Total
Total的相关文献在1990年到2022年内共计857篇,主要集中在肿瘤学、自动化技术、计算机技术、内科学
等领域,其中期刊论文854篇、会议论文1篇、专利文献2篇;相关期刊303种,包括石油化工、计算机应用文摘、中国化学快报:英文版等;
相关会议1种,包括2003年全国骨关节损伤专题研讨会等;Total的相关文献由2335位作者贡献,包括王志军、raymond、Geoffrey Savage等。
Total
-研究学者
- 王志军
- raymond
- Geoffrey Savage
- Merrill A. Ritter
- Tatsuya Sueyoshi
- WANG
- Anders Troelsen
- Atul F Kamath
- Cheng Li
- Hana Badani
- John B. Meding
- Kamlesh N. Pathak
- Ke Chen
- Kenneth E. Davis
- Liel Galili
- Lin WANG
- Ming-Jong Lin
- Quanjun Cui
- Ran Hovav
- Ran Schwarzkopf
- Samwel Victor Manyele
- Satya Ranjan Sarker
- Shakil Ahmed Polash
- Sheetal P. Karia
- Shmuel Galili
- Sung Jang Chung
- Takeshi Nagai
- Tanushree Saha
- Thomas Kallemose
- 李雅丽
- 萤火虫
- A. V. Chithra
- Aharon Segev
- Alex Farris
- Alice Rotini
- Alison K Klika
- Andrii Tykhonov
- Bhallamudi Ravi
- Binay Kumar Adhikari
- Carlos A Higuera
- Chang Hyun Nam
- Darshan S. Shah
- Deepak Ramanathan
- Di Wu
- El Hadji Oumar Ndoye
- Fa Jun NAN
- Fumio Maruyama
- Grygorii Sokhrannyi
- Ha Young Park
- Henrik Husted
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摘要:
Arm宣布扩展其物联网全面解决方案 (Total Solutions for IoT) 产品路线图,新增两款全新基于Arm Cortex M和Cortex A 处理器 的解决方案, 以简化并加速物联网和嵌入式开发流程。在此次扩展的产品路线图中,Arm同时推出迄今性能最强且安全性最高的Cortex M处理器Arm Cortex M85,并将Arm虚拟硬件扩展至包括第三方设备在内的更多平台,进而使开发流程更简单流畅。
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王娟(审校);
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摘要:
{日本}大王制纸与Livedo携手开发纸尿裤回收技术大王制纸与Livedo公司合作,开发纸尿裤回收技术,将绒毛浆和其他材料重新用于生产新的纸尿裤。他们利用日本Total Care Systems公司开发的技术,从使用过的纸尿裤中分离出绒毛浆、塑料和高吸收性树脂。大王制纸自2005年以来一直在与Total Care公司合作,但早期的方法是将塑料和SAP废料用于制造燃料,将绒毛浆用于制造建筑材料。大王制纸和Livedo公司不断改进工艺,以便将这些材料用于生产纸尿裤。
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摘要:
欧莱雅集团与LanzaTech、Total合作推出可持续包装法国美容巨头欧莱雅集团(S.A.)宣布与碳回收公司LanzaTech和能源公司Total(道达尔)合作推出首个利用工业碳排放物制作的可持续包装。具体的过程是,首先Lanza Tech公司利用一种特殊的生物工艺捕获工业碳排放,并将其转化为乙醇。随后,Total利用与IFP Axens联合开发的创新脱水工艺,将乙醇转化为乙烯,再将其聚合成与化石产品具有相同技术特征的聚乙烯,最后,欧莱雅则使用这种聚乙烯生产与传统聚乙烯相同质量和性能的包装。
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刘昭青(编译)
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摘要:
日本三菱造船与法国能源巨头TotalEnergies公司进行可行性研究,以开发LCO_(2)运输船。LCO_(2)运输船在将CO_(2)从其排放源输送至储存设施供利用方面起着关键作用。CO_(2)捕获、利用和储存作为实现脱碳化的有效手段,正引起全世界的关注。三菱造船正在积极寻求LCO_(2)运输船的商业化。MHI集团通过集中三菱造船建造LPG和LNG运输船积累的先进气体处理技术,以及三菱重工工程的CO_(2)捕获技术,为构建跨越海洋和陆地的CCUS价值链作出贡献。
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韩宇(摘译)
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摘要:
法国TotalEnergies公司宣布一项为期四年的研究项目,其与Veolia公司合作,在位于La Mede的生物炼油厂种植微藻,并且从空气或者工业生产中捕获CO_(2)来生产低碳强度的生物燃料。据称,微藻可以替代传统农作物作为生产油的原料,并且是一个“碳负排放”过程。目前,La Mede生物炼油厂可生产500 kt/a优质加氢植物油。
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Bahman Zohuri;
Farahnaz Behgounia;
Ziba Zibandeh Nezam
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摘要:
In the past decade or so,AI(artificial intelligence)technology has been growing with such a mesmerizing speed that today its presence in almost any industry that deals with any huge sheer volume of data is taking advantage of AI by integrating it into their day-to-day operation.Meanwhile,seven billion people worldwide shape the world’s energy system and directly impact the fundamental drivers of energy,both renewable and non-renewable sources,to meet the demand for electricity from them.These energy sources can be reached from nature such as solar,wind,etc.,and human-made such as NPPs(nuclear power plants)in the form of either fission as an old technology since the Manhattan project and in the near future as fusion in the form of magnetic or inertial confinements.Meanwhile,AI controlling nuclear reactors