Advanced Life Science
Part 1: Lipid Droplet Biology
Teacher: Liu Pingsheng
Difference with lipoproteins and other cellular organelles
Uncertainty and problems
2. Structural Proteins and Protein Composition
MPL, MLDP, MLDS, YLDPs, CLDPs
Lipid synthetic and catalytic
3. Formation and Functions
Growth and degradation
Fusion and fission
Trafficking (movement and interaction with other cellular organelles)
4. Lipid Droplets in Mammals and Other Organisms
Other mammalian cells
Genetic Model Organisms:
Advanced Life Science
Plant Genomics and Molecular Breeding
Teacher: 景海春 Jing Haichun
1. Agriculture, crop domestication and human civilisation
2. Classical breeding
3. Omics technologies and genome selection
5. Germplasm collection and evaluation
6. Mutational breeding
7. Molecular markers
8. Gene Transformation
11. Future of crop breeding
Advanced Life Science
Teacher: 高斌 Gaobin
Immunology 2013 is designed as an introduction course of immunology for biology postgraduates. The class will give students a general view of immunology and some detailed development in certain selected area of immunology. This course covers the components of the immune system, Innate immunity, the cell biology of antigen processing and presentation, antibody and B cells, T cell response, the molecular structure and assembly of MHC molecules, and the pathogenesis of immunologically mediated diseases and immune system as dense system against infectious disease and tumor, and immunology as tool for general biology including antibody technology and flow cytometry. The course is structured as a series of lectures and mini-seminars in which individual research cases are discussed with faculty tutors. It will cover following topics:
A) The components of Immunology
1. Introduction of Immunology
Mini Seminar Series a: History of Immunolgy
2. Innate immunity and Macrophage and NK
Mini Seminar Series b: Modification of NK cell as tumour killers
3. Antigen processing and DC
Mini Seminar Series c: Calreticulin- A board member of a plc
4. Antibody and B cells
Mini Seminar Series d: Combody- one domain antibody multimer with improved avidity,
5. MHC and T cells
Mini Seminar Series e: Strategies for retargeting T cells for tumour therapy
6. Allergy and Mast cells
Mini Seminar f: Mast cells as a nosy friend
B) Immunology and diseases
1. Immunology and infectious diseases
3. Immunology related diseases
C) Immunology as research tool for biology
1. Antibody as a tool for Qualitative and quantitative analysis of protein
2. Flow cytometry for cell characterization and isolation
Human Physiology: from cell functions to life
Preparatory Course: biology, anatomy/histology and physics
Object: graduate students
Purpose and Requirement: This course is designed for graduate students to have a comprehensive view in human physiology with special focuses on cell functions, cells-supported activities in life and their mechanistic processes. In addition to the knowledge of cellular principles and integrative functions in human life, the course will introduce how to use variable technologies testing hypothesis and establishing theories in physiology. These should help students to raise the abilities of logical thinking and fantastic experimental design in their future studies. The contents in this course are suitable for the students who will conduct the research in life science, such as neuroscience, molecular/cellular biology, biophysics, biochemistry, genetics and zoology. The students who are going to take this course are expected to have basic knowledge in cell biology, histology and anatomy.
Abstract: Four hours per lecture
第一章 Neurophysiology: physiological functions and their mechanisms in the central nervous system.
Lecture one: neural physiology, brain functions and brain disorders.
Lecture two: technologies used in neurophysiology
Lecture three: the physiology of neurons and synapses.
Lecture four: neural encodings in brain networks
Lecture five: sensation, motion and cognition physiology
Lecture six: homeostasis in brain functions
第二章 Physiology in muscle cells
Lecture seven: cardiac muscle cells and heart functions
Lecture eight: smooth muscles and their functions in the systems of circulation and respiration.
Lecture nine: smooth muscles and their functions in the systems of digestion and others.
Lecture ten: skeletal muscle cells and motion control
第三章 Physiology in endothelium and epithelium cells
Lecture eleven: endothelium cells and their functions in the systems of circulation, respiration, urine and digestion.
Lecture twelve: endothelium cells and their functions in the systems of endocrine and reproduction.
Lecture thirteen: the interactions among endothelium, muscle and nerve cells.
Lecture fourteen: the brain coordinates activities in different systems
第五章 Final examination
Text books：Human Physiology edited by Rodney et al. 2003 the fourth edition; Fundamental Neuroscience edited by Square et al. 2008 the second edition; Cellular and Molecular Neurophysiology edited by Hammond 2008 the third edition.
