Fast Geodesic Active Fields for Image Registration Based on Splitting and Augmented Lagrangian Approaches.

In this paper, we present an efficient numerical scheme for the recently introduced geodesic active fields (GAF) framework for geometric image registration. This framework considers the registration task as a weighted minimal surface problem. Hence, the data-term and the regularization-term are combined through multiplication in a single, parametrization invariant and geometric cost functional. The multiplicative coupling provides an intrinsic, spatially varying and data-dependent tuning of the regularization strength, and the parametrization invariance allows working with images of nonflat geometry, generally defined on any smoothly parametrizable manifold. The resulting energy-minimizing flow, however, has poor numerical properties. Here, we provide an efficient numerical scheme that uses a splitting approach; data and regularity terms are optimized over two distinct deformation fields that are constrained to be equal via an augmented Lagrangian approach. Our approach is more flexible than standard Gaussian regularization, since one can interpolate freely between isotropic Gaussian and anisotropic TV-like smoothing. In this paper, we compare the geodesic active fields method with the popular Demons method and three more recent state-of-the-art algorithms: NL-optical flow, MRF image registration, and landmark-enhanced large displacement optical flow. Thus, we can show the advantages of the proposed FastGAF method. It compares favorably against Demons, both in terms of registration speed and quality. Over the range of example applications, it also consistently produces results not far from more dedicated state-of-the-art methods, illustrating the flexibility of the proposed framework.

The inhibition of fat cell proliferation by n-3 fatty acids in dietary obese mice.

ABSTRACT: BACKGROUND: Long-chain n-3 polyunsaturated fatty acids (LC n-3 PUFA) of marine origin exert multiple beneficial effects on health. Our previous study in mice showed that reduction of adiposity by LC n-3 PUFA was associated with both, a shift in adipose tissue metabolism and a decrease in tissue cellularity. The aim of this study was to further characterize the effects of LC n-3 PUFA on fat cell proliferation and differentiation in obese mice. METHODS: A model of inducible and reversible lipoatrophy (aP2-Cre-ERT2 PPARgammaL2/L2 mice) was used, in which the death of mature adipocytes could be achieved by a selective ablation of peroxisome proliferator-activated receptor gamma in response to i.p. injection of tamoxifen. Before the injection, obesity was induced in male mice by 8-week-feeding a corn oil-based high-fat diet (cHF) and, subsequently, mice were randomly assigned (day 0) to one of the following groups: (i) mice injected by corn-oil-vehicle only, i.e."control" mice, and fed cHF; (ii) mice injected by tamoxifen in corn oil, i.e. "mutant" mice, fed cHF; (iii) control mice fed cHF diet with 15% of dietary lipids replaced by LC n-3 PUFA concentrate (cHF+F); and (iv) mutant mice fed cHF+F. Blood and tissue samples were collected at days 14 and 42. RESULTS: Mutant mice achieved a maximum weight loss within 10 days post-injection, followed by a compensatory body weight gain, which was significantly faster in the cHF as compared with the cHF+F mutant mice. Also in control mice, body weight gain was depressed in response to dietary LC n-3 PUFA. At day 42, body weights in all groups stabilized, with no significant differences in adipocyte size between the groups, although body weight and adiposity was lower in the cHF+F as compared with the cHF mice, with a stronger effect in the mutant than in control mice. Gene expression analysis documented depression of adipocyte maturation during the reconstitution of adipose tissue in the cHF+F mutant mice. CONCLUSION: Dietary LC n-3 PUFA could reduce both hypertrophy and hyperplasia of fat cells in vivo. Results are in agreement with the involvement of fat cell turnover in control of adiposity.

Nutritional status in commercial currant fields

Selostus: Herukkaviljelmien ravinnetila

Weeds in spring cereal fields in Finland - a third survey

Selostus: Kolmas kevätviljapeltojen rikkakasvikartoitus

Overfishing of small pelagic fishes increases trophic overlap between immature and mature striped dolphins in the Mediterranean Sea

The interactions among diet, ecology, physiology, and biochemistry affect N and C stable isotope signatures in animal tissues. Here, we examined if ecological segregation among animals in relation to sex and age existed by analyzing the signatures of delta15N and delta13C in the muscle of Western Mediterranean striped dolphins. Moreover, we used a Bayesian mixing model to study diet composition and investigated potential dietary changes over the last two decades in this population. For this, we compared isotope signatures in samples of stranded dolphins obtained during two epizootic events occurring in 1990 and 2007-2008. Mean delta13C values for females and males were not significantly different, but age-related variation indicated delta13C enrichment in both sexes, suggesting that females and males most likely fed in the same general areas, increasing their consumption of benthic prey with age. Enrichment of delta15N was only observed in females, suggesting a preference for larger or higher trophic level prey than males, which could reflect different nutritional requirements. delta13C values showed no temporal variation, although the mean delta15N signature decreased from 1990 to 2007-2008, which could indicate a dietary shift in the striped dolphin over the last two decades. The results of SIAR indicated that in 1990, hake and sardine together contributed to 60% on the diet of immature striped dolphins, and close to 90% for mature striped dolphins. Conversely, the diet of both groups in 2007-2008 was more diverse, as hake and sardine contributed to less than 40% of the entire diet. These results suggest a dietary change that was possibly related to changes in food availability, which is consistent with the depletion of sardine stocks by fishing.

