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Arterial thrombosis in the context of HCV-associated vascular disease can be prevented by protein C

Cellular & molecular Immunology 2017年第12期14卷 986-996页

作者： philipp blüm Joachim Pircher monika merkle Thomas Czermak Andrea Ribeiro Hanna mannell Florian Krötz Alexander Hennrich michael Spannagl Simone Köppel Erik Gaitzsch markus Wörnle medizinische Klinik und Poliklinik IV InnenstadtKlinikum der Universität München80336 MünchenGermany Walter Brendel Centre of Experimental medicine and munich Heart Alliance Ludwig Maximilians University München80336 MünchenGermany medizinische Klinik und Poliklinik I Klinikum der Universität München80336 MünchenGermany Abteilung für Transfusionsmedizin Zelltherapeutika und HämostaseologieKlinikum der Universität München80336 MünchenGermany

Hepatitis C virus(HCV)infection is a major problem *** is not limited to liver disease but is frequently complicated by immune-mediated extrahepatic manifestations such as glomerulonephritis or vasculitis.A fatal complication of HCV-associated vascular disease is ***:polyribocytidylic acid(poly(I:C)),a synthetic analog of viral RNA,induces a Toll-like receptor 3(TLR3)-dependent arteriolar thrombosis without significant thrombus formation in venules in *** procoagulant effects are caused by increased endothelial synthesis of tissue factor and PAI-1 without platelet *** addition to human umbilical endothelial cells(HUVEC),human mesangial cells(HmC)produce procoagulatory factors,cytokines and adhesion molecules after stimulation with poly(I:C)or HCV-containing cryoprecipitates from a patient with a HCV infection as *** protein C(APC)is able to prevent the induction of procoagulatory factors in HUVEC and HmC in vitro and blocks the effects of poly(I:C)and HCV-RNA on the expression of cytokines and adhesion molecules in HmC but not in *** vivo,protein C inhibits poly(I:C)-induced arteriolar ***,endothelial cells are de facto able to actively participate in immune-mediated vascular thrombosis caused by viral ***,we provide evidence for the ability of protein C to inhibit TLR3-mediated arteriolar thrombosis caused by HCV infection.

关键词： hepatitis C thrombosis toll-like receptor 3

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Energy Disaggregation of Industrial machinery Utilizing Artificial Neural Networks for Non-intrusive Load monitoring

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Energy and AI 2024年第3期17卷 342-356页

作者： philipp Pelger Johannes Steinleitner Alexander Sauer Fraunhofer Institute for manufacturing Engineering and Automation IPA Stuttgart 70569Germany Institute for Energy Efficiency in Production(EEP) University of StuttgartStuttgart 70569Germany

This paper explores the application of non-intrusive load monitoring techniques in the industrial sector for disaggregating the energy consumption of machinery in manufacturing processes. With an increasing focus on energy efficiency and decarbonization measures, achieving energy transparency in production becomes crucial. Utilizing non-intrusive load monitoring, energy data analysis and processing can provide valuable insights for informed decision-making on energy efficiency improvements and emission reductions. While non-intrusive load monitoring has been extensively researched in the building and residential sectors, the application in the industrial manufacturing domain needs to be further explored. This paper addresses this research gap by adapting established non-intrusive load monitoring techniques to an industrial dataset. By employing artificial neural networks for energy disaggregation, the determination of energy consumption of industrial machinery is made possible. Therefore, a generally applicable cross-energy carrier method to disaggregate the energy consumption of machinery in manufacturing processes is developed using a design science research approach and validated through a practical case study utilizing a compressed air demonstrator. The results show that the utilization of artificial neural networks is well-suited for energy disaggregation of industrial data, effectively identifying on and off states, multi-level states and continuously variable states. Non-intrusive load monitoring should be further considered in the research of emerging artificial intelligence technologies in energy consumption evaluation. It can be a viable alternative for intrusive load monitoring and is a prerequisite to installing energy meters for every machine.

