Identifying Data 2022/23
Subject (*) Advanced Calculus  Code 610G04009
Study programme
Grao en Nanociencia e Nanotecnoloxía
Descriptors Cycle Period Year Type Credits
Graduate 2nd four-month period
First Basic training 6
Language
Spanish
Galician
Teaching method Face-to-face
Prerequisites
Department Matemáticas
Coordinador
Suarez Taboada, Maria
E-mail
maria.suarez3@udc.es
Lecturers
García Rodríguez, José Antonio
López Salas, José Germán
Suarez Taboada, Maria
E-mail
jose.garcia.rodriguez@udc.es
jose.lsalas@udc.es
maria.suarez3@udc.es
Web http://https://campusvirtual.udc.gal/course/view.php?id=15383
General description Nesta asignatura preténdese o desenvolvemento de competencias que permitan ao alumnado desenvolver un coñecemento critico do calculo diferencial e integral de varias variables.

Study programme competencies
Code Study programme competences
A3 CE3 - Reconocer y analizar problemas físicos, químicos, matemáticos, biológicos en el ámbito de la Nanociencia y Nanotecnología, así como plantear respuestas o trabajos adecuados para su resolución, incluyendo el uso de fuentes bibliográficas.
A7 CE7 - Interpretar los datos obtenidos mediante medidas experimentales y simulaciones, incluyendo el uso de herramientas informáticas, identificar su significado y relacionarlos con las teorías químicas, físicas o biológicas apropiadas.
B2 CB2 - Que los estudiantes sepan aplicar sus conocimientos a su trabajo o vocación de una forma profesional y posean las competencias que suelen demostrarse por medio de la elaboración y defensa de argumentos y la resolución de problemas dentro de su área de estudio
B4 CB4 - Que los estudiantes puedan transmitir información, ideas, problemas y soluciones a un público tanto especializado como no especializado
B5 CB5 - Que los estudiantes hayan desarrollado aquellas habilidades de aprendizaje necesarias para emprender estudios posteriores con un alto grado de autonomía
B6 CG1 - Aprender a aprender
B7 CG2 - Resolver problemas de forma efectiva.
B8 CG3 - Aplicar un pensamiento crítico, lógico y creativo.
B9 CG4 - Trabajar de forma autónoma con iniciativa.
B10 CG5 - Trabajar de forma colaborativa.
B11 CG6 - Comportarse con ética y responsabilidad social como ciudadano/a y como profesional.
B12 CG7 - Comunicarse de manera efectiva en un entorno de trabajo.
C3 CT3 - Utilizar las herramientas básicas de las tecnologías de la información y las comunicaciones (TIC) necesarias para el ejercicio de su profesión y para el aprendizaje a lo largo de su vida
C7 CT7 - Desarrollar la capacidad de trabajar en equipos interdisciplinares o transdisciplinares, para ofrecer propuestas que contribuyan a un desarrollo sostenible ambiental, económico, político y social.
C8 CT8 - Valorar la importancia que tiene la investigación, la innovación y el desarrollo tecnológico en el avance socioeconómico y cultural de la sociedad
C9 CT9 - Tener la capacidad de gestionar tiempos y recursos: desarrollar planes, priorizar actividades, identificar las críticas, establecer plazos y cumplirlos

Learning aims
Learning outcomes Study programme competences
Conocer y manejar con soltura las funciones en varias variables escalares y vectoriales: su representación espacial, su necesidad en el modelado de problemas reales, el cálculo de límites y la continuidad A3
A7
B2
B4
B5
B6
B7
B8
B9
B10
B11
B12
C3
C7
C8
C9
Conocer y manejar con soltura el cálculo diferencial en varias variables: derivadas parciales y direccionales, operadores diferenciales, desarrollo de Taylor y cálculo de extremos y extremos condicionados. Saber aplicar los conocimientos a problemas reales, especialmente relacionados con la titulación. A3
A7
B2
B4
B5
B6
B7
B8
B9
B10
B11
B12
C3
C7
C8
C9
Conocer y adquirir soltura en las técnicas de integración en varias variables, aplicándolo a problemas reales. A3
A7
B2
B4
B5
B6
B7
B8
B9
B10
B11
B12
C3
C7
C8
C9
Conocer y adquirir soltura en la integración sobre curvas y superficies. Saber aplicar las fórmulas de Green y Stokes, aplicándolo a problemas relacionados con la titulación A3
A7
B2
B4
B5
B6
B7
B8
B9
B10
B11
B12
C3
C7
C8
C9
Manejar herramientas de software que implementen las metodologías estudiadas y saber analizar los resultados. A3
A7
B2
B4
B5
B6
B7
B8
B9
B10
B11
B12
C3
C7
C8
C9

