Análise das distorções em leituras angulares de imagens fotográficas

CONTEXTUALIZAÇÃO: A biofotogrametria é uma técnica difundida na área da saúde e, apesar dos cuidados metodológicos, há distorções nas leituras angulares das imagens fotográficas. OBJETIVO: Mensurar o erro das medidas angulares em imagens fotográficas com diferentes resoluções digitais em um objeto com ângulos pré-demarcados. MÉTODOS: Utilizou-se uma esfera de borracha com 52 cm de circunferência. O objeto foi previamente demarcado com ângulos de 10º, 30º, 60º e 90º, e os registros fotográficos foram realizados com o eixo focal da câmera a três metros de distância e perpendicular ao objeto, sem utilização de zoom óptico e com resolução de 3, 5 e 10 Megapixels (Mp). Todos os registros fotográficos foram armazenados, e os valores angulares foram analisados por um experimentador previamente treinado, utilizando o programa ImageJ. As aferições das medidas foram realizadas duas vezes, com intervalo de 15 dias entre elas. Posteriormente, foram calculados os valores de acurácia, erro relativo e em graus, precisão e Coeficiente de Correlação Intraclasse (ICC). RESULTADOS: Quando analisado o ângulo de 10º, a média da acurácia das medidas foi maior para os registros com resolução de 3 Mp em relação às resoluções de 5 e 10 Mp. O ICC foi considerado excelente para as três resoluções de imagem analisadas e, em relação aos ângulos analisados nos registros fotográficos, pôde-se verificar maior acurácia, menor erro relativo e em graus e maior precisão para o ângulo de 90º, independentemente da resolução da imagem. CONCLUSÃO: Os registros fotográficos realizados com a resolução de 3 Mp proporcionaram medidas de maiores valores de acurácia e precisão e menores valores de erro, sugerindo ser a resolução mais adequada para gerar imagem de ângulos de 10º e 30º.

Differential Proteomic Analysis of Noncardia Gastric Cancer from Individuals of Northern Brazil

Gastric cancer is the second leading cause of cancer-related death worldwide. The identification of new cancer biomarkers is necessary to reduce the mortality rates through the development of new screening assays and early diagnosis, as well as new target therapies. In this study, we performed a proteomic analysis of noncardia gastric neoplasias of individuals from Northern Brazil. The proteins were analyzed by two-dimensional electrophoresis and mass spectrometry. For the identification of differentially expressed proteins, we used statistical tests with bootstrapping resampling to control the type I error in the multiple comparison analyses. We identified 111 proteins involved in gastric carcinogenesis. The computational analysis revealed several proteins involved in the energy production processes and reinforced the Warburg effect in gastric cancer. ENO1 and HSPB1 expression were further evaluated. ENO1 was selected due to its role in aerobic glycolysis that may contribute to the Warburg effect. Although we observed two up-regulated spots of ENO1 in the proteomic analysis, the mean expression of ENO1 was reduced in gastric tumors by western blot. However, mean ENO1 expression seems to increase in more invasive tumors. This lack of correlation between proteomic and western blot analyses may be due to the presence of other ENO1 spots that present a slightly reduced expression, but with a high impact in the mean protein expression. In neoplasias, HSPB1 is induced by cellular stress to protect cells against apoptosis. In the present study, HSPB1 presented an elevated protein and mRNA expression in a subset of gastric cancer samples. However, no association was observed between HSPB1 expression and clinicopathological characteristics. Here, we identified several possible biomarkers of gastric cancer in individuals from Northern Brazil. These biomarkers may be useful for the assessment of prognosis and stratification for therapy if validated in larger clinical study sets.

Effect of temperature and storage time on cellular analysis of fresh pleural fluid samples

L. Antonangelo, F. S. Vargas, M. M. P. Acencio, A. P. Cora, L. R. Teixeira, E. H. Genofre and R. K. B. Sales Effect of temperature and storage time on cellular analysis of fresh pleural fluid samples Objective: Despite the methodological variability in preparation techniques for pleural fluid cytology, it is fundamental that the cells should be preserved, permitting adequate morphological classification. We evaluated numerical and morphological changes in pleural fluid specimens processed after storage at room temperature or under refrigeration. Methods: Aliquots of pleural fluid from 30 patients, collected in ethylenediaminetetraacetic acid-coated tubes and maintained at room temperature (21 degrees C) or refrigeration (4 degrees C) were evaluated after 2 and 6 hours and 1, 2, 3, 4, 7 and 14 days. Evaluation of cytomorphology and global and percentage counts of leucocytes, macrophages and mesothelial cells were included. Results: The samples had quantitative cellular variations from day 3 or 4 onwards, depending on the storage conditions. Morphological alterations occurred earlier in samples maintained at room temperature (day 2) than in those under refrigeration (day 4). Conclusions: This study confirms that storage time and temperature are potential pre-analytical causes of error in pleural fluid cytology.

Interpolation estimate for a finite-element space with embedded discontinuities

We consider a recently proposed finite-element space that consists of piecewise affine functions with discontinuities across a smooth given interface Γ (a curve in two dimensions, a surface in three dimensions). Contrary to existing extended finite element methodologies, the space is a variant of the standard conforming Formula space that can be implemented element by element. Further, it neither introduces new unknowns nor deteriorates the sparsity structure. It is proved that, for u arbitrary in Formula, the interpolant Formula defined by this new space satisfies Graphic where h is the mesh size, Formula is the domain, Formula, Formula, Formula and standard notation has been adopted for the function spaces. This result proves the good approximation properties of the finite-element space as compared to any space consisting of functions that are continuous across Γ, which would yield an error in the Formula-norm of order Graphic. These properties make this space especially attractive for approximating the pressure in problems with surface tension or other immersed interfaces that lead to discontinuities in the pressure field. Furthermore, the result still holds for interfaces that end within the domain, as happens for example in cracked domains.

A regional multirnodulus algorithm for blind equalization of QAM signals: Introduction and steady-state analysis

It is well known that constant-modulus-based algorithms present a large mean-square error for high-order quadrature amplitude modulation (QAM) signals, which may damage the switching to decision-directed-based algorithms. In this paper, we introduce a regional multimodulus algorithm for blind equalization of QAM signals that performs similar to the supervised normalized least-mean-squares (NLMS) algorithm, independently of the QAM order. We find a theoretical relation between the coefficient vector of the proposed algorithm and the Wiener solution and also provide theoretical models for the steady-state excess mean-square error in a nonstationary environment. The proposed algorithm in conjunction with strategies to speed up its convergence and to avoid divergence can bypass the switching mechanism between the blind mode and the decision-directed mode. (c) 2012 Elsevier B.V. All rights reserved.

Enabling Blocks for Integrated CMOS UWB Transceivers

The last decades have seen an unrivaled growth and diffusion of mobile telecommunications. Several standards have been developed to this purposes, from GSM mobile phone communications to WLAN IEEE 802.11, providing different services for the the transmission of signals ranging from voice to high data rate digital communications and Digital Video Broadcasting (DVB). In this wide research and market field, this thesis focuses on Ultra Wideband (UWB) communications, an emerging technology for providing very high data rate transmissions over very short distances. In particular the presented research deals with the circuit design of enabling blocks for MB-OFDM UWB CMOS single-chip transceivers, namely the frequency synthesizer and the transmission mixer and power amplifier. First we discuss three different models for the simulation of chargepump phase-locked loops, namely the continuous time s-domain and discrete time z-domain approximations and the exact semi-analytical time-domain model. The limitations of the two approximated models are analyzed in terms of error in the computed settling time as a function of loop parameters, deriving practical conditions under which the different models are reliable for fast settling PLLs up to fourth order. Besides, a phase noise analysis method based upon the time-domain model is introduced and compared to the results obtained by means of the s-domain model. We compare the three models over the simulation of a fast switching PLL to be integrated in a frequency synthesizer for WiMedia MB-OFDM UWB systems. In the second part, the theoretical analysis is applied to the design of a 60mW 3.4 to 9.2GHz 12 Bands frequency synthesizer for MB-OFDM UWB based on two wide-band PLLs. The design is presented and discussed up to layout level. A test chip has been implemented in TSMC CMOS 90nm technology, measured data is provided. The functionality of the circuit is proved and specifications are met with state-of-the-art area occupation and power consumption. The last part of the thesis deals with the design of a transmission mixer and a power amplifier for MB-OFDM UWB band group 1. The design has been carried on up to layout level in ST Microlectronics 65nm CMOS technology. Main characteristics of the systems are the wideband behavior (1.6 GHz of bandwidth) and the constant behavior over process parameters, temperature and supply voltage thanks to the design of dedicated adaptive biasing circuits.

