The ACIGA Data Analysis programme

The Data Analysis programme of the Australian Consortium for Interferometric Gravitational Astronomy (ACIGA) was set up in 1998 by the first author to complement the then existing ACIGA programmes working on suspension systems, lasers and optics, and detector configurations. The ACIGA Data Analysis programme continues to contribute significantly in the field; we present an overview of our activities.Comment: 10 pages, 0 figures, accepted, Classical and Quantum Gravity, (Proceedings of the 5th Edoardo Amaldi Conference on Gravitational Waves, Tirrenia, Pisa, Italy, 6-11 July 2003

Network sensitivity to geographical configuration

Gravitational wave astronomy will require the coordinated analysis of data from the global network of gravitational wave observatories. Questions of how to optimally configure the global network arise in this context. We have elsewhere proposed a formalism which is employed here to compare different configurations of the network, using both the coincident network analysis method and the coherent network analysis method. We have constructed a network model to compute a figure-of-merit based on the detection rate for a population of standard-candle binary inspirals. We find that this measure of network quality is very sensitive to the geographic location of component detectors under a coincident network analysis, but comparatively insensitive under a coherent network analysis.Comment: 7 pages, 4 figures, accepted for proceedings of the 4th Edoardo Amaldi conference, incorporated referees' suggestions and corrected diagra

Variations in older people\u27s emergency care use by social care setting: a systematic review of international evidence

\ua9 The Author(s) 2023. Published by Oxford University Press. BACKGROUND: Older adults\u27 use of social care and their healthcare utilization are closely related. Residents of care homes access emergency care more often than the wider older population; however, less is known about emergency care use across other social care settings. SOURCES OF DATA: A systematic review was conducted, searching six electronic databases between January 2012 and February 2022. AREAS OF AGREEMENT: Older people access emergency care from a variety of community settings. AREAS OF CONTROVERSY: Differences in study design contributed to high variation observed between studies. GROWING POINTS: Although data were limited, findings suggest that emergency hospital attendance is lowest from nursing homes and highest from assisted living facilities, whilst emergency admissions varied little by social care setting. AREAS TIMELY FOR DEVELOPING RESEARCH: There is a paucity of published research on emergency hospital use from social care settings, particularly home care and assisted living facilities. More attention is needed on this area, with standardized definitions to enable comparisons between studies

Spectral Line Removal in the LIGO Data Analysis System (LDAS)

High power in narrow frequency bands, spectral lines, are a feature of an interferometric gravitational wave detector's output. Some lines are coherent between interferometers, in particular, the 2 km and 4 km LIGO Hanford instruments. This is of concern to data analysis techniques, such as the stochastic background search, that use correlations between instruments to detect gravitational radiation. Several techniques of `line removal' have been proposed. Where a line is attributable to a measurable environmental disturbance, a simple linear model may be fitted to predict, and subsequently subtract away, that line. This technique has been implemented (as the command oelslr) in the LIGO Data Analysis System (LDAS). We demonstrate its application to LIGO S1 data.Comment: 11 pages, 5 figures, to be published in CQG GWDAW02 proceeding

Bayesian detection of unmodeled bursts of gravitational waves

The data analysis problem of coherently searching for unmodeled gravitational-wave bursts in the data generated by a global network of gravitational-wave observatories has been at the center of research for almost two decades. As data from these detectors is starting to be analyzed, a renewed interest in this problem has been sparked. A Bayesian approach to the problem of coherently searching for gravitational wave bursts with a network of ground-based interferometers is here presented. We demonstrate how to systematically incorporate prior information on the burst signal and its source into the analysis. This information may range from the very minimal, such as best-guess durations, bandwidths, or polarization content, to complete prior knowledge of the signal waveforms and the distribution of sources through spacetime. We show that this comprehensive Bayesian formulation contains several previously proposed detection statistics as special limiting cases, and demonstrate that it outperforms them.Comment: 18 pages, 3 figures, revisions based on referee comment

The age of data-driven proteomics : how machine learning enables novel workflows

A lot of energy in the field of proteomics is dedicated to the application of challenging experimental workflows, which include metaproteomics, proteogenomics, data independent acquisition (DIA), non-specific proteolysis, immunopeptidomics, and open modification searches. These workflows are all challenging because of ambiguity in the identification stage; they either expand the search space and thus increase the ambiguity of identifications, or, in the case of DIA, they generate data that is inherently more ambiguous. In this context, machine learning-based predictive models are now generating considerable excitement in the field of proteomics because these predictive models hold great potential to drastically reduce the ambiguity in the identification process of the above-mentioned workflows. Indeed, the field has already produced classical machine learning and deep learning models to predict almost every aspect of a liquid chromatography-mass spectrometry (LC-MS) experiment. Yet despite all the excitement, thorough integration of predictive models in these challenging LC-MS workflows is still limited, and further improvements to the modeling and validation procedures can still be made. In this viewpoint we therefore point out highly promising recent machine learning developments in proteomics, alongside some of the remaining challenges

Young people's understanding, attitudes and involvement in decision-making about genome sequencing for rare diseases: A qualitative study with participants in the UK 100,000 genomes project

Genome sequencing (GS) will have a profound impact on the diagnosis of rare and inherited diseases in children and young people. We conducted 27 semi-structured interviews with young people aged 11-19 having GS through the UK 100,000 Genomes Project. Participants demonstrated an understanding of the role and function of genes and DNA, however the terms 'genome' and 'genome sequencing' were less well understood. Participants were primarily motivated to take part to get a diagnosis or identify the gene causing their condition. The majority of participants understood they might not receive a diagnostic result. Most were unconcerned about data security or access, however anxieties existed around what the results might show and the potential for disappointment if the result was negative. Signing an assent form empowered young people, formalised the process and instilled a sense of responsibility for their choice to participate. Most young people (≥16 years) had consented to receive secondary findings and had come to that decision without parental influence. Our research suggests that at least some young people are capable of making informed decisions about taking part in GS, and that involving them in discussions about testing can empower them to take responsibility over healthcare decisions that affect them

Double Exchange Alone Does Not Explain the Resistivity of La1−xSrxMnO3La_{1-x} Sr_x MnO_3

The $La_{1-x} Sr_x MnO_3$ system with $0.2 \lesssim x \lesssim 0.4$ has traditionally been modelled with a ``double exchange'' Hamiltonian, in which it is assumed that the only relevant physics is the tendency of carrier hopping to line up neighboring spins. We present a solution of the double exchange model, show it is incompatible with many aspects of the resistivity data, and propose that a strong electron-phonon interaction arising from a Jahn-Teller splitting of the outer Mn d-level plays a crucial role.Comment: Figure available via concentional mail. Contact [email protected]

Robot rights? Towards a social-relational justification of moral consideration \ud

Should we grant rights to artificially intelligent robots? Most current and near-future robots do not meet the hard criteria set by deontological and utilitarian theory. Virtue ethics can avoid this problem with its indirect approach. However, both direct and indirect arguments for moral consideration rest on ontological features of entities, an approach which incurs several problems. In response to these difficulties, this paper taps into a different conceptual resource in order to be able to grant some degree of moral consideration to some intelligent social robots: it sketches a novel argument for moral consideration based on social relations. It is shown that to further develop this argument we need to revise our existing ontological and social-political frameworks. It is suggested that we need a social ecology, which may be developed by engaging with Western ecology and Eastern worldviews. Although this relational turn raises many difficult issues and requires more work, this paper provides a rough outline of an alternative approach to moral consideration that can assist us in shaping our relations to intelligent robots and, by extension, to all artificial and biological entities that appear to us as more than instruments for our human purpose