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Chinese Journal of Mechanical engineering 2024年第4期37卷 215-230页

作者： Xiancheng Zhang Xin Pan Hao Zeng Haofu Zhou Beijing Key Laboratoryof Health Monitoring and Self-recovery for High-end Mechanical Equipment Beijing University of Chemical TechnologyBeijing 100029China engineering research center of Chemical Safety(Ministry of Education) Beijing University of Chemical TechnologyBeijing 100029China engineering Management Department of China Three Gorges New Energy(Group)Co. Ltd.Beijing 101199China

intelligent fault diagnosis is an important method in rotating machinery fault diagnosis and equipment health *** deal with co-frequency vibration faults,a type of typical fault in rotating machinery,this paper proposes a fault diagnosis method based on the stacked autoencoder(SAE)and ensembled ***,the time-and frequency-domain features of several co-frequency vibration faults are summarized based on the mechanism analysis and calculated using actual vibration *** realize and validate the high-precision diagnosis method of rotating equipment with co-frequency faults proposed in this study,the following three criteria are required:First,to improve the effectiveness and robustness of the ensembled model and the sliding window using data augmentation,adding noise,autoencoder(AE)and SAE methods are analyzed in terms of principle and practical ***,ResNet is used as the feature extractor for the ensembled ResNet-SVM *** extraction is carried out twice,and the extracted co-frequency fault features are more ***,the data augmentation method and ensemble ResNet-SVM are combined for fault diagnosis and compared with other *** experimental results show that the accuracy of the proposed method can exceed 99.9%.

关键词： Co-frequency vribation data argumentation Ensembeled ResNet-SVM High precision fault diagnosis

Welding depth measurement for different mode lasers using optical coherence tomography

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Chinese Optics Letters 2024年第1期22卷 41-46页

作者：谢冠明王三宏张跃强李由胡彪傅愉于起峰 Institute of intelligent Optical Measurement and Detection Shenzhen UniversityShenzhen 518060China College of Physics and Optoelectronic engineering Shenzhen UniversityShenzhen 518060China Shenzhen Sincevision Technology Co. Ltd.Shenzhen 518055China National Key Laboratory of Human Factors engineering China Astronaut Research and Training CenterBeijing 100094China College of Aerospace Science and engineering National University of Defense TechnologyChangsha 410073China

Optical coherence tomography(OCT)allows a direct and precise measurement of laser welding depth by coaxially measuring the keyhole depth and can be used for process monitoring and *** OCT measurement was taken during single-beam laser welding,the keyhole instability of aluminum welding resulted in highly scattered OCT data and complicated the welding depth extraction *** a combination of an inner core beam and an outer ring beam,a novel adjustable ring mode(ARM)laser for producing a stable keyhole was applied to the OCT *** ARM laser power arrangements were conducted on aluminum and *** results indicated that the ring beam greatly improved the stability of the core beam-induced keyhole,and smooth welding depth can be extracted from the concentrated OCT data.

关键词： optical coherence tomography adjustable ring mode laser laser welding welding depth

A digital twin-enhanced collaborative maintenance paradigm for aero-engine fleet

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Frontiers of engineering Management 2024年第2期11卷 356-361页

作者： Jiawei REN Ying CHENG Yingfeng ZHANG Fei TAO School of Automation Science and Electrical engineering Beihang UniversityBeijing 100083China School of Mechanical engineering Northwestern Polytechnical UniversityXi’an 710072China Digital Twin International research center International Research Institute for Multidisciplinary SciencesBeihang UniversityBeijing 100083China

Maintenance of aero-engine fleets is crucial for the efficiency,safety,and reliability of the aviation *** the increasing demand for air transportation,maintaining high-performing aero-engines has become *** maintenance,specifically targeting aero-engine fleets,involves the coordination of multiple tasks and resources to enhance management efficiency and reduce *** Twin(DT)technology provides essential technical support for the intelligent operation and maintenance of aero-engine *** maps physical object properties to the virtual world,creating high-fidelity,dynamic ***,DT-enhanced collaborative maintenance faces various challenges,including the construction of complex system-layer DT models,management of massive integrated DT data,and the development of fusion mechanisms and decision-making methods for DT data and *** these challenges will allow the aviation industry to optimize aero-engine fleet maintenance,ensuring safety,efficiency,and cost-effectiveness while meeting the growing demand for air transportation.

