adsabs/AstroCLIMB huggingface dataset:
Paper: Electron Acceleration in Magnetic Islands in Quasi-parallel Shocks
Authors: N. Bessho, L.-J. Chen, M. Hesse, J. Ng, L. B. Wilson, J. E. Stawarz, H. Madanian
Figure caption: (a) Current density J  z  at Ω i  t = 20.63. (b) Electron temperature T  e . (c) Electric field E  y . The black curves are the magnetic field lines projected on the x–y plane. (d) Electron energy distribution in 45d  i  < x < 47d  i  (marked by the red bar in (a)–(c)). The vertical line represents a Lorentz factor of γ = 7.5.
Paper: A Comprehensive Study of Open Cluster Chemical Homogeneity Using APOGEE and Milky Way Mapper Abundances
Authors: Amaya Sinha, Gail Zasowski, Peter Frinchaboy, Katia Cunha, Diogo Souto, Jamie Tayar, Keivan Stassun
Figure caption: Cluster membership plot for M67. Top left: the distribution of stars on the sky in R.A. and decl., with cluster members colored in blue, cluster member candidates that did not pass Section 2.2.1's kinematic and parallax cuts in red, and field stars in gray. Top right: the KDE distribution of radial velocities of the cluster members compared to nearby field stars. Middle left: the distribution of the combined proper motion of the cluster members compared to nearby field stars. Middle right: the distribution of parallaxes of the cluster members compared to nearby field stars. Bottom left: the distribution of [Fe/H] of the cluster members compared to nearby field stars; note that this was not used to prune membership. Bottom right: The Kiel diagram of cluster members compared to surrounding stars. We also plot the MIST isochrone (J. Choi et al. 2016; A. Dotter 2016) for this cluster’s age and metallicity in black.
Paper: A Comprehensive Study of Open Cluster Chemical Homogeneity Using APOGEE and Milky Way Mapper Abundances
Authors: Amaya Sinha, Gail Zasowski, Peter Frinchaboy, Katia Cunha, Diogo Souto, Jamie Tayar, Keivan Stassun
Figure caption: The literature comparison plots for the well-studied OCs in our sample using APOGEE DR17 (colored in black). The horizontal line indicates the median 99.7% confidence limit for that cluster’s homogeneity.
Paper: A Comprehensive Study of Open Cluster Chemical Homogeneity Using APOGEE and Milky Way Mapper Abundances
Authors: Amaya Sinha, Gail Zasowski, Peter Frinchaboy, Katia Cunha, Diogo Souto, Jamie Tayar, Keivan Stassun
Figure caption: The literature comparison plots for the well-studied OCs in our sample using IPL-3 Cannon (colored in blue). The horizontal line indicates the median 99.7% confidence limit for that cluster’s homogeneity.
Paper: A Comprehensive Study of Open Cluster Chemical Homogeneity Using APOGEE and Milky Way Mapper Abundances
Authors: Amaya Sinha, Gail Zasowski, Peter Frinchaboy, Katia Cunha, Diogo Souto, Jamie Tayar, Keivan Stassun
Figure caption: The literature comparison plots for the well-studied OCs in our sample using IPL-3 Payne (colored in red). The horizontal line indicates the median 99.7% confidence limit for that cluster’s homogeneity.
Paper: A Comprehensive Study of Open Cluster Chemical Homogeneity Using APOGEE and Milky Way Mapper Abundances
Authors: Amaya Sinha, Gail Zasowski, Peter Frinchaboy, Katia Cunha, Diogo Souto, Jamie Tayar, Keivan Stassun
Figure caption: These figure follows the same layout as Figure 1 in Section 2.2.1.
Paper: A Comprehensive Study of Open Cluster Chemical Homogeneity Using APOGEE and Milky Way Mapper Abundances
Authors: Amaya Sinha, Gail Zasowski, Peter Frinchaboy, Katia Cunha, Diogo Souto, Jamie Tayar, Keivan Stassun
Figure caption: This figure follows the same layout as Figure 1 in Section 2.2.1.
