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When exposure measurement error (EME), confounder measurement error (CME), or both are present, health effect estimates regarding exposure mixtures and critical exposure time-window may not represent the true effects. For example, in air…
We present data driven deep learning models for forecasting and monitoring amine emissions and key performance parameters in amine-based post-combustion carbon capture systems. Using operational data from the CESAR1 solvent campaign at…
The diffuse morphology and transient nature of coronal mass ejections (CMEs) make them difficult to identify and track using traditional image processing techniques. We apply multiscale methods to enhance the visibility of the faint CME…
The complexity of linear mixed-effects (LME) models means that traditional diagnostics are rendered less effective. This is due to a breakdown of asymptotic results, boundary issues, and visible patterns in residual plots that are…
Collider experiments provide an opportunity to produce particles at close distances and momenta. The measured correlation functions between particles can provide information on both the effective emission source and the interaction…
Successful quantitative measurement of carbon content in coal using laser-induced breakdown spectroscopy (LIBS) is suffered from relatively low precision and accuracy. In the present work, the spectrum standardization method was combined…
The international Muon Ionization Cooling Experiment (MICE) will perform a systematic investigation of ionization cooling of a muon beam. The demonstration is based on a simplified version of a neutrino factory cooling channel. As the…
Coronal mass ejections (CMEs) and other solar eruptive phenomena can be physically linked by combining data from a multitude of ground-based and space-based instruments alongside models, however this can be challenging for automated…
The radial expansion of coronal mass ejections (CMEs) is known to occur from remote observations; from the variation of their properties with radial distance; and from local in situ plasma measurements showing a decreasing speed profile…
Because the traditional observable of charge-dependent azimuthal correlator $\gamma$ contains both contributions from the chiral magnetic effect (CME) and its background, a new observable of $R_{\Psi_{m}}$ has been recently proposed which…
We consider the task of causal structure learning over measurement dependence inducing latent (MeDIL) causal models. We show that this task can be framed in terms of the graph theoretic problem of finding edge clique covers,resulting in an…
A mechanism connecting ice algal ecodynamics with the buildup of organic macromolecules in brine channels is tested offline in a reduced model of pack geochemistry. Driver physical quantities are extracted from the global sea ice dynamics…
Recent work shows that in-context learning and optimization of in-context examples (ICE) can significantly improve the accuracy of large language models (LLMs) on a wide range of tasks, leading to an apparent consensus that ICE optimization…
Detailed scheduling has traditionally been optimized for the reduction of makespan and manufacturing costs. However, growing awareness of environmental concerns and increasingly stringent regulations are pushing manufacturing towards…
The growing urgency of the climate crisis has driven the implementation of diverse policy instruments to mitigate greenhouse gas (GHG) emissions. Among them, carbon pricing mechanisms such as carbon taxes and emissions trading systems…
Emissions markets play a vital role in emissions reduction by incentivizing firms to minimize costs. However, their effectiveness heavily depends on the decisions of policymakers, future economic activity, and the availability of abatement…
Load shifting by commercial and industrial power consumers reduces costs and Scope 2 emissions for the consumer and the grid. Incentivizing this behavior requires tools for valuing flexibility amidst the heterogeneity in load…
Many material properties can be traced back to properties of their grain boundaries. Grain boundary energy (GBE), as a result, is a key quantity of interest in the analysis and modeling of microstructure. A standard method for calculating…
This study presents a semi-nonparametric Latent Class Choice Model (LCCM) with a flexible class membership component. The proposed model formulates the latent classes using mixture models as an alternative approach to the traditional random…
Quantifying exhaled CO2 from free-roaming cattle is both a direct indicator of rumen metabolic state and a prerequisite for farm-scale carbon accounting, yet no existing system can deliver continuous, spatially resolved measurements without…