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The Triple Helix of innovation as a double game involving domestic and foreign actors

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Journal of Data and Information Science 2024年第1期9卷 82-100页

作者： Eustache mêgnigbêto University of Antwerp Antwerpen 2000Belgium

Purpose:The collaboration relationships between innovation actors at a geographic level may be considered as grouping two separate layers,the domestic and the *** the level of each layer,the relationships and the actors involved constitute a Triple Helix *** paper distinguished three levels of analysis:the global grouping together all actors,the domestic grouping together domestic actors,and the foreign related to only actors from partner ***/methodology/approach:Bibliographic records data from the Web of Science for South Korea and West Africa breakdown per innovation actors and distinguishing domestic and international collaboration are analyzed with game *** core,the Shapley value,and the nucleolus are computed at the three levels to measure the synergy between ***:The synergy operates more in South Korea than in West Africa;the government is more present in West Africa than in South Korea;domestic actors create more synergy in South Korea,but foreign more in West Africa;South Korea can consume all the foreign synergy,which is not the case of West *** limitations:Research data are limited to publication records;techniques and methods used may be extended to other research *** implications:West African governments should increase their investment in science,technology,and innovation to benefit more from the synergy their innovation actors contributed at the foreign ***,the results of the current study may not be sufficient to prove that greater investment will yield benefits from foreign ***/value:This paper uses game theory to assess innovation systems by computing the contribution of foreign actors to knowledge production at an area *** proposes an indicator to this end.

关键词： Triple Helix Game theory core Shapley value Nucleolus South Korea West Africa

Parametric investigation on the novel and cost-effective nano fly ash impregnated geopolymer system for sustainable construction

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Frontiers of Structural and Civil Engineering 2024年第2期18卷 170-183页

作者： R.mOHANA S.m.Leela BHARATHI Department of Civil Engineering Mepco Schlenk Engineering CollegeSivakasi 626123India

The hazardous environmental effects of greenhouse gas emissions and climate change demand alternative sources for cementitious materials in the construction *** development of geopolymer structures provides a way of producing 100%cement-free *** this research work,a novel and simple way of deriving nano particles from waste fly ash particles is *** effect of adding the synthesized nano fly ash particles as a filler medium in geopolymer mortars was investigated by considering strength and durability *** optimization was done by using regression analysis on the geopolymer mortar and the impact of adding nano fly ash particles was studied by varying different percentages of addition ranging from 0 to 7.5%by weight of binder *** the results,it was observed that 1%nano fly ash acted not only as a filler but also as nano-sized precursors of the polymerization process,resulting in denser geopolymer *** can explain the extraordinary gain in strength of 72.11 mPa as well as the denser core with negligible level of chloride ion penetration,making the material suitable for the development of structures susceptible to marine environment.

关键词： geopolymer nano fly ash chloride ion penetration durability polymerization fillers

Control and vibration analyses of a sandwich doubly curved micro-composite shell with honeycomb,truss,and corrugated cores based on the fourth-order shear deformation theory

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Applied mathematics and mechanics(English Edition) 2024年第10期45卷 1773-1790页

作者： F.SHIRDELAN m.mOHAmmADImEHR F.BARGOZINI Department of Solid mechanics Faculty of Mechanical EngineeringUniversity of KashanKashan 87317-53153Iran

Curved shells are increasingly utilized in applied engineering due to their shared characteristics with other sandwich structures,flexibility,and attractive ***,the inability of controlling and regulating vibrations and destroying them afterward is a challenge to *** this paper,the curve shell equations and a linear quadratic regulator are adopted for the state feedback design to manage the structure vibrations in state space forms.A five-layer sandwich doubly curved micro-composite shell,comprising two piezoelectric layers for the sensor and actuator,is modeled by the fourth-order shear deformation *** core(honeycomb,truss,and corrugated)is analyzed for the bearing of transverse shear *** results show that the honeycomb core has a greater effect on the *** the parameters related to the core and the weight percentage of graphene increase,the frequency *** uniform distribution of graphene platelets results in the lowest natural frequency while the natural frequency ***,without taking into account the piezoelectric layers,the third-order shear deformation theory(TSDT)and fourth-order shear deformation theory(FOSDT)align ***,when the piezoelectric layers are incorporated,these two theories diverge significantly,with the frequencies in the FOSDT being lower than those in the TSDT.

