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The purpose of this paper is to develop an yield-based process capability index (PCI), C _py , to overcome the shortcomings of existing PCIs that limit their use and lead to inaccurate measures of quality conformance under a variety of common conditions.

–C _py is developed conceptually to flexibly and accurately reflect conformance and then used to numerically measure inaccuracies of C _pk .

–C _py overcomes many of the problems associated with existing PCIs, including C _pk . The degree of process distribution non-normality, level of quality (the sigma level), and whether the process is centered or shifted left or right affect the direction and size of process capability error produced by C _pk . The accuracy of C _pk can be greatly affected by process data that deviate even slightly from normality.

–C _py offers numerous advantages compared to existing PCIs. It accurately reflects process conformance regardless of the process distribution. It is applicable even if the process has multiple characteristics and with both variable and attribute data. Its calculation is relatively simple and the necessary data for it are likely already captured by most organizations.

The main contributions are the development of a new PCI, C _py ; a conceptual analysis of its advantages; and a numerical analysis of the improved accuracy of C _py as compared to C _pk for shifted and non-shifted process means for normal, nearly normal, and highly non-normal distributions over a range of process variability levels.

In his soliloquy, Hamlet reasons about the choice of whether to end his life or not. Our own experience of choice contains many such instances of choice as the outcome of a reasoning process. This aspect of choice is not discussed in this book although I would look to Chapter 3 on mathematics, logic, artificial intelligence and ordinary language to provide a route into investigating this aspect.

The purpose of this paper is to develop pyridine polyesteramide coatings from Linseed (Linum ussitatissimum) seeds oil for the utilisation of a sustainable resource as coating material, as well as to improve the coating properties.

Linseed oil was first converted into N,N bis 2‐hydroxyethyl linseed oil fatty amide (HELA). The resin was synthesized by the reaction of linseed oil fatty amide diol with 2,3‐pyridine di carboxylic acid to develop pyridine polyesteramide (Py‐PEA) and further treated with poly(styrene‐co‐maleic anhydride)(SMA) in different phr (part per hundred part of resin). The structural elucidation of Py‐PEA was carried out by FT‐IR, 1H‐NMR and 13C‐NMR spectral techniques. The thermal stability and curing behaviour of the resin were determined by differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA), respectively. The physico‐mechanical and anticorrosive properties were investigated by standard laboratory methods.

The authors developed a good anticorrosive coating material from sustainable resource. The physico‐mechanical and anticorrosive performance evaluation exhibited satisfactory results. The approach facilitated curing to occur at ambient temperature and the thermal studies revealed that Py‐PEA‐SMA‐45 might be safely used up to 140°C.

Poly(styrene‐co‐maleic anhydride) modified pyridine polyesteramide coatings showed the highest scratch hardness 3.0 kg, flexibility (1/8 inch canonical mandrel bend test) and gloss at 45° is 62‐64. Among all, Py‐PEA‐SMA 45 showed the best physico‐mechanical and chemical resistance performance. Thus, the resin may be used as an effective coating material.

The paper shows that the synthesis of polyesteramide resin from vegetable oil provides a new way to utilize a renewable resource based raw material.

To determine the mortality of drug users after release from prison in Denmark, a cohort of drug users was identified from two national registers during 1996‐2001: the drug treatment register (T) and the register of viral hepatitis (H). Incarcerations were extracted from the national penal register, vital status from the civil register, and causes of death from the death certificate register and the police register of drug‐related deaths. We identified 15,885 drug users (T: 15,735, H: 896), 62% of the estimated drug‐using population in Denmark. There were 1000 observed deaths, of which 51% were classified as overdose deaths. Mortality in the treatment cohort was 2.4/100 person years (py) (95% C.I. 2.2‐2.5/100 py) compared to the general population expectation of 0.2/100 py. Within the first 2 weeks after release from prison, 26 deaths were observed among 6019 released drug users corresponding to 13/100 py (95% CI 8‐19/100 py). Overdose deaths accounted for 24/26 deaths (92%) in the first two weeks compared to 121/179 (68%) hereafter (p <0.001). We conclude that drug users released from prison are at high risk of overdose death. We suggest that methadone treatment should be evaluated as a way to decrease mortality after release from prison.

The purpose of this paper is to present a simulation‐based approach for modeling multi‐year non‐life insurance risk in internal risk models. Strategic management in an insurance company requires a multi‐year time horizon for economic decision making, for example, in the context of internal risk models. In the literature to date, only the ultimate perspective and, more recently, the one‐year perspective (for Solvency II purposes) are considered.

The authors present a way of defining and calculating multi‐year claims development results and extend the simulation‐based algorithm (“re‐reserving”) for quantifying one‐year non‐life insurance risk, presented in Ohlsson and Lauzeningks, to a multi‐year perspective.

The multi‐year algorithm is applied to the chain ladder reserving model framework of Mack (1993).

The usefulness of the new multi‐year horizon is illustrated in the context of internal risk models by means of a case study, where the multi‐year algorithm is applied to a claims development triangle based on Mack and on England and Verrall. This algorithm has been implemented in an excel tool, which is given as supplemented material.

To the best of the authors' knowledge, there are no model approaches or studies on insurance risk for projection periods of not just one, but several, new accident years; this requires a suitable extension of the classical Mack model; however, consideration of multiple years is crucial in the context of enterprise risk management.

As eyewitnesses provide the most valuable information for criminal investigations, it is important to further develop and test techniques for collecting eyewitness testimony so that they meet the major objective of a police interview: obtaining details pertaining to criminal actions. The purpose of this paper is to test a new instruction – the re-enactment investigative instruction – formulated to collect the most fine-grained details of a criminal event as accurately as possible. It leads the interviewee to decompose all directly recollected actions into the most minimal actions so that the event can be accurately re-enacted.

In all, 40 participants individually viewed a video depicting a robbery, were randomly assigned to a re-enactment or structured interview (SI) group and then interviewed face-to-face. Each interview was comprised of two free recall phases and a questioning phase. Manipulation of the re-enactment instruction took place in the second free recall phase of the re-enactment interviews (RIs).

The RI elicited more correct information compared to the SI (d=1.14), and slightly but not significantly less incorrect information (d=0.09). Participants in the RI condition reported significantly more details pertaining to general and specific actions.

The re-enactment instruction shows the potential to increase witness recall in a way that promotes recall of both additional correct information and investigative-relevant information.

The instruction provides witnesses a retrieval strategy that facilitates overcoming both the gap between memory availability and accessibility and the gap between memory availability and output regulation, eliciting more details with no significant increase of errors.

Automated condition surveys have been recently introduced for condition assessment of highway infrastructures worldwide. Accurate predictions of the current state, median life (ML) and future state of highway infrastructures are crucial for developing appropriate inspection and maintenance strategies for newly created as well as existing aging highway infrastructures. The paper aims to discuss these issues.

This paper proposes Markov Chain based deterioration modelling using a linear transition probability (LTP) matrix method and a median life expectancy (MLE) algorithm. The proposed method is applied and evaluated using condition improvement between the two successive inspections from the Surface Condition Assessment of National Network of Roads survey of the UK Pavement Management System.

The proposed LTP matrix model utilises better insight than the generic or decoupling linear approach used in estimating transition probabilities formulated in the past. The simulated LTP predicted conditions are portrayed in a deterioration profile and a pairwise correlation. The MLs are computed statistically with a cumulative distribution function plot.

The paper concludes that MLE is ideal for projecting half asset life, and the LTP matrix approach presents a feasible approach for new maintenance regime when more certain deterioration data become available.