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Strategies to achieve effective nitrogen activation

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Carbon Energy 2024年第5期6卷 137-163页

作者： Bin Chang Huabin Zhang Shuhui sun Gaixia Zhang KAUST Catalysis Center(KCC) King Abdullah University of Science and Technology(KAUST)ThuwalKingdom of Saudi Arabia Institut National de la Recherche Scientifique(INRS) CentreÉnergie Matériaux TélécommunicationsVarennesQuébecCanada Department of Electrical Engineering École de Technologie Supérieure(ÉTS)MontréalQuébecCanada

Ammonia serves as a crucial chemical raw material and hydrogen energy *** electrocatalytic nitrogen reduction reaction(NRR),powered by renewable energy,has attracted tremendous interest during the past few *** some achievements have been revealed in aqueous NRR,significant challenges have also been *** activity and selectivity are fundamentally limited by nitrogen activation and competitive hydrogen *** review focuses on the hurdles of nitrogen activation and delves into complementary strategies,including materials design and system optimization(reactor,electrolyte,and mediator).Then,it introduces advanced interdisciplinary technologies that have recently emerged for nitrogen activation using high-energy physics such as plasma and *** a better understanding of the corresponding reaction mechanisms in the coming years,these technologies have the potential to be extended in further *** review provides further insight into the reaction mechanisms of selectivity and stability of different reaction *** then recommend a rigorous and detailed protocol for investigating NRR performance and also highlight several potential research directions in this exciting field,coupling with advanced interdisciplinary applications,in situ/operando characterizations,and theoretical calculations.

关键词： activation via mediators catalyst optimization electrochemical nitrogen fixation high-energy activation of nitrogen nitrogen

Universal dynamic scaling and Contact dynamics in quenched quantum gases

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Frontiers of physics 2024年第2期19卷 213-220页

作者： Jia-Nan Cui Zhengqiang Zhou Mingyuan sun School of Science Beijing University of Posts and TelecommunicationsBeijing 100876China State Key Lab of Information Photonics and Optical Communications Beijing University of Posts and TelecommunicationsBeijing 100876China

Recently universal dynamic scaling is observed in several systems,which exhibit a spatiotemporal self-similar scaling behavior,analogous to the spatial scaling near phase *** latter one arises from the emergent continuous scaling *** by this,we investigate the possible relation between the scaling dynamics and the continuous scaling symmetry in this *** derive a theorem that the scaling invariance of the quenched Hamiltonian and the initial density matrix can lead to the universal dynamic *** is further demonstrated both in a two-body system analytically and in a many-body system *** the latter one,we calculate the dynamics of quantum gases quenched from the zero interaction to a finite interaction via the non-equilibrium high-temperature virial expansion.A dynamic scaling of the momentum distribution appears in certain momentum-time windows at unitarity as well as in the weak interacting ***,this universal scaling dynamics persists approximately with smaller scaling exponents even if the scaling symmetry is fairly *** findings may offer a new perspective to interpret the related *** also study the Contact dynamics in the BEC−BCS ***,the half-way time displays a maximum near unitarity while some damping oscillations occur on the BEC side due to the dimer state,which can be used to detect possible two-body bound states in experiments.

关键词： dynamic scaling Contact dynamics quantum gases cold atom quench dynamics virial expansion continuous scaling symmetry

Two-dimensional semiconductor heterostructures for photocatalytic CO_(2)conversion

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Science China Chemistry 2024年第8期67卷 2434-2447页

作者： Yang Wu Mingyu Wu Yongfu sun Yi Xie Hefei National Research Center for Physical Sciences at Microscale University of Science and Technology of ChinaHefei 230026China

The CO_(2)reduction into carbon-contained fuel via solar energy offers the powerful tools to realize the zero-emission carbon *** to the intriguing features of the two-dimensional(2D)heterostructures,it is susceptible to modulate the electronic structure as well as the surface geometry for optimizing the photocatalytic CO_(2)*** this perspective,we surveyed the fundamental insights of 2D semiconductor heterostructures,involving the fabrication strategies and classification of the 2D semiconductor ***,we have detailly discussed the overview of 2D semiconductor heterostructure for optimizing CO_(2)photocatalytic influenced factors,including the solar energy utilization,photogenerated carriers separation,and redox reaction ***,we showed the significant advantages of 2D heterostructures in elevating CO_(2)photoreduction performance,focusing on activity,selectivity and *** analyzing the limitations and developments,we ended by putting forward insights into the further researches about the CO_(2)photocatalysts and reactor design,even industrial applications.

