4,875 research outputs found
Myocardial Architecture and Patient Variability in Clinical Patterns of Atrial Fibrillation
Atrial fibrillation (AF) increases the risk of stroke by a factor of four to
five and is the most common abnormal heart rhythm. The progression of AF with
age, from short self-terminating episodes to persistence, varies between
individuals and is poorly understood. An inability to understand and predict
variation in AF progression has resulted in less patient-specific therapy.
Likewise, it has been a challenge to relate the microstructural features of
heart muscle tissue (myocardial architecture) with the emergent temporal
clinical patterns of AF. We use a simple model of activation wavefront
propagation on an anisotropic structure, mimicking heart muscle tissue, to show
how variation in AF behaviour arises naturally from microstructural differences
between individuals. We show that the stochastic nature of progressive
transversal uncoupling of muscle strands (e.g., due to fibrosis or gap
junctional remodelling), as occurs with age, results in variability in AF
episode onset time, frequency, duration, burden and progression between
individuals. This is consistent with clinical observations. The uncoupling of
muscle strands can cause critical architectural patterns in the myocardium.
These critical patterns anchor micro-re-entrant wavefronts and thereby trigger
AF. It is the number of local critical patterns of uncoupling as opposed to
global uncoupling that determines AF progression. This insight may eventually
lead to patient specific therapy when it becomes possible to observe the
cellular structure of a patient's heart.Comment: 5 pages, 4 figures. For supplementary materials please contact Kishan
A. Manani at [email protected]
Thermal Testing and Model Correlation of the Magnetospheric Multiscale (MMS) Observatories
International Conference on Envronmental Systems (ICES), Seattle WA NCTS 20964-15. The Magnetospheric Multiscale (MMS) mission is a Solar Terrestrial Probes mission comprising four identically instrumented spacecraft that will use Earths magnetosphere as a laboratory tostudy the microphysics of three fundamental plasma processes: magnetic reconnection, energetic particle acceleration, and turbulence. This paper presents the complete thermal balance (TB) test performed on the first of four observatories to go through thermal vacuum (TV) and the minibalance testing that was performed on the subsequent observatories to provide a comparison of all four. The TV and TB tests were conducted in a thermal vacuum chamber at the Naval Research Laboratory (NRL) in Washington, D.C. with the vacuum level higher than 1.3 x 10-4 Pa (10-6 torr)and the surrounding temperature achieving -180 C. Three TB test cases were performed that included hot operational science, cold operational science and a cold survival case. In addition to the three balance cases a two hour eclipse and a four hour eclipse simulation was performed during the TV test to provide additional transient data points that represent the orbit in eclipse (or Earth's shadow) The goal was to perform testing such that the flight orbital environments could be simulated as closely as possible. A thermal model correlation between the thermal analysis and the test results was completed. Over 400 1-Wire temperature sensors, 200 thermocouples and 125 flight thermistor temperature sensors recorded data during TV and TB testing. These temperatureversus time profiles and their agreements with the analytical results obtained using Thermal Desktop and SINDAFLUINT are discussed. The model correlation for the thermal mathematical model (TMM) is conducted based on the numerical analysis results and the test data. The philosophy of model correlation was to correlate the model to within 3 C of the test data using the standard deviation and mean deviation error calculation. Individual temperature error goal is to be within 5 C and the heater power goal is to be within 5 of test data. The results of the model correlation are discussed and the effect of some material and interface parameters on the temperature profiles are presented
Thermal Testing and Model Correlation of the Magnetospheric Multiscale (MMS) Observatories
The Magnetospheric Multiscale (MMS) mission is a Solar Terrestrial Probes mission comprising four identically instrumented spacecraft that will use Earth's magnetosphere as a laboratory to study the microphysics of three fundamental plasma processes: magnetic reconnection, energetic particle acceleration, and turbulence. This paper presents the complete thermal balance (TB) test performed on the first of four observatories to go through thermal vacuum (TV) and the minibalance testing that was performed on the subsequent observatories to provide a comparison of all four. The TV and TB tests were conducted in a thermal vacuum chamber at the Naval Research Laboratory (NRL) in Washington, D.C. with the vacuum level higher than 1.3 x 10 (sup -4) pascals (10 (sup -6) torr) and the surrounding temperature achieving -180 degrees Centigrade. Three TB test cases were performed that included hot operational science, cold operational science and a cold