关键词： vibration and control doubly curved shell micro-composite honeycomb truss corrugate core

An explainable AI framework for robust and transparent data-driven wind turbine power curve models

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Energy and AI 2024年第1期15卷 312-327页

作者： Simon Letzgus Klaus-Robert müller machine Learning Group Technische Universitβe BerlinStraβe des 17.Juni 135Berlin10623Germany Berlin Institute for the Foundations of Learning and Data Berlin10587Germany Department of Artificial Intelligence Korea UniversitySeoul136-713South Korea max Planck Institute for Informatics Saarbrücken66123Germany

In recent years,increasingly complex machine learning methods have become state-of-the-art in modelling wind turbine power curves based on operational *** these methods often exhibit superior performance on test sets,they face criticism due to a perceived lack of transparency and concerns about their robustness in dynamic,non-stationary environments encountered by wind *** this work,we address these issues and present a framework that leverages explainable artificial intelligence methods to gain systematic insights into data-driven power curve *** its core,we propose a metric to quantify how well a learned model strategy aligns with the underlying physical principles of the *** novel tool enables model validation beyond the conventional error metrics in an automated *** demonstrate,for instance,its capacity as an indicator for model generalization even when limited data is ***,it facilitates understanding how decisions made during the machine learning development process,such as data selection,pre-processing,or training parameters,affect learned *** a result,we obtain physically more reasonable models,a prerequisite not only for robustness but also for meaningful insights into turbine operation by domain *** latter,we illustrate in the context of wind turbine performance *** summary,the framework aims to guide researchers and practitioners alike toward a more informed selection and utilization of data-driven wind turbine power curve models.

关键词： Explainable AI(XAI) machine learning Wind energy Wind turbine power curve SCADA Condition monitoring

The gold-telluride connection:Evidence for multiple fluid pulses in the Jinqingding telluride-rich gold deposit of Jiaodong Peninsula,Eastern China

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Geoscience Frontiers 2024年第3期15卷 146-165页

作者： Wenyan Cai mingchun Song m.Santosh Jian Li School of Resources and Environmental Engineering Shandong University of TechnologyZibo 255049China Hebei Key Laboratory of Strategic Critical mineral Resources Hebei GEO UniversityShijiazhuang 050031China School of Earth Sciences and Resources China University of Geosciences Beijing29 Xueyuan RoadBeijing 100083China Department of Earth Science University of AdelaideAdelaide SA 5005Australia

The mechanism of gold migration,enrichment,and precipitation in forming world-class gold deposits has been a topic of wide interest,particularly where these deposits are abundant in *** Jiaodong Peninsula in eastern China hosts some of the world-class gold deposits among which the Jinqingding deposit is one of the best examples with substantial telluride mineralization and thus provides opportunity to investigate the genetic connection between tellurium and gold *** orebody in this deposit is hosted in the NE-NNE-trending Jiangjunshi-Quhezhuang fault with the Jurassic Kunyushan granitic pluton as wall *** deposit involved three mineralization stages as inferred from assemblages and crosscutting relationships between *** stages are:(I)pre-ore gold-poor quartz-pyrite veins,(II)main ore auriferous quartz-pyrite-Te/Bi-minerals±sphalerite±chalcopyrite±barite±marcasite veins,and(III)post-ore quartz-calcite *** present here the textural,isotopic,and geochemical variations of different stages/generations of pyrite based on scanning electron microscopy-energy dispersive spectroscopy(SEm-EDS),electron probe microanalysis(EPmA),and laser ablation inductively coupled plasma mass spectrometry(LA-ICP-mS).Pyrite in the Jinqingding deposit displays distinct ***1a shows a porous and dissolution-reprecipitation texture in the core,whereas Py1b exhibits a smooth and flat *** analysis reveals contrasting elemental compositions,with Py1a characterized by low Au(avg.0.14 ppm),As(avg.15.57 ppm),Ag(avg.17.71 ppm),and Te(avg.19.22 ppm)contents,but elevated Co(avg.1068.10 ppm)and Ni(224.12 ppm)concentrations,and variable sulfur isotopic composition(δ^(34)SV-CDT=9.54‰-12.12‰).Conversely,Py1b displays increased concentrations of these elements and a more concentratedδ^(34)SV-CDT value(11.99‰-12.23‰),possibly associated with weak coupled dissolution-reprecipitation(CDR)*** Stage II,pyrite can be further categorized

关键词： Episodic fluid pulses Sulfur reservoir Gold-Te precipitation Jinqingding deposit Jiaodong Peninsula

Automatic Rule Discovery for Data Transformation Using Fusion of Diversified Feature Formats

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Computers, materials & Continua 2024年第7期80卷 695-713页

作者： G.Sunil Santhosh Kumar m.Rudra Kumar Department of CSE Jawaharlal Nehru Technological UniversityAnantapur515002India Department of CSE Marri Laxman Reddy Institute of Technology and ManagementHyderabad500043India Department of Information Technology Mahatma Gandhi Institute of TechnologyHyderabad500075India

This article presents an innovative approach to automatic rule discovery for data transformation tasks leveraging XGBoost,a machine learning algorithm renowned for its efficiency and *** framework proposed herein utilizes the fusion of diversified feature formats,specifically,metadata,textual,and pattern *** goal is to enhance the system’s ability to discern and generalize transformation rules fromsource to destination formats in varied ***,the article delves into the methodology for extracting these distinct features from raw data and the pre-processing steps undertaken to prepare the data for the *** sections expound on the mechanism of feature optimization using Recursive Feature Elimination(RFE)with linear regression,aiming to retain the most contributive features and eliminate redundant or less significant *** core of the research revolves around the deployment of the XGBoostmodel for training,using the prepared and optimized feature *** article presents a detailed overview of the mathematical model and algorithmic steps behind this ***,the process of rule discovery(prediction phase)by the trained XGBoost model is explained,underscoring its role in real-time,automated data *** employingmachine learning and particularly,the XGBoost model in the context of Business Rule Engine(BRE)data transformation,the article underscores a paradigm shift towardsmore scalable,efficient,and less human-dependent data transformation *** research opens doors for further exploration into automated rule discovery systems and their applications in various sectors.