Teaching Mode：Lecture with slide presentation plus discussion
Teacher： Wang, Jin-Hui (王晋辉)
Advanced Quantum Mechanics
Instructor: Ling-Fong Li
Textbook: J. J. Sakurai and J. Napolitano, \Modern Quantum Mechanisc", 2nd edition (Addison-Wesley), (2010)
Outline of topics
1. Fundamental Concepts
(a) Stern-Gerlach Experiments
(b) Physical States, Observables and Measurement
(c) Wave Functions in Position and Momentum Space
2. Quantum Dynamics
(a) Time Evolution and Schrodinger Equation
(b) Schrodinger Picture and Heidenberg Picture
(c) Simple Harmonic Oscillator
(d) Schrodinger's wave equation
3. Theory of Angular Momentum
(a) Rotation and Angular Momentum Commutation Relation
and Finite Rotation
(c) Density Operator and Pure verse Mixed Ensembles
(d) Eigenvalue and Eigenvectors of Angular momentum
(e) Orbital Angular momentum
(f) Addition of Angular momenta
Overview of Recent Development in Physics
The goal of this course is to give students a simple overview of the most recent development in physics. The emphasis is on the conceptual understanding rather than the technical details. It will cover the following 3 main areas of physics: high energy physics, condensed matter physics and astrophysics as described below;
A) High Energy Physics -------- September 26 to Oct 17
1. Standard Model of Electroweak and Strong Interaction
2. Neutrino Oscillations
3. Beyond Standard Model physics—Grand Unification, String Theory, …..
Instructor --- Professor Ling-Fong Li, UCAS, email@example.com.
B) Condensed Matter Physics -------- October 24 to November 21
1. Cold Atom
2. Nano Material
3. High Tc Superconductor
Instructor --- Professor Shao-Jing Qin, Institute of Theoretical Physics, firstname.lastname@example.org
C) Astrophysics -------- November 28 to December 26
1. Dark Matter
2. Dark Energy
3. Inflationary Cosmology
4. Galaxy Formation
Instructor ---Professor Li-Jun Gou, National Astronomical Observatories, email@example.com
The grade for this course will be determined by the reports submitted by each student at the end of each of these periods, i. e., one report for high energy, one for astrophysics and one for condensed matter physics. These reports can either be a summary of all the topics in each area, or a report on some topics related to the course approved by the instructor. The length of the paper should be of order of 3 pages.
Course Title: Earth System Science
Part 3:Introduction to Geodynamics
2013 Fall Semester
Professor of Geophysics, University of Chinese Academy of Sciences
This course will introduce the field of geodynamics, the study of dynamical processes of the solid Earth. As such, it is rooted in fundamental physics and highly interdisciplinary. Mathematics is the central tool used to apply physical theories and create predictive models of the Earth. Geodynamics provides the quantitative foundation for the theory of Plate Tectonics, the basic organizing paradigm for our understanding of the solid Earth.
D. L. Turcotte and J. Schubert, Geodynamics, Second Edition, Cambridge University Press, 2002.
Preliminary Course Outline:
Week 1: Plate tectonics; Stress and strain in solids;
Week 2: Elasticity and flexure;
Week 3: Heat transfer;
Week 4: Fluid mechanics;
Week 5: Rock rheology; Faulting.
Course Title: Earth System Science
Class Instructor: Dr. Zhaodong Feng (call me: Jordan)
Major Reference: Earth’s Climate: Past and Future (2nd). By William F. Ruddiman (2008), W.H. Freeman Publication, New York
Minor Reference: Global Climate System (patterns, processes, and teleconnections). By Howard A. Bridgman and John E. Oliver (2006), Cambridge University Press, New York.
Earth systems science views Earth as a physical system of interrelated phenomena, governed by complex processes involving the geosphere, atmosphere, hydrosphere and. biosphere. The Earth system science approach emphasizes relevant interactions of chemical, physical, biological and dynamical processes that extend over spatial scales from microns to the size of planetary orbits, and over time scales of milliseconds to billions of years. The Earth systems approach has become widely accepted as a framework posing disciplinary and interdisciplinary questions in relationship to humankind.
The aim of this class is to guide the students through a comprehensive understanding of the earth systems by adopting systematic and holistic approaches to the earth’s climate. First, interactions among the four major spheres are digested from climatologic point of view. Second, the interactions among sub-systems of the earth’s climate are tackled from energy-balance perspective. Third, the different time-scales and different spatial scales are thoroughly dealt with from geological perspectives. Finally, human forcing factors and the consequences are thoroughly investigated and future scenarios are discussed based on modeling results. The students upon completing this class are expected to be capable to conduct a sound scientific research on climate change or able to make a scientifically sound decision on environment management related issues.
