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Integrated carbon and nitrogen management for cost-effective environmental policies in China

Science (New York, N.Y.) 2025年第6751期388卷 1098-1103页

作者： Xin Xu Xiuming Zhang Yiyang Zou Tianrun Chen Jingfang Zhan Luxi Cheng Wilfried Winiwarter Shaohui Zhang Peter M Vitousek Wim de Vries Baojing Gu State Key Laboratory of Soil Pollution Control and Safety Zhejiang University Hangzhou China. College of Environmental and Resource Sciences Zhejiang University Hangzhou China. International Institute for Applied Systems Analysis Laxenburg Austria. Ministry of Education Key Laboratory of Environment Remediation and Ecological Health Zhejiang University Hangzhou China. College of Computer Science and Technology Zhejiang University Hangzhou China. Policy Simulation Laboratory Zhejiang University Hangzhou China. Institute of Environmental Engineering University of Zielona Góra Zielona Góra Poland. School of Economics and Management Beihang University Beijing China. Department of Earth System Science Stanford University Stanford CA USA. Wageningen University and Research Earth Systems and Global Change Group Wageningen Netherlands. Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment Zhejiang University Hangzhou China.

Carbon and nitrogen are central elements in global biogeochemical cycles. To effectively manage carbon and nitrogen in China, we developed a comprehensive model for quantifying their fluxes, investigating their interplay across 16 human and natural subsystems. Between 1980 and 2020, nitrogen losses in China increased 2.3-fold and carbon emissions surged 6.5-fold. Integrated carbon and nitrogen management holds the potential for a 74% reduction in nitrogen losses to air and water and a 91% decrease in carbon emissions to the atmosphere by 2060. Compared with separate control of carbon or nitrogen, integrated management delivers an additional reduction of 1.8 million tons of nitrogen and 26.5 million tons of carbon by 2060, bringing out a 37% decrease in unit abatement cost and a net societal benefit of 1384 billion USD.

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AN ADAPTIVE FINITE ELEMENT METHOD FOR TWO-DIMENSIONAL ELLIPTIC EQUATIONS WITH LINE DIRAC SOURCES

arXiv

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arXiv 2021年

作者： Cao, Huihui Li, Hengguang Yi, Nianyu Yin, Peimeng Hunan Key Laboratory for Computation and Simulation in Science and Engineering School of Mathematics and Computational Science Xiangtan University Hunan Xiangtan411105 China Wayne State University Department of Mathematics DetroitMI48202 United States Multiscale Methods and Dynamics Group Computer Science and Mathematics Division Oak Ridge National Laboratory Oak RidgeTN37831 United States

In this paper, we propose a novel adaptive finite element method for an elliptic equation with line Dirac delta functions as a source term. We first study the well-posedness and global regularity of the solution in the whole domain. Instead of regularizing the singular source term and using the classical residual-based a posteriori error estimator, we propose a novel a posteriori estimator based on an equivalent transmission problem with zero source term and nonzero flux jumps on line fractures. The transmission problem is defined in the same domain as the original problem excluding on line fractures, and the solution is therefore shown to be more regular. The estimator relies on meshes conforming to the line fractures and its edge jump residual essentially uses the flux jumps of the transmission problem on line fractures. The error estimator is proven to be both reliable and efficient, an adaptive finite element algorithm is proposed based on the error estimator and the bisection refinement method. Numerical tests show that quasi-optimal convergence rates are achieved even for high order approximations and the adaptive meshes are only locally refined at singular points. © 2021, CC BY-NC-ND.

关键词： Fracture

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Towards responsible AI for education: Hybrid human-AI to confront the Elephant in the room

arXiv

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arXiv 2025年

作者： Hooshyar, Danial Šír, Gustav Yang, Yeongwook Kikas, Eve Hämäläinen, Raija Kärkkäinen, Tommi Gašević, Dragan Azevedo, Roger School of digital Technologies Tallinn University Tallinn Estonia Department of Education University of Jyväskylä Jyväskylä Finland Department of Computer Science Czech Technical University Prague Czech Republic Department of Computer Science and Engineering Gangneung-Wonju National University Wonju Korea Republic of School of Natural Sciences and Health Tallinn University Tallinn Estonia Faculty of Information Technology University of Jyväskylä Jyväskylä Finland Faculty of Information Technology Monash University ClaytonVIC Australia School of Modeling Simulation and Training University of Central Florida Orlando United States

