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Deep learning CNN-APSO-LSSVM hybrid fusion model for feature optimization and gas-bearing prediction

Petroleum Science 2024年第4期21卷 2329-2344页

作者： Jiu-Qiang Yang Nian-Tian Lin kai zhang Yan Cui Chao Fu Dong zhang College of Earth Sciences and Engineering Shandong University of Science and Technology Laboratory for Marine Mineral Resources Qingdao National Laboratory for Marine Science and Technology Transportation Institute of Inner Mongolia University Key Laboratory of Gas Hydrate Qingdao Institute of Marine Geology Ministry of Natural Resources

Conventional machine learning(CML) methods have been successfully applied for gas reservoir prediction. Their prediction accuracy largely depends on the quality of the sample data; therefore, feature optimization of the input samples is particularly important. Commonly used feature optimization methods increase the interpretability of gas reservoirs; however, their steps are cumbersome, and the selected features cannot sufficiently guide CML models to mine the intrinsic features of sample data efficiently. In contrast to CML methods, deep learning(DL) methods can directly extract the important features of targets from raw data. Therefore, this study proposes a feature optimization and gas-bearing prediction method based on a hybrid fusion model that combines a convolutional neural network(CNN)and an adaptive particle swarm optimization-least squares support vector machine(APSO-LSSVM). This model adopts an end-to-end algorithm structure to directly extract features from sensitive multicomponent seismic attributes, considerably simplifying the feature optimization. A CNN was used for feature optimization to highlight sensitive gas reservoir information. APSO-LSSVM was used to fully learn the relationship between the features extracted by the CNN to obtain the prediction results. The constructed hybrid fusion model improves gas-bearing prediction accuracy through two processes of feature optimization and intelligent prediction, giving full play to the advantages of DL and CML methods. The prediction results obtained are better than those of a single CNN model or APSO-LSSVM model. In the feature optimization process of multicomponent seismic attribute data, CNN has demonstrated better gas reservoir feature extraction capabilities than commonly used attribute optimization methods. In the prediction process, the APSO-LSSVM model can learn the gas reservoir characteristics better than the LSSVM model and has a higher prediction accuracy. The constructed CNN-APSO-LSSVM mode

关键词： Multicomponent seismic data Deep learning Adaptive particle swarm optimization Convolutional neural network Least squares support vector machine Feature optimization Gas-bearing distribution prediction

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A Survey on Blockchain-Based Federated Learning:Categorization,Application and Analysis

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 2451-2477页

作者： Yuming Tang Yitian zhang Tao Niu zhen Li Zijian zhang Huaping Chen Long zhang School of Cyberspace Science&Technology Beijing Institute of TechnologyBeijing100081China School of Computer Science&Technology Beijing Institute of TechnologyBeijing100081China Southeast Institute of Information Technology Beijing Institute of TechnologyPutian351100China Qianxin Technology Group Co. Ltd.Beijing100044China

Federated Learning(FL),as an emergent paradigm in privacy-preserving machine learning,has garnered significant interest from scholars and engineers across both academic and industrial *** its innovative approach to model training across distributed networks,FL has its vulnerabilities;the centralized server-client architecture introduces risks of single-point ***,the integrity of the global model—a cornerstone of FL—is susceptible to compromise through poisoning attacks by malicious *** attacks and the potential for privacy leakage via inference starkly undermine FL’s foundational privacy and security *** these reasons,some participants unwilling use their private data to train a model,which is a bottleneck in the development and industrialization of federated *** technology,characterized by its decentralized ledger system,offers a compelling solution to these *** inherently prevents single-point failures and,through its incentive mechanisms,motivates participants to contribute computing ***,blockchain-based FL(BCFL)emerges as a natural progression to address FL’s *** study begins with concise introductions to federated learning and blockchain technologies,followed by a formal analysis of the specific problems that FL *** discusses the challenges of combining the two technologies and presents an overview of the latest cryptographic solutions that prevent privacy leakage during communication and incentives in *** addition,this research examines the use of BCFL in various fields,such as the Internet of Things and the Internet of ***,it assesses the effectiveness of these solutions.

