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NASA NTRS2002

Long-term Trends in Interplanetary Magnetic Field Strength and Solar Wind Structure during the 20th Century

Lockwood et al have recently reported an approximately 40% increase in the radial component of the interplanetary magnetic field (IMF) at Earth between 1964 and 1996. We argue that this increase does not constitute a secular trend but is largely the consequence of lower than average fields during solar cycle 20 (1964-1976) in comparison with surrounding cycles. For times after 1976 the average IMF strength has actually decreased slightly. Examination of the cosmic ray intensity, an indirect measure of the IMF strength, over the last five solar cycles (19-23) also indicates that cycle averages of the IMF strength have been relatively constant since approximately 1954. We also consider the origin of the well-documented increase in the geomagnetic alphaalpha index that occurred primarily during the first half of the twentieth century. We surmise that the coronal mass ejection (CME) rate for recent solar cycles was approximately twice as high as that for solar cycles 100 years ago. However, this change in the CME rate and the accompanying increase in 27-day recurrent storm activity reported by others are unable to account completely for the increase in alphaalpha. Rather, the CMEs and recurrent high-speed streams at the beginning of the twentieth century must have been embedded in a background of slow solar wind that was less geoeffective (having, for example, lower IMF strength and/or flow speed) than its modern counterpart.

Richardson, I. G.↗
NASA NTRS2003

Importance of mitral valve repair associated with left ventricular reconstruction for patients with ischemic cardiomyopathy: a real-time three-dimensional echocardiographic study

BACKGROUND: Left ventricular (LV) reconstruction surgery leads to early improvement in LV function in ischemic cardiomyopathy (ICM) patients. This study was designed to evaluate the impact of mitral valve (MV) repair associated with LV reconstruction on LV function 1-year after surgery in ICM patients assessed by real-time 3-dimensional echocardiography (3DE). METHODS AND RESULTS: Sixty ICM patients who underwent the combination surgery (LV reconstruction in 60, MV repair in 30, and revascularization in 52 patients) were studied. Real-time 3DE was performed and LV volumes were obtained at baseline, discharge, 6-month and >or=12-month follow-up. Reduction in end-diastolic volumes (EDV) by 29% and in end-systolic volumes by 38% were demonstrated immediately after surgery and remained at subsequent follow-up (P<0.0001). The LV ejection fraction significantly increased by about 10% at discharge and was maintained >or=12-month (P<0.0001). Although the LV volumes were significantly larger in patients with MV repair before surgery (EDV, 235+/-87 mL versus 193+/-67 mL, P<0.05), they were similar to LV volumes of the patients without MV repair at subsequent follow-ups. However, the EDV increased from 139+/-24 mL to 227+/-79 mL (P<0.01) in 7 patients with recurrent mitral regurgitation (MR). Improvement in New York Heart Association functional class occurred in 81% patients during late follow-up. CONCLUSIONS: Real-time 3DE demonstrates that LV reconstruction provides significant reduction in LV volumes and improvement in LV function which is sustained throughout the 1-year follow-up with 84% cardiac event free survival. If successful, MV repair may prevent LV redilation, while recurrent MR is associated with increased LV volumes.

Clinical Trial↗
NASA NTRS2005

Outbursts in Symbiotic Binaries

A major question for symbiotic stars concerns the nature and cause of their outbursts. A small subset of symbiotics, the slow novae are fairly well established as thermonuclear events that last on the order of decades. The several symbiotic recurrent novae, which are much shorter and last on the order of months, are also thought to be thermonuclear runaways. Yet the majority of symbiotics are neither slow novae nor recurrent novae. These are the so-called classical symbiotics, many of which show outbursts whose cause is not well understood. In some cases, jets are produced in association with an outburst, therefore an investigation into the causes of outbursts will yield important insights into the production of collimated outflows. To investigate the cause and nature of classical symbiotic outbursts, we initiated a program of multiwavelength observations of these events. In FUSE Cycle 2, we obtained six observational epochs of the 2000-2002 classic symbiotic outburst in the first target of our campaign - class prototype, Z Andromedae. That program was part of a coordinated multi-wavelength Target-of-Opportunity (TOO) campaign with FUSE, XMM, Chandra, MERLIN, the VLA, and ground-based spectroscopic and high time-resolution photometric observations. Our campaign proved the concept, utility, and need for coordinated multi-wavelength observations in order to make progress in understanding the nature of the outburst mechanisms in symbiotic stars. Indeed, the FUSE data were the cornerstone of this project

