Significance: Current medical imaging systems have many limitations for applications in cardiovascular diseases. New technologies may overcome these limitations. Particularly interesting are technologies for diagnosis of cardiac diseases, e.g. fibrosis, myocarditis, and transplant rejection.
Aim: To introduce and assess a new optical system capable of assessing cardiac muscle tissue using light-scattering spectroscopy (LSS) in conjunction with machine learning.
Approach: We applied an ovine model to investigate if the new LSS system is capable of estimating densities of cell nuclei in cardiac tissue. We measured the nuclear density using fluorescent labeling, confocal microscopy, and image processing. Spectra acquired from the same cardiac tissues were analyzed with spectral clustering and convolutional neural networks to assess feasibility and reliability of density quantification.
Results: Spectral clustering revealed distinct groups of spectra correlated to ranges of nuclear density. Convolutional neural networks correctly classified 3 groups of spectra with low, medium, or high nuclear density with 95.00±11.77% (mean and standard deviation) accuracy. The analysis revealed sensitivity of the accuracy to wavelength range and subsampling of spectra.
Conclusions: LSS and machine learning are capable of assessing nuclear density in cardiac tissues. The approach could be useful for diagnosis of cardiac diseases associated with an increase of nuclei.
Environmental noise may affect hearing and a variety of non-auditory disease processes. There is some evidence that, like other environmental hazards, noise may be differentially distributed across communities based on socioeconomic status. We aimed to a) predict daytime noise pollution levels and b) assess disparities in daytime noise exposure in Chicago, Illinois. We measured 5-minute daytime noise levels (Leq, 5-min) at 75 randomly selected sites in Chicago in March 2019. Geographically based variables thought to be associated with noise were obtained and used to fit a noise land-use regression model to estimate the daytime environmental noise level at the centroid of the census blocks. Demographic and socioeconomic data were obtained from the City of Chicago for the 77 community areas, and associations with daytime noise levels were assessed using spatial autoregressive models. Mean sampled noise level (Leq, 5-min) was 60.6 dBA. The adjusted R2 and root mean square error of the noise land use regression model and the validation model were 0.60 and 4.67 dBA and 0.51 and 5.90 dBA, respectively. Nearly 75% of city blocks and 85% of city communities have predicted daytime noise level higher than 55 dBA. Of the socioeconomic variables explored, only community per capita income was associated with mean community predicted noise levels and was highest for communities with incomes in the 2nd quartile. Both the noise measurements and land-use regression modeling demonstrate that Chicago has levels of environmental noise likely contributing to the total burden of environmental stressors. Noise is not uniformly distributed across Chicago; it is associated with proximity to roads and public transportation and is higher among communities with mid-to-low incomes per capita, which highlights how socially and economically disadvantaged communities may be disproportionately impacted by this environmental exposure.
This dataset comprises MODTRAN radiative transfer simulations used to determine scene-specific enhancement spectra for matched filter retrieval of CH4 and CO2 concentrations from imaging spectroscopy data. An example implementation to generate a enhancement spectrum is also included.
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.
This study of the role and impact of the subject selector in academic libraries is unique and long overdue. We focused on the Pac-12 university libraries, a representative sample of nationwide academic libraries. The strength of our investigation is this small, focused sample size and unique statistical analysis of subject specialists. There is a wide variety among these libraries with respect to the hiring requirements for MLIS, the MLIS with an additional advanced-subject master’s degree, and those libraries who hire non-MLIS librarians. This investigation has the possibility of promoting greater awareness for the future of subject specialists in academic libraries.
