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At least 667 records · Page 37

Relationships between Vehicle Pricing and Features: Data Driven Analysis of the Chinese Vehicle Market

A full-scale understanding of the dynamics of the Chinese vehicle market can benefit stakeholders with respect to rational decision-making and effective long-term investment. This study attempts to discover the common vehicle pricing patterns in the Chinese market by quantifying statistical correlations among critical vehicle features from intrinsic powertrain systems to extrinsic market positioning. The data samples involve almost all passenger vehicle models sold in 2013 to 2019. After comparing multiple statistical methodologies, a log-transformation variant of the multinomial linear regression model was found to be the best one, and the goodness of fit shows that this model can offer stable estimates, which were validated using 2019 market data. The insights achieved are: (1) The price and major performance features of SUVs/crossovers are similar to those of sedans; (2) If all other explicit features remain the same, the price of a Japanese midsize sedan is 62% higher than that of a Chinese midsize sedan, and European midsize vehicles have the highest prices overall. (3) The incremental price of fuel consumption varies by vehicle class and fuel economy. For example, from 30 to 50 MPG, the vehicle price increases by $119 for a Chinese brand sedan vehicle, by $69 for a Chinese brand SUV.

33 ADVANCED PROPULSION SYSTEMS↗

Electric Double-Layer Structure in Primitive Model Electrolytes. Comparing Molecular Dynamics with Local-Density Approximations

We evaluate the accuracy of local-density approximations (LDAs) using explicit molecular dynamics simulations of binary electrolytes comprised of equisized ions in an implicit solvent. The Bikerman LDA, which considers ions to occupy a lattice, poorly captures excluded volume interactions between primitive model ions. Instead, LDAs based on the Carnahan–Starling (CS) hard-sphere equation of state capture simulated values of ideal and excess chemical potential profiles extremely well, as is the relationship between surface charge density and electrostatic potential. Excellent agreement between the EDL capacitances predicted by CS-LDAs and computed in molecular simulations is found even in systems where ion correlations drive strong density and free charge oscillations within the EDL, despite the inability of LDAs to capture the oscillations in the detailed EDL profiles.

25 ENERGY STORAGE↗

Impact of point spread function higher moments error on weak gravitational lensing – II. A comprehensive study

ABSTRACT Weak lensing is one of the most powerful probes for dark matter and dark energy science, although it faces increasing challenges in controlling systematic uncertainties as the statistical errors become smaller. The point spread function (PSF) needs to be precisely modeled to avoid systematic error on the weak lensing measurements. The weak lensing biases induced by errors in the PSF model second moments, i.e. its size and shape, are well-studied. However, Zhang et al. showed that errors in the higher moments of the PSF may also be a significant source of systematics for upcoming weak lensing surveys. Therefore, this work comprehensively investigate the modelling quality of PSF moments from the 3rd to 6th order, and propagate the PSFEx higher moments modelling error in the HSC survey data set to the weak lensing shear–shear correlation functions and their cosmological analyses. The overall multiplicative shear bias associated with errors in PSF higher moments can cause an ∼0.1σ shift on the cosmological parameters for LSST Y10, while the associated additive biases can induce 1σ uncertainties in cosmology parameter inference for LSST Y10, if not accounted. We compare the PSFEx model with PSF in Full FOV, and find similar performance in modelling the PSF higher moments. We conclude that PSF higher moment errors of the future PSF models should be reduced from those in current methods, otherwise needed to be explicitly modeled in the weak lensing analysis.

79 ASTRONOMY AND ASTROPHYSICS↗

General solution to the electric double layer with discrete interfacial charges

We provide extensive molecular dynamics simulations of counterion and coion distributions near an impenetrable plane with fixed discrete charges. The numerical results are described by an explicit solution that distinguishes the plasma (math/σ>3) and the binding regime (math/σ<3) where σ is the ion diameter and Ac = |e/ν| (ν is the surface charge density). In the plasma regime, the solution consists of a product of two functions that can be computed from simpler models and reveals that the effects of the discreteness of the charge extends over large distances from the plane. The solution in the binding regime consists of a Stern layer of width σ and a diffuse layer, but contrary to standard approaches, the strong correlations between ions within the Stern layer and the diffuse layer require a description in terms of a “displaced” diffuse layer. The solution is found to describe electrolytes of any valence at all concentrations investigated (up to 0.4M) and includes the case of additional specific interactions such as van der Waals attraction and other generalizations. We discuss some open questions.