关键词： Non-intrusive load monitoring Energy transparency Energy consumption evaluation Industrial manufacturing Artificial neural networks

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molecular insights of exercise therapy in disease prevention and treatment

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Signal Transduction and Targeted Therapy 2024年第6期9卷 2564-2597页

作者： David Walzik Tiffany Y.Wences Chirino philipp Zimmer Niklas Joisten Division of Performance and Health(Sports medicine) Institute for Sport and Sport ScienceTU Dortmund University44227 DortmundNorth Rhine-WestphaliaGermany Division of Exercise and movement Science Institute for Sport ScienceUniversity of Göttingen37075 GöttingenLower SaxonyGermany

Despite substantial evidence emphasizing the pleiotropic benefits of exercise for the prevention and treatment of various diseases,the underlying biological mechanisms have not been fully *** exercise benefits have been attributed to signaling molecules that are released in response to exercise by different tissues such as skeletal muscle,cardiac muscle,adipose,and liver *** signaling molecules,which are collectively termed exerkines,form a heterogenous group of bioactive substances,mediating inter-organ crosstalk as well as structural and functional tissue *** scientific endeavors have focused on identifying and characterizing new biological mediators with such ***,some investigations have focused on the molecular targets of exerkines and the cellular signaling cascades that trigger adaption processes.A detailed understanding of the tissue-specific downstream effects of exerkines is crucial to harness the health-related benefits mediated by exercise and improve targeted exercise programs in health and ***,we review the current in vivo evidence on exerkine-induced signal transduction across multiple target tissues and highlight the preventive and therapeutic value of exerkine signaling in various *** emphasizing different aspects of exerkine research,we provide a comprehensive overview of(i)the molecular underpinnings of exerkine secretion,(ii)the receptor-dependent and receptor-independent signaling cascades mediating tissue adaption,and(iii)the clinical implications of these mechanisms in disease prevention and treatment.

关键词： prevention treatment collective

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The whole and its parts: Visualizing Gaussian mixture models

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Visual Informatics 2024年第2期8卷 67-79页

作者： Joachim Giesen philipp Lucas Linda Pfeiffer Laines Schmalwasser Kai Lawonn Friedrich-Schiller-University Jena Germany German Aerospace Center DLR-Institute of Data Science Jena Germany

Gaussian mixture models are classical but still popular machine learning *** appealing feature of Gaussian mixture models is their tractability,that is,they can be learned efficiently and exactly from data,and also support efficient exact inference queries like soft clustering data *** seemingly simple,Gaussian mixture models can be hard to *** are at least four aspects to understanding Gaussian mixture models,namely,understanding the whole distribution,its individual parts(mixture components),the relationships between the parts,and the interplay of the whole and its *** a structured literature review of applications of Gaussian mixture models,we found the need for supporting all four *** identify candidate visualizations that effectively aid the user needs,we structure the available design space along three different representations of Gaussian mixture models,namely as functions,sets of parameters,and sampling *** the design space,we implemented three design concepts that visualize the overall distribution together with its ***,we assessed the practical usefulness of the design concepts with respect to the different user needs in expert interviews and an insight-based user study.

关键词： Gaussian mixture models

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Transfer learning from synthetic data for open-circuit voltage curve reconstruction and state of health estimation of lithium-ion batteries from partial charging segments

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Energy and AI 2024年第3期17卷 80-97页

作者： Tobias Hofmann Jacob Hamar Bastian mager Simon Erhard Jan philipp Schmidt Chair of Systems Engineering for Electrical Energy Storage University of BayreuthWeiherstraße 26Bayreuth95448BavariaGermany BmW Group Petuelring 130Munich80809BavariaGermany

Data-driven models for battery state estimation require extensive experimental training data,which may not be available or suitable for specific tasks like open-circuit voltage(OCV)reconstruction and subsequent state of health(SOH)*** study addresses this issue by developing a transfer-learning-based OCV reconstruction model using a temporal convolutional long short-term memory(TCN-LSTm)network trained on synthetic data from an automotive nickel cobalt aluminium oxide(NCA)cell generated through a mechanistic model *** data consists of voltage curves at constant temperature,C-rates between C/30 to 1C,and a SOH-range from 70%to 100%.The model is refined via Bayesian optimization and then applied to four use cases with reduced experimental nickel manganese cobalt oxide(NmC)cell training data for higher use *** TL models’performances are compared with models trained solely on experimental data,focusing on different C-rates and voltage *** results demonstrate that the OCV reconstruction mean absolute error(mAE)within the average battery electric vehicle(BEV)home charging window(30%to 85%state of charge(SOC))is less than 22 mV for the first three use cases across all *** SOH estimated from the reconstructed OCV exhibits an mean absolute percentage error(mAPE)below 2.2%for these *** study further investigates the impact of the source domain on TL by incorporating two additional synthetic datasets,a lithium iron phosphate(LFP)cell and an entirely artificial,non-existing,cell,showing that solely the shifting and scaling of gradient changes in the charging curve suffice to transfer knowledge,even between different cell chemistries.A key limitation with respect to extrapolation capability is identified and evidenced in our fourth use case,where the absence of such comprehensive data hindered the TL process.

