Results for “interval” — Page 24

NASA NTRS1999

Heart rate dynamics before spontaneous onset of ventricular fibrillation in patients with healed myocardial infarcts

The traditional methods of analyzing heart rate (HR) variability have failed to predict imminent ventricular fibrillation (VF). We sought to determine whether new methods of analyzing RR interval variability based on nonlinear dynamics and fractal analysis may help to detect subtle abnormalities in RR interval behavior before the onset of life-threatening arrhythmias. RR interval dynamics were analyzed from 24-hour Holter recordings of 15 patients who experienced VF during electrocardiographic recording. Thirty patients without spontaneous or inducible arrhythmia events served as a control group in this retrospective case control study. Conventional time- and frequency-domain measurements, the short-term fractal scaling exponent (alpha) obtained by detrended fluctuation analysis, and the slope (beta) of the power-law regression line (log power - log frequency, 10(-4)-10(-2) Hz) of RR interval dynamics were determined. The short-term correlation exponent alpha of RR intervals (0.64 +/- 0.19 vs 1.05 +/- 0.12; p <0.001) and the power-law slope beta (-1.63 +/- 0.28 vs -1.31 +/- 0.20, p <0.001) were lower in the patients before the onset of VF than in the control patients, but the SD and the low-frequency spectral components of RR intervals did not differ between the groups. The short-term scaling exponent performed better than any other measurement of HR variability in differentiating between the patients with VF and controls. Altered fractal correlation properties of HR behavior precede the spontaneous onset of VF. Dynamic analysis methods of analyzing RR intervals may help to identify abnormalities in HR behavior before VF.

Non-NASA Center↗

NASA NTRS1998

Interactions between CO2 chemoreflexes and arterial baroreflexes

We studied interactions between CO2 chemoreflexes and arterial baroreflexes in 10 supine healthy young men and women. We measured vagal carotid baroreceptor-cardiac reflexes and steady-state fast Fourier transform R-R interval and photoplethysmographic arterial pressure power spectra at three arterial pressure levels (nitroprusside, saline, and phenylephrine infusions) and three end-tidal CO2 levels (3, 4, and 5%, fixed-frequency, large-tidal-volume breathing, CO2 plus O2). Our study supports three principal conclusions. First, although low levels of CO2 chemoreceptor stimulation reduce R-R intervals and R-R interval variability, statistical modeling suggests that this effect is indirect rather than direct and is mediated by reductions of arterial pressure. Second, reductions of R-R intervals during hypocapnia reflect simple shifting of vagally mediated carotid baroreflex responses on the R-R interval axis rather than changes of baroreflex gain, range, or operational point. Third, the influence of CO2 chemoreceptor stimulation on arterial pressure (and, derivatively, on R-R intervals and R-R interval variability) depends critically on baseline arterial pressure levels: chemoreceptor effects are smaller when pressure is low and larger when arterial pressure is high.

NASA Discipline Cardiopulmonary↗

NASA NTRSDate not supplied

Enabling Intelligent Data Downlink Prioritization of In-Situ Observations through Generalizable and Computationally Inexpensive Anomaly Detection

High-fidelity measurements of magnetic fields and other observed properties, such as energetic particle fluxes, are a necessary component to our understanding of the highly dynamic near-Earth space environment. As our desire to study smaller-scale phenomena such as shocks and dipolorizations has increased, we have been driven to take and telemeter measurements at higher cadences. Unfortunately, many missions are unable to downlink all their captured data due to the well-known data transmission bottleneck at the DSN. These missions must then prioritize their high-cadence data such that the most scientifically useful intervals are transmitted. One simple prioritization technique uses the spacecraft position to telemeter data from only the region of interest. Although easy to implement, this method does not leverage the available scientific data and can omit intervals of useful scientific data when they lie outside the region of interest. The Magnetospheric Multiscale Mission (MMS) uses mission-specific parameterization of several data products to automatically prioritize scientifically useful intervals. Then, MMS verifies the automatically selected intervals by having a domain expert manually select intervals for downlink. The overall complexity required by this technique make it prohibitive for deployment on low-cost platforms (i.e., CubeSats) or on future missions featuring large constellations of satellites such as the Geospace Dynamics Constellation (GDC). We present preliminary results for a simple, generic, and data-driven method of downlink prioritization for magnetic field (and other) measurements. Specifically, Principal Components Analysis (PCA) and One-Class Support Vector Machines (OC-SVMs) are used to detect intervals containing anomalous activity, which can then be prioritized for subsequent downlink. The computational simplicity of this algorithm makes it an excellent candidate for implementation on spaceflight hardware, as well as provide generalizability to a broad range of missions and data products. Initial analysis of this technique has been performed using magnetic field measurements from the Magnetospheric Multiscale Mission and CASSIOP, where it automatically identified scientifically interesting intervals containing Alfvén waves and EMIC activity.

