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閩南—西班牙文獻叢刊三：明心寶鑑

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　　《明心寶鑑》抄譯本收藏於西班牙馬德里國家圖書館，此書是十四世紀以來流行於東亞各地的書籍，為童蒙用書與善書，內容抄撮各種書籍中的嘉言警語，作為修身、行世之用。十六世紀下半葉閩南人至馬尼拉經商、住居，亦將此類日用書籍帶至馬尼拉。《明心寶鑑》抄譯本由西班牙道明會傳教士嗃呣????（Juan Cobo）與馬尼拉唐人合作抄譯，約完成於1590年前後，具體呈現大航海時代閩南人與西班牙語世界的交流過程與成果，為人類「世界記憶」（Memory of the World）的重要資產。   　　The translated transcription of the Beng Sim Po Ca

m was a collection of the Biblioteca Nacional de España in Madrid. A popular book that had been circulating in East Asia since the fourteenth century, it was used for children's enlightenment and moral guidance. It collected proverbs and warnings from various texts which were meant to cultivate mora

l character and advise on choices in life. When Hokkien people arrived in Manila in late sixteenth century for trade and settlement, they also brought books of daily use like this one to Manila. The translated transcription of the Beng Sim Po Cam was transcribed by Spanish Dominican missionary Juan

Cobo with help from Chinese in Manila. It was completed around 1590, and it definitely presented the process and achievements of Hokkien-Spanish interaction during the Age of Discovery. It is also an important and precious asset of "Memory of the World" for the mankind.

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

為了解決Korea Time Taiwan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.

Advances in Data Science and Information Engineering: Proceedings from Icdata 2020 and Ike 2020

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Robert Stahlbock is a researcher and lecturer at the Institute of Information Systems at the University of Hamburg. He is also lecturer at the FOM University of Applied Sciences since 2003. He holds a diploma in Business Administration and a PhD from the University of Hamburg. His research interests

are focused on managerial decision support and issues related to maritime logistics and other industries as well as operations research, information systems, business intelligence and data science. He is author of research studies published in international prestigious journals, conference proceedi

ngs and book chapters. He serves as guest editor of data science related books, as reviewer for international leading journals as well as a member of conference program committees. He is General Chair of the annual International Conference on Data Science since 2006. He also consults companies in va

rious sectors and projects. Dr. Gary Weiss is an associate professor in the Department of Computer and Information Science at Fordham University. His main research area is data mining. His early research focused on real-world issues that make learning from data difficult, such as class imbalance. Ov

er the last decade he has directed the WIreless Sensor Data Mining (WISDM) lab, and has focused on extracting knowledge from sensors on smartphones and smartwatches, mainly to perform automated activity recognition and behavioral biometrics. He is currently devoting much of his attention to data min

ing of educational data. Dr. Weiss has published over ninety papers in Data Mining and other areas of Computer Science. Dr. Weiss received his B.S. in Computer Science from Cornell University, his M.S. in Computer Science from Stanford University, and his Ph.D. in Computer Science from Rutgers Unive

rsity. Prior to starting work at Fordham University in 2004, Dr. Weiss spent more than 15 years working for AT&T Labs. Dr. Mahmoud Abou-Nasr, Adjunct Faculty, CIS Department, University of Michigan Dearborn, USA. Technical Expert, Neural Networks & Intelligent Systems, Research & Advanced Engineerin

g, Ford Motor Company, USA (1993-2018). Dr. Abou-Nasr is a Senior Member of the IEEE and Vice Chair Technical Activities Computational Intelligence & Systems Man and Cybernetics SEM Chapter (2011-2014). He has received the B.Sc. degree in Electrical Engineering in 1977 from the University Of Alexand

ria, Alexandria, Egypt, the M.S. and the Ph.D. degrees in 1984 and 1994 respectively from the University Of Windsor, Ontario, Canada, both in Electrical Engineering. He has been a Technical Expert with Ford Motor Company, Research and Advanced Engineering, where he led research & development of deep

learning, recurrent neural networks and advanced computational intelligence techniques for automotive applications. His research interests are in the areas of deep learning, deep convolutional networks, recurrent neural networks, reinforcement learning, pattern recognition, forecasting, data mining

