adsabs/AstroCLIMB huggingface dataset:
Paper: Mechanical Modification of Chondrule Fine-grained Rims by Dusty Nebular Shocks
Authors: Augusto Carballido, Lorin S. Matthews, Romy D. Hanna, Truell W. Hyde
Figure caption: Mean dust temperatures from runs 1–9, 46–54, and 82–90 (see Table 2 in the Appendix). Data for three different impact speeds v imp (0.5 km s−1, red curves; 1 km s−1, green curves; and 3 km s−1, blue curves) are shown. The error bands correspond to one standard deviation. High temperatures are produced for the highest impact speed and the highest dust fraction in the impacting cloud (f cloud = 0.1).
Paper: Mechanical Modification of Chondrule Fine-grained Rims by Dusty Nebular Shocks
Authors: Augusto Carballido, Lorin S. Matthews, Romy D. Hanna, Truell W. Hyde
Figure caption: FGR embayments (indicated by ovals) and chondrule protrusions (shown by rectangles) from run 48 (left panel; v imp = 1.0 km s−1, f cloud = 0.1, f FGR = 0.1) and from a backscattered-electron (BSE) image of the Paris CM chondrite produced by Zanetta et al. (2021) (right panel, modified). The white bar in the upper right corner of the BSE image represents a length of 100 μm.
Paper: Mechanical Modification of Chondrule Fine-grained Rims by Dusty Nebular Shocks
Authors: Augusto Carballido, Lorin S. Matthews, Romy D. Hanna, Truell W. Hyde
Figure caption: Sample snapshots of simulation 27 (v imp = 0.7 km s−1, f cloud = 0.1, f FGR = 0.5) at t = 0.00 μs (top row), 0.19 μs (middle row), and 1.00 μs (bottom row). The left panels show the objects (chondrule and dust), the center panels show the temperature, and the right panels show the collision pressure. One should note the large temperature gradient developed in the dust component after the impact.
Paper: Mechanical Modification of Chondrule Fine-grained Rims by Dusty Nebular Shocks
Authors: Augusto Carballido, Lorin S. Matthews, Romy D. Hanna, Truell W. Hyde
Figure caption: Mean (blue circles) and maximum (red triangles) dust temperatures as a function of impact speed. Error bars, where visible, indicate one standard deviation over the simulation run time. A steeper dependence results if the impacting dust cloud contains the highest dust fraction (f cloud = 0.1, third column).
Paper: Mechanical Modification of Chondrule Fine-grained Rims by Dusty Nebular Shocks
Authors: Augusto Carballido, Lorin S. Matthews, Romy D. Hanna, Truell W. Hyde
Figure caption: Change in FGR mass, with respect to the initial FGR mass, m FGR, 0, in units of the latter. The FGR mass is approximated by the amount of dust material within the region 100 μm ≤ x ≤ 300 μm, −150 μm ≤ z ≤ 0 μm. The horizontal dashed lines indicate zero change of FGR mass.
Paper: Mechanical Modification of Chondrule Fine-grained Rims by Dusty Nebular Shocks
Authors: Augusto Carballido, Lorin S. Matthews, Romy D. Hanna, Truell W. Hyde
Figure caption: Ratio of FGR thermal energy per unit FGR mass to dust cloud kinetic energy per unit cloud mass (see Equation (1)), as a function of impact speed. The top row shows the ratio β mean, corresponding to the spatial mean of the FGR temperature, while the bottom row shows ﹩{\beta }_{\max }﹩, designating the spatial maximum of the FGR temperature. The three columns correspond to the three values of f cloud used in our simulations. The green, black, and blue points denote FGR dust fractions f FGR = 0.1, 0.3m, and 0.5, respectively.
Paper: Mechanical Modification of Chondrule Fine-grained Rims by Dusty Nebular Shocks
Authors: Augusto Carballido, Lorin S. Matthews, Romy D. Hanna, Truell W. Hyde
Figure caption: Maximum pressures from runs 1–9, 46–54, and 82–90 (see Table 2 in the Appendix). Data for three different impact speeds v imp (0.5 km s−1, red curves; 1 km s−1, green curves; and 3 km s−1, blue curves) are shown. The highest pressures occur soon after collision of a dense cloud with an FGR (f cloud = 0.1, third column).