This course is designed to provide a systematic knowledge regarding global environmental change so that the knowledge can serve as a foundation for further scientific research or as a decision-making reference for practical applications. The course will first focus on the present interactions among the four spheres by bringing the newest findings of the Earth’s System research into the class. The course then explores the long-term patterns of the Earth’s System change by presenting the newest data from deep-sea cores, ice cores, and terrestrial sequences. After understanding the current spatial patterns and the long-term temporal patterns, future changes will be discussed based on modeling predictions. Finally, the socio-economic perspectives of the global environmental changes will also be presented to the students.
(1) If you miss 20% of lectures (calculated as the ratio of your missed hours over the total hours of this class), you will automatically get F; (2) 6 points will be deducted for each one of recorded absences from the total of 100 points after your 1-excused absence; (3) medical-resulted and extracurricular-caused absences are also counted as absences.
1st Exam (20 points): on Meteorology and Modern Climate Systems
2nd Exam (25 points): on Climatic Evolution and Long-term Mechanisms
3rd Exam (25 points): on Human Impacts and Future Climates
4th Exam (30 points): Presentation (15 points) and Final Paper (25 points) on current “hotspot” issues.
100-90 = A
89-85 = B+
84-80 = B
79-75 = C+
74-70 = C
69-60 = D
<60 = F
Week 1: Global Temperature and Global Precipitation (reading: chapters 1-2 of minor text)
Week 2: Air Circulation and Ocean Circulation (reading: chapters 3-4 of major text) (1st Exam)
Week 3: Long-term Climate Change and Astronomic Forcing (reading: chapters 7 & 8 of major text)
Week 4: Last Glacial Climate Changes (reading: chapters 14-16 of major text) (2nd Exam)
Week 5: Short-term Carbon Cycle and Greenhouse Effects (reading: chapter 18 of major text)
Week 6: Feedback Mechanisms and Climate Modeling (reading: chapter 9 of minor text) and Evidence and Consequences of Global Warming (reading: chapter 19 of major text) (3rd Exam)
Week 7: Social Responses to Climate Change (reading materials will be supplied)
Week 8: Students’ Presentations (i.e., 4th Exam)
Topics of presentations and final papers include (not limited to):
(1) Past climate changes,
(2) Current climate crisis,
(3) Biological responses to climate changes,
(4) Human forcing factors and responses,
(5) Climate changes and energy politics,
(6) Climate changes and water resources,
(7) Climate Change and Socioeconomic.
Requirements for Final Paper:
(1) Single-spaced, time font, 12 size8-10 page writing including up to 3 figures,
(2) Following the format of Earth and Planetary Change (an example will be provided),
(3) References adequately cited and formatted according to the format of Earth and Planetary Change,
(4) 8-10 papers properly (cited) in the paper (properly cited means: the paper is cited for a justifiable reason).
Specific Point Allocation for PPT Presentation (15 points of the allocated 30 points):
(1) Clarity of Verbal Communication and quality of PPT slides: 4 point
(2) Introduction (Rationale or Logic or WHY): 3 points
(3) Data Presentation (how did you get the data and what you got): 3 points
(4) Data Analysis or data review or data critics: 3 point
(5) Conclusions (are they clearly stated? Do data support your conclusions?): 2 point
Specific Point Allocation for Final Paper (15 points of the allocated 30 points):
(1) Introduction (Rationale or Logic or WHY): 5 points
(2) Data Presentation (how did you get the data and what you got): 4 points
(3) Data Analysis or data review or data critics: 3 points
(4) Conclusions (are they clearly stated? Do data support your conclusions?): 3 points
Course Syllabus: Earth’s Climate Change
Dr. Juzhi Hou, email: firstname.lastname@example.org
Dr. Daniel R. Joswiak, email: email@example.com
Earth's Climate: Past and Future by William F. Ruddiman
Paleoclimatology - Reconstructing Climates of the Quaternary by Raymond S. Bradley
This course aims to provide students an outline of Earth’s Climate from billion years ago to present and near future. The course will discuss the climate changes at tectonic-scale, to orbital-scale, to deglacial, to historical and future.
