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At least 379 records · Page 21

The Colorado East River Community Observatory Data Collection

Abstract The U.S. Department of Energy's (DOE) Colorado East River Community Observatory (ER) in the Upper Colorado River Basin was established in 2015 as a representative mountainous, snow‐dominated watershed to study hydrobiogeochemical responses to hydrological perturbations in headwater systems. The ER is characterized by steep elevation, geologic, hydrologic and vegetation gradients along floodplain, montane, subalpine, and alpine life zones, which makes it an ideal location for researchers to understand how different mountain subsystems contribute to overall watershed behaviour. The ER has both long‐term and spatially‐extensive observations and experimental campaigns carried out by the Watershed Function Scientific Focus Area (SFA), led by Lawrence Berkeley National Laboratory, and researchers from over 30 organizations who conduct cross‐disciplinary process‐based investigations and modelling of watershed behaviour. The heterogeneous data generated at the ER include hydrological, genomic, biogeochemical, climate, vegetation, geological, and remote sensing data, which combined with model inputs and outputs comprise a collection of datasets and value‐added products within a mountainous watershed that span multiple spatiotemporal scales, compartments, and life zones. Within 5 years of collection, these datasets have revealed insights into numerous aspects of watershed function such as factors influencing snow accumulation and melt timing, water balance partitioning, and impacts of floodplain biogeochemistry and hillslope ecohydrology on riverine geochemical exports. Data generated by the SFA are managed and curated through its Data Management Framework. The SFA has an open data policy, and over 70 ER datasets are publicly available through relevant data repositories. A public interactive map of data collection sites run by the SFA is available to inform the broader community about SFA field activities. Here, we describe the ER and the SFA measurement network, present the public data collection generated by the SFA and partner institutions, and highlight the value of collecting multidisciplinary multiscale measurements in representative catchment observatories.

54 ENVIRONMENTAL SCIENCES↗

RCSB Protein Data bank: Tools for visualizing and understanding biological macromolecules in 3D

Abstract Now in its 52nd year of continuous operations, the Protein Data Bank (PDB) is the premiere open‐access global archive housing three‐dimensional (3D) biomolecular structure data. It is jointly managed by the Worldwide Protein Data Bank (wwPDB) partnership. The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) is funded by the National Science Foundation, National Institutes of Health, and US Department of Energy and serves as the US data center for the wwPDB. RCSB PDB is also responsible for the security of PDB data in its role as wwPDB‐designated Archive Keeper. Every year, RCSB PDB serves tens of thousands of depositors of 3D macromolecular structure data (coming from macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro‐electron diffraction). The RCSB PDB research‐focused web portal ( RCSB.org ) makes PDB data available at no charge and without usage restrictions to many millions of PDB data consumers around the world. The RCSB PDB training, outreach, and education web portal ( PDB101.RCSB.org ) serves nearly 700 K educators, students, and members of the public worldwide. This invited Tools Issue contribution describes how RCSB PDB (i) is organized; (ii) works with wwPDB partners to process new depositions; (iii) serves as the wwPDB‐designated Archive Keeper; (iv) enables exploration and 3D visualization of PDB data via RCSB.org ; and (v) supports training, outreach, and education via PDB101.RCSB.org . New tools and features at RCSB.org are presented using examples drawn from high‐resolution structural studies of proteins relevant to treatment of human cancers by targeting immune checkpoints.

59 BASIC BIOLOGICAL SCIENCES↗

PTM‐Psi : A python package to facilitate the computational investigation of p ost‐ t ranslational m odification on p rotein s tructures and their i mpacts on dynamics and functions

Abstract Post‐translational modification (PTM) of a protein occurs after it has been synthesized from its genetic template, and involves chemical modifications of the protein's specific amino acid residues. Despite of the central role played by PTM in regulating molecular interactions, particularly those driven by reversible redox reactions, it remains challenging to interpret PTMs in terms of protein dynamics and function because there are numerous combinatorially enormous means for modifying amino acids in response to changes in the protein environment. In this study, we provide a workflow that allows users to interpret how perturbations caused by PTMs affect a protein's properties, dynamics, and interactions with its binding partners based on inferred or experimentally determined protein structure. This Python‐based workflow, called PTM‐Psi , integrates several established open‐source software packages, thereby enabling the user to infer protein structure from sequence, develop force fields for non‐standard amino acids using quantum mechanics, calculate free energy perturbations through molecular dynamics simulations, and score the bound complexes via docking algorithms. Using the S ‐nitrosylation of several cysteines on the GAP2 protein as an example, we demonstrated the utility of PTM‐Psi for interpreting sequence–structure–function relationships derived from thiol redox proteomics data. We demonstrate that the S ‐nitrosylated cysteine that is exposed to the solvent indirectly affects the catalytic reaction of another buried cysteine over a distance in GAP2 protein through the movement of the two ligands. Our workflow tracks the PTMs on residues that are responsive to changes in the redox environment and lays the foundation for the automation of molecular and systems biology modeling.

