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- Description:
- Objectives: Falls in hospitals pose a significant safety risk, leading to injuries, prolonged hospitalization, and lasting complications. This study explores the potential of augmented reality (AR) technology in healthcare facility design to mitigate fall risk. Background: Few studies have investigated the impact of hospital room layouts on falls due to the high cost of building physical prototypes. This study introduces an innovative approach using AR technology to advance methods for healthcare facility design efficiently. Methods: Ten healthy participants enrolled in this study to examine different hospital room designs in AR. Factors of interest included room configuration, door type, exit side of the bed, toilet placement, and the presence of IV equipment. AR trackers captured trajectories of the body as participants navigated through these AR hospital layouts, providing insights into user behavior and preferences. Results: Door type influenced the degree of backward and sideways movement, with the presence of an IV pole intensifying the interaction between door and room type, leading to increased sideways and backward motion. Participants displayed varying patterns of backward and sideways travel depending on the specific room configurations they encountered. Conclusions: AR can be an efficient and cost-effective method to modify room configurations to identify important design factors before conducting physical testing. The results of this study provide valuable insights into the effect of environmental factors on movement patterns in simulated hospital rooms. These results highlight the importance of considering environmental factors, such as the type of door and bathroom location, when designing healthcare facilities.
- Keyword:
- hospital room and fall prevention
- Subject:
- Patients' Rooms and Accident Prevention
- Creator:
- Seddighi, Nooshin, Fino, Peter C. , and Wong, Bob
- Owner:
- Madison Golden
- Based Near Label Tesim:
- University of Utah, Utah, United States
- Language:
- English
- Date Uploaded:
- 11/09/2023
- Date Modified:
- 10/29/2024
- Date Created:
- 2022-07-14 to 2022-11-18
- License:
- Other – See README file for more information.
- Resource Type:
- Dataset
- Identifier:
- http://doi.org/10.7278/S50d-evm5-vh17
-
- Description:
- Classification of barrier island morphology stems from the seminal work of M. O. Hayes and others, which linked island shape to tidal range and wave height and defined coastal energy regimes (i.e., wave-dominated, mixed energy, tide-dominated). If true, this general relationship represents a process-based framework to link modern and ancient systems, and is key for determining paleomorphodynamic relationships. Here we present a new semi-global database of barrier islands and spits (n = 702). Shape parameters (aspect, circularity, and roundness) are used to quantify island boundary shape, and assess potential correlation with coastal energy regime using global wave and tide models. In adopting the original energy classification as originally put forth (i.e., wave dominated, wave-influenced mixed, tide-influenced mixed, tide dominated), results show that wave-dominated islands have statistically different mean shape values from those in the mixed energy fields, but the two mixed energy designations are not distinct from each other. Furthermore, each energy regime field contains a wide range of island shapes, with no clear trends present. Linear regression modeling shows that tidal range and wave height account for < 10% of the documented variance in island shape, a strong indication that other controls must be considered. Therefore, while energy regime distinctions can be used descriptively, their utility in predicting and constraining island shape is limited: barrier island shape is not indicative of coastal energy regime, and vice versa. Our analysis also demonstrates empirical scaling relationships among modern barrier islands for the first time, with implications for subsurface prediction. and This is the dataset of the Modern Barrier Island Database published in Mulhern et al., 2017 Marine Geology paper titled "Is Barrier Island Morphology a Function of Wave and Tide Regime?" with the DOI https://doi.org/10.1016/j.margeo.2017.02.016. If using this dataset please cite both the dataset and the paper.
- Keyword:
- paleomorphodynamic relationships, geology, barrier island, shallow marine, island shape, wave-dominated islands, shoreline morphology, Modern Barrier Island Database, and coastal geomorphology
- Subject:
- Geology
- Creator:
- Johnson, Cari L., Mulhern, Julia S., and Martin, John M.
