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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

WE-A-17A-09: Exploiting Electromagnetic Technologies for Real-Time Seed Drop Position Validation in Permanent Implant Brachytherapy

Purpose: To report on preliminary results validating the performance of a specially designed LDR brachytherapy needle prototype possessing both electromagnetic (EM) tracking and seed drop detection abilities. Methods: An EM hollow needle prototype has been designed and constructed in collaboration with research partner Philips Healthcare. The needle possesses conventional 3D tracking capabilities, along with a novel seed drop detection mechanism exploiting local changes of electromagnetic properties generated by the passage of seeds in the needle's embedded sensor coils. These two capabilities are exploited by proprietary engineering and signal processing techniques to generate seed drop position estimates in real-time treatment delivery. The electromagnetic tracking system (EMTS) used for the experiment is the NDI Aurora Planar Field Generator. The experiment consisted of dropping a total of 35 seeds in a prismatic agarose phantom, and comparing the 3D seed drop positions of the EMTS to those obtained by an image analysis of subsequent micro-CT scans. Drop position error computations and statistical analysis were performed after a 3D registration of the two seed distributions. Results: Of the 35 seeds dropped in the phantom, 32 were properly detected by the needle prototype. Absolute drop position errors among the detected seeds ranged from 0.5 to 4.8 mm with mean and standard deviation values of 1.6 and 0.9 mm, respectively. Error measurements also include undesirable and uncontrollable effects such as seed motion upon deposition. The true accuracy performance of the needle prototype is therefore underestimated. Conclusion: This preliminary study demonstrates the potential benefits of EM technologies in detecting the passage of seeds in a hollow needle as a means of generating drop position estimates in real-time treatment delivery. Such tools could therefore represent a potentially interesting addition to existing brachytherapy protocols for rapid dosimetry validation. Equipments and fundings for this project were provided by Philips Medical.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

System wide analyses have underestimated protein abundances and the importance of transcription in mammals

Large scale surveys in mammalian tissue culture cells suggest that the protein expressed at the median abundance is present at 8000–16 000 molecules per cell and that differences in mRNA expression between genes explain only 10–40% of the differences in protein levels. We find, however, that these surveys have significantly underestimated protein abundances and the relative importance of transcription. Using individual measurements for 61 housekeeping proteins to rescale whole proteome data from Schwanhausser et al. (2011), we find that the median protein detected is expressed at 170 000 molecules per cell and that our corrected protein abundance estimates show a higher correlation with mRNA abundances than do the uncorrected protein data. In addition, we estimated the impact of further errors in mRNA and protein abundances using direct experimental measurements of these errors. The resulting analysis suggests that mRNA levels explain at least 56% of the differences in protein abundance for the 4212 genes detected by Schwanhausser et al. (2011), though because one major source of error could not be estimated the true percent contribution should be higher. We also employed a second, independent strategy to determine the contribution of mRNA levels to protein expression. We show that the variance in translation rates directly measured by ribosome profiling is only 12% of that inferred by Schwanhausser et al. (2011), and that the measured and inferred translation rates correlate poorly (R2 = 0.13). Based on this, our second strategy suggests that mRNA levels explain ~81% of the variance in protein levels. We also determined the percent contributions of transcription, RNA degradation, translation and protein degradation to the variance in protein abundances using both of our strategies. While the magnitudes of the two estimates vary, they both suggest that transcription plays a more important role than the earlier studies implied and translation a much smaller role. Finally, the above estimates only apply to those genes whose mRNA and protein expression was detected. Based on a detailed analysis by Hebenstreit et al. (2012), we estimate that approximately 40% of genes in a given cell within a population express no mRNA. Since there can be no translation in the absence of mRNA, we argue that differences in translation rates can play no role in determining the expression levels for the ~40% of genes that are non-expressed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Gaussian Kernel Methods for Seismic Fragility and Risk Assessment of Mid-Rise Buildings

