The structural drivers of homelessness in Australia 2001-11

This second and final report, from a project addressing this broad question, builds on our earlier analysis of the spatial dynamics of homelessness from 2001 to 2011. It examines the role of housing and labour markets, household income, income inequality, climate and demographic profiles in shaping the spatial distribution of homelessness across Australia. Interest in the role of structural versus individual level drivers of homelessness has been longstanding in the homelessness research and policy fields. Some have argued that homelessness is caused by structural factors such as weak labour markets and tight housing markets (Neale 1997), while others have emphasised individual factors such as mental illness, a history of contact with institutions, or poor decision-making as the key causes (Neale 1997). More recently a loose consensus has emerged where homelessness is understood to be caused by the interaction of individual risk factors and adverse structural conditions (Fitzpatrick & Christian 2006; Lee et al. 2010; Pleace 2000; O'Flaherty 2004)

A study protocol for a randomised crossover study evaluating the effect of diets differing in carbohydrate quality on ileal content and appetite regulation in healthy humans

A major component of the digesta reaching the colon from the distal ileum is carbohydrate. This carbohydrate is subject to microbial fermentation and can radically change bacterial populations in the colon and the metabolites they produce, particularly short-chain fatty acids (SCFA). However, very little is currently known about the forms and levels of carbohydrate in the ileum and the composition of the ileal microbiota in humans. Most of our current understanding of carbohydrate that is not absorbed by the small intestine comes from ileostomy models, which may not reflect the physiology of an intact gastrointestinal tract. We will investigate how ileal content changes depending on diet using a randomised crossover study in healthy humans. Participants will be inpatients at the research facility for three separate 4-day visits. During each visit, participants will consume one of three diets, which differ in carbohydrate quality: 1) low-fibre refined diet; 2) high-fibre diet with intact cellular structures; 3) high-fibre diet where the cellular structures have been disrupted (e.g. milling, blending). On day 1, a nasoenteric tube will be placed into the distal ileum and its position confirmed under fluoroscopy. Ileal samples will be collected via the nasoenteric tube and metabolically profiled, which will determine the amount and type of carbohydrate present, and the composition of the ileal microbiota will be measured. Blood samples will be collected to assess circulating hormones and metabolites. Stool samples will be collected to assess faecal microbiota composition. Subjective appetite measures will be collected using visual analogue scales. Breath hydrogen will be measured in real-time as a marker of intestinal fermentation. Finally, an continuous fermentation model will be inoculated with ileal fluid in order to understand the shift in microbial composition and SCFA produced in the colon following the different diets. ISRCTN11327221. [Abstract copyright: Copyright: © 2019 Byrne CS et al.

Spatiotemporal slope stability analytics for failure estimation (SSSAFE): linking radar data to the fundamental dynamics of granular failure

Impending catastrophic failure of granular earth slopes manifests distinct kinematic patterns in space and time. While risk assessments of slope failure hazards have routinely relied on the monitoring of ground motion, such precursory failure patterns remain poorly understood. A key challenge is the multiplicity of spatiotemporal scales and dynamical regimes. In particular, there exist a precursory failure regime where two mesoscale mechanisms coevolve, namely, the preferred transmission paths for force and damage. Despite extensive studies, a formulation which can address their coevolution not just in laboratory tests but also in large, uncontrolled field environments has proved elusive. Here we address this problem by developing a slope stability analytics framework which uses network flow theory and mesoscience to model this coevolution and predict emergent kinematic clusters solely from surface ground motion data. We test this framework on four data sets: one at the laboratory scale using individual grain displacement data; three at the field scale using line-of-sight displacement of a slope surface, from ground-based radar in two mines and from space-borne radar for the 2017 Xinmo landslide. The dynamics of the kinematic clusters deliver an early prediction of the geometry, location and time of failure

Effect of supervised aerobic exercise rehabilitation on physical fitness and quality-of-life in survivors of critical illness: an exploratory minimized controlled trial (PIX study)

BACKGROUND: Evidence is limited for the effectiveness of interventions for survivors of critical illness after hospital discharge. We explored the effect of an 8-week hospital-based exercise-training programme on physical fitness and quality-of-life. METHODS: In a parallel-group minimized controlled trial, patients were recruited before hospital discharge or in the intensive care follow-up clinic and enrolled 8–16 weeks after discharge. Each week, the intervention comprised two sessions of physiotherapist-led cycle ergometer exercise (30 min, moderate intensity) plus one equivalent unsupervised exercise session. The control group received usual care. The primary outcomes were the anaerobic threshold (in ml O(2) kg(−1) min(−1)) and physical function and mental health (SF-36 questionnaire v.2), measured at Weeks 9 (primary time point) and 26. Outcome assessors were blinded to group assignment. RESULTS: Thirty patients were allocated to the control and 29 to the intervention. For the anaerobic threshold outcome at Week 9, data were available for 17 control vs 13 intervention participants. There was a small benefit (vs control) for the anaerobic threshold of 1.8 (95% confidence interval, 0.4–3.2) ml O(2) kg(−1) min(−1). This advantage was not sustained at Week 26. There was evidence for a possible beneficial effect of the intervention on self-reported physical function at Week 9 (3.4; −1.4 to 8.2 units) and on mental health at Week 26 (4.4; −2.4 to 11.2 units). These potential benefits should be examined robustly in any subsequent definitive trial. CONCLUSIONS: The intervention appeared to accelerate the natural recovery process and seems feasible, but the fitness benefit was only short term. CLINICAL TRIAL REGISTRATION: Current Controlled Trials ISRCTN65176374 (http://www.controlled-trials.com/ISRCTN65176374)