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The letter is a response to Frohlich's (1983) comments on an earlier paper (Mecherikunnel et al., 1983) containing a brief survey of the available data on the solar constant and its spectral distribution. The sources of the initial data used in the above study are mentioned, and comments are made on the accuracy of the measurements. Reasons are given for using NASA/ASTM data in the computations.
This research uses machine-learned computational analyses to predict the cognitive performance impairment of rats induced by irradiation. The experimental data in the analyses is from a rodent model exposed to ≤ 15 cGy of individual Galactic Cosmic Radiation (GCR) ions: 4He, 16O, 28Si, 48Ti, or 56Fe, expected for a Lunar or Mars mission. This work investigates rats at a subject-based level and uses performance scores taken before irradiation to predict impairment in Attentional Set-shifting (ATSET) data post-irradiation. Here, the worst performing rats of the control group define the impairment thresholds based on population analyses via cumulative distribution functions, leading to the labeling of impairment for each subject. A significant finding is the exhibition of a dose-dependent increasing probability of impairment for 1 to 10 cGy of 28Si or 56Fe in the Simple Discrimination (SD) stage of the ATSET, and for 1 to 10 cGy of 56Fe in the Compound Discrimination (CD) stage. On a subject-based level, implementing Machine Learning (ML) classifiers such as the Gaussian Naïve Bayes, Support Vector Machine, and Artificial Neural Networks identifies rats that have a higher tendency for impairment after GCR exposure. The algorithms employ the experimental prescreenperformance scores as multidimensional input features to predict each rodent’s susceptibility to cognitive impairment due to space radiation exposure. The receiver operating characteristic and the precision-recall curves of the ML models show a better prediction of impairment when 56Feis the ion in question in both SD and CD stages. They, however, do not depict impairment due to 4Hein SD and 28Siin CD, suggesting no dose-dependent impairment response in these cases. One key finding of our study is that prescreen performance scores can be used to predict the ATSET performance impairments. This result is significant to crewed space missions as it supports the potential of predicting an astronaut’s impairment in a specific task before spaceflight through the implementation of appropriately trained ML tools. Future research can focus on constructing ML ensemble methods to integrate the findings from the methodologies implemented in this study for morerobust predictionsof cognitive decrements due to space radiation exposure.
Over the last decade a series of techniques has been developed to correct hyperspectral imaging sensor data to apparent surface reflectance. The techniques range from the empirical line method that makes use of ground target measurements to model-based methods such as ATREM that derive parameters from the data themselves to convert radiance to reflectance, and combinations of the above. Here we describe a technique that combines ground measurements of spectral irradiance with existing radiative transfer models to derive the model equivalent of an empirical line method correction without the need for uniform ground targets of different reflectance.
The Experiment AO 138-6 was located on the trailing edge of the Long Duration Exposure Facility as part of the French Cooperative Payload (FRECOPA) Experiment. It was purely passive in nature: material specimens 2 x 2 cm, independently mounted in sample-holders, with their surface in the same reference plane, were exposed to space. Thirty samples were set in a vacuum-tight canister which was opened in space a few days after LDEF deployment and closed while still in orbit ten months later; twenty-four samples were directly exposed to space for the total flight duration (preflight handling, shuttle bay environment, separation from shuttle, shuttle environment, LEO environment, docking, descent, transfer to KSC). Materials included paints (conductive or nonconductive), SSM's, polymeric films, surface coatings, composite materials, and metals. After sample retrieving, inspection and measurements were carried out in atmospheric laboratory conditions on each sample: observation with binocular lenses and scanning electron microscopy, spectral relectance and transmittance using an integrating sphere in the wavelength range 280-2300 nm, emissivity by the means of a Gier & Dunkle portable reflectometer, electron spectroscopy for chemical analysis-x-ray photoelectron spectroscopy (ESCA-XPS), and Rutherford backscattering spectroscopy (RBS) measurements on some selected samples. The results obtained from flight were compared to laboratory data obtained in UV-irradiation tests when these data were available. As a general statement a good spectral concordance is observed for all samples not in the canister so long as air recoveries are taken into account. For one material, the degradation is more important for the sample in the canister than for those of the same material mounted at the surface of the tray; for most samples in the canister the degradation is slightly higher than the one which can be predicted from laboratory standard irradiations. Contamination problems having been ruled out, the higher temperature experience by the samples on the inside of canister probably explains these phenomena.