The objectives of this course include:
1. Learning how climate scientists solve problems;
2. Understanding of the components of the Earth’s climate system and their feedback;
3. Familiar with the climate changes at different time scales and their causes;
4. Understanding of the role of CO2 in the climate systems;
5. Understanding of the orbital monsoon hypothesis.
Part I: Frame of climate science, 2 lectures in 2 weeks,
Part II: Tectonic-scale climate change, 2 lectures in 2 weeks,
Part III: Orbital-scale climate change, 2 lectures in 2 weeks,
Part IV: Deglacial climate change, 2 lectures in 2 weeks,
Part V: Historical and future climate change, 2 lectures in 2 weeks,
Part VI: Final exam.
Functional Nanostructure: Synthesis, Characterizations and Device Applications
Prof. Jun He, Prof. Zhixiang Wei and Prof. Liming Xie
4 hrs/week by instructor. 1 hr/week by teaching assistant.
Homework: 12 assignments
Typically 40% homework, 40% each midterm, 20% final.
Solid state physics, semiconductor physics, general chemistry，physical chemistry
This course includes three sections: inorganic semiconductor nanostructures, organics functional nanostructure and characterization of nanomaterials. The first section provides atoms-to-device introduction to the latest semiconductor quantum heterostructures. It covers nanostructures growth, their electronic, optical, and transport properties, their role in exploring new physical phenomena, and their utilization in devices. For the second part, By studying of this section, student should know the history and principles of organic electronics, understand how to use various strategies to produce organic functional nanomaterials, get the ideas how to construct useful organic electronic and optoelectronic devices, including filed effect transistors, light emitting diodes, and photovoltaics. The third provides Electron microscopic characterization of nanomaterials, Spectroscopic characterization of nanomaterials and some latest pplications of nanomaterials in nanomedicine.
Schedule of the course
Contents of the course
Section 1: Low dimensional semiconductors
1. History and principles organic electronics
(1) History of modern physics
(2) The origin of conducting and semiconducting properties of low dimensional semiconductor
2. Growth technique of Low dimensional semiconductors
(1) Molecul;ar beam epitaxy
(2) Metal-organic Chemical Vapor Deposition
(3) Chemical Vapor Deposition
3. Properties and application of Low dimensional semiconductors
(1) Opto-electronic devices
(2) Solar and Environmental applications
(3) Nanogenerator and others
Section 2: Organic functional materials
4. History and principles organic electronics
(1) History of organic electronics
(2) The origin of conducting and semiconducting properties of organic functional materials
5. Preparation of organic functional nanomaterials
(1) Self-assembly of organic functional nanomaterials
(2) Fabrication method of organic electronic devices
6. Properties and application
(1) organic filed effect transistors
(2) organic light emitting diodes
(3) organic photovoltaics
Section 3: Characterization of nanomaterials
7. Electron microscopic (EM) characterization of nanomaterials
(1) Introduction to transmission electron microscopy (TEM), scanning electron microscopy (SEM), electron diffraction and related techniques
(2) Examples using electron microscopy to characterize nanomaterials (such as nanowires, quantum dots, graphene, carbon nanotubes)
(3) By studying of this section, student will know the principle of EM and its applications in nanomaterial characterization.
8. Spectroscopic characterization of nanomaterials
(1) Introduction to FL, Raman and IR
(2) Examples using FL, Raman and IR to characterize nanomaterials (such as nanowires, quantum dots, graphene, carbon nanotubes)
(3) By studying of this section, student will know the principle of FL, Raman and IR and their application in nanomaterial characterization.
9. Applications of nanomaterials in biomedicine
(1) Nanomaterials as imaging probes
(2) Nanomaterials as drug carriers
(3) By studying of this section, student will get a brief idea about broad applications of nanomaterials in nanomedicine.
Textbook and any related course material:
Low dimensional semiconductor structures: fundamental and device applications
Edited by Keith Barnham and Dimitri Vvedensky
Organic Electronics, Materials, Processing, Electronics, and Apllications
Edited by Franky So
Characterization of Materials, edited by Elton N. Kaufmann (editor-in-chief), Wiley-Interscience.
Transmission Electron Microscopy, edited by David B. Williams and C. Barry Carter, Springer.
Principles of Fluorescence Spectroscopy, third edition, edited by Joseph R. Lakowicz, Springer.
Introductory Raman Spectroscopy, second edition, edited by John R. Ferraro, Kazuo Nakamoto and Chris W. Brown, Elsevier.
