Thermal impact from a thermoelectric power plant on a tropical coastal lagoon

Tropical coastal areas are sensitive ecosystems to climate change, mainly due to sea level rise and increasing water temperatures. Furthermore, they may be subject to numerous stresses, including heat releases from energy production. The Urias coastal lagoon (SE Gulf of California), a subtropical tidal estuary, receives cooling water releases from a thermoelectric power plant, urban and industrial wastes, and shrimp farm discharges. In order to evaluate the plant thermal impact, we measured synchronous temperature time series close to and far from the plant. Furthermore, in order to discriminate the thermal pollution impact from natural variability, we used a high-resolution hydrodynamic model forced by, amongst others, cooling water release as a continuous flow (7.78 m3 s?1) at 6 °C overheating temperature. Model results and field data indicated that the main thermal impact was temporally restricted to the warmest months, spatially restricted to the surface layers (above 0.6 m) and distributed along the shoreline within ?100 m of the release point. The methodology and results of this study can be extrapolated to tropical coastal lagoons that receive heat discharges.<br/

Comparative study of density functional theories of the exchange-correlation hole and energy in silicon

We present a detailed study of the exchange-correlation hole and exchange-correlation energy per particle in the Si crystal as calculated by the Variational Monte Carlo method and predicted by various density functional models. Nonlocal density averaging methods prove to be successful in correcting severe errors in the local density approximation (LDA) at low densities where the density changes dramatically over the correlation length of the LDA hole, but fail to provide systematic improvements at higher densities where the effects of density inhomogeneity are more subtle. Exchange and correlation considered separately show a sensitivity to the nonlocal semiconductor crystal environment, particularly within the Si bond, which is not predicted by the nonlocal approaches based on density averaging. The exchange hole is well described by a bonding orbital picture, while the correlation hole has a significant component due to the polarization of the nearby bonds, which partially screens out the anisotropy in the exchange hole.Comment: 16 pages, 5 figures, RevTeX, added conten

Efficient tool segmentation for endoscopic videos in the wild

In recent years, deep learning methods have become the most effective approach for tool segmentation in endoscopic images, achieving the state of the art on the available public benchmarks. However, these methods present some challenges that hinder their direct deployment in real world scenarios. This work explores how to solve two of the most common challenges: real-time and memory restrictions and false positives in frames with no tools. To cope with the first case, we show how to adapt an efficient general purpose semantic segmentation model. Then, we study how to cope with the common issue of only training on images with at least one tool. Then, when images of endoscopic procedures without tools are processed, there are a lot of false positives. To solve this, we propose to add an extra classification head that performs binary frame classification, to identify frames with no tools present. Finally, we present a thorough comparison of this approach with current state of the art on different benchmarks, including real medical practice recordings, demonstrating similar accuracy with much lower computational requirements

Domain and View-Point Agnostic Hand Action Recognition

Hand action recognition is a special case of action recognition with applications in human-robot interaction, virtual reality or life-logging systems. Building action classifiers able to work for such heterogeneous action domains is very challenging. There are very subtle changes across different actions from a given application but also large variations across domains (e.g. virtual reality vs life-logging). This work introduces a novel skeleton-based hand motion representation model that tackles this problem. The framework we propose is agnostic to the application domain or camera recording view-point. When working on a single domain (intra-domain action classification) our approach performs better or similar to current state-of-the-art methods on well-known hand action recognition benchmarks. And, more importantly, when performing hand action recognition for action domains and camera perspectives which our approach has not been trained for (cross-domain action classification), our proposed framework achieves comparable performance to intra-domain state-of-the-art methods. These experiments show the robustness and generalization capabilities of our framework

3D-MiniNet: Learning a 2D Representation from Point Clouds for Fast and Efficient 3D LIDAR Semantic Segmentation

LIDAR semantic segmentation is an essential task that provides 3D semantic information about the environment to robots. Fast and efficient semantic segmentation methods are needed to match the strong computational and temporal restrictions of many real-world robotic applications. This work presents 3D-MiniNet, a novel approach for LIDAR semantic segmentation that combines 3D and 2D learning layers. It first learns a 2D representation from the raw points through a novel projection which extracts local and global information from the 3D data. This representation is fed to an efficient 2D Fully Convolutional Neural Network (FCNN) that produces a 2D semantic segmentation. These 2D semantic labels are re-projected back to the 3D space and enhanced through a post-processing module. The main novelty in our strategy relies on the projection learning module. Our detailed ablation study shows how each component contributes to the final performance of 3D-MiniNet. We validate our approach on well known public benchmarks (SemanticKITTI and KITTI), where 3D-MiniNet gets state-of-the-art results while being faster and more parameter-efficient than previous methods

Search for direct production of charginos and neutralinos in events with three leptons and missing transverse momentum in √s = 7 TeV pp collisions with the ATLAS detector

A search for the direct production of charginos and neutralinos in final states with three electrons or muons and missing transverse momentum is presented. The analysis is based on 4.7 fb−1 of proton–proton collision data delivered by the Large Hadron Collider and recorded with the ATLAS detector. Observations are consistent with Standard Model expectations in three signal regions that are either depleted or enriched in Z-boson decays. Upper limits at 95% confidence level are set in R-parity conserving phenomenological minimal supersymmetric models and in simplified models, significantly extending previous results

