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Cu-catalyzed cross-couplings under ligandless conditions

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Chinese Chemical Letters 2007年第10期18卷 1199-1202页

作者： chuan zhou tao Juan Li Xin Cui Yao Fu Qing Xiang Guo Department of Chemistry University of Science and Technology of China Hefei 230026 China

The possibility to carry out Cu-catalyzed cross-couplings under ligandless conditions was studied. It was found that by using K3PO4 as the base, the cross-coupling could proceed successfully between aryl iodides and s... 详细信息

关键词： Cu Catalysis Cross-coupling Ligand free

Cu-catalyzed arylation of phosphinic amide facilitated by (±)-trans-cyclohexane-1,2-diamine

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Chinese Chemical Letters 2007年第9期18卷 1033-1036页

作者： Juan Li Song Lin Zhang chuan zhou tao Yao Fu Qing Xiang Guo Department of Chemistry University of Science and Technology of China Hefei 230026 China

Cu-catalyzed cross coupling between phosphinic amides and aryl halides was accomplished for the first time by using (±)-trans-cyclohexane-1,2-diamine as the ligand. This reaction provided a novel approach for synthesizing arylated phosphinic amides. Both kinetic measurement and theoretical calculation indicated that phosphinic amides were much less reactive than amides by about 10 times in Cu-catalyzed cross coupling.

关键词： Phosphinic amide Copper Catalyst Cross coupling

Synthesis of unnatural N-glycosyl α-amino acids via Petasis reaction

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Chinese Chemical Letters 2014年第4期25卷 532-534页

作者： chuan-zhou tao Zhong-Tang Zhang Jian-Wei Wu Rong-Hua Li Zhi-Ling Cao School of Chemical Engineering Huaihai Institute of Technology Jiangsu Marine Resources Development Research Institute

A convenient and efficient protocol for the synthesis of unnatural N-glycosyl cz-amino acids was developed. Condensation of 1,3,4,6-tetra-O-actyl-/%D-glucosamine hydrochloride, alkenyl boronic acid, and glyoxylic acid was achieved in CH2C12 to give the derivatives of 2-（N-glycosyl）aminobut-3-enoic acid which may find applications in glycobiology research and medicinal chemistry.

关键词： N-'Glycosyl s-amino acid Petasis reaction D-Glucosamine Alkenyl boronic acid

Track-before-detect for bistatic radar based on pseudo-spectrum

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Chinese Journal of Aeronautics 2024年第1期37卷 236-246页

作者： tao HAN Gongjian zhou School of Electronics and Information Engineering Harbin Institute of TechnologyHarbin 150001China Key Laboratory of Marine Environmental Monitoring and Information Processing Ministry of Industry and Information TechnologyHarbin 150001China

Track-Before-Detect(TBD) is an efficient method to detect dim targets for radars. Conventional TBD usually follows an approximate motion model of the target, which may cause an inaccurate integration of the target energy. A TBD technique on basis of pseudo-spectrum in mixed coordinates adopting an accurate motion model for bistatic radar system is developed in this *** predicted position in bistatic polar plane is derived according to a nonlinear function that exactly describes the constant Cartesian velocity motion. Then around the predicted position, a pseudo-spectrum is formulated and its samples are accumulated to the integration frame for energy integration. The evolution of the state and the procedure of accumulation of the target energy are derived elaborately. The superior performance of the proposed method is demonstrated by some simulations.

关键词： Weak target detection Bistatic radar Track-before-detect Pseudo-spectrum Multiframe integration

Physiological and pathological functions of circular RNAs in the nervous system

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Neural Regeneration Research 2024年第2期19卷 342-349页

作者： Min zhou Shi Li chuan Huang School of Life Sciences Chongqing UniversityChongqingChina

Circular RNAs(circRNAs)are a class of covalently closed single-stranded RNAs that are expressed during the development of specific cells and *** play crucial roles in physiological and pathological processes by sponging microRNAs,modulating gene transcription,controlling the activity of certain RNA-binding proteins,and producing functional peptides.A key focus of research at present is the functionality of circRNAs in the nervous system and several advances have emerged over the last 2 ***,the precise role of circRNAs in the nervous system has yet to be comprehensively *** this review,we first summarize the recently described roles of circRNAs in brain development,maturity,and ***,we focus on the involvement of circRNAs in various diseases of the central nervous system,such as brain cancer,chronic neurodegenerative diseases,acute injuries of the nervous system,and neuropathic pain.A better understanding of the functionality of circRNAs will help us to develop potential diagnostic,prognostic,and therapeutic strategies to treat diseases of the nervous system.

