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人工智能英文参考文献(最新120个)

人工智能是一门新兴的具有挑战力的学科。

自人工智能诞生以来,发展迅速,产生了许多分支。

诸如强化学习、模拟环境、智能硬件、机器学习等。

但是,在当前人工智能技术迅猛发展,为人们的生活带来许多便利。

下面是搜索整理的人工智能英文参考文献的分享，供大家借鉴参考。

人工智能英文参考文献一：[1]Lars Egevad,Peter Str?m,Kimmo Kartasalo,Henrik Olsson,Hemamali Samaratunga,Brett Delahunt,Martin Eklund. The utility of artificial intelligence in the assessment of prostate pathology[J]. Histopathology,2020,76(6).[2]Rudy van Belkom. The Impact of Artificial Intelligence on the Activities ofa Futurist[J]. World Futures Review,2020,12(2).[3]Reza Hafezi. How Artificial Intelligence Can Improve Understanding in Challenging Chaotic Environments[J]. World Futures Review,2020,12(2).[4]Alejandro Díaz-Domínguez. How Futures Studies and Foresight Could Address Ethical Dilemmas of Machine Learning and Artificial Intelligence[J]. World Futures Review,2020,12(2).[5]Russell T. Warne,Jared Z. Burton. Beliefs About Human Intelligence in a Sample of Teachers and Nonteachers[J]. Journal for the Education of the Gifted,2020,43(2).[6]Russell Belk,Mariam Humayun,Ahir Gopaldas. Artificial Life[J]. Journal of Macromarketing,2020,40(2).[7]Walter Kehl,Mike Jackson,Alessandro Fergnani. Natural Language Processing and Futures Studies[J]. World Futures Review,2020,12(2).[8]Anne Boysen. Mine the Gap: Augmenting Foresight Methodologies with Data Analytics[J]. World Futures Review,2020,12(2).[9]Marco Bevolo,Filiberto Amati. The Potential Role of AI in Anticipating Futures from a Design Process Perspective: From the Reflexive Description of “Design” to a Discussion of Influences by the Inclusion of AI in the Futures Research Process[J]. World Futures Review,2020,12(2).[10]Lan Xu,Paul Tu,Qian Tang,Dan Seli?teanu. Contract Design for Cloud Logistics (CL) Based on Blockchain Technology (BT)[J]. Complexity,2020,2020.[11]L. Grant,X. Xue,Z. Vajihi,A. Azuelos,S. Rosenthal,D. Hopkins,R. Aroutiunian,B. Unger,A. Guttman,M. Afilalo. LO32: Artificial intelligence to predict disposition to improve flow in the emergency department[J]. CJEM,2020,22(S1).[12]A. Kirubarajan,A. Taher,S. Khan,S. Masood. P071: Artificial intelligence in emergency medicine: A scoping review[J]. CJEM,2020,22(S1).[13]L. Grant,P. Joo,B. Eng,A. Carrington,M. Nemnom,V. Thiruganasambandamoorthy. LO22: Risk-stratification of emergency department syncope by artificial intelligence using machine learning: human, statistics or machine[J]. CJEM,2020,22(S1).[14]Riva Giuseppe,Riva Eleonora. OS for Ind Robots: Manufacturing Robots Get Smarter Thanks to Artificial Intelligence.[J]. Cyberpsychology, behavior and social networking,2020,23(5).[15]Markus M. Obmann,Aurelio Cosentino,Joshy Cyriac,Verena Hofmann,Bram Stieltjes,Daniel T. Boll,Benjamin M. Yeh,Matthias R. Benz. Quantitative enhancement thresholds and machine learning algorithms for the evaluation of renal lesions using single-phase split-filter dual-energy CT[J]. Abdominal Radiology,2020,45(1).[16]Haytham H. Elmousalami,Mahmoud Elaskary. Drilling stuck pipe classification and mitigation in the Gulf of Suez oil fields using artificial intelligence[J]. Journal of Petroleum Exploration and Production Technology,2020,10(10).[17]Rüdiger Schulz-Wendtland,Karin Bock. Bildgebung in der Mammadiagnostik –Ein Ausblick <trans-title xml:lang="en">Imaging in breast diagnostics—an outlook [J]. Der Gyn?kologe,2020,53(6).</trans-title>[18]Nowakowski Piotr,Szwarc Krzysztof,Boryczka Urszula. Combining an artificial intelligence algorithm and a novel vehicle for sustainable e-waste collection[J]. Science of the Total Environment,2020,730.[19]Wang Huaizhi,Liu Yangyang,Zhou Bin,Li Canbing,Cao Guangzhong,Voropai Nikolai,Barakhtenko Evgeny. Taxonomy research of artificial intelligence for deterministic solar power forecasting[J]. Energy Conversion and Management,2020,214.[20]Kagemoto Hiroshi. Forecasting a water-surface wave train with artificial intelligence- A case study[J]. Ocean Engineering,2020,207.[21]Tomonori Aoki,Atsuo Yamada,Kazuharu Aoyama,Hiroaki Saito,Gota Fujisawa,Nariaki Odawara,Ryo Kondo,Akiyoshi Tsuboi,Rei Ishibashi,Ayako Nakada,Ryota Niikura,Mitsuhiro Fujishiro,Shiro Oka,Soichiro Ishihara,Tomoki Matsuda,Masato Nakahori,Shinji Tanaka,Kazuhiko Koike,Tomohiro Tada. Clinical usefulness of a deep learning‐based system as the first screening on small‐bowel capsule endoscopy reading[J]. Digestive Endoscopy,2020,32(4).[22]Masashi Fujii,Hajime Isomoto. Next generation of endoscopy: Harmony with artificial intelligence and robotic‐assisted devices[J]. Digestive Endoscopy,2020,32(4).[23]Roberto Verganti,Luca Vendraminelli,Marco Iansiti. Innovation and Design in the Age of Artificial Intelligence[J]. Journal of Product Innovation Management,2020,37(3).[24]Yuval Elbaz,David Furman,Maytal Caspary Toroker. Modeling Diffusion in Functional Materials: From Density Functional Theory to Artificial Intelligence[J]. Advanced Functional Materials,2020,30(18).[25]Dinesh Visva Gunasekeran,Tien Yin Wong. Artificial Intelligence in Ophthalmology in 2020: A Technology on the Cusp for Translation and Implementation[J]. Asia-Pacific Journal of Ophthalmology,2020,9(2).[26]Fu-Neng Jiang,Li-Jun Dai,Yong-Ding Wu,Sheng-Bang Yang,Yu-Xiang Liang,Xin Zhang,Cui-Yun Zou,Ren-Qiang He,Xiao-Ming Xu,Wei-De Zhong. The study of multiple diagnosis models of human prostate cancer based on Taylor database by artificial neural networks[J]. Journal of the Chinese Medical Association,2020,83(5).[27]Matheus Calil Faleiros,Marcello Henrique Nogueira-Barbosa,Vitor Faeda Dalto,JoséRaniery Ferreira Júnior,Ariane Priscilla Magalh?es Tenório,Rodrigo Luppino-Assad,Paulo Louzada-Junior,Rangaraj Mandayam Rangayyan,Paulo Mazzoncini de Azevedo-Marques. Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging[J]. Advances in Rheumatology,2020,60(1078).[28]Balamurugan Balakreshnan,Grant Richards,Gaurav Nanda,Huachao Mao,Ragu Athinarayanan,Joseph Zaccaria. PPE Compliance Detection using Artificial Intelligence in Learning Factories[J]. Procedia Manufacturing,2020,45.[29]M. Stévenin,V. Avisse,N. Ducarme,A. de Broca. Qui est responsable si un robot autonome vient à entra?ner un dommage ?[J]. Ethique et Santé,2020.[30]Fatemeh Barzegari Banadkooki,Mohammad Ehteram,Fatemeh Panahi,Saad Sh. Sammen,Faridah Binti Othman,Ahmed EL-Shafie. Estimation of Total Dissolved Solids (TDS) using New Hybrid Machine Learning Models[J]. Journal of Hydrology,2020.[31]Adam J. Schwartz,Henry D. Clarke,Mark J. Spangehl,Joshua S. Bingham,DavidA. Etzioni,Matthew R. Neville. Can a Convolutional Neural Network Classify Knee Osteoarthritis on Plain Radiographs as Accurately as Fellowship-Trained Knee Arthroplasty Surgeons?[J]. The Journal of Arthroplasty,2020.[32]Ivana Nizetic Kosovic,Toni Mastelic,Damir Ivankovic. Using Artificial Intelligence on environmental data from Internet of Things for estimating solar radiation: Comprehensive analysis[J]. Journal of Cleaner Production,2020.[33]Lauren Fried,Andrea Tan,Shirin Bajaj,Tracey N. Liebman,David Polsky,Jennifer A. Stein. Technological advances for the detection of melanoma: Part I. Advances in diagnostic techniques[J]. Journal of the American Academy of Dermatology,2020.[34]Mohammed Amoon,Torki Altameem,Ayman Altameem. Internet of things Sensor Assisted Security and Quality Analysis for Health Care Data Sets Using Artificial Intelligent Based Heuristic Health Management System[J]. Measurement,2020.[35]E. Lotan,C. Tschider,D.K. Sodickson,A. Caplan,M. Bruno,B. Zhang,Yvonne W. Lui. Medical Imaging and Privacy in the Era of Artificial Intelligence: Myth, Fallacy, and the Future[J]. Journal of the American College of Radiology,2020.[36]Fabien Lareyre,Cédric Adam,Marion Carrier,Juliette Raffort. Artificial Intelligence in Vascular Surgery: moving from Big Data to Smart Data[J]. Annals of Vascular Surgery,2020.[37]Ilesanmi Daniyan,Khumbulani Mpofu,Moses Oyesola,Boitumelo Ramatsetse,Adefemi Adeodu. Artificial intelligence for predictive maintenance in the railcar learning factories[J]. Procedia Manufacturing,2020,45.[38]Janet L. McCauley,Anthony E. Swartz. Reframing Telehealth[J]. Obstetrics and Gynecology Clinics of North America,2020.[39]Jean-Emmanuel Bibault,Lei Xing. Screening for chronic obstructive pulmonary disease with artificial intelligence[J]. The Lancet Digital Health,2020,2(5).[40]Andrea Laghi. Cautions about radiologic diagnosis of COVID-19 infection driven by artificial intelligence[J]. The Lancet Digital Health,2020,2(5).人工智能英文参考文献二：[41]K. Orhan,I. S. Bayrakdar,M. Ezhov,A. Kravtsov,T. ?zyürek. Evaluation of artificial intelligence for detecting periapical pathosis on cone‐beam computed tomography scans[J]. International Endodontic Journal,2020,53(5).[42]Avila A M,Mezi? I. Data-driven analysis and forecasting of highway traffic dynamics.[J]. Nature communications,2020,11(1).[43]Neri Emanuele,Miele Vittorio,Coppola Francesca,Grassi Roberto. Use of CT andartificial intelligence in suspected or COVID-19 positive patients: statement of the Italian Society of Medical and Interventional Radiology.[J]. La Radiologia medica,2020.[44]Tau Noam,Stundzia Audrius,Yasufuku Kazuhiro,Hussey Douglas,Metser Ur. Convolutional Neural Networks in Predicting Nodal and Distant Metastatic Potential of Newly Diagnosed Non-Small Cell Lung Cancer on FDG PET Images.[J]. AJR. American journal of roentgenology,2020.[45]Coppola Francesca,Faggioni Lorenzo,Regge Daniele,Giovagnoni Andrea,Golfieri Rita,Bibbolino Corrado,Miele Vittorio,Neri Emanuele,Grassi Roberto. Artificial intelligence: radiologists' expectations and opinions gleaned from a nationwide online survey.[J]. La Radiologia medica,2020.[46]?. ? ? ? ? [J]. ,2020,25(4).[47]Savage Rock H,van Assen Marly,Martin Simon S,Sahbaee Pooyan,Griffith Lewis P,Giovagnoli Dante,Sperl Jonathan I,Hopfgartner Christian,K?rgel Rainer,Schoepf U Joseph. Utilizing Artificial Intelligence to Determine Bone Mineral Density Via Chest Computed Tomography.[J]. Journal of thoracic imaging,2020,35 Suppl 1.[48]Brzezicki Maksymilian A,Bridger Nicholas E,Kobeti? Matthew D,Ostrowski Maciej,Grabowski Waldemar,Gill Simran S,Neumann Sandra. Artificial intelligence outperforms human students in conducting neurosurgical audits.[J]. Clinical neurology and neurosurgery,2020,192.[49]Lockhart Mark E,Smith Andrew D. Fatty Liver Disease: Artificial Intelligence Takes on the Challenge.[J]. Radiology,2020,295(2).[50]Wood Edward H,Korot Edward,Storey Philip P,Muscat Stephanie,Williams George A,Drenser Kimberly A. The retina revolution: signaling pathway therapies, genetic therapies, mitochondrial therapies, artificial intelligence.[J]. Current opinion in ophthalmology,2020,31(3).[51]Ho Dean,Quake Stephen R,McCabe Edward R B,Chng Wee Joo,Chow Edward K,Ding Xianting,Gelb Bruce D,Ginsburg Geoffrey S,Hassenstab Jason,Ho Chih-Ming,Mobley William C,Nolan Garry P,Rosen Steven T,Tan Patrick,Yen Yun,Zarrinpar Ali. Enabling Technologies for Personalized and Precision Medicine.[J]. Trends in biotechnology,2020,38(5).[52]Fischer Andreas M,Varga-Szemes Akos,van Assen Marly,Griffith L Parkwood,Sahbaee Pooyan,Sperl Jonathan I,Nance John W,Schoepf U Joseph. Comparison of Artificial Intelligence-Based Fully Automatic Chest CT Emphysema Quantification to Pulmonary Function Testing.[J]. AJR. American journal ofroentgenology,2020,214(5).[53]Moore William,Ko Jane,Gozansky Elliott. Artificial Intelligence Pertaining to Cardiothoracic Imaging and Patient Care: Beyond Image Interpretation.[J]. Journal of thoracic imaging,2020,35(3).[54]Hwang Eui Jin,Park Chang Min. Clinical Implementation of Deep Learning in Thoracic Radiology: Potential Applications and Challenges.[J]. Korean journal of radiology,2020,21(5).[55]Mateen Bilal A,David Anna L,Denaxas Spiros. Electronic Health Records to Predict Gestational Diabetes Risk.[J]. Trends in pharmacological sciences,2020,41(5).[56]Yao Xiang,Mao Ling,Lv Shunli,Ren Zhenghong,Li Wentao,Ren Ke. CT radiomics features as a diagnostic tool for classifying basal ganglia infarction onset time.[J]. Journal of the neurological sciences,2020,412.[57]van Assen Marly,Banerjee Imon,De Cecco Carlo N. Beyond the Artificial Intelligence Hype: What Lies Behind the Algorithms and What We Can Achieve.[J]. Journal of thoracic imaging,2020,35 Suppl 1.[58]Guzik Tomasz J,Fuster Valentin. Leaders in Cardiovascular Research: Valentin Fuster.[J]. Cardiovascular research,2020,116(6).[59]Fischer Andreas M,Eid Marwen,De Cecco Carlo N,Gulsun Mehmet A,van Assen Marly,Nance John W,Sahbaee Pooyan,De Santis Domenico,Bauer Maximilian J,Jacobs Brian E,Varga-Szemes Akos,Kabakus Ismail M,Sharma Puneet,Jackson Logan J,Schoepf U Joseph. Accuracy of an Artificial Intelligence Deep Learning Algorithm Implementing a Recurrent Neural Network With Long Short-term Memory for the Automated Detection of Calcified Plaques From Coronary Computed Tomography Angiography.[J]. Journal of thoracic imaging,2020,35 Suppl 1.[60]Ghosh Adarsh,Kandasamy Devasenathipathy. Interpretable Artificial Intelligence: Why and When.[J]. AJR. American journal of roentgenology,2020,214(5).[61]M.Rosario González-Rodríguez,M.Carmen Díaz-Fernández,Carmen Pacheco Gómez. Facial-expression recognition: An emergent approach to the measurement of tourist satisfaction through emotions[J]. Telematics and Informatics,2020,51.[62]Ru-Xi Ding,Iván Palomares,Xueqing Wang,Guo-Rui Yang,Bingsheng Liu,Yucheng Dong,Enrique Herrera-Viedma,Francisco Herrera. Large-Scale decision-making: Characterization, taxonomy, challenges and future directions from an Artificial Intelligence and applications perspective[J]. Information Fusion,2020,59.[63]Abdulrhman H. Al-Jebrni,Brendan Chwyl,Xiao Yu Wang,Alexander Wong,Bechara J. Saab. AI-enabled remote and objective quantification of stress at scale[J]. Biomedical Signal Processing and Control,2020,59.[64]Gillian Thomas,Elizabeth Eisenhauer,Robert G. Bristow,Cai Grau,Coen Hurkmans,Piet Ost,Matthias Guckenberger,Eric Deutsch,Denis Lacombe,Damien C. Weber. The European Organisation for Research and Treatment of Cancer, State of Science in radiation oncology and priorities for clinical trials meeting report[J]. European Journal of Cancer,2020,131.[65]Muhammad Asif. Are QM models aligned with Industry 4.0? A perspective on current practices[J]. Journal of Cleaner Production,2020,258.[66]Siva Teja Kakileti,Himanshu J. Madhu,Geetha Manjunath,Leonard Wee,Andre Dekker,Sudhakar Sampangi. Personalized risk prediction for breast cancer pre-screening using artificial intelligence and thermal radiomics[J]. Artificial Intelligence In Medicine,2020,105.[67]. Evaluation of Payer Budget Impact Associated with the Use of Artificial Intelligence in Vitro Diagnostic, Kidneyintelx, to Modify DKD Progression:[J]. American Journal of Kidney Diseases,2020,75(5).[68]Rohit Nishant,Mike Kennedy,Jacqueline Corbett. Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda[J]. International Journal of Information Management,2020,53.[69]Hoang Nguyen,Xuan-Nam Bui. Soft computing models for predicting blast-induced air over-pressure: A novel artificial intelligence approach[J]. Applied Soft Computing Journal,2020,92.[70]Benjamin S. Hopkins,Aditya Mazmudar,Conor Driscoll,Mark Svet,Jack Goergen,Max Kelsten,Nathan A. Shlobin,Kartik Kesavabhotla,Zachary A Smith,Nader S Dahdaleh. Using artificial intelligence (AI) to predict postoperative surgical site infection: A retrospective cohort of 4046 posterior spinal fusions[J]. Clinical Neurology and Neurosurgery,2020,192.[71]Mei Yang,Runze Zhou,Xiangjun Qiu,Xiangfei Feng,Jian Sun,Qunshan Wang,Qiufen Lu,Pengpai Zhang,Bo Liu,Wei Li,Mu Chen,Yan Zhao,Binfeng Mo,Xin Zhou,Xi Zhang,Yingxue Hua,Jin Guo,Fangfang Bi,Yajun Cao,Feng Ling,Shengming Shi,Yi-Gang Li. Artificial intelligence-assisted analysis on the association between exposure to ambient fine particulate matter and incidence of arrhythmias in outpatients of Shanghai community hospitals[J]. Environment International,2020,139.[72]Fatemehalsadat Madaeni,Rachid Lhissou,Karem Chokmani,Sebastien Raymond,Yves Gauthier. Ice jam formation, breakup and prediction methods based on hydroclimatic data using artificial intelligence: A review[J]. Cold Regions Science and Technology,2020,174.[73]Steve Chukwuebuka Arum,David Grace,Paul Daniel Mitchell. A review of wireless communication using high-altitude platforms for extended coverage and capacity[J]. Computer Communications,2020,157.[74]Yong-Hong Kuo,Nicholas B. Chan,Janny M.Y. Leung,Helen Meng,Anthony Man-Cho So,Kelvin K.F. Tsoi,Colin A. Graham. An Integrated Approach of Machine Learning and Systems Thinking for Waiting Time Prediction in an Emergency Department[J]. International Journal of Medical Informatics,2020,139.[75]Matteo Terzi,Gian Antonio Susto,Pratik Chaudhari. Directional adversarial training for cost sensitive deep learning classification applications[J]. Engineering Applications of Artificial Intelligence,2020,91.[76]Arman Kilic. Artificial Intelligence and Machine Learning in Cardiovascular Health Care[J]. The Annals of Thoracic Surgery,2020,109(5).[77]Hossein Azarmdel,Ahmad Jahanbakhshi,Seyed Saeid Mohtasebi,Alfredo Rosado Mu?oz. Evaluation of image processing technique as an expert system in mulberry fruit grading based on ripeness level using artificial neural networks (ANNs) and support vector machine (SVM)[J]. Postharvest Biology and Technology,2020,166.[78]Wafaa Wardah,Abdollah Dehzangi,Ghazaleh Taherzadeh,Mahmood A. Rashid,M.G.M. Khan,Tatsuhiko Tsunoda,Alok Sharma. Predicting protein-peptide binding sites with a deep convolutional neural network[J]. Journal of Theoretical Biology,2020,496.[79]Francisco F.X. Vasconcelos,Róger M. Sarmento,Pedro P. Rebou?as Filho,Victor Hugo C. de Albuquerque. Artificial intelligence techniques empowered edge-cloud architecture for brain CT image analysis[J]. Engineering Applications of Artificial Intelligence,2020,91.[80]Masaaki Konishi. Bioethanol production estimated from volatile compositions in hydrolysates of lignocellulosic biomass by deep learning[J]. Journal of Bioscience and Bioengineering,2020,129(6).人工智能英文参考文献三：[81]J. Kwon,K. Kim. Artificial Intelligence for Early Prediction of Pulmonary Hypertension Using Electrocardiography[J]. Journal of Heart and Lung Transplantation,2020,39(4).[82]C. Maathuis,W. Pieters,J. van den Berg. Decision support model for effects estimation and proportionality assessment for targeting in cyber operations[J]. Defence Technology,2020.[83]Samer Ellahham. Artificial Intelligence in Diabetes Care[J]. The American Journal of Medicine,2020.[84]Yi-Ting Hsieh,Lee-Ming Chuang,Yi-Der Jiang,Tien-Jyun Chang,Chung-May Yang,Chang-Hao Yang,Li-Wei Chan,Tzu-Yun Kao,Ta-Ching Chen,Hsuan-Chieh Lin,Chin-Han Tsai,Mingke Chen. Application of deep learning image assessment software VeriSee? for diabetic retinopathy screening[J]. Journal of the Formosan Medical Association,2020.[85]Emre ARTUN,Burak KULGA. Selection of candidate wells for re-fracturing in tight gas sand reservoirs using fuzzy inference[J]. 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硅烷偶联剂KH550_改性白炭黑及其在环氧树脂中的应用