Paper: Regulation of Solar Wind Electron Temperature Anisotropy by Collisions and Instabilities
Authors: Peter H. Yoon, Chadi S. Salem, Kristopher G. Klein, Mihailo M. Martinović, Rodrigo A. López, Jungjoon Seough, Muhammad Sarfraz, Marian Lazar, Shaaban M. Shaaban
Figure caption: (Left) Initial ensemble positions of core electrons plotted against the backdrop of core electron data distribution. (Right) The same for the halo electrons, plotted against the backdrop of halo electron 2D distribution. The numerical designations signify the case numbers; 1–81. The colormap background data distributions use electron measurements from the Helios mission.
Paper: Regulation of Solar Wind Electron Temperature Anisotropy by Collisions and Instabilities
Authors: Peter H. Yoon, Chadi S. Salem, Kristopher G. Klein, Mihailo M. Martinović, Rodrigo A. López, Jungjoon Seough, Muhammad Sarfraz, Marian Lazar, Shaaban M. Shaaban
Figure caption: (Left) Initial ensemble positions in the case of collective instability saturation, for core electrons plotted against the backdrop of core electron data distribution. (Right) The same for the halo electrons, plotted against the backdrop of halo electron 2D distribution.
Paper: Determining the Extents, Geometries, and Kinematics of Narrow-line Region Outflows in Nearby Seyfert Galaxies
Authors: Garrett E. Polack, Mitchell Revalski, D. Michael Crenshaw, Travis C. Fischer, Henrique R. Schmitt, Steven B. Kraemer, Beena Meena, Marc Rafelski
Figure caption: Kinematic plots for the full sample of AGN, following the same structure detailed in Figure 8.
Paper: Determining the Extents, Geometries, and Kinematics of Narrow-line Region Outflows in Nearby Seyfert Galaxies
Authors: Garrett E. Polack, Mitchell Revalski, D. Michael Crenshaw, Travis C. Fischer, Henrique R. Schmitt, Steven B. Kraemer, Beena Meena, Marc Rafelski
Figure caption: Output plots from the isophotal ellipse models shown in Appendix B. The x-axis gives distance from the nucleus in arcseconds, while the y-axis shows the model ellipticity, major axis position angle in degrees, and surface brightness in log counts for each elliptical isophote.
Paper: Primordial Black Holes Generated by Fast-roll Mechanism in Noncanonical Natural Inflation
Authors: Soma Heydari, Kayoomars Karami
Figure caption: Variations of (a) the scalar field, (b) the Hubble parameter, (c) the field derivative, (d) the first SR parameter, and (e) the second SR parameter against the e-folds number N for cases A (red curves), B (green curves), C (blue curves), D (purple curves), and F (brown curves).
Paper: Primordial Black Holes Generated by Fast-roll Mechanism in Noncanonical Natural Inflation
Authors: Soma Heydari, Kayoomars Karami
Figure caption: The PBH mass spectra concerning cases A (red curve), B (green curve), C (blue curve), and F (brown curve). The observational restricted portions are demonstrated by colored domains. The disallowed portions are prohibited by observations of CMB (P. D. Serpico et al. 2020; purple portion), LIGO–Virgo event (B. J. Kavanagh et al. 2018; B. P. Abbott et al. 2019; Z. C. Chen & Q. G. Huang 2020; C. Bœhm et al. 2021; red portion), microlensing events through MACHO (C. Alcock et al. 2001) and EROS (P. Tisserand et al. 2007; khaki portion), Kepler (K. Griest et al. 2014; blue portion), Icarus (M. Oguri et al. 2018), OGLE (P. Mroz et al. 2017; H. Niikura et al. 2019), and Subaru-HSC (D. Croon et al. 2020; green portion), and PBHs evaporation (B. J. Carr et al. 2010; S. Clark et al. 2017; R. Laha 2019; B. Dasgupta et al. 2020; S. Mittal et al. 2022; pink portion). The only permissible portion (the brown portion) in the plot is defined by the ultrashort-timescale microlensing events in the OGLE data (P. Mroz et al. 2017; H. Niikura et al. 2019).
Paper: Primordial Black Holes Generated by Fast-roll Mechanism in Noncanonical Natural Inflation
Authors: Soma Heydari, Kayoomars Karami
Figure caption: (Left) The curvature power spectra with regard to wavenumber k for cases A (red curve), B (green curve), C (blue curve), and D (purple curve). Here, the red, blue, and green circles depict k *, k peak, and k reh. (Right) The comoving Hubble radius against N, in which the red, blue, and green circles depict the horizon leaving (reverting) for the scales ﹩{k}_{* }^{-1}﹩, ﹩{k}_{\mathrm{peak}}^{-1}﹩, and ﹩{k}_{\mathrm{reh}}^{-1}﹩, respectively. The shadowy portions correspond to the reverting scales to the horizon during the reheating stage.
