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Role of catalyst surface-active sites in the hydrogenation ofα,β-unsaturated aldehyde

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Frontiers of Chemical Science and Engineering 2024年第6期18卷 41-69页

作者： Haixiang Shi Tongming Su Zuzeng qin Hongbing ji School of Chemistry and Chemical Engineering Guangxi Key Laboratory of Petrochemical Resource Processing and Process Intensification TechnologyGuangxi UniversityNanning 530004China Zhejiang Green Petrochemical and Light Hydrocarbon Transformation Research Institute Zhejiang University of TechnologyHangzhou 310014China

As an important technology in fine chemical production,the selective hydrogenation ofα,β-unsaturated aldehydes has attracted much attention in recent *** the process ofα,β-unsaturated aldehyde hydrogenation,a conjugated system is formed between>C=CC=O,leading to hydrogenation at both ends of the conjugated system,which competes with each other and results in more complex ***,improving the reaction selectivity is also difficult in industrial ***,many researchers have reported that surface-active sites on catalysts play a crucial role inα,β-unsaturated aldehyde *** review attempts to summarize recent advances in understanding the effects of surface-active sites(SASs)over metal catalysts for enhancing the process of *** construction strategies and roles of SASs for hydrogenation catalysts are *** attention has been given to the adsorption configuration and transformation mechanism ofα,β-unsaturated aldehydes on catalysts,which contributes to understanding the relationship between SASs and hydrogenation *** addition,recent advances in metal-supported catalysts for the selective hydrogenation ofα,β-unsaturated aldehydes to understand the role of SASs in hydrogenation are briefly ***,the opportunities and challenges will be highlighted for the future development of the precise construction of SASs.

关键词： α,β-unsaturatedd aldehydes hydrogenation active site cinnamaldehyde

Resolution Enhancement of SOHO/MDI Magnetograms

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Research in Astronomy and Astrophysics 2024年第6期24卷 358-367页

作者： Ying qin Kai-Fan ji Hui Liu Xiao-Guang Yu Yunnan Observatories Chinese Academy of SciencesKunming 650011China University of Chinese Academy of Sciences Beijing 100049China Yunnan Key Laboratory of Solar Physics and Space Science Kunming 650216China Key Laboratory for the Structure and Evolution of Celestial Objects Chinese Academy of SciencesKunming 650216China

Research on the solar magnetic field and its effects on solar dynamo mechanisms and space weather events has benefited from the continual improvements in instrument resolution and measurement *** augmentation and assimilation of historical observational data timelines also play a significant role in understanding the patterns of solar magnetic field *** the realm of astronomical data processing,super-resolution(SR)reconstruction refers to the process of using a substantial corpus of training data to learn the nonlinear mapping between low-resolution(LR)and high-resolution(HR)images,thereby achieving higherresolution astronomical *** paper is an application study in high-dimensional nonlinear *** learning models were employed to perform SR modeling on SOHO/MDI magnetograms and SDO/HMI magnetograms,thus reliably achieving resolution enhancement of full-disk SOHO/MDI magnetograms and enhancing the image resolution to obtain more detailed *** this study,a data set comprising 9717pairs of data from 2010 April to 2011 February was used as the training set,1332 pairs from 2011 March were used as the validation set and 1034 pairs from 2011 April were used as the test *** data preprocessing,we randomly cropped 128×128 sub-images as the LR cases from the full-disk MDI magnetograms,and the corresponding 512×512 sub-images as HR ones from the HMI full-disk magnetograms for model *** tests conducted have shown that the study successfully produced reliable 4×SR reconstruction of full-disk MDI *** MESR model's results(0.911)were highly correlated with the target HMI magnetographs as indicated by the correlation coefficient ***,the method achieved the best PSNR,SSIM,MAE and RMSE values,indicating that the MESR model can effectively reconstruct magnetograms.

