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NASA NTRS2014

Improving Sensorimotor Adaptation Following Long Duration Space Flight by Enhancing Vestibular Information Transfer

Crewmember adapted to the microgravity state may need to egress the vehicle within a few minutes for safety and operational reasons after gravitational transitions. The transition from one sensorimotor state to another consists of two main mechanisms: strategic and plastic-adaptive and have been demonstrated in astronauts returning after long duration space flight. Strategic modifications represent "early adaptation" - immediate and transitory changes in control that are employed to deal with short-term changes in the environment. If these modifications are prolonged then plastic-adaptive changes are evoked that modify central nervous system function, automating new behavioral responses. More importantly, this longer term adaptive recovery mechanism was significantly associated with their strategic ability to recover on the first day after return to Earth G. We are developing a method based on stochastic resonance to enhance information transfer by improving the brain's ability to detect vestibular signals (Vestibular Stochastic Resonance, VSR) especially when combined with balance training exercises such as sensorimotor adaptability (SA) training for rapid improvement in functional skill, for standing and mobility. This countermeasure to improve detection of vestibular signals is a stimulus delivery system that is wearable/portable providing low imperceptible levels of white noise based binaural bipolar electrical stimulation of the vestibular system (stochastic vestibular stimulation). To determine efficacy of vestibular stimulation on physiological and perceptual responses during otolith-canal conflicts and dynamic perturbations we have conducted a series of studies: We have shown that imperceptible binaural bipolar electrical stimulation of the vestibular system across the mastoids enhances balance performance in the mediolateral (ML) plane while standing on an unstable surface. We have followed up on the previous study showing VSR stimulation improved balance performance in both ML and anteroposterior planes while stimulating in the ML axis only. We have shown the efficacy of VSR stimulations on enhancing physiological and perceptual responses of whole-body orientation during low frequency perturbations (0.1 Hz) on the ocular motor system using a variable radius centrifuge on both physiological (using eye movements) and perceptual responses (using a joystick) to track imposed oscillations. The variable radius centrifuge provides a selective tilting sensation that is detectable only by the otolith organs providing conflicting information from the canal organs of the vestibular system (intra-vestibular conflict). These results indicate that VSR can improve performance in sensory conflict scenarios like that experienced during space flight. We have showed the efficacy of VSR stimulation to improve balance and locomotor control on subjects exposed to continuous, sinusoidal lateral motion of the support surface while walking on a treadmill while viewing perceptually matched linear optic flow. We have shown the safety of short term continuous use of up to 4 hours of VSR stimulation and its efficacy in improving balance and locomotor function in Parkinson's Disease patients. This technique for improving vestibular signal detection may thus provide additional information to improve strategic abilities. We hypothesize that VSR stimulation will act synergistically with SA training to improve adaptability by increased utilization of vestibular information and therefore serve to optimize and personalize the SA countermeasure prescription. This forms the basis of its usefulness both as a training modality and further help in significantly reducing the number of days required to recover functional performance to preflight levels after long duration space flight.

Mulavara, A. P.↗

NASA NTRS2014

Using Tests Designed to Measure Individual Sensorimotor Subsystem Perfomance to Predict Locomotor Adaptability

