Journal of The Royal Society Interface最新文献

Buzz pollination involves the release of pollen from, primarily, poricidal anthers through vibrations generated by certain bee species. Despite previous experimental and numerical studies, the intricacies of pollen dynamics within vibrating anthers remain elusive due to the challenges in observing these small-scale, opaque systems. This research employs the discrete element method to simulate the pollen expulsion process in vibrating anthers. By exploring various frequencies and displacement amplitudes, a correlation between how aggressively the anther shakes and the initial rate of pollen expulsion is observed under translating oscillations. This study highlights that while increasing both the frequency and displacement of vibration enhances pollen release, the rate of release does not grow linearly with their increase. Our findings also reveal the significant role of pollen-pollen interactions, which account for upwards of one-third of the total collisions. Comparisons between two types of anther exits suggest that pore size and shape also influence expulsion rates. This research provides a foundation for more comprehensive models that can incorporate additional factors such as cohesion, adhesion and Coulomb forces, paving the way for deeper insights into the mechanics of buzz pollination and its variability across different anther types and vibration parameters.

Swimming and flying animals produce thrust with oscillating fins, flukes or wings. The relationship between frequency f, amplitude A and forward velocity U can be described with a Strouhal number St, where St = 2fA/U, where animals are observed to cruise with [Formula: see text]-0.4. Under these conditions, thrust is produced economically and a reverse von Kármán wake is observed. However, propeller-driven craft produce thrust with steadily revolving blades and a helical wake. Here, the simplified aerodynamic geometry of lift-based thrust production is described, applicable to both oscillating and revolving foils. The same geometric principles apply in both cases: if the foil moves too slowly, it cannot produce thrust; if it moves too fast, it produces thrust with excessive power demand. Effective, economic thrust production by animals is not the result of oscillating foils or cyclic vortex shedding; rather, the selection of amplitude and frequency, and wake vortex structure, are corollaries of driving an efficient foil velocity with finite amplitudes. Observed Strouhal numbers for cruising animals appear too low for optimal mechanical efficiency; however, the deviation from optimal efficiency may be small, and there are physical and physiological advantages to relatively low amplitudes and frequencies for swimming and flapping flight.

The design of photobioreactors for microalgae cultivation aims to achieve an architecture that allows the most efficient photosynthetic growth. The availability of light at wavelengths that are important for photosynthesis is therefore particularly crucial for reactor design. While testing different reactor types in practice is expensive, simulations could effectively limit the range of material and reactor design options. In this study, procedural three-dimensional modelling together with ray tracing was used to create virtual models of a conventional glass photobioreactor lit from the outside and a steel photobioreactor with embedded light sources. The measured transmittance and reflectance of Chlorella vulgaris culture were used as a basis for light interaction simulation, and spectral images of the same species were used to validate the simulation results. This type of simulation could have the potential for comparing different reactor architectures, geometries and light attenuation to facilitate the transition to large-scale cultivation. Our results show that the proposed simulator is usable in photobioreactor geometry design as well as in the estimation of available illumination on wavelengths where microalgae have strong absorption peaks, but the handling of light scattering still needs improvement. To the authors' best knowledge, this is the first attempt, not focused on a specific use case, to build a general photobioreactor design tool capable of estimating hyperspectral light attenuation in microalgae suspension. All software code and used datasets are made available for the reader as open source.

Dissipative environments are ubiquitous in nature, from microscopic swimmers in low-Reynolds-number fluids to macroscopic animals in frictional media. In this study, we consider a mathematical model of a slender elastic locomotor with an internal rhythmic neural pattern generator to examine various undulatory locomotion such as Caenorhabditis elegans swimming and crawling behaviours. By using local mechanical load as mechanosensory feedback, we have found that undulatory locomotion robustly emerges in different rheological media. This progressive behaviour is then characterized as a global attractor through dynamical systems analysis with a Poincaré section. Furthermore, by controlling the mechanosensation, we were able to design the dynamical systems to manoeuvre with progressive, reverse and turning motions as well as apparently random, complex behaviours, reminiscent of those experimentally observed in C. elegans. The mechanisms found in this study, together with our dynamical systems methodology, are useful for deciphering complex animal adaptive behaviours and designing robots capable of locomotion in a wide range of dissipative environments.

Achroia grisella (Fabricius, 1794) (Lepidoptera: Pyralidae) is a pyralid moth with two ears in its abdomen that it uses for detecting mates and predators. Despite no connection between the two ears having been found and no other elements having been observed through X-ray scans of the moth, it seems to be capable of directional hearing with just one ear when one of them is damaged. It is therefore suspected that the morphology of the eardrum can provide directional cues for sound localization. Here, we use finite element modelling software COMSOL to model a simplified version of the eardrum, an elliptical plate with two sections of different thicknesses and a mass load at the centre of the thin section, to try to determine if the morphology of the ear is responsible for the moth's monoaural directional hearing. Results indicate that the resonance mode and directionality response of the elliptical plate with two thicknesses and a mass load match that of the moth closely and provide an enhanced response to sounds coming from the front of the moth. Damping is also considered in the resonant mode, and it is observed to improve the resemblance of the simulation to real moth ear measurements.

