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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

FluxSat: Long-term Earth Science Data Record (ESDR) for Terrestrial Gross Primary Production (GPP) based on satellite data calibrated with eddy covariance data

Gross primary production (GPP), the amount of carbon dioxide (CO 2 ) assimilated by plants through photosynthesis, is one of the most variable and uncertain components of the global carbon cycle. Global GPP has been estimated with a number of process-based models, data-driven, and hybrid approaches. Dynamic global vegetation models (DGVMs), driven by observed environmental changes, are used for global carbon budget assessments and long-term (climate) prediction. Benchmarking these and other models globally with data-driven GPP estimates is critical for understanding the land sink and ensuring accurate forecasts of the carbon cycle. In addition, global data-driven GPP estimates are crucial for studies of interannual variability, including trends that are linked to mechanisms with large uncertainties, such as the indirect CO 2 fertilization effect related to greening. In response to a community need for a GPP data set that well captures spatio-temporal variability, we developed FluxSat, a data-driven approach that optimizes the use of satellite reflectance data from the NASA MODerate-resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites, calibrated using ground-based eddy covariance (EC) data. We are enhancing (spatially, higher resolution) and extending FluxSat (in time, with additional sensors) to create a high quality long term GPP Earth System Data Record (ESDR) for use in model benchmarking, carbon cycle modeling, and studies of trends and interannual variability. Our team’s objectives are to: 1. Update and document the current MODIS FluxSat GPP (daily, 0.05o and 0.5o resolutions) products with latest available MODIS and EC data sets; 2. Extend FluxSat GPP record forward in time with the Visible Infrared Imaging Radiometer Suite (VIIRS) on operational weather satellites going forward; 3. Extend FluxSat GPP record backward in time using the Advanced Very High Resolution Radiometer (AVHRR) on weather satellites dating back to 1981; 4. Provide higher spatial resolution MODIS and VIIRS GPP (0.0083o). 5. Thoroughly evaluate all FluxSat products with independent data; and 6. Create a homogenized long-term GPP record spanning 40+ years. We will discuss plans for this long-term data set that is supported through the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program.

gross Primary Production↗
NASA NTRSDate not supplied

Assessment of Long-term Trends in the Collection 4 Total Ozone Record from the Ozone Monitoring Instrument

Long-term changes in total ozone affect the amount of harmful UV radiation reaching Earth’s surface and reflect progress made towards recovery of stratospheric ozone. Satellite total ozone data are also used to estimate long-term trends in tropospheric ozone, a reactive and potent greenhouse gas, by subtracting the stratospheric column timeseries from that of total ozone. For these scientific applications, the long-term stability should be better than 1%. Left unchecked, instrument calibration drift can produce a trend of this magnitude or greater. NASA has produced nearly twenty years of total ozone data from the Ozone Monitoring Instrument (OMI) using the Total Ozone Mapping Spectrometer (TOMS) algorithm. The drift in the OMI instrument as monitored by ice radiance calibration has been relatively slow, but it has reached a level of ~3% over the mission lifetime. This drift was corrected in the recently released Collection 4 OMI calibrated radiances, updating the Collection 3 calibration released in 2006. We have reprocessed the OMI total ozone record using the Collection 4 calibration and updates to the TOMS algorithm. We summarize these changes and evaluate their impact by comparing to the previous Collection 3 OMI dataset, the Suomi NPP Ozone Mapping and Profiler Suite Nadir Mapper (OMPS-NM) and Solar Backscatter UV (SBUV) Merged Ozone Dataset (MOD) total ozone records and other independent satellite total ozone datasets. Climatological radiance residuals from OMI and OMPS-NM are calculated and compared to investigate differences in spectral calibration that can cause drifts in long-term total ozone trends. We also analyze the tropospheric ozone record produced using the Collection 4 OMI total ozone and stratospheric column ozone from MLS. Collection 3 OMI data processed with the TOMS algorithm show a positive drift relative to other satellite and ground-based data of 1-2 DU per decade. Initial results show that this drift is reduced in Collection 4 OMI, due to the updated OMI calibration. In this work we will quantify the improvements in Collection 4 OMI relative to independent data sources at both the ozone and radiance level

