Bayesian atmospheric tomography for detection and quantification of methane emissions : application to data from the 2015 Ginninderra release experiment

Detection and quantification of greenhouse-gas emissions is important for both compliance and environment conservation. However, despite several decades of active research, it remains predominantly an open problem, largely due to model errors and assumptions that appear at each stage of the inversion processing chain. In 2015, a controlled-release experiment headed by Geoscience Australia was carried out at the Ginninderra Controlled Release Facility, and a variety of instruments and methods were employed for quantifying the release rates of methane and carbon dioxide from a point source. This paper proposes a fully Bayesian approach to atmospheric tomography for inferring the methane emission rate of this point source using data collected during the experiment from both point-and path-sampling instruments. The Bayesian framework is designed to account for uncertainty in the parameterisations of measurements, the meteorological data, and the atmospheric model itself when performing inversion using Markov chain Monte Carlo (MCMC). We apply our framework to all instrument groups using measurements from two release-rate periods. We show that the inversion framework is robust to instrument type and meteorological conditions. From all the inversions we conducted across the different instrument groups and release-rate periods, our worst-case median emission rate estimate was within 36% of the true emission rate. Further, in the worst case, the closest limit of the 95% credible interval to the true emission rate was within 11% of this true value

Algebraic double cut and join : a group-theoretic approach to the operator on multichromosomal genomes

Establishing a distance between genomes is a significant problem in computational genomics, because its solution can be used to establish evolutionary relationships including phylogeny. The “double cut and join” (DCJ) model of chromosomal rearrangement proposed by Yancopoulos et al. (Bioinformatics 21:3340–3346, 2005) has received attention as it can model inversions, translocations, fusion and fission on a multichromosomal genome that may contain both linear and circular chromosomes. In this paper, we realize the DCJ operator as a group action on the space of multichromosomal genomes. We study this group action, deriving some properties of the group and finding group-theoretic analogues for the key results in the DCJ theory

MERCAT : visualising molecular epidemiology data combining genetic markers and drug resistance profiles

Molecular epidemiology uses genetic information from bacterial isolates to shed light on the population structure and dynamics of pathogens. Bacterial pathogens can now be studied by whole genome sequencing, but for some well-studied pathogens such as Mycobacterium tuberculosis a wealth of information is also available from other sources such as spoligotyping and multi-locus variable-number-tandem-repeats (VNTR). Isolates are also frequently tested for susceptibility to antibiotics. Methods of analysis are available for each type of data but it would be informative to combine multiple sources of information into a single analysis or visualisation. Here, we propose and implement a simple way to visualise genotypes along with drug resistance profiles for multiple drugs. We also present a way to combine information from different markers to aid in visualising relationships among isolates. These methods help to reveal the origins and spread of multi-drug resistant lineages of pathogens. We introduce a new computational package, MERCAT (Molecular Epidemiology Researcher's Collection of Analytical Tools), for analysing genotypic data from bacterial isolates. The software is available as an open source package in the statistical language R with a user-friendly interface using R Shiny. Although we focus on tuberculosis and the major molecular markers used to understand tuberculosis transmission – multilocus VNTR-typing (MLVA or MIRU) and spoligotyping – the methods and tools can be applied to other bacteria and can be easily tailored to other genetic markers such as SNP data from whole genome sequencing

