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Encyclopedia of Robotics

為了解決Respectively的問題，作者 這樣論述：

Dr. Marcelo H. Ang, Jr., received the B.S. degrees (Cum Laude) in Mechanical Engineering and Industrial Management Engineering from the De La Salle University, Manila, Philippines, in 1981; the M.S. degree in Mechanical Engineering from the University of Hawaii at Manoa, Honolulu, Hawaii, in 1985; a

nd the M.S. and Ph.D. degrees in Electrical Engineering from the University of Rochester, Rochester, New York, in 1986 and 1988, respectively. His work experience include heading the Technical Training Division of Intel’s Assembly and Test Facility in the Philippines, research positions at the East

West Center in Hawaii and at the Massachusetts Institute of Technology, and a faculty position as an Assistant Professor of Electrical Engineering at the University of Rochester, New York. In 1989, Dr. Ang joined the Department of Mechanical Engineering of the National University of Singapore, where

he is currently an Associate Professor. In addition to academic and research activities, he is actively involved in the Singapore Robotic Games as its founding chairman. His research interests span the areas of robotics, mechatronics, automation, computer control and applications of intelligent sys

tems methodologies.Prof. Dr. Oussama Khatibis Professor of Computer Science, Artificial Intelligence Laboratory, Department of Computer Science, Stanford University, California, USA. His research interests are methodologies and technologies of autonomous robots, cooperative robots, human-centered ro

botics, haptic interaction, dynamic simulation, virtual environments, augmented tele operation and human-friendly robot design.Prof. Dr. Bruno Sicilianowas born in Naples, Italy, on October 27, 1959. He received the Laurea degree and the Research Doctorate degree in Electronic Engineering from the U

niversity of Naples in 1982 and 1987, respectively. He is Professor of Control and Robotics and Director of the PRISMA Lab in the Department of Electrical Engineering and Information Technology at University of Naples. His research interests include identification and adaptive control, impedance and

force control, visual tracking and servoing, redundant and cooperative manipulators, lightweight flexible arms, aerial robots, human-centered and service robotics. He has co-authored 11 books, 70 journal papers, 200 conference papers and book chapters; his book Robotics: Modelling, Planning and Contr

ol is one of the most widely adopted textbooks worldwide. He has delivered more than 100 invited lectures and seminars at institutions worldwide. He is a Fellow of IEEE, ASME and IFAC. He is Co-Editor of the Springer Tracts in Advanced Robotics series, and has served on the editorial boards of sever

al journals as well as Chair or Co-Chair for numerous international conferences. He co-edited the Springer Handbook of Robotics, which received the AAP PROSE Award for Excellence in Physical Sciences & Mathematics and was also the winner in the category Engineering & Technology. His group has been g

ranted twelve European projects. He has served the IEEE Robotics and Automation Society as President, as Vice-President for Technical Activities and Vice-President for Publications, as a member of the AdCom and as a Distinguished Lecturer.

Respectively進入發燒排行的影片

父母親身體狀況與嬰幼兒先天性缺陷之關聯性研究

為了解決Respectively的問題，作者陳悠祈 這樣論述：

隨著社會經濟壓力逐漸增大，晚婚生子成了趨勢。根據內政部人口統計，西元2019年台灣女性生育第一胎年齡在35歲以上者高達23％，約為西元2009年的2.4倍。高齡產婦的增加，導致妊娠糖尿病、羊水過多、懷孕引起之高血壓等妊娠風險上升，進而造成出生兒的先天性缺陷風險增加。近來，商業保險中的婦嬰險推展，不僅提供產婦保障，同時為新生兒帶來保障。且因應客戶需求，不再侷限於孩子一兩年短期的保障，也觀察其多年後的情形，加強對特定先天缺陷及相關住院、手術醫療面的給付。此外，一般保險公司在提供此保障時，產婦需要填寫健康告知聲明書，藉此預測未來承保的風險，然而父親對嬰幼兒先天缺陷隱含的潛在危險因子可能仍需

再列入考量。因此本研究期望透過「衛生福利部衛生福利資料科學中心」所提供之資料，藉由廣義線性模型，探討2004年至2017年0-7歲嬰幼兒之先天缺陷與父母親危險因子的關聯性。 研究顯示，觀察西元2004年至2017年的2,326,774位新生兒，其0-7歲罹患先天缺陷的機率為4.067%，當中約有20%的先天缺陷者於2歲後才發覺。在其他條件皆相同之下，父親年齡、母親年齡增加十歲時，則會分別使嬰幼兒其先天缺陷率提高為原本的1.013倍（95%CI=0.995-1.031）、1.185倍（95%CI=1.162-1.209）。而母親有任一懷孕危險因子所生育的嬰幼兒其先天缺陷率(例如:心臟疾病、

孕期抽煙、妊娠糖尿病)則是母親無任一懷孕危險因子的1.144倍（95%CI=0.995-1.314）-2.003倍（95%CI=1.932-2.077）之間。希望藉由本研究所得先天缺陷相關資訊，提供保險公司作為訂價上風險的評估，也使雙親藉由事先瞭解懷孕的危險因子能有效做好相關的預防措施，在生育的路上更加順利。

Encyclopedia of Robotics

為了解決Respectively的問題，作者 這樣論述：

Dr. Marcelo H. Ang, Jr., received the B.S. degrees (Cum Laude) in Mechanical Engineering and Industrial Management Engineering from the De La Salle University, Manila, Philippines, in 1981; the M.S. degree in Mechanical Engineering from the University of Hawaii at Manoa, Honolulu, Hawaii, in 1985; a

nd the M.S. and Ph.D. degrees in Electrical Engineering from the University of Rochester, Rochester, New York, in 1986 and 1988, respectively. His work experience include heading the Technical Training Division of Intel’s Assembly and Test Facility in the Philippines, research positions at the East

