Characterization and Modeling of Spatial Variability in a Complex Alluvial Aquifer: Implications on Solute Transport

Field investigations of stratified alluvial deposits suggest that they can give rise to a hierarchy of permeability modes across scales, corresponding to a hierarchy of sedimentary unit types and thus may lead to enhanced plume spread in such media. In this work, we model the sedimentary architecture of the alluvium deposits in Fortymile Wash, Nevada, using a hierarchical transition probability geostatistical approach. The alluvial aquifer comprises a segment of the groundwater flow pathway from the potential high-level nuclear waste repository at Yucca Mountain, Nevada to the downstream accessible environment and may be a natural barrier to radionuclide migration. Thus our main goal is to quantify the impact of spatial variability in the alluvium on solute transport. The alluvial aquifer is a gravel-dominated braid-belt deposit, having lower-permeability paleosols interstratified with higher-permeability gravel-bar deposits. A three-dimensional hierarchical hydrofacies model is developed through fusion of multiple geologic data types and sources. Markov chain models of transition probabilities are employed to represent complex patterns of spatial variability at each hierarchical level in a geostatistical fashion and to impose realistic constraints to such variations through conditioning on existing data. The link between the alluvium spatial variability and solute dispersion at different spatiotemporal scales is demonstrated using the stochastic-Lagrangian transport theory. We show that the longitudinal macrodispersivity can be on the order of hundreds to thousands of meters, and it may not reach its asymptotic value until after 1,000 years of traveltime

Characterization and Modeling of Spatial Variability in a Complex Alluvial Aquifer: Implications on Solute Transport

Field investigations of stratified alluvial deposits suggest that they can give rise to a hierarchy of permeability modes across scales, corresponding to a hierarchy of sedimentary unit types and thus may lead to enhanced plume spread in such media. In this work, we model the sedimentary architecture of the alluvium deposits in Fortymile Wash, Nevada, using a hierarchical transition probability geostatistical approach. The alluvial aquifer comprises a segment of the groundwater flow pathway from the potential high-level nuclear waste repository at Yucca Mountain, Nevada to the downstream accessible environment and may be a natural barrier to radionuclide migration. Thus our main goal is to quantify the impact of spatial variability in the alluvium on solute transport. The alluvial aquifer is a gravel-dominated braid-belt deposit, having lower-permeability paleosols interstratified with higher-permeability gravel-bar deposits. A three-dimensional hierarchical hydrofacies model is developed through fusion of multiple geologic data types and sources. Markov chain models of transition probabilities are employed to represent complex patterns of spatial variability at each hierarchical level in a geostatistical fashion and to impose realistic constraints to such variations through conditioning on existing data. The link between the alluvium spatial variability and solute dispersion at different spatiotemporal scales is demonstrated using the stochastic-Lagrangian transport theory. We show that the longitudinal macrodispersivity can be on the order of hundreds to thousands of meters, and it may not reach its asymptotic value until after 1,000 years of traveltime

Protocol for a Scoping Review: Establishing Ground Truth for Delirium Prediction Models in Adult Patients in Acute Care

Background: Artificial Intelligence (AI) in healthcare has shown potential, particularly utilising Electronic Health Record (EHR) data to predict diseases. Delirium, characterised by cognitive changes and attention disruption due to underlying medical conditions, presents a significant obstacle to healthcare. It has been linked to increased morbidity, mortality, dementia progression, elevated costs, and premature transfers to long-term care facilities. The lack of a robust ground truth is a significant challenge faced by AI systems developed to predict delirium. The ground truth consists of verified labels for the outcome to be predicted. With delirium being underreported and poorly documented in hospital settings, creating an accurate and reliable ground truth for delirium prediction systems needs a well-thought-out strategy. Aim: The aim of this scoping review is to summarise and discuss strategies to establish ground truth in datasets used to develop delirium prediction systems for adults in acute care settings. Methods: We will use the Population, Concept, and Context (PCC) approach to define search blocks, and PubReMiner, along with a librarian, to identify relevant search terms. The search will be conducted in three databases (PubMed, IEEE, Cochrane Library). We will use Covidence for the screening process and extract data via REDCap using an extraction table guided by the PROBAST tool and the CHARMS checklist, including a risk of bias assessment. Results: The forthcoming journal article will summarise reported strategies used to establish ground truth for the development of delirium prediction models and discuss their strengths and weaknesses. Conclusion: Developers could benefit from selecting a suitable strategy to establish ground truth based on the summary and discussion presented in this scoping review. This may ultimately improve the accuracy of predictive models by enabling access to higher quality training data and allowing more reliable evaluation of predictive performance, thus increasing model efficiency for real-world implementation

Supplemental Information 1: Time to foraging for crickets in odor and control treatments

Anti-predator behaviors like vigilance or hiding come at the expense of other fitness increasing behaviors such as foraging. To compensate for this trade-off, prey assess predation risk and modify the frequency of anti-predator behaviors according to the likelihood of the threat. In this study, we tested the ability of house crickets (Acheta domesticus) to indirectly assess predation risk via odors from a mammalian predator, Elliot’s short-tailed shrew (Blarina hylophaga). As natural differences in encounter rates and predation risk differs between sexes, we tested if male and female crickets perceive similar rates of predation risk from the presence of shrew odor measured via anti-predator behavioral response. Crickets were placed in enclosed, cardboard-lined chambers either treated with shrew odor or control, along with a food source. Time until foraging was measured for each individual and compared across treatment and sex. We found that in the presence of shrew odor, female crickets delayed foraging while males showed no response. These results suggest adult crickets can use chemical cues to detect mammalian predators. Furthermore, we demonstrate that female crickets associate greater predation risk from shrew predators than do male crickets, which are more stationary yet acoustically conspicuous. As predation risk potentially differs drastically for each sex, changes to the operational sex ratios of wild cricket populations could be influenced by the identity of the predator community