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  • 2020-2024  (68)
  • 1
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    The Carboniferous Timescale (2020)
    London : The Geological Society
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    Schlagwort(e): Carboniferous; Pangaea; ice age; biochronology; biostratigraphy; magnetostratigraphy; radioisotopic age
    Beschreibung / Inhaltsverzeichnis: 10 December 2020 --- Proposed chronostratigraphic units for the Carboniferous and Early Permian of the southwestern Gondwana margin / Carlos R. González and Pamela Díaz Saravia / Geological Society, London, Special Publications, 512, https://doi.org/10.1144/SP512-2020-48 --- 7 December 2020 --- A geomagnetic polarity timescale for the Carboniferous / Mark W. Hounslow / Geological Society, London, Special Publications, 512, https://doi.org/10.1144/SP512-2020-102 --- 1 December 2020 --- Carboniferous Smaller Foraminifera: Convergences and Divergences / Daniel Vachard and François Le Coze / Geological Society, London, Special Publications, 512, https://doi.org/10.1144/SP512-2020-42 --- 30 November 2020 --- Carboniferous Crinoids / William I. Ausich, Thomas W. Kammer and Georgy V. Mirantsev / Geological Society, London, Special Publications, 512, https://doi.org/10.1144/SP512-2020-71 --- 27 November 2020 --- Carboniferous macrofloral biostratigraphy – an overview / Stanislav Opluštil, Christopher J. Cleal, Jun Wang and Mingli Wan / Geological Society, London, Special Publications, 512, https://doi.org/10.1144/SP512-2020-97 --- 26 November 2020 --- The biostratigraphy of Carboniferous chondrichthyans / Michał Ginter / Geological Society, London, Special Publications, 512, https://doi.org/10.1144/SP512-2020-91 --- 25 November 2020 --- Carboniferous isotope stratigraphy / Jitao Chen, Bo Chen and Isabel P. Montañez / Geological Society, London, Special Publications, 512, https://doi.org/10.1144/SP512-2020-72 --- 24 November 2020 --- Carboniferous conodont biostratigraphy / James E. Barrick, Alexander S. Alekseev, Silvia Blanco-Ferrera, Natalia V. Goreva, Keyi Hu, Lance L. Lambert, Tamara I. Nemyrovska, Yuping Qi, Scott M. Ritter and Javier Sanz-López / Geological Society, London, Special Publications, 512, https://doi.org/10.1144/SP512-2020-38
    Seiten: Illustrationen, Diagramme, Karten
    Ausgabe: online first
    URL: https://sp.lyellcollection.org/online-first/512
    Sprache: Englisch
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  • 2
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    Diffusion Source Inference for Large-Scale Complex Networks Based on Network Percolation (2023)
    In:  IEEE Transactions on Neural Networks and Learning Systems
    Details
    Publikationsdatum: 2024-01-23
    Beschreibung: This article studies the diffusion-source-inference (DSI) problem, whose solution plays an important role in real-world scenarios such as combating misinformation and controlling diffusions of information or disease. The main task of the DSI problem is to optimize an estimator, such that the real source can be more precisely targeted. In this article, we assume that the state of a number of nodes, called observer set, in a network could be investigated if necessary, and study what configuration of those nodes could facilitate a better solution for the DSI problem. In particular, we find that the conventional error distance metric cannot precisely evaluate the effectiveness of varied DSI approaches in heterogeneous networks, and thus propose a novel and more general measurement, the candidate set, that is formulated to contain the diffusion source for sure. We propose the percolation-based evolutionary framework (PrEF) to optimize the observer set such that the candidate set can be minimized. Hence, one could further conduct more intensive investigation or search on only a few nodes to target the source. To achieve that, we first theoretically show that the size of the candidate set is bounded by the size of the largest component cover, and demonstrate that there are some similarities between the DSI problem and the network immunization problem. We find that, given the associated direction information of the diffusion is known on observers, the minimization of the candidate set is equivalent to the minimization of the order parameter if we view the observer set as the removal node set. Hence, PrEF is developed based on the network percolation and evolutionary algorithm. The effectiveness of the proposed method is validated on both synthetic and empirical networks in regard to varied circumstances. Our results show that the developed approach could achieve much smaller candidate sets compared to the state of the art in almost all cases, e.g., it is better in 26 out of 27 empirical networks and 155 out of 162 cases regarding the critical threshold. Meanwhile, our approach is also more stable, i.e., it works well irrespective of varied infection probabilities, diffusion models, and underlying networks. More importantly, we provide a framework for the analysis of the DSI problem in large-scale networks.