关键词： XGBoost business rule engine machine learning categorical query language humanitarian computing environment

A novel homozygous missense variant in ARSK causes mPS X,a new subtype of mucopolysaccharidosis

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Genes & Diseases 2024年第3期11卷 87-90页

作者： miao Sun Cornelia K.Kaminsky Philip Deppe mai-Brittllse Frederic m.Vaz Barbara Plecko Torben Lubke Linda m.Randolph Division of Genomic medicine Department of Pathology and Laboratory MedicineChildren's Hospital Los Angeles/Keck School of Medicine of USCLos AngelesCA 90027USA Department of Radiology Children's Hospital Los Angeles/Keck School of Medicine of USCLos AngelesCA 90027USA Department of Chemistry BiochemistryBielefeld UniversityBielefeld 33615Germany Amsterdam UmC Location University of Amsterdam Department of Clinical Chemistry and PediatricsLaboratory Genetic Metabolic DiseasesEmma Children's HospitalMeibergdreef 9Amsterdam 1100 DEthe Netherlands Amsterdam Gastroenterology Endocrinology metabolism Inborn Errors of MetabolismAmsterdam 1105 BKthe Netherlands core Facility metabolomics Amsterdam UMC Location University of AmsterdamAmsterdam 1100DDthe Netherlands Department of Pediatrics Division of General PediatricsMedical Universityof GrazGraz8036Austria Division of medical Genetics Department of PediatricsChildren's Hospital Los Angeles/Keck School of Medicine of USCLos AngelesCA 90027USA

mucopolysaccharidoses(mPS)are a group of rare inborn errors of metabolism caused by defective lysosomal enzymes which prevent cells from degrading and recycling certain carbohydrates and fats,resulting in the storage of glycosaminoglycans in cells throughout the *** leads to multisystem abnormalities involving bone,connective tissues,brain,blood,spinal cord,skin,and other tissues.

关键词： metabolism doses polys

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 ForaJuiz de ForaBrazil Department of Computational 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 combining 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

Improving the operational stability of perovskite solar cells with cesium-doped graphene oxide interlayer

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Journal of Energy Chemistry 2024年第9期96卷 483-490页

作者： masaud Almalki Katerina Anagnostou Konstantinos Rogdakis Felix T.Eickemeyer mostafa Othman minas m.Stylianakis Dimitris Tsikritzis Anwar Q.Alanazi Nikolaos Tzoganakis Lukas Pfeifer Rita Therisod Xiaoliang mo Christian m.Wolff Aïcha Hessler-Wyser Shaik m.Zakeeruddin Hong Zhang Emmanuel Kymakis michael Grätzel Laboratory of Photonics and Interfaces École Polytechnique Fédérale de Lausanne(EPFL)Lausanne 1015Switzerland Department of Electrical and Computer Engineering Hellenic Mediterranean UniversityHeraklionCrete 71410Greece Institute of Electrical and microengineering(IEm)Photovoltaics and Thin-Film Electronics Laboratory(PV-Lab) École Polytechnique Fédérale de Lausanne(EPFL)Neuchâtel 2000Switzerland Department of Nursing Faculty of Health SciencesHellenic Mediterranean UniversityCrete 71410Greece Centre Interdisciplinaire de microscopie Electronique École Polytechnique Fédérale de Lausanne(EPFL)Lausanne 1015Switzerland Future Energy Technology Institute King Abdulaziz City for Science and Technology(KACST)P.O.Box 6086Riyadh 11442Saudi Arabia State Key Laboratory of Photovoltaic Science and Technology Shanghai Frontiers Science Research Base of Intelligent Optoelectronics and PerceptionInstitute of OptoelectronicsDepartment of Materials ScienceFudan UniversityShanghai 200433China

Perovskite solar cells(PSCs)have made great advances in terms of power conversion efficiency(PCE),yet their subpar stability continues to hinder their *** interface between the perovskite layer and the charge-carrier transporting layers plays a crucial role in undermining the stability of *** this work,we propose a strategy to stabilize high-performance PSCs with PCE over 23%by introducing a cesium-doped graphene oxide(GO-Cs)as an interlayer between the perovskite and hole-transporting *** GO-Cs treated PSCs exhibit excellent operational stability with a projected T80(the time where the device PCE reduces to 80%of its initial value)of 2143 h of operation at the maximum powering point under one sun illumination.

关键词： Perovskite solar cells Doped graphene oxide Graphene related material Long-term operational stability