Seismic fragility functions can be evaluated using the cloud analysis method with linear regression which makes three fundamental assumptions about the relation between structural response and seismic intensity: log-linear median relationship, constant standard deviation, and Gaussian distributed errors. While cloud analysis with linear regression is a popular method, the degree to which these individual and compounded assumptions affect the fragility and the risk of mid-rise buildings needs to be systematically studied. This paper conducts such a study considering three building archetypes that make up a bulk of the building stock: RC moment frame, steel moment frame, and wood shear wall. Gaussian kernel methods are employed to capture the data-driven variations in the median structural response and standard deviation and the distributions of residuals with the intensity level. With reference to the Gaussian kernels approach, it is found that while the linear regression assumptions may not affect the fragility functions of lower damage states, this conclusion does not hold for the higher damage states (such as the Complete state). In addition, the effects of linear regression assumptions on the seismic risk are evaluated. For predicting the demand hazard, it is found that the linear regression assumptions can impact the computed risk for larger structural response values. However, for predicting the loss hazard with downtime as the decision variable, linear regression can be considered adequate for all practical purposes.

58 GEOSCIENCES↗
DOE OSTI2015

Impact of baryonic processes on weak-lensing cosmology: Power spectrum, nonlocal statistics, and parameter bias

We study the impact of baryonic physics on cosmological parameter estimation with weak-lensing surveys. We run a set of cosmological hydrodynamics simulations with different galaxy formation models. We then perform ray-tracing simulations through the total matter density field to generate 100 independent convergence maps with a field of view of 25 deg{sup 2}, and we use them to examine the ability of the following three lensing statistics as cosmological probes: power spectrum (PS), peak counts, and Minkowski functionals (MFs). For the upcoming wide-field observations, such as the Subaru Hyper Suprime-Cam (HSC) survey with a sky coverage of 1400 deg{sup 2}, these three statistics provide tight constraints on the matter density, density fluctuation amplitude, and dark energy equation of state, but parameter bias is induced by baryonic processes such as gas cooling and stellar feedback. When we use PS, peak counts, and MFs, the magnitude of relative bias in the dark energy equation of state parameter w is at a level of, respectively, δw∼0.017, 0.061, and 0.0011. For the HSC survey, these values are smaller than the statistical errors estimated from Fisher analysis. The bias could be significant when the statistical errors become small in future observations with a much larger survey area. We find that the bias is induced in different directions in the parameter space depending on the statistics employed. While the two-point statistic, i.e., PS, yields robust results against baryonic effects, the overall constraining power is weak compared with peak counts and MFs. On the other hand, using one of peak counts or MFs, or combined analysis with multiple statistics, results in a biased parameter estimate. The bias can be as large as 1σ for the HSC survey and will be more significant for upcoming wider-area surveys. We suggest to use an optimized combination so that the baryonic effects on parameter estimation are mitigated. Such a “calibrated” combination can place stringent and robust constraints on cosmological parameters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

SU-C-BRD-04: Comparison of Shallow Fluence to Deep Point Dose Measurements for Spine VMAT SBRT Patient-Specific QA

Purpose: To investigate the sensitivity of traditional gamma-index-based fluence measurements for patient-specific measurements in VMAT delivered spine SBRT. Methods: The ten most recent cases for spine SBRT were selected. All cases were planned with Eclipse RapidArc for a TrueBeam STx. The delivery was verified using a point dose measurement with a Pinpoint 3D micro-ion chamber in a Standard Imaging Stereotactic Dose Verification Phantom. Two points were selected for each case, one within the target in a low dose-gradient region and one in the spinal cord. Measurements were localized using on-board CBCT. Cumulative and separate arc measurements were acquired with the ArcCheck and assessed using the SNC patient software with a 3%/3mm and 2%/2mm gamma analysis with global normalization and a 10% dose threshold. Correlations between data were determined using the Pearson Product-Moment Correlation. Results: For our cohort of patients, the measured doses were higher than calculated ranging from 2.2%–9.7% for the target and 1.0%–8.2% for the spinal cord. There was strong correlation between 3%/3mm and 2%/2mm passing rates (r=0.91). Moderate correlation was found between target and cord dose with a weak fit (r=0.67, R-Square=0.45). The cumulative ArcCheck measurements showed poor correlation with the measured point doses for both the target and cord (r=0.20, r=0.35). If the arcs are assessed separately with an acceptance criteria applied to the minimum passing rate between all arcs, a moderate negative correlation was found for the target and cord (r=−0.48, r= −0.71). The case with the highest dose difference (9.7%) received a passing rate of 97.2% for the cumulative arcs and 87.8% for the minimum with separate arcs. Conclusion: Our data suggest that traditional passing criteria using ArcCheck with cumulative measurements do not correlate well with dose errors. Separate arc analysis shows better correlation but may still miss large dose errors. Point dose verifications are recommended.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Quality Assurance With Plan Veto: Reincarnation of a Record and Verify System and Its Potential Value