关键词： Alzheimer’s disease amyotrophic lateral sclerosis brain development circRNAs neuropathic pain Parkinson’s disease

C-CORE:Clustering by Code Representation to Prioritize Test Cases in Compiler Testing

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 2069-2093页

作者： Wei zhou Xincong Jiang chuan Qin School of Electronic Information and Electrical Engineering Shanghai Jiao Tong UniversityShanghai200240China Hikvision Research Institute Hangzhou Hikvision Digital Technology Co.Ltd.Hangzhou310051China

Edge devices,due to their limited computational and storage resources,often require the use of compilers for program ***,ensuring the security and reliability of these compilers is of paramount importance in the emerging field of edge *** widely used testing method for this purpose is fuzz testing,which detects bugs by inputting random test cases into the target ***,this process consumes significant time and *** improve the efficiency of compiler fuzz testing,it is common practice to utilize test case prioritization *** researchers use machine learning to predict the code coverage of test cases,aiming to maximize the test capability for the target compiler by increasing the overall predicted coverage of the test ***,these methods can only forecast the code coverage of the compiler at a specific optimization level,potentially missing many optimization-related *** this paper,we introduce C-CORE(short for Clustering by Code Representation),the first framework to prioritize test cases according to their code representations,which are derived directly from the source *** approach avoids being limited to specific compiler states and extends to a broader range of compiler ***,we first train a scaled pre-trained programming language model to capture as many common features as possible from the test cases generated by a *** this pre-trained model,we then train two downstream models:one for predicting the likelihood of triggering a bug and another for identifying code representations associated with ***,we cluster the test cases according to their code representations and select the highest-scoring test case from each cluster as the high-quality test *** reduction in redundant testing cases leads to time *** evaluation results reveal that code representations are better at distinguishing test capabilities,and C-CORE significantly enhanc

关键词： Compiler testing test case prioritization code representation

Design of AI-Enhanced and Hardware-Supported Multimodal E-Skin for Environmental Object Recognition and Wireless Toxic Gas Alarm

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Nano-Micro Letters 2024年第12期16卷 1-22页

作者： Jianye Li Hao Wang Yibing Luo Zijing zhou He Zhang Huizhi Chen Kai tao chuan Liu Lingxing Zeng Fengwei Huo Jin Wu State Key Laboratory of Optoelectronic Materials and Technologies and the Guangdong Province Key Laboratory of Display Material and Technology School of Electronics and Information TechnologySun Yat-Sen UniversityGuangzhou 510275People’s Republic of China Ministry of Education Key Laboratory of Micro and Nano Systems for Aerospace School of Mechanical EngineeringNorthwestern Polytechnical UniversityXi’an 710072People’s Republic of China Research&Development Institute of Northwestern Polytechnical University in Shenzhen Shenzhen 518063People’s Republic of China The Institute of Flexible Electronics(IFE Future Technologies)Xiamen UniversityXiamen 361005People’s Republic of China Key Laboratory of Flexible Electronics(KLOFE) School of Flexible Electronics(Future Technologies)Nanjing Tech University30 South Puzhu RoadNanjing 211816People’s Republic of China State Key Laboratory of Transducer Technology Shanghai 200050People’s Republic of China Guangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced Manufacturing Guangzhou 510641People’s Republic of China State Key Laboratory of Polymer Materials Engineering Sichuan UniversityChengdu 610065People’s Republic of China Guangdong Provincial Key Laboratory of Research and Development of Natural Drugs and School of Pharmacy Guangdong Medical UniversityDongguan 523808People’s Republic of China The First Dongguan Affiliated Hospital Guangdong Medical UniversityDongguan 523808People’s Republic of China Engineering Research Center of Polymer Green Recycling of Ministry of Education College of Environment and ResourcesFujian Normal UniversityFuzhou 350007People’s Republic of China

Post-earthquake rescue missions are full of challenges due to the unstable structure of ruins and successive *** of the current rescue robots lack the ability to interact with environments,leading to low rescue *** multimodal electronic skin(e-skin)proposed not only reproduces the pressure,temperature,and humidity sensing capabilities of natural skin but also develops sensing functions beyond it—perceiving object proximity and NO2 *** multilayer stacked structure based on Ecoflex and organohydrogel endows the e-skin with mechanical properties similar to natural *** robots integrated with multimodal e-skin and artificial intelligence(AI)algorithms show strong environmental perception capabilities and can accurately distinguish objects and identify human limbs through grasping,laying the foundation for automated post-earthquake ***,the combination of e-skin and NO2 wireless alarm circuits allows robots to sense toxic gases in the environment in real time,thereby adopting appropriate measures to protect trapped people from the toxic *** e-skin powered by AI algorithms and hardware circuits exhibits powerful environmental perception and information processing capabilities,which,as an interface for interaction with the physical world,dramatically expands intelligent robots’application scenarios.