Contents
Topic Sub-topic
Unit 1: Topology in R^n Scalar product, norm and distance.
Classification of points and sets.
Topology in R: bounded sets, supreme, infimo, maximum and minimum.
Polar, cylindrical and spherical oordinates.
Applications.
Unit 2: Functions of more than one variable Scalar and vector functions.
Level sets.
Continuity.
Applications.
Unit 3: Differentiation of functions of more than one variables and applications Directional derivative.
Partial derivatives: properties and practical computations.
Differerential of a function.
Relationship between the differential and the partial derivatives.
Gradient vector, relationship with the directional derivatives.
Jacobian matrix.
Higher order partial derivatives.
Introduction to vector calculus.
Taylor's theorem for scalar functions.
Critical points, classification.
Hessian matrix.
Extremos condicionados: reducción de la dimensión, método de los multiplicadores de Lagrange.
Aplicaciones.
Unit 4: Integration of functions of one and more variables Double integrals.
Triples integrals.
Change of variables in double and triple integrals.
Applications of integrals.
Unit 5: Integration in curves and surfaces Parameterized curves.
Integral line.
Gradient function and conservative field.
Green's theorem.
Parameterized surfaces.
Integral of surface. Sotkes theorem. Divergence's theorem.
Applications.

Planning
Methodologies / tests Competencies Ordinary class hours Student’s personal work hours Total hours
Guest lecture / keynote speech A3 A7 B6 B11 C8 28 56 84
ICT practicals B2 B4 B5 B7 B12 C3 C7 C8 12 25 37
Mixed objective/subjective test A3 B2 B6 B7 B9 3 0 3
Problem solving B2 B4 B5 B7 B8 B9 B10 B12 C3 C7 C9 8 16 24
 
Personalized attention 2 0 2
 
(*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students.

Methodologies
Methodologies Description
Guest lecture / keynote speech Exhibition of the contents specified in the program of the subject, for this, audiovisual media or blackboard will be used.
ICT practicals Interactive practices in which relevant problems in the field of Science and Engineering will be solved, for this the Python programming language will be used
Mixed objective/subjective test Development of issues and problems of the subject.
Problem solving Sessions where relevant problems in the field of Sciences and Engineering will be presented, which will be solved both analytically and numerically. The student must be able to reach the solution of any problem by hand or alternatively using computer tools, and compare the results.

Personalized attention
Methodologies
Problem solving
ICT practicals
Description
a) During practical and solving problems lessons, professors will help students to develop purposed problems as well as applications to problems outside the scope of Science and Engineering.
b) As specific personalized attention measures for "Students with partial time dedication recognition and academic exemption from attendance exemption" for the study of the subject, the continuous assessment of practical lessons through ICT and problem solving will be carried out through online tests.


b)As medidas de atención personalizada específicas para o “Alumnado con recoñecemento de dedicación a tempo parcial e dispensa académica de exención de asistencia” para o estudo da materia, a avaliación continua das prácticas a través de TIC e da resolución de problemas realizarase mediante probas parciais online.