59 BASIC BIOLOGICAL SCIENCES↗

Ca X ML: Chemistry‐informed machine learning explains mutual changes between protein conformations and calcium ions in calcium‐binding proteins using structural and topological features

Proteins' flexibility is a feature in communicating changes in cell signaling instigated by binding with secondary messengers, such as calcium ions, associated with the coordination of muscle contraction, neurotransmitter release, and gene expression. When binding with the disordered parts of a protein, calcium ions must balance their charge states with the shape of calcium-binding proteins and their versatile pool of partners depending on the circumstances they transmit. Accurately determining the ionic charges of those ions is essential for understanding their role in such processes. However, it is unclear whether the limited experimental data available can be effectively used to train models to accurately predict the charges of calcium-binding protein variants. Here, we developed a chemistry-informed, machine-learning algorithm that implements a game theoretic approach to explain the output of a machine-learning model without the prerequisite of an excessively large database for high-performance prediction of atomic charges. We used the ab initio electronic structure data representing calcium ions and the structures of the disordered segments of calcium-binding peptides with surrounding water molecules to train several explainable models. Network theory was used to extract the topological features of atomic interactions in the structurally complex data dictated by the coordination chemistry of a calcium ion, a potent indicator of its charge state in protein. Our design created a computational tool of Ca X ML, which provided a framework of explainable machine learning model to annotate ionic charges of calcium ions in calcium-binding proteins in response to the chemical changes in an environment. Our framework will provide new insights into protein design for engineering functionality based on the limited size of scientific data in a genome space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Pseudoenzyme β‐Amylase9 From Arabidopsis Activates α‐Amylase3: A Possible Mechanism to Promote Stress‐Induced Starch Degradation

ABSTRACT Starch accumulation in plants provides carbon for nighttime use, for regrowth after periods of dormancy, and for times of stress. Both ɑ‐ and β‐amylases (AMYs and BAMs, respectively) catalyze starch hydrolysis, but their functional roles are unclear. Moreover, the presence of catalytically inactive amylases that show starch excess phenotypes when deleted presents questions on how starch degradation is regulated. Plants lacking one of these catalytically inactive β‐amylases, BAM9, have enhanced starch accumulation when combined with mutations in BAM1 and BAM3, the primary starch degrading BAMs in response to stress and at night, respectively. BAM9 has been reported to be transcriptionally induced by stress although the mechanism for BAM9 function is unclear. From yeast two‐hybrid experiments, we identified the plastid‐localized AMY3 as a potential interaction partner for BAM9. We found that BAM9 interacted with AMY3 in vitro and that BAM9 enhances AMY3 activity about three‐fold. Modeling of the AMY3‐BAM9 complex predicted a previously undescribed alpha–alpha hairpin in AMY3 that could serve as a potential interaction site. Additionally, AMY3 lacking the alpha–alpha hairpin is unaffected by BAM9. Structural analysis of AMY3 showed that it can form a homodimer in solution and that BAM9 appears to replace one of the AMY3 monomers to form a heterodimer. The presence of both BAM9 and AMY3 in many vascular plant lineages, along with model‐based evidence that they heterodimerize, suggests that the interaction is conserved. Collectively these data suggest that BAM9 is a pseudoamylase that activates AMY3 in response to cellular stress, possibly facilitating stress recovery.

