Seismic waveform inversion for core-mantle boundary topography

International audience

Quantification of air quality in space and time and its effects on health

The long-term adverse effects on health associated with air pollution exposure can be estimated using either cohort or spatio-temporal ecological designs. In a cohort study, the health status of a cohort of people are assessed periodically over a number of years, and then related to estimated ambient pollution concentrations in the cities in which they live. However, such cohort studies are expensive and time consuming to implement, due to the long-term follow up required for the cohort. Therefore, spatio-temporal ecological studies are also being used to estimate the long-term health effects of air pollution as they are easy to implement due to the routine availability of the required data. Spatio-temporal ecological studies estimate the health impact of air pollution by utilising geographical and temporal contrasts in air pollution and disease risk across $n$ contiguous small-areas, such as census tracts or electoral wards, for multiple time periods. The disease data are counts of the numbers of disease cases occurring in each areal unit and time period, and thus Poisson log-linear models are typically used for the analysis. The linear predictor includes pollutant concentrations and known confounders such as socio-economic deprivation. However, as the disease data typically contain residual spatial or spatio-temporal autocorrelation after the covariate effects have been accounted for, these known covariates are augmented by a set of random effects. One key problem in these studies is estimating spatially representative pollution concentrations in each areal which are typically estimated by applying Kriging to data from a sparse monitoring network, or by computing averages over modelled concentrations (grid level) from an atmospheric dispersion model. The aim of this thesis is to investigate the health effects of long-term exposure to Nitrogen Dioxide (NO2) and Particular matter (PM10) in mainland Scotland, UK. In order to have an initial impression about the air pollution health effects in mainland Scotland, chapter 3 presents a standard epidemiological study using a benchmark method. The remaining main chapters (4, 5, 6) cover the main methodological focus in this thesis which has been threefold: (i) how to better estimate pollution by developing a multivariate spatio-temporal fusion model that relates monitored and modelled pollution data over space, time and pollutant; (ii) how to simultaneously estimate the joint effects of multiple pollutants; and (iii) how to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. Specifically, chapters 4 and 5 are developed to achieve (i), while chapter 6 focuses on (ii) and (iii). In chapter 4, I propose an integrated model for estimating the long-term health effects of NO2, that fuses modelled and measured pollution data to provide improved predictions of areal level pollution concentrations and hence health effects. The air pollution fusion model proposed is a Bayesian space-time linear regression model for relating the measured concentrations to the modelled concentrations for a single pollutant, whilst allowing for additional covariate information such as site type (e.g. roadside, rural, etc) and temperature. However, it is known that some pollutants might be correlated because they may be generated by common processes or be driven by similar factors such as meteorology. The correlation between pollutants can help to predict one pollutant by borrowing strength from the others. Therefore, in chapter 5, I propose a multi-pollutant model which is a multivariate spatio-temporal fusion model that extends the single pollutant model in chapter 4, which relates monitored and modelled pollution data over space, time and pollutant to predict pollution across mainland Scotland. Considering that we are exposed to multiple pollutants simultaneously because the air we breathe contains a complex mixture of particle and gas phase pollutants, the health effects of exposure to multiple pollutants have been investigated in chapter 6. Therefore, this is a natural extension to the single pollutant health effects in chapter 4. Given NO2 and PM10 are highly correlated (multicollinearity issue) in my data, I first propose a temporally-varying linear model to regress one pollutant (e.g. NO2) against another (e.g. PM10) and then use the residuals in the disease model as well as PM10, thus investigating the health effects of exposure to both pollutants simultaneously. Another issue considered in chapter 6 is to allow for the uncertainty in the estimated pollution concentrations when estimating their health effects. There are in total four approaches being developed to adjust the exposure uncertainty. Finally, chapter 7 summarises the work contained within this thesis and discusses the implications for future research.

