The Ocean Colour Climate Change Initiative: III. A round-robin comparison on in-water bio-optical algorithms

Satellite-derived remote-sensing reflectance (Rrs) can be used for mapping biogeochemically relevant variables, such as the chlorophyll concentration and the Inherent Optical Properties (IOPs) of the water, at global scale for use in climate-change studies. Prior to generating such products, suitable algorithms have to be selected that are appropriate for the purpose. Algorithm selection needs to account for both qualitative and quantitative requirements. In this paper we develop an objective methodology designed to rank the quantitative performance of a suite of bio-optical models. The objective classification is applied using the NASA bio-Optical Marine Algorithm Dataset (NOMAD). Using in situRrs as input to the models, the performance of eleven semi-analytical models, as well as five empirical chlorophyll algorithms and an empirical diffuse attenuation coefficient algorithm, is ranked for spectrally-resolved IOPs, chlorophyll concentration and the diffuse attenuation coefficient at 489 nm. The sensitivity of the objective classification and the uncertainty in the ranking are tested using a Monte-Carlo approach (bootstrapping). Results indicate that the performance of the semi-analytical models varies depending on the product and wavelength of interest. For chlorophyll retrieval, empirical algorithms perform better than semi-analytical models, in general. The performance of these empirical models reflects either their immunity to scale errors or instrument noise in Rrs data, or simply that the data used for model parameterisation were not independent of NOMAD. Nonetheless, uncertainty in the classification suggests that the performance of some semi-analytical algorithms at retrieving chlorophyll is comparable with the empirical algorithms. For phytoplankton absorption at 443 nm, some semi-analytical models also perform with similar accuracy to an empirical model. We discuss the potential biases, limitations and uncertainty in the approach, as well as additional qualitative considerations for algorithm selection for climate-change studies. Our classification has the potential to be routinely implemented, such that the performance of emerging algorithms can be compared with existing algorithms as they become available. In the long-term, such an approach will further aid algorithm development for ocean-colour studies.

Modeling Multivariate Interest Rates Using Time-Varying Copulas and Reducible Nonlinear Stochastic Differential Equations

We propose a new approach for modeling nonlinear multivariate interest rate processes based on time-varying copulas and reducible stochastic differential equations (SDEs). In the modeling of the marginal processes, we consider a class of nonlinear SDEs that are reducible to Ornstein--Uhlenbeck (OU) process or Cox, Ingersoll, and Ross (1985) (CIR) process. The reducibility is achieved via a nonlinear transformation function. The main advantage of this approach is that these SDEs can account for nonlinear features, observed in short-term interest rate series, while at the same time leading to exact discretization and closed-form likelihood functions. Although a rich set of specifications may be entertained, our exposition focuses on a couple of nonlinear constant elasticity volatility (CEV) processes, denoted as OU-CEV and CIR-CEV, respectively. These two processes encompass a number of existing models that have closed-form likelihood functions. The transition density, the conditional distribution function, and the steady-state density function are derived in closed form as well as the conditional and unconditional moments for both processes. In order to obtain a more flexible functional form over time, we allow the transformation function to be time varying. Results from our study of U.S. and UK short-term interest rates suggest that the new models outperform existing parametric models with closed-form likelihood functions. We also find the time-varying effects in the transformation functions statistically significant. To examine the joint behavior of interest rate series, we propose flexible nonlinear multivariate models by joining univariate nonlinear processes via appropriate copulas. We study the conditional dependence structure of the two rates using Patton (2006a) time-varying symmetrized Joe--Clayton copula. We find evidence of asymmetric dependence between the two rates, and that the level of dependence is positively related to the level of the two rates. (JEL: C13, C32, G12) Copyright The Author 2010. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org, Oxford University Press.

The electron pressure in the outer atmosphere of ∈ Eri (K2 V)

Observations of ? Eri (K2 V) have been made with the Space Telescope Imaging Spectrograph on the Hubble Space Telescope. The spectra obtained show a number of emission lines which can be used to determine, or place limits on, the electron density and pressure. Values of the electron pressure are required in order to make quantitative models of the transition region and inner corona from absolute line fluxes, and to constrain semi-empirical models of the chromosphere. Using line flux ratios in Si II and O IV a mean electron pressure of P = NT = 4.8 × 10 cm K is derived. This value is compatible with the lower and upper limits to P found from flux ratios in C III, O V and Fe XII. Some inconsistencies which may be because of small uncertainties in the atomic data used are discussed.

