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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 325 records · Page 18

Regulator of G protein signaling 4 is a novel target of GATA-6 transcription factor

GATA transcription factors regulate an array of genes important in cell proliferation and differentiation. Here we report the identification of regulator of G protein signaling 4 (RGS4) as a novel target for GATA-6 transcription factor. Although three sites (a, b, c) within the proximal region of rabbit RGS4 promoter for GATA transcription factors were predicted by bioinformatics analysis, only GATA-a site (16 bp from the core TATA box) is essential for RGS4 transcriptional regulation. RT-PCR analysis demonstrated that only GATA-6 was highly expressed in rabbit colonic smooth muscle cells but GATA-4/6 were expressed in cardiac myocytes and GATA-1/2/3 expressed in blood cells. Adenovirus-mediated expression of GATA-6 but not GATA-1 significantly increased the constitutive and IL-1β-induced mRNA expression of the endogenous RGS4 in colonic smooth muscle cells. IL-1β stimulation induced GATA-6 nuclear translocation and increased GATA-6 binding to RGS4 promoter. These data suggest that GATA factor could affect G protein signaling through regulating RGS4 expression, and GATA signaling may develop as a future therapeutic target for RGS4-related diseases. - Highlights: • GATA-6 is highly expressed in colonic smooth muscle cells. • RGS4 is a novel target for GATA-6 transcription factor. • GATA-a response element is essential to regulate the core promoter of RGS4. • GATA-6 regulates IL-1β-induced RGS4 upregulation.

60 APPLIED LIFE SCIENCES↗

Th17 cell-mediated immune responses promote mast cell proliferation by triggering stem cell factor in keratinocytes

Although mast cells are traditionally thought to function as effector cells in allergic responses, they have increasingly been recognized as important regulators of various immune responses. Mast cells mature locally; thus, tissue-specific influences are important for promoting mast cell accumulation and survival in the skin and the gastrointestinal tract. In this study, we determined the effects of keratinocytes on mast cell accumulation during Th17-mediated skin inflammation. We observed increases in dermal mast cells in imiquimod-induced psoriatic dermatitis in mice accompanied by the expression of epidermal stem cell factor (SCF), a critical mast cell growth factor. Similar to mouse epidermal keratinocytes, SCF was highly expressed in the human HaCaT keratinocyte cell line following stimulation with IL−17. Further, keratinocytes promoted mast cell proliferation following stimulation with IL−17 in vitro. However, the effects of keratinocytes on mast cells were significantly diminished in the presence of anti−CD117 (stem cell factor receptor) blocking antibodies. Taken together, our results revealed that the Th17-mediated inflammatory environment promotes mast cell accumulation through keratinocyte-derived SCF. - Highlights: • Psoriasis-like skin inflammation increase dermal mast cells. • Keratinocyte produce stem cell factor in psoriasis-like skin inflammation. • Keratinocyte promote mast cell proliferation by stem cell factor dependent manner.

60 APPLIED LIFE SCIENCES↗

Assessing the predictive impact of factor fixing with an adaptive uncertainty-based approach .

Despite widespread use of factor fixing in environmental modeling, its effect on model predictions has received little attention and is instead commonly presumed to be negligible. We propose a proof-of-concept adaptive method for systematically investigating the impact of factor fixing. The method uses Global Sensitivity Analysis methods to identify groups of sensitive parameters, then quantifies which groups can be safely fixed at nominal values without exceeding a maximum acceptable error, demonstrated using the 21-dimensional Sobol’ G-function. Furthermore, three error measures are considered for quantities of interest, namely Relative Mean Absolute Error, Pearson Product-Moment Correlation and Relative Variance. Results demonstrate that factor fixing may cause large errors in the model results unexpectedly, when preliminary analysis suggests otherwise, and that the default value selected affects the number of factors to fix. To improve the applicability and methodological development of factor fixing, a new research agenda encompassing five opportunities is discussed for further attention.

