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Five levels of image processing software are enumerated and discussed: (1) logging and formatting; (2) radiometric correction; (3) correction for geometric camera distortion; (4) geometric/navigational corrections; and (5) general software tools. Specific concerns about access to and analysis of digital imaging data within the Planetary Data System are listed.
The influence of varying the content of Co, Cr, Mo, Ta, and Al in a series of cast Ni-based gamma/gamma'superalloys on the behavior of aluminide coatings was studied in burner rig cyclic oxidation tests at 1100 C. The alloys had nominally fixed levels of Ti, W, Cb, Zr, C, and B. The alloy compositions were based on a full 2(sup 5)-fractional statistical design supplemented by 10 star point alloys and a center point alloy. This full central composite design of 43 alloys plus two additional alloys with extreme Al levels allowed a complete second degree estimating equation to be derived from the 5-compositional variables. The weight change/time data for the coated samples fitted well to the paralinear oxidation model and enabled a modified oxidation attack parameter, K'(sub a) to be derived to rank the alloys and log K' (sub a ) to be used as the dependent variable in the estimating equation to determine the oxidation resistance of the coating as a function of the underlying alloy content. The most protective aluminide coatings are associated with the highest possible base ally contents of CR and Al and at a 4 percent Ta level. The Mo and Co effects interact but at fixed levels of 0, 5, or 10% Co. A 4% Mo level is optimum.
The Calibrated Ancillary System (CAS) provides real-time calibrated parameters from the orbiter downlink (ancillary data) to the Goddard Space Flight Center (GSFC). This user's guide contains the introduction to the equipment, operation, general procedures, and specific procedures of the CAS. Volume 3 describes logging and delogging procedures, real-time procedures, and error messages.
This paper discusses the albedoes and phase angle effects found for 400 members of eight debris swarms using observations obtained in 1990 and 1991 with the NASA Johnson Space Center CCD-equipped portable Schmidt telescope. The mean albedo derived by comparing optical brightnesses with averaged radar cross sections (RCS's) is 10 percent. The standard deviation in log albedo is 0.40 if the RCS's are assumed to contribute equally to the scatter. The RCS's used in this work are the median values obtained by comparing data from 47 separate RCS catalog updates. Forty objects are sufficiently free of tumble or aspect angle effects to yield consistent phase function slopes. These range from specular in nature (zero slope) through Lambertian (moderate slope) to lunar (steep slope) with the mean lying midway between specular and Lambertian.
We analyze the temperature and EUV line emission of a coronal cavity and surrounding streamer in terms of a morphological forward model. We use a series of iron line ratios observed with the Hinode Extreme-ultraviolet Imaging Spectrograph (EIS) on 2007 Aug. 9 to constrain temperature as a function of altitude in a morphological forward model of the streamer and cavity. We also compare model prediction of the EIS EUV line intensities and polarized brightness (pB) data from the Mauna Loa Solar Observatory (MLSO) MK4. This work builds on earlier analysis using the same model to determine geometry of and density in the same cavity and streamer. The fit to the data with altitude dependent temperature profiles indicates that both the streamer and cavity have temperatures in the range 1.4-1.7 MK. However, the cavity exhibits substantial substructure such that the altitude dependent temperature profile is not sufficient to completely model conditions in the cavity. Coronal prominence cavities are structured by magnetism so clues to this structure are to be found in their plasma properties. These temperature substructures are likely related to structures in the cavity magnetic field. Furthermore, we find that the model overestimates the line intensities by a factor of 4-10, while overestimating pB data by no more than a factor of 1.4. One possible explanation for this is that there may be a significant amount of material at temperatures outside of the range log T(K) approximately equals 5.8 - 6.7 in both the cavity and the streamer.
