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At least 181 records · Page 10

Angular dependence models for radiance to flux conversion

Angular dependence models (ADM) used for converting the measured radiance to flux at the top of the atmosphere are reviewed, and emphasis is placed on the measure of their effectiveness and the implications of requiring the ADMs to satisfy reciprocity. The overall significance of the ADMs is figured out by analyzing the same satellite data with a single Lambertian model, single mean model, and the 12 Earth Radiation Budget Experiment (ERBE) ADMs. It is shown that the Lambertian ADM is inadequate, while the mean ADM results in nearly unbiased fluxes but creates substantial differences for individual pixel fluxes. The standard ERBE ADM works well except for a 10-pct to 15-pct albedo growth across the scan; a modified ADM based on the standard ERBE ADM but forced to satisfy the principle of reciprocity increases the limb brightening and reduces the albedo growth but does not improve the scanner and nonscanner intercomparison.

Green, Richard N.↗

Stochasticity of comet P/Slaughter-Burnham

Three comets are now known to be at or near the 1/1 resonance with Jupiter: P/Slaughter-Burnham, P/Boethin and the newly discovered P/Ge-Wang. Although details of the individual orbits differ, the three comets have very similar dynamical behavior: their orbits show many transitions between the different types of resonant motion (satellite libration, anti-satellite libration, and circulating motion). The stochastic character of such cometary orbits, mainly due to encounters with Jupiter is investigated using Lyapunov Characteristic Indicators. For each comet of the group, we study the influences on the stochasticity of initial eccentricity, inclination, longitude of node, and l-l(sub J) (mean longitude of comet minus mean longitude of Jupiter). We present here our first results for P/Slaughter-Burnham.

Benest, Daniel↗

A fuzzy set preference model for market share analysis

Consumer preference models are widely used in new product design, marketing management, pricing, and market segmentation. The success of new products depends on accurate market share prediction and design decisions based on consumer preferences. The vague linguistic nature of consumer preferences and product attributes, combined with the substantial differences between individuals, creates a formidable challenge to marketing models. The most widely used methodology is conjoint analysis. Conjoint models, as currently implemented, represent linguistic preferences as ratio or interval-scaled numbers, use only numeric product attributes, and require aggregation of individuals for estimation purposes. It is not surprising that these models are costly to implement, are inflexible, and have a predictive validity that is not substantially better than chance. This affects the accuracy of market share estimates. A fuzzy set preference model can easily represent linguistic variables either in consumer preferences or product attributes with minimal measurement requirements (ordinal scales), while still estimating overall preferences suitable for market share prediction. This approach results in flexible individual-level conjoint models which can provide more accurate market share estimates from a smaller number of more meaningful consumer ratings. Fuzzy sets can be incorporated within existing preference model structures, such as a linear combination, using the techniques developed for conjoint analysis and market share estimation. The purpose of this article is to develop and fully test a fuzzy set preference model which can represent linguistic variables in individual-level models implemented in parallel with existing conjoint models. The potential improvements in market share prediction and predictive validity can substantially improve management decisions about what to make (product design), for whom to make it (market segmentation), and how much to make (market share prediction).

Turksen, I. B.↗

Power Measurement Errors on a Utility Aircraft

Extensive flight test data obtained from two recent performance tests of a UH 60A aircraft are reviewed. A power difference is calculated from the power balance equation and is used to examine power measurement errors. It is shown that the baseline measurement errors are highly non-Gaussian in their frequency distribution and are therefore influenced by additional, unquantified variables. Linear regression is used to examine the influence of other variables and it is shown that a substantial portion of the variance depends upon measurements of atmospheric parameters. Correcting for temperature dependence, although reducing the variance in the measurement errors, still leaves unquantified effects. Examination of the power difference over individual test runs indicates significant errors from drift, although it is unclear how these may be corrected. In an idealized case, where the drift is correctable, it is shown that the power measurement errors are significantly reduced and the error distribution is Gaussian. A new flight test program is recommended that will quantify the thermal environment for all torque measurements on the UH 60. Subsequently, the torque measurement systems will be recalibrated based on the measured thermal environment and a new power measurement assessment performed.