硅烷偶联剂KH550改性白炭黑及其在环氧树脂中的应用赵志明，李文琼，靳朝辉，于朝生（东北林业大学化学化工与资源利用学院，东北林业大学森林植物生态学教育部重点实验室，黑龙江哈尔滨150040）摘要：利用硅烷偶联剂KH550对白炭黑纳米粉体进行表面接枝改性，并制备改性白炭黑（mSiO 2）/环氧树脂（EP ）浇铸体，利用傅里叶变换红外光谱（FTIR ）、X 射线衍射（XRD ）、粒度分析、拉伸性能测试、热重分析（TG ）、扫描电镜（SEM ）等手段对改性前后的白炭黑粒、mSiO 2/EP 浇铸体进行表征分析，探究了KH550对白炭黑的改性效果以及mSiO 2用量对浇铸体力学性能、耐热性和结构的影响。

结果表明：以异丙醇作为分散剂，当KH550质量分数为20%，反应温度为90℃，反应时间为5h ，在醇、水混合溶剂中可以实现KH550对白炭黑的表面改性；当改性白炭黑用量为8%(wt.)时，浇铸体综合性能最好，拉伸强度为41.29MPa ，较纯EP 提升了95.2%；其最大分解速率时的温度为377℃，较纯EP 提升了14℃。

关键词：KH550；白炭黑；改性；环氧树脂；拉伸强度中图分类号：TQ 127.2Study on Surface Modiﬁ cation of Silica with KH550 and Its Application in Epoxy ResinZHAO Zhi-ming, LI Wen-qiong, JIN Zhao-hui, YU Chao-sheng（ College of Chemistry, Chemical Engineering and Resource Utilization, Northeast Forestry University; Key Laboratory of ForestPlant Ecology, Ministry of Education, Northeast Forestry University, Harbin 150040, Heilongjiang, China )Abstract: The silane coupling agent KH550 was used to modify the silica by surface grafting and to prepare modiﬁ ed silica (mSiO 2)/epoxy resin (EP) casts. The silica pellets and mSiO 2/EP casts before and after modiﬁcation were characterised by means of Fourier transform infrared spectroscopy (FTIR), X-ray diﬀ raction (XRD), particle size analysis, tensile properties testing, thermogravimetric analysis (TG) and scanning electron microscopy (SEM). The eﬀ ect of KH550 on the modiﬁ cation of silica and the eﬀ ect of mSiO 2 dosage on the mechanical properties, heat resistance and structure of the cast body were investigated. The results show that the surface modiﬁ cation of silica by KH550 can be achieved in a mixed solvent of alcohol and water when the mass fraction of KH550 is 20%, the reaction temperature is 90°C and the reaction time is 5h, using isopropanol as the dispersant. Furthermore, the mechanical properties and thermal stability of the mSiO 2/EP composites were improved by the KH550 modiﬁ cation. When the amount of mSiO 2 was 8% (wt.), the tensile strength of the mSiO 2/EP composite exhibited 41.29MPa, which resulted in an increase of tensile strength by 95.2%, and a maximum decomposition rate temperature of 377°C, which is 14°C higher than that of pure EP materials.Key words: KH550; silica; modiﬁ cation; EP; tensile strength 作者简介：赵志明，硕士研究生，主要从事功能材料研究工作。

IGCS19-0405 ：产品说明书

abnormal vaginal bleeding requiring intervention had no statis-tical difference between VP and WVP patients group (p=0.3074)as other complications as well(table1).Median of related days of vaginal bleeding after the procedure were 7.4days(SD8.75)in VP group and7.34days(SD8.52)in WVP group,with no statistical difference(p=0.912). Conclusions Insert a vaginal pack or not,after LEEP,do not affect the number of postoperative gynecologic intervention due to vaginal bleeding or the amount of postoperative bleed-ing days.Previous pregnancies,hormonal status,cytology or LEEP specimen characteristics did not affect the disclosure. We also could not find any risk factor associated to abnormal bleeding.Based on that,the use of vaginal pack can be omit-ted with no further complications.IGCS19-0405382LATERALLY EXTENDED ENDOPELVIC RESECTION(LEER) AND NEOVAGINE,PATIENT WITH RECTALADENOCARCINOMA AND RECURRENCE IN CERVIX,VAGINA AND PELVIC WALL:A PURPOSE OF A CASE1J Torres*,2J Saenz,3O Suescun,3M Medina,4L Trujillo.1Especialista en entrenamiento–Universidad Militar Nueva Granada–Instituto Nacional de Cancerologia,Department of Gynecologic Oncology,Bogota D.C.,Colombia;2Especialista en entrenamiento–Universidad Militar Nueva Granada–Instituto Nacional de Cancerologia,Department of Gynecologic Oncology,Bogota D.C,Colombia;3Instituto Nacional de Cancerologia, Department of Gynecologic Oncology,Bogota D.C,Colombia;4Instituto Nacional de Cancerologia,Department of Gynecologic Oncology,Bogota D.C.,Colombia10.1136/ijgc-2019-IGCS.382Objectives Exenteration is used to treat cancers of the lower and middle female genital tract in the irradiated pelvis. Höckel described laterally extended endopelvic resection (LEER)as an approach in which the resection line extends to the pelvic side wall.Methods A49-year-old patient diagnosed with rectal adenocar-cinoma10years ago,managed with chemotherapy plus radio-therapy.T umor relapse at3years,management with low abdominoperineal resection and definitive colostomy.Second relapse4years later,compromising the posterior aspect of the coccyx and right side of the pelvis with irresecability criteria, management was decided with chemotherapy with capecita-bine,oxaliplatin and bevacizumab.New relapse at2years in the cervix,vagina and pelvic wall.Images without distance disease,type LEER management with extension of pelvic floor margins and resection of muscle pubococcygeus and right lat-eral iliococcygeus with neovagina(Singapore flap)and non-continent urinary derivation with bilateral cutaneous ureteros-tomy,achieving adequate lateral margin with curative intent. During follow-up with favorable evolution.Results LEER combines at least two procedures:total mesorec-tal excision,total mesometrial resection or total mesovesical resection.It may even require resection of the pelvic wall, internal obturator muscle,pubococcygeus,iliococcygeus,coccy-geus or internal iliac vessels.In combination with neovagina, it would offer better results in non-gynecological cancer relapses.Conclusions LEER with neovagina can be offered as a new therapy to a selected subset of patients with relapse in adja-cent gynecological organs with good oncological,functional and aesthetic results.Symptom Management–Supportive Cancer CareIGCS19-0706383PHOTOBIOMODULATION AND MANUAL LYMPHDRAINAGE FOR NIPPLE NECROSIS TREATMENT INBREAST CANCER:A CASE REPORT1J Baiocchi,2L Campanholi,3G Baiocchi*.1Oncofisio,Physical Therapy,Sao Paulo,Brazil;2CESCAGE,Physical Therapy,Ponta Grossa,Brazil;3AC Camargo Cancer Center, Gynecologic Oncology,Sao Paulo,Brazil10.1136/ijgc-2019-IGCS.383Objectives Recently,breast reconstruction after mastectomywith nipple preservation became an option of breast cancer surgery.Despite its efficacy and aesthetic superiority,the nip-ple preservation is associated with several complications in the postoperative period.The photobiomodulation therapy,for-merly known as low-intensity laser therapy,demonstrated tis-sue promotion repair by cellular repair biostimulation, angiogenesis and anti-inflammatory effects.These characteris-tics suggest a potential role for repair of chronic wounds andmay be applicable in necrosis treatment.Our aim was toreport the effects of the physiotherapeutic intervention through photobiomodulation therapy in a patient with nipple necrosis after risk reducing mastectomy.Methods We report a case of a breast cancer surgery with nip-ple necrosis treated with low-level laser therapy.The patientwas a36-year-old women who developed skin nipple necrosisin the right breast after bilateral reconstructive mastectomy.She had6sessions of low-level laser therapy.Results A female subject developed a nipple necrosis of morethan40%on the right breast after mastectomy and recon-struction.She was referred to Physical Therapy(PT)and thePT sessions were composed by manual lymph drainage,man-ual therapy for de AWS,exercises of strength and flexibility, followed by LLLT with laser660nm,2joules per point atevery1cm.Therapy was implemented for12times in total,from May2016to June2016.A re-evaluation was performed monthly from July13,2016to November2017.After18 months of follow-up,the sustained effects of LLLT were found.Conclusions Low-level laser therapy is effective for the skin cicatrization after nipple necrosis.IGCS19-0446384CONTRACEPTION AND FERTILITY COUNSELING INPATIENTS RECEIVING CHEMOTHERAPY1A Elnaggar*,2A Calfee,1LB Daily,2T Hasley,1T Tillmanns.1West Cancer Center and Research Institute,Gynecologic Oncology,Memphis,USA;2University of Tennessee Health Science Center,Obstetrics and Gynecology,Mempis,USA10.1136/ijgc-2019-IGCS.384Objectives Cancer care advances allow more patients to pursue fertility.Unfortunately,treatments may have detrimental effectson fertility and fetus should pregnancy occur.This study examines physician documentation and patient perceptions of fertility and contraception counseling. on December 24, 2023 by guest. Protected by copyright./ Int J Gynecol Cancer: first published as 10.1136/ijgc-2019-IGCS.384 on 18 September 2019. Downloaded fromMethods IRB approval obtained for a cross-sectional study of men and women,ages18–50,with newly diagnosed malig-nancy between May2017and2018.Prior sterilization,secon-dary or synchronous cancer,or prior chemotherapy were exclusionary.Consented patients received a survey regarding perception on receipt and quality of,counseling.Demographic, sexual,and social information was obtained.Differences were evaluated using chi-square tests.Results Fifty-three of179patients identified participated. Majority were women(75v25%).Patients were more likely to have perceived counseling for contraception and fertility than documented.The majority perceived counseling as suffi-cient regarding contraception and fertility.Men were more likely than women to be perceive counsel-ing regarding fertility(85v43%,p=0.010).However,both felt fertility counseling to be sufficient with similar rates of documentation.Caucasians were more likely to perceive receipt of fertility counseling(68v29%)and to perceive it to be sufficient(70v40%),then African Americans,with the same rate of documentation(35%).Conclusions Significant discrepancies in perception counsel-ing regarding contraception and fertility were seen.Gen-der and race were important factors for the perception of fertility counseling,while only race was a factor to qual-ity of perceived counseling.These differences occurred despite equal rates of physician documentation,across all groups.IGCS19-0430385WHO ARE YOU CALLING OLD?PRACTICE PATTERNS AND MANAGEMENT OF NONAGENARIANS PRESENTINGTO A GYNECOLOGIC ONCOLOGIST FOR INITIALCONSULTATIONE Ryan*,B Margolis,B Pothuri.New York University Langone Health,Obstetrics and Gynecology,New York,USA10.1136/ijgc-2019-IGCS.385Objectives T o describe the practice patterns and treatment of nonagenarians who initiated care with a gynecologic oncologist.Methods Retrospective chart review of women aged90or older who presented to a gynecologic oncologist between10/ 09and12/18at an urban academic medical center.Descrip-tive statistics utilized for variables of interest.Results We identified34nonagenarians(median age92,range 90–98):10(29%)had benign disease,8(24%)pre-malignancy or suspected malignancy,and16(47%)malignancy.Of these, 79%had age and/or functional status discussed in the care plan.Of the8with suspected malignancy,5declined further workup.The cancer distribution revealed5(31%)vulvar,5 (31%)uterine,4(25%)ovarian,1(6%)vaginal and1(6%) cervical bined,37%had stage I disease;6% stage3;6%stage4;13%recurrent;and25%unstaged.All received treatment plans:7(47%)with palliative intent and8 (53%)with curative intent.In the curative group,7under-went surgery(1adjuvant chemotherapy)and1chemotherapy/radiation.In the palliative group,4underwent radiation,1 chemotherapy and2declined/unknown.Overall,13(87%) completed the proposed treatment.T reatment-related complica-tions included1superficial skin infection and1thirty-day readmission.Conclusions Nonagenarians often presented with vulvar or endometrial cancer and87%successfully completed treatmentwith minimal adverse effects or toxicity.Age and/or functionalstatus were considered in the care plan for79%of women,but it did not preclude treatments that had the potential to preserve meaningful quality of life and/or cure patients oftheir disease.IGCS19-0646386RISK FACTORS COMPREHENSIVE GERIATRICASSESSMENT FOR EARLY DEATH IN ELDERLY PATIENTSWITH GYNECOLOGICAL CANCER.A PROSPECTIVECOHORT STUDY1J Sales*,2C Azevedo,2C santos,3L sales,4M Bezerra,5G Bezerra,4Z cavalcanti,6MJ Mello.1IMIP,Geriatric Oncology,Recife,Brazil;2IMIP,Oncology,Recife,Brazil;3FPS,Medical Course,Recife,Brazil;4IMIP,geriatric,Recife,Brazil;5HMV,oncology,caruaru,Brazil;6IMIP,post graduation,Recife,Brazil10.1136/ijgc-2019-IGCS.386Objectives T o determine risk factors for early death identifiedthe Comprehensive Geriatric Assessment(CGA)in elderly patients with gynecological cancer(EPGC).Methods Prospective cohort study.Participants with a recent diagnosis of cancer were from eight community hospitals andone cancer center in Northeast Brazil and were recruited dur-ing their first medical appointment at the outpatient oncologic clinic.A basal CGA was done before the treatment decision (ADL,Charlson Comorbidity Index-CCI,Karnofsky Perform-ance status–KPS,GDS15,IPAQ,MMSE,MNA,MNA-SF,PS,PPS,Polipharmacy,TUG).During the follow up of12 months,information about the treatments performed,the tar-geted interventions and early death was collected.Overall sur-vival was estimated using the Kaplan–Meier method,and survival curves were compared using the Log rank test for cat-egorical variables.A multivariate Cox proportional hazardsmodel was used.Results From2015–2017,84EPGC,mean age69,6±7,9;range60–96),were enrolled,25%were metastatic disease.tumor site:40,4%cervical uterine,36,9%endometrial,20,2%ovary and2,3vulva.Nine(10.7%)ECP died in less than12 months of follow-up.In our multivariate model,controlled byage,site of cancer and cancer stage,the remaining significantrisk factors were malnutrition/nonutrition determined byMNA-SF(HR3.70,95%CI1.81–5.99,p<0.001),Katz index(HR 3.60,CI 1.56–3.81,p<0.001)CCI>2(HR2,74,CI1.0.74–10.20,p=0.013)and Polipharmacy(HR2.65,CI0.71–9.81,p<0.001).Conclusions The CGA at admission identified risk factors (Nutritional risk,polypharmacy,functionality for Katz indexand comorbidity index)for premature death in EPGC.They can help to plan a personalized care. on December 24, 2023 by guest. Protected by copyright./ Int J Gynecol Cancer: first published as 10.1136/ijgc-2019-IGCS.384 on 18 September 2019. Downloaded from。

软件工程英文参考文献(优秀范文105个)

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肺部磨玻璃结节的诊治策略

肺部磨玻璃结节的诊治策略王群【摘要】肺部磨玻璃结节(ground glass nodule, GGN)是一种影像学表现,可能是肺部恶性肿瘤或良性病变.目前对于肺部磨玻璃结节的诊疗仍存在争议.2017年Fleischner协会和美国国立综合癌症网络(National Comprehensive Cancer Network, NCCN)都更新了GGN诊疗的指南,与之前的版本相比,手术或活检的指征更严,随访的间隔时间更长.临床工作中,GGN的大小、实性成分大小、动态随访变化和CT值都是判断手术介入时机的因素.GGN的诊疗中还存在一些误区:抗生素的使用、正电子发射型计算机断层显像(positron emission tomography-computed tomography, PET-CT)检查、贴近胸膜的纯GGN和进入GGN的血管都是值得注意的问题.总之,GGN是一种发展缓慢的病灶,可以安全地进行随访.%Pulmonary ground glass nodule (GGN) is a term of radiological manifestation, which may be malignant or benign. The management for pulmonary GGN remains controversial. Both Fleischner society and National Comprehensive Cancer Network (NCCN) panel updated the guideline for the management of GGN in 2017. Compared with previous ver-sions, the indication for surgery or biopsy is stricter, and the recommended follow-up interval is prolonged. In clinical practice, the size of GGN component, the size of consolidation component, dynamic change during follow-up and computed tomog-raphy (CT) value are the four factors that help surgeons to decide the timing of surgery. There are some misunderstandings for the management of GGN, such as the administration of antibiotics, the use of positron emission tomography-computed tomography (PET-CT), pure GGN adjacent to visceral pleura, and GGN with penetrating vessel. In conclusion, GGN is a kind of slowly growing lesion, which can be followed up safely.【期刊名称】《中国肺癌杂志》【年(卷),期】2018(021)003【总页数】3页(P160-162)【关键词】肺肿瘤;肺部磨玻璃结节;诊断【作者】王群【作者单位】200032 上海,复旦大学附属中山医院胸外科【正文语种】中文肺部磨玻璃结节（ground glass nodule, GGN）是指计算机断层扫描（computed tomography, CT）上边界清楚或不清楚的肺内密度增高影，其病变密度不足以掩盖其中走行的血管和支气管影。

Guideline for Structural Health Monitoring F08b

SAMCO Final Report 2006 F08b Guideline for Structural Health Monitoring
CONTENTS
1 2 3 3.1 3.1.1 3.1.1.1 3.1.1.2 3.1.2 3.1.2.1 3.1.2.2 3.1.3 3.2 3.3 3.3.1 3.3.2 3.3.2.1 3.3.2.2 3.3.2.3 3.3.2.4 3.3.2.5 3.3.2.6 3.3.2.7 3.3.2.8 3.3.2.9 3.3.3 3.3.4 3.3.5 3.3.5.1 4 4.1 4.2 4.2.1 4.2.2 4.2.3 4.2.4 4.2.4.1 4.2.4.2 4.2.4.3 4.2.5 Introduction........................................................................................ 5 Objectives and outline of the guideline............................................ 6 Analysis of actions ............................................................................ 7 Classification of actions ........................................................................7 Type of actions .........................................................................................7 Static loads.........................................................................................7 Dynamic loads....................................................................................7 Character of actions .................................................................................8 Dead loads .........................................................................................8 Live loads ...........................................................................................8 Loads and load effects .............................................................................8 Objectives and approach to action analysis ........................................8 Determination of actions based on dimension, duration and local effect .......................................................................................................9 Measurands for characterisation of actions ..............................................9 Determination of actions.........................................................................10 Monitoring pattern ............................................................................10 Wind loads .......................................................................................11 Wave loads and swell loads .............................................................11 Traffic loads......................................................................................11 Loading by displacements ................................................................12 Weight loads ....................................................................................12 Impact and collision loads; vibrations ...............................................12 Temperature loads ...........................................................................13 Effects caused by physical - chemical processes .............................13 Load combinations .................................................................................13 Use and analysis of measurement data..................................................14 Load models...........................................................................................14 Calibration of load models ................................................................15 Diagnostic of structures.................................................................. 16 Preamble ...............................................................................................16 Structural Condition Analysis .............................................................16 Description of design and construction of the structure...........................16 Determination of threshold values for position stability, serviceability and load bearing capacity.......................................................................17 Structural identification ...........................................................................18 Application of NDT techniques ...............................................................19 Steel structures ................................................................................19 Reinforced and prestressed structures .............................................19 Masonry structures...........................................................................20 Field tests...............................................................................................20

