Search results for "fluid"

showing 10 items of 5513 documents

Spreading of Competing Information in a Network

2020

We propose a simple approach to investigate the spreading of news in a network. In more detail, we consider two different versions of a single type of information, one of which is close to the essence of the information (and we call it good news), and another of which is somehow modified from some biased agent of the system (fake news, in our language). Good and fake news move around some agents, getting the original information and returning their own version of it to other agents of the network. Our main interest is to deduce the dynamics for such spreading, and to analyze if and under which conditions good news wins against fake news. The methodology is based on the use of ladder fermion…

Computer scienceGeneral Physics and Astronomylcsh:Astrophysics01 natural sciencesArticle010305 fluids & plasmas37M05Simple (abstract algebra)0103 physical scienceslcsh:QB460-466operatorial modelsStatistical dispersionStatistical physics010306 general physicslcsh:ScienceSettore MAT/07 - Fisica Matematica(<i>H</i><i>ρ</i>)-induced dynamicsSingle type37N20lcsh:QC1-99947L90spreading of newslcsh:QFake news(H ρ)-induced dynamicslcsh:Physics(Hρ)-induced dynamicsEntropy
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Deep Learning-Based Methods for Prostate Segmentation in Magnetic Resonance Imaging

2021

Magnetic Resonance Imaging-based prostate segmentation is an essential task for adaptive radiotherapy and for radiomics studies whose purpose is to identify associations between imaging features and patient outcomes. Because manual delineation is a time-consuming task, we present three deep-learning (DL) approaches, namely UNet, efficient neural network (ENet), and efficient residual factorized convNet (ERFNet), whose aim is to tackle the fully-automated, real-time, and 3D delineation process of the prostate gland on T2-weighted MRI. While UNet is used in many biomedical image delineation applications, ENet and ERFNet are mainly applied in self-driving cars to compensate for limited hardwar…

Computer scienceGraphics processing unit02 engineering and technologyResiduallcsh:TechnologyArticle030218 nuclear medicine & medical imaginglcsh:Chemistrydeep learning; segmentation; prostate; MRI; ENet; UNet; ERFNet; radiomicsSet (abstract data type)03 medical and health sciences0302 clinical medicineENetERFNet0202 electrical engineering electronic engineering information engineeringGeneral Materials ScienceSegmentationlcsh:QH301-705.5InstrumentationSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniFluid Flow and Transfer ProcessesprostateArtificial neural networklcsh:Tbusiness.industryProcess Chemistry and TechnologyDeep learningsegmentationGeneral EngineeringProcess (computing)deep learningUNetPattern recognitionlcsh:QC1-999Computer Science Applicationslcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040radiomics020201 artificial intelligence & image processingArtificial intelligenceCentral processing unitlcsh:Engineering (General). Civil engineering (General)businesslcsh:PhysicsMRIApplied Sciences
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Pre-conceptual design of EU DEMO balance of plant systems: Objectives and challenges

2021

Abstract The European Research Roadmap to the Realisation of Fusion Energy foresees that the DEMO reactor is going to succeed ITER in the pathway towards the exploitation of nuclear fusion, achieving long plasma operation time, demonstrating tritium self-sufficiency and producing net electric output on an industrial scale. Therefore, its design must be more oriented towards the Balance of Plant (BoP) than it is in ITER. Since the early pre-conceptual phase of the DEMO project, emphasis has been laid on identifying the main requirements affecting the overall architecture of the BoP. For instance, specific efforts and proper solutions have been envisaged to cope with the pulsed nature of the …

Computer scienceHCPBBalance of plant7. Clean energy01 natural sciencesPhase (combat)010305 fluids & plasmasConceptual design0103 physical sciencesOperation timeGeneral Materials ScienceArchitecture010306 general physicsDEMOSettore ING-IND/19 - Impianti NucleariCivil and Structural Engineeringbalance of plant; DEMO; HCPB; WCLLBalance of plantMechanical EngineeringEuropean researchIndustrial scaleWCLLDesign phaseNuclear Energy and Engineering13. Climate actionSystems engineeringBalance of plant DEMO HCPB WCLL
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Preliminary design of EU DEMO helium-cooled breeding blanket primary heat transfer system

