The heat is on: climate change, extreme heat and bushfires in WA

Climate change is increasing the intensity and frequency of heatwaves in Western Australia and driving up the likelihood of very high fire danger weather. Western Australia is experiencing a long-term increase in average temperatures and in 2014 the state recorded its highest ever annual average maximum temperature. The number of heatwave days in Perth has increased by 50% since 1950. Nine of Western Australia’s hottest Januarys on record have occurred in the last 10 years. The number of days per year with severe fire danger weather is projected to almost double in south west Western Australia by 2090 if global carbon emissions are not drastically reduced. Recent fires in Western Australia have been influenced by record hot dry conditions. The long-term trend to hotter weather in Western Australia has worsened fire weather and contributed to an increase in the frequency and severity of bushfires. The concept of a normal bushfire season is rapidly changing as bushfires increase in number, burn for longer and affect larger areas of land. By 2030, the number of professional firefighters in WA will need to more than double to meet the increasing risk of bushfires. 3. The economic, social and environmental costs of increased extreme heat and bushfire activity is likely to be immense. In Perth, from 1994-2006, there were over 20 heat attributable deaths per year. If average maximum temperatures were 2°C warmer, this number would almost double to 40 deaths. Some of Western Australia’s most fire-prone regions may become unlivable as the risks to lives and property caused by bushfires continue to increase. Without effective action on climate change, there will be 20 times the number of dangerous days for outdoor workers by 2070, reducing productivity. 4. Tackling climate change is critical to protecting Western Australia’s prosperity. As a nation we must join the global effort to substantially reduce emissions and rapidly move away from fossil fuels to renewable energy if we are to limit the severity of extreme heat and bushfires both in Western Australia and nationally

Bad Citrus: Reducing Adversarial Costs with Model Distances

Recent work by Jia et al., showed the possibility of effectively computing pairwise model distances in weight space, using a model explanation technique known as LIME. This method requires query-only access to the two models under examination. We argue this insight can be leveraged by an adversary to reduce the net cost (number of queries) of launching an evasion campaign against a deployed model. We show that there is a strong negative correlation between the success rate of adversarial transfer and the distance between the victim model and the surrogate used to generate the evasive samples. Thus, we propose and evaluate a method to reduce adversarial costs by finding the closest surrogate model for adversarial transfer

The Mass Assembly of Fossil Groups of Galaxies in the Millennium Simulation

The evolution of present-day fossil galaxy groups is studied in the Millennium Simulation. Using the corresponding Millennium gas simulation and semi-analytic galaxy catalogues, we select fossil groups at redshift zero according to the conventional observational criteria, and trace the haloes corresponding to these groups backwards in time, extracting the associated dark matter, gas and galaxy properties. The space density of the fossils from this study is remarkably close to the observed estimates and various possibilities for the remaining discrepancy are discussed. The fraction of X-ray bright systems which are fossils appears to be in reasonable agreement with observation, and the simulations predict that fossil systems will be found in significant numbers (3-4% of the population) even in quite rich clusters. We find that fossils assemble a higher fraction of their mass at high redshift, compared to non-fossil groups, with the ratio of the currently assembled halo mass to final mass, at any epoch, being about 10 to 20% higher for fossils. This supports the paradigm whereby fossils represent undisturbed, early-forming systems in which large galaxies have merged to form a single dominant elliptical.Comment: 11 pages, 8 figures, submitted to MNRA

Search Engine for Antimicrobial Resistance: A Cloud Compatible Pipeline and Web Interface for Rapidly Detecting Antimicrobial Resistance Genes Directly from Sequence Data.