A difficult aspect of cyber security is the ability to achieve automated real time intrusion prevention across various sets of systems. To this extent, several companies are offering comprehensive solutions that leverage an "accuracy of scale" and moving much of the intelligence and detection on the Cloud, relying on an ever-growing set of data and analytics to increase decision accuracy. Often, they provide tools to visualize the decision workflows in attack prevention (as well as tune the algorithm) but those solutions are not always practical as companies see the problem as "global" that is, from a unified Cyber-security standpoint. However, a key to a successful Cyber-security program is transparency and trust: from an experimental team viewpoint, this specifically means having the ability to immediately see what and from where, who has been blocked and being able to inform the community in case of a revoked access without the need for filing a "ticket" (that may eventually be answered) – in other words, rapid response to their user-base is essential but solutions targeting "sub-groups" in an organization are not often available. We have come up with a versatile solution leveraging the ELK stack (Elasticsearch, Logstash, & Kibana) and an IPS (Intrusion Prevention System) based WAF (Web Application Firewall) from Signal Sciences. Signal Science allows the streaming of detailed logs in a Logstash format suitable for custom solutions for visualization. By combining these two tools, we have strengthened our security posture and enabled individual experiments to monitor their own traffic. Specifically, the IPS WAF provides unique data such as country of origin, protocol, response code, source IP, and paths accessed. In this contribution, we will show how we engineered a visualization solution so experiment groups could access a dashboard with predefined graphs but also, where they can create individual customizable dashboards used to display blocked traffic and troubleshoot latency issues. We will discuss the details and procedures for developing and configuring these tools and how it benefits cyber security postures across our scientific based environment.
The PI of this project was Jeff Scargle of NASA/Ames. Co-I's were Alma Connors of Eureka Scientific/Wellesley, and myself. Part of the work was subcontracted to Eureka Scientific via SAO, with Vinay Kashyap as PI. This project was originally assigned grant number NCC2-1206, and was later changed to NCC2-1350 for administrative reasons. The goal of the project was to obtain, derive, and develop statistical and data analysis tools that would be of use in the analyses of high-resolution, high-sensitivity data that are becoming available with new instruments. This is envisioned as a cross-disciplinary effort with a number of "collaborators" including some at SA0 (Aneta Siemiginowska, Peter Freeman) and at the Harvard Statistics department (David van Dyk, Rostislav Protassov, Xiao-li Meng, Epaminondas Sourlas, et al). We have developed a new tool to reliably measure the metallicities of thermal plasma. It is unfeasible to obtain high-resolution grating spectra for most stars, and one must make the best possible determination based on lower-resolution, CCD-type spectra. It has been noticed that most analyses of such spectra have resulted in measured metallicities that were significantly lower than when compared with analyses of high- resolution grating data where available (see, e.g., Brickhouse et al., 2000, ApJ 530,387). Such results have led to the proposal of the existence of so-called Metal Abundance Deficient, or "MAD" stars (e.g., Drake, J.J., 1996, Cool Stars 9, ASP Conf.Ser. 109, 203). We however find that much of these analyses may be systematically underestimating the metallicities, and using a newly developed method to correctly treat the low-counts regime at the high-energy tail of the stellar spectra (van Dyk et al. 2001, ApJ 548,224), have found that the metallicities of these stars are generally comparable to their photospheric values. The results were reported at the AAS (Sourlas, Yu, van Dyk, Kashyap, and Drake, 2000, BAAS 196, v32, #54.02), and at the conference on Statistical Challenges in Modem Astronomy (Sourlas, van Dyk, Kashyap, Drake, and Pease, 2003, SCMA 111, Eds. E.D.Feigelson, G.J.Babu, New York:Springer, p489-490). We also described the limitations of one of the most egregiously misused and misapplied statistical tests in astrophysical