Paper: Mechanical Modification of Chondrule Fine-grained Rims by Dusty Nebular Shocks
Authors: Augusto Carballido, Lorin S. Matthews, Romy D. Hanna, Truell W. Hyde
Figure caption: Maximum impact pressure as a function of impact speed. See text for a description of the method of computation. The error bars, where visible, correspond to one standard deviation. A steeper dependence results for high dust cloud fractions.
Paper: Photometric Survey of Neptune's Trojan Asteroids. I. The Color Distribution
Authors: Larissa Markwardt, Hsing Wen Lin, 省文 林, David Gerdes, Fred C. Adams
Figure caption: Measured g − r vs. r − i of the NT population. Blue points are colors of scattered TNOs, and orange triangles are JTs, both taken from the literature (Hainaut et al. 2012). Light-blue crosses are previously observed colors of NTs that the “Trojan color conundrum” was based on (Sheppard & Trujillo 2006; Sheppard 2012; Parker et al. 2013; Jewitt 2018), while the blue plus signs are more recently observed NT colors that bring this conundrum into question (Lin et al. 2019; Bolin et al. 2023). Targets observed in this paper are shown as green squares. Solar color and the reddening line (see Section 3.4) are depicted as a yellow star and orange dotted line, respectively. Objects that have multiple observations in this paper are connected by a dotted–dashed line. NTs that have been previously observed in the literature are connected by a dashed line. The yellow line marks values where the PCA yields values equal to our cutoff of 1.75 (see Figure 6 and Section 4.2). Objects in the yellow region are above this cutoff and considered ultrared in this paper. The blue line marks values where the PCA yields values equal to our cutoff of −1.25 (see Figure 6 and Section 4.2). Objects in the blue region are bluer than this cutoff and considered blue in this paper. The top and right inset plots show the kernel density estimation (KDE) of the g − r and r − i distributions, respectively, of the included subpopulations.
Paper: Photometric Survey of Neptune's Trojan Asteroids. I. The Color Distribution
Authors: Larissa Markwardt, Hsing Wen Lin, 省文 林, David Gerdes, Fred C. Adams
Figure caption: Measured g − r vs. r − z of the NT population. Navy upward-pointing triangles, green downward-pointing triangles, and blue circles are measurements taken from the literature of TNOs (scattered, cold, and hot, respectively; Schwamb et al. 2019). Teal plus signs are colors of NTs taken from the literature (Lin et al. 2019). Targets observed in this paper are shown as orange squares. Solar color and the reddening line (see Section 3.4) are depicted as a yellow star and orange dotted line, respectively. Objects that have observations taken in this paper and from the literature are connected with a dashed line. Objects that have multiple observations in this paper are connected by a dotted–dashed line. The green ellipse demarcates the region of color–color space occupied only by cold TNOs. The top and right inset plots show the KDE of the g − r and r − z distributions, respectively, of the included subpopulations.
Paper: Photometric Survey of Neptune's Trojan Asteroids. I. The Color Distribution
Authors: Larissa Markwardt, Hsing Wen Lin, 省文 林, David Gerdes, Fred C. Adams
Figure caption: The results of running a PCA with the g − r and r − i colors of certain solar system populations. The green histogram corresponds to the JTs (taken from Hainaut et al. 2012). The blue and orange histograms correspond to the red and ultrared subpopulations of the scattered TNOs, taken from Hainaut et al. (2012); the classification of red vs. ultrared was determined by using a clustering algorithm (DBSCAN; Pedregosa et al. 2011) that separated the TNOs into two subpopulations.
Paper: Photometric Survey of Neptune's Trojan Asteroids. I. The Color Distribution
Authors: Larissa Markwardt, Hsing Wen Lin, 省文 林, David Gerdes, Fred C. Adams
Figure caption: Cumulative distributions of the principal component (see Section 4.2) values of populations in the solar system. The cutoff between red and ultrared as defined by this PCA is shown as a black dashed line (see Figure 6). The cutoff between red and blue objects is similarly shown as a dotted–dashed line. The JT and scattered TNO results are shown as orange and navy histograms, respectively. The NT observations from previous literature are shown as a blue histogram. The NT observations from this work are shown as a green histogram.
