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  1. Over the eastern north Atlantic (ENA) ocean, a total of 21 non-drizzling single-layer marine boundary layer (MBL) stratus and stratocumulus cloud caseperiods are selected in order to investigate the impacts of the environmental variables on the aerosol-cloud interaction (ACI_r) using the ground-based measurements from the Department of Energy Atmospheric Radiation Measurement (ARM) facility at the ENA site during the period 2016 – 2018. The ACI_r represents the relative change of cloud-droplet effective radius r_e with respect to the relative change of cloud condensation nuclei (CCN) number concentration (N_CCN) in the water vapor stratified environment. The ACI_r values vary from -0.004more »to 0.207 with increasing precipitable water vapor (PWV) conditions, indicating that r_e is more sensitive to the CCN loading under sufficient water vapor supply, owing to the combined effect of enhanced condensational growth and coalescence processes associated with higher N_c and PWV. The environmental effects on ACI_r are examined by stratifying the data into different lower tropospheric stability (LTS) and vertical component of turbulence kinetic energy (TKE_w) regimes. The higher LTS normally associates with a more adiabatic cloud layer and a lower boundary layer and thus results in higher CCN to cloud droplet conversion and ACI_r. The ACI_r values under a range of PWV double from low TKE_w to high TKE_w regime, indicating a strong impact of turbulence on the ACI_r. The stronger boundary layer turbulence represented by higher TKE_w strengthens the connection and interaction between cloud microphysical properties and the underneath CCN and moisture sources. With sufficient water vapor and low CCN loading, the active coalescence process broadens the cloud droplet size distribution spectra, and consequently results in an enlargement of r_e. The enhanced N_c conversion and condensational growth induced by more intrusions of CCN effectively decrease r_e, which jointly presents as the increased ACI_r. The TKE_w median value of 0.08 m^2 s^(-2) suggests a feasible way in distinguishing the turbulence-enhanced aerosol-cloud interaction in non-drizzling MBL clouds.« less
  2. We develop a framework for learning sparse nonparametric directed acyclic graphs (DAGs) from data. Our approach is based on a recent algebraic characterization of DAGs that led to a fully continuous program for scorebased learning of DAG models parametrized by a linear structural equation model (SEM). We extend this algebraic characterization to nonparametric SEM by leveraging nonparametric sparsity based on partial derivatives, resulting in a continuous optimization problem that can be applied to a variety of nonparametric and semiparametric models including GLMs, additive noise models, and index models as special cases. Unlike existing approaches that require specific modeling choices, lossmore »functions, or algorithms, we present a completely general framework that can be applied to general nonlinear models (e.g. without additive noise), general differentiable loss functions, and generic black-box optimization routines.« less
  3. Free, publicly-accessible full text available June 1, 2023
  4. Free, publicly-accessible full text available December 22, 2022
  5. Free, publicly-accessible full text available April 1, 2023
  6. Spatial–temporal data arise frequently in biomedical, environmental, political and social science studies. Capturing dynamic changes of time-varying correlation structure is scientifically important in spatio-temporal data analysis. We approximate the time-varying empirical estimator of the spatial correlation matrix by groups of selected basis matrices representing substructures of the correlation matrix. After projecting the correlation structure matrix onto a space spanned by basis matrices, we also incorporate varying-coefficient model selection and estimation for signals associated with relevant basis matrices. The unique feature of the proposed method is that signals at local regions corresponding with time can be identified through the proposed penalizedmore »objective function. Theoretically, we show model selection consistency and the oracle property in detecting local signals for the varying-coefficient estimators. The proposed method is illustrated through simulation studies and brain fMRI data.« less
  7. Engineering catalytic sites at the atomic level provide an opportunity to understand the catalyst’s active sites, which is vital to the development of improved catalysts. Herein, we show a reliable and tunable polyoxometalate (POM) template-based synthetic strategy to atomically engineer metal doping sites onto metallic 1T-MoS2, using Anderson-type POMs (XMo6, X = FeIII, CoIII, or NiII) as precursors. Benefiting from the synergistic effect of doping metals into 1T-MoS2 and the possible tuning effect of the Ni-O-Mo bond, the optimized Ni and O incorporated 1T-MoS2 (NiO@1T-MoS2) catalyst excels in the hydrogen evolution reaction (HER). With a positive onset potential of ~more »0 V and a low overpotential of -46 mV in 1.0 M KOH, its results are comparable to 20% Pt/C. First-principles calculations reveal co-doping Ni and O into 1T-MoS2 assists the processes of both water dissociation and hydrogen generation from their intermediate states. This research will expand on the ability to improve the activities of various catalysts by precisely engineering atomic activation sites to achieve significant electronic modulations and improve atomic utilization efficiencies.« less
  8. We report a precision measurement of the parity-violating asymmetry APV in the elastic scattering of longitudinally polarized electrons from 208Pb. We measure APV=550±16(stat)±8(syst) parts per billion, leading to an extraction of the neutral weak form factor FW(Q2=0.00616  GeV2)=0.368±0.013. Combined with our previous measurement, the extracted neutron skin thickness is Rn−Rp=0.283±0.071  fm. The result also yields the first significant direct measurement of the interior weak density of 208Pb: ρ0W=−0.0796±0.0036(exp)±0.0013(theo)  fm−3 leading to the interior baryon density ρ0b=0.1480±0.0036(exp)±0.0013(theo)  fm−3. The measurement accurately constrains the density dependence of the symmetry energy of nuclear matter near saturation density, with implications for the size and composition of neutron stars.
  9. Free, publicly-accessible full text available September 1, 2022