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Rock mass quality prediction on tunnel faces with incomplete multi-source dataset via tree-augmented naive Bayesian network

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International Journal of Mining Science and Technology 2024年第3期34卷 323-337页

作者： Hongwei Huang Chen Wu Mingliang Zhou Jiayao Chen Tianze Han le Zhang Key Laboratory of Geotechnical and Underground Engineering of Ministry of Education Tongji UniversityShanghai 200092China Department of Geotechnical Engineering Tongji UniversityShanghai 200092China School of Civil Engineering Beijing Jiaotong UniversityBeijing 100044China Qingdao Guoxin Second Jiaozhou Bay Subsea Tunnel Co. Ltd.Qingdao 266071China

Rock mass quality serves as a vital index for predicting the stability and safety status of rock tunnel *** tunneling practice,the rock mass quality is often assessed via a combination of qualitative and quantitative ***,due to the harsh on-site construction conditions,it is rather difficult to obtain some of the evaluation parameters which are essential for the rock mass quality *** this study,a novel improved Swin Transformer is proposed to detect,segment,and quantify rock mass characteristic parameters such as water leakage,fractures,weak *** site experiment results demonstrate that the improved Swin Transformer achieves optimal segmentation results and achieving accuracies of 92%,81%,and 86%for water leakage,fractures,and weak interlayers,respectively.A multisource rock tunnel face characteristic(RTFC)dataset includes 11 parameters for predicting rock mass quality is *** the limitations in predictive performance of incomplete evaluation parameters exist in this dataset,a novel tree-augmented naive Bayesian network(BN)is proposed to address the challenge of the incomplete dataset and achieved a prediction accuracy of 88%.In comparison with other commonly used Machine learning models the proposed BN-based approach proved an improved performance on predicting the rock mass quality with the incomplete *** utilizing the established BN,a further sensitivity analysis is conducted to quantitatively evaluate the importance of the various parameters,results indicate that the rock strength and fractures parameter exert the most significant influence on rock mass quality.

关键词： Rock mass quality Tunnel faces Incomplete multi-source dataset Improved Swin Transformer Bayesian networks

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Rethinking multi-spatial information for transferable adversarial attacks on speaker recognition systems

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CAAI Transactions on Intelligence Technology 2024年第3期9卷 620-631页

作者： Junjian Zhang Hao Tan le Wang Yaguan Qian Zhaoquan Gu Guangzhou University GuangzhouChina Department of New Networks Peng Cheng LaboratoryShenzhenChina Harbin Institute of Technology(Shenzhen) ShenzhenChina Zhejiang University of Science and Technology HangzhouChina

Adversarial attacks have been posing significant security concerns to intelligent systems,such as speaker recognition systems(SRSs).Most attacks assume the neural networks in the systems are known beforehand,while black-box attacks are proposed without such information to meet practical *** black-box attacks improve trans-ferability by integrating multiple models or training on multiple datasets,but these methods are *** by the optimisation strategy with spatial information on the perturbed paths and samples,we propose a Dual Spatial Momentum Iterative Fast Gradient Sign Method(DS-MI-FGSM)to improve the transferability of black-box at-tacks against ***,DS-MI-FGSM only needs a single data and one model as the input;by extending to the data and model neighbouring spaces,it generates adver-sarial examples against the integrating *** reduce the risk of overfitting,DS-MI-FGSM also introduces gradient masking to improve *** authors conduct extensive experiments regarding the speaker recognition task,and the results demonstrate the effectiveness of their method,which can achieve up to 92%attack success rate on the victim model in black-box scenarios with only one known model.

关键词： speaker recognition spoofing attacks

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A Novel Supercapacitor Degradation Prediction Using a 1D Convolutional Neural Network and Improved Informer Model

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Protection and Control of Modern Power Systems 2024年第4期9卷 51-68页

作者： Hao Zhang Zhenxiao Yi le Kang Yi Zhang Kai Wang the College of Materials Science and Engineering Xi’an University of Science and Technol-ogyXi’an 710054China the School of Electrical Engineering Qingdao UniversityQingdao 266071China the School of Energy Sciences and Engineering Nanjing Tech UniversityNanjing 211816China

