Real-Time Bayesian Analysis of Ground Motion Envelopes for Earthquake Early Warning

Current earthquake early warning systems usually make magnitude and location predictions and send out a warning to the users based on those predictions. We describe an algorithm that assesses the validity of the predictions in real-time. Our algorithm monitors the envelopes of horizontal and vertical acceleration, velocity, and displacement. We compare the observed envelopes with the ones predicted by Cua & Heaton's envelope ground motion prediction equations (Cua 2005). We define a "test function" as the logarithm of the ratio between observed and predicted envelopes at every second in real-time. Once the envelopes deviate beyond an acceptable threshold, we declare a misfit. Kurtosis and skewness of a time evolving test function are used to rapidly identify a misfit. Real-time kurtosis and skewness calculations are also inputs to both probabilistic (Logistic Regression and Bayesian Logistic Regression) and nonprobabilistic (Least Squares and Linear Discriminant Analysis) models that ultimately decide if there is an unacceptable level of misfit. This algorithm is designed to work at a wide range of amplitude scales. When tested with synthetic and actual seismic signals from past events, it works for both small and large events.

Computationally-guided thermostabilization of the primary endoglucanase from Hypocrea jecorina for cellulosic biofuel production

The creation of thermostable enzymes has wide-ranging applications in industrial, scientific, and pharmaceutical settings. As various stabilization techniques exist, it is often unclear how to best proceed. To this end, we have redesigned Cel5A (HjCel5A) from Hypocrea jecorina (anamorph Trichoderma reesei) to comparatively evaluate several significantly divergent stabilization methods: 1) consensus design, 2) core repacking, 3) helix dipole stabilization, 4) FoldX ΔΔG approximations, 5) Triad ΔΔG approximations, and 6) entropy reduction through backbone stabilization. As several of these techniques require structural data, we initially solved the first crystal structure of HjCel5A to 2.05 Å. Results from the stabilization experiments demonstrate that consensus design works best at accurately predicting highly stabilizing and active mutations. FoldX and helix dipole stabilization, however, also performed well. Both methods rely on structural data and can reveal non-conserved, structure-dependent mutations with high fidelity. HjCel5A is a prime target for stabilization. Capable of cleaving cellulose strands from agricultural waste into fermentable sugars, this protein functions as the primary endoglucanase in an organism commonly used in the sustainable biofuels industry. Creating a long-lived, highly active thermostable HjCel5A would allow cellulose hydrolysis to proceed more efficiently, lowering production expenses. We employed information gleaned during the survey of stabilization techniques to generate HjCel5A variants demonstrating a 12-15 °C increase in the temperature at which 50% of the total activity persists, an 11-14 °C increase in optimal operating temperature, and a 60% increase over the maximal amount of hydrolysis achievable using the wild type enzyme. We anticipate that our comparative analysis of stabilization methods will prove useful in future thermostabilization experiments.