Characterization of temporal and spectral variations in solar ultraviolet irradiance over a solar cycle is essential for understanding the forcing of Earth's atmosphere and climate. Satellite measurements of solar UV variability for solar cycles 21, 22, and 23 show consistent solar cycle irradiance changes at key wavelengths (e.g. 205 nm, 250 nm) within instrumental uncertainties. All historical data sets also show the same relative spectral dependence for both short-term (rotational) and long-term (solar cycle) variations. Empirical solar irradiance models also produce long-term solar UV variations that agree well with observational data. Recent UV irradiance data from the Solar Radiation and Climate Experiment (SORCE) Spectral Irradiance Monitor (SIM) and Solar Stellar Irradiance Comparison Experiment (SOLSTICE) instruments covering the declining phase of Cycle 23 present a different picture oflong-term solar variations from previous results. Time series of SIM and SOLSTICE spectral irradiance data between 2003 and 2007 show solar variations that greatly exceed both previous measurements and predicted irradiance changes over this period, and the spectral dependence of the SIM and SOLSTICE variations during these years do not show features expected from solar physics theory. The use of SORCE irradiance variations in atmospheric models yields substantially different middle atmosphere ozone responses in both magnitude and vertical structure. However, short-term solar variability derived from SIM and SOLSTICE UV irradiance data is consistent with concurrent solar UV measurements from other instruments, as well as previous results, suggesting no change in solar physics. Our analysis of short-term solar variability is much less sensitive to residual instrument response changes than the observations of long-term variations. The SORCE long-term UV results can be explained by under-correction of instrument response changes during the first few years of measurements, rather than requiring an unexpected change in the physical behavior of the Sun.
Two count conversion algorithms and the associated dynamic sensor model for the M/WFOV nonscanner radiometers are defined. The sensor model provides and updates the constants necessary for the conversion algorithms, though the frequency with which these updates were needed was uncertain. This analysis therefore develops mathematical models for the conversion of irradiance at the sensor field of view (FOV) limiter into data counts, derives from this model two algorithms for the conversion of data counts to irradiance at the sensor FOV aperture and develops measurement models which account for a specific target source together with a sensor. The resulting algorithms are of the gain/offset and Kalman filter types. The gain/offset algorithm was chosen since it provided sufficient accuracy using simpler computations.
Surface radiation instruments were operated at various locations during the Wisconsin First ISSCP (International Satellite Cloud Climatology Project) Regional Experiment (FIRE) and Surface Radiation Budget (SRB) experiment in October 1986. Satellite data were distributed to scientists who had previously developed satellite algorithms to estimate downwelled shortwave irradiance. Results of intercomparison of ground-truth values with the satellite-derived estimates are described.
GOME radiance, irradiance, and ozone products were validated by NASA Goddard Space Flight Center through three tasks which included, pre-launch calibration comparisons with SBUV and TOMS radiometric standards, validation of GOME Level-1 irradiance and radiance and Level 2 total ozone data products using SBUV/2 and TOMS algorithms and data, and studies of GOME data using the Goddard radiative transfer code. The prelaunch calibration using the NASA large aperture integrating sphere was checked against that provided by TPD. Agreement in the calibration constants, derived in air, between the Goddard and TPD system were better than 3%. Validation of Level-1 irradiance data included comparison of GOME and SSBUV and the UARS solar irradiances measurements. Large wavelength dependent differences, as high as 10%, were noted between GOME and the US instruments. This discrepancy has now been attributed to radiometric sensitivity changes experienced by GOME when operating in a vacuum. GOME Earth radiance data were then compared to the NOAA-14 SBUV/2 radiances. These results show that between 340 and 400 nm the differences in GOME and SBUV/2 data are less than 5% with some wavelength dependence. At wavelengths shorter than 300 nm, differences are of the order of 10% or more where the GOME radiances are larger. To test GOME DOAS retrieved total ozone values, these values were compared with ozone amounts retrieved using GOME radiances in the TOMS version-7 algorithm. The differences showed a solar zenith angle dependence ranging from 0 to 10% where the TOMS algorithm values were higher. GOME radiances below 300 nm were further validated by selecting radiances at wavelengths normally used by SBUV and processing them through the SBUV ozone profile algorithm and then compared to climatological values. The GOME ozone profiles ranged from 10-30% lower over altitude compared to climatological values. This is consistent with the offsets detected in the SBUV/2 radiance comparisons at wavelengths shorter than 300 nm.