Purpose: To quantify the potential impact of the Integrating the Healthcare Enterprise–Radiation Oncology Quality Assurance with Plan Veto (QAPV) on patient safety of external beam radiation therapy (RT) operations. Methods and Materials: An institutional database of events (errors and near-misses) was used to evaluate the ability of QAPV to prevent clinically observed events. We analyzed reported events that were related to Digital Imaging and Communications in Medicine RT plan parameter inconsistencies between the intended treatment (on the treatment planning system) and the delivered treatment (on the treatment machine). Critical Digital Imaging and Communications in Medicine RT plan parameters were identified. Each event was scored for importance using the Failure Mode and Effects Analysis methodology. Potential error occurrence (frequency) was derived according to the collected event data, along with the potential event severity, and the probability of detection with and without the theoretical implementation of the QAPV plan comparison check. Failure Mode and Effects Analysis Risk Priority Numbers (RPNs) with and without QAPV were compared to quantify the potential benefit of clinical implementation of QAPV. Results: The implementation of QAPV could reduce the RPN values for 15 of 22 (71%) of evaluated parameters, with an overall average reduction in RPN of 68 (range, 0-216). For the 6 high-risk parameters (>200), the average reduction in RPN value was 163 (range, 108-216). The RPN value reduction for the intermediate-risk (200 > RPN > 100) parameters was (0-140). With QAPV, the largest RPN value for “Beam Meterset” was reduced from 324 to 108. The maximum reduction in RPN value was for Beam Meterset (216, 66.7%), whereas the maximum percentage reduction was for Cumulative Meterset Weight (80, 88.9%). Conclusion: This analysis quantifies the value of the Integrating the Healthcare Enterprise–Radiation Oncology QAPV implementation in clinical workflow. We demonstrate that although QAPV does not provide a comprehensive solution for error prevention in RT, it can have a significant impact on a subset of the most severe clinically observed events.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Surface analysis insight note: X‐ray photoelectron spectroscopy analysis of battery electrodes—Challenges with nickel–manganese–cobalt and Li examples using an Al Kα x‐ray source

X‐ray photoelectron spectroscopy (XPS) has become a highly important tool for the analysis of battery materials and components. However, both anecdotal and detailed analysis of selected parts of the literature indicate that many reports of XPS on battery electrodes have significant analysis or data flaws. In this paper, we highlight several of the common challenges that analysts face when using XPS for battery materials, pointing to recent literature that addresses many of the critical issues associated with sample preparation as well as data collection and analysis. A common error for battery materials (and other materials) involves ignoring peak overlaps and interferences. Specifically, when a “minor” peak associated with a component in relatively high concentration overlaps or contributes to the primary peak (or one recommended for quantitative analysis) from a different element in the material. Overlap issues apply to many battery electrodes composed of many elements with complex photoelectron peak structures, as well as those involving peaks with seemingly simpler spectral envelopes such as Li and F. Examples of issues associated with battery systems are highlighted by a discussion of challenges associated with XPS analysis of Li and nickel–manganese–cobalt (NMC) electrodes in battery systems. Lithium analysis has challenges associated with the preparation and an often‐unrecognized peak overlap with F. In our laboratory and in the literature, NMC electrodes are often examined and new XPS users do not always recognize interference of the Auger signal from F KLL (in or on the electrode) with Ni 2p photoelectron spectrum when generated with Al Kα X‐rays. The use of simulated spectra involving both F and NiO demonstrates the extent of F Auger contributions to the Ni 2p signal strength as a function of the F/Ni atom ratio in the material and suggests spectra information that can be used to identify how significant effects will be on the resultant spectra. Our analysis demonstrates that in many cases overlap issues are significant for real electrode materials.