Sonneborn, George↗
NASA NTRS2005

Outbursts in Symbiotic Binaries: Z and Continued Observation

A major question for symbiotic stars concerns the nature and cause of their outbursts. A small subset of symbiotics, the "slow novae" are fairly well established as thermonuclear events that last on the order of decades. The several symbiotic "recurrent novae", which are much shorter and last on the order of months, are also thought to be thermonuclear runaways. Yet the majority of symbiotics are neither slow novae nor recurrent novae. These are the so-called "classical symbiotics," many of which show outbursts whose cause is not well understood. In some cases, jets are produced in association with an outburst, therefore an investigation into the causes of outbursts will yield important insights into the production of collimated outflows. To investigate the cause and nature of classical symbiotic outbursts, we initiated a program of multi- wavelength observations of these events. First of all in FUSE Cycle 2, we obtained six observational epochs of the 2000-2002 classic symbiotic outburst in the first target of our campaign - class prototype, Z Andromedae. That program was part of a coordinated multi-wavelength Target-of-Opportunity (TOO) campaign with FUSE, XMM, Chandra, MERLIN, the VLA, and ground-based spectroscopic and high time-resolution photometric observations. Our campaign proved the concept, utility, and need for coordinated multi-wavelength observations in order to make progress in understanding the nature of the outburst mechanisms in symbiotic stars. Indeed, the FUSE data were the cornerstone of this project. The present program is a continuation of that cycle 2 effort. Indeed, the observations acquired in this program are vital to the proper interpretation of the material acquired in cycle 2 as the new data cover the critical time period when the star continues to decline from outburst and actually returns to quiescence. The utilization of these data have allowed us to refine and complete description of our new model for classical symbiotic system outbursts.

Sonneborn, George↗
NASA NTRS2004

Cluster observations of quasi-periodic impulsive signatures in the dayside northern lobe: High-latitude flux transfer events?

We report on a series of quasi-periodic reversals in GSM B(sub Z) observed by the four Cluster spacecraft in the northern dayside lobe poleward of the cusp on 23 February 2001. During an interval of about 35 min, multiple reversals (negative to positive) in B(sub Z) of approximately 1-min duration with an approximate 8-min recurrence time were observed. The individual structures do not resemble low-latitude flux transfer events (FTE) [Russell and Elphic, 1979] but the 8-min recurrence frequency suggests that intermittent reconnection may be occurring .Measurements (appropriately lagged) of the solar wind at ACE show that the IMF was southward-oriented with a strong B(sub X) and that a modest dynamic pressure increased as the events started. The multi-point observations afforded by the Cluster spacecraft were used to infer the motion (direction and speed) of the observed magnetic field reversals. The associated currents were also calculated and they are consistent with the spatial confinement of the observed magnetic field reversals. We propose that the observed reversals are due to flux tubes reconnecting with closed field lines on the dayside. Ancillary data from the Cluster Ion Spectrometry (CIS) and Plasma Electron And Current Experiment (PEACE) instruments were used to develop a physical picture of the reversals.

Thompson, S. M.↗
NASA NTRS2007

IMP 8 GME Particle Observations Over Three Solar Cycles

The Goddard Medium Energy experiment on the IMP 8 spacecraft has made nearly continuous observations of the near-Earth energetic particle environment from its launch in October, 1973 until near present. We summarize several aspects of these observations, including solar energetic particle events, CIR-associated events, and cosmic ray modulations. In particular, we note that, as expected fiom the pattern of smaller recurrent (27 day) cosmic ray modulations seen in the mid 1980's A less than 0 solar minimum compared to the previous and following (A greater than 0) minima, recurrent modulations are again reduced in the current solar minimum.