Expected level of proficiency from students entering the course:
Syllabus of Spectroscopic Analysis
Course type: Basic course for chemistry or related field
Teaching object：Graduated Students in Chemistry or related field
Professor：Xu Jingwei 徐经伟
Course time：Oct. 2013 to Nov. 2013
1) Purpose of this course
Spectroscopic analysis means the analysis of spectra that results from the interaction of radiation and samples for the determination of the characters of the samples. These characters include the chemical constitutes, contents of different components, structure and geometric isomer of the molecular, reaction mechanism and process. Spectroscopic analysis is fast, correct, sensitive and repeatable. It is wildly used in chemistry, pharmaceuticals, chemical engineering, environment, food fields and others. The main instruments used in spectroscopic analysis are infrared (IR), Raman, NMR, UV and MS spectrometers.
The teaching objects of this course are graduate students in chemistry or related fields. By studying of this course, students should understand the principles and application of spectroscopic analysis, and are able to analyze related spectra and to obtain related information and conclusions by the analysis. This course is taught by PPT and has a final exam.
The contents of this course include principle and application of IR, Raman, NMR, UV and mass spectroscopy. The main reference books are following:
1. 徐经伟，牛利，高翔，崔勐，《波谱分析》Spectroscopic Analysis，科学出版社出版，2013 波谱分析，
2. Norman B Colthup, Lawrence H Daly and Stephen E Wierley, Introduction to Infrared and Raman Spectroscopy, Third Edition, Academic Press, San Diego, 1990.
3. K Nakanoto, Infrared and Raman Spectra of Inorganic and Coordination Coumpounds, Sixth Edition, John Wiley & Sons, New Jersey, 2009.
4. L A Woodward, Introduction to the Theory of Molecular Vibrations and Vibrational Spectroscopy. Oxford University Press, Ely House, London, 1972.
5. Cotter R J. Time-of-flight mass spectrometry: instrumentation and applications in biological research; ACS: Washington, DC,1997.
6. J Cavanagh, W J Fairbrother et al, Protein NMR Spectroscopy, Principles and Practice, Elsevier Inc. 2007.
7. H. Gunther，Harald Gunther, Harald G Nther，NMR Spectroscopy: Basic Principles, Concepts, and Applications in Chemistry，2nd ed，John Wiley & Sons，1995.
8. Pretsch, E.; Bühlmann, P.; Badertscher, M. Structure Determination of Organic Compounds, 4th Edition, Berlin, Springer-Verlag, 2009。
2) Schedule of the course
3) Contents of the course
Section one: Principle of NMR（1）
2. Phenomenon of nuclear spin and nuclear magnetic resonance
3. Boltzmann distribution and macroscopic magnetization
4. Rotating coordinate system and process of macroscopic magnetization in rotating coordinate system
5. Fourier transform
6. Pulse and free induction decay
7. Single pulse NMR experiment
By studying of section one, student should know the history of NMR, understand the concepts of nuclear moment, nuclear spin, macroscopic magnetization, grasp the principle of Fourier transform and single pulse experiment.
Section two: Principle of NMR（2）
1. Quadrature detection
2.1 Longitudinal relaxation
2.2 transverse relaxation
2.3 Determination of T2 by Spin-echo
2.4 Mechanism of relaxation
3. Shielding factor
4. Chemical shift
5. Pulse Fourier transform NMR spectrometer
By studying of section tow, student should understand the principle of quadrature detector, mechanism of relaxation, concepts of shielding factor and chemical shift, know how the spectrometer to work.
Section three: proton NMR spectra（1）
1. Some aspects of proton chemical shift
1.1 Inductive effects
1.2 Magnetic anisotropy
1.3 Ring current
1.4 Hydrogen bond
1.5 Solvent and others
2. Proton chemical shift of organic compounds
2.2 Alkene and alkyne
2.4 Alcohol and ether
2.6 Aldehyde and carboxylic acid
2.7 Ketone and ester
2.8 Amine, amide and nitro compounds
2.9 Heterocyclic compounds
By studying of section three, student should understand how the chemical shift is varied under different conditions and know the basic chemical shift range for different organic compounds.
