Search results for "Treme"

showing 10 items of 356 documents

Effects of changing climate on European stream invertebrate communities : A long-term data analysis

2018

Long-term observations on riverine benthic invertebrate communities enable assessments of the potential impacts of global change on stream ecosystems. Besides increasing average temperatures, many studies predict greater temperature extremes and intense precipitation events as a consequence of climate change. In this study we examined long-term observation data (10-32years) of 26 streams and rivers from four ecoregions in the European Long-Term Ecological Research (LTER) network, to investigate invertebrate community responses to changing climatic conditions. We used functional trait and multi-taxonomic analyses and combined examinations of general long-term changes in communities with deta…

0106 biological sciencesConservation of Natural ResourcesEnvironmental EngineeringClimate ChangeEcology (disciplines)ta1172010603 evolutionary biology01 natural sciencesRiversAnimalsEnvironmental ChemistryEcosystemWaste Management and DisposalEcosystemInvertebrateEcology010604 marine biology & hydrobiologyfungiTemperatureExtreme eventsGlobal changeInvertebratesPollutionEuropeBenthic zoneLong term dataEnvironmental scienceta1181sense organsIntroduced SpeciesBiologieScience of the Total Environment
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Advanced methods of plant disease detection. A review

2014

International audience; Plant diseases are responsible for major economic losses in the agricultural industry worldwide. Monitoring plant health and detecting pathogen early are essential to reduce disease spread and facilitate effective management practices. DNA-based and serological methods now provide essential tools for accurate plant disease diagnosis, in addition to the traditional visual scouting for symptoms. Although DNA-based and serological methods have revolutionized plant disease detection, they are not very reliable at asymptomatic stage, especially in case of pathogen with systemic diffusion. They need at least 1–2 days for sample harvest, processing, and analysis. Here, we d…

0106 biological sciencesEnvironmental Engineering[SDV]Life Sciences [q-bio]DiseaseBiology01 natural sciences03 medical and health sciencesCommercial kitsVolatile organic compoundsSpectroscopyPlant disease030304 developmental biology2. Zero hunger0303 health sciencesbusiness.industryDNA-based methods Immunological assays Spectroscopy Biophotonics Plant disease Remote sensing Volatile organic compounds Commercial kitsEffective managementExtremely HelpfulRemote sensingPlant diseaseCrop protectionBiotechnologyRisk analysis (engineering)DNA-based methodsImmunological assaysBiophotonicsbusinessAgronomy and Crop Science010606 plant biology & botany
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Long-Term Climate Trends and Extreme Events in Northern Fennoscandia (1914–2013)

2017

We studied climate trends and the occurrence of rare and extreme temperature and precipitation events in northern Fennoscandia in 1914–2013. Weather data were derived from nine observation stations located in Finland, Norway, Sweden and Russia. The results showed that spring and autumn temperatures and to a lesser extent summer temperatures increased significantly in the study region, the observed changes being the greatest for daily minimum temperatures. The number of frost days declined both in spring and autumn. Rarely cold winter, spring, summer and autumn seasons had a low occurrence and rarely warm spring and autumn seasons a high occurrence during the last 20-year interval (1994–2013…

0106 biological sciencesextreme eventsAtmospheric Science010504 meteorology & atmospheric sciencesclimate trends climate warming cold season extreme events northern Fennoscandiata1171010603 evolutionary biology01 natural sciencesExtreme temperatureclimate warmingSpring (hydrology)Precipitationsääilmiötlcsh:Science0105 earth and related environmental sciencesgeographygeography.geographical_feature_categorycold seasonCold seasonGlobal warmingExtreme eventsilmastonmuutoksetclimate trendsnorthern Fennoscandiasademäärä13. Climate actionClimatologyFennoskandiaFrostPeriod (geology)Environmental sciencelämpötilalcsh:QClimate
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The influence of thermal extremes on coral reef fish behaviour in the Arabian/Persian Gulf

2019

Despite increasing environmental variability within marine ecosystems, little is known about how coral reef fish species will cope with future climate scenarios. The Arabian/Persian Gulf is an extreme environment, providing an opportunity to study fish behaviour on reefs with seasonal temperature ranges which include both values above the mortality threshold of Indo-Pacific reef fish, and values below the optimum temperature for growth. Summer temperatures in the Gulf are comparable to those predicted for the tropical ocean by 2090–2099. Using field observations in winter, spring and summer, and laboratory experiments, we examined the foraging activity, distance from refugia and resting tim…

0106 biological sciencesgeographygeography.geographical_feature_categorybiologyCoral reef fish010604 marine biology & hydrobiologyfungiPomacentrusCoral reefAquatic SciencePlanktonbiology.organism_classification010603 evolutionary biology01 natural sciencesOceanographyBenthic zoneEnvironmental scienceMarine ecosystemDamselfishBehaviour Plasticity Climate change Coral reef fish Extreme environmentReefgeographic locationsCoral Reefs
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The tougher the environment, the harder the adaptation? A psychological point of view in extreme situations

2021

IF: 2.8 (Q1); International audience; Grounded within a multidimensional and multilevel approach, the aim of this study was to investigate the time course of Psychological Adaptation Process (PAP) dimensions (social, emotional, occupational, and physical) during one-year polar winter-overs in Subantarctic and Antarctic stations. The effects of perceived control (PC) at the start of polar winter on the dynamics of the PAP dimensions were also examined. The present findings clarify some changes in PAP in extreme environments: (a) The dimensions of psychological adaptation evolved differently as a function of environmental conditions; and (b) PC influenced the trajectories of PAP dimensions. T…

