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By estimating the total amount of water released by volcanic processes on Mars, the abundance of H2O at 10 m was estimated. This value was based on mapping volcanic units, estimating thicknesses and volumes, and using a 10 wt. percent value H2O from terrestrial analogs. By combining such estimates with crater count ages, it is also possible to estimate the timing of water release through Martian history.
A large number of neutron stars (NSs), approximately 10(exp 9), populate the Galaxy, but only a tiny fraction of them is observable during the short radio pulsar lifetime. The majority of these isolated NSs, too cold to be detectable by their own thermal emission, should be visible in X-rays as a result of accretion from the interstellar medium. The ROSAT All-Sky Survey has, however, shown that such accreting isolated NSs are very elusive: only a few tentative candidates have been identified, contrary to theoretical predictions that up to several thousand should be seen. We suggest that the fundamental reason for this discrepancy lies in the use of the standard Bondi formula to estimate the accretion rates. We compute the expected source counts using updated estimates of the pulsar velocity distribution, realistic hydrogen atmosphere spectra, and a modified expression for the Bondi accretion rate, as suggested by recent MHD simulations and supported by direct observations in the case of accretion around supermassive black holes in nearby galaxies and in our own. We find that, whereas the inclusion of atmospheric spectra partly compensates for the reduction in the counts due to the higher mean velocities of the new distribution, the modified Bondi formula dramatically suppresses the source counts. The new predictions are consistent with a null detection at the ROSAT sensitivity.
We have developed a new method based on the sublimation of adenine from Escherichia coli to estimate bacterial cell counts in natural samples. To demonstrate this technique, several types of natural samples including beach sand, seawater, deep-sea sediment, and two soil samples from the Atacama Desert were heated to a temperature of 500 C for several seconds under reduced pressure. The sublimate was collected on a cold finger and the amount of adenine released from the samples then determined by high performance liquid chromatography (HPLC) with UV absorbance detection. Based on the total amount of adenine recovered from DNA and RNA in these samples, we estimated bacterial cell counts ranging from approx. l0(exp 5) to l0(exp 9) E. coli cell equivalents per gram. For most of these samples, the sublimation based cell counts were in agreement with total bacterial counts obtained by traditional DAPI staining. The simplicity and robustness of the sublimation technique compared to the DAPI staining method makes this approach particularly attractive for use by spacecraft instrumentation. NASA is currently planning to send a lander to Mars in 2009 in order to assess whether or not organic compounds, especially those that might be associated with life, are present in Martian surface samples. Based on our analyses of the Atacama Desert soil samples, several million bacterial cells per gam of Martian soil should be detectable using this sublimation technique.
We have developed a new method based on the sublimation of adenine from Escherichia coli to estimate bacterial cell counts in natural samples. To demonstrate this technique, several types of natural samples, including beach sand, seawater, deep-sea sediment, and two soil samples from the Atacama Desert, were heated to a temperature of 500 degrees C for several seconds under reduced pressure. The sublimate was collected on a cold finger, and the amount of adenine released from the samples was then determined by high-performance liquid chromatography with UV absorbance detection. Based on the total amount of adenine recovered from DNA and RNA in these samples, we estimated bacterial cell counts ranging from approximately 10(5) to 10(9) E. coli cell equivalents per gram. For most of these samples, the sublimation-based cell counts were in agreement with total bacterial counts obtained by traditional DAPI (4,6-diamidino-2-phenylindole) staining.
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The equivalence of three separate investigations that related LANDSAT digital count (DC) to ground measured reflectance (R) was demonstrated. One investigator related DC data to the cosZ, where Z is the solar zenith angle, for surfaces of constant R. The second investigator corrected the DC data to the solar zenith angle of 39 degrees before relating to surface R. Both of these investigators used LANDSAT 1 and 2 data from overpass dates 1972 through 1977. A third investigator calculated the relation between DC and R based on atmospheric radiative transfer theory. The equation coefficients obtained from these three investigators for all four LANDSAT MSS bands were shown to be equivalent although differences in ground reflectance measurement procedures have created coefficient variations among the three investigations. These relations should be useful for testing atmospheric radiative transfer theory.
