Publications by authors named "R Retkute"
Article Synopsis
- There is a critical need for mathematical models to enhance surveillance and management of transboundary pest invasions, specifically targeting desert locusts, which pose a significant threat to smallholder farmers.
- The proposed integrated modeling framework predicts locust populations by incorporating various life stages and their movement patterns in search of suitable environments for breeding and feeding.
- This framework combines epidemiological modeling, weather data, and atmospheric transport models, aiming to serve as a practical tool for predicting locust swarm movements during future upsurges.
Tracking cells as they divide and progress through differentiation is a fundamental step in understanding many biological processes, such as the development of organisms and progression of diseases. In this study, we investigate a machine learning approach to reconstruct lineage trees in experimental systems based on mutating synthetic genomic barcodes. We refine previously proposed methodology by embedding information of higher level relationships between cells and single-cell barcode values into a feature space.
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- Machine learning applications in healthcare have potential benefits, but their real-world accuracy, especially for different patient groups, is still uncertain, prompting a community challenge focused on predicting all-cause mortality.
- The challenge involved 345 participants forming 25 teams from across 10 countries, who created 25 models trained on a dataset of over 1.1 million patients, with the best model achieving a high performance score.
- Analysis showed significant variability in model accuracy based on patient subpopulations, indicating both the possibilities and limitations of using AI in clinical settings.
Acclimation of photosynthesis to light intensity (photoacclimation) takes days to achieve and so naturally fluctuating light presents a potential challenge where leaves may be exposed to light conditions that are beyond their window of acclimation. Experiments generally have focused on unchanging light with a relatively fixed combination of photosynthetic attributes to confer higher efficiency in those conditions. Here a controlled LED experiment and mathematical modelling was used to assess the acclimation potential of contrasting Arabidopsis thaliana genotypes following transfer to a controlled fluctuating light environment, designed to present frequencies and amplitudes more relevant to natural conditions.
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- * Geostatistical methods analyze spatial data from prevalence surveys, helping to create maps that improve disease risk assessment and planning of targeted interventions.
- * A new Bayesian approach combines geostatistical maps with transmission models to better evaluate the impact of control programs at a local level, applied successfully to lymphatic filariasis in East Africa.