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Research on Stock Price Prediction Method Based on the GAN-LSTM-Attention Model

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Computers, Materials & Continua 2025年第1期82卷 609-625页

作者： Peng Li Yanrui Wei Lili Yin college of Computer science and technology Harbin University of Science and TechnologyHarbin150006China

Stock price prediction is a typical complex time series prediction problem characterized by dynamics,nonlinearity,and *** paper introduces a generative adversarial network model that incorporates an attention mechanism(GAN-LSTM-Attention)to improve the accuracy of stock price ***,the generator of this model combines the Long and Short-Term Memory Network(LSTM),the Attention Mechanism and,the Fully-Connected Layer,focusing on generating the predicted stock *** discriminator combines the Convolutional Neural Network(CNN)and the Fully-Connected Layer to discriminate between real stock prices and generated stock ***,to evaluate the practical application ability and generalization ability of the GAN-LSTM-Attention model,four representative stocks in the United States of America(USA)stock market,namely,Standard&Poor’s 500 Index stock,Apple Incorporatedstock,AdvancedMicroDevices Incorporatedstock,and Google Incorporated stock were selected for prediction experiments,and the prediction performance was comprehensively evaluated by using the three evaluation metrics,namely,mean absolute error(MAE),root mean square error(RMSE),and coefficient of determination(R2).Finally,the specific effects of the attention mechanism,convolutional layer,and fully-connected layer on the prediction performance of the model are systematically analyzed through ablation *** results of experiment show that the GAN-LSTM-Attention model exhibits excellent performance and robustness in stock price prediction.

关键词： Stock price prediction generative adversarial network attention mechanism time-series prediction

Isobaric enzymatic assays reveal depth-dependent variation in microbial ectoenzyme activities in the deepest ocean on Earth

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science China Earth sciences 2025年第1期68卷 185-194页

作者： Junwei CAO Jiahua WANG Hongge ZHANG Junhao DENG Binbin PAN Jiawang CHEN Li ZHANG Jiasong FANG college of Oceanography and Ecological science Shanghai Ocean University Ocean college Zhejiang University Laboratory for Marine Biology and Biotechnology Qingdao National Laboratory for Marine Science and Technology

Microbial ectoenzymes play essential roles in the transformation and mineralization of organic matter in the ***, conventional methods for measuring microbial ectoenzyme activities(MEAs) in the deep ocean under atmospheric conditions can misrepresent the metabolic activities of indigenous microbial communities. To overcome this limitation, we measured the activities of three microbial ectoenzymes(aminopeptidase, α-glucosidase, and β-glucosidase) under both atmospheric and in situ pressure conditions in seawater collected using pressure-retaining and non-pressure-retaining samplers in the Challenger Deep, Mariana Trench. In the case of aminopeptidase and α-glucosidase, the highest isobaric MEAs were observed in the surface layer(50 m), followed by those at abyssopelagic depths(4,000–6,000 m) for aminopeptidase, hadal realm(10,903 m)for α-glucosidase, while β-glucosidase activity exhibited the highest value at 10,903 m. Furthermore, the isobaric MEAs in hadal waters were commonly found to be higher than the decompressed counterparts, highlighting the importance of pressure-retaining sampling and isobaric enzymatic assays. The half-saturation constant(Km) showed a general decreasing trend with depth,suggesting that the deep ocean microbes might have adapted to the high-pressure and oligotrophic environment by increasing their ectoenzyme's affinity to substrate. Furthermore, particle-free MEAs contribute more to the total MEAs in the deep ocean than particle-associated MEAs, suggesting the significance of cell-associated and dissolved ectoenzymes in ocean *** study provides a foundation for future investigations of MEAs in the ocean and has important implications for understanding the dynamics of microbially mediated biogeochemical cycling in marine ecosystems.

关键词： Pressure-retaining sampling Microbial ectoenzyme activity Deep-sea microbes High pressure Mariana Trench

First observation results of Macao science Satellite-1 on lightning-induced electron precipitation

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science China Earth sciences 2025年第1期68卷 1-10页

作者： Yongping WANG Yixin SUN Qiugang ZONG Gaopeng LU Xudong GU Ze-Jun HU Bin LI Key Laboratory for Polar science Ministry of Natural Resources Polar Research Institute of China Institute of Space Physics and Applied technology Peking University State Key Laboratory of Lunar and Planetary science Macau University of Science and Technology School of Earth and Space sciences University of Science and Technology of China School of Electronic Information Wuhan University

The Medium-energy Electron Spectrometers(MES) is a space-borne instrument onboard Macao science Satellite-1(MSS-1) dedicated to monitoring the typical charged particle radiation characteristics in the satellite orbit and the process of their occurrence and development, including short bursts of lightning-induced electron precipitation(LEP).This paper presents the first results of the LEP measurements by the MSS-1.47 LEP events are identified with the routine operation for 3 months since satellite launch, all within the range of 1.5

