The spectral impact of magnetic activity on disc-integrated HARPS-N solar observations: exploring new activity indicators
Explore the source record for details and available documents.
A P G Thompson↗
SEARCH · Engineering Papers
Results for “Activities”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Antisense oligodeoxynucleotide inhibition of a swelling-activated cation channel in osteoblast-like osteosarcoma cells
By patch-clamp analysis, we have shown that chronic, intermittent mechanical strain (CMS) increases the activity of stretch-activated cation channels of osteoblast-like UMR-106.01 cells. CMS also produces a swelling-activated whole-cell conductance (Gm) regulated by varying strain levels. We questioned whether the swelling-activated conductance was produced by stretch-activated cation channel activity. We have identified a gene involved in the increase in conductance by using antisense oligodeoxynucleotides (ODN) derived from the alpha 1-subunit genes of calcium channels found in UMR-106.01 cells (alpha1S, alpha1C, and alpha1D). We demonstrate that alpha 1C antisense ODNs abolish the increase in Gm in response to hypotonic swelling following CMS. Antisense ODNs to alpha1S and alpha1D, sense ODNs to alpha1C, and sham permeabilization had no effect on the conductance increase. In addition, during cell-attached patch-clamp studies, antisense ODNs to alpha1c completely blocked the swelling-activated and stretch-activated nonselective cation channel response to strain. Antisense ODNs to alpha1S treatment produced no effect on either swelling-activated or stretch-activated cation channel activity. There were differences in the stretch-activated and swelling-activated cation channel activity, but whether they represent different channels could not be determined from our data. Our data indicate that the alpha1C gene product is involved in the Gm and the activation of the swelling-activated cation channels induced by CMS. The possibility that swelling-activated cation channel genes are members of the calcium channel superfamily exists, but if alpha1c is not the swelling-activated cation channel itself, then its expression is required for induction of swelling-activated cation channel activity by CMS.
NASA Discipline Musculoskeletal↗
Towards an Enhanced Droplet Activation Scheme for Multi-Moment Bulk Microphysics Schemes
Initial droplet spectra produced upon activation impact the ensuing chain of microphysical processes andtherefore play a crucial role in cloud evolution. This work re-examines dependencies of newly formed clouddroplet size distribution (CDSD) characteristics on environmental and aerosol properties via parcel model simulationsthat serve as the basis for a multi-moment bulk microphysics droplet activation scheme suitable for acloud-resolving model (CRM). It is found that applying a fixed size threshold to define activated droplets versusemploying physical considerations can lead to erroneous activation and overly broad CDSDs for high aerosolconcentration and weak updraft conditions. Aerosol distributions characterized by larger median sizes and/orincreased solubility can result in greater activated droplet numbers, whereas impacts of these parameters onCDSD spectral width depend on both aerosol number concentration and updraft velocity. An expansion of theactivation scheme to include CDSD spectral width is proposed to aid efforts to extend high-order momentprediction to cloud droplet categories in CRMs as well as better represent variability in the activation process onthe cloud scale.simulations to investigate the regime dependence of the relative dispersion(d)1 of newly activated CDSDs, where d is the ratio of dropletradius standard deviation (σ) to the mean radius (r ). C16 demonstratedthat increasing Na resulted in increasing (decreasing) d values via reducedcondensational narrowing (spectral broadening) rates within theAL (UL) regime, with d values peaking in the TR regime. Their findingssuggest a similar regime dependence for d as R09 noted for Nc and helpexplain reportedly conflicting relationships between Na and CDSDspectral characteristics (cf. Hudson and Noble, 2014; Liu et al., 2014),although the applicability of these results within bulk microphysicalschemes was not addressed.Simulating aerosol-cloud interactions with CRMs employing bulkmicrophysics requires that the scheme minimally predict two CDSDparameters, namely mass and number concentrations, and represent thedroplet activation