Matthew G. Finley↗

NASA NTRSDate not supplied

Enabling Intelligent Data Downlink Prioritization of In-Situ Observations through Generalizable and Computationally Inexpensive Anomaly Detection

High-fidelity measurements of magnetic fields and other observed properties, such as energetic particle fluxes, are a necessary component to our understanding of the highly dynamic near-Earth space environment. As our desire to study smaller-scale phenomena such as shocks and dipolorizations has increased, we have been driven to take and telemeter measurements at higher cadences. Unfortunately, many missions are unable to downlink all their captured data due to the well-known data transmission bottleneck at the DSN. These missions must then prioritize their high-cadence data such that the most scientifically useful intervals are transmitted. One simple prioritization technique uses the spacecraft position to telemeter data from only the region of interest. Although easy to implement, this method does not leverage the available scientific data and can omit intervals of useful scientific data when they lie outside the region of interest. The Magnetospheric Multiscale Mission (MMS) uses mission-specific parameterization of several data products to automatically prioritize scientifically useful intervals. Then, MMS verifies the automatically selected intervals by having a domain expert manually select intervals for downlink. The overall complexity required by this technique make it prohibitive for deployment on low-cost platforms (i.e., CubeSats) or on future missions featuring large constellations of satellites such as the Geospace Dynamics Constellation (GDC). We present preliminary results for a simple, generic, and data-driven method of downlink prioritization for magnetic field (and other) measurements. Specifically, Principal Components Analysis (PCA) and One-Class Support Vector Machines (OC-SVMs) are used to detect intervals containing anomalous activity, which can then be prioritized for subsequent downlink. The computational simplicity of this algorithm makes it an excellent candidate for implementation on spaceflight hardware, as well as provide generalizability to a broad range of missions and data products. Initial analysis of this technique has been performed using magnetic field measurements from the Magnetospheric Multiscale Mission and CASSIOP, where it automatically identified scientifically interesting intervals containing Alfvén waves and EMIC activity.