West Center in Hawaii and at the Massachusetts Institute of Technology, and a faculty position as an Assistant Professor of Electrical Engineering at the University of Rochester, New York. In 1989, Dr. Ang joined the Department of Mechanical Engineering of the National University of Singapore, where

he is currently an Associate Professor. In addition to academic and research activities, he is actively involved in the Singapore Robotic Games as its founding chairman. His research interests span the areas of robotics, mechatronics, automation, computer control and applications of intelligent sys

tems methodologies.Prof. Dr. Oussama Khatibis Professor of Computer Science, Artificial Intelligence Laboratory, Department of Computer Science, Stanford University, California, USA. His research interests are methodologies and technologies of autonomous robots, cooperative robots, human-centered ro

botics, haptic interaction, dynamic simulation, virtual environments, augmented tele operation and human-friendly robot design.Prof. Dr. Bruno Sicilianowas born in Naples, Italy, on October 27, 1959. He received the Laurea degree and the Research Doctorate degree in Electronic Engineering from the U

niversity of Naples in 1982 and 1987, respectively. He is Professor of Control and Robotics and Director of the PRISMA Lab in the Department of Electrical Engineering and Information Technology at University of Naples. His research interests include identification and adaptive control, impedance and

force control, visual tracking and servoing, redundant and cooperative manipulators, lightweight flexible arms, aerial robots, human-centered and service robotics. He has co-authored 11 books, 70 journal papers, 200 conference papers and book chapters; his book Robotics: Modelling, Planning and Contr

ol is one of the most widely adopted textbooks worldwide. He has delivered more than 100 invited lectures and seminars at institutions worldwide. He is a Fellow of IEEE, ASME and IFAC. He is Co-Editor of the Springer Tracts in Advanced Robotics series, and has served on the editorial boards of sever

al journals as well as Chair or Co-Chair for numerous international conferences. He co-edited the Springer Handbook of Robotics, which received the AAP PROSE Award for Excellence in Physical Sciences & Mathematics and was also the winner in the category Engineering & Technology. His group has been g

ranted twelve European projects. He has served the IEEE Robotics and Automation Society as President, as Vice-President for Technical Activities and Vice-President for Publications, as a member of the AdCom and as a Distinguished Lecturer.

An Integrated Approach For Uncovering Novel DNA Methylation Biomarkers For Non-small Cell Lung Carcinoma

為了解決Respectively的問題，作者VAIBHAV KUMAR SUNKARIA 這樣論述：

Introduction - Lung cancer is one of primal and ubiquitous cause of cancer related fatalities in the world. Leading cause of these fatalities is non-small cell lung cancer (NSCLC) with a proportion of 85%. The major subtypes of NSCLC are Lung Adenocarcinoma (LUAD) and Lung Small Cell Carcinoma (LUS

C). Early-stage surgical detection and removal of tumor offers a favorable prognosis and better survival rates. However, a major portion of 75% subjects have stage III/IV at the time of diagnosis and despite advanced major developments in oncology survival rates remain poor. Carcinogens produce wide

spread DNA methylation changes within cells. These changes are characterized by globally hyper or hypo methylated regions around CpG islands, many of these changes occur early in tumorigenesis and are highly prevalent across a tumor type.Structure - This research work took advantage of publicly avai

lable methylation profiling resources and relevant comorbidities for lung cancer patients extracted from meta-analysis of scientific review and journal available at PubMed and CNKI search which were combined systematically to explore effective DNA methylation markers for NSCLC. We also tried to iden

tify common CpG loci between Caucasian, Black and Asian racial groups for identifying ubiquitous candidate genes thoroughly. Statistical analysis and GO ontology were also conducted to explore associated novel biomarkers. These novel findings could facilitate design of accurate diagnostic panel for

practical clinical relevance.Methodology - DNA methylation profiles were extracted from TCGA for 418 LUAD and 370 LUSC tissue samples from patients compared with 32 and 42 non-malignant ones respectively. Standard pipeline was conducted to discover significant differentially methylated sites as prim

ary biomarkers. Secondary biomarkers were extracted by incorporating genes associated with comorbidities from meta-analysis of research articles. Concordant candidates were utilized for NSCLC relevant biomarker candidates. Gene ontology annotations were used to calculate gene-pair distance matrix fo

r all candidate biomarkers. Clustering algorithms were utilized to categorize candidate genes into different functional groups using the gene distance matrix. There were 35 CpG loci identified by comparing TCGA training cohort with GEO testing cohort from these functional groups, and 4 gene-based pa

nel was devised after finding highly discriminatory diagnostic panel through combinatorial validation of each functional cluster.Results – To evaluate the gene panel for NSCLC, the methylation levels of SCT(Secritin), FOXD3(Forkhead Box D3), TRIM58(Tripartite Motif Containing 58) and TAC1(Tachikinin

1) were tested. Individually each gene showed significant methylation difference between LUAD and LUSC training cohort. Combined 4-gene panel AUC, sensitivity/specificity were evaluated with 0.9596, 90.43%/100% in LUAD; 0.949, 86.95%/98.21% in LUSC TCGA training cohort; 0.94, 85.92%/97.37 in GEO 66

836; 0.91,89.17%/100% in GEO 83842 smokers; 0.948, 91.67%/100% in GEO83842 non-smokers independent testing cohort. Our study validates SCT, FOXD3, TRIM58 and TAC1 based gene panel has great potential in early recognition of NSCLC undetermined lung nodules. The findings can yield universally accurate

and robust markers facilitating early diagnosis and rapid severity examination.