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Hepatobiliary & Pancreatic Diseases International 2024年第2期23卷 146-153页

作者： Philip c.muller matthias Pfister Dilmurodjon Eshmuminov Kuno Lehmann Department of Surgery and Transplantation University Hospital ZurichRämistrasse 100Zurich CH-8091Switzerland

Background:Liver transplantation(LT)for neuroendocrine liver metastases(NELm)is still in *** c.mparing LT with liver resection(LR)for NELm are scarce,as patient selection is heterogeneous and experience is *** goal of this review was to provide a critical analysis of the evidence on LT versus LR in the treatment of *** sources:A scoping literature search on LT and LR for NELm was performed with Pubmed,including English articles up to march ***:International guidelines rec.mmend LR for NELm in resectable,well-differentiated tumors in the absence of extrahepatic.metastatic disease with superior results of LR c.mpared to systemic or liver-directed *** liver surgery has extended resectability criteria whilst entailing increased perioperative risk and short disease-free *** highly selected patients(based on the milan criteria)with unresectable NELm,oncologic results of LT are *** factors include tumor biology(G1/G2)and burden,waiting time for LT,patient age and extrahepatic *** on low-level evi-dence,LT for low-grade NELm within the milan criteria resulted in improved disease-free survival and overall survival c.mpared to *** benefits of LT were lost in patients beyond the milan ***:With adherence to strict selection criteria especially tumor biology,LT for NELm is bec.ming a valuable option providing oncologic benefits c.mpared to *** evidence suggests even stricter selection criteria with regard to tumor biology.

关键词： Liver transplantation Neuroendocrine liver metastases Liver resection Selection criteria Tumor biology

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脑动静脉畸形的7T非增强mR成像

国际医学放射学杂志 2016年第3期 326-327页

作者： K.H.Wrede P.Dammann S.Johst c.mnninghoff m.Schlamann S.maderwald 李志鹏 Erwin L.Hahn Institute for magnetic Resonance Imaging University Duisburg-Essen

摘要目的前瞻性评估7 T mR时间飞跃(TOF)mRA和7 T非对比增强磁化准备快速梯度回波(mPRAGE)对颅内动静脉畸形(AVm)显示,并与1.5 T TOF mRA以及DSA做对比分析。方法招募20例具有单个或者多个AVm的病人,研究方案包括7 T和1.5 T的TOF mRA,以... 详细信息

摘要目的前瞻性评估7 T mR时间飞跃(TOF)mRA和7 T非对比增强磁化准备快速梯度回波(mPRAGE)对颅内动静脉畸形(AVm)显示,并与1.5 T TOF mRA以及DSA做对比分析。方法招募20例具有单个或者多个AVm的病人,研究方案包括7 T和1.5 T的TOF mRA,以及7 T的非对比增强mPRAGE序列,另外所有的病人都进行了4支血管的3D DSA检查。由2名放射科医生使用5点量表分析AVm以下

关键词： mRA 对比增强 TOF AVm mR

consumer transparency in the production chain for plant varieties produced using new genomic techniques

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aBIOTEcH 2024年第2期5卷 239-246页

作者： J.m.Lukasiewicz c.c.m.van de Wiel L.A.P.Lotz m.J.m.Smulders Wageningen University&Research P.O.Box 386NL-6700 AJ WageningenThe Netherlands

Plants edited with new genomic techniques(NGTs)currently fall under the Genetically modified Organisms Directive(2001/18/Ec)in the European *** the proposal of the European c.mmission,NGT plants are partially exempted from the regulations of this *** proposal makes a distinction between two categories of NGT plants:NGT-1 and ***-1 category plants are considered equal to plants obtained through conventional breeding *** plants will not be labelled for the consumer,although they will be labelled as ***-2 category plants may be labelled with additional information as a positive *** of seeds of varieties made with gene editing,but not the products,would mean that most steps in the production chain are transparent,but not the last step towards ***“right to know”and increasing knowledge of gene-edited food is a c.mmon theme in food labelling towards ***,we describe current labelling regimes and registers and how these may be applied to provide transparency on gene-edited products to ***,we also look into consumer studies,which indicate a greater acceptance of gene-edited food among consumers,especially when additional benefits such as sustainability are mentioned.

