adsabs/AstroCLIMB huggingface dataset:
Paper: Observational Properties of 155 O- and B-type Massive Pulsating Stars 
Authors: Xiang-dong Shi, 相东 施, Sheng-bang Qian, 声帮 钱, Li-ying Zhu, 俐颖 朱, Liang Liu, 亮 刘, Lin-jia Li, 临甲 李, Lei Zang, 蕾 臧
Figure caption: Example low-resolution spectra of Be star TIC53327951 from LAMOST.
Paper: Infrared Galaxies Detected by the Atacama Cosmology Telescope
Authors: Ece Kilerci, Tetsuya Hashimoto, Tomotsugu Goto, Ersin Göğüş, Seong Jin Kim, Simon C.-C. Ho, Yi Hang Valerie Wong
Figure caption: Log (T ap,DR3/T cat,DR3) as a function of ﹩\mathrm{log}{T}_{\mathrm{cat},\mathrm{DR}3}﹩ for sources in the DR3 point-source catalog (Datta et al. 2019). Here, T ap,DR3 is the DR3 differential CMB temperature measured within an aperture with a 1.0×FWHMPSF diameter. T cat,DR3 is the differential CMB temperature in the DR3 point-source catalog. The observed frequency is 150 GHz. The horizontal dashed black line indicates y = 0, while the solid blue line is the best-fit linear function (y = ax + b) to the data points. In this linear fit, a = 0.006 ± 0.001, b = − 0.379 ± 0.003, and ﹩{\sigma }_{\mathrm{log}T}=0.041﹩. ﹩{\sigma }_{\mathrm{log}T}﹩ indicates the vertical data dispersion around the best-fit linear function in logarithm scale. ﹩{\sigma }_{\mathrm{log}T}=0.041﹩ corresponds to a ∼10% dispersion in linear scale.
Paper: Infrared Galaxies Detected by the Atacama Cosmology Telescope
Authors: Ece Kilerci, Tetsuya Hashimoto, Tomotsugu Goto, Ersin Göğüş, Seong Jin Kim, Simon C.-C. Ho, Yi Hang Valerie Wong
Figure caption: Log (f apcor,DR5/f cat,DR3) as a function of ﹩\mathrm{log}{f}_{\mathrm{cat},\mathrm{DR}3}﹩ for sources in the DR3 point-source catalog (Datta et al. 2019). Here, f apcor,DR5 is the measured DR5 flux density corrected for aperture effect. f cat,DR3 is the flux density in the DR3 point-source catalog. The observed frequency is 150 GHz for both DR3 and DR5. The horizontal dashed black line indicates y = 0, while the solid blue line is the best-fit linear function to the data points. Here, a = 0.008 ± 0.020, b = −0.019 ± 0.030, and ﹩{\sigma }_{\mathrm{log}f}=0.096﹩. ﹩{\sigma }_{\mathrm{log}f}﹩ indicates the vertical data dispersion around the best-fit linear function in logarithm scale. ﹩{\sigma }_{\mathrm{log}f}=0.096﹩ corresponds to a ∼20% dispersion in linear scale.
Paper: Infrared Galaxies Detected by the Atacama Cosmology Telescope
Authors: Ece Kilerci, Tetsuya Hashimoto, Tomotsugu Goto, Ersin Göğüş, Seong Jin Kim, Simon C.-C. Ho, Yi Hang Valerie Wong
Figure caption: Example ACT images of four of the sources (with S/N ≥ 5) in our sample, detected at 98 GHz (left column), 150 GHz (middle column), and 220 GHz (right column), respectively. The source detections are shown inside the adopted searching radii (white circles) for matching. The image coordinates are provided in pixel units (1 pixel corresponds to 0.′5). The first three rows indicate AKARI-matched ACT sources, while the bottom row shows an IRAS-matched ACT source. The center of each panel corresponds to the position of the AKARI or IRAS source.
Paper: Infrared Galaxies Detected by the Atacama Cosmology Telescope
Authors: Ece Kilerci, Tetsuya Hashimoto, Tomotsugu Goto, Ersin Göğüş, Seong Jin Kim, Simon C.-C. Ho, Yi Hang Valerie Wong
Figure caption: The distributions of the α 98−150 (left), α 98−220 (middle), and α 150−220 (right) spectral indices. The black distributions represent galaxies that are classified as AGNs, according to the spectral indices, while the gray ones represent the galaxies that are classified as DSFGs.
