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Prof. S. Swaminathan

 

 

This course helps the learners to understand thoroughly the key concepts of tissue organization, remodeling and strategies for restoration of tissue function. This will enable them to design tissue regeneration and tissue injury repair strategies.

 

Sl. No

Course content

Duration (in hours)

Module

1.

Introduction to tissue engineering, Cells as therapeutic Agents with examples, Cell numbers and growth rates.

2

Module 1

2.

Tissue organization, Tissue Components, Tissue types, Functional subunits. Tissue Dynamics, Dynamic states of tissues, Homeostasis in highly prolific tissues and Tissue repair. Angiogenesis.

3

 Module 2

3.

Cellular fate processes, Cell differentiation, Cell migration - underlying biochemical process.

3

 Module 3

4.

Cell division - mitotic cell cycle, Cell death - biological description of apoptosis.

3

 Module 4

5.

Coordination of cellular fate processes - soluble signals, types of growth factors and chemokines, sending and receiving a signal, processing a signal, integrated responses, soluble growth factor receptors, Malfunctions in soluble signaling.

3

 Module 5

6.

Cell-extracellular matrix interactions - Binding to the ECM, Modifying the ECM, Malfunctions in ECM signaling.

Direct Cell-Cell contact - Cell junctions in tissues, malfunctions in direct cell-cell contact signaling. Response to mechanical stimuli.

3

 Module 6

7.

Measurement of cell characteristics - cell morphology, cell number and viability, cell-fate processes, cell motility, cell function.

2

 Module 7

8.

Cell and tissue culture - types of tissue culture, media, culture environment and maintenance of cells in vitro, cryopreservation.

3

 Module 8

9.

Basis for Cell Separation, characterization of cell separation, methods of cell separation.

3

 Module 9

10.

Biomaterials in tissue engineering - biodegradable polymers and polymer scaffold processing.

3

 Module 10

11.

Growth factor delivery, Stem cells.

3

Module 11

12.

Gene therapy.

1

Module 12

13.

Bioreactors for Tissue Engineering.

1

Module 13

14.

In vivo cell & tissue engineering case studies: Artificial skin, Artificial blood vessels.

3

Module 14

15.

In vivo cell & tissue engineering case studies: Artificial pancreas, Artificial liver.

3

Module 15

16.

In vivo cell & tissue engineering case studies: Regeneration of bone, muscle.

3

Module 16

17.

In vivo cell & tissue engineering case studies: Nerve regeneration.

3

Module 17
 

Total

45

 

 

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Syllabus

 

This course aims to train the first year BE/B tech students in basic principles of English language, enabling them to use active and passive vocabulary in different academic and professional contexts, developing their LSRW skills, namely listening, speaking, reading and writing skills thereby improving their proficiency in oral and written communication in technical English.

 

 

S.No.

Topics and Contents

Duration in hours

Module

1.

Technical vocabulary, Using words in contexts-Use of suffixes to form nouns from verbs and adjectives-Articles-Conjunctions and prepositions.

3

PDF

2.

Tenses-Active and Passive voices, Degrees of comparison.

1

PDF

3.

Reading text: Skimming for general information- Notemaking, Listening and transferring of information from text to graphic forms-bar charts,flow charts-Paragraph writing.

3

PDF

4.

Role play - Conversational Techniques, discussions-Oral reporting.

2

PDF

5.

Vocabulary items: Words with prefixes("Multi" - "Under" -)Asking and answering questions,spelling ad punctuation.

2

PDF

6.

Reading comprehension- Scanning for information.

1

PDF

7.

Listening and guided note taking-Paragraph writing-Using notes-Giving suitable headings,sub-headings for paragraphs.

4

PDF

8.

Comparing and contrasting using expressions of comparisons- Discussing creative ideas.

2

PDF

9.

Compound nouns - negative prefixes - Antonyms - Use of modal verbs.

1

PDF

10.

Making sentences using phrases.

1

PDF

11.

Tenses: Simple past and present perfect, Reported Speech.

2

PDF

12.

Reading and guessing meanings in context, Listening and Note-taking.

2

PDF

13.

Channel conversation from text to chart, Making recommendations.

2

PDF

14.

Discussion- Role play explaining and convincing.

1

PDF

15.

