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Pencil-beam scanning proton therapy is particularly sensitive to anatomic changes, which may affect the delivered dose distribution. This study examined whether offline adaptation using on-treatment magnetic resonance imaging (MRI) scan during proton therapy could improve plan quality for pediatric patients.
Globally, freshwater shortage is one of the most dangerous risks for society. Changing hydro-climatic and socioeconomic conditions have aggravated water scarcity over the past decades. A wide range of studies show that water scarcity will intensify in the future, as a result of both increased consumptive water use and, in some regions, climate change. Although it is well-known that El Niño- Southern Oscillation (ENSO) affects patterns of precipitation and drought at global and regional scales, little attention has yet been paid to the impacts of climate variability on water scarcity conditions, despite its importance for adaptation planning. Therefore, we present the first global-scale sensitivity assessment of water scarcity to ENSO, the most dominant signal of climate variability. We show that over the time period 1961-2010, both water availability and water scarcity conditions are significantly correlated with ENSO-driven climate variability over a large proportion of the global land area (> 28.1 %); an area inhabited by more than 31.4% of the global population. We also found, however, that climate variability alone is often not enough to trigger the actual incidence of water scarcity events. The sensitivity of a region to water scarcity events, expressed in terms of land area or population exposed, is determined by both hydro-climatic and socioeconomic conditions. Currently, the population actually impacted by water scarcity events consists of 39.6% (CTA: consumption-to-availability ratio) and 41.1% (WCI: water crowding index) of the global population, whilst only 11.4% (CTA) and 15.9% (WCI) of the global population is at the same time living in areas sensitive to ENSO-driven climate variability. These results are contrasted, however, by differences in growth rates found under changing socioeconomic conditions, which are relatively high in regions exposed to water scarcity events. Given the correlations found between ENSO and water availability and scarcity conditions, and the relative developments of water scarcity impacts under changing socioeconomic conditions, we suggest that there is potential for ENSO-based adaptation and risk reduction that could be facilitated by more research on this emerging topic.
A computational fluid dynamics (CFD) method has been employed to compute vortical flows around slender wing/body configurations. The emphasis of the paper is on the effectiveness of an adaptive grid procedure in "capturing" concentrated vortices generated at sharp edges or flow separation lines of lifting surfaces flying at high angles of attack. The method is based on a tetrahedral unstructured grid technology developed at the NASA Langley Research Center. Two steady-state, subsonic, inviscid and Navier-Stokes flow test cases are presented to demonstrate the applicability of the method for solving practical vortical flow problems. The first test case concerns vortex flow over a simple 65' delta wing with different values of leading-edge bluntness, and the second case is that of a more complex fighter configuration. The superiority of the adapted solutions in capturing the vortex flow structure over the conventional unadapted results is demonstrated by comparisons with the windtunnel experimental data. The study shows that numerical prediction of vortical flows is highly sensitive to the local grid resolution and that the implementation of grid adaptation is essential when applying CFD methods to such complicated flow problems.
A computational fluid dynamics (CFD) method has been employed to compute vortical flows around slender wing/body configurations. The emphasis of the paper is on the effectiveness of an adaptive grid procedure in "capturing" concentrated vortices generated at sharp edges or flow separation lines of lifting surfaces flying at high angles of attack. The method is based on a tetrahedral unstructured grid technology developed at the NASA Langley Research Center. Two steady-state, subsonic, inviscid and Navier-Stokes flow test cases are presented to demonstrate the applicability of the method for solving practical vortical flow problems. The first test case concerns vortex flow over a simple 65deg delta wing with different values of leading-edge bluntness, and the second case is that of a more complex fighter configuration. The superiority of the adapted solutions in capturing the vortex flow structure over the conventional unadapted results is demonstrated by comparisons with the windtunnel experimental data. The study shows that numerical prediction of vortical flows is highly sensitive to the local grid resolution and that the implementation of grid adaptation is essential when applying CFD methods to such complicated flow problems.
In cross-silo federated learning (FL), sensitive text datasets remain confined to local organizations due to privacy regulations, making repeated training for each downstream task both communication-intensive and privacy-demanding. A promising alternative is to generate differentially private (DP) synthetic datasets that approximate the global distribution and can be reused across tasks. However, pretrained large language models (LLMs) often fail under domain shift, and federated finetuning is hindered by computational heterogeneity: only resource-rich clients can update the model, while weaker clients are excluded, amplifying data skew and the adverse effects of DP noise. We propose a flexible participation framework that adapts to client capacities. Strong clients perform DP federated finetuning, while weak clients contribute through a lightweight DP voting mechanism that refines synthetic text. To ensure the synthetic data mirrors the global dataset, we apply control codes (e.g., labels, topics, metadata) that represent each client’s data proportions and constrain voting to semantically coherent subsets. This two-phase approach requires only a single round of communication for weak clients and integrates contributions from all participants. Experiments show that our framework improves distribution alignment and downstream robustness under DP and heterogeneity.
