The data was obtained from the FDTD simulations. For one of the FDTD simulations, the conductivity data for British Columbia was used in order to obtain the simulated data. The data obtained from simulations are post-processed using MATLAB for plotting the figures in the paper.
We determined whether a large, multi-analyte panel of circulating biomarkers can improve detection of early-stage pancreatic ductal adenocarcinoma (PDAC). We defined a biologically relevant subspace of blood analytes based on previous identification in premalignant lesions or early-stage PDAC and evaluated each in pilot studies. The 31 analytes that met minimum diagnostic accuracy were measured in serum of 837 subjects (461 healthy, 194 benign pancreatic disease, 182 early stage PDAC). We used machine learning to develop classification algorithms using the relationship between subjects based on their changes across the predictors. Model performance was subsequently evaluated in an independent validation data set from 186 additional subjects.
This is the IDL code used to create the results published in Mace, G. G., Benson, S., Humphries, R., Gombert P. M., Sterner, E.: Natural marine cloud brightening in the Southern Ocean, Atmospheric Chemistry and Physics. The IDL code processes MOD03 geolocation fields, MOD06_L2 cloud retrievals, MODIS ocean color chlorophyll-a concentrations and CERES shortwave albedo data that is distributed by NASA data archives. It creates statistical results for non-precipitating or weakly precipitating warm, liquid, shallow, marine boundary layer clouds.
The data are bed-scale measurements taken from virtual outcrop models (Morris, E.A., Atlas, C.E., Johnson, C.L., 2023, Architectural analysis of the Panther Tongue - virtual outcrop models) and calibrated with measurements taken at outcrop in the field.
Abstract: Data for Performance evaluation of the Alphasense OPC-N3 and Plantower PMS5003 sensor in measuring dust events in the Salt Lake Valley, Utah
This data file was used to estimate the performance of the Alphasense OPC-N3 and PMS5003 sensor in measuring ambient PM10, especially during dust events, and to obtain correction factors to correct the PMS5003 data. During April 2022, the OPC-N3 and PMS5003 sensors were collocated with federal equivalent method (FEM)at two Utah Division of Air Quality (UDAQ) sites: Hawthorne (HW) station and Environmental Quality (EQ) station. One residential site (RS)was also tested, with OPC-N3 and PMS5003 collocated with GRIMM portable aerosol spectrophotometer. The FEM data (PM2.5 and PM10 concentrations) and meteorological parameters (wind speed, wind direction, relative humidity, and temperature) for the two UDAQ sites were downloaded from the EPA website. The Excel sheet contained all the raw data and the processed data. The FEM, OPC-N3, and PMS5003 measurements were labeled as FEM-YYY, OPC-YYY, and PMS-YYY, where YYY represents the sites nomenclature, i.e., HW, EQ, and RS. The sheet labeled “HW”, “RS”, and,” EQ” contained the raw measurements (meteorological, PM10, and PM2.5 (whenever applicable)) for the sites. The sheet” PM-ratio-based correlation” provided the data used to get the PM-ratio-based correlation. Briefly, based on the ratio of FEM-HW PM2.5/PM10, the FEM-HW and PMS-HW PM10 measurements were segregated into six bins: PM2.5/PM10: <0.2, 0.2-0.3, 0.3-0.4, 0.4-0.5, 0.5-0.7, and >0.7. For each bin, the co-located PMS-HW PM10 concentrations were linearly regressed against the FEM-HW PM10 concentrations to obtain correction factors (slope and intercept). These correction factors were later used to correct the PMS PM10 concentrations at the other two locations (RS and EQ), presented in the sheets with labels “RS correction using GRIMM ratio”, “RS correction using opc ratio” and “EQ corrected using EQ ratio”. Each sheet also includes the calculation of RMSE and NRMSE of OPC-YYY and PMS-YYY against FEM-YYY, with YYY as the site nomenclature.
The dataset contains Gas Chromatography (GC) data pertaining to the bulk electrolytic experiments, biocatalytic, organocatalytic reactions, and standards used in the study. The standard GC files calibrate the sensitivity of the column in the Gas Chromatograph to 1-heptanol, heptanal, and the corresponding alpha-hydrazino aldehyde. This information is used to quantify the peaks of 1-heptanol and heptanal obtained in the bulk electrolytic experiments and the alpha-hydrazino aldehyde obtained in the organocatalytic step.
The objective of this study was to determine the influence of face shields on the concentration of respirable aerosols in the breathing zone of the wearer. The experimental approach involved the generation of poly-dispersed respirable test dust aerosol in a low-speed wind tunnel over 15 minutes, with a downstream breathing mannequin. Aerosol concentrations were measured in the breathing zone of the mannequin and at an upstream location using two laser spectrophotometers that measured particle number concentration over the range 0.25-31 µm. Three face shield designs were tested (A, B and C), and were positioned on the mannequin operated at a high and low breathing rate. Efficiency – the reduction in aerosol concentration in the breathing zone – was calculated as a function of particle size and overall, for each face shield. Face shield A, a bucket hat with flexible shield, had the highest efficiency, approximately 95%, while more traditional face shield designs had efficiency 53-78%, depending on face shield and breathing rate. Efficiency varied by particle size, but the pattern differed among face shield designs. Face shields decreased the concentration of respirable aerosols in the breathing zone, when aerosols were carried perpendicular to the face. Additional research is needed to understand the impact of face shield position relative to the source.
This dataset accompanies the research article entitled, "Etiology-Specific Remodeling in Ventricular Tissue of Heart Failure Patients and its Implications for Computational Modeling of Electrical Conduction," where we quantified fibrosis and performed electrophysiological simulation to investigate electrical propagation in etiologically varied heart failure tissue samples. Included are raw confocal microscopic images, data for extracting and processing the raw images and script to analyze fibrosis and generate meshes for simulation.
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.
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.