关键词： aero-engine fleet collaborative maintenance Digital Twin(DT) complex system

Enhancing Wireless Sensor Network Efficiency through Al-Biruni Earth Radius Optimization

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Computers, Materials & Continua 2024年第6期79卷 3549-3568页

作者： Reem Ibrahim Alkanhel Doaa Sami Khafaga Ahmed Mohamed Zaki Marwa M.Eid Abdyalaziz A.Al-Mooneam Abdelhameed Ibrahim S.K.Towfek Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer Science and intelligent Systems research center BlacksburgVirginia24060USA Delta Higher Institute for engineering and Technology Mansoura35511Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Artificial Intelligence and Computational Intelligence research center MeridenConnecticut06450USA School of ICT Faculty of EngineeringDesign and Information&Communications Technology(EDICT)Bahrain PolytechnicP.O.Box 33349Isa TownBahrain

The networks of wireless sensors provide the ground for a range of applications,including environmental moni-toring and industrial *** the networks can overcome obstacles like power and communication reliability and sensor coverage is the crux of network *** infrastructure planning should be focused on increasing performance,and it should be affected by the detailed data about node *** work recommends the creation of each sensor’s specs and radius of influence based on a particular geographical location,which will contribute to better network planning and *** using the ARIMA model for time series forecasting and the Al-Biruni Earth Radius algorithm for optimization,our approach bridges the gap between successive terrains while seeking the equilibrium between exploration and *** implementing adaptive protocols according to varying environments and sensor constraints,our study aspires to improve overall network *** compare the Al-Biruni Earth Radius algorithm along with Gray Wolf Optimization,Particle Swarm Optimization,Genetic Algorithms,and Whale Optimization about performance on real-world *** the most efficient in the optimization process,Biruni displays the lowest error rate at *** two other statistical techniques,like ANOVA,are also useful in discovering the factors influencing the nature of sensor data and network-specific *** to the multi-faceted support the comprehensive approach promotes,there is a chance to understand the dynamics that affect the optimization outcomes better so decisions about network design can be *** delivering better performance and reliability for various in-situ applications,this research leads to a fusion of time series forecasters and a customized optimizer algorithm.

关键词： Wireless sensor networks optimization ARIMA model BER algorithm metaheuristic algorithms

An improved model combining machine learning and Kalman filtering architecture for state of charge estimation of lithium-ion batteries

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Green Energy and intelligent Transportation 2024年第4期3卷 1-11页

作者： Yan Li Min Ye Qiao Wang Gaoqi Lian Baozhou Xia National engineering research center for Highway Maintenance Equipment Chang'an UniversityXi'an710064China Chair for Electrochemical Energy Conversion and Storage Systems Institute for Power Electronics and Electrical Drives(ISEA)RWTH Aachen UniversityAachen52062Germany

Accurate state of charge(SOC)estimation of lithium-ion batteries is a fundamental prerequisite for ensuring the normal and safe operation of electric vehicles,and it is also a key technology component in battery management *** recent years,lithium-ion battery SOC estimation methods based on data-driven approaches have gained significant ***,these methods commonly face the issue of poor model generalization and limited *** address such issues,this study proposes a closed-loop SOC estimation method based on simulated annealing-optimized support vector regression(SA-SVR)combined with minimum error entropy based extended Kalman filter(MEE-EKF)***,a probability-based SA algorithm is employed to optimize the internal parameters of the SVR,thereby enhancing the precision of original SOC ***,utilizing the framework of the Kalman filter,the optimized SVR results are incorporated as the measurement equation and further processed through the MEE-EKF,while the ampere-hour integral physical model serves as the state equation,effectively attenuating the measurement noise,enhancing the estimation accuracy,and improving generalization *** proposed method is validated through battery testing experiments conducted under three typical operating conditions and one complex and random operating condition with wide temperature variations under only one condition *** results demonstrate that the proposed method achieves a mean absolute error below 0.60%and a root mean square error below 0.73%across all operating conditions,showcasing a significant improvement in estimation accuracy compared to the benchmark *** high precision and generalization capability of the proposed method are evident,ensuring accurate SOC estimation for electric vehicles.

