This course focuses on the basic molecular mechanisms employed by various viruses for virus growth and host cell invasion. Different cellular signaling and host defense pathways are also included. Organizer:Dr. Wen Chang College of Medicine SHU-CHUN TENG Saturday 34 PTMP8014 2

See details at the class homepage: http://www.rslabntu.net/courses/remote_sensing See details at the class homepage: http://www.rslabntu.net/courses/remote_sensing College of Bio-Resources & Agriculture KE SHENG CHENG Friday 789 BSE5019 3

1.INTRODUCTION(MING-JU CHEN/DEPARTMENT OF ANIMAL SCIENCE AND TECHNOLOGY)

2.SOIL CHARACTERISTICS, POLLUTION AND REMEDIATION TECHNIQUES IN TAIWAN

(ZUENG-SANG CHEN/DEPARTMENT OF AGRICULTURAL CHEMISTRY)

3.VEGETATION ECOLOGY AND DIVERSITY OF TAIWAN (KUO-FANG CHUNG/SCHOOL OFFOREST AND RESOURCE CONSERVATION)

4.FRUIT PRODUCTION IN TAIWAN(KUO-TAN LI/DEPARTMENT OF HORTICULTURE AND LANDSCAPE ARCHITECTURE)

5.CONTROL TECHNIQUES OF IMPORTANT DISEASES OF FRUIT TREES IN TAIWAN(TING-HSUAN HUNG/DEPARTMENT OF PLANT PATHOLOGY AND MICROBIOLOGY)

6.CROP BREEDING IN TAIWAN(YANN-RONG LIN/DEPARTMENT OF AGRONOMY)

7.TAIWAN FLORAL INDUSTRY AND POSTHARVEST TECHNIQUES (JEN-CHIH CHEN/INSTITUTE OF BIOTECHNOLOGY)

8.STATUS QUO OF PEST CONTROL IN TAIWANESE AGRICULTURE (HOW-JING LEE/DEPARTMENT OF ENTOMOLOGY)


9.INTRODUCTION OF DOMESTIC LIVESTOCK IN TAIWAN (YU-TEN JU/DEPARTMENT OF ANIMAL SCIENCE AND TECHNOLOGY)

10.ANIMAL DISEASE PROTECTION AND QUARANTINE IN TAIWAN(CHIN-CHENG CHOU/SCHOOL OF VETERINARY MEDICINE)

11.APPLICATION OF BIOTECHNOLOGY ON MODERN AGRICULTURE (MEN-CHI CHANG/DEPARTMENT OF AGRONOMY)

12.AGRICULTURAL BIOTECHNOLOGY AND FUNCTIONAL FOODS IN TAIWAN(YI-CHEN LO/INSTITUTE OF FOOD SCIENCE AND TECHNOLOGY)

13.ADVANCED BIOTECHNOLOGIES FOR ANIMAL PRODUCTION AND REPRODUCTION(LI-YING SUNG/INSTITUTE OF BIOTECHNOLOGY)

14.INTRODUCTION TO AGRICULTURAL ENGINEERING IN TAIWAN (MING-CHE HU/Department of Bioenvironmental Systems Engineering)

15.AGRICULTURAL MECHANIZATION IN TAIWAN(SUMING CHEN,CHUNG-KEE YEH/DEPARTMENT OF BIO-INDUSTRIAL MECHATRONICS ENGINEERING)

16.AGRICULTURAL EXTENSION AND COMMUNICATION IN TAIWAN (HSUI-PING YUEH/DEPARTMENT OF BIO-INDUSTRY COMMUNICATION AND DEVELOPMENT)

17.AGRICULTURAL TRADE LIBERALIZATION AND THE RESPONDING STRATEGY(RHUNG-JIEH WOO/DEPARTMENT OF AGRICULTURAL ECONOMICS)

18.FINAL EXAM
College of Bio-Resources & Agriculture MING JU CHEN Wednesday 34 AniSci5028 2

1．緒論 2．廢棄物的特性指標及分析方法 3．廢棄物的特性 4．廢棄物處理方法 5．池塘 6．好氣處理 7．厭_處理 8．堆肥化處理 9．養殖廢水與廢棄物處理 10．_染源控制 11．實驗 本課程主要針對生物_業廢棄物的種類及其對生態環境之影響,廢棄物的特性及分析方法,現行之處理方法,_染源之控制及管理,以及廢棄物之回收及利用等作整體性的介紹，希望學生在修習本課程之後對農業廢棄物的現況能有通盤的了解。 College of Bio-Resources & Agriculture CHU-YANG CHOU Tuesday 789 BME5703 3

MOLECULAR BIOLOGY College of Medicine FANG-JEN LEE Wednesday 34 Friday 34 MolMed7003 4 The upper limit of the number of non-majors: 5.

