785 research outputs found
Energy Dissipation and Trapping of Particles Moving on a Rough Surface
We report an experimental, numerical and theoretical study of the motion of a
ball on a rough inclined surface. The control parameters are , the diameter
of the ball, , the inclination angle of the rough surface and ,
the initial kinetic energy. When the angle of inclination is larger than some
critical value, , the ball moves at a constant average
velocity which is independent of the initial conditions. For an angle , the balls are trapped after moving a certain distance. The
dependence of the travelled distances on , and . is
analysed. The existence of two kinds of mechanisms of dissipation is thus
brought to light. We find that for high initial velocities the friction force
is constant. As the velocity decreases below a certain threshold the friction
becomes viscous.Comment: 8 pages RevTeX, 12 Postscript figure
Photochemical routes to silicon epitaxy
The photochemistry of Si2H6 adsorbed on a hydrogen terminated silicon surface and the subsequentreactions of the photolysis products were investigated using high resolution electron energy lossspectroscopy and by measuring time-of-flight distributions with a mass spectrometer. The crackingpattern of the products ejected directly into the gas phase without colliding with either the surfaceor other molecules indicates that the primary photolysis channels yield mostly fragments thatcontain one silicon atom. It is likely that silicon is added to the surface by insertion of SiH2 radicalsinto Si–H bonds at the surface but there is little evidence for reactions that remove excess hydrogenfrom the surface at 110
Instability of dilute granular flow on rough slope
We study numerically the stability of granular flow on a rough slope in
collisional flow regime in the two-dimension. We examine the density dependence
of the flowing behavior in low density region, and demonstrate that the
particle collisions stabilize the flow above a certain density in the parameter
region where a single particle shows an accelerated behavior. Within this
parameter regime, however, the uniform flow is only metastable and is shown to
be unstable against clustering when the particle density is not high enough.Comment: 4 pages, 6 figures, submitted to J. Phys. Soc. Jpn.; Fig. 2 replaced;
references added; comments added; misprints correcte
Redrafting Ohio\u27s Advance Directive Laws
The Bioethics Network of Ohio (BENO) held its second annual conference on June 12, 1992 at Ohio Dominican College, Columbus, Ohio. Attendees recommended that a Task Force\u27 review Ohio\u27s Durable Power of Attorney for Health Care (DPAHC) and Modified Uniform Rights for the Terminally Ill (MURTIA) laws and suggest changes that would retain the basic structure of these provisions but also simplify and clarify their meaning. The Task Force completed a draft in six months and circulated it to approximately 450 individual and institutional BENO members. About one hundred members responded and this article incorporates most of their comments
Effect of Workflow Improvements in Endovascular Stroke Treatment A Systematic Review and Meta-Analysis
Background and Purpose—Rapid initiation of endovascular stroke treatment is associated with better clinical outcome.
The effect of specific improvements is not well known. We performed a systematic review and meta-analysis on the
effectiveness of specific workflow improvements on time to treatment and outcome.
Methods—A random-effects meta-analysis was used to evaluate the difference in mean time to treatment between
intervention group and control group. Secondary outcomes included good functional outcome at 90 days (modified
Rankin Scale score 0–2).
Results—Fifty-one studies (3 randomized controlled trials, 13 prepost intervention studies, and 35 observational studies)
with in total 8467 patients were included. Most frequently reported workflow intervention types concerned anesthetic
management (n=26), in-hospital patient transfer management (n=14), and prehospital management (n=11). Patients in
the intervention group had shorter time to treatment intervals (weighted mean difference, 26 minutes; 95% CI, 19–33;
P<0.001) compared with controls. Subgroup meta-analysis of intervention types also showed a shorter time to treatment
in the intervention group: a mean difference of 12 minutes (95% CI, 6–17; P<0.001) for anesthetic management, 37
minutes (95% CI, 22–52; P<0.001) for prehospital management, 41 minutes (95% CI, 27–54; P<0.001) for in-hospital
patient transfer management, 47 minutes (95% CI, 28–67; P<0.001) for teamwork, and 64 minutes (95% CI, 24–104;
P=0.002) for feedback. The mean difference in time to treatment of studies with multiple interventions implemented
simultaneously was 50 minutes (95% CI, 31–69; P<0.001) in favor of the intervention group. Patients in the intervention
group had increased likelihood of favorable outcome (risk ratio [RR], 1.39; 95% CI, 1.15–1.66; P<0.001).
Conclusions—Interventions in the workflow of endovascular stroke treatment lead to a significant reduction in time to
treatment and results in an increased likelihood of favorable outcome. Acute stroke care should be reorganized by
making use of the examples of workflow interventions described in this review to ensure the best medical care for stroke
patients
Prediction of final infarct volume from native CT perfusion and treatment parameters using deep learning
CT Perfusion (CTP) imaging has gained importance in the diagnosis of acute
stroke. Conventional perfusion analysis performs a deconvolution of the
measurements and thresholds the perfusion parameters to determine the tissue
status. We pursue a data-driven and deconvolution-free approach, where a deep
neural network learns to predict the final infarct volume directly from the
native CTP images and metadata such as the time parameters and treatment. This
would allow clinicians to simulate various treatments and gain insight into
predicted tissue status over time. We demonstrate on a multicenter dataset that
our approach is able to predict the final infarct and effectively uses the
metadata. An ablation study shows that using the native CTP measurements
instead of the deconvolved measurements improves the prediction.Comment: Accepted for publication in Medical Image Analysi
Impact of guidelines for the management of minor head injury on the utilization and diagnostic yield of CT over two decades, using natural language processing in a large dataset
Objectives We investigated the impact of clinical guidelines for the management of minor head injury on utilization and
diagnostic yield of head CT over two decades.
Methods Retrospective before-after study using multiple electronic health record data sources. Natural language processing
algorithms were developed to rapidly extract indication, Glasgow Coma Scale, and CT outcome from clinical records, creating
two datasets: one based on all head injury CTs from 1997 to 2009 (n = 9109), for which diagnostic yield of intracranial traumatic
findings was calculated. The second dataset (2009–2014) used both CT reports and clinical notes from the emergency department, enabling selection of minor head injury patients (n = 4554) and calculation of both CT utilization and diagnostic yield.
Additionally, we tested for significant changes in utilization and yield after guideline implementation in 2011, using chi-square
statistics and logistic regression.
Results The yield was initially nearly 60%, but in a decreasing trend dropped below 20% when CT became routinely used for
head trauma. Between 2009 and 2014, of 4554 minor head injury patients overall, 85.4% underwent head CT. After guideline
implementation in 2011, CT utilization significantly increased from 81.6 to 87.6% (p = 7 × 10−7
), while yield significantly
decreased from 12.2 to 9.6% (p = 0.029).
Conclusions The number of CTs performed for head trauma gradually increased over two decades, while the yield decreased. In 2011,
despite implementation of a guideline aiming to improve selective use of CT in minor head injury, utilization significantly increased
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