Scale bridging concepts in molecular simulation : coarse-graining and thermodynamic coupling

In dieser Arbeit wurden Simulation von Flüssigkeiten auf molekularer Ebene durchgeführt, wobei unterschiedliche Multi-Skalen Techniken verwendet wurden. Diese erlauben eine effektive Beschreibung der Flüssigkeit, die weniger Rechenzeit im Computer benötigt und somit Phänomene auf längeren Zeit- und Längenskalen beschreiben kann.rnrnEin wesentlicher Aspekt ist dabei ein vereinfachtes (“coarse-grained”) Modell, welches in einem systematischen Verfahren aus Simulationen des detaillierten Modells gewonnen wird. Dabei werden ausgewählte Eigenschaften des detaillierten Modells (z.B. Paar-Korrelationsfunktion, Druck, etc) reproduziert.rnrnEs wurden Algorithmen untersucht, die eine gleichzeitige Kopplung von detaillierten und vereinfachten Modell erlauben (“Adaptive Resolution Scheme”, AdResS). Dabei wird das detaillierte Modell in einem vordefinierten Teilvolumen der Flüssigkeit (z.B. nahe einer Oberfläche) verwendet, während der Rest mithilfe des vereinfachten Modells beschrieben wird.rnrnHierzu wurde eine Methode (“Thermodynamische Kraft”) entwickelt um die Kopplung auch dann zu ermöglichen, wenn die Modelle in verschiedenen thermodynamischen Zuständen befinden. Zudem wurde ein neuartiger Algorithmus der Kopplung beschrieben (H-AdResS) der die Kopplung mittels einer Hamilton-Funktion beschreibt. In diesem Algorithmus ist eine zur Thermodynamischen Kraft analoge Korrektur mit weniger Rechenaufwand möglich.rnrnAls Anwendung dieser grundlegenden Techniken wurden Pfadintegral Molekulardynamik (MD) Simulationen von Wasser untersucht. Mithilfe dieser Methode ist es möglich, quantenmechanische Effekte der Kerne (Delokalisation, Nullpunktsenergie) in die Simulation einzubeziehen. Hierbei wurde zuerst eine Multi-Skalen Technik (“Force-matching”) verwendet um eine effektive Wechselwirkung aus einer detaillierten Simulation auf Basis der Dichtefunktionaltheorie zu extrahieren. Die Pfadintegral MD Simulation verbessert die Beschreibung der intra-molekularen Struktur im Vergleich mit experimentellen Daten. Das Modell eignet sich auch zur gleichzeitigen Kopplung in einer Simulation, wobei ein Wassermolekül (beschrieben durch 48 Punktteilchen im Pfadintegral-MD Modell) mit einem vereinfachten Modell (ein Punktteilchen) gekoppelt wird. Auf diese Weise konnte eine Wasser-Vakuum Grenzfläche simuliert werden, wobei nur die Oberfläche im Pfadintegral Modell und der Rest im vereinfachten Modell beschrieben wird.

Global modeling of pollutant transport and deposition from anthropogenic emission hot spots on global scale

