Widespread loss of safe lake ice access in response to a warming climate.

Millions of people rely on lake ice for safe winter recreation. Warming air temperatures impact the phenology (timing of formation and breakup) and quality (ratio of black to white ice) of lake ice cover, both critical components of ice safety. Later formation and earlier breakup of lake ice lead to overall shorter periods of use.

Analysis of electrode arrangements for brain stroke diagnosis via electrical impedance tomography through numerical computational models.

Rapid stroke-type classification is crucial for improved prognosis. However, current methods for classification are time-consuming, require expensive equipment, and can only be used in the hospital. One method that has demonstrated promise in a rapid, low-cost, non-invasive approach to stroke diagnosis is electrical impedance tomography (EIT).

Adaptive changes in tumor cells in response to reductive stress.

Reductive stress is characterized by an excess of cellular electron donors and can be linked with various human pathologies including cancer. We developed melanoma cell lines resistant to reductive stress agents: rotenone (ROT), n-acetyl-L-cysteine, (NAC), or dithiothreitol (DTT). Resistant cells divided more rapidly and had intracellular homeostatic redox-couple ratios that were shifted towards the reduced state.

Applied machine learning for stroke differentiation by electrical impedance tomography with realistic numerical models.

Electrical impedance tomography (EIT) may have potential to overcome existing limitations in stroke differentiation, enabling low-cost, rapid, and mobile data collection. Combining bioimpedance measurement technologies such as EIT with machine learning classifiers to support decision-making can avoid commonly faced reconstruction challenges due to the nonlinear and ill-posed nature of EIT imaging. Therefore, in this work, we advance this field through a study integrating realistic head models with clinically relevant test scenarios, and a robust architecture consisting of nested cross-validation and principal component analysis.