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At least 955 records · Page 53

Experimental and Theoretical Study of Azimuth Angle and Polarization Dependences of Sum-Frequency-Generation Vibrational Spectral Features of Uniaxially Aligned Cellulose Crystals

Comprehensive interpretation of vibrational sum-frequency-generation (SFG) spectroscopic features of SFG-active nanodomains interspersed in amorphous bulk requires the knowledge of nonlinear susceptibility, χ ijk (2) , of the SFG-active phase as a function of its spatial arrangement in the bulk as well as the polarizations of the probe lights. Our work reports the full analysis of the azimuth angle and polarization dependence of SFG signals from a control sample consisting of uniaxially aligned cellulose Iβ crystals. The χ ijk (2) terms of cellulose were estimated from quantum mechanics calculations using time-dependent density functional theory (TD-DFT), and a simple structural model was built with truncated glucose dimers. The theoretical azimuth angle and polarization dependences of characteristic CH/CH 2 and OH stretch modes of cellulose were compared with the experimentally observed trends. These comparisons revealed that the relative polarity of crystallites within the SFG coherence length, the random quasi phase-matching of polycrystalline domains, and the preferential packing of crystallites in the bulk play important roles governing the spectral features. Compared to that of small molecules, the difference between chiral and achiral responses in SFG spectra is more difficult to confirm because of the inhomogeneous distribution of crystallites in the bulk sample.

59 BASIC BIOLOGICAL SCIENCES↗

The use of copulas to practical estimation of multivariate stochastic differential equation mixed effects models

A system of stochastic differential equations (SDE) with mixed-effects parameters and multivariate normal copula density function were used to develop tree height model for Scots pine trees in Lithuania. A two-step maximum likelihood parameter estimation method is used and computational guidelines are given. After fitting the conditional probability density functions to outside bark diameter at breast height, and total tree height, a bivariate normal copula distribution model was constructed. Predictions from the mixed-effects parameters SDE tree height model calculated during this research were compared to the regression tree height equations. The results are implemented in the symbolic computational language MAPLE.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Global leaf trait estimates biased due to plasticity in the shade

The study of leaf functional trait relationships, the so-called leaf economics spectrum , is based on the assumption of high-light conditions (as experienced by sunlit leaves). Owing to the exponential decrease of light availability through canopies, however, the vast majority of the world's vegetation exists in at least partial shade. Plant functional traits vary in direct dependence of light availability, with different traits varying to different degrees, sometimes in conflict with expectations from the economic spectrum. This means that the derived trait relationships of the global leaf economic spectrum are probably dependent on the extent to which observed data in existing large-scale plant databases represent high-light conditions. Here, using an extensive worldwide database of within-canopy gradients of key physiological, structural and chemical traits, along with three different global trait databases we show that: (1) accounting for light-driven trait plasticity can reveal novel trait relationships, particularly for highly plastic traits (for example, the relationship between net assimilation rate per area (A a ) and leaf mass per area (LMA)); and (2) a large proportion of leaf traits in current global plant databases reported as measured in full sun were probably measured in the shade. Our results show that even though the majority of leaves exist in the shade, along with a large proportion of observations, our current understanding is too focused on conditions in the sun.

59 BASIC BIOLOGICAL SCIENCES↗

Localized Active Space Pair-Density Functional Theory

Accurate quantum chemical methods for the prediction of spin-state energy gaps for strongly correlated systems are computationally expensive and scale poorly with the size of the system. This makes calculations for many experimentally interesting molecules impractical even with abundant computational resources. Previous work has shown that the localized active space (LAS) self-consistent field (SCF) method can be an efficient way to obtain multiconfiguration SCF wave functions of comparable quality to the corresponding complete active space (CAS) ones. To obtain quantitative results, a post-SCF method is needed to estimate the complete correlation energy. One such method is multiconfiguration pair-density functional theory (PDFT), which calculates the energy based on the density and on-top pair density obtained from a multiconfiguration wave function. In this work, we introduce localized-active-space PDFT, which uses a LAS wave function for subsequent PDFT calculations. The method is tested by computing spin-state energies and gaps in conjugated organic molecules and a bimetallic compound and comparing to the corresponding CAS-PDFT values.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Phylogenomics databases for facilitating functional genomics in rice

The completion of whole genome sequence of rice (Oryza sativa) has significantly accelerated functional genomics studies. Prior to the release of the sequence, only a few genes were assigned a function each year. Since sequencing was completed in 2005, the rate has exponentially increased. As of 2014, 1,021 genes have been described and added to the collection at The Overview of functionally characterized Genes in Rice online database (OGRO). Despite this progress, that number is still very low compared with the total number of genes estimated in the rice genome. One limitation to progress is the presence of functional redundancy among members of the same rice gene family, which covers 51.6 % of all non-transposable element-encoding genes. There remain a significant portion or rice genes that are not functionally redundant, as reflected in the recovery of loss-of-function mutants. To more accurately analyze functional redundancy in the rice genome, we have developed a phylogenomics databases for six large gene families in rice, including those for glycosyltransferases, glycoside hydrolases, kinases, transcription factors, transporters, and cytochrome P450 monooxygenases. In this review, we introduce key features and applications of these databases. We expect that they will serve as a very useful guide in the post-genomics era of research.

