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Chinese Journal of Chemistry 2021年第9期39卷 2422-2432页

作者： Yan-Rong Zeng Ya-Nan Li Jue Yang Ping Yi Lei huang lie-jun huang Wei Gu Zhan-Xing Hu Yan-Mei Li Chun-Mao Yuan Xiao-Jiang Hao State Key Laboratory of Functions and Applications of Medicinal Plants Guizhou Medical UniversityGuiyangGuizhou 550014China The Key Laboratory of Chemistry for Natural Products of Guizhou Province and Chinese Academy of Sciences GuiyangGuizhou 550014China State Key Laboratory of Phytochemistry and Plant Resources in West China Kunming Institute of BotanyChinese Academy of SciencesKunmingYunnan 650201China

Eleven biogenetically related polyprenylated acylphloroglucinols(PPAPs),including four novel skeletons(1-4)and five new com-pounds(5-9),were isolated from the flowers of Hypericum *** A-D(1-4)represented the first example of a unique dilactone structure containing carbonyl bonded single 5-lactone and tricyclic γ-lactone *** structures were elucidated by NMR analysis,X-ray crystallography,and ECD ***,we revised the structure of hyperibrin B to hy perm on one I(9)via NMR an alysis,a qua ntum computational chemistry method,and hypothetic bios yn thetic con *** compounds(5,6,and 9)with significant MDR reversal activity(RF ranging from 61 to 223)were superior to the positive control verapamil(MCF-7/ADR,RF:53;HepG2/ADRz RF:124).Mechanism study for compound 5 indicated that this compound could inhibit the function of P-gp tran sport rather tha n its expressi on,and the possible recog nition mechanism betwee n compo und 5 and P-gp was predicted by molecular docking.

关键词： Hypericum monogynum Phytochemistry Structure elucidation Biological activity Multidrug resistance reversal activity

Parallel Driving with Big Models and Foundation Intelligence in Cyber-hysical-ocial Spaces

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Research 2024年第2期2024卷 1-17页

作者： Xiao Wang jun huang Yonglin Tian Chen Sun lie Yang Shanhe Lou Chen Lv Changyin Sun Fei-Yue Wang School of Artificial Intelligence Anhui UniversityHefeiChina Macao University of Science and Technology MacaoChina State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijingChina MVSLab Department of Mechanical and Mechatronics EngineeringUniversity of Waterloo200 University Ave WestWaterlooON N2L3G1Canada School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingaporeSingapore

Recent years have witnessed numerous technical breakthroughs in connected and autonomous vehicles (CAVs). On the one hand, these breakthroughs have significantly advanced the development of intelligent transportation systems (ITSs);on the other hand, these new traffic participants introduce more complex and uncertain elements to ITSs from the social space. Digital twins (DTs) provide real-time, data-driven, precise modeling for constructing the digital mapping of physical-world ITSs. Meanwhile, the metaverse integrates emerging technologies such as virtual reality/mixed reality, artificial intelligence, and DTs to model and explore how to realize improved sustainability, increased efficiency, and enhanced safety. More recently, as a leading effort toward general artificial intelligence, the concept of foundation model was proposed and has achieved significant success, showing great potential to lay the cornerstone for diverse artificial intelligence applications across different domains. In this article, we explore the big models embodied foundation intelligence for parallel driving in cyber-physical-social spaces, which integrate metaverse and DTs to construct a parallel training space for CAVs, and present a comprehensive elucidation of the crucial characteristics and operational mechanisms. Beyond providing the infrastructure and foundation intelligence of big models for parallel driving, this article also discusses future trends and potential research directions, and the ?S?goals of parallel driving.