process. Various activation schemes aim to determineNc from aerosol and environmental properties and include analyticalexpressions (e.g., Abdul-Razzak et al., 1998; Morrison et al., 2005) aswell as lookup tables (LUTs) based on detailed parcel model calculations(e.g., Saleeby and Cotton, 2004, hereafter SC04; Segal and Khain,2006; Thompson and Eidhammer, 2014). Expressions to diagnose CDSDspectral width from Nc (Grabowski, 1998; Liu et al., 2006; Morrison andGrabowski, 2007) or cloud water content (Geoffroy et al., 2010) havealso been developed, although more robust methods to obtain CDSDspectral width upon activation are presently lacking. This latter point isrelevant for triple-moment (3 M) bulk microphysics that aim to predictdistribution spectral width alongside number and mass concentrations(e.g., Loftus et al., 2014; Milbrandt and Yau, 2005).The current work extends the findings of C16 to the current LUTbasedaerosol activation scheme used in the Regional AtmosphericModeling System (RAMS) (Cotton et al., 2003; SC04; Saleeby and vanden Heever, 2013, hereafter SvdH13) and additionally examinesaerosol size and solubility impacts on newly activated CDSD properties.Because early cloud development processes such as condensationalgrowth, evaporation, and droplet self-collection depend on and impactCDSD spectral width (Hudson and Yum, 1997; Seifert and Beheng 2001;Lu and Seinfeld, 2006; Igel and van den Heever, 2017), an expansion ofthe activation LUTs to include CDSD spectral width is proposed as apreliminary step for extending 3M prediction to CDSDs in CRMs forimproved simulations of aerosol-cloud interactions.2. MethodologyThe current RAMS two-moment microphysics module determinesthe fractional number of aerosol particles that activate to cloud dropletsfrom five-dimensional LUTs based on model predicted air temperature(T), w, Na, and the geometric median radius (rg) and soluble fraction (ε)of the aerosol size distribution (SvdH13). These LUTs are created offlineusing a one-dimensional Lagrangian adiabatic parcel model (Feingoldand Heymsfield, 1992; Heymsfield and Sabin, 1989; SC04) to simulateexplicit droplet activation and initial CDSD growth for a range of ambientatmospheric conditions [T, w] and binned lognormal aerosol sizedistributions given by= ⎡⎣ ⎢− ⎤⎦ ⎥N r Nr π σr rσ( )2 lnexp[ln( / )]2(ln )aggg22 (1)where r is the dry aerosol particle bin radius and σg is the geometricstandard deviation of the distribution. As the parcel model simulationsfocus on the activation process, other processes such as coalescence,sedimentation, and mixing are not considered. Details of the parcelmodel can be found in SC04 and SvdH13, and only a brief description isprovided here. At the onset of parcel model calculations, the initiallydry aerosol particles in all bins first deliquesce and reach theirequilibrium diameters in a sub-saturated environment based on theKöhler equation for solution droplets. The parcel is then lifted at a fixedupward velocity w, and particle growth by vapor diffusion, along withconcurrent changes in the ambient environment, are iteratively computedusing the Variable-coefficient Ordinary Differential Equation(VODE) solver (Brown et al., 1989). The time resolution of these calculationsis determined within the VODE solver, and the frequency atwhich the solver is called is controlled by a longer model time stepbased on fixed upward parcel displacement increments (Δz) at thespecified w (Δt=Δz/w). Model calculations proceed until the parcelreaches a height 50m beyond the level of maximum saturation ratio(Smax) or total parcel displacement exceeds 2 km. Upon model termination,Smax and the fractional number of aerosols (factv) resulting innewly formed cloud droplets, defined as particles having diameters of atleast 2 μm, are cataloged in the LUTs according to the specified T, w, Na,rg, and ε parameter values.A critical point regarding the creation of these LUTs is the use of afixed minimum diameter (Dmin) to define cloud droplets in the parcelmodel, which can produce erroneous CDSD characteristics, particularlywithin the UL regime. For aerosol distributions with large rg valuesunder low SS conditions, for example, deliquesced aerosols within thelarge tail of the distribution can exceed 2 μm in diameter yet remainunactivated as ‘haze’ particles (Levin and Cotton, 2009; McFigganset al., 2006). For this study, aerosol particles activate to cloud dropletsbased on the critical diameter Dcrit as a function of parcel supersaturationratio (Sr) as in R09:D = σ MS RTρ83 ln( ) critsol wr w (2)where σsol is the surface tension of a solution droplet, Mw and ρw are themolar mass and density of liquid water, respectively, and R is theuniversal gas constant. Additionally, at relatively large w values withinthe AL regime, Nc stabilizes shortly after reaching supersaturation.However, parcel ascent and condensational growth continue beyondthe level of Smax, potentially causing additional narrowing of the CDSD.In the current work, model calculations terminate upon reaching Smaxas changes in Nc are negligible with continued ascent (Peng et al., 2007;R09).Parcel model simulations are performed to examine the sensitivitiesof CDSD characteristics to w, Na, rg, and ε, with the ranges for theseparameters listed in Table 1. Aerosols are assumed to be a mix of solubleand insoluble material of equal density, specified by ε, where fullysoluble aerosols correspond to ammonium sulfate with hygroscopicityparameter κ=0.61 (Petters and Kreidenweis, 2007). FollowingSvdH13, aerosol geometric standard deviation is fixed at σg=1.8, andaerosol distributions (Eq. 1) are partitioned into 100 logarithmicallyspacedbins spanning a size range specific to each rg value. For all simulations,Δz=1 m, and initial values of relative humidity, air temperatureand pressure are set to RH=0.99, T=10 °C and p=900 hPa,respectively.
Loftus, Adrian M.↗
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↗
Prediction of Active-Region CME Productivity from Magnetograms
We report results of an expanded evaluation of whole-active-region magnetic measures as predictors of active-region coronal mass ejection (CME) productivity. Previously, in a sample of 17 vector magnetograms of 12 bipolar active regions observed by the Marshall Space Flight Center (MSFC) vector magnetograph, from each magnetogram we extracted a measure of the size of the active region (the active region s total magnetic flux a) and four measures of the nonpotentiality of the active region: the strong-shear length L(sub SS), the strong-gradient length L(sub SG), the net vertical electric current I(sub N), and the net-current magnetic twist parameter alpha (sub IN). This sample size allowed us to show that each of the four nonpotentiality measures was statistically significantly correlated with active-region CME productivity in time windows of a few days centered on the day of the magnetogram. We have now added a fifth measure of active-region nonpotentiality (the best-constant-alpha magnetic twist parameter (alpha sub BC)), and have expanded the sample to 36 MSFC vector magnetograms of 31 bipolar active regions. This larger sample allows us to demonstrate statistically significant correlations of each of the five nonpotentiality measures with future CME productivity, in time windows of a few days starting from the day of the magnetogram. The two magnetic twist parameters (alpha (sub 1N) and alpha (sub BC)) are normalized measures of an active region s nonpotentially in that they do not depend directly on the size of the active region, while the other three nonpotentiality measures (L(sub SS), L(sub SG), and I(sub N)) are non-normalized measures in that they do depend directly on active-region size. We find (1) Each of the five nonpotentiality measures is statistically significantly correlated (correlation confidence level greater than 95%) with future CME productivity and has a CME prediction success rate of approximately 80%. (2) None of the nonpotentiality measures is a significantly better CME predictor than the others. (3) The active-region phi shows some correlation with CME productivity, but well below a statistically significant level (correlation confidence level less than approximately 80%; CME prediction success rate less than approximately 65%). (4) In addition to depending on magnetic twist, CME productivity appears to have some direct dependence on active-region size (rather than only an indirect dependence through a correlation of magnetic twist with active-region size), but it will take a still larger sample of active regions (50 or more) to certify this. (5) Of the five nonpotentiality measures, L(sub SG) appears to be the best for operational CME forecasting because it is as good or better a CME predictor than the others and it alone does not require a vector magnetogram; L(sub SG) can be measured from a line-of-sight magnetogram such as from the Michelson Doppler Imager (MDI) on the Solar and Heliospheric Observatory (SOHO).
