Adelaide Research & Scholarship
Adelaide Research & Scholarship (AR&S) is the University of Adelaide’s digital repository. AR&S provides a platform for the collection, organisation, access and preservation of the research and scholarly outputs of the University community in digital formats, as well as digital management of information in physical formats.
University of Adelaide higher degree by research theses are deposited into the AR&S Theses community as part of the final thesis lodgement process.
AR&S also serves as the home of the digital collections of University Library Archives and Special Collections. Items include digitized representations of physical items, such as photographs and full texts, and digital-born materials, allowing worldwide access to our heritage and research collections.
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Recent Submissions
Observation of high-energy neutrinos from the Galactic plane
(Sissa Medialab Srl, 2024) Abbasi, R.; Ackermann, M.; Adams, J.; Agarwalla, S.K.; Aguilar, J.A.; Ahlers, M.; Alameddine, J.M.; Amin, N.M.; Andeen, K.; Anton, G.; Argüelles, C.; Ashida, Y.; Athanasiadou, S.; Axani, S.N.; Bai, X.; Balagopal, A.V.; Baricevic, M.; Barwick, S.W.; Basu, V.; Bay, R.; et al.; 38th International Cosmic Ray Conference (ICRC) (26 Jul 2023 - 3 Aug 2023 : Nagoya, Japan)
IceCube has discovered a flux of astrophysical neutrinos and presented evidence for the first neutrino sources, a flaring blazar known as TXS 0506+056 and the active galaxy NGC 1068. However, the sources responsible for the majority of the astrophysical neutrino flux remain elusive. In addition to hypothetical sources within our Galaxy, high energy neutrinos are produced when cosmic rays interact at their acceleration sites and during propagation through the interstellar medium. The Galactic plane has therefore long been hypothesized as a neutrino source. In this contribution, new results are presented for searches of neutrino sources utilizing a dataset that builds upon recent advances in deep-learning-based reconstruction methods for neutrino-induced cascades. This work presents the first observation of high-energy neutrinos from the Milky Way Galaxy, rejecting the background-only hypothesis at 4.5~σ. The neutrino signal is consistent with diffuse emission from the Galactic plane, potentially in combination with emission by a population of sources.
Observation of high-energy neutrinos from the Galactic plane
(American Association for the Advancement of Science (AAAS), 2023) Abbasi, R.; Ackermann, M.; Adams, J.; Aguilar, J.A.; Ahlers, M.; Ahrens, M.; Alameddine, J.M.; Alves, A.A.; Amin, N.M.; Andeen, K.; Anderson, T.; Anton, G.; Argüelles, C.; Ashida, Y.; Athanasiadou, S.; Axani, S.; Bai, X.; Balagopal V, A.; Barwick, S.W.; Basu, V.; et al.
The origin of high-energy cosmic rays, atomic nuclei that continuously impact Earth's atmosphere, is unknown. Because of deflection by interstellar magnetic fields, cosmic rays produced within the Milky Way arrive at Earth from random directions. However, cosmic rays interact with matter near their sources and during propagation, which produces high-energy neutrinos. We searched for neutrino emission using machine learning techniques applied to 10 years of data from the IceCube Neutrino Observatory. By comparing diffuse emission models to a background-only hypothesis, we identified neutrino emission from the Galactic plane at the 4.5σ level of significance. The signal is consistent with diffuse emission of neutrinos from the Milky Way but could also arise from a population of unresolved point sources.
Prevalence of unmet supportive care needs reported by individuals ever diagnosed with cancer in Australia: a systematic review to support service prioritisation
(Springer, 2023) Roseleur, J.; Edney, L.C.; Jung, J.; Karnon, J.