Gen nbn™: 2020 and Beyond: The Future of a Connected Australia

The nbn™ network is an essential piece of national infrastructure that enhances connectivity throughout Australia’s vast continental landmass. Connectivity is arguably the quintessential resource of the new century: more important than natural resources, military power or industrial manufacturing. Each order-of-magnitude increase in digital capacity changes how people, businesses and institutions think and live connectivity, translating niche or boutique digital experiences into mainstream practices. The nbn™ network is one of many conditions required for sustainable and significant change. To take advantage of the unprecedented potential that the nbn™ network brings, Australia is expected to see advances in areas such as education, training, digital literacy, and community engagement. With careful attention to these areas, the rollout of the nbn™ network raises prospects for the realisation of new economic and cultural possibilities. Just as the move from dial-up narrowband to always-on broadband has, in less than two decades, created habits, expectations, dependencies and connections, we anticipate the expansion of fast broadband will create powerful opportunities for gen nbn™. Australians continue to adopt the internet at extraordinary rates. The Australian Bureau of Statistics reports six in every seven households had internet at home in 2015 – up from two-thirds in 2007/08. Conservative estimates see these figures growing to 94 per cent of households by 2020, encompassing virtually all households by 2030 will be connected across a mix of nbn broadband, 4G mobile internet and other internet services. The nbn™ network will match much of this demand, delivering access to remote and densely populated areas across the continent The opportunities are many, but they are mirrored by challenges that we must collectively address. Movements away from and towards major and regional urban centres, in part facilitated by connectivity, rejuvenate some communities and place strains on others. Lowered thresholds for start-ups pose competitive challenges for established firms in health, energy and media. There is great potential to consolidate many Australians’ digital habits of social and multimedia consumption and enable them to move up the ‘ladder of opportunity’. But without the necessary interventions, it is possible that Australia’s digital divide will deepen. Australians need to anticipate and solve the challenges that confront us so we can optimise the significant cultural, political and economic benefits that potentially accompany greater connectivity afforded by the nbn™ network. Acknowledging these challenges, this report also outlines the many opportunities to which fast broadband via the nbn™ network will enable. It focuses on the likely impacts on lifestyle, consumption, work, wellbeing and learning. Australia is a technologically advanced country. Australians are early adopters of technological development, integrating technology into work and other life-activities. With government, community and corporate investment in innovation, Australia is poised to play a leading role in the development of the technology sector globally. By mobilising individuals and communities in the project of activating the potential of the nbn™ network delivery platform, Australia is well placed to be the most integrated, digitally connected continent on the planet. Australia is currently at a tipping point. National high-speed connectivity opens up an array of possibilities for economic prosperity and social benefit. But if the nation is to maximise the opportunities and meet the challenges, this will require a collective effort that builds upon and strengthens existing face-to-face connections and community-based engagement. The nbn™ network is a key digital platform. How we use it will matter

The Ginninderra CH4 and CO2 release experiment : an evaluation of gas detection and quantification techniques

A methane (CH4) and carbon dioxide (CO2) release experiment was held from April to June 2015 at the Ginninderra Controlled Release Facility in Canberra, Australia. The experiment provided an opportunity to compare different emission quantification techniques against a simulated CH4 and CO2 point source release, where the actual release rates were unknown to the participants. Eight quantification techniques were assessed: three tracer ratio techniques (two mobile); backwards Lagrangian stochastic modelling; forwards Lagrangian stochastic modelling; Lagrangian stochastic (LS) footprint modelling; atmospheric tomography using point and using integrated line sensors. The majority of CH4 estimates were within 20% of the actual CH4 release rate (5.8 g/min), with the tracer ratio technique providing the closest estimate to both the CH4 and CO2 release rates (100 g/min). Once the release rate was known, the majority of revised estimates were within 10% of the actual release rate. The study illustrates the power of measuring the emission rate using multiple simultaneous methods and obtaining an ensemble median or mean. An ensemble approach to estimating the CH4 emission rate proved successful with the ensemble median estimate within 16% for the actual release rate for the blind release experiment and within 2% once the release rate was known. The release also provided an opportunity to assess the effectiveness of stationary and mobile ground and aerial CH4 detection technologies. Sensor detection limits and sampling rates were found to be significant limitations for CH4 and CO2 detection. A hyperspectral imager's capacity to image the CH4 release from 100 m, and a Boreal CH4 laser sensor's ability to track moving targets suggest the future possibility to map gas plumes using a single laser and mobile aerial reflector