Astronauts experience sensorimotor disturbances during the initial exposure to microgravity and during the readapation phase following a return to a gravitational environment. These alterations may lead to disruption in the ability to perform mission critical functions during and after these gravitational transitions. Astronauts show significant inter-subject variation in adaptive capability following gravitational transitions. The way each individual's brain synthesizes the available visual, vestibular and somatosensory information is likely the basis for much of the variation. Identifying the presence of biases in each person's use of information available from these sensorimotor subsystems and relating it to their ability to adapt to a novel locomotor task will allow us to customize a training program designed to enhance sensorimotor adaptability. Eight tests are being used to measure sensorimotor subsystem performance. Three of these use measures of body sway to characterize balance during varying sensorimotor challenges. The effect of vision is assessed by repeating conditions with eyes open and eyes closed. Standing on foam, or on a support surface that pitches to maintain a constant ankle angle provide somatosensory challenges. Information from the vestibular system is isolated when vision is removed and the support surface is compromised, and it is challenged when the tasks are done while the head is in motion. The integration and dominance of visual information is assessed in three additional tests. The Rod & Frame Test measures the degree to which a subject's perception of the visual vertical is affected by the orientation of a tilted frame in the periphery. Locomotor visual dependence is determined by assessing how much an oscillating virtual visual world affects a treadmill-walking subject. In the third of the visual manipulation tests, subjects walk an obstacle course while wearing up-down reversing prisms. The two remaining tests include direct measures of knee and ankle proprioception and a functional movement assessment that screens for movement restrictions and asymmetries. To assess each subject's locomotor adaptability subjects walk for twenty minutes on a treadmill that oscillates laterally at 0.3 Hz. Throughout the test metabolic cost provides a measure of exertion and step frequency provides a measure of stability. Additionally, at four points during the perturbation period, reaction time tests are used to probe changes in the amount of mental effort being used to perform the task. As with the adaptive capability observed in astronauts during gravitational transitions, our data shows significant variability between subjects. To aid in the analysis of the results, custom software tools have been developed to enhance in the visualization of the large number of output variables. Preliminary analyses of the data collected to date do not show a strong relationship between adaptability and any single predictor variable. Analysis continues to identify a multifactorial predictor outcome "signature" that do inform us of locomotor adaptability.

Peters, B. T.↗

NASA NTRS2015

Virtual Reality as a Medium for Sensorimotor Adaptation Training and Spaceflight Countermeasures

With the upcoming shift to extra‐long duration missions (1 year) aboard the ISS, sensorimotor adaptations during transitory periods in‐and‐out of microgravity are more important to understand and prepare for. Advances in virtual reality technology enables everyday adoption of these tools for entertainment and use in training. Experiencing virtual environments (VE) allows for the manipulation of visual flow to elicit automatic motor behavior and produce sensorimotor adaptation (SA). Recently, the ability to train individuals using repeatable and varied exposures to SA challenges has shown success by improving performance during exposure to a novel environment (Batson 2011). This capacity to 'learn to learn' is referred to as sensorimotor adaptive generalizability and, through the use of treadmill training, represents an untapped potential for individualized countermeasures. The goal of this study is to determine the feasibility of present head mounted displays (HMDs) to produce compelling visual flow information and the expected adaptations for use in future SA treadmill‐based countermeasures. Participants experience infinite hallways providing congruent (baseline) or incongruent visual information (half or double speed) via HMD while walking on an instrumented treadmill at 1.1m/s. As gait performance approaches baseline levels, an adaptation time constant is derived to establish individual time‐to‐adapt (TTA). It is hypothesized that decreasing the TTA through SA treadmill training will facilitate sensorimotor adaptation during gravitational transitions. In this way, HMD technology represents a novel platform for SA training using off‐the‐shelf consumer products for greater training flexibility in astronaut and terrestrial applications alike.

Madansingh, S.↗

NASA NTRS2016

Developing Personalized Sensorimotor Adaptability Countermeasures for Spaceflight

Astronauts experience sensorimotor disturbances during their initial exposure to microgravity and during the re-adaptation phase following a return to an Earth-gravitational environment. Interestingly, astronauts who return from spaceflight show substantial differences in their abilities to readapt to a gravitational environment. The ability to predict the manner and degree to which individual astronauts would be affected would improve the effectiveness of countermeasure training programs designed to enhance sensorimotor adaptability. In this paper we will be presenting results from our ground-based study that show how behavioral, brain imaging and genomic data may be used to predict individual differences in sensorimotor adaptability to novel sensorimotor environments. This approach will allow us to better design and implement sensorimotor adaptability training countermeasures against decrements in post-mission adaptive capability that are customized for each crewmember's sensory biases, adaptive capacity, brain structure, functional capacities, and genetic predispositions. The ability to customize adaptability training will allow more efficient use of crew time during training and will optimize training prescriptions for astronauts to ensure expected outcomes.