Falconer, D. A.↗
Circadian force and EMG activity in hindlimb muscles of rhesus monkeys
Continuous intramuscular electromyograms (EMGs) were recorded from the soleus (Sol), medial gastrocnemius (MG), tibialis anterior (TA), and vastus lateralis (VL) muscles of Rhesus during normal cage activity throughout 24-h periods and also during treadmill locomotion. Daily levels of MG tendon force and EMG activity were obtained from five monkeys with partial datasets from three other animals. Activity levels correlated with the light-dark cycle with peak activities in most muscles occurring between 08:00 and 10:00. The lowest levels of activity generally occurred between 22:00 and 02:00. Daily EMG integrals ranged from 19 mV/s in one TA muscle to 3339 mV/s in one Sol muscle: average values were 1245 (Sol), 90 (MG), 65 (TA), and 209 (VL) mV/s. The average Sol EMG amplitude per 24-h period was 14 microV, compared with 246 microV for a short burst of locomotion. Mean EMG amplitudes for the Sol, MG, TA, and VL during active periods were 102, 18, 20, and 33 microV, respectively. EMG amplitudes that approximated recruitment of all fibers within a muscle occurred for 5-40 s/day in all muscles. The duration of daily activation was greatest in the Sol [151 +/- 45 (SE) min] and shortest in the TA (61 +/- 19 min). The results show that even a "postural" muscle such as the Sol was active for only approximately 9% of the day, whereas less active muscles were active for approximately 4% of the day. MG tendon forces were generally very low, consistent with the MG EMG data but occasionally reached levels close to estimates of the maximum force generating potential of the muscle. The Sol and TA activities were mutually exclusive, except at very low levels, suggesting very little coactivation of these antagonistic muscles. In contrast, the MG activity usually accompanied Sol activity suggesting that the MG was rarely used in the absence of Sol activation. The results clearly demonstrate a wide range of activation levels among muscles of the same animal as well as among different animals during normal cage activity.
NASA Discipline Musculoskeletal↗
Systematic Mapping of Bacterial CRISPRa Systems for Synergistic Gene Activation Reveals Antagonistic Effects
CRISPR gene activation (CRISPRa) tools have shown great promise for bacterial strain engineering but often require customization for each intended application. Our goal is to create generalizable CRISPRa tools that can overcome previous limitations of gene activation in bacteria. In eukaryotic cells, multiple activators can be combined for synergistic gene activation. To identify potential effectors for synergistic activation in bacteria, we systematically characterized bacterial activator proteins with a set of engineered synthetic promoters. We found that optimal target sites for different activators could vary by up to 200 bases in the region upstream of the transcription start site (TSS). These optimal target sites qualitatively matched previous reports for each activator, but the precise targeting rules varied between different promoters. By characterizing targeting rules in the same promoter context, we were able to test activator combinations with each effector positioned at its optimal target site. We did not find any activator combinations that produced synergistic activation, and we found that many combinations were antagonistic. Furthermore, this systematic investigation highlights fundamental mechanistic differences between bacterial and eukaryotic transcriptional activation systems and suggests that alternative strategies will be necessary for strong bacterial gene activation at arbitrary endogenous targets.
CRISPR activation↗
The Maximum Free Magnetic Energy Allowed in a Solar Active Region
Two whole-active-region magnetic quantities that can be measured from a line-of-sight magnetogram are (sup L) WL(sub SG), a gauge of the total free energy in an active region's magnetic field, and sup L(sub theta), a measure of the active region's total magnetic flux. From these two quantities measured from 1865 SOHO/MDI magnetograms that tracked 44 sunspot active regions across the 0.5 R(sub Sun) central disk, together with each active region's observed production of CMEs, X flares, and M flares, Falconer et al (2009, ApJ, submitted) found that (1) active regions have a maximum attainable free magnetic energy that increases with the magnetic size (sup L) (sub theta) of the active region, (2) in (Log (sup L)WL(sub SG), Log(sup L) theta) space, CME/flare-productive active regions are concentrated in a straight-line main sequence along which the free magnetic energy is near its upper limit, and (3) X and M flares are restricted to large active regions. Here, from (a) these results, (b) the observation that even the greatest X flares produce at most only subtle changes in active region magnetograms, and (c) measurements from MSFC vector magnetograms and from MDI line-of-sight magnetograms showing that practically all sunspot active regions have nearly the same area-averaged magnetic field strength: =- theta/A approximately equal to 300 G, where theta is the active region's total photospheric flux of field stronger than 100 G and A is the area of that flux, we infer that (1) the maximum allowed ratio of an active region's free magnetic energy to its potential-field energy is ~1, and (2) any one CME/flare eruption releases no more than a small fraction (less than ~10%) of the active region's free magnetic energy. This work was funded by NASA's Heliophysics Division and NSF's Division of Atmospheric Sciences.
