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Predictor−corrector inverse design scheme for property−composition prediction of amorphous alloys

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Transactions of Nonferrous Metals Society of China 2025年第1期35卷 169-183页

作者： Tao long Zhi-lin long Bo PANG School of Mechanical Engineering and Mechanics Xiangtan UniversityXiangtan 411105China School of Civil Engineering Xiangtan UniversityXiangtan 411105China

In order to develop a generic framework capable of designing novel amorphous alloys with selected target properties,a predictor−corrector inverse design scheme(PCIDS)consisting of a predictor module and a corrector module was presented.A high-precision forward prediction model based on deep neural networks was developed to implement these two *** utmost importance,domain knowledge-guided inverse design networks(DKIDNs)and regular inverse design networks(RIDNs)were also *** forward prediction model possesses a coefficient of determination(R^(2))of 0.990 for the shear modulus and 0.986 for the bulk modulus on the testing ***,the DKIDNs model exhibits superior performance compared to the RIDNs *** is finally demonstrated that PCIDS can efficiently predict amorphous alloy compositions with the required target properties.

关键词： amorphous alloys machine learning deep neural networks inverse design elastic modulus

Evaluating complementaries among urban water,energy,infrastructure,and social Sustainable Development Goals in China

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Journal of Environmental Sciences 2025年第3期149卷 585-597页

作者： Ke Yu Yifan Song Jin lin shen Qu School of Management and Economics Beijing Institute of TechnologyBeijing 100081China Center for Energy&Environmental Policy Research Beijing Institute of TechnologyBeijing 100081China

Urban areas’performance in water,energy,infrastructure,and socio-economic sectors is intertwined and measurable through Sustainable Development Goals(SDGs)6–*** synergy among these is critical for *** study constructs an indicator framework that reflects progress towards these urban SDGs in *** indicate underperformance in SDGs 8–11,suggesting the need for transformative *** network analysis,the research reveals complementarities among these ***,the SDG space divides into socio-economic and ecological clusters,with SDG 6(Clean Water and Sanitation)central to ***,SDG 8(Decent Work and Economic Growth)and SDG 9(Industry,Innovation,and Infrastructure)act as bridges,while greater synergies exist between SDG 12(Responsible Consumption and Production)and SDG 13(Climate Action).An in-depth view at the indicator-level shows a core-periphery structure,emphasizing indicators like SDG 6.2(Wastewater Treatment Rate)and SDG 6.6(Recycled Water Production Capacity per capita)as *** study confirms the urban SDG space’s stability and predictiveness,underscoring its value in steering well-aligned policy decisions for sustainable growth.

关键词： Sustainable development goals Synergy Urban development Policy decisions

Remaining Life Prediction Method for Photovoltaic Modules Based on Two-Stage Wiener Process

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Energy Engineering 2025年第1期122卷 331-347页

作者： Jie lin Hongchi shen Tingting Pei Yan Wu School of Electrical Engineering and Information Engineering Lanzhou University of TechnologyLanzhou730050China

Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation *** service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental *** cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz Information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.

关键词： Photovoltaic modules degradation stochastic processes lifetime prediction

Unintentional emissions of polychlorinated naphthalenes in China:Sources,composition,and historical trends

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Journal of Environmental Sciences 2025年第2期148卷 221-229页

作者： Ye Huang lin Huang Ying Li Nazupar Sidikjan Yunshan Zhang Yan Chen Yangmin Chen Ye Li Wei Du long Chen YanWu Shanshan Zhang Jing Yang Wenjun Meng Guofeng shen Min Liu Shu Tao Key Laboratory of Geographic Information Science of the Ministry of Education School of Geographic SciencesEast China Normal UniversityShanghai 200241China Yunnan Provincial Key Laboratory of Soil Carbon Sequestration and Pollution Control Faculty of Environmental Science&EngineeringKunming University of Science&TechnologyKunming 650500China Laboratory of Earth Surface Processes College of Urban and Environmental SciencePeking UniversityBeijing 100871China

