Showing papers by "Technical University of Madrid published in 2017"
TL;DR: An in depth review of rare event detection from an imbalanced learning perspective and a comprehensive taxonomy of the existing application domains of im balanced learning are provided.
Abstract: 527 articles related to imbalanced data and rare events are reviewed.Viewing reviewed papers from both technical and practical perspectives.Summarizing existing methods and corresponding statistics by a new taxonomy idea.Categorizing 162 application papers into 13 domains and giving introduction.Some opening questions are discussed at the end of this manuscript. Rare events, especially those that could potentially negatively impact society, often require humans decision-making responses. Detecting rare events can be viewed as a prediction task in data mining and machine learning communities. As these events are rarely observed in daily life, the prediction task suffers from a lack of balanced data. In this paper, we provide an in depth review of rare event detection from an imbalanced learning perspective. Five hundred and seventeen related papers that have been published in the past decade were collected for the study. The initial statistics suggested that rare events detection and imbalanced learning are concerned across a wide range of research areas from management science to engineering. We reviewed all collected papers from both a technical and a practical point of view. Modeling methods discussed include techniques such as data preprocessing, classification algorithms and model evaluation. For applications, we first provide a comprehensive taxonomy of the existing application domains of imbalanced learning, and then we detail the applications for each category. Finally, some suggestions from the reviewed papers are incorporated with our experiences and judgments to offer further research directions for the imbalanced learning and rare event detection fields.
1,448 citations
Vienna University of Technology1, University of Potsdam2, Swedish Meteorological and Hydrological Institute3, University of Messina4, University of Split5, University of Padua6, University of Zagreb7, University of Bologna8, University of Naples Federico II9, Polytechnic University of Turin10, Moscow State University11, Dokuz Eylül University12, University of Bath13, Slovak University of Technology in Bratislava14, Finnish Environment Institute15, Czech Hydrometeorological Institute16, University of Liverpool17, University of Architecture, Civil Engineering and Geodesy18, Technical University of Madrid19, Helmholtz Centre for Environmental Research - UFZ20, ETH Zurich21, Maynooth University22, Polish Academy of Sciences23, ODESSA24, University of Ljubljana25, Roma Tre University26, Norwegian Water Resources and Energy Directorate27, Polytechnic University of Tirana28, University of Belgrade29
TL;DR: Analysis of the timing of river floods in Europe over the past 50 years found clear patterns of changes in flood timing that can be ascribed to climate effects, and highlights the existence of a clear climate signal in flood observations at the continental scale.
Abstract: A warming climate is expected to have an impact on the magnitude and timing of river floods; however, no consistent large-scale climate change signal in observed flood magnitudes has been identified so far. We analyzed the timing of river floods in Europe over the past five decades, using a pan-European database from 4262 observational hydrometric stations, and found clear patterns of change in flood timing. Warmer temperatures have led to earlier spring snowmelt floods throughout northeastern Europe; delayed winter storms associated with polar warming have led to later winter floods around the North Sea and some sectors of the Mediterranean coast; and earlier soil moisture maxima have led to earlier winter floods in western Europe. Our results highlight the existence of a clear climate signal in flood observations at the continental scale.
557 citations
TL;DR: Variation in the prevalence of obesity across the European continent suggests the existence of different profiles of risk or protection factors operating in different countries, which could indicate suitable targets for interventions to help manage the obesity epidemic in Europe.
Abstract: Over the last 10 years the prevalence of obesity across the European continent has in general been rising. With the exception of a few countries where a levelling-off can be perceived, albeit at a high level, this upward trend seems likely to continue. However, considerable country to country variation is noticeable, with the proportion of people with obesity varying by 10% or more. This variation is intriguing and suggests the existence of different profiles of risk or protection factors operating in different countries. The identification of such protection factors could indicate suitable targets for interventions to help manage the obesity epidemic in Europe. This report is the output of a 2-day workshop on the ‘Diversity of Obesity in Europe'. The workshop included 14 delegates from 12 different European countries. This report contains the contributions and discussions of the materials and viewpoints provided by these 14 experts; it is not the output of a single mind. However, such is the nature of scientific analysis regarding obesity that it is possible that a different set of 14 experts may have come to a different set of conclusions. Therefore the report should not be seen as a definitive statement of a stable situation. Rather it is a focus for discussion and comment, and a vehicle to drive forward further understanding and management of obesity in Europe.