Paper: Primordial Black Holes Generated by Fast-roll Mechanism in Noncanonical Natural Inflation
Authors: Soma Heydari, Kayoomars Karami
Figure caption: Same as Figure 4, but for case F (brown curve) realizing slow-reheating period with N reh = 24.63 and low temperature T reh = 1.33 × 107GeV.
Paper: Primordial Black Holes Generated by Fast-roll Mechanism in Noncanonical Natural Inflation
Authors: Soma Heydari, Kayoomars Karami
Figure caption: The present-time density spectra of the secondary GWs ﹩{{\rm{\Omega }}}_{{\mathrm{GW}}_{0}}{h}^{2}﹩ with regard to frequency for cases A (red curve), B (green curve), C (blue curve), D (purple curve), and F (brown curve) as well as the observational dominions of EPTA (brown domain), SKA (purple domain), NANOGrav 15 yr data (gray shadowy area), LISA (orange domain), DECIGO (red domain), and BBO (green domain). The power-like functioning of ﹩{{\rm{\Omega }}}_{{\mathrm{GW}}_{0}}{h}^{2}﹩ spectra has been represented by dashed black lines in various frequency ranges according to Table 5 for cases A and D.
Paper: Primordial Black Holes Generated by Fast-roll Mechanism in Noncanonical Natural Inflation
Authors: Soma Heydari, Kayoomars Karami
Figure caption: (a) The curvature and (b) the tensor power spectra with regard to the comoving wavenumber k for Cases A (red curves), B (green curves), C (blue curves), D (purple curves), and F (brown curves). The colored zones are prohibited through the CMB observations (Y. Akrami et al. 2020; light-green), PTA observations (K. Inomata & T. Nakama 2019; yellow), the impact on the ratio of neutrons to protons in the course of Big Bang nucleosynthesis (BBN; D. Jeong et al. 2014; T. Nakama et al. 2014; K. Inomata et al. 2016; cyan), and the μ-distortion of CMB (D. J. Fixsen et al. 1996; J. Chluba et al. 2012; orange).
Paper: Primordial Black Holes Generated by Fast-roll Mechanism in Noncanonical Natural Inflation
Authors: Soma Heydari, Kayoomars Karami
Figure caption: Establishment of the swampland criteria for cases of the model encompass (a) the distance conjecture Δϕ/M  P  < c 1 and (b) the de Sitter conjecture M  P ∣V ,ϕ /V∣ > c 2.
Paper: The Diffusion Tensor of Protons at 1 au: Comparing Simulation, Observation, and Theory
Authors: P. L. Els, N. E. Engelbrecht, J. T. Lang, R. D. Strauss
Figure caption: Comparison of simulation results (small green points) vs. prior observational estimates for the proton perpendicular MFP, as a function of rigidity. The gray dashed line denotes the I. D. Palmer (1982) consensus range, while other observational points are taken from R. A. Burger et al. (2000). Theoretical estimates shown are calculated from the UNLT (Equation (17), blue dashed line), RBD (Equation (19), red line), FLRW (Equation (21), black dashed line), and NLGC (Equation (22), solid black line) theories. Also shown are theoretical values for λ ⊥ computed for all combinations of parameters listed in Table 1. See text for details.
Paper: The Diffusion Tensor of Protons at 1 au: Comparing Simulation, Observation, and Theory
Authors: P. L. Els, N. E. Engelbrecht, J. T. Lang, R. D. Strauss
Figure caption: Comparison of simulation results (small green bars) vs. prior observational estimates for the proton parallel MFP, as a function of rigidity. The gray shaded region denotes the I. D. Palmer (1982) consensus range, while other observational points are taken from J. W. Bieber et al. (1994, 2002, 2004), A. Sáiz et al. (2005), W. Dröge et al. (2014), and J. T. Lang et al. (2024). The black line indicates the magnetostatic QLT parallel MFP (Equation (14)), and small horizontal red dashes denote values for λ ∥ computed using Equation (14) for all combinations of parameters listed in Table 1. See text for details.
