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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

CNOT-based quantum swapping of polarization and modal encoded qubits in photonic Ti:LiNbO{sub 3} channel waveguides

A photonic circuit aimed at implementing a CNOT-based quantum swapping of the modal and polarization qubits, is designed and simulated, using Ti:LiNbO{sub 3} indiffused channel waveguides. A few on-chip optical elements such as the polarization-sensitive odd-mode analyzers and combiners, along with the electrically controllable directional couplers and polarization converters, are incorporated within the circuit and together serve to realize the operation of a deterministic single-photon quantum swap gate. Entanglement generation is realized on-chip by means of two concurrent spontaneous parametric down-conversion processes in the twice periodically poled Ti:LiNbO{sub 3} waveguide, placed at the input section of the circuit. The constituent elements of the circuit are characterized separately using numerical beam propagation method in RSoft program package. Two poling periods of Λ{sub 1}=11.762 μm and Λ{sub 2}=23.667 μm are calculated for the dual periodically perturbed structure in the circuit. The directional couplers operate at V{sub DC}=31.6 V. Maximum polarization conversion efficiency is achieved by applying a constant switching voltage of V{sub EO}=4.52 V.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Sertad1 encodes a novel transcriptional co-activator of SMAD1 in mouse embryonic hearts

Highlights: •SERTAD1 interacts with SMAD1. •Sertad1 is expressed in mouse embryonic hearts. •SERTAD1 is localized in both cytoplasm and nucleus of cardiomyocytes. •SERTAD1 enhances expression of BMP target cardiogenic genes as a SMAD1 co-activator. -- Abstract: Despite considerable advances in surgical repairing procedures, congenital heart diseases (CHDs) remain the leading noninfectious cause of infant morbidity and mortality. Understanding the molecular/genetic mechanisms underlying normal cardiogenesis will provide essential information for the development of novel diagnostic and therapeutic strategies against CHDs. BMP signaling plays complex roles in multiple cardiogenic processes in mammals. SMAD1 is a canonical nuclear mediator of BMP signaling, the activity of which is critically regulated through its interaction partners. We screened a mouse embryonic heart yeast two-hybrid library using Smad1 as bait and identified SERTAD1 as a novel interaction partner of SMAD1. SERTAD1 contains multiple potential functional domains, including two partially overlapping transactivation domains at the C terminus. The SERTAD1-SMAD1 interaction in vitro and in mammalian cells was further confirmed through biochemical assays. The expression of Sertad1 in developing hearts was demonstrated using RT-PCR, western blotting and in situ hybridization analyses. We also showed that SERTAD1 was localized in both the cytoplasm and nucleus of immortalized cardiomyocytes and primary embryonic cardiomyocyte cultures. The overexpression of SERTAD1 in cardiomyocytes not only enhanced the activity of two BMP reporters in a dose-dependent manner but also increased the expression of several known BMP/SMAD regulatory targets. Therefore, these data suggest that SERTAD1 acts as a SMAD1 transcriptional co-activator to promote the expression of BMP target genes during mouse cardiogenesis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

EBV-encoded EBNA1 regulates cell viability by modulating miR34a-NOX2-ROS signaling in gastric cancer cells

Highlights: • ROS content and NOX2 expression are higher in EBV-positive gastric cancer cells relative to EBV-negative gastric cancer cells. • Upregulation of NOX2 expression by EBNA1 plays an important role in the cell viability of gastric cancer cells. • Modulation of NOX2 expression by EBNA1 is regulated at the transcriptional level via miR34a. • Reactivation of miR34a could be a potential anti-cancer strategy in EBV-infected gastric cancer. Epstein-Barr virus (EBV) nuclear antigen 1 (EBNA1) is a viral protein expressed in all EBV-infected cells that induces malignant transformation. EBNA1 is reported to contribute to tumor progression through an increase in reactive oxygen species via nicotinamide adenine dinucleotide phosphate oxidase. However, the underlying molecular mechanism of EBNA1-induced ROS accumulation in gastric cancer is poorly understood. Here, we demonstrated that miR34a regulation by EBNA1 determined cell fate in EBV-infected gastric cancer cells. ROS content and NOX2 expression were higher in EBNA1-expressing SNU719 cells than in EBNA1-nonexpressing SNU638 cells. Downregulation of NOX2 using siRNA technology in SNU719 cells decreased cell viability and ROS content. Regulation of EBNA1 expression in EBV-associated gastric cancers modulated NOX2 expression, ROS content and cell viability. We also showed that upregulation of NOX2 by EBNA1 was mediated by downregulating miRNA34a. Finally, overexpression of miR34a in EBNA1-expressing SNU719 cells induced typical apoptosis, suggesting that reactivation of miR34a in EBNA1-expressing gastric cancer cells could be a strategy for treatment of EBV-infected gastric cancer cells.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Combinatorial transcription factor binding encodes cis -regulatory wiring of mouse forebrain GABAergic neurogenesis