Development and Applications of CRISPR-Cas9 for Genome Engineering

Leading EdgeReviewDevelopment and Applications ofCRISPR-Cas9for Genome EngineeringPatrick D.Hsu,1,2,3Eric nder,1and Feng Zhang1,2,*1Broad Institute of MIT and Harvard,7Cambridge Center,Cambridge,MA02141,USA2McGovern Institute for Brain Research,Department of Brain and Cognitive Sciences,Department of Biological Engineering, Massachusetts Institute of Technology,Cambridge,MA02139,USA3Department of Molecular and Cellular Biology,Harvard University,Cambridge,MA02138,USA*Correspondence:zhang@/10.1016/j.cell.2014.05.010Recent advances in genome engineering technologies based on the CRISPR-associated RNA-guided endonuclease Cas9are enabling the systematic interrogation of mammalian genome function.Analogous to the search function in modern word processors,Cas9can be guided to speciﬁc locations within complex genomes by a short RNA search ing this system, DNA sequences within the endogenous genome and their functional outputs are now easily edited or modulated in virtually any organism of choice.Cas9-mediated genetic perturbation is simple and scalable,empowering researchers to elucidate the functional organization of the genome at the systems level and establish causal linkages between genetic variations and biological phenotypes. In this Review,we describe the development and applications of Cas9for a variety of research or translational applications while highlighting challenges as well as future directions.Derived from a remarkable microbial defense system,Cas9is driving innovative applications from basic biology to biotechnology and medicine.IntroductionThe development of recombinant DNA technology in the1970s marked the beginning of a new era for biology.For theﬁrst time,molecular biologists gained the ability to manipulate DNA molecules,making it possible to study genes and harness them to develop novel medicine and biotechnology.Recent advances in genome engineering technologies are sparking a new revolution in biological research.Rather than studying DNA taken out of the context of the genome,researchers can now directly edit or modulate the function of DNA sequences in their endogenous context in virtually any organism of choice, enabling them to elucidate the functional organization of the genome at the systems level,as well as identify causal genetic variations.Broadly speaking,genome engineering refers to the process of making targeted modiﬁcations to the genome,its contexts (e.g.,epigenetic marks),or its outputs(e.g.,transcripts).The ability to do so easily and efﬁciently in eukaryotic and especially mammalian cells holds immense promise to transform basic sci-ence,biotechnology,and medicine(Figure1).For life sciences research,technologies that can delete,insert, and modify the DNA sequences of cells or organisms enable dis-secting the function of speciﬁc genes and regulatory elements. Multiplexed editing could further allow the interrogation of gene or protein networks at a larger scale.Similarly,manipu-lating transcriptional regulation or chromatin states at particular loci can reveal how genetic material is organized and utilized within a cell,illuminating relationships between the architecture of the genome and its functions.In biotechnology,precise manipulation of genetic building blocks and regulatory machin-ery also facilitates the reverse engineering or reconstruction of useful biological systems,for example,by enhancing biofuel production pathways in industrially relevant organisms or by creating infection-resistant crops.Additionally,genome engi-neering is stimulating a new generation of drug development processes and medical therapeutics.Perturbation of multiple genes simultaneously could model the additive effects that un-derlie complex polygenic disorders,leading to new drug targets, while genome editing could directly correct harmful mutations in the context of human gene therapy(Tebas et al.,2014). Eukaryotic genomes contain billions of DNA bases and are difﬁcult to manipulate.One of the breakthroughs in genome manipulation has been the development of gene targeting by homologous recombination(HR),which integrates exogenous repair templates that contain sequence homology to the donor site(Figure2A)(Capecchi,1989).HR-mediated targeting has facilitated the generation of knockin and knockout animal models via manipulation of germline competent stem cells, dramatically advancing many areas of biological research.How-ever,although HR-mediated gene targeting produces highly pre-cise alterations,the desired recombination events occur extremely infrequently(1in106–109cells)(Capecchi,1989),pre-senting enormous challenges for large-scale applications of gene-targeting experiments.To overcome these challenges,a series of programmable nuclease-based genome editing technologies havebeen1262Cell157,June5,2014ª2014Elsevier Inc.developed in recent years,enabling targeted and efﬁcient modi-ﬁcation of a variety of eukaryotic and particularly mammalian species.Of the current generation of genome editing technolo-gies,the most rapidly developing is the class of RNA-guided endonucleases known as Cas9from the microbial adaptive im-mune system CRISPR (clustered regularly interspaced short palindromic repeats),which can be easily targeted to virtually any genomic location of choice by a short RNA guide.Here,we review the development and applications of the CRISPR-associated endonuclease Cas9as a platform technology for achieving targeted perturbation of endogenous genomic ele-ments and also discuss challenges and future avenues for inno-vation.Programmable Nucleases as Tools for Efﬁcient and Precise Genome EditingA series of studies by Haber and Jasin (Rudin et al.,1989;Plessis et al.,1992;Rouet et al.,1994;Choulika et al.,1995;Bibikova et al.,2001;Bibikova et al.,2003)led to the realization that tar-geted DNA double-strand breaks (DSBs)could greatly stimulate genome editing through HR-mediated recombination events.Subsequently,Carroll and Chandrasegaran demonstrated the potential of designer nucleases based on zinc ﬁnger proteins for efﬁcient,locus-speciﬁc HR (Bibikova et al.,2001,2003).Moreover,it was shown in the absence of an exogenous homol-ogy repair template that localized DSBs can induce insertions or deletion mutations (indels)via the error-prone nonhomologous end-joining (NHEJ)repair pathway (Figure 2A)(Bibikova et al.,2002).These early genome editing studies established DSB-induced HR and NHEJ as powerful pathways for the versatileand precise modiﬁcation of eukaryotic genomes.To achieve effective genome editing via introduction of site-speciﬁc DNA DSBs,four major classes of customizable DNA-binding proteins have been engineered so far:meganucleases derived from microbial mobile genetic elements (Smith et al.,2006),zinc ﬁnger (ZF)nucleases based on eukaryotic transcrip-tion factors (Urnov et al.,2005;Miller et al.,2007),transcription activator-like effectors (TALEs)from Xanthomonas bacteria (Christian et al.,2010;Miller et al.,2011;Boch et al.,2009;Mos-cou and Bogdanove,2009),and most recently the RNA-guided DNA endonuclease Cas9from the type II bacterial adaptive im-mune system CRISPR (Cong et al.,2013;Mali et al.,2013a ).Meganuclease,ZF,and TALE proteins all recognize speciﬁc DNA sequences through protein-DNA interactions.Although meganucleases integrate its nuclease and DNA-binding domains,ZF and TALE proteins consist of individual modules targeting 3or 1nucleotides (nt)of DNA,respectively (Figure 2B).ZFs and TALEs can be assembled in desired combi-nations and attached to the nuclease domain of FokI to direct nucleolytic activity toward speciﬁc genomic loci.Each of these platforms,however,has unique limitations.Meganucleases have not been widely adopted as a genome engineering platform due to lack of clear correspondence between meganuclease protein residues and their target DNA sequence speciﬁcity.ZF domains,on the other hand,exhibit context-dependent binding preference due to crosstalk between adjacent modules when assembled into a larger array (Maeder et al.,2008).Although multiple strategies have been developed to account for these limitations (Gonzaelz et al.,2010;Sander et al.,2011),assembly of functional ZFPs with the desired DNA binding speciﬁcity remains a major challenge that requires an extensive screening process.Similarly,although TALE DNA-binding monomers are for the most part modular,they can still suffer from context-dependent speciﬁcity (Juillerat et al.,2014),and their repetitive sequences render construction of novel TALE arrays labor intensive and costly.Given the challenges associated with engineering of modular DNA-binding proteins,new modes of recognition would signiﬁ-cantly simplify the development of custom nucleases.The CRISPR nuclease Cas9is targeted by a short guide RNA that recognizes the target DNA via Watson-Crick base pairing (Figure 2C).The guide sequence within these CRISPR RNAs typically corresponds to phage sequences,constituting the nat-ural mechanism for CRISPR antiviral defense,but can be easily replaced by a sequence of interest to retarget the Cas9nuclease.Multiplexed targeting by Cas9can now be achieved at unprecedented scale by introducing a battery of short guideFigure 1.Applications of Genome EngineeringGenetic and epigenetic control of cells with genome engineering technologies is enabling a broad range of applications from basic biology to biotechnology and medicine.(Clockwise from top)Causal genetic mutations or epigenetic variants associated with altered biological function or disease phenotypes can now be rapidly and efﬁciently recapitulated in animal or cellular models (Animal models,Genetic variation).Manipulating biological circuits could also facilitate the generation of useful synthetic materials,such as algae-derived,silica-based diatoms for oral drug delivery (Materials).Additionally,precise genetic engineering of important agricultural crops could confer resistance to envi-ronmental deprivation or pathogenic infection,improving food security while avoiding the introduction of foreign DNA (Food).Sustainable and cost-effec-tive biofuels are attractive sources for renewable energy,which could be achieved by creating efﬁcient metabolic pathways for ethanol production in algae or corn (Fuel).Direct in vivo correction of genetic or epigenetic defects in somatic tissue would be permanent genetic solutions that address the root cause of genetically encoded disorders (Gene surgery).Finally,engineering cells to optimize high yield generation of drug precursors in bacterial factories could signiﬁcantly reduce the cost and accessibility of useful therapeutics (Drug development).Cell 157,June 5,2014ª2014Elsevier Inc.1263RNAs rather than a library of large,bulky proteins.The ease of Cas9targeting,its high efﬁciency as a site-speciﬁc nuclease,and the possibility for highly multiplexed modiﬁcations have opened up a broad range of biological applications across basic research to biotechnology and medicine.The utility of customizable DNA-binding domains extends far beyond genome editing with site-speciﬁc endonucleases.Fusing them to modular,sequence-agnostic functional effector domains allows ﬂexible recruitment of desired perturbations,such as transcriptional activation,to a locus of interest (Xu and Bestor,1997;Beerli et al.,2000a;Konermann et al.,2013;Maeder et al.,2013a;Mendenhall et al.,2013).In fact,any modular enzymatic component can,in principle,be substituted,allowing facile additions to the genome engineering toolbox.Integration of genome-and epigenome-modifying enzymes with inducible protein regulation further allows precise temporal control of dynamic processes (Beerli et al.,2000b;Konermann et al.,2013).CRISPR-Cas9:From Yogurt to Genome EditingThe recent development of the Cas9endonuclease for genome editing draws upon more than a decade of basic research into understanding the biological function of the mysterious repetitive elements now known as CRISPR (Figure 3),which are found throughout the bacterial and archaeal diversity.CRISPR loci typically consist of a clustered set of CRISPR-associated (Cas)genes and the signature CRISPR array—a series of repeat sequences (direct repeats)interspaced by variable sequences (spacers)corresponding to sequences within foreign genetic elements (protospacers)(Figure 4).Whereas Cas genes are translated into proteins,most CRISPR arrays are ﬁrst tran-scribed as a single RNA before subsequent processing into shorter CRISPR RNAs (crRNAs),which direct the nucleolytic activity of certain Cas enzymes to degrade target nucleic acids.The CRISPR story began in 1987.While studying the iap enzyme involved in isozyme conversion of alkaline phosphatase in E.coli ,Nakata and colleagues reported a curious set of 29nt repeats downstream of the iap gene (Ishino et al.,1987).Unlike most repetitive elements,which typically take the form of tandem repeats like TALE repeat monomers,these 29nt repeats were interspaced by ﬁve intervening 32nt nonrepetitive sequences.Over the next 10years,as more microbial genomes were sequenced,additional repeat elements were reported from genomes of different bacterial and archaeal strains.Mojica and colleagues eventually classiﬁed interspaced repeat sequences as a unique family of clustered repeat elements present in >40%of sequenced bacteria and 90%of archaea (Mojica et al.,2000).These early ﬁndings began to stimulate interest in such micro-bial repeat elements.By 2002,Jansen and Mojica coined the acronym CRISPR to unify the description of microbial genomic loci consisting of an interspaced repeat array (Jansen et al.,2002;Barrangou and van der Oost,2013).At the same time,several clusters of signature CRISPR-associated (cas )genes were identiﬁed to be well conserved and typically adjacent to the repeat elements (Jansen et al.,2002),serving as a basis for the eventual classiﬁcation of three different types of CRISPR systems (types I–III)(Haft et al.,2005;Makarova et al.,2011b ).Types I and III CRISPR loci contain multiple Cas proteins,now known to form complexes with crRNA (CASCADE complex for type I;Cmr or Csm RAMP complexes for type III)to facilitate the recognition and destruction of target nucleic acids (BrounsFigure 2.Genome Editing Technologies Exploit Endogenous DNA Repair Machinery(A)DNA double-strand breaks (DSBs)are typically repaired by nonhomologous end-joining (NHEJ)or homology-directed repair (HDR).In the error-prone NHEJ pathway,Ku heterodimers bind to DSB ends and serve as a molecular scaffold for associated repair proteins.Indels are introduced when the complementary strands undergo end resection and misaligned repair due to micro-homology,eventually leading to frameshift muta-tions and gene knockout.Alternatively,Rad51proteins may bind DSB ends during the initial phase of HDR,recruiting accessory factors that direct genomic recombination with homology arms on an exogenous repair template.Bypassing the matching sister chromatid facilitates the introduction of precise gene modiﬁcations.(B)Zinc ﬁnger (ZF)proteins and transcription activator-like effectors (TALEs)are naturally occurring DNA-binding domains that can be modularly assembled to target speciﬁc se-quences.ZF and TALE domains each recognize 3and 1bp of DNA,respectively.Such DNA-binding proteins can be fused to the FokI endonuclease to generate programmable site-speciﬁc nucleases.(C)The Cas9nuclease from the microbial CRISPR adaptive immune system is localized to speciﬁc DNA sequences via the guide sequence on its guide RNA (red),directly base-pairing with the DNA target.Binding of a protospacer-adjacent motif (PAM,blue)downstream of the target locus helps to direct Cas9-mediated DSBs.1264Cell 157,June 5,2014ª2014Elsevier Inc.et al.,2008;Hale et al.,2009)(Figure 4).In contrast,the type II system has a signiﬁcantly reduced number of Cas proteins.However,despite increasingly detailed mapping and annotation of CRISPR loci across many microbial species,their biological signiﬁcance remained elusive.A key turning point came in 2005,when systematic analysis of the spacer sequences separating the individual direct repeats suggested their extrachromosomal and phage-associated ori-gins (Mojica et al.,2005;Pourcel et al.,2005;Bolotin et al.,2005).This insight was tremendously exciting,especially given previous studies showing that CRISPR loci are transcribed (Tang et al.,2002)and that viruses are unable to infect archaeal cells carrying spacers corresponding to their own genomes (Mojica et al.,2005).Together,these ﬁndings led to the specula-tion that CRISPR arrays serve as an immune memory and defense mechanism,and individual spacers facilitate defense against bacteriophage infection by exploiting Watson-Crick base-pairing between nucleic acids (Mojica et al.,2005;Pourcel et al.,2005).Despite these compelling realizations that CRISPR loci might be involved in microbial immunity,the speciﬁc mech-anism of how the spacers act to mediate viral defense remained a challenging puzzle.Several hypotheses were raised,including thoughts that CRISPR spacers act as small RNA guides to degrade viral transcripts in a RNAi-like mechanism (Makarova et al.,2006)or that CRISPR spacers direct Cas enzymes to cleave viral DNA at spacer-matching regions (Bolotin et al.,2005).Working with the dairy production bacterial strain Strepto-coccus thermophilus at the food ingredient company Danisco,Horvath and colleagues uncovered the ﬁrst experimental evidence for the natural role of a type II CRISPR system as an adaptive immunity system,demonstrating a nucleic-acid-based immune system in which CRISPR spacers dictate target speci-ﬁcity while Cas enzymes control spacer acquisition and phage defense (Barrangou et al.,2007).A rapid series of studies illumi-nating the mechanisms of CRISPR defense followed shortly and helped to establish the mechanism as well as function of all three types of CRISPR loci in adaptive immunity.By studying the type I CRISPR locus of Escherichia coli ,van der Oost and colleagues showed that CRISPR arrays are transcribed and converted into small crRNAs containing individual spacers to guide Cas nuclease activity (Brouns et al.,2008).In the same year,CRISPR-mediated defense by a type III-A CRISPR system from Staphylococcus epidermidis was demonstrated to block plasmid conjugation,establishing the target of Cas enzyme activity as DNA rather than RNA (Marrafﬁni andSontheimer,Figure 3.Key Studies Characterizing and Engineering CRISPR SystemsCas9has also been referred to as Cas5,Csx12,and Csn1in literature prior to 2012.For clarity,we exclusively adopt the Cas9nomenclature throughout this Review.CRISPR,clustered regularly interspaced short palindromic repeats;Cas,CRISPR-associated;crRNA,CRISPR RNA;DSB,double-strand break;tracrRNA,trans -activating CRISPR RNA.Cell 157,June 5,2014ª2014Elsevier Inc.12652008),although later investigation of a different type III-B system from Pyrococcus furiosus also revealed crRNA-directed RNA cleavage activity(Hale et al.,2009,2012).As the pace of CRISPR research accelerated,researchers quickly unraveled many details of each type of CRISPR system (Figure4).Building on an earlier speculation that protospacer-adjacent motifs(PAMs)may direct the type II Cas9nuclease to cleave DNA(Bolotin et al.,2005),Moineau and colleagues high-lighted the importance of PAM sequences by demonstrating that PAM mutations in phage genomes circumvented CRISPR inter-ference(Deveau et al.,2008).Additionally,for types I and II,the lack of PAM within the direct repeat sequence within the CRISPR array prevents self-targeting by the CRISPR system.In type III systems,however,mismatches between the50end of the crRNA and the DNA target are required for plasmid interference(Marraf-ﬁni and Sontheimer,2010).By2010,just3years after theﬁrst experimental evidence for CRISPR in bacterial immunity,the basic function and mecha-nisms of CRISPR systems were becoming clear.A variety of groups had begun to harness the natural CRISPR system for various biotechnological applications,including the generation of phage-resistant dairy cultures(Quiberoni et al.,2010)and phylogenetic classiﬁcation of bacterial strains(Horvath et al., 2008,2009).However,genome editing applications had not yet been explored.Around this time,two studies characterizing the functional mechanisms of the native type II CRISPR system elucidated the basic components that proved vital for engineering a simple RNA-programmable DNA endonuclease for genome editing. First,Moineau and colleagues used genetic studies in Strepto-coccus thermophilus to reveal that Cas9(formerly called Cas5,Csn1,or Csx12)is the only enzyme within the cas gene cluster that mediates target DNA cleavage(Garneau et al.,2010).Next,Charpentier and colleagues revealed a key component in the biogenesis and processing of crRNA in type II CRISPR systems—a noncoding trans-activating crRNA(tracrRNA)that hybridizes with crRNA to facilitate RNA-guided targeting of Cas9(Deltcheva et al.,2011).This dual RNA hybrid,together with Cas9and endogenous RNase III,is required for processing the CRISPR array transcript into mature crRNAs(Deltcheva et al.,2011).These two studies suggested that there are at least three components(Cas9, the mature crRNA,and tracrRNA)that are essential for recon-stituting the type II CRISPR nuclease system.Given the increasing importance of programmable site-speciﬁc nucleases based on ZFs and TALEs for enhancing eukaryotic genome editing,it was tantalizing to think that perhaps Cas9could be developed into an RNA-guided genome editing system. From this point,the race to harness Cas9for genome editing wason.Figure4.Natural Mechanisms of Microbial CRISPR Systems in Adaptive Immunity Following invasion of the cell by foreign genetic elements from bacteriophages or plasmids(step 1:phage infection),certain CRISPR-associated (Cas)enzymes acquire spacers from the exoge-nous protospacer sequences and install them into the CRISPR locus within the prokaryotic genome (step2:spacer acquisition).These spacers are segregated between direct repeats that allow the CRISPR system to mediate self and nonself recognition.The CRISPR array is a noncoding RNA transcript that is enzymatically maturated through distinct pathways that are unique to each type of CRISPR system(step3:crRNA biogenesis and processing).In types I and III CRISPR,the pre-crRNA transcript is cleaved within the repeats by CRISPR-asso-ciated ribonucleases,releasing multiple small crRNAs.Type III crRNA intermediates are further processed at the30end by yet-to-be-identiﬁed RNases to produce the fully mature transcript.In type II CRISPR,an associated trans-activating CRISPR RNA(tracrRNA)hybridizes with the direct repeats,forming an RNA duplex that is cleaved and processed by endogenous RNase III and other unknown nucleases.Maturated crRNAs from type I and III CRISPR systems are then loaded onto effector protein complexes for target recognition and degradation.In type II systems, crRNA-tracrRNA hybrids complex with Cas9to mediate interference.Both type I and III CRISPR systems use multi-protein interference modules to facilitate target recognition.In type I CRISPR,the Cascade com-plex is loaded with a crRNA molecule,constituting a catalytically inert surveillance complex that rec-ognizes target DNA.The Cas3nuclease is then recruited to the Cascade-bound R loop,mediatingtarget degradation.In type III CRISPR,crRNAs associate either with Csm or Cmr complexes that bind and cleave DNA and RNA substrates,respectively.In contrast,the type II system requires only the Cas9nuclease to degrade DNA matching its dual guide RNA consisting of a crRNA-tracrRNA hybrid.1266Cell157,June5,2014ª2014Elsevier Inc.In2011,Siksnys and colleaguesﬁrst demonstrated that the type II CRISPR system is transferrable,in that transplantation of the type II CRISPR locus from Streptococcus thermophilus into Escherichia coli is able to reconstitute CRISPR interference in a different bacterial strain(Sapranauskas et al.,2011).By 2012,biochemical characterizations by the groups of Charpent-ier,Doudna,and Siksnys showed that puriﬁed Cas9from Strep-tococcus thermophilus or Streptococcus pyogenes can be guided by crRNAs to cleave target DNA in vitro(Jinek et al., 2012;Gasiunas et al.,2012),in agreement with previous bacte-rial studies(Garneau et al.,2010;Deltcheva et al.,2011;Sapra-nauskas et al.,2011).Furthermore,a single guide RNA(sgRNA) can be constructed by fusing a crRNA containing the targeting guide sequence to a tracrRNA that facilitates DNA cleavage by Cas9in vitro(Jinek et al.,2012).In2013,a pair of studies simultaneously showed how to suc-cessfully engineer type II CRISPR systems from Streptococcus thermophilus(Cong et al.,2013)and Streptococcus pyogenes (Cong et al.,2013;Mali et al.,2013a)to accomplish genome editing in mammalian cells.Heterologous expression of mature crRNA-tracrRNA hybrids(Cong et al.,2013)as well as sgRNAs (Cong et al.,2013;Mali et al.,2013a)directs Cas9cleavage within the mammalian cellular genome to stimulate NHEJ or HDR-mediated genome editing.Multiple guide RNAs can also be used to target several genes at once.Since these initial studies,Cas9has been used by thousands of laboratories for genome editing applications in a variety of experimental model systems(Sander and Joung,2014).The rapid adoption of the Cas9technology was also greatly accelerated through a com-bination of open-source distributors such as Addgene,as well as a number of online user forums such as http://www. and . Structural Organization and Domain Architecture ofCas9The family of Cas9proteins is characterized by two signature nuclease domains,RuvC and HNH,each named based on homology to known nuclease domain structures(Figure2C). Though HNH is a single nuclease domain,the full RuvC domain is divided into three subdomains across the linear protein sequence,with RuvC I near the N-terminal region of Cas9and RuvC II/IIIﬂanking the HNH domain near the middle of the pro-tein.Recently,a pair of structural studies shed light on the struc-tural mechanism of RNA-guided DNA cleavage by Cas9. First,single-particle EM reconstructions of the Streptococcus pyogenes Cas9(SpCas9)revealed a large structural rearrange-ment between apo-Cas9unbound to nucleic acid and Cas9in complex with crRNA and tracrRNA,forming a central channel to accommodate the RNA-DNA heteroduplex(Jinek et al., 2014).Second,a high-resolution structure of SpCas9in complex with sgRNA and the complementary strand of target DNA further revealed the domain organization to comprise of an a-helical recognition(REC)lobe and a nuclease(NUC)lobe consisting of the HNH domain,assembled RuvC subdomains,and a PAM-interacting(PI)C-terminal region(Nishimasu et al.,2014) (Figure5A and Movie S1).Together,these two studies support the model that SpCas9 unbound to target DNA or guide RNA exhibits an autoinhibited conformation in which the HNH domain active site is blocked by the RuvC domain and is positioned away from the REC lobe (Jinek et al.,2014).Binding of the RNA-DNA heteroduplex would additionally be sterically inhibited by the orientation of the C-ter-minal domain.As a result,apo-Cas9likely cannot bind nor cleave target DNA.Like many ribonucleoprotein complexes,the guide RNA serves as a scaffold around which Cas9can fold and orga-nize its various domains(Nishimasu et al.,2014).The crystal structure of SpCas9in complex with an sgRNA and target DNA also revealed how the REC lobe facilitates target binding.An arginine-rich bridge helix(BH)within the REC lobe is responsible for contacting the308–12nt of the RNA-DNA het-eroduplex(Nishimasu et al.,2014),which correspond with the seed sequence identiﬁed through guide sequence mutation ex-periments(Jinek et al.,2012;Cong et al.,2013;Fu et al.,2013; Hsu et al.,2013;Pattanayak et al.,2013;Mali et al.,2013b). The SpCas9structure also provides a useful scaffold for engi-neering or refactoring of Cas9and sgRNA.Because the REC2 domain of SpCas9is poorly conserved in shorter orthologs, domain recombination or truncation is a promising approach for minimizing Cas9size.SpCas9mutants lacking REC2retain roughly50%of wild-type cleavage activity,which could be partly attributed to their weaker expression levels(Nishimasu et al., 2014).Introducing combinations of orthologous domain re-combination,truncation,and peptide linkers could facilitate the generation of a suite of Cas9mutant variants optimized for different parameters such as DNA binding,DNA cleavage,or overall protein size.Metagenomic,Structural,and Functional Diversity of Cas9Cas9is exclusively associated with the type II CRISPR locus and serves as the signature type II gene.Based on the diversity of associated Cas genes,type II CRISPR loci are further subdivided into three subtypes(IIA–IIC)(Figure5B)(Makarova et al.,2011a; Chylinski et al.,2013).Type II CRISPR loci mostly consist of the cas9,cas1,and cas2genes,as well as a CRISPR array and tracrRNA.Type IIC CRISPR systems contain only this minimal set of cas genes,whereas types IIA and IIB have an additional signature csn2or cas4gene,respectively(Chylinski et al.,2013). Subtype classiﬁcation of type II CRISPR loci is based on the architecture and organization of each CRISPR locus.For example,type IIA and IIB loci usually consist of four cas genes, whereas type IIC loci only contain three cas genes.However, this classiﬁcation does not reﬂect the structural diversity of Cas9proteins,which exhibit sequence homology and length variability irrespective of the subtype classiﬁcation of their parental CRISPR locus.Of>1,000Cas9nucleases identiﬁed from sequence databases(UniProt)based on homology,protein length is rather heterogeneous,roughly ranging from900to1600 amino acids(Figure5C).The length distribution of most Cas9 proteins can be divided into two populations centered around 1,100and1,350amino acids in length.It is worth noting that a third population of large Cas9proteins belonging to subtype IIA,formerly called Csx12,typically contain around1500amino acids.Despite the apparent diversity of protein length,all Cas9pro-teins share similar domain architecture(Makarova et al.,2011a;Cell157,June5,2014ª2014Elsevier Inc.1267。