Paper: The Diffusion Tensor of Protons at 1 au: Comparing Simulation, Observation, and Theory
Authors: P. L. Els, N. E. Engelbrecht, J. T. Lang, R. D. Strauss
Figure caption: Top panels: histograms of exponents acquired through power-law fits to simulated parallel (left panels) and perpendicular (right panels) MFPs (blue bars) for all nine simulated energies. Middle panels: same as the top panels, but for MFPs calculated for the theoretical expressions introduced in Section 3.2, using as inputs parameter combinations from Table 1. Vertical lines indicate expected theoretical values. Bottom panels: Pearson correlation coefficients for both simulation fits (blue bars) and various theory fits. See text for details.
Paper: The Diffusion Tensor of Protons at 1 au: Comparing Simulation, Observation, and Theory
Authors: P. L. Els, N. E. Engelbrecht, J. T. Lang, R. D. Strauss
Figure caption: Top panel: simulated drift reduction term κ  A /κ ws as a function of rigidity, compared with different theoretical models for the drift reduction term. Bottom panel: simulated drift reduction term as a function of perpendicular MFP, color-coded by particle rigidity.
Paper: The Diffusion Tensor of Protons at 1 au: Comparing Simulation, Observation, and Theory
Authors: P. L. Els, N. E. Engelbrecht, J. T. Lang, R. D. Strauss
Figure caption: Histograms of exponents acquired through power-law fits to simulated parallel (left panels) and perpendicular (right panels) MFPs (blue bars), alongside their corresponding Pearson coefficients (orange bars). Top panels show results from fits to MFPs at the lowest three simulation energies, middle panels show results to fits for MFPs at the three intermediate energies, and bottom panels show results from fits to the three highest energies. Vertical lines indicate expected theoretical values. See text for details.
Paper: The Diffusion Tensor of Protons at 1 au: Comparing Simulation, Observation, and Theory
Authors: P. L. Els, N. E. Engelbrecht, J. T. Lang, R. D. Strauss
Figure caption: Plot of all simulated MFPs (in au) as a function of rigidity (in GV). The top panel shows the parallel MFP, the middle panel shows the perpendicular MFP, and the bottom panel shows the drift coefficient normalized to the corresponding weak scattering drift coefficient. The color bar indicates percentage deviation over the last 500λ  c /V 0 of the run.
Paper: The Diffusion Tensor of Protons at 1 au: Comparing Simulation, Observation, and Theory
Authors: P. L. Els, N. E. Engelbrecht, J. T. Lang, R. D. Strauss
Figure caption: Example of a typical running DC, showing the parallel (top) and perpendicular (middle) components, along with the drift reduction (bottom). DCs are generated by variation of the total variance in the magnetic fluctuations, with κ 0, κ 1, and κ 2 using ﹩\delta {B}_{T}^{2}=5.17﹩, 15.91, and 26.65 nT2, respectively. See text for details.
Paper: The Diffusion Tensor of Protons at 1 au: Comparing Simulation, Observation, and Theory
Authors: P. L. Els, N. E. Engelbrecht, J. T. Lang, R. D. Strauss
Figure caption: Comparison of simulation results of the ratio of the perpendicular to parallel MFP as a function of rigidity, vs. prior observational estimates. The gray region indicates the I. D. Palmer (1982) consensus range. The color scheme mirrors that of Figure 7, for ease of comparison.
Paper:  pop-cosmos: Scaleable Inference of Galaxy Properties and Redshifts with a Data-driven Population Model
Authors: Stephen Thorp, Justin Alsing, Hiranya V. Peiris, Sinan Deger, Daniel J. Mortlock, Boris Leistedt, Joel Leja, Arthur Loureiro
Figure caption: Example SED posteriors for individual galaxies under the pop-cosmos prior. Top left: the galaxy with minimum ∣Δ z ∣, i.e., the posterior median closest to z spec. Top right: the galaxy with maximum ∣Δ z ∣, i.e., with z phot posterior median furthest from z spec. Bottom left: an X-ray-selected AGN for which we find f AGN > 2, i.e., an SED with twice as much AGN flux as galaxy flux. Bottom right: a galaxy with a significant X-ray detection that is a large outlier with ∣Δ z ∣ > 0.15. Fluxes are in microjanskys. Corresponding redshift posteriors are in Figure 5. Horizontal bars on the COSMOS data indicate the FWHM of the passbands.