Bousman, William G.↗

A quantitative comparison of simultaneous BOLD fMRI and NIRS recordings during functional brain activation

Near-infrared spectroscopy (NIRS) has been used to noninvasively monitor adult human brain function in a wide variety of tasks. While rough spatial correspondences with maps generated from functional magnetic resonance imaging (fMRI) have been found in such experiments, the amplitude correspondences between the two recording modalities have not been fully characterized. To do so, we simultaneously acquired NIRS and blood-oxygenation level-dependent (BOLD) fMRI data and compared Delta(1/BOLD) (approximately R(2)(*)) to changes in oxyhemoglobin, deoxyhemoglobin, and total hemoglobin concentrations derived from the NIRS data from subjects performing a simple motor task. We expected the correlation with deoxyhemoglobin to be strongest, due to the causal relation between changes in deoxyhemoglobin concentrations and BOLD signal. Instead we found highly variable correlations, suggesting the need to account for individual subject differences in our NIRS calculations. We argue that the variability resulted from systematic errors associated with each of the signals, including: (1) partial volume errors due to focal concentration changes, (2) wavelength dependence of this partial volume effect, (3) tissue model errors, and (4) possible spatial incongruence between oxy- and deoxyhemoglobin concentration changes. After such effects were accounted for, strong correlations were found between fMRI changes and all optical measures, with oxyhemoglobin providing the strongest correlation. Importantly, this finding held even when including scalp, skull, and inactive brain tissue in the average BOLD signal. This may reflect, at least in part, the superior contrast-to-noise ratio for oxyhemoglobin relative to deoxyhemoglobin (from optical measurements), rather than physiology related to BOLD signal interpretation.

Non-NASA Center↗

Future human bone research in space

Skylab crewmembers demonstrated negative calcium (Ca) balance reaching about -300 mg/day by flight day 84. Limited bone density (BMD) measurements documented that bone was not lost equally from all parts of the skeleton. Subsequent BMD studies during long duration Russian flights documented the regional extent of bone loss. These studies demonstrated mean losses in the spine, femur neck, trochanter, and pelvis of about 1%-1.6% with large differences between individuals as well as between bone sites in a given individual. Limited available data indicate postflight bone recovery occurred in some individuals, but may require several years for complete restoration. Long duration bedrest studies showed a similar pattern of bone loss and calcium balance (-180 mg/day) as spaceflight. During long duration bedrest, resorption markers were elevated, formation markers were unchanged, 1,25 vitamin D (VitD) and calcium absorption were decreased, and serum ionized Ca was increased. Although this information is a good beginning, additional spaceflight research is needed to assess architectural and subregional bone changes, elucidate mechanisms, and develop efficient as well as effective countermeasures. Space research poses a number of unique problems not encountered in ground-based laboratory research. Therefore, researchers contemplating human spaceflight research need to consider a number of unique problems related to spaceflight in their experimental design.

NASA Center JSC↗

Development of Primary Volatile Production in COMET C/20O9 Pl (GARRADD) During its 2011-2O12 Apparition

We quantified primary volatiles in comet C/2009 Pl (Garradd) through pre- and post-perihelion observations acquired during its apparition in 2011-12 [1,2,3]. Detected volatiles include H2O, CO, CH4, C2H2, C2H6, HCN, NH3, H2CO, and CH3OH. We present production rates and chemical abundance ratios (relative to water) for all species, and I-D spatial profiles for multiple primary volatiles. We discuss these findings in the context of an emerging taxonomy based on primary volatiles in comets [4]. We used three spectrometer/telescope combinations. On UT 20ll August 7 (Rh 2.4 AU) and September 17-21 (Rh 2.0 AU), we used CRIRES at ESO's Very Large Telescope (VLT) [1]. On September 8 and 9 (Rh 2.1 AU), we used NIRSPEC at Keck-2 and CSHELL at IRTF [2]. Using NIRSPEC on October 13 and 2012 January 08 (Rh 1.83 and 1.57 AU, respectively), we detected nine primary volatiles pre-perihelion, and six post-perihelion [3]. CO was enriched in Garradd while C2H2 was strongly depleted. C2H6 and CH3OH displayed abundances close to those measured for the majority of Oort cloud comets observed to date. The high fractional abundance of CO identifies comet C12009 P1 as a CO-rich comet. Spatial profiles revealed notable differences among individual primary species. Given the relatively large heliocentric distance of C/2009 Pl, we explored the effect of water not being fully sublimated within our field of view and we identi$, the "missing" water fraction needed to reconcile the retrieved abundance ratios with the mean values found for "organics-normal" comets.

