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At least 73 records · Page 4

Application of acute maximal exercise to protect orthostatic tolerance after simulated microgravity

We tested the hypothesis that one bout of maximal exercise performed at the conclusion of prolonged simulated microgravity would improve blood pressure stability during an orthostatic challenge. Heart rate (HR), mean arterial blood pressure (MAP), norepinephrine (NE), epinephrine (E), arginine vasopressin (AVP), plasma renin activity (PRA), atrial natriuretic peptide (ANP), cardiac output (Q), forearm vascular resistance (FVR), and changes in leg volume were measured during lower body negative pressure (LBNP) to presyncope in seven subjects immediately prior to reambulation from 16 days of 6 degrees head-down tilt (HDT) under two experimental conditions: 1) after maximal supine cycle ergometry performed 24 h before returning to the upright posture (exercise) and 2) without exercise (control). After HDT, the reduction of LBNP tolerance time from pre-HDT levels was greater (P = 0.041) in the control condition (-2.0 +/- 0.2 min) compared with the exercise condition (-0.4 +/- 0.2 min). At presyncope after HDT, FVR and NE were higher (P < 0.05) after exercise compared with control, whereas MAP, HR, E, AVP, PRA, ANP, and leg volume were similar in both conditions. Plasma volume (PV) and carotid-cardiac baroreflex sensitivity were reduced after control HDT, but were restored by the exercise treatment. Maintenance of orthostatic tolerance by application of acute intense exercise after 16 days of simulated microgravity was associated with greater circulating levels of NE, vasoconstriction, Q, baroreflex sensitivity, and PV.

NASA Discipline Cardiopulmonary

Response of slow and fast muscle to hypothyroidism: maximal shortening velocity and myosin isoforms

This study examined both the shortening velocity and myosin isoform distribution of slow- (soleus) and fast-twitch (plantaris) skeletal muscles under hypothyroid conditions. Adult female Sprague-Dawley rats were randomly assigned to one of two groups: control (n = 7) or hypothyroid (n = 7). In both muscles, the relative contents of native slow myosin (SM) and type I myosin heavy chain (MHC) increased in response to the hypothyroid treatment. The effects were such that the hypothyroid soleus muscle expressed only the native SM and type I MHC isoforms while repressing native intermediate myosin and type IIA MHC. In the plantaris, the relative content of native SM and type I MHC isoforms increased from 5 to 13% and from 4 to 10% of the total myosin pool, respectively. Maximal shortening velocity of the soleus and plantaris as measured by the slack test decreased by 32 and 19%, respectively, in response to hypothyroidism. In contrast, maximal shortening velocity as estimated by force-velocity data decreased only in the soleus (-19%). No significant change was observed for the plantaris.

Non-NASA Center

Skeletal muscle fiber type composition and performance during repeated bouts of maximal, concentric contractions

Force output and fatigue and recovery patterns were studied during intermittent short-term exercise. 27 men performed three bouts of 30 maximal unilateral knee extensions on 2 different occasions. Blood flow was maintained or occluded during recovery periods (60 s). Blood flow was restricted by inflating a pneumatic cuff placed around the proximal thigh. Muscle biopsies from vastus lateralis were analyzed for identification of fast twitch (FT) and slow twitch (ST) fibers and relative FT area. Peak torque decreased during each bout of exercise and more when blood flow was restricted during recovery. Initial peak torque (IPT) and average peak torque (APT) decreased over the three exercise bouts. This response was 3 fold greater without than with blood flow during recovery. IPT and APT decreased more in individuals with mainly FT fibers than in those with mainly ST fibers. It is suggested that performance during repeated bouts of maximal concentric contractions differs between individuals with different fiber type composition. Specifically, in high intensity, intermittent exercise with emphasis on anaerobic energy release a high FT composition may not necessarily be advantageous for performance.

