Selective Migration in New Towns: Influence on Regional Accountability in Early School Leaving

In an attempt to stop the rampant suburbanization, which countries experienced after World War II, a 'new town' policy was enrolled. As a major objective, and related to its origins, new towns were effective in attracting low and medium income households. Nowadays, cities and municipalities experience an increased accountability in which incentives are provided by 'naming and shaming'. This paper focuses on an issue where both historical and local policy come together: early school leaving. Using an iterative matching analysis, it suggests how to account for differences in population and regional characteristics. In other words, how to compare and interpret early school leaving in new towns in a more `fair' way. The results point out that (statistically) mitigating historical differences is necessary, even though this does not necessarily means that 'naming' is replaced by 'shaming'.Urban Economics; New Town; Early School Leaving; Naming and Shaming; Iterative Matching, Urban Planning

Comparison between hybrid and fully kinetic models of asymmetric magnetic reconnection: coplanar and guide field configurations

Magnetic reconnection occurring in collisionless environments is a multi-scale process involving both ion and electron kinetic processes. Because of their small mass, the electron scales are difficult to resolve in numerical and satellite data, it is therefore critical to know whether the overall evolution of the reconnection process is influenced by the kinetic nature of the electrons, or is unchanged when assuming a simpler, fluid, electron model. This paper investigate this issue in the general context of an asymmetric current sheet, where both the magnetic field amplitude and the density vary through the discontinuity. A comparison is made between fully kinetic and hybrid kinetic simulations of magnetic reconnection in coplanar and guide field systems. The models share the initial condition but differ in their electron modeling. It is found that the overall evolution of the system, including the reconnection rate, is very similar between both models. The best agreement is found in the guide field system, which confines particle better than the coplanar one, where the locality of the moments is violated by the electron bounce motion. It is also shown that, contrary to the common understanding, reconnection is much faster in the guide field system than in the coplanar one. Both models show this tendency, indicating that the phenomenon is driven by ion kinetic effects and not electron ones.Comment: 11 pages, 8 figures, accepted in Physics of Plasma

Evidence Propagation and Consensus Formation in Noisy Environments

We study the effectiveness of consensus formation in multi-agent systems where there is both belief updating based on direct evidence and also belief combination between agents. In particular, we consider the scenario in which a population of agents collaborate on the best-of-n problem where the aim is to reach a consensus about which is the best (alternatively, true) state from amongst a set of states, each with a different quality value (or level of evidence). Agents' beliefs are represented within Dempster-Shafer theory by mass functions and we investigate the macro-level properties of four well-known belief combination operators for this multi-agent consensus formation problem: Dempster's rule, Yager's rule, Dubois & Prade's operator and the averaging operator. The convergence properties of the operators are considered and simulation experiments are conducted for different evidence rates and noise levels. Results show that a combination of updating on direct evidence and belief combination between agents results in better consensus to the best state than does evidence updating alone. We also find that in this framework the operators are robust to noise. Broadly, Yager's rule is shown to be the better operator under various parameter values, i.e. convergence to the best state, robustness to noise, and scalability.Comment: 13th international conference on Scalable Uncertainty Managemen

Dose rationale and pharmacokinetics of dexmedetomidine in mechanically ventilated new-borns : impact of design optimisation

Purpose: There is a need for alternative analgosedatives such as dexmedetomidine in neonates. Given the ethical and practical difficulties, protocol design for clinical trials in neonates should be carefully considered before implementation. Our objective was to identify a protocol design suitable for subsequent evaluation of the dosing requirements for dexmedetomidine in mechanically ventilated neonates. Methods: A published paediatric pharmacokinetic model was used to derive the dosing regimen for dexmedetomidine in a first-in-neonate study. Optimality criteria were applied to optimise the blood sampling schedule. The impact of sampling schedule optimisation on model parameter estimation was assessed by simulation and re-estimation procedures for different simulation scenarios. The optimised schedule was then implemented in a neonatal pilot study. Results: Parameter estimates were more precise and similarly accurate in the optimised scenarios, as compared to empirical sampling (normalised root mean square error: 1673.1% vs. 13,229.4% and relative error: 46.4% vs. 9.1%). Most importantly, protocol deviations from the optimal design still allowed reasonable parameter estimation. Data analysis from the pilot group (n = 6) confirmed the adequacy of the optimised trial protocol. Dexmedetomidine pharmacokinetics in term neonates was scaled using allometry and maturation, but results showed a 20% higher clearance in this population compared to initial estimates obtained by extrapolation from a slightly older paediatric population. Clearance for a typical neonate, with a post-menstrual age (PMA) of 40 weeks and weight 3.4 kg, was 2.92 L/h. Extension of the study with 11 additional subjects showed a further increased clearance in pre-term subjects with lower PMA. Conclusions: The use of optimal design in conjunction with simulation scenarios improved the accuracy and precision of the estimates of the parameters of interest, taking into account protocol deviations, which are often unavoidable in this event-prone population

Application of the multidimensional fatigue inventory (MFI-20) in cancer patients receiving radiotherapy.

In this paper the psychometric properties of the multidimensional fatigue inventory (MFI-20) are established further in cancer patients. The MFI is a 20-item self-report instrument designed to measure fatigue. It covers the following dimensions: general fatigue, physical fatigue, reduced activity, reduced motivation and mental fatigue. The instrument was used in a Dutch and Scottish sample of cancer patients receiving radiotherapy. The dimensional structure was assessed using confirmatory factor analyses (Lisrel's unweighted least-squares method). The hypothesised five-factor model appeared to fit the data in both samples (adjusted goodness of fit; AGFI: 0.97 and 0.98). Internal consistency of the separate scales was good in both the Dutch and Scottish samples with Cronbach's alpha coefficients ranging from 0.79 to 0.93. Construct validity was assessed by correlating the MFI-20 to activities of daily living, anxiety and depression. Significant relations were assumed. Convergent validity was investigated by correlating the MFI scales with a visual analogue scale measuring fatigue and with a fatigue-scale derived from the Rotterdam Symptom Checklist. Results support the validity of the MFI-20. The highly similar results in the Dutch and Scottish sample suggest that the portrayal of fatigue using the MFI-20 is quite robust