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Unveiling the secrets of gastrointestinal mucous adenocarcinoma survival after surgery with artificial intelligence:A population-based study

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World Journal of Gastrointestinal Oncology 2024年第6期16卷 2404-2418页

作者： Jie Song Xiang-Xiu Yan Fang-Liang Zhang yong-yi lei Zi-yin Ke Fang Li Kai Zhang Yu-Qi He Wei Li Chao Li Yuan-Ming Pan Department of Gastroenterology Dongying People’s HospitalDongying Hospital of Shandong Provincial Hospital GroupDongying 257000Shandong ProvinceChina Gastrointestinal Surgery Department Suining Central HospitalSuining 629000Sichuan ProvinceChina Obstetrical Department Suining Central HospitalSuining 629000Sichuan ProvinceChina School of Medicine Shenzhen Campus of Sun Yat-sen UniversityShenzhen 518107Guangdong ProvinceChina Department of Pathology Aerospace Center HospitalPeking University Aerospace School of Clinical MedicineBeijing 100049China General Department Beijing Chest HospitalCapital Medical University/Beijing Tuberculosis and Thoracic Tumor Research InstituteBeijing 101149China Department of Gastroenterology Beijing Chest HospitalCapital Medical University/Beijing Tuberculosis and Thoracic Tumor Research InstituteBeijing 101149China Department of Thoracic Surgery Sichuan Academy of Medical Sciences and Sichuan Provincial People’s HospitalUniversity of Electronic Science and Technology of ChinaChengdu 610072Sichuan ProvinceChina Department of Gastroenterology Aerospace Center HospitalPeking University Aerospace School of Clinical MedicineBeijing 100049China Cancer Research Center Beijing Chest HospitalCapital Medical University/Beijing Tuberculosis and Thoracic Tumor Research InstituteBeijing 101149China

BACKGROUND Research on gastrointestinal mucosal adenocarcinoma(GMA)is limited and controversial,and there is no reference tool for predicting postoperative *** To investigate the prognosis of GMA and develop predictive *** From the Surveillance,Epidemiology,and End Results database,we collected clinical information on patients with *** random sampling,the patients were divided into the discovery(70%of the total,for model training),validation(20%,for model evaluation),and completely blind test cohorts(10%,for further model evaluation).The main assessment metric was the area under the receiver operating characteristic curve(AUC).All collected clinical features were used for Cox proportional hazard regression analysis to determine factors influencing GMA’s *** This model had an AUC of 0.7433[95% confidence intervals(95%CI):0.7424-0.7442]in the discovery cohort,0.7244(GMA:0.7234-0.7254)in the validation cohort,and 0.7388(95%CI:0.7378-0.7398)in the test *** packaged it into Windows software for doctors’use and uploaded *** gastric adenocarcinoma had the worst prognosis,and these were protective factors of GMA:Regional nodes examined[hazard ratio(HR):0.98,95%CI:0.97-0.98,P<0.001]and chemotherapy(HR:0.62,95%CI:0.58-0.66,P<0.001).CONCLUSION The deep learning-based tool developed can accurately predict the overall survival of patients with GMA *** surgery,chemotherapy,and adequate lymph node dissection during surgery can improve patient outcomes.

关键词： Deep learning Gastrointestinal mucous adenocarcinoma Overall survival Surgery Clinical tool

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Atomistic study on the microscopic mechanism of grain boundary embrittlement induced by small dense helium bubbles in iron

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Nuclear Science and Techniques 2024年第3期35卷 84-95页

作者： lei Peng yong-Jie Sun Jing-yi Shi yi-Fei Liu Shang-Ming Chen Liu-Liu Li State Key Laboratory of Particle Detection and Electronics University of Science and Technology of ChinaHefei 230026China School of Nuclear Science and Technology University of Science and Technology of ChinaHefei 230027China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of ChinaChengdu 610213China

The helium bubbles induced by 14 MeV neutron irradiation can cause intergranular fractures in reduced activation ferritic martensitic steel,which is a candidate structural material for fusion *** order to elucidate the susceptibility of different grain boundaries(GBs)to helium-induced embrittlement,the tensile fracture processes of 10 types of GBs with and without helium bubbles in body-centered cubic(bcc)iron at the relevant service temperature of 600 K were investigated via molecular dynamics *** results indicate that in the absence of helium bubbles,the GBs studied here can be classified into two distinct categories:brittle GBs and ductile *** atomic scale analysis shows that the plastic deformation of ductile GB at high temperatures originates from complex plastic deformation mechanisms,including the Bain/Burgers path phase transition and deformation twinning,in which the Bain path phase transition is the most dominant plastic deformation ***,the presence of helium bubbles severely inhibits the plastic deformation channels of the GBs,resulting in a significant decrease in elongation at *** bubble-decorated GBs,the ultimate tensile strength increases with the increase in the misorientation ***,the coherent twin boundary∑3{112}was found to maintain relatively high fracture strength and maximum failure strain under the influence of helium bubbles.

