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Physics, Chemistry, Informatics Biostatistics and English

A.Y. 2018/2019

Learning objectives

1) Conoscenze e capacità di comprensione: lo studente dovrà dimostrare di possedere le conoscenze dei principi di base delle discipline affrontate nei diversi moduli e di aver compreso le tematiche trattate: dai principi di base della Fisica, della Chimica,e del ragionamento statistico applicati ai dati biologici di interesse veterinario, alla organizzazione, consultazione e analisi dei dati con strumenti informatici e linguistici appropriati.

2) Capacità di applicare conoscenze e comprensione:l o studente dovrà dimostrare di saper applicare le conoscenze acquisite i)alla risoluzione di semplici problemi analitici propri delle diverse discipline, ii) alla consultazione di fonti e banche dati scientifiche,iii) alla comprensione dei risultati ottenuti. Dovrà dimostrare di comprendere la terminologia scientifica in italiano ed inglese delle diverse discipline e di aver sviluppato una capacità di utilizzo di software di base per la gestione di dati, riferimenti bibliografici e presentazione dei risultati analitici.

3) Autonomia di giudizio: lo studente dovrà dimostrate di aver raggiunto autonomia di giudizio nella utilizzazione del materiale didattico messo a disposizione e nella scelta di fonti scientifiche autorevoli per la comprensione e risoluzione di quesiti analitici di base delle diverse materie e nell'utilizzo dei principali software.

4) Abilità comunicative: lo studente dovrà dimostrare di essere in grado di esporre e organizzare le nozioni acquisite con la terminologia scientifica più adeguata durante le attività frontali ed esercitative previste nel corso e alla prova d'esame.

2) Capacità di applicare conoscenze e comprensione:l o studente dovrà dimostrare di saper applicare le conoscenze acquisite i)alla risoluzione di semplici problemi analitici propri delle diverse discipline, ii) alla consultazione di fonti e banche dati scientifiche,iii) alla comprensione dei risultati ottenuti. Dovrà dimostrare di comprendere la terminologia scientifica in italiano ed inglese delle diverse discipline e di aver sviluppato una capacità di utilizzo di software di base per la gestione di dati, riferimenti bibliografici e presentazione dei risultati analitici.

3) Autonomia di giudizio: lo studente dovrà dimostrate di aver raggiunto autonomia di giudizio nella utilizzazione del materiale didattico messo a disposizione e nella scelta di fonti scientifiche autorevoli per la comprensione e risoluzione di quesiti analitici di base delle diverse materie e nell'utilizzo dei principali software.

4) Abilità comunicative: lo studente dovrà dimostrare di essere in grado di esporre e organizzare le nozioni acquisite con la terminologia scientifica più adeguata durante le attività frontali ed esercitative previste nel corso e alla prova d'esame.

Expected learning outcomes

Undefined

**Lesson period:**
First semester

**Assessment methods:** Esame

**Assessment result:** voto verbalizzato in trentesimi

Course syllabus and organization

### Single session

Responsible

Lesson period

First semester

**ATTENDING STUDENTS**

**Modulo: Fisica**

**Course syllabus**

OBJECTIVES:

Presentation of the basic principles of physics, with references and applications to some topics in Medicine and Biology in order to highlight the importance of the subject for the analysis and understanding of natural phenomena.

MODULE PROGRAM: (the program might be changed according to the teacher of a. y. 2018/19)

- INTRODUCTION: · Introduction to Science and Physics · Scientific Method · Measurement of physical quantities, Units · International System, fundamental and derived quantities · Value and uncertainty in a series of measurements · Significant digits and rounding · Scientific notation, orders of magnitude. (1h)

- CINEMATICS: · Time · Space · Speed · Periodic and wave phenomena · Duration of a phenomenon · Frequency · Inertial mass · Length, area, volume measurements · Density · Average and instantaneous speeds · Acceleration. (1h)

- FORCES: · Forces · The Three Principles of Dynamics · Straight Motions · The Law of Universal Gravitation and Gravity Acceleration · Weight · Falling Free. (2h)