, optimization and control. Currently he is an adjunct faculty member of the computer and information science department, of the University of Michigan Dearborn. Prior to joining Ford, he held electronics and software engineering positions with the aerospace and robotics industries in the areas of r

eal-time control and embedded communications protocols. He is a co-editor of a book on ＂Real World Data Mining Applications,＂ Annals of Information Systems, Springer and associate editor of the DMIN’09-DMIN’17, ICDATA’18-ICDATA’19 proceedings. He is a member of the program and technical committees o

f IJCNN, WCCI, ISVC and ECAI. He is also a reviewer for IJCNN, MSC, CDC, Neural Networks and IEEE Transactions on Neural Networks & Learning Systems. Dr. Abou-Nasr has organized and chaired symposia & special sessions in SSCI16, WCCI 2015, DMIN and IJCNN conferences as well as international classifi

cation competitions in WCCI Hong Kong (2008) and IJCNN San Jose, CA (2011).Professor Cheng-Ying Yang received the M.S. degree in Electronic Engineering from Monmouth University, New Jersey, and Ph.D. degree from the University of Toledo, Ohio. He is a member of IEEE Satellite & Space Communication S

ociety. Also, he has the editorships of International Journal of Network Security and International Journal of Electronics and Information Engineering. Currently, he is employed as a Professor at Department of Computer Science, University of Taipei, Taiwan. His research interests are performance ana

lysis of digital communication systems, error control coding, signal processing and computer security. Professor Hamid R. Arabnia received a Ph.D. degree in Computer Science from the University of Kent (England) in 1987. He is currently a Professor Emeritus of Computer Science at University of Georg

ia, USA, where he has been since October 1987. His research interests include parallel and distributed processing techniques & algorithms, supercomputing, Data Science, imaging science, and other compute intensive problems. Applications of interest include: medical imaging and security. Most recent

activities include: Studying ways to promote legislation that would prevent cyber-stalking, cyber-harassment, and cyber-bullying. As a victim of cyber-harassment and cyber-bullying, in 2017 he won a lawsuit with damages awarded to him for a total of ＄2.3 Million and ＄656K attorney costs. Since this

court case was one of the few cases of its kind in the United States, this ruling is considered to be important; Final Judgement for damages was issued in Leon County Courthouse of Tallahassee in Florida by Circuit Court Judge. Prof. Arabnia is Editor-in-Chief of The Journal of Supercomputing (Sprin

ger). He is also on the editorial and advisory boards of 30 other journals. He is the book series editor-in-chief of ＂Transactions of Computational Science and Computational Intelligence＂ (Springer). He has won 12 distinguished awards, including the ＂Outstanding Research Contributions to the Field o

f Supercomputing＂ (President of IEEE/SMC) and ＂Distinguished Research Award＂ for Outstanding Contributions to Adaptable Communication Systems (ACM SIGAPP IMCOM). Dr. Arabnia is Fellow and Advisor of Center of Excellence in Terrorism, Resilience, Intelligence & Organized Crime Research (CENTRIC). He

has been a PI/Co-PI on about ＄8 Million externally funded projects, about ＄200K internally funded projects, and about ＄4 Million equipment grants. During his tenure as Director of Graduate Programs, Dr. Arabnia secured the largest level of funding in the history of the department for supporting the

research and education of graduate students (PhD, MS). Dr. Arabnia has delivered a number of keynote and plenary lectures at international conferences; most recently at: The 14th IEEE International Conference on Parallel and Distributed Systems (ICPADS, Australia); International Conference on Future

Generation Communication and Networking (FGCN / IEEE CS, Sanya); The 10th IEEE International Conference on High Performance Computing and Communications (HPCC, Dalian); and ACM IMCOM International Conference. He has also delivered a number of ＂distinguished lectures＂ at various universities and res

earch units/centers (USA, Spain, South Korea, Japan, Iran, Saudi Arabia, UK, Canada, Turkey, China, Ireland, Australia, ...); his distinguished lectures were funded and sponsored by US Department of Defense, SERSC of Republic of Korea, US National Science Foundation, H2020 of Europe, and others. Dr.