447 citations
TL;DR: In this paper, it was shown that the effective dynamics of the inflaton field presents a near-inflection point which slows down the field right before the end of inflation and gives rise to a prominent spike in the fluctuation power spectrum at scales much smaller than those probed by CMB and Large Scale Structure (LSS) observations.
445 citations
University of Electronic Science and Technology of China1, Northumbria University2, University of Bolton3, Griffith University4, University of Edinburgh5, University of Cambridge6, University of Manchester7, Technical University of Madrid8, Nanyang Technological University9, Tokyo Institute of Technology10
TL;DR: In this article, the authors acknowledge support from the Innovative electronic manufacturing research centre (IeMRC) through the EPSRC funded flagship project SMART MICROSYSTEMS.
439 citations
ETH Zurich1, University of Ulm2, Vrije Universiteit Brussel3, Royal Museum for Central Africa4, University of Coimbra5, University of Helsinki6, University of Victoria7, University of Innsbruck8, University of Milan9, Czech University of Life Sciences Prague10, Spanish National Research Council11, Swiss Federal Institute for Forest, Snow and Landscape Research12, Institut national de la recherche agronomique13, Laval University14, University of Ljubljana15, United States Geological Survey16, Ben-Gurion University of the Negev17, Center for International Forestry Research18, Dresden University of Technology19, Technical University of Berlin20, University of Arkansas21, University of Kansas22, Max Planck Society23, National Museum of Natural History24, Desert Botanical Garden25, Humboldt State University26, Sukachev Institute of Forest27, National University of Comahue28, National Scientific and Technical Research Council29, Agricultural Research Organization, Volcani Center30, Wageningen University and Research Centre31, Naturalis32, Pablo de Olavide University33, Autonomous University of Barcelona34, University of Lisbon35, Mediterranean University36, Technical University of Madrid37, University of Western Sydney38, University of Debrecen39, Natural Resources Canada40, American Hotel & Lodging Educational Institute41, Open University of Cyprus42, University of Cyprus43, University of Patras44, University of Colorado Boulder45, Northern Arizona University46, University of Novi Sad47, European Forest Institute48, Estonian University of Life Sciences49, University of Alberta50, University of Minnesota51, University of Forestry, Sofia52
TL;DR: The results imply that growth-based mortality algorithms may be a powerful tool for predicting gymnosperm mortality induced by chronic stress, but not necessarily so for angiosperms and in case of intense drought or bark-beetle outbreaks.
Abstract: Tree mortality is a key factor influencing forest functions and dynamics, but our understanding of the mechanisms
leading to mortality and the associated changes in tree growth rates are still limited. We compiled a new pan-conti-
nental tree-ring width database from sites where both dead and living trees were sampled (2970 dead and 4224 living
trees from 190 sites, including 36 species), and compared early and recent growth rates between trees that died and
those that survived a given mortality event. We observed a decrease in radial growth before death in ca. 84% of the
mortality events. The extent and duration of these reductions were highly variable (1–100 years in 96% of events) due
to the complex interactions among study species and the source(s) of mortality. Strong and long-lasting declines were
found for gymnosperms, shade- and drought-tolerant species, and trees that died from competition. Angiosperms
and trees that died due to biotic attacks (especially bark-beetles) typically showed relatively small and short-term
growth reductions. Our analysis did not highlight any universal trade-off between early growth and tree longevity
within a species, although this result may also reflect high variability in sampling design among sites. The intersite
and interspecific variability in growth patterns before mortality provides valuable information on the nature of the
mortality process, which is consistent with our understanding of the physiological mechanisms leading to mortality.
Abrupt changes in growth immediately before death can be associated with generalized hydraulic failure and/or
bark-beetle attack, while long-term decrease in growth may be associated with a gradual decline in hydraulic performance coupled with depletion in carbon reserves. Our results imply that growth-based mortality algorithms may be
a powerful tool for predicting gymnosperm mortality induced by chronic stress, but not necessarily so for angiosperms and in case of intense drought or bark-beetle outbreaks.