Paper: The Evryscope Fast Transient Engine: Real-time Detection for Rapidly Evolving Transients
Authors: Hank Corbett, Jonathan Carney, Ramses Gonzalez, Octavi Fors, Nathan Galliher, Amy Glazier, Ward S. Howard, Nicholas M. Law, Robert Quimby, Jeffrey K. Ratzloff, Alan Vasquez Soto
Figure caption: Left: a 4° × 1° region near Proxima Centauri from reference, science, and subtraction images from EFTE, the HOTPANTS algorithm (Becker 2015), and the ZOGY algorithm (Zackay et al. 2016). For ZOGY, we include both the scaled S corr image used for point-source detection and the proper difference image D. In the subtraction images, a faint satellite streak (left), a variable star (bottom left), and an M-dwarf superflare (far right; Howard et al. 2018) are successfully recovered. The EFTE direct subtraction produces 47% more 3σ detections than ZOGY for this field, and it can be computed 10 times faster for this image size. Right: cutouts from the images on the left showing the ﹩1^{\prime} \times 1^{\prime} ﹩ region centered on Proxima Cen.
Paper: The Evryscope Fast Transient Engine: Real-time Detection for Rapidly Evolving Transients
Authors: Hank Corbett, Jonathan Carney, Ramses Gonzalez, Octavi Fors, Nathan Galliher, Amy Glazier, Ward S. Howard, Nicholas M. Law, Robert Quimby, Jeffrey K. Ratzloff, Alan Vasquez Soto
Figure caption: Top left: map of the flux ratio between a science and reference image couplet. Top right: the corresponding flux ratio error map. The flux ratio is measured based on forced aperture photometry of several thousand reference stars, and it is interpolated across each single-camera full-resolution image based on the observed flux ratio, in an equally spaced grid of 384 image sectors. Bottom: relative aperture flux residuals before and after correcting with the interpolated flux ratio, as a function of the x- and y-positions on the sensor. The correction improves the flux match between the images by <1%, which is not significant for short (Δt  D  = 2 minute) subtraction baselines. The increases in the flux offset at the edges of the image are caused by aperture losses due to the variable Evryscope PSF.
Paper: The Evryscope Fast Transient Engine: Real-time Detection for Rapidly Evolving Transients
Authors: Hank Corbett, Jonathan Carney, Ramses Gonzalez, Octavi Fors, Nathan Galliher, Amy Glazier, Ward S. Howard, Nicholas M. Law, Robert Quimby, Jeffrey K. Ratzloff, Alan Vasquez Soto
Figure caption: Left: examples of simulated transients with magnitudes ﹩g^{\prime} =10,11,12,13,14,15﹩ at the center and edges of a typical mid-galactic-latitude Evryscope image. The PSFs at each position are modeled as normalized, aligned, and sigma-clipped combinations of nearby isolated stars, producing morphologically plausible star-like injections. These simulations are used for the initial conditioning of our ML vetting system. Right: difference images for each subimage, using a reference frame taken 2 minutes before the injected science image.
Paper: The Evryscope Fast Transient Engine: Real-time Detection for Rapidly Evolving Transients
Authors: Hank Corbett, Jonathan Carney, Ramses Gonzalez, Octavi Fors, Nathan Galliher, Amy Glazier, Ward S. Howard, Nicholas M. Law, Robert Quimby, Jeffrey K. Ratzloff, Alan Vasquez Soto
Figure caption: Architecture of VETNET, a convolutional RB classifier used by EFTE. The inputs to the network are a triplet of 30 × 30 pixel cutouts around the center of each candidate, taken from the reference, science, and direct difference images. All trainable layers, except for the final dense unit, use ReLU activation. The pairs of convolution layers are all followed by max-pooling layers, with 20% dropout for regularization. The network visualization was generated with Net2Vis (Bäuerle et al. 2021).