Paper:  pop-cosmos: Scaleable Inference of Galaxy Properties and Redshifts with a Data-driven Population Model
Authors: Stephen Thorp, Justin Alsing, Hiranya V. Peiris, Sinan Deger, Daniel J. Mortlock, Boris Leistedt, Joel Leja, Arthur Loureiro
Figure caption: Redshift posteriors for the four galaxies shown in Figure 4. Posteriors for pop-cosmos and Prospector are shown as histograms; credible intervals for LePhare and EAZY are shaded regions. Spectroscopic redshift is shown as a dashed line.
Paper:  pop-cosmos: Scaleable Inference of Galaxy Properties and Redshifts with a Data-driven Population Model
Authors: Stephen Thorp, Justin Alsing, Hiranya V. Peiris, Sinan Deger, Daniel J. Mortlock, Boris Leistedt, Joel Leja, Arthur Loureiro
Figure caption: Probability integral transform (PIT) test for the redshift posteriors under the pop-cosmos and Prospector models. For each galaxy in the COSMOS spectroscopic sample, we estimate the posterior probability that z < z spec.
Paper:  pop-cosmos: Scaleable Inference of Galaxy Properties and Redshifts with a Data-driven Population Model
Authors: Stephen Thorp, Justin Alsing, Hiranya V. Peiris, Sinan Deger, Daniel J. Mortlock, Boris Leistedt, Joel Leja, Arthur Loureiro
Figure caption: Comparison of Δ z  = (z − z spec)/(1 + z spec) for pop-cosmos and LePhare. Each cell is colored based on the number of galaxies (out of the spectroscopic sample) it contains. The gray shaded region indicates where LePhare and pop-cosmos agree to within 0.15 × (1 + z).
Paper:  pop-cosmos: Scaleable Inference of Galaxy Properties and Redshifts with a Data-driven Population Model
Authors: Stephen Thorp, Justin Alsing, Hiranya V. Peiris, Sinan Deger, Daniel J. Mortlock, Boris Leistedt, Joel Leja, Arthur Loureiro
Figure caption: Box-and-whisker plot showing the distribution of fractional errors made in P( ϑ ) for 256,000 different  ϑ , using different ODE solver tolerances (measured relative to the reference value of P ref( ϑ ) computed with atol = rtol = 10−9). Boxes show the median and interquartile range. Whiskers show the 5th and 95th percentiles. Outliers are shown as gray points. Upper panel shows the time taken for 256,000 prior evaluations on a single NVIDIA A100 GPU.
Paper:  pop-cosmos: Scaleable Inference of Galaxy Properties and Redshifts with a Data-driven Population Model
Authors: Stephen Thorp, Justin Alsing, Hiranya V. Peiris, Sinan Deger, Daniel J. Mortlock, Boris Leistedt, Joel Leja, Arthur Loureiro
Figure caption: Redshift posterior medians for COSMOS galaxies with irac 1 < 26. The histogram bars for pop-cosmos are stacked; the fraction of each bar within the r < 25 cut that J. Alsing et al. (2024) used on the training set is shown in maroon, with the fraction with r > 25 shown in lighter pink. The total height of the bar corresponds to the total number of galaxies in that redshift bin (irrespective of r-band magnitude). The green histogram shows LePhare results from J. R. Weaver et al. (2022).
Paper:  pop-cosmos: Scaleable Inference of Galaxy Properties and Redshifts with a Data-driven Population Model
Authors: Stephen Thorp, Justin Alsing, Hiranya V. Peiris, Sinan Deger, Daniel J. Mortlock, Boris Leistedt, Joel Leja, Arthur Loureiro
Figure caption: Full 16-dimensional posterior distributions of  ϑ  under the pop-cosmos (red) and Prospector (blue) priors for the X-ray-selected AGN (lower-left panel of Figures 4 and 5).
Paper:  pop-cosmos: Scaleable Inference of Galaxy Properties and Redshifts with a Data-driven Population Model
Authors: Stephen Thorp, Justin Alsing, Hiranya V. Peiris, Sinan Deger, Daniel J. Mortlock, Boris Leistedt, Joel Leja, Arthur Loureiro
Figure caption: Photometric vs. spectroscopic redshifts for the 297 out-of-training-sample galaxies that have r > 25 and irac 1 < 26. Results are shown for pop-cosmos and LePhare.