关键词： Helium bubble Grain boundary Embrittlement Reduced activation ferritic martensitic steel Molecular dynamics Bain path

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Metarelation2vec:A Metapath-Free Scalable Representation Learning Model for Heterogeneous Networks

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Tsinghua Science and Technology 2024年第2期29卷 553-575页

作者： lei Chen Yuan Li yong lei Xingye Deng School of Information and Electrical Engineering Hunan University of Science and TechnologyXiangtan 411201China School of Computer Science and Engineering Hunan University of Science and TechnologyXiangtan 411201China

Metapaths with specific complex semantics are critical to learning diverse semantic and structural information of heterogeneous networks(HNs)for most of the existing representation learning ***,any metapaths consisting of multiple,simple metarelations must be driven by domain *** sensitive,expensive,and limited metapaths severely reduce the flexibility and scalability of the existing models.A metapath-free,scalable representation learning model,called Metarelation2vec,is proposed for HNs with biased joint learning of all metarelations in a bid to address this ***,a metarelation-aware,biased walk strategy is first designed to obtain better training samples by using autogenerating cooperation probabilities for all metarelations rather than using expert-given ***,grouped nodes by the type,a common and shallow skip-gram model is used to separately learn structural proximity for each node ***,grouped links by the type,a novel and shallow model is used to separately learn the semantic proximity for each link ***,supervised by the cooperation probabilities of all meta-words,the biased training samples are thrown into the shallow models to jointly learn the structural and semantic information in the HNs,ensuring the accuracy and scalability of the *** experimental results on three tasks and four open datasets demonstrate the advantages of our proposed model.

关键词： metarelation random walk heterogeneous network metapath representation learning

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Availability evaluation of controller area networks under the influence of intermittent connection faults

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Frontiers of Information Technology & Electronic Engineering 2024年第4期25卷 555-568页

作者： Longkai WANG leiming ZHANG yong lei State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang UniversityHangzhou 310027China The 14th Research Institute of China Electronics Technology Group Corporation Nanjing 210039China

Controller area networks(CANs),as one of the widely used fieldbuses in the industry,have been extended to the automation field with strict standards for safety and *** practice,factors such as fatigue and insulation wear of the cables can cause intermittent connection(IC)faults to occur frequently in the CAN,which will affect the dynamic behavior and the safety of the ***,quantitatively evaluating the performance of the CAN under the influence of IC faults is crucial to real-time health monitoring of the *** this paper,a novel methodology is proposed for real-time quantitative evaluation of CAN availability when considering IC faults,with the system availability parameter being calculated based on the network state transition ***,the causal relationship between IC fault and network error response is constructed,based on which the IC fault arrival rate is ***,the states of the network considering IC faults are analyzed,and the deterministic and stochastic Petri net(DSPN)model is applied to describe the transition relationship of the ***,the parameters of the DSPN model are determined and the availability of the system is calculated based on the probability distribution and physical meaning of markings in the DSPN model.A testbed is constructed and case studies are conducted to verify the proposed methodology under various experimental *** results show that the estimation results obtained using the proposed method agree well with the actual values.

关键词： Controller area network Intermittent connection fault Arrival rate Deterministic and stochastic Petri net Availability evaluation

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An Encoding-Decoding Framework Based on CNN for circ RNA-RBP Binding Sites Prediction

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Chinese Journal of Electronics 2024年第1期33卷 256-263页

作者： Yajing GUO Xiujuan lei yi PAN School of Computer Science Shaanxi Normal University Faculty of Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of Sciences Department of Computer Science Georgia State University

Predicting RNA binding protein(RBP) binding sites on circular RNAs(circ RNAs) is a fundamental step to understand their interaction mechanism. Numerous computational methods are developed to solve this problem, but they cannot fully learn the features. Therefore, we propose circ-CNNED, a convolutional neural network(CNN)-based encoding and decoding framework. We first adopt two encoding methods to obtain two original matrices. We preprocess them using CNN before fusion. To capture the feature dependencies, we utilize temporal convolutional network(TCN) and CNN to construct encoding and decoding blocks, respectively. Then we introduce global expectation pooling to learn latent information and enhance the robustness of circ-CNNED. We perform circ-CNNED across 37 datasets to evaluate its effect. The comparison and ablation experiments demonstrate that our method is superior. In addition, motif enrichment analysis on four datasets helps us to explore the reason for performance improvement of circ-CNNED.

