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您的检索式：作者名="Caitlin Ross"
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| 1 | Sleep and stress in the acute phase of concussion in youth显示文摘This study sought to address the complex interplay between both biological and psychological perceptions of stress and sleep in the acute stages following a mild traumatic brain injury.A secondary goal was to identify potential targets for intervention.Eleven acutely injured youth(mean age 12 years)were studied at home with overnight actigraphy,salivary cortisol and melatonin assays,and subjective ratings of stress and fatigue(injured group).Nine matched control youth also were assessed(control group).Results suggested longer sleep latencies(time to fall asleep)and higher levels of fatigue in the injured group exist(p=0.025 and p=0.004,respectively).In the injured group,stress and sleep onset were significantly related with most subjects meeting criteria for Acute Stress Disorder.Melatonin levels were lower at bedtime in the injured group.Saliva samples were collected via passive drool at three time points:~1 h before bed(“bedtime”or T1),immediately upon waking(time 2:T2),and 30 min post-waking(time 3:T3).Overnight increases in cortisol(T1 to T2)were greater for the injured group;however,post-sleep changes in cortisol(T2 to T3)were reversed with control concentrations increasing.These findings are unique in using actigraphy and salivary hormone levels in an acutely injured youth while in their homes.The differences in sleep latency and the presence of injury-related stress point to potential treatment targets in acute concussion. | Arthur Maerlender Caitlin Masterson Jessica L.Calvi Todd Caze Ross Mathiasen Dennis Molfese | 2020 | Sports Medicine and Health Science2020，2，2： | 0 |
| 2 | A visual analytics system for optimizing the performance of large-scale networks in supercomputing systems显示文摘The overall efficiency of an extreme-scale supercomputer largely relies on the performance of its network interconnects.Several of the state of the art supercomputers use networks based on the increasingly popular Dragonfly topology.It is crucial to study the behavior and performance of different parallel applications running on Dragonfly networks in order to make optimal system configurations and design choices,such as job scheduling and routing strategies.However,in order to study these temporal network behavior,we would need a tool to analyze and correlate numerous sets of multivariate time-series data collected from the Dragonfly's multi-level hierarchies.This paper presents such a tool-a visual analytics system-that uses the Dragonfly network to investigate the temporal behavior and optimize the communication performance of a supercomputer.We coupled interactive visualization with time-series analysis methods to help reveal hidden patterns in the network behavior with respect to different parallel applications and system configurations.Our system also provides multiple coordinated views for connecting behaviors observed at different levels of the network hierarchies,which effectively helps visual analysis tasks.We demonstrate the effectiveness of the system with a set of case studies.Our system and findings can not only help improve the communication performance of supercomputing applications,but also the network performance of next-generation supercomputers. | Takanori Fujiwara Jianping Kelvin Li Misbah Mubarak Caitlin Ross Christopher D.Carothers Robert B.Ross Kwan-Liu Ma | 2018 | Visual Informatics2018，2，1： | 0 |
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