关键词： Labelling New genomic techniques consumer transparency Plant products

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 c.mputational and Applied mechanics Federal University of Juiz de ForaJuiz de ForaBrazil Department of c.mputational modeling Polytechnic InstituteRio de Janeiro State UniversityNova FriburgoBrazil Petrobras Rio de JaneiroBrazil Department of Stratigraphy and Paleontology Rio de Janeiro State UniversityRio de JaneiroBrazil

Rock samples'TOc content is the best indicator of the organic.matter in source *** origin rock samples’analysis is used to calculate it manually by *** method requires time and resources because it relies on samples from many well intervals in source ***,research has been done to aid this *** learning algorithms can estimate total organic carbon instead of well logs and stratigraphic *** 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 *** algorithms,differential evolution,particle swarm optimization,grey wolf optimization,artificial bee colony,and evolution strategies were used to improve machine learning models to predict *** six metaheuristics were integrated into four machine learning methods:extreme learning machine,elastic net linear model,linear support vector regression,and multivariate adaptive regression *** samples from the YuDong-Nan shale gas field,located in the Sichuan basin,were used to evaluate the hybrid *** findings show that c.mbining machine learning models with an evolutionary algorithms in a hybrid fashion produce flexible models that accurately predict *** 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 *** 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

Single atom cu-N-c catalysts for the electro-reduction of cO_(2) to cO assessed by rotating ring-disc electrode

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Journal of Energy chemistry 2024年第1期88卷 169-182,I0004页

作者： S.Pérez-Rodríguez m.Gutiérrez-Roa c.Giménez-Rubio D.Ríos-Ruiz P.Arévalo-cid m.V.martínez-Huerta A.Zitolo m.J.Lázaro D.Sebastián Instituto de carboquímica(cSIc) Miguel Luesma Castán 450018 ZaragozaSpain Instituto de catálisis y Petroleoquímica(cSIc) Marie Curie 228049 MadridSpain Synchrotron SOLEIL L’Orme des MerisiersDépartementale 12891190France

The electrochemical cO_(2) reduction reaction(cO_(2)RR) to controllable chemicals is considered as a promising pathway to store intermittent renewable energy. Herein, a set of catalysts based on copper-nitrogendoped carbon xerogel(cu-N-c) are successfully developed varying the copper amount and the nature of the copper precursor, for the efficient cO_(2)RR. The electrocatalytic performance of cu-N-c.materials is assessed by a rotating ring-disc electrode(RRDE), technique still rarely explored for cO_(2)RR. For c.mparison, products are also characterized by online gas chromatography in a H-cell. The as-synthesized cu-Nc catalysts are found to be active and highly cO selective at low overpotentials(from -0.6 to -0.8 V ***) in 0.1 m KHcO_(3), while H_(2) from the c.mpetitive water reduction appears at larger overpotentials(-0.9 V vs. RHE). The optimum copper acetate-derived catalyst containing cu-N_(4) moieties exhibits a cO_(2)-to-cO turnover frequency of 997 h^(-1) at -0.9 V vs. RHE with a H_(2)/cO ratio of 1.8. These results demonstrate that RRDE configuration can be used as a feasible approach for identifying electrolysis products from cO_(2)RR.