- Owner:
- Julia Mulhern
- Language:
- English
- Date Uploaded:
- 09/08/2021
- Date Modified:
- 06/03/2024
- Date Created:
- 2015-01-01 to 2017-12-31
- License:
- CC BY NC - Allows others to use and share your data non-commercially and with attribution.
- Resource Type:
- Dataset
- Identifier:
- https://doi.org/10.7278/S50d-5pzj-r9vr
-
- Description:
- While several studies have qualitatively investigated age- and region-dependent adhesion between the vitreous and retina, no studies have directly measured the vitreoretinal strength of adhesion. In this study, we developed a rotational peel device and associated methodology to measure the maximum and steady-state peel forces between the vitreous and the retina. Vitreoretinal adhesion in the equator and posterior pole were measured in human eyes from donors ranging 30 to 79 years of age, and in sheep eyes from premature, neonatal, young lamb, and young adult sheep. In human eyes, maximum peel force in the equator (7.24 ± 4.13 mN) was greater than in the posterior pole (4.08 ± 2.03 mN). This trend was especially evident for younger eyes from donors 30 to 39 years of age. After 60 years of age, there was a significant decrease in the maximum equatorial (4.69 ± 2.52 mN, p = 0.016) and posterior pole adhesion (2.95 ± 1.25 mN, p = 0.037). In immature sheep eyes, maximum adhesion was 7.60 ± 3.06 mN, and did not significantly differ between the equator and posterior pole until young adulthood. At this age, the maximum adhesion in the equator nearly doubled (16.67 ± 7.45 mN) that of the posterior pole, similar to the young adult human eyes. Light microscopy images suggest more disruption of the inner limiting membrane (ILM) in immature sheep eyes compared to adult sheep eyes. Interestingly, in human eyes, ILM disruption was significantly greater in the posterior pole (p < 0.05) and in people over 60 years of age (p < 0.02). These findings supplement the current discussion surrounding age-related posterior vitreous detachment, and the risk factors and physiological progressions associated with this condition. In addition, these data further our understanding of the biomechanical mechanisms of vitreoretinal adhesion, and can be used to develop age- appropriate computational models simulating retinal detachment, hemorrhaging, or retinal trauma. See Creveling CJ, Colter J, Coats B. 2018. Changes in vitreoretinal adhesion with age and region in human and sheep eyes. Frontiers in Bioengineering and Biotechnology 6. https://doi.org/10.3389/fbioe.2018.00153.
- Keyword:
- ophthalmology, retina, vitreous, adhesion, ocular, human, eye, peel test, and sheep
- Subject:
- Quantitative measurement and Vitreoretinal adhesion
- Creator:
- Coats, Brittany and Creveling, Christopher
- Contributor:
- Colter, Jourdan
- Owner:
- BRIAN MCBRIDE
- Based Near Label Tesim:
- Salt Lake City, Utah, United States
- Language:
- English
- Date Uploaded:
- 07/10/2019
- Date Modified:
- 06/03/2024
- Date Created:
- Completed 2017-06-01
- License:
- CC BY – Allows others to use and share your data, even commercially, with attribution.
- Resource Type:
- Image, Dataset, and Video
- Identifier:
- https://doi.org/10.7278/S5BK19H3
-
- Description:
- This dataset is a custom Kraken2 formatted database for the identification of Fungi from shotgun metagenomic data. Kraken2 is a k-mer based read classifier (Wood et al. 2019; https://genomebiology.biomedcentral.com/articles/10.1186/s13059-019-1891-0). The dataset was built with the default k-mer length (k=35) from all publicly available fungal genomes at JGI Mycocosm ( https://mycocosm.jgi.doe.gov/mycocosm/home), and all archaea, bacteria, viral, plasmid, human, fungi, plant, and protozoa genomes, as well as the UniVec Core and nt reference database at NCBI ( https://www.ncbi.nlm.nih.gov/). The reference genomes and sequences were downloaded from JGI and NCBI in March 2020.