Mumma, M. J.↗

Impact of The Protective Renin-Angiotensin System (RAS) on The Vasoreparative Function of CD34+ CACs in Diabetic Retinopathy

Purpose: In diabetes, the impaired vasoreparative function of Circulating Angiogenic Cells (CACs) is believed to contribute to the progression of diabetic retinopathy (DR). Accumulating evidence suggests that the protective arm of renin-angiotensin system (RAS) ACE2 Angiotensin-(1-7) Mas plays an important role in restoring the function of diabetic CACs. We examined the protective RAS in CACs in diabetic individuals with different stages of retinopathy. Methods: Study subjects (n43) were recruited as controls or diabetics with either no DR, mild non-proliferative DR (NPDR), moderate NPDR, severe NPDR or proliferative DR (PDR). Fundus photography and fluorescein angiograms were analyzed using Vessel Generation Analysis (VESGEN) software in a cohort of subjects. CD34+ CACs were isolated from peripheral blood of diabetics and control subjects. RAS gene expressions in CACs were measured by qPCR. The vasoreparative function of CACs was assessed by migration ability toward CXCL12 using the QCM 5M 96-well chemotaxis cell migration assay. Results: ACE2 gene is a key enzyme converting the deleterious Angiotensin II to the beneficial Angiotensin-(1-7). ACE2 expression in CACs from diabetic subjects without DR was increased compared to controls, suggestive of compensation (p0.0437). The expression of Mas (Angiotensin-(1-7) receptor) in CACs was also increased in diabetics without DR, while was reduced in NPDR compared to controls (p0.0002), indicating a possible loss of compensation of the protective RAS at this stage of DR. The presence of even mild NPDR was associated with CD34+ CAC migratory dysfunction. When pretreating CACs of DR subjects with Angiotensin-(1-7), migratory ability to a chemoattractant CXCL12 was restored (p0.0008). By VESGEN analysis, an increase in small vessel density was observed in NPDR subjects when compared with the controls. Conclusions: These data suggest the protective RAS axis within diabetic CACs may help maintain their vasoreparative potential. The VESGEN analysis supports the presence of retinal repair in small vessels. The loss of the protective arm of RAS may predict the progression of DR.

diabetes↗

Evaluation of Multiple Flow Constrained Area Capacity Setting Methods for Collaborative Trajectory Options Program

The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP.

NextGen↗

Evaluation of Multiple Flow Constrained Area Capacity Setting Methods for Collaborative Trajectory Options Program

The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP.

NextGen↗

Reusing Data and Metadata to Create New Metadata Through Machine-Learning & Other Programmatic Methods

Recent improvements in natural language processing (NLP) enable metadata to be created programmatically from reused original metadata or even the dataset itself. Transfer-learning applied to NLP has greatly improved performance and reduced training data requirements. In this talk, we’ll compare machine-generated metadata to human-generated metadata and discuss characteristics of metadata and data archives that affect suitability for machine-learning reuse of metadata. Where as human-generated metadata is often populated once, populated from the perspective of data supplier, populated by many individuals with different words for the same thing, and limited in length, machine-generated metadata can be updated any number of times, generated from the perspective of any user, constrained to a standardized set of terms that can be evolved over time, and be any length required. Machine-learning generated metadata offers benefits but also additional needs in terms of version control, process transparency, human-computer interaction, and IT requirements. As a successful example, we’ll discuss how a dataset of abstracts and associated human-tagged keywords from a standardized list of several thousand keywords were used to create a machine-learning model that predicted keyword metadata for open-source code projects on code.nasa.gov. We’ll also discuss a less successful example from data.nasa.gov to show how data archive architecture and characteristics of initial metadata can be strong controls on how easy it is to leverage programmatic methods to reuse metadata to create additional metadata.

