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The chromosome-level genome of double-petal phenotype jasmine provides insights into the biosynthesis of floral scent

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Horticultural Plant Journal 2024年第1期10卷 259-272页

作者： Xiangyu Qi Huadi Wang Shuyun Liu shuangshuang chen Jing Feng Huijie chen Ziyi qin Quanming chen Ikram Blilou Yanming Deng Jiangsu Key Laboratory for Horticultural Crop Genetic Improvement Institute of Leisure AgricultureJiangsu Academy of Agricultural SciencesNanjingJiangsu 210014China School of Life Sciences Jiangsu UniversityZhenjiangJiangsu 212013China College of Horticulture Nanjing Agricultural UniversityNanjingJiangsu 210014China Shanghai Personal Biotechnology Company Limited Shanghai 200231China Biological and Environmental Sciences and Engineering King Abdullah University of Science and TechnologyThuwal 23955-6900Saudi Arabia

Jasmine(Jasminum sambac Aiton)is a well-known cultivated plant species for its fragrant flowers used in the perfume industry and ***,the genetic basis of its floral scent is largely *** this study,using PacBio,Illumina,10×Genomics and highthroughput chromosome conformation capture(Hi-C)sequencing technologies,a high-quality chromosome-level reference genome for *** was obtained,exploiting a double-petal phenotype cultivar‘shuangbanmoli’(JSSB).The results showed that the final assembled genome of JSSB is 580.33 Mb in size(contig N50=1.05 Mb;scaffold N50=45.07 Mb)with a total of 39618 predicted protein-coding *** analyses revealed that the JSSB genome has undergone an ancient whole-genome duplication(WGD)event at 91.68 million years ago(Mya).It was estimated that *** diverged from the lineage leading to Olea europaea and Osmanthus fragrans about 28.8 *** the basis of a combination of genomic,transcriptomic and metabolomic analyses,a range of floral scent volatiles and genes were identified involved in the benzenoid/phenylpropanoid and terpenoid biosynthesis *** results provide new insights into the molecular mechanism of its fragrance biosynthesis in jasmine.

关键词： Jasminum sambac Aiton Oleaceae Genome evolution Floral scent Terpene synthase

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Low-energy-consumption temperature swing system for CO_(2) capture by combining passive radiative cooling and solar heating

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Green Energy & Environment 2024年第3期9卷 507-515页

作者： Ying-Xi Dang Peng Tan Bin Hu chen Gu Xiao-qin Liu Lin-Bing Sun State Key Laboratory of Materials-Oriented Chemical Engineering Jiangsu National Synergetic Innovation Center for Advanced Materials(SICAM)College of Chemical EngineeringNanjing Tech UniversityNanjing211816China

Temperature-swing adsorption(TSA)is an effective technique for CO_(2) capture,but the temperature swing procedure is ***,we report a low-energy-consumption system by combining passive radiative cooling and solar heating for the uptake of CO_(2) on commercial activated carbons(CACs).During adsorption,the adsorbents are coated with a layer of hierarchically porous poly(vinylidene fluoride-co-hexafluoropropene)[P(VdF-HFP)HP],which cools the adsorbents to a low temperature under sunlight through radiative *** desorption,CACs with broad absorption of the solar spectrum are exposed to light irradiation for *** heating and cooling processes are completely driven by solar *** tests under mimicked sunlight using the CACs show that the performance of this system is comparable to that of the traditional ***,under real sunlight irradiation,the adsorption capacity of the CACs can be well maintained after multiple *** present work may inspire the development of new temperature swing procedures with little energy consumption.

关键词： CO_(2)capture Solar heating Passive radiative cooling Temperature swing adsorption

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Impedance Model for Instability Analysis of LCC-HVDCs Considering Transformer Saturation

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Journal of Modern Power Systems and Clean Energy 2024年第4期12卷 1309-1319页

作者： qin Jiang Ruiting Xu Baohong Li Xiang chen Yue Yin Tianqi Liu Frede Blaabjerg College of Electrical Engineering Sichuan UniversityChengdu 610065China Smart Grid Key Laboratory of Sichuan Province Chengdu 610065China Department of Energy Technology Aalborg UniversityAalborg 9920Denmark

In line commutated converter based high-voltage direct current(LCC-HVDC)transmission systems,the trans-former saturation can induce harmonic instability,which poses a serious threat to the safe operation of the power ***-ever,the nonlinear characteristics of the power grids introduced by the transformer saturation considerably limit the application of the conventional analysis *** address the issue,this paper derives a linear model for the transformer saturation caused by the DC current due to the converter ***-terwards,the nonlinear characteristics of power grids with the transformer saturation is described by a complex valued imped-ance *** on the derived impedance matrix,the sys-tem harmonic stability is analyzed and the mechanism of the transformer saturation induced harmonic instability is ***,the sensitivity analysis is conducted to find the key fac-tors that influence the system core saturation *** proposed impedance model is verified by the electromagnetic transient simulation,and the simulation results corroborate the effectiveness of the proposed impedance *** TermsLine commutated converter based high voltage direct current(LCC-HVDC),transformer saturation,harmonic instability,impedance model.

