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DOE OSTI2020

On hybrid scenarios in KSTAR

We report the status of hybrid scenario experiments in Korea Superconducting Tokamak Advanced Research (KSTAR). The hybrid scenario is defined as stationary discharges with ${\beta _{\rm{N}}}$ $ \geqslant $ 2.4 and ${H_{89}}$ $ \geqslant $ 2.0 at ${q_{95}}$ < 6.5 without or with very mild sawtooth activities in KSTAR. It is being developed towards reactor-relevant conditions. High performance of ${\beta _{\rm{N}}} \lesssim 3.0$, ${H_{89}} \lesssim 2.4$ and G-factor ($ \equiv {\beta _{\rm{N}}}{H_{89}}/q_{95}^2$) $ \lesssim 0.4$6 has been achieved and sustained for $ \gtrsim 40{{\tau }_{\text{E}}}$ at ne/nGW ~ 0.7 with heating power of $ \lesssim $5 MW. Some KSTAR hybrid discharges exhibit a unique feature of a slow transition from conventional H-mode to hybrid mode after the third neutral beam injection. The reason for the confinement enhancement is extensively studied in this transition period of a representative discharge exhibiting a common feature of KSTAR hybrid scenarios. 0D performance analysis with magnetohydrodynamic activities, 1D kinetic profile dynamics, power balance analysis, linear gyro-kinetic analysis and edge pedestal stability analysis were conducted. The enhancement is thought to be from both the core and the pedestal. The improvement in the core region of the ion energy channel is observed from the linear gyro-kinetic analysis considering the electromagnetic, the fast ion, the Shafranov shift, ${\it{\omega }_{E \times B}}$, and the magnetic shear effect. The electromagnetic finite $\beta $ stabilisation plays a role in the inner core region at ${\rho _{\rm{tor}}}\sim0.35$ together with the fast ion effect. The alpha stabilisation effect is also found at ${\rho _{\rm{tor}}}\sim0.5$. ${\omega _{E \times B}}$, which could reduce the linear growth of the ion temperature gradient mode in the outer core region at ${\rho _{\rm{tor}}}\sim0.5 - 0.7$ with the highest contribution from the toroidal rotation. Furthermore, regarding the improvement in the pedestal, Shafranov shift broadens the stability boundary of the pedestal in support of the diamagnetic effect. The pedestal height and width could be reproduced by the EPED model, while a realistic current profile is used to calculate the internal inductance for Shafranov shift. Based on these findings, a comprehensive confinement enhancement mechanism has been proposed by considering the core-edge interplay.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2017

Tensor-Dictionary Learning with Deep Kruskal-Factor Analysis

We introduce new dictionary learning methods for tensor-variate data of any order. We represent each data item as a sum of Kruskal decomposed dictionary atoms within the framework of beta-process factor analysis (BPFA). Our model is nonparametric and can infer the tensor-rank of each dictionary atom. This Kruskal-Factor Analysis (KFA) is a natural generalization of BPFA. We also extend KFA to a deep convolutional setting and develop online learning methods. We test our approach on image processing and classification tasks achieving state of the art results for 2D & 3D inpainting and Caltech 101. The experiments also show that atom-rank impacts both overcompleteness and sparsity.

Stevens, Andrew J.↗

DOE OSTI2025

Diverging drivers of fungal diversity: seasonal effects shape aboveground communities, while geographical patterns govern belowground communities in rubber tree ecosystems

Understanding the spatiotemporal dynamics of microbial communities is essential for predicting their ecological roles and interactions with host plants. In a recent study, Wei and colleagues (Microbiol Spectr 13:e02097-24, 2024) investigated fungal diversity across multiple plant and soil compartments in rubber trees over two seasons and two geographically distinct regions in China. Their findings revealed that alpha diversity was primarily influenced by seasonal changes and physicochemical factors, while beta diversity exhibited a strong geographical pattern, shaped by leaf phosphorus and soil available potassium. These results highlight the role of environmental drivers in shaping within-community diversity, while other factors contribute to the differences between fungal communities across the soil–plant continuum. By distinguishing the effects of temporal and spatial factors, this study provides detailed insights into plant-associated microbiomes and emphasizes the need for further research on the functional implications of microbial diversity in the context of changing environmental and agricultural conditions.

fungal diversity↗

NASA NTRS2000

Effects of orbital spaceflight on human osteoblastic cell physiology and gene expression