SOLERS22 Working Group 1 had extensive discussions of current and future space and ground-based observations of total solar irradiance as well as near-UV, visible, and infrared irradiances during the 1-day SOLERS22 meeting held at the IAU Colloquium No. 143 on June 25, 1993. The list of WG1 members attending this session is given at the end of this report.
Traditionally, accelerator SEE testing is accomplished by removing the tops of packages so that the IC chips are accessible to heavy ions. However, ICs in some advanced packages cannot be de-lidded so a different approach is used that involves grinding and/or chemically etching away part of the package and the chip from the back side. The parts are then tested from the back side with ions having sufficient range to reach the sensitive volume. More recently, the entire silicon substrate in an SOI/SRAM was removed, making it possible to use low-energy ions with shorter ranges. Where removal of part of the package is not possible, facilities at Michigan State, NASA Space Radiation Laboratory, GANIL (France) and GSI (Germany) offer high-energy heavy ions with long ranges so that the ions can reach the devices' sensitive volumes without much change in the LET. Unfortunately, a run will typically involve only one ion species having a single energy and LET due to the long time it takes to tune a new energy. The Variable Depth Bragg Peak (VDBP) method is similar to the above method in that it involves the use of high-energy heavy ions that are able to pass through the packaging material and reach the device, obviating the need to remove the package. However, the method provides a broad range of LETs from a single ion by inserting degraders in the beam that modify the ion energy and, therefore, the LET. The crux of the method involves establishing a fiduciary point for degrader thickness, i.e., where the Bragg peak is located precisely at the sensitive volume in the device, for which the measured SEU cross-section and the ion LET are both also maxima and can be calculated using a Monte-Carlo program, TRIM. Once the fiduciary point has been established, calibrated high density polyethylene (HDPE) degraders are inserted into or removed from the beam to vary the ion LET at the device in a known manner. After each change of degrader thickness, the SEU cross-section is measured and the corresponding LET calculated from the change in degrader thickness. That information is used to generate a plot of cross-section as a function of ion LET. The advantages of this approach are that the part does not have to be de-lidded and a broad range of LETs is available from a single heavy ion without having to go to non-normal angles of incidence to change the "effective" LET. As we will show, it is possible to obtain an entire curve of cross-section versus LET using just two or three ions. Fig. 1 shows curves of cross-section vs LET for a Freescale 4 Mbit SOI/SRAM measured at the 88" Cyclotron at Berkeley and at NSRL. The open symbols are the data obtained from Berkeley for top-side and back-side irradiation. The solid data points are for the data obtained at NSRL using a device for which the package was intact. The data are for Iron and Gold and cover a range of LETs from 4 MeV.cm2/mg to 84 MeV.cm2/mg. The agreement between the data obtained from Berkeley and from NSRL is excellent, demonstrating that the VDBP method is capable of providing accurate values of cross-section versus LET, at least for the 4 Mbit SRAM. Details of the technique will be included in the final presentation.
Available quantitative data on solar total and spectral irradiance is examined in the context of utilization of solar irradiance for terrestrial applications of solar energy. A brief review is given on the extraterrestrial solar total and spectral irradiance values. Computed values of solar spectral irradiance at ground level for different air mass values and various levels of atmospheric pollution or turbidity are also presented. Wavelengths are given for computation of solar absorptance, transmittance and reflectance by the 100-selected-ordinate method and by the 50-selected-ordinate method from air mass two solar spectral irradiance for the four degrees of atmospheric pollution. Total solar spectral irradiance measured with a prism monochromator is examined to evaluate the direct solar spectral irradiance for a surface normal to the sun's rays and to compare the computed spectrum with the experimentally observed one.