Session TA1 includes short reports covering: (1) Indices of Baroreceptor Reflex Sensitivity: The Use in Rehabilitation Medicine and Space Cardiology; (2) +Gz and +Gx Tolerance of Healthy Persons of Non-Flying Trades at Primary Selection of the Centrifuge; (3) Effect of Dry Immersion on Calf Blood Supply During Sustained Contraction and Upright Exercise in Man; (4) Cardiovascular and Valsalva Responses during Parabolic flight; (5) An Analysis of the Cardiovascular Responses under Hyper- and Hypo-Gravity Environments using a Mathematical model; (6) Effect of Very Gradual Onset Rate +Gz Exposures on the Cardiovascular System; and (7) NASA Specialized Center of Research and Training (NSCORT) in Integrated Physiology: Mechanisms of Physiological Adaptations to Microgravity.
A computational fluid dynamics (CFD) method has been employed to compute vortical flows around slender wing/body configurations. The emphasis of the paper is on the effectiveness of an adaptive grid procedure in "capturing" concentrated vortices generated at sharp edges or flow separation lines of lifting surfaces flying at high angles of attack. The method is based on a tetrahedral unstructured grid technology developed at the NASA Langley Research Center. Two steady-state, subsonic, inviscid and Navier-Stokes flow test cases are presented to demonstrate the applicability of the method for solving practical vortical flow problems. The first test case concerns vortex flow over a simple 65 delta wing with different values of leading-edge radius. Although the geometry is quite simple, it poses a challenging problem for computing vortices originating from blunt leading edges. The second case is that of a more complex fighter configuration. The superiority of the adapted solutions in capturing the vortex flow structure over the conventional unadapted results is demonstrated by comparisons with the wind-tunnel experimental data. The study shows that numerical prediction of vortical flows is highly sensitive to the local grid resolution and that the implementation of grid adaptation is essential when applying CFD methods to such complicated flow problems.
A computational fluid dynamics (CFD) method has been employed to compute vortical flows around slender wing/body configurations. The emphasis of the paper is on the effectiveness of an adaptive grid procedure in "capturing" concentrated vortices generated at sharp edges or flow separation lines of lifting surfaces flying at high angles of attack. The method is based on a tetrahedral unstructured grid technology developed at the NASA Langley Research Center. Two steady-state, subsonic, inviscid and Navier-Stokes flow test cases are presented to demonstrate the applicability of the method for solving vortical flow problems. The first test case concerns vortex flow over a simple 65 delta wing with different values of leading-edge radius. Although the geometry is quite simple, it poses a challenging problem for computing vortices originating from blunt leading edges. The second case is that of a more complex fighter configuration. The superiority of the adapted solutions in capturing the vortex flow structure over the conventional unadapted results is demonstrated by comparisons with the wind-tunnel experimental data. The study shows that numerical prediction of vortical flows is highly sensitive to the local grid resolution and that the implementation of grid adaptation is essential when applying CFD methods to such complicated flow problems.
Polynomial chaos expansions (PCEs) are widely used for uncertainty quantification (UQ) tasks, particularly in the applied mathematics community. However, PCE has received comparatively less attention in the statistics literature, and fully Bayesian formulations remain rare—especially with implementations in R. Motivated by the success of adaptive Bayesian machine learning models such as BART, BASS and BPPR, we develop a new fully Bayesian adaptive PCE method with an efficient and accessible R implementation: khaos. Our approach includes a novel proposal distribution that enables data-driven interaction selection and supports a modified g-prior tailored to PCE structure. Through simulation studies and real-world UQ applications, we demonstrate that the Bayesian adaptive PCE provides competitive performance for surrogate modeling, global sensitivity analysis and ordinal regression tasks.
As zero-carbon electricity systems become the trend of future grid, the system inertia provided by conventional synchronous generators (SGs) keeps decreasing. The resultant lower system inertia will inevitably cause frequency stability problem, especially in the first few seconds following disturbance. To tackle this challenge, this paper proposes a frequency stability constraint for power systems unit commitment problem by considering the fast frequency responses (FFRs) from inverter-based resources (IBRs). Our developed frequency stability constraint is grounded on an analytical frequency nadir estimation framework that considers both SG and IBR dynamics. The accuracy of our frequency nadir estimation framework is validated by most severe N-1 contingency simulation result in a real island system. Then, the adaptive inertia frequency stability constraint is derived by performing sensitivity analysis with our frequency nadir estimation framework. Finally, we demonstrate the effectiveness of our developed frequency stability constraint with one year day-ahead unit commitment results of the island system.
