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Intelligent speed adaptation for visibility technology affects drivers’speed selection along curves with sight limitations

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Journal of Traffic and Transportation Engineering(English Edition) 2024年第1期11卷 16-27页

作者： Abrar Hazoor alberto Terrafino leandro l.Di Stasi Marco Bassani Department of Environment Landand Infrastructure EngineeringPolitecnico di TorinoTorino 10129Italy Road Traffic Division Nord UniversityStjørdal 7502Norway Mind Brainand Behavior Research Centre(CIMCYC)University of GranadaGranada 18071Spain

Sight obstructions along road curves can lead to a crash if the driver is not able to stop the vehicle in *** is a particular issue along curves with limited available sight,where speed management is necessary to avoid unsafe situations(e.g.,driving off the road or invading the other traffic lane).To solve this issue,we proposed a novel intelligent speed adaptation(ISA)system for visibility,called V-ISA(intelligent speed adaptation for visibility).It estimates the real-time safe speed limits based on the prevailing sight conditions.V-ISA comes with three variants with specific feedback modalities(1)visual and(2)auditory information,and(3)direct intervention to assume control over the vehicle ***,we investigated the efficiency of each of the three V-ISA variants on driving speed choice and lateral behavioural response along road curves with limited and unsafe available sight distances,using a driving *** also considered curve road geometry(curve direction:rightward ***).Sixty active drivers were recruited for the *** half of them(experimental group)tested the three V-ISA variants(and a V-ISA off condition),the other half always drove with the V-ISA off(validation group).We used a linear mixed-effect model to evaluate the influence of V-ISA on driver *** V-ISA variants were efficient at reducing speeds at entrance points,with no discernible negative impact on driver lateral *** rightward curves,the V-ISA intervening variant appeared to be the most effective at adapting to sight *** of the current study implies that V-ISA might assist drivers to adjust their operating speed as per prevailing sight conditions and,consequently,establishes safer driving conditions.

关键词： Sight distance Intelligent speed adaptation Driver behaviour Road safety Driving simulation Advanced driver assistance systems

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Predicting grain size-dependent superplastic properties in friction stir processed ZK30 magnesium alloy with machine learning methods

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Journal of Magnesium and Alloys 2024年第5期12卷 1931-1943页

作者： Farid Bahari-Sambran Fernando carreno c.M.cepeda-Jiménez alberto Orozco-caballero Physical Metallurgy Department CENIM-CSICAv.Gregorio del Amo 828040 MadridSpain Department of Mechanical Engineering Chemistry and Industrial DesignPolytechnic University of MadridRonda de Valencia 328012MadridSpain

The aim of this work is to predict,for the first time,the high temperature flow stress dependency with the grain size and the underlaid deformation mechanism using two machine learning models,random forest(RF)and artificial neural network(ANN).With that purpose,a ZK30 magnesium alloy was friction stir processed(FSP)using three different severe conditions to obtain fine grain microstructures(with average grain sizes between 2 and 3μm)prone to extensive superplastic *** three friction stir processed samples clearly deformed by grain boundary sliding(GBS)deformation mechanism at high *** maximum elongations to failure,well over 400% at high strain rate of 10^(-2)s^(-1),were reached at 400℃ in the material with coarsest grain size of 2.8μm,and at 300℃ for the finest grain size of 2μ***,the superplastic response decreased at 350℃ and 400℃ due to thermal instabilities and grain coarsening,which makes it difficult to assess the operative deformation mechanism at such *** work highlights that the machine learning models considered,especially the ANN model with higher accuracy in predicting flow stress values,allow determining adequately the superplastic creep behavior including other possible grain size scenarios.

关键词： Machine learning Artificial intelligence Magnesium alloys Superplasticity Friction stir processing Grain coarsening

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Middle Eocene chondrichthyan fauna from Antarctic Peninsula housed in the Museo de la Plata,Argentina

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Advances in Polar Science 2024年第1期35卷 14-47页

作者： Martina cHARNEllI Soledad GOUIRIc-cAVAllI Marcelo A.REGUERO alberto l.c.one Agencia Nacional de Promoción científica y Tecnológica(ANPcyT) Godoy Cruz 2370Argentina División Paleontología Vertebrados Museo de La PlataPaseo del Bosque s/nLa Plata B1900FWAArgentina Facultad de ciencias Naturales y Museo de la Plata(FcNyM) Universidad Nacional de La Plata(UNLP)La Plata CP 1900Argentina Instituto Antártico Argentino(IAA) General San Martín B1650HMKArgentina consejo Nacional de Investigaciones científicas y Técnicas(cONIcET) Buenos Aires C1425FQBArgentina

In recent years,the taxonomy and systematics of the cartilaginous fish taxa from the Eocene la Meseta Formation of Seymour(Marambio)Island,Antarctica have been extensively discussed in a series of papers,resulting in a complete revision of the Antarctic Eocene ichthyofauna housed in the Vertebrate Paleontology collection of the Museo de la Plata,*** collection constitutes one of the largest and taxonomically most diverse in the world,with approximately 20000 specimens,which provides a solid database used for the analysis of qualitative and quantitative chondrichthyan taxonomic *** information provided herein might be useful to understand the sudden decline in chondrichthyan taxonomic diversity towards the top of la Meseta Formation as well as its potential relationship with environmental changes during the Eocene.

