Community Structure Characterization

This entry discusses the problem of describing some communities identified in a complex network of interest, in a way allowing to interpret them. We suppose the community structure has already been detected through one of the many methods proposed in the literature. The question is then to know how to extract valuable information from this first result, in order to allow human interpretation. This requires subsequent processing, which we describe in the rest of this entry

Robust Poisson Surface Reconstruction

Abstract. We propose a method to reconstruct surfaces from oriented point clouds with non-uniform sampling and noise by formulating the problem as a convex minimization that reconstructs the indicator func-tion of the surface’s interior. Compared to previous models, our recon-struction is robust to noise and outliers because it substitutes the least-squares fidelity term by a robust Huber penalty; this allows to recover sharp corners and avoids the shrinking bias of least squares. We choose an implicit parametrization to reconstruct surfaces of unknown topology and close large gaps in the point cloud. For an efficient representation, we approximate the implicit function by a hierarchy of locally supported basis elements adapted to the geometry of the surface. Unlike ad-hoc bases over an octree, our hierarchical B-splines from isogeometric analysis locally adapt the mesh and degree of the splines during reconstruction. The hi-erarchical structure of the basis speeds-up the minimization and efficiently represents clustered data. We also advocate for convex optimization, in-stead isogeometric finite-element techniques, to efficiently solve the min-imization and allow for non-differentiable functionals. Experiments show state-of-the-art performance within a more flexible framework.

No iron fertilization in the equatorial Pacific Ocean during the last ice age

The equatorial Pacific Ocean is one of the major high-nutrient, low-chlorophyll regions in the global ocean. In such regions, the consumption of the available macro-nutrients such as nitrate and phosphate is thought to be limited in part by the low abundance of the critical micro-nutrient iron1. Greater atmospheric dust deposition2 could have fertilized the equatorial Pacific with iron during the last ice age—the Last Glacial Period (LGP) but the effect of increased ice-age dust fluxes on primary productivity in the equatorial Pacific remains uncertain. Here we present meridional transects of dust (derived from the 232Th proxy), phytoplankton productivity (using opal, 231Pa/230Th and excess Ba), and the degree of nitrate consumption (using foraminifera-bound δ15N) from six cores in the central equatorial Pacific for the Holocene (0–10,000 years ago) and the LGP (17,000–27,000 years ago). We find that, although dust deposition in the central equatorial Pacific was two to three times greater in the LGP than in the Holocene, productivity was the same or lower, and the degree of nitrate consumption was the same. These biogeochemical findings suggest that the relatively greater ice-age dust fluxes were not large enough to provide substantial iron fertilization to the central equatorial Pacific. This may have been because the absolute rate of dust deposition in the LGP (although greater than the Holocene rate) was very low. The lower productivity coupled with unchanged nitrate consumption suggests that the subsurface major nutrient concentrations were lower in the central equatorial Pacific during the LGP. As these nutrients are today dominantly sourced from the Subantarctic Zone of the Southern Ocean, we propose that the central equatorial Pacific data are consistent with more nutrient consumption in the Subantarctic Zone, possibly owing to iron fertilization as a result of higher absolute dust fluxes in this region7,8. Thus, ice-age iron fertilization in the Subantarctic Zone would have ultimately worked to lower, not raise, equatorial Pacific productivity

Performance of juvenile turbot (Scophthalmus maximus) fed varying dietary L-carnitine levels at different stocking densities

Commercial farming of turbot (Scophthalmus maximus) at high stocking densities may lead to growth depression and increasing production costs. Moreover, the high levels of accumulated waste in an intensive system may cause rapid deterioration of water quality, which may undermine the production. L-carnitine is known as a growth-enhancer which shows promise as mitigator of crowding effects. The effects of stocking densities (4, 8, 11 and 14 kg m²) on growth performance, feed utilization and body composition were evaluated during 75 days on turbot (75.6 ± 2.8 g) fed two dietary L-carnitine levels (40 or 240 mg kg¹). At the end of the feeding trial, total ammonia excretion (TAN) was measured postprandially for 24h. Specific growth rate and weight gain decreased with increasing stocking density. Fish held at 4 kg m² had higher final body weight (94-96 g) than fish held at higher densities (80-87 g). Protein efficiency ratio was higher in fish held at 4 kg m² (1.33-1.36), in comparison to fish stocked at 8 kg m² (0.98) or 14 kg m² (0.45). Voluntary feed intake decreased from 0.70 to 0.56% BW with increasing stocking density. Dietary L-carnitine supplementation did not affect growth performance and body composition, except for body L-carnitine content which increased from 75 to 128 mg kg¹ BW with supplementation. Fish fed 240 mg L-carnitine supplements had lower TAN that the ones fed 40 mg L-carnitine (p A aquicultura de pregado (Scophthalmus maximus) utilizando elevadas densidades pode reduzir o crescimento e aumentar os custos de produção. Elevados níveis de metabolitos gerados nestes sistemas intensivos provocam rápida deterioração da qualidade da água, podendo também comprometer a performance da produção. A L-carnitina atua como potenciadora do crescimento parecendo ser promissora por atenuar alguns desses efeitos. Os efeitos de densidades (4, 8, 11 e 14 kg m²) no desempenho do crescimento, composição corporal foram avaliados em pregados (75,6 ± 2,8 g) alimentados durante 75 dias a dois níveis dietéticos de L-carnitina (40 ou 240 mg kg¹). Após esse período, determinou-se a excreção de amônia pós-prandial durante 24 horas. Os peixes cultivados na menor densidade, 4 kg m², apresentaram melhores taxas de crescimento e ganho de peso (94-96 g) em comparação aos mantidos em altas densidades (80-87 g). A taxa de eficiência proteica foi mais elevada a 4 kg m² (1,33-1,36), do que a densidades de 8 kg m² (0,98) ou 14 kg m² (0,45). A ingestão voluntária de alimento decresceu de 0,70 para 0,56% do peso corporal com o incremento da densidade. A suplementação de carnitina não afetou o crescimento e a composição corporal, com exceção do conteúdo de carnitine da carcaça que passou de 75 a 128 mg kg¹. Peixes alimentados com suplementos de 240 mg L-carnitina apresentam excreção de amônia mais baixa comparativamente aos alimentados com 40 mg L-carnitina (p < 0,05)