Collection 4 OMI Total Ozone↗
NASA NTRSDate not supplied

Abrasive Effects of Lunar Regolith on Material Wear for Long-Term Lunar Applications

Long-term operations on the Moon’s surface require materials that can withstand the harsh lunar environment. Lunar dust and regolith pose significant threats to the long-term durability of materials used in lunar applications. Lunar dust, easily perturbed and dispersed, adheres and abrades materials due to its rough and irregular grain morphology. More closely representing this abrasion action through experimental laboratory testing is critical in assessing the durability of potential lunar candidate materials used in mechanical, sensor, and human-based systems. In this study, the performance of materials using Taber abrasive wheels made from lunar regolith simulant was assessed and compared to results obtained using standard ceramic-based abrasion materials. The results highlight a difference in the abrasive wear rates between the lunar regolith simulant and the standard ceramic-based abrasive. Utilizing the mechanisms and testing capabilities of this two-body abrasive interaction leveraging regolith-based abrasives may more closely represent the interplay between materials and lunar dust, which is vital for assessing the long-term viability of materials for extended lunar missions. Improved lunar testing capabilities may also enhance evaluations of the long-term performance degradation of passive and active dust mitigation methods.

Zachary Stein↗
DOE OSTI2021

Verification and validation of developed short-term forecasting models

Recent advancements in machine learning (ML) and artificial intelligence (AI) technologies provide an opportunity for leveraging data-driven algorithms to predict future nuclear power plant (NPP) operating conditions by using recorded plant process data. Successfully implementing these models can lead to cost-reducing, conditioned-based predictive maintenance through optimized maintenance schedules and a reduction of unnecessary maintenance activities. This report discusses the verification and validation of short-term forecasting processes (i.e., data cleaning, feature selection, model optimization, and forecasting) developed in previous reports. The verification and validation (V&V) process demonstrates the expected precision and accuracy when the ML model encounters new datasets from different systems. Shapley additive explanations were used as the primary means of feature selection across these different data set. Individual models were trained for each data set, then validated through a cross-validation procedure. In this report, two different ML models were tasked to predict variables from three different plant process data sets with varying prediction horizons. The results indicate that support vector regression (SVR) outperformed long short-term memory (LSTM) neural networks in regard to each data set and each prediction horizon in this study, but further tuning and optimization could improve long short-term memory results. However, each forecasting model showed reduced performance as the prediction horizon was extended from 1 hour to 1 day ahead. Research is ongoing to evaluate the optimal input variable space, which is based on a given set of process parameters, to further improve forecasting accuracy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Development of Short-Term Forecasting Models Using Plant Asset Data and Feature Selection

Nuclear power plants collect and store large volumes of heterogeneous data from various components and systems. With recent advances in machine learning (ML) techniques, these data can be leveraged to develop diagnostic and short-term forecasting models to better predict future equipment condition. Maintenance operations can then be planned in advance whenever degraded performance is predicted, thus resulting in fewer unplanned outages and the optimization of maintenance activities. This enables lower maintenance costs and improves the overall economics of nuclear power. This paper focuses on developing a short-term forecasting process that leverages a feature selection process to distill large volumes of heterogeneous data and predict specific equipment parameters. A variety of feature selection methods, including Shapley Additive Explanations (SHAP) and variance inflation factor (VIF), were used to select the optimal features as inputs for three ML methods: long short-term memory (LSTM) networks, support vector regression (SVR), and random forest (RF). Each combination of model and input features was used to predict a pump bearing temperature both 1 and 24 hours in advance, based on actual plant system data. The optimal inputs for the LSTM and SVR were selected using the SHAP values, while the optimal input for the RF consisted solely of the response variable itself. Each model produced similar 1-hour-ahead predictions, with root mean square errors (RMSEs) of roughly 0.006. For the 24-hour-ahead predictions, differences could be seen between LSTM, SVR, and RF, as reflected by model performances of 0.036 +- 0.014, 0.0026 +- 0, and 0.063 +- 0.004 RMSE, respectively. As big data and continuous online monitoring become more widely available, the proposed feature selection process can be used for many applications beyond the prediction of process parameters within nuclear infrastructure.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Long-Term Degradation of Passivated Emitter and Rear Contact Silicon Solar Cell under Light and Heat

