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Ecological network analysis reveals complex responses of tree species life stage interactions to stand variables

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Journal of Forestry research 2024年第1期35卷 29-43页

作者： Hengchao Zou Huayong Zhang Tousheng Huang research center for engineering Ecology and Nonlinear Science North China Electric Power UniversityBeijing 102206People’s Republic of China

Tree interactions are essential for the structure,dynamics,and function of forest ecosystems,but variations in the architecture of life-stage interaction networks(LSINs)across forests is unclear.Here,we constructed 16 LSINs in the mountainous forests of northwest Hebei,China based on crown overlap from four mixed forests with two dominant tree species.Our results show that LSINs decrease the complexity of stand densities and basal areas due to the interaction cluster differentiation.In addition,we found that mature trees and saplings play different roles,the first acting as“hub”life stages with high connectivity and the second,as“bridges”controlling information flow with high centrality.Across the forests,life stages with higher importance showed better parameter stability within LSINs.These results reveal that the structure of tree interactions among life stages is highly related to stand variables.Our efforts contribute to the understanding of LSIN complexity and provide a basis for further research on tree interactions in complex forest communities.

关键词： Tree interactions Life stages Interaction networks Ecological complexity

Effects of virtual agents on interaction efficiency and environmental immersion in MR environments

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虚拟现实与智能硬件（中英文） 2024年第2期6卷 169-179页

作者： Yihua BAO Jie GUO Dongdong WENG Yue LIU Zeyu TIAN beijing engineering research center of Mixed Reality and Advanced Display Beijing Institute of TechnologyBeijing 100081China Pengcheng Laboratory Shenzhen 518038China

Background Physical entity interactions in mixed reality(MR)environments aim to harness human capabilities in manipulating physical objects,thereby enhancing virtual environment(VEs)functionality.In MR,a common strategy is to use virtual agents as substitutes for physical entities,balancing interaction efficiency with environmental immersion.However,the impact of virtual agent size and form on interaction performance remains unclear.Methods Two experiments were conducted to explore how virtual agent size and form affect interaction performance,immersion,and preference in MR environments.The first experiment assessed five virtual agent sizes(25%,50%,75%,100%,and 125%of physical size).The second experiment tested four types of frames(no frame,consistent frame,half frame,and surrounding frame)across all agent sizes.Participants,utilizing a head mounted display,performed tasks involving moving cups,typing words,and using a mouse.They completed questionnaires assessing aspects such as the virtual environment effects,interaction effects,collision concerns,and preferences.Results Results from the first experiment revealed that agents matching physical object size produced the best overall performance.The second experiment demonstrated that consistent framing notably enhances interaction accuracy and speed but reduces immersion.To balance efficiency and immersion,frameless agents matching physical object sizes were deemed optimal.Conclusions Virtual agents matching physical entity sizes enhance user experience and interaction performance.Conversely,familiar frames from 2D interfaces detrimentally affect interaction and immersion in virtual spaces.This study provides valuable insights for the future development of MR systems.

关键词： Mixed reality Virtual agents Interaction performance Environmental immersion Virtual environments

Ecological impacts of the expansion of offshore wind farms on trophic level species of marine food chain

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Journal of Environmental Sciences 2024年第5期139卷 226-244页

作者： Lijing Wang Bangguo Wang Wenxi Cen Rui Xu Yuwei Huang Xin Zhang Yinghui Han Yuanxun Zhang College of Resources and Environment University of Chinese Academy of SciencesBeijing 101408China Yanshan Earth Critical Zone and Surface Fluxes research Station University of Chinese Academy of SciencesBeijing 101408China Chinese research Academy of Environmental Sciences Beijing 100012China National Joint research center for Yangtze River Conservation Beijing 100012China College of Environmental engineering Beijing University of TechnologyBeijing 100124China Institute of Eco-Environmental Forensics Shandong UniversityQingdao 266237China