Paper: Photometric Survey of Neptune's Trojan Asteroids. I. The Color Distribution
Authors: Larissa Markwardt, Hsing Wen Lin, 省文 林, David Gerdes, Fred C. Adams
Figure caption: The differences in observed color between NTs in this paper and the literature as compared to the average error on our observations. The differences in g − r, r − i, and r − z observations are shown as blue, orange, and green histograms, respectively. The average g − r, r − i, and r − z errors are shown as blue dotted, green dotted–dashed, and orange dashed lines, respectively.
Paper: Photometric Survey of Neptune's Trojan Asteroids. I. The Color Distribution
Authors: Larissa Markwardt, Hsing Wen Lin, 省文 林, David Gerdes, Fred C. Adams
Figure caption: PSF modeling and subtraction. Top left: a star with the PSF model contour. Bottom left: the image of NT. Middle: the model of the star (top) and the NT (bottom). Right: the images after subtraction of the model.
Paper: Photometric Survey of Neptune's Trojan Asteroids. I. The Color Distribution
Authors: Larissa Markwardt, Hsing Wen Lin, 省文 林, David Gerdes, Fred C. Adams
Figure caption: This figure shows our least-squares approach to fitting ﹩r^{\prime} ﹩-band light curves and colors for an example NT target, 2013 VX30. Each observation is shown as a colored point (blue downward-pointing triangle for ﹩g^{\prime} ﹩, green square for ﹩r^{\prime} ﹩, yellow diamond for ﹩i^{\prime} ﹩, and orange leftward-pointing triangle for ﹩z^{\prime} ﹩). We then used a constant but free-parameter color term to convert each observation to an ﹩r^{\prime} ﹩-band observation; these points are shown as black circles. The solid line is our least-squares fit to the ﹩r^{\prime} ﹩-band (black) points. The dotted lines show our 1σ deviation from this fit.
Paper: Earth as a Transiting Exoplanet: A Validation of Transmission Spectroscopy and Atmospheric Retrieval Methodologies for Terrestrial Exoplanets
Authors: Jacob Lustig-Yaeger, Victoria S. Meadows, David Crisp, Michael R. Line, Tyler D. Robinson
Figure caption: Best-fit model of Earth’s high-resolution transmission spectrum in the 5–7.2 μm wavelength range using the 66° latitude TP profile. The data are shown in black, the best-fitting model spectrum is shown in blue, and various colors are used in the bottom panels to indicate each molecule’s contribution to the model spectrum. The shading for O2 indicates the contribution from both O2–O2 CIA and O2–N2 CIA. In the bottom panel, HNO3, CH4, and H2O show subtle absorption features above a O2–N2 CIA, O2–O2 CIA, and H2O continuum.
Paper: Earth as a Transiting Exoplanet: A Validation of Transmission Spectroscopy and Atmospheric Retrieval Methodologies for Terrestrial Exoplanets
Authors: Jacob Lustig-Yaeger, Victoria S. Meadows, David Crisp, Michael R. Line, Tyler D. Robinson
Figure caption: Earth’s observed cloud-free transit transmission spectrum from Macdonald & Cowan (2019) binned to a resolution of Δλ = 0.02 μm and fit using SMARTER. The data are shown in black, the best-fitting model (Model 1) spectrum is shown in white and blue, and various colors are used to indicate each molecule’s contribution to the model spectrum. The most prominent features are due to CO2 and O3, but a rich diversity of habitability indicators, biosignatures, and technosignatures are present.
Paper: Earth as a Transiting Exoplanet: A Validation of Transmission Spectroscopy and Atmospheric Retrieval Methodologies for Terrestrial Exoplanets
Authors: Jacob Lustig-Yaeger, Victoria S. Meadows, David Crisp, Michael R. Line, Tyler D. Robinson
Figure caption: Comparison of transmission spectrum models with and without refraction. The upper-left panel shows the two spectral models atop the observed data in the 6 μm band of interest. The lower-left panel shows the residuals between the model with and without refraction, which appears anticorrelated with the spectral continuum. This relationship is borne out more clearly in the right panel, which shows the model residuals as a function of transit altitude where larger model differences due to refraction are observed at lower altitudes. Finally, the zoomed insert visually emphasizes this point by showing a comparison of individual CO2 and H2O lines. The cores of optically thick lines that probe higher altitudes are not affected by refraction, while the continuum and optically thin line and cores are slightly affected, with larger refraction effects seen at lower altitudes.