Matthew G. Finley↗

DOE OSTI2025

Expedition UT-GOM2-2 Site H

Pressure and conventional cores were collected at Site H of the Walker Ridge Protracted Area Block 313 in the Terrebonne Basin, deepwater Gulf of America (Gulf of Mexico) during the University of Texas (UT) Deepwater Hydrate Coring Expedition (UT-GOM2-2). Pressure and conventional cores were collected continuously to a depth of 155.1 meters below the seafloor (mbsf). At deeper depths, cores were taken periodically from hydrate-bearing sands and their bounding muds to a total depth of 861.3 mbsf. 162.6 m of conventional core and 54.8 m of pressure core were recovered. Twelve temperature measurements were made between 27.1 and 144.5 mbsf to determine the geothermal gradient. At the seafloor, more than 4 m of sandy silt of unknown origin was encountered. Beneath this sand, to a depth of about 200 mbsf, the section was composed of interbedded mud and biogenic carbonate ooze. The ooze correlated to low density and high porosity intervals observed in the previously acquired logging while drilling (LWD) data and as measured. These ooze intervals also correspond to lighter sediment color, increased Ca content based on X-ray florescence (XRF) core scanning, and increased calcareous nannofossil abundance. Calcareous nannofossil biostratigraphy constrains the entire record to the Pleistocene (< 0.91 million years), with a pronounced increase in sedimentation rate with depth. Below 200 mbsf, the section was predominantly composed of mud with two thicker, hydrate-bearing coarse-grained intervals, which are commonly known as the Blue and Orange sands. The dissolved gas concentration was quantified from pressure cores. In the shallow section, dissolved methane concentration increased below the sulfate-methane transition zone (SMTZ) and reaches saturation (the limit of solubility for methane) at 147 mbsf. Gas expansion was very common in conventional and depressurized pressure (conventionalized) cores below the SMTZ. At deeper depths, the methane concentration within muds bounding the Blue and Orange reservoirs was generally found to be less than saturation. The dissolved and hydrate gas composition is consistent with a microbial source, containing greater than 99.99% methane and only trace concentrations of ethane, propane, and butane. The methane to ethane ratio (C1 /C2 ) and the methane to ethane plus propane (C1 /(C2 +C3 )) decrease with depth down to at least 678 mbsf, mainly driven by the increase in ethane with depth. It is unclear if this trend continues through the Orange sand interval. The δ13C isotopic signature of methane ranges between -69.9 and -78.5 ‰ relative to the Vienna Pee Dee Belemnite (VPDB) standard. Pressure core recovery in sandy intervals was poor. However, pressure core logs of the Orange sand show intervals of low density and high velocity, which are indicative of high hydrate saturation. One pressure core was degassed and the average hydrate saturation in the core was determined to be 24%. One core from within the Orange sand was composed of interbedded graded sandy silt and mud. The sandy silts from this core are composed of mainly quartz and feldspar with some lithics. Most of the recovered pressure core samples are maintained at near in-situ pressure and temperature (within the hydrate stability field) at the University of Texas Pressure Core Center awaiting analysis. In the shallow section, samples will be used to determine the flux of organic carbon through the basin system, find the rate at which that carbon was consumed, and understand the microbial population responsible for these processes. In the deeper section, samples from in and around the hydrate reservoirs will be used to determine the petrophysical properties of the reservoir and bounding seals in these systems.

03 NATURAL GAS↗

NASA NTRS1992

Responses of heart rate and blood pressure to KC-135 hyper-gravity

Many investigators have clarified the effects of hyper gravitational-inertial forces (G) upon the cardiovascular system, using the centrifugal apparatus with short rotating radius. We investigated the cardiovascular responses to KC-135 hyper-G flight with negligibly small angular velocity. Six normal, healthy subjects 29 to 40 years old (5 males and 1 female) took part in this experiment. Hyper gravitational-inertial force was generated by the KC-135 hyper-G flight, flown in a spiral path with a very long radius of 1.5 miles. Hyper-G was sustained for 3 minutes with 1.8 +Gz in each session and was repeatedly exposed to very subject sitting on a chair 5 times. The preliminary results of blood pressure and R-R interval are discussed. An exposure of 1.8 +Gz stress resulted in a remarkable increase of systolic and diastolic blood pressure, while the pulse pressure did not change and remained equal to the control level regardless of an exposure of hyper-G. These results in blood pressure indicate an increase of resistance in the peripheral vessels, when an exposure of hyper-G was applied. The R-R interval was calculated from ECG. R-R interval in all subjects was changed but not systematically, and R-R interval became obviously shorter during the hyper-G period than during the 1 +Gz control period although R-R interval varied widely in some cases. The coefficient of variation of R-R interval was estimated to determine the autonomic nerve activity, but no significant change was detectable.