Muscle Contraction

Coding for Parallel Links to Maximize the Expected Value of Decodable Messages

When multiple parallel communication links are available, it is useful to consider link-utilization strategies that provide tradeoffs between reliability and throughput. Interesting cases arise when there are three or more available links. Under the model considered, the links have known probabilities of being in working order, and each link has a known capacity. The sender has a number of messages to send to the receiver. Each message has a size and a value (i.e., a worth or priority). Messages may be divided into pieces arbitrarily, and the value of each piece is proportional to its size. The goal is to choose combinations of messages to send on the links so that the expected value of the messages decodable by the receiver is maximized. There are three parts to the innovation: (1) Applying coding to parallel links under the model; (2) Linear programming formulation for finding the optimal combinations of messages to send on the links; and (3) Algorithms for assisting in finding feasible combinations of messages, as support for the linear programming formulation. There are similarities between this innovation and methods developed in the field of network coding. However, network coding has generally been concerned with either maximizing throughput in a fixed network, or robust communication of a fixed volume of data. In contrast, under this model, the throughput is expected to vary depending on the state of the network. Examples of error-correcting codes that are useful under this model but which are not needed under previous models have been found. This model can represent either a one-shot communication attempt, or a stream of communications. Under the one-shot model, message sizes and link capacities are quantities of information (e.g., measured in bits), while under the communications stream model, message sizes and link capacities are information rates (e.g., measured in bits/second). This work has the potential to increase the value of data returned from spacecraft under certain conditions.

Klimesh, Matthew A.

Improving the Accuracy of Predicting Maximal Oxygen Consumption (VO2pk)

Maximal oxygen (VO2pk) is the maximum amount of oxygen that the body can use during intense exercise and is used for benchmarking endurance exercise capacity. The most accurate method to determineVO2pk requires continuous measurements of ventilation and gas exchange during an exercise test to maximal effort, which necessitates expensive equipment, a trained staff, and time to set-up the equipment. For astronauts, accurate VO2pk measures are important to assess mission critical task performance capabilities and to prescribe exercise intensities to optimize performance. Currently, astronauts perform submaximal exercise tests during flight to predict VO2pk; however, while submaximal VO2pk prediction equations provide reliable estimates of mean VO2pk for populations, they can be unacceptably inaccurate for a given individual. The error in current predictions and logistical limitations of measuring VO2pk, particularly during spaceflight, highlights the need for improved estimation methods.

Downs, Meghan E.

Gate Drive Technology Evaluation and Development to Maximize Switching Speed of SiC Discrete Devices and Power Modules in Hard Switching Applications

To understand the limitation of maximizing the switching speed of SiC low current discrete devices and high current power modules in hard switching applications, double pulse tests are conducted and the testing results are analyzed. For power modules, the switching speed is generally limited by the parasitics rather than the gate drive capability. For the discrete SiC device, the conventional voltage source gate drive (VSG) is not sufficient to maximize the switching speed even if the external gate resistance is minimized. The limitation of existing current source gate drives (CSG) are analyzed, and a CSG dedicated for SiC discrete devices is proposed, which can provide constant current during the switching transient regardless of the high Miller voltage and large internal gate resistance. Compared with the conventional VSG, the proposed CSG achieves 67% faster turnon time and 50% turn-off time, and 68% reduction in switching loss at full load condition.

Handong Gui

The PIAA-Vortex Coronagraph: A New Coronagraph Technology to Maximize Exo-Earth Yields in the Astro2020 Era

Detecting and characterizing the atmospheres of terrestrial exoplanets is a main goal of the IR/O/UV flagship mission recommended by the Astro2020 Report. Achieving this goal depends critically on developing coronagraph technology that maximizes the potential number of terrestrial exoplanets we predict we can characterize, i.e. the exoEarth yield. Stringent constraints on low-order aberration sensitivity, inner working angle, and throughput as a function of telescope pupil complexity have been one of the main limiting factors affecting the yield of coronagraphs, and is a driving factor for telescope design considerations such as whether to use an off-axis or on-axis architecture. We present a hybrid PIAA-Vortex coronagraph concept that relaxes many of these constraints, and makes on-axis telescopes with centrally obstructed pupils a viable region of the design trade-space for the IR/O/UV flagship. Using the LUVOIR-A pupil as a baseline to design around, we present a coronagraph architecture with a small, ~2.5 lambda/D working angle that is insensitive to tip/tilt aberrations and stellar angular diameters on the order of 0.1 lambda/D. Pupil-plane apodization is achieved with PIAA-style mirror apodizations we obtain using a formalism we have developed to simultaneously optimize the contrast and low-order aberration sensitivity of coronagraphs designed for arbitrary telescope pupils and dark-hole geometries. By using PIAA to apodize in the pupil plane, the PIAA-Vortex coronagraph mitigates the trade-off between planet throughput, IWA, and aberration sensitivity, resulting in significantly higher yields for coronagraphs on obstructed pupils and new opportunities to maximize our ability to detect biomarkers in the Astro2020 era.