关键词： Federated learning blockchain privacy-preserving

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Key progresses of MOE key laboratory of macromolecular synthesis and functionalization in 2022

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Chinese Chemical Letters 2024年第3期35卷 114-126页

作者： Xumeng Deng kaihao Chen kai Pang Xiaoting Liu Minsong Gao Jie Ren Guanwen Yang Guangpeng Wu Chengjian zhang Xufeng Ni Peng zhang Jian Ji Jianzhao Liu zhengwei Mao Ziliang Wu zhen Xu Haoke zhang Hanying Li MOE Key Laboratory of Macromolecular Synthesis and Functionalization International Research Center for X PolymersDepartment of Polymer Science and EngineeringZhejiang UniversityHangzhou 310027China

In 2022,The MOE Key Laboratory of Macromolecular Synthesis and Functionalization in Zhejiang University had achieved several important ***,a series of well-defined dinuclear organoboron catalysts were developed to precisely control the enchainment of ether and carbonate segments during the copolymerization of CO_(2)and ***,polyester had been synthesized through cationic copolymerization of cyclic ***,ring-opening polymerization of carbon dioxide based valerolactone had been achieved,revealing the prospect of 3-ethylidene-6-vinyltetrahydro-2H-pyran-2-one(EVL)in utilizing CO_(2)and synthesizing functional ***,machine learning methods have been applied to biomaterial research,enabling high-throughput screening of functional biomaterial surfaces for implantable devices,and searching for potent antimicrobial peptides in whole combinatorial peptide ***,methods of characterization of biomacromolecule RNA transcription and manipulation of nucleoside modification were ***,artificial enzymes-armed Bifidobacterium Longum probiotics were established to tune down gut ***,three-dimensional(3D)printing technologies were used to engineer tough supramolecular ***,hydroplastic foaming graphene frameworks for acoustic and conductive polymer composites were provided for ***,aggregate photophysics about the nature of through-space interactions(TSIs)and manipulating their strength in small molecules with non-conjugated structure had been ***,the forming mechanism of a newfound nested texture in poly(L-lactic acid)(PLLA)spherulitic films had been ***,the isotropically dyeing mechanism of KDP single crystals grown from hydrogels have been *** related works are reviewed in this paper.

关键词： Polymer Catalyst Biomaterial research mRNA Hydrogel Graphene Crystal

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City Network Evolution Characteristics of Smart Industry: Evidence from Yangtze River Delta, China

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Chinese Geographical Science 2024年第5期34卷 829-848页

作者： SHEN Lizhen ZHONG Zhaocheng CHEN Cheng zhang Shanqi zhen Feng School of Architecture and Urban Planning Nanjing UniversityNanjing 210093China Hefei Urban Planning&Design Institute Hefei 230041China

The dual-path model of industrial evolution and spatial progression has been widely acknowledged and incorporated into the strategic planning to promote the development of urban industries and regional ***,current research on inter-enter-prise city networks mainly focuses on the single sector of flows on all enterprise branches,such as product value chains and production factors,but neglects that of particular industry *** upon the new economic geography and city networks theory,this paper develops a methodological framework that focuses on the analysis of city network evolution characteristics of smart ***-larly,a conceptual model of smart industry enterprise-industry-city is proposed and then applied to a case study of smart industry in the Yangtze River Delta Region,*** enterprise supplier-customer data,a city network of smart industry is constructed and sub-sequently analyzed with the proposed *** indicate that the smart industry network in Yangtze River Delta Region exhibits a hierarchical structure and the expansion of the network presents a small-world network *** study not only makes a meth-odological contribution for revealing the industrial and spatial evolution path of the current smart industry,but also provides empirical support for the formulation of new economic development policies focused on smart industries,demonstrating the role of city clusters as carriers of regional synergistic development.

关键词： smart industry city networks social network analysis methodological framework Yangtze River Delta,China

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Earth-abundant Zn-dipyrrin chromophores for efficient CO2 photoreduction

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National Science Review 2024年第6期11卷 214-222页

作者： Song Guo Fu-Gui Zeng Xiao-Di Li kai-kai Chen Ping Wang Tong-Bu Lu Zhi-Ming zhang Institute for New Energy Materials and Low Carbon Technologies School of Materials Science& Engineering Tianjin University of Technology

The development of strong sensitizing and Earth-abundant antenna molecules is highly desirable for CO2reduction through artificial photosynthesis. Herein, a library of Zn–dipyrrin complexes（Z-1-Z-6） are rationally designed via precisely controlling their molecular configuration to optimize strong sensitizing Earth-abundant photosensitizers. Upon visible-light excitation, their special geometry enables intramolecular charge transfer to induce a charge-transfer state, which was first demonstrated to accept electrons from electron donors. The resulting long-lived reduced photosensitizer was confirmed to trigger consecutive intermolecular electron transfers for boosting CO2-to-CO conversion. Remarkably, the Earth-abundant catalytic system with Z-6 and Fe-catalyst exhibits outstanding performance with a turnover number of >20 000 and 29.7% quantum yield, representing excellent catalytic performance among the molecular catalytic systems and highly superior to that of noble-metal photosensitizer Ir（ppy）2（bpy）+under similar conditions. Experimental and theoretical investigations comprehensively unveil the structure–activity relationship, opening up a new horizon for the development of Earth-abundant strong sensitizing chromophores for boosting artificial photosynthesis.