Urban centers significantly contribute to anthropogenic air pollution, although they cover only a minor fraction of the Earth's land surface. Since the worldwide degree of urbanization is steadily increasing, the anthropogenic contribution to air pollution from urban centers is expected to become more substantial in future air quality assessments. The main objective of this thesis was to obtain a more profound insight in the dispersion and the deposition of aerosol particles from 46 individual major population centers (MPCs) as well as the regional and global influence on the atmospheric distribution of several aerosol types. For the first time, this was assessed in one model framework, for which the global model EMAC was applied with different representations of aerosol particles. First, in an approach with passive tracers and a setup in which the results depend only on the source location and the size and the solubility of the tracers, several metrics and a regional climate classification were used to quantify the major outflow pathways, both vertically and horizontally, and to compare the balance between pollution export away from and pollution build-up around the source points. Then in a more comprehensive approach, the anthropogenic emissions of key trace species were changed at the MPC locations to determine the cumulative impact of the MPC emissions on the atmospheric aerosol burdens of black carbon, particulate organic matter, sulfate, and nitrate. Ten different mono-modal passive aerosol tracers were continuously released at the same constant rate at each emission point. The results clearly showed that on average about five times more mass is advected quasi-horizontally at low levels than exported into the upper troposphere. The strength of the low-level export is mainly determined by the location of the source, while the vertical transport is mainly governed by the lifting potential and the solubility of the tracers. Similar to insoluble gas phase tracers, the low-level export of aerosol tracers is strongest at middle and high latitudes, while the regions of strongest vertical export differ between aerosol (temperate winter dry) and gas phase (tropics) tracers. The emitted mass fraction that is kept around MPCs is largest in regions where aerosol tracers have short lifetimes; this mass is also critical for assessing the impact on humans. However, the number of people who live in a strongly polluted region around urban centers depends more on the population density than on the size of the area which is affected by strong air pollution. Another major result was that fine aerosol particles (diameters smaller than 2.5 micrometer) from MPCs undergo substantial long-range transport, with about half of the emitted mass being deposited beyond 1000 km away from the source. In contrast to this diluted remote deposition, there are areas around the MPCs which experience high deposition rates, especially in regions which are frequently affected by heavy precipitation or are situated in poorly ventilated locations. Moreover, most MPC aerosol emissions are removed over land surfaces. In particular, forests experience more deposition from MPC pollutants than other land ecosystems. In addition, it was found that the generic treatment of aerosols has no substantial influence on the major conclusions drawn in this thesis. Moreover, in the more comprehensive approach, it was found that emissions of black carbon, particulate organic matter, sulfur dioxide, and nitrogen oxides from MPCs influence the atmospheric burden of various aerosol types very differently, with impacts generally being larger for secondary species, sulfate and nitrate, than for primary species, black carbon and particulate organic matter. While the changes in the burdens of sulfate, black carbon, and particulate organic matter show an almost linear response for changes in the emission strength, the formation of nitrate was found to be contingent upon many more factors, e.g., the abundance of sulfuric acid, than only upon the strength of the nitrogen oxide emissions. The generic tracer experiments were further extended to conduct the first risk assessment to obtain the cumulative risk of contamination from multiple nuclear reactor accidents on the global scale. For this, many factors had to be taken into account: the probability of major accidents, the cumulative deposition field of the radionuclide cesium-137, and a threshold value that defines contamination. By collecting the necessary data and after accounting for uncertainties, it was found that the risk is highest in western Europe, the eastern US, and in Japan, where on average contamination by major accidents is expected about every 50 years.

A Web GIS Decision Support System For Coastal Risk Assessment and Mitigation Planning

Coastal flooding poses serious threats to coastal areas around the world, billions of dollars in damage to property and infrastructure, and threatens the lives of millions of people. Therefore, disaster management and risk assessment aims at detecting vulnerability and capacities in order to reduce coastal flood disaster risk. In particular, non-specialized researchers, emergency management personnel, and land use planners require an accurate, inexpensive method to determine and map risk associated with storm surge events and long-term sea level rise associated with climate change. This study contributes to the spatially evaluation and mapping of social-economic-environmental vulnerability and risk at sub-national scale through the development of appropriate tools and methods successfully embedded in a Web-GIS Decision Support System. A new set of raster-based models were studied and developed in order to be easily implemented in the Web-GIS framework with the purpose to quickly assess and map flood hazards characteristics, damage and vulnerability in a Multi-criteria approach. The Web-GIS DSS is developed recurring to open source software and programming language and its main peculiarity is to be available and usable by coastal managers and land use planners without requiring high scientific background in hydraulic engineering. The effectiveness of the system in the coastal risk assessment is evaluated trough its application to a real case study.

