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Non-standard errors
(2021)
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.
Neurogenic dysphagia is one of the most frequent and prognostically relevant neurological deficits in a variety of disorders, such as stroke, parkinsonism and advanced neuromuscular diseases. Flexible endoscopic evaluation of swallowing (FEES) is now probably the most frequently used tool for objective dysphagia assessment in Germany. It allows evaluation of the efficacy and safety of swallowing, determination of appropriate feeding strategies and assessment of the efficacy of different swallowing manoeuvres. The literature furthermore indicates that FEES is a safe and well-tolerated procedure. In spite of the huge demand for qualified dysphagia diagnostics in neurology, a systematic FEES education has not yet been established. The structured training curriculum presented in this article aims to close this gap and intends to enforce a robust and qualified FEES service. As management of neurogenic dysphagia is not confined to neurologists, this educational programme is applicable to other clinicians and speech–language therapists with expertise in dysphagia as well. The systematic education in carrying out FEES across a variety of different professions proposed by this curriculum will help to spread this instrumental approach and to improve dysphagia management.
he most basic behavioural states of animals can be described as active or passive. While high-resolution observations of activity patterns can provide insights into the ecology of animal species, few methods are able to measure the activity of individuals of small taxa in their natural environment. We present a novel approach in which a combination of automatic radiotracking and machine learning is used to distinguish between active and passive behaviour in small vertebrates fitted with lightweight transmitters (<0.4 g).
We used a dataset containing >3 million signals from very-high-frequency (VHF) telemetry from two forest-dwelling bat species (Myotis bechsteinii [n = 52] and Nyctalus leisleri [n = 20]) to train and test a random forest model in assigning either active or passive behaviour to VHF-tagged individuals. The generalisability of the model was demonstrated by recording and classifying the behaviour of tagged birds and by simulating the effect of different activity levels with the help of humans carrying transmitters. The model successfully classified the activity states of bats as well as those of birds and humans, although the latter were not included in model training (F1 0.96–0.98).
We provide an ecological case-study demonstrating the potential of this automated monitoring tool. We used the trained models to compare differences in the daily activity patterns of two bat species. The analysis showed a pronounced bimodal activity distribution of N. leisleri over the course of the night while the night-time activity of M. bechsteinii was relatively constant. These results show that subtle differences in the timing of species' activity can be distinguished using our method.
Our approach can classify VHF-signal patterns into fundamental behavioural states with high precision and is applicable to different terrestrial and flying vertebrates. To encourage the broader use of our radiotracking method, we provide the trained random forest models together with an R package that includes all necessary data processing functionalities. In combination with state-of-the-art open-source automated radiotracking, this toolset can be used by the scientific community to investigate the activity patterns of small vertebrates with high temporal resolution, even in dense vegetation.
Almost ten years after the European Commission action plan on building a capital markets union (CMU) and despite incremental progress, e.g. in the form of the EU Listing Act, the picture looks dire. Stock exchanges, securities markets, and supervisory authorities remain largely national, and, in many cases, European companies have decided to exclusively list overseas. Notwithstanding the economic and financial benefits of market integration, CMU has become a geopolitical necessity. A unified capital market can bolster resilience, strategic autonomy, and economic sovereignty, reduce dependence on external funding, and may foster economic cooperation between member states.
The reason for the persistent stand-still in Europe’s CMU development is not so much the conflict between market- and state-based integration, but rather the hesitancy of national regulatory and supervisory bodies to relinquish powers. If EU member states wanted to get real about CMU (as they say, and as they should), they need to openly accept the loss of sovereignty that follows from a true unified capital market. Building on economic as well as historical evidence, the paper offers viable proposals on how to design competent institutions within the current European framework.
This note outlines the case for speedy capital market integration and for the adoption of a common regulatory framework and single supervisory authority from a political economy perspective. We also show the alternative case for harmonization and centralization via regulatory competition, elaborating how competition between EU jurisdictions by way of full mutual recognition may lead to a (cost-)efficient and standardized legal framework for capital markets. Lastly, the note addresses the political economy conflict that underpins the implementation of both models for integrating capital markets. We point out that, in both cases, national authorities experience a loss of legislative and jurisdictional competence at the national level. We predict that any plan to foster a stronger capital market union, following an institution based or a market-based strategy, will face opposition from powerful national stakeholders.
The most basic behavioural states of animals can be described as active or passive. However, while high-resolution observations of activity patterns can provide insights into the ecology of animal species, few methods are able to measure the activity of individuals of small taxa in their natural environment. We present a novel approach in which the automated VHF radio-tracking of small vertebrates fitted with lightweight transmitters (< 0.2 g) is used to distinguish between active and passive behavioural states.
A dataset containing > 3 million VHF signals was used to train and test a random forest model in the assignment of either active or passive behaviour to individuals from two forest-dwelling bat species (Myotis bechsteinii (n = 50) and Nyctalus leisleri (n = 20)). The applicability of the model to other taxonomic groups was demonstrated by recording and classifying the behaviour of a tagged bird and by simulating the effect of different types of vertebrate activity with the help of humans carrying transmitters. The random forest model successfully classified the activity states of bats as well as those of birds and humans, although the latter were not included in model training (F-score 0.96–0.98).
The utility of the model in tackling ecologically relevant questions was demonstrated in a study of the differences in the daily activity patterns of the two bat species. The analysis showed a pronounced bimodal activity distribution of N. leisleri over the course of the night while the night-time activity of M. bechsteinii was relatively constant. These results show that significant differences in the timing of species activity according to ecological preferences or seasonality can be distinguished using our method.
Our approach enables the assignment of VHF signal patterns to fundamental behavioural states with high precision and is applicable to different terrestrial and flying vertebrates. To encourage the broader use of our radio-tracking method, we provide the trained random forest models together with an R-package that includes all necessary data-processing functionalities. In combination with state-of-the-art open-source automated radio-tracking, this toolset can be used by the scientific community to investigate the activity patterns of small vertebrates with high temporal resolution, even in dense vegetation.