The Differential Emissivity Imaging Disdrometer (DEID) is a new evaporation-based optical and thermal instrument designed to measure the mass, size, density, and type of individual hydrometeors and their bulk properties. Hydrometeor spatial dimensions are measured on a heated metal plate using an infrared camera by exploiting the much higher thermal emissivity of water compared with metal. As a melted hydrometeor evaporates, its mass can be directly related to the loss of heat from the hotplate assuming energy conservation across the hydrometeor. The heat-loss required to evaporate a hydrometeor is found to be independent of environmental conditions including ambient wind velocity, moisture level, and temperature. The difference in heat loss for snow versus rain for a given mass offers a method for discriminating precipitation phase. The DEID measures hydrometeors at sampling frequencies up to 1 Hz with masses and effective diameters greater than 1 µg and 200 µm, respectively, determined by the size of the hotplate and the thermal camera specifications. Measurable snow water equivalent (SWE) precipitation rates range from 0.001 to 200 mm h−1, as validated against a standard weighing bucket. Preliminary field-experiment measurements of snow and rain from the winters of 2019 and 2020 provided continuous automated measurements of precipitation rate, snow density, and visibility. Measured hydrometeor size distributions agree well with canonical results described in the literature. and A new precipitation sensor, the Differential Emissivity Imaging Disdrometer (DEID), is used to provide the first continuous measurements of the mass, diameter, and density of individual hydrometeors. The DEID consists of an infrared camera pointed at a heated aluminum plate. It exploits the contrasting thermal emissivity of water and metal to determine individual particle mass by assuming that energy is conserved during the transfer of heat from the plate to the particle during evaporation. Particle density is determined from a combination of particle mass and morphology. A Multi-Angle Snowflake Camera (MASC) was deployed alongside the DEID to provide refined imagery of particle size and shape. Broad consistency is found between derived mass-diameter and density-diameter relationships and those obtained in prior studies. However, DEID measurements show a generally weaker dependence with size for hydrometeor density and a stronger dependence for aggregate snowflake mass.
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.
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.
This dataset encompasses the valid, completed, and qualitative data collected during the 2021 “Survey of Anime Convention Attendance in Response to Covid-19.” This survey was distributed online through social media platforms, community spaces, and industry listservs/resources in order to reach organizers, attendees, and fans of anime conventions (i.e., “cons”). The survey was intended to discover how those who attend anime conventions (i.e., "con-goers") have been experiencing changes in the anime convention scene during the COVID-19 pandemic, particularly in 2020-2021. Traditionally, anime cons and con-related activities such as cosplay (dressing up as a favorite character) are held in person. However, in 2020-2021, most cons have been cancelled or moved online; this is the first time in over 40 years, in the US and worldwide, that the anime convention scene has been so quiet. With this survey, investigators sought to capture firsthand impressions of this unprecedented moment, learning how con-goers were experiencing these changes and whether they had safety or other concerns about anime cons returning in late 2021 and early 2022.
This dataset accompanies the research article entitled, "Ambient vibration modal analysis of natural rock towers and fins," where we investigate the ambient vibrations of 14 rock rowers and perform modal analysis on 3D models of the landforms. Included are the vibration data and 3D models.
The similar orbital distances and incidence rates of debris disks and the prominent rings observed in protoplanetary disks suggest a potential connection between these structures. We explore this connection with new calculations that follow the evolution of rings of pebbles and planetesimals as they grow into planets and generate dusty debris. Depending on the initial solid mass and planetesimal formation efficiency, the calculations predict diverse outcomes for the resulting planet masses and accompanying debris signature. When compared with debris disk incidence rates as a function of luminosity and time, the model results indicate that the known population of bright cold debris disks can be explained by rings of solids with the (high) initial masses inferred for protoplanetary disk rings and modest planetesimal formation efficiencies that are consistent with current theories of planetesimal formation. These results support the possibility that large protoplanetary disk rings evolve into the known cold debris disks. The inferred strong evolutionary connection between protoplanetary disks with large rings and mature stars with cold debris disks implies that the remaining majority population of low-mass stars with compact protoplanetary disks leave behind only modest masses of residual solids at large radii and evolve primarily into mature stars without detectable debris beyond 30 au. The approach outlined here illustrates how combining observations with detailed evolutionary models of solids strongly constrains the global evolution of disk solids and underlying physical parameters such as the efficiency of planetesimal formation and the possible existence of invisible reservoirs of solids in protoplanetary disks.
This dataset includes a 3-D model of the Courthouse Mesa toppling rock slab instability in Utah. These data were used in conjunction with ambient seismic array data to conduct modal analyses and improve the structural characterization of the rock slope instability. Data include a 3-D model of the rock slope instability (.stl) and a COMSOL Multiphysics project file showing the boundary conditions and solutions of the best model run (.mph). This dataset accompanies the research article entitled "Rock slope instability structural characterization using array-based modal analysis."
