Wind Power Forecasting Based on Echo State Networks and Long Short-Term Memory

Wind power generation has presented an important development around the world. However, its integration into electrical systems presents numerous challenges due to the variable nature of the wind. Therefore, to maintain an economical and reliable electricity supply, it is necessary to accurately predict wind generation. The Wind Power Prediction Tool (WPPT) has been proposed to solve this task using the power curve associated with a wind farm. Recurrent Neural Networks (RNNs) model complex non-linear relationships without requiring explicit mathematical expressions that relate the variables involved. In particular, two types of RNN, Long Short-Term Memory (LSTM) and Echo State Network (ESN), have shown good results in time series forecasting. In this work, we present an LSTM+ESN architecture that combines the characteristics of both networks. An architecture similar to an ESN is proposed, but using LSTM blocks as units in the hidden layer. The training process of this network has two key stages: (i) the hidden layer is trained with a descending gradient method online using one epoch; (ii) the output layer is adjusted with a regularized regression. In particular, the case is proposed where Step (i) is used as a target for the input signal, in order to extract characteristics automatically as the autoencoder approach; and in the second stage (ii), a quantile regression is used in order to obtain a robust estimate of the expected target. The experimental results show that LSTM+ESN using the autoencoder and quantile regression outperforms the WPPT model in all global metrics used

Hardening by transformation and cold working in a hadfield steel cone crusher liner

This paper presents the characterization of a secondary cone crusher concave liner made of Hadfield steel used in Chilean mining after crushing copper minerals during all service life. During use, a cone crusher concave liner suffers indentation (cold working) and abrasion; this combination provides the concave with a layer that constantly renews itself, maintaining a surface highly resistant to abrasive wear. The results presented here were obtained using optical microscopy, microhardness test, measuring abrasion using the dry sand/rubber wheel apparatus, and x-ray diffraction peaks analysis through the classic Williamson–Hall method. After analysis of results, two hardened surfaces have been found—one a product of heat treatment and the other due to deformation during use. This work proposes ways to explain them; the first one uses a thermodynamic model to calculate stacking fault energy, and the second compares the liner with cold-rolled samples.Fil: Allende Seco, Rodrigo. Universidad de Santiago de Chile; ChileFil: Artigas, Alfredo. Universidad de Santiago de Chile; ChileFil: Bruna, Héctor. Universidad de Santiago de Chile; ChileFil: Carvajal, Linton. Universidad de Santiago de Chile; ChileFil: Monsalve, Alberto. Universidad de Santiago de Chile; ChileFil: Sklate Boja, Maria Florencia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Física de Rosario. Universidad Nacional de Rosario. Instituto de Física de Rosario; Argentin

Impact Assessment on the Parallel Performance of Node-Core Combinations in a Multicore Cluster Environment: A Case of Study

Multicore processors have opened new paths for improving the parallel performance in cluster environments. Nevertheless, the selection of different combinations between the amount of nodes and the number of cores per node implies different results in terms of parallel performance. We performed an impact assessment on the parallel performance of node-core combinations using a parallel approach of a machine learning ensemble algorithm. Our results reveal that two key factors for selecting a suitable node-core combination: the network capabilities and the workload distribution. We observed that the network interconnection limits the amount of nodes that can be efficiently used, due to the extranode communications does not allow to keep scaling as the number of nodes is increased. The best results were obtained by reaching a balance between intra-node and extra-node communications. By the other hand, the parallel performance can be negatively affected when the workload distribution is not homogeneous among nodes.Sociedad Argentina de Informática e Investigación Operativ

Role played by the environment in the emergence and spread of antimicrobial resistance (AMR) through the food chain