MCAO for Extremely Large Telescopes: the cases of LBT and E-ELT

Several MCAO systems are under study to improve the angular resolution of the current and of the future generation large ground-based telescopes (diameters in the 8-40 m range). The subject of this PhD Thesis is embedded in this context. Two MCAO systems, in dierent realization phases, are addressed in this Thesis: NIRVANA, the 'double' MCAO system designed for one of the interferometric instruments of LBT, is in the integration and testing phase; MAORY, the future E-ELT MCAO module, is under preliminary study. These two systems takle the sky coverage problem in two dierent ways. The layer oriented approach of NIRVANA, coupled with multi-pyramids wavefront sensors, takes advantage of the optical co-addition of the signal coming from up to 12 NGS in a annular 2' to 6' technical FoV and up to 8 in the central 2' FoV. Summing the light coming from many natural sources permits to increase the limiting magnitude of the single NGS and to improve considerably the sky coverage. One of the two Wavefront Sensors for the mid- high altitude atmosphere analysis has been integrated and tested as a stand- alone unit in the laboratory at INAF-Osservatorio Astronomico di Bologna and afterwards delivered to the MPIA laboratories in Heidelberg, where was integrated and aligned to the post-focal optical relay of one LINC-NIRVANA arm. A number of tests were performed in order to characterize and optimize the system functionalities and performance. A report about this work is presented in Chapter 2. In the MAORY case, to ensure correction uniformity and sky coverage, the LGS-based approach is the current baseline. However, since the Sodium layer is approximately 10 km thick, the articial reference source looks elongated, especially when observed from the edge of a large aperture. On a 30-40 m class telescope, for instance, the maximum elongation varies between few arcsec and 10 arcsec, depending on the actual telescope diameter, on the Sodium layer properties and on the laser launcher position. The centroiding error in a Shack-Hartmann WFS increases proportionally to the elongation (in a photon noise dominated regime), strongly limiting the performance. To compensate for this effect a straightforward solution is to increase the laser power, i.e. to increase the number of detected photons per subaperture. The scope of Chapter 3 is twofold: an analysis of the performance of three dierent algorithms (Weighted Center of Gravity, Correlation and Quad-cell) for the instantaneous LGS image position measurement in presence of elongated spots and the determination of the required number of photons to achieve a certain average wavefront error over the telescope aperture. An alternative optical solution to the spot elongation problem is proposed in Section 3.4. Starting from the considerations presented in Chapter 3, a first order analysis of the LGS WFS for MAORY (number of subapertures, number of detected photons per subaperture, RON, focal plane sampling, subaperture FoV) is the subject of Chapter 4. An LGS WFS laboratory prototype was designed to reproduce the relevant aspects of an LGS SH WFS for the E-ELT and to evaluate the performance of different centroid algorithms in presence of elongated spots as investigated numerically and analytically in Chapter 3. This prototype permits to simulate realistic Sodium proles. A full testing plan for the prototype is set in Chapter 4.

Cooperative Wireless Networks for Localization

This thesis adresses the problem of localization, and analyzes its crucial aspects, within the context of cooperative WSNs. The three main issues discussed in the following are: network synchronization, position estimate and tracking. Time synchronization is a fundamental requirement for every network. In this context, a new approach based on the estimation theory is proposed to evaluate the ultimate performance limit in network time synchronization. In particular the lower bound on the variance of the average synchronization error in a fully connected network is derived by taking into account the statistical characterization of the Message Delivering Time (MDT) . Sensor network localization algorithms estimate the locations of sensors with initially unknown location information by using knowledge of the absolute positions of a few sensors and inter-sensor measurements such as distance and bearing measurements. Concerning this issue, i.e. the position estimate problem, two main contributions are given. The first is a new Semidefinite Programming (SDP) framework to analyze and solve the problem of flip-ambiguity that afflicts range-based network localization algorithms with incomplete ranging information. The occurrence of flip-ambiguous nodes and errors due to flip ambiguity is studied, then with this information a new SDP formulation of the localization problem is built. Finally a flip-ambiguity-robust network localization algorithm is derived and its performance is studied by Monte-Carlo simulations. The second contribution in the field of position estimate is about multihop networks. A multihop network is a network with a low degree of connectivity, in which couples of given any nodes, in order to communicate, they have to rely on one or more intermediate nodes (hops). Two new distance-based source localization algorithms, highly robust to distance overestimates, typically present in multihop networks, are presented and studied. The last point of this thesis discuss a new low-complexity tracking algorithm, inspired by the Fano’s sequential decoding algorithm for the position tracking of a user in a WLAN-based indoor localization system.