Paper: Earth as a Transiting Exoplanet: A Validation of Transmission Spectroscopy and Atmospheric Retrieval Methodologies for Terrestrial Exoplanets
Authors: Jacob Lustig-Yaeger, Victoria S. Meadows, David Crisp, Michael R. Line, Tyler D. Robinson
Figure caption: Retrieval results on Earth’s observed cloud-free transit transmission spectrum binned to a resolution of Δλ = 0.02 μm, with 10% random noise added, and fit using the DYNESTY nested sampling algorithm. The upper set of panels show 1D posterior histograms (blue) for each model parameter compared to the respective “true” atmospheric profiles from Figure 3. The median and 1σ intervals are listed above each panel. The lower panel shows the spectral data (black with uncertainties) and the median retrieved model spectrum (white and blue) surrounded by 1σ and 3σ credibility envelopes (often thinner than the median model line width).
Paper: Earth as a Transiting Exoplanet: A Validation of Transmission Spectroscopy and Atmospheric Retrieval Methodologies for Terrestrial Exoplanets
Authors: Jacob Lustig-Yaeger, Victoria S. Meadows, David Crisp, Michael R. Line, Tyler D. Robinson
Figure caption: Fits to synthetic JWST spectra and the corresponding retrieved atmospheric constraints. The upper subplots show 1D marginalized posterior distributions for retrievals using NIRSpec G395M data (blue) and MIRI LRS data (orange) compared to the true vertical profiles exhibited by Earth’s atmosphere (black lines). The middle and bottom panels show the synthetic JWST spectra for 80 stacked transits of TRAPPIST-1e observed with NIRSpec G395M and MIRI LRS, respectively, along with the ± 1σ and 3σ uncertainty envelopes around the median model fits.
Paper: Earth as a Transiting Exoplanet: A Validation of Transmission Spectroscopy and Atmospheric Retrieval Methodologies for Terrestrial Exoplanets
Authors: Jacob Lustig-Yaeger, Victoria S. Meadows, David Crisp, Michael R. Line, Tyler D. Robinson
Figure caption: Retrieved CO2 VMR from the high-resolution full wavelength spectrum compared to the temporal evolution of the CO2 concentration retrieved from ACE as reported in Foucher et al. (2011). The purple line shows our retrieved CO2 VMR with dark and light shading to indicate the 1σ and 3σ credible intervals, respectively, from our model fixed at the average Earth TP profile. The agreement is quite good considering that the transmission spectrum fit using our model is vertically integrated over the atmospheric column, spatially integrated over the entire globe, and temporally integrated over many years of SCISAT mission operation.
Paper: Earth as a Transiting Exoplanet: A Validation of Transmission Spectroscopy and Atmospheric Retrieval Methodologies for Terrestrial Exoplanets
Authors: Jacob Lustig-Yaeger, Victoria S. Meadows, David Crisp, Michael R. Line, Tyler D. Robinson
Figure caption: Marginalized posterior distributions for the NIRSpec G395M (blue) and MIRI LRS (orange) retrievals discussed in Section 3.3 and Figure 11. These constraints correspond to 80 stacked transits of TRAPPIST-1e using each instrument.
Paper: Earth as a Transiting Exoplanet: A Validation of Transmission Spectroscopy and Atmospheric Retrieval Methodologies for Terrestrial Exoplanets
Authors: Jacob Lustig-Yaeger, Victoria S. Meadows, David Crisp, Michael R. Line, Tyler D. Robinson
Figure caption: Best-fit model of Earth’s high-resolution transmission spectrum in the 3.7–5 μm wavelength range using the mean Earth TP profile. The data are shown in black, the best-fitting model spectrum is shown in blue, and various colors are used to indicate each molecule’s contribution to the model spectrum.
Paper: Earth as a Transiting Exoplanet: A Validation of Transmission Spectroscopy and Atmospheric Retrieval Methodologies for Terrestrial Exoplanets
Authors: Jacob Lustig-Yaeger, Victoria S. Meadows, David Crisp, Michael R. Line, Tyler D. Robinson
Figure caption: Best-fit model of Earth’s high-resolution transmission spectrum in the full 2–14 μm wavelength range using the mean Earth TP profile. The data are shown in black, the best-fitting model spectrum is shown in blue, and various colors are used to indicate each molecule’s contribution to the model spectrum.