Advanced designs enable high-efficiency solar cells; however, more complex structures create new long-term stability concerns. Herein, the long-term degradation processes affecting advanced silicon solar cells using laboratory-based illumination and heating over hundreds of hours are investigated. The activation energy for the degradation of voltage is estimated and the degradation rates to normal solar cell operating temperature ranges are extrapolated. The cell degradation observed at high temperatures in the lab is kinetically similar to the process affecting field-deployed modules contributing to 0.37% year-1 of annualized degradation. Electroluminescence and photoluminescence mapping show that the degradation is dominated by minority carrier lifetime reduction. Suns-open-circuit voltage and light beam-induced current results indicate that the degradation could result from passivation degradation at the surface or defect formation in the near-subsurface region, leading to increased minority carrier recombination. This work highlights a long-term degradation process under elevated temperature and illumination that may continue to affect cells in an irreversible manner that is separate from recoverable light-induced degradation and light- and elevated temperature-induced degradation.

14 SOLAR ENERGY↗
DOE OSTI2025

Depth-dependent links between microbial taxa and nitrous oxide emissions in a long-term cotton cropping system employing soil health practices

Long-term management practices can shape soil microbial communities in ways that influence nitrogen (N) dynamics and nitrous oxide (N 2 O) emissions. We leverage a 41-year continuous cotton cropping experiment with contrasting tillage, cover cropping, and N fertilization regimes to investigate how these long-term strategies influence soil microbial communities and their associations with N 2 O fluxes during the cotton growing season. Using 16S rRNA gene metabarcoding, we assessed microbial composition in surface and subsurface soils and evaluated its relationship with temporal N 2 O emissions. Among the management practices, N fertilization – a known driver of N 2 O emissions – had the strongest effect on microbial community composition and was linked to a greater number of taxa correlated to N 2 O emissions, particularly in surface soils. Soil pH emerged as a key variable influencing microbial structure across depth and was negatively associated with both N 2 O emissions and microbial composition in the surface layers of fertilized soils. In total, 57 archaeal/bacterial taxa were correlated with N 2 O fluxes, but only seven were shared across depths, suggesting distinct microbial contributors in surface and subsurface soils. Several of these taxa have been previously reported to be associated with N and C cycling processes such as nitrate respiration or carbon turnover, indicating functional context to their correlation with N 2 O fluxes. Temporal shifts in the abundance of key taxa aligned with seasonal peaks in N 2 O emissions, notably in early and late August, and were most pronounced under conventional tillage, hairy vetch cover cropping, and N fertilization. While 16S-based associations cannot confirm functional gene presence or activity, these findings demonstrate that long-term fertilization and associated soil acidification are dominant drivers of microbial shifts linked to N 2 O emissions and highlight the importance of accounting for depth-specific and seasonal microbial dynamics when evaluating management impacts on greenhouse gas emissions.

