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Effects of Andrade and Burgers rheologies on glacial isostatic adjustment modeling in Antarctica

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Geodesy and Geodynamics 2024年第5期15卷 429-440页

作者： alexandre Boughanemi Anthony Mémin UniversitéCôte d'Azur CNRSObservatoire de la Côte d'AzurIRDGéoazur250 rue Albert EinsteinSophia Antipolis 06560 ValbonneFrance

Variations in ice mass deform the Earth and modify its gravity field,a process known as Glacial Isostatic Adjustment(GIA).GIA in Antarctica remains poorly constrained due to the cumulative effect of past and present ice-mass changes,the unknown history of the past ice-mass change,and the uncertainties on the mechanical properties of the *** paper investigates the effect of using Andrade and Burgers viscoelastic rheologies,rather than the commonly used Maxwell rheology,to model GIA-induced deformation in *** Love number and Green's function formalism are used to compute the radial surface displacements and the gravity changes induced by the past and present ice-mass *** consider an Earth model whose elastic properties and radial structure are averaged from the Preliminary Reference Earth Model and two viscosity profiles to account for the recently published results on the present ice-mass *** the three rheological laws affects the temporal response of the Earth differently,leading to smaller discrepancies than those induced by the two viscosity *** differences are the largest between Maxwell and Burgers rheologies during the 100-1000 years following the beginning of the surface-mass *** show that using the Andrade and Burgers rheologies allows the Earth to respond on decennial to centennial time scales,up to 10 m more than *** only the recent ice-mass changes,the deformation rates derived from Burgers and Andrade rheologies are several times larger than those estimated by Maxwell rheology.

关键词： GIA Antarctica Modeling Rheology Displacement Viscosity GNSS

Influence of manufacturing process-induced geometrical defects on the energy absorption capacity of polymer lattice structures

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Defence Technology（防务技术） 2024年第5期35卷 47-59页

作者： alexandre Riot Enrico Panettieri Antonio Cosculluela Marco Montemurro Universite de Bordeaux Arts et Metiers Institute of TechnologyCNRSINRABordeaux INPHESAM UniversiteI2M UMR 5295F-33405 TalenceFrance French Atomic Energy Commission Route des GargailsCedexF-33114Le BarpFrance

Modern additive manufacturing processes enable fabricating architected cellular materials of complex shape,which can be used for different *** them,lattice structures are increasingly used in applications requiring a compromise among lightness and suited mechanical properties,like improved energy absorption capacity and specific stiffness-to-weight and strength-to-weight ratios.A dedicated modeling strategy to assess the energy absorption capacity of lattice structures under uni-axial compression loading is presented in this *** numerical model is developed in a non-linear framework accounting for the strain rate effect on the mechanical responses of the lattice *** geometries,i.e.,cubic body centered cell,octet cell,rhombic-dodecahedron and truncated cuboctahedron 2+,are ***,the influence of the relative density of the representative volume element of each geometry,the strain-rate dependency of the bulk material and of the presence of the manufacturing process-induced geometrical imperfections on the energy absorption capacity of the lattice structure is *** main outcome of this study points out the importance of correctly integrating geometrical imperfections into the modeling strategy when shock absorption applications are aimed for.

关键词： Lattice structures Architected cellular materials Dynamic simulation Energy absorption Geometrical imperfection Additive manufacturing

To drain or not to drain after distal pancreatectomy: reflexions on the PANDORINA trial

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Hepatobiliary Surgery and Nutrition 2024年第4期13卷 675-677页

作者： Maxime Constant alexandre Doussot Department of Digestive and Surgical Oncology Liver Transplantation UnitCHU BesanconBesançonFrance

We read with great interest the PANDORINA study(1).This international multicenter(mostly from the Netherlands)randomized controlled trial aimed at determining whether omitting drainage after distal pancreatectomy(DP)was equivalent in terms of complications to systematic drainage *** primary outcome was the occurrence of severe complications at 90 days defined as Dindo-Clavien grade≥*** main secondary outcome was the occurrence of grade B–C postoperative pancreatic fistula(POPF)at 90 *** both outcomes,the non-inferiority threshold was set at 8%.Randomization was performed intraoperatively,stratified by annual center volume(high volume defined as DP≥40/year)and the risk of POPF according to the distal fistula risk score(D-FRS)combining pancreas thickness(high risk,>19 mm)and main pancreatic duct diameter(high risk,>3 mm)measured both at the isthmus(2).