Despite significant advancements in AI-driven educational systems and ongoing calls for responsible AI for education, multiple critical issues remain unresolved—acting as the elephant in the room within the AI in education, learning analytics, educational data mining, learning sciences, and educational psychology communities. This critical analysis paper identifies and examines nine persistent challenges that continue to undermine the fairness, transparency, and effectiveness of current AI methods and applications in education. These include: 1) the lack of clarity around what AI for education truly means—often ignoring the distinct purposes, strengths, and limitations of different AI families—and the growing trend of equating it with domain-agnostic, company-driven large language models;2) the widespread neglect of essential learning processes such as motivation, emotion, and (meta)cognition in AI-driven learner modelling and their contextual nature;3) the limited integration of domain knowledge and lack of stakeholder involvement in AI design and development;4) the continued use of non-sequential machine learning models on temporal educational data, which fails to capture the dynamics and dependencies critical to understanding real learning progressions;5) the misuse of non-sequential metrics to evaluate sequential or temporal models;6) using unreliable explainable AI methods to provide explanations for black-box models;7) ignoring ethical guidelines in addressing data inconsistencies during model training;8) use of mainstream AI methods for pattern discovery and learning analytics without systematic benchmarking, which risks leading to unreliable conclusions;and 9) focusing on global prescriptions while overlooking localized, student-specific recommendations. Supported by both theoretical and empirical research, we demonstrate how hybrid AI methods—specifically neural-symbolic AI—address the elephant in the room and serve as the foundation for building responsibl

关键词： Teaching

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Perturbations and Phase Transitions in Swarm Optimization Algorithms

arXiv

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arXiv 2025年

作者： Vantuch, Tomáš Zelinka, Ivan Adamatzky, Andrew Marwan, Norbert Center ENET Technical University of Ostrava Czech Republic Modeling Evolutionary Algorithms Simulation and Artificial Intelligence Faculty of Electrical & Electronics Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam Department of Computer Science Technical University of Ostrava Czech Republic Unconventional Computing Lab UWE Bristol United Kingdom Leibniz Association Potsdam Germany

Natural systems often exhibit chaotic behavior in their space-time evolution. Systems transiting between chaos and order manifest a potential to compute, as shown with cellular automata and artificial neural networks. We demonstrate that swarm optimization algorithms also exhibit transitions from chaos, analogous to a motion of gas molecules, when particles explore solution space disorderly, to order, when particles follow a leader, similar to molecules propagating along diffusion gradients in liquid solutions of reagents. We analyze these ‘phase-like’ transitions in swarm optimization algorithms using recurrence quantification analysis and Lempel-Ziv complexity estimation. We demonstrate that converging iterations of the optimization algorithms are statistically different from non-converging ones in a view of applied chaos, complexity and predictability estimating indicators. An identification of a key factor responsible for the intensity of their phase transition is the main contribution of this paper. We examined an optimization as a process with three variable factors – an algorithm, number generator and optimization function. More than 9.000 executions of the optimization algorithm revealed that the nature of an applied algorithm itself is the main source of the phase transitions. Some of the algorithms exhibit larger transition-shifting behavior while others perform rather transition-steady computing. These findings might be important for future extensions of these algorithms. © 2025, CC BY-NC-ND.

关键词： Cellular automata

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A robotic and virtual testing platform highlighting the promise of soft wearable actuators for wrist tremor suppression

Device

引用

Device 2025年第6期3卷

作者： Alona Shagan Shomron Christina Chase-Markopoulou Johannes R. Walter Johanna Sellhorn-Timm Yitian Shao Tobias Nadler Audrey Benson Isabell Wochner Ellen H. Rumley Isabel Wurster Philipp Klocke Daniel Weiss Syn Schmitt Christoph Keplinger Daniel F.B. Haeufle Robotic Materials Department Max Planck Institute for Intelligent Systems Stuttgart Germany Institute for Modelling and Simulation of Biomechanical Systems University of Stuttgart Stuttgart Germany Stuttgart Center for Simulation Science (SimTech) University of Stuttgart Stuttgart Germany Hertie Institute for Clinical Brain Research University of Tübingen Tübingen Germany Haptic Intelligence Department Max Planck Institute for Intelligent Systems Stuttgart Germany Institute for Computer Engineering (ZITI) University of Heidelberg Heidelberg Germany Paul M. Rady Department of Mechanical Engineering University of Colorado Boulder CO USA Center for Neurology Department of Neurodegenerative Diseases University of Tübingen Tübingen Germany Center for Bionic Intelligence (BITS) Tübingen and Stuttgart Germany Material Science and Engineering Program University of Colorado Boulder CO USA Werner Reichardt Center for Integrative Neuroscience University of Tübingen Tübingen Germany

