78 research outputs found
Analysis of Inter-Limb Asymmetry of Landing Forces and Ankle Injury in Warfighters: A Prospective Study
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Systemic Low-Grade Inflammation and Associations with Sleep Disturbance in Marine Corps Officer Candidates During Training
Load Differences in Male and Female Marine Officer Candidates Quantified by Inertial Measurement Units
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Relationship Between Isometric Inter-Limb Asymmetry and Strength of the Lower Extremity in Military Personnel
Continuous Monitorization of Physiologic Mediators of Allostasis Indicate Overuse Injury Risk in Marine Officer Candidates
Quantum Vacuum Contribution to the Momentum of the Dielectric Media
Momentum transfer between matter and electromagnetic field is analyzed. The
related equations of motion and conservation laws are derived using
relativistic formalism. Their correspondence to various, at first sight
self-contradicting, experimental data (the so called Abraham-Minkowski
controversy) is demonstrated. A new, Casimir like, quantum phenomenon is
predicted: contribution of vacuum fluctuations to the motion of dielectric
liquids in crossed electric and magnetic fields. Velocities about can
be expected due to the contribution of high frequency vacuum modes
Bone Mineral Density and Tibial Microarchitecture Changes in Division I Male and Female Cross - Country Runners
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Structural Differences in the Tibial Metaphysis Between Female NCAA Division I Cross - Country Runners and Gymnasts
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Learning and innovative elements of strategy adoption rules expand cooperative network topologies
Cooperation plays a key role in the evolution of complex systems. However,
the level of cooperation extensively varies with the topology of agent networks
in the widely used models of repeated games. Here we show that cooperation
remains rather stable by applying the reinforcement learning strategy adoption
rule, Q-learning on a variety of random, regular, small-word, scale-free and
modular network models in repeated, multi-agent Prisoners Dilemma and Hawk-Dove
games. Furthermore, we found that using the above model systems other long-term
learning strategy adoption rules also promote cooperation, while introducing a
low level of noise (as a model of innovation) to the strategy adoption rules
makes the level of cooperation less dependent on the actual network topology.
Our results demonstrate that long-term learning and random elements in the
strategy adoption rules, when acting together, extend the range of network
topologies enabling the development of cooperation at a wider range of costs
and temptations. These results suggest that a balanced duo of learning and
innovation may help to preserve cooperation during the re-organization of
real-world networks, and may play a prominent role in the evolution of
self-organizing, complex systems.Comment: 14 pages, 3 Figures + a Supplementary Material with 25 pages, 3
Tables, 12 Figures and 116 reference
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