Severity of Complications after Locking Plate Osteosynthesis in Distal Femur Fractures.

: Locked plating for distal femur fractures is widely recommended and used. We systematically reviewed clinical studies assessing the benefits and harms of fracture fixation with locked plates in AO/OTA Type 32 and 33 femur fractures. : A comprehensive literature search of PubMed, Embase, Cinahl, Web of Science, and the Cochrane Database was performed.

Innovative approaches in soil carbon sequestration modelling for better prediction with limited data.

Soil carbon accounting and prediction play a key role in building decision support systems for land managers selling carbon credits, in the spirit of the Paris and Kyoto protocol agreements. Land managers typically rely on computationally complex models fit using sparse datasets to make these accounts and predictions. The model complexity and sparsity of the data can lead to over-fitting, leading to inaccurate results when making predictions with new data.

Person-to-person opinion dynamics: An empirical study using an online game.

A model needs to make verifiable predictions to have any scientific value. In opinion dynamics, the study of how individuals exchange opinions with one another, there are many theoretical models which attempt to model opinion exchange, one of which is the Martins model, which differs from other models by using a parameter that is easier to control for in an experiment. In this paper, we have designed an experiment to verify the Martins model and contribute to the experimental design in opinion dynamic with our novel method.

Mathematical measures of societal polarisation.

In opinion dynamics, as in general usage, polarisation is subjective. To understand polarisation, we need to develop more precise methods to measure the agreement in society. This paper presents four mathematical measures of polarisation derived from graph and network representations of societies and information-theoretic divergences or distance metrics.

A data fusion approach to the estimation of temporary populations: An application to Australia.

This study establishes a new method for estimating the monthly Average Population Present (APP) in Australian regions. Conventional population statistics, which enumerate people where they usually live, ignore the significant spatial mobility driving short term shifts in population numbers. Estimates of the temporary or ambient population of a region have several important applications including the provision of goods and services, emergency preparedness and serve as more appropriate denominators for a range of social statistics.

Retrospective identification of latent subgroups of emergency department patients: A machine learning approach.

Objective: This research aims to (i) identify latent subgroups of ED presentations in Australian public EDs using a data-driven approach and (ii) compare clinical, socio-demographic and time-related characteristics of ED presentations broadly using the subgroups.

Methods: We examined presentations to four public hospital EDs in Queensland from 2009 to 2014. An unsupervised machine learning algorithm, Clustering Large Applications, was used to cluster ED presentations.

Identifying and quantifying general practice-type emergency department presentations.

Objective: This research aims to (i) identify general practice-type (GP-type) presentations to EDs in South-East Queensland, Australia and (ii) compare and quantify the clinical, socio-demographic and time-varying characteristics between GP-type and non-GP-type presentations.

Methods: Data were collected from presentations to four EDs in Queensland from 2009 to 2014. A modified version of the Australasian College for Emergency Medicine (ACEM) method for identifying GP-type ED presentations was used.

Climate variability and dengue fever in Makassar, Indonesia: Bayesian spatio-temporal modelling.

A range of Bayesian models have been used to describe spatial and temporal patterns of disease in areal unit data. In this study, we applied two Bayesian spatio-temporal conditional autoregressive (ST CAR) models, one of which allows discontinuities in risk between neighbouring areas (creating 'groups'), to examine dengue fever patterns. Data on annual (2002-2017) and monthly (January 2013 - December 2017) dengue cases and climatic factors over 14 geographic areas were obtained for Makassar, Indonesia.

Forecasting daily counts of patient presentations in Australian emergency departments using statistical models with time-varying predictors.

Objective: This research aimed to (i) assess the effects of time-varying predictors (day of the week, month, year, holiday, temperature) on daily ED presentations and (ii) compare the accuracy of five methods for forecasting ED presentations, including four statistical methods and a machine learning approach.

Methods: Predictors of ED presentations were assessed using generalised additive models (GAMs), generalised linear models, multiple linear regression models, seasonal autoregressive integrated moving average models and random forest. The accuracy of short-term (14 days), mid-term (30 days) and long-term (365 days) forecasts were compared using two measures of forecasting error.

Bayesian Spatial Survival Models for Hospitalisation of Dengue: A Case Study of Wahidin Hospital in Makassar, Indonesia.

Spatial models are becoming more popular in time-to-event data analysis. Commonly, the intrinsic conditional autoregressive prior is placed on an area level frailty term to allow for correlation between areas. We considered a range of Bayesian Weibull and Cox semiparametric spatial models to describe a dataset on hospitalisation of dengue.

Holocene Demographic Changes and the Emergence of Complex Societies in Prehistoric Australia.

A continental-scale model of Holocene Australian hunter-gatherer demography and mobility is generated using radiocarbon data and geospatial techniques. Results show a delayed expansion and settlement of much of Australia following the termination of the late Pleistocene until after 9,000 years ago (or 9ka). The onset of the Holocene climatic optimum (9-6ka) coincides with rapid expansion, growth and establishment of regional populations across ~75% of Australia, including much of the arid zone.

Burglar Target Selection: A Cross-national Comparison.

Objectives: This study builds on research undertaken by Bernasco and Nieuwbeerta and explores the generalizability of a theoretically derived offender target selection model in three cross-national study regions.

Methods: Taking a discrete spatial choice approach, we estimate the impact of both environment- and offender-level factors on residential burglary placement in the Netherlands, the United Kingdom, and Australia. Combining cleared burglary data from all study regions in a single statistical model, we make statistical comparisons between environments.

Nonresponse bias in randomized controlled experiments in criminology: Putting the Queensland Community Engagement Trial (QCET) under a microscope.

Objectives: The goal of this article is to examine whether or not the results of the Queensland Community Engagement Trial (QCET)-a randomized controlled trial that tested the impact of procedural justice policing on citizen attitudes toward police-were affected by different types of nonresponse bias.

Method: We use two methods (Cochrane and Elffers methods) to explore nonresponse bias: First, we assess the impact of the low response rate by examining the effects of nonresponse group differences between the experimental and control conditions and pooled variance under different scenarios. Second, we assess the degree to which item response rates are influenced by the control and experimental conditions.

A stochastic neighborhood conditional autoregressive model for spatial data.

A spatial process observed over a lattice or a set of irregular regions is usually modeled using a conditionally autoregressive (CAR) model. The neighborhoods within a CAR model are generally formed deterministically using the inter-distances or boundaries between the regions. An extension of CAR model is proposed in this article where the selection of the neighborhood depends on unknown parameter(s).