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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records

Measurements of differential cross sections of top quark pair production in association with jets in pp collisions at $\sqrt{s}=13 $ TeV using the ATLAS detector

Measurements of differential cross sections of top quark pair production in association with jets by the ATLAS experiment at the LHC are presented. The measurements are performed as functions of the top quark transverse momentum, the transverse momentum of the top quark-antitop quark system and the out-of-plane transverse momentum using data from pp collisions at s√=13 TeV collected by the ATLAS detector at the LHC in 2015 and corresponding to an integrated luminosity of 3.2 fb -1 . The top quark pair events are selected in the lepton (electron or muon) + jets channel. The measured cross sections, which are compared to several predictions, allow a detailed study of top quark production.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

FoxO1 inhibition promotes differentiation of human embryonic stem cells into insulin producing cells

Highlights: • The level of p-FoxO1 protein increases during differentiation of hESCs into IPCs. • FoxO1 knockdown promotes IPC differentiation of hESCs. • FoxO1 overexpression inhibits IPC differentiation of hESCs. • Inhibition of FoxO1 by AS promotes the differentiation of hESCs into IPCs. • AS may promote IPC maturation via modulating subcellular location of FoxO1 and Pdx1. Insulin-producing cells (IPCs) derived from human embryonic stem cells (hESCs) hold great potential for cell transplantation therapy in diabetes. Tremendous progress has been made in inducing differentiation of hESCs into IPCs in vitro, of which definitive endoderm (DE) protocol mimicking foetal pancreatic development has been widely used. However, immaturity of the obtained IPCs limits their further applications in treating diabetes. Forkhead box O1 (FoxO1) is involved in the differentiation and functional maintenance of murine pancreatic β cells, but its role in human β cell differentiation is under elucidation. Here, we showed that although FoxO1 expression level remained consistent, cytoplasmic phosphorylated FoxO1 protein level increased during IPC differentiation of hESCs induced by DE protocol. Lentiviral silencing of FoxO1 in pancreatic progenitors upregulated the levels of pancreatic islet differentiation-related genes and improved glucose-stimulated insulin secretion response in their progeny IPCs, whereas overexpression of FoxO1 showed the opposite effects. Notably, treatment with the FoxO1 inhibitor AS1842856 displayed similar effects with FoxO1 knockdown in pancreatic progenitors. These effects were closely associated with the mutually exclusive nucleocytoplasmic shuttling of FoxO1 and Pdx1 in the AS1842856-treated pancreatic progenitors. Our data demonstrated a promising effect of FoxO1 inhibition by the small molecule on gene expression profile during the differentiation, and in turn, on determining IPC maturation via modulating subcellular location of FoxO1 and Pdx1. Therefore, we identify a novel role of FoxO1 inhibition in promoting IPC differentiation of hESCs, which may provide clues for induction of mature β cells from hESCs and clinical applications in regenerative medicine.

60 APPLIED LIFE SCIENCES↗

Differential gene expression profiling of human adipose stem cells differentiating into smooth muscle-like cells by TGFβ1/BMP4

Regenerative repair of the vascular system is challenging from the perspectives of translational medicine and tissue engineering. There are fundamental hurdles in front of creating bioartificial arteries, which involve recaputilation of the three-layered structure under laboratory settings. Obtaining and maintaining smooth muscle characteristics is an important limitation, as the transdifferentiated cells fail to display mature phenotype. This study aims to shed light on the smooth muscle differentiation of human adipose stem cells (hASCs). To this end, we first acquired hASCs from lipoaspirate samples. Upon characterization, the cells were induced to differentiate into smooth muscle (SM)-like cells using a variety of inducer combinations. Among all, TGFβ1/BMP4 combination had the highest differentiation efficiency, based on immunohistochemical analyses. hSM-like cell samples were compared to hASCs and to the positive control, human coronary artery-smooth muscle cells (hCA-SMCs) through gene transcription profiling. Microarray findings revealed the activation of gene groups that function in smooth muscle differentiation, signaling pathways, extracellular modeling and cell proliferation. Our results underline the effectiveness of the growth factors and suggest some potential variables for detecting the SM-like cell characteristics. Evidence in transcriptome level was used to evaluate the TGFβ1/BMP4 combination as a previously unexplored effector for the smooth muscle differentiation of adipose stem cells. - Highlights: • Human adipose stem cells (hASCs) were isolated, characterized and cultured. • Growth factor combinations were evaluated for their effectiveness in differentiation using IHC. • hASCs were differentiated into smooth muscle (SM)-like cells using TGF-β1 and BMP4 combination. • Microarray analysis was performed for hASCs, SM-like cells and coronary artery-SMCs. • Microarray data was used to perform hierarchical clustering and interpretation of activated pathways.