关键词： Lithium-ion battery State of charge estimation Support vector regression Simulated annealing optimization Kalman filter

An improved transfer learning strategy for short-term cross-building energy prediction usingdata incremental

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Building Simulation 2024年第1期17卷 165-183页

作者： Guannan Li Yubei Wu Chengchu Yan Xi Fang Tao Li Jiajia Gao Chengliang Xu Zixi Wang School of Urban Construction Wuhan University of Science and TechnologyWuhan 430065China Anhui Province Key Laboratory of intelligent Building and Building Energy-saving Anhui Jianzhu UniversityHefei 230601China State Key Laboratory of Green Building in Western China Xi'an University of Architecture and TechnologyXi'an 710055China College of Urban Construction Nanjing Tech UniversityNo.200North Zhongshan RoadNanjing 210009China Key Laboratory of Low-grade Energy Utilization Technologies and Systems(Chongqing University) Ministry of Education of ChinaChongqing UniversityChongqing 400044China College of Civil engineering Hunan UniversityChangsha 410082China Hubei Provincial engineering research center of Urban Regeneration Wuhan University of Science and TechnologyWuhan 430065China

The available modelling data shortage issue makes it difficult to guarantee the performance of data-driven building energy prediction(BEP)models for both the newly built buildings and existing information-poor *** knowledge transfer learning(KTL)and data incremental learning(DIL)can address the data shortage issue of such *** new building scenarios with continuous data accumulation,the performance of BEP models has not been fully investigated considering the data accumulation ***,which can learn dynamic features from accumulated data adapting to the developing trend of new building time-series data and extend BEP model's knowledge,has been rarely *** studies have shown that the performance of KTL models trained with fixed data can be further improved in scenarios with dynamically changing ***,this study proposes an improved transfer learning cross-BEP strategy continuously updated using the coarse data incremental(CDI)*** hybrid KTL-DIL strategy(LSTM-DANN-CDI)uses domain adversarial neural network(DANN)for KLT and long short-term memory(LSTM)as the Baseline BEP *** evaluation is conducted to systematically qualify the effectiveness and applicability of KTL and improved ***-world data from six-type 36 buildings of six types are adopted to evaluate the performance of KTL and KTL-DIL in data-driven BEP tasks considering factors like the model increment time interval,the available target and source building data *** with LSTM,results indicate that KTL(LSTM-DANN)and the proposed KTL-DIL(LSTM-DANN-CDI)can significantly improve the BEP performance for new buildings with limited *** with the pure KTL strategy LSTM-DANN,the improved KTL-DIL strategy LSTM-DANN-CDI has better prediction performance with an average performance improvement ratio of 60%.

关键词： building energy prediction(BEP) cross-building data incremental learning(DIL) domain adversarial neural network(DANN) knowledge transfer learning(KTL)

Model informed precision medicine of Chinese herbal medicines formulas-A multi-scale mechanistic intelligent model

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Journal of Pharmaceutical Analysis 2024年第4期14卷 585-600页

作者： Yuanyuan Qian Xiting Wang Lulu Cai Jiangxue Han Zhu Huang Yahui Lou Bingyue Zhang Yanjie Wang Xiaoning Sun Yan Zhang Aisong Zhu Zhejiang Key Laboratory of Blood-Stasis-Toxin Syndrome Zhejiang Chinese Medical UniversityHangzhou310000China Academy of Mathematics and Systems Science Chinese Academy of SciencesBeijing100190China Zhejiang engineering research center for“Preventive treatment”Smart Health of Traditional Chinese Medicine Zhejiang Chinese Medical UniversityHangzhou310000China College of Basic Medical Sciences Zhejiang Chinese Medical UniversityHangzhou310000China Affiliated Hospital of Liaoning University of Traditional Chinese Medicine Shenyang110032China Academy of Chinese Medical Science Zhejiang Chinese Medical UniversityHangzhou310000China

Recent trends suggest that Chinese herbal medicine formulas(CHM formulas)are promising treatments for complex *** characterize the precise syndromes,precise diseases and precise targets of the precise targets between complex diseases and CHM formulas,we developed an artificial intelligence-based quantitative predictive algorithm(DeepTCM).DeepTCM has gone through multilevel model calibration and validation against a comprehensive set of herb and disease data so that it accurately captures the complex cellular signaling,molecular and theoretical levels of traditional Chinese medicine(TCM).As an example,our model simulated the optimal CHM formulas for the treatment of coronary heart disease(CHD)with depression,and through model sensitivity analysis,we calculated the balanced scoring of the ***,we constructed a biological knowledge graph representing interactions by associating herb-target and gene-disease ***,we experimentally confirmed the therapeutic effect and pharmacological mechanism of a novel model-predicted intervention in humans and *** novel multiscale model opened up a new avenue to combine“disease syndrome”and“macro micro”system modeling to facilitate translational research in CHM formulas.

