Danielle McDermott

Characterizing skyrmion flow phases with principal component analysis

Cynthia J. O. Reichhardt, Danielle McDermott, C. Reichhardt

Principal component analysis (PCA) is a powerful method that can identify patterns in large, complex data sets by constructing low-dimensional order parameters from higher-dimensional feature vectors. There are increasing efforts to use space-and-time-dependent PCA to detect transitions in nonequilibrium systems that are …

us (code pays fourni par la source)

Characterizing Skyrmion Flow Phases with Principal Component Analysis

Cynthia J. O. Reichhardt, Danielle McDermott

Principal component analysis (PCA) is a powerful method that can identify patterns in large, complex data sets by constructing low-dimensional order parameters from higher-dimensional feature vectors. There are increasing efforts to use space-and-time-dependent PCA to detect transitions in nonequilibrium systems that are …

Status Epilepticus Protocol Variation Across Accredited National Association of Epilepsy Centers Members

Laura K. Lamberta, Melissa M. Asmar, Megan M. Fredwall, Stephanie M. Ahrens et autres

OBJECTIVES: Status epilepticus (SE) is a neurologic emergency that requires urgent recognition and medical management. SE management remains heterogeneous across centers. METHODS: We analyzed SE treatment protocols from level 3 and level 4 epilepsy centers. Discrete data including stabilization measures, timing of …

us (code pays fourni par la source)

Sensitivity of an integrated experiment to uncertainty in the high explosive equations of state

Beth A. Lindquist, Ryan B. Jadrich, Rachel A. Morneau, Danielle McDermott et autres

Traditionally, hydrodynamics simulations are performed with a single equation-of-state (EOS) to describe each material. These EOSs typically have a physics-informed functional form with adjustable parameters that are calibrated in order to replicate small-scale data. However, because the calibration data have uncertainty and …

us (code pays fourni par la source)

Using principal component analysis to distinguish different dynamic phases in superconducting vortex matter

Cynthia J. O. Reichhardt, Danielle McDermott, Charles M. Reichhardt

Vortices in type-II superconductors driven over random disorder are known to exhibit a remarkable variety of distinct nonequilibrium dynamical phases that arise owing to the competition between vortex-vortex interactions, the quenched disorder, and the drive. These include pinned states, elastic flows, plastic …

us (code pays fourni par la source)

Using Principal Component Analysis to Distinguish Different Dynamic Phases in Superconducting Vortex Matter

Cynthia J. O. Reichhardt, Danielle McDermott, C. Reichhardt

Vortices in type-II superconductors driven over random disorder are known to exhibit a remarkable variety of distinct nonequilibrium dynamical phases that arise due to the competition between vortex-vortex interactions, the quenched disorder, and the drive. These include pinned states, elastic flows, plastic …

Using machine learning to characterize active matter phases: implications for active dynamics on optical substrates

Cynthia J. O. Reichhardt, Danielle McDermott, Charles M. Reichhardt

Feasibility study of microburst VNS therapy in drug-resistant focal and generalized epilepsy

Cornelia Natasha Drees, Pegah Afra, Ryan S. Verner, Lesley C. Kaye et autres

BACKGROUND: Vagus nerve stimulation (VNS) at low frequencies (≤30 Hz) has been an established treatment for drug-resistant epilepsy (DRE) for over 25 years. OBJECTIVE: To examine the initial safety and efficacy performance of an investigational, high-frequency (≥250 Hz) VNS paradigm herein called …

us, gb, be (code pays fourni par la source)

Characterizing different motility-induced regimes in active matter with machine learning and noise

Danielle McDermott, Cynthia J. O. Reichhardt

We examine motility-induced phase separation (MIPS) in two-dimensional run-and-tumble disk systems using both machine learning and noise fluctuation analysis. Our measures suggest that within the MIPS state there are several distinct regimes as a function of density and run time, so that …

us (code pays fourni par la source)

Characterizing Different Motility Induced Regimes in Active Matter with Machine Learning and Noise

Danielle McDermott, Cynthia J. O. Reichhardt

We examine motility-induced phase separation (MIPS) in two-dimensional run and tumble disk systems using both machine learning and noise fluctuation analysis. Our measures suggest that within the MIPS state there are several distinct regimes as a function of density and run time, …

us (code pays fourni par la source)

Microburst Vagus Nerve Stimulation: Safety and Efficacy Outcomes (S44.003)

Cornelia Natasha Drees, Mesha‐Gay Brown, Danielle McDermott, Lesley C. Kaye et autres

We assessed the clinical impact of Microburst-VNS in an early feasibility study.

us, be (code pays fourni par la source)

Course Modifications to Promote Student Mental Health and Move toward Universal Design for Learning

Melissa Eblen‐Zayas, Kristen M. Burson, Danielle McDermott

In response to widespread concerns about student mental health, a growing movement in higher education is focused on fostering student well-being as an important element of student success. Thriving college students experience a level of psychological well-being that contributes to their persistence …

us (code pays fourni par la source)