关键词： Drainage distal pancreatectomy(DP) randomized controlled trial

A review of federated learning in renewable energy applications:Potential,challenges,and future directions

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Energy and AI 2024年第3期17卷 444-457页

作者： Albin Grataloup Stefan Jonas Angela meyer Bern University of Applied Sciences School of Engineering and Computer ScienceQuellgasse 21Biel2501Switzerland Universitàdella Svizzera italiana Faculty of InformaticsVia la Santa 1Lugano-Viganello6962Switzerland Delft University of Technology Department of Geoscience and Remote SensingStevinweg 1Delft2628The Netherlands

Federated learning has recently emerged as a privacy-preserving distributed machine learning *** learning enables collaborative training of multiple clients and entire fleets without sharing the involved training *** preserving data privacy,federated learning has the potential to overcome the lack of data sharing in the renewable energy sector which is inhibiting innovation,research and *** paper provides an overview of federated learning in renewable energy *** discuss federated learning algorithms and survey their applications and case studies in renewable energy generation and *** also evaluate the potential and the challenges associated with federated learning applied in power and energy ***,we outline promising future research directions in federated learning for applications in renewable energy.

关键词： Federated learning Renewable energy Dis tributed learning Data heterogeneity Privacy Data sharing Wind energy Solar energy Buildings Review

Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability:A comprehensive systematic review

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Environmental Science and Ecotechnology 2024年第3期19卷 29-59页

作者： Simon Elias Bibri John Krogstie Amin Kaboli alexandre Alahi School of Architecture Civil and Environmental Engineering(ENAC)Civil Engineering Institute(IIC)Visual Intelligence for Transportation(VITA)Swiss Federal Institute of Technology Lausanne(EPFL)LausanneSwitzerland Department of Computer Science Norwegian University of Science and Technology(NTNU)TrondheimNorway School of Engineering Institute of Mechanical EngineeringSwiss Federal Institute of Technology Lausanne(EPFL)LausanneSwitzerland

The recent advancements made in the realms of Artificial Intelligence(AI)and Artificial Intelligence of Things(AIoT)have unveiled transformative prospects and opportunities to enhance and optimize the environmental performance and efficiency of smart *** strides have,in turn,impacted smart eco-cities,catalyzing ongoing improvements and driving solutions to address complex environmental *** aligns with the visionary concept of smarter eco-cities,an emerging paradigm of urbanism characterized by the seamless integration of advanced technologies and environmental ***,there remains a significant gap in thoroughly understanding this new paradigm and the intricate spectrum of its multifaceted underlying *** bridge this gap,this study provides a comprehensive systematic review of the burgeoning landscape of smarter eco-cities and their leadingedge AI and AIoT solutions for environmental *** ensure thoroughness,the study employs a unified evidence synthesis framework integrating aggregative,configurative,and narrative synthesis *** the core of this study lie these subsequent research inquiries:What are the foundational underpinnings of emerging smarter eco-cities,and how do they intricately interrelate,particularly urbanism paradigms,environmental solutions,and data-driven technologies?What are the key drivers and enablers propelling the materialization of smarter eco-cities?What are the primary AI and AIoT solutions that can be harnessed in the development of smarter eco-cities?In what ways do AI and AIoT technologies contribute to fostering environmental sustainability practices,and what potential benefits and opportunities do they offer for smarter eco-cities?What challenges and barriers arise in the implementation of AI and AIoT solutions for the development of smarter eco-cities?The findings significantly deepen and broaden our understanding of both the significant potential of AI and AIoT technologi