- Keyword:
- protozoa, Kraken2 database, plant, bacteria, genomes, fungi, human, archaea, plasmid, and virus
- Subject:
- Mycology and Genomics
- Creator:
- Dentinger, Bryn T. M.
- Owner:
- Bryn Dentinger
- Language:
- English
- Date Uploaded:
- 06/08/2022
- Date Modified:
- 06/03/2024
- Date Created:
- 2020-03-29
- License:
- CC BY NC - Allows others to use and share your data non-commercially and with attribution.
- Resource Type:
- Software or Program Code and Dataset
- Identifier:
- https://doi.org/10.7278/S50d-154b-fppf
-
- Description:
- Data were collected from the free online available International Ionosphere Reference (IRI) database ( https://kauai.ccmc.gsfc.nasa.gov/instantrun/iri) for January 1, 2020. The data were then interpolated from 1km to our desired resolution of 0.1km. This is is profile used to simulate the 3D FDTD models to observe the propagation of power line harmonic radiation through the ionosphere.
- Keyword:
- Ionosphere and Inhomogeneous Ionosphere
- Subject:
- FDTD (mathematics), plasmas (physics) , and ionospheric electron density
- Creator:
- Pedgaonkar, Apoorva
- Owner:
- Based Near Label Tesim:
- Salt Lake City, Utah, United States
- Language:
- English
- Date Uploaded:
- 07/12/2024
- Date Modified:
- 09/06/2024
- Date Created:
- 2020-01-20
- License:
- Public Domain – This data is free of copyright restrictions (e.g. government sponsored data).
- Resource Type:
- Dataset
- Identifier:
- http://doi.org/10.7278/S5d-hpp0-g1wy
-
- Description:
- This dataset summarizes burial counts according to burial type (free, temporary, or perpetual) for the cemeteries of Père-Lachaise, Montmartre, and Montparnasse in Paris. The data covers the period of 1804 to 1840 and was derived from the digitized daily records of burial for the city of Paris, which are currently held in the Archives de Paris. See Registres journaliers d'inhumation https://archives.paris.fr/r/216/cimetieres). These data are organized by the number of each burial type recorded per page of the digitized records.
- Keyword:
- Paris, burial, Montparnasse, and Pere-Lachaise
- Subject:
- Paris, Montparnasse, and Père-Lachaise, Cimetière du
- Creator:
- Alexander, Kaylee P.
- Owner:
- Kaylee Alexander
- Based Near Label Tesim:
- Paris, Île-de-France, France
- Language:
- English
- Date Uploaded:
- 02/11/2023
- Date Modified:
- 06/03/2024
- Date Created:
- 2019-01-01 to 2021-01-01
- License:
- CC BY NC - Allows others to use and share your data non-commercially and with attribution.
- Resource Type:
- Dataset
- Identifier:
- https://doi.org/10.7278/S50d-d18q-yfzt
-
- Description:
- This dataset is based on the 1816, two-volume publication, Le champ du repos, ou le Cimetière Mont-Louis, dit du Père Delachaise. Compiled over the course of 1815 by MM. Roger and Roger (a father-son team), Le champ du repos contains the epitaphs and scale drawing of over 2000 monuments present in the cemetery of Père-Lachaise (Paris, France) by the end of 1815. The author of this dataset has combined the information from this volume (including demographics of the deceased drawn from epitaphs, visual characteristics of monuments, and the locations of monuments within the cemetery) with data from the digitized records of burial available from the Archives de Paris ( https://archives.paris.fr/r/216/cimetieres/). Thus, this dataset details every known monument present in the Cemetery of Père-Lachaise by the end of 1815 with information about the type of burial (free, temporary, or perpetual) that it marked.
- Keyword:
- Paris, France, tombstones, cemeteries, Pere-Lachaise, nineteenth centry, epitaphs, and monuments
- Subject:
- funerary structures, cemeteries, and nineteenth century (dates CE)
- Creator:
- Alexander, Kaylee P.