Safety and reliability are crucial for the next-generation supercapacitors used in energy storage systems,while accurate prediction of the degradation trajectory and remaining useful life(RUL)is essential for analyzing degradation and evaluating performance in energy storage *** study proposes a novel data processing and improved one-dimensional convolutional neural network(1D CNN)-informer framework for robust RUL *** data preprocessing,all data from two structures are adjusted to a unified format,and cross-entropy loss is used to couple the 1D CNN and ***,the minimum-maximum feature scaling method is used for normalization to accelerate the training process in reaching the minimum cost function.A relative position encoding algorithm is introduced to improve the Informer model,enabling it to better learn the sequence relationships between data and effectively reduce prediction *** data in dif-ferent working conditions are used to validate the proposed *** with other existing methods,the maximum root mean square error is reduced by 32.71%,the mean absolute error is reduced by 28.50%,and R^(2) is increased by 4.79%.The strategy considers the complementarity between two single models,which can extract features and enrich local details,as well as enhance the model’s global perception *** experimental results demonstrate that the proposed model achieves high-precision and robust RUL prediction,thereby pro-moting the industrial application of supercapacitors.

关键词： Supercapacitors remaining useful life convolution neural network transformer informer

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Deep learning for broadleaf weed seedlings classification incorporating data variability and model flexibility across two contrasting environments

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Artificial Intelligence in Agriculture 2024年第2期12卷 29-43页

作者： Lorenzo león Cristóbal Campos Juan Hirzel Instituto de Investigaciones Agropecuarias(INIA) INIA QuilamapuAvda.Vicente Méndez 515ChillánChile Fundacion ObservatorioÑuble Arauco 340ChillanChile

The increasing deployment of deep learning models for distinguishing weeds and crops has witnessed notable strides in agricultural ***,a conspicuous gap endures in the literature concerning the training and testing of models across disparate environmental *** methodologies either delineate a single dataset distribution into training,validation,and testing subsets or merge datasets from diverse condi-tions or distributions before their division into the *** study aims to ameliorate this gap by extending to several broadleaf weed categories across varied distributions,evaluating the impact of training convolutional neural networks on datasets specific to particular conditions or distributions,and assessing their performance in entirely distinct settings through three *** evaluating diverse network architectures and training approaches(finetuning versus feature extraction),testing various architectures,employing different training strategies,and amalgamating data,we devised straightforward guidelines to ensure the model's deployability in contrasting environments with sustained precision and *** Experiment 1,conducted in a uniform environment,accuracy ranged from 80%to 100%across all models and training strategies,with finetune mode achieving a superior performance of 94%to 99.9%compared to the feature extraction mode at 80%to 92.96%.Experiment 2 underscored a significant performance decline,with accuracy fig-ures between 25%and 60%,primarily at 40%,when the origin of the test data deviated from the train and valida-tion *** 3,spotlighting dataset and distribution amalgamation,yielded promising accuracy metrics,notably a peak of 99.6%for ResNet in finetuning mode to a low of 69.9%for InceptionV3 in feature extraction *** pivotal findings emphasize that merging data from diverse distributions,coupled with finetuned training on advanced architectures like ResNet and MobileNet,markedly enhances

关键词： Artificial neural networks Deep learning Transfer learning Precision farming Feature extraction Finetuning Generalization Out-of-domain distribution Domain adaptation Multi-domain learning

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Metabolic basis of solute carrier transporters in treatment of type 2 diabetes mellitus

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Acta Pharmaceutica Sinica B 2024年第2期14卷 437-454页

作者： Jiamei le Yilong Chen Wei Yang Ligong Chen Jianping Ye Shanghai Key Laboratory of Molecular Imaging Zhoupu HospitalShanghai University of Medicine and Health SciencesShanghai 201318China School of Health Science and Engineering University of Shanghai for Science and TechnologyShanghai 200093China Metabolic Disease Research Center Zhengzhou Central Hospital Affiliated to Zhengzhou UniversityZhengzhou 450007China School of Pharmaceutical Sciences Tsinghua UniversityBeijing 100084China Research Center for Basic Medicine Academy of Medical SciencesZhengzhou UniversityZhengzhou 450052China