Transcription factors (TFs) bind combinatorially to cis-regulatory elements, orchestrating transcriptional programs. Although studies of chromatin state and chromosomal interactions have demonstrated dynamic neurodevelopmental cis-regulatory landscapes, parallel understanding of TF interactions lags. To elucidate combinatorial TF binding driving mouse basal ganglia development, we integrated chromatin immunoprecipitation sequencing (ChIP-seq) for twelve TFs, H3K4me3-associated enhancer-promoter interactions, chromatin and gene expression data, and functional enhancer assays. We identified sets of putative regulatory elements with shared TF binding (TF-pRE modules) that orchestrate distinct processes of GABAergic neurogenesis and suppress other cell fates. The majority of pREs were bound by one or two TFs; however, a small proportion were extensively bound. These sequences had exceptional evolutionary conservation and motif density, complex chromosomal interactions, and activity as in vivo enhancers. Our results provide insights into the combinatorial TF-pRE interactions that activate and repress expression programs during telencephalon neurogenesis and demonstrate the value of TF binding toward modeling developmental transcriptional wiring.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

A one-time truncate and encode multiresolution stochastic framework

In this work a novel adaptive strategy for stochastic problems, inspired from the classical Harten's framework, is presented. The proposed algorithm allows building, in a very general manner, stochastic numerical schemes starting from a whatever type of deterministic schemes and handling a large class of problems, from unsteady to discontinuous solutions. Its formulations permits to recover the same results concerning the interpolation theory of the classical multiresolution approach, but with an extension to uncertainty quantification problems. The present strategy permits to build numerical scheme with a higher accuracy with respect to other classical uncertainty quantification techniques, but with a strong reduction of the numerical cost and memory requirements. Moreover, the flexibility of the proposed approach allows to employ any kind of probability density function, even discontinuous and time varying, without introducing further complications in the algorithm. The advantages of the present strategy are demonstrated by performing several numerical problems where different forms of uncertainty distributions are taken into account, such as discontinuous and unsteady custom-defined probability density functions. In addition to algebraic and ordinary differential equations, numerical results for the challenging 1D Kraichnan–Orszag are reported in terms of accuracy and convergence. Finally, a two degree-of-freedom aeroelastic model for a subsonic case is presented. Though quite simple, the model allows recovering some physical key aspect, on the fluid/structure interaction, thanks to the quasi-steady aerodynamic approximation employed. The injection of an uncertainty is chosen in order to obtain a complete parameterization of the mass matrix. All the numerical results are compared with respect to classical Monte Carlo solution and with a non-intrusive Polynomial Chaos method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Encoding nonlinear and unsteady aerodynamics of limit cycle oscillations using nonlinear sparse Bayesian learning

This article investigates the applicability of a recently proposed, nonlinear sparse Bayesian learning (NSBL) algorithm to identify and estimate the complex aerodynamics of limit cycle oscillations. NSBL provides a semi-analytical framework for determining the data-optimal sparse model nested within a (potentially) over-parameterized model. This is particularly relevant to nonlinear dynamical systems where modelling approaches involve the use of physics-based and data-driven components. In such cases, the data-driven components, where analytical descriptions of the physical processes are not readily available, are often prone to overfitting, meaning that the empirical aspects of these models will often involve the calibration of an unnecessarily large number of parameters. While an overparameterized model may fit the observed data well, such models may be inadequate for making predictions in regimes that are different from those wherein the data were recorded. In view of this, it is desirable to not only calibrate the model parameters, but also identify the optimal compromise between data fit and model complexity. In this article, we exhibit the optimal model discovery for an aeroelastic system wherein the structural dynamics are well-known and described by a differential equation model, coupled with a semi-empirical aerodynamic model for laminar separation flutter, resulting in low-amplitude limit cycle oscillations (LCO). To illustrate the performance of the algorithm, in this article, we use synthetic data and demonstrate the ability of the algorithm to correctly rediscover the optimal model and model parameters, given a known data-generating model. The synthetic data are generated from a forward simulation of a known differential equation model with parameters selected so as to mimic the dynamics observed in wind-tunnel experiments. Subsequently, we demonstrate the performance of the algorithm for model selection using noisy LCO data from wind tunnel experiments. As there is no ground truth available for the experimental data case, we provide a comparison between NSBL and Bayesian model selection to validate the results, and demonstrate the use of NSBL as an efficient alternative to traditional methods.

97 MATHEMATICS AND COMPUTING↗