BACKGROUND: Antimicrobial resistance remains a growing and significant concern in human and veterinary medicine. Current laboratory methods for the detection and surveillance of antimicrobial resistant bacteria are limited in their effectiveness and scope. With the rapidly developing field of whole genome sequencing beginning to be utilised in clinical practice, the ability to interrogate sequencing data quickly and easily for the presence of antimicrobial resistance genes will become increasingly important and useful for informing clinical decisions. Additionally, use of such tools will provide insight into the dynamics of antimicrobial resistance genes in metagenomic samples such as those used in environmental monitoring. RESULTS: Here we present the Search Engine for Antimicrobial Resistance (SEAR), a pipeline and web interface for detection of horizontally acquired antimicrobial resistance genes in raw sequencing data. The pipeline provides gene information, abundance estimation and the reconstructed sequence of antimicrobial resistance genes; it also provides web links to additional information on each gene. The pipeline utilises clustering and read mapping to annotate full-length genes relative to a user-defined database. It also uses local alignment of annotated genes to a range of online databases to provide additional information. We demonstrate SEAR's application in the detection and abundance estimation of antimicrobial resistance genes in two novel environmental metagenomes, 32 human faecal microbiome datasets and 126 clinical isolates of Shigella sonnei. CONCLUSIONS: We have developed a pipeline that contributes to the improved capacity for antimicrobial resistance detection afforded by next generation sequencing technologies, allowing for rapid detection of antimicrobial resistance genes directly from sequencing data. SEAR uses raw sequencing data via an intuitive interface so can be run rapidly without requiring advanced bioinformatic skills or resources. Finally, we show that SEAR is effective in detecting antimicrobial resistance genes in metagenomic and isolate sequencing data from both environmental metagenomes and sequencing data from clinical isolates.This research was funded by GlaxoSmithKline, the Centre for Environment, Fisheries and Aquaculture Science and the Biotechnology and Biological Sciences Research Council under an industrial CASE studentship. The funder Centre for Environment, Fisheries and Aquaculture Science provided support in the form of salaries, research materials and facilities for authors DVJ and CBA, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The funder GlaxoSmithKline provided support in the form of salaries for author JR, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.This is the final version. It was first published by PLOS at http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0133492

Comparative metagenomics reveals a diverse range of antimicrobial resistance genes in effluents entering a river catchment.

The aquatic environment has been implicated as a reservoir for antimicrobial resistance genes (ARGs). In order to identify sources that are contributing to these gene reservoirs, it is crucial to assess effluents that are entering the aquatic environment. Here we describe a metagenomic assessment for two types of effluent entering a river catchment. We investigated the diversity and abundance of resistance genes, mobile genetic elements (MGEs) and pathogenic bacteria. Findings were normalised to a background sample of river source water. Our results show that effluent contributed an array of genes to the river catchment, the most abundant being tetracycline resistance genes tetC and tetW from farm effluents and the sulfonamide resistance gene sul2 from wastewater treatment plant (WWTP) effluents. In nine separate samples taken across 3 years, we found 53 different genes conferring resistance to seven classes of antimicrobial. Compared to the background sample taken up river from effluent entry, the average abundance of genes was three times greater in the farm effluent and two times greater in the WWTP effluent. We conclude that effluents disperse ARGs, MGEs and pathogenic bacteria within a river catchment, thereby contributing to environmental reservoirs of ARGs.This research was funded by the Centre for Environment, Fisheries and Aquaculture Science, GlaxoSmithKline and the Biotechnology and Biological Sciences Research Council. Metagenomic sequencing was performed by the Sequencing Service and Wellcome Trust Biomedical Informatics Hub, Exeter (UK).This is the author accepted manuscript. It is currently under an indefinite embargo pending publication by IWA Publishing

The extragalactic sub-mm population: predictions for the SCUBA Half-Degree Extragalactic Survey (SHADES)

