Hydrologic landscape regionalisation using deductive classification and random forests

Landscape classification and hydrological regionalisation studies are being increasingly used in ecohydrology to aid in the management and research of aquatic resources. We present a methodology for classifying hydrologic landscapes based on spatial environmental variables by employing non-parametric statistics and hybrid image classification. Our approach differed from previous classifications which have required the use of an a priori spatial unit (e.g. a catchment) which necessarily results in the loss of variability that is known to exist within those units. The use of a simple statistical approach to identify an appropriate number of classes eliminated the need for large amounts of post-hoc testing with different number of groups, or the selection and justification of an arbitrary number. Using statistical clustering, we identified 23 distinct groups within our training dataset. The use of a hybrid classification employing random forests extended this statistical clustering to an area of approximately 228,000 km2 of south-eastern Australia without the need to rely on catchments, landscape units or stream sections. This extension resulted in a highly accurate regionalisation at both 30-m and 2.5-km resolution, and a less-accurate 10-km classification that would be more appropriate for use at a continental scale. A smaller case study, of an area covering 27,000 km2, demonstrated that the method preserved the intra- and inter-catchment variability that is known to exist in local hydrology, based on previous research. Preliminary analysis linking the regionalisation to streamflow indices is promising suggesting that the method could be used to predict streamflow behaviour in ungauged catchments. Our work therefore simplifies current classification frameworks that are becoming more popular in ecohydrology, while better retaining small-scale variability in hydrology, thus enabling future attempts to explain and visualise broad-scale hydrologic trends at the scale of catchments and continents.

Minimising post-operative risk using a Post-Anaesthetic Care Tool (PACT): protocol for a prospective observational study and cost-effectiveness analysis

Introduction: While the risk of adverse events following surgery has been identified, the impact of nursing care on early detection of these events is not well established. A systematic review of the evidence and an expert consensus study in post-anaesthetic care identified essential criteria for nursing assessment of patient readiness for discharge from the Post-Anaesthetic Care Unit. These criteria were included in a new nursing assessment tool, the Post-Anaesthetic Care Tool (PACT), and incorporated into the post-anaesthetic documentation at a large health service. The aim of this study is to test the clinical reliability of the PACT and evaluate whether use of PACT will i) enhance the recognition and response to patients at risk of deterioration in PACU; ii) improve documentation for handover from PACU nurse to ward nurse; iii) result in improved patient outcomes; and iv) reduce health care costs.

Methods and analysis: A prospective, non-randomised, pre- and post-implementation design comparing: (i) patients (n=750) who have surgery prior to the implementation of the PACT and (ii) patients (n=750) who have surgery after PACT. The study will examine the use of the tool through the observation of patient care and nursing handover. Patient outcomes and cost effectiveness will be determined from health service data and medical record audit. Descriptive statistics will be used to describe the sample and compare the two patient groups (pre- and post-intervention). Differences in patient outcomes between the two groups will be compared using the Cochran-Mantel-Haenszel test and regression analyses and reported as odds ratios with the corresponding 95% confidence intervals.

Conclusion: This study will test the clinical reliability and cost-effectiveness of the PACT. It is hypothesised that the PACT will enable nurses to recognise and respond to patients at risk of deterioration, improve handover to ward nurses, improve patient outcomes, and reduce health care costs.

The effect of active video games by ethnicity, sex and fitness: subgroup analysis from a randomised controlled trial

BACKGROUND: The prevention and treatment of childhood obesity is a key public health challenge. However, certain groups within populations have markedly different risk profiles for obesity and related health behaviours. Well-designed subgroup analysis can identify potential differential effects of obesity interventions, which may be important for reducing health inequalities. The study aim was to evaluate the consistency of the effects of active video games across important subgroups in a randomised controlled trial (RCT).

FINDINGS: A two-arm, parallel RCT was conducted in overweight or obese children (n=322; aged 10-14 years) to determine the effect of active video games on body composition. Statistically significant overall treatment effects favouring the intervention group were found for body mass index, body mass index z-score and percentage body fat at 24 weeks. For these outcomes, pre-specified subgroup analyses were conducted among important baseline demographic (ethnicity, sex) and prognostic (cardiovascular fitness) groups. No statistically significant interaction effects were found between the treatment and subgroup terms in the main regression model (p=0.36 to 0.93), indicating a consistent treatment effect across these groups.

CONCLUSIONS: Preliminary evidence suggests an active video games intervention had a consistent positive effect on body composition among important subgroups. This may support the use of these games as a pragmatic public health intervention to displace sedentary behaviour with physical activity in young people.

Prespecified dose-response analysis for A Very Early Rehabilitation Trial (AVERT)

OBJECTIVE:
Our prespecified dose-response analyses of A Very Early Rehabilitation Trial (AVERT) aim to provide practical guidance for clinicians on the timing, frequency, and amount of mobilization following acute stroke.

METHODS:
Eligible patients were aged ≥18 years, had confirmed first (or recurrent) stroke, and were admitted to a stroke unit within 24 hours of stroke onset. Patients were randomized to receive very early and frequent mobilization, commencing within 24 hours, or usual care. We used regression analyses and Classification and Regression Trees (CART) to investigate the effect of timing and dose of mobilization on efficacy and safety outcomes, irrespective of assigned treatment group.

RESULTS:
A total of 2,104 patients were enrolled, of whom 2,083 (99.0%) were followed up at 3 months. We found a consistent pattern of improved odds of favorable outcome in efficacy and safety outcomes with increased daily frequency of out-of-bed sessions (odds ratio [OR] 1.13, 95% confidence interval [CI] 1.09 to 1.18, p < 0.001), keeping time to first mobilization and mobilization amount constant. Increased amount (minutes per day) of mobilization reduced the odds of a good outcome (OR 0.94, 95% CI 0.91 to 0.97, p < 0.001). Session frequency was the most important variable in the CART analysis, after prognostic variables age and baseline stroke severity.

