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At least 289 records · Page 16

Mechanosensitive channels of Escherichia coli: the MscL gene, protein, and activities

Although mechanosensory responses are ubiquitous and diverse, the molecular bases of mechanosensation in most cases remain mysterious MscL, a mechanosensitive channel of large conductance of Escherichia coli and its bacterial homologues are the first and currently only channel molecules shown to directly sense mechanical stretch of the membrane. In response to the tension conveyed via the lipid bilayer, MscL increases its open probability by several orders of magnitude. In the present review we describe the identification, cloning, and first sets of biophysical and structural data on this simplest mechanosensory molecule. We discovered a 2.5-ns mechanosensitive conductance in giant E. coli spheroplasts. Using chromatographies to enrich the target and patch clamp to assay the channel activity in liposome-reconstituted fractions, we identified the MscL protein and cloned the mscL gene. MscL comprises 136 amino acid residues (15 kDa), with two highly hydrophobic regions, and resides in the inner membrane of the bacterium. PhoA-fusion experiments indicate that the protein spans the membrane twice with both termini in the cytoplasm. Spectroscopic techniques show that it is highly helical. Expression of MscL tandems and covalent cross-linking suggest that the active channel complex is a homo-hexamer. We have identified several residues, which when deleted or substituted, affect channel kinetics or mechanosensitivity. Although unique when discovered, highly conserved MscL homologues in both gram-negative and gram-positive bacteria have been found, suggesting their ubiquitous importance among bacteria.

Non-NASA Center↗

Luminous Binary Supersoft X-Ray Sources

One of the key accomplishments of the two preceding years was our development of an algorithm to select SSSs in external galaxies which have been observed by Chandra or XMM-Newton. By applying this algorithm to data from a number of galaxies, we discovered an extension of the class of SSSs to sources that are somewhat harder (100 - 300 eV, instead of tens of eV), but which are nevertheless much softer than canonical X-ray sources. We call these new sources quasisoft sources (QSSs). During this past year, we have built on and extended this work. We have (1) continued to identify SSSs and QSSs in external galaxies, (2) worked on models for the sources and find that black hole models seem promising for a subset of them, and (3) have studied individual systems, especially M101-ULX1. This special system has been observed as an SSS in its high &ate, with a luminosity in excess of 10(exp 41) erg/s. It has also been observed as a QSS when it is less luminous, and as a hard source in its low state. It is one of the best candidates to be an accreting intermediate-mass black hole. We have several papers in preparation. Below we list papers which are complete, including only new work and papers whose status has changed (e.g., been accepted for publication) since our last report. In addition, our work on QSSs has received some publicity. It was the subject of a Chandra press release and was picked up by several media outlets.

Oliversen, Ronald J.↗

CALIOP Version 3 Data Products: A Comparison to Version 2

After launch we discovered that the CALIOP daytime measurements were subject to thermally induced beamdrift,and this caused the calibration to vary by as much as 30% during the course of a single daytime orbit segment. Using an algorithm developed by Powell et al.(2010), empirically derived correction factors are now computed in near realtime as a function of orbit elapsed time, and these are used to compensate for the beam wandering effects.

Vaughan, Mark↗

The Kepler End-to-End Data Pipeline: From Photons to Far Away Worlds

The Kepler mission is described in overview and the Kepler technique for discovering exoplanets is discussed. The design and implementation of the Kepler spacecraft, tracing the data path from photons entering the telescope aperture through raw observation data transmitted to the ground operations team is described. The technical challenges of operating a large aperture photometer with an unprecedented 95 million pixel detector are addressed as well as the onboard technique for processing and reducing the large volume of data produced by the Kepler photometer. The technique and challenge of day-to-day mission operations that result in a very high percentage of time on target is discussed. This includes the day to day process for monitoring and managing the health of the spacecraft, the annual process for maintaining sun on the solar arrays while still keeping the telescope pointed at the fixed science target, the process for safely but rapidly returning to science operations after a spacecraft initiated safing event and the long term anomaly resolution process.The ground data processing pipeline, from the point that science data is received on the ground to the presentation of preliminary planetary candidates and supporting data to the science team for further evaluation is discussed. Ground management, control, exchange and storage of Kepler's large and growing data set is discussed as well as the process and techniques for removing noise sources and applying calibrations to intermediate data products.