Imaging and modeling of pore scale processes in porous media using X-ray computed tomography and lattice Boltzmann solver

In der Erdöl– und Gasindustrie sind bildgebende Verfahren und Simulationen auf der Porenskala im Begriff Routineanwendungen zu werden. Ihr weiteres Potential lässt sich im Umweltbereich anwenden, wie z.B. für den Transport und Verbleib von Schadstoffen im Untergrund, die Speicherung von Kohlendioxid und dem natürlichen Abbau von Schadstoffen in Böden. Mit der Röntgen-Computertomografie (XCT) steht ein zerstörungsfreies 3D bildgebendes Verfahren zur Verfügung, das auch häufig für die Untersuchung der internen Struktur geologischer Proben herangezogen wird. Das erste Ziel dieser Dissertation war die Implementierung einer Bildverarbeitungstechnik, die die Strahlenaufhärtung der Röntgen-Computertomografie beseitigt und den Segmentierungsprozess dessen Daten vereinfacht. Das zweite Ziel dieser Arbeit untersuchte die kombinierten Effekte von Porenraumcharakteristika, Porentortuosität, sowie die Strömungssimulation und Transportmodellierung in Porenräumen mit der Gitter-Boltzmann-Methode. In einer zylindrischen geologischen Probe war die Position jeder Phase auf Grundlage der Beobachtung durch das Vorhandensein der Strahlenaufhärtung in den rekonstruierten Bildern, das eine radiale Funktion vom Probenrand zum Zentrum darstellt, extrahierbar und die unterschiedlichen Phasen ließen sich automatisch segmentieren. Weiterhin wurden Strahlungsaufhärtungeffekte von beliebig geformten Objekten durch einen Oberflächenanpassungsalgorithmus korrigiert. Die Methode der „least square support vector machine” (LSSVM) ist durch einen modularen Aufbau charakterisiert und ist sehr gut für die Erkennung und Klassifizierung von Mustern geeignet. Aus diesem Grund wurde die Methode der LSSVM als pixelbasierte Klassifikationsmethode implementiert. Dieser Algorithmus ist in der Lage komplexe geologische Proben korrekt zu klassifizieren, benötigt für den Fall aber längere Rechenzeiten, so dass mehrdimensionale Trainingsdatensätze verwendet werden müssen. Die Dynamik von den unmischbaren Phasen Luft und Wasser wird durch eine Kombination von Porenmorphologie und Gitter Boltzmann Methode für Drainage und Imbibition Prozessen in 3D Datensätzen von Böden, die durch synchrotron-basierte XCT gewonnen wurden, untersucht. Obwohl die Porenmorphologie eine einfache Methode ist Kugeln in den verfügbaren Porenraum einzupassen, kann sie dennoch die komplexe kapillare Hysterese als eine Funktion der Wassersättigung erklären. Eine Hysterese ist für den Kapillardruck und die hydraulische Leitfähigkeit beobachtet worden, welche durch die hauptsächlich verbundenen Porennetzwerke und der verfügbaren Porenraumgrößenverteilung verursacht sind. Die hydraulische Konduktivität ist eine Funktion des Wassersättigungslevels und wird mit einer makroskopischen Berechnung empirischer Modelle verglichen. Die Daten stimmen vor allem für hohe Wassersättigungen gut überein. Um die Gegenwart von Krankheitserregern im Grundwasser und Abwässern vorhersagen zu können, wurde in einem Bodenaggregat der Einfluss von Korngröße, Porengeometrie und Fluidflussgeschwindigkeit z.B. mit dem Mikroorganismus Escherichia coli studiert. Die asymmetrischen und langschweifigen Durchbruchskurven, besonders bei höheren Wassersättigungen, wurden durch dispersiven Transport aufgrund des verbundenen Porennetzwerks und durch die Heterogenität des Strömungsfeldes verursacht. Es wurde beobachtet, dass die biokolloidale Verweilzeit eine Funktion des Druckgradienten als auch der Kolloidgröße ist. Unsere Modellierungsergebnisse stimmen sehr gut mit den bereits veröffentlichten Daten überein.