Paper: The Evryscope Fast Transient Engine: Real-time Detection for Rapidly Evolving Transients
Authors: Hank Corbett, Jonathan Carney, Ramses Gonzalez, Octavi Fors, Nathan Galliher, Amy Glazier, Ward S. Howard, Nicholas M. Law, Robert Quimby, Jeffrey K. Ratzloff, Alan Vasquez Soto
Figure caption: EVRT-192099, a 5.5 mag flare from a star associated with 1RXS J174441.6-531551 in the ROSAT All-Sky Survey Bright Source Catalogue (Voges et al. 1999; Fresneau & Osborn 2009). The reference frame from 2019 October 4 at 9:06 UT is the science image from 8:58 UT, showing the sliding reference frame used by our direct subtraction algorithm.
Paper: The Evryscope Fast Transient Engine: Real-time Detection for Rapidly Evolving Transients
Authors: Hank Corbett, Jonathan Carney, Ramses Gonzalez, Octavi Fors, Nathan Galliher, Amy Glazier, Ward S. Howard, Nicholas M. Law, Robert Quimby, Jeffrey K. Ratzloff, Alan Vasquez Soto
Figure caption: Data flow and layout of the EFTE pipelines. The operations (orange) and real-time reduction (blue) components are independent for each observatory, while the pipeline monitoring (purple) and shared databases (green) collate data from both Evryscope-North and Evryscope-South.
Paper: The Evryscope Fast Transient Engine: Real-time Detection for Rapidly Evolving Transients
Authors: Hank Corbett, Jonathan Carney, Ramses Gonzalez, Octavi Fors, Nathan Galliher, Amy Glazier, Ward S. Howard, Nicholas M. Law, Robert Quimby, Jeffrey K. Ratzloff, Alan Vasquez Soto
Figure caption: Median PSFs across a 6 × 4 grid of sensor regions. PSF variability as a function of chip position is evident; however, long-term measurements of the Evryscope optical stability (Ratzloff et al. 2020) indicate that the PSFs are repeatable over time, despite aberrations.
Paper: The Evryscope Fast Transient Engine: Real-time Detection for Rapidly Evolving Transients
Authors: Hank Corbett, Jonathan Carney, Ramses Gonzalez, Octavi Fors, Nathan Galliher, Amy Glazier, Ward S. Howard, Nicholas M. Law, Robert Quimby, Jeffrey K. Ratzloff, Alan Vasquez Soto
Figure caption: Network accuracy vs. number of forward passes through the network for the validation set. The performances converge at 10 samples. The error bars represent the standard deviations of the results across 20 iterations.
Paper: The Evryscope Fast Transient Engine: Real-time Detection for Rapidly Evolving Transients
Authors: Hank Corbett, Jonathan Carney, Ramses Gonzalez, Octavi Fors, Nathan Galliher, Amy Glazier, Ward S. Howard, Nicholas M. Law, Robert Quimby, Jeffrey K. Ratzloff, Alan Vasquez Soto
Figure caption: (a) and (b) Photometric offsets between the Evryscope and PanSTARRS g bands as a function of g − r before and after calibration with the color and airmass terms above, respectively. The large offsets below the linear trend are caused by blended sources and low-S/N detections that were not filtered based on the light-curve quality metric described in Section 5.1. (c) and (d) The same as above, but with g − i colors in place of g − r, to demonstrate the performance over a wider variety of colors. No calibration fits are made as a function of the i-band colors. (e) and (f) The photometric calibration performance for many-epoch light curves as a function of magnitude. The sigma-clipped rms photometric offset decreases from 0.16 to 0.06 mag for sources between 8 < m  g  < 14.5 with the application of color terms.
Paper: The Evryscope Fast Transient Engine: Real-time Detection for Rapidly Evolving Transients
Authors: Hank Corbett, Jonathan Carney, Ramses Gonzalez, Octavi Fors, Nathan Galliher, Amy Glazier, Ward S. Howard, Nicholas M. Law, Robert Quimby, Jeffrey K. Ratzloff, Alan Vasquez Soto
Figure caption: Sample on-sky candidates taken from the VETNET test set. The “Actual” and “Pred” values represent the sky truth class as determined by a human inspector and the predicted class as determined by the network, respectively. Each histogram is an approximation of the normalized Bayesian posterior distribution for the probability of the candidate representing a real astrophysical event, quantified using the entropy-based ﹩{\mathbb{C}}﹩ metric from Killestein et al. (2021). In cases where the sky truth and the network prediction disagree, ﹩{\mathbb{C}}﹩ is typically <0.5, or extenuating circumstances exist, such as the anomalous PSFs in panels (f) and (l), or the potential human misclassifications in (h), (i), and (k).