关键词： cu-N-c carbon xerogel Rotating ring disc electrode carbon dioxide reduction reaction carbon monoxide

Important step towards an understanding of the exotic Z_(c)(3900)

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Science china(Physics,mechanics & Astronomy) 2024年第9期67卷 199-200页

作者： c.Hanhart Institute for Advanced Simulation Forschungszentrum JulichJilich D-52425Germany

The Standard model of particle physics,which contains the field theories for the electro-weak interaction(QED)and the strong interaction(QcD),is an extremely successful theory describing a huge variety of phenomena at... 详细信息

关键词： interaction atomic describing

An improved pulse coupled neural networks model for semantic IoT

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Digital c.mmunications and Networks 2024年第3期10卷 557-567页

作者： Rong ma Zhen Zhang Yide ma Xiping Hu Edith c.H.Ngai Victor c.m.Leung School of Information Science and Engineering Lanzhou UniversityLanzhou 730000China School of medical Technology Beijing Institute of TechnologyBeijing100081China Department of Electrical and Electronic Engineer The University of Hong KongHong Kong 999077China college of c.mputer Science and Software Engineering Shenzhen UniversityShenzhen 518060China Department of Electrical and c.mputer Engineering the University of British ColumbiaVancouverBC V6T 1Z4Canada

In recent years,the Internet of Things(IoT)has gradually developed applications such as collecting sensory data and building intelligent services,which has led to an explosion in mobile data ***,with the rapid development of artificial intelligence,semantic c.mmunication has attracted great attention as a new c.mmunication ***,for IoT devices,however,processing image information efficiently in real time is an essential task for the rapid transmission of semantic *** the increase of model parameters in deep learning methods,the model inference time in sensor devices continues to *** contrast,the Pulse coupled Neural Network(PcNN)has fewer parameters,making it more suitable for processing real-time scene tasks such as image segmentation,which lays the foundation for real-time,effective,and accurate image ***,the parameters of PcNN are determined by trial and error,which limits its *** overc.me this limitation,an Improved Pulse coupled Neural Networks(IPcNN)model is proposed in this *** IPcNN constructs the connection between the static properties of the input image and the dynamic properties of the neurons,and all its parameters are set adaptively,which avoids the inconvenience of manual setting in traditional methods and improves the adaptability of parameters to different types of *** segmentation results demonstrate the validity and efficiency of the proposed self-adaptive parameter setting method of IPcNN on the gray images and natural images from the matlab and Berkeley Segmentation *** IPcNN method achieves a better segmentation result without training,providing a new solution for the real-time transmission of image semantic information.

关键词： Internet of things(IoT) Semantic information Real-time application Improved pulse coupled neural network Image segmentation

Semi-analytical investigation of heat transfer in a porous convective radiative moving longitudinal fin exposed to magnetic field in the presence of a shape-dependent trihybrid nanofluid

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Applied mathematics and mechanics(English Edition) 2024年第1期45卷 197-216页

作者： c.G.PAVITHRA B.J.GIREESHA m.L.KEERTHI Department of PG Studies and Research in mathematics Kuvempu UniversityShankaraghatta 577451India Department of mathematics and Statistics M.S.Ramaiah University of Applied SciencesBengaluru 560058India

The thermal examination of a non-integer-ordered mobile fin with a magnetism in the presence of a trihybrid nanofluid(Fe_3O_4-Au-Zn-blood) is carried out. Three types of nanoparticles, each having a different shape, are considered. These shapes include spherical(Fe_3O_4), cylindrical(Au), and platelet(Zn) configurations. The c.mbination approach is utilized to evaluate the physical and thermal characteristics of the trihybrid and hybrid nanofluids, excluding the thermal conductivity and dynamic viscosity. These two properties are inferred by means of the interpolation method based on the volume fraction of nanoparticles. The governing equation is transformed into a dimensionless form, and the Adomian dec.mposition Sumudu transform method(ADSTm) is adopted to solve the conundrum of a moving fin immersed in a trihybrid nanofluid. The obtained results agree well with those numerical simulation results, indicating that this research is reliable. The influence of diverse factors on the thermal overview for varying noninteger values of γ is analyzed and presented in graphical representations. Furthermore, the fluctuations in the heat transfer concerning the pertinent parameters are studied. The results show that the heat flux in the presence of the c.mbination of spherical, cylindrical, and platelet nanoparticles is higher than that in the presence of the c.mbination of only spherical and cylindrical nanoparticles. The temperature at the fin tip increases by 0.705 759% when the value of the Peclet number increases by 400%, while decreases by 11.825 13% when the value of the Hartman number increases by 400%.