Imaging of crustal scatterers using multiple seismic arrays

Array seismology is an useful tool to perform a detailed investigation of the Earth’s interior. Seismic arrays by using the coherence properties of the wavefield are able to extract directivity information and to increase the ratio of the coherent signal amplitude relative to the amplitude of incoherent noise. The Double Beam Method (DBM), developed by Krüger et al. (1993, 1996), is one of the possible applications to perform a refined seismic investigation of the crust and mantle by using seismic arrays. The DBM is based on a combination of source and receiver arrays leading to a further improvement of the signal-to-noise ratio by reducing the error in the location of coherent phases. Previous DBM works have been performed for mantle and core/mantle resolution (Krüger et al., 1993; Scherbaum et al., 1997; Krüger et al., 2001). An implementation of the DBM has been presented at 2D large-scale (Italian data-set for Mw=9.3, Sumatra earthquake) and at 3D crustal-scale as proposed by Rietbrock & Scherbaum (1999), by applying the revised version of Source Scanning Algorithm (SSA; Kao & Shan, 2004). In the 2D application, the rupture front propagation in time has been computed. In 3D application, the study area (20x20x33 km3), the data-set and the source-receiver configurations are related to the KTB-1994 seismic experiment (Jost et al., 1998). We used 60 short-period seismic stations (200-Hz sampling rate, 1-Hz sensors) arranged in 9 small arrays deployed in 2 concentric rings about 1 km (A-arrays) and 5 km (B-array) radius. The coherence values of the scattering points have been computed in the crustal volume, for a finite time-window along all array stations given the hypothesized origin time and source location. The resulting images can be seen as a (relative) joint log-likelihood of any point in the subsurface that have contributed to the full set of observed seismograms.

Reinforcement Lernen mit Regularisierungsnetzwerken

Die Arbeit behandelt das Problem der Skalierbarkeit von Reinforcement Lernen auf hochdimensionale und komplexe Aufgabenstellungen. Unter Reinforcement Lernen versteht man dabei eine auf approximativem Dynamischen Programmieren basierende Klasse von Lernverfahren, die speziell Anwendung in der Künstlichen Intelligenz findet und zur autonomen Steuerung simulierter Agenten oder realer Hardwareroboter in dynamischen und unwägbaren Umwelten genutzt werden kann. Dazu wird mittels Regression aus Stichproben eine Funktion bestimmt, die die Lösung einer "Optimalitätsgleichung" (Bellman) ist und aus der sich näherungsweise optimale Entscheidungen ableiten lassen. Eine große Hürde stellt dabei die Dimensionalität des Zustandsraums dar, die häufig hoch und daher traditionellen gitterbasierten Approximationsverfahren wenig zugänglich ist. Das Ziel dieser Arbeit ist es, Reinforcement Lernen durch nichtparametrisierte Funktionsapproximation (genauer, Regularisierungsnetze) auf -- im Prinzip beliebig -- hochdimensionale Probleme anwendbar zu machen. Regularisierungsnetze sind eine Verallgemeinerung von gewöhnlichen Basisfunktionsnetzen, die die gesuchte Lösung durch die Daten parametrisieren, wodurch die explizite Wahl von Knoten/Basisfunktionen entfällt und so bei hochdimensionalen Eingaben der "Fluch der Dimension" umgangen werden kann. Gleichzeitig sind Regularisierungsnetze aber auch lineare Approximatoren, die technisch einfach handhabbar sind und für die die bestehenden Konvergenzaussagen von Reinforcement Lernen Gültigkeit behalten (anders als etwa bei Feed-Forward Neuronalen Netzen). Allen diesen theoretischen Vorteilen gegenüber steht allerdings ein sehr praktisches Problem: der Rechenaufwand bei der Verwendung von Regularisierungsnetzen skaliert von Natur aus wie O(n**3), wobei n die Anzahl der Daten ist. Das ist besonders deswegen problematisch, weil bei Reinforcement Lernen der Lernprozeß online erfolgt -- die Stichproben werden von einem Agenten/Roboter erzeugt, während er mit der Umwelt interagiert. Anpassungen an der Lösung müssen daher sofort und mit wenig Rechenaufwand vorgenommen werden. Der Beitrag dieser Arbeit gliedert sich daher in zwei Teile: Im ersten Teil der Arbeit formulieren wir für Regularisierungsnetze einen effizienten Lernalgorithmus zum Lösen allgemeiner Regressionsaufgaben, der speziell auf die Anforderungen von Online-Lernen zugeschnitten ist. Unser Ansatz basiert auf der Vorgehensweise von Recursive Least-Squares, kann aber mit konstantem Zeitaufwand nicht nur neue Daten sondern auch neue Basisfunktionen in das bestehende Modell einfügen. Ermöglicht wird das durch die "Subset of Regressors" Approximation, wodurch der Kern durch eine stark reduzierte Auswahl von Trainingsdaten approximiert wird, und einer gierigen Auswahlwahlprozedur, die diese Basiselemente direkt aus dem Datenstrom zur Laufzeit selektiert. Im zweiten Teil übertragen wir diesen Algorithmus auf approximative Politik-Evaluation mittels Least-Squares basiertem Temporal-Difference Lernen, und integrieren diesen Baustein in ein Gesamtsystem zum autonomen Lernen von optimalem Verhalten. Insgesamt entwickeln wir ein in hohem Maße dateneffizientes Verfahren, das insbesondere für Lernprobleme aus der Robotik mit kontinuierlichen und hochdimensionalen Zustandsräumen sowie stochastischen Zustandsübergängen geeignet ist. Dabei sind wir nicht auf ein Modell der Umwelt angewiesen, arbeiten weitestgehend unabhängig von der Dimension des Zustandsraums, erzielen Konvergenz bereits mit relativ wenigen Agent-Umwelt Interaktionen, und können dank des effizienten Online-Algorithmus auch im Kontext zeitkritischer Echtzeitanwendungen operieren. Wir demonstrieren die Leistungsfähigkeit unseres Ansatzes anhand von zwei realistischen und komplexen Anwendungsbeispielen: dem Problem RoboCup-Keepaway, sowie der Steuerung eines (simulierten) Oktopus-Tentakels.