54 ENVIRONMENTAL SCIENCES↗

Fourier band-power E/B-mode estimators for cosmic shear

We introduce new Fourier band-power estimators for cosmic shear data analysis and E/B-mode separation. We consider both the case where one performs E/B-mode separation and the case where one does not. The resulting estimators have several nice properties which make them ideal for cosmic shear data analysis. First, they can be written as linear combinations of the binned cosmic shear correlation functions. Secondly, they account for the survey window function in real-space. Thirdly, they are unbiased by shape noise since they do not use correlation function data at zero separation. Fourthly, the band-power window functions in Fourier space are compact and largely non-oscillatory. Fifthly, they can be used to construct band-power estimators with very efficient data compression properties. In particular, we find that all of the information on the parameters Ωm, σ8 and ns in the shear correlation functions in the range of ~10–400 arcmin for single tomographic bin can be compressed into only three band-power estimates. Finally, we can achieve these rates of data compression while excluding small-scale information where the modelling of the shear correlation functions and power spectra is very difficult. Given these desirable properties, these estimators will be very useful for cosmic shear data analysis.

79 ASTRONOMY AND ASTROPHYSICS↗

Accuracy of first-principles interatomic interactions and predictions of ferroelectric phase transitions in perovskite oxides: Energy functional and effective Hamiltonian

While first-principles density functional theory (DFT)-based models have been effective in capturing the physics of ferroelectric phase transitions in BaTiO 3 , PbTiO 3 , and KNbO 3 , quantitative estimates of the transition temperatures (T C ) have errors that are believed to originate from the errors in estimating lattice constants obtained within the local density approximation (LDA) and generalized gradient approximation (GGA) of DFT. The recently developed strongly constrained and appropriately normed (SCAN) meta-GGA functional has been shown to be quite accurate in the estimation of lattice constants. Here, we present a quantitative analysis of the estimates of ferroelectric ground-state properties of eight perovskite oxides and transition temperatures of BaTiO 3 , PbTiO 3 , and KNbO 3 obtained with molecular dynamics simulations using an effective Hamiltonian derived from the SCAN meta-GGA-based DFT. Relative to LDA, we find an improvement in the estimates of T C , which arises from the changes in the calculated strain-phonon, anharmonic coupling constants, and strength of ferroelectric instabilities, i.e., frequencies of the soft modes. We also assess the errors in T C originating from approximately integrating out the high-energy phonons during construction of the model Hamiltonian through estimates of the effects of fourth-order couplings between the soft mode and higher-energy modes of BaTiO 3 , PbTiO 3 , and KNbO 3 . We find that inclusion of these anharmonic couplings results in deeper double-well energy functions of ferroelectric distortions and further improvement in the estimates of transition temperatures. Consistently improved estimates of lattice constants and transition temperatures with the SCAN meta-GGA calculations augur well for their use in simulations of superlattices or heterostructures of perovskite oxides, in which the effects of lattice matching are critical.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Potential and limitations of inferring ecosystem photosynthetic capacity from leaf functional traits

Abstract The aim of this study was to systematically analyze the potential and limitations of using plant functional trait observations from global databases versus in situ data to improve our understanding of vegetation impacts on ecosystem functional properties ( EFP s). Using ecosystem photosynthetic capacity as an example, we first provide an objective approach to derive robust EFP estimates from gross primary productivity ( GPP ) obtained from eddy covariance flux measurements. Second, we investigate the impact of synchronizing EFP s and plant functional traits in time and space to evaluate their relationships, and the extent to which we can benefit from global plant trait databases to explain the variability of ecosystem photosynthetic capacity. Finally, we identify a set of plant functional traits controlling ecosystem photosynthetic capacity at selected sites. Suitable estimates of the ecosystem photosynthetic capacity can be derived from light response curve of GPP responding to radiation (photosynthetically active radiation or absorbed photosynthetically active radiation). Although the effect of climate is minimized in these calculations, the estimates indicate substantial interannual variation of the photosynthetic capacity, even after removing site‐years with confounding factors like disturbance such as fire events. The relationships between foliar nitrogen concentration and ecosystem photosynthetic capacity are tighter when both of the measurements are synchronized in space and time. When using multiple plant traits simultaneously as predictors for ecosystem photosynthetic capacity variation, the combination of leaf carbon to nitrogen ratio with leaf phosphorus content explains the variance of ecosystem photosynthetic capacity best (adjusted R 2 = 0.55). Overall, this study provides an objective approach to identify links between leaf level traits and canopy level processes and highlights the relevance of the dynamic nature of ecosystems. Synchronizing measurements of eddy covariance fluxes and plant traits in time and space is shown to be highly relevant to better understand the importance of intra‐ and interspecific trait variation on ecosystem functioning.