Section four: proton NMR spectra（2）
1. Scalar coupling
1.1 Mechanism of coupling
1.2 2JHH , 3JHH and long-range coupling
2. Chemically equivalent and magnetically equivalent
3. Spin systems
4. Quantum mechanical treatment for coupling two spin system
5. Fist-order spectra
6. Complex spectra
Section five: Carbon-13 NMR spectra（1）
1. Nuclear magnetic double resonance and proton broad band decoupling
2. Overhauser effect
3. Inverse gated decoupling
4. Gated decoupling
5. Chemical shift of Carbon-13
Section six: Carbon-13 NMR spectra of organic compounds
2. Alkene and alkyne
4. Alcohol and ether
6. Aldehyde and carboxylic acid
7. Ketone and ester
8. Amine, amide and nitro compounds
9. Heterocyclic compounds
Section 7: Density Matrix and product operator
1. Density Matrix
2. Liouville-von Neumann equation
3. Density matrix description of NMR experiment
3.1 The one spin system
3.2 The two spin system
4. Product operator
4.1 Product operator description of INEPT and refocus-INEPT
4.2 Product operator description of DEPT
Section 8: Two Dimensional NMR
1. General Aspects of 2D NMR
2. Heteronuclear Chemical Shift Correlation
3. Heteronuclear Single Quantum Correlation
4. Heteronuclear Multiple Quantum Correlation
5. Heteronuclear Multiple-Bond Correlation
6. Nuclear Overhauser Effect Spectroscopy
7. Rotating Frame Overhauser Effect Spectroscopy
Section 9: IR Principle (1)
1. Classical Description for Diatomic Molecular Vibration
2. Quantum Description for Diatomic Molecular Vibration
2.1 The Quantum Mechanical Harmonic Oscillator
2.2 The Boltzmann Distribution
2.3 The Anharmonic Oscillator
Section 10: IR Principle (2)
1. Rotating Spectra of Diatomic molecule
1.1 Rotating Function and Energy of Diatomic molecule
1.2 Rotating Spectra of Diatomic molecule
1.3 Nonrigid Rotator
2. Vibrational and Rotating Spectra of Diatomic molecule
Section 11: The Theoretic Analysis of Multiple Atomic Molecular Vibration
1. Normal Modes of Vibrations
2. Normal Modes of CO2
3. Internal Coordinates and Wilson FG Matrix
Section 12: Molecular Symmetry
1. Symmetry and Point Groups
2. Matrix Representation of symmetry operations
3. Irreducible Representation and Charchter Tables
4. The Number of Fundamentals of Each type
5. Select Rules
Section 13: IR Spectra of Organic compounds
2. Alkene and alkyne
4. Alcohol and ether
6. Aldehyde and carboxylic acid
7. Ketone and ester
8. Amine, amide and nitro compounds
9. Heterocyclic compounds
Section 14: Raman Spectroscopy
2. Principle of Raman Spectroscopy
2.1 Classical theory of Raman Spectroscopy
2.2 Quantum theory of Raman Spectroscopy
2.3 Raman Spectra and Vibrational Energy
2.4 Selective Rule
2.5 Comparison of Raman with IR
3. Raman Spectrometer
4. Experimental methods of Raman Spectroscopy
4.1 Fourier Raman Spectroscopy
4.2 Resonance Raman Scattering
4.3 Surface Enhanced Raman Scattering
4.4 Raman Imaging
Section 15: Application of Raman Spectroscopy
1.1 Structure and Conformation Analysis
1.2 Deformation Analysis
1.3 Liquid Crystal
2. Carbon Materials
2.2 Carbon Nano-tube
4.1 Active Ingredient in Tablet and Capsule
4.2 Crystal Structure Analysis in Pharmaceutical Preparation
4.3 Raman Imaging for the Active Ingredient in Pharmaceutical Preparation
Section 16: UV Spectroscopy
2. Energy Transition and Ultraviolet Spectrum
3. UV Spectra of Organic compounds
4. Structural Analysis by UV
Section 17: Mass Spectroscopy (1)
1.1 History of Mass Spectroscopy
1.2 Mass Spectroscopy and Spectrometer
2. Ion Source
2.1 Electron Ionization
2.2 Chemical Ionization
2.3 Field Ionization and Field Desorption
2.4 Fast Atom Bombardment
2.5 Matrix Assisted Laser Desorption Ionization
2.6 Electrospray Ionization
2.7 Desorption Electrospray Ionization
Section 18: Mass Spectroscopy (2)
1. Mass Analyzer
1.1 Magnetic Mass Spectrometer
1.2 Time of Flight Mass Spectrometer
1.3 Quadrupole Mass Spectrometer
1.4 Ion Trap Mass Spectrometer
1.5 Fourier Transform Ion Cyclotron Resonance Mass Spectrometer
2. Tandem Mass Spectroscopy
2.1 Space Tandem Mass Spectroscopy
2.1 Time Tandem Mass Spectroscopy
3. Chromatography Mass Spectroscopy
3.1 Gas Chromatography Mass Spectroscopy
3.2 Liquid Chromatography Mass Spectroscopy
4. Fragmentation Reaction
4.1 Basic Concepts
4.2 Fragmentation Reaction
4.3 Analysis of Mass Spectra
5. Application of Mass Spectroscopy
5.1 Structural Analysis of the Small Molecule
5.2 Sequential Analysis of the Small Peptide
5.3 Analysis of the Polymer
Section 19: Comprehensive Spectroscopic Analysis
1. Comprehensive Analysis of Deserpidine
2. Comprehensive Analysis of Methyclothiazide
Section 20: Final Examimation
Instructor: Ying Liu
Prerequisite ：data structure, computer algorithms, programming, database
The goal of the course is to provide the students with knowledge and hands-on experience in developing data mining algorithms and applications. Firstly, the course will introduce the motivation of data mining techniques. Then, present the principles and major classic algorithms in data mining. Next, the course will introduce some successful applications to the students. Finally, advanced topics and the most recent techniques will be introduced as well.