60 APPLIED LIFE SCIENCES↗

XYLEM NAC DOMAIN1, an angiosperm NAC transcription factor, inhibits xylem differentiation through conserved motifs that interact with RETINOBLASTOMA‐RELATED

Summary The Arabidopsis thaliana gene XYLEM NAC DOMAIN1 ( XND1 ) is upregulated in xylem tracheary elements. Yet overexpression of XND1 blocks differentiation of tracheary elements. The molecular mechanism of XND1 action was investigated. Phylogenetic and motif analyses indicated that XND1 and its homologs are present only in angiosperms and possess a highly conserved C‐terminal region containing linear motifs (CKII‐acidic, LXCXE, E2F TD ‐like and LXCXE‐mimic) predicted to interact with the cell cycle and differentiation regulator RETINOBLASTOMA‐RELATED (RBR). Protein–protein interaction and functional analyses of XND1 deletion mutants were used to test the importance of RBR‐interaction motifs. Deletion of either the LXCXE or the LXCXE‐mimic motif reduced both the XND1–RBR interaction and XND1 efficacy as a repressor of differentiation, with loss of the LXCXE motif having the strongest negative impacts. The function of the XND1 C‐terminal domain could be partially replaced by RBR fused to the N‐terminal domain of XND1. XND1 also transactivated gene expression in yeast and plants. The properties of XND1, a transactivator that depends on multiple linear RBR‐interaction motifs to inhibit differentiation, have not previously been described for a plant protein. XND1 harbors an apparently angiosperm‐specific combination of interaction motifs potentially linking the general differentiation regulator RBR with a xylem‐specific pathway for inhibition of differentiation.

Zhao, Chengsong↗

Linear fractional differential equations and eigenfunctions of fractional differential operators

Eigenfunctions associated with Riemann–Liouville and Caputo fractional differential operators are obtained by imposing a restriction on the fractional derivative parameter. Those eigenfunctions can be used to express the analytical solution of some linear sequential fractional differential equations. As a first application, we discuss analytical solutions for the so-called fractional Helmholtz equation with one variable, obtained from the standard equation in one dimension by replacing the integer order derivative by the Riemann–Liouville fractional derivative. A second application consists of an initial value problem for a fractional wave equation in two dimensions in which the integer order partial derivative with respect to the time variable is replaced by the Caputo fractional derivative. The classical Mittag-Leffler functions are important in the theory of fractional calculus because they emerge as solutions of fractional differential equations. Starting with the solution of a specific fractional differential equation in terms of these functions, we find a way to express the exponential function in terms of classical Mittag-Leffler functions. A remarkable characteristic of this relation is that it is true for any value of the parameter n appearing in the definition of the functions, i.e., we have an infinite family of different expressions for e{sup x} in terms of classical Mittag-Leffler functions.

97 MATHEMATICS AND COMPUTING↗

Measurement of differential cross sections and W+/W- cross-section ratios for W boson production in association with jets at $$ \sqrt{s}=8 $$ TeV with the ATLAS detector

This paper presents a measurement of the W boson production cross section and the W + /W - cross-section ratio, both in association with jets, in proton-proton collisions at $\sqrt{s}$ = 8 with the ATLAS experiment at the Large Hadron Collider. The measurement is performed in final states containing one electron and missing transverse momentum using data corresponding to an integrated luminosity of 20.2 fb -1 . Differential cross sections for events with at least one or two jets are presented for a range of observables, including jet transverse momenta and rapidities, the scalar sum of transverse momenta of the visible particles and the missing transverse momentum in the event, and the transverse momentum of the W boson. For a subset of the observables, the differential cross sections of positively and negatively charged W bosons are measured separately. In the cross-section ratio of W + /W - the dominant systematic uncertainties cancel out, improving the measurement precision by up to a factor of nine. The observables and ratios selected for this paper provide valuable input for the up quark, down quark, and gluon parton distribution functions of the proton.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Differential cross section measurements for γ n → π - p above the first nucleon resonance region

