Chancellery Research - Research Publications
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ItemThe Living Instruments Project: Sharing sounds of heritage instruments in the Grainger Museum Collection(Australasian Sound Recordings Association, 2022-01-01)The Living Instruments project aims to digitally preserve the sound of the fragile Grainger instrument collection, but it also presents a way of transforming the relationship between musical artefacts and their cultural value with a diverse group of people including contemporary makers. The Living Instruments project emerged in the nexus of teaching, learning, and research activity in the Faculty of Fine Arts and Music, and the stewardship of Percy Grainger’s historic instruments held in the Grainger Museum, at the University of Melbourne. It aims to provide greater research opportunities and creative engagement with the instruments through an interactive platform of sonic resources. This paper provides an overview of the stimulus for the Living Instruments project and shares the stages of the research journey and public outcomes.
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ItemCompetitive Triplet Formation and Recombination in Crystalline Films of Perylenediimide Derivatives: Implications for Singlet Fission(AMER CHEMICAL SOC, 2020-05-28)Developing photostable compounds that undergo quantitative singlet fission (SF) is a key challenge. As SF necessitates electron transfer between neighboring molecules, the SF rate is highly sensitive to intermolecular coupling in the solid state. We investigate SF in thin films for a series of perylenediimide (PDI) molecules. By adding different substituents at the imide positions, the packing of the molecules in the solid state can be changed. The relationship between SF parameters and the stacked geometry in PDI films is investigated, with two-electron direct coupling found to be the main SF mechanism. Time-resolved emission and transient absorption data show that all of the PDI films undergo SF although with different rates and yields varying from 35 to 200%. The results show that PDI1 and 2, which are stacked PDI pairs twisted out of alignment along the highest occupied molecular orbital to lowest unoccupied molecular orbital transition, exhibit faster and more efficient SF up to 200% yield. We demonstrate that both triplet formation and decay rates are highly sensitive to the ordering of the molecules within a film. The results of this study will assist in the design of optimized structures with a fast SF rate and low recombination rate that are required for useful light harvesting applications.
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ItemBenchmarks for measurement of duplicate detection methods in nucleotide databases(OXFORD UNIV PRESS, 2023-12-18)UNLABELLED: Duplication of information in databases is a major data quality challenge. The presence of duplicates, implying either redundancy or inconsistency, can have a range of impacts on the quality of analyses that use the data. To provide a sound basis for research on this issue in databases of nucleotide sequences, we have developed new, large-scale validated collections of duplicates, which can be used to test the effectiveness of duplicate detection methods. Previous collections were either designed primarily to test efficiency, or contained only a limited number of duplicates of limited kinds. To date, duplicate detection methods have been evaluated on separate, inconsistent benchmarks, leading to results that cannot be compared and, due to limitations of the benchmarks, of questionable generality. In this study, we present three nucleotide sequence database benchmarks, based on information drawn from a range of resources, including information derived from mapping to two data sections within the UniProt Knowledgebase (UniProtKB), UniProtKB/Swiss-Prot and UniProtKB/TrEMBL. Each benchmark has distinct characteristics. We quantify these characteristics and argue for their complementary value in evaluation. The benchmarks collectively contain a vast number of validated biological duplicates; the largest has nearly half a billion duplicate pairs (although this is probably only a tiny fraction of the total that is present). They are also the first benchmarks targeting the primary nucleotide databases. The records include the 21 most heavily studied organisms in molecular biology research. Our quantitative analysis shows that duplicates in the different benchmarks, and in different organisms, have different characteristics. It is thus unreliable to evaluate duplicate detection methods against any single benchmark. For example, the benchmark derived from UniProtKB/Swiss-Prot mappings identifies more diverse types of duplicates, showing the importance of expert curation, but is limited to coding sequences. Overall, these benchmarks form a resource that we believe will be of great value for development and evaluation of the duplicate detection or record linkage methods that are required to help maintain these essential resources. DATABASE URL: : https://bitbucket.org/biodbqual/benchmarks.
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ItemNo Preview AvailableDirective Explanations for Actionable Explainability in Machine Learning Applications(ASSOC COMPUTING MACHINERY, 2023-12)In this article, we show that explanations of decisions made by machine learning systems can be improved by not only explaining why a decision was made but also explaining how an individual could obtain their desired outcome. We formally define the concept of directive explanations (those that offer specific actions an individual could take to achieve their desired outcome), introduce two forms of directive explanations (directive-specific and directive-generic), and describe how these can be generated computationally. We investigate people’s preference for and perception toward directive explanations through two online studies, one quantitative and the other qualitative, each covering two domains (the credit scoring domain and the employee satisfaction domain). We find a significant preference for both forms of directive explanations compared to non-directive counterfactual explanations. However, we also find that preferences are affected by many aspects, including individual preferences and social factors. We conclude that deciding what type of explanation to provide requires information about the recipients and other contextual information. This reinforces the need for a human-centered and context-specific approach to explainable AI.