Systematic investigation of automated plan generation for breast cancer including beam angle and isocenter selection

Il tumore al seno è il più comune tra le donne nel mondo. La radioterapia è comunemente usata dopo la chirurgia per distruggere eventuali cellule maligne rimaste nel volume del seno. Nei trattamenti di radioterapia bisogna cercare di irradiare il volume da curare limitando contemporaneamente la tossicità nei tessuti sani. In clinica i parametri che definiscono il piano di trattamento radioterapeutico sono selezionati manualmente utilizzando un software di simulazione per trattamenti. Questo processo, detto di trial and error, in cui i differenti parametri vengono modificati e il trattamento viene simulato nuovamente e valutato, può richiedere molte iterazioni rendendolo dispendioso in termini di tempo. Lo studio presentato in questa tesi si concentra sulla generazione automatica di piani di trattamento per irradiare l'intero volume del seno utilizzando due fasci approssimativamente opposti e tangenti al paziente. In particolare ci siamo concentrati sulla selezione delle direzioni dei fasci e la posizione dell'isocentro. A questo scopo, è stato investigata l'efficacia di un approccio combinatorio, nel quale sono stati generati un elevato numero di possibili piani di trattamento utilizzando differenti combinazioni delle direzioni dei due fasci. L'intensità del profilo dei fasci viene ottimizzata automaticamente da un algoritmo, chiamato iCycle, sviluppato nel ospedale Erasmus MC di Rotterdam. Inizialmente tra tutti i possibili piani di trattamento generati solo un sottogruppo viene selezionato, avente buone caratteristiche per quel che riguarda l'irraggiamento del volume del seno malato. Dopo di che i piani che mostrano caratteristiche ottimali per la salvaguardia degli organi a rischio (cuore, polmoni e seno controlaterale) vengono considerati. Questi piani di trattamento sono matematicamente equivalenti quindi per selezionare tra questi il piano migliore è stata utilizzata una somma pesata dove i pesi sono stati regolati per ottenere in media piani che abbiano caratteristiche simili ai piani di trattamento approvati in clinica. Questo metodo in confronto al processo manuale oltre a ridurre considerevol-mente il tempo di generazione di un piano di trattamento garantisce anche i piani selezionati abbiano caratteristiche ottimali nel preservare gli organi a rischio. Inizialmente è stato utilizzato l'isocentro scelto in clinica dal tecnico. Nella parte finale dello studio l'importanza dell'isocentro è stata valutata; ne è risultato che almeno per un sottogruppo di pazienti la posizione dell'isocentro può dare un importante contributo alla qualità del piano di trattamento e quindi potrebbe essere un ulteriore parametro da ottimizzare. 