Purpose: Improved health outcomes for individuals ever diagnosed with cancer require comprehensive, coordinated care that addresses their supportive care needs. Implementing interventions to address these is confounded by a lack of evidence on population needs and a large pool of potential interventions. This systematic review estimates the point prevalence of different supportive care needs stratified by the tool used to measure needs and cancer type in Australia. Methods: We searched MEDLINE, Embase, and Scopus from 2010 to April 2023 to identify relevant studies published on the prevalence of supportive care needs in Australia. Results: We identified 35 studies that met the inclusion criteria. The highest prevalent unmet need across all cancers was ‘fear of cancer spreading’ (20.7%) from the Supportive Care Needs Survey Short-Form 34 (SCNS-SF34), ranging from 9.4% for individuals ever diagnosed with haematological cancer to 36.3% for individuals ever diagnosed with gynaecological cancer, and ‘concerns about cancer coming back’ (17.9%) from the Cancer Survivors’ Unmet Needs (CaSUN), ranging from 9.7% for individuals ever diagnosed with prostate cancer to 37.8% for individuals ever diagnosed with breast cancer. Two studies assessed needs in Aboriginal and Torres Strait Islander populations, reporting the highest needs for financial worries (21.1%). Conclusions: Point prevalence estimates presented here, combined with estimates of the costs and effects of potential interventions, can be used within economic evaluations to inform evidence-based local service provision to address the supportive care needs of individuals ever diagnosed with cancer. Implications for Cancer Survivors: Local health services can use local evidence to prioritise the implementation of interventions targeted at unmet needs.
Psychosocial factors, dentist-patient relationships, and oral health-related quality of life: a structural equation modelling
(BMC, 2023) Song, Y.; Luzzi, L.; Brennan, D.
Background: Psychosocial factors and dentist-patient relationships (DPR) have been suggested to be associated with oral health outcomes. This study aimed to test a conceptual model which hypothesised relationships among psychosocial factors, DPR variables, and oral health-related quality of life (OHRQoL) in the ‘distal-to-proximal’ framework. Methods: A total of 12,245 adults aged 18 years or over living in South Australia were randomly sampled for the study. Data were collected from self-complete questionnaires in 2015–2016. The outcome variable of Oral Health Impact Profile was used to measure OHRQoL. Psychosocial domain consisted of psychological well-being, social support, and health self-efficacy. DPR domain included trust in dentists, satisfaction with dental care, and dental fear. The hypothesised model was tested using the two-step approach in structural equation modelling. Results: Data were analysed from 3767 respondents after the screening/preparing process (adjusted valid response rate 37.4%). In the first step of the analysis, confirmatory factor analyses produced acceptable measurement models for each of the six latent variables (GFI = 0.95, CFI = 0.98, RMSEA = 0.04). The final structural model indicated that better well-being, higher self-efficacy, and more satisfaction were associated with lower oral health impact (β = − 0.12, − 0.07, − 0.14, respectively) whereas fear was positively associated (β = 0.19). Among intermediates, support was positively associated with satisfaction within a small effect size (β = 0.06) as compared to self-efficacy with trust (β = 0.22). The invariance of the final model was also confirmed on participants’ SES and dental service characteristics except the variable of ‘last dental visit’. Conclusions: Psychosocial factors and DPR variables were associated with oral health impact in both direct and indirect paths. The framework of ‘distal-to-proximal’ actions is empirically supported from psychosocial factors via DPR variables to OHRQoL.
Regional Video Object Segmentation by Efficient Motion-Aware Mask Propagation
(IEEE, 2023) Miao, B.; Bennamoun, M.; Gao, Y.; Mian, A.; International Conference on Digital Image Computing: Techniques and Applications (DICTA) (30 Nov 2022 - 2 Dec 2022 : Sydney, Australia & virtual online)
The use of optical flow to aid feature matching has been employed in recent self-supervised video object segmentation (VOS) methods and has shown promising results. However, computing pixel-wise optical flow is costly, and the optical flow can also be further utilized for efficient regional segmentation. To address these challenges, we propose an efficient motionaware mask propagation approach, dubbed EMMP, for selfsupervised VOS. EMMP introduces an efficient patch optical flow to compute the motion offsets of image patches for dynamic matching ROI generation. Fine-grained pixel-wise feature matching is performed based on the dynamic matching ROIs for mask propagation. To reduce redundant segmentation while avoiding unnecessary computations, we re-use the patch optical flow to estimate reliable foreground ROIs in the next frame and perform regional segmentation. Evaluation on benchmark VOS datasets shows that EMMP achieves competitive performance with significant wall-clock speed-ups compared to existing selfsupervised training methods, e.g., EMMP slightly outperforms MAMP and runs about 2× faster on segmentation. In addition, EMMP performs on par with many supervised training methods.