Gosses, Justin↗

Extreme Wet and Dry Conditions Affected Differently by Greenhouse Gases and Aerosols

Global warming due to greenhouse gases and atmospheric aerosols alter precipitation rates, but the influence on extreme precipitation by aerosols relative to greenhouse gases is still not well known. Here we use the simulations from the Precipitation Driver and Response Model Intercomparison Project that enable us to compare changes in mean and extreme precipitation due to greenhouse gases with those due to black carbon and sulfate aerosols, using indicators for dry extremes as well as for moderate and very extreme precipitation. Generally, we find that the more extreme a precipitation event is, the more pronounced is its response relative to global mean surface temperature change, both for aerosol and greenhouse gas changes. Black carbon (BC) stands out with distinct behavior and large differences between individual models. Dry days become more frequent with BC-induced warming compared to greenhouse gases, but so does the intensity and frequency of extreme precipitation. An increase in sulfate aerosols cools the surface and thereby the atmosphere, and thus induces a reduction in precipitation with a stronger effect on extreme than on mean precipitation. A better understanding and representation of these processes in models will provide knowledge for developing strategies for both climate change and air pollution mitigation.

Sillmann, Jana↗

AeroCom Phase III Multi-Model Evaluation of the Aerosol Life Cycle and Optical Properties Using Ground and Space-Based Remote Sensing as Well as Surface In Situ Observations

Within the framework of the AeroCom (Aerosol Comparisons between Observations and Models) initiative, the state-of-the-art modelling of aerosol optical properties is assessed from 14 global models participating in the phase III control experiment (AP3). The models are similar to CMIP6/AerChemMIP Earth System Models (ESMs) and provide a robust multi-model ensemble. Inter-model spread of aerosol species lifetimes and emissions appears to be similar to that of mass extinction coefficients (MECs), suggesting that aerosol optical depth (AOD) uncertainties are associated with a broad spectrum of parameterised aerosol processes. Total AOD is approximately the same as in AeroCom phase I (AP1) simulations. However, we find a 50 % decrease in the optical depth (OD) of black carbon (BC), attributable to a combination of decreased emissions and lifetimes. Relative contributions from sea salt (SS) and dust (DU) have shifted from being approximately equal in AP1 to SS contributing about 2∕3 of the natural AOD in AP3. This shift is linked with a decrease in DU mass burden, a lower DU MEC, and a slight decrease in DU lifetime, suggesting coarser DU particle sizes in AP3 compared to AP1. Relative to observations, the AP3 ensemble median and most of the participating models underestimate all aerosol optical properties investigated, that is, total AOD as well as fine and coarse AOD (AODf, AODc), Ångström exponent (AE), dry surface scattering (SCdry), and absorption (ACdry) coefficients. Compared to AERONET, the models underestimate total AOD by ca. 21 % ± 20 % (as inferred from the ensemble median and interquartile range). Against satellite data, the ensemble AOD biases range from −37 % (MODIS-Terra) to −16 % (MERGED-FMI, a multi-satellite AOD product), which we explain by differences between individual satellites and AERONET measurements themselves. Correlation coefficients (R) between model and observation AOD records are generally high (R>0.75), suggesting that the models are capable of capturing spatio-temporal variations in AOD. We find a much larger underestimate in coarse AODc (∼ −45 % ± 25 %) than in fine AODf (∼ −15 % ± 25 %) with slightly increased inter-model spread compared to total AOD. These results indicate problems in the modelling of DU and SS. The AODc bias is likely due to missing DU over continental land masses (particularly over the United States, SE Asia, and S. America), while marine AERONET sites and the AATSR SU satellite data suggest more moderate oceanic biases in AODc. Column AEs are underestimated by about 10 % ± 16 %. For situations in which measurements show AE > 2, models underestimate AERONET AE by ca. 35 %. In contrast, all models (but one) exhibit large overestimates in AE when coarse aerosol dominates (bias ca. +140 % if observed AE < 0.5). Simulated AE does not span the observed AE variability. These results indicate that models overestimate particle size (or underestimate the fine-mode fraction) for fine-dominated aerosol and underestimate size (or overestimate the fine-mode fraction) for coarse-dominated aerosol. This must have implications for lifetime, water uptake, scattering enhancement, and the aerosol radiative effect, which we can not quantify at this moment. Comparison against Global Atmosphere Watch (GAW) in situ data results in mean bias and inter-model variations of −35 % ± 25 % and −20 % ± 18 % for SCdry and ACdry, respectively. The larger underestimate of SCdry than ACdry suggests the models will simulate an aerosol single scattering albedo that is too low. The larger underestimate of SCdry than ambient air AOD is consistent with recent findings that models overestimate scattering enhancement due to hygroscopic growth. The broadly consistent negative bias in AOD and surface scattering suggests an underestimate of aerosol radiative effects in current global aerosol models. Considerable inter-model diversity in the simulated optical properties is often found in regions that are, unfortunately, not or only sparsely covered by ground-based observations. This includes, for instance, the Sahara, Amazonia, central Australia, and the South Pacific. This highlights the need for a better site coverage in the observations, which would enable us to better assess the models, but also the performance of satellite products in these regions. Using fine-mode AOD as a proxy for present-day aerosol forcing estimates, our results suggest that models underestimate aerosol forcing by ca. −15 %, however, with a considerably large interquartile range, suggesting a spread between −35 % and +10 %.