data archiving↗

Use of Semantic Technology to Create Curated Data Albums

One of the continuing challenges in any Earth science investigation is the discovery and access of useful science content from the increasingly large volumes of Earth science data and related information available online. Current Earth science data systems are designed with the assumption that researchers access data primarily by instrument or geophysical parameter. Those who know exactly the data sets they need can obtain the specific files using these systems. However, in cases where researchers are interested in studying an event of research interest, they must manually assemble a variety of relevant data sets by searching the different distributed data systems. Consequently, there is a need to design and build specialized search and discover tools in Earth science that can filter through large volumes of distributed online data and information and only aggregate the relevant resources needed to support climatology and case studies. This paper presents a specialized search and discovery tool that automatically creates curated Data Albums. The tool was designed to enable key elements of the search process such as dynamic interaction and sense-making. The tool supports dynamic interaction via different modes of interactivity and visual presentation of information. The compilation of information and data into a Data Album is analogous to a shoebox within the sense-making framework. This tool automates most of the tedious information/data gathering tasks for researchers. Data curation by the tool is achieved via an ontology-based, relevancy ranking algorithm that filters out nonrelevant information and data. The curation enables better search results as compared to the simple keyword searches provided by existing data systems in Earth science.

Ramachandran, Rahul↗

Open Boundary Particle-in-Cell Simulation of Dipolarization Front Propagation

First results are presented from an ongoing open boundary 2-1/2D particle-in-cell simulation study of dipolarization front (DF) propagation in Earth's magnetotail. At this stage, this study is focused on the compression, or pileup, region preceding the DF current sheet. We find that the earthward acceleration of the plasma in this region is in general agreement with a recent DF force balance model. A gyrophase bunched reflected ion population at the leading edge of the pileup region is reflected by a normal electric field in the pileup region itself, rather than through an interaction with the current sheet. We discuss plasma wave activity at the leading edge of the pileup region that may be driven by gradients, or by reflected ions, or both; the mode has not been identified. The waves oscillate near but above the ion cyclotron frequency with wavelength several ion inertial lengths. We show that the waves oscillate primarily in the perpendicular magnetic field components, do not propagate along the background magnetic field, are right handed elliptically (close to circularly) polarized, exist in a region of high electron and ion beta, and are stationary in the plasma frame moving earthward. We discuss the possibility that the waves are present in plasma sheet data, but have not, thus far, been discovered.

dipolarization front↗

The Peculiar X-Ray Transient Swift J0840.7-3516: An Unusual Low-mass X-Ray Binary or a Tidal Disruption Event?

We report on the X-ray properties of the new transient Swift J0840.7−3516, discovered with Swift/BAT in 2020February, using extensive data from Swift, MAXI, NICER, and NuSTAR. The source flux increased for∼103safter the discovery, decayed rapidly over∼5 orders of magnitude in five days, and then remained almost constant over nine months. Large-amplitude short-term variations on timescales of 1–104s were observed throughout the decay. In the initial flux rise, the source showed a hard power-law-shaped spectrum with a photon index of∼1.0extending up to∼30 keV, above which an exponential cutoff was present. The photon index increased in the following rapid decay and became∼2 at the end of the decay. A spectral absorption feature at 3–4 keV was detected in the decay. It is not straightforward to explain all the observed properties by any known class of X-ray sources. We discuss the possible nature of the source, including a Galactic low-mass X-ray binary with multiple extreme properties and a tidal disruption event by a supermassive black hole or a Galactic neutron star.

