Reversible signal transmission in an active mechanical metamaterial

Mechanical metamaterials are designed to enable unique functionalities, but are typically limited by an initial energy state and require an independent energy input to function repeatedly. Our study introduces a theoretical active mechanical metamaterial that incorporates a biological reaction mechanism to overcome this key limitation of passive metamaterials. Our material allows for reversible mechanical signal transmission, where energy is reintroduced by the biologically motivated reaction mechanism. By analysing a coarse grained continuous analogue of the discrete model, we find that signals can be propagated through the material by a travelling wave. Analysis of the continuum model provides the region of the parameter space that allows signal transmission, and reveals similarities with the well-known FitzHugh-Nagumo system. We also find explicit formulae that approximate the effect of the timescale of the reaction mechanism on the signal transmission speed, which is essential for controlling the material.Comment: 20 pages, 7 figure

Geometric analysis enables biological insight from complex non-identifiable models using simple surrogates

An enduring challenge in computational biology is to balance data quality and quantity with model complexity. Tools such as identifiability analysis and information criterion have been developed to harmonise this juxtaposition, yet cannot always resolve the mismatch between available data and the granularity required in mathematical models to answer important biological questions. Often, it is only simple phenomenological models, such as the logistic and Gompertz growth models, that are identifiable from standard experimental measurements. To draw insights from the complex, non-identifiable models that incorporate key biological mechanisms of interest, we study the geometry of a map in parameter space from the complex model to a simple, identifiable, surrogate model. By studying how non-identifiable parameters in the complex model quantitatively relate to identifiable parameters in surrogate, we introduce and exploit a layer of interpretation between the set of non-identifiable parameters and the goodness-of-fit metric or likelihood studied in typical identifiability analysis. We demonstrate our approach by analysing a hierarchy of mathematical models for multicellular tumour spheroid growth. Typical data from tumour spheroid experiments are limited and noisy, and corresponding mathematical models are very often made arbitrarily complex. Our geometric approach is able to predict non-identifiabilities, subset non-identifiable parameter spaces into identifiable parameter combinations that relate to individual data features, and overall provide additional biological insight from complex non-identifiable models

Notes and Discussion Piece: Status of the Topeka Shiner in Iowa

The Topeka shiner Notropis topeka is native to Iowa, Kansas, Minnesota, Missouri, Nebraska, and South Dakota and has been federally listed as endangered since 1998. Our goals were to determine the present distribution and qualitative status of Topeka shiners throughout its current range in Iowa and characterize the extent of decline in relation to its historic distribution. We compared the current (2016–2017) distribution to distributions portrayed in three earlier time periods. In 2016–2017 Topeka shiners were found in 12 of 20 HUC10 watersheds where they occurred historically. Their status was classified as stable in 21% of the HUC10 watersheds, possibly stable in 25%, possibly recovering in 8%, at risk in 33%, and possibly extirpated in 13% of the watersheds. The increasing trend in percent decline evident in earlier time periods reversed, going from 68% in 2010–11 to 40% in the most recent surveys. Following decades of decline, the status of Topeka shiners in Iowa appears to be improving. One potential reason for the reversal in the distributional decline of Topeka shiners in Iowa is the increasing number of oxbow restorations. Until a standardized monitoring program is established for Iowa, periodic status assessments such as this will be necessary to chronicle progress toward conserving this endangered fish species

Cultures of psychiatry and the professional socialization process: the case of containment methods for disturbed patients

Acute mental disorder necessitating admission to hospital is often accompanied by disturbed behaviour that threatens the health of the person concerned or that of those around them. A range of containment methods are used by psychiatric professionals to keep patients and staff safe. These strategies are strongly emotive and attract strong moral valuations, yet differ sharply between countries. This paper reports a study to investigate the relationship between attitudes to these containment methods, and exposure to psychiatric education and practice. It was hypothesized that the culture of psychiatry in the study country would socialise students' views towards the locally dominant pattern of relative evaluations. Nine cohorts of student psychiatric nurses at different stages of their training at one UK University were asked to complete ratings on 11 containment methods. Containment methods fell into five groups, with mechanical restraint and net beds attracting the most severe disapproval. Neither the relative evaluation of methods, nor the intensity of those evaluations, changed systematically with duration of training. The findings support the interpretation that the relative evaluations of psychiatric containment methods are a property of wider national cultures, rather than an isolated tradition of professional psychiatric practice

Efficient inference and identifiability analysis for differential equation models with random parameters