16S rRNA gene sequencing↗
DOE OSTI2020

Exact and locally implicit source term solvers for multifluid-Maxwell systems

Recently, a family of models that couple multifluid systems to the full Maxwell equations have been used in laboratory, space, and astrophysical plasma modeling. These models are more complete descriptions of the plasma than reduced models like magnetohydrodynamic (MHD) since they are derived more closely from the full kinetic Vlasov-Maxwell system, without assumptions like quasi-neutrality, negligible electron mass, etc. Thus these models naturally retain non-ideal MHD effects like electron inertia, Hall term, pressure anisotropy/nongyrotropy, displacement current, among others. One obstacle to broader application of these model is that an explicit treatment of their source terms leads to the need to resolve rapid processes like plasma oscillation and electron cyclotron motion, even when these are not important. In this paper, we suggest two ways to address this issue. First, we derive the analytic solutions to the source update equations, which can be implemented as a practical, but less generic solver. We then develop a time-centered, locally implicit algorithm to update the source terms, allowing stepping over the fast kinetic time-scales. For a plasma with S species, the locally implicit algorithm involves inverting a local (3 S + 3) × (3 S + 3) matrix only, thus is very efficient. The performance can be further increased by using the direct update formulas to skip null calculations. In this paper, we present benchmarks illustrating the exact energy-conservation of the locally implicit solver, as well as its efficiency and robustness for both small-scale, idealized problems and largescale, complex systems. The locally implicit algorithm can be also easily extended to include other local sources, like collisions and ionization, which are difficult to solve analytically.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Dirty bomb source term characterization and downwind dispersion: Review of experimental evidence

Dirty bombs are considered one of the easiest forms of radiological terrorism, a form of terrorism based on the deliberate use of radiological material to cause adverse effects in a target population. One U.S. Government official has even described a dirty bomb attack as “all but inevitable”. While people in the vicinity of the blast may experience acute radiation effects, people downwind may unknowingly be contaminated by the radioactive airborne particulate and face increased long-term cancer risk. The likelihood of increased cancer risk depends on the radionuclide used and its specific activity, its aerosolization potential, the particle sizes generated in the blast, and where a person is with respect to the detonation. Different studies have reported that plausible radionuclides for dirty bomb include 60 Co, 90 Sr, 137 Cs, 192 Ir, 241 Am based on their availability in commercial sources as well as safeguards, the amount needed for adverse health effects, previous mishandling of radionuclides and malicious uses. In order to have increased long-term cancer risk, the radionuclide would have to deposit inside the body by entering the respiratory tract and then possibly migrate to other organs or bones (ground shine is not considered in this paper because areas affected by the event will likely become inaccessible). This implies that the particles will have to be smaller than 10 μm to be inhaled. Experiments involving the detonation of dirty bombs have shown that particles or droplets smaller than 10 μm are generated, independently from the initial radionuclide or its state (e.g., powder, solution). Atmospheric tests have shown that in unobstructed terrain, the radionuclide laden cloud can travel kilometers downwind even for relatively small amounts of explosives. Furthermore, buildings in the path of the cloud can change the dose rate. For instance, in one experiment with a single building, the dose rate was 1–2 orders of magnitude lower behind the obstacle compared to its front face. For people walking around, the amount of particulate deposited on them and inhaled will depend on their path relative to the cloud, resulting in the counterintuitive result that the closer people may actually not be the ones more at risk because they could simply miss the bulk of the cloud in their wandering. In summary, the long-term cancer risk for people caught in a dirty bomb cloud away from the detonation requires considering where and when the people are, which radionuclide was used, and the layout of the obstacles (e.g., buildings, vegetation) in the path of the cloud.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2020

Long-term spatial and temporal solar resource variability over America using the NSRDB version 3 (1998–2017)

The study assesses the long-term spatial and temporal solar resource variability in America using the 20-year National Renewable Energy Laboratory's (NREL's) National Solar Radiation Database (NSRDB). Specifically, the coefficient of variation (COV) is used to analyze the spatial and temporal (interannual and seasonal) variability. Further, both spatial and temporal long-term variability are analyzed using the Köppen-Geiger climate classification. The temporal variability is found that, on average, the continental United States (CONUS) COV reaches up to 5% for global horizontal irradiance (GHI) and 10% for direct normal irradiance (DNI), and that the NSRDB domain's COV is roughly twice that of CONUS. For the seasonal variability analysis, the winter months are found to exhibit higher COV than the other seasons. In particular, December exhibits the highest variability, reaching on average 30% for DNI and 20% for GHI over various areas. On the other hand, the summer months demonstrate significantly lower variability, reaching only less than 20% for DNI and 10% for GHI, on average. Similarly, the spatial variability is analyzed by comparing each pixel to its neighbors. The long-term spatial variability is found to increase with the number of neighboring pixels being considered, which is equivalent to an increase in distance (within a 100-km x 100-km square grid). As expected, the DNI spatial variability is higher than that of GHI. Moreover, the annual solar irradiance anomalies are found to reach ±25% for both GHI and DNI (and even exceed those value in some instances) during each year of the 20-year period.