关键词： Line commutated converter based high voltage direct current(LCC-HVDC) transformer saturation harmonic instability impedance model

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CrossLinkNet: An Explainable and Trustworthy AI Framework for Whole-Slide Images Segmentation

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Computers, Materials & Continua 2024年第6期79卷 4703-4724页

作者： Peng Xiao Qi Zhong Jingxue chen Dongyuan Wu Zhen qin Erqiang Zhou Network and Data Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of ChinaChengdu610054China Faculty of Data Science City University of MacaoMacao999078China

In the intelligent medical diagnosis area,Artificial Intelligence(AI)’s trustworthiness,reliability,and interpretability are critical,especially in cancer *** neural networks,while excellent at processing natural images,often lack interpretability and adaptability when processing high-resolution digital pathological *** limitation is particularly evident in pathological diagnosis,which is the gold standard of cancer diagnosis and relies on a pathologist’s careful examination and analysis of digital pathological slides to identify the features and progression of the ***,the integration of interpretable AI into smart medical diagnosis is not only an inevitable technological trend but also a key to improving diagnostic accuracy and *** this paper,we introduce an innovative Multi-Scale Multi-Branch Feature Encoder(MSBE)and present the design of the CrossLinkNet *** MSBE enhances the network’s capability for feature extraction by allowing the adjustment of hyperparameters to configure the number of branches and *** CrossLinkNet Framework,serving as a versatile image segmentation network architecture,employs cross-layer encoder-decoder connections for multi-level feature fusion,thereby enhancing feature integration and segmentation *** quantitative and qualitative experiments on two datasets demonstrate that CrossLinkNet,equipped with the MSBE encoder,not only achieves accurate segmentation results but is also adaptable to various tumor segmentation tasks and scenarios by replacing different feature ***,CrossLinkNet emphasizes the interpretability of the AI model,a crucial aspect for medical professionals,providing an in-depth understanding of the model’s decisions and thereby enhancing trust and reliability in AI-assisted diagnostics.

关键词： Explainable AI security trustworthy CrossLinkNet whole slide images

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High-speed flexible near-infrared organic photodiode for optical communication

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National Science Review 2024年第3期11卷 227-238页

作者： Yu Zhu Hongbin chen Ruiman Han Hao qin Zhaoyang Yao Hang Liu Yanfeng Ma Xiangjian Wan Guanghui Li Yongsheng chen The Centre of Nanoscale Science and Technology and Key Laboratory of Functional Polymer Materials Institute of Polymer ChemistryTianjin Key Laboratory of Functional Polymer Materials College of Chemistry and Renewable Energy Conversion and Storage Center(RECAST) Nankai University State Key Laboratory of Elemento-Organic Chemistry Nankai University

Optical communication is a particularly compelling technology for tackling the speed and capacity bottlenecks in data communication in modern society. Currently, the silicon photodetector plays a dominant role in high-speed optical communication across the visible-near-infrared spectrum. However, its intrinsic rigid structure, high working bias and low responsivity essentially limit its application in next-generation flexible optoelectronic devices. Herein, we report a narrow-bandgap non-fullerene acceptor（NFA） with a remarkable π-extension in the direction of both central and end units（CH17） with respect to the Y6 series, which demonstrates a more effective and compact 3D molecular packing, leading to lower trap states and energetic disorders in the photoactive film. Consequently, the optimized solution-processed organic photodetector（OPD） with CH17 exhibits a remarkable response time of 91 ns（λ = 880 nm） due to the high charge mobility and low parasitic capacitance, exceeding the values of most commercial Si photodiodes and all NFA-based OPDs operating in self-powered mode. More significantly, the flexible OPD exhibits negligible performance attenuation（<1%） after bending for 500 cycles, and maintains 96% of its initial performance even after 550 h of indoor exposure. Furthermore, the high-speed OPD demonstrates a high data transmission rate of 80 MHz with a bit error rate of 3.5 × 10-4, meaning it has great potential in next-generation high-speed flexible optical communication systems.