This report presents data for survival of mouse intestinal crypt cells, mouse testes weight loss as an indicator of survival of spermatogonial stem cells, and survival of rat 9L spheroid cells after irradiation in the plateau region of unmodified particle beams ranging in mass from 4He to 139La. The LET values range from 1.6 to 953 keV/microns. These studies examine the RBE-LET relationship for two normal tissues and for an in vitro tissue model, multicellular spheroids. When the RBE values are plotted as a function of LET, the resulting curve is characterized by a region in which RBE increases with LET, a peak RBE at an LET value of 100 keV/microns, and a region of decreasing RBE at LETs greater than 100 keV/microns. Inactivation cross sections (sigma) for these three biological systems have been calculated from the exponential terminal slope of the dose-response relationship for each ion. For this determination the dose is expressed as particle fluence and the parameter sigma indicates effect per particle. A plot of sigma versus LET shows that the curve for testes weight loss is shifted to the left, indicating greater radiosensitivity at lower LETs than for crypt cell and spheroid cell survival. The curves for cross section versus LET for all three model systems show similar characteristics with a relatively linear portion below 100 keV/microns and a region of lessened slope in the LET range above 100 keV/microns for testes and spheroids. The data indicate that the effectiveness per particle increases as a function of LET and, to a limited extent, Z, at LET values greater than 100 keV/microns. Previously published results for spread Bragg peaks are also summarized, and they suggest that RBE is dependent on both the LET and the Z of the particle.
The Solar Dynamics Observatory (SDO) was launched on February 11,2010 into partly cloudy skies over Cape Canaveral, Florida. SDO moved into a 28 degree inclined geosynchronous orbit over the longitude of the ground station in New Mexico. SDO is the first Space Weather Mission in NASA's Living With a Star Program. SDO's main goal is to understand and predict those solar variations that influence life on Earth and our technological systems. The SDO science investigations will determine how the Sun's magnetic field is generated and structured, how this stored magnetic energy is released into the heliosphere as the solar wind, energetic particles, and variations in the solar irradiance. The SDO mission consists of three scientific investigations (AIA, EVE, and HMI), a spacecraft bus, and a dedicated Ka-band ground station to handle the 150 Mbps data flow. SDO continues a long tradition of NASA missions providing calibrated solar spectral irradiance data, in this case using multiple measurements of the irradiance and rocket underflights of the spacecraft. The other instruments on SDO will be used to explain and develop predictive models of the solar spectral irradiance in the extreme ultraviolet. Science teams at LMSAL, LASP, and Stanford are responsible for processing, analyzing, distributing, and archiving the science data. We will talk about the building of SDO, its launch, and the data and science it will provide to NASA.
The Solar Dynamics Observatory (SDO) was launched on February 11, 2010 into the partly cloudy skies above Cape Canaveral, Florida. Over the next month SDO moved into a 28 degree inclined geosynchronous orbit at the longitude of the ground station in New Mexico. SDO is the first Space Weather Mission in NASA's Living With a Star Program. SDO's main goal is to understand and predict those solar variations that influence life on Earth and our technological systems. The SDO science investigations will determine how the Sun's magnetic field is generated and structured, how this stored magnetic energy is released into the heliosphere as the solar wind, energetic particles, and variations in the solar irradiance. The SDO mission consists of three scientific investigations (AIA, EVE, and HMI), a spacecraft bus, and a dedicated Ka-band ground station to handle the 150 Mbps data flow. SDO continues a long tradition of NASA missions providing calibrated solar spectral irradiance data, in this case using multiple measurements of the irradiance and rocket underflights of the spacecraft. The other instruments on SDO will be used to explain and develop predictive models of the solar spectral irradiance in the extreme ultraviolet. Science teams at LMSAL, LASP, and Stanford are responsible for processing, analyzing, distributing, and archiving the science data. We will talk about the launch of SDO and describe the data and science it is providing to NASA.