机器人辅助腹腔镜与传统腹腔镜行结直肠癌手术的安全性和有效性比较

李书原，楼征，张卫
（海军军医大学第一附属医院肛肠外科上海 200433）
摘要结直肠癌是最常见的消化道恶性肿瘤之一，严重威胁着患者的身体健康。外科手术是治疗结直肠癌的有效方法。目前，微创手术因创伤小、恢复快等优点，成为许多患者的首选。传统腹腔镜手术在技术上存在一定的难度，它需要外科医生拥有丰富的腹腔镜操作经验。而达芬奇机器人拥有高清的 3D 镜头、灵活的机械臂以及更符合人体工程学的操作方式，在设计上优于腹腔镜。但多项研究结果显示，机器人结直肠手术的围手术期结果、远期结果与传统腹腔镜相比未见明显优势，而费用却明显增加。目前，机器人结直肠手术已被证实是安全可行的，其便于进行体内肠吻合，并可以缩短学习曲线。达芬奇机器人可在手术空间狭小、解剖复杂的盆腔内操作。在面对内脏肥胖、骨盆狭窄、低位肿瘤等病例时，它的视觉系统也有助于辨识解剖层次，更好的保留盆腔自主神经，可能会促进泌尿与性功能的术后恢复。随着各领域的新技术不断发展和融合，以及外科医生机器人手术经验的积累，相信机器人手术在未来会拥有更广阔的应用前景。
使用 PubMed 数据库搜索 2015 年至 2020 年 4 月期间的“robotic”、“robot”“laparoscopic”、 “robot-assisted”、“colorectal”、“colonel”、 “rectal”等术语。文章的参考部分也被搜索并添加到相关研究。因为机器人手术是相对较新源自的技术，所以多中心随机研究的数量有限。
虽然机器人结肠癌手术已经在多个国家和地区广泛开展，但是缺乏有力的临床证据。本文通过收录的 10 篇高质量文献来探讨机器人在结肠癌手术中的安全性及有效性（见表 1）[13-22]。
2.1 术中和围手术期效果
部分研究表明，机器人辅助腹腔镜行结肠

IDEXX 4Dx

Screening for vector-borne disease IDEXX 4Dx® Plus Test clinical reference guideWith the IDEXX 4Dx ® Plus T est, a positive result can also be an indication of ticks and and the pathogens they carry. Know more with every resultdetect antibodies to these pathogens When you use the IDEXX 4Dx Plus T est as a screening tool, you maycarried by these ticks Anaplasmaphagocytophilum Borrelia burgdorferi (Lyme disease)Ehrlichia ewingiiEhrlichia canis Anaplasma platysBabesia spp.Rocky Mountain spotted feverEhrlichia chaffeensis TularemiaRocky Mountain spotted fever STARIBartonella spp.Babesia spp.Ehrlichia canis Brown dog tickRhipicephalus sanguineusAmerican dog tickDermacentor variabilisBlack-legged tick (deer tick)Ixodes scapularis Ixodes pacificusLone star tickAmblyomma americanumRocky Mountain spotted fever TularemiaGeographic tickdistribution as of 20213that may also transmit other pathogens and infections to dogs and peopleLyme diseasebacterium Borrelia burgdorferi cases that have mild to severe disease.* S erology is typically used to diagnose Lyme disease. B. burgdorferi Did you know?•D ogs testing positive for antibodies to the C 6 peptide had 43% increased risk of having chronic kidney disease (CKD) compared to seronegative dogs.4• T he C 6 peptide used in the IDEXX 4Dx ® Plus Test and Lyme Quant C 6® Antibody Test does not cross-react with the antibody response to commercially available Lyme vaccines.5 • D ogs with seroreactivity to both B. burgdorferi and Anaplasma phagocytophilum may have two times the risk of developing clinical illness than singularly infected dogs.2Borrelia burgdorferiPrimary vectorsIxodes scapularis or Ixodes pacificus Black-legged tick (deer tick)Pathology• Localizes in tissues of infected dogs • Synovitis (may be subclinical) • Lyme nephritisClinical presentationChronic infection with clinical signs that may present acutely:• Fever, anorexia• Polyarthritis, lameness• Rapidly progressive renal failure • Neurologic syndromesLaboratory abnormalities• Elevated C 6 antibody level ≥ 30 U/mL • May have proteinuria• M ay have IDEXX SDMA ® T est result > 14 µg/dLCKD monitoring• Chemistry panel with SDMA – R ecommended to evaluate forthe development of protein-losing kidney disease• Urinalysis with Reflex UPC – R ecommended to evaluate forproteinuria • CBC with blood film evaluation – R ecommended as part of aminimum databaseHeartworm diseaseDirofilaria immitis, the causative agent of heartworm disease, is transmitted when mosquitoes infected with D. immitis larvae feed on (or bite) a healthy dog. Heartworm disease has subtle or mild clinical signs in the early stages, making preventive measures so much more important—especially as advanced infection may result in death.Did you know?•D espite availability of monthly preventives, prevalence rates of canine heartworm have remained consistent nationwide.7•T he American Heartworm Society (AHS) and the Companion Animal Parasite Council (CAPC) recommend testing all dogs for both antigen and microfilariae annually.7,8•F or more information and current recommendations on treating canine heartworm disease, goto or . Dirofilaria immitisPrimary vectorMosquitoPathologyInfective larvae (L3) mature to adult worms in the heart and pulmonary arteriesClinical presentation Asymptomatic at first, later developing:• Mild, persistent cough• Lethargy• Exercise intolerance• Reduced appetite• Weight lossLaboratory abnormalities that may be seen • Eosinophilia• Azotemia• Increased liver enzymes• ProteinuriaAnaplasmaphagocytophilumAnaplasma platysPrimary vectorsIxodes scapularis Ixodes pacificusBlack-legged tick (deer tick)Rhipicephalus sanguineus (brown dog tick)PathologyInfects neutrophilsInfects plateletsClinical presentationCan present acutely:• F ever • Anorexia • Lethargy• Polyarthritis, lameness • Neurologic signsUsually minimal clinical signs, but some dogs may have:• F ever • Uveitis• Petechiae and ecchymoses • EpistaxisLaboratory abnormalities• Thrombocytopenia• Anemia• Lymphopenia• Increased liver enzymesOther findings may be seen:• Decreased albumin • Increased globulin• Increased ALP and ALT • Proteinuria• Decreased Urine SG • Increased UPC NotePrevious infection may not prevent reinfection and persistent infections are possible.9,10Canine anaplasmosisCanine granulocytic anaplasmosis is caused by the bacterium Anaplasma phagocytophilum (transmitted by the black-legged tick [deer tick]). Anaplasma platys (transmitted by the brown dog tick) is the cause of infectious cyclic thrombocytopenia.Did you know?•M any mammalian species, including humans, are susceptible to A. phagocytophilum infection. •D ogs coinfected with Anaplasma and other bacterial pathogens may have more complex disease presentations and respond more slowly to therapy.• A .platys infects canine platelets and is frequently seen as a coinfection with Ehrlichia canis .Canine ehrlichiosisCanine ehrlichiosis is caused by the bacteria Ehrlichia canis (transmitted by the brown dog tick) and Ehrlichia ewingii (transmitted by the lone star tick). Canine Ehrlichia infections may progress to the subclinical phase or may become chronic infections.Ehrlichia canisEhrlichia ewingiiPrimary vectorRhipicephalus sanguineus (Brown dog tick)Amblyomma americanum (Lone star tick)PathologyInfects monocytes Infects granulocytesClinical presentation• Fever, anorexia, lethargy • Bleeding disorders • Polyarthritis, lameness • Lymphadenomegaly • Neurologic signs• Fever, anorexia, lethargy • Polyarthritis, lameness • Neurologic signsLaboratory abnormalitiesNotePrevious infection may not prevent reinfection, and persistent infections are possible.12,14Did you know?• D ogs coinfected with E. canis and A. platys were found to have more severe anemia and thrombocytopenia than dogs with either single infection.11• I n a study of healthy dogs with antibodies to E. canis , 39% were thrombocytopenic.12• C hronic E. canis infections, if left untreated, can lead to bone marrow dysfunction or kidney disease.• D ogs with Ehrlichia antibodies in E. canis endemic areas had a 112% increased risk of developing chronic kidney disease (CKD).13CKD monitoring• Chemistry panel with SDMA - R ecommended to evaluate forsecondary kidney disease.• Urinalysis with UPC - R ecommended to evaluatefor proteinuria • CBC with blood film - R ecommended as part of aminimum database• Anemia• Thrombocytopenia • Hyperglobulinemia • ProteinuriaOther clinical findings may include:• Decreased albumin • Increased globulin• Mild increased ALT and ALP • Increased SDMA • Creatinine• Decreased urine specific gravity, proteinuria • Increased urine protein:creatinine (UPC) ratio.Serology and PCR for sick patients For dogs presenting with clinical signs consistent with a vector-borne disease, usingserology and PCR together improves your ability to make an accurate diagnosis.Serology Polymerase chain reaction (PCR)Measures Antibody response of host Nucleic acid (DNA) from pathogenBenefits Useful for screening as well as diagnosisof infection Specifically identifies pathogens indicating active infectionLimitations Clinical signs may precede a measurableantibody response A negative PCR result does not necessarily rule out infectionDogs with ehrlichiosis and anaplasmosis may present with clinical signs at different times after infection. Which sick dog are you dealing with? Benefits and limitations of each diagnostic methodrecrudescence presents presents presentsWhen to use the IDEXX vector-borne disease RealPCR™ panels• S ick patients with clinical signsand/or laboratory abnormalitiesconsistent with a vector-borne illness• P atients with subclinical infectionsbased on history, physicalexamination, serology, and clinicallaboratory findings“No single test is sufficientfor diagnosing an infectious disease in a sick patient.”Edward Breitschwerdt, DVM, DACVIM*Professor, Internal MedicineCollege of Veterinary Medicine,North Carolina State University* D r. Breitschwerdt has a business relationship with IDEXX pursuant to which he receives compensation from IDEXX from time to time. The views expressed in this guide are solely those of Dr. Breitschwerdt.References1. G eneral guidelines: Parasite testing and protection guided by veterinarians [dog].Companion Animal Parasite Council website. /guidelines /general-guidelines. Updated July 29, 2020. Accessed November 17. 2021. 2. B eall MJ, Chandrashekar R, Eberts MD, et al. Serological and molecular prevalenceof Borrelia burgdorferi , Anaplasma phagocytophilum , and Ehrlichia species in dogs from Minnesota. Vector-Borne Zoonotic Dis . 2008;8(4):455–464. doi:10.1089/vbz.2007.0236 3. R egions where ticks live [maps]. Centers for Disease Control and Prevention website./ticks/geographic_distribution.html. November 17, 2021. 4. D rake C, Coyne M, McCrann DJ, Buch J, Mack R. Risk of development of chronickidney disease after exposure to Borrelia burgdorferi and Anaplasma spp. T op Companion Anim Med. 2020;42:100491. doi:10.1016/j.tcam.2020.100491 5. O ’Connor TP , Esty KJ, Hanscom JL, Shields P , Philipp MT . Dogs vaccinatedwith common Lyme disease vaccines do not respond to IR 6, the conserved immunodominant region of the VlsE surface protein of Borrelia burgdorferi.Clin Diagn Lab Immunol. 2004;11(3):458–462. doi:10.1128/CDLI.11.3.458-462.2004 6. S traubinger RK. PCR-based quantification of Borrelia burgdorferi organisms in caninetissues over a 500-day postinfection period. J Clin Microbiol. 2000;38(6):2191–2199. doi:10.1128/JCM.38.6.2191-2199.2000 7. C APC prevalence maps: heartworm [dog]. Companion Animal Parasite Councilwebsite. /maps/#/2021/all-year/heartworm-canine/dog/united-states. Accessed November 17, 2021.8. A merican Heartworm Society. Current canine guidelines for the prevention, diagnosis,and management of heartworm infection in dogs . 2020. Accessed November 17, 2021. https:///images/pdf/AHS_Canine_Guidelines_11_ 13_20.pdf?1605556516 9. E genvall A, Lilliehöök I, Bjöersdorff A, et al. Detection of granulocytic Ehrlichia speciesDNA by PCR in persistently infected dogs. Vet Rec . 2000;146(7):186–190. doi:10.1136/vr.146.7.186 10. B reitschwerdt EB, Hegarty BC, Qurollo BA, et al. Intravascular persistence ofAnaplasma platys , Ehrlichia chaffeensis , and Ehrlichia ewingii DNA in the blood of a dog and two family members. Parasit Vectors . 2014;7:298. doi:10.1186/1756-3305-7-298 11. G aunt S, Beall M, Stillman B, et al. Experimental infection and co-infection of dogs withAnaplasma platys and Ehrlichia canis : hematologic, serologic and molecular findings. Parasit Vectors . 2010;3(1):33. doi:10.1186/1756-3305-3-33 12. H egarty BC, de Paiva Diniz PP , Bradley JM, Lorentzen L, Breitschwerdt E. Clinicalrelevance of annual screening using a commercial enzyme-linked immunosorbentassay (SNAP 3Dx) for canine ehrlichiosis. J Am Anim Hosp Assoc. 2009;45(3):118–124. doi:10.5326/0450118 13. B urton W, Drake C, Ogeer J, et al. Association between exposure to Ehrlichia spp.and risk of developing chronic kidney disease in dogs. J Am Anim Hosp Assoc . 2020;56(3):159–164. doi:10.5326/JAAHA-MS-7012 14. S tarkey LA, Barrett AW, Beall MJ, et al. Persistent Ehrlichia ewingii infection indogs after natural tick infestation. J Vet Intern Med . 2015;29(2):552–555. doi:10.1111/jvim.12567 15. S nellgrove AN, Krapiunaya I, Ford SL, et al. Vector competence of Rhipicephalussanguineus sensu stricto for Anaplasma platys . Ticks Tick Borne Dis. 2020;11(6):101517. doi:10.1016/j.ttbdis.2020.101517Depend on the most accurate and comprehensive screenSNAP 4Dx Plus T estReference-laboratory quality in the palm of your hand, for superior diagnostic accuracy at the pointof care.Lab 4Dx Plus T estAvailable from IDEXX Reference Laboratories as a stand-alone test or as part of a more comprehensiveparasite screen with the Fecal Dx Antigen Panel with Lab 4Dx Plus Test-Canine.SNAP ® technology uses a proprietary three-step process to deliver dependable sensitivity and specificity.Available in-clinic or from IDEXX Reference LaboratoriesStrengthen the bonds.IDEXX Laboratories, Inc.One IDEXX DriveWestbrook, Maine 04092United StatesAmerican dog tick (Dermacentor variabilis) photographer: Susan E. Ellis, USDA-APHIS-PPQ. Black-legged tick (Ixodes scapularis), lone star tick (Amblyomma americanum), and brown dog tick (Rhipicephalus sanguineus) photographer: James L. Occi.© 2022 IDEXX Laboratories, Inc. All rights reserved. • 09-69074-13All ®/TM marks are owned by IDEXX Laboratories, Inc. or its affiliates in the United States and/or other countries. The IDEXX Privacy Policy is available at .。