Kevin Fogarty

Debiasing Watermarks for Large Language Models via Maximal Coupling

Watermarking language models is essential for distinguishing between human and machine-generated text and thus maintaining the integrity and trustworthiness of digital communication. Here, we present a novel green/red list watermarking approach that partitions the token set into “green” and “red” lists, subtly increasing the generation probability for green tokens. To correct token distribution bias, our method employs maximal coupling, using a uniform coin flip to decide whether to apply bias correction, with the result embedded as a pseudorandom watermark signal. Theoretical analysis confirms this approach’s unbiased nature and robust detection capabilities. Experimental results show that it outperforms prior techniques by preserving text quality while maintaining high detectability, and it demonstrates resilience to targeted modifications aimed at improving text quality. This research provides a promising watermarking solution for language models, balancing effective detection with minimal impact on text quality.

97 MATHEMATICS AND COMPUTING

A Joinable Undercarriage to Maximize Payload (JUMP) Lunar Lander for Cargo Delivery to the Lunar Surface

Currently, NASA has engaged industry to develop a series of small to medium capacity landers with payload capacities of up to 5-9 tons by the mid to late 2020s. This contrasts with the former Constellation program, where the Altair lunar lander was targeting a payload capability of roughly 14-20 tons. Investment in smaller landers may present future challenges in delivering habitat modules larger than lunar lander cabins or small logistics modules to the lunar surface. Additionally, given a projected SLS flight rate of 1-2 launches per year, a lunar surface buildup from small elements seems problematic at best. While commercial launchers provide a supplement to SLS, many of the current and projected launch vehicles deliver less than 20 tons to a Trans-Lunar Injection – even fewer to the lunar surface. However, a possible solution could emerge if the lander itself could be launched in pieces with a buildup in Cislunar space. Thus, launchers with these capacities could contribute to a lunar lander capable of delivering 30 tons or more to the lunar surface. This paper introduces the notional concept of a Joinable Undercarriage to Maximized Payload (JUMP) lander. Key elements of a proposed JUMP lander concept will be discussed, followed by recommendations and forward work.

Human spaceflight

Floatable Protective Layers: a Strategy to Minimize Solid Electrolyte Interphase Growth and Maximize the Lithium Utilization

Abstract Maximizing lithium (Li) utilization is crucial for enhancing the long‐term stability of Li‐based batteries. In anode‐free Li batteries (AFLBs), although the initial formation of solid electrolyte interphase (SEI) is beneficial on limiting further reaction between Li and electrolyte, large volume change of Li metal anode (LMA) during cycling often leads to continuous breakdown and re‐formation of SEI and formation of inactive Li, hindering its efficiency. In this study, a novel strategy is presented to protect Li metal by applying a floatable protection layer (FPL) on a copper substrate, enabling large Li particles to be primarily deposited below FPL, but SEI to be primarily formed above FPL. This approach effectively minimizes the direct contact between electrolyte and freshly deposited Li, therefore mitigating the continuous side reactions and early failure of AFLBs. As a result, Li consumption is minimized, and the overall stability of the battery is significantly enhanced. Further development of this approach can also be used to improve the performance of other Li‐based batteries for large‐scale applications.

