Using Coxian Phase-Type Distributions to Identify Patient Characteristics for Duration of Stay in Hospital

Coxian phase-type distributions are a special type of Markov model that describes duration until an event occurs in terms of a process consisting of a sequence of latent phases. This paper considers the use of Coxian phase-type distributions for modelling patient duration of stay for the elderly in hospital and investigates the potential for using the resulting distribution as a classifying variable to identify common characteristics between different groups of patients according to their (anticipated) length of stay in hospital. The identification of common characteristics for patient length of stay groups would offer hospital managers and clinicians possible insights into the overall management and bed allocation of the hospital wards.

Associations between maternal characteristics and pregnancy-related stress among low-risk mothers: An observational cross-sectional study

Background: Pregnancy is viewed as a major life event and, while the majority of healthy, low-risk women adapt well to pregnancy, there are those whose levels of stress are heightened by the experience.

Objectives: To determine the level of pregnancy-related stress experienced by a group of healthy, low-risk pregnant women and to relate the level of stress with a number of maternal characteristics.

Design: An observational cross-sectional study.

Setting: A large, urban maternity centre in Northern Ireland.

Participants: Of the 306 pregnant women who were invited to participate, 278 provided informed consent and were administered one self-complete questionnaire. Due to the withdrawal criteria, 15 questionnaires were removed from the analysis, resulting in a final sample of 263 healthy, low-risk pregnant women.

Methods: Levels of stress were measured using a self-report measure designed to assess specific worries and concerns relating to pregnancy. Maternal characteristics collected included age, marital status, social status, parity, obstetric history, perceived health status and 'wantedness' for the pregnancy. Regression analysis was undertaken using an ordinary linear regression model.

Results: The mean prenatal distress score in the sample was 15.1 (SD = 7.4; range 0-46). The regression model showed that women who had had previous pregnancies, with or without complications, had significantly lower mean prenatal distress scores than primiparous women (p < 0.01). Women reporting poorer physical health had higher mean prenatal distress scores than those who reported at least average health, while women aged 16-20 experienced a mean increase in the reported prenatal distress score (p < 0.05) in comparison to the reference group of 36 years and over.

Conclusions: This study brings to light the prevalence of pregnancy-related stress within a sample representative of healthy, low-risk women. Current antenatal care is ill-equipped to identify women suffering from high levels of stress; yet a growing body of research evidence links stress with adverse pregnancy outcomes. This study emphasises that healthy, low-risk women experience a range of pregnancy-related stress and identification of stress levels, either through the use of a simple stress measurement tool or through the associated factors identified within this research study, provides valuable data on maternal well-being. (C) 2010 Elsevier Ltd. All rights reserved.

The Characteristics of Wave Impacts on an Oscillating Wave Surge Converter

Wave impacts on an oscillating wave surge converter are examined using experimental and numerical methods. The mechanics of the impact event are identified experimentally with the use of images recorded with a high-speed camera. It is shown that it is the device that impacts the wave rather than a breaking wave impacting the device. Numerical simulations using two different approaches are used to further understand the issue. Good agreement is shown between numerical simulations and experimental measurements at 25th scale.

The Characteristics of Wave Impacts on an Oscillating Wave Surge Converter

Wave impacts on an Oscillating Wave Surge Converter are examined using experimental and numerical methods. The mechanics of the impact event are identified experimentally with the use of images recorded with a high speed camera. It is shown that it is the device which impacts the wave rather than a breaking wave impacting the device. Numerical simulations using two different approaches are used to further understand the issue. Good agreement is shown between numerical simulations and experimental measurements at 25th scale.

Evidential event inference in transport video surveillance

This paper presents a new framework for multi-subject event inference in surveillance video, where measurements produced by low-level vision analytics usually are noisy, incomplete or incorrect. Our goal is to infer the composite events undertaken by each subject from noise observations. To achieve this, we consider the temporal characteristics of event relations and propose a method to correctly associate the detected events with individual subjects. The Dempster–Shafer (DS) theory of belief functions is used to infer events of interest from the results of our vision analytics and to measure conflicts occurring during the event association. Our system is evaluated against a number of videos that present passenger behaviours on a public transport platform namely buses at different levels of complexity. The experimental results demonstrate that by reasoning with spatio-temporal correlations, the proposed method achieves a satisfying performance when associating atomic events and recognising composite events involving multiple subjects in dynamic environments.