SNAP—Ⅳ评定量表在教师中的应用

SNAP—Ⅳ评定量表在教师中的应用目的探讨儿童注意缺陷多动障碍诊断中，SNAP-Ⅳ量表在家长和教师中的运用比较，为ADHD的诊断提供更好的方法。

方法收集2017年1月～12月在我科多动症门诊根确诊ADHD的儿童248例，男孩210例，女孩38例，对SNAP-Ⅳ量表中家长和教师的注意缺陷、多动冲动阳性条目数进行比较，同时对不同性别的阳性条目数进行比较。

结果教师量表中注意缺陷阳性条目数为（6.54±2.04），高于家长量表的（5.98±2.13），差异具有统计学意义（P＜0.05）。

教师量表中多动冲动阳性条目数为（4.56±2.82），与家长量表的（4.74±2.59）比较，差异无统计学意义（P>0.05）。

在不同性别比较中，男孩教师量表的注意缺陷阳性条目数高于家长（P＜0.01），多动冲动阳性条目数比较，差异无统计学意义（P>0.05）；而女孩教师量表注意缺陷阳性条目数与家长量表比较，差异无统计学意义（P>0.05），多动冲动阳性条目数高于家长量表（P＜0.01）。

结论无论是家长还是教师均存在主观不利因素，临床医师在诊断过程中不能单纯根据SNAP-Ⅳ问卷中条目得分做出结论，应向家长（主要带养人）认真询问病史，仔细观察孩子的外部特征及就诊过程中的表现，同时结合体格检查、血液、脑电图检查以及注意力测试等客观检查方法来做出正确诊断。

如果最后结论与家长方面仍然存在较大偏差，应考虑孩子是否存在其他方面的行为问题，进一步找出深层次的原因，给出正确的指导。

Abstract：Objective To investigate the use of SNAP-IV in parents and teachers in the diagnosis of attention deficit hyperactivity disorder in children，and to provide a better method for the diagnosis of ADHD. Methods A total of 248 children，including 210 boys and 38 girls，who were diagnosed with ADHD in our department from January to December 2017 were enrolled. The number of attention deficits and hyperactive impulses in parents and teachers on the SNAP-IV scale were collected. Compare the number of positive entries for different genders. Results The number of positive defects in the teacher scale was （6.54±2.04），which was higher than that of the parental scale （5.98±2.13），and the difference was statistically significant （P ＜0.05）. The number of hyperactive impulse positive items in the teacher scale was （4.56±2.82），which was not statistically significant （P>0.05）compared with the parental scale （4.74±2.59）. In the comparison of different genders，the number of attention deficit-positive items in the boy teacher scale was higher than that in the parents （P＜0.01），and the number of hyperactive impulse positive items was not statistically significant （P>0.05）；while the girl teacher scale noticed The number of defective positive items was not significantly different from the parental scale （P>0.05），and the number of hyperactive impulse positive items was higher than the parental scale （P＜0.01）. Conclusion Both parents and teachers have subjective disadvantages. Clinicians cannot make conclusions based solely on the scores of the entries in the SNAP-IV questionnaire during the diagnosis process. Parents （primary adopters）should be carefully asked about the medical history and carefully observe the external characteristics of the children. And the performance during the visit，combined with physical examination，blood，EEG and attention test to make acorrect diagnosis. If the final conclusion still has a large deviation from the parent，it should consider whether the child has other behavioral problems，further find out the deeper reasons，and give correct guidance.Key words：Children with attention deficit hyperactivity disorder；Children；SNAP-IV assessment scale注意缺陷多动障碍（attention deficit hyperactivity disorder，ADHD）又称多动症，是指发生于儿童时期，主要变现为与患儿年龄不相称的注意力不集中、活动过度、情绪冲动，伴有认知障碍和学习困难的一组综合征，是一组常见的儿童发育行为问题。

ITERATIVE TECHNIQUES FOR BLIND SOURCE SEPARATION

EUSIPCO ’92ITERATIVE TECHNIQUES FOR BLIND SOURCE SEPARATIONUSING ONLY FOURTH-ORDER CUMULANTSJean-François CardosoTélécom Paris.Dept Signal,46rue Barrault,75634Paris CEDEX13,FRANCE.Email:cardoso@sig.enst.frAbstract."Blind source separation"is an array processing problem without a priori information(no array manifold).This model can be identiﬁed resorting to4th-order cumulants only via the concept of4th-order signal subspace(FOSS)which is deﬁned as a matrix space.This idea leads to a"Blind MUSIC"approach where identiﬁcation is achieved by looking for the(approximate)intersections between the FOSS and the manifold of1D projection matrices.Pratical implementations of these ideas are discussed and illustrated with computer simulations.1.INTRODUCTIONThis paper adresses the problem of blind source separation or independent component analysis in the complex case where it can be seen as a narrow-band array processing problem:the output,denoted x(t),of an array of m sensors listening at n discrete sources takes the form: (1)x(t)=p=1,nΣs p(t)a p+n(t)where s p(t)denotes the complex signal emmited by the p-th source;where a p is aﬁxed(deterministic)vector called the p-th source signature;and where n(t)is an independent additive noise assumed to be normally distributed with arbitrary covariance.In"standard"array processing,the same data model is used but the source signatures depend on very few location parameters and this dependence is assumed to be known via the array manifold.In contrast,we adress here the blind problem where no a priori information is available about source signatures.Hence blind qualiﬁes any processing based on the sole obervations."Blindness"is compensated by exploiting the hypothesized assumption of source independence.In the following it is assumed that:•source signals are statistically independent,•source signals have non vanishing kurtosis,•source signatures are linearly independent.Blind source separation is understood as estimation of the source signals s p(t),while blind identiﬁcation refers to the estimation of the source signatures a p.In the following, we focus on identﬁcation since separation can be based on signature estimates.The blind problem is interesting because its solution allows to process narrow band array data without explicit knowledge about array geometry and without assumptions about wavefront shapes.Various solutions relying on the use of both2nd-order and4th-order cumulant statistics of the array output have already been reported[1-4].These approaches make use of2nd-order information to whiten the data,and4th-order information is then used to process the resulting orthogonalized problem.The additive noise is assumed to be normally distributed:it has no effect on the(exact)4th-order cumulants but2nd-order noise cumulants do not vanish so that the spatial structure of the noise covariance has to be known,modelled or estimated in order to achieve consistent2nd-order prewhitening. These limitations can be overcome by giving up the idea of 2nd-order whitening and resorting to4th-order cumulants only[5-6].It is the purpose of this communication to show how the concept of fourth-order signal subspace yields simple implementations of4th-order only blind identiﬁcation.2.BLIND IDENTIFICATION2.1On identiﬁability.The blind context does not lead to full identiﬁability of the model(1)because any complex factor can be exchanged between s p and a p without modifying the observation.Hence if no a priori information is available,each signature can be identiﬁed only up to a scale factor.We take advantage of this to assume,without any loss of generality,that each signature a p has unit norm.With this constraint,an unidentiﬁable phase term is still present in a p.For each source p,we denote asΠp the orthogonal projector onto the1D space where the p th component lives.It is the space spanned by the signature a p and the projector onto it is(2)Πp=∆a p a p∗This hermitian matrix is unaffected by any phase term in a p and conversely determines a p up to a phase term.It follows that the projectorsΠp are the algebraic quantities that can be,at best,identiﬁed in the blind context.It iseasily seen that knowing these projectors is sufﬁcient to perform blind separation of the source signals s p(t) because they allow to construct for each source the linear ﬁlter that zeroes all the components but the one speciﬁed. We then deﬁne blind identiﬁcation as the problem of estimating the projectorsΠp from sample statistics only. 2.2Blind MUSIC.The approach to blind identiﬁcation presented in this contribution can be seen as a blind4th-order version of the celebrated MUSIC algorithm.The MUSIC technique is based on the concept of signal subspace which is the vector space spanned by the steering vectors.It can be summarized as i)Estimate the signal subspace using the covariance.ii)Search for the steering vectors which are the closest to the signal subspace.The search is,of course,across the array manifold:this is how MUSIC exploits the a priori information contained in the parameterization of the steering vectors.The fourth-order signal subspace(FOSS)is deﬁned as the real span of the projectorsΠp i.e.as the linear matrix space made of all possible linear combinations with real coefﬁcients of the projectorsΠp:(3)FOSS={M|M=p=1,nΣγp a p a p∗,γp∈R}Let us now consider the following idea for blind identiﬁcation i.e.estimation of theΠp:i)Estimate the FOSS using4th-order cumulants.ii)Search for the orthogonal1D projectors which are the closest to the FOSS.The closest projectors to the FOSS are taken as estimates of the source projectorsΠp.Such an idea could be termed"blind MUSIC"because,in spite of its strong analogy with the classical MUSIC,no signature parameterization is assumed here:the search is across the so called rank one manifold(ROM)which is deﬁned as the set of all rank-one unit-norm hermitian matrices i.e.across all the1D orthogonal projectors.The reason why Blind MUSIC works is that a matrix space with structure as in eq.(3)is shown,under mild conditions,to contain no other1D projectors than the ones used in its construction,i.e.theΠp.This is obviously true as soon as the signatures a p are linearly independent since in that case,a matrix M as in eq.(3)has a rank equal to the number of non-zero coefﬁcientsγp.If M is a1D projector, it has rank one,hence all the coefﬁcientsγp but one are zero and M is then necessarily one of theΠp.We now have to discuss i)FOSS estimation from4th-order cumulants ii)practical implementations of the blind MUSIC search.3.FOURTH-ORDER SIGNAL SUBSPACE3.1Quadricovariance.Weﬁnd convenient to make temporary use of indexed notations to express the cumulants of the vector process x.Let us denote by x i the i-th coordinate of vector x and by x i the i-th coordinate of its dual x∗.Of course,only orthonormal basis are used: x i is just the complex conjugate of x i.The covariance classically is the matrix R whose(i,j)-coordinate denoted r i j is the2nd-order cumulant of x i and x j:(4)r i j=∆Cum(x i,x j)1≤i,j≤m Similarly,we deﬁne the quadricovariance of x as the set of m4complex scalars,q il jk,1≤i,j,k,l≤m:(5)q il jk=∆Cum(x i,x j,x k,x l)Our approach to process4th-order information is to consider the quadricovariance as a matrix mapping denoted Q,which to any matrix M with coordinates m i j associates the matrix N=Q(M)with coordinates n i j according to:(6)n i j=1≤k,l≤mΣq il jk m k lThe quadricovariance has the two following properties:i) it maps any hermitian matrix to another hermitian matrix. ii)it is itself an hermitian operator in the(usual)sense that for any matrices M and N we have<N|Q(M)>∗= <M|Q(N)>with the Euclidian scalar product <M|N>=∆Tr(NM H).These are trivial consequences of cumulant symmetries.It follows[3]that the quadricovariance admits m2real eigenvalues,denoted µi,i=1,m2and m2corresponding orthonormal hermitian eigen-matrices,denoted E i,i=1,m2,verifying:∀i=1,m2Q(E i)=µi E i withE i=E i H,µi∈R,Tr(E i E j)=δ(i,j)As a simple consequence[3]of cumulant additivity and multilinearity,the quadricovariance of a linear mixture(1) of independent components takes the special form:(7)Q(M)=p=1,nΣk p a p∗Ma a p a p a p∗with no contribution from the additive noise(since it has been assumed Gaussian and independent of the signals) and where the kurtosis of the p-th source is denoted by k p: (8)k p=∆Cum(s p,s p∗,s p∗,s p)Equation(7)evidences that the image space of the quadricovariance Q is spanned by the projectors Πp=a p a p∗(hence the name"FOSS").It has exactly rank n if no kurtosis k p is zero and if the projectorsΠp are linearly independent.This last condition is fulﬁlled whenever the signatures a p are themselves independent.It follows that quadricovariance eigen-decomposition shows only n non-zero eigenvalues.Let us assume that they are numbered in such a way that the corresponding n eigen-matrices are(E i|i=1,n).These eigen-matrices form an hermitian orthonormal basis of the FOSS.3.2FOSS estimation.When a strongly consistent estimate of the signal covariance is used,the2nd-order signal subspace estimate obtained via eigen-decomposition also is strongly consistent.The same can be shown to hold for the FOSS estimates obtained from an eigen-decomposition of the sample quadricovariance into eigen-matrices.This should be the preferred FOSS estimation method for small arrays but eigen-decomposition of the quadricovariance may be too expensive with large arrays.Note however that only a small number of eigen-matrices need to be estimated(n and not m2)and this fact can lead to large computational savings(see[7]).Even in that case, the whole set of4th-order cumulants is needed,and quadricovariance estimation cost may be prohibitive. Fortunately,the FOSS can be estimated in a simpler manner.We demonstrate this in the(rather common)case where signals are circurlarly distributed.Cumulant expression in terms of the moments then reduces to: (9)q il jk=E{x i x j x k x l}−r i j r l k−r l j r i kand it is readily checked that the quadricovariance image of any matrix M accordingly reduces to:(10)Q(M)=E{(x∗Mx x)x x∗}−RMR−R Tr(MR) This expression admits an obvious sample counterpart showing that Q(M)can be estimated at a cost similar to the covariance.This suggests to choose a priori a set of n hermitian matrices M i and to estimate Q(M i)according to (10).The result will be a set of n almost surely independent matrices of the FOSS.They can then be orthonormalized(by a Gram-Schmidt procedure for instance)into an orthonormal hermitian basis of the FOSS. Such a procedure obviously yields FOSS estimates with higher variance than those obtained by eigen-decomposition of the whole set of4th-order cumulants. Since it is not possible to ensure in advance that the Q(M i) actually are independent,a safer solution would be to use a number of M i larger than n.4.BLIND MUSIC IMPLEMENTATIONFrom now on,we assume that a FOSS estimate is available in the form of a set of n hermitian orthonormal matrices:(M i|i=1,n)forming a basis of the estimated FOSS.The following search implementations do not depend on the particular FOSS estimation technique.Blind MUSIC can be implemented as searching through the FOSS the closest ROM matrix(see the PQN technique below)or,alternatively,as searching through the ROM the closest FOSS matrix(seeΠV3)In both cases,the suggested techniques do not implement the search via a gradient(or similar)approach but expresses the Blind MUSIC estimates asﬁxed points of an appropriate mapping.In our simulations,we have found that theseﬁxed points were the only stable points:the blind MUSIC search can then be implemented as the iteration of these mappings with arbitrary starting points.4.1ΠV3Search.The natural approach to blind MUSIC is to maximize the norm of the projection onto the FOSS of a matrix A under the constraint that it is a1D projector. Using an orthonormal hermitian basis,the squared norm of this projection,denoted d,is the sum of the squared projections onto each basis matrix.(11)d=i=1,nΣTr2(A M i)Blind MUSIC estimates are obtained as the maximizers of d under the constraint that A=v v∗with v∗v=1.Since Tr(A M i)=v∗M i v,the variation with respect to v of a Lagrange function L=1/2d−λv∗v associated to this constrained optimization problem is:δL=i=1,nΣ(v∗M i v)(v∗M iδv+δv∗M i v)−λ(v∗δv+v∗δv) Deﬁning the cubic vector mapping v→φ(v)as: (13)φ(v)=∆Σi=1,n(v∗M i v)M i vthe Lagrange function variation is rewritten in:(14)δL=(φ−λv)∗δv+δv∗(φ−λv)which is zero for anyδv iffφ(v)=λv.This is equivalent to v being aﬁxed point of the mapping v→Φ(v)where: (15)Φ(v)=∆φ(v)/|φ(v)|TheΠV3search(where V3is a reminder for the cubic dependence on the iterated vector)starts with a random vector and then iteratively computes its image throughΦ.4.2PQN Search.An alternate approach is to search for matrices of the FOSS that are as close as possible to the ROM.The basic idea is to start with an arbitrary matrix of the FOSS and to repeatedly project it onto the ROM and back onto the FOSS.Projection onto the ROM is equivalent to truncating the matrix to itsﬁrst principal eigen-component,which requires an eigen-decomposition at each step.On the other hand,repeatedly squaring a matrix has the effect of enhancing the dominant eigenvalue.In our experiments,we have found that the projection onto the ROM,being included in the iteration loop,could be replaced by a simple matrix squaring followed by renormalization The PQN algorithm is just cycling through the three steps of projection,quadration, and normalization,hence the acronym"PQN".After convergence,the dominating eigen-vector is extracted, providing an estimate of one of the source signatures.Quadration and projection can be efﬁciently implemented in a single step by representing the iterated matrix,say A,by its(real)coordinates a i,i=1,n in the FOSS basis:A=Σa i M i.The squared matrix then is A2=Σa i a j M i M j.Since an orthonormal basis is used, the projection of A2onto the FOSS has coordinates a k′given by:(16)a k′=Σi,j t ijk a i a j with t ijk=∆Tr(M i M j M k) Hence,by pre-computing the table t ijk,each quadration-projection is computed in the single step(16),involving only n3real multiplications.4.3Simulation results The following simulation results are for a uniform linear half-wavelength array of4sensors, two independent PSK modulated sources of unit variance located respectively at0and20degrees(i.e.under the same lobe).The signal is corrupted by additive Gaussian white noise with covarianceσI.We performed20Monte-Carlo runs using the PQN algorithm for data lengths of50, 100,200,500,1000and for noise levelsσ=-10,0,10,20 dB.For each run,we plot a performance indexρdeﬁnedas (17)ρ=n1p =1,nΣ1−Tr (Πˆp Πp)where each Πˆpis the estimated p -th projector.This index also is the squared sine of the angle between each signature and its estimate (averaged on the sources).Perf.index10E-110E-210E-310E-4501002005001000-10dB SNR•••••••••••••••••••••••••••••••Perf.index10E-110E-210E-310E-45010020050010000dB SNR•••••••••••••••••••••••••••••••••••••••••••••••••Perf.index10E-110E-210E-310E-450100200500100010dB SNR•••••••••••••••••••••••••••••••••••••••••••••••••••••••••••For negative SNR,the data lengths used here do notallow any correct estimation :the performance index is close to 0.5,indicating "random estimation"!But as the SNR gets positive meaningful estimates are obtained with relatively short data lengths.Also note that there is no signiﬁcant improvement when the SNR goes from 10dB to 20dB.This is a general feature of 4th-order-only blind techniques :when the noise level is low enough,the performance is dominated by the sample size.This could be contrasted with the standard parametric MUSIC (2nd-order or 4th-order)where,at low noise levels,the varianceSample sizePerf.index10E-110E-210E-310E-450100200500100020dB SNR •••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••of the estimates is proportional to the noise power.Another remark is that these simulations are for equipowered sources :the performance would degrade for a source when its power gets weaker.This effect shows at any order but is naturally more severe at fourth-order than at 2nd-order.Just as in the MUSIC case,asymptotic performance can be obtained in closed form but room is deﬁnitely lacking for exposition of the results.They will be presented at the conference.CONCLUSION.The notion of fourth-order signal subspace (FOSS)has been introduced.This matrix space,function of the 4th-order cumulants,is the natural 4th-order counterpart of the classical 2nd-order signal subspace.Exploited in a "blind MUSIC"fashion,it allows for blind identiﬁcation without resorting to 2nd-order information.This can be done with one of the low cost ﬁxed point techniques presented here.REFERENCES[1]on,"Independent Component Analysis",Proc.Int.Workshop on Higher-Order Stat.,Chamrousse,France,Jul.91,pp.111-120.[2]M.Gaeta,coume,"Source Separation Without A Priori Knowledge :the Maximum Likelihood Solution",Proc.EUSIPCO,Barcelona,Spain,Sept.90,pp.621-624.[3]J.F.Cardoso,"Eigen-structure of the fourth-order cumulant tensor with application to the blind source separation problem",Proc.ICASSP’90,pp.2655-2658,Albuquerque,1990.[4]V.C.Soon,L.Tong,Y.F.Huang,R.Liu,"An extended fourth order blind identiﬁcation algorithm in spatially correlated noise",Proc.ICASSP’90,pp.1365-1368,Albuquerque,1990.[5]J.F.Cardoso,"Super-Symmetric Decomposition of the Fourth-Order Cumulant Tensor.Blind Identiﬁcation of More Sources than Sensors",Proc.ICASSP’91,pp.3109-3112,Toronto,1991.[6]G.Giannakis,S.Shamsunder,"Modelling of non Gaussian array data using cumulants :DOA estimation with less sensors than sources",Proc.of conf.on Info.Sci.and Syst.,Baltimore,MD,1991.[7]J.F.Cardoso,on,"Tensor-based Independent Component Analysis",Proc.EUSIPCO,Barcelona,Spain,Sept.90,pp.673-676.。