The global demand for renewable energy has resulted in a rapid expansion of offshore wind farms(OWFs)and increased attention to the ecological impacts of OWFs on the marine ecosystem.Previous reviews mainly focused on the OWFs’impacts on individual species like birds,bats,or mammals.This review collected numerous field-measured data and simulated results to summarize the ecological impacts on phytoplankton,zooplankton,zoobenthos,fishes,and mammals from each trophic level and also analyze their interactions in the marine food chain.Phytoplankton and zooplankton are positively or adversely affected by the‘wave effect’,‘shading effect’,oxygen depletion and predation pressure,leading to a ±10% fluctuation of primary production.Although zoobenthos are threatened transiently by habitat destruction with a reduction of around 60% in biomass in the construction stage,their abundance exhibited an over 90% increase,dominated by sessile species,due to the‘reef effect’in the operation stage.Marine fishes and mammals are to endure the interferences of noise and electromagnetic,but they are also aggregated around OWFs by the‘reef effect’and‘reserve effect’.Furthermore,the complexity of marine ecosystem would increase with a promotion of the total system biomass by 40% through trophic cascade effects strengthen and resource partitioning alternation triggered by the proliferation of filter-feeders.The suitable site selection,long-term monitoring,and life-cycle-assessment of ecological impacts of OWFs that are lacking in current literature have been described in this review,as well as the carbon emission and deposition.

关键词： Offshore wind farms(OWFs) Ecological impacts Plankton Benthos Fish Mammal

Field-based evidence for the enrichment of intrinsic antibiotic resistome stimulated by plant-derived fertilizer in agricultural soil

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Journal of Environmental Sciences 2024年第1期135卷 728-740页

作者： Shihai Liu Ziming Han Dong Zhu Xiao Luan Liujie Deng Liping Dong Min Yang Yu Zhang State Key Laboratory of Environmental Aquatic Chemistry Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China State Key Laboratory of Urban and Regional Ecology Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China State Environmental Protection engineering center for Harmless Treatment and Resource Utilization of Antibiotic Residues Khorgos 835007China University of Chinese Academy of Sciences Beijing 100049China

Animal manures have been demonstrated to enhance antibiotic resistance in agricultural soils.However,little is known about the effects of plant-derived fertilizer on soil antibiotic resistome.Herein,metagenomic sequencing was used to investigate the effects of a plantderived fertilizer processed from sugarcane and beet on soil antibiotic resistance genes(ARGs)in a soybean field along crop growth stages.ARG profiles in the soils amended by plant-derived fertilizer were compared with those in the soils amended by chicken manure.The abundance and diversity of total ARGs in the soils amended by plant-derived fertilizer were significantly(P<0.05)elevated at the sprout stage,to a level comparable to that in the manured soils.Whereas,unlike chicken manure mainly introducing manure-borne ARGs to soil,the plant-derived fertilizer was indicated to mainly enrich multidrug resistance genes in soil by nourishing indigenous bacteria.ARGs with abundances in amended soils significantly(P<0.05)higher than in unamended soils at the sprout stage of soybean were considered as enriched ARGs.Decrease in the abundance of the enriched ARGs was observed in both the amended soils from the sprout to the harvest.Network analysis further identified Proteobacteria and Bacteroidetes as the primary bacterial taxa involved in the temporal variation of the enriched ARGs in the soils amended by plant-derived fertilizer,while in manured soils were Firmicutes and Actinobacteria.As revealed by multivariate statistical analyses,variation of the enriched ARGs in the soils amended by plant-derived fertilizer was majorly attributed to the response of co-occurred bacteria to depleting nutrients,which was different from the failed establishment of manure-borne bacteria in the manured soils.Our study provided field-based evidence that plant-derived fertilizer stimulated the intrinsic antibiotic resistome,and proposed attention to the un-perceived risk since some clinically relevant ARGs originate and evolve from natural resistome.

关键词： Organic fertilizer Intrinsic antibiotic resistance Indigenous bacteria Metagenomic sequencing

Efficient construction of calcium fluoride nanoaggregates for enhanced water vapor adsorption

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Particuology 2024年第6期89卷 191-197页

作者： Dan-Lei Yang Jing Cao Rong-Kun Liu Jie-Xin Wang School of Life Sciences and Chemical engineering Jiangsu Second Normal UniversityNanjing210013China State Key Laboratory of Organic-Inorganic Composites Beijing University of Chemical TechnologyBeijing 100029China research center of the Ministry of Education for High Gravity engineering and Technology Beijing University of Chemical TechnologyBeijing100029China Petrochemical research Institute PetroChinaBeijing102206China

