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Aromatic and olefinic C–H alkenylation by catalysis with spirocyclic NHC Ru(Ⅳ) pincer complex

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Science China Chemistry 2023年第10期66卷 2791-2796页

作者： Heng Cai Yong-Qiang Tu Ka Lu Qi-Long Chen Fu-Min Zhang Xiao-Ming Zhang yuan-jiang pan Zhi-Bo Yan State Key Laboratory of Applied Organic Chemistry&College of Chemistry and Chemical Engineering Lanzhou UniversityLanzhou 730000China School of Chemistry and Chemical Engineering Frontiers Science Center for Transformative MoleculesShanghai Jiao Tong UniversityShanghai 200240China Department of Chemistry Zhejiang UniversityHangzhou 310027China

Catalyst innovation lies at the heart of transition-metal-catalyzed reaction development. In this article, we have explored the C(sp2)–H alkenylation activity with novel spirocyclic N-heterocyclic carbene(NHC)-based cyclometalated ruthenium pincer catalyst system, SNRu-X. After screening catalyst and condition, a high valent Ru(Ⅳ) dioxide(X = O_(2)) species has demonstrated superior reactivity in the catalytic alkenylation of aromatic and olefinic C–H bonds with unactivated alkenyl bromides and triflates. This reaction has achieved the easy construction of a wide range of(hetero)aromatic alkenes and dienes, in good to excellent yields with exclusive selectivity. Preliminary mechanistic studies indicate that this reaction may proceed through a single electron transfer(SET) triggered oxidative addition, by doing so, providing valuable complementary to classical alkenylation reactions that are dependent on activated alkenyl precursors.

关键词： transitionmetal catalysis spirocyclic NHC-Ru pincer catalyst C-H alkenylation single electron transfer pathway unactivated alkenyl bromides and triflates

Simulation study of the performance of the Very Large Area gamma-ray Space Telescope

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Nuclear Science and Techniques 2024年第9期35卷 1-17页

作者： Xu pan Wei jiang Chuan Yue Shi-Jun Lei Yu-Xin Cui Qiang yuan Key Laboratory of Dark Matter and Space Astronomy Purple Mountain ObservatoryChinese Academy of SciencesNanjing 210023China School of Astronomy and Space Science University of Science and Technology of ChinaHefei 230026China

The Very Large Area gamma-ray Space Telescope(VLAST)is a mission concept proposed to detect gamma-ray photons through both Compton scattering and electron–positron pair production mechanisms,thus enabling the detection of photons with energies ranging from MeV to *** project aims to conduct a comprehensive survey of the gamma-ray sky from a low-Earth orbit using an anti-coincidence detector,a tracker detector that also serves as a low-energy calorimeter,and a high-energy imaging *** developed a Monte Carlo simulation application of the detector using the GEANT4 toolkit to evaluate the instrument performance,including the effective area,angular resolution,and energy resolution,and explored specific optimizations of the detector *** simulation-based analysis indicates that the current design of the VLAST is physically feasible,with an acceptance above 10 m^(2)sr which is four times larger than that of the Fermi-LAT,an energy resolution better than 2%at 10 GeV,and an angular resolution better than 0.2◦at 10 *** VLAST project promises to make significant contributions to the field of gamma-ray astronomy and enhance our understanding of the cosmos.

关键词： Space astronomy Gamma-ray telescope Calorimeter Monte Carlo simulation

Preliminary studies on the chemical characterization and antioxidant properties of acidic polysaccharides from Sargassum fusiforme

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Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2008年第9期9卷 721-727页

作者： Jing ZHOU, Nan HU, Ya-lin WU, yuan-jiang pan, Cui-rong SUN (Department of Chemistry, Zhejiang University, Hangzhou 310027, China) Department of Chemistry Zhejiang University Hangzhou 310027 China.

In order to investigate the antioxidant properties of the polysaccharides from the brown alga Sargassum fusiforme, the crude polysaccharides from S. fusiforme (SFPS) were extracted in hot water, and the lipid peroxidation inhibition assay exhibited that SFPS possessed a potential antioxidant activity. Hence, two purely polymeric fractions, SFPS-1 and SFPS-2 were isolated by the column of DEAE (2-diethylaminoethanol)-Sepharose Fast Flow, with their molecular weights of 51.4 and 30.3 kDa determined by high performance gel permeation chromatography (HPGPC). They were preliminarily characterized using chemical analysis in combination of infrared (IR) and nuclear magnetic resonance (NMR) spectroscopies and found to contain large amounts of uronic acids and β-glycosidical linkages. The antioxidant activities of these two SFPS fractions were evaluated using superoxide and hydroxyl radical-scavenging assays. The results show that the antioxidant ability of SFPS-2 was higher than that of SFPS-1, probably correlating with the molecular weight and uronic acid content.