14 SOLAR ENERGY↗
DOE OSTI2023

Experimental and Computational Mechanisms that Govern Long-Term Stability of CO 2 -Adsorbed ZIF-8-Based Porous Liquids

Porous liquids (PLs) based on the zeolitic imidazole framework ZIF-8 are attractive systems for carbon capture since the hydrophobic ZIF framework can be solvated in aqueous solvent systems without porous host degradation. However, solid ZIF-8 is known to degrade when exposed to CO 2 in wet environments, and therefore the long-term stability of ZIF-8-based PLs is unknown. Here, through aging experiments, the long-term stability of a ZIF-8 PL formed using the water, ethylene glycol, and 2-methylimidazole solvent system was systematically examined, and the mechanisms of degradation were elucidated. The PL was found to be stable for several weeks, with no ZIF framework degradation observed after aging in N 2 or air. However, for PLs aged in a CO 2 atmosphere, formation of a secondary phase occurred within 1 day from the degradation of the ZIF-8 framework. From the computational and structural evaluation of the effects of CO 2 on the PL solvent mixture, it was identified that the basic environment of the PL caused ethylene glycol to react with CO 2 forming carbonate species. These carbonate species further react within the PL to degrade ZIF-8. The mechanisms governing this process involves a multistep pathway for PL degradation and lays out a long-term evaluation strategy of PLs for carbon capture. Additionally, it clearly demonstrates the need to examine the reactivity and aging properties of all components in these complex PL systems in order to fully assess their stabilities and lifetimes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Cations Control Lipid Bilayer Memcapacitance Associated with Long-Term Potentiation

Phospholipid bilayers can be described as capacitors whose capacitance per unit area (specific capacitance, C m ) is determined by their thickness and dielectric constant–independent of applied voltage. It is also widely assumed that the C m of membranes can be treated as a “biological constant”. Recently, using droplet interface bilayers (DIBs), it was shown that zwitterionic phosphatidylcholine (PC) lipid bilayers can act as voltage-dependent, nonlinear memory capacitors, or memcapacitors. When exposed to an electrical “training” stimulation protocol, capacitive energy storage in lipid membranes was enhanced in the form of long-term potentiation (LTP), which enables biological learning and long-term memory. LTP was the result of membrane restructuring and the progressive asymmetric distribution of ions across the lipid bilayer during training, which is analogous, for example, to exponential capacitive energy harvesting from self-powered nanogenerators. Here, we describe how LTP could be produced from a membrane that is continuously pumped into a nonequilibrium steady state, altering its dielectric properties. During this time, the membrane undergoes static and dynamic changes that are fed back to the system’s potential energy, ultimately resulting in a membrane whose modified molecular structure supports long-term memory storage and LTP. Here, we also show that LTP is very sensitive to different salts (KCl, NaCl, LiCl, and TmCl 3 ), with LiCl and TmCl 3 having the most profound effect in depressing LTP, relative to KCl. This effect is related to how the different cations interact with the bilayer zwitterionic PC lipid headgroups primarily through electric-field-induced changes to the statistically averaged orientations of water dipoles at the bilayer headgroup interface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Considerations for Medium-Term Load Forecasting in Morocco

There are many factors that determine how demand for electricity may change over time. Medium-term load forecasting is a subset of load forecasting that focuses on the next year. This presentation summarizes analysis performed by NREL on medium-term load forecasting performed for the Moroccan energy system. This analysis includes hourly regressions and load clustering. This work also describes potential next steps that can be implemented by ONEE to improve this medium-term load forecasting.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Long Term Damage Testing (NREL)