367 citations
TL;DR: In this paper, the relevance of informal farmer knowledge and learning practices in constructing alternative pathways in sustainable agriculture and strengthening agricultural resilience is explored, based on 11 case studies carried out within the international RETHINK research programme.
353 citations
TL;DR: This paper compares three commercially available ultrawideband location systems (Ubisense, BeSpoon, and DecaWave) under the same experimental conditions, in order to do a critical performance analysis of the 3-D positioning estimation performance.
Abstract: Most ultrawideband (UWB) location systems already proposed for position estimation have only been individually evaluated for particular scenarios. For a fair performance comparison among different solutions, a common evaluation scenario would be desirable. In this paper, we compare three commercially available UWB systems (Ubisense, BeSpoon, and DecaWave) under the same experimental conditions, in order to do a critical performance analysis. We include the characterization of the quality of the estimated tag-to-sensor distances in an indoor industrial environment. This testing space includes areas under line-of-sight (LOS) and diverse non-LOS conditions caused by the reflection, propagation, and the diffraction of the UWB radio signals across different obstacles. The study also includes the analysis of the estimated azimuth and elevation angles for the Ubisense system, which is the only one that incorporates this feature using an array antenna at each sensor. Finally, we analyze the 3-D positioning estimation performance of the three UWB systems using a Bayesian filter implemented with a particle filter and a measurement model that takes into account bad range measurements and outliers. A final conclusion is drawn about which system performs better under these industrial conditions.
342 citations
TL;DR: In this article, the potential for cover crops to mitigate climate change by tallying all of the positive and negative impacts of cover crops on the net global warming potential of agricultural fields is reviewed.
Abstract: Cover crops have long been touted for their ability to reduce erosion, fix atmospheric nitrogen, reduce nitrogen leaching, and improve soil health. In recent decades, there has been resurgence in cover crop adoption that is synchronous with a heightened awareness of climate change. Climate change mitigation and adaptation may be additional, important ecosystem services provided by cover crops, but they lie outside of the traditional list of cover cropping benefits. Here, we review the potential for cover crops to mitigate climate change by tallying all of the positive and negative impacts of cover crops on the net global warming potential of agricultural fields. Then, we use lessons learned from two contrasting regions to evaluate how cover crops affect adaptive management for precipitation and temperature change. Three key outcomes from this synthesis are (1) Cover crop effects on greenhouse gas fluxes typically mitigate warming by ~100 to 150 g CO2 e/m2/year, which is higher than mitigation from transitioning to no-till. The most important terms in the budget are soil carbon sequestration and reduced fertilizer use after legume cover crops. (2) The surface albedo change due to cover cropping, calculated for the first time here using case study sites in central Spain and Pennsylvania, USA, may mitigate 12 to 46 g CO2 e/m2/year over a 100-year time horizon. And (3) Cover crop management can also enable climate change adaptation at these case study sites, especially through reduced vulnerability to erosion from extreme rain events, increased soil water management options during droughts or periods of soil saturation, and retention of nitrogen mineralized due to warming. Overall, we found very few tradeoffs between cover cropping and climate change mitigation and adaptation, suggesting that ecosystem services that are traditionally expected from cover cropping can be promoted synergistically with services related to climate change.
322 citations
Food and Agriculture Organization1, Université libre de Bruxelles2, University of Leeds3, Environmental Change Institute4, United Nations Development Programme5, Google6, University of Adelaide7, Bartın University8, Sapienza University of Rome9, Technical University of Madrid10, Swedish University of Agricultural Sciences11, United States Department of Agriculture12, World Resources Institute13
TL;DR: An estimate of global forest extent in dryland biomes is reported, based on analyzing more than 210,000 0.5-hectare sample plots through a photo-interpretation approach using large databases of satellite imagery at very high spatial resolution and very high temporal resolution, available through the Google Earth platform.