Detailed ground-based observations of snow are scarce in remote regions such as the Arctic. Here, Multi-Angle Snowflake Camera (MASC) measurements of over 55,000 solid hydrometeors — obtained during a two-year period from August 2016 to August 2018 at Oliktok Point, Alaska — are analyzed and compared to similar measurements from an earlier experiment at Alta, Utah. In general, distributions of hydrometeor fall speed, fall orientation, aspect ratio, flatness, and complexity (i.e., riming degree) were observed to be very similar between the two locations, except that Arctic hydrometeors tended to be smaller. In total, the slope parameter defining a negative exponential of the size distribution was approximately 50% steeper in the Arctic as at Alta. 66% of particles were observed to be rimed or moderately rimed, with some suggestion that riming is favored by weak boundary layer stability. On average, the fall speed of rimed particles was not notably different from aggregates. However, graupel density and fall speed increase as cloud temperatures approach the melting point.
We discuss a new set of ~ 500 numerical n-body calculations designed to constrain the masses and bulk densities of Styx, Nix, Kerberos, and Hydra. Comparisons of different techniques for deriving the semimajor axis and eccentricity of the four satellites favor methods relying on the theory of Lee & Peale (2006), where satellite orbits are derived in the context of the restricted three body problem (Pluto, Charon, and one massless satellite). In each simulation, we adopt the nominal satellite masses derived in Kenyon & Bromley (2019b), multiply the mass of at least one satellite by a numerical factor f >= 1, and establish whether the system ejects at least one satellite on a time scale <= 4.5~Gyr. When the total system mass is large (f >> 1), ejections of Kerberos are more common. Systems with lower satellite masses (f ~ 1) usually eject Styx. In these calculations, Styx often signals an ejection by moving to higher orbital inclination long before ejection; Kerberos rarely signals in a useful way. The n-body results suggest that Styx and Kerberos are more likely to have bulk densities comparable with water ice, rho_SK <= 2 g/cm^3, than with rock. A strong upper limit on the total system mass, M_SNKH <= 9.5 x 10^19 g, also places robust constraints on the average bulk density of the four satellites, rho_SNKH <= 1.4 g/cm^3. These limits support models where the satellites grow out of icy material ejected during a major impact on Pluto or Charon.
This dataset accompanies the research article entitled, "Ground Motion Amplification at Natural Rock Arches in the Colorado Plateau ," where we analyzed 13 sandstone arches in Utah, computing site-to-reference spectral amplitude ratios from continuous ambient seismic data and comparing these to spectral ratios during earthquakes and teleseismic activity. Included in this dataset are the arch vibration data.
This dataset contains the materials necessary to reproduce the study submitted to Remote Sensing: "Tradeoffs Between UAS Spatial Resolution and Accuracy for Deep Learning Semantic Segmentation Applied to Wetland Vegetation Species Mapping". This includes the raw imagery output from the camera aboard the unoccupied aerial vehicle, the Red-Edge MX, captured over the Howard Slough Waterfowl Management Area, Utah, in August of 2020, resampled images, code to resample the images, a link to ground reference data, and the training and testing data used for the convolutional neural network in the study.
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.
This file contains experimental data from the Ph.D. thesis “Mechanisms Governing Ash Aerosol Formation and Deposition during Solid Fuel Combustion” at the University of Utah. The data include particle sizes, weights, and compositions of ash aerosols and deposits formed in the combustion of a range of fossil and biomass solid fuels under a wide range of conditions. Operation pressure, fuel composition and combustor scale are changed across these tests. These experimental data can provide information and inputs for further studies, such as modeling the ash deposition process, in the future.
Research background: Concern about global warming has called for new combustion systems to be used in order to reduce CO2 emissions from coal-fired power generation. Pressurized oxy-coal combustion coupled with carbon capture and storage as well as co-firing biomass with coal are gaining more interest in building new power plants and retrofitting existing plants. The combustion conditions of these systems could be significantly changed and thus affect the ash formation and deposition. The experimental work of this thesis consists of combustion tests at various scales and conditions, namely, on a 100 kWth rated oxy-fuel combustor (OFC), a 300 kWth rated entrained flow pressurized reactor (EFPR), a 1.5 MWth rated horizontal multifuel combustor (L1500) and a 500 MWe full-size utility boiler (Hunter). The solid fuels involved in these tests include pulverized coal, torrefied wood, blend fuels of the coal and wood, and coal with K/Cl/S additives. In each test, iso-kinetically sampled ash aerosols are analyzed in terms of particle size distributions and size-segregated compositions. Ash deposition rates are measured using a surface-temperature-controlled probe which simulates the deposition process on superheater tubes.
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.