关键词： Gondwana Antarctica Paleogene ichthyofauna Seymour(Marambio)Island

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Metal-modulated epitaxy of Mg-doped Al_(0.80)In_(0.20)N-based layer for application as the electron blocking layer in deep ultraviolet light-emitting diodes

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Journal of Semiconductors 2024年第5期45卷 80-89页

作者： Horacio Irán Solís-cisneros carlos alberto Hernández-Gutiérrez Enrique campos-González Máximo lópez-lópez Optomechatronics Group Tecnológico Nacional de México Campus Tuxtla Gutiérrezcarretera Panamericana 1080C.P.29050Tuxtla GutiérrezChiapasMéxico Departamento de Física Instituto Nacional de Investigaciones NuclearesCarretera México-Toluca s/nC.P.52750La Marquesa OcoyoacacMéxico Departamento de Física Centro de Investigación y estudios Avanzados del Instituto Politécnico NacionalAv.Instituto Politécnico Nacional 2508San Pedro ZacatencoGustavo A.Madero07360 Ciudad de MéxicoCDMXMéxico

This work reports the growth and characterization of p-AlInN layers doped with Mg by plasma-assisted molecular beam epitaxy(PAMBE).AlInN was grown with an Al molar fraction of 0.80 by metal-modulated epitaxy(MME)with a thickness of 180 nm on Si(111)substrates using AlN as buffer *** substrate temperatures were used to enhance the incorporation of indium atoms into the alloy without clustering,as confirmed by X-ray diffraction(XRD).cathodoluminescence measurements revealed ultraviolet(UV)range ***,Hall effect measurements indicated a maximum hole mobility of 146 cm^(2)/(V∙s),corresponding to a free hole concentration of 1.23×10^(19)cm^(−3).The samples were analyzed by X-ray photoelectron spectroscopy(XPS)estimating the alloy composition and extracting the Fermi level by valence band ***-doped AlInN layers were studied for use as the electron-blocking layer(EBl)in lED *** varied the Al composition in the EBl from 0.84 to 0.96 molar fraction to assess its theoretical effects on electroluminescence,carrier concentration,and electric field,using SIlVAcO *** results from this study highlight the importance and capability of producing high-quality Mg-doped p-AlInN layers through *** simulations suggest that an Al content of 0.86 is optimal for achieving desired outcomes in electroluminescence,carrier concentration,and electric field.

关键词： metal-modulated epitaxy AlInN DUV-lED EBl simulation

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Distributed Energy and Reserve Scheduling in local Energy communities Using l-BFGS Optimization

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cSEE Journal of Power and Energy Systems 2024年第3期10卷 942-952页

作者： Mohammad Dolatabadi Alireza Zakariazadeh alberto Borghetti Pierluigi Siano Department of Management&Innovation Systems University of SalernoSalernoItaly Department of Electrical Electronicand Information EngineeringUniversity of BolognaBolognaItaly University of Science and Technology of Mazandaran BehshahrIran Department of Power Systems National University of Science and Technology POLITEHNICA BucharestBucharestRomania IEEE

Encouraging citizens to invest in small-scale renewable resources is crucial for transitioning towards a sustainable and clean energy *** energy communities(lEcs)are expected to play a vital role in this ***,energy scheduling in lEcs presents various challenges,including the preservation of customer privacy,adherence to distribution network constraints,and the management of computational *** paper introduces a novel approach for energy scheduling in renewable-based lEcs using a decentralized optimization *** proposed approach uses the limitedmemory Broyden–Fletcher–Goldfarb–Shanno(l-BFGS)method,significantly reducing the computational effort required for solving the mixed integer programming(MIP)*** incorporates network constraints,evaluates energy losses,and enables community participants to provide ancillary services like a regulation reserve to the grid *** assess its robustness and efficiency,the proposed approach is tested on an 84-bus radial distribution *** indicate that the proposed distributed approach not only matches the accuracy of the corresponding centralized model but also exhibits scalability and preserves participant privacy.