Abstract: Dryland biomes cover two-fifths of Earth’s land surface, but their forest area is poorly known. Here, we report an estimate of global forest extent in dryland biomes, based on analyzing more than 210,000 0.5-hectare sample plots through a photo-interpretation approach using large databases of satellite imagery at (i) very high spatial resolution and (ii) very high temporal resolution, which are available through the Google Earth platform. We show that in 2015, 1327 million hectares of drylands had more than 10% tree-cover, and 1079 million hectares comprised forest. Our estimate is 40 to 47% higher than previous estimates, corresponding to 467 million hectares of forest that have never been reported before. This increases current estimates of global forest cover by at least 9%.
302 citations
TL;DR: A conceptual model capable of displaying an overview of the stakeholders taking part in the initiative in relation to the projects developed and the challenges they face is developed and applied to the case of the Vienna Smart City strategy.
TL;DR: In this article, the authors describe the requirements and needs for new, advanced materials for the fusion-facing components of a tokamak/or stellarator reactor, including fiber-reinforced and laminated structures, and mechanically alloyed tungsten materials.
Abstract: Plasma-facing materials and components in a fusion reactor are the interface between the
plasma and the material part. The operational conditions in this environment are probably
the most challenging parameters for any material: high power loads and large particle and
neutron fluxes are simultaneously impinging at their surfaces. To realize fusion in a tokamak
or stellarator reactor, given the proven geometries and technological solutions, requires an
improvement of the thermo-mechanical capabilities of currently available materials. In its
first part this article describes the requirements and needs for new, advanced materials for the
plasma-facing components. Starting points are capabilities and limitations of tungsten-based
alloys and structurally stabilized materials. Furthermore, material requirements from the
fusion-specific loading scenarios of a divertor in a water-cooled configuration are described,
defining directions for the material development. Finally, safety requirements for a fusion
reactor with its specific accident scenarios and their potential environmental impact lead to
the definition of inherently passive materials, avoiding release of radioactive material through
intrinsic material properties. The second part of this article demonstrates current material
development lines answering the fusion-specific requirements for high heat flux materials.
New composite materials, in particular fiber-reinforced and laminated structures, as well
as mechanically alloyed tungsten materials, allow the extension of the thermo-mechanical
operation space towards regions of extreme steady-state and transient loads. Self-passivating
TL;DR: It has been verified that the use of multiple criteria decision making techniques hybridized with group decision-making techniques is quite common, and theUse of both techniques for assessing sustainability problems has risen over the last few years.
Queen Mary University of London1, University of Birmingham2, Academic Medical Center3, VU University Medical Center4, King's College London5, University of Graz6, St Thomas' Hospital7, University of Southern Denmark8, University College Dublin9, University of Adelaide10, Technical University of Madrid11, State University of Campinas12, University of North Carolina at Chapel Hill13, University of Antwerp14, Katholieke Universiteit Leuven15, Monash University16, Norwegian School of Sport Sciences17, University of Manitoba18, University of Melbourne19, Alexandria University20, University of Mazandaran21, Oslo University Hospital22, University of Tampere23, University of Western Australia24, University of Modena and Reggio Emilia25, California Polytechnic State University26, Federal University of São Paulo27, Technische Universität München28, University of Copenhagen29, Norwegian University of Science and Technology30, Lund University31, Odense University Hospital32, University of Health Sciences Antigua33, Copenhagen University Hospital34, Keele University35
TL;DR: Diet and lifestyle interventions in pregnancy are clinically effective in reducing GWG irrespective of risk factors, with no effects on composite maternal and fetal outcomes.