Biochemistry & Molecular Biology↗

Tripartite interactions among free-living, N-fixing bacteria, arbuscular mycorrhizal fungi, and plants: Mutualistic benefits and community response to co-inoculation

Interactions between arbuscular mycorrhizal (AM) fungi and free-living nitrogen fixers (FLNF) occur in the rhizosphere where they can enhance plant nutrient acquisition, impact plant growth, and affect soil processes. Tripartite mutualism commonly occurs between nodule-forming plants, symbiotic diazotrophs, and AM fungi, and can occur between non-nodulating plants, FLNF, and AM fungi. However, information on the extent of, and controls on, tripartite mutualism in non-nodulating plant systems is limited to a small number of crop plants and culturable microbial inoculum, mostly in greenhouse growing conditions. We conducted a systematic literature review to synthesize the current understanding of the responses of plants, AM fungi, and FLNF to co-inoculation, as well as the conditions affecting tripartite mutualism and the magnitude and range of benefits conferred. Our review shows that plants generally benefit from co-inoculation with AM fungi and FLNF taxa, but benefits are highly variable and context dependent, ranging from 94% reduction in plant shoot biomass to 255% increase in total plant biomass. Additionally, the presence of AM fungi can increase abundance of FLNF and the presence of FLNF can increase AM fungal root colonization, but these responses also vary widely. Major factors influencing variation in response to co-inoculation by all organisms include plant phenology/age, soil type and nutrient availability, and partner pairing. There is potential for leveraging these tripartite mutualisms to improve plant productivity and soil microbial function, but successful application is more likely with a thorough understanding of the environmental and mechanistic controls on these relationships and testing of field-scale implementation.

59 BASIC BIOLOGICAL SCIENCES↗

Rigidity‐Driven Structural Isomers in the NaCl–Ga 2 S 3 System: Implications for Energy Storage

Alternative energy sources require the search for innovative materials with promising functionalities. Systems with unusual chemical properties represent an insufficiently explored domain, concealing unexpected features. Using diffraction and Raman spectroscopy over a wide temperature range, supported by first‐principles simulations, a rare phenomenon is unveiled: phase‐dependent chemical interactions between binary components in the NaCl–Ga 2 S 3 system. In this unique occurrence, previously intact binary crystalline species transform upon melting into mixed liquid structural isomers, forming bonds with new partners. The chemical combinatorics appears to be fully reversible for stable crystals and liquids. Despite this, rapidly frozen glasses out of thermodynamic equilibrium remain in a metastable isomeric state, offering remarkable properties, particularly a high room‐temperature Na + conductivity, comparable to the best sodium halide superionic conductors and therefore encouraging for sodium solid‐state batteries and energy applications. A rigidity paradigm is responsible for the observed phenomenon, as the extremely constrained Ga 2 S 3 crystal lattice does not survive viscous flow, breaking up at a short‐range level. The removal of rigidity constraints and dense packing leads to a significant increase in empty space, which is the origin of high sodium diffusivity. Broadly, the rigidity‐driven structural isomerism opens up an inspiring path to the discovery of atypical materials.

25 ENERGY STORAGE↗

Energy and Emission Prediction for Mixed-Vehicle Transit Fleets Using Multi-task and Inductive Transfer Learning

Public transit agencies are focused on making their fixed-line bus systems more energy efficient by introducing electric (EV) and hybrid (HV) vehicles to their fleets. However, because of the high upfront cost of these vehicles, most agencies are tasked with managing a mixed-fleet of internal combustion vehicles (ICEVs), EVs, and HVs. In managing mixed-fleets, agencies require accurate predictions of energy use for optimizing the assignment of vehicles to transit routes, scheduling charging, and ensuring that emission standards are met. The current state-of-the-art is to develop separate neural network models to predict energy consumption for each vehicle class. Although different vehicle classes’ energy consumption depends on a varied set of covariates, we hypothesize that there are broader generalizable patterns that govern energy consumption and emissions. In this paper, we seek to extract these patterns to aid learning to address two problems faced by transit agencies. First, in the case of a transit agency which operates many ICEVs, HVs, and EVs, we use multi-task learning (MTL) to improve accuracy of forecasting energy consumption. Second, in the case where there is a significant variation in vehicles in each category, we use inductive transfer learning (ITL) to improve predictive accuracy for vehicle class models with insufficient data. As this work is to be deployed by our partner agency, we also provide an online pipeline for joining the various sensor streams for fixed-line transit energy prediction. Here, we find that our approach outperforms vehicle-specific baselines in both the MTL and ITL settings.