- DYNAMICS I: · Principle of energy conservation · Energy forms · Work and energy · Power · Conservative and dissipative forces · Potential energy · Kinetic energy. (2h)

- DYNAMICS II: · Kinetic energy theorem · Mechanical energy conservation · Linear momentum and conservation law · Mass center · Rotational motions: angular velocity and angular acceleration · Moment of inertia. (2h)

- STATICA: · Simple machines · Angular momentum and conservation law · Torque · Statics and its cardinal equations: equilibrium · Simple machines and mechanical gain. (2h)

- THERMAL PHENOMENA I: · Dissipative forces: friction, machine performance · Extensive and intensive properties/quantities · Specific weight · Pressure · Phases of Matter · Molecular interactions and internal energy · Temperature and Heat · Heat transport. (2h)

- THERMAL PHENOMENA II: · Thermal expansion/contraction · Thermal capacity and specific heat · Thermal conductivity · Thermodynamics, state variables, thermodynamic systems · Ideal gases, equation of state. (2h)

- THERMODYNAMICS: · Zero principle · First principle · Second principle · Entropy · Third principle · Thermodynamic Potentials, Equilibirum States and Free Energies. (2h)

- STATICS OF FLUIDS: · Fluids · Pressure Isotropy · Stevin's Law: Hydrostatic Pressure · Pascal's Principle · Archimede's Principle · Surface tension, capillarity · Flow rate. (2h)

- DYNAMICS OF FLUIDS, ELECTROMAGNETIC PHENOMENA: · Bernulli's Theorem · Viscosity · Laminar motion, turbolent motion · The atom: microscopic structure · Electric charge · Coulomb force · Field and electrical potential · Electric current · Ohm laws, resistance and resistivity · Electrical power and Joule effect · Magnetic fields · The laser. (3h)

- OPTICS, ACOUSTICS, NUCLEAR PHYSICS, MEDICAL PHYSICS: · Waves · Optics · Acoustics · Nuclear Physics · Physics in Medicine · Diagnostic Techniques: Physical Applications. (3h)

Starting from the fourth lesson, in the first 30 minutes of the class exercises, related to the topics already covered in previous lessons, are proposed and solved.

Presentation of the basic principles of physics, with references and applications to some topics in Medicine and Biology in order to highlight the importance of the subject for the analysis and understanding of natural phenomena.

MODULE PROGRAM: (the program might be changed according to the teacher of a. y. 2018/19)

- INTRODUCTION: · Introduction to Science and Physics · Scientific Method · Measurement of physical quantities, Units · International System, fundamental and derived quantities · Value and uncertainty in a series of measurements · Significant digits and rounding · Scientific notation, orders of magnitude. (1h)

- CINEMATICS: · Time · Space · Speed · Periodic and wave phenomena · Duration of a phenomenon · Frequency · Inertial mass · Length, area, volume measurements · Density · Average and instantaneous speeds · Acceleration. (1h)

- FORCES: · Forces · The Three Principles of Dynamics · Straight Motions · The Law of Universal Gravitation and Gravity Acceleration · Weight · Falling Free. (2h)

- DYNAMICS I: · Principle of energy conservation · Energy forms · Work and energy · Power · Conservative and dissipative forces · Potential energy · Kinetic energy. (2h)

- DYNAMICS II: · Kinetic energy theorem · Mechanical energy conservation · Linear momentum and conservation law · Mass center · Rotational motions: angular velocity and angular acceleration · Moment of inertia. (2h)

- STATICA: · Simple machines · Angular momentum and conservation law · Torque · Statics and its cardinal equations: equilibrium · Simple machines and mechanical gain. (2h)

- THERMAL PHENOMENA I: · Dissipative forces: friction, machine performance · Extensive and intensive properties/quantities · Specific weight · Pressure · Phases of Matter · Molecular interactions and internal energy · Temperature and Heat · Heat transport. (2h)

- THERMAL PHENOMENA II: · Thermal expansion/contraction · Thermal capacity and specific heat · Thermal conductivity · Thermodynamics, state variables, thermodynamic systems · Ideal gases, equation of state. (2h)