Paper:  pop-cosmos: Scaleable Inference of Galaxy Properties and Redshifts with a Data-driven Population Model
Authors: Stephen Thorp, Justin Alsing, Hiranya V. Peiris, Sinan Deger, Daniel J. Mortlock, Boris Leistedt, Joel Leja, Arthur Loureiro
Figure caption: Photometric redshift distribution for the full r < 25 COSMOS sample from the four estimators. Posterior medians are used for pop-cosmos, Prospector, and LePhare; MAP estimates are used for EAZY.
Paper: Exploring the Dynamic Rotational Profile of the Hotter Solar Atmosphere: A Multiwavelength Approach Using SDO/AIA Data
Authors: Srinjana Routh, Bibhuti Kumar Jha, Dibya Kirti Mishra, Tom Van Doorsselaere, Vaibhav Pant, Subhamoy Chatterjee, Dipankar Banerjee
Figure caption: The variance of ΔΩLoS for change in LoS angle for a (a) 5 Mm structure in high resolution and (b) 150 Mm structure in AIA resolution. An order 4 regression fit has been used to show the general trend in ΔΩLoS.
Paper: Exploring the Dynamic Rotational Profile of the Hotter Solar Atmosphere: A Multiwavelength Approach Using SDO/AIA Data
Authors: Srinjana Routh, Bibhuti Kumar Jha, Dibya Kirti Mishra, Tom Van Doorsselaere, Vaibhav Pant, Subhamoy Chatterjee, Dipankar Banerjee
Figure caption: An example image with flare from 2014 October 25 in heliographic coordinates after smoothing as visible in 131 Å (top) and 193 Å (bottom) channels. Since flares are spontaneous, short-term transient events with a lifespan much less than 6 hr, we assume they do not contribute to our long-term correlation analysis. So, channels 131 Å and 193 Å are represented by their cooler counterparts contributed primarily by Fe VII and Fe XII (﹩{\mathrm{Log}}_{10}T=5.8,6.2﹩), respectively.
Paper: Exploring Waveform Variations among Neutron Star Ray-tracing Codes for Complex Emission Geometries
Authors: Devarshi Choudhury, Anna L. Watts, Alexander J. Dittmann, M. Coleman Miller, Sharon M. Morsink, Tuomo Salmi, Serena Vinciguerra, Slavko Bogdanov, Sebastien Guillot, Michael T. Wolff, Zaven Arzoumanian
Figure caption: Energy-summed waveforms (left) and phase-summed spectra (right) generated by the different codes for the Ring-Eq configuration (top), the corresponding fractional differences between the different X-PSI resolution settings as benchmarked against the ultra settings (top-middle), the fractional differences between the IM code against the X-PSI standard and ultra resolution settings (bottom-middle), and the fractional differences between the Alberta code against the IM code, the X-PSI standard and ultra resolution settings (bottom). The gray dashed lines in the fractional difference plots indicate the expected Poisson fluctuation for the X-PSI ultra waveform scaled to yield a total of 106 counts. The legends shown in the spectral plot also apply to the waveform plot.
Paper: Exploring Waveform Variations among Neutron Star Ray-tracing Codes for Complex Emission Geometries
Authors: Devarshi Choudhury, Anna L. Watts, Alexander J. Dittmann, M. Coleman Miller, Sharon M. Morsink, Tuomo Salmi, Serena Vinciguerra, Slavko Bogdanov, Sebastien Guillot, Michael T. Wolff, Zaven Arzoumanian
Figure caption: Spot cell mesh discretization for the Crescent-Polar configuration for the different X-PSI resolution settings. The axes represent the total number of cell mesh elements considered for the construction of the hot spot along the azimuth (x-axis) and colatitude (y-axis). The boundary in the azimuthal direction is cyclical because the spot region extends over one of the poles, while the lower boundary in colatitude encompasses a coordinate singularity. The colors depict the proper area occupied by the hot region within each mesh element, which is used to weigh the contribution of that cell. As a result, the cells at the boundary of the spot only emit partially, as compared to the cells within. Since the visible area is rather small and elongated for this configuration, edge effects become significant, leading to a poor approximation when using a coarse mesh resolution.