关键词： Stretchable hydrogel sensors Multimodal e-skin Artificial intelligence Post-earthquake rescue Wireless toxic gas alarm

MCIF-Transformer Mask RCNN:Multi-Branch Cross-Scale Interactive Feature Fusion Transformer Model for PET/CT Lung Tumor Instance Segmentation

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Computers, Materials & Continua 2024年第6期79卷 4371-4393页

作者： Huiling Lu tao zhou School of Medical Information&Engineering Ningxia Medical UniversityYinchuan750004China School of Computer Science and Engineering North Minzu UniversityYinchuan750021China Key Laboratory of Image and Graphics Intelligent Processing of State Ethnic Affairs Commission NorthMinzu UniversityYinchuan750021China

The precise detection and segmentation of tumor lesions are very important for lung cancer computer-aided ***,in PET/CT(Positron Emission Tomography/Computed Tomography)lung images,the lesion shapes are complex,the edges are blurred,and the sample numbers are *** solve these problems,this paper proposes a Multi-branch Cross-scale Interactive Feature fusion Transformer model(MCIF-Transformer Mask RCNN)for PET/CT lung tumor instance segmentation,The main innovative works of this paper are as follows:Firstly,the ResNet-Transformer backbone network is used to extract global feature and local feature in lung *** pixel dependence relationship is established in local and non-local fields to improve the model perception ***,the Cross-scale Interactive Feature Enhancement auxiliary network is designed to provide the shallow features to the deep features,and the cross-scale interactive feature enhancement module(CIFEM)is used to enhance the attention ability of the fine-grained ***,the Cross-scale Interactive Feature fusion FPN network(CIF-FPN)is constructed to realize bidirectional interactive fusion between deep features and shallow features,and the low-level features are enhanced in deep semantic ***,4 ablation experiments,3 comparison experiments of detection,3 comparison experiments of segmentation and 6 comparison experiments with two-stage and single-stage instance segmentation networks are done on PET/CT lung medical image *** results showed that APdet,APseg,ARdet and ARseg indexes are improved by 5.5%,5.15%,3.11%and 6.79%compared with Mask RCNN(resnet50).Based on the above research,the precise detection and segmentation of the lesion region are realized in this *** method has positive significance for the detection of lung tumors.

关键词： PET/CT images instance segmentation mask RCNN interactive fusion transformer

Real-time predictions of the 2023–2024 climate conditions in the tropical Pacific using a purely data-driven Transformer model

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Science China Earth Sciences 2024年

作者： Rong-Hua ZHANG Lu zhou chuan GAO Lingjiang tao School of Marine Sciences Nanjing University of Information Science and Technology Laoshan Laboratory Key Laboratory of Ocean Observation and Forecasting Key Laboratory of Ocean Circulation and Waves Institute of OceanologyChinese Academy of Sciences University of Chinese Academy of Sciences

Following triple La Ni?a events during 2020–2022, the future evolution of climate conditions over the tropical Pacific has been a focused interest in ENSO-related communities. Observations and modeling studies indicate that an El Ni?o event is occurring in 2023; however, large uncertainties remain in terms of its detailed evolution, and the factors affecting its resultant amplitude remain to be understood. Here, a novel deep learning-based Transformer model is adopted to make real-time predictions for the 2023–2024 climate conditions in the tropical Pacific. Several key fields vital to the El Ni?o and Southern Oscillation(ENSO) in the tropical Pacific are collectively and simultaneously utilized in model training and in making predictions; therefore, this purely data-driven model is configured in both training and predicting procedures such that the coupled ocean-atmosphere interactions are adequately represented. Also similar to dynamic models, the prediction procedure is executed in a rolling manner to allow ocean-atmosphere anomaly exchanges month by month; the related key fields during multi-month time intervals(TIs) prior to prediction target months are taken as input predictors, serving as initial conditions to precondition the future evolution more effectively. Real-time predictions indicate that the climate conditions in the tropical Pacific are surely to develop into an El Ni?o state in late 2023. Furthermore, sensitivity experiments are conducted to examine how prediction skills are affected by the input predictor specifications, including TIs during which information on initial conditions is retained for making predictions. A comparison with other dynamic coupled models is also made to demonstrate the prediction performance for the 2023–2024 El Ni?o event.

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