Moore, Ronald L.↗
The Limit of Free Magnetic Energy in Active Regions
By measuring from active-region magnetograms a proxy of the free energy in the active region fs magnetic field, it has been found previously that (1) there is an abrupt upper limit to the free energy the field can hold that increases with the amount of magnetic field in the active region, the active region fs magnetic flux content, and (2) the free energy is usually near its limit when the field explodes in a CME/flare eruption. That is, explosive active regions are concentrated in a main-sequence path bordering the free-energy ]limit line in (flux content, free-energy proxy) phase space. Here, from measurement of Marshall Space Flight Center vector magnetograms, we find the magnetic condition that underlies the free ]energy limit and the accompanying main sequence of explosive active regions. Using a suitable free ]energy proxy measured from vector magnetograms of 44 active regions, we find that (1) in active regions at and near their free ]energy limit, the ratio of magnetic-shear free energy to the non ]free magnetic energy the potential field would have is approximately 1 in the core field, the field rooted along the neutral line, and (2) this ratio is progressively less in active regions progressively farther below their free ]energy limit. This shows that most active regions in which this core-field energy ratio is much less than 1 cannot be triggered to explode; as this ratio approaches 1, most active regions become capable of exploding; and when this ratio is 1 or greater, most active regions are compelled to explode. From these results we surmise the magnetic condition that determines the free ]energy limit is the ratio of the free magnetic energy to the non-free energy the active region fs field would have were it completely relaxed to its potential ]field configuration, and that this ratio is approximately 1 at the free-energy limit and in the main sequence of explosive active regions.
Moore, Ron↗
Arsenic activation and compensation in single crystal CdTe bilayers
In state-of-the art polycrystalline CdTe photovoltaics, group-V dopant activation is about 2%. Low activation can create electronic defects and lead to recombination and band tail losses. To develop methods to overcome this limitation, dopant activation was systematically investigated using molecular beam epitaxy (MBE) grown single crystal bilayers of As-doped CdTe on undoped CdTe. Results suggest multiple paths for improved As-activation in polycrystalline CdTe-based devices. It was found that the carrier concentration in this MBE material saturated at ∼3 × 1016 cm−3, with high levels (>50%) of As-activation possible. High activation could be achieved with a post-growth activation temperature of ∼450 °C, when the initial doping level was below the saturation level. However, at typical polycrystalline As incorporation levels (>5 × 1016 cm−3), the excess As is inactive or compensating, requiring elevated temperatures (500–600 °C) to achieve high activation. Oxygen in the annealing ambient was detrimental, while the effect of CdCl2 in the ambient is more case-dependent. A 575 °C activation anneal was combined with a 450 °C CdCl2 treatment to better understand the implications for polycrystalline CdTe. Interestingly, on highly doped samples, processes ending with a high temperature step displayed high activation, while those ending at 450 °C significantly reduced the carrier concentration (with or without CdCl2 in the ambient). Low activation can be restored with another high temperature anneal, allowing reproducible toggling between high and low activation based on the final temperature. Photoluminescence revealed the presence of donor–acceptor pairs in the low activation state that appear to be associated with a compensating defect.