开启片剂完整性的窗户(中英文对照)

开启片剂完整性的窗户日本东芝公司，剑桥大学摘要：由日本东芝公司和剑桥大学合作成立的公司向《医药技术》解释了FDA支持的技术如何在不损坏片剂的情况下测定其完整性。

太赫脉冲成像的一个应用是检查肠溶制剂的完整性，以确保它们在到达肠溶之前不会溶解。

关键词：片剂完整性，太赫脉冲成像。

能够检测片剂的结构完整性和化学成分而无需将它们打碎的一种技术，已经通过了概念验证阶段，正在进行法规申请。

由英国私募Teraview公司研发并且以太赫光（介于无线电波和光波之间）为基础。

该成像技术为配方研发和质量控制中的湿溶出试验提供了一个更好的选择。

该技术还可以缩短新产品的研发时间，并且根据厂商的情况，随时间推移甚至可能发展成为一个用于制药生产线的实时片剂检测系统。

TPI技术通过发射太赫射线绘制出片剂和涂层厚度的三维差异图谱，在有结构或化学变化时太赫射线被反射回。

反射脉冲的时间延迟累加成该片剂的三维图像。

该系统使用太赫发射极，采用一个机器臂捡起片剂并且使其通过太赫光束，用一个扫描仪收集反射光并且建成三维图像(见图)。

技术研发太赫技术发源于二十世纪九十年代中期13本东芝公司位于英国的东芝欧洲研究中心，该中心与剑桥大学的物理学系有着密切的联系。

日本东芝公司当时正在研究新一代的半导体，研究的副产品是发现了这些半导体实际上是太赫光非常好的发射源和检测器。

二十世纪九十年代后期，日本东芝公司授权研究小组寻求该技术可能的应用，包括成像和化学传感光谱学，并与葛兰素史克和辉瑞以及其它公司建立了关系，以探讨其在制药业的应用。

虽然早期的结果表明该技术有前景，但日本东芝公司却不愿深入研究下去，原因是此应用与日本东芝公司在消费电子行业的任何业务兴趣都没有交叉。

这一决定的结果是研究中心的首席执行官DonArnone和剑桥桥大学物理学系的教授Michael Pepper先生于2001年成立了Teraview公司一作为研究中心的子公司。

TPI imaga 2000是第一个商品化太赫成像系统，该系统经优化用于成品片剂及其核心完整性和性能的无破坏检测。

探讨后腹腔镜下输尿管切开取石术与经尿道输尿管软镜钬激光碎石术在治疗嵌顿性输尿管上段结石的疗效和并发症

临床医学China &Foreign Medical Treatment 中外医疗探讨后腹腔镜下输尿管切开取石术与经尿道输尿管软镜钬激光碎石术在治疗嵌顿性输尿管上段结石的疗效和并发症比较陈克明济南市第三人民医院泌尿外科，山东济南 250132［摘要］目的研究嵌顿性输尿管上段结石经后腹腔镜下输尿管切开取石术与经尿道输尿管软镜钬激光碎石术的临床价值。

方法随机选取2021年8月—2023年8月济南市第三人民医院泌尿外科治疗的60例嵌顿性输尿管上段结石患者为研究对象，根据不同的治疗方式分成软镜组与腹腔镜组，各30例。

软镜组患者行输尿管软镜下钬激光碎石术，腹腔镜组行经后腹腔镜下输尿管切开取石术。

比较两组患者的术后发热、结石清除以及并发症发生情况，比较两组患者手术相关指标，包括手术时间、术后疼痛评分、住院时间。

结果两组术后发热、结石清除以及并发症发生情况对比，差异无统计学意义（P 均>0.05）；软镜组手术时间（57.23±10.34）min 、住院时间（4.10±0.54）d 、术后疼痛评分（2.21±0.43）分均优于腹腔镜组，差异有统计学意义（t =6.879、9.195、8.181，P 均<0.05）。

结论后腹腔镜下输尿管切开取石术在清除结石方面可能更有效。

然而，其伴随着较大的手术创伤和较多的术后疼痛。

相比之下，经尿道输尿管软镜钬激光碎石术具有更加明显的优势，可以减轻术后的疼痛，并降低手术和住院的时间，在选择治疗方法时应根据具体情况进行权衡。

［关键词］输尿管；结石；并发症；疗效；手术时间；住院时间［中图分类号］ R714.258 ［文献标识码］ A ［文章编号］ 1674-0742（2024）03(a)-0027-04Comparison of the Efficacy and Complications of Posterior Laparoscopic Ureterotomy and Lithotripsy with Transurethral Ureteral Flexible Hol⁃mium Laser Lithotripsy in the Treatment of Embedded Upper Ureteral StonesCHEN KemingDepartment of Urology, Jinan Third People's Hospital, Jinan, Shandong Province, 250132 China[Abstract] Objective To study the clinical value of holmium laser lithotripsy for embedded upper ureteral stones via posterior laparoscopic ureterotomy and transurethral ureteral flexible lens. Methods A total of 60 patients with embed⁃ded upper ureteral stones treated in the Department of Urology of Jinan Third People's Hospital from August 2021 to August 2023 were randomly selected as the study objects, and they were divided into the flexible lens group and the laparoscopic group according to different treatment, with 30 cases in each group. The flexible lens group received hol⁃mium laser lithotripsy under flexible ureteroscopy, and the laparoscopic group was treated with posterior laparoscopicureterotomy and lithotripsy. The occurrence of postoperative fever, stone removal, and complications were compared between the two groups, and the surgery-related indexes of the two groups were compared, including operation time, postoperative pain score, and hospitalization time. Results There was no statistically significant difference in the occur⁃rence of postoperative fever, stone removal, and complications between the two groups (all P >0.05). The operation time DOI ：10.16662/ki.1674-0742.2024.07.027[作者简介] 陈克明（1981-），男，本科，副主任医师，研究方向为泌尿外科结石及肿瘤。