We determined total conduction (Wilson) currents and flash rates for 850 overflights of electrified clouds spanning regions including the Southeastern United States, the Western Atlantic Ocean, the Gulf of Mexico, Central America and adjacent oceans, Central Brazil, and the South Pacific. The overflights include storms over land and ocean, with and without lightning, and with positive and negative Wilson currents. We combined these individual storm overflight statistics with global diurnal lightning variation data from the Lightning Imaging Sensor (LIS) and Optical Transient Detector (OTD) to estimate the thunderstorm and electrified shower cloud contributions to the diurnal variation in the global electric circuit. The contributions to the global electric circuit from lightning producing clouds are estimated by taking the mean current per flash derived from the overflight data for land and ocean overflights and combining it with the global lightning rates (for land and ocean) and their diurnal variation derived from the LIS/OTD data. We estimate the contribution of non-lightning producing electrified clouds by assuming several different diurnal variations and total non-electrified storm counts to produce estimates of the total storm currents (lightning and non-lightning producing storms). The storm counts and diurnal variations are constrained so that the resultant total current diurnal variation equals the diurnal variation in the fair weather electric field (+/-15%). These assumptions, combined with the airborne and satellite data, suggest that the total mean current in the global electric circuit ranges from 2.0 to 2.7 kA, which is greater than estimates made by others using other methods.
The effects of time estimation technique and task condition on the production and verbal estimation of time intervals ranging from 5 to 14 sec were investigated. The duration of time intervals during each task condition pretracking, tracking (subject performed a one-axis tracking), and posttracking was estimated by the subjects. The ratio of the subject's time estimate to actual interval length was computed for each trial. Productions were typically longer than verbal estimates of the same duration and produced durations were typically too long whereas verbal estimates were too short relative to the correct duration. A significant interaction was found between counting technique and tracking condition for both estimation methods. A significant effect could be attributed to the addition of a tracking task: produced durations increased in length, whereas verbal estimates decreased in length. The durations produced without counting were significantly less accurate and consistent with the addition of a tracking task. Verbal estimation mean accuracy, but not consistency, was adversely affected by the addition of a tracking task when the subjects were instructed not to count.
Multi-energy soft x-ray pinhole cameras have been designed, built, calibrated, and operated at Madison symmetric Torus, Alcator C-Mod, and more recently at Tokamak a configuration variable and Tungsten Environment in Steady-State Tokamak (WEST), to measure plasma emission across multiple energy ranges. Here we describe a new methodology to estimate the local continuum radiated power density and the plasma effective charge (Z eff ) directly from photon-counting measurements of the line-free continuum emission (Bremsstrahlung and Radiative Recombination) in several energy bands between 11 and 18 keV. This capability is particularly valuable for confinement systems using metal plasma-facing components, where x-ray losses from interactions with the sputtered wall can represent a significant fraction of the total radiated power (P rad ). The approach leverages a well-characterized detector responsivity, modeled by a complementary error function, and interprets the differential multi-energy measurements between adjacent energy levels through the probability density function of a Gaussian distribution. The implementation of this diagnostic technique is currently under development on the WEST tokamak, aiming at the goal of providing real-time P rad and Z eff measurements during long-pulse operation (up to 1000 s) in the 2026 campaign.
Oil and natural gas are primary sources of energy in the United States. Improved drilling and extracting techniques have led to a renewed interest in historic oil and gas fields, but limited records of legacy wells make new drilling efforts more difficult, as abandoned wells may provide conduits for liquids and gases to migrate into groundwater reservoirs or the atmosphere. Well finding using aeromagnetic surveys pinpoints the location of steel-cased wells, detecting both active and abandoned wells, including buried casings lacking aboveground markers. Here, we present six aeromagnetic surveys conducted in Pennsylvania and Wyoming as case studies, comparing the magnetic points to locations known in databases. In all study sites, more magnetic points were detected than recorded in databases. Based on differences between theoretical database well counts and the actual number of wells detected in surveys, we estimated the total number of wells in Pennsylvania to be 395 000–466 000 and 181 000–182 000 in Wyoming. Extrapolating to the national level, in this work, we estimate the average number of wells in the continental United States is 6.04 ± 19.97 million wells with 1.16 ± 3.84 million of those designated as abandoned wells, within the range of previous abandoned well count estimations. Although aeromagnetic surveys are limited to detecting steel-cased wells and do not differentiate sites based on well status, this study nevertheless demonstrates the utility of aeromagnetic surveys in well finding efforts across the country and shows limitations in database records of oil and natural gas wells.
