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Greenhouse gas emissions from Daihai Lake,China:Should eutrophication and salinity promote carbon emission dynamics?

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Journal of Environmental Sciences 2024年第1期135卷 407-423页

作者： Xiangwei Li Ruihong Yu jun wang Heyang Sun Xinyu Liu Xiaohui Ren shuai Zhuang Zhiwei Guo Xixi Lu Inner Mongolia Key Laboratory of River and Lake Ecology School of Ecology and EnvironmentInner Mongolia UniversityHohhot 010070China Key Laboratory of Mongolian Plateau Ecology and Resource Utilization Ministry of EducationHohhot 010070China Autonomous Region Collaborative Innovation Center for Integrated Management of Water Resources and Water Environment in the Inner Mongolia Reaches of the Yellow River Hohhot 010018China Department of Geography National University of Singapore117570Singapore

Greenhouse gases(GHGs)emitted or absorbed by lakes are an important component of the global carbon cycle.However,few studies have focused on the GHG dynamics of eutrophic saline lakes,thus preventing a comprehensive understanding of the carbon cycle.Here,we conducted four sampling analyses using a floating chamber in Daihai Lake,a eutrophication saline lake in Inner Mongolia Autonomous Region,China,to explore its carbon dioxide(CO_(2))and methane(CH_(4))emissions.The mean CO_(2)emission flux(FCO_(2))and CH_(4)emission flux(FCH_(4))were 17.54±14.54 mmol/m^(2)/day and 0.50±0.50 mmol/m^(2)/day,respectively.The results indicated that Daihai Lake was a source of CO_(2)and CH_(4),and GHG emissions exhibited temporal variability.The mean CO_(2)partial pressure(p CO_(2))and CH_(4)partial pressure(p CH_(4))were 561.35±109.59μatm and 17.02±13.45μatm,which were supersaturated relative to the atmosphere.The regression and correlation analysis showed that the main influencing factors of p CO_(2)were wind speed,dissolved oxygen(DO),total nitrogen(TN)and Chlorophyll a(Chl.a),whereas the main influencing factors of p CH_(4)were water temperature(WT),Chl.a,nitrate nitrogen(NO_(3)^(-)-N),TN,dissolved organic carbon(DOC)and water depth.Salinity regulated carbon mineralization and organic matter decomposition,and it was an important influencing factor of p CO_(2)and p CH_(4).Additionally,the trophic level index(TLI)significantly increased p CH_(4).Our study elucidated that salinity and eutrophication play an important role in the dynamic changes of GHG emissions.However,research on eutrophic saline lakes needs to be strengthened.

关键词： Eutrophication Salinity Greenhouse gas emissions Inland lake Inner Mongolia Autonomous Region

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A mix & act liposomes of phospholipase A2-phosphatidylserine for acute brain detoxification by blood‒brain barrier selective-opening

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Acta Pharmaceutica Sinica B 2024年第4期14卷 1827-1844页

作者： Zinan Zhang Wenbin Cao Huanchun Xing shuai Guo Lijuan Huang Lin wang Xin Sui Kui Lu Yuan Luo Yongan wang jun Yang State Key Laboratory of Toxicology and Medical Countermeasures Beijing Institutes of Pharmacology and ToxicologyBeijing 100850China Tianjin University of Science and Technology Tianjin 300222China Hebei University of Science and Technology Shijiazhuang 050018China

In the treatment of central nervous system disease,the blood-brain barrier(BBB)is a major obstruction to drug delivery that must be overcome.In this study,we propose a brain-targeted delivery strat-egy based on selective opening of the BBB.This strategy allows some simple bare nanoparticles to enter the brain when mixed with special opening material;however,the BBB still maintains the ability to completely block molecules from passing through.Based on the screening of BBB opening and matrix delivery mate-rials,we determined that phospholipase A2-catalyzed 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoserine li-posomes can efficiently carry drugs into the brain immediately.At an effective dose,this delivery system is safe,especially with its effect on the BBB being reversible.This mix&act delivery system has a simple structure and rapid preparation,making it a strong potential candidate for drug delivery across the BBB.