关键词： Smarter eco-cities Smart eco-cities Smart cities Artificial intelligence Artificial intelligence of things Machine learning Environmental sustainability Climate change

The impact of heterogeneity and pore network characteristics on single and multi-phase fluid propagation in complex porous media:An X-ray computed tomography study

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Petroleum Science 2024年第3期21卷 1719-1738页

作者： Shohreh Iraji Tales Rodrigues De Almeida Eddy Ruidiaz Munoz Mateus Basso alexandre Campane Vidal Department of Mechanical Engineering(FEM) State University of Campinas(UNICAMP)CampinasSP13083-860Brazil Department of Geology and Natural Resources Geosciences Institute(IG)State University of Campinas(UNICAMP)CampinasSP.13083-855.Brazil LRAP/COPPE/COPPETEC/UFRJ Rua Moniz Aragao 360Bloco 4 Cidade UniversitariaRio de Janeiro21941-594Brazil Center of Energy and Petroleum Studies(CEPETRO) State University of Campinas(UNICAMP)CampinasSP13083-896Brazil

This study investigates the impact of pore network characteristics on fluid flow through complex and heterogeneous porous media,providing insights into the factors affecting fluid propagation in such ***,high-resolution or micro X-ray computed tomography(CT)imaging techniques were utilized to examine outcrop stromatolite samples of the Lagoa Salgada,considered flow analogous to the Brazilian Pre-salt carbonate *** petrophysical results comprised two distinct stromatolite depositional facies,the columnar and the fine-grained *** generating pore network model(PNM),the study quantified the relationship between key features of the porous system,including pore and throat radius,throat length,coordination number,shape factor,and pore *** study found that the less dense pore network of the columnar sample is typically characterized by larger pores and wider and longer throats but with a weaker connection of throats to *** facies exhibited less variability in the radius of the pores and throats in comparison to throat ***,a series of core flooding experiments coupled with medical CT scanning was designed and conducted in the plug samples to assess flow propagation and saturation *** study revealed that the heterogeneity and presence of disconnected or dead-end pores significantly impacted the flow patterns and ***-phase flow patterns and oil saturation distribution reveal a preferential and heterogeneous displacement that mainly swept displaced fluid in some regions of plugs and bypassed it in *** relation between saturation profiles,porosity profiles,and the number of fluid flow patterns for the samples was *** for the columnar plug sample was the enhancement in recovery factor after shifting to lower salinity water injection(SB)observed.

关键词： Pore network model Heterogeneous porous media Flow patterns Dead-end pores

The role of extracorporeal life support and timing of repair in infants with congenital diaphragmatic hernia

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World Journal of Pediatric Surgery 2024年第2期7卷 90-99页

作者： Daniel B Gehle Logan C meyer Tim Jancelewicz Le Bonheur Children's Hospital University of Tennessee Health Science CenterMemphisTennesseeUSA

Extracorporeal life support(ECLS)serves as a rescue therapy for patients with congenital diaphragmatic hernia(CDH)and severe cardiopulmonary failure,and only half of these patients survive to *** costly intervention has a significant complication risk and is reserved for patients with the most severe disease physiology refractory to maximal cardiopulmonary *** contraindications to ECLS do exist such as coagulopathy,lethal chromosomal or congenital anomaly,very preterm birth,or very low birth weight,but many of these limits are being evaluated through further *** guidelines from the past decade vary in recommendations for ECLS use in patients with CDH but this therapy appears to have a survival benefit in the most severe subset of *** outcomes have been observed for patients treated at high-volume *** review details the evolving literature surrounding management paradigms for timing of CDH repair for patients receiving preoperative *** recent data support early repair following cannulation to avoid non-repair which is uniformly fatal in this *** ECLS runs are associated with decreased survival,and patient physiology should guide ECLS weaning and eventual decannulation rather than limiting patients to arbitrary run *** of care across centers is a major focus to limit unnecessary costs and improve short-term and long-term outcomes for these complex patients.