Solute carriers(SLCs) constitute the largest superfamily of membrane transporter *** transporters, present in various SLC families, play a vital role in energy metabolism by facilitating the transport of diverse substances, including glucose, fatty acids, amino acids, nucleotides, and *** actively participate in the regulation of glucose metabolism at various steps, such as glucose uptake(e.g., SLC2A4/GLUT4), glucose reabsorption(e.g., SLC5A2/SGLT2), thermogenesis(e.g., SLC25A7/UCP-1), and ATP production(e.g., SLC25A4/ANT1 and SLC25A5/ANT2). The activities of these transporters contribute to the pathogenesis of type 2 diabetes mellitus(T2DM). Notably, SLC5A2 has emerged as a valid drug target for T2DM due to its role in renal glucose reabsorption, leading to groundbreaking advancements in diabetes drug discovery. Alongside SLC5A2, multiple families of SLC transporters involved in the regulation of glucose homeostasis hold potential applications for T2DM therapy. SLCs also impact drug metabolism of diabetic medicines through gene polymorphisms, such as rosiglitazone(SLCO1B1/OATP1B1) and metformin(SLC22A1-3/OCT1-3 and SLC47A1, 2/MATE1, 2). By consolidating insights into the biological activities and clinical relevance of SLC transporters in T2DM, this review offers a comprehensive update on their roles in controlling glucose metabolism as potential drug targets.

关键词： Solute carriers(SLCs) Energ ymetabolism ATP production Type 2 diabetes mellitus(T2DM) Glucose homeostasis Polymorphisms

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An investigation on topologies of hybrid manifold,impinging-jet nozzle and micro-pin-fin heat sinks

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Science China(Technological Sciences) 2024年第4期67卷 1061-1076页

作者： SHI Qianlei YAO Xiaole LIU Qian QIN le JU Xing XU Chao Key Laboratory of Power Station Energy Transfer Conversion and System of MOE North China Electric Power UniversityBeijing 102206China

The hybrid manifold micro-pin-fin(MMPF)heat sink combined nozzle jets is an option for large-scale integrated circuits(LSI).The demond for uniform and ultra-high heat flux removal by MMPF heat sink has not been adequately *** work aims to solve the problem of fluid *** proposed basic tiling topologies,including square,regular hexagon,30°rhombus,and 60°rhombus topologies,provide different organized fluid flows and heat transfer *** present study focuses on comparing these topologies according to independent porous medium parameters,such as nozzle pore size D_(Z),flow pore size D_(X,Y),and porosityε.The results show that the square topology achieves the smallest total thermal resistance R_(tot)value of0.0975×10^(-4)K m^2/W,while the hexagon topology achieved the highest value of COP/?T,which was 2033.9 K^(-1).According to the sensitivity analysis results,the optimal total thermal resistance can be obtained by balancing the influences of nozzle pore size,flow pore size,and *** optimal pressure drop can be obtained by maximizing the porosity.

关键词： heat sink ultra-high heat flux manifold micro-pin-fin impinging-jet topology

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Quantitative evaluation of the contribution of underground space to urban resilience:A case study in China

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Underground Space 2024年第4期17卷 1-24页

作者： Si-Cong Liu Fang-le Peng Yong-Kang Qiao Yun-Hao Dong Research Center for Underground Space&Department of Geotechnical Engineering Tongji UniversityShanghai 200092China

Urban underground space(UUS)development has been acknowledged as a positive contribution to urban resilience(UR).Such contribution has been qualitatively addressed in recent years,but only quantitatively discussed in few *** evaluation methods for UR are widely used in China and around the world,but the role of underground space is barely *** paper provides a way to bridge this gap on the city scale.A UR evaluation framework was carefully constructed that covers the basic aspects and elements of *** contributions of UUS to UR were identified and integrated into the UR evaluation framework,and the measurement methods for each indicator related to UUS were determined.A case study of 19 sample cities in China were conducted using the integrated evaluation *** analysis and clustering analysis were further adopted to interpret the evaluation results,mainly with three indicators reflecting the level of UUS development,namely UUS area(m^(2)),UUS density(104 m^(2)/km^(2))and UUS area per capita(m^(2)/person).The results showed a strong correlation between UUS area and *** average proportion of UR provided by UUS in the 19 sample cities was 16.46%,while the maximum figure reached 29.20%.The sample cities were clustered into four categories based on the relationship between the proportion of UR provided by UUS,UUS area,and GDP per capita,where both high and low UUS area tend to provide less proportion of resilience than the medium UUS *** suggestions for UUS utilization were proposed to assist cities in achieving urban resilience.

