University of Colorado Boulder

About: University of Colorado Boulder is a education organization based out in Boulder, Colorado, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 48794 authors who have published 115151 publications receiving 5387328 citations. The organization is also known as: CU Boulder & UCB.

Test sensitivity is secondary to frequency and turnaround time for COVID-19 screening.

Abstract: The COVID-19 pandemic has created a public health crisis. Because SARS-CoV-2 can spread from individuals with presymptomatic, symptomatic, and asymptomatic infections, the reopening of societies and the control of virus spread will be facilitated by robust population screening, for which virus testing will often be central. After infection, individuals undergo a period of incubation during which viral titers are too low to detect, followed by exponential viral growth, leading to peak viral load and infectiousness and ending with declining titers and clearance. Given the pattern of viral load kinetics, we model the effectiveness of repeated population screening considering test sensitivities, frequency, and sample-to-answer reporting time. These results demonstrate that effective screening depends largely on frequency of testing and speed of reporting and is only marginally improved by high test sensitivity. We therefore conclude that screening should prioritize accessibility, frequency, and sample-to-answer time; analytical limits of detection should be secondary.

Direct observations of atmospheric aerosol nucleation.

Abstract: Atmospheric nucleation is the dominant source of aerosol particles in the global atmosphere and an important player in aerosol climatic effects. The key steps of this process occur in the sub–2-nanometer (nm) size range, in which direct size-segregated observations have not been possible until very recently. Here, we present detailed observations of atmospheric nanoparticles and clusters down to 1-nm mobility diameter. We identified three separate size regimes below 2-nm diameter that build up a physically, chemically, and dynamically consistent framework on atmospheric nucleation—more specifically, aerosol formation via neutral pathways. Our findings emphasize the important role of organic compounds in atmospheric aerosol formation, subsequent aerosol growth, radiative forcing and associated feedbacks between biogenic emissions, clouds, and climate.

Supernova constraints and systematic uncertainties from the first three years of the supernova legacy survey

Abstract: We combine high redshift Type Ia supernovae from the first 3 years of the Supernova Legacy Survey (SNLS) with other supernova (SN) samples, primarily at lower redshifts, to form a high-quality joint sample of 472 SNe (123 low-$z$, 93 SDSS, 242 SNLS, and 14 {\it Hubble Space Telescope}). SN data alone require cosmic acceleration at >99.9% confidence, including systematic effects. For the dark energy equation of state parameter (assumed constant out to at least $z=1.4$) in a flat universe, we find $w = -0.91^{+0.16}_{-0.20}(\mathrm{stat}) ^{+0.07}_{-0.14} (\mathrm{sys})$ from SNe only, consistent with a cosmological constant. Our fits include a correction for the recently discovered relationship between host-galaxy mass and SN absolute brightness. We pay particular attention to systematic uncertainties, characterizing them using a systematics covariance matrix that incorporates the redshift dependence of these effects, as well as the shape-luminosity and color-luminosity relationships. Unlike previous work, we include the effects of systematic terms on the empirical light-curve models. The total systematic uncertainty is dominated by calibration terms. We describe how the systematic uncertainties can be reduced with soon to be available improved nearby and intermediate-redshift samples, particularly those calibrated onto USNO/SDSS-like systems.

Global patterns of terrestrial biological nitrogen (N2) fixation in natural ecosystems

Abstract: Human activities have clearly caused dramatic alterations of the terrestrial nitrogen cycle, and analyses of the extent and effects of such changes are now common in the scientific literature. However, any attempt to evaluate N cycling processes within ecosystems, as well as anthropogenic influences on the N cycle, requires an understanding of the magnitude of inputs via biological nitrogen fixation (BNF). Although there have been many studies addressing the microbiology, physiology, and magnitude of N fixation at local scales, there are very few estimates of BNF over large scales. We utilized >100 preexisting published estimates of BNF to generate biome- and global-level estimates of biological N fixation. We also used net primary productivity (NPP) and evapotranspiration (ET) estimates from the Century terrestrial ecosystem model to examine global relationships between these variables and BNF as well as to compare observed and Century-modeled BNF. Our data-based estimates showed a strong positive relationship between ecosystem ET and BNF, and our analyses suggest that while the model's simple relationships for BNF predict broad scale patterns, they do not capture much of the variability or magnitude of published rates. Patterns of BNF were also similar to patterns of ecosystem NPP. Our “best estimate” of potential nitrogen fixation by natural ecosystems is ∼195 Tg N yr−1, with a range of 100–290 Tg N yr−1. Although these estimates do not account for the decrease in natural N fixation due to cultivation, this would not dramatically alter our estimate, as the greatest reductions in area have occurred in systems characterized by relatively low rates of N fixation (e.g., grasslands). Although our estimate of BNF in natural ecosystems is similar to previously published estimates of terrestrial BNF, we believe that this study provides a more documented, constrained estimate of this important flux.

Digital cameras with designs inspired by the arthropod eye

Abstract: In arthropods, evolution has created a remarkably sophisticated class of imaging systems, with a wide-angle field of view, low aberrations, high acuity to motion and an infinite depth of field. A challenge in building digital cameras with the hemispherical, compound apposition layouts of arthropod eyes is that essential design requirements cannot be met with existing planar sensor technologies or conventional optics. Here we present materials, mechanics and integration schemes that afford scalable pathways to working, arthropod-inspired cameras with nearly full hemispherical shapes (about 160 degrees). Their surfaces are densely populated by imaging elements (artificial ommatidia), which are comparable in number (180) to those of the eyes of fire ants (Solenopsis fugax) and bark beetles (Hylastes nigrinus). The devices combine elastomeric compound optical elements with deformable arrays of thin silicon photodetectors into integrated sheets that can be elastically transformed from the planar geometries in which they are fabricated to hemispherical shapes for integration into apposition cameras. Our imaging results and quantitative ray-tracing-based simulations illustrate key features of operation. These general strategies seem to be applicable to other compound eye devices, such as those inspired by moths and lacewings (refracting superposition eyes), lobster and shrimp (reflecting superposition eyes), and houseflies (neural superposition eyes).