97 MATHEMATICS AND COMPUTING↗

Search for electroweak production of a vector-like T quark using fully hadronic final states

A search is performed for electroweak production of a vector-like top quark partner T of charge 2/3 in association with a top or bottom quark, using proton-proton collision data at $\sqrt{s} =$ 13 TeV collected by the CMS experiment at the LHC in 2016. The data sample corresponds to an integrated luminosity of 35.9 fb$^{-1}$. The search targets T quarks over a wide range of masses and fractional widths, decaying to a top quark and either a Higgs boson or a Z boson in fully hadronic final states. The search is performed using two experimentally distinct signatures that depend on whether or not each quark from the decays of the top quark, Higgs boson, or Z boson produces an individual resolved jet. Jet substructure, b tagging, and kinematic variables are used to identify the top quark and boson jets, and also to suppress the standard model backgrounds. The data are found to be consistent with the expected backgrounds. Upper limits at 95% confidence level are set on the cross sections for T quark-mediated production of tHQq, tZQq, and their sum, where Q is the associated top or bottom heavy quark and q is another associated quark. The limits are given for each search signature for various T quark widths up to 30% of the T quark mass, and are between 2 pb and 20 fb for T quark masses in the range 0.6-2.6 TeV. These results are significantly more sensitive than prior searches for electroweak single production of T$\to$tH and represent the first constraints on T$\to$tZ using hadronic decays of the Z boson with this production mode.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Collider phenomenology of a gluino continuum

Continuum supersymmetry is a class of models in which the supersymmetric partners together with part of the standard model come from a conformal sector, broken in the IR near the TeV scale. Such models not only open new doors for addressing the problems of the standard model, but also have unique signatures at hadron colliders, which might explain why we have not yet seen any superpartners at the LHC. Here we use gauge-gravity duality to model the conformal sector, generate collider simulations, and finally analyze continuum gluino signatures at the LHC. Due to the increase in the number of jets produced the bounds are weaker than for the minimal supersymmetric standard model with the same gluino mass threshold.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Sparticle spectroscopy and dark matter in a U(1) B-L extension of MSSM

We consider a class of SUSY models in which the MSSM gauge group is supplemented with a gauged U(1) B-L symmetry and a global U(1) R symmetry. This extension introduces only electrically neutral states, and the new SUSY partners effectively double the number of states in the neutralino sector that now includes a blino (from B - L) and singlino from a gauge singlet superfield. If the DM density is saturated by a LSP neutralino, the model yields quite a rich phenomenology depending on the DM composition. The LSP relic density constraint provides a lower bound on the stop and gluino masses of about 3 TeV and 4 TeV respectively, which is testable in the near future collider experiments such as HL-LHC.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Non-Abelian electric field correlator at NLO for dark matter relic abundance and quarkonium transport

We perform a complete next-to-leading order calculation of the non-Abelian electric field correlator in a SU(N c ) plasma, which encodes properties of the plasma relevant for heavy particle bound state formation and dissociation, and is different from the correlator for the heavy quark diffusion coefficient. The calculation is carried out in the real-time formalism of thermal field theory and includes both vacuum and finite temperature contributions. By working in the R ξ gauge, we explicitly show the results are gauge independent, infrared and collinear safe. The renormalization group equation of this electric field correlator is determined by that of the strong coupling constant. Our next-to-leading order calculation can be directly applied to any dipole singlet-adjoint transition of heavy particle pairs. For example, it can be used to describe dissociation and (re)generation of heavy quarkonia inside the quark-gluon plasma well below the melting temperature, as well as heavy dark matter pairs (or charged co-annihilating partners) in the early universe.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Search for top squark pair production in a final state with two tau leptons in proton-proton collisions at $ \sqrt{s} =$ 13 TeV

A search for pair production of the supersymmetric partner of the top quark, the top squark, in proton-proton collision events at $ \sqrt{s} $ = 13 TeV is presented in a final state containing hadronically decaying tau leptons and large missing transverse momentum. This final state is highly sensitive to high-tan β or higgsino-like scenarios in which decays of electroweak gauginos to tau leptons are dominant. The search uses a data set corresponding to an integrated luminosity of 77.2 fb$^{−1}$, which was recorded with the CMS detector during 2016 and 2017. No significant excess is observed with respect to the background prediction. Exclusion limits at 95% confidence level are presented in the top squark and lightest neutralino mass plane within the framework of simplified models, in which top squark masses up to 1100 GeV are excluded for a nearly massless neutralino.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Search for squarks and gluinos in final states with jets and missing transverse momentum using 139 fb -1 of $ \sqrt{s} $ = 13 TeV pp collision data with the ATLAS detector

