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The daytime oxidation of biogenic hydrocarbons is attributed to both OH radicals and O3, while nighttime chemistry is dominated by the reaction with O3 and NO3 radicals. Here, the diurnal pattern of Secondary Organic Aerosol (SOA) originating from biogenic hydrocarbons was intensively evaluated under varying environmental conditions (temperature, humidity, sunlight intensity, NOx levels, and seed conditions) by using the UNIfied Partitioning Aerosol phase Reaction (UNIPAR) model, which comprises multiphase gas-particle partitioning and in-particle chemistry. The oxidized products of three different hydrocarbons (isoprene, α-pinene, and β-caryophyllene) were predicted by using near explicit gas mechanisms for four different oxidation paths (OH, O3, NO3, and O(3P)) during day and night. The gas mechanisms implemented the Master Chemical Mechanism (MCM v3.3.1), the reactions that formed low volatility products via peroxy radical (RO2) autoxidation, and self- and cross-reactions of nitrate-origin RO2. In the model, oxygenated products were then classified into volatility-reactivity base lumping species, which were dynamically constructed under varying NOx levels and aging scales. To increase feasibility, the UNIPAR model that equipped mathematical equations for stoichiometric coefficients and physicochemical parameters of lumping species was integrated with the SAPRC gas mechanism. The predictability of the UNIPAR model was demonstrated by simulating chamber-generated SOA data undermore »
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Super-resolution live-cell imaging of CTCF- and cohesin-mediated chromatin loops reveals that these loops are rare and dynamic.Free, publicly-accessible full text available April 29, 2023
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The prediction of Secondary Organic Aerosol (SOA) in regional scales is traditionally performed by using gas-particle partitioning models. In the presence of inorganic salted wet aerosols, aqueous reactions of semivolatile organic compounds can also significantly contribute to SOA formation. The UNIfied Partitioning-Aerosol phase Reaction (UNIPAR) model utilizes the explicit gas mechanism to better predict SOA formation from multiphase reactions of hydrocarbons. In this work, the UNIPAR model was incorporated with the Comprehensive Air Quality Model with Extensions (CAMx) to predict the ambient concentration of organic matter (OM) in urban atmospheres during the Korean-United States Air Quality (2016 KORUS-AQ) campaign. The SOA mass predicted with the CAMx-UNIPAR model changed with varying levels of humidity and emissions and in turn, has the potential to improve the accuracy of OM simulations. The CAMx-UNIPAR model significantly improved the simulation of SOA formation under the wet condition, which often occurred during the KORUS-AQ campaign, through the consideration of aqueous reactions of reactive organic species and gas-aqueous partitioning. The contribution of aromatic SOA to total OM was significant during the low-level transport/haze period (24-31 May 2016) because aromatic oxygenated products are hydrophilic and reactive in aqueous aerosols. The OM mass predicted with the CAMx-UNIPAR model wasmore »
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Mirrokni, V (Ed.)Signal estimation problems with smoothness and sparsity priors can be naturally modeled as quadratic optimization with L0-“norm” constraints. Since such problems are non-convex and hard-to-solve, the standard approach is, instead, to tackle their convex surrogates based on L1-norm relaxations. In this paper, we propose new iterative (convex) conic quadratic relaxations that exploit not only the L0-“norm” terms, but also the fitness and smoothness functions. The iterative convexification approach substantially closes the gap between the L0-“norm” and its L1 surrogate. These stronger relaxations lead to significantly better estimators than L1-norm approaches and also allow one to utilize affine sparsity priors. In addition, the parameters of the model and the resulting estimators are easily interpretable. Experiments with a tailored Lagrangian decomposition method indicate that the proposed iterative convex relaxations yield solutions within 1% of the exact L0-approach, and can tackle instances with up to 100,000 variables under one minute.
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We combine equation of state of dense matter up to twice nuclear saturation density (nsat = 0.16 fm−3 ) obtained using chiral effective field theory (χEFT), and recent observations of neutron stars to gain insights about the high-density matter encountered in their cores. A key element in our study is the recent Bayesian analysis of correlated EFT truncation errors based on order-byorder calculations up to next-to-next-to-next-to-leading order in the χEFT expansion. We refine the bounds on the maximum mass imposed by causality at high densities, and provide stringent limits on the maximum and minimum radii of ∼ 1.4 M and ∼ 2.0 M stars. Including χEFT predictions from nsat to 2 nsat reduces the permitted ranges of the radius of a 1.4 M star, R1.4, by ∼ 3.5 km. If observations indicate R1.4 < 11.2 km, our study implies that either the squared speed of sound c 2 s > 1/2 for densities above 2 nsat, or that χEFT breaks down below 2 nsat. We also comment on the nature of the secondary compact object in GW190814 with mass ' 2.6 M , and discuss the implications of massive neutron stars > 2.1 M (2.6 M ) in future radiomore »