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.
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.
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.
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 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.
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.
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.
This dataset accompanies the research article entitled, "Vibration of Natural Rock Arches and Towers Excited by Helicopter-Sourced Infrasound," where we investigate the vibration response of seven landforms to helicopter-sourced infrasound during controlled flight. Included are time-series vibration data of the landforms and nearby ground during and before helicopter flight, time-series infrasound data, 3D photogrammetry models of the studied landforms, and GPS data from the helicopter.
We analyzed 4,754 broadband seismic recordings of the SKS, SKKS, and SPdKS wavefield from 13 high quality events sampling the Samoa ultralow-velocity zone (ULVZ). We measured differential travel-times and amplitudes between the SKKS and SKS arrivals, which are highly sensitive to the emergence of the SPdKS seismic phase, which is in turn highly sensitive to lowermost mantle velocity perturbations such as generated by ULVZs. We modeled these data using a 2-D axi-symmetric waveform modeling approach and are able to explain these data with a single ULVZ. In order to predict both travel-time and amplitude perturbations we found that a large ULVZ length in the great circle arc direction on the order of 10° or larger is required. The large ULVZ length limits acceptable ULVZ elastic parameters. Here we find that δVS and δVP reductions from 20% to 22% and 15% to 17% respectively gives us the best fit, with a thickness of 26 km. Initial 3-D modeling efforts do not recover the extremes in the differential measurements, demonstrating that 3-D effects are important and must be considered in the future. However, the 3-D modeling is generally consistent with the velocity reductions recovered with the 2-D modeling. These velocity reductions are compatible with a compositional component to the ULVZ. Furthermore, geodynamic predictions for a compositional ULVZ that is moving predict a long linear shape similar to the shape of the Samoa ULVZ we confirm in this study.
and This collection includes radial component displacement seismograms in the time window including the SKS, SKKS and SPdKS seismic arrivals. These data all interact with the Samoa ultra-low velocity zone at the core-mantle boundary. All data used in the study of Krier et al., 2021 (JGR) is included in this collection.
Using a suite of numerical calculations, we consider the long-term evolution of
circumbinary debris from the Pluto--Charon giant impact. Initially, these solids
have large eccentricity and pericenters near Charon's orbit. On time scales of
100--1000 yr, dynamical interactions with Pluto and Charon lead to the ejection
of most solids from the system. As the dynamics moves particles away from the
barycenter, collisional damping reduces the orbital eccentricity of many particles.
These solids populate a circumbinary disk in the Pluto-Charon orbital plane; a large
fraction of this material lies within a `satellite zone' that encompasses the orbits
of Styx, Nix, Kerberos, and Hydra. Compared to the narrow rings generated from the
debris of a collision between a trans-Neptunian object (TNO) and Charon,
disks produced after the giant impact are much more extended and may be a less promising option for producing small circumbinary satellites.