Measurement of D*+/- meson production in jets from pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

This paper reports a measurement of D*+/- meson production in jets from proton-proton collisions at a center-of-mass energy of sqrt(s) = 7 TeV at the CERN Large Hadron Collider. The measurement is based on a data sample recorded with the ATLAS detector with an integrated luminosity of 0.30 pb^-1 for jets with transverse momentum between 25 and 70 GeV in the pseudorapidity range |eta| < 2.5. D*+/- mesons found in jets are fully reconstructed in the decay chain: D*+ -> D0pi+, D0 -> K-pi+, and its charge conjugate. The production rate is found to be N(D*+/-)/N(jet) = 0.025 +/- 0.001(stat.) +/- 0.004(syst.) for D*+/- mesons that carry a fraction z of the jet momentum in the range 0.3 < z < 1. Monte Carlo predictions fail to describe the data at small values of z, and this is most marked at low jet transverse momentum.Comment: 10 pages plus author list (22 pages total), 5 figures, 1 table, matches published version in Physical Review

3D zero-thickness coupled interface finite element:Formulation and application

In many fields of geotechnical engineering, the modelling of interfaces requires special numerical tools. This paper presents the formulation of a 3D fully coupled hydro-mechanical finite element of interface. The element belongs to the zero-thickness family and the contact constraint is enforced by the penalty method. Fluid flow is discretised through a three-node scheme, discretising the inner flow by additional nodes. The element is able to reproduce the contact/loss of contact between two solids as well as shearing/sliding of the interface. Fluid flow through and across the interface can be modelled. Opening of a gap within the interface influences the longitudinal transmissivity as well as the storage of water inside the interface. Moreover the computation of an effective pressure within the interface, according to the Terzaghi’s principle creates an additional hydro-mechanical coupling. The uplifting simulation of a suction caisson embedded in a soil layer illustrates the main features of the element. Friction is progressively mobilised along the shaft of the caisson and sliding finally takes place. A gap is created below the top of the caisson and filled with water. It illustrates the storage capacity within the interface and the transversal flow. Longitudinal fluid flow is highlighted between the shaft of the caisson and the soil. The fluid flow depends on the opening of the gap and is related to the cubic law

Repeatable semantic reef-mapping through photogrammetry and label-augmentation

In an endeavor to study natural systems at multiple spatial and taxonomic resolutions, there is an urgent need for automated, high-throughput frameworks that can handle plethora of information. The coalescence of remote-sensing, computer-vision, and deep-learning elicits a new era in ecological research. However, in complex systems, such as marine-benthic habitats, key ecological processes still remain enigmatic due to the lack of cross-scale automated approaches (mms to kms) for community structure analysis. We address this gap by working towards scalable and comprehensive photogrammetric surveys, tackling the profound challenges of full semantic segmentation and 3D grid definition. Full semantic segmentation (where every pixel is classified) is extremely labour-intensive and difficult to achieve using manual labeling. We propose using label-augmentation, i.e., propagation of sparse manual labels, to accelerate the task of full segmentation of photomosaics. Photomosaics are synthetic images generated from a projected point-of-view of a 3D model. In the lack of navigation sensors (e.g., a diver-held camera), it is difficult to repeatably determine the slope-angle of a 3D map. We show this is especially important in complex topographical settings, prevalent in coral-reefs. Specifically, we evaluate our approach on benthic habitats, in three different environments in the challenging underwater domain. Our approach for label-augmentation shows human-level accuracy in full segmentation of photomosaics using labeling as sparse as 0.1%, evaluated on several ecological measures. Moreover, we found that grid definition using a leveler improves the consistency in community-metrics obtained due to occlusions and topology (angle and distance between objects), and that we were able to standardise the 3D transformation with two percent error in size measurements. By significantly easing the annotation process for full segmentation and standardizing the 3D grid definition we present a semantic mapping methodology enabling change-detection, which is practical, swift, and cost-effective. Our workflow enables repeatable surveys without permanent markers and specialized mapping gear, useful for research and monitoring, and our code is available online. Additionally, we release the Benthos data-set, fully manually labeled photomosaics from three oceanic environments with over 4500 segmented objects useful for research in computer-vision and marine ecology

Hydromechanical modelling of shaft sealing for CO2 storage

The geological sequestration of CO2 in abandoned coal mines is a promising option to mitigate climate changes while providing sustainable use of the underground cavities. In order to certify the efficiency of the storage, it is essential to understand the behaviour of the shaft sealing system. The paper presents a numerical analysis of CO2 transfer mechanisms through a mine shaft and its sealing system. Different mechanisms for CO2 leakage are considered, namely multiphase flow through the different materials and flow along the interfaces between the lining and the host rock. The study focuses on the abandoned coal mine of Anderlues, Belgium, which was used for seasonal storage of natural gas. A two-dimensional hydromechanical modelling of the storage site is performed and CO2 injection into the coal mine is simulated. Model predictions for a period of 500 years are presented and discussed with attention. The role and influence of the interface between the host rock and the concrete lining are examined. In addition the impact of some uncertain model parameters on the overall performance of the sealing system is analysed through a sensitivity analysis