2018

Abstract The European DEMO conceptual design foresees four Breeding Blanket (BB) concepts that rely on different cooling and breeding technologies. As DEMO has been conceived to deliver net electricity to the grid, the choice of the blanket coolant plays a pivotal role in the reactor design having a strong influence on plant operation, safety and maintenance. Moreover, the machine pulsed operation makes the BB Primary Heat Transfer System (PHTS) the main hub of the DEMO Balance of Plant (BoP). Within this framework, a study has been carried out to design the Ex-Vessel PHTS of the Helium-Cooled Pebble Bed (HCPB) BB concept. The paper describes criteria and rationale followed with the aim to …

Computer scienceHCPBNuclear engineeringBlanket01 natural sciences7. Clean energy010305 fluids & plasmasConceptual design0103 physical sciencesHeat exchangerGeneral Materials Science010306 general physicsDEMOSettore ING-IND/19 - Impianti NucleariCivil and Structural EngineeringBalance of plantPipingbusiness.industryMechanical EngineeringCoolantNuclear Energy and EngineeringHeat transferPHTSMaterials Science (all)ElectricitybusinessGas compressorFusion Engineering and Design
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Progress in EU Breeding Blanket design and integration

2018

Abstract In Europe (EU), in the frame of the EUROfusion consortium activities, four Breeding Blanket (BB) concepts are being developed with the aim of fulfilling the performances required by a near-term fusion power demonstration plant (DEMO) in terms of tritium self-sufficiency and electricity production. The four blanket options cover a wide range of technological possibilities, as water and helium are considered as possible coolants and solid ceramic breeder in combination with beryllium and PbLi as tritium breeder and neutron multipliers. The strategy for the BB selection and operation has to account for the challenging schedule of the EU DEMO, the ambitious operational requirements of …

Computer scienceIn-vessel and ex-vessel componentsBlanketContinuous design7. Clean energy01 natural sciencesBalance of plan010305 fluids & plasmas[SPI]Engineering Sciences [physics]Balance of plant; Breeding Blanket; In-vessel and ex-vessel components; Civil and Structural Engineering; Nuclear Energy and Engineering; Materials Science (all); Mechanical Engineering0103 physical sciencesGeneral Materials Science010306 general physicsSettore ING-IND/19 - Impianti NucleariCivil and Structural EngineeringBalance of plantBreeding BlanketMechanical EngineeringFrame (networking)Schedule (project management)tIn-vessel and ex-vessel componentsElectricity generationNuclear Energy and Engineering13. Climate actionInterfacingSystems engineeringDemonstration PlantIn-vessel and ex-vessel componentMaterials Science (all)Design evolution
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Robust Resolution-Enhanced Prostate Segmentation in Magnetic Resonance and Ultrasound Images through Convolutional Neural Networks

2021

[EN] Prostate segmentations are required for an ever-increasing number of medical applications, such as image-based lesion detection, fusion-guided biopsy and focal therapies. However, obtaining accurate segmentations is laborious, requires expertise and, even then, the inter-observer variability remains high. In this paper, a robust, accurate and generalizable model for Magnetic Resonance (MR) and three-dimensional (3D) Ultrasound (US) prostate image segmentation is proposed. It uses a densenet-resnet-based Convolutional Neural Network (CNN) combined with techniques such as deep supervision, checkpoint ensembling and Neural Resolution Enhancement. The MR prostate segmentation model was tra…

Computer scienceMR prostate imagingUS prostate imagingINGENIERIA MECANICAconvolutional neural networklcsh:TechnologyConvolutional neural network030218 nuclear medicine & medical imaginglcsh:Chemistry03 medical and health sciences0302 clinical medicinemedicineGeneral Materials Sciencelcsh:QH301-705.5Instrumentation030304 developmental biologyFluid Flow and Transfer Processes0303 health sciencesmedicine.diagnostic_testlcsh:Tbusiness.industryProcess Chemistry and TechnologyConvolutional Neural NetworksUltrasoundResolution (electron density)General EngineeringMagnetic resonance imagingPattern recognitionProstate Segmentationlcsh:QC1-999Computer Science ApplicationsNeural resolution enhancementlcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040Christian ministryArtificial intelligencelcsh:Engineering (General). Civil engineering (General)Magnetic Resonance and Ultrasound Imagesbusinesslcsh:PhysicsProstate segmentationApplied Sciences
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Technology in Mathematics Teaching

2019

This chapter introduces the chapter of the book, in situating it in a trajectory of two researchers.