Mulavara, A. P.↗

NASA NTRS2019

Global Response Patterns of Major Rainfed Crops to Adaptation by Maintaining Current Growing Periods and Irrigation

Increasing temperature trends are expected to impact yields of major field crops by affecting various plant processes, such as phenology, growth, and evapotranspiration. However, future projections typically do not consider the effects of agronomic adaptation in farming practices. We use an ensemble of seven Global Gridded Crop Models to quantify the impacts and adaptation potential of field crops under increasing temperature up to 6 K, accounting for model uncertainty. We find that without adaptation, the dominant effect of temperature increase is to shorten the growing period and to reduce grain yields and production. We then test the potential of two agronomic measures to combat warming-induced yield reduction: (i) use of cultivars with adjusted phenology to regain the reference growing period duration and (ii) conversion of rainfed systems to irrigated ones in order to alleviate the negative temperature effects that are mediated by crop evapotranspiration. We find that cultivar adaptation can fully compensate global production losses up to 2 K of temperature increase, with larger potentials in continental and temperate regions. Irrigation could also compensate production losses, but its potential is highest in arid regions, where irrigation expansion would be constrained by water scarcity. Moreover, we discuss that irrigation is not a true adaptation measure but rather an intensification strategy, as it equally increases production under any temperature level. In the tropics, even when introducing both adapted cultivars and irrigation, crop production declines already at moderate warming, making adaptation particularly challenging in these areas.

Minoli, Sara↗

NASA NTRS2020

Adaptive Hexapod Simulator Motion Based on Aircraft Stability

This paper determined the feasibility of an adaptive hexapod simulator motion algorithm based on aircraft roll stability. An experiment was conducted that used a transport aircraft model in the Vertical Motion Simulator at NASA Ames Research Center. Eighteen general aviation pilots flew a heading-capture task and a stall task consecutively under four motion configurations: baseline hexapod, adaptive hexapod, optimized hexapod, and full motion. The adaptive motion was more similar to the baseline hexapod motion in the heading-capture task when the aircraft was more stable, and more similar to the optimized hexapod motion in the stall task when the aircraft was more unstable. Pilot motion ratings and task performance in the heading-capture task under the adaptive hexapod motion were more similar to baseline hexapod motion compared to optimized hexapod motion. However, motion ratings and task performance in the stall task under the adaptive motion were not significantly more similar to the optimized hexapod motion compared to baseline hexapod motion. Motion ratings and overall task performance under optimized hexapod motion as opposed to baseline hexapod motion were always more similar to the full motion condition. This paper showed that adaptive motion based on aircraft stability is feasible and can be implemented in a straightforward way. More research is required to test the adaptive motion algorithm in different tasks.

Zaal, Peter M. T.↗

NASA NTRS2020

Verification of Anisotropic Mesh Adaptation for Turbulent Simulations over ONERA M6 Wing

Unstructured anisotropic mesh adaptation is known to be an efficient way to control discretization errors in Computational Fluid Dynamics (CFD) simulations. Method verification is required to provide the confidence for routine use in production analysis. The current work aims at verification of anisotropic mesh adaptation for RANS simulations over the ONERA M6 wing. The present verification study is performed using four different flow solvers, three different implementations of the metric field, and three mesh mechanics packages. Two of the flow solvers use stabilized finite-element discretizations (FUN3D-SFE and GGNS), one uses finite-volume discretization (FUN3D-FV), and the last one uses mixed finite-volume and finite element discretizations (Wolf). The mesh adaptation is based on an error estimator that aims to control the quadratic error term in the linear interpolation of Mach number. Two sets of adaptations were performed; the first one controls the interpolation error in L2 norm and the second one controls the interpolation error in L4 norm. Convergence studies were performed on the forces and the pitching moment using all four solvers, and the results are compared with previously verified convergence studies on fixed (nonadapted) meshes. Both forces and pitching moment on adapted meshes are found to be converging to the fine mesh values faster than those on fixed meshes. In addition to forces and moments, convergence of surface pressure and skin friction coefficients at various measurement locations on the wing are also presented. Adapted-mesh surface pressure distributions agree with the fine fixed mesh pressure distributions. Adapted-mesh skin friction distributions contain high frequency noise with mean values approaching the fixed mesh pressure skin friction distributions.