THE OBJECTIVES OF THIS COURSE ARE

1) TO PROVIDE GRADUATE STUDENTS WITH AN OVERVIEW OF RECENT DEVELOPMENTS IN ANIMAL BIOTECHNOLOGY;

2) TO IMPROVE GRADUATE STUDENTS’ PRESENTATION SKILLS. AFTER EXTENSIVE REVIEW AND DISCUSSION OF VARIOUS BIOTECHNOLOGIES, EACH STUDENT WILL BE ASKED TO GIVE A PRESENTATION IN THE AREA OTHER THAN THEIR OWN RESEARCH.

I WILL MEET WITH ALL STUDENTS INDIVIDUALLY SEVERAL TIMES DURING THEIR LITERATURE SEARCH, PREPARATION OF PRESENTATION OUTLINE AND PRESENTATION PRACTICE.

LAB DEMONSTRATIONS OF BASIC EMBRYOLOGY TECHNIQUES WILL BE INCLUDED AS WELL. GUEST SPEAKERS WILL PLAN TO INVITE FOR THE LECTURES AS NECESSARY. College of Bio-Resources & Agriculture Wednesday 234 Biot5007 3

This course introduces the state-of-the-art energy technology and development. Subjects include energy generation, storage and conversion technology and related applications will be covered. For example: hydrogen economy, nuclear energy, wind power and solar cells, batteries, green buildings etc. I aim to prepare students with abilities of active learning and creative thinking. Innovative pedagogical methods such as fishbowl discussion, brainstorming, mock conference, and debate etc. will be practiced in this class. College of Bio-Resources & Agriculture Students are required to study the assigned contents each week, and exchange ideas and thoughts in class. 50% of the final grade is based on in-class discussions, while the other 50% is based on the final report. The topics of final projects, which focus on energy issues facing Taiwan, will be developed over the course of the classes by each student. HSUN-YI CHEN Tuesday 6 Friday 34 BME5920 3

INTRODUCTION?EPIGENETIC OVERVIEW DNA METHYLATION AND GENOME DEFENSE RNAI AND HETEROCHROMATIN EVOLUTION OF MAMMALIAN EPIGENETIC CONTROL SYSTEMS EPIGENETICS AND DEVELOPMENT EPIGENTICS AND HUMAN DISEASE X-INACTIVATION GENOMIC IMPRINTING IN MAMMALS GENOMIC IMPRINTING IN PLANTS EPIGNETICS AND REPROGRAMMING EPIGENETICS IN ASSISTED REPRODUCTIVE TECHNIQUES APPLIED EPIGENETICS: FLOWERING PLANTS AND TISSUE ENGINEERING College of Bio-Resources & Agriculture Monday 678 Biot8001 3 The upper limit of the number of non-majors: 15.

This is a class integrates the concepts of structural biology and bioinformatics. The basic principle of amino acids and structre will be explained first, then the modern methods to resolve atomic resolution of protein structures. The relation of protein structure and function will be emphasized in the third part of this class. Bioinformatic principles, methods and modern developments will be followed. 1. Understand amino acids and protein structures. 2. Modern approaches to resolve protein structure. 3. Protein structure and function. 4. Software-based analysis of protein sequence. 5. Bioinformatic theories 6. Current developments of bioinformatics methods. College of Life Science This class will be taught in English. CHII-SHEN YANG Friday 678 Biot8003 3 The upper limit of the number of non-majors: 15.

This course includes presenters of Taiwan, Japan, Thailand, and Brunei, to provide understanding of international perspectives of environmental and occupational health. For the students to understand international perspectives of environmental and occupational health, and to interact with international teachers and students DISTANCE LEARNING NATIONAL TAIWAN UNIVERSITY Interaction with international teachers and students final report and presentation Tuesday 67 OMIH5056 2

