This month’s highlights blog features all the best content published in our research journals in August. This month we have: Good vibrations, How sheepdogs control their flock, Scratching beneath the surface, High risk high reward and It takes two.
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Elastic constants determine the relationship between stress and strain in a material and play a central role in both macroscopic solid mechanics as well as solid-state physics on an atomistic scale. Resonant ultrasound spectroscopy (RUS) is the state of the art technique to measure the second-order elastic constants from free-vibration acoustic resonance frequencies of a solid. This Proceedings A paper studies the pressure dependence of the elastic moduli and develops a method to determine the third-order elastic constants from high-pressure RUS experiment. Because the third-order elastic constants are responsible for anharmonic interaction of atoms in a crystal, the results presented indicate that it is possible to “hear the shape of an inter-atomic potential” from the vibration frequencies.
Scientists have developed a mathematical shepherding model based on real sheep-dog interactions. This Interface paper shows that data collected from specially designed GPS tracking backpacks fitted to a flock of sheep and its sheepdog was used to generate the algorithm. The model shows that herding sheep involves two basic rules: closing the gaps and moving the flock forwards. Wise shepherds have known this for years of course, but numerical confirmation could help apply the principle to different scenarios such as human crowd control or cleaning up of the environment.
Scratching Beneath The Surface
Quantifying the impact of biochemical compounds on collective cell spreading is an essential element of drug design, with various applications including developing chronic wound and cancer treatments. Scratch assays are a technically simple and inexpensive method used to study collective cell spreading; however, most previous interpretations of these assays are qualitative and do not provide quantitative insight into the mechanisms involved. Research published in Open Biology combines experimental data, modelling and Bayesian inference techniques to develop a method which allows for the extraction quantitative results. This novel method will potentially provide a very powerful tool for the extraction of accurate information about experimental data in a wide range of contexts.
The presentation of information has previously masked humans’ risky nature, giving the impression that we are more risk averse than many animals. New research published in Biology Letters last month suggests that this is because risks are explained to humans in experiments, whereas animals need to ‘learn’ the risks. Researchers designed experiments so that that both humans and pigeons learned risks through experience – providing rewards of food for the pigeons and points in a computer game for the humans. If rewards were low, both species were risk averse, however, if the rewards were high they showed risk-seeking behaviour, selecting high–risk doors with the greatest potential reward.
Intensive agriculture has long since been a key perpetrator of biodiversity loss. Two major conservation strategies are often employed to tackle this: in farm reduction of local management intensity or an increase in the surrounding natural areas. Using a quantitative synthesis of the published literature this Proceedings B paper shows that reducing management intensity within fields significantly increased plant and invertebrate biodiversity, whilst strategies at the landscape scale increased vertebrate and invertebrate species. Thus, both strategies need to be employed together for effective conservation.