The quasifree gamma d -> pi(-)p(p) differential cross section has been measured with CLAS at photon beam energies E-gamma from 0.445 to 2.510 GeV (corresponding to W from 1.311 to 2.366 GeV) for pion center-of-mass angles cos theta(c.m.)(pi) from -0.72 to 0.92. A correction for final state interactions has been applied to these data to extract the gamma n -> pi(-)p differential cross sections. These cross sections are quoted in 8428 (E-gamma, cos theta(c.m)(pi)) bins, a factor of nearly 3 increase in the world statistics for this channel in this kinematic range. These new data help to constrain coupled-channel analysis fits used to disentangle the spectrum of N* resonances and extract their properties. Selected photon decay amplitudes N* -> gamma n at the resonance poles are determined for the first time and are reported here.

CLAS Collaboration↗

CHIQUITA1 maintains the temporal transition between proliferation and differentiation in Arabidopsis thaliana

ABSTRACT Body size varies widely among species, populations and individuals, depending on the environment. Transitioning between proliferation and differentiation is a crucial determinant of final organ size, but how the timing of this transition is established and maintained remains unknown. Using cell proliferation markers and genetic analysis, we show that CHIQUITA1 (CHIQ1) is required to maintain the timing of the transition from proliferation to differentiation in Arabidopsis thaliana. Combining kinematic and cell lineage-tracking studies, we found that the number of actively dividing cells in chiquita1-1 plants decreases prematurely compared with wild-type plants, suggesting CHIQ1 maintains the proliferative capacity in dividing cells and ensures that cells divide a specific number of times. CHIQ1 belongs to a plant-specific gene family of unknown molecular function and genetically interacts with three close members of its family to control the timing of proliferation exit. Our work reveals the interdependency between cellular and organ-level processes underlying final organ size determination.

59 BASIC BIOLOGICAL SCIENCES↗

Implementing Ordinary Differential Equation Solvers in Rust Programming Language for Modeling Vehicle Powertrain Systems: Preprint

Efficient and accurate ordinary differential equation (ODE) solvers are necessary for powertrain and vehicle dynamics modeling. However, current commercial ODE solvers can be financially prohibitive, leading to a need for accessible, effective, open-source ODE solvers designed for powertrain modeling. Rust is a compiled programming language that has the potential to be used for fast and easy-to-use powertrain models, given its exceptional computational performance, robust package ecosystem, and short time required for modelers to become proficient. However, of the three commonly used (>3,000 downloads) packages in Rust with ODE solver capabilities, only one has more than four numerical methods implemented, and none are designed specifically for modeling physical systems. Therefore, the goal of the Differential Equation System Solver (DESS) was to implement accurate ODE solvers in Rust designed for the component-based problems often seen in powertrain modeling. DESS is a text-based software package that provides a flexible framework for building and solving systems of ODEs. This allows DESS to be included as a dependency for automotive powertrain models that require a variety of solvers and solver configurations. Seven explicit ODE solver methods have been implemented in DESS: Euler’s, Heun’s, midpoint, Ralston’s, classic Runge-Kutta, Bogacki-Shampine, and Cash-Karp. These represent five fixed-step methods and two adaptive-step methods. This paper shows that the solver implementations increase accuracy and computational efficiency compared to Euler's method when modeling a system of three thermal masses in Rust. DESS also includes features designed for modeling component-based physical systems. Users can define relationships between nodes in their system, which the package then translates into a system of equations, leading to simpler and more intuitive code. In the case of a three-thermal-mass system, the user can specify node thermal properties (e.g., thermal capacitance), how nodes are interconnected, and thermal conductance between nodes rather than providing a system of equations. The core contribution from this work is an open-source, text-based Rust package with ODE solvers for automotive powertrain modeling to support cost-free, fast, and accurate simulation.

ADVANCED PROPULSION SYSTEMS↗

Runge–Kutta method for solving fuzzy differential equations under generalized differentiability

In this paper, we interpret a fuzzy differential equation by using the strongly generalized differentiability concept. Utilizing the Generalized Characterization Theorem, we investigate the problem of finding a numerical approximation of solutions. The Runge–Kutta approximation method is implemented and its error analysis, which guarantees pointwise convergence, is given. The method applicability is illustrated by solving a linear first-order fuzzy differential equation.