Aravind Balan↗

NASA NTRSDate not supplied

Automatic Boundary-Layer Adaptation of Structured Grids in VULCAN-CFD

In supersonic and hypersonic flow computations, well-resolved boundary layers are essential for accurate quantification of surface heating and transition prediction, particularly via linear stability analysis. Grid design for hypersonic flows with shocks, boundary-layer separation, and/or complex mean flow features incorporating spanwise/azimuthal inhomogeneities is a difficult issue. In comparison to a manual grid adaptation procedure, an autonomous grid adaptation technique offers significant improvements in computing time and solution quality. The VULCAN-CFD solver already includes a validated procedure for automatic adaption of structured grids to the bow shock. The present focus is on implementing an automatic boundary-layer adaptation capability in VULCAN-CFD that adapts structured, multiblock grids to both the bow shock and the boundary layer at the same time. The boundary-layer adaptation algorithm allows the user to specify the number of cells within the boundary layer, along with the input parameters used for detecting the edge of the boundary layer, namely, the variable used in the edge detection criterion,the edge detection method, the detection direction, and the relaxation factor used during the morphing of the grid. The algorithm automatically distributes grid points along the wall-normal direction to achieve a smooth variation in grid spacing from the edge of the boundary layer to a"junction" location within the outer part of the grid. Illustrative results are presented for three different high-speed configurations: the two-dimensional flow over a cylinder at Mach 17.6 and unit Reynolds number of Re=0.38x10^6 m^-1, the axisymmetric flow over a cone-cylinder-flare model at Mach 6.0 and Re = 10.5×10^6 m^-1, and the three-dimensional flow over a blunt, 7-degree half-angle cone at 5-degree angle of attack in a Mach 9.79 flow with Re = 17.1×10^6 m^-1. The automated boundary-layer adaptation is shown to provide an adequate grid topology that is aligned with the bow shock in the outer part of the grid and also resolves the viscous boundary-layer region close to the surface.

boundary layer transition↗

NASA NTRSDate not supplied

Effect of anisotropic mesh adaptation on surface pressure predictions for atmospheric entry simulations.

Recently, a metric-based mesh adaptation capability has been developed for the advanced compressible flow solver US3D. Metric-based mesh adaptation is a solution informed mesh adaptation strategy that typically improves the resolution of the mesh along anisotropic flow features, like strong shock waves or shear layers. An anisotropic error indicator is reconstructed based on a provided Computational Fluid Dynamics (CFD) solution which prescribes the locally desired element size and orientation. The benefits of this mesh adaptation strategy is twofold: first, it simplifies the manual meshing labor that typically needs to be carried out by the CFD engineer because the mesh adaptation is informed by the provided solution. Second, the computational cost is kept to a minimum while improving the resolution of the simulation. The aim here is to demonstrate how anisotropic mesh adaptation can be employed to improve the predictions of surface pressure for atmospheric entry vehicles. In this work, we compare CFD simulations that use this newly developed anisotropic mesh adaptation capability for US3D with pressure data that was collected by Mars Entry, Descent, and Landing Instrumentation 2 (MEDLI2) during the atmospheric entry phase of Mars2020.

D. Ekelschot↗

NASA NTRSDate not supplied

Effect of Anisotropic Mesh Adaptation on Surface Pressure Predictions for Atmospheric Entry Simulations

A metric-based mesh adaptation capability has been developed for the advanced compressible flow solver US3D. Metric-based mesh adaptation is a solution informed mesh adaptation strategy that improves the resolution of the mesh along anisotropic flow features, like strong shock waves or shear layers. An anisotropic error indicator is reconstructed based on a provided Computational Fluid Dynamics (CFD) solution which prescribes the locally desired element size and orientation. The benefits of this mesh adaptation strategy is twofold: first, it simplifies the manual meshing labor that typically needs to be carried out by the CFD engineer because the mesh adaptation is informed by the provided solution. Second, the computational cost is kept to a minimum while improving the resolution of the simulation. The aim here is to demonstrate how anisotropic mesh adaptation can be employed to improve the predictions of surface pressure for atmospheric entry vehicles. In this work, we compare CFD simulations that use this newly developed anisotropic mesh adaptation capability for US3D with pressure data that was collected by Mars Entry, Descent, and Landing Instrumentation (MEDLI2) suite.