关键词： Liposomes Phospholipase A2 Phosphoserine Blood-brainbarrier Selectively open Mix&act

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Magnetic NiFe_(2)O_(4)@FeNi_(3)core-shell nanospheres derived from FeNi-LDH precursor anchoring on rGO nanosheets for enhanced electromagnetic wave absorption

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Journal of Materials Science & Technology 2024年第4期171卷 101-114页

作者： Kunyao Cao Yuan Fang shuai wang Yue Zhang Jiayue Wen jun Chen Rui Zhao Weidong Xue School of Materials and Energy University of Electronic Science and Technology of ChinaChengdu 610054China

Graphene has been extensively utilized in the domain of electromagnetic wave(EMW)absorption ma-terials because of its excellent electrical conductivity.However,the inferior impedance matching per-formance and the single loss mechanism vastly restrict the application.Hence,it’s an effective strat-egy to solve these issues by introducing magnetic components.Notably,layer double hydroxide(LDH)is an appropriate template to obtain magnetic component materials.Considering that ferromagnetic met-als such as Fe,Co,Ni,and their corresponding metal oxides are usually treated as magnetic compo-nents which are promising candidates for EMW absorption materials.Therefore,in this work,a FeNi-layered double hydroxide-reduced graphene oxide(FeNi-LDH-rGO)aerogel was synthesized through a series of processes such as electrostatic self-assembly,hydrothermal,freeze-drying,and annealing.The magnetic NiFe_(2)O_(4)@FeNi_(3)core-shell nanospheres were obtained from FeNi-LDH precursor,anchoring on rGO nanosheets after the annealing treatment.Furthermore,the effects of different mass ratios of LDH to GO as well as different annealing temperatures of LDH-rGO aerogel on the EMW absorption prop-erty and impedance matching performance were explored.As a consequence,the fabricated ultralight 600LDH-rGO 2:1 aerogel shows a broad effective absorption bandwidth(EAB)of 7.04 GHz at a thickness of 2.3 mm with a low filling content of only 6 wt%and a low density of 4.4 mg/cm^(3).In conclusion,the synthetic LDH-rGO aerogels offer an effective strategy for preparing EMW absorption materials that own three-dimensional porous network structure and unique magnetic NiFe_(2)O_(4)@FeNi_(3)core-shell struc-ture nanospheres.

关键词： Electrostatic self-assembly Electromagnetic wave absorption LDH-rGO aerogel Layered double hydroxide Reduced graphene oxide NiFe_(2)O_(4)@FeNi_(3)core-shell structure

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Ammonia storage and slip under steady and transient state in close-coupled SCR

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Journal of Environmental Sciences 2024年第4期138卷 470-481页

作者： Shiyu Liu Zhaohuan Zhang Zexian Guo Boyuan wang Buyu wang Xiao Ma Shijin shuai State Key Laboratory of Automotive Safety and Energy Tsinghua UniversityBeijing 100084China Institute for Aero Engine Tsinghua UniversityBeijing 100084China

The close-coupled selective catalytic reduction(cc-SCR)catalyst is an effective technology to reduce tailpipe NOx emission during cold start.This paper investigated the optimal ammonia storage under steady and transient state in the cc-SCR.The study showed that a trade-off between NOx conversion efficiency and ammonia slip is observed on the pareto solutions under steady state,and the optimal ammonia storage is calculated with ammonia slip less than 10μL/L based on the ChinaⅥemission legislation.The rapid temperature increase will lead to severe ammonia slip in the transient test cycle.A simplified 0-D calculation method on ammonia slip under transient state is proposed based on kinetic model of ammonia adsorption and desorption.In addition,the effect of ammonia storage,catalyst temperature and temperature increasing rate on ammonia slip are analyzed.The optimal ammonia storage is calculated with maximum ammonia slip less than 100μL/L according to the oxidation efficiency of ammonia slip catalyst(ASC)downstream cc-SCR.It was found that the optimal ammonia storage under transient state is much lower than that under steady state in cc-SCR at lower temperature,and a phase diagram is established to analyze the influence of temperature and temperature increasing rate on optimal ammonia storage.