Stage at diagnosis and colorectal cancer survival in six high-income countries:A population-based study of patients diagnosed during 2000-2007

Background. Large international differences in colorectal cancer survival exist, even between countries with similar healthcare. We investigate the extent to which stage at diagnosis explains these differences. Methods. Data from population-based cancer registries in Australia, Canada, Denmark, Norway, Sweden and the UK were analysed for 313 852 patients diagnosed with colon or rectal cancer during 2000-2007. We compared the distributions of stage at diagnosis. We estimated both stage-specific net survival and the excess hazard of death up to three years after diagnosis, using flexible parametric models on the log-cumulative excess hazard scale. Results. International differences in colon and rectal cancer stage distributions were wide: Denmark showed a distribution skewed towards later-stage disease, while Australia, Norway and the UK showed high proportions of 'regional' disease. One-year colon cancer survival was 67% in the UK and ranged between 71% (Denmark) and 80% (Australia and Sweden) elsewhere. For rectal cancer, one-year survival was also low in the UK (75%), compared to 79% in Denmark and 82-84% elsewhere. International survival differences were also evident for each stage of disease, with the UK showing consistently lowest survival at one and three years. Conclusion. Differences in stage at diagnosis partly explain international differences in colorectal cancer survival, with a more adverse stage distribution contributing to comparatively low survival in Denmark. Differences in stage distribution could arise because of differences in diagnostic delay and awareness of symptoms, or in the thoroughness of staging procedures. Nevertheless, survival differences also exist for each stage of disease, suggesting unequal access to optimal treatment, particularly in the UK. © 2013 Informa Healthcare.

Stage at diagnosis and ovarian cancer survival:Evidence from the international cancer benchmarking partnership

Objective: We investigate what role stage at diagnosis bears in international differences in ovarian cancer survival. Methods: Data from population-based cancer registries in Australia, Canada, Denmark, Norway, and the UK were analysed for 20,073 women diagnosed with ovarian cancer during 2004-07. We compare the stage distribution between countries and estimate stage-specific one-year net survival and the excess hazard up to 18 months after diagnosis, using flexible parametric models on the log cumulative excess hazard scale. Results: One-year survival was 69% in the UK, 72% in Denmark and 74-75% elsewhere. In Denmark, 74% of patients were diagnosed with FIGO stages III-IV disease, compared to 60-70% elsewhere. International differences in survival were evident at each stage of disease; women in the UK had lower survival than in the other four countries for patients with FIGO stages III-IV disease (61.4% vs. 65.8-74.4%). International differences were widest for older women and for those with advanced stage or with no stage data. Conclusion: Differences in stage at diagnosis partly explain international variation in ovarian cancer survival, and a more adverse stage distribution contributes to comparatively low survival in Denmark. This could arise because of differences in tumour biology, staging procedures or diagnostic delay. Differences in survival also exist within each stage, as illustrated by lower survival for advanced disease in the UK, suggesting unequal access to optimal treatment. Population-based data on cancer survival by stage are vital for cancer surveillance, and global consensus is needed to make stage data in cancer registries more consistent. © 2012 Elsevier Inc.

Joint inversion of geophysical and hydrologic data during water infiltration

Tese de doutoramento, Ciências Geofísicas e da Geoinformação (Geofísica), Universidade de Lisboa, Faculdade de Ciências, 2014

Modeling and optimization of extracellular polysaccharides production by Enterobacter A47

