A Thruster Sub-System Module (TSSM) for solar electric propulsion

Solar Electric Propulsion (SEP) is currently being studied for possible use in a number of near-earth and planetary missions. Thruster systems for these missions could be integrated directly into a spacecraft or modularized into a Thruster Sub-System Module (TSSM). A TSSM for electric propulsion missions would consist of a 30-cm ion thruster, thruster gimbal system, propellant storage and feed system, associated Power Processing Unit (PPU), thermal control system and complete supporting structure. The TSSM would be wholly self-contained and be essentially a plug-in or strap-on electric stage with simple mechanical, thermal, electrical and propellant interfaces. The TSSM described in this report is designed for a broad range of missions requiring from two to ten TSSM's mounted in a 2 by x configuration. The thermal control system is designed to accommodate waste heat from the power processor based on realistic efficiencies when the TSSM is operating from 0.7 to 3.5 AU's. The modules are 0.61 M (2 ft) wide by 2.29 M (7.5 ft) long and have a dry weight including propellant tank of 54.4 kg (120 lb). The propellant tank will hold 145.1 kg (320 lb) of mercury

Composition of the hot plasma near geosynchronous altitude

Although there were no direct measurements of the composition of the hot (keV) plasma at geosynchronous altitudes, the combination of other observations leads to the conclusion that, at least during geomagnetically disturbed periods, there are significant fluxes of ions heavier than protons in this region. Ion composition measurements below 8000 km altitude show upward streaming fluxes of both O(+) and H(+) ions in the L-region of the geosynchronous orbit. These observations are consistent with the conclusion that at least a portion of the total ion fluxes observed at geosynchronous altitude to be highly peaked near the magnetic field lines are heavier than protons and originate in the ionosphere

Analysis of satellite data on energetic particles of ionospheric origin

The morphology was studied of precipitating O(+) and H(+) ions in the energy range 0.7 equal to or less than E equal to or less than 12 keV during the storm-time period from December 16-18, 1971, which encompassed two principal magnetic storms. The results are described with emphasis on the temporal variations of parameters characterizing the intensity, average energy, and spatial location of the zones of precipitation of the two ionic species. One of the principal results was the finding that the intensity of the precipitating O(+) ions was well correlated with the geomagnetic indices which measure the strength of magnetospheric substorm activity and the strength of the storm-time ring current. Since the O(+) ions are almost certainly of ionospheric origin the correlations indicate that a previously unknown strong coupling mechanism existed between the magnetosphere and the ionosphere during the storm period

Analysis of satellite data on energetic particles of ionospheric origin

The principal result of this program has been the completion of a detailed statistical study of the properties of precipitating O(+) and H(+) ions during two principal magnetic storms. The results of the analysis of selected data of ion mass spectrometer experiment on satellites are given with emphasis on the morphology of the O(+) ions of ionospheric origin with energies in the 0.7 les than or equal to E less than or equal to 12 keV range that were discovered with this experiment

A structural and thermal packaging approach for power processing units for 30-cm ion thrusters

Solar Electric Propulsion (SEP) is currently being studied for possible use in a number of near earth and planetary missions. The thruster subsystem for these missions would consist of 30 centimeter ion thrusters with Power Processor Units (PPU) clustered in assemblies of from two to ten units. A preliminary design study of the electronic packaging of the PPU has been completed at Lewis Research Center of NASA. This study evaluates designs meeting the competing requirements of low system weight and overall mission flexibility. These requirements are evaluated regarding structural and thermal design, electrical efficiency, and integration of the electrical circuits into a functional PPU layout

ATDRS payload technology research and development

Four technology development tasks were chosen to reduce (or at least better understand) the technology risks associated with proposed approaches to Advanced Tracking and Data Relay Satellite (ATDRS). The four tasks relate to a Tri-Band Antenna feed system, a Digital Beamforming System for the S Band Multiple Access System (SMA), an SMA Phased Array Antenna, and a Configuration Thermal/Mechanical Analysis task. The objective, approach, and status of each are discussed