Sviluppo di applicazioni mobile platform-independent: Un caso di studio basato sul framework sencha

Negli ultimi anni si è imposto il concetto di Ubiquitous Computing, ovvero la possibilità di accedere al web e di usare applicazioni per divertimento o lavoro in qualsiasi momento e in qualsiasi luogo. Questo fenomeno sta cambiando notevolmente le abitudini delle persone e ciò è testimoniato anche dal fatto che il mercato mobile è in forte ascesa: da fine 2014 sono 45 milioni gli smartphone e 12 milioni i tablet in circolazione in Italia. Sembra quasi impossibile, dunque, rinunciare al mobile, soprattutto per le aziende: il nuovo modo di comunicare ha reso necessaria l’introduzione del Mobile Marketing e per raggiungere i propri clienti ora uno degli strumenti più efficaci e diretti sono le applicazioni. Esse si definiscono native se si pongono come traguardo un determinato smartphone e possono funzionare solo per quel sistema operativo. Infatti un’app costruita, per esempio, per Android non può funzionare su dispositivi Apple o Windows Phone a meno che non si ricorra al processo di porting. Ultimamente però è richiesto un numero sempre maggiore di app per piattaforma e i dispositivi presenti attualmente sul mercato presentano differenze tra le CPU, le interfacce (Application Programming Interface), i sistemi operativi, l’hardware, etc. Nasce quindi la necessità di creare applicazioni che possano funzionare su più sistemi operativi, ovvero le applicazioni platform-independent. Per facilitare e supportare questo genere di lavoro sono stati definiti nuovi ambienti di sviluppo tra i quali Sencha Touch e Apache Cordova. Il risultato finale dello sviluppo di un’app attraverso questi framework è proprio quello di ottenere un oggetto che possa essere eseguito su qualsiasi dispositivo. Naturalmente la resa non sarà la stessa di un’app nativa, la quale ha libero accesso a tutte le funzionalità del dispositivo (rubrica, messaggi, notifiche, geolocalizzazione, fotocamera, accelerometro, etc.), però con questa nuova app vi è la garanzia di un costo di sviluppo minore e di una richiesta considerevole sul mercato. L’obiettivo della tesi è quello di analizzare questo scenario attraverso un caso di studio proveniente da una realtà aziendale che presenta proprio la necessità di sviluppare un’applicazione per più piattaforme. Nella prima parte della tesi viene affrontata la tematica del mobile computing e quella del dualismo tra la programmazione nativa e le web app: verranno analizzate le caratteristiche delle due diverse tipologie cercando di capire quale delle due risulti essere la migliore. Nella seconda parte sarà data luce a uno dei più importanti framework per la costruzione di app multi-piattaforma: Sencha Touch. Ne verranno analizzate le caratteristiche, soffermandosi in particolare sul pattern MVC e si potrà vedere un confronto con altri framework. Nella terza parte si tratterà il caso di studio, un app mobile per Retail basata su Sencha Touch e Apache Cordova. Nella parte finale si troveranno alcune riflessioni e conclusioni sul mobile platform-independent e sui vantaggi e gli svantaggi dell’utilizzo di JavaScript per sviluppare app.

Programmazione di sistemi multi-agente: la piattaforma Jason come caso di studio

L’obiettivo principale di questo elaborato è di mostrare in un primo momento i concetti fondamentali che stanno alla base del paradigma ad agenti. Una volta introdotti, essi verranno collocati in un determinato ambiente di programmazione attraverso una piattaforma specifica chiamata Jason. Come sarà facile capire dalla lettura di questa trattazione, un sistema ad agenti è costituito dagli agenti stessi e dall’ambiente in cui sono situati. L’ambiente risulta quindi un altro tassello fondamentale ed è stato introdotto allo scopo un nuovo paradigma per la programmazione di ambienti chiamato Agent & Artifact. Nello specifico, verrà ampiamente descritto il framework di riferimento di tale paradigma: CArtAgO. Dopo aver illustrato i concetti e gli strumenti per poter agilmente programmare e progettare sistemi ad agenti, verrà infine mostrato un esempio di applicazione di tale tecnologia attraverso un case study. Il progetto del sistema in questione riguarda un reale caso aziendale e integra la tecnologia RFID con quella ad agenti per fornire la soluzione ad un problema noto come quello del controllo periodico delle scorte.