关键词： magnetic fields techniques:image processing virtual observatory tools Sun:magnetic fields

Experimental and numerical investigation of the impacts of rotor tip-rake on excitation forces of pump-jet propulsors

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Journal of Hydrodynamics 2024年第1期36卷 142-157页

作者： Xue-qin ji Xiao-song Zhang Chen-jun Yang Xiao-qian Dong State Key Laboratory of Ocean Engineering Marine Numerical Experiment CentreSchool of Naval ArchitectureOcean and Civil EngineeringShanghai Jiao Tong UniversityShanghai200240China CSSC Shanghai Marine Energy Saving Technology Co. Ltd.Shanghai200011China China Ship Scientific Research Center Shanghai Branch Shanghai200011China

The tip-clearance flow in a pump-jet propulsor exerts great impacts on the fluctuating pressures and resultant unsteady forces,which are important sources of structural vibrations and radiated noise *** blade geometry close to the tip is an important factor determining the vortex strength in the tip-clearance *** the open-water condition,the effects of raking the rotor tips on the duct-surface fluctuating pressures and the resultant unsteady forces acting on different components of the propulsor are investigated via physical model experiments and the numerical solution of Reynolds-averaged Navier-Stokes(RANS)equations coupled with the SST k-ωturbulence *** measured and simulated results of hydrodynamic pressures are consistent to each other,and the simulated flows help better understand why the fluctuating pressures change with the tip *** strong fluctuations of duct-surface pressures are caused by intensive tip separation *** duct-surface pressure fluctuations are effectively reduced by using the rake distribution near the tip towards blade back side and,for the combination of the five-bladed rotor and the seven-bladed stator,the resultant unsteady horizontal(and vertical)forces acting on the duct and stator are also reduced;while increasing rake leads to negative effect on pressure fluctuations and unsteady horizontal(and vertical)forces acting on all the components of the propulsor.

关键词： Pump-jet tip-clearance tip-rake fluctuating pressures excitation forces

An efficient data-driven global sensitivity analysis method of shale gas production through convolutional neural network

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Petroleum Science 2024年第4期21卷 2475-2484页

作者： Liang Xue Shuai Xu jie Nie ji qin jiang-Xia Han Yue-Tian Liu qin-Zhuo Liao State Key Laboratory of Petroleum Resources and Engineering China University of Petroleum (Beijing) Department of Oil-Gas Field Development Engineering College of Petroleum Engineering China University of Petroleum (Beijing) Chuanqing Drilling Engineering Co.Ltd. China National Petroleum Corporation

The shale gas development process is complex in terms of its flow mechanisms and the accuracy of the production forecasting is influenced by geological parameters and engineering parameters. Therefore, to quantitatively evaluate the relative importance of model parameters on the production forecasting performance, sensitivity analysis of parameters is required. The parameters are ranked according to the sensitivity coefficients for the subsequent optimization scheme design. A data-driven global sensitivity analysis(GSA) method using convolutional neural networks(CNN) is proposed to identify the influencing parameters in shale gas production. The CNN is trained on a large dataset, validated against numerical simulations, and utilized as a surrogate model for efficient sensitivity analysis. Our approach integrates CNN with the Sobol' global sensitivity analysis method, presenting three key scenarios for sensitivity analysis: analysis of the production stage as a whole, analysis by fixed time intervals, and analysis by declining rate. The findings underscore the predominant influence of reservoir thickness and well length on shale gas production. Furthermore, the temporal sensitivity analysis reveals the dynamic shifts in parameter importance across the distinct production stages.

关键词： Shale gas Global sensitivity Convolutional neural network Data-driven

Microplastic exposure disturbs sleep structure,reduces lifespan,and decreases ovary size in Drosophila melanogaster

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Zoological Research 2024年第4期45卷 805-820页

作者： Wei Yan Zi-jie Li Zi-Yi Lin Shu-qin ji William Ka Fai Tse Zhi-Qiang Meng chang Liu Lei Li Shenzhen-Hong Kong Institute of Brain Science Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhenGuangdong 518000China CAS Key Laboratory of Brain Connectome and Manipulation the Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhenGuangdong 518000China Laboratory of Developmental Disorders and Toxicology Center for Promotion of International Education and ResearchFaculty of AgricultureKyushu UniversityFukuokaFukuoka 819-0395Japan Shenzhen Key Laboratory of Drug Addiction the Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhenGuangdong 518000China Guangdong Provincial Key Laboratory of Brain Connectome and Behavior Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhenGuangdong 518000China