A search for the supersymmetric partners of quarks and gluons (squarks and gluinos) in final states containing jets and missing transverse momentum, but no electrons or muons, is presented. The data used in this search were recorded by the ATLAS experiment in proton-proton collisions at a centre-of-mass energy of $\sqrt{s}$ = 13 TeV during Run 2 of the Large Hadron Collider, corresponding to an integrated luminosity of 139 fb -1 . The results are interpreted in the context of various R -parity-conserving models where squarks and gluinos are produced in pairs or in association and a neutralino is the lightest supersymmetric particle. An exclusion limit at the 95% confidence level on the mass of the gluino is set at 2.30 TeV for a simplified model containing only a gluino and the lightest neutralino, assuming the latter is massless. For a simplified model involving the strong production of mass-degenerate first- and second-generation squarks, squark masses below 1.85 TeV are excluded if the lightest neutralino is massless. These limits extend substantially beyond the region of supersymmetric parameter space excluded previously by similar searches with the ATLAS detector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Exploring the phenomenology of weak adjoint scalars in minimal R -symmetric models

We examine the phenomenology of the scalar fields in weak and Higgs sectors of minimal R-symmetric models, in particular the ‘swino’ and ‘sbino’, the scalar partners to the chiral fields that marry the electroweak gauge bosons in Dirac gaugino models. These fields are in adjoint representations of SU(2) and U(1) and have both CP-even and CP-odd components. The interactions of these new states are summarized, and decay widths are computed analytically to one loop order. We discuss the tree level contributions of these new states to the mass spectrum of MSSM sfermions. We also explore production cross sections and decay signatures at colliders for several chosen benchmarks. We find that large regions of parameter space are unconstrained by present collider data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Dark freeze-out cogenesis

We propose a new mechanism where a multi-component dark sector generates the observed dark matter abundance and baryon asymmetry and thus addresses the coincidence between the two. The thermal freeze-out of dark matter annihilating into meta-stable dark partners sets the dark matter relic abundance while providing the out-of-equilibrium condition for baryogenesis. The meta-stable state triggers baryon asymmetry production by its decay well after the freeze-out and potentially induces a period of early matter domination before its decay. The dark matter and baryon abundances are related through number conservation within the dark sector (cogenesis). The “coincidence” is a natural outcome with GeV- to TeV-scale symmetric dark matter and the dark sector’s interactions with the Standard Model quarks. We present a UV-complete model and explore its phenomenological predictions, including dark matter direct detection signals, LHC signatures of new massive particles with color charges and long-lived particles with displaced vertices, dark matter-induced nucleon conversions, (exotic) dark matter indirect detection signals, and effects on the cosmological matter power spectrum. As a side result, we provide a novel analytical treatment for dark sector freeze-out, which may prove useful in the study of related scenarios.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Neutrino masses and magnetic moments of electron and muon in the Zee Model

We explore parameter space in the Zee Model to resolve the long-standing tension of the electron and muon anomalous magnetic moment (AMM). The model comprises a second Higgs doublet and a charged singlet at electroweak scale and generates Majorana neutrino masses at one-loop level; the neutral partner of the SU(2) L doublet contributes to the AMM of electron and muon via one loop and two-loop corrections. We propose two minimal flavor structures that can explain these anomalies while fitting the neutrino oscillation data. We find that the neutral Higgs resides in the mass range of roughly 10–300 GeV or 1–30 GeV, depending on the flavor structures. The model is consistent with constraints from colliders, electroweak precision data, and lepton flavor violation. To be comprehensive, we examine the constraints from the electric dipole moment (EDM) and find a region of parameter space that gives a sizable contribution to muon EDM while simultaneously giving corrections to muon AMM. In addition to the light scalar, the two charged scalars with masses as low as 100 GeV can induce nonstandard neutrino interactions ε ee as large as 8%, potentially hinting at new physics. We also investigate the projected capability of future lepton colliders to probe the currently allowed parameter space consistent with both electron and muon AMMs via direct searches in the ℓ + ℓ – → ℓ + ℓ – (H→ℓ + ℓ – )channel.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Heavy neutral leptons at muon colliders

The future high-energy muon colliders, featuring both high energy and low background, could play a critical role in our searches for new physics. The smallness of neutrino mass is a puzzle of particle physics. Broad classes of solutions to the neutrino puzzles can be best tested by seeking the partners of SM light neutrinos, dubbed as heavy neutral leptons (HNLs), at muon colliders. We can parametrize HNLs in terms of the mass m N and the mixing angle with ℓ-flavor U ℓ . In this work, we focus on the regime m N > O(100) GeV and study the projected sensitivities on the |U ℓ | 2 – m N plane with the full-reconstructable HNL decay into a hadronic W and a charged lepton. The projected reach in |U ℓ | 2 leads to the best sensitivities in the TeV realm.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