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   Li, Siying; Mount, Timothy D; Tong, Lang (September 2024, IEEE)
2. Energy-Resolved Information Scrambling in Energy-Space Lattices

   https://doi.org/10.1103/PhysRevLett.126.070601  

   Pegahan, S.; Arakelyan, I.; Thomas, J. E. (February 2021, Physical Review Letters)

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3. Vibrational Energy Landscapes and Energy Flow in GPCRs

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4. Past energy allocation overwhelms current energy stresses in determining energy allocation trade‐offs

   https://doi.org/10.1002/ece3.10402  

   Griffen, Blaine D.; Bolander, Mikayla; Blakeslee, April; Crane, Laura C.; Repetto, Michele F.; Tepolt, Carolyn K.; Toscano, Benjamin J. (August 2023, Ecology and Evolution)

   Abstract Regeneration of lost appendages is a gradual process in many species, spreading energetic costs of regeneration through time. Energy allocated to the regeneration of lost appendages cannot be used for other purposes and, therefore, commonly elicits energetic trade‐offs in biological processes. We used limb loss in the Asian shore crabHemigrapsus sanguineusto compare the strength of energetic trade‐offs resulting from historic limb losses that have been partially regenerated versus current injuries that have not yet been repaired. Consistent with previous studies, we show that limb loss and regeneration results in trade‐offs that reduce reproduction, energy storage, and growth. As may be expected, we show that trade‐offs in these metrics from historic limb losses far outweigh trade‐offs from current limb losses, and correlate directly with the degree of historic limb loss that has been regenerated. As regenerating limbs get closer to their normal size, these historical injuries get harder to detect, despite the continued allocation of additional resources to limb development. Our results demonstrate the importance of and a method for identifying historic appendage losses and of quantifying the amount of regeneration that has already occurred, as opposed to assessing only current injury, to accurately assess the strength of energetic trade‐offs in animals recovering from nonlethal injury. 

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5. Energy transport in glasses

   https://doi.org/10.1039/c9sm02171j  

   Flenner, Elijah; Wang, Lijin; Szamel, Grzegorz (January 2020, Soft Matter)

   The temperature dependence of the thermal conductivity is linked to the nature of the energy transport at a frequency ω , which is quantified by thermal diffusivity d ( ω ). Here we study d ( ω ) for a poorly annealed glass and a highly stable glass prepared using the swap Monte Carlo algorithm. To calculate d ( ω ), we excite wave packets and find that the energy moves diffusively for high frequencies up to a maximum frequency, beyond which the energy stays localized. At intermediate frequencies, we find a linear increase of the square of the width of the wave packet with time, which allows for a robust calculation of d ( ω ), but the wave packet is no longer well described by a Gaussian as for high frequencies. In this intermediate regime, there is a transition from a nearly frequency independent thermal diffusivity at high frequencies to d ( ω ) ∼ ω −4 at low frequencies. For low frequencies the sound waves are responsible for energy transport and the energy moves ballistically. The low frequency behavior can be predicted using sound attenuation coefficients. 

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