Paper: The Evryscope Fast Transient Engine: Real-time Detection for Rapidly Evolving Transients
Authors: Hank Corbett, Jonathan Carney, Ramses Gonzalez, Octavi Fors, Nathan Galliher, Amy Glazier, Ward S. Howard, Nicholas M. Law, Robert Quimby, Jeffrey K. Ratzloff, Alan Vasquez Soto
Figure caption: Top: astrometric localization performance for the EFTE pipeline. Bottom: rms localization scatter as a function of magnitude. The performance is subpixel at the 99th percentile, with a typical rms scatter of 7″, excepting stars brighter than 7 mag, which are typically saturated, and those dimmer than 14 mag, where source confusion dominates in the source extraction.
Paper: The Evryscope Fast Transient Engine: Real-time Detection for Rapidly Evolving Transients
Authors: Hank Corbett, Jonathan Carney, Ramses Gonzalez, Octavi Fors, Nathan Galliher, Amy Glazier, Ward S. Howard, Nicholas M. Law, Robert Quimby, Jeffrey K. Ratzloff, Alan Vasquez Soto
Figure caption: The performance of VETNET on the on-sky test set. Top: precision and recall as a function of the VETNET RB score. At the RB = 0.5 threshold, the observed precision and recall are 95.4% and 94.4%, respectively. Middle: entropy-based confidence scores for false positives and false negatives as a function of the VETNET RB score threshold. The shaded regions indicate the score regions where no false positives or false negatives occur within the on-sky test set. Bottom: receiver operating characteristic (ROC) curve for VETNET. The area under the ROC curve is 0.99, representing the probability that a random real candidate will receive a higher RB score than a random bogus candidate. The “no-skill” line indicates the expected performance curve for a random classifier.
Paper: The Evryscope Fast Transient Engine: Real-time Detection for Rapidly Evolving Transients
Authors: Hank Corbett, Jonathan Carney, Ramses Gonzalez, Octavi Fors, Nathan Galliher, Amy Glazier, Ward S. Howard, Nicholas M. Law, Robert Quimby, Jeffrey K. Ratzloff, Alan Vasquez Soto
Figure caption: Misclassified training set samples relabeled based on the entropy-based confidence of the VETNET predictions. Network reclassifications typically affect samples that are difficult to classify manually. Samples (a) and (c) were initially classified as real by human vetters, but were relabeled as bogus by the algorithm. Both have pathological PSFs, likely caused by interpolation artifacts from resampling near a cosmic ray, a particle strike, or an unmasked bad pixel. Sample (b) is of low significance and off-center, but was manually classified as bogus, before being confidently relabeled as real by VETNET.
Paper: The Evryscope Fast Transient Engine: Real-time Detection for Rapidly Evolving Transients
Authors: Hank Corbett, Jonathan Carney, Ramses Gonzalez, Octavi Fors, Nathan Galliher, Amy Glazier, Ward S. Howard, Nicholas M. Law, Robert Quimby, Jeffrey K. Ratzloff, Alan Vasquez Soto
Figure caption: Survey completeness as a function of magnitude for both the current EFTE, with a VETNET RB threshold score of 0.5, and the previous version described in Corbett et al. (2020). The completeness is measured on a synthetic sample of injected transient and variable sources. The recovery probability for sources brighter than m  g  = 13.2 is 99.9%, which rapidly falls to 50% at m  g  = 14. The shaded regions represent the 90% confidence intervals of each curve, based on the percentiles of the per-image recovery functions.
Paper: The Evryscope Fast Transient Engine: Real-time Detection for Rapidly Evolving Transients
Authors: Hank Corbett, Jonathan Carney, Ramses Gonzalez, Octavi Fors, Nathan Galliher, Amy Glazier, Ward S. Howard, Nicholas M. Law, Robert Quimby, Jeffrey K. Ratzloff, Alan Vasquez Soto
Figure caption: Photometric calibration offsets between ATLAS-REFCAT2 and EFTE. The median rms offset in the region 8 < m  g  < 14.5 is 0.06 mag. The anomalously bright and high-precision measurements (upper right) are due to source confusion and blending. The underreporting of magnitudes due to saturation is evident for stars brighter than ﹩g^{\prime} =8﹩.
