias.

Análise de componentes principais aplicada a ruído eletroquímico

Neste trabalho foi utilizado um método matemático para classificar registros de potencial e corrente de ensaios de corrosão na técnica de amperimetria de resistência nula (ZRA). Foi aplicado o método estatístico de múltiplas variáveis simples chamado Análise dos Componentes Principais (PCA), cujo objetivo principal foi identificar padrões nestes dados de ruído eletroquímico. Foram testados o aço carbono UNS G10200, os aços inoxidáveis austenítico UNS S31600 e o superduplex UNS S32750 em meios de ácido sulfúrico (5% H2SO4), cloreto férrico (0,1 mol/L FeCl3) e hidróxido de sódio (0,1% NaOH). Os ensaios foram replicados com oito repetições para se ter reprodutibilidade e conhecimento dos aspectos estatísticos envolvidos. Os resultados mostraram que a análise de componentes principais pode ser utilizada como uma ferramenta para analisar sinais de ruído eletroquímico, identificando os clusters dos comportamentos potencial-tempo, corrente-tempo e acessoriamente identificar os outliersdos registros temporais.

Autonomous extraction of optimal flame fronts in OH planar laser-induced fluorescence images.

The location of a flame front is often taken as the point of maximum OH gradient. Planar laser-induced fluorescence of OH can be used to obtain the flame front by extracting the points of maximum gradient. This operation is typically performed using an edge detection algorithm. The choice of operating parameters a priori poses significant problems of robustness when handling images with a range of signal-to-noise ratios. A statistical method of parameter selection originating in the image processing literature is detailed, and its merit for this application is demonstrated. A reduced search space method is proposed to decrease computational cost and render the technique viable for large data sets. This gives nearly identical output to the full method. These methods demonstrate substantial decreases in data rejection compared to the use of a priori parameters. These methods are viable for any application where maximum gradient contours must be accurately extracted from images of species or temperature, even at very low signal-to-noise ratios.

Dynamics of in-plane arch rocking: An energy approach

This study employs an analytical model to describe the rocking response of a masonry arch to in-plane seismic loading. Through evaluation of the rate of energy input to the system, the model reveals the ground motions that cause maximum rocking amplification. An experimental investigation of small-scale masonry arches subjected to past earthquake time histories is used to evaluate the analytical model and to explore arch rocking behaviour. The results demonstrate that rocking amplification can occur, but is highly sensitive to slight variations in the ground motion. Thus, the accuracy to which the arch response can be predicted is brought into perspective. The concept that the primary impulse of an expected ground motion is fundamentally important in predicting arch collapse is evaluated in light of the developed energy approach. Finally, a statistical method is proposed for predicting the probability of arch collapse during seismic loading.

Bayesian inference for multidimensional NMR image reconstruction

Reconstruction of an image from a set of projections has been adapted to generate multidimensional nuclear magnetic resonance (NMR) spectra, which have discrete features that are relatively sparsely distributed in space. For this reason, a reliable reconstruction can be made from a small number of projections. This new concept is called Projection Reconstruction NMR (PR-NMR). In this paper, multidimensional NMR spectra are reconstructed by Reversible Jump Markov Chain Monte Carlo (RJMCMC). This statistical method generates samples under the assumption that each peak consists of a small number of parameters: position of peak centres, peak amplitude, and peak width. In order to find the number of peaks and shape, RJMCMC has several moves: birth, death, merge, split, and invariant updating. The reconstruction schemes are tested on a set of six projections derived from the three-dimensional 700 MHz HNCO spectrum of a protein HasA.

Accelerating Bayesian hierarchical clustering of time series data with a randomised algorithm.

We live in an era of abundant data. This has necessitated the development of new and innovative statistical algorithms to get the most from experimental data. For example, faster algorithms make practical the analysis of larger genomic data sets, allowing us to extend the utility of cutting-edge statistical methods. We present a randomised algorithm that accelerates the clustering of time series data using the Bayesian Hierarchical Clustering (BHC) statistical method. BHC is a general method for clustering any discretely sampled time series data. In this paper we focus on a particular application to microarray gene expression data. We define and analyse the randomised algorithm, before presenting results on both synthetic and real biological data sets. We show that the randomised algorithm leads to substantial gains in speed with minimal loss in clustering quality. The randomised time series BHC algorithm is available as part of the R package BHC, which is available for download from Bioconductor (version 2.10 and above) via http://bioconductor.org/packages/2.10/bioc/html/BHC.html. We have also made available a set of R scripts which can be used to reproduce the analyses carried out in this paper. These are available from the following URL. https://sites.google.com/site/randomisedbhc/.

黄土高原坡地表层土壤饱和导水率和水分含量空间变异特征

表层土壤水分含量和饱和导水率对深层土壤水分的动态的变化具有重要的决定作用。在黄土高原坡地(50m×360 m)范围内进行网格(10 m×10 m)取样,用地统计学方法研究表层(0~30 cm)土壤饱和导水率和水分含量的空间变异特征。结果表明:1)坡地表层土壤密度变化规律为坡下位大于坡上位,土壤饱和导水率变异系数为0.37,属于中等变异强度;2)饱和导水率和自然对数化的饱和导水率在360 m尺度内均不具备空间结构特征,是纯随机变量,线性有基台模型适用于描述表层土壤水分的分布特征,水分分布存在明显的块金效应,并且随滞后距离的增加半方差变大;3)饱和导水率和水分含量从坡上位到坡下位均呈现波浪式变化,饱和导水率大的采样点土壤水分含量低,反之则高。