718 research outputs found

    Influence of self-disassembly of bridges on collective flow characteristics of swarm robots in a single-lane and periodic system with a gap

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    Inspired by the living bridges formed by ants, swarm robots have been developed to self-assemble bridges to span gaps and self-disassemble them. Self-disassembly of bridges may increase the transport efficiency of swarm robots by increasing the number of moving robots, and also may decrease the efficiency by causing gaps to reappear. Our aim is to elucidate the influence of self-disassembly of bridges on the collective flow characteristics of swarm robots in a single-lane and periodic system with a gap. In the system, robots span and cross the gap by self-assembling a single-layer bridge. We consider two scenarios in which self-disassembling bridges is prevented (prevent-scenario) or allowed (allow-scenario). We represent the horizontal movement of robots with a typical car-following model, and simply model the actions of robots for self-assembling and self-disassembling bridges. Numerical simulations have revealed the following results. Flow-density diagrams in both the scenarios shift to the higher-density region as the gap length increases. When density is low, allow-scenario exhibits the steady state of repeated self-assembly and self-disassembly of bridges. If density is extremely low, flow in this state is greater than flow in prevent-scenario owing to the increase in the number of robots moving horizontally. Otherwise, flow in this state is smaller than flow in prevent-scenario. Besides, flow in this state increases monotonically with respect to the velocity of robots in joining and leaving bridges. Thus, self-disassembling bridges is recommended for only extremely low-density conditions in periodic systems. This study contributes to the development of the collective dynamics of self-driven particles that self-assemble structures, and stirs the dynamics with other self-assembled structures, such as ramps, chains, and towers.Comment: 13 pages, 9 figure

    Symbiotic Nutrient Exchange in Arbuscular Mycorrhiza

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    多時間スケールでの可視偏光・多波長観測による相対論ジェットの構造及び放射領域の研究

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    内容の要約広島大学(Hiroshima University)博士(理学)Sciencedoctora

    Effectiveness of Winter-Flooding in Organic Rice Farming and Some Relating Management Practices

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    Poster Session

    Production of overdense plasmas by launching 2,45 GHz electron cyclotron waves in a helical device

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    For production of low temperature plasmas with low collisionality, 2.45GHz microwave power up to 20kW is injected perpendicularly to the toroidal field at very low toroidal field BtComment: 12th International Congress on Plasma Physics, 25-29 October 2004, Nice (France

    The Relationship Between Deep Rooting and Nitrate Leaching of Wheat in Subsoil Acidity

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    Poster Session

    Human movement decisions during Coronavirus Disease 2019

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    To predict epidemics' future course in changing situations, understanding human mobility patterns is important, notwithstanding decision-making process uncertainties owing to difficulties in quantifying people's mobility change decision timings, which make the mobility-epidemic causal relationship unclear. We used the 'mobility avoidance index' to investigate time-series changes during Japan's Coronavirus Disease 2019 (eight waves until February 2023) as a previous study, which measured this index using accommodation reservation data-booking/cancellation timings-was able to quantify the timing of decision-making for mobility changes. Our analyses revealed two general patterns: 1) the index increased/decreased proportional to logarithms of reported cases during the first wave, conforming with Weber-Fechner's psychophysics law; 2) its slope against the change in the number of reported cases had similar values among the waves, but its intercepts changed as the waves passed, suggesting that people neglected reported cases lower than a certain threshold for behavioural decision-making. We shifted the threshold level as the waves passed, and named this pattern 'shift of negligible epidemic' rule. It is the first pattern quantitatively observed, that possesses decision making tendencies for future mobility avoidance. Our findings contribute to constructing a mathematical model, which simultaneously considers epidemics and human mobility dynamics
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