Paper List
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Pharmacophore-based design by learning on voxel grids
This paper addresses the computational bottleneck and limited novelty in conventional pharmacophore-based virtual screening by introducing a voxel cap...
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CONFIDE: Hallucination Assessment for Reliable Biomolecular Structure Prediction and Design
This paper addresses the critical limitation of current protein structure prediction models (like AlphaFold3) where high-confidence scores (pLDDT) can...
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On the Approximation of Phylogenetic Distance Functions by Artificial Neural Networks
This paper addresses the core challenge of developing computationally efficient and scalable neural network architectures that can learn accurate phyl...
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EcoCast: A Spatio-Temporal Model for Continual Biodiversity and Climate Risk Forecasting
This paper addresses the critical bottleneck in conservation: the lack of timely, high-resolution, near-term forecasts of species distribution shifts ...
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Training Dynamics of Learning 3D-Rotational Equivariance
This work addresses the core dilemma of whether to use computationally expensive equivariant architectures or faster symmetry-agnostic models with dat...
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Fast and Accurate Node-Age Estimation Under Fossil Calibration Uncertainty Using the Adjusted Pairwise Likelihood
This paper addresses the dual challenge of computational inefficiency and sensitivity to fossil calibration errors in Bayesian divergence time estimat...
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Few-shot Protein Fitness Prediction via In-context Learning and Test-time Training
This paper addresses the core challenge of accurately predicting protein fitness with only a handful of experimental observations, where data collecti...
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scCluBench: Comprehensive Benchmarking of Clustering Algorithms for Single-Cell RNA Sequencing
This paper addresses the critical gap of fragmented and non-standardized benchmarking in single-cell RNA-seq clustering, which hinders objective compa...
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.