A protocol for a discrete choice experiment: understanding preferences of patients with cancer towards their cancer care across metropolitan and rural regions in Australia.

Medical decision-making in oncology is a complicated process and to date there are few studies examining how patients with cancer make choices with respect to different features of their care. It is also unknown whether patient choices vary by geographical location and how location could account for observed rural and metropolitan cancer differences. This paper describes an ongoing study that aims to (1) examine patient and healthcare-related factors that influence choices of patients with cancer; (2) measure and quantify preferences of patients with cancer towards cancer care using a discrete choice experiment (DCE) and (3) explore preference heterogeneity between metropolitan and rural locations.

H∞ observer-based control for discrete-time one-sided Lipschitz systems with unknown inputs

This paper investigates the problem of robust observer-based stabilization for a class of one-sided nonlinear discrete-time systems subjected to unknown inputs. We propose a simple simultaneous state and input estimator. A nonlinear controller is then proposed to compensate for the effects of unknown inputs and to ensure asymptotic stability in a closed loop. Several mathematical artifacts are used to deduce stability conditions expressed in terms of linear matrix inequalities. To show high performances of the proposed technique, a relevant example is provided with comparisons to recent results.

Pseudoconvex proximal splitting for L∞problems in multiview geometry

In this paper we study optimization methods for minimizing large-scale pseudoconvex L∞problems in multiview geometry. We present a novel algorithm for solving this class of problem based on proximal splitting methods. We provide a brief derivation of the proposed method along with a general convergence analysis. The resulting meta-algorithm requires very little effort in terms of implementation and instead makes use of existing advanced solvers for non-linear optimization. Preliminary experiments on a number of real image datasets indicate that the proposed method experimentally matches or outperforms current state-of-the-art solvers for this class of problems.

Paradox lost: variable colour-pattern geometry is associated with differences in movement in aposematic frogs

Aposematic signal variation is a paradox: predators are better at learning and retaining the association between conspicuousness and unprofitability when signal variation is low. Movement patterns and variable colour patterns are linked in non-aposematic species: striped patterns generate illusions of altered speed and direction when moving linearly, affecting predators' tracking ability; blotched patterns benefit instead from unpredictable pauses and random movement. We tested whether the extensive colour-pattern variation in an aposematic frog is linked to movement, and found that individuals moving directionally and faster have more elongated patterns than individuals moving randomly and slowly. This may help explain the paradox of polymorphic aposematism: variable warning signals may reduce protection, but predator defence might still be effective if specific behaviours are tuned to specific signals. The interacting effects of behavioural and morphological traits may be a key to the evolution of warning signals. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Geometry and geography

This is an extract from an ongoing project: a ficitionalised memoir in poetic fragments connecting personal trauma with the fall-out from the scientific research in the Cold War. It is influenced by Michel Blanchot's The Writing of the Disaster and an ongoing meditation on the poetics of Marguerite Duras and the poetics of awkwardness.

A dynamic time warped clustering technique for discrete event simulation-based system analysis

Abstract This paper introduces a novel approach for discrete event simulation output analysis. The approach combines dynamic time warping and clustering to enable the identification of system behaviours contributing to overall system performance, by linking the clustering cases to specific causal events within the system. Simulation model event logs have been analysed to group entity flows based on the path taken and travel time through the system. The proposed approach is investigated for a discrete event simulation of an international airport baggage handling system. Results show that the method is able to automatically identify key factors that influence the overall dwell time of system entities, such as bags that fail primary screening. The novel analysis methodology provides insight into system performance, beyond that achievable through traditional analysis techniques. This technique also has potential application to agent-based modelling paradigms and also business event logs traditionally studied using process mining techniques.

Discrete Wirtinger-based inequality and its application

In this paper, we derive a new inequality, which encompasses the discrete Jensen inequality. The new inequality is applied to analyze stability of linear discrete systems with an interval time-varying delay and a less conservative stability condition is obtained. Two numerical examples are given to show the effectiveness of the obtained stability condition.