97 MATHEMATICS AND COMPUTING↗

Fourier Neural Networks as Function Approximators and Differential Equation Solvers

We present a Fourier neural network (FNN) that can be mapped directly to the Fourier decomposition. The choice of activation and loss function yields results that replicate a Fourier series expansion closely while preserving a straightforward architecture with a single hidden layer. The simplicity of this network architecture facilitates the integration with any other higher-complexity networks, at a data pre- or postprocessing stage. We validate this FNN on naturally periodic smooth functions and on piecewise continuous periodic functions. We showcase the use of this FNN for modeling or solving partial differential equations with periodic boundary conditions. The main advantages of the current approach are the validity of the solution outside the training region, interpretability of the trained model, and simplicity of use.

Fourier decomposition↗

On random fuzzy fractional partial integro-differential equations under Caputo generalized Hukuhara differentiability

This paper is devoted to the study of the solvability of random fuzzy fractional partial integro-differential equations under Caputo generalized Hukuhara differentiability. The notions of random fuzzy variables and fuzzy stochastic processes are developed for multivariable functions. The existence and uniqueness of two types of integral solutions generated from Darboux problem for nonlinear wave equations are proved using the successive approximations method and Gronwall’s inequality for stochastic processes. The continuous dependence on the data, the boundedness, and the stability with probability one of integral solutions are established to confirm the well posedness of our model. Some computational examples are presented to illustrate the theoretical results.

97 MATHEMATICS AND COMPUTING↗

Publishing unbinned differential cross section results

Machine learning tools have empowered a qualitatively new way to perform differential cross section measurements whereby the data are unbinned, possibly in many dimensions. Unbinned measurements can enable, improve, or at least simplify comparisons between experiments and with theoretical predictions. Furthermore, many-dimensional measurements can be used to define observables after the measurement instead of before. There is currently no community standard for publishing unbinned data. While there are also essentially no measurements of this type public, unbinned measurements are expected in the near future given recent methodological advances. The purpose of this paper is to propose a scheme for presenting and using unbinned results, which can hopefully form the basis for a community standard to allow for integration into analysis workflows. This is foreseen to be the start of an evolving community dialogue, in order to accommodate future developments in this field that is rapidly evolving.

47 OTHER INSTRUMENTATION↗

Distributed Delay Differential Equation Representations of Cyclic Differential Equations

Compartmental ordinary differential equation (ODE) models are used extensively in mathematical biology. When transit between compartments occurs at a constant rate, the well-known linear chain trick can be used to show that the ODE model is equivalent to an Erlang distributed delay differential equation (DDE). Here, we demonstrate that compartmental models with nonlinear transit rates and possibly delayed arguments are also equivalent to a scalar distributed DDE. To illustrate the utility of these equivalences, we calculate the equilibria of the scalar DDE, and compute the characteristic function---without calculating a determinant. Further, we derive the equivalent scalar DDE for two examples of models in mathematical biology and use the DDE formulation to identify physiological processes that were otherwise hidden by the compartmental structure of the ODE model.

97 MATHEMATICS AND COMPUTING↗

Subsurface Grain Morphology Reconstruction by Differential Aperture X-ray Microscopy

A multistep, non-destructive grain morphology reconstruction methodology that is applicable to near-surface volumes is developed and tested on synthetic grain structures. This approach probes the subsurface crystal orientation using differential aperture x-ray microscopy on a sparse grid across the microstructure volume of interest. Resulting orientation data are clustered according to proximity in physical and orientation space and used as seed points for an initial Voronoi tessellation to (crudely) approximate the grain morphology. Curvature-driven grain boundary relaxation, simulated by means of the Voronoi implicit interface method, progressively improves the reconstruction accuracy. The similarity between bulk and readily accessible surface reconstruction error provides an objective termination criterion for boundary relaxation.

36 MATERIALS SCIENCE↗

Basis adaptation and domain decomposition for steady-state partial differential equations with random coefficients

We present a novel approach for solving steady-state stochastic partial differential equations in high-dimensional random parameter space. The proposed approach combines spatial domain decomposition with basis adaptation for each subdomain. The basis adaptation is used to address the curse of dimensionality by constructing an accurate low-dimensional representation of the stochastic PDE solution (probability density function and/or its leading statistical moments) in each subdomain. Restricting the basis adaptation to a specific subdomain affords finding a locally accurate solution. Then, the solutions from all of the subdomains are stitched together to provide a global solution. We support our construction with numerical experiments for a steady-state diffusion equation with a random spatially dependent coefficient. Our results show that accurate global solutions can be obtained with significantly reduced computational costs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