Megumi Shidatsu↗

TOI-1231 b: A Temperate, Neptune-sized Planet Transiting the Nearby M3 Dwarf NLTT 24399

We report the discovery of a transiting, temperate, Neptune-sized exoplanet orbiting the nearby (d = 27.5 pc), M3V star TOI-1231 (NLTT 24399, L 248-27, 2MASS J10265947-5228099). The planet was detected using photometric data from the Transiting Exoplanet Survey Satellite and followed up with observations from the Las Cumbres Observatory and the Antarctica Search for Transiting ExoPlanets program. Combining the photometric data sets, we find that the newly discovered planet has a radius of 3.65(+0.16,-0.15)Rꚛ and an orbital period of 24.246 days. Radial velocity measurements obtained with the Planet Finder Spectrograph on the Magellan Clay telescope confirm the existence of the planet and lead to a mass measurement of 15.5 ± 3.3 Mꚛ. With an equilibrium temperature of just 330 K, TOI-1231 b is one of the coolest small planets accessible for atmospheric studies thus far, and its host star's bright near-infrared brightness (J = 8.88, Ks = 8.07) makes it an exciting target for the Hubble Space Telescope and the James Webb Space Telescope. Future atmospheric observations would enable the first comparative planetology efforts in the 250–350 K temperature regime via comparisons with K2-18 b. Furthermore, TOI-1231's high systemic radial velocity (70.5 km/s) may allow for the detection of low-velocity hydrogen atoms escaping the planet by Doppler, shifting the H i Lyα stellar emission away from the geocoronal and interstellar medium absorption features.

Jennifer A. Burt↗

An In-Time Aviation Safety Management System (IASMS) Concept of Operations for Part 139 Airports

Today’s airports are complex multi-faceted ecosystems. Currently, of the 517certificatedairports, 270arerequired to use safety management systems (SMSs) to identify and mitigate known hazards and emergent risks and to voluntarily share safety data with commercial operators and tenants. Airports manage a wide variety of hazards. These traffic hubs have direct responsibilities, such as removing foreign object debris from runways and taxiways and configuring runways to help prevent against incursions and tail strikes during takeoff. To ensure safety in the future NAS, the National Academies recommended an In-time Aviation Safety Management System (IASMS). An IASMS will employ services, functions, and capabilities (SFCs) to identify and mitigate hazards that are proactively and predictively managed based on data analytics of detected anomalies, precursors, and trends. SFCs would scale with airport complexity and environmental conditions using increasingly automated systems to respond proactively to hazards and, by using integrated data sources and predictive safety analytical methods, discover new, never before seen risks.

Ellis, K↗

In-Time Safety Management for Part 139 Airports

Today’s airports are complex multi-faceted ecosystems. Currently, of the 517 certificated airports, 270 are required to use safety management systems (SMSs) to identify and mitigate known hazards and emergent risks and to voluntarily share safety data with commercial operators and tenants. Airports manage a wide variety of hazards. These traffic hubs have direct responsibilities, such as removing foreign object debris from runways and taxiways and configuring runways to help prevent against incursions and tail strikes during takeoff. To ensure safety in the future NAS, the National Academies recommended an In-time Aviation Safety Management System (IASMS). An IASMS will employ services, functions, and capabilities (SFCs) to identify and mitigate hazards that are proactively and predictively managed based on data analytics of detected anomalies, precursors, and trends. SFCs would scale with airport complexity and environmental conditions using increasingly automated systems to respond proactively to hazards and, by using integrated data sources and predictive safety analytical methods, discover new, never before seen risks.

IASMS↗

Analyzing Source Apportioned Methane in Northern California During DISCOVER-AQ-CA Using Airborne Measurements and Model Simulations

This study analyzes source apportioned methane (CH4) emissions and atmospheric concentrations in northern California during the Discover-AQ-CA field campaign using airborne measurement data and model simulations. Source apportioned CH4 emissions from the Emissions Database for Global Atmospheric Research (EDGAR) version 4.2 were applied in the 3-D chemical transport model GEOS-Chem and analyzed using airborne measurements taken as part of the Alpha Jet Atmospheric eXperiment over the San Francisco Bay Area (SFBA) and northern San Joaquin Valley (SJV). During the time period of the Discover-AQ-CA field campaign EDGAR inventory CH4 emissions were 5.30 Gg/day (Gg 1.0 109 grams) (equating to 1.9 103 Gg/yr) for all of California. According to EDGAR, the SFBA and northern SJV region contributes 30 of total emissions from California. Source apportionment analysis during this study shows that CH4 concentrations over this area of northern California are largely influenced by global emissions from wetlands and local/global emissions from gas and oil production and distribution, waste treatment processes, and livestock management. Model simulations, using EDGAR emissions, suggest that the model under-estimates CH4 concentrations in northern California (average normalized mean bias (NMB) -5 and linear regression slope 0.25). The largest negative biases in the model were calculated on days when hot spots of local emission sources were measured and atmospheric CH4 concentrations reached values 3.0 parts per million (model NMB -10). Sensitivity emission studies conducted during this research suggest that local emissions of CH4 from livestock management processes are likely the primary source of the negative model bias. These results indicate that a variety, and larger quantity, of measurement data needs to be obtained and additional research is necessary to better quantify source apportioned CH4 emissions in California and further the understanding of the physical processes controlling them.