关键词： flexible organic photodetector high-speed NIR organic photodetector optical communication light fidelity narrow-bandgap non-fullerene acceptors

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Myosin Va‑dependent Transport of NMDA Receptors in Hippocampal Neurons

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Neuroscience Bulletin 2024年第8期40卷 1053-1075页

作者： Ru Gong Linwei qin Linlin chen Ning Wang Yifei Bao Wei Lu Ministry of Education(MOE)Key Laboratory of Developmental Genes and Human Disease School of Life Science and TechnologySoutheast UniversityNanjing 210096China Department of Neurosurgery State Key Laboratory of Medical NeurobiologyMOE Frontiers Center for Brain ScienceHuashan HospitalInstitute for Translational Brain ResearchFudan UniversityShanghai 200032China Department of Neurobiology Nanjing Medical UniversityNanjing 210096China Co‑innovation Center of Neuroregeneration Nantong UniversityNantong 226001China

N-methyl-D-aspartate receptor(NMDAR)trafficking is a key process in the regulation of synaptic efficacy and brain ***,the molecular mechanism underlying the surface transport of NMDARs is largely *** we identified myosin Va(MyoVa)as the specific motor protein that traffics NMDARs in hippocampal *** found that MyoVa associates with NMDARs through its cargo binding *** association was increased during NMDAR surface *** of MyoVa suppressed NMDAR *** further demonstrated that Ca^(2+)/calmodulin-dependent protein kinase Ⅱ(CaMKⅡ)regulates NMDAR transport through its direct interaction with ***,MyoVa employed Rab11 family-interacting protein 3(Rab11/FIP3)as the adaptor proteins to couple themselves with NMDARs during their ***,the knockdown of FIP3 impairs hippocampal ***,we conclude that in hippocampal neurons,MyoVa conducts active transport of NMDARs in a CaMKII-dependent manner.

关键词： Myosin Va NMDA receptor CaMKⅡ Transport Memory

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Multi-Scale Design and Optimization of Composite Material Structure for Heavy-Duty Truck Protection Device

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1961-1980页

作者： Yanhui Zhang Lianhua Ma Hailiang Su Jirong qin Zhining chen Kaibiao Deng School of Mechanical and Automotive Engineering Guangxi University of Science and TechnologyLiuzhou545006China Commercial Vehicle Technology Center Dongfeng Liuzhou Automobile Co.Ltd.Liuzhou545005China School of Mechanical and Automotive Engineering South China University of TechnologyGuangzhou510641China

In this paper,to present a lightweight-developed front underrun protection device(FUPD)for heavy-duty trucks,plain weave carbon fiber reinforced plastic(CFRP)is used instead of the original high-strength ***,the mechanical and structural properties of plain carbon fiber composite anti-collision beams are comparatively analyzed from a multi-scale *** studying the design capability of carbon fiber composite materials,we investigate the effects of TC-33 carbon fiber diameter(D),fiber yarn width(W)and height(H),and fiber yarn density(N)on the front underrun protective beam of carbon fiber *** on the investigation,a material-structure matching strategy suitable for the front underrun protective beam of heavy-duty trucks is ***,the composite material structure is optimized by applying size optimization and stack sequence optimization methods to obtain the higher performance carbon fiber composite front underrun protection beam of commercial *** results show that the fiber yarn height(H)has the greatest influence on the protective beam,and theH1matching scheme for the front underrun protective beamwith a carbon fiber composite structure exhibits superior *** proposed method achieves a weight reduction of 55.21% while still meeting regulatory requirements,which demonstrates its remarkable weight reduction effect.

关键词： Structural optimization front underrun protection device carbon fiber reinforced plastic multi-scale model lightweight design

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Dynamic SLAM Visual Odometry Based on Instance Segmentation:A Comprehensive Review

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Computers, Materials & Continua 2024年第1期78卷 167-196页

作者： Jiansheng Peng qing Yang Dunhua chen chengjun Yang Yong Xu Yong qin College of Automation Guangxi University of Science and TechnologyLiuzhou545000China Department of Artificial Intelligence and Manufacturing Hechi UniversityHechi547000China