关键词： Lithium-ion battery State of health estimation Transfer learning OCV curve Partial charging Synthetic data

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Routine utilization of machine perfusion in liver transplantation:Ready for prime time?

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World Journal of Gastroenterology 2024年第11期30卷 1488-1493页

作者： Alessandro Parente Keyue Sun philipp Dutkowski Am James Shapiro Andrea Schlegel Department of Surgery Division of TransplantationUniversity of Alberta HospitalEdmonton T6G 2B7Canada Immunity and Inflammation Lerner Research InstituteClevelandOH 44195United States Swiss Hepato-Pancreato-Biliary Center Department of Visceral and Transplantation SurgeryUniversity Hospital ZurichZurich 8091Switzerland Immunity and Inflammation Digestive Disease and Surgery InstituteClevelandOH 44195United States

The last decade has been notable for increasing high-quality research and dramatic improvement in outcomes with dynamic liver *** evidence from numerous randomized controlled trials has been pooled by meta-analyses,providing the highest available evidence on the protective effect of machine perfusion(mP)over static cold storage in liver transplantation(LT).Based on a protective effect with less complications and improved graft survival,the field has seen a paradigm shift in organ *** editorial focuses on the role of mP in LT and how it could become the new“gold standard”.Strong collaborative efforts are needed to explore its effects on long-term outcomes.

关键词： Liver transplantation machine perfusion Viability assessment Hypothermic oxygenated perfusion Normothermic machine perfusion

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Impact of exercise on markers of B cell-related immunity:A systematic review

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Journal of Sport and Health Science 2024年第3期13卷 339-352,I0002页

作者： David Walzik Sergen Belen Karen Wilisch marie Kupjetz Silvana Kirschke Tobias Esser Niklas Joisten Alexander Schenk Sebastian Proschinger philipp Zimmer Division of Performance and Health(Sports medicine) Institute for Sport and Sport ScienceTU Dortmund UniversityDortmund 44227Germany

Background:B cells represent a crucial component of adaptive immunity that ensures long-term protection from infection by generating pathogen-specific *** alters B cell counts and immunoglobulin levels,but evidence-based conclusions on potential benefits for adaptive immunity are *** systematic review assessed current literatures on the impact of acute exercise and exercise training on B cells,immunoglobulins,and markers of secretory immunity in human ***:According to the Preferred Reporting Items for Systematic Reviews and meta-Analyses(PRISmA)guidelines,mEDLINE,Web of Science,and Embase were searched on march 8,***-randomized controlled trials and crossover trials investigating the impact of acute exercise or exercise training on B cell counts and proportions,immunoglobulin levels,salivary flow rate,or secretory immunoglobulin A secretion rate were *** and reporting of exercise training studies were assessed using the Tool for the Assessment of Study Quality and reporting in *** characteristics,outcome measures,and statistically significant changes were summarized ***:Of the 67 eligible studies,22 applied acute exercise and 45 applied exercise *** included outcomes revealed significant alterations over time in acute exercise and exercise training context,but only a few investigations showed significant differences compared to control *** and plasma immunoglobulin A levels were most consistently increased in response to exercise ***:B cell-related outcomes are altered by acute exercise and exercise training,but evidence-based conclusions cannot be drawn with high confidence due to the large heterogeneity in populations and exercise ***-designed trials with large sample sizes are needed to clarify how exercise shapes B cell-related immunity.