An empirical method was developed to measure how solar and atmospheric conditions affect Landsat images by comparing Landsat MSS data with terrain reflectance. Terrain reflectance was measured with a four-channel radiometer designed to measure radiance in wavelength bands matched to the Landsat MSS data. Other instrumentation included a digital data logger, an irradiance meter, and a video camera with recorder. Reflectance of many terrain elements which could be registered to the Landsat digital data were measured from a low-flying aircraft. Correlations of reflectance with Landsat radiance verified a linear atmospheric model with an additive (path radiance) term and a multiplicative (transmittance) term. Coefficients from this model permit the extension of spectral signatures in computer-aided classification of Landsat images.
The activity cavity radiometer irradiance monitor is supplying the first high precision data on solar total irradiance at the Earth. Thee classes of variability were discovered: large variations of amplitudes up to 0.2%; small high frequency variations in the form of a continuum in the periodogram, extending up to the Nyquist frequency; and sharp spikes at frequencies corresponding to the individual p modes already known from radial velocity measurements. The observed variations (up to 0.3%, on time scales of several days) were identified with sunspot darkness. The data analysis is expected to give information about the solar interior, as well as about the solar input to the terrestrial climate.
The analyses of Willson et al. (1981) and Hudson et al. (1981) are extended in correlating the total solar irradiance monitor (ACRIM) data with the routine synoptic sunspot data. At the simplest level, this correlation reveals clearly that the so-called 'missing flux' is truly missing in the sense that large young active regions do produce at net diminution of the irradiance when their spots cross the central meridian. It is pointed out that the irradiance deficit must of course be made up, either promptly or on intermediate time scales; this is because the surface effects cannot perturb the energy generation processes in the interior. In the approach taken here, simple models of the reemission are constructed, the total reemission is scaled to the estimated sunspot deficit, and an attempt is made to measure the parameters of the models by a statistical comparison with ACRIM data.
INTRODUCTION We use artificial neural networks (ANNs) as an example machine learning (ML) tool to predict the cognitive performance impairment of rats induced by irradiation. The experimental data in the analyses is attentional set-shifting (ATSET) test scores from a rodent model exposed to ≤15 cGy of individual galactic cosmic radiation (GCR) ions: 4He, 28Si, or 56Fe, expected for a Lunar or Mars mission [1]. This work investigates rats at a subject-based level and uses applied dose and performance scores taken before irradiation to predict whether a rat will be impaired when irradiated. The results of this study are significant to crewed space missions as they support the potential of predicting an astronaut’s impairment in a specific task before spaceflight through the implementation of appropriately trained ML tools. METHODS Data used in this work are scores from the ATSET, a multi-stage constrained cognitive flexibility test [2]. Our computational model utilizes the number of attempts to reach the criterion to pass a stage as a behavioral performance measure for rats. We use the post-irradiation scores, generate thresholds from cumulative distribution plots of non-irradiated rats, and calculate the percent of irradiated rats whose scores fall below the threshold to infer how each radiation type/dose affects a population. Rats scoring above the threshold are labeled impaired while the others are non-impaired. We then employ ANNs as a typical ML technique, and use each subject’s individual scores taken before radiation along with the applied dose, to predict their personal susceptibility to cognitive impairment due to space radiation exposure. RESULTS AND CONCLUSION A significant finding is the exhibition of a dose-dependent increasing probability of impairment for 1 to 10 cGy of 28Si or 56Fe in the simple discrimination (SD) stage of the ATSET, and for 1 to 10 cGy of 56Fe in the compound discrimination (CD) stage. On a subject-based level, implementing ML classifiers such as ANNs identifies rats that have a higher tendency for impairment after GCR exposure [1]. The receiver operating characteristic (ROC) and the precision-recall (PR) curves of the ML models show a better prediction of impairment when 56Fe is the ion in question in both SD (Figure 1) and CD stages. They, however, do not depict impairment due to 4He in SD (Figure 1) and 28Si in CD, suggesting no dose-dependent impairment response in these cases. In this work, “good” prediction pertains to “better-than-random-chance”, due to the limited sample size and the high inter- and intra-individual variabilities in response to brain stimulation paradigms, as applicable to both animals and humans. More behavioral tests and biomarkers should be investigated on the same subjects, to be fed to the ML models to capture the agents responsible for performance alterations of some individuals versus others.