J1406+0102: Dust Obscured Galaxy Hiding Super Eddington Accretion System with Bright Radio Emission

Recent high-$z$ quasar observations strongly indicate that super-Eddington accretion is a crucial phase to describe the existence of supermassive black holes (SMBHs) with $M_\mathrm{BH} \gtrsim 10^9 M_\odot$ at $z \gtrsim 7$. Motivated by the theoretical suggestion that the super-Eddington phase efficiently produces outflows and jets bright in radio bands, we search and find a super-Eddington radio-loud dust-obscured galaxy (DOG) J1406+0102 at $z=0.236$, through cross-matching of the infrared-bright DOGs of Noboriguchi et al. (2019) with the VLA/FIRST 1.4 GHz radio and the SDSS optical spectral catalog. DOG J1406+0102 shows broad components in the Balmer lines. Assuming those lines are from the broad line region, it gives BH mass estimation of $\log\ (M_\mathrm{BH}/M_\odot)=7.30 \pm 0.25$, and AGN luminosity of $\log (L_\mathrm{bol,[OIII]}/\mathrm{erg}~\mathrm{s}^{-1}) = 45.91\pm0.38$ estimated from the intrinsic [OIII] luminosity, resulting in super-Eddington accretion of $\lambda_\mathrm{Edd}\simeq 3$. We show that 1) DOG J1406+0102 is operating strong AGN feedback: the [OIII] outflow velocity exceeds the escape velocity of the host galaxy halo and the kinetic efficiency is obtained as $\approx$ 8% that can be sufficient to quench the host galaxy, 2) the expected future growth pathway of DOG J1406+0102 would join an over-massive BH trajectory and 3) radio-loud DOGs can provide a significant contribution to the high-energy ($\gtrsim$ 100 TeV) cosmic neutrino background if we assume DOG J1406+0102 as a representative of radio-loud DOGs.Comment: 10 pages, 5 figures, submitted to ApJ

H1821+643: The most X-ray and infrared luminous AGN in the Swift/BAT survey in the process of rapid stellar and supermassive black hole mass assembly

H1821+643 is the most X-ray luminous non-beamed AGN of $L_\mathrm{14-150 keV}= 5.2\times 10^{45}$ erg s$^{-1}$ in the Swift/BAT ultra-hard X-ray survey and it is also a hyper-luminous infrared (IR) galaxy $L_\mathrm{IR} = 10^{13.2} L_\odot$ residing in the center of a massive galaxy cluster, which is a unique environment achieving the rapid mass assembly of black holes (BH) and host galaxies in the local universe. We decompose the X-ray to IR spectral energy distribution (SED) into the AGN and starburst component using the SED fitting tool CIGALE-2022.0 and show that H1821+643 consumes a large amount of cold gas ($\dot{M}_\mathrm{con}$) with star-formation rate of $\log ( \mathrm{SFR}/M_{\odot}~\mathrm{yr}^{-1}) = 3.01 \pm 0.04$ and BH accretion rate of $\log (\dot{M}_\mathrm{BH}/M_{\odot}~\mathrm{yr}^{-1}) = 1.20 \pm 0.05$. This high $\dot{M}_\mathrm{con}$ is larger than the cooling rate ($\dot{M}_\mathrm{cool}$) of the intra-cluster medium (ICM), $\dot{M}_\mathrm{con}/\dot{M}_\mathrm{cool} \gtrsim 1$, which is one to two order magnitude higher than the typical value of other systems, indicating that H1821 provides the unique and extreme environment of rapid gas consumption. We also show that H1821+643 has an efficient cooling path achieving from $10^7$ K to $10^2$ K thanks to [OIII] 63 $\mu \mathrm{m}$, which is a main coolant in low temperature range ($10^4$ K to $10^2$ K) with a cooling rate of $\dot{M}_{\mathrm{cool}}=3.2\times 10^5\ M_{\odot}\mathrm{~yr^{-1}}$, and the star-forming region extends over 40 kpc scale.Comment: 20 pages, 8 figures, accepted for publication in Ap

Model of lung cancer surgery risk derived from a Japanese nationwide web-based database of 78 594 patients during 2014–2015

OBJECTIVESUsing data obtained from a Japanese nationwide annual database with web-based data entry, we developed a risk model of mortality and morbidity after lung cancer surgery.METHODSThe characteristics and operative and postoperative data from 80 095 patients who underwent lung cancer surgery were entered into the annual National Clinical Database of Japan data sets for 2014 and 2015. After excluding 1501 patients, the development data set for risk models included 38 277 patients entering in 2014 and the validation data set included 40 317 patients entering in 2015. Receiver–operating characteristic curves were generated for the outcomes of mortality and composite mortality/major morbidity. The concordance index was used to assess the discriminatory ability and validity of the model.RESULTSThe 30-day mortality and overall mortality rates, including in-hospital deaths, were 0.4% and 0.8%, respectively, in 2014, and 0.4% and 0.8%, respectively, in 2015. The rate of major morbidity was 5.6% in 2014 and 5.6% in 2015. Several risk factors were significantly associated with mortality, namely, male sex, performance status, comorbidities of interstitial pneumonia and liver cirrhosis, haemodialysis and the surgical procedure pneumonectomy. The concordance index for mortality and composite mortality/major morbidity was 0.854 (P < 0.001) and 0.718 (P < 0.001), respectively, for the development data set and 0.849 (P < 0.001) and 0.723 (P < 0.001), respectively, for the validation data set.CONCLUSIONSThis model was satisfactory for predicting surgical outcomes after pulmonary resection for lung cancer in Japan and will aid preoperative assessment and improve clinical outcomes for lung cancer surgery

Mask and Cloze: Automatic Open Cloze Question Generation Using a Masked Language Model

This paper conducts the first trial to apply a masked language AI model and the &#x201C;Gini coefficient&#x201D; to the field of English study. We propose an algorithm named CLOZER that generates open cloze questions that inquiry knowledge of English learners. Open cloze questions (OCQ) have been attracting attention for both measuring the ability and facilitating the learning of English learners. However, since OCQ is in free form, teachers have to ensure that only a ground truth answer and no additional words will be accepted in the blank. A remarkable benefit of CLOZER is to relieve teachers of the burden of producing OCQ. Moreover, CLOZER provides a self-study environment for English learners by automatically generating OCQ. We evaluated CLOZER through quantitative experiments on 1,600 answers and show its effectiveness statistically. Compared with human-generated questions, we also revealed that CLOZER can generate OCQs better than the average non-native English teacher. Additionally, we conducted a field study at a high school to clarify the benefits and hurdles when introducing CLOZER. Then, on the basis of our findings, we proposed several design improvements