关键词： convection radiation moving longitudinal fin Adomian dec.mposition Sumudu transform method(ADSTm) trihybrid nanofluid magnetic field

Optimization of a photovoltaic-battery system using deep reinforc.ment learning and load forecasting

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Energy and AI 2024年第2期16卷 168-183页

作者： António corte Real G.Pontes Luz J.m.c.Sousa m.c.Brito S.m.Vieira IDmEc Instituto Superior TécnicoUniversidade de LisboaLisboa1049-001Portugal Instituto Dom Luiz Faculdade de CiênciasUniversidade de LisboaCampo Grande1749-016LisboaPortugal

Home Energy management Systems(HEmS)are increasingly relevant for demand-side management at the residential level by collecting data(energy,weather,electricity prices)and controlling home appliances or storage *** control can be performed with classical models that find optimal solutions,with high real-time c.mputational cost,or data-driven approaches,like Reinforc.ment Learning,that find good and flexible solutions,but depend on the availability of load and generation data and demand high c.mputational resources for *** this work,a novel HEmS is proposed for the optimization of an electric battery operation in a real,online and data-driven environment that integrates state-of-the-art load forecasting c.mbining cNN and LSTm neural networks to increase the robustness of *** Reinforc.ment Learning agents are trained with different algorithms(Double DQN,Dueling DQN,Rainbow and Proximal Policy Optimization)in order to minimize the cost of electricity purchase and to maximize photovoltaic self-consumption for a PV-Battery residential *** show that the best Reinforc.ment Learning agent achieves a 35%reduction in total cost when c.mpared with an optimization-based agent.

关键词： Energy management system Deep reinforc.ment learning Demand-side management Load forecasting Deep learning Energy storage systems

cO oxidation under lean and stoichiometric conditions over ceriazirconia with very low metal contents(cu,co,Ag and Pt)

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Journal of Rare Earths 2024年第9期42卷 1669-1681,I0002页

作者： J.c.martínez-munuera m.P.Yeste A.García-García mcmA Group Department of Inorganic Chemistry and Institute of MaterialsUniversity of AlicanteCarretera de San Vicente del Raspeig s/n03690San Vicente del RaspeigAlicanteSpain Solid chemistry and catalysis Group Department of Materials ScienceMetallurgic Engineering and Inorganic ChemistryInstitute of Electronic Microscopy and Materials ResearchUniversity of CádizAp.40E-11510Puerto RealCádizSpain

In this work,several ceria-zirconia based catalysts with very lo w(and equimolar) metal contents were prepared,characterised and tested for the cO oxidatio n reaction(under lean and stoichiometric conditions),trying to emulate those conditions found in a diesel oxidation catalyst(DOc) system from a diesel engine and those encountered under gasoline exhaust(λ=1).The metals chosen are cu,co,Ag and Pt(as a reliable benc.mark).The results reveal enormous differences among reducibility and catalytic activity despite quite similar structural and textural properties of the catalysts,showing differences among dispersion(Ag-catalyst seems to present a low level of dispersion).This catalyst seems to be characterised,as well,by a strong electronic interaction between ce and Ag centres which is suggested to yield an improved reducibility under H_(2)-TPR ***,the order in catalytic activity(cu>Ag>co≈Pt>>support) seems not to follow the order found in reducibility and the cu-catalyst seems to be the most active independently on the reaction conditions,yielding nearly overlapped cO oxidation catalytic *** restingly,a stro ng correlation between the catalytic activity under the two conditions tested and the OSc values of the ce_(0.8)Zr_(0.2)O_(2)-supported metal catalysts is ***,OSc parameter measured at 150℃ can be used as a relevant descriptor to evaluate the cO oxidation activity at low and medium conversions for the investigated catalysts,much better than the H_(2)-TPR measurements.

关键词： cO oxidation Low metal content ceria-zirconia copper species OSc parameter Rare earths