Calcium fluoride(CaF_(2))is an ideal adsorbent for the dehydration of gaseous hydrogen fluoride(HF)containing water vapor.In this work,a novel CaF_(2)absorbent,spherical CaF_(2)nanoaggregates(NAs)with a closely packed structure,was proposed and efficiently fabricated by spray drying technology.As the building blocks of CaF_(2)NAs,the CaF_(2)nanoparticles(NPs)were prepared by the addition of excess calcium ions(Ca^(2+))or fluorine ions(F−)in the synthesis.The results indicated that the CaF_(2)NPs synthesized by excess Ca^(2+)and the corresponding NAs exhibited much better water vapor adsorption properties than their counterparts by excess F−,owing to higher zeta potentials.More importantly,whether excess Ca^(2+)or F^(−),CaF_(2)NAs had further enhanced water vapor adsorption capacity compared to primary CaF_(2)NPs,possibly owing to their unique nano-micro secondary structures and higher surface areas.This work has great potential in the development of high-performance absorbents for separating moisture from corrosive gas HF.

关键词： CaF_(2)nanoaggregates Water vapor adsorption Spray drying

Optimal geometrical configuration and oxidation state of cobalt cations in spinel oxides to promote the performance of Li-O_(2) battery

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Nano research 2024年第1期17卷 221-227页

作者： Yu Zhang Shuting Zhang Mengwei Yuan Yufeng Li Rong Liu Caiyun Nan Chen Chen engineering research center of Advanced Rare Earth Materials Department of ChemistryTsinghua UniversityBeijing 100084China beijing Key Laboratory of Energy Conversion and Storage Materials Institution College of ChemistryBeijing Normal UniversityBeijing 100875China X-ray diffraction Lab Analytical and Testing CenterBeijing Normal UniversityBeijing 100875China

Co_(3)O_(4) is considered as one of promising cathode catalysts for lithium oxygen(Li-O_(2))batteries,which contains both tetrahedral Co^(2+)sites(Co^(2+)Td)and octahedral Co^(3+)sites(Co^(3+)Oh).It is important to reveal the effect of optimal geometric configuration and oxidation state of cobalt ion in Co_(3)O_(4) to improve the performance of Li-O_(2) batteries.Herein,through regulating the synthesis process,Co^(2+)and Co^(3+)sites in Co_(3)O_(4) were replaced with Zn and Al atoms to form materials with a unique Co site.The Li-O_(2) batteries based on ZnCo_(2)O_(4) showed longer cycle life than that of CoAl_(2)O_(4),suggesting that in Co_(3)O_(4),the Co^(3+)Oh site is a relatively better geometric configuration than Co^(2+)Td site for Li-O_(2) batteries.Theoretical calculations revealed that Co^(3+)Oh sites provide higher catalysis activity,regulating the adsorption energy of the intermediate LiO_(2) and accelerating the kinetics of the reaction in batteries,which further leads to the change of the morphology of the discharge product and ultimately improves the electrochemical performance of the batteries.

关键词： lithium oxygen(Li-O_(2))batteries geometrical configuration oxidation state lithium peroxide

Brain-inspired multimodal approach for effluent quality prediction using wastewater surface images and water quality data

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Frontiers of Environmental Science & engineering 2024年第3期18卷 69-82页

作者： Junchen Li Sijie Lin Liang Zhang Yuheng Liu Yongzhen Peng Qing Hu School of Environment Harbin Institute of TechnologyHarbin 150090China School of Environmental Science and engineering Southern University of Science and TechnologyShenzhen 518055China engineering Innovation center of SUSTech(beijing) Southern University of Science and TechnologyBeijing 100083China Faculty of Environment and Life Beijing University of TechnologyBeijing 100124China engineering research center of Intelligence Perception and Autonomous Control Ministry of EducationBeijing 100124China

Efficiently predicting effluent quality through data-driven analysis presents a significant advancement for consistent wastewater treatment operations.In this study,we aimed to develop an integrated method for predicting effluent COD and NH3 levels.We employed a 200 L pilot-scale sequencing batch reactor(SBR)to gather multimodal data from urban sewage over 40 d.Then we collected data on critical parameters like COD,DO,pH,NH_(3),EC,ORP,SS,and water temperature,alongside wastewater surface images,resulting in a data set of approximately 40246 points.Then we proposed a brain-inspired image and temporal fusion model integrated with a CNN-LSTM network(BITF-CL)using this data.This innovative model synergized sewage imagery with water quality data,enhancing prediction accuracy.As a result,the BITF-CL model reduced prediction error by over 23%compared to traditional methods and still performed comparably to conventional techniques even without using DO and SS sensor data.Consequently,this research presents a cost-effective and precise prediction system for sewage treatment,demonstrating the potential of brain-inspired models.

