Results 231 to 240 of about 315,169 (276)
Advanced Functional Materials, EarlyView.In this work, a magnetic core‐shell catalyst (HOF‐on‐Fe3O4/ZIF‐67) is successfully synthesized, consisting of a metal–organic framework (ZIF‐67) with magnetic Fe3O4 as the core and a porous hydrogen‐bonded organic framework (HOF) as the shell. The catalyst efficiently activated peroxymonosulfate, resulting in rapid and effective removal of water ...
Yingying Du +4 more
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Advanced Functional Materials, EarlyView.The layer‐by‐layer (LbL) assembly of coordination solids, enabled by the surface‐mounted metal‐organic framework (SURMOF) platform, is on the cusp of generating the organic counterpart of the epitaxy of inorganics. The programmable and sequential SURMOF protocol, optimized by machine learning (ML), is suited for accessing high‐quality thin films of ...
Zhengtao Xu +2 more
wiley +1 more source
Advanced Functional Materials, EarlyView.Intelligent radiative cooling devices, adaptable to various weather conditions, have the potential for year‐round energy savings. This study introduces a sustainable dual‐mode film made from polycaprolactone nanofibers and upcycled chip bags for effective thermal management.
Qimeng Song +4 more
wiley +1 more source
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Physical Review Letters, 2008
We propose to estimate transfer entropy using a technique of symbolization. We demonstrate numerically that symbolic transfer entropy is a robust and computationally fast method to quantify the dominating direction of information flow between time series from structurally identical and nonidentical coupled systems.
Matthäus, Staniek, Klaus, Lehnertz
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We propose to estimate transfer entropy using a technique of symbolization. We demonstrate numerically that symbolic transfer entropy is a robust and computationally fast method to quantify the dominating direction of information flow between time series from structurally identical and nonidentical coupled systems.
Matthäus, Staniek, Klaus, Lehnertz
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Transfer entropy on symbolic recurrences
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2019Recurrence quantification analysis offers a powerful framework to investigate complexity in dynamical systems. While several studies have demonstrated the possibility of multivariate recurrence quantification analysis, information-theoretic tools for the discovery of causal links remain elusive.
Maurizio Porfiri, Manuel Ruiz Marín
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Measuring information transfer by dispersion transfer entropy
Communications in Nonlinear Science and Numerical Simulation, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Boyi Zhang, Pengjian Shang
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Accelerating transfer entropy computation
2014 International Conference on Field-Programmable Technology (FPT), 2014Transfer entropy is a measure of information transfer between two time series. It is an asymmetric measure based on entropy change which only takes into account the statistical dependency originating in the source series, but excludes dependency on a common external factor.
Shengjia Shao +3 more
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Chaotic Communication via Temporal Transfer Entropy
Physical Review Letters, 2008We propose a new perspective on communication using chaos. A binary message is encoded into the temporally causal relations on a coupled maps ring of N chaotic nodes. From the analysis of temporal transfer entropy, the masked information can be recovered from transmitted signals at the receiver.
Yao-Chen, Hung, Chin-Kun, Hu
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Transfer entropies within dynamical effects framework
Physical Review E, 2020Transfer entropy (TE) is widely used in time-series analysis to detect causal couplings between temporally evolving objects. As a coupling strength quantifier, the TE alone often seems insufficient, raising the question of its further interpretations.
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