Genetic diversity and relationship in American and African oil palm as revealed by RFLP and AFLP molecular markers

The objective of this work was to evaluate the genetic diversity, its organization and the genetic relationships within oil palm (Elaeis oleifera (Kunth) Cortés, from America, and E. guineensis (Jacq.), from Africa) germplasm using Restriction Fragment Length Polymorphism (RFLP) and Amplified Fragment Length Polymorphism (AFLP). In complement to a previous RFLP study on 241 E. oleifera accessions, 38 E. guineensis accessions were analyzed using the same 37 cDNA probes. These accessions covered a large part of the geographical distribution areas of these species in America and Africa. In addition, AFLP analysis was performed on a sub-set of 40 accessions of E. oleifera and 22 of E. guineensis using three pairs of enzyme/primer combinations. Data were subjected to Factorial Analysis of Correspondence (FAC) and cluster analysis, with parameters of genetic diversity being also studied. Results appeared congruent between RFLP and AFLP. In the E. oleifera, AFLP confirmed the strong structure of genetic diversity revealed by RFLP, according to geographical origin of the studied material, with the identification of the same four distinct genetic groups: Brazil, French Guyana/Surinam, Peru, north of Colombia/Central America. Both markers revealed that genetic divergence between the two species is of the same magnitude as that among provenances of E. oleifera. This finding is in discrepancy with the supposed early tertiary separation of the two species.

Postmortem angiography after vascular perfusion with diesel oil and a lipophilic contrast agent.

OBJECTIVE: The objective of our study was to establish optimal perfusion conditions for high-resolution postmortem angiography that would permit dynamic visualization of the arterial and venous systems. MATERIALS AND METHODS: Cadavers of two dogs and one cat were perfused with diesel oil through a peristaltic pump. The lipophilic contrast agent Lipiodol Ultra Fluide was then injected, and angiography was performed. The efficiency of perfusion was evaluated in the chick chorioallantoic membrane. RESULTS: Vessels could be seen up to the level of the smaller supplying and draining vessels. Hence, both the arterial and the venous sides of the vascular system could be distinguished. The chorioallantoic membrane assay revealed that diesel oil enters microvessels up to 50 microm in diameter and that it does not penetrate the capillary network. CONCLUSION: After establishing a postmortem circulation by diesel oil perfusion, angiography can be performed by injection of Lipiodol Ultra Fluide. The resolution of the images obtained up to 3 days after death is comparable to that achieved in clinical angiography.

Kernel-based Mapping of Meteorological Fields in Complex Orography

Due to the advances in sensor networks and remote sensing technologies, the acquisition and storage rates of meteorological and climatological data increases every day and ask for novel and efficient processing algorithms. A fundamental problem of data analysis and modeling is the spatial prediction of meteorological variables in complex orography, which serves among others to extended climatological analyses, for the assimilation of data into numerical weather prediction models, for preparing inputs to hydrological models and for real time monitoring and short-term forecasting of weather.In this thesis, a new framework for spatial estimation is proposed by taking advantage of a class of algorithms emerging from the statistical learning theory. Nonparametric kernel-based methods for nonlinear data classification, regression and target detection, known as support vector machines (SVM), are adapted for mapping of meteorological variables in complex orography.With the advent of high resolution digital elevation models, the field of spatial prediction met new horizons. In fact, by exploiting image processing tools along with physical heuristics, an incredible number of terrain features which account for the topographic conditions at multiple spatial scales can be extracted. Such features are highly relevant for the mapping of meteorological variables because they control a considerable part of the spatial variability of meteorological fields in the complex Alpine orography. For instance, patterns of orographic rainfall, wind speed and cold air pools are known to be correlated with particular terrain forms, e.g. convex/concave surfaces and upwind sides of mountain slopes.Kernel-based methods are employed to learn the nonlinear statistical dependence which links the multidimensional space of geographical and topographic explanatory variables to the variable of interest, that is the wind speed as measured at the weather stations or the occurrence of orographic rainfall patterns as extracted from sequences of radar images. Compared to low dimensional models integrating only the geographical coordinates, the proposed framework opens a way to regionalize meteorological variables which are multidimensional in nature and rarely show spatial auto-correlation in the original space making the use of classical geostatistics tangled.The challenges which are explored during the thesis are manifolds. First, the complexity of models is optimized to impose appropriate smoothness properties and reduce the impact of noisy measurements. Secondly, a multiple kernel extension of SVM is considered to select the multiscale features which explain most of the spatial variability of wind speed. Then, SVM target detection methods are implemented to describe the orographic conditions which cause persistent and stationary rainfall patterns. Finally, the optimal splitting of the data is studied to estimate realistic performances and confidence intervals characterizing the uncertainty of predictions.The resulting maps of average wind speeds find applications within renewable resources assessment and opens a route to decrease the temporal scale of analysis to meet hydrological requirements. Furthermore, the maps depicting the susceptibility to orographic rainfall enhancement can be used to improve current radar-based quantitative precipitation estimation and forecasting systems and to generate stochastic ensembles of precipitation fields conditioned upon the orography.

Ecological niche overlap in sister species: how do oil-collecting bees Macropis europaea and M. fulvipes (Hymenoptera: Melittidae) avoid competition and hybridization?

Oil-collecting bees are found worldwide and always in association with particular oil-producing flowers. In the Western Palearctic, three oil-collecting bee species within the genus Macropis (Hymenoptera, Melittidae) interact in a tight pollination mutualism with species of the only European oil-producing plant genus Lysimachia L. (Myrsinaceae). Two of these oil-collecting bees (Macropis europaea and Macropis fulvipes) show overlapping geographic distributions, comparable morphologies, and similar ecological characteristics (e.g., habitat type, floral preferences). In view of these similarities, we presume that hybridization should occur between the two species unless potential variation among the species' ecological niches prevents it, simultaneously decreasing competition for resources. Using modern genetic analyses and ecological niche modeling on a large bee sampling throughout Europe, we discuss new perspectives on the ecology and evolutionary history of this mutualism.

Stress intensity factor of wood from crack-tip displacement fields obtained from digital image processing

Abstract