Deep learning for computer vision: a comparison between convolutional neural networks and hierarchical temporal memories on object recognition tasks

In recent years, Deep Learning techniques have shown to perform well on a large variety of problems both in Computer Vision and Natural Language Processing, reaching and often surpassing the state of the art on many tasks. The rise of deep learning is also revolutionizing the entire field of Machine Learning and Pattern Recognition pushing forward the concepts of automatic feature extraction and unsupervised learning in general. However, despite the strong success both in science and business, deep learning has its own limitations. It is often questioned if such techniques are only some kind of brute-force statistical approaches and if they can only work in the context of High Performance Computing with tons of data. Another important question is whether they are really biologically inspired, as claimed in certain cases, and if they can scale well in terms of "intelligence". The dissertation is focused on trying to answer these key questions in the context of Computer Vision and, in particular, Object Recognition, a task that has been heavily revolutionized by recent advances in the field. Practically speaking, these answers are based on an exhaustive comparison between two, very different, deep learning techniques on the aforementioned task: Convolutional Neural Network (CNN) and Hierarchical Temporal memory (HTM). They stand for two different approaches and points of view within the big hat of deep learning and are the best choices to understand and point out strengths and weaknesses of each of them. CNN is considered one of the most classic and powerful supervised methods used today in machine learning and pattern recognition, especially in object recognition. CNNs are well received and accepted by the scientific community and are already deployed in large corporation like Google and Facebook for solving face recognition and image auto-tagging problems. HTM, on the other hand, is known as a new emerging paradigm and a new meanly-unsupervised method, that is more biologically inspired. It tries to gain more insights from the computational neuroscience community in order to incorporate concepts like time, context and attention during the learning process which are typical of the human brain. In the end, the thesis is supposed to prove that in certain cases, with a lower quantity of data, HTM can outperform CNN.

Actor Kit: Design and Development of an Actor Framework for Swift

Nell'ambito dello sviluppo software, la concorrenza è sempre stata vista come la strada del futuro. Tuttavia, questa è stata spesso ignorata a causa del continuo sviluppo dell'hardware che ha permesso agli sviluppatori di continuare a scrivere software sequenziale senza doversi preoccupare delle performance. In un'era in cui le nuove architetture hardware presentano processori multi-core, tutto questo non è più possibile. L'obiettivo di questa tesi è stato quello di considerare il Modello ad Attori come valida alternativa allo sviluppo di applicazioni in ambito mobile e quindi di progettare, sviluppare e distribuire un nuovo framework sulla base di tale modello. Il lavoro parte quindi da una panoramica di Swift, il nuovo linguaggio di programmazione presentato da Apple al WWDC 2014, in cui vengono analizzati nel dettaglio i meccanismi che abilitano alla concorrenza. Successivamente viene descritto il modello ad attori in termini di: attori, proprietà, comunicazione e sincronizzazione. Segue poi un'analisi delle principali implementazioni di questo modello, tra cui: Scala, Erlang ed Akka; quest'ultimo rappresenta la base su cui è stato ispirato il lavoro di progettazione e sviluppo del framework Actor Kit. Il quarto capitolo descrive tutti i concetti, le idee e i principi su cui il framework Actor Kit è stato progettato e sviluppato. Infine, l'ultimo capitolo presenta l'utilizzo del framework in due casi comuni della programmazione mobile: 1) Acquisizione dati da Web API e visualizzazione sull'interfaccia utente. 2) Acquisizione dati dai sensori del dispositivo. In conclusione Actor Kit abilita la progettazione e lo sviluppo di applicazioni secondo un approccio del tutto nuovo nell'ambito mobile. Un possibile sviluppo futuro potrebbe essere l'estensione del framework con attori che mappino i framework standard di Apple; proprio per questo sarà reso pubblico con la speranza che altri sviluppatori possano evolverlo e renderlo ancora più completo e performante.

