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Paper: Properties of Solar Wind Current Sheets in the Martian Space Environment
Authors: Yangjun Chen, Mingyu Wu, Heying Wang, Peng E, Sudong Xiao, Guoqiang Wang, Xuesong Leng, Aimin Du, Tielong Zhang
Figure caption: The distributions of SCSs at the ﹩{X}-{R}﹩ plane (﹩{\rm{R}}=\sqrt[2]{{Y}^{2}+{Z}^{2}}﹩). The bin size is ﹩{0.2\times 0.2{R}}_{M}﹩ (﹩{R}_{M}﹩ is the Martian radius). (a) The orbital coverage time of MAVEN. (b) The number of CSs in each bin. (c) The occurrence rate. The black solid and dashed curves indicate the bow shock and induced magnetopause obtained from Trotignon et al. (2006).
Paper: Properties of Solar Wind Current Sheets in the Martian Space Environment
Authors: Yangjun Chen, Mingyu Wu, Heying Wang, Peng E, Sudong Xiao, Guoqiang Wang, Xuesong Leng, Aimin Du, Tielong Zhang
Figure caption: (a) The percentage of CS events as a function of the depth ﹩{B}_{\min }/{B}_{T}.﹩ (b) The dependence of the depth ﹩{B}_{\min }/{B}_{T}﹩ on the rotation angle ω. The small crosses indicate the depth ﹩{B}_{\min }/{B}_{T}﹩ of the CS events. The histograms represent median values of the depth ﹩{B}_{\min }/{B}_{T}﹩ for each bin (with a width of 15°). In this figure, the cyan color represents SCSs, whereas the orange color represents MCSs.
Paper: Properties of Solar Wind Current Sheets in the Martian Space Environment
Authors: Yangjun Chen, Mingyu Wu, Heying Wang, Peng E, Sudong Xiao, Guoqiang Wang, Xuesong Leng, Aimin Du, Tielong Zhang
Figure caption: The distributions of MCSs at the ﹩{X}-{R}﹩ plane (﹩{R}=\sqrt[2]{{Y}^{2}+{Z}^{2}}﹩). The format is the same as Figure 7.
Paper: Properties of Solar Wind Current Sheets in the Martian Space Environment
Authors: Yangjun Chen, Mingyu Wu, Heying Wang, Peng E, Sudong Xiao, Guoqiang Wang, Xuesong Leng, Aimin Du, Tielong Zhang
Figure caption: (a) The time series of the sunspot number. (b) The time series of ﹩{R}_{{\rm{MS}}}.﹩ The gray shaded areas indicate that we focus on the time range of MAVEN observations between 2014 October 10 and 2016 January 31 for this study. The red vertical and blue lines indicate the beginning and ending of the time interval used.
Paper: Properties of Solar Wind Current Sheets in the Martian Space Environment
Authors: Yangjun Chen, Mingyu Wu, Heying Wang, Peng E, Sudong Xiao, Guoqiang Wang, Xuesong Leng, Aimin Du, Tielong Zhang
Figure caption: The format is the same as in Figure 2, but for the CS in the Martian magnetosheath observed by MAVEN on 2015 March 25.
Paper: Insights into the Production of 44Ti and Nickel Isotopes in Core-collapse Supernovae
Authors: Tianshu Wang, Adam Burrows
Figure caption:  44Ti yield (left) and 44Ti/56Ni ratio (right) and as a function of time. The circular dot on each curve marks the beginning point of extrapolation. The black hole formers (19.56 and 40 M ⊙) are plotted as dashed curves. The black horizontal line shows the solar 44Ca/56Fe ratio as a reference. The asymptotic 44Ti yield is not achieved in most models until 10 s post-bounce, except the lowest-mass ones (e.g., 9a, 9b, 9.25, and 9.5 M ⊙). The growth of the 44Ti yield in the extrapolated phase comes mostly from the α-rich freeze-out process in the proton-rich neutrino-driven winds, which initially produces proton-rich isotopes such as 45V and 46Cr and then converts them into 44Ti as the temperature decreases. See the text for a discussion.
