Typification and economic analysis of beef-producing farms in Spain

In spite of different economic agents’ interests, as well as the Administration’s effort in promoting extensive beef-producing systems over the last years, this kind of activity still hasn’t reached the desirable levels, being necessary that farmers perceive an appropriate benefit which supports their activity. In this sense, this paper, using the data obtained by a statistical survey representing all the extensive beef-producing farms existing in Castile and Leon (Spain), aims to analyze the economical results of extensive beef-producing farms, previously classified in representative groups according a quantitative method. The study is a preliminary research which intends to generate additional knowledge about the role of the different variables which make part of the economic results, and takes part of a research project financed by Castile and Leon Regional Governments, Education and Culture Council, through the annual program to support research projects (Order EDU/1143/2004).Cluster Analysis, extensive beef producing systems, economic accounts, Livestock Production/Industries,

Ada real-time services and virtualization

Virtualization techniques have received increased attention in the field of embedded real-time systems. Such techniques provide a set of virtual machines that run on a single hardware platform, thus allowing several application programs to be executed as though they were running on separate machines, with isolated memory spaces and a fraction of the real processor time available to each of them.This papers deals with some problems that arise when implementing real-time systems written in Ada on a virtual machine. The effects of virtualization on the performance of the Ada real-time services are analysed, and requirements for the virtualization layer are derived. Virtual-machine time services are also defined in order to properly support Ada real-time applications. The implementation of the ORK+ kernel on the XtratuM supervisor is used as an example

Secuenciación dinámica de sistemas de fabricación flexible mediante aprendizaje automático: análisis de los principales sistemas de secuenciación existentes

Una forma habitual de secuenciar de modo dinámico los trabajos en los sistemas de fabricación es mediante el empleo de reglas de secuenciación. Sin embargo, el problema que presenta este método es que el comportamiento del sistema de fabricación dependerá de su estado, y no existe una regla que supere a las demás en todos los posibles estados que puede presentar el sistema de fabricación. Por lo tanto, sería interesante usar en cada momento la regla más adecuada. Para lograr este objetivo, se pueden utilizar sistemas de secuenciación que emplean aprendizaje automático que permiten, analizando el comportamiento previo del sistema de fabricación (ejemplos de entrenamiento), obtener el conocimiento necesario para determinar la regla de secuenciación más apropiada en cada instante. En el presente trabajo se realiza una revisión de los principales sistemas de secuenciación existentes en la literatura que utilizan aprendizaje automático para variar de forma dinámica la regla de secuenciación empleada en cada momento

Signals of CP Violation Beyond the MSSM in Higgs and Flavor Physics

We study an extension of the Higgs sector of the Minimal Supersymmetric Standard Model (MSSM), considering the effects of new degrees of freedom at the TeV scale, and allowing for sources of CP violation beyond the MSSM (BMSSM). We analyze the impact of the BMSSM sources of CP violation on the Higgs collider phenomenology and on low energy flavor and CP violating observables. We identify distinct Higgs collider signatures that cannot be realized, either in the case without CP violating phases or in the CP violating MSSM, and investigate the prospects to probe them at the Tevatron and the LHC. The most striking benchmark scenario has three neutral Higgs bosons that all decay dominantly into W boson pairs and that are well within the reach of the 7 TeV LHC run. On the other hand, we also present scenarios with three Higgs bosons that have masses M_Hi > 150 GeV and decay dominantly into b bbar. Such scenarios are much more challenging to probe and can even lie completely outside the reach of the 7 TeV LHC run. We explore complementary scenarios with standard MSSM Higgs signals that allow to accommodate a sizable B_s mixing phase as indicated by D0, as well as the excess in B_s --> mu+ mu- candidates recently reported by CDF. We find that, in contrast to the MSSM, a minimal flavor violating soft sector is sufficient to generate significant corrections to CP violating observables in meson mixing, compatible with EDM constraints. In particular, a sizable B_s mixing phase, S_psiphi < 0.4, can be achieved for specific regions of parameter space. Such a large B_s mixing phase would unambiguously imply a sizable suppression of S_psiKs with respect to the SM prediction and a BR(B_s --> mu+ mu-) close to the 95% C.L. upper bound reported by CDF.Comment: 58 pages, 15 figures, 2 tables, v2 matches published versio

Localization Method for Autonomous Vehicles by using Vertical Elements in the Environment