- THERMODYNAMICS: · Zero principle · First principle · Second principle · Entropy · Third principle · Thermodynamic Potentials, Equilibirum States and Free Energies. (2h)

- STATICS OF FLUIDS: · Fluids · Pressure Isotropy · Stevin's Law: Hydrostatic Pressure · Pascal's Principle · Archimede's Principle · Surface tension, capillarity · Flow rate. (2h)

- DYNAMICS OF FLUIDS, ELECTROMAGNETIC PHENOMENA: · Bernulli's Theorem · Viscosity · Laminar motion, turbolent motion · The atom: microscopic structure · Electric charge · Coulomb force · Field and electrical potential · Electric current · Ohm laws, resistance and resistivity · Electrical power and Joule effect · Magnetic fields · The laser. (3h)

- OPTICS, ACOUSTICS, NUCLEAR PHYSICS, MEDICAL PHYSICS: · Waves · Optics · Acoustics · Nuclear Physics · Physics in Medicine · Diagnostic Techniques: Physical Applications. (3h)

Starting from the fourth lesson, in the first 30 minutes of the class exercises, related to the topics already covered in previous lessons, are proposed and solved.

**Modulo: Chimica**

**Course syllabus**

The Chemistry module (3 CFU, 32 h) is aimed at providing information preparatory to later courses, mainly Biochemistry and Molecular Biology. Besides basic concepts of general, inorganic and organic chemistry suitable to describing the qualitative and quantitative composition and reactivity of matter, the course deals with basic aspects of chemical equilibrium, thermodynamics and kinetics, which are essential to understand any biological process. Each topic is presented in short theoretical lectures, followed by exercitative classes consisting in exercizes which emphasize the importance of a quantitative approach in science

Theoretical lectures (16 h)

Periodic table: elements, isotopes, atomic weight, oxidation number, periodic properties (1h)

Different types of chemical bonds, chemical reactions (1 h)

Basic of quantitative chemistry: concept of mole and molarity (1 h)

Aggregation state of matter (1 h)

Chemical equilibrium: reversible and irreversible reactions (1 h)

Water, solutions, electrolytic dissociation (1 h)

Acids, bases, pH (3 h)

Buffers (2 h)

Redox reactions, redox potential (1 h)

Thermodynamics and kinetics of chemical reactions (2 h)

Basic concepts of organic chemistry: functional groups of organic molecules (double bonds, alcoholic hydroxylic, carbonylic and carboxylic groups) (2 h)

Exercitative lectures

Stoichiometry: structural formula of inorganic molecules and ions of biological interest (2 h) (class)

Stoichiometry: exercises on mass and concentration of chemical compounds (3 h) (class)

Stoichiometry: exercises on electrolytic dissociation (1 h) (class)

Stoichiometry : calculation of pH in acqueous solutions (3 h) (class)

Practical laboratory: acid base titration in the presence of a pH indicator (3 h) (chemistry laboratory)

Stoichiometry: exercises on buffers (2 h) (class)

Exercises on structural formula of organic compounds (hydrocarbons, alcohols, aldehydes, ketones, carboxylic acids) (2 h) (class)

Theoretical lectures (16 h)

Periodic table: elements, isotopes, atomic weight, oxidation number, periodic properties (1h)

Different types of chemical bonds, chemical reactions (1 h)

Basic of quantitative chemistry: concept of mole and molarity (1 h)

Aggregation state of matter (1 h)

Chemical equilibrium: reversible and irreversible reactions (1 h)

Water, solutions, electrolytic dissociation (1 h)

Acids, bases, pH (3 h)

Buffers (2 h)

Redox reactions, redox potential (1 h)

Thermodynamics and kinetics of chemical reactions (2 h)

Basic concepts of organic chemistry: functional groups of organic molecules (double bonds, alcoholic hydroxylic, carbonylic and carboxylic groups) (2 h)