Abstract: Background: Diet- and physical activity-based interventions in pregnancy have the potential to alter maternal and child outcomes. Objectives: To assess whether or not the effects of diet and lifestyle interventions vary in subgroups of women, based on maternal body mass index (BMI), age, parity, Caucasian ethnicity and underlying medical condition(s), by undertaking an individual patient data (IPD) meta-analysis. We also evaluated the association of gestational weight gain (GWG) with adverse pregnancy outcomes and assessed the cost-effectiveness of the interventions. Data sources: MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, Database of Abstracts of Reviews of Effects and Health Technology Assessment database were searched from October 2013 to March 2015 (to update a previous search). Review methods: Researchers from the International Weight Management in Pregnancy Collaborative Network shared the primary data. For each intervention type and outcome, we performed a two-step IPD random-effects meta-analysis, for all women (except underweight) combined and for each subgroup of interest, to obtain summary estimates of effects and 95% confidence intervals (CIs), and synthesised the differences in effects between subgroups. In the first stage, we fitted a linear regression adjusted for baseline (for continuous outcomes) or a logistic regression model (for binary outcomes) in each study separately; estimates were combined across studies using random-effects meta-analysis models. We quantified the relationship between weight gain and complications, and undertook a decision-analytic model-based economic evaluation to assess the cost-effectiveness of the interventions. Results: Diet and lifestyle interventions reduced GWG by an average of 0.70 kg (95% CI-0.92 to-0.48 kg; 33 studies, 9320 women). The effects on composite maternal outcome [summary odds ratio (OR) 0.90, 95% CI 0.79 to 1.03; 24 studies, 8852 women] and composite fetal/neonatal outcome (summary OR 0.94, 95% CI 0.83 to 1.08; 18 studies, 7981 women) were not significant. The effect did not vary with baseline BMI, age, ethnicity, parity or underlying medical conditions for GWG, and composite maternal and fetal outcomes. Lifestyle interventions reduce Caesarean sections (OR 0.91, 95% CI 0.83 to 0.99), but not other individual maternal outcomes such as gestational diabetes mellitus (OR 0.89, 95% CI 0.72 to 1.10), pre-eclampsia or pregnancy-induced hypertension (OR 0.95, 95% CI 0.78 to 1.16) and preterm birth (OR 0.94, 95% CI 0.78 to 1.13). There was no significant effect on fetal outcomes. The interventions were not cost-effective. GWG, including adherence to the Institute of Medicine-recommended targets, was not associated with a reduction in complications. Predictors of GWG were maternal age (summary estimate-0.10 kg, 95% CI-0.14 to-0.06 kg) and multiparity (summary estimate-0.73 kg, 95% CI-1.24 to-0.23 kg). Limitations: The findings were limited by the lack of standardisation in the components of intervention, residual heterogeneity in effects across studies for most analyses and the unavailability of IPD in some studies. Conclusion: Diet and lifestyle interventions in pregnancy are clinically effective in reducing GWG irrespective of risk factors, with no effects on composite maternal and fetal outcomes. Future work: The differential effects of lifestyle interventions on individual pregnancy outcomes need evaluation. Study registration: This study is registered as PROSPERO CRD42013003804.
TL;DR: The irradiation of gold nanorod colloids with a femtosecond laser can be tuned to induce controlled nan orod reshaping, yielding colloid clusters with exceptionally narrow localized surface plasmon resonance bands.
Abstract: The irradiation of gold nanorod colloids with a femtosecond laser can be tuned to induce controlled nanorod reshaping, yielding colloids with exceptionally narrow localized surface plasmon resonance bands. The process relies on a regime characterized by a gentle multishot reduction of the aspect ratio, whereas the rod shape and volume are barely affected. Successful reshaping can only occur within a narrow window of the heat dissipation rate: Low cooling rates lead to drastic morphological changes, and fast cooling has nearly no effect. Hence, a delicate balance must be achieved between irradiation fluence and surface density of the surfactant on the nanorods. This perfection process is appealing because it provides a simple, fast, reproducible, and scalable route toward gold nanorods with an optical response of exceptional quality, near the theoretical limit.
Technical University of Madrid1, University of Portsmouth2, Universidade Federal de Juiz de Fora3, Józef Piłsudski University of Physical Education in Warsaw4, University of New South Wales5, Queensland University of Technology6, University of the Sunshine Coast7, Federal University of Paraíba8, University of Milan9, Oxylane Group10, Loughborough University11, Royal Free Hospital12, University of Ottawa13, Universidad Autónoma de San Luis Potosí14, University of Chieti-Pescara15, Auburn University16, University of Valencia17, Fernando Pessoa University18, Manchester Metropolitan University19, Novosibirsk State University20
TL;DR: It is intended that the TISEM can also be applied to evaluate bias in thermographic studies and to guide practitioners in the use of this technique.