关键词： breakthrough integrate corners

Chimeric Monkey Born Alive with a High Contribution of Donor Cells

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Neuroscience Bulletin 2024年第6期40卷 849-851页

作者： Jia huang jun Wu Department of Molecular Biology University of Texas Southwestern Medical CenterDallasTX75390USA Hamon Center for Regenerative Science and Medicine University of Texas Southwestern Medical CenterDallasTX75390USA Cecil H.and Ida Green Center for Reproductive Biology Sciences University of Texas Southwestern Medical CenterDallasTX75390USA

Chimeras,which consist of cells from different individuals or different species,represent an important tool in biological *** in the early twentieth century,studies on chimeras have been focusing on understanding fundamental genetic and cellular developmental *** the advances in genetic engineering and embryonic stem cell(ESC)technology,chimeras have become an important tool for the generation of transgenic animals.

关键词： mechanisms advances developmental

Energy-information trade-off induces continuous and discontinuous phase transitions in lateral predictive coding

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Science China(Physics,Mechanics & Astronomy) 2024年第6期67卷 79-85页

作者： Zhen-Ye huang Ruyi Zhou Miao huang Hai-jun Zhou Key Laboratory for Theoretical Physics Institute of Theoretical PhysicsChinese Academy of SciencesBeijing 100190China School of Physical Sciences University of Chinese Academy of SciencesBeijing 100049China School of Optics and Photonics Beijing Institute of TechnologyBeijing 100081China Minjiang Collaborative Center for Theoretical Physics Minjiang UniversityFuzhou 350108China

Lateral predictive coding is a recurrent neural network that creates energy-efficient internal representations by exploiting statistical regularity in sensory ***,we analytically investigate the trade-off between information robustness and energy in a linear model of lateral predictive coding and numerically minimize a free energy *** observed several phase transitions in the synaptic weight matrix,particularly a continuous transition that breaks reciprocity and permutation symmetry and builds cyclic dominance and a discontinuous transition with the associated sudden emergence of tight balance between excitatory and inhibitory *** optimal network follows an ideal gas law over an extended temperature range and saturates the efficiency upper bound of energy *** results provide theoretical insights into the emergence and evolution of complex internal models in predictive processing systems.

关键词： predictive coding recurrent neural network phase transition internal model free energy

Joint Sample Position Based Noise Filtering and Mean Shift Clustering for Imbalanced Classification Learning

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Tsinghua Science and Technology 2024年第1期29卷 216-231页

作者： Lilong Duan Wei Xue jun huang Xiao Zheng School of Computer Science and Technology Anhui University of TechnologyMaanshan 243032China Institute of Artificial Intelligence Hefei Comprehensive National Science CenterHefei 230088China

The problem of imbalanced data classification learning has received much *** classification algorithms are susceptible to data skew to favor majority samples and ignore minority *** weighted minority oversampling technique(MWMOTE)is an effective approach to solve this problem,however,it may suffer from the shortcomings of inadequate noise filtering and synthesizing the same samples as the original minority *** this end,we propose an improved MWMOTE method named joint sample position based noise filtering and mean shift clustering(SPMSC)to solve these ***,in order to effectively eliminate the effect of noisy samples,SPMsC uses a new noise filtering mechanism to determine whether a minority sample is noisy or not based on its position and distribution relative to the majority *** that MWMOTE may generate duplicate samples,we then employ the mean shift algorithm to cluster minority samples to reduce synthetic replicate ***,data cleaning is performed on the processed data to further eliminate class *** on extensive benchmark datasets demonstrate the effectiveness of SPMsC compared with other sampling methods.

关键词： imbalanced data classification oversampling noise filtering clustering

An artificial intelligence approach for particle transport velocity prediction in horizontal flows

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Particuology 2024年第9期92卷 234-250页

作者： Haoyu Chen Zhiguo Wang Hai huang jun Zhang College of Petroleum Engineering Xi'an Shiyou UniversityXi'an710065China Shaanxi Key Laboratory of Carbon Dioxide Sequestration and Enhanced Oil Recovery Xi'an710065China College of New Energy Xi'an Shiyou UniversityXi'an710065China Engineering Research Center of Smart Energy and Carbon Neutral in Oil&Gas Field Universities of Shaanxi ProvinceChina The Erosion/Corrosion Research Center The University of TulsaOK74104United States