are about to happen.The basic idea is to apply AI with its two subset components as ML(machine learning),and DL(deep learning)techniques to go through the mountains of data that come from a reactor,spot patterns in it,and calling them to the unit’s human attention operators is not invadable either.Designers of such nuclear reactors will combine simulation and real-world data,comparing scenarios from each to develop“confidence[in]what they can predict and what is the range of uncertainty of their prediction”.Adding that,in the end,the operator will make the final decisions in order to keep these power plants safe while they are in operation and how to secure them against cyber-attack natural or human-made disasters.In this short communication article,we would like to see how we can prove some of these concepts;then a NPP manufacturer can pick it up and use it in their designs of a new generation of these reactors.
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Shun Zhang;
Hajime Orita;
Hiroyuki Egawa;
Ryota Matsui;
Suguru Yamauchi;
Yukinori Yube;
Sanae Kaji;
Toru Takahashi;
Shinichi Oka;
Noriyuki Inaki;
Tetsu Fukunaga
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摘要:
BACKGROUND Total laparoscopic distal gastrectomy(TLDG)is increasing due to some advantages over open surgery,which has generated interest in gastrointestinal surgeons.However,TLDG is technically demanding especially for lymphadenectomy and gastrointestinal reconstruction.During the course of training,trainee surgeons have less chances to perform open gastrectomy compared with that of senior surgeons.AIM To evaluate an appropriate,efficient and safe laparoscopic training procedures suitable for trainee surgeons.METHODS Ninety-two consecutive patients with gastric cancer who underwent TLDG plus Billroth I reconstruction using an augmented rectangle technique and involving trainees were reviewed.The trainees were taught a laparoscopic view of surgical anatomy,standard operative procedures and practiced essential laparoscopic skills.The TLDG procedure was divided into regional lymph node dissections and gastrointestinal reconstruction for analyzing trainee skills.Early surgical outcomes were compared between trainees and trainers to clarify the feasibility and safety of TLDG performed by trainees.Learning curves were used to assess the utility of our training system.RESULTS Five trainees performed a total of 52 TLDGs(56.5%),while 40 TLDGs were conducted by two trainers(43.5%).Except for depth of invasion and pathologic stage,there were no differences in clinicopathological characteristics.Trainers performed more D2 gastrectomies than trainees.The total operation time was significantly longer in the trainee group.The time spent during the lesser curvature lymph node dissection and the Billroth I reconstruction were similar between the two groups.No difference was found in postoperative complications between the two groups.The learning curve of the trainees plateaued after five TLDG cases.CONCLUSION Preparing trainees with a laparoscopic view of surgical anatomy,standard operative procedures and practice in essential laparoscopic skills enabled trainees to perform TLDG safely and feasibly.
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摘要:
为了推动移动创新的进一步发展,Arm近日宣布从2022年开始,所有面向市场的Cortex A大核都将仅支持64位。这项计划作为Arm专注于“全面计算(Total Compute)”的一部分,旨在突破计算性能、安全性和优化开发者的资源访问,以打造最引人入胜和沉浸式的应用程序。系统级芯片设计的变革方法Arm在去年推出“全面计算”,目的是通过改进设计方法,以超越原始CPU的性能,并采用更全面的方式,可以根据实际用例分析改变系统设计,进而满足由移动驱动的新现实需求。
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