Chapter 1: Introduction
Motivation, major issues, major applications, characteristics
Chapter 2: Data warehouse
Model, architecture, operations
Chapter 3: Data pre-processing
Data cleaning, data transformation, data reduction
Chapter 4: Association Rules
Apriori, FP-Growth, Partition, DIC, DHP, multi-level association rules, quantitative association rules, major applications
Chapter 5: Classification
Decision tree, Bayesian Classifier, Classification by backpropagation, KNN classifier, statistical prediction models, major applications
Chapter 6: Clustering
Partitioning methods, hierarchical methods, density-based methods, grid-based methods, major applications
Chapter 7: Applications
Credit scoring, oil exploration, customer relationship management, cosmological simulation
Chapter 8: Advanced techniques
Text mining, Web mining, sequence mining, stream mining, parallel data mining, graph mining
Data Mining, Concepts and Techniques. Jiawei Han and Micheline Kamber, Morgan Kaufmann, 2006.
Introduction to Data Mining, Pang-Ning Tan, Michael Steinbach and Vipin Kumar, Addison-Wesley, 2006.
To be announced in class
This course is an introduction to applied statistics and data analysis. Topics are chosen from descriptive measures, sampling and sampling distribution, estimation and confidence interval, hypothesis test, and linear regression. Data analysis is difficult without some computing tools and the course will introduce some statistical computing with Excel.
1. Tamhane, Ajit C., and Dorothy D. Dunlop. Statistics and Data Analysis: From Elementary to Intermediate. Prentice Hall, 2000.
2. Weiss, Neil A. Introductory Statistics (9th Edition). Pearson Education, Inc, 2012.
Dr. Qian Wang, email: firstname.lastname@example.org, phone: 62521051.
Course: Input-output Analysis by Xiuli Liu
Date: From September 15 to November 15, 2013
Time: Monday (10:00am-11:40am) and Tuesday (10:00am-11:40am) Every week
Session 1: The history and development of input-output analysis
Session 2: Foundations of Input-Output Analysis
Session 3: Production Functions and the Input-Output Model
Session 4: An Illustration of Input-Output Calculations
Session 5: Open Models and Closed Models
Session 6: The Price Model Overview
Session 7: The Price Model based on Monetary Data
Session 8: The Price Model based on Physical Data
Session 9: Input-Output Models at the Regional Level
Session 10: Many-Region Models: The Interregional Approach
Session 11: The Regional Tables
Session 12: Numerical Example: Hypothetical Two-Region Multiregional Case
Session 13: Multipliers in the Input-Output Model
Session 14: Income/Employment Multipliers
Session 15: Regional Multipliers
Session 16: Miyazawa Multipliers
Session 17: Multipliers and Elasticities
Session 18: Multiplier Decompositions
Session 19: Stone’s Additive Decomposition
Contact: email@example.com, 15810683845
Pattern recognition techniques are used to automatically classify physical objects (handwritten characters, tissue samples) or abstract multidimensional patterns (n points in d dimensions) into known or possibly unknown categories. A number of commercial pattern recognition systems are available for character recognition, handwriting recognition, document classification, fingerprint classification, speech and speaker recognition, white blood cell (leukocyte) classification, military target recognition, etc. Most machine vision systems employ pattern recognition techniques to identify objects for sorting, inspection, and assembly. The design of a pattern recognition system requires the following modules: (i) sensing, (ii) feature extraction and selection, (iii) decision making and (iv) performance evaluation. The availability of networked MEMS (low cost, high performance and miniaturized) sensors have resulted in vast amount of digitized data. Need for efficient archival and retrieval of this data has fostered the development of pattern recognition algorithms in new application domains.