literature, the F-test for verifying model components (Protassov, van Dyk, Connors, Kashyap, and Siemiginowska, 2002, ApJ, 571,545). Indeed, a search through the ApJ archives turned up 170 papers in the 5 previous years that used the F-test explicitly in some form or the other, and with the vast majority of them not using it correctly! Indeed, looking at just 4 issues of the ApJ in 2001, we found 13 instances of its use, of which nine were demonstrably incorrect. Clearly, it is difficult to understate the importance of this issue. We also worked on speeding up Bayes Blocks and Sparse Bayes Blocks algorithms to make them more tractable for large searches. We also supported staistics students and postdocs in both explicit physics- model-based (spectra with tens of thousands of atomic lines) and "model-free" -- i.e. non-parametric or semi-parametric -- algorithms. Work on using more of the latter is just beginning; while using multi-scale methods for Poisson imaging has come to hition. In fact, "An Image Restoration Technique with Error Estimates", by D. Esch, A. Connors, M. Karovska, and D. van Dyk, was published by ApJ (Esch et a1.2004, ApJ, 610, 1213). The code has been delivered to M. Karovska for CXC; and is available for beta-testing upon request. The other large project we worked on was on the self-consistent modeling of logN-logs curves in the Poisson limit. logN-logs curves are a fundamental tool in the study of source populations, luminosity functions, and cosmological parameters. However, their determination is hampered by statistical effects such as the Eddington bias, incompleteness due to detection efficiency, faint source flux fluctuations, etc. We have develed a new and powerful method using the full Poisson machinery that allows us to model the logN-logs distribution of X-ray sources in a self-consistent manner. Because we properly account for all the above statistical effects, our modeling is valid over the full range of the data, and not just for strong sources, as is normally done. Using a Bayesian approach and modeling the fluxes with known functional forms such as simple or broken power-laws, and conditioning the expected photon counts on the fluxes, the background contamination, effective area, detector vignetting, and detection probability, we can delve deeply into the low counts regime and extend the usefulness of medium sensitivity surveys such as ChAMP by orders of magnitude. The built-in flexibility of the algorithm also allows a simultaneous analysis of multiple datasets. We have applied this analysis to a set a Chandra observations (Sourlas, Kashyap, Zezas, van Dyk, 2004, HEAD #8, #16.32)
We derive direct-measurement gas-phase metallicities of 7.4 < 12 + log(O/H) < 8.4 for 14 low-mass emission- line galaxies at 0.3 < z < 0.8 identified in the Faint Infrared Grism Survey. We use deep slitless G102 grism spectroscopy of the Hubble Ultra Deep Field, dispersing light from all objects in the field at wavelengths between 0.85 and 1.15 μm. We run an automatic search routine on these spectra to robustly identify 71 emission-line sources, using archival data from Very Large Telescope (VLT)/Multi-Unit Spectroscopic Explorer (MUSE) to measure additional lines and confirm redshifts. We identify 14 objects with 0.3 < z < 0.8 with measurable [O III] λ4363 Å emission lines in matching VLT/MUSE spectra. For these galaxies, we derive direct electron-temperature gas-phase metallicities with a range of 7.4 < 12 + log(O/H) < 8.4. With matching stellar masses in the range of 10(exp 7.9) Solar Mass < M(sub *) < 10(exp 10.4) Solar Mass, we construct a mass–metallicity (MZ) relation and find that the relation is offset to lower metallicities compared to metallicities derived from alternative methods (e.g., R(sub 23), O3N2, N2O2) and continuum selected samples. Using star formation rates derived from the Hα emission line, we calculate our galaxies’ position on the Fundamental Metallicity Relation, where we also find an offset toward lower metallicities. This demonstrates that this emission-line-selected sample probes objects of low stellar masses but even lower metallicities than many comparable surveys. We detect a trend suggesting galaxies with higher Specific Star Formation (SSFR) are more likely to have lower metallicity. This could be due to cold accretion of metal-poor gas that drives star formation, or could be because outflows of metal-rich stellar winds and SNe ejecta are more common in galaxies with higher SSFR.