Mass spectrometers have been included in the payloads of several deep space missions over the past three decades. Our laboratory has designed and developed mass spectrometers for the Galileo Probe into the atmosphere of Jupiter, the Pioneer Venus Orbiter, the Cassini Orbiter Mission to Saturn, the Cassini/Huygens Probe Mission to Saturn's moon Titan, the Nozomi Mission to Mars, and most recently the CONTOUR comet nucleus flyby mission. Each mission has required attention to miniaturization, autonomous sampling, and consideration of the special hazards and measurement requirements of the target environment. Development ongoing in our laboratory includes further miniaturization, improved performance in the areas of sensitivity and precision for the important isotope measurements, and adaptation for the unusual environments to be encountered in locations such as the surface or subsurface of Europa or Mars. Various aspects of both the technical implementation of these delivered and planned experiments and the science drivers will be described.
Several common defects that we have sought to minimize in immersing virtual environments are: static sensor spatial distortion, visual latency, and low update rates. Human performance within our environments during large amplitude 3D tracking was assessed by objective and subjective methods in the presence and absence of these defects. Results show that 1) removal of our relatively small spatial sensor distortion had minor effects on the tracking activity, 2) an Adapted Cooper-Harper controllability scale proved the most sensitive subjective indicator of the degradation of dynamic fidelity caused by increasing latency and decreasing frame rates, and 3) performance, as measured by normalized RMS tracking error or subjective impressions, was more markedly influenced by changing visual latency than by update rate.
Entry probes provide useful insights into the structures of planetary atmospheres, but give only one-dimensional pictures of complex four-dimensional systems that vary on all temporal and spatial scales. This makes the interpretation of the results quite challenging, especially as regards atmospheric dynamics. Here is a planetary meteorologist's vision of what the next generation of atmospheric entry probe missions should be: Dedicated sounding instruments get most of the required data from orbit. Relatively simple and inexpensive entry probes are released from the orbiter, with low entry velocities, to establish ground truth, to clarify the vertical structure, and for adaptive observations to enhance the dataset in preparation for sensitive operations. The data are assimilated onboard in real time. The products, being immediately available, are of immense benefit for scientific and operational purposes (aerobraking, aerocapture, accurate payload delivery via glider, ballooning missions, weather forecasts, etc.).
Key indoor air quality pollutant formaldehyde (H 2 CO) is tracked on International Space Station (ISS) using passive badges returned to the ground periodically for analysis. The process is time-consuming both in preparation and for analysis upon return 6-12 months later. Badges also require precious crew time for deploy, retrieval and stow. As NASA’s focus in space exploration shifts to the Moon and Mars, archival sample return becomes increasingly impractical, so the aim of this project is to develop a highly reliable real-time analyzer for H 2 CO at low concentrations with data downlinked. Potential sources of H 2 CO include materials off gassing, use of formalin as a tissue fixative in biological payloads and overheating of acetal polymers. The Spacecraft Maximum Allowable Concentration (SMAC) for H 2 CO in air is 100 ppb for exposures of 7 days or longer. ISS concentrations of H 2 CO are running only 10 - 30 ppb in the recent several years but have spiked as high as 60 ppb. Gateway real time monitoring requirements for H 2 CO call for a range of 8 - 138 ppb. For this project, a concentration range of 5 - 500 ppb H 2 CO is targeted. The core tunable diode laser spectroscopy (TDLS) technology used for this project was developed by Vista Photonics through the NASA and US Navy Small Business Innovation Research (SBIR) programs. Monitors based on TDLS have been demonstrated on ISS, trialed on a nuclear submarine and are being certified as portable Anomaly Gas Analyzers (AGA) for both ISS and Orion. Initially, direct absorption TDLS was used exclusively in these devices. The H 2 CO target concentration, however, is low ppb, and a longer wavelength is required, so a photoacoustic spectroscopy (PAS) technique was adapted, where the laser excitation is detected by a sensitive microphone vs. a conventional photodetector. This paper will discuss the results of NASA-JSC laboratory testing of a prototype PAS based formaldehyde in air monitor and briefly discuss next steps.