Data is at the center of the so-called fourth paradigm of scientific research that will spawn new sciences useful to the society. Data is also the new and extremely strong driving force behind many present-day applications, such as smart city, manufacturing informatics, and societal security, to name a few. It is thus imperative that our students know how to handle data, analyze data, use data and draw insights from data. This course aims at acquainting the students with the analytical foundation of data handling techniques. The course consists of a series of seminar talks with substantial student participation, in the form of research and presentation in response to posted questions about main topics in data analytics and modeling. 1. Scope Broad topics covered in the course include: •Regression & curve fitting •Probability distribution & parameter estimation •Mixture models, latent variable models & hybrid distributions •Hidden Markov models, Markov random fields, & graphic models •Pattern recognition & decision theory •Neural networks and deep learning Well spend 2-3 weeks on each topic (some may take up to 4 weeks). 2. Format For each topic, a number of questions to help students learn the subject will be posted in advance. Individual student will be assigned to conduct research, answer specific questions and return with presentations to the class. Each student presentation is of duration ~20 min, followed by ~10 min questions and discussion. Students who are assigned to address specific questions have one week time to prepare for the presentation. Common questions shared by all topics are: – What are the problems that gave rise to the particular topic & concept? (The original motivation) – What problems beyond the original motivation will the topic and the related techniques be able to solve? (New and novel applications) – What are the problem formulations with relevant assumptions that have been proposed? (The methodology and formulation) – What are the ensemble of techniques that were developed to solve the problem? (The tools and capabilities) – How do these techniques solve the problem or contribute to the solutions? (The solution mechanism) – What are the limitations of the solutions proposed so far? Any remaining open problems in the topic? (Research opportunities) In addition to these common questions, some topic-specific questions may also be posted and addressed in student presentations. After all posted questions about a subject are addressed in student presentations, one or two commentary sessions by the lecturer on the subject will follow so as to complete the systematic development of understanding of the subject. The course will be primarily conducted in English. To reflect the applicability of the subject matter to local problems, local languages may also be used as the circumstance calls for it. No official textbook is assigned in this course. Students are expected to conduct research with all university provided resources (e.g., books in the library) and information available on the web. Class notes by the lecturer will be distributed in due course. 3. Prerequisite Both graduate and undergraduate students can enroll in the class, as long as they have completed engineering mathematics courses, particularly Probability and Statistics or the equivalent. Overall, students will be exposed to data analytic topics and their historical perspectives, learn to ask and analyze related problems, understand the modeling techniques and their origins, and conceive of new applications and research opportunities. College of Electrical Engineering & Computer Science No written test will be given in the special course. Student presentations are evaluated by the class and moderated by the lecturer. JUANG BIING-HWANG Thursday 234 CSIE5610 3

Data is at the center of the so-called fourth paradigm of scientific research that will spawn new sciences useful to the society. Data is also the new and extremely strong driving force behind many present-day applications, such as smart city, manufacturing informatics, and societal security, to name a few. It is thus imperative that our students know how to handle data, analyze data, use data and draw insights from data. This course aims at acquainting the students with the analytical foundation of data handling techniques. The course consists of a series of seminar talks with substantial student participation, in the form of research and presentation in response to posted questions about main topics in data analytics and modeling. 1. Scope Broad topics covered in the course include: •Regression & curve fitting •Probability distribution & parameter estimation •Mixture models, latent variable models & hybrid distributions •Hidden Markov models, Markov random fields, & graphic models •Pattern recognition & decision theory •Neural networks and deep learning Well spend 2-3 weeks on each topic (some may take up to 4 weeks). 2. Format For each topic, a number of questions to help students learn the subject will be posted in advance. Individual student will be assigned to conduct research, answer specific questions and return with presentations to the class. Each student presentation is of duration ~20 min, followed by ~10 min questions and discussion. Students who are assigned to address specific questions have one week time to prepare for the presentation. Common questions shared by all topics are: – What are the problems that gave rise to the particular topic & concept? (The original motivation) – What problems beyond the original motivation will the topic and the related techniques be able to solve? (New and novel applications) – What are the problem formulations with relevant assumptions that have been proposed? (The methodology and formulation) – What are the ensemble of techniques that were developed to solve the problem? (The tools and capabilities) – How do these techniques solve the problem or contribute to the solutions? (The solution mechanism) – What are the limitations of the solutions proposed so far? Any remaining open problems in the topic? (Research opportunities) In addition to these common questions, some topic-specific questions may also be posted and addressed in student presentations. After all posted questions about a subject are addressed in student presentations, one or two commentary sessions by the lecturer on the subject will follow so as to complete the systematic development of understanding of the subject. The course will be primarily conducted in English. To reflect the applicability of the subject matter to local problems, local languages may also be used as the circumstance calls for it. No official textbook is assigned in this course. Students are expected to conduct research with all university provided resources (e.g., books in the library) and information available on the web. Class notes by the lecturer will be distributed in due course. 3. Prerequisite Both graduate and undergraduate students can enroll in the class, as long as they have completed engineering mathematics courses, particularly Probability and Statistics or the equivalent. Overall, students will be exposed to data analytic topics and their historical perspectives, learn to ask and analyze related problems, understand the modeling techniques and their origins, and conceive of new applications and research opportunities. College of Electrical Engineering & Computer Science No written test will be given in the special course. Student presentations are evaluated by the class and moderated by the lecturer. JUANG BIING-HWANG Thursday 234 CSIE5610 3