Exercitative lectures

Stoichiometry: structural formula of inorganic molecules and ions of biological interest (2 h) (class)

Stoichiometry: exercises on mass and concentration of chemical compounds (3 h) (class)

Stoichiometry: exercises on electrolytic dissociation (1 h) (class)

Stoichiometry : calculation of pH in acqueous solutions (3 h) (class)

Practical laboratory: acid base titration in the presence of a pH indicator (3 h) (chemistry laboratory)

Stoichiometry: exercises on buffers (2 h) (class)

Exercises on structural formula of organic compounds (hydrocarbons, alcohols, aldehydes, ketones, carboxylic acids) (2 h) (class)

**Modulo: Informatica e Biostatistica**

**Course syllabus**

Learning objectives: Acquisition of basic concepts of computer science and descriptive and inferential statistics applied to biological data. Acquisition of basic skills for the practical use of a spreadsheet for the analysis of biological data.

Syllabus

1. Theoretical Classes

· Introduction to the subject: the importance of biostatistics in Veterinary Medicine. Descriptive and inferential statistics. Samples and populations. Types of variables: qualitative, quantitative. Accuracy, accuracy and distortion (1 hrs)

· Descriptive statistics. Absolute, relative and cumulative frequency tables. Diagrams and histograms. Percentiles and Quantiles. Arithmetic and geometric mean, median, mode, interquartile difference. Range of variation, deviance, variance, standard deviation, coefficient of variation (2 hrs)

· Probability. Sample distributions. Statistical test. Basic rules of probability. Contingency tables. Bayes theorem in diagnostic applications: false positives.. The sampling distribution of an estimate: the standard error. The confidence interval. Verifying hypotheses. Null hypothesis and alternative statistical significance and P-value. Check hypothesis and confidence intervals. Error types I and II (2 hrs)

· Analysis of proportions: binomial distribution. Estimating proportions: confidence interval and standard error of a proportion. The chi squared test. The Poisson distribution. Normal distribution. Normalized standard distribution. The central limit theorem (2 hrs)

· Inference to a population with normal distribution: distribution, assumption, and properties. The t test for a sample. The t test for comparison between two averages. Paired and independent data. The comparison between the averages of several groups: analysis of variance (2 hrs)

· Relationship between variables: covariance. Correlation and linear regression (2 hrs)

· Introduction to information science: Information concept, algorithm, coding and language. The encoding of information, data, letters and images. Decimal, hexadecimal, binary numeration. Text encoding: ASCII and UNICODE format. Image formats: bitmap graphics and vector graphics (3 hrs)

· Use of spreadsheets: operators, absolute and relative references, biological data management, formulas and tools for statistical analysis of data (2 hrs)

2. Practical classes (Computer Classroom):

· Databases: CAB Abstract (3 hrs) PubMed (3 hrs) OPAC (3 hrs)

· Using Spreadsheets: Importing Data and Formats. Working with tables and charts Working with dates (2 hrs)

· Statistical variables and their representation: designing questionnaires for building datasets containing different types of variables. Randomization (3 hrs)

· Dataset analysis: data import and control, formatting, data quality control (2 hrs)

· Construction of tables and graphs appropriate for the analysis of different types of variables: paddle and overlapping bars diagrams, pie charts; maps; Dispersion diagrams, histograms, Sturges rule, percentiles and quantiles, cumulative frequency distributions, contingency tables (4 hrs)

· Descriptive statistics: Calculation of the principal position and dispersion measurements: arithmetic and geometric mean, mode, median, percentile and quantile (3 hrs)

· Variation range; Interquartile interval; Deviance standard deviation and variation coefficient (3hrs)

· Evaluation of the normality of a distribution. Outlier identification and evaluation (2 hrs)

· Standard error. Confidence interval of an average with known variance and not. Confidence interval and standard error of a ratio (4 hrs)

· Chi square test for the evaluation of the goodness of fit and for contingency table analysis (2 hrs)

· Use of statistical tables and excel functions for determining the critical values of the different distributions (2 hrs)

· T test for paired and independent data (3 hrs)