关键词： congenital life repair

Assimilation of GOES-R Geostationary Lightning Mapper Flash Extent Density Data in GSI 3DVar, EnKF, and Hybrid En3DVar for the Analysis and Short-Term Forecast of a Supercell Storm Case

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Advances in Atmospheric Sciences 2024年第2期41卷 263-277页

作者： Rong KONG Ming XUE Edward R.MANSELL Chengsi LIU alexandre O.FIERRO Center for Analysis and Prediction of Storms Norman Oklahoma 73072U.S.A University of Oklahoma Norman Oklahoma 73072U.S.A NOAA/National Severe Storms Laboratory NormanOklahoma 73072U.S A.4Zentralanstalt für Meteorologie und Geodynamik Department of Forecasting Models-ZAMGVienna 1190Austria

Capabilities to assimilate Geostationary Operational Environmental Satellite “R-series ”(GOES-R) Geostationary Lightning Mapper(GLM) flash extent density(FED) data within the operational Gridpoint Statistical Interpolation ensemble Kalman filter(GSI-EnKF) framework were previously developed and tested with a mesoscale convective system(MCS) case. In this study, such capabilities are further developed to assimilate GOES GLM FED data within the GSI ensemble-variational(EnVar) hybrid data assimilation(DA) framework. The results of assimilating the GLM FED data using 3DVar, and pure En3DVar(PEn3DVar, using 100% ensemble covariance and no static covariance) are compared with those of EnKF/DfEnKF for a supercell storm case. The focus of this study is to validate the correctness and evaluate the performance of the new implementation rather than comparing the performance of FED DA among different DA schemes. Only the results of 3DVar and pEn3DVar are examined and compared with EnKF/DfEnKF. Assimilation of a single FED observation shows that the magnitude and horizontal extent of the analysis increments from PEn3DVar are generally larger than from EnKF, which is mainly caused by using different localization strategies in EnFK/DfEnKF and PEn3DVar as well as the integration limits of the graupel mass in the observation operator. Overall, the forecast performance of PEn3DVar is comparable to EnKF/DfEnKF, suggesting correct implementation.

关键词： GOES-R lightning data assimilation EnKF EnVar

Topology reduction through machine learning to accelerate dynamic simulation of district heating

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Energy and AI 2024年第3期17卷 247-260页

作者： Dubon Rodrigue Mohamed Tahar Mabrouk Bastien Pasdeloup Patrick meyer Bruno Lacarrière IMT Atlantique GEPEAUMR CNRS 61444 rue Alfred KastlerNantesF-44307France IMT Atlantique Lab-STICCUMR CNRS 6285655 Av.du TechnopoleBrestF-29238France

District heating networks (DHNs) provide an efficient heat distribution solution in urban areas, accomplished through interconnected and insulated pipes linking local heat sources to local consumers. This efficiency is further enhanced by the capacity of these networks to integrate renewable heat sources and thermal storage systems. However, integration of these systems adds complexity to the physical dynamics of the network, necessitating complex dynamic simulation models. These dynamic physical simulations are computationally expensive, limiting their adoption, particularly in large-scale networks. To address this challenge, we propose a methodology utilizing Artificial Neural Networks (ANNs) to reduce the computational time associated with the DHNs dynamic simulations. Our approach consists in replacing predefined clusters of substations within the DHNs with trained surrogate ANNs models, effectively transforming these clusters into single nodes. This creates a hybrid simulation framework combining the predictions of the ANNs models with the accurate physical simulations of remaining substation nodes and pipes. We evaluate different architectures of Artificial Neural Network on diverse clusters from four synthetic DHNs with realistic heating demands. Results demonstrate that ANNs effectively learn cluster dynamics irrespective of topology or heating demand levels. Through our experiments, we achieved a 27% reduction in simulation time by replacing 39% of consumer nodes while maintaining acceptable accuracy in preserving the generated heat powers by sources.

关键词： District heating network Topology reduction Artificial neural networks Hybrid modeling Graph based formulation