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ItemNo Preview AvailableGenerating Dynamic Kernels via Transformers for Lane Detection(IEEE, 2023-01-01)
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ItemNo Preview AvailableNear-Wall Flow Statistics in High-Reτ Drag-Reduced Turbulent Boundary Layers(SPRINGER, 2023-01-01)
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ItemA preliminary investigation into the influence of archaeological material on the yellowing of polyethylene storage bags(Routledge, 2021)Concerns around the degradation of plastics have been part of conservation discourse for decades. The spotlight is usually on art and objects, and conservation and display materials, however it could be argued that a significant volume of the plastics in museums is associated with storage bags. This study asked whether the condition of plastic storage bags might be influenced by what is stored inside them. If specific materials can be identified as more likely to affect plastic degradation, museums may have a lead-indicator for efficiently monitoring storage risks. This case study developed a methodology for applying multivariate analysis to collected data to answer this question. A subset of polyethylene self-seal bags used to pack archaeological material from the ‘Casselden Place’ assemblage at Museums Victoria was evaluated. Objective data were combined with subjective assessment of bag degradation features gathered during a collection survey and interrogated using multivariate statistical analysis. Results indicate (1) different levels of yellowing are associated with particular plastic bag stocks and (2) ceramic, slate and tile finds are more likely than other materials to be contained within yellower bags. The research points to future enquiry and demonstrates this methodology shows promise for extension to other large cultural datasets.
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ItemNo Preview AvailableThe Women’s Healthy Ageing Project: A pattern of cognitive decline after brain injury(Wiley, 2021-12)Abstract Background It is well recognised that damage sustained by traumatic brain injury (TBI) initiate injury mechanisms that continue to develop long after insult. Increasing evidence suggests TBI may lead to chronic cognitive decline and the development of dementia later in life. However, due to the low rate of TBI in the general community, there is a paucity of data on the impact of cognitive decline in community TBI. We examined longitudinal cognitive changes over a 12‐year period to determine if there was any relationship with community reported TBI. Method The Women’s Healthy Aging Project is an ongoing longitudinal cohort study of community‐dwelling Australian women. Assessments included an extensive range of measures, including neuropsychological testing of multiple cognitive domains and questions relating to head injury. In total, 110 women had complete neuropsychological testing at all three time points; from 2002, 2012 and 2014. Of these women, nine (aged 56‐65 in 2002) had a history of moderate to severe TBI. Composite cognitive scores were compared to 18 healthy controls randomly selected from the complete dataset individually matched for age, education, and APO4‐genotype. Analyses were conducted in five datasets drawn from the complete dataset and results were averaged. Result Median scores for executive function were similar for both the TBI group and healthy controls in 2002, lower in the TBI group by 2012 and this difference increased further in 2014. Median scores for verbal episodic memory were slightly lower in the TBI group than controls in 2002 and 2012, and this difference increased in 2014. Although this initial pilot study with small samples in mid‐aged healthy women did not show statistically significant results, the observed relationships were constant over the five datasets, warranting further exploration. Conclusion In our small pilot study, we observed greater rate of decline of both executive function and verbal episodic memory in women with a history of TBI. Findings warrant a need for larger studies to explore this relationship as it indicates that community‐based reported TBI may impact cognitive performance even in early ageing. Further work will continue to explore cognitive trajectories in women with a mean age 80 at next follow‐up.
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ItemNo Preview AvailableA macro-element model for predicting the combined load behaviour of spudcan foundations in clay overlying sand(Thomas Telford Ltd., 2021-10-26)A macro-element model for predicting the load–displacement behaviour of a spudcan foundation in clay overlying sand when subjected to combined vertical, horizontal and moment loading is introduced. Observations from detailed drum centrifuge tests that measured the effect of the underlying sand layer on the foundation behaviour are combined with finite-element results and theoretical developments to derive the components of the model. The yield surface defined by the centrifuge test results suggests that as the spudcan nears the underlying sand layer, the absolute horizontal capacity remains relatively constant, while the vertical and moment capacities increase at approximately the same normalised rate. The model is demonstrated to accurately predict foundation behaviour by retrospectively simulating the experimental results. This macro-element model has the advantage that it can be integrated into the structural analyses of jack-up platforms required for site-specific assessments.
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ItemNo Preview AvailableDisease Delineation for Multiple Sclerosis, Friedreich Ataxia, and Healthy Controls Using Supervised Machine Learning on Speech Acoustics(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2023)Neurodegenerative disease often affects speech. Speech acoustics can be used as objective clinical markers of pathology. Previous investigations of pathological speech have primarily compared controls with one specific condition and excluded comorbidities. We broaden the utility of speech markers by examining how multiple acoustic features can delineate diseases. We used supervised machine learning with gradient boosting (CatBoost) to delineate healthy speech from speech of people with multiple sclerosis or Friedreich ataxia. Participants performed a diadochokinetic task where they repeated alternating syllables. We subjected 74 spectral and temporal prosodic features from the speech recordings to machine learning. Results showed that Friedreich ataxia, multiple sclerosis and healthy controls were all identified with high accuracy (over 82%). Twenty-one acoustic features were strong markers of neurodegenerative diseases, falling under the categories of spectral qualia, spectral power, and speech rate. We demonstrated that speech markers can delineate neurodegenerative diseases and distinguish healthy speech from pathological speech with high accuracy. Findings emphasize the importance of examining speech outcomes when assessing indicators of neurodegenerative disease. We propose large-scale initiatives to broaden the scope for differentiating other neurological diseases and affective disorders.