Richardson, Ian↗
NASA NTRS2008

Spatial and Alignment Analyses for a field of Small Volcanic Vents South of Pavonis Mons Mars

The Tharsis province of Mars displays a variety of small volcanic vent (10s krn in diameter) morphologies. These features were identified in Mariner and Viking images [1-4], and Mars Orbiter Laser Altimeter (MOLA) data show them to be more abundant than originally observed [5,6]. Recent studies are classifying their diverse morphologies [7-9]. Building on this work, we are mapping the location of small volcanic vents (small-vents) in the Tharsis province using MOLA, Thermal Emission Imaging System, and High Resolution Stereo Camera data [10]. Here we report on a preliminary study of the spatial and alignment relationships between small-vents south of Pavonis Mons, as determined by nearest neighbor and two-point azimuth statistical analyses. Terrestrial monogenetic volcanic fields display four fundamental characteristics: 1) recurrence rates of eruptions,2 ) vent abundance, 3) vent distribution, and 4) tectonic relationships [11]. While understanding recurrence rates typically requires field measurements, insight into vent abundance, distribution, and tectonic relationships can be established by mapping of remotely sensed data, and subsequent application of spatial statistical studies [11,12], the goal of which is to link the distribution of vents to causal processes.

Bleacher, J. E.↗
NASA NTRS2011

Magnetotail Reconnection and Flux Circulation: Jupiter and Saturn Compared

The Jovian magnetosphere has been visited by eight spacecraft, and the magnetometer data have been used to identify dozens of plasmoids and ~250 field dipolarizations associated with magnetic reconnection in the tail [e.g. Vogt et al., 2010]. Since the arrival of the Cassini spacecraft at Saturn in 2004, the magnetometer instrument has also been used to identify reconnection signatures. The deepest magnetotail orbits were in 2006, and during this time 34 signatures of plasmoids were identified. In this study we compare the statistical properties of plasmoids at Jupiter and Saturn such as duration, size, location, and recurrence period. Such parameters can be influenced by many factors, including the different Dungey cycle timescales and cross-magnetospheric potential drops at the two planets. We present superposed epoch analyses of plasmoids at the two planets to determine their average properties and to infer their role in the reconfiguration of the nightside of the magnetosphere. We examine the contributions of plasmoids to the magnetic flux transfer cycle at both planets. At Jupiter, there is evidence of an extended interval after reconnection where the field remains northward (analogous to the terrestrial post-plasmoid plasma sheet). At Saturn we see a similar feature, and calculate the amount of flux closed on average in reconnection events, leading us to an estimation of the recurrence rate of plasmoid release.

Jackman, C. M.↗
NASA NTRS2011

Cassini Observations of Plasmoid Structure and Dynamics: Implications for the Role of Magnetic Reconnection in Magnetospheric Circulation at Saturn

We survey the Cassini magnetometer data during the deep tail orbits in 2006, and find 34 direct encounters with plasmoids. They occur as single, isolated events but also in groups of two or more plasmoids as is frequently observed at Earth . We show a case study example of three such plasmoids over three hours, where we estimate an upper limit of 5.68 GWb of flux closure, and derive a reconnection rate over this interval of 526 kV. We show the results of a superposed epoch analysis of al1 34 plasmoids indicating that, on average, plasmoids at Saturn are approix.8 min in duration and they tend toward a loop-like, as opposed to flux rope-like topology, with little or no axial core magnetic field. Our analysis shows that plasmoids at Saturn are followed by an extended interval of the post-plasmoid plasma sheet (PPPS) lasting approx.58 min. The average open magnetic flux disconnected by the continued reconnet:tion following plasmoid formation that creates the PPPS is approx.3 GWb. We calculate expected recurrence rates for plasmoids, and compare these with a derived observational recurrence rate of one plasmoid every approx.2.4 days, explaining the reasons why the spacecraft has not observed as many plasmoids as we predict will be released. We conclude that the Cassini magnetometer measurements require a combination of Vasyliunas-type closed-flux plasma sheet and Dungey-type open-flux lobe reconnection to account for the observed properties of the plasmoids and PPPS in Saturn's magnetotail.