关键词： Close-coupled SCR Ammonia storage and slip Steady and transient state Generic algorithm

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Vector meson effects on multi-Skyrmion states from the rational map ansatz

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中国科学:物理学、力学、天文学英文版 2023年第11期66卷 126-135页

作者： jun-shuai wang Yong-Liang Ma College of Physics Jilin UniversityChangchun130012China School of Fundamental Physics and Mathematical Sciences Hangzhou Institute for Advanced StudyUniversity of Chinese Academy of Sciences(UCAS)Hangzhou310024China TaiJi Laboratory for Gravitational Wave Universe(Beijing/Hangzhou) UCASBeijing100049China

The roles of the lightest vector mesons ρ and ω in the multi-Skyrmion states are studied using the hidden local symmetry approach up to the next-to-leading order,including the homogeneous Wess-Zumino terms.The low-energy constants in the effective field theory are determined using the Sakai-Sugimoto model and the flat-space five-dimensional Yang-Mills action.With only two inputs,m_(ρ) and f_(π),it is possible to determine all low-energy constants without ambiguity.The vector meson effects can be investigated by sequentially integrating vector mesons,and their geometry can be elucidated by comparing the results using the low-energy constants estimated from the Sakai-Sugimoto model and the flat-space five-dimensional Yang-Mills action.We found that theρmeson reduces the masses of the multi-Skyrmion states and increases the overlaps of their constituents,whereas theωmeson repulses the constituents of the multi-Skyrmion states and increases their masses.Therefore,these vector mesons are crucial in the Skyrme model approach to nuclei.We also found that the warping factor,an essential element in the holographic model of QCD,affects the properties of the multi-Skyrmion states and cannot be ignored.

关键词： vector meson multi-Skyrmion state rational map hidden local symmetry

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Event-triggered distributed optimization for model-free multi-agent systems

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Frontiers of Information Technology & Electronic Engineering 2024年第2期25卷 214-224页

作者： Shanshan ZHENG shuai LIU Licheng wang College of Science University of Shanghai for Science and TechnologyShanghai200093China College of Automation Engineering Shanghai University of Electric PowerShanghai200090China

In this paper,the distributed optimization problem is investigated for a class of general nonlinear model-free multi-agent systems.The dynamical model of each agent is unknown and only the input/output data are available.A model-free adaptive control method is employed,by which the original unknown nonlinear system is equivalently converted into a dynamic linearized model.An event-triggered consensus scheme is developed to guarantee that the consensus error of the outputs of all agents is convergent.Then,by means of the distributed gradient descent method,a novel event-triggered model-free adaptive distributed optimization algorithm is put forward.Sufficient conditions are established to ensure the consensus and optimality of the addressed system.Finally,simulation results are provided to validate the effectiveness of the proposed approach.

关键词： Distributed optimization Multi-agent systems Model-free adaptive control Event-triggered mechanism

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Photocatalytic transformation of selected biomass derivatives to value added chemicals and hydrogen fuel

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Chinese Chemical Letters 2024年第3期35卷 19-26页

作者： Xiangjun Liu shuai Zhang Miao wang junqi wang School of Human Settlements and Civil Engineering Xi'an Jiaotong UniversityXi'an 710049China

Biomass is the most bountiful renewable carbon resource on earth.Photocatalytic transformation is a promising method to utilize biomass to obtain high-value-added chemicals and it has more obvious advantages compared with thermochemical and biological processes due to the milder operational conditions,fewer reagents and equipment.Semiconductor material is one of the most common kinds of heterogeneous biomass photocatalysts,which has the advantages of high selectivity,stable catalytic performance,long activation time,and low cost.In this paper,the significant research progress on the photocatalytic transformation of biomass with semiconductor materials to produce high-value-added chemicals is reviewed,and the three most typical semiconductor photocatalysts(TiO_(2),Cd S,and g-C_(3)N_(4))are detailed.The photocatalytic mechanism and photocatalytic system optimization including structural modification,metal co-catalyst loading,and introduction of heterojunction are presented.Besides,the main problems,the development direction and trend of semiconductor materials in photocatalytic transformations of biomass in the future are prospected,which provide guidance and inspiration for the further development of semiconductor photocatalysts and make contributions to the progress in efficient utilization of biomass.