54 ENVIRONMENTAL SCIENCES↗

Linear Distribution System State Estimation Using Synchrophasor Data and Pseudo-Measurement

State estimation is often a challenging task in distribution systems due to deploying a limited number of measurement devices. Moreover, the integration of precise distributionlevel phasor measurement unites, a.k.a micro-PMUs, along with inaccurate pseudo-measurements in state estimation introduces another challenge. These issues might decrease the efficiency of traditional standard weighted least squares (WLS) for distribution system state estimation. This paper proposes a novel linear distribution system state estimation with taken different types of measurements, including micro-PMU measurements and line current measurements, into account. To involve pseudomeasurements into the linear state estimation, a linearization method based on the Taylor’s approximation is adopted to reformulate pseudo-measurement functions in a linear form. The results obtained via numerical simulations show that the proposed linear state estimation method performs similarly to the standard nonlinear WLS estimator. In addition, the sensitivity analyses results show that our method has a better performance compared to WLS once a limited number of highly precise micro-PMUs are accompanied with inaccurate pseudo-measurements in state estimation.

State estimation Distribution system Micro-PMU Lin↗

Representing Complex Systems as Graphs for Debugging and Predictive Maintenance-Preliminary Thoughts

Representing complex systems as graphs enables use of mathematical tools to identify faults or predict failures. Graph nodes correspond to individual modules or subsystems, and edges link coupled system parts. ‘Probes’ measure the node outputs, monitoring the system health for unexpected behavior. Assuming one cannot probe every point, within a system, the fault correlates to a region—not necessarily the specific location. Bayesian networks trained to understand fault patterns can accurately identify the source. The diagnostic tool described aides debugging by pinpointing system failure causes. For predictive maintenance, probe data develop probability distribution functions describing subsystem mean time to failure. Unit lifetime can be estimated through these probability distributions. Two approaches include using Bayesian classifiers to infer the system failure source and developing maintenance schedules by treating systems as collections of random variables. When failure behavior does not follow a closed form function, use of similarity models is proposed.

97 MATHEMATICS AND COMPUTING↗

Combining pairwise structural similarity and deep learning interface contact prediction to estimate protein complex model accuracy in CASP15

Abstract Estimating the accuracy of quaternary structural models of protein complexes and assemblies (EMA) is important for predicting quaternary structures and applying them to studying protein function and interaction. The pairwise similarity between structural models is proven useful for estimating the quality of protein tertiary structural models, but it has been rarely applied to predicting the quality of quaternary structural models. Moreover, the pairwise similarity approach often fails when many structural models are of low quality and similar to each other. To address the gap, we developed a hybrid method (MULTICOM_qa) combining a pairwise similarity score (PSS) and an interface contact probability score (ICPS) based on the deep learning inter‐chain contact prediction for estimating protein complex model accuracy. It blindly participated in the 15th Critical Assessment of Techniques for Protein Structure Prediction (CASP15) in 2022 and performed very well in estimating the global structure accuracy of assembly models. The average per‐target correlation coefficient between the model quality scores predicted by MULTICOM_qa and the true quality scores of the models of CASP15 assembly targets is 0.66. The average per‐target ranking loss in using the predicted quality scores to rank the models is 0.14. It was able to select good models for most targets. Moreover, several key factors (i.e., target difficulty, model sampling difficulty, skewness of model quality, and similarity between good/bad models) for EMA are identified and analyzed. The results demonstrate that combining the multi‐model method (PSS) with the complementary single‐model method (ICPS) is a promising approach to EMA.