Satake, Hirotaka↗

NASA NTRS1994

Optically broadcasting wind direction indicator

An optically broadcasting wind direction indicator generates flashes of light which are separated by a time interval that is directly proportional to the angle of the wind direction relative to a fixed direction, such as north. An angle/voltage transducer generates a voltage that is proportional to the wind direction relative to the fixed direction, and this voltage is employed by timing circuitry or a microprocessor that generates pulses for actuating a light source trigger circuit first at the start of the time interval, and then at the end of the time interval. To aid an observer in distinguishing between the beginning and end of the interval, two stop flashes can be provided in quick succession. The time scale is preferably chosen so that each second of the time interval corresponds to 30 deg of direction relative to north. In this manner, an observer can easily correlate the measured time interval to the wind direction by visualizing the numbers on a conventional clock face, each of which correspond to one second of time and 30 deg of angle.

Zysko, Jan A.↗

NASA NTRS1995

Combining Speed Information Across Space

We used speed discrimination tasks to measure the ability of observers to combine speed information from multiple stimuli distributed across space. We compared speed discrimination thresholds in a classical discrimination paradigm to those in an uncertainty/search paradigm. Thresholds were measured using a temporal two-interval forced-choice design. In the discrimination paradigm, the n gratings in each interval all moved at the same speed and observers were asked to choose the interval with the faster gratings. Discrimination thresholds for this paradigm decreased as the number of gratings increased. This decrease was not due to increasing the effective stimulus area as a control experiment that increased the area of a single grating did not show a similar improvement in thresholds. Adding independent speed noise to each of the n gratings caused thresholds to decrease at a rate similar to the original no-noise case, consistent with observers combining an independent sample of speed from each grating in both the added- and no-noise cases. In the search paradigm, observers were asked to choose the interval in which one of the n gratings moved faster. Thresholds in this case increased with the number of gratings, behavior traditionally attributed to an input bottleneck. However, results from the discrimination paradigm showed that the increase was not due to observers' inability to process these gratings. We have also shown that the opposite trends of the data in the two paradigms can be predicted by a decision theory model that combines independent samples of speed information across space. This demonstrates that models typically used in classical detection and discrimination paradigms are also applicable to search paradigms. As our model does not distinguish between samples in space and time, it predicts that discrimination performance should be the same regardless of whether the gratings are presented in two spatial intervals or two temporal intervals. Our last experiment largely confirmed this prediction.

Verghese, Preeti↗

NASA NTRS1995

Combining Speed Information Across Space

We used speed discrimination tasks to measure the ability of observers to combine speed information from multiple stimuli distributed across space. We compared speed discrimination thresholds in a classical discrimination paradigm to those in an uncertainty/search paradigm. Thresholds were measured using a temporal two-interval forced-choice design. In the discrimination paradigm, the n gratings in each interval all moved at the same speed and observers were asked to choose the interval with the faster gratings. Discrimination thresholds for this paradigm decreased as the number of gratings increased. This decrease was not due to increasing the effective stimulus area as a control experiment that increased the area of a single grating did not show a similar improvement in thresholds. Adding independent speed noise to each of the n gratings caused thresholds to decrease at a rate similar to the original no-noise case, consistent with observers combining an independent sample of speed from each grating in both the added- and no-noise cases. In the search paradigm, observers were asked to choose the interval in which one of the n gratings moved faster. Thresholds in this case increased with the number of gratings, behavior traditionally attributed to an input bottleneck. However, results from the discrimination paradigm showed that the increase was not due to observers' inability to process these gratings. We have also shown that the opposite trends of the data in the two paradigms can be predicted by a decision theory model that combines independent samples of speed information across space. This demonstrates that models typically used in classical detection and discrimination paradigms are also applicable to search paradigms. As our model does not distinguish between samples in space and time, it predicts that discrimination performance should be the same regardless of whether the gratings are presented in two spatial intervals or two temporal intervals. Our last experiment largely confirmed this prediction.