Dirk Ekelschot↗

DOE OSTI2022

A business approach to climate adaptation in local communities

Climate change poses risks to the assets and operations of businesses. They can anticipate, prepare for, and adapt to the potential impacts of climate change by focusing on modifying their own internal operations. But businesses can find additional opportunities to adapt by examining their relationships with local governments. Businesses provide critical services to the communities in which they are located, and also benefit from services provided by the local governments. This symbiotic relationship is an important consideration for businesses as they work to adapt to a changing climate. By thinking broadly about how working with local governments can influence their resilience, businesses may be able to uncover additional adaptation opportunities and enhance their adaption efforts in ways they may not be able to achieve on their own. Here, this paper includes two case studies of businesses that pursued adaptation efforts with local, state, or federal government officials to provide real-world context for the symbiotic relationships that exist between the private and public sectors in communities.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Drought adaptation index (DAI) based on BLUP as a selection approach for drought-resilient switchgrass germplasm

This study introduces a Drought Adaptation Index (DAI), derived from Best Linear Unbiased Prediction (BLUP), as a method to assess drought resilience in switchgrass (Panicum virgatum L.). A panel of 404 genotypes was evaluated under drought-stressed (CV) and well-watered (UC) conditions over four consecutive years (2019–2022). BLUP-estimated biomass yields were used to calculate the DAI, which enabled classification of genotypes into four adaptation groups: very well-adapted, well-adapted, adapted, and unadapted. The DAI was compared with conventional drought tolerance indices, including the Stress Susceptibility Index (SSI), Stress Tolerance Index (STI), Geometric Mean Productivity (GMP), and Yield Stability Index (YSI). Correlation analyses demonstrated strong agreement between DAI and these indices, supporting its validity and consistency. Biplot analyses using the Genotype plus Genotype-by-Environment Interaction (GGE) and Additive Main Effects and Multiplicative Interaction (AMMI) models revealed significant genotype-by-environment interactions (GEI) and identified J222.A, J463.A, and J295.A. A as high-performing genotypes, with J222.A exhibiting greater yield stability across treatments and years. Additionally, DAI isoline curves provided a graphical representation of differential genotype performance under drought and control conditions. These visualizations aided in distinguishing genotypes with stable and superior biomass yield across contrasting environments. Overall, the BLUP-based DAI is a robust and practical selection tool that improves the accuracy of identifying drought-resilient, high-yielding switchgrass genotypes. Its integration into breeding programs offers a comprehensive framework for improving biomass productivity and stress adaptation under variable climatic conditions. The application of DAI supports the development of climate-resilient cultivars and contributes to sustainable bioenergy and forage production systems.

BLUP↗

DOE OSTI2025

Adaptive anomaly detection for identifying attacks in cyber-physical systems: A systematic literature review

Modern cyberattacks in cyber-physical systems (CPS) rapidly evolve and cannot be deterred effectively with most current methods, which focus on characterizing past threats. Adaptive anomaly detection (AAD) is among the most promising techniques to detect evolving cyberattacks, with an emphasis on fast data processing and model adaptation. AAD has been researched extensively; however, to the best of our knowledge, our work is the first systematic literature review (SLR) on current research in this field. We present a comprehensive SLR, gathering 397 relevant papers and systematically analyzing 65 of them (47 research and 18 survey papers) on AAD in CPS from 2013 to November 2023. We introduce a novel taxonomy considering attack types, CPS application, learning paradigm, data management, and algorithms. Our findings show that most studies addressed either model adaptation or data processing, but rarely both simultaneously. This indicates a research gap in fully adaptive solutions. We also categorize algorithms, datasets, and attack characteristics, and summarize strengths and weaknesses across the literature. Our review provides a structured and accessible reference for researchers and practitioners, offering insights into key trends and highlighting limitations in current approaches. Finally, we outline several future research directions, including the need for integrated real-time processing and adaptive learning, explainability, and uncertainty quantification in AAD for CPS.