关键词： Proteins RNA Neural networks Encoding Robustness Decoding Convolutional neural networks

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Multiscale observation in wide-spatial radar surveillance based on coherent FDA design

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Science China(Information Sciences) 2024年第2期67卷 232-252页

作者： lei YU Feng HE yi SU College of Electronics Science National University of Defense Technology

Wide-spatial radar surveillance missions are challenging tasks, requiring an increased power budget and agility in transmission aimed at extracting information from multiple targets in different environments. These requirements necessitate high transmitting degrees of freedom(DOF) to achieve the objective of multiscale observation for specific tasks in specialized regions of interest. Herein, we exploit the multiscale observation ability in wide-spatial radar surveillance based on frequency diverse array(FDA)radar. The proposed method facilitates spatial anisotropic control of multiple radar resources, including the transmitting waveforms, beampattern, and bandwidth. By utilizing a coherent FDA radar, we offer principles for the selection of baseband waveforms, in addition to the quantitative design of the beampattern gain and optimal bandwidth from the perspective of detection. The feasibility of the proposed method is validated through numerical experiments, thus indicating the potential in wide-spatial radar surveillance. Moreover,this work can be regarded as a preliminary attempt to gauge the efficacy of the computational array, a novel academic concept.

关键词： multi-scale observation wide-spatial surveillance frequency diverse array (FDA) beampattern synthesis frequency diversity gain computational array

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Grain boundary engineering for enhancing intergranular damage resistance of ferritic/martensitic steel P92

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Nuclear Science and Techniques 2024年第5期35卷 186-199页

作者： lei Peng Shang-Ming Chen Jing-yi Shi yong-Jie Sun yi-Fei Liu yin-Zhong Shen Hong-Ya He Hui-Juan Wang Jie Tian State Key Laboratory of Particle Detection and Electronics University of Science and Technology of ChinaHefei 230026China School of Nuclear Science and Technology University of Science and Technology of ChinaHefei 230027China School of Materials Engineering Shanghai University of Engineering Science333 Long Teng RoadShanghai 201620China Experimental Center of Engineering and Material Science University of Science and Technology of ChinaHefei 230026China

Ferritic/martensitic(F/M)steel is widely used as a structural material in thermal and nuclear power ***,it is susceptible to intergranular damage,which is a critical issue,under service *** this study,to improve the resistance to intergranular damage of F/M steel,a thermomechanical process(TMP)was employed to achieve a grain boundary engineering(GBE)microstructure in F/M steel *** TMP,including cold-rolling thickness reduction of 6%,9%,and 12%,followed by austenitization at 1323 K for 40 min and tempering at 1053 K for 45 min,was applied to the as-received(AR)P92 *** prior austenite grain(PAG)size,prior austenite grain boundary character distribution(GBCD),and connectivity of prior austenite grain boundaries(PAGBs)were *** to the AR specimen,the PAG size did not change *** fraction of coincident site lattice boundaries(CSLBs,3≤Σ≤29)and Σ3^(n) boundaries along PAGBs decreased with increasing reduction ratio because the recrystallization fraction increased with increasing reduction *** PAGB connectivity of the 6%deformed specimen slightly deteriorated compared with that of the AR ***,potentiodynamic polarization studies revealed that the intergranular damage resistance of the studied steel could be improved by increasing the fraction of CSLBs along the PAGBs,indicating that the TMP,which involves low deformation,could enhance the intergranular damage resistance.

