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Effects ofAchnatherum inebriansecotypes and endophyte status on plant growth, plant nutrient, soil fertility and soil microbial community

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Soil science Society of America Journal 2022年第4期86卷

作者： Yuanyuan Jin Zhenjiang Chen Yali He James F. White Kamran Malik Taixiang Chen Chunjie Li State Key Laboratory of Grassland Agro-ecosystems Key Laboratory of Grassland Livestock Industry Innovation Ministry of Agriculture and Rural Affairs Engineering Research Center of Grassland Industry Ministry of Education Gansu Tech Innovation Centre of Western China Grassland Industry Centre for Grassland Microbiome College of Pastoral Agriculture Science and Technology Lanzhou Univ. Lanzhou 730000 China Contribution: Conceptualization Data curation Methodology Contribution: Data curation Investigation Dep. of Plant Biology Rutgers Univ. New Brunswick NJ 08901 USA Contribution: Funding acquisition Resources

Effects of endophytes infection on bacterial and fungal communities in soil have been extensively studied. However, how the presence of Epichloë endophytes and environmental factors influence the nitrifying genes abundance of ammonia-oxidizing archaea ( amoA -AOA) and bacteria ( amoA -AOB), and denitrifying genes abundances of N reduction ( nirS and nirK ) and nitrous oxide reduction ( nosZ ) in soil is unclear. In the study, the copy number of 16S rRNA , 18S rRNA , amo A-AOB, amoA -AOA, nirS , nirK , and nosZ genes in rhizosphere soils of drunken horse grass [ Achnatherum inebrians (Hance) Keng] with the infected (E+) and uninfected (E–)endophyte five ecotypes after 3 yr field cultivation were investigated using quantitative polymerase chain reaction (PCR). The effects of A. inebrians in geographic source on plant growth, soil fertility, and microbial community was greater than in different endophyte status. The copy number of the 16S rRNA , amoA -AOA, nirK , and nosZ genes from different ecotypes (Qinghai, QH; and Tianzhu, TZ) were significantly affected by Epichloë endophyte. The copy number of the 16S rRNA , 18S rRNA , amo A-AOB. amoA -AOA, nirS , nirK , and nosZ genes positively related to soil pH, moisture, C/N ratio, and soil ammonium nitrogen (NH 4 + ), and soil organic carbon (SOC) contents. Endophyte infection significantly increased plant biomass of A. inebrians from QH ecotype. Plant total chlorophyll and soil nitrate nitrogen (NO 3 – ) were the main factor for the Epichloë endophyte and ecotype to affect plant dry weight. Further studies are required to confirm the regulation of soil NO 3 – as an important factor in Epichloë endophyte affecting plant growth and the soil microbial community structure in relation to N cycling. The effects of Epichloë endophyte on plant and soil depends on ecotypes. The response of Epichloë gansuensis was stronger than that of Epichloë inebrians . Epichloë infection altered 16S, amoA -AOB and amoA -AOA, nirK and nosZ genes

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Sending-or-not-sending twin-field quantum key distribution with discrete-phase-randomized weak coherent states

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Physical Review Research 2020年第4期2卷 043304-043304页

作者： Cong Jiang Zong-Wen Yu Xiao-Long Hu Xiang-Bin Wang Jinan Institute of Quantum Technology Jinan Shandong 250101 People's Republic of China State Key Laboratory of Low-Dimensional Quantum Physics Department of Physics Tsinghua University Beijing 100084 People's Republic of China Data Communication Science and Technology Research Institute Beijing 100191 People's Republic of China Shanghai Branch CAS Center for Excellence and Synergetic Innovation Center in Quantum Information and Quantum Physics University of Science and Technology of China Shanghai 201315 People's Republic of China Shenzhen Institute for Quantum Science and Engineering and Physics Department Southern University of Science and Technology Shenzhen 518055 China

In many security proofs of quantum key distribution, the random phases of coherent states are assumed to be continuously modulated. However, in practice, we can only take discrete phase randomization to coherent-state sources. In this paper, we study the sending-or-not-sending (SNS) protocol with discrete-phase-randomized coherent states. We present the security proof of the SNS protocol with discrete phase modulation. We then present analytic formulas for key rate calculation. With the decoy-state method and the properties of trace distance, we get the analytical formula of the upper bound of the phase-flip error rate. We also get the lower bound of the yield of untagged bits, which can be calculated by either analytical formula or linear programming. Our numerical simulation results show that with only six phase values, the key rates of the SNS protocol can exceed the linear bound and, with 12 phase values, the key rates are very close to the results of the SNS protocol with continuously modulated phase randomization.

关键词： Quantum cryptography

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Identifying Highly Influential Travellers for Spreading Disease on a Public Transport System

Identifying Highly Influential Travellers for Spreading Dise...

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IEEE International Symposium on World of Wireless Mobile and Multimedia Networks (WoWMoM)

作者： Ahmad El Shoghri Jessica Liebig Raja Jurdak Lauren Gardner Salil S. Kanhere University of New South Wales Sydney NSW Australia Data61 Commonwealth Scientific and Industrial Research Organization Brisbane QLD AUSTRALIA School of Computer Science Queensland University of Technology Brisbane QLD AUSTRALIA Department of Civil and Systems Engineering Johns Hopkins University Baltimore MD USA Research Center for Integrated Transport Innovation (rCITI) UNSW Sydney Sydney NSW AUSTRALIA School of Computer Science and Engineering University of New South Wales Sydney NSW AUSTRALIA

ISBN: (数字)9781728173740

ISBN: (纸本)9781728173757

The recent outbreak of a novel coronavirus and its rapid spread underlines the importance of understanding human mobility. Enclosed spaces, such as public transport vehicles (e.g. buses and trains), offer a suitable environment for infections to spread widely and quickly. Investigating the movement patterns and the physical encounters of individuals on public transit systems is thus critical to understand the drivers of infectious disease outbreaks. For instance, previous work has explored the impact of recurring patterns inherent in human mobility on disease spread, but has not considered other dimensions such as the distance travelled or the number of encounters. Here, we consider multiple mobility dimensions simultaneously to uncover critical information for the design of effective intervention strategies. We use one month of citywide smart card travel data collected in Sydney, Australia to classify bus passengers along three dimensions, namely the degree of exploration, the distance travelled and the number of encounters. Additionally, wes imulate disease spread on the transport network and trace the infection paths. We investigate in detail the transmissions between the classified groups while varying the infection probability and the suspension time of pathogens. Our results show that characterizing individuals along multiple dimensions simultaneously uncovers a complex infection interplay between the different groups of passengers, that would remain hidden when considering only a single dimension. We also identify groups that are more influential than others given specific disease characteristics, which can guide containment and vaccination efforts.

关键词： Pathogens Australia Suspensions Global Positioning System Infectious diseases Sociology

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Macro-scale roughness reveals the complex history of asteroids Didymos and Dimorphos

arXiv

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arXiv 2024年

作者： Vincent, Jean-Baptiste Asphaug, Erik Barnouin, Olivier Beccarelli, Joel Benavidez, Paula G. Campo-Bagatin, Adriano Chabot, Nancy L. Ernst, Carolyn M. Hasselmann, Pedro H. Hirabayashi, Masatoshi Ieva, Simone Karatekin, Özgür Kašpárek, Tomáš Kohout, Tomáš Lin, Zhong-Yi Lucchetti, Alice Michel, Patrick Murdoch, Naomi Pajola, Maurizio Parro, Laura M. Raducan, Sabina D. Sunshine, Jessica Tancredi, Gonzalo Trigo-Rodriguez, Josep M. Zinzi, Angelo DLR Institute of Planetary Research Berlin Germany Lunar and Planetary Laboratory University of Arizona TucsonAZ85721 United States Johns Hopkins University Applied Physics Laboratory LaurelMD United States INAF-OAPD Astronomical Observatory of Padova Italy IUFACyT - DFISTS Universidad de Alicante Spain INAF-OAR Rome Italy Daniel Guggenheim School of Aerospace Engineering Georgia Institute of Technology United States Royal Observatory of Belgium Brussels Belgium Brno University of Technology Czech Republic Department of Geosciences and Geography University of Helsinki Finland Institute of Geology of the Czech Academy of Sciences Czech Republic Institute of Astronomy National Central University No. 300 Zhongda Rd. Zhongli Dist. Taoyuan City32001 Taiwan Université Côte d’Azur Observatoire de la Côte d’Azur CNRS Laboratoire Lagrange Nice France The University of Tokyo Department of Systems Innovation School of Engineering Tokyo Japan Université de Toulouse Toulouse France University of Bern Switzerland Department of Astronomy Department of Geology College ParkMD United States Facultad de Ciencias Universidad de la República Uruguay Campus UAB c/Can Magrans s/n Cerdanyola del vallès Catalonia Barcelona Spain ASI-Space Science Data Center Roma Italy

Morphological mapping is a fundamental step in studying the processes that shaped an asteroid surface. Yet, it is challenging and often requires multiple independent assessments by trained experts. Here, we present fast methods to detect and characterize meaningful terrains from the topographic roughness: entropy of information, and local mean surface orientation. We apply our techniques to Didymos and Dimorphos, the target asteroids of NASA’s DART mission: first attempt to deflect an asteroid. Our methods reliably identify morphological units at multiple scales. The comparative study reveals various terrain types, signatures of processes that transformed Didymos and Dimorphos. Didymos shows the most heterogeneity and morphology that indicate recent resurfacing events. Dimorphos is comparatively rougher than Didymos, which may result from the formation process of the binary pair and past interaction between the two bodies. Our methods can be readily applied to other bodies and data sets. © 2024, CC BY.

关键词： Image processing

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Multi-label classification for multi-temporal, multi-spatial coral reef condition monitoring using vision foundation model with adapter learning

arXiv

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arXiv 2025年

作者： Shao, Xinlei Chen, Hongruixuan Zhao, Fan Magson, Kirsty Chen, Jundong Li, Peiran Wang, Jiaqi Sasaki, Jun Department of Socio-Cultural Environmental Studies Graduate School of Frontier Sciences The University of Tokyo Chiba Kashiwa277-8563 Japan Department of Complexity Science and Engineering Graduate School of Frontier Sciences The University of Tokyo Chiba Kashiwa277-8563 Japan Department of Environment Systems Graduate School of Frontier Sciences The University of Tokyo Chiba Kashiwa277-8563 Japan New Heaven Reef Conservation Program Koh Tao Surat Thani84360 Thailand Data Science and AI Innovation Research Promotion Center Shiga University Shiga Hikone522-8522 Japan Interfaculty Initiative in Information Studies The University of Tokyo Tokyo113-0033 Japan

Coral reef ecosystems provide essential ecosystem services, but face significant threats from climate change and human activities. Although advances in deep learning have enabled automatic classification of coral reef conditions, conventional deep models struggle to achieve high performance when processing complex underwater ecological images. Vision foundation models, known for their high accuracy and cross-domain generalizability, offer promising solutions. However, fine-tuning these models requires substantial computational resources and results in high carbon emissions. To address these challenges, adapter learning methods such as Low-Rank Adaptation (LoRA) have emerged as a solution. This study introduces an approach integrating the DINOv2 vision foundation model with the LoRA fine-tuning method. The approach leverages multi-temporal field images collected through underwater surveys at 15 dive sites at Koh Tao, Thailand, with all images labeled according to universal standards used in citizen science-based conservation programs. The experimental results demonstrate that the DINOv2-LoRA model achieved superior accuracy, with a match ratio of 64.77%, compared to 60.34% achieved by the best conventional model. Furthermore, incorporating LoRA reduced the trainable parameters from 1,100M to 5.91M. Transfer learning experiments conducted under different temporal and spatial settings highlight the exceptional generalizability of DINOv2-LoRA across different seasons and sites. This study is the first to explore the efficient adaptation of foundation models for multi-label classification of coral reef conditions under multi-temporal and multi-spatial settings. The proposed method advances the classification of coral reef conditions and provides a tool for monitoring, conserving, and managing coral reef ecosystems. © 2025, CC BY-NC-SA.

关键词： Biotic

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Accelerating drug repurposing for COVID-19 via modeling drug mechanism of action with large scale gene-expression profiles

arXiv

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arXiv 2020年

作者： Han, Lu Shan, Guangcun Chu, Bingfeng Wang, Hongyu Wang, Zhongjian Gao, Shengqiao Zhou, Wenxia Beijing Institute of Pharmacology and Toxicology State Key Laboratory of Toxicology and Medical Countermeasures Beijing100850 China School of Instrumentation Science and Opto-electronics Engineering Beijing Advanced Innovation Center for Big Data-based Precision Medicine Beihang University Beijing100083 China First Medical Center of PLA General Hospital Beijing100853 China Chengdu Jianshu Technology Co. Ltd Chengdu610015 China

The novel coronavirus disease, COVID-19, has rapidly spread worldwide. Developing methods to identify the therapeutic activity of drugs based on phenotypic data can improve the efficiency of drug development. Here, a state-of-the-art machine-learning method was used to identify drug mechanisms of action (MoA) based on the cell image features of 1105 drugs in the LINCS database. As the multi-dimensional features of cell images are affected by non-experimental factors, the characteristics of similar drugs vary considerably, and it is difficult to effectively identify the MoA of drugs as there is substantial noise. By applying the supervised information theoretic metric-learning (ITML) algorithm, a linear transformation made drugs with the same MoA aggregate. By clustering drugs to communities and performing enrichment analysis, we found that transferred image features were more conducive to the recognition of drug MoA. Image features analysis showed that different features play important roles in identifying different drug functions. Drugs that significantly affect cell survival or proliferation, such as cyclin-dependent kinase inhibitors, were more likely to be enriched in communities, whereas other drugs might be decentralized. Chloroquine and clomiphene, which block the entry of virus, were clustered into the same community, indicating that similar MoA could be reflected by the cell image. Overall, the findings of the present study laid the foundation for the discovery of MoAs of new drugs, based on image data. In addition, it provided a new method of drug repurposing for COVID-19. Copyright © 2020, The Authors. All rights reserved.

关键词： Coronavirus

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Lifelong property price prediction: A case study for the toronto real estate market

arXiv

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arXiv 2020年

作者： Peng, Hao Li, Jianxin Wang, Zheng Yang, Renyu Liu, Mingzhe Zhang, Mingming Yu, Philip S. He, Lifang Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100083 China School of Computing University of Leeds LeedsLS2 9JT United Kingdom UrBrain Technology Canada Department of Computer Science University of Illinois at Chicago Chicago60607 United States Department of Computer Science and Engineering Lehigh University BethlehemPA18015 United States

We present LUCE, the first life-long predictive model for automated property valuation. LUCE addresses two critical issues of property valuation: the lack of recent sold prices and the sparsity of house data. It is designed to operate on a limited volume of recent house transaction data. As a departure from prior work, LUCE organizes the house data in a heterogeneous information network (HIN) where graph nodes are house entities and attributes that are important for house price valuation. We employ a Graph Convolutional Network (GCN) to extract the spatial information from the HIN for house-related data like geographical locations, and then use a Long Short Term Memory (LSTM) network to model the temporal dependencies for house transaction data over time. Unlike prior work, LUCE can make effective use of the limited house transactions data in the past few months to update valuation information for all house entities within the HIN. By providing a complete and up-to-date house valuation dataset, LUCE thus massively simplifies the downstream valuation task for the targeting properties. We demonstrate the benefit of LUCE by applying it to large, real-life datasets obtained from the Toronto real estate market. Extensive experimental results show that LUCE not only significantly outperforms prior property valuation methods but also often reaches and sometimes exceeds the valuation accuracy given by independent experts when using the actual realization price as the ground truth. Copyright © 2020, The Authors. All rights reserved.

关键词： Long short-term memory

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Model Predictive Control for Spacecraft Attitude Maneuver under Actuators Power Limitation

Model Predictive Control for Spacecraft Attitude Maneuver un...

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第三十八届中国控制会议

作者： Xinxin Zhang Mingmin Liu Qinglei Hu School of Automation Science and Electrical Engineering Beihang University Shanghai Aerospace Control Technology Institude Beijing Advanced Innovation Center for Big-Data Based Precision Medicine Beihang University

This paper proposes a model predictive controller for power-limited spacecraft attitude maneuver considering the actuators' power limitation and the torque and angular momentum saturation. In the space exploration mission, the power provided by the solar panels is limited, and the performance of the reaction wheels is related to the available power. Therefore,the available power for reaction wheels is taken into account in controller design. Besides, the control torque and angular momentum constraints of reaction wheels are also described as inequalities herein. Then, the constrained discrete-time spacecraft attitude dynamics actuated by redundant reaction wheels is derived and the model predictive control is implemented to calculate the control torque while minimizing the special performance index. The validity and effectiveness of the proposed scheme are illustrated through numerical simulations.