Nearly 80 million people in the world deal with medical conditions that cause involuntary periodic movements known as tremors. Wearable soft robotic devices offer a potential solution for actively suppressing these tremors. However, existing prototypes face limitations in actuation performance and complex testing procedures. We present a comprehensive approach for the rapid evaluation of emerging wearable tremor-suppression technologies. This method combines reproducing patient-recorded tremor episodes and measuring tremor suppression in a robotic platform, termed a “mechanical patient”, with validation of the achieved suppression performance of soft actuators via biomechanical modeling, thereby avoiding time-consuming clinical testing in the early stages of development. Using this approach, we highlight that an antagonistic pair of slim and lightweight electrohydraulic actuators can effectively suppress clinically relevant tremors between 2 and 8 Hz. The biomechanical model confirms that the pair of actuators generates adequate suppression forces for all tested tremors.

关键词： tremor suppression mechanical patient soft actuators wearable devices biomechanical simulation DTI-4: Validate

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Soil liquefaction assessment by using hierarchical Gaussian Process model with integrated feature and instance based domain adaption for multiple data sources

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AI in Civil engineering 2022年第1期1卷 50-81页

作者： Hongwei Guo Timon Rabczuk Yanfei Zhu Hanyin Cui Chang Su Xiaoying Zhuang Department of Geotechnical Engineering Tongji University1239 Siping RoadShanghai 200092People’s Republic of China Computational Science and Simulation Technology Institute of PhotonicsLeibniz Universität HannoverAppelstr.1130167 HannoverGermany Shanghai Tunnel Engineering Co. Ltd.No 1099 Wanping South RoadXuhuiShanghai 200032People’s Republic of China Key Laboratory of Geotechnical and Underground Engineering of Ministry of Education Tongji University1239 Siping RoadShanghai 200092People’s Republic of China ALISR Laboratory College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh 11543Saudi Arabia State Key Laboratory of Acoustics Institute of AcousticsChinese Academy of SciencesHaidian DistrictNo.21 North 4th Ring RoadBeijing 100190People’s Republic of China.

For soil liquefaction prediction from multiple data sources,this study designs a hierarchical machine learning model based on deep feature extraction and Gaussian Process with integrated domain adaption *** proposed model first combines deep fisher discriminant analysis(DDA)and Gaussian Process(GP)in a unified framework,so as to extract deep discriminant features and enhance the model performance for *** deliver fair evalu-ation,the classifier is validated in the approach of repeated stratified K-fold cross ***,five different data resources are presented to further verify the model’s robustness and *** reuse the gained knowledge from the existing data sources and enhance the generality of the predictive model,a domain adaption approach is formu-lated by combing a deep Autoencoder with TrAdaboost,to achieve good performance over different data records from both the in-situ and laboratory *** comparing the proposed model with classical machine learn-ing models,such as supported vector machine,as well as with the state-of-art ensemble learning models,it is found that,regarding seismic-induced liquefaction prediction,the predicted results of this model show high accuracy on all datasets both in the repeated cross validation and Wilcoxon signed rank ***,a sensitivity analysis is made on the DDA-GP model to reveal the features that may significantly affect the liquefaction.

关键词： Liquefaction Machine learning Deep fisher discriminant analysis Gaussian Process Ensemble methods Domain adaption

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The impact of AI on engineering design procedures for dynamical systems

