Two months after it was firstly reported, the novel coronavirus disease COVID-19 spread worldwide. However, the vast majority of reported infections until February occurred in China. To assess the ...effect of early travel restrictions adopted by the health authorities in China, we have implemented an epidemic metapopulation model that is fed with mobility data corresponding to 2019 and 2020. This allows to compare two radically different scenarios, one with no travel restrictions and another in which mobility is reduced by a travel ban. Our findings indicate that i) travel restrictions might be an effective measure in the short term, however, ii) they are ineffective when it comes to completely eliminate the disease. The latter is due to the impossibility of removing the risk of seeding the disease to other regions. Furthermore, our study highlights the importance of developing more realistic models of behavioral changes when a disease outbreak is unfolding.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Abstract
Many collective phenomena such as epidemic spreading and cascading failures in socioeconomic systems on networks are caused by perturbations of the dynamics. How perturbations propagate ...through networks, impact and disrupt their functions may depend on the network, the type and location of the perturbation as well as the spreading dynamics. Previous work has analyzed the retardation effects of the nodes along the propagation paths, suggesting a few transient propagation "scaling” regimes as a function of the nodes’ degree, but regardless of motifs such as triangles. Yet, empirical networks consist of motifs enabling the proper functioning of the system. Here, we show that basic motifs along the propagation path jointly determine the previously proposed scaling regimes of distance-limited propagation and degree-limited propagation, or even cease their existence. Our results suggest a radical departure from these scaling regimes and provide a deeper understanding of the interplay of self-dynamics, interaction dynamics, and topological properties.
Understanding how interurban movements can modify the spatial distribution of the population is important for transport planning but is also a fundamental ingredient for epidemic modeling. We ...illustrate this on vacation trips for all transportation modes in China during the Lunar New Year and compare the results for 2019 with the ones for 2020 where travel bans were applied for mitigating the spread of a novel coronavirus (COVID-19). We first show that inter-urban travel flows are broadly distributed and display both large temporal and spatial fluctuations, making their modeling very difficult. When flows are larger, they appear to be more dispersed over a larger number of origins and destinations, creating
de facto
hubs that can spread an epidemic at a large scale. These movements quickly induce (in about a week for this case) a very strong population concentration in a small set of cities. We characterize quantitatively the return to the initial distribution by defining a pendular ratio which allows us to show that this dynamics is in general very slow and even stopped for the 2020 Lunar New Year due to travel restrictions. Travel restrictions obviously limit the spread of the diseases between different cities, but have thus the counter-effect of keeping high concentration in a small set of cities,
a priori
favoring intra-city spread, unless individual contacts are strongly limited. These results shed some light on the statistics of interurban movements and how they modify the national distribution of populations, a crucial ingredient for devising effective control strategies at a national level.
Abstract In the real world, many dynamic behaviors can be explained by the propagation of perturbations, such as the transfer of chemical signals and the spread of infectious diseases. Previous ...researchers have achieved excellent results in approximating the global propagation time, revealing the mechanism of signal propagation through multiple paths. However, the known frameworks rely on the extension of physical concepts rather than mathematically rigorous derivations. As a result, they may not perfectly predict time or explain the underlying physical significance in certain specific cases. In this paper, we propose a novel method for decomposing network topology, focusing on two modules: the tree-like module and the path-module. Subsequently, we introduce a new framework for signal propagation analysis, which can be applied to estimate the propagation time for two fundamental global topology modules and provide a rigorous proof for the propagation time in global topology. Compared to previous work, our results are not only more concise, clearly defined, efficient, but also are more powerful in predicting propagation time which outperforms some known results in some cases, for example, biochemical dynamics.Additionally, the proposed framework is based on information transfer pathways, which can be also applied to other physical fields, such as network stability, network controlling and network resilience.
Various disasters stem from minor perturbations, such as the spread of
infectious diseases, cascading failure in power grids, etc. Analyzing
perturbations is crucial for both theoretical and ...application fields. Previous
researchers have proposed basic propagation patterns for perturbation and
explored the impact of basic network motifs on the collective response to these
perturbations, However, the current framework is limited in its ability to
decouple interactions, and therefore cannot analyze more complex structures. In
this article, we establish an effective, robust and powerful propagation
framework under a general dynamic model. This framework reveals common and
dense network motifs that exert a critical influence on signal propagation,
often spanning orders of magnitude compared with conclusions generated by
previous work. Moreover, our framework provides a new approach to understand
the fundamental principles of complex systems and the negative feedback
mechanism, which is of great significance for research of system controlling
and network resilience.