Paper: Insights into the Production of 44Ti and Nickel Isotopes in Core-collapse Supernovae
Authors: Tianshu Wang, Adam Burrows
Figure caption: Final 44Ti and 56Ni yields of our theoretical 3D models compared to observed values in Cas A and SN 1987A. The black hole formers (19.56 and 40 M ⊙) are plotted as square dots. In addition to our 3D models, we include the 18.88 M ⊙ model from Sieverding et al. (2023a; the black triangle, labeled as S23). The observed 44Ti and 56Ni masses of Cas A are taken from Grefenstette et al. (2017) and Hwang & Laming (2012), while the SN 1987A values are taken from Boggs et al. (2015) and McCray & Fransson (2016). Our 3D models can easily produce a high amount of 44Ti and reach the high 44Ti/56Ni ratio observed in Cas A. Therefore, the “44Ti problem” (The et al. 2006) is no longer an issue in self-consistent long-term, 3D, initially nonrotating CCSN models. In addition, the lower 44Ti/56Ni ratios of the black hole formers clearly show the important role of neutrino-driven winds in the production of 44Ti, since the winds in these models are turned off after black hole formation.
Paper: Insights into the Production of 44Ti and Nickel Isotopes in Core-collapse Supernovae
Authors: Tianshu Wang, Adam Burrows
Figure caption: Neutrino-driven wind mass outflow rates measured at 500 km, smoothed over 100 ms. Although there are fluctuations in the wind mass outflow rates, they generally decay exponentially with time at later times, which allows us to extrapolate their evolution. We fit exponential relations to the wind mass outflow rates in the last 1.5–2 s of each simulation. The black hole formers (19.56 and 40 M ⊙) are not shown on this plot because their neutrino-driven winds are instantly turned off after the black hole formation (which is the end of the 3D simulation).
Paper: Insights into the Production of 44Ti and Nickel Isotopes in Core-collapse Supernovae
Authors: Tianshu Wang, Adam Burrows
Figure caption:  56Ni yield as a function of time. The circular dot on each curve marks the beginning point of extrapolation. The black hole formers (19.56 and 40 M ⊙) are plotted as dashed curves, and they have no extrapolated neutrino-driven winds. In all models, the majority of 56Ni is produced in the first 4–5 s after the bounce, while the more aspherical models with stronger long-lasting accretion (e.g., the 11, 19, 25, and 60 M ⊙ models) experience a further 10% 56Ni production during the extrapolated phase. This late-time 56Ni increase results from the α-rich freeze-out process in the enhanced neutrino-driven winds (see Figure 1) due to their longer-lasting accretion. However, in general, after a few seconds, the neutrino-driven winds do not contribute much to the total 56Ni yields.
Paper: Insights into the Production of 44Ti and Nickel Isotopes in Core-collapse Supernovae
Authors: Tianshu Wang, Adam Burrows
Figure caption:  57Ni yield and 57Ni/56Ni ratio as a function of time. The circular dot on each curve marks the beginning point of extrapolation. The black hole formers (19.56 and 40 M ⊙) are plotted as dashed curves. The black horizontal line shows the solar 57Fe/56Fe ratio as a reference. Similar to 44Ti, a large amount of 57Ni is produced at later times (>5 s post-bounce) due to the α-rich freeze-out process in the proton-rich neutrino-driven winds. However, a high 57Ni/56Ni ratio (e.g., 3×10−2) cannot be reached unless the explosion has a significant amount of neutron-rich ejecta.
Paper: Using the Cartwheel CME to Predict Off-limb Observations of CMEs for New and Upcoming UV and EUV Spectrometers
Authors: E. M. Wraback, E. Landi, W. B. Manchester
Figure caption: Graphical representation of the potential electron temperature diagnostics for SPICE (top) and EUVST (bottom) vs. the effective temperature. The black line represents T eff = T ratio.
Paper: Insights into the Production of 44Ti and Nickel Isotopes in Core-collapse Supernovae
Authors: Tianshu Wang, Adam Burrows
Figure caption: Final 57Ni and 56Ni yield of 3D theoretical models compared to observed values in SN 1987A. The black hole formers (19.56 and 40) are plotted as square dots. Despite the large error bars, SN 1987A has a higher 57Ni/56Ni ratio than most of our models. Only the most neutron-rich explosion (9a) shows a 57Ni/56Ni ratio within the 1σ range of the observation. One possibility is that SN 1987A exploded more prompt than most of our massive models and ejected a larger amount of neutron-rich matter. See the text for more discussions.