DOE's Regional Test Center program has fielded several strings of PV modules as part of their Long Term Testing program. Some of these modules have been installed since 2016 and have been exposed to severe weather events. A key to developing long lifespans for PV modules (in excess of 30 years) is understanding how damage and defects develop, propagate and progress. Researchers at the NREL Regional Test Center have started developing testing procedures and analysis tools in order to characterize modules in a controlled manner with the goal of understanding how damage spreads under normal operations. Characterization methods include EL and IR imaging, outdoor and indoor IV curves, and long term exposure monitoring. Modules to be evaluated will be chosen based on severity of defect, ability to track changes in defect and space requirements. The samples will be loaded at maximum power using grid-tied inverters or other means. Gathering and reporting on this data may help engineers and scientists design for damage and improve long-term performance.

crack damage↗
DOE OSTI2022

Adoption of biofuels for marine shipping decarbonization: A long‐term price and scalability assessment

Abstract This study assessed the long‐term annual biofuel production capacity potential and price in the United States and shed light on the prospect of biofuel adoption for marine propulsion. A linear programming model was developed to assist the projections and provide insightful analyses. The projected long‐term (2040) maximum annual capacity of biofuels in the United States is 245 million metric tons (Mt) or 65 billion gallons of heavy fuel oil gallon equivalent (HFOGE) when based on the median feedstock availability. Between 2022 (near‐term) and 2040, the potential biofuel capacity increases by over 40%, attributed to increased feedstock availability. At a price range up to $500/t, biodiesel is the main product, and the annual capacity (12 Mt) is limited to feedstock availability constraints. Biodiesel and corn ethanol are the main biofuels at a price range up to $750/t. At a higher price point (above $750/t), the biofuel types and annual capacities increase substantially (218 Mt per year). Biofuels above this price include gasoline‐, jet‐, and diesel‐range blendstocks, as well as bio‐methanol, bio‐propane, and biogas. This study concludes that the US domestic feedstock availability coupled with advanced conversion technologies can produce substantial amounts of biofuels to achieve a critical mass and be impactful as alternative marine fuels. There is also a need to improve the biofuel price for marine shipping adoption. Policies and economic incentives that provide temporary financial support would help facilitate maritime biofuel adoption. © 2022 Alliance for Sustainable Energy, LLC. Biofuels, Bioproducts and Biorefining published by Society of Industrial Chemistry and John Wiley & Sons Ltd.

09 BIOMASS FUELS↗
DOE OSTI2026

Long‐term growth and persistence of granitic inselbergs in a semi‐arid cratonic landscape

Granitic inselbergs are enduring landforms that punctuate planation surfaces in tectonically stable settings, yet the mechanisms and timescales of their persistence remain debated. Here, in this study, we present a multinuclide cosmogenic dataset ( 10 Be, 26 Al and 21 Ne) from bedrock, fluvial sediments and planation surfaces in the semi-arid Central Ceará Domain, north-eastern Brazil, to quantify denudation rates and reconstruct the long-term dynamics of residual relief formation. This triple-nuclide approach enables independent validation of denudation contrasts and long-term exposure histories, providing quantitative constraints on inselberg evolution that a single-nuclide approach could not resolve. Bedrock denudation rates (1–4 m Myr −1 ) are systematically lower than basin-wide rates (8–14 m Myr −1 ), revealing a regional pattern of vertical differential denudation. When combined with summit elevations and surface exposure ages of up to 5 Myr, these contrasts suggest that cumulative relief growth has been operating over timescales of tens of millions of years (1–57 Myr). Morphological and structural observations further indicate localized mass wasting and heterogeneous erosion styles, modulated by rock fabric and joint density. Cosmogenic nuclide inventories in detrital sediments reveal partial reworking from older sediment stocks, including surface pebbles with exposure ages up to 5 Myr, which record multistage of burial and re-exposure histories and reflect episodic remobilization in low-connectivity, semi-arid catchments. Rather than static relicts of ancient surfaces, inselbergs in this cratonic setting emerge as dynamic landforms actively sustained by slow but persistent differential denudation. These results provide new constraints on long-term cratonic landscape evolution and underscore the interplay between lithological resistance, structural inheritance and sediment transfer processes in sustaining topographic relief. They also call for a critical reassessment of classical inselberg models, suggesting that hybrid mechanisms, rather than single-process paradigms, more accurately capture the complexity of residual landform development in cratonic interiors.

