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Internal Climate Variability Obscures Future Freezing Rain Changes Despite Global Warming Trend
Abstract Although numerous studies have projected changes in freezing rain under future climate conditions, the internal variability of freezing rain remains poorly quantified. Here, we introduce a framework utilizing a novel machine‐learning algorithm to diagnose freezing rain in reanalysis and climate model simulations. By employing multivariate quantile mapping, we decompose the projected freezing rain trend into contributions from changes in temperature, relative humidity, and precipitation, which helps separate the forced response from internal climate variability. Our finding reveals a notable decrease in freezing rain occurrence in most areas. Despite a substantial temperature increase, internal variability overshadows climate forcing across a large portion of the eastern United States until about 2050. This insight has implications for practitioners, suggesting that the observed freezing rain frequency climatology continues to provide a relevant baseline for decision‐making in the near term. However, longer‐term design and adaptation plans should consider the projected changes in these regions.
Climate-induced tree-mortality pulses are obscured by broad-scale and long-term greening
Not provided.
Model uncertainty obscures major driver of soil carbon
Understanding the formation and stabilization mechanisms of soil organic carbon (SOC) is important for managing land carbon (C) and mitigating climate change. Tao et al. reported that microbial C use efficiency (CUE) is the primary determinant of global SOC storage and that the relative impact of plant C inputs on SOC is minor. Although soil microbes undoubtedly play an important role in SOC cycling, we are concerned about the robustness of the approach taken by Tao et al. In conclusion, the potential biases in their analyses may lead to misleading, model-dependent results.
Groundwater residence time estimates obscured by anthropogenic carbonate
In central California, irrigation seepage perturbs groundwater inorganic carbon chemistry and complicates radiocarbon dating.
Evaluation of Commercially-Available Obscurants as a Delay Method for Industrial Irradiator Facilities.
Abstract not provided.
Taongi: An Obscure Atoll on the International Stage
Taongi is a microscopic dot in the vast expanse of the Pacific Ocean. Comprised of ten small islands, the atoll has never been permanently inhabited. The ancient Melanesians who settled the Marshallese Archipelago bypassed Taongi because the atoll was too dry to sustain a permanent settlement. Despite its seeming insignificance, Taongi has been a fixture in international affairs since its European discovery in 1526, including being at the center of a simmering feud between Los Alamos and the University of California Radiation Laboratory (UCRL).
Developing an Obscurant System to Protect Radiological Sources in Industrial Irradiator Facilities.
Abstract not provided.
Insight with X-rays:Imaging and Quantifying Obscured Deformation
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VOID INSIGHT: Venturing Obscure Information Depths: Insight Navigation via Spatial Investigation of Generative & Hyperdimensional Topologies
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Machine Learning-Enabled Quantitative Analysis of Optically Obscure Scratches on Nickel-Plated Additively Manufactured (AM) Samples
Additively manufactured metal components often have rough and uneven surfaces, necessitating post-processing and surface polishing. Hardness is a critical characteristic that affects overall component properties, including wear. This study employed K-means unsupervised machine learning to explore the relationship between the relative surface hardness and scratch width of electroless nickel plating on additively manufactured composite components. The Taguchi design of experiment (TDOE) L9 orthogonal array facilitated experimentation with various factors and levels. Initially, a digital light microscope was used for 3D surface mapping and scratch width quantification. However, the microscope struggled with the reflections from the shiny Ni-plating and scatter from small scratches. To overcome this, a scanning electron microscope (SEM) generated grayscale images and 3D height maps of the scratched Ni-plating, thus enabling the precise characterization of scratch widths. Optical identification of the scratch regions and quantification were accomplished using Python code with a K-means machine-learning clustering algorithm. The TDOE yielded distinct Ni-plating hardness levels for the nine samples, while an increased scratch force showed a non-linear impact on scratch widths. The enhanced surface quality resulting from Ni coatings will have significant implications in various industrial applications, and it will play a pivotal role in future metal and alloy surface engineering.
Spectroscopic Observations of Obscured Populations in the Inner Galaxy: 2MASS-GC02, Terzan 4, and the 200 km s{sup −1} stellar peak
The interpretation of potentially new and already known stellar structures located at low latitudes is hindered by the presence of dense gas and dust, as observations toward these sight lines are limited. We have identified Apache Point Observatory Galaxy Evolution Experiment (APOGEE) stars belonging to the low-latitude globular clusters 2MASS-GC02 and Terzan 4, presenting the first chemical element abundances of stars residing in these poorly studied clusters. As expected, the signature of multiple populations coexisting in these metal-rich clusters is evident. We redetermine the radial velocity of 2MASS-GC02 to be −87 ± 7 km s{sup −1}, finding that this cluster’s heliocentric radial velocity is offset by more than 150 km s{sup −1} from the literature value. We investigate a potentially new low-latitude stellar structure and a kiloparsec-scale nuclear disk (or ring) that has been put forward to explain a high-velocity (V {sub GSR} ∼ 200 km s{sup −1}) peak reported in several Galactic bulge fields based on the APOGEE commissioning observations. New radial velocities of field stars at (l, b) = (−6°,0 °) are presented and combined with the APOGEE observations at negative longitudes to carry out this search. Unfortunately no prominent −200 km s{sup −1} peak at negative longitudes along the plane of the Milky Way are apparent, as predicted for the signature of a nuclear feature. The distances and Gaia EDR3 proper motions of the high-V {sub GSR} stars do not support the current models of stars on bar-supporting orbits as an explanation of the +200 km s{sup −1} peak.
Can Neutron Star Tidal Effects Obscure Deviations from General Relativity?
Abstract One of the main goals of gravitational-wave astrophysics is to study gravity in the strong-field regime and constrain deviations from general relativity (GR). Any such deviation affects not only binary dynamics and gravitational-wave emission but also the structure and tidal properties of compact objects. In the case of neutron stars, masses, radii, and tidal deformabilities can all differ significantly between different theories of gravity. Currently, the measurement uncertainties in neutron star radii and tidal deformabilities are quite large. However, much less is known about how the large uncertainty in the nuclear equation of state (EOS) might affect tests of GR using binary neutron star mergers. Conversely, using the wrong theory of gravity might lead to incorrect constraints on the nuclear EOS. Here, we study this problem within scalar–tensor (ST) theory. We apply the recently derived ℓ = 2 tidal Love numbers in this theory to parameter estimation of GW170817. Correspondingly, we test if physics beyond GR could bias measurements of the nuclear EOS and neutron star radii. We find that parameter inference for both the GR and ST cases returns consistent component masses and tidal deformabilities. The radius and the EOS posteriors, however, differ between the two theories, but neither is excluded by current observational limits. This indicates that measurements of the nuclear EOS may be biased and that deviations from GR could go undetected when analyzing current binary neutron star mergers.
An optimal ALMA image of the Hubble Ultra Deep Field in the era of JWST : obscured star formation and the cosmic far-infrared background
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Spectroscopic Confirmation of Obscured AGN Populations from Unsupervised Machine Learning
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Infrared colours and spectral energy distributions of hard X-ray selected obscured and Compton-thick active galactic nuclei
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X-Ray Redshifts of Obscured Chandra Source Catalog Active Galactic Nuclei
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