关键词： Zn complex photocatalysis CO2 reduction charge transfer photosensitizer

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Single-atom Ni-N_(4) for enhanced electrochemical sensing

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Nano Research 2024年第8期17卷 7658-7664页

作者： Zhuhui Qin Bo Tang Guiru zhang Chongqing Zhu Kun Jiang Bowei zhang Fu-zhen Xuan Shanghai Key Laboratory of Intelligent Sensing and Detection Technology East China University of Science and TechnologyShanghai 200237China Key Laboratory of Pressure Systems and Safety of Ministry of Education East China University of Science and TechnologyShanghai 200237China School of Mechanical and Power Engineering East China University of Science and TechnologyShanghai 200237China Key Laboratory of Theoretical and Computational Photochemistry Ministry of EducationCollege of ChemistryBeijing Normal UniversityBeijing 100875China Interdisciplinary Research Center School of Mechanical EngineeringShanghai Jiao Tong UniversityShanghai 200240China

Single-atom catalysts(SACs)attract widespread attention in heterogeneous catalysis due to their maximum atomic utilization efficiency and unique physical and chemical ***,their applications in chemical sensing keep huge potential but remain ***,a Ni-N_(4)-C SAC was synthesized for the trace detection of dopamine(DA)and uric acid(UA).The Ni-N_(4)-C SAC exhibited superior sensing performance compared to the Ni *** detection range for DA and UA were 0.05–75μM and 5–90μM with detection limits of 0.027 and 0.82μM,*** functional theory(DFT)computations indicate that Ni-N_(4)-C has a lower reaction barrier during electrochemical process,indicating that the atomic Ni sites possess higher intrinsic activity than Ni ***,DA and UA show strong potential dependency on the Ni-N_(4)-C catalyst,indicating its applicability for their concurrent *** work extends the application of SACs in chemical sensing.

关键词： single-atom catalysts chemical sensing dopamine uric acid

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Management of triplet excitons transition:fine regulation of Förster and dexter energy transfer simultaneously

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Light(Science & Applications) 2024年第2期13卷 302-315页

作者： Jiaqiang Wang Yujie Yang Xinnan Sun Xiaoning Li Liyao zhang zhen Li Institute of Molecular Aggregation Science Tianjin UniversityTianjin300072China School of Life Sciences Tianjin UniversityTianjin300072China Hubei Key Lab on Organic and Polymeric Opto-Electronic Materials Department of ChemistryWuhan UniversityWuhan430072China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan430072China Joint School of National University of Singapore Tianjin UniversityInternational Campus of Tianjin UniversityBinhai New CityFuzhou350207China

Understanding and management of triplet excitons transition in the same molecule remain a great ***,for the first time,by host engineering,manageable transitions of triplet excitons in a naphthalimide derivative NDOH were achieved,and monitored through the intensity ratio(ITADF/IRTP)between thermally activated delayed fluorescence(TADF)and room-temperature phosphorescence(RTP).Energy differences between lowest triplet excited states of host and guest were changed from 0.03 to 0.17 eV,and ITADF/IRTP of NDOH decreased by 200 times,thus red shifting the afterglow *** was proposed that shorter conjugation length led to larger band gaps of host materials,thus contributing to efficient Dexter and inefficient Förster energy ***,no transition to singlet state and only strongest RTP with quantum yield of 13.9%could be observed,when PBNC with loosest stacking and largest band gap acted as *** work provides novel insight for the management and prediction of triplet exciton transitions and the development of smart afterglow materials.

关键词： materials transition transitions

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Effects of Heat Transfer on Laminar-to-Turbulent Transition over a Compressor Blade Operating at Low Reynolds Number

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Journal of Thermal Science 2024年第5期33卷 1826-1838页

作者： LU Lehan WANG Mingyang zhang Yanfeng SUN Shuang HUANG zhen WANG Maomao Department of aviation Engineering Civil Aviation University of ChinaTianjin 300300China Institute of Engineering Thermophysics Chinese Academy of SciencesBeijing 100190China State Key Laboratory of Aerodynamics CARDCMianyang 621000China

To control the transition process in a laminar separation bubble(LSB)over an ultra-high load compressor blade at a Re of 1.5×10^(5),the effects of wall heat transfer were considered and numerically investigated by large eddy simulations(LES).Compared with the adiabatic wall condition,the local kinematic viscosity of airflow was reduced by wall cooling;thus the effects of turbulent dissipation on the growth of fluctuations were *** such,the transition occurred much earlier,and the size of LSB became *** the cooled surface,the spanwise vortices deformed much more rapidly and the size of hairpin vortex structures was ***,the rolling-up of 3D hairpin vortices and the ejection and sweeping process very close to the blade surface was ***,the aerodynamic losses of the compressor blade were reduced by 18.2%and 38.4%for the two cooled wall *** results demonstrated the feasibility of wall cooling in controlling the transition within an LSB and reducing the aerodynamic loss of an ultra-highly loaded compressor blade.