25 ENERGY STORAGE↗
DOE OSTI2019

High-Resolution, Rapid-Scan Dual-Doppler Retrievals of Vertical Velocity in a Simulated Supercell

Observation system simulation experiments are used to evaluate different dual-Doppler analysis (DDA) methods for retrieving vertical velocity w at grid spacings on the order of 100 m within a simulated tornadic supercell. Variational approaches with and without a vertical vorticity equation constraint are tested, along with a typical (traditional) method involving vertical integration of the mass conservation equation. The analyses employ emulated radar data from dual-Doppler placements 15, 30, and 45 km east of the mesocyclone, with volume scan intervals ranging from 10 to 150 s. The effect of near-surface data loss is examined by denying observations below 1 km in some of the analyses. At the longer radar ranges and when no data denial is imposed, the “traditional” method produces results similar to those of the variational method and is much less expensive to implement. However, at close range and/or with data denial, the variational method is much more accurate, confirming results from previous studies. The vorticity constraint shows the potential to improve the variational analysis substantially, reducing errors in the w retrieval by up to 30% for rapid-scan observations (≤30 s) at close range when the local vorticity tendency is estimated using spatially variable advection correction. However, the vorticity constraint also degrades the analysis for longer scan intervals, and the impact diminishes with increased range. Furthermore, analyses using 30-s data also frequently outperform analyses using 10-s data, suggesting a limit to the benefit of increasing the radar scan rate for variational DDA employing the vorticity constraint.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Water transport properties of virtual fractal porous media: Implications for the unsaturated transport properties of cement-based materials

Cement-based materials are more and more recognized as fractal materials. From a practical point of view, fractality means that the pore size distribution can be described using fractal scaling law (i.e. power functions). Here, the simplest scaling law making use of a single fractal dimension was used to generate simple and virtual fractal porous media (based on bundles of parallel cylindrical pores). The capillary curve and permeability (relative and intrinsic) of the virtual porous media were then estimated through theoretical and numerical approaches. The results show that: (1) although bereft of any physical basis, van Genuchten equation bears some fractal information; (2) although highly flexible, van Genuchten equation fails to perfectly fit the capillary curves and can thus generate error in inverse analysis (for intrinsic permeability evaluation) and (3) there seems to be a relation between the intrinsic permeability and van Genuchten pressure parameter.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Understanding and Estimating Error Propagation in Neural Networks for Scientific Data Analysis

Neural networks are increasingly integrated into scientific discovery, where input data reduction and model quantization play a key role in accelerating inference. However, understanding and mitigating the impact of these techniques on output error is critical for ensuring reliable results, particularly in tasks demanding high numerical precision. This paper introduces a comprehensive framework for optimizing neural network inference in scientific computing by combining data reduction and weight quantization while maintaining error-controlled outcomes. We develop theoretical analyses to bound error propagation under these reductions and propose a framework that balances computational performance with error constraints. Evaluation on real-world learning-based combustion simulations and satellite image classification demonstrates that our derived error bounds accurately predict observed errors while enabling significant computational speedup under our framework. This work highlights the potential for further leveraging advancements in modern lossy compression algorithms and hardware accelerators that support lower-precision formats.