Abstract We present a synthetic multi‐scale, multi‐physics dataset constructed from the Kimberlina 1.2 CO 2 reservoir model based on a potential CO 2 storage site in the Southern San Joaquin Basin of California. Among 300 models, one selected reservoir‐simulation scenario produces hydrologic‐state models at the onset and after 20 years of CO 2 injection. Subsequently, these models were transformed into geophysical properties, including P‐ and S‐wave seismic velocities, saturated density where the saturating fluid can be a combination of brine and supercritical CO 2 , and electrical resistivity using established empirical petrophysical relationships. From these 3D distributions of geophysical properties, we have generated synthetic time‐lapse seismic, gravity and electromagnetic responses with acquisition geometries that mimic realistic monitoring surveys and are achievable in actual field situations. We have also created a series of synthetic well logs of CO 2 saturation, acoustic velocity, density and induction resistivity in the injection well and three monitoring wells. These were constructed by combining the low‐frequency trend of the geophysical models with the high‐frequency variations of actual well logs collected at the potential storage site. In addition, to better calibrate our datasets, measurements of permeability and pore connectivity have been made on cores of Vedder Sandstone, which forms the primary reservoir unit. These measurements provide the range of scales in the otherwise synthetic dataset to be as close to a real‐world situation as possible. This dataset consisting of the reservoir models, geophysical models, simulated time‐lapse geophysical responses and well logs forms a multi‐scale, multi‐physics testbed for designing and testing geophysical CO 2 monitoring systems as well as for imaging and characterization algorithms. The suite of numerical models and data have been made publicly available for downloading on the National Energy Technology Laboratory's (NETL) Energy Data Exchange (EDX) website.
We describe the ongoing efforts to apply Machine Learning techniques to improve the performance of our accelerator and target. Specially, we are looking to minimize halo beam losses in the absence of a proper physics model, automatically detect and log anomalies in the target support systems such as cooling, and detect and prevent errant beam pulses in the linac. We also describe the infrastructure we use to acquire and stream data to the GPU cluster for training, our code development cycle, and edge computing for model inference. To minimize halo beam losses, we use a Reinforcement Learning technique tested on a virtual accelerator. The target anomaly detection is trained on archived data using incomplete physics models and is made part of the existing target reporting system. The errant beam prevention analyzes beam current and beam phase waveforms as well as accelerator configuration data to predict errant pulses. We also develop continual learning to adapt to changes in the accelerator.
Background: Globally, loss to follow-up (LTFU) remains a significant public health concern despite the rapid expansion of antiretroviral medication programs. It is a significant cause of treatment failure and threatens the enhancement of HIV treatment outcomes among patients on antiretroviral therapy (ART). However, there is a paucity of evidence on its incidence and predictors in Ethiopia. Thus, this study aimed to examine the incidence and predictors of LTFU among adult HIV patients receiving ART at hospitals in Central Ethiopia. Methods: A multi-centered facility-based retrospective cohort study was conducted among 432 randomly selected adult patients who received antiretroviral therapy. Data were entered into EpiData version 3.1 and exported to Stata version 14 for analysis. The Kaplan–Meier failure function was employed to determine the overall failure estimates, and the log-rank test was used to compare the probability of failure among the different categories of variables. The Cox proportional hazard model was used to identify independent predictors of LTFU. Results: Overall, 172 (39.8%) study participants were lost to follow-up over the 10-year follow-up period with an incidence rate of 8.12 (95% CI: 7.11, 9.09) per 1,000 person-months. Undisclosed HIV status (AHR: 1.96, 95% CI: 1.14, 3.36), not able to work (AHR: 1.84, 95% CI: 1.13, 2.22), opportunistic infections (AHR: 3.13, 95% CI: 2.17, 4.52), CD4 < 200 cell/mL (AHR: 1.95, 95% CI: 1.18, 3.21), not receiving isoniazid preventive therapy (IPT) (AHR: 2.57, 95% CI: 1.62, 4.06), not participating in clubs (AHR: 1.68, 95% CI: 1.10, 2.22), side effects of drugs (AHR: 1.44, 95% CI: 1.02, 2.04), and high viral load (AHR: 3.15, 95% CI: 1.81, 5.47) were identified as significant predictors of loss to follow-up. Conclusion: In this study, the incidence of LTFU was high. The focus should be on creating awareness and prevention programs that aim to reduce loss to follow-up by continuing counseling, especially on the negative effects of loss to follow-up and the benefits of ART care.
