Acute and Chronic Lead Exposure in Four Avian Scavenger Species in Switzerland.

Despite irrefutable evidence of its negative impact on animal behaviour and physiology, lethal and sublethal lead poisoning of wildlife is still persistent and widespread. For scavenging birds, ingestion of ammunition, or fragments thereof, is the major exposure route. In this study, we examined the occurrence of lead in four avian scavengers of Switzerland and how it differs between species, regions, and age of the bird. We measured lead concentration in liver and bone of the two main alpine avian scavengers (golden eagle Aquila chrysaetos and bearded vulture Gypaetus barbatus) over the entire area of the Swiss Alps and two of the main avian scavengers occurring in the lowlands of Switzerland (red kite Milvus milvus and common raven Corvus corax). Of those four species, only the bearded vulture is an obligate scavenger. We found that lead burdens in the two alpine avian scavengers were higher than those found for the same species elsewhere in Europe or North America and reached levels compatible with acute poisoning, whereas lead burdens of the two lowland avian scavengers seemed to be lower. Several golden eagles, but only one red kite with abnormally high bone lead concentrations were found. In all four species, a substantial proportion of birds had elevated levels which presumably represent recent (liver lead levels) or past (bone lead levels) uptake of sublethal doses of lead.

Robotic Plaster Spraying: Crafting Surfaces with Adaptive Thin-Layer Printing.

Embedded in a long tradition of craftsmanship, inside or outside building surfaces, is often treated with plaster, which plays both functional and ornamental roles. Today, plasterwork is predominantly produced through rationalized, time-, and cost-efficient processes, used for standardized building elements. These processes have also gained interest in the construction robotics field, and while such approaches target the direct automation of standardized plasterwork, they estrange themselves from the inherent qualities of this malleable material that are well known from the past. This research investigates the design potentials of robotic plaster spraying, proposing an adaptive, thin-layer vertical printing method for plasterwork that aims to introduce a digital craft through additive manufacturing. The presented work is an explorative study of a digitally controlled process that can be applied to broaden the design possibilities for the surfaces of building structures. It involves the spraying of multiple thin layers of plaster onto a vertical surface to create volumetric formations or patterns, without the use of any formwork or support structures. This article describes the experimental setup and the initial results of the data collection method involving systematic studies with physical testing, allowing to develop means to predict and visualize the complex-to-simulate material behavior, which might eventually enable to design with the plasticity of this material in a digital design tool.

Dynamic modelling to identify mitigation strategies for the COVID-19 pandemic.

Relevant pandemic-spread scenario simulations can provide guiding principles for containment and mitigation policies. We devised a compartmental model to predict the effectiveness of different mitigation strategies with a main focus on mass testing. The model consists of a set of simple differential equations considering the population size, reported and unreported infections, reported and unreported recoveries, and the number of COVID-19-inflicted deaths. We assumed that COVID-19 survivors are immune (e.g., mutations are not considered) and that the virus is primarily passed on by asymptomatic and pre-symptomatic individuals. Moreover, the current version of the model does not account for age-dependent differences in the death rates, but considers higher mortality rates due to temporary shortage of intensive care units. The model parameters have been chosen in a plausible range based on information found in the literature, but it is easily adaptable, i.e., these values can be replaced by updated information any time. We compared infection rates, the total number of people getting infected and the number of deaths in different scenarios. Social distancing or mass testing can contain or drastically reduce the infections and the predicted number of deaths when compared with a situation without mitigation. We found that mass testing alone and subsequent isolation of detected cases can be an effective mitigation strategy, alone and in combination with social distancing. It is of high practical relevance that a relationship between testing frequency and the effective reproduction number of the virus can be provided. However, unless one assumes that the virus can be globally defeated by reducing the number of infected persons to zero, testing must be upheld, albeit at reduced intensity, to prevent subsequent waves of infection. The model suggests that testing strategies can be equally effective as social distancing, though at much lower economic costs. We discuss how our mathematical model may help to devise an optimal mix of mitigation strategies against the COVID-19 pandemic. Moreover, we quantify the theoretical limit of contact tracing and by how much the effect of testing is enhanced, if applied to sub-populations with increased exposure risk or prevalence.

Smart investment of virus RNA testing resources to enhance Covid-19 mitigation.