- Owner:
- Kaylee Alexander
- Language:
- English, French
- Date Uploaded:
- 01/27/2023
- Date Modified:
- 06/05/2024
- Date Created:
- 2021-01-01
- License:
- CC BY NC - Allows others to use and share your data non-commercially and with attribution.
- Resource Type:
- Dataset
- Identifier:
- https://doi.org/10.7278/S50d-4cbs-yrv1
-
- Description:
- Forests play a major role in the global carbon cycle. Previous studies on the capacity of forests to sequester atmospheric CO2 have mostly focused on carbon uptake, but the roles of carbon turnover time and its spatiotemporal changes remain poorly understood. Here, we used long-term inventory data (1955-2018) from 695 mature forest plots to quantify temporal trends in living vegetation carbon turnover time across tropical, temperate, and cold climate zones, and compared plot data to eight Earth system models (ESMs). Long-term plots consistently showed decreases in living vegetation carbon turnover time, likely driven by increased tree mortality across all major climate zones. Changes in living vegetation carbon turnover time were negatively correlated with CO2 enrichment in both forest plot data and ESM simulations. However, plot-based correlations between living vegetation carbon turnover time and climate drivers such as precipitation and temperature diverged from those of ESM simulations. Our analyses suggest that forest carbon sinks are likely to be constrained by a decrease in living vegetation carbon turnover time, and accurate projections of forest carbon sink dynamics will require an improved representation of tree mortality processes and their sensitivity to climate in ESMs.
- Keyword:
- tree mortality, forest carbon stocks, carbon turnover, forest productivity, cold climate zone, tropical climate zone, climate change, carbon cycle, temperate climate zone, and earth system models
- Subject:
- Forestry
- Creator:
- Anderegg, William R.L., Schraub, Marcus, Yu, Kailiang, Gessler, Arthur, Penuelas, Josep, Cailleret, Maxine, Peng, Changhui, Condit, Richard, Ferretti, Marco, Hubbell, Stephen P., Smith, William K., Sardans, Jordi, Levanic, Tom, Zhu, Kai, and Trugman, Anna T.
- Owner:
- KAILIANG YU
- Language:
- English
- Date Uploaded:
- 10/24/2019
- Date Modified:
- 10/29/2024
- Date Created:
- 2018–2019
- License:
- CC BY NC - Allows others to use and share your data non-commercially and with attribution.
- Resource Type:
- Dataset
- Identifier:
- https://doi.org/doi:10.7278/S50D-D656-FSP2
-
- Description:
- Thin boundary layer Arctic mixed-phase clouds are generally thought to precipitate pristine and aggregate ice crystals. Here we present automated surface photographic measurements showing that only 35\% of precipitation particles exhibit negligible riming and that graupel particles $\geq1\,\rm{mm}$ in diameter commonly fall from clouds with liquid water paths less than $50\,\rm{g\,m^{-2}}$. A simple analytical formulation predicts that significant riming enhancement can occur in updrafts with speeds typical of Arctic clouds, and observations show that such conditions are favored by weak temperature inversions and strong radiative cooling at cloud top. However, numerical simulations suggest that a mean updraft speed of $0.75\,\rm{m\,s^{-1}}$ would need to be sustained for over one hour. Graupel can efficiently remove moisture and aerosols from the boundary layer. The causes and impacts of Arctic riming enhancement remain to be determined.
- Keyword:
- computational research, radiative transfer, microwave radiometer, liquid water path, graupel, Alaska, atmospheric radiation measurement, water vaper, atmospheric sciences, and arctic
- Subject:
- Atmospheric sciences, Computational research, and Arctic research
- Creator:
- Garrett, Timothy J. and Fitch, Kyle E.
