Paper List
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Emergent Spatiotemporal Dynamics in Large-Scale Brain Networks with Next Generation Neural Mass Models
This work addresses the core challenge of understanding how complex, brain-wide spatiotemporal patterns emerge from the interaction of biophysically d...
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Human-Centred Evaluation of Text-to-Image Generation Models for Self-expression of Mental Distress: A Dataset Based on GPT-4o
This paper addresses the critical gap in evaluating how AI-generated images can effectively support cross-cultural mental distress communication, part...
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GOPHER: Optimization-based Phenotype Randomization for Genome-Wide Association Studies with Differential Privacy
This paper addresses the core challenge of balancing rigorous privacy protection with data utility when releasing full GWAS summary statistics, overco...
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Real-time Cricket Sorting By Sex A low-cost embedded solution using YOLOv8 and Raspberry Pi
This paper addresses the critical bottleneck in industrial insect farming: the lack of automated, real-time sex sorting systems for Acheta domesticus ...
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Collective adsorption of pheromones at the water-air interface
This paper addresses the core challenge of understanding how amphiphilic pheromones, previously assumed to be transported in the gas phase, can be sta...
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pHapCompass: Probabilistic Assembly and Uncertainty Quantification of Polyploid Haplotype Phase
This paper addresses the core challenge of accurately assembling polyploid haplotypes from sequencing data, where read assignment ambiguity and an exp...
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Setting up for failure: automatic discovery of the neural mechanisms of cognitive errors
This paper addresses the core challenge of automating the discovery of biologically plausible recurrent neural network (RNN) dynamics that can replica...
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Influence of Object Affordance on Action Language Understanding: Evidence from Dynamic Causal Modeling Analysis
This study addresses the core challenge of moving beyond correlational evidence to establish the *causal direction* and *temporal dynamics* of how obj...
Generating a Contact Matrix for Aged Care Settings in Australia: an agent-based model study
University of New South Wales
The 30-Second View
IN SHORT: This study addresses the critical gap in understanding heterogeneous contact patterns within aged care facilities, where existing population-level contact matrices fail to capture the nuanced interactions that drive infection transmission in these high-risk environments.
Innovation (TL;DR)
- Methodology Developed a transferable agent-based modeling framework specifically for aged care settings, parameterized with empirical survey data from 21 aged care workers to capture realistic staff-resident interaction patterns.
- Methodology Integrated proximity-based contact definitions (1.5m and 3m thresholds with 3-second duration) with temporal analysis to identify high-risk contact clustering during structured daily routines like communal activities and care tasks.
- Biology Demonstrated that medium care residents experience the highest infection risk despite not having the highest contact frequency, revealing non-linear relationships between contact patterns and transmission outcomes.
Key conclusions
- Low and medium care residents had the highest contact frequencies (particularly with morning/afternoon shift staff), while high care residents and night staff had substantially fewer contacts, with Poisson regression confirming significant variation by care level and shift (p<0.001).
- Vaccination scenarios reduced predicted transmission by up to 68%, with maximum impact achieved when both staff and residents were vaccinated, demonstrating the multiplicative protective effect of comprehensive vaccination coverage.
- Temporal analysis revealed clustering of high-risk contacts during structured daily routines, with infection risk highest during high-contact shifts and among medium care residents, highlighting the importance of timing in intervention strategies.
Abstract: This study presents an agent-based model (ABM) developed to simulate staff and resident interactions within a synthetic aged care facility, capturing movement, task execution, and proximity-based contact events across three staff shifts and varying levels of resident care. Contacts were defined by spatial thresholds (1.5 m and 3 m) and cumulative duration, enabling the generation of detailed contact matrices. Simulation results showed that low and medium care residents experienced the highest frequency of interactions, particularly with staff on morning and afternoon shifts, while high care residents and night staff had substantially fewer contacts. Contact rates varied significantly by care level and shift, confirmed through Poisson-based regression modelling. Temporal analyses revealed clustering of high-risk contacts during structured daily routines, especially communal and care activities. An integrated airborne transmission module, seeded with a single infectious staff member, demonstrated that infection risk was highest during high-contact shifts and among medium care residents. Vaccination scenarios reduced predicted transmission by up to 68%, with the greatest impact observed when both staff and residents were vaccinated. These findings highlight the importance of accounting for contact heterogeneity in aged care and demonstrate the utility of ABMs for evaluating targeted infection control strategies in high-risk, enclosed environments.