The rapid accumulation of plastic waste in landfill, waterways and oceans is becoming a critical problem, one that current recycling technologies are not capable of solving. Recent proposed approaches in the depolymerization of waste plastics employ an Olefin-Intermediate Process (OIP), where feedstocks like polyolefin plastics are ‘activated,’ producing an olefin...
The agricultural sector is one of the largest contributors to global climate change but is also one of the most vulnerable to its impacts. Farmers are at increasing risk of livelihood loss, which produces risks for their physical and emotional wellbeing on a global scale. Swift and effective adaptation is...
It is well documented that microplastics and semi-synthetic particles (<5 mm) pervade the marine environment, with their ingestion by marine fauna eliciting global concern. While fishes exposed to microparticles in a laboratory setting have exhibited both sub-lethal and lethal effects, the diversity in material, morphology, and size of these contaminants...
Ocean deoxygenation is predicted to increase in severity over the next few decades, posing a threat to marine life and fishing economies. Improved predictions of ocean deoxygenation depend on a better understanding of the biogeochemical mechanisms that underly this process. Within the realm of biogeochemical mechanisms, this project specifically investigated...
Signaling refers to the addition of non-content information to a text in order to emphasize certain ideas and/or clarify the organization. There is increased interest in using typographic signaling, such as boldface type, different font sizes and ruled lines, to format computer program source code listings. However, little evidence exists...
Iterative algorithms are simple yet efficient in solving large-scale optimization problems in practice. With a surge in the amount of data in past decades, these methods have become increasingly important in many application areas including matrix/tensor recovery, deep learning, data mining, and reinforcement learning. To optimize or improve iterative algorithms,...
Improving crop cultivars for use on organic farms is pertinent, as current elite germplasm is less resilient within the more variable context of organic farm environments. Although a growing number of studies have focused on organic plant breeding in cereal crops, very few have focused on vegetable crops, especially those...
The distribution of mobile marine predators often reflects underlying dynamic ecological processes. The geographical focus of this PhD is the South Taranaki Bight (STB) of New Zealand, where wind-driven coastal upwelling generates productivity and prey to support a blue whale foraging ground. The STB is also New Zealand’s most industrial...
The primary goal of this dissertation is to improve the quality of nuclear data available to the nuclear science community. We propose to accomplish this by applying machine learning algorithms to the large number of available benchmark experiments and simulations, with the goal of determining which nuclear data have strong...
In this work, we study the problem of learning and improving policies for probabilistic planning problems. In the first part, we train neural network policies for probabilistic planning problems modeled as factored Markov decision problems. The objective is to train problem-specific neural networks via supervised learning to imitate the action...