space-based remote sensing↗

Evaluation of Self-Scheduling Exercises Completed by Analog Crewmembers in NASA's Human Exploration Research Analog (HERA)

NASA human spaceflight missions are inherently dynamic and require frequent scheduling changes in order to adapt to changing mission priorities and objectives. Tactical level changes to the mission plan are traditionally made by a team of expert planners and operations specialists on the ground. However, astronauts are expected to execute missions more autonomously during future long duration missions. Astronauts will need to take on some of the responsibility of managing their own schedule while still abiding by the numerous constraints required by human spaceflight operations. This paper summarizes salient elements of crew performance in NASA’s Human Exploration Research Analog Campaign 3. Analog crewmembers completed a series of self-scheduling exercises to evaluate Playbook’s usability towards enabling self-scheduling without support from ground control. Playbook is a self-scheduling software tool designed and developed by our team. We also investigated how to best communicate self-scheduling tasks and constraints to the crew in order to facilitate efficient self-scheduling during isolation in a realistic environment. Our analysis identified that 30 minutes was sufficient to complete complex self-scheduling tasks. Our evaluation also identified differences between individual and collaborative performance; analog crewmembers completed self-scheduling exercises more quickly as a team as opposed to individually and reported lower subjective difficulty ratings overall.

HERA↗

Nanosensors for Evaluating Hazardous Environments

Personnel working in a confined environment can be exposed to hazardous gases, and certain gases can be extremely dangerous even in concentrations as low as a few parts per billion. Nanosensors can be placed in multiple locations over a large area, thus allowing for more precise and timely detection of gas leaks. ASRC Aerospace and its research partners are developing nanosensors to detect various gases, including hydrogen, ammonia, nitrogen tetroxide, and hydrazine. Initial laboratory testing demonstrated the capability to detect these gases in concentrations lower than parts per million, and current testing is evaluating sensitivity at concentration levels three orders of magnitude lower. Testing and development continue to improve the response and recovery times and to increase the sensitivity of the devices. The development team is evaluating different coatings and electrodes to determine the optimum configuration for detecting and identifying a variety of gases. The small footprint of the nanosensors allows several devices to be placed into a single substrate. Each sensor is responsive in a different way to different gases. Embedding multiple devices into a single substrate results in better reliability and less frequent calibrations. The use of different coatings for individual elements of a multichannel sensor allows different gases to be identified. The sensor system is implemented by the use of a custom multichannel signal conditioner amplifier built on a small multichip module. This device processes the output of the sensors and transmits a signal that can be monitored and analyzed remotely.