He, Weiming [New Jersey Institute of Technology]↗
DOE OSTI2017

Model Uncertainties for Valencia RPA Effect for MINERvA

This technical note describes the application of the Valencia RPA multi-nucleon effect and its uncertainty to QE reactions from the GENIE neutrino event generator. The analysis of MINERvA neutrino data in Rodrigues et al. PRL 116 071802 (2016) paper makes clear the need for an RPA suppression, especially at very low momentum and energy transfer. That published analysis does not constrain the magnitude of the effect; it only tests models with and without the effect against the data. Other MINERvA analyses need an expression of the model uncertainty in the RPA effect. A well-described uncertainty can be used for systematics for unfolding, for model errors in the analysis of non-QE samples, and as input for fitting exercises for model testing or constraining backgrounds. This prescription takes uncertainties on the parameters in the Valencia RPA model and adds a (not-as-tight) constraint from muon capture data. For MINERvA we apply it as a 2D ($q_0$,$q_3$) weight to GENIE events, in lieu of generating a full beyond-Fermi-gas quasielastic events. Because it is a weight, it can be applied to the generated and fully Geant4 simulated events used in analysis without a special GENIE sample. For some limited uses, it could be cast as a 1D $Q^2$ weight without much trouble. This procedure is a suitable starting point for NOvA and DUNE where the energy dependence is modest, but probably not adequate for T2K or MicroBooNE.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Modeling the Echelle Spectra Continuum with Alpha Shapes and Local Regression Fitting

Continuum normalization of echelle spectra is an important data analysis step that is difficult to automate. Polynomial fitting requires a reasonably high-order model to follow the steep slope of the blaze function. However, in the presence of deep spectral lines, a high-order polynomial fit can result in ripples in the normalized continuum that increase errors in spectral analysis. Here, we present two algorithms for flattening the spectrum continuum. The Alpha-shape Fitting to Spectrum algorithm is completely data driven, using an alpha shape to obtain an initial estimate of the blaze function. The Alpha-shape and Lab Source Fitting to Spectrum algorithm incorporates a continuum constraint from a laboratory source reference spectrum for the blaze function estimation. These algorithms are tested on a simulated spectrum, where we demonstrate improved normalization compared to polynomial regression for continuum fitting. We show an additional application, using the algorithms for mitigation of spatially correlated quantum efficiency variations and fringing in the charge-coupled device detector of the EXtreme PREcision Spectrometer.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Surface temperature comparison of the Arctic winter MOSAiC observations, ERA5 reanalysis, and MODIS satellite retrieval

Atmospheric model systems, such as those used for weather forecast and reanalysis production, often have significant and systematic errors in their representation of the Arctic surface energy budget and its components. The newly available observation data of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition (2019/2020) enable a range of model analyses and validation in order to advance our understanding of potential model deficiencies. In the present study, we analyze deficiencies in the surface radiative energy budget over Arctic sea ice in the ERA5 global atmospheric reanalysis by comparing against the winter MOSAiC campaign data, as well as, a pan-Arctic level-2 MODIS ice surface temperature remote sensing product. We find that ERA5 can simulate the timing of radiatively clear periods, though it is not able to distinguish the two observed radiative Arctic winter states, radiatively clear and opaquely cloudy, in the distribution of the net surface radiative budget. The ERA5 surface temperature over Arctic sea ice has a conditional error with a positive bias in radiatively clear conditions and a negative bias in opaquely cloudy conditions. The mean surface temperature error is 4°C for radiatively clear situations at MOSAiC and up to 15°C in some parts of the Arctic. The spatial variability of the surface temperature, given by 4 observation sites at MOSAiC, is not captured by ERA5 due to its spatial resolution but represented in the level-2 satellite product. The sensitivity analysis of possible error sources, using satellite products of snow depth and sea ice thickness, shows that the positive surface temperature errors during radiatively clear events are, to a large extent, caused by insufficient sea ice thickness and snow depth representation in the reanalysis system. A positive bias characterizes regions with ice thickness greater than 1.5 m, while the negative bias for thinner ice is partly compensated by the effect of snow.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Screening-Constant-by-Unit-Nuclear-Charge method investigations of high lying ({sup 1}D{sub 2},{sup 1}S{sub 0}) ns, nd Rydberg series in the photoionization spectra of the halogen-like ion Kr{sup +}