During long-term spaceflight, astronauts lose bone, in part due to a reduction in bone formation. It is not clear, however, whether the force imparted by gravity has direct effects on bone cells. To examine the response of bone forming cells to weightlessness, human fetal osteoblastic (hFOB) cells were cultured during the 17 day STS-80 space shuttle mission. Fractions of conditioned media were collected during flight and shortly after landing for analyses of glucose utilization and accumulation of type I collagen and prostaglandin E(2) (PGE(2)). Total cellular RNA was isolated from flight and ground control cultures after landing. Measurement of glucose levels in conditioned media indicated that glucose utilization occurred at a similar rate in flight and ground control cultures. Furthermore, the levels of type I collagen and PGE(2) accumulation in the flight and control conditioned media were indistinguishable. The steady-state levels of osteonectin, alkaline phosphatase, and osteocalcin messenger RNA (mRNA) were not significantly changed following spaceflight. Gene-specific reductions in mRNA levels for cytokines and skeletal growth factors were detected in the flight cultures using RNase protection assays. Steady-state mRNA levels for interleukin (IL)-1alpha and IL-6 were decreased 8 h following the flight and returned to control levels at 24 h postflight. Also, transforming growth factor (TGF)-beta(2) and TGF-beta(1) message levels were modestly reduced at 8 h and 24 h postflight, although the change was not statistically significant at 8 h. These data suggest that spaceflight did not significantly affect hFOB cell proliferation, expression of type I collagen, or PGE(2) production, further suggesting that the removal of osteoblastic cells from the context of the bone tissue results in a reduced ability to respond to weightlessness. However, spaceflight followed by return to earth significantly impacted the expression of cytokines and skeletal growth factors, which have been implicated as mediators of the bone remodeling cycle. It is not yet clear whether these latter changes were due to weightlessness or to the transient increase in loading resulting from reentry.

Non-NASA Center↗

DOE OSTI2021

Identification and selection of optimal reference genes for qPCR-based gene expression analysis in Fucus distichus under various abiotic stresses

Quantitative gene expression analysis is an important tool in the scientist’s belt. The identification of evenly expressed reference genes is necessary for accurate quantitative gene expression analysis, whether by traditional RT-PCR (reverse-transcription polymerase chain reaction) or by qRT-PCR (quantitative real-time PCR; qPCR). In the Stramenopiles (the major line of eukaryotes that includes brown algae) there is a noted lack of known reference genes for such studies, largely due to the absence of available molecular tools. Here we present a set of nine reference genes (Elongation Factor 1 alpha (EF1A), Elongation Factor 2 alpha (EF2A), Elongation Factor 1 beta (EF1B), 14-3-3 Protein, Ubiquitin Conjugating Enzyme (UBCE2), Glyceraldehyde-3-phosphate Dehydrogenase (GAPDH), Actin Related Protein Complex (ARP2/3), Ribosomal Protein (40s; S23), and Actin) for the brown alga Fucus distichus . These reference genes were tested on adult sporophytes across six abiotic stress conditions (desiccation, light and temperature modification, hormone addition, pollutant exposure, nutrient addition, and wounding). Suitability of these genes as reference genes was quantitatively evaluated across conditions using standard methods and the majority of the tested genes were evaluated favorably. However, we show that normalization genes should be chosen on a condition-by-condition basis. We provide a recommendation that at least two reference genes be used per experiment, a list of recommended pairs for the conditions tested here, and a procedure for identifying a suitable set for an experimenter’s unique design. With the recent expansion of interest in brown algal biology and accompanied molecular tools development, the variety of experimental conditions tested here makes this study a valuable resource for future work in basic biology and understanding stress responses in the brown algal lineage.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Structural Adaptation in Its Orphan Domain Engenders Betaglycan with an Alternate Mode of Growth Factor Binding Relative to Endoglin

Not Available

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Sub-Sampled Imaging for STEM: Maximising Image Speed, Resolution and Precision Through Reconstruction Parameter Refinement

Sub-sampling during image acquisition in scanning transmission electron microscopy (STEM) has been shown to provide a means to increase the overall speed of acquisition while at the same time providing an efficient means to control the dose, dose rate and dose overlap delivered to the sample. In this paper, we discuss specifically the parameters used to reconstruct sub-sampled images and highlight their effect on inpainting using the beta-process factor analysis (BPFA) methodology. The selection of the main control parameters can have a significant effect on the resolution, precision and sensitivity of the final inpainted images, and here we demonstrate a method by which these parameters can be optimised for any image in STEM. As part of this paper, we also provide a link to open source code and a tutorial on its use, whereby these parameters can be tested for any datasets. When coupled with the hardware necessary to rapidly sub-sample images in STEM, this approach can have significant implications for imaging beam sensitive materials and dynamic processes.

