A systematic literature inventory on the interaction between dietary factors and environmental chemical exposures for nervous system health outcomes - Chelsea A. Weitekamp; Caleb Watson; Ellen Hata; Kirstin Hester; Urmila P. Kodavanti; Christopher Lau; David M. Lehmann; Colette N. Miller; Rachel M. Shaffer; Fatima Soliman; Martha Powers; Francesca M. Branch (Food and Chemical Toxicology, 2026)

Multifidelity Monte Carlo method for rapid uncertainty quantification in CO$$_2$$ storage applications - Francesca Watson; Øystein Klemetsdal; Kjetil Olsen Lye (Computational Geosciences, 2025)
We present a multifidelity Multilevel Monte Carlo (MLMC) method for efficient uncertainty quantification in CO $$_2$$ 2 storage applications. By combining full-physics reservoir models with reduced-order vertical equilibrium (VE) models, the approach significantly reduces computational cost while maintaining accuracy. VE models, which assume vertical equilibrium and model only lateral flow, enable rapid simulation of complex, layered reservoirs. We demonstrate the method on realistic case studies, including the Johansen and Sleipner sites, showing that MLMC with VE can significantly reduce simulation time compared to standard Monte Carlo methods. This makes large-scale ensemble simulations feasible for applications such as storage capacity estimation and improved uncertainty estimates to be used in value-of-information (VOI) monitoring design.

The use of flow diagnostics to rank model ensembles - Francesca Watson; Stein Krogstad; Knut-Andreas Lie (Computational Geosciences, 2022)
Ensembles of geomodels provide an opportunity to investigate a range of parameters and possible operational outcomes for a reservoir. Full-featured dynamic modelling of all ensemble members is often computationally unfeasible, however some form of modelling, allowing us to discriminate between ensemble members based on their flow characteristics, is required. Flow diagnostics (based on a single-phase, steady-state simulation) can provide tools for analysing flow patterns in reservoir models but can be calculated in a much shorter time than a full-physics simulation. Heterogeneity measures derived from flow diagnostics can be used as proxies for oil recovery. More advanced flow diagnostic techniques can also be used to estimate recovery. With these tools we can rank ensemble members and choose a subset of models, representing a range of possible outcomes, which can then be simulated further. We demonstrate two types of flow diagnostics. The first are based on volume-averaged travel times, calculated on a cell by cell basis from a given flow field. The second use residence time distributions, which take longer to calculate but are more accurate and allow for direct estimation of recovery volumes. Additionally we have developed new metrics which work better for situations where we have a non-uniform initial saturation, e.g., a reservoir with an oil cap. Three different ensembles are analysed: Egg, Norne, and Brugge. Very good correlation, in terms of model ranking and recovery estimates, is found between flow diagnostics and full simulations for all three ensembles using both the cell-averaged and residence time based diagnostics.

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity - Chiara Fallerini; Nicola Picchiotti; Margherita Baldassarri; Kristina Zguro; Sergio Daga; Francesca Fava; Elisa Benetti; Sara Amitrano; Mirella Bruttini; Maria Palmieri; Susanna Croci; Mirjam Lista; et al. (Human Genetics, 2022)
The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.

Comparison of Flow and Transport Experiments on 3D Printed Micromodels with Direct Numerical Simulations - Francesca Watson; Julien Maes; Sebastian Geiger; Eric Mackay; Mike Singleton; Thomas McGravie; Terry Anouilh; T. Dawn Jobe; Shuo Zhang; Susan Agar; Sergey Ishutov; Franciszek Hasiuk (Transport in Porous Media, 2019)

Epigenetic variation among natural populations of the South African sandhopper Talorchestia capensis - Simone Baldanzi; Ralph Watson; Christopher D. McQuaid; Gavin Gouws; Francesca Porri (Evolutionary Ecology, 2017)

Dissolution of CO2 From Leaking Fractures in Saline Formations - Francesca E. Watson; Simon A. Mathias; Jeroen van Hunen; Susie E. Daniels; Richard R. Jones (Transport in Porous Media, 2012)

Time trial performance in normal and high ambient temperature: is there a role for 5-HT? - Bart Roelands; Maaike Goekint; Luk Buyse; Frank Pauwels; Guy De Schutter; Francesca Piacentini; Hiroshi Hasegawa; Phil Watson; Romain Meeusen (European Journal of Applied Physiology, 2009)

Performance and thermoregulatory effects of chronic bupropion administration in the heat - Bart Roelands; Hiroshi Hasegawa; Philip Watson; Maria Francesca Piacentini; Luk Buyse; Guy De Schutter; Romain Meeusen (European Journal of Applied Physiology, 2009)