TL;DR: In this paper, the accuracy and performance of three soft computing techniques (i.e., adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN) and support vector machine (SVM)) were assessed for predicting daily horizontal global solar radiation from measured meteorological variables in the Yucatan Peninsula, Mexico.
TL;DR: A review of statistical and machine-learning data-based predictive models, which have been applied to dam safety analysis is presented in this article, where some aspects to take into account when developing analysis of this kind, such as the selection of the input variables, its division into training and validation sets, and the error analysis are discussed.
Abstract: Predictive models are an important element in dam safety analysis. They provide an estimate of the dam response faced with a given load combination, which can be compared with the actual measurements to draw conclusions about dam safety. In addition to numerical finite element models, statistical models based on monitoring data have been used for decades for this purpose. In particular, the hydrostatic-season-time method is fully implemented in engineering practice, although some limitations have been pointed out. In other fields of science, powerful tools such as neural networks and support vector machines have been developed, which make use of observed data for interpreting complex systems
. This paper contains a review of statistical and machine-learning data-based predictive models, which have been applied to dam safety analysis
. Some aspects to take into account when developing analysis of this kind, such as the selection of the input variables, its division into training and validation sets, and the error analysis, are discussed. Most of the papers reviewed deal with one specific output variable of a given dam typology and the majority also lack enough validation data. As a consequence, although results are promising, there is a need for further validation and assessment of generalisation capability. Future research should also focus on the development of criteria for data pre-processing and model application.
TL;DR: A chimeric recombinant spider silk protein (spidroin) whose aqueous solubility equals that of native spider silk dope and a spinning device that is based solely on aqueously buffers, shear forces and lowered pH is presented.
Abstract: Herein we present a chimeric recombinant spider silk protein (spidroin) whose aqueous solubility equals that of native spider silk dope and a spinning device that is based solely on aqueous buffers, shear forces and lowered pH. The process recapitulates the complex molecular mechanisms that dictate native spider silk spinning and is highly efficient; spidroin from one liter of bacterial shake-flask culture is enough to spin a kilometer of the hitherto toughest as-spun artificial spider silk fiber.
TL;DR: This review focuses on the current knowledge about the impact of microorganisms in wine aroma and flavour, and the biochemical reactions and pathways in which they participate, therefore contributing to both the quality and acceptability of wine.
Abstract: Wine is a complex matrix that includes components with different chemical natures, the volatile compounds being responsible for wine aroma quality. The microbial ecosystem of grapes and wine, including Saccharomyces and non-Saccharomyces yeasts, as well as lactic acid bacteria, is considered by winemakers and oenologists as a decisive factor influencing wine aroma and consumer’s preferences. The challenges and opportunities emanating from the contribution of wine microbiome to the production of high quality wines are astounding. This review focuses on the current knowledge about the impact of microorganisms in wine aroma and flavour, and the biochemical reactions and pathways in which they participate, therefore contributing to both the quality and acceptability of wine. In this context, an overview of genetic and transcriptional studies to explain and interpret these effects is included, and new directions are proposed. It also considers the contribution of human oral microbiota to wine aroma conversion and perception during wine consumption. The potential use of wine yeasts and lactic acid bacteria as biological tools to enhance wine quality and the advent of promising advice allowed by pioneering -omics technologies on wine research are also discussed.
TL;DR: It is shown that Faraday/Vernadsky warming trend is an extreme case, circa twice those of the long-term records from other parts of the northern AP, and the results indicate that the cooling initiated in 1998/1999 has been most significant in the N and NE of the AP and the South Shetland Islands.
Technical University of Madrid1, Netherlands Environmental Assessment Agency2, Pablo de Olavide University3, University of the Basque Country4, Centre national de la recherche scientifique5, Wageningen University and Research Centre6, Institut national de la recherche agronomique7, University of Göttingen8, Spanish National Research Council9, Xunta de Galicia10, Mayo Clinic11, Complutense University of Madrid12, Karlsruhe Institute of Technology13, Polytechnic University of Valencia14, University of Aberdeen15
TL;DR: In this article, an integrated assessment of the potential of different management practices for mitigating specific components of the total GHG budget (N2O and CH4 emissions and C sequestration) of Mediterranean agro-systems was performed.