47 OTHER INSTRUMENTATION↗

DOE OSTI2017

Acquisition of STEM Images by Adaptive Compressive Sensing

Compressive Sensing (CS) allows a signal to be sparsely measured first and accurately recovered later in software [1]. In scanning transmission electron microscopy (STEM), it is possible to compress an image spatially by reducing the number of measured pixels, which decreases electron dose and increases sensing speed [2,3,4]. The two requirements for CS to work are: (1) sparsity of basis coefficients and (2) incoherence of the sensing system and the representation system. However, when pixels are missing from the image, it is difficult to have an incoherent sensing matrix. Nevertheless, dictionary learning techniques such as Beta-Process Factor Analysis (BPFA) [5] are able to simultaneously discover a basis and the sparse coefficients in the case of missing pixels. On top of CS, we would like to apply active learning [6,7] to further reduce the proportion of pixels being measured, while maintaining image reconstruction quality. Suppose we initially sample 10% of random pixels. We wish to select the next 1% of pixels that are most useful in recovering the image. Now, we have 11% of pixels, and we want to decide the next 1% of “most informative” pixels. Active learning methods are online and sequential in nature. Our goal is to adaptively discover the best sensing mask during acquisition using feedback about the structures in the image. In the end, we hope to recover a high quality reconstruction with a dose reduction relative to the non-adaptive (random) sensing scheme. In doing this, we try three metrics applied to the partial reconstructions for selecting the new set of pixels: (1) variance, (2) Kullback-Leibler (KL) divergence using a Radial Basis Function (RBF) kernel, and (3) entropy. Figs. 1 and 2 display the comparison of Peak Signal-to-Noise (PSNR) using these three different active learning methods at different percentages of sampled pixels. At 20% level, all the three active learning methods underperform the original CS without active learning. However, they all beat the original CS as more of the “most informative” pixels are sampled. One can also argue that CS equipped with active learning requires less sampled pixels to achieve the same value of PSNR than CS with pixels randomly sampled, since all the three PSNR curves with active learning grow at a faster pace than that without active learning. For this particular STEM image, by observing the reconstructed images and the sensing masks, we find that while the method based on RBF kernel acquires samples more uniformly, the one on entropy samples more areas of significant change, thus less uniformly. The KL-divergence method performs the best in terms of reconstruction error (PSNR) for this example [8].

Xie, Weiyi↗

DOE OSTI2019

Crystal structure of the WFIKKN2 follistatin domain reveals insight into how it inhibits growth differentiation factor 8 (GDF8) and GDF11

Growth differentiation factor 8 (GDF8; also known as myostatin) and GDF11 are closely related members of the transforming growth factor β (TGF-β) family. GDF8 strongly and negatively regulates skeletal muscle growth, and GDF11 has been implicated in various age-related pathologies such as cardiac hypertrophy. GDF8 and GDF11 signaling activities are controlled by the extracellular protein antagonists follistatin; follistatin-like 3 (FSTL3); and WAP, follistatin/kazal, immunoglobulin, Kunitz, and netrin domain–containing (WFIKKN). All of these proteins contain a follistatin domain (FSD) important for ligand binding and antagonism. Here, we investigated the structure and function of the FSD from murine WFIKKN2 and compared it with the FSDs of follistatin and FSTL3. Using native gel shift and surface plasmon resonance analyses, we determined that the WFIKKN2 FSD can interact with both GDF8 and GDF11 and block their interactions with the type II receptor activin A receptor type 2B (ActRIIB). Further, we solved the crystal structure of the WFIKKN2 FSD to 1.39 Å resolution and identified surface-exposed residues that, when substituted with alanine, reduce antagonism of GDF8 in full-length WFIKKN2. Furthermore, comparison of the WFIKKN2 FSD with those of follistatin and FSTL3 revealed differences in both the FSD structure and position of residues within the domain that are important for ligand antagonism. Taken together, our results indicate that both WFIKKN and follistatin utilize their FSDs to block the type II receptor but do so via different binding interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Integrating the evidence for a terrestrial carbon sink caused by increasing atmospheric CO 2