关键词： Sargassum fusiforme Polysaccharide Antioxidant activity Uronic acid Molecular weight

New Diterpenoid Alkaloids from Delphinium Souliei Franch

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Chinese Chemical Letters 1999年第5期10卷 395-396页

作者： Lan HE yuan jiang pan Xuan pan Bo Gang LI Yao Zu CHEN(Department of Chemistry. Beijing Normal University. Beijing 100085 Department of Chemistry. Zhejiang University. Hangzhou 310027Department of Pharmcy. Lanzhou Medical College. Lanzhou 730000The Che Beijing Normal Univ Dept Chem Beijing 100085 Peoples R China Zhejiang Univ Dept Chem Hangzhou 310027 Peoples R China Lanzhou Med Coll Dept Pharm Lanzhou 730000 Peoples R China Chinese Acad Sci Chengdu Inst Biol Chengdu 610041 Peoples R China

Continuing investigation of Delphinium souliei Franch yielded two minor new diterpenoid alkaloids--souline E(1) and souline F(2), their structures were determined on the basis of spectroscopic evidences.

关键词： Delphinium souliei new deterpenoid alkaloids souline E and F spectral data

A Minor New Diterpenoid Alkaloids from the Roots of Delphinium Souliei Franch

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Chinese Chemical Letters 1999年第12期10卷 0-0页

作者： Lan HE yuan jiang pan Bo Gang LI Yao Zu CHEN(1Department of Chemistry, Beijing Normal University, Beijing, 100085)(2 Department of Chemistry, Zhejiang University, Hangzhou 310027)(3The Chengdu institute of Biology, Chinese Academy of Sciences, Chengdu Beijing Normal Univ Dept Chem Beijing 100085 Peoples R China Zhejiang Univ Dept Chem Hangzhou 310027 Peoples R China Chinese Acad Sci Chengdu Inst Biol Chengdu 610041 Peoples R China

A minor new diterpenoid alkaloid, soulidine, was isolated from the roots of DelphiniumSouliei Franch, its structure was established on the basis of spectral evidences.

关键词： DeIPhinium souliei new deterpenoid alkaloid soulidine spectral data.

Scavenging activity and mechanism study of ferulic acid against reactive carbonyl species acrolein

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Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2019年第11期20卷 868-876页

作者： Zhi-hao TAO Chang LI Xiao-fei XU yuan-jiang pan Department of Chemistry Zhejiang UniversityHangzhou 310027China College of Life Sciences Zhejiang Chinese Medical UniversityHangzhou 310053China

Acrolein,known as one of the most common reactive carbonyl species,is a toxic small molecule affecting human health in daily *** study is focused on the scavenging abilities and mechanism of ferulic acid and some other phenolic acids against *** the 13 phenolic compounds investigated,ferulic acid was found to have the highest efficiency in scavenging acrolein under physiological *** acid remained at(3.04±1.89)%and acrolein remained at(29.51±4.44)%after being incubated with each other for 24 *** molecular mechanism of the detoxifying process was also *** products,namely 2-methoxy-4-vinyIphenol(product 21)and 5-(4-hydroxy-3-methoxyphenyl)pent-4-enal(product 22),were identified though nuclear magnetic resonanee(NMR)and gas chromatography-mass spectrometry(GC-MS),after the scavenging *** acid showed significant activity in scavenging acrolein under physiological *** study indicates a new method for inhibiting damage from acrolein.

关键词： Acrolein Reactive carbonyl species Ferulic acid Cytotoxicity Oxidative stress

Real-Time Intelligent Diagnosis of Co-frequency Vibration Faults in Rotating Machinery Based on Lightweight-Convolutional Neural Networks

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Chinese Journal of Mechanical Engineering 2024年第2期37卷 264-282页

作者： Xin pan Xiancheng Zhang Zhinong jiang Guangfu Bin Beijing Key Laboratory of Health Monitoring and Self-recovery for High-End Mechanical Equipment College of Mechanical and Electrical EngineeringBeijing University of Chemical TechnologyBeijing 100029China Key Laboratory of Engine Health Monitoring-Control and Networking(Ministry of Education) College of Mechanical and Electrical EngineeringBeijing University of Chemical TechnologyBeijing 100029China College of Mechanical Engineering Hunan University of Science and TechnologyXiangtan 411201China