Expanding nominal compounds-words with multiple meanings –moderate verbs-error correction-compound adjectives.

2

PDF

16.

Simple past and present perfect tense.

1

PDF

17.

Reading – Prediction of content-Understanding advertisements.

2

PDF

18.

Scanning the text and comprehension check.

1

PDF

19.

Listening for details-Listening comprehension.

1

PDF

20.

Writing Definitions - Expression of views and purpose-Role play-Discussion-Speculating about future.

2

PDF

21.

Formation of nouns, verbs and adjectives from root words.

1

PDF

22.

Useful phrases and expressions.

1

PDF

23.

‘If’ conditional clauses-gerunds.

1

PDF

24.

Reading for comprehension- Intensive reading.

1

PDF

25.

Accuracy in listening- listening to discussion on specific issues.

1

PDF

26.

Group Discussion.

2

PDF

27.

Role play - (Stating, discussing problems and proposing solutions).

1

PDF

28.

Planning  a tour- writing an itenary , writing formal letters- letter to editor.

1

PDF

 

Total

45

 

 

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Prof. R. John Bosco Balaguru                                           Dr. B.G. Jeyaprakash

 

 

 
The course will focus on Physics of low dimensional semiconducting materials and their electrical, optical, thermal and mechanical properties, Engineering the semiconducting nanomaterials for nanodevice development and their applications to the budding Science & Engineering students.
 

 

Sl. No

Course contents

Duration (in hours)

Module

1.

Wave Partical Duality and Heisenberg Principle, Schrodinger Wave Equation, Ferimi-Dirac and Bose-Einstein Distributions.

3

Module 1

2.

Electrons in Mesoscopic Structure – Characteristic Length in Mesoscopic Systems.

2

Module 2

3.

Kronig–Penney Model- Free-Electron / Quasifree-Electron Approximation: Density of States Function.

3

Module 3

4.

Energy Bands in Typical Semicondutor – Elementary Transport in Semiconductors, Degenerate Semiconductors – Optical Processes in Semiconductors – Interband Absorption – Exitonic Effects.

3

Module 4

5.

Classification of Low Dimensional Materials - Basic Properties of Low Dimensional Semiconductor Nanostructures, Comparison of Bulk and Nanostructured Semicoducting Materials.

2

Module 5

6.

Quantum Size Effect – Electrical Conductivity: Surface Scattering – Change of Electronic Structure – Quantum Transport – Conductance Quantization.

3

Module 6

7.

Quantum Wells - Quantum Wires - Quantum Dots – Quantum Limit of Conductance & Quantum Capacitance - Quantum HALL Effect.

4

Module 7

8.

Strained Layers - Effect of Strain on Valence Bands - Band Structure in Quantum Wells - Excitonic Effects in Quantum Wells.

2

Module 8

9.

Optical Properties of Quantum Well, Quantum Dot, Surface Plasmon Resonance.

3

Module 9

10.

Lattice Vibrations, Phonons, Specific Heat Capacity, Thermal Conductivity.

2

Module 10

11.

Melting Point and Lattice Constant – Mechanical Properties, Diffusion – Elasticity – Hall-Petch Relationship for Nanostructured Materials – Creep – Super Plasticity.

3

Module 11

12.

Short Channel MOS Transistor – Split Gate Transfer – Electron Wave Transistor – Electron Spin Transistor – Quantum Cellular Automata – Quantum Dot Array.

3

Module 12

13.

Tunnel Effect and Tunneling Elements, Tunnel Diode, Resonant Tunneling Diode, Three Terminal Resonant Tunneling Devices – Technology of RTD – Digital Circuit Design based on RTDs.

3

Module 13

14.

Principle of SET – SET Circuit Design – Comparison between FET and SET - SET Circuit Designs.

3

Module 14

15.

Nanostructured MOS Gas Sensors - Gas Sensing Mechanism, Gas Sensing Characteristics of Nanomaterials Synthesized by Physical /Chemical Methods.

4

Module 15

16.

Quantum Well & Quantum Dot Lasers – Quantum Well and Super Lattice Photo Detectors – Quantum Well Modulators.