Novel modeling of task versus rest brain state predictability using a dynamic time warping spectrum: comparisons and contrasts with other standard measures of brain dynamics

Dynamic time warping, or DTW, is a powerful and domain-general sequence alignment method for computing a similarity measure. Such dynamic programming-based techniques like DTW are now the backbone and driver of most bioinformatics methods and discoveries. In neuroscience it has had far less use, though this has begun to change. We wanted to explore new ways of applying DTW, not simply as a measure with which to cluster or compare similarity between features but in a conceptually different way. We have used DTW to provide a more interpretable spectral description of the data, compared to standard approaches such as the Fourier and related transforms. The DTW approach and standard discrete Fourier transform (DFT) are assessed against benchmark measures of neural dynamics. These include EEG microstates, EEG avalanches, and the sum squared error (SSE) from a multilayer perceptron (MLP) prediction of the EEG time series, and simultaneously acquired FMRI BOLD signal. We explored the relationships between these variables of interest in an EEG-FMRI dataset acquired during a standard cognitive task, which allowed us to explore how DTW differentially performs in different task settings. We found that despite strong correlations between DTW and DFT-spectra, DTW was a better predictor for almost every measure of brain dynamics. Using these DTW measures, we show that predictability is almost always higher in task than in rest states, which is consistent to other theoretical and empirical findings, providing additional evidence for the utility of the DTW approach

Disconnection of network hubs and cognitive impairment after traumatic brain injury.

Traumatic brain injury affects brain connectivity by producing traumatic axonal injury. This disrupts the function of large-scale networks that support cognition. The best way to describe this relationship is unclear, but one elegant approach is to view networks as graphs. Brain regions become nodes in the graph, and white matter tracts the connections. The overall effect of an injury can then be estimated by calculating graph metrics of network structure and function. Here we test which graph metrics best predict the presence of traumatic axonal injury, as well as which are most highly associated with cognitive impairment. A comprehensive range of graph metrics was calculated from structural connectivity measures for 52 patients with traumatic brain injury, 21 of whom had microbleed evidence of traumatic axonal injury, and 25 age-matched controls. White matter connections between 165 grey matter brain regions were defined using tractography, and structural connectivity matrices calculated from skeletonized diffusion tensor imaging data. This technique estimates injury at the centre of tract, but is insensitive to damage at tract edges. Graph metrics were calculated from the resulting connectivity matrices and machine-learning techniques used to select the metrics that best predicted the presence of traumatic brain injury. In addition, we used regularization and variable selection via the elastic net to predict patient behaviour on tests of information processing speed, executive function and associative memory. Support vector machines trained with graph metrics of white matter connectivity matrices from the microbleed group were able to identify patients with a history of traumatic brain injury with 93.4% accuracy, a result robust to different ways of sampling the data. Graph metrics were significantly associated with cognitive performance: information processing speed (R(2) = 0.64), executive function (R(2) = 0.56) and associative memory (R(2) = 0.25). These results were then replicated in a separate group of patients without microbleeds. The most influential graph metrics were betweenness centrality and eigenvector centrality, which provide measures of the extent to which a given brain region connects other regions in the network. Reductions in betweenness centrality and eigenvector centrality were particularly evident within hub regions including the cingulate cortex and caudate. Our results demonstrate that betweenness centrality and eigenvector centrality are reduced within network hubs, due to the impact of traumatic axonal injury on network connections. The dominance of betweenness centrality and eigenvector centrality suggests that cognitive impairment after traumatic brain injury results from the disconnection of network hubs by traumatic axonal injury

Electrometer system measures nanoamps at high voltage

Floating electrometer eliminates major source of error since any leakage from electrometer case, which is at high voltage, appears only as load on high voltage supply and not as part of current being measured. Commands to and data from floating electrometer are transferred across high voltage interface by means of optical channels