Kernel-based methods for change detection in remote sensing images

Nowadays, the joint exploitation of images acquired daily by remote sensing instruments and of images available from archives allows a detailed monitoring of the transitions occurring at the surface of the Earth. These modifications of the land cover generate spectral discrepancies that can be detected via the analysis of remote sensing images. Independently from the origin of the images and of type of surface change, a correct processing of such data implies the adoption of flexible, robust and possibly nonlinear method, to correctly account for the complex statistical relationships characterizing the pixels of the images. This Thesis deals with the development and the application of advanced statistical methods for multi-temporal optical remote sensing image processing tasks. Three different families of machine learning models have been explored and fundamental solutions for change detection problems are provided. In the first part, change detection with user supervision has been considered. In a first application, a nonlinear classifier has been applied with the intent of precisely delineating flooded regions from a pair of images. In a second case study, the spatial context of each pixel has been injected into another nonlinear classifier to obtain a precise mapping of new urban structures. In both cases, the user provides the classifier with examples of what he believes has changed or not. In the second part, a completely automatic and unsupervised method for precise binary detection of changes has been proposed. The technique allows a very accurate mapping without any user intervention, resulting particularly useful when readiness and reaction times of the system are a crucial constraint. In the third, the problem of statistical distributions shifting between acquisitions is studied. Two approaches to transform the couple of bi-temporal images and reduce their differences unrelated to changes in land cover are studied. The methods align the distributions of the images, so that the pixel-wise comparison could be carried out with higher accuracy. Furthermore, the second method can deal with images from different sensors, no matter the dimensionality of the data nor the spectral information content. This opens the doors to possible solutions for a crucial problem in the field: detecting changes when the images have been acquired by two different sensors.

Evaluation of four whole-plant inoculation methods to analyze the pathogenicity of Erwinia amylovora under quarantine conditions

Four methods were tested to assess the fire-blight disease response on grafted pear plants. The leaves of the plants were inoculated with Erwinia amylovora suspensions by pricking with clamps, cutting with scissors, local infiltration, and painting a bacterial suspension onto the leaves with a paintbrush. The effects of the inoculation methods were studied in dose-time-response experiments carried out in climate chambers under quarantine conditions. A modified Gompertz model was used to analyze the disease-time relatiobbnships and provided information on the rate of infection progression (rg) and time delay to the start of symptoms (t0). The disease-pathogen-dose relationships were analyzed according to a hyperbolic saturation model in which the median effective dose (ED50) of the pathogen and maximum disease level (ymax) were determined. Localized infiltration into the leaf mesophile resulted in the early (short t0) but slow (low rg) development of infection whereas in leaves pricked with clamps disease symptoms developed late (long t0) but rapidly (high rg). Paintbrush inoculation of the plants resulted in an incubation period of medium length, a moderate rate of infection progression, and low ymax values. In leaves inoculated with scissors, fire-blight symptoms developed early (short t0) and rapidly (high rg), and with the lowest ED50 and the highest ymax

Body composition: overview of methods and future directions of research.

A short overview is given on the most important analytical body composition methods. Principles of the methods and advantages and limitations of the methods are discussed also in relation to other fields of research such as energy metabolism. Attention is given to some new developments in body composition research such as chemical multiple-compartment models, computerized tomography or nuclear magnetic resonance imaging (tissue level), and multifrequency bioelectrical impedance. Possible future directions of body composition research in the light of these new developments are discussed.

A comparative analysis of two methods for the calculation of electric-field-induced perturbations to molecular vibration

Two common methods of accounting for electric-field-induced perturbations to molecular vibration are analyzed and compared. The first method is based on a perturbation-theoretic treatment and the second on a finite-field treatment. The relationship between the two, which is not immediately apparent, is made by developing an algebraic formalism for the latter. Some of the higher-order terms in this development are documented here for the first time. As well as considering vibrational dipole polarizabilities and hyperpolarizabilities, we also make mention of the vibrational Stark effec

A comparative analysis by means of quantum molecular similarity measures of density distributions derived from conventional ab initio and density functional methods

A procedure based on quantum molecular similarity measures (QMSM) has been used to compare electron densities obtained from conventional ab initio and density functional methodologies at their respective optimized geometries. This method has been applied to a series of small molecules which have experimentally known properties and molecular bonds of diverse degrees of ionicity and covalency. Results show that in most cases the electron densities obtained from density functional methodologies are of a similar quality than post-Hartree-Fock generalized densities. For molecules where Hartree-Fock methodology yields erroneous results, the density functional methodology is shown to yield usually more accurate densities than those provided by the second order Møller-Plesset perturbation theory