54 ENVIRONMENTAL SCIENCES↗

Individual low-carbon behaviors and influencing factors: Insights from a behavior survey study in China

Climate change is a major global concern. Greenhouse gas emissions that cause global climate change are directly or indirectly affected by human activities. Individual low-carbon behaviors are crucial in reducing CO 2 emissions and improving environmental and ecological health. To effectively promote individual low-carbon behavior, this study designed a questionnaire on the factors influencing individual low-carbon intentions and behavior based on theoretical models of environmental behavior. A total of 2430 valid questionnaires were collected in China. This study focuses on analyzing the impact of demographic characteristics, internal and external factors on individual low-carbon behaviors and their interrelationships. The research shows correlations between internal and external factors in determining low-carbon intention or behaviors. Internal factors-related low-carbon behavior is not closely linked with demographic variables, whereas the external factors-related low-carbon behavior vary significantly by age, residence, education, marital status, occupation, and income. The findings have important implications for designing effective policies to promote low-carbon behaviors, such as creating a more favorable external environment and increasing the use of policy tools for reducing CO 2 emission.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A semiparametric latent factor model for large scale temporal data with heteroscedasticity

Large scale temporal data have flourished in a vast array of applications, and their sophisticated structures, especially the heteroscedasticity among subjects with inter- and intra-temporal dependence, have fueled a great demand for new statistical models. In this paper, with covariate information, we consider a flexible model for large scale temporal data with subject-specific heteroscedasticity. Formally, the model employs latent semiparametric factors to simultaneously account for the subject-specific heteroscedasticity and the contemporaneous and/or serial correlations. The subject-specific heteroscedasticity is modeled as the product of the unobserved factor process and subject’s covariate effect, which is further characterized via additive models. For estimation, we propose a two-step procedure. First, the latent factor process and nonparametric loading are recovered through projection-based methods, and following, we estimate the regression components by approaches motivated from the generalized least squares. By scrupulously examining the non-asymptotic rates for recovering the factor process and its loading, we show the consistency and efficiency of estimated regression coefficients in the absence of prior knowledge of latent factor process and subject’s covariate effect. Here, the statistical guarantees remain valid even for finite time points that makes our method particularly appealing when the subjects significantly outnumber the observation time points. Using comprehensive simulations, we demonstrate the finite sample performance of our method, which corroborates the theoretical findings. Finally, we apply our method to a data set of air quality and energy consumption collected at 129 monitoring sites in the United States in 2015.

97 MATHEMATICS AND COMPUTING↗

Effective g factor of low-density two-dimensional holes in a Ge quantum well

Here we report the measurements of the effective g factor of low-density two-dimensional holes in a Ge quantum well. Using the temperature dependence of the Shubnikov-de Haas oscillations, we extract the effective g factor in a magnetic field perpendicular to the sample surface. Very large values of the effective g factor, ranging from ~13 to ~28, are observed in the density range of 1.4×10 10 cm -2 – 1.4×10 11 cm -2 . When the magnetic field is oriented parallel to the sample surface, the effective g factor is obtained from a protrusion in the magneto-resistance data that signify full spin polarization. In the latter orientation, a small effective g factor, ~1.3-1.4, is measured in the density range of 1.5×10 10 cm -2 –2×10 10 cm -2 . Finally, this very strong anisotropy is consistent with theoretical predictions and previous measurements in other 2D hole systems, such as InGaAs and GaSb.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Flavor dependence of the pion and kaon form factors and parton distribution functions

The separate quark flavor contributions to the pion and kaon valence quark distribution functions are studied, along with the corresponding electromagnetic form factors in the space-like region. The calculations are made using the solution of the Bethe-Salpeter equation for the model of Nambu and Jona-Lasinio with proper-time regularization. Both the pion and kaon form factors and the valence quark distribution functions reproduce many features of the available empirical data. The larger mass of the strange quark naturally explains the empirical fact that the ratio u(K) + (x)/u(pi) + (x) drops below unity at large x, with a value of approximately M$2\atop{u}$/Ms$2\atop{s}$ as x → 1. With regard to the elastic form factors we report a large flavor dependence, with the u-quark contribution to the kaon form factor being an order of magnitude smaller than that of the s-quark at large Q 2 , which may be a sensitive measure of confinement effects in QCD. Surprisingly though, the total K + and π + form factors differ by only 10%. Lastly, in general we find that flavor breaking effects are typically around 20%.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Pion gravitational form factors in the QCD instanton vacuum. I

The pion form factors of the QCD energy-momentum tensor (EMT) are studied in the instanton liquid model (ILM) of the QCD vacuum. In this approach, the breaking of conformal symmetry is encoded in the form of stronger-than-Poisson fluctuations in the number of instantons. For the trace of the EMT, it is shown that the gluonic trace anomaly term contributes half the pion mass, with the other half coming from the quark-mass-dependent σ term. The Q 2 dependence of the form factors is governed by glueball and scalar meson exchanges. For the EMT, the spin-0 (trace) and spin-2 (traceless rank-2 tensor) form factors are computed at next-to-leading order in the instanton density using effective quark operators. Relations between the gluon and quark contributions to the EMT form factors are derived. The form factors are also expressed in terms of the pion light-front wave functions in the ILM. The results at the low resolution scale of the inverse instanton size are evolved to higher scales using the renormalization group equation. The ILM results compare well with those of recent lattice QCD calculations. Published by the American Physical Society 2024