CONCLUSION:
These data suggest that shorter, more frequent mobilization early after acute stroke is associated with greater odds of favorable outcome at 3 months when controlling for age and stroke severity.

CLASSIFICATION OF EVIDENCE:
This study provides Class III evidence that shorter, more frequent early mobilization improves the chance of regaining independence after stroke.

Comparison of soluble manganese(IV) and acidic potassium permanganate chemiluminescence detection using flow injection and sequential injection analysis for the determination of ascorbic acid in vitamin C tablets

The limits of detection (3s) for ascorbic acid were 5×10⁻⁸ M with acidic potassium permanganate using both flow injection analysis (FIA) and sequential injection analysis (SIA) whereas the soluble manganese(IV) afforded 1×10⁻⁸ M and 5×10⁻⁹ M for FIA and SIA, respectively. Determinations of ascorbic acid in Vitamin C tablets were achieved with minimal sample pretreatment using a standard additions calibration and gave good agreement with those of iodimetric titration.

Antecedents of recommending infrequently purchased services: a conceptualisation and an empirical analysis

This project aimed to conceptualise and analyse empirically the antecedents of word-of-mouth in the context of an infrequently purchased service (tourism special events). The relationships examined included those between involvement, past experience, overall satisfaction, interest in attending next time, likelihood of attending next time, and the likelihood of recommending to others that they attend the event. There was some support for the overall model, in that the regressing of likelihood of recommending on the other variables produced an equation containing measures of most of the key variables, viz., revisit intention, satisfaction, revisit interest, and involvement. However, involvement appeared to operate in the opposite direction to that hypothesised.

Fruit and vegetable consumption and stroke : meta-analysis of cohort studies

Background
Increased consumption of fruit and vegetables has been shown to be associated with a reduced risk of stroke in most epidemiological studies, although the extent of the association is uncertain. We quantitatively assessed the relation between fruit and vegetable intake and incidence of stroke in a meta-analysis of cohort studies.

Methods
We searched MEDLINE, EMBASE, the Cochrane Library, and bibliographies of retrieved articles. Studies were included if they reported relative risks and corresponding 95% CIs of stroke with respect to frequency of fruit and vegetable intake.

Findings
Eight studies, consisting of nine independent cohorts, met the inclusion criteria. These groups included 257 551 individuals (4917 stroke events) with an average follow-up of 13 years. Compared with individuals who had less than three servings of fruit and vegetables per day, the pooled relative risk of stroke was 0·89 (95% CI 0·83–0·97) for those with three to five servings per day, and 0·74 (0·69–0·79) for those with more than five servings per day. Subgroup analyses showed that fruit and vegetables had a significant protective effect on both ischaemic and haemorrhagic stroke.

Interpretation
Increased fruit and vegetable intake in the range commonly consumed is associated with a reduced risk of stroke. Our results provide strong support for the recommendations to consume more than five servings of fruit and vegetables per day, which is likely to cause a major reduction in strokes.

Experimental investigation and finite element analysis for the study of residual stresses in roller burnished components

Burnishing is a surface modification process, which involves plastic deformation of the material at the surface of the component due to the application a highly polished and hard roller, under pressure. This results in the improvement of the surface finish of the component and induces residual compressive stresses on the surface of the component. The present work deals with the optimization of the burnishing force for the best surface finish, at constant speed and feed, for Aluminium and Mild steel workpieces. A 3dimensional finite element model is proposed for the simulation of the burnishing process, and the analysis is carried out at the optimum force determined experimentally. The induced compressive stress in the components is determined from the finite element analysis and this value is then compared with the results obtained from X-ray diffraction technique.

A neural networks learning algorithm for minor component analysis and its convergence analysis

The eigenvector associated with the smallest eigenvalue of the autocorrelation matrix of input signals is called minor component. Minor component analysis (MCA) is a statistical approach for extracting minor component from input signals and has been applied in many fields of signal processing and data analysis. In this letter, we propose a neural networks learning algorithm for estimating adaptively minor component from input signals. Dynamics of the proposed algorithm are analyzed via a deterministic discrete time (DDT) method. Some sufficient conditions are obtained to guarantee convergence of the proposed algorithm.

Using supervised and unsupervised techniques to determine groups of patients with different doctor-patient stability

Decision trees and self organising feature maps (SOFM) are frequently used to identify groups. This research aims to compare the similarities between any groupings found between supervised (Classification and Regression Trees - CART) and unsupervised classification (SOFM), and to identify insights into factors associated with doctor-patient stability. Although CART and SOFM uses different learning paradigms to produce groupings, both methods came up with many similar groupings. Both techniques showed that self perceived health and age are important indicators of stability. In addition, this study has indicated profiles of patients that are at risk which might be interesting to general practitioners.

Determinants of female fertility in Taiwan, 1966–2001 : empirical evidence from cointegration and variance decomposition analysis

This study investigates the determinants of the fertility rate in Taiwan over the period 1966–2001. Consistent with theory, the key explanatory variables in Taiwan's fertility model are real income, infant mortality rate, female education and female labor force participation rate. The test for cointegration is based on the recently developed bounds testing procedure while the long-run and short-run elasticities are based on the autoregressive distributed lag model. Among our key results, female education and female labor force participation rate are found to be the key determinants of fertility in Taiwan in the long run. The variance decom-position analysis indicates that in the long run approximately 45percent of the variation in fertility is explained by the combined impact of female labor force participation, mortality and income, implying that socioeconomic development played an important role in the fertility transition in Taiwan. This result is consistent with the traditional structural hypothesis.