A new all-round density functional based on spin states and SN2 barriers

We report here a new empirical density functional that is constructed based on the performance of OPBE and PBE for spin states and SN 2 reaction barriers and how these are affected by different regions of the reduced gradient expansion. In a previous study [Swart, Sol̀, and Bickelhaupt, J. Comput. Methods Sci. Eng. 9, 69 (2009)] we already reported how, by switching between OPBE and PBE, one could obtain both the good performance of OPBE for spin states and reaction barriers and that of PBE for weak interactions within one and the same (SSB-sw) functional. Here we fine tuned this functional and include a portion of the KT functional and Grimme's dispersion correction to account for π- π stacking. Our new SSB-D functional is found to be a clear improvement and functions very well for biological applications (hydrogen bonding, π -π stacking, spin-state splittings, accuracy of geometries, reaction barriers)

Two complementary molecular energy decomposition schemes: the Mayer and Ziegler-Rauk methods in comparison

In the present paper we discuss and compare two different energy decomposition schemes: Mayer's Hartree-Fock energy decomposition into diatomic and monoatomic contributions [Chem. Phys. Lett. 382, 265 (2003)], and the Ziegler-Rauk dissociation energy decomposition [Inorg. Chem. 18, 1558 (1979)]. The Ziegler-Rauk scheme is based on a separation of a molecule into fragments, while Mayer's scheme can be used in the cases where a fragmentation of the system in clearly separable parts is not possible. In the Mayer scheme, the density of a free atom is deformed to give the one-atom Mulliken density that subsequently interacts to give rise to the diatomic interaction energy. We give a detailed analysis of the diatomic energy contributions in the Mayer scheme and a close look onto the one-atom Mulliken densities. The Mulliken density ρA has a single large maximum around the nuclear position of the atom A, but exhibits slightly negative values in the vicinity of neighboring atoms. The main connecting point between both analysis schemes is the electrostatic energy. Both decomposition schemes utilize the same electrostatic energy expression, but differ in how fragment densities are defined. In the Mayer scheme, the electrostatic component originates from the interaction of the Mulliken densities, while in the Ziegler-Rauk scheme, the undisturbed fragment densities interact. The values of the electrostatic energy resulting from the two schemes differ significantly but typically have the same order of magnitude. Both methods are useful and complementary since Mayer's decomposition focuses on the energy of the finally formed molecule, whereas the Ziegler-Rauk scheme describes the bond formation starting from undeformed fragment densities

Health behaviours, socioeconomic status, and mortality: further analyses of the British Whitehall II and the French GAZEL prospective cohorts

BACKGROUND: Differences in morbidity and mortality between socioeconomic groups constitute one of the most consistent findings of epidemiologic research. However, research on social inequalities in health has yet to provide a comprehensive understanding of the mechanisms underlying this association. In recent analysis, we showed health behaviours, assessed longitudinally over the follow-up, to explain a major proportion of the association of socioeconomic status (SES) with mortality in the British Whitehall II study. However, whether health behaviours are equally important mediators of the SES-mortality association in different cultural settings remains unknown. In the present paper, we examine this issue in Whitehall II and another prospective European cohort, the French GAZEL study. METHODS AND FINDINGS: We included 9,771 participants from the Whitehall II study and 17,760 from the GAZEL study. Over the follow-up (mean 19.5 y in Whitehall II and 16.5 y in GAZEL), health behaviours (smoking, alcohol consumption, diet, and physical activity), were assessed longitudinally. Occupation (in the main analysis), education, and income (supplementary analysis) were the markers of SES. The socioeconomic gradient in smoking was greater (p<0.001) in Whitehall II (odds ratio [OR] = 3.68, 95% confidence interval [CI] 3.11-4.36) than in GAZEL (OR = 1.33, 95% CI 1.18-1.49); this was also true for unhealthy diet (OR = 7.42, 95% CI 5.19-10.60 in Whitehall II and OR = 1.31, 95% CI 1.15-1.49 in GAZEL, p<0.001). Socioeconomic differences in mortality were similar in the two cohorts, a hazard ratio of 1.62 (95% CI 1.28-2.05) in Whitehall II and 1.94 in GAZEL (95% CI 1.58-2.39) for lowest versus highest occupational position. Health behaviours attenuated the association of SES with mortality by 75% (95% CI 44%-149%) in Whitehall II but only by 19% (95% CI 13%-29%) in GAZEL. Analysis using education and income yielded similar results. CONCLUSIONS: Health behaviours were strong predictors of mortality in both cohorts but their association with SES was remarkably different. Thus, health behaviours are likely to be major contributors of socioeconomic differences in health only in contexts with a marked social characterisation of health behaviours. Please see later in the article for the Editors' Summary.

Transapical aortic valve implantation without angiography: proof of concept.