59 BASIC BIOLOGICAL SCIENCES↗

Path integral Monte Carlo simulations of H{sub 2} adsorbed to lithium-doped benzene: A model for hydrogen storage materials

Finite temperature quantum and anharmonic effects are studied in H{sub 2}–Li{sup +}-benzene, a model hydrogen storage material, using path integral Monte Carlo (PIMC) simulations on an interpolated potential energy surface refined over the eight intermolecular degrees of freedom based upon M05-2X/6-311+G(2df,p) density functional theory calculations. Rigid-body PIMC simulations are performed at temperatures ranging from 77 K to 150 K, producing both quantum and classical probability density histograms describing the adsorbed H{sub 2}. Quantum effects broaden the histograms with respect to their classical analogues and increase the expectation values of the radial and angular polar coordinates describing the location of the center-of-mass of the H{sub 2} molecule. The rigid-body PIMC simulations also provide estimates of the change in internal energy, ΔU{sub ads}, and enthalpy, ΔH{sub ads}, for H{sub 2} adsorption onto Li{sup +}-benzene, as a function of temperature. These estimates indicate that quantum effects are important even at room temperature and classical results should be interpreted with caution. Our results also show that anharmonicity is more important in the calculation of U and H than coupling—coupling between the intermolecular degrees of freedom becomes less important as temperature increases whereas anharmonicity becomes more important. The most anharmonic motions in H{sub 2}–Li{sup +}-benzene are the “helicopter” and “ferris wheel” H{sub 2} rotations. Treating these motions as one-dimensional free and hindered rotors, respectively, provides simple corrections to standard harmonic oscillator, rigid rotor thermochemical expressions for internal energy and enthalpy that encapsulate the majority of the anharmonicity. At 150 K, our best rigid-body PIMC estimates for ΔU{sub ads} and ΔH{sub ads} are −13.3 ± 0.1 and −14.5 ± 0.1 kJ mol{sup −1}, respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Explaining the extra crystal-field mode in 𝐴 ⁢Ce ⁢𝑋 2 (𝐴 = K, Rb, Na; 𝑋 = O, S, Se, Te)

A growing list of Ce-based magnets have shown an extra and heretofore unexplained crystal electric field (CEF) mode at high energies. We describe a process whereby an optical phonon can produce a split CEF mode well above the phonon energy. We use density functional theory and point-charge model calculations to estimate the phonon distortions and coupling to model this effect in KCeO 2 , showing that it accounts for the extra CEF mode observed. Furthermore, this mechanism is generic and may explain the extra modes observed on a variety of Ce 3+ compounds.

36 MATERIALS SCIENCE↗

Complete collision data set for electrons scattering on molecular hydrogen and its isotopologues: III. Vibrational excitation via electronic excitation and radiative decay

We present state-resolved cross sections for vibrational excitation via electronic excitation followed by radiative decay (ERD), for electrons scattering on all bound vibrational levels of the ground electronic state ($X\hspace{1.5 mm} ^1Σ_g^+$) of molecular hydrogen and its isotopologues (H 2 , HD, HT, D 2 , DT and T 2 ). We consider excitation of the singlet $\textit{n}$ = 2–3 states (where n refers to the united-atoms-limit principle quantum number) and account for all possible decay pathways back to the bound vibrational levels of the ground electronic state ($X\hspace{1.5 mm} ^1Σ_g^+$) to produce an estimate for the ERD cross sections. A selection of the results are presented in graphical form and a full data set is provided as both numerical values and analytic fit functions in supplementary data files. The uncertainty in the cross sections is estimated to be 11%, except for scattering on the highest bound vibrational level of HD, HT, D 2 , and DT, where the uncertainty is 21%. The data can be downloaded from the MCCC database at mccc-db.org.

74 ATOMIC AND MOLECULAR PHYSICS↗

Methodology for Estimating Thermal and Neutron Embrittlement of Cast Austenitic Stainless Steels During Service in Light Water Reactors

Cast austenitic stainless steel (CASS) materials, which have a duplex structure consisting of austenite and ferrite phases, are susceptible to thermal embrittlement during reactor service. In addition, the prolonged exposure of these materials, which are used in reactor core internals, to neutron irradiation changes their microstructure and microchemistry, and these changes degrade their fracture properties even further. This paper presents a revision of the procedure and correlations presented in NUREG/CR-4513, Rev. 1 (Aug. 1994) for predicting the change in fracture toughness and tensile properties of CASS components due to thermal aging during service in light water reactors (LWRs) at 280–330 °C (535–625 °F). The methodology is applicable to CF-3, CF-3M, CF-8, and CF-8M materials with a ferrite content of up to 40%. The fracture toughness, tensile strength, and Charpy-impact energy of aged CASS materials are estimated from known material information. Embrittlement is characterized in terms of room-temperature (RT) Charpy-impact energy. The extent or degree of thermal embrittlement at “saturation” (i.e., the minimum impact energy that can be achieved for a material after long-term aging) is determined from the chemical composition of the material. Charpy-impact energy as a function of the time and temperature of reactor service is estimated from the kinetics of thermal embrittlement, which are also determined from the chemical composition. The fracture toughness J-R curve for the aged material is then obtained by correlating RT Charpy-impact energy with fracture toughness parameters. A common “predicted lower-bound” J-R curve for CASS materials of unknown chemical composition is also defined for a given grade of material, range of ferrite content, and temperature. In addition, guidance is provided for evaluating the combined effects of thermal and neutron embrittlement of CASS materials used in the reactor core internal components. The correlations for estimating the change in tensile strength, including the Ramberg/Osgood parameters for strain hardening, are also described.