Methane↗

A Machine Learning Model for Solar Sail Shape Reconstruction Using Flight Data

Solar sail deformation leads to disturbance torques from solar radiation pressure, driving performance requirements for momentum management systems. For the Solar Cruiser technology demonstrator mission, we have developed a model leveraging neural network-based machine learning to derive sail shape characteristics. The model uses torque and attitude telemetry simulated from a reduced-order tensor model of the deformed sail mesh over a characterization sequence. The machine learning model predicts sail boom deflection with comparable accuracy to that of an onboard context camera. This model can discover sail shape with no additional mass or data downlink requirements, allowing for validation of sail force modeling assumptions using in flight data. The results from the project hold promise for the further implementation of machine learning techniques in solar sail telemetry analysis and control.

solar sail↗

A Machine Learning Model for Solar Sail Shape Reconstruction Using Flight Data

Solar sail deformation leads to disturbance torques from solar radiation pressure, driving performance requirements for momentum management systems. For the Solar Cruiser technology demonstrator mission, we have developed a model leveraging neural network-based machine learning to derive sail shape characteristics. The model uses torque and attitude telemetry simulated from a reduced-order tensor model of the deformed sail mesh over a characterization sequence. The machine learning model predicts sail boom deflection with comparable accuracy to that of an onboard context camera. This model can discover sail shape with no additional mass or data downlink requirements, allowing for validation of sail force modeling assumptions using in flight data. The results from the project hold promise for the further implementation of machine learning techniques in solar sail telemetry analysis and control.

solar sail↗

Constrained or unconstrained? Neural-network-based equation discovery from data

Throughout many fields, practitioners often rely on differential equations to model systems. Yet, for many applications, the theoretical derivation of such equations and/or the accurate resolution of their solutions may be intractable. Instead, recently developed methods, including those based on parameter estimation, operator subset selection, and neural networks, allow for the data-driven discovery of both ordinary and partial differential equations (PDEs), on a spectrum of interpretability. The success of these strategies is often contingent upon the correct identification of representative equations from noisy observations of state variables and, as importantly and intertwined with that, the mathematical strategies utilized to enforce those equations. Specifically, the latter has been commonly addressed via unconstrained optimization strategies. Representing the PDE as a neural network, we propose to discover the PDE (or the associated operator) by solving a constrained optimization problem and using an intermediate state representation similar to a physics-informed neural network (PINN). The objective function of this constrained optimization problem promotes matching the data, while the constraints require that the discovered PDE is satisfied at a number of spatial collocation points. We present a penalty method and a widely used trust-region barrier method to solve this constrained optimization problem, and we compare these methods on numerical examples. Our results on several example problems demonstrate that the latter constrained method outperforms the penalty method, particularly for higher noise levels or fewer collocation points. This work motivates further exploration into using sophisticated constrained optimization methods in scientific machine learning, as opposed to their commonly used, penalty-method or unconstrained counterparts. For both of these methods, we solve these discovered neural network PDEs with classical methods, such as finite difference methods, as opposed to PINNs-type methods relying on automatic differentiation. Here, we briefly highlight how simultaneously fitting the data while discovering the PDE improves the robustness to noise and other small, yet crucial, implementation details.

Data-driven discovery↗

Autonomous Information Unit: Why Making Data Smart Can also Make Data Secured?