Polysaccharides are gaining increasing attention as potential environmental friendly and sustainable building blocks in many fields of the (bio)chemical industry. The microbial production of polysaccharides is envisioned as a promising path, since higher biomass growth rates are possible and therefore higher productivities may be achieved compared to vegetable or animal polysaccharides sources. This Ph.D. thesis focuses on the modeling and optimization of a particular microbial polysaccharide, namely the production of extracellular polysaccharides (EPS) by the bacterial strain Enterobacter A47. Enterobacter A47 was found to be a metabolically versatile organism in terms of its adaptability to complex media, notably capable of achieving high growth rates in media containing glycerol byproduct from the biodiesel industry. However, the industrial implementation of this production process is still hampered due to a largely unoptimized process. Kinetic rates from the bioreactor operation are heavily dependent on operational parameters such as temperature, pH, stirring and aeration rate. The increase of culture broth viscosity is a common feature of this culture and has a major impact on the overall performance. This fact complicates the mathematical modeling of the process, limiting the possibility to understand, control and optimize productivity. In order to tackle this difficulty, data-driven mathematical methodologies such as Artificial Neural Networks can be employed to incorporate additional process data to complement the known mathematical description of the fermentation kinetics. In this Ph.D. thesis, we have adopted such an hybrid modeling framework that enabled the incorporation of temperature, pH and viscosity effects on the fermentation kinetics in order to improve the dynamical modeling and optimization of the process. A model-based optimization method was implemented that enabled to design bioreactor optimal control strategies in the sense of EPS productivity maximization. It is also critical to understand EPS synthesis at the level of the bacterial metabolism, since the production of EPS is a tightly regulated process. Methods of pathway analysis provide a means to unravel the fundamental pathways and their controls in bioprocesses. In the present Ph.D. thesis, a novel methodology called Principal Elementary Mode Analysis (PEMA) was developed and implemented that enabled to identify which cellular fluxes are activated under different conditions of temperature and pH. It is shown that differences in these two parameters affect the chemical composition of EPS, hence they are critical for the regulation of the product synthesis. In future studies, the knowledge provided by PEMA could foster the development of metabolically meaningful control strategies that target the EPS sugar content and oder product quality parameters.

L'excès de poids chez les enfants québécois

Objectifs : Analyser l’évolution de l’embonpoint chez les enfants québécois entre 4 et 8 ans et évaluer le rôle des différents facteurs de risque sur l’excès de poids persistant. Les données proviennent de l’étude longitudinale du développement des enfants du Québec (ÉLDEQ, 1998-2010). Cette enquête est réalisée par l’Institut de la statistique du Québec auprès d’une cohorte de 2120 nourrissons québécois nés en 1998, faisant l’objet d’un suivi annuel à partir de l’âge de 5 mois. Méthodes d’analyse : univariées, bivariées, modélisation semi-paramétrique, analyses de régressions logistique et log-linéaire (Poisson). Principaux résultats : i) L’excès de poids persistant chez les enfants âgés de 4 à 8 ans est un phénomène fluctuant, qui ne varie pas de façon significative selon le sexe ; ii) Le fait d’allaiter les enfants ne semble pas avoir un effet protecteur en ce qui concerne l’excès de poids ; iii) En ce qui concerne le poids à la naissance, les données dont on dispose ne nous permettent pas de tirer des conclusions ; iv) Le fait d’avoir une santé moins qu’excellente à la naissance semble augmenter le risque d’avoir un excès de poids persistant ; v)Ce qui influence surtout, c’est de toujours manger trop ou trop vite, ou le fait de vivre dans une famille avec un ou deux parents qui font de l’embonpoint ; vi) Les mères qui ont fume pendant leur grossesse présentent une probabilité plus élevée d’avoir des enfants avec un excès de poids persistant que celles qui n’ont pas fumé.

Developmental trajectories of marijuana use and psychological distress : exploring the co-occurrence of these phenomena in early adolescence

