Real-time heterodyned measurements of spatio-frequency dynamics in fibre lasers

We report high-resolution real-time measurements of spectrum evolution in a fibre. The proposed method combines optical heterodyning with a technique of spatio-temporal intensity measurements revealing fast spectral dynamics of cavity-based systems.

A coupled movement and bioenergetics model to explore the spawning migration of anchovy in the Bay of Biscay

Adult anchovies in the Bay of Biscay perform north to south migration from late winter to early summer for spawning. However, what triggers and drives the geographic shift of the population remains unclear and poorly understood. An individual-based fish model has been implemented to explore the potential mechanisms that control anchovy's movement routes toward its spawning habitats. To achieve this goal, two fish movement behaviors – gradient detection through restricted area search and kinesis – simulated fish response to its dynamic environment. A bioenergetics model was used to represent individual growth and reproduction along the fish trajectory. The environmental forcing (food, temperature) of the model was provided by a coupled physical–biogeochemical model. We followed a hypothesis-testing strategy to actualize a series of simulations using different cues and computational assumptions. The gradient detection behavior was found as the most suitable mechanism to recreate the observed shift of anchovy distribution under the combined effect of sea-surface temperature and zooplankton. In addition, our results suggested that southward movement occurred more actively from early April to middle May following favorably the spatio-temporal evolution of zooplankton and temperature. In terms of fish bioenergetics, individuals who ended up in the southern part of the bay presented better condition based on energy content, proposing the resulting energy gain as an ecological explanation for this migration. The kinesis approach resulted in a moderate performance, producing distribution pattern with the highest spread. Finally, model performance was not significantly affected by changes on the starting date, initial fish distribution and number of particles used in the simulations, whereas it was drastically influenced by the adopted cues.

Dynamic instabilities in scalar neural field equations with space-dependent delays

In this paper we consider a class of scalar integral equations with a form of space-dependent delay. These non-local models arise naturally when modelling neural tissue with active axons and passive dendrites. Such systems are known to support a dynamic (oscillatory) Turing instability of the homogeneous steady state. In this paper we develop a weakly nonlinear analysis of the travelling and standing waves that form beyond the point of instability. The appropriate amplitude equations are found to be the coupled mean-field Ginzburg-Landau equations describing a Turing-Hopf bifurcation with modulation group velocity of O(1). Importantly we are able to obtain the coefficients of terms in the amplitude equations in terms of integral transforms of the spatio-temporal kernels defining the neural field equation of interest. Indeed our results cover not only models with axonal or dendritic delays but those which are described by a more general distribution of delayed spatio-temporal interactions. We illustrate the predictive power of this form of analysis with comparison against direct numerical simulations, paying particular attention to the competition between standing and travelling waves and the onset of Benjamin-Feir instabilities.

Die mittelpleistozäne Flußentwicklung im nordöstlichen Harzvorland: Petrographie, Terrassenstratigraphie