Computer scienceMathematics educationTrajectory (fluid mechanics)
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On the thermo-mechanical behaviour of DEMO water-cooled lithium lead equatorial outboard blanket module

2017

Abstract Within the framework of EUROfusion R&D activities an intense research campaign has been carried out at the University of Palermo, in close cooperation with ENEA Brasimone, in order to investigate the thermo-mechanical performances of the DEMO water-cooled lithium lead breeding blanket (WCLL). In particular, attention has been paid to the most recent geometric configuration of the DEMO WCLL outboard equatorial module, as designed by WCLL project team during 2015, endowed with an attachment system based on the use of radial pins, purposely outlined to connect the module back-plate to its back-supporting structure, that have been properly considered to simulate more realistically the …

Computer scienceMechanical EngineeringWater cooledGeometric configurationDEMO reactor WCLL blanket Lithium-lead Thermo-mechanicsMechanical engineeringBlanket01 natural sciencesFinite element method010305 fluids & plasmasNuclear Energy and EngineeringCabin pressurizationLinearization0103 physical sciencesGeneral Materials Science010306 general physicsSettore ING-IND/19 - Impianti NucleariThermo mechanicalCivil and Structural EngineeringFusion Engineering and Design
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Status of the EU DEMO HCLL breeding blanket design development

2018

International audience; In the framework of the European “HORIZON 2020” innovation and research programme, the EUROfusion Consortium develops a design of a fusion power demonstrator (DEMO). One of the key components in the fusion reactor is the Breeding Blanket (BB) surrounding the plasma, ensuring tritium self-sufficiency, heat removal for conversion into electricity, and neutron shielding. CEA-Saclay, with the support of Wigner-RCP and Centrum výzkumu Řež, is in charge of the development of one of the four BB concepts investigated in Europe for DEMO: the Helium Cooled Lithium Lead (HCLL) BB. The rationales of the HCLL are the use of Eurofer as structural material, eutectic liquid lithium-…

Computer scienceNuclear engineeringBlanketBreeding7. Clean energy01 natural sciences010305 fluids & plasmasTritium breeding ratio0103 physical sciencesGeneral Materials Science010306 general physicsDEMOSettore ING-IND/19 - Impianti NucleariCivil and Structural EngineeringBreeding BlanketHelium gasMechanical EngineeringFusion power[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationCoolantNuclear Energy and EngineeringElectromagnetic shieldingHCLLBlanketMaterials Science (all)Design evolution
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Integrating Environmental Temperature Conditions into the SIR Model for Vector-Borne Diseases

2020

International audience; Nowadays, Complex networks are used to model and analyze various problems of real-life e.g. information diffusion in social networks, epidemic spreading in human population etc. Various epidemic spreading models are proposed for analyzing and understanding the spreading of infectious diseases in human contact networks. In classical epidemiological models, a susceptible person becomes infected after getting in contact with an infected person among the human population only. However, in vector-borne diseases, a human can be infected also by a living organism called a vector. The vector population that also help in spreading diseases is very sensitive to environmental f…

Computer sciencePopulationEpidemic dynamicsEpidemic SpreadingComplex NetworkContact networkMachine learningcomputer.software_genre01 natural sciences010305 fluids & plasmasEnvironmental temperature0103 physical sciences[INFO]Computer Science [cs]010306 general physicseducationeducation.field_of_studybusiness.industryTemperatureComplex network3. Good healthHomogeneousDy- namics on NetworkVector (epidemiology)Artificial intelligenceSIR modelEpidemic modelbusinesscomputer
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