· Evaluation of the Null and alternative hypothesis (1 hrs)

· Analysis of variance with one and two factors. F Test (2 hrs)

· Post-hoc Test: Dunnet and Scheffé (2 hrs)

· Relationship Measures: Covariance, Correlation (2 hrs)

· Linear regression. Expected Values. Residues. Coefficient of determination(2hrs)

Syllabus

1. Theoretical Classes

· Introduction to the subject: the importance of biostatistics in Veterinary Medicine. Descriptive and inferential statistics. Samples and populations. Types of variables: qualitative, quantitative. Accuracy, accuracy and distortion (1 hrs)

· Descriptive statistics. Absolute, relative and cumulative frequency tables. Diagrams and histograms. Percentiles and Quantiles. Arithmetic and geometric mean, median, mode, interquartile difference. Range of variation, deviance, variance, standard deviation, coefficient of variation (2 hrs)

· Probability. Sample distributions. Statistical test. Basic rules of probability. Contingency tables. Bayes theorem in diagnostic applications: false positives.. The sampling distribution of an estimate: the standard error. The confidence interval. Verifying hypotheses. Null hypothesis and alternative statistical significance and P-value. Check hypothesis and confidence intervals. Error types I and II (2 hrs)

· Analysis of proportions: binomial distribution. Estimating proportions: confidence interval and standard error of a proportion. The chi squared test. The Poisson distribution. Normal distribution. Normalized standard distribution. The central limit theorem (2 hrs)

· Inference to a population with normal distribution: distribution, assumption, and properties. The t test for a sample. The t test for comparison between two averages. Paired and independent data. The comparison between the averages of several groups: analysis of variance (2 hrs)

· Relationship between variables: covariance. Correlation and linear regression (2 hrs)

· Introduction to information science: Information concept, algorithm, coding and language. The encoding of information, data, letters and images. Decimal, hexadecimal, binary numeration. Text encoding: ASCII and UNICODE format. Image formats: bitmap graphics and vector graphics (3 hrs)

· Use of spreadsheets: operators, absolute and relative references, biological data management, formulas and tools for statistical analysis of data (2 hrs)

2. Practical classes (Computer Classroom):

· Databases: CAB Abstract (3 hrs) PubMed (3 hrs) OPAC (3 hrs)

· Using Spreadsheets: Importing Data and Formats. Working with tables and charts Working with dates (2 hrs)

· Statistical variables and their representation: designing questionnaires for building datasets containing different types of variables. Randomization (3 hrs)

· Dataset analysis: data import and control, formatting, data quality control (2 hrs)

· Construction of tables and graphs appropriate for the analysis of different types of variables: paddle and overlapping bars diagrams, pie charts; maps; Dispersion diagrams, histograms, Sturges rule, percentiles and quantiles, cumulative frequency distributions, contingency tables (4 hrs)

· Descriptive statistics: Calculation of the principal position and dispersion measurements: arithmetic and geometric mean, mode, median, percentile and quantile (3 hrs)

· Variation range; Interquartile interval; Deviance standard deviation and variation coefficient (3hrs)

· Evaluation of the normality of a distribution. Outlier identification and evaluation (2 hrs)

· Standard error. Confidence interval of an average with known variance and not. Confidence interval and standard error of a ratio (4 hrs)

· Chi square test for the evaluation of the goodness of fit and for contingency table analysis (2 hrs)

· Use of statistical tables and excel functions for determining the critical values of the different distributions (2 hrs)

· T test for paired and independent data (3 hrs)

· Evaluation of the Null and alternative hypothesis (1 hrs)

· Analysis of variance with one and two factors. F Test (2 hrs)

· Post-hoc Test: Dunnet and Scheffé (2 hrs)

· Relationship Measures: Covariance, Correlation (2 hrs)

· Linear regression. Expected Values. Residues. Coefficient of determination(2hrs)

**Modulo: Inglese**

**Course syllabus**

HOW THE COURSE IS DIVIDED

The Course, 3 CFU, is divided into twelve 2-hour Lectures (3 CFU - 24 hours) dealing with English language structures of relevance to scientific English; Reading and Listening Comprehension of scientific production; Scientific Terminology; Output of scientific material.