Paper: Using the Cartwheel CME to Predict Off-limb Observations of CMEs for New and Upcoming UV and EUV Spectrometers
Authors: E. M. Wraback, E. Landi, W. B. Manchester
Figure caption: DEM of the Cartwheel CME using the EIS observations. The solid lines represent the DEM values. The shaded regions correspond to a 1σ uncertainty on the MCMC calculation.
Paper: Exploring the Broadband Spectral and Timing Characteristics of GRS 1915+105 with AstroSat and NICER Observations
Authors: Ruchika Dhaka, Ranjeev Misra, Pankaj Jain, J. S. Yadav
Figure caption: The top-left panel depicts the fractional rms spectrum of AstroSat (For high flux at ∼2 Hz frequency), specifically LAXPC10 and 20, along with NICER. Concurrently, the top-right panels present the time-lag spectrum for the high flux of AstroSat at approximately ∼2 Hz. The energy range used as a reference for calculating the time-lag spectra was chosen to be 6–8 keV band for LAXPC and 6–7 keV for NICER. On the other hand, the bottom-left panel shows the fractional rms spectrum, while the bottom-right panel illustrates the time-lag spectrum for the low flux at around ∼2 Hz. In this case, the reference energy band used for calculating the time-lag spectra is 10.0–14.0 keV for LAXPC and 3–5 keV NICER. The solid line represents the predicted model for energy-dependent rms and time lag, while the points show the observational results. The heating rate, Diskbb norm, and temperature were varied to explain the frac rms and time lag variation.
Paper: Detection of Dimethyl Ether in the Central Region of the MWC 480 Protoplanetary Disk
Authors: Yoshihide Yamato, Yuri Aikawa, Viviana V. Guzmán, Kenji Furuya, Shota Notsu, Gianni Cataldi, Karin I. Öberg, Chunhua Qi, Charles J. Law, Jane Huang, Richard Teague, Romane Le Gal
Figure caption: Left and middle: gas density (left) and temperature (middle) structure of the disk model. The dashed lines in the middle panel enclose the region where molecules distribute for each boundary temperature in the models (80, 100, 120, and 140 K from outside). The upper boundary of the regions is z/r = 0.3, which is also depicted by the dashed lines. Right: comparison of the observed and modeled spectra of the CH3OCH3 transitions at ∼299.89 GHz for the models, with different boundary temperatures of CH3OCH3 (blue for the 80 K model and orange for the 100 K model). The spectra of these models are nearly identical and overlap.
Paper: Exploring the Broadband Spectral and Timing Characteristics of GRS 1915+105 with AstroSat and NICER Observations
Authors: Ruchika Dhaka, Ranjeev Misra, Pankaj Jain, J. S. Yadav
Figure caption: The left panel shows the power density spectra for high flux in the 0.005–80 Hz frequency range, using LAXPC10, LAXPC20, and NICER. The right panel shows the PDS of low flux in the frequency range of 0.005–80 Hz using LAXPC10, LAXPC20, and NICER. The red and black colors distinguish NICER and LAXPC10, LAXPC20 PDS.
Paper: Exploring the Broadband Spectral and Timing Characteristics of GRS 1915+105 with AstroSat and NICER Observations
Authors: Ruchika Dhaka, Ranjeev Misra, Pankaj Jain, J. S. Yadav
Figure caption: A 2.3775 binned background-subtracted light curve generated from LAXPC20 in the energy range 4–50 keV (top-left panel), SXT in the energy range 1–7 keV (middle left panel), and NICER in the energy range 1.3–10.0 keV (bottom-left panel) for the simultaneous observations made on October 31 and 2017 November 1. The right panel represents the LAXPC20 light curve with the hardness ratio varying with time. The hardness ratio is defined as the ratio of the count rate in the 8–30 keV and 4–8 keV energy bands. The shaded region indicates the low flux regime, while the remaining area pertains to the high flux.
Paper: Exploring the Broadband Spectral and Timing Characteristics of GRS 1915+105 with AstroSat and NICER Observations
Authors: Ruchika Dhaka, Ranjeev Misra, Pankaj Jain, J. S. Yadav
Figure caption: The left panels show the energy spectra of NICER/LAXPC of high flux in the top panel and low flux in the bottom panel, respectively, in the energy range of 1.5–20 keV. The SXT/LAXPC spectra for the high and low fluxes are shown in the right top and right bottom panels in the 1–20 keV energy range. The residuals are displayed beneath each spectrum. The data points for NICER, LAXPC20, and SXT are represented in blue, red, and black, respectively.