Lim, Hyung‐Seok [Energy and Environment Directorat

Implementing the finite-volume three-pion scattering formalism across all non-maximal isospins

We present a numerical exploration of the relativistic-field-theory (RFT) formalism for three pions with all possible values of non-maximal isospin, I πππ = 2, 1 and 0. Using the generic-isospin extension of the RFT formalism [1] and applying our open-source Python library to implement the framework, we predict a range of three-pion energies for illustrative values of the two-to-two scattering amplitudes for various finite-volume irreps also with non-zero total momentum P in the finite-volume frame. The results restrict attention to the case of a vanishing intrinsic three-body interaction so that the spectra can be understood as a baseline. In future lattice QCD calculations, deviations from these values will be translated into evidence for intrinsic three-body effects in the various scattering channels.

hadronic spectroscopy

CMPLE: Correlation Modeling to Decode Photosynthesis Using the Minorize–Maximize Algorithm

In plant genomic experiments, correlations among various biological traits (phenotypes) give new insights into how genetic diversity may have tuned biological processes to enhance fitness under diverse conditions. Consequently, knowing how the correlations are affected by genetic (G) and environmental (E) factors helps develop climate-resilient plants. However, the current literature lacks any method for assessing the effect of predictors on pairwise correlations among multiple phenotypes together with easily interpretable model parameters. To address this need, we propose to model pairwise correlations directly in terms of G and E and develop a computationally efficient inference procedure. Two major novelties in our methodology are (1) the use of a composite pairwise likelihood method to avoid the positive definiteness restriction on the correlation matrix and (2) the use of a novel Minorize–Maximize (MM) algorithm for the efficient estimation of a large number of parameters. The proposed method shows excellent numerical performance on synthetic datasets. Here, the analysis of the motivating data on cowpea reveals that the rates of solar energy storage by photosynthesis (the aggregate trait) are differentially affected by different genetic loci through two distinct processes: “photoinhibition” which results from photodamage caused by excess light, and “photoprotection” which protects plants from photodamage but also results in energy loss.

Correlation modeling

Design and optimization of a modular hydrogen-based integrated energy system to maximize revenue via nuclear-renewable sources

Here, this paper demonstrates a novel modular distributed framework that uses optimal energy-dispatching strategies to enable greater flexibility and profitability in nuclear-renewable integrated energy systems (NR-IES). Hydrogen is used as a commodity in this framework since its production can improve grid stability and system operational flexibility, decarbonize heavy industry, and create an additional revenue stream for electricity generators, particularly nuclear power plants with high operational expenses. The proposed solution addresses the challenges associated with merging multiple software and services from various domains by using functional mock-up units (FMU) to co-simulate diverse subsystems designed in various platforms. The tightly coupled integrated energy system (IES) is optimized to maximize revenue by utilizing the deep reinforcement learning (DRL) technique to make smart dispatching decisions based on variable electricity prices and the availability of renewable energy. Proximal policy optimization (PPO) algorithm is used in training and testing the DRL agent. Over a period of 120 days, the proposed hydrogen-based IES framework showed about 10% revenue boost compared to a non-hydrogen generating baseline IES while also providing an easily-adoptable framework which can help to improve the flexibility of future generation nuclear power plants.

29 ENERGY PLANNING, POLICY, AND ECONOMY

Maximizing efficiency of dataset compression for machine learning potentials with information theory

Machine learning interatomic potentials (MLIPs) balance high accuracy and lower costs compared to density functional theory calculations, but their performance often depends on the size and diversity of training datasets. Large datasets improve model accuracy and generalization but are computationally expensive to produce and train on, while smaller datasets risk discarding rare but important atomic environments and compromising MLIP accuracy/reliability. Here, we develop an information-theoretical framework to quantify the efficiency of dataset compression methods and propose an algorithm that maximizes this efficiency. By framing atomistic dataset compression as an instance of the minimum set cover (MSC) problem over atom-centered environments, our method identifies the smallest subset of structures that contains as much information as possible from the original dataset while pruning redundant information. The approach is extensively demonstrated on the GAP-20 and TM23 datasets and validated on 64 varied datasets from the ColabFit repository. Across all cases, MSC consistently retains outliers, preserves dataset diversity, and reproduces the long-tail distributions of forces even at high compression rates, outperforming other subsampling methods. Furthermore, MLIPs trained on MSC-compressed datasets exhibit reduced error for out-of-distribution data even in low-data regimes. We explain these results using an outlier analysis and show that such quantitative conclusions could not be achieved with conventional dimensionality reduction methods. The algorithm is implemented in the open-source QUESTS package and can be used for several tasks in atomistic modeling, from data subsampling, outlier detection, and training improved MLIPs at a lower cost.