COURSE DETAILS (the program might be changed according to the teacher of a. y. 2018/19)

1. Introduction to Scientific English (ESP) - Essentials of Scientific English 1 - Reading Comprehension;

2. Essentials of Scientific English 2 - Listening Comprehension;

3. Scientific Terminology - Reading Comprehension;

4. Tenses for Scientific English: present, past and future - Listening Comprehension;

5. Nouns and verb agreement - Reading and Speaking about Veterinary career;

6. Adjectives and quantifiers - Reading and Speaking about animals of veterinary interest;

7. Writing ESP (English for Specific Purpose):Basics 1 - Making hypotheses - IMRAD model;

8. Writing ESP: Basics 2 - Passive forms of verbs - An Abstract - example;

9. Power Point Presentations - examples;

10. Writing ESP - Scientific Papers - examples;

11. Writing ESP - Short Communications and Audioslides - examples;

12. Meet International Certification Testing: TOEFL and IELTS - English Language Mock Test.

The Course, 3 CFU, is divided into twelve 2-hour Lectures (3 CFU - 24 hours) dealing with English language structures of relevance to scientific English; Reading and Listening Comprehension of scientific production; Scientific Terminology; Output of scientific material.

COURSE DETAILS (the program might be changed according to the teacher of a. y. 2018/19)

1. Introduction to Scientific English (ESP) - Essentials of Scientific English 1 - Reading Comprehension;

2. Essentials of Scientific English 2 - Listening Comprehension;

3. Scientific Terminology - Reading Comprehension;

4. Tenses for Scientific English: present, past and future - Listening Comprehension;

5. Nouns and verb agreement - Reading and Speaking about Veterinary career;

6. Adjectives and quantifiers - Reading and Speaking about animals of veterinary interest;

7. Writing ESP (English for Specific Purpose):Basics 1 - Making hypotheses - IMRAD model;

8. Writing ESP: Basics 2 - Passive forms of verbs - An Abstract - example;

9. Power Point Presentations - examples;

10. Writing ESP - Scientific Papers - examples;

11. Writing ESP - Short Communications and Audioslides - examples;

12. Meet International Certification Testing: TOEFL and IELTS - English Language Mock Test.

**NON-ATTENDING STUDENTS**

**Modulo: Fisica**

**Course syllabus**

Not available: frequency to lectures is compulsory

**Modulo: Chimica**

**Course syllabus**

Not available: frequency to lectures is compulsory

**Modulo: Informatica e Biostatistica**

**Course syllabus**

Not available: frequency to lectures is compulsory

**Modulo: Inglese**

**Course syllabus**

Not available: frequency to lectures is compulsory

Modulo: Chimica

CHIM/03 - GENERAL AND INORGANIC CHEMISTRY - University credits: 0

CHIM/06 - ORGANIC CHEMISTRY - University credits: 0

CHIM/06 - ORGANIC CHEMISTRY - University credits: 0

Practicals: 16 hours

Lessons: 16 hours

Lessons: 16 hours

Professor:
Negri Armando

Modulo: Fisica

FIS/07 - APPLIED PHYSICS - University credits: 3

Lessons: 24 hours

Professor:
Pettinato Vincenzina

Modulo: Informatica e Biostatistica

SECS-S/02 - STATISTICS FOR EXPERIMENTAL AND TECHNOLOGICAL RESEARCH - University credits: 5

Practicals: 48 hours

Lessons: 16 hours

Lessons: 16 hours

Professor:
Crepaldi Paola

Modulo: Inglese

L-LIN/12 - LANGUAGE AND TRANSLATION - ENGLISH - University credits: 3

Lessons: 24 hours

Professor:
Mc Intire Amy Marie

Educational website(s)

Professor(s)

Reception:

keeping an appointment by e-mail

Sezione di Zootecnica Agraria, 1st floor, Via Celoria 2

Reception:

on appointment