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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

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

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 recognition rate of the network with relatively small com

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 multiplexing.The emergence of deep learning has opened new avenues for designing OMs.However,existing deep learning methods for OMs primarily focus on forward design,which limits their design capabilities,lacks global optimization,and relies on prior knowledge.Additionally,most OMs are static,with fixed functionalities once processed.To overcome these limitations,we propose an inverse design deep learning method for dynamic OMs.Our approach comprises a forward prediction network and an inverse retrieval network.The forward prediction network establishes a mapping between meta-unit structure parameters and reflectance spectra.The inverse retrieval network generates a library of meta-unit structure parameters based on target requirements,enabling end-to-end design of OMs.By incorporating the dynamic tunability of the phase change material Sb2Te3with inverse design deep learning,we achieve the design and verification of dynamic multifunctional OMs.Our results demonstrate OMs with multiple information channels and encryption capabilities that can realize multiple physical field optical modulation functions.When 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 light.In the crystalline state,the encrypted information remains secure even with the correct polarization input,achieving double encryption.This research points towards ultra-compact,high-capacity,and highly secure information storage approaches.

关键词： polarization inverse approach

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Vibration attenuation performance of wind turbine tower using a prestressed tuned mass damper under seismic excitation

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Earthquake Engineering and Engineering Vibration 2024年第2期23卷 511-524页

作者： lei Zhenbo Liu Gang Wang Hui Hui yi School of Civil Engineering Chongqing UniversityChongqing 400045China Key Laboratory of New Technology for Construction of Cities in Mountain Area Chongqing UniversityMinistry of EducationChongqing 400045China

With the rapid development of large megawatt wind turbines,the operation environment of wind turbine towers(WTTs)has become increasingly complex.In particular,seismic excitation can create a resonance response and cause excessive vibration of the WTT.To investigate the vibration attenuation performance of the WTT under seismic excitations,a novel passive vibration control device,called a prestressed tuned mass damper(PS-TMD),is presented in this study.First,a mathematical model is established based on structural dynamics under seismic excitation.Then,the mathematical analytical expression of the dynamic coefficient is deduced,and the parameter design method is obtained by system tuning optimization.Next,based on a theoretical analysis and parameter design,the numerical results showed that the PS-TMD was able to effectively mitigate the resonance under the harmonic basal acceleration.Finally,the time-history analysis method is used to verify the effectiveness of the traditional pendulum tuned mass damper(PTMD)and the novel PS-TMD device,and the results indicate that the vibration attenuation performance of the PS-TMD is better than the PTMD.In addition,the PS-TMD avoids the nonlinear effect due to the large oscillation angle,and has the potential to dissipate hysteretic energy under seismic excitation.

关键词： wind turbine tower prestressed tuned mass damper vibration control seismic excitation numerical simulation

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Molecular Generation and Optimization of Molecular Properties Using a Transformer Model

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Big Data Mining and Analytics 2024年第1期7卷 142-155页

作者： Zhongyin Xu Xiujuan lei Mei Ma yi Pan School of Computer Science Shaanxi Normal UniversityXi'an 710119China Faculty of Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China

Generating novel molecules to satisfy specific properties is a challenging task in modern drug discovery,which requires the optimization of a specific objective based on satisfying chemical rules.Herein,we aim to optimize the properties of a specific molecule to satisfy the specific properties of the generated molecule.The Matched Molecular Pairs(MMPs),which contain the source and target molecules,are used herein,and logD and solubility are selected as the optimization properties.The main innovative work lies in the calculation related to a specific transformer from the perspective of a matrix dimension.Threshold intervals and state changes are then used to encode logD and solubility for subsequent tests.During the experiments,we screen the data based on the proportion of heavy atoms to all atoms in the groups and select 12365,1503,and 1570 MMPs as the training,validation,and test sets,respectively.Transformer models are compared with the baseline models with respect to their abilities to generate molecules with specific properties.Results show that the transformer model can accurately optimize the source molecules to satisfy specific properties.

关键词： molecular optimization transformer Matched Molecular Pairs(MMPs) logD solubility

NOX4 promotes tumor progression through the MAPK-MEK1/2-ERK1/2 axis in colorectal cancer

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World Journal of Gastrointestinal Oncology 2024年第4期16卷 1421-1436页

作者： Yu-Jie Xu Ya-Chang Huo Qi-Tai Zhao Jin-Yan Liu yi-Jun Tian lei-lei Yang yi Zhang Biotherapy Center and Cancer Center The First Affiliated Hospital of Zhengzhou UniversityZhengzhou 450052Henan ProvinceChina Department of Oncology Henan Provincial People’s HospitalPeople’s Hospital of Zhengzhou UniversityPeople’s Hospital of Henan UniversityZhengzhou 450003Henan ProvinceChina