Paper: Exploring the Broadband Spectral and Timing Characteristics of GRS 1915+105 with AstroSat and NICER Observations
Authors: Ruchika Dhaka, Ranjeev Misra, Pankaj Jain, J. S. Yadav
Figure caption: Hardness–Intensity Diagram using LAXPC20 data (observation ID G08_028T01_9000001656) with 10 s time binning. The hardness ratio is consistent with the definition provided in Figure 1, and the X-ray intensity (X-axis) is extracted within the 4–30 keV energy range.
Paper: Detection of Dimethyl Ether in the Central Region of the MWC 480 Protoplanetary Disk
Authors: Yoshihide Yamato, Yuri Aikawa, Viviana V. Guzmán, Kenji Furuya, Shota Notsu, Gianni Cataldi, Karin I. Öberg, Chunhua Qi, Charles J. Law, Jane Huang, Richard Teague, Romane Le Gal
Figure caption: Parameter covariances and marginalized posterior distributions for the MCMC spectral fit. The values and errors at the top of each panel indicate the 16th, 50th (median), and 84th percentiles of the posterior distributions.
Paper: Detection of Dimethyl Ether in the Central Region of the MWC 480 Protoplanetary Disk
Authors: Yoshihide Yamato, Yuri Aikawa, Viviana V. Guzmán, Kenji Furuya, Shota Notsu, Gianni Cataldi, Karin I. Öberg, Chunhua Qi, Charles J. Law, Jane Huang, Richard Teague, Romane Le Gal
Figure caption: 1.03 mm continuum image made with a Briggs robust value of 0.5. The inset panel presents the zoomed-in view of the vicinity of the new submillimeter source. The beam size of 0.″31 × 0.″21 (PA = 8.°2) is shown in the lower left corner of each panel. A scale bar is shown in the lower right corner of each panel.
Paper: A Comparison of the X-Ray Polarimetric Properties of Stellar and Supermassive Black Holes
Authors: M. Lynne Saade, Philip Kaaret, Ioannis Liodakis, Steven R. Ehlert
Figure caption: Plot of the logarithm of the PD vs. the logarithm of the black hole mass (M BH). Orange denotes a soft state observation, blue denotes a hard state observation, magenta denotes an SPL observation, and black denotes a source that is obscured. Stellar mass black holes are plotted as circles; supermassive black holes are plotted as squares. Note that MCG 05-23-16, the soft state of Swift J1727.8-1613, and LMC X-1 have upper limits on the PD, while 4U 1957+115 has an upper limit on the mass. There is no clear trend in the PD with respect to mass, as expected if the accretion geometry of stellar black holes and supermassive black holes is similar.
Paper: A Comparison of the X-Ray Polarimetric Properties of Stellar and Supermassive Black Holes
Authors: M. Lynne Saade, Philip Kaaret, Ioannis Liodakis, Steven R. Ehlert
Figure caption: Plot of the logarithm of the PD for each source vs. the offset between the PA and the main axis of the system. Only sources with system axis position angle measurements are plotted. Blue denotes a hard state observation, magenta denotes an SPL observation, black denotes an obscured source, and orange denotes a soft state observation. Polarization was not confidently detected for the soft state observations; thus, the PA offset from system axis values should be regarded as tentative. Stellar mass black holes are plotted as circles; supermassive black holes are plotted as squares. Error bars on the system offset are derived from uncertainties on the PA only.
Paper: A Comparison of the X-Ray Polarimetric Properties of Stellar and Supermassive Black Holes
Authors: M. Lynne Saade, Philip Kaaret, Ioannis Liodakis, Steven R. Ehlert
Figure caption: Diagram of the polarization behavior of obscured black holes. Blue represents the corona, orange represents the accretion disk, and red represents the obscuring torus. The purple lines indicate the path of photons. Photons from the corona Compton scatter off of the torus and into the line of sight. If the torus is extended in the vertical direction, then the polarization angle is oriented perpendicular to that plane, or perpendicular to axis of symmetry of the system. In this case, the polarization vector is pointed out of the page.