关键词： two-dimensional semiconductor heterostructures photocatalysis CO_(2)conversion

Causal reasoning in typical computer vision tasks

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Science China(Technological Sciences) 2024年第1期67卷 105-120页

作者： ZHANG KeXuan sun QiYu ZHAO ChaoQiang TANG Yang Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of EducationEast China University of Science and TechnologyShanghai 200237China National Key Laboratory of Air based Information Perception and Fusion Luoyang 471000China Luoyang Institute of Electro Optical Equipment of Avic Luoyang 471000China

Deep learning has revolutionized the field of artificial *** on the statistical correlations uncovered by deep learning-based methods,computer vision tasks,such as autonomous driving and robotics,are growing *** being the basis of deep learning,such correlation strongly depends on the distribution of the original data and is susceptible to uncontrolled *** the guidance of prior knowledge,statistical correlations alone cannot correctly reflect the essential causal relations and may even introduce spurious *** a result,researchers are now trying to enhance deep learningbased methods with causal *** theory can model the intrinsic causal structure unaffected by data bias and effectively avoids spurious *** paper aims to comprehensively review the existing causal methods in typical vision and visionlanguage tasks such as semantic segmentation,object detection,and image *** advantages of causality and the approaches for building causal paradigms will be *** roadmaps are also proposed,including facilitating the development of causal theory and its application in other complex scenarios and systems.

关键词： causal reasoning computer vision tasks vision-language tasks semantic segmentation object detection

Optimal Time-of-use Pricing for Renewable Energy-powered Microgrids: A Multi-agent Evolutionary Game Theory-based Approach

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 162-174页

作者： Yu Zeng Yinliang Xu Xinwei Shen Hongbin sun Tsinghua-Berkeley Shenzhen Institute.Tsinghua Shenzhen International Graduate School Tsinghua UniversityShenzhen 518055China Department of Electrical Engineering Tsinghua UniversityBeijing 100084China

While price schedules can help improve the economic efficiency of renewable energy-powered microgrids,timeof-use(TOU)pricing has been identified as an effective way for microgrid development,which is presently limited by its high *** this study,we propose an evolutionary game theoretic model to explore optimal TOU pricing for development of renewable energy-powered microgrids by applying a multi-agent system,that comprises a government agent,local utility company agent,and different types of consumer *** the proposed model,we design objective functions for the company and the consumers and obtain a Nash equilibrium using backward *** pricing strategies,namely,the TOU seasonal pricing and TOU monthly pricing,are evaluated and compared with traditional fixed *** numerical results demonstrate that TOU schedules have significant potential for development of renewable energy-powered microgrids and are recommended for an electric company to replace traditional fixed ***,TOU monthly pricing is more suitable than TOU seasonal pricing for microgrid development.

关键词： Game theory microgrid multi-agent system renewable energy time-of-use pricing

Predicting Hurricane Evacuation Decisions with Interpretable Machine Learning Methods

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International Journal of Disaster Risk Science 2024年第1期15卷 134-148页

作者： Yuran sun Shih‑Kai Huang Xilei Zhao Department of Civil and Coastal Engineering University of FloridaGainesvilleFL 32611USA Department of Emergency Management and Public Administration Jacksonville State UniversityJacksonvilleAL 36265USA

Facing the escalating effects of climate change,it is critical to improve the prediction and understanding of the hurricane evacuation decisions made by households in order to enhance emergency *** studies in this area often have relied on psychology-driven linear models,which frequently exhibited limitations in *** present study proposed a novel interpretable machine learning approach to predict household-level evacuation decisions by leveraging easily accessible demographic and resource-related predictors,compared to existing models that mainly rely on psychological *** enhanced logistic regression model(that is,an interpretable machine learning approach) was developed for accurate predictions by automatically accounting for nonlinearities and interactions(that is,univariate and bivariate threshold effects).Specifically,nonlinearity and interaction detection were enabled by low-depth decision trees,which offer transparent model structure and robustness.A survey dataset collected in the aftermath of Hurricanes Katrina and Rita,two of the most intense tropical storms of the last two decades,was employed to test the new *** findings show that,when predicting the households’ evacuation decisions,the enhanced logistic regression model outperformed previous linear models in terms of both model fit and predictive *** outcome suggests that our proposed methodology could provide a new tool and framework for emergency management authorities to improve the prediction of evacuation traffic demands in a timely and accurate manner.

