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Science China Chemistry 2024年第4期67卷 1224-1228页

作者： Ming-Ming Gan Zi-En Zhang Yi-Fan Zhang Heng Zhang li-ying sun ying-Feng Han Key Laboratory of Synthetic and Natural Functional Molecule Chemistry of the Ministry of Education Xi’an Key Laboratory of Functional Supramolecular Structure and MaterialsCollege of Chemistry and Materials ScienceNorthwest UniversityXi’an 710127China

In this study,we present a supramolecular templating approach for constructing polyimidazolium salt containing crown ether and cyclobutane moieties.This strategy involves the formation of metal-carbene templates,photochemical cycloaddition,and subsequent demetallation of metal ions.Driven by the host-guest chemistry between crown ether units and ammonium salts,we successfully fabricated a supramolecular polymer SPN1,which features imidazolium receptors and cyclobutane units.The obtained SPN1 demonstrates outstanding reversible stimulus-response,antibacterial behavior and conductivity.

关键词： metal-carbene template crown ether polyimidazolium salt host-guest chemistry

Development and performance evaluation of a culture-independent nanopore amplicon-based sequencing method for accurate typing and antimicrobial resistance profiling in Neisseria gonorrhoeae

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Science China(life Sciences) 2024年第2期67卷 421-423页

作者： Chi Zhang Lulu Zhang Feng Wang Yaling Zeng liying sun Di Wang Yamei li liqin Wang Junping Peng NHC Key Laboratory of Systems Biology of Pathogens Institute of Pathogen BiologyChinese Academy of Medical Sciences&Peking Union Medical CollegeBeijing 100176China Key Laboratory of Respiratory Disease Pathogenomics Chinese Academy of Medical SciencesBeijing 100730China Shenzhen Center for Chronic Disease Control Shenzhen 518020China

Dear Editor,Bacterial antimicrobial resistance(AMR)poses a serious threat to global human health(Antimicrobial Resistance Collaborators,2022).Comprehensive profiling of AMR and accurate molecular typing are important for tracking and controlling the emergence and dissemination of antibiotic-resistant bacteria(Yahara et al.,2021).We previously developed a multiplex amplicon sequencing-based method for directly sequencing AMR-related loci in N.gonorrhoeae from clinical samples(Zhang et al.,2021).

关键词： gonorrhoeae resistance

Deep3DSketch-im:rapid high-fidelity AI 3D model generation by single freehand sketches

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Frontiers of Information Technology & Electronic Engineering 2024年第1期25卷 149-159页

作者： Tianrun CHEN Runlong CAO Zejian li ying ZANG lingyun sun College of Computer Science and Technology Zhejiang UniversityHangzhou 310027China School of Software Technology Zhejiang UniversityHangzhou 310027China School of Information Engineering Huzhou UniversityHuzhou 313000China

The rise of artificial intelligence generated content(AIGC)has been remarkable in the language and image fields,but artificial intelligence(AI)generated three-dimensional(3D)models are still under-explored due to their complex nature and lack of training data.The conventional approach of creating 3D content through computer-aided design(CAD)is labor-intensive and requires expertise,making it challenging for novice users.To address this issue,we propose a sketch-based 3D modeling approach,Deep3DSketch-im,which uses a single freehand sketch for modeling.This is a challenging task due to the sparsity and ambiguity.Deep3DSketch-im uses a novel data representation called the signed distance field(SDF)to improve the sketch-to-3D model process by incorporating an implicit continuous field instead of voxel or points,and a specially designed neural network that can capture point and local features.Extensive experiments are conducted to demonstrate the effectiveness of the approach,achieving state-of-the-art(SOTA)performance on both synthetic and real datasets.Additionally,users show more satisfaction with results generated by Deep3DSketch-im,as reported in a user study.We believe that Deep3DSketch-im has the potential to revolutionize the process of 3D modeling by providing an intuitive and easy-to-use solution for novice users.