36 MATERIALS SCIENCE↗

Holographic Entropy Relations

Abstract We develop a framework for the derivation of new information theoretic quantities which are natural from a holographic perspective. We demonstrate the utility of our techniques by deriving the tripartite information (the quantity associated to monogamy of mutual information) using a set of abstract arguments involving bulk extremal surfaces. Our arguments rely on formal manipulations of surfaces and not on local surgery or explicit computation of entropies through the holographic entanglement entropy prescriptions. As an application, we show how to derive a family of similar information quantities for an arbitrary number of parties. The present work establishes the foundation of a broader program that aims at the understanding of the entanglement structures of geometric states for an arbitrary number of parties. We stress that our method is completely democratic with respect to bulk geometries and is equally valid in static and dynamical situations. While rooted in holography, we expect that our construction will provide a useful characterization of multipartite correlations in quantum field theories.

Hubeny, Veronika E.↗

Coaction and double-copy properties of configuration-space integrals at genus zero

We investigate configuration-space integrals over punctured Riemann spheres from the viewpoint of the motivic Galois coaction and double-copy structures generalizing the Kawai-Lewellen-Tye (KLT) relations in string theory. For this purpose, explicit bases of twisted cycles and cocycles are worked out whose orthonormality simplifies the coaction. We present methods to efficiently perform and organize the expansions of configuration-space integrals in the inverse string tension α' or the dimensional-regularization parameter ϵ of Feynman integrals. Generating-function techniques open up a new perspective on the coaction of multiple polylogarithms in any number of variables and analytic continuations in the unintegrated punctures. We present a compact recursion for a generalized KLT kernel and discuss its origin from intersection numbers of Stasheff polytopes and its implications for correlation functions of two-dimensional conformal field theories. We find a non-trivial example of correlation functions in (p, 2) minimal models, which can be normalized to become uniformly transcendental in the p → ∞ limit.

Conformal Field Theory↗

Phase transition from fcc to bcc structure of the Cu-clusters during nanocrystallization of Fe{sub 85.2}Si{sub 1}B{sub 9}P{sub 4}Cu{sub 0.8} soft magnetic alloy

A role of Cu on the nanocrystallization of an Fe{sub 85.2}Si{sub 1}B{sub 9}P{sub 4}Cu{sub 0.8} alloy was investigated by X-ray absorption fine structure (XAFS) and transmission electron microscopy (TEM). The Cu K-edge XAFS results show that local structure around Cu is disordered for the as-quenched sample whereas it changes to fcc-like structure at 613 K. The fcc Cu-clusters are, however, thermodynamically unstable and begin to transform into bcc structure at 638 K. An explicit bcc structure is observed for the sample annealed at 693 K for 600 s in which TEM observation shows that precipitated bcc-Fe crystallites with ∼12 nm are homogeneously distributed. The bcc structure of the Cu-clusters transforms into the fcc-type again at 973 K, which can be explained by the TEM observations; Cu segregates at grain boundaries between bcc-Fe crystallites and Fe{sub 3}(B,P) compounds. Combining the XAFS results with the TEM observations, the structure transition of the Cu-clusters from fcc to bcc is highly correlated with the preliminary precipitation of the bcc-Fe which takes place prior to the onset of the first crystallization temperature, T{sub x1} = 707 K. Thermodynamic analysis suggests that an interfacial energy density γ between an fcc-Cu cluster and bcc-Fe matrix dominates at a certain case over the structural energy between fcc and bcc Cu, ΔG{sub fcc} {sub −} {sub bcc}, which causes phase transition of the Cu clusters from fcc to bcc structure.

