Singly Cabibbo suppressed decays of Λc+\Lambda_{c}^+ with SU(3) flavor symmetry

We analyze the weak processes of anti-triplet charmed baryons decaying to octet baryons and mesons with the SU(3) flavor symmetry and topological quark diagram scheme. We study the decay branching ratios without neglecting the contributions from ${\cal O}(\overline{15})$ for the first time in the SU(3) flavor symmetry approach. The fitting results for the Cabibbo allowed and suppressed decays of $\Lambda_{c}^+$ are all consistent with the experimental data. We predict all singly Cabibbo suppressed decays. In particular, we find that ${\cal B}(\Lambda_c^+\to p \pi^0)=(1.3\pm0.7)\times 10^{-4}$, which is slightly below the current experimental upper limit of $2.7\times 10^{-4}$ and can be tested by the ongoing experiment at BESIII as well as the future one at Belle-II.Comment: 11 pages, 2 figure, revised version accepted by PL

Hidden Trends in 90 Years of Harvard Business Review

In this paper, we demonstrate and discuss results of our mining the abstracts of the publications in Harvard Business Review between 1922 and 2012. Techniques for computing n-grams, collocations, basic sentiment analysis, and named-entity recognition were employed to uncover trends hidden in the abstracts. We present findings about international relationships, sentiment in HBR's abstracts, important international companies, influential technological inventions, renown researchers in management theories, US presidents via chronological analyses.Comment: 6 pages, 14 figures, Proceedings of 2012 International Conference on Technologies and Applications of Artificial Intelligenc

Properties of Interstellar Medium In Infrared-Bright QSOs Probed by [O I] 63 μm and [C II] 158 μm Emission Lines

We present a study of the interstellar medium (ISM) in the host galaxies of nine QSOs at 0.1 1 IR-bright QSOs. One target, W0752+19, shows an additional broad velocity component (~720 km s^(−1)) and exceptionally strong [O I] 63 μm emission with L_([O I]63μm)/L_(FIR) of 10^(−2), an order of magnitude higher than the average value found among local (U)LIRGs. Combining with the analyses of the Sloan Digital Sky Survey optical spectra, we conclude that the [O I] 63 μm emission in these QSOs is unlikely excited by shocks. We infer that the broad [O I] 63 μm emission in W0752+19 could arise from the warm and dense ISM in the narrow-line region of the central active galactic nucleus. Another possible explanation is the existence of a dense gas outflow with n_H ~ 10^4 cm^(−3), where the corresponding broad [C II] emission is suppressed. Based on the far-IR [O I] and [C II] line ratios, we estimate constraints on the ISM density and UV radiation field intensity of n_H ≾ 10^(3.3) cm^(−3) and 10^3 10^4

PLM-ICD: Automatic ICD Coding with Pretrained Language Models

Automatically classifying electronic health records (EHRs) into diagnostic codes has been challenging to the NLP community. State-of-the-art methods treated this problem as a multilabel classification problem and proposed various architectures to model this problem. However, these systems did not leverage the superb performance of pretrained language models, which achieved superb performance on natural language understanding tasks. Prior work has shown that pretrained language models underperformed on this task with the regular finetuning scheme. Therefore, this paper aims at analyzing the causes of the underperformance and developing a framework for automatic ICD coding with pretrained language models. We spotted three main issues through the experiments: 1) large label space, 2) long input sequences, and 3) domain mismatch between pretraining and fine-tuning. We propose PLMICD, a framework that tackles the challenges with various strategies. The experimental results show that our proposed framework can overcome the challenges and achieves state-of-the-art performance in terms of multiple metrics on the benchmark MIMIC data. The source code is available at https://github.com/MiuLab/PLM-ICDComment: Accepted to the ClinicalNLP 2022 worksho