关键词： Content creation Sketch Three-dimensional(3D)modeling 3D reconstruction Shape from X Artificial intelligence(AI)

Harnessing innate immune pathways for therapeutic advancement in cancer

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Signal Transduction and Targeted Therapy 2024年第4期9卷 1506-1564页

作者： Ankang Hu li sun Hao lin Yuheng liao Hui Yang ying Mao Department of Neurosurgery Huashan HospitalFudan UniversityShanghaiP.R.China Institute for Translational Brain Research Shanghai Medical CollegeFudan University ShanghaiPR.China National Center for Neurological Disorders Huashan HospitalShanghai Medical CollegeFudan UniversityShanghaiP.R.China Shanghai Key Laboratory of Brain Function Restoration and Neural Regeneration Shanghai Clinical Medical Center of NeurosurgeryNeurosurgical Institute of Fudan UniversityHuashan HospitalShanghai Medical CollegeFudan UniversityShanghaiP.R.China State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science and MOE Frontiers Center for Brain Science Institutes of Brain ScienceShanghai Medical CollegeFudan UniversityShanghaiP.R.China Shanghai Key Laboratory of Medical Epigenetics International Co-laboratory of Medical Epigenetics and Metabolism(Ministry of Science and Technology)and Key Laboratory of Metabolism and Molecular Medicine(Ministry of Education)and Molecular and Cell Biology LabInstitutes of Biomedical SciencesShanghai Medical College of Fudan UniversityShanghaiP.R.China

The innate immune pathway is receiving increasing attention in cancer therapy.This pathway is ubiquitous across various cell types,not only in innate immune cells but also in adaptive immune cells,tumor cells,and stromal cells.Agonists targeting the innate immune pathway have shown profound changes in the tumor microenvironment(TME)and improved tumor prognosis in preclinical studies.However,to date,the clinical success of drugs targeting the innate immune pathway remains limited.Interestingly,recent studies have shown that activation of the innate immune pathway can paradoxically promote tumor progression.The uncertainty surrounding the therapeutic effectiveness of targeted drugs for the innate immune pathway is a critical issue that needs immediate investigation.In this review,we observe that the role of the innate immune pathway demonstrates heterogeneity,linked to the tumor development stage,pathway status,and specific cell types.We propose that within the TME,the innate immune pathway exhibits multidimensional diversity.This diversity is fundamentally rooted in cellular heterogeneity and is manifested as a variety of signaling networks.The pro-tumor effect of innate immune pathway activation essentially reflects the suppression of classical pathways and the activation of potential pro-tumor alternative pathways.Refining our understanding of the tumor's innate immune pathway network and employing appropriate targeting strategies can enhance our ability to harness the anti-tumor potential of the innate immune pathway and ultimately bridge the gap from preclinical to clinicalapplication.

关键词： drugs therapeutic innate

Adenylate cyclase activates the cAMP signalling pathway to enhance platelet-rich plasma-treated Achilles tendon disease,a theoretical bioinformatics-based study

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World Journal of Orthopedics 2024年第2期15卷 192-200页

作者： Jing-Yi sun Cai li Feng-ying Du College of Basic Medical Science Qilu Medical UniversityZibo 255300Shandong ProvinceChina Department of Gastroenterological Surgery Shandong Provincial Hospital of Shandong First Medical UniversityJinan 250021Shandong ProvinceChina

The effectiveness of platelet-rich plasma(PRP)for the treatment of Achilles tendon disorders still needs to be evaluated through a series of prospective studies,but genomic analysis can reveal the existence of complementary PRP treatment options.Based on the 96 platelet activation-related genes in the Kyoto Encyclopedia of Genes and Genomes(KEGG)database,we performed Gene Ontology functional enrichment analysis and KEGG enrichment analysis,pathway correlation analysis,and enrichment mapping to determine the enrichment results of the gene set enrichment analysis and found that the cAMP signalling pathway may be the key to enhancing the effectiveness of PRP treatment.The cAMP signalling pathway interacts with the Rap1 signalling pathway and cGMPPKG signalling pathway to mediate the entire pathophy-siological process of Achilles tendon disease.Moreover,ADCY1-9 may be the key to the activation of the cAMP signalling network.Further based on the data in the Gene Expression Omnibus database,it was found that ADCY4 and ADCY7 may be the players that play a major role,associated with the STAT4-ADCY4-LAMA5 axis and the GRbeta-ADCY7-SEMA3C axis,which is expected to be a complementary target for enhancing the efficacy of PRP in the treatment of Achilles tendon disease.