BACKGROUND Metabolic reprogramming plays a key role in cancer progression and clinical outcomes;however,the patterns and primary regulators of metabolic reprogramming in colorectal cancer(CRC)are not well understood.AIM To explore the role of nicotinamide adenine dinucleotide phosphate oxidase 4(NOX4)in promoting progression of CRC.METHODS We evaluated the expression and function of dysregulated and survival-related metabolic genes using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes.Consensus clustering was used to cluster CRC based on dysregulated metabolic genes.A prediction model was constructed based on survival-related metabolic genes.Sphere formation,migration,invasion,proliferation,apoptosis and clone formation was used to evaluate the biological function of NOX4 in CRC.mRNA sequencing was utilized to explore the alterations of gene expression NOX4 over-expression tumor cells.In vivo subcutaneous and lung metastasis mouse tumor model was used to explore the effect of NOX4 on tumor growth.RESULTS We comprehensively analyzed 3341 metabolic genes in CRC and identified three clusters based on dysregulated metabolic genes.Among these genes,NOX4 was highly expressed in tumor tissues and correlated with worse survival.In vitro,NOX4 overexpression induced clone formation,migration,invasion,and stemness in CRC cells.Furthermore,RNA-sequencing analysis revealed that NOX4 overexpression activated the mitogen-activated protein kinase-MEK1/2-ERK1/2 signaling pathway.Trametinib,a MEK1/2 inhibitor,abolished the NOX4-mediated tumor progression.In vivo,NOX4 overexpression promoted subcutaneous tumor growth and lung metastasis,whereas trametinib treatment can reversed the metastasis.CONCLUSION Our study comprehensively analyzed metabolic gene expression and highlighted the importance of NOX4 in promoting CRC metastasis,suggesting that trametinib could be a potential therapeutic drugs of CRC clinical therapy targeting NOX4.

关键词： Colorectal cancer Metabolic reprogramming Metastasis Nicotinamide adenine dinucleotide phosphate oxidase 4 Mitogen-activated protein kinase signaling

IoV environment exploring coordination:A federated learning approach

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Digital Communications and Networks 2024年第1期10卷 135-141页

作者： Tong Ding lei Liu yi Zhu Lizhen Cui Zhongmin Yan School of Software Shandong UniversityJinan250101China

Exploring open fields with coordinated unmanned vehicles is popular in academia and industries.One of the most impressive applicable approaches is the Internet of Vehicles(lov).The IoV connects vehicles,road infrastructures and communication facilities to provide solutions for exploration tasks.However,the coordination of acquiring information from multi-vehicles may risk data privacy.To this end,sharing high-quality experiences instead of raw data has become an urgent demand.This paper employs a Deep Reinforcement Learning(DRL)method to enable IoVs to generate training data with prioritized experience and states,which can support the IoV to explore the environment more efficiently.Moreover,a Federated Learning(FL)experience sharing model is established to guarantee the vehicles'privacy.The numerical results show that the proposed method presents a better successful sharing rate and a more stable convergence within the comparison of fundamental methods.The experiments also suggest that the proposed method could support agents without full information to achieve the tasks.

关键词： Internet of vehicle Deep reinforcement learning Federated learning Data privacy

Microstructure and mechanical properties of Ti/Al/Ti clad plates prepared via powder-in-tube method

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Journal of Iron and Steel Research(International) 2024年第3期31卷 670-687页

作者： Xian-lei Hu Qin-cheng Xie yi Yuan ying Zhi State Key Laboratory of Rolling and Automation Northeastern UniversityShenyang 110819LiaoningChina Suzhou Dongbao Haixing Metal Material Technology Co. Ltd.Suzhou 215600JiangsuChina School of Material Science and Engineering Northeastern UniversityShenyang 110819LiaoningChina

The Ti/Al/Ti clad plates exhibit a broad spectrum of potential applications.However,the conventional techniques of hot-pressing composite and explosive composite are intricate and environmentally hazardous.A novel method was introduced for preparing clad plates,namely,the powder-in-tube method.This method involves a combination of cold rolling,annealing at a temperature of 550℃,and double rolling.The morphology of the intermetallic compound layer was analyzed through the utilization of interface stripping test,tensile test,and microscopic characterization.The interface morphology,interface bonding properties,tensile fracture structures,and properties of plates under the first and second rolling were compared,along with the effects of intermetallic compounds on the interface properties.The results indicate that the powder-in-tube method,when annealed at 550℃,can produce a composite plate featuring a complete and uniform Ti/Al interface.The obtained plate exhibits a peeling strength of 21.5 N/mm,tensile strength of 424 MPa,and elongation of 11.5%.Furthermore,a systematic analysis was conducted to determine the causes of performance degra-dation observed during annealing at temperatures of 600 and 650℃.

关键词： Powder-in-tube method-Ti/Al/Ti clad plate Annealing Cold rolling-Mechanical property