Jackman, C. M.↗
NASA NTRS2015

Constraining the Physics of AM Canum Venaticorum Systems with the Accretion Disk Instability Model

Recent work by Levitan et al. has expanded the long-term photometric database for AM CVn stars. In particular, their outburst properties are well correlated with orbital period and allow constraints to be placed on the secular mass transfer rate between secondary and primary if one adopts the disk instability model for the outbursts. We use the observed range of outbursting behavior for AM CVn systems as a function of orbital period to place a constraint on mass transfer rate versus orbital period. We infer a rate approximately 5 x 10(exp -9) solar mass yr(exp -1) ((P(sub orb)/1000 s)(exp -5.2)). We show that the functional form so obtained is consistent with the recurrence time-orbital period relation found by Levitan et al. using a simple theory for the recurrence time. Also, we predict that their steep dependence of outburst duration on orbital period will flatten considerably once the longer orbital period systems have more complete observations.

accretion↗
NASA NTRS2021

The X-ray Bursts of XTE J1739-285: A NICER Sample

In this work, we report on observations with the Neutron Star Interior Composition Explorer of the known neutron star X-ray transient XTE J1739–285. We observed the source in 2020 February and March, finding it in a highly active bursting state. Across a 20 day period, we detected 32 thermonuclear X-ray bursts, with an average burst recurrence time of-+2.0 hr0.30.4. A timing and spectral analysis of the ensemble of X-ray bursts reveals homogeneous burst properties, evidence for short-recurrence time bursts, and the detection of a 386.5 Hz burst oscillation candidate. The latter is especially notable, given that a previous study of this source claimed a 1122 Hz burst oscillation candidate. We did not find any evidence of variability near 1122 Hz and instead find that the 386.5 Hz oscillation is the more prominent signal of the two burst oscillation candidates. Hence, we conclude it is unlikely that XTE J1739–285 has a submillisecond rotation period.

X-ray burst↗
NASA NTRS2022

A Generalized Approach to Aircraft Trajectory Prediction via Supervised Deep Learning

As research advances diverse forms and missions of aircraft, the National Airspace System (NAS) will become increasingly crowded, limiting current communications resources to accommodate aviation operations. Ongoing research proposes a paradigm of airspace communications, such that resources are autonomously and dynamically allocated via intelligent agents; this allocation requires accurate representations of the NAS, including the predicted positions of aircraft. State-of-the-art research emphasizes the importance of a hybrid-recurrent framework for trajectory prediction and compares the impact of commonly considered weather data on prediction accuracy. However, current research has been limited in its scope of efforts, frequently utilizing a unique flight route, architecture, set of weather data, and date range. This article considers the challenges of generalizing hybrid-recurrent predictive models for flight trajectories. Results illustrate an increase in error variance when identical models are trained over a generalized set of flights; this may be mitigated with careful tuning of hyperparameters, both in the network structure and optimization algorithms. Even so, an irreducible vertical error was identified, resulting from the complex takeoff and landing procedures which can not be correlated to functions of weather or additional assumptions of aircraft behavior. Finally, the use of a test route indicates that generalized models still do not possess sufficient knowledge for general aircraft predictions, with mean error increases ranging from 70-500%. These results illustrate the need for continued efforts on improving model versatility, as well as potential limitations for spectrum allocation near airports and other centers.

Nathan Schimpf↗
NASA NTRS1994

Citrate and renal calculi: an update

Citrate is an inhibitor of the crystallization of stone-forming calcium salts. Hypocitraturia, frequently encountered in patients with nephrolithiasis, is therefore an important risk factor for stone formation. Potassium citrate provides physiological and physicochemical correction and inhibits new stone formation, not only in hypocitraturic calcium nephrolithiasis but also in uric acid nephrolithiasis. Inhibition of stone recurrence has now been validated by a randomized trial. Ongoing research has disclosed additional causes of hypocitraturia (sodium excess, low intestinal alkali absorption, but not primary citrate malabsorption). Moreover, new insights on potassium citrate action have been shown, notably that some of absorbed citrate escapes oxidation and contributes to the citraturic response, that ingestion with a meal does not sacrifice physiological or physicochemical action, that orange juice mimics but does not completely duplicate its actions, that potassium citrate may have a beneficial bone-sparing effect, that it may reduce stone fragments following ESWL, and that danger of aluminum toxicity is not great in subjects with functioning kidneys. Finally, the research on potassium citrate has led to two promising products, calcium citrate as an optimum calcium supplement and potassium-magnesium citrate which may be superior to potassium citrate in the management of stone disease.