TL;DR: In this paper, the authors summarized the current state-of-the-art and challenges for the future developments of fiber-reinforced composites for structural applications with multifunctional capabilities.
Abstract: This review paper summarizes the current state-of-art and challenges for the future developments of fiber-reinforced composites for structural applications with multifunctional capabilities. After a brief analysis of the reasons of the successful incorporation of fiber-reinforced composites in many different industrial sectors, the review analyzes three critical factors that will define the future of composites. The first one is the application of novel fiber-deposition and preforming techniques together with innovative liquid moulding strategies, which will be combined by optimization tools based on novel multiscale modelling approaches, so fiber-reinforced composites with optimized properties can be designed and manufactured for each application. In addition, composite applications will be enhanced by the incorporation of multifunctional capabilities. Among them, electrical conductivity, energy storage (structural supercapacitors and batteries) and energy harvesting (piezoelectric and solar energy) seem to be the most promising ones.
TL;DR: Developing approximate inference techniques to solve fundamental problems in signal processing, such as localization of objects in wireless sensor networks and the Internet of Things, and multiple source reconstruction from electroencephalograms.
Abstract: A fundamental problem in signal processing is the estimation of unknown parameters or functions from noisy observations. Important examples include localization of objects in wireless sensor networks [1] and the Internet of Things [2]; multiple source reconstruction from electroencephalograms [3]; estimation of power spectral density for speech enhancement [4]; or inference in genomic signal processing [5]. Within the Bayesian signal processing framework, these problems are addressed by constructing posterior probability distributions of the unknowns. The posteriors combine optimally all of the information about the unknowns in the observations with the information that is present in their prior probability distributions. Given the posterior, one often wants to make inference about the unknowns, e.g., if we are estimating parameters, finding the values that maximize their posterior or the values that minimize some cost function given the uncertainty of the parameters. Unfortunately, obtaining closed-form solutions to these types of problems is infeasible in most practical applications, and therefore, developing approximate inference techniques is of utmost interest.
TL;DR: In this paper, the authors present an overview of some basic concepts of close range HSI on plants, concerning the plant-light interaction, instrumental setup, and spectral data analysis, and discuss some of the technical challenges related to the implementation of HSI in the close range assessment of plant traits.
TL;DR: The wpath semantic similarity method has produced a statistically significant improvement over other semantic similarity methods, and in a real category classification evaluation, the wpath method has shown the best performance in terms of accuracy and F score.
Abstract: This paper presents a method for measuring the semantic similarity between concepts in Knowledge Graphs (KGs) such as WordNet and DBpedia. Previous work on semantic similarity methods have focused on either the structure of the semantic network between concepts (e.g., path length and depth), or only on the Information Content (IC) of concepts. We propose a semantic similarity method, namely wpath, to combine these two approaches, using IC to weight the shortest path length between concepts. Conventional corpus-based IC is computed from the distributions of concepts over textual corpus, which is required to prepare a domain corpus containing annotated concepts and has high computational cost. As instances are already extracted from textual corpus and annotated by concepts in KGs, graph-based IC is proposed to compute IC based on the distributions of concepts over instances. Through experiments performed on well known word similarity datasets, we show that the wpath semantic similarity method has produced a statistically significant improvement over other semantic similarity methods. Moreover, in a real category classification evaluation, the wpath method has shown the best performance in terms of accuracy and F score.
TL;DR: In this paper, the authors presented a methodology for the analysis of frequency dynamics in large-scale power systems with high level of wind energy penetration by means of a simplified model for DFIG-based wind turbines.
Abstract: This paper presents a methodology for the analysis of frequency dynamics in large-scale power systems with high level of wind energy penetration by means of a simplified model for DFIG-based wind turbines. In addition, a virtual inertia controller version of the optimized power point tracking (OPPT) method is implemented for this kind of wind turbines, where the maximum power point tracking curve is shifted to drive variations in the active power injection as a function of both the grid frequency deviation and its time derivative. The proposed methodology integrates the model in a primary frequency control scheme to analyze the interaction with the rest of the plants in the power system. It is also proven that, under real wind conditions, the proposed version of the OPPT method allows us to smooth the wind power injected into the grid, thereby reducing frequency fluctuations.