Concept and realization of the A4 compton backscattering polarimeter at MAMI

The main concern of the A4 parity violation experiment at the Mainzer Microtron accelerator facility is to study the electric and magnetic contributions of strange quarks to the charge and magnetism of the nucleons at the low momentum transfer region. More precisely, the A4 collaboration investigates the strange quarks' contribution to the electric and magnetic vector form factors of the nucleons. Thus, it is important that the A4 experiment uses an adequate and precise non-destructive online monitoring tool for the electron beam polarization when measuring single spin asymmetries in elastic scattering of polarized electrons from unpolarized nucleons. As a consequence, the A4 Compton backscattering polarimeter was designed and installed such that we can take the absolute measurement of the electron beam polarization without interruption to the parity violation experiment. The present study shows the development of an electron beam line that is called the chicane for the A4 Compton backscattering polarimeter. The chicane is an electron beam transport line and provides an interaction region where the electron beam and the laser beam overlap. After studying the properties of beam line components carefully, we developed an electron beam control system that makes a beam overlap between the electron beam and the laser beam. Using the system, we can easily achieve the beam overlap in a short time. The electron control system, of which the performance is outstanding, is being used in production beam times. And the study presents the development of a scintillating fiber electron detector that reduces the statistical error in the electron polarization measurement. We totally redesigned the scintillating fiber detector. The data that were taken during a 2008 beam time shows a huge background suppression, approximately 80 percent, while leaving the Compton spectra almost unchanged when a coincidence between the fiber detector and the photon detector is used. Thus, the statistical error of the polarization measurement is reduced by about 40 percent in the preliminary result. They are the significant progress in measuring a degree of polarization of the electron beam.

Reverse Engineering tools: development and experimentation of innovative methods for physical and geometrical data integration and post-processing

In recent years, the use of Reverse Engineering systems has got a considerable interest for a wide number of applications. Therefore, many research activities are focused on accuracy and precision of the acquired data and post processing phase improvements. In this context, this PhD Thesis deals with the definition of two novel methods for data post processing and data fusion between physical and geometrical information. In particular a technique has been defined for error definition in 3D points’ coordinates acquired by an optical triangulation laser scanner, with the aim to identify adequate correction arrays to apply under different acquisition parameters and operative conditions. Systematic error in data acquired is thus compensated, in order to increase accuracy value. Moreover, the definition of a 3D thermogram is examined. Object geometrical information and its thermal properties, coming from a thermographic inspection, are combined in order to have a temperature value for each recognizable point. Data acquired by an optical triangulation laser scanner are also used to normalize temperature values and make thermal data independent from thermal-camera point of view.

A Framework for the Automation of Discrete-Event Simulation Experiments

Simulation is an important resource for researchers in diverse fields. However, many researchers have found flaws in the methodology of published simulation studies and have described the state of the simulation community as being in a crisis of credibility. This work describes the project of the Simulation Automation Framework for Experiments (SAFE), which addresses the issues that undermine credibility by automating the workflow in the execution of simulation studies. Automation reduces the number of opportunities for users to introduce error in the scientific process thereby improvingthe credibility of the final results. Automation also eases the job of simulation users and allows them to focus on the design of models and the analysis of results rather than on the complexities of the workflow.

Limitations of Remotely-sensed Aerosol as a Spatial Proxy for Fine Particulate Matter

Recent research highlights the promise of remotely-sensed aerosol optical depth (AOD) as a proxy for ground-level PM2.5. Particular interest lies in the information on spatial heterogeneity potentially provided by AOD, with important application to estimating and monitoring pollution exposure for public health purposes. Given the temporal and spatio-temporal correlations reported between AOD and PM2.5 , it is tempting to interpret the spatial patterns in AOD as reflecting patterns in PM2.5 . Here we find only limited spatial associations of AOD from three satellite retrievals with PM2.5 over the eastern U.S. at the daily and yearly levels in 2004. We then use statistical modeling to show that the patterns in monthly average AOD poorly reflect patterns in PM2.5 because of systematic, spatially-correlated error in AOD as a proxy for PM2.5 . Furthermore, when we include AOD as a predictor of monthly PM2.5 in a statistical prediction model, AOD provides little additional information to improve predictions of PM2.5 when included in a model that already accounts for land use, emission sources, meteorology and regional variability. These results suggest caution in using spatial variation in AOD to stand in for spatial variation in ground-level PM2.5 in epidemiological analyses and indicate that when PM2.5 monitoring is available, careful statistical modeling outperforms the use of AOD.