Source record↗

Growth Control and Disease Mechanisms in Computational Embryogeny

This paper presents novel approach to applying growth control and diseases mechanisms in computational embryogeny. Our method, which mimics fundamental processes from biology, enables individuals to reach maturity in a controlled process through a stochastic environment. Three different mechanisms were implemented; disease mechanisms, gene suppression, and thermodynamic balancing. This approach was integrated as part of a structural evolutionary model. The model evolved continuum 3-D structures which support an external load. By using these mechanisms we were able to evolve individuals that reached a fixed size limit through the growth process. The growth process was an integral part of the complete development process. The size of the individuals was determined purely by the evolutionary process where different individuals matured to different sizes. Individuals which evolved with these characteristics have been found to be very robust for supporting a wide range of external loads.

Genetic algorithm↗

Estimation of Optimum Stimulus Amplitude for Balance Training using Electrical Stimulation of the Vestibular System

Sensorimotor changes such as posture and gait instabilities can affect the functional performance of astronauts after gravitational transitions. Sensorimotor Adaptability (SA) training can help alleviate decrements on exposure to novel sensorimotor environments based on the concept of 'learning to learn' by exposure to varying sensory challenges during posture and locomotion tasks (Bloomberg 2015). Supra-threshold Stochastic Vestibular Stimulation (SVS) can be used to provide one of many challenges by disrupting vestibular inputs. In this scenario, the central nervous system can be trained to utilize veridical information from other sensory inputs, such as vision and somatosensory inputs, for posture and locomotion control. The minimum amplitude of SVS to simulate the effect of deterioration in vestibular inputs for preflight training or for evaluating vestibular contribution in functional tests in general, however, has not yet been identified. Few studies (MacDougall 2006; Dilda 2014) have used arbitrary but fixed maximum current amplitudes from 3 to 5 mA in the medio-lateral (ML) direction to disrupt balance function in healthy adults. Giving this high level of current amplitude to all the individuals has a risk of invoking side effects such as nausea and discomfort. The goal of this study was to determine the minimum SVS level that yields an equivalently degraded balance performance. Thirteen subjects stood on a compliant foam surface with their eyes closed and were instructed to maintain a stable upright stance. Measures of stability of the head, trunk, and whole body were quantified in the ML direction. Duration of time they could stand on the foam surface was also measured. The minimum SVS dosage was defined to be that level which significantly degraded balance performance such that any further increase in stimulation level did not lead to further balance degradation. The minimum SVS level was determined by performing linear fits on the performance variable at different stimulation levels. Results from the balance task suggest that there are inter-individual differences and the minimum SVS amplitude was found to be in the range of 1 mA to 2.5 mA across subjects. SVS resulted in an average decrement of balance task performance in the range of 62%-73% across different measured variables at the minimum SVS amplitude in comparison to the control trial (no stimulus). Training using supra-threshold SVS stimulation is one of the sensory challenges used for preflight SA training designed to improve adaptability to novel gravitational environments. Inter-individual differences in response to SVS can help customize the SA training paradigms using minimal dosage required. Another application of using SVS is to simulate acute deterioration of vestibular sensory inputs in the evaluation of tests for assessing vestibular function.

Goel, R.↗

Radial variation of lunar crater rim topography

The paper presents results of determinations of variations of rim topography as a function of range from the crater rim for a group of morphologically fresh craters. It is found that the rate at which exterior crater topography converges with the surrounding surface is highly variable among different radial directions at individual craters as well as between different craters, and that at several craters, oblique impact appears to have contributed to azimuthal elevation/range variations.

Settle, M.↗