The organ-specific toxicity resulting from microplastic(MP)exposure has been extensively explored,particularly concerning the gut,liver,testis,and ***,under natural conditions,these effects are not restricted to specific organs or *** whether MP exposure presents a systemic threat to an entire organism,impacting factors such as lifespan,sleep,and fecundity,is *** this study,we investigated the effects of dietary exposure to two different doses of MPs(1–5μm)using the terrestrial model organism Drosophila *** indicated that the particles caused gut damage and remained within the digestive *** MP exposure significantly shortened the lifespan of adult *** short-term exposure disrupted sleep patterns,increasing the length of daytime sleep ***,one week of MP exposure reduced ovary size,with a trend towards decreased egg-laying in mated *** MPs did not penetrate the brain or ovaries,transcriptome analysis revealed altered gene expression in these *** the ovary,Gene Ontology(GO)analysis indicated genotoxic effects impacting inflammation,circadian regulation,and metabolic processes,with significant impacts on extracellular structure-related *** the brain,GO analysis identified changes in pathways associated with proteolysis and carbohydrate ***,this study provides compelling evidence of the systemic negative effects of MP exposure,highlighting the urgent need to address and mitigate environmental MP pollution.

关键词： Microplastics Sleep Lifespan Reproduction Risk assessment Drosophila melanogaster

Mitigation of black carbon emissions could immediately reduce 6.3% of glacier melting in the Qilian Mountains

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Advances in Climate change Research 2024年第4期15卷 725-736页

作者： ji-Zu CHEN Wen-Tao DU Shi-chang KANG Xiang qin Wei-Jun SUN Li-Hui LUO Yang LI Jun-Hua YANG You-Yan jiANG Qilian Shan Station of Glaciology and Eco-environment Key Laboratory of Cryospheric Science and Frozen Soil EngineeringNorthwest Institute of Eco-Environment and ResourcesChinese Academy of SciencesLanzhou 730000China College of Geography and Environment Shandong Normal UniversityJinan 250014China Zhangye Meteorological Bureau Zhangye 734000China Lanzhou Regional Climate Center Lanzhou 730020China Institute of International Rivers and Eco-security Yunnan UniversityKunming 650500China Gansu Provincial Industry Technology Center of Inteligent Equipment and Big Data for Disaster Prevention Northwest Institute of Eco-Environment and ResourcesChinese Academy of ScienceLanzhou 730000China

Global warming in tandem with surface albedo reduction caused by black carbon(BC)deposition on glaciers accelerated glacier melting;however,their respective contributions remain *** in the Qilian Mountains are crucial for the development of oases in the Hexi Corridor;however,their area has decreased by more than 20%over the past ***,this study developed a dynamic deposition model for light-absorbing particles(LAPs),coupled with a surface energy and mass balance *** comprehensively assessed the effects of BC and warming on the melting of a typical glacier in the Qilian Mountains based on the coupled *** on the glacier surface caused 13.1%of annual glacier-wide melting,of which directly deposited atmospheric BC reduced the surface albedo by 0.02 and accounted for 9.1%of glacier *** air temperature during 2000-2010 has increased by 1.5°C relative to that during the 1950s,accounting for 51.9%of current glacier ***,BC emission have increased by 4.6 times compared to those of the early Industrial Revolution recorded in an ice core,accounting conservatively for 6.3%of current glacier *** BC emissions has a limited influence on current glacier melting;however,in the long-term,mitigation should exert a noteworthy impact on glacier melting through the self-purification of glaciers.