The present study deals with the evolution of the middle Pleistocene river system in the north-eastern foreland of the Harz Mtns. Sediments of the middle fluvial terrace level (early Saalian time) are the main objectives. By using these sediments supplementary with some results of upper fluvial terrace level (early Elesterian time or older) the fluvial palaeogeography within the area has been reconstructed. The sediments were investigated with respect to their gravel spectra, heavy mineral record, sedimentary structures and altitude above the recent river beds. Due to the resulting specifics the sediments have been attributed to particular rivers in the area. Furthermore it is possible to distinguish between fluvial sediments and Elsterian as well as Saalian fluvioglacial deposits. Together with discernible middle or upper terrace characteristics this led to a spatio-temporal reconstruction of the palaeo river system of the Harz Mtns. It revealed that not only during upper terrace sedimentation but even while middle terraces were deposited the rivers partly diversed. These river diversions were mainly caused by hydrodynamic changes reflecting interaction of the fluvial system with Elsterian and Saalian ice shield formation in the north. The Rivers Ecker, Ilse, Rammelsbach, Holtemme, Goldbach, Bode, Selke and Eine were affected by this development as follows: Upper terrace level formation: • The Ecker River formerly ran between its recent river bed and that of the Use River in direction to the Großer Fallstein Mtn. • The Use River flowed to the NE towards the Huy Mtn. • The Goldbach River and the Holtemme River mutually ran to the NW south of the Huy Mtn. After uniting with the Use River and Ecker River it ran south of the Großer Fallstein Mtn. Middle terrace level formation: • The Ecker River flowed far more NE. • Near to the Harz Mtns. the Use River flowed more in the E. The tributary junction of the Rammelsbach River was located far more downstream. Thereafter the Use River ran to the N between Huy Mtn. and Großer Fallstein Mtn. to end up flowing in the area of the Großes Bruch. • The Holtemme River kept its course. Its recent tributary the Goldbach River flowed to the NE and joined the Bode River after leaving the Harz Mtn. Range. • The Eine River ran to the NW when passing todays city of Aschersleben. After flowing together with the Selke River in the area of the Seeländerei it became a tributary to the Bode River. • The Bode River within the recent tributary junction of the Holtemme ran far more in the W. In the area of the Espenbruch it flowed eastwards to the Saale River. The following general implications resulted out of the study: • The so called “mixed sediments” sensu Rosenberger & Altermann (1975) have now been interpreted as proximal fluvioglacial deposits. • High altitudes of middle terrace fluvial deposits in the courses of the Ecker River and Use River were formerly assigned to post middle Pleistocene uplift of the Großer Fallstein Mtn. (Feldmann, 2002). The present study suggests that the unusual high altitudes should rather be attributed to post middle terrace level erosion of the shortened Ilse- Rammelsbach river system or fluvioglacial processes below the glacier. • Within the north-eastern foreland of the Harz Mtns. middle terrace level deposits have previously been subdivided by cryoturbation horizons or short-term progradation of Saalian glaciation. This is not supported by own results for the examined area.

Effects of trawling on sessile megabenthos in the Great Barrier Reef and evaluation of the efficacy of management strategies

A series of related research studies over 15 years assessed the effects of prawn trawling on sessile megabenthos in the Great Barrier Reef, to support management for sustainable use in the World Heritage Area. These large-scale studies estimated impacts on benthos (particularly removal rates per trawl pass), monitored subsequent recovery rates, measured natural dynamics of tagged megabenthos, mapped the regional distribution of seabed habitats and benthic species, and integrated these results in a dynamic modelling framework together with spatio-temporal fishery effort data and simulated management. Typical impact rates were between 5 and 25% per trawl, recovery times ranged from several years to several decades, and most sessile megabenthos were naturally distributed in areas where little or no trawling occurred and so had low exposure to trawling. The model simulated trawl impact and recovery on the mapped species distributions, and estimated the regional scale cumulative changes due to trawling as a time series of status for megabenthos species. The regional status of these taxa at time of greatest depletion ranged from ∼77% relative to pre-trawl abundance for the worst case species, having slow recovery with moderate exposure to trawling, to ∼97% for the least affected taxon. The model also evaluated the expected outcomes for sessile megabenthos in response to major management interventions implemented between 1999 and 2006, including closures, effort reductions, and protected areas. As a result of these interventions, all taxa were predicted to recover (by 2-14% at 2025); the most affected species having relatively greater recovery. Effort reductions made the biggest positive contributions to benthos status for all taxa, with closures making smaller contributions for some taxa. The results demonstrated that management actions have arrested and reversed previous unsustainable trends for all taxa assessed, and have led to a prawn trawl fishery with improved environmental sustainability. © 2015 International Council for the Exploration of the Sea 2015. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Modelling human behaviour and event detection from videos

Automatic analysis of human behaviour in large collections of videos is gaining interest, even more so with the advent of file sharing sites such as YouTube. However, challenges still exist owing to several factors such as inter- and intra-class variations, cluttered backgrounds, occlusion, camera motion, scale, view and illumination changes. This research focuses on modelling human behaviour for action recognition in videos. The developed techniques are validated on large scale benchmark datasets and applied on real-world scenarios such as soccer videos. Three major contributions are made. The first contribution is in the area of proper choice of a feature representation for videos. This involved a study of state-of-the-art techniques for action recognition, feature extraction processing and dimensional reduction techniques so as to yield the best performance with optimal computational requirements. Secondly, temporal modelling of human behaviour is performed. This involved frequency analysis and temporal integration of local information in the video frames to yield a temporal feature vector. Current practices mostly average the frame information over an entire video and neglect the temporal order. Lastly, the proposed framework is applied and further adapted to real-world scenario such as soccer videos. A dataset consisting of video sequences depicting events of players falling is created from actual match data to this end and used to experimentally evaluate the proposed framework.

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.