Assessment
Methodologies Competencies Description Qualification
Problem solving B2 B4 B5 B7 B8 B9 B10 B12 C3 C7 C9 Resolución de problemas de carácter práctico. 20
ICT practicals B2 B4 B5 B7 B12 C3 C7 C8 Resolución de problemas de carácter práctico empregando o linguaxe de programación Python 20
Mixed objective/subjective test A3 B2 B6 B7 B9 Proba que inclúe a resolución de cuestións e problemas da materia
60
 
Assessment comments

The final qualification of the subject consists of three parts:

  • Practical qualifications by ITC (CP): between 0 and 2 points
  • Solving problems qualifications (CR): between 0 and 2 points

  • Objective test qualification (CE): between 0 and 6 points.

The
final qualification will be the sum of the three parts CP + CR + CE, if
the qualification of the objective test is greater than 2 (over 10
points). In other situation, the final qualification will be the
qualification of the objective test, CE.

The qualifications of the
practical lessons by ITC (CR) and solving problems (CP) will be kept
for the second opportunity of the assessment.

In the proceedings, the students who do not attend the final test will be considered as "Not presented".


Sources of information
Basic

Bibliography:

  • Jerrold Marsden. " Cálculo Vectorial". Pearson. Edición 6ª. 2018.

  • Ron Larson, Bruce Edwards. "Cálculo. Tomo II". Cengage Learning, Edición 10ª.2018.

  • Claudia Neuhauser, "Calculus for Biology and Medicine", Prentice Hall.Edición 2ª. 2004.
  • Robert G. Mortimer. "Mathematics for Physical Chemistry". Pearson. Edición 4ª. 2013.

  • Saturnino L. Salas, Finar Hille, Garret J. Etgen. "Calculus II. Una y varias varialbles" (Vol. nº 2). Reverté. Edición 4ª. 2018.

  • Edward Jen Herman, Gilbert Strang. "Calculus. Volumen 3". OpenStax. Rice University. Disponible gratuitamente en :https://openstax.org/details/books/calculus-volume-3

Bibliography for practical lessons by ITC:

  • Jeffrey J. Heys. "Chemical and Biomedical Engineering Calculations using Python". Wiley. 2017.

  • Svein Linge, Hans P. Langtangen. "Programming for Computations - Python. A Gentle Introduction to Numerical Simulations with Python". Springer. Texts in Computational Science and Engineering. Edición 1ª. 2017.

  • Anders Mathe-Sorenssen."Elementary Mechanics Using Python: A Modern Course Combining Analytical and Numerical Techniques (Undergraduate Lecture Notes in Physics)". Springer. 2015.

  • Robert Johansson. "Numerical Python: Scientific Computing and Data Science Applications with Numpy, Scipy and Matplotlib". Apress. . Edición: 2ª. 2018.Rubin H. Landau, Manuel J. Paez, Christian C. Bordeiany. "Computational Physics: Problem Solving with Computers". Wiley VCH Verlag GmbH. Edición 2ª. 2007.

Complementary


Recommendations
Subjects that it is recommended to have taken before
Fundamentals of Mathematics/610G04001
Physics: Mechanics and Waves/610G04002

Subjects that are recommended to be taken simultaneously
Fundamentals of Computing Science/610G04010

Subjects that continue the syllabus
Numerical and Statistical Methods/610G04013
Differential Equations/610G04016

Other comments
  • It is recommended to have knowledge of the second year of high school

  • Daily study of the contents treated in the classroom, complementing them with the recommended bibliography.

  • Gender perspective: as stated in the transversal competences of the title (C4), the development of a critical, open and respectful citizenship with diversity in our society will me promoted, highlighting the equal rights of students without discrimination based on gender or sexual condition. An inclusive language will be used in the material and during the development of the lessons.
  • Green Campus Program of the Faculty of Science

    In order to achieve an inmediate and sustainablem and to fullfill the point 6 of the "Declaración Ambiental da Facultade de Ciencias (2020)", the work carried out in this subject will be requested in virtual format or computer support.



(*)The teaching guide is the document in which the URV publishes the information about all its courses. It is a public document and cannot be modified. Only in exceptional cases can it be revised by the competent agent or duly revised so that it is in line with current legislation.