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Axial-vector form factors of the nucleon from lattice QCD

In this paper, we present results for the form factors of the isovector axial vector current in the nucleon state using large scale simulations of lattice QCD. The calculations were done using eight ensembles of gauge configurations generated by the MILC collaboration using the HISQ action with 2 + 1 + 1 dynamical flavors. These ensembles span three lattice spacings a ≈ 0.06 , 0.09, and 0.12 fm and light-quark masses corresponding to the pion masses M π ≈ 135, 225, and 310 MeV. High-statistics estimates allow us to quantify systematic uncertainties in the extraction of G A (Q 2 ) and the induced pseudoscalar form factor G P (Q 2 ) . We perform a simultaneous extrapolation in the lattice spacing, lattice volume and light-quark masses of the axial charge radius r A data to obtain physical estimates. Using the dipole ansatz to fit the Q 2 behavior we obtain r A | dipole = 0.49(3) fm , which corresponds to M A = 1.39(9) GeV , and is consistent with M A = 1.35(17) GeV obtained by the miniBooNE collaboration. The estimate obtained using the z -expansion is r A | z - expansion = 0.46(6) fm, and the combined result is r A | combined = 0.48(4) fm. Analysis of the induced pseudoscalar form factor G P (Q 2 ) yields low estimates for g* P and g π NN compared to their phenomenological values. To understand these, we analyze the partially conserved axial current (PCAC) relation by also calculating the pseudoscalar form factor. Lastly, we find that these low values are due to large deviations in the PCAC relation between the three form factors, and in the pion-pole dominance hypothesis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Nucleon axial form factor from elementary target data

Precise neutrino-nucleon amplitudes are essential ingredients for predicting neutrino event rates in current and upcoming long-baseline neutrino oscillation experiments. A common neutrino interaction with a low reaction threshold and with most of the energy carried by two final state particles is quasielastic scattering, for which the nucleon axial form factor, 𝐹 𝐴⁡ (𝑄 2 ), is a dominant source of uncertainty. Improvements to the nucleon axial form factor rely on neutrino scattering data with elementary targets to reduce or eliminate the need for nuclear modeling systematics. This work examines constraints on the nucleon axial form factor that can be achieved from datasets of neutrino scattering on deuterium targets, Lattice QCD predictions, and from the recent hydrogen target data from the MINERvA Collaboration. Significant tension is found between hydrogen and deuterium target data, suggesting that extractions from deuterium underestimate both the central value and uncertainty of the form factor. Parametrizations for and uncertainties of the nucleon axial form factor using the 𝑧 expansion are provided.

FOS: Physical sciences↗

DeepGRN: prediction of transcription factor binding site across cell-types using attention-based deep neural networks

Abstract Background Due to the complexity of the biological systems, the prediction of the potential DNA binding sites for transcription factors remains a difficult problem in computational biology. Genomic DNA sequences and experimental results from parallel sequencing provide available information about the affinity and accessibility of genome and are commonly used features in binding sites prediction. The attention mechanism in deep learning has shown its capability to learn long-range dependencies from sequential data, such as sentences and voices. Until now, no study has applied this approach in binding site inference from massively parallel sequencing data. The successful applications of attention mechanism in similar input contexts motivate us to build and test new methods that can accurately determine the binding sites of transcription factors. Results In this study, we propose a novel tool (named DeepGRN) for transcription factors binding site prediction based on the combination of two components: single attention module and pairwise attention module. The performance of our methods is evaluated on the ENCODE-DREAM in vivo Transcription Factor Binding Site Prediction Challenge datasets. The results show that DeepGRN achieves higher unified scores in 6 of 13 targets than any of the top four methods in the DREAM challenge. We also demonstrate that the attention weights learned by the model are correlated with potential informative inputs, such as DNase-Seq coverage and motifs, which provide possible explanations for the predictive improvements in DeepGRN. Conclusions DeepGRN can automatically and effectively predict transcription factor binding sites from DNA sequences and DNase-Seq coverage. Furthermore, the visualization techniques we developed for the attention modules help to interpret how critical patterns from different types of input features are recognized by our model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Systems Biology Model of Interactions between Tissue Growth Factors and DNA Damage Pathways: Low Dose Response and Cross-Talk in TGFβ and ATM Signaling