Chopra, O. K.↗

Nonparametric Method of Least Squares: Accounting for Seasonality

We consider the problem of restoring a nonparametric dependence described by the sum of linear trend and seasonal component, i.e., a periodic function with the known period. We obtain the asymptotic distribution of the parameter estimates and the trend component. We find the mathematical expectation of the residual sum of squares. We also develop the methods of estimation of the seasonal component and construction of the interval forecast.

97 MATHEMATICS AND COMPUTING↗

X-Ray Bolometric Corrections for Compton-thick Active Galactic Nuclei

We present X-ray bolometric correction factors, κ{sub Bol} (≡L{sub Bol}/L{sub X}), for Compton-thick (CT) active galactic nuclei (AGNs) with the aim of testing AGN torus models, probing orientation effects, and estimating the bolometric output of the most obscured AGNs. We adopt bolometric luminosities, L{sub Bol}, from literature infrared (IR) torus modeling and compile published intrinsic 2–10 keV X-ray luminosities, L{sub X}, from X-ray torus modeling of NuSTAR data. Our sample consists of 10 local CT AGNs, where both of these estimates are available. We test for systematic differences in κ{sub Bol} values produced when using two widely used IR torus models and two widely used X-ray torus models, finding consistency within the uncertainties. We find that the mean κ{sub Bol} of our sample in the range of L{sub Bol}≈10{sup 42}--10{sup 45} erg s{sup −1} is log{sub 10} κ{sub Bol} = 1.44 ± 0.12 with an intrinsic scatter of ∼0.2 dex, and that our derived κ{sub Bol} values are consistent with previously established relationships between κ{sub Bol} and L{sub Bol} and κ{sub Bol} and Eddington ratio (λ{sub Edd}). We investigate if κ{sub Bol} is dependent on N{sub H} by comparing our results on CT AGNs to published results on less-obscured AGNs, finding no significant dependence. Since many of our sample are megamaser AGNs, known to be viewed edge-on, and furthermore under the assumptions of AGN unification whereby unobscured AGNs are viewed face-on, our result implies that the X-ray emitting corona is not strongly anisotropic. Finally, we present κ{sub Bol} values for CT AGNs identified in X-ray surveys as a function of their observed L{sub X}, where an estimate of their intrinsic L{sub X} is not available, and redshift, useful for estimating the bolometric output of the most obscured AGNs across cosmic time.

79 ASTRONOMY AND ASTROPHYSICS↗

Action-based dynamical modeling for the Milky Way disk

We present RoadMapping, a full-likelihood dynamical modeling machinery that aims to recover the Milky Way’s (MW) gravitational potential from large samples of stars in the Galactic disk. RoadMapping models the observed positions and velocities of stars with a parameterized, three-integral distribution function (DF) in a parameterized axisymmetric potential. We investigate through differential test cases with idealized mock data how the breakdown of model assumptions and data properties affect constraints on the potential and DF. Our key results are: (i) If the MW’s true potential is not included in the assumed model potential family, we can—in the axisymmetric case—still find a robust estimate for the potential, with only ≲10% difference in surface density within |z|⩽1.1 kpc inside the observed volume. (ii) Modest systematic differences between the true and model DF are inconsequential. E.g., when binning stars to define sub-populations with simple DFs, binning errors do not affect the modeling as long as the DF parameters of neighboring bins differ by <20%. In addition, RoadMapping ensures unbiased potential estimates for either (iii) small misjudgements of the spatial selection function (i.e., ≲15% at the survey volume’s edge), (iv) if distances are known to within 10%, or (v) if proper motion uncertainties are known within 10% or are smaller than δμ≲1 mas yr{sup −1}. Challenges are the rapidly increasing computational costs for large sample sizes. Overall, RoadMapping is well suited to making precise new measurements of the MW’s potential with data from the upcoming Gaia releases.

79 ASTRONOMY AND ASTROPHYSICS↗