Heterogeneity is a dominant factor in the behaviour of many biological processes. Despite this, it is common for mathematical and statistical analyses to ignore biological heterogeneity as a source of variability in experimental data. Therefore, methods for exploring the identifiability of models that explicitly incorporate heterogeneity through variability in model parameters are relatively underdeveloped. We develop a new likelihood-based framework, based on moment matching, for inference and identifiability analysis of differential equation models that capture biological heterogeneity through parameters that vary according to probability distributions. As our novel method is based on an approximate likelihood function, it is highly flexible; we demonstrate identifiability analysis using both a frequentist approach based on profile likelihood, and a Bayesian approach based on Markov-chain Monte Carlo. Through three case studies, we demonstrate our method by providing a didactic guide to inference and identifiability analysis of hyperparameters that relate to the statistical moments of model parameters from independent observed data. Our approach has a computational cost comparable to analysis of models that neglect heterogeneity, a significant improvement over many existing alternatives. We demonstrate how analysis of random parameter models can aid better understanding of the sources of heterogeneity from biological data.Comment: Minor changes to text. Additional results in supplementary material. Additional statistics regarding results given in main and supplementary materia

Profile likelihood analysis for a stochastic model of diffusion in heterogeneous media

We compute profile likelihoods for a stochastic model of diffusive transport motivated by experimental observations of heat conduction in layered skin tissues. This process is modelled as a random walk in a layered one-dimensional material, where each layer has a distinct particle hopping rate. Particles are released at some location, and the duration of time taken for each particle to reach an absorbing boundary is recorded. To explore whether this data can be used to identify the hopping rates in each layer, we compute various profile likelihoods using two methods: first, an exact likelihood is evaluated using a relatively expensive Markov chain approach; and, second we form an approximate likelihood by assuming the distribution of exit times is given by a Gamma distribution whose first two moments match the expected moments from the continuum limit description of the stochastic model. Using the exact and approximate likelihoods we construct various profile likelihoods for a range of problems. In cases where parameter values are not identifiable, we make progress by re-interpreting those data with a reduced model with a smaller number of layers.Comment: 41 pages, 11 figure

Evaluating Antioxidant Activity of Selected Plant Species Native to Cedarville, Ohio

Over the past several decades, there has been an increase in the number of synthetic drug molecules developed and utilized to treat various conditions. Although these synthetic drugs have proven useful, there has been growing public concern regarding the potentially negative long-term effects of synthetic agents on the body. As a result, there has been an increased interest in identifying and utilizing plant extracts and purified compounds since they are perceived to be a more natural alternative to synthetic drugs. The goal of this study was to evaluate the specific antioxidant properties of alsike clover Trifolum hybridum when produced under differing growing conditions. The alsike clover was collected from the campus of Cedarville University, Cedarville, Ohio for testing. Alsike clover was removed from the field in January 2013, and transplanted indoors under grow lights for 14 days. These plants were then subjected to three separate 60-day treatments: control treatment - watering to field capacity with no fertilizer; positive treatment - watering to field capacity with fertilizer; and negative treatment - half of the water given to the field capacity treatment with no fertilizer. The rationale for choosing these different treatments was to evaluate the effects of specific growing conditions on bioactive secondary metabolite production in alsike clover. The biological evaluation was accomplished by conducting diphenylpicrylhyrazyl (DPPH) free-radical scavenging and Folin Ciocalteu assays to assess the concentration of polyphenolic compounds. Results from these experiments indicate that the biological and chemical profiles of alsike clover can be influenced by the environmental conditions under which the plants are grown

Canonical Particle Acceleration in FRI Radio Galaxies

Matched resolution multi-frequency VLA observations of four radio galaxies are used to derive the asymptotic low energy slope of the relativistic electron distribution. Where available, low energy slopes are also determined for other sources in the literature. They provide information on the acceleration physics independent of radiative and other losses, which confuse measurements of the synchrotron spectra in most radio, optical and X-ray studies. We find a narrow range of inferred low energy electron energy slopes, n(E)=const*E^-2.1 for the currently small sample of lower luminosity sources classified as FRI (not classical doubles). This distribution is close to, but apparently inconsistent with, the test particle limit of n(E)=const*E^-2.0 expected from strong diffusive shock acceleration in the non-relativistic limit. Relativistic shocks or those modified by the back-pressure of efficiently accelerated cosmic rays are two alternatives to produce somewhat steeper spectra. We note for further study the possiblity of acceleration through shocks, turbulence or shear in the flaring/brightening regions in FRI jets as they move away from the nucleus. Jets on pc scales and the collimated jets and hot spots of FRII (classical double) sources would be governed by different acceleration sites and mechanisms; they appear to show a much wider range of spectra than for FRI sources.Comment: 16 figures, including 5 color. Accepted to Astrophysical Journa