Understanding how interurban movements can modify the spatial distribution of the population is important for transport planning but is also a fundamental ingredient for epidemic modeling. We focus ...here on vacation trips (for all transportation modes) during the Chinese Lunar New Year and compare the results for 2019 with the ones for 2020 where travel bans were applied for mitigating the spread of a novel coronavirus (COVID-19). We first show that these travel flows are broadly distributed and display both large temporal and spatial fluctuations, making their modeling very difficult. When flows are larger, they appear to be more dispersed over a larger number of origins and destinations, creating de facto hubs that can spread an epidemic at a large scale. These movements quickly induce (in about a week) a very strong population concentration in a small set of cities. We characterize quantitatively the return to the initial distribution by defining a pendular ratio which allows us to show that this dynamics is very slow and even stopped for the 2020 Lunar New Year due to travel restrictions. Travel restrictions obviously limit the spread of the diseases between different cities, but have thus the counter-effect of keeping high concentration in a small set of cities, a priori favoring intra-city spread, unless individual contacts are strongly limited. These results shed some light on how interurban movements modify the national distribution of populations, a crucial ingredient for devising effective control strategies at a national level.
Schematic diagram of hydrothermal synthesis graphitic carbon nitride nanosheets-carbon nanotube composite and theirs application for electrochemical sensing catechol and hydroquinone.
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...•Self-assembly of graphitic carbon nitride nanosheets-carbon nanotube composite.•CNNS-CNT show more stronger conductivity than CNNS and CNT.•CNNS-CNT has been performed for detection of catechol and hydroquinone.•The probe was applied to detect practical samples with satisfactory results.
In this paper, three-dimensional (3D) graphitic carbon nitride nanosheets-carbon nanotube (CNNS-CNT) composite was synthesized via hydrothermal reaction of 2D CNNS and 1D CNT-COOH by π-π stacking and electrostatic interactions. This CNNS-CNT composite was characterized by transmission electron microscope, scanning electron microscope, x-ray diffraction and fourier-transform infrared. In addition, the CNNS-CNT composite displayed excellent conductivity comparing with CNNS and CNT-COOH monomer. This composite was applied for electrochemical simultaneous determination of catechol (CC) and hydroquinone (HQ) with good sensitivity, wide linear range and low detection limit. In addition, this CNNS-CNT composite modified electrode was also applied to detect practical samples with satisfactory results.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
A novel composite film of Au@carbon dots (Au@CDs)–chitosan (CS) modified glassy carbon electrode (Au@CDs–CS/GCE) was prepared in a simple manner and applied in the sensitive and reliable ...determination of dopamine (DA). The CDs had carboxyl groups with negative charge, which not only gave it have good stability but also enabled interaction with amine functional groups in DA through electrostatic interaction to multiply recognize DA with high specificity, and the Au nanoparticle could make the surface of the electrode more conductive. Compared with the bare GCE, CS/GCE, and CDs–CS/GCE electrodes, the Au@CDs–CS/GCE had higher catalytic activity toward the oxidation of DA. Furthermore, Au@CDs–CS/GCE exhibited good ability to suppress the background current from large excess ascorbic acid (AA) and uric acid (UA). Under the optimal conditions, selective detection of DA in a linear concentration range of 0.01–100.0μM was obtained with the limit of 0.001μM (3S/N). At the same time, the Au@CDs–CS/GCE was also applied to the detection of DA content in DA's injection with satisfactory results, and the biosensor could keep its activity for at least 2 weeks.
•The Au@carbon dots were used for good electrochemical signal with good biocompatibility.•Highly sensitive and selective detection of dopamine by the Au@CDs–CS/GCE.•This method was applied to the detection of DA content in its injection with satisfactory results.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
•Machine learning-based active flutter suppression.•Automatically learning the optimal controller parameters via reinforcement learning.•Avoiding the conventional and tedious procedure of manual ...tuning.•Compatible with different aero-servo-elastic systems and different control laws.•Expanding the flutter boundary of a flexible flying-wing aircraft by 36.6% robustly.
It is challenging to synthesize controller parameters for high-dimensional aeroservoelastic systems, such as a flexible aircraft, so that the controller cannot work effectively. This paper presents a novel design approach of machine learning-based control law for the problem of active flutter suppression. The approach is able to automatically tune the controller parameters via machine learning and avoid the conventional and tedious procedure of manual tuning. As such, the approach leads to a controller with better performance synthesized. The paper deals with a case study of active flutter suppression for a flexible flying-wing aircraft and demonstrates the control performance and efficiency of the machine learning-based control scheme in expanding the flutter boundaries. Based on the environment/agent interface of reinforcement learning, the proposed approach takes the closed-loop aeroservoelastic system as an environment and the actor-critic neural networks as an agent. The approach trains the policy of synthesizing the optimal controller parameters through the interaction between the environment and the agent. In the numerical simulation, with the active flutter suppression controller synthesized via the well-trained policy automatically, the critical flutter speed of the closed-loop aeroservoelastic system increases by about 36.6% compared to the open-loop system robustly. Moreover, the stability and the robustness of the closed-loop aeroservoelastic system designed via the proposed approach are better than that with a conventional robust H∞ controller.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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