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Three types of payment methods have been introduced across European countries in attempts to encourage better, more integrated care of persons with multimorbidity: pay-for-performance; pay-for-coordination; and an all-inclusive payment method. We examine whether there are differences in the way these payment methods affect health and healthcare use in persons with multimorbidity.

Using individual-level survey data from twenty European countries, we examine unadjusted differences in average outcomes for the years 2011–2015 by whether countries adopted new payment methods for integrated care. We then test for a differential effect for multimorbid persons using linear, individual random effects regressions, including country and time fixed effects and clustering standard errors at the country level.

We find little effect of varying payment methods on key outcomes for multimorbid individuals despite the theoretical predictions and the rhetoric in many policy documents.

Policymakers should bear in mind that the success of the payment method relies on the specific design of the incentives and their implementation. New effective models of care and how to incentivise these for multimorbid patients is an ongoing research priority.

This paper is the first to study the effects of payments for integration on the dimensions and populations these schemes intend to affect; health and healthcare use at the individual level for multimorbid individuals.

Some past studies of credit risk ratings migration have found trend reversals and evidence that the data‐generating process is nonstationary. Using a sample of Farm Credit System mortgages, we find no compelling statistical evidence of either phenomenon. We do find evidence that our sample of loans may be characterized by two types of borrowers – namely, movers and stayers. This type of borrower heterogeneity is unobserved because movers who do not migrate are indistinguishable from stayers who never migrate. We report on the development of a flexible nonparametric model for estimating transition probabilities. The model can also be used to estimate nonstationary transition probabilities and an example is provided.

Despite overall reductions in levels of smoking in the UK, rates of offender smoking remain high. In 2016, it was announced that prisons in England and Wales would gradually introduce a smoking ban. The purpose of this paper is to explore offenders’ perceptions around the upcoming smoking ban.

A total of eight focus groups were conducted in four prisons across the North of England. Both smoking and non-smoking offenders participated in the focus groups, and thematic analysis was used to explore the findings.

Themes generated from the data were “freedom and rights”, “the prison environment” and “guiding support”. Participants discussed how the smoking ban was viewed as a punishment and restricted their freedom, with perceptions as to why the ban was being implemented centring around others trying to control them. Participants expressed concerns around the financial implications of the smoking ban on already stretched prison resources. Participants also recommended improving the nicotine replacement therapy on offer, and increasing the range of leisure activities within the prison to prepare for the smoking ban.

Overall, it was apparent that participants’ awareness of the smoking ban was generally poor. It is recommended that offenders need to be made more aware of the smoking cessation support they will receive and given the opportunity to ask questions about the smoking ban. Increasing offenders’ awareness of the ban may reduce stress associated with a perceived lack of choice around their smoking behaviours.

The premise of this research is that the coupling of reinforcement learning algorithms and computational dynamics can be used to design efficient control strategies and to improve the cooling of hot components by quenching, a process that is classically carried out based on professional experience and trial-error methods. Feasibility and relevance are assessed on various 2-D numerical experiments involving boiling problems simulated by a phase change model. The purpose of this study is then to integrate reinforcement learning with boiling modeling involving phase change to optimize the cooling process during quenching.

The proposed approach couples two state-of-the-art in-house models: a single-step proximal policy optimization (PPO) deep reinforcement learning (DRL) algorithm (for data-driven selection of control parameters) and an in-house stabilized finite elements environment combining variational multi-scale (VMS) modeling of the governing equations, immerse volume method and multi-component anisotropic mesh adaptation (to compute the numerical reward used by the DRL agent to learn), that simulates boiling after a phase change model formulated after pseudo-compressible Navier–Stokes and heat equations.

Relevance of the proposed methodology is illustrated by controlling natural convection in a closed cavity with aspect ratio 4:1, for which DRL alleviates the flow-induced enhancement of heat transfer by approximately 20%. Regarding quenching applications, the DRL algorithm finds optimal insertion angles that adequately homogenize the temperature distribution in both simple and complex 2-D workpiece geometries, and improve over simpler trial-and-error strategies classically used in the quenching industry.

To the best of the authors’ knowledge, this constitutes the first attempt to achieve DRL-based control of complex heat and mass transfer processes involving boiling. The obtained results have important implications for the quenching cooling flows widely used to achieve the desired microstructure and material properties of steel, and for which differential cooling in various zones of the quenched component will yield irregular residual stresses that can affect the serviceability of critical machinery in sensitive industries.

This paper aims to report the study of a fluid buoy system that includes wave effects, with particular emphasis on validating the numerical results with experimental data.

A fluid–solid coupled algorithm is proposed to describe the motion of a rigid buoy under the effects of waves. The Navier–Stokes equations are solved with the open-source finite volume package Code Saturne, in which a free-surface capture technique and equations of motion for the solid are implemented. An ad hoc experiment on a laboratory scale is built. A buoy is placed into a tank partially filled with water; the tank is mounted into a shake table and subjected to controlled motion that promotes waves. The experiment allows for recording the evolution of the free surface at the control points using the ultrasonic sensors and the movement of the buoy by tracking the markers by postprocessing the recorded videos. The numerical results are validated by comparison with the experimental data.

The implemented free-surface technique, developed within the framework of the finite-volume method, is validated. The best-obtained agreement is for small amplitudes compatible with the waves evolving under deep-water conditions. Second, the algorithm proposed to describe rigid-body motion, including wave analysis, is validated. The numerical body motion and wave pattern satisfactorily matched the experimental data. The complete 3D proposed model can realistically describe buoy motions under the effects of stationary waves.

The novel aspects of this study encompass the implementation of a fluid–structure interaction strategy to describe rigid-body motion, including wave effects in a finite-volume context, and the reported free-surface and buoy position measurements from experiments. To the best of the authors’ knowledge, the numerical strategy, the validation of the computed results and the experimental data are all original contributions of this work.

This paper aims to identify factors that affect agricultural mortgage default and prepayment.

Using a sample of farm credit system loans, prepayment and default are modeled as competing risks with potentially non‐stationary covariates using a statistical/econometric technique called survival snalysis (SA).

The analysis suggests that the primary drivers of prepayment and default are the rate of interest charged by the lender at origination and the borrower's current ratio at origination. Tests of the existence of a geographic effect indicate that despite bank management belief to the contrary, branches may not be homogeneous.

This analysis would be improved if more data were available in an easily obtainable manner to control for unobserved heterogeneity. Unobserved heterogeneity or incomplete specification within a model can be problematic. Inferences among regression coefficients can be problematic in that the estimates have inflated variances and unreliable test statistics. In addition, more frequent measures of the time‐varying covariates could be obtained to improve upon the SA models presented above. Future analyses could also incorporate other sections of the agricultural credit association portfolio, as well as a comparison to variable rate notes. One other logical next step would be to obtain loan collateral values to obtain estimates of the exposure at default, and the loss given default, or the estimates needed for the advanced internal ratings based approach described in the Basel Accords.

This paper provides a method for lenders to measure and model mortgage termination, an important consideration for risk managers when determining capital adequacy described in the Basel Accords.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.