Nonlinearly charged Lifshitz black holes for any exponent z>1z>1

Charged Lifshitz black holes for the Einstein-Proca-Maxwell system with a negative cosmological constant in arbitrary dimension $D$ are known only if the dynamical critical exponent is fixed as $z=2(D-2)$. In the present work, we show that these configurations can be extended to much more general charged black holes which in addition exist for any value of the dynamical exponent $z>1$ by considering a nonlinear electrodynamics instead of the Maxwell theory. More precisely, we introduce a two-parametric nonlinear electrodynamics defined in the more general, but less known, so-called $(\mathcal{H},P)$-formalism and obtain a family of charged black hole solutions depending on two parameters. We also remark that the value of the dynamical exponent $z=D-2$ turns out to be critical in the sense that it yields asymptotically Lifshitz black holes with logarithmic decay supported by a particular logarithmic electrodynamics. All these configurations include extremal Lifshitz black holes. Charged topological Lifshitz black holes are also shown to emerge by slightly generalizing the proposed electrodynamics

Integration of biophysical connectivity in the spatial optimization of coastal ecosystem services

Ecological connectivity in coastal oceanic waters is mediated by dispersion of the early life stages of marine organisms and conditions the structure of biological communities and the provision of ecosystem services. Integrated management strategies aimed at ensuring long-term service provision to society do not currently consider the importance of dispersal and larval connectivity. A spatial optimization model is introduced to maximise the potential provision of ecosystem services in coastal areas by accounting for the role of dispersal and larval connectivity. The approach combines a validated coastal circulation model that reproduces realistic patterns of larval transport along the coast, which ultimately conditions the biological connectivity and productivity of an area, with additional spatial layers describing potential ecosystem services. The spatial optimization exercise was tested along the coast of Central Chile, a highly productive area dominated by the Humboldt Current. Results show it is unnecessary to relocate existing management areas, as increasing no-take areas by 10% could maximise ecosystem service provision, while improving the spatial representativeness of protected areas and minimizing social conflicts. The location of protected areas was underrepresented in some sections of the study domain, principally due to the restriction of the model to rocky subtidal habitats. Future model developments should encompass the diversity of coastal ecosystems and human activities to inform integrative spatial management. Nevertheless, the spatial optimization model is innovative not only for its integrated ecosystem perspective, but also because it demonstrates that it is possible to incorporate time-varying biophysical connectivity within the optimization problem, thereby linking the dynamics of exploited populations produced by the spatial management regime.Comment: 30 pages, 5 figures, 2 tables; 1 graphical abstract. In this version: numbering of figures corrected, updated figure 2, typos corrected and references fixe

Assessing a novel modelling approach with high resolution UAV imagery for monitoring health status in priority riparian forests

ResearchBackground: Black alder (Alnus glutinosa) forests are in severe decline across their area of distribution due to a disease caused by the soil-borne pathogenic Phytophthora alni species complex (class Oomycetes), “alder Phytopththora”. Mapping of the different types of damages caused by the disease is challenging in high density ecosystems in which spectral variability is high due to canopy heterogeneity. Data obtained by unmanned aerial vehicles (UAVs) may be particularly useful for such tasks due to the high resolution, flexibility of acquisition and cost efficiency of this type of data. In this study, A. glutinosa decline was assessed by considering four categories of tree health status in the field: asymptomatic, dead and defoliation above and below a 50% threshold. A combination of multispectral Parrot Sequoia and UAV unmanned aerial vehicles -red green blue (RGB) data were analysed using classical random forest (RF) and a simple and robust three-step logistic modelling approaches to identify the most important forest health indicators while adhering to the principle of parsimony. A total of 34 remote sensing variables were considered, including a set of vegetation indices, texture features from the normalized difference vegetation index (NDVI) and a digital surface model (DSM), topographic and digital aerial photogrammetry-derived structural data from the DSM at crown level. Results: The four categories identified by the RF yielded an overall accuracy of 67%, while aggregation of the legend to three classes (asymptomatic, defoliated, dead) and to two classes (alive, dead) improved the overall accuracy to 72% and 91% respectively. On the other hand, the confusion matrix, computed from the three logistic models by using the leave-out cross-validation method yielded overall accuracies of 75%, 80% and 94% for four-, three- and two-level classifications, respectively. Discussion: The study findings provide forest managers with an alternative robust classification method for the rapid, effective assessment of areas affected and non-affected by the disease, thus enabling them to identify hotspots for conservation and plan control and restoration measures aimed at preserving black alder forestsinfo:eu-repo/semantics/publishedVersio