Paper: The Evryscope Fast Transient Engine: Real-time Detection for Rapidly Evolving Transients
Authors: Hank Corbett, Jonathan Carney, Ramses Gonzalez, Octavi Fors, Nathan Galliher, Amy Glazier, Ward S. Howard, Nicholas M. Law, Robert Quimby, Jeffrey K. Ratzloff, Alan Vasquez Soto
Figure caption: The measured rms values of 10,671 randomly selected long-term Evryscope light curves. The performance in the detrended light curves ranges from 20 mmag at the bright end to 20% for dim sources. The rms values for the raw light curves are averages of the measured rms in each pointing, neglecting zeropoint offsets between ratchets.
Paper: The Evryscope Fast Transient Engine: Real-time Detection for Rapidly Evolving Transients
Authors: Hank Corbett, Jonathan Carney, Ramses Gonzalez, Octavi Fors, Nathan Galliher, Amy Glazier, Ward S. Howard, Nicholas M. Law, Robert Quimby, Jeffrey K. Ratzloff, Alan Vasquez Soto
Figure caption: Cumulative histogram (a) and distribution (b) of the time delay between the exposure and the insertion of vetted candidates into the remote database, between 2019 November 25 and 2020 January 1. 98.5% of the images were fully reduced into lists of transient candidates within 120 s, before the next image was complete.
Paper: The Evryscope Fast Transient Engine: Real-time Detection for Rapidly Evolving Transients
Authors: Hank Corbett, Jonathan Carney, Ramses Gonzalez, Octavi Fors, Nathan Galliher, Amy Glazier, Ward S. Howard, Nicholas M. Law, Robert Quimby, Jeffrey K. Ratzloff, Alan Vasquez Soto
Figure caption: Spectrum of EVRT-3586872 at +14.87 minutes from the end of the first Evryscope detection of a flare candidate. The spectrum has been flux-calibrated and normalized. The overlaid curve is a two-component blackbody spectrum, consisting of a fitted 22,852 K flare continuum and a 3256 K quiescent thermal spectrum.
Paper: Characterization of Low-mass Companions to Kepler Objects of Interest Observed with APOGEE-N
Authors: Caleb I. Cañas, Chad F. Bender, Suvrath Mahadevan, Dmitry Bizyaev, Nathan De Lee, Scott W. Fleming, Fred Hearty, Steven R. Majewski, Christian Nitschelm, Donald P. Schneider, Javier Serna, Keivan G. Stassun, Guđmundur Stefánsson, Guy S. Stringfellow, John C. Wilson
Figure caption: (a) The mass–radius diagram spanning the regime of substellar companions and convective M dwarfs. The KOIs characterized in this work are shown as red stars, while the published objects are shown as gray circles. A nominal isochrone of 8 Gyr (the median SED age for the 28 KOIs) is plotted for reference. A total of 24 objects are nongrazing and have larger radii than theoretical models predict. The regions shown in panels (b) and (c) are marked with rectangles. (b). The mass–radius diagram for the nine nongrazing KOI companions spanning 30 M J < M 2 < 110 M J. (c) The mass–radius diagram for the 15 nongrazing KOI companions spanning 140 M J < M 2 < 250 M J. The objects in panels (b) and (c) are colored based on the age estimated from the SED fit. Evolutionary tracks for 2 and 8 Gyr from models by Marley et al. (2021; Sonora21), Phillips et al. (2020; ATMO20), Baraffe et al. (1998; BCAH98), and Baraffe et al. (2015; BHAC15) are plotted for reference and use the same color scale as the stars.
Paper: Characterization of Low-mass Companions to Kepler Objects of Interest Observed with APOGEE-N
Authors: Caleb I. Cañas, Chad F. Bender, Suvrath Mahadevan, Dmitry Bizyaev, Nathan De Lee, Scott W. Fleming, Fred Hearty, Steven R. Majewski, Christian Nitschelm, Donald P. Schneider, Javier Serna, Keivan G. Stassun, Guđmundur Stefánsson, Guy S. Stringfellow, John C. Wilson
Figure caption: The ratio between the measured radius and the predicted radius from the evolutionary models of Baraffe et al. (2015) and Marley et al. (2021) as a function of the period (left panel) and stellar age (right panel). In each panel, nongrazing KOIs are plotted as red stars, while grazing KOIs are shown as white stars. For clarity, KOI-2513 is not shown in this plot because of the large uncertainty on radius. Each system is compared to the prediction from evolutionary models at the median age determined from the SED fit. The Spearman correlation (r  s ) and associated p-value are listed for each panel. On average, the observed radii are 9.1% larger than the predicted radii.
