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- Description:
- This is a data set for generating current densities used for the validation of two methods. Similarly, it gives the electric fields for the 80-minute validation of the two methods. Furthermore, the partial transfer function method calculated electric fields are also deposited in this dataset. Similarly, the spectrum of each source and impulse response obtained from the FDTD model are also included. Finally, the electric fields were obtained for 8 hours using the PTF method.
- Keyword:
- FDTD, Geoelectric fields, Partial transfer function, and Long-time span
- Subject:
- geoelectricity and finite difference time domain method
- Creator:
- Sharma Paneru, Prashanna
- Owner:
- Based Near Label Tesim:
- Salt Lake City, Utah, United States
- Language:
- English
- Date Uploaded:
- 11/08/2024
- Date Modified:
- 11/11/2024
- Date Created:
- 2024-01-01 to 2024-11-08
- License:
- Public Domain – This data is free of copyright restrictions (e.g. government sponsored data).
- Resource Type:
- Dataset
- Identifier:
- https://doi.org/10.7278/S5d-ev5n-d1v5
-
- Description:
- The objective of using the wireless sensors was to improve understanding of the heterogeneity of healthcare worker (HCW) contact with patients and the physical environment in patients’ rooms. The framework and design were based on contact networks with a) nodes defined by HCW’s, rooms, and items in the room and b) edges defined by HCW’s in the room, near the bed, and touching items. Nodes had characteristics of HCW role and room number. Edges had characteristics of day, start time, and duration. Thus, patterns and heterogeneity could be understood within contexts of time, space, roles, and patient characteristics. At the University of Utah Hospital Cardiovascular ICU (CVICU), a 20-bed unit, we collected data for 54 days. HCW contact with patients was measured using wireless sensors to capture time spent in patient rooms as well as time spent near the patient bed. HCW contact with the physical environment was measured using wireless sensors on the following items in patient rooms: door, sink, toilet, over-bed table, keyboard, vital signs monitor touchscreen, and cart. HCW’s clipped a sensor to their clothing or lanyard. This dataset contains cleaned sensor pings of RFD reads between healthcare worker worn sensors and environmental sensors placed in facility using methods described in the "Data Cleaning Steps" section.
- Keyword:
- patient contact and wireless sensors
- Subject:
- cardiology
- Creator:
- Rubin, Michael, Haroldsen, Candace, and Leecaster, Molly
- Contributor:
- Huber, Tavis and Stratford, Kristina
- Owner:
- Michael Rubin
- Based Near Label Tesim:
- Salt Lake City, Utah, United States
- Language:
- English
- Date Uploaded:
- 12/26/2023
- Date Modified:
- 11/05/2024
- Date Created:
- 2018-01-01 to 2018-12-31
- License:
- CC BY NC - Allows others to use and share your data non-commercially and with attribution.
- Resource Type:
- Dataset
- Identifier:
- www.doi.org/10.7278/S50d-twbh-955q
-
- Description:
- The objective of using the wireless sensors was to improve understanding of the heterogeneity of healthcare worker (HCW) contact with patients and the physical environment in patients’ rooms. The framework and design were based on contact networks with a) nodes defined by HCW’s, rooms, and items in the room and b) edges defined by HCW’s in the room, near the bed, and touching items. Nodes had characteristics of HCW role and room number. Edges had characteristics of day, start time, and duration. Thus, patterns and heterogeneity could be understood within contexts of time, space, roles, and patient characteristics. At the University of Utah Hospital Cardiovascular ICU (CVICU), a 20-bed unit, we collected data for 54 days. HCW contact with patients was measured using wireless sensors to capture time spent in patient rooms as well as time spent near the patient bed. HCW contact with the physical environment was measured using wireless sensors on the following items in patient rooms: door, sink, toilet, over-bed table, keyboard, vital signs monitor touchscreen, and cart. HCW’s clipped a sensor to their clothing or lanyard. This dataset contains cleaned event-level data processed from sensor pings of RFD reads between healthcare worker worn sensors and environmental sensors placed in facility using methods described in the "Data Cleaning Steps" section.