survival case. In addition to the three balance cases a two hour eclipse and a four hour eclipse simulation was performed during the TV test to provide additional transient data points that represent the orbit in eclipse (or Earth's shadow) The goal was to perform testing such that the flight orbital environments could be simulated as closely as possible. A thermal model correlation between the thermal analysis and the test results was completed. Over 400 1-Wire temperature sensors, 200 thermocouples and 125 flight thermistor temperature sensors recorded data during TV and TB testing. These temperature versus time profiles and their agreements with the analytical results obtained using Thermal Desktop and SINDA/FLUINT are discussed. The model correlation for the thermal mathematical model (TMM) is conducted based on the numerical analysis results and the test data. The philosophy of model correlation was to correlate the model to within 3 degrees Centigrade of the test data using the standard deviation and mean deviation error calculation. Individual temperature error goal is to be within 5 degrees Centigrade and the heater power goal is to be within 5 percent of test data. The results of the model correlation are discussed and the effect of some material and interface parameters on the temperature profiles are presented
A Simple Model for Identifying Critical Structures in Atrial Fibrillation
Atrial fibrillation (AF) is the most common abnormal heart rhythm and the
single biggest cause of stroke. Ablation, destroying regions of the atria, is
applied largely empirically and can be curative but with a disappointing
clinical success rate. We design a simple model of activation wavefront
propagation on a structure mimicking the branching network architecture of
heart muscle and show how AF emerges spontaneously as age-related parameters
change. We identify regions responsible for the initiation and maintenance of
AF, the ablation of which terminates AF. The simplicity of the model allows us
to calculate analytically the risk of arrhythmia. This analytical result allows
us to locate the transition in parameter space and highlights that the
transition from regular to fibrillatory behaviour is a finite-size effect
present in systems of any size. These clinically testable predictions might
inform ablation therapies and arrhythmic risk assessment.Comment: 5 pages, 4 figures. For supplementary materials please contact Kishan
A. Manani at [email protected]
The 2016 Reactivations of Main-Belt Comets 238P/Read and 288P/(300163) 2006 VW139
We report observations of the reactivations of main-belt comets 238P/Read and
288P/(300163) 2006 VW139, that also track the evolution of each object's
activity over several months in 2016 and 2017. We additionally identify and
analyze archival SDSS data showing 288P to be active in 2000, meaning that both
238P and 288P have now each been confirmed to be active near perihelion on
three separate occasions. From data obtained of 288P from 2012-2015 when it
appeared inactive, we find best-fit R-band H,G phase function parameters of
H_R=16.80+/-0.12 mag and G_R=0.18+/-0.11, corresponding to effective component
radii of r_c=0.80+/-0.04 km, assuming a binary system with equally-sized
components. Fitting linear functions to ejected dust masses inferred for 238P
and 288P soon after their observed reactivations in 2016, we find an initial
average net dust production rate of 0.7+/-0.3 kg/s and a best-fit start date of
2016 March 11 (when the object was at a true anomaly of -63 deg) for 238P, and
an initial average net dust production rate of 5.6+/-0.7 kg/s and a best-fit
start date of 2016 August 5 (when the object was at a true anomaly of -27 deg)
for 288P. Applying similar analyses to archival data, we find similar start
points for previous active episodes for both objects, suggesting that minimal
mantle growth or ice recession occurred between the active episodes in
question. Some changes in dust production rates between active episodes are
detected, however. More detailed dust modeling is suggested to further clarify
the process of activity evolution in main-belt comets.Comment: 21 pages, 9 figures, accepted by A
MalwareDNA: Simultaneous Classification of Malware, Malware Families, and Novel Malware
Malware is one of the most dangerous and costly cyber threats to national
security and a crucial factor in modern cyber-space. However, the adoption of
machine learning (ML) based solutions against malware threats has been
relatively slow. Shortcomings in the existing ML approaches are likely
contributing to this problem. The majority of current ML approaches ignore
real-world challenges such as the detection of novel malware. In addition,
proposed ML approaches are often designed either for malware/benign-ware
classification or malware family classification. Here we introduce and showcase
preliminary capabilities of a new method that can perform precise
identification of novel malware families, while also unifying the capability
for malware/benign-ware classification and malware family classification into a
single framework.Comment: Accepted at IEEE ISI 202
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