The goal of this work is to provide autonomous cars with an alternative method to estimate their position in the world. It focuses on those situations when the GPS signal gets imprecise, weak or even lost due to environment conditions (long tunnels, dense forests, high buildings around, etc.). By installing two Velodyne VLP-16 LiDAR devices on the top of the car, located on both front corners of the vehicle structure, it is possible to acquire a 3D representation of this environment as a point cloud. This point cloud will be analyzed in order to find thin, vertical elements, such as traffic signals, traffic lights and so on. If these elements have been previously georeferenced, this is, their coordinates have been acquired and saved, the method will try to compare and match the incoming information from the environment to the georeferenced objects, i.e., performing data association. If the detected elements match any of the georeferenced ones, the car will correct an estimate of its position in a global frame.RoboCity2030-DIH-CM, Madrid Robotics Digital Innovation Hub, S2018/NMT-4331, funded by R&D Activities Program in Comunidad de Madrid and cofunded by EU Structural Funds.Peer reviewe

Predicting non-native seaweeds global distributions: The importance of tuning individual algorithms in ensembles to obtain biologically meaningful results

ABSTRACT: Modelling non-native marine species distributions is still a challenging activity. This study aims to predict the global distribution of five widespread introduced seaweed species by focusing on two mains aspects of the ensemble modeling process: (1) Does the enforcement of less complex models (in terms of number of predictors) help in obtaining better predictions? (2) What are the implications of tuning the configuration of individual algorithms in terms of ecological realism? Regarding the first aspect, two datasets with different number of predictors were created. Regarding the second aspect, four algorithms and three configurations were tested. Models were evaluated using common evaluation metrics (AUC, TSS, Boyce index and TSS-derived sensitivity) and ecological realism. Finally, a stepwise procedure for model selection was applied to build the ensembles. Models trained with the large predictor dataset generally performed better than models trained with the reduced dataset, but with some exceptions. Regarding algorithms and configurations, Random Forest (RF) and Generalized Boosting Models (GBM) scored the highest metric values in average, even though, RF response curves were the most unrealistic and non-smooth and GBM showed overfitting for some species. Generalized Linear Models (GLM) and MAXENT, despite their lower scores, fitted smoother curves (especially at intermediate complexity levels). Reliable and biologically meaningful predictions were achieved. Inspecting the number of predictors to include in final ensembles and the selection of algorithms and its complexity have been demonstrated to be crucial for this purpose. Additionally, we highlight the importance of combining quantitative (based on multiple evaluation metrics) and qualitative (based on ecological realism) methods for selecting optimal configurations.This work was funded by the National Plan for Research in Science and Technological Innovation from the Spanish Government 2017-2020 [grant number C3N-pro project PID2019-105503RB-I00] and co-funded by the European Regional Development’s funds. SS-V acknowledges financial support under a predoctoral grant from the Spanish Ministry of Education andVocational Training [grantnumber:FPU18/03573]. CH acknowledges the financial support from the Government of Cantabria through the Fénix Programme and under a postdoctoral grant from the University of Cantabria [grant number: POS-UC- 2020-07]. This work is part of the PhD project of SS-V

Nested Socio-Ecological Maps as a Spatial Planning Instrument for Estuary Conservation and Ecosystem-Based Management

ABSTRACT: Estuaries are socio-ecological systems that can be represented as a holistic combination of biotic and abiotic conditions in spatially explicit units defined by: (i) the ecotope, as the integration of the physiotope (abiotic-homogeneous units) and the biotope (biotic-homogeneous units), and (ii) the anthrotope, synthesizing data on human drivers of ecological change. Nested physiotopes were identified in an estuary using a hierarchical approach that integrates information about eight abiotic, and biologically meaningful, variables. The biotope of Zostera noltei was delimited using a potential distribution model of species and overlapped with the physiotope map to characterize the ecotopes. The anthrotope was estimated as the cumulative impacts of anthropic activities over the ecotopes. The diversity of Z. noltei ecotopes was compared with the anthrotope map to estimate the potential impacts of human pressures on this species. The hierarchical methodology and resulting maps provide flexible and interdisciplinary tools for conservation, management, education and research.This research was part of the ECOTOPO project (RTI2018-096409-B-I00) financially supported by the Spanish Ministry of Science and Innovation through the National Plan for Scientific Research