Large-scale neural dynamics: simple and complex

We review the use of neural field models for modelling the brain at the large scales necessary for interpreting EEG, fMRI, MEG and optical imaging data. Albeit a framework that is limited to coarse-grained or mean-field activity, neural field models provide a framework for unifying data from different imaging modalities. Starting with a description of neural mass models we build to spatially extended cortical models of layered two-dimensional sheets with long range axonal connections mediating synaptic interactions. Reformulations of the fundamental non-local mathematical model in terms of more familiar local differential (brain wave) equations are described. Techniques for the analysis of such models, including how to determine the onset of spatio-temporal pattern forming instabilities, are reviewed. Extensions of the basic formalism to treat refractoriness, adaptive feedback and inhomogeneous connectivity are described along with open challenges for the development of multi-scale models that can integrate macroscopic models at large spatial scales with models at the microscopic scale.

Prevalencia e incidencia de cáncer en habitantes de Sibaté, y georeferenciación de casos 2010-2014

Introducción: El Cáncer es prevenible en algunos casos, si se evita la exposición a sustancias cancerígenas en el medio ambiente. En Colombia, Cundinamarca es uno de los departamentos con mayores incrementos en la tasa de mortalidad y en el municipio de Sibaté, habitantes han manifestado preocupación por el incremento de la enfermedad. En el campo de la salud ambiental mundial, la georreferenciación aplicada al estudio de fenómenos en salud, ha tenido éxito con resultados válidos. El estudio propuso usar herramientas de información geográfica, para generar análisis de tiempo y espacio que hicieran visible el comportamiento del cáncer en Sibaté y sustentaran hipótesis de influencias ambientales sobre concentraciones de casos. Objetivo: Obtener incidencia y prevalencia de casos de cáncer en habitantes de Sibaté y georreferenciar los casos en un periodo de 5 años, con base en indagación de registros. Metodología: Estudio exploratorio descriptivo de corte transversal,sobre todos los diagnósticos de cáncer entre los años 2010 a 2014, encontrados en los archivos de la Secretaria de Salud municipal. Se incluyeron unicamente quienes tuvieron residencia permanente en el municipio y fueron diagnosticados con cáncer entre los años de 2010 a 2104. Sobre cada caso se obtuvo género, edad, estrato socioeconómico, nivel académico, ocupación y estado civil. Para el análisis de tiempo se usó la fecha de diagnóstico y para el análisis de espacio, la dirección de residencia, tipo de cáncer y coordenada geográfica. Se generaron coordenadas geográficas con un equipo GPS Garmin y se crearon mapas con los puntos de la ubicación de las viviendas de los pacientes. Se proceso la información, con Epi Info 7 Resultados: Se encontraron 107 casos de cáncer registrados en la Secretaria de Salud de Sibaté, 66 mujeres, 41 hombres. Sin división de género, el 30.93% de la población presento cáncer del sistema reproductor, el 18,56% digestivo y el 17,53% tegumentario. Se presentaron 2 grandes casos de agrupaciones espaciales en el territorio estudiado, una en el Barrio Pablo Neruda con 12 (21,05%) casos y en el casco Urbano de Sibaté con 38 (66,67%) casos. Conclusión: Se corroboro que el análisis geográfico con variables espacio temporales y de exposición, puede ser la herramienta para generar hipótesis sobre asociaciones de casos de cáncer con factores ambientales.

Field-oriented assessment of agricultural crops through temporal segmentation of modis VI data.

Monitoring agricultural crops constitutes a vital task for the general understanding of land use spatio-temporal dynamics. This paper presents an approach for the enhancement of current crop monitoring capabilities on a regional scale, in order to allow for the analysis of environmental and socio-economic drivers and impacts of agricultural land use. This work discusses the advantages and current limitations of using 250m VI data from the Moderate Resolution Imaging Spectroradiometer (MODIS) for this purpose, with emphasis in the difficulty of correctly analyzing pixels whose temporal responses are disturbed due to certain sources of interference such as mixed or heterogeneous land cover. It is shown that the influence of noisy or disturbed pixels can be minimized, and a much more consistent and useful result can be attained, if individual agricultural fields are identified and each field's pixels are analyzed in a collective manner. As such, a method is proposed that makes use of image segmentation techniques based on MODIS temporal information in order to identify portions of the study area that agree with actual agricultural field borders. The pixels of each portion or segment are then analyzed individually in order to estimate the reliability of the temporal signal observed and the consequent relevance of any estimation of land use from that data. The proposed method was applied in the state of Mato Grosso, in mid-western Brazil, where extensive ground truth data was available. Experiments were carried out using several supervised classification algorithms as well as different subsets of land cover classes, in order to test the methodology in a comprehensive way. Results show that the proposed method is capable of consistently improving classification results not only in terms of overall accuracy but also qualitatively by allowing a better understanding of the land use patterns detected. It thus provides a practical and straightforward procedure for enhancing crop-mapping capabilities using temporal series of moderate resolution remote sensing data.