Progettazione e sviluppo multi-platform di applicazioni mobile: un caso di studio in Xamarin

In questa tesi viene trattato l'argomento dello sviluppo multi-platform di applicazioni mobile. Viene effettuata una panoramica degli approcci possibili e dei relativi framework per lo sviluppo. Individuato l'approccio ritenuto piu interessante, viene affrontato un caso di studio per poter convalidare la tecnologia.

Early non-invasive cardiac output monitoring in hemodynamically unstable intensive care patients: A multi-center randomized controlled trial

Introduction Acute hemodynamic instability increases morbidity and mortality. We investigated whether early non-invasive cardiac output monitoring enhances hemodynamic stabilization and improves outcome. Methods A multicenter, randomized controlled trial was conducted in three European university hospital intensive care units in 2006 and 2007. A total of 388 hemodynamically unstable patients identified during their first six hours in the intensive care unit (ICU) were randomized to receive either non-invasive cardiac output monitoring for 24 hrs (minimally invasive cardiac output/MICO group; n = 201) or usual care (control group; n = 187). The main outcome measure was the proportion of patients achieving hemodynamic stability within six hours of starting the study. Results The number of hemodynamic instability criteria at baseline (MICO group mean 2.0 (SD 1.0), control group 1.8 (1.0); P = .06) and severity of illness (SAPS II score; MICO group 48 (18), control group 48 (15); P = .86)) were similar. At 6 hrs, 45 patients (22%) in the MICO group and 52 patients (28%) in the control group were hemodynamically stable (mean difference 5%; 95% confidence interval of the difference -3 to 14%; P = .24). Hemodynamic support with fluids and vasoactive drugs, and pulmonary artery catheter use (MICO group: 19%, control group: 26%; P = .11) were similar in the two groups. The median length of ICU stay was 2.0 (interquartile range 1.2 to 4.6) days in the MICO group and 2.5 (1.1 to 5.0) days in the control group (P = .38). The hospital mortality was 26% in the MICO group and 21% in the control group (P = .34). Conclusions Minimally-invasive cardiac output monitoring added to usual care does not facilitate early hemodynamic stabilization in the ICU, nor does it alter the hemodynamic support or outcome. Our results emphasize the need to evaluate technologies used to measure stroke volume and cardiac output--especially their impact on the process of care--before any large-scale outcome studies are attempted.

Managing water resources in dynamic settings: A multi-level, multi-stakeholder perspective

The aim of the present article is to contribute to the debate on the role of research in sustainable management of water and related resources, based on experiences in the Upper Ewaso Ng’iro and Pangani river basins in East Africa. Both basins are characterised by humid, resource-rich highlands and extensive semi-arid lowlands, by growing demand for water and related resources, and by numerous conflicting stakeholder interests. Issues of scale and level, on the one hand, and the normative dimension of sustainability, on the other hand, are identified as key challenges for research that seeks to produce relevant and applicable results for informed decision-making. A multi-level and multi-stakeholder perspective, defined on the basis of three minimal principles, is proposed here as an approach to research for informed decision-making. Key lessons learnt from applying these principles in the two river basins are presented and discussed in the light of current debate.

Clinical application and reliability of a post abdominal surgery pain assessment scale (PASPAS) in horses

The aim of this study was to refine a multi-dimensional scale based on physiological and behavioural parameters, known as the post abdominal surgery pain assessment scale (PASPAS), to quantify pain after laparotomy in horses. After a short introduction, eight observers used the scale to assess eight horses at multiple time points after laparotomy. In addition, a single observer was used to test the correlation of each parameter with the total pain index in 34 patients, and the effect of general anaesthesia on PASPAS was investigated in a control group of eight horses. Inter-observer variability was low (coefficient of variation 0.3), which indicated good reliability of PASPAS. The correlation of individual parameters with the total pain index differed between parameters. PASPAS, which was not influenced by general anaesthesia, was a useful tool to evaluate pain in horses after abdominal surgery and may also be useful to investigate analgesic protocols or for teaching purposes.

