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Large Divergence in Tropical Hydrological Projections Caused by Model Spread in Vegetation Responses to Elevated CO 2
Increasing atmospheric CO 2 and associated global warming are expected to alter the global hydrological cycle, thereby posing widespread threats to freshwater availability. However, future hydrological projections differ greatly between models, particularly over the tropical regions. The large difference between model projections directly limits policy planning efforts, and the responsible modeling processes remain unclear. Here, we identify the primary processes accounting for model differences in tropical hydrological changes using multiple CO 2 sensitivity experiments in the Coupled Model Intercomparison Project. We show that differences in projected changes to tropical evapotranspiration, precipitation, and surface water availability mainly arise from model representations of vegetation cover and stomatal conductance responses to elevated CO 2 and associated changes in atmospheric moisture and circulation. Atmospheric responses to sea surface warming contribute additionally to the divergence in hydrological projections. Given the importance of vegetation responses to elevated CO 2 and associated atmosphere feedbacks, our results underscore the need to improve representations of the vegetation physiological response to rising CO 2 and its coupling to the atmosphere, to provide reliable tropical hydrological projections.
Inferring the spread of COVID-19: the role of time-varying reporting rate in epidemiological modelling
The role of epidemiological models is crucial for informing public health officials during a public health emergency, such as the COVID-19 pandemic. However, traditional epidemiological models fail to capture the time-varying effects of mitigation strategies and do not account for under-reporting of active cases, thus introducing bias in the estimation of model parameters. To infer more accurate parameter estimates and to reduce the uncertainty of these estimates, we extend the SIR and SEIR epidemiological models with two time-varying parameters that capture the transmission rate and the rate at which active cases are reported to health officials. Using two real data sets of COVID-19 cases, we perform Bayesian inference via our SIR and SEIR models with time-varying transmission and reporting rates and via their standard counterparts with constant rates; our approach provides parameter estimates with more realistic interpretation, and 1-week ahead predictions with reduced uncertainty. Furthermore, we find consistent under-reporting in the number of active cases in the data that we consider, suggesting that the initial phase of the pandemic was more widespread than previously reported.
Assessing the impact of interregional mobility on COVID19 spread in Spain using transfer entropy
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How turbulence spreading improves power handling in quiescent high confinement fusion plasmas
Viable magnetic fusion devices necessitate combining good confinement with effective power flux handling. A major concern for ITER, and devices beyond, is the divertor heat load width, which sets peak boundary heat loads on the plasma-facing materials. Current estimates of the heat flux width are narrow for future reactors. Here, we demonstrate how pedestal turbulence can expand into, or entrain, the stable scrape-off-layer and so broaden the heat flux width beyond these neoclassical predictions. Employing combined theoretical, computational, and experimental approaches, we focus on quiescent high confinement discharges on the DIII-D tokamak, but the results are of broader significance. Our findings uncover common trends in the edge turbulence intensity flux, the pressure perturbation skewness, and the turbulence mixing length, which together determine the heat flux width. This research demonstrates the physics of scrape-off-layer broadening by turbulence and highlights the promise of a turbulent pedestal for successful core-edge integration in ITER and future fusion devices.
Toward Å-fs-meV Resolution in Electron Microscopy: Systematic Simulation of the Temporal Spread of Single-Electron Packets
Though efforts to improve the temporal resolution of transmission electron microscopes (TEMs) have waxed and waned for decades, with relatively recent advances routinely reaching sub-picosecond scales, fundamental and practical challenges have hindered the advance of combined Å-fs-meV resolutions, particularly for core-loss spectroscopy and real-space imaging. This is due in no small part to the complexity of the approach required to access timescales upon which electrons, atoms, molecules, and materials first begin to respond and transform – attoseconds to picoseconds. Here we present part of a larger effort devoted to systematically mapping the instrument parameter space of a TEM modified to reach ultrafast timescales. With General Particle Tracer, we studied the statistical temporal distributions of single-electron packets as a function of various fs pulsed-laser parameters and electron-gun configurations and fields for the exact architecture and dimensions of a Thermo Fisher Tecnai Femto ultrafast electron microscope. We focused on easily-adjustable parameters, such as laser pulse duration, laser spot size, photon energy, Wehnelt aperture diameter, and photocathode size. In addition to establishing trends and dispersion behaviors, we identify regimes within which packet duration can be 100s of fs and approach the 300-fs laser limit employed here. Overall, the results provide a detailed picture of the temporal behavior of single-electron packets in the Tecnai Femto gun region, forming the initial contribution of a larger effort.