关键词： Glacier Melting Black carbon Simulation Qilian Mountains

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

Huannao Yicong Decoction(还脑益聪方) Extract Reduces Inflammation and Cell Apoptosis in Aβ_(1-42)-Induced Alzheimer's Disease Model of Rats

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Chinese Journal of Integrative Medicine 2017年第9期23卷 672-680页

作者： WANG Qi LI Hao WANG Fei-xue GAO Lei qin ji-chang LIU jian-gang WEI Yun LIU Mei-xia Gerontology Department Xiyuan Hospital China Academy of Chinese Medical Sciences Graduate School Beijing University of Chinese Medicine

Objective： Huannao Yicong Decoction （还脑益聪方, HYD）, an effective herbal formula against Alzheimer＇s disease （AD）, has been proven to have neuroprotective action in amyloid β-protein1.42 （Aβ1-42）-induced rat model. This study was designed to characterize mechanisms by which HYD leads to suppression of inflammation and apoptosis in the brains of Aβ1-42-induced rat. Methods： A total of 72 rats were divided into 6 groups, which were referred to as： sham operation group, model group, donepezil-treated group, HYD low-dose group （HYDL）, HYD middle-dose group （HYDM） and HYD high-dose group （HYDH）. Rats in HYDL, HYDM and HYDH were injected with Aβ1-42 at the CA1 region of hippocampus to form AD model and were fed the HYD extract at different dose of 3.78, 7.56 and 18.90 g crude drug/kg. The behavioral changes of rats were evaluated by Morris water maze （MWM） before sacrifice. Pathological changes of the brain tissue were evaluated using hematoxylin eosin （HE） staining. The levels of intedeukin-1 （IL-1） and tumor necrosis factor-α （TNF-α ） were measured by radioimmunoassay. The levels of A 13 and proteins that are associated with apoptosis such as B-ceil lymphoma-2 protein （Bcl-2）, Bcl-2-associated X protein （Bax）, cysteine-aspartic protease （caspase）-3, -8, -9 and -12 in serum were measured by immunohistochemistry. Results： Compared with the sham operation group, the spatial learning and memory abilities of AD rats were significantly decreased （P〈0.05 or P〈0.01; Expressions of IL-1, TNF-α, Aβ and apoptosis-signaling proteins caspase-3, -8, -9, -12 were significantly up-regulated （P〈0.05 or P〈0.01）. The ratio of Bcl-2 to Bax were significantly decreased in the model group （P〈0.01）. When treated with HYD extract, the spatial learning and memory abilities of AD-model rats were significantly increased （P〈0.05 or P〈0.01）, IL-1, TNF- α, Aβ, caspase-3, -8, -9 and -12 were down-regulated （P〈0.05 or P〈0.01）, and the ratio of Bcl-2 to Bax were reduced （P〈0.05 or P〈0.01）. Conclusions： HY

关键词： Alzheimer's disease apoptosis inflammation Huannao Yicong Decoction Chinese medicinecompound

Data-driven casting defect prediction model for sand casting based on random forest classification algorithm

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China Foundry 2024年第2期21卷 137-146页

作者： Bang Guan Dong-hong Wang Da Shu Shou-qin Zhu Xiao-yuan ji Bao-de Sun Shanghai Key Lab of Advanced High-Temperature Materials and Precision Forming School of Materials Science and EngineeringShanghai Jiao Tong UniversityShanghai 200240China State Key Lab of Metal Matrix Composites Shanghai Jiao Tong UniversityShanghai 200240China Hefei Casting and Forging Factory of Anhui Heli Co. LtdHefei 230000China State Key Laboratory of Materials Processing and Die&Mould Technology Huazhong University of Science and TechnologyWuhan 430074China

The complex sand-casting process combined with the interactions between process parameters makes it difficult to control the casting quality,resulting in a high scrap rate.A strategy based on a data-driven model was proposed to reduce casting defects and improve production efficiency,which includes the random forest(RF)classification model,the feature importance analysis,and the process parameters optimization with Monte Carlo *** collected data includes four types of defects and corresponding process parameters were used to construct the RF *** results show a recall rate above 90% for all *** Gini Index was used to assess the importance of the process parameters in the formation of various defects in the RF ***,the classification model was applied to different production conditions for quality *** the case of process parameters optimization for gas porosity defects,this model serves as an experimental process in the Monte Carlo method to estimate a better temperature *** prediction model,when applied to the factory,greatly improved the efficiency of defect *** show that the scrap rate decreased from 10.16% to 6.68%.

关键词： sand casting process data-driven method classification model quality prediction feature importance