14 SOLAR ENERGY↗
The Active Asteroids Citizen Science Program: Overview and First Results
Abstract We present the Citizen Science program Active Asteroids and describe discoveries stemming from our ongoing project. Our NASA Partner program is hosted on the Zooniverse online platform and launched on 2021 August 31, with the goal of engaging the community in the search for active asteroids—asteroids with comet-like tails or comae. We also set out to identify other unusual active solar system objects, such as active Centaurs, active quasi-Hilda asteroids (QHAs), and Jupiter-family comets (JFCs). Active objects are rare in large part because they are difficult to identify, so we ask volunteers to assist us in searching for active bodies in our collection of millions of images of known minor planets. We produced these cutout images with our project pipeline that makes use of publicly available Dark Energy Camera data. Since the project launch, roughly 8300 volunteers have scrutinized some 430,000 images to great effect, which we describe in this work. In total, we have identified previously unknown activity on 15 asteroids, plus one Centaur, that were thought to be asteroidal (i.e., inactive). Of the asteroids, we classify four as active QHAs, seven as JFCs, and four as active asteroids, consisting of one main-belt comet (MBC) and three MBC candidates. We also include our findings concerning known active objects that our program facilitated, an unanticipated avenue of scientific discovery. These include discovering activity occurring during an orbital epoch for which objects were not known to be active, and the reclassification of objects based on our dynamical analyses.
Astronomy & Astrophysics↗
Correlation of the Coronal Mass Ejection Productivity of Solar Active Regions with Measures of their Global Nonpotentiality from Vector Magnetograms: Baseline Results
Conventional magnetograms and chromospheric and coronal images show qualitatively that the fastest coronal mass ejections (CMEs) are magnetic explosions from sunspot active regions where the magnetic field is globally strongly sheared and twisted from its minimum-energy potential configuration. We present measurements from active region vector magnetograms that start to quantify the dependence of an active region's CME productivity on the global nonpotentiality of its magnetic field. From each of 17 magnetograms of 12 bipolar active regions, we measured the size of the active region (the magnetic flux content, phi) and three separate measures of the global nonpotentiality (L(sub SS), the length of strong-shear, strong-field main neutral line: I(sub N), the net electric current connecting one polarity to the other; and alpha = (mu)I(sub N)/phi), a flux normalized measure of the field twist). From these measurements and the observed CME productivity of the active regions, we find that: (1) All three measures of global nonpotentiality are statistically correlated with the active region flux content and with each other; (2) All three measures of global nonpotentiality are significantly correlated with CME productivity. The flux content correlates with CME productivity, but at a lower statistically significant confidence level (less than 95%); (3) The net current is less closely correlated with CME productivity than alpha and the correlation of CME productivity with flux content is even weaker. If these differences in correlation strength, and a significant correlation of alpha with flux content, persist to larger active regions, this would imply that the size of active regions does not affect CME productivity except through global nonpotentiality; and (4) For each of the four global magnetic quantities, the correlation with CME productivity is stronger for a two-day time window for the CME production than for windows half as wide or twice as wide. This plausibly is a result of the most counterproductive active regions producing less than one CME per day, and from the active region's evolution often significantly changing the global nonpotentiality over the course of several days. These results establish that measures of active region global nonpotentiality from vector magnetograms (such as L(sub SS), I(sub N), and alpha) should be useful for prediction a active region CMEs.
Falconer, D. A.↗
Exploring the Solar System Activities Outline: Hands-On Planetary Science for Formal Education K-14 and Informal Settings
Activities by NASA scientists and teachers focus on integrating Planetary Science activities with existing Earth science, math, and language arts curriculum. The wealth of activities that highlight missions and research pertaining to the exploring the solar system allows educators to choose activities that fit a particular concept or theme within their curriculum. Most of the activities use simple, inexpensive techniques that help students understand the how and why of what scientists are learning about comets, asteroids, meteorites, moons and planets. With these NASA developed activities students experience recent mission information about our solar system such as Mars geology and the search for life using Mars meteorites and robotic data. The Johnson Space Center ARES Education team has compiled a variety of NASA solar system activities to produce an annotated thematic outline useful to classroom educators and informal educators as they teach space science. An important aspect of the outline annotation is that it highlights appropriate science content information and key science and math concepts so educators can easily identify activities that will enhance curriculum development. The outline contains URLs for the activities and NASA educator guides as well as links to NASA mission science and technology. In the informal setting educators can use solar system exploration activities to reinforce learning in association with thematic displays, planetarium programs, youth group gatherings, or community events. Within formal education at the primary level some of the activities are appropriately designed to excite interest and arouse curiosity. Middle school educators will find activities that enhance thematic science and encourage students to think about the scientific process of investigation. Some of the activities offered are appropriate for the upper levels of high school and early college in that they require students to use and analyze data.