关键词： Photocatalytic transformation Biomass Semiconductor material H_(2) High value-added chemical

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DCEL:classifier fusion model for Android malware detection

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Journal of Systems Engineering and Electronics 2024年第1期35卷 163-177页

作者： XU Xiaolong JIANG shuai ZHAO Jinbo wang Xinheng Jiangsu Key Laboratory of Big Data Security&Intelligent Processing Nanjing University of Posts and TelecommunicationsNanjing 210023China School of Computer Science Nanjing University of Posts and TelecommunicationsNanjing 210023China School of Computing and Engineering University of West LondonLondon W55RFUK

The rapid growth of mobile applications,the popularity of the Android system and its openness have attracted many hackers and even criminals,who are creating lots of Android malware.However,the current methods of Android malware detection need a lot of time in the feature engineering phase.Furthermore,these models have the defects of low detection rate,high complexity,and poor practicability,etc.We analyze the Android malware samples,and the distribution of malware and benign software in application programming interface(API)calls,permissions,and other attributes.We classify the software’s threat levels based on the correlation of features.Then,we propose deep neural networks and convolutional neural networks with ensemble learning(DCEL),a new classifier fusion model for Android malware detection.First,DCEL preprocesses the malware data to remove redundant data,and converts the one-dimensional data into a two-dimensional gray image.Then,the ensemble learning approach is used to combine the deep neural network with the convolutional neural network,and the final classification results are obtained by voting on the prediction of each single classifier.Experiments based on the Drebin and Malgenome datasets show that compared with current state-of-art models,the proposed DCEL has a higher detection rate,higher recall rate,and lower computational cost.

关键词： Android malware detection deep learning ensemble learning model fusion

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Multi-level coarse-grained discrete element method modeling of cylinder particle flow in a rotating drum

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Particuology 2024年第5期88卷 218-238页

作者： Lei Xu Xiukai Wu shuai wang Shiyi Bao Institute of Process Equipment and Control Engineering Zhejiang University of TechnologyHangzhou 310023China Engineering Research Center of Process Equipment and Remanufacturing Ministry of EducationZhejiang University of TechnologyHangzhou 310023China College of Mechanical Engineering Zhejiang University of TechnologyHangzhou 310023China State Key Laboratory of Clean Energy Utilization Zhejiang UniversityHangzhou 310027China

The coarse-grained discrete element method(DEM)is probably a feasible option for simulating an actual drum-type biomass boiler,which contains over 10 million cylinder particles.A multi-level study was conducted based on particle and coarse-grained level data to evaluate the adequacy of the coarse-grained approach in terms of geometrical characteristics,kinematic features,and dynamic properties.Two scaling laws for contact parameters were used and compared during the simulations.The results show that the coarse-grained approach can accurately predict the positions of the free surface and active-passive interface,the mixing index,and the orientation properties.Deviations in the velocity fields may occur due to the worse flowability of coarse-grained particles near the free surface.The efficiency is significantly improved by the coarse-grained model compared with the corresponding original case(the same DEM code without a coarse-grained model was used for the original simulations).

关键词： Coarse-grained method Discrete element method(DEM) Cylinder particle Rotating drum Granular flow

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BCCLR:A Skeleton-Based Action Recognition with Graph Convolutional Network Combining Behavior Dependence and Context Clues

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Computers, Materials & Continua 2024年第3期78卷 4489-4507页

作者： Yunhe wang Yuxin Xia shuai Liu College of Information Science and Engineering Institute of Interdisciplinary StudiesHunan Normal UniversityChangsha410081China School of Educational Sciences Institute of Interdisciplinary StudiesHunan Normal UniversityChangsha410081China

In recent years,skeleton-based action recognition has made great achievements in Computer Vision.A graph convolutional network(GCN)is effective for action recognition,modelling the human skeleton as a spatio-temporal graph.Most GCNs define the graph topology by physical relations of the human joints.However,this predefined graph ignores the spatial relationship between non-adjacent joint pairs in special actions and the behavior dependence between joint pairs,resulting in a low recognition rate for specific actions with implicit correlation between joint pairs.In addition,existing methods ignore the trend correlation between adjacent frames within an action and context clues,leading to erroneous action recognition with similar poses.Therefore,this study proposes a learnable GCN based on behavior dependence,which considers implicit joint correlation by constructing a dynamic learnable graph with extraction of specific behavior dependence of joint pairs.By using the weight relationship between the joint pairs,an adaptive model is constructed.It also designs a self-attention module to obtain their inter-frame topological relationship for exploring the context of actions.Combining the shared topology and the multi-head self-attention map,the module obtains the context-based clue topology to update the dynamic graph convolution,achieving accurate recognition of different actions with similar poses.Detailed experiments on public datasets demonstrate that the proposed method achieves better results and realizes higher quality representation of actions under various evaluation protocols compared to state-of-the-art methods.

关键词： Action recognition deep learning GCN behavior dependence context clue self-attention

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