    Sprache: Englisch
    Materialart: info:eu-repo/semantics/article
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  • 3
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    Neural-Network-Based Adaptive Tracking Control for Nonlinear Multiagent Systems: The Observer Case (2023)
    In:  IEEE Transactions on Cybernetics
    Details
    Publikationsdatum: 2023-02-03
    Beschreibung: This article focuses on the neural-network (NN)-based adaptive tracking control issue for a class of high-order nonlinear multiagent systems both subjected to the immeasurable state variables and unknown external disturbance. Combining with the radial basis function NNs (RBF NNs), the composite disturbance observer and state observer for each follower are established, respectively. The purpose of this work is to develop NN-based adaptive tracking control schemes such that the output of each follower ultimately tracks that of the leader and all the signals of the closed-loop systems are semiglobally uniformly ultimately bounded by utilizing the backstepping technique. Furthermore, so as to cope with the sparsity of the control resources, the proposed method is extended to the event-triggered case and the adaptive event-triggered tracking control protocol is formulated for nonlinear multiagent systems. Finally, the numerical example is performed to verify the efficacy of the proposed approach.
    Sprache: Englisch
    Materialart: info:eu-repo/semantics/article
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  • 4
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    Event-Triggered Adaptive Containment Control for Heterogeneous Stochastic Nonlinear Multiagent Systems (2023)
    In:  IEEE Transactions on Neural Networks and Learning Systems
    Details
    Publikationsdatum: 2023-04-14
    Beschreibung: This article investigates the event-triggered adaptive containment control problem for a class of stochastic nonlinear multiagent systems with unmeasurable states. A stochastic system with unknown heterogeneous dynamics is established to describe the agents in a random vibration environment. Besides, the uncertain nonlinear dynamics are approximated by radial basis function neural networks (NNs), and the unmeasured states are estimated by constructing the NN-based observer. In addition, the switching-threshold-based event-triggered control method is adopted with the hope of reducing communication consumption and balancing system performance and network constraints. Moreover, we develop the novel distributed containment controller by utilizing the adaptive backstepping control strategy and the dynamic surface control (DSC) approach such that the output of each follower converges to the convex hull spanned by multiple leaders, and all signals of the closed-loop system are cooperatively semi-globally uniformly ultimately bounded in mean square. Finally, we verify the efficiency of the proposed controller by the simulation examples.
    Sprache: Englisch
    Materialart: info:eu-repo/semantics/article
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  • 5
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    Cooperative Learning of Multi-Agent Systems via Reinforcement Learning (2023)
    In:  IEEE Transactions on Signal and Information Processing over Networks
    Details
    Publikationsdatum: 2023-04-14
    Beschreibung: In many specific scenarios, accurateand practical cooperative learning is a commonly encountered challenge in multi-agent systems. Thus, the current investigation focuses on cooperative learning algorithms for multi-agent systems and underpins an alternate data-based neural network reinforcement learning framework. To achieve the data-based learning optimization, the proposed cooperative learning framework, which comprises two layers, introduces a virtual learning objective. The followers learn the behaviors of the virtual objects in the first layer based on the adaptive neural networks (NNs). Specifically, the actor and critic NNs are applied to acquire cooperative behaviors and assess this layer's long-term utility function. Then another layer realizes the tracking performance between the virtual objects and the leader by introducing the local data-based performance index. Then, we formulate a resulting deterministic optimization problem and resolve it effectively with the policy iteration algorithm. This intuitive cooperative learning algorithm also preserves good robustness properties and eliminates the dependence on the prior knowledge of the multi-agent system model in the solution process. Finally, a multi-robot formation system demonstrates this promising development's practical appeal and highly effective outcome.
    Sprache: Englisch
    Materialart: info:eu-repo/semantics/article
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  • 6
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    The triple benefits of slimming and greening the Chinese food system (2022)
    In:  Nature Food
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    Publikationsdatum: 2023-07-26
    Beschreibung: The Chinese food system has undergone a transition of unprecedented speed, leading to complex interactions with China’s economy, health and environment. Structural changes experienced by the country over the past few decades have boosted economic development but have worsened the mismatch between food supply and demand, deteriorated the environment, driven obesity and overnutrition levels up, and increased the risk for pathogen spread. Here we propose a strategy for slimming and greening the Chinese food system towards sustainability targets. This strategy takes into account the interlinkages between agricultural production and food consumption across the food system, going beyond agriculture-focused perspectives. We call for a food-system approach with integrated analysis of potential triple benefits for the economy, health and the environment, as well as multisector collaboration in support of evidence-based policymaking.