Energy positions and quantum defects of the 4s{sup 2}4p{sup 4} ({sup 1}D{sub 2},{sup 1}S{sub 0}) ns, nd Rydberg series originating from the 4s{sup 2}4p{sup 52}P{sub 3/2}{sup ∘} ground state and from the 4s{sup 2}4p{sup 52}P{sub 1/2}{sup ∘} metastable state of Kr{sup +} are reported. Calculations are performed using the Screening Constant by Unit Nuclear Charge (SCUNC) method. The results obtained are in suitable agreement with recent experimental data from the combined ASTRID merged-beam set up and Fourier Transform Ion Cyclotron Resonance device (Bizau et al., 2011), ALS measurements (Hinojosa et al., 2012), and multi-channel R-matrix eigenphase derivative calculations (McLaughlin and Balance, 2012). In addition, analysis of the 4s{sup 2}4p{sup 4}({sup 1}D{sub 2})nd and the 4s{sup 2}4p{sup 4}({sup 1}S{sub 0})nd resonances is given via the SCUNC procedure. The excellent results obtained from our work point out that the SCUNC formalism may be used to confirm the results of the analysis from the standard quantum-defect expansion formulas. Eventual errors occurring in the analysis can then be automatically detected and corrected via the SCUNC procedure.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2019

Optimization of Kaplan Hydroturbine at Very Low Head With Rim-Driven Generator

The objective of the paper is to study the design and optimization of Kaplan hydroturbines for a very low head (less than 3 m), with a particular emphasis on the use of rim-drive electrical generators. The work is based on an experimental setup and computational fluid dynamics (CFD) analysis of various design parameters for maximum output power and efficiency. Two designs are presented in this paper. One is a 90-cm (35-in.) diameter vertical-oriented Kaplan hydroturbine system as an intended product capable of generating over 50 kW. The other is a smaller, 7.6-cm (3-in.) diameter horizontal-oriented system for prototyping and laboratory verification. Both are analyzed through CFD based on large eddy simulation (LES) of transient turbulence. Specific design for the runner and the stator, intake tube shape, as well as guide vanes upstream of the turbine was studied to get the most from the available head. The intent is to use 3D-printing manufacturing techniques, which may offer original design opportunities as well as the possibility of turbine and water conduit design customization as a function of the head and flow available from a specific site. Based on the CFD analysis, the 7.6-cm diameter system achieved the highest power output and the maximum efficiency at the rotational speed range of 1500–2000 rpm, while for the experimental testing, the optimum rotational speed range was 1000–1500 rpm. Because of the mismatch between CFD and experimental results, the CFD results were correlated due to the presence of air and friction; moreover, error and uncertainty analysis were presented for both methods. For the 90-cm case, the optimum performance was found at a rotational speed around 350 rpm according to the CFD results. Finally, investigating the shape of the intake tube of the hydroturbine setup can significantly increase the power output and the efficiency of the system.

Energy & Fuels↗
DOE OSTI2016

Is the expansion of the universe accelerating? All signs point to yes

The accelerating expansion of the universe is one of the most profound discoveries in modern cosmology, suggesting a universe in which 70% of the mass-energy density has an unknown form spread uniformly across the universe. This result has been well established using a combination of cosmological probes, resulting in a “standard model” of modern cosmology that is a combination of a cosmological constant with cold dark matter and baryons. The first compelling evidence for the acceleration came in the late 1990s, when two independent teams studying Type Ia supernovae discovered that distant SNe Ia were dimmer than expected. The combined analysis of modern cosmology experiments, including SNe Ia, the Hubble constant, baryon acoustic oscillations, and the cosmic microwave background, has now measured the contributions of matter and the cosmological constant to the energy density of the universe to better than 0.01, providing a secure measurement of acceleration. A recent study has claimed that the evidence for acceleration from SNe Ia is “marginal.” Here we demonstrate errors in that analysis that reduce the acceleration significance from SNe Ia, and further demonstrate that conservative constraints on the curvature or matter density of the universe increase the significance even more. Analyzing the Joint Light-curve Analysis supernova sample, we find 4.2σ evidence for acceleration with SNe Ia alone, and 11.2σ in a flat universe. With our improved supernova analysis and not rejecting all other cosmological constraints, we find that acceleration is quite secure.

79 ASTRONOMY AND ASTROPHYSICS↗