A variety of mitigation strategies have been employed against the Covid-19 pandemic. Social distancing is still one of the main methods to reduce spread, but it entails a high toll on personal freedom and economic life. Alternative mitigation strategies that do not come with the same problems but are effective at preventing disease spread are therefore needed. Repetitive mass-testing using PCR assays for viral RNA has been suggested, but as a stand-alone strategy this would be prohibitively resource intensive. Here, we suggest a strategy that aims at targeting the limited resources available for viral RNA testing to subgroups that are more likely than the average population to yield a positive test result. Importantly, these pre-selected subgroups include symptom-free people. By testing everyone in these subgroups, in addition to symptomatic cases, large fractions of pre- and asymptomatic people can be identified, which is only possible by testing-based mitigation. We call this strategy smart testing (ST). In principle, pre-selected subgroups can be found in different ways, but for the purpose of this study we analyze a pre-selection procedure based on cheap and fast virus antigen tests. We quantify the potential reduction of the epidemic reproduction number by such a two-stage ST strategy. In addition to a scenario where such a strategy is available to the whole population, we analyze local applications, e.g. in a country, company, or school, where the tested subgroups are also in exchange with the untested population. Our results suggest that a two-stage ST strategy can be effective to curb pandemic spread, at costs that are clearly outweighed by the economic benefit. It is technically and logistically feasible to employ such a strategy, and our model predicts that it is even effective when applied only within local groups. We therefore recommend adding two-stage ST to the portfolio of available mitigation strategies, which allow easing social distancing measures without compromising public health.

On the mechanical power output required for human running - Insight from an analytical model.

In this paper the dynamics of human running on flat terrain and the required mechanical power output with its dependency on various parameters is investigated. Knowing the required mechanical power output is of relevance due to its relationship with the metabolic power. For example, a better understanding of the dependencies of required mechanical power output on weight, running and wind speed, step frequency, ground contact time etc. is very valuable for the assessment, analysis and optimization of running performance. Therefore, a mathematical model based on very few assumptions is devised. The purpose of the proposed model is to relate running speed and required mechanical power output as an algebraic function of the runner's mass, height, step rate, ground contact time and wind speed. This is relevant in order to better understand the mechanical energy cost of locomotion, and how much it depends on which parameters. The first of the main energy dissipation mechanisms is due to vertical oscillation, i.e., during each step some of the potential energy difference gets transformed into heat. The second mechanism is due to the anterior ground reaction force during the first part of stance and the third is due to aerodynamic drag. With the approximations of constant running speed and a sinusoidal vertical ground reaction force profile one obtains closed algebraic expressions for the center of mass trajectory and the required mechanical power output. Comparisons of model predictions and reported performance data suggest that approximately a quarter of the ground impact energy is stored during the first part of ground contact and then released during the remaining stance phase. Further, one can conclude from the model that less mechanical power output is required when running with higher step rates and a higher center of mass. Non intuitive is the result that a shorter ground contact time is beneficial for fast runs, while the opposite holds for slow runs. An important advantage of the devised model compared to others is that it leads to closed algebraic expressions for the center of mass trajectory and mechanical power output, which are functions of measurable quantities, i.e., of step rate, ground contact time, running speed, runner's mass, center of mass height, aerodynamic drag at some given speed, wind speed and heart rate. Moreover, the model relies on very few assumptions, which have been verified, and the only tuning parameter is the ratio of recovered elastic energy.

Leopard predation and primate evolution.

Although predation is an important driving force of natural selection its effects on primate evolution are still not well understood, mainly because little is known about the hunting behaviour of the primates' various predators. Here, we present data on the hunting behaviour of the leopard (Panthera pardus), a major primate predator in the Tai; forest of Ivory Coast and elsewhere. Radio-tracking data showed that forest leopards primarily hunt for monkeys on the ground during the day. Faecal analyses confirmed that primates accounted for a large proportion of the leopards' diet and revealed in detail the predation pressure exerted on the eight different monkey and one chimpanzee species. We related the species-specific predation rates to various morphological, behavioural and demographic traits that are usually considered adaptations to predation (body size, group size, group composition, reproductive behaviour, and use of forest strata). Leopard predation was most reliably associated with density, suggesting that leopards hunt primates according to abundance. Contrary to predictions, leopard predation rates were not negatively, but positively, related to body size, group size and the number of males per group, suggesting that predation by leopards did not drive the evolution of these traits in the predicted way. We discuss these findings in light of some recent experimental data and suggest that the principal effect of leopard predation has been on primates' cognitive evolution.