Adaptation↗

DOE OSTI2019

Bio-Inspired adaptive damping in hydrokinetic energy harnessing using flow-induced oscillations

A hydrokinetic energy converter using Flow Induced Oscillations (FIOs) of a one-degree-of-freedom cylinder-oscillator, with nonlinear adaptive damping and linear spring stiffness, is introduced and studied experimentally. Comparison to a linear-oscillator in FIO shows that this new converter, with velocity-proportional damping coefficient, is more effective in galloping, where both flow and cylinder speeds are higher. It also impacts VIV, since the converter is no longer restricted by fixed damping, which results either in ceasing motion due to excessive damping, or in low harnessed energy due to insufficient damping. The impact is most profound in the VIV to galloping transition where adaptive damping prevents shutting down of hydrokinetic energy conversion. Damping-to-velocity rate, linear spring-stiffness, and flow-velocity are the experimental parameters with Reynolds number 30,000 ≤ Re ≤ 120,000. Here, experimental results for amplitude response, frequency response, energy harvesting, efficiency and instantaneous energy of the converter are presented and discussed. The main conclusions are: (1) The nonlinear, adaptive, velocity-proportional damping coefficient increases the harnessed power. (2) The operational range of flow velocities increases. (3) At lower flow speeds, the adaptive damping stabilizes the unstable oscillations typically occurring in this region. (4) At higher flow speeds, adaptive damping results in higher harnessed power than constant damping, thus, better emulating passively a corresponding, natural, active motion by fish. (5) Increase of 51%–95% in converted power by the nonlinear oscillator compared to linear oscillator has been measured. (6) The adaptive damping converter reaches a plateau in harnessed efficiency at high flow velocity (fully developed galloping).

13 HYDRO ENERGY↗

DOE OSTI2023

Physics-based adaptivity of a spectral method for the Vlasov–Poisson equations based on the asymmetrically-weighted Hermite expansion in velocity space

We propose a spectral method for the 1D-1V Vlasov–Poisson system where the discretization in velocity space is based on asymmetrically-weighted Hermite functions, dynamically adapted via a scaling α and shifting u of the velocity variable. Specifically, at each time instant an adaptivity criterion selects new values of α and u based on the numerical solution of the discrete Vlasov–Poisson system obtained at that time step. Once the new values of the Hermite parameters α and u are fixed, the Hermite expansion is updated and the discrete system is further evolved for the next time step. The procedure is applied iteratively over the desired temporal interval. The key aspects of the adaptive algorithm are: the map between approximation spaces associated with different values of the Hermite parameters that preserves total mass, momentum and energy; and the adaptivity criterion to update α and u based on physics considerations relating the Hermite parameters to the average velocity and temperature of each plasma species. For the discretization of the spatial coordinate, we rely on Fourier functions and use the implicit midpoint rule for time stepping. The resulting numerical method possesses intrinsically the property of fluid-kinetic coupling, where the low-order terms of the expansion are akin to the fluid moments of a macroscopic description of the plasma, while kinetic physics is retained by adding more spectral terms. Moreover, the scheme features conservation of total mass, momentum and energy associated in the discrete, for periodic boundary conditions. A set of numerical experiments confirms that the adaptive method outperforms the non-adaptive one in terms of accuracy and stability of the numerical solution.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

The contribution of the neuroendocrine system to adaption after repeated daily ozone exposure in rats