关键词： Wastewater treatment system Water quality prediction Data driven analysis Brain-inspired model Multimodal data Attention mechanism

Integrated Active Suspension and Anti-Lock Braking Control for Four-Wheel-Independent-Drive Electric Vehicles

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Chinese Journal of Mechanical engineering 2024年第1期37卷 87-98页

作者： Ze Zhao Lei Zhang Xiaoling Ding Zhiqiang Zhang Shaohua Li Liang Gu National engineering research center for Electric Vehicles Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Mechanical Behavior and System Safety of Traffic engineering Structures Shijiazhuang Tiedao UniversityShijiazhuang 050043China

This paper presents an integrated control scheme for enhancing the ride comfort and handling performance of a four-wheel-independent-drive electric vehicle through the coordination of active suspension system(ASS)and anti-lock braking system(ABS).First,a longitudinal-vertical coupled vehicle dynamics model is established by integrating a road input model.Then the coupling mechanisms between longitudinal and vertical vehicle dynamics are analyzed.An ASS-ABS integrated control system is proposed,utilizing an H∞controller for ASS to optimize load transfer effect and a neural network sliding mode control for ABS implementation.Finally,the effectiveness of the proposed control scheme is evaluated through comprehensive tests conducted on a hardware-in-loop(HIL)test platform.The HIL test results demonstrate that the proposed control scheme can significantly improve the braking performance and ride comfort compared to conventional ABS control methods.

关键词： Four-wheel-independent-drive electric vehicles Active suspension system(ASS) Anti-lock braking system(ABS) Vertical-longitudinal vehicle dynamics

Regression Method for Rail Fastener Tightness Based on center-Line Projection

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Chinese Journal of Mechanical engineering 2024年第2期37卷 356-371页

作者： Yuanhang Wang Duxin Liu Sheng Guo Yifan Wu Jing Liu Wei Li Hongjie Wang Robotics research center School of MechanicalElectronic and Control EngineeringBeijing Jiaotong UniversityBeijing 100044China China Construction Industrial&Energy engineering Group Co. Ltd.Nanjing 210023China

In the railway system,fasteners have the functions of damping,maintaining the track distance,and adjusting the track level.Therefore,routine maintenance and inspection of fasteners are important to ensure the safe operation of track lines.Currently,assessment methods for fastener tightness include manual observation,acoustic wave detection,and image detection.There are limitations such as low accuracy and efficiency,easy interference and misjudgment,and a lack of accurate,stable,and fast detection methods.Aiming at the small deformation characteristics and large elastic change of fasteners from full loosening to full tightening,this study proposes high-precision surface-structured light technology for fastener detection and fastener deformation feature extraction based on the center-line projection distance and a fastener tightness regression method based on neural networks.First,the method uses a 3D camera to obtain a fastener point cloud and then segments the elastic rod area based on the iterative closest point algorithm registration.Principal component analysis is used to calculate the normal vector of the segmented elastic rod surface and extract the point on the centerline of the elastic rod.The point is projected onto the upper surface of the bolt to calculate the projection distance.Subsequently,the mapping relationship between the projection distance sequence and fastener tightness is established,and the influence of each parameter on the fastener tightness prediction is analyzed.Finally,by setting up a fastener detection scene in the track experimental base,collecting data,and completing the algorithm verification,the results showed that the deviation between the fastener tightness regression value obtained after the algorithm processing and the actual measured value RMSE was 0.2196 mm,which significantly improved the effect compared with other tightness detection methods,and realized an effective fastener tightness regression.

关键词： Railway system Fasteners Tightness inspection Neural network regression 3D point cloud processing