关键词： Chinese herbal medicine formulas Precision medicine Mathematical modeling Systems biology Coronary heart disease Depression Ischemia-reperfusion Inflammation

Anti-Jamming Null Space Projection Beamforming Based on Symbiotic Radio

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工程与科学中的计算机建模(英文) 2024年第1期138卷 679-689页

作者： Baofeng Ji Yifan Liu Tingpeng Li Ling Xing Weixing Wang Shahid Mumtaz Xiaolong Shang Wanying Liu Congzheng Han State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System(CEMEE) Luoyang471000China research and Innovation center of intelligent System Longmen LaboratoryLuoyang471000China College of Information engineering Henan University of Science and TechnologyLuoyang471000China Institute of Atmospheric Physics Chinese Academy of Sciences(LAGEO)Beijing100000China Instituto de Telecomunicaes Aveiro3800-005Portugal Chinese Academy of Agricultural Mechanization Sciences Beijing100000China

With the development of information technology,more and more devices are connected to the Internet through wireless communication to complete data *** to the broadcast characteristics ofwireless channels,wireless networks have suffered more and more malicious *** layer security has received extensive attention from industry and *** is considered to be one of the most important technologies related to physical layer *** beamforming technology,messages can be transmitted to legitimate users in an offset direction that is as orthogonal as possible to the interference channel to ensure the reception SINR by legitimate *** the symbiotic radio(SR)technology,this paper considers a symbiotic radio antijamming MIMO system equipped with a multi-antenna system at the main base *** order to avoid the interference signal and improve the SINR of the signal received by the *** base station is equipped with a uniform rectangular antenna array,and using Null Space Projection(NSP)Beamforming,intelligent Reflecting Surface(IRS)can assist in changing the beam’s *** simulation results show that NSP Beamforming could make a better use of the null space of interference,which can effectively improve the received SINR of users under directional interference,and improve the utilization efficiency of signal energy.

关键词： Symbiotic radio anti-jamming MIMO NSP Beamforming physical layer security

Antitumor efficacy and potential mechanism of FAP-targeted radioligand therapy combined with immune checkpoint blockade

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Signal Transduction and Targeted Therapy 2024年第7期9卷 2936-2952页

作者： Liang Zhao Yizhen Pang Yangfan Zhou Jianhao Chen Hao Fu Wei Guo Weizhi Xu Xin Xue Guoqiang Su Long Sun Hua Wu Jingjing Zhang Zhanxiang Wang Qin Lin Xiaoyuan Chen Haojun Chen Department of Nuclear Medicine and Minnan PET center Xiamen Key Laboratory of RadiopharmaceuticalsThe First Affiliated Hospital of Xiamen UniversitySchool of MedicineXiamen UniversityXiamenChina Departments of Diagnostic Radiology SurgeryChemical and Biomolecular Engineeringand Biomedical EngineeringYong Loo Lin School of Medicine and College of Design and EngineeringNational University of SingaporeSingaporeSingapore Clinical Imaging research Centre Centre for Translational MedicineYong Loo Lin School of MedicineNational University of SingaporeSingaporeSingapore Department of Radiation Oncology Xiamen Cancer CenterXiamen Key Laboratory of Radiation OncologyThe First Affiliated Hospital of Xiamen UniversitySchool of MedicineXiamen UniversityXiamenChina Department of Colorectal Tumor Surgery Xiamen Cancer CenterXiamen Key Laboratory of Radiation OncologyThe First Affiliated Hospital of Xiamen UniversitySchool of MedicineXiamen UniversityXiamenChina Department of Cardiothoracic Surgery Zhongda HospitalSchool of MedicineSoutheast UniversityNanjingChina Nanomedicine Translational research Program NUS Center for NanomedicineYong Loo Lin School of MedicineNational University of SingaporeSingaporeSingapore Department of Neurosurgery and Department of Neuroscience Fujian Key Laboratory of Brain Tumors Diagnosis and Precision TreatmentXiamen Key Laboratory of Brain Centerthe First Affiliated Hospital of Xiamen UniversitySchool of MedicineXiamen UniversityXiamenChina Institute of Molecular and Cell Biology Agency for ScienceTechnology and Research(A*STAR)SingaporeSingapore Xiamen Key Laboratory of Rare Earth Photoelectric Functional Materials Xiamen Institute of Rare Earth MaterialsHaixi InstituteChinese Academy of SciencesXiamenChina