Paper: Fitting Thermal Evolution Models to the Chronological Record of Erg Chech 002 and Modeling the Ejection Conditions of the Meteorite
Authors: Wladimir Neumann, Robert Luther, Mario Trieloff, Philip M. Reger, Audrey Bouvier
Figure caption: Cumulative mass per shock stage. Shown are (a) the normalized escaping ejected material and (b) the fraction of this material, which originates from the formation depth between 800 and 1300 m. The mass in panel (a) is normalized to the projectile mass. In panel (a), the cases of an impact velocity of 500 and 5000 m s−1 are indicated by dashed and solid lines, respectively. The differently shaded gray bars indicate shock stages M-S2, M-S3, and M-S7 according to Stöffler & Hamann (2018). In panel (b), only impacts with 5000 m s−1 produce a significant amount of material that was affected by shocks over 1 GPa. The projectile radius a is specified in the legend for all cases. The data for the three largest impactors in panel (b) are summarized in Table 3.
Paper: The Second International Asteroid Warning Network Timing Campaign: 2005 LW3
Authors: Davide Farnocchia, Vishnu Reddy, James M. Bauer, Elizabeth M. Warner, Marco Micheli, Matthew J. Payne, Tony Farnham, Michael S. Kelley, Miguel R. Alarcon, Paolo Bacci, Roberto Bacci, Mauro Bachini, Kevin Baillié, Giorgio Baj, Daniel Bamberger, Anatoly P. Barkov, Stefan Beck, Guido Betti, Enrico Biancalani, Bryce T. Bolin, David Briggs, Luca Buzzi, Haowen Cheng, Eric Christensen, Alessandro Coffano, Luca Conversi, Christophe Demeautis, Larry Denneau, Josselin Desmars, Anlaug A. Djupvik, Leonid Elenin, Paolo Fini, Tobias Felber, Randy Flynn, Gianni Galli, Mikael Granvik, Bill Gray, Zuri Gray, Luca Grazzini, Werner Hasubick, Tobias Hoffmann, Robert Holmes, Marco Iozzi, Alexander L. Ivanov, Viktor A. Ivanov, Natalya V. Ivanova, Cristóvão Jacques, Hai Jiang, Zheng Jinghui, Anni Kasikov, Myung-Jin Kim, Balaji Kumar, Hee-Jae Lee, Bin Li, Jing Liu, Javier Licandro, Tyler Linder, Vadim E. Lysenkov, Martina Maestripieri, Andrea Mantero, Vladimiro Marinello, Jennie McCormick, Darrel Moon, Alessandro Nastasi, James D. Neill, Guenther Neue, Artem O. Novichonok, Francisco Ocaña, Gianpaolo Pizzetti, Anton Pomazan, Josiah N. Purdum, Christophe Ratinaud, Dong-Goo Roh, Filipp D. Romanov, Nello Ruocco, Toni Santana-Ros, Toni Scarmato, Anastasia Schmalz, Sergei Schmalz, Miquel Serra-Ricart, Clay Sherrod, Nick Sioulas, Andrea Soffiantini, Giacomo Succi, David J. Tholen, Jeppe S. Thomsen, William Thuillot, Richard Wainscoat, Guy Wells, Robert Weryk, Nikolai A. Yakovenko, Hong-Suh Yim, Chengxing Zhai
Figure caption: Left: weighted rms of the cross-track residuals of each tracklet as a function of the astrometric position uncertainties. Right: estimated mean timing error for each tracklet of observations considered in our analysis. Crosses correspond to survey data, and dots correspond to follow-up data. Three outliers with timing errors between 2 and 4 s fall outside the plot. The two dashed lines correspond to the orbital uncertainty mapped into the along-track direction in the plane of sky and converted to time using the rate of motion.