Particle entrainment is an inevitable phenomenon in pipeline systems,especially during the development and extraction phases of oil and gas *** predicting the critical velocity for particle transport is a key focus for implementing effective sand control *** work presents a semi-supervised learning–deep hybrid kernel extreme learning machine(SSL-DHKELM)model for predicting the critical velocity,which integrates multiple machine learning theories including the deep learning approach,which is adept at advanced feature ***,the SSL framework enhances the model's capabilities when data availability is *** improved slime mould algorithm is also employed to optimize the model's *** proposed model has high accuracy on both the sample dataset and out-of-sample *** trained with only 10%of the data,the model's error still did not increase ***,this model achieves superior predictive accuracy compared to existing mechanistic models,demonstrating its impressive performance and robustness.

关键词： Particle transport Critical velocity Deep learning Semi-supervised learning Extreme learning machine

Hole cleaning evaluation and installation spacing optimization of cuttings bed remover in extended-reach drilling

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Petroleum Science 2024年第3期21卷 2005-2022页

作者： Shuo Peng Wen-jun huang De-Li Gao MOE Key Laboratory of Petroleum Engineering China University of Petroleum-BeijingBeijing102249China State Key Laboratory of Petroleum Resources and Engineering China University of Petroleum-BeijingBeijing102249China

In extended-reach or long-horizontal drilling,cuttings usually deposit at the bottom of the *** cuttings accumulate to a certain thickness,complex problems such as excessive torque and drag,tubing buckling,and pipe stuck probably occur,which results in a lot of non-productive time and remedial *** bed remover can efficiently destroy deposited cuttings in time through hydraulic and mechanical stirring *** paper aims to build a method for hole cleaning evaluation and installation spacing optimization of cuttings bed remover to improve the wellbore cleaning ***,a Computational Fluid Dynamics approach with Eulerian—Eulerian multiphase model was utilized to investigate the mechanism of cuttings transportation,and a new type of cuttings bed remover was ***,an evaluation method of hole cleaning effect of remover was *** that,the effects of several drilling parameters on hole cleaning including flow rate of drilling fluid,rotational speed of drillpipe,rate of penetration,wellbore size,rheological property of drilling fluid,and remover eccentricity on the performance of cuttings bed remover were *** results demonstrate that the new type of remover with streamline blade performs better than conventional *** efficiency of hole cleaning is greatly improved by increasing the rotational speed of drillpipe,flow rate of drilling fluid,remover eccentricity,and 6 rpm Fann dial reading for drilling *** higher rate of penetration and large wellbore size result in worse hole *** findings can serve as an important guide for the structure optimization design of cuttings bed remover and installation spacing of removers.

关键词： Extended-reach drlling Drilling hydraulics Cuttings transport Hole cleaning Cuttings bed remover

Machine learning-assisted sparse observation assimilation for real-time aerodynamic field perception

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Science China(Technological Sciences) 2024年第5期67卷 1458-1469页

作者： ZHAO QingYu huang jun GUO YuXin PAN YuXuan JI JingJing huang YongAn State Key Laboratory of Intelligent Manufacturing Equipment and Technology School of Mechanical Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074China

Accurate aerodynamic distribution perception and real-time flight state evaluation are crucial for flight safety,e.g.,stall ***,the observations are usually sparse due to limitations in sensor mounting space and cost,and a reconstruction technology is urgently ***,a machine learning-assisted assimilation method based on sparse observations has been *** from the traditional reconstruction methods focusing on boundary condition correction,the proposed method formulates the flow field pressure distribution as a linear superposition of flow field modes,thereby forming a real-time reconstruction pattern that combines offline modal extraction using computational fluid dynamics(CFD)with real-time determination of modal weights using a neural *** this study,CFD simulations were conducted under 800different operating conditions for common modal extraction and model *** weights of these modes were determined online based on merely five observations for reconstructing the full pressure field.A pressure reconstruction with a relative error of 6.1%and a mean square error of 0.003 was achieved within the prescribed condition *** computational cost was just2 ms for each reconstruction run,significantly faster than the 20 min required by the classical reconstruction ensemble transform Kalman *** also showed that the method maintains almost the same accuracy amidst 1.5%measurement *** practical examples,shock waves and the change of lift coefficient were analyzed using the proposed method,providing remarkable evidence for the capability of the method in supporting stall *** validate the method’s effectiveness and explore its potential in real-time and accurate monitoring of an aircraft.