TL;DR: In this paper, the authors reviewed the 2014-2016 JET results in the light of their significance for optimising the ITER research plan for the active and non-active operation, stressing the importance of the magnetic configurations and the recent measurements of fine-scale structures in the edge radial electric.
Abstract: The 2014-2016 JET results are reviewed in the light of their significance for optimising the ITER research plan for the active and non-active operation. More than 60 h of plasma operation with ITER first wall materials successfully took place since its installation in 2011. New multi-machine scaling of the type I-ELM divertor energy flux density to ITER is supported by first principle modelling. ITER relevant disruption experiments and first principle modelling are reported with a set of three disruption mitigation valves mimicking the ITER setup. Insights of the L-H power threshold in Deuterium and Hydrogen are given, stressing the importance of the magnetic configurations and the recent measurements of fine-scale structures in the edge radial electric. Dimensionless scans of the core and pedestal confinement provide new information to elucidate the importance of the first wall material on the fusion performance. H-mode plasmas at ITER triangularity (H = 1 at β N ∼ 1.8 and n/n GW ∼ 0.6) have been sustained at 2 MA during 5 s. The ITER neutronics codes have been validated on high performance experiments. Prospects for the coming D-T campaign and 14 MeV neutron calibration strategy are reviewed.
TL;DR: In this article, high-fidelity simulations of the material behavior at the micro level are used to predict ply properties and ascertain the effect of ply constituents and microstructure on the homogenized ply behavior.
Abstract: Qualification of Fiber Reinforced Polymer materials (FRP’s) for manufacturing of structural components in the aerospace industry is usually associated with extensive and costly experimental campaigns. The burden of testing is immense and materials should be characterized under different loading states (tension, compression, shear) and environmental conditions (temperature, humidity) to probe their structural integrity during service life. Recent developments in multiscale simulation, together with increased computational power and improvements in modeling tools, can be used to alleviate this scenario. In this work, high-fidelity simulations of the material behavior at the micro level are used to predict ply properties and ascertain the effect of ply constituents and microstructure on the homogenized ply behavior. This approach relies on the numerical analysis of representative volume elements equipped with physical models of the ply constituents. Its main feature is the ability to provide fast predictions of ply stiffness and strength properties for different environmental conditions of temperature and humidity, in agreement with the experimental results, showing the potential to reduce the time and costs required for material screening and characterization.
TL;DR: It is suggested that MIK2 is a nexus linking cell wall integrity sensing to growth and environmental cues and is required for resistance to the fungal root pathogen Fusarium oxysporum.
Abstract: Plants actively perceive and respond to perturbations in their cell walls which arise during growth, biotic and abiotic stresses However, few components involved in plant cell wall integrity sensing have been described to date Using a reverse-genetic approach, we identified the Arabidopsis thaliana leucine-rich repeat receptor kinase MIK2 as an important regulator of cell wall damage responses triggered upon cellulose biosynthesis inhibition Indeed, loss-of-function mik2 alleles are strongly affected in immune marker gene expression, jasmonic acid production and lignin deposition MIK2 has both overlapping and distinct functions with THE1, a malectin-like receptor kinase previously proposed as cell wall integrity sensor In addition, mik2 mutant plants exhibit enhanced leftward root skewing when grown on vertical plates Notably, natural variation in MIK2 (also named LRR-KISS) has been correlated recently to mild salt stress tolerance, which we could confirm using our insertional alleles Strikingly, both the increased root skewing and salt stress sensitivity phenotypes observed in the mik2 mutant are dependent on THE1 Finally, we found that MIK2 is required for resistance to the fungal root pathogen Fusarium oxysporum Together, our data identify MIK2 as a novel component in cell wall integrity sensing and suggest that MIK2 is a nexus linking cell wall integrity sensing to growth and environmental cues