关键词： Grain boundary engineering Ferritic/martensitic steel Prior austenite grain boundary character distribution Grain boundary connectivity Intergranular damage resistance

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Fatigue-resistant Hydrogels

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Chemical Research in Chinese Universities 2024年第1期40卷 64-77页

作者： LI Luofei lei Hai CAO yi Collaborative Innovation Center of Advanced Microstructures National Laboratory of Solid State MicrostructureDepartment of PhysicsNanjing UniversityNanjing 210093P.R.China Department of Physics Zhejiang UniversityHangzhou 310027P.R.China

Hydrogels have been extensively studied for applications in various fields, such as tissue engineering and soft robotics, as determined by their mechanical properties. The mechanical design of hydrogels typically focuses on the modulus, toughness, and deformability. These characteristics play important roles and make great achievements for hydrogel use. In recent years, a growing body of research has concentrated on the fatigue property of hydrogels, which determines their resistance to crack propagation in the networks during cyclic mechanical loads for applications. However, knowledge of hydrogel fatigue behavior remains notably deficient. Here, we present a brief overview of the fatigue behavior of hydrogels, encompassing the general experimental methods to measure the fatigue property and fundamental theoretical calculation models. Then, we highlight multiple strategies to enhance the fatigue resistance of hydrogels. Finally, we present our perspectives on fatigue-resistant hydrogels, outstanding challenges and potential directions for future research.

关键词： Hydrogel Fatigue-resistant Fracture

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Improved multi-scale inverse bottleneck residual network based on triplet parallel attention for apple leaf disease identification

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Journal of Integrative Agriculture 2024年第3期23卷 901-922页

作者： lei Tang Jizheng yi Xiaoyao Li College of Computer&Information Engineering Central South University of Forestry and TechnologyChangsha 410004China Yuelushan Laboratory Carbon Sinks Forests Variety Innovation Center Changsha 410000China

Accurate diagnosis of apple leaf diseases is crucial for improving the quality of apple production and promoting the development of the apple industry. However, apple leaf diseases do not differ significantly from image texture and structural information. The difficulties in disease feature extraction in complex backgrounds slow the related research progress. To address the problems, this paper proposes an improved multi-scale inverse bottleneck residual network model based on a triplet parallel attention mechanism, which is built upon ResNet-50, while improving and combining the inception module and ResNext inverse bottleneck blocks, to recognize seven types of apple leaf(including six diseases of alternaria leaf spot, brown spot, grey spot, mosaic, rust, scab, and one healthy). First, the 3×3 convolutions in some of the residual modules are replaced by multi-scale residual convolutions, the convolution kernels of different sizes contained in each branch of the multi-scale convolution are applied to extract feature maps of different sizes, and the outputs of these branches are multi-scale fused by summing to enrich the output features of the images. Second, the global layer-wise dynamic coordinated inverse bottleneck structure is used to reduce the network feature loss. The inverse bottleneck structure makes the image information less lossy when transforming from different dimensional feature spaces. The fusion of multi-scale and layer-wise dynamic coordinated inverse bottlenecks makes the model effectively balances computational efficiency and feature representation capability, and more robust with a combination of horizontal and vertical features in the fine identification of apple leaf diseases. Finally, after each improved module, a triplet parallel attention module is integrated with cross-dimensional interactions among channels through rotations and residual transformations, which improves the parallel search efficiency of important features and the recogniti

关键词： multi-scale module inverse bottleneck structure triplet parallel attention apple leaf disease

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Dynamic multifunctional metasurfaces:an inverse design deep learning approach

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Photonics Research 2024年第1期12卷 123-133页

作者： ZHI-DAN lei yi-DUO XU CHENG lei YAN ZHAO DU WANG The Institute of Technological Sciences Wuhan UniversityWuhan 430072China College of Materials Science and Engineering Sichuan UniversityChengdu 610065China

Optical metasurfaces(OMs)offer unprecedented control over electromagnetic waves,enabling advanced optical *** emergence of deep learning has opened new avenues for designing ***,existing deep learning methods for OMs primarily focus on forward design,which limits their design capabilities,lacks global optimization,and relies on prior ***,most OMs are static,with fixed functionalities once *** overcome these limitations,we propose an inverse design deep learning method for dynamic *** approach comprises a forward prediction network and an inverse retrieval *** forward prediction network establishes a mapping between meta-unit structure parameters and reflectance *** inverse retrieval network generates a library of meta-unit structure parameters based on target requirements,enabling end-to-end design of *** incorporating the dynamic tunability of the phase change material Sb2Te3with inverse design deep learning,we achieve the design and verification of dynamic multifunctional *** results demonstrate OMs with multiple information channels and encryption capabilities that can realize multiple physical field optical modulation *** Sb2Te3is in the amorphous state,near-field nano-printing based on meta-unit amplitude modulation is achieved for X-polarized incident light,while holographic imaging based on meta-unit phase modulation is realized for circularly polarized *** the crystalline state,the encrypted information remains secure even with the correct polarization input,achieving double *** research points towards ultra-compact,high-capacity,and highly secure information storage approaches.

关键词： polarization inverse approach

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