Here we present the first results of our ongoing project conducting simultaneous multiwavelength observations of flares on nearby active M dwarfs. We acquired data of the nearby dM3.5e star EV Lac using five different observatories: NASA’s Transiting Exoplanet Survey Satellite (TESS), NASA’s Neil Gehrels Swift Observatory (Swift), NASA’s Neutron Interior Composition Explorer (NICER), the University of Hawaii 2.2-meter telescope (UH88), and the Las Cumbres Observatory Global Telescope (LCOGT) Network. During the ~25 days of TESS observations, we acquired three simultaneous UV/X-ray observations using Swift that total ~18 ks, 21 simultaneous epochs totaling ~98 ks of X-ray data using NICER, one observation (~3 hr) with UH88, and one observation (~3 hr) with LCOGT. We identified 56 flares in the TESS light curve with estimated energies in the range log E T (erg) = (30.5–33.2), nine flares in the Swift UVM2 light curve with estimated energies in the range log E UV (erg) = (29.3–31.1), 14 flares in the NICER light curve with estimated minimum energies in the range log E N (erg) = (30.5–32.3), and 1 flare in the LCOGT light curve with log E L (erg) = 31.6. We find that the flare frequency distributions (FFDs) of TESS and NICER flares have comparable slopes, β T = -0.67 ± 0.09 and β N = - 0.65 ± 0.19, and the FFD of UVOT flares has a shallower slope (β U = -0.38 ± 0.13). Furthermore, we do not find conclusive evidence for either the first ionization potential (FIP) or the inverse FIP effect during coronal flares on EV Lac.
We report evidence for a quasi-periodic oscillation (QPO) in the optical light curve of KIC 9650712, a narrow-line Seyfert 1 galaxy in the original Kepler field. After the development and application of a pipeline for Kepler data specific to active galactic nuclei (AGNs), one of our sample of 21 AGNs selected by infrared photometry and X-ray flux demonstrates a peak in the power spectrum at log ν = −6.58 Hz, corresponding to a temporal period of t = 44 days. We note that although the power spectrum is well fit by a model consisting of a Lorentzian and a single power law, alternative continuum models cannot be ruled out. From optical spectroscopy, we measure the black hole mass of this AGN as log (M(sub BH)/solar mass) = 8.17. We find that this frequency lies along a correlation between low-frequency QPOs and black hole mass from stellar and intermediate mass black holes to AGNs, similar to the known correlation in high-frequency QPOs.
We present the first results of our ongoing project conducting simultaneous multiwavelength observations of flares on nearby active M dwarfs. We acquired data of the nearby dM3.5e star EV Lac using five different observatories: NASA's Transiting Exoplanet Survey Satellite (TESS), NASA's Neil Gehrels Swift Observatory (Swift), NASA's Neutron Interior Composition Explorer (NICER), the University of Hawaii 2.2-meter telescope (UH88), and the Las Cumbres Observatory Global Telescope (LCOGT) Network. During the ∼25 days of TESS observations, we acquired three simultaneous UV/X-ray observations using Swift that total ∼18 ks, 21 simultaneous epochs totaling ∼98 ks of X-ray data using NICER, one observation (∼3 hr) with UH88, and one observation (∼3 hr) with LCOGT. We identified 56 flares in the TESS light curve with estimated energies in the range log E(T) (erg) = (30.5–33.2), nine flares in the Swift UVM2 light curve with estimated energies in the range log E(UV) (erg) = (29.3–31.1), 14 flares in the NICER light curve with estimated minimum energies in the range log E(N) (erg) = (30.5–32.3), and 1 flare in the LCOGT light curve with log E(L) (erg) = 31.6. We find that the flare frequency distributions (FFDs) of TESS and NICER flares have comparable slopes, β(T) = −0.67 ± 0.09 and β(N) = − 0.65 ± 0.19, and the FFD of UVOT flares has a shallower slope (β(U) = −0.38 ± 0.13). Furthermore, we do not find conclusive evidence for either the first ionization potential (FIP) or the inverse FIP effect during coronal flares on EV Lac.