Random walks and related spatial stochastic models have been used in a range of application areas, including animal and plant ecology, infectious disease epidemiology, developmental biology, wound healing and oncology. Classical random walk models assume that all individuals in a population behave independently, ignoring local physical and biological interactions. This assumption simplifies the mathematical description of the population considerably, enabling continuum-limit descriptions to be derived and used in model analysis and fitting. However, interactions between individuals can have a crucial impact on population-level behaviour. In recent decades, research has increasingly been directed towards models that include interactions, including physical crowding effects and local biological processes such as adhesion, competition, dispersal, predation and adaptive directional bias. In this article, we review the progress that has been made with models of interacting individuals. We aim to provide an overview that is accessible to researchers in application areas, as well as to specialist modellers. We focus particularly on derivation of asymptotically exact or approximate continuum-limit descriptions and simplified deterministic models of mean-field behaviour and resulting spatial patterns. We provide worked examples and illustrative results of selected models. We conclude with a discussion of current areas of focus and future challenges.

Can a micron-sized sack of interacting molecules autonomously learn an internal model of a complex and fluctuating environment? We draw insights from control theory, machine learning theory, chemical reaction network theory and statistical physics to develop a general architecture whereby a broad class of chemical systems can autonomously learn complex distributions. Our construction takes the form of a chemical implementation of machine learning's optimization workhorse: gradient descent on the relative entropy cost function, which we demonstrate can be viewed as a form of integral feedback control. We show how this method can be applied to optimize any detailed balanced chemical reaction network and that the construction is capable of using hidden units to learn complex distributions.

Contact tracing is commonly used to manage infectious diseases of both humans and animals. It aims to detect early and control potentially infected individuals or farms that had contact with infectious cases. Because it is very resource-intensive, contact tracing is usually performed on a pre-defined time window, based on previous knowledge of the duration of the incubation period. However, pre-defined time windows may not be always relevant, reducing the efficiency of contact tracing. In this study, we estimated the day when farms were first infected with highly pathogenic avian influenza viruses, a devastating pathogen causing severe socio-economic damage in domestic poultry. The estimation was performed by fitting a stochastic mechanistic model to observed daily mortality data from 63 infected poultry farms in France and The Netherlands, using approximate Bayesian computation. Independent of the poultry species or country, the estimates of the time of first infection ranged between 3.4 (95% credible interval-CrI: 2.6, 4.6) and 19.9 (95% CrI: 11.9, 31.3) days prior to the last observation. We developed an online application to provide real-time support to policymakers by estimating realistic ranges of dates of first infection to inform contact tracing and improve its efficiency.

The human body consists of many different soft biological tissues that exhibit diverse microstructures and functions and experience diverse loading conditions. Yet, under many conditions, the mechanical behaviour of these tissues can be described well with similar nonlinearly elastic or inelastic constitutive relations, both in health and some diseases. Such constitutive relations are essential for performing nonlinear stress analyses, which in turn are critical for understanding physiology, pathophysiology and even clinical interventions, including surgery. Indeed, most cells within load-bearing soft tissues are highly sensitive to their local mechanical environment, which can typically be quantified using methods of continuum mechanics only after the constitutive relations are determined from appropriate data, often multi-axial. In this review, we discuss some of the many experimental findings of the structure and the mechanical response, as well as constitutive formulations for 10 representative soft tissues or organs, and present basic concepts of mechanobiology to support continuum biomechanical studies. We conclude by encouraging similar research along these lines, but also the need for models that can describe and predict evolving tissue properties under many conditions, ranging from normal development to disease progression and wound healing. An important foundation for biomechanics and mechanobiology now exists and methods for collecting detailed multi-scale data continue to progress. There is, thus, considerable opportunity for continued advancement of mechanobiology and biomechanics.

COVID-19 vaccine programmes must account for variable immune responses and waning protection. Existing descriptions of antibody responses to COVID-19 vaccination convey limited information about the mechanisms of antibody production and maintenance. We describe antibody dynamics after COVID-19 vaccination with two biologically motivated mathematical models. We fit the models using Markov chain Monte Carlo to seroprevalence data from 14 602 uninfected individuals in England between May 2020 and September 2022. We analyse the effect of age, vaccine type, number of doses and the interval between doses on antibody production and longevity. We find evidence that individuals over 35 years old twice vaccinated with ChAdOx1-S generate a persistent antibody response suggestive of long-lived plasma cell induction. We also find that plasmablast productive capacity is greater in: younger people than older people (≤4.5-fold change in point estimates); people vaccinated with two doses than one dose (≤12-fold change); and people vaccinated with BNT162b2 than ChAdOx1-S (≤440-fold change). We find the half-life of an antibody to be 23-106 days. Routinely collected seroprevalence data are invaluable for characterizing within-host mechanisms of antibody production and persistence. Extended sampling and linking seroprevalence data to outcomes would enable conclusions about how humoral kinetics protect against disease.