NASA Discipline Regulatory Physiology↗
NASA NTRSDate not supplied

Predicting Adverse Events and their Precursors in Aviation Using Multi-Class Multiple-Instance Learning

In recent years, there has been a rapid growth in the application of machine learning techniques that leverage aviation data collected from commercial airline operations to improve safety. Anomaly detection and predictive maintenance have been the main targets for machine learning applications. However, this paper focuses on the identification of precursors, which is a relatively newer application. Precursors are events correlated with adverse events that happen prior to the adverse event itself. Therefore, precursor mining provides many benefits including understanding the reasons behind a safety incident and the ability to identify signatures, which can be tracked throughout a flight to alert the operators of an potential upcoming adverse event. This work proposes using the multiple-instance learning (MIL) framework, a weakly supervised learning task, combined with a carefully designed Multi-Head Convolutional Neural Networks-Recurrent Neural Networks (MHCNN-RNN) architecture to predict different type of adverse events for any given flights and identify their precursors with little to no post-processing.Results obtained show that the MHCNN-RNN is able to accurately forecast high speed and high path angle events during the approach, and that it is also capable of determining the aircraft’s parameters that are correlated to these events. These parameters can be considered precursors to the events.

multiple instance learning↗
NASA NTRS2021

DroughtCast: A Machine Learning Forecast of the United States Drought Monitor

Drought is one of the most ecologically and economically devastating natural phenomena affecting the United States, causing the U.S. economy billions of dollars in damage, and driving widespread degradation of ecosystem health. Many drought indices are implemented to monitor the current extent and status of drought so stakeholders such as farmers and local governments can appropriately respond. Methods toforecast drought conditions weeks to months in advance are less common but would provide a more effective early warning system to enhance drought response, mitigation, and adaptation planning. To resolve this issue, we introduce DroughtCast, a machine learning framework for forecasting the United States Drought Monitor (USDM). DroughtCast operates on the knowledge that recent anomalies in hydrology and meteorology drive future changes in drought conditions. We use simulated meteorology and satellite observed soil moisture as inputs into a recurrent neural network to accurately forecast the USDM between 1 and 12 weeks into the future. Our analysis shows that precipitation, soil moisture, and temperature are the most important input variables when forecasting future drought conditions. Additionally, a case study of the 2017 Northern Plains Flash Drought shows that DroughtCast was able to forecast a very extreme drought event up to 12 weeks before its onset. Given the favorable forecasting skill of the model, DroughtCast may provide a promising tool for land managers and local governments in preparing for and mitigating the effects of drought.

Machine Learning↗
NASA NTRS2020

Amino Acid Encoding for Deep Learning Applications

Background: The number of applications of deep learning algorithms in bioinformatics is increasing as they usually achieve superior performance over classical approaches, especially, when bigger training datasets are available. In deep learning applications, discrete data, e.g. words or n-grams in language, or amino acids or nucleotides in bioinformatics, are generally represented as a continuous vector through an embedding matrix. Recently, learning this embedding matrix directly from the data as part of the continuous iteration of the model to optimize the target prediction – a process called ‘end-to-end learning’ – has led to state-of-the-art results in many fields. Although usage of embeddings is well described in the bioinformatics literature, the potential of end-to-end learning for single amino acids, as compared to more classical manually-curated encoding strategies, has not been systematically addressed. To this end, we compared classical encoding matrices, namely one-hot, VHSE8 and BLOSUM62, to end-to-end learning of amino acid embeddings for two different prediction tasks using three widely used architectures, namely recurrent neural networks (RNN), convolutional neural networks (CNN), and the hybrid CNN-RNN. Results: By using different deep learning architectures, we show that end-to-end learning is on par with classical encodings for embeddings of the same dimension even when limited training data is available, and might allow for a reduction in the embedding dimension without performance loss, which is critical when deploying the models to devices with limited computational capacities. We found that the embedding dimension is a major factor in controlling the model performance. Surprisingly, we observed that deep learning models are capable of learning from random vectors of appropriate dimension. Conclusion: Our study shows that end-to-end learning is a flexible and powerful method for amino acid encoding. Further, due to the flexibility of deep learning systems, amino acid encoding schemes should be benchmarked against random vectors of the same dimension to disentangle the information content provided by the encoding scheme from the distinguishability effect provided by the scheme.

Deep-learning↗