Radiotherapy combined with immune checkpoint blockade holds great promise for synergistic antitumor *** radionuclide therapy delivers radiation directly to tumor ***1004 is a fibroblast activation protein(FAP)-targeting radiopharmaceutical,conjugated with the albumin binder Evans Blue,which has demonstrated enhanced tumor uptake and retention in previous preclinical and clinical ***,we demonstrate that^(68)Ga/^(177)Lu-labeled LNC1004 exhibits increased uptake and prolonged retention in MC38/NIH3T3-FAP and CT26/NIH3T3-FAP tumor *** therapy with^(177)Lu-LNC1004 induced a transient upregulation of PD-L1 expression in tumor *** combination of^(177)Lu-LNC1004 and anti-PD-L1 immunotherapy led to complete eradication of all tumors in MC38/NIH3T3-FAP tumor-bearing mice,with mice showing 100%tumor rejection upon ***,single-cell RNA sequencing(scRNA-seq),and TCR sequencing revealed that combination therapy reprogrammed the tumor microenvironment in mice to foster antitumor immunity by suppressing malignant progression and increasing cell-to-cell communication,CD8^(+)T-cell activation and expansion,M1 macrophage counts,antitumor activity of neutrophils,and T-cell receptor diversity.A preliminary clinical study demonstrated that^(177)Lu-LNC1004 was well-tolerated and effective in patients with refractory ***,scRNA-seq of peripheral blood mononuclear cells underscored the importance of addressing immune evasion through immune checkpoint blockade *** was emphasized by the observed increase in antigen processing and presentation juxtaposed with T cell *** conclusion,our data supported the efficacy of immunotherapy combined with^(177)Lu-LNC1004 for cancer patients with FAP-positive tumors.

关键词： immunity retention holds

Customized scaffolds for large bone defects using 3D‑printed modular blocks from 2D‑medical images

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Bio-Design and Manufacturing 2024年第1期7卷 74-87页

作者： Anil AAcar Evangelos Daskalakis Paulo Bartolo Andrew Weightman Glen Cooper Gordon Blunn Bahattin Koc Faculty of engineering and Natural Sciences Sabanci UniversityIstanbul 34956Türkiye D Bioprinting Laboratory Sabanci University Nanotechnology Research and Application CenterIstanbul 34956Türkiye School of Mechanical Aerospace and Civil EngineeringManchester Institute of BiotechnologyUniversity of ManchesterManchester M139PLUK Singapore Centre for 3D Printing School of Mechanical and Aerospace EngineeringNanyang Technological UniversitySingapore 639798Singapore School of Pharmacy and Biomedical Sciences University of PortsmouthPortsmouth PO12UPUK

Additive manufacturing(AM)has revolutionized the design and manufacturing of patient-specific,three-dimensional(3D),complex porous structures known as scaffolds for tissue engineering *** use of advanced image acquisition techniques,image processing,and computer-aided design methods has enabled the precise design and additive manufacturing of anatomically correct and patient-specific implants and ***,these sophisticated techniques can be timeconsuming,labor-intensive,and ***,the necessary imaging and manufacturing equipment may not be readily available when urgent treatment is needed for trauma *** this study,a novel design and AM methods are proposed for the development of modular and customizable scaffold blocks that can be adapted to fit the bone defect area of a *** modular scaffold blocks can be combined to quickly form any patient-specific scaffold directly from two-dimensional(2D)medical images when the surgeon lacks access to a 3D printer or cannot wait for lengthy 3D imaging,modeling,and 3D printing during *** proposed method begins with developing a bone surface-modeling algorithm that reconstructs a model of the patient’s bone from 2D medical image measurements without the need for expensive 3D medical imaging or *** algorithm can generate both patient-specific and average bone ***,a biomimetic continuous path planning method is developed for the additive manufacturing of scaffolds,allowing porous scaffold blocks with the desired biomechanical properties to be manufactured directly from 2D data or *** algorithms are implemented,and the designed scaffold blocks are 3D printed using an extrusion-based AM *** and instructions are also provided to assist surgeons in assembling scaffold blocks for the self-repair of patient-specific large bone defects.

关键词： Additive manufacturing Modular scaffolds Large bone defect Customized scaffold design Patient-specific scaffolds