The etiology of radiation carcinogenesis has been described in terms of aberrant changes that span several levels of biological organization. Growth factors regulate many important cellular and tissue functions including apoptosis, differentiation and proliferation. A variety of genetic and epigenetic changes of growth factors have been shown to contribute to cancer initiation and progression. It is known that cellular and tissue damage to ionizing radiation is in part initiated by the production of reactive oxygen species, which can activate cytokine signaling, and the DNA damage response pathways, most notably the ATM signaling pathway. Recently, the transforming growth factor β (TGFβ) pathway has been shown to regulate or directly interact with the ATM pathway in the response to radiation. The relevance of this interaction with the ATM pathway is not known although p53 becomes phosphorylated and DNA damage responses are involved. However, growth factor interactions with DNA damage responses have not been elucidated particularly at low doses, and further characterization of their relationship to cancer processes is warranted. Our goal will be to use a systems biology approach to mathematically and experimentally describe the low-dose responses and cross-talk between the ATM and TGFβ pathways initiated by low- and high-LET radiation. We will characterize ATM and TGFβ signaling in epithelial and fibroblast cells using 2D models and ultimately extending to 3D organotypic cell culture models to begin to elucidate possible differences that may occur for different cell types and/or inter-cellular communication. We will investigate the roles of the Smad and Activating transcription factor 2 (ATF2) proteins as the potential major contributors to crosstalk between the TGFβ and ATM pathways, and links to cell cycle control and/or the DNA damage response, and potential differences in their responses at low and high doses. We have developed various experimental approaches to apply to these problems using confocal microscopy and flow cytometry to detail changes at low dose/dose-rate in order to understand individual cell responses, and will establish our mathematical models based on the experimental findings resulting from changes in DNA repair, apoptosis and proliferation.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

A User-Centered Design Exploration of Factors That Influence the Rideshare Experience

The rise of real-time information communication through smartphones and wireless networks enabled the growth of ridesharing services. While personal rideshare services (individuals riding alone or with acquaintances) initially dominated the market, the popularity of pooled ridesharing (individuals sharing rides with people they do not know) has grown globally. However, pooled ridesharing remains less common in the U.S., where personal vehicle usage is still the norm. Vehicle design and rideshare services may need to be tailored to user preferences to increase pooled rideshare adoption. Based on a large, national U.S. survey (N = 5385), the results of exploratory and confirmatory factor analyses suggested that four key factors influence riders’ willingness to consider pooled ridesharing: comfort/ease of use, convenience, vehicle technology/accessibility, and passenger safety. A binomial logistic regression was conducted to determine how the four factors influence one’s willingness to consider pooled ridesharing. The two factors that positively influence riders’ willingness to consider pooled ridesharing are vehicle technology/accessibility (B = 1.10) and convenience (B = 0.94), while lack of passenger safety (B = –0.63) and comfort/ease of use (B = –0.17) are pooled ridesharing deterrents. Understanding user-centered design and service factors are critical to increase the use of pooled ridesharing services in the future.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Biomedical and Human Factors Requirements for a Manned Earth Orbiting Station

The primary objective of this study is to determine which biomedical and human factors measurements must be made aboard a space station to assure adequate evaluation of the astronaut's health and performance during prolonged space flights. The study has employed, where possible, a medical and engineering systems analysis to define the pertinent life sciences and space station design parameters and their influence on a measurement program. The major areas requiring evaluation in meeting the study objectives include a definition of the space environment, man's response to the environment, selection of measurement and data management techniques, experimental program, space station design requirements, and a trade-off analysis with final recommendations. The space environment factors that are believed to have a significant effect on man were evaluated. This includes those factors characteristic of the space environment (e. g. weightlessness, radiation) as well as those created within the space station (e. g. toxic contaminants, capsule atmosphere). After establishing the general features of the environment, an appraisal was made of the anticipated response of the astronaut to each of these factors. For thoroughness, the major organ systems and functions of the body were delineated, and a determination was made of their anticipated response to each of the environmental categories. A judgment was then made on the medical significance or importance of each response, which enabled a determination of which physiological and psychological effects should be monitored. Concurrently, an extensive list of measurement techniques and methods of data management was evaluated for applicability to the space station program. The various space station configurations and design parameters were defined in terms of the biomedical and human factors requirements to provide the measurements program. Research design of experimental programs for various station configurations, mission durations, and crew sizes were prepared, and, finally, a trade-off analysis of the critical variables in the station planning was completed with recommendations to enhance the confidence in the measurement program.