Dynamic Simultaneous Localization and Mapping(SLAM)in visual scenes is currently a major research area in fields such as robot navigation and autonomous ***,in the face of complex real-world envi-ronments,current dynamic SLAM systems struggle to achieve precise localization and map *** the advancement of deep learning,there has been increasing interest in the development of deep learning-based dynamic SLAM visual odometry in recent years,and more researchers are turning to deep learning techniques to address the challenges of dynamic *** to dynamic SLAM systems based on deep learning methods such as object detection and semantic segmentation,dynamic SLAM systems based on instance segmentation can not only detect dynamic objects in the scene but also distinguish different instances of the same type of object,thereby reducing the impact of dynamic objects on the SLAM system’s *** article not only introduces traditional dynamic SLAM systems based on mathematical models but also provides a comprehensive analysis of existing instance segmentation algorithms and dynamic SLAM systems based on instance segmentation,comparing and summarizing their advantages and *** comparisons on datasets,it is found that instance segmentation-based methods have significant advantages in accuracy and robustness in dynamic ***,the real-time performance of instance segmentation algorithms hinders the widespread application of dynamic SLAM *** recent years,the rapid development of single-stage instance segmentationmethods has brought hope for the widespread application of dynamic SLAM systems based on instance ***,possible future research directions and improvementmeasures are discussed for reference by relevant professionals.

关键词： Dynamic SLAM instance segmentation visual odometry

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Systematic investigation of Radix Salviae for treating diabetic peripheral neuropathy disease based on network Pharmacology

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World Journal of Diabetes 2024年第5期15卷 945-957页

作者： Tao Kang Xiao qin Yan chen Qian Yang Department of Neurology Shaanxi Provincial People’s HospitalXi'an 710068Shaanxi ProvinceChina

BACKGROUND Diabetic peripheral neuropathy(DPN)is a debilitating complication of diabetes mellitus with limited available treatment *** Salviae,a traditional Chinese herb,has shown promise in treating DPN,but its therapeutic mech-anisms have not been systematically *** Radix Salviae(Danshen in pinin),a traditional Chinese medicine(TCM),is widely used to treat DPN in ***,the mechanism through which Radix Salviae treats DPN remains ***,we aimed to explore the mechanism of action of Radix Salviae against DPN using network *** The active ingredients and target genes of Radix Salviae were screened using the TCM pharmacology database and analysis *** genes associated with DPN were obtained from the Gene Cards and OMIM databases,a drug-com-position-target-disease network was constructed,and a protein–protein inter-action network was subsequently constructed to screen the main *** Ontology(GO)functional annotation and pathway enrichment analysis were performed via the Kyoto Encyclopedia of Genes and Genomes(KEGG)using *** A total of 56 effective components,108 targets and 4581 DPN-related target genes of Radix Salviae were *** with Radix Salviae for DPN mainly involved 81 target *** top 30 major targets were selected for enrichment analysis of GO and KEGG *** These results suggested that Radix Salviae could treat DPN by regulating the AGE-RAGE signaling pathway and the PI3K-Akt signaling ***,Danshen may affect DPN by regulating inflammation and apoptosis.

关键词： Diabetic peripheral neuropathy Radix Salviae Network pharmacology Systematic investigation

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In-Vehicle Network Injection Attacks Detection Based on Feature Selection and Classification

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Automotive Innovation 2024年第1期7卷 138-149页

作者： Haojie Ji Liyong Wang Hongmao qin Yinghui Wang Junjie Zhang Biao chen Key Laboratory of Modern Measurement and Control Technology Ministry of EducationBeijing Information Science and Technology UniversityBeijing 100192China State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body College of Mechanical and Vehicle EngineeringHunan UniversityChangsha 410082China School of Transportation Science and Engineering Beihang UniversityBeijing 100191China Hefei Innovation Research Institute Beihang UniversityHefei 230012China

Detecting abnormal data generated from cyberattacks has emerged as a crucial approach for identifying security threats within in-vehicle *** transmission of information through in-vehicle networks needs to follow specific data for-mats and communication protocols ***,statistical algorithms are employed to learn these variation rules and facilitate the identification of abnormal ***,the effectiveness of anomaly detection outcomes often falls short when confronted with highly deceptive in-vehicle network *** this study,seven representative classification algorithms are selected to detect common in-vehicle network attacks,and a comparative analysis is employed to identify the most suitable and favorable detection *** consideration of the communication protocol characteristics of in-vehicle networks,an optimal convolutional neural network(CNN)detection algorithm is proposed that uses data field characteristics and classifier selection,and its comprehensive performance is *** addition,the concept of Hamming distance between two adjacent packets within the in-vehicle network is introduced,enabling the proposal of an enhanced CNN algorithm that achieves robust detection of challenging-to-identify abnormal *** paper also presents the proposed CNN classifica-tion algorithm that effectively addresses the issue of high false negative rate(FNR)in abnormal data detection based on the timestamp feature of data *** experimental results validate the efficacy of the proposed abnormal data detection algorithm,highlighting its strong detection performance and its potential to provide an effective solution for safeguarding the security of in-vehicle network information.

关键词： Classification algorithm Anomaly detection In-vehicle network Feature extraction Injecting attack

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