We reconstruct the extra-galactic gamma-ray source-count distribution, or dN/dS, of resolved and unresolved sources by adopting machine learning techniques. Specifically, we train a convolutional neural network on synthetic 2-dimensional sky-maps, which are built by varying parameters of underlying source-counts models and incorporate the Fermi-LAT instrumental response functions. The trained neural network is then applied to the Fermi-LAT data, from which we estimate the source count distribution down to flux levels a factor of 50 below the Fermi-LAT threshold. We perform our analysis using 14 years of data collected in the (1,10) GeV energy range. The results we obtain show a source count distribution which, in the resolved regime, is in excellent agreement with the one derived from cataloged sources, and then extends as dN/dS ~ S -2 in the unresolved regime, down to fluxes of 5 · 10 -12 cm -2 s -1 . The neural network architecture and the devised methodology have the flexibility to enable future analyses to study the energy dependence of the source-count distribution.
The binomial probability distribution is used to treat the statistics of a microbiological sample that is split into two parts, with only one part evaluated for spore count. One wishes to estimate the total number of spores in the sample based on the counts obtained from the part that is evaluated (pour fraction). Formally, the binomial distribution is recharacterized as a function of the observed counts (successes), with the total number (trials) an unknown. The pour fraction is the probability of success per spore (trial). This distribution must be renormalized in terms of the total number. Finally, the new renormalized distribution is integrated and mathematically inverted to yield the maximum estimate of the total number as a function of a desired level of confidence ( P(<n)=LOC ). Selected results of the indicated numerical calculations are presented. For LOC=0.5, or the likely value, the estimates differ little from the usual calculation: the number of spores counted divided by the pour fraction. The extension to recovery efficiency corrections is also presented. Now the product of recovery efficiency and pour fraction may be small enough that the likely value may be much larger than the usual calculation: the number of spores divided by that product. The use of this analysis would not be limited to microbiological data.
Imagery of coarse resolution, such weather satellite imagery with 1 sq km pixels, is increasingly used to monitor dynamic and fragmented types of land surface types, such as scars from recent fires and ponds in wetlands. Accurate estimates of these land cover types at regional to global scales are required to assess the roles of fires and wetlands in global warming, yet difficult to compute when much of the area is accounted for by fragments about the same size as the pixels. In previous research, we found that size distribution of the fragments in several example scenes fit simple two-parameter models and related effects of coarse resolution to errors in area estimates based on pixel counts. We report on progress to develop accurate area estimates based on modelling the size distribution of the fragments, including analysis of size distributions on an expanded set of maps developed from digital imagery and a test of a procedure to correct for effects of coarse spatial resolution.
Sandia National Laboratories has developed a capability to estimate parameters of epidemiological models from case reporting data to support responses to the COVID-19 pandemic. A differentiating feature of this work is the ability to simultaneously estimate county-specific disease transmission parameters in a nation-wide model that considers mobility between counties. The approach is focused on estimating parameters in a stochastic SEIR model that considers mobility between model patches (i.e., counties) as well as additional infectious compartments. The inference engine developed by Sandia includes (1) reconstruction and (2) transmission parameter inference. Reconstruction involves estimating current population counts within each of the compartments in a modified SEIR model from reported case data. Reconstruction produces input for the inference formulations, and it provides initial conditions that can be used in other modeling and planning efforts. Inference involves the solution of a large-scale optimization problem to estimate the time profiles for the transmission parameters in each county. These provide quantification of changes in the transmission parameter over time (e.g., due to impact of intervention strategies). This capability has been implemented in a Python-based software package, epi_inference, that makes extensive use of Pyomo [5] and IPOPT [10] to formulate and solve the inference formulations.
Imagery of coarse resolution, such weather satellite imagery with 1 square kilometer pixels, is increasingly used to monitor dynamic and fragmented types of land surface types, such as scars from recent fires and ponds in wetlands. Accurate estimates of these land cover types at regional to global scales are required to assess the roles of fires and wetlands in global warming, yet difficult to compute when much of the area is accounted for by fragments about the same size as the pixels. In previous research, we found that size distribution of the fragments in several example scenes fit simple two-parameter models and related effects of coarse resolution to errors in area estimates based on pixel counts. We summarize our model based approach to improved area estimations and report on progress to develop accurate areas estimates based on modeling the size distribution of the fragments, including analysis of size distributions on an expanded set of maps developed from digital imagery.