[EN]The role of food-producing environments in the emergence and spread of antimicrobial resistance (AMR) in EU plant-based food production, terrestrial animals (poultry, cattle and pigs) and aquaculture was assessed. Among the various sources and transmission routes identified, fertilisers of faecal origin, irrigation and surface water for plant-based food and water for aquaculture were considered of major importance. For terrestrial animal production, potential sources consist of feed, humans, water, air/dust, soil, wildlife, rodents, arthropods and equipment. Among those, evidence was found for introduction with feed and humans, for the other sources, the importance could not be assessed. Several ARB of highest priority for public health, such as carbapenem or extended-spectrum cephalosporin and/or fluoroquinolone-resistant Enterobacterales (including Salmonella enterica), fluoroquinolone-resistant Campylobacter spp., methicillin-resistant Staphylococcus aureus and glycopeptide-resistant Enterococcus faecium and E. faecalis were identified. Among highest priority ARGs blaCTX-M, blaVIM, blaNDM, blaOXA-48-like, blaOXA-23, mcr, armA, vanA, cfr and optrA were reported. These highest priority bacteria and genes were identified in different sources, at primary and post-harvest level, particularly faeces/manure, soil and water. For all sectors, reducing the occurrence of faecal microbial contamination of fertilisers, water, feed and the production environment and minimising persistence/recycling of ARB within animal production facilities is a priority. Proper implementation of good hygiene practices, biosecurity and food safety management systems is very important. Potential AMR-specific interventions are in the early stages of development. Many data gaps relating to sources and relevance of transmission routes, diversity of ARB and ARGs, effectiveness of mitigation measures were identified. Representative epidemiological and attribution studies on AMR and its effective control in food production environments at EU level, linked to One Health and environmental initiatives, are urgently required.S

Role played by the environment in the emergence and spread of antimicrobial resistance (AMR) through the food chain

The role of food-producing environments in the emergence and spread of antimicrobial resistance (AMR) in EU plant-based food production, terrestrial animals (poultry, cattle and pigs) and aquaculture was assessed. Among the various sources and transmission routes identified, fertilisers of faecal origin, irrigation and surface water for plant-based food and water for aquaculture were considered of major importance. For terrestrial animal production, potential sources consist of feed, humans, water, air/dust, soil, wildlife, rodents, arthropods and equipment. Among those, evidence was found for introduction with feed and humans, for the other sources, the importance could not be assessed. Several ARB of highest priority for public health, such as carbapenem or extended-spectrum cephalosporin and/or fluoroquinolone-resistant Enterobacterales (including Salmonella enterica), fluoroquinolone-resistant Campylobacter spp., methicillin-resistant Staphylococcus aureus and glycopeptide-resistant Enterococcus faecium and E. faecalis were identified. Among highest priority ARGs blaCTX-M, blaVIM, blaNDM, blaOXA-48-like, blaOXA-23, mcr, armA, vanA, cfr and optrA were reported. These highest priority bacteria and genes were identified in different sources, at primary and post-harvest level, particularly faeces/manure, soil and water. For all sectors, reducing the occurrence of faecal microbial contamination of fertilisers, water, feed and the production environment and minimising persistence/recycling of ARB within animal production facilities is a priority. Proper implementation of good hygiene practices, biosecurity and food safety management systems is very important. Potential AMR-specific interventions are in the early stages of development. Many data gaps relating to sources and relevance of transmission routes, diversity of ARB and ARGs, effectiveness of mitigation measures were identified. Representative epidemiological and attribution studies on AMR and its effective control in food production environments at EU level, linked to One Health and environmental initiatives, are urgently required.info:eu-repo/semantics/publishedVersio

Transmission of antimicrobial resistance (AMR) during animal transport

The transmission of antimicrobial resistance (AMR) between food-producing animals (poultry, cattle and pigs) during short journeys ( 8 h) directed to other farms or to the slaughterhouse lairage (directly or with intermediate stops at assembly centres or control posts, mainly transported by road) was assessed. Among the identified risk factors contributing to the probability of transmission of antimicrobial-resistant bacteria (ARB) and antimicrobial resistance genes (ARGs), the ones considered more important are the resistance status (presence of ARB/ARGs) of the animals pre-transport, increased faecal shedding, hygiene of the areas and vehicles, exposure to other animals carrying and/or shedding ARB/ARGs (especially between animals of different AMR loads and/or ARB/ARG types), exposure to contaminated lairage areas and duration of transport. There are nevertheless no data whereby differences between journeys shorter or longer than 8 h can be assessed. Strategies that would reduce the probability of AMR transmission, for all animal categories include minimising the duration of transport, proper cleaning and disinfection, appropriate transport planning, organising the transport in relation to AMR criteria (transport logistics), improving animal health and welfare and/or biosecurity immediately prior to and during transport, ensuring the thermal comfort of the animals and animal segregation. Most of the aforementioned measures have similar validity if applied at lairage, assembly centres and control posts. Data gaps relating to the risk factors and the effectiveness of mitigation measures have been identified, with consequent research needs in both the short and longer term listed. Quantification of the impact of animal transportation compared to the contribution of other stages of the food-production chain, and the interplay of duration with all risk factors on the transmission of ARB/ARGs during transport and journey breaks, were identified as urgent research needs.info:eu-repo/semantics/publishedVersio

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected