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  • 1
    In: Journal of Plant Ecology, Oxford University Press (OUP)
    Abstract: Managing invasions in the context of globalization is a challenge in part because of the difficulty of inferring invader impacts from their invasiveness (i.e., ability to invade ecosystems). Specifically, the relationship between invasiveness and impact may be context-dependent and it has not been explored in such a unique ecosystem as the Tibetan Plateau. Here, we investigated 32 invasive plant species on the Tibetan Plateau in terms of their distribution, abundance, per capita effects on natives and traits across a large geographic transect to test the relationship between invasiveness and impacts on native communities. We decomposed the components (range, R; local abundance, A; per capita effect, E) that drive impacts, and investigated the relative contributions of plant traits to these components. The results showed that there was no correlation between invasiveness (R × A) and impacts (R × A × E) of invasive species on the Tibetan Plateau. Specifically, plant invasiveness per se did not indicate a serious threat of harmful impact. In this ecosystem, R and A together drove invasiveness, while R alone drove impacts. Fruit type significantly influenced E, and species bearing berry fruits had the most negative per capita effects. However, plant traits did not drive invasiveness or impact through R, A or E. Our results suggest that the mismatch between components driving invasiveness vs. impact prevented prediction of impacts of invasive species from their invasiveness. Thus, management actions directed against invasive plants should prioritize broadly distributed species or those with demonstrated high impacts on native species.
    Type of Medium: Online Resource
    ISSN: 1752-993X
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2023
    detail.hit.zdb_id: 2381013-0
    SSG: 12
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  • 2
    Online Resource
    Online Resource
    ASTES Journal ; 2017
    In:  Advances in Science, Technology and Engineering Systems Journal Vol. 2, No. 3 ( 2017-06), p. 545-552
    In: Advances in Science, Technology and Engineering Systems Journal, ASTES Journal, Vol. 2, No. 3 ( 2017-06), p. 545-552
    Type of Medium: Online Resource
    ISSN: 2415-6698
    URL: Issue
    Language: Unknown
    Publisher: ASTES Journal
    Publication Date: 2017
    detail.hit.zdb_id: 2901531-5
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  • 3
    Online Resource
    Online Resource
    Hindawi Limited ; 2021
    In:  Journal of Healthcare Engineering Vol. 2021 ( 2021-8-17), p. 1-10
    In: Journal of Healthcare Engineering, Hindawi Limited, Vol. 2021 ( 2021-8-17), p. 1-10
    Abstract: Microexpression can manifest the real mood of humans, which has been widely concerned in clinical diagnosis and depression analysis. To solve the problem of missing discriminative spatiotemporal features in a small data set caused by the short duration and subtle movement changes of microexpression, we present a dual-stream spatiotemporal attention network (DSTAN) that integrates dual-stream spatiotemporal network and attention mechanism to capture the deformation features and spatiotemporal features of microexpression in the case of small samples. The Spatiotemporal networks in DSTAN are based on two lightweight networks, namely, the spatiotemporal appearance network (STAN) learning the appearance features from the microexpression sequences and the spatiotemporal motion network (STMN) learning the motion features from optical flow sequences. To focus on the discriminative motion areas of microexpression, we construct a novel attention mechanism for the spatial model of STAN and STMN, including a multiscale kernel spatial attention mechanism and global dual-pool channel attention mechanism. To obtain the importance of each frame in the microexpression sequence, we design a temporal attention mechanism for the temporal model of STAN and STMN to form spatiotemporal appearance network-attention (STAN-A) and spatiotemporal motion network-attention (STMN-A), which can adaptively perform dynamic feature refinement. Finally, the feature concatenate-SVM method is used to integrate STAN-A and STMN-A to a novel network, DSTAN. The extensive experiments on three small spontaneous microexpression data sets of SMIC, CASME, and CASME II demonstrate the proposed DSTAN can effectively cope with the recognition of microexpressions.
    Type of Medium: Online Resource
    ISSN: 2040-2309 , 2040-2295
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2021
    detail.hit.zdb_id: 2545054-2
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  • 4
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2022
    In:  Journal of Forestry Research Vol. 33, No. 6 ( 2022-12), p. 1867-1879
    In: Journal of Forestry Research, Springer Science and Business Media LLC, Vol. 33, No. 6 ( 2022-12), p. 1867-1879
    Abstract: Larix olgensis , one of the most important timber species in northeastern China, is used for paper making and construction. In this study, 10 wood properties (wood density, fiber length, fiber width, fiber length- to width ratio, hemicellulose content, cellulose content, holocellulose content, lignin content, ash content, and carbon content) of 10 provenances of L. olgensis planted at sites of CuoHai (CH), JiaGeDaQi (JGDQ), LiangShui (LS), and Mao’erShan (MES) were analyzed. The results of ANOVA showed that almost traits differed significantly among locations and provenances, with a significant interaction effect. Each trait also differed significant among provenances within sites. The phenotypic and genetic coefficient of variation (PCV and GCV) and provenance heritability ( H 2 ) for wood properties ranged from 1.122 to 27.365%, from 0.564% to 21.113% and from 0.332 to 0.996, respectively. A correlation analysis showed that wood density was significantly negatively correlated with cellulose content and holocellulose content at sites CH, JGDQ, and LS, but were significantly positively correlated at site MES. Wood density was significantly negatively correlated with lignin content at CH and JGDQ, but not at LS and MES. Fiber width (FW) was negatively correlated with the ratio of fiber length (FL) to width across sites, and FW and FL/W were all positively correlated with FL. Lignin content was significantly positively correlated with hemicellulose content at site JGDQ and significantly negatively correlated with cellulose content and with holocellulose content at site MES. Interestingly, carbon content was positively correlated with cellulose content and holocellulose content at CH, but negatively correlated with these two traits at site MES. In a correlation analysis of wood properties with geographic, soil and climatic characteristics at the four sites, wood properties were mainly correlated with latitude and altitude of the site and affected by the average annual precipitation and temperature simultaneously. To select superior pulpwood provenances and high carbon storage provenances, we selected the two best provenances with excellent wood properties for each location based on a multi-trait comprehensive evaluation, which can be used as the preferred materials for the establishment of large-scale plantations in specific locations.
    Type of Medium: Online Resource
    ISSN: 1007-662X , 1993-0607
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2299615-1
    SSG: 23
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  • 5
    Online Resource
    Online Resource
    Elsevier BV ; 2020
    In:  Computer Communications Vol. 152 ( 2020-02), p. 34-45
    In: Computer Communications, Elsevier BV, Vol. 152 ( 2020-02), p. 34-45
    Type of Medium: Online Resource
    ISSN: 0140-3664
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2020
    detail.hit.zdb_id: 1478742-8
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  • 6
    Online Resource
    Online Resource
    MDPI AG ; 2023
    In:  Sensors Vol. 23, No. 23 ( 2023-11-30), p. 9541-
    In: Sensors, MDPI AG, Vol. 23, No. 23 ( 2023-11-30), p. 9541-
    Abstract: With the advantages of real-time data processing and flexible deployment, unmanned aerial vehicle (UAV)-assisted mobile edge computing systems are widely used in both civil and military fields. However, due to limited energy, it is usually difficult for UAVs to stay in the air for long periods and to perform computational tasks. In this paper, we propose a full-duplex air-to-air communication system (A2ACS) model combining mobile edge computing and wireless power transfer technologies, aiming to effectively reduce the computational latency and energy consumption of UAVs, while ensuring that the UAVs do not interrupt the mission or leave the work area due to insufficient energy. In this system, UAVs collect energy from external air-edge energy servers (AEESs) to power onboard batteries and offload computational tasks to AEESs to reduce latency. To optimize the system’s performance and balance the four objectives, including the system throughput, the number of low-power alarms of UAVs, the total energy received by UAVs and the energy consumption of AEESs, we develop a multi-objective optimization framework. Considering that AEESs require rapid decision-making in a dynamic environment, an algorithm based on multi-agent deep deterministic policy gradient (MADDPG) is proposed, to optimize the AEESs’ service location and to control the power of energy transfer. While training, the agents learn the optimal policy given the optimization weight conditions. Furthermore, we adopt the K-means algorithm to determine the association between AEESs and UAVs to ensure fairness. Simulated experiment results show that the proposed MODDPG (multi-objective DDPG) algorithm has better performance than the baseline algorithms, such as the genetic algorithm and other deep reinforcement learning algorithms.
    Type of Medium: Online Resource
    ISSN: 1424-8220
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2052857-7
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