Publications by authors named "B Abbott"

896 Publications

What do we need to predict groundwater nitrate recovery trajectories?

Sci Total Environ 2021 May 8;788:147661. Epub 2021 May 8.

Univ Rennes, CNRS, Géosciences Rennes, UMR 6118, 35000 Rennes, France; Univ Rennes, CNRS, OSUR (Observatoire des sciences de l'univers de Rennes), UMS 3343, 35000 Rennes, France. Electronic address:

Nitrate contamination affects many of the Earth's aquifers and surface waters. Large-scale predictions of groundwater nitrate trends normally require the characterization of multiple anthropic and natural factors. To assess different approaches for upscaling estimates of nitrate recovery, we tested the influence of hydrological, historical, and biological factors on predictions of future nitrate concentration in aquifers. We tested the factors with a rich hydrogeological dataset from a fractured bedrock catchment in western France (Brittany). A sensitivity analysis performed on a calibrated model of groundwater flow, denitrification, and nitrogen inputs revealed that trends in nitrate concentration can effectively be approximated with a limited number of key parameters. The total mass of nitrate that entered the aquifer since the beginning of the industrial period needs to be characterized, but the shape of the historical nitrogen input time series can be largely simplified without substantially altering the predictions. Aquifer flow and transport processes can be represented by the mean and standard deviation of the residence time distribution, offering a tractable tool to make reasonable predictions at watershed to regional scales. Apparent sensitivity to denitrification rate was primarily attributable to time lags in oxygen depletion, meaning that denitrification can be simplified to an on/off process, defined only by the time needed for nitrate to reach the hypoxic reactive layer. Obtaining these key parameters at large scales is still challenging with currently available information, but the results are promising regarding our future ability to predict nitrate concentration with integrated monitoring and modeling approaches.
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http://dx.doi.org/10.1016/j.scitotenv.2021.147661DOI Listing
May 2021

Mesoporous Silica Nanoparticles: Properties and Strategies for Enhancing Clinical Effect.

Pharmaceutics 2021 Apr 17;13(4). Epub 2021 Apr 17.

Stephenson Cancer Center, University of Oklahoma, Oklahoma City, OK 73104, USA.

Due to the theragnostic potential of mesoporous silica nanoparticles (MSNs), these were extensively investigated as a novel approach to improve clinical outcomes. Boasting an impressive array of formulations and modifications, MSNs demonstrate significant in vivo efficacy when used to identify or treat myriad malignant diseases in preclinical models. As MSNs continue transitioning into clinical trials, a thorough understanding of the characteristics of effective MSNs is necessary. This review highlights recent discoveries and advances in MSN understanding and technology. Specific focus is given to cancer theragnostic approaches using MSNs. Characteristics of MSNs such as size, shape, and surface properties are discussed in relation to effective nanomedicine practice and projected clinical efficacy. Additionally, tumor-targeting options used with MSNs are presented with extensive discussion on active-targeting molecules. Methods for decreasing MSN toxicity, improving site-specific delivery, and controlling release of loaded molecules are further explained. Challenges facing the field and translation to clinical environments are presented alongside potential avenues for continuing investigations.
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http://dx.doi.org/10.3390/pharmaceutics13040570DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8072651PMC
April 2021

Search for Dark Matter Produced in Association with a Dark Higgs Boson Decaying into W^{±}W^{∓} or ZZ in Fully Hadronic Final States from sqrt[s]=13  TeV pp Collisions Recorded with the ATLAS Detector.

Phys Rev Lett 2021 Mar;126(12):121802

CERN, Geneva, Switzerland.

Several extensions of the Standard Model predict the production of dark matter particles at the LHC. An uncharted signature of dark matter particles produced in association with VV=W^{±}W^{∓} or ZZ pairs from a decay of a dark Higgs boson s is searched for using 139  fb^{-1} of pp collisions recorded by the ATLAS detector at a center-of-mass energy of 13 TeV. The s→V(qq[over ¯])V(qq[over ¯]) decays are reconstructed with a novel technique aimed at resolving the dense topology from boosted VV pairs using jets in the calorimeter and tracking information. Dark Higgs scenarios with m_{s}>160  GeV are excluded.
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http://dx.doi.org/10.1103/PhysRevLett.126.121802DOI Listing
March 2021

Longitudinal Flow Decorrelations in Xe+Xe Collisions at sqrt[s_{NN}]=5.44  TeV with the ATLAS Detector.

Phys Rev Lett 2021 Mar;126(12):122301

Department of Physics, Alexandru Ioan Cuza University of Iasi, Iasi, Romania.

The first measurement of longitudinal decorrelations of harmonic flow amplitudes v_{n} for n=2-4 in Xe+Xe collisions at sqrt[s_{NN}]=5.44  TeV is obtained using 3  μb^{-1} of data with the ATLAS detector at the LHC. The decorrelation signal for v_{3} and v_{4} is found to be nearly independent of collision centrality and transverse momentum (p_{T}) requirements on final-state particles, but for v_{2} a strong centrality and p_{T} dependence is seen. When compared with the results from Pb+Pb collisions at sqrt[s_{NN}]=5.02  TeV, the longitudinal decorrelation signal in midcentral Xe+Xe collisions is found to be larger for v_{2}, but smaller for v_{3}. Current hydrodynamic models reproduce the ratios of the v_{n} measured in Xe+Xe collisions to those in Pb+Pb collisions but fail to describe the magnitudes and trends of the ratios of longitudinal flow decorrelations between Xe+Xe and Pb+Pb. The results on the system-size dependence provide new insights and an important lever arm to separate effects of the longitudinal structure of the initial state from other early and late time effects in heavy-ion collisions.
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http://dx.doi.org/10.1103/PhysRevLett.126.122301DOI Listing
March 2021

Arbitrary-Order Derivatives of Quantum Chemical Methods via Automatic Differentiation.

J Phys Chem Lett 2021 Apr 25;12(12):3232-3239. Epub 2021 Mar 25.

Center for Computational Quantum Chemistry, University of Georgia, Athens, Georgia 30602, United States.

Herein, we present for the first time a general methodology for obtaining arbitrary-order nuclear coordinate derivatives of electronic energies derived from quantum chemistry methods. By leveraging modern advances in automatic differentiation software, we demonstrate that exact derivatives can be obtained for any method. This innovation completely bypasses the issues associated with the computational stability of applying numerical differentiation methods and dispenses the need to derive challenging formulae for analytic energy derivatives. We describe a freely available and open-source software implementation of our scheme and demonstrate its use in obtaining exact nuclear derivatives of energies from Hartree-Fock theory, second-order Møller-Plesset perturbation theory (MP2), and coupled cluster theory with single, double, and perturbative triple excitations [CCSD(T)]. Our sample computations include up to sextic derivatives and span a variety of test systems with up to 100 basis functions, confirming the viability of this scheme for a wide range of applications. Many of the results obtained have hitherto been unobtainable by exact means due to a lack of higher-order derivative formulae. The details of our implementation and possible further developments are discussed.
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http://dx.doi.org/10.1021/acs.jpclett.1c00607DOI Listing
April 2021