36 MATERIALS SCIENCE↗

Poisson Equation for a (General) Homogeneous d-Dimensional Ellipsoid with Applications to Beam Envelope Tracking

This note describes the solution of the free-space Poisson equation in the interior of a $d$-dimensional homogeneous ellipsoid, and the associated space charge fields. An explicit formula (\ref{Sformula}) is provided that relates the $d\times d$ matrix describing the space charge (quadratic) potential to the $d\times d$ covariance matrix of the ellipsoid. For the cases $d=2$ and $d=3$, this result is used to determine the linear map corresponding to a space charge kick, that may be used to push the beam $6\times 6$ covariance matrix during envelope tracking. The treatment of upright ellipsoids for $d=2$ and $d=3$ is well-represented in the literature. However, the approach taken here emphasizes a general ellipsoid with arbitrary correlations in any dimension. The Appendix provides a general solution of the free-space Poisson equation in dimension $d$ for a source distribution with ellipsoidal symmetry.

97 MATHEMATICS AND COMPUTING↗

Exciton–Phonon Coupling Induces a New Pathway for Ultrafast Intralayer-to-Interlayer Exciton Transition and Interlayer Charge Transfer in WS 2 –MoS 2 Heterostructure: A First-Principles Study

Despite the weak, van der Waals interlayer coupling, photoinduced charge transfer vertically across atomically thin interfaces can occur within surprisingly fast, sub-50 fs time scales. An early theoretical understanding of charge transfer is based on a noninteracting picture, neglecting excitonic effects that dominate optical properties of such materials. We employ an ab initio many-body perturbation theory approach, which explicitly accounts for the excitons and phonons in the heterostructure. Our large-scale first-principles calculations directly probe the role of exciton-phonon coupling in the charge dynamics of the WS 2 /MoS 2 heterobilayer. We find that the exciton-phonon interaction induced relaxation time of photoexcited excitons at the K valley of MoS 2 and WS 2 is 67 and 15 fs at 300 K, respectively, which sets a lower bound to the intralayer-to-interlayer exciton transfer time and is consistent with experiment reports. We further show that electron-hole correlations facilitate novel transfer pathways that are otherwise inaccessible to noninteracting electrons and holes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Controlling protein adsorption modes electrostatically

Protein adsorption on surfaces is ubiquitous in biology and in biotechnology. There are various forces required for controlling protein adsorption. Here, we introduce an explicit ion coarse-grained molecular dynamics simulation approach for studying the effects of electrostatics on protein adsorption, and 2D protein assembly on charged surfaces. Our model accounts for the spatial distribution of protein charges. We use catalase as our model protein. We find that the preferential adsorption mode of proteins at low protein concentration on a charged surface is “standing up”. When the protein concentration in a solution increases to reach a critical density on the surface, the adsorption mode switches from “standing up” to a mixed state “flat on” and “standing up”, which increases the lateral correlations among the adsorbed proteins. As such, the changes in the adsorption mode arise from the protein adsorption that cancel the surface charge and the protein–protein repulsion. This correlated surface structure melts as the salt concentration increases because the charged surface is cancelled by the salt ions and the proteins de-adsorb. For the case of strongly charged surfaces the “standing up” conformation remains more favorable even at high protein adsorption at low salt concentrations since in that conformation the surface charge is cancelled more effectively, generating an even more laterally correlated structure. We elucidate the effects of parameters such as surface charge density, salt concentration, and protein charges on the different adsorption modes and the structure and organization of proteins on the charged surfaces. Finally, this study provides a guide for controlling protein assembly on surfaces.

59 BASIC BIOLOGICAL SCIENCES↗

Coordination Sphere of Lanthanide Aqua Ions Resolved with Ab Initio Molecular Dynamics and X-ray Absorption Spectroscopy

