Investigating Geospatial Holograms for Special Weapons and Tactics Teams

2009 ◽  
pp. 5-19 ◽  
Author(s):  
Sven Fuhrmann ◽  
Nevada J. Smith ◽  
Mark Holzbach ◽  
Terry Nichols
Keyword(s):  
Pilot Study ◽  
Three Dimensional ◽  
Route Planning ◽  
Team Members ◽  
Spatial Features ◽  
Usability Tests ◽  
Design Requirements ◽  
Swat Team ◽  
Point Light ◽  
Initial Research

Special Weapons and Tactics (SWAT) teams rely heavily on collecting and applying geospatial intelligence. Traditional two-dimensional mapping products might limit or hinder successful operations by not showing important three-dimensional information of the terrain and its natural and/or human-built objects. Geospatial holograms are able to display these three dimensional spatial features to users without requiring special eyewear or using complex viewing technologies. A point light source is all that is required to make the imagery visible. Before introducing geospatial holograms into the SWAT domain, where lives are at potential risk, a series of usefulness, acceptance, and usability tests need to be performed. One of the key geospatial hologram design requirements identified for SWAT incidents was support for effective route planning and wayfinding. This paper will report about a first pilot study that investigated and compared wayfinding performance of SWAT teams using both traditional 2D imagery and geospatial holograms. Our initial research indicates that geospatial holograms could enhance SWAT operations, especially in multi-story environments. In the pilot study geospatial holograms were positively reviewed by SWAT team members and were described as a technology that should be further explored.

scholarly journals 1326. Vancomycin Area Under the Concentration-Time Curve (AUC) Estimation Using a Bayesian Approach Versus First-Order Pharmacokinetic Equations: A Pilot Study

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S673-S673
Author(s):  
Jeffrey Pearson ◽  
Yazed S Alsowaida ◽  
B S Pharm ◽  
David W Kubiak ◽  
Mary P Kovacevic ◽  
...  
Keyword(s):  
Pilot Study ◽  
Median Time ◽  
Bayesian Modeling ◽  
Surgical Prophylaxis ◽  
Time Curve ◽  
Team Members ◽  
First Order ◽  
Concentration Time ◽  
Study Team ◽  
Auc Estimation

Abstract Background Current guidelines endorse area under the concentration-time curve (AUC)-based monitoring over trough-only monitoring for systemic vancomycin. Vancomycin AUC can be estimated using either Bayesian modeling software or first-order pharmacokinetic (PK) calculations. The objective of this pilot study was to evaluate and compare the efficiency and feasibility of these two approaches for calculating the estimated vancomycin AUC. Methods A single-center crossover study was conducted in four medical/surgical units at Brigham and Women’s Hospital over a 3-month time period. All adult patients who received vancomycin were included. Patients were excluded if they were receiving vancomycin for surgical prophylaxis, were on hemodialysis, if vancomycin was being dosed by level, or if vancomycin levels were never drawn. The primary endpoint was the amount of time study team members spent calculating the estimated AUC and determining regimen adjustments with Bayesian modeling compared to first-order PK calculations. Secondary endpoints included the number of vancomycin levels drawn and the percent of those drawn that were usable for AUC calculations. Results One hundred twenty-four patients received vancomycin during the study, of whom 47 met inclusion criteria. The most likely reasons for exclusion were receiving vancomycin for surgical prophylaxis (n=40) or never having vancomycin levels drawn (n=32). The median time taken to assess levels in the Bayesian arm was 9.3 minutes [interquartile range (IQR) 7.8-12.4] versus 6.8 minutes (IQR 4.8-8.0) in the 2-level PK arm (p=0.004). However, if Bayesian software is integrated into the electronic health record (EHR), the median time to assess levels was 3.8 minutes (IQR 2.3-6.8, p=0.019). In the Bayesian arm, 30 of 34 vancomycin levels (88.2%) were usable for AUC calculations, compared to 28 of 58 (48.3%) in the 2-level PK arm. Conclusion With EHR integration, the use of Bayesian software to calculate the AUC was more efficient than first-order PK calculations. Additionally, vancomycin levels were more likely to be usable in the Bayesian arm, thereby avoiding delays in estimating the vancomycin AUC. Disclosures All Authors: No reported disclosures