Polychlorinated naphthalenes(PCNs)are detrimental to human health and the *** the commercial production of PCNs banned,unintentional releases have emerged as a significant environmental ***,relevant information is still *** this study,provincial emissions for eight PCNs homologues from 37 sources in the Chinese mainland during the period of 1960-2019 were estimated based on a source-specific and time-varying emission factor *** results showed that the total PCNs emissions in 2019 reached 757.0 kg with Hebei ranked at the top among all the provinces and iron&steel industry as the biggest ***-chlorinated PCNs comprised 90%of emissions by mass,while highly chlorinated PCNs dominated in terms of toxicity,highlighting divergent priorities for mitigating emissions and safeguarding human *** emissions showed an overall upward trend from 1960 to 2019 driven by emission increase from iron&steel industry in terms of source,and from North China and East China in terms of geographic ***-capita emissions followed an inverted U-shaped environmental Kuznets curvewhile emission intensities decreased with increasing per-capita Gross Domestic Product(GDP)following a nearly linear pattern when log-transformed.

关键词： PCNs Emission inventory Emission factor Composition profile Emission intensity Chinese mainland

On the Riemann–Hilbert problem for the reverse space-time nonlocal Hirota equation with step-like initial data

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Communications in Theoretical Physics 2025年第2期77卷 32-40页

作者： Bei-Bei Hu ling Zhang Zu-Yi shen Ji lin School of Mathematics and Finance Chuzhou University Applied Mathematics Research Center Chuzhou University Department of Physics Zhejiang Normal University

In this paper, we use the Riemann–Hilbert(RH) method to investigate the Cauchy problem of the reverse space-time nonlocal Hirota equation with step-like initial data: q(z, 0) = o(1) as z →-∞ and q(z, 0) = δ + o(1) as z → ∞, where δ is an arbitrary positive constant. We show that the solution of the Cauchy problem can be determined by the solution of the corresponding matrix RH problem established on the plane of complex spectral parameter λ. As an example, we construct an exact solution of the reverse space-time nonlocal Hirota equation in a special case via this RH problem.

关键词： nonlocal Hirota equation Cauchy problem Riemann-Hilbert problem step-like initial data

The Security of Using Large Language Models:A Survey With Emphasis on ChatGPT

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 1-26页

作者： Wei Zhou Xiaogang Zhu Qing-long Han lin Li Xiao Chen sheng Wen Yang Xiang the School of Science Computing and Engineering Technologies Swinburne University of Technology IEEE the School of Computer and Mathematical Sciences the University of Adelaide Adelaide the Faculty of Science and Engineering Southern Cross University the School of Information and Physical Sciences the University of Newcastle

ChatGPT is a powerful artificial intelligence(AI)language model that has demonstrated significant improvements in various natural language processing(NLP) tasks. However, like any technology, it presents potential security risks that need to be carefully evaluated and addressed. In this survey, we provide an overview of the current state of research on security of using ChatGPT, with aspects of bias, disinformation, ethics, misuse,attacks and privacy. We review and discuss the literature on these topics and highlight open research questions and future *** this survey, we aim to contribute to the academic discourse on AI security, enriching the understanding of potential risks and mitigations. We anticipate that this survey will be valuable for various stakeholders involved in AI development and usage, including AI researchers, developers, policy makers, and end-users.

关键词： Artificial intelligence (AI) ChatGPT large language models (LLMs) security

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单通道防空导弹电子稳像技术分析与系统设计

系统仿真学报 2007年第9期19卷 2026-2029,2036页

作者：卜彦龙沈林成国防科学技术大学机电工程与自动化学院湖南长沙410073

针对单通道防空导弹弹旋耦合等问题,提出了不依靠惯性器件的导弹电子稳像方法,在获得稳定目标图像的同时,还能够得到导弹的实时运动参数。对单通道导弹电子稳像的基本原理进行了研究,详细阐述了其中涉及的弹目相对运动成像建模、导弹运... 详细信息