Paper: A Comparison of the X-Ray Polarimetric Properties of Stellar and Supermassive Black Holes
Authors: M. Lynne Saade, Philip Kaaret, Ioannis Liodakis, Steven R. Ehlert
Figure caption: Plot of the PD of the IXPE black hole sources vs. their inclination. Orange denotes a soft state observation, blue denotes a hard state observation, magenta denotes an SPL observation, and black denotes an obscured source. Stellar mass black holes are plotted as circles; supermassive black holes are plotted as squares. Note that IC 4329A and MCG 5-23-16 have upper limits on the inclination.
Paper: A Comparison of the X-Ray Polarimetric Properties of Stellar and Supermassive Black Holes
Authors: M. Lynne Saade, Philip Kaaret, Ioannis Liodakis, Steven R. Ehlert
Figure caption: Diagram of the polarization behavior of unobscured black holes in the hard state. Orange represents the accretion disk; blue represents the corona. The purple lines indicate the path of photons. Photons from the accretion disk inversely Compton scatter in the corona toward our line of sight. If the corona is extended along the plane of the accretion disk, then the polarization angle is oriented perpendicular to that plane, or parallel to axis of symmetry of the system. In this case, the polarization vector is oriented vertically.
Paper: Data-driven Stellar Intrinsic Colors and Dust Reddenings for Spectrophotometric Data: From the Blue-edge Method to a Machine Learning Approach
Authors: He Zhao, 赫 赵, Shu Wang, 舒 王, Biwei Jiang, 碧沩 姜, Jun Li, 军 李, Dongwei Fan, 东卫 樊, Yi Ren, 逸 任, Xiaoxiao Ma, 晓骁 马
Figure caption: Statistics of the absolute color differences between observed colors and the XGBoost predictions as a function for T eff, ﹩{\rm{log}}\,g﹩, [M/H], and G magnitude for the test set. Rows from top to bottom show the differences for G BP − G RP, G BP − K S, and J − K S. For colored squares and lines in each panel: blue is the MedAD, red is the RMSD, and green is the AD90%. These statistics were calculated in different bins with a step of 200 K for T eff, 0.25 for ﹩{\rm{log}}\,g﹩, 0.25 dex for [M/H], and 0.5 mag for G, respectively.
Paper: Data-driven Stellar Intrinsic Colors and Dust Reddenings for Spectrophotometric Data: From the Blue-edge Method to a Machine Learning Approach
Authors: He Zhao, 赫 赵, Shu Wang, 舒 王, Biwei Jiang, 碧沩 姜, Jun Li, 军 李, Dongwei Fan, 东卫 樊, Yi Ren, 逸 任, Xiaoxiao Ma, 晓骁 马
Figure caption: The same as Figure 4 but for stars hotter than 8000 K. The points are color coded by their number density calculated by a Gaussian kernel density estimation.
Paper: Reionization Parameter Inference from 3D Minkowski Functionals of the 21 cm Signals
Authors: Kangning Diao, Zhaoting Chen, Xuelei Chen, Yi Mao
Figure caption: Illustrations of the instrumental effects in mock SKA and HERA-like observations. The top left panel shows a slice of the 21 cm signal at z = 7 (corresponding to ﹩{\bar{x}}_{{\rm{H}}{\rm\small{I}}}=0.32﹩) in the FAINT GALAXIES model. The panels in the middle (bottom) row show the 21 cm signals that are applied with the instrumental effects with the HERA-like (SKA) observations. In each of the middle and bottom rows, panels from the left to the right column show the 21 cm signals that are convolved with the PSF (first column), a realization of thermal noise simulations (second column), the PSF-convolved 21 cm signals with thermal noise applied (third column), the PSF-convolved 21 cm signals that are applied with thermal noise and foreground wedge cut (fourth column), respectively. Note that the color bar for the middle and bottom panels, as shown at the bottom of the figure, is different from the color bar for the top left panel.
Paper: Reionization Parameter Inference from 3D Minkowski Functionals of the 21 cm Signals
Authors: Kangning Diao, Zhaoting Chen, Xuelei Chen, Yi Mao
Figure caption: The MFs around transition points with SKA-Low noise between different stages. We show four MFs (from top to bottom)—V 0, V 1, V 2, and V 3, respectively, around four different transition points (from left to right). The gray-dotted, red solid, and blue dashed lines represent the average MFs before, during, and after the transition point. The 1σ errors of each line are shown in the shaded region with the same color.