Cardiac muscle adapts well to changes in loading conditions. For example, left ventricular (LV) hypertrophy may be induced physiologically (via exercise training) or pathologically (via hypertension or valvular heart disease). If hypertension is treated, LV hypertrophy regresses, suggesting a sensitivity to LV work. However, whether physical inactivity in nonathletic populations causes adaptive changes in LV mass or even frank atrophy is not clear. We exposed previously sedentary men to 6 (n = 5) and 12 (n = 3) wk of horizontal bed rest. LV and right ventricular (RV) mass and end-diastolic volume were measured using cine magnetic resonance imaging (MRI) at 2, 6, and 12 wk of bed rest; five healthy men were also studied before and after at least 6 wk of routine daily activities as controls. In addition, four astronauts were exposed to the complete elimination of hydrostatic gradients during a spaceflight of 10 days. During bed rest, LV mass decreased by 8.0 +/- 2.2% (P = 0.005) after 6 wk with an additional atrophy of 7.6 +/- 2.3% in the subjects who remained in bed for 12 wk; there was no change in LV mass for the control subjects (153.0 +/- 12.2 vs. 153.4 +/- 12.1 g, P = 0.81). Mean wall thickness decreased (4 +/- 2.5%, P = 0.01) after 6 wk of bed rest associated with the decrease in LV mass, suggesting a physiological remodeling with respect to altered load. LV end-diastolic volume decreased by 14 +/- 1.7% (P = 0.002) after 2 wk of bed rest and changed minimally thereafter. After 6 wk of bed rest, RV free wall mass decreased by 10 +/- 2.7% (P = 0.06) and RV end-diastolic volume by 16 +/- 7.9% (P = 0.06). After spaceflight, LV mass decreased by 12 +/- 6.9% (P = 0.07). In conclusion, cardiac atrophy occurs during prolonged (6 wk) horizontal bed rest and may also occur after short-term spaceflight. We suggest that cardiac atrophy is due to a physiological adaptation to reduced myocardial load and work in real or simulated microgravity and demonstrates the plasticity of cardiac muscle under different loading conditions.
Plants benefit from their close association with soil microbes which assist in their response to abiotic and biotic stressors. Yet much of what we know about plant stress responses is based on studies where the microbial partners were uncontrolled and unknown. Under climate change, the soil microbial community will also be sensitive to and respond to abiotic and biotic stressors. Thus, facilitating plant adaptation to climate change will require a systems-based approach that accounts for the multi-dimensional nature of plant–microbe–environment interactions. In this perspective, we highlight some of the key factors influencing plant–microbe interactions under stress as well as new tools to facilitate the controlled study of their molecular complexity, such as fabricated ecosystems and synthetic communities. When paired with genomic and biochemical methods, these tools provide researchers with more precision, reproducibility, and manipulability for exploring plant–microbe–environment interactions under a changing climate.
Are the oceans turning into deserts? Rising temperature, increasing surface stratification, and decreasing vertical inputs of nutrients are expected to cause an expansion of warm, nutrient deplete ecosystems. Such an expansion is predicted to negatively affect a trio of key ocean biogeochemical features: phytoplankton biomass, primary productivity, and carbon export. However, phytoplankton communities are complex adaptive systems with immense diversity that could render them at least partially resilient to global changes. This can be illustrated by the biology of the Prochlorococcus “collective.” Adaptations to counter stress, use of alternative nutrient sources, and frugal resource allocation can allow Prochlorococcus to buffer climate-driven changes in nutrient availability. In contrast, cell physiology is more sensitive to temperature changes. We argue that biogeochemical models need to consider the adaptive potential of diverse phytoplankton communities. However, a full understanding of phytoplankton resilience to future ocean changes is hampered by a lack of global biogeographic observations to test theories. We propose that the resilience may in fact be greater in oligotrophic waters than currently considered with implications for future predictions of phytoplankton biomass, primary productivity, and carbon export.
An adaptive buddy check algorithm is presented that adjusts tolerances for outlier observations based on the variability of surrounding data. The algorithm derives from a statistical hypothesis test combined with maximum-likelihood covariance estimation. Its stability is shown to depend on the initial identification of outliers by a simple background check. The adaptive feature ensures that the final quality control decisions are not very sensitive to prescribed statistics of first-guess and observation errors, nor on other approximations introduced into the algorithm. The implementation of the algorithm in a global atmospheric data assimilation is described. Its performance is contrasted with that of a non-adaptive buddy check, for the surface analysis of an extreme storm that took place in Europe on 27 December 1999. The adaptive algorithm allowed the inclusion of many important observations that differed greatly from the first guess and that would have been excluded on the basis of prescribed statistics. The analysis of the storm development was much improved as a result of these additional observations.