关键词： aerodynamic force sparse observation neural networks pressure field reconstruction

Quantifying the Tension between Cosmological Models and JWST Red Candidate Massive Galaxies

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Research in Astronomy and Astrophysics 2024年第4期24卷 1-6页

作者： jun-Chao Wang Zhi-Qi huang Lu huang Jianqi Liu School of Physics and Astronomy Sun Yat-sen UniversityZhuhai 519082China CSST Science Center for the Guangdong-Hong Kong-Macao Greater Bay Area Zhuhai519082China CAS Key Laboratory of Theoretical Physics Institute of Theoretical PhysicsChinese Academy of SciencesBeijing 100190China

We develop a Python tool to estimate the tail distribution of the number of dark matter halos beyond a mass threshold and in a given volume in a *** code is based on the extended Press-Schechter model and is computationally efficient,typically taking a few seconds on a personal laptop for a given set of cosmological *** high efficiency of the code allows a quick estimation of the tension between cosmological models and the red candidate massive galaxies released by the James Webb Space Telescope,as well as scanning the theory space with the Markov Chain Monte Carlo *** an example application,we use the tool to study the cosmological implication of the candidate galaxies presented in Labbéet *** standard Λcold dark matter(ΛCDM)model is well consistent with the data if the star formation efficiency can reach~0.3 at high *** a low star formation efficiency ε~0.1,theΛCDM model is disfavored at~2σ-3σconfidence level.

关键词： (cosmology:)cosmological parameters Galaxy:abundances Galaxy:formation

Research progress in performance improvement strategies and sulfur conversion mechanisms of Li-S batteries based on Fe series nanomaterials

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Nano Research 2024年第9期17卷 8045-8067页

作者： Ziyang huang Zhenghua Wang Lei Zhou jun Pu Key Laboratory of Functional Molecular Solids(Ministry of Education) College of Chemistry and Materials ScienceAnhui Provincial Engineering Laboratory for New-Energy Vehicle Battery Energy-Storage MaterialsAnhui Normal UniversityWuhu 241000China School of Energy and Power Engineering Jiangsu UniversityZhenjiang 212013China Department of Electrical Engineering Eindhoven University of TechnologyEindhoven MB 5600The Netherlands

Lithium-sulfur(Li-S)batteries hold the potential to revolutionize energy storage due to the high theoretical capacity and energy ***,the commercialization process is seriously hindered by the rapid capacity decay and low utilization of sulfur,caused by the inevitable slow dynamics and the“shuttle effect”.The incorporation of metal-based electrocatalysts into sulfur cathodes shows promise in promoting the conversion of lithium polysulfides(LiPSs),reducing the“shuttle effect”,and enhancing cell kinetics and cycle *** these,Fe-based materials,characterized by environmental friendliness,low cost,abundant reserves,and high activity,are extensively used in sulfur cathode *** article reviews the advancements of Fe-based materials in enhancing Li-S batteries in recent *** from single/multi-component Fe-based metal compounds and single/bimetallic atoms,the influence of different Fe coordination environments on the conversion mechanism of LiPSs is *** is hoped that this review and the proposed prospects can further stimulate the development and application of the Fe element in Li-S batteries in the future.

关键词： Li-S batteries Fe-based nanomaterials shuttle effect reaction kinetics