Verghese, Preeti↗

NASA NTRS1997

Isotopic Signature of the Ancient Biosphere

The age distribution of 261 field localities, sampled for their well-preserved Archean and Proterozoic sedimentary rocks, revealed a 500-700 Ma episodicity. Assuming that the numbers of sites are a proxy for mass of sediments, the record of well-preserved sediments is more abundant in the intervals 3.5-3.3, 2.8-2.5, 2.1-1.8, 1.5-1.3, and 1.0-0.54 Ga than in the intervening intervals. It is proposed that the crustal inventory of photosynthetic organic carbon was modulated by the volume of sedimentation in sites favorable for the burial and long-term preservation of organic carbon. Tectonic processes controlled this sediment volume. Episodic increases in the organic inventory led to stepwise increases in oxidized reservoirs (e.g., O2, SO4(2-), Fe(3+). The interval 2.9-2.5 Ga recorded a large rise in seawater Sr-87/Sr-86, the oldest-known extensive banded iron formations, and the first evidence (C-13-depleted kerogens) of O2 use by methylotrophic bacteria. The interval 2.2-1.8 Ga has both carbon isotopic evidence for a stepwise increase in the organic reservoir and also paleosol evidence for an O2 increase. The interval 1.1-0.6 Ga shows isotopic evidence for another organic carbon increase. The interval 1.5-1.3 Ga revealed no such increases as yet, perhaps because incomplete rifting of the mid-Proterozoic supercontinent was associated with extensive sedimentation in oxidized continental basins, producing redbeds, coarse clastics, etc. Such sedimentation did not promote the burial of reduced carbon.

DesMarais, D. J.↗

NASA NTRS2000

Physiological basis for human autonomic rhythms

Oscillations of arterial pressures, heart periods, and muscle sympathetic nerve activity have been studied intensively in recent years to explore otherwise obscure human neurophysiological mechanisms. The best-studied rhythms are those occurring at breathing frequencies. Published evidence indicates that respiratory fluctuations of muscle sympathetic nerve activity and electrocardiographic R-R intervals result primarily from the action of a central 'gate' that opens during expiration and closes during inspiration. Parallel respiratory fluctuations of arterial pressures and R-R intervals are thought to be secondary to arterial baroreflex physiology: changes in systolic pressure provoke changes in the R-R interval. However, growing evidence suggests that these parallel oscillations result from the influence of respiration on sympathetic and vagal-cardiac motoneurones rather than from baroreflex physiology. There is a rapidly growing literature on the use of mathematical models of low- and high-frequency (respiratory) R-R interval fluctuations in characterizing instantaneous 'sympathovagal balance'. The case for this approach is based primarily on measurements made with patients in upright tilt. However, the strong linear relation between such measures as the ratio of low- to high-frequency R-R interval oscillations and the angle of the tilt reflects exclusively the reductions of the vagal (high-frequency) component. As the sympathetic component does not change in tilt, the low- to high-frequency R-R interval ratio provides no proof that sympathetic activity increases. Moreover, the validity of extrapolating from measurements performed during upright tilt to measurements during supine rest has not been established. Nonetheless, it is clear that measures of heart rate variability provide important prognostic information in patients with cardiovascular diseases. It is not known whether reduced heart rate variability is merely a marker for the severity of disease or a measurement that identifies functional reflex abnormalities contributing to terminal dysrhythmias.

Review, Tutorial↗

NASA NTRS1998

Controlled breathing protocols probe human autonomic cardiovascular rhythms

The purpose of this study was to determine how breathing protocols requiring varying degrees of control affect cardiovascular dynamics. We measured inspiratory volume, end-tidal CO2, R-R interval, and arterial pressure spectral power in 10 volunteers who followed the following 5 breathing protocols: 1) uncontrolled breathing for 5 min; 2) stepwise frequency breathing (at 0.3, 0.25, 0.2, 0.15, 0.1, and 0.05 Hz for 2 min each); 3) stepwise frequency breathing as above, but with prescribed tidal volumes; 4) random-frequency breathing (approximately 0.5-0.05 Hz) for 6 min; and 5) fixed-frequency breathing (0.25 Hz) for 5 min. During stepwise breathing, R-R interval and arterial pressure spectral power increased as breathing frequency decreased. Control of inspired volume reduced R-R interval spectral power during 0.1 Hz breathing (P < 0.05). Stepwise and random-breathing protocols yielded comparable coherence and transfer functions between respiration and R-R intervals and systolic pressure and R-R intervals. Random- and fixed-frequency breathing reduced end-tidal CO2 modestly (P < 0.05). Our data suggest that stringent tidal volume control attenuates low-frequency R-R interval oscillations and that fixed- and random-rate breathing may decrease CO2 chemoreceptor stimulation. We conclude that autonomic rhythms measured during different breathing protocols have much in common but that a stepwise protocol without stringent control of inspired volume may allow for the most efficient assessment of short-term respiratory-mediated autonomic oscillations.