- Keyword:
- patient contact and wireless sensors
- Subject:
- cardiology
- Creator:
- Leecaster, Molly, Rubin, Michael, and Haroldsen, Candace
- Contributor:
- Huber, Tavis and Stratford, Kristina
- Owner:
- Michael Rubin
- Based Near Label Tesim:
- Salt Lake City, Utah, United States
- Language:
- English
- Date Uploaded:
- 12/26/2023
- Date Modified:
- 11/05/2024
- Date Created:
- 2018-01-01 to 2018-12-31
- License:
- CC BY NC - Allows others to use and share your data non-commercially and with attribution.
- Resource Type:
- Dataset
- Identifier:
- www.doi.org/10.7278/S50d-hmxz-4bf1
-
- Description:
- This dataset contains room occupancy during the study period at University of Utah hospital. Admission, Discharge, and Transfer (ADT) data is captured in participating hospitals to characterize room occupancy and non-occupancy in wards. These data are pulled from multiple sources collected during the study by study staff as well as harvested EHR data. Data were adjudicated and compiled into one comprehensive file. Data manipulation included redaction of dates, replaced with study days 1-n, as well as transformation from long format to wide for ease of use.
- Keyword:
- bed occupancy, transfer, discharge, ADT, and admission
- Subject:
- bed occupancy
- Creator:
- Haroldsen, Candace, Rubin, Michael, and Leecaster, Molly
- Contributor:
- Huber, Tavis and Stratford, Kristina
- Owner:
- Michael Rubin
- Based Near Label Tesim:
- Salt Lake City, Utah, United States
- Language:
- English
- Date Uploaded:
- 12/26/2023
- Date Modified:
- 11/05/2024
- Date Created:
- 2018-01-01 to 2018-12-31
- License:
- CC BY NC - Allows others to use and share your data non-commercially and with attribution.
- Resource Type:
- Dataset
- Identifier:
- www.doi.org/10.7278/S50d-6wz0-jk8j
-
- Description:
- This dataset provides access to data from personnel records of miner employment from 1900–1919. Records from the Utah Copper Company are handwritten and contain the following employee information: name, date employed, address, dependents, age, weight, height, eyes, hair, gender, and nationality. Data has been transcribed and released as a .tsv (Tab Separated Values) file. Technical metadata has been redacted.
- Keyword:
- mining, copper miners, Bingham Copper Mine, and labor records
- Subject:
- mining camps, miners, Bingham Copper Mine (Utah), and copper miners
- Creator:
- Neatrour, Anna and Wittmann, Rachel Jane
- Depositor:
- Kaylee Alexander
- Owner:
- ANNA NEATROUR
- Based Near Label Tesim:
- Salt Lake City, Utah, United States
- Language:
- English
- Date Uploaded:
- 11/16/2023
- Date Modified:
- 11/05/2024
- Date Created:
- 1900-01-01 to 1919-12-31 (original data) and 2019-01-01 to 2021-12-31 (transcribed)
- License:
- CCO – As the data author, you are choosing to place your data into the public domain.
- Resource Type:
- Dataset
- Identifier:
- https://doi.org/10.7278/S50d-7zxh-42hf
-
- Description:
- The dataset contains velocity measurements along the fiber optic cable connecting the University of Utah campus to the University of Utah Downtown data center (875 West Temple, Salt Lake City, UT). The data has been collected using the Distributed acoustic sensing (DAS) system that records the vibration signals along 8.4 km long optical fiber every 4.9-m interval with a sampling rate of approximately 1000 Hz. The fiber is mainly installed along the red line of TRAX, which is the light rail system of the Utah Transit Authority. The route intersects the East Bench fault, which is known as an active fault segment of the Wasatch Fault zone. Although no earthquake signals were detected, the velocity data converted to strain rate clearly show the operation of trains between the stations at 450 S Main Street and 900 South 200 West. Analysis of this dataset is expected to provide insights into seismic velocities at shallow depths and structures associated with fault scarps. and See README file for data retrieval instructions.