Robust and Efficient Surface Reconstruction From Range Data

We describe a robust but simple algorithm to reconstruct a surface from a set of merged range scans. Our key contribution is the formulation of the surface reconstruction problem as an energy minimisation problem that explicitly models the scanning process. The adaptivity of the Delaunay triangulation is exploited by restricting the energy to inside/outside labelings of Delaunay tetrahedra. Our energy measures both the output surface quality and how well the surface agrees with soft visibility constraints. Such energy is shown to perfectly fit into the minimum s - t cuts optimisation framework, allowing fast computation of a globally optimal tetrahedra labeling, while avoiding the shrinking bias that usually plagues graph cuts methods.The behaviour of our method confronted to noise, undersampling and outliers is evaluated on several data sets and compared with other methods through different experiments: its strong robustness would make our method practical not only for reconstruction from range data but also from typically more difficult dense point clouds, resulting for instance from stereo image matching. Our effective modeling of the surface acquisition inverse problem, along with the unique combination of Delaunay triangulation and minimum s - t cuts, makes the computational requirements of the algorithm scale well with respect to the size of the input point cloud.Computer Graphics Forum28

Microaerobic conditions in anaerobic sludge promote changes in bacterial composition favouring biodegradation of polymeric siloxanes

© The Royal Society of Chemistry.Volatile organic silicon compounds (VOSiC) are harmful pollutants to the biota and ecological dynamics as well as biogas-based energy conversion systems. However, there is a lack of understanding regarding the source of VOSiCs in biogas, especially arising from the biochemical conversion of siloxane polymers such as polydimethylsiloxanes (PDMS). The biodegradation of PDMS was evaluated under anaerobic/microaerobic conditions (PO2 = 0, 1, 3, 5%), using wastewater treatment plant (WWTP) sludge as an inoculum and PDMS as a co-substrate (0, 50, 100, 500 ppm). On average, strictly anaerobic treatments produced significantly less methane than the 3 and 5% microaerated ones, which show the highest PMDS biodegradation at 50 ppm. Thauera sp. and Rhodococcus sp. related phylotypes were identified as the most abundant bacterial groups in microaerated treatments, and siloxane-related molecules were identified as remnants of PDMS catabolism. Our study demonstrates that microaeration promotes changes to the native bacterial community which favour the biological degradation of PDMS. This confirms that the presence of VOSiC (e.g., D4-D6) in biogas is not only due to its direct input in wastewaters, but also to the PDMS microbial catabolism. Microaerobic conditions enhance both PDMS and (subsequent) VOSiC degradation in the liquid phase, increasing the concentrations of D4 and D5 in biogas, and the production of less toxic siloxane-based derivatives in the liquid phase. This study suggests that microaeration of the anaerobic sludge can significantly decrease the concentration of PDMSs in the WWTP effluent. However, for WWTPs to become effective barriers for the emission of these ecotoxic contaminants to the environment, such a strategy needs to be coupled with an efficient biodegradation of VOSiCs from the biogas. This journal isScience Academy-BAGEPBoğaziçi University; Folio: 15B06SUP2ANID FONDECYT; Folio: 1211858CONICYT-MEC; Folio: 8013006

DensePose 3D: lifting canonical surface maps of articulated objects to the third dimension

We tackle the problem of monocular 3D reconstruction of articulated objects like humans and animals. We contribute DensePose 3D, a method that can learn such reconstructions in a weakly supervised fashion from 2D image annotations only. This is in stark contrast with previous deformable reconstruction methods that use parametric models such as SMPL pre-trained on a large dataset of 3D object scans. Because it does not require 3D scans, DensePose 3D can be used for learning a wide range of articulated categories such as different animal species. The method learns, in an end-to-end fashion, a soft partition of a given category-specific 3D template mesh into rigid parts together with a monocular reconstruction network that predicts the part motions such that they reproject correctly onto 2D DensePose-like surface annotations of the object. The decomposition of the object into parts is regularized by expressing part assignments as a combination of the smooth eigenfunctions of the Laplace-Beltrami operator. We show significant improvements compared to state-of-the-art nonrigid structure-from-motion baselines on both synthetic and real data on categories of humans and animals