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Sonographic findings of acute appendiceal diverticulitis
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作者 Tadao Kubota toshihiro omori +3 位作者 Joji Yamamoto Motoki Nagai Satoshi Tamaki Ken Sasaki 《World Journal of Gastroenterology》 SCIE CAS CSCD 2006年第25期4104-4105,共2页
Preoperative images of acute appendiceal diverticulitis are rarely reported because of the difficulty of distinguishing appendiceal diverticulitis from other iliocecal diseases like acute appendicitis or cecal diverti... Preoperative images of acute appendiceal diverticulitis are rarely reported because of the difficulty of distinguishing appendiceal diverticulitis from other iliocecal diseases like acute appendicitis or cecal diverticulitis. We report a case of preoperatively diagnosed acute appendiceal diverticulitis. A 30-year-old female with a presumptive diagnosis of acute appendicitis from history and physical examination was admitted to our hospital. Ultrasound sonography showed inflamed appendiceal diverticula and inflammatory changes of the surrounding tissue. The swollen appendix was detected but its findings were slightly different from those of typical acute appendicitis in the following points. One difference was the thickened wall of the appendix, the other difference was the presence of air in the appendix. The patient underwent appendectomy and the pathological specimen revealed inflammatory changes of diverticula within the appendix. 展开更多
关键词 Appendlceal diverticulitis SONOGRAPHY Preoperative diagnosis
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Machine learning assisted design of γ′-strengthened Co-base superalloys with multi-performance optimization 被引量:11
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作者 Pei Liu Haiyou Huang +7 位作者 Stoichko Antonov Cheng Wen Dezhen Xue Houwen Chen Longfei Li Qiang Feng toshihiro omori Yanjing Su 《npj Computational Materials》 SCIE EI CSCD 2020年第1期1138-1146,共9页
Designing a material with multiple desired properties is a great challenge,especially in a complex material system.Here,we propose a material design strategy to simultaneously optimize multiple targeted properties of ... Designing a material with multiple desired properties is a great challenge,especially in a complex material system.Here,we propose a material design strategy to simultaneously optimize multiple targeted properties of multi-component Co-base superalloys via machine learning.The microstructural stability,γ′solvus temperature,γ′volume fraction,density,processing window,freezing range,and oxidation resistance were simultaneously optimized. 展开更多
关键词 BASE optimization STRENGTHENED
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