This course will introduce the fundamentals of pattern recognition with application examples. Techniques for analyzing multidimensional data of various types and scales along with algorithms for projection, dimensionality reduction, clustering and classification of data will be explained. The course will present various approaches to exploratory data analysis and classifier design so students can make judicious choices when confronted with real pattern recognition problems. It is important to emphasize that the design of a complete pattern recognition system for a specific application domain requires domain knowledge, which is beyond the scope of this course.
Probability and statistics, Digital signal processing, Linear systems
Duda, Hart and Stork, Pattern Classification, Second Edition, Wiley, 2001.
Course grade will be assigned based on scores on 3 homework assignments, one project, and final close book exam. Weights for these three components are as follows: HW (30%), PROJECT (30%), Exam(40).
All homework solutions must reflect your own work. Failure to do so will result in a grade of 0 in the course.
The purpose of the project is to enable the students to get some hands-on experience in the design, implementation and evaluation of pattern recognition algorithms. To facilitate the completion of the project in a semester, it is advised that students work in teams of two. You are expected to evaluate different preprocessing, feature extraction, and classification approaches to achieve as high accuracy as possible on the selected classification task.
The project report should clearly explain the objective of the study, some background work on this problem, difficulty of the classification task, choice of representation, choice of classifiers, classifier combination strategies, error rate estimation, etc. For most of the classifiers, e.g., support vector machines and neural networks, software packages are available in the public domain. Feel free to use them. Emphasis of the project is to solve a practical and interesting pattern recognition problem using the tools that you have learnt in this course. It would be instructive to see how close you can come to the state-of-the-art accuracy on this database. Use the projection algorithms to display 2- and 3-dimensional representations of the multidimensional patterns.
Course objectives: (1)Evaluating software system; (2)Hands-on projects with open source;(3)Creating SNS, LMS and Intranet like Applications;(4)Enable the intelligent processing of information and add-value that can’t be delivered by other means;
You'll Learn: (1) how computing thinking take effect in developing useful software system and the ability to distinguish between good and bad Internet service ideas; (2)ability to deal with the complexity in designing and implementing your applications; (3)how to create a good software models for a specific application systems requirement; (4) how to make a assessment for a software system; (5) team working for conceiving and designing a useful application.
There two kind of audiences as following. The first category is the professional software developers building online large scale Web applications. The second category is the managers evaluating packaged software aimed at supporting online communities. We assume that students know how to write a computer program and debug it. We do not assume knowledge of any particular programming languages, standards, or protocols. The most concise statement of the course goal is to improve your way of thinking. Student would learn how to master the diversity and complexity in contemporary large scale Web applications. We promote the critical reading and thinking. Students are required to read and assimilate information from the readings beyond the material covered in class. Throughout the semester, papers and chapters of the texts will be read and discussed. Analytical writing and presentation are required. Students are asked to think critically and reason about information presented in the textbooks or papers. This critical evaluation requires that students offer their own understanding of the significance of what students have learned. Students should be able to present their knowledge to the public. The grade rules include two components: group project and individual work. The group project component has two parts: project prototype counts 25%, presentation counts 15%. The individual work component has three parts: final examination counts 30%, each homework counts 5%, final paper counts 15%.
We are going to discuss the following 6 topic or themes during the lecture time.
Chapter 1 Computing Thinking
What are the domain problems?
Problem solving process and paradigm
Value-Driven and Model Driven approach
Mapping from Requirement to Software Solutions
Computing Thinking and Basic Concepts
Data and its presentation
Algorithm and Abstraction
Chapter 2 Mastering Software Complexity
Dimension of Complexity: Requirement Change, Technology Change, Human Cognitive Level.
Divide and Conquer approach
Chapter 3 Software Models
Domain knowledge: What are the major concepts in this domain under discuss?
Induction and classification: Actors, Actions, Entities, Process or Code, Information Architecture, Web usability.
Business models and domain models: Values of the enterprise / the related system / software system, who will get what benefits from the software?
Chapter 4 System Structure and Behavior
Chapter 5 Evaluating Model
Open source model