- Keyword:
- seismology, urban seismology, distributed acoustic sensing, fiber optic cable, and strain rate
- Subject:
- Geophysics, Seismology, Seismology--Observations, and Surface fault ruptures
- Creator:
- Kim, HyeJeong and Lin, Fan-Chi
- Contributor:
- Chambers, Derrick
- Owner:
- Kaylee Alexander
- Based Near Label Tesim:
- Salt Lake City, Utah, United States
- Language:
- English
- Date Uploaded:
- 07/01/2024
- Date Modified:
- 11/05/2024
- Date Created:
- 2023-05-24 to 2023-05-26 (period 1), 2023-08-03 to 2023-08-11 (period 3), 2023-12-22 to 2024-01-02 (period 4), and 2023-06-29 to 2023-07-10 (period 2)
- License:
- CC BY NC - Allows others to use and share your data non-commercially and with attribution.
- Identifier:
- https://doi.org/10.7278/S5d-kgxx-ev8y
-
- Description:
- Atypical atrial flutter is seen post-ablation in patients, and it can be challenging to map. These flutters are typically set up around areas of scar in the left atrium. MRI can reliably identify left atrial scar. We propose a personalized computational model using patient specific scar information, to generate a monodomain model. In the model conductivities are adjusted for different tissue regions and flutter was induced with a premature pacing protocol. The model was tested prospectively in patients undergoing atypical flutter ablation. The simulation-predicted flutters were visualized and presented to clinicians. Validation of the computational model was motivated by recording from electroanatomical mapping. These personalized models successfully predicted clinically observed atypical flutter circuits and at times even better than invasive maps leading to flutter termination at isthmus sites predicted by the model.
- Keyword:
- Biomedical Engineering, Computer Simulation, and Atrial Flutter
- Subject:
- Biomedical Engineering
- Creator:
- Lange, Matthias, Dosdall, Derek J., Kwan, Eugene, MacLeod, Rob S., Bunch, T. Jared, and Ranjan, Ravi
- Owner:
- Matthias Lange
- Based Near Label Tesim:
- Salt Lake City, Utah, United States
- Language:
- English
- Date Uploaded:
- 06/10/2023
- Date Modified:
- 10/29/2024
- Date Created:
- 2020-01-01 to 2022-12-31
- License:
- CC BY – Allows others to use and share your data, even commercially, with attribution.
- Resource Type:
- Dataset
- Identifier:
- https://doi.org/10.7278/S50d-fdna-tekm
-
- Description:
- Background: The objective of this study was to evaluate the effect of utilising larger lens cubes on phacoemulsification efficiency and chatter using 3 tips of different sizes and 2 ultrasound (US) approaches. Methods: This was an in vitro laboratory study conducted at the John A. Moran Eye Center Laboratory, University of Utah, Salt Lake City, UT, USA. Porcine lens nuclei were formalin-soaked for 2 hours, then divided into either 2.0 mm or 3.0 mm cubes. 30 degree bent 19 G, 20 G, and 21 G tips were used with a continuous torsional US system; and straight 19 G, 20 G, and 21 G tips were used with a micropulse longitudinal US system. Efficiency and chatter were determined. Results: Mean phacoemulsification removal time was higher with the 3.0 mm lens cube for all US variations and tip sizes. There were statistically significant differences between the 19 G and 21 G tips with micropulse longitudinal US using the 2.0 mm lens cube and the 3.0 mm lens cube, as well as with continuous transversal US using the 2.0 mm lens cube and the 3.0 mm lens cube. There was no significant difference between 19 G and 20 G tips with either lens cube size in either US approach. However, using both US approaches, trends were identical for both lens cube sizes in which the 19 G tips performed better than the 20 G and 21 G tips. Conclusion: Regardless of lens size, the 19 G needle was the most efficient, with the fewest outliers and smallest standard deviations.
- Keyword:
- vacuum, phacoemulsification, ultrasound, porcine, lens size, and cataract
- Subject:
- ophthalmology
- Creator:
- Barlow, William R., Bernhisel, Ashlie A., Zaugg, Brian, Olson, Randall J., Ramshekar, Aniket, Heczko, Joshua B., and Pettey, Jeff H.