Atmospheric carbon dioxide concentration ([CO 2 ]) is increasing, which increases leaf-scale photosynthesis and intrinsic water-use efficiency. These direct responses have the potential to increase plant growth, vegetation biomass, and soil organic matter; transferring carbon from the atmosphere into terrestrial ecosystems (a carbon sink). A substantial global terrestrial carbon sink would slow the rate of [CO 2 ] increase and thus climate change. However, ecosystem CO 2 -responses are complex or confounded by concurrent changes in multiple agents of global change and evidence for a [CO 2 ]-driven terrestrial carbon sink can appear contradictory. In this work, we synthesise theory and broad, multi-disciplinary evidence for the effects of increasing [CO 2 ] (iCO 2 ) on the global terrestrial carbon sink. Evidence suggests a substantial increase in global photosynthesis since pre-industry. Established theory, supported by experiments, indicates that iCO 2 is likely responsible for about half of the increase. Global carbon budgeting, atmospheric data, and forest inventories indicate a historical carbon sink, and these apparent iCO 2 -responses are high in comparison with experiments and theory. Plant mortality and soil carbon iCO 2 -responses are highly uncertain. In conclusion, a range of evidence supports a positive terrestrial carbon sink in response to iCO 2 , albeit with uncertain magnitude and strong suggestion of a role for additional agents of global change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Electron Temperature Gradient Driven Transport Model for Tokamak Plasmas

A new model for electron temperature gradient (ETG) modes is developed as a component of the Multi-Mode anomalous transport module [T. Rafiq \textit{et al.,} Phys Plasmas \textbf{20}, 032506 (2013)] to predict a time dependent electron temperature profile in conventional and low aspect ratio tokamaks. This model is based on two-fluid equations that govern the dynamics of low-frequency short- and long-wavelength electromagnetic toroidal ETG driven drift modes. A low collisionality NSTX discharge is used to scan the plasma parameter dependence on the ETG real frequency, growth rate, and electron thermal diffusivity. Electron thermal transport is discovered in the deep core region where modes are more electromagnetic in nature. Several previously reported gyrokinetic trends are reproduced, including the dependencies of density gradients, magnetic shear, $\beta$ and gradient of $\beta$ $(\betap)$, collisionality, safety factor, and toroidicity, where $\beta$ is the ratio of plasma pressure to the magnetic pressure. The electron heat diffusivity associated with the ETG mode is discovered to be on a scale consistent with the experimental diffusivity determined by power balance analysis.

ETG↗

DOE OSTI2025

NETL RDE Image Classification Dataset 2025 - 14 Classes

Dataset including high-speed down-axis RDE images used for updated image classification study. This dataset includes 180,000 images with 14 classifications: 1CW, 1CCW, 2CW, 2CCW, 3CW, 3CCW, Deflagration, 4CW, 4CCW, 5CW, and 5CCW. Images are cropped to center annulus, and resized to 301x301 pixels. Images are filtered using the AFRL Beta correction factor.

Dataset↗

DOE OSTI2025

NETL RDE Image Classification Dataset 2020 - 10 Classes

Dataset including high-speed down-axis RDE images used for updated image classification study. This dataset includes 100,000 images with 10 classifications: 1CW, 1CCW, 2CW, 2CCW, 3CW, 3CCW, and Deflagration. Images are cropped to center annulus, and resized to 301x301 pixels. Images are filtered using the AFRL Beta correction factor.

AS↗

DOE OSTI2017

Deletion of TGF-β1 Increases Bacterial Clearance by Cytotoxic T Cells in a Tuberculosis Granuloma Model

Mycobacterium tuberculosis is the pathogenic bacterium that causes tuberculosis (TB), one of the most lethal infectious diseases in the world. The only vaccine against TB is minimally protective, and multi-drug resistant TB necessitates new therapeutics to treat infection. Developing new therapies requires a better understanding of the complex host immune response to infection, including dissecting the processes leading to formation of granulomas, the dense cellular lesions associated with TB. In this work, we pair experimental and computational modeling studies to explore cytokine regulation in the context of TB. We use our next-generation hybrid multi-scale model of granuloma formation ( GranSim ) to capture molecular, cellular, and tissue scale dynamics of granuloma formation. We identify TGF-β1 as a major inhibitor of cytotoxic T-cell effector function in granulomas. Deletion of TGF-β1 from the system results in improved bacterial clearance and lesion sterilization. We also identify a novel dichotomous regulation of cytotoxic T cells and macrophages by TGF-β1 and IL-10, respectively. These findings suggest that increasing cytotoxic T-cell effector functions may increase bacterial clearance in granulomas and highlight potential new therapeutic targets for treating TB.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1987