Cosmogenic nuclides↗
DOE OSTI2021

Long‐term drench of exopolysaccharide from Leuconostoc pseudomesenteroides XG5 protects against type 1 diabetes of NOD mice via stimulating GLP ‐1 secretion

Abstract BACKGROUND Type 1 diabetes is an autoimmune disease that results in the specific destruction of insulin‐producing beta cells in the pancreas. The aim of this study was to investigate the mechanism of exopolysaccharide from Leuconostoc pseudomesenteroides XG5 (XG5 EPS) against type 1 diabetes. RESULTS Long‐term drench of XG5 EPS delayed the onset of autoimmune diabetes and had fewer islets with high‐grade infiltration (an insulitis score of 3 or 4) than untreated NOD mice. Oral administration of 50 mg kg −1 d −1 XG5 EPS increased the insulin and glucagon‐like peptide‐1 (GLP‐1) levels of serum, stimulated GLP‐1 secretion and upregulated gcg mRNA expression of colon in NOD mice. Moreover, oral administration of 50 mg kg −1 d −1 XG5 EPS significantly increased total short‐chain fatty acids levels in the colon contents, especially those of acetic acid and butyric acid. In NCI‐H716 cells, 500 and 1000 μmol L −1 sodium butyrate promoted the secretion of GLP‐1 and upregulated the mRNA expression of gcg and PC3 , while XG5 EPS and sodium acetate did not stimulate the GLP‐1 secretion. Therefore, long‐term drench of XG5 EPS delayed the onset of autoimmune diabetes, which may be directly correlated with the increase of butyrate in the colon of NOD mice. CONCLUSION Long‐term drench of 50 mg kg −1 d −1 XG5 EPS promoted the expression and secretion of GLP‐1 by increasing the production of butyric acid, thereby delaying T1D onset in NOD mice. © 2021 Society of Chemical Industry.

Pan, Lei↗
DOE OSTI2025

Spinning black hole scattering at $ \mathcal{O} $(G 3 S 2 )(G 3 S 2 ): Casimir terms, radial action and hidden symmetry

We resolve subtleties in calculating the post-Minksowskian dynamics of binary systems, as a spin expansion, from massive scattering amplitudes of fixed finite spin. In particular, the apparently ambiguous spin Casimir terms can be fully determined from the gradient of the spin-diagonal part of the amplitudes with respect to S 2 = −s(s+1)ħ 2 , using an interpolation between massive amplitudes with different spin representations. From two-loop amplitudes of spin-0 and spin-1 particles minimally coupled to gravity, we extract the spin Casimir terms in the conservative scattering angle between a spinless and a spinning black hole at $ \mathcal{O} $(G 3 S 2 ), finding agreement with known results in the literature. This completes an earlier study [Phys. Rev. Lett. 130 (2023), 021601] that calculated the non-Casimir terms from amplitudes. We also illustrate our methods using a model of spinning bodies in electrodynamics, finding agreement between scattering amplitude predictions and classical predictions in a root-Kerr electromagnetic background up to $ \mathcal{O} $(α 3 S 2 ). For both gravity and electrodynamics, the finite part of the amplitude coincides with the two-body radial action in the aligned spin limit, generalizing the amplitude-action relation beyond the spinless case. Surprisingly, the two-loop amplitude displays a hidden spin-shift symmetry in the probe limit, which was previously observed at one loop. We conjecture that the symmetry holds to all orders in the coupling constant and is a consequence of integrability of Kerr orbits in the probe limit at the first few orders in spin.

Classical Theories of Gravity↗