De illusie van het politieke primaat: macht en onmacht van de Nederlandse politiek

Oratie uitgesproken door Prof.dr. Anchrit Wille bij de aanvaarding van het bijzonder hoogleraarschap ingesteld door het CAOP met als leeropdracht Transities in de publieke sector aan de Universiteit Leiden op 21 november 2022Oratie uitgesproken door Prof.dr. Anchrit Wille bij de aanvaarding van het bijzonder hoogleraarschap ingesteld door het CAOP met als leeropdracht Transities in de publieke sector aan de Universiteit Leiden op 21 november 2022The politics and administration of institutional chang

De opmars van de politieke experts

The politics and administration of institutional chang

De opmars van de politieke experts

The politics and administration of institutional chang

Strong host phylogenetic and ecological effects on host competency for avian influenza in Australian wild birds

Host susceptibility to parasites is mediated by intrinsic and external factors such as genetics, ecology, age and season. While waterfowl are considered central to the reservoir community for low pathogenic avian influenza A viruses (LPAIV), the role of host phylogeny has received limited formal attention. Herein, we analysed 12 339 oropharyngeal and cloacal swabs and 10 826 serum samples collected over 11 years from wild birds in Australia. As well as describing age and species-level differences in prevalence and seroprevalence, we reveal that host phylogeny is a key driver in host range. Seasonality effects appear less pronounced than in the Northern Hemisphere, while annual variations are potentially linked to El Niño–Southern Oscillation. Our study provides a uniquely detailed insight into the evolutionary ecology of LPAIV in its avian reservoir community, defining distinctive processes on the continent of Australia and expanding our understanding of LPAIV globally.Michelle Wille, Simeon Lisovski, David Roshier, Marta Ferenczi, Bethany J. Hoye, Trent Leen, Simone Warner, Ron A. M. Fouchier, Aeron C. Hurt, Edward C. Holmes, and Marcel Klaasse

Gap-filling eddy covariance methane fluxes:Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET)

Factors Associated with Revision Surgery after Internal Fixation of Hip Fractures

Background: Femoral neck fractures are associated with high rates of revision surgery after management with internal fixation. Using data from the Fixation using Alternative Implants for the Treatment of Hip fractures (FAITH) trial evaluating methods of internal fixation in patients with femoral neck fractures, we investigated associations between baseline and surgical factors and the need for revision surgery to promote healing, relieve pain, treat infection or improve function over 24 months postsurgery. Additionally, we investigated factors associated with (1) hardware removal and (2) implant exchange from cancellous screws (CS) or sliding hip screw (SHS) to total hip arthroplasty, hemiarthroplasty, or another internal fixation device. Methods: We identified 15 potential factors a priori that may be associated with revision surgery, 7 with hardware removal, and 14 with implant exchange. We used multivariable Cox proportional hazards analyses in our investigation. Results: Factors associated with increased risk of revision surgery included: female sex, [hazard ratio (HR) 1.79, 95% confidence interval (CI) 1.25-2.50; P = 0.001], higher body mass index (fo