Magnetotails at unmagnetized bodies - Comparison of Comet Giacobini-Zinner and Venus

It is found that the near ionopause environs play a crucial role in the tail formation process at both Venus and G-Z and that draping at the two very different sized bodies occurs on ionopause scale sizes. On the other hand, ion densities, downtail mass fluxes, tailward J x B forces, and lobe betas are factors of about 10,000, 50, 100, and 20 times greater in the G-Z tail than in Venus', while bulk flow speeds and ion temperatures are factors of about 15 and 240 times lower. These large quantitative differences in the properties within the two magnetotails are attributable to the significantly greater upstream mass loading of the solar wind by the extended neutral atmosphere at G-Z (comets in general) compared to the gravitationally bound atmosphere of Venus.

Mccomas, D. J.↗

NASA NTRSDate not supplied

Common Cause Failures Dominate and Defeat Redundancy

Common cause failures occur when several malfunctions are produced by a single event or process. They are especially damaging when they eliminate an entire set of redundant systems and disable their intended function. Redundancy is used when the individual system failure probability is unacceptably high. Redundancy can improve the overall system failure probability if the failures are independent, but the reliability gain is limited if there are dependent failures having a common cause. No amount of redundancy can reduce the total failure probability below the common cause failure probability. Common cause failures defeat redundancy. Systems with high reliability requirements often use extensive redundancy. These highly redundant systems rarely fail unless all the redundant components providing a particular function fail. Complete failures of such highly redundant systems are then usually common cause failures. Common cause failures are prevalent in highly redundant, high reliability systems. Common cause failures dominate redundancy. Redundant systems may fail due to specification, design, manufacturing, operations, or maintenance problems that disable all the identical redundant systems. Common cause failures typically account for one tenth of all failures. If the failure probability is relatively low and common cause failures are significant, adding more than two or three redundant identical units usually gives little added reliability improvement. Common cause failures can be reduced by using diverse components with different technologies and manufacturers, by separating and shielding subsystems, and by avoiding shared control, power, or location. External events and shared vulnerabilities may still cause common cause failures.

common cause failures↗

NASA NTRSDate not supplied

Common Cause Failures Dominate and Defeat Redundancy

common cause failures↗

DOE OSTI2019

Direct determination of the La 138 β -decay Q value using Penning trap mass spectrometry

Background: The understanding and description of forbidden decays provides interesting challenges for nuclear theory. These calculations could help to test underlying nuclear models and interpret experimental data. Purpose: Compare a direct measurement of the 138 La $\beta$-decay $Q$ value with the beta-decay spectrum end-point energy measured by Quarati et al. using LaBr 3 detectors [Appl. Radiat. Isot. 108, 30 (2016)]. Use new precise measurements of the 138 La $\beta$-decay and electron capture (EC) $Q$ values to improve theoretical calculations of the $\beta$-decay spectrum and EC probabilities. Method: High-precision Penning trap mass spectrometry was used to measure cyclotron frequency ratios of 138 La, 138 Ce and 138 Ba ions from which beta-decay and EC Q values for 138 La were obtained.Results: The 138 La beta-decay and EC Q values were measured to be Q$_\beta$ = 1052.42(41) keV and $Q_{EC}$ = 1748.41(34) keV, improving the precision compared to the values obtained in the most recent atomic mass evaluation [Wang, et al., Chin. Phys. C 41, 030003 (2017)] by an order of magnitude. These results are used for improved calculations of the 138 La $\beta$-decay shape factor and EC probabilities. New determinations for the 138 Ce 2EC $Q$ value and the atomic masses of 138 La, 138 Ce, and 138 Ba are also reported. Conclusion: The 138 La $\beta$-decay Q value measured by Quarati et al. is in excellent agreement with our new result, which is an order of magnitude more precise. Uncertainties in the shape factor calculations for 138 La $\beta$-decay using our new $Q$ value are reduced by an order of magnitude. Uncertainties in the EC probability ratios are also reduced and show improved agreement with experimental data.

138La↗