J. reine angew. Math. 549 (2002), 47—77 Journal für die reine und angewandte Mathematik (

J.reine angew.Math.549(2002),47—77Journal fu¨r die reine undangewandte Mathematik(Walter de GruyterBerlinÁNew York2002Discrete constant mean curvature surfaces andtheir indexBy Konrad Polthier at Berlin and Wayne Rossman at KobeAbstract.We deﬁne triangulated piecewise linear constant mean curvature surfaces using a variational characterization.These surfaces are critical for area amongst continuous piecewise linear variations which preserve the boundary conditions,the simplicial structures, and(in the nonminimal case)the volume to one side of the surfaces.We thenﬁnd explicit formulas for complete examples,such as discrete minimal catenoids and helicoids.We use these discrete surfaces to study the index of unstable minimal surfaces,by nu-merically evaluating the spectra of their Jacobi operators.Our numerical estimates conﬁrm known results on the index of some smooth minimal surfaces,and provide additional in-formation regarding their area-reducing variations.The approach here deviates from other numerical investigations in that we add geometric interpretation to the discrete surfaces.1.IntroductionSmooth submanifolds,and surfaces in particular,with constant mean curvature(cmc) have a long history of study,and modern work in thisﬁeld relies heavily on geometric and analytic machinery which has evolved over hundreds of years.However,nonsmooth sur-faces are also natural mathematical objects,even though there is less machinery available for studying them.For example,consider M.Gromov’s approach of doing geometry using only a set with a measure and a measurable distance function[9].Here we consider piecewise linear triangulated surfaces—we call them‘‘discrete surfaces’’—which have been brought more to the forefront of geometrical research by com-puter graphics.We deﬁne cmc for discrete surfaces in R3so that they are critical for volume-preserving variations,just as smooth cmc surfaces are.Discrete cmc surfaces have both in-teresting di¤erences from and similarities with smooth ones.For example,they are di¤erent in that smooth minimal graphs in R3over a bounded domain are stable,whereas discrete minimal graphs can be highly unstable.We will explore properties like this in section2.In section3we will see some ways in which these two types of surfaces are similar. We will see that:a discrete catenoid has an explicit description in terms of the hyperboliccosine function,just as the smooth catenoid has;and a discrete helicoid can be described with the hyperbolic sine function,just as a conformally parametrized smooth helicoid is;and there are discrete Delaunay surfaces which have translational periodicities,just as smooth Delaunay surfaces have.Pinkall and Polthier [17]used Dirichlet energy and a numerical minimization proce-dure to ﬁnd discrete minimal surfaces.In this work,we rather have the goal to describe dis-crete minimal surfaces as explicitly as possible,and thus we are limited to the more funda-mental examples,for example the discrete minimal catenoid and helicoid.We note that these explicit descriptions will be useful test candidates when implementing a procedure that we describe in the next paragraphs.Discrete surfaces have ﬁnite dimensional spaces of admissible variations,therefore the study of linear di¤erential operators on the variation spaces reduces to the linear algebra of matrices.This advantage over smooth surfaces with their inﬁnite dimensional variation spaces makes linear operators easier to handle in the discrete case.This suggests that a useful procedure for studying the spectra of the linear Jacobi operator in the second variation formula of smooth cmc surfaces is to consider the corre-sponding spectra of discrete cmc approximating surfaces.Although similar to the ﬁnite ele-ment method in numerical analysis,here the ﬁnite element approximations will have geo-metric and variational meaning in their own right.As an example,consider how one ﬁnds the index of a smooth minimal surface,that is the number of negative points in the spectrum.The standard approach is to replace the metric of the surface with the metric obtained by pulling back the spherical metric via the Gauss map.This approach can yield the index:for example,the indexes of a complete catenoid and a complete Enneper surface are 1([7]),the index of a complete Jorge-Meeks n -noid is 2n À3([12],[11])and the index of a complete genus k Costa-Ho¤man-Meeks surface is 2k þ3for every k e 37([14],[13]).However,this approach does not yield the eigenvalues and eigenfunctions on compact portions of the original minimal surfaces,as the metric has been changed.It would be interesting to know the eigenfunctions associated to negative eigenvalues since these represent the directions of variations that reduce area.The above procedure of approximating by discrete surfaces can provide this information.In sections 5and 6we establish some tools for studying the spectrum of discrete cmc surfaces.Then we test the above procedure on two standard cases—a (minimal)rectangle,and a portion of a smooth minimal catenoid bounded by two circles.In these two cases we know the spectra of the smooth surfaces (section 4),and we know the discrete minimal sur-faces as well (section 3),so we can check that the above procedure produces good approx-imations for the eigenvalues and smooth eigenfunctions (section 7),which indeed must be the case,by the theory of the ﬁnite element method [4],[8].With these successful tests,we go on to consider cases where we do not a priori know what the smooth eigenfunctions should be,such as the Jorge-Meeks 3-noid and the genus 1Costa surface (section 7).The above procedure can also be implemented using discrete approximating surfaces which are found only numerically and not explicitly,such as surfaces found by the method in [17].And in fact,we use the method in [17]to ﬁnd approximating surfaces for the 3-noid and Enneper surface and Costa surface.Polthier and Rossman,Curvature surfaces48We note also that Ken Brakke’s surface evolver software [3]is an e‰cient tool for numerical index calculations using the same discrete ansatz.Our main emphasis here is to provide explicit formulations for the discrete Jacobi operator and other geometric proper-ties of discrete surfaces.Many of the discrete minimal and cmc surfaces introduced here are available as in-teractive models at EG-Models [19].2.Discrete minimal and cmc surfacesWe start with a variational characterization of discrete minimal and discrete cmc sur-faces.This characterization will allow us to construct explicit examples of unstable discrete cmc surfaces.Note that merely ﬁnding minima for area with respect to a volume constraint would not su‰ce for this as that would produce only stable examples.We will later use these discrete cmc surfaces for our numerical spectra computations.The following deﬁnitions for discrete surfaces and their variations work equally well in any ambient space R n but for simplicity we restrict to R 3.Deﬁnition 2.1.A discrete surface in R 3is a triangular mesh T which has the topology of an abstract 2-dimensional simplicial surface K combined with a geometric C 0realization in R 3that is piecewise linear on each simplex.The geometric realization j K j is determined by a set of vertices V ¼f p 1;...;p m g H R 3.T can be identiﬁed with the pair ðK ;V Þ.The simplicial complex K represents the connectivity of the mesh.The 0,1,and 2dimensional simplices of K represent the vertices,edges,and triangles of the discrete surface.Let T ¼ðp ;q ;r Þdenote an oriented triangle of T with vertices p ;q ;r A V .Let pq denote an edge of T with endpoints p ;q A V .For p A V ,let star ðp Þdenote the triangles of T that contain p as a vertex.For an edge pq ,let star ðpq Þdenote the (at most two)triangles of T that contain the edge pq .Deﬁnition 2.2.Let V ¼f p 1;...;p m g be the set of vertices of a discrete surface T .A variation T ðt Þof T is deﬁned as a C 2variation of the vertices p iFigure 1.At each vertex p the gradient of discrete area is the sum of the p 2-rotated edge vectors J ðr Àq Þ,as in Equation(1).p i ðt Þ:½0;e Þ!R 3so that p i ð0Þ¼p i E i ¼1;...;m :The straightness of the edges and the ﬂatness of the triangles are preserved as the vertices move.In the smooth situation,the variation at interior points is typically restricted to nor-mal variation,since the tangential part of the variation only performs a reparametrization of the surface.However,on discrete surfaces there is an ambiguity in the choice of normal vectors at the vertices,so we allow arbitrary variations.But we will later see (section 7)that our experimental results can accurately estimate normal variations of a smooth surface when the discrete surface is a close approximation to the smooth surface.In the following we derive the evolution equations for some basic entities under sur-face variations.The area of a discrete surface isarea ðT Þ:¼PT A T area T ;where area T denotes the Euclidean area of the triangle T as a subset of R 3.Let T ðt Þbe a variation of a discrete surface T .At each vertex p of T ,the gradient of area is‘p area T ¼12P T ¼ðp ;q ;r ÞA star pJ ðr Àq Þ;ð1Þwhere J is rotation of angle p 2in the plane of each oriented triangle T .The ﬁrst derivative of the surface area is then given by the chain ruled dt area T ¼P p A Vh p 0;‘p area T i :ð2ÞThe volume of an oriented surface T is the oriented volume enclosed by the cone of the surface over the origin in R 3vol T :¼16P T ¼ðp ;q ;r ÞA T h p ;q Âr i ¼13P T ¼ðp ;q ;r ÞA Th ~N ;p i Áarea T ;where p is any of the three vertices of the triangle T and~N¼ðq Àp ÞÂðr Àp Þ=jðq Àp ÞÂðr Àp Þj is the oriented normal of T .It follows thatPolthier and Rossman,Curvature surfaces50‘p vol T¼PT¼ðp;q;rÞA star p qÂr=6ð3Þandd dt vol T¼Pp A Vh p0;‘p vol T i:ð4ÞRemark2.1.Note also that‘p vol T¼PT¼ðp;q;rÞA star p À2Áarea TÁ~NþpÂðrÀqÞÁ=6.Furthermore,if p is an interior vertex,then the boundary of star p is closed and PT A star ppÂðrÀqÞ¼0.Hence the qÂr in Equation(3)can be replaced with2Áarea TÁ~N whenever p is an interior vertex.In the smooth case,a minimal surface is critical with respect to area for any variation thatﬁxes the boundary,and a cmc surface is critical with respect to area for any variation that preserves volume andﬁxes the boundary.We wish to deﬁne discrete cmc surfaces so that they have the same variational properties for the same types of variations.So we will consider variations TðtÞof T thatﬁx the boundary q T and that additionally preserve volume in the nonminimal case,which we call permissible variations.The condition that makes a discrete surface area-critical for any permissible variation is expressed in the fol-lowing deﬁnition.Deﬁnition2.3.A discrete surface has constant mean curvature(cmc)if there exists a constant H so that‘p area¼H‘p vol for all interior vertices p.If H¼0then it is minimal.This deﬁnition for discrete minimality has been used in[17].In contrast,our deﬁnition of discrete cmc surfaces di¤ers from[15],where cmc surfaces are characterized algorithm-ically using discrete minimal surfaces in S3and a conjugation pare also [2]for a deﬁnition via discrete integrable systems which lacks variational properties.Remark2.2.If T is a discrete minimal surface that contains a simply-connected dis-crete subsurface T0that lies in a plane,then it follows easily from Equation(1)that the dis-crete minimality of T is independent of the choice of triangulation of the trace of T0.2.0.1.Notation from th e th eoryofﬁnite elements.Consider a vector-valued functionv pj A R3deﬁned on the n interior vertices V int¼f p1;...;p n g of T.We may extend thisfunction to the boundary vertices of T as well,by assuming v p¼~0A R3for each boundaryvertex p.The vectors v pj are the variation vectorﬁeld of any boundary-ﬁxing variation ofthe formp jðtÞ¼p jþtÁv pj þOðt2Þ;ð5Þthat is,p0jð0Þ¼v pj.We deﬁne the vector~v A R3n by~v t¼ðv t p1;...;v tp nÞ:ð6ÞThe variation vectorﬁeld~v can be naturally extended to a piece-wise linear continuous R3-valued function v on T,with v in the following vector space:Polthier and Rossman,Curvature surfaces51Deﬁnition2.4.On a discrete surface T we deﬁne the space of piecewise linear functionsS h:¼f v:T!R3j v A C0ðTÞ;v is linear on each T A T and v j q T¼0g: This space is named S h,as in the theory ofﬁnite elements.Note that any compo-nent function of any function v A S h has bounded Sobolev H1norm.For each triangle T¼ðp;q;rÞin T and each v A S h,v j T ¼v p c pþv q c qþv r c r;ð7Þwhere c p:T!R is the head function on T which is1at p and is0at all other vertices ofT and extends linearly to all of T in the unique way.The functions c pj form a basis(withscalars in R3)for the3n-dimensional space S h.2.0.2.Non-uniqueness of discrete minimal disks.Uniqueness of a bounded mini-mal surface with a given boundary ensures that it is stable.For smooth minimal surfaces, uniqueness can sometimes be decided using the maximum principle of elliptic equations, which ensures that the minimal surface is contained in the convex hull of its boundary, and,if the boundary has a1-1projection to a convex planar curve,then it is unique for that boundary and is a minimal graph.The maximum principle also shows that any mini-mal graph is unique even when the projection of its boundary is not convex.More gener-ally,stability still holds when the surface merely has a Gauss map image contained in a hemisphere,as shown in[1](although their proof employs tools other than the maximum principle).However,such statements do not hold for discrete minimal surfaces.Consider the surface shown in the left-hand side of Figure2,whose height function has a local maxi-mum at an interior vertex.This example does not lie in the convex hull of its boundary and thereby disproves the general existence of a discrete version of the maximum principle.Also, the three surfaces on the right-hand side in Figure3are all minimal graphs over an annular domain with the same boundary contours and the same simplicial structure,and yet they are not the same surfaces,hence graphs with given simplicial structure are not unique.And the left-hand surface in Figure3is a surface whose Gauss map is contained in a hemisphere but which is unstable(this surface is not a graph)—another example of this property is the ﬁrst annular surface in Figure3,which is also unstable.(We deﬁne stability of discrete cmc surfaces in section5.)The inﬂuence of the discretization on nonuniqueness,like as in the annular examples of Figure3,can also be observed in a more trivial way for a discrete minimal graph over a simply connected convex domain.The two surfaces on the right-hand side of Figure2have the same trace,i.e.they are identical as geometric surfaces,but they are di¤erent as discrete surfaces.Interior vertices may be freely added and moved inside the middle planar square without a¤ecting minimality(see Remark2.2).In contrast to existence of these counterexamples we believe that some properties of smooth minimal surfaces remain true in the discrete setting.We say that a discrete surface is a disk if it is homeomorphic to a simply connected domain.Conjecture2.1.Let T H R3be a discrete minimal disk whose boundary projects in-jectively to a convex planar polygonal curve,then T is a graph over that plane.The authors were able to prove this conjecture with the extra assumption that all the triangles of the surface are acute,using the fact that the maximum principle(a height function cannot attain a strict interior maximum)actually does hold when all triangles are acute.One can ask if a discrete minimal surface T with given simplicial structure and boundary is unique if it has a1-1perpendicular or central projection to a convex polygonal domain in a plane.The placement of the vertices need not be unique,as we saw in Remark 2.2,however,one can consider if there is uniqueness in the sense that the trace of T in R3is unique:Conjecture2.2.Let G H R3be a polygonal curve that eitherðAÞ:projects injec-tively to a convex planar polygonal curve,orðBÞ:has a1-1central projection from a point p A R3to a convex planar polygonal curve.Let K be a given abstract simplicial disk,and let g:q K!G be a given piecewise linear map.If T is a discrete minimal surface that is a geometric realization of K so that the map q K!q T equals g,then the trace of T in R3is uniquely determined.Furthermore,T is a graph in the caseðAÞ,and T is contained in the cone of G over p in the caseðBÞ.We have the following weaker form of Conjecture2.2,which follows from Corollary5.1of section5in the case that there is only one interior vertex:Conjecture 2.3.If a discrete minimal surface is a graph over a convex polygonal do-main ,then it is stable .3.Explicit discrete surfacesHere we describe explicit discrete catenoids and helicoids,which seem to be the ﬁrst explicitly known nontrivial complete discrete minimal surfaces (with minimality deﬁned variationally).3.1.Discrete minimal catenoids.To derive an explicit formula for embedded com-plete discrete minimal catenoids,we choose the vertices to lie on congruent planar polygo-nal meridians,with the meridians placed so that the traces of the surfaces will have dihedral symmetry.We will ﬁnd that the vertices of a discrete meridian lie equally spaced on a smooth hyperbolic cosine curve.Furthermore,these discrete catenoids will converge uniformly in compact regions to the smooth catenoid as the mesh is made ﬁner.We begin with a lemma that prepares the construction of the vertical meridian of the discrete minimal catenoid,by successively adding one horizontal ring after another starting from an initial ring.Since our construction will lead to pairwise coplanar triangles,the star of each individual vertex can be made to consist of four triangles (see Remark 2.2).We now derive an explicit representation of the position of a vertex surrounded by four such triangles in terms of the other four vertex positions.The center vertex is assumed to be coplanar with each of the two pairs of two opposite vertices,with those two planes becoming the plane of the vertical meridian and the horizontal plane containing a dihedrally symmetric polygonal ring (consisting of edges of the surface).See Figure 4.Lemma 3.1.Suppose we have four vertices p ¼ðd ;0;e Þ,q 1¼ðd cos y ;Àd sin y ;e Þ,q 2¼ða ;0;b Þ,and q 3¼ðd cos y ;d sin y ;e Þ,for given real numbers a ,b ,d ,e ,and angle y so that b 3e .Then there exists a choice of real numbers x and y and a ﬁfth vertex q 4¼ðx ;0;y Þso that the discrete surface formed by the four triangles ðp ;q 1;q 2Þ,ðp ;q 2;q 3Þ,ðp ;q 3;q 4Þ,and ðp ;q 4;q 1Þis minimal ,i.e.‘p area ðstar p Þ¼0;if and only if2ad >ðe Àb Þ21þcos y:Figure 4.The construction in Lemma 3.1and a discrete minimal catenoid.Polthier and Rossman,Curvature surfaces54Furthermore,when x and y exist,they are unique and must be of the formx¼2ð1þcos yÞd3þðaþ2dÞðeÀbÞ2 2adð1þcos yÞÀðeÀbÞ2;y¼2eÀb:Proof.First we note that the assumption b3e is necessary.If b¼e,then one may choose y¼b,and then there is a free1-parameter family of choices of x,leading to a trivial planar surface.For simplicity we apply a vertical translation and a homothety about the origin of R3 to normalize d¼1,e¼0,and by doing a reﬂection if necesary,we may assume b<0.Let c¼cos y and s¼sin y.We derive conditions for the coordinate components of‘p area to vanish.The second component vanishes by symmetry of star ing the deﬁnitionsc1:¼ðaÀ1Þs2Àb2ð1ÀcÞﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃ2b2ð1ÀcÞþðaÀ1Þ2s2q;c2:¼abþbﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃ2b2ð1ÀcÞþðaÀ1Þ2s2q;theﬁrst(resp.third)component of‘p area vanishes ifc1¼y2ð1ÀcÞÀðxÀ1Þs2ﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃ2y2ð1ÀcÞþðxÀ1Þ2s2q;resp:c2¼ÀðxÀ1ÞyÀ2yﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃ2y2ð1ÀcÞþðxÀ1Þ2s2q:ð8ÞDividing one of these equations by the other we obtainxÀ1¼c2yð1ÀcÞþ2c1c2sÀc1yy;ð9Þso x is determined by y.It now remains to determine if one canﬁnd y so that c2s2Àc1y30.If xÀ1is chosen as in equation(9),then theﬁrst minimality condition of equation(8)holds if and only if the second one holds as well.So we only need to insert this value for xÀ1into theﬁrst minimality condition and check for solutions y.When c130, weﬁnd that the condition becomes1¼c2s2Àc1yj c2s2Àc1y jyj y jÀð1ÀcÞy2À2s2ﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃ2ð1ÀcÞc22s4þ4c21s2þÀ2ð1ÀcÞc21þs2ð1ÀcÞ2c22Áy2 q:SinceÀð1ÀcÞy2À2s2<0,note that this equation can hold only if c2s2Àc1y and y have opposite signs,so the equation becomes1¼ð1ÀcÞy2þ2s2ﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃ2ð1ÀcÞc22s4þ4c21s2þÀ2ð1ÀcÞc21þs2ð1ÀcÞ2c22Áy2q;Polthier and Rossman,Curvature surfaces55which simpliﬁes to1¼ﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃð1ÀcÞy2þ2s2 pﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃð1ÀcÞc22s2þ2c21 q:This implies y2is uniquely determined.Inserting the valuey¼G b;oneﬁnds that the above equation holds.When y¼b<0,weﬁnd that c2s2Àc1y<0, which is impossible.When y¼Àb>0,weﬁnd that c2s2Àc1y<0if and only if 2að1þcÞ>b2.And when y¼Àb and2að1þcÞ>b2,we have the minimality condition whenx¼2þ2cþab2þ2b2 2aþ2acÀb:Inverting the transformation we did at the beginning of this proof brings us back to the general case where d and e are not necessarily1and0,and the equations for x and y be-come as stated in the lemma.When c1¼0,we haveðaÀ1Þð1þcÞ¼b2andðxÀ1Þð1þcÞ¼y2,so,in particular, we have a>1and therefore2að1þcÞ>b2.The right-hand side of equation(8)implies y¼Àb and x¼a.Again,inverting the transformation from the beginning of this proof, we have that x and y must be of the form in the lemma for the case c1¼0as well.rThe next lemma provides a necessary and su‰cient condition for when two points lie on a scaled cosh curve,a condition that is identical to that of the previous lemma.That these conditions are the same is crucial to the proof of the upcoming theorem.Lemma3.2.Given two pointsða;bÞandðd;eÞin R2with b3e,and an angle y with j y j<p,there exists an r so that these two points lie on some vertical translate of the modiﬁed cosh curvegðtÞ¼0@r cosh teÀbarccosh1þ1rðeÀbÞ21þcos y!"#;t1A;t A R;if and only if2ad>ðeÀbÞ2 1þcos y.Proof.Deﬁne^d¼eÀb1þcos y.Without loss of generality,we may assume0<a e dand e>0,and henceÀe e b<e.If the pointsða;bÞandðd;eÞboth lie on the curve gðtÞ, thenarccosh1þ^d2r2!¼arccoshdrÀsignðbÞÁarccoshar;Polthier and Rossman,Curvature surfaces 56where signðbÞ¼1if b f0and signðbÞ¼À1if b<0.Note that if b¼0,then a must equalr(and so arccosh a r¼0).This equation is solvable(for either value of signðbÞ)if and only ifd r þﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃd2r2À1r!arþﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃa2r2À1r!¼1þ^d2r2þ^drﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃ2þ^d2r2swhen b e0,ord r þﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃd2rÀ1 sa r þﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃa2rÀ1s¼1þ^d2rþ^drﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃ2þ^d2rswhen b f0,for some r Að0;a .The right-hand side of these two equations has the follow-ing properties:(1)It is a nonincreasing function of r Að0;a .(2)It attains someﬁnite positive value at r¼a.(3)It is greater than the function2^d2=r2.(4)It approaches2^d2=r2asymptotically as r!0.The left-hand sides of these two equations have the following properties:(1)They attain the sameﬁnite positive value at r¼a.(2)Theﬁrst one is a nonincreasing function of r Að0;a .(3)The second one is a nondecreasing function of r Að0;a .(4)The second one attains the value d=a at r¼0.(5)Theﬁrst one is less than the function4ad=r2.(6)Theﬁrst one approaches4ad=r2asymptotically as r!0.It follows from these properties that one of the two equations above has a solution for some r if and only if2ad>^d2.This completes the proof.rWe now derive an explicit formula for discrete minimal catenoids,by specifying the vertices along a planar polygonal meridian.Then the traces of the surfaces will have dihe-dral symmetry of order k f3.The surfaces are tessellated by planar isosceles trapezoids like a Z2grid,and each trapezoid can be triangulated into two triangles by choosing a di-Polthier and Rossman,Curvature surfaces57agonal of the trapeziod as the interior edge.Either diagonal can be chosen,as this does not a¤ect the minimality of the catenoid,by Remark 2.2.The discrete catenoid has two surprising features.First,the vertices of a meridian lie on a scaled smooth cosh curve (just as the proﬁle curve of smooth catenoids lies on the cosh curve),and there is no a priori reason to have expected this.Secondly,the vertical spacing of the vertices along the meridians is constant.Theorem 3.1.There exists a four-parameter family of embedded and complete discrete minimal catenoids C ¼C ðy ;d ;r ;z 0Þwith dihedral rotational symmetry and planar meridians .If we assume that the dihedral symmetry axis is the z-axis and that a meridian lies in the xz-plane ,then ,up to vertical translation ,the catenoid is completely described by the following properties :(1)The dihedral angle is y ¼2p k,k A N ,k f 3.(2)The vertices of the meridian in the xz-plane interpolate the smooth cosh curvex ðz Þ¼r cosh 1raz ;witha ¼r d arccosh 1þ1r 2d 21þcos y!;where the parameter r >0is the waist radius of the interpolated cosh curve ,and d >0is the constant vertical distance between adjacent vertices of the meridian .(3)For any given arbitrary initial value z 0A R ,the proﬁle curve has vertices of the form ðx j ;0;z j Þwithz j ¼z 0þj d ;x j ¼x ðz j Þ;where x ðz Þis the meridian in item 2above .(4)The planar trapezoids of the catenoid may be triangulated independently of each other (by Remark 2.2).Proof.By Lemma 3.1,if we have three consecutive vertices ðx n À1;z n À1Þ,ðx n ;z n Þ,and ðx n þ1;z n þ1Þalong the meridian in the xz -plane,they satisfy the recursion formulax n þ1¼ðx n À1þ2x n Þ^d 2þ2x 3n 2x n x n À1À^d 2;z n þ1¼z n þd ;ð10Þwhere d ¼z n Àz n À1and ^d¼d =ﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃ1þcos y p .As seen in Lemma 3.1,the vertical distance be-Polthier and Rossman,Curvature surfaces58。

非缺血性扩张型心肌病心源性猝死的危险因素

敏感性和特异性较低ꎬ当前基于射血分数( ＥＦ) 的指
南确实导致了大量不必要的ＩＣＤ植入ꎮ 未来的研
究应结合新的心律失常危险标志物的发现和验证ꎬ
以提高ＬＶＥＦ对ＮＩＤＣＭ危险分层的价值ꎮ
性心脏病中ꎬ心肌纤维化是ＶＡ的底物ꎬ瘢痕是正常
回路和“ 瘢痕相关” 室速的产生ꎮ 这一机制也可能
有助于某些ＮＩＤＣＭ患者的室性心动过速〔３６〕 ꎮ 越来
ｍｅｎｔｉａ:ｓｙｓｔｅｍａｔｉｃｒｅｖｉｅｗｐｒｏｔｏｃｏｌ〔Ｊ〕 . ＪＡｄｖＮｕｒｓꎬ２０２０ꎻ７６ (１２ ) :
３６６２￣８
４８ＡｍｊａｄＩꎬＮｉａｚｉＩＫꎬＴｏｏｒＨＧꎬｅｔａｌＡｃｕｔｅｅｆｆｅｃｔｓｏｆａｅｒｏｂｉｃｅｘｅｒｃｉｓｅ
ｏｎｓｏｍａｔｏｓｅｎｓｏｒｙ￣ｅｖｏｋｅｄｐｏｔｅｎｔｉａｌｓｉｎｐａｔｉｅｎｔｓｗｉｔｈｍｉｌｄｃｏｇｎｉｔｉｖｅ
ＤＣＭ的ＳＣＤ风险的关系ꎬ包括ＱＲＳ时限、Ｔ波电交
中国老年学杂志２０２１年２月第４１卷
６７０
替、左束支传导阻滞 ( ＬＢＢＢ ) 、ＱＴｃ、心房颤动等ꎮ
４心脏磁共振( ＣＭＲ) 标志物
者不良结局的一个强有力的独立预测因子ꎮ ＤＣＭ
估ꎬ并通过使用钆对比剂ꎬ提供了心肌瘢痕形成的数
发生水肿的共同作用下ꎬ心肌细胞外间隙增宽ꎬ可以
容纳更多的钆对比剂ꎬ同时亦可表现出延迟强化特
点〔３２〕 ꎮ 其良好的空间分辨率及组织特异性在各种
类型的心肌病变诊断方面具有较好优势〔３３〕 ꎬ 因此
ＬＧＥ被认为是非侵入性评估心肌纤维化的金标
准〔３４〕 ꎮ 早期的荟萃分析已经确认ＬＧＥ是非缺血性