Allen, J. S.↗
Software Displays Data on Active Regions of the Sun
The Solar Active Region Display System is a computer program that generates, in near real time, a graphical display of parameters indicative of the spatial and temporal variations of activity on the Sun. These parameters include histories and distributions of solar flares, active region growth, coronal mass ejections, size, and magnetic configuration. By presenting solar-activity data in graphical form, this program accelerates, facilitates, and partly automates what had previously been a time-consuming mental process of interpretation of solar-activity data presented in tabular and textual formats. Intended for original use in predicting space weather in order to minimize the exposure of astronauts to ionizing radiation, the program might also be useful on Earth for predicting solar-wind-induced ionospheric effects, electric currents, and potentials that could affect radio-communication systems, navigation systems, pipelines, and long electric-power lines. Raw data for the display are obtained automatically from the Space Environment Center (SEC) of the National Oceanic and Atmospheric Administration (NOAA). Other data must be obtained from the NOAA SEC by verbal communication and entered manually. The Solar Active Region Display System automatically accounts for the latitude dependence of the rate of rotation of the Sun, by use of a mathematical model that is corrected with NOAA SEC active-region position data once every 24 hours. The display includes the date, time, and an image of the Sun in H light overlaid with latitude and longitude coordinate lines, dots that mark locations of active regions identified by NOAA, identifying numbers assigned by NOAA to such regions, and solar-region visual summary (SRVS) indicators associated with some of the active regions. Each SRVS indicator is a small pie chart containing five equal sectors, each of which is color-coded to provide a semiquantitative indication of the degree of hazard posed by one aspect of the activity at the indicated location. The five aspects in question are the history of solar flares, the history of coronal mass ejections, the growth or decay of activity, the overall size, and the magnetic configuration. Mouse-clicking on an active-region-marking dot, SRVS indicator, or NOAA region number causes the program to generate a solar-region summary table (SRT) for the active region in question. The SRT contains additional quantitative and qualitative data, beyond those contained in the SRVS: These data include the solar coordinates of the region, the area of the region and its change in area during the past 24 hours, the change in the number of sunspots in the region during the past 24 hours, the magnetic configuration, and the types, dates, and times of the most recent flare and coronal mass ejection.
Golightly, Mike↗
The Limit of Magnetic-Shear Energy in Solar Active Regions
It has been found previously, by measuring from active-region magnetograms a proxy of the free energy in the active region's magnetic field, (1) that there is a sharp upper limit to the free energy the field can hold that increases with the amount of magnetic field in the active region, the active region's magnetic flux content, and (2) that most active regions are near this limit when their field explodes in a coronal mass ejection/flare eruption. That is, explosive active regions are concentrated in a main-sequence path bordering the free-energy-limit line in (flux content, free-energy proxy) phase space. Here, we present evidence that specifies the underlying magnetic condition that gives rise to the free-energy limit and the accompanying main sequence of explosive active regions. Using a suitable free-energy proxy measured from vector magnetograms of 44 active regions, we find evidence that (1) in active regions at and near their free-energy limit, the ratio of magnetic-shear free energy to the non-free magnetic energy the potential field would have is of the order of one in the core field, the field rooted along the neutral line, and (2) this ratio is progressively less in active regions progressively farther below their free-energy limit. Evidently, most active regions in which this core-field energy ratio is much less than one cannot be triggered to explode; as this ratio approaches one, most active regions become capable of exploding; and when this ratio is one, most active regions are compelled to explode.
