Wereported the first case of hypersensitivity pneumonitis (HP) by an edible mushroom, Pleurotus Eryngii (Eringi). A 54-year-old womanhad worked in a Bunashimeji mushroom factory for 42 months, and she movedto a new factory producing Eringi. Twomonths after, she was found to have HPby the spore of Eringi. Although no radiological finding was detected 6 months before the onset of HP, serum surfactant protein D (SP-D) had been elevated. We speculated that type II pneumocyte activation might prepare the ground for HP during the former exposure to Bunashimeji, and serum SP-D levels might reflect their conditions. (Internal Medicine 41: 571-573, 2002)

This paper elaborates on the design of a machine translation evaluation method that aims to determine to what degree the meaning of an original text is preserved in translation, without looking into the grammatical correctness of its constituent sentences. The basic idea is to have a human evaluator take the sentences of the translated text and, for each of these sentences, determine the semantic relationship that exists between it and the sentence immediately preceding it. In order to minimise evaluator dependence, relations between sentences are expressed in terms of the conjuncts that can connect them, rather than through explicit categories. For an n-sentence text this results in a list of n − 1 sentence-to-sentence relationships, which we call the text's connectivity profile. This can then be compared to the connectivity profile of the original text, and the degree of correspondence between the two would be a measure for the quality of the translation. A set of "essential" conjuncts was extracted for English and Japanese, and a computer interface was designed to support the task of inserting the most fitting conjuncts between sentence pairs. With these in place, several sets of experiments were performed.

Background: To treat diseases caused by genetic variants, it is necessary to identify disease-causing variants in patients. However, since there are a large number of disease-causing variants, the application of AI is required. We propose AI to solve this problem and report the results of its application in identifying disease-causing variants. Methods: To assist physicians in their task of identifying disease-causing variants, we propose an explainable AI (XAI) that combines high estimation accuracy with explainability using a knowledge graph. We integrated databases for genomic medicine and constructed a large knowledge graph that was used to achieve the XAI. Results: We compared our XAI with random forests and decision trees. Conclusion: We propose an XAI that uses knowledge graphs for explanation. The proposed method achieves high estimation performance and explainability. This will support the promotion of genomic medicine.

When translating formal documents, capturing the sentence structure specific to the sublanguage is extremely necessary to obtain high-quality translations. This paper proposes a novel global reordering method that focuses on long-distance reordering to capture the global sentence structure of a sublanguage. The proposed method learns global reordering models without syntactic parsing from a non-annotated parallel corpus and works in conjunction with conventional syntactic reordering. The experimental results regarding patent abstract sublanguage show concrete improvements in translation quality, both for Japanese-to-English and English-to-Japanese translations.

Patent claim sentences, despite their legal importance in patent documents, still pose difficulties for state-of-the-art statistical machine translation (SMT) systems owing to their extreme lengths and their special sentence structure. This paper describes a method for improving the translation quality of claim sentences, by taking into account the features specific to the claim sublanguage. Our method overcomes the issue of special sentence structure, by transferring the sublanguage-specific sentence structure from the source language to the target language, using a set of synchronous context-free grammar rules. Our method also overcomes the issue of extreme lengths by taking the sentence components to be the processing unit for SMT. An experiment demonstrates that our proposed method significantly improves the translation quality in terms of RIBES scores by over 25 points, in all of the four translation directions i.e., English-to-Japanese, Japanese-to-English, Chinese-to-Japanese and Japanese-toChinese directions. Alongside the improvement in RIBES scores, improvements of † , National