    Sprache: Englisch
    Materialart: info:eu-repo/semantics/article
    Format: application/pdf
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  • 7
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    Soil quality both increases crop production and improves resilience to climate change (2022)
    In:  Nature Climate Change
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    Publikationsdatum: 2023-07-26
    Beschreibung: Interactions between soil quality and climate change may influence the capacity of croplands to produce sufficient food. Here, we address this issue by using a new dataset of soil, climate and associated yield observations for 12,115 site-years representing 90% of total cereal production in China. Across crops and environmental conditions, we show that high-quality soils reduced the sensitivity of crop yield to climate variability leading to both higher mean crop yield (10.3 ± 6.7%) and higher yield stability (decreasing variability by 15.6 ± 14.4%). High-quality soils improve the outcome for yields under climate change by 1.7% (0.5–4.0%), compared to low-quality soils. Climate-driven yield change could result in reductions of national cereal production of 11.4 Mt annually under representative concentration pathway RCP 8.5 by 2080–2099. While this production reduction was exacerbated by 14% due to soil degradation, it can be reduced by 21% through soil improvement. This study emphasizes the vital role of soil quality in agriculture under climate change.
    Sprache: Englisch
    Materialart: info:eu-repo/semantics/article
    Format: application/pdf
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  • 8
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    Plant-based dietary patterns in relation to mortality among older adults in China (2022)
    In:  Nature Aging
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    Publikationsdatum: 2023-07-26
    Beschreibung: A plant-based dietary pattern has been recommended for its potential health and environmental benefits, but its relation to mortality warrants further exploration1. We examined this association among 13,154 adults aged 65 years and older (57.4% female) in the Chinese Longitudinal Healthy Longevity Survey (CLHLS). The overall plant-based diet index (PDI), healthful plant-based diet index (hPDI) and unhealthful plant-based diet index (uPDI) were calculated using dietary data collected by a simplified food frequency questionnaire (FFQ). Compared with the lowest quintile, participants in the highest quintile of PDI and hPDI had a decreased risk of all-cause mortality (hazard ratio (HR) = 0.92; 95% confidence interval (CI) 0.86, 0.98 for PDI; HR = 0.81, 95% CI, 0.76, 0.87 for hPDI), whereas participants with the highest uPDI scores had a 17% (95% CI, 9%, 26%) increased risk. Among plant foods, fresh fruits, fresh vegetables, legumes, garlic, nuts and tea were the main protective contributors, whereas preserved vegetables and sugar were associated with a higher risk of mortality. These findings support the beneficial roles of overall and healthful plant-based dietary patterns. The quality, and not only quantity, of plant foods should be emphasized in relevant public health recommendations.
    Sprache: Englisch
    Materialart: info:eu-repo/semantics/article
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  • 9
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    Occurrence of crop pests and diseases has largely increased in China since 1970 (2022)
    In:  Nature Food
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    Publikationsdatum: 2023-07-27
    Beschreibung: Crop pests and diseases (CPDs) are emerging threats to global food security, but trends in the occurrence of pests and diseases remain largely unknown due to the lack of observations for major crop producers. Here, on the basis of a unique historical dataset with more than 5,500 statistical records, we found an increased occurrence of CPDs in every province of China, with the national average rate of CPD occurrence increasing by a factor of four (from 53% to 218%) during 1970–2016. Historical climate change is responsible for more than one-fifth of the observed increment of CPD occurrence (22% ± 17%), ranging from 2% to 79% in different provinces. Among the climatic factors considered, warmer nighttime temperatures contribute most to the increasing occurrence of CPDs (11% ± 9%). Projections of future CPDs show that at the end of this century, climate change will lead to an increase in CPD occurrence by 243% ± 110% under a low-emissions scenario (SSP126) and 460% ± 213% under a high-emissions scenario (SSP585), with the magnitude largely dependent on the impacts of warmer nighttime temperatures and decreasing frost days. This observation-based evidence highlights the urgent need to accurately account for the increasing risk of CPDs in mitigating the impacts of climate change on food production.
    Sprache: Englisch
    Materialart: info:eu-repo/semantics/article
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  • 10
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    Narrowing uncertainties in the effects of elevated CO2 on crops (2020)
    In:  Nature Food
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    Publikationsdatum: 2023-07-27
    Beschreibung: Plant responses to rising atmospheric carbon dioxide (CO2) concentrations, together with projected variations in temperature and precipitation will determine future agricultural production. Estimates of the impacts of climate change on agriculture provide essential information to design effective adaptation strategies, and develop sustainable food systems. Here, we review the current experimental evidence and crop models on the effects of elevated CO2 concentrations. Recent concerted efforts have narrowed the uncertainties in CO2-induced crop responses so that climate change impact simulations omitting CO2 can now be eliminated. To address remaining knowledge gaps and uncertainties in estimating the effects of elevated CO2 and climate change on crops, future research should expand experiments on more crop species under a wider range of growing conditions, improve the representation of responses to climate extremes in crop models, and simulate additional crop physiological processes related to nutritional quality.
    Materialart: info:eu-repo/semantics/article
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