关键词： Lightning-induced electron precipitation Inner radiation belts Energetic electrons Macao science Satellite-1

Fluorinated poly(p-triphenylene isatin) anion exchange membranes based on hydrophilic hydroxyl side chain modulation for fuel cells

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Journal of Energy Chemistry 2025年第1期100卷 702-709页

作者： Yiman Gu Yanchao Zhang Zhanyu Li Yijia Lei Baozeng Sun Xiaoyu Yu Zhe Wang college of Chemistry and Life science Changchun University of Technology college of Chemical Engineering Changchun University of Technology School of Materials science and Engineering Changchun University of Technology Key Laboratory of Advanced Functional Polymer Membrane Materials of Jilin Province

The development of alkaline fuel cells is moving forward at an accelerated pace,and the application of ether-free bonded polymers to anion exchange membranes （AEMs） has been widely ***,the question of the“trade-off”between AEM ionic conductivity and dimensional stability remains *** strategy of inducing microphase separation to improve the performance of AEM has attracted much attention recently,but the design of optimal molecular structures is still being ***,this work introduced different ratios of 3-bromo-1,1,1-trifluoroacetone （x=40,50,and 60） into the main chain of poly（p-terphenylene isatin）.Because fluorinated groups have excellent hydrophobicity,hydrophilic hydroxyl-containing side chains are introduced to jointly adjust the formation of phase separation *** results show that PTI-PTF50-NOH AEM with the appropriate fluorinated group ratio has the best ionic conductivity and alkali stability under the combined effect of *** has an ionic conductivity of 133.83 mS cm-1at 80°*** addition,the OH-conductivity remains at 89%of the initial value at 80°C and 3 M KOH for 1056 h of *** cell polarization curve based on PTI-PTF50-NOH shows a power density of 734.76 mW cm-2at a current density of 1807.7 mA cm-2.

关键词： Potassium hydroxide

Prospects on mangrove knowledge services in the smart era: From plant atlas to knowledge graphs

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science China Earth sciences 2025年第1期68卷 111-127页

作者： Zhi-Wei HOU Wenlong JING Cheng-Zhi QIN Ji YANG Qing XIA Xiaoling YIN Key Laboratory of Guangdong for Utilization of Remote Sensing and Geographical Information System Guangdong Open Laboratory of Geospatial Information Technology and Application Guangzhou Institute of Geography Guangdong Academy of Sciences Southern Marine science and Engineering Guangdong Laboratory (Guangzhou) State Key Laboratory of resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of Sciences college of resources and Environment University of Chinese Academy of Sciences School of Traffic & Transportation Engineering Changsha University of Science and Technology

Mangroves are crucial to the ecological security of the Earth and human well-being. Their management, conservation, and restoration are of great importance and necessitate the support of spatio-temporal information and multidisciplinary knowledge such as biology and ecology. Traditional knowledge services such as plant atlas provide illustrated textual knowledge of mangroves. However, this kind of service is oriented to information retrieval and is incapable of effectively mining and utilizing fragmented knowledge from multi-source heterogeneous data, facing the problem of “massive data, rare knowledge”. Knowledge graphs are capable of extracting, organizing, and fusing the knowledge contained in massive data into semantic networks that can be understood and computed by computers. They provide a solution for the realization of intelligent knowledge services. Focusing on the urgent need for mangrove knowledge acquisition, formal representation, and intelligent services, this paper proposes a research prospect on mangrove knowledge graphs and knowledge services. We first analyze the similarities and differences between various domain-specific concepts of Tupu. On this basis, we define the mangrove knowledge graph as a large-scale knowledge base that integrates multi-disciplinary knowledge and spatio-temporal information with mangrove ecosystems as the core. Then, we propose a research framework for mangrove knowledge services that can realize the transformation from multi-modal data to intelligent knowledge services, including multiple research levels such as ubiquitous data sensing and aggregation, knowledge organization and graph construction, and intelligent mangrove knowledge services. Subsequently, the methods and workflow for constructing mangrove knowledge graphs are introduced. Finally, we discuss the challenges and possible future directions of mangrove knowledge services in the smart era, including the construction of a mangrove knowledge system that integra

关键词： Mangrove Tupu Knowledge graph Multi-modal Knowledge service

An Improved Practical Byzantine Fault-Tolerant Algorithm Based on XGBoost Grouping for Consortium Chains

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Computers, Materials & Continua 2025年第1期82卷 1295-1311页

作者： Xiaowei Wang Haiyang Zhang Jiasheng Zhang Yingkai Ge Kexin Cui Zifu Peng Zhengyi Li Lihua Wang college of Electronic and Information Engineering Shandong University of Science and TechnologyQingdao266590China