EARTH ORBIT↗

Cloning the promoter for transforming growth factor-beta type III receptor. Basal and conditional expression in fetal rat osteoblasts

Transforming growth factor-beta binds to three high affinity cell surface molecules that directly or indirectly regulate its biological effects. The type III receptor (TRIII) is a proteoglycan that lacks significant intracellular signaling or enzymatic motifs but may facilitate transforming growth factor-beta binding to other receptors, stabilize multimeric receptor complexes, or segregate growth factor from activating receptors. Because various agents or events that regulate osteoblast function rapidly modulate TRIII expression, we cloned the 5' region of the rat TRIII gene to assess possible control elements. DNA fragments from this region directed high reporter gene expression in osteoblasts. Sequencing showed no consensus TATA or CCAAT boxes, whereas several nuclear factors binding sequences within the 3' region of the promoter co-mapped with multiple transcription initiation sites, DNase I footprints, gel mobility shift analysis, or loss of activity by deletion or mutation. An upstream enhancer was evident 5' proximal to nucleotide -979, and a silencer region occurred between nucleotides -2014 and -2194. Glucocorticoid sensitivity mapped between nucleotides -687 and -253, whereas bone morphogenetic protein 2 sensitivity co-mapped within the silencer region. Thus, the TRIII promoter contains cooperative basal elements and dispersed growth factor- and hormone-sensitive regulatory regions that can control TRIII expression by osteoblasts.

Non-NASA Center↗

Human Factors in Aeronautics at NASA

This is a briefing to a regularly meeting DoD group called the Human Systems Community of Interest: Mission Effectiveness. I was asked to address human factors in aeronautics at NASA. (Exploration (space) human factors has apparently already been covered.) The briefing describes human factors organizations at NASA Ames and Langley. It then summarizes some aeronautics tasks that involve the application of human factors in the development of specific tools and capabilities. The tasks covered include aircrew checklists, dispatch operations, Playbook, Dynamic Weather Routes, Traffic Aware Strategic Aircrew Requests, and Airplane State Awareness and Prediction Technologies. I mention that most of our aeronautics work involves human factors as embedded in development tasks rather than basic research.

NASA↗

Development of a Fleet-Level Human Factors Engineering Program to Support the Digital Modernization of Multiple Turbine Control Systems

A number of years ago, Duke Energy and the United States (U.S.) Department of Energy (DOE) entered into a collaboration to support Duke’s digital upgrade activities for the main control rooms at three of their commercial nuclear power stations. The collaboration specifically focused on the human factors engineering (HFE) aspects of Duke’s plans to upgrade the legacy turbine control systems (TCS) at their Brunswick, Robinson, and Harris plants. This TSC upgrade involved installing a common digital control system (DCS), or distributed instrumentation and control (I&C) system platform, which multiple digital plant control systems can be integrated onto as the control rooms are modernized over time. Given the breadth and depth of the scope of this upgrade, DOE researchers at Idaho National Laboratory (INL) with expertise in human factors collaborated with Duke throughout the entire HFE life cycle to help ensure the upgrade was performed in a manner consistent with regulatory human factors review criteria, such as the U.S. Nuclear Regulatory Commission’s (NRC) Human Factors Engineering Program Review Model (NUREG 0711, 2012). This paper describes the HFE researchers performed through the early and middle phases of these TCS upgrades. Specific HFE activities include: 1) the development of a human factors program management plan, 2) performing an operational experience review, 3) evaluating the design human system interface while it was still in the early stages of development, and 4) developing a framework to help map these HFE activities to NUREG-0711 to help understand and catalog the value of different types and phases of human performance data collection. These four HFE activities are described in more detail below.

99 GENERAL AND MISCELLANEOUS↗

Understanding Bifacial PV Modeling: Raytracing and View Factor Models

As part of the PV Magazine Webinar 'View-factor vs. ray tracing - which bifacial modelling techniques should you use?,' the second part lead by NREL will explore the different rear-irradiance calculation software, which fall into two categories: view-factor and ray-tracing models. View factor models assume isotropic scattering of reflected rays, allowing for calculation of irradiance by integration. Due-diligence software such as PVSyst or SAM use the view-factor model. Ray-tracing models simulate multipath reflection and absorption of individual rays entering a scene. Raytracing software such as bifacial_radiance, which is the only available open-source toolkit, offers the possibility of reproducing complex scenes, including shading or finite-system edge effects. This can be useful to evaluate specific system geometries, shading and obstructions, areas of different albedo and electrical mismatch, all topics of interest to the prediction of bifacial performance. Model agreement for view factors and bifacial_radiance software is improving and has been shown to be between 2% (absolute) when compared with measured results.

14 SOLAR ENERGY↗