Ozone-induced lung injury/inflammation dissipates despite continued exposure for 3 or more days; however, the mechanisms of adaptation/habituation remain unclear. Since ozone effects are mediated through adrenal-derived stress hormones, which also regulate longevity of centrally-mediated stress response, we hypothesized that ozone-adaptation is linked to diminution of neuroendocrine stress-axes activation and glucocorticoid levels. Male Wistar-Kyoto-rats (12-week-old) were injected with vehicle or a therapeutically-relevant dexamethasone dose (0.01-mg/kg/day; intraperitoneal) for 1-month to determine if suppression of glucocorticoid signaling was linked to adaptation. Vehicle- and dexamethasone-treated rats were exposed to air or 0.8-ppm ozone, 4 h/day × 2 or 4 days to assess the impacts of acute exposure and adaptation, respectively. Dexamethasone reduced thymus and spleen weights, circulating lymphocytes, corticosterone and increased insulin. Ozone increased lavage-fluid protein and neutrophils and decreased circulating lymphocytes at day-2 but not day-4. Ozone-induced hyperglycemia, glucose intolerance and inhibition of beta-cell insulin release occurred at day-1 but not day-3. Ozone depleted circulating prolactin, thyroid-stimulating hormone, and luteinizing-hormone at day-2 but not day-4, suggesting central mediation of adaptation. Adrenal epinephrine biosynthesis gene, Pnmt, was up-regulated after ozone exposure at both timepoints. However, genes involved in glucocorticoid biosynthesis were up-regulated after day-2 but not day-4, suggesting that acute 1- or 2-day ozone-mediated glucocorticoid increase elicits feedback inhibition to dampen hypothalamic stimulation of ACTH release in response to repeated subsequent ozone exposures. Although dexamethasone pretreatment affected circulating insulin, lymphocytes and adrenal genes, it had modest effect on ozone adaptation. In conclusion, ozone adaptation likely involves lack of hypothalamic response due to reduced availability of circulating glucocorticoids.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

Quantitative comparison of adaptive sampling methods for protein dynamics

Adaptive sampling methods, often used in combination with Markov state models, are becoming increasingly popular for speeding up rare events in simulation such as molecular dynamics (MD) without biasing the system dynamics. Several adaptive sampling strategies have been proposed, but it is not clear which methods perform better for different physical systems. Here, we present a systematic evaluation of selected adaptive sampling strategies on a wide selection of fast folding proteins. The adaptive sampling strategies were emulated using models constructed on already existing MD trajectories. We provide theoretical limits for the sampling speed-up and compare the performance of different strategies with and without using some a priori knowledge of the system. The results show that for different goals, different adaptive sampling strategies are optimal. In order to sample slow dynamical processes such as protein folding without a priori knowledge of the system, a strategy based on the identification of a set of metastable regions is consistently the most efficient, while a strategy based on the identification of microstates performs better if the goal is to explore newer regions of the conformational space. Interestingly, the maximum speed-up achievable for the adaptive sampling of slow processes increases for proteins with longer folding times, encouraging the application of these methods for the characterization of slower processes, beyond the fast-folding proteins considered here.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Decentralized Filtering Adaptive Neural Network Control for Uncertain Switched Interconnected Nonlinear Systems

This article presents a novel decentralized filtering adaptive neural network control framework for uncertain switched interconnected nonlinear systems. Each subsystem has its own decentralized controller based on the established decentralized state predictor. For each subsystem, the nonlinear uncertainties are approximated by a Gaussian radial basis function (GRBF) neural network incorporated with a piecewise constant adaptive law, where the adaptive law will update adaptive parameters from the error dynamics between the host system and the decentralized state predictor by discarding the unknowns, whereas a decentralized filtering control law is derived to cancel both local and mismatched uncertainties from other subsystems, as well as achieve the local objective tracking of the host system. The achievement of global objective depends on the achievement of local objective for each subsystem. The matched uncertainties are canceled directly by adopting their opposite in the control signal, whereas a dynamic inversion of the system is required to eliminate the effect of the mismatched uncertainties on the output. By exploiting the average dwell time principle, the error bounds between the real system and the virtual reference system, which defines the best performance that can be achieved by the closed-loop system, are derived. A numerical example is given to illustrate the effectiveness of the decentralized filtering adaptive neural network control architecture by comparing against the model reference adaptive control (MRAC).

Average dwell time, decentralized, filtering adapt↗