Magmatism and volcanism have evolved the Martian lithosphere, surface, and climate throughout the history of Mars. Constraining the rates of magma generation and timing of volcanism on the surface clarifies the ways in which magma and volcanic activity have shaped these Martian systems. The ages of lava flows on other planets are often estimated using impact crater counts, assuming that the number and size-distribution of impact craters per unit area reflect the time the lava flow has been on the surface and exposed to potential impacts. Here we show that impact crater age model uncertainty is reduced by adding stratigraphic information observed at locations where neighboring lavas abut each other, and demonstrate the significance of this reduction in age uncertainty for understanding the history of a volcanic field comprising 29 vents in the 110-kilometer-diameter caldera of Arsia Mons, Mars. Each vent within this caldera produced lava flows several to tens of kilometers in length; these vents are likely among the youngest on Mars, since no impact craters in their lava flows are larger than 1 kilometer in diameter. First, we modeled the age of each vent with impact crater counts performed on their corresponding lava flows and found very large age uncertainties for the ages of individual vents, often spanning the estimated age for the entire volcanic field. The age model derived from impact crater counts alone is broad and unimodal, with estimated peak activity in the field around 130Ma (megaannum, 1 million years). Next we applied our volcano event age model (VEAM), which uses a directed graph of stratigraphic relationships and random sampling of the impact crater age determinations to create alternative age models. Monte Carlo simulation was used to create 10,000 possible vent age sets. The recurrence rate of volcanism is calculated for each possible age set, and these rates are combined to calculate the median recurrence rate of all simulations. Applying this approach to the 29 volcanic vents, volcanism likely began around 200-300Ma then first peaked around 150Ma, with an average production rate of 0.4 vents per Myr (million years). The recurrence rate estimated including stratigraphic data is distinctly bimodal, with a second, lower peak in activity around 100Ma. Volcanism then waned until the final vents were produced 10-90Ma. Based on this model, volume flux is also bimodal, reached a peak rate of 1-8 cubic kilometers per million years by 150Ma and remained above half this rate until about 90Ma, after which the volume flux diminished greatly. The onset of effusive volcanism from 200-150Ma might be due to a transition of volcanic style away from explosive volcanism that emplaced tephra on the western flank of Arsia Mons, while the waning of volcanism after the 150Ma peak might represent a larger-scale diminishing of volcanic activity at Arsia Mons related to the emplacement of flank apron lavas.
The effects of changing land use/land cover on global climate and ecosystems due to greenhouse gas emissions and changing energy and nutrient exchange rates are being addressed by federal programs such as NASA's Mission to Planet Earth (MTPE) and by international efforts such as the International Geosphere-Biosphere Program (IGBP). The quantification of these effects depends on accurate estimates of the global extent of critical land cover types such as fire scars in tropical savannas and ponds in Arctic tundra. To address the requirement for accurate areal estimates, methods for producing regional to global maps with satellite imagery are being developed. The only practical way to produce maps over large regions of the globe is with data of coarse spatial resolution, such as Advanced Very High Resolution Radiometer (AVHRR) weather satellite imagery at 1.1 km resolution or European Remote-Sensing Satellite (ERS) radar imagery at 100 m resolution. The accuracy of pixel counts as areal estimates is in doubt, especially for highly fragmented cover types such as fire scars and ponds. Efforts to improve areal estimates from coarse resolution maps have involved regression of apparent area from coarse data versus that from fine resolution in sample areas, but it has proven difficult to acquire sufficient fine scale data to develop the regression. A method for computing accurate estimates from coarse resolution maps using little or no fine data is therefore needed.
The Neutron Star Interior Composition Explorer (NICER) is an X-ray astrophysics payload on the International Space Station. It enables unprecedented high-precision timing of millisecond pulsars (MSPs) without the pulse broadening and delays due to dispersion and scattering within the interstellar medium that plague radio timing. We present initial timing results from a year of data on the MSPs PSR B1937+21 and PSR J0218+4232, and nine months of data on PSR B1821−24. NICER time-of-arrival uncertainties for the three pulsars are consistent with theoretical lower bounds and simulations based on their pulse shape templates and average source and background photon count rates. To estimate timing stability, we use the σz measure, which is based on the average of the cubic coefficients of polynomial fits to subsets of timing residuals. So far we are achieving timing stabilities σz≈3×10−14 for PSR B1937+21 and on the order of 10−12 for PSRs B1821−24 and J0218+4232. Within the span of our NICER data we do not yet see the characteristic break point in the slope of σz; detection of such a break would indicate that further improvement in the cumulative root-mean-square timing residual is limited by timing noise. We see this break point in our comparison radio data sets for PSR B1821−24 and PSR B1937+21 on timescales of >2 yr.