To resolve the fleeting structures of lanthanide Ln 3+ aqua ions in solution, we (i) performed the first ab initio molecular dynamics (AIMD) simulations of the entire series of Ln 3+ aqua ions in explicit water solvent using pseudopotentials and basis sets recently optimized for lanthanides and (ii) measured the symmetry of the hydrating waters about Ln 3+ ions (Nd 3+ , Dy 3+ , Er 3+ , Lu 3+ ) for the first time with extended X-ray absorption fine structure (EXAFS). EXAFS spectra were measured experimentally and generated from AIMD trajectories to directly compare simulation, which concurrently considers the electronic structure and the atomic dynamics in solution, with experiment. In this study, we performed a comprehensive evaluation of EXAFS multiple-scattering analysis (up to 6.5 Å) to measure Ln–O distances and angular correlations (i.e., symmetry) and elucidate the molecular geometry of the first hydration shell. This evaluation, in combination with symmetry-dependent L 3 - and L 1 -edge spectral analysis, shows that the AIMD simulations remarkably reproduces the experimental EXAFS data. The error in the predicted Ln–O distances is less than 0.07 Å for the later lanthanides, while we observed excellent agreement with predicted distances within experimental uncertainty for the early lanthanides. Our analysis revealed a dynamic, symmetrically disordered first coordination shell, which does not conform to a single molecular geometry for most lanthanides. This work sheds critical light on the highly elusive coordination geometry of the Ln 3+ aqua ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Prostatome: A combined anatomical and disease based MRI atlas of the prostate

Purpose: In this work, the authors introduce a novel framework, the anatomically constrained registration (AnCoR) scheme and apply it to create a fused anatomic-disease atlas of the prostate which the authors refer to as the prostatome. The prostatome combines a MRI based anatomic and a histology based disease atlas. Statistical imaging atlases allow for the integration of information across multiple scales and imaging modalities into a single canonical representation, in turn enabling a fused anatomical-disease representation which may facilitate the characterization of disease appearance relative to anatomic structures. While statistical atlases have been extensively developed and studied for the brain, approaches that have attempted to combine pathology and imaging data for study of prostate pathology are not extant. This works seeks to address this gap. Methods: The AnCoR framework optimizes a scoring function composed of two surface (prostate and central gland) misalignment measures and one intensity-based similarity term. This ensures the correct mapping of anatomic regions into the atlas, even when regional MRI intensities are inconsistent or highly variable between subjects. The framework allows for creation of an anatomic imaging and a disease atlas, while enabling their fusion into the anatomic imaging-disease atlas. The atlas presented here was constructed using 83 subjects with biopsy confirmed cancer who had pre-operative MRI (collected at two institutions) followed by radical prostatectomy. The imaging atlas results from mapping thein vivo MRI into the canonical space, while the anatomic regions serve as domain constraints. Elastic co-registration MRI and corresponding ex vivo histology provides “ground truth” mapping of cancer extent on in vivo imaging for 23 subjects. Results: AnCoR was evaluated relative to alternative construction strategies that use either MRI intensities or the prostate surface alone for registration. The AnCoR framework yielded a central gland Dice similarity coefficient (DSC) of 90%, and prostate DSC of 88%, while the misalignment of the urethra and verumontanum was found to be 3.45 mm, and 4.73 mm, respectively, which were measured to be significantly smaller compared to the alternative strategies. As might have been anticipated from our limited cohort of biopsy confirmed cancers, the disease atlas showed that most of the tumor extent was limited to the peripheral zone. Moreover, central gland tumors were typically larger in size, possibly because they are only discernible at a much later stage. Conclusions: The authors presented the AnCoR framework to explicitly model anatomic constraints for the construction of a fused anatomic imaging-disease atlas. The framework was applied to constructing a preliminary version of an anatomic-disease atlas of the prostate, the prostatome. The prostatome could facilitate the quantitative characterization of gland morphology and imaging features of prostate cancer. These techniques, may be applied on a large sample size data set to create a fully developed prostatome that could serve as a spatial prior for targeted biopsies by urologists. Additionally, the AnCoR framework could allow for incorporation of complementary imaging and molecular data, thereby enabling their careful correlation for population based radio-omics studies.

60 APPLIED LIFE SCIENCES↗

Price equation captures the role of drug interactions and collateral effects in the evolution of multidrug resistance

Bacterial adaptation to antibiotic combinations depends on the joint inhibitory effects of the two drugs (drug interaction [DI]) and how resistance to one drug impacts resistance to the other (collateral effects [CE]). Here we model these evolutionary dynamics on two-dimensional phenotype spaces that leverage scaling relations between the drug-response surfaces of drug-sensitive (ancestral) and drug-resistant (mutant) populations. We show that evolved resistance to the component drugs – and in turn, the adaptation of growth rate – is governed by a Price equation whose covariance terms encode geometric features of both the two-drug-response surface (DI) in ancestral cells and the correlations between resistance levels to those drugs (CE). Within this framework, mean evolutionary trajectories reduce to a type of weighted gradient dynamics, with the drug interaction dictating the shape of the underlying landscape and the collateral effects constraining the motion on those landscapes. We also demonstrate how constraints on available mutational pathways can be incorporated into the framework, adding a third key driver of evolution. Our results clarify the complex relationship between drug interactions and collateral effects in multidrug environments and illustrate how specific dosage combinations can shift the weighting of these two effects, leading to different and temporally explicit selective outcomes.