Deformation of the Fermi surface in the extended Hubbard model

The deformation of the Fermi surface induced by Coulomb interactions is investigated in the t-t'-Hubbard model. The interplay of the local U and extended V interactions is analyzed. It is found that exchange interactions V enhance small anisotropies producing deformations of the Fermi surface which break the point group symmetry of the square lattice at the Van Hove filling. This Pomeranchuck instability competes with ferromagnetism and is suppressed at a critical value of U(V). The interaction V renormalizes the t' parameter to smaller values what favours nesting. It also induces changes on the topology of the Fermi surface which can go from hole to electron-like what may explain recent ARPES experiments.Comment: 5 pages, 4 ps figure

Superconducting and pseudogap phases from scaling near a Van Hove singularity

We study the quantum corrections to the Fermi energy of a two-dimensional electron system, showing that it is attracted towards the Van Hove singularity for a certain range of doping levels. The scaling of the Fermi level allows to cure the infrared singularities left in the BCS channel after renormalization of the leading logarithm near the divergent density of states. A phase of d-wave superconductivity arises beyond the point of optimal doping corresponding to the peak of the superconducting instability. For lower doping levels, the condensation of particle-hole pairs due to the nesting of the saddle points takes over, leading to the opening of a gap for quasiparticles in the neighborhood of the singular points.Comment: 4 pages, 6 Postscript figures, the physical discussion of the results has been clarifie

Peachy Parallel Assignments (EduHPC 2018)

Peachy Parallel Assignments are a resource for instructors teaching parallel and distributed programming. These are high-quality assignments, previously tested in class, that are readily adoptable. This collection of assignments includes implementing a subset of OpenMP using pthreads, creating an animated fractal, image processing using histogram equalization, simulating a storm of high-energy particles, and solving the wave equation in a variety of settings. All of these come with sample assignment sheets and the necessary starter code.Departamento de Informática (Arquitectura y Tecnología de Computadores, Ciencias de la Computación e Inteligencia Artificial, Lenguajes y Sistemas Informáticos)Facilitar la inclusión de ejercicios prácticos de programación paralela en cursos de Computación Paralela o de alto rendimiento (HPC)Comunicación en congreso: Descripción de ejercicios prácticos con acceso a material ya desarrollado y probado

A structured constitutive model for simulating the behaviour of an overconsolidated bonded clay

The paper presents some improvements in the formulation of a kinematic hardening constitutive soil model incorporating structure initially proposed for soft clays. For the modelling of overconsolidated bonded clay the elastic formulation was deemed more important. Two different alternatives, one purely empirically based the other with a background in thermodynamics were implemented. It was also found that a smooth elastoplastic transition was required to avoid a spurious stiffness degradation response. Consequently, the hardening modulus formulation of the model was modified. The paper presents some results from a parametric analysis of the triaxial drained response of a material tailored to mimic London clay. The results chosen do not show a major difference between the chosen alternative elastic formulations, although both do improve the original model response. On the other hand the importance of ensuring a smooth elasto-plastic transition is clearly highlighted

Colombian fruit and vegetables recognition using convolutional neural networks and transfer learning

Automatic image recognition is a convenient option for labeling and categorizing fruits and vegetables in supermarkets. This paper proposes the design and implementation of an automatic classification system for Colombian fruits, by training a convolutional neural network. A database was created to train and test the system, which consisted of 4980 images, labeled in 22 classes, each corresponding to pictures of the same kind of fruit, trying to reproduce the variability of a real case scenario with occlusions, different positions, rotations, lightings, colors, etc., and the use of bags. On-training data augmentation was used to further increase the robustness of the model. Additionally, transfer learning was implemented by taking the parameters of a pretrained model used for fruit classification as the new initial parameters of the proposed convolutional network, achieving an increase of the classification accuracy compared with the same model when trained with random initial weights. The final classification accuracy of the network was 98.12% which matches the scores achieved on previous works that performed fruit classification on less challenging datasets. Considering top-3 classification we report an accuracy of 99.95%. © 2020 IOP Publishing Ltd. All rights reserved

Microscopic description of d-wave superconductivity by Van Hove nesting in the Hubbard model

We devise a computational approach to the Hubbard model that captures the strong coupling dynamics arising when the Fermi level is at a Van Hove singularity in the density of states. We rely on an approximate degeneracy among the many-body states accounting for the main instabilities of the system (antiferromagnetism, d-wave superconductivity). The Fermi line turns out to be deformed in a manner consistent with the pinning of the Fermi level to the Van Hove singularity. For a doping rate $\delta \sim 0.2$, the ground state is characterized by d-wave symmetry, quasiparticles gapped only at the saddle-points of the band, and a large peak at zero momentum in the d-wave pairing correlations.Comment: 4 pages, 2 Postscript figure