In this paper, we introduce a new fine-grain distributed information protection mechanism which can self-protect, self-discover, self-organize, and self-manage. In our approach, we decompose data into smaller pieces and provide individualized protection. We also provide a policy control mechanism to allow 'smart' access control and context based re-assembly of the decomposed data. By combining smart policy with individually protected data, we are able to provide better protection of sensitive information and achieve more flexible access during emergency conditions. As a result, this new fine-grain protection mechanism can enable us to achieve better solutions for problems such as distributed information protection and identity theft.

data security↗

Energetic charged particles in the Uranian magnetosphere

The cosmic ray instrument on Voyager 2 obtained detailed charged particle data on the path the spacecraft followed through the newly-discovered Uranian magnetosphere. Notably, the electron counts did not rise above background until the spacecraft was deep in the magnetosphere. The data further indicated that the satellites Miranda, Ubriel and Ariel impose a sweep effect on MeV electrons, which move radially inward from some source in the outer magnetosphere or the magnetotail. The energetic particle data also supported a firm pitch angle dependence for proton energy spectra in the 1-8 MeV range. Finally, the particle density data were commensurate with a dipole magnetic field tilted 60.1 deg in relation to the planet and rotating every 17.4 hr, close to estimates from other instruments.

Stone, E. C.↗

The luminosity function at the end of the main sequence: Results of a deep, large-area, CCD survey for cool dwarfs

The luminosity function at the end of the main sequence is determined from V, R, and I data taken by the charge coupled devices (CCD)/Transit Instrument, a dedicated telescope surveying an 8.25 min wide strip of sky centered at delta = +28 deg, thus sampling Galactic latitudes of +90 deg down to -35 deg. A selection of 133 objects chosen via R - I and V - I colors has been observed spectroscopically at the 4.5 m Multiple Mirror Telescope to assess contributions by giants and subdwarfs and to verify that the reddest targets are objects of extremely late spectral class. Eighteen dwarfs of type M6 or later have been discovered, with the latest being of type M8.5. Data used for the determination of the luminosity function cover 27.3 sq. deg down to a completeness limit of R = 19.0. This luminosity function, computed at V, I, and bolometric magnitudes, shows an increase at the lowest luminosities, corresponding to spectral types later than M6- an effect suggested in earlier work by Reid & Gilmore and Legget & Hawkins. When the luminosity function is segregated into north Galactic and south Galactic portions, it is found that the upturn at faint magnitudes exists only in the southern sample. In fact, no dwarfs with M(sub I) is greater than or equal to 12.0 are found within the limiting volume of the 19.4 sq deg northern sample, in stark contrast to the smaller 7.9 sq deg area at southerly latitudes where seven such dwarfs are found. This fact, combined with the fact that the Sun is located approximately 10-40 pc north of the midplane, suggests that the latest dwarfs are part of a young population with a scale height much smaller than the 350 pc value generally adopted for other M dwarfs. These objects comprise a young population either because the lower metallicities prevelant at earlier epochs inhibited the formation of late M dwarfs or because the older counterparts of this population have cooled beyond current detection limits. The latter scenario would hold if these late-type M dwarfs are substellar. The luminosity function data together with an empirical derivation of the mass-luminosity relation (from Henry & McCarthy) are used to compute a mass function independent of theory. This mass function increases toward the end of the main sequence, but the observed density of M dwarfs is still insufficient to account for the missing mass. If the increases seen in the luminosity and mass functions are indicative of a large, unseen, substellar population, brown dwarfs may yet add significantly to the mass of the Galaxy.

Kirkpatrick, J. Davy↗

X-ray emission associated with filament activity

The temporal and spatial relationships of activated filaments, soft X-ray production, and H-alpha flares are investigated. The events chosen for study are from a sample of 114 hours of the very best, high-resolution H-alpha records of active regions gleaned from about 150 days of observations of active regions by Big Bear Solar Observatory, all with simultaneous mapping X-ray heliometer coverage. In the final data set, 20 flares are chosen for detailed study (10 significant flares and 10 smaller flarelike events). The data are examined for preflare filament activation and preflare X-ray enhancements with a view to discover a link between the two phenomena. To the limits set by the data, no convincing evidence for consistent preflare effects in H-alpha or X-rays is found. Aside from the 'disparition brusque', it seems clear that filament activity is not directly responsible for any dramatic effects in X-rays, and even there, the enhancement comes after the filament has disappeared.

Acton, L. W.↗