- Contributor:
- Shkurko, Konstantin , Talaei, Ahmad, Gaustad, Krista, and Maahn, Maximilian
- Owner:
- BRIAN MCBRIDE
- Based Near Label Tesim:
- Oliktok Point, Alaska, United States
- Language:
- English
- Date Uploaded:
- 06/04/2020
- Date Modified:
- 10/25/2024
- Date Created:
- Code creation: 2016-12-08 to 2018-06-09, Processed: 2017-06-27, and Processed: 2019-03-20
- License:
- CC BY NC - Allows others to use and share your data non-commercially and with attribution.
- Resource Type:
- Software or Program Code and Dataset
- Identifier:
- https://doi.org/10.7278/s50dva5jk2pd
-
- Description:
- Weather-related research often requires synthesizing vast amounts of data that need archival solutions that are both economical and viable during and past the lifetime of the project. Public cloud computing services (e.g., from Amazon, Microsoft, or Google) or private clouds managed by research institutions are providing object data storage systems appropriate for long-term archives of such large geophysical data sets. , Current Status: Our research group no longer needs to maintain archives of High Resolution Rapid Refresh (HRRR) model output at the University of Utah since complete publicly-accessible archives of HRRR model output are now available from the Google Cloud Platform and Amazon Web Services (AWS) as part of the NOAA Open Data Program. Google and AWS store the HRRR model output in GRIB2 format, a file type that efficiently stores hundreds of two-dimensional variable fields for a single valid time. Despite the highly compressible nature of GRIB2 files, they are often on the order of several hundred MB each, making high-volume input/output applications challenging due to the memory and compute resources needed to parse these files. With support from the Amazon Sustainability Data Initiative, our group is now creating and maintaining HRRR model output in an optimized format, Zarr, in a publicly-accessible S3 bucket- hrrrzarr. HRRR-Zarr contains sets for each model run of analysis and forecast files sectioned into 96 small chunks for every variable. The structure of the HRRR-Zarr files are designed to allow users the flexibility to access only the data they need through selecting subdomains and parameters of interest without the overhead that comes from accessing numerous GRIB2 files. , and History: This effort began in 2015 to illustrate the use of a private cloud object store developed by the Center for High Performance Computing (CHPC) at the University of Utah. We began archiving thousands of two-dimensional gridded fields (each one containing over 1.9 million values over the contiguous United States) from the High-Resolution Rapid Refresh (HRRR) data assimilation and forecast modeling system. The archive has been used for retrospective analyses of meteorological conditions during high-impact weather events, assessing the accuracy of the HRRR forecasts, and providing initial and boundary conditions for research simulations. The archive has been accessible interactively and through automated download procedures for researchers at other institutions that can be tailored by the user to extract individual two-dimensional grids from within the highly compressed files. Over a thousand users have voluntarily registered to use the HRRR archive at the University of Utah. Our archive has grown to over 130 Tbytes of model output but we no longer need to continue that effort since the GRIB2 files are available now via Google and AWS. As mentioned above, we now provide much of the same information in an alternative format that is appropriate particularly for machine-learning applications.
- Keyword:
- data assimilation, Zarr, weather, forecasts, high resolution rapid refresh, and numerical weather prediction
- Subject:
- atmospheric science
- Creator:
- Horel, John and Blaylock, Brian
- Contributor:
- University of Utah Center for High Performance Computing, NOAA Earth Systems Research Laboratory, Amazon Open Data Program, and NOAA Environmental Modeling Center
- Depositor:
- BRIAN MCBRIDE
- Owner:
- JOHN HOREL
- Based Near Label Tesim:
- Alaska, Alaska, United States and United States, , United States
- Language:
- binary and English
- Date Uploaded:
- 07/10/2019
- Date Modified:
- 04/18/2024
- Date Created:
- 2015-04-18 to 2019-07-10
- License:
- CC BY – Allows others to use and share your data, even commercially, with attribution.
- Resource Type:
- Dataset
- Identifier:
- https://dx.doi.org/10.7278/S5JQ0Z5B