关键词： Distributed optimization flexibility services l-BFGS method local energy community renewables reserve

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Effect of radiative loss mechanisms on FIR thermometric parameters of Nd^(3+)-doped lithium tellurite glasses

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Journal of Rare Earths 2024年第7期42卷 1250-1257,I0002页

作者： c.Y.Morassuti A.P.l Silva l.A.O.Nunes S.M.lima l.H.c.Andrade Optical and Photothermal Spectroscopy Group(GEOF) Center for Studies in Natural Resources(CERNA)State University of Mato Grosso do Sul(UEMS)C.P.351DouradosMSBrazil Renato Archer Information Technology center Dom Pedro I Highway(SP-65)Km 1436-Chácaras Campos dos AmaraisCampinasSPBrazil Institute of Physics of São carlos University of São PauloSão CarlosSPBrazil

Nd^(3+)-doped tellurite glasses are promising materials for thermometers based on the fluorescence intensity ratio(FIR)***,at high Nd^(3+)concentrations,energy transfer(ET)processes such as optical reabsorption and cross-relaxation can affect the Nd^(3+)emission,which has been little explored in the ***,the present work investigated the use of Nd^(3+)-doped tellurite glass(samples doped with Nd^(3+)at 0.2 mol%,0.5 mol%,2.0 mol%,and 4.0 mol%)in fluorescence thermometers,in the temperature range from 299 to 371 *** results indicate a strong dependence of the FIR parameters on the Nd^(3+)concentration,due to changes in the emission band profiles caused by optical reabsorption of the Nd^(3+)emissions and cross-relaxation processes.A decrease of the relative sensitivity of the ratio^(4)F_(5/2)→^(4)I_(9/2)/^(4)F_(3/2)→^(4)I_(9/2)is observed for samples doped with higher amounts of Nd^(3+).The maximum relative sensitivity at 299 K is 3.00%/K,which is the highest value among the reported Nd^(3+)ions.

关键词： Nd^(3+)-doped tellurite glass Fluorescence intensity ratio Optical thermometry Judd-Ofelt Rare earths

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Nonaqueous potassium-ion full-cells:Mapping the progress and identifying missing puzzle pieces

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Journal of Energy chemistry 2024年第6期93卷 384-399,I0010页

作者： Badre larhrib louiza larbi lénaïc Madec Universite de Pau et des Pays de l’Adour E2S UPPACNRSIPREMPauFrance Universitéde Haute-Alsace Institut de Science des Matériaux de Mulhouse(IS2M)CNRS UMR 7361F-68100 MulhouseFrance Universitéde Strasbourg F-67081 StrasbourgFrance Réseau sur le Stockage Electrochimique de l’Energie CNRS FR3459AmiensFrance Institut des Matériaux Jean Rouxel(IMN) CNRS UMR 6502Univ.Nantes44322 Cedex 3 NantesFrance

This review addresses the growing interest for potassium-ion full-cells(KIFcs)in view of the transition from potassium-ion half-cells(KIHcs)toward commercial K-ion batteries(KIBs).It focuses on the key parameters of KIFcs such as the electrode/electrolyte interfaces challenge,major barriers,and recent advancements in *** strategies for enhancing KIFc performance,including interfaces co ntrol,electrolyte optimization,electrodes capacity ratio,electrode material screening and electrode design,are *** review highlights the need to evaluate KIBs in full-cell configurations as half-cell results are strongly impacted by the K metal *** also emphasizes the importance of understanding solid electrolyte interphase(SEI)formation in KIFcs and explores promising nonaqueous as well as quasiand all-solid-state electrolytes *** review thus paves the way for practical,cost-effective,and scalable KIBs as energy storage systems by offering insights and guidance for future research.

关键词： K-ion full-cells Potassium-ion batteries cross-talk Solid-state batteries Potassium reactivity Electrolyte design Electrode design

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Molecular and cellular mechanisms of neuroprotection by oligopeptides from snake venoms

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BIOcEll 2024年第6期48卷 897-904页

作者： cARlOS alberto-SIlVA BRENDA RUFINO DA SIlVA Natural and Humanities Sciences center Experimental Morphophysiology LaboratoryFederal University of ABC(UFABC)São Bernardo do CampoSão PauloBrazil

Venom snake-derived peptides have multiple biochemical,pharmacological,and toxicological proﬁles,allowing for the discovery of new medicinal products and therapeutic *** review speciﬁcally examines the fundamental elements of neuroprotection offered by different oligopeptides derived from snake *** also includes a brief evaluation of short peptides that are being considered as potential therapeutic ***-rich peptides and tryptophyllin family peptides isolated from the crude venom of Viperidae family snakes,speciﬁcally Bothrops atrox,Bothrops jararaca,and Bothrops moojeni,have been shown to have pro-survival properties,the ability to reduce oxidative stress,and the ability to promote cell viability and mitochondrial *** signiﬁcant mechanisms are related to the neuroprotection mediated by snake venom oligopeptides:(1)Activation of the l-arginine metabolite pathway,such as polyamines from ornithine metabolism,which reduces N-methyl-D-aspartate(NMDA)-type glutamate receptor activity;(2)Enhancement of cell viability by activating the nerve growth factor-signaling pathway;and(3)Activation of the Muscarinic acetylcholine receptor subtype M1(mAchR-M1).These small peptides show promise as neuroprotective agents against a variety of neurodegenerative disorders.