Gjini, Erida↗

SpArcFiRe: Scalable automated detection of spiral galaxy arm segments

Given an approximately centered image of a spiral galaxy, we describe an entirely automated method that finds, centers, and sizes the galaxy (possibly masking nearby stars and other objects if necessary in order to isolate the galaxy itself) and then automatically extracts structural information about the spiral arms. For each arm segment found, we list the pixels in that segment, allowing image analysis on a per-arm-segment basis. We also perform a least-squares fit of a logarithmic spiral arc to the pixels in that segment, giving per-arc parameters, such as the pitch angle, arm segment length, location, etc. The algorithm takes about one minute per galaxies, and can easily be scaled using parallelism. We have run it on all ∼644,000 Sloan objects that are larger than 40 pixels across and classified as 'galaxies'. We find a very good correlation between our quantitative description of a spiral structure and the qualitative description provided by Galaxy Zoo humans. Our objective, quantitative measures of structure demonstrate the difficulty in defining exactly what constitutes a spiral 'arm', leading us to prefer the term 'arm segment'. We find that pitch angle often varies significantly segment-to-segment in a single spiral galaxy, making it difficult to define the pitch angle for a single galaxy. We demonstrate how our new database of arm segments can be queried to find galaxies satisfying specific quantitative visual criteria. For example, even though our code does not explicitly find rings, a good surrogate is to look for galaxies having one long, low-pitch-angle arm—which is how our code views ring galaxies. SpArcFiRe is available at http://sparcfire.ics.uci.edu.

79 ASTRONOMY AND ASTROPHYSICS↗

Magnetic interactions in strongly correlated systems: Spin and orbital contributions

We present a technique to map an electronic model with local interactions (a generalized multi-orbital Hubbard model) onto an effective model of interacting classical spins, by requiring that the thermodynamic potentials associated to spin rotations in the two systems are equivalent up to second order in the rotation angles, when the electronic system is in a symmetry-broken phase. This allows to determine the parameters of relativistic and non-relativistic magnetic interactions in the effective spin model in terms of equilibrium Green’s functions of the electronic model. The Hamiltonian of the electronic system includes, in addition to the non-relativistic part, relativistic single-particle terms such as the Zeeman coupling to an external magnetic field, spin–orbit coupling, and arbitrary magnetic anisotropies; the orbital degrees of freedom of the electrons are explicitly taken into account. We determine the complete relativistic exchange tensors, accounting for anisotropic exchange, Dzyaloshinskii–Moriya interactions, as well as additional non-diagonal symmetric terms (which may include dipole–dipole interaction). The expressions of all these magnetic interactions are determined in a unified framework, including previously disregarded features such as the vertices of two-particle Green’s functions and non-local self-energies. We do not assume any smallness in spin–orbit coupling, so our treatment is in this sense exact. Finally, we show how to distinguish and address separately the spin, orbital and spin–orbital contributions to magnetism, providing expressions that can be computed within a tight-binding Dynamical Mean Field Theory.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Molecular dynamics simulations of the structure and single-particle dynamics of mixtures of divalent salts and ionic liquids