020301 aerospace & aeronauticsPoint (typography)media_common.quotation_subject[SHS.PSY]Humanities and Social Sciences/PsychologyAerospace EngineeringMultilevel analysesPerceived control02 engineering and technologyExtreme environmentsPsychological dimensions01 natural sciences[SHS.PSY] Humanities and Social Sciences/Psychology0203 mechanical engineeringPsychological adaptation0103 physical sciencesTime coursePerceived controlAdaptationPsychologyAdaptation (computer science)Function (engineering)010303 astronomy & astrophysicsCognitive psychologymedia_common
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The role of urban growth, climate change, and their interplay in altering runoff extremes

2018

Changes in climate and urban growth are the most influential factors affecting hydrological characteristics in urban and extra-urban contexts. The assessment of the impacts of these changes on the extreme rainfall–runoff events may have important implications on urban and extra-urban management policies against severe events, such as floods, and on the design of hydraulic infrastructures. Understanding the effects of the interaction between climate change and urban growth on the generation of runoff extremes is the main aim of this paper. We carried out a synthetic experiment on a river catchment of 64 km2to generate hourly runoff time series under different hypothetical scenarios. We impos…

0208 environmental biotechnologySettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaextremeClimate changeclimate change; extreme; runoff change; runoff components; tRIBS model; urban growth; Water Science and Technology02 engineering and technology020801 environmental engineeringclimate changeurban growthEnvironmental sciencerunoff componentWater resource managementSurface runoffrunoff changerunoff componentstRIBS modelWater Science and Technology
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Extreme minimal learning machine: Ridge regression with distance-based basis

2019

The extreme learning machine (ELM) and the minimal learning machine (MLM) are nonlinear and scalable machine learning techniques with a randomly generated basis. Both techniques start with a step in which a matrix of weights for the linear combination of the basis is recovered. In the MLM, the feature mapping in this step corresponds to distance calculations between the training data and a set of reference points, whereas in the ELM, a transformation using a radial or sigmoidal activation function is commonly used. Computation of the model output, for prediction or classification purposes, is straightforward with the ELM after the first step. In the original MLM, one needs to solve an addit…

0209 industrial biotechnologyComputer scienceCognitive Neuroscienceneuraalilaskentaneuroverkot02 engineering and technologyrandomized learning machinesSet (abstract data type)extreme learning machine020901 industrial engineering & automationArtificial Intelligenceextreme minimal learning machine0202 electrical engineering electronic engineering information engineeringExtreme learning machineta113Training setBasis (linear algebra)Model selectionminimal learning machineOverlearningComputer Science ApplicationskoneoppiminenTransformation (function)020201 artificial intelligence & image processingAlgorithmNeurocomputing
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Online fitted policy iteration based on extreme learning machines

2016

Reinforcement learning (RL) is a learning paradigm that can be useful in a wide variety of real-world applications. However, its applicability to complex problems remains problematic due to different causes. Particularly important among these are the high quantity of data required by the agent to learn useful policies and the poor scalability to high-dimensional problems due to the use of local approximators. This paper presents a novel RL algorithm, called online fitted policy iteration (OFPI), that steps forward in both directions. OFPI is based on a semi-batch scheme that increases the convergence speed by reusing data and enables the use of global approximators by reformulating the valu…

0209 industrial biotechnologyInformation Systems and ManagementRadial basis function networkArtificial neural networkComputer sciencebusiness.industryStability (learning theory)02 engineering and technologyMachine learningcomputer.software_genreManagement Information Systems020901 industrial engineering & automationArtificial IntelligenceBellman equation0202 electrical engineering electronic engineering information engineeringBenchmark (computing)Reinforcement learning020201 artificial intelligence & image processingArtificial intelligencebusinesscomputerSoftwareExtreme learning machineKnowledge-Based Systems
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Serious Game Design for Flooding Triggered by Extreme Weather

2017

Managing crises with limited resources through a serious game is deemed as one of the ways of training and can be regarded as an alternative to a table-top exercise. This article presents the so-called “Operasjon Tyrsdal” serious game, inspired by a real case of extreme weather that hit the west coast of Norway. This reference case is used to add realism to the game. The game is designed for a single player, while the mechanics are framed in such a way that the player will have limited resources, and elevated event pressure over time. Beside applying an iterative Scrum method with seven Sprint cycles, we combined the development work with desk research and used the involvement of testers, i…

021110 strategic defence & security studiesExtreme weatherComputer scienceComputingMilieux_PERSONALCOMPUTING0211 other engineering and technologies0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processing02 engineering and technologySerious gameWater resource managementFlooding (computer networking)International Journal of Information Systems for Crisis Response and Management
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A Pan-Cancer Approach to Predict Responsiveness to Immune Checkpoint Inhibitors by Machine Learning

2019

Immunotherapy by using immune checkpoint inhibitors (ICI) has dramatically improved the treatment options in various cancers, increasing survival rates for treated patients. Nevertheless, there are heterogeneous response rates to ICI among different cancer types, and even in the context of patients affected by a specific cancer. Thus, it becomes crucial to identify factors that predict the response to immunotherapeutic approaches. A comprehensive investigation of the mutational and immunological aspects of the tumor can be useful to obtain a robust prediction. By performing a pan-cancer analysis on gene expression data from the Cancer Genome Atlas (TCGA, 8055 cases and 29 cancer types), we …

0301 basic medicineCancer ResearchImmune checkpoint inhibitorsmedicine.medical_treatmentimmunology-pancancerimmune checkpoint inhibitorContext (language use)Machine learningcomputer.software_genrelcsh:RC254-282Article03 medical and health sciences0302 clinical medicinemedicineExtreme gradient boostingPan cancerbusiness.industryCancerImmunotherapylcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogensMatthews correlation coefficientmedicine.diseaseSupport vector machine030104 developmental biologymachine learningOncology030220 oncology & carcinogenesisArtificial intelligencebusinesscomputerCancers
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