关键词： heat transfer compressor blade laminar-to-turbulent transition loss generation

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S-scheme regulated Ni_(2)P-NiS/twinned Mn_(0.5)Cd_(0.5)S hetero-homojunctions for efficient photocatalytic H_(2)evolution

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Journal of Materials Science & Technology 2024年第2期169卷 148-157页

作者： Qiqi zhang zhen Wang Yuhang Song Jun Fan Tao Sun Enzhou Liu School of Chemical Engineering/Xi’an Key Laboratory of Special Energy Materials Northwest UniversityXi’an 710069China

Effective bulk phase and surface charge separation is critical for charge utilization during the photo-catalytic energy conversion *** this work,the ternary Ni_(2)P-NiS/twinned Mn_(0.5)Cd_(0.5)S(T-MCS)nanohybrids were successfully constructed via combining Ni_(2)P-NiS with T-MCS solid solution for visible light photocatalytic H_(2)evolution.T-MCS is composed of zinc blende Mn_(0.5)Cd_(0.5)S(ZB-MCS)and wurtzite Mn_(0.5)Cd_(0.5)S(WZ-MCS)and those two alternatively arranged crystal phases endow T-MCS with excellent bulk phase charge separation performance for the slight energy level difference between ZB-MCS and WZ-MCS.S-scheme carriers transfer route between NiS and T-MCS can accelerate the interfacial charge separation and retain the active electrons and holes,meanwhile,co-catalyst Ni_(2)P as electron receiver and proton reduction center can further optimize the H_(2)evolution reaction kinetics based on the surface Schottky barrier *** above-formed homo-heterojunctions can establish multiple charge transfer channels in the bulk phase of T-MCS and interface of T-MCS and Ni_(2)*** the synergistic effect of twinned homojunction,S-scheme heterojunction,and Schottky barrier,the ternary Ni_(2)P-NiS/T-MCS com-posite manifested an H_(2)production rate of 122.5 mmol h^(-1)g^(-1),which was 1.33,1.24,and 2.58 times higher than those of the NiS/T-MCS(92.4 mmol h^(-1)g^(-1)),Ni_(2)P/T-MCS(98.4 mmol h^(-1)g^(-1)),and T-MCS(47.5 mmol h^(-1)g^(-1)),*** work demonstrates a promising strategy to develop efficient sul-fides photocatalyst toward targeted solar-driven H_(2)evolution through homo-heterojunction engineering.

关键词： Photocatalytic H_(2)evolution Twinned Mn_(0.5)Cd_(0.5)S Homojunction S-scheme heterojunction Schottky barrier

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Enhancing flotation recovery of residual carbon from gasification waste by mixing hydrophobic powder with diesel as collector

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Particuology 2024年第6期89卷 211-217页

作者： Rui Han Ningning zhang Anning Zhou zhen Li Jinzhou Qu Hong Wang College of Chemistry and Chemical Engineering Xi’an University of Science and TechnologyXi’anShaanxi 710054China

Coal gasification fine slag(CGFS)is a solid waste containing residual carbon and ash generated during the coal gasification process,and the separation of the two components is the essential way to realize its environmental pollution reduction and resource value *** flotation is the preferred method for separating CGFS,but there is a barrier of low carbon recovery in this process due to the extensive adsorption of collector by the well-developed pores on residual *** this study,a sufficiently simple yet innovative collector,a mixture of hydrophobic powder and diesel,was proposed in an attempt to break the *** experiments with common diesel and this novel collector were performed respectively,and FTIR,XPS,and SEM-EDX were employed to analyze the collector action *** results revealed that the novel collector could significantly improve the residual carbon recovery;test results demonstrated that the novel collector could increase the hydrophobic functional group content on the fine slag surface,and the hydrophobic powders in this novel collector mainly appeared at the pore openings of the flotation *** essence of the mechanism is that the hydrophobic powders play a dual role of blocking pores and providing adsorption sites,thus facilitating the spreading of diesel on the carbon surface and promoting its *** study can provide creative ideas for the efficient disposal of coal gasification waste.

关键词： Coal gasification fine slag Carbon recovery Collector Fotation Hydrophobic powder

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