Moore, Ronald↗
The Limit of Magnetic-Shear Energy in Solar Active Regions
It has been found previously, by measuring from active ]region magnetograms a proxy of the free energy in the active region fs magnetic field, (1) that there is a sharp upper limit to the free energy the field can hold that increases with the amount of magnetic field in the active region, the active region fs magnetic flux content, and (2) that most active regions are near this limit when their field explodes in a CME/flare eruption. That is, explosive active regions are concentrated in a main ]sequence path bordering the free ]energy ]limit line in (flux content, free ]energy proxy) phase space. Here we present evidence that specifies the underlying magnetic condition that gives rise to the free ]energy limit and the accompanying main sequence of explosive active regions. Using a suitable free energy proxy measured from vector magnetograms of 44 active regions, we find evidence that (1) in active regions at and near their free ]energy limit, the ratio of magnetic ]shear free energy to the non ]free magnetic energy the potential field would have is of order 1 in the core field, the field rooted along the neutral line, and (2) this ratio is progressively less in active regions progressively farther below their free ]energy limit. Evidently, most active regions in which this core ]field energy ratio is much less than 1 cannot be triggered to explode; as this ratio approaches 1, most active regions become capable of exploding; and when this ratio is 1, most active regions are compelled to explode.
Moore, Ronald L.↗
Super active regions and production of major solar flares
The success of imaging detectors with small fields of veiw such as HXIS or P/OF (Pinhole/Occulter Facility) depends heavily on pointing to the right place at the right time. During the solar maximum years many active regions coexist on the solar disk. Therefore, in order to point the imaging detector to the right place, it is important to know which active region is most likely to produce major flares. This knowledge is also important for flare prediction. As a first step toward this goal active regions have been identified which produced major flares observed by HXRBS (Hard X-Ray Burst Spectrometer) on SMM during February 1980 through December 1983. For this study the HXRBS Event List, an updated flare list compiled by the HXRBS group, and the Comprehensive Reports of the Solar Geophysical Data were used. During this period, HXRBS detected hard X-rays from approx 7000 solar flares, out of which only 441 flares produced X-rays with peak count rates exceeding 1000 counts/s. Flares with such high peak count rates are major flares. During the same time period about 2100 active regions passed across the solar disk, out of which only 153 were observed to produce major flares. (Some active regions are known to persist for several solar rotations, but at each passage new active region numbers are assigned and the estimate is based on active region numbers.) Out of these 153 active regions, 25 were observed to produce 5 or more major flares. Considering their high productivity of major flares, we may call these active regions super active regions. These 25 super active regions produced 209 major flares, accounting for 51% of all the major flares with identified active regions.
Bai, T.↗
Developmental regulation of collagenase-3 mRNA in normal, differentiating osteoblasts through the activator protein-1 and the runt domain binding sites
Collagenase-3 mRNA is initially detectable when osteoblasts cease proliferation, increasing during differentiation and mineralization. We showed that this developmental expression is due to an increase in collagenase-3 gene transcription. Mutation of either the activator protein-1 or the runt domain binding site decreased collagenase-3 promoter activity, demonstrating that these sites are responsible for collagenase-3 gene transcription. The activator protein-1 and runt domain binding sites bind members of the activator protein-1 and core-binding factor family of transcription factors, respectively. We identified core-binding factor a1 binding to the runt domain binding site and JunD in addition to a Fos-related antigen binding to the activator protein-1 site. Overexpression of both c-Fos and c-Jun in osteoblasts or core-binding factor a1 increased collagenase-3 promoter activity. Furthermore, overexpression of c-Fos, c-Jun, and core-binding factor a1 synergistically increased collagenase-3 promoter activity. Mutation of either the activator protein-1 or the runt domain binding site resulted in the inability of c-Fos and c-Jun or core-binding factor a1 to increase collagenase-3 promoter activity, suggesting that there is cooperative interaction between the sites and the proteins. Overexpression of Fra-2 and JunD repressed core-binding factor a1-induced collagenase-3 promoter activity. Our results suggest that members of the activator protein-1 and core-binding factor families, binding to the activator protein-1 and runt domain binding sites are responsible for the developmental regulation of collagenase-3 gene expression in osteoblasts.
NASA Discipline Musculoskeletal↗