- Depositor:
- Susan Schulman
- Owner:
- Jeff Pettey
- Based Near Label Tesim:
- Salt Lake City, Utah, United States
- Language:
- English
- Date Uploaded:
- 11/26/2019
- Date Modified:
- 10/29/2024
- Date Created:
- 2018-02-01 to 2018-02-04
- 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-ZTWP-VF00
-
- Description:
- Light-scattering spectroscopy (LSS) is an established optical approach for nondestructive characterization of biological tissues. Here, we investigated the capabilities of LSS and convolutional neural networks (CNNs) to quantitatively characterize the composition and arrangement of cardiac tissues. We assembled tissue constructs from 200 μm thick sections of fixed myocardium and aortic wall. Thickness of the tissue constructs was similar to the thickness of atrial free wall. In the assembled constructs, the aortic sections represented fibrotic tissue and the depth, volume fraction, and arrangement of these fibrotic insets were varied. We gathered spectra with wavelengths from 500-1100 nm from the constructs at multiple locations relative to a light source. We used single and combinations of two spectra for training of CNNs. With independently measured spectra, we assessed the accuracy of the trained CNNs for classification of tissue constructs from single spectra and combined spectra. In general, classification accuracy with single spectra was smaller than with combined spectra. Combined spectra including spectra from fibers distal from the illumination fiber typically yielded a higher accuracy than proximal single collection fibers. Maximal classification accuracy of depth detection, volume fraction and permutated arrangements was (mean±stddev) 88.97±2.49%, 76.33±1.51% and 84.25±1.88%, respectively. Our studies demonstrate the reliability of quantitative characterization of tissue composition and arrangements using a combination of LSS and CNNs. Potential clinical applications of the developed approach include intraoperative quantification and mapping of atrial fibrosis as well as assessment of ablation lesions.
- Keyword:
- cardiology, neural networks, cardiovascular imaging, heart, spectroscopy, machine learning, and optical imaging
- Subject:
- cardiology
- Creator:
- Hitchcock, Robert W., Sachse, Frank B., Cottle, Brian K., Kelson, Bailey E. B., and Knighton, Nathan J.
- Owner:
- Frank Sachse
- Based Near Label Tesim:
- Salt Lake City, Utah, United States
- Language:
- English
- Date Uploaded:
- 01/09/2020
- Date Modified:
- 10/29/2024
- Date Created:
- 2019-01-01 to 2019-02-08 and 2020-07-21 to 2020-08-07
- 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-3Q4J-SC4Y
-
- Description:
- We apply Bayesian inference to instrument calibration and experimental-data uncertainty analysis for the specific application of measuring radiative intensity with a narrow-angle radiometer. We develop a physics-based instrument model that describes temporally varying radiative intensity, the indirectly measured quantity of interest, as a function of scenario and model parameters. We identify a set of five uncertain parameters, find their probability distributions (the posterior or inverse problem) given the calibration data by applying Bayes’ Theorem, and employ a local linearization to marginalize the nuisance parameters resulting from errors-in-variables. We then apply the instrument model to a new scenario that is the intended use of the instrument, a 1.5 MW coal-fired furnace. Unlike standard error propagation, this Bayesian method infers values for the five uncertain parameters by sampling from the posterior distribution and then computing the intensity with quantifiable uncertainty at the point of a new, in-situ furnace measurement (the posterior predictive or forward problem). Given the instrument-model context of this analysis, the propagated uncertainty provides a significant proportion of the measurement error for each in-situ furnace measurement. With this approach, we produce uncertainties at each temporal measurement of the radiative intensity in the furnace, successfully identifying temporal variations that were otherwise indistinguishable from measurement uncertainty.
- Keyword:
- coal-fired furnace, measurements, uncertainty quantification, Bayesian, and radiometer
- Subject:
- Validation and Simulation
- Creator:
- Scheib, Kaitlyn, Spinti, Jennifer P., Smith, Sean T., Harding, N. Stanley, Smith, Philip J., and Draper, Teri S.
- Owner:
- Philip Smith
- Based Near Label Tesim:
- Salt Lake City, Utah, United States
- Language:
- English
- Date Uploaded:
- 12/01/2020
- Date Modified:
- 10/25/2024
- Date Created:
- 2020-11-01 to 2020-11-30
- License:
- CC BY NC - Allows others to use and share your data non-commercially and with attribution.
- Resource Type:
- Software or Program Code
- Identifier:
- https://doi.org/10.7278/S50D6AFQ84VP
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