关键词： Artifcial Intelligence(AI) Decision-making modeling Hurricane evacuation Interpretable machine learning Nonlinearity and interaction detection

Robust Forecasting-Aided State Estimation Considering Uncertainty in Distribution System

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CSEE Journal of Power and Energy Systems 2024年第4期10卷 1632-1641页

作者： Dongchen Hou Yonghui sun Linchuang Zhang Sen Wang College of Energy and Electrical Engineering Hohai UniversityNanjing 210098China

With the development of the smart grid,the distribution system operation conditions become more complex and ***,due to the influence of observation outliers and uncertain noise statistics,it is more difficult to grasp the dynamic operation characteristics of distribution *** order to address these problems,by using projection statistics and the noise covariance updating technology based on the Sage-Husa noise estimator,for distribution power system with outliers and uncertain noise statistics,a robust adaptive cubature Kalman filter forecasting-aided state estimation method is proposed based on generalized-maximum likelihood type ***,an adaptive strategy,which can enhance the filtering accuracy under normal conditions,is *** the simulation part,the branch parameters and node load parameters of the test system are appropriately modified to simulate the asymmetry of the three-phase branch parameters and the asymmetry of the three-phase ***,through simulation experiments on the improved test system,it is verified that the robust forecasting-aided state estimation method,presented in this paper,can effectively perceive the actual operating state of the distribution network in different simulation scenarios.

关键词： Cubature Kalman filter distribution power system forecasting-aided state estimation projection statistics

Skill enhancement learning with knowledge distillation

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Science China(Information Sciences) 2024年第8期67卷 206-220页

作者： Naijun LIU Fuchun sun Bin FANG Huaping LIU Department of Computer Science and Technology Tsinghua University

Skill learning through reinforcement learning has significantly progressed in recent years. However, it often struggles to efficiently find optimal or near-optimal policies due to the inherent trial-and-error exploration in reinforcement learning. Although algorithms have been proposed to enhance skill learning efficacy, there is still much room for improvement in terms of skill learning performance and training stability. In this paper, we propose an algorithm called skill enhancement learning with knowledge distillation(SELKD), which integrates multiple actors and multiple critics for skill learning. SELKD employs knowledge distillation to establish a mutual learning mechanism among actors. To mitigate critic overestimation bias,we introduce a novel target value calculation method. We also perform theoretical analysis to ensure the convergence of SELKD. Finally, experiments are conducted on several continuous control tasks, illustrating the effectiveness of the proposed algorithm.

关键词： skill learning enhancement learning reinforcement learning knowledge distillation

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Systemic modulation of skeletal mineralization by magnesium implant promoting fracture healing: Radiological exploration enhanced with PCA-based machine learning in a rat femoral model

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Journal of Magnesium and Alloys 2024年第3期12卷 1009-1020页

作者： Yu sun Heike Helmholz Regine Willumeit-Römer Institute of Metallic Biomaterials Helmholtz-Zentrum HereonGermany

The clinical application of magnesium(Mg)and its alloys for bone fractures has been well supported by in vitro and in vivo ***,there were studies indicating negative effects of high dose Mg intake and sustained local release of Mg ions on bone metabolism or repair,which should not be ignored when developing Mg-based ***,it remains necessary to assess the biological effects of Mg implants in animal models relevant to clinical treatment *** primary purpose of this study was to validate the beneficial effects of intramedullary Mg implants on the healing outcome of femoral fractures in a modified rat *** addition,the mineralization parameters at multiple anatomical sites were evaluated,to investigate their association with healing outcome and potential clinical *** to the control group without Mg implantation,postoperative imaging at week 12 demonstrated better healing outcomes in the Mg group,with more stable unions in 3D analysis and high-mineralized bridging in 2D *** bone tissue mineral density(TMD)was higher in the Mg group at the non-operated femur and lumbar vertebra,while no differences between groups were identified regarding the bone tissue volume(TV),TMD and bone mineral content(BMC)in *** the surgical femur,the Mg group presented higher TMD,but lower TV and BMC in the distal metaphyseal region,as well as reduced BMC at the osteotomy *** component analysis(PCA)-based machine learning revealed that by selecting clinically relevant parameters,radiological markers could be constructed for differentiation of healing outcomes,with better performance than 2D *** study provides insights and preclinical evidence for the rational investigation of bioactive materials,the identification of potential adverse effects,and the promotion of diagnostic capabilities for fracture healing.

关键词： Magnesium Implants Bone fracture Mineralization Systemic modulation Principal component analysis.