Greater association of peak neuromuscular performance with cortical bone geometry, bone mass and bone strength than bone density : a study in 417 older women

BACKGROUND: We evaluated which aspects of neuromuscular performance are associated with bone mass, density, strength and geometry. METHODS: 417 women aged 60-94years were examined. Countermovement jump, sit-to-stand test, grip strength, forearm and calf muscle cross-sectional area, areal bone mineral content and density (aBMC and aBMD) at the hip and lumbar spine via dual X-ray absorptiometry, and measures of volumetric vBMC and vBMD, bone geometry and section modulus at 4% and 66% of radius length and 4%, 38% and 66% of tibia length via peripheral quantitative computed tomography were performed. The first principal component of the neuromuscular variables was calculated to generate a summary neuromuscular variable. Percentage of total variance in bone parameters explained by the neuromuscular parameters was calculated. Step-wise regression was also performed. RESULTS: At all pQCT bone sites (radius, ulna, tibia, fibula), a greater percentage of total variance in measures of bone mass, cortical geometry and/or bone strength was explained by peak neuromuscular performance than for vBMD. Sit-to-stand performance did not relate strongly to bone parameters. No obvious differential in the explanatory power of neuromuscular performance was seen for DXA aBMC versus aBMD. In step-wise regression, bone mass, cortical morphology, and/or strength remained significant in relation to the first principal component of the neuromuscular variables. In no case was vBMD positively related to neuromuscular performance in the final step-wise regression models. CONCLUSION: Peak neuromuscular performance has a stronger relationship with leg and forearm bone mass and cortical geometry as well as proximal forearm section modulus than with vBMD.

Discrete inequalities based on multiple auxiliary functions and their applications to stability analysis of time-delay systems

Abstract
This paper presents new discrete inequalities for single summation and double summation. These inequalities are based on multiple auxiliary functions and include the Jensen discrete inequality and the discrete Wirtinger-based inequality as special cases. An application of these discrete inequalities to analyse stability of linear discrete systems with an interval time-varying delay is studied and a less conservative stability condition is obtained. Three numerical examples are given to show the effectiveness of the obtained stability condition.

Patient and nurse preferences for nurse handover-using preferences to inform policy: a discrete choice experiment protocol

INTRODUCTION: Nursing bedside handover in hospital has been identified as an opportunity to involve patients and promote patient-centred care. It is important to consider the preferences of both patients and nurses when implementing bedside handover to maximise the successful uptake of this policy. We outline a study which aims to (1) identify, compare and contrast the preferences for various aspects of handover common to nurses and patients while accounting for other factors, such as the time constraints of nurses that may influence these preferences.; (2) identify opportunities for nurses to better involve patients in bedside handover and (3) identify patient and nurse preferences that may challenge the full implementation of bedside handover in the acute medical setting. METHODS AND ANALYSIS: We outline the protocol for a discrete choice experiment (DCE) which uses a survey design common to both patients and nurses. We describe the qualitative and pilot work undertaken to design the DCE. We use a D-efficient design which is informed by prior coefficients collected during the pilot phase. We also discuss the face-to-face administration of this survey in a population of acutely unwell, hospitalised patients and describe how data collection challenges have been informed by our pilot phase. Mixed multinomial logit regression analysis will be used to estimate the final results. ETHICS AND DISSEMINATION: This study has been approved by a university ethics committee as well as two participating hospital ethics committees. Results will be used within a knowledge translation framework to inform any strategies that can be used by nursing staff to improve the uptake of bedside handover. Results will also be disseminated via peer-reviewed journal articles and will be presented at national and international conferences.

A convex geometry-based blind source separation method for separating nonnegative sources

This paper presents a convex geometry (CG)-based method for blind separation of nonnegative sources. First, the unaccessible source matrix is normalized to be column-sum-to-one by mapping the available observation matrix. Then, its zero-samples are found by searching the facets of the convex hull spanned by the mapped observations. Considering these zero-samples, a quadratic cost function with respect to each row of the unmixing matrix, together with a linear constraint in relation to the involved variables, is proposed. Upon which, an algorithm is presented to estimate the unmixing matrix by solving a classical convex optimization problem. Unlike the traditional blind source separation (BSS) methods, the CG-based method does not require the independence assumption, nor the uncorrelation assumption. Compared with the BSS methods that are specifically designed to distinguish between nonnegative sources, the proposed method requires a weaker sparsity condition. Provided simulation results illustrate the performance of our method.