Combustion emissions produced from burning real transportation fuels have many environmental impacts. However, detailed chemistry across multiple phases, time scales, and thermodynamic conditions make predicting combustion emissions challenging. Detailed modeling of the gas phase alone is prohibitively expensive, due to the large size and stiffness of the kinetic models. The...
In recent decades the habitat of North American beaver (Castor canadensis) has expanded from boreal forests into pan-Arctic tundra ecosystems. It is unknown how the advance of beavers into Arctic watersheds will impact microbial communities responsible for the mineralization of organic matter (OM), which has implications for carbon cycling. To...
Learning latent space representations of high-dimensional world states has been at the core of recent rapid growth in reinforcement learning(RL). At the same time, RL algo- rithms have suffered from ignored uncertainties in the predicted estimates of model-free or model-based methods. In our work, we investigate both of these aspects...
Transformation is a major bottleneck for genetic engineering and gene editing in forest tree species. This includes most genotypes of Populus and Eucalyptus, which are some of the world’s most widely-cultivated genera of plantation forest trees. To provide new tools for transformation, I tested the transcription factor-protein chimera consisting of...
Alzheimer’s Disease (AD) is a neurodegenerative pathology currently affecting nearly 44 million individuals worldwide, yet there are not currently any effective treatments or preventions for AD despite the rapid development in our understanding of the disease over the last four decades. The medical and sanitary innovations of the last century...
It is desirable for complex engineered systems to perform missions efficiently and economically, even when these missions' complex, variable, long-term operational profiles make it likely for hazards to arise. It is thus important to design these systems to be resilient so that they will actively prevent and recover from hazards...
Machine learning (ML) and deep learning (DL) models impact our daily lives with applications in natural language modeling, image analysis, healthcare, genomics, and bioinformatics. The exponential growth of biological sequence data necessitates accompanying advances in computational methods. Although deep learning is highly effective for detecting and classifying biological sequences, challenges...
Large dams and their respective reservoirs can provide renewable energy and water security, but also profoundly alter riverine ecosystems. In the Pacific Northwest, dams and reservoirs cause discontinuities in river networks that have been particularly problematic for anadromous fishes. As barriers to the upstream and downstream migration of anadromous fishes,...
Tidal marshes are dynamic ecosystems that are threatened by climate change and sea-level rise. To characterize baseline condition and historic climate sensitivities, and improve projections into the future, new methods are required that integrate data from the field and remote sensing platforms. Marsh elevation response models can be calibrated with...
Historically, the difficulty of obtaining pure cultures of abundant marine
microbial plankton has an obstacle to reconstructing the underlying
mechanisms of biogeochemistry in the ocean. While a number of dominant
marine species from the ocean surface have been cultured, the dominant
microbial plankton of the dark ocean proved far more...