100618003磨合数据

油门　％记录号工况工况名称运行时间　s转速　r∕mi扭矩　N．m功率　kW油耗率　g∕油耗量　kg∕11磨合90080023119.3265.2 5.1320.6 21磨合90079923019.3269.7 5.1721 31磨合90080023119.3264.1 5.0720.9 42磨合60090024523.1268.3 6.1722.1 52磨合60090024322.9268.1 6.1421.9 62磨合60090024423268.5 6.1522.2 73磨合900100026127.4262.47.1323.4 83磨合900100026127.3263.57.223.7 93磨合900100026127.3263.37.1823.5 104磨合600100052054.422412.2326.7 114磨合600100052254.6224.412.2327 124磨合600100052154.5224.112.2327 135磨合900120034843.7265.511.5527.6 145磨合900120034543.3265.711.4928 155磨合900120034543.4266.511.5327.8 166磨合600120060075.4237.217.8731.3 176磨合600120060175.5236.117.7630.6 186磨合600119960075.1236.917.8531.3 197磨合900140043063264.116.6432 207磨合900139843062.9263.716.6132.1 217磨合900140043063.1263.316.6132.5 228磨合6001399690101.1236.823.9837.4 238磨合6001398690101.3236.723.9537.1 248磨合6001400690101.1236.223.8837.1 259磨合6001600700117.3241.328.3443.3 269磨合6001601700117.6241.828.3343.3 279磨合6001600700117.2241.828.3343.5 289磨合6001601700117.2241.928.3643.8 299磨合6001600700117.5239.128.0542.8 309磨合6001597700116.8240.628.1642.8 3110磨合60015981030172.3224.938.8749.3 3210磨合60015981030172.7224.238.6949.7 3310磨合60015981030172.4224.938.7849.8 3410磨合60016011030172.8224.438.8249.6 3510磨合60016021030172.7225.738.8949.8 3610磨合60015981030172.4224.638.850.3 3710磨合60016011030172.6224.938.8350 3810磨合60016021030172.5225.738.9549.7 3910磨合60016021030172.8225.538.9450.1 4011磨合6001800861162.523538.0754 4111磨合6001800861162.4234.938.0754.1 4211磨合6001805860162235.237.9953.7 4311磨合6001795859161.8234.738.0353.9 4411磨合6001793859161.3234.838.0254.7 4511磨合6001805860162.123538.0154.2 4611磨合6001799860162233.938.0754.5 4711磨合6001801860162.3235.138.1152.4 4811磨合6001803860162.2233.337.8152.3 4911磨合6001798860162.623437.9353.1 5011磨合600180086016223437.9452.7 5111磨合6001799860162233.737.9453 5212磨合60017931200225.4225.951.0961 5312磨合60017961200225.9225.151.0660.6 5412磨合60018001200226.2225.551.0560.35512磨合60018011200226.5225.951.1260.6 5612磨合60018001200226225.450.9560.6 5712磨合60018001200225.9226.451.0660.9 5812磨合60017981200225.9225.851.0561 5912磨合60018021200227.3226.251.0460.9 6012磨合60018001200226.422651.1161.6 6112磨合60017991200225.7224.65161.1 6212磨合60018001200225.7225.551.0761 6312磨合60017951200225.5225.951.1361.4 6412磨合60018001200226.1225.851.0660.8 6512磨合60017981200225.8226.551.1961.1 6612磨合60018001200226.722651.1260.9 6713磨合60019051030205.5227.446.7860 6813磨合60019011030205.422846.7460.5 6913磨合60018961029204.4227.446.6661.2 7013磨合60019021030205.3227.446.7760.4 7113磨合60019021030205228.246.7861.2 7213磨合60019001030205.5228.146.7660.8 7313磨合60018971030205.8227.746.761.1 7413磨合60019021031206.5228.346.6960.9 7513磨合60018901030203.4229.646.7661.5 7613磨合60019001030205.9227.146.7261.2 7713磨合60018841029204.7228.846.7361.9 7813磨合60018961030204.2228.646.8560.9 7914磨合60018991300258.9223.558.0465.6 8014磨合60018981301258.3224.157.9966.5 8114磨合60019131305261.4222.557.9866.1 8214磨合60018981300258.1223.857.9466.1 8314磨合60018961301259.5224.157.8766.2 8414磨合60018921298257.6222.957.7666.3 8514磨合60019011300257.5223.257.765.9 8614磨合60019051302260.2223.857.7965.7 8714磨合60018971301261224.157.7165.9 8814磨合60019081302259222.257.7165.5 8914磨合60018991301258.3222.457.5163.8 9014磨合60018971300258.2222.557.4764.3 9114磨合60019021300257.9223.157.7764.1 9214磨合60019041299258.6222.657.6364.7 9314磨合60018961301258222.857.6365.2 9415磨合6001499700109.7238.126.0340.5 9515磨合6001500700109.9238.426.240.4 9615磨合6001499700109.9238.826.2340.3 9715磨合6001497700110238.326.1939.9 9815磨合6001499700109.9238.726.240.1 9915磨合6001498700109.9238.225.8340 10015磨合6001499700109.8238.726.2140.4 10115磨合6001501700110.1238.126.1740.2 10215磨合6001499700110.1237.526.1140.2 10315磨合6001499700109.9237.826.0240.2 10415磨合6001502700110.2237.525.9940.1 10515磨合6001495700109.8237.225.8940.4 10616磨合60012971200162.9212.834.7444.3 10716磨合60012981200163211.234.4444 10816磨合60012991200163.4213.634.7944.6 10916磨合60012991200163.2213.434.6844.311016磨合60012961200162.9212.734.7244.4 11116磨合60012991200163.4212.234.6144.3 11216磨合60012951200162.6212.534.6344.6 11316磨合60012961200162.9210.734.3844.5 11416磨合60013011200163.3209.234.0744.3燃油温度　℃机油压力　k机油温度　℃大气压力　k环境温度　℃相对湿度　％中冷后温　℃中冷前压　k中冷后压　k中冷前温　℃3.5 5.542.233.538101.13728.534188.83.3 5.342.925.334.6101.238.328.734387.73.2 5.243.217.333101.239.428.733590.27.28.941.831.551.210131.227.944382.87.59.144.426.546.9101.132.928.339688.76.98.644.816.238.4101.236.128.539587.19.71148.420.433.410137.828.843489.19.511.249.818.131.1101.139.429430899.311.150.216.728.2101.140.729.241491.621.823.460.820.527101.24229.341290.621.823.461.722.924.8101.243.729.441190.821.523.16223.322.8101.345.129.440891.325.526.666.627.121.7101.346.329.6517912526.166.42820.7101.446.929.6508922526.265.82820101.447.329.652090.3495085.838.619.1101.448.229.748893.451.25283.841.937.9101.137.42949892.947.748.695.24725.7101.247.830.449192.450.350.285.34149101.136.829.659590.849.949.986.740.940.7101.240.23057792.149.549.687.241.634.3101.342.730.257492.380.680.4111.84631.5101.344.530.455194.180.379.7112.241.928.4101.44630.554794.579.479.2112.141.727.1101.547.230.654794.5989712743.425.6101.548.430.959696.398.897.3128.14324.3101.549.331.159296.798.597127.843.323.4101.65031.259396.697.496.4128.142.823.1101.650.331.259296.699.698121.142.653.110134.738.660994.39997.5123.342.845.610137.339.160295.1 132.1129.9146.841.939101.140.230.757997.4 129.8127.5149.842.629.510140.840.259095.7 128.2126.3151.442.72510144.243.257697.3 129.7127.6152.543.122.2101.146.944.357197.8 129.4127.6152.143.319.7101.249.333.557097.9 129127.215343.618.1101.351.138.356798.1 128.1126153.642.116.7101.452.63856698.2 127.5125.7153.743.115.6101.453.837.656498.4 128.8127154.343.614.6101.554.938.356298.4 122119.4153.542.414.2101.555.437.960599.5 123.2120.115342.514.1101.655.63860499.5 122119.3151.942.814.1101.655.738.160599.6 122.3119.8151.14313.9101.655.737.960299.7 123.3120.6150.243.113.6101.65637.960099.8 122119.7152.943.713.6101.656.43860299.8 123120.1151.842.613.7101.656.437.960099.8 127.2124.3138.442.743.4101.433.836.662396.3 127.8124.7140.742.836.7101.436.537.761597.8 127.1124.2141.442.732.2101.538.937.761098.3 127.7124.9142.843.128.8101.640.937.561098.8 126.9124.1143.54326.3101.742.737.760898.8 162.5158.9166.143.323.3101.84538.3591100.9 162158.5166.843.921101.94737.6589101.1 161157.7167.243.318.110249.337.9589101.2160.6156.9167.443.316.21025138.1588101.2 159.8156.3168.443.215102.152.338.6588101.2 159.7156167.942.614.5102.152.938.5586101.5 159.1155.5168.642.313.7102.253.938.2584101.6 160.3156.6167.942.813.3102.254.537.5583101.6 159.3155.8169.743.713.1102.254.937.8583101.6 157.7154.216943.312.6102.355.638.3584101.4 157.7154.1167.941.912.2102.356.137.6583101.4 159155.8168.242.511.9102.356.637.9582101.6 158.9155.216943.511.7102.456.838.2581101.6 158.7155.1167.143.311.1102.357.337.6580101.7 159.2155.7166.743.510.7102.45837.7580101.5 141.513816043.611102.457.538.1592101.7 142.4138.7159.843.711.7102.456.837.8592101.7 142.7139.4158.643.111.7102.456.438.1590101.7 141.9138.51594311.7102.356.138590101.7 142.1138.6159.443.111.6102.355.537.7590101.7 141.8138.2160.443.111.6102.355.338.1589101.8 140.7137.4159.142.811.6102.355.137.7590101.7 142.5139.1159.343.111.4102.35538.1590101.7 140.2136.8159.142.711.2102.355.237.8589101.7 139.8136.4160.743.211.5102.354.838.1590101.7 141.4137.9159.143.112.1102.354.637.5587101.7 141.5138159.643.112.2102.354.637.6589101.7 167.1162.9175.143.411.9102.35537.5577103.6 1671631754311.7102.355.538.2575103.8 167.5162.9175.543.211.4102.455.738.4576103.9 166.7162.6177.243.811.3102.455.937.5575103.8 167.3163.2175.844.411.1102.456.237.8577103.6 166.3162.3175.644.911102.456.538.3578103.5 165.8161.8176.444.710.9102.456.738579103.3 168.4163.9174.644.110.6102.456.937.6580103.3 165.2161.3176.243.910.8102.456.938.4578103.4 166161.9175.144.510.7102.456.938580103.3 165.8161.3164.842.431.1101.632.939.3604102.2 166161.6167.142.826.4101.736.138.8592103.7 166.6162.316943.223101.83937.1589104.6 167.4162.9170.243.219.6101.941.537.4588104.9 166.3161.7170.843.117.310243.837.5586105.1 88.187.2114.442.51510246.138.154597.3 87.987.411542.613.2102.147.238.154996.7 87.286.5115.342.512.3102.24837.954896.8 87.487.1114.74311.6102.248.837.854696.9 87.687.1115.14311.7102.349.537.754197.5 86.185.5113.642.511.1102.350.437.653498.4 88.187.1113.943.711.2102.350.637.355495.5 87.487.1114.744.210.9102.350.937.254596.7 87.58711544.310.8102.351.337.454396.8 86.885.9115.943.110.6102.351.23854396.8 86.786.1116.14210.2102.351.338.254397 85.885.3116.341.79.9102.352.138.354296.8 114.2113.5135.143.89.4102.35437.645298.4 113.3113134.643.88.7102.455.737.4438100.5 113.1113.3133.444.38.4102.557.137.845298 113113.2134.642.58102.558.137.845397.9112.1112135.342.77.6102.558.837.945297.7 112.2111.9134.743.27.6102.559.337.745397.9 111.6111.3135.143.37.2102.659.83844898.4 111.4111.9135.1437.1102.659.838.344399.2 112.1112.3135.242.7 6.9102.66038.644698.7排气背压　k进气负压　k记录时间进气温度　℃涡后温度　℃进水温度　℃出水温度　℃84.786.819537.30.7-0.12010-09-16 15:54:4879.280.419838.10.6-0.12010-09-16 16:09:4880.985.820038.20.7-0.12010-09-16 16:24:4940.258.520634.30.7-0.12010-09-17 09:39:25648121336.40.6-0.12010-09-17 09:49:2635.48121237.60.7-0.12010-09-17 10:16:4777.483.621938.21-0.12010-09-17 14:17:3078.381.922339.40.9-0.12010-09-17 14:32:3084.281.322440.11-0.12010-09-17 14:47:3045.581.532240.3 1.1-0.12010-09-17 14:57:30748332841.1 1.4-0.12010-09-17 15:07:3172.883.233041.4 1.5-0.12010-09-17 15:17:3156.581.629442 1.9-0.12010-09-17 15:32:3181.683.729441.6 1.7-0.12010-09-17 15:47:3138.580.829441.3 1.7-0.12010-09-17 16:02:3176.384.137542.8 2.5-0.12010-09-17 16:12:3177.98536540.6 2.3-0.12010-09-18 09:49:5135.381.738250.7 2.4-0.22010-09-19 16:13:0332.281.433342.6 2.7-0.42010-09-20 09:42:1134.881.533643 2.9-0.42010-09-20 09:57:1236.480.933643.73-0.32010-09-20 10:12:1244.778.338346.24-0.52010-09-20 10:22:1248.682.438046.5 4.1-0.52010-09-20 10:32:1250.382.537846.3 4.2-0.52010-09-20 10:42:1249.282.536448.4 5.8-0.92010-09-20 10:52:1259.383.236248.9 5.8-0.92010-09-20 11:02:1357.282.936048.2 6.2-0.82010-09-20 11:12:135882.936048.8 5.9-0.92010-09-20 11:22:1359.583.234043.86-12010-09-21 07:55:1850.382.634945.4 5.7-0.92010-09-21 08:05:1949.282.840247.38.5-1.32010-09-21 08:15:1955.182.839052.48.6-1.12010-09-21 13:55:5242.882.340454.38.4-1.12010-09-21 14:05:5246.982.441154.78.6-1.12010-09-21 14:15:5243.282.341455.58.6-1.32010-09-21 14:25:5244.682.341655.28.5-1.12010-09-21 14:35:5345.680.541555.98.3-12010-09-21 14:45:5347.982.541554.58.6-1.12010-09-21 14:55:5348.182.541655.98.4-12010-09-21 15:05:5358.683.238257.79.3-1.32010-09-21 15:15:5352.482.838057.59.5-1.32010-09-21 15:25:5352.582.837854.89.7-1.42010-09-21 15:35:545382.237855.49.7-1.22010-09-21 15:45:5456.482.837753.29.3-1.42010-09-21 15:55:5453.382.837856.69.6-1.42010-09-21 16:05:5453.382.837555.59.6-1.42010-09-21 16:15:5433.282.335742.89.9-1.62010-09-22 09:15:3736.782.436444.39.8-1.62010-09-22 09:25:3839.182.537145.69.5-1.42010-09-22 09:35:384182.537445.89.8-1.52010-09-22 09:45:3842.682.637646.19.5-1.52010-09-22 09:55:3843.382.843555.113.7-1.82010-09-22 10:05:3845.482.943749.513.7-1.92010-09-22 10:15:3844.182.74369413.6-1.72010-09-22 10:25:3942.581.443696.313.7-1.72010-09-22 10:35:3942.882.843552.313.7-1.82010-09-22 10:45:3943.582.943466.313.8-1.82010-09-22 10:55:39 43.882.943454.913.7-1.82010-09-22 11:05:39 4482.84336713.8-1.72010-09-22 11:15:40 44.18243451.813.7-1.92010-09-22 11:25:40 44.282.943349.513.6-1.82010-09-22 11:35:40 43.982.943148.213.5-1.82010-09-22 11:45:4043.782.943148.913.9-1.62010-09-22 11:55:4044.182.743349.813.7-1.82010-09-22 12:05:40 4481.643148.413.8-1.72010-09-22 12:15:41 44.382.943051.213.6-1.82010-09-22 12:25:41 41.582.739950.612.8-1.82010-09-22 12:35:41 41.282.739849.913-1.82010-09-22 12:45:41 4182.639749.712.9-1.72010-09-22 12:55:41 40.782.139848.712.9-1.82010-09-22 13:05:41 40.978.939952.413-1.72010-09-22 13:15:42 40.882.740052.812.7-1.82010-09-22 13:25:42 40.682.639949.312.8-1.72010-09-22 13:35:42 40.382.639949.413.1-1.92010-09-22 13:45:42 40.581.839949.312.7-1.82010-09-22 13:55:42 40.578.140151.712.8-1.82010-09-22 14:05:42 40.482.740049.512.9-1.82010-09-22 14:15:43 40.382.640151.312.7-1.72010-09-22 14:25:4342.582.94495216.5-2.12010-09-22 14:35:4343.882.844951.516.4-1.92010-09-22 14:45:4344.381.145053.417.1-2.22010-09-22 14:55:43 46.382.945154.116.1-2.22010-09-22 15:05:44 45.182.945051.516.6-2.12010-09-22 15:15:44 458345050.816.1-22010-09-22 15:25:44 45.182.945154.316.5-2.22010-09-22 15:35:44 45.381.744952.116.9-2.12010-09-22 15:45:44 49.183.345152.516.1-2.22010-09-22 15:55:44 45.682.945048.616.5-2.12010-09-22 16:05:45 5983.443340.416.9-2.32010-09-23 09:23:11 74.785.444242.916.7-2.22010-09-23 09:33:11 76.58544644.316.5-2.32010-09-23 09:43:11 76.4854494516.2-2.22010-09-23 09:53:12 76.38545147.916.2-2.12010-09-23 10:03:12 68.182.837343.45-0.62010-09-23 10:13:1270.183.237242.6 4.6-0.72010-09-23 10:23:1271.383.437243.2 5.2-0.62010-09-23 10:33:1272.883.537243.2 5.1-0.62010-09-23 10:43:13 77.183.937243.8 5.2-0.62010-09-23 10:53:13 8283.637043 5.2-0.62010-09-23 11:03:13 76.384.437143.6 4.9-0.72010-09-23 11:13:13 73.68437145.2 5.1-0.72010-09-23 11:23:13 73.483.937145.3 5.1-0.72010-09-23 11:33:1473.183.937044.45-0.62010-09-23 11:43:1474.284.237046.8 5.2-0.62010-09-23 11:53:14 72.983.536946.2 4.9-0.62010-09-23 12:03:14 78.984.445346.4 5.3-0.72010-09-23 12:13:14 83.284.245545.2 5.4-0.72010-09-23 12:23:15 61.782.745244.7 5.6-0.62010-09-23 12:33:15 69.583.945045.4 5.5-0.72010-09-23 12:43:1568.483.445045.6 5.6-0.62010-09-23 12:53:1569.483.645045.4 5.6-0.72010-09-23 13:03:15 74.58444945.7 5.5-0.72010-09-23 13:13:15 80.783.744846.3 5.6-0.72010-09-23 13:23:16 82.387.344746.7 5.6-0.72010-09-23 13:33:16。

基于深度学习的新型妇科后装施源器自动重建系统研发

Research and development of a novel automatic reconstruction system based on deep learning for gynecological applicator/Zhang Wenjun, Yu Lang, Zhang Jie, Y ang Bo, Luo Chunli, Qiu JieDepartment of Radiation Oncology, Chinese Academy of Medical Sciences, Peking Union Medical College, Peking Union Medical College Hospital, Beijing 100730, China Corresponding author: [Abstract] Objective: We have developed a deep learning-based automatic reconstruction system for applicators, aiming to achieve efficient and accurate automatic reconstruction of Fletcher applicators in computed tomography (CT)-guided gynecological brachytherapy. Methods: The automatic reconstruction system of applicator was divided into two main parts. One part was an applicator mask on CT images that was split by 2.5D DpnUNet, and other part was a digitized centerline of the applicator channel that was obtained through three-dimensional (3D) connected region algorithm and skeleton extraction algorithm. The documents of 68 patients who received gynecological brachytherapy in Peking Union Medical College Hospital from July of 2022 to July of 2023 were selected. The CT plans of 10 patients of them were used as test set, and the CT plans of other 58 patients were used to train by adopting 10-fold cross validation method. The comparison of geometric consistency was conducted between the results of developed automatic reconstruction system and the results of manual reconstruction. The high risk clinical target volume (HR-CTV), 90% and 98% dose target volume (D 90, D 98) of dosimetric indicators, as well as the minimum dose (D 2cc ) within 2cc volume that received maximum exposure dose on bladder, rectum, sigmoid colon and small intestine, were designed and obtained through the 3D rear mounted reverse optimization plan. And then, the clinical feasibility of the automatic reconstruction system was further explored. Results: In the data of 10 patients of test set, the average distances of automatic reconstruction, manual reconstruction and the top-end of the centerline of left-right fornix canal were respectively 0.335, 0.361 and 0.362 mm. The average Hausdorff distances between the centerlines were respectively 0.398, 0.367 and 0.324 mm. Additionally, the differences of dose-volume histogram (DVH) parameters between the two types of plans was less than 2% under kept the consistency between location and duration of stay. There were very high geometric consistency and clinical value between the two types of plans. Conclusion: The automatic reconstruction system of applicators can realize fully-automatic reconstruction with high-precision of Fletcher applicators, and reduce the probability of potential human error and improve clinical work efficiency. [Key words] Deep learning; Brachytherapy; Gynecological applicatorFund programs: Central High-level Hospital Clinical Research Project on the Research and Clinical Application of Innovative T echnologies in Brachytherapy (2022-PUMCH-B-052); Peking Union Medical College and the National High Level Hospital Clinical Research Funding(2022-PUMCH-A-101)[摘要] 目的：开发一种基于深度学习的施源器自动重建系统，以实现CT引导妇科近距离治疗中Fletcher施源器高效准确地自动重建。

碧云天生物技术 Min6 (小鼠胰岛β细胞) 产品说明书

碧云天生物技术/Beyotime Biotechnology订货热线：400-168-3301或800-8283301订货e-mail：******************技术咨询：*****************网址：碧云天网站微信公众号Min6 (小鼠胰岛β细胞)产品编号产品名称包装C7406 Min6 (小鼠胰岛β细胞) 1支/瓶产品简介：Organism Tissue Morphology Culture Properties Mus musculus (Mouse) Pancreas Epithelial Adherent本细胞株详细信息如下:General InformationCell Line Name Min6 (Mouse Islet Β Cells)Synonyms Min6; MIN-6; Mouse INsulinoma 6Organism Mus musculus (Mouse)Tissue PancreasCell Type －Morphology EpithelialDisease Mouse insulinomaStrain －Biosafety Level* －Age at Sampling 13 weeksGender －Genetics －Ethnicity －Applications －Category Transformed cell line* Biosafety classification is based on U.S. Public Health Service Guidelines, it is the responsibility of the customer to ensure that their facilities comply with biosafety regulations for their own country.CharacteristicsKaryotype －Virus Susceptibility －Derivation －Clinical Data －Antigen Expression －Receptor Expression －Oncogene －Genes Expressed －Gene expressiondatabases －Metastasis －Tumorigenic －Effects －Comments －Culture MethodDoubling Time －Methods for Passages Wash by PBS once then 0.05% trypsin-EDTA solution and incubate at room temperature, observe cells under an inverted microscope until cell layer is dispersed (usually 1 minute)Medium DMEM (high glucose) 10% FBS+0.05mM 2-Mercaptoethanol MCH2 / 5 C7406 Min6 (小鼠胰岛β细胞)400-1683301/800-8283301 碧云天/BeyotimeSpecial Remarks －Medium Renewal －Subcultivation Ratio 1:5 to 1:15 Growth Condition 95% air+ 5% CO 2, 37ºC Freeze medium DMEM (high glucose)+20% FBS+10% DMSO ，也可以订购碧云天的细胞冻存液(C0210)。

原发性闭角型青光眼动物模型研究进展

原发性闭角型青光眼动物模型研究进展潘金花;赵瑛;相波;宋姗姗【摘要】青光眼是一组伴有特征性视神经损害和视野缺损的视神经病变,是世界上三大致盲性眼病之一.青光眼性失明,就目前医学治疗手段而言是无法使其逆转而恢复的.目前关于青光眼的发病机制还不清楚.但可以明确的是高眼压是造成青光眼的危险因素.因此在青光眼研究领域中,利用动物模型来研究青光眼的发病机制或治疗等已经成为必不可少的研究工具.本文主要概述了近些年来关于原发性角闭型青光眼高眼压动物模型的研究进展.【期刊名称】《中医眼耳鼻喉杂志》【年(卷),期】2017(007)003【总页数】5页(P161-165)【关键词】原发性闭角型青光眼;动物模型;综述【作者】潘金花;赵瑛;相波;宋姗姗【作者单位】610075,四川成都,成都中医药大学;610075,四川成都,成都中医药大学;610075,四川成都,成都中医药大学;610075,四川成都,成都中医药大学【正文语种】中文【中图分类】R775青光眼有很多种分类方法,可以根据病因学,解剖学和发病机制等分类,通常主要分为原原发性开角型青光眼(Primary Open Angle Glaucoma,POAG),原发性闭角型青光眼(Primary Angle Closure Glaucoma PACG),原发性先天性青光眼(PrimaryCongenital Glaucoma,PCG)等三大类。

西方国家青光眼患病人数中POAG 和PCG 是最常见的类型[1],而亚洲地区主要是以开角型青光眼为主。

Quigley[2]等根据世界各地以人群为基础的流行病学研究,用联合国2010年和2020年世界人口推算,2010年全球青光眼人数将达到6050万,而到2020年青光眼人数将增加到7960万。

原发性闭角型青光眼主要分布于亚洲,尤其是我国最常见[3]。

青光眼的发病机制目前主要有机械压力学说和血管缺血学说,目前青光眼的发病机制尚不清楚,但是高眼压是最主要的危险因素。