Conceptual Reference Model for Virtual Factory: Potentials for Collaborative Business

Part 11: Reference and Conceptual Models

EFECTOS ASIMÉTRICOS DE LA POLÍTICA MONETARIA

El objetivo de este documento es obtener evidencia empírica acerca de la existencia de efectos asimétricos de la política monetaria sobre el nivel de actividad económica, con base en el comportamiento de la tasa de interés. Se observa un efecto asimétrico de la política monetaria cuando tasas de interés por encima de su nivel fundamental tienen un efecto sobre la actividad económica significativamente distinto del que tendría una tasa de interés por debajo de su nivel fundamental.La identificación de cambios en la tasa de interés que reflejan cambios de política se realiza por mínimos cuadrados en dos etapas. En la primera etapa, el nivel fundamental de la tasa de interés se estima con una regla de Taylor modificada y sus residuos son utilizados para identificar el estado de la política. La segunda etapa consiste en una regresión del producto real sobre una constante y los valores rezagados de los residuos positivos y negativos obtenidos en la primera etapa. La asimetría vendría determinada por la significancia estadística de los coeficientes individuales de los residuos positivos y negativos y de la diferencia entre estos.La evidencia empírica, para el periodo 1994:01-2002:11, sugiere la existencia de una asimetría débil de la política monetaria. Lo anterior debido a que aunque los incrementos y disminuciones en la tasa de interés afectan el nivel de producción significativamente, la diferencia del impacto no resulta significativa.AbstractThe objective of this paper is to obtain empirical evidence about the existence of asymmetric effects of monetary policy over economic activity, based on interest rate behavior. Monetary policy shows an asymmetric effect when an interest rate over their fundamental level have an impact on economic activity that is significantly different from that when interest rate are below its fundamental level.Changes in interest rate that reflect changes of policy are identified using two stage least squares. In the first stage, the fundamental level of the interest rate is estimated with a modified Taylor rule and residuals are used to identify the state of the policy. The second stage consists of a regression of the real output on a constant and lagged values of the positive and negative residuals obtained in the first stage. The asymmetry would come determined by the statistical significance of individual coefficients of positive and negative residuals and the difference between them.The empirical evidence, over the 1994:01-2002:11 period, suggests the existence of weak asymmetry of monetary policy. Although increases and reductions in interest rate affect the production level significantly, the difference of the impact is not significant.

Three essays on liquidity

Doutoramento em Gestão.

Aplicaciones del Caos y la Complejidad en la Cadena de Suministros del Sector Agroindustrial

La presente investigación consiste en determinar las aplicaciones existentes de las teorías del caos y las teorías de la complejidad en la cadena de suministro del sector agroindustrial colombiano. Además, tiene como propósito describir el sector de la agroindustria y la cadena de suministro, identificar los modelos de caos y complejidad y posteriormente determinar cuáles de éstos son aplicables al sector. Se define el caos como una sub-disciplina de las matemáticas que estudia sistemas complejos o dinámicos y tiene inmerso implicaciones filosóficas; por otra parte complejidad es la cualidad que adquiere un sistema en el que hay diversos componentes relacionados. Se ha identificado que en el ámbito colombiano existen diferentes estudios enfocados en la construcción de modelos agroindustriales, donde se adopta el concepto de complejidad para calificar el atributo de dichos modelos que involucran la armonización e integración de diferentes actores, desde los productores hasta los consumidores. En este estudio se emplea un estudio monográfico de tipo documental teniendo como unidad de análisis la cadena de suministro del sector agroindustrial. Los resultados indican que las teorías del caos y complejidad se encuentran presentes dentro de la cadena de suministros del sector agroindustrial colombiano, ya que en ella se ocurre la interconexión entre productores, procesadores y comercializadores, interactuando entre ellos y presentando alteraciones en su comportamiento económico a lo largo del tiempo en función de variaciones de las condiciones iniciales influenciadas por variables macroeconómicas, ambientales, sociales y políticas.

Estimation of the satellite ephemerides of Saturn using optical navigation pictures of Cassini

The goal of this dissertation thesis is the estimation of the Saturnian satellites ephemerides using optical data of Cassini. In the first part we describe the software employed for the reduction of the images showing its main features and the accuracy that can be achieved comparing the results with published astrometry. Afterwards we describe the orbit determination problem (ODP) with particular focus on the weights selection for the estimation process. The third chapter describes the dynamical model used and the sources of potential errors in the residuals. The model have been validated trying to replicate JPL's published ephemerides SAT365, SAT375, SAT389 and SAT409. The final part investigates the residuals and the estimated ephemerides with particular focus on the giant moon Titan, the only in the solar system with an atmosphere other than the Earth. No astrometry have been retrieved in literature of Titan using optical observables, thus this represents one of the first investigations of the giant.