Background: Cardiac computed tomographic scans, coronary angiograms, and aortographies are routinely performed in transcatheter heart valve therapies. Consequently, all patients are exposed to multiple contrast injections with a following risk of nephrotoxicity and postoperative renal failure. The transapical aortic valve implantation without angiography can prevent contrast-related complications. Methods: Between November 2008 and November 2009, 30 consecutive high-risk patients (16 female, 53.3%) underwent transapical aortic valve implantation without angiography. The landmarks identification, the stent-valve positioning, and the postoperative control were routinely performed under transesophageal echocardiogram and fluoroscopic visualization without contrast injections. Results: Mean age was 80.1 +/- 8.7 years. Mean valve gradient, aortic orifice area, and ejection fraction were 60.3 +/- 20.9 mm Hg, 0.7 +/- 0.16 cm(2), and 0.526 +/- 0.128, respectively. Risk factors were pulmonary hypertension (60%), peripheral vascular disease (70%), chronic pulmonary disease (50%), previous cardiac surgery (13.3%), and chronic renal insufficiency (40%) (mean blood creatinine and urea levels: 96.8 +/- 54 mu g/dL and 8.45 +/- 5.15 mmol/L). Average European System for Cardiac Operative Risk Evaluation was 32.2 +/- 13.3%. Valve deployment in the ideal landing zone was 96.7% successful and valve embolization occurred once. Thirty-day mortality was 10% (3 patients). Causes of death were the following: intraoperative ventricular rupture (conversion to sternotomy), right ventricular failure, and bilateral pneumonia. Stroke occurred in one patient at postoperative day 9. Renal failure (postoperative mean blood creatinine and urea levels: 91.1 +/- 66.8 mu g/dL and 7.27 +/- 3.45 mmol/L), myocardial infarction, and atrioventricular block were not detected. Conclusions: Transapical aortic valve implantation without angiography requires a short learning curve and can be performed routinely by experienced teams. Our report confirms that this procedure is feasible and safe, and provides good results with low incidence of postoperative renal disorders. (Ann Thorac Surg 2010; 89: 1925-33) (C) 2010 by The Society of Thoracic Surgeons

Simulation methods with extended stability for stiff biochemical kinetics

Background: With increasing computer power, simulating the dynamics of complex systems in chemistry and biology is becoming increasingly routine. The modelling of individual reactions in (bio)chemical systems involves a large number of random events that can be simulated by the stochastic simulation algorithm (SSA). The key quantity is the step size, or waiting time, τ, whose value inversely depends on the size of the propensities of the different channel reactions and which needs to be re-evaluated after every firing event. Such a discrete event simulation may be extremely expensive, in particular for stiff systems where τ can be very short due to the fast kinetics of some of the channel reactions. Several alternative methods have been put forward to increase the integration step size. The so-called τ-leap approach takes a larger step size by allowing all the reactions to fire, from a Poisson or Binomial distribution, within that step. Although the expected value for the different species in the reactive system is maintained with respect to more precise methods, the variance at steady state can suffer from large errors as τ grows. Results: In this paper we extend Poisson τ-leap methods to a general class of Runge-Kutta (RK) τ-leap methods. We show that with the proper selection of the coefficients, the variance of the extended τ-leap can be well-behaved, leading to significantly larger step sizes.Conclusions: The benefit of adapting the extended method to the use of RK frameworks is clear in terms of speed of calculation, as the number of evaluations of the Poisson distribution is still one set per time step, as in the original τ-leap method. The approach paves the way to explore new multiscale methods to simulate (bio)chemical systems.

Evaluation of Different Methods to Calculate Heavy-Truck VMT, Final Report, December 2004

Reliable estimates of heavy-truck volumes are important in a number of transportation applications. Estimates of truck volumes are necessary for pavement design and pavement management. Truck volumes are important in traffic safety. The number of trucks on the road also influences roadway capacity and traffic operations. Additionally, heavy vehicles pollute at higher rates than passenger vehicles. Consequently, reliable estimates of heavy-truck vehicle miles traveled (VMT) are important in creating accurate inventories of on-road emissions. This research evaluated three different methods to calculate heavy-truck annual average daily traffic (AADT) which can subsequently be used to estimate vehicle miles traveled (VMT). Traffic data from continuous count stations provided by the Iowa DOT were used to estimate AADT for two different truck groups (single-unit and multi-unit) using the three methods. The first method developed monthly and daily expansion factors for each truck group. The second and third methods created general expansion factors for all vehicles. Accuracy of the three methods was compared using n-fold cross-validation. In n-fold cross-validation, data are split into n partitions, and data from the nth partition are used to validate the remaining data. A comparison of the accuracy of the three methods was made using the estimates of prediction error obtained from cross-validation. The prediction error was determined by averaging the squared error between the estimated AADT and the actual AADT. Overall, the prediction error was the lowest for the method that developed expansion factors separately for the different truck groups for both single- and multi-unit trucks. This indicates that use of expansion factors specific to heavy trucks results in better estimates of AADT, and, subsequently, VMT, than using aggregate expansion factors and applying a percentage of trucks. Monthly, daily, and weekly traffic patterns were also evaluated. Significant variation exists in the temporal and seasonal patterns of heavy trucks as compared to passenger vehicles. This suggests that the use of aggregate expansion factors fails to adequately describe truck travel patterns.