Non-NASA Center↗

NASA NTRS1989

Monolithic transistor gate energy recovery system

Energy is recovered from an insulated gate semiconductor switch, such as a MOSFET, that is otherwise lost in the gate capacitance by producing a notch in the gate control voltage for an interval B following an interval A after initial application of a gate control voltage pulse for turning the switch on, and a notch for an interval C following termination of the gate control voltage pulse followed by interval D during which the switch is turned on again, where each interval is a period .DELTA.T given by ##EQU1## L.sub.s is the inductance (discrete and/or parasitic) in series with the gate electrode of the insulated gate semiconductor switch, and C.sub.in is the capacitance of that switch between its gate and source electrodes. The interval .DELTA.T may be provided directly by timing in a pulse forming circuit for the gate control voltage applied, or adaptively by sensing the gate voltage v.sub.g and comparing it with fixed progressively higher voltages v.sub.1, v.sub.2 and v.sub.3, where v.sub.2 is intermediate v.sub.1 and v.sub.3 which correspond to the lower and upper levels of v.sub.g as the switch is turned off and on.

Rippel, Wally E.↗

NASA NTRS2008

Uncertainty and Sensitivity Analyses of a Two-Parameter Impedance Prediction Model

This paper presents comparisons of predicted impedance uncertainty limits derived from Monte-Carlo-type simulations with a Two-Parameter (TP) impedance prediction model and measured impedance uncertainty limits based on multiple tests acquired in NASA Langley test rigs. These predicted and measured impedance uncertainty limits are used to evaluate the effects of simultaneous randomization of each input parameter for the impedance prediction and measurement processes. A sensitivity analysis is then used to further evaluate the TP prediction model by varying its input parameters on an individual basis. The variation imposed on the input parameters is based on measurements conducted with multiple tests in the NASA Langley normal incidence and grazing incidence impedance tubes; thus, the input parameters are assigned uncertainties commensurate with those of the measured data. These same measured data are used with the NASA Langley impedance measurement (eduction) processes to determine the corresponding measured impedance uncertainty limits, such that the predicted and measured impedance uncertainty limits (95% confidence intervals) can be compared. The measured reactance 95% confidence intervals encompass the corresponding predicted reactance confidence intervals over the frequency range of interest. The same is true for the confidence intervals of the measured and predicted resistance at near-resonance frequencies, but the predicted resistance confidence intervals are lower than the measured resistance confidence intervals (no overlap) at frequencies away from resonance. A sensitivity analysis indicates the discharge coefficient uncertainty is the major contributor to uncertainty in the predicted impedances for the perforate-over-honeycomb liner used in this study. This insight regarding the relative importance of each input parameter will be used to guide the design of experiments with test rigs currently being brought on-line at NASA Langley.

Jones, M. G.↗

NASA NTRS2015

Wind Magnetic Clouds for 2010-2012: Model Parameter Fittings, Associated Shock Waves, and Comparisons to Earlier Periods