Monitoring time-dependent deformation patterns through geodetic techniques

In this thesis we focus on the analysis and interpretation of time dependent deformations recorded through different geodetic methods. Firstly, we apply a variational Bayesian Independent Component Analysis (vbICA) technique to GPS daily displacement solutions, to separate the postseismic deformation that followed the mainshocks of the 2016-2017 Central Italy seismic sequence from the other, hydrological, deformation sources. By interpreting the signal associated with the postseismic relaxation, we model an afterslip distribution on the faults involved by the mainshocks consistent with the co-seismic models available in literature. We find evidences of aseismic slip on the Paganica fault, responsible for the Mw 6.1 2009 L’Aquila earthquake, highlighting the importance of aseismic slip and static stress transfer to properly model the recurrence of earthquakes on nearby fault segments. We infer a possible viscoelastic relaxation of the lower crust as a contributing mechanism to the postseismic displacements. We highlight the importance of a proper separation of the hydrological signals for an accurate assessment of the tectonic processes, especially in cases of mm-scale deformations. Contextually, we provide a physical explanation to the ICs associated with the observed hydrological processes. In the second part of the thesis, we focus on strain data from Gladwin Tensor Strainmeters, working on the instruments deployed in Taiwan. We develop a novel approach, completely data driven, to calibrate these strainmeters. We carry out a joint analysis of geodetic (strainmeters, GPS and GRACE products) and hydrological (rain gauges and piezometers) data sets, to characterize the hydrological signals in Southern Taiwan. Lastly, we apply the calibration approach here proposed to the strainmeters recently installed in Central Italy. We provide, as an example, the detection of a storm that hit the Umbria-Marche regions (Italy), demonstrating the potential of strainmeters in following the dynamics of deformation processes with limited spatio-temporal signature

Polychaete assemblage of an impacted estuary, Guanabara Bay, Rio de Janeiro, Brazil

Thirty-eight stations were sampled in Guanabara Bay, Rio de Janeiro, Brazil, to assess the spatio-temporal diversity and biomass of sublittoral polychaetes. Samples were collected during the dry (September 2000) and rainy season (May 2001) in shallow sublittoral sediments. The polychaete spatial composition showed a heterogeneous distribution throughout the bay. A negative gradient of diversity and biomass was observed towards the inner parts of the bay and sheltered areas. A wide azoic area was found inside the bay. Some high-biomass and low-diversity spots were found near a sewage-discharge point. In these areas, the polychaete biomass increased after the rainy season. A diversified polychaete community was identified around the bay mouth, with no dramatic changes of this pattern between the two sampling periods. Deposit-feeders were dominant in the entire study area. The relative importance of carnivores and omnivores increased towards the outer sector, at stations with coarse sediment fractions. Guanabara Bay can be divided into three main zones with respect to environmental conditions and polychaete diversity and biomass patterns: A) High polychaete diversity, hydrodynamically exposed areas composed of sandy, oxidized or moderately reduced sediments with normoxic conditions in the water column. B) Low diversity and high biomass of deposit and suspension-feeding polychaete species in the middle part of the bay near continental inflows, comprising stations sharing similar proportions of silt, clay and fine sands. C) Azoic area or an impoverished polychaete community in hydrodynamically low-energy areas of silt and clay with extremely reduced sediments, high total organic matter content and hypoxic conditions in the water column, located essentially from the mid-bay towards the north sector. High total organic matter content and hypoxic conditions combined with slow water renewal in the inner bay seemed to play a key role in the polychaete diversity and biomass. Sedimentation processes and organic load coming from untreated sewage into the bay may have negatively affected the survivorship of the fauna.

