Adaptive soft sensing of river flow prediction for wastewater treatment operation and risk management

Many wastewater utilities have discharge permits directly tied with the receiving river flow, so it is critical to have accurate prediction of the hydraulic throughput to ensure safe operation and environment protection. Current empirical knowledge-based operation faces many challenges, so in this study we developed and assessed daily-adaptive, probabilistic soft sensor prediction models to forecast the next month's average receiving river flowrate and guide the utility operations. By comparing 11 machine-learning methods, extra trees regression exhibits desired deterministic prediction accuracy at day 0 (overall accuracy index: 3.9 × 10^-3 1/cms²) (cms: cubic meter per second), which also increases steadily over the course of the month (e.g., MAPE and RMSE decrease from 41.46% and 23.31 cms to 3.31% and 2.81 cms, respectively). The overall classification accuracy of three river flow classes reaches 0.79 at the beginning and increases to about 0.97 over the course of the predicted month. To manage the uncertainty caused by potential false negative classification as overestimations, a probabilistic assessment on the predictions based on 95% lower PI is developed and successfully reduces the false negative classification from 17% to nearly zero with a slight sacrifice of overall classification accuracy.

Widespread Prion-Based Control of Growth and Differentiation Strategies in Saccharomyces cerevisiae

Theory and experiments suggest that organisms would benefit from pre-adaptation to future stressors based on reproducible environmental fluctuations experienced by their ancestors, but the mechanisms driving pre-adaptation remain enigmatic. We report that the [SMAUG⁺] prion allows yeast to anticipate nutrient repletion after periods of starvation, providing a strong selective advantage. By transforming the landscape of post-transcriptional gene expression, [SMAUG⁺] regulates the decision between two broad growth and survival strategies: mitotic proliferation or meiotic differentiation into a stress-resistant state. [SMAUG⁺] is common in laboratory yeast strains, where standard propagation practice produces regular cycles of nutrient scarcity followed by repletion. Distinct [SMAUG⁺] variants are also widespread in wild yeast isolates from multiple niches, establishing that prion polymorphs can be utilized in natural populations. Our data provide a striking example of how protein-based epigenetic switches, hidden in plain sight, can establish a transgenerational memory that integrates adaptive prediction into developmental decisions.