We report a molecular dynamics study of the structure and single-particle dynamics of mixtures of a protic (ethylammonium nitrate) and an aprotic (1-butyl-3-methylimidazolium hexaflurophosphate [BMIM][PF{sub 6}]) room-temperature ionic liquids doped with magnesium and calcium salts with a common anion at 298.15 K and 1 atm. The solvation of these divalent cations in dense ionic environments is analyzed by means of apparent molar volumes of the mixtures, radial distribution functions, and coordination numbers. For the protic mixtures, the effect of salt concentration on the network of hydrogen bonds is also considered. Moreover, single-particle dynamics of the salt cations is studied by means of their velocity autocorrelation functions and vibrational densities of states, explicitly analyzing the influence of salt concentration, and cation charge and mass on these magnitudes. The effect of the valency of the salt cation on these properties is considered comparing the results with those for the corresponding mixtures with lithium salts. We found that the main structural and dynamic features of the local solvation of divalent cations in ionic liquids are similar to those of monovalent salts, with cations being localized in the polar nanoregions of the bulk mixture coordinated in monodentate and bidentate coordination modes by the [NO{sub 3}]{sup −} and [PF{sub 6}]{sup −} anions. However, stronger electrostatic correlations of these polar nanoregions than in mixtures with salts with monovalent cations are found. The vibrational modes of the ionic liquid (IL) are seen to be scarcely affected by the addition of the salt, and the effect of mass and charge on the vibrational densities of states of the dissolved cations is reported. Cation mass is seen to exert a deeper influence than charge on the low-frequency vibrational spectra, giving a red shift of the vibrational modes and a virtual suppression of the higher energy vibrational modes for the heavier Ca{sup 2+} cations. No qualitative difference with monovalent cations was found in what solvation is concerned, which suggests that no enhanced reduction of the mobility of these cations and their complexes in ILs respective to those of monovalent cations is to be expected.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Non percolative nature of the metal-insulator transition and persistence of local Jahn-Teller distortions in the rhombohedral regime of La 1-x Ca x MnO 3

Evolution of the average and local crystal structure of Ca-doped LaMnO 3 has been studied across the metal to insulator (MI) and the orthorhombic to rhombohedral (OR) structural phase transitions over a broad temperature range for two Ca concentrations (x = 0.18,0.22). Combined Rietveld and high real space resolution atomic pair distribution function (PDF) analysis of neutron total scattering data was carried out with aims of exploring the possibility of nanoscale phase separation (PS) in relation to MI transition, and charting the evolution of local Jahn-Teller (JT) distortion of MnO 6 octahedra across the OR transition at T S ~720 K. The study utilized explicit two-phase PDF structural modeling, revealing that away from T MI there is no evidence for nanoscale phase coexistence. The local JT distortions disappear abruptly upon crossing into the metallic regime both with doping and temperature, with only a small temperature-independent signature of quenched disorder being observable at low temperature as compared to CaMnO 3 . The results hence do not support the percolative scenario for the MI transition in La 1–x Ca x MnO 3 based on PS, and question its ubiquity in the manganites. In contrast to LaMnO 3 that exhibits long-range orbital correlations and sizable octahedral distortions at low temperature, the doped samples with compositions straddling the MI boundary exhibit correlations (in the insulating regime) limited to only ~1 nm with observably smaller distortions. In the x = 0.22 sample local JT distortions are found to persist across the OR transition and deep into the R phase (up to ~1050 K), where they are crystallographically prohibited. As a result, their magnitude and subnanometer spatial extent remain unchanged.

36 MATERIALS SCIENCE↗

Explainable Machine Learning for Functional Data

Black-box machine learning models are recognized as useful tools for prediction applications, but the algorithmic complexity of some models causes interpretation challenges. Explainability methods have been proposed to provide insight into these models, but there is little research focused on supervised modeling with functional data inputs. We argue that, especially in applications of high consequence, it is important to explicitly model the functional dependence in a black-box analysis to not obscure or misrepresent patterns in explanations. As such, we propose the V ariable importance E xplainable E lastic S hape A nalysis (VEESA) pipeline for training supervised machine learning models with functional inputs. The pipeline is an analysis process that includes the data preprocessing, modeling, and post-hoc explanations. The preprocessing is done using elastic functional principal components analysis, which accounts for vertical and horizontal variability in functional data and, ultimately, allows for explanations in the original data space that identify the important functional variability without bias due to correlated variables. Here, we demonstrate the pipeline on two high-consequence applications: explosives classification for national security and inkjet printer identification in forensic science. The applications exhibit the VEESA pipeline’s ability to provide an understanding of the characteristics of the functional data useful for prediction. Code for implementing the pipeline is available in the veesa R package (and supplemental python code).

Elastic Shape Analysis↗