A Dynamic Analysis of Tuberculosis Dissemination to Improve Control and Surveillance

Background: Detailed analysis of the dynamic interactions among biological, environmental, social, and economic factors that favour the spread of certain diseases is extremely useful for designing effective control strategies. Diseases like tuberculosis that kills somebody every 15 seconds in the world, require methods that take into account the disease dynamics to design truly efficient control and surveillance strategies. The usual and well established statistical approaches provide insights into the cause-effect relationships that favour disease transmission but they only estimate risk areas, spatial or temporal trends. Here we introduce a novel approach that allows figuring out the dynamical behaviour of the disease spreading. This information can subsequently be used to validate mathematical models of the dissemination process from which the underlying mechanisms that are responsible for this spreading could be inferred. Methodology/Principal Findings: The method presented here is based on the analysis of the spread of tuberculosis in a Brazilian endemic city during five consecutive years. The detailed analysis of the spatio-temporal correlation of the yearly geo-referenced data, using different characteristic times of the disease evolution, allowed us to trace the temporal path of the aetiological agent, to locate the sources of infection, and to characterize the dynamics of disease spreading. Consequently, the method also allowed for the identification of socio-economic factors that influence the process. Conclusions/Significance: The information obtained can contribute to more effective budget allocation, drug distribution and recruitment of human skilled resources, as well as guiding the design of vaccination programs. We propose that this novel strategy can also be applied to the evaluation of other diseases as well as other social processes.

Abundance of sedentary consumers and sessile organisms along the wave exposure gradient of subtropical rocky shores of the south-west Atlantic

Sedentary consumers play an important role on populations of prey and, hence, their patterns of abundance, distribution and coexistence on shores are important to evaluate their potential influence on ecosystem dynamics. Here, we aimed to describe their spatio-temporal distribution and abundance in relation to wave exposure in the intertidal rocky shores of the south-west Atlantic to provide a basis for further understanding of ecological processes in this system. The abundance and composition of the functional groups of sessile organisms and sedentary consumers were taken by sampling the intertidal of sheltered and moderately exposed shores during a period of one year. The sublittoral fringe of sheltered areas was dominated by macroalgae, while the low midlittoral was dominated by bare rock and barnacles. In contrast, filter-feeding animals prevailed at exposed shores, probably explaining the higher abundance of the predator Stramonita haemastoma at these locations. Limpets were more abundant at the midlittoral zone of all shores while sea urchins were exclusively found at the sublittoral fringe of moderately exposed shores, therefore, adding grazing pressure on these areas. The results showed patterns of coexistence, distribution and abundance of those organisms in this subtropical area, presumably as a result of wave action, competition and prey availability. It also brought insights on the influence of top-down and bottom-up processes in this area.

Animated solid model of the lung constructed from unsynchronized MR sequential images

This work discusses a 4D lung reconstruction method from unsynchronized MR sequential images. The lung, differently from the heart, does not have its own muscles, turning impossible to see its real movements. The visualization of the lung in motion is an actual topic of research in medicine. CT (Computerized Tomography) can obtain spatio-temporal images of the heart by synchronizing with electrocardiographic waves. The FOV of the heart is small when compared to the lung`s FOV. The lung`s movement is not periodic and is susceptible to variations in the degree of respiration. Compared to CT, MR (Magnetic Resonance) imaging involves longer acquisition times and it is not possible to obtain instantaneous 3D images of the lung. For each slice, only one temporal sequence of 2D images can be obtained. However, methods using MR are preferable because they do not involve radiation. In this paper, based on unsynchronized MR images of the lung an animated B-Repsolid model of the lung is created. The 3D animation represents the lung`s motion associated to one selected sequence of MR images. The proposed method can be divided in two parts. First, the lung`s silhouettes moving in time are extracted by detecting the presence of a respiratory pattern on 2D spatio-temporal MR images. This approach enables us to determine the lung`s silhouette for every frame, even on frames with obscure edges. The sequence of extracted lung`s silhouettes are unsynchronized sagittal and coronal silhouettes. Using our algorithm it is possible to reconstruct a 3D lung starting from a silhouette of any type (coronal or sagittal) selected from any instant in time. A wire-frame model of the lung is created by composing coronal and sagittal planar silhouettes representing cross-sections. The silhouette composition is severely underconstrained. Many wire-frame models can be created from the observed sequences of silhouettes in time. Finally, a B-Rep solid model is created using a meshing algorithm. Using the B-Rep solid model the volume in time for the right and left lungs were calculated. It was possible to recognize several characteristics of the 3D real right and left lungs in the shaded model. (C) 2007 Elsevier Ltd. All rights reserved.