In response to the challenges presented by the unreliable identity of the master node,high communication overhead,and limited network support size within the Practical Byzantine Fault-Tolerant(PBFT)algorithm for consortium chains,we propose an improved PBFT algorithm based on XGBoost grouping called XG-PBFT in this ***-PBFT constructs a dataset by training important parameters that affect node performance,which are used as classification indexes for *** XGBoost algorithm then is employed to train the dataset,and nodes joining the system will be grouped according to the trained grouping *** them,the nodes with higher parameter indexes will be assigned to the consensus group to participate in the consensus,and the rest of the nodes will be assigned to the general group to receive the consensus *** order to reduce the resource waste of the system,XG-PBFT optimizes the consensus protocol for the problem of high complexity of PBFT ***,we evaluate the performance of *** experimental results show that XG-PBFT can significantly improve the performance of throughput,consensus delay and communication complexity compared to the original PBFT algorithm,and the performance enhancement is significant compared to other algorithms in the case of a larger number of *** results demonstrate that the XG-PBFT algorithm is more suitable for large-scale consortium chains.

关键词： Consortium chain PBFT grouping reputation XGBoost

Copper-catalyzed C–H bond functionalization enabled by programmed alternating current

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science China Chemistry 2025年第1期68卷 10-11页

作者： Zhoumei Tan Kun Xu Chengchu Zeng Beijing Key Laboratory of Environmental and Viral Oncology College of Chemistry and Life Science Beijing University of Technology

Synthetic electrochemistry has been selected as one of the Top Ten Emerging Technologies in Chemistry in 2023 by International Union of Pure and Applied Chemistry (IUPAC)[1]. It has emerged as a sustainable platform for organic synthesis and has exhibited a wide range of applications from academia to industry [2]. However, electrosynthesis has been predominantly performed by using direct current (DC).

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Novel flexible and transparent microstrip low-pass filter design with Π-shaped DGS

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The Journal of China Universities of Posts and Telecommunications 2025年

作者： Liu Zhaohan Han Yunan Qiu Xianbo Li Xianli college of Information science and technology， Beijing University of Chemical technology

This paper proposes a new design for a transparent low-pass filter (LPF) using a flexible PTFE material and metallic copper. The transparent microstrip filter employs an asymmetric Π-shaped structure with dimensions of 260 mm × 13 mm × 0.148 mm， which owns a narrow transition band and achieves an insertion loss of less than 1.0 dB below 0.26 GHz. Furthermore， the insertion loss of the transparent microstrip filter can exceed 30 dB in the stopband of 1.02 GHz to 6.50 GHz. Square holes are added to the copper layer to improve the transparency of the LPF， and the filter performance can be adjusted by changing the square hole area and resolution. Additionally， multiple identical structures are cascaded to increase the insertion loss in the stopband while maintaining the passband. The transparent microstrip LPF has the characteristics of flexibility， high transparency， and significant insertion loss in the stopband， making it suitable for applications that require electromagnetic protection in a clear field of vision.

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Understanding the local structure and thermophysical behavior of Mg-La liquid alloys via machine learning potential

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International Journal of Minerals,Metallurgy and Materials 2025年第2期32卷 439-449页

作者： Jia Zhao Taixi Feng Guimin Lu National Engineering Research Center for Integrated Utilization of Salt Lake Resource East China University of Science and TechnologyShanghai 200237China Joint International Laboratory for Potassium and Lithium Strategic resources East China University of Science and TechnologyShanghai 200237China

The local structure and thermophysical behavior of Mg-La liquid alloys were in-depth understood using deep potential molecular dynamic(DPMD) simulation driven via machine learning to promote the development of Mg-La alloys. The robustness of the trained deep potential(DP) model was thoroughly evaluated through several aspects, including root-mean-square errors(RMSEs), energy and force data, and structural information comparison results;the results indicate the carefully trained DP model is reliable. The component and temperature dependence of the local structure in the Mg-La liquid alloy was analyzed. The effect of Mg content in the system on the first coordination shell of the atomic pairs is the same as that of temperature. The pre-peak demonstrated in the structure factor indicates the presence of a medium-range ordered structure in the Mg-La liquid alloy, which is particularly pronounced in the 80at% Mg system and disappears at elevated temperatures. The density, self-diffusion coefficient, and shear viscosity for the Mg-La liquid alloy were predicted via DPMD simulation, the evolution patterns with Mg content and temperature were subsequently discussed, and a database was established accordingly. Finally, the mixing enthalpy and elemental activity of the Mg-La liquid alloy at 1200 K were reliably evaluated,which provides new guidance for related studies.

关键词： magnesium-lanthanum liquid alloys local structure macroscopic properties thermodynamic behavior deep potential mo-lecular dynamic simulation

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