Study design, baseline patient characteristics and intervention in a cross-cultural framework: results from the ADORE study

OBJECTIVE : To describe the methodology and to present the baseline findings of the Attention-deficit/hyperactivity Disorder Observational Research in Europe (ADORE) study, the primary objective of which is to describe the relationship between treatment regimen prescribed and quality of life of children with ADHD in actual practice. METHODS : In this 2-year prospective observational study, data on diagnosis, prescribed treatment and outcomes of ADHD were collected at seven time points by paediatricians and child psychiatrists on 1,573 children recruited in 10 European countries. The data presented here from the 1,478 patients included in the analyses describe the baseline condition, initial treatment regimen prescribed and quality of life of families with children with ADHD. RESULTS : Patients had a mean age of 9.0 years (SD 2.5) and 84% were male. Physicians diagnoses were made using DSM-IV (43 %), ICD-10 (32%) and both DSM-IV and ICD-10 (12 %). Mean age of awareness of a problem was 5.1 years, suggesting an average delay of approximately 4 years between awareness and diagnosis of ADHD. Baseline ADHD rating scale scores (physicianrated) indicated moderate to severe ADHD. Parent-rated SDQ scores were in agreement and suggested significant levels of co-existing problems. CGI-S, CGAS and CHIPCE scores also indicated significant impairment. Patients were offered the following treatments after the initial assessment: pharmacotherapy (25 %), psychotherapy (19 %), combination of pharmacotherapy and psychotherapy (25 %), other therapy (10 %) and no treatment (21 %). CONCLUSION : The ADORE study shows that ADHD is similarly recognised across 10 European countries and that the children are significantly impaired across a wide range of domains. In this respect, they resemble children described in previous ADHD samples.

The Importance of Scale for Spatial-confounding Bias and Precision of Spatial Regression Estimators

Increasingly, regression models are used when residuals are spatially correlated. Prominent examples include studies in environmental epidemiology to understand the chronic health effects of pollutants. I consider the effects of residual spatial structure on the bias and precision of regression coefficients, developing a simple framework in which to understand the key issues and derive informative analytic results. When the spatial residual is induced by an unmeasured confounder, regression models with spatial random effects and closely-related models such as kriging and penalized splines are biased, even when the residual variance components are known. Analytic and simulation results show how the bias depends on the spatial scales of the covariate and the residual; bias is reduced only when there is variation in the covariate at a scale smaller than the scale of the unmeasured confounding. I also discuss how the scales of the residual and the covariate affect efficiency and uncertainty estimation when the residuals can be considered independent of the covariate. In an application on the association between black carbon particulate matter air pollution and birth weight, controlling for large-scale spatial variation appears to reduce bias from unmeasured confounders, while increasing uncertainty in the estimated pollution effect.

Underestimation of Standard Errors in Multi-Site Time Series Studies

Multi-site time series studies of air pollution and mortality and morbidity have figured prominently in the literature as comprehensive approaches for estimating acute effects of air pollution on health. Hierarchical models are generally used to combine site-specific information and estimate pooled air pollution effects taking into account both within-site statistical uncertainty, and across-site heterogeneity. Within a site, characteristics of time series data of air pollution and health (small pollution effects, missing data, highly correlated predictors, non linear confounding etc.) make modelling all sources of uncertainty challenging. One potential consequence is underestimation of the statistical variance of the site-specific effects to be combined. In this paper we investigate the impact of variance underestimation on the pooled relative rate estimate. We focus on two-stage normal-normal hierarchical models and on under- estimation of the statistical variance at the first stage. By mathematical considerations and simulation studies, we found that variance underestimation does not affect the pooled estimate substantially. However, some sensitivity of the pooled estimate to variance underestimation is observed when the number of sites is small and underestimation is severe. These simulation results are applicable to any two-stage normal-normal hierarchical model for combining information of site-specific results, and they can be easily extended to more general hierarchical formulations. We also examined the impact of variance underestimation on the national average relative rate estimate from the National Morbidity Mortality Air Pollution Study and we found that variance underestimation as much as 40% has little effect on the national average.