We fitted the parameters of magnetic clouds (MCs) as identified in the Wind spacecraft data from early 2010 to the end of 2012 using the model of Lepping, Jones, and Burlaga (J. Geophys. Res. 95, 1195, 1990). The interval contains 48 MCs and 39 magnetic cloud-like (MCL) events. This work is a continuation of MC model fittings of the earlier Wind sets, including those in a recent publication, which covers 2007 to 2009. This period (2010 - 2012) mainly covers the maximum portion of Solar Cycle 24. Between the previous and current interval, we document 5.7 years of MCs observations. For this interval, the occurrence frequency of MCs markedly increased in the last third of the time. In addition, over approximately the last six years, the MC type (i.e. the profile of the magnetic-field direction within an MC, such as North-to-South, South-to-North, all South) dramatically evolved to mainly North-to-South types when compared to earlier years. Furthermore, this evolution of MC type is consistent with global solar magnetic-field changes predicted by Bothmer and Rust (Coronal Mass Ejections, 139, 1997). Model fit parameters for the MCs are listed for 2010 - 2012. For the 5.7 year interval, the observed MCs are found to be slower, weaker in estimated axial magnetic-field intensity, and shorter in duration than those of the earlier 12.3 years, yielding much lower axial magnetic-field fluxes. For about the first half of this 5.7 year period, i.e. up to the end of 2009, there were very few associated MC-driven shock waves (distinctly fewer than the long-term average of about 50 % of MCs). But since 2010, such driven shocks have increased markedly, reflecting similar statistics as the long-term averages. We estimate that 56 % of the total observed MCs have upstream shocks when the full interval of 1995 - 2012 is considered. However, only 28 % of the total number of MCLs have driven shocks over the same period. Some interplanetary shocks during the 2010 - 2012 interval are seen to apparently occur without an obvious MC-driver, probably indicating an encounter with a distant flank of a MC-driven shock. Some of these may be driven by a different kind of structure, however.

Magnetic clouds↗

NASA NTRS2019

Discovery of Activities via Statistical Clustering of Fixation Patterns

Human behavior often consists of a series of distinct activities, each characterized by a unique signature of visual behavior. This is true even in a restricted domain, such as piloting an aircraft, where patterns of visual signatures might represent activities like communicating, navigating, and monitoring. We propose a novel analysis method for gaze-tracking data, to perform blind discovery of these activities based on their behavioral signatures. The method is in some respects similar to recurrence analysis, but here we compare not individual fixations, but groups of fixations aggregated over a fixed time interval. The duration of this interval is a parameter that we will refer to as τ. We assume that the environment has been divided into a set of N different areas-of-interest (AOIs). For a given interval of time of duration τ, we compute the proportion of time spent fixating each AOI, resulting in an N-dimensional vector. These proportions can be converted to counts by multiplying by τ divided by the average fixation duration (another parameter that we fix at 280 milliseconds). We compare different intervals by computing the chi-square statistic. The p-value associated with the statistic is the likelihood of observing the data under the hypothesis that the data in the two intervals were generated by a single process with a single set of probabilities governing the fixation of each AOI. We have investigated the method using a set of 10 synthetic "activities," that sample 4 AOIs. Four of these activities visit 3 of the 4 AOIs, with equal probability; as there are four different ways to leave-one- out, there are four such activities. Similarly, there are six different activities that leave-two-out. Sequences of simulated behavior were generated by running each activity for 40 seconds, in sequence, for a total of 6.7 minutes. The figure to the right shows the matrix of chi-square statistics, using a value of 2.8 seconds for τ, corresponding to 10 fixations. Low values (dark) indicate poor evidence for activity differences, while high values (bright) indicate strong evidence. The dark squares along the main diagonal each correspond to the forty second intervals in which the activity was held constant; the 4x4 block at the lower left corresponds to the four leave-one-out activities, while the 6x6 block in the upper right corresponds to the leave-two-out activities. (The anti-diagonal pattern of white squares indicates those activity pairs that share no AOIs.) The chi-square values can be binarized by choosing a particular significance level; we are interested in grouping bins that represent the same activity, effectively accepting the null hypothesis. Therefore, we may adopt a relatively lax criterion; for example, choosing a p-value of 0.2 means that two behaviors that have only a 1-in-5 chance of being produced by a single activity might nevertheless be clustered together. We have explored several methods to perform clustering on the data and solving for the activity probabilities. Greedy methods begin by selecting the time bin that is similar to the most (or least) other bins, and then forming a cluster from it and all other non-discriminable bins. These methods show mediocre performance, as they do not take into account temporal contiguity. Preliminary results indicate that methods that "grow" clusters in time from seed points perform better.