关键词： Urban underground space(UUS) Urban resilience Resilience evaluation Resilient development

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Planning an adaptive reuse development of underutilized urban underground infrastructures:A case study of Qingdao,China

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Underground Space 2024年第1期14卷 18-33页

作者： Yong-Kang Qiao Fang-le Peng Yun-Hao Dong Chun-Fang Lu Research Center for Underground Space&Department of Geotechnical Engineering Tongji UniversityShanghai 200092China

Urban underground infrastructures(UUIs)are a vital component of built capital for urban ***,many cities are now home to a multitude of disused or underutilized UUIs,not least aged purpose-built underground facilities,causing a waste of valuable underground space resource *** the process of urban renewal,adaptive reuse can be an attractive solution to breathe new life into underutilized UUIs,while addressing some of the modern problems of the built environment by an economically feasible ***,there is a prevalent absence in the current literature of the overarching planning and decision-making approaches for an adaptive reuse development of underutilized *** the intention of addressing this shortfall,this paper first lays out development strategies,then sets the generic patterns for adaptive reuse of disused or underutilized *** the city of Qingdao,China as a case study,detailed planning and decision-making approaches with the aid of multi-source data and spatial analysis tools are *** is anticipated that the findings of this research will assist the adaptive reuse development of UUIs in providing theoretical guidance and empirical evidence,thereby enhancing the role of urban underground space use in contributing to urban revitalization and urban sustainability.

关键词： Urban underground infrastructures Underutilized Adaptive reuse Planning Urban renewal

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Polycomb and trithorax:Their yin-yang dynamics in plants

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Molecular Plant 2024年第6期17卷 845-847页

作者： Fan Xu Daolei Zhang Liang le Li Pu Biotechnology Research Institute Chinese Academy of Agricultural SciencesBeijing 100081China School of Life Science Inner Mongolia UniversityHohhot 010021China

Polycomb(PcG)and trithorax(trxG)are two groups of conserved epigenetic complexes that maintain active and repressive states of target genes by altering their chromatin states to regulate plant development and stress *... 详细信息

关键词： maintain complexes states

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Striking Stabilization Effect of Spinel Cobalt Oxide Oxygen Evolution Electrocatalysts in Neutral pH by Dual-Sites Iron Incorporation

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Energy & Environmental Materials 2024年第2期7卷 152-160页

作者： Shuairu Zhu Xue Wang Jiabo le Na An Jianming Li Deyu Liu Yongbo Kuang Key Laboratory of Advanced Fuel Cells and Electrolyzers Technology of Zhejiang Province Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences1219 Zhongguan West RoadNingbo 315201China Zhejiang Institute of Tianjin University 85 Zhongguan West RoadNingbo 315201China Research Center of New Energy Research Institute of Petroleum Exploration&Development20 Xueyuan RoadBeijing 100083China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences19(A)Yuquan RoadBeijing 100049China

Developing stable and efficient nonprecious-metal-based oxygen evolution catalysts in the neutral electrolyte is a challenging but essential goal for various electrochemical ***,cobalt-based spinels have drawn a considerable amount of attention but most of them operate in alkali ***,the frequently studied Co-Fe spinel system never exhibits appreciable stability in nonbasic conditions,not to mention attract further investigation on its key structural motif and transition states for activity ***,we report exceptional stable Co-Fe spinel oxygen evolution catalysts(~30%Fe is optimal)in a neutral electrolyte,owing to its unique metal ion arrangements in the crystal *** introduced iron content enters both the octahedral and tetrahedral sites of the spinel as Fe^(2+)and Fe^(3+)(with Co ions having mixed distribution as well).Combining density functional theory calculations,we find that the introduction of Fe to Co_(3)O_(4)lowers the covalency of metal-oxygen bonds and can help suppress the oxidation of Co^(2+/3+)and 0^(2-).It implies that the Co-Fe spinel will have minor surface reconstruction and less lattice oxygen loss during the oxygen evolution reaction process in comparison with Co_(3)O_(4)and hence show much better *** findings suggest that there is still much chance for the spinel structures,especially using reasonable sublattices engineering via multimetal doping to develop advanced oxygen evolution catalysts.

关键词： dual-sites iron electrocatalyst stability neutral electrolyte oxygen evolution reaction spinel oxides

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