Does poaching distort training?

We analyse the efficiency of the labour market outcome in a competitive search equilibrium model with endogenous turnover and endogenous general human capital formation. We show that search frictions do not distort training decisions if firms and their employees are able to coordinate efficiently, for instance, by using long-term contracts. In the absence of efficient coordination devices there is too much turnover and too little investments in general training. Nonetheless, the number of training firms and the amount of training provided are constrained optimal, and training subsidies therefore reduce welfare.Matching; Training; Poaching; Efficiency

Performance pay and adverse selection

We study equilibrium wage contracts in a labour market with adverse selection and moral hazard. Firms offer incentive contracts to their employees to motivate them to exert effort. Providing incentives comes, however, at a cost, as it leads to misallocation of effort across tasks. With ex ante identical workers, the optimal wage contract is linear, and the equilibrium resource allocation optimal. With ex ante heterogenous workers, firms may increase the incentive power of the wage contract to attract the better workers. The resulting equilibrium is separating, in the sense that workers self-select on contracts. Furthermore, the contracts offered to the good workers are too high powered compared to the contracts that maximise welfare.-

Equilibrium Incentive Contracts

We study a labour market in which firms can observe workers’ output but not their effort, and in which a worker’s productivity in a given firm depends on a worker-firm specific component, unobservable for the firm. Firms offer wage contracts that optimally trade off effort and wage costs. As a result, employed workers enjoy rents, which in turn create unemployment. We show that the incentive power of the equilibrium wage contract is constrained socially efficient in the absence of unemployment benefits. We then apply the model to explain the recent increase in performance-pay contracts. Within our model, this can be explained by three different factors: (i) increased importance of non-observable effort, (ii) a fall in the marginal tax rate, (iii) a reduction in the heterogeneity of workers performing the same task. The likely effect of all three factors is an increase in the equilibrium unemployment rate.Incentives; Contracts; Unemployment; efficiency

Uncertainty modelling in multi-criteria analysis of water safety measures

Water utilities must assess risks and make decisions on safety measures in order to obtain a safe and sustainable drinking water supply. The World Health Organization emphasises preparation of Water Safety Plans, in which risk ranking by means of risk matrices with discretised probability and consequence scales is commonly used. Risk ranking enables prioritisation of risks but there is currently no common and structured way of performing uncertainty analysis and using risk ranking for evaluating and comparing water safety measures. To enable a proper prioritisation of safety measures and an efficient use of available resources for risk reduction, two alternative models linking risk ranking and multi-criteria decision analysis (MCDA) are presented and evaluated. The two models specifically enable uncertainty modelling in MCDA and they differ in terms of how uncertainties in risk levels are considered. The need of formal handling of risk and uncertainty in MCDA is emphasised in the literature and the suggested models provide innovations that are not dependent on the application domain. In the case study application presented here, possible safety measures are evaluated based on the benefit of estimated risk reduction, the cost of implementation and the probability of not achieving an acceptable risk level. Additional criteria such as environmental impact and consumer trust may also be included when applying the models. The case study shows how safety measures can be ranked based on preference scores or cost-effectiveness and how measures not reducing the risk enough can be identified and disqualified. Furthermore, the probability of each safety measure being ranked highest can be calculated. The two models provide a stepwise procedure for prioritising safety measures and enable a formalised handling of uncertainties in input data and results

Interobserver agreement for neonatal seizure detection using multichannel EEG

Objective To determine the interobserver agreement (IOA) of neonatal seizure detection using the gold standard of conventional, multichannel EEG. Methods A cohort of full-term neonates at risk of acute encephalopathy was included in this prospective study. The EEG recordings of these neonates were independently reviewed for seizures by three international experts. The IOA was estimated using statistical measures including Fleiss' kappa and percentage agreement assessed over seizure events (event basis) and seizure duration (temporal basis). Results A total of 4066 h of EEG recordings from 70 neonates were reviewed with an average of 2555 seizures detected. The IOA was high with temporal assessment resulting in a kappa of 0.827 (95% CI: 0.769–0.865; n = 70). The median agreement was 83.0% (interquartile range [IQR]: 76.6–89.5%; n = 33) for seizure and 99.7% (IQR: 98.9–99.8%; n = 70) for nonseizure EEG. Analysis of events showed a median agreement of 83.0% (IQR: 72.9–86.6%; n = 33) for seizures with 0.018 disagreements per hour (IQR: 0.000–0.090 per hour; n = 70). Observers were more likely to disagree when a seizure was less than 30 sec. Overall, 33 neonates were diagnosed with seizures and 28 neonates were not, by all three observers. Of the remaining nine neonates with contradictory EEG detections, seven presented with low total seizure burden. Interpretation The IOA is high among experts for the detection of neonatal seizures using conventional, multichannel EEG. Agreement is reduced when seizures are rare or have short duration. These findings support EEG-based decision making in the neonatal intensive care unit, inform EEG interpretation guidelines, and provide benchmarks for seizure detection algorithms.Peer reviewe