Constructive Distributed Work: An Integrated Approach to Sustainable Collaboration and Research for Distributed Teams

2021 ◽  
pp. 105065192110214
Author(s):  
Michelle McMullin ◽  
Bradley Dilger
Keyword(s):  
Best Practices ◽  
Team Building ◽  
Three Dimensional ◽  
Integrated Approach ◽  
Interdisciplinary Teams ◽  
Digital Tools ◽  
Distributed Teams ◽  
Distributed Work ◽  
Team Members ◽  
Negative Impacts

Academic work increasingly involves creating digital tools with interdisciplinary teams distributed across institutions and roles. The negative impacts of distributed work are described at length in technical communication scholarship, but such impacts have not yet been realized in collaborative practices. By integrating attention to their core ethical principles, best practices, and work patterns, the authors are developing an ethical, sustainable approach to team building that they call constructive distributed work. This article describes their integrated approach, documents the best practices that guide their research team, and models the three-dimensional thinking that helps them develop sustainable digital tools and ensure the consistent professional development of all team members.

Impact of Three-Dimensional Printed Pelvicaliceal System Models on Residents' Understanding of Pelvicaliceal System Anatomy Before Percutaneous Nephrolithotripsy Surgery: A Pilot Study

2016 ◽  
Vol 30 (10) ◽  
pp. 1132-1137 ◽  
Author(s):  
Hasan Anıl Atalay ◽  
Volkan Ülker ◽  
İlter Alkan ◽  
Halil Lütfi Canat ◽  
Ünsal Özkuvancı ◽  
...  
Keyword(s):  
Pilot Study ◽  
Three Dimensional ◽  
System Models ◽  
Percutaneous Nephrolithotripsy

scholarly journals Protein-protein docking using learned three-dimensional representations

2019 ◽  
Author(s):  
Georgy Derevyanko ◽  
Guillaume Lamoureux
Keyword(s):  
Protein Interactions ◽  
Network Architecture ◽  
Protein Complexes ◽  
Three Dimensional ◽  
Spatial Arrangement ◽  
Protein Docking ◽  
Protein Protein Interactions ◽  
Translational Invariance ◽  
Shape Complementarity ◽  
Spatial Features

AbstractProtein-protein interactions are determined by a number of hard-to-capture features related to shape complementarity, electrostatics, and hydrophobicity. These features may be intrinsic to the protein or induced by the presence of a partner. A conventional approach to protein-protein docking consists in engineering a small number of spatial features for each protein, and in minimizing the sum of their correlations with respect to the spatial arrangement of the two proteins. To generalize this approach, we introduce a deep neural network architecture that transforms the raw atomic densities of each protein into complex three-dimensional representations. Each point in the volume containing the protein is described by 48 learned features, which are correlated and combined with the features of a second protein to produce a score dependent on the relative position and orientation of the two proteins. The architecture is based on multiple layers of SE(3)-equivariant convolutional neural networks, which provide built-in rotational and translational invariance of the score with respect to the structure of the complex. The model is trained end-to-end on a set of decoy conformations generated from 851 nonredundant protein-protein complexes and is tested on data from the Protein-Protein Docking Benchmark Version 4.0.

scholarly journals Workload implications for clinic workflow with implementation of three-dimensional printed customized bolus for radiation therapy: A pilot study

PLoS ONE ◽  
2018 ◽  
Vol 13 (10) ◽  
pp. e0204944 ◽  
Author(s):  
Eric Ehler ◽  
David Sterling ◽  
Kathryn Dusenbery ◽  
Jessica Lawrence
Keyword(s):  
Radiation Therapy ◽  
Pilot Study ◽  
Three Dimensional
Sign in / Sign up

Export Citation Format

Share Document