We present predictions for the angular correlation function and redshift distribution for SHADES, the SCUBA HAlf-Degree Extragalactic Survey, which will yield a sample of around 300 sub-mm sources in the 850 micron waveband in two separate fields. Complete and unbiased photometric redshift information on these sub-mm sources will be derived by combining the SCUBA data with i) deep radio imaging already obtained with the VLA, ii) guaranteed-time Spitzer data at mid-infrared wavelengths, and iii) far-infrared maps to be produced by BLAST, the Balloon-borne Large-Aperture Sub-millimeter Telescope. Predictions for the redshift distribution and clustering properties of the final anticipated SHADES sample have been computed for a wide variety of models, each constrained to fit the observed number counts. Since we are dealing with around 150 sources per field, we use the sky-averaged angular correlation function to produce a more robust fit of a power-law shape w(theta)=(theta/A)^{-delta} to the model data. Comparing the predicted distributions of redshift and of the clustering amplitude A and slope delta, we find that models can be constrained from the combined SHADES data with the expected photometric redshift information.Comment: updated and improved version, accepted for publication in the MNRA

Potential of Australian Bermudagrasses (\u3cem\u3eCynodon\u3c/em\u3e spp.) for Pasture in Subtropical Australia

In Australia, little work has been carried out on the improvement of tropical or subtropical pastures in recent years. There seems to be an increasing demand for pastures that can withstand heavy grazing, while producing high yields of high quality forage in the humid subtropical regions of Australia. Most graziers, who live in these areas, have small acreages, which they graze intensively. Cynodon spp. represent a potential source of grasses with these attributes. This study will evaluate the pasture potential of a large number of bermudagrass (Cynodon spp.) ecotypes collected from across Australia

A multisite longitudinal evaluation of patient characteristics associated with a poor response to non-surgical multidisciplinary management of low back pain in an advanced practice physiotherapist-led tertiary service

Background: Non-surgical multidisciplinary management is often the first pathway of care for patients with chronic low back pain (LBP). This study explores if patient characteristics recorded at the initial service examination have an association with a poor response to this pathway of care in an advanced practice physiotherapist-led tertiary service. Methods: Two hundred and forty nine patients undergoing non-surgical multidisciplinary management for their LBP across 8 tertiary public hospitals in Queensland, Australia participated in this prospective longitudinal study. Generalised linear models (logistic family) examined the relationship between patient characteristics and a poor response at 6 months follow-up using a Global Rating of Change measure. Results: Overall 79 of the 178 (44%) patients completing the Global Rating of Change measure (28.5% loss to follow-up) reported a poor outcome. Patient characteristics retained in the final model associated with a poor response included lower Formal Education Level (ie did not complete school) (Odds Ratio (OR (95% confidence interval)) (2.67 (1.17–6.09), p = 0.02) and higher self-reported back disability (measured with the Oswestry Disability Index) (OR 1.33 (1.01–1.77) per 10/100 point score increase, p = 0.046). Conclusions: A low level of formal education and high level of self-reported back disability may be associated with a poor response to non-surgical multidisciplinary management of LBP in tertiary care. Patients with these characteristics may need greater assistance with regard to their comprehension of health information, and judicious monitoring of their response to facilitate timely alternative care if no benefits are attained.</p

Cosmic CARNage II: the evolution of the galaxy stellar mass function in observations and galaxy formation models

We present a comparison of the observed evolving galaxy stellar mass functions with the predictions of eight semi-analytic models and one halo occupation distribution model. While most models are able to fit the data at low redshift, some of them struggle to simultaneously fit observations at high redshift. We separate the galaxies into 'passive' and 'star-forming' classes and find that several of the models produce too many low-mass star-forming galaxies at high redshift compared to observations, in some cases by nearly a factor of 10 in the redshift range 2.5 < z < 3.0. We also find important differences in the implied mass of the dark matter haloes the galaxies inhabit, by comparing with halo masses inferred from observations. Galaxies at high redshift in the models are in lower mass haloes than suggested by observations, and the star formation efficiency in low-mass haloes is higher than observed. We conclude that many of the models require a physical prescription that acts to dissociate the growth of low-mass galaxies from the growth of their dark matter haloes at high redshift.Facultad de Ciencias Astronómicas y GeofísicasInstituto de Astrofísica de La Plat