Le début de l’adolescence est une période de changements rapides où la détresse psychologique et l’expérimentation de la marijuana sont choses fréquentes. Certaines études longitudinales ont démontré que ces deux phénomènes ont tendance à se manifester conjointement tandis que d’autres n’ont pu observer de tel lien. Ces résultats divergents suggèrent que plusieurs questions persistent concernant la nature de cette relation. Cette thèse a pour objectif d’explorer la consommation de marijuana et la détresse psychologique en début d’adolescence afin de mieux saisir les changements à travers le temps, ainsi que d’examiner si ces deux problématiques évoluent conjointement et s’influencent réciproquement. Un échantillon de 448 adolescents garçons et filles fréquentant deux écoles secondaires de Montréal, ont été suivi de secondaire I à secondaire III. De 1999 à 2001, les participants ont complété un questionnaire à chaque année de l’étude incluant des mesures portant sur la consommation de marijuana et la détresse psychologique (IDPESQ-14). Un modèle de mixture semi-paramétrique (Nagin, 2005) a été utilisé afin d’identifier les trajectoires développementales de la consommation de marijuana et de détresse psychologique. Des analyses ont également été effectuées afin d’établir les liens d’appartenance entre chacune des trajectoires de consommation identifiées et la détresse psychologique lors de la première année de l`étude, ainsi qu’entre chacune des trajectoires de détresse psychologique et la consommation de marijuana en première année du secondaire. Finalement, des analyses de trajectoires jointes ont été effectuées afin de déterminer l’interrelation entre la consommation de marijuana et la détresse psychologique. Les résultats de notre étude suggèrent qu’il existe une grande hétérogénéité au niveau de la consommation de marijuana et la détresse psychologique. Trois trajectoires développementales ont été identifiées pour la consommation de marijuana: consommation légère, consommation grandissante et consommation élevée et stable. Trois trajectoires ont également été observées pour la détresse psychologique : basse, moyenne et élevée. Nos résultats démontrent la présence d’un lien entre la détresse psychologique rapportée lors de la première année de l’étude et les trajectoires de consommation problématiques. Ce lien a également été observé entre la consommation de marijuana rapportée lors de première année de l’étude et les trajectoires problématiques de détresse psychologique. Les analyses de trajectoires jointes démontrent la présence d’une concordance entre la consommation de marijuana et la détresse psychologique. Cette interrelation est toutefois complexe puisque les trajectoires de détresse psychologique élevée sont associées à un niveau de consommation de marijuana plus problématique mais l’inverse de cette association est moins probable. Notre étude met en lumière la nature asymétrique de la concordance entre la consommation de marijuana et la détresse psychologique.

Trajectoires développementales des dimensions du profil de dysrégulation (CBCL-DE) – agressivité, anxiété et inattention : éléments prédicteurs de diplomation au secondaire chez les garçons.

Ouvrage réalisé sous la supervision du comité de jury composé des membres suivants: Dre Leila Ben Amor, Dre Diane Sauriol, Daniel Fiset, PhD. & Éric Lacourse PhD.

‘Modeling and Analysis of Competing Risks Data’

there has been much research on analyzing various forms of competing risks data. Nevertheless, there are several occasions in survival studies, where the existing models and methodologies are inadequate for the analysis competing risks data. ldentifiabilty problem and various types of and censoring induce more complications in the analysis of competing risks data than in classical survival analysis. Parametric models are not adequate for the analysis of competing risks data since the assumptions about the underlying lifetime distributions may not hold well. Motivated by this, in the present study. we develop some new inference procedures, which are completely distribution free for the analysis of competing risks data.

Sensitivity analysis of a catchment-scale nitrogen model

There are now considerable expectations that semi-distributed models are useful tools for supporting catchment water quality management. However, insufficient attention has been given to evaluating the uncertainties inherent to this type of model, especially those associated with the spatial disaggregation of the catchment. The Integrated Nitrogen in Catchments model (INCA) is subjected to an extensive regionalised sensitivity analysis in application to the River Kennet, part of the groundwater-dominated upper Thames catchment, UK The main results are: (1) model output was generally insensitive to land-phase parameters, very sensitive to groundwater parameters, including initial conditions, and significantly sensitive to in-river parameters; (2) INCA was able to produce good fits simultaneously to the available flow, nitrate and ammonium in-river data sets; (3) representing parameters as heterogeneous over the catchment (206 calibrated parameters) rather than homogeneous (24 calibrated parameters) produced a significant improvement in fit to nitrate but no significant improvement to flow and caused a deterioration in ammonium performance; (4) the analysis indicated that calibrating the flow-related parameters first, then calibrating the remaining parameters (as opposed to calibrating all parameters together) was not a sensible strategy in this case; (5) even the parameters to which the model output was most sensitive suffered from high uncertainty due to spatial inconsistencies in the estimated optimum values, parameter equifinality and the sampling error associated with the calibration method; (6) soil and groundwater nutrient and flow data are needed to reduce. uncertainty in initial conditions, residence times and nitrogen transformation parameters, and long-term historic data are needed so that key responses to changes in land-use management can be assimilated. The results indicate the general, difficulty of reconciling the questions which catchment nutrient models are expected to answer with typically limited data sets and limited knowledge about suitable model structures. The results demonstrate the importance of analysing semi-distributed model uncertainties prior to model application, and illustrate the value and limitations of using Monte Carlo-based methods for doing so. (c) 2005 Elsevier B.V. All rights reserved.