Leonidas Deligiannidis is a Professor of Computer Science at Wentworth Institute of Technology in Boston, MA. His foundation in Computer Science was first established when he earned his B.S. from Northeastern University College of Computer Science. He then went on to obtain two advanced degrees in

the field from Tufts University. He has been active in the field since then, investigating subjects like Brain Computer Interfaces, Security, Business-oriented visualizations, and STEM Education. He has also served in industrial positions outside the scope of his academic work, using his acumen for

several companies. His industry experience includes both entrepreneur startups in healthcare and high-tech networking companies. He has received multiple awards for his efforts, including multiple Achievement Awards for his contributions to Imaging Science by the World Congress in Computer Science,

Computer Engineering, and Applied Computing, IEEE best paper awards, as well as a University Presidential award for his scholarly achievements. In addition, he has served as a referee for many journals in computer science and is a member of the program and organizing committees for notable conferenc

es in his field.

大台北地區冬季期間細懸浮微粒中水溶性離子組成特徵探討

為了解決Korea Time Taiwan的問題，作者杜育誠 這樣論述：

本研究探討冬季期間大台北地區大氣中細懸浮微粒的水溶性離子組成特性及逐時變動趨勢。於2021年1月1日至2021年3月31日在新北市泰山區明志科技大學校園內利用氣體與氣膠同步採樣連續監測儀(2060 MARGA R)分析每小時HNO3、SO2及NH3氣體與NH4+、Na+、K+、Ca2+、Mg2+、Cl-、NO3-及SO42-離子濃度。結果顯示HNO3、SO2及NH3在採樣期間的平均濃度分別為0.39 μg/m3、0.26 μg/m3及3.24 μg/m3。陽離子NH4+、Na+、K+、Ca2+及Mg2+的平均濃度分別為1.73、0.30、0.17、0.08及0.06 μg/m3。陰離子SO4

2-、NO3-及Cl-的平均濃度分別為3.12、2.32及0.40 μg/m3。其中Na+、Ca2+、K+及SO42-分別約有49.06%、10.65%、5.83%及2.30%是來自於海鹽飛沫。採樣期間水溶性離子占PM2.5質量濃度約42.44%，其中以SO42-、NO3-及NH4+為主要組成，占總水溶性離子約84.06%。採樣期間的硫氧化率(SOR)與氮氧化率(NOR)平均值分別為0.91與0.78，顯示採樣期間微粒中所含的SO42-及NO3-主要來自衍生性硫酸鹽及硝酸鹽。而本研究採樣期間的中和率(NR)平均值為1.02，顯示微粒接近於中性。採樣期間共有180小時PM2.5質量濃度超過35

μg/m3，事件小時(PM2.5≥ 35 μg/m3)的水溶性離子由高到低依序為NO3-、SO42-、NH4+、Cl-、K+、Na+、Ca2+、Mg2+。在事件小時中，除了Na+以外，其餘水溶性離子平均質量濃度皆高於非事件小時(PM2.5< 35 μg/m3)。但若依照水溶性離子占PM2.5比例來看，除了NO3-及NH4+占比有所提升外，其餘水溶性離子占PM2.5皆為下降趨勢。同時NOR在事件小時期間顯著增加，可見在事件小時期間所增加的衍生氣膠主要以NH4NO3微粒為主。另外藉由NR中和率來看，在事件小時的NR較非事件小時略高，相較而言較偏鹼性，表示有較多量的NH3可以中和大氣中HNO3及H2

SO4。