SKT5SciSumm -- A Hybrid Generative Approach for Multi-Document Scientific Summarization

Summarization for scientific text has shown significant benefits both for the research community and human society. Given the fact that the nature of scientific text is distinctive and the input of the multi-document summarization task is substantially long, the task requires sufficient embedding generation and text truncation without losing important information. To tackle these issues, in this paper, we propose SKT5SciSumm - a hybrid framework for multi-document scientific summarization (MDSS). We leverage the Sentence-Transformer version of Scientific Paper Embeddings using Citation-Informed Transformers (SPECTER) to encode and represent textual sentences, allowing for efficient extractive summarization using k-means clustering. We employ the T5 family of models to generate abstractive summaries using extracted sentences. SKT5SciSumm achieves state-of-the-art performance on the Multi-XScience dataset. Through extensive experiments and evaluation, we showcase the benefits of our model by using less complicated models to achieve remarkable results, thereby highlighting its potential in advancing the field of multi-document summarization for scientific text

A Survey of Pre-trained Language Models for Processing Scientific Text

The number of Language Models (LMs) dedicated to processing scientific text is on the rise. Keeping pace with the rapid growth of scientific LMs (SciLMs) has become a daunting task for researchers. To date, no comprehensive surveys on SciLMs have been undertaken, leaving this issue unaddressed. Given the constant stream of new SciLMs, appraising the state-of-the-art and how they compare to each other remain largely unknown. This work fills that gap and provides a comprehensive review of SciLMs, including an extensive analysis of their effectiveness across different domains, tasks and datasets, and a discussion on the challenges that lie ahead.Comment: Resources are available at https://github.com/Alab-NII/Awesome-SciL

Toll-like receptor pre-stimulation protects mice against lethal infection with highly pathogenic influenza viruses

<p>Abstract</p> <p>Since the beginning of the 20th century, humans have experienced four influenza pandemics, including the devastating 1918 'Spanish influenza'. Moreover, H5N1 highly pathogenic avian influenza (HPAI) viruses are currently spreading worldwide, although they are not yet efficiently transmitted among humans. While the threat of a global pandemic involving a highly pathogenic influenza virus strain looms large, our mechanisms to address such a catastrophe remain limited. Here, we show that pre-stimulation of Toll-like receptors (TLRs) 2 and 4 increased resistance against influenza viruses known to induce high pathogenicity in animal models. Our data emphasize the complexity of the host response against different influenza viruses, and suggest that TLR agonists might be utilized to protect against lethality associated with highly pathogenic influenza virus infection in humans.</p

イリョウ ケア カンレン ハイエン ニ カンスル マエムキ エキガク チョウサ

医療ケア関連肺炎(HCAP)は,ATS/IDSAの肺炎のガイドライン(2005年)にて提唱された概念である.当院におけるHCAPの特徴を明らかにする目的で前向き研究を行った.2010年1～12月に獨協医科大学越谷病院呼吸器内科に市中肺炎で入院した患者を対象とした.HCAPと市中肺炎(CAP)の判断にあたっては, HCAP疑い因子の有無をアンケートにより調査した.それ以外の介入は行わず,背景因子,肺炎重症度,肺炎の再燃の有無について調査した.年齢はHCAP 73±10歳,CAP 65±9歳(p<0.05)と両群間で有意差を認め,HCAP群では悪性腫瘍の合併が多く(p<0.05),自立度が低かった(p<0.05).入院時検査所見,胸部X線点数は,両群間に有意差を認めなかった.肺炎重症度は,A-DROPでは,HCAP群が,軽症30%,中等症63%,重症7%,CAP群が,軽症75%,中等症12%,重症13%で,有意差がみられた(p<0.05)が,PSIスコアでは,重症度に有意差を認めなかった.30日以内の肺炎再燃はHCAP群で21%,CAP群では0%であった.本研究より,HCAPでは,入院時の重症度に関らず,より慎重な経過観察が必要であることが示唆された.詳細にHCAP危険因子に関する病歴を聴取し,HCAPをCAPと誤認しないようにすることが重要である.Backgrounds:Healthcare associated pneumonia(HCAP) is a new concept proposed in guidelines for themanagement of adults with hospital-acquired, ventilatorassociated,and healthcare-associated pneumonia by ATS/IDSA. Several retrospective studies investigating the characteristicof HCAP in Japan have been performed. However,at present, a cohort study exploring the characteristic ofHCAP in Japan has not been published.Patients and Methods:This study was a prospectiveobservational study. Patients with pneumonia who admittedto Dokkyo Medical University Koshigaya Hospital betweenJanuary and December in 2010 were enrolled in this study.After giving informed consent, the patients were requestedto fill out a questionnaire designed to obtain informationabout risk factors of HCAP and divided into groups, HCAPor CAP, and their clinical characteristics were observed.Results:Mean age of enrolled patients were 73±10 yr inHCAP and 65±9 yr in CAP (p<0.05). The percentage ofpatients with malignant diseases were higher in HCAPgroup (p<0.05). There were no statistically significant differencesin WBC, CRP or chest X ray score on admissionbetween the groups. A-DROP score showed statistically asignificant difference between the groups while PSI scoredid not. The recurrence of pneumonia within 30 days afterdischarge of hospital was 21 % in HCAP groups but 0 % inCAP group.Conclusion:This study showed that patients withHCAP need to receive more careful care and observation toprevent recurrence even though the severity of pneumoniaon admission was not very high. It is crucial to take patients\u27history carefully to identify correctly whether a patientis with HCAP or CAP

Anomalously low amplitude of S waves produced by the 3D structures in the lower mantle

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