针对单通道防空导弹弹旋耦合等问题,提出了不依靠惯性器件的导弹电子稳像方法,在获得稳定目标图像的同时,还能够得到导弹的实时运动参数。对单通道导弹电子稳像的基本原理进行了研究,详细阐述了其中涉及的弹目相对运动成像建模、导弹运动参数估计方法以及导引头图像运动补偿方法等关键技术,在此基础上,设计了导弹电子稳像系统。仿真试验验证了方法的有效性。

关键词：单通道防空导弹导弹电子稳像成像模型运动估计运动补偿

维普期刊数据库

Isothermal reduction kinetics and reduction prediction for iron ore pellets

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Journal of Iron and Steel Research International 2025年第1期32卷 64-72页

作者： Fei Meng Hao Liu Yue-lin Qin Huang-jie Hua Yin Deng Ze-zheng Sun long-hai Liu School of Metallurgy and Materials Engineering Chongqing University of Science and TechnologyChongqing401331China CISDI Group Co. Ltd.Chongqing401122China College of Materials Science and Engineering Chongqing UniversityChongqing400044China Sichuan Desheng Group Vanadium&Titanium Co. Ltd.Leshan614000SichuanChina

Iron ore pellets,as one of the main charges of blast furnaces,have a greater impact on the CO_(2)emission reduction and stable operation of blast *** isothermal reduction behavior of the pellets obtained from a Chinese steel plant was studied in the gas mixtures of CO and N_(2).The results showed the reduction process is divided into two *** reduction in the initial stage(time t≤40 min)is cooperatively controlled by internal diffusion and interface chemical reactions with the activation energy of 30.19 and 16.67 kJ/mol,*** controlling step of the reduction in the final stage(t>40 min)is internal diffusion with the activation energy of 34.60 kJ/*** reduction process can be described by two equations obtained from kinetic *** reduction degree can be predicted under different temperatures and time,and the predicted results showed an excellent correlation with the experimental *** reduction mechanisms were confirmed by the analysis of the scanning electron microscope equipped with an energy dispersive spectrometer and optical microscope.

关键词： Pellet Reduction behavior Kinetics Mechanism Reduction prediction

Development and application of an intelligent thermal state monitoring system for sintering machine tails based on CNN-LSTM hybrid neural networks

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Journal of Iron and Steel Research International 2025年第1期32卷 52-63页

作者： Da-lin Xiong Xin-yu Zhang Zheng-wei Yu Xue-feng Zhang Hong-ming long Liang-jun Chen Anhui Province Key Laboratory of Metallurgical Engineering&Resources Recycling Anhui University of TechnologyMa’anshan243002AnhuiChina School of Metallurgical Engineering Anhui University of TechnologyMa’anshan243032AnhuiChina School of Computer Science Anhui University of TechnologyMa’anshan243032AnhuiChina

Real-time prediction and precise control of sinter quality are pivotal for energy saving,cost reduction,quality improvement and efficiency enhancement in the ironmaking *** advance,the accuracy and comprehensiveness of sinter quality prediction,an intelligent flare monitoring system for sintering machine tails that combines hybrid neural networks integrating convolutional neural network with long short-term memory(CNN-LSTM)networks was *** system utilized a high-temperature thermal imager for image acquisition at the sintering machine tail and employed a zone-triggered method to accurately capture dynamic feature images under challenging conditions of high-temperature,high dust,and *** feature images were then segmented through a triple-iteration multi-thresholding approach based on the maximum between-class variance method to minimize detail loss during the segmentation *** the advantages of CNN and LSTM networks in capturing temporal and spatial information,a comprehensive model for sinter quality prediction was constructed,with inputs including the proportion of combustion layer,porosity rate,temperature distribution,and image features obtained from the convolutional neural network,and outputs comprising quality indicators such as underburning index,uniformity index,and FeO content of the *** accuracy is notably increased,achieving a 95.8%hit rate within an error margin of±*** the system is applied,the average qualified rate of FeO content increases from 87.24%to 89.99%,representing an improvement of 2.75%.The average monthly solid fuel consumption is reduced from 49.75 to 46.44 kg/t,leading to a 6.65%reduction and underscoring significant energy saving and cost reduction effects.

关键词： Sinter quality Convolutional neural network long short-term memory Image segmentation FeO prediction