2

Module 16

 

Total

45

 

 

 

 

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Prof. M. Vijayalakshmi

 

 

Systems Biology- Fundamentals- gene expression paradigms - genetic switch in Lambda Phage -Noise-based Switches and Amplifiers for Gene Expression -Ecoli chemotaxis - genetic oscillators - Noise in Biochemical Systems-Quorum Sensing - Programmed Population Control by Cell-Cell Communication and Regulated Killing- Drosophila Development - Establishment of Developmental Precision and Proportions in the Early Drosophila embryo -Gene expression networks -Gene regulation at a single cell level-Transcription Networks basic concepts

 

Sl. No

Topics

Hours

Module

1.

Systems Biology – Fundamentals

  • Overview of Gene Control –Working of Genetic Switches – Introductory Systems Biology The biochemical paradigm, genetic paradigm and the systems paradigm.

5

Module 1

2.

Kinetics

  • Equilibrium Binding and Co-operativity -Michaelis-Menten Kinetics –identical and independent binding sites – Identical and interacting binding sites, non-interacting binding sites.

  • Genetic switch in Lambda Phage -Noise-based Switches and Amplifiers for Gene Expression.

  • Synthetic genetic switches –Ecoli chemotaxis –biological oscillators- genetic oscillators -The Origin and Consequences of Noise in Biochemical Systems.

15

6

 

4

 

5

Module 2

3.

Developmental Systems Biology

  • Building an Organism Starting From a Single Cell -Quorum Sensing – Programmed Population Control by Cell-Cell Communication and Regulated Killing- Drosophila Development.

  • Establishment of Developmental Precision and Proportions in the Early Drosophila embryo.

8

5

 

3

Module 3

4.

Gene expression networks

  • Gene regulation at a single cell level- Transcription Networks  -basic concepts -coherent Feed Forward Loop (FFL) and delay gate -The incoherent FFL -Temporal order, Signaling networks and neuron circuits -Aspects of multi-stability in gene networks.

14

 

Module 4

 

Total

42

 

 

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Prof. K. Vijayarekha

 

 

This course gives the importance and usefulness of pattern recognition in modern world. Images can be classified based on their patterns. Clustering which helps in differentiating groups of data is included in this course. Decision functions will be dealt in with. Pattern recognition with the help of the membership of incoming functions will be taught.

The extractable measure of an image called features which help us distinguish one image from the other will be studied. Feature extraction and feature selection will also form a part of this course. As application of pattern recognition, Pattern recognition using Fuzzy logic and neural network will be used.

 

Module

Course content

Hours

Module

I

INTRODUCTION TO PATTERN RECOGNITION

Basic concepts- Structure of a typical pattern recognition system.

4

Module 1

II

DECISION FUNCTIONS

Role of decision functions in pattern recognition- Linear and generalized decision functions - Concept of pattern space and weight space - Geometric properties - Implementation of decision functions.

5

Module 2

III

FEATURES

Feature vectors - Feature spaces - Problem of feature identification Feature selection and feature extraction.

4

Module 3

IV

CLUSTERING

Distance measures - Clustering transformation and feature ordering - Clustering in feature selection - Feature selection through entropy minimization.

5

Module 4

V

PATTERN CLASSIFICATION BY DISTANCE FUNCTIONS

Pattern classification by distance functions - Minimum distance classification - Cluster and cluster seeking algorithms - Pattern classification by likelihood functions.

4

Module 5

VI

PATTERN CLASSIFICATION BY STATISTICAL FUNCTIONS

Pattern classification using Statistical classifiers - Bayes’ classifier - Classification performance measures - Risk and error probabilities.

5

Module 6

VII

PATTERN RECOGNITION USING FUZZY CLASSIFIERS

Fuzzy and crisp classification - Fuzzy clustering - Fuzzy pattern recognition - Syntactic pattern recognition- Selection of primitives - Syntax analysis for pattern recognition.

5

Module 7

VIII

PATTERN RECOGNITION USING NEURAL CLASSIFIERS

Introduction - Neural network structures for PR, Neural network based pattern associators - Feed forward networks trained by back propagation - ART networks.

5

Module 8

IX

APPLICATION OF PATTERN RECOGNITION

Application of pattern recognition problem applied forclassification of leather images - Application of pattern recognition problem for classification of citrus fruit images.

3

Module 9

 

Total

40