Mercury, the innermost planet, formed under highly reduced conditions, based mainly on surface Fe, S, and Si abundances determined from MESSENGER mission data. The minor element Cr may serve as an independent oxybarometer but only very limited Cr data have been previously reported for Mercury. We report Cr/Si abundances across Mercury's surface based on MESSENGER X-Ray Spectrometer data throughout the spacecraft's orbital mission. The heterogeneous Cr/Si ratio ranges from 3.6 × 10 -5 in the Caloris Basin to 0.0012 within the high-magnesium region, with an average southern hemisphere value of 0.0008 (corresponding to about 200 ppm Cr). Absolute Cr/Si values have systematic uncertainty of at least 30%, but relative variations are more robust. By combining experimental Cr partitioning data along with planetary differentiation modeling, we find that if Mercury formed with bulk chondritic Cr/Al, Cr must be present in the planet's core and differentiation must have occurred at log ƒO 2 in the range of IW-6.5 to IW-2.5 in the absence of sulfides in its interior and a range of IW-5.5 to IW-2 with an FeS layer at the core-mantle boundary. Models with large fractions of Mg-Ca-rich sulfides in Mercury's interior are more compatible with moderately reducing conditions (IW-5.5 to IW-4) owing to the instability of Mg-Ca-rich sulfides at elevated ƒO 2 . These results indicate that if Mercury differentiated at a log ƒO 2 lower than IW-5.5, the presence of sulfides whether in the form of a FeS layer at the top of the core or Mg-Ca-rich sulfides within the mantle would be unlikely.
Scientific computing workloads at HPC facilities have been shifting from traditional numerical simulations to AI/ML applications for training and inference while processing and producing ever-increasing amounts of scientific data. To address the growing need for increased storage capacity, lower access latency, and higher bandwidth, emerging technologies such as non-volatile memory are integrated into supercomputer I/O subsystems. With these emerging trends, we need a better understanding of the multilayer supercomputer I/O systems and ways to use these subsystems efficiently. In this work, we study the I/O access patterns and performance characteristics of two representative supercomputer I/O subsystems. Through an extensive analysis of year-long I/O logs on each system, we report new observations in I/O reads and writes, unbalanced use of storage system layers, and new trends in user behaviors at the HPC I/O middleware stack.
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The International Mass Timber Alliance (IMTA) is a global organization of industry leaders, engineers, scientists, and associations dedicated to advancing mass timber construction. Its mission is to generate and disseminate scientific data supporting the development of standardized construction and energy efficient practices that promote the adoption of mass timber worldwide. IMTA collaborated with Oak Ridge National Laboratory (ORNL) to leverage ORNL’s expertise in building envelope modeling and testing to evaluate how mass timber construction can reduce peak heating and cooling demand, lower overall energy use, and improve resilience during power outages. A previous study of 80 mass timber buildings in Finland found measured energy use up to 50% lower than predicted by simulation. This project aimed to validate and extend those findings for U.S. buildings through analytical modeling, laboratory testing, and full-scale building evaluations. The research focused on the thermal performance of low-embodied-energy wall assemblies, such as cross-laminated timber (CLT) panels and log walls, with particular attention to the effects of thermal inertia on indoor comfort and energy performance. While mass timber’s structural and fire-resistance properties are well documented, its whole-building thermal behavior has received limited attention. Field data, simulation results, and resilience testing from this study will inform future modeling practices, design guidelines, and construction practices by quantifying the unique thermal and demand-flexibility benefits of mass timber construction.