36 MATERIALS SCIENCE

Small-𝑥 behavior in QCD from maximal entanglement and conformal invariance

Recent evidence suggests that, at small Bjorken 𝑥, QCD evolution drives the proton into a state of maximal entanglement. If the evolution kernel is assumed to be conformally invariant—as is the case for the Balitsky-Fadin-Kuraev-Lipatov equation—we can describe it by a conformal field theory. Moreover, the central charge 𝑐 of the corresponding conformal field theory emerges as the key parameter governing the 𝑥 dependence of both the entanglement entropy and the structure function. Here we apply the exact Bethe ansatz methods to the quantum spin chain dual to Lipatov’s high energy effective action to extract the central charge of the theory, and find that 𝑐 = 1. This implies the ∼𝑥 −1/3 small 𝑥 behavior for the structure function—the prediction that can be tested at the forthcoming Electron-Ion Collider.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

Celestial Dual for Maximal Helicity Violating Amplitudes

It is shown that a 2D conformal field theory consisting of a central charge c Liouville theory, a chiral level one, rank N Kac-Moody algebra, and a weight − 3 / 2 free fermion holographically generate 4D maximal helicity violating tree-level scattering amplitudes. The correlators of this 2D conformal field theory give directly the 4D leaf amplitudes associated to a single hyperbolic slice of flat space. The 4D celestial amplitudes arise in a large- N and semiclassical large- c limit, according to the holographic dictionary, as a translationally invariant combination of leaf amplitudes. A step in the demonstration is showing that the semiclassical limit of Liouville correlators are given by contact 3D anti–de Sitter Witten diagrams. Published by the American Physical Society 2024

Physics

Network-Aware and Welfare-Maximizing Dynamic Pricing for Energy Sharing

The proliferation of behind-the-meter (BTM) distributed energy resources (DER) within the electrical distribution network presents significant supply and demand flexibilities, but also introduces operational challenges such as voltage spikes and reverse power flows. In response, this paper proposes a network-aware dynamic pricing framework tailored for energy-sharing coalitions that aggregate small, but ubiquitous, BTM DER downstream of a distribution system operator's (DSO) revenue meter that adopts a generic net energy metering (NEM) tariff. By formulating a Stackelberg game between the energy-sharing market leader and its prosumers, we show that the dynamic pricing policy induces the prosumers toward a network-safe operation and decentrally maximizes the energysharing social welfare. The dynamic pricing mechanism involves a combination of a locational ex-ante dynamic price and an ex-post allocation, both of which are functions of the energy sharing's BTM DER. The ex-post allocation is proportionate to the price differential between the DSO NEM price and the energy-sharing locational price. Simulation results using real DER data and the IEEE 13-bus test systems illustrate the dynamic nature of network-aware pricing at each bus, and its impact on voltage.

aggregates

How Much Reserve Fuel: Quantifying the Maximal Energy Cost of System Disturbances

Motivated by the design question of additional fuel needed to complete a task in an uncertain environment, this paper introduces metrics to quantify the maximal additional energy used by a control system in the presence of bounded disturbances, compared to a nominal, disturbance-free system. In particular, we consider the task of finite-time stabilization for a linear, time-invariant system. We compare the nominal energy required to achieve this task in the disturbance-free system to the worst-case energy over all feasible disturbances. Solving for the worst-case energy over all disturbances first leads to an optimal control problem with a least-squares solution, and then an infinite-dimensional optimization problem where we derive an upper bound on the solution. The comparison of energies is accomplished using additive and multiplicative metrics, for which we derive bounds. Simulation examples on an ADMIRE fighter jet model demonstrate the practicability of these metrics, and their variation with the distance of the initial condition from the origin and the task completion time.

koopman operator, resilience