关键词： Antibody B-lymphocyte Exercise Humoral immunity Immune system

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Key technologies for wireless network digital twin towards smart railways

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High-Speed Railway 2024年第1期2卷 1-10页

作者： Ke Guan Xinghai Guo Danping He philipp Svoboda marion Berbineau Stephen Wang Bo Ai Zhangdui Zhong markus Rupp State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong UniversityBeijing 100044China School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing 100044China Christian Doppler Laboratory for Digital Twin Assisted AI for Sustainable Radio Access Networks Institute of TelecommunicationsTU WienVienna 1040Austria UniversitéGustave Eiffel COSYSLEOSTVilleneuve d′Ascq 59650France VIAVI marconi Labs VIAVI SolutionsStevenage SG12ANUK Institute of Telecommunications TU WienVienna 1040Austria

An emerging railway technology called smart railway promises to deliver higher transportation efficiency,enhanced comfort in services,and greater *** smart railway is expected to integrate fifth-generation mobile communication(5G),Artificial Intelligence(AI),and other technologies,which poses new problems in the construction,operation and maintenance of railway wireless *** Digital Twins(DTs),which have recently emerged as a new paradigm for the design of wireless networks,can address these problems and enable the whole lifecycle management of railway wireless ***,there are still many scientific issues and challenges for railway-oriented wireless *** key technologies to solve these problems are introduced and described,including characterization of materials'physical-Em properties,autonomous reconstruction of Three-dimensional(3D)environment model,AI-empowered environmental cognition,Ray-Tracing(RT),model-based and AIbased RT acceleration,and generation of multi-spectra sensing ***,this paper presents our research results for each key technology and describes the wireless network planning and optimization system based on highperformance RT developed by our *** paper outlines the framework for realizing the wireless DT of smart railways,providing the direction for future research.

关键词： Digital twin Smart railways Ray tracing Channel characterization

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Improved training framework in a neural network model for disruption prediction and its application on EXL-50

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Plasma Science and Technology 2024年第5期26卷 29-39页

作者：蔡剑青梁云峰 Alexander KNIEPS 齐东凯王二辉向皓明廖亮黄杰阳杰黄佳刘建文 philipp DREWS 徐帅顾翔高轶琛罗宇李直 the EXL-50 Team Institute of Plasma Physics Chinese Academy of SciencesHefei 230031People’s Republic of China Forschungszentrum Jülich GmbH Institut für Energie-und Klimaforschung-PlasmaphysikPartner of the Trilateral Cluster(TEC)Jülich 52425Germany ENN Science and Technology Development Co. LtdLangfang 065001People’s Republic of China

A neural network model with a classical annotation method has been used on the EXL-50tokamak to predict impending ***,the results revealed issues of overfitting and overconfidence in predictions caused by inaccurate *** mitigate these issues,an improved training framework has been *** this approach,soft labels from previous training serve as teachers to supervise the further learning process;this has lead to a significant improvement in predictive model ***,this enhancement is primarily attributed to the coupling effect of the soft labels and correction *** improved training framework introduces an instance-specific label smoothing method,which reflects a more nuanced model assessment on the likelihood of a *** presents a possible solution to effectively address the challenges associated with accurate labeling across different machines.

关键词： neural network disruption soft label EXL-50 tokamak

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The AiiDA-KKR plugin and its application to highthroughput impurity embedding into a topological insulator

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npj Computational materials 2021年第1期7卷 108-116页

作者： philipp Rüßmann Fabian Bertoldoand Stefan blügel Peter Grünberg Institut and Institute for Advanced Simulation Forschungszentrum Jülich and JARAD-52425 JülichGermany

The ever increasing availability of supercomputing resources led computer-based materials science into a new era of highthroughput ***,Pizzi et *** the AiiDA framework that provides a way to automate calculations while allowing to store the full provenance of complex workflows in a *** present the development of the AiiDA-KKR plugin that allows to perform a large number of ab initio impurity embedding calculations based on the relativistic full-potential Korringa-Kohn-Rostoker Green function *** capabilities of the AiiDA-KKR plugin are demonstrated with the calculation of several thousand impurities embedded into the prototypical topological insulator *** results are collected in the JuDiT database which we use to investigate chemical trends as well as Fermi level and layer dependence of physical properties of *** includes the study of spin moments,the impurity’s tendency to form in-gap states or its effect on the charge doping of the *** properties depend on the detailed electronic structure of the impurity embedded into the host crystal which highlights the need for ab initio calculations in order to get accurate predictions.

关键词： method topological embedding

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