Paper: The Second International Asteroid Warning Network Timing Campaign: 2005 LW3
Authors: Davide Farnocchia, Vishnu Reddy, James M. Bauer, Elizabeth M. Warner, Marco Micheli, Matthew J. Payne, Tony Farnham, Michael S. Kelley, Miguel R. Alarcon, Paolo Bacci, Roberto Bacci, Mauro Bachini, Kevin Baillié, Giorgio Baj, Daniel Bamberger, Anatoly P. Barkov, Stefan Beck, Guido Betti, Enrico Biancalani, Bryce T. Bolin, David Briggs, Luca Buzzi, Haowen Cheng, Eric Christensen, Alessandro Coffano, Luca Conversi, Christophe Demeautis, Larry Denneau, Josselin Desmars, Anlaug A. Djupvik, Leonid Elenin, Paolo Fini, Tobias Felber, Randy Flynn, Gianni Galli, Mikael Granvik, Bill Gray, Zuri Gray, Luca Grazzini, Werner Hasubick, Tobias Hoffmann, Robert Holmes, Marco Iozzi, Alexander L. Ivanov, Viktor A. Ivanov, Natalya V. Ivanova, Cristóvão Jacques, Hai Jiang, Zheng Jinghui, Anni Kasikov, Myung-Jin Kim, Balaji Kumar, Hee-Jae Lee, Bin Li, Jing Liu, Javier Licandro, Tyler Linder, Vadim E. Lysenkov, Martina Maestripieri, Andrea Mantero, Vladimiro Marinello, Jennie McCormick, Darrel Moon, Alessandro Nastasi, James D. Neill, Guenther Neue, Artem O. Novichonok, Francisco Ocaña, Gianpaolo Pizzetti, Anton Pomazan, Josiah N. Purdum, Christophe Ratinaud, Dong-Goo Roh, Filipp D. Romanov, Nello Ruocco, Toni Santana-Ros, Toni Scarmato, Anastasia Schmalz, Sergei Schmalz, Miquel Serra-Ricart, Clay Sherrod, Nick Sioulas, Andrea Soffiantini, Giacomo Succi, David J. Tholen, Jeppe S. Thomsen, William Thuillot, Richard Wainscoat, Guy Wells, Robert Weryk, Nikolai A. Yakovenko, Hong-Suh Yim, Chengxing Zhai
Figure caption: Cross-track (left panel) and timing (right panel) errors (crosses and dots) and 1σ error bars for a tracklet of observations collected by V17 during the campaign. The two dashed lines correspond to the orbit solution uncertainty in the along-track direction scaled by the rate of motion. Crosses correspond to positions obtained by stacking images, while dots are for positions measured from single images.
Paper: Mechanical Modification of Chondrule Fine-grained Rims by Dusty Nebular Shocks
Authors: Augusto Carballido, Lorin S. Matthews, Romy D. Hanna, Truell W. Hyde
Figure caption: Basic numerical setup. The orange rectangle represents a portion of a chondrule. The gray points represent dust particles: those immediately above the chondrule (between z = −50 μm and z = 0 μm) belong to the initial FGR, while those above z = 0 μm are part of a “dust cloud” that collides with the FGR as a result of a nebular shock. Both chondrule and dust materials are modeled as dunite. The dust grain radii follow the MRN size distribution of interstellar grains (Mathis et al. 1977).
Paper: Mechanical Modification of Chondrule Fine-grained Rims by Dusty Nebular Shocks
Authors: Augusto Carballido, Lorin S. Matthews, Romy D. Hanna, Truell W. Hyde
Figure caption: Schematic representation of our proposed FGR modification mechanism. The rimmed chondrule encounters a nebular shock, which itself drives a “cloud” of dust particles. This cloud impacts the FGR, producing structural changes in the rim.
Paper: Earth as a Transiting Exoplanet: A Validation of Transmission Spectroscopy and Atmospheric Retrieval Methodologies for Terrestrial Exoplanets
Authors: Jacob Lustig-Yaeger, Victoria S. Meadows, David Crisp, Michael R. Line, Tyler D. Robinson
Figure caption: Empirical transmission spectrum of the cloudless Earth from Macdonald & Cowan (2019). The top panel shows the full wavelength range in high-resolution (light blue) and binned to a lower resolution (Δλ = 0.02 μm; dark blue). The lower panels zoom into the 4.2 μm CO2 band, showing progressively smaller wavelength ranges and highlighting the fully resolved spectral lines with no apparent observational noise. The data behind this figure is available at DOI:10.5281/zenodo.8280710 (Macdonald & Cowan 2023), which was obtained from the ACE-FTS Atmospheric Atlases (Hughes et al. 2014) at http://www.ace.uwaterloo.ca/atlas.php. A modified copy in machine-readable format is available with the article.(The data used to create this figure are available.)