Evaluation of a Commercial Enzyme Linked Immunosorbent Assay (ELISA) for the Determination of the Neurotoxin BMAA in Surface Waters

The neurotoxin ß-N-methylamino-L-alanine (BMAA) is suspected to play a role in Alzheimer’s disease, Parkinson’s disease and amyotrophic lateral sclerosis. Because BMAA seems to be produced by cyanobacteria, surface waters are screened for BMAA. However, reliable analysis of BMAA requires specialized and expensive equipment. In 2012, a commercial enzyme-linked immunosorbent assay (ELISA) for determination of BMAA in surface waters was released. This kit could enable fast and relatively cheap screening of surface waters for BMAA. The objective of this study was to determine whether the BMAA ELISA kit was suitable for the determination of BMAA concentrations in surface waters. We hypothesised that the recovery of spiked samples was close to 100% and that the results of unspiked sample analysis were comparable between ELISA and liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis. However, we found that recovery was higher than 100% in most spiked samples, highest determined recovery was over 400%. Furthermore, the ELISA gave a positive signal for nearly each tested sample while no BMAA could be detected by LC-MS/MS. We therefore conclude that in its current state, the kit is not suitable for screening surface waters for BMAA

Distributed Neural Representations of Conditioned Threat in the Human Brain

Detecting and responding to threat engages several neural nodes including the amygdala, hippocampus, insular cortex, and medial prefrontal cortices. Recent propositions call for the integration of more distributed neural nodes that process sensory and cognitive facets related to threat. Integrative, sensitive, and reproducible distributed neural decoders for the detection and response to threat and safety have yet to be established. We combine functional MRI data across varying threat conditioning and negative affect paradigms from 1465 participants with multivariate pattern analysis to investigate distributed neural representations of threat and safety. The trained decoders sensitively and specifically distinguish between threat and safety cues across multiple datasets. We further show that many neural nodes dynamically shift representations between threat and safety. Our results establish reproducible decoders that integrate neural circuits, merging the well-characterized \u27threat circuit\u27 with sensory and cognitive nodes, discriminating threat from safety regardless of experimental designs or data acquisition parameters

Wake Development behind Paired Wings with Tip and Root Trailing Vortices: Consequences for Animal Flight Force Estimates

Recent experiments on flapping flight in animals have shown that a variety of unrelated species shed a wake behind left and right wings consisting of both tip and root vortices. Here we present an investigation using Particle Image Velocimetry (PIV) of the behaviour and interaction of trailing vortices shed by paired, fixed wings that simplify and mimic the wake of a flying animal with a non-lifting body. We measured flow velocities at five positions downstream of two adjacent NACA 0012 aerofoils and systematically varied aspect ratio, the gap between the wings (corresponding to the width of a non-lifting body), angle of attack, and the Reynolds number. The range of aspect ratios and Reynolds number where chosen to be relevant to natural fliers and swimmers, and insect flight in particular. We show that the wake behind the paired wings deformed as a consequence of the induced flow distribution such that the wingtip vortices convected downwards while the root vortices twist around each other. Vortex interaction and wake deformation became more pronounced further downstream of the wing, so the positioning of PIV measurement planes in experiments on flying animals has an important effect on subsequent force estimates due to rotating induced flow vectors. Wake deformation was most severe behind wings with lower aspect ratios and when the distance between the wings was small, suggesting that animals that match this description constitute high-risk groups in terms of measurement error. Our results, therefore, have significant implications for experimental design where wake measurements are used to estimate forces generated in animal flight. In particular, the downstream distance of the measurement plane should be minimised, notwithstanding the animal welfare constraints when measuring the wake behind flying animals