Paper: Reionization Parameter Inference from 3D Minkowski Functionals of the 21 cm Signals
Authors: Kangning Diao, Zhaoting Chen, Xuelei Chen, Yi Mao
Figure caption: The posterior distribution of EOR parameters using the SKA-Low configuration with 1000 hr observation for the FAINT GALAXIES (left) and BRIGHT GALAXIES (right) models, respectively. The lower left plot in each panel shows the 1σ (dark-shaded region) and 2σ region (light-shaded region), with the results from MFs shown in red and PS shown in blue. The dashed lines indicate the fiducial parameter values. The lower-right plot and upper-left plot in each panel show the marginalized probability distribution, where 1σ intervals are shown as the shaded regions.
Paper: Reionization Parameter Inference from 3D Minkowski Functionals of the 21 cm Signals
Authors: Kangning Diao, Zhaoting Chen, Xuelei Chen, Yi Mao
Figure caption: The MF V 3 at z = 8, assuming thermal noise with SKA-Low deep (top) and HERA-like (bottom) observations, respectively. Here, we assume different scenarios of foreground cut—the no-foreground-cut scenario (blue solid line), an optimistic (default) foreground wedge slope m = 0.35 (0.5) for SKA (HERA-like) observations (red solid line), and a more realistic scenario where the value of the wedge slope m is doubled from the default value (cyan solid line). All fields are normalized to have the same Gaussian template (gray-dotted line). We also show the 1σ errors in shaded regions with the same color.
Paper: Reionization Parameter Inference from 3D Minkowski Functionals of the 21 cm Signals
Authors: Kangning Diao, Zhaoting Chen, Xuelei Chen, Yi Mao
Figure caption: The average MFs and corresponding 1σ errors in shaded regions, assuming SKA-Low noise. We consider the no-foreground-cut scenario (left) and the foreground scenario with the wedge slope m = 0.7 (right), respectively. We show the results by varying four different sets of reionization parameters that all yield ﹩{\bar{x}}_{{\rm{H}}{\rm\small{I}}}\approx 0.60﹩ at z = 8.
Paper: Reionization Parameter Inference from 3D Minkowski Functionals of the 21 cm Signals
Authors: Kangning Diao, Zhaoting Chen, Xuelei Chen, Yi Mao
Figure caption: The PSFs used for the mock observations at z = 8 using SKA-Low (left) and for HERA-like observations (right), respectively.
Paper: Reionization Parameter Inference from 3D Minkowski Functionals of the 21 cm Signals
Authors: Kangning Diao, Zhaoting Chen, Xuelei Chen, Yi Mao
Figure caption: The bubble size distribution of the reionization field in the simulation for the FAINT GALAXIES model at z = 7 (solid yellow line) and z = 8 (solid blue line). The FWHM of the PSF is shown for the HERA-like configuration (dotted–dashed lines) and SKA-Low (dashed lines), respectively.
Paper: Reionization Parameter Inference from 3D Minkowski Functionals of the 21 cm Signals
Authors: Kangning Diao, Zhaoting Chen, Xuelei Chen, Yi Mao
Figure caption: Same as Figure 6 but for the HERA-like configuration with 1000 hr observation (and with different axis scales).
Paper: Mapping the Longitudinal Magnetic Field in the Atmosphere of an Active Region Plage from the Inversion of the Near-ultraviolet CLASP2.1 Spectropolarimetric Data
Authors: Hao Li, Tanausú del Pino Alemán, Javier Trujillo Bueno, Ryohko Ishikawa, Ernest Alsina Ballester, David E. McKenzie, Luca Belluzzi, Donguk Song, Takenori J. Okamoto, Ken Kobayashi, Laurel A. Rachmeler, Christian Bethge, Frédéric Auchère
Figure caption: AIA images in the 304 (A), 171 (B), and 1600 Å (C) bands. (D) IRIS slit-jaw image at 2796 Å. (E) HMI magnetogram. Panels (A), (B), and (C) are shown in log scale. The blue vertical lines indicate the 16 slit positions in the CLASP2.1 observation. The red, yellow, and green “×” symbols in panel (E) indicate the position of the example profiles shown in Figures 3, 8, and 10–12.