Paper: Characterization of Low-mass Companions to Kepler Objects of Interest Observed with APOGEE-N
Authors: Caleb I. Cañas, Chad F. Bender, Suvrath Mahadevan, Dmitry Bizyaev, Nathan De Lee, Scott W. Fleming, Fred Hearty, Steven R. Majewski, Christian Nitschelm, Donald P. Schneider, Javier Serna, Keivan G. Stassun, Guđmundur Stefánsson, Guy S. Stringfellow, John C. Wilson
Figure caption: A plot of the KOIs listed in Table 1 and observed by our program overlaid on the Kepler footprint from Mullally et al. (2016a). The APOGEE-KOI field is listed above the CCD modules from the Kepler field observed as part of our program between 2013 and 2020. The 1.°49 APOGEE-N FOV is plotted as a dotted circle. The marker reflects the DR25 disposition from the NASA Exoplanet Archive. The APOGEE-KOI program observed 714 confirmed planets (blue circles), 441 planetary candidates (red squares), and 446 false positives (green diamonds) for a median of 19 visits. For reference, KOIs not observed as part of this program but observed multiple times with APOGEE-N are shown as black triangles.
Paper: Characterization of Low-mass Companions to Kepler Objects of Interest Observed with APOGEE-N
Authors: Caleb I. Cañas, Chad F. Bender, Suvrath Mahadevan, Dmitry Bizyaev, Nathan De Lee, Scott W. Fleming, Fred Hearty, Steven R. Majewski, Christian Nitschelm, Donald P. Schneider, Javier Serna, Keivan G. Stassun, Guđmundur Stefánsson, Guy S. Stringfellow, John C. Wilson
Figure caption: Gaussian process detrending. The example above shows the detrending result for one-quarter of long-cadence data for KOI-1416. The out-of-transit photometric variability in the Kepler light curve can be modeled using a quasiperiodic kernel. The top panel shows the flux (black points) normalized to the median value, while the middle panel is a magnification to the region highlighted by the rectangle. The red line is the maximum a posteriori model. The bottom panel shows the phase-folded photometry, once the baseline found by the Gaussian process is removed. No additional processing (e.g., sigma clipping) is performed.
Paper: Characterization of Low-mass Companions to Kepler Objects of Interest Observed with APOGEE-N
Authors: Caleb I. Cañas, Chad F. Bender, Suvrath Mahadevan, Dmitry Bizyaev, Nathan De Lee, Scott W. Fleming, Fred Hearty, Steven R. Majewski, Christian Nitschelm, Donald P. Schneider, Javier Serna, Keivan G. Stassun, Guđmundur Stefánsson, Guy S. Stringfellow, John C. Wilson
Figure caption: The eccentricity as a function of the period for published brown-dwarf-hosting systems. Gray triangles denote the brown dwarfs with ﹩{M}_{2}\sin i\lt 42.5\,{M}_{{\rm{J}}}﹩, while gray squares are larger than this mass. The dashed line indicates the maximum eccentricity for systems unaffected by tides when adopting a circularization period (see Halbwachs et al. 2005) of 10 days. The KOIs are denoted as red squares or triangles, depending on the mass.
Paper: An Extensive Catalog of Early-type Dwarf Galaxies in the Local Universe: Morphology and Environment
Authors: Sanjaya Paudel, Suk-Jin Yoon, Jaewon Yoo, Rory Smith, Daya Nidhi Chhatkuli, Rajesh Kumar Bachchan, Binil Aryal, Binod Adhikari, Namuna Adhikari, Amrit Sedain, Sharup Sheikh, Sarashwati Dhital, Ashutosh Giri, Rabin Baral
Figure caption: All-sky distribution of identified dEs in our sample. The sky coordinate is in the Aitoff projection. The blue and green circles represent the sky position of dEs with and without radial velocity information, respectively. The black circles represent the sky positions of giant galaxies. We also highlight two cluster regions, Virgo and Fornax, using the red circles of 10° and 7° radii, respectively.