activity analysis↗

NASA NTRS2022

Patches of Magnetic Switchbacks and Their Origins

Parker Solar Probe (PSP) has shown that the solar wind in the inner heliosphere is characterized by the quasi omnipresence of magnetic switchbacks ("switchback" hereinafter), local backward bends of magnetic field lines. Switchbacks also tend to come in patches, with a large-scale modulation that appears to have a spatial scale size comparable to supergranulation on the Sun. Here we inspect data from the first 10 encounters of PSP focusing on different time intervals when clear switchback patches were observed by PSP. We show that the switchbacks modulation, on a timescale of several hours, seems to be independent of whether PSP is near perihelion, when it rapidly traverses large swaths of longitude remaining at the same heliocentric distance, or near the radial-scan part of its orbit, when PSP hovers over the same longitude on the Sun while rapidly moving radially inwards or outwards. This implies that switchback patches must also have an intrinsically temporal modulation most probably originating at the Sun. Between two consecutive patches, the magnetic field is usually very quiescent with weak fluctuations. We compare various parameters between the quiescent intervals and the switchback intervals. The results show that the quiescent intervals are typically less Alfvénic than switchback intervals, and the magnetic power spectrum is usually shallower in quiescent intervals. We propose that the temporal modulation of switchback patches may be related to the "breathing" of emerging flux that appears in images as the formation of "bubbles" below prominences in the Hinode/SOT observations.

Solar wind↗

NASA NTRS2025

Components Refurbishment and Chemical Analysis Facility, SWMU #041 - Per- and Polyfluoroalkyl Substances Site Assessment Report Kennedy Space Center, Florida

This PFAS Site Assessment (SA) Report presents the activities and results associated with PFAS investigations at the Components Refurbishment and Chemical Analysis (CRCA) facility located at Kennedy Space Center (KSC), Florida. In 2022, CRCA was identified as an Area of Potential Concern because the facility stores several potential PFAS-containing chemicals. A groundwater sample collected from an onsite monitoring well detected PFOA and PFOS at concentrations greater than State of Florida provisional Groundwater Cleanup Target Levels (pGCTLs). PFAS SA activities were conducted between March 2022 and February 2024. During this timeframe, a total of 16 direct-push technology (DPT) locations and 82 discrete samples were collected from these locations, along with 90 monitoring well samples. The analytical data screening process focused on State of Florida pGCTLs and United States Environmental Protection Agency (USEPA) Regional Screening Level (RSLs) from November 2023 to evaluate the data. Analytical results identified PFOS, PFOA, and PFBA at concentrations exceeding their respective RSLs at each depth interval (shallow, intermediate, and deep). PFOS and PFOA had the largest footprint of RSL exceedances in each depth interval, but pGCTL exceedances were only observed at limited locations in the shallow and intermediate intervals. PFBA had the highest detections of any PFAS compound, with concentrations exceeding 180,000 nanograms per liter (ng/L), which is 100-times the RSL of 1,800 ng/L in the shallow and intermediate intervals and 10-times the RSL in the deep interval. The maximum PFBA detection was 841,000 ng/L at shallow monitoring well, MW0006. The PFAS SA also included samples collected from the onsite hydraulic containment system (HCS) which was installed to control and treat the onsite chlorinated volatile organic compound (CVOC) plume. Influent and effluent aqueous samples were collected monthly from the system. PFAS concentrations were relatively the same for both influent and effluent samples, indicating that while the HCS has been effective for CVOC treatment, it does not provide any additional treatment for PFAS compounds. Since the HCS has achieved its objectives, the system was shut down in December 2024. PFAS data gaps still exist, to include surface water and soil, which were not sampled during this SA. Soil sampling near the Chemical Process Area is recommended. Surface water and soil sampling at select stormwater outfalls is also recommended. Additionally, further groundwater sampling is recommended (DPT and monitoring well) in all depth intervals to delineate the extent of PFAS impacts at CRCA.

K Alex Murphy↗