Probing the innermost regions of AGN via time-resolved spectral analysis

The dynamics and geometry of the material inflowing and outflowing close to the supermassive black hole in active galactic nuclei are still uncertain. X-rays are the most suitable way to study the AGN innermost regions because of the Fe Kα emission line, a proxy of accretion, and Fe absorption lines produced by outflows. Winds are typically classified as Warm Absorbers (slow and mildly ionized) and Ultra Fast Outflows (fast and highly ionized). Transient Obscurers -optically thick winds that produce strong spectral hardening in X-rays, lasting from days to months- have been observed recently. Emission and absorption features vary on time-scales from hours to years, probing phenomena at different distances from the SMBH. In this work, we use time-resolved spectral analysis to investigate the accretion and ejection flows, to characterize them individually and search for correlations. We analyzed XMM-Newtomn data of a set of the brightest Seyfert 1 galaxies that went through an obscuration event: NGC 3783, NGC 3227, NGC 5548, and NGC 985. Our aim is to search for emission/absorption lines in short-duration spectra (∼ 10ks), to explore regions as close as the SMBH as the statistics allows for, and possibly catch transient phenomena. First we run a blind search to detect emission/absorption features, then we analyze their evolution with Residual Maps: we visualize simultaneously positive and negative residuals from the continuum in the time-energy plane, looking for patterns and relative time-scales. In NGC 3783 we were able to ascribe variations of the Fe Kα emission line to absorptions at the same energy due to clumps in the obscurer, whose presence is detected at >3σ, and to determine the size of the clumps. In NGC 3227 we detected a wind at ∼ 0.2c at ∼ 2σ, briefly appearing during an obscuration event.

Simulation of optical observables for space missions to small bodies

The navigation of deep space spacecraft requires accurate measurement of the probe’s state and attitude with respect to a body whose ephemerides may not be known with good accuracy. The heliocentric state of the spacecraft is estimated through radiometric techniques (ranging, Doppler, and Delta-DOR), while optical observables can be introduced to improve the uncertainty in the relative position and attitude with respect to the target body. In this study, we analyze how simulated optical observables affect the estimation of parameters in an orbit determination problem, considering the case of the ESA’s Hera mission towards the binary asteroid system composed of Didymos and Dimorphos. To this extent, a shape model and a photometric function are used to create synthetic onboard camera images. Then, using a stereophotoclinometry technique on some of the simulated images, we create a database of maplets that describe the 3D geometry of the surface around a set of landmarks. The matching of maplets with the simulated images provides the optical observables, expressed as pixel coordinates in the camera frame, which are fed to an orbit determination filter to estimate a certain number of solve-for parameters. The noise introduced in the output optical observables by the image processing can be quantified using as a metric the quality of the residuals, which is used to fine-tune the maplet-matching parameters. In particular, the best results are obtained when using small maplets, with high correlation coefficients and occupation factors.

Characterization of Mars rotational dynamics from Doppler tracking of the InSight lander

In the last decades the evolution of radio science has made it possible to infer the atmosphere composition, the surface and the internal structure of the planets. Since the arrival of the first landers on Mars it was possible to make accurate measurements of the dynamics of this planet; in this thesis we will focus on InSight, considering the data disclosed by the JPL relative to the period from November 26th, 2018 to August 15th, 2021. In particular, the Doppler and Range measurements conducted by the RISE (Rotation and Interior Structure Experiment) will be analyzed. Since the accuracy of these measurements was improved significantly the effects due to the atmosphere of Mars might be measured so it should thus be possible to obtain a better estimate of the parameters characterizing the rotational dynamic of Mars. A large part of this study will therefore be dedicated to the study, modeling, implementation and analysis of the atmosphere of Mars, in both its components: troposphere and ionosphere. Once the complete model of Mars had been built, i.e. including the atmosphere, it was then possible to analyze the residuals, obtained between the data of the measurements carried out and the values predicted by the developed model, in order to obtain an estimate of the rotational dynamic of Mars.