Direct and indirect root defences of milkweed (Asclepias syriaca): trophic cascades, trade-offs and novel methods for studying subterranean herbivory

P>1. Entomopathogenic nematodes can function as indirect defence for plants that are attacked by root herbivores. By releasing volatile organic compounds (VOCs), plants signal the presence of host insects and thereby attract nematodes.2. Nonetheless, how roots deploy indirect defences, how indirect defences relate to direct defences, and the ecological consequences of root defence allocation for herbivores and plant biomass are essentially unknown.3. We investigate a natural below-ground tritrophic system, involving common milkweed, a specialist root-boring beetle and entomopathogenic nematodes, and asked whether there is a negative genetic correlation between direct defences (root cardenolides) and indirect defences (emission of volatiles in the roots and nematode attraction), and between constitutive and inducible defences.4. Volatiles of roots were analysed using two distinct sampling methods. First, we collected emissions from living Asclepias syriaca roots by dynamic headspace sampling. This method showed that attacked A. syriaca plants emit five times higher levels of volatiles than control plants. Secondly, we used a solid phase micro-extraction (SPME) method to sample the full pool of volatiles in roots for genetic correlations of volatile biosynthesis.5. Field experiments showed that entomopathogenic nematodes prevent the loss of biomass to root herbivory. Additionally, suppression of root herbivores was mediated directly by cardenolides and indirectly by the attraction of nematodes. Genetic families of plants with high cardenolides benefited less from nematodes compared to low-cardenolide families, suggesting that direct and indirect defences may be redundant. Although constitutive and induced root defences traded off within each strategy (for both direct and indirect defence, cardenolides and VOCs, respectively), we found no trade-off between the two strategies.6. Synthesis. Constitutive expression and inducibility of defences may trade off because of resource limitation or because they are redundant. Direct and indirect defences do not trade off, likely because they may not share a limiting resource and because independently they may promote defence across the patchiness of herbivore attack and nematode presence in the field. Indeed, some redundancy in strategies may be necessary to increase effective defence, but for each strategy, an economy of deployment reduces overall costs.

Practical considerations for conducting ecotoxicity test methods with manufactured nanomaterials: what have we learnt so far?

This review paper reports the consensus of a technical workshop hosted by the European network, NanoImpactNet (NIN). The workshop aimed to review the collective experience of working at the bench with manufactured nanomaterials (MNMs), and to recommend modifications to existing experimental methods and OECD protocols. Current procedures for cleaning glassware are appropriate for most MNMs, although interference with electrodes may occur. Maintaining exposure is more difficult with MNMs compared to conventional chemicals. A metal salt control is recommended for experiments with metallic MNMs that may release free metal ions. Dispersing agents should be avoided, but if they must be used, then natural or synthetic dispersing agents are possible, and dispersion controls essential. Time constraints and technology gaps indicate that full characterisation of test media during ecotoxicity tests is currently not practical. Details of electron microscopy, dark-field microscopy, a range of spectroscopic methods (EDX, XRD, XANES, EXAFS), light scattering techniques (DLS, SLS) and chromatography are discussed. The development of user-friendly software to predict particle behaviour in test media according to DLVO theory is in progress, and simple optical methods are available to estimate the settling behaviour of suspensions during experiments. However, for soil matrices such simple approaches may not be applicable. Alternatively, a Critical Body Residue approach may be taken in which body concentrations in organisms are related to effects, and toxicity thresholds derived. For microbial assays, the cell wall is a formidable barrier to MNMs and end points that rely on the test substance penetrating the cell may be insensitive. Instead assays based on the cell envelope should be developed for MNMs. In algal growth tests, the abiotic factors that promote particle aggregation in the media (e.g. ionic strength) are also important in providing nutrients, and manipulation of the media to control the dispersion may also inhibit growth. Controls to quantify shading effects, and precise details of lighting regimes, shaking or mixing should be reported in algal tests. Photosynthesis may be more sensitive than traditional growth end points for algae and plants. Tests with invertebrates should consider non-chemical toxicity from particle adherence to the organisms. The use of semi-static exposure methods with fish can reduce the logistical issues of waste water disposal and facilitate aspects of animal husbandry relevant to MMNs. There are concerns that the existing bioaccumulation tests are conceptually flawed for MNMs and that new test(s) are required. In vitro testing strategies, as exemplified by genotoxicity assays, can be modified for MNMs, but the risk of false negatives in some assays is highlighted. In conclusion, most protocols will require some modifications and recommendations are made to aid the researcher at the bench. [Authors]