arXiv

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arXiv 2024年

作者： de Payrebrune, Kristin M. Flaßkamp, Kathrin Ströhla, Tom Sattel, Thomas Bestle, Dieter Röder, Benedict Eberhard, Peter Peitz, Sebastian Stoffel, Marcus Rutwik, Gulakala Aditya, Borse Wohlleben, Meike Sextro, Walter Raff, Maximilian Remy, C. David Yadav, Manish Stender, Merten van Delden, Jan Lüddecke, Timo Langer, Sabine C. Schultz, Julius Blech, Christopher RPTU Kaiserslautern-Landau Institute for Computational Physics in Engneering Gottlieb-Daimler-Straße 74 Kaiserslautern67663 Germany Saarland University Systems Engineering Systems Modeling and Simulation Campus Saarbrücken66123 Germany TU Ilmenau Mechatronics group Max-Planck-Ring 12 Ilmenau98693 Germany Brandenburg University of Technology Cottbus-Senftenberg Chair of Engineering Mechanics and Vehicle Dynamics Siemens-Halske-Ring 14 Cottbus03046 Germany University of Stuttgart Institute of Engineering and Computational Mechanics Pfaffenwaldring 9 Stuttgart70569 Germany TU Dortmund Department of Computer Science & Lamarr Institute Joseph-von-Fraunhofer-Str. 25 Dortmund44227 Germany RWTH Aachen University Institute of General Mechanics Eilfschornsteinstraße 18 Aachen52062 Germany Paderborn University Faculty of Mechanical Engineering Dynamics and Mechatronics Warburger Str. 100 Paderborn33098 Germany University of Stuttgart Institute for Nonlinear Mechanics Pfaffenwaldring 9 Stuttgart70569 Germany Technische Universität Berlin Chair of Cyber-Physical Systems in Mechanical Engineering Straße des 17. Juni 135 Berlin10623 Germany University of Göttingen Institute of Informatics Goldschmidtstr. 7 Göttingen37077 Germany Technische Universität Braunschweig Institute for Acoustics and Dynamics Langer Kamp 19 Braunschweig38106 Germany

Artificial intelligence (AI) is driving transformative changes across numerous fields, revolutionizing conventional processes and creating new opportunities for innovation. The development of mechatronic systems is undergoing a similar transformation. Over the past decade, modeling, simulation, and optimization techniques have become integral to the design process, paving the way for the adoption of AI-based methods. In this paper, we examine the potential for integrating AI into the engineering design process, using the V-model from the VDI guideline 2206, considered the state-of-the-art in product design, as a foundation. We identify and classify AI methods based on their suitability for specific stages within the engineering product design workflow. Furthermore, we present a series of application examples where AI-assisted design has been successfully implemented by the authors. These examples, drawn from research projects within the DFG Priority Program SPP 2353: Daring More Intelligence - Design Assistants in Mechanics and Dynamics, showcase a diverse range of applications across mechanics and mechatronics, including areas such as acoustics and robotics. © 2024, CC BY.

关键词： Mechatronics

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Nonlinear dynamics in an optoelectronic feedback delay oscillator with piecewise linear transfer functions from the laser diode and photodiode

引用

Physical Review E 2020年第4期102卷 042217-042217页

作者： Géraud R. Goune Chengui Kengne Jacques Paul Woafo Yanne K. Chembo Laboratories d'Automatique et Informatique Appliquée (UR-AIA) Department of Electrical Engineering IUT-FV Bandjoun P.O. Box 134 Bandjoun Cameroon Laboratory of Modelling and Simulation in Engineering Biomimetics and Prototypes Department of Physics Faculty of Science P.O. Box 812 Yaoundé Cameroon University of Maryland A. James Clark School of Engineering Department of Electrical and Computer Engineering and Institute for Research in Electronics and Applied Physics (IREAP) 8279 Paint Branch Drive College Park Maryland 20742 USA

We investigate the nonlinear dynamics of a recent architecture of an optoelectronic oscillator, where the emitting laser and the receiving diode are connected in a head-to-tail configuration via an optical fiber delay line. The resulting nonlinear transfer function is a piecewise linear profile, and its interplay with the delay leads to many complex behaviors such as relaxation oscillations and deterministic chaos. This system belongs to a recent class of optoelectronic oscillators where the nonlinearity does not originate from the sinusoidal transfer function of an imbalanced interferometer, and, in particular, it is a simple optoelectronic oscillator configuration that is capable of displaying a chaotic behavior. The results of the analytic study are confirmed by numerical simulations and experimental measurements.

关键词： Control & applications of chaos Chaotic systems

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Investigation of the Electronic, Magnetic, Exchange Interactions, and Magnetocaloric Properties in Orthotitanate Oxides Rtio3 (R = Er, Ho)

SSRN

引用

SSRN 2023年

作者： Jmal, Sohail Ait Tamerd, Mohamed Ait Mounkachi, Omar Salvestrini, Jean Paul Balli, Mohamed AMEEC Team LERMA International University of Rabat Parc Technopolis Rocade de Rabat- Salé 11100 Morocco Laboratory of Condensed Matter and Interdisciplinary Sciences Department of Physics Faculty of Sciences Mohammed V University in Rabat PO Box 1014 Rabat Morocco Modeling Simulation & Data Analysis Program Mohammed VI Polytechnic University Ben Guerir43150 Morocco Institute of Applied Physics Mohammed VI Polytechnic University Lot 660 Hay Moulay Rachid BP 43150 Ben Guerir Morocco CNRS IRL 2958 Georgia Tech CNRS 2 rue Marconi Metz57070 France Georgia Institute of Technology School of Electrical and Computer Engineering AtlantaGA30332-0250 United States