关键词： Platelet-rich plasma Achilles tendon disease cAMP Adenylate cyclase Complementary target

Artificial intelligence-assisted repair of peripheral nerve injury: a new research hotspot and associated challenges

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Neural Regeneration Research 2024年第3期19卷 663-670页

作者： Yang Guo liying sun Wenyao Zhong Nan Zhang Zongxuan Zhao Wen Tian Department of Hand Surgery Beijing Jishuitan HospitalBeijingChina

Artificial intelligence can be indirectly applied to the repair of peripheral nerve injury.Specifically,it can be used to analyze and process data regarding peripheral nerve injury and repair,while study findings on peripheral nerve injury and repair can provide valuable data to enrich artificial intelligence algorithms.To investigate advances in the use of artificial intelligence in the diagnosis,rehabilitation,and scientific examination of peripheral nerve injury,we used CiteSpace and VOSviewer software to analyze the relevant literature included in the Web of Science from 1994–2023.We identified the following research hotspots in peripheral nerve injury and repair:(1)diagnosis,classification,and prognostic assessment of peripheral nerve injury using neuroimaging and artificial intelligence techniques,such as corneal confocal microscopy and coherent anti-Stokes Raman spectroscopy;(2)motion control and rehabilitation following peripheral nerve injury using artificial neural networks and machine learning algorithms,such as wearable devices and assisted wheelchair systems;(3)improving the accuracy and effectiveness of peripheral nerve electrical stimulation therapy using artificial intelligence techniques combined with deep learning,such as implantable peripheral nerve interfaces;(4)the application of artificial intelligence technology to brain-machine interfaces for disabled patients and those with reduced mobility,enabling them to control devices such as networked hand prostheses;(5)artificial intelligence robots that can replace doctors in certain procedures during surgery or rehabilitation,thereby reducing surgical risk and complications,and facilitating postoperative recovery.Although artificial intelligence has shown many benefits and potential applications in peripheral nerve injury and repair,there are some limitations to this technology,such as the consequences of missing or imbalanced data,low data accuracy and reproducibility,and ethical issues(e.g.,privacy,data security,research transparency).Future re

关键词： artificial intelligence artificial prosthesis medical-industrial integration brain-machine interface deep learning machine learning networked hand prosthesis neural interface neural network neural regeneration peripheral nerve

Integrated Frequency-constrained Scheduling Considering Coordination of Frequency Regulation Capabilities from Multi-source Converters

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 261-274页

作者： Jiaming li ying Qiao Zongxiang Lu Wei Ma Xin Cao Rongfu sun the Department of Electrical Engineering Tsinghua UniversityBeijing 100084China the China suntien Green Energy limited Company Shijiazhuang 050011China the State Grid Jibei Electric Power Company Beijing 100054China

As the proportion of renewable energy(RE)increases,the inertia and the primary frequency regulation(FR)capability of the power system decrease.Thus,ensuring frequency security in the scheduling model has become a new technical requirement in power systems with a high share of RE.Due to a shortage of conventional synchronous generators,the frequency support of multi-source converters has become an indispensable part of the system frequency resources,especially variable-speed wind turbine generation(WTG)and battery energy storage(BES).Quantitative expression of the FR capability of multi-source converters is necessary to construct frequency-constrained scheduling model.However,the frequency support performance of these converter-interfaced devices is related to their working states,operation modes,and parameters,and the complex coupling of these factors has not been fully exploited in existing models.In this study,we propose an integrated frequency-constrained scheduling model considering the coordination of FR capabilities from multi-source converters.Switchable FR control strategies and variable FR parameters for WTG with or without reserved power are modeled,and multi-target allocation of BES capacity between tracking dispatch instruction and emergency FR is analyzed.Then,the variable FR capabilities of WTG and BES are embedded into the integrated frequency-constrained scheduling model.The nonlinear constraints for frequency security are precisely linearized through an improved iteration-based strategy.The effectiveness of the proposed model is verified in a modified IEEE 24-bus standard system.The results suggest that the coordinated participation of BES and WTG in FR can effectively reduce the cost of the scheduling model while meeting frequency security constraints.

关键词： Battery energy storage(BES) wind turbine generation(WTG) frequency regulation(FR) frequency security power system scheduling

A Weakly-Supervised Crowd Density Estimation Method Based on Two-Stage linear Feature Calibration

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 965-981页

作者： Yong-Chao li Rui-Sheng Jia ying-Xiang Hu Hong-Mei sun the College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao 266590 the Faculty of Information Science and Engineering Ocean University of ChinaQingdao 266000China the College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao 266590China the College of Computer Science and Engineering Nanjing University of Science and TechnologyNanjing 210000China