The co-frequency vibration fault is one of the common faults in the operation of rotating equipment,and realizing the real-time diagnosis of the co-frequency vibration fault is of great significance for monitoring the health state and carrying out vibration suppression of the *** engineering scenarios,co-frequency vibration faults are highlighted by rotational frequency and are difficult to identify,and existing intelligent methods require more hardware conditions and are exclusively ***,Lightweight-convolutional neural networks(LW-CNN)algorithm is proposed in this paper to achieve real-time fault *** critical parameters are discussed and verified by simulated and experimental signals for the sliding window data augmentation *** on LW-CNN and data augmentation,the real-time intelligent diagnosis of co-frequency is ***,a real-time detection method of fault diagnosis algorithm is proposed for data acquisition to fault *** is verified by experiments that the LW-CNN and sliding window methods are used with high accuracy and real-time performance.

关键词： Co-frequency vibration Real-time diagnosis LW-CNN Data augmentation

MAUN:Memory-Augmented Deep Unfolding Network for Hyperspectral Image Reconstruction

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1139-1150页

作者： Qian Hu Jiayi Ma yuan Gao Junjun jiang Yixuan yuan Electronic Information School Wuhan UniversityWuhan 430072China School of Computer Science and Technology Harbin Institute of TechnologyHarbin 150001China Department of Electronic Engineering Chinese University of Hong KongHong Kong 999077China

Spectral compressive imaging has emerged as a powerful technique to collect the 3D spectral information as 2D *** algorithm for restoring the original 3D hyperspectral images(HSIs)from compressive measurements is pivotal in the imaging *** approaches painstakingly designed networks to directly map compressive measurements to HSIs,resulting in the lack of interpretability without exploiting the imaging *** some recent works have introduced the deep unfolding framework for explainable reconstruction,the performance of these methods is still limited by the weak information transmission between iterative *** this paper,we propose a Memory-Augmented deep Unfolding Network,termed MAUN,for explainable and accurate HSI ***,MAUN implements a novel CNN scheme to facilitate a better extrapolation step of the fast iterative shrinkage-thresholding algorithm,introducing an extra momentum incorporation step for each iteration to alleviate the information ***,to exploit the high correlation of intermediate images from neighboring iterations,we customize a cross-stage transformer(CSFormer)as the deep denoiser to simultaneously capture self-similarity from both in-stage and cross-stage features,which is the first attempt to model the long-distance dependencies between iteration *** experiments demonstrate that the proposed MAUN is superior to other state-of-the-art methods both visually and *** code is publicly available at https://***/HuQ1an/MAUN.

关键词： Deep folding iteration

Drug-Target Interactions Prediction Based on Signed Heterogeneous Graph Neural Networks

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Chinese Journal of Electronics 2024年第1期33卷 231-244页

作者： Ming CHEN Yajian jiang Xiujuan LEI Yi pan Chunyan JI Wei jiang College of Information Science and Engineering Hunan Normal University School of Computer Science Shaanxi Normal University Faculty of Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of Sciences Computer Science Department BNU-HKBU United International College

Drug-target interactions(DTIs) prediction plays an important role in the process of drug *** computational methods treat it as a binary prediction problem, determining whether there are connections between drugs and targets while ignoring relational types information. Considering the positive or negative effects of DTIs will facilitate the study on comprehensive mechanisms of multiple drugs on a common target, in this work, we model DTIs on signed heterogeneous networks, through categorizing interaction patterns of DTIs and additionally extracting interactions within drug pairs and target protein pairs. We propose signed heterogeneous graph neural networks(SHGNNs), further put forward an end-to-end framework for signed DTIs prediction, called SHGNN-DTI,which not only adapts to signed bipartite networks, but also could naturally incorporate auxiliary information from drug-drug interactions(DDIs) and protein-protein interactions(PPIs). For the framework, we solve the message passing and aggregation problem on signed DTI networks, and consider different training modes on the whole networks consisting of DTIs, DDIs and PPIs. Experiments are conducted on two datasets extracted from Drug Bank and related databases, under different settings of initial inputs, embedding dimensions and training modes. The prediction results show excellent performance in terms of metric indicators, and the feasibility is further verified by the case study with two drugs on breast cancer.

关键词： Drugs Training Proteins Measurement Message passing Prediction methods Graph neural networks