Factors Affecting Dissolved Silica Concentrations, and DSi and DIN Stoichiometry in a Human Impacted Watershed (Po River, Italy)

Data on dissolved (DSi) and particulate (PSi) silica concentrations, along with DSi and DIN (dissolved inorganic nitrogen) stoichiometry in surface waters were reviewed for the Po river watershed. DSi in the cascade river and lake ecosystems followed clear upstream-downstream gradients. The DSi (77–178 kt Si y^???1) and PSi (879–1,486 kt Si y^???1) loadings from the Po river to the Adriatic Sea display strong inter-annual variability, related with the river discharge. In the lowland river reaches, the DSi to DIN ratio highlighted frequent potential Si limitation, especially in summer during diatom blooms. Since the Po river watershed is heavily inhabited and exploited with agriculture (~43 % of the total surface) and livestock husbandry (~3.4 × 10⁶ cattle heads), agriculture likely interferes with the natural silicon cycle. We present a preliminary assessment of the biogenic silica (BSi) which was fixed in and harvested with the main crop biomass. In the period 2000–2010, the total BSi in crops was 270–386 kt Si y^???1. Three main cereals (maize, wheat, rice) accounted for 70 % BSi, of which 89 % was accumulated in straw. The quantity of BSi that was annually accumulated in the cereal biomass increased 2–4 folds from 1950 to 2010. We estimated that a great part of the BSi accumulated in straw and fodder was processed by the cattle stock and returned to soil as manure. A large part of the cropland is exposed to erosion and PSi can be exported to canals and rivers at particularly high rates during flash flood events. Recent transformations of either agricultural practices or crop typology probably perturb the Si cycling.     

Efficient global optimization for high-dimensional constrained problems by using the Kriging models combined with the partial least squares method

In many engineering optimization problems, the number of function evaluations is often very limited because of the computational cost to run one high-fidelity numerical simulation. Using a classic optimization algorithm, such as a derivative-based algorithm or an evolutionary algorithm, directly on a computational model is not suitable in this case. A common approach to addressing this challenge is to use black-box surrogate modelling techniques. The most popular surrogate-based optimization algorithm is the efficient global optimization (EGO) algorithm, which is an iterative sampling algorithm that adds one (or many) point(s) per iteration. This algorithm is often based on an infill sampling criterion, called expected improvement, which represents a trade-off between promising and uncertain areas. Many studies have shown the efficiency of EGO, particularly when the number of input variables is relatively low. However, its performance on high-dimensional problems is still poor since the Kriging models used are time-consuming to build. To deal with this issue, this article introduces a surrogate-based optimization method that is suited to high-dimensional problems. The method first uses the ‘locating the regional extreme’ criterion, which incorporates minimizing the surrogate model while also maximizing the expected improvement criterion. Then, it replaces the Kriging models by the KPLS(+K) models (Kriging combined with the partial least squares method), which are more suitable for high-dimensional problems. Finally, the proposed approach is validated by a comparison with alternative methods existing in the literature on some analytical functions and on 12-dimensional and 50-dimensional instances of the benchmark automotive problem ‘MOPTA08’.     

Analysis of the receiver response in lidar measurements

We report on the calculation of the effective telescope area in lidar applications by a ray-tracing approach. This method allows one to consider the true experimental working conditions and hence to obtain accurate values of the effective telescope area as a function of the height. This in turn allows the retrieval of the signal from the ranges where the overlap function is not constant (e.g., lower ranges), thus increasing the useful range interval. Moreover, we show that the spherical mirrors are more appropriate than the parabolic ones for most of the lidar measurements, although a particular alignment procedure, such as the one we describe, must be used.     

On Computing the Prediction Sum of Squares Statistic in Linear Least Squares Problems with Multiple Parameter or Measurement Sets

The prediction sum of squares is a useful statistic for comparing different models. It is based on the principle of leave-one-out or ordinary cross-validation, whereby every measurement is considered in turn as a test set, for the model parameters trained on all but the held out measurement. As for linear least squares problems, there is a simple well-known non-iterative formula to compute the prediction sum of squares without having to refit the model as many times as the number of measurements. We extend this formula to cases where the problem has multiple parameter or measurement sets. We report experimental results on the fitting of a warp between two images, for which the number of deformation centres is automatically selected, based on one of the proposed non-iterative formulae.     

Implicit Non-Rigid Structure-from-Motion with Priors

This paper describes an approach to implicit Non-Rigid Structure-from-Motion based on the low-rank shape model. The main contributions are the use of an implicit model, of matching tensors, a rank estimation procedure, and the theory and implementation of two smoothness priors. Contrarily to most previous methods, the proposed method is fully automatic: it handles a substantial amount of missing data as well as outlier contaminated data, and it automatically estimates the degree of deformation. A major problem in many previous methods is that they generalize badly. Although the estimated model fits the visible training data well, it often predicts the missing data badly. To improve generalization a temporal smoothness prior and a surface shape prior are developed. The temporal smoothness prior constrains the camera trajectory and the configuration weights to behave smoothly. The surface shape prior constrains consistently close image point tracks to have similar implicit structure. We propose an algorithm for achieving a Maximum A Posteriori (map) solution and show experimentally that the map-solution generalizes far better than the prior-free Maximum Likelihood (ml) solution.     

Feature-Based Deformable Surface Detection with Self-Occlusion Reasoning

This paper presents a method for detecting a textured deformed surface in an image. It uses (wide-baseline) point matches between a template and the input image. The main contribution of the paper is twofold. First, we propose a robust method based on local surface smoothness capable of discarding outliers from the set of point matches. Our method handles large proportions of outliers (beyond 70% with less than 15% of false positives) even when the surface self-occludes. Second, we propose a method to estimate a self-occlusion resistant warp from point matches. Our method allows us to realistically retexture the input image. A pixel-based (direct) registration approach is also proposed. Bootstrapped by our robust point-based method, it finely tunes the warp parameters using the value (intensity or color) of all the visible surface pixels. The proposed framework was tested with simulated and real data. Convincing results are shown for the detection and retexturing of deformed surfaces in challenging images.     

Interferometric radar vs. accelerometer for dynamic monitoring of large structures: An experimental comparison

Interferometric radar has been recently proposed as a measurement instrument for dynamic testing/monitoring of large structures, such as bridges, towers, buildings, and dams, which is currently performed by networks of accelerometers. In this paper, the authors report a direct comparison between the two measurement techniques (radar interferometer vs. accelerometers) both employed during a field test on a bridge. As different quantities, displacement and acceleration are measured by the two techniques, a preliminary discussion about signals and noise has been necessary. Finally, the experimental results are critically discussed.