关键词： Neuroprotective peptides Neurodegenerative disease Oxidative stress Reactive oxygen species Biopeptides

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A Tutorial on Federated learning from Theory to Practice:Foundations,Software Frameworks,Exemplary Use cases,and Selected Trends

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IEEE/cAA Journal of Automatica Sinica 2024年第4期11卷 824-850页

作者： M.Victoria luzón Nuria Rodríguez-Barroso alberto Argente-Garrido Daniel Jiménez-lópez Jose M.Moyano Javier Del Ser Weiping Ding Francisco Herrera Department of Software Engineering Andalusian Research Institute in Data Science and Computational Intelligence(DaSCI)University of GranadaGranada 18071Spain Department of computer Science and Artificial Intelligence Andalusian Research Institute in Data Science and Computational Intelligence(DaSCI)University of GranadaGranada 18071Spain Department of communications Engineering University of the Basque Country(UPV/EHU)and also with TECNALIABasque Research&Technology Alliance(BRTA)Spain School of Information Science and Technology Nantong UniversityNantong 226019China

When data privacy is imposed as a necessity,Federated learning(Fl)emerges as a relevant artificial intelligence field for developing machine learning(Ml)models in a distributed and decentralized *** allows Ml models to be trained on local devices without any need for centralized data transfer,thereby reducing both the exposure of sensitive data and the possibility of data interception by malicious third *** paradigm has gained momentum in the last few years,spurred by the plethora of real-world applications that have leveraged its ability to improve the efficiency of distributed learning and to accommodate numerous participants with their data *** virtue of Fl,models can be learned from all such distributed data sources while preserving data *** aim of this paper is to provide a practical tutorial on Fl,including a short methodology and a systematic analysis of existing software ***,our tutorial provides exemplary cases of study from three complementary perspectives:i)Foundations of Fl,describing the main components of Fl,from key elements to Fl categories;ii)Implementation guidelines and exemplary cases of study,by systematically examining the functionalities provided by existing software frameworks for Fl deployment,devising a methodology to design a Fl scenario,and providing exemplary cases of study with source code for different Ml approaches;and iii)Trends,shortly reviewing a non-exhaustive list of research directions that are under active investigation in the current Fl *** ultimate purpose of this work is to establish itself as a referential work for researchers,developers,and data scientists willing to explore the capabilities of Fl in practical applications.

关键词： Data privacy distributed machine learning federated learning software frameworks

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Performance of evolutionary optimized machine learning for modeling total organic carbon in core samples of shale gas fields

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Petroleum 2024年第1期10卷 150-164页

作者： leonardo Goliatt c.M.Saporetti l.c.Oliveira E.Pereira Department of computational and Applied Mechanics Federal University of Juiz de Fora Department of computational Modeling Polytechnic Institute Rio de Janeiro State University Petrobras Department of Stratigraphy and Paleontology Rio de Janeiro State University

Rock samples' TOc content is the best indicator of the organic matter in source rocks. The origin rock samples' analysis is used to calculate it manually by specialists. This method requires time and resources because it relies on samples from many well intervals in source rocks. Therefore, research has been done to aid this effort. Machine learning algorithms can estimate total organic carbon instead of well logs and stratigraphic studies. In light of these efforts, the current work present a study on automating the total organic carbon estimation using machine learning approaches improved by an evolutionary methodology to give the model flexibility and precision. Genetic algorithms, differential evolution, particle swarm optimization, grey wolf optimization, artificial bee colony, and evolution strategies were used to improve machine learning models to predict TOc. The six metaheuristics were integrated into four machine learning methods: extreme learning machine, elastic net linear model, linear support vector regression, and multivariate adaptive regression splines. core samples from the YuDong-Nan shale gas field, located in the Sichuan basin, were used to evaluate the hybrid strategy. The findings show that combining machine learning models with an evolutionary algorithms in a hybrid fashion produce flexible models that accurately predict TOc. The results show that, independent of the metaheuristic used to guide the model selection, optimized extreme learning machines attained the best performance scores according to six metrics. Such hybrid models can be used in exploratory geological research,particularly for unconventional oil and gas resources.

关键词： Total organic carbon Hybrid models Automated machine learning Evolutionary algorithms Geology

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