Investigation of theoretical scaling laws using large eddy simulations for airborne spreading of viral contagion from sneezing and coughing
Using a set of large eddy point-particle simulations, we explore the fluid dynamics of an ejected puff resulting from a cough/sneeze. The ejection contains over 61,000 potentially virus-laden droplets at an injection Reynolds number of about 46,000, comparable to an actual cough/ sneeze. We observe that global puff properties, such as centroid, puff volume, momentum, and buoyancy vary little across realizations. Other properties, such as maximum extent, shape, and edge velocity of the puff, may exhibit substantial variation. In many realizations, a portion of the puff splits off and advances along a random direction, while keeping airborne droplet nuclei afloat. This peeled-off portion provides a mechanism for virus-laden droplets to travel over large distances in a short amount of time. We also observe that the vast majority of droplets remain suspended within the puff after all liquid has evaporated. The main objectives of the study are to (i) evaluate assumptions of Balachandar’s et al. theory [Int. J. Multiphase Flow 132, 103439 (2020)], which include buoyancy effects, shape of the puff, and droplet evaporation rate, (ii) obtain values of closure parameters, which include location and time of the virtual origin, and puff entrainment and drag coefficients, and (iii) evaluate the accuracy of the theory in predicting the shape, size, and location of the puff, as well as droplet number density long after ejection. The theory adequately predicts global puff properties including size, velocity, and distance traveled, the largest size of droplets that exit the puff due to settling, and the droplet size distribution within the puff long after ejection.
High-throughput evaluation of half-metallicity of Co 2 MnSi Heusler alloys using composition-spread films and spin-integrated hard X-ray photoelectron spectroscopy
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A general framework for removing point-spread function additive systematics in cosmological weak lensing analysis
ABSTRACT Cosmological weak lensing measurements rely on a precise measurement of the shear two-point correlation function (2PCF) along with a deep understanding of systematics that affect it. In this work, we demonstrate a general framework for detecting and modelling the impact of PSF systematics on the cosmic shear 2PCF and mitigating its impact on cosmological analysis. Our framework can detect PSF leakage and modelling error from all spin-2 quantities contributed by the PSF second and higher moments, rather than just the second moments, using the cross-correlations between galaxy shapes and PSF moments. We interpret null tests using the HSC Year 3 (Y3) catalogs with this formalism and find that leakage from the spin-2 combination of PSF fourth moments is the leading contributor to additive shear systematics, with total contamination that is an order-of-magnitude higher than that contributed by PSF second moments alone. We conducted a mock cosmic shear analysis for HSC Y3 and find that, if uncorrected, PSF systematics can bias the cosmological parameters Ωm and S8 by ∼0.3σ. The traditional second moment-based model can only correct for a 0.1σ bias, leaving the contamination largely uncorrected. We conclude it is necessary to model both PSF second and fourth moment contaminations for HSC Y3 cosmic shear analysis. We also reanalyse the HSC Y1 cosmic shear analysis with our updated systematics model and identify a 0.07σ bias on Ωm when using the more restricted second moment model from the original analysis. We demonstrate how to self-consistently use the method in both real space and Fourier space, assess shear systematics in tomographic bins, and test for PSF model overfitting.
Quantum chaos and the complexity of spread of states
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Competition, Collaboration, and Optimization in Multiple Interacting Spreading Processes
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Many-Body Quantum Teleportation via Operator Spreading in the Traversable Wormhole Protocol
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Spread Spectrum Time Domain Reflectometry With Lumped Elements on Asymmetric Transmission Lines
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Observational constraints reduce model spread but not uncertainty in global wetland methane emission estimates
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Experimental evaluation of respiratory droplet spread to rooms connected by a central ventilation system
This article presents results from an experimental study to ascertain the transmissibility of the SARS-CoV-2 virus between rooms in a building that are connected by a central ventilation system. Respiratory droplet surrogates made of mucus and virus mimics were released in one room in a test building and measurements of concentration levels were made in other rooms connected via the ventilation system. The paper presents experimental results for different ventilation system configurations, including ventilation rate, filtration level (up to MERV-13), and fractional outdoor air intake. The most important finding is that respiratory droplets can and do transit through central ventilation systems, suggesting a mechanism for viral transmission (and COVID-19 specifically) within the built environment in reasonable agreement with well-mixed models. We also find the deposition of these droplets on room walls to be negligibly small. Furthermore, the energy use impact of the different configuration settings is also quantified to help inform intelligent building operation that can simultaneously address energy use and occupant health.