Understanding and projecting sea level change

There is intense scientific and public interest in the Intergovernmental Panel on Climate Change (IPCC) projections of sea level for the twenty-first century and beyond. The Fourth Assessment Report (AR4) projections, obtained by applying standard methods to the results of the World Climate Research Programme Coupled Model Experiment, includes estimates of ocean thermal expansion, the melting of glaciers and ice caps (G&ICs), increased melting of the Greenland Ice Sheet, and increased precipitation over Greenland and Antarctica, partially offsetting other contributions. The AR4 recognized the potential for a rapid dynamic ice sheet response but robust methods for quantifying it were not available. Illustrative scenarios suggested additional sea level rise on the order of 10 to 20 cm or more, giving a wide range in the global averaged projections of about 20 to 80 cm by 2100. Currently, sea level is rising at a rate near the upper end of these projections. Since publication of the AR4 in 2007, biases in historical ocean temperature observations have been identified and significantly reduced, resulting in improved estimates of ocean thermal expansion. Models that include all climate forcings are in good agreement with these improved observations and indicate the importance of stratospheric aerosol loadings from volcanic eruptions. Estimates of the volumes of G&ICs and their contributions to sea level rise have improved. Results from recent (but possibly incomplete) efforts to develop improved ice sheet models should be available for the 2013 IPCC projections. Improved understanding of sea level rise is paving the way for using observations to constrain projections. Understanding of the regional variations in sea level change as a result of changes in ocean properties, wind-stress patterns, and heat and freshwater inputs into the ocean is improving. Recently, estimates of sea level changes resulting from changes in Earth's gravitational field and the solid Earth response to changes in surface loading have been included in regional projections. While potentially valuable, semi-empirical models have important limitations, and their projections should be treated with caution

Survival analysis of cereal crop variety innovations in the UK

This paper explores the changing survival patterns of cereal crop variety innovations in the UK since the introduction of plant breeders’ rights in the mid-1960s. Using non-parametric, semi-parametric and parametric approaches, we examine the determinants of the survival of wheat variety innovations, focusing on the impacts of changes to Plant Variety Protection (PVP) regime over the last four decades. We find that the period since the introduction of the PVP regime has been characterised by the accelerated development of new varieties and increased private sector participation in the breeding of cereal crop varieties. However, the increased flow of varieties has been accompanied by a sharp decline in the longevity of innovations. These trends may have contributed to a reduction in the returns appropriated by plant breeders from protected variety innovations and may explain the decline of conventional plant breeding in the UK. It may also explain the persistent demand from the seed industry for stronger protection. The strengthening of the PVP regime in conformity with the UPOV Convention of 1991, the introduction of EU-wide protection through the Community Plant Variety Office and the introduction of royalties on farm-saved seed have had a positive effect on the longevity of protected variety innovations, but have not been adequate to offset the long term decline in survival durations.

A statistical approach to the problem of restoring damaged and contaminated images

We address the problem of automatically identifying and restoring damaged and contaminated images. We suggest a novel approach based on a semi-parametric model. This has two components, a parametric component describing known physical characteristics and a more flexible non-parametric component. The latter avoids the need for a detailed model for the sensor, which is often costly to produce and lacking in robustness. We assess our approach using an analysis of electroencephalographic images contaminated by eye-blink artefacts and highly damaged photographs contaminated by non-uniform lighting. These experiments show that our approach provides an effective solution to problems of this type.