In a crowd density estimation dataset,the annotation of crowd locations is an extremely laborious task,and they are not taken into the evaluation metrics.In this paper,we aim to reduce the annotation cost of crowd datasets,and propose a crowd density estimation method based on weakly-supervised learning,in the absence of crowd position supervision information,which directly reduces the number of crowds by using the number of pedestrians in the image as the supervised information.For this purpose,we design a new training method,which exploits the correlation between global and local image features by incremental learning to train the network.Specifically,we design a parent-child network(PC-Net)focusing on the global and local image respectively,and propose a linear feature calibration structure to train the PC-Net simultaneously,and the child network learns feature transfer factors and feature bias weights,and uses the transfer factors and bias weights to linearly feature calibrate the features extracted from the Parent network,to improve the convergence of the network by using local features hidden in the crowd images.In addition,we use the pyramid vision transformer as the backbone of the PC-Net to extract crowd features at different levels,and design a global-local feature loss function(L2).We combine it with a crowd counting loss(LC)to enhance the sensitivity of the network to crowd features during the training process,which effectively improves the accuracy of crowd density estimation.The experimental results show that the PC-Net significantly reduces the gap between fullysupervised and weakly-supervised crowd density estimation,and outperforms the comparison methods on five datasets of Shanghai Tech Part A,ShanghaiTech Part B,UCF_CC_50,UCF_QNRF and JHU-CROWD++.

关键词： Crowd density estimation linear feature calibration vision transformer weakly-supervision learning

Review and Perspectives on Human Emotion for Connected Automated Vehicles

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Automotive Innovation 2024年第1期7卷 4-44页

作者： Wenbo li Guofa li Ruichen Tan Cong Wang Zemin sun ying li Gang Guo Dongpu Cao Keqiang li School of Vehicle and Mobility Tsinghua University30 Shuangqing RdBeijing 100084China College of Mechanical and Vehicle Engineering Chongqing University174 Shazheng RdChongqing 400044China College of Computer Science and Technology Jilin University2699 Qianjin RdChangchun 130012China School of Mechanical Engineering Beijing Institute of Technology5 Zhongguancun South RdBeijing 100081China Lyles School of Civil Engineering Purdue University550 Stadium Mall DriveWest LafayetteIN 47907USA

The progression toward automated driving and the latest advancement in vehicular networking have led to novel and natural human-vehicle-road systems,in which affective human-vehicle interaction is a crucial factor affecting the acceptance,safety,comfort,and traffic efficiency of connected and automated vehicles(CAVs).This development has inspired increasing inter-est in how to develop affective interaction framework for intelligent cockpit in CAVs.To enable affective human-vehicle interactions in CAVs,knowledge from multiple research areas is needed,including automotive engineering,transportation engineering,human-machine interaction,computer science,communication,as well as industrial engineering.However,there is currently no systematic survey considering the close relationship between human-vehicle-road and human emotion in the human-vehicle-road coupling process in the CAV context.To facilitate progress in this area,this paper provides a comprehensive literature survey on emotion-related studies from multi-aspects for better design of affective interaction in intelligent cockpit for CAVs.This paper discusses the multimodal expression of human emotions,investigates the human emotion experiment in driving,and particularly emphasizes previous knowledge on human emotion detection,regulation,as well as their applications in CAVs.The promising research perspectives are outlined for researchers and engineers from different research areas to develop CAVs with better acceptance,safety,comfort,and enjoyment for users.

关键词： Intelligent vehicles Intelligent cockpit Human-machine interaction Emotion recognition Emotion regulation

Hybrid Model of Power Transformer Fault Classification Using C-set and MFCM – MCSVM

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 672-685页

作者： Ali Abdo Hongshun liu Yousif Mahmoud Hongru Zhang ying sun Qingquan li Jian Guo Shandong Provincial Key Laboratory of UHV Transmission Technology and Equipment School of Electrical EngineeringShandong UniversityJinan 250061China

This paper aims to increase the diagnosis accuracy of the fault classification of power transformers by introducing a new off-line hybrid model based on a combination subset of the et method(C-set)&modified fuzzy C-mean algorithm(MFCM)and the optimizable multiclass-SVM(MCSVM).The innovation in this paper is shown in terms of solving the predicaments of outliers,boundary proportion,and unequal data existing in both traditional and intelligence models.Taking into consideration the closeness of dissolved gas analysis(DGA)data,the C-set method is implemented to subset the DGA data samples based on their type of faults within unrepeated subsets.Then,the MFCM is used for removing outliers from DGA samples by combining highly similar data for every subset within the same cluster to obtain the optimized training data(OTD)set.It is also used to minimize dimensionality of DGA samples and the uncertainty of transformer condition monitoring.After that,the optimized MCSVM is trained by using the(OTD).The proposed model diagnosis accuracy is 93.3%.The obtained results indicate that our model significantly improves the fault identification accuracy in power transformers when compared with other conventional and intelligence models.

关键词： Combination subset of set(C-set)method modified fuzzy C-means(MFCM) optimizable multiclass-SVM(MCSVM) optimized training data(OTD)