Strong correlated materials are emerging materials in low magnetocaloric cooling applications. The development of these fields necessitates materials with appealing magnetic, and magnetocaloric features. In this context, Density Functional Theory (DFT) combined with Monte Carlo simulations (MCs) are performed to comprehensively examine various physical, and magnetic features of the orthorhombic perovskite-type RTiO3. A metallic behavior of (Ho, Er)TiO3 has been found via the density of state using GGA+U approach. X-ray magnetic circular dichroism (XMCD) was carried out to identify the magnetic contributions of Ho, Er, and Ti atoms in HoTiO3, and ErTiO3 compounds. The spin-orbit coupling was added in our calculations to study and evaluate the magnetocrystalline anisotropies of RTiO3 with (R= Ho, Er). We noticed an easy magnetization axis along the b-direction for HoTiO3, and along the c-direction for ErTiO3. Low magnetocrystalline anisotropy energies were found compared to other perovskite oxides such as RVO3, and RMnO3indicating that a weak rotating magnetocaloric effect (RMCE) is expected in (Ho, Er)TiO3. Moreover, the exchange coupling interactions were calculated using Ising model, the (Ti-Ti) interaction coupling is ferromagnetic, and larger than the other exchange interactions in (Ho, Er)TiO3. Furthermore, these exchange coupling interactions were utilized within the Heisenberg model for MCs, allowing us to understand the driving mechanisms underlying magnetocaloric and magnetic behaviors in (Ho, Er)TiO3. © 2023, The Authors. All rights reserved.

关键词： Perovskite

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Magnetization and Spin Dynamics in Two-Dimensional Magnets

Magnetization and Spin Dynamics in Two-Dimensional Magnets

引用

Magnetic Conference - Short Papers (INTERMAG Short Papers), IEEE International

作者： Laith Alahmed Bhuwan Nepal Juan Macy Brian Casas Arjun Sapkota Alessandro R Mazza Matthew Brahlek Jiajia Wen Wencan Jin Steven S.-L. Zhang Claudia Mewes Li-Chuan Zhang Yuriy Mokrousov Wei Zhang Young S. Lee Luis Balicas Tim Mewes Xiaoqian Zhang Peng Li Department of Electrical and Computer Engineering Auburn University Auburn AL USA Department of Physics University of Alabama Tuscaloosa AL USA National High Magnetic Field Laboratory Florida State University Tallahassee FL USA Materials Science and Technology Division Oak Ridge National Laboratory Oak Ridge TN USA Department of Physics Auburn University Auburn AL USA Stanford Institute for Materials and Energy Sciences SLAC National Accelerator Laboratory Menlo Park CA USA Department of Physics Case Western Reserve University Cleveland OH USA Peter Grünberg Institut and Institute for Advanced Simulation Forschungszentrum Jülich and JARA Jülich Germany Institute of Physics Johannes Gutenberg University Mainz Mainz Germany Department of Physics and Astronomy University of North Carolina at Chapel Hill Chapel Hill North Carolina USA Shenzhen Institute for Quantum Science and Engr. Southern University of Science and Technology Shenzhen China School of Microelectronics University of Science and Technology of China Hefei China

The discovery of magnetism in two-dimensional (2D) van der Waals (vdW) materials has flourished a new endeavor of fundamental problems in magnetism. In this talk, we will discuss the magnetization and spin dynamics in two types of 2D magnets: a room-temperature vdW magnetic crystal Fe5GeTe2 with a Curie temperature Tc = 332 K and Cu(1,3-bdc), a quasi-2D magnet with a Kagome lattice. Ferromagnetic resonance was performed with external magnetic fields applied along the c-axis (H║c) and the ab-plane (H║ab). We have found a sizable Landé g-factor difference between the H║c and H║ab cases for both Fe5GeTe2 and Cu(1,3-bdc). The FMR measurements have also revealed that Fe 5 GeTe 2 has a damping constant comparable to Permalloy. Our experiments highlight key information regarding the magnetic state and spin scattering processes in 2D magnets, which can lead to implementations of 2D magnets based spintronic devices.

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