关键词： Power Limitation Attitude Maneuver Redundant Reaction Wheels Model Predictive Control

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Satellite mission planning for moving targets observation via data driven approach

Satellite mission planning for moving targets observation vi...

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第三十八届中国控制会议

作者： Xin Wen Mingmin Liu Qinglei Hu School of Automation Science and Electrical Engineering Beihang University Shanghai Aerospace Control Technology Institute Beijing Advanced Innovation Center for Big-Data Based Precision Medicine Beihang University

Satellite mission planning is an important premise for earth observation. Traditional satellite mission planning is mainly aimed at fixed ground targets, which cannot meet the increasingly complex mission requirements. This paper considers the moving target observation, and puts forward a method of satellite mission planning via data driven approach. This method forecasts the future track and position information of the moving target through a modified Long Short-Term Memory(M-LSTM) networks algorithm, and proposes a Constraint Satisfaction Genetic Algorithm(CSGA) to plan the missions of moving target observation based on the results of M-LSTM algorithm. In view of the complexity of the constraint and task conflict in the moving target observation, CSGA embeds the constraints into the genetic algorithm through conditional forms, and a conflict resolution operator is designed in CSGA to resolve task conflicts. Simulation results demonstrate the efficiency of the LSTM-CSGA method to solve the mission planning and get a higher observation accuracy.

关键词： Moving target observation mission planning Long Short-Term Memory networks Constraint Satisfaction Genetic Algorithm

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Graphene Mediates Charge Transfer between Lead Chromate and a Cobalt Cubane Cocatalyst for Photocatalytic Water Oxidation

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Angewandte Chemie 2023年第21期135卷

作者： Wenchao Jiang Lingcong Zhang Chenwei Ni Ming Shi Yue Zhao Yuting Deng Haibo Chi Ruotian Chen Prof. Xiuli Wang Prof. Rengui Li Prof. Can Li School of Chemistry and Materials Science University of Science and Technology of China 230026 Hefei China State Key Laboratory of Catalysis Dalian National Laboratory for Clean Energy iChEM (Collaborative Innovation Center of Chemistry for Energy Materials) Dalian Institute of Chemical Physics Chinese Academy of Sciences 116023 Dalian China Contribution: Data curation (lead) Formal analysis (lead) Investigation (lead) Writing - original draft (lead) Writing - review & editing (lead) University of Chinese Academy of Sciences Center of Materials Science and Optoelectronics Engineering 100049 Beijing China Contribution: Formal analysis (supporting) Contribution: Formal analysis (lead) Funding acquisition (lead) Investigation (equal) Writing - original draft (lead) Writing - review & editing (lead)

The interfacial barrier of charge transfer from semiconductors to cocatalysts means that the photogenerated charges cannot be fully utilized, especially for the challenging water oxidation reaction. Using cobalt cubane molecules (Co 4 O 4 ) as water oxidation cocatalysts, we rationally assembled partially oxidized graphene (pGO), acting as a charge-transfer mediator, on the hole-accumulating {−101} facets of lead chromate (PbCrO 4 ) crystal. The assembled pGO enables preferable immobilization of Co 4 O 4 molecules on the {−101} facets of the PbCrO 4 crystal, which is favorable for the photogenerated holes transferring from PbCrO 4 to Co 4 O 4 molecules. The surface charge-transfer efficiency of PbCrO 4 was boosted by selective assembly of pGO between PbCrO 4 and Co 4 O 4 molecules. An apparent quantum efficiency for photocatalytic water oxidation on the Co 4 O 4 /pGO/PbCrO 4 photocatalyst exceeded 10 % at 500 nm. This strategy of rationally assembling